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Reply to the reviewers

1. General Statements

We would like to thank the reviewers for their critical input on the manuscript and we are glad that, overall, they recognize that the extensive analysis of the endochondral perinatal bone we describe in this manuscript can constitute a useful resource both for the bone development and hematopoietic fields. Their input has allowed us to revise the manuscript such that it is much improved in our opinion. In this section, we wish to comment on the main common aspects raised by the reviewers, while specific point-by-point responses are provided below.

Fist, we are aware of the lack of functional assays mentioned by the reviewers, a limitation we explicitly mentioned in our original manuscript. While this is certainly a direction we will take in the future, we consider that such experiments are out of the scope and intentions of our study, given the magnitude of the resources and time they require (e.g. generation of new mouse alleles for cell fate tracking or selective ablation of specific populations, cell transplants into immunocompromised newborns, etc.). As stated in our original manuscript, this study is meant to be a resource that provides new findings and hypotheses that might be relevant for more specialized groups to functionally evaluate (e.g. teams working on thymus seeding progenitors, on adipogenesis or on immune tolerance in newborns, to name a few). As such, we believe our work has an intrinsic value. In fact, this is the first study with single cell resolution that not only compares bone populations before and after birth and with the adult tissue, but also one of the few in which all cell compartments (mesenchymal, endothelial and hematopoietic) are considered. Our manuscript hence brings a new layer of analysis not available in more directed studies, such as those based on flow cytometry (FC), in which not all populations are detected, either by lineage fraction discrimination or due to the lack of surface markers with validated antibodies for FC. This is relevant as our study identifies several new cluster-specific genetic markers and reveals their dynamic/changing expression (perinatal vs adult), or identifies that loci previously targeted for lineage tracing studies are not cluster-specific, which in our view will be useful for the interpretation of previous reports.

The other major point brought up in the reviewers’ reports is that our analysis would be nicely complemented by the spatial localization in the perinatal bone of the various populations we describe in our study. We also agree with the reviewers on this point, which we had considered, but for which we found severe technical limitations. Spatial transcriptomics with cellular resolution would be the ideal method to address this aspect, and we tested two different methods on our samples and under several fixation and permeabilization conditions. Unfortunately, and in contrast to brain tissue used as control, these attempts have been unsuccessful in consistently detecting even ubiquitous transcripts in perinatal bone samples. As spatial transcriptomics is a technology in constant development and several new platforms and approaches are becoming available, we expect that one or several of these various methods, at the moment mostly optimized for soft tissues, will be eventually set-up for mRNA detection with true cellular resolution in perinatal and adult bone samples.

Finally, immunofluorescence (IF) against specific markers is not a suitable approach in this case to unequivocally localize related cell populations such as the ones we describe (e.g. fibroblastic clusters). While flow cytometry has the unique advantage of performing lineage exclusion using cocktails of antibodies conjugated to the same fluorophore to label populations of cells which are not the aim of the study (e.g. hematopoietic and endothelial cells can be excluded by the use of TER119 plus CD45 and CD31, respectively), IF would require the availability of multiple specific antibodies, each conjugated to a different fluorophore, which are not available. In this regard, we would also like to point out that several studies that report the localization of specific cell populations in the bone have done so by taking advantage of genetic reporters (e.g. knock-in alleles encoding intracellular GFP or RFP). As previously mentioned, we consider that the generation of such new genetic tools is out of the scope of this manuscript.

1. Point-by-point description of the revisions

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

* In this new manuscript, Rueda and colleagues present an extensive bioinformatics analysis of single cell transcriptomic data obtained for mouse endochondral bone cell populations before and after birth. They describe gene markers of mesenchymal and hematopoietic cells pointing to differences with adult bone populations, and they use gene ontology and trajectory analyses to infer possible roles of these cells in the developing bone. The data could provide a valuable resource for further understanding endochondral bone development and the changes driving this process in peri-natal stages. However, they are also significant weaknesses. *

* A major weakness is that the scRNA-seq data lack validation through other techniques and functional assays. Namely, in situ data are missing to locate the various cell populations in the developing bones, especially the different types of fibroblastic cells identified by the authors. Such data would go a long way to understand the possible functions of the cell populations. Although the authors tried to complement their data with a review of the literature, most of the conclusions remain purely speculative and not sufficiently supported by scientific and statistic rigor. This makes the Results section more like a discussion than a description of the results. For instance, the authors proposed important regulatory functions for the fibroblastic clusters, but there is no data supporting this other than broad GO terms associated with genes expressed in these cells. Related to this point, the title of the manuscript does not accurately reflect the content of the study**. *

We thank the reviewer for the critical evaluation of our study and for considering it of potential interest for the field, and we have revised the manuscript to take into account his/her comments. We agree with the reviewer that including data to localize in situ the different cell populations would be highly informative. In fact, we had already attempted to perform these experiments using one of the most validated approaches, in situ sequencing (ISS). Despite assaying several fixation and permeabilization conditions, we could not reliably detect even ubiquitously expressed genes in all cells in PN1 bone sections. After discussing with a number of providers that have recently launched instruments capable of performing spatial transcriptomics technology, they all agreed that bone tissue is generally difficult to use for spatial transcriptomics technology. In summary, this data suggests that further optimization of ISS or of alternative spatial transcriptomics approaches will be needed in the future to robustly detect transcripts in bone sections with cellular resolution so as to localize in situ the various cell populations we describe in our study.

Finally, and given our attempt to interpret our analysis of the scRNAseq data in the context of the vast literature that considers both the mesenchymal and the hematopoietic compartments, we agree with the reviewer on the speculative nature of some our conclusions that he/she mentions at the end of the paragraph, an aspect also brought up by the other reviewers. Hence, starting with the title (being now “The cellular landscape of the endochondral bone during the transition to extrauterine life”), we have systematically modified such statements throughout the text to accurately make this distinction.

Other points: 1. The authors missed to report in the Results section which skeletal elements they used for their analyses and which skeletal elements were used for the adult dataset that they compared their data with. Differences in skeletal elements and in the ways whereby these samples were collected and processed could explain differences detected in the two types of datasets. Also, the sex and age of the samples for the adult dataset should be reported.

We now state also in the Results section that we collected forelimb long bones (excluding the handplate) for perinatal stages. In addition, we also indicate that the benchmark study by Baccin et al. used adult bone samples of mixed origin (femurs, tibiae, hips and spines) from 8-12 weeks old females. We agree with the reviewer that both this difference, as well as those related to the extraction protocols, might contribute to some of the variability we report. We now mention both these possibilities in the Discussion.

• It is unclear whether PN1 is the day that mice are born (classically referred to as P0) or the next day.*

As the reviewer indicates, P0 is the day of birth, and PN1 is the following day, which is the stage we chose for analysis. We have now indicated this clearly in the Materials and Methods section.

• It is unclear whether the cells obtained for each biological replicate were pooled for the scRNA-seq assays or were treated individually. It is thus unclear how reproducible the data are.*

In order to capture biological variability, each sample represented pooled littermates (5 fetuses for E18.5 and 4 pups at PN1), and processed as a single scRNA-seq library per stage to minimize technical variation. As our samples contained individuals from both sexes, already indicated in the original manuscript, we have now deconvoluted our datasets and computed male/female cell clustering so as to capture biological variability in duplicates (except for the sex, which is not considered as highly relevant at these stages). We assigned a “female” or “male” sex to a cell if it had at least one transcript read from a female or male specific transcript, respectively. If cells had at least one transcript read from both male and female specific genes, the cell was tagged as “undetermined”. Cells without any sex-specific transcript reads were tagged as “NA”. For the E18.5 sample we identified 21% female cells, 42% male cells, 3.7% undetermined and 33.3% NA cells. For the PN1 sample we identified 42.3% female cells, 28.1% male cells, 4.4% undetermined and 25.2% NA cells. This analysis, now shown in the new Fig. S2 and explained in Materials and Methods, reveals that all mesenchymal, hematopoietic and endothelial clusters are detected in both biological replicates. Finally, the changes we highlighted in the manuscript in the mesenchymal compartment between E18.5 and PN1 (TC, SPF and AFP) are maintained independently if the cells are processed as a single pool per stage or separated according to sex.

• It is not clear in the gating strategy chosen for the flow cytometry as shown in Fig. 1A why the green gate containing cells expressing high levels of CD9, CD140 and CD31 has been extended in between the purple and orange gates containing CD140 and CD31 negative cells.*

While the option mentioned by the reviewer is certainly plausible, this would have diluted the number of hematopoietic cells with intermediate CD9 levels present in our datasets. As our aim was to make sure even less abundant populations from all compartments would be captured in the scRNAseq libraries, we selected the sorting strategy depicted in Fig. 1A.

• Are cells from all the sequenced samples homogenously distributed in the scRNA-seq clusters? Authors should provide this information and add statistic when they describe changes in the amount of cells per cluster between E18.5 and PN1 stages.*

As mentioned in comment 3, we have now deconvoluted the datasets according to sex, which shows all clusters are represented in both biological duplicates and that overall follow similar trends in the E18.5 and PN1 samples.

• On the basis of what markers the AFP population has been called adipogenic? Authors present Ptch2 and Notch3 as markers of this cluster, but not adipogenic progenitor genes.*

Fig. 1C represents differentially expressed markers between clusters, which is why we chose these two representative markers for the AFP population. AFP cells also express adipogenic genes such as Pparg, Lpl or Gas6, although not exclusively. Cluster annotation is based on their molecular signature per se, GO and SCENIC analysis, which identified adipogenic regulons as active in the AFP cluster (see Fig. S10).

• Authors claim that there is a good correlation between OsC and osteo-CAR clusters. However, OsC cells do not express Cxcl12 and other typical CAR cell markers.*

We thank the reviewer for raising this very important point, as both our study and other recent ones (Liu et al., 2022, doi.org/10.1038/s41467-022-28775-x; Kara et al., 2023, doi:10.1016/j.devcel.2023.02.003), show that the most representative genes that historically define CARs (e.g. Cxcl12-high and LepR) are still not expressed at these stages, which indicates that these cells are not yet present at perinatal stages. Accordingly, we did not annotate any perinatal cluster as CAR cells. However, we did observe that other genes such as Runx2, Sp7, Spp1 or Alpl define populations belonging to the OsC cluster that map to the same integrated coordinates as the adult osteo-CAR cluster defined by Baccin et al. (Fig. 2C, bottom panel and Fig. S3, bottom panels). These observations stress the importance of performing ontogenic analysis for each marker defining specific populations, and that data obtained from adult tissue cannot be extrapolated to perinatal stages. We have also corrected the figure legend, which was certainly confusing in this respect.

• In Figure 6 expression of PaS cell markers should be shown for both adult and perinatal populations. Additionally, have the authors tested that the sorted cells in panel C have the same progenitor properties as the PaS cells?*

As requested by the reviewer, we have added the expression of PaS cell markers in adults to Fig. 6 (new panels in Fig. 6B). We are certainly considering exploring in the future the progenitor properties of the sorted cells in comparison to PaS, but these in vivo experiments will require extensive experimentation such as kidney subcapsular transplants in newborns in an immunocompromised background. We consider that these complex in vivo experiments are out of the scope of this manuscript, conceived as a resource paper.

Reviewer #1 (Significance (Required)):

* *As indicated in the comments for the authors, the new scRNA-seq data could become a useful resource for subsequent studies, but they are at present insufficient to represent a significant scientific advancement. The main concern is that new cell populations appear to have been identified by the authors, but a number of questions were not answered such as regarding their actual location in the skeletal elements, their origins, their fates and their functions. Generating such data would require a major amount of effort and require substantial revision of the manuscript.

Our study uncovers, in an unbiased and unsupervised manner, the heterogeneity of the entire perinatal bone with cellular resolution. As the reviewer points out, addressing the origin, fates and functions of the various cell clusters we describe would require a major financial effort and years to be completed. We consider that those aims are well beyond the aims of our manuscript, which is intended as a resource for the large scientific community in the field.

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

* **In the study by Rueda et al. the authors use single cell RNA-sequencing to investigate differences in cellular composition bones/bone marrow between late gestational stage mouse embryos and their perinatal counterparts. The authors describe specific differences in the relative abundance of putative cell types and use established bioinformatic tools to infer interactions as well as molecular mechanisms determining specific functions. The employed methods are well described and the results are presented in a very clear and understandable manner. Despite that, the findings do not provide any substantial knowledge advance but are rather confirming work of published literature while supplementing available single cell RNA-sequencing datasets of mouse bones at adult ages. As such, this work provides an interesting resource but does not report novel biology.

Major comment: The authors explore the interesting transition of embryonic to perinatal bone/bone marrow using single RNA-sequencing. This fills a gap for the field of bone and hematopoietic researchers. There is little to criticize about the presented data. However, while it provides a nice resource, the knowledge gained is incremental. As acknowledged by the authors themselves, their study lacks functional validation of any findings made or conclusions drawn from bioinformatic tools in this manuscript. They use published work to validate their findings but do not go beyond that to confirm putative new biology. Some examples are listed in the minor comments.*

We thank the reviewer for the overall positive comments on our manuscript as a resource study and his/her critical input that we have taken into account when preparing the revised version of the manuscript. Despite the lack of functional validation (already discussed in the General Statements section), we feel that our molecular analysis does provide new valuable insight into the biology of the perinatal bone. For instance, this is the first report that categorizes the heterogeneity of all perinatal bone populations with single cell resolution, and the first that explores the cellular changes in the bone that accompany birth. It also provides an important resource for the generation of more specific genetic models for cell fate tracking or for the interpretation of previous results. Finally, while it is only an inference, our interactome analysis predicts interactions between specific mesenchymal and hematopoietic populations, opening new possibilities for specialists in the specific fields to functionally address in a directed manner (e.g. interactions between the mesenchymal compartment and the Eo/Bas or the ICL-TSP2 subpopulations, which, to the best of our knowledge, have not been previously postulated).

*Minor comments: *

1. * Remark: 10X Chromium does not provide whole transcriptomic coverage but rather captures the most highly abundant transcripts without for example being able to distinguish alternatively spliced gene variants. Based on that, interpretation of gene expression, or the absence of a gene in the dataset, should be interpreted carefully.*

The reviewer is correct, as the method used only captures the 3’UTR of each transcript. We have therefore added a sentence in Materials and Methods to address the limitation of the method. Still, our approach is widely used in the field, as it allows capturing several thousand cells and one facilitating the direct comparison with other datasets, as we ourselves did when integrating the adult dataset from Baccin et al.

• The fact that bone marrow adipose tissue begins to accumulate after birth is well known. It is therefore not surprising that adipogenic progenitor populations start to accumulate perinatally (established by studies cited by the authors). Thus, these results only confirm the validity of the dataset. This represents an example on how the majority of findings have been presented here.*

We fully agree that some of our results confirm, at the single cell level, knowledge previously stablished with other methods. However, and continuing with the case of adipose tissue mentioned by the reviewer, the analysis of our datasets with unbiased tools allowed the identification of fibroblastic populations, such as AFP or GFP, which shown by GO terms and, most importantly, by highly-relevant regulons identified by SCENIC, to be potentially associated with thermogenesis and brown fat differentiation. As far as we know, the specific transcriptional regulators involved in brown fat differentiation in the bone are poorly defined. In addition, adipogenesis is not the only aspect we highlight, being other novel association the putative interaction between fibroblastic mesenchymal populations and Eo/Bas and ILC-ISLP2 hematopoietic cells. These are just two examples of relevant aspects uncovered by that our holistic analysis of all bone population, and that might be further explored by specialized groups in the respective fields.

• Given that the authors do not provide functional validation of putative new molecular interactions (by CellPhoneDB) their conclusions should be presented in a more tempered manner and acknowledged as inference rather than fact.*

We agree with the reviewer and accordingly, we have tuned-down several statements throughout the text (see also response to Reviewer #1).

• Similarly, the authors claim "...we identified Ptx4 as a novel tenogenic-specific gene...". This is too strong a conclusion as this has not been functionally validated. It should at least be tested by immuno-(co)-staining.*

Being Ptx4 a secreted molecule, it would be very difficult to reliably assign the signal to a specific population by co-immunolocalization with bona fide tenogenic markers such as Scx or Tnmd. Besides, when pointing out Ptx4 specific expression in the tenogenic branch of the TC cluster, we intended to suggest the potential use of this locus for the generation of novel genetic tools. We have reformulated this sentence to clearly indicate this and avoid claiming that Ptx4 is a novel tenogenic marker.

• The authors identify "uncommitted clusters" as mesenchymal progenitor populations without actual showing that they are even related by lineage. This is a general pitfall in analyzing single cell RNA-sequencing data and making trajectory/pseudotime inferences. It is now well-established that the mesenchymal compartment is highly heterogeneous and composed of multiple distinct cellular lineages. Trajectory inference tools such as PHATE do not distinguish those different mesenchymal lineages. As such, the presented results cannot be considered valid unless there is proper functional validation.*

We agree with the reviewer on the limitation of this type of analysis, such as its inability to resolve phenotypic convergence (e.g. the case for osteoblasts generated from reprogrammed hypertrophic chondrocytes or from perichondrial cells). We have therefore removed the PHATE data from the manuscript.

• The description of PaS being mainly associated with compact bone is neither correct nor supported by cited studies. The authors show potential additional markers to target Pas in mice, but fail to validate their point that these markers could be used in human tissue as well.*

We thank the reviewer for pointing this out and we apologize for our incorrect wording. What we intended to mean is that PaS cells can only be efficiently extracted by enzymatic treatment of the bone fraction after bone marrow aspiration in adults. We have now corrected these instances in the revised manuscript.

Concerning the validation in human samples of the proposed additional markers for the PaS population, we agree that this is an important point, but one that would require the processing of fetal/newborn human bone tissue for FC, which is beyond our capacities and the scope of the current manuscript

Figure 1c: the legend for dotsize is off scale.

We thank the reviewer for spotting this mistake, which inadvertedly happened during figure assembly and is now corrected.

Reviewer #2 (Significance (Required)):

• Strength:
• thorough analysis of single cell RNA-sequencing datasets including integration of published work
• good writing and figure presentation
• dataset fills gap for the field as the presented ages have not been published

Limitations: - lacking functional validation - lack of new biology - mostly confirmation of known facts

Advance: - knowledge gain is incremental - good resource

Audience: - fills a gap in the bone and hematopoietic research field as a resource

My expertise: Skeletal stem cell lineage biology, single cell RNA-sequencing of bone cell populations.*

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

*__

Summary The authors present data on a very interesting model, mouse bone just before and after birth. In this timeframe, the organism has to adapt from a buoyant, nurtured environment to stronger gravitational forces acting upon the skeletal structure, changed oxygen uptake, changed demands to the immune system and its development, and an overall changed metabolism. The authors introduce these changes and their importance in a clear, easy-to read introduction, and this clear structure and language continue throughout the manuscript. Comparing scRNA-seq of bone E18.5 and adult stage, comparable findings by Liu Y. et al., (https://doi.org/10.1038/s41467-022-28775-x) have been previously shown. However, this manuscript showed additional postnatal day 1 (P1) data. All computational analyses are well done, for the most part well described, and, notably, the integration of previously published data allows us to put the results of this study into context and compare them to the adult situation. Data sharing is not optimal, but it is already very good. The only downside is that most of the computational analyses are done at a very limited level of depth and merely provide initial insights and an overview of the data presented.

We thank the reviewer for the overall positive view of our manuscript and his/her critical comments which we have tried to address in our revisions. We wish to apologize for our omission in citing the Liu et al. study, which is now corrected in the revised text. In this respect, we would like to point out that the Liu et al. study is mostly centered in the endothelial compartment, whereas our work is more focused on the mesenchymal populations. Hence, both studies are complementary. Of note, Liu et al. were able to detect Wnt2 expression in E18.5 endothelial cells using targeted single-cell RNA-seq for a panel of specific genes, while in our data, more focused on the mesenchymal compartment, Wnt2 expression maps mostly to the SFP fibroblastic cluster, with low expression in few endothelial cells. In our view, this apparent discrepancy is not such, but the result of different strategies of sorting and enrichment, and illustrates the need of having complementary studies and datasets (e.g the SFP populations may also be an additional source of Wnt2 to promote hematopoietic stem and progenitor cell proliferation, as reported by Liu et al.).

As for the limited depth on our analysis mentioned by the reviewer, we would like to point out that we made a major effort to put our observations in the context of the vast literature on both the mesenchymal and hematopoietic compartments, which forced us to synthetize in the main text. When possible, we added additional data as part of the supplementary information (e.g. full CellPhoneDB inferred interactions as Excel tables).

*Further comments will be given in bullet-point form, split by their impact on the overall message of the manuscript. *

* Major • The authors provide FACS results for the cell clusters and types they defined from the scRNA-Seq data but do not provide any results on where and in which cellular contexts these cells are found in the bone and whether their spatial proximity and proteome (via staining, for example) make it likely or unlikely to see the cell-cell communication suggested in their CellPhoneDB analysis. The authors should either provide such results or adjust sentences as follows to not overstate their results: "These analyses also unveiled the complex MC-HC connectome, in particular the abundant interactions of fibroblastic SFP, AFP, CLFP, and GFP populations with HPC, and quite outstandingly, with the ILC-TSP2 and Eo/Bas clusters."*

We agree with the reviewer but, as previously commented in the General Statements and in our response to Reviewer #1, spatial localization of all populations is technically challenging in the bone and the methods we have tested fall short for the precise and reliable localization of specific bone cell populations with cellular resolution. Following his/her suggestion, we have systematically edited the text so as to not overstate any message stemming from our expression analysis.

• To address the issue of lineage commitment, the authors could offer some functional assessments between E18.5 and P1 or Adult bone BMSCs stromal cells subset that were sorted using FACS (Fig. 6).*

As commented in our response to Reviewer #2, and given the complex lineage relations in the bone, addressing this point would require extensive in vivo experimentation through transplant surgery in immunocompromised newborns or genetic analysis using novel mouse alleles, both of which we consider out of the scope of our study, conceived as a resource. Of note, in Fig. 6 we did not analyze by FC any adult population, but in the revised Fig. 6A, we now provide the expression of all markers in perinatal and adult datasets. In relation with lineage relations, we have also removed the PHATE analysis from the revised manuscript, as suggested by Reviewer #2.

Minor • The visualization of UMAP embeddings is very inconsistent across the manuscript and misleading or irritating in some cases. For example, in Figure 1b, the separation of the background grid is not clearly visible between E18 and PN1. In other figures in the same manuscript, borders around the figures solve this issue. Additionally, axes are either missing or unlabeled, whereas for UMAP embeddings, irrelevant axis tick labels and grid lines are present in most figures. It would benefit the overall flow and visualization of the manuscript if UMAP figures were more consistent.

We apologize for these inconsistencies and we thank the reviewer for pointing them out. We have now separated both panels in Fig. 1B and added borders so as to separate both UMAP plots. We have also added the missing labeling of axes throughout the manuscript so as to make all figures more consistent. We have chosen to keep both grid lines and tick labels as they help in the comparison of Harmony-integrated datasets.

• For Figure 1b specifically, it might also make sense to outline the main cell populations in both UMAPs, as in Figure 2a.*

Agreed and done.

• Average gene expression cannot take on values below 0, as that is the lower bound for expression counts. Figure 1c seems to show the colorbar dropping below 0 though. This might just be a problem of confusing color bar label placement, but it should be addressed. It should also be assured that, indeed, there has not been a mix-up and expression values are limited to >=0.*

We should have explained this better. These dotplots in Fig.1 and the heatmap in Fig. S1 use the normalized and scaled expression value (mean=0; standard deviation=1), which means that it might be negative expression values. These instances are interpreted as genes in which the expression levels are lower than the mean expression level in the dataset and facilitate the visualization of differential gene expression in the different clusters. We have now indicated this clearly in the figure legends.

• For the PHATE analysis, was there any batch correction applied to address potential batch effects between the E18 and PN1 datasets?*

We have removed from the manuscript all PHATE analysis. Still, as we use Harmony integration as a batch-correction tool, we now describe it now in detail in the Materials and Methods section.

• Figure 4a: From the text, it is clear that CellPhoneDB was used to calculate significant interactions between cell types. However, it is not clear which threshold (even if default) was used to determine what constitutes a significant interaction.*

We apologize for this omission. We have indicated both in the revised figure legend and in Materials and Methods the threshold (p-value ≤0.05; as calculated by CellPhoneDB) that was used to represent all significant interactions and shown in Fig. 4A.

• Figure 4b: It is unclear why a collection of chord representations was chosen here, as chord diagrams of this kind generally do not provide any useful additional information apart from an interaction being found to be significant (by a certain threshold) between two cell types. Lacking are generally more interesting parameters, such as the interaction score of such interactions or the expression of the involved ligands and receptors, in comparison to other cell types, where the respective interaction was not predicted to be significant. In this particular case, it is also unclear what is encoded by the width of the respective arrows. This should be made clear. Additionally, a suggestion could be to either present this information in an array of two DotPlots, one for ligands and receptors, respectively, or to encode additional information in, for example, the arrow or connector width, with the connector encoding the mean ligand expression and the arrow head encoding the mean receptor expression in the chord diagram.*

We initially chose to use chord plots as we thought it would be a visual way to represent significant interactions but, as the reviewer points out, they do not provide any additional information. In the line with the reviewer’s suggestion, we have substituted all Fig. 4B chord representations for bubble plots in which are both encoded the mean scaled expression of the ligand/receptor pair (the output of the CellPhoneDB tool) and the mean percentage of cells in the clusters expressing the corresponding molecules. We believe that this modification makes this figure more informative and visually easier to interpret.

• The authors do not mention how many genes were used as marker genes for GFP, SFP, etc. for the GO term enrichment analysis. This number (if low), the significance cut-offs, and the method used to determine DEGs could potentially have an impact on the GO enrichment results. The authors should therefore, already in the main manuscript text, mention the number of genes used for each of these cell subtypes and the method used to determine them. The text mentions cellranger, but the underlying methodology is not mentioned.*

In the revised manuscript, we have included how differential gene expression between clusters was calculated (DEGs were obtained using the FindAllMarkers() function in Seurat, using the default parameters -by default Seurat uses the Wilcoxon Rank Sum test for statistical testing) and the genes used for GO analysis (DEGs were filtered to include genes with an adjusted p-value ≤0.005; gene lists provided as new Supplementary Table 1). The resulting number of genes used for GO analysis at E18.5/PN1 was 218/280 (AFP), 455/480 (CLFP), 185/234 (GFP) and 436/305 (SFP). Retrieved GO terms were filtered by a ratio fold of enriched/expected ≥ 2 and manually curated.

Reviewer #3 (Significance (Required)):

* This study and single cell RNA-sequencing data further analyze the distinctions between the neonatal and adult stages of hematopoietic cells and bone stromal cells. This study also demonstrated the cellular heterogeneity of hematopoietic and bone stromal cells, as well as how cellular cross-talk supports osteogenic and hematopoietic cells. This sequencing data will be useful in the future to comprehend how the bone and marrow adapt to a stronger gravitational force operating on the skeletal structure, as well as to changed oxygen consumption, requirements for the development of the immune system, and an overall altered metabolism.*

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

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Referee #3

Evidence, reproducibility and clarity

Summary

The authors present data on a very interesting model, mouse bone just before and after birth. In this timeframe, the organism has to adapt from a buoyant, nurtured environment to stronger gravitational forces acting upon the skeletal structure, changed oxygen uptake, changed demands to the immune system and its development, and an overall changed metabolism. The authors introduce these changes and their importance in a clear, easy-to read introduction, and this clear structure and language continue throughout the manuscript. Comparing scRNA-seq of bone E18.5 and adult stage, comparable findings by Liu Y. et al., (https://doi.org/10.1038/s41467-022-28775-x) have been previously shown. However, this manuscript showed additional postnatal day 1 (P1) data.

All computational analyses are well done, for the most part well described, and, notably, the integration of previously published data allows us to put the results of this study into context and compare them to the adult situation. Data sharing is not optimal, but it is already very good. The only downside is that most of the computational analyses are done at a very limited level of depth and merely provide initial insights and an overview of the data presented. Further comments will be given in bullet-point form, split by their impact on the overall message of the manuscript.

Major

• The authors provide FACS results for the cell clusters and types they defined from the scRNA-Seq data but do not provide any results on where and in which cellular contexts these cells are found in the bone and whether their spatial proximity and proteome (via staining, for example) make it likely or unlikely to see the cell-cell communication suggested in their CellPhoneDB analysis. The authors should either provide such results or adjust sentences as follows to not overstate their results:
  • "These analyses also unveiled the complex MC-HC12 connectome, in particular the abundant interactions of fibroblastic SFP, AFP, CLFP13, and GFP populations with HPC, and quite outstandingly, with the ILC-TSP2 and 14 Eo/Bas clusters."
• To address the issue of lineage commitment, the authors could offer some functional assessments between E18.5 and P1 or Adult bone BMSCs stromal cells subset that were sorted using FACS (Fig. 6).

Minor

• The visualization of UMAP embeddings is very inconsistent across the manuscript and misleading or irritating in some cases. For example, in Figure 1b, the separation of the background grid is not clearly visible between E18 and PN1. In other figures in the same manuscript, borders around the figures solve this issue. Additionally, axes are either missing or unlabeled, whereas for UMAP embeddings, irrelevant axis tick labels and grid lines are present in most figures. It would benefit the overall flow and visualization of the manuscript if UMAP figures were more consistent.
• For Figure 1b specifically, it might also make sense to outline the main cell populations in both UMAPs, as in Figure 2a.
• Average gene expression cannot take on values below 0, as that is the lower bound for expression counts. Figure 1c seems to show the colorbar dropping below 0 though. This might just be a problem of confusing color bar label placement, but it should be addressed. It should also be assured that, indeed, there has not been a mix-up and expression values are limited to >=0.
• For the PHATE analysis, was there any batch correction applied to address potential batch effects between the E18 and PN1 datasets?
• Figure 4a: From the text, it is clear that CellPhoneDB was used to calculate significant interactions between cell types. However, it is not clear which threshold (even if default) was used to determine what constitutes a significant interaction.
• Figure 4b: It is unclear why a collection of chord representations was chosen here, as chord diagrams of this kind generally do not provide any useful additional information apart from an interaction being found to be significant (by a certain threshold) between two cell types. Lacking are generally more interesting parameters, such as the interaction score of such interactions or the expression of the involved ligands and receptors, in comparison to other cell types, where the respective interaction was not predicted to be significant. In this particular case, it is also unclear what is encoded by the width of the respective arrows. This should be made clear. Additionally, a suggestion could be to either present this information in an array of two DotPlots, one for ligands and receptors, respectively, or to encode additional information in, for example, the arrow or connector width, with the connector encoding the mean ligand expression and the arrow head encoding the mean receptor expression in the chord diagram.
• The authors do not mention how many genes were used as marker genes for GFP, SFP, etc. for the GO term enrichment analysis. This number (if low), the significance cut-offs, and the method used to determine DEGs could potentially have an impact on the GO enrichment results. The authors should therefore, already in the main manuscript text, mention the number of genes used for each of these cell subtypes and the method used to determine them. The text mentions cellranger, but the underlying methodology is not mentioned.

Significance

This study and single cell RNA-sequencing data further analyze the distinctions between the neonatal and adult stages of hematopoietic cells and bone stromal cells. This study also demonstrated the cellular heterogeneity of hematopoietic and bone stromal cells, as well as how cellular cross-talk supports osteogenic and hematopoietic cells. This sequencing data will be useful in the future to comprehend how the bone and marrow adapt to a stronger gravitational force operating on the skeletal structure, as well as to changed oxygen consumption, requirements for the development of the immune system, and an overall altered metabolism.

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Referee #2

Evidence, reproducibility and clarity

In the study by Rueda et al. the authors use single cell RNA-sequencing to investigate differences in cellular composition bones/bone marrow between late gestational stage mouse embryos and their perinatal counterparts. The authors describe specific differences in the relative abundance of putative cell types and use established bioinformatic tools to infer interactions as well as molecular mechanisms determining specific functions. The employed methods are well described and the results are presented in a very clear and understandable manner. Despite that, the findings do not provide any substantial knowledge advance but are rather confirming work of published literature while supplementing available single cell RNA-sequencing datasets of mouse bones at adult ages. As such, this work provides an interesting resource but does not report novel biology.

Major comment: The authors explore the interesting transition of embryonic to perinatal bone/bone marrow using single RNA-sequencing. This fills a gap for the field of bone and hematopoietic researchers. There is little to criticize about the presented data. However, while it provides a nice resource, the knowledge gained is incremental. As acknowledged by the authors themselves, their study lacks functional validation of any findings made or conclusions drawn from bioinformatic tools in this manuscript. They use published work to validate their findings but do not go beyond that to confirm putative new biology. Some examples are listed in the minor comments.

Minor comments:

1. Remark: 10X Chromium does not provide whole transcriptomic coverage but rather captures the most highly abundant transcripts without for example being able to distinguish alternatively spliced gene variants. Based on that, interpretation of gene expression, or the absence of a gene in the dataset, should be interpreted carefully.
2. The fact that bone marrow adipose tissue begins to accumulate after birth is well known. It is therefore not surprising that adipogenic progenitor populations start to accumulate perinatally (established by studies cited by the authors). Thus, these results only confirm the validity of the dataset. This represents an example on how the majority of findings have been presented here.
3. Given that the authors do not provide functional validation of putative new molecular interactions (by CellPhoneDB) their conclusions should be presented in a more tempered manner and acknowledged as inference rather than fact.
4. Similarly, the authors claim "...we identified Ptx4 as a novel tenogenic-specific gene...". This is too strong a conclusion as this has not been functionally validated. It should at least be tested by immuno-(co)-staining.
5. The authors identify "uncommitted clusters" as mesenchymal progenitor populations without actual showing that they are even related by lineage. This is a general pitfall in analyzing single cell RNA-sequencing data and making trajectory/pseudotime inferences. It is now well-established that the mesenchymal compartment is highly heterogeneous and composed of multiple distinct cellular lineages. Trajectory inference tools such as PHATE do not distinguish those different mesenchymal lineages. As such, the presented results cannot be considered valid unless there is proper functional validation.
6. The description of Pas being mainly associated with compact bone is neither correct nor supported by cited studies. The authors show potential additional markers to target Pas in mice, but fail to validate their point that these markers could be used in human tissue as well.
7. Figure 1c: the legend for dotsize is off scale.

Significance

Strength:

• thorough analysis of single cell RNA-sequencing datasets including integration of published work
• good writing and figure presentation
• dataset fills gap for the field as the presented ages have not been published

Limitations:

• lacking functional validation
• lack of new biology - mostly confirmation of known facts

Advance:

• knowledge gain is incremental
• good resource

Audience:

• fills a gap in the bone and hematopoietic research field as a resource

My expertise: Skeletal stem cell lineage biology, single cell RNA-sequencing of bone cell populations

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Referee #1

Evidence, reproducibility and clarity

In this new manuscript, Rueda and colleagues present an extensive bioinformatics analysis of single cell transcriptomic data obtained for mouse endochondral bone cell populations before and after birth. They describe gene markers of mesenchymal and hematopoietic cells pointing to differences with adult bone populations, and they use gene ontology and trajectory analyses to infer possible roles of these cells in the developing bone. The data could provide a valuable resource for further understanding endochondral bone development and the changes driving this process in peri-natal stages. However, they are also significant weaknesses.

A major weakness is that the scRNA-seq data lack validation through other techniques and functional assays. Namely, in situ data are missing to locate the various cell populations in the developing bones, especially the different types of fibroblastic cells identified by the authors. Such data would go a long way to understand the possible functions of the cell populations. Although the authors tried to complement their data with a review of the literature, most of the conclusions remain purely speculative and not sufficiently supported by scientific and statistic rigor. This makes the Results section more like a discussion than a description of the results. For instance, the authors proposed important regulatory functions for the fibroblastic clusters, but there is no data supporting this other than broad GO terms associated with genes expressed in these cells. Related to this point, the title of the manuscript does not accurately reflect the content of the study.

Other points:

1. The authors missed to report in the Results section which skeletal elements they used for their analyses and which skeletal elements were used for the adult dataset that they compared their data with. Differences in skeletal elements and in the ways whereby these samples were collected and processed could explain differences detected in the two types of datasets. Also, the sex and age of the samples for the adult dataset should be reported.
2. It is unclear whether PN1 is the day that mice are born (classically referred to as P0) or the next day.
3. It is unclear whether the cells obtained for each biological replicate were pooled for the scRNA-seq assays or were treated individually. It is thus unclear how reproducible the data are.
4. It is not clear in the gating strategy chosen for the flow cytometry as shown in Fig. 1A why the green gate containing cells expressing high levels of CD9, CD140 and CD31 has been extended in between the purple and orange gates containing CD140 and CD31 negative cells.
5. Are cells from all the sequenced samples homogenously distributed in the scRNA-seq clusters? Authors should provide this information and add statistic when they describe changes in the amount of cells per cluster between E18.5 and PN1 stages.
6. On the basis of what markers the AFP population has been called adipogenic? Authors present Ptch2 and Notch3 as markers of this cluster, but not adipogenic progenitor genes.
7. Authors claim that there is a good correlation between OsC and osteo-CAR clusters. However, OsC cells do not express Cxcl12 and other typical CAR cell markers.
8. In Figure 6 expression of PaS cell markers should be shown for both adult and perinatal populations. Additionally, have the authors tested that the sorted cells in panel C have the same progenitor properties as the PaS cells?

Significance

As indicated in the comments for the authors, the new scRNA-seq data could become a useful resource for subsequent studies, but they are at present insufficient to represent a significant scientific advancement. The main concern is that new cell populations appear to have been identified by the authors, but a number of questions were not answered such as regarding their actual location in the skeletal elements, their origins, their fates and their functions. Generating such data would require a major amount of effort and require substantial revision of the manuscript.

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Reply to the reviewers

Through Review Commons, we received some highly favorable and constructive feedback from reviewers who are clearly knowledgeable about phylogenomics and/or the field of bacterial anti-phage immunity. We have responded to all suggestions made by the reviewers, which we feel have substantially improved and clarified the manuscript. We thank all three reviewers for their thoughtfulness and time.

Reviewer #1

Evidence, reproducibility and clarity

Culbertson and Levin present an elegant computational analysis of the evolutionary history of several families of immune proteins conserved in bacteria and metazoan cells. The authors' work is impressive, revealing interesting insight into previously known connections and identifying exciting new connections that further link bacterial anti-phage defense and animal innate immunity. The results are overall well-presented and will have an important impact on multiple related fields. I have a few comments for the authors to help explain some of the new connections observed in their findings and clarify the results for a general audience.

We thank the reviewer for their kind appraisal of our manuscript as well as their helpful comments. We found their comments to be very useful in strengthening our work and increasing the clarity of the writing.

Comments: 1) The authors adeptly navigate difficult and changing nomenclature around cGAS-STING signaling but there may be room for clarifying terminology. Although historically the term "CD-NTase" has been used to describe both bacterial and animal enzymes (including by this reviewer's older work as well), the field has now settled on consistent use of the name "CD-NTase" to describe bacterial cGAS/DncV-like enzymes and the use of the names "cGAS" and "cGLR" to describe animal cGAS-like receptor proteins. Nearly all papers describing bacterial signaling use the term CD-NTase, and since 2021 most papers describing divergent cGAS-like enzymes in animal signaling now use the term "cGLR" (for recent examples see primary papers Holleufer et al 2021 PMID 34261128; Slavik et al 2021 PMID 34261127; Li et al 2023 PMID 37379839; Cai et al 2023 PMID 37659413 and review articles Cai et al 2022 PMID 35149240; Slavik et al 2023 PMID 37380187; Fan et al 2021 PMID 34697297; West et al 2021 PMID 34373639 Unterholzner Cell 2023 PMID 37478819). Kingdom-specific uses of CD-NTase and cGLR may help add clarity to the manuscript especially as each group of enzyme is quite divergent and many protein members synthesize signaling molecules that are distinct from cyclic GMP-AMP (i.e. not cGAS).

Related to this point, the term "SMODS" is useful for describing the protein family domain originally identified in the elegant work of Burroughs and Aaravind (Burroughs et al 2015 PMID 26590262), but this term is rarely used in papers focused on the biology of these systems. "eSMODS" is a good name, but the authors may want to consider a different description to better fit with current terminology.

We appreciate the reviewer’s suggestion and have updated the text to try to be more clear (ex: using cGLR as a more specific term whenever possible). However, as OAS is distinctly not a cGLR, strict kingdom-specific use of the terms CD-NTase and cGLR is not possible. We have updated the Mab21 superfamily to be re-named as the cGLR superfamily, as those seem to be synonymous based on recent literature. At this time we are choosing to stick with the eSMODS terminology as it remains to be shown that these eukaryotic proteins have a CD-NTase-like biochemical function.

An example of how we have tried to navigate this naming issues is:

“The cGLR superfamily passed all four of these HGT thresholds, as did another eukaryotic clade of CD-NTases that were all previously undescribed. We name this clade the eukaryotic SMODS (eSMODS) superfamily, because the top scoring domain from hmmscan for each sequence in this superfamily was the SMODS domain (PF18144), which is typically found only in bacterial CD-NTases (Supplementary Data).”

2) The authors state that proteins were identified using an iterative HMM-based search until they "began finding proteins outside of the family of interest" (Line 86). Is it possible to please explain in more detail what this means? A key part of the analysis pipeline is knowing when to stop, especially as some proteins like CD-NTases and cGLRs share related-homology to other major enzyme groups like pol-beta NTases while other proteins like STING and viperin are more unique.

We have updated the text to better explain how we determined that a given protein sequence was excluded:

“After using this approach to create pan-eukaryotic HMMs for each protein family, we then added in bacterial homologs to generate universal HMMs (Fig. 1A and Supp. Fig. 1), continuing our iterative searches until we either failed to find any new protein sequences or began finding proteins outside of the family of interest (Supp. Fig. 1). To define the boundaries that separated our proteins of interest from neighboring gene families, we focused on including homologs that shared protein domains that defined that family (see Materials and Methods for domain designations) and were closer to in-group sequences than the outgroup sequences on a phylogenetic tree (outgroup sequences are noted in the Materials and Methods). “

We also added a section to the Methods specifically defining our outgroups:

“As outgroup sequences, we used Poly(A) RNA polymerase (PAP) sequences for the CD-NTases, and molybdenum cofactor biosynthetic enzyme (MoaA) for viperin. We did not have a suitable outgroup for STING domains, nor did any diverged outgroups come up in our searches.”

3) The authors comment on several controls to guard against potential contaminating bacterial sequences present in metazoan genome sequencing datasets (Lines 174-182). It may be helpful to include this very important part of the analysis as part of the stepwise schematic in Figure 1a. Additionally, have the authors used other eukaryotic features like the presence of introns or kingdom specific translation elements (e.g. Shine-Dalgarno- vs. Kozak-like sequences) as part of the analysis?

We agree that it will be very interesting to look for these eukaryotic gene features, both to rule out contamination and to discern how eukaryotes have acquired and domesticated bacteria-like immune proteins. However, one limitation when working with the data in EukProt is that many species are represented by de novo transcriptome datasets and therefore information about the local gene environment, introns, or promoters are unavailable.

4) A particularly surprising result of the analysis is a proposed connection between oligoadenylate synthase-like (OAS-like) enzymes and bacterial Clade C CD-NTases. A concern with these results is that previous structural analysis has demonstrated that bacterial CD-NTase enzymes and animal cGLRs are more closely related to each other than they are to OAS (Slavik et al 2021 PMID 34261127). Can the authors provide further support for a connection between OAS and Clade C CD-NTases? The C-terminal alpha-helix bundle of OAS is known to be distinct (Lohöfener et al 2015 PMID 25892109) and perhaps AlphaFold2 modeling of bacterial Clade C CD-NTases and additional OAS sequences may provide further bioinformatic evidence to support the authors' conclusions.

We were also surprised by this finding as it seems to be in opposition to structural comparisons in studies such as Whiteley et. al 2019 (PMID 30787435). As the reviewer suggests,e used AlphaFold to predict the structures of two CD-NTases, that of Bacterioides uniformis (Clade C016) and Escherichia coli (Clade C018) as well as a previously uncharacterized OAS-like protein (Tripos fusus P058904) and compared those structural predictions to those of cGAS (PDB: 6CTA), OAS1 (PDB: 4RWO), and DncV (PDB: 4TY0). We used the DALI server to make these all vs all comparisons.

     We have not included these analyses in the manuscript as the results were largely inconclusive. The average pairwise z-score between any of these structures was around 20, with a narrow range of scores between 16 (e.g. OAS vs. DncV) and 22 (e.g. DncV vs. the Clade C CD-NTases). For reference, the z-score of a given protein compared to itself was ~50 and a z-score of 20 is a general DALI benchmark used to determine if structures are homologous ( z-scores between 8-20 are in a gray area, and 20+ are generally considered homologous).

In our view, these pairwise structural comparisons suffer from essentially the same problem that is evident in phylogenetic trees containing only animal and bacterial homologs. Namely, all structures/sequences under consideration are extremely different from each other, on very long branches that are difficult to place with confidence when few homologs are being considered. The benefit of our approach is that we have the ideal species diversity to break up the long branches (particularly with respect to the OAS superfamily), allowing us to place those sequences confidently on the phylogeny.

That said, while we have strong support for the topology of OAS within the CD-NTase tree, the interpretation of the relationships relies partly on the inferred root of the tree. In our analyses, we opted not to include a distant outgroup such as pol-beta for rooting purposes, as these sequences aligned poorly with the CD-NTases, resulting in a substantial decrease in alignment and tree quality. Instead, in Fig. 2 we present a tree that is arbitrarily rooted within the bacterial CD-NTases, as this root allows for clade C to be phylogenetically coherent. Our data are also consistent with an alternative rooting, placing OAS as an outgroup. If so, this would yield a tree that implies that OAS-like sequences could have given rise to all other CD-NTases and that, within the non-OAS sequences, all bacterial CD-NTases emerged from within Clade C. We thought it slightly more likely that the root of CD-NTases was solidly within bacteria, hence the display we chose. However, we were not intending to rule out an OAS-outgroup model here. As this response to reviewers will be publically available alongside the final manuscript, we hope this clarifies our claims about the placement of OAS.

5) One of the most exciting results in the paper is identification of a family of putative CD-NTase enzymes conserved in metazoans. Although full description may be beyond the scope of this paper, if possible, some more analysis would be interesting here: a. Are these CD-NTase enzymes in a conserved gene neighborhood within the metazoan genomes (i.e. located next to a potential cyclic nucleotide receptor?) b. Do these metazoan genomes encode other known receptors for cyclic nucleotide signaling (PFAM searches for CARF or SAVED domains for instance). c. Similar to points 3 and 4, is it possible to add further evidence for support of these proteins as true metazoan sequences that have predicted structural homology to bacterial CD-NTase enzymes?

Yes agreed, we think point a is an exciting avenue of questioning to pursue. However, as mentioned above, the Eukprot dataset often does not provide the relevant information for the analyses proposed. Therefore, we feel that answering questions about the genomic region of these proteins is beyond the scope of the current manuscript. In particular, all 6 of the eSMODS species are represented only by transcriptomes, making these analyses impossible.

For point b, we searched EukProt with HMMs for SAVED domains (PF18145), finding 24 total SAVED-containing proteins in EukProt. (We did not find a CARF HMM in Pfam, Tigrfam or other databases, and so could not easily carry out these searches.) Five of the 24 SAVED-containing sequences came from species encoding an eSMODS gene. This represented 3 species out of the total 20 species where we detected a SAVED domain. While this is a potentially intriguing overlap, we cannot make a strong claim about whether these SAVED sequences derive from eukaryotes vs. bacterial contamination without undergoing the extensive searching and phylogenetic tree construction methods for SAVED domains that we have performed for our three families of interest. We expect this will be an interesting line of inquiry for a future study.

For point c, we agree that additional evidence to support the finding that the eSMODS are eukaryotic rather than bacterial sequences would be helpful. To us, the strongest pieces of evidence would be: 1) presence of eukaryotic gene architecture, 2) adjacency to clearly eukaryotic genes in the contig, and/or 3) fluorescence in situ hybridization experiments in these species to localize where the genes are encoded. Unfortunately, the transcriptome data available does not provide this level of information. We hope that other groups will follow up on these genes and species to decide the matter more definitively. In the meantime, we feel that our filters for HGT vs. contamination have done as much as possible with the existing dataset. We have modified the text in this region to leave open potential scenarios that could be fooling us, such as the presence of unusual, long-term, eukaryote-associated symbionts in the taxa where we detect eSMODS:

“For species represented only by transcriptomes, these criteria may still have difficulty distinguishing eukaryote-bacteria HGT from certain specific scenarios such as the long-term presence of dedicated, eukaryote-associated, bacterial symbionts. However, because these criteria allow us to focus on relatively old HGT events, they give us higher confidence these events are likely to be real. ”

6) The authors state that obvious CD-NTase/cGLR enzymes are not present in organisms that encode the group of divergent eukaryotic "blSTINGs". Have the authors analyzed the protein-coding genes encoded immediately upstream and downstream of the blSTING proteins with AlphaFold2 and FoldSeek? It would be very exciting if putative cyclic nucleotide generating enzymes are predicted to be encoded within the nearby gene neighborhood.

Similar to the eSMODS, the majority of the species with blSTINGs were represented by transcriptomes (22/26). We do agree that this type of analysis would be very interesting. However, we feel that this is beyond the scope of this manuscript.

7) Line 144 appears to reference the incorrect supplementary figure. SI Figure 4 may be the correct reference?

We agree and have made this change. We thank the reviewer for catching this error.

I hope the authors will find my comments useful, thank you for the opportunity to read this exciting manuscript.

Significance

Culbertson and Levin present an elegant computational analysis of the evolutionary history of several families of immune proteins conserved in bacteria and metazoan cells. The authors' work is impressive, revealing interesting insight into previously known connections and identifying exciting new connections that further link bacterial anti-phage defense and animal innate immunity. The results are overall well-presented and will have an important impact on multiple related fields. I have a few comments for the authors to help explain some of the new connections observed in their findings and clarify the results for a general audience.

Reviewer #2

Evidence, reproducibility and clarity

Describe your expertise? Molecular Evolution, Mechanisms of Protein evolution, Phylogenomics, Adaptation.

Summary: This manuscript broadly aims to improve our understanding the evolutionary relationships between eukaryote and bacterial protein families where members of those families have immune roles. The study focuses on three such families and samples deeply across the eukaryotic tree. The approaches taken include a nice application of the EukProt database and the use of homology detection approaches that are sensitive to the issues of assigning homology through deep time. The main findings show the heterogeneity in means by which these families have arisen, with some of the families originating at least as far back as the LCA of eukaryotes, in contrast the wide spread yet patchy distribution of other families is the result of repeated independent HGT events and/or convergent domain shuffling.

We thank the reviewer for this excellent review and their helpful comments and suggestions. We firmly believe that these comments will strengthen and clarify our work.

Major Comments: 1. Overall the level of detail provided throughout the manuscript is lacking, perhaps the authors were constrained by a word limit for initial submission, if so then this limit needs to be extended to include the detail necessary. In addition, there are some structural issues throughout, e.g. some of the very brief intro (see later comment) reads a little more like methods (paragraph 2) and abstract (paragraph 3). The results section is lacking detail of the supporting evidence from the clever analyses that were clearly performed and the statistics underpinning conclusions are not included.

Good suggestion, we have updated the paper to include more details and statistics on the analyses that were performed. We have also expanded on some of the most interesting findings about these bacterial innate immune proteins in the introduction (see Comment 2 below for our changes), as well as shifting the methods-like paragraph mentioned (paragraph 2) to later on in the paper. For paragraph 3, we have slimmed this down to include fewer details, but leave the final paragraph of the Introduction as a brief synopsis to prime the reader for the rest of the paper.

1. The intro and discussion both include statements about some recent discoveries that bacteria and mammals share mechanisms of innate immunity - but there is no further detail into what would appear to be important work leading to this study. This context needs to be provided in more detail therefore I would encourage the authors to expand on the intro to include specific detail on these significant prior studies. In addition, more background information on the gene families investigated in detail here would be useful e.g. how the proteins produced influence immunity etc should be a feature of the intro. A clear and concise rationale for why these 3 particular gene families (out of all the possible innate immune genes known) were selected for analysis.

We have added in additional background about some of the most exciting discoveries made in the past few years. We also included specific rationale as to why we chose to look at cGAS, STING, and Viperin.

Specifically, we have added the following to the introduction:

“ For example, bacterial cGAS-DncV-like nucleotidyltransferases (CD-NTases), which generate cyclic nucleotide messengers (similar to cGAS), are massively diverse with over 6,000 CD-NTase proteins discovered to date. Beyond the cyclic GMP-AMP signals produced by animal cGAS proteins, bacterial CD-NTases are capable of producing a wide array of nucleotide signals including cyclic dinucleotides, cyclic trinucleotides, and linear oligonucleotides [11,14]. Many of these bacterial CD-NTase products are critical for bacterial defense against viral infection[8]. Interestingly, these discoveries with the CD-NTases mirror what has been discovered with bacterial viperins. In mammals, viperin proteins restrict viral replication by generating 3’-deoxy-3’,4’didehdro- (ddh) nucleotides[4,15–17] block RNA synthesis and thereby inhibit viral replication[15,18]. Mammalian viperin generates ddhCTP molecules while bacterial viperins can generate ddhCTP, ddhUTP, and ddhGTP. In some cases, a single bacterial protein is capable of synthesizing two or three of these ddh derivatives[4]. These discoveries have been surprising and exciting, as they imply that some cellular defenses have deep commonalities spanning across the entire Tree of Life, with additional new mechanisms of immunity waiting to be discovered within diverse microbial lineages. But despite significant homology, these bacterial and animal immune proteins are often distinct in their molecular functions and operate within dramatically different signaling pathways (reviewed here[5]). How, then, have animals and other eukaryotes acquired these immune proteins?”

In regards to why we choose to investigate CD-NTases, STING, and Viperin specifically, we have added the following to the third paragraph of the introduction:

“We choose to focus on the cGAS, STING, and Viperin for a number of reasons. First, in metazoans cGAS and STING are part of the same signaling pathway whereas bacterial CD-NTases often act independently of bacterial STINGs[21], raising interesting questions about how eukaryotic immune proteins have gained their signaling partners. Also, given the vast breadth of bacterial CD-NTase diversity, we were curious as to if any eukaryotes had acquired CD-NTases distinct from cGAS. For similar reasons, we investigated Viperin, which also has a wide diversity in bacteria but a much more narrow described function in eukaryotes.”

1. Context: Genome quality is always a concern, and confirming the absence of an element/protein in a genome is challenging given the variation in quality of available genomes. Low BUSCO scores mean that the assessment of gene loss is difficult to evaluate (but we are not provided with said scores). Query: in the results section it states that the BUSCO completeness scores (which need to be provided) etc were insufficient to explain the pattern of gene loss. I would like to know how they reached this conclusion - what statistical analyses (ANOVA?? OTHER??) have been performed to support this statement and please include the associated P values etc. Similarly, throughout the paper, including in the discussion section, the point is brushed over. If, given a statistical test, you find that some of the disparity in gene presence is explained by BUSCO score, most of your findings are still valid. It would just be difficult to make conclusions about gene loss.

We have rewritten this section to be more clear about what we feel we can and cannot say about gene loss and BUSCO scores. This section now reads:

“However, outside of Metazoa, these homologs were sparsely distributed, such that for most species in our dataset (711/993), we did not recover proteins from any of the three immune families examined (white space, lack of colored bars, Fig. 1B). While some of these absences may be due to technical errors or dataset incompleteness (Supp. Fig. 2), we interpret this pattern as a reflection of ongoing, repeated gene losses across eukaryotes, as has been found for other innate immune proteins[27–29] and other types of gene families surveyed across eukaryotes[28,30–32]. Indeed, many of the species that lacked any of the immune homologs were represented by high-quality datasets (Ex: Metazoa, Chlorplastida, and Fungi). Thus, although it is always possible that our approach has missed some homologs, we believe the resulting data represents a fair assessment of the diversity across eukaryotes, at least for those species currently included within EukProt.”

In addition, we direct readers to EukProt v3, where the BUSCO scores are publicly available.

“BUSCO scores can also be viewed on EukProt v3 (https://evocellbio.com/SAGdb/images/EukProtv3.busco.output.txt).”

1. In terms of the homolog search strategy - line 394 - can you please state what an "outgroup gene family" means in this context. It is unclear but very important to the downstream interpretation of results.

We have updated the materials and methods to specifically name our outgroups:

“As outgroup sequences, we used Poly(A) RNA polymerase (PAP) sequences for the CD-NTases, and molybdenum cofactor biosynthetic enzyme (MoaA) for viperin. We did not have a suitable outgroup for STING domains, nor did any diverged outgroups come up in our searches.”

1. For reproducibility, the materials and methods section needs to provide more detail/sufficient detail to reproduce these results. E.g the section describing phase 1 of the euk searches the text here repeats what is in the results section for the crystal structure work but doesn't give me any information on how, what method was used to "align the crystal structures", what scoring scheme is used and how the scoring scheme identifies "the core"? What specific parameters are used throughout. Why is MAFFT the method of choice for some of the analyses? Whereas, in other cases both MAFFT and MUSCLE are employed. What are the specific settings used for the MAFFT alignments throughout - is it default (must state if that is the case) or is it MAFFT L-INS-I with default settings etc.

We have updated the text to include the specific settings used each time a particular software package was deployed. We also have included information for STING as to how we aligned 3 published crystal structures to determine the boundaries of homology.

Here is how we now discuss identifying the “core” STING domain:

“ For STING, where the Pfam profile includes regions of the protein outside of the STING domain, we generated a new HMM for the initial search. First, we aligned crystal structures of HsSTING (6NT5), Flavobacteriaceae sp. STING (6WT4) and Crassostrea gigas STING (6WT7) with the RCSB PDB “Pairwise Structure Alignment” tool with a jFATCAT (rigid) option[73,74]. We defined a core “STING” domain, as the ungapped region of 6NT5 that aligned with 6WT7 and 6WT4 (residues G152-V329 of 6NT5).Then we aligned 15 eukaryotic sequences from PF15009 (all 15 of the “Reviewed” sequences on InterPro) with MAFFT(v7.4.71)[75] with default parameters and manually trimmed the sequences down to the boundaries defined by our crystal alignment (residues 145-353 of 6NT5). We then trimmed the alignment with TrimAI (v1.2)[76] with options -gt 0.2. The trimmed MSA was then used to generate an HMM profile with hmmbuild from the hmmer (v3.2.1) package (hmmer.org) using default settings. “

We employed three alignment softwares at specific times throughout our analyses. MAFFT was used as our default aligner for most of the analysis. Hmmalign (part of the hmmer package) was used to make the alignments prior to hmmbuild. The overall goal of this work was to reconstruct the evolutionary history of these proteins via a phylogenetic tree. To ensure that this tree topology was as robust as possible we employed the more computationally intensive, but more accurate, tree builder MUSCLE. We have updated the text in the methods section to be more clear as to why we used each software.

We have updated the methods section to read:

“MUSCLE was deployed in parallel with MAFFT to generate these final alignments to ensure that the final tree topology would be as robust as possible. MUSCLE is a slightly more accurate but more computationally intensive alignment software[79].”

1. The justification for the number of HMM searches needs to be included. The choice of starting points for the HMMs was cryptic - please provide details. It is likely that you ran the search until no more sequences were found or until sequences were added from a different gene family, and that these happened to be between 3 and 5 searches, but it reads like you wanted to run it 3 or 5 times and that corresponds to the above condition. Something like this would be clearer: "The profile was [...] until no more sequences were found or until sequences from other gene families were found which was between 3 and 5 times in all cases" - the same is true of figure 1.

We agree that this could have been worded better. We have updated the text to make it more clear that we searched until saturation which happened to occur between 3-5 searches and not that we arbitrarily wanted to do 3-5 searches.

We have updated the text, which now reads:

“After using this approach to create pan-eukaryotic HMMs for each protein family, we then added in bacterial homologs to generate universal HMMs (Fig. 1A and Supp. Fig. 1), continuing our iterative searches until we either failed to find any new protein sequences or began finding proteins outside of the family of interest (Supp. Fig. 1). To define the boundaries that separated our proteins of interest from neighboring gene families, we focused on including homologs that shared protein domains that defined that family (see Materials and Methods for domain designations) and were closer to in-group sequences than the outgroup sequences on a phylogenetic tree (outgroup sequences are noted in the Materials and Methods). “

We also updated the figure legend to Fig. 1. It now reads:

“Each set of searches was repeated until few or no additional eukaryotic sequences were recovered which was between 3-5 times in all cases.”

1. Why do you limit hits to 10 per species - might this lead to misleading findings about gene family diversity? Info and justification for approach is required (411-412).

We limited the hits to 10 per species to limit the influence of any one species on our alignments and subsequent phylogenetic trees. This 10-per-species cap was never reached with any search for STING or Viperin, but was used to throttle the number of Metazoan hits when searching for CD-NTases. Because of this, we probably have missed some amount of the diversity of Metazoan Mab21-like/OAS-like sequences, although this was not a focus of our manuscript. We have updated the text to be more clear about why we have included this limit and when the limit was invoked.

We have update the text, which now reads:

“HMM profiles were used to search EukProt via hmmsearch (also from hmmer v3.2.1) with a statistical cutoff value of 1e-3 and -hit parameter set to 10 (i.e. the contribution of a single species to the output list is capped at 10 sequences). It was necessary to cap the output list, as EukProt v3 includes de novo transcriptome assemblies with multiple splice isoforms of the same gene and we wanted to limit the overall influence a single species had on the overall tree. We never reached the 10 species cap for any search for STING or viperin homologs; only for the CD-NTases within Metazoa did this search cap limit hits.”

1. The information in Supplementary Figure 3 is quite difficult to assess visually, but I think that is what is expected from that figure. However, this is an important underpinning element of the work and should really be quantitatively assessed. A metric of comparison of trees, with defined thresholds etc there are many out there, even a simple Robinson-Foulds test perhaps? Essentially - comparing the panels in Supplementary Figure 3 by eye is unreliable and in this case not possible given there are no labels. It would also be important to provide these full set of phylogenies generated and associated RF/other scores as supplementary file.

We agree that this Supplementary Figure is difficult to assess by eye, however we feel that it is vital to show this data. Visually, we do feel like this figure conveys the idea that while individual branches may move around, the major clades/areas of interest are stable across the different alignments and tree builders. To increase robustness, we have included the weighted Robinson-Foulds test results into a new panel of this figure (Supplementary Fig. 3B).

We have added a section to the methods on how this weighted Robinson-Foulds test was conducted:

“Weighted Robinson-Foulds distances for Supp. Fig. 3B were calculated with Visual TreeCmp (settings: -RFWeighted -Prune trees -include summary -zero weights allowed)[83].”

We added the weighted Robinson-Foulds data to Supplemental Fig. 3 and have updated the figure legend to reflect this new data. The new legend for Supp. Fig. 3B reads:

“(B) The average weighted Robinson-Foulds distances all pairwise comparisons between the four tree types (MAFFT/MUSCLE alignment built with IQTREE/RAXML-ng). Although the distances were higher for the CD-NTase tree (as expected for this highly diverse gene family), all of the key nodes defining the cGLR, OAS, and eSMODS superfamilies, as well as their nearest bacterial relatives, were well supported (>70 ultrafast bootstrap value).”

1. Does domain shuffling mean that phylogenetic reconstruction is less valid? How was the alignment performed in these cases to account for this.

Thank you for bringing this up, this is a point we have now clarified in the text. Our searches, alignments, and trees are all of single protein domains, as typically only conservation within domains is retained across the vast distances between bacteria and eukaryotes. As such, domain shuffling should have no impact on the validity of that phylogenetic reconstruction. We have updated the text to be more clear about the scope of the alignments and searches. We made changes to our wording throughout the manuscript. One specific example of this is:

“Using maximum likelihood phylogenetic reconstruction on the STING domain alone, we identified STING-like sequences from 26 diverse microeukaryotes whose STING domains clustered in between bacterial and metazoan sequences, breaking up the long branch.”

Minor Comments: 10. I am not sure about the use of the term "truly ancestral" or variants thereof, same issues with "significant homology" and "inherited since LECA and possibly longer" .. these are awkwardly phrased. E.g. I think perhaps "homologous across the whole length" might be clearer, and elsewhere "present in LECA and possibly earlier" may be more fitting.

       We have updated the text for these phrases throughout the manuscript and have replaced them with more specific language.

1. Line 75 - "Detecting" rather than discovering?

We appreciate the suggestion. However, because many of these gene families have never been described in the eukaryotic lineages considered here, we think ‘discovering’ is more appropriate. Indeed, the eSMODS lineage demonstrates that our search approach has the power to find not just new homologs but to discover totally new subfamilies of these eukaryotic proteins.

1. 132-133 - more justification is needed for the choice of bacterial genes.

We have clarified that our selection of bacterial CD-NTases included every known CD-NTase at the time of our analysis. The text now reads:

“As representative bacterial CD-NTases, we used 6,132 bacterial sequences, representing a wide swath of CD-NTase diversity[43]. To our knowledge, this dataset included every known bacterial CD-NTase at the time of our analysis.”

1. For the downsizing from 6000 to 500 what were the criteria and thresholds.

We have updated the text to include the PDA software options for downsampling.The text now reads:

“We downsampled the CD-NTase bacterial sequences from ~6000 down to 500 using PDA software (options -k 500) on a FastTree (default settings) tree built upon a MAFFT (default parameters) tree, to facilitate more manageable computation times on alignments and tree construction.“

1. How are you rooting your trees e.g. figure 2? Information is provided for Viperin but not others.

We have updated the text to ensure that the root of every tree is specifically stated.

1. In the results section on CD-NTases I think it would be best to place the second paragraph detailing the role of cGAS earlier in this section, perhaps after the first sentence.

We have moved the second paragraph, which introduces cGAS, OAS, and the other CD-NTases to the beginning of the CD-NTase section.The first paragraph of the CD-NTase section of the results now reads:

“We next studied the evolution of the innate immune proteins, beginning with cGAS and its broader family of CD-NTase enzymes. Following infections or cellular damage, cGAS binds cytosolic DNA and generates cyclic GMP-AMP (cGAMP)[32–35], which then activates downstream immune responses via STING [34,36–38]. Another eukaryotic CD-NTase, 2’5’-Oligoadenylate Synthetase 1 (OAS1), synthesizes 2',5'-oligoadenylates which bind and activate Ribonuclease L (RNase L)[39]. Activated RNase L is a potent endoribonuclease that degrades both host and viral RNA species, reducing viral replication (reviewed here[40,41]). Some bacterial CD-NTases such as DncV behave similar to animal cGAS; they are activated by phage infection and produce cGAMP[8,42,43]. These CD-NTases are commonly found within cyclic oligonucleotide-based anti-phage signaling systems (CBASS) across many bacterial phyla and archaea[8,27,43].”

1. Is FASTtree really necessary to include as it will underperform in all instances? Removing that method and comparing the remaining two (i.e. IQTREE and RAXML) - what level of disagreement do you find between the 2 alignment and 2 tree building methods? The cases that disagree should also be detailed.

We agree that FASTtree underperforms against IQTREE and RAXML and have eliminated those trees from the supplement. We initially had included FASTtree, as it still seems to be widely used in phylogenetic analyses within the recent papers on bacterial immune homologs, but we completely agree with the reviewer and have removed it. In addition, we have calculated and added in the average weighted Robinson-Foulds Distance to Supplemental Figure 3. Our manuscript focuses on features of the phylogenetic trees that were consistent across all the replicate methods. However, given the numerous sequences and high degree of divergence involved, there were many cases where individual branches shifted between the methods, e.g. if individual CD-NTases within bacterial clade G swapped positions with one another. The differences we observed between the trees were inconsequential to our overall conclusions.

1. Again a structural point - the start to paragraph "To understand the evolutionary history of CD-NTases we used the Pfam domain PF03281 as a starting point", I don't know at this point why or how you have done this. The sentence seems a little premature. I would therefore suggest that you start that paragraph with your motivation, "In order to..." and then finish that paragraph with your sentence in quotes above which actually summarizes the paragraph.

We have updated the text to clear up this paragraph (in addition to other structural changes in the CD-NTase section. The paragraph containing information about how we started the HMM searches for the CD-NTases now reads:

“ To begin our sequence searches for eukaryotic CD-NTases, we used the Pfam domain PF03281, representing the main catalytic domain of cGAS, as a starting point. As representative bacterial CD-NTases, we used 6,132 bacterial sequences, representing a wide swath of CD-NTase diversity[21]. Following our iterative HMM searches, we recovered 313 sequences from 109 eukaryotes, of which 34 were metazoans (Supplemental Data and Fig. 1B). Within the phylogenetic trees, most eukaryotic sequences clustered into one of two distinct superfamilies: the cGLR superfamily (defined by clade and containing a Mab21 PFAM domain: PF03281) or the OAS superfamily (OAS1-C: PF10421) (Fig. 2A). Bacterial CD-NTases typically had sequences matching the HMM for the Second Messenger Oligonucleotide or Dinucleotide Synthetase domain (SMODS: PF18144).”

1. Line 148 - "within" change to "before"?

We have updated the text with this suggestion.

1. Unclear from text as is whether you found any STING homologs in arthropods (~line 157). Please update the text for clarity. Would also suggest that "agreeing" should be replaced with "aligning".

We found several STING homologs in arthropods and have updated the text to specifically note this. We also have updated the text as per the suggestion of using the term “aligning” instead of “agreeing”.The text now reads:

“Almost half of these species (10/19) were arthropods, aligning with prior findings of STING sparseness among arthropods(Wu et al. 2014). We did find STING homologs in 8/19 arthropod species in EukProt v3, including the previously identified STINGs of Drosophila melanogaster, Apis mellifera and Tribolium castaneum(Wu et al. 2014; Margolis, Wilson, and Vance 2017).”

1. Line 169 - If clade D is not a clade, maybe it should be called something different.

Yes, unfortunate naming, isn’t it? Clade D is not a coherent clade in our results nor when it was first described, but we feel that for consistency with the rest of the field, it is best if we adhere to previously published nomenclature.

1. Line 188-190 - In principle, max likelihood should be able to infer the right tree even with high divergence.

Yes, we agree that maximum likelihood methods should be able to infer the correct tree. However, we are not sure what change the reviewer is suggesting here.

1. Paragraph starting at 199 - eSMODS - always unknown function or mostly - could be important.

To our knowledge the function of the two closest bacterial CD-NTases to the eSMODS group have an unknown function.

1. For calling HGT you state that one of the criteria is that the euk and bac sequences branched near one another, what is "near" in this scenario?

“Near” in this case refers to being adjacent on the phylogenetic tree. We have updated the text for clarity. The text now reads:

“To minimize such false positive HGT calls, we took a conservative approach in our analyses, considering potential bacteria-eukaryote HGT events to be trustworthy only if: 1) eukaryotic and bacterial sequences branched adjacent to one another with strong support (bootstrap values >70); 2) the eukaryotic sequences formed a distinct subclade, represented by at least 2 species from the same eukaryotic supergroup; 3) the eukaryotic sequences were produced by at least 2 different studies; and 4) the position of the horizontally transferred sequences was robust across all alignment and phylogenetic reconstruction methods used (Supp. Fig. 3A).”

1. In legends be specific about what type of support value, e.g. bootstrap or jack-knife.. I think it is always bootstrap but would be good to have that precision.

Our phylogenetic trees only use bootstrap values for support and so have updated the figure legends and methods to provide this information. Apologies for this lack of clarity.

1. Throughout the text if stating e.g. "clustered robustly and with high support" please provide the appropriate values.

We have updated the text to provide bootstrap values when invoking statements about support. An example of this is:

“There are two clades of Chloroplastida (a group within Archaeplastida) sequences that branch robustly (>80 ultrafast bootstrap value) within the bacteria clade.”

1. It is unclear from the text how the animal origin of the TIR domain is supported (~line 274). Please provide necessary details to support your statements in the results section.

Our phylogenetic tree of TIR domains (Supp. Fig. 7), places C. gigas’ TIR domain (of its STING protein) clusters with high support next to other metazoan TIR domains.

We have updated the STING section to include these lines:

“We also investigated the possibility that C. gigas acquired the TIR-domain of its TIR-STING protein via HGT from bacteria, however this analysis also suggested an animal origin for the TIR domain (Supp. Fig. 7), as the C. gigas TIR domain clustered with other metazoan TIR domains such as Homo sapiens TICAM1 and 2 (ultrafast bootstrap value of 75). Eukaryotic TIR-STINGs are also rare, further supporting the hypothesis that this protein resulted from recent convergence, where animals independently fused STING and TIR domains to make a protein resembling bacterial TIR-STINGs, consistent with previous reports[19].”

1. Replace similar with -> similar "to"

We have accepted the suggestion and replaced “with” with “to”.

1. Line 266: It was previously shown .. or it is known but not "it was previously known"

We have rephrased the sentence to be clearer: “Some eukaryotes like C. gigas…”.

1. The last sentence in paragraph ~line 277: "Our work also identified a number of non-metazoan STINGS...." Please expand on this and provide some of the details on this finding in the text or point to the figure that supports the statement and provide a little more detail here.

The intent of the words on line 277 was a summary of what we had previously discussed in the STING section. For clarity we updated the text, which now reads:

“Interestingly the non-metazoan, blSTINGs (Fig. 3C) that are found in the Stramenopiles, Haptista, Rhizaria, Choanoflagellates and Amoebozoa have a TM-STING domain architecture similar to animal STINGs but a STING domain more similar to bacterial STINGs..”

blSTINGs are discussed in more detail earlier in the STING section (specifically paragraph 3) where we say:

“Using maximum likelihood phylogenetic reconstruction on the STING domain alone, we identified STING-like sequences from 26 diverse microeukaryotes whose STING domains clustered in between bacterial and metazoan sequences, breaking up the long branch. We name these sequences the bacteria-like STINGs (blSTINGs) because they were the only eukaryotic group of STINGs with a bacteria-like Prok_STING domain (PF20300) and because of the short branch length (0.86 vs. 1.8) separating them from bacterial STINGs on the tree (Fig. 3C). While a previous study reported STING domains in two eukaryotic species (one in Stramenopiles and one in Haptista) [19], we were able to expand this set to additional species and also recover blSTINGs from Amoebozoa, Rhizaria and choanoflagellates. This diversity allowed us to place the sequences on the tree with high confidence (bootstrap value >70), recovering a substantially different tree than previous work[19]. As for CD-NTases, the tree topology we recovered was robust across multiple different alignment and phylogenetic tree construction algorithms (Supp. Fig. 3A).”

1. Line 294: it is unclear which are the orphan taxa -we are directed to figure 1 but there is no notation for orphan taxa here perhaps add something to the figure to make obvious which these are.

We have updated the text to mention these orphan taxa specifically by name.

The text now reads:

“The 194 viperin-like proteins we recovered came from 158 species spanning the full range of eukaryotic diversity, including organisms from all of the major eukaryotic supergroups, as well as some orphan taxa whose taxonomy remains open to debate (Fig. 1, Ancyromonadida, Hemimastigophora, Malawimonadida).”

1. Lines 340-341 - some redundant use of eukaryotic/eukaryotes

We have updated the text to reduce redundancy.

1. Lines 475-480 - some further detail needed - how were sequences trimmed to the TIR domain? - what were your starting sequences? etc.

We have updated the text detailing how we acquired a set of proteins from Interpro and how we used hmmscan to determine the coordinates for the TIR domains in those proteins. We then isolated the TIR domains (using the coordinates defined by hmmscan) and proceeded to align those sequences

The text now reads:

“We used hmmscan to identify the coordinates of TIR domains in a list of 203 TIR domain containing-sequences from InterPro (all 203 proteins from curated “Reviewed” selection of IPR000157 (Toll/interleukin-1 receptor homology (TIR) domain as of 2023-04-04)) and 104 bacterial TIR-STING proteins (the same TIR-STING proteins used in Fig. 3)[3]. Next, we trimmed the sequences down to the hmmscan identified TIR coordinates and aligned the TIR domains with MUSCLE (-super5). We trimmed the alignments with TrimAL and built a phylogenetic tree with IQtree (-s, -bb 1000, -m TEST, -nt AUTO).”

1. Check that the colour schemes for branches etc are detailed in the legends of supplementary as well as main.

We have updated the text of figure legends to be more clear about our maintenance of the same color scheme throughout the manuscript. This involved ensuring that the following statement (or an equivalent statement) was present in the figure legends of Figures 2, 3, 4, S2, S3,S4,S5,S6, and S7:

“Eukaryotic sequences are colored according to eukaryotic group as in Fig. 1B.”

1. The threshold set for gaps is very strict at 0.2. This seems quite strict given the sequences are potentially quite highly divergent. What length are the alignments that you are using after trimming - these details need to be included and considered.

We have updated the text to specifically detail how long our alignments were after trimming and how that post-trimming length compares to the length of the alignment for each PFAM group.

Specifically, the text now reads:

“The length of these final alignments were 232, 175, and 346 amino acids long for CD-NTases, STING, and viperin respectively. These alignments represent ≥75% of the length of alignment their respective PFAM domain (PF3281 (Mab-21 protein nucleotidyltransferase domain) for CD-NTases, PF20300 (Prokaryotic STING domain) for STING, and PF404055 (Radical SAM family) for viperin.”

1. How were sequences downsampled with PDA? Line 424.

We have updated the text to include the PDA settings that were used to downsample sequences. The text now reads:

“To ensure the combined HMM did not have an overrepresentation of either bacterial or eukaryotic sequences, we downsampled the bacterial sequences and eukaryotic sequences to obtain 50 phylogenetically diverse sequences of each, and then combined the two downsampled lists. To do this, eukaryotic and bacterial sequences were each separately aligned with MAFFT (default parameters), phylogenetic trees were built with FastTree (v2.1.10)[77], and the Phylogenetic Diversity Analyzer (pda/1.0.3)[78] software with options -k 50 or -k 500 with otherwise default parameters was run the the FastTree files to downsample the sequences while maximizing remaining sequence diversity.”

1. Please provide adequate descriptions for the materials in the supplementary files for the manuscript, they currently lack description. They are useful and we fully support their inclusion with sufficient information.

We have expanded the descriptions of the provided supplementary files.

1. The starting sequences, hmm pipeline and scripts would be great to include, apologies if we have missed them.

We have added the starting bacterial sequences to the supplementary data, as well as the final HMMs, and the one script that we used in our analysis. All other software (including the included script) is freely and publicly available.

Significance

This study provides us with examples of instances where a medley of different mechanisms have resulted in the emergence of innate immune proteins across eukaryotes. The study is entirely bioinformatic in nature and provides some nice cases for future study. The thorough search strategies are to be commended. The limitations of the work are that we don't know whether the functions have also been conserved across deep time and/or in the independent events described. Nevertheless, this work contributes to a growing body of evidence on the complex, and sometimes shared, nature of the evolution of animal and bacterial immunity. I would classify this nice study as a conceptual advance of our understanding of the evolution of protein families through deep time and would imagine it is of interest to a broad audience of biologists from immunologists to evolutionary biologists and structural biologists.

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

The manuscript by Culbertson and Levin takes a bioinformatic approach to investigate the evolutionary origins/trajectories of three different proteins domains involved in innate immunity in both bacteria and eukaryotes: cGAS/CD-NTases, STING, and Viperins. To perform this analysis, the authors apply an iterative homology search model to the EukProt database of eukaryotic genomes. Their analysis finds that that eukaryotic CD-NTases arose from multiple horizontal gene transfer events between bacteria and eukaryotes. They also fill in an important gap in understanding how STING from bacteria evolved into modern human STING by identifying blasting in diverse eukaryotes. Finally, they determine that Viperins are an ancient protein family that likely existed in LECA, but found two more recent HGT events for proteins related in Vipirin.

Major comments

1. The hypothesis for the origin of STING via convergent domain shuffling could be handled with a little more care in the text. The authors show that homologs of STING from animals can also be found in the genomes of diverse eukaryotes outside the metazoa, demonstrating (1) STING and cGAS have had different histories, and (2) that these sequences are more bacteria-like than metazoan STING. However, in multiple places (the title, line 275, elsewhere) the term "convergence" could be misleading. "Convergence" leaves the reader with the impression that there is no common ancestor between the STING domain from bacteria and eukaryotes. I understand that the authors are using "convergent domain shuffling" to draw this distinction, but I'm unsure if a naïve reader will glean the distinction between domain shuffling and STING itself converging. I would argue that we simply cannot place eukaryotic STING and blSTING proteins on the tree of bSTING sequences. i.e. blSTING are no more related to bacterial TM-STING than bacterial TIR-STING (likely the missing bSTING sequences are simply extinct?). Can the authors curate their language to state more simply that STING likely arose through horizontal gene transfer, but it is unlikely that bacterial TM-STING is the unequivocal progenitor?

We thank the reviewer for this comment, and we absolutely agree that we should be clearer about the distinction between convergence and convergent domain shuffling. We have changed the title and edited the text to increase clarity. In addition, we have clarified what our data does and does say about the evolutionary history of STING. We feel that our STING tree (Fig.3 C), due to a general sparseness of eukaryotic and bacterial sequences, is insufficient to confidently call if eukaryotes acquired STING by HGT or if STING was present in the LECA.

We have added the following to clear up this issue:

“Overall, the phylogenetic tree we constructed (Fig. 3C) suggests that there is domain-level homology between bacterial and eukaryotic STINGs, but due to sparseness and lack of a suitable outgroup, this tree does not definitively explain the eukaryotic origin of the STING domain. However, the data does clearly support a model in which convergent domain shuffling in eukaryotes and bacteria generated similar TM-STING and TIR-STING proteins independently.”

Minor Comments

1. Spelling error in Figure 3B and 3C: "cannoical"

Thanks, we have corrected this error.

1. Figure 5 could be improved to more clearly articulate the findings of the manuscript. In A, it's unclear how OAS relates to Mab21 and a reader not paying close attention might think that OAS was part of the gene duplications after Mab21 was acquired. The LECA origins of OAS are also not presented (albeit, these are still defined in the legend). In B, this panel would suggest that there was not horizontal transfer of STING from bacteria to eukaryotes but rather both domains of life received STING from a separate source. My understanding is STING did likely arise in bacteria, however, the assumption that extant TM-STING in bacteria is the predecessor of TM-STING in eukaryotes is not well supported. Similarly for the TIR domain.

We have updated Fig. 5 to more clearly show that OAS was likely in the LECA and that eSMODS and cGLRs were HGT’d from bacteria to other eukaryotic lineages. For STING, it was not our intent to imply that the extant TM-STING in bacteria is the predecessor of TM-STING in eukaryotes, and we agree with the reviewer that this is unlikely. Although we do not have sufficient data to speak to the origin of the STING domain itself, we do feel confident in our evidence of domain shuffling. Our illustration in Fig 5B was meant to correspond to the following statement: “Drawing on a shared ancient repertoire of protein domains that includes STING, TIR, and transmembrane (TM) domains, bacteria and eukaryotes have convergently evolved similar STING proteins through domain shuffling.” We believe this inference valid and best describes our results for STING.

1. Line 119: While the role of Mab21L1-2 are established for development, I'm unaware of a role for MB21D2 in development (or any other phenotype).

We agree with the reviewer that MB21D2 has not been shown to have any phenotype and have corrected the wording to clarify this point.

The line now reads “However, the immune functions of Mab21L1 and MB21D2 remain unclear, although Mab21L1they has been shown to be important for development[29–31].”

1. Line 210: "Gamma" should be "genes"

We have corrected this error and replaced the word.

Reviewer #3 (Significance (Required)):

This work is of high quality, is timely, and will have a large impact on shaping the field. The origins and evolution of antiviral immunity from bacteria to eukaryotes have been investigated from multiple angles. While the phylogeny and evolutionary trajectory of these genes have been traced in bacteria, there have been relatively fewer analyses across diverse (non-metazoan) eukaryotes. For this reason, I am confident that this manuscript will help future researchers select homologs for investigation and guide similar analyses of other bacterial defense systems.

A particular challenge of this work is accounting for gene loss across taxa and weighing that possibility against horizontal gene transfer. The authors are conservative in their conclusions and well-reasoned. The comments I have can be addressed with changes to the writing and emphasis of certain points.

I expect these findings to be of interest to a broad audience of evolutionary biologists, microbiologists, and immunologists.

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

Learn more at Review Commons

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Referee #3

Evidence, reproducibility and clarity

The manuscript by Culbertson and Levin takes a bioinformatic approach to investigate the evolutionary origins/trajectories of three different proteins domains involved in innate immunity in both bacteria and eukaryotes: cGAS/CD-NTases, STING, and Viperins. To perform this analysis, the authors apply an iterative homology search model to the EukProt database of eukaryotic genomes. Their analysis finds that that eukaryotic CD-NTases arose from multiple horizontal gene transfer events between bacteria and eukaryotes. They also fill in an important gap in understanding how STING from bacteria evolved into modern human STING by identifying blasting in diverse eukaryotes. Finally, they determine that Viperins are an ancient protein family that likely existed in LECA, but found two more recent HGT events for proteins related in Vipirin.

Major comments

1. The hypothesis for the origin of STING via convergent domain shuffling could be handled with a little more care in the text. The authors show that homologs of STING from animals can also be found in the genomes of diverse eukaryotes outside the metazoa, demonstrating (1) STING and cGAS have had different histories, and (2) that these sequences are more bacteria-like than metazoan STING. However, in multiple places (the title, line 275, elsewhere) the term "convergence" could be misleading. "Convergence" leaves the reader with the impression that there is no common ancestor between the STING domain from bacteria and eukaryotes. I understand that the authors are using "convergent domain shuffling" to draw this distinction, but I'm unsure if a naïve reader will glean the distinction between domain shuffling and STING itself converging. I would argue that we simply cannot place eukaryotic STING and blSTING proteins on the tree of bSTING sequences. i.e. blSTING are no more related to bacterial TM-STING than bacterial TIR-STING (likely the missing bSTING sequences are simply extinct?). Can the authors curate their language to state more simply that STING likely arose through horizontal gene transfer, but it is unlikely that bacterial TM-STING is the unequivocal progenitor?

Minor Comments

1. Spelling error in Figure 3B and 3C: "cannoical"
2. Figure 5 could be improved to more clearly articulate the findings of the manuscript. In A, it's unclear how OAS relates to Mab21 and a reader not paying close attention might think that OAS was part of the gene duplications after Mab21 was acquired. The LECA origins of OAS are also not presented (albeit, these are still defined in the legend). In B, this panel would suggest that there was not horizontal transfer of STING from bacteria to eukaryotes but rather both domains of life received STING from a separate source. My understanding is STING did likely arise in bacteria, however, the assumption that extant TM-STING in bacteria is the predecessor of TM-STING in eukaryotes is not well supported. Similarly for the TIR domain.
3. Line 119: While the role of Mab21L1-2 are established for development, I'm unaware of a role for MB21D2 in development (or any other phenotype).
4. Line 210: "Gamma" should be "genes"

Significance

This work is of high quality, is timely, and will have a large impact on shaping the field. The origins and evolution of antiviral immunity from bacteria to eukaryotes have been investigated from multiple angles. While the phylogeny and evolutionary trajectory of these genes have been traced in bacteria, there have been relatively fewer analyses across diverse (non-metazoan) eukaryotes. For this reason, I am confident that this manuscript will help future researchers select homologs for investigation and guide similar analyses of other bacterial defense systems.

A particular challenge of this work is accounting for gene loss across taxa and weighing that possibility against horizontal gene transfer. The authors are conservative in their conclusions and well-reasoned. The comments I have can be addressed with changes to the writing and emphasis of certain points.

I expect these findings to be a interest to a broad audience of evolutionary biologists, microbiologists, and immunologists.

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

Describe your expertise? Molecular Evolution, Mechanisms of Protein evolution, Phylogenomics, Adaptation.

Summary: This manuscript broadly aims to improve our understanding the evolutionary relationships between eukaryote and bacterial protein families where members of those families have immune roles. The study focusses on three such families and samples deeply across the eukaryotic tree. The approaches taken include a nice application of the EukProt database and the use of homology detection approaches that are sensitive to the issues of assigning homology through deep time. The main findings show the heterogeneity in means by which these families have arisen, with some of the families originating at least as far back as the LCA of eukaryotes, in contrast the wide spread yet patchy distribution of other families is the result of repeated independent HGT events and/or convergent domain shuffling.

Major Comments:

1. Overall the level of detail provided throughout the manuscript is lacking, perhaps the authors were constrained by a word limit for initial submission, if so then this limit needs to be extended to include the detail necessary. In addition, there are some structural issues thorughout, e.g. some of the very brief intro (see later comment) reads a little more like methods (paragraph 2) and abstract (paragraph 3). The results section is lacking detail of the supporting evidence from the clever analyses that were clearly performed and the statistics underpinning conclusions are not included.
2. The intro and discussion both include statements about some recent discoveries that bacteria and mammals share mechanisms of innate immunity - but there is no further detail into what would appear to be important work leading to this study. This context needs to be provided in more detail therefore I would encourage the authors to expand on the intro to include specific detail on these significant prior studies. In addition, more background information on the gene families investigated in detail here would be useful e.g. how the proteins produced influence immunity etc should be a feature of the intro. A clear and concise rationale for why these 3 particular gene families (out of all the possible innate immune genes known) were selected for analysis.
3. Context: Genome quality is always a concern, and confirming the absence of an element/protein in a genome is challenging given the variation in quality of available genomes. Low BUSCO scores mean that the assessment of gene loss is difficult to evaluate (but we are not provided with said scores). Query: in the results section it states that the BUSCO completeness scores (which need to be provided) etc were insufficient to explain the pattern of gene loss. I would like to know how they reached this conclusion - what statistical analyses (ANOVA?? OTHER??) have been performed to support this statement and please include the associated P values etc. Similarly, throughout the paper, including in the discussion section, the point is brushed over. If, given a statistical test, you find that some of the disparity in gene presence is explained by BUSCO score, most of your findings are still valid. It would just be difficult to make conclusions about gene loss.
4. In terms of the homolog search strategy - line 394 - can you please state what an "outgroup gene family" means in this context. It is unclear but very important to the downstream interpretation of results.
5. For reproducibility, the materials and methods section needs to provide more detail/sufficient detail to reproduce these results. E.g the section describing phase 1 of the euk searches the text here repeats what is in the results section for the crystal structure work but doesn't give me any information on how, what method was used to "align the crystal structures", what scoring scheme is used and how the scoring scheme identifies "the core"? What specific parameters are used throughout. Why is MAFFT the method of choice for some of the analyses? Whereas, in other cases both MAFFT and MUSCLE are employed. What are the specific settings used for the MAFFT alignments throughout - is it default (must state if that is the case) or is it MAFFT L-INS-I with default settings etc.
6. The justification for the number of HMM searches needs to be included. The choice of starting points for the HMMs was cryptic - please provide details. It is likely that you ran the search until no more sequences were found or until sequences were added from a different gene family, and that these happened to be between 3 and 5 searches, but it reads like you wanted to run it 3 or 5 times and that corresponds to the above condition. Something like this would be clearer: "The profile was [...] until no more sequences were found or until sequences from other gene families were found which was between 3 and 5 times in all cases" - the same is true of figure 1.
7. Why do you limit hits to 10 per species - might this lead to misleading findings about gene family diversity? Info and justification for approach is required (411-412)
8. The information in Supplementary Figure 3 is quite difficult to assess visually, but I think that is what is expected from that figure. However, this is an important underpinning element of the work and should really be quantitatively assessed. A metric of comparison of trees, with defined thresholds etc there are many out there, even a simple Robinson-Foulds test perhaps? Essentially - comparing the panels in Supplementary Figure 3 by eye is unreliable and in this case not possible given there are no labels. It would also be important to provide these full set of phylogenies generated and associated RF/other scores as supplementary file.
9. Does domain shuffling mean that phylogenetic reconstruction is less valid? How was the alignment performed in these cases to account for this.

Minor Comments:

1. I am not sure about the use of the term "truly ancestral" or variants thereof, same issues with "significant homology" and "inherited since LECA and possibly longer" .. these are awkwardly phrased. E.g. I think perhaps "homologous across the whole length" might be clearer, and elsewhere "present in LECA and possibly earlier" may be more fitting.
2. Line 75 - "Detecting" rather than discovering?
3. 132-133 - more justification is needed for the choice of bacterial genes.
4. For the downsizing from 6000 to 500 what were the criteria and thresholds.
5. How are you rooting your trees e.g. figure 2? Information is provided for Viperin but not others.
6. In the results section on CD-NTases I think it would be best to place the second paragraph detailing the role of cGAS earlier in this section, perhaps after the first sentence.
7. Is FASTtree really necessary to include as it will underperform in all instances? Removing that method and comparing the remaining two (i.e. IQTREE and RAXML) - what level of disagreement do you find between the 2 alignment and 2 tree building methods? The cases that disagree should also be detailed.
8. Again a structural point - the start to paragraph "To understand the evolutionary history of CD-NTases we used the Pfam domain PF03281 as a starting point", I don't know at this point why or how you have done this. The sentence seems a little premature. I would therefore suggest that you start that paragraph with your motivation, "In order to..." and then finish that paragraph with your sentence in quotes above which actually summarises the paragraph.
9. Line 148 - "within" change to "before"?
10. Unclear from text as is whether you found any STING homologs in arthropods (~line 157). Please update the text for clarity. Would also suggest that "agreeing" should be replaced with "aligning".
11. Line 169 - If clade D is not a clade, maybe it should be called something different.
12. Line 188-190 - In principle, max likelihood should be able to infer the right tree even with high divergence.
13. Paragraph starting at 199 - eSMODS - always unknown function or mostly - could be important.
14. For calling HGT you state that one of the criteria is that the euk and bac sequences branched near one another, what is "near" in this scenario?
15. In legends be specific about what type of support value, e.g. bootstrap or jack-knife.. I think it is always bootstrap but would be good to have that precision.
16. Throughout the text if stating e.g. "clustered robustly and with high support" please provide the appropriate values.
17. It is unclear from the text how the animal origin of the TIR domain is supported (~line 274). Please provide necessary details to support your statements in the results section.
18. Replace similar with -> similar "to"
19. Line 266: It was previously shown .. or it is known but not "it was previously known"
20. The last sentence in paragraph ~line 277: "Our work also identified a number of non-metazoan STINGS...." Please expand on this and provide some of the details on this finding in the text or point to the figure that supports the statement and provide a little more detail here.
21. Line 294: it is unclear which are the orphan taxa -we are directed to figure 1 but there is no notation for orphan taxa here perhaps add something to the figure to make obvious which these are.
22. Lines 340-341 - some redundant use of eukaryotic/eukaryotes
23. Lines 475-480 - some further detail needed - how were sequences trimmed to the TIR domain? - what were your starting sequences? etc.
24. Check that the colour schemes for branches etc are detailed in the legends of supplementary as well as main.
25. The threshold set for gaps is very strict at 0.2. This seems quite strict given the sequences are potentially quite highly divergent. What length are the alignments that you are using after trimming - these details need to be included and considered.
26. How were sequences downsampled with PDA? Line 424.
27. Please provide adequate descriptions for the materials in the supplementary files for the manuscript, they currently lack description. They are useful and we fully support their inclusion with sufficient information.
28. The starting sequences, hmm pipeline and scripts would be great to include, apologies if we have missed them.

Significance

This study provides us with examples of instances where a medley of different mechanisms have resulted in the emergence of innate immune proteins across eukaryotes. The study is entirely bioinformatic in nature and provides some nice cases for future study. The thorough search strategies are to be commended. The limitations of the work are that we don't know whether the functions have also been conserved across deep time and/or in the independent events described. Nevertheless, this work contributes to a growing body of evidence on the complex, and sometimes shared, nature of the evolution of animal and bacterial immunity. I would classify this nice study as a conceptual advance of our understanding of the evolution of protein families through deep time and would imagine it is of interest to a broad audience of biologists from immunologists to evolutionary biologists and structural biologists.

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Referee #1

Evidence, reproducibility and clarity

Culbertson and Levin present an elegant computational analysis of the evolutionary history of several families of immune proteins conserved in bacteria and metazoan cells. The authors' work is impressive, revealing interesting insight into previously known connections and identifying exciting new connections that further link bacterial anti-phage defense and animal innate immunity. The results are overall well-presented and will have an important impact on multiple related fields. I have a few comments for the authors to help explain some of the new connections observed in their findings and clarify the results for a general audience.

Comments:

1. The authors adeptly navigate difficult and changing nomenclature around cGAS-STING signaling but there may be room for clarifying terminology. Although historically the term "CD-NTase" has been used to describe both bacterial and animal enzymes (including by this reviewer's older work as well), the field has now settled on consistent use of the name "CD-NTase" to describe bacterial cGAS/DncV-like enzymes and the use of the names "cGAS" and "cGLR" to describe animal cGAS-like receptor proteins. Nearly all papers describing bacterial signaling use the term CD-NTase, and since 2021 most papers describing divergent cGAS-like enzymes in animal signaling now use the term "cGLR" (for recent examples see primary papers Holleufer et al 2021 PMID 34261128; Slavik et al 2021 PMID 34261127; Li et al 2023 PMID 37379839; Cai et al 2023 PMID 37659413 and review articles Cai et al 2022 PMID 35149240; Slavik et al 2023 PMID 37380187; Fan et al 2021 PMID 34697297; West et al 2021 PMID 34373639 Unterholzner Cell 2023 PMID 37478819). Kingdom-specific uses of CD-NTase and cGLR may help add clarity to the manuscript especially as each group of enzyme is quite divergent and many protein members synthesize signaling molecules that are distinct from cyclic GMP-AMP (i.e. not cGAS).

Related to this point, the term "SMODS" is useful for describing the protein family domain originally identified in the elegant work of Burroughs and Aaravind (Burroughs et al 2015 PMID 26590262), but this term is rarely used in papers focused on the biology of these systems. "eSMODS" is a good name, but the authors may want to consider a different description to better fit with current terminology. 2. The authors state that proteins were identified using an iterative HMM-based search until they "began finding proteins outside of the family of interest" (Line 86). Is it possible to please explain in more detail what this means? A key part of the analysis pipeline is knowing when to stop, especially as some proteins like CD-NTases and cGLRs share related-homology to other major enzyme groups like pol-beta NTases while other proteins like STING and viperin are more unique. 3. The authors comment on several controls to guard against potential contaminating bacterial sequences present in metazoan genome sequencing datasets (Lines 174-182). It may be helpful to include this very important part of the analysis as part of the stepwise schematic in Figure 1a. Additionally, have the authors used other eukaryotic features like the presence of introns or kingdom specific translation elements (e.g. Shine-Dalgarno- vs. Kozak-like sequences) as part of the analysis? 4. A particularly surprising result of the analysis is a proposed connection between oligoadenylate synthase-like (OAS-like) enzymes and bacterial Clade C CD-NTases. A concern with these results is that previous structural analysis has demonstrated that bacterial CD-NTase enzymes and animal cGLRs are more closely related to each other than they are to OAS (Slavik et al 2021 PMID 34261127). Can the authors provide further support for a connection between OAS and Clade C CD-NTases? The C-terminal alpha-helix bundle of OAS is known to be distinct (Lohöfener et al 2015 PMID 25892109) and perhaps AlphaFold2 modeling of bacterial Clade C CD-NTases and additional OAS sequences may provide further bioinformatic evidence to support the authors' conclusions. 5. One of the most exciting results in the paper is identification of a family of putative CD-NTase enzymes conserved in metazoans. Although full description may be beyond the scope of this paper, if possible, some more analysis would be interesting here:

a. Are these CD-NTase enzymes in a conserved gene neighborhood within the metazoan genomes (i.e. located next to a potential cyclic nucleotide receptor?)

b. Do these metazoan genomes encode other known receptors for cyclic nucleotide signaling (PFAM searches for CARF or SAVED domains for instance).

c. Similar to points 3 and 4, is it possible to add further evidence for support of these proteins as true metazoan sequences that have predicted structural homology to bacterial CD-NTase enzymes? 6. The authors state that obvious CD-NTase/cGLR enzymes are not present in organisms that encode the group of divergent eukaryotic "blSTINGs". Have the authors analyzed the protein-coding genes encoded immediately upstream and downstream of the blSTING proteins with AlphaFold2 and FoldSeek? It would be very exciting if putative cyclic nucleotide generating enzymes are predicted to be encoded within the nearby gene neighborhood. 7. Line 144 appears to reference the incorrect supplementary figure. SI Figure 4 may be the correct reference?

I hope the authors will find my comments useful, thank you for the opportunity to read this exciting manuscript.

Philip Kranzusch

Significance

Culbertson and Levin present an elegant computational analysis of the evolutionary history of several families of immune proteins conserved in bacteria and metazoan cells. The authors' work is impressive, revealing interesting insight into previously known connections and identifying exciting new connections that further link bacterial anti-phage defense and animal innate immunity. The results are overall well-presented and will have an important impact on multiple related fields. I have a few comments for the authors to help explain some of the new connections observed in their findings and clarify the results for a general audience.

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Reply to the reviewers

We thanks the reviewers for their critique of our report and our responses to all of their comments are given below.

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

Summary Toxoplasma gondii is an obligate intracellular parasite. Intracellular survival critical depends on secretory vesicles named dense granules. These vesicles are predicted to contain >100 different proteins that are released into PV, PV membrane and the host cell to control the parasites intracellular environment and host cell gene expression and immune response. How and where these vesicles are released from the parasite is a long-standing question in the field because T. gondii, and other apicomplexan parasites contained a complex pellicular cytoskeletal structure called the IMC which limits dense granule access to the plasma membrane. In this manuscript by Chelaghma, Ke and colleagues demonstrates for the first time that dense granules are secreted from the parasite at pore structures called the apical annuli. The authors used their previously generated HyperLOPIT data set and identified a plasma membrane protein that is specifically enriched at the apical annuli. Using BioID the authors then identify three SNARE proteins that also localize at the apical annuli. The localization of these proteins is determined using excellent super-resolution structured illumination microscopy. Conditional protein knockdowns for all four proteins were created and both proteomics and microscopy used to demonstrate a reduction in dense granule secretion in the absence of these proteins. Collectively, these data make new and substantial contributions to our understanding of mechanisms of dense granule secretion. Major comments: Overall, these data is convincing and well-described. The text is clear and well written. There are a few instances (see below) where the authors doesn't adequately describe the data or over state the strength of the results. These issues could all be addressed editorially or by process existing data.

Comment 1.1

The authors use proteomics and IFA to show that there is a reduction (rather than an inhibition of) in dense granule secretion. However, from the phase images in figure 5, the vacuoles of KD parasites look normal and so not have the phenotypes that one would expect after a significant reduction in dense granule secretion, such as the "bubble" phenotype described for GRA17 and GRA23 knockouts (Gold et al 2015; PMID: 25974303). Authors should describe their findings in the context of the expected phenotypes based on the published literature. The statement on line 369-371 is too strong and should imply a reduction rather than an inhibition of dense granule secretion.

Authors’ response: It is difficult to compare our results to individual dense granule protein mutants described in the literature because such phenotypes are the result of the loss of only a single protein being exported to the host, whereas we are observing the effects of the reduction of secretion of up to 120+ different proteins. Furthermore, we agree with this reviewer that none of the protein knockdowns appear to completely prevent dense granule secretion, which we implied by ‘inhibition’, and this could be either due to incomplete knockdown of each of these proteins with some residue function, or some redundancy where other proteins can contribute to secretion. We have changed the statement flagged by this reviewer to: ‘Depletion of all four of these proteins affects dense granule secretion*’ to avoid the interpretation of complete loss of function. We now further state that residual secretion may still occur and consider this in the light of possible reasons for this (Discussion, paragraph 4). In any case, none of these considerations change our conclusion that these proteins, at the site of the apical annuli, are implicated in dense granule secretion. *

__Comment 1.2 __

The more severe phenotype observed in the AAQa iKD and the additional localizations of AAQa and AAQc suggests an additional role for these protein in protein trafficking that is supported by the authors data. In both AAQa and AAQc there appears to be an accumulation of GRA1 in a post-Golgi compartment and is less vesicular in appearance than the phenotype observed in the AAQb iKD parasites. Additionally, I disagree with the authors assessment that KD of these proteins does not effect microneme localization. In both AAQa and AAQc there appears to be increased number of micronemes at the basal end of the parasites compared with controls. Although this is not a direct focus of the authors papers, a description of these findings should be included in the results and discussion sections.

Authors’ response: We have included a more complete discussion that considers the differences in phenotypes of the four mutants, including additional locations of two SNAREs, all of which is consistent with known SNARE biology (Discussion, fourth paragraph). These considerations, however, have no impact on our conclusions where all four proteins, including two that are exclusive to the apical annuli, have equivalent effects on dense granule exocytosis.

Concerning the effects on microneme and rhoptries of the different knockdowns, we have modified and limited our interpretation to overall IFA staining strength and protein organelle protein abundance by proteomics, where we see no differences. This addresses if there is a major post-Golgi trafficking defect that could affect biogenesis of all of micronemes, rhoptries and dense granules, for which we see no evidence. Whether there are subtle differences in the location of these organelles, which are known to show some variability, is beyond the scope or relevance to our central questions. Given that growth phenotypes are seen for all mutants, it is quite possible that secondary effects of retarded cells might present as some disorder within the cell, although we saw nothing conspicuous of this nature in many hundreds of examples observed.

__ Comment 1.3__

Presentation of the data in Figure 5. This figure contains images where the fluorescent dense granule signal is overlaid on phase images. However, in some cases (AAQb, AAQc, AAQa, GRA1 KD) the merged imaged looks like a straight merges of the two images, whereas in the rest of the images it looks like a thresholded fluorescent image is merge with phase. Authors need to process the images in consistent manner and provide a description of the image processing in the figure legend and materials and methods.

Authors’ response: Thank you for this suggestion, we have now processed all of these merges the same way (ImageJ -> merge channels -> Composite Sum). While the merges are only intended to aid in aligning the fluorescence signal with the phase image, we agree that it is better to present them the same way.

Minor comments:

Comment 1.4

The discussion is overly long and could be shorted in some places. Lines 373 and 388 in particularly don't seems directly relevant to the manuscript.

Authors’ response: The paragraph identified by this reviewer considers the LMBD protein that is the first, and currently only, trans plasma membrane protein specific to the apical annuli that implies that this structure is exposed to the exterior of the cell. It is, therefore, of considerable significance to how we interpret the function and behaviour of these annular structures. We believe that it is very relevant to our study to consider what else is known about these relatively mysterious, but widely conserved, eukaryotic proteins, which is the subject of this paragraph. The other reviewers highlight the relevance of LMBD3 to the interpretation of this structure. This reviewer hasn’t identified any further superfluous discussion elements, and we believe that the current length is not excessive and is justified.

Comment 1.5

Line 184 - Remove question mark from this sentence

Authors’ response: The question mark has been removed.

Comment 1.6

Line 321. Should read Figure 7A, not figure 6A.

Authors’ response: Thank you, corrected.

Comment 1.7

Line 139 - should read Figure 1B instead of 2C

Authors’ response: Thank you, corrected (although to 1C, which is in fact correct).

Comment 1.8

Figure 3- Column labels for early, mid, or late endodyogeny would help with the clarity of this figure, especially for readings who are unfamiliar with the field.

Authors’ response: We have labelled the figure as suggested.

Comment 1.9

Figure S2 - the letter n is missing from knockdown labels. And the number 3 from LMBD 3 is covering the word knockdown in the last panel.

Authors’ response: Thank you, corrected.

Reviewer #1 (Significance (Required)):

The manuscript provides, for the first time, insight into the mechanism of dense granule secretion in Toxoplasma and identifies the sites on parasite pellicle where these vesicles can traverse the IMC to reach the plasma membrane. This is a significant conceptual advance in our understanding of this cellular vital process, one that is required for T. gondii intracellular survival. This paper would have broad interest from other research groups studying parasitology, secretion and protein trafficking.

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

Summary: This manuscript reports on characterizing the function of the long-known apical annuli, which are pores embedded in the membrane skeleton of Toxoplasma gondii. Since their function has remained long elusive, this manuscript is a major breakthrough.

Comment 2.1

It is of note, however, that this breakthrough, using the same three SNAREs, was recently, in parallel, also reported by Fu et al in PLoS Pathogens (PMID 36972314), which work is cited here. The additional novelty here is the finding of LMDB3 in the plasma membrane at the site of the annuli. This is a widely conserved protein for which little function is known except roles in signaling, The connection between LMDB3 and the SNAREs is through BioID, but they are preys quite far down the list. Furthermore, the function of LMDB3 is not explored here. As such, the additional advance compared to the Fu et al report is limited. The function of the SNAREs in dense granule exocytosis is much more robustly done here through the proteomics data displaying an accumulation of DG proteins.

Authors’ response: While it is true that the discovery of the three SNAREs at the apical annuli was made and reported in parallel by Fu et al (2023), a major difference in their conclusions is that they suggest that dense granules are not secreted at this site (this reviewer has mistakenly thought that this was their conclusion — “In our experiments, none of the SNAREs were shown to be related to the exocytosis of GRAs. Therefore, the mechanism that mediates exocytosis of GRAs at the plasma membrane remains to be elucidated.” Fu et al (2023)*). The failure of Fu et al to detect this was almost certainly because they only tested for dense granule secretion defects by inducing depletion of the apical annuli SNAREs after the parasites had invaded the host cells. It is known that dense granule protein secretion happens rapidly in the initial moments after invasion, so apical annuli perturbation in their assay would have only occurred after these secretion events. We directly discuss this experimental difference in our revised discussion and how it accounts for their different conclusions (Discussion, fourth paragraph). We independently tested for this effect by quantitative proteomics which further supported our conclusions. *

As this reviewer indicates, we additionally discovered that a protein (LMBD3) also spans the plasma membrane at these structures, and this implicates signalling or events at the cell surface. We show that this protein is also required for normal dense granule secretion. While we have not identified an explicit mechanistic role for LMBD3 in this process, such insight is also lacking for all LMBD proteins, including those in humans where they are implicated in disease. While we continue to pursue this interesting question of LMBD3 function, we are by no means alone in cell biology for these answers to be outstanding still.

Comment 2.2

The presentation of the data is very clean and convincing, and the broader evolutionary context is well-presented as well. The discussion on whether maintaining the IMC during cell division is an innovation or ancestral is an open debate where the authors seem to come down on the side of innovation, but the evidence could go either way, so I would caution a bit more.

Authors’ response: We are puzzled by this reviewer’s comment because we do not make reference to the maintenance of the IMC during cell division in this evolutionary context — ancestral or a recent innovation. We describe the case of Toxoplasma and its close relatives maintaining the maternal IMC during division as ‘unusual’, not ancestral (second sentence of the last paragraph of the Discussion), and this is the only statement that we think might have elicited this query from the reviewer. But this does not imply what the ancestral state might have been which is not a subject of any of our considerations here.

Major comments: - Are the key conclusions convincing?

Comment 2.3

The identification of the three SNARE proteins through BioID is not very convincingly represented in Table S1. These SNAREs were not showing significant changes and were not detected universally across the three bio-reps, and thyn were also present in the controls. Although this does not diminish the message of the work, this appears to be quite Cherry-picked, while other top hits in the BioID were overlooked, e.g. Nd6 and Nd2 are right in the top ten, which have a demonstrated role in rhoptry exocytosis. This certainly piqued my interest, but is not even discussed.

*Authors’ response: We have used BioID as a protein discovery strategy, not to directly measure protein proximity for which it is an imperfect measure for many technical reasons. Accordingly, discovered ‘candidates’ for proteins that might occur at the annuli were all independently verified by protein reporter tagging. We focused our efforts on discovering apical annuli plasma membrane-tethered proteins and, therefore, parsed our BioID data for those shown previously to be in the plasma membrane by LOPIT spatial proteomics (Barylyuk et al, 2020). It is true that the SNARE proteins were not favoured over many other proteins in the BioID signal, but their verified location at these sites justified our pursuit of them as new apical annuli proteins. *

Other proteins, including the previously identified apical proteins Nd6 and Nd2 that are implicated in rhoptry secretion, similarly piqued our interest! But when we reporter-tagged them they were revealed as BioID false positives, consistent with published work on these proteins, and other ‘top hits’ included some other false positives. Table S1 is included as a further recourse for the field, but it only served as a first step in functional protein discovery in our study.

Comment 2.4

TgAAQa, TgAAQb and TgAAQc were recently also reported to localize to the annuli by Fu et al 2023 (PMID: 36972314; this report is even cited in this manuscript for Rab11a accumulation), who gave them different names: TgStx1, TgStx20, and TgStx21 (not in this order). I see no reason to adopt a new nomenclature here, which will be very confusing in the future literature. Please adopt the Stx names in this manuscript.

*Authors’ response: We agree that where there is precedent in naming it is better to use the earliest used names. Naming of proteins is also best done to reflect orthologues found between species so that consistent names indicate common functions. The naming system proposed by Fu et al for the Qa, Qb and Qc SNAREs unfortunately does not fulfil this second important criterion. They based their names on ‘Syntaxin’ which was first used for an animal SNARE of the nervous system that is almost exclusively used for Qa paralogues. Furthermore, in animals Stx1-4 are all vertebrate-specific Qa paralogues that have arisen only in this group. So, to name the Qa SNARE of Toxoplasma according to one of these animal-specific nerve proteins (Stx1) implies an evolutionary inheritance that is very unlikely (i.e., lateral gene transfer from an animal) and is unsupported by published phylogenies. Furthermore, Fu et al also give the Qb and Qc SNAREs the animal Qa name ‘syntaxin’, and arbitrarily number them Stx21 and Stx20. So, while they have named these proteins first, we think that the names given provide confusing and misleading labels for these proteins. *

We initially proposed a simpler system according to the location of the SNARE in Toxoplasma (AA = Apical Annuli) and the Q domain type (Qa, Qb, Qc), e.g., AAQa. But on reflection we propose using precedent and orthology and adopt the existing orthologue names as the most useful solution. Klinger et al (2022) have resolved the phylogeny of the three Toxoplasma SNAREs, and they group with strong phylogenetic support with known eukaryote-wide orthogroups with previous names: Qa=StxPM (Syntaxin Plasma Membrane); Qb=NPSN (Novel Plant ‘Syntaxin’); and Qc=Syp7 (a Qc SNARE family originally thought to be specific to plants). These SNARE types are all known to operate at the plasma membrane, and accordingly the names TgStxPM, TgNPSN, and TgSyp7 would indicate their orthology and similar functional location known in other eukaryotes. We have justified this preferred naming system in the text of our report (Discussion, third paragraph), but making it clear which Fu et al names correspond to these more universally consistent names so that these can be easily cross-referenced.

Comment 2.5

No knock-down of LMBD3 is pursued: how would this impact SNARE distribution and/or other annuli proteins? The fitness score is very severe, -4.07, so this is somewhat puzzling. Lower comment is related. This could provide tantalizing insights in the architecture of the annuli, and/or their function as a secretory conduit.

LMBD3 relative to the SNAREs is not explored: co-IPs or detergent extraction to see if they are all in a physically interacting complex. What keeps them together. Is LBCDR3 interfacing with any annuli proteins Cen2 is suggested through the image in Fig 2A, though there appears to be some separation in some images: AAP2, 3 and 5 were previously shown to have smaller diameters than Cen2 and therefore appear better positioned.

Authors’ response: LMBD3 knockdowns were pursued in so far as identifying that they also have a phenotype of reduced dense granule secretion as for the SNAREs, but it will indeed require further studies of this intriguing molecule to define its specific function. Our central questions of this study were what is the association of the apical annuli with respect to the IMC and plasma membrane, and what is the overall significance and function of these structures. These core questions have been answered in our study. The questions that this review raises here are further and logical questions specifically related to LMBD3 that we are now pursuing as an independent follow-on study.

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

Comment 2.6

The discussion on whether maintaining the IMC during cell division is an innovation or ancestral is an open debate where the authors seem to come down on the side of innovation, but the evidence could go either way, so I would caution a bit more.

Authors’ response: This comment (2.2) is already made and addressed above.

• 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.

Comment 2.7

The heavy focus on the LMBD3 in Fig 1 and the evolutionary discussion would warrant a more direct functional dissection. Either through an LMDB3 known-down, or its interface with the SNAREs or annuli more directly.

Authors’ response: This reviewer has not made it clear that further work on LMBD3 is necessary to support the conclusions of the paper or address the questions that we have asked, only that they would like to see more insight into LMBD3. We would also! But we do present knock-down studies and show that there are functional consequences for dense granule secretion. The question of if LMBD3 is involved in the maintenance of apical annuli structure and/or integrity is an interesting one, but a further question to those that we have presented in this first study. LMBD proteins have poorly characterised molecular functions throughout eukaryotes, and while we are also motivated to understand their role more, this has not proven a straightforward task in other systems also.

Comment 2.8

The claim that the annuli are the conduits though which the dense granules travel to get exocytosis is not directly supported by any of the experiments as it is solely based on co-localization studies, not even direct interactions.

Authors’ response: We agree that we have not directly observed dense granules in the act of secretion at the apical annuli. Dense granules are known to be very mobile in the cell and traffic dynamically on actin networks. So, they do not accumulate at any one site, and their fusion and exocytosis is likely a rapid, transient event. Multiple lines of evidence for them pausing and fusing with the plasma membrane, while indirect, independently support this conclusion:

• SNARE proteins restricted to the apical annuli in the plasma membrane are required for normal dense granule secretion
• When these SNAREs are depleted dense granule proteins accumulate in the parasite
• Rab11A is a further vesicle-tethering molecule that has been shown to be attached to dense granules and its mutation also leads to inhibition of dense granule proteins (Venugopal et al, 2020)
• When the apical annuli SNAREs are depleted Rab11A accumulates at the annuli (Fu et al, 2023) Collectively, we believe that the claim that the apical annuli are the sites of dense granule secretion is very strongly supported, particularly by the very molecules that would be required for vesicle docking and fusing at these sites, and is justified to be noted in the title. We have, however, made it clear in our report now that these data are indirect and that dense granules are yet to be captured in the act of secreting their contents at these sites (Discussion, paragraph five).

**Referees cross-commenting**

The consolidating themes I see (and value) in the reviews:

Comment 2.9

1. functional follow up of role of LMDB3 Authors’ response: This work is already part of a follow-up project.

Comment 2.10

adopt nomenclature of Fu et al, to avoid confusion in literature

Authors’ response: Please see our response to Comment 2.4

Comment 2.11

better integrate the findings in light of the Fu et al publication throughout this manuscript

*Authors’ response: We have further acknowledged and compared our findings to those of the parallel study of Fu et al with additional text in the discussion. *

Comment 2.12

no direct evidence of dense granules at annuli; attenuate the claims (in title etc), or include supportive data

Authors’ response: Please see our response to the equivalent Comment 2.8 above.

Reviewer #2 (Significance (Required)):

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

Comment 2.13

The presented manuscript reports on a novel protein, LMBD3, embedded in the plasma membrane of Toxoplasma gondii at the site of the apical annuli, which are pores across the inner membrane complex (IMC) skeleton. This provides a novel, putative connection between the cytoplasm and plasma membrane, although this is not directly explored here. Through LMDB3 proximity biotinylation, three SNAREs are identified that were recently reported to be involved in dense granule exocytosis, which is is confirmed here through robust proteomic experiments.

Authors’ response: This reviewer has made an error here in stating that the parallel study of Fu et al implicated the apical annuli SNAREs with dense granule exocytosis. See our response to Comment 2.1 where we describe why the experimental design used for Fu et al was unlikely to test this question effectively.

• Place the work in the context of the existing literature (provide references, where appropriate). The annuli were first reported in 2006, and understanding of their proteomic composition has expanded over the years, however, a function has remained long elusive. This report, together with another parallel performed work, now uses three SNAREs, named TgAAQa, TgAAQb and TgAAQc in this report but previously named TgStx1, TgStx20, and TgStx21 (not in this orthologous order), localizing to the annuli as tool to assign the function of the annuli to exocytosis of the dense granules during intracellular parasite multiplication. The evolutionary context and concepts of the new findings are very well-embedded in the existing literature and insights.

• State what audience might be interested in and influenced by the reported findings. The audience comprises people with a specific interest beyond apicomplexan biology, basically all Alveolates as they all share a similar membrane skeleton. Assigning a putative function to widely conserved LMBD3 will be of high interest to this completely different audience as well.

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

In the submitted work "Apical annuli are specialised sites of post-invasion secretion of dense granules in Toxoplasma", the authors explore the role of the apical annuli in T. gondii. They identify a number of proteins that localize to the membranes at the annuli, including SNARE proteins that are known players in vesicle fusion. They also shown that knockdown of several annuli localized proteins blocks replication and secretion of dense granule cargo into the parasitophorous vacuole. Overall, the work is well done and an important contribution to the field.

Major comments

Comment 3.1

1. In the title and throughout the manuscript the authors claim that the apical annuli are sites of dense granule secretion (e.g. "firmly implicating the apical annuli as the site of dense granule docking and membrane fusion." or "that the apical annuli are sites of vesicle fusion and exocytosis"). However, there does not appear to be direct evidence of the dense granules docking and fusing at these sites.

It would be ideal to see vesicles docked via EM at the annuli, either in wildtype or knockdown parasites. This may not be possible - if not, I recommend toning down the conclusions on docking (or "specialized sites of secretion" as this has not been shown) and instead stating that these structures play a critical role in dense granule secretion. Authors’ response: Please see our response to Comments 2.8 & 2.12, and we have toned down this conclusion as requested to make it clear that direct observations of dense granule fusion are yet to be made. Capturing the transient event of dense granule docking by EM would indeed be a very challenging ambition.

Comment 3.2

The authors should discuss earlier (in the results) the findings of Fu et al. which:

Authors’ response: The parallel study of Fu et al (2023) has indeed generated some similar data, but there are also multiple points of difference including their conclusions. We discuss all of these relevant points in the Discussion, and believe that it would make the Results narrative confusing to introduce this element of discussion there. Our study has not been performed in response to theirs, but rather was conducted in parallel.

• show the localization of some of the same SNAREs at the apical annuli. Fu et al also see localization to the plasma membrane separate from the annuli for some of these proteins. Do you see plasma membrane spots as well upon longer exposures? Can differences be explained by the position or type of tag used?

Authors’ response: Fu et al have indeed used different reporters and expressed the SNARE fusion proteins with different non-native promoters. They used a very bulky reporter which combined 12 HA tags as well as the large Auxin-Inducible Degron (AID), and together it is possible that they observe some mistargeting artefacts. For our location studies we used the small epitope 3xV5 only. We did not see the additional locations that they report, and this may be due to the larger modification that they made to these proteins.

• Fu et al also shows similar plaque defects in the knockdowns and loss of trafficking of plasma membrane proteins to the periphery. In general, the studies from this group are very complementary - they should be better acknowledged.

Authors’ response: We have included more frequent reference and comparison to the Fu et al study now in our Discussion.

• Fu et al see an invasion defect but no defect in GRA secretion - Do you see an invasion defect? These differences should be discussed

Authors’ response: See our response to Comments 2.1 & 2.13 regarding why the Fu et al could not detect the GRA secretion defect. We discuss this in our Discussion now (Discussion paragraph four). We also consider the Fu et al study of an invasion defect as flawed. Both our and their study show that depletion of apical annuli SNAREs has a strong replication phenotype of parasites within the host vacuole. Given induced SNARE depletion must occur during this growing stage of the parasites, to ask if apical annuli could be involved directly in invasion processes requires testing for invasion competence of already very sick cells. It is, therefore, not possible to control for secondary effects on invasion incompetence due to general cell malaise. Furthermore, Fu et al report on invasion efficiency using an assay that relies on SAG1 presentation on the cell surface. However, they conclude independently in their study that SAG1 delivery to the surface is inhibited in their SNARE knockdowns. This further confounds any attempt to reliable measure invasion and any role for these SNAREs in this process. Therefore, for biological as well as technical reasons, we have not tested for a possible role of annuli in invasion.

• It would be helpful for the field to use the same nomenclature whenever possible. Is it possible to use the naming described earlier?

Authors’ response: Please see our response to Comment 2.4.

Comment 3.3

Fig 1C - The authors use trypsin shaving to demonstrate plasma membrane localization of LMBD3. They are probably correct - but it is important to definitively distinguish between plasma membrane and IMC membrane localization. a. The western blot bands for GAP40 should be quantified. It appears that GAP40 is also reduced and it could be reduced to a similar extent as SAG1 without quantification. In addition, this protection from digestion could be confirmed with a second marker in the space between the PM and IMC membranes like GAP45 (whereas cytoplasmic/mito markers like profilin and Tom40 are likely further protected by the IMC membranes and are thus less relevant here).

Authors’ response: Quantitation of Western blots is notoriously inaccurate and, rather, we use it here as a qualitative indication of trypsin sensitivity of proteins in intact cells. The LMBD3 protein is completely transformed within the first time point (1 hour) to stable products of proteolysis of this polytopic membrane protein — presumably to those now protected within the cell. Known GPI-anchored surface protein SAG1 shows similar immediate sensitivity, although it is known that internalised SAG1 pools are constantly recycled to the surface and hence gradual elimination of the residual SAG1 band over 4 hours. The internal protein markers (GAP40, PRF, TOM40) show no discernible change in the first hour and little if any beyond that (within the variation common to Western blotting). GAP40 shares an equivalent polytopic membrane topology to LMBD3 except it occurs in the IMC membrane directly below the plasma membrane, so we think this is the more suitable control. Thus, this trypsin shaving experiment gives a binary output: sensitive or insensitive. This conclusion is further supported by the published spatial proteomics study (Barylyuk et al. 2020) which shows that LMBD3 segregates with other integral membrane proteins specific to the plasma membrane and not with the IMC proteins. Our super resolution imaging of LMBD3 relative to inner membrane complex markers (Centrin2, GAP45, IMC1) also show it as peripheral to them, further corroborating the plasma membrane location.

1. Is it possible to N-terminally tag LMBD3 and then examine plasma membrane localization by detection of the tag without permeabilization? (this would also confirm the proposed topology) Authors’ response: We have tried to N-terminally tag LMBD3 with an epitope reporter but this integration was not tolerated by the cell, presumable because it interferes with membrane insertion of this protein that is essential for cell viability. So, this experimental option is not available.

Comment 3.4

I think it is important to make clear for the reader what is happening here. The paper sounds as though the dense granules directly dock at the annuli for release. It also seems possible from this work and Fu et al that secretion at the annuli occurs via small vesicles that originate from the dense granules. Perhaps a diagram or model would help the reader here (and discuss why DGs or other vesicles are not routinely seen at the annuli if this is the critical portal - and perhaps why the organelles are not clustered in the apical end of the cell if this is where they are needed)

Authors’ response: This comment is related to that of review 2 (Comments 2.8/12), although we note again that Fu et al did not conclude that dense granules are exocytosed at this site. It is also unclear why this reviewer envisages that small vesicles arise from the dense granules, rather than the dense granule itself fusing at the annuli to the plasma membrane. Indeed, the occurrence of Rab11A on the dense granules, and the accumulation of this protein at the annuli with SNARE knockdown, supports that it is the dense granules that dock at this site. Why dense granules don’t otherwise cluster at their sites of secretion but are instead motile in the cell, their movement driven by Myosin F on actin filaments, is not known. Perhaps these otherwise bulky organelles would create too much cellular crowding that could interfere with other processes. We have addressed all of these points in additions to the discussion so that these interesting unknowns are transparent to the reader (Discussion paragraph 5).

Comment 3.5

Figure 5. The authors state the knockdown results in "strong phenotypes of reduced plaque development" - The plaque assays should be quantified.

• Are there no plaques or just very small ones here?

Authors’ response: The reviewer provides no rationale for this request or states what questions could be addressed by doing so. Indeed, none of our conclusions would be affected. We use the plaque assays to test whether each of the proteins tested are independently necessary for some facet of normal parasite growth where the result is binary — no difference in plaque size versus near or complete absence of plaque development. The interpretation of differing plaque sizes between different knockdown mutations is a very inexact science with assumptions of equal rates of protein depletion, sensitivity of relative protein abundance, modes of action of mutation, and kinetics of plaque growth very difficult to validate for meaningful comparisons to be made. Therefore, we don’t see any useful role for plaque quantification in the research questions that we’ve addressed or the conclusions that we present.

Comment 3.6

Figure 6 a. Fig 6A - The use of digitonin for semipermeabilization requires controls as there is typically a lot of variability across the monolayer. This is ideally done with something to show that the host plasma membrane has been permeabilized (e.g. host tubulin) and the PVM has not been permeabilized (e.g. SAG1). Otherwise, perhaps the authors could state what percent of cells showed the data like the representative images shown or describe further how selective permeabilization was assessed? (or wider fields with many cells and vacuoles?)

*Authors’ response: As requested, we have included a supplemental figure showing wider fields of view where multiple vacuoles are seen. These data show that the vacuoles are similarly stained with no evidence of variability of digitonin permeabilization. The reduction in GRA5 secretion shown by microscopy is further supported by this protein being quantified using proteomics as enriched in the parasites when the apical annuli proteins are depleted (Fig 7). *

Comment 3.7

1. Fig 6B - "the GRA signal seen within the parasite was increased compared to the control" This is not clear from the AAQb image shown as it appears more is also present in the vacuole (or perhaps residual body?) Can this be clarified? Authors’ response: Yes, in this image it appears that the ‘residual body’, which is also an integral internal compartment of the growing parasite rosette, is a site of dense granule accumulation. We have modified the text to make it clear that the observations of IFA images showing ‘apparent’ increase in dense granule staining were then directly tested by quantitative proteomics. These subsequent data (Fig 7) provided a clear measure of the increase in dense granule proteins in the parasites when apical annuli function was perturbed.

Minor comments

Comment 3.8

1. Line 215-217 The authors state that "Collectively these data imply that the apical annuli provide coordinated gaps in the IMC barrier that forms at the earliest point of IMC development and that they maintain access of the cytosol to these specialised locations in the plasma membrane."
2. However, their data shows that LMBD3 only recruits once daughters are emerging (not earliest point of IMC development). Please clarify? Is this just referring to Centrin2 or LMBD3 as well? Authors’ response: Yes, the other AAPs indicate that these structures form early, and they were mentioned as such in the sentences preceding this statement — hence ‘collectively’.

Comment 3.9

Fig 5. Regarding growth arrest. AAQa appears to show an arrest but is it possible the others just grow slower? Do they arrest later and hence fail to form a plaque? Is there incomplete knockdown which enables a few parasites to persist?

*Authors’ response: It is true that it is difficult to discern complete growth arrest from *

*very retarded growth. However, neither alternative would affect our conclusions where we use these phenotypes as an indication of apical annuli participating in process required for normal growth. All plaque assays show strong growth phenotypes. Nevertheless, we have removed the use of the term ‘growth arrest’ with respect to these phenotypes (including in the Abstract) and replaced it with growth impairment. *

Comment 3.10

Line 132, Fig 1 A-C. For clarity it may be better for the reader if LMBD3 is named earlier, or if Fig 1 refers to the gene ID for panels A-C before its named.

Authors’ response: This is a good idea and we have made this change, making note of the rationale for this name when we present the phylogeny.

Comment 3.11

Line 30 - "represent a second structure in the IMC specialised for protein secretion" this is confusing - do the authors mean in addition to the micronemes/rhoptries at the apical complex? Maybe "a second structure in the parasite" would be clearer

Authors’ response: To clarify we have reworded as follows: ‘The apical annuli, therefore, represent a second type of IMC-embedded structure to the apical complex that is specialised for protein secretion’

Comment 3.12

Line 440 - the author states that "these pre- and post-invasion secretion processes are also biochemically separated because both microneme and rhoptry secretion are SNARE-independent" Is this from the Cova and Dubios papers cited a line later? I took a quick scan of these papers and neither appear to show this? Cova claims still this is still unclear and Dubios says SNAREs are likely involved?

Authors’ response: While both microneme and rhoptry secretion use distinctive molecular machineries for controlling membrane fusion for exocytosis, it is true that it is not formally known that these processes completely lack SNARE involvement, and neither paper cited here can eliminate this possibility. We have therefore, removed this short part of the discussion where we consider that dense granules might be unique amongst these three compartments in relying on SNAREs.

Text editing

Comment 3.13

1. Line 94 - plasma membrane or cell surface. Clarify here - do you mean plasma membrane or under the membrane at the periphery? Authors’ response: We have modified as: ‘plasma membrane including the cell surface’.

Comment 3.14

Line 321 refers to Fig 6A but should say 7A. Panel 7B is never referenced in the text.

Authors’ response: Thank you, we have corrected this and only sited Fig7 because A and B are both relevant to the statement made in the text.

Comment 3.15

Line 347-242 and fig 4A - the discussion of Q-SNARES and diagram could use some references for the reader

Authors’ response: Thank you for this suggestion, we have acted on this request.

Comment 3.16

The methods says plaque assays were 7 days, fig 5 legend says 8 days

Authors’ response: Thank you, this is corrected as 8 days.

**Referees cross-commenting**

• I completely agree with Rev 2
• I also think examining invasion given Rev1 comment on the micronemes and the data from Fu et al would be worthwhile and straightforward to do

Authors’ response: Please see our response to Comment 3.2 where the validity of measuring invasion competence of poorly growing, and/or arrested, parasites is scientifically questionable. It would require controls of similarly unhealthy parasites where the apical annuli are unaffected, but it is difficult to imagine how one would deliver such a control.

Reviewer #3 (Significance (Required)):

This is an excellent study that assesses the role of apical annuli in parasite secretion. It is an important addition to the field (and outstanding imaging that provides a high level of detail to the study). The study could be improved by better integrating a recent similar study noted by the authors and in the review

Authors’ response: We have provided more direct discussion of the Fu et al paper in our Discussion section.

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Referee #3

Evidence, reproducibility and clarity

In the submitted work "Apical annuli are specialised sites of post-invasion secretion of dense granules in Toxoplasma", the authors explore the role of the apical annuli in T. gondii. They identify a number of proteins that localize to the membranes at the annuli, including SNARE proteins that are known players in vesicle fusion. They also shown that knockdown of several annuli localized proteins blocks replication and secretion of dense granule cargo into the parasitophorous vacuole. Overall, the work is well done and an important contribution to the field.

Major comments

1. In the title and throughout the manuscript the authors claim that the apical annuli are sites of dense granule secretion (e.g. "firmly implicating the apical annuli as the site of dense granule docking and membrane fusion." or "that the apical annuli are sites of vesicle fusion and exocytosis"). However, there does not appear to be direct evidence of the dense granules docking and fusing at these sites.

It would be ideal to see vesicles docked via EM at the annuli, either in wildtype or knockdown parasites. This may not be possible - if not, I recommend toning down the conclusions on docking (or "specialized sites of secretion" as this has not been shown) and instead stating that these structures play a critical role in dense granule secretion.<br /> 2. The authors should discuss earlier (in the results) the findings of Fu et al. which: - show the localization of some of the same SNAREs at the apical annuli. Fu et al also see localization to the plasma membrane separate from the annuli for some of these proteins. Do you see plasma membrane spots as well upon longer exposures? Can differences be explained by the position or type of tag used? - Fu et al also shows similar plaque defects in the knockdowns and loss of trafficking of plasma membrane proteins to the periphery. In general, the studies from this group are very complementary - they should be better acknowledged. - Fu et al see an invasion defect but no defect in GRA secretion - Do you see an invasion defect? These differences should be discussed - It would be helpful for the field to use the same nomenclature whenever possible. Is it possible to use the naming described earlier? 3. Fig 1C - The authors use trypsin shaving to demonstrate plasma membrane localization of LMBD3. They are probably correct - but it is important to definitively distinguish between plasma membrane and IMC membrane localization. - a. The western blot bands for GAP40 should be quantified. It appears that GAP40 is also reduced and it could be reduced to a similar extent as SAG1 without quantification. In addition, this protection from digestion could be confirmed with a second marker in the space between the PM and IMC membranes like GAP45 (whereas cytoplasmic/mito markers like profilin and Tom40 are likely further protected by the IMC membranes and are thus less relevant here). - b. Is it possible to N-terminally tag LMBD3 and then examine plasma membrane localization by detection of the tag without permeabilization? (this would also confirm the proposed topology) 4. I think it is important to make clear for the reader what is happening here. The paper sounds as though the dense granules directly dock at the annuli for release. It also seems possible from this work and Fu et al that secretion at the annuli occurs via small vesicles that originate from the dense granules. Perhaps a diagram or model would help the reader here (and discuss why DGs or other vesicles are not routinely seen at the annuli if this is the critical portal - and perhaps why the organelles are not clustered in the apical end of the cell if this is where they are needed) 5. Figure 5. The authors state the knockdown results in "strong phenotypes of reduced plaque development" - The plaque assays should be quantified. - Are there no plaques or just very small ones here? 6. Figure 6

a. Fig 6A - The use of digitonin for semipermeabilization requires controls as there is typically a lot of variability across the monolayer. This is ideally done with something to show that the host plasma membrane has been permeabilized (e.g. host tubulin) and the PVM has not been permeabilized (e.g. SAG1). Otherwise, perhaps the authors could state what percent of cells showed the data like the representative images shown or describe further how selective permeabilization was assessed? (or wider fields with many cells and vacuoles?)

b. Fig 6B - "the GRA signal seen within the parasite was increased compared to the control" This is not clear from the AAQb image shown as it appears more is also present in the vacuole (or perhaps residual body?) Can this be clarified?

Minor comments

1. Line 215-217 The authors state that "Collectively these data imply that the apical annuli provide coordinated gaps in the IMC barrier that forms at the earliest point of IMC development and that they maintain access of the cytosol to these specialised locations in the plasma membrane."
2. However, their data shows that LMBD3 only recruits once daughters are emerging (not earliest point of IMC development). Please clarify? Is this just referring to Centrin2 or LMBD3 as well?
3. Fig 5. Regarding growth arrest. AAQa appears to show an arrest but is it possible the others just grow slower? Do they arrest later and hence fail to form a plaque? Is there incomplete knockdown which enables a few parasites to persist?
4. Line 132, Fig 1 A-C. For clarity it may be better for the reader if LMBD3 is named earlier, or if Fig 1 refers to the gene ID for panels A-C before its named.
5. Line 30 - "represent a second structure in the IMC specialised for protein secretion" this is confusing - do the authors mean in addition to the micronemes/rhoptries at the apical complex? Maybe "a second structure in the parasite" would be clearer
6. Line 440 - the author states that "these pre- and post-invasion secretion processes are also biochemically separated because both microneme and rhoptry secretion are SNARE-independent" Is this from the Cova and Dubios papers cited a line later? I took a quick scan of these papers and neither appear to show this? Cova claims still this is still unclear and Dubios says SNAREs are likely involved?

Text editing

1. Line 94 - plasma membrane or cell surface. Clarify here - do you mean plasma membrane or under the membrane at the periphery?
2. Line 321 refers to Fig 6A but should say 7A. Panel 7B is never referenced in the text.
3. Line 347-242 and fig 4A - the discussion of Q-SNARES and diagram could use some references for the reader
4. The methods says plaque assays were 7 days, fig 5 legend says 8 days

Referees cross-commenting

• I completely agree with Rev 2
• I also think examining invasion given Rev1 comment on the micronemes and the data from Fu et al would be worthwhile and straightforward to do

Significance

This is an excellent study that assesses the role of apical annuli in parasite secretion. It is an important addition to the field (and outstanding imaging that provides a high level of detail to the study). The study could be improved by better integrating a recent similar study noted by the authors and in the review

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Referee #2

Evidence, reproducibility and clarity

Summary:

This manuscript reports on characterizing the function of the long-known apical annuli, which are pores embedded in the membrane skeleton of Toxoplasma gondii. Since their function has remained long elusive, this manuscript is a major breakthrough. It is of note, however, that this breakthrough, using the same three SNAREs, was recently, in parallel, also reported by Fu et al in PLoS Pathogens (PMID 36972314), which work is cited here. The additional novelty here is the finding of LMDB3 in the plasma membrane at the site of the annuli. This is a widely conserved protein for which little function is known except roles in signaling, The connection between LMDB3 and the SNAREs is through BioID, but they are preys quite far down the list. Furthermore, the function of LMDB3 is not explored here. As such, the additional advance compared to the Fu et al report is limited. The function of the SNAREs in dense granule exocytosis is much more robustly done here through the proteomics data displaying an accumulation of DG proteins. The presentation of the data is very clean and convincing, and the broader evolutionary context is well-presented as well. The discussion on whether maintaining the IMC during cell division is an innovation or ancestral is an open debate where the authors seem to come down on the side of innovation, but the evidence could go either way, so I would caution a bit more.

Major comments:

• Are the key conclusions convincing?

The identification of the three SNARE proteins through BioID is not very convincingly represented in Table S1. These SNAREs were not showing significant changes and were not detected universally across the three bio-reps, and thyn were also present in the controls. Although this does not diminish the message of the work, this appears to be quite Cherry-picked, while other top hits in the BioID were overlooked, e.g. Nd6 and Nd2 are right in the top ten, which have a demonstrated role in rhoptry exocytosis. This certainly piqued my interest, but is not even discussed.

TgAAQa, TgAAQb and TgAAQc were recently also reported to localize to the annuli by Fu et al 2023 (PMID: 36972314; this report is even cited in this manuscript for Rab11a accumulation), who gave them different names: TgStx1, TgStx20, and TgStx21 (not in this order). I see no reason to adopt a new nomenclature here, which will be very confusing in the future literature. Please adopt the Stx names in this manuscript.

No knock-down of LMBD3 is pursued: how would this impact SNARE distribution and/or other annuli proteins? The fitness score is very severe, -4.07, so this is somewhat puzzling. Lower comment is related. This could provide tantalizing insights in the architecture of the annuli, and/or their function as a secretory conduit.

LMBD3 relative to the SNAREs is not explored: co-IPs or detergent extraction to see if they are all in a physically interacting complex. What keeps them together. Is LBCDR3 interfacing with any annuli proteins Cen2 is suggested through the image in Fig 2A, though there appears to be some separation in some images: AAP2, 3 and 5 were previously shown to have smaller diameters than Cen2 and therefore appear better positioned. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The discussion on whether maintaining the IMC during cell division is an innovation or ancestral is an open debate where the authors seem to come down on the side of innovation, but the evidence could go either way, so I would caution a bit more. - 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.

The heavy focus on the LMBD3 in Fig 1 and the evolutionary discussion would warrant a more direct functional dissection. Either through an LMDB3 known-down, or its interface with the SNAREs or annuli more directly. The claim that the annuli are the conduits though which the dense granules travel to get exocytosis is not directly supported by any of the experiments as it is solely based on co-localization studies, not even direct interactions.

Referees cross-commenting

The consolidating themes I see (and value) in the reviews: 1. functional follow up of role of LMDB3 2. adopt nomenclature of Fu et al, to avoid confusion in literature 3. better integrate the findings in light of the Fu et al publication throughout this manuscript 4. no direct evidence of dense granules at annuli; attenuate the claims (in title etc), or include supportive data

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

The presented manuscript reports on a novel protein, LMBD3, embedded in the plasma membrane of Toxoplasma gondii at the site of the apical annuli, which are pores across the inner membrane complex (IMC) skeleton. This provides a novel, putative connection between the cytoplasm and plasma membrane, although this is not directly explored here. Through LMDB3 proximity biotinylation, three SNAREs are identified that were recently reported to be involved in dense granule exocytosis, which is is confirmed here through robust proteomic experiments. - Place the work in the context of the existing literature (provide references, where appropriate).

The annuli were first reported in 2006, and understanding of their proteomic composition has expanded over the years, however, a function has remained long elusive. This report, together with another parallel performed work, now uses three SNAREs, named TgAAQa, TgAAQb and TgAAQc in this report but previously named TgStx1, TgStx20, and TgStx21 (not in this orthologous order), localizing to the annuli as tool to assign the function of the annuli to exocytosis of the dense granules during intracellular parasite multiplication. The evolutionary context and concepts of the new findings are very well-embedded in the existing literature and insights. - State what audience might be interested in and influenced by the reported findings.

The audience comprises people with a specific interest beyond apicomplexan biology, basically all Alveolates as they all share a similar membrane skeleton. Assigning a putative function to widely conserved LMBD3 will be of high interest to this completely different audience as well.

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Referee #1

Evidence, reproducibility and clarity

Summary

Toxoplasma gondii is an obligate intracellular parasite. Intracellular survival critical depends on secretory vesicles named dense granules. These vesicles are predicted to contain >100 different proteins that are released into PV, PV membrane and the host cell to control the parasites intracellular environment and host cell gene expression and immune response. How and where these vesicles are released from the parasite is a long-standing question in the field because T. gondii, and other apicomplexan parasites contained a complex pellicular cytoskeletal structure called the IMC which limits dense granule access to the plasma membrane. In this manuscript by Chelaghma, Ke and colleagues demonstrates for the first time that dense granules are secreted from the parasite at pore structures called the apical annuli. The authors used their previously generated HyperLOPIT data set and identified a plasma membrane protein that is specifically enriched at the apical annuli. Using BioID the authors then identify three SNARE proteins that also localize at the apical annuli. The localization of these proteins is determined using excellent super-resolution structured illumination microscopy. Conditional protein knockdowns for all four proteins were created and both proteomics and microscopy used to demonstrate a reduction in dense granule secretion in the absence of these proteins. Collectively, these data make new and substantial contributions to our understanding of mechanisms of dense granule secretion.

Major comments:

Overall, these data is convincing and well-described. The text is clear and well written. There are a few instances (see below) where the authors doesn't adequately describe the data or over state the strength of the results. These issues could all be addressed editorially or by process existing data.

The authors use proteomics and IFA to show that there is a reduction (rather than an inhibition of) in dense granule secretion. However, from the phase images in figure 5, the vacuoles of KD parasites look normal and so not have the phenotypes that one would expect after a significant reduction in dense granule secretion, such as the "bubble" phenotype described for GRA17 and GRA23 knockouts (Gold et al 2015; PMID: 25974303). Authors should describe their findings in the context of the expected phenotypes based on the published literature. The statement on line 369-371 is too strong and should imply a reduction rather than an inhibition of dense granule secretion.

The more severe phenotype observed in the AAQa iKD and the additional localizations of AAQa and AAQc suggests an additional role for these protein in protein trafficking that is supported by the authors data. In both AAQa and AAQc there appears to be an accumulation of GRA1 in a post-Golgi compartment and is less vesicular in appearance than the phenotype observed in the AAQb iKD parasites. Additionally, I disagree with the authors assessment that KD of these proteins does not effect microneme localization. In both AAQa and AAQc there appears to be increased number of micronemes at the basal end of the parasites compared with controls. Although this is not a direct focus of the authors papers, a description of these findings should be included in the results and discussion sections.

Presentation of the data in Figure 5. This figure contains images where the fluorescent dense granule signal is overlaid on phase images. However, in some cases (AAQb, AAQc, AAQa, GRA1 KD) the merged imaged looks like a straight merges of the two images, whereas in the rest of the images it looks like a thresholded fluorescent image is merge with phase. Authors need to process the images in consistent manner and provide a description of the image processing in the figure legend and materials and methods.

Minor comments:

The discussion is overly long and could be shorted in some places. Lines 373 and 388 in particularly don't seems directly relevant to the manuscript.

Line 184 - Remove question mark from this sentence

Line 321. Should read Figure 7A, not figure 6A.

Line 139 - should read Figure 1B instead of 2C

Figure 3- Column labels for early, mid, or late endodyogeny would help with the clarity of this figure, especially for readings who are unfamiliar with the field.

Figure S2 - the letter n is missing from knockdown labels. And the number 3 from LMBD 3 is covering the word knockdown in the last panel.

Significance

The manuscript provides, for the first time, insight into the mechanism of dense granule secretion in Toxoplasma and identifies the sites on parasite pellicle where these vesicles can traverse the IMC to reach the plasma membrane. This is a significant conceptual advance in our understanding of this cellular vital process, one that is required for T. gondii intracellular survival. This paper would have broad interest from other research groups studying parasitology, secretion and protein trafficking.

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Reply to the reviewers

We thank the reviewers for their critiques of our manuscript and for recognizing the importance of the questions about 3D genome organisation that it addresses. We plan to address most of their comments in our revised manuscript.

Reviewer #1

1. The aneuploid karyotype of the MCF-7 cells used is a concern. GREB1 is present in four copies, with two on abnormal chromosomes which may not be regulated in the same way as primary cells. The authors should include caveats to this effect in the text to account for this.

We indicated (pg 5) that there are 4 copies of GREB1, 2 of which are on re-arranged chromosomes. RNA FISH (Figure 1C) suggests all 4 of these alleles are induced by estrogen. On each allele, the GREB1 enhancer and promoter remain closely apposed by imaging (Figure 2, DNA FISH) indicating no gross chromosomal rearrangements around the GREB1 locus. This is confirmed by our Hi-C data (Figure 2A), where any genomic rearrangements at the GREB1 locus would be detectable when the sequencing data were aligned to the reference genome. In the revised manuscript we highlight these points in the respective results sections (pgs 5 and 6). Our data suggest that all 4 alleles of GREB1 in MCF7 cells are regulated in the same way.

2. The authors should also include more information on the generation and verification of the enhancer deletion cell lines. An illustration of the PCR primers used for screening, as well as an illustration of the sequenced product traces aligned with the reference genome (as opposed to just showing the deleted regions) should be included in Fig. S1D. This would give the reader more confidence that the designed knockout has occurred in the same way on all alleles. Furthermore, long-range PCRs and sequencing should be considered to confirm that no larger deletions have occurred (e.g. Owens et al., 2019 PMID: 31127293).

We have replaced FigS1D with a new Figure Supplement (Figure S1.2A) that incorporates a more comprehensive diagram of the strategy used for the generation and screening of the enhancer deletion cell lines. This also includes the sequencing traces aligned to the reference genome for each of the clones used in this work. Additionally, in the revised manuscript, we will check the deletions using the C-TALE sequencing data obtained from the enhancer-deleted clones.

1. The changes in the measured E-P interaction frequency following gene activation are __weak __at best and make visual interpretation of the results difficult. Showing the reciprocal virtual 4C plots from the promoter would help to reassure the reader that the observed effect is real.

We thank the reviewer for this suggestion, and we will now include virtual 4C plots from the GREB1 and NRIP1promoters in our revised manuscript. These will be in figures 2B, 2E, 3C, 4C and in the supplementary figures 2B, 4B, 5C and 6C.

4. Furthermore, the precise 3C method used is not clear. The authors repeatedly refer to "Capture-C" (a commonly used 3C-based approach using biotinylated oligos to pull down targets of interest) but the citation used (Golov et al. 2019) refers to a conceptually similar method called "C-TALE". This should be clarified in the text.

We thank the reviewer for pointing out this potential confusion. We replace the term Capture-C with C-TALE throughout the revised manuscript.

5. As for the changes in contact frequency, the observed changes in distance measurements between conditions are very small (although statistically significant). We acknowledge that this is likely due to the relatively small linear distances between enhancers and promoters in this study. However, it would be helpful to see the effects of the induction/treatments on a one or more control loci which is not affected by oestrogen signalling given that global changes in nuclear shape/volume and/or cell cycle effects could occur within this time (e.g. effects of tamoxifen treatment on MCF-7 cell cycle distribution, (Osborne et al. 1983 PMID: 6861130), which could impact nuclear volume.

Data from DNA FISH control probes are already included in Supplementary Figure S3 showing no change in intra-nuclear distances and thus no general effects on chromatin compaction due to nuclear volume or cell cycle. Virtual 4C data for the entire captured regions around GREB1and NRIP1 are show in Fig S2C, also showing no general effect on the wider capture windows. We will include similar data from the viewpoint of the gene promoters in the revised manuscript. Hi-C and imaging data from the enhancer deletion cell lines (Fig S4) also supports that we are looking at an ER-specific effect, not a global one. With the regard to the comment on the effects of tamoxifen treatment on MCF-7 cell cycle distribution, we see no effects of tamoxifen on 3D genome organisation at GREB1 and NRIP1 by Hi-C or by imaging.

6. The authors discuss previous studies demonstrating that E2 and 4OH recruit different sets of proteins to their target genes. Given that this is central to the conclusion that the ER ligand (and its recruited co-factors) determines the E-P interaction frequency and 3D distances observed, it would be important to demonstrate this at the GREB1/NRIP1 loci specifically. ChIP data of the co-activators/repressors recruited by E2 and 4OH, respectively, would greatly strengthen this claim.

We acknowledge that investigating co-activator and co-repressor recruitment to the studied loci will strengthen our interpretation our conclusions. In the revision we will perform and include ChIP-qPCR at NRIP1, GREB1 and control loci assaying for PolII, co-activators such as p300, mediator and SRC-3 and the co-repressors N-CoR in control, estradiol and tamoxifen treated cells. We will also perform ChIP-qPCR of PolII and co-activators in cell treated with flavopiridol and triptolide.

1. The observed uncoupling of E-P contact frequency and 3D distance upon transcriptional inhibition is interesting and offers clues to the molecular details underlying E-P interactions. However, the use of flavopiridol and triptolide, while common in the field, should be carefully qualified given the potential for their indirect effects on transcription. This is particularly important for flavopiridol given its ability to target multiple cyclin-dependent kinases beyond CDK9 and its role in transcription initiation.

In the revised manuscript we indicate that “Flavopiridol inhibits several CDKs, including CDK9/PTEF-b”

Minor comments:

i. In the introduction and beginning of discussion, it would be helpful to detail previous studies where FISH-based analyses have shown more proximal E-P positioning upon activation, to make it clear that differences in E-P proximity appear to be gene-specific. Some examples include Williamson et al. (2016; PMID 27402708) and Chen et al. (2018; PMID 30038397). Speculation as to why some genes behave in this way while others do not, would also be worthwhile.

We have followed the reviewer’s suggestion and noted these two studies in the Introduction of a revised manuscript. Given that the focus of this current manuscript is to explore discrepancies between Hi-C and DNA FISH, we do not think that this is the right forum for a wider discussion of why there might be differences in E-P proximity between different biological systems.

ii. On page 6, the authors state that after deletion of the NRIP1 enhancer there is "almost total loss of NRIP1 induction in response to E2". This does not seem to match the data where in 3 out of 4 replicates (2 for each clone) there is a statistically significant increase in number of RNA FISH foci upon E2 stimulation in the NRIP1 enhancer KOs. This suggests that, as for GREB1, the regulation of these genes is not solely controlled by the deleted enhancers. This should be clarified in the text.

The reviewer is referring to the data on NRIP1 expression in two NRIP1 enhancer deletion clones in Fig 1D and the replicate data in Supplementary Fig S1 (upper-right panel). These data show almost no induction of NRIP12 by E2 compared to wild-type cells. We stand by our statement.

iii. The labelling of the FISH probes in Supp. Fig. S2 could be improved as it is currently very difficult to read these.

We will try to improve this in a revised Figure S2.

iv Given that the authors have referenced a distance of 200 nm as potentially being an important threshold for gene activation, it would be useful to include the fraction of alleles which are below this distance alongside the cumulative frequency plots in Figure 2D and elsewhere in the paper as the cumulative frequency plots can be hard to read in some cases (e.g. Supp. Fig. S3B e-p). This would also allow the authors to show consistency across replicates.

We thank the reviewer for this suggestion to make the data easier to interpret. In a revised manuscript, we will incorporate the fraction of alleles below and above 200 nm for the DNA-FISH experiments in Figure 2D and Figure S4A-B.

v. For clarity, it would be helpful to include the difference map between the vehicle-treated unstimulated/stimulated conditions for the 3C plots in Fig. 4. This would help contextualise the resulting differences observed with the drug treatments. Same for Supp. Fig. S6.

We will include the difference heatmap between the vehicle- and estradiol treated samples for vehicle, flavopiridol and triptolide treated samples.

vi. Statistical comparisons are not shown for all 3D FISH-based distance measurements (e.g. Supp. Figs. S3A, S4C, D, S6E). If this is because the tests were done and the results were non-significant this should be indicated.

We had omitted all non-significant p values (>0.05) from the graphs to stop them getting too cluttered. All p values are documented in the supplementary tables. However, following the reviewer’s comment, we will indicate all non-significant statistical comparisons on the graphs.

vii. On page 13, the authors state that increased E-P separation occurs "before nascent transcription of the gene is detected by either TT-seq or RNA FISH". This does not appear to be correct given that baseline levels of transcription are observed in the absence of ER stimulation by both methods (Fig. 1). This should be clarified in the text.

We have amended this statement to now indicate that “This is before an induction of nascent transcription of the gene….”

Reviewer #2

1. The authors make strong claims and although these are generally reasonably well supported by the data, it is important to acknowledge that they are based on two loci. This manuscript would be stronger if the authors could include additional loci in their study design. If this is not possible, it would be good to acknowledge that the conclusions are preliminary/speculative at this stage.

The reviewer makes a fair point, and we emphasized throughout the text – including at the end of the Discussion - that we are examining just two gene loci. In a revised manuscript we will include DNA-FISH data for a third locus comprising the CCND1 gene, for which we have preliminary data.

*2. It would be helpful if the authors could clarify the strategy they used for their FISH probe design. The enhancer and promoter fosmid probes (which are used for the majority of the experiments) are not centered on the active elements and do not even seem to overlap in the case of the GREB1 enhancer fosmid probe. The 10 kb enhancer probe seems better placed for the GREB1 locus, but the 10 kb enhancer probe does not seem to overlap with the enhancer in the NRIP1 locus. It is conceivable that the exact location of the probes has a big impact on the measurements and it would therefore be helpful if the authors could comment on the location of the probes and add additional probes if required to strengthen their conclusions. In addition, the fosmid probes are very large (40 kb). Although the authors acknowledge this, it would be helpful if they could comment on how overlap between 40 kb probes should be interpreted in relation to a potential rather focal contact between (proteins bound to) regions of In the case of GREB1, the fosmid probes were chosen to maximize the distance between them as the promoter and the enhancer of the gene are genomically relatively close to each other. This was not an issue in the case of the NRIP1 locus where fosmid probes could be placed centered on the TSS and the enhancer region. In the case of the 10 kb probes, these were designed to be centered on the regions where higher E2-induced C-TALE contact frequencies were detected. Virtual 4C plots using the TSS regions as viewpoints (incorporated into the revised manuscript) clearly show that, in the case of NRIP1, the contact frequency peak does not fall on the main ER peak.

1. It is not clear to me why the authors would choose to work with a locus that is present in 4 copies in their cell line. Is the entire regulatory region (incl. enhancers) preserved for the two additional copies of the gene? Can the authors comment on how this may impact on their measurements?

See response to Reviewer 1, point 1. Our Hi-C data would have revealed if there were genomic rearrangements in the 600kb window surrounding GREB1.

4. Figure 2D shows an increase in E-P separation for the NRIP1 locus across all timepoints, with cumulative frequency plots shown for the 10 min timepoint. However, the data for the second replicate shown in Figure S2D are a lot less robust and not significant for the 10 min timepoint. It is important that the authors either provide additional data to support the robustness of this experiment or acknowledge that the results are not fully reproducible.

We acknowledge this, but we would like to note that there is an increase in the median distance for all time points, although this difference is not significant in some of the timepoints. Additionally, DNA-FISH data obtained using the 10 kb probes confirm these observations.

5. The data presented in Figure 2F for clone 2 of the GREB1 enhancer deletion still show increased E-P distance upon activation. How do the authors explain this?

This increase in distance is not statistically significant (p-0.33 – see Table S2) and is not seen for the replicate data in Fig. S4.

Minor comments:

i. Could the authors comment on the observation that the NRIP1 promoter is not bound by ERa or p300 upon estrogen activation? Are there ATAC-seq or H3K27ac ChIP-seq data available for these conditions?

We included ATAC-seq tracks in Figure 1A where a peak on the NRIP1 promoter is clearly seen.

ii. It is not obvious which timepoint is shown in Figure 1D.

Pre-mRNA FISH in enhancer deleted clones was done in cells treated with vehicle or E2 for 60 minutes. This will be made clearer in the figure legend.

iii. Why did the authors choose e-i and p-i instead of e-c and p-c in Supplementary Figure 3B?

We apologize as it was an oversight not to include the e-c data for this experiment. This is now included in Supplementary figure S4B.

iv. "We treated hormone starved MCF-7 cells with flavopiridol or triptolide for 5 min before adding E2 for 30 min (Fig. 4A)." Does this mean that the FLV/TRP treatment lasted for 35 min or did the authors wash it out before adding E2? Please clarify.

This observation is correct, and it was made clear in Figure 4A and in the figure legend.

v. The authors refer to their Capture-C data as "high-resolution". However, the methods section mentions that the data for the GREB1 and NRIP1 locus are 5 kb and 10 kb resolution, respectively. This is not particularly high for a targeted approach, certainly not in light of the MNase-based approaches that have recently been developed. I therefore think that the "high-resolution" claims should be removed from the paper.

In line with the reviewer’s suggestion, we have removed the term high-resolution when referring from our own data.

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Referee #2

Evidence, reproducibility and clarity

In this manuscript, Gómez Acuña and colleagues have investigated changes in enhancer-promoter (E-P) interactions with both 3C and DNA FISH. As a model system, they have used the activation of estrogen receptor-dependent enhancers, which allows for examination of changes in E-P interactions at relatively high temporal resolution. Surprisingly, they find that gene activation is associated with increased E-P interactions as measured by 3C but reduced spatial proximity as measured by DNA FISH. The authors show that both these measurements are dependent on the presence of the enhancer. In contrast, blocking transcription with inhibitors does not have a strong effect on the 3C measurements, but abolishes the increased spatial E-P separation as measured by DNA FISH following estrogen induction.

Overall, this is an interesting and thought-provoking study. However, the strong conclusions are not fully supported by the data, as explained in further detail below.

Major comments:

• The authors make strong claims and although these are generally reasonably well supported by the data, it is important to acknowledge that they are based on two loci. This manuscript would be stronger if the authors could include additional loci in their study design. If this is not possible, it would be good to acknowledge that the conclusions are preliminary/speculative at this stage.
• It would be helpful if the authors could clarify the strategy they used for their FISH probe design. The enhancer and promoter fosmid probes (which are used for the majority of the experiments) are not centered on the active elements and do not even seem to overlap in the case of the GREB1 enhancer fosmid probe. The 10 kb enhancer probe seems better placed for the GREB1 locus, but the 10 kb enhancer probe does not seem to overlap with the enhancer in the NRIP1 locus. It is conceivable that the exact location of the probes has a big impact on the measurements and it would therefore be helpful if the authors could comment on the location of the probes and add additional probes if required to strengthen their conclusions. In addition, the fosmid probes are very large (40 kb). Although the authors acknowledge this, it would be helpful if they could comment on how overlap between 40 kb probes should be interpreted in relation to a potential rather focal contact between (proteins bound to) regions of <1 kb.
• It is not clear to me why the authors would choose to work with a locus that is present in 4 copies in their cell line. Is the entire regulatory region (incl. enhancers) preserved for the two additional copies of the gene? Can the authors comment on how this may impact on their measurements?
• Figure 2D shows an increase in E-P separation for the NRIP1 locus across all timepoints, with cumulative frequency plots shown for the 10 min timepoint. However, the data for the second replicate shown in Figure S2D are a lot less robust and not significant for the 10 min timepoint. It is important that the authors either provide additional data to support the robustness of this experiment or acknowledge that the results are not fully reproducible.
• The data presented in Figure 2F for clone 2 of the GREB1 enhancer deletion still show increased E-P distance upon activation. How do the authors explain this?

Minor comments:

• Could the authors comment on the observation that the NRIP1 promoter is not bound by ERa or p300 upon estrogen activation? Are there ATAC-seq or H3K27ac ChIP-seq data available for these conditions?
• It is not obvious which timepoint is shown in Figure 1D.
• Why did the authors choose e-i and p-i instead of e-c and p-c in Supplementary Figure 3B?
• "We treated hormone starved MCF-7 cells with flavopiridol or triptolide for 5 min before adding E2 for 30 min (Fig. 4A)." Does this mean that the FLV/TRP treatment lasted for 35 min or did the authors wash it out before adding E2? Please clarify.
• The authors refer to their Capture-C data as "high-resolution". However, the methods section mentions that the data for the GREB1 and NRIP1 locus are 5 kb and 10 kb resolution, respectively. This is not particularly high for a targeted approach, certainly not in light of the MNase-based approaches that have recently been developed. I therefore think that the "high-resolution" claims should be removed from the paper.

Referees cross-commenting I agree with the comments raised by Reviewer 1

Significance

Since 3C and DNA FISH are widely used, the discrepancy between these measurements that is described here is of potential broad interest to the field. Since these claims are rather strong and have potential far-reaching implications, it would be helpful if the authors could strengthen their conclusions further, by improving the robustness of the data and including additional loci and additional probes to show that the measurements are not specific for these two loci or dependent on the location of the probes. I think that the paper is in principle also publishable without these additional experiments, but in that case, it would be very important to explicitly acknowledge the limitations of the data throughout the manuscript and clarify that the conclusions are preliminary/speculative at this stage.

Expertise: 3D genome organization.

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Referee #1

Evidence, reproducibility and clarity

Gómez Acuña et al.

Transcription decouples estrogen-dependent changes in enhancer-promoter contact frequencies and spatial proximity

Summary

This study by Gómez Acuña et al. addresses a highly relevant question in the field of gene regulation: what are the mechanisms by which enhancers and promoters communicate to control expression of a target gene? This work tackles an apparent dichotomy as to whether enhancers (E) and promoters (P) need to come into close physical proximity in order to activate gene expression. While 3C-based methods have consistently suggested that the frequency of 'contacts' between enhancers and promoters increases during gene activation, imaging approaches have, in some instances, shown that these elements move further away from each other during this process. Gómez Acuña et al. have used 3C- and imaging-based methods in parallel at two inducible genes in the MCF-7 breast cancer cell line to confront this issue.

The study focusses on two oestrogen-responsive genes, GREB1 and NRIP1, which are fully activated within 1 h of oestradiol (E2) treatment of MCF-7 cells in in vitro culture. Using a capture-based 3C method, the authors show small increases in contacts between putative enhancers and promoters during gene induction. In contrast, for both genes they also observe increased distances between these elements by DNA FISH. The authors used CRISPR-Cas9 to delete the putative nearby enhancers and showed that these phenomena are likely dependent on these elements.

Next, the authors questioned whether recruitment of the oestrogen receptor (ER) itself or co-activators recruited by ER upon stimulation are responsible for the observed effects. By comparing E2 with tamoxifen (4OH), which recruit co-activators and -repressors, respectively, they only observed the effects on E-P contact and proximity in the presence of the activating stimulus (E2), suggesting recruitment of activating protein machinery is required.

Finally, they tested the effects of small molecules known to inhibit different stages of the transcription cycle. Both flavopiridol and triptolide abrogated the effect on E-P proximity observed by DNA FISH but did not affect the increase in E-P contacts seen by C-TALE. This suggested that these phenomena can be uncoupled, and that the act of transcription itself (and perhaps the associated production of RNA) is required for the physical separation of enhancers and promoters but not the increase in E-P contact frequency.

Major comments

Given the significance of the question posed in this study (see Significance section), it is important that the claims highlighted in this paper are appropriately supported by the experimental evidence. There are a number of issues with the design of the experiments in the current manuscript which are as follows:

1. The aneuploid karyotype of the MCF-7 cells used is a concern. GREB1 is present in four copies, with two on abnormal chromosomes which may not be regulated in the same way as primary cells. The authors should include caveats to this effect in the text to account for this.
2. The authors should also include more information on the generation and verification of the enhancer deletion cell lines. An illustration of the PCR primers used for screening, as well as an illustration of the sequenced product traces aligned with the reference genome (as opposed to just showing the deleted regions) should be included in Fig. S1D. This would give the reader more confidence that the designed knockout has occurred in the same way on all alleles. Furthermore, long-range PCRs and sequencing should be considered to confirm that no larger deletions have occurred (e.g. Owens et al., 2019 PMID: 31127293).
3. The changes in the measured E-P interaction frequency following gene activation are weak at best and make visual interpretation of the results difficult. Showing the reciprocal virtual 4C plots from the promoter would help to reassure the reader that the observed effect is real. Furthermore, the precise 3C method used is not clear. The authors repeatedly refer to "Capture-C" (a commonly used 3C-based approach using biotinylated oligos to pull down targets of interest) but the citation used (Golov et al. 2019) refers to a conceptually similar method called "C-TALE". This should be clarified in the text.
4. As for the changes in contact frequency, the observed changes in distance measurements between conditions are very small (although statistically significant). We acknowledge that this is likely due to the relatively small linear distances between enhancers and promoters in this study. However, it would be helpful to see the effects of the induction/treatments on a one or more control loci which is not affected by oestrogen signalling given that global changes in nuclear shape/volume and/or cell cycle effects could occur within this time (e.g. effects of tamoxifen treatment on MCF-7 cell cycle distribution, (Osborne et al. 1983 PMID: 6861130), which could impact nuclear volume.
5. The authors discuss previous studies demonstrating that E2 and 4OH recruit different sets of proteins to their target genes. Given that this is central to the conclusion that the ER ligand (and its recruited co-factors) determines the E-P interaction frequency and 3D distances observed, it would be important to demonstrate this at the GREB1/NRIP1 loci specifically. ChIP data of the co-activators/repressors recruited by E2 and 4OH, respectively, would greatly strengthen this claim.
6. The observed uncoupling of E-P contact frequency and 3D distance upon transcriptional inhibition is interesting and offers clues to the molecular details underlying E-P interactions. However, the use of flavopiridol and triptolide, while common in the field, should be carefully qualified given the potential for their indirect effects on transcription. This is particularly important for flavopiridol given its ability to target multiple cyclin-dependent kinases beyond CDK9 and its role in transcription initiation.

Minor comments

1. In the introduction and beginning of discussion, it would be helpful to detail previous studies where FISH-based analyses have shown more proximal E-P positioning upon activation, to make it clear that differences in E-P proximity appear to be gene-specific. Some examples include Williamson et al. (2016; PMID 27402708) and Chen et al. (2018; PMID 30038397). Speculation as to why some genes behave in this way while others do not, would also be worthwhile.
2. On page 6, the authors state that after deletion of the NRIP1 enhancer there is "almost total loss of NRIP1 induction in response to E2". This does not seem to match the data where in 3 out of 4 replicates (2 for each clone) there is a statistically significant increase in number of RNA FISH foci upon E2 stimulation in the NRIP1 enhancer KOs. This suggests that, as for GREB1, the regulation of these genes is not solely controlled by the deleted enhancers. This should be clarified in the text.
3. The labelling of the FISH probes in Supp. Fig. S2 could be improved as it is currently very difficult to read these.
4. Given that the authors have referenced a distance of 200 nm as potentially being an important threshold for gene activation, it would be useful to include the fraction of alleles which are below this distance alongside the cumulative frequency plots in Figure 2D and elsewhere in the paper as the cumulative frequency plots can be hard to read in some cases (e.g. Supp. Fig. S3B e-p). This would also allow the authors to show consistency across replicates.
5. For clarity, it would be helpful to include the difference map between the vehicle-treated unstimulated/stimulated conditions for the 3C plots in Fig. 4. This would help contextualise the resulting differences observed with the drug treatments. Same for Supp. Fig. S6.
6. Statistical comparisons are not shown for all 3D FISH-based distance measurements (e.g. Supp. Figs. S3A, S4C, D, S6E). If this is because the tests were done and the results were non-significant this should be indicated.
7. On page 13, the authors state that increased E-P separation occurs "before nascent transcription of the gene is detected by either TT-seq or RNA FISH". This does not appear to be correct given that baseline levels of transcription are observed in the absence of ER stimulation by both methods (Fig. 1). This should be clarified in the text.

Referees cross-commenting

Reviewer #2 is in good agreement with our review. The study is interesting but there are several caveats that need addressing as pointed out by both reviewers. We agree that it could take a lot of work to sort these points out in full experimentally but without this the authors should be careful not to overinterpret their data and comment on the shortcomings as it stands.

Significance

The question the authors are addressing here is of importance to the field. For several years, researchers have been attempting to uncover the mechanisms by which enhancers deliver information to their target promoters and this study highlights some potentially fundamental issues with the way in which these problems are typically addressed. It is generally accepted that in most cases, the frequency of 'contacts' between enhancers and promoters as measured by 3C-based methods increases as a gene becomes active. It is still unclear what exactly these 3C methods are measuring given that the radius of crosslinking and the extent to which protein-protein linkages between two DNA helices contribute to the observed contact frequency are unknown. In short, despite its widespread use, it is not clear whether contact frequency as measured by 3C is proportional to three-dimensional distance or something more nebulous. The issues raised in this paper are therefore critical for the accurate conception of mechanistic models of gene regulation.

The use of a well-studied inducible system to enable sampling of gene activation events at high temporal resolution means that the authors can ensure a level of control over the experimental conditions. The experiments appear to have been carried out to a high standard, with necessary controls generally included where appropriate. The analyses are well-documented and the results are consistent over the various reported experiments within the manuscript. The conclusions are thought-provoking and will challenge the field to be clearer about what 3C-based methods can and cannot show. This study will also surely lead to follow-up work to more specifically address the possible molecular mechanisms explaining the above observations. The main limitations of this study are the cell line and genes studied, with GREB1 being present in four copies in the aneuploid genome of MCF-7 cells. As stated above, there is some concern that using cells with such a chaotic genome as a starting point for investigating E-P interactions might prevent the authors from drawing clear and unambiguous conclusions. Perhaps related to this, the effect size of the E-P interactions upon stimulation as measured by C-TALE/Capture-C are underwhelming to say the least. Particularly for NRIP1, it was sometimes hard to tell where to look to see the supposed increase in E-P interactions, even with arrows as guidance.

Despite these limitations, this work raises an important issue that needs further clarification. It will require the field to reconsider what 3C-based analyses actually tell us with respect to E-P contact/proximity, and as a result models of E-P communication may need revising. This work is of broad interest to those work in the fields of nuclear biology and more specifically gene regulation. This will include both basic research scientists as well as those attempting to exploit enhancer-promoter dependencies for therapeutic purposes.

Expertise

Gene regulation, genome organisation and 3D structure.

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Reply to the reviewers

1. General Statements

We would like to thank the 3 reviewers for their comments and suggestions for our manuscript. We believe that the revisions we plan to make, based on the comments by the reviewers, will greatly enhance the quality of our manuscript.

We would like to respond to some reviewer comments here, since they do not fit into any of the subsequent sections.

Reviewer #3

In the Results section that describes the delay in gata2b expression (page 4 and Supp. Fig. 4), the authors show that the mutant embryos start expressing more gata2b at 30 - 36hpf after the decreased expression at earlier time points, with no difference at 48hpf. What could explain that recovery?

We thank reviewer 3 for this question. The partial functionality of the Cx41.8 channel in cx41.8tq/tq mutants may explain why the HSPC program is eventually induced (leading to sufficient mitochondrial ROS production for Hif1/2α stabilisation). However, this could also result from functional redundancy between Cx41.8 and other connexins such as Cx43 or Cx45.6 in the mitochondria, since they are also expressed in zebrafish arterial ECs at 24hpf (Gurung et al, Sci Rep, 2022) and cx43 knockdown has previously been shown to result in an HSPC specification defect in zebrafish (Jiang et al, Fish Physiol Biochem, 2010). Together, these aspects may explain the recovery, although delayed, of gata2b expression in the cx41.8tq/tq mutant, as discussed in detail in our manuscript.

The authors showed that gata2b expression can be rescued by ROS induction in the dose-dependent manner (page 6 and Fig.3 and Supp. Fig. 6). Is this what rescues gata2b expression at 30hpf in the cx41.8 mutants?

This is exactly right, we hypothesize that in cx41.8tq/tq mutants, it takes longer for mitochondrial ROS production to reach above the threshold required to stabilise Hif1/2α and hence induce gata2b expression, which is supported by the data referred to by this reviewer.

Are any vascular defects in the mutant embryos?

Our lab previously reported that cx41.8tq/tq embryos have faster ISV growth rate (Denis et al, Front Physiol, 2019). However, we found no evidence of a link between the ISV growth rate increase and the HSPC specification defect in these embryos. Importantly, we show that aorta specification is normal in cx41.8tq/tq mutants, as determined by dll4 expression at 24 (Supp. Fig. 1C) and 28 hpf (Supp. Fig. 1D).

2. Description of the planned revisions

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

Summary

The manuscript by Petzold et al. explores the functions of connexin 41.8 (cx41.8) (mammalian homologue Connexin 40) in hematopoietic stem cell (HSC) formation in the zebrafish dorsal aorta. The authors use a cx41.8 allele that appears to be hypomorphic, as the phenotype is milder than a previous cx41.8 allele that the same group published (Cacialli et al., 2021). cx41.8tq/tq mutants exhibit delayed onset of hemogenic endothelial specification, as marked by gata2b at 24 hpf, but HSPC development proceeds normally from 48 hpf onwards. A new reporter line for cx41.8, Tg(cx41.8:GFP), was generated and is expressed in the floor of the dorsal aorta, consistent with the location of hemogenic endothelial cells. Lower ROS production in the whole cell and in the mitochondria was reported in the cx41.8tq/tq mutants, and treatment with ROS enhancers, H2O2 and menadione, appeared to rescue the mutant phenotype of reduced HSPCs at 28 hpf. Finally, the authors tested a link between cx41.8 and Hif1α by pharmaceutically (DMOG/CoCl2) or genetically (vhl morpholino) inhibiting Hif inhibitors, and observed a rescue of HSPC formation in cx41.8 mutants.

I think it would be important for the authors to address the mechanisms of why cx41.8tq/tq and the other cx41.8-/- (leot1/t1) mutant phenotypes are different, with the latter allele showing more severe phenotypes of increased HSPC apoptosis and reduced HSPCs during later development. The authors speculate the cx41.8tq/tq allele encodes a missense mutation in one of the channel domains, and as such, might be a hypomorph. The authors cited the original paper by Watanabe et al. (2006); however, this paper actually noted that the cx41.8tq/tq allele is likely to be a dominant negative - and as such, should have exhibited a stronger phenotype than the leot1/t1 mutant allele. From the paper: "leotw28 and leotq270 heterozygotes have phenotypes different from that of WT; thus, they represent dominant-negative alleles." Importantly, no data are shown to provide evidence that the allele is a hypomorph - at minimum, qPCR data should be provided to show whether there is NMD of the mRNA in cx41.8tq/tq mutants.

We would like to thank the reviewer for this comment and suggestion. As the reviewer has rightly pointed out, the cx41.8tq/tq mutation is thought to result in a protein with dominant-negative function (Watanabe et al, EMBO Rep, 2006; Watanabe et al, J Biol Chem, 2016).

In fact, we agree that the mutant cx41.8tq/tq protein acts as a dominant-negative and although the reviewer is right to point out that the cx41.8t1/t1 mutant may thus exhibit a stronger phenotype which we found not to be the case (runx1 expression was found to be normal in the cx41.8t1/t1 mutant, Cacialli et al, Nature Commun, 2021), we provided our explanation for this in the discussion of the manuscript:

“The partial functionality of the Cx41.8 channel in cx41.8tq/tq mutants [14] may explain why the HSPC program is eventually induced. However, this could also result from functional redundancy between Cx41.8 and other connexins such as Cx43 or Cx45.6 in the mitochondria, since they are also expressed in zebrafish arterial ECs at 24hpf [18] and cx43 knockdown has previously been shown to result in an HSPC specification defect in zebrafish [36]. This potential functional redundancy may also provide an explanation as to why HSPCs are specified normally, without any delay, in cx41.8t1/t1 embryos [12]. In these null mutants, cx41.8 expression is completely absent but may be functionally compensated by other connexins, whereas in cx41.8tq/tq mutants, although cx41.8 is expressed, its channel function is reduced [14]. Moreover, as Cx41.8 may form heterotypic channels with Cx43 and/or Cx45.6 (and potentially also with others), the function of these chimeric channels would also be altered”

We believe this addresses the reviewers concern regarding this, especially given the fact that Cx43 and Cx45.6 have been found to be expressed in arterial ECs at 24 hpf, as cited in the manuscript. With regards to the reviewer’s question about whether there is NMD of the cx41.8 transcript, given that the cx41.8tq/tq mutation is missense and does not result in a premature stop codon (usually required for NMD to be induced, Kurosaki et al, J Cell Sci, 2016), we do not believe that there is NMD of the cx41.8 transcript in cx41.8tq/tq mutants. We will however verify this by carrying out the experiment suggested by this reviewer, qPCR analysis of cx41.8 expression in cx41.8tq/tq embryos and wild-type controls.

The quantification data in this manuscript are not satisfactory. The authors only provide graphs that show embryos with "low", "medium" and "high" numbers of HSPCs, which is incredibly subjective. Considering that the authors already have the cx41.8tq/tq in the Tg(myb:GFP) background (Figure 1E), they could have quantified the precise numbers of Tg(myb:GFP)-positive cells at different timepoints and with the different pharmaceutical rescue experiments. Ideally, this should be combined with other HSPC markers such as Tg(cd41:GFP) or Tg(runx1:GFP) - although this could be limited by the authors' access to the lines or time it takes to cross the mutants to the transgenes.

We thank reviewer 1 for their concern regarding this. Indeed the reviewer is correct, it would take us too long (at least 6 months) to generate the cx41.8tq/tq cd41:GFP or cx41.8tq/tq runx1:GFP lines, however, as stated, we do already have the cx41.8tq/tq cmyb:GFP zebrafish line. That said, repeating the pharmacological experiments using the cx41.8tq/tq cmyb:GFP zebrafish line would demand months of work and we do not currently have the personnel to perform all of this. However, we will perform the same experiment as performed previously to generate figure 1E but also at earlier timepoints. The cmyb:EGFP transgene marks nascent HSPCs from 28 hpf, and so we will aim to image, and quantify differences in budding HSPCs in cx41.8tq/tq cmyb:EGFP and cmyb:EGFP controls between 28 hpf and 36 hpf. We agree with the reviewer that this will add depth to our study and will provide evidence to back up our conclusions.

The link between cx41.8 and Hif1α is tenuous. The authors should perform in situ hybridization for the hif1 genes and their downstream effector notch1 which is known to be important for the HSPC specification (Gerri et al., 2018).

We thank the reviewer for this point. we do not expect hif1/2α expression to be affected in this mutant. Mitochondrial ROS has been shown to stabilise Hif1/2α at the protein level, not the mRNA level. Our data, and that of others (Harris et al, Blood, 2013), suggest that in the absence of mitochondrial ROS, prolyl hydroxylases are not inhibited by mitochondrial ROS, and they target Hif1/2α for ubiquitination and subsequent destruction in a Vhl-dependent manner (as shown in Fig. 4D). We have changed the text in the manuscript to clarify that Hif is stabilised on the protein level (please see the section below).

Since we do however expect notch1a and notch1b expression to be altered in our mutant embryos, as they are transcriptionally regulated by Hif1/2α (Gerri, Blood, 2018), we will perform in situ hybridisation and qPCR analysis of these 2 genes at 18-24 hpf in cx41.8tq/tq mutants and controls to clarify this point and solidify our model.

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

Summary

Petzold et al are here addressing the potential function of the connexin Cx48.1, a protein involved in the structure of gap junctions, in the specification of future hematopoietic stem cells and progenitors (HSPCs). This piece of work is complementing their previous results showing the function of this connexin isoform in HSPC expansion in the transient hematopoietic niche in the caudal tissue of the zebrafish embryo. They explore phenotypes triggered by the expression of a mutant form bearing a single amino-acid substitution in the fourth transmembrane domain of the protein. Using whole mount in situ hybridization (WISH) of the two transcription factors Gata2b and Runx1, a novel transgenic fish line that expresses eGFP under the control of the Cx48.1 promoter region, and a series of drug treatments interfering with, or promoting, the formation of reactive oxygen species (ROS) production and oxidative stress, they propose that Cx48.1 is also involved upstream of HSPC amplification, rather in their specification at the level of the hemogenic endothelium constituting the ventral floor of the dorsal aorta. Mechanistically, they hypothesize that this function relies on mitochondria-derived ROS that would destabilize the VHL protein involved in mediating the degradation of Hif1/2a transcription factors, thereby stabilizing the Hif1/2a-Notch1a/b signaling axis involved in specification of the hemogenic endothelium.

The WISH and quantitative analyses.

Most of the quantitative analyses in the work are based on chromogenic WISH, which is not sufficiently accurate because leading to highly variable results, in addition to its lack of linearity. WISH is also subjected to important variations, particularly for transcription factors that are expressed at low levels such as Runx1, and to some extent Gata2b also. One obvious example in the paper is the inconsistency of signals that are observed Fig1C (Gata2b, left, wt, 24hpf) and FigS3B (Gata2b, left, wt, 24hpf) in which the signal is barely visible and is comparable to the signal for the cx41.8tq/tq mutant Fig1C, right.

In addition, in the timings that are analyzed in FigS3 (Gata2b, 26 and 28hpf) to argue on temporal delay of expression in the cx41.8tq/tq mutant, the Gata2b signal is masked by the strong increase in tissues other than the hemogenic endothelium in the dorsal aorta (including signal in the somites as well as, possibly, increase in background). In this very example, it is legitimate to question the accuracy of the quantification methodology when the signal in the tissue of interest is drowned in the overall signal from surrounding tissues; how can the authors explain the 100% of embryos that have a 'Low' signal in the region of interest (FigS3C, cx41.8tq/tq mutant in comparison to WT)? This point is also valid for the data quantified FigS4 in which the fitting between WISH data and the quantifications appears to be questionable (for all timing points: 30, 32, 36, 48hpf and comparing mutant with the WT.

My suggestion would be to complement the WISH data and improve the quantitative analyses using another, more accurate approach such as qRT-PCR for example (on dissected trunk regions and, if necessary because of expression in other surrounding tissues (in the case of Gata2b at later time points), after FACS-sorting using a fish line expressing a fluorescent reporter driven by a vascular promoter, ex: the kdrl:mCherry line used in the work). This is particularly important for the expression of the two transcription factors Runx1 and the more upstream Gata2b, the latter being involved in HSPC specification which is taken as a reference. qRT-PCR experiments should be feasible relatively easily and in a reasonable time frame as the technics is not very time consuming and easily accessible.

We thank reviewer 2 for their concerns regarding the in situ quantifications used during this study. Although the approach we have used is widely used in the field to quantify gene expression differences, we appreciate that our data could be strengthened by complementing it with another approach. As such we will do the following:

• We will complement our in situ hybridisation characterisation of delayed hemogenic endothelium formation and HSPC specification with qPCR experiments. For this, we will dissect the trunks of 8tq/tq embryos and controls and perform qPCR analysis of gata2b expression at the timepoints analysed during development (Supp. Fig. 3 A-D and Supp. Fig. 4 A-D), whilst also using the same approach to compliment the data for gata2b and runx1 expression at 24 hpf (Figure 1C and D). We agree with the reviewer that this is a feasible approach and would add robustness to the data we already show.

  2- Fluorescence imaging and associated interpretation/conclusions.

The fluorescence images (Fig1E; Fig2B,D; Fig3A) are very difficult to analyze; they lack resolution because they appear to be epifluorescence images and not confocal images. When the signal is low, which is in particular the case for the novel Cx41.8:EGFP fish line, Fig2B (which is confirmed with the FACS GFP signal in comparison to the mCherry of the kdrl:mCherry fish line), it is not possible to provide convincing images on the vascular/aortic expression because of the high background of diffusion (the authors state 'likely to be the aortic floor', indeed it is not possible to validate the fact that the expression is truly in potential hemogenic cells). The double positive population in the FACS (Fig2C, right) does not resolve the issue because if indeed cx41.8 is expressed in endothelial cells (as expected from previous studies), the double positive population could equally be endothelial cells from inter-somitic vessels, for example (not to mention the underlying vein which is very close to the aorta in the trunk)). Fig2D, images are too small and, again, the resolution is not good enough to say that double positive cells are on the aortic floor. It is recommended to convince the reader that the authors try to confirm their statements by using confocal microscopy and increase the magnification of the relevant regions of interest.

We thank this reviewer for this point. We will address this concern by using, as they suggest, confocal microscopy to try to get higher resolution images. In particular, we will do the following:

• We will use confocal microscopy to image the 8:EGFP line as was done previously (Fig 2B), in order to obtain higher resolution images of expression of cx41.8 in the floor of the aorta.
• We will also use confocal microscopy to image the 8:EGFP;kdrl:mCherry line as was done in Fig 2D, in order to gain higher resolution images.
• We will also increase the magnification of the relevant regions of our confocal microscopy images as suggested by this reviewer.

  There is an inconsistency in the data between Fig1E (40hpf, in vivo imaging using the cmyb:GFP fish line) and FigS2 (48hpf, WISH cmyb); how can we observe 'HSPCs budding from the dorsal aorta' (see legend Fig1, arrowheads) which seems very much decreased in the imaging experiment for the cx41.8tq/tq mutant in comparison to WT, and have no effect on the cmyb signals FigS2B? What are the GFP+ cells that are aligned along the elongated yolk Fig1E and that appeared to be decreased in number in the mutant?

We agree that this disparity is confusing for the reader. We believe the disparity between these results is due firstly to the fact that the experiment in Supp. Fig 2C was performed 8 hours after that in Fig 1E and secondly due to the time it takes for GFP to fold (in the case of Fig 1E). It is also important to keep in mind that the phenotype is not a complete absence of HSPC budding, but only a delay in the onset of EHT.

• We will however address this concern by carrying out the experiment described above - we will perform the same experiment as performed previously to generate figure 1E but also at earlier timepoints. The cmyb:EGFP transgene marks nascent HSPCs from 28 hpf, and so we will aim to image, and quantify differences in budding HSPCs in 8tq/tq cmyb:EGFP and cmyb:EGFP controls at numerous timepoints from 28 hpf to 36 hpf. This will add depth to our study by providing evidence to back up our conclusions.
• We will remove the 40-hpf timepoint (Fig 1E) to avoid confusion regarding the disparity with cmyb expression by WISH in Supp. Fig 2C.
• Regarding the GFP+ cells aligned along the yolk in 1E, we thank the reviewer for pointing this out. These cells are multiciliated cells, from the kidney tubules (Wang et al, Development 2013). We will determine whether their numbers do indeed differ between 8tq/tq;cmyb:EGFP and cmyb:EGFP controls in our new confocal experiments and will mention this in the manuscript if they do.

  It would be important to investigate/show, at least with qualitative WISH experiments all along the time-window of HSPC specification as stated by the authors (26-54hpf, see main text third paragraph of Results), that Cx41.8 is detected in arterial endothelial cells (and perhaps enriched in the hemogenic endothelium?), in complement to the work they are referring to on transcriptomic data at 24hpf (Ref18 Gurung et al Sci Rep 2022). Ideally, these WISH data should be resolutive enough to provide clear localization in aortic cells versus cells in the aortic floor to bring significant added value to the work that lacks spatial resolution (ex: fluorescent WISH using confocal microscopy, allowing to superpose signal with cell types (either by double fluorescent WISH (vascular marker + Cx41.8) or superposing fluorescence signals with transmitted light)).

We agree with this reviewer regarding this point. The way we will address this is to use confocal microscopy at different timepoints from 24-40 hpf using the cx41.8:EGFP; kdrl:mCherry line to show that expression of cx41.8 is indeed present and enriched in the floor of the dorsal aorta during the timeframe of HSPC specification. We believe that imaging this line using confocal microscopy will be sufficient to clearly show this.

It would be more informative and secure, Fig2D, to show images of the double transgenics (Cx48.1:eGFP;kdrl:mCherry) at 28-30 hpf (rather than 48 hpf) which is more narrowed down to the specification of the hemogenic endothelium thus preventing any risk to visualize the fluorescence signals coming from recently born HSPCs rather than signals from cells embedded in the aortic floor.

We thank the reviewer for this suggestion, which we believe would indeed improve the manuscript. As discussed above, we will indeed use confocal microscopy at different timepoints, including 28-30 hpf using the cx41.8:EGFP;kdrl:mCherry line to show that expression of cx41.8 is indeed present and enriched in the floor of the dorsal aorta during the timeframe of HSPC specification. We believe that imaging this line using confocal microscopy will be sufficient to clearly show this and so thank the reviewer for this excellent suggestion.

To make the data more convincing on the ROS production in the ventral side of the cord in wild type embryos (which suggests that future hemogenic cells are already ventralized at that stage), it would be important to obtain confocal images of the region of interest and perform reconstitution of Z-stacks with a sagittal view (rather than longitudinal). It would be nice also to obtain comparable images later on, after lumenization and before initiation of HSPC emergence (before 28hpf).

We thank the reviewer for this suggestion and agree that the suggested approach will solidify our data. As such, we will carry out the proposed experiment, using confocal imaging to gain longitudinal and sagittal images of mitoSOX staining in WT embryos and cx41.8tq/tq mutants at both 16 hpf and 26 hpf.

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

Reviewer #1

Related to the above point, the authors should test whether the gap junction function of Cx41.8 is intact in the cx41.8tq/tq mutants by assessing calcium waves in the GCamp transgenic line.

…we have also now found additional published in vivo evidence that Cx41.8 channel function is reduced in the cx41.8tq/tq mutant, which is now also cited in the new version of the manuscript (please see our full response to this point below).

Please see the section “Description of analyses that authors prefer not to carry out” for additional information regarding the GCamp experiment suggestion.

The link between cx41.8 and Hif1α is tenuous. The authors should perform in situ hybridization for the hif1 genes…

We thank reviewer 1 for making this point. To clarify this, we do not expect hif1/2α expression to be affected in this mutant. Mitochondrial ROS has been shown to stabilise Hif1/2α at the protein level, not the mRNA level. Our data, and that of others (Harris et al, Blood, 2013), suggest that in the absence of mitochondrial ROS, prolyl hydroxylases are not inhibited by mitochondrial ROS, and they target Hif1/2α for ubiquitination and subsequent destruction in a Vhl dependent manner (as shown in Fig. 4D).

To clarify this in the manuscript, we have adjusted the text in three places (including in the abstract) to clarify that Hif1/2α is stabilised at the protein level, as shown below. We believe these changes have made this important point more understandable for the reader:

1. “… Mitochondrial-derived reactive oxygen species (ROS) have been shown to stabilise the hypoxia-inducible factor 1/2a (Hif1/2a) proteins, allowing them..”
2. “Recent research has demonstrated that hypoxia and mitochondrial ROS are required for the stabilisation of the transcription factors Hif1/2a at the protein level”
3. “… as mitochondrial ROS generation may eventually reach the threshold required to sufficiently stabilise the Hif1/2a proteins for downstream”

   Reviewer #2

Importantly, it appears also that all over the WISH quantifications, the reader cannot appreciate the accuracy of the categories High/Medium/Low, which is not at all developed in the Methods section (paragraph Image processing and WISH phenotypic analyses).

We have developed the Methods section (paragraph Image processing and WISH phenotypic analyses), which was highlighted as a concern by this reviewer, in order to detail exactly how we performed our image analysis and statistical analyses using this approach. We believe this will satisfy the concerns reviewer 2 has regarding this and appreciate that they have a point that this was indeed underdeveloped in the original submission.

Finally, there is a confusion in the quantification regarding the number of HSPCs (see the beginning of the second paragraph of Results 'The HSPC specification defect in cx41.8tq/tq mutants is due to a delay in Gata2b expression') and the % of embryos falling into the 3 categories High/Medium/Low FigS2, cmyb 48hpf. The authors use this argument (based on the WISH cmyb signals) to infer that the deficit in the cx41.8tq/tq mutant is not due to controlling HSPC number (no difference in cmyb between WT and mutant) but rather upstream, at the level of the hemogenic endothelium, which is not a thorough argument at that point.

We thank reviewer 2 for pointing this out to us and agree that the wording we used is a little confusing. We have therefore added to the first sentence of the second paragraph in the results section “'The HSPC specification defect in cx41.8tq/tq mutants is due to a delay in gata2b expression” which now reads:

“Hence, since HSPC specification is initially reduced, but then recovers in cx41.8tq/tq embryos, we suspected a delay in the formation of the haemogenic endothelium in these mutants. To test this hypothesis…”

We believe this change to the manuscript will satisfy the reviewers concern by making this section more logical for the reader.

The authors should take care of the fact that at 16hpf, it is an overstatement to speak of an aorta when the cord is starting to lumenize at around 18hpf, Jin et al Development 2005 (see Main text referring to Fig3).

We thank the reviewer for this clarification. We have changed the relevant text to state “vascular cord” instead of “aorta” and have mentioned that it begins to lumenize around 18hpf for clarification. We have also added the suggested reference.

Reviewer #3

As Gata2 has been shown to be a positive autoregulator of itself in mice (Nozawa 2009, Katsumura 2016) and might do so in zebrafish (Dobrzycki 2020), so could gata2b recover itself, in a dose-dependent manner, without the Hif-Nocth1 axis once enough of it is expressed?

We thank reviewer 3 for this suggestion. We believe that our data show that Cx41.8 is required for mitochondrial ROS production, which stabilises Hif1/2α and switches on downstream gata2b via Notch1a/b (which will be added, see previous section). As such, we believe that the Hif1/2α/Notch1a/b axis is required, at least for the initial induction of gata2b expression. However, reviewer 3 makes a very interesting point regarding the potential for gata2b to positively autoregulate itself, which may of course occur once gata2b expression has been induced by the Cx41.8-mitoROS-Hif1/2α-Notch1a/b-gata2b pathway. We thank the reviewer again for this interesting proposition and have added this suggestion into our discussion in the following paragraph:

“GATA2 has been shown to positively autoregulate its own expression in mice (Nozawa et al, Genes to Cells, 2009; Katsumura et al, Cell Reports 2016), and Gata2b may also act in this way in zebrafish (Dobrzycki et al, Commun Biol, 2020). Therefore, it is interesting to speculate that once gata2b expression has been induced by the Cx-mitoROS-Hif1/2α-Notch1a/b-gata2b pathway, it may also further induce its own expression, which would make the induction of the haematopoietic transcriptional program more robust”

Is Hif1/2a expression affected in the mutant? Is it expressed normally but then degraded faster due to the absence of mitochondrial ROS or is it less Hif1/2a expressed overall?

We thank reviewer 3 for this question, which is similar to a point made by reviewer 1. To clarify, we do not expect hif1/2α expression to be affected in this mutant. Mitochondrial ROS has been shown to stabilise Hif1/2α at the protein level, not the mRNA level. Our data, and that of others (Harris et al, Blood, 2013), suggest that in the absence of mitochondrial ROS, prolyl hydroxylases are not inhibited by mitochondrial ROS, and they target Hif1/2α for ubiquitination and subsequent destruction in a Vhl dependent manner (as shown in Fig. 4D).

To clarify this in the manuscript, we have adjusted the text in three places (including in the abstract) to clarify that Hif1/2α is stabilised at the protein level, as shown below. We believe these changes have made this important point more understandable for the reader:

1. “… Mitochondrial-derived reactive oxygen species (ROS) have been shown to stabilise the hypoxia-inducible factor 1/2a (Hif1/2a) proteins, allowing them..”
2. “Recent research has demonstrated that hypoxia and mitochondrial ROS are required for the stabilisation of the transcription factors Hif1/2a at the protein level”
3. “… as mitochondrial ROS generation may eventually reach the threshold required to sufficiently stabilise the Hif1/2a proteins for downstream”

   Does MO-mediated knockdown of vhl in the wildtype and mutant (page 7and Fig. ) result in more HSPCs, following the increase in gata2b expression from WT baseline? Does that high expression persist, or does it drop?

This is an important question. We had already clarified this in the case of cx41.8tq/tq, since we showed that the vhl MO results in more HSPCs (as determined by runx1 expression) at 28 hpf (Supp. Fig. 8A) but we have now added data for the same marker at the same timepoint for WT embryos (Supp. Fig. 8B).

Although the vhl MO results in an increase in runx1 signal in WT embryos, since the majority of WT embryos injected with the control MO already have “high” runx1 WISH signal at 28 hpf, the difference between injected and control MO injected WT embryos is not significant (Supp. Fig. 8B), as can be expected. This is now explained in the manuscript following the relevant data addition.

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

Reviewer #1

One major missing component is experimental data that distinguish the gap junction/plasma membrane- related and the mitochondrial membrane-related functions of Cx41.8. This is critical, as the role of Connexins in the mitochondria remains poorly understood (and Connexin 43 is the best understood one). Thus, it is a big claim by the authors that Cx41.8 primarily acts through the mitochondria and not the gap junctions. Suggested experiment: The authors should generate a fluorophore-tagged Cx41.8 - under a ubiquitous (ubb or actin) or HSPC-/hemogenic endothelium-specific (gata2b) promoter to monitor the protein localization of Cx41.8. Providing data on whether Cx41.8 protein indeed localizes to the mitochondria is important to support their claim.

We thank the reviewer for this suggestion, which we agree would be a nice experimental approach to try to investigate whether Cx41.8 does indeed localise to the mitochondria in zebrafish endothelial cells.

However, EGFP fused full-length cx41.8 has previously been generated and was reported to be nonfunctional, and it was suggested that the amount of localised Cx41.8 is also too small to detect using this approach (Watanabe et al, Pigment Cell Melanoma Res, 2012; Usui et al, BBA Advances, 2021). An EGFP tagged CT-truncated Cx41.8 construct has also been generated and shown to rescue the cx41.8t1/t1 mutant (Usui et al, BBA Advances, 2021), but EGFP expression again could not be detected using this construct in zebrafish.

As such, since efforts to carry out such an approach have failed in previous attempts and since it has already been demonstrated that CX40 (orthologous to cx41.8) localises to the mitochondria of endothelial cells (Guo et al, Am J Physiol Cell Physiol, 2017), we believe that confirmation of Cx41.8 localisation to the mitochondria in vivo in zebrafish endothelial cells will be very difficult and too time-consuming in the context of this manuscript.

Related to the above point, the authors should test whether the gap junction function of Cx41.8 is intact in the cx41.8tq/tq mutants by assessing calcium waves in the GCamp transgenic line.

We agree with the reviewer that this would be a very elegant approach in order to analyse whether Cx41.8 channel function is affected in cx41.8tq/tq mutants. However, we feel that this experiment is definitely beyond the scope of this manuscript. Furthermore, carrying out this experiment would require the acquisition of the GCamp line as well as multiple crosses with the cx41.8tq/tq line which, together, we envisage would take at least 9 months before the experiments can be performed, as so this experiment would also be too time consuming for this manuscript. Finally, we believe there is already strong published evidence that the cx41.8tq/tq mutant results in disrupted channel function (Watanabe et al, EMBO Rep, 2006), as already cited in our manuscript. However, since then, we have also now found additional published in vivo evidence that cx41.8tq/tq channel function is reduced, which is now also cited in the new version of the manuscript.

The authors might also want to consider performing transcriptomic analysis (bulk RNA sequencing) from purified HSCs in wild types and cx41.8 mutants and assess the downstream pathways affected by the loss of this gene.

Although this is an interesting proposition, we consider this suggestion to be out of the scope of this manuscript, especially since our model involves changes in gene expression upstream of HSPC induction, and, expression of the key genes thought to be affected (notch1a/b and gata2b) can be checked using a much more cost and time efficient approach, by qPCR, which we will do, as discussed above.

Are the authors sure of their statement on budding HSPCs when the GFP signal pointed by arrows could in majority be hemogenic cells? (which would be in favor of their hypothesis on Cx41.8 being involved rather in hemogenic endothelium/HSPC specification).

Since cmyb is a marker of HSPCs and not of the haemogenic endothelium as demonstrated in numerous publications (North et al, Nature, 2007; Bertrand et al, Development, 2008; Bertrand et al, Nature, 2010 and others). Hence, we are confident that this transgene is marking nascent HSPCs and not the haemogenic endothelium.

As mentioned by the authors in the Discussion, the other connexin Cx43 (Ref 36, Jiang et al 2010) is playing a significant role in HSPC specification in the zebrafish and is expressed in zebrafish arterial cells at 24 hpf. Hence there may be some functional redundancy between Cx43 and Cx48.1, as supported by previous work from the authors showing that a null mutant of Cx48.1 does not exhibit any phenotype in HSPC specification (Ref12, Cacialli et al 2021). This may be problematic for the experiments using drug treatments in the present work, because they are not selective for the different connexins (ex: anti-oxydants (NAC), connexin blockers (heptanol, CBX)), thus blurring interpretations on the specific function of Cx48.1 versus the ones exerted by Cx43 (this should be also valid for the vhl MO treatments).

This comment is strengthened by the fact that the authors do not systematically address, for both WT and mutant embryos (Fig3 E, F; FigS6; FigS8), if expression levels with drugs/H2O2/MO are different for the 2 conditions (if relatively equal, it would indeed indicate that these drugs/conditions possibly act on another connexin, which would help the authors in their analyses and interpretations).

We thank the reviewer for these comments and we agree with their concerns regarding the possibility of other Connexins being affected by our experiments using drug treatments. However, we do not rule this out in our manuscript and actually discuss it as being a very realistic prospect, as written about in the discussion section.

Sadly, to the best of our knowledge, no selective Cx41.8 inhibitors have been described for use in zebrafish, otherwise we would of course have used this. Hence, this was the reason for our choice of compounds, many of which we also used in our previous publication (Cacialli et al, Nature Commun, 2021).

The haemogenic endothelium/HSPC phenotype in cx41.8tq/tq embryos confirms that this connexin plays a role in HSPC specification, whilst we believe disentangling which other connexins are also involved in this process will be interesting to look into in other future studies but is beyond the scope of this one – we believe that together, the data presented in our manuscript, along with the revisions we plan to carry out, will be convincing to demonstrate a role for Cx41.8 in the mechanism we describe.

The authors may try to rescue the wt phenotype by expressing, in the Cx48.1tq/tq mutants, the mRNA encoding for the wt protein.

Although we appreciate this suggestion, we do not believe this experiment will add much in terms of value to the conclusions of our manuscript and, as such, we believe this suggestion is surplus to requirements for this manuscript.

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Referee #3

Evidence, reproducibility and clarity

The authors have successfully shown how disruption in connexin (cx)41.8 results in delayed gata2b expression due to Hif1/2a instability in the absence of mitochondrial ROS. The data is presented well, and the paper is written clearly. The paper is well structured, and the data supports the authors' argument. This study provides a valuable contribution to the field.

Could the authors clarify the following questions:

1. In the Results section that describes the delay in gata2b expression (page 4 and Supp. Fig. 4), the authors show that the mutant embryos start expressing more gata2b at 30 - 36hpf after the decreased expression at earlier time points, with no difference at 48hpf. What could explain that recovery? The authors showed that gata2b expression can be rescued by ROS induction in the dose-dependent manner (page 6 and Fig.3 and Supp. Fig. 6). Is this what rescues gata2b expression at 30hpf in the cx41.8 mutants? As Gata2 has been shown to be a positive autoregulator of itself in mice (Nozawa 2009, Katsumura 2016) and might do so in zebrafish (Dobrzycki 2020), so could gata2b recover itself, in a dose-dependent manner, without the Hif-Nothc1 axis once enough of it is expressed?
2. Does MO-mediated knockdown of vhl in the wildtype and mutant (page 7and Fig. 4) result in more HSPCs, following the increase in gata2b expression from WT baseline? Does that high expression persist, or does it drop?
3. Is Hif1/2a expression affected in the mutant? Is it expressed normally but then degraded faster due to the absence of mitochondrial ROS or is it less Hif1/2a expressed overall? Are any vascular defects in the mutant embryos?

Significance

his study provides a valuable contribution to the field of developmental hematopoiesis.

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Referee #2

Evidence, reproducibility and clarity

Summary

Petzold et al are here addressing the potential function of the connexin Cx48.1, a protein involved in the structure of gap junctions, in the specification of future hematopoietic stem cells and progenitors (HSPCs). This piece of work is complementing their previous results showing the function of this connexin isoform in HSPC expansion in the transient hematopoietic niche in the caudal tissue of the zebrafish embryo. They explore phenotypes triggered by the expression of a mutant form bearing a single amino-acid substitution in the fourth transmembrane domain of the protein. Using whole mount in situ hybridization (WISH) of the two transcription factors Gata2b and Runx1, a novel transgenic fish line that expresses eGFP under the control of the Cx48.1 promoter region, and a series of drug treatments interfering with, or promoting, the formation of reactive oxygen species (ROS) production and oxidative stress, they propose that Cx48.1 is also involved upstream of HSPC amplification, rather in their specification at the level of the hemogenic endothelium constituting the ventral floor of the dorsal aorta. Mechanistically, they hypothesize that this function relies on mitochondria-derived ROS that would destabilize the VHL protein involved in mediating the degradation of Hif1/2a transcription factors, thereby stabilizing the Hif1/2a-Notch1a/b signaling axis involved in specification of the hemogenic endothelium.

Major comments

My major comments on the work are on the accuracy of the data in regard to the two main experimental approaches used by the authors and their subsequent analysis/quantification.

1. the WISH and quantitative analyses. Most of the quantitative analyses in the work are based on chromogenic WISH, which is not sufficiently accurate because leading to highly variable results, in addition to its lack of linearity. WISH is also subjected to important variations, particularly for transcription factors that are expressed at low levels such as Runx1, and to some extent Gata2b also. One obvious example in the paper is the inconsistency of signals that are observed Fig1C (Gata2b, left, wt, 24hpf) and FigS3B (Gata2b, left, wt, 24hpf) in which the signal is barely visible and is comparable to the signal for the cx41.8tq/tq mutant Fig1C, right. In addition, in the timings that are analyzed in FigS3 (Gata2b, 26 and 28hpf) to argue on temporal delay of expression in the cx41.8tq/tq mutant, the Gata2b signal is masked by the strong increase in tissues other than the hemogenic endothelium in the dorsal aorta (including signal in the somites as well as, possibly, increase in background). In this very example, it is legitimate to question the accuracy of the quantification methodology when the signal in the tissue of interest is drowned in the overall signal from surrounding tissues; how can the authors explain the 100% of embryos that have a 'Low' signal in the region of interest (FigS3C, cx41.8tq/tq mutant in comparison to WT)? This point is also valid for the data quantified FigS4 in which the fitting between WISH data and the quantifications appears to be questionable (for all timing points: 30, 32, 36, 48hpf and comparing mutant with WT). Importantly, it appears also that all over the WISH quantifications, the reader cannot appreciate the accuracy of the categories High/Medium/Low, which is not at all developed in the Methods section (paragraph Image processing and WISH phenotypic analyses); hence, it is not possible to evaluate the accuracy/validity of statistics in particular in the experiments in which the quantification into these categories is used for CoCl2 and morpholino analyses to address the contribution of the Hif1/2a-Notch1a/b pathway Fig4 (these experiments generating results that are not as 'black and white' than the other ones in the paper, hence requiring more accuracy; for example, are the differences in the quantification (% of embryos) significant between the WT+vhl MO and Cx41.8tq/tq mutant + vhl MO? Comparing the 2 WISH results for those conditions does not appear to be very convincing).

My suggestion would be to complement the WISH data and improve the quantitative analyses using another, more accurate approach such as qRT-PCR for example (on dissected trunk regions and, if necessary because of expression in other surrounding tissues (in the case of Gata2b at later time points), after FACS-sorting using a fish line expressing a fluorescent reporter driven by a vascular promoter, ex: the kdrl:mCherry line used in the work). This is particularly important for the expression of the two transcription factors Runx1 and the more upstream Gata2b, the latter being involved in HSPC specification which is taken as a reference. qRT-PCR experiments should be feasible relatively easily and in a reasonable time frame as the technics is not very time consuming and easily accessible.

Finally, there is a confusion in the quantification regarding the number of HSPCs (see the beginning of the second paragraph of Results 'The HSPC specification defect in cx41.8tq/tq mutants is due to a delay in Gata2b expression') and the % of embryos falling into the 3 categories High/Medium/Low FigS2, cmyb 48hpf. The authors use this argument (based on the WISH cmyb signals) to infer that the deficit in the cx41.8tq/tq mutant is not due to controlling HSPC number (no difference in cmyb between WT and mutant) but rather upstream, at the level of the hemogenic endothelium, which is not a thorough argument at that point.<br /> 2. Fluorescence imaging and associated interpretation/conclusions.

The fluorescence images (Fig1E; Fig2B,D; Fig3A) are very difficult to analyze; they lack resolution because they appear to be epifluorescence images and not confocal images. When the signal is low, which is in particular the case for the novel Cx41.8:EGFP fish line, Fig2B (which is confirmed with the FACS GFP signal in comparison to the mCherry of the kdrl:mCherry fish line), it is not possible to provide convincing images on the vascular/aortic expression because of the high background of diffusion (the authors state 'likely to be the aortic floor', indeed it is not possible to validate the fact that the expression is truly in potential hemogenic cells). The double positive population in the FACS (Fig2C, right) does not resolve the issue because if indeed cx41.8 is expressed in endothelial cells (as expected from previous studies), the double positive population could equally be endothelial cells from inter-somitic vessels, for example (not to mention the underlying vein which is very close to the aorta in the trunk)). Fig2D, images are too small and, again, the resolution is not good enough to say that double positive cells are on the aortic floor. It is recommended to convince the reader that the authors try to confirm their statements by using confocal microscopy and increase the magnification of the relevant regions of interest.

There is an inconsistency in the data between Fig1E (40hpf, in vivo imaging using the cmyb:GFP fish line) and FigS2 (48hpf, WISH cmyb); how can we observe 'HSPCs budding from the dorsal aorta' (see legend Fig1, arrowheads) which seems very much decreased in the imaging experiment for the cx41.8tq/tq mutant in comparison to WT, and have no effect on the cmyb signals FigS2B? What are the GFP+ cells that are aligned along the elongated yolk Fig1E and that appeared to be decreased in number in the mutant? Are the authors sure of their statement on budding HSPCs when the GFP signal pointed by arrows could in majority be hemogenic cells? (which would be in favor of their hypothesis on Cx41.8 being involved rather in hemogenic endothelium/HSPC specification).

Other Major Comments:

• It would be important to investigate/show, at least with qualitative WISH experiments all along the time-window of HSPC specification as stated by the authors (26-54hpf, see main text third paragraph of Results), that Cx41.8 is detected in arterial endothelial cells (and perhaps enriched in the hemogenic endothelium?), in complement to the work they are referring to on transcriptomic data at 24hpf (Ref18 Gurung et al Sci Rep 2022). Ideally, these WISH data should be resolutive enough to provide clear localization in aortic cells versus cells in the aortic floor to bring significant added value to the work that lacks spatial resolution (ex: fluorescent WISH using confocal microscopy, allowing to superpose signal with cell types (either by double fluorescent WISH (vascular marker + Cx41.8) or superposing fluorescence signals with transmitted light)).
• As mentioned by the authors in the Discussion, the other connexin Cx43 (Ref 36, Jiang et al 2010) is playing a significant role in HSPC specification in the zebrafish and is expressed in zebrafish arterial cells at 24 hpf. Hence there may be some functional redundancy between Cx43 and Cx48.1, as supported by previous work from the authors showing that a null mutant of Cx48.1 does not exhibit any phenotype in HSPC specification (Ref12, Cacialli et al 2021). This may be problematic for the experiments using drug treatments in the present work, because they are not selective for the different connexins (ex: anti-oxydants (NAC), connexin blockers (heptanol, CBX)), thus blurring interpretations on the specific function of Cx48.1 versus the ones exerted by Cx43 (this should be also valid for the vhl MO treatments). This comment is strengthened by the fact that the authors do not systematically address, for both WT and mutant embryos (Fig3 E, F; FigS6; FigS8), if expression levels with drugs/H2O2/MO are different for the 2 conditions (if relatively equal, it would indeed indicate that these drugs/conditions possibly act on another connexin, which would help the authors in their analyses and interpretations).

Minor comments

• The authors should take care of the fact that at 16hpf, it is an overstatement to speak of an aorta when the cord is starting to lumenize at around 18hpf, Jin et al Development 2005 (see Main text referring to Fig3). To make the data more convincing on the ROS production in the ventral side of the cord in wild type embryos (which suggests that future hemogenic cells are already ventralized at that stage), it would be important to obtain confocal images of the region of interest and perform reconstitution of Z-stacks with a sagittal view (rather than longitudinal). It would be nice also to obtain comparable images later on, after lumenization and before initiation of HSPC emergence (before 28hpf).
• The authors may try to rescue the wt phenotype by expressing, in the Cx48.1tq/tq mutants, the mRNA encoding for the wt protein.
• It would be more informative and secure, Fig2D, to show images of the double transgenics (Cx48.1:eGFP;kdrl:mCherry) at 28-30 hpf (rather than 48 hpf) which is more narrowed down to the specification of the hemogenic endothelium thus preventing any risk to visualize the fluorescence signals coming from recently born HSPCs rather than signals from cells embedded in the aortic floor.

Significance

Petzold et al propose a potentially appealing function of connexin Cx48.1 expressed in the zebrafish in the specification of the vascular aortic subtype of cells that will ultimately lead to the formation of hematopoietic stem cell precursors, ie the hemogenic endothelium. They build the work on a possible translation of the function of connexin Cx40 in mammals that is described to localize to mitochondrial membranes in endothelial cells and promote the production of ROS in mitochondria. They propose a function of mitochondria-derived ROS in stabilizing the Hif1/2-Notch1 pathway that is essential for HSPC precursor specification and that may be extended to developmental hematopoiesis in mammals (the putative ortholog of zebrafish Cx48.1 in mammals (Cx40) is highly expressed in the hemogenic endothelium of mouse and human species (see the Discussion paragraph)).

The proposed model is potentially of high significance for the field of hematopoiesis and more generally for translation of knowledge to regenerative medicine aimed at producing hematopoietic stem cells endowed with long term regenerative potential. However, the current work remains preliminary, suffering from lack of resolution in the main experimental axes that are undertaken (WISH analyses and their low accuracy quantifications; low resolution of in situ live imaging; apparent weaknesses of methodologies that are difficult to fully appreciate since poorly detailed in the Method section, in particular regarding WISH quantification and, hence, statistical significance). My recommendation is that the authors should put some efforts in completing the work with other, more quantitative, methodologies (ex: qRT-PCR) and improving the quality/resolution of imaging (by providing confocal images to alleviate any ambiguity on what is visualized and strengthen the results); these are technical approaches that are relatively standard in the field and the authors have extensively used qRT-PCR and FACS-sorting in their previously published work. Also, the endogenous expression of Cx48.1 in the hemogenic endothelium, during the time-window of its specification (20-28hpf), should be addressed; this would be essential to complement the imaging performed with the new transgenic line that expresses eGFP under the control of the Cx48.1 promoter and which provides weak fluorescence signals).

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Referee #1

Evidence, reproducibility and clarity

Summary

The manuscript by Petzold et al. explores the functions of connexin 41.8 (cx41.8) (mammalian homologue Connexin 40) in hematopoietic stem cell (HSC) formation in the zebrafish dorsal aorta. The authors use a cx41.8 allele that appears to be hypomorphic, as the phenotype is milder than a previous cx41.8 allele that the same group published (Cacialli et al., 2021). cx41.8tq/tq mutants exhibit delayed onset of hemogenic endothelial specification, as marked by gata2b at 24 hpf, but HSPC development proceeds normally from 48 hpf onwards. A new reporter line for cx41.8, Tg(cx41.8:GFP), was generated and is expressed in the floor of the dorsal aorta, consistent with the location of hemogenic endothelial cells. Lower ROS production in the whole cell and in the mitochondria was reported in the cx41.8tq/tq mutants, and treatment with ROS enhancers, H2O2 and menadione, appeared to rescue the mutant phenotype of reduced HSPCs at 28 hpf. Finally, the authors tested a link between cx41.8 and Hif1α by pharmaceutically (DMOG/CoCl2) or genetically (vhl morpholino) inhibiting Hif inhibitors, and observed a rescue of HSPC formation in cx41.8 mutants.

Major comments

• I think it would be important for the authors to address the mechanisms of why cx41.8tq/tq and the other cx41.8-/- (leot1/t1) mutant phenotypes are different, with the latter allele showing more severe phenotypes of increased HSPC apoptosis and reduced HSPCs during later development. The authors speculate the cx41.8tq/tq allele encodes a missense mutation in one of the channel domains, and as such, might be a hypomorph. The authors cited the original paper by Watanabe et al. (2006); however, this paper actually noted that the cx41.8tq/tq allele is likely to be a dominant negative - and as such, should have exhibited a stronger phenotype than the leot1/t1 mutant allele. From the paper: "leotw28 and leotq270 heterozygotes have phenotypes different from that of WT; thus, they represent dominant-negative alleles." Importantly, no data are shown to provide evidence that the allele is a hypomorph - at minimum, qPCR data should be provided to show whether there is NMD of the mRNA in cx41.8tq/tq mutants.
• One major missing component is experimental data that distinguish the gap junction/plasma membrane- related and the mitochondrial membrane-related functions of Cx41.8. This is critical, as the role of Connexins in the mitochondria remains poorly understood (and Connexin 43 is the best understood one). Thus, it is a big claim by the authors that Cx41.8 primarily acts through the mitochondria and not the gap junctions. Suggested experiment: The authors should generate a fluorophore-tagged Cx41.8 - under a ubiquitous (ubb or actin) or HSPC-/hemogenic endothelium-specific (gata2b) promoter to monitor the protein localization of Cx41.8. Providing data on whether Cx41.8 protein indeed localizes to the mitochondria is important to support their claim.
• Related to the above point, the authors should test whether the gap junction function of Cx41.8 is intact in the cx41.8tq/tq mutants by assessing calcium waves in the GCamp transgenic line.
• The quantification data in this manuscript are not satisfactory. The authors only provide graphs that show embryos with "low", "medium" and "high" numbers of HSPCs, which is incredibly subjective. Considering that the authors already have the cx41.8tq/tq in the Tg(myb:GFP) background (Figure 1E), they could have quantified the precise numbers of Tg(myb:GFP)-positive cells at different timepoints and with the different pharmaceutical rescue experiments. Ideally, this should be combined with other HSPC markers such as Tg(cd41:GFP) or Tg(runx1:GFP) - although this could be limited by the authors' access to the lines or time it takes to cross the mutants to the transgenes.
• The link between cx41.8 and Hif1α is tenuous. The authors should perform in situ hybridization for the hif1 genes and their downstream effector notch1 which is known to be important for the HSPC specification (Gerri et al., 2018). The authors might also want to consider performing transcriptomic analysis (bulk RNA sequencing) from purified HSCs in wild types and cx41.8 mutants and assess the downstream pathways affected by the loss of this gene.

Significance

Overall, this study presents another piece of evidence that Connexin 41.8 regulates HSC formation. It provides a potential link between Connexin 41.8, mitochondrial ROS regulation and Hif/hypoxia-sensitive pathways in promoting endothelial-to-hematopoietic transition. The role of the mitochondrial ROS in particular is quite interesting and might provide a new angle into the role of connexins in regulating hemato-vascular development; however, the authors would need to strengthen the link between Cx41.8 and mitochondrial respiration.

It is important to note that the quantitative data in this manuscript need to be strengthened and refined to strengthen the conclusions. The study is not very deeply mechanistic and appears to be more at an observational/correlational level. The manuscript might be of interest for people in the hematopoietic field but does not shed much more insight into the cellular and molecular mechanisms that govern HSC formation, particularly in light of the paper on Cx41.8 role by the same group (Cacialli et al., 2021).

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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:

Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Please place your comments about significance in section 2.

In the manuscript "Regulation of adaptive growth decisions via phosphorylation of the TRAPPII complex in Arabidopsis" the authors investigate the TRAPPII interactome carried out by an already published IP-MS screen. They study previously identified shaggy-like kinases SK as TRAPII interactors and the phosphorylation sites by Y2H (interactions of wild type, deletion mutants and phosphomutants) and kinase assays (in vitro) and pharmacological inhibition in the subunit AtTRS120. The authors provide a deeper phenotypical analysis of trapii null mutant lines and classification as "decision mutants", based on "limited budget" and "conflict of interest" experiments (previously described) as a starting point of investigations of TGN function in comparison with hormone mutants. Cell elongation is used as a response phenotype. Authors focus on mainly TRS120 and phosphorylation by SK and partly on another TRAPP component, CLUB. Authors study the assays with differing kinases, e.g. Y2H with BIN2, phosphorylation with SK11.

Major comments:

• Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

A major issue is that new claims and conclusions are not supported by the new data provided here. The title says "in Arabidopsis", but only components are from Arabidopsis. Interactions, instead, are studied in this manuscript by Y2H in yeast, and phosphorylation in vitro. The abstract is very misleading and does not distinguish which aspects are studied in vitro and which in vivo. The Abstract does not mention that this study is based on previously identified interactome data.

o The figure legends are often not sufficiently detailed to understand what exactly is represented.

Therefore, it is not possible to judge in every case whether experiments are supported by data. E.g.

Fig. 1: A, describe which data were used and which control for IP-MS had been taken into account. B, this is a plot, please describe what is represented. Explain better why Shaggy kinases were chosen. C, explain the principle and what is represented. How is this experiment controlled and how is it ensured that negative results are not caused by absent proteins.

Fig. 2: Indicate the phosphorylation sites in the other subfigures. Fig. 2E: How was it generated, explain what is seen. Since this is the only figure illustrating the protein complex of TRAPP, this figure should be more thoroughly prepared and labeled. I recommend a better visualized protein complex. As before, Fig. 2F remains unclear.

Fig. 3: Please add a figure illustrating the mutations. 3C: what has been diluted? Other examples are found in other figures.

Fig. 4: Shouldn't the wild type be compared with all the mutants? Then statistics have to be conducted accordingly. Better explain G and H. If there are quotients, explain of what exactly.

Fig. 5. Same as before. How do I see that there is a phenotype? There is no comparison with wild type. It is also unclear to which values the statistics refer to.

Fig. 6: Please guide the reader through the figure and experiment.

Fig. 8: I miss the connection with other shaggy-like kinases. This summary could be more complete. What about phosphorylation sites?

o Line 133-134: "we focus on the TRAPPII complex as a starting point as it is required for all aspects of TGN function, including the sorting of proteins such as PINs to distinct membrane domains" I did not find an obvious connection to the PIN transporters as well as clear data to TGN functions. This sentence was for me misleading about the context of this manuscript.

o Figure 1C: A supporting Western Blot control is needed, to fully validate the missing interaction of BIN2 with the truncated variants of TRS120 and CLUB. Additionally, swapping the constructs from DB to AD and vice versa will provide a better set-up of the interaction screen. This should be easily done in a few weeks.

o Line 431-432: "This presents intriguing implications regarding the potential role of the AtSK-TRAPPII module in meeting the unique demands of endomembrane traffic in plants." Why do the authors come to this assumption? Further discussion is needed here.

o Figure 2F: What serves as positive controls? What is the purpose of showing every panel between each TRS120-T2 variant with CLUB-C2, CLUB-C3, TRS120-T1 and TRS120-T3 and not only interactions between BIN2 and the TRS120-T2 variants? Why are there six negative controls as it is every time the same control? - Please request additional experiments only if they are essential for the conclusions. Alternatively, ask the authors to qualify their claims as preliminary or speculative, or to remove them altogether.

Clearly, title, abstract and statements have to be formulated differently. The discussion should contain a limitations paragraph in which the authors detail that conclusions are based on in vitro, yeast and plant IP-MS screening data, and they should describe approaches how the study can be continued in the future. Which alternative explanations are possible. Are SKs and TRAPP expressed and present in the same locations? - If you have constructive further reaching suggestions that could significantly improve the study but would open new lines of investigations, please label them as "OPTIONAL". - Demonstrating interactions and phosphorylation by other approaches in vivo - demonstrating effects of TRAPP phosphomutants and lack of kinases in vivo - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated time investment for substantial experiments. - Are the data and the methods presented in such a way that they can be reproduced?

o Figure S9: Is it not a loss of chlorophyll instead of GFP? Does not look like a fluorescent image.

o Lacking information of pH of in vitro kinase assay solution with Mass-spectrometry.

o What is the purpose of transferring 10 days old seedlings to fresh plates for scanning? Needs additional information for understanding, at the moment it sounds more like unnecessary extra stress for the seedlings.

o Why are seedlings grown under constant light? - Are the experiments adequately replicated and statistical analysis adequate?

o Figure 5: It will be good to use ANOVA for statistics here. I personally doubt the high significance of some parameters, e.g. for club-2 cell width and cell surface area between dark and darkW due to the high standard errors. Rechecking with the original values is necessary. Why is there no comparison between wild-type and the two mutants?

o Figure 7A - C, statistic is probably not correct. For example: in A statistical differences with P<0.001 between wild-type (~100 %) and TRS120SαβγD (~80 %), in C statistical difference of only P<0.05 between wild-type type (90 %) and TRS120SαβγD (60 %)

o No information on IP-MS replicate numbers mentioned.

o Also see comments above to figures

Minor comments:

• Specific experimental issues that are easily addressable.
  • Specific experimental issues that are easily addressable.

o Figure 4, S7, S8, S11 and S12: It will be helpful to support the data with images of the seedlings. - Are the text and figures clear and accurate? Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

o The introduction is quite lengthy with unnecessary information, e.g. about PIN transporters, but useful information about shaggy-like kinases and connection to brassinosteroid signaling is lacking.

o Figure 1C: In the figure legend is no explanation of abbreviation "Co"; no explanation of BET3, TRS31, Tca17 and TRIPP; no indication that spots come from different plates (just visible by different brightness of the squares). Why are there eleven negative controls as it is every time the same control?

o Figure 1C is specifically for BIN2, but BIN2 was not identified in the IP-MS screen represented in Figure 1B. Why does 1C not focus on SK11/12/32, identified in 1B?

o Figure 1C shows several truncated variants of TRS120 and CLUB, a schematic overview as represented in Figure 2A will be helpful for the understanding of 1C. Order of variants should be the same (now: in 1C first TRS than CLUB in 2A first CLUB than TRS).

o Figure 1C: Interaction of TRS120 full-length with BIN2 is missing in this figure but is presented in Figure 2F.

o Result of Figure 2F is described after Figure 3. Better arrangement of Figures or text is needed here.

o Figure 3A: Why was AtSK11 and not BIN2 used for the main figure? Better change Figure 3A with Figure S4 to keep the focus on BIN2. No explanation of the result in the text.

o Figure 3A: In the figure legend is no explanation of abbreviation CBB. What are the non-phosporylated variants? Where are they shown? Description sounds that only TRS120-T2-SαβγA versus TRS120-T2 WT was tested by t-test is this correct? And if yes, why?

o No need for Figure 3B, information was already given in Figure 2A + B.

o Figure 3C: Why BIL2 for Clade II and not BIN2?

o Figure 4: Why are A-E not directly compared to wild-type but trs120-4 as seen in 4F? What is the purpose of using different types of diagram?

o Figure 4H: Why are phyAphyBcry1cry2 and pyrpyl1pyl2pyl4 depicted? No description in the text.

o Figure 6: Confusing order of given information in the figure legend. Sentence one belongs to D and H only, second sentence describes whole figure. o Figure 6D + H, color difference between black and blue is hard to see, better change one into e.g. red.

o Figure 7D - F wrong indication of D to F, named in the description as A) - C). Why is E different to D in F (D and F: 0-1 is attenuated, >1 enhanced; E the other way around).

o Figure S9A: Indication of protein size on the Coomassie gel is missing and the respective position of 160 kDa is not visible on the gel.

o Figure S12D: No explanation of the color code in the figure legend.

o Consistent labelling and layout of all Figures and Supplemental Figures will be helpful. E.g., Figure 3A and S4; in S8A-E + S11A-C bars of different conditions have the same color. Most of the figure legends are quite shortly described and lack information about what kind of data is presented.

o YFP parameters are described in material and methods, but no YFP construct appeared in the manuscript to my knowledge. - Are prior studies referenced appropriately? - Lines 243-245: Text is nearly identical to Kalbfuß et al., 2022. - Lines 246-254: Text is identical to Kalbfuß et al., 2022. - Are the text and figures clear and accurate?

Please see the above and below comments to figures and figure legends. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Overall, the manuscript may have very interesting data and new findings. It is very interesting that the authors study the regulation of a protein complex that may mediate environment responses and intracellular Golgi functions. However, it is very difficult to follow and understand the ideas and concept of the manuscript. This manuscript is based on a previously published interactome study by Rybek et al. 2014, Steiner et al. 2016, Kalde et al. 209. Moreover, a physiological approach is published in Kalbfuß et al. 2022. The outcomes and conclusions from these previously published manuscripts and the emanating open questions addressed here should be clearly described in the introduction. This is currently not the case. Moreover, many experimental approaches and results (e.g. figures, figure legends) are not properly described. Overall, it is therefore not possible to understand the manuscript without studying in depth all other manuscripts. Before the manuscript can be more thoroughly judged, it is necessary that the authors rewrite the manuscript, reorganize it and explain better their ideas and approaches. It is also necessary to explain and define unusual terms such as "decision mutants", "limited budget" and "conflict of interest" experiments, which are crucial for the understanding. The importance of the TRAPPII complex should be illustrated using specific physiological examples and the context in which this complex is studied here has to be explained. Before this is not corrected, the following assessment will remain rather incomplete. Another complication is that two subunits of TRAPP were studied and different types of SKs, however, authors did not systematically analyze all interactions. At least it should be thoroughly described, and a flow chart would be helpful as supplemental figure clearly describe which types of proteins were tested in the different assays. The introduction is not well written. It is very lengthy, however the important messages from previous publications are left out. Thus the open question is not understandable (see above). Instead, the results parts start with introduction again. Explanations are also lacking in every result paragraph on the approach and expected data. The Discussion is also not very well written. It is much focused on physiological and molecular actions and consequences in plants. However, there should be at first a technical discussion on the relevance since in the study is based on in vitro and heterologous expression data, and the physiological analysis was only conducted with knockouts but not phosphomutants. Therefore, the link between the protein interaction and physiological functions needs to be worked out.

Referees cross-commenting

My colleague and I have read thoroughly the manuscript and found a number of issues which we indicated in our review. These points can be fixed by the authors, if they formulate more carefully and remove the overstatements. They should also work on reorganizing and including more explanations.

Significance

Provide contextual information to readers (editors and researchers) about the novelty of the study, its value for the field and the communities that might be interested.

The following aspects are important:

One new aspect of this story is the validation of interaction of TRAPII subunits as substrate for AtSKs and their action as phosphorylation agents shown in vitro. The other new aspect is the phenotypical characterization of trapii mutants under stress-conditions (grown in darkness) and additive stress (with additional drought stress). The potential interaction with brassinosteroid signaling via BIN2 is intriguing.

• General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? A strength is that a new interaction is further studied. A weakness is that the studies are primarily conducted in yeast and in vitro, leaving open how relevant this process is in plants. A strength is further studies and phenotypic analysis of trapii mutant effects. A weakness is that this mutant analysis is disconnected from the action of SKs.

Further, the writing should be improved and more clear (see comments above). - Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...). The introduction gives the impression of a stronger investigation of TGN function, which is from my point of view not the case and should be reformulated and/or put into a deeper context with known literature. The authors switch several times between the different TRAPPII subunits and shaggy-like kinases in the main figures which made it for me very confusing. I believe that rearranging some data/figures will improve the understanding of the story. The text is also lacking explanations of many abbreviations and gene names which caused more difficulties in understanding the story and slowed down the reviewing process. From my point of view it seems to be necessary to read the often cited Kalbfuß et al., 2022 publication before, as many important technical aspects and scientific background, e.g. the reason to use specific control mutants, are well explained there, but are lacking in this manuscript and needs improvement. - Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? Based on the cited literature in this manuscript the direction of the story with "limited budget" and "conflict of interest" situations to classify mutants methodically seems to be a recently emerged approach. Apart from that this manuscript provides only new impact on TRAPII and AtSKs specific knowledge based on well-established and frequently used techniques that address the problem in vitro and in a heterologous system. Therefore, this story will be interesting for researchers specialized in stress responses, TGN and growth defects as well as important for basic research. Limitations in interpretation are present. - Please 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.

Our field of research is related to nutrition-regulated processes especially in Arabidopsis with a strong methodological background in interactomics, physiological, morphological and molecular responses and biochemical approaches and microscopy.

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Referee #2

Evidence, reproducibility and clarity

Summary

This manuscript adopted the concept that plants have cognitive ability and proposed the hypothesis that the trans-Golgi network plays a role in the decision process of cells. It investigates how this organelle function in order to reach the right decision when exposed to the combined drought stress and dark or to germination under osmotic stress. The study tests the hypothesis focusing on the on the TRAPPII complex. The authors demonstrated that defects (mutations) on TRAPPII complex cause wrong growth decisions, particularly when seedling are exposed to decisions with trade-offs.

Major comments

The experiments made for this study are enough to support the conclusions, and they were performed with adequate procedures. I just make the comment that follows.

Lines 468-472: The authors propose that "signal integration and decision-making occur at the AtSK-TRAPPII interface". It should be considered whether the decision is made in a specific step and location or if all the cascade of responses is the decision process. It is proposed that TRAPPII makes the decision and the Rab GTPase cascades (or the downstream signals) implement the decision. The authors demonstrated that a defect on TRAPPII causes wrong-decisions, but what would happen if TRAPPII were normal but something downstream was defective and could would proceed the regular process? Would it also lead to wrong growth decisions? I am afraid that any defect may cause wrong decisions because the decision is the full metabolic process and not a single step in the route.

Minor comments

Lines 259-260: To make it easier to follow the reasoning, the reader should be informed what were the expected responses in case of "primary defects in cytokinesis".

Line 413: Correct Kim et al (2023).

Significance

This study offers an important contribution to the discussion on how plants make decisions. The signals and the cascade of stimuli flows through an intricate network. This study demonstrates that on of the streams of information used for growth decisions passes through the Golgi complex.

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Referee #1

Evidence, reproducibility and clarity

Universally present across the eukaryotic world, TRAPPII is a hetero-oligomeric complex that plays a key role in the regulation of the TGN that has often been classified as a multisubunit tethering complex, although conclusive evidence for the tethering role is still lacking. In contrast, it is well established that the complex acts as a GEF for RAB11, primarily by studies carried out with model fungi such as Saccharomyces cerevisiae and Aspergillus nidulans. Atomic structures have revealed that a few amino acids in one of the subunits of the complex suffice to "kick off" GDP from the active site of the substrate RAB. While some of the subunits are necessary to place the RAB nucleotide binding pocket at the right distance from the key TRAPPII residues on the target membrane, it seems unlikely that the sole function played by this Md complex is catalysing the exchange of GDP by GTP in the target GTPase. In this particular regard, our understanding of other potential physiological roles of the complex is utterly incomplete

This very well written manuscript explores the regulation of TRAPPII by phosphorylation, more precisely, the role of phospho-sites in the regulation of TRS120/TRAPPC9. Using co-immunoprecipitation strategies coupled to mass spectrometry, the authors identified a member of the saggy/GSK family of kinases. Given that the interaction of protein kinases with their substrates is supposed to be transient, this is technically sound result that testifies to the impeccable methodology used by authors. They further exploit MS methodology and two hybrid analysis to identify region of TRAPPC9 interacting with the kinase, as well as the phosphorylated residues. The authors close the circle by establishing that substitutions of these residues result in modified responses to abiotic stresses. Thus, a significant merit of this work is opening up the can of regulation by phosphorylation of TRAPP functions

Experiments/challenges for the future are determining the downstream components that govern these physiological changes in response to phosphorylation of TRAPPII, and expanding these phosphorylation studies to TRAPPIII. This latter complex is involved both in exocytosis and in autophagy, and it seems plausible that alternation between these two different fates is governed by post-translational modifications of the type studied here.

My suggestions to the authors: there has been a burst of atomic structures of TRAPPs recently, with three papers authored by the Fromme, Munro and Sui labs. It mighty worth comparing the longer Trs120 in these structures with the prediction of the shorter protein from Arabidopsis. A very minor point is that possibly the most thorough report on the localisation of TRAPPII to the TGN is that co-signed by Mario Pinar and myself in the Journal of cell science

Referees cross-commenting

I have nothing to add to my review, which was made from the point of view of TRAPP researcher. if my colleagues understand that the manuscript is hyperbolic in places, over statements should be removed

Significance

TRAPPII is regulated by TRAPPC9 phosphorylation in cruciferae. Convincing evidence. Impeccable presentation and writing.

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Reply to the reviewers

Review Commons Refereed Preprint #RC-2023-02149

Dear Reviewers #1 and #2,

We extend our deepest gratitude for your dedication to reviewing our manuscript during such a busy period. We have diligently addressed the insightful feedback provided in our revisions. The variable quality of human fetal tissues, due to fixation and extended preservation times, is acknowledged as a limitation that may affect the quality of our immunostaining results. Despite this, we maintain that the findings from these experiments are crucial for human applications. The extrapolation of the results from mice experiments to human biology is a critical step in propelling research forward. We are confident that our paper, with its acknowledged limitations, still offers valuable contributions to our understanding in this domain.

Please find the primary amendments of our revision detailed below for your review.

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

Summary Yamaguchi et al. performed a comprehensive characterisation of lymphatic vessel development in human embryos, spanning stages C8 to GW9. Through the utilisation of immunohistochemistry targeting proteins expressed in the lymphatic endothelium and blood endothelium, the authors have discerned the presence of lymphatic endothelial cells within the cardinal vein and in extraveinal locations. By systematically analysing the progression of embryonic stages, the authors identified the emergence of lymph sacs. Furthermore, they confirmed the presence of lymphatics in various organs, such as the heart, kidney, lung, and mesentery. However, lymphatics were not detected in the central nervous system during the embryonic stages. At the molecular level, lymphatic endothelial cells express similar factors as in mice, including Prox1, Vegfr3, Lyve1, and PDPN, although the timing and combination of these factors may vary depending on the tissue. This study significantly contributes to our knowledge of lymphatic development in humans.

Major comments Human embryo samples are exceptionally valuable and ethically sensitive, making their maximum utilisation crucial. While the authors conducted a thorough anatomical and molecular analysis, it raises questions about whether more insights can be gleaned.

Specifically, the authors should clarify whether data from embryos collected at CS8-CS10 were processed, and what was the status of venous and lymphatic development?

Response: After a careful review of the clinical data for the specimen previously classified as CS8, we found a record indicating the initial detection of a heartbeat in the preceding week, an observation not made earlier. When correlating the last menstrual period with the morphological features, such as the open neural tube, it suggests that the specimen may actually be at CS 9-10, rather than CS8. We have revised the details in our records to reflect this more accurate staging in Table 1. We have included sections of this particular specimen for Figures for reviewer 1. Despite exhaustive sectioning until the sample was depleted, the heart structure was not located. The developmental stage of the specimen seems comparable to that of a mouse embryo at approximately embryonic day 7.5, evidenced by what appears to be a caudal neuropore. In addition, we observed surrounding blood vessels expressing PECAM, which contained nucleated red blood cells, but these did not exhibit Prox1 expression.

Figure for reviewer 1. Prox1 Expression Pattern in a CS9-10 Human Embryo.

Cross-section of a CS9-10 human embryo. Immunostaining for PECAM and Prox1.

The authors commented that CS11 lymphatic vessels were not identified in the vein. Was there any indication of LECs outside the vein? Could the authors include images of this stage?

Response: The CS11 embryo is depicted in Supplemental Figure 2A-C’. In this section, identification of one side of the precardinal vein was possible. Furthermore, formation of the pharyngeal arch was observed. Prox1 expression was absent in the precardinal vein at this stage.

For embryos at CS12, it would be insightful to know the proportion of LECs versus VECs within the vein, the quantity of LECs outside the veins, and whether there was section-dependent variability in these observations. Response:

For a single section, the numerical data for the right and left anterior cardinal veins were averaged. This process was repeated and the results were then averaged across two sections.

1. The proportion of LECs to VECs within the vein. On average, there were 18.25 nuclei per cross-section of the CV; of these, 4.5 were Prox1-/PECAM+ blood endothelial cells (BECs), and 13.75 were Prox1+/PECAM+ LECs. Therefore, BECs constituted 24.7%, and LECs constituted 75.3%.

The number of LECs outside the veins.

There were an average of 9.75 Prox1+/PECAM+ cells located externally to the CV."

This point is described in Figure 1 legends as follows.

On average, there were 18.25 nuclei per cross-section of the CV; of these, 4.5 were Prox1-/PECAM+ blood endothelial cells (BECs), and 13.75 were Prox1+/PECAM+ LECs. Therefore, BECs constituted 24.7%, and LECs constituted 75.3%. There were an average of 9.75 Prox1+/PECAM+ cells located externally to the CV. (Page 11, lines 486-490)

It would be helpful if Table 1, "Information of human embryos and fetuses", could be complemented with a summary of the main findings at each stage, including which markers LECs expressed and their distribution.

To strengthen the assertion that this study provides unique insights compared to those of mice, a schematic summarizing the similarities and differences between mouse and human observations should be included. Response:

We have enriched the information presented in Table 1 and introduced Figure 5 as a new comprehensive illustration. Figure 5 provides a comparative analysis of lymphatic vessel development between mice and humans, with a particular emphasis on the early stages of development, meticulously summarizing the alterations in lymphatic marker expression at specific stages.

The authors mentioned differences in lymphatic markers at various regions of the embryo and different developmental stages. It is essential to clarify whether all regions express the same markers at the latest developmental stage. Response:

We have added immunostaining for Podoplanin and LYVE1 at GW9 as Supplemental Figure 4X-Y''. This demonstrates the expression of Podoplanin and LYVE1 in lymphatic vessels of the lung, heart, kidney, mesentery, intestinal wall, and lower jaw. This information regarding the expression of LYVE1 and PDPN has also been incorporated into the main body of the text under the section of ‘The Development of Lymphatic Vessels Varies Among Organs’.

A discussion of the limitations of analysing embryos from abnormal pregnancies is necessary. In addition to the determined lack of chromosomal abnormalities, it is crucial to consider phenotypical and morphological integrity. The authors should address the possibility of developmental defects and mutations causing abnormalities in the lymphatic vessels.

Response:

In the "Tissue Collection and Ethical Considerations" section of the Materials and Methods, we have addressed the possibility that developmental defects and mutations may cause abnormalities in the lymphatic vessels.

This is depicted as follows:

Detailed information regarding each sample is presented in Table 1. The sex of each sample was not determined, with the exception of one case of miscarriage. In this particular case, chromosomal analysis verified the absence of any karyotypic abnormalities. There were no malformations observed in any of the embryos or fetuses. Nevertheless, for the remaining embryos, there is a possibility that developmental defects or mutations could lead to abnormalities in the lymphatic vessels. (Page 7, lines340-346)

Minor comments In the abstract, the authors refer to lymphatic malformations as a specific type of lymphatic disease. We recommend acknowledging the broader implications of this study beyond such specific cases.　

Response:

We have modified the concluding paragraph of the Abstract to reflect a more expansive and encompassing narrative as follows.

Our research clarifies the early development of human lymphatic vessels, contributing to a better understanding of the evolution and phylogenetic relationships of lymphatic systems, and enriching our knowledge of the role of lymphatics in various human diseases. (Page2, lines 58-60)

The term "lymph-related disease" should be clarified for better understanding. Response:

To make it clearer, we have modified the last paragraph of the Introduction that includes 'lymph-related disease' as follows.

Our research offers essential insights into the evolution and phylogeny of lymphatic vessels, and may also illuminate the pathogenesis of lymphatic-related diseases, which include lymphedema, obesity, cardiovascular disorders, Crohn's disease, and congenital lymphatic disease, such as lymphatic malformation. (Page 3, lines127-131)

Figure 3S shows kidney samples, not the myocardium or endocardium, as indicated. Response:

No, it is correct. Figure 3P-S represents the heart, which is surrounded by the lungs on both sides. Figure 3S depicts the endocardium, indicating that lymphatic vessels are not present within the endocardial layer.

Reviewer #1 (Significance (Required)):

This study largely reaffirms the existing knowledge from mouse models and previous human data. Given the absence of a cure for lymphatic diseases, gaining a deeper understanding of how lymphatic vessels develop in humans could serve as a crucial stepping stone in this field of research.

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

This study by Yamaguchi et al., explores the progression of lymphatic vessel growth in different stages of human embryos. They also try to identify the origin of the lymphatic vessels in different organs. The study first shows that lymphatic endothelial cells (LECs) first show up in the anterior cardinal veins (ACVs) of CS12 in human embryos, which is similar to what is known to occur in mouse embryos. They also checked whether the PROX1+ LECs of the heart are derived from Flk1+/Isl+/PECAM- cells. However, Flk1+/Isl+/PECAM- cells do not co-express PROX1. These results suggest that in human embryos LECs originate from the ACVs. The authors then identify that lympho-venous valves formed between lymph sacs and the cardinal veins at around Carnegie Stage (CS)18. The valves have showed obvious bicuspid shape at Gestational week (GW)9. Finally, the authors demonstrate that the development of lymphatic vessels happens at different time points in various organs. At CS16, lymphatic vessels and LECs can be detected in the lower jaw, heart and the lungs; mesenteric and intestinal lymphatic vessels can be detected between CS17 and CS18; kidney lymphatic vessels can be found at CS23; At GW9, the lymphatic vessels are observed around the aorta, which may combine to form the future thoracic duct. Together, this informative study sheds light on the progression of lymphatic vasculatures during embryonic stage in humans.

This study has many strengths, in addition to some areas that if addressed, would further increase the impact of the findings. These include:

1. Since immunostaining is the major method that the authors have used for their work, they could use positive and negative controls (secondary antibody only or IgG control) for different antibodies. The authors can also show some Isl1 and Flk1 staining in GW9 fetus or adult tissue, like PROX1 or LYVE1 in Supplemental figure 1.

Response:

We have introduced new Supplemental Figures 1I-N. Included are negative controls for fluorescent staining with only the secondary antibody (Supplemental Figure I-I’’’’) and for DAB staining with only the secondary antibody (Supplemental Figure J-L). Furthermore, we have added images showing Flk1 staining within lymph sacs (Supplemental Figure 1M) and Isl1 staining (Supplemental Figure 1N). Flk1 expression was confirmed in the lymph sacs; however, Isl1 expression was not observed.

The description regarding the negative controls is as follows.

Additionally, the specificity of the staining was confirmed with controls using only the secondary antibodies (Supplemental Figure 1I-L). (Page 3, lines146-147)

The description regarding Flk1 and Isl1 in the lymph sac is as follows.

Additionally, at GW9, Flk1 expression was detected in the cervical lymph sac, but Isl1 expression was not (Supplemental Figure 1M and N). (Page4, lines186-187)

Figures 1 F-H, S' and S", U', U", and U'" are hard to appreciate. Can the authors offer higher quality images or show some confocal images?

Response:

In response to the reviewer's comments, we conducted several trials to improve image quality. However, due to fixation issues, we were unable to enhance the quality beyond the original for the CS12 specimen. Therefore, all images except those of VEGFR3 have been left unchanged. It is possible that the quality appeared reduced in the initial submission due to compression, making them difficult to view. We will resubmit without reducing the image quality as much as possible and ask for your understanding in this matter. Additionally, the CS12 specimen was very small, and there was a limited number of sections available, making further attempts challenging. This is also a limitation of research using human embryos. Regarding Figure 1R-U’’’, we have revised and replaced the images, although the quality has not significantly changed. We believe this may also be due to the compression of the image quality at the time of submission. There is no change in the conclusions drawn.

According to the author's previous publications (ref 17 and 30) and literature (ref 31), Flk+/Isl+/PECAM- cells differentiate into LECs. However, in this work they did not observe any PROX1+Isl1+ cells at CS13 and CS14. I am curious to know if they found any PROX1+Isl1+ cells at later time points such as GW9.

Response:

Isl1 is posited to be an early transcription factor that directs the differentiation of undifferentiated mesodermal cells towards a cardiac lineage. Our prior research utilizing tamoxifen-inducible mice indicated that a cohort of cells expressing Isl1 at a defined interval (E6.5 to E9.5 in mice) contributes to the formation of lymphatic structures in the head, neck, mediastinum, and heart before subsequently losing this expression(Maruyama et al., eLife, 2022). However, in human studies, it is not possible to trace the lineage and differentiation trajectories of Isl1+ cells. Consequently, we anticipated finding LECs that initially express Isl1 in the embryonic stage, with this expression diminishing as development ensues. Nevertheless, such cell groups were not observed in human embryos. In mice, our search for cells concurrently expressing Isl1, Prox1, Flk1, or PECAM from E9.0 to E11.5 (referenced in Maruyama et al., eLife, 2022, Supplemental Figure 3) also yielded no such populations. This evidence suggests that Isl1 protein expression in the cardiac pharyngeal mesoderm likely ceases during the differentiation into lymphatic endothelium. Given the hypothesis that Isl1+/Prox1+ LECs might exist at an earlier developmental stage, we examined specimens from CS16, 17, and 18 for the presence of such LECs but to no avail. This investigation has been documented as Supplemental Figure 3Q-S for the CS16 sample. With the GW9 sample, due to its substantial size, we initially conducted a DAB staining search for lumen structures that might express Isl1. However, no such structures were identified. Moreover, despite conducting triple immunostaining for PECAM, Isl1, and Prox1, we were unable to locate any LECs or lymphatic vessels expressing Isl1.

The description regarding Isl1 and Prox1 expression for CS16 and GW9 is as follows:

At CS16, cells co-expressing Prox1 and Isl1 were not observed in the lower jaw or the cardiac outflow tract regions (Supplemental Figure 3Q-S'). Additionally, at GW9, Flk1 expression was detected in the cervical lymph sac, but Isl1 expression was not (Supplemental Figure 1M and N). (Page 4, lines184-187)

For the GW9 stage, we have provided images of lymphatic vessels in the lung and heart stained with PECAM, Isl1, and Prox1 as a Figure for the reviewer's consideration.

Figure for reviewer 2. Isl1 is not expressed in GW9 lymphatic vessels.

Fluorescent immunostaining of PECAM, Prox1, and VEGFR3 was conducted at GW 9 fetuses. Scale bars 100μm.

Figure 3 N and O show comparable VEGFR3+PROX1+ cell numbers in different time points, however it shows increased VEGFR3+PROX1+ vessel numbers. If so, do LECs become more elongated and form the vessel-like structures?

Response:

In our previous findings (Maruyama et al., Dev bio, 2019, Maruyama et al., iScience, 2021), we documented that surrounding the heart, LECs progressively interconnect to form a reticular network, which is subsequently remodeled into more substantial lumen-bearing vessels. This sequence appears to be conserved in humans, with LECs initially presenting as solitary entities that gradually interlace into a network. Presumably, a portion of this network is then streamlined, giving rise to increasingly luminal structures. Therefore, while the count of LECs remains constant, there is an augmentation in the number of defined luminal vessels. This observation has been depicted as follows.

Throughout this process, the initially mesh-like capillary lymphatics undergo progressive remodeling to establish lumen-bearing vessels. Consequently, while the density of LECs per unit area remains relatively stable, there is an increase in the number of lymphatic vessels possessing distinct luminal structures (Figure 3N and O). (Page 5, lines 220-223)

The authors have mentioned that the staging of the embryos and fetuses was done by Carnegie stage and clinical information. The authors should offer more detailed information about those embryos and fetuses. For example, crown-rump length, menstrual weeks, craniofacial features etc. This information will be useful for other researchers in this field.

Reply:

We have substantially expanded the data presented in Table 1 regarding embryos and fetuses. For specimens dating back over 15 years, some lacked echo graphic details. In those instances, we estimated the developmental stage by integrating available data, such as the date of the last menstrual period or morphological features of the fetus. For a case initially assessed as CS 8, which had no recorded cardiac activity in the preceding week, a subsequent ultrasound noted a heartbeat. Considering this alongside the specimen's size, we revised the estimated stage to CS 9-10, correlating with the onset of heart formation. Despite exhaustive sectioning of this particular embryo until the samples were depleted, the heart structure remained undetected. Nevertheless, taking into account morphological observations, such as an open neural tube, the stage was adjudged to be CS9-10. Furthermore, for ectopic pregnancies, which frequently necessitated emergency surgeries due to symptoms like abdominal pain or bleeding, preoperative embryonic data was often unavailable.

Reviewer #2 (Significance (Required)):

Strengths: Very informative results for human embryonic lymphatic development. They have performed the experiments at various developmental stages.

Limitations: Image quality need to be improved. Many high magnification images are not clear. Human samples come from certain diseases, which might have affected the embryo's development.

Advance: this study clarified the process of early lymphatic vessel formation in human embryos.

Audience: clinical and basic science in developmental biology and lymphatic biology.

Reviewer expertise: lymphatic development, lymphatic biology, vascular biology.

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 #2

Evidence, reproducibility and clarity

This study by Yamaguchi et al., explores the progression of lymphatic vessel growth in different stages of human embryos. They also try to identify the origin of the lymphatic vessels in different organs. The study first shows that lymphatic endothelial cells (LECs) first show up in the anterior cardinal veins (ACVs) of CS12 in human embryos, which is similar to what is known to occur in mouse embryos. They also checked whether the PROX1+ LECs of the heart are derived from Flk1+/Isl+/PECAM- cells. However, Flk1+/Isl+/PECAM- cells do not co-express PROX1. These results suggest that in human embryos LECs originate from the ACVs. The authors then identify that lympho-venous valves formed between lymph sacs and the cardinal veins at around Carnegie Stage (CS)18. The valves have showed obvious bicuspid shape at Gestational week (GW)9. Finally, the authors demonstrate that the development of lymphatic vessels happens at different time points in various organs. At CS16, lymphatic vessels and LECs can be detected in the lower jaw, heart and the lungs; mesenteric and intestinal lymphatic vessels can be detected between CS17 and CS18; kidney lymphatic vessels can be found at CS23; At GW9, the lymphatic vessels are observed around the aorta, which may combine to form the future thoracic duct. Together, this informative study sheds light on the progression of lymphatic vasculatures during embryonic stage in humans.

This study has many strengths, in addition to some areas that if addressed, would further increase the impact of the findings. These include:

1. Since immunostaining is the major method that the authors have used for their work, they could use positive and negative controls (secondary antibody only or IgG control) for different antibodies. The authors can also show some Isl1 and Flk1 staining in GW9 fetus or adult tissue, like PROX1 or LYVE1 in Supplemental figure 1.
2. Figures 1 F-H, S' and S", U', U", and U'" are hard to appreciate. Can the authors offer higher quality images or show some confocal images?
3. According to the author's previous publications (ref 17 and 30) and literature (ref 31), Flk+/Isl+/PECAM- cells differentiate into LECs. However, in this work they did not observe any PROX1+Isl1+ cells at CS13 and CS14. I am curious to know if they found any PROX1+Isl1+ cells at later time points such as GW9.
4. Figure 3 N and O show comparable VEGFR3+PROX1+ cell numbers in different time points, however it shows increased VEGFR3+PROX1+ vessel numbers. If so, do LECs become more elongated and form the vessel-like structures?
5. The authors have mentioned that the staging of the embryos and fetuses was done by Carnegie stage and clinical information. The authors should offer more detailed information about those embryos and fetuses. For example, crown-rump length, menstrual weeks, craniofacial features etc. This information will be useful for other researchers in this field.

Significance

Strengths: Very informative results for human embryonic lymphatic development. They have performed the experiments at various developmental stages.

Limitations: Image quality need to be improved. Many high magnification images are not clear. Human samples come from certain diseases, which might have affected the embryo's development.

Advance: this study clarified the process of early lymphatic vessel formation in human embryos.

Audience: clinical and basic science in developmental biology and lymphatic biology.

Reviewer expertise: lymphatic development, lymphatic biology, vascular biology.

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Referee #1

Evidence, reproducibility and clarity

Summary

Yamaguchi et al. performed a comprehensive characterisation of lymphatic vessel development in human embryos, spanning stages C8 to GW9. Through the utilisation of immunohistochemistry targeting proteins expressed in the lymphatic endothelium and blood endothelium, the authors have discerned the presence of lymphatic endothelial cells within the cardinal vein and in extraveinal locations. By systematically analysing the progression of embryonic stages, the authors identified the emergence of lymph sacs. Furthermore, they confirmed the presence of lymphatics in various organs, such as the heart, kidney, lung, and mesentery. However, lymphatics were not detected in the central nervous system during the embryonic stages. At the molecular level, lymphatic endothelial cells express similar factors as in mice, including Prox1, Vegfr3, Lyve1, and PDPN, although the timing and combination of these factors may vary depending on the tissue. This study significantly contributes to our knowledge of lymphatic development in humans.

Major comments

Human embryo samples are exceptionally valuable and ethically sensitive, making their maximum utilisation crucial. While the authors conducted a thorough anatomical and molecular analysis, it raises questions about whether more insights can be gleaned.

Specifically, the authors should clarify whether data from embryos collected at CS8-CS10 were processed, and what was the status of venous and lymphatic development?

The authors commented that CS11 lymphatic vessels were not identified in the vein. Was there any indication of LECs outside the vein? Could the authors include images of this stage?

For embryos at CS12, it would be insightful to know the proportion of LECs versus VECs within the vein, the quantity of LECs outside the veins, and whether there was section-dependent variability in these observations.

It would be helpful if Table 1, "Information of human embryos and fetuses", could be complemented with a summary of the main findings at each stage, including which markers LECs expressed and their distribution.

The authors mentioned differences in lymphatic markers at various regions of the embryo and different developmental stages. It is essential to clarify whether all regions express the same markers at the latest developmental stage.

To strengthen the assertion that this study provides unique insights compared to those of mice, a schematic summarising the similarities and differences between mouse and human observations should be included.

A discussion of the limitations of analysing embryos from abnormal pregnancies is necessary. In addition to the determined lack of chromosomal abnormalities, it is crucial to consider phenotypical and morphological integrity. The authors should address the possibility of developmental defects and mutations causing abnormalities in the lymphatic vessels.

Minor comments

In the abstract, the authors refer to lymphatic malformations as a specific type of lymphatic disease. We recommend acknowledging the broader implications of this study beyond such specific cases.

The term "lymph-related disease" should be clarified for better understanding.

Figure 3S shows kidney samples, not the myocardium or endocardium, as indicated.

Significance

This study largely reaffirms the existing knowledge from mouse models and previous human data. Given the absence of a cure for lymphatic diseases, gaining a deeper understanding of how lymphatic vessels develop in humans could serve as a crucial stepping stone in this field of research.

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Reply to the reviewers

The authors do not wish to provide a response at this time since our responses contain graphs and tables that might contain formatting errors in the conversion process.

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Referee #3

Evidence, reproducibility and clarity

The authors characterized circRNAs that can escape degradation in cells infected by alpha-, beta and gamma herpesviruses both in cultured cells and in mice. During lytic infection, ten circRNAs were modulated across the virus subfamilies, and 67 circRNAs were upregulated after virus infection or treatment with interferon- or interferon-. The authors examined in detail interferon-induced circRNA circRELL1 and noted that this circRNA suppresses lytic infection, likely by interacting with the mTOR pathway and promoting cell proliferation. They also made the astonishing observation that the circRNAs were more resistant to cleavage by virus-encoded nucleases than their linear counterparts. This is a comprehensive study that reveals circRNA key players that control lytic and latent herpesvirus infections.

Comments:

1. Linear mRNA abundances are decreased after infection, but linear-derived circRNA abundances are upregulated. What determines increased circRNA abundances when their linear counterparts become limiting? Is the rate of splicing/back-splicing altered in infected cells? Is nuclear-cytoplasmic transport of circRNAs changed?
2. CircRELL1 loss of function experiment: Does the employed siRNA affect the abundance of linear RELL1 mRNA?
3. CircRELL1 gain of function experiment: How was this performed?
4. Why are circRNA and, especially circRELL1, resistant to degradation in interferon-treated cells when OAS genes, and presumably RNAseL, are upregulated?

Significance

This study enhances our knowledge of circRNAs in viral infections.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In this manuscript, Dremel et al explore the interplay between herpesvirus and circRNAs. This team has been a pioneer in the field and has made important discoveries about the regulation of circRNAs during herpesviral infection. While past work focused on the gamma-herpesviruses, here in this study, they expand their work to alpha and beta HV as well as extending their findings into animal models. They found consistent increase in CircRNA levels and found that these circRNAs are mostly resistant to viral-induced RNA decay. They then uncover that these circRNA can be induced by interferon which indicates that circRNAs could act as a first line of anti-viral defense. Consistently, they found that circRELL1, previously identified as a circRNA inhibiting KSHV lytic infection, can also restrict HSV-1. This seemingly conserved anti-viral capacity could point to an evolutionarily conserved mechanism of defense against infection. This study combines together an impressive amount of sequencing data and elegantly draws parallels between the various HV. While this is a complex story, bringing together expression levels of mRNA, circRNA and even diving into miRNA networks, this is extremely well written and as a reader, you feel transported into a well-crafted journey that keeps uncovering novel and exciting findings.

Major comments:

• there is a back and forth between the HVs that are included in the study: fig 1 has HSV, CMV and KSHV; while fig 2 is HSV, KSHV and MHV68. For clarity and consistency, the authors should consider including all 4 representative HV in their figures.
• this might be a misunderstanding that just needs clarification: CIRCScores provide a measure of CircRNA reads over their linear counterparts: during host shutoff, the linear counterpart would likely decrease and therefore the CIRCscore would artificially go up. So the fact that the CIRCscore remains constant over lytic reactivation in KSHV and MHV68, wouldn't that indicate that instead the CircRNA level go down?
• what happens to circRNAs in HCMV infection as they do not encode an endoRNase?
• line 238: the authors should discuss why CpG and poly I:C treatment largely failed to induce expression of CircRELL1
• line 289: if CircRELL1 is induced in response to infection, it could be interesting to induce its expression after infection (maybe a DOX-inducible promoter on the lentivirus) instead of prior to infection (which might hinder infection and hide more significant effects later).
• line 329: the authors mention that the mRNA targets of SOX carry a "degenerate motif": do the circRNA downregulated during KSHV infection contain such motif?

Minor comments:

• figure 3B should show p-values
• figure 3B: showing expression levels of the endoRNases could provide some context for the extent of their effect
• I would refrain from using sentences referring to phenotype "trending upward" which basically reflects that the results are not significant in either upward or downward direction.

Significance

CircRNAs are only beginning to emerge as important regulators of gene expression in cells. Only recent developments in sequencing technology have allowed scientists to even detect the presence of these small RNA. Their roles and mechanism of induction remain largely uncharacterized, let alone in the context of viral infection. This team has pioneered the exploration of CircRNA in KSHV and is now poised to extend their findings to other members of the herpesvirus family. This study will be of interest to a broad audience, both virologist looking to better understand the viral-host battle during infection and RNA biologists seeking to better characterize how gene expression can be controlled with circRNA. There is also major therapeutic potential with these types of approaches.

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Referee #1

Evidence, reproducibility and clarity

The manuscript by Dremel et al reports on IFN-induced circRNAs that are produced in response to herpesviral infections and that are resistant to virus-mediated degradation (e.g. host shut-off). They provide a wealth of interesting data on circRNA production changes in response to infection with alpha, beta, and gamma herpesviruses and identify a number of host circRNAs that are commonly regulated across all subfamilies. Using circRELL1 as an example, they demonstrate a modest impact on productive HSV-1 infections (which follows up on their previous report of circRELL1 impacting KSHV lytic infection). They subsequently propose a new model in which a subset of IFN-stimulated genes produce both mRNAs and circRNAs with the potential for antiviral activity, the latter operating as a 'workaround' for avoiding virus-mediated shutoff.

Major Comments

• Line 146: The authors extended their analysis to HSV-1 latently infected mouse trigeminal ganglia but potentially missed a trick but not including an analysis of HSV-1/VZV infected human trigeminal ganglia for which potentially compatible datasets are available (PMID: 29563516).
• Line 264: The authors note that a direct relationship in gene expression changes was observed between some circRNAs and mRNAs and not others. However, a gene level analysis may be problematic here as many genes encode multiple distinct transcript isoforms that are variably regulated e.g. during infection. A transcript level analysis (e.g. using Kallisto/Salmon) might enable the authors to specifically link circRNAs with individual mRNA isoforms which would be valuable information in the context of interferon-driven gene expression. Alternatively, the lack of a direct relationship in gene expression changes may also link to variability in circRNA decay / halflives. The authors could potentially solve this using a metabolic labelling approach to measure mRNA and circRNA decay rates for a subset of the genes of interest.
• Line 273: The weak element in the paper relates to the role of circRELL1 in restricting HSV-1 productive infections. The effects observed are modest at best and the biological impact appears limited. It is also entirely unclear how circRELL1 might act to restrict HSV-1. The paper would significantly benefit from the authors extending their analysis to include 2-3 additional circRNAs that are commonly regulated by herpesviruses to determine (i) whether similar effects are observed and (iii) to determine whether a compound effect can be achieved by targeted silencing of multiple IFN-responsive circRNAs at the same time.

Minor comments

• Line 55: To this reviewers knowledge, only eight routinely infect humans (HSV1, HSV2, VZV, HCMV, HHV6, HHV7, EBV, and KSHV. It's possible the authors are considering HHV6A and HHV6B as distinct but this is not really the case.
• Line 57: As written it implies that therapeutic agents capable of clearing VZV exist which is not really the case.
• Line 132: The authors inclusion of previously published data (e.g. HCMV) along with reams of their own makes for a compelling analysis.
• Line 582: A number of the sequencing datasets are not yet publicly available. This should be rectified before publication.

Significance

It is clear that a lot of work has gone into this manuscript and there a reams of data that will provide a great resource for mining to the wider herpesvirus community. While this naturally leads to a more descriptive nature, it does not undermine the value of the data. However, as indicated below, more functional validation is required if this work is to provide a significant step forward in our understanding of how and why IFN-induced circRNAs might be important for combating viral infections.

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Reply to the reviewers

We have thoroughly revised the manuscript, taking into account all comments from all four reviewers. We have added new data (Supplemental Figure 2 and Supplemental Figure 4) in response to these comments.

Reviewer 1

The assessment of data reproducibility is currently uncertain due to the absence of replication and statistical analysis in the dataset. It is essential to provide explicit information regarding sample sizes or replicates for all data and figures, data should be presented as mean +/- SD/SEM, and the interpretation of results should be grounded in rigorous statistical analysis. The lack of experimental replicates and statistical analysis in most of the figures presented raises major concerns regarding the validity of the result.

We have now added error bars for the graphs in Figure 3D, E, F, G, H; Figure 4 D, F, G, H, I, J; Figure 5 B, C, D, E, F, G; and Figure 6B, C, D. All GTPase assays have repeated three times. The mean ± S.D. (n = 3) is plotted for each condition. For high-speed pelleting assays, all assays have been conducted three times, and a representative assay is shown.

Why was only one of the MiD proteins, specifically MiD49, studied, while MiD51 was not includedin the investigation?

This is an excellent point. In our previous work (doi:10.1101/2023.07.31.551267), we found that MiD49 and MiD51 were strikingly similar in their abilities to activate Drp1 after their own activation with fatty acyl-CoA. We feel that the demonstration here with MiD49 suggests that a similar effect would occur with MiD51. Due to time constraints for the lead author, preparing more MiD51 protein was out of the scope of what could be done. We now add a line in the Discussion that results for MiD51 may be different.

The author suggestion of Drp1 phosphorylation, based on the mobility of protein observed in SDS-PAGE gel (fig 4A, 5A, 6A), is not a sufficiently valid assessment. While western blot analysis is a valid method to assess Drp1 phosphorylation, it is essential to include replicates for semi-quantitation and demonstrate the reproducibility of the results. Moreover, it is recommended to incorporate Western blot analyses to provide additional support for the findings presented in Figures 5 and 6.

• We agree with the reviewer that additional information on the phosphorylation state of these proteins should be provided. We now include phospho-proteomic analysis for Erk2 phosphorylation of WT Drp1 and Drp1-S600D (Supplemental Table 1), showing that S579 is by far the predominant phosphorylation site. For WT Drp1, three lines of evidence now suggest efficient Erk2 phosphorylation of S579:
• Western blot using anti-phosphoS579
• Phosphoproteomic analysis
• Gel shift

For the Drp1-S600D phosphorylation, we have phosphoproteomic and gel shift analysis. For isoform 6, we regrettably only have gel shift. However, given the fact that the effect of Erk2 treatment on actin-stimulated GTPase activity mimics what we found for WT-Drp1 and for Drp1-phosphoS579/S600D, we think it is highly likely that the equivalent phosphorylation (S629 in this case) has been affected.

Data on phosphorylated peptides with replicates experiments should be presented.

We now present these data, which have been significantly expanded since the initial submission (new Supplemental Table 1). While non-phophorylated S579 is still detected in both the WT and S600D phosphorylation reactions, the phosphorylated peptide is 2.2 and 2.3-fold more abundant, respectively. Our conclusion is that Erk2 efficiently phosphorylates S579, although stoichiometric phosphorylation was not obtained here. We have added statements in the relevant sections of the Result, and in the Methods. We have also added Supplemental Table 1 to show the spectral counts obtained from phospho-proteomic analysis, and have deposited the raw data files with the PRIDE consortium (access information in the Methods).

Please provide additional context or specific details about the GFP-tagged Drp1 protein, such as the protein site where GFP was attached, as well as whether this tag could potentially impact the Drp1 GTPase activity and oligomerization. Figure 7C and D appear to suggest an increase in the GTPase activity of the GFP-Drp1 protein.

We have now added these details to the Methods section, and have also added the complete amino acid sequence for the final purified construct in Supplemental Figure 4. We have also added that a previous study (PMID: 32901052) found that inclusion of GFP strongly inhibited Drp1 GTPase activity. We do not observe this effect here or in a previous study (PMID: 27559132), and provide possible reasons for this difference in the Methods. The reviewer points out that the activity of GFP-Drp1 appears higher than that of un-tagged Drp1 (comparing 7C with 7D). We find that the GTPase activity of Drp1 alone varies between 1 and 2 uM/min/uM protein depending on the preparation. This variation occurs for both untagged and GFP-tagged Drp1. This difference in basal activity from prep-to-prep might relate to differences between protein preparations, or exact amount of time required to freeze the aliquots of purified protein (we freeze small aliquots ( An optional experiment that would significantly enhance the biological relevance of the findings presented in the current study is to assess the morphology of mitochondria in cells expressing the phospho-mimetic mutant Drp1 proteins. This experiment would provide valuable insights into the functional consequences of Drp1 S579 and S600 phosphorylation on mitochondrial structure and dynamics.

We fully agree that these would be valuable experiments. The issue is that a large number of experiments using phospho-mimetic mutants in cells have already been conducted, with varying results (Taguchi et al., 2007; Qi et al., 2011; Yu et al., 2011; Strack et al., 2013; Kashatus et al., 2015; Serasinghe et al., 2015; Xu et al., 2016; Brand et al., 2018; Han et al., 2020, Chang and Blackstone, 2007; Cribbs and Strack, 2007; Cereghetti et al., 2008; Wikstrom et al., 2013, Han et al., 2008，Wang et al., 2012 Jhun BS, Sheu, 2018, J Physiol). To conduct more targeted tests examining specific forms of Drp1 activation in cells (for example, through Mff, MiD proteins, actin, or cardiolipin) will require extensive work that is outside the scope here. Our feeling is that S579 phosphorylation is likely to recruit another molecule (probably a protein) that has an activating effect. We tried to test one possibility (NME3, mentioned in the Discussion) but failed to produce useable NME3 protein for these tests and, given time constraints for the lead author, could not address this further.

Provide reference for method on actin polymerization.

We have now added a reference in the ‘Actin preparation for biochemical assays’ section of the Methods (PMID 16472659).

Rectify the error in referencing figure 3 panels within the figure legends of Supplemental Fig S1.

Thank you, we have changed this.

The inclusion of full length isoform 6 is commendable. However, there is no mentioned of isoform6 in the method section.

Thank you for pointing this out. We have added description of the construct and referenced our previous paper that used it.

Since papers deposited in bioRxiv have not undergone peer review, reference #7 should not becited as references in scholarly work.

Reference 7 has so far been reviewed by a peer-review journal. e are addressing reviewers’ concerns and will re-submit soon. We do not know how to rectify the issue of referencing this work, because it describes an extensive amount of groundwork for the MiD proteins. Our hope is that this work will be in press by the time the work reviewed here is ready for publication.

Please provide details about the calculation of GTPase activity and the distinctions between the specific GTPase activity and total GTPase activity shown in figure 8D-F.

We now describe these calculations in the “GTPase assay” section of the Methods.

Reviewer 2

Overall, the experiments described here are carried out with rigor and the conclusions drawn are of significance to understanding how phosphorylation regulates Drp1 functions.

Thank you for these kind comments!

Phosphorylation of both the serine residues appears to elicit a common effect in that they inhibitDrp1's stimulated GTPase activity. This would suggest that phosphorylation affects Drp1's self-assembly as tightly packed helical scaffolds. Instead of sedimentation analysis, an EM analysis of helical scaffolds on cardiolipin-containing membrane nanotubes or in the presence of soluble adaptors causing Drp1 to form filaments would provide a direct readout for defects in self-assembly.

This is an excellent point, and we would love to conduct this work. Given our current EM infrastructure and expertise, these experiments would take extensive time for us to do. We do have a collaborator who could carry these out, but feel that the time it would take even for them to do this correctly is beyond that which we have (the lead author is transitioning to their next career phase). We have added the point that further EM studies of this type are necessary to test the effect on Drp1 assembly more directly.

I am not sure of the rationale for experiments reported in Fig. 7 and 8. If the idea was to test if hetero oligomerization with WT Drp1 rescues defects associated with phosphorylated Drp1 then this could be stated explicitly in the manuscript. GFP-Drp1 is used as a WT mimic but a previous report (PMID: 30531964) indicates that this construct is severely defective in stimulated GTPase assays, much like the K38A mutant. But the rationale of using these constructs is not quite apparent. Is the intention to test if defects seen in the phospho-mimetic mutants of Drp1 can be rescued by the presence of a 'seed' of WT Drp1. If so, then this could be stated explicitly in the manuscript. But regardless, I am not quite sure what this data set achieves in terms of addressing mechanism.

We apologize for not being clearer in our explanation of these experiments. Our goal was to test the effects of partial Drp1 phosphorylation on overall Drp1 activity, which likely mimics more accurately the cellular situation (wherein only a portion of the Drp1 population is likely to be phosphorylated even upon kinase activation). We now discuss these experiments in a clearer manner. For the GFP-Drp1, we do not observe the effect on GTPase activity shown in that previous manuscript by another laboratory, either here or in previous studies (eg, PMID: 27559132). In the Methods, we now provide a discussion of these differences and possible reasons for them, as well as providing the complete amino acid sequence of our GFP-fusion construct in Supplemental Figure 4.

Finally, it would have been nice to see if the phospho-mimetic mutants of Drp1 produce the same effects on mitochondrial structure as those reported earlier. Reanalyzing their effects in a cellular assay becomes important because it would consolidate this work for the readers to evaluate the'true' effects of phosphorylation on Drp1 functions. If the phospho-mimetic mutants fare in a manner like those previously reported, then it signifies that stimulation in GTPase activity is not a readout that directly correlates with Drp1 functions. If not, then the results presented here would establish a comprehensive analysis of in vitro biochemical activities and in vivo functions of the phospho-mimetic mutants.

We fully agree that these would be valuable experiments. The issue is that a large number of experiments using phospho-mimetic mutants in cells have already been conducted, with varying results (Taguchi et al., 2007; Qi et al., 2011; Yu et al., 2011; Strack et al., 2013; Kashatus et al., 2015; Serasinghe et al., 2015; Xu et al., 2016; Brand et al., 2018; Han et al., 2020, Chang and Blackstone, 2007; Cribbs and Strack, 2007; Cereghetti et al., 2008; Wikstrom et al., 2013, Han et al., 2008，Wang et al., 2012 Jhun BS, Sheu, 2018, J Physiol). To conduct more targeted tests examining specific forms of Drp1 activation in cells (for example, through Mff, MiD proteins, actin, or cardiolipin) will require extensive work that is outside the scope here. Our feeling is that S579 phosphorylation is likely to recruit another molecule (probably a protein) that has an activating effect. We tried to test one possibility (NME3, mentioned in the Discussion) but failed to produce useable NME3 protein for these tests and, given time constraints for the lead author, could not address this further.

Previous work reports that the effect of actin on the GTPase activity of Drp1 is biphasic but the binding to actin is not. This is quite confounding, and the authors could perhaps explain why this is the case.

The reviewer makes an excellent point, which we now explain further in the manuscript. We have also discussed this in doi:10.1101/2023.07.31.551267 (see Figure 2D in that work). Our interpretation is that it is the density of Drp1 bound to the actin that provides the activation, by positioning the GTPase domains in close proximity. As the amount of actin increases, the Drp1 becomes more dispersed on the filaments, and activation decreases. We observe the same effect for MiD49 and MiD51 oligomers (see the above-mentioned reference).

The manuscript cites PMID: 23798729 for expression analysis of slice variants but PMID:29853636 provides a more compressive analysis. The authors could cite this work.

Thank you for this reference. We were unaware of it, but are very glad to know of it now. We now include this reference. In particular, in the legend to Figure 1C (table of splice variants), we now state that this table is for human Drp1, and that additional splice variants have been identified for murine Drp1 (PMID 29853636).

Reviewer 3

The splendid results of the manuscript willbe interesting to the researchers in the related fields.

Thank you for this nice comment!

The manuscript provided well-organized biochemistry results for comparisons between phosphorylation of Drp1 S579 and S600. It is the reviewer's comments that the authors may include experiments that manipulate Drp1 phosphorylation at different amino acids in cells. Such experiments will provide strong support for this manuscript.

• We fully agree that these would be valuable experiments. The issue is that a large number of experiments using phospho-mimetic mutants in cells have already been conducted (Taguchi et al., 2007; Qi et al., 2011; Yu et al., 2011; Strack et al., 2013; Kashatus et al., 2015; Serasinghe et al., 2015; Xu et al., 2016; Brand et al., 2018; Han et al., 2020, Chang and Blackstone, 2007; Cribbs and Strack, 2007; Cereghetti et al., 2008; Wikstrom et al., 2013, Han et al., 2008，Wang et al., 2012 Jhun BS, Sheu, 2018, J Physiol). To conduct more targeted tests examining specific forms of Drp1 activation in cells (for example, through Mff, MiD proteins, actin, or cardiolipin) will require extensive work that is outside the scope here. Our feeling is that S579 phosphorylation is likely to recruit another molecule (probably a protein) that has an activating effect. We tried to test one possibility (NME3, mentioned in the Discussion) but failed to produce useable NME3 protein for these tests and, given time constraints for the lead author, could not address this further.

  The authors discussed the known factors that involved in Drp1 activation, such as its receptors, actin and cardiolipin. Recent JCB paper (J. Cell Biol. 2023 Vol. 222 No. 10 e202303147) indicates that intermembrane space protein Mdi1/Atg44 may play a role in coordinating mitochondria fission with Dnm1 (Drp1 in yeast cells). It will be valuable if the manuscript could also discuss the potential factor.

• Thank you for this comment. We now include Mdi1/Atg44 as a possible factor that might be influenced by Drp1 phosphorylation. Two points we would like to make here are: there doesn’t seem to be an Mdi1 homologue in mammals, so the equivalent factor must be identified before testing; and Mdi1 is an inter-membrane space protein, so any effect of Drp1 phosphorylation on coordinated functioning with Mdi1 would either require an intermediary factor or exposure of the IMS in some way.

  Keywords cannot represent the manuscript. It is recommended that the authors use other words to for the current manuscript.

We have removed K38A from this list. The other key words are not mentioned in the Abstract.

Reviewer 4

The authors showed that the binding of Drp1 to actin depends on salt concentrations (Fig. 2Band C). In the presence of 65 mM NaCl, the phosphomimetic mutants showed decreased binding to actin. The GTPase assay is performed with 65 mM KCl, in which actin did not stimulate GTP hydrolysis of the phosphomimetic mutants. In contrast, with 140 mM NaCl, the S579D Drp1 exhibits slightly enhanced actin binding compared to WT Drp1. Could the authors assess the actin-activated GTPase activity in the 140 mM salt condition to test if actin activates GTP hydrolysis ofS579D Drp1 more potently than WT?

This is a good point by the reviewer. However, with limited time for the first author, we chose to focus on the reviewer’s other comments (see below).

Both phosphomimetic mutants show reduced activation for GTP hydrolysis in the presence of cardiolipin, Mff, and MiD49. Is this because the mutants have a lower affinity for these interactors? Or do they bind with the same affinity but experience diminished activation? The data suggests the latter scenario, potentially resulting from decreased oligomerization properties. Can the authors provide more insights on this, for example, by measuring their interaction in the presence of GMP- PCP, which fully induces oligomerization in all three forms of Drp1?

• These are interesting ideas, and we conducted experiments similar to what the reviewer described: co-sedimentation experiments with combinations of Drp1 and Mff under three nucleotide states: no nucleotide, GMP-PCP, and GTP. We used Mff for these experiments because we have this protein in abundance, and have previously characterized this construct as a trimer in PMID 34347505. We use a high concentration of Mff (50 mM) versus Drp1 (1.3 mM) because of the relatively low affinity between the two proteins (shown in PMID 34347505). We find the following:
• In the absence of nucleotide, Mff does not cause an increase in pelletable Drp1 for any of the Drp1 constructs.
• In the GTP state, the presence of Mff greatly increases the amount of Drp1 in the pellet, suggestive of increased Drp1 oligomerization. This effect occurs for all Drp1 constructs (WT, S579D and S600D mutants), but the amounts of both Drp1 and Mff in the pellets are about 50% less for both mutants than for the WT construct. This result suggests a decrease in oligomerization for the mutants, but not necessarily a decrease in Mff binding.

I'm curious what happens to oligomerization if GTP is added instead of nonhydrolyzable GMP-PCP (Fig. 1D). Does this lead to higher oligomerization in the mutants compared to WT since the mutants seem to have lower GTPase activity? This might explain why phosphorylation increases mitochondrial localization of Drp1 in cells seen in some studies.

This is another interesting thought, and we describe the new experiments we conducted in the response to the previous comment. Essentially, while GTP does cause a slight increase in pelletable Drp1, the increase is somewhat similar for all constructs. As described in the last comment, the addition of Mff causes a substantial increase in pelletable Drp1 for both WT and the mutants. This result suggests that, while the basal oligomeric state of Drp1 (in the absence of nucleotide) is reduced for the mutants (our original analytical ultracentrifugation data), the mutants appear to be capable of responding to GTP and Mff in a similar manner to WT. We acknowledge that the assay used here (pelleting) lacks the precision required to draw detailed conclusions on oligomerization or interaction with Mff, and we try to reflect this in our discussion of the data. We do feel, however, that these data are useful to report, in guiding future study.

Please include the number of experimental repeats and error bars where applicable.

We have now added number of experimental repeats and error bars for the graphs in Figure 3D, E, F, G, H; Figure 4 D, F, G, H, I, J; Figure 5 B, C, D, E, F, G; and Figure 6B, C, D.

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Referee #4

Evidence, reproducibility and clarity

During mitochondrial division, a mechanochemical GTPase, Drp1, interacts with its receptor proteins, phospholipids, and the actin cytoskeleton. These interactions regulate the mitochondrial recruitment of Drp1 and its activities, including oligomerization and GTP hydrolysis. Drp1 undergoes serine phosphorylation at two primary sites (S579 and S600 in human isoform 3). It has been suggested that S579 phosphorylation activates Drp1, while S600 phosphorylation inhibits Drp1. However, the biochemical effects of these phosphorylations on Drp1's activity are mostly unexplored. The current study by Liu et al. addresses this crucial question in extensive biochemical assays using recombinant proteins. First, the authors showed that phosphomimetic Drp1 mutations (S579D or S600D) have a reduced ability to oligomerize. Second, both mutants exhibited decreases in their activation for GTP hydrolysis by actin, and concurrently, they demonstrated reduced binding to actin. Third, the Drp1 phosphomimetic mutants showed decreased activation for GTP hydrolysis by cardiolipin and two receptor proteins, Mff and MiD49. This reduction was also evident when Mff was combined with actin. The authors confirmed these results by phosphorylating WT Drp1 at S579 in vitro using the protein kinase Erk2. The effects of phosphorylation seem consistent across Drp1 isoforms with different alternative exons.

Specific comments

1. The authors showed that the binding of Drp1 to actin depends on salt concentrations (Fig. 2B and C). In the presence of 65 mM NaCl, the phosphomimetic mutants showed decreased binding to actin. The GTPase assay is performed with 65 mM KCl, in which actin did not stimulate GTP hydrolysis of the phosphomimetic mutants. In contrast, with 140 mM NaCl, the S579D Drp1 exhibits slightly enhanced actin binding compared to WT Drp1. Could the authors assess the actin-activated GTPase activity in the 140 mM salt condition to test if actin activates GTP hydrolysis of S579D Drp1 more potently than WT?
2. Both phosphomimetic mutants show reduced activation for GTP hydrolysis in the presence of cardiolipin, Mff, and MiD49. Is this because the mutants have a lower affinity for these interactors? Or do they bind with the same affinity but experience diminished activation? The data suggests the latter scenario, potentially resulting from decreased oligomerization properties. Can the authors provide more insights on this, for example, by measuring their interaction in the presence of GMP-PCP, which fully induces oligomerization in all three forms of Drp1?
3. I'm curious what happens to oligomerization if GTP is added instead of nonhydrolyzable GMP-PCP (Fig. 1D). Does this lead to higher oligomerization in the mutants compared to WT since the mutants seem to have lower GTPase activity? This might explain why phosphorylation increases mitochondrial localization of Drp1 in cells seen in some studies.
4. Please include the number of experimental repeats and error bars where applicable.

Significance

Overall, the current study provides a comprehensive set of biochemical data for the role of Drp1 phosphorylation using cutting-edge in vitro assays. One might expect that S579 phosphorylation would enhance some of Drp1's action while S600 phosphorylation would show the opposite impact. Unexpectedly and interestingly, the authors found that both phosphorylations decrease Drp1's activities. Therefore, this work significantly advances our mechanistic understanding of mitochondrial division.

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Referee #3

Evidence, reproducibility and clarity

Summary

The manuscript aimed to clarify the effects of Drp1 phosphorylation on its activation under different factors, such as receptors, actin and cardiolipin. The manuscript performed experiments with purified proteins to examine the correlation of protein-protein interactions and enzymatic activity. The authors specifically focused on the phosphorylation of s S579 and S600 of Drp1 isoform 3, which is the most abundant in HeLa, HL60 and PC12 cells. The results demonstrated the difference of post-translational modification on S579 and S600. The manuscript went further to suggest that additional factors may exist for the Drp1 activation by S579 phosphorylation.

Major Concerns

1. The manuscript provided well-organized biochemistry results for comparisons between phosphorylation of Drp1 S579 and S600. It is the reviewer's comments that the authors may include experiments that manipulate Drp1 phosphorylation at different amino acids in cells. Such experiments will provide strong support for this manuscript.
2. The authors discussed the known factors that involved in Drp1 activation, such as its receptors, actin and cardiolipin. Recent JCB paper (J. Cell Biol. 2023 Vol. 222 No. 10 e202303147) indicates that intermembrane space protein Mdi1/Atg44 may play a role in coordinating mitochondria fission with Dnm1 (Drp1 in yeast cells). It will be valuable if the manuscript could also discuss the potential factor.

Minor Concerns

Keywords cannot represent the manuscript. It is recommended that the authors use other words to for the current manuscript.

Significance

The authors provided a model for Drp1 catalytic activity. The splendid results of the manuscript will be interesting to the researchers in the related fields.

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Referee #2

Evidence, reproducibility and clarity

The results presented here indicate that phosphorylation of either serine residue negatively affects Drp1's tendency to oligomerize and substantially reduces stimulation of its GTPase activity in the presence of actin, adaptor proteins and cardiolipin-containing vesicles.

Overall, the experiments described here are carried out with rigor and the conclusions drawn are of significance to understanding how phosphorylation regulates Drp1 functions.

Major Comments:

1. Phosphorylation of both the serine residues appears to elicit a common effect in that they inhibit Drp1's stimulated GTPase activity. This would suggest that phosphorylation affects Drp1's self-assembly as tightly packed helical scaffolds. Instead of sedimentation analysis, an EM analysis of helical scaffolds on cardiolipin-containing membrane nanotubes or in the presence of soluble adaptors causing Drp1 to form filaments would provide a direct readout for defects in self-assembly.
2. I am not sure of the rationale for experiments reported in Fig. 7 and 8. If the idea was to test if hetero oligomerization with WT Drp1 rescues defects associated with phosphorylated Drp1 then this could be stated explicitly in the manuscript. GFP-Drp1 is used as a WT mimic but a previous report (PMID: 30531964) indicates that this construct is severely defective in stimulated GTPase assays, much like the K38A mutant. But the rationale of using these constructs is not quite apparent. Is the intention to test if defects seen in the phospho-mimetic mutants of Drp1 can be rescued by the presence of a 'seed' of WT Drp1. If so, then this could be stated explicitly in the manuscript. But regardless, I am not quite sure what this data set achieves in terms of addressing mechanism.
3. Finally, it would have been nice to see if the phospho-mimetic mutants of Drp1 produce the same effects on mitochondrial structure as those reported earlier. Reanalyzing their effects in a cellular assay becomes important because it would consolidate this work for the readers to evaluate the 'true' effects of phosphorylation on Drp1 functions. If the phospho-mimetic mutants fare in a manner like those previously reported, then it signifies that stimulation in GTPase activity is not a readout that directly correlates with Drp1 functions. If not, then the results presented here would establish a comprehensive analysis of in vitro biochemical activities and in vivo functions of the phospho-mimetic mutants.

Minor comments:

1. Previous work reports that the effect of actin on the GTPase activity of Drp1 is biphasic but the binding to actin is not. This is quite confounding, and the authors could perhaps explain why this is the case.
2. The manuscript cites PMID: 23798729 for expression analysis of slice variants but PMID: 29853636 provides a more compressive analysis. The authors could cite this work.

Significance

This manuscript reports an extensive and systematic evaluation of the effects of serine phosphorylation on Drp1's GTPase activity in the presence of actin, adaptor proteins and cardiolipin-containing vesicles. Drp1 is predominantly phosphorylated at two sites, S579 and S600 (numbering based on isoform 1). A large body of literature indicates that phosphorylation at S579 activates Drp1 functions while phosphorylation at S600 inhibits Drp1 functions. But as the authors point out, the effects of phosphorylation on the biochemical functions of Drp1 have not been reported, which is what the present manuscript does.

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Referee #1

Evidence, reproducibility and clarity

Summary

The present study aims to delineate the effect of S579 and S600 phosphorylation on Drp1 oligomerisation and GTPase activity. Using phospho-mimetic mutant Drp1 proteins, in conjunction with GTPase activity and phosphorylation assays, as well as size exclusion chromatography, the authors conclude that phosphorylation of residue S579 does not activate Drp1 directly. Notably, the authors did not perform cell-based assays to assess mitochondrial fission. The abstract concludes by stating, "our results suggest that nearest neighbour interactions within the Drp1 oligomer affect catalytic activity". However, this assertion appears to lack clarity and direct support from the presented results. Further clarification or evidence linking the observed data to this conclusion would enhance the overall comprehensibility and validity of the study's findings.

Major comments

• The assessment of data reproducibility is currently uncertain due to the absence of replication and statistical analysis in the dataset. It is essential to provide explicit information regarding sample sizes or replicates for all data and figures, data should be presented as mean +/- SD/SEM, and the interpretation of results should be grounded in rigorous statistical analysis. The lack of experimental replicates and statistical analysis in most of the figures presented raises major concerns regarding the validity of the result.
• Why was only one of the MiD proteins, specifically MiD49, studied, while MiD51 was not included in the investigation?
• The author suggestion of Drp1 phosphorylation, based on the mobility of protein observed in SDS-PAGE gel (fig 4A, 5A, 6A), is not a sufficiently valid assessment. While western blot analysis is a valid method to assess Drp1 phosphorylation, it is essential to include replicates for semi-quantitation and demonstrate the reproducibility of the results. Moreover, it is recommended to incorporate Western blot analyses to provide additional support for the findings presented in Figures 5 and 6.
• Data on phosphorylated peptides with replicates experiments should be presented.
• Please provide additional context or specific details about the GFP-tagged Drp1 protein, such as the protein site where GFP was attached, as well as whether this tag could potentially impact the Drp1 GTPase activity and oligomerisation. Figure 7C and D appear to suggest an increase in the GTPase activity of the GFP-Drp1 protein.
• An optional experiment that would significantly enhance the biological relevance of the findings presented in the current study is to assess the morphology of mitochondria in cells expressing the phospho-mimetic mutant Drp1 proteins. This experiment would provide valuable insights into the functional consequences of Drp1 S579 and S600 phosphorylation on mitochondrial structure and dynamics.

Minor comments

• Provide reference for method on actin polymerisation.
• Rectify the error in referencing figure 3 panels within the figure legends of Supplemental Fig S1.
• The inclusion of full length isoform 6 is commendable. However, there is no mentioned of isoform 6 in the method section.
• Since papers deposited in bioRxiv have not undergone peer review, reference #7 should not be cited as references in scholarly work.
• Please provide details about the calculation of GTPase activity and the distinctions between the specific GTPase activity and total GTPase activity shown in figure 8D-F.

Significance

The current investigation holds promise for advancing our understanding of the impact of post-translational modifications, specifically those occurring at the S579 and S600 sites, on Drp1 activity. Nevertheless, the absence of experimental replication and comprehensive statistical analysis introduces notable concerns regarding the credibility and replicability of the findings.

Audience: Basic research that focus on mitochondrial morphology and Drp1 biology.

I lack expertise in velocity analytical ultracentrifugation and, as a result, am unable to provide an assessment regarding the validity and accuracy of the assay.

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Reply to the reviewers

Replies to Reviewers

Thank you for inviting us to submit our revised manuscript titled, “Diffusive mediator feedbacks control the health-to-disease transition of skin inflammation.” We appreciate the time and effort the editor and each of the reviewers have dedicated to providing insightful feedback on ways to strengthen our manuscript. The revisions in the main text in response to the detailed comments are highlighted in red and were proofread by professional English editors. We hope that our revision and responses address all the concerns raised by the reviewer, and we look forward to hearing from you regarding this submission.

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

The manuscript provides a model of interacting populations of pro- and anti-inflammatory mediators to explain spatial patterns associated with various inflammatory conditions. The work is robust and articulated well, and is certainly scientifically relevant.

Authors: Thank you for your positive evaluation and many insightful comments on our manuscript. We have incorporated your feedback, and hope that our revisions satisfy all the comments.

Minor amendments:

Personally, I feel that the model should be reported prior to the results, as the choice of model is likely to have great significance on the observations. It would be preferable for the reader to have a clear picture of the governing equations in their mind as they digest the results.

Au: Following this reviewer's suggestion, we have relocated the Method section including the model description to be written prior to the Result section (p.9-14 lines 152-232; revised manuscript).

The literature review is largely relatively thorough; however, I think it is important that the previous works of Joanne Dunster (University of Reading) and collaborators are included, as these are very closely related to this work. In particular, the authors should note the following two papers, which take a spatial approach:

• Bayani, A., Dunster, J.L., Crofts, J.J. et al. Mechanisms and Points of Control in the Spread of Inflammation: A Mathematical Investigation. Bull Math Biol 82, 45 (2020). https://doi.org/10.1007/s11538-020-00709-y

• Bayani A, Dunster JL, Crofts JJ, Nelson MR (2020) Spatial considerations in the resolution of inflammation: Elucidating leukocyte interactions via an experimentally-calibrated agent-based model. PLoS Comput Biol 16(11): e1008413. https://doi.org/10.1371/journal.pcbi.1008413

Au: We have incorporated this comment by adding the two suggested papers to the relevant sentences in the literature review (p.6 line 118-119; revised manuscript) as follows: “Previous reaction-diffusion models, including chemotactic cells, have reproduced the resolution of inflammation in the lung [Bayani et al. 2020a, Bayani et al. 2020b]”

One key point that should be mentioned in the discussion is that the model neglects any immune cells (e.g. neutrophils, macrophages) which contribute greatly to the inflammatory condition. Since these cells are motile, and also can contribute both pro- and anti-inflammatory effects, they are likely to influence spatial patterns significantly. It is not necessarily a problem that these aren't included in the model, but I feel that it is important that their omission be discussed in the manuscript.

Au: We have now discussed the immune cells in the “Future implications” as the reviewer suggested (p.29 line 477-483; revised manuscript) as follows: “This is probably because the present model focuses on the non-chemotactic cells (e.g., including keratinocytes), whereas chemotactic cells (e.g., macrophages and neutrophils) also contribute to skin inflammation [Zhang and An 2007, Coondoo 2011]. Moreover, the present model focuses on the innate immune response, whereas the skin initiates an acquired immune response in the persistence of the innate immune response. Therefore, incorporating the chemotactic cells and acquired immune response into the model will reproduce the end of the expansion.”

Reviewer #1 (Significance (Required)):

The manuscript advances our current understanding of spatially spreading inflammation and corresponding patterns, but needs to be contextualized against existing literature as described above.

This manuscript will appeal to theoreticians (Mathematicians) and clinicians/experimentalists alike.

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

The authors propose a minimal mechanistic mathematical model able to reproduce qualitatively different spatial patterns observed in healthy and disease epidermis. The starting point is a systematic review of medical images of different dermatological conditions, which they classify and successfully capture according to the spatial patterns. It is an interesting piece of work, but I consider that it will gain significance if the theoretical results are compared again with the clinical data. Specifically, the authors show a very interesting map between parameter regions and different spatial patterns; this result should be compared back to clinical data, to confirm that specific changes in spatial patterns indeed result from predicted changes in a specific parameter (e.g., due to a genetic condition that affects a feedback strength).

Authors: We thank you for providing your valuable comments on our manuscript.

Following your suggestion about the comparison of theoretical results with the clinical data, we have predicted which specific parameters including the feedback strength cause specific transitions of spatial patterns in the respective diseases. The discussion was added on p.26 lines 415-438 in the revised manuscript as follows: “The parameter-to-patterning correspondence (Fig. 4A, B, S2 Fig., and S3 Fig.) allows us to infer the pathogenesis mechanism in various diseases exhibiting each of diverse expanding patterns (seen in Table 2). For instance, psoriasis exhibits all five expanding patterns (Table 2) and increased levels of pro-inflammatory mediator (TNF-α) [Ringham et al. 2019], which is consistent with our theoretical results. The elevated pro-inflammatory mediator in psoriatic skin has been suggested to be caused by genetic mutations affecting regulatory feedback [Valeyev et al. 2010]. Considering these previous studies, our model predicts a psoriasis progression where fading pattern transits to arcuate, polycyclic, gyrate, annular, and circular pattern where increase in the TNF-α level is possibly due to mutation-induced alteration in the feedback parameters, e.g., increase of the production of pro-inflammatory mediator qa (Fig. 4A). Alternatively, Lyme disease exhibits circular, annular, and polycyclic patterns (Table 2). A clinical report showed that patients in Missouri predominantly exhibit an annular pattern without prognostic symptoms, while those in New York tend to exhibit a circular pattern with prognostic symptoms following the same treatment [Wormser et al. 2005]. Considering our theoretical result that the overproduction of pro-inflammatory mediators and the depletion of anti-inflammatory mediators leads to the annular and circular pattern, respectively (Fig 4, 5A, and B), altered levels of pro-inflammatory and anti-inflammatory mediators may significantly impact the development and prognosis of Lyme disease in Missouri and New York patients, respectively.

These qualitative parameter estimations will be verified in the future through parameter quantification in each diseased skin exhibiting any expanding patterns. By incorporating this quantitative correspondence between patterns and parameters measured in each disease into the present model, we would develop each disease-specific model with a quantitative predictability of how much change of the skin parameters transit from healthy to diseased pattern or vice versa. Therefore, this study provides the first step to controlling the healthy-to-diseased transition of skin inflammation via diffusive mediator feedback.”

Another shortcoming of this work is that some of the conclusions are rushed: the parameter-to-spatial patterns analysis would strongly benefit from adding a quantitative to the qualitative description, e.g., mapping how changes in a given parameter value results in gradual changes in fading speed. Along the same line, the stability analysis for the different fading pattens was performed only for selected parameter values, it is not clear how variations in parameter values affect the sizes of the basins of attraction of the different steady states; we want to make sure that the parameter values were not cherry-picked. Further, given that the authors show bistability for some parameter values, then the dependency on initial conditions on the final spatial pattern should be more extensively investigated.

Au: We have incorporated these comments by adding a quantitative description including new results and future research strategies following each of the three constructive suggestions raised by the reviewer.

First, regarding “the fading speed” the reviewer suggested, fading speed is affected by changes in parameters involved in mediator production. In particular, the speed is reduced by an increase in the production parameters of pro-inflammatory mediators (pa, qa) and a decrease in those of anti-inflammatory mediators (pi, qi) (Fig.2. C and D). Moreover, “the size of the basins” the reviewer pointed out corresponds to the distance between ST (Threshold) and SH (Healthy state) in the cases with excitability. The distance between ST and SH becomes closer indicating the health state being less stable when pro-inflammatory mediators (pa, qa) increase or anti-inflammatory mediators (pi, qi) decrease from the healthy fading pattern. The imbalance of the mediator production transits the fast fading pattern with a small trajectory into a slow fading pattern with a larger trajectory. As imbalance goes on, the expanding pattern appears in the order of arcuate, polycyclic, and gyrate (Fig. 5). In cases with bistability, the size of basins corresponds to the relative distance ST to SH and ST to SI (Inflamed state). The circular and annular patterns appear when the distance between ST and SH is closer. On the other hand, when the distance between ST and SI was closer, the inflamed area shrank rather than expanded. The shrinking pattern appeared by reducing the production of pro-inflammatory mediators (pa, qa) or increasing the production of anti-inflammatory mediators (pi, qi) under conditions of stability. We have added a new figure and described this finding in Results (p.24 lines 384-388; revised manuscript) as follows: “As a result, we found that the distance between the healthy state (SH) and the threshold state (ST, a closer unstable steady state to SH) was the smallest in the gyrate pattern and increased in the order of polycyclic, arcuate, slow fading pattern, and fast fading pattern (Fig. 5C–F, S4 Fig. B and C). The fast fading pattern showed a smaller trajectory (green curve in S4 Fig. B and C) of change in the mediator concentration than the slow fading pattern.”

Second, regarding “the dependency on initial conditions”, we have further added a new result (p.24 line 374-382; revised manuscript) as follows: “The number of stable states determines the pattern regardless of the initial condition in the spatial distribution of mediator concentration. Similar to the fading pattern (Fig. 2), the arcuate, polycyclic, and gyrate patterns with the excitability appeared reproducibly, independently of the initial conditions due to a single stable state SH (Fig. 5C-F). Even in circular and annular patterns with bistability where the threshold ST was closer to the inflamed state SI than the healthy state SH (Fig. 5A-B), the final spatial pattern was dominated by the SI independently of the initial condition. On the contrary, when ST was closer to the SH than the SI, the inflamed area shrank rather than fading (S4 Fig. A). These results are general outcomes of the traveling wave of bistable systems [Murray 2002], and consistent with the previous theoretical studies on inflammations [Sudo and Fujimoto 2022, Volpert 2009]. ”

Finally, we have added “a quantitative to the qualitative description as a future research strategy (p.27 line 432-438; revised manuscript) as follows: “These qualitative parameter estimations will be verified in the future through parameter quantification in each diseased skin exhibiting any expanding patterns. By incorporating this quantitative correspondence between patterns and parameters measured in each disease into the present model, we would develop each disease-specific model with a quantitative predictability of how much change of the skin parameters transit from healthy to diseased pattern or vice versa. Therefore, this study provides the first step to controlling the healthy-to-diseased transition of skin inflammation via diffusive mediator feedback.”

For reproducibility it is essential that the authors add a much more detailed description of the methods, including the software tools / numerical analysis tools used. Making the code publicly available would also be very beneficial to ensure the reproducibility of the results.

Au: Following your suggestion, we have added a description of the methods, including the simulation code, to the “Methods” (p.13 lines 231-232; revised manuscript) as follows: “A simulation code written in C language is available from GitHub: https://github.com/MakiSudo/Erythema-Patterns/blob/main/AInondim.c.”

In conclusion, the work is very interesting and worth publishing, but requires (a) to come back to the clinical data for validation of model predictions, (b) a more thorough and quantitative investigation of the effects of parameter variations on model behaviors, (c) a more rigorous and systematic presentation of the methods, (d) carefully explaining how the proposed model is similar / differs to the classical activator -inhibitor model proposed by Turing, and (e) discussing / showing if the fading patterns result from a turning instability.

Au: For (a) “validation of model predictions,” (b) “model behaviors,” and (c) “a more rigorous and systematic presentation of the methods,” we have reflected your suggestions in the revised manuscript as described above.

Regarding (d) and (e), we have added an explanation of “how the proposed model is similar/differs to the classical activator–inhibitor model” and “if the fading patterns result from Turing instability” after the model construction in Methods (p.11-12 line 210-216; revised manuscript) as follows: “Reaction terms of this model are similar to the classical activator-inhibitor model proposed by Turing [Turing 1952], which includes the negative feedback of the activator through the inhibitor and the positive feedback of the activator. These reaction terms potentially result in Turing instability. However, the present model setting does not show Turing instability. The reason is that Turing instability requires a large difference between the diffusion coefficients of the activator and inhibitor [Murray 2002], whereas these coefficients in the present model were set to be equal based on molecular findings that these molecular weights are close in proximity [Coondoo 2011]. ”

**Referees cross-commenting**

I agree with the comments from Reviewer #1.

Reviewer #2 (Significance (Required)):

The work aims to bridge mathematical modelling to dermatological practice, which is much needed to enable the use of theoretical and computational tools to clinical decision-making. While some mathematical models of skin inflammation have been proposed in the past (refer to papers from the RJ Tanaka group in systems dermatology), most of these do not consider explicitly the spatial component, which is crucial for modelling the clinically visible spatial patterns. Potentially interested audience includes biomathematicians, systems biologists, systems dermatologists, and, if the validation of the model predictions is achieved (as suggested above), also dermatologists.

I am a systems biologists working on multi-scale mechanistic mathematical modelling of epithelial tissue diseases. The work I just reviewed falls exactly within my area of expertise.

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Referee #2

Evidence, reproducibility and clarity

The authors propose a minimal mechanistic mathematical model able to reproduce qualitatively different spatial patterns observed in healthy and disease epidermis. The starting point is a systematic review of medical images of different dermatological conditions, which they classify and successfully capture according to the spatial patterns. It is an interesting piece of work, but I consider that it will gain significance if the theoretical results are compared again with the clinical data. Specifically, the authors show a very interesting map between parameter regions and different spatial patterns; this result should be compared back to clinical data, to confirm that specific changes in spatial patterns indeed result from predicted changes in a specific parameter (e.g., due to a genetic condition that affects a feedback strength). Another shortcoming of this work is that some of the conclusions are rushed: the parameter-to-spatial patterns analysis would strongly benefit from adding a quantitative to the qualitative description, e.g., mapping how changes in a given parameter value results in gradual changes in fading speed. Along the same line, the stability analysis for the different fading pattens was performed only for selected parameter values, it is not clear how variations in parameter values affect the sizes of the basins of attraction of the different steady states; we want to make sure that the parameter values were not cherry-picked. Further, given that the authors show bistability for some parameter values, then the dependency on initial conditions on the final spatial pattern should be more extensively investigated.

For reproducibility it is essential that the authors add a much more detailed description of the methods, including the software tools / numerical analysis tools used. Making the code publicly available would also be very beneficial to ensure the reproducibility of the results.

In conclusion, the work is very interesting and worth publishing, but requires (a) to come back to the clinical data for validation of model predictions, (b) a more thorough and quantitative investigation of the effects of parameter variations on model behaviors, (c) a more rigorous and systematic presentation of the methods, (d) carefully explaining how the proposed model is similar / differs to the classical activator -inhibitor model proposed by Turing, and (e) discussing / showing if the fading patterns result from a turning instability.

Referees cross-commenting

I agree with the comments from Reviewer #1.

Significance

The work aims to bridge mathematical modelling to dermatological practice, which is much needed to enable the use of theoretical and computational tools to clinical decision-making. While some mathematical models of skin inflammation have been proposed in the past (refer to papers from the RJ Tanaka group in systems dermatology), most of these do not consider explicitly the spatial component, which is crucial for modelling the clinically visible spatial patterns. Potentially interested audience includes biomathematicians, systems biologists, systems dermatologists, and, if the validation of the model predictions is achieved (as suggested above), also dermatologists.

I am a systems biologists working on multi-scale mechanistic mathematical modelling of epithelial tissue diseases. The work I just reviewed falls exactly within my area of expertise.

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

The manuscript provides a model of interacting populations of pro- and anti-inflammatory mediators to explain spatial patterns associated with various inflammatory conditions. The work is robust and articulated well, and is certainly scientifically relevant.

Minor amendments:

Personally, I feel that the model should be reported prior to the results, as the choice of model is likely to have great significance on the observations. It would be preferable for the reader to have a clear picture of the governing equations in their mind as they digest the results.

The literature review is largely relatively thorough; however, I think it is important that the previous works of Joanne Dunster (University of Reading) and collaborators are included, as these are very closely related to this work. In particular, the authors should note the following two papers, which take a spatial approach:

• Bayani, A., Dunster, J.L., Crofts, J.J. et al. Mechanisms and Points of Control in the Spread of Inflammation: A Mathematical Investigation. Bull Math Biol 82, 45 (2020). https://doi.org/10.1007/s11538-020-00709-y
• Bayani A, Dunster JL, Crofts JJ, Nelson MR (2020) Spatial considerations in the resolution of inflammation: Elucidating leukocyte interactions via an experimentally-calibrated agent-based model. PLoS Comput Biol 16(11): e1008413. https://doi.org/10.1371/journal.pcbi.1008413

One key point that should be mentioned in the discussion is that the model neglects any immune cells (e.g. neutrophils, macrophages) which contribute greatly to the inflammatory condition. Since these cells are motile, and also can contribute both pro- and anti-inflammatory effects, they are likely to influence spatial patterns significantly. It is not necessarily a problem that these aren't included in the model, but I feel that it is important that their omission be discussed in the manuscript.

Significance

The manuscript advances our current understanding of spatially spreading inflammation and corresponding patterns, but needs to be contextulised against existing literature as described above.

This manuscript will appeal to theoreticians (Mathematicians) and clinicians/experimentalists alike.

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Reply to the reviewers

1. General Statements [optional]

Thank you for the constructive comments and suggestions from the reviewers to further strengthen our manuscript (RC-2023-02156) entitled, “CNTN4 modulates neural elongation through interplay with APP”. In response to the reviewer’s comments, we have outlined the following revision plan. Please find the point-by-point responses to the reviewer comments in red. All the additions and changes in the manuscript are shown as track changes. We trust that the revised manuscript and revision plan will meet the approval of the editor and reviewers. We would also be glad to respond to any further questions and comments that you may have.

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 2 6) Figure 8 C-E shows a reduction of APP mRNA in SH-SY5Y knockdown of CNTN4 and a reduction CNTN4 mRNA in SH-SY5Y knockdown for APP. These data suggest might suggest that "interaction between CNTN4 and APP contributes to their gene expression". However, this observation needs to be proved mainly in the CNTN4 and APP KO mice.

Thank you for your insightful comment. We recognize the importance of validating this observation in CNTN4 and APP knockout mice. In line with your suggestion, we are currently conducting these experiments and plan to incorporate the results into our revised manuscript.

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

Reviewer #1 Page 12, lines 7-9. The conclusion here is that CNTN4 KO and APP KO phenotypes are different. But a more interesting way to look at it is that the Scholl analysis of dendrites shows that they are almost exactly the reverse of each other with regard to near and distal morphologic differences. That could be interesting. Maybe CNTN4 binding inhibits APP signaling or binding to another partner, or APP binding inhibits CNTN4 signaling or binding to another partner, or both. Then loss of either one would hyper-activate the signal induced by the other and give the observed yin-yang phenotypic relationship. I note that this would not fit with the neuroblastoma phenotypes, which seem to be in the same direction; but a developing brain is different in many ways from a neuroblastoma cell in culture. The Discussion is also somewhat vague about possible interpretations of the two phenotypes in vivo.

Thank you for your valuable insights. In response to your comments, we have expanded our discussion (line 420) to include the following considerations: “Our hypothesis is that when CNTN4 is deficient there are two possibilities considered, 1) the function to which the binding of CNTN4 to APP contributes is lost, and the ability of CNTN4 to regulate dendritic spine formation diminishes which would cause abnormal neurite outgrowth (Figure 8); 2) the loss of CNTN4 would cause other proteins to alternately bind to the E1 domain of APP and affect neurite outgrowth and arborization. For example, the arborization trends of the near and distal Sholl apical and basal dendrites are the opposite of one another in the Cntn4- and App-deficient mice, respectively. Loss of either CNTN4 or APP may activate these opposing scenarios through inhibition of signaling, binding to another partner or both. However, further studies are needed to understand the interplay.”

Reviewer #1 Where is APP normally expressed in the developing mouse brain? A few sentences in the introduction or discussion would be helpful. This information was provided for Cntn4 in the introduction.

Thank you for this suggestion. We have now included important background information on APP expression in the Introduction (line 95): “Osterfield et al. has previously shown a direct binding between CNTN4 and transmembrane amyloid-beta precursor protein (APP). Expression of APP in mice has been observed early in development, and is ubiquitously expressed in adult mice (45).”

Reviewer #1 Minor grammatical items.

Page 3, line 6. "Over 1000 genes..."

Page 4, line 17. "...battery to study Cntn4-deficient mice, which revealed subtle..."

Page 5. First sentence in the Results section. "the cortical layer thickness is involved in migration" - that phrase needs to be reworked.

Page 6, line 16. "total numbers of cells or of neurons"

Page 8, line 12. "maturity morphologies" - that phrase needs to be reworked.

Page 8, line 16. "In vitro primary cell culturing..." should be "Primary cell culturing...". After all, the only kind of cell culturing is in vitro.

Thank you for pointing out these grammatical issues. We appreciate your attention to detail and have carefully revised each of the mentioned sections in the manuscript to ensure clarity and accuracy. The corrections have been implemented as follows:

Page 3, line 6: The phrase "Over 1000 genes..." has been added into line 52

Page 4, line 17: "...battery to study Cntn4-deficient mice, which revealed subtle..." has been added to line 88

Page 5, first sentence in the Results section is now “In the cerebral cortex, the cortical layer thickness is related to migration and may be an indicator of neurodevelopment abnormalities.” (line 113)

Page 6, line 16: "total numbers of cells or of neurons" has been added to line 138

Page 8, line 12: The term "maturity morphologies" has been replaced by “spine morphologies” in line 183.

Page 8, line 16: The phrase "In vitro primary cell culturing..." has been replaced by "Primary cell culturing..." (line 188)

Reviewer #2 1) Figure 1A-E shows the organization of cortical layers in the CNTN4+/- and CNTN4-/- respect to WT mice. Looking at the NeuN staining the images in C show a reduction of the NeuN+ neurons of the upper layer in the CNTN4-/- mice with respect to WT mice, confirmed by the quantification and an increase of the NeuN+ neurons of the lower layer in the CNTN4-/-mice respect to WT mice, not confirmed by the quantification. Or upper layer thickness is reduced and the density of the NeuN+ is not changed. Also, surprisingly the Cux1/NeuN+ neurons are reduced in the CNTN4+/- compared to CNTN4-/- and WT mice, but images for the CNTN4+/- were not shown. These results need to be better clarified.

Thank you for your insightful comments. We understand the importance of clearly presenting the staining differences among the layers however were faced with limitations due to space constraints in including the Cntn4+/- images initially. In response, we have revised Figure 1 to display the three phenotypes (Cntn4+/+, Cntn4+/-, and Cntn4-/-) side-by-side using smaller images for a more comprehensive comparison. Regarding the quantification presented in Figure 1D and 1E, our analysis indicates that while there is a reduction in the number of NeuN+ neurons in the upper layers of the Cntn4-/- mice, this reduction is not statistically significant when compared to the Cntn4+/+ mice. A similar pattern is observed in the lower layers. However, we did observe a significant reduction in the thickness of the upper layer in the Cntn4-/- mice, which suggests a change in cell density, even though the overall number of cells (DAPI+) remains consistent across phenotypes. This implies a shift in the proportion of cells in the Cntn4-/- mice. We have now clarified this in the results section, emphasizing the change in neuronal proportion rather than density (line 144), to better convey our findings.

Reviewer #2 2) Figure 3 shows the quantification of dendritic spines but there are no images to support the quantification, in particular, it's unclear how "abnormal spines" were morphologically defined.

Thank you for your valuable feedback regarding Figure 3. In response to your comment, we have now incorporated representative images of the apical dendritic spines into Figure 3. These images feature white arrows pointing to specific examples of spine morphology, thereby visually supporting our quantification. To further clarify how the dendritic spines were morphologically categorized, we have updated both the Materials and Methods section under 'Golgi Staining' and the legend of Figure 3. Furthermore, we have referenced a pertinent study in the Methods section where similar categorization of spine morphology has been undertaken. This citation provides a methodological context and validation for our approach in spine classification. Additionally, the reader can refer to Figure 3A schematic for examples.

Reviewer #2 5) Figure 6 shows a nice characterization of dendrite arborizations in the APP-/- mice. However, these results are not really related to the function of CNTN4. Indeed, the minimal alteration in the number of apical dendrite tips that have been described in the APP-/- mice might be due to a function of APP unrelated to the interaction with CNTN4.

Thank you for highlighting this aspect of our study. We acknowledge that the findings in the APP-/- mice, as presented in Figure 6, might initially seem tangential to the primary focus on CNTN4. However, our intention in examining the App-/- mice was guided by prior studies indicating a potential link between APP and the pyramidal neuron phenotypes observed in cortical neurons. This exploration was aimed at broadening our understanding of APP's role in neuronal development, which, while not exclusively tied to its interaction with CNTN4, is nevertheless relevant to the overarching context of our research. To address your concern and enhance clarity, we have made an explicit statement in the manuscript's discussion section (line 383): “Results in the App-/- mice cannot be attributed solely to any interaction APP may have with CNTN4.”

Reviewer #2 4) Figures 6 B and C should show the colocalization of CNTN4 with APP, however, it's difficult to see any colocalization with images at this low magnification. Please provide images at higher magnification.

Thank you for the comment. We have adjusted Figure 6B and 6C to include zoomed in versions of the existing image to highlight regions of colocalization. It should also be noted from the description in the main text results that the expression pattern isn’t just colocalization.

Reviewer #2 3) The results of Figure 4 do not really provide a significant clue regarding the function of CNTN4 in relation to all the other data presented in this paper. Also, the staining of CNTN4 should be shown.

Thank you for your feedback regarding Figure 4. We understand your concerns about the relevance of these results to the overall function of CNTN4 as explored in our study. Our objective with Figure 4 was to contrast the effects of CNTN4 overexpression in primary cultured neurons with the phenotypes observed in the CNTN4 knockout detailed elsewhere in the manuscript. This comparison was intended to provide a more comprehensive understanding of CNTN4's role in neuronal development and function. To address your point about the visualization of CNTN4, we have now included more explicit details in the legend of Figure 4 (line 1210). Both the full-length Cntn4 construct and the empty pcDNA3.1 control vector used in our experiments are tagged with GFP.

Reviewer #1 Page 12, bottom. One would expect that the effect of CRISPR KO would be a complete elimination of the western blot band. It appears from the Figure and text that there is a little bit of residual signal. Could that band simply be cross-reactivity with another protein? Could it be protein contamination from serum? Or is the cell line not clonally pure?

Thank you for your comment and for pointing out the ambiguity in our manuscript. We have now revised the relevant sections to describe mRNA and protein expression levels more accurately.

To clarify, in our study, CRISPR knockout effectively eliminated CNTN4 protein expression in the CNTN4 knockout cell line, and similarly, APP protein expression was completely diminished in the APP knockout cell line. This complete reduction aligns with the expected outcomes of successful CRISPR knockout. Furthermore, we observed that the level of CNTN4 protein expression in the APP knockout cell lines showed a reduction of approximately 50%. Similarly, the level of APP protein expression in the CNTN4 knockout cell lines was reduced by about 50%. We believe these findings suggest an interdependent regulatory mechanism between CNTN4 and APP, which we have now elaborated upon in the revised manuscript (line 285).

Reviewer #2 7) The discussion is too long and needs to be more concise.

Thank you for your feedback regarding the length of our discussion section. We appreciate your guidance on enhancing the manuscript's clarity and focus. In response to your comment, we have thoroughly reviewed and condensed the discussion. Our aim was to streamline the content without compromising the coverage of our broad study.

4. 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.

Reviewer #1 Page 11. It isn't clear whether the binding of a soluble protein ligand to a cell-surface protein is measuring cis or trans binding configurations. It could be either or both, depending on the geometry of the interaction. Demonstrating a bone fide cis interaction is not easy - that requires a FRET experiment with tagged cell-surface proteins or a cryoEM structure.

Thank you for your insightful suggestion regarding the experimental approach to differentiate between cis and trans binding configurations. We acknowledge the importance of distinguishing these interactions and the potential insights that such experiments, like FRET with tagged proteins or cryoEM structure analysis, could provide. However, after careful consideration, we have concluded that incorporating these specific methodologies would extend beyond the current scope of our paper. While the suggestion of a more detailed examination through FRET or cryoEM is undoubtedly valuable, it would necessitate a separate set of experimental conditions and analyses, potentially forming the basis for future research.

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Referee #2

Evidence, reproducibility and clarity

In this paper, Bamford et al. showed a reduced cortical thickness in the motor cortex of Cntn4-/- mice, but cortical cell migration and differentiation were unaffected. They also found morphological changes in neurons in the M1 region of the motor cortex, indicating that CNTN4 is also involved in the morphology and spine density of neurons in the motor cortex. With mass spectrometry analysis they identified a number of interaction partners for CNTN4, among then they confirmed a previously demonstrated interaction between CNTN4 and APP. Thus, this study demonstrates that CNTN4 contributes to cortical development and that its binding and interplay with APP might also be important for neural elongation.

The paper shows nice and convincing results, but the following points should be fully addressed in order to improve the significance of these findings.

1. Figure 1A-E shows the organization of cortical layers in the CNTN4+/- and CNTN4-/- respect to WT mice. Looking at the NeuN staining the images in C show a reduction of the NeuN+ neurons of the upper layer in the CNTN4-/- mice with respect to WT mice, confirmed by the quantification and an increase of the NeuN+ neurons of the lower layer in the CNTN4-/-mice respect to WT mice, not confirmed by the quantification. Or upper layer thickness is reduced and the density of the NeuN+ is not changed. Also, surprisingly the Cux1/NeuN+ neurons are reduced in the CNTN4+/- compared to CNTN4-/- and WT mice, but images for the CNTN4+/- were not shown. These results need to be better clarified.
2. Figure 3 shows the quantification of dendritic spines but there are no images to support the quantification, in particular, it's unclear how "abnormal spines" were morphologically defined.
3. The results of Figure 4 do not really provide a significant clue regarding the function of CNTN4 in relation to all the other data presented in this paper. Also, the staining of CNTN4 should be shown.
4. Figures 6 B and C should show the colocalization of CNTN4 with APP, however, it's difficult to see any colocalization with images at this low magnification. Please provide images at higher magnification.
5. Figure 6 shows a nice characterization of dendrite arborizations in the APP-/- mice. However, these results are not really related to the function of CNTN4. Indeed, the minimal alteration in the number of apical dendrite tips that have been described in the APP-/- mice might be due to a function of APP unrelated to the interaction with CNTN4.
6. Figure 8 C-E shows a reduction of APP mRNA in SH-SY5Y knockdown of CNTN4 and a reduction CNTN4 mRNA in SH-SY5Y knockdown for APP. These data suggest might suggest that "interaction between CNTN4 and APP contributes to their gene expression". However, this observation needs to be proved mainly in the CNTN4 and APP KO mice.
7. The discussion is too long and needs to be more concise.

Significance

This study demonstrates that CNTN4 contributes to cortical development and that its binding and interplay with APP might also be important for neural elongation. However, the role of APP interaction on CNTN4 function was not well demonstrated.

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Referee #1

Evidence, reproducibility and clarity

9-17-2023

Bamford et al present a very thorough series of experiments to explore the role of CNTN4 and its interacting partner APP in the development of the mouse cerebral cortex. The manuscript presents the following analyses/experiments: (1) a thickness analysis of different cortical areas in the CNTN4 KO mouse, finding reduced cortical thickness and reduced cell numbers in motor cortex; (2) a pyramidal dendrite and spine morphologic analysis in motor cortex in the CNTN4 KO mouse, finding defects in proximal dendritic morphology and altered spine distribution; (3) a biochemical (mass spectrometry) search for CNTN binding partners in 293 cells, finding APP among others and confirming a previous finding; (4) a cell adhesion analysis in transfected 293 cells showing a trans interactions between the extracellular domains of CNTN4 and APP; (5) an analysis of pyramidal dendritic morphology in APP KO mouse motor cortex that looks like the reciprocal of the Scholl analysis phenotype observed with CNTN4 KO mouse cortex, and (6) a demonstration that neurite outgrowth is reduced in cultured SH-SY5Y neuroblastoma cells with CRISPR-mediated deletion mutations of either CNTN4, APP, or both. The experiments look to be technically well done, and they data are interpreted with an appropriate level of caution.

This work will be of substantial interest to scientists working on CNS development in general and cortical development in particular. Genetic variation in CNTN4 has been implicated in developmental disorders, such as autism spectrum disorder, and the present work represents an important step forward in defining the mechanistic underpinning of that phenotype. This work will also be of interest to those studying Alzheimer disease who wonder (as many have) what the normal function of APP is.

Minor comments:

Page 11. It isn't clear whether the binding of a soluble protein ligand to a cell-surface protein is measuring cis or trans binding configurations. It could be either or both, depending on the geometry of the interaction. Demonstrating a bone fide cis interaction is not easy - that requires a FRET experiment with tagged cell-surface proteins or a cryoEM structure.

Page 12, lines 7-9. The conclusion here is that CNTN4 KO and APP KO phenotypes are different. But a more interesting way to look at it is that the Scholl analysis of dendrites shows that they are almost exactly the reverse of each other with regard to near and distal morphologic differences. That could be interesting. Maybe CNTN4 binding inhibits APP signaling or binding to another partner, or APP binding inhibits CNTN4 signaling or binding to another partner, or both. Then loss of either one would hyper-activate the signal induced by the other and give the observed yin-yang phenotypic relationship. I note that this would not fit with the neuroblastoma phenotypes, which seem to be in the same direction; but a developing brain is different in many ways from a neuroblastoma cell in culture. The Discussion is also somewhat vague about possible interpretations of the two phenotypes in vivo.

Page 12, bottom. One would expect that the effect of CRISPR KO would be a complete elimination of the western blot band. It appears from the Figure and text that there is a little bit of residual signal. Could that band simply be cross-reactivity with another protein? Could it be protein contamination from serum? Or is the cell line not clonally pure?

Where is APP normally expressed in the developing mouse brain? A few sentences in the introduction or discussion would be helpful. This information was provided for Cntn4 in the introduction.

Minor grammatical items.

Page 3, line 6. "Over 1000 genes..."

Page 4, line 17. "...battery to study Cntn4-deficient mice, which revealed subtle..."

Page 5. First sentence in the Results section. "the cortical layer thickness is involved in migration" - that phrase needs to be reworked.

Page 6, line 16. "total numbers of cells or of neurons"

Page 8, line 12. "maturity morphologies" - that phrase needs to be reworked.

Page 8, line 16. "In vitro primary cell culturing..." should be "Primary cell culturing...". After all, the only kind of cell culturing is in vitro.

Significance

This work will be of substantial interest to scientists working on CNS development in general and cortical development in particular. Genetic variation in CNTN4 has been implicated in developmental disorders, such as autism spectrum disorder, and the present work represents an important step forward in defining the mechanistic underpinning of that phenotype. This work will also be of interest to those studying Alzheimer disease who wonder (as many have) what the normal function of APP is.

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Reply to the reviewers

We thank the reviewers for their comments and constructive criticisms of the manuscript. We thank them for positive comments on the high quality of the genetic screen and recognizing our contributions in respect of RDGB work in Drosophila.

In general, there is one important comment by the reviewers about the candidates identified in the proteomic screen as potential VAP interactors which have then been tested in the genetic screen. Reviewers have noted that many proteins in the proteomics study identified as VAP interactors do not have the classical FFAT motif that mediates VAP interaction. Therefore, what is the significance of such genes?

Response: It is important to reflect on the fact that while VAP interacts with FFAT motifs in proteins , a VAP immunoprecipitation will identify two classes of proteins (i) those with classical FFAT motifs (ii) those proteins without FFAT motifs that interact indirectly with VAP via proteins which themselves have FFAT motifs. We have already depicted this in Fig 2A as category C proteins.

We believe that the in vivo genetic screen does in fact serve the specific purpose of testing the functional significance of such non-FFAT containing proteins identified in the proteomic screen by functional validation of their ability to modulate rdgB degeneration.

Key modifications to the text and a few experiments planned are listed in the next sections against pointwise response to reviewer comments. We believe that this will strengthen the manuscript.

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

Mishra and colleagues have conducted a large genetic screen to identify modulators of a Drosophila model for retinal degeneration. Using biomolecular techniques, they selected a few hundred proteins that interact with an ER bound protein VAP, to further test them in the retinal degeneration model. This was done by downregulating their expression using interference RNA (RNAi). Degeneration was first measured through a pseudopupil analysis, then suppressors of degeneration were further tested in a different retinal degeneration model, and finally through an ERG experiment. Finally, they focused on a strong suppressor of degeneration, dCert, by using a mutant allele to confirm the findings from the RNAi. The results suggest that a handful of these candidates are suppressors in this model of retinal degeneration, and identify at which stage of retinal degeneration these proteins may be involved in. These proteins may have a significance in forms of neurodegeneration.

Major comment: - Perhaps a larger number of replicates could be done in the optical neutralization experiment as well as in the ERG. Figure 4.A(i) and (ii), please clearly state n values. I would suggest this as optional, but perhaps ut could help to increase n?

Each optical neutralization experiment was done using 5 independent animals and 10 ommatidia were scored from each animal. For the optical neutralization experiment in 4.A(i) and (ii) we did 5 independent animals with 10 ommatidia/ animal for the statistical score. Based on our past experience, this number is sufficient to capture the intra-ommatidial variability in each eye and the inter animal variability between animals. This information will be added to the figure legend.

For the ERGs minimum 5 animals were used per experiment which is already mentioned in the figure legend and conforms to the standards of analysis in the field for such experiments.<br /> - For human orthologs (Table 1), it could be worthwhile to add alignment scores between fly and human?

We will add the table with the alignment score

Minor comment: - Clarify the purpose in focusing on dCert specifically in the last results section and discussion - Several typos - Affect vs effect

• Following the initial genetic screen, it was necessary to characterize a genes to understand in detail the temporal and spatial aspects of it role in modulating degeneration. Dcert was chosen for several reasons (i) a classical germ line mutant allele was available (ii) Prior papers had established its role as a protein that functions at contact sites. We will clarify our purpose of including dCert as proof of principle in the discussion part.

-Typos will be corrected.

Reviewer #1 (Significance (Required)):

General assessment:

The main significance of this study comes from the focus on proteins that are known to interact with VAP. This implies that the suppressors of degeneration that they have identified in the RdgB9 model may have an effect in other neurodegenerative models, namely in ALS models. This could have a very high significant potential in therapeutic avenues for neurodegenerative diseases.

Among six candidates that had an effect with knocked down through RNAi, they pursued a single one (dCert) as proof of principle. It would help to add a justification for this choice in the main text and whether the authors have performed or intend to perform experiments using mutant forms of the other candidate proteins.

Although six candidate genes were available for analysis, there were no mutants available in two of them (SET and CG3071). Mutants in Yeti are homozygous lethal making it difficult to work on it in this setting. However a viable mutant in APC is now available and a CG9205 CRISPR germ line deletion mutant has recently been generated in our lab. We will use these two alleles to test their, interaction with rdgB like we did for dcert. Since dCert and CG9205 have membrane interacting domains we prefer to focused on these two genes for this study as proof of principle.

The work from Raghu and his team have been leading the research surrounding this model of degeneration in Drosophila. This study naturally further extends their field of research, identifying more candidates that modulate this form of degeneration, and helping elucidate the pathways leading to cellular degeneration.

These results will be of high interest for specialized researchers studying the molecular pathways that lead to cellular degeneration, both in the context of retinal degeneration as well as neurodegeneration. Specifically, researchers that may be interested in these candidate proteins and how they may play a role in the pathogenesis of various degenerative diseases.

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

Summary: In this study, Mishra and colleagues combine proteomic techniques with Drosophila genetics to identify interactors of the endoplasmic reticulum (ER) protein VAP and analyse their indirect implication in the light-dependent retinal degeneration phenotype caused by misfunction of the lipid transfer protein RdgB, another VAP interactor. This is an ideal model system to study neurodegeneration in vivo via which the authors aim to further understand the molecular mechanisms involved in VAP-RdgB's function in maintenance of membrane lipid homeostasis. Of an initial list of 403 VAP mammalian interactors found via Immunoprecipitation - Mass Spectromety performed in a human cell line, 52 homologous Drosophila genes are found to suppress the RdgB degeneration phenotype upon knockdown. The authors then test a series of genetic interactions to dissect the potential role of these genes in the degeneration phenotype and identify six genes that likely suppress the phenotype by directly acting on the same molecular processes as RdgB, two of which (Cert and CG9205) could have a direct mechanistic role in the lipid homeostasis maintained by the VAP-RdgB complex.

Major comments: - The model suggested by the authors in Fig 2A is one by which the tested genes influence the VAP-RdgB function via direct binding to VAP. The direct interaction with VAP is a core aspect of the study as the IP-MS experiment biases the list of genes tested in Drosophila, and this list is often referred to as "VAP interacting proteins". However, the interactions between the proteins coded by the most relevant genes in the genetic screen and VAP are not tested. In fact, of the six genes that are found to likely modulate the same processes as RdgB, four probably do so via affecting gene expression, as discussed by the authors, therefore making it unlikely that they are true VAP interactors (unless they shuttle from the ER to the nucleus). Additionally, it would seem that most of the 52 genes found to suppress the degeneration phenotype are not necessarily VAP interactors either as only a handful of genes in this list have predicted strong FFAT motifs. In general, the authors should provide additional comments/evidence on the interaction, or likelihood of the interaction, of these proteins with VAP, that should include: o The IP-MS data should be made available (at least on my end, in the current submission the supplementary lists available cover only the 52 genes found to suppress the phenotype, I found the list of 403 genes in the biorXiv submission but this also does not include data on the enrichment of each hit in the IP-MS). It should be made clear how enriched were each of the proteins in the analysis, and how high the most relevant genes in the genetic screen rank within this interactor list.

We will provide more details on the MS data. We can add the ratio (VAP WT vs VAP mutant) and the PSM, number of peptides etc in the table, and we will deposit the raw data on PRIDE repository.

It is true that some of the genetic interactors, especially those that do not have an obvious FFAT motif likely influence the retinal degeneration phenotype either by indirect interactions with VAP or functional interactions rather than structural interaction. This point can be emphasized in the discussion. It is important to note that this is in some senses a good reason to couple of protein interaction screen with a genetic screen., the genetic screen sometimes uncovering functional interactions via indirect mechanism. The likely mode of interaction can be made clear in a revision.

o The authors should provide further detail on the rationale behind defining the list of 403 genes to be tested (for example, what was the threshold enrichment considered as interaction). Also in relation to this, the authors should at least provide speculation as to why more than half of the 403 genes defined do not have an FFAT motif, despite the fact that the proteomic data was normalized to a non-FFAT motif binding mutant of VAP which should be capable of maintaining non-FFAT mediated interactions of the protein.

As the reviewer correctly mentions, the 403 genes from the proteomics screen used for the genetic screen all satisfied the criterion of being differentially enriched in binding seen to wild type VAP but not the non-binding version of VAP. This is despite that fact that many of these proteins do not have an identifiable FFAT motif. The reason for this is most likely that the candidates without the FFAT motif most likely bind to VAP indirectly via a protein which itself has an FFAT motif. This is depicted in Figure 2A. This has already been explained in the text but this can be elaborated further.

The rationale for including candidates from the proteomic screen without an FFAT motif in the genetic screen is that we were interested in all candidates that might influence RDGB function whether they are direct or indirect binders of VAP.

o The authors should acknowledge the limitations of their experimental design in regards to identifying real interactors of VAP in Drosophila and avoid referring to this set of genes as "VAP interacting proteins" and rather use a more accurate description such as "proteins enriched in the IP-MS" or at least "potential VAP interacting proteins".

We agree that the use of ‘potential VAP interactors’ may be more appropriate.

o Testing interaction between VAP and all the 52 genes found to suppress the phenotype would be a huge amount of work. But the finding most relevant to the initial premise of the study (i.e. "molecular mechanisms underlying lipid transfer protein function at membrane contact sites") is that Cert (a lipid transfer protein) and CG9205 (fly homolog of a mammalian lipid transfer protein) influence RdgB function. Demonstrating an interaction between these proteins and VAP would argue for the experimental design and support the hypothesis and model of the study. Cert is already a well established interactor of VAP, hence the authors would not need to add anything regarding this protein. Is CG9205 expected to be also a true interactor of VAP? Biochemical experiments could be used to test this idea, or even recently developed in silico modelling of interactions (i.e. AlphaFold Multimer) could be of help. If no interaction is observed/expected this should also be pointed out in the manuscript. Optionally, showing localization of Cert or CG9205 to the ER-PM interface would also greatly support the model of VAP-RdgB regulation suggested by the authors.

We agree that further experimental evidence to support the interaction of CG9205 would add useful information. This can be attempted by co-IP or by in silico methods such as Alpha fold multimer.

Minor comments: - In the model shown in Fig2A, it would seem that many proteins can bind VAP in addition to RdgB, however, VAP proteins have only one FFAT binding pocket. This model would only be possible if oligomerization of VAP is considered (oligomerization of VAP has been reported to occur, see for example PMID:20207736). The model should be redrawn considering this fact.

We agree.

• In line 161 of the text VPS13D is mentioned, however VPS13C is the gene indicated in Fig 1D.

The text will be corrected.

Reviewer #2 (Significance (Required)):

Previous studies by some of the authors and others have shown that RdgB can transfer lipids between the ER, to which it binds via VAP, and the plasma membrane (PM), and is required for proper replenishment of PI(4,5)P2 in the PM which is in turn necessary for sustained PLC signaling in Drosophila photoreceptors. Lack of RdgB leads to light-dependent degeneration of the retina, and hence it is utilized by the authors as a model for neurodegeneration. Given the clear phenotype of RdgB loss-of-function and the ease of Drosophila genetics, this system represents an ideal model to perform screens for the identification of new genes involved in maintaining neuronal lipid homeostasis required for proper function of the photoreceptors in vivo, and this aspect is the main strength of this study. Importantly, the use of this system could also shed light on the mechanisms behind human neurodegenerative disorders, as many of these involve dysregulation of lipid signaling and lipid transfer at membrane contact sites. A novel and interesting finding is the identification of another lipid transfer protein, Cert, to be involved in the degeneration of photoreceptors.

The main limitation lies in the experimental design proposed by the authors to define the genes that are studied in their system. These are identified as potential interactors of human VAP in a mammalian cell line. Despite the fact that VAP is a highly conserved protein, and the genes identified are present in Drosophila as well, there is no evidence that these interactions are in fact occurring in Drosophila photoreceptors, and in fact, based on the function and the lack of VAP-binding motif in many of the 52 genes identified to have an effect on the RdgB phenotype, it is likely that many of the interactions are purely genetic and indirect, and that the modulation of the phenotype could in fact be due to a wide variety of factors (including, as discussed by the authors, gene expression, post-translational modifications, trafficking of proteins, etc) unrelated to mechanisms of VAP-RdgB mediated lipid transfer at ER-PM membrane contact sites.

A more unbiased screen could have been carried out to identify VAP interactors involved in this degeneration phenotype by testing all of the FFAT or FFAT-related motif containing proteins. Due to this initial bias in the selection of genes to be tested, it is possible that other important VAP interactors that play a role at the ER-PM interface of photoreceptors have not been identified.

We agree that an alternative approach might have been to perform the VAP interaction proteomics in fly photoreceptors rather than start with a proteomics data set from mammalian cells. At this late stage in the project this will not be a feasible approach. However, we could consider testing any FFAT containing proteins, identified bioinformatically in the fly genome in the future.

An initial bioinformatics analysis has revelated that there are only 51 genes in the entire fly genome with an identifiable conventional FFAT motif. Of these 7 are already part of the genetic screen already completed. Of the remaining 44 genes, 11 show no expression in the eye and 9 show very low expression. Thus, using the approach suggested by the reviewer ca. 24 genes with FFAT motifs could have been missed and therefore could be screened, subject to genetic tools, i.e RNAi lines being available for these.

This study provides great functional advance in the understanding of genes implicated in photoreceptor degeneration, and in those regards it is a great resource for a specialized audience, as it enables further characterization by others of the different processes implicated in this neurodegeneration phenotype. However, the advance is small in regards to the core mechanism of RdgB function at VAP-mediated ER-PM, which was the main aim of the article and the most broadly interesting aspect of the study. Many of the VAP-interacting proteins identified in the proteomic approach were already expected to be VAP interactors as they contain FFAT motifs, and these FFAT-containing proteins do not seem to have a major role in VAP-RdgB maintenance of neuronal lipid homeostasis, with the exception of Cert. The implication of Cert in RdgB-mediated lipid homeostasis is certainly interesting as it touches on a current topic in the field of membrane contact sites related to how the multiple interactions of VAP, a universal contact site adaptor at the ER, are regulated and influenced by each other.

Reviewer's field of expertise: Lipid transfer at membrane contact sites; membrane lipid homeostasis in neurons. All of the Drosophila data seem to be of good general quality to me, but I do not have any expertise in Drosophila work.

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Referee #2

Evidence, reproducibility and clarity

Summary: In this study, Mishra and colleagues combine proteomic techniques with Drosophila genetics to identify interactors of the endoplasmic reticulum (ER) protein VAP and analyse their indirect implication in the light-dependent retinal degeneration phenotype caused by misfunction of the lipid transfer protein RdgB, another VAP interactor. This is an ideal model system to study neurodegeneration in vivo via which the authors aim to further understand the molecular mechanisms involved in VAP-RdgB's function in maintenance of membrane lipid homeostasis. Of an initial list of 403 VAP mammalian interactors found via Immunoprecipitation - Mass Spectromety performed in a human cell line, 52 homologous Drosophila genes are found to suppress the RdgB degeneration phenotype upon knockdown. The authors then test a series of genetic interactions to dissect the potential role of these genes in the degeneration phenotype and identify six genes that likely suppress the phenotype by directly acting on the same molecular processes as RdgB, two of which (Cert and CG9205) could have a direct mechanistic role in the lipid homeostasis maintained by the VAP-RdgB complex.

Major comments:

• The model suggested by the authors in Fig 2A is one by which the tested genes influence the VAP-RdgB function via direct binding to VAP. The direct interaction with VAP is a core aspect of the study as the IP-MS experiment biases the list of genes tested in Drosophila, and this list is often referred to as "VAP interacting proteins". However, the interactions between the proteins coded by the most relevant genes in the genetic screen and VAP are not tested. In fact, of the six genes that are found to likely modulate the same processes as RdgB, four probably do so via affecting gene expression, as discussed by the authors, therefore making it unlikely that they are true VAP interactors (unless they shuttle from the ER to the nucleus). Additionally, it would seem that most of the 52 genes found to suppress the degeneration phenotype are not necessarily VAP interactors either as only a handful of genes in this list have predicted strong FFAT motifs. In general, the authors should provide additional comments/evidence on the interaction, or likelihood of the interaction, of these proteins with VAP, that should include:
• The IP-MS data should be made available (at least on my end, in the current submission the supplementary lists available cover only the 52 genes found to suppress the phenotype, I found the list of 403 genes in the biorXiv submission but this also does not include data on the enrichment of each hit in the IP-MS). It should be made clear how enriched were each of the proteins in the analysis, and how high the most relevant genes in the genetic screen rank within this interactor list.
• The authors should provide further detail on the rationale behind defining the list of 403 genes to be tested (for example, what was the threshold enrichment considered as interaction). Also in relation to this, the authors should at least provide speculation as to why more than half of the 403 genes defined do not have an FFAT motif, despite the fact that the proteomic data was normalized to a non-FFAT motif binding mutant of VAP which should be capable of maintaining non-FFAT mediated interactions of the protein.
• The authors should acknowledge the limitations of their experimental design in regards to identifying real interactors of VAP in Drosophila and avoid referring to this set of genes as "VAP interacting proteins" and rather use a more accurate description such as "proteins enriched in the IP-MS" or at least "potential VAP interacting proteins".
• Testing interaction between VAP and all the 52 genes found to suppress the phenotype would be a huge amount of work. But the finding most relevant to the initial premise of the study (i.e. "molecular mechanisms underlying lipid transfer protein function at membrane contact sites") is that Cert (a lipid transfer protein) and CG9205 (fly homolog of a mammalian lipid transfer protein) influence RdgB function. Demonstrating an interaction between these proteins and VAP would argue for the experimental design and support the hypothesis and model of the study. Cert is already a well established interactor of VAP, hence the authors would not need to add anything regarding this protein. Is CG9205 expected to be also a true interactor of VAP? Biochemical experiments could be used to test this idea, or even recently developed in silico modelling of interactions (i.e. AlphaFold Multimer) could be of help. If no interaction is observed/expected this should also be pointed out in the manuscript. Optionally, showing localization of Cert or CG9205 to the ER-PM interface would also greatly support the model of VAP-RdgB regulation suggested by the authors.

Minor comments:

• In the model shown in Fig2A, it would seem that many proteins can bind VAP in addition to RdgB, however, VAP proteins have only one FFAT binding pocket. This model would only be possible if oligomerization of VAP is considered (oligomerization of VAP has been reported to occur, see for example PMID:20207736). The model should be redrawn considering this fact.
• In line 161 of the text VPS13D is mentioned, however VPS13C is the gene indicated in Fig 1D.

Significance

Previous studies by some of the authors and others have shown that RdgB can transfer lipids between the ER, to which it binds via VAP, and the plasma membrane (PM), and is required for proper replenishment of PI(4,5)P2 in the PM which is in turn necessary for sustained PLC signaling in Drosophila photoreceptors. Lack of RdgB leads to light-dependent degeneration of the retina, and hence it is utilized by the authors as a model for neurodegeneration. Given the clear phenotype of RdgB loss-of-function and the ease of Drosophila genetics, this system represents an ideal model to perform screens for the identification of new genes involved in maintaining neuronal lipid homeostasis required for proper function of the photoreceptors in vivo, and this aspect is the main strength of this study. Importantly, the use of this system could also shed light on the mechanisms behind human neurodegenerative disorders, as many of these involve dysregulation of lipid signaling and lipid transfer at membrane contact sites. A novel and interesting finding is the identification of another lipid transfer protein, Cert, to be involved in the degeneration of photoreceptors.

The main limitation lies in the experimental design proposed by the authors to define the genes that are studied in their system. These are identified as potential interactors of human VAP in a mammalian cell line. Despite the fact that VAP is a highly conserved protein, and the genes identified are present in Drosophila as well, there is no evidence that these interactions are in fact occurring in Drosophila photoreceptors, and in fact, based on the function and the lack of VAP-binding motif in many of the 52 genes identified to have an effect on the RdgB phenotype, it is likely that many of the interactions are purely genetic and indirect, and that the modulation of the phenotype could in fact be due to a wide variety of factors (including, as discussed by the authors, gene expression, post-translational modifications, trafficking of proteins, etc) unrelated to mechanisms of VAP-RdgB mediated lipid transfer at ER-PM membrane contact sites. A more unbiased screen could have been carried out to identify VAP interactors involved in this degeneration phenotype by testing all of the FFAT or FFAT-related motif containing proteins. Due to this initial bias in the selection of genes to be tested, it is possible that other important VAP interactors that play a role at the ER-PM interface of photoreceptors have not been identified.

This study provides great functional advance in the understanding of genes implicated in photoreceptor degeneration, and in those regards it is a great resource for a specialized audience, as it enables further characterization by others of the different processes implicated in this neurodegeneration phenotype. However, the advance is small in regards to the core mechanism of RdgB function at VAP-mediated ER-PM, which was the main aim of the article and the most broadly interesting aspect of the study. Many of the VAP-interacting proteins identified in the proteomic approach were already expected to be VAP interactors as they contain FFAT motifs, and these FFAT-containing proteins do not seem to have a major role in VAP-RdgB maintenance of neuronal lipid homeostasis, with the exception of Cert. The implication of Cert in RdgB-mediated lipid homeostasis is certainly interesting as it touches on a current topic in the field of membrane contact sites related to how the multiple interactions of VAP, a universal contact site adaptor at the ER, are regulated and influenced by each other.

Reviewer's field of expertise: Lipid transfer at membrane contact sites; membrane lipid homeostasis in neurons. All of the Drosophila data seem to be of good general quality to me, but I do not have any expertise in Drosophila work.

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Referee #1

Evidence, reproducibility and clarity

Mishra and colleagues have conducted a large genetic screen to identify modulators of a Drosophila model for retinal degeneration. Using biomolecular techniques, they selected a few hundred proteins that interact with an ER bound protein VAP, to further test them in the retinal degeneration model. This was done by downregulating their expression using interference RNA (RNAi). Degeneration was first measured through a pseudopupil analysis, then suppressors of degeneration were further tested in a different retinal degeneration model, and finally through an ERG experiment. Finally, they focused on a strong suppressor of degeneration, dCert, by using a mutant allele to confirm the findings from the RNAi.

The results suggest that a handful of these candidates are suppressors in this model of retinal degeneration, and identify at which stage of retinal degeneration these proteins may be involved in. These proteins may have a significance in forms of neurodegeneration.

Major comment:

• Perhaps a larger number of replicates could be done in the optical neutralization experiment as well as in the ERG. Figure 4.A(i) and (ii), please clearly state n values. I would suggest this as optional, but perhaps ut could help to increase n?
• For human orthologs (Table 1), it could be worthwhile to add alignment scores between fly and human?

Minor comment:

• Clarify the purpose in focusing on dCert specifically in the last results section and discussion
• Several typos
• Affect vs effect

Significance

General assessment:

The main significance of this study comes from the focus on proteins that are known to interact with VAP. This implies that the suppressors of degeneration that they have identified in the RdgB9 model may have an effect in other neurodegenerative models, namely in ALS models. This could have a very high significant potential in therapeutic avenues for neurodegenerative diseases.

Among six candidates that had an effect with knocked down through RNAi, they pursued a single one (dCert) as proof of principle. It would help to add a justification for this choice in the main text and whether the authors have performed or intend to perform experiments using mutant forms of the other candidate proteins.

The work from Raghu and his team have been leading the research surrounding this model of degeneration in Drosophila. This study naturally further extends their field of research, identifying more candidates that modulate this form of degeneration, and helping elucidate the pathways leading to cellular degeneration.

These results will be of high interest for specialized researchers studying the molecular pathways that lead to cellular degeneration, both in the context of retinal degeneration as well as neurodegeneration. Specifically, researchers that may be interested in these candidate proteins and how they may play a role in the pathogenesis of various degenerative diseases.

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Reply to the reviewers

1. General Statements

We thank the reviewers for their time and both thoughtful and constructive comments. Their specific points are addressed below but a general point that we would like to comment on is that in the original version it appears we did not make our model clear enough. The dogma in the field is that Rab7 is recruited to endosomes from a cytosolic pool via exchange with Rab5 (mediated by Mon1/Ccz1). Our work instead indicates that the majority of Rab7 is delivered to Dictyostelium phagosomes by fusion with other endocytic compartments. It was not our intention to imply there was no canonical recruitment of Rab7 from a cytosolic pool, and indeed we provide data to show this happens at a low level and discuss this in the manuscript. Nonetheless, we clearly over-stated the exclusivity of Rab7 recruitment to phagosomes via fusion at several points and our original model cartoon, and have tried to better explain or more nuanced model with multiple routes for Rab7 acquisition in this revision, including a completely redrawn model figure (Fig. 7).

2. Description of the planned revisions

Reviewer 1:

1. The observation that macropinosomes undergo retrograde fusion with newly formed phagosomes to facilitate phagosome maturation is an interesting notion that challenges the traditional model. However, not all phagocytes exhibit a high level of macropinocytosis, and axenic Dictyostelium cells used in the study may be an exception. Thus, it remains unclear whether fusion with macropinosomes is universally required for phagosome maturation. WT Dictyostelium cells or axenic cells cultured under SorMC/Ka condition (Paschke et al., PLoS One, 2018) exhibit significantly reduced macropinocytosis. The authors could examine whether the accumulation of Rab7 and V-ATPase on large-sized phagosomes is delayed in these cells. These experiments may help broaden the applicability of the authors’ finding.

As our previous work (Buckley et al. PloS pathogens 2019) demonstrated that bacterially-grown PIKfyve mutants are also defective in bacterial killing and growth it is highly likely that cells also are defective in V-ATPase and Rab7 acquisition. However, we agree that formally testing this will further support our conclusions and improve the paper and should be quite straightforward.

We will therefore co-express GFP-V-ATPase and RFP-Rab7 in both Ax2 and non-axenic cells grown on bacteria and repeat our analysis of recruitment to phagosomes – with the caveat that non-axenic cells do not phagocytose large particles such as yeast (Bloomfield et al. eLife 2015), so the imaging and quantification will be more challenging in this case.

PIKfyve seems to play a specific role in the maturation of phagosomes but not macropinosomes. The differences may be driven by signaling from phagocytic receptors, as the author suggested. Alternatively, the large size of the yeast-containing phagosomes may require additional steps for efficient lysosomal delivery. The authors should consider examining whether PIKfyve is needed for the delivery of Rab7 and V-ATPase to phagosomes of comparable size to regular macropinosomes, such as those containing K. aerogenes or small beads. In addition, whether the process also involves fusion between phagosomes and macropinosomes should be verified.

Whilst it is possible that large size of yeast-containing phagosomes requires additional mechanisms to process them, our previous data demonstrate that PIKfyve is also required to kill much smaller bacteria such as Klebsiella and Legionella (Buckley et al. PloS pathogens 2019). Furthermore, in this paper we also showed that loss of PIKfyve disrupts phagosomal proteolysis using 3um beads, and showed that V-ATPase recruitment was reduced on purified phagosomes containing 1um beads. We therefore find consistent defects on phagosomes of different size, with different cargos. Nonetheless, the experiments above, observing V-ATPase and Rab7 in cells grown on bacteria should directly address this point.

As suggested, we will also perform a dextran pulse-chase prior to addition of bacteria to test if we can observe macropinocytic delivery to bacteria-containing phagosomes - perhaps using E. coli as their elongated shape may help phagosome visualisation.

In the previous study from the authors' group (Buckley et al., PLoS Pathog, 2019), it was shown that the accumulation of V-ATPase on phagosomes begins immediately after internalization in both PIKfyve mutant and WT, although V-ATPase accumulation reaches only half of the levels seen in WT. This partial accumulation of V-ATPase differs from the almost complete absence of Rab7 recruitment found in this study, which raises the question of whether there exists yet another population of fusogenic vesicles that are positive for V-ATPase but negative for Rab7. This could be checked by simultaneously examining the dynamics of V-ATPase and Rab7 during yeast phagocytosis in the PIKfyve mutant.

We agree with the referee that there are multiple pools of V-ATPase, and we show that there is both a very early PIKfyve-independent recruitment of both V-ATPase and Rab7 as well as a later and more substantial pool delivered in a PIKfyve-dependent manner. It is clear that V-ATPase and Rab7 do not always co-localise however - the clearest example being on the contractile vacuole, which has lots of V-ATPase but no Rab7 (the large bright magenta structure in Fig 2G.).

We suspect that the dramatically reduced, but not completely absent levels of both V-ATPase and Rab7 recruitment in the absence of PIKfyve are similar, but the challenges with imaging these very small low levels means we cannot formally exclude that there is a pool of V-ATPase vesicles that lack Rab7 which fuse to very early phagosomes. Nonetheless, as we will already be looking at V-ATPase and Rab7 in PIKfyve KO's in the experiments above will also attempt to unequivocally differentiate a pool of V-ATPase positive/Rab7 negative vesicles fusing with phagosomes.

Reviewer 2:

(1) The authors show that deletion of PIKfyve results "in an almost complete block in Rab7 delivery to phagosomes" (page 17) indicating that the delivery of Rab7 depends on fusion with Rab7-positive structures. This would suggest that the Rab7-GEF Mon1-Ccz1 is not localized to the membrane of the phagosomes. Could the authors test for the presence of Mon1-Ccz1 in either fluorescence microscopy experiments or on purified phagosomes to exclude the possibility of a "canonical" Rab7 recruitment by its GEF? If the GEF is found on phagosomal membranes it would indicate that a Rab-transition from Rab5 to Rab7 occurs on the phagosome during maturation, but on a low level. The later fusion event might be a homotypic fusion of two Rab7-positive compartments. The observed fusion events could still deliver the bulk of Rab7 and other endolysosomal proteins to the phagosome. If the Rab7-GEF is not found on phagosomes how do the authors envision that the organelle keeps its identity? Is it solely dependent on PI(3,5)P2? What is the fate of the Rab7-negative phagosome in ∆PIKfyve cells if Rab7 is not delivered to the membrane, is there degradation happening over longer periods of time?

This is an excellent suggestion, for which we thank the reviewer. Mon1 and Ccz1 are highly conserved, with clear Dictyostelium orthologues that have never been studied. Our model is that there is a small proportion of Rab7 driven by this canonical pathway so would expect Ccz1/Mon1 to coincide with loss of Rab5 and be unaffected by loss of PIKfyve - although subsequent Rab7 delivery would be lost. This is easy to test by cloning and expressing GFP-fusions of both Ccz1 and Mon1 and would be highly informative. Note we do not exclude canonical Rab7 recruitment in our model (see discussion), our data just indicate this has a minor contribution.

Reviewer 3:

The focus is on their manuscript is loading of Rab7 on phagosomes, but there's no indication about Rab7 activation (GTP-loading). Would the RILP-C33 probe work in Dictyostelium? If not possible, the activation state of Rab7 should still be discussed. Despite Rab7 on other organelles in PIKfyve-inhibited cells, is this active or not?

The GTP-loading status of Rab7 is a good question, although the general dogma is that membrane-localised Rabs are active. We will try the RILP-C33 probe in Dictystelium as suggested, but as these cells lack an endogenous RILP orthologue there is a high chance it will not work. Sadly, reliable tools to asses active Rab status are a general limitation for the field, so if the RILP-C33 probe does not work we will add this caveat to the discussion.

The authors need to better address the confusing kinetics of early Rab7 recruitment, followed by SnxA (Fig. 4G, same for VatM - Fig. 4I ) - which is counterintuitive if PIKfyve activity is required to recruit Rab7. How do the authors explain this? Are phagosomes prevented from acquiring Rab7 in PIKfyve deficient cells because of a defect on phagosomes or the endo-lysosomes loaded with Rab7 (but not active).

We believe this again relates to the over-simplification of our model. Our data indicate both PIKfyve dependent and independent Rab7 recruitment. In contrast to the abrupt recruitment of SnxA at ~120 seconds (Vines et al. JCB 2023), both Rab7 and VatM accumulate gradually over time starting from almost immediately following engulfment (Buckley et al. 2019, and Figure 2F). Our data indicate that the first stage of this is PIKfyve independent, and is responsible for ~10% of the total Rab7/V-ATPase accumulation by both the imaging in this paper, and Western blot for V-ATPase on purified phagosomes in Buckley et al. PLoS pathogens 2019. The arrival of some Rab7/V-ATPase prior to PI(3,5)P2 therefore supports our model where there are multiple sources of Rab7.

As the reviewer quite rightly points out, interpretation of the defects observed in the absence of PIKfyve becomes complex and we cannot completely differentiate between a defect on the phagosome, or the Rab7 compartments that fuse with them (or indeed both). In fact, we already note that small Rab7 compartments that we observe in wild-type cells are much more sparse in PIKfyve mutants. Therefore whilst the requirement for PI(3,5)P2 in the clustering and fusion of macropinosomes with phagosomes is clear, additional effects on the PI(3,5)P2-independent Rab7 compartments cannot be excluded.

The experiments above using the RILP-C33 active Rab7 biosensor as well as observation of the Mon1/Ccz complex should further clarify this, but we will also add further discussion of these points.

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

Reviewer 1:

Minor comments.

1. It is unclear how the experiment in Figure 3G was conducted. If microscopic analysis was involved, the corresponding images should be included.

We apologise that we overlooked this and have now added a full description in the materials and methods (P8 L16-21). Fluorescence measurements were performed using a plate reader, so there are no images.

Page 11-Line 2, the sentence "there was no obvious clustering around the nascent phagosome (Figure 2D)." It is Figure 2E, not Figure 2D.

Corrected.

There is an inconsistency regarding the description of fluorescent fusion proteins. For example, both GFP (RFP)-2xFyve and 2xFyve-GFP (RFP), as well as GFP-Rab5 and Rab5-GFP, were used. Typically, placing GFP (or RFP) before a gene suggests N-terminal tagging, while placing it after the gene implies C-terminal tagging. The authors should clarify the position of the fluorescent tag and ensure consistency in their descriptions.

We apologise for this oversight, and have been through and corrected all fusion protein references accordingly.

One of the videos was not referred in the manuscript or described in the Video legends. This video seems to correspond to Figure 5A, albeit with a different pseudo-color scheme.

This has been corrected. Video 7 does correspond to Fig 5A, and we have corrected the colour scheme to match and added references to the video in the text and figure legend.

Reviewer 2:

(2) In their abstract, the authors state that they "...delineate multiple subpopulations of Rab7-positive endosomes that fuse sequentially with phagosomes" (page 2, line 14,15). However, the data provides only evidence for V-ATPase or PI(3,5) P2-containing structures and the authors conclude to my understanding that macropinosomes are the main source for vesicular structures fusing with phagosomes. I would ask the authors to please be clear on the identity of the "Rab7-donor"-structures throughout the manuscript. Saying that they delineate multiple subpopulations of endosomes seems to be overstated.

We identify that macropinosomes are one source (subpopulation) of Rab7/PI(3,5)P2 vesicles but our data clearly show that they are the only source of Rab7 - there is clearly an additional early Rab positive / PI(3,5)P2-negative subpopulation of vesicles that cluster and fuse too at earlier stages. For example, in Figure 4F we co-express Rab7a/SnxA and show that whilst all the SnxA vesicles also contain Rab7 (and dextran), there is a clear separate population of small and early-fusing population of Rab7-containing vesicles that do not possess PI(3,5)P2. This is further validated in Figure 5B and C. To our mind this clearly demonstrates and defines different Rab7 endosomal populations, although we do not yet know the origins of the initial Rab7-positive/PI(3,5)P2 negative population - as discussed in our response to their point (3) below.

Minor points:

(1) The sentence "...which both deactivates and dissociates Rab5, and recruits and activates Rab7 on endosomes" is at least problematic as it suggests that Mon1-Ccz1 directly drives GTP-hydrolysis of Rab5 and dissociates it from the membrane. Indeed, Mon1-Ccz1 is shown to interfere with the positive feedback loop of the Rab5-GEF by interacting with Rabex (Poteryaev et al., 2010), so a rather indirect effect of Mon1-Ccz1. A GAP and the GDI are needed for Rab5 deactivation and dissociation from the membrane. How both are involved in the endosomal Rab-conversion is not clarified.

We have changed the text to better represent this complexity (P4 L4-6)

(2) Signals of RFP-labeled proteins are difficult to interpret throughout the experiments. What are the structures that show a strong accumulation of red signal in Fig. 1A,B, Fig 2G and Fig4A (20sec.) If these are fluorescently labeled proteins it would suggest that most of the proteins cluster/accumulate in the cell. Can the authors provide better images?

We appreciate that some of these reporters with multiple localisations can be difficult to interpret. This is major challenge for these sort of studies and main reason we use the large and easily-identified yeast containing phagosomes for quantification. In Fig. 1 the large structure is the large peri-nuclear cluster of Rab5 previously reported (Tu et al. JCB 2022). In Fig. 2G the bright structure is the recruitment of V-ATPase on the CV. Both these large structures easily distinguished from the phagosomal pool we are interested in. Whilst we would love to provide better images, this is simply not possible - both these other structures are unavoidable and we are already using some of the best microscopy methods available. We have however clarified the additional localisations seen in these images in the revised figure legends.

(3) On page 11 the authors state "...macropinosomes in ∆PIKfyve cells still appeared much larger. Quantification of their size and fluorescence intensity demonstrated that although macropinosomes started off the same size,...". This statement is not reflected in the data depicted in Fig. 3A,B. The size of the single labeled macropinosome appears to be larger in wildtype than in ∆PIKfyve cells from the beginning on. However, the quantification in Fig 3F is clear. So, are these bad examples in 3A,B, are they swapped or is this due to the additional expression of GFP-Rab7A? Could you please comment on the effect that the (over-)expression of GFP-tagged Rab-GTPases might have on the observations described in this paper in the discussion part?

As you can see from the error bars in Figure 3F, macropinosomes are extremely variable in size - ranging from ~0.2-5 microns in size in axenic Dicytostelium. The image in Figure 3B is therefore indicative of this heterogeneity, rather than being a "bad example". This is why we designed the experiment to quantify several hundred vesicles in order to make any conclusions - as well as doing it in the absence of any GFP-fusion expression.

Although we have not noticed any issues (enlarged vesicles are also clear in GFP-Rab7 expressing cells in Figure 1B), we do of course accept that GFP-Rab7 expression itself may have some detrimental effects on maturation and this is why we quantified macropinosome size in untransformed cells. We have clarified this in the results section (P12 L28).

(4) In Fig. 6E it is hard to distinguish if the dextran is accumulating inside the phagosome. I would suggest conducting a 3D reconstruction of these images to allow judging if macropinosomes fused with the phagosomes or if they cluster around the neck of the phagosome.

This would be nice, but not possible as these images are from single confocal sections, rather than a complete high-resolution Z-stack. We have however added an enlargement of both Figure 6D and E which we feel now more clearly shows the presence of dextran within the bounding PI(3)P membrane of the phagosome.

(5) In the discussion, the authors state that the small pool of "PIKfyve-independent Rab7" is "insufficient to for subsequent fusion with other Rab7A-positive compartments, further Rab7 enrichment, and lysosomal fusion." What is the rationale for this conclusion? Is it shown how many Rabs are necessary to induce a tethering and fusion event? It would be good to revise this part of the discussion also in respect of the first major point of my comments above.

Our data show that in the absence of PIKfyve, phagosomes still remove Rab5 and gain a small pool of Rab7 but progress no further. This is consistent with some block in the HOPS-mediated homotypic fusion of Rab7 compartments. However, we accept that this is not necessarily due to simply not having enough Rab's so have rephrased the discussion accordingly.

(6) The intention of the paragraph about phagosomal ion channels is for this reviewer somehow out of context. It is not clear to me how the authors relate this to their findings. It would be could to bring this into a broader context.

__ __We mention ion channels in the background as they represent the main class of PI(3,5)P2 effectors known so far. We feel this is important background context, even if our studies do not directly relate to this.

Reviewer 3:

Their disclosure and use of statistics is incomplete and/or inconsistent, and potentially wrong in some cases. For example, the authors disclose the number biological repeats in a few experiments (Fig. 3C, F) but not in the majority. Instead, they state the number of phagosomes without indicating biological repeats (eg. Fig. 2 and others). So, it is not possible to know if their data are reproducible. Despite not indicating independent experiments in some cases, they speak of SEM, which applies to mean of means from biological repeats. In other cases, none of this is disclosed (eg Fig. 3G). Often there is no indication of what statistical test was done OR if a statistical test was done (eg. Fig. 3G, Fig. 4, etc). I would recommend the authors review the excellent resource paper published in JCB on SuperPlots to better follow statistical expectations. This is essential to improve reproducibility and confidence in their observations.

We apologise if this was unclear for the referee, but we have tried to be clear in each case. The confusion likely lies in the definition of a biological repeat, which depends on the type of experiment. For quantification of phagocytic events over time, we feel it reasonable to take each individual event (each from an individual organism) as a biological repeat. This is because events are relatively rare and taken from multiple different movies, and it is not technically possible to film both mutants and controls simultaneously. In all these sort of experiments (e.g. Figure 2) we have shown standard deviation, which indicates the reproducibility between phagocytic events. We have clarified that these events are from movies obtained on at least 3 independent days in the methods.

In other cases, such as Figure 3C and F and Figures 5-6, we are able to take measurements across multiple cells simultaneously at each timepoint. It is therefore appropriate to average over multiple independent experimental repeats rather than individual cells. We have therefore used SEM in our analysis, and both the number of individual cells and independent repeats are stated on the graphs and legend. This was incomplete in a few cases but has now been clarified in all cases.

Regarding statistical tests, which ones were used now been clarified in each figure legend. Note that in Fig 3G, we do not apply any test as both lines essentially overlap and it is clear there would not be any convincing differences. In Figure 4, the graphs all compare co-expression of different reporters rather than different mutants or conditions and are from single events. We therefore feel statistical tests are unnecessary and inappropriate. Comparison of the same reporters between strains averaged across multiple events, with statistical analysis is shown in Fig 2 instead. All these points have now been added to the statistics section of the methods (P9 L1-6)

Minor Comments

It is interesting that 2FYVE-GFP stays on phagosomes for 50 min or more - this is distinct from macrophages. Please comment. Have the authors tried other PI(3)P probes to see if the same (PX-GFP).

We have not used other probes but we have no reason to believe 2xFYVE does not behave as predicted as it is the same probe used for most macrophage studies (FYVE domain from human Hrs), and gets removed from macropinosomes exactly as expected. We did not originally comment in this manuscript but PI3P dynamics are even more interesting as our previous data indicate that latex-bead containing phagosomes lose PI3P after 10 minutes (Buckley et al 2019, Figure 4F-G) This indicates phagosome maturation can be regulated by the cargo (under further investigation). Importantly however, both bead and yeast-containing phagosomes have comparable defects in the absence of PIKfyve. This is more fully discussed in our previous paper (Vines et al. JCB 2023) where we characterise PI(3)P and PI(3,5)P2 dynamics in more detail.

Fig. 7 model: the macropinosome in the diagram seems like a dead end as depicted - is there any arrow or change that could be added to show that it doesn't just sit there in the middle? Also, the light green on yellow hurts the eyes!

We apologise, there was actually supposed to be an arrow there but it was lost somewhere in the drafting process. The whole figure has now been updated to more clearly describe our full and more complex model.

Fig. 3F, could be converted to volume assuming macropinosomes are spheres.

This is true, however as these images are taken from single planes we cannot know where in the sphere the slices are and therefore what the maximum diameter would be. We therefore prefer to keep it as area so as not to confuse and over-interpret the data.

Pg. 10, line 10 - Vps34 is Class III PI3K, not Class II.

Corrected.

4. 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.

• *

Reviewer 2:

(3) ("OPTIONAL") Optionally, the authors could also try to clarify these structures' identity by including further colocalization studies with additional early and late endosomal marker proteins. Are they for example positive for early or late endosomal markers like EEA1, ESCRT or Retromer? How about organelle-specific SNAREs? This would give further insights into the character of the "Rab7-donor" structures and would allow to clarify if multiple subpopulations are contributing to phagosome maturation in a sequential order as stated in the abstract. As I am not an expert on Dictyostellium I can`t estimate the effort that would go into such an experimental setup. However, since the time scale of the events in the cell is nicely worked out in this study, these colocalization studies would not need to be conducted as live-cell microscopy experiments.

This is a sensible suggestion that would in theory help define these populations. However many of these markers are poorly defined with respect to phagosomes and/or Dictyostelium. Dictyostelium does not posses an EEA orthologue, but our data also indicate that these vesicles do not possess PI3P so cannot be canonical early endosomes. We have previously characterised WASH/retromer and whilst it is recruited to phagosomes at around the time of Rab5/7 transition Retromer appears to be recruited from the cytosol and drive recycling rather than being delivered on endosomes that fuse (see King et al. PNAS 2016). We have also previously looked at ESCRT (Lopez-Jimenez et al. PLoS Pathogens 2018) which also does not appear to have any recruitment to early phagosomes that would be consistent with a Rab7-sub-population. The SNAREs are yet to be studied in any detail, as they are often too divergent to assign a direct mammalian orthologue.

Therefore, whilst this is a sensible suggestion, and something we would like to follow up in the future, this is not straight-forward and we feel outside the scope of the current study. We have however included additional discussion of this in the revised manuscript (P20 L21-26).

Reviewer 3:

Major Comments:

1. Based on the current data, I am not entirely convinced that Rab7 is delivered mostly by fusion with other compartments. At least the data as provided cannot exclude other models. For example, Rab7-containing organelles that cluster with phagosomes may form contact sites that provide a local environment to load cytosolic Rab7. There's also a possibility that some of their Rab7 clusters are membrane sub-domains and not vesicles. Or perhaps, there is a first wave of cytosolic Rab7 recruitment, which then initiates fusion with Rab7 compartments, i.e., there is a two-phase Rab7 recruitment. While this last possibility is consistent with recruitment of Rab7 by fusion (the second phase), the authors present a model that is too simplistic and conclusive based on the data. The authors may be right, but they need to strengthen their evidence towards their claim. Maybe EM could help determine some of these issues. Perhaps better would be the use of FRAP, photo-activation, or optigenetics of Rab7. For example, if Rab7 is acquired on phagosomes after photobleaching clusters of Rab7, this would suggest a cytosolic Rab7 contribution, and if not, this would support their model. I recognize that these experiments are not necessarily trivial, but either the authors augment their data (as suggested or with other approaches) or significantly pare down their conclusions.

We agree with the Referee that we cannot completely exclude other models, and as we talk about in the discussion, we do not wish to do so. We apologise if the role of fusion was over-stated but the model we propose is as the referee suggests: there is likely an early first wave of canonical Rab7 recruitment from the cytosol that is independent of PIKfyve before the majority of Rab7 is subsequently delivered by fusion in a PIKfyve-dependent manner. Our data indicate that the second wave is both quantitively and functionally more significant (see functional data in Buckley et al. 2019).

We do however agree with the referee that we cannot formally exclude things such as contact-site mediated recruitment from the cytosol or sub-domains but not fusion however there is no data to support these either. In contrast, the hypothetical clustered Rab7 contacts/subdomains often (but not always) contain the transmembrane V-ATPase complex (Figure 2G) which must be delivered by fusion.

However we do not wish to over-simplify our conclusions and as we state in the discussion, we do think there is probably a small amount of Rab7 recruited from the cytosol by the canonical pathway. We accept that our cartoon in Figure 7 is over-focussed on fusion so we have substantially revised this, as well as the discussion to give a more balanced and complex view.

Regarding the proposed experiments, unfortunately, the imaging required to acquire these movies is already at the very limit of what is possible so we do not believe it would be technically feasible to employ methods such as FRAP and optogenetics on these relatively fast-moving phagosomes with the temporal resolution required. Furthermore, to differentiate recruitment from a cytosolic pool, every GFP-Rab7 cluster would need to be photobleached, which could not be reliably achieved.

However, this point will be largely addressed by the suggestion of Reviewer 2 to look at the Mon1/Ccz complex. The presence or absence of this will give strong evidence for canonical Rab5/7 transition and Rab7 recruitment from the cytosol which would significantly clarify our model and define the two different mechanisms of Rab7 recruitment to phagosomes.

Early macropinosomes fuse with early phagosomes more readily than 10-min old macropinosomes. Do 10-min old macropinosomes not fuse with older phagosomes? Is this not an issue of mismatched age?

This is an interesting point that we have clarified in the text. We agree with reviewer that it appears the ages of the macropinosomes and phagosomes must match but our data indicate this only occurs when both parties possess PI(3,5)P2 as macropinosome fusions appears to happen in a single burst at about 240 seconds (Figure 6F) rather than as a continuous process. We also do not start to see any fusion of these older macropinosomes when the phagosomes get past the initial first 10 minutes of maturation (Figure 6G).

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Referee #3

Evidence, reproducibility and clarity

In Vines et al., the authors used time-lapse imaging of Dictyostelium to investigate the spatial-temporal maturation of macropinosomes labelled with a short pulse of dextran and phagosomes using yeast particles. The phagocytes expressed fluorescent Rab5 and/or Rab7 and/or biosensors for PI(3)P using 2FYVE-GFP and PI(3,5)P2 using the authors recently disclosed SnxA. They quantified the dynamics of these probes in wild-type and PIKfyve-deleted cells. The authors provide evidence for their main observations, which are that: i) Rab5 and PI(3)P are acquired early and independently of PIKfyve on phagosomes and macropinosomes, ii) but phagosomes require PIKfyve to acquire Rab7, iii) that phagosomes acquire Rab7 by fusing with Rab7-containing vesicles that cluster around the phagosome, iv) that macropinosomes do not require PIKfyve for Rab7 acquisition, and v) that PI(3,5)P2 on phagosomes follows Rab7. While the imaging data is high quality and supports several of the claims, the major discovery as proposed here is not fully supported by the data provided. I think the authors must address the following to strengthen their otherwise beautiful work.

Major Comments:

1. Based on the current data, I am not entirely convinced that Rab7 is delivered mostly by fusion with other compartments. At least the data as provided cannot exclude other models. For example, Rab7-containing organelles that cluster with phagosomes may form contact sites that provide a local environment to load cytosolic Rab7. There's also a possibility that some of their Rab7 clusters are membrane sub-domains and not vesicles. Or perhaps, there is a first wave of cytosolic Rab7 recruitment, which then initiates fusion with Rab7 compartments, i.e., there is a two-phase Rab7 recruitment. While this last possibility is consistent with recruitment of Rab7 by fusion (the second phase), the authors present a model that is too simplistic and conclusive based on the data. The authors may be right, but they need to strengthen their evidence towards their claim. Maybe EM could help determine some of these issues. Perhaps better would be the use of FRAP, photo-activation, or optigenetics of Rab7. For example, if Rab7 is acquired on phagosomes after photobleaching clusters of Rab7, this would suggest a cytosolic Rab7 contribution, and if not, this would support their model. I recognize that these experiments are not necessarily trivial, but either the authors augment their data (as suggested or with other approaches) or significantly pare down their conclusions.
2. The focus is on their manuscript is loading of Rab7 on phagosomes, but there's no indication about Rab7 activation (GTP-loading). Would the RILP-C33 probe work in Dictyostelium? If not possible, the activation state of Rab7 should still be discussed. Despite Rab7 on other organelles in PIKfyve-inhibited cells, is this active or not?
3. The authors need to better address the confusing kinetics of early Rab7 recruitment, followed by SnxA (Fig. 4G, same for VatM - Fig. 4I ) - which is counterintuitive if PIKfyve activity is required to recruit Rab7. How do the authors explain this? Are phagosomes prevented from acquiring Rab7 in PIKfyve deficient cells because of a defect on phagosomes or the endo-lysosomes loaded with Rab7 (but not active).
4. Their disclosure and use of statistics is incomplete and/or inconsistent, and potentially wrong in some cases. For example, the authors disclose the number biological repeats in a few experiments (Fig. 3C, F) but not in the majority. Instead, they state the number of phagosomes without indicating biological repeats (eg. Fig. 2 and others). So, it is not possible to know if their data are reproducible. Despite not indicating independent experiments in some cases, they speak of SEM, which applies to mean of means from biological repeats. In other cases, none of this is disclosed (eg Fig. 3G). Often there is no indication of what statistical test was done OR if a statistical test was done (eg. Fig. 3G, Fig. 4, etc). I would recommend the authors review the excellent resource paper published in JCB on SuperPlots to better follow statistical expectations. This is essential to improve reproducibility and confidence in their observations.
5. Early macropinosomes fuse with early phagosomes more readily than 10-min old macropinosomes. Do 10-min old macropinosomes not fuse with older phagosomes? Is this not an issue of mismatched age?

Minor Comments

1. It is interesting that 2FYVE-GFP stays on phagosomes for 50 min or more - this is distinct from macrophages. Please comment. Have the authors tried other PI(3)P probes to see if the same (PX-GFP).
2. Fig. 7 model: the macropinosome in the diagram seems like a dead end as depicted - is there any arrow or change that could be added to show that it doesn't just sit there in the middle? Also, the light green on yellow hurts the eyes!
3. Fig. 3F, could be converted to volume assuming macropinosomes are spheres.
4. Pg. 10, line 10 - Vps34 is Class III PI3K, not Class II.

Significance

Overall, the potential novelty of this work is the authors' proposal that phagosomes acquire Rab7 mostly by fusion with Rab7-labelled organelles rather than a cytosolic tool. This is distinct from existing models that assume phagosomes acquire Rab7 from a cytosolic pool that is loaded onto the membrane. They also suggest that PIKfyve plays a role in this process. However, as noted above, this claim needs to stronger data as the current data allows for other possible models, in my opinion.

This work is of relevance to cell biologists interested in membrane trafficking, phagocytosis, model organisms, and microscopy.

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Referee #2

Evidence, reproducibility and clarity

Summary

Vines et al. investigate in their manuscript the contribution of the lipid kinase PIKfyve on the maturation of phagosome. They follow the fate of the two main classes of identity markers of endocytic organelles: PIPs (PI(3)P and PI(3,5)P2) and Rab-GTPases (Rab5 and Rab7) in wildtype and ∆PIKfyve Dictyostelium discoideum cells. To follow the two species of PIPs they utilize the established reporter-proteins GFP-2xFYVE (PI(3)P-binder) and GFP-SnxA (PI(3,5)P2-binder) and correlate them with the appearance of fluorescently tagged Rab-GTPases on membranes of phagosomes in live-cell imaging. They find that the deletion of PIKfyve does not alter the recruitment and behaviour of Rab5. Therefore a lack of PI(3,5)P2 does not affect the early stages of phagosome formation. However, later stages of phagosome maturation are apparently affected by the lack of PI(3,5)P2: the Rab-GTPase Rab7 is not localizing to the membrane of the phagosome. Closer inspection of their live cell imaging data led the authors to the conclusion that Rab7 is delivered by the fusion of Rab7-positive structures with the phagosomes in wildtype cells. This fusion seems to be dependent on PIKfyve and PI(3,5)P2. However, surprisingly, the recruitment of Rab7 to macropinosomes or endosomal structures is independent of PIKfyve. The authors conclude (i) that lysosomal components are delivered to phagosomes by fusion of PI(3,5)P2-positive macropinosomes and (ii) a non-canonical delivery from Rab7 to phagosomes by fusion instead of GEF-dependent recruitment from the cytosol.

Major comments

Overall, the submitted manuscript of Vines et al. is of very good quality. The presented data supports mainly the conclusions that the authors draw. Methods and statistical analysis are sound and well-described. Their rationale, the description of results, and the presentation of data are easy to follow and understand. However, there are two major points that I would like to address here:

1. The authors show that deletion of PIKfyve results "in an almost complete block in Rab7 delivery to phagosomes" (page 17) indicating that the delivery of Rab7 depends on fusion with Rab7-positive structures. This would suggest that the Rab7-GEF Mon1-Ccz1 is not localized to the membrane of the phagosomes. Could the authors test for the presence of Mon1-Ccz1 in either fluorescence microscopy experiments or on purified phagosomes to exclude the possibility of a "canonical" Rab7 recruitment by its GEF? If the GEF is found on phagosomal membranes it would indicate that a Rab-transition from Rab5 to Rab7 occurs on the phagosome during maturation, but on a low level. The later fusion event might be a homotypic fusion of two Rab7-positive compartments. The observed fusion events could still deliver the bulk of Rab7 and other endolysosomal proteins to the phagosome. If the Rab7-GEF is not found on phagosomes how do the authors envision that the organelle keeps its identity? Is it solely dependent on PI(3,5)P2? What is the fate of the Rab7-negative phagosome in ∆PIKfyve cells if Rab7 is not delivered to the membrane, is there degradation happening over longer periods of time?
2. In their abstract, the authors state that they "...delineate multiple subpopulations of Rab7-positive endosomes that fuse sequentially with phagosomes" (page 2, line 14,15). However, the data provides only evidence for V-ATPase or PI(3,5) P2-containing structures and the authors conclude to my understanding that macropinosomes are the main source for vesicular structures fusing with phagosomes. I would ask the authors to please be clear on the identity of the "Rab7-donor"-structures throughout the manuscript. Saying that they delineate multiple subpopulations of endosomes seems to be overstated.

("OPTIONAL") Optionally, the authors could also try to clarify these structures' identity by including further colocalization studies with additional early and late endosomal marker proteins. Are they for example positive for early or late endosomal markers like EEA1, ESCRT or Retromer? How about organelle-specific SNAREs? This would give further insights into the character of the "Rab7-donor" structures and would allow to clarify if multiple subpopulations are contributing to phagosome maturation in a sequential order as stated in the abstract. As I am not an expert on Dictyostellium I can`t estimate the effort that would go into such an experimental setup. However, since the time scale of the events in the cell is nicely worked out in this study, these colocalization studies would not need to be conducted as live-cell microscopy experiments.

Minor comments

Minor points:

1. The sentence "...which both deactivates and dissociates Rab5, and recruits and activates Rab7 on endosomes" is at least problematic as it suggests that Mon1-Ccz1 directly drives GTP-hydrolysis of Rab5 and dissociates it from the membrane. Indeed, Mon1-Ccz1 is shown to interfere with the positive feedback loop of the Rab5-GEF by interacting with Rabex (Poteryaev et al., 2010), so a rather indirect effect of Mon1-Ccz1. A GAP and the GDI are needed for Rab5 deactivation and dissociation from the membrane. How both are involved in the endosomal Rab-conversion is not clarified.
2. Signals of RFP-labeled proteins are difficult to interpret throughout the experiments. What are the structures that show a strong accumulation of red signal in Fig. 1A,B, Fig 2G and Fig4A (20sec.) If these are fluorescently labeled proteins it would suggest that most of the proteins cluster/accumulate in the cell. Can the authors provide better images?
3. On page 11 the authors state "...macropinosomes in ∆PIKfyve cells still appeared much larger. Quantification of their size and fluorescence intensity demonstrated that although macropinosomes started off the same size,...". This statement is not reflected in the data depicted in Fig. 3A,B. The size of the single labeled macropinosome appears to be larger in wildtype than in ∆PIKfyve cells from the beginning on. However, the quantification in Fig 3F is clear. So, are these bad examples in 3A,B, are they swapped or is this due to the additional expression of GFP-Rab7A? Could you please comment on the effect that the (over-)expression of GFP-tagged Rab-GTPases might have on the observations described in this paper in the discussion part?
4. In Fig. 6E it is hard to distinguish if the dextran is accumulating inside the phagosome. I would suggest conducting a 3D reconstruction of these images to allow judging if macropinosomes fused with the phagosomes or if they cluster around the neck of the phagosome.
5. In the discussion, the authors state that the small pool of "PIKfyve-independent Rab7" is "insufficient to for subsequent fusion with other Rab7A-positive compartments, further Rab7 enrichment, and lysosomal fusion." What is the rationale for this conclusion? Is it shown how many Rabs are necessary to induce a tethering and fusion event? It would be good to revise this part of the discussion also in respect of the first major point of my comments above.
6. The intention of the paragraph about phagosomal ion channels is for this reviewer somehow out of context. It is not clear to me how the authors relate this to their findings. It would be could to bring this into a broader context.

Referees cross-commenting

Reviewer #1 provides valid questions. Addressing them would improve the manuscript by allowing consideration if the findings only apply to Dictyostellium or is of broader interest.

I completely agree with the concern of Reviewer #3 that the data provided so far would also allow for alternative models. The authors need to include further controls to exclude Rab7 recruitment or activation by any other means than fusion.

Significance

The manuscript by Vines et al. describes a very interesting novel observation on how the organelle identity marker Rab7 is delivered to phagosomes. They propose a mechanism, the delivery of Rab7 by PIKfyve-dependent fusion events with Rab7-positive macropinosomes, which is in contrast to the canonical model that endosomal organelles gain their Rab7-identity by maturation from a Rab5-positive compartment with the help of the Rab7-GEF Mon1-Ccz1. In the proposed mechanism the lipid-kinase PIKfyve, which is also involved in cellular signaling processes, plays the key role. In this study the authors present profound live cell imaging experiments combined with pulse-chase uptake of phagosomal cargoes. The obtained data is giving surprising new insights on the order of events in the maturation of phagosomes and suggests an unprecedentedly important role for PIKfyve in the maturation process. These new insights are of broad interest to a readership interested in transport, maturation and signaling processes along the endolysosomal system as well as of interest in the perspective of pathogen invasion to host cells.

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Referee #1

Evidence, reproducibility and clarity

PIKfyve/Fab1, a kinase responsible for phosphorylating PI3P to produce PI(3,5)P2, regulates phagosome maturation across various organisms. A previous work from the authors' group demonstrated that disrupting PIKfyve in Dictyostelium inhibits the delivery of V-ATPase and hydrolase, thus dramatically reducing the ability of cells to acidify newly formed phagosomes and digest their contents. The current manuscript further dissects the function of PIKfyve and PI(3,5)P2. Using live cell imaging, the authors show that nascent phagosomes acquire Rab7 by fusion with multiple populations of Rab7-positive vesicles, and the loss of PIKfyve abolishes this event. One of these fusogenic vesicle populations was identified as PI(3,5)P2-positive macropinosomes, which dock and fuse with phagosomes in a PIKfyve-dependent manner. Based on these findings, the authors propose that PIKfyve contributes to phagosome maturation by promoting heterotypic fusion between phagosomes and macropinosomes, which help deliver regulatory components necessary for phagosome acidification and digestion. This study provides fresh insights into the process of phagosome maturation. The work was well designed, performed and presented, and the manuscript is clearly written. However, there are several questions that should be addressed to strengthen the conclusions of the manuscript.

Major points:

1. The observation that macropinosomes undergo retrograde fusion with newly formed phagosomes to facilitate phagosome maturation is an interesting notion that challenges the traditional model. However, not all phagocytes exhibit a high level of macropinocytosis, and axenic Dictyostelium cells used in the study may be an exception. Thus, it remains unclear whether fusion with macropinosomes is universally required for phagosome maturation. WT Dictyostelium cells or axenic cells cultured under SorMC/Ka condition (Paschke et al., PLoS One, 2018) exhibit significantly reduced macropinocytosis. The authors could examine whether the accumulation of Rab7 and V-ATPase on large-sized phagosomes is delayed in these cells. These experiments may help broaden the applicability of the authors' finding.
2. PIKfyve seems to play a specific role in the maturation of phagosomes but not macropinosomes. The differences may be driven by signaling from phagocytic receptors, as the author suggested. Alternatively, the large size of the yeast-containing phagosomes may require additional steps for efficient lysosomal delivery. The authors should consider examining whether PIKfyve is needed for the delivery of Rab7 and V-ATPase to phagosomes of comparable size to regular macropinosomes, such as those containing K. aerogenes or small beads. In addition, whether the process also involves fusion between phagosomes and macropinosomes should be verified.
3. In the previous study from the authors' group (Buckley et al., PLoS Pathog, 2019), it was shown that the accumulation of V-ATPase on phagosomes begins immediately after internalization in both PIKfyve mutant and WT, although V-ATPase accumulation reaches only half of the levels seen in WT. This partial accumulation of V-ATPase differs from the almost complete absence of Rab7 recruitment found in this study, which raises the question of whether there exists yet another population of fusogenic vesicles that are positive for V-ATPase but negative for Rab7. This could be checked by simultaneously examining the dynamics of V-ATPase and Rab7 during yeast phagocytosis in the PIKfyve mutant.

Minor points:

1. It is unclear how the experiment in Figure 3G was conducted. If microscopic analysis was involved, the corresponding images should be included.
2. Page 11-Line 2, the sentence "there was no obvious clustering around the nascent phagosome (Figure 2D)." It is Figure 2E, not Figure 2D.
3. There is an inconsistency regarding the description of fluorescent fusion proteins. For example, both GFP (RFP)-2xFyve and 2xFyve-GFP (RFP), as well as GFP-Rab5 and Rab5-GFP, were used. Typically, placing GFP (or RFP) before a gene suggests N-terminal tagging, while placing it after the gene implies C-terminal tagging. The authors should clarify the position of the fluorescent tag and ensure consistency in their descriptions.
4. One of the videos was not referred in the manuscript or described in the Video legends. This video seems to correspond to Figure 5A, albeit with a different pseudo-color scheme.

Significance

Disruption of PIKfyve results in severe defects in phagosomal maturation across different organisms, but the underlying mechanism remains unclear. This study demonstrates that PIKfyve plays a specific role in phagosome maturation by promoting heterotypic fusion between macropinosomes and newly formed phagosomes. These fusion events provide a means for the rapid delivery of lysosomal components to early phagosomes. The study challenges the conventional model of phagosome maturation and provides novel insights into the complex dynamics involved. Nonetheless, further investigations are needed to elucidate the exact role of PIKfyve/PI(3,5)P2 in regulating vesicle fusion and to explore whether the proposed model can be applied to other endocytic pathways or cell types.

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Reply to the reviewers

1) List of the detailed experiments we plan to perform (including aforementioned experiments):

• Careful analysis of the daughter cell size by measuring the real volume.

• Quantifications of PCM (pericentrin and γ-tubulin) proteins and Plk1 with respect to centrosome age in G2 and metaphase (for Plk1) cells.

• Analysis of the amount of Plk1 of metaphase cells when cenexin protein is absent (siControl vs siCenexin), and measurements of Plk1 in WT-cenexin vs. cenexinS796A mutant to test if Cenexin controls a subpool of Plk1 at centrosomes.

• Careful analysis of Ctrl and TPX2 depletion experiment data in 1:1 cells. We plan to repeat the experiment to confirm or infirm on the contribution of TPX2 in spindle asymmetry.

• Measurement of the PCM volume/intensity in 2:2 and 1:1 metaphase cells, to highlight on the contribution of the daughter centrioles in recruiting PCM proteins.

• Live cell imaging of 2:2 cells and measurements of different parameters; cortex-to-centrosome and spindle pole to metaphase plate (half-spindle (a)symmetry) distances.

• Long-term live cell imaging of 2:2 cells to investigate whether the asymmetry in centrosome-age dependent daughter cell size also affects the duration of the ensuing cell cycle. While we have carried out such long-term movies in the past, we are aware that they can be challenging due to high cell mobility over longer time courses.

• Investigation of the microtubule nucleation capacity under different conditions of PCM protein depletion (depletion of Cdk5rap2 and/or pericentrin).

• Analysis of the effect of the over-expression of PCM protein (Cdk5Rap2) on the (a)symmetry of the mitotic spindle size

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2) detailed answers (in green) to the reviewers’ comments:

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__Reviewer #1: __

__(Major points) __

1. The discovery of differences in half-spindle size during symmetric division is intriguing. However, the methodology for quantification of the data remains unclear. Key questions, such as how the center of the metaphase plate is determined from the image data, the definition of exact pole position when centrioles are located at spindle poles, the objective determination of daughter cell diameter and width from the image data, and the referential position of the cortex, need more detailed explanation in the manuscript. Additionally, it's crucial to elucidate the specific index used to quantify differences from the image data, especially when dealing with data that only varies by a few percent. Providing clarity on these aspects and, in some cases, re-quantifying the data should be necessary.

We have already included clearer explanations in the method parts and results part about our methodology and will include a supplementary figure on how precisely we defined and measured the half-spindle sizes, as well as the index used for the asymmetry (using a methodology that we previously used in Dudka et al., Nature Comm., 2018). In addition, we will use a second method to measure the real daughter cell volume.

The mechanism behind the difference in half-spindle size, related to the subdistal appendage (SDA), raises questions, especially considering that SDA is believed to disassemble during mitosis. Exploring whether differences in the localization of PCM components and half-spindle size result from disparities in Plk1 and PCM loading during G2/early mitosis, prior to SDA disassembly, necessitates experimental verification.

As suggested by the reviewer we will quantify the amounts of PCM proteins on the old and young centrosome in G2 cells (and therefore prior SDA reorganization). This will also allow us to test whether the asymmetry depends on the SDA themselves, or the corresponding SDA proteins, which still accumulate specifically on the oldest centrosomes during mitosis

For investigating the mechanism of half-spindle size asymmetry, many perturbation experiments employ knock-down techniques. To directly address the cause of asymmetry, it might be valuable to artificially localize Plk1 and PCM factors to one spindle pole using optogenetic tools or similar approaches and then quantify half-spindle and daughter cell sizes.

We thank the reviewers for this suggestion, as it could indeed, be of great interest and provide a direct proof of principle. Unfortunately, based on our experience in establishing such a cell line we know that just the generation of such a light-manipulated stable cell line that contains markers for centrosomes and chromosomes or kinetochores takes 6-9 months, in the best-case scenario. This experiment is therefore not possible within a normal revision round (even if extended to 6 months).

The asymmetry in Plk1 sub-population recruitment by SDA triggers the observed effects, but the evidence for this is relatively weak, given the small difference in spindle asymmetry. Quantifying the amount of Plk1 in its activated form, particularly in the context of SDA dismantling during metaphase, could strengthen this aspect of the study.

While the commercial antibodies against the activated form of Plk1 (phospho-T210) work very well by immunoblotting, we have not been able to get it to work by immunofluorescence. We will nevertheless, test whether variation in the fixation methods can solve this issue. Alternatively, we will test to which extend depletion of Cenexin, or the presence of Cenexin WT vs the non-phosphorylatable Cenexin mutant affects the overall population of Plk1 on both spindle poles.

While the focus on half-spindle size asymmetry during symmetric division is intriguing, it's important to address the broader physiological significance. The primary outcome of this asymmetry is differences in daughter cell size, which limits the broader significance of the study. Furthermore, the quantification method for daughter cell size warrants scrutiny and clarification.

As mentioned above, we will use different method to measure and investigate daughter cell size (a)symmetry. Moreover, we will attempt with long-term live cell movies to test whether the variation in centrosome-age dependent daughter cell size also affects the duration of the ensuing cell cycle.

(Minor points)

1. Table 1 lists factors with asymmetric localization not analyzed in detail in this paper. It would be beneficial to discuss whether these factors play a role in spindle asymmetry, and the authors should address the completeness of the data in Table 1 in terms of selecting factors for analysis.

We agree with this comment that other factors may participate in the regulation of spindle asymmetry. However, we performed this screening to identify key drivers of spindle (a)symmetry based on an investigation of the Pearson’s correlation coefficient and the value of slope.

In addition, some of these proteins are known to control spindle size in acting in a same pathway (TPX2/Kif2A/Katanin) and (Pericentrin/CDK5RAP2/ϒ-tubulin). We will incorporate these points and the reasons for our selection in the discussion

In Figure 1H, the impact of centriolin knock-out on the distribution of unaligned polar chromosomes is different from the effect of cenexin S796A in Figure 6H. This difference should be explained to provide clarity on the observed discrepancies.

We will better explain this difference.

In Figure 2A, there is no correlation data presented between daughter cell asymmetry and the presence or absence of cenexin signal. This relationship should be elucidated for a more comprehensive understanding.

We will clarify this point. Specifically, we plotted the daughter cell symmetry index for 2:2 and 1:1 cells with respect to centrosome age. All the daughter cells display the presence of a cenexin signal at both grandmother and mother centrioles with a difference in fluorescence intensity that enables us to assign them to “old” vs “young centrosomes. We found a significant result indicating that there is a relationship between centrosome age and the formation of daughter cell with different sizes.

In Figure 4G and H, the mean value of spindle asymmetry increases with siRNA treatment of Cdk5Rap2 or PCNT compared to the control. The possible interpretation of this finding should be discussed.

This is an interesting observation that needs to be discussed in our revision.

Figure 4K shows that the asymmetry of PCNT distribution is not eliminated by centriolin knock-down. This observation requires clarification and discussion.

It has been shown that pericentrin is directly recruited by Plk1 at centriole (Soung et al., 2009). In addition, pericentrin has a PACT-domain that directly targets pericentrin to the centriole (Gillingham and Munro., 2000). Moreover, it has been demonstrated that the grandmother centriole is slightly longer than the mother one (Kong et al., 2020). Altogether, this suggests that the old and young centrosomes, based on this intrinsic property, may recruit different amount of pericentrin.

We will add this explanation in the discussion.

It appears that the difference in spindle asymmetry of the control group in Figure 5A is smaller than in other data. This discrepancy should be addressed. Additionally, the influence of TPX2 depletion on spindle formation, and any corresponding spindle staining data, should be included.

This point will be discussed in the revised version of the manuscript.

Claiming that the daughter centriole recruits PCM based on Figure 6A data alone may require additional supporting evidence. It is essential to investigate whether there is a clear PCM signal when the daughter centriole disengages in late mitosis and maintain consistency in the interpretation.

As suggested by the reviewer 2, we will measure PCM volume/intensity in both 2:2 and 1:1 cells to demonstrate that daughter centrioles directly recruit PCM proteins.

The lack of difference in TPX2 distribution in Figure 7E should be explained, along with a discussion of how this observation aligns with the spindle asymmetry data and any inconsistencies.

We will discuss this point in the revised manuscript.

The differing N numbers between samples in all the figures may affect the validity of comparisons. The authors should discuss whether it is necessary to have consistent N numbers in each experiment for more robust conclusions.

Indeed, this is an important point that must be discussed.

Reviewer #2____:

Major comments:

1) It is not completely clear how the authors determined whether a spindle was asymmetric or not. In the methods, they say that statistical tests are described in the legends. In Figure 1 legend they say: "Each condition was compared to a theoretical distribution centered at 0 (dashed line)". How did they generate this theoretical distribution?

As explained under point 1 of reviewer 1, we will provide a more thorough explanation of our methodology and how we decide whether a spindle is symmetric or not. In brief, a perfectly symmetric spindle would yield an asymmetry index of 0, as there is no difference between the two half-spindle sizes.

2) The authors claim that TPX2 depletion results in loss of spindle asymmetry in 1:1 cells, but the difference is very small (1.7% in control vs 1.3% in TPX2 depletion, Fig 5B) and the data is more variable in TPX2 depletion, which makes it less likely that a statistically significant difference from 0 would be found. Firstly, perhaps the authors could check the standard error of the mean, which provides a measure of how accurate the mean is with regard to N and variation. If a dataset is more spread (such as in TPX2 depletion) a higher N is required to attain the same accuracy in the mean value. This is normally not so important when directly comparing two datasets, but in this case the authors are comparing each dataset to 0. So, are the authors measuring enough cells in the TPX2 depletion to be sure that a 1.3% value is not significantly different from 0? Secondly, I don't understand why the control cells have such a low asymmetry index (1.7%), when previous data in the paper shows an asymmetry index of 4.1% (Fig 1D) and 3.4% (Fig 4E) in control 1:1 cells. This suggests that something about the way this experiment was carried out dampens the asymmetry, which could therefore lead the authors to conclude that TPX2 is more important than it really is.

We agree with this comment, the mean of the control condition is smaller compared to others controls. As mentioned above, we will carefully look at the data (SD vs SEM) and in case add a new replicate to confirm or infirm the involvement of TPX2 in the formation of asymmetric spindles.

3) The authors claim that daughter centrioles are associated with some Pericentrin and suggest that this may be why 2:2 centrosomes have less of an asymmetry than 1:1 centrosomes (Fig 6A). It is unclear whether the authors consider these daughter centrioles as being prematurely disengaged (they make reference to the fact that they previously showed how disengaged daughters recruit γ-tubulin, but it's unclear if this is related to their current observations). In Figure 6A, the Centrin spots look too far apart for engaged centrioles (~750nm). I appreciate that this may be the only way to dectect Pericentrin around the daughter at this resolution, but it may also force the authors to select cells where the centrioles have prematurely disengaged. For the asymmetry measurements, the authors presumably did not select cells where they could distinguish mother and daughter centrioles. One way to address this issue would be to compare PCM size at centrosomes in 2:2 cells with centrosomes in 1:1 cells. The expectation would be that centrosomes in 2:2 cells would have more PCM, due to the contribution of the daughter centrioles.

We agree that on those high-resolution images the daughter centrioles seem to be far from the mother ones. The metaphase cells presented in this figure, are wild-type non-treated cells for which the daughter centrioles are engaged. Indeed, our own investigation of the centriole engagement status by expansion microscopy, indicates that over 98% of centriole pairs in metaphase RPE1 cells are engaged.

Nevertheless, as suggested by the reviewer and to validate that daughter centrioles participate in this process, we will compare PCM size in 2:2 and 1:1 metaphase cells.

4) The authors show that Plk1 recruitment by Cenexin (via S796 phosphorylation), which happens only at mother centrosomes, is important for asymmetry. Nevertheless, they show that Plk1 is symmetrically distributed between mother and daughter centrosomes (Table 1). This does not really fit, unless daughter centrosomes recruit more cenexin-independent Plk1 than mother centrosomes or if the cenexin-bound pool of Plk1 is only a minor fraction of total Plk1. If so, do the authors think that the Cenexin-bound pool of Plk1 is more potent than the rest of centrosomal Plk1?

As indicated in point 4 of reviewer 1 we will test which proportion of the Plk1 pool at spindle poles depends on the presence of Cenexin, as we suspect that this Plk1 population is only a subpopulation.

5) The circles drawn to measure cell size in Figures 2A,E and 7C do not look like a good representation of cell area (as the cells are not perfectly round). The authors use a formular for circle area with an approximation of the radius (based on mean length/width of an oval. It would be much better to use ImageJ to draw a freehand line around the perimeter of the cell and use the in-built tool to measure the area.

As mentioned in point 1 of reviewer 1 we will use another method to measure daughter cell size.

Minor comments:

1) Asymmetry in centrosome size that correlates with centrosome age in apparently symmetrically dividing "cells" has been observed previously in Drosophila syncytial embryos (Conduit et al., 2010a, Curr. Bio.). I think this should be mentioned somewhere given the topic of the study.

We thank the reviewer for this information. This paper will be discussed in the revised version.

2) A full description of statistical tests and n numbers for each experiment should be provided in the methods, even if this duplicates information in the Figure legends.

We will add this information in the method.

OPTIONAL EXPERIMENTS:

3) Given that chTOG is very important for microtubule nucleation, it seems strange that this protein was not analysed for a potential asymmetry.

As suggested by the reviewers we will test for a potential chTOG asymmetry and its impact on spindle size asymmetry.

4) Cooling-warming experiments could be done using higher concentration of formaldehyde, as it's likely that microtubule nucleation is not immediately halted when using 4% formaldehyde.

The fixation solution was chilled at 4°C, which should halt any further depolymerization. We will specify this point in the Material and Methods section.

Reviewer ____#____3:

Major points:

1) The evaluation of spindle and cell size asymmetry related to centrosome age only relies on fixed sample preparation. Cells should be followed by time-lapse microscopy as the metaphase plate position relative to the spindle poles and/or the cell cortex may fluctuate over time and as the observed differences remain in a very subtle range. This is an important possibility to consider for 1:1, 1:0 or 0:0 spindle pole configurations where centrosome integrity is impaired.

We agree with the reviewer that this is a drawback of our approach, but the experiments the reviewer suggests is not possible for 1:0 or 0:0 or only in an approximate manner. Indeed, we do not have a centriole-independent spindle pole marker that would allow us to mark precisely the position of the spindle pole. In the past we used Sir-tubulin, which gave us an approximate position of the spindle poles, and which allowed to us monitor the spindle asymmetry over time of 1:0 cells (see Dudka et al., 2019), a point that we will discuss. Nevertheless, as suggested by the reviewer we will attempt to monitor these asymmetries in 2:2 and/or 1:1 cells expressing GFP-Centrin1 and GFP-CENPA (kinetochore marker) in WT conditions. Indeed, we cannot expand this approach to all the conditions, as the calculation of the spindle asymmetry index is based on a very high number of cells, and the monitoring of spindle asymmetry can only be achieved by selecting mitotic cells one-by-one and then monitoring them over a short period of them (Tan et al., eLife, 2015), which makes such an approach extremely time-consuming.

2) Cell size asymmetry was evaluated based on cell area at the equator. Volumes will be a better indicator as daughter cell shapes can be different in telophase if they do not re-adhere at the same speed. This evaluation should also be confirmed with another readout, like the position of the cleavage furrow relative to the spindle poles in late anaphase, as again the observed differences are in a very subtle range.

As indicated in the similar points of reviewer 1 and 2, we will improve our methodology to take this comment in account

3) The authors propose that differential microtubule nucleation at the spindle poles underlies spindle size symmetry breaking without providing direct evidence. If the observed spindle symmetry in the 1:1 configuration after pericentrin, CDK5RAP2 or g-tubulin siRNA fuels this interpretation (Fig4C), the differential microtubule nucleation capacity at the spindle poles after microtubule-depolymerisation-repolymerisation assays was not evaluated in these conditions, as compared to the control situation.

As suggested by the reviewer we will analyze the microtubule nucleation capacity after the downregulation of PCM proteins.

4) If differential microtubule nucleation at the spindle poles is responsible for spindle asymmetry, overexpression of PCM proteins or g-tubulin should be sufficient for re-establishment of symmetric protein distribution, spindle and cell size symmetry in 2:2 or 1:1 configuration. The authors should evaluate whether this is the case or not.

This is an interesting suggestion, which we will test, although overexpression of these proteins might also lead to other defects in the spindle, such as multipolar spindles.

5) The authors describe that the cortex-centrosome distance is not changed according to centrosome age (Fig2C), but centrosome-metaphase plate distance is (Fig1D). These observations are difficult to reconcile if differential microtubule-nucleation capacity is at play. Again, time-lapse microscopy would enable to detect over time whether only metaphase plate position relative to spindle poles is changing or if spindle pole position relative to the cell cortex is also fluctuating.

We plan to give a try to image WT 2:2 cells by time lapse microscopy and to measure several parameters such as half-spindle size, spindle (a)symmetry and the cortex to centrosome distance over time.

Minor points:

6) Main PCM and MT nucleation protein "depletion" do not appear to impact spindle assembly, but only spindle symmetry in 1:1 and 1:0 configurations (Fig4A and 4F-H). Can it be explained by the fact that their depletion is not always total (for pericentrin, Fig5F versus FigS2A or Fig7G)? Can they comment on this point?

Spindles displaying abnormal centriole number at spindle poles (1:1 and 1:0) can still assemble bipolar spindle in absence of the main PCM proteins (Chinen et al., JCB, 2021, and Watanabe et al., JCB, 2020).

In our study, the depletion of PCM protein is almost total (97% for pericentrin, 98% for Cdk5Rap2).

7) If centrosome age dictates spindle and cell size asymmetry through differential MT-nucleation capacity at the spindle poles, how can this process be modulated? Indeed, centrosome age is common to all cell types, but cell size asymmetry is more or less pronounced. The authors should further discuss this point based on the literature.

We will discuss this point in the discussion.

__ Description of the revisions that we have already carried out in the revised manuscript__

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1. The discovery of differences in half-spindle size during symmetric division is intriguing. However, the methodology for quantification of the data remains unclear. Key questions, such as how the center of the metaphase plate is determined from the image data, the definition of exact pole position when centrioles are located at spindle poles, the objective determination of daughter cell diameter and width from the image data, and the referential position of the cortex, need more detailed explanation in the manuscript. Additionally, it's crucial to elucidate the specific index used to quantify differences from the image data, especially when dealing with data that only varies by a few percent. Providing clarity on these aspects and, in some cases, re-quantifying the data should be necessary.

We have already included clearer explanations in the method parts and results part about our methodology and will include a supplementary figure on how precisely we defined and measured the half-spindle sizes, as well as the index used for the asymmetry (using a methodology that we previously used in Dudka et al., Nature Comm., 2018). In addition, we will use a second method to measure the real daughter cell volume.

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__ Description of the experiments that we prefer not to carry out:__

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Point 3 of reviewer 1 : For investigating the mechanism of half-spindle size asymmetry, many perturbation experiments employ knock-down techniques. To directly address the cause of asymmetry, it might be valuable to artificially localize Plk1 and PCM factors to one spindle pole using optogenetic tools or similar approaches and then quantify half-spindle and daughter cell sizes.

We thank the reviewers for this suggestion, as it could indeed, be of great interest and provide a direct proof of principle. Unfortunately, based on our experience in establishing such a cell line we know that just the generation of such a light-manipulated stable cell line that contains markers for centrosomes and chromosomes or kinetochores takes 6-9 months, in the best-case scenario. This experiment is therefore not possible within a normal revision round (even if extended to 6 months).

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Referee #3

Evidence, reproducibility and clarity

The manuscript entitled "centrosome age breaks spindle size symmetry even in "symmetrically" dividing cells" by Thomas and Meraldi reports that centrosome age impacts microtubule-nucleation capacity and is sufficient to tune spindle symmetry and cell size in human culture cell lines. The manuscript is overall clear, well written, illustrated and discussed. Nonetheless, some key experiments are missing as the authors report very subtle differences that need to be confirmed with complementary experiments, including time-lapse microscopy and alternative evaluations of cell sizes. The mechanism by which spindle symmetry breaking is established by centrosome age is not clear, even if the authors have identified some important actors at the spindle poles.

Major points:

1. The evaluation of spindle and cell size asymmetry related to centrosome age only relies on fixed sample preparation. Cells should be followed by time-lapse microscopy as the metaphase plate position relative to the spindle poles and/or the cell cortex may fluctuate over time and as the observed differences remain in a very subtle range. This is an important possibility to consider for 1:1, 1:0 or 0:0 spindle pole configurations where centrosome integrity is impaired.
2. Cell size asymmetry was evaluated based on cell area at the equator. Volumes will be a better indicator as daughter cell shapes can be different in telophase if they do not re-adhere at the same speed. This evaluation should also be confirmed with another readout, like the position of the cleavage furrow relative to the spindle poles in late anaphase, as again the observed differences are in a very subtle range.
3. The authors propose that differential microtubule nucleation at the spindle poles underlies spindle size symmetry breaking without providing direct evidence. If the observed spindle symmetry in the 1:1 configuration after pericentrin, CDK5RAP2 or -tubulin siRNA fuels this interpretation (Fig4C), the differential microtubule nucleation capacity at the spindle poles after microtubule-depolymerisation-repolymerisation assays was not evaluated in these conditions, as compared to the control situation.
4. If differential microtubule nucleation at the spindle poles is responsible for spindle asymmetry, overexpression of PCM proteins or -tubulin should be sufficient for re-establishment of symmetric protein distribution, spindle and cell size symmetry in 2:2 or 1:1 configuration. The authors should evaluate whether this is the case or not.
5. The authors describe that the cortex-centrosome distance is not changed according to centrosome age (Fig2C), but centrosome-metaphase plate distance is (Fig1D). These observations are difficult to reconcile if differential microtubule-nucleation capacity is at play. Again, time-lapse microscopy would enable to detect over time whether only metaphase plate position relative to spindle poles is changing or if spindle pole position relative to the cell cortex is also fluctuating.

Minor points:

1. Main PCM and MT nucleation protein "depletion" do not appear to impact spindle assembly, but only spindle symmetry in 1:1 and 1:0 configurations (Fig4A and 4F-H). Can it be explained by the fact that their depletion is not always total (for pericentrin, Fig5F versus FigS2A or Fig7G)? Can they comment on this point?
2. If centrosome age dictates spindle and cell size asymmetry through differential MT-nucleation capacity at the spindle poles, how can this process be modulated? Indeed, centrosome age is common to all cell types, but cell size asymmetry is more or less pronounced. The authors should further discuss this point based on the literature.

Significance

The question of whether centrosome age is translated into different capacity to nucleate microtubules and related consequences on spindle and cell size symmetry has already been addressed in different model systems. Nonetheless, cell lines were previously described as dividing symmetrically since their spindle is symmetric in size and since they give rise to daughter cells of equivalent sizes. The present manuscript reports a thorough re-evaluation of this question and provides evidence that subtle differences in PCM and spindle pole protein recruitment, microtubule-nucleation capacity and spindle symmetry can be observed as a function of centrosome age. They also identify some key actors whose differential recruitment at the spindle poles can underlie spindle symmetry breaking, even if their involvement seems to differ from one cell line to another one. This manuscript could be submitted after appropriate revisions as a report and will benefit to the basic research cell biology community.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In this study, the authors show that in two types of human tissue culture cells the half spindles associated with mother centrosomes are slightly longer, on average, than the half spindles associated with daughter centrioles. They show that this correlates with centrosome age, with mother centrosomes tending to be associated with the longer half spindle, and with a correlative asymmetry in the size of daughter cells. They show that spindle asymmetry relates to asymmetries in the amount of certain PCM components at centrosomes, including Pericentrin, CDK5RAP2, TPX2, and γ-tubulin, which preferentially accumulate at mother centrosomes. Pericentrin/CDK5RAP2/TPX2/γ-tubulin are known to be involved, directly or indirectly, with microtubule nucleation, and the authors also show how that microtubule nucleation is more robust at mother centrosomes and that depletion of either Pericentrin, CDK5RAP2, TPX2, or γ-tubulin abolishes (or reduces) spindle asymmetry. The suggestion is that enhanced microtubule nucleation at the mother centrosome leads to longer half spindles and subsequent asymmetric positioning of the division plane and daughter cells of unequal size. Centrosome and spindle asymmetry is partially masked by the apparent equal accumulation of PCM at daughter centrioles, such that cells with centrosomes containing only mother centrioles show higher levels of asymmetry.

Mechanistically, the authors show that a Cenexin-bound pool of Plk1, a kinase required for PCM assembly, is important for centrosome and spindle asymmetry. Cenexin is an "upstream" sub-distal appendage protein only found at mother centrosomes (due to appendage structures only being present on the grandmother centriole). Nevertheless, depletion of a more downstream sub-distal appendage protein, Centriolin, also abrogated spindle asymmetry, suggesting that multiple proteins of the sub-distal appendages are necessary for asymmetry. Results from some experiments show that spindle asymmetry and a known asymmetry in the distribution of polar centrosomes are mechanistically separable, while other experiments show a link.

Major comments:

1. It is not completely clear how the authors determined whether a spindle was asymmetric or not. In the methods, they say that statistical tests are described in the legends. In Figure 1 legend they say: "Each condition was compared to a theoretical distribution centered at 0 (dashed line)". How did they generate this theoretical distribution?
2. The authors claim that TPX2 depletion results in loss of spindle asymmetry in 1:1 cells, but the difference is very small (1.7% in control vs 1.3% in TPX2 depletion, Fig 5B) and the data is more variable in TPX2 depletion, which makes it less likely that a statistically significant difference from 0 would be found. Firstly, perhaps the authors could check the standard error of the mean, which provides a measure of how accurate the mean is with regard to N and variation. If a dataset is more spread (such as in TPX2 depletion) a higher N is required to attain the same accuracy in the mean value. This is normally not so important when directly comparing two datasets, but in this case the authors are comparing each dataset to 0. So, are the authors measuring enough cells in the TPX2 depletion to be sure that a 1.3% value is not significantly different from 0? Secondly, I don't understand why the control cells have such a low asymmetry index (1.7%), when previous data in the paper shows an asymmetry index of 4.1% (Fig 1D) and 3.4% (Fig 4E) in control 1:1 cells. This suggests that something about the way this experiment was carried out dampens the asymmetry, which could therefore lead the authors to conclude that TPX2 is more important than it really is.
3. The authors claim that daughter centrioles are associated with some Pericentrin and suggest that this may be why 2:2 centrosomes have less of an asymmetry than 1:1 centrosomes (Fig 6A). It is unclear whether the authors consider these daughter centrioles as being prematurely disengaged (they make reference to the fact that they previously showed how disengaged daughters recruit γ-tubulin, but it's unclear if this is related to their current observations). In Figure 6A, the Centrin spots look too far apart for engaged centrioles (~750nm). I appreciate that this may be the only way to dectect Pericentrin around the daughter at this resolution, but it may also force the authors to select cells where the centrioles have prematurely disengaged. For the asymmetry measurements, the authors presumably did not select cells where they could distinguish mother and daughter centrioles. One way to address this issue would be to compare PCM size at centrosomes in 2:2 cells with centrosomes in 1:1 cells. The expectation would be that centrosomes in 2:2 cells would have more PCM, due to the contribution of the daughter centrioles.
4. The authors show that Plk1 recruitment by Cenexin (via S796 phosphorylation), which happens only at mother centrosomes, is important for asymmetry. Nevertheless, they show that Plk1 is symmetrically distributed between mother and daughter centrosomes (Table 1). This does not really fit, unless daughter centrosomes recruit more cenexin-independent Plk1 than mother centrosomes or if the cenexin-bound pool of Plk1 is only a minor fraction of total Plk1. If so, do the authors think that the Cenexin-bound pool of Plk1 is more potent than the rest of centrosomal Plk1?
5. The circles drawn to measure cell size in Figures 2A,E and 7C do not look like a good representation of cell area (as the cells are not perfectly round). The authors use a formular for circle area with an approximation of the radius (based on mean length/width of an oval. It would be much better to use ImageJ to draw a freehand line around the perimeter of the cell and use the in-built tool to measure the area.

Minor comments:

1. Asymmetry in centrosome size that correlates with centrosome age in apparently symmetrically dividing "cells" has been observed previously in Drosophila syncytial embryos (Conduit et al., 2010a, Curr. Bio.). I think this should be mentioned somewhere given the topic of the study.
2. A full description of statistical tests and n numbers for each experiment should be provided in the methods, even if this duplicates information in the Figure legends.

OPTIONAL EXPERIMENTS: 3. Given that chTOG is very important for microtubule nucleation, it seems strange that this protein was not analysed for a potential asymmetry. 4. Cooling-warming experiments could be done using higher concentration of formaldehyde, as it's likely that microtubule nucleation is not immediately halted when using 4% formaldehyde.

Significance

This a well-conducted study with results being presented clearly and concisely. The methodology is solid in the main. The study reveals something unexpected - that apparently symmetrically dividing human tissue culture cells divide asymmetrically. While the asymmetry is only slight, it could be important - although the authors do not address its relevance for the cell population. Having analysed only 2 cultured cell types, it remains unclear if this is a widespread phenomenon, and whether this occurs in a more natural setting. Nevertheless, the proposed model (Plk1 at SDA's => increased PCM at mother => increased nucleation => offset division plane), which is supported by the data, would suggest this could be a widespread phenomenon. This study will be of interest to anyone studying cell division, but it would require some degree of insight into the importance of the observations for it to appeal to a very broad audience.

I am a cell biologist with an interest in cell division and microtubule regulation.

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Referee #1

Evidence, reproducibility and clarity

In this paper, the authors demonstrated that there is asymmetry in mitotic spindles, which are usually considered symmetric. That is, they found that centrosome age causes asymmetry in the size of the half-spindle even when the number of centrioles forming the spindle poles is the usual pair or when there is only one mother centriole. It is also suggested that the difference in half-spindle size is due to the different microtubule-organizing activity of the centrosomes at each spindle pole. Furthermore, they observe that the difference in half-spindle size also results in asymmetries in the size of the daughter cells after cell division. In this study, they mainly analyze the mechanism by employing the condition of 1:1 number of centrioles, in which the difference in half-spindle size is more sharply pronounced. They showed that the subdistal appendage (SDA) of the centriole of the old centrosome is important for the molecular basis of this half-spindle size difference, as the SDA-dependent recruitment of the Plk1 pool mediates an asymmetric localization of pericentrin, Cdk5rap2, gamma-tubulin, TPX2, and other factors at the spindle poles. In addition, knockdown of these factors eliminated the half-spindle size asymmetry. They also confirm these findings using a different human cell line, BJ cells. In conclusion, they propose that, reflecting centrosome age, the old centrosome promotes asymmetric spindle formation by localizing a group of factors that promote microtubule organization, originating from the SDA-Plk1 pathway.

Major points

1. The discovery of differences in half-spindle size during symmetric division is intriguing. However, the methodology for quantification of the data remains unclear. Key questions, such as how the center of the metaphase plate is determined from the image data, the definition of exact pole position when centrioles are located at spindle poles, the objective determination of daughter cell diameter and width from the image data, and the referential position of the cortex, need more detailed explanation in the manuscript. Additionally, it's crucial to elucidate the specific index used to quantify differences from the image data, especially when dealing with data that only varies by a few percent. Providing clarity on these aspects and, in some cases, re-quantifying the data should be necessary.
2. The mechanism behind the difference in half-spindle size, related to the subdistal appendage (SDA), raises questions, especially considering that SDA is believed to disassemble during mitosis. Exploring whether differences in the localization of PCM components and half-spindle size result from disparities in Plk1 and PCM loading during G2/early mitosis, prior to SDA disassembly, necessitates experimental verification.
3. For investigating the mechanism of half-spindle size asymmetry, many perturbation experiments employ knock-down techniques. To directly address the cause of asymmetry, it might be valuable to artificially localize Plk1 and PCM factors to one spindle pole using optogenetic tools or similar approaches and then quantify half-spindle and daughter cell sizes.
4. The asymmetry in Plk1 sub-population recruitment by SDA triggers the observed effects, but the evidence for this is relatively weak, given the small difference in spindle asymmetry. Quantifying the amount of Plk1 in its activated form, particularly in the context of SDA dismantling during metaphase, could strengthen this aspect of the study.
5. While the focus on half-spindle size asymmetry during symmetric division is intriguing, it's important to address the broader physiological significance. The primary outcome of this asymmetry is differences in daughter cell size, which limits the broader significance of the study. Furthermore, the quantification method for daughter cell size warrants scrutiny and clarification.

Minor points

1. Table 1 lists factors with asymmetric localization not analyzed in detail in this paper. It would be beneficial to discuss whether these factors play a role in spindle asymmetry, and the authors should address the completeness of the data in Table 1 in terms of selecting factors for analysis.
2. In Figure 1H, the impact of centriolin knock-out on the distribution of unaligned polar chromosomes is different from the effect of cenexin S796A in Figure 6H. This difference should be explained to provide clarity on the observed discrepancies.
3. In Figure 2A, there is no correlation data presented between daughter cell asymmetry and the presence or absence of cenexin signal. This relationship should be elucidated for a more comprehensive understanding.
4. In Figure 4G and H, the mean value of spindle asymmetry increases with siRNA treatment of Cdk5Rap2 or PCNT compared to the control. The possible interpretation of this finding should be discussed.
5. Figure 4K shows that the asymmetry of PCNT distribution is not eliminated by centriolin knock-down. This observation requires clarification and discussion.
6. It appears that the difference in spindle asymmetry of the control group in Figure 5A is smaller than in other data. This discrepancy should be addressed. Additionally, the influence of TPX2 depletion on spindle formation, and any corresponding spindle staining data, should be included.
7. Claiming that the daughter centriole recruits PCM based on Figure 6A data alone may require additional supporting evidence. It is essential to investigate whether there is a clear PCM signal when the daughter centriole disengages in late mitosis and maintain consistency in the interpretation.
8. The lack of difference in TPX2 distribution in Figure 7E should be explained, along with a discussion of how this observation aligns with the spindle asymmetry data and any inconsistencies.
9. The differing N numbers between samples in all the figures may affect the validity of comparisons. The authors should discuss whether it is necessary to have consistent N numbers in each experiment for more robust conclusions.

Significance

In summary, while the study is intriguing for its exploration of spindle asymmetry during symmetric division, the major points raised here highlight areas where further clarification and data interpretation are needed. A more rigorous quantification method and additional evidence to support the proposed SDA-Plk1 signal as the initiator of asymmetry would enhance the study's validity. Moreover, addressing concerns about daughter cell size quantification and the physiological relevance of spindle asymmetry is essential for a more comprehensive understanding of the findings. This research presents an interesting challenge for researchers in the centrosome and mitotic spindle field.

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Reply to the reviewers

Manuscript number: RC-2023-02172

Corresponding author(s): Philip Elks

[The “revision plan” should delineate the revisions that authors intend to carry out in response to the points raised by the referees. It also provides the authors with the opportunity to explain their view of the paper and of the referee reports.

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1. General Statements [optional]

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In this paper we report the discovery that a member of the tribbles pseudokinase family, TRIB1 is expressed in human monocytes and is upregulated after stimulation with mycobacterial antigen in a human patient challenge model, the first direct link between immune cell Tribbles expression and innate immune response to infection. We then interrogated the mechanisms of Tribbles roles in TB using a human disease relevant whole-organism in vivo zebrafish model of TB. We show that specifically TRIB1 modulation can tip the battle between host and pathogen enhancing the innate immune response and reducing bacterial burden. We then uncover the molecular mechanisms responsible for the host protective effect of TRIB1, with enhanced antimicrobial reactive nitrogen species and il-1beta, via cooperation with Cop1 E3 ubiquitin ligase. Our findings demonstrate, for the first time, TRIB1 as a host moderator of antimicrobial mechanisms, whose manipulation is of benefit to the host during mycobacterial infection and as such, a potential novel therapeutic target against TB infection.

We thank the reviewers for their positive appraisal of our work and for their helpful suggestions that will improve our manuscript. In particular we would like to highlight the reviewer’s comments on the gap/need for a new zebrafish in vivo model to understand the roles of tribbles in infection that can “be extrapolated into the human system”, and how they feel these findings will be of broad interest and “significance to cross section of the research community” attracting “interest from readers in the fields of infection, immunity, hematology and animal models” alongside “researchers studying all aspects of Tribbles pseudokinase function, especially researchers seeking models to test small molecule agonists and antagonists.”

2. Description of the planned revisions

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Reviewer 1

The major weakness of the manuscript is that the authors do not evaluate C/EBP transcription factors at all. It is rather surprising as they emphasize cooperation between Trib1 and Cop1 in the main title. C/EBP family proteins are key factors of Trib1-mediated modulation of granulocytes and monocytes. Also, slbo, a drosophila homolog of C/EBP, is a target of tribbles, indicating that the pathway is evolutionary conserved. I would request the following experiments and discussions.

RESPONSE: We agree that possible C/EBP roles should be discussed in detail, and we will add a new discussion section on this.

We stand by our data that the host protective mechanism of Trib1 acts requires Cop1, but we are not able to directly show a C/EBP mechanism within the scope of the current project due to a lack of tools/knowledge in the zebrafish on this (further points/comments below on this). It is important to note that we have not claimed a C/EBP mechanism in our manuscript, and we think it is possibly unlikely given that monocyte and granulocyte numbers are not altered after TRIB1 manipulation. Indeed, there are many other candidates other than C/EBP that COP1 could be acting through. Some examples include MAPK (Niespolo et al., Front Immunol, 2020), serine threonine kinases (Durzynska et al., Structure, 2017) and beta-Catenin (Zahid et al., Proteins, 2022).

In response to this comment, we have modified the title from “Tribbles1 and Cop1 cooperate to protect the host during in vivo mycobacterial infection” to “Tribbles1 is host protective during in vivo mycobacterial infection”. We believe our data does show that the protective effect of Tribbles requires Cop1, but changing the title in this way removes any suggestion that they directly cooperate in the potential C/EBP dependent manner, suggested by the reviewer.

Although the authors found the number of neutrophils and monocytes unchanged by Trib1 overexpression nor knockdown, they did not demonstrate the differentiation status of both cell types. This is quite an important issue, given that Trib1 knockout promotes granulocytic differentiation via C/EBPa accumulation in mice. Also, the analysis of granulocytic/monocytic differentiation will provide the crucial information how Trib1 protects the host from mycobacterial infection regulating hematopoietic cell functions. The authors should perform morphological analysis and examine cell surface marker expression to examine whether Trib1 and Cop1 modulates granulocytic and monocytic differentiation with and without Mm infection.

RESPONSE: Unfortunately, we do not have the same level of immunology knowledge nor the antibodies to look at cell surface markers in zebrafish larvae (it is noted that the reviewer identifies that they “not have sufficient expertise in zebrafish models.” We agree with the reviewer that this would be an obvious and informative experiment to do in mouse models, but is not currently possible in zebrafish larval models). The transgenic promoters used (mpx for neutrophils and mpeg1) are robust and widely published to look at total neutrophil and macrophage numbers (Renshaw et al., Blood 2006; Ellett et al., Blood 2011). Mpx, encoding myeloperoxidase, is expressed late in neutrophil differentiation. It is also worth noting that the zebrafish larval model is still a developing organism, and neutrophil/macrophage numbers rise every day between 1 and 5 days post fertilisation, therefore any effect/delay in leukocyte differentiation would likely be captured at the 2dpf timepoint we have already quantified. We cannot perform leukocyte counts during Mm infection reliably as neutrophils/macrophages cluster around infected areas making counting challenging.

However, in response to this comment we will:

1. Use a new Tribbles 1 stable CRISPR-Cas9 knockout mutant we have generated and assess neutrophil differentiation using Sudan Black (SD). SD stains neutrophil granules the development of which is during a late phase of neutrophil differentiation.
2. Interestingly, it has been shown that a zebrafish myeloid specific C/EBP (c/ebp1) is not required for initial macrophage or granulocyte development, but knockdown does result in a loss of the secondary granule gene LysC (Su et al., Zebrafish, 2007). Therefore, our findings are not inconsistent with existing literature, even if C/EBPs are regulated by Tribbles. However, to test this further we will use an LysC:mCherry transgenic line (Buchan et al., PLoS One 2019) to assess expression in developing neutrophils after trib1 manipulation.

It is interesting that Cop1 knockdown zebrafish is viable, given its ubiquitous expression and multiple important targets of protein degradation. The authors should provide the details of phenotype of Cop1 KO larva and discuss on this issue.

RESPONSE: Zebrafish mutants are much less often embryonic lethal than mice as maternally contributed protein stores allow for basic metabolic functions to occur throughout the short period of embryonic development (Rossant and Hopkins. Genes and Development 1992). However, in the case of Cop1 Crispant, this is a knockdown rather than a knockout, so there may be sufficient remaining Cop1 availability for development if it is indeed a requirement for larval viability. Although Cop1 knockout mice are non-viable, hypomorphs are viable and develop relatively normally (similar to our knockdown zebrafish) but are tumour prone as Cop1 is required for effective tumour suppression (Milgliorini et al., JCI, 2011).

We had not commented on the Cop1 larvae phenotype as they look like they develop normally eg. normal body axis, development. However, we agree that this is a relevant point to incorporate into the manuscript and thus will add a comment on this in the Results section. Furthermore, we will add wholebody neutrophil counts into supplementary information, which we have performed and there is no change with cop1 knockdown, suggesting no difference in granulopoiesis.

[Optional] To obtain the more solid evidence for the Cop1 dependent function of Trib1 on mycobacteria infection, it is better to use the Trib1 mutant that loses the Cop1 binding activity. This experiment will strength the authors' conclusion of the Trib1 and Cop1 cooperation.

RESPONSE: We will address this comment by using a newly generated stable zebrafish CRISPR-Cas9 Tribbles 1 knockout line with a 14 base pair deletion that is predicted to lead a premature stop at 94aa in the middle of the pseudokinase domain, lacking the catalytic loop. This also lacks the predicted COP1 binding area at the C terminal of the protein. We will assess bacterial burden in this model.

1. Previous studies have shown multiple defects in hematopoietic lineages such as M2-like macrophages and eosinophils in Trib1 KO mice, suggesting that Trib1 affects cellular functions of macrophages upon mycobacteria infection. I would request the authors to mention some ideas on this point in discussion.

RESPONSE: We will add a section in the discussion to address this.

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Reviewer 2

Structural comparisons are relatively descriptive of identity etc. Nowadays it should be relatively straightforward to comment on structural conservation based on Alphafold models. Specific details may not be accurate but gross folds will be, and comparing those may be more informative.

RESPONSE: We have taken an initial look at Alphafold models and there are indeed structural similarities between zebrafish and human Tribbles. We will incorporate Alphafold structural models and comment on similarities/differences.

Some discussion of the mechanisms regulating TRIB1/2/3 transcriptionally is probably relevant given the differential upregulation observed during infection. There is quite a bit of characterisation of different Tribble promoter regions in humans-how Edoes this translate to Zebrafish?

RESPONSE: We will add a discussion point on what is known about Tribbles promoter regions in humans. We will assess whether anything is known about the promoter regions in zebrafish Tribbles (we have not identified literature on this currently). If nothing is known on this in zebrafish we will attempt to search for regulatory regions found in humans in the zebrafish promoters.

In terms of Crispr use-can it be confirmed that Crispr modified cell lines have effects at the protein level? This is not my specific expertise, but the supplementary evidence shown seems to show some genomic editing is occurring, but not necessarily how it effects protein levels.

RESPONSE: We do not have antibodies that work on zebrafish Tribbles proteins to assess this directly. However, we will address this comment by using a newly generated stable zebrafish CRISPR Tribbles 1 knockout line with a 14 base pair deletion that is predicted to lead a premature stop at 94aa in the middle of the pseudokinase domain, lacking the catalytic loop. Unlike the “CRISPant” knockdown work in the peer-reviewed version, this represents a full knockout of Tribbles 1. We will assess the trib1 cDNA of the full knockout line to assess the knockout in terms of transcript.

A major conclusion of the paper seems to be that TRIB1 works with COP1 in Zebrafish to mediate response to infection. However the discussion does not particularly tie this with the other discussed mechanisms. E.g. JAK/STS, and EBP-linked responses are discussed separately from COP1, where they could well be linked?

RESPONSE: We agree and this comment fits in with some comments from reviewer 1. We will rework areas of the discussion to address this and bring possible mechanisms together into a new discission section.

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Reviewer 3

All comments addressed in new revision (see below).

It is noted that this reviewer has “expertise from genetic studies of model organisms to assess all aspects of the tools and approaches used in the paper.”

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

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Reviewer 1

Figure 1D, E, F is mislabeled in lines 268-271.

RESPONSE: Apologies for this typo, this has now been changed.

Typo in line 399.

RESPONSE: We have changed “suggesting” to “suggest”.

Figure 6A-B is mislabeled in line 415

RESPONSE: Apologies for this typo. We have changed this from “Figure 5A-B” to “Figure 6A-B”.

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Reviewer 2

• *

While the protective effect is stated as an effect size 'close to that of HIF-1a', is there additional rationale suggesting that the two may be linked?

RESPONSE: Yes, there have been a number of studies that link Tribbles and Hif1-alpha. The best characterised link is in different cancer cells where Tribbles 3 has been linked to HIF-1alpha or hypoxia (in breast cancer (Wennemers, Breast Cancer Research 2011), renal cell carcinoma cells (Hong et al., Inj J Biol Sci, 2019) and adenocarcinoma (Xing et al., Cancer Management Research, 2020). In Drosophila Hif-1alpha induces TRIB in fat body tissue (Noguchi et al., Genes Cells 2022). We have now added references to these studies to the relevant section in the results.

Reviewer 3

• *

Minor issues: small problems with clarity and figure panel correlation as detailed below:

Mycobacterium marinum Lines 363-365 Refers to Fig 2C-D should be 3C-D

RESPONSE: Apologies for this typo. This has now been changed to 3C-D.

negative controls DN Hif-1alpha and PR (Figure 4A-B). Similarly, trib1 overexpression increased the levels of anti-nitrotyrosine staining, a proxy for immune cell antimicrobial nitric oxide production (Forlenza et al. 2008), to similar levels of DA Hif-1alpha (Elks et al. 2014; Elks et al) Not seeing this for Trib1

RESPONSE: We are not completely sure what the reviewer is referring to here. We think possible confusion stems from the increase of nitric oxide in trib1 is compared to the phenol red control, so we have now clarified that in the text.

As previously observed, overexpression of trib1 significantly reduced bacterial burden compared to phenol red controls when co-injected with tyrosinase guide (Figure 5A-B).

The Fig 3 A-B is correct, although 6A-B appear to be novel panels showing this result

RESPONSE: Yes, we agree, 6A-B has new results showing similar results to 3A-B, as it is necessary to include siblings from the same clutch in each graph to make direct comparisons. To avoid unnecessary confusion, we have removed the “as previously observed” for figure 6 as we had not previously had the tyrosinase co-injection so these are indeed new data.

444 no comma 446 no comma 457 no comma after "activation"

RESPONSE: We have removed these punctuations.

472-475 confusing - better structure in particular in 474 what does "this" refer to?

RESPONSE: We agree, and have clarified in the following new, clarified sentences:

“Lipid droplets form in macrophages during Mtb infection that are potentially used as source of lipids by Mtb to allow for intracellular growth (Daniel et al. 2011). However, more recent findings suggest that lipid droplets are formed during the immune activation process after macrophage Mtb infection (Knight et al. 2018), that can subsequently influence the dynamics response of macrophage host defence (Menon et al. 2019). This macrophage lipid metabolism and handling could potentially be influenced by Tribbles.”

525-526 confusing - better structure perhaps begin with 'Because...'

RESPONSE: We have changed this confusing sentence to:

“Here, we demonstrate il-1b and NO control by Trib1, suggesting that Trib1 controls multiple immune pathways and that therapeutic Trib1 manipulation may be more effective than targeting individual immune pathways alone.”

confusing 538 "this and 539 pave the way for further research into TRIB1 as a target for host-derived therapies" Perhaps "further research into TRIB1 as a target for host-derived therapies could potentially improve infection outcome of mycobacterial infection via pharmacological targeted delivery methods and transient manipulation through genetic approaches"

RESPONSE: We have changed this sentence as suggested.

4. 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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Reviewer 1

1. The authors should investigate the expression of the C/EBPa protein p42 isoform and/or other C/EBP family proteins such as C/EBPb, and confirm that the p42 is degraded by Trib1 overexpression and recovered by Trib1 and Cop1 knockout. It is also important to determine both p42 and p30 isoforms are preserved in zebrafish.

RESPONSE: This is a complex point to unpick in zebrafish and we believe this to be out of the scope of the current project. We do not claim a link to C/EBP. As mentioned in above comments we think that a link to C/EBP may be unlikely given that monocyte and granulocyte numbers are not altered after TRIB1 manipulation. We will add more data to look at different markers of neutrophils (see above comments). There are many other candidates other than C/EBP that COP1 could be acting through. Some examples include MAPK (Niespolo et al., Front Immunol, 2020), serine threonine kinases (Durzynska et al., Structure, 2017) and beta-Catenin (Zahid et al., Proteins, 2022). There is also evidence suggesting that COP1 and C/EBP have distinct binding sites on TRIB1, potentially unlinking their activity in some biological situations (Murphy et al., Structure, 2015).

C/EBPa is found in zebrafish and is involved in myeloid differentiation and haematopoeisis (Yuan et al., Blood 2011). There is not a huge amount in the literature on this, but it has been shown in zebrafish models that the drug Tanshinone IIA reduces C/EBPa (Park et al., In J Mol Sci, 2017) and we know from previous work in our department that Tanshinone IIA does not affect total neutrophil numbers in the zebrafish larvae (Robertson et al., Sci Trans Medicine, 2014). The most involved C/EBP in zebrafish myelopoiesis appears is a zebrafish specific isoform called c/ebp1 that is myeloid expressed (Lyons et al., Blood 2001). This has a highly conserved carboxy-terminal bZIP domain but the amino-terminal domains are unique. Interestingly, reduction of c/ebp1 does not ablate initial macrophage or granulocyte development, but did result in loss of expression of LysC, a secondary granule marker (we are checking expression of this gene after Trib1 modulation using a LysC:mCherry transgenic zebrafish line).

We do not have antibodies or tools to detect p42 and p30 in zebrafish. As Tribbles1 regulation of C/EBPa appears to be post-translational (Bauer et al., J Clin Invest, 2015), this would be incredibly challenging to unpick in the zebrafish model due to lack of tools to do this. Due to this and the reasons above we believe this to be out of the scope of the current project.

[Optional] The effect of enhanced ERK phosphorylation by Trib1 for the protective effect against mycobacterial infection is another interesting point. It would be better if the authors could provide the ERK phosphorylation status upon Trib1 overexpression.

RESPONSE: Unfortunately, we have no method to answer this question to a conclusive level within the scope of this project. There are limited reports of phosphorylated ERK antibodies that work in wholemount zebrafish (eg, Maurer and Sagerström, BMC Developmental Biology, 2018, that use a rabbit antibody), but this is widely expressed in many tissues of the zebrafish and immune cells would be challenging to resolve.

Reviewer 2

We have addressed or propose to address all of reviewer 2’s comments.

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Reviewer 3

We have addressed or propose to address all of reviewer 3’s comments.

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Referee #3

Evidence, reproducibility and clarity

Summary: In this manuscript, the authors test the role of Tribbles psuedokinase 1 in the primary immune defence against Mycobacterium tuberculosis, the pathogen in tuberculosis. After showing increased Trib1 and 2 in response to mycobacterial infection cell culture and from biopsies of challenged human tissue, they turn to a zebrafish model of infection of the caudal vein with Mycobacterium marinum, a natural fish pathogen similar in effects on macrophages to M. tuberculosis in humans.

Authors find that overexpression of tribs 1, 2 and 3 had no strong effect on development but reduced the bacterial burder significantly for Trib1, less so for Trib2 and not at all for Trib3. Converesely, Trib1 Crisper-mediated knockdown increased Mm burde, which 3 had no effect ( and 2 guide RNAs were not effective at reducing Trib2).

Trib1 increased levels of pro-inflammatory interleukin 1 beta, as measure by a reporter gne , which Trib3 had no similar effect, which was on par to the effect of the Hif-1alpha transcription factor, known to regulate il-1beta. The effect of Trib1 was not upon increased Hif-a (hence independent) but was dependent on the co-factor COP1, a known target of the Trib1 C-tail when activated

No major problems seen

Minor issues: small problems with clarity and figure panel correlation as detailed below Mycobacterium marinum Lines 363-365 Refers to Fig 2C-D should be 3C-D

1. 386 negative controls DN Hif-1and PR (Figure 4A-B). Similarly, trib1 overexpression increased
2. 387 the levels of anti-nitrotyrosine staining, a proxy for immune cell antimicrobial nitric oxide

3. 388 production (Forlenza et al. 2008), to similar levels of DA Hif-1(Elks et al. 2014; Elks et al. Not seeing this for Trib1

4. 414 As previously observed, overexpression of trib1 significantly reduced bacterial burden

5. 415 compared to phenol red controls when co-injected with tyrosinase guide (Figure 5A-B). The Fig 3 A-B is correct, although 6A-B appear to be novel panels showing this result

444 no comma 446 no comma 457 no comma after "activation" 472-475 confusing - better structure in particular in 474 what does "this" refer to? 525-526 confusing - better structure perhaps begin with 'Because...'

confusing 538 "this and 539 pave the way for further research into TRIB1 as a target for host-derived therapies"

Perhaps "further research into TRIB1 as a target for host-derived therapies could potentially improve infection outcome of mycobacterial infection via pharmacological targeted delivery methods and transient manipulation through genetic approaches"

Significance

General assessment: The paper is well written and clear. The importance of developing host derived therapies is stated well in the introduction and the discussion makes clear the significance of the work to developing the zebrafish as a useful alternative to traditional models for studying the pathophysiology of mycobacterial infection.

Advance: for the Tribbles field, which I can comment on, this advances an important and neglected model organism (the zebrafish), introducing this set of three homologs Trib1, 2 and 3, that are well studied in mammals, Drosophila and C.elegans.

Audience: The paper will be of significance to cross section of the research community on the one hand developing novel approaches to treat TB and on the other to researchers studying all aspects of Tribbles pseudokinase function, especially researchers seeking models to test small molecule agonists and antagonists.

I have expertise from genetic studies of model organisms to assess all aspects of the tools and approaches used in the paper.

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Referee #2

Evidence, reproducibility and clarity

The paper by Hammond et al characterises the role of Tribbles proteins in Zebrafish in response to MTb infection. They show interesting upregulation of TRIB1 and 2, relative to TRIB3 which is not upregulated. This may provide an interesting system to further explore the role of Tribbles in response to infection, which is currently underexplored, but could do with some additional detail to stake that claim more strongly.

Major Comments

Some discussion of the mechanisms regulating TRIB1/2/3 transcriptionally is probably relevant given the differential upregulation observed during infection. There is quite a bit of characterisation of different Tribble promoter regions in humans-how does this translate to Zebrafish?

Structural comparisons are relatively descriptive of identity etc. Nowadays it should be relatively straightforward to comment on structural conservation based on Alphafold models. Specific details may not be accurate but gross folds will be, and comparing those may be more informative.

In terms of Crispr use-can it be confirmed that Crispr modified cell lines have effects at the protein level? This is not my specific expertise, but the supplementary evidence shown seems to show some genomic editing is occurring, but not necessairly how it effects protein levels.

While the protective effect is stated as an effect size 'close to that of HIF-1a', is there additional rationale suggesting that the two may be linked?

Minor comment

A major conclusion of the paper seems to be that TRIB1 works with COP1 in Zebrafish to mediate response to infection. However the discussion does not particularly tie this with the other discussed mechanisms. E.g. JAK/STS, and EBP-linked responses are discussed seperately from COP1, where they could well be linked?

Significance

Tribbles are clearly important in immune cell development. The work is an interesting foray into Tribbles in Zebrafish, which is an interesting tool to be developed going forward. It also hints at a broader role of Tribbles in human infection, but this requires more work to play out.

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Referee #1

Evidence, reproducibility and clarity

Summary

The paper by Hammond et al. describes the protective role of Trib1 for mycobacterial infection such as tuberculosis. They first found that TRIB1 expression is upregulated upon mycobacterial antigen injection in human monocytes. They then tried to perform functional studies using a zebrafish model. To achieve the study, they confirmed the preservation of Trib family genes in zebrafish. The transgenic zebrafish expressing exogenous trib1 demonstrated decreased bacterial burden of M. marium, and trib1 knockdown showed the opposite effect. Trib1 expression also induced the production of Il1B and NO in the Hif independent manner. Finally, they found that cop1 knockdown reduced trib1-mediated protection against Mm infection.

Major comments

The major weakness of the manuscript is that the authors do not evaluate C/EBP transcription factors at all. It is rather surprising as they emphasize cooperation between Trib1 and Cop1 in the main title. C/EBP family proteins are key factors of Trib1-mediated modulation of granulocytes and monocytes. Also, slbo, a drosophila homolog of C/EBP, is a target of tribbles, indicating that the pathway is evolutionary conserved. I would request the following experiments and discussions.

1. The authors should investigate the expression of the C/EBPa protein p42 isoform and/or other C/EBP family proteins such as C/EBPb, and confirm that the p42 is degraded by Trib1 overexpression and recovered by Trib1 and Cop1 knockout. It is also important to determine both p42 and p30 isoforms are preserved in zebrafish.
2. Although the authors found the number of neutrophils and monocytes unchanged by Trib1 overexpression nor knockdown, they did not demonstrate the differentiation status of both cell types. This is quite an important issue, given that Trib1 knockout promotes granulocytic differentiation via C/EBPa accumulation in mice. Also, the analysis of granulocytic/monocytic differentiation will provide the crucial information how Trib1 protects the host from mycobacterial infection regulating hematopoietic cell functions. The authors should perform morphological analysis and examine cell surface marker expression to examine whether Trib1 and Cop1 modulates granulocytic and monocytic differentiation with and without Mm infection.
3. It is interesting that Cop1 knockdown zebrafish is viable, given its ubiquitous expression and multiple important targets of protein degradation. The authors should provide the details of phenotype of Cop1 KO larva and discuss on this issue.
4. [Optional] The effect of enhanced ERK phosphorylation by Trib1 for the protective effect against mycobacterial infection is another interesting point. It would be better if the authors could provide the ERK phosphorylation status upon Trib1 overexpression.
5. [Optional] To obtain the more solid evidence for the Cop1 dependent function of Trib1 on mycobacteria infection, it is better to use the Trib1 mutant that loses the Cop1 binding activity. This experiment will strength the authors' conclusion of the Trib1 and Cop1 cooperation.

Minor comments

1. Previous studies have shown multiple defects in hematopoietic lineages such as M2-like macrophages and eosinophils in Trib1 KO mice, suggesting that Trib1 affects cellular functions of macrophages upon mycobacteria infection. I would request the authors to mention some ideas on this point in discussion.
2. Figure 1D, E, F is mislabeled in lines 268-271.
3. Typo in line 399.
4. Figure 6A-B is mislabeled in line 415

Referees cross-commenting

I do not have any cross-comments, however, I believe comments of other reviewers are helpful for authors.

Significance

This study is the first report on the Tribbles protective function for mycobacterial infection. The use of the zebrafish model is unique and provides useful information on tribbles family genes are expressed in hematopoietic cells in zebrafish. As granulocytic and monocytic functions are conserved between fish and mammals, the results can be extrapolated into the human system to understand infection and pathogenic mechanisms of mycobacterium. The lack of investigation on C/EBP transcription factors is a major limitation to be improved in this study, since C/EBPa is a key molecule in the Trib1 and Cop1 cooperation in granulocytic differentiation. The manuscript will attract interest from readers in the fields of infection, immunity, hematology and animal models. This reviewer's field of expertise is hematology/oncology/model animals, although I do not have sufficient expertise in zebrafish models.

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Reply to the reviewers

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

The mechanisms that differentiate ER from the nuclear envelope (NE) remain to be fully elucidated but likely depend at least in part on junctions between the ER and NE. How such junctions are formed and maintained is the subject of this manuscript where extensive correlative light and electron microscopy is used to observe and characterize ER-nuclear envelope (ER-NE) junctions at distinct phases of the cell cycle. The authors make use of their own electron tomography data as well as publicly available focused-ion beam scanning electron microscopy (FIB-SEM) datasets to compare the morphology of these junctions in different human cell types as well as in budding yeast. The major finding is that ER-NE junctions in human cell lines are more constricted than ER-ER junctions, often to the point of excluding lumen. The examination of mitotic cells suggests that this constriction likely occurs at the end of mitosis as the NE is completing its maturation from ER to NE. The implications of these morphological changes are discussed but there are no mechanistic or functional studies. Overall, the data are well presented, are of high quality and are rigorously evaluated. The manuscript is well written and scholarly, and the speculations as to the function of the constrictions are reasonable. I only have minor comments. *We thank the reviewer for the positive evaluation on our work and for the useful suggestions on how to further improve the manuscript.

1. * In Figure 2D, the authors present evidence to demonstrate that an hourglass-like constriction occurs at ER-NE junctions. From the side view, it is difficult to interpret this on the plot, particularly for the ER-NE junctions with a lumen. Perhaps, in the supplemental data, the authors could plot both with and without lumen data separately, and color-code individual traces? I believe this would convey the hourglass nature of these constrictions more clearly.* To make it easier to see individual membrane profiles, we will plot the profiles with and without lumen separately and labelled each profile with distinct colour, as the reviewer suggested.

* In the Methods section, the authors should describe how carbon-coating of sapphire discs was achieved. If these were provided from the manufacturer precoated, this should be specified.*

We coated the sapphire discs with carbon by ourselves. We will specify how the carbon-coating was done in the revised manuscript.

* On page 10, Figure 5F callout 9 lines from the bottom likely should be 5E. We will correct this error.

Reviewer #1 (Significance (Required)):

Overall, this work provides an important new morphological perspective on the nature of ER-NE junctions in human cells. As the authors describe in their introduction, such junctions have been noted previously in the literature but not in a dedicated study using modern imaging techniques in human cell lines. In describing the morphology of these junctions, the authors lay the groundwork for future mechanistic, functional, and structural studies. We thank the reviewer for appreciating the significance and the impact of our work.

*

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• *

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

Summary: In this manuscript, Bragulat-Teixidor et al., use correlative live-cell imaging and electron tomography to study the structure of the endoplasmic reticulum-nuclear envelope (ER-NE) junction in HeLa cells (and also in S. cerevisiae). The authors also make use of publicly available whole-cell FIB-SEM datasets to study ER-NE junctions in mouse pancreatic islet, HeLa, and human macrophage cells to corroborate their findings in other cell types.

The authors show that the structure of the ER-NE junction in interphase cells adopts an hourglass shape with a constricted neck. Comparing the ER-NE junction to the ER tubule-sheet junction, the authors show that these structures are different: the ER tubule-sheet junction is not constricted. Because the NE forms from the ER during postmitotic NE assembly, the authors compare the structure of the ER-NE junctions in anaphase, telophase, and interphase cells, and find that the junction becomes constricted in telophase. The number of ER-NE junctions increase going from telophase to interphase.

While the authors do not provide any direct evidence for this, they propose a functional model where the ER-NE junction is constricted because it regulates the supply of certain lipids and proteins from the ER to the NE. One proposed example is that the constriction of the ER-NE junction might prevent the passage of large protein aggregates from entering the NE.

The general question of how the structure of the ER-NE junction might regulate the passage of lipids and proteins from the ER to the NE is interesting and potentially important. However, the authors should address the following issues to improve the accuracy and completeness of this manuscript for it to be considered for publication. *We thank the reviewer for the appreciation of our work and the thoughtful suggestions for further improvements.

* Major comments: 1. The authors compare the structure of the ER-NE junction to the structure of the ER tubule-sheet junction in interphase cells. They should instead or in addition be comparing the ER-NE junction to ER sheet-sheet junctions. This is likely a better comparison for two reasons:

i) The NE is similar to an ER sheet due to its flat and extended structure. The ER membranes surrounding the NE consists mostly of a dense network of sheet-like ER (Zheng et al., 2022, PMID: 34912111). Therefore, the ER-NE junction should be compared to these NE-adjacent ER sheet-sheet junctions and not ER tubule-sheet junctions which are likely to be found in the cell periphery.

ii) In HeLa cells, the NE assembles from large ER sheets and not ER tubules (Zhao et al., 2023, PMID: 37098350; Otsuka et al., 2018, PMID: 29323269; Lu et al., 2011, PMID: 21825076). Therefore, the ER-ER junctions the authors are already studying in anaphase cells are likely to be ER sheet-sheet junctions, which should be kept the same in their analysis of the ER-ER junctions in interphase cells.

Related to this point, comparing the side view panels in Figure 2D with 2H, it seems that the width of the ER membranes on either side of the neck region of the ER-NE junction is in fact getting wider (more sheet-like). This is in contrast to the ER-ER junction where the width stays constant for the ER tubule that is fusing onto the ER sheet. This suggests that indeed, the ER-NE junction is more similar to an ER sheet-sheet junction. *It is a very interesting possibility that the ER-NE junction might be similar to the ER sheet-sheet junction. We will inspect whether the ER that forms the ER-NE junction consists of sheet or tubular ER in our EM tomograms, and describe the outcome in the revised manuscript.

* The authors claim that in late anaphase cells, the ER-ER/NE (written like this because the ER and NE cannot be distinguished like the authors also point out) junctions are not constricted and had a similar morphology to ER-ER junctions in interphase. However, this claim is only qualitative at the moment, as the authors do not provide any quantification of the width of the ER-ER/NE junctions in late anaphase cells. To make the current claim that the ER-NE junction only becomes constricted in telophase, the authors should report the width of the ER-ER/NE junctions in late anaphase cells.

In late anaphase cells, large ER sheets initially wrap around chromatin at the periphery of the chromosome mass (Zhao et al., 2023, PMID: 37098350; Otsuka et al., 2018, PMID: 29323269; Lu et al., 2011, PMID: 21825076). Therefore, the authors might find it easier to identify ER-ER/NE junctions in the so-called "non-core" regions, instead of in the current regions shown in Figure 3A. *As the reviewer pointed out, we did not provide quantification of the width of ER-ER/NE junctions in late anaphase cells. We will measure them and show the quantification in the revised manuscript.

* Minor comments: 1. In the Supplementary Figures 1 A-D, make the scale bars white. Currently, the black scale bars are especially difficult to see in the top panels in Supplementary Figure 1C. *We will change the colour of some scale bars to make them more visible in the Supplementary Figure 1.

* In the Results section entitled "The number of ER-NE junctions per cell increases from telophase to interphase", the authors should tone down this claim because the number of telophase cells examined is low (only 2 telophase versus 9 interphase cells). It would be better to include the word "slightly" in the title to change it to "slightly increases". *We will modify the text accordingly. * In the Results section entitled "The number of ER-NE junctions per cell increases from telophase to interphase", the authors state "These densities were much lower than those of ER-ER junctions...". For sure this is true for ER tubule-tubule junctions in the periphery of the cell as ER tubules form an intricate network by constantly fusing to each other, but it's not clear if this is also the case for ER tubule-sheet or ER sheet-sheet junctions. For clarity, the authors should state that they mean ER tubule-tubule junctions.

Same comment also for the statement "...although their abundance remains considerably lower than that of ER-ER junctions or nuclear pores at both cell cycle stages". The authors should state that they mean ER tubule-tubule junctions. We will clarify what we mean by ER-ER junctions in the revised manuscript. * In the Results section entitled "The constricted morphology of ER-NE junctions is observed in different mammalian cells, but not in budding yeast", the authors state "...pancreatic islet cells (Figure 5A), HeLa (Figure 5B), and macrophage (Figure 5C) were significantly smaller than most ER-ER junctions (Figure 5F)". The last figure reference here is wrong and should be changed to Figures 5D-E. We will correct this error. * In Discussion, the authors state "Proteins known to form and stabilize junctions in the ER, including Atlastins and Lunapark...". The authors should specify that they mean ER tubule-tubule three-way junctions. Also more generally throughout the manuscript, the authors should be more careful in specifying which ER-ER junctions they mean in each case.*

As pointed out in the Major comment 3 above, we will clarify this point in the revised manuscript.*

1. In Discussion, the authors state "Thus, we favour a second scenario in which ER-NE junctions are generated from ER tubules that contact and eventually fuse with the ONM". Given that the ER membranes adjacent to the NE are mostly sheet-like (as pointed out in Major comment 1 above), the authors need to explain how they think an ER tubule (mostly found in the cell periphery) could access and fuse to the NE. As mentioned in the response to Major comment 1 above, we will examine if the ER that forms ER-NE junctions is tubule or sheet in our EM tomograms. Depending on the outcome of the examination, we will rephrase the text.

*

* Reviewer #2 (Significance (Required)):

Although the ER-NE junction has been studied in other organisms before, this study represents the first structural characterisation of the ER-NE junction in mammalian cells. Therefore, this study represents an advance for the field in gaining a better understanding of different ER structures and morphologies. How the ER is remodelled during the cell cycle is also an interesting question and an active field of research (Merta et al., 2021 PMID: 34853314; Zhao et al., 2023, PMID: 37098350) which this study further contributes to. This study would therefore be interesting for anyone interested in ER structure/morphology, ER-NE connections, and cell cycle regulation of such ER-NE connections.

My field expertise is in ER and NE. I do not have sufficient expertise to evaluate the methodology for the EM tomography part of this paper. We thank the reviewer for appreciating the novelty and the impact of our work.

*

*

*

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

The manuscript by Bragulat-Teixidor et al. is a study of the connection of the ER with the nuclear envelope. It uses advanced ultrastructural techniques: high pressure freezing instead of chemical fixation and EM tomography instead of serial sectioning. Synchronized HeLa cell cultures were examined during interphase, late anaphase (4-6 min after anaphase onset) and early telophase (8-10 minutes after anaphase onset).

The investigators find an unexpected, unusual structure - a constricted neck 7-20 wide and about 10 nm long where the ER connects to the nuclear envelope. The 7 nm connections had no apparent lumen. These are not seen in late anaphase when the NE has not yet formed, but they are seen a few minutes later during early telophase when there is a newly formed NE surrounding the chromosomes. A quantitation was made of their abundance, more was found later during interphase, and with wider lumens.

It is very nice to show the EM images as uncolored and segmented (colored). The images shown in the figures are presumably the best that were obtained during the study. Heavy metals do not stain membranes uniformly or exclusively, and identification of structures doesn't always seem unambiguous. The three dimensional information can certainly make this easier though this information is difficult or not possible to show in journal format. In the end, the reader must depend on the judgment of the person who did the analysis. Overall, the analysis seems trustworthy. *We thank the reviewer for the comment. To better present the three-dimensional structure of ER-NE junctions, we will provide movies of the EM sub-tomograms containing the junctions. In this way, the readers will be able to inspect the three-dimensional structure of six ER-NE junctions.

* HeLa cells are very convenient for getting information on cell cycle dependence. However, they are cancer cells in culture, so it is important to look at other cell types as well. The same methodology was used on budding yeast and they saw a wide tentlike connection, which reproduces an earlier study. This seems more consistent with what is known or expected from ER membranes. It is not less interesting but perhaps less puzzling. To get evidence on other mammalian cells, the authors did an analysis of data from OpenOrganelle. These are high pressure frozen cells / tissue imaged by FIB-SEM. The voxels are 4 nm, which is significantly larger than those in EM tomography. Unfortunately, the difficulty of identifying structures is correspondingly more significant. The images shown do not contradict the HeLa results but by themselves (without the HeLa cell data), a convincing case for narrow connections probably couldn't be made. *The reviewer raises a very good point about a limitation of the FIB-SEM datasets in OpenOrganelle. We agree with the reviewer that, as we had mentioned in the manuscript (line 6–11, page 10), the spatial resolution of the FIB-SEM datasets are not enough to gain insights into the exact morphology of the 7–20 nm wide ER-NE junctions because the voxel size is 4 nm. However, the resolution is good enough to examine if ER-NE junctions are narrower than ER-ER junctions, as shown in Figure 5A–E. The fact that we rarely found non-constricted ER-NE junctions in FIB-SEM datasets confirms the tiny nature of ER-NE junctions. To clarify this point, we will modify the text (line 24–25 on page 10) as below:

Previous: This analysis of FIB-SEM images confirms the hourglass morphology that distinguishes ER–NE from ER–ER junctions as seen in our EM tomograms…

Revised: This analysis of FIB-SEM images confirms that ER-NE junctions are narrower than ER-ER junctions as seen in our EM tomograms…

* The work in this manuscript seems to have been done well. Assuming that this structure is confirmed in other mammalian cells, another kind of question comes to mind: is this the final word on ER to NE connections? The lumenless neck does not seem like it would be a stable structure, somehow it seems like a transient one. In the future, it would help if a new structural protein was identified or some theoretical analysis to help explain the shape. *Certainly, this will not be the final word on ER-NE junctions, which are crucial for the ER-to-NE transport of lipids and transmembrane proteins. In the future, it will be important to identify structural proteins regulating the junctions and reveal how their constricted morphology affects the ER-to-NE transport. We believe that, as you kindly mentioned in the last paragraph of your comments, our observations “serve as a starting point for further structural and functional work” for this unique yet fundamental junctions that connect the ER to nucleus.

* It is generally now assumed that high pressure freezing preserves structure perfectly. However, in this reviewer's mind, there is a possibility that some structures are not. The sample is brought to 2000 atmospheres within a few milliseconds, frozen, then the high pressure is released after a second. Although many intracellular structures do seem well preserved, could the junction be susceptible to high pressure? A second source of uncertainty is that in order to embed the samples in resin, the water was removed by freeze substitution. This is known to cause a small amount of tissue shrinkage and possibly could alter a delicate structure. Another way to look at this kind of structure is cryo-EM tomography on hydrated lamellae from plunge frozen cells. I don't recommend that the authors do another arduous, possibly too arduous set of experiments with a completely different technique, but perhaps another group has data which could support their findings. *We think it is very unlikely that ER-NE junctions were deformed due to the high-pressure freezing. In general, high-pressure freezing allows vitrification of specimens up to 0.5 mm in thickness and the vitrification works better for thinner specimens. Our specimens are only 0.02 mm thick monolayer cells frozen in a chamber with 0.03 mm depth. Thus, the vitrification is expected to occur fast and the ER-NE junctions must have been frozen in the same way as in other regions of the cell.

However, as the reviewer pointed out, it is possible that the dehydration of the samples due to freeze substitution might cause deformation in ER-NE junctions. To verify the structural preservation of ER-NE junctions in our protocol, we will compare the morphology of the ER and NE in cryo-EM datasets that are available in public databases with ours. We will describe the outcome in the revised manuscript.

We think that our conclusion from the EM analysis is solid, because we observed significant structural difference between ER-NE junctions and ER-ER junctions in the same cells (Figure 2). In addition, we found the morphology change of ER-NE junctions in late-anaphase, early-telophase, and interphase cells that were high-pressure frozen and freeze-substituted on the same sapphire disc, and found that the ER-NE junctions became progressively constricted from telophase to interphase (Figure 3).

* The following are suggestions for the Discussion:

Yeast have many of the same biochemical processes as mammalian cells. Perhaps their lack of narrow connections can be used as a clue to the function of the narrow necks seen in HeLa cells. For instance, the authors speculate that the narrow connection serves to keep phosphatidylserine in the nuclear envelope low. If the yeast nucleus has the same concentration of phosphatidylserine as the ER, it would provide good evidence for this idea. Yes, it is indeed the case. It was shown that the yeast outer nuclear membrane has the same concentration of phosphatidylserine as the ER (Tsuji et al., Proc. Natl. Acad. Sci. U. S. A.*, 2019). We had described this in the discussion on page 14 “this phosphatidylserine enrichment occurs in mammalian cells and not in budding yeast (Tsuji et al., 2019)”, which was probably overlooked by the reviewer. In the revised manuscript, we will rephrase the text to make this point clearer.

* There might be other instances of lumenless neck structures. Dynamin mutants can cause a stable constricted tubule - are the dimensions of this tubule similar to that of the ER / NE connections? Or possibly some ESCRT related structure? These are very interesting questions. As shown in Figure 2A-D and Supplementary Figure 1B, the inner diameter (an inner leaflet distance) of the lumenless ER-NE junctions is below 1 nm. In contrast, the inner diameter of most constricted membrane tubules that the dynamin mutant K44A Dynamin 1 generates is 3.7 nm (Antonny et al., EMBO J., 2016, doi: 10.15252/embj.201694613). The inner diameter of membrane tubules that ESCRT-III subunits CHMP1B and IST1 form is 4.4 nm (Nguyen et al., Nat. Struct. Mol. Biol.*, 2020, doi: 10.1038/s41594-020-0404-x). Thus, the lumenless ER-NE junctions is unique in their highly-constricted nature and might be regulated by proteins other than dynamin or ESCRT proteins. We will discuss this point in the revised manuscript.

* There do not seem to be any recent studies of the ER / nuclear membrane connection in fixed cells. However, there is serial section data online which can be inspected. There are connections in mouse brain cortex in the data of Kasthuri et al., 2015 (https://neurodata.io/project/ocp/). Instead of a tubule connection, there seems to be a narrow sheet of ER that connects to the nuclear envelope. But there is something odd about these too. The authors may like to mention something about this or similar work in their manuscript. This reviewer has looked at chemically fixed data from several cell types from his own unpublished data and connections are surprisingly hard to find. Possibly, the connection is particularly sensitive to chemical fixation.* We inspected the serial section data of mouse brain cortex that was chemically fixed. The nuclear envelope in this dataset is deformed and does not seem well preserved. We do not think that we can extract useful information on the ultrastructure of ER-NE junctions from this dataset, and thus will not mention this work in our manuscript.

It is great to hear that the reviewer tried to look for ER-NE junctions in their own EM data. The frequency of ER-NE junctions is rare (only 0.1 junction per square micrometer, Figure 4). Thus, we think that the reason why it was hard to find the junctions in the reviewer’s data is due to the low-frequent nature of this junction and not due to the chemical fixation.

• *

* Reviewer #3 (Significance (Required)):

This is a careful and thorough study of the connection between the ER and the nuclear envelope. The discovery of reticulons and similar proteins, along with biophysical modeling, made the form of the ER accessible to analysis. The factors that govern ER structure are now much better understood. This is particularly true of sheets versus tubules, the three way tubule junctions and to some extent, the junction of ER tubules coming out of the edge of a sheet. However, with all this activity, the subject of the connection of the ER to the nucleus has not been examined in detail. What makes it different is that the tubule is connected perpendicular to the plane of a sheet.*

We thank the reviewer for appreciating the quality and novelty of our work.

* The manuscript uses the best ultrastructural techniques and provides strong evidence for a narrow neck at this connection in HeLa cells. With the same methodology, yeast cells (S. cerevisiae) have a wider connection. OpenOrganelle data from other mammalian cell types was examined. This data has less resolution and although it does not contradict the HeLa cell data, it does not support it strongly. *As mentioned in the response to one of this reviewer’s comments above, the spatial resolution of FIB-SEM datasets is good enough to examine if ER-NE junctions are narrower than ER-ER junctions. We think that our observation of several mammalian cells in FIB-SEM datasets strongly supports the conclusion that ER-NE junctions are narrower than ER-ER junctions and extends our findings in HeLa cells to two other mammalian cell types.

* This work is of interest to cell biologists specializing in membranous organelles or those interested in nuclear physiology. The connection of ER to nuclear envelope is an interesting problem that has not been studied recently. This manuscript could very well serve as a starting point for further structural or functional work by the authors or other groups. *We thank the reviewer for appreciating the significance and impact of our work.

*

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

Summary: Membrane bound ribosomes and ER exit sites are present in the cytosolic side of nuclear envelope (NE), suggesting that NE shares protein translocation, folding and quality control functions with the endoplasmic reticulum (ER). Moreover, membrane continuity between the ER and outer NE membrane is evident, and, thus, NE is considered as a subdomain of the ER. To support this, during cell division, NE loses its identity, and participates to daughter cells as part of the ER. However, NE has also membrane proteins and luminal proteins that are enriched to NE and absent from ER during interface, and the segregation of NE specific proteins/lipids occurs concomitantly with NE formation during late anaphase/telophase. In this study, the ultrastructure of the ER-NE junctions is described using high resolution electron tomography. Results show convincingly a specific constriction at the ER-NE neck during interface in several mammalian cell types. This structure is absent during metaphase, and also from the budding yeast. Authors present a model for the formation of ER-NE junctions in higher eukaryotes and speculate about their functional role. *We thank the reviewer for the appreciation of our work and the valuable suggestions for further improvements.

* Major comments: The main conclusion of the paper is that although the ER and outer NE membranes are continuous, a specific hourglass shaped constriction at the neck is found in higher mammalian cells during interphase. The structure is specific to ER-NE necks, as it is absent during metaphase and ER-ER junctions. For the analysis, authors used high pressure freezing to ensure best structural preservation. Unfortunately, fixation is not the only potential source of artifacts; during tomography at ambient temperature, the thinning of the plastic sections under the beam can be up to 30%. In evaluation of the results, authors should consider how this thinning could affect the measurements of membrane distances and luminal width, and what type of distortions may happen as a consequence of asymmetric shrinkage.*

In addition to analysis of own samples, authors took advantage of the publicly available whole-cell datasets in OpenOrganelle and used these datasets to expand the number of cell types analyzed. Moreover, the 3D-datasets were generated with different imaging technique, FIB-SEM. Although this technique provides lower resolution in general, it provides isotropic resolution, and the data could be used to eliminate the shortcomings of the tomography, thinning of the sections and the missing wedge. The authors could expand the comparison of the data from these different sources from this perspective, especially since HeLa cells were used in their own tomography studies and FIB-SEM datasets in OpenOrganelle. Similarly, it would be interesting to see if similar approach could be used to compare their results to those obtained by cryo-EM by utilizing the cryo-EM database. Have authors checked if any suitable datasets for analysis of ER-NE junctions could be found from public archives? For the analysis of mitotic cells, double thymidine block was used to synchronize the cell culture. It is not clear, why synchronization was necessary, as CLEM was used to select the cells, and their number was rather low. Do cells continue growing and synthesizing new proteins during thymidine blocks? As one way to control potential artifacts due to the synchronization treatment, authors could compare the average thickness of ER and NE in naturally occurring interphase and mitotic cells vs. synchronized cells. We agree with the reviewer that it is important to clarify the degree of shrinkage and deformation of the sample that our EM protocol might introduce. To access the degree of sample shrinkage and deformation in the plastic sections, we will compare the ONM-INM distance measured in our plastic sections with the one in cryo-EM tomograms of rapidly-frozen and FIB-milled mammalian cells that are publically available (EMPIAR, the Electron Microscopy Public Image Archive, https://www.ebi.ac.uk/pdbe/emdb/empiar/), and describe the outcome in the revised manuscript.

The reason why we synchronized the cell cycle is to enrich cells in late anaphase and early telophase in the same plastic sections, so that we can compare their ultrastructure side-by-side. In the revised manuscript, we will examine if the double thymidine block affects the ER-NE junction morphology by comparing the morphology of the ER and NE between the synchronised and non-synchronised cells.

As we described in the response to Reviewer 3, we think that our conclusion from the EM analysis is solid because of the following reasons. (i) We observed a significant structural difference between ER-NE junctions and ER-ER junctions in the same cells (Figure 2). (ii) We discovered a morphology change of ER-NE junctions in late-anaphase, early-telophase, and interphase cells that were freeze-substituted on the same sapphire disc; the ER-NE junctions became progressively constricted from telophase to interphase (Figure 3).

Minor comments: On page 5, last chapter (+ Fig.1 legend and materials and methods): "the quick tomograms covered the entire NE" is misleading, as the imaging covered a thin layer of the entire NE only. - Authors could have analyzed the entire NE from the FIB-SEM datasets but chose to use stereological approach to minimize their work.

We will modify the text to make it clear that the quick tomograms covered the NE in a section and not the entire NE of the cell in the revised manuscript.

* To save time from the readers to follow the reference, authors could describe how the specimens used in OpenOrganelle datasets were fixed and processed, especially as they emphasize the importance of high pressure freezing in their own sample prep. Similarly, in Fig.4 legend, authors refer to measurements done in the previous study without explaining how and from what type of data. *We thank the reviewer for pointing these out. We will describe how the OpenOrganelle datasets were generated and how the nuclear surface area measurement was done.

• *

Is there a difference between mesh generation and segmentation, or is it just two different terms used for the same thing by different programs? We apologize our short description of these terms. We will clarify these terms in the revised manuscript.

*

Reviewer #4 (Significance (Required)):

General assessment: ER-NE gates were described earlier in the literature for specific cell types using standard thin-section TEM imaging, and in this study, the analysis was done with modern technology at 3D. The text is fluent and clear, and the quality of the images was excellent. The analysis of the data was thorough, and materials and methods including image analysis part were presented accurately and clearly. Ultrastructural analysis was done systematically, and generated models are beautiful and informative. Much thought has put into planning of the experiments and experimental approach. The shortcoming of the study is its limitation to ultrastructural analysis only without attempts to connect to any mechanism. The discussion part contains lot of speculation of the factors that might be needed for the formation and maintenance of the constriction and present several hypotheses for the function of the constriction. The paper would be much stronger if one of few of the leads would be followed, and if there would be any explanation for the role of these structures, or factors affecting them. *We thank the reviewer for the appreciation of the clarity and quality of our work. The molecular mechanism that regulates the function, shape and biogenesis of ER-NE junctions will be the subject of future studies, for which our discovery of a highly-constricted morphology of the ER-NE junctions lays the groundwork.

* Advance: The paper provides a very nice example for the reuse of publicly archived imaging datasets to complement own experimental work. Hopefully this paper encourages others to the same path, as the large volumeEM datasets require significant investments and contain wealth of potential for reuse. *We strongly agree with the reviewer. The volume EM datasets that are publically available contain wealth of potential for new discoveries. We also hope that our paper encourages other scientists to make good use of those datasets and also to deposit their own data to the public databases. We will deposit our EM tomograms to EMPIAR, the Electron Microscopy Public Image Archive.

* The paper strengthens the description of the ER-NE junction structure significantly and convincingly but does not further our understanding of the mechanisms behind the structure nor the function of them and raises more questions than provides answers. For structural analysis of this kind, the state-of-the-art technology is cryo-EM (e.g., preparation of lamella with cryo-FIB-SEM followed by cryo-tomography), and in this study, the technical limitations come from plastic embedding and ambient temperature imaging. The used techniques would be more adequate for cell biological study, where the described structure is somehow connected to the function in cell, or the factor(s) needed to the formation or maintenance are identified. *Indeed, a limitation of our current study is that we did not reveal the underlying molecular mechanism and the functions of the constricted morphology of ER-NE junctions. We do not think that cryo-EM is necessarily required because we have collected evidence that the ER-NE connections are distinct from the ER-ER junctions in not only our EM tomography data (Fig. 2) but also in the EM datasets deposited in public databases (Fig. 5).

* Audience: This study will be of special interest to cell biology community. The study could be an opening to several lines of research, e.g., identification of the factors forming or maintaining the structure, the potential function of the structure, how the structure affects the dynamics of the NE/ER membrane and luminal proteins. *We thank the reviewer for appreciating the impact of our work.

* Reviewer's expertise: The reviewer has long experience in electron microscopy, volumeEM techniques and image analysis, and operates mainly in the field of cell biology.*

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

Learn more at Review Commons

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Referee #4

Evidence, reproducibility and clarity

Summary:

Membrane bound ribosomes and ER exit sites are present in the cytosolic side of nuclear envelope (NE), suggesting that NE shares protein translocation, folding and quality control functions with the endoplasmic reticulum (ER). Moreover, membrane continuity between the ER and outer NE membrane is evident, and, thus, NE is considered as a subdomain of the ER. To support this, during cell division, NE loses its identity, and participates to daughter cells as part of the ER. However, NE has also membrane proteins and luminal proteins that are enriched to NE and absent from ER during interface, and the segregation of NE specific proteins/lipids occurs concomitantly with NE formation during late anaphase/telophase. In this study, the ultrastructure of the ER-NE junctions is described using high resolution electron tomography. Results show convincingly a specific constriction at the ER-NE neck during interface in several mammalian cell types. This structure is absent during metaphase, and also from the budding yeast. Authors present a model for the formation of ER-NE junctions in higher eukaryotes and speculate about their functional role.

Major comments:

The main conclusion of the paper is that although the ER and outer NE membranes are continuous, a specific hourglass shaped constriction at the neck is found in higher mammalian cells during interphase. The structure is specific to ER-NE necks, as it is absent during metaphase and ER-ER junctions. For the analysis, authors used high pressure freezing to ensure best structural preservation. Unfortunately, fixation is not the only potential source of artifacts; during tomography at ambient temperature, the thinning of the plastic sections under the beam can be up to 30%. In evaluation of the results, authors should consider how this thinning could affect the measurements of membrane distances and luminal width, and what type of distortions may happen as a consequence of asymmetric shrinkage. In addition to analysis of own samples, authors took advantage of the publicly available whole-cell datasets in OpenOrganelle and used these datasets to expand the number of cell types analyzed. Moreover, the 3D-datasets were generated with different imaging technique, FIB-SEM. Although this technique provides lower resolution in general, it provides isotropic resolution, and the data could be used to eliminate the shortcomings of the tomography, thinning of the sections and the missing wedge. The authors could expand the comparison of the data from these different sources from this perspective, especially since HeLa cells were used in their own tomography studies and FIB-SEM datasets in OpenOrganelle. Similarly, it would be interesting to see if similar approach could be used to compare their results to those obtained by cryo-EM by utilizing the cryo-EM database. Have authors checked if any suitable datasets for analysis of ER-NE junctions could be found from public archives? For the analysis of mitotic cells, double thymidine block was used to synchronize the cell culture. It is not clear, why synchronization was necessary, as CLEM was used to select the cells, and their number was rather low. Do cells continue growing and synthesizing new proteins during thymidine blocks? As one way to control potential artifacts due to the synchronization treatment, authors could compare the average thickness of ER and NE in naturally occurring interphase and mitotic cells vs. synchronized cells.

Minor comments:

On page 5, last chapter (+ Fig.1 legend and materials and methods): "the quick tomograms covered the entire NE" is misleading, as the imaging covered a thin layer of the entire NE only. - Authors could have analyzed the entire NE from the FIB-SEM datasets but chose to use stereological approach to minimize their work. To save time from the readers to follow the reference, authors could describe how the specimens used in OpenOrganelle datasets were fixed and processed, especially as they emphasize the importance of high pressure freezing in their own sample prep. Similarly, in Fig.4 legend, authors refer to measurements done in the previous study without explaining how and from what type of data. Is there a difference between mesh generation and segmentation, or is it just two different terms used for the same thing by different programs?

Significance

General assessment:

ER-NE gates were described earlier in the literature for specific cell types using standard thin-section TEM imaging, and in this study, the analysis was done with modern technology at 3D. The text is fluent and clear, and the quality of the images was excellent. The analysis of the data was thorough, and materials and methods including image analysis part were presented accurately and clearly. Ultrastructural analysis was done systematically, and generated models are beautiful and informative. Much thought has put into planning of the experiments and experimental approach. The shortcoming of the study is its limitation to ultrastructural analysis only without attempts to connect to any mechanism. The discussion part contains lot of speculation of the factors that might be needed for the formation and maintenance of the constriction and present several hypotheses for the function of the constriction. The paper would be much stronger if one of few of the leads would be followed, and if there would be any explanation for the role of these structures, or factors affecting them.

Advance:

The paper provides a very nice example for the reuse of publicly archived imaging datasets to complement own experimental work. Hopefully this paper encourages others to the same path, as the large volumeEM datasets require significant investments and contain wealth of potential for reuse.

The paper strengthens the description of the ER-NE junction structure significantly and convincingly but does not further our understanding of the mechanisms behind the structure nor the function of them and raises more questions than provides answers. For structural analysis of this kind, the state-of-the-art technology is cryo-EM (e.g., preparation of lamella with cryo-FIB-SEM followed by cryo-tomography), and in this study, the technical limitations come from plastic embedding and ambient temperature imaging. The used techniques would be more adequate for cell biological study, where the described structure is somehow connected to the function in cell, or the factor(s) needed to the formation or maintenance are identified.

Audience:

This study will be of special interest to cell biology community. The study could be an opening to several lines of research, e.g., identification of the factors forming or maintaining the structure, the potential function of the structure, how the structure affects the dynamics of the NE/ER membrane and luminal proteins.

Reviewer's expertise:

The reviewer has long experience in electron microscopy, volumeEM techniques and image analysis, and operates mainly in the field of cell biology.

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

The manuscript by Bragulat-Teixidor et al. is a study of the connection of the ER with the nuclear envelope. It uses advanced ultrastructural techniques: high pressure freezing instead of chemical fixation and EM tomography instead of serial sectioning. Synchronized HeLa cell cultures were examined during interphase, late anaphase (4-6 min after anaphase onset) and early telophase (8-10 minutes after anaphase onset).

The investigators find an unexpected, unusual structure - a constricted neck 7-20 wide and about 10 nm long where the ER connects to the nuclear envelope. The 7 nm connections had no apparent lumen. These are not seen in late anaphase when the NE has not yet formed, but they are seen a few minutes later during early telophase when there is a newly formed NE surrounding the chromosomes. A quantitation was made of their abundance, more was found later during interphase, and with wider lumens.

It is very nice to show the EM images as uncolored and segmented (colored). The images shown in the figures are presumably the best that were obtained during the study. Heavy metals do not stain membranes uniformly or exclusively, and identification of structures doesn't always seem unambiguous. The three dimensional information can certainly make this easier though this information is difficult or not possible to show in journal format. In the end, the reader must depend on the judgment of the person who did the analysis. Overall, the analysis seems trustworthy.

HeLa cells are very convenient for getting information on cell cycle dependence. However, they are cancer cells in culture, so it is important to look at other cell types as well. The same methodology was used on budding yeast and they saw a wide tentlike connection, which reproduces an earlier study. This seems more consistent with what is known or expected from ER membranes. It is not less interesting but perhaps less puzzling.

To get evidence on other mammalian cells, the authors did an analysis of data from OpenOrganelle. These are high pressure frozen cells / tissue imaged by FIB-SEM. The voxels are 4 nm, which is significantly larger than those in EM tomography. Unfortunately, the difficulty of identifying structures is correspondingly more significant. The images shown do not contradict the HeLa results but by themselves (without the HeLa cell data), a convincing case for narrow connections probably couldn't be made.

The work in this manuscript seems to have been done well. Assuming that this structure is confirmed in other mammalian cells, another kind of question comes to mind: is this the final word on ER to NE connections? The lumenless neck does not seem like it would be a stable structure, somehow it seems like a transient one. In the future, it would help if a new structural protein was identified or some theoretical analysis to help explain the shape.

It is generally now assumed that high pressure freezing preserves structure perfectly. However, in this reviewer's mind, there is a possibility that some structures are not. The sample is brought to 2000 atmospheres within a few milliseconds, frozen, then the high pressure is released after a second. Although many intracellular structures do seem well preserved, could the junction be susceptible to high pressure? A second source of uncertainty is that in order to embed the samples in resin, the water was removed by freeze substitution. This is known to cause a small amount of tissue shrinkage and possibly could alter a delicate structure. Another way to look at this kind of structure is cryo-EM tomography on hydrated lamellae from plunge frozen cells. I don't recommend that the authors do another arduous, possibly too arduous set of experiments with a completely different technique, but perhaps another group has data which could support their findings.

The following are suggestions for the Discussion:

Yeast have many of the same biochemical processes as mammalian cells. Perhaps their lack of narrow connections can be used as a clue to the function of the narrow necks seen in HeLa cells. For instance, the authors speculate that the narrow connection serves to keep phosphatidylserine in the nuclear envelope low. If the yeast nucleus has the same concentration of phosphatidylserine as the ER, it would provide good evidence for this idea.

There might be other instances of lumenless neck structures. Dynamin mutants can cause a stable constricted tubule - are the dimensions of this tubule similar to that of the ER / NE connections? Or possibly some ESCRT related structure?

There do not seem to be any recent studies of the ER / nuclear membrane connection in fixed cells. However, there is serial section data online which can be inspected. There are connections in mouse brain cortex in the data of Kasthuri et al., 2015 (https://neurodata.io/project/ocp/). Instead of a tubule connection, there seems to be a narrow sheet of ER that connects to the nuclear envelope. But there is something odd about these too. The authors may like to mention something about this or similar work in their manuscript. This reviewer has looked at chemically fixed data from several cell types from his own unpublished data and connections are surprisingly hard to find. Possibly, the connection is particularly sensitive to chemical fixation.

Significance

This is a careful and thorough study of the connection between the ER and the nuclear envelope. The discovery of reticulons and similar proteins, along with biophysical modeling, made the form of the ER accessible to analysis. The factors that govern ER structure are now much better understood. This is particularly true of sheets versus tubules, the three way tubule junctions and to some extent, the junction of ER tubules coming out of the edge of a sheet. However, with all this activity, the subject of the connection of the ER to the nucleus has not been examined in detail. What makes it different is that the tubule is connected perpendicular to the plane of a sheet.

The manuscript uses the best ultrastructural techniques and provides strong evidence for a narrow neck at this connection in HeLa cells. With the same methodology, yeast cells (S. cerevisiae) have a wider connection. OpenOrganelle data from other mammalian cell types was examined. This data has less resolution and although it does not contradict the HeLa cell data, it does not support it strongly.

This work is of interest to cell biologists specializing in membranous organelles or those interested in nuclear physiology. The connection of ER to nuclear envelope is an interesting problem that has not been studied recently. This manuscript could very well serve as a starting point for further structural or functional work by the authors or other groups.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In this manuscript, Bragulat-Teixidor et al., use correlative live-cell imaging and electron tomography to study the structure of the endoplasmic reticulum-nuclear envelope (ER-NE) junction in HeLa cells (and also in S. cerevisiae). The authors also make use of publicly available whole-cell FIB-SEM datasets to study ER-NE junctions in mouse pancreatic islet, HeLa, and human macrophage cells to corroborate their findings in other cell types.

The authors show that the structure of the ER-NE junction in interphase cells adopts an hourglass shape with a constricted neck. Comparing the ER-NE junction to the ER tubule-sheet junction, the authors show that these structures are different: the ER tubule-sheet junction is not constricted. Because the NE forms from the ER during postmitotic NE assembly, the authors compare the structure of the ER-NE junctions in anaphase, telophase, and interphase cells, and find that the junction becomes constricted in telophase. The number of ER-NE junctions increase going from telophase to interphase.

While the authors do not provide any direct evidence for this, they propose a functional model where the ER-NE junction is constricted because it regulates the supply of certain lipids and proteins from the ER to the NE. One proposed example is that the constriction of the ER-NE junction might prevent the passage of large protein aggregates from entering the NE.

The general question of how the structure of the ER-NE junction might regulate the passage of lipids and proteins from the ER to the NE is interesting and potentially important. However, the authors should address the following issues to improve the accuracy and completeness of this manuscript for it to be considered for publication.

Major comments:

1. The authors compare the structure of the ER-NE junction to the structure of the ER tubule-sheet junction in interphase cells. They should instead or in addition be comparing the ER-NE junction to ER sheet-sheet junctions. This is likely a better comparison for two reasons:

i) The NE is similar to an ER sheet due to its flat and extended structure. The ER membranes surrounding the NE consists mostly of a dense network of sheet-like ER (Zheng et al., 2022, PMID: 34912111). Therefore, the ER-NE junction should be compared to these NE-adjacent ER sheet-sheet junctions and not ER tubule-sheet junctions which are likely to be found in the cell periphery.

ii) In HeLa cells, the NE assembles from large ER sheets and not ER tubules (Zhao et al., 2023, PMID: 37098350; Otsuka et al., 2018, PMID: 29323269; Lu et al., 2011, PMID: 21825076). Therefore, the ER-ER junctions the authors are already studying in anaphase cells are likely to be ER sheet-sheet junctions, which should be kept the same in their analysis of the ER-ER junctions in interphase cells.

Related to this point, comparing the side view panels in Figure 2D with 2H, it seems that the width of the ER membranes on either side of the neck region of the ER-NE junction is in fact getting wider (more sheet-like). This is in contrast to the ER-ER junction where the width stays constant for the ER tubule that is fusing onto the ER sheet. This suggests that indeed, the ER-NE junction is more similar to an ER sheet-sheet junction. 2. The authors claim that in late anaphase cells, the ER-ER/NE (written like this because the ER and NE cannot be distinguished like the authors also point out) junctions are not constricted and had a similar morphology to ER-ER junctions in interphase. However, this claim is only qualitative at the moment, as the authors do not provide any quantification of the width of the ER-ER/NE junctions in late anaphase cells. To make the current claim that the ER-NE junction only becomes constricted in telophase, the authors should report the width of the ER-ER/NE junctions in late anaphase cells.

In late anaphase cells, large ER sheets initially wrap around chromatin at the periphery of the chromosome mass (Zhao et al., 2023, PMID: 37098350; Otsuka et al., 2018, PMID: 29323269; Lu et al., 2011, PMID: 21825076). Therefore, the authors might find it easier to identify ER-ER/NE junctions in the so-called "non-core" regions, instead of in the current regions shown in Figure 3A.

Minor comments:

1. In the Supplementary Figures 1 A-D, make the scale bars white. Currently, the black scale bars are especially difficult to see in the top panels in Supplementary Figure 1C.
2. In the Results section entitled "The number of ER-NE junctions per cell increases from telophase to interphase", the authors should tone down this claim because the number of telophase cells examined is low (only 2 telophase versus 9 interphase cells). It would be better to include the word "slightly" in the title to change it to "slightly increases".
3. In the Results section entitled "The number of ER-NE junctions per cell increases from telophase to interphase", the authors state "These densities were much lower than those of ER-ER junctions...". For sure this is true for ER tubule-tubule junctions in the periphery of the cell as ER tubules form an intricate network by constantly fusing to each other, but it's not clear if this is also the case for ER tubule-sheet or ER sheet-sheet junctions. For clarity, the authors should state that they mean ER tubule-tubule junctions.

Same comment also for the statement "...although their abundance remains considerably lower than that of ER-ER junctions or nuclear pores at both cell cycle stages". The authors should state that they mean ER tubule-tubule junctions. 4. In the Results section entitled "The constricted morphology of ER-NE junctions is observed in different mammalian cells, but not in budding yeast", the authors state "...pancreatic islet cells (Figure 5A), HeLa (Figure 5B), and macrophage (Figure 5C) were significantly smaller than most ER-ER junctions (Figure 5F)". The last figure reference here is wrong and should be changed to Figures 5D-E. 5. In Discussion, the authors state "Proteins known to form and stabilize junctions in the ER, including Atlastins and Lunapark...". The authors should specify that they mean ER tubule-tubule three-way junctions. Also more generally throughout the manuscript, the authors should be more careful in specifying which ER-ER junctions they mean in each case. 6. In Discussion, the authors state "Thus, we favour a second scenario in which ER-NE junctions are generated from ER tubules that contact and eventually fuse with the ONM". Given that the ER membranes adjacent to the NE are mostly sheet-like (as pointed out in Major comment 1 above), the authors need to explain how they think an ER tubule (mostly found in the cell periphery) could access and fuse to the NE.

Significance

Although the ER-NE junction has been studied in other organisms before, this study represents the first structural characterisation of the ER-NE junction in mammalian cells. Therefore, this study represents an advance for the field in gaining a better understanding of different ER structures and morphologies. How the ER is remodelled during the cell cycle is also an interesting question and an active field of research (Merta et al., 2021 PMID: 34853314; Zhao et al., 2023, PMID: 37098350) which this study further contributes to. This study would therefore be interesting for anyone interested in ER structure/morphology, ER-NE connections, and cell cycle regulation of such ER-NE connections.

My field expertise is in ER and NE. I do not have sufficient expertise to evaluate the methodology for the EM tomography part of this paper.

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Referee #1

Evidence, reproducibility and clarity

The mechanisms that differentiate ER from the nuclear envelope (NE) remain to be fully elucidated but likely depend at least in part on junctions between the ER and NE. How such junctions are formed and maintained is the subject of this manuscript where extensive correlative light and electron microscopy is used to observe and characterize ER-nuclear envelope (ER-NE) junctions at distinct phases of the cell cycle. The authors make use of their own electron tomography data as well as publicly available focused-ion beam scanning electron microscopy (FIB-SEM) datasets to compare the morphology of these junctions in different human cell types as well as in budding yeast. The major finding is that ER-NE junctions in human cell lines are more constricted than ER-ER junctions, often to the point of excluding lumen. The examination of mitotic cells suggests that this constriction likely occurs at the end of mitosis as the NE is completing its maturation from ER to NE. The implications of these morphological changes are discussed but there are no mechanistic or functional studies. Overall, the data are well presented, are of high quality and are rigorously evaluated. The manuscript is well written and scholarly, and the speculations as to the function of the constrictions are reasonable. I only have minor comments.

1. In Figure 2D, the authors present evidence to demonstrate that an hourglass-like constriction occurs at ER-NE junctions. From the side view, it is difficult to interpret this on the plot, particularly for the ER-NE junctions with a lumen. Perhaps, in the supplemental data, the authors could plot both with and without lumen data separately, and color-code individual traces? I believe this would convey the hourglass nature of these constrictions more clearly.
2. In the Methods section, the authors should describe how carbon-coating of sapphire discs was achieved. If these were provided from the manufacturer precoated, this should be specified.
3. On page 10, Figure 5F callout 9 lines from the bottom likely should be 5E.

Significance

Overall, this work provides an important new morphological perspective on the nature of ER-NE junctions in human cells. As the authors describe in their introduction, such junctions have been noted previously in the literature but not in a dedicated study using modern imaging techniques in human cell lines. In describing the morphology of these junctions, the authors lay the groundwork for future mechanistic, functional, and structural studies.

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Reply to the reviewers

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

The manuscript entitled "The Drosophila Tumour Suppressor Lgl and Vap33 activate the Hippo pathway by a dual mechanism, involving RtGEF/Git/Arf79F and inhibition of the V-ATPase." by Portela et al. presents an interesting perspective of the molecular mechanism regulating Hippo pathway, revealing new proteins involved in this process. In this study, the authors try to show us that Lgl activates the Hippo pathway via Vap33 either by interacting with RtGEF/Git/Arf79F or by inhibiting V-ATPase, thus controlling epithelial tissue growth. The methodology used by the authors is adequate but could benefit from further experiments that would allow them to reach the conclusions stated in their research. Thus, based on the interpretation of the results presented by the authors some concerns were raised that should be addressed during the review process and that are explained in the major comments. Major comments: • It is not clear why in "The Hippo signaling pathway is negatively regulated by V-ATPase activity in Drosophila" section, the authors use Vha68-2 RNAi to reduce the activity of V-ATPase and later they use the overexpression of Vha44 to activate V-ATPase. The authors should explain why they used different proteins to regulate V-ATPase. The way the authors wrote their results sounds like different Vha proteins regulate V-ATPase, which means that cells may have different ways to activate V-ATPases, not being clear if regardless that the downstream effect of V-ATPase activation is always reflected in the Hippo pathway. Thus, the authors should state what other Vha proteins may have a similar effect, I would like to see evidence that Vha44 and Vha68 knockdown and overexpression leads to similar results.

Response: Vha68-2 and Vha44 are both components of the V-ATPase. We have added further details to the results to make this clearer. We have previously shown that knocking down several components of the V-ATPase, which disrupt V-ATPase function, have a similar effect on the Notch pathway (Portela et al., 2018 Sci. Signal., PMID: 29871910). Vha44 overexpression had been documented to result in V-ATPase activation (Petzoldt et al., 2013, Dis Model Mech., PMID: 23335205), and no other Drosophila V-ATPase transgenes were available to conduct experiments with other lines.

• In "Vap33 activates the Hippo pathway" section, the authors' conclusions represent a big statement considering the results obtained. Though Diap1 is a Hippo pathway target, it does not mean that this protein is solely regulated by this pathway. For example, there are studies that show that this gene can also be transcribed by STAT activity. Though in the following section the authors show how Vap33 activates this pathway, the results obtained in the section "Vap33 activates the Hippo pathway" are not enough to make this assumption. We suggest that the authors rephrase this section. (Optional: To maintain this statement, the authors should have performed, for example, a luciferase assay containing specifically Hippo pathway binding sites in the Diap1 gene, showing that the transcription factor of the Hippo pathway is somehow regulated by Vap33). Response: Whilst Jak-STAT signalling has been shown to induce Diap1 expression in the wing disc during development (PMID: 28045022), however expression profiling after activation of the Jak-STAT signalling in the eye epithelium did not identify Diap1 as a target (PMID: 19504457). Additionally, there are no reports that Lgl depletion in eye disc clones elevates Jak-STAT signalling (Stephens et al., J. Mol. Biol. 2018, PMID: 29409995), but instead loss of cell polarity in scrib mutant cells in the eye disc results in expression of the Jak-STAT pathway ligand, Upd, and non-cell autonomous induction of Jak-STAT signalling in the surrounding wild-type cells (PMID: 25719210, __PMID: __23108407). We have previously shown that Lgl depletion leads to inactivation of the Hippo pathway and elevates expression of the canonical Yki targets, Ex and Diap1 (Grzeschik et al., 2010, Curr Biol., PMID: 20362447). In this current study we show that Vap33 overexpression leads to the downregulation of Diap1 and in lgl mutant tissue reduces the elevated Diap1 expression. Since there is no evidence that either Lgl or Vap33 (VAPB) perturbations affect the Jak-STAT signalling pathway, we conclude from our results that Vap33 acts by reducing Yki activity and thus activating the Hippo pathway. We have added additional explanation to this section of our manuscript.

• The authors present a highly speculative discussion, raising different hypotheses. Though such hypotheses are well supported by the literature, the authors would enrich the quality of their research if indeed they could prove them. Particularly, testing for vesicle acidification, testing if V-ATPase indeed blocks the interaction of Lgl/Vap33/RtGEF/Git/Arf79F, and alters Hpo localization, testing if Git/RtGEF inhibits Arf79F and consequent Hpo localization. Response: Although it would extend the paper to conduct further experiments, my lab is now closed so this is not possible. We have already published that vesicle acidification is increased in lgl mutant tissue (Portela et al., 2018, Sci. Signal., PMID: 29871910) and that Hpo localization is altered in lgl mutant tissue (Grzeschik et al., 2010, Curr. Biol., PMID: 20362447).

• The authors should also apply more specific techniques to infer how the Hippo pathway is affected by such genetic manipulation since diap1 can be a target gene of different pathways. Response: We have shown that lgl mutant tissue also shows upregulation of the Hippo pathway target, Ex-LacZ, and affects the phosphorylation of Yki (Grzeschik et al., 2010, Curr. Biol., PMID: 20362447), and RtGEF/Git mutant tissue shows upregulation of the Yki target, Ex-LacZ (Dent et al., 2015, Curr. Biol., PMID: 25484297). Since RtGEF/Git are positive regulators of Hippo, but there is no evidence that they are involved in the regulation of the Jak-STAT pathway, the effect of Vap33 overexpression on Diap1 levels in the context of a RtGEF knockdown (Fig 5) is most likely to be due to effects on the Hippo pathway. Similarly, since Lgl deficiency upregulates Yki targets, Ex-LacZ and Diap1 (Grzeschik et al., 2010, Curr. Biol., PMID: 20362447), the reduction of the elevated Diap1 levels in lgl mutant clones by knocking down or reducing Arf79F activity (Fig 7), is most likely due to inhibition of Yki activity and therefore elevated Hippo pathway signalling.

Minor comments: • The authors present a well-structured manuscript, that generally is easy to understand. However, at some points, the statements given by the authors seem highly speculative. • The figures presented in this manuscript and the statistical analysis seem adequate and are clearly described.

Response: We thank the reviewer for their support of our study. We have added more explanation to support our conclusions.

Reviewer #1 (Significance (Required)):

The study presented by Portela et al. gives new insights into the regulation of the Hippo pathway with the discovery of new proteins involved in this mechanism, which can be interesting to those working on basic research and focused on studying signal transduction. However, this study lacks some novelty. Throughout the manuscript, the authors only observed the physiological consequences of manipulating this pathway based on the eye phenotypes, and in the discussion, many hypotheses were raised based on the already available literature, which shows that much is already known about the Hippo pathway. The advances shown in this study are limited to the description of the signaling pathway itself and to the eye morphology. As a suggestion, the authors should explore the knowledge of their findings in order to understand how we can use them to achieve advances in other fields and physiological conditions. For example, only at the end of the discussion, did the authors raise the questions that would really push their discoveries a step forward, namely how this mechanism acts during the response to tissue wounding and whether the mammalian orthologs of Lgl and Vap33 also act via these mechanisms to control tissue growth in mammals. It would be interesting if the authors could direct their research efforts to understand if the proteins identified can be targeted to improve wound healing or to delay aging for example. Altogether, the authors present an interesting study but, at this moment, it still lacks the significance and novelty needed for publication. We encourage the authors to keep up their good work to address these suggestions, which will definitely improve the quality of their study.

Response: We respectfully disagree with the reviewer’s comments regarding the significance of our study. On the contrary, our study is significant since it has discovered a mechanism linking Lgl and Vap33-RtGEF/Git/Arf79F and the V-ATPase to the regulation of the Hippo pathway, an important tissue growth regulatory and tumour suppressor pathway. The Drosophila eye epithelium is a highly validated model for exploring mechanisms that are relevant to human epithelial biology and cancer. Whilst extending our studies of the mechanism by which Lgl controls the Hippo pathway to wound healing and mammalian systems would be the next step, this is beyond the scope of this discovery paper.

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

Summary This manuscript investigates potential mechanisms through which the lgl gene might affect the Hippo signaling pathway. The authors employ a combination of physical interaction studies and clonal analysis in Drosophila eye discs to investigate potential links between lgl and other genes. Some of the results are intriguing, but the analysis is rather preliminary, and there are technical concerns with some of the results presented.

Main issues - The authors propose effects of genes involved in vesicle trafficking and acidification in Hippo signaling, but there is no clear cellular mechanism described by which these effects could be mediated. This deserves further consideration. eg if they think there are effects on the localization of Hippo, this could be directly examined. In the Discussion, the authors suggest that "The V-ATPase might therefore act to inhibit Hippo pathway signalling by blocking the interaction of Lgl/Vap33/RtGEF/Git/Arf79F with Hpo in vesicles, thereby altering Hpo localization and inhibiting its activity." but Hippo is a cytoplasmic protein and has never been reported to be within vesicles.

Response: Whilst Hpo is a cytoplasmic protein there is evidence that it could also be associated with vesicles, since Hpo pathway components bind to several endocytic proteins by mass spectrometry analysis (Kwon et al., 2013, Science, PMID: 24114784; Verghese and Moberg, 2020, Front. Cell Dev. Biol., PMID: 32010696). We have previously published that Hippo localization is altered in lgl mutant tissue (Grzeschik et al., 2010, Curr. Biol., PMID: 20362447). For a better precision, we have updated the wording to state that the proteins described in our manuscript may alter Hippo localization “on endosomes” as opposed to the previous “in vesicles”.

• The Yki stains in Fig. 1 are confusing. The nature of the signal throughout the wing disc looks very different in 1A vs 1B vs 1C, this needs to be explained or re-examined. Fig 1C (wts RNAi ) seems to show an elevated Yki signal in some cells, and lower in others in - prior studies have reported that wts affects the nuclear vs cytoplasmic localization of Yki, but not its levels, so this needs to be clarified.

Response: There are some tissue folds in the eye disc tissues that might be confusing the reviewer, but Yki nuclear staining is lower in Vha68-2 mutant clones, and higher in wts knockdown and Vha44 over-expressing clones (arrowheads). When Yki is concentrated in the nucleus the staining appears more intense, as it does in the wts knockdown clones. Similar results on Yki staining upon Hippo pathway impairment in epithelial tissues have been obtained by other Hippo pathway researchers (eg PMID: 20362445, __PMID: 19900439, PMID: __19913529, __PMID: __26364751).

• In Fig 1D the clones appear to have different effects in different regions of the eye disc; the authors should clarify. Also, the disc in 1D appears much younger than the discs in 1A-C, but similar age discs should be used for all comparisons.

Response: All eye discs are from wandering 3rd instar larvae, but the mounting of the samples on the slide and the confocal Z-section could account for apparent different regions of the eye disc showing stronger upregulation of Ex-LacZ and Yki staining. The data has been statistically analysed from multiple eye discs and the effects observed are significantly different to the control (as plotted in Fig 1E).

• The authors should clarify whether any the manipulations they perform are associated with Jnk activation, as this could potentially provide an alternative explanation for downregulation of Hippo signaling.

Response: Lgl mutant clones only upregulate the JNK target MMP1 in some cells at the border of the clones but show elevated Yki activity within the clones. Vha44 overexpressing clones do show upregulation of JNK signalling (Petzoldt et al., 2013, Dis Model Mech., PMID: 23335205), but since JNK signalling is known to inhibit Yki activity in the eye epithelium (PMID: 22190496), it is unlikely that the upregulation of Yki activity (downregulation of Hippo signalling) in Vha44 overexpressing clones is due to JNK activation.

• The authors report in Fig 2C,E that over-expression of Vap33 reduced expression of Diap1, which they interpret as evidence of increased Hippo pathway activity, but this experiment is lacking essential controls, as the apparent reduction of Diap1 could simply reflect increased cell death or a change in focal plane, and indeed the difference in the label stain makes it look like these cells are undergoing apoptosis. Thus it's important to also have a stain for a neutral protein, or at least a DNA stain. Additionally, it is important to stain for at least one additional marker of Hippo pathway activity (eg ex-lacZ or Yki localization), as there are other pathways that regulate Diap1

Response: We have previously examined the effect of Vap33 overexpressing clones on the Notch signalling pathway and do not see a reduction in Notch target gene expression relative to the control (Portela et al., 2018, Sci. Signal., PMID: 29871910, Fig 3). Thus, although there might be some cell death in Vap33 overexpressing clones (possibly due to lower Diap1 levels), it is unlikely that cell death per se results in lower Diap1 levels. We are unable to conduct further experiments to examine other Hippo pathway activity markers since my lab is now closed.

• In Fig. 4 the authors perform PLA experiments to examine potential association between various pairs of proteins, but they don't show us key controls. They report in the text using single antibodies as negative controls, but this doesn't control for non-specific localization of antibodies. The better negative control is to do the PLA experiments in parallel on tissues lacking the protein being detected (eg from animals not expressing the GFP- or RFP-tagged proteins they are examining). Also, there is a lot of variation in the apparent signals shown in different PLA experiments in fig 4, the authors should comment on this.

Response: We have previously used the PLA assay to examine Lgl and Vap33 interactions (Portela et al., 2018, Sci. Signal., PMID: 29871910, Fig 2) and have conducted an experiment expressing Vap33 tagged with HA via the GMR driver in the posterior region of the eye disc and then detected Lgl-HA protein interactions, which only showed PLA foci in the posterior region where Vap33-HA is expressed but not in the anterior region where Vap33-HA is not expressed. This may be thought of as the best possible control since these differentially expressing regions were part of the same tissue sample. Furthermore, in our previous study (Portela et al., 2018, Sci. Signal., PMID: 29871910, Fig S2), we conducted a negative control PLA using the GFP and Vap33 antibodies in eye tissue not expressing GFP-Lgl and observed no PLA foci. We have edited the text to refer to these controls.

The variation in PLA signal may be due to low levels of expression of certain proteins or lower levels of protein-protein interactions. We have edited the text to add this explanation.

• The authors claim that RtGEF mutant cells increase Diap1 expression, and that Vap33 over-expression reverses this effect (Fig. 5). The effect of RtGEF looks very subtle and variable, it should be confirmed by examining additional reporters of Hippo pathway activity. It also seems like the disc in 5A is at a different stage &/or the quantitation is done from a different region as compared to the disc in 5C.

Response: RtGEF mutant cells have also been shown to upregulate the Yki target, Ex-LacZ (Dent et al., 2015). Unfortunately, we were unable to construct an Ex-LacZ RtGEF mutant stock and there was no available Ex antibody.

For Diap1 quantification, clones were chosen just posterior to the morphogenetic furrow of each eye disc and multiple clones were analysed relative to the adjacent wild-type clones in many samples and quantified and plotted in Fig 5E.

• The analysis of the influence of Vha68-2 mutant clones, and their genetic interaction with Git, similarly suffers from missing controls and incomplete analysis. Additional Hippo reporters besides just Diap1 should be examined. The Diap1 analysis which shows reduced expression needs examination of neutral controls or nuclear markers to assess potential apoptosis within clones, or changes in focal plane.

Response: We have also examined the effect of Vha68-2 clones on Ex-LacZ expression (Figure 1) and show that it is also reduced relative to the surrounding wild-type clones.

We have previously examined Vha68-2 mutant clones for the expression of a Notch pathway target (Portela et al., 2018, Sci. Signal., PMID: 29871910, Fig S1) and show with DAP1 staining that cells are in the same plane and are retained in pupal retina, so are not dying. We now refer to our previous study in the text.

Similarly, the analysis of Arf79F mutant clones in Fig 7E,G is compromised by lack of controls for viability and tissue layer, and analysis of an additional Hippo reporter is once again essential.

Response: We don’t believe DAPI stains are necessary as the GFP membrane/cytoplasmic staining clearly shows the outline of the cells and where the nucleus is in the mutant clones and shows that the cells are intact and not dying.

Reviewer #2 (Significance (Required)):

The strength of the study is the potential dissection of novel connections between the lgl tumor suppressor and the Hippo pathway. However, there are signifiant limitations due to the preliminary nature of the study, which is incomplete and missing essential controls. If these limitations are overcome the work will be of interest to specialists in the field.

Response: We are hoping that our explanations and responses to the main issues above alleviate concerns regarding controls.

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

In this study, Portela and colleagues identified new regulators of Hippo pathway downstream of the core apico-basal polarity protein Lgl. While the impact of Lgl depletion of Yki activation was already characterised both in Drosophila and Vertebrates, the mechanism connecting these two pathways was still unclear. Using the Drosophila eye, mosaic analysis, epistatic analysis and mass-spectrometry, they identified two routes through which Lgl depletion can lead to Hippo pathway downregulation and eye overgrowth. This regulation required the previously characterised Lgl interactor Vap33, which on the one hand activates Hippo by inhibiting the V-ATPase, and on the other hand activates Hippo through its interactions with the actin regulators Git, RtGEF (two previously characterised regulators of Hippo, https://pubmed.ncbi.nlm.nih.gov/25484297/) . They also identified another regulator of Hippo downstream of Lgl, Arf79F, whose ortholog interact with Git in mammals and is also in close proximity with Hippo, Git and RtGEF in Drosophila, and whose depletion abolish Hippo downregulation and eye overgrowth in Lgl mutant. This is a well performed study which identified new links between Lgl and regulation of the Hippo pathway. Many of them are conserved in mammals and may be relevant in pathological conditions associated with Lgl loss of function and Yap missregulation. The experiments are well conducted with a quite thorough epistatic analysis combined with many assays to characterize protein interactions. Admittedly, the molecular mechanism remains uncharacterised and some experiments may help to indicate putative mechanisms, but the characterisation of these news regulators and clear genetic interactions results constitute already solid and interesting data. I have some suggestions though that could help to reinforce the conclusions.

Main suggestions :

1. While the precise molecular mechanisms is not absolutely necessary, it would be interesting to document the subcellular localisation of these new Hippo regulators in WT and Lgl mutant context (Git, RtGEF Vap33 and Arf79F), either with Antibody if they exist, or with fusion protein (which for a good part were already generated for the PLA results). This may reveal obvious misslocalisation which would support the role of Lgl as a scaffolding protein that maintain proper subcellular localisation of these factors.

Response: Whilst this experiment would extend the study, we are unable to do this since my lab has now closed.

Most of the epistatic experiments focus on factors that rescue the overgrowth and increase of diap1 expression in Lgl mutant. Did the author test if any of these core regulators are sufficient to recapitulate Lgl mutant eye phenotype, for instance Vap33 KD in the eye, or Arf79F overexpression. Negative results would still be informative as they would point to the existence of other downstream regulators of the eye phenotype

Response: Vap33 knockdown by RNAi in clones does not phenocopy the lgl mutant mosaic adult eye phenotype (Portela et al., 2018, Sci. Signal., PMID: 29871910, Fig 2), presumably due to other functions of Vap33. We have added further details regarding this point In the Discussion.

We have not examined Arf79F overexpressing clones.

It is at the moment hard to interpret the relevance of the results obtained by PLA. While there are some negative controls based on the absence of secondary antibody, what is the number of particle obtained for two non-interacting cortical proteins ? Since this is based on proximity, I would expect that some positive particles would still appear by chance, but much less than for two physically interacting proteins or subunits of a complex. Could the author provide such a negative control by testing for instance Git/RtGEF with another non-interacting cortical protein ? That would help to assess the relevance of the conclusions based on PLA.

Response: The PLA is a robust assay to assess protein-protein interactions of proteins that are

Some of the epistatic links are a bit hard to interpret at the moment, and additional epistatic test may be relevant. For instance, the increase of diap1 upon Git depletion in the Vha68 mutant (Figure 6) is used to conclude that Git is required for the Hippo upregulation upon reduced V-ATPase activity. However this could be compatible with two independent branches regulating Hippo (in an opposite manner), which is more less what is suggested by the authors in their conclusion and the model of figure 8. I would suggest to reformulate this conclusion in the result part. Similarly, there is currently no experimental exploration of the epistatic link between Arf79F, Git and RtGEF (which is based on results in mammals). It would be interesting to check if Git and RtGEF mutant phenotype (Hippo downregulation) can also be suppressed by downregulation of Arf79F.

Response: We have now added further explanation to the result section regarding Fig 6.

Unfortunately, we are unable to do further experiments since my lab is now closed.

Apart from very obvious phenotype (eye in Lgl mutant mosaic) it is a bit hard to interpret the picture of adult eye provided in this study (specially for mild phenotype). Could the authors provide more explanation in the legends, and if possible some quantitative evaluation of the phenotype when relevant? Otherwise, apart from obvious rescue of the Lgl mutant, it is a bit hard to interpret the other genotypes (e.g. : Vap33OE, RtGEF mutant, Vha68 mutant)

Response: We have added more explanation of the adult eye phenotypes in the text/fig legends.

Other minor points :

1. I would recommend when possible to clearly indicate in Figure 8 which part of the pathway are clearly documented in this study, and which part are still hypothetical (eg: link with PAK).

Response: We have re-drawn the model figure to highlight what we have found in this study by adding orange arrows between Lgl-Vap33-RtGEF/Git-Arf79F-Hpo and Lgl-Vap33-V-ATPase and V-ATPase-Hpo.

1. Page 4, the sentence "as aPKC's association with the Hpo orthologs, MST1/2, and uncoupling MST from the downstream kinase, LATS (Wts), thereby leading to increased nuclear YAP (Yki) activity [17], consistent with what we observe in Drosophila [5]." may need to be reformulated (at least I had trouble to understand it).

Response: We have edited the sentence to "In mammalian systems, deregulation of Lgl/aPKC impairs Hippo signalling and induces cell transformation, which mechanistically involves the association of aPKC with the Hpo orthologs, MST1/2, thereby uncoupling MST from the downstream kinase, LATS (Wts) and leading to increased nuclear YAP (Yki) activity [17], consistent with what we observe in Drosophila [5]."

1. Page 11 : "a decrease in Diap1 expression was observed and clones were smaller than wild-type clones (Fig 7E), suggesting that the Arf79F knockdown clones were being out-competed" I am not sure one can conclude from this that the clone are "outcompeted" (which would suggest at context dependent disappearance of clone, while here the data could be totally compatible with a cell-autonomous decrease of growth and survival). This statement would only make sense if global eye depletion of Ar79F had no adult eye phenotype.

Response: We have edited the sentence to "a decrease in Diap1 expression was observed and clones were smaller than wild-type clones (Fig 7E), suggesting that the Arf79F knockdown clones have reduced tissue growth ----."

Reviewer #3 (Significance (Required)):

This study identifies regulators of Hippo which through their interactions with Vap33 explains for the first time how Lgl depletion leads to Hippo misregulation (without impairing apico-basal polarity). This is an interesting study based on epistatic analysis and mass-spectrometry and identify several regulators conserved in mammals. While the molecular mechanism remained to be explored, it clarifies for the first time how Lgl depletion ( a core regulator of apico-basal polarity) leads to Hippo downregulation and tissue overgrowth, a phenotype also observed in mammals and characterised several years ago in Drosophila. The authors previously characterised the interaction between Vap33 and Lgl and its role in the regulation of Notch signaling through the V-ATPase. This study nicely complement these previous results and connect now Vap33 with Hippo and Lgl while answering a long unresolved question (how Lgl depletion affect Hippo pathway).

This results will be interesting for the large community studying the hippo pathway, apico-basal polarity and tissue growth. It also outlines interesting factors that could be relevant for tumour neoplasia and hyperplasia.

I have expertise in epithelial biology, apoptosis, cell competition, Drosophila, cell extrusion, mechanobiology, morphogenesis and growth regulation.

Response: We thank the reviewer for recognizing the significance of our study.

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Referee #3

Evidence, reproducibility and clarity

In this study, Portela and colleagues identified new regulators of Hippo pathway downstream of the core apico-basal polarity protein Lgl. While the impact of Lgl depletion of Yki activation was already characterised both in Drosophila and Vertebrates, the mechanism connecting these two pathways was still unclear. Using the Drosophila eye, mosaic analysis, epistatic analysis and mass-spectrometry, they identified two routes through which Lgl depletion can lead to Hippo pathway downregulation and eye overgrowth. This regulation required the previously characterised Lgl interactor Vap33, which on the one hand activates Hippo by inhibiting the V-ATPase, and on the other hand activates Hippo through its interactions with the actin regulators Git, RtGEF (two previously characterised regulators of Hippo, https://pubmed.ncbi.nlm.nih.gov/25484297/) . They also identified another regulator of Hippo downstream of Lgl, Arf79C, whose ortholog interact with Git in mammals and is also in close proximity with Hippo, Git and RtGEF in Drosophila, and whose depletion abolish Hippo downregulation and eye overgrowth in Lgl mutant.

This is a well performed study which identified new links between Lgl and regulation of the Hippo pathway. Many of them are conserved in mammals and may be relevant in pathological conditions associated with Lgl loss of function and Yap missregulation. The experiments are well conducted with a quite thorough epistatic analysis combined with many assays to characterize protein interactions. Admittedly, the molecular mechanism remains uncharacterised and some experiments may help to indicate putative mechanisms, but the characterisation of these news regulators and clear genetic interactions results constitute already solid and interesting data. I have some suggestions though that could help to reinforce the conclusions.

Main suggestions:

1. While the precise molecular mechanisms is not absolutely necessary, it would be interesting to document the subcellular localisation of these new Hippo regulators in WT and Lgl mutant context (Git, RtGEF Vap33 and Arf79F), either with Antibody if they exist, or with fusion protein (which for a good part were already generated for the PLA results). This may reveal obvious misslocalisation which would support the role of Lgl as a scaffolding protein that maintain proper subcellular localisation of these factors.
2. Most of the epistatic experiments focus on factors that rescue the overgrowth and increase of diap1 expression in Lgl mutant. Did the author test if any of these core regulators are sufficient to recapitulate Lgl mutant eye phenotype, for instance Vap33 KD in the eye, or Ar79C overexpression. Negative results would still be informative as they would point to the existence of other downstream regulators of the eye phenotype
3. It is at the moment hard to interpret the relevance of the results obtained by PLA. While there are some negative controls based on the absence of secondary antibody, what is the number of particle obtained for two non-interacting cortical proteins ? Since this is based on proximity, I would expect that some positive particles would still appear by chance, but much less than for two physically interacting proteins or subunits of a complex. Could the author provide such a negative control by testing for instance Git/RtGEF with another non-interacting cortical protein ? That would help to assess the relevance of the conclusions based on PLA.
4. Some of the epistatic links are a bit hard to interpret at the moment, and additional epistatic test may be relevant. For instance, the increase of diap1 upon Git depletion in the Vha68 mutant (Figure 6) is used to conclude that Git is required for the Hippo upregulation upon reduced V-ATPase activity. However this could be compatible with two independent branches regulating Hippo (in an opposite manner), which is more less what is suggested by the authors in their conclusion and the model of figure 8. I would suggest to reformulate this conclusion in the result part. Similarly, there is currently no experimental exploration of the epistatic link between Arf68C, Git and RtGEF (which is based on results in mammals). It would be interesting to check if Git and RtGEF mutant phenotype (Hippo downregulation) can also be suppressed by downregulation of Arf79C.
5. Apart from very obvious phenotype (eye in Lgl mutant mosaic) it is a bit hard to interpret the picture of adult eye provided in this study (specially for mild phenotype). Could the authors provide more explanation in the legends , and if possible some quantitative evaluation of the phenotype when relevant ? Otherwhise, apart from obvious rescue of the Lgl mutant, it is a bit hard to interpret the other genotypes (e.g. : Vap33OE, RtGEF mutant, Vha68 mutant)

Other minor points:

1. I would recommend when possible to clearly indicate in Figure 8 which part of the pathway are clearly documented in this study, and which part are still hypothetical (eg: link with PAK).
2. Page 4, the sentence "as aPKC's association with the Hpo orthologs, MST1/2, and uncoupling MST from the downstreamkinase, LATS (Wts), thereby leading to increased nuclear YAP (Yki) activity [17], consistent with what we observe in Drosophila [5]." may need to be reformulated (at least I had trouble to understand it).
3. Page 11 : "a decrease in Diap1 expression was observed and clones were smaller than wild-type clones (Fig 7E),suggesting that the Arf79F knockdown clones were being out-competed" I am not sure one can conclude from this that the clone are "outcompeted" (which would suggest at context dependent disappearance of clone, while here the data could be totally compatible with a cell-autonomous decrease of growth and survival). This statement would only make sense if global eye depletion of Ar79F had no adult eye phenotype.

Significance

This study identifies regulators of Hippo which through their interactions with Vap33 explains for the first time how Lgl depletion leads to Hippo misregulation (without impairing apico-basal polarity). This is an interesting study based on epistatic analysis and mass-spectrometry and identify several regulators conserved in mammals. While the molecular mechanism remained to be explored, it clarifies for the first time how Lgl depletion ( a core regulator of apico-basal polarity) leads to Hippo downregulation and tissue overgrowth, a phenotype also observed in mammals and characterised several years ago in Drosophila. The authors previously characterised the interaction between Vap33 and Lgl and its role in the regulation of Notch signaling through the V-ATPase. This study nicely complement these previous results and connect now Vap33 with Hippo and Lgl while answering a long unresolved question (how Lgl depletion affect Hippo pathway).

This results will be interesting for the large community studying the hippo pathway, apico-basal polarity and tissue growth. It also outlines interesting factors that could be relevant for tumour neoplasia and hyperplasia.

I have expertise in epithelial biology, apoptosis, cell competition, Drosophila, cell extrusion, mechanobiology, morphogenesis and growth regulation.

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Referee #2

Evidence, reproducibility and clarity

Summary

This manuscript investigates potential mechanisms through which the lgl gene might affect the Hippo signaling pathway. The authors employ a combination of physical interaction studies and clonal analysis in Drosophila eye discs to investigate potential links between lgl and other genes. Some of the results are intriguing, but the analysis is rather preliminary, and there are technical concerns with some of the results presented.

Main issues

• The authors propose effects of genes involved in vesicle trafficking and acidification in Hippo signaling, but there is no clear cellular mechanism described by which these effects could be mediated. This deserves further consideration. eg if they think there are effects on the localization of Hippo, this could be directly examined. In the Discussion, the authors suggest that "The V-ATPase might therefore act to inhibit Hippo pathway signalling by blocking the interaction of Lgl/Vap33/RtGEF/Git/Arf79F with Hpo in vesicles, thereby altering Hpo localization and inhibiting its activity." but Hippo is a cytoplasmic protein and has never been reported to be within vesicles.
• The Yki stains in Fig. 1 are confusing. The nature of the signal throughout the wing disc looks very different in 1A vs 1B vs 1C, this needs to be explained or re-examined. Fig 1C (wts RNAi ) seems to show an elevated Yki signal in some cells, and lower in others in - prior studies have reported that wts affects the nuclear vs cytoplasmic localization of Yki, but not its levels, so this needs to be clarified.
• In Fig 1D the clones appear to have different effects in different regions of the eye disc; the authors should clarify. Also, the disc in 1D appears much younger than the discs in 1A-C, but similar age discs should be used for all comparisons.
• The authors should clarify whether any the manipulations they perform are associated with Jnk activation, as this could potentially provide an alternative explanation for downregulation of Hippo signaling.
• The authors report in Fig 2C,E that over-expression of Vap33 reduced expression of Diap1, which they interpret as evidence of increased Hippo pathway activity, but this experiment is lacking essential controls, as the apparent reduction of Diap1 could simply reflect increased cell death or a change in focal plane, and indeed the difference in the label stain makes it look like these cells are undergoing apoptosis. Thus it's important to also have a stain for a neutral protein, or at least a DNA stain. Additionally, it is important to stain for at least one additional marker of Hippo pathway activity (eg ex-lacZ or Yki localization), as there are other pathways that regulate Diap1
• In Fig. 4 the authors perform PLA experiments to examine potential association between various pairs of proteins, but they don't show us key controls. They report in the text using single antibodies as negative controls, but this doesn't control for non-specific localization of antibodies. The better negative control is to do the PLA experiments in parallel on tissues lacking the protein being detected (eg from animals not expressing the GFP- or RFP-tagged proteins they are examining). Also, there is a lot of variation in the apparent signals shown in different PLA experiments in fig 4, the authors should comment on this.
• The authors claim that RtGEF mutant cells increase Diap1 expression, and that Vap33 over-expression reverses this effect (Fig. 5). The effect of RtGEF looks very subtle and variable, it should be confirmed by examining additional reporters of Hippo pathway activity. It also seems like the disc in 5A is at a different stage &/or the quantitation is done from a different region as compared to the disc in 5C.
• The analysis of the influence of Vha68-2 mutant clones, and their genetic interaction with Git, similarly suffers from missing controls and incomplete analysis. Additional Hippo reporters besides just Diap1 should be examined. The Diap1 analysis which shows reduced expression needs examination of neutral controls or nuclear markers to assess potential apoptosis within clones, or changes in focal plane.

Similarly, the analysis of Arf79F mutant clones in Fig 7E,G is compromised by lack of controls for viability and tissue layer, and analysis of an additional Hippo reporter is once again essential.

Significance

The strength of the study is the potential dissection of novel connections between the lgl tumor suppressor and the Hippo pathway. However, there are signifiant limitations due to the preliminary nature of the study, which is incomplete and missing essential controls. If these limitations are overcome the work will be of interest to specialists in the field.

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Referee #1

Evidence, reproducibility and clarity

The manuscript entitled "The Drosophila Tumour Suppressor Lgl and Vap33 activate the Hippo pathway by a dual mechanism, involving RtGEF/Git/Arf79F and inhibition of the V-ATPase." by Portela et al. presents an interesting perspective of the molecular mechanism regulating Hippo pathway, revealing new proteins involved in this process.

In this study, the authors try to show us that Lgl activates the Hippo pathway via Vap33 either by interacting with RtGEF/Git/Arf79F or by inhibiting V-ATPase, thus controlling epithelial tissue growth. The methodology used by the authors is adequate but could benefit from further experiments that would allow them to reach the conclusions stated in their research.

Thus, based on the interpretation of the results presented by the authors some concerns were raised that should be addressed during the review process and that are explained in the major comments.

Major comments:

• It is not clear why in "The Hippo signaling pathway is negatively regulated by V-ATPase activity in Drosophila" section, the authors use Vha68-2 RNAi to reduce the activity of V-ATPase and later they use the overexpression of Vha44 to activate V-ATPase. The authors should explain why they used different proteins to regulate V-ATPase. The way the authors wrote their results sounds like different Vha proteins regulate V-ATPase, which means that cells may have different ways to activate V-ATPases, not being clear if regardless that the downstream effect of V-ATPase activation is always reflected in the Hippo pathway. Thus, the authors should state what other Vha proteins may have a similar effect, I would like to see evidence that Vha44 and Vha68 knockdown and overexpression leads to similar results.
• In "Vap33 activates the Hippo pathway" section, the authors' conclusions represent a big statement considering the results obtained. Though Diap1 is a Hippo pathway target, it does not mean that this protein is solely regulated by this pathway. For example, there are studies that show that this gene can also be transcribed by STAT activity. Though in the following section the authors show how Vap33 activates this pathway, the results obtained in the section "Vap33 activates the Hippo pathway" are not enough to make this assumption. We suggest that the authors rephrase this section. (Optional: To maintain this statement, the authors should have performed, for example, a luciferase assay containing specifically Hippo pathway binding sites in the Diap1 gene, showing that the transcription factor of the Hippo pathway is somehow regulated by Vap33).
• The authors present a highly speculative discussion, raising different hypotheses. Though such hypotheses are well supported by the literature, the authors would enrich the quality of their research if indeed they could prove them. Particularly, testing for vesicle acidification, testing if V-ATPase indeed blocks the interaction of Lgl/Vap33/RtGEF/Git/Arf79F, and alters Hpo localization, testing if Git/RtGEF inhibits Arf79F and consequent Hpo localization.
• The authors should also apply more specific techniques to infer how the Hippo pathway is affected by such genetic manipulation since diap1 can be a target gene of different pathways.

Minor comments:

• The authors present a well-structured manuscript, that generally is easy to understand. However, at some points, the statements given by the authors seem highly speculative.
• The figures presented in this manuscript and the statistical analysis seem adequate and are clearly described.

Significance

The study presented by Portela et al. gives new insights into the regulation of the Hippo pathway with the discovery of new proteins involved in this mechanism, which can be interesting to those working on basic research and focused on studying signal transduction. However, this study lacks some novelty. Throughout the manuscript, the authors only observed the physiological consequences of manipulating this pathway based on the eye phenotypes, and in the discussion, many hypotheses were raised based on the already available literature, which shows that much is already known about the Hippo pathway.

The advances shown in this study are limited to the description of the signaling pathway itself and to the eye morphology. As a suggestion, the authors should explore the knowledge of their findings in order to understand how we can use them to achieve advances in other fields and physiological conditions. For example, only at the end of the discussion, did the authors raise the questions that would really push their discoveries a step forward, namely how this mechanism acts during the response to tissue wounding and whether the mammalian orthologs of Lgl and Vap33 also act via these mechanisms to control tissue growth in mammals. It would be interesting if the authors could direct their research efforts to understand if the proteins identified can be targeted to improve wound healing or to delay aging for example.

Altogether, the authors present an interesting study but, at this moment, it still lacks the significance and novelty needed for publication. We encourage the authors to keep up their good work to address these suggestions, which will definitely improve the quality of their 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 #3

Evidence, reproducibility and clarity

Summary

In their manuscript, Tetzlaff et al. report a substantially improved protocol for the isolation of mitochondria from the parasitic apicomplexan Toxoplasma gondii, which allowed improved sequencing and in-depth analyses of the organism's peculiarly complex mitochondrial genome. Follow-up small RNA-sequencing made it then possible to confirm the expression of fragmented mitochondrial ribosomal RNAs (mt-rRNAs) and to identify a dozen new RNA species of unknown function. The authors document not only multiple Toxoplasma mitochondrial genes that overlap one another-including rRNA and protein-coding genes, otherwise a rare occurrence-but also show that some fragmented rRNA genes recombine, effectively leading to multifunctional sequence segments, another rare feature and consequence of the peculiar architecture of the organism's mitochondrial genome. Lastly, the authors confirm that products of three genes presumed to encode pieces of the highly fragmented mitochondrial large subunit (mtLSU) rRNA do indeed assemble-presumably with additional components-into large molecular-weight complex(es).

Major comments

Key conclusions of the manuscript are that Toxoplasma's mitogenome encodes overlapping rRNA and protein-coding genes, divergent and chimeric rRNA pieces, and several small RNAs (sRNAs) of unknown function. Provided evidence is very solid for certain aspects of the study, but objectionable for the others as detailed below.

1. The extent of the presented analysis of rRNAs and unassigned sRNAs seems lacking. In several places of the manuscript, the authors wonder about potential implications of divergent rRNA sequences, but their analyses appear to have been limited to sequence similarity searches. Had modelling of secondary structure interactions been attempted, this conundrum could potentially be solved. Importantly, similarity searches (to conventional rRNAs) were performed using BLASTN, which is a rather crude tool for the purpose, instead of covariance models/HMMs. It is therefore not entirely surprising that some sRNAs remained unassigned. Admittedly, recognizing rRNA motifs in divergent RNAs is a challenging issue. However, it is important to not conflate similarity to conventional rRNA and the molecule's functionality as an rRNA, i.e., sequence divergence does not necessarily disqualify the unassigned sRNAs as potential rRNAs. Mitochondrial rRNA sequences are among the most divergent, often constrained only by base-pairing, if at all, as has shown the research on kinetoplastid and diplonemid mt-rRNAs, which contain very few conserved elements and very few base pairs (e.g., Ramrath,2018,Science & Valach,2023,NAR). Even in generally less divergent cases such as green algae, the fragment encoding a highly divergent and derived 5S-like rRNA has only been recognized as such only after the mitoribosome structures were determined (Waltz,2021,Nature Comm & Tobiasson,2022,Nature Comm). It would not be surprising if the same was the case for Toxoplasma's fairly quickly evolving mitochondrial genome.
2. The discovery of overlapping protein-coding and rRNA genes is intriguing, but the authors do not explain why it should be considered as fundamentally groundbreaking as the 'Abstract' and 'Discussion' make it sound. Gene overlaps are found in mitochondria of many organisms (e.g., fungi, animals, various protists), especially of tRNA and protein-coding genes. Even in Plasmodium, a rather close relative of Toxoplasma studied in the presented work, LSUB (rRNA) gene overlaps cob (protein) gene in the antisense orientation. Admittedly, the extent of the overlaps in Toxoplasma does seem fairly high at a first glance, but it is necessary to provide more data and, importantly, broader context to make the case that Toxoplasma overlaps are in any way special. For instance, what is the average size of the overlaps? What is their cumulative size? How does their extent (i.e., the size of overlapping coding sequences compared to the total length of coding sequences) compare to gene overlaps in other (mitochondrial) genomes? Certain additional aspects of the analysis and interpretation of protein- and/or rRNA-coding sequence overlaps are somewhat underdeveloped. For example, are the RNA-coding regions that overlap protein-coding sequences more divergent in those three conserved proteins compared to other organisms, i.e., does their function as rRNA take precedence, or is the converse the truth, i.e., are the rRNA sections more divergent? RNA19 (overlapping coxIII and cob) is the only example discussed in depth, but at least a short sentence summarizing the overall picture would be useful. As for the authors' interpretations, proposed formation of sRNA:mRNA hybrids, through which sRNAs could by implicated in facilitating mRNA recognition by the mitoribosome, is an interesting hypothesis, but a simpler scenario, which is given very little space, is that the genes happen to overlap by chance and that the overlaps are merely a consequence of genome compaction (a phenomenon that the authors rightly highlight). Without a comprehensive analysis, it is impossible to conclude which possibility is more likely. For instance, if both protein-coding and non-protein-coding sequences are divergent, this would indicate that there are few evolutionary constraints and so the fact that these sequences overlap means very little and might be just due to neutral drift, an effect of genome compaction without much consequence for the organism. Lastly, considerable significance is attributed in the study to the presence of antisense overlaps, especially between rRNA- (or sRNA-) and protein-coding genes. Yet, the overall extent of sense and antisense overlaps in the Toxoplasma mitogenome is quite similar, which-again-seems to point to a neutral evolutionary process. Can the authors elaborate if this aspect of the genome architecture was taken into account and if they regard it as of lesser relevance (and why, if so)?
3. Another controversial issue concerns prevalent sequence block combinations and their impact on mitochondrial gene expression regulation. The authors postulate that 5′-terminal blocks of protein-coding genes always occurring near other protein-coding blocks has some functional significance. However, concluding this from just two cases (even if out of two) is quite speculative and seems like reading too much into a pattern that could very well be due to chance alone. The authors argue that the fact that 5′ ends of coxI & coxIII genes overlap is another indication of potential gene expression coordination. While it is possible to envisage such a regulation because of the 5′ termini proximity, the overlap between these genes means that their connection is hardwired into the genome, making it difficult to compare this particular case to the other sequence blocks. Arguably, it is tempting to speculate that an evolutionary pressure exists to coordinate protein expression and such a coordination does not indeed seem implausible, but the presented data and arguments are not convincing. The authors should at least expand on their ideas in the 'Discussion' and indicate potential experiments and/or which additional data could support (or refute) their speculation.
4. My last major point concerns the experimental examination of large-molecular weight complexes and the interpretation of its results. To prove incorporation of the sRNAs into the mitoribosome, i.e., confirm that they do indeed represent rRNAs, the authors opted to investigate their distribution across a sucrose velocity gradient. This is a relatively simple and powerful approach and although it does not provide an irrevocable proof, it can be used to gain very useful insights. However, the presented design has critical flaws: 1) all sRNAs selected for Northern blot were mtLSU components, so only the mtLSU would be detected; 2) a single cytosolic LSU component was used as the control, so the distribution of cyto-SSU subunit, cyto-ribosome, and cyto-polysomes is actually unclear; 3) the authors' interpretation relies on the assumption that both mitochondrial and cytosolic ribosomes preserve their association as polysomes, but no relevant control is provided for this. For example, in Figure 6, fractions 6-14 clearly contain cyto-LSU, but polysomes (e.g., disomes) might just as well start in fractions 12-14; without additional controls, or at least continuous monitoring of UV absorbance across the gradient (to show a typical polysomal pattern), it is not guaranteed that what was detected actually included cyto-polysomes. The main concern, however, is the migration of mitoribosomes. First, the authors presume that the fractions 7-8 contain the mitochondrial monosomes because they are the fractions closest to the gradient top. This is not guaranteed. In fact, based on the experience of our and our colleagues' labs and taking into consideration the conditions used for the described experiment (more precisely, the use of Triton and deoxycholate, which in many organisms lead to mitoribosome subunit dissociation), it seems quite likely that fractions 7-9 actually contain separated mtLSU, not monosomes. Fractions in higher sucrose concentration would then represent monosomes and possibly assembly intermediates, though perhaps also a minor polysomal fraction (if the interactions are preserved in the conditions used). In particular, if the assembly process in Apicomplexa is as complex as in Euglenozoa (e.g., see papers on kinetoplastid mitoribosomes Saurer,2019,Science & Tobiasson,2021,EMBO Journal), which does not seem unlikely in Toxoplasma given the necessity to incorporate ~15 distinct rRNA pieces per mitoribosomal subunit, then the assembly intermediates might form ribonucleoprotein complexes that migrate quite far into a sucrose gradient (e.g., as in kinetoplastid mtSSU, Maslov,2007,Mol Biol Parasit). Thus, while it can be reasonably well argued that the detected RNAs co-migrate with the mtLSU (and possibly mito-monosome), the claim that they associate with mito-polysomes is open to question. More critically, investigating only sRNAs that are clearly identifiable as rRNA pieces-and all from the mtLSU at that-does not automatically prove that all sRNAs associate with the mitoribosome. To argue that the unassigned sRNAs are associated with mitoribosomes, northern blots of as many as possible (but at the very least one) unassigned sRNAs are absolutely necessary. However, I encourage the authors to consider performing additional experiments to address the issues raised in the preceding paragraph: for example, a western blot of mitochondrial ribosomal protein(s), a northern blot with at least one mtSSU rRNA fragment (since all three shown are from mtLSU), as well as a test that would examine the influence of detergents on mitoribosome stability (e.g., use milder detergents such as digitonin or dodecylmaltoside). Furthermore, if experimental conditions are identified allowing subunit dissociation, it would be possible to discern to which subunit which sRNA belongs and, importantly, whether the unassigned sRNAs are just "disguised" rRNAs (simplest explanation) or something completely different (speculative explanation seemingly favoured by the authors). All this would substantially boost the significance of the presented work.

Minor comments

General comments

The word "novel" is rather overused in the manuscript. At several places, it is inappropriate, as the presented results are not as unprecedented as the manuscript makes them sound; at other places, it might be acceptable, but as the word's meaning is vague, the text would benefit from using more informative term(s) instead. The former case is exemplified by the sentence at the lane 102 "Here, we present a novel method for enriching organellar nucleic acids" - "novel" does not simply mean "new", but alludes to "unprecedented"; yet, the devised method, albeit clever, is a modification of existing approaches. The sentence at the lane 182 illustrates the latter case where "novel blocks" are mentioned, but "previously not detected blocks" would be more appropriate and to the point. The labelling of 5′ and 3′ is inconsistent throughout the manuscript - sometimes the prime is used, sometimes the apostrophe, sometimes it is the single quotation mark.

Abstract

In light of the raised concerns, the authors should consider carefully rewording this section, as some of the formulations are mis-representing the data and lead to unjustified generalizations.

Introduction

lanes 72-73: "How rRNA fragments are assembled into functional ribosomes remains an enigma." - Without proper context, this statement feels like an exaggeration. Fragmented rRNAs are known from other species and their mitoribosome structures were determined in the past few years (i.e., Tetrahymena, Polytomella, Chlamydomonas). Arguably, these mt-rRNAs are not as fragmented as in Toxoplasma, but at the very least, it is clear that base-pairing of rRNA pieces and RNA-binding proteins play significant roles in the process. If the authors think that this is not the case in apicomplexans, this should be at least alluded to, if not explained. l. 80-83: The paragraph mixes information on Plasmodium and Toxoplasma. To a non-initiated reader, this can be quite confusing. It would be useful to specify which species the authors refer to. l. 83-86: The information on the atovaquone impact lacks reference(s). l. 105: "demonstrated that they are incorporated into polysomes" - In light of the issues raised above and if the authors opt not to expand the work as suggested above, this claim (and similar throughout the text) should be emended. l. 106-108: "allowed us to identify novel transcripts, many of which originate from block boundaries and contain mixed origins from coding and noncoding regions." - This sentence would benefit from rephrasing because it is difficult to comprehend (the sequences overlap protein-coding and non-protein-coding regions, but do not contain any origins).

Results

l. 115-117: "cell fractionation method that takes advantage of the differential cholesterol content in plasma membranes" - Does Toxoplasma contain cholesterol? Perhaps it might be more practical to refer to sterols (since the effect of digitonin is not limited to cholesterol). l. 147: "significant increase" - It might be useful to specify that the increase was ~42-fold, so that readers can see the extent of improvement; it has the advantage of really highlighting the achievement. l. 180: "have been lettered from A-V" - Rewording to "designated by letters from A to V" works better. l. 213-218: This section is essentially a discussion so should be moved the corresponding section of the manuscript. l. 262-265: cotranscripts/transcript isoforms - It is a matter of nomenclature, but it seems more appropriate to refer to "a transcript containing LSUF and LSUG regions" instead of a co-transcript, because in the latter case, one then expects that these two will be separated in a following processing step, which-as the authors demonstrate-is clearly not the case for the vast majority of the population of these rRNA pieces. Given the prevalence of the larger pieces, it seems more appropriate to refer to the "smaller transcript isoforms" as possible degradation products and not isoforms, which implies some kind of functional relevance. l. 281: In the section "Discovery of novel rRNA fragments", it might be useful to provide a graphical representation or at least a sentence summarizing all different categories of sRNAs. For instance, what is missing from the text is that there are 11 species for which homologous sequences in "conventional" rRNAs were not identified and out of these only 4 seem to have sequence homologs in other Apicomplexa. In addition, in Table S5, the authors could indicate where these homologs are located in Plasmodium, since these appear to be newly identified candidates for Plasmodium sRNA species/rRNA pieces. l. 313-314: "In general, block combinations lead to the expression of novel RNAs in T. gondii that are not found in apicomplexan species with a simpler genome organization. " - It is not clear where this generalization comes from: Fig.S5A shows that RNA5, RNA7, RNA23t extend across block borders (but based on Table S5 are not unique to Toxoplasma), while only RNA31 and RNA34 are both absent from other Apicomplexa and extend across block borders - yet, this is still less than half of all newly identified sRNAs. In addition, the novelty claim is not clear either: based on the presented data, several sRNAs that overlap are clearly present in other apicomplexans (e.g., RNA1 and RNA2) and thus are not completely new, but merely more divergent in Toxoplasma, because parts of their sequence have been replaced by the shared sequence segment. l. 319-320: "None of the three RNAs had detectable homologies to rRNA." - Specify to which rRNAs were the sequences compared to make the inference. l. 320-321: "For all five coding-noncoding RNAs, homologs are present in the mitochondrial genome of P. falciparum." - Does this mean that they remain unassigned in Plasmodium as well or that they have not been previously recognized in Plasmodium? Confusingly, RNA34 is labeled as not having homologs in Apicomplexa in Table S5. In addition, mentioning "coding-noncoding RNAs" is somewhat misleading because some of the sRNAs clearly code for mt-rRNA pieces. l. 335-338: This section contains contradictory statements that should be reformulated. A couple of sentences prior, the authors experimentally determined that RNA19 actually overlaps only a single protein-coding sequence (coxI), but then refer to the original and demonstrably incorrect annotation of RNA19 overlapping also the cob gene. l. 341: The authors mention similarity to rRNA, but do not specify which rRNA. Referring to similarity to known or conserved rRNA sequences or segments would work better. Still, the region of the block S (i.e., 5′ proximal segment of RNA19) falls into the region between helices H51 and H60 of the domain III in the LSU secondary structure, which is sequence-wise relatively poorly conserved-especially in mitochondrial rRNAs-so sequence divergence is not unexpected. l. 366: "Note that RNA1 and RNA2 are registered according to their shared sequence" - Unclear what "registered" means here. l. 416-421: Specifying when reference is made to cytosolic vs. mitochondrial monosomes and polysomes would make this section and the related parts of the 'Discussion' clearer. Also, the authors clearly state here that there might be technical reasons for what they observed, but ignore this possibility in the 'Discussion' and assume that they did indeed separate polysomes.

Discussion

l. 444: "the reshuffling appears limited to specific block borders and is not random" - How many biological replicates of nanopore sequencing were performed? Did the authors test other T. gondii strains? What about other apicomplexan species? Unless this has been done, there is no demonstration that the block order and block-joining frequencies documented here are (more or less) constant and that block order is under some kind of purifying selection. Hence, the conclusion that the block borders are not random is debatable. Arguably, it is not random in this particular experiment, but neither is it limited to specific blocks because most combinations have been detected (even if at low frequency; Figure S1). l. 450: "One intriguing finding is the obligate linkage of coding sequences" - Presuming this sentence is about protein-coding sequences, this should be reformulated because it mis-represents the actual data. Figure 2 clearly shows that protein-coding blocks are often linked to rRNA-coding blocks. l. 454: "balancing the expression of coxI and coxIII" - Not clear where this information comes from, as it is not from the cited papers. l. 460-461: "Our small RNA sequencing results revealed another potential advantage of the block organization of the T. gondii mitochondrial genome" - This should be reformulated. Clearly, the discovery of the 15 sRNAs was facilitated by the recognition of block order, but the presented argument is a bit confusing: how does the organization into blocks provide an "advantage" and what kind of advantage do the authors mean? (An evolutionary advantage or an advantage related to gene expression regulation or an advantage for their sRNA-Seq data mapping?) l. 462-478: Multiple explanations are provided for the existence of sRNAs at block borders and what these sRNAs represent. While I agree that it is important to consider all options, even the more debatable ones, the authors seem to forget the simplest possibility: the identified unassigned sRNAs could well be rRNA pieces and them being encoded across block borders is not any more, nor any less surprising than the fact that protein-coding genes are encoded across (several) gene blocks. l. 485: "antisense RNA surveillance" - In contrast to the nuclei, the existence of a genuine antisense RNA "surveillance" mechanism in mitochondria is uncertain. Given what is known from mitochondria of other organisms (especially plants and kinetoplastids), it seems more likely that certain regions of sense and antisense transcripts are protected from exonucleases by RNA-binding proteins (RBPs such as PPR and related helix-turn-helix repeat proteins, e.g., Toxoplasma's homologs HPRs discovered in Plasmodium [Hillebrand,2018,NAR]), leading to RNAs that partially overlap, but are actually protected from base-pairing by these RBPs. This is not taken into account in any presented explanation of the phenomenon of antisense gene overlaps. l. 490: "start codon. while also " - Typo: should be a comma, not a dot. l. 500: "discovery of block-border sRNAs highlights the complex regulatory mechanisms at play" - This should be reformulated: the claim is very speculative, since no hard data are provided on such regulatory mechanisms in the presented work. l. 504: "sRNAs are incorporated into polysome-size structures" - In light of the concerns raised in the preceding section, this should be reformulated. l. 539-540: The closing sentence should be reformulated. The mitogenome organization in blocks per se does not "allow" the sequences to function as both mRNA and rRNA. Rather, it seems to be a combination of 1) the compactness of the genome that seems to lead to the re-use of certain segments in both mRNA and rRNA or in two distinct rRNAs, and 2) the apparently dynamic nature of the genome (due to recombination among gene blocks) that brings together certain combinations of gene blocks.

Methods

l. 607: Only agarose gel separation is mentioned, but most experiments shown are of denaturing PAGE separations (which is actually mentioned in several figure legends). l. 636: "Paste your materials and methods section here." - To be removed. l. 662: "NUMTS" - This should be "NUMTs"; the same typo occurs at multiple places in the 'Methods' section. l. 704: "Homology search for novel transcript annotation" - Somewhat confusing title; it is possible to guess what the authors likely mean, but it is unclear. l. 715: "New block annotations can be found in GenBank." - 1) The whole community would very likely appreciate if the GenBank entries were properly annotated (i.e., genes added), not just showed sequences as is currently the case for all Namasivayam,2021,Genome Res entries (not sure about the authors' own entries because they were inaccessible). If impossible to update the entries of the Namasivayam,2021,Genome Res study, then just submitting anew properly annotated GenBank entries would be appropriate. 2) It was not possible to properly assess some of the claims in the manuscript because access to the files was not provided to reviewers, nor have been the newly submitted GenBank entries made public by the authors.

Figures

Figure 1B - The load of total proteins into each well is unclear. Ponceau stain does not show identical loads, so it is unclear what the reader should take as the reference. Figure 1D -The phrasing "fragments found in the pellet fractions of the protocol" is a bit awkward. The fragments are in the pellet fractions after plasma membrane permeabilization and benzonase incubation, not in the "fractions of the protocol". Figure 2 - The chosen hues of red and green (for coxI and coxIII) are of such similar intensity that they are virtually indistinguishable to ~2% of the readers. A colourblind-friendly palette would be very much appreciated. For guidelines, see for example: https://www.nature.com/articles/nmeth.1618 . Figure 3 - The use of lowercase letters to indicate the probes (instead of the full probe names) is a nice idea and simplifies the reading experience, but the use of the same letter 'a' in different figures for different probes is confusing. Labeling each probe with a unique ID/letter and indicating this ID in the Table S6 (e.g., by adding an additional column) would work much better. Figure 4A - The wiggle lines for rRNAs are coloured in purple shades, which contrast with the grey colour that is assigned to them in the Figure 2. Keeping a consistent colour palette across figures would be preferable. Figure 4C - If the E.coli sequence was on the outer lines, the Toxoplasma sequences could be closer to one another, which would make it easier for the reader to understand the alignment. Figure 5 - Purple shades for rRNA are somewhat difficult to discern from the blue cob. Also, the 'reference' wiggles would work better if demarcated as a key because this would make it visually clearer that they are shared by the A and B panels.

Supplementary Information

Figure S1 - An explanation what the A and B panels show is missing. Figure S5 - It is difficult to appreciate the extent of overlaps with protein-coding sequences if these are missing from the figure (unlike in Fig.5). Table S4 - Nuclear genome accession number is missing. Add "mitochondrial" to the label of the column "sequence blocks". Table S5 - 1) It is unclear what the 'rRNA homology' refers to. (It does not seem to be the nomenclature used by Feagin et al.,2012, PLoS One.) 2) An extension of the table (or perhaps a separate table) with the cumulative size of mtLSU and mtSSU rRNA pieces, as well as unassigned sRNAs, would be useful. 3) It should also be stated somewhere if homologs of any of the rRNA pieces known from Plasmodium are missing in Toxoplasma. (If so, they could be among the newly identified short RNAs.)

Referees cross-commenting

Referee #2 rightly pointed out that basic statistics on nanopore reads, as well as omitted methodological details (e.g., minimap2 and SAMtools settings) would be welcome. Similarly, Figure 2 should indicate the upstream/downstream block orientation. If the authors intend to position their work as a major achievement in mitochondrial enrichment for Toxoplasma (as the text currently indicates), I also agree that a comparison with previously published protocols would not be out of place.

Significance

Speaking from personal experience, devising a protocol for such a substantial mitochondrial enrichment, as the study presents, is a great technical achievement, which cannot be understated, especially for a protist or any somewhat unconventional model organism. The mitoribosomal community will certainly take notice of the improved catalogue of mitochondrial rRNA pieces, while the discovery of overlapping protein-coding and rRNA genes will be of interest to those working in the field of mitochondrial evolutionary biology. The study already provides a significant upgrade from the previous attempts to understand the nature of the mitochondrial genome in Toxoplasma (and in Apicomplexa in general), and is well positioned to become a source of inspiration for future studies in the field. However, being at a crossroad of genomics, evolution, and molecular biology, it has certain limitations in its current form, mainly because the evolutionary and molecular biology aspects would benefit from further development (see 'Major concerns'). The text is generally well written and accompanying figures well designed, but clarifications, broader context, and less speculative interpretation would be welcome (as detailed mostly in 'Minor concerns'). To justify publication in a journal with a broad readership, the authors should provide additional experimental evidence to strengthen their case and generalize their findings.

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Referee #2

Evidence, reproducibility and clarity

In this article, the authors delve into an intriguing topic, aiming to enhance our understanding of the organization of the mitochondrial genome of T. gondii, a parasite of significant importance in both human and animal health contexts.

In essence, their approach involves enriching mitochondrial material, followed by genome sequencing and the analysis of mitochondrial short RNAs. They achieve a remarkable depth of mitochondrial sequencing and generate valuable RNA data. Furthermore, their efforts lead to the discovery and annotation of new short RNAs.

Overall, the article is well-crafted and presents compelling results. However, it's worth noting that, at times, the authors appear somewhat self-congratulatory, and certain results might be perceived as overly ambitious. Nevertheless, the discussion is aptly constructed.

Major comment:

They assert certain discoveries that had already been reported. Notably, they adapt an existing protocol for mitochondrial enrichment and describe it as 'We developed a protocol to enrich T. gondii mitochondria.' It's worth noting that they neither reference a more recently described protocol (PMC6851545) nor compare the performance of their modified protocol with the original.

The protocol they employ does not seem to yield exceptionally high success rates, as mitochondrial DNA constitutes less than 10% of the total sequenced DNA.

Additionally, they frequently mention the identification of specific combinations of sequence blocks previously identified by Namasivayam et al. (PMC8092004), which was also discussed in Namasivayam et al. 2021."

Missing in the supplementary material are basic details on the sequences performed. Distribution of mitochondrial reads length, depth, etc.

Further clarification is needed for Figure 2. Specifically, the frequency units or combinations of frequency (A, B, and C) are not clearly explained. While the matrix's asymmetry suggests a 5'- 3' orientation difference, this orientation difference is not explicitly specified (B). Additionally, the fragment Mp does not appear in the block combination figure (C).

Some points to improve the introduction:

Provide an evolutionary context for the following phrase: 'An idiosyncratic feature of Apicomplexa is a highly derived mitochondrial genome.' Specify what you intend to emphasize.

Line56: The sentence must begin with a capital letter

In line 58 "Nuclear genes encoding proteins with functions in mitochondria contribute strongly to P. falciparum and T. gondii cell fitness" Although it is mentioned later, it would be more effective to introduce the fact that all but three genes are encoded in the nucleus.

Line68: "Apicomplexan mitogenomes usually code only for three proteins" It seems to me that 'usually' should not be included.

Line 65-67: The sentence should include that the mitochondrial genome is composed of a total of 20 blocks of repeating sequences organized in multiple DNA molecules of varying length and non-random combinations

At the end of the introduction, the authors state that they have developed a protocol for mitochondrial enrichment. The text should be modified taking into account that: 1- The new protocol is an adaptation of another existing protocol. In fact, the Methods the authors say the protocol was "slightly" modified. 2- There is already existing mitochondrial enrichment protocol available [Reference: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851545/#mmi14357-bib-0074]. In any case, they should consider performing a comparative analysis between the proposed protocol and existing ones to determine its relative effectiveness. It should be noted that the proposed protocol enriches in organelles (including the nucleus and apicoplast), but when sequencing DNA, mitochondrial DNA accounts for only 5% of the total reads, which may raise doubts about its overall efficacy.

Some points related to Results section:

Lines 113-115: 'To distinguish between NUMTs (nuclear DNA sequences that originated from mitochondria) and true mitochondrial sequences, it is necessary to enrich mitochondrial DNA.' I disagree with this sentence. NUMTs, in general, consist of very short sequences. With long reads, it is relatively straightforward to differentiate mitochondrial sequences from those nuclear sequences that have small mitochondrial fractions. In my opinion, even many Illumina reads can be confidently identified as belonging solely to the mitochondria. I found this article that supports this argument, indicating that the majority of NUMTs are less than 100 nucleotides in length [Reference: https://pubmed.ncbi.nlm.nih.gov/37293002/].

Lines 166-168: 'A previous sequencing study used Oxford Nanopore sequencing technology (ONT) to identify combinations of sequence blocks in T. gondii mitochondria (Namasivayam et al. 2021).' However, it's important to note that Namasivayam's group did not merely use ONT to identify combinations of blocks; rather, they discovered, identified, and defined these combinations based on sequencing with long reads.

Line 177: "The length of mitochondrial reads ranged from 87 nt to 17,424 nt" It would be beneficial to include a histogram depicting the length distribution of the obtained reads. It's worth noting that nanopore reads tend to be shorter than Illumina reads

Line 194-195 "we found that only a small fraction of all possible block combinations are prevalent within the genome" this has been previously described (PMC8092004)

Line 201. "This indicates that the genome's flexibility is limited and that not all block combinations are realized". This is consistent with the findings published by Namasivayam et al. in 2021, which have already established that the combination of the 21 blocks is non-random.

Line 205: "All combinations are well covered in our ONT results and helped to refine block borders relative to previous annotations (Fig. S2)" In the supplementary materials the authors say: "However, the blocks Fp, Kp, and Mp frequently occur separately in the mitochondrial genome We therefore treated Fp, Kp and Mp as separate blocks and have shortened the blocks F, K and M accordingly". As far as I understand, for this very reason, Namasivayam and collaborators annotate them as partial fragments, which may appear in other regions but are, in turn, parts of larger F, K, and M fragments. To redefine the segments F, K, and M without the sequences corresponding to Fp, Kp, and Mp, as shown in Figure S2, these fragments should be distinct from the 'partials.' In other words, segments of the type (F minus Fp), (K minus Kp), and (M minus Mp) should appear in the reads, and should be distinguishable from Fp, Kp, and Mp. If this distinction is made, I am satisfied with the new definition.However, if such a separation is not evident, it seems important to clarify it in the text or to reconsider this new definition.

Lines 221-223: "This suggests that there is no need to postulate mechanisms of genomic or posttranscriptional block shuffling to arrive at full-length open reading frames." The authors argue that invoking mechanisms of genomic or post-transcriptional block shuffling is unnecessary to explain the presence of full-length open reading frames, given that genes represent 2-3% of mitochondrial sequences. However, there is a missing estimate regarding the probability of encountering all three genes within a single molecule or mitochondrial genome, as well as the total number of sequenced mitochondria. Consequently, the statement appears overly assertive. In the absence of alternative mechanisms for generating complete genes, this would mean that at most only 1646 mitochondrial genomes would have been sequenced. To comprehensively address this issue, the authors should consider discussing this scenario further. They should also provide information about how many reads they found containing all three genes and how many contained two of the genes.

Lines 249-250 "using the block combinations identified here by ONT sequencing " which is the difference between blocks identified here with those on Namasivayam ? The division of M, K and F fragments?

Line 287: "The six remaining small RNA fragments are specific to T. gondii" I would suggest being more cautious in this sentence by stating that they were not found in other organisms. Given the similarity of the mitochondrial genome between T. gondii, N. caninum, and other coccidians, it would be expected to find them in these organisms as well.

Line 300 "Among the novel small RNAs identified, there is also a class that was only detectable due to our insights into genome block combinations." A valid strategy is to map the small RNAs to the generated nanopore reads or to an assembly made with these reads, rather than solely relying on the single blocks or combinations of blocks, as this approach would yield the same result.

Line 444: "Upon closer scrutiny, however, the reshuffling appears limited to specific block borders and is not random" This was already established by Namasivayam et al 2021.

I would like to highlight the potential for a more comprehensive examination of the mitochondrial genome in the discussion. While the proposed explanations for the presence of sRNAs at the 'block borders' appear plausible, it's worth noting that the definition of these blocks is artificial rather than biological. I think it is interesting to discuss without the concept of block sequences, but of sequences existing in the mitochondrial genome. Therefore, it's important to discuss whether these sequences (the block borders) are consistently present in all mitochondrial genomes. The total cumulative length of the blocks is 5.9 Kb, which is relatively small and comparable to one of the smallest mitochondrial genomes on record. It is conceivable that recombination and the generation of new sequences play a role in expanding genomic space for encoding, such as RNAs.

Line 535-536 "We developed a protocol to enrich T. gondii mitochondria and used Nanopore sequencing to comprehensively map the genome with its repeated sequence blocks." I find this sentence to be somewhat assertive, especially considering that they modified an existing protocol and obtained results that may not be optimal. Additionally, they have not compared their protocol with other available methods for mitochondrial enrichment.

Some points related to Method section: In none of the experiments is it specified how many parasites were initially used as a starting point

"Masking NUMTs in the T. gondii nuclear genome" it's unclear whether the authors utilize all hits or filter the results of BLASTN. It would be helpful if they specify the criteria for filtering, such as identity percentage or query coverage. Additionally, it's not clear how they generate the GFF3 file from the BLAST results, or whether they instead create a BED file. Providing clarification on this process would enhance the reproducibility of their methods. Moreover, it would be beneficial if the authors include information regarding the number of sequences they intend to mask, the average length of the NUMTs, and the total percentage of the genome these masked sequences represent.

Line 657 "Mapping results were filtered using SAMtools"<br /> The text does not specify the filtering criteria or the parameters used for this process.

Line 673 establish "No matching reads were found" in the "Sequence comparisons of ONT reads found here with published ONT reads for the T. gondii mitochondrial genome" but in the results the authors say: "While smaller reads of our dataset are found in full within longer reads in the published datasets, we do not find any examples for reads that would be full matches between the dataset. Could you provide a more detailed explanation? Specifically, I would like to know how many reads from the dataset (including their length) are also present in other datasets, and at what minimum length do they cease to coincide?

689 - The text does not specify the filtering criteria or the parameters used for Samtools filtering process.

Lines 689-693 Please describe better the methodology used.

Line 696: the program is fastp not fastq (Chen et al. 2018)

Line 697: what do you mean only the ends of the reads were mapped? how many bases? Or do they mean that they map the reads fowrards and reverse reads?

Significance

In this article, the authors delve into an intriguing topic, aiming to enhance our understanding of the organization of the mitochondrial genome of T. gondii, a parasite of significant importance in both human and animal health contexts.

In essence, their approach involves enriching mitochondrial material, followed by genome sequencing and the analysis of mitochondrial short RNAs. They achieve a remarkable depth of mitochondrial sequencing and generate valuable RNA data. Furthermore, their efforts lead to the discovery and annotation of new short RNAs.

Overall, the article is well-crafted and presents compelling results. However, it's worth noting that, at times, the authors appear somewhat self-congratulatory, and certain results might be perceived as overly ambitious. Nevertheless, the discussion is aptly constructed.

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Referee #1

Evidence, reproducibility and clarity

Summary:

Mitochondrial genomes of Apicomplexa parasites have undergone dramatic reductions during their evolution with genes for only three proteins remaining. In addition, ribosomal RNA genes are present in different, often species-specific gene arrangements. Toxoplasma exhibits massive variations in gene arrangement that are distributed over multiple copies. In this study the Schmitz-Linneweber lab not only re-analysed the mitochondrial genome of Toxoplasma gondii using a novel protocol for enriching the organellar nucleic acid, allowing to sequence the mitochondrial genome at unprecedented depth, they also addressed an enigma regarding the expression status of mitochondrial ribosomes. While indirect evidence of mitochondrial translation exists, no direct evidence for active mitoribosomes exist and their composition is still poorly understood. Here, using HTS or small RNAs the authors demonstrate that they are incorporated into polysomes. Furthermore, the authors developed the hypothesis that the block-based genome organization enables the dual utilization of mitochondrial sequences as both messenger RNAs and ribosomal RNAs.

Own opinion/Major comments

The mitochondria of the Apicomplexa are characterized by massive gene transfer into the cell nucleus, and sequence rearrangements, which has led to a single, questioned genome reorganization. The underlying mechanisms of gene transcription and translation are also poorly understood. In a previous study, the Kissinger lab demonstrate the unique organization of the mitochondrial genome that consists of minimally of 21 sequence blocks (SBs) totaling 5.9 kb that exist as nonrandom concatemers (Namasivayam et al. 2021). In this study the authors optimized a new isolation technique of organellar content to sequence the mitochondrial genome. This new purification protocol appears to be very robust and allowed the sequencing of mitochondrial genome at unprecedented depth. The obtained data not only validate previous studies, but they also suggest several new features, such as (potentially) continuous reshuffling of DNA blocks, leading to independent block combinations. The most important aspect of this study is the demonstration of polysomes and the presence of rRNAs within these complexes, taking previous studies (i.e. Lacombe et al., 2019) a step further. Taking all these efforts and data into account it is a very nice and interesting study that will certainly be of interest for a broader readership. All the presented data and analysis appear to be solid and well controlled. However, it must be mentioned that this reviewer is not an expert when it comes to the analysis and comparison of huge genomic datasets and the opinion of a bioinformatician would be helpful in assessing this study in more detail. All other data (organellar purification and analysis of polysomes) appear state of the art and no corrections are required.

Referees cross-commenting

I agree with reviewer 2 and 3. Some additional details on techniques and the enrichment should be added.

Significance

General assessment:

Taking all these efforts and data into account it is a very nice and interesting study that will certainly be of interest for a broader readership. All the presented data and analysis appear to be solid and well controlled. However, it must be mentioned that this reviewer is not an expert when it comes to the analysis and comparison of huge genomic datasets and the opinion of a bioinformatician would be helpful in assessing this study in more detail. All other data (organellar purification and analysis of polysomes) appear state of the art and no corrections are required.

Advance:

The study fills an important gap in our knowledge regarding the organization and translational activity of the apicomplexan (Toxoplasma) mitoribosome. See also comments above.

Audience: Cell Biology, Parasitology, Mitochondria

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Reply to the reviewers

Manuscript number: RC-2023-02012

Corresponding author(s): Frederic, Berger

[Please use this template only if the submitted manuscript should be considered by the affiliate journal as a full revision in response to the points raised by the reviewers.

If you wish to submit a preliminary revision with a revision plan, please use our "Revision Plan" template. It is important to use the appropriate template to clearly inform the editors of your intentions.]

1. General Statements [optional]

This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

We thank reviewers for useful suggestions and comments on our manuscript which helped to improve and strengthen our conclusions. Our point-by-point answers are below. We have answered most of the points raised by the reviewers and added numerous new experimental data including detailed structural and biochemical analyses that led to support further that BCP4 (and not BCP3) is the plant functional counterpart of MDC1 because in response to DNA damage it binds phosphorylated H2A.X and recruits the MRN complex. In addition, we provide further support to the phylogenetic analysis and evidence for the plant counterpart of PAXIP1.

We believe that our revised manuscript which includes a set of new experimental data strongly support our main conclusion that BCP4 is a functional counterpart of metazoan MDC1.

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)):

MDC1 is a key regulator of DNA damage responses (DDR) in animals. MDC1 has multiple protein domains, in which the BRCT domain binds γH2A.X. However, plants lack the homolog of MDC1. In this study, the authors found that BCP4 binds γH2A.X and proposed that BCP4 is a functional counterpart of MDC1, which will greatly enhance our understanding of plant DDR pathway. I have the following concerns.

1. The relationship between BCP3 and BCP4 needs to be clarified. Line 255, the authors mentioned that"we conclude that BCP3 and BCP4 have functional properties as human MDC1". In the Abstract, the authors mentioned that "we identified BCP4 as a candidate ortholog of human MDC1". I am confused about the conclusion. Both BCP3 and BCP4 are or only BCP4 is MDC1? In addition, in BCP3 and BCP4, only their BRCT domains share homology with MDC1. They lack other domains of MDC1. Therefore, "ortholog" may not be an appropriate term. I think "functional counterpart" may be a better term.

Response: Our analysis emphasizes the fact that human MDC1 is very derived from an ancestral form MDC1 that did not share most domains found in MDC1 from mammals. Because it is still difficult to establish with certainly what the ancestral MDC1 was, we agree that functional counterpart is a more correct term, so we changed this accordingly throughout the manuscript.

BCP1-4 all contains tandem BRCT domains. I am wondering whether it is possible to figure out why only BCP3 and BCP4 bind γH2A.X through sequence analysis. Are there any key residues essential for γH2A.X binding?

Response: We used AlphaFold models of tBRCT domain of BCP1, BCP2, BCP3, and BCP4. While in Alphafold models the tBRCT domain of each BCP protein largely overlaps with a structure of human MDC1 tBRCT domain, only the tBRCT domain of BCP3 and BCP4 are predicted to make contacts with γH2A.X similar to that of human MDC1. Although residues that are involved are not fully conserved between BCP3/4 and human MDC1 we obtain in vitro data supporting that the interaction of BCP4 is mediated by a comparable pocket of three key residues that contact the phosphate group of γH2A.X. See also answers to comments of Referee #2 and new Figures 3 and 4, corresponding description on page 8-9, and Supporting figure 3.

Line 183, "On an unrooted phylogenetic tree, these two proteins clustered with MDC1 and PAXIP1 (Figure 1B).". In Figure 1B, MDC1 is closer to BCP3 and BCP4 than PAXIP1 and PAXIP1 is closer to BCP2 than MDC1. If the authors want to include PAXIP1 in Figure 1C, the authors should include BCP2 as well. In the γH2A.X binding assays, I do not understand why the authors tested BCP1 instead of BCP2. In Figure 2D, why bcp2 was not included?

Response: We created a new alignment for Figure 1C including BCP2 tBRCT domain and the tree that includes all BCP BRCT domain (Figure 1D) does support a close relation between MDC1 and BCP3 and 4 and PAXIP1 and BCP1. As we stated on page 5-6 lines 175-178, BCP2, also contains acetyltransferase domain, which is unique for plant BCP2 protein. Based on its domain organization, BCP2 was not considered as a candidate for MDC1 homolog, and we did not perform mutant complementation. This is why after our initial analysis of bcp mutants (DNA damage sensitivity, formation of gammaH2A.X, and phylogeny), and based on similarities with MDC1 and PAXIP1 we focused on bcp1, 3, and 4 mutants and the corresponding proteins. The function of BCP2 remains to be investigated, but this is out of the scope of this manuscript that is primarily dedicated to find the functional counterparts of MDC1 and PAXIP1.

The expression level of BCP1-4 in the mutants need to be examined using qRT-PCR. Especially, for the bcp3 mutant, which is a weak allele.

Response: We did not perform this experiment, because it was done in Vladejic et al., 2022 and expression data are available from various genomic dataset on TAIR.

The authors used "bleomycin" or "zeocin" in different parts. Please be consistent.

Response: We consistently use Bleomycin for treatment of seedlings followed by western blotting and Zeocin for true leaf assay. These two agents produce DNA double strand brakes in similar ways, and we could show previously that levels of γH2A.X and γH2A.W.7 are similar when using these two agents (Rosa M, Mittelsten Scheid O Bio. Protoc. 4:e1093. doi: 10.21769/BioProtoc.1093: Lorkovic et al., Curr Biol. 2017, doi: 10.1016/j.cub.2017.03.002). Zeocin was chosen for true leaf assays because we observe lower variation between batches and biological repeats compared with bleomycin.

1. Figure 3E and 3F, please indicate the treatments of the upper and lower panels.

Response: Thank you for pointing this out. This has been indicated in the corresponding legend of the new Figure 3 A - C.

Line 338, "bcp1 mutants show reduced homologous recombination rates (Fan et al., 2022; Vladejić et al., 2022; Yu et al., 2023)". The bcp1 mutant was not reported in Fan et al. paper.

Response: This sentence has been changed to accurately describe data in each of the mentioned papers.

Line 40, please add a comma after "In ". Line 331, please add a comma after "In mammals". animal

Response: This has been corrected.

Line 123, "only BRCA1 and BARD1 were described in plant lineage". Additional BRCT proteins were described in plants, including XIP1 (Nat. Commun. 13:7942), BCP1/DDRM2 (New Phytol. 238:1073-1084; Front. Plant Sci. 13:1023358), and DDRM1 (PNAS, 119: e2202970119).

Response: This sentence refers to known BRCT domain mediator/effector proteins. From the published data about XIP1, BCP1/DDRM2, and DDRM1, it is not possible to assign these functions to proteins in question. Nevertheless, we changed this sentence to avoid ambiguous interpretation and we later in the text introduce XIP1, BCP1/DDRM2, and DDRM1 proteins as needed.

Reviewer #1 (Significance (Required)):

This study identified BCP4 as a functional counterpart of MDC1, which filled the gap of plant DDR signaling.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __ In this study, Frédéric Berger and colleagues identified BCP4 in Arabidopsis thaliana as a potential plant orthologue of vertebrate MDC1. The conclusions are based on both in silico analysis (phylogenetic analysis) and in vitro biochemical and cell biological experiments. BCP4 loss causes sensitivity of DNA damage. Moreover, BCP4 binds to a phosphopeptide derived from the C-terminus of H2AX, via its C-terminal BRCT domains and forms foci in cells exposed to DNA damage, which co-localize with gammaH2AX foci.

Major comments: The conclusions are generally supported by the data, but the evidence presented is still quite limited. For example, it is still possible that BCP4 recruitment to sites of DNA damage is mediated by another protein and not by direct interaction with gammaH2AX. To firmly conclude that BCP4 is an MDC1 orthologue, it is in my opinion essential to perform a (limited) mutagenesis analysis. The key amino acids in the BRCT domains that recognize gammaH2AX need to be mutated and it has to be shown that these mutants are defective for H2AX phosphopeptide binding and are not recruited to sites of DNA damage. Such residues may be tricky to identify, but one obvious candidate would be the Ser residue in beta1 (VLFS motif). In vertebrates, this is a Thr that directly interacts with the phosphate in gammaH2AX. Another possible critical site may be shortly before alpha2 (RTRN motif). In vertebrates, it is RTVK, and the K makes direct contacts with the phosphate in gammaH2AX. This function is perhaps carried out by an R. Structure prediction with alphafold may help to identify the most critical residues

Response: We thank the reviewer for these suggestions. We used AphaFold to predict structures of tBRCT domains of all BCPproteins and compared them with structure of human MDC1 in complex with gamaH2A.X peptide. Based on these analyses we performed mutagenesis of critical amino acids in BCP4 based on their predicted interaction and their conservation. We showed that mutations of critical residues reduced or almost completely abolished binding of BCP4 to γH2A.X. These data are now part of the new Figure 4. See also corresponding description on page 8-9. In addition we provide genetic data that show that the foci formation of BCP4 depends on H2A.X (new Fig 3B and C). We did not attempt genetic complementation experiments with these mutants because it would take nine months to obtain stable transgenic plant lines expressing various mutant versions of BCP4 and the limitation of Arabidopsis transgenesis does not allow to control precisely the expression of transgenes, which could cause a difficult interpretation in this particular case.

Another critical issue is the introduction of the study. This needs to be revised, because the literature is not correctly cited in several places. For example, the cited paper by Salguero et al., 2019 did not show that the PST repeats of MDC1 constitute a docking site of TP53BP1, but instead, that the PST repeats can bind to chromatin independently of gammaH2AX.

Response: We thank the reviewer for spotting this mistake. We carefully checked all references and corrected all wrongly associated ones or used original reports instead of reviews.

Also, we did re-write some parts of the Introduction as referee #1 also asked for some clarification.

The data are generally well presented and convincing. The only thing that needs to be added is a quantification of the microscopic analysis (e.g. number of foci per cell, or similar).

Response: We quantified the foci number in all mutants reported in Figure 2C. These data are now included in the new Figure 2D. Optional: it would be interesting to address the question why plants seem to have two MDC1 orthologues. The longer BCP4 and the shorter BCP3. What is the functional difference between those? Do they perhaps distribute functions that are combined in one protein in vertebrate MDC1 on two different proteins? Response: Thank you for prompting us to address this outstanding question. We now provide evidence supporting that only BCP4 is a functional counterpart of MDC1. We show that a specific region of BCP4 but not BCP3 is able to interact with NBS1 of the MRN complex (see new Figure 6). Also, BCP3 is missing the N-terminal TQxϕ repeats present in BCP4. Although the function of these repeats is unknown at this point, these data together suggest some functional diversification between BCP3 and BCP4. We mention this on page 11, lines 372-374.

Reviewer #2 (Significance (Required)):

The strength of the study is the detailed phylogenetic analysis. Also, the biochemistry and cell biology is well done.

Limitations are the lack of evidence that BCP4 carries out functions in the cell (beyond recognising gammaH2AX) that are carried out by MDC1 in vertebrate cells

Response: We thank the reviewer for pointing out this important point. To address it we performed pull-down assays with TQxϕ and SQ/DWD regions of BCP4 with NBS1 and found that Arabidopsis NBS1 interacts with the SQ/DWD region, and that this interaction is mediated by FHA+tBRCT of NBS1. Based on Alphafold prediction, we performed further deletion and point mutation analysis of the SQ/DWD region and defined that the binding of NBS1 requires an alpha-helix comprising sequence that is not conserved in BCP3. So, we concluded that a sequence specific of BCP4 (not in BCP3) is capable of recruiting the MRN subunit NBS1.

At this point we could not demonstrate this in vivo by analyzing NBS1 foci in BCP4 mutant background. Unfortunately, commercial antibodies for plant NBS1 or other subunits of the MRN complex are not available, and to get transgenic plants expressing fluorescent protein tagged NBS1 would require a period much longer than the time for reasonable revisions of a manuscript. Nevertheless, our in vitro interaction data strongly argue for BCP4 having function in binding MRN complex as human MDC1, although the mode of interaction of BCP4 with NBS1 is different from that of human MDC1 and NBS1.

Please see the new Figure 6 and corresponding description on page 11-12.

The study is of great interest to readers working on chromatin responses to DNA damage in plants.

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

Summary The authors set out to find proteins containing BRCT domain to isolate the readers of phosphorylated H2A.X in plants. Using systematic analysis of the BRCT domain proteome, they discovered 21 proteins. Further analysis showed that BCP3 and BCP4 are the ortholog of animal MDC1 and BCP1 is the animal ortholog of PAXIP1. They also extended their work to an evolutionary perspective, finding that BCP1 and BCP4 in plants and PAXIP1 and MDC1 in metazoans evolved independently form a common ancestor. However, this manuscript raises some concerns. Checkout the comments and questions below.

Major comments: 1) If you think that BCP3 and BCP4 work as a mediator of DDR, can you show us that those mutants have a defect of DDR? The authors only assessed true leaf developing. Leaf developing is affected by not only DNA damage but also other factor. Therefore, authors should show us additional data showing the BCP mutant lines show defective of DNA damage response.

Response: The “true leaf assay” is a classical assay for testing plant mutants for DNA damage sensitivity (Rosa M, Mittelsten Scheid O Bio. Protoc. 4:e1093. doi: 10.21769/BioProtoc.1093). If DNA damage occurs and is not efficiently repaired, meristematic cells in shoot meristem are arrested and do not divide, hence plants do not produce the first pair of “true” leaves after cotyledons expand. In this assay cotyledons open and grow normally as they are already fully determined and do not undergo any cell division after seed germination.

In this assay the treated WT seedlings also show a reduction of the number of plants with true leaves as compared with untreated WT (100%). Furthermore, WT and mutant seedlings develop normally and comparably without Zeocin induced DNA damage.

2) Do you have DNA damage sensitivity data for bcp3 bcp4 double mutants?

Response: We obtained bcp3bcp4 double mutant and tested it for DNA damage sensitivity. The double mutant is slightly more sensitive than bcp4 single mutant, but not as sensitive as H2A.X mutant. The reason for this is presumably the nature of the bcp3 mutant allele available, with a T-DNA insertion located in the 5’-UTR with some residual expression of BCP3 protein as reported by Vladejic et al., 2022. We did not feel that this would improve the manuscript, so we did not include this data. To obtain a new mutant allele would take time and work beyond the reasonable time required for revision. In addition, since we show that the functional counterpart of MDC1 is BCP4, we did not think that it is relevant to pursue further the characterization of the function of BCP3 in the context of this manuscript.

3) Some red algae have H2A.X but don't have BCP4 and BCP1 (Figure 4). In this case, how do they read the phosphorylated H2A.X? Can you discuss the point?

Response: Actually, most red algae do not even have H2A.X. At this point we do not have data that could answer this question and it is difficult to make any prediction about this. Analysis of DDR system in red algae is totally beyond the scope of the current manuscript. See also answer to comment #5.

4) L307-L312: I thought that the timing of the appearance of SQEF motif in H2A.X differ from the appearance of BCP4 from Figure 4. Why do you say that the evolution of BCP4 and H2A.X coincides?

Response: we thank the Reviewer for pointing out the need for clarification.

Histone H2A with a C-terminal SQEF/Y motif is categorized as H2A.X that distinguishes this variant from H2A.Z (not discussed here) and H2A itself. In Archaeplastida many algal species possess either H2A or H2A.X. Only in streptophytes the ancestral gene duplicated leading to neofunctionalization of both H2A and H2A.X and in this case H2A.X form a monophyletic clade. The evolution of BPC1 and 4 are slightly posterior or coincident with this neofunctionalized H2A.X variant, suggesting co-evolution in streptophytes.

5) Some red algae don't have BCP1, BCP4 and H2A.X. How do they transfer the signal to downstream? Do you have any idea about this?

Response: To address this interesting question we re-analyzed BRCT domain proteome of the red algae and again could not find any protein containing features of BCP4 present in green algae and land plants or in Opistokont MDC1.

We did find that red algae without MDC1 do encode MRE11, RAD50 but not NBS1. Also, components of non-homologous end joining DNA repair pathway, Ku70 and Ku80 are conserved in these organisms. So, how some red algae cope with DNA damage remains enigmatic. Similarly unicellular red algae do not have the classical autophagy pathway. This is the result of the very strong genome reduction (Response: Thanks for this comment. We did change title of the manuscript to avoid ambiguity.

Minor comments: 6) I think you should show us a schematic representation of BAP1 and PAXIP1 to compare both protein features.

Response: We added schematic presentation of PAXIP1 to Supporting Figure 2B.

7) L176-L178: Which data support this sentence? Response: The sentence in question: “BCP1 has two tBRCT domains positioned at the N- and C-terminus and a so far unrecognized C-terminal PHD finger which is present in all plant lineages except Brassicaceae (Supporting Figure S1A and S2A).”

Response: Our data presented on Supporting Figure S1A (schematic presentation of BCP1 protein with indicated PHD finger consensus sequence) and S2A and Source data (alignment of PHD fingers in BCP1 in flowering plants, non-flowering land plants and multicellular green algae) clearly demonstrate the presence of a C-terminal PHD finger in BCP1 except in Brassicaceae. These can also be seen in the full complement of BCP1 sequences that are available in Source data.

8) L271-L279: There are unreadable characters at "TQx_".

Response: This very likely appeared during conversion into PDF file. We fixed this now.

Reviewer #3 (Significance (Required)):

Significance: General assessment: This study give us an idea how organisms have evolved the upstream system of DDR.

Advances: This study extend the knowledge of DNA damage response in plants.

Audience: broad and basic research

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Referee #3

Evidence, reproducibility and clarity

Summary

The authors set out to find proteins containing BRCT domain to isolate the readers of phosphorylated H2A.X in plants. Using systematic analysis of the BRCT domain proteome, they discovered 21 proteins. Further analysis showed that BCP3 and BCP4 are the ortholog of animal MDC1 and BCP1 is the animal ortholog of PAXIP1. They also extended their work to an evolutionary perspective, finding that BCP1 and BCP4 in plants and PAXIP1 and MDC1 in metazoans evolved independently form a common ancestor. However, this manuscript raises some concerns. Checkout the comments and questions below.

Major comments:

1. If you think that BCP3 and BCP4 work as a mediator of DDR, can you show us that those mutants have a defect of DDR? The authors only assessed true leaf developing. Leaf developing is affected by not only DNA damage but also other factor. Therefore, authors should show us additional data showing the BCP mutant lines show defective of DNA damage response.
2. Do you have DNA damage sensitivity data for bcp3 bcp4 double mutants?
3. Some red algae have H2A.X but don't have BCP4 and BCP1 (Figure 4). In this case, how do they read the phosphorylated H2A.X? Can you discuss the point?
4. L307-L312: I thought that the timing of the appearance of SQEF motif in H2A.X differ from the appearance of BCP4 from Figure 4. Why do you say that the evolution of BCP4 and H2A.X coincides?
5. Some red algae don't have BCP1, BCP4 and H2A.X. How do they transfer the signal to downstream? Do you have any idea about this?
6. Title is not clear to understand. Please change it more suitable one.

Minor comments:

1. I think you should show us a schematic representation of BAP1 and PAXIP1 to compare both protein features.
2. L176-L178: Which data support this sentence?
3. L271-L279: There are unreadable characters at "TQx_".

Significance

General assessment:

This study give us an idea how organisms have evolved the upstream system of DDR.

Advances:

This study extend the knowledge of DNA damage response in plants.

Audience:

broad and basic research

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Referee #2

Evidence, reproducibility and clarity

In this study, Frédéric Berger and colleagues identified BCP4 in Arabidopsis thaliana as a potential plant orthologue of vertebrate MDC1. The conclusions are based on both in silico analysis (phylogenetic analysis) and in vitro biochemical and cell biological experiments. BCP4 loss causes sensitivity of DNA damage. Moreover, BCP4 binds to a phosphopeptide derived from the C-terminus of H2AX, via its C-terminal BRCT domains and forms foci in cells exposed to DNA damage, which co-localize with gammaH2AX foci.

Major comments:

The conclusions are generally supported by the data, but the evidence presented is still quite limited. For example, it is still possible that BCP4 recruitment to sites of DNA damage is mediated by another protein and not by direct interaction with gammaH2AX. To firmly conclude that BCP4 is an MDC1 orthologue, it is in my opinion essential to perform a (limited) mutagenesis analysis. The key amino acids in the BRCT domains that recognize gammaH2AX need to be mutated and it has to be shown that these mutants are defective for H2AX phosphopeptide binding and are not recruited to sites of DNA damage. Such residues may be tricky to identify, but one obvious candidate would be the Ser residue in beta1 (VLFS motif). In vertebrates, this is a Thr that directly interacts with the phosphate in gammaH2AX. Another possible critical site may be shortly before alpha2 (RTRN motif). In vertebrates, it is RTVK, and the K makes direct contacts with the phosphate in gammaH2AX. This function is perhaps carried out by an R. Structure prediction with alphafold may help to identify the most critical residues

Another critical issue is the introduction of the study. This needs to be revised, because the literature is not correctly cited in several places. For example, the cited paper by Salguero et al., 2019 did not show that the PST repeats of MDC1 constitute a docking site of TP53BP1, but instead, that the PST repeats can bind to chromatin independently of gammaH2AX.

The data are generally well presented and convincing. The only thing that needs to be added is a quantification of the microscopic analysis (e.g. number of foci per cell, or similar).

Optional: it would be interesting to address the question why plants seem to have two MDC1 orthologues. The longer BCP4 and the shorter BCP3. What is the functional difference between those? Do they perhaps distribute functions that are combined in one protein in vertebrate MDC1 on two different proteins?

Significance

The strength of the study is the detailed phylogenetic analysis. Also, the biochemistry and cell biology is well done.

Limitations are the lack of evidence that BCP4 carries out functions in the cell (beyond recognising gammaH2AX) that are carried out by MDC1 in vertebrate cells

The study is of great interest to readers working on chromatin responses to DNA damage in plants.

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Referee #1

Evidence, reproducibility and clarity

MDC1 is a key regulator of DNA damage responses (DDR) in animals. MDC1 has multiple protein domains, in which the BRCT domain binds γH2A.X. However, plants lack the homolog of MDC1. In this study, the authors found that BCP4 binds γH2A.X and proposed that BCP4 is a functional counterpart of MDC1, which will greatly enhance our understanding of plant DDR pathway. I have the following concerns.

1. The relationship between BCP3 and BCP4 needs to be clarified. Line 255, the authors mentioned that"we conclude that BCP3 and BCP4 have functional properties as human MDC1". In the Abstract, the authors mentioned that "we identified BCP4 as a candidate ortholog of human MDC1". I am confused about the conclusion. Both BCP3 and BCP4 are or only BCP4 is MDC1? In addition, in BCP3 and BCP4, only their BRCT domains share homology with MDC1. They lack other domains of MDC1. Therefore, "ortholog" may not be an appropriate term. I think "functional counterpart" may be a better term.
2. BCP1-4 all contains tandem BRCT domains. I am wondering whether it is possible to figure out why only BCP3 and BCP4 bindγH2A.X through sequence analysis. Are there any key residues essential for γH2A.X binding?
3. Line 183, "On an unrooted phylogenetic tree, these two proteins clustered with MDC1 and PAXIP1 (Figure 1B).". In Figure 1B, MDC1 is closer to BCP3 and BCP4 than PAXIP1 and PAXIP1 is closer to BCP2 than MDC1. If the authors want to include PAXIP1 in Figure 1C, the authors should include BCP2 as well. In the γH2A.X binding assays, I do not understand why the authors tested BCP1 instead of BCP2.
4. The expression level of BCP1-4 in the mutants need to be examined using qRT-PCR. Especially, for the bcp3 mutant, which is a weak allele.
5. The authors used "bleomycin" or "zeocin" in different parts. Please be consistent.
6. In Figure 2D, why bcp2 was not included?
7. Figure 3E and 3F, please indicate the treatments of the upper and lower panels.
8. Line 338, "bcp1 mutants show reduced homologous recombination rates (Fan et al., 2022; Vladejić et al., 2022; Yu et al., 2023)". The bcp1 mutant was not reported in Fan et al. paper.
9. Line 40, please add a comma after "In animal". Line 331, please add a comma after "In mammals".
10. Line 123, "only BRCA1 and BARD1 were described in plant lineage". Additional BRCT proteins were described in plants, including XIP1 (Nat. Commun. 13:7942), BCP1/DDRM2 (New Phytol. 238:1073-1084; Front. Plant Sci. 13:1023358), and DDRM1 (PNAS, 119: e2202970119).

Significance

This study identified BCP4 as a functional counterpart of MDC1, which filled the gap of plant DDR signaling.

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Reply to the reviewers

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Reply to the Reviewers

I thank the Referees for their...

Referee #1

1. The authors should provide more information when...

Responses + The typical domed appearance of a hydrocephalus-harboring skull is apparent as early as P4, as shown in a new side-by-side comparison of pups at that age (Fig. 1A). + Though this is not stated in the MS 2. Figure 6: Why has only...

Response: We expanded the comparison

Minor comments:

1. The text contains several...

Response: We added...

Referee #2

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Referee #2

Evidence, reproducibility and clarity

Summary:

This manuscript addresses how the first mitotic spindle is centered in the ascidian zygote to promote a symmetric cell division. This is a universal problem in animals because the sperm centrosome, which will form the poles of the mitotic spindle, is initially at the edge of the zygote because it comes in from the outside. The authors hypothesize that cortical pulling is turned off so that a combination of microtubule pushing and cytoplasmic pulling can center the mitotic spindle. Experimental methods include live imaging of ascidian zygotes injected with mRNAs and proteins as well as computational modeling. Results support the hypothesis that cortical pulling is turned off at the same time that the spindle centers.

Major comments:

Inhibition of entry into mitosis by p21 injection prevents centrosome centering. This results supports the idea that CDK activity is required for centrosome centering but does not specifically support the inhibition of cortical pulling model.

Data in figure 3 is used to support the conclusion that cytoplasmic pulling does not change between interphase and mitosis and therefore an increase in cytoplasmic pulling during mitosis cannot be responsible for the centering of the spindle. This interpretation needs to be more carefully qualified in the text of the results and discussion. The only "pulling proxy" that is quantitatively compared between interphase and mitosis is movement of Cell Mask Red-labeled endosomes toward or away from the centrosome. (1) Only endosomes are tracked and it is possible that yolk granules or mitochondria could exhibit different results.

(2) If endosomes were the only contributors to cytoplasmic pulling, the ratio of anterograde vs retrograde transport would be significant. Data in Fig. S2C looks like this might change between interphase and mitosis but no statistical result is shown testing for a change in this ratio.

(3) Single plane imaging is justifiably used for this high speed analysis which means that vesicles are likely to leave the focal plane frequently. Leaving the focal plane would artificially reduce "track persistence" which is strangely reported in "n.u." units with very small values. N.u. units are not defined. The units should by um like total transport. A more accurate statement might be: "We could not detect a significant change in centrosome-direct endosome transport in our experiments but we cannot exclude the possibility that a significant difference would be detected with different cargo or different methods." The data presented in figure 4 provides very strong evidence that cortical pulling is reduced in mitosis relative to interphase, supporting the overall conclusion of the paper.<br /> The interpretation of fig. 5 is not strongly supported. Latrunculin is not necessarily going to inhibit cortical pulling and cortical pushing without affecting cytoplasmic pulling. In C. elegans, depletion of GPR/LGN would be the appropriate experiment. The interpretation should be qualified. The presentation of figure 6 could be improved. The protrusions indicative of cortical pushing are not quantified interphase vs mitosis. Qualitatively, there are more protrusions during mitosis than interphase which could support an increase in cortical pushing as a mechanism promoting centration. The interpretation of this result should be clarified. Whether cortical pushing is regulated in the model should also be clarified. The cytosim results presented in figure 7 lend support to he overall conclusions of the manuscript. The legend for figure 7B should state the number of simulations run for each condition.

Minor comments:

The presentation of figure 1 could be improved. 1A and 1D are redundant, and C and D are cited in the text before B. The most important data is figure 1B (quantification of the distance of the paternal DNA from the cell center) but no images of DNA are shown. Only a cartoon of DNA localization is shown. The results text states that the data in fig. 1B was derived from time-lapse sequences of zygotes

(1) expressing histone h2b::tomato,

(2) histone h2b::venus, or

(3) stained with Hoechst. If the zygotes all had microtubules and DNA labelled, Fig. 1A could be 2 color time-lapse images showing both DNA and microtubules. 1A could have the larger number of time points currently in 1D, then 1D could be deleted. The authors should then take care to cite the sub figures in order in the text. Given the number of DNA labeling methods, it would also be appropriate in the methods to state how the authors know that the labeling methods are non-toxic (especially the live cell Hoechst labeling). Fig. S1B needs statistically significant differences marked since the text states that the significant differences in Fig. 1B were reproduced in fixed images in S1B.

The legend for fig. 2B needs to be clarified. It states that the dark shaded bar is "mitosis entry" but the p21 injected zygotes are not entering mitosis at this timepoint.

The legend to figure 4B could spell out Cell Mask Orange.

Referees cross-commenting

I agree with most of reviewer 1's comments. The author's should validate their membrane ingression assay for cortical pulling by providing quantification of cortical actin after latrunculin treatment in each condition. Regarding the expectation that the sperm aster should move toward the cortex during interphase when cortical pulling is active, Fig. 1B shows significant movement toward the cortex during meiosis but movement away (with no statistical significance marked) during interphase. This might be due to a balance with microtubule pushing on the membrane. However, this question raises the need for better presentation of the data in figure 1B. The sperm DNA should start at 0 um from the cortex at fertilization. Is the huge variability in sperm DNA position at the first time point due to variability in egg diameter? If so, an additional plot of distance from the cortex or better a plot with %radius instead of um would be helpful. Or, is the huge variability due to significant movement of the sperm DNA during meiosis before the first time point? If this is the cases, the authors might present a scatter plot of the net displacement toward or away from the cortex for each individual zygote. This improved analysis might address some of reviewer 1's concerns.

Significance

Because inhibition of cortical pulling during M phase has been reported in multiple species before, to have a really high impact, the authors would need to identify the relevant phosphorylation sites on dynein/dynactin/LGN and show that non-phosphorlatable mutants retain invaginations in M phase and the aster fails to center. The work could have a moderate impact on the field with just the controls already suggested.

Significance

Significance

Centering of the first mitotic spindle is an important biological process that has been previously addressed in C. elegans and mammalian zygotes. This manuscript provides a high quality description of centering in ascidian zygotes with appropriate comparisons to mammals and C. elegans. While the quality of the data is strong, no new molecular mechanisms are identified which limits the significance. Because the authors cite primate papers showing that ascidian centering follows the pattern of primates, it is not clear how the current study adds new medical significance to what is already known. Perhaps the authors could highlight what was not shown in the primate papers that is shown in the current manuscript.

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Referee #1

Evidence, reproducibility and clarity

Summary:

Proper mitotic spindle orientation is decisive for asymmetric cell division and cell volume regulation after cell division. Different cellular systems utilize many ways to orient the spindle in space and time. In this work, the authors investigate the mechanisms regulating sperm aster centration in the zygote of ascidian Phallusia mammillata. The authors show that the sperm aster stays close to the cell cortex at the vegetal pole during interphase and migrates to the cell centre during mitosis. Their data reveal that cortical pulling forces are active during interphase, and these forces are off during mitosis. The strength of the work is that the authors are analyzing the aster positioning in eggs of ascidians, where the aster behaviour is similar to primates. The work's limitation is that most important conclusions are made using inhibitors that can impact multiple processes in the zygote of Phallusia mammillata (please see below).

Major Comments:

• In Fig. 4, the authors claim that the cortical forces are strong in interphase and weak in mitosis. This experiment was performed in conditions that disturb the actin cytoskeleton, and the cell membrane invaginations were monitored as a proxy for cortical force generation. Here the authors observed that the number of invaginations are decreased in mitosis, compared to the interphase. This led them to conclude cortical pulling forces are higher in interphase than in mitosis. The change in behaviour of the cell membrane invaginations could be because of a difference in actomyosin-based cytoskeleton thickness/dynamics between interphase and mitosis. Do the authors know if the cortical actomyosin meshwork between interphase and mitosis remains the same?

• Similarly, did the authors test if the injection of p21 or cyclinBdelta90 does not change the actin cytoskeleton in the injected cell versus the non-injected cell (Fig. 4)?

• If the cortical pulling forces are acting on the sperm asters in interphase, as the authors concluded, I wonder why do the authors not observe a significantly more number of invaginations close to the sperm asters because of the high density of microtubules in that region?

• The authors mentioned that these membrane invaginations are microtubule-dependent and cited Godard at al., 2021. This point is vital; thus, the authors should include the nocodazole experiment in their data. Since the dynamic nature of microtubules is critical for aster positioning in C. elegans zygote, the authors should further test if dynamic microtubules regulate sperm aster position in interphase by treating these cells with taxol.

• Also, the authors should analyze if the membrane invaginations during interphase are dynein/dynactin-dependent.

• If the cortical pulling forces are the chief reason to keep sperm asters close to the cell membrane during interphase, then over time, the sperm aster distance from its geometric centre to the cell membrane should decrease. Do the authors observe this?

• The authors should quantify the number of invaginations at the two-cell stage in p21 or cyclinBdelta90 injected cells.

• In Fig. 5, the authors inhibit the actin cytoskeleton for characterizing if the cortical pulling forces are critical to prevent aster migration. The impact of the actin cytoskeleton on aster migration is quite indirect and does not affirmatively support their conclusions that it is via impacting cortical pulling forces. Can the authors show that cortical force generators (dynein/dynactin complexes) are localized at the membrane in their system, and if the actin inhibitors impact their localization?

• It would be important for the readers to see both the DNA and the asters in Fig. 1 as the authors have injected Ensconsin-GFP and H2B-Tom mRNAs. Also, why did the authors choose to measure the distance between male DNA and the cell centre? They could measure the geometric centre of the male aster to the cell centre before the meeting and the centre of the mitotic spindle to the cell centre after spindle assembly, which would be more appropriate for studying spindle behaviour.

Minor points:

1. Do the authors know if the microtubule dynamics remain unaltered in p21 injected zygote (Fig.2)? It could simply be that the impact of p21 injection on aster migration is because of the change in microtubule dynamics

2. In line 149, the authors write, 'During meiosis I, the aster is in the egg cortex' I guess that the authors would like to say that it is juxtaposed to the cell cortex.

Significance

The strength of the work is that the authors are analyzing the aster positioning in eggs of ascidians, where the aster behaviour is similar to primates. The work's limitation is that most important conclusions are made using inhibitors that can impact multiple processes in the zygote of Phallusia mammillata (please see the comments).

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)): Evidence reproducibility and clarity The authors report that the human-specific KLF factor KLF7 can induce pluripotency in humans and can improve the reset toward naïve pluripotency when cells are cultured the PXGL medium. KLF7 falls behind KLF4 in reprogramming efficiency but might have a unique role in naïve reset (10-20 fold less efficient in iPSC colony yield). The topic of the study is interesting and adds important insights into the roles of KLF factors along the pluripotency continuum and pinpoints differences between mice and human. There are implications for stem cell engineering and boosting the developmental potency of stem cells (blastoid formation potential, interspecies chimera formation). However, some of the claims as to the unique role of KLF7 are unconvincing in the absence of comparison with other KLF factors, especially the Yamanaka factor KLF4. The flow and coherence of the text can be improved - at times reasoning and motivation of experiments are hard to follow

Major comments - Why would a pan-pluripotency factor KLF7 which is expressed in both primed and naïve cells more potently trigger the naïve reset than the naïve specific factors KLF4/5/17? Such a comparison could widen the scope and interest of their work.. I would find it interesting if authors would compare the ability of key KLF factors to induce naivety. This is of particular interest as the overexpression of engineered Sox along with KLF4 was reported to improve the quality and developmental potential of PSC in multiple species (MacCarthy et al bioarxiv). Such an analysis could reveal unique features of KLF family members and lead to advanced stem cell models. They actually claim the SK naïve reset does not require naïve medium but the expression of SK alone is sufficient to induce this state. What do the authors think about this claim? Overall I feel the potential role of KLF7 in naïve reset is interesting but underdeveloped.

We thank the reviewer for the useful comments.

It has been shown in murine PSCs, that the pluripotency factors Nanog and Oct4 are expressed both at the naive and primed state and their forced expression, in combination with a medium supporting naive pluripotency, efficiently resets primed murine PSCs to naive (Radzisheuskaya A. et al., 2013; Theunissen T. et al., 2011). It is therefore not surprising that a similar regulation might also be conserved in human and that the general pluripotency factor KLF7 is expressed in both states and drives efficient resetting.

Moreover, we agree that a direct comparison with another KLF factor could improve our work, so thanks to the reviewer’s suggestions, we will generate conventional/primed hPSCs with exogenous KLF4 expression in order to assess the efficiency of chemical resetting compared to hPSCs with overexpression of KLF7.

Minor comments

• P3, line 52: "Surprisingly, however, KLF4 is also routinely used to generate conventional human iPSCs." Why is this surprising? KLF4 (and SOX2) are the most potent iPSC factors whilst MYC and OCT4 can be omitted (at least in mouse).

Thank you for pointing this out. We have rephrased the text accordingly (line 51).

• It would be nice if the demonstration of pluripotency and quality of KLF7 iPSC go beyond transcriptome profiling and included some further assays common in the field.

We assessed the quality of our OSK7M iPSCs by performing an EBs differentiation assay (Fig. 3d). We rephrased the text to further highlight this experiment (line 106). Of note, in vivo assays like teratoma formation are not allowed in Italy due to official regulations on animal testing.

• Fig 1A-B: color coding (of dots) is very confusing- which ones are PSCs and which ones are iPSCs? Another colour palette might fix. What is meant by "interrogating previously published data" (line 67)? Are these public RNA-seq data that were re-analyzed? I

We will highlight in the figures which cells are PSCs or iPSCs using different colours and shapes.

We rephrase the text to clarify that available RNA-seq data were reanalysed (line 67).

• Fig 2b: how were the colony numbers obtained? By morphology, or using live cell staining? So form of staining is recommended colony counting (i.e. TRA-1-60).

We scored colonies both based on their morphology and after OCT4/NANOG staining. Actually, we observed that the counting based on morphology underestimated the number of iPSC colonies, so it is a more stringent method to score reprogrammed cells.

• Fig 2e: Also, they say that "[t]hree technical replicates were carried out for all quantitative PCR". Unless I'm mistaken, it seems that only two technical replicates were performed for these qPCR reactions (two dots visible per bar).

In figure 2e dots refer to two independent experiments. In each experiment we carried out three technical replicates for each sample.

• Fig 3c: "colture"; change to "culture" (and the title: "bone fide" should be "bona fide")

Thank you. We amended the typos in the figure and in the text (line 111).

• For Fig 2/3: since the paper is on KLF4/7, I'm surprised that expression levels of OCT4 and SOX2 were analysed but not KLF4. Given that the main finding was that KLF4 was not upregulated in PSCs, I would be interested to see what the KLF4 levels are like in the iPSCs. RNA-seq analysis/qPCR would be best; but if the authors would like to use other methods, that's fine too.

This is a good suggestion, we will add to Figure 3b the KLF4 expression levels.

• Fig 4: The explanatory text is too sparse. Readers should be reminded of the differences between of naïve and primed PSCs and the known roles of KLF4 (this could also be improved in the introduction). List names of naïve media used on top of author names (5iLA, PXGL, EPSCM etc). Why was HENSM by Hanna excluded?

We will amend the text explaining the main differences between naive and primed PSCs and the role of KLF4.

We will add PSCs derived in the HENSM medium in the analyses shown in figure 4.

• Fig 5: KLF7 is classified as a general pluripotency marker, but KLF4/KLF17 are classified as naïve markers. In that case, wouldn't it make more sense to overexpress a naïve specific marker in order to achieve naïve iPSCs at least as a control? What was the motivation here? I think the authors need to provide a more compelling reasoning why only KLF7 was studied or add more data for other KLFs (especially since it seems that the reprogramming efficiency of KLF4 is higher than that of KLF7 for conventional reprogramming (see Fig 2B)...)

We will perform resetting experiments using KLF4, as suggested, in order to compare the efficiency of KLF7 to a known naive factor.

o Fig 5B: the text currently says that the cells on the left side of Fig 5B are from Day7; but it says the cells are from Day0 in the actual figure. Which one is it? Also, based on how the text is written, do the cells on the left also contain EOS, or are they the wild-type variety?

We agree that the text was confusing. Colonies appeared at day 7, but we showed them at day 12, when they were larger and easier to see. We amended the text accordingly. Moreover, the images at day 0 are simply the cell lines at the beginning of the resetting, which also contain EOS, as quantified on the right panels of Fig. 5b.

o Fig 5c: not all markers in this figure are naïve markers (as stated in the text); would suggest separating the markers and labelling them accordingly AND rewriting the text to reflect that.

We labelled the markers in the Fig. 5c as suggested by the reviewer and rephrased the text (line 136-137).

o Life cell reporters for naivety (CD75,SUSD2) could enrich this study.

We believe that the combination of bulk RNAseq and immunostaining for functional regulators of naive pluripotency (i.e. KLF17 and OCT4 (Lea et al., 2021 Development; Theunissen et al., 2014 Cell Stem Cell) are sufficient to described the acquisition of naive pluripotency.

• Schemes in 5A/6A could indicate when transgenes were added

For our chemical resetting experiments we used conventional hiPSCs (KiPS) with stable expression of KLF7 or an EMPTY vector (lines 126-127). We have also added this detail in the figure legends (line 291).

• Fig 7: the claim regard mouse pluripotency is a little outside of the scope of this paper; would recommend de-emphasizing the claim .

We will streamline the discussion and put less emphasis on murine PSCs.

• Could authors comment on the molecular features and whether there might be any non-redundant biochemical of KLF7 compared to other stemness-related KLFs? Looking at the conservation of the amino acids mediating base readout (-1,2,3,6) I expect specificity for DNA to be identical between KLF7 and KLF4 i.e. Figure S1A as reference for the C2H2numbering convention: https://www.cell.com/cms/10.1016/j.stemcr.2018.07.002/attachment/51171b7f-e644-4b0e-93c9-837632fd5d10/mmc1.pdf

We thank the reviewer for the good suggestion that will be included in the revised manuscript.

• Similarly, are there features outside the DBD that might suggest a unique activity (IDR, TAD,PTM)? It seems KLF7 generates iPSCs much less efficiently than KLF4. Given the high similarity between their DBDs I wonder why this is so.

As above, this is an excellent point for discussion that will be added to revised manuscript.

Reviewer #1 (Significance (Required)): Significance • General assessment: The strength of the study is that the authors provide a potentially new way for the naïve reset in humans. This could improve human stem cell and embryo models. A limitation is that evidence is solely based on molecular (not functional) profiling and the uniqueness of KLF7 versus other KLF's (first and foremost KLF4) was not established. • Advance: Findings on the human-specific role of KLF7 are novel and interesting especially the ability to facilitate the naïve reset. Yet, in the absence of a more systematic comparison with other methods (and KLF factors), the claim that KLF7 is essential for this feat is unconvincing. • Audience: It's of interest to basic researchers in the broader stem cell community and those interested in early embryo development. I work on cellular reprogramming, sequence-structure-function analysis of reprogramming factors and pluripotency.

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Reviewer #2 (Evidence, reproducibility and clarity (Required)): The naïve pluripotency is established in the inner cell mass (ICM) of blastocysts. After implantation, the naïve epiblast becomes primed for lineage specification. Pluripotent stem cells (PSCs) have been successfully derived from early embryos at different stages. In mice, stem cell derivations from ICM yield naïve ESCs. Primed PSCs derived from E5.5-7.5 epiblast are epiblast stem cells (EpiSCs). In humans, stem cell derivations from human embryos have yielded PSCs with features distinct from mouse ESCs and more like EpiSCs. Recently, naïve human PSCs have been directly isolated from pre-implantation epiblast or transformed from primed PSCs. Derivation of naïve hPSCs contributes to studying the molecular events of early lineage specification and accelerates the development of the generation of humanized organs in animal models from naïve hPSCs, opening an exciting avenue for regenerative medicine.

In this manuscript, the authors found that OSK7M could enable the reprogramming of human primary somatic cells. KLF7 is highly expressed in naive PSCs and its forced expression in conventional hPSCs induces upregulation of naive markers and boosts the efficiency of chemical resetting to naive PSCs, suggesting that KLF7 is a general human pluripotency factor and an inducer of pluripotency. The new findings extend KLF7 function in naïve PSC generation and also provide references for the efficient generation of naive PSCs. The people who focus on studying pluripotency and early embryo development might be interested in and influenced by the findings. The data are in general convincing. However, there are some issues that need to be resolved and improved.

Major comments:

1. Line 90: The authors showed that colonies derived from OSKM and OSK7M cocktails could be readily propagated for at least 10 passages. How many passages can OSK7M-iPSCs maintain in vitro prolonged culture?

And how about the pluripotency and developmental potential of OSK7M-iPSCs for a long-time culture? For example, pluripotency gene expression and teratoma formation.

We culture OSK7M-iPSCs up to 10 passages without noticing any abnormalities in the morphologies and duplication rate. However, we could extend such cultures for 5-10 more passages (i.e. a total of 2 months from iPSC generation) and perform staining for pluripotency markers or molecular analyses (by qPCR) and EBs differentiation assay to assess their developmental potential.

In vivo assays like teratoma formation are not allowed in Italy due to official regulations on animal testing.

1. Overexpression of KLF7 promotes the derivation of naïve PSCs. Are they different from naïve PSCs derived only by chemical resetting? For example, the pluripotency, the in vitro or in vivo developmental potential, and the efficiency of human blastoid generation.

A key feature of naive PSCs is the potential to differentiate towards the trophoblast lineage in addition to the 3 germ layers. We will perform in vitro differentiation and EB formation assay to gauge the effect of KLF7 on differentiation potential.

However, establishing a human blastoid generation protocol would be beyond the scope of the current study.

As the manuscript mentioned, KLF7 is a general human pluripotency factor and an inducer of pluripotency. How does KLF7 knock-out affect the biological characteristics of hESCs? And whether KLF17 KO affects the derivation of naïve PSCs?

We agree that it would be informative to study the requirement of KLF7 for the maintenance of primed pluripotency and during resetting. We plan to do so either by knockdown or CRISPRi, depending on which technique allows efficient and controllable depletion of KLF7. It might be the case that a straight KO of KLF7 induces the collapse of primed PSCs, making resetting experiments not feasible.

1. Can naïve PSCs be directly reprogrammed from somatic cells with OSK7M under the PXGL medium? If so, how is the efficiency?

We believe that studying the role of KLF7 in the context of direct reprogramming of somatic cells to naive pluripotency would go beyond the scope of this manuscript, as it would require substantial work for optimisation and generation of reagents.

Moreover, we think that both by over-expression and inhibition of KLF7 during resetting, we will be able to investigate its involvement in naive pluripotency acquisition.

1. Figure 6d: The data showed that in PXGL medium, KiPS (EMPTY) contained about 66% of KLF17+ cells on day 7 and declined to 30% of KLF17+ cells on day 12. Why do KLF17+ cells (naïve PSCs) decline in PXGL medium? Cells overexpressing KLF7 contained about 62% of KLF17+ cells on day 7 and increased to 89% of KLF17+ cells on day 12. Whether KLF7 function at this stage?

The reviewer raised an intriguing point, concerning the maintenance of naive markers during resetting. Chemical resetting seems to induce transiently >60% of KLF17+/OCT4+ positive cells by day 7, however only a fraction of these cells is stabilised until day 12 (30%). In the presence of KLF7 overexpression, we observed a similar induction at day 7, which is maintained, or increased, up to day 12.

This would indicate that KLF7 is important for the maintenance of a population of naive cells, rather than only for their induction.

We will add this important point to the discussion.

1. Figure 6e: The authors showed transcriptome analysis of KiPS KLF7 cells compared to KiPS16 EMPTY cells in standard culture conditions and found that trophoblast markers were not significantly changed. How is the gene expression during primed to naive transition or TSC differentiation?

We have already investigated this aspect, showing that at day 12 during primed to naive transition there is a strong induction of TSC markers, which is ablated by KLF7 expression (Fig. 5d). Quantitative immunostaining for GATA3 (TSC marker) confirmed this lack of activation in the presence of KLF7 (Fig. 6c).

Minor comments:

1. KLF7 is expressed in both primed and naive PSCs and when overexpressed in conventional PSCs, it enhances chemical resetting to naive PSCs. During primed to naïve transition, how does the KLF7 gene expression pattern change?

This is a good suggestion, we will analyse the expression patter of KLF7 during resetting.

1. Line 52: The reference should be added.

Thank you, we will add the reference.

1. Line 210-212: The reference should be added.

Thank you, we will add the reference.

Reviewer #2 (Significance (Required)): The people who focus on studying pluripotency and early embryo development might be interested in and influenced by the findings. The data are in general convincing. However, there are some issues that need to be resolved and improved.

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Reviewer #3 (Evidence, reproducibility and clarity (Required)): Summary: In this manuscript, the authors found that KLF7 is generally expressed in both prime and naïve human pluripotent stem cells. They showed that KLF7 could replace KLF4 to induce human iPS cells in the microfluidic reprogramming system. The authors then found that overexpression of KLF7 in human prime iPSCs can facilitate the generation of naïve iPS cells. They also showed that KLF7 is a repressor of trophoblast markers. Collectively, these findings indicated that KLF7 is a general pluripotency inducer for human iPS and naïve iPS induction.

Major comments:

1. In Figure 2, as the reprogramming efficiency of OSK7M is much lower than that of OSKM, the authors should provide an OSM control to show whether the cells can be reprogrammed without KLF4 and KLF7.

We have performed the requested experiment (reprogramming with OSM only) as part of a manuscript in preparation. We observed an efficiency of reprogramming significantly lower than OSK7M, yet primary iPS colonies could be obtained.

We believe that this is due to the expression of KLF4 and KLF7 in human fibroblasts, as shown in Figure 4a.

1. It will be more convincing to perform a teratoma assay of OSK7M-iPSCs to demonstrate their multilineage differentiation potential.

In vivo assays like teratoma formation cannot be performed in Italy due to official regulations on animal testing.

However, we could extend such cultures for 5-10 more passages (i.e. a total of 2 months from iPSC generation) and perform staining for pluripotency markers or molecular analyses (by qPCR) and EBs differentiation assay to assess their multilineage differentiation potential.

1. Since KLF7 is also expressed in primed human iPS cells, the authors should show the expression level of KLF7 in the established KLF7-iPSC and EMPTY-iPS.

Good suggestion, we will add it to Figure 3b.

Minor comments:

The author claimed that KLF7 is a direct repressor of trophoblast markers, but the data in the manuscript cannot support this conclusion. The author can only claim that KLF7 can inhibit the expression of trophoblast markers.

We agree with the reviewer, and we believe that there was a misunderstanding. On pages 8-9 line 182-190 we also concluded that KLF7 regulates naive pluripotency markers, rather than trophoblast markers. We will rephrase the text to make it clearer.

Reviewer #3 (Significance (Required)): KLF family proteins such as KLF4 and KLF17 have been identified as pluripotent inducers. In this study, the authors demonstrated that KLF7 is a novel pluripotent inducer of human IPS and naïve iPS cells, providing new insights into the functions of KLF family proteins in human pluripotency induction.

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

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Referee #3

Evidence, reproducibility and clarity

Summary:

In this manuscript, the authors found that KLF7 is generally expressed in both prime and naïve human pluripotent stem cells. They showed that KLF7 could replace KLF4 to induce human iPS cells in the microfluidic reprogramming system. The authors then found that overexpression of KLF7 in human prime iPSCs can facilitate the generation of naïve iPS cells. They also showed that KLF7 is a repressor of trophoblast markers. Collectively, these findings indicated that KLF7 is a general pluripotency inducer for human iPS and naïve iPS induction.

Major comments:

1. In Figure 2, as the reprogramming efficiency of OSK7M is much lower than that of OSKM, the authors should provide an OSM control to show whether the cells can be reprogrammed without KLF4 and KLF7.
2. It will be more convincing to perform a teratoma assay of OSK7M-iPSCs to demonstrate their multilineage differentiation potential.
3. Since KLF7 is also expressed in primed human iPS cells, the authors should show the expression level of KLF7 in the established KLF7-iPSC and EMPTY-iPS.

Minor comments:

The author claimed that KLF7 is a direct repressor of trophoblast markers, but the data in the manuscript cannot support this conclusion. The author can only claim that KLF7 can inhibit the expression of trophoblast markers.

Significance

KLF family proteins such as KLF4 and KLF17 have been identified as pluripotent inducers. In this study, the authors demonstrated that KLF7 is a novel pluripotent inducer of human IPS and naïve iPS cells, providing new insights into the functions of KLF family proteins in human pluripotency induction.

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

Learn more at Review Commons

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Referee #2

Evidence, reproducibility and clarity

The naïve pluripotency is established in the inner cell mass (ICM) of blastocysts. After implantation, the naïve epiblast becomes primed for lineage specification. Pluripotent stem cells (PSCs) have been successfully derived from early embryos at different stages. In mice, stem cell derivations from ICM yield naïve ESCs. Primed PSCs derived from E5.5-7.5 epiblast are epiblast stem cells (EpiSCs). In humans, stem cell derivations from human embryos have yielded PSCs with features distinct from mouse ESCs and more like EpiSCs. Recently, naïve human PSCs have been directly isolated from pre-implantation epiblast or transformed from primed PSCs. Derivation of naïve hPSCs contributes to studying the molecular events of early lineage specification and accelerates the development of the generation of humanized organs in animal models from naïve hPSCs, opening an exciting avenue for regenerative medicine.

In this manuscript, the authors found that OSK7M could enable the reprogramming of human primary somatic cells. KLF7 is highly expressed in naive PSCs and its forced expression in conventional hPSCs induces upregulation of naive markers and boosts the efficiency of chemical resetting to naive PSCs, suggesting that KLF7 is a general human pluripotency factor and an inducer of pluripotency. The new findings extend KLF7 function in naïve PSC generation and also provide references for the efficient generation of naive PSCs. The people who focus on studying pluripotency and early embryo development might be interested in and influenced by the findings. The data are in general convincing. However, there are some issues that need to be resolved and improved.

Major comments:

1. Line 90: The authors showed that colonies derived from OSKM and OSK7M cocktails could be readily propagated for at least 10 passages. How many passages can OSK7M-iPSCs maintain in vitro prolonged culture? And how about the pluripotency and developmental potential of OSK7M-iPSCs for a long-time culture? For example, pluripotency gene expression and teratoma formation.
2. Overexpression of KLF7 promotes the derivation of naïve PSCs. Are they different from naïve PSCs derived only by chemical resetting? For example, the pluripotency, the in vitro or in vivo developmental potential, and the efficiency of human blastoid generation. As the manuscript mentioned, KLF7 is a general human pluripotency factor and an inducer of pluripotency. How does KLF7 knock-out affect the biological characteristics of hESCs? And whether KLF17 KO affects the derivation of naïve PSCs?
3. Can naïve PSCs be directly reprogrammed from somatic cells with OSK7M under the PXGL medium? If so, how is the efficiency?
4. Figure 6d: The data showed that in PXGL medium, KiPS (EMPTY) contained about 66% of KLF17+ cells on day 7 and declined to 30% of KLF17+ cells on day 12. Why do KLF17+ cells (naïve PSCs) decline in PXGL medium? Cells overexpressing KLF7 contained about 62% of KLF17+ cells on day 7 and increased to 89% of KLF17+ cells on day 12. Whether KLF7 function at this stage?
5. Figure 6e: The authors showed transcriptome analysis of KiPS KLF7 cells compared to KiPS16 EMPTY cells in standard culture conditions and found that trophoblast markers were not significantly changed. How is the gene expression during primed to naive transition or TSC differentiation?

Minor comments:

1. KLF7 is expressed in both primed and naive PSCs and when overexpressed in conventional PSCs, it enhances chemical resetting to naive PSCs. During primed to naïve transition, how does the KLF7 gene expression pattern change?
2. Line 52: The reference should be added.
3. Line 210-212: The reference should be added.

Significance

The people who focus on studying pluripotency and early embryo development might be interested in and influenced by the findings.

The data are in general convincing. However, there are some issues that need to be resolved and improved.

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

Learn more at Review Commons

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Referee #1

Evidence, reproducibility and clarity

The authors report that the human-specific KLF factor KLF7 can induce pluripotency in humans and can improve the reset toward naïve pluripotency when cells are cultured the PXGL medium. KLF7 falls behind KLF4 in reprogramming efficiency but might have a unique role in naïve reset (10-20 fold less efficient in iPSC colony yield). The topic of the study is interesting and adds important insights into the roles of KLF factors along the pluripotency continuum and pinpoints differences between mice and human. There are implications for stem cell engineering and boosting the developmental potency of stem cells (blastoid formation potential, interspecies chimera formation). However, some of the claims as to the unique role of KLF7 are unconvincing in the absence of comparison with other KLF factors, especially the Yamanaka factor KLF4. The flow and coherence of the text can be improved - at times reasoning and motivation of experiments are hard to follow

Major comments

• Why would a pan-pluripotency factor KLF7 which is expressed in both primed and naïve cells more potently trigger the naïve reset than the naïve specific factors KLF4/5/17? Such a comparison could widen the scope and interest of their work.. I would find it interesting if authors would compare the ability of key KLF factors to induce naivety. This is of particular interest as the overexpression of engineered Sox along with KLF4 was reported to improve the quality and developmental potential of PSC in multiple species (MacCarthy et al bioarxiv). Such an analysis could reveal unique features of KLF family members and lead to advanced stem cell models. They actually claim the SK naïve reset does not require naïve medium but the expression of SK alone is sufficient to induce this state. What do the authors think about this claim? Overall I feel the potential role of KLF7 in naïve reset is interesting but underdeveloped.

Minor comments

• P3, line 52: "Surprisingly, however, KLF4 is also routinely used to generate conventional human iPSCs." Why is this surprising? KLF4 (and SOX2) are the most potent iPSC factors whilst MYC and OCT4 can be omitted (at least in mouse).
• It would be nice if the demonstration of pluripotency and quality of KLF7 iPSC go beyond transcriptome profiling and included some further assays common in the field.
• Fig 1A-B: color coding (of dots) is very confusing- which ones are PSCs and which ones are iPSCs? Another colour palette might fix What is meant by "interrogating previously published data" (line 67)? Are these public RNA-seq data that were re-analyzed? I
• Fig 2b: how were the colony numbers obtained? By morphology, or using live cell staining? So form of staining is recommended colony counting (i.e. TRA-1-60).
• Fig 2e: Also, they say that "[t]hree technical replicates were carried out for all quantitative PCR". Unless I'm mistaken, it seems that only two technical replicates were performed for these qPCR reactions (two dots visible per bar).
• Fig 3c: "colture"; change to "culture" (and the title: "bone fide" should be "bona fide")
• For Fig 2/3: since the paper is on KLF4/7, I'm surprised that expression levels of OCT4 and SOX2 were analysed but not KLF4. Given that the main finding was that KLF4 was not upregulated in PSCs, I would be interested to see what the KLF4 levels are like in the iPSCs. RNA-seq analysis/qPCR would be best; but if the authors would like to use other methods, that's fine too.
• Fig 4: The explanatory text is too sparse. Readers should be reminded of the differences between of naïve and primed PSCs and the known roles of KLF4 (this could also be improved in the introduction). List names of naïve media used on top of author names (5iLA, PXGL, EPSCM etc). Why was HENSM by Hanna excluded?
• Fig 5: KLF7 is classified as a general pluripotency marker, but KLF4/KLF17 are classified as naïve markers. In that case, wouldn't it make more sense to overexpress a naïve specific marker in order to achieve naïve iPSCs at least as a control? What was the motivation here? I think the authors need to provide a more compelling reasoning why only KLF7 was studied or add more data for other KLFs (especially since it seems that the reprogramming efficiency of KLF4 is higher than that of KLF7 for conventional reprogramming (see Fig 2B)...)
  • Fig 5B: the text currently says that the cells on the left side of Fig 5B are from Day7; but it says the cells are from Day0 in the actual figure. Which one is it? Also, based on how the text is written, do the cells on the left also contain EOS, or are they the wild-type variety?
  • Fig 5c: not all markers in this figure are naïve markers (as stated in the text); would suggest separating the markers and labelling them accordingly AND rewriting the text to reflect that.
  • Life cell reporters for naivety (CD75,SUSD2) could enrich this study.
• Schemes in 5A/6A could indicate when transgenes were added
• Fig 7: the claim regard mouse pluripotency is a little outside of the scope of this paper; would recommend de-emphasizing the claim .
• Could authors comment on the molecular features and whether there might be any non-redundant biochemical of KLF7 compared to other stemness-related KLFs? Looking at the conservation of the amino acids mediating base readout (-1,2,3,6) I expect specificity for DNA to be identical between KLF7 and KLF4 i.e. Figure S1A as reference for the C2H2numbering convention: https://www.cell.com/cms/10.1016/j.stemcr.2018.07.002/attachment/51171b7f-e644-4b0e-93c9-837632fd5d10/mmc1.pdf
• Similarly, are there features outside the DBD that might suggest a unique activity (IDR, TAD,PTM)? It seems KLF7 generates iPSCs much less efficiently than KLF4. Given the high similarity between their DBDs I wonder why this is so.

Significance

• General assessment: The strength of the study is that the authors provide a potentially new way for the naïve reset in humans. This could improve human stem cell and embryo models. A limitation is that evidence is solely based on molecular (not functional) profiling and the uniqueness of KLF7 versus other KLF's (first and foremost KLF4) was not established.
• Advance: Findings on the human-specific role of KLF7 are novel and interesting especially the ability to facilitate the naïve reset. Yet, in the absence of a more systematic comparison with other methods (and KLF factors), the claim that KLF7 is essential for this feat is unconvincing.
• Audience: It's of interest to basic researchers in the broader stem cell community and those interested in early embryo development.

I work on cellular reprogramming, sequence-structure-function analysis of reprogramming factors and pluripotency.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

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

In this study, it is shown that cofilin severs actin filaments slowly when fascin is present. Authors show that this is due to slower cluster nucleation of cofilin on fascin-induced actin bundles. Interestingly, the authors show that cofilin binding promotes helicity in actin filament bundles which in turn promotes fascin exclusion and more cofilin clustering in adjacent filament bundles; thus, inducing local transmission of structural changes.

The authors use an elegant approach, and the data is nicely presented. Overall, I

consider that this manuscript is in good shape to be published. It might benefit from language editing, though.

We thank the reviewer for their positive comments. We have edited the manuscript to improve its readability (changes are in blue in the manuscript).

Reviewer #1 (Significance (Required)):

According to me the significance of this manuscript is that elegantly shows the molecular details of the cofilin severing effect of fascin-induced actin filament bundles. The authors show that cofilin binding promotes helicity in actin filament bundles which in turn promotes fascin exclusion and more cofilin clustering in adjacent filament bundles; thus, inducing local transmission of structural changes.

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

Summary:

In this study, Chikireddy et al. perform a series of experiments in which they compare the efficiency of cofilin-mediated severing and actin filament disassembly on individual filaments versus bundles of different sizes from by the actin-bundling protein fascin. The key outcome, quite distinct from previously published conclusions by the authors themselves and other authors, is that fascin bundling actually reduces cofilin-mediated severing mostly because of much slower "nucleation" of cofilin clusters on fascin-bound filament bundles. Cofilin cluster formation is followed by local fascin removal, and the nucleation of a cofilin cluster on an adjacent bundle in the absence of fascin is strongly enhanced. The reason for the latter surprising observation is not entirely clear, but proposed to arise from cofilin-mediated changes in filament helicity of neighboring filaments. To my understanding, the main reason why fascin protects from cofilin severing here rather than enhancing it (as reported previously) is due to the lack of constraining of the induced, cofilin-mediated twist, because if this twist is constrained e.g. by anchoring of the bundles to the surface chamber, then severing by cofilin is accelerated.

We thank the reviewer for their positive feedback on the manuscript. We have substantially edited the manuscript in light of the insightful comments of the reviewer (changes are in blue).

Major comments:

I think the study is very well done, most experiments are super-elegant and controlled; I really don't have any objections against the conclusions drawn, as most of what I have seen is totally justified and reasonable. So from a scientific point of view, I can easily agree with all the major conclusions drawn, and so in my view, this should be published fast.

Minor comments:

There are two minor points that could be addressed:

1) I am not entirely convinced by the conclusions drawn from the EM images shown in Figure 6A, and in particular by the filaments in two-filament bundles locally twisting around each other (without breaking) at spatial sites lacking fascin and decorated by cofilin. This is hard to imagine for me, and the evidence for something like this happening is not very strong, as in the EM, only larger bundles could be observed. In addition, I am not sure that the braiding of filaments seen in the presence of cofilin is really occurring just locally on cofilin-decorated bundle segments and thus indeed coincides with loss of fascin as proposed in the scheme in Fig. 6B.

Can the authors exclude that the braiding is not caused by some experimental artefact, as induced perhaps by sample preparation for negative staining?

We thank the reviewer for raising this point. We have repeated the negative staining EM experiments several times and now show new images and quantification (new Supp Fig. 13). In our new series of experiments, the braiding that was previously shown in Fig. 6 proved difficult to reproduce and to quantify. We therefore decided to remove EM observations from the main Fig. 6, and we no longer present them as evidence supporting the mechanism that we propose for inter-filament cooperativity.

From EM images, we now quantify the frequency of fragmentation of large actin filament bundles. We observed that bundles often terminate with the ends of their filaments in close proximity, consistent with sharp breaks due to co-localized cofilin clusters.

We have rewritten this part of the result section in the manuscript which now reads : ‘To further investigate larger bundles, we imaged them using negative staining electron microscopy. In the absence of cofilin, filaments in bundles are arranged in a parallel manner, as previously reported in vitro (Jansen et al, 2011). Compared with the control, filament bundles exposed to cofilin show numerous sharp breaks (65 breaks per 122 µm of bundles, versus 4 breaks per 68 µm in the control. Supp. Fig. 13). This is consistent with bundle fragmentation occurring at boundaries of co-localized cofilin clusters.’

Did the authors quantify the occurrence of such braided bundle segments with and without cofilin?

How large are these braided segments on average when you quantify them? Would you also see them if you prepared the bundles for an alternative EM-technique, such as Cryo-EM, for instance?

As mentioned in the answer to the previous point, the braided segments proved difficult to reproduce and quantify, and we have removed EM experiments from the main figure 6. Instead of the braided segments, we now quantify the severing of the bundles, and the distribution of filament ends at the extremities of the bundles (new Supp. Fig. 13).

We have not tried Cryo-EM due to limited access to such experimental tools within the timeframe of the study.

This may admittedly all be experimentally challenging, but would it be possible to combine the negative staining of filaments with staining for cofilin and/or fascin using immunogold technology, to prove that the braided segments do indeed correlate with high cofilin and low fascin concentrations? In the absence of such data, and in particular in the absence of a clear quantification, the proposal is too strong in my view. Finally, it would be nice (albeit not essential I guess) to also look at two-filament bundles. The authors stated these can not be easily generated due to the tendency of fascin to promote the formation of larger bundles, but can this not be titrated/tuned somehow by lowering fascin concentrations, to come closer in reality to what is proposed to occur in the scheme in Figure 6B? In any case, the way the data are presented right now appears to constitute a pretty large gap between experimental evidence and theoretical model.

We agree with the reviewer that EM observations are limited and, alone, do not provide strong evidence in favor of braiding/super-twisting being the mechanism responsible for inter-filament cooperativity (please see our answers to the points above). We have performed negative staining EM assays at higher cofilin-1 concentration (500 nM) compared to microfluidics assays, in order for cofilin to quickly bind to filaments, even in large bundles, so that our chances to capture bundles targeted by cofilin would be high.

Nevertheless, both microfluidics and EM observations point in the same direction : bundle fragmentation by cofilin is caused by the co-localized cooperative nucleation of cofilin clusters.

2) I think that the proposal of cofilin-decorated filaments to "transfer" the resulting cofilin-induced changes in filament helicity onto neighboring filaments in the bundle, which is proposed to occur locally and in the absence of fascin is a bit vague, and difficult to understand mechanistically. Can the authors speculate, at least, how they think this would occur? Are there no alternative possibilities for explaining obtained results? Maybe I am missing something here, but with considering cofilin to be monomeric and only harboring one actin-binding site, this proposal of helicity transfer onto neighboring filaments seems inconclusive.

On single actin filaments, the change of helicity induced by cofilin binding has been observed by many groups using EM and cryoEM (e.g. McGough et al, JBC 1997 10.1083/jcb.138.4.771; Egelman et al, PNAS 2011 10.1073/pnas.1110109108 ; Huehn et al, JBC 2018 10.1074/jbc.AC118.001843). These studies have revealed that actin subunits get ‘tilted’ relative to their original orientation along the filament long axis. This leads to the shortening of the helical pitch for cofilin-saturated actin filament segments.

In our assays, the progressive binding of cofilin along a single filament creates a cluster where all actin subunits are tilted and the helical pitch of the filaments within the cluster is shortened (from a half pitch of 36 nm down to 27 nm). This change of helicity in a cluster induces the rotation of one end of the filament relative to the other (as we have shown previously in Wioland et al, PNAS 2019). Therefore, if two parallel filaments are stapled together, the local twisting of one filament causes the twisting of the other in the overlapping region.

We have rephrased this point to more clearly explain this in the last paragraph of the results section:

“From our kinetic analysis, we propose the following model that recapitulates the binding of cofilin to fascin-induced 2-filament bundles (Fig. 6D). Initially, actin filaments in fascin-induced bundles are in conformations that are less favorable for cofilin binding than isolated actin filaments. Once a cofilin cluster has nucleated, its expansion locally triggers fascin unbinding and prevents it from rebinding. The increase of filament helicity induced by cofilin causes a local twisting of the entire bundle, thereby changing the helicity of the adjacent filament in the fascin-free region facing the cofilin cluster. In this region, the increase in filament helicity enhances cofilin affinity, and thus locally promotes the nucleation of a cofilin cluster (inter-filament cooperativity).”

We have tried to think of other alternative scenarios that might explain our observations, but none appeared to be valid.

Reviewer #2 (Significance (Required)):

General assessment:

The strength of this study is that owing, at least in part, to the microfluidics devices employed and the careful biochemistry, the experimental setups are super-controlled and clean, and they are used in a highly innovative and elegant fashion. The simulations are also nice! A limitation is that it is not entirely clear how precisely the main observations can be translated to what's happening in vivo. The results are largely dependent on the bundles not being constrained I understand, so to what extent would bundles be unconstrained in vivo? Perhaps this is not so important, because the experimental setup allows the authors to dissect specific biochemical behaviors and inter-dependencies between distinct actin binding proteins, but the latter view (if correct) could be stated more clearly!

We thank the reviewer for their remarks. We have updated the part where we discuss the biological implications of our in vitro observations to better explain how the twist-constraints expected for fascin bundles in cells would accelerate cofilin bundle disassembly.

Advance:

As stated above, the results are opposite to the proposed synergistic activities of fascin and cofilin observed for bundles previously, perhaps because they were not constrained. So although touched in part and in a very polite fashion in the discussion, the authors could specify more clearly what the differences between the studies are, and which of the distinct activities observed either here or in previous literature will be dominant or more relevant to consider in the future? This will be hard to discern as is now, in particular for non-experts.

We agree with the reviewer that the manuscript will benefit from discussing more in depth the plausible reasons why our experimental observations are in disagreement with the earlier interpretation by Breitsprecher and colleagues. We have extended our discussion on this point, which now reads: “Previously, using pyrene-actin bulk experiments, Breitsprecher and colleagues observed a diminished cofilin binding to fascin-induced filament bundles (Breitsprecher et al, 2011). In spite of this, their observation of fluorescently labeled actin filament bundles seemed to indicate an efficient severing activity. Since cofilin was not fluorescently labeled, they could not observe cofilin clusters, and they proposed that severing was enhanced because fascin served as anchors along filaments and impeded cofilin-induced changes in filament helicity”

Audience:

This manuscript will be most influential for a specialized audience interested in the complexities of biochemical activities of specific actin binding proteins when looking at them in combination. Although specialized, this is still a quite relevant audience though, since prominent actin binding proteins like cofilin are highly important in virtually any cell type and various actin structures, hence of broad relevance again in this respect.

Expertise:

I am a cell biologist and geneticist interested in actin dynamics and actin-based, motile processes.

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

My only major concern that is that although the authors provide data that strongly supports interfilament cooperativity in two filament bundles for cofilin binding, the evidence to support that this induces filament twist on the opposing filament is not strong enough to conclusively establish this as the mechanism for the observed interfilament cooperativity. This is stated as such in the results section as a proposed model, but stated with more certainty than the presented data supports in the discussion. It might be better, based on the data presented, to state this as one possible mechanism for the observed cooperativity.

We thank the reviewer for their remark. We have edited our discussion section to clearly say that inter-filament cooperativity arises from cofilin-induced filament twisting is a proposed model that would best account for what we observed: “Indeed, we report here the exclusion of fascin from within cofilin clusters, and a strong increase in the nucleation of cofilin clusters on adjacent filaments. This inter-filament cooperativity mechanism leads to the co-localized nucleation of cofilin clusters, and permits bundle fragmentation faster than if the nucleation of cofilin clusters on adjacent filaments were purely random. To our knowledge, this is the first time such inter-filament cooperativity is ever reported. To explain this mechanism, we propose that the cofilin-induced change of helicity produced locally on one filament can be transmitted to the adjacent filaments within the bundle (Fig. 6D).”

So far, we have been unable to propose alternative mechanisms that could explain our observations in light of what is known for cofilin at the single filament level (a similar point was raised by reviewer #2, please see above).

Areas within the paper, if addressed, will improve the arguments presented as well as the readability of the paper.

(1) The authors use both the terms cofilin binding (in section I of the results) as well as cofilin nucleation (in section III of the results). It is unclear if these terms are meant to indicate the same, or different, processes. The manuscript would benefit from a clear explanation of the steps of cofilin-mediated disassembly measured and quantified in the experiments, namely nucleation (or binding), cluster growth, and filament or bundle fragmentation. A clear description of these steps would also allow the reader to follow the logic of the experiments from Figure 3 to Figure 5.

We have edited the introduction to better describe the different steps of cofilin activity, and to remove any ambiguity whereas we are referring to cofilin binding or cofilin nucleation.

2) Throughout the paper, the authors move from single filaments, to 2-filament bundles, to multifilament bundles, using different concentrations of fascin and cofilin. Given the biphasic behavior of cofilin, namely that low concentrations favor severing and high concentrations can favor coating and filament stabilization, I think it is important that concentrations for the components are consistent across experiments, and if changes of concentrations of important components (such as cofilin and fascin) are changed, a clear explanation as to why is included.

As explained in the beginning of the result section, most of our experiments and quantification of cofilin activity using the microfluidics assay were done using 200 nM fascin and 200 nM cofilin as a standard. This is the case, in particular, for all the data shown in Fig 2, 3 and 4, where we compare the behavior of single filaments, 2-filament bundles, and larger bundles, exposed to the same protein concentrations.

We have also explored higher fascin and cofilin concentrations to document their respective impact, always mentioning any change in concentration. We agree with the reviewer that cofilin activity is biphasic at the single filament level (in the range of 0 to 1 µM for mammalian ADF/cofilin, at physiological pH 7.4). In the case of fascin-induced bundles (already for two-filament bundles), filament saturation by cofilin, and thus their stabilization, will occur at higher cofilin concentration. This is mainly due to the lower nucleation activity of cofilin on fascin-induced bundles, preventing the nucleation of numerous cofilin clusters that will eventually fuse together, thus preventing saturation of filament bundles by cofilin before bundle fragmentation.

(3) In Figure 2, it is mentioned that for the spectrin seeds with the microfluidics, the filaments consisting of larger bundles were not analyzed along with the single filament and 2-filament bundles. Instead, a different experiment with seeds attached to beads is used to assess larger filament bundles. Why were larger bundles not analyzed in the microfluidic experiment?

We appreciate the insightful observation by the reviewer. When elongating actin filaments from spectrin-actin seeds, the seeds are randomly located on the glass coverslip of the microfluidics chamber. Upon exposure to fascin, only a subsection of any filament will be in contact with one or multiple filaments, ultimately forming a bundle due to the presence of fascin. In the case of high filament densities leading to large bundles, it is very difficult to identify the exact subsection of each filament which is engaged in a bundle or not. Despite our attempts to image individual filaments before and after exposure to fascin for enhanced clarity, the inherent difficulty persisted.

This limitation hindered our ability to quantify cofilin activity on large bundles when using spectrin-actin seeds randomly distributed on glass. To address this, we opted for an alternative approach involving micron-sized beads coated with spectrin-actin seeds. This modification not only circumvents the aforementioned limitation but also aids in the formation of larger bundles (up to 10 filaments per bundle). This adjustment significantly enhances our ability to study and quantify cofilin activity on larger bundles, contributing to a more robust and comprehensive understanding of cofilin activity on bundles.

And conversely, why were 2 filament bundles not assessed with the beads? Comparing the findings on two filament bundles with the findings on multifilament bundles would be easier for the reader if the small and large bundles were evaluated in the same experiments. If this is not experimentally feasible, the authors need to provide clearer explanation as to why this analysis is not included.

Actually, we did assess 2-filament bundles in the bead assay. The cofilin activity on 2-filament bundles from beads are reported, along with larger bundles, in figure 3E-F for nucleation, and in figure 4C for cofilin cluster growth rates.

(4) The authors indicate that at increased fascin concentration (1uM) that single filaments decrease the nucleation rate of cofilin clusters. The authors should comment on the mechanism for fascin (at 1uM concentration) for affecting cofilin binding.

We thank the review for this comment. We now comment on this mechanism in the result section:

“This observation is consistent with the low affinity of fascin for the side of single actin filaments. Furthermore, this indicates that cofilin and fascin may have overlapping binding sites, or that a more complex competition may exist between the two proteins, where the binding of one protein would induce conformational changes on neighboring actin subunits affecting the binding of the other protein.”

(5) The authors should determine and include the dissociation rate for the labeled cofilin used in this study, especially given the proposed mechanism for cofilin excluding fascin within the bundles.

• If the reviewer means that we need to characterize the behavior of the labeled cofilin: in Wioland et al 2017, we have previously reported that cofilin dissociates slowly from cluster boundaries (at 0.7 s-1 for cofilin-1 on alpha-skeletal rabbit actin, as used in the present study) and extremely slowly from inside a cofilin cluster (~2.10-5 s-1).

• If the reviewer means that we should investigate the competition between fascin and cofilin along bundles: we agree that this is indeed an interesting question. However this is quite complex because many unknown parameters are involved. In addition to the on/off-rates of each protein and how it is affected by the presence or the proximity of the other protein, we need to consider that fascin has fewer binding sites than cofilin, and that their accessibility changes as the helicity of the filament evolves as cofilin binds. Investigating this question would require many experiments, which we would need to confront to a model. We believe that this is out of the scope of this manuscript.

(6) For Figure 4, D and E, what do the dynamics of fascin and cofilin signal look like on a larger filament bundle? It would be informative to provide the cofilin cluster nucleation rate on larger filament bundles with a range of fascin concentrations (as in 3D for a two filament bundle).

It would be interesting indeed to investigate the dynamics of fascin and cofilin on larger bundles. However, this experiment is quite challenging due to the fluorescence background of fluorescently-labeled fascin in our microfluidics assay (regardless of bundle size). We have been unable to perform this assay with success on large bundles. Moreover, it is difficult for us to carry out more of these experiments now that the first author of the study has left the lab.

However, based on our results, we would expect that, for large bundles, increasing fascin concentration would also have a limited impact on the reduction of cofilin nucleation. Indeed, for 2-filament bundles, we can note that the increase of fascin concentration has a more limited impact on the nucleation of cofilin clusters (fig. 3D, roughly ~2 fold decrease for fascin from 100 to 500 nM), than the number of filaments per bundle (fig. 3F, a 10-fold decrease when increasing the size of a bundle from 2 to 10 filaments).

(7) Additionally, it would be useful to report the cofilin severing rate at a range of cofilin concentrations, at least for the 2 filament bundles.

Cofilin severing rate is not dependent on cofilin concentration in solution. This has been reported previously by several groups, including ours (e.g. Suarez et al, Current Biology 2011 ; Gressin et al, Current Biology 2015; Wioland et al, Current Biology 2017).

Below is the comparison of cofilin cluster severing at 100 and 200 nM cofilin, on single actin filaments, which we added to supplementary figure 10.

At 100 nM cofilin, we measured a similar cofilin cluster severing rate on 2-filament bundles, by measuring the survival fraction of overlapping cofilin clusters that lead to 2-filament bundle fragmentation over time. The figure pasted below is new Supp. Fig. 11.

When the severing occurs in the two filament bundles, does this severing occur mostly at boundaries with cofilin-actin and bare actin or does this severing occur at cofilin-actin/fascin-actin boundaries?

This is an interesting point. In the presence of a saturating amount of fascin, on 2-filament bundles, one fascin protein is bound every 13 actin subunits along each filament of a bundle. Most of the time, a cofilin boundary will not be in contact with a fasin-bound actin subunit. The limited spatial resolution of optical microscopy does not allow to say whether fascin was present at the boundary of a cofilin cluster or not when severing occurred. Nonetheless, we show that cofilin cluster severing is unaffected by fascin-bundling (i.e. severing rates per cofilin cluster boundary are similar on single filaments and on 2-filament bundles). Overall, bundling by fascin probably does not change the way cofilin severs, i.e. it occurs at the boundary between cofilin-decorated and bare actin regions.

(8) For the images of large bundles appearing braided in figure 6A, the lower left panel the braided appearance is not obvious. Additionally, what is the number of filaments in the bundles shown? Finally, given that in Figure 3F it is indicated that cofilin cluster nucleation events are rare on large bundles, and the cluster growth rate is reduced on large bundles (Figure 4C), the authors need to indicate how frequently this braided appearance is observed as well as what the nucleation rate, growth rate and severing rate is for 500nM cofilin on bundles.

We have repeated the negative staining EM experiments several times and now show new images and quantification (new Supp. Fig. 13). In our new series of experiments, the braiding that was previously shown in Fig. 6 proved difficult to reproduce and to quantify. We therefore decided to remove EM observations from the main fig 6, and we no longer present them as evidence supporting the mechanism that we propose for inter-filament cooperativity.

As stated in point (7) above, the severing rate is independent of cofilin concentration. We’ve used 500 nM cofilin, which is a rather high cofilin concentration, to investigate bundle fragmentation in EM, as in solution we mostly form large bundles and they are more slowly targeted by cofilin than individual or 2-filament bundles (figure 3F & 4C). At the single filament and 2-filament bundle level, the nucleation of cofilin clusters is extremely fast at 500 nM cofilin (> 10-4 s-1 per binding site).

(9) The authors indicate that the rapid fragmentation of twist constrained 2-filament bundles prevented them from directly quantifying the nucleation rate of the subsequent cofilin clusters that overlapped the initial ones. I'm unclear why this is the case, and if this is the case, I don't understand how the authors can be sure that a second nucleation event occurred in the twist constrained bundles. From the experimental data in 7C, it appears that the fragmentation rate for two filament bundles is similar to the fragmentation rate for twist constrained single filaments. The authors need to clearly state what they were able to observe and quantify as well as include the timing for this severing. If the authors could not observe a second nucleation event prior to severing, this should be clearly stated.

Fragmentation of a 2-filament bundle requires the severing of two co-localized cofilin clusters, one on each filament. When 2-filament bundles are twist-constrained the sequence of events leading to bundle fragmentation is fast, thus it is difficult to separate the events within the resolution of our experiment. In this case, cofilin clusters sever quickly, thus the size of the clusters is small, which translates into a low fluorescence intensity. Therefore, the quantification of the increase of cofilin fluorescence intensity along a bundle did not allow us to unambiguously identify the ‘cooperative’ nucleation of two-overlapping cofilin clusters before the bundle is fragmented. So, apart from the quantification of the nucleation of cofilin clusters, which we show is unaffected by twist-constraining the bundles, we were unable to measure the growth rate nor the severing rate of cofilin clusters.

Numerical simulations, using similar severing rates for cofilin clusters on both twist-constrained single filaments and 2-filament bundles, satisfactorily reproduce our experimental observations (dashed lines in Fig. 3C).

We have edited the ‘Twist-constrained bundle fragmentation’ section to clearly say what we measured and what could not be measured : “We observed that the nucleation rate of cofilin clusters was similar for both twist-constrained and twist-unconstrained fascin bundles (Supp. Fig. 15), in agreement with observations on single actin filaments (Wioland et al, 2019b).

The rapid fragmentation of twist-constrained 2-filament bundles prevented us from directly quantifying the nucleation rate of the subsequent cofilin clusters that overlapped with the initial ones, as well as cluster growth and severing rates.”

This could be due to the rapid fragmentation, but it could also be due to severing occurring in the absence of a second cofilin nucleation event. It would be informative to compare the time from cofilin nucleation to severing event for two filament bundles in twist constrained and unconstrained. Clarification of the dynamics of nucleation and spreading of cofilin and the timing of fragmentation of the twist constrained filament bundles is needed.

As explained in the previous point, cofilin-induced severing occurs significantly faster on twist-constrained single actin filaments compared to unconstrained filaments.

For twist-unconstrained filament bundles, we never observed bundle fragmentation that originated from only one cofilin cluster. For twist-constrained bundles, while our observation is limited by the rapid fragmentation of the bundles, it is hard to imagine that a single cofilin cluster on one filament would induce the fragmentation of the neighboring filament. Recently, Bibeau et al, PNAS 2023, using magnetic tweezers to twist single actin filaments, showed that, without cofilin, applying up to 1 rotation/µm to an actin filament does not cause its fragmentation. It is thus reasonable to say that cofilin binding is required to fragment twist-constrained filaments.

Moreover, in our numerical simulations (without inter-filament cooperativity, faithfully reproducing the kinetic of 2-filament fragmentation observed in microfluidics), 75% of bundle fragmentation resulted from a sequential nucleation of cofilin clusters, with the nucleation of the second cofilin cluster occurring after the first cofilin cluster has already severed one filament of the bundle.

(10) Discussion of how twist constrained fragmentation dynamics might affect the dynamics of larger bundles in structures such as filopodia would be useful.

We had substantially edited the discussion section of the manuscript, attempting to better discuss the physiological implications of our in vitro observations (bundle size & twist-constraints).

Minor changes that would improve the paper:

(11) In Figure 1C, Figure 2B and Figure 2E, the indication, on the graph, of the fold-change between the rates is confusing as it is not clear from the labeling on the graph that the x15 is referring to the slope of the lines, keeping this information in the legend is appropriate, but if it is to be included on the graph, perhaps adding in the linear fit on the graph is also needed.

We have edited the figures accordingly, and included fit lines in figure 1.

(12) Figure 7A, lining up the diagram with the kymographs below would help improve interpretation of the diagram and simulation. Alternatively, if the diagram (upper) in A does not diagram the kymographs below, this needs to be clearly stated, and it would be preferable that the diagram above matches the kymographs below.

We have edited the figure layout accordingly.

(13) Despite referencing the Breitsprecher, 2011 paper in the introduction, the authors do not explain how their results showing that cofilin fragments filament bundles slower than single actin filaments correspond with the Breitsprecher findings that fascin bundles favors cofilin filament severing. While the authors do not need to explain the Breitsprecher data, if they reference these findings that run counter to their results, an explanation for the discrepancy would be reasonable to include in the discussion.

We agree with the reviewer comments, which was also a comment made by reviewer #2. We now more directly discuss possible discrepancies between Breitsprecher and our studies : “Previously, using pyrene-actin bulk experiments, Breitsprecher and colleagues reported a diminished cofilin binding to fascin-induced filament bundles (Breitsprecher et al, 2011). In spite of this, their observation of fluorescently labeled actin filament bundles seemed to indicate an efficient severing activity. Since cofilin was not fluorescently labeled, they could not observe cofilin clusters, and they proposed that severing was enhanced because fascin served as anchors along filaments and impeded cofilin-induced changes in filament helicity. This proposed mechanism bears resemblance to our previously reported findings for artificially twist-constrained single actin filaments (Wioland et al, 2019b). Here, we show that this mechanism does not occur in fascin-induced bundles.”

Reviewer #3 (Significance (Required)):

The research presented in "Fascin-induced bundling protects actin filament from disassembly by cofilin" is relevant and of interest to the field as it directly addresses a limitation in our understanding of how cofilin-induced severing occurs in F-actin bundles. Bundled F-actin may constitute the majority of linear F-actin within the cell and is specifically important in F-actin-based structures such as filopodia and stress-fibers. The data supports a model for interfilament cooperativity that provides a molecular mechanism for cofilin-mediated severing of fascin-bundled filaments.

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

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Referee #3

Evidence, reproducibility and clarity

My only major concern that is that although the authors provide data that strongly supports interfilament cooperativity in two filament bundles for cofilin binding, the evidence to support that this induces filament twist on the opposing filament is not strong enough to conclusively establish this as the mechanism for the observed interfilament cooperativity. This is stated as such in the results section as a proposed model, but stated with more certainty than the presented data supports in the discussion. It might be better, based on the data presented, to state this as one possible mechanism for the observed cooperativity.

Areas within the paper, if addressed, will improve the arguments presented as well as the readability of the paper.

1. The authors use both the terms cofilin binding (in section I of the results) as well as cofilin nucleation (in section III of the results). It is unclear if these terms are meant to indicate the same, or different, processes. The manuscript would benefit from a clear explanation of the steps of cofilin-mediated disassembly measured and quantified in the experiments, namely nucleation (or binding), cluster growth, and filament or bundle fragmentation. A clear description of these steps would also allow the reader to follow the logic of the experiments from Figure 3 to Figure 5.
2. Throughout the paper, the authors move from single filaments, to 2-filament bundles, to multifilament bundles, using different concentrations of fascin and cofilin. Given the biphasic behavior of cofilin, namely that low concentrations favor severing and high concentrations can favor coating and filament stabilization, I think it is important that concentrations for the components are consistent across experiments, and if changes of concentrations of important components (such as cofilin and fascin) are changed, a clear explanation as to why is included.
3. In Figure 2, it is mentioned that for the spectrin seeds with the microfluidics, the filaments consisting of larger bundles were not analyzed along with the single filament and 2-filament bundles. Instead, a different experiment with seeds attached to beads is used to assess larger filament bundles. Why were larger bundles not analyzed in the microfluidic experiment? And conversely, why were 2 filament bundles not assessed with the beads? Comparing the findings on two filament bundles with the findings on multifilament bundles would be easier for the reader if the small and large bundles were evaluated in the same experiments. If this is not experimentally feasible, the authors need to provide clearer explanation as to why this analysis is not included.
4. The authors indicate that at increased fascin concentration (1uM) that single filaments decrease the nucleation rate of cofilin clusters. The authors should comment on the mechanism for fascin (at 1uM concentration) for affecting cofilin binding.
5. The authors should determine and include the dissociation rate for the labeled cofilin used in this study, especially given the proposed mechanism for cofilin excluding fascin within the bundles.
6. For Figure 4, D and E, what do the dynamics of fascin and cofilin signal look like on a larger filament bundle? It would be informative to provide the cofilin cluster nucleation rate on larger filament bundles with a range of fascin concentrations (as in 3D for a two filament bundle).
7. Additionally, it would be useful to report the cofilin severing rate at a range of cofilin concentrations, at least for the 2 filament bundles. When the severing occurs in the two filament bundles, does this severing occur mostly at boundaries with cofilin-actin and bare actin or does this severing occur at cofilin-actin/fascin-actin boundaries?
8. For the images of large bundles appearing braided in figure 6A, the lower left panel the braided appearance is not obvious. Additionally, what is the number of filaments in the bundles shown? Finally, given that in Figure 3F it is indicated that cofilin cluster nucleation events are rare on large bundles, and the cluster growth rate is reduced on large bundles (Figure 4C), the authors need to indicate how frequently this braided appearance is observed as well as what the nucleation rate, growth rate and severing rate is for 500nM cofilin on bundles.
9. The authors indicate that the rapid fragmentation of twist constrained 2-filament bundles prevented them from directly quantifying the nucleation rate of the subsequent cofilin clusters that overlapped the initial ones. I'm unclear why this is the case, and if this is the case, I don't understand how the authors can be sure that a second nucleation event occurred in the twist constrained bundles. From the experimental data in 7C, it appears that the fragmentation rate for two filament bundles is similar to the fragmentation rate for twist constrained single filaments. The authors need to clearly state what they were able to observe and quantify as well as include the timing for this severing. If the authors could not observe a second nucleation event prior to severing, this should be clearly stated. This could be due to the rapid fragmentation, but it could also be due to severing occurring in the absence of a second cofilin nucleation event. It would be informative to compare the time from cofilin nucleation to severing event for two filament bundles in twist constrained and unconstrained. Clarification of the dynamics of nucleation and spreading of cofilin and the timing of fragmentation of the twist constrained filament bundles is needed.
10. Discussion of how twist constrained fragmentation dynamics might affect the dynamics of larger bundles in structures such as filopodia would be useful.

Minor changes that would improve the paper:

1. In Figure 1C, Figure 2B and Figure 2E, the indication, on the graph, of the fold-change between the rates is confusing as it is not clear from the labeling on the graph that the x15 is referring to the slope of the lines, keeping this information in the legend is appropriate, but if it is to be included on the graph, perhaps adding in the linear fit on the graph is also needed.
2. Figure 7A, lining up the diagram with the kymographs below would help improve interpretation of the diagram and simulation. Alternatively, if the diagram (upper) in A does not diagram the kymographs below, this needs to be clearly stated, and it would be preferable that the diagram above matches the kymographs below.
3. Despite referencing the Breitsprecher, 2011 paper in the introduction, the authors do not explain how their results showing that cofilin fragments filament bundles slower than single actin filaments correspond with the Breitsprecher findings that fascin bundles favors cofilin filament severing. While the authors do not need to explain the Breitsprecher data, if they reference these findings that run counter to their results, an explanation for the discrepancy would be reasonable to include in the discussion.

Significance

The research presented in "Fascin-induced bundling protects actin filament from disassembly by cofilin" is relevant and of interest to the field as it directly addresses a limitation in our understanding of how cofilin-induced severing occurs in F-actin bundles. Bundled F-actin may constitute the majority of linear F-actin within the cell and is specifically important in F-actin-based structures such as filopodia and stress-fibers. The data supports a model for interfilament cooperativity that provides a molecular mechanism for cofilin-mediated severing of fascin-bundled filaments.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In this study, Chikireddy et al. perform a series of experiments in which they compare the efficiency fo cofilin-mediated severing and actin filament disassembly on individual filaments versus bundles of different sizes from by the actin-bundling protein fascin. The key outcome, quite distinct from previously published conclusions by the authors themselves and other authors, is that fascin bundling actually reduces cofilin-mediated severing mostly because of much slower "nucleation" of cofilin clusters on fascin-bound filament bundles. Cofilin cluster formation is followed by local fascin removal, and the nucleation of a cofilin cluster on an adjacent bundle in the absence of fascin is strongly enhanced. The reason for the latter surprising observation is not entirely clear, but proposed to arise from cofilin-mediated changes in filament helicity of neighboring filaments. To my understanding, the main reason why fascin protects from cofilin severing here rather than enhancing it (as reported previously) is due to the lack of constraining of the induced, cofilin-mediated twist, because if this twist is constrained e.g. by anchoring of the bundles to the surface chamber, then severing by cofilin is accelerated.

Major comments:

I think the study is very well done, most experiments are super-elegant and controlled; I really don't have any objections against the conclusions drawn, as most of what I have seen is totally justified and reasonable. So from a scientific point of view, I can easily agree with all the major conclusions drawn, and so in my view, this should be published fast.

Minor comments:

There are two minor points that could be addressed:

1. I am not entirely convinced by the conclusions drawn from the EM images shown in Figure 6A, and in particular by the filaments in two-filament bundles locally twisting around each other (without breaking) at spatial sites lacking fascin and decorated by cofilin. This is hard to imagine for me, and the evidence for something like this happening is not very strong, as in the EM, only larger bundles could be observed. In addition, I am not sure that the braiding of filaments seen in the presence of cofilin is really occurring just locally on cofilin-decorated bundle segments and thus indeed coincides with loss of fascin as proposed in the scheme in Fig. 6B. Can the authors exclude that the braiding is not caused by some experimental artefact, as induced perhaps by sample preparation for negative staining? Did the authors quantify the occurrence of such braided bundle segments with and without cofilin? How large are these braided segments on average when you quantify them? Would you also see them if you prepared the bundles for an alternative EM-technique, such as Cryo-EM, for instance? This may admittedly all be experimentally challenging, but would it be possible to combine the negative staining of filaments with staining for cofilin and/or fascin using immunogold technology, to prove that the braided segments do indeed correlate with high cofilin and low fascin concentrations? In the absence of such data, and in particular in the absence of a clear quantification, the proposal is too strong in my view. Finally, it would be nice (albeit not essential I guess) to also look at two-filament bundles. The authors stated these can not be easily generated due to the tendency of fascin to promote the formation of larger bundles, but can this not be titrated/tuned somehow by lowering fascin concentrations, to come closer in reality to what is proposed to occur in the scheme in Figure 6B? In any case, the way the data are presented right now appears to constitute a pretty large gap between experimental evidence and theoretical model.
2. I think that the proposal of cofilin-decorated filaments to "transfer" the resulting cofilin-induced changes in filament helicity onto neighboring filaments in the bundle, which is proposed to occur locally and in the absence of fascin is a bit vague, and difficult to understand mechanistically. Can the authors speculate, at least, how they think this would occur? Are there no alternative possibilities for explaining obtained results? Maybe I am missing something here, but with considering cofilin to be monomeric and only harboring one actin-binding site, this proposal of helicity transfer onto neighboring filaments seems inconclusive.

Significance

General assessment:

The strength of this study is that owing, at least in part, to the microfluidics devices employed and the careful biochemistry, the experimental setups are super-controlled and clean, and they are used in a highly innovative and elegant fashion. The simulations are also nice! A limitation is that it is not entirely clear how precisely the main observations can be translated to what's happening in vivo. The results are largely dependent on the bundles not being constrained I understand, so to what extent would bundles be unconstrained in vivo? Perhaps this is not so important, because the experimental setup allows the authors to dissect specific biochemical behaviors and inter-dependencies between distinct actin binding proteins, but the latter view (if correct) could be stated more clearly!

Advance:

As stated above, the results are opposite to the proposed synergistic activities of fascin and cofilin observed for bundles previously, perhaps because they were not constrained. So although touched in part and in a very polite fashion in the discussion, the authors could specify more clearly what the differences between the studies are, and which of the distinct activities observed either here or in previous literature will be dominant or more relevant to consider in the future? This will be hard to discern as is now, in particular for non-experts.

Audience:

This manuscript will be most influential for a specialized audience interested in the complexities of biochemical activities of specific actin binding proteins when looking at them in combination. Although specialized, this is still a quite relevant audience though, since prominent actin binding proteins like cofilin are highly important in virtually any cell type and various actin structures, hence of broad relevance again in this respect.

Expertise:

I am a cell biologist and geneticist interested in actin dynamics and actin-based, motile processes.

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Referee #1

Evidence, reproducibility and clarity

In this study, it is shown that cofilin severs actin filaments slowly when fascin is present. Authors show that this is due to slower cluster nucleation of cofilin on fascin-induced actin bundles. Interestingly, the authors show that cofilin binding promotes helicity in actin filament bundles which in turn promotes facin exclusion and more cofilin clustering in adjacent filament bundles; thus, inducing local transmission of structural changes.

The authors use an elegant approach, and the data is nicely presented. Overall, I consider that this manuscript is in good shape to be published. It might benefit from language editing, though.

Significance

According to me the significance of this manuscript is that elegantly shows the molecular details of the cofilin severing effect of fascin-induced actin filament bundles. The authors show that cofilin binding promotes helicity in actin filament bundles which in turn promotes facin exclusion and more cofilin clustering in adjacent filament bundles; thus, inducing local transmission of structural changes.

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Reply to the reviewers

ReviewCommons Reviews Point-by-Point

Manuscript number: RC-2023-02131

Corresponding author(s): Holger, Gerhardt

Reviewer #1

Evidence, reproducibility and clarity

Summary: Giese et al. use genetic lineage tracing techniques and novel computational analysis methods to quantify and predict how the spatial distribution of ECs changes over time in the developing mouse retina from P5 to P9. They also develop mathematical models to describe and predict the response of ECs to the hypothesized dual force-field formed by the chemoattractant VEGFA, and the flow-induced shear stress.

Given that the mouse retina cannot be live imaged, these new methods are essential to infer cell dynamics from static images. With these methods the authors confirm previous findings that arteries are formed by endothelial cells derived from veins, or tip cells, or capillaries. They then combine their genetic system with Cdc42 and Rac1 floxed alleles to understand the function of these genes in EC mobilization. They find that Cdc42 has a very strong role in EC mobilization to arteries, not so much to the sprouting front, whereas the loss of Rac1 has relatively minor effects in vivo. Loss of Rac1 slows the cells but they maintain their directionality towards arteries. The discussion section and integration of these paper findings with previous work in the field is excellent.

Overall, this work provides a much higher level of quantitative analysis of endothelial cell dynamics in the developing vasculature of the mouse retina. It also provides mathematical models that can be useful to explain and predict the impact of other genetic mutations or pharmacological interventions during vascular development.

Reviewer #1, Major comment 1: This work provides one of the finest examples of quantitative biology in the vascular biology field. The conclusion on cell dynamics is however largely based on static images measurements and pre-defined mathematical models given also previous work and the proposed model of a dual-force field. The authors conclude that sprouting front cells mainly migrate away towards VEGF, whereas remodelling plexus cells migrate towards arteries. However, this is based on the entire EC population measurements/displacement and averaging, and does not account for the possibility of a few ECs having a different behaviour from most of their neighbours. This comment is related with the fact that arteries are formed mainly by tip-derived ECs, the cells closest to the VEGF source and further away from the flow/shear stress force. It seems the authors model presented here would not allow this to happen. According to the model presented, it seems that an EC close to the VEGF source, and subjected to low flow (shear stress), would always migrate to the front and never turn back towards arteries. Can a more complex model enable the consideration of the stochastic loss of VEGF signalling (or gain of shear stress sensing) by some ECs at the sprouting front ? And their subsequent formation of arteries ?

Response: We would like to thank the reviewer for these insightful views and for raising these questions. The aim of the computational model is to provide the simplest possible model that can be used to obtain estimates of EC migration patterns. This computational model can be used to introduce other aspects of endothelial cell behaviour, including proliferation and subpopulations with different migration sensitivities. However, the stochastic loss of VEGF signalling or gain of shear stress sensing is modelled by a stochastic term. For example, the coupling strength for control is 0.36, meaning that 0.36 is explained by directed migration along the force field, while the remaining 0.64 of the movement is stochastic. We agree that this could also be modelled differently to disentangle this stochastic term if more data on subpopulations were given. This will certainly be a fruitful direction for future research. As we do not have explicit proliferation data or data on subpopulations, direct inclusion of these extensions is difficult to validate and justify, or must be based on further assumptions or speculation.

We agree with the reviewer that there are likely distinct subpopulations, given also that ECs can compensate for higher sensitivity to shear stress or VEGF-A with higher migration speed (see Figure 2 F). Currently, the shear stress cue is overwritten by the VEGF-A cue in the sprouting front. Furthermore, both cues cancel each other out in the transition region from remodelling plexus to sprouting front, this was also suggested in (Barbacena et al., 2022) though this behaviour can be explained by heterogeneity or ECs being randomly polarised due to conflicting cues, which is not directly resolved by the data.

Nevertheless, random migration is a very inefficient strategy as shown in our theoretical investigation. Therefore, at the system level, it seems to be a much more efficient strategy to have EC subpopulations, since in this case ECs would migrate directly along one of the cues, rather than behaving randomly due to conflicting cues. We will add these considerations to the discussion of the mathematical model.

*Reviewer #1, Major comment 2: Previous work by Laviña et al showed that Cdc42 is required for the migration of ECs to the sprouting front. The authors' data suggest that Cdc42 is not necessary for this process. *

__Response: __We thank the reviewer for highlighting these points. We report a significant phenotype for Cdc42 depleted cells in the sprouting front: There is a significant shift of labelled cells from arterial to venous direction from P5 to P9 and in particular from P8 to P9. Therefore, the region of the sprouting front above the artery lacks Cdc42-depleted ECs, which can be clearly seen in the KDE plots in Figure 3.

A very important difference in our study is the definition of the sprouting front. In our study, the sprouting front is a whole region that extends to the tip of the vein, see Figure 2 and explanation on page 7: “Additionally, each retina was divided into a remodelled region containing mature veins and arteries (in the following called remodelling plexus) and a region lacking mature vessels (called sprouting front)”. However, in Lavina et al., as well as in some other studies, for example Barbacena et al., the sprouting front is the very end of the retinal vasculature. In Barbacena et al. the sprouting front is VEGFA dependent on the 100-200 μm from the very edge of the vasculature, whereas our region of interest extends much further for about 500 μm and we may lose definition for a tip cell related Cdc42 phenotype in our analysis. Our KDE plots extending from 0 (optic nerve) to 2000 μm (end of the vasculature) show a clear sprouting front Cdc42 phenotype, indicating that there is an accumulation of Cdc42 KO ECs at the end of the veins. However, these plots lose definition in the region analysed in Lavina et al. and Barbacena et al. Therefore, we will extend our analysis and explicitly report cell number proportions in the sprouting front that are compatible with (Lavina et al., 2018) and (Barbacena et al., 2022).

We will add a quantification of EC proportions in the sprouting front to make our study more comparable.

*Reviewer #1, Major comment 2 (continued): Could the difference between previous and the authors results be technical and related with the different stage of induction/analysis or the extent of Cdc42 deletion ? Did the authors tried inducing at P1 and collecting at P6/P7 ? *

Response: Lavina et al. used earlier induction time points at P0, P1 and P2. We do not know whether a retina at P5 requires less Cdc42 for sprouting front development. At this time point (P5), there is a distinct vasculature of veins, arteries forming a vascular plexus, and a sprouting front in contrast to P1, which is mainly a small vascular plexus. We will add these important points to the discussion of our manuscript.

In order to understand the role Cdc42 and Rac1 play in sprouting angiogenesis and migration to the sprouting front that is not influenced by different Cre lines and induction regimen, we will co-culture control and Cdc42/Rac1-deficient HUVECs in 3D microfluidic devices and analyse their sprouting over a number of days . With this assay we will be able to quantify the proportion of siCdc42/siRAC1 cells in tip and stalk positions compared to control, as well as do junctional and cytoskeletal analysis via immunofluorescent staining. See preliminary data in Additional Fig. 1 .

Reviewer #1, Major comment 2 (continued): The reporters used were also different and they may have different sensitivities to tamoxifen (and hence report Cdc42 deletion differently).

__Response: __This is correct as different Cre reporters have been shown to exhibit different sensitivities to recombine, including some with tamoxifen independent activity. The mTmG reporter we used however has been shown to reliably report tamoxifen induced recombination. Nevertheless, given that the reporter allele and the floxed gene alleles can recombine independent from each other, we cannot exclude the possibility that some GFP expressing cells still express Cdc42 or Rac1, or that some cells that have lost expression of Cdc42 or Rac1 due to recombination remain GFP negative. Statistically, these will however be rare events. The fact that we track all GFP positive cells allows us to draw conclusions on population behaviour, but not necessarily on the validity of any specific cell. The power of our analysis lies in the ability to draw conclusions on many randomly labelled populations across multiple time points without the necessity to validate each individual cell. The fact that the GFP population that carries floxed alleles for Cdc42 or Rac1 behave differently from those that do not provides strong evidence for successful loss of function for most of the cells. Importantly, unlike conventional full KO, this altered population behaviour occurs in the absence of an overt overall tissue phenotype, as we only lose gene function in a subpopulation of endothelial cells. The fact that we observe distinct deficiencies for migration towards the artery but not towards the sprouting front is therefore likely a true reflection of distinct functional importance and not evidence for a technical problem. Orthogonal evidence for such a selective role stems further from our in vitro cell culture experiments.

In the revised manuscript, we will include new mosaic flow-migration microfluidic studies as well as the mosaic vessel-on-chip assays mentioned above to independently verify the selective role for Cdc42 in flow-migration coupling versus sprouting (Additional Fig. 1).

Reviewer #1, Major comment 3: In the last section, some of the junctional/polarity/actin markers and analysis done in vitro could be also done in vivo.

Response: We agree with the reviewer that these experiments could be very informative to investigate junctional, polarity and actin markers. However, we believe that without a specific question these experiments would be rather explorative, do not add significant information to the current message of the study and can therefore not justify further animal experiments. This should in our opinion be the subject of future work.

We will however, quantify junctional markers in a sprouting 3D assay, see response to Reviewer #1, Major comment 2.

Reviewer #1, Major comment 4: The extent of Rac1 deletion in the mosaic experiments (done with suboptimal doses of

tamoxifen) could be analysed. This is especially relevant since minor effects for Rac1 were observed in these in vivo experiments.

Response: Lavina et al. used earlier induction time points at P0, P1 and P2. We do not know whether a retina at P5 requires less Cdc42 for sprouting front development. At this time point (P5), there is a distinct vasculature of veins, arteries forming a vascular plexus, and a sprouting front in contrast to P1, which is mainly a small vascular plexus. We will add these important points to the discussion of our manuscript.

In order to understand the role Cdc42 and Rac1 play in sprouting angiogenesis and migration to the sprouting front that is not influenced by different Cre lines and induction regimen, we will co-culture control and Cdc42/Rac1-deficient HUVECs in 3D microfluidic devices and analyse their sprouting over a number of days . With this assay we will be able to quantify the proportion of siCdc42/siRAC1 cells in tip and stalk positions compared to control, as well as do junctional and cytoskeletal analysis via immunofluorescent staining. See preliminary data in Additional Fig. 1 .

Reviewer #1, Minor comment 1: Lee et al., 2022 is a review. Better cite the original papers if possible: Some examples: Xu et al., 2014, Pitulescu et al 2017 and Lee et al., 2021.

Response: We would like to thank the reviewer for this suggestion and have added the citations to original publications where appropriate (see page 2 in the “Introduction” section).

Reviewer #1, Minor comment 2: Figure 1A: Stage of induction with tamoxifen is missing. Likely P5.

Response: We added this information to the caption of Figure 1A, Figure 3A and Figure 4A.

Reviewer #1, Minor comment 3: Figure 3 and 4 data would be easier to compare/understand by readers if part of the Wt data in Figure 1 was also plotted here. Or at least a Wt trend/average line on top of the mutant data, for us to see how much Cdc42 or Rac1 deletion changes the behaviour of the mutant cells versus the Wt cells.

Response: We agree with this suggestion and will add the wild type data for comparison in Figure 3 and 4.

Reviewer #1, Minor comment 4: Overall, for all dot plots and heatmaps, would be better to indicate the total number of cells analysed/plotted since the power of the analysis is related with cell number rather than number of retinas.

Response: We would like to thank the reviewer for this comment and agree that indicating the number of cells analysed allows the reader to contextualise the results more easily. We will therefore add estimated numbers of cells analysed to the respective figures. However, it is important to note that we used labelled pixels (GFP and ERG positive) as a proxy for the EC distribution, but did not segment out single cells. We always used the same number of 10,000 randomly selected pixels by bootstrapping to quantify the endothelial cell distributions. The heat map plots summarise the single cell behaviour pooled together for all retina samples. Therefore, each retina contributed equally to the analysis. This way, we could provide statistics on independent biological replicated samples for a thorough analysis.

Significance

General assessment: This paper is very strong on the quantitative analysis and mathematical modelling. Methods used and the model proposed may be of broad relevance for the field of vascular biology. It is however based on certain author-defined parameters and assumptions. EC dynamics in vivo can be much more complex than what can be modelled by equations. For example, heterogenous single cell genetics and signalling inputs can induce changes in cells that override the normal/average behaviour of the cells that are modelled. Despite the high level of quantitative analysis and modelling, the main findings here presented are not entirely novel, given previous work. For example, it was previously known that arteries are formed by vein/tip/capillary cells. It was also known that Cdc42 was required for proper EC migration away from veins (Laviña et al., 2018). However, the better quantitative analysis here presented does provide a higher level of detail and reliability.

The mosaic genetics used to delete Cdc42 is in general clear since few reporter positive cells can make arteries, suggesting efficient deletion of this gene. The data also goes in line with previous work. However for Rac1, given that a much weaker phenotype was observed, is not possible to be sure that all GFP+ ECs had deletion of Rac1. This is especially important in mosaic genetic experiments, using a suboptimal dose of tamoxifen. The extent of Rac1 deletion in GFP+ cells was not analysed. Which leaves the open question if Rac1 is really dispensable for EC migration and arterialization. Embryos lacking Rac1 in endothelial cells die early during development. Therefore ECs fully lacking Rac1 may have stronger defects than the ones shown here. All this data was obtained in the postnatal retina angiogenesis system. Other organ vessels may develop differently. Future work will tell if the models proposed can explain the dynamics of ECs during the growth of other vascular beds.

*Audience: Vascular/Cell biology researchers and bioinformaticians developing tools for image analysis and/or cell migration/dynamics modelling. *

Expertise of Reviewer: Vascular Biology. I do not have sufficient expertise to evaluate the mathematical modelling part of this paper.

Reviewer #2

Evidence, reproducibility and clarity

Summary: Giese et al., develop a computational model to track the migration of tip and venous endothelial cells (ECs) into developing arteries in the mouse retina. They validate prior studies which have identified important roles of shear stress and VEGFA gradient in driving EC migration and argue through their model that these dual forces shift in their relative influence along the vein-artery axis. Through in vivo lineage tracing in combination with Cre-inducible mouse knockout models, Giese et al., explore the role of Cdc42 and Rac1 in flow-migration coupling. They conclude that Cdc42, and not Rac1, is the primary driver of polarized flow-migration, further confirming this result with in vitro flow experiments involving siRNA depletion of Cdc42. Finally, the authors show that Cdc42 also plays a role in EC migration independent of flow, highlighting that its role in migration is universal and directly related to both actin regulation and cell junction dynamics.

Reviewer #2, Major comment 1: In Figure 1 the authors show retinas from a Vegfr3CreERT2 mouse model and make the claim that Vegfr3 is expressed in ECs in developing veins and tip cells, but not in arteries. Ralf Adam's group has previously shown that while Vegfr3 is more abundant in veins and capillaries than in arteries, expression is not exclusive to these EC subtypes (Ehling 2013). They, along with studies from Christer Betsholtz and Kari Alitalo's groups, show that Vegfr3 is observed in postnatal arteries (Tammela 2008, Ehling 2013). Indeed, from the panels in figure 1 (specifically P6 and P7) and supplemental figure 1, it appears that there may also be low levels of Vegfr3 expression in the arterial branches of postnatal Vegfr3CreERT2 mouse retinas. The authors should consider revising their statement that "ECs in arteries, however, do not express Vegfr3" and provide quantification of the number of GFP-labeled cells in arteries, veins and capillaries for each postnatal time point. Additional lineage tracing from later stages when migration into arteries is halted would be a good control for demonstrating that Vegfr3CreERT2 is not expressed in arteries, further support the authors' argument and conclusions.

Response: We would like to thank the reviewer for this comment. The percentage of labelled ECs in arteries of retinas for mice injected at P5 and collection at P6 is close to zero in all conditions (0.38 % +- 0.08 % (SEM) for control, 0.35 % +- 0.05 % (SEM) for Cdc42 depleted and 0.36 % +- 0.07% (SEM) for Rac1 depleted ECs). The same is true for mice injected at P8 and collected at P9 (0.22 % +- 0.06 % (SEM) for control, 0.11 % +- 0.03 % (SEM) for Cdc42 depleted and 0.11 % +- 0.01 % (SEM) for Rac1 depleted ECs).

As suggested by the reviewer, we will therefore revise the statement "ECs in arteries, however, do not express Vegfr3" and instead present the exact numbers in the revised manuscript, as this claim cannot be rejected or supported by our data. We will also add a discussion with references to (Tammela et al. 2008, Ehling et al. 2013) in our revised manuscript.

We would like to point out that this does not change the results of our study, since for us the Cre line is primarily a tool to label ECs of venous and microvascular origin to follow the change in EC distributions over time, and any pan endothelial Cre line would be suitable for our analysis. This was demonstrated for example in (Jin et al. 2022), where ECs with Cdh5Cre-induced expression of iSureCre+ MbTomato were used.

In addition, we will provide percentages as well as total cell numbers for labelled ECs in veins, arteries and capillaries in the revision of our manuscript for all time points and conditions.

Reviewer #2, Major comment 2: In their computational simulations, the authors investigate three models: random walking of ECs (M1), VEGFA gradient driven migration (M2), and integrated VEGFA /shear-stress driven migration (M3). The reader naturally wonders why a model considering only shear-stress driven migration is not presented as a control simulation. The absence of this model reduces the strength of the claims that only the M3 model captures observed EC movement rates, the mean population shift in vein-artery distance, and the arterial proportion of ECs.

__Response: __We agree with the reviewer and will certainly add a simulation of a shear stress only model and introduce it as model M4 in the revised manuscript.

Reviewer #2, Major comment 3: Much of the terminology in this study needs more detailed explanation and carefully usage. It would be more friendly to readers if they were consolidated into a box figure or table. (For example, how is coupling strength related or different from coupling rate?) The reported numbers of these factors are noted separately in text here and there. It would be helpful to put them together to highlight the difference between different models and mutant strains, as this is one of the novel findings for this study.

Response: Thank you for pointing this out. The word 'coupling rate' was incorrectly used in the introduction on page 3. It has been replaced by 'coupling strength', which is used throughout the text. We will add a table with quantitative information and explanations of parameters.

Reviewer #2, Major comment 4: The lack of labelled cells in the P9 retinas of Cdc42iECKO mice is striking (Figure 3), and strong evidence for the importance of Cdc42 in the migration of ECs towards arteries. The authors cite Lavina et al, 2018 when they note that Cdc42 depleted ECs proliferate at normal rates, but independent verification of this observation through EdU quantification would allow the authors to distinguish between the two possibilities outlined on page 15 of the manuscript: local proliferation vs enhanced migration of non-recombined ECs. These experiments and analyses are expected to be quick (depending on the availability of mice) and low cost. An independent EC proliferation analysis would also give the authors insight into the degree to which localized proliferation likely impacts vein-artery migration, a parameter which is currently unaccounted for in their computational model. The authors recognize that the lack of EC proliferation parameters is a limitation of their current model and speculate that this makes their estimates of vein to artery migration slightly too low. Independent EC proliferation analysis would thus be informative and may allow the authors to remove this speculation from their discussion.

__Response: __We do not see any reduction in the labelled Cdc42 population (Supplementary Figure 2) at P9. for all conditions we observe an increase of the labelled population from earlier to later stages (P6, P7, P8, P9). Our analysis is robust with respect to EC number, meaning that changes in EC number does not change the distribution. Our computational model would only slightly be affected by the difference in proliferation between arterial and venous beds, but not by the total number of proliferation events.

It is known from the literature that endothelial activation by shear stress is associated with inhibition of EC proliferation (Dejana et al. 2004; Bogorad et al. 2015). We used immunostaining to label phospho-histone H3 (pHH3) in perfused monolayers after 12 hours of flow exposure to uncover the effects that downregulation of Rho GTPases might have on the proliferation of ECs after exposure to flow. The biomarker pHH3 is a well-established standard for detecting the late G2 phase of mitosis. As shown in Additional Fig. 5, and in agreement with the literature, proliferation of ECs under flow conditions decreased by 27.38% compared to control static conditions. Following Rho GTPase depletion, siCdc42 cells further decreased their proliferation by 22.48% compared to control flow conditions, respectively. No significant difference was observed in siRac1 cells. It has been shown that the absence of Cdc42 increases EC apoptosis both in vivo and in vitro (Barry et al. 2015; Jin et al., 2013), but the role of Cdc42 in endothelial proliferation remains unclear in the literature. The data presented here suggest that Cdc42 has a modest effect on endothelial proliferation under flow in vitro. As shown in Additional Fig. 5, none of the loss-of-function conditions appeared to drastically alter the effect of flow on reducing proliferation in confluent monolayers. This suggests that RhoGTPases may not play a major role in the regulation of proliferation under the influence of flow.

We do not expect any further insight from EdU staining since also with EdU staining we could only quantify ECs entering the S phase in static images and how this translates into proliferation would still introduce further speculation. We therefore addressed this question in our discussion, as a quantification of proliferation would go beyond the scope of this study.

Of note, any requests for additional in vivo experiments would require new animal licence application and therefore a considerable time delay which we would only suggest to accept if substantial additional insight was to be expected. As it stands, all our claims are supported by several independent observations and can where necessary and as detailed in our revision plan, be addressed by orthogonal means.

Reviewer #2, Major comment 5: In the legends of Figure 1B & C, no information about the x or y-axis were mentioned. Even though the authors explained it elsewhere in the text or other figures, it is the first time that these parameters show up in the paper, which would be a proper place to note the details of these KDE plots.

Response: We added this information in the caption of Figure 1B,C, Figure 3B,C, and Figure 4B,C.

Reviewer #2, Major comment 6: In the legends of Figure 2B & C, it mentioned the results of coupling strength and fraction of shear stress, which was not obvious by just looking at the figures provided. It is also not mentioned whether the numbers are calculated by collected or predicted data.

__Response: __We agree with the reviewer that this information should be more prominent in the figure and will add it accordingly. These are predicted data, where we systematically tested different values of key parameters. We will therefore also change the caption of the figure from “Simulation of EC migration in the retinal vasculature” to “Prediction of EC distributions from computational model simulations” to make this clear.

Reviewer #2, Major comment 7: Please direct the reader to the supplemental figure containing the tamoxifen injection strategy when the Vegfr3CreERT2 mouse model is introduced in the text and when Cdc42 and Rac1 EC knockout is discussed in the methods.

__Response: __We also moved Supplementary Figure 1 and 2 to the beginning of the supplement as they are now referenced first in the main text and hope this will erase the confusion.

Reviewer #2, Major comment 8: There appears to be a significant degree of variance in the KDE plots from Figures 1, 3, and 4. It would therefore be helpful if the authors could include plots of the remodeling plexus and sprouting front that show the median for each dataset (similar to Figure 1 D and E), since this is less likely to be skewed by extrema. Additionally, for clarity and ease to read, it would be nice if author can consolidate the results of the mean from WT, Cdc42 and Rac 1 iECKO side by side. The images of the retina are striking, but the quantification is not as well-communicated.

Response: We plotted the median (including 10th and 90th percentile) already in Figure 1 Supplement 1, Figure 3 Supplement 1 and Figure 4 Supplement 1 and found significant

Reviewer #2, Major comment 8 (continued): If the argument is that Cdc42 only disrupts the migration, but not the differentiation, of artery EC, the authors should see a significant difference between WT and Cdc42 iECKO only in P9, but not early stages.

Response: We are not sure that we have fully understood the reviewer's reasoning, but our data confirm the reviewer's prediction of disrupted Cdc42 KO EC migration: The timeline for the percentage of labelled arterial ECs relative to the total labelled EC population is shown in Additional Fig. 2. Here, a significant increase was observed for both control and Rac1 iECKO ECs between time points P8 and P9, but not at earlier stages. For Cdc42 iECKO no significant increase was found at all stages. A direct comparison of all conditions is shown in Additional Fig. 3. Similarly, the proportion of Cdc42 iECKO compared to control is significantly different at P9 for mice injected at P5, but not at earlier stages.

Reviewer #2, Minor comment 1: For KDE plots in Figure 1B and Figure 3B, the authors labeled the x-axis differently (r vs dr). No description about the x-axis is noted in the legends. Please consider keeping the label consistent so the readers can relate and compare them.

Response: Thank you for spotting this mislabelling. We changed the axis annotation to d_r in Figure 1 as it is used in Figure 3,4 and throughout the text. We added furthermore information on the x and y axis in the caption of Figure 1B,C, Figure 3B,C, and Figure 4B,C. See also major comment 5.

Reviewer #2, Minor comment 2: For the in vitro study, the cell line used is not mentioned in the results, even though there is a method section about HUVEC. Authors should note this information in the main text.

Response: We agree with the reviewer and have added the following information in the main text on page 18 in the section “Cdc42, but not Rac1, drives polarised flow-migration in vitro” stating:

“To assess EC migration under coupling to shear forces in vitro, siScrambled (siScr) control, siCdc42 and siRac1 treated human umbilical venous endothelial cell (HUVEC) monolayers were exposed to 20 dynes/cm2 of flow using the Ibidi perfusion system and observed for up to 17 hours using a non-toxic fluorescent DNA dye for nuclear tracking.”

*Reviewer #2, Minor comment 3: Please note the flow direction in Figure 5B. *

__Response: __We have added an additional indication of flow direction for Figure 5B to improve the clarity of the figure. Note that the direction of flow is already indicated in Figure 5A and is the same throughout the figure.

Reviewer #2, Minor comment 4: The naming of supplemental figures requires revisiting. Currently there are two figures labeled with variations of supplementary Figure 1, which makes identifying the correct data challenging.

Response: We regret that the reviewer found the labelling of supplementary figures ambiguous and thank the reviewer for spotting this mislabelling. We corrected the label Figure S1 to Supplementary Figure 1. Furthermore, we also moved Supplementary Figure 1 and 2 to the beginning of the supplement as they are now referenced first in the main text and hope this will erase the confusion (also see Reviewer #2, major comment 7).

Reviewer #2, Minor comment 5: There appears to be a small typo on page 16 in second paragraph in the sentence that currently reads "Nevertheless, only few cells reached the arteries by P9"

Response: We changed this sentence: “Nevertheless, the accumulation of Rac1-deficient ECs in the artery was less pronounced compared to control.” Also we provide actual numbers, see Additional Fig. 2 and Additional Fig. 3 and our response to Reviewer #1, Major comment 4.

Reviewer #2, Minor comment 6: The axis labels for the plots in Figure 5, Figure 2 Supplement 1, and Supplementary Figure 2 are currently very tiny and difficult to read.

Response: We agree with this suggestion and will increase the size of the axis labels.

Reviewer #2, Minor comment 7: Additional information is required to describe the trajectory plots in Figure 2 Supplement 1, Figure 3 Supplement 3 and Figure 4 Supplement 3. I assume that blue trajectories move in the positive x direction while orange trajectories move in the negative x direction, but this is currently not specified in any of the legends.

Response: We added a specification in the figure legend.

Significance

Giese et al advance current understanding of the molecular mechanisms that guide vein to artery migration by convincingly demonstrating (both in-vivo and in-vitro) that Cdc42 is essential for this process. In addition, they present a computational model that captures the dual force field of VEGFA and shear stress gradients to simulate and quantify this migratory process in the mouse retina: a tool which will likely be useful for future mechanistic studies of vascular remodeling and EC migration. As far as I am aware, no standard coordinate system exists in the field for the quantification and modeling of this migratory process, so the introduction of this method alone serves as a useful innovation for the field of vascular biology.

It should be noted by authors and the editors that the mathematical details of the computational model and its statistical accuracies are not evaluated in this review, which instead focuses on the study's findings as they relate to EC biology and vascular development.

This study complements previous work that has identified populations of ECs that appear to be primed for incorporation into arteries, termed "pre-arteries" (Su et al 2018, Phansalkar 2021, Luo 2021). The authors' observation of heterogeneous EC movements during migration supports the intriguing suggestion that actin regulation through Cdc42 may be related to the establishment or phenotype of this pre-artery identity, though further mechanistic work will be required to validate this hypothesis, as noted by Giese et al in their thoughtful discussion.

Reviewer #3

Evidence, reproducibility and clarity

Summary: this study uses VEGFR3cre as a lineage tracking system to track venous endothelial cells within the maturing retina postpartum in order to investigate the cues related to sprouting and remodeling of the vascular network. They use complex computation modeling to predict outcome and come with in vivo/vitro observations.

They identify that venous EC move towards the arterial bed with flow and oxygen tensions as critical parameter. It is an impressive study that in principle confirms earlier studies on the role of EC population in sprouting and vascular remodeling however utilizes an interesting cell population based computational approach. Since these finding are pretty new, confirmation with different technologies and approaches is important.

However for more "traditional" vascular biologist it is very difficult to understand and follow particular if not familiar with the data presentation and mathematical modeling. This is a major shortcoming of this manuscript because I feel that if the authors would put more effort to better communicate their findings to a broader community not only enhance the value of their findings but also disseminate their computational approaches to a broader vascular scientist community.

__Response: __We thank the reviewer for this valuable critique, we will add a table where all parameters are described. Furthermore, we will add an additional subpanel in Figure 2 to explain the computational model.

I do have a couple of model related comments. The authors are using different models without adequate description.

The VEGFR3 is a lymphatic EC tracking model that potential can be used to track venous tip cells in the retina. But this model is not characterized within the retina in the study the author cite. I believe it would be necessary to characterize this model in traditional way before it can be used as described.

__Response: __We appreciate this comment and generally agree with the wish to see Cre lines well characterised. This is particularly relevant in studies where researchers delete a gene of interest using a Cre line and then make claims about the role of the gene in certain tissues with assumed recombination specificity. In our study however, we are not using the Cre line as a lymphatic or venous specific line to make such claims. Instead we use it in combination with the mTmG reporter, to quantify population distributions. Therefore every sample is its own “characterization”.

We could cite literature that support our claim of lack of arterial expression (Ehling et al., 2013, Tammela et al., 2008) of Vegfr3 in postnatal retina, but these studies did not use this Cre-line. For the purpose of our study, and in line with previous comments by referee 2, we feel it is best to moderate the claim, as very rarely single arterial cells can be found to have recombined 24 h after tamoxifen injection, see Additional Fig. 2 and Additional Fig. 3. The revised manuscript therefore has the claim toned down to better reflect this. Nevertheless, the utility of the Cre-line is not dependent on whether or not single arterial cells can be labelled, as the coordinate system and population quantification shows the population shift. This would even be valid using Cre-lines with random endothelial recombination in all vascular segments (Jin et al., 2022).

If deemed necessary, we have reporter expression from various stages of recombination in the postnatal retina, as well as in the developing brain, as well as comparison with arterial Cre-lines such a BMX cre. A rather complete characterization could be provided in supplements. However, we would argue that this is not relevant for the present study.

Distance to artery /veins is one parameter the authors are using in their modeling. I'm not sure I understand how they determine it since ECs can original form any place with the venous network, then again they might not.

__Response: __In the computational model we assume an initial distribution that is derived from the distribution at P6, which is shown in Figure 2A (middle panel). In summary, we do not hypothesise any origin of the ECs but start with the experimentally observed distribution at P6. From this starting distribution and for the following time steps we can then compute the exact distances to the closest vein and artery.

SiRNA experiment do not show knock down efficiency, which is probably also heterogenous. I'm not sure if this affects the modeling. In the last set they use HUVECs which is a very specialized "venous" ECs which I would not use for their modelsystem.

__Response: __The knockdown efficiency is shown in the supplementary data, see Figure 5 Supplementary data 2: qPCR knockdown validation. We do not use the in vitro data for the computational modelling, only the distribution in the in vivo data. Vegfr3 is expressed in endothelial tip cells and ECs in the developing vein, as well as in scattered ECs throughout the primitive vascular plexus. Therefore, despite the general limitations of in vitro systems, HUVECs are very similar to the in vivo situation shown in our study. HUVECs, despite being of venous origin, are a very versatile tool for endothelial studies. They express both venous and arterial genes, including dll4 and many components of the notch signalling cascade. Importantly, they are heterogenous, but adapt to media and flow conditions. The medium we use stimulates a microvascular growth pattern, and exposing HUVECs to flow results in transcriptional and proteomic changes that fit well with microvascular responses. Using fully differentiated arterial endothelial cells would not be useful as we are modelling endothelial responses that set in venous and microvascular regions of the vascular plexus in vivo, and stimulate a response that leads to movement towards arteries. We have therefore purposefully chosen and validated this model system.

Significance

I already commented in the above paragraph on this topics

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Referee #3

Evidence, reproducibility and clarity

Summary:

this study uses VEGFR3cre as a lineage tracking system to track venous endothelial cells within the maturing retina postpartum in order to investigate the cues related to sprouting and remodeling of the vascular network. They use complex computation modeling to predict outcome and come with in vivo/vitro observations.

They identify that venous EC move towards the arterial bed with flow and oxygen tensions as critical parameter. It is an impressive study that in principle confirms earlier studies on the role of EC population in sprouting and vascular remodeling however utilizes an interesting cell population based computational approach. Since these finding are pretty new, confirmation with different technologies and approaches is important.

However for more "traditional" vascular biologist it is very difficult to understand and follow particular if not familiar with the data presentation and mathematical modeling. This is a major shortcoming of this manuscript because I feel that if the authors would put more effort to better communicate their findings to a broader community not only enhance the value of their findings but also disseminate their computational approaches to a broader vascular scientist community. I do have a couple of model related comments. The authors are using different models without adequate description. The VEGFR3 is a lymphatic EC tracking model that potential can be used to track venous tip cells in the retina. But this model is not characterized within the retina in the study the author cite. I believe it would be necessary to characterize this model in traditional way before it can be used as described. Distance to artery /veins is one parameter the authors are using in their modeling. I'm not sure I understand how they determine it since ECs can original form any place with the venous network, then again they might not. SiRNA experiment do not show knock down efficiency, which is probably also heterogenous. I'm not sure if this affects the modeling. In the last set they use HUVECs which is a very specialized "venous" ECs which I would not use for their modelsystem

Significance

The VEGFR3 is a lymphatic EC tracking model that potential can be used to track venous tip cells in the retina. But this model is not characterized within the retina in the study the author cite. I believe it would be necessary to characterize this model in traditional way before it can be used as described.

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Referee #2

Evidence, reproducibility and clarity

Summary:

Giese et al., develop a computational model to track the migration of tip and venous endothelial cells (ECs) into developing arteries in the mouse retina. They validate prior studies which have identified important roles of shear stress and VEGFA gradient in driving EC migration and argue through their model that these dual forces shift in their relative influence along the vein-artery axis. Through in vivo lineage tracing in combination with Cre-inducible mouse knockout models, Giese et al., explore the role of Cdc42 and Rac1 in flow-migration coupling. They conclude that Cdc42, and not Rac1, is the primary driver of polarized flow-migration, further confirming this result with in vitro flow experiments involving siRNA depletion of Cdc42. Finally, the authors show that Cdc42 also plays a role in EC migration independent of flow, highlighting that its role in migration is universal and directly related to both actin regulation and cell junction dynamics.

Major Comments:

1. In Figure 1 the authors show retinas from a Vegfr3CreERT2 mouse model and make the claim that Vegfr3 is expressed in ECs in developing veins and tip cells, but not in arteries. Ralf Adam's group has previously shown that while Vegfr3 is more abundant in veins and capillaries than in arteries, expression is not exclusive to these EC subtypes (Ehling 2013). They, along with studies from Christer Betsholtz and Kari Alitalo's groups, show that Vegfr3 is observed in postnatal arteries (Tammela 2008, Ehling 2013). Indeed, from the panels in figure 1 (specifically P6 and P7) and supplemental figure 1, it appears that there may also be low levels of Vegfr3 expression in the arterial branches of postnatal Vegfr3CreERT2 mouse retinas. The authors should consider revising their statement that "ECs in arteries, however, do not express Vegfr3" and provide quantification of the number of GFP-labeled cells in arteries, veins and capillaries for each postnatal time point. Additional lineage tracing from later stages when migration into arteries is halted would be a good control for demonstrating that Vegfr3CreERT2 is not expressed in arteries, further support the authors' argument and conclusions.

2. In their computational simulations, the authors investigate three models: random walking of ECs (M1), VEGFA gradient driven migration (M2), and integrated VEGFA /shear-stress driven migration (M3). The reader naturally wonders why a model considering only shear-stress driven migration is not presented as a control simulation. The absence of this model reduces the strength of the claims that only the M3 model captures observed EC movement rates, the mean population shift in vein-artery distance, and the arterial proportion of ECs.

3. Much of the terminology in this study needs more detailed explanation and carefully usage. It would be more friendly to readers if they were consolidated into a box figure or table. (For example, how is coupling strength related or different from coupling rate?) The reported numbers of these factors are noted separately in text here and there. It would be helpful to put them together to highlight the difference between different models and mutant strains, as this is one of the novel findings for this study.

4. The lack of labelled cells in the P9 retinas of Cdc42iECKO mice is striking (Figure 3), and strong evidence for the importance of Cdc42 in the migration of ECs towards arteries. The authors cite Lavina et al, 2018 when they note that Cdc42 depleted ECs proliferate at normal rates, but independent verification of this observation through EdU quantification would allow the authors to distinguish between the two possibilities outlined on page 15 of the manuscript: local proliferation vs enhanced migration of non-recombined ECs. These experiments and analyses are expected to be quick (depending on the availability of mice) and low cost. An independent EC proliferation analysis would also give the authors insight into the degree to which localized proliferation likely impacts vein-artery migration, a parameter which is currently unaccounted for in their computational model. The authors recognize that the lack of EC proliferation parameters is a limitation of their current model and speculate that this makes their estimates of vein to artery migration slightly too low. Independent EC proliferation analysis would thus be informative and may allow the authors to remove this speculation from their discussion.

5. In the legends of Figure 1B & C, no information about the x or y-axis were mentioned. Even though the authors explained it elsewhere in the text or other figures, it is the first time that these parameters show up in the paper, which would be a proper place to note the details of these KDE plots.

6. In the legends of Figure 2B & C, it mentioned the results of coupling strength and fraction of shear stress, which was not obvious by just looking at the figures provided. It is also not mentioned whether the numbers are calculated by collected or predicted data.

7. Please direct the reader to the supplemental figure containing the tamoxifen injection strategy when the Vegfr3CreERT2 mouse model is introduced in the text and when Cdc42 and Rac1 EC knockout is discussed in the methods.

8. There appears to be a significant degree of variance in the KDE plots from Figures 1, 3, and 4. It would therefore be helpful if the authors could include plots of the remodeling plexus and sprouting front that show the median for each dataset (similar to Figure 1 D and E), since this is less likely to be skewed by extrema. Additionally, for clarity and ease to read, it would be nice if author can consolidate the results of the mean from WT, Cdc42 and Rac 1 iECKO side by side. The images of the retina are striking, but the quantification is not as well-communicated. If the argument is that Cdc42 only disrupts the migration, but not the differentiation, of artery EC, the authors should see a significant difference between WT and Cdc42 iECKO only in P9, but not early stages.

Minor Comments:

1. For KDE plots in Figure 1B and Figure 3B, the authors labeled the x-axis differently (r vs dr). No description about the x-axis is noted in the legends. Please consider keeping the label consistent so the readers can relate and compare them.

2. For the in vitro study, the cell line used is not mentioned in the results, even though there is a method section about HUVEC. Authors should note this information in the main text.

3. Please note the flow direction in Figure 5B.

4. The naming of supplemental figures requires revisiting. Currently there are two figures labeled with variations of supplementary Figure 1, which makes identifying the correct data challenging.

5. There appears to be a small typo on page 16 in second paragraph in the sentence that currently reads "Nevertheless, only few cells reached the arteries by P9"

6. The axis labels for the plots in Figure 5, Figure 2 Supplement 1, and Supplementary Figure 2 are currently very tiny and difficult to read.

7. Additional information is required to describe the trajectory plots in Figure 2 Supplement 1, Figure 3 Supplement 3 and Figure 4 Supplement 3. I assume that blue trajectories move in the positive x direction while orange trajectories move in the negative x direction, but this is currently not specified in any of the legends.

Significance

Giese et al advance current understanding of the molecular mechanisms that guide vein to artery migration by convincingly demonstrating (both in-vivo and in-vitro) that Cdc42 is essential for this process. In addition, they present a computational model that captures the dual force field of VEGFA and shear stress gradients to simulate and quantify this migratory process in the mouse retina: a tool which will likely be useful for future mechanistic studies of vascular remodeling and EC migration. As far as I am aware, no standard coordinate system exists in the field for the quantification and modeling of this migratory process, so the introduction of this method alone serves as a useful innovation for the field of vascular biology.

• It should be noted by authors and the editors that the mathematical details of the computational model and its statistical accuracies are not evaluated in this review, which instead focuses on the study's findings as they relate to EC biology and vascular development.

• This study complements previous work that has identified populations of ECs that appear to be primed for incorporation into arteries, termed "pre-arteries" (Su et al 2018, Phansalkar 2021, Luo 2021). The authors' observation of heterogeneous EC movements during migration supports the intriguing suggestion that actin regulation through Cdc42 may be related to the establishment or phenotype of this pre-artery identity, though further mechanistic work will be required to validate this hypothesis, as noted by Giese et al in their thoughtful discussion.

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Referee #1

Evidence, reproducibility and clarity

Summary:

Giese et al. use genetic lineage tracing techniques and novel computational analysis methods to quantify and predict how the spatial distribution of ECs changes over time in the developing mouse retina from P5 to P9. They also develop mathematical models to describe and predict the response of ECs to the hypothesized dual force-field formed by the chemoattractant VEGFA, and the flow-induced shear stress. Given that the mouse retina cannot be live imaged, these new methods are essential to infer cell dynamics from static images. With these methods the authors confirm previous findings that arteries are formed by endothelial cells derived from veins, or tip cells, or capillaries. They then combine their genetic system with Cdc42 and Rac1 floxed alleles to understand the function of these genes in EC mobilization. They find that Cdc42 has a very strong role in EC mobilization to arteries, not so much to the sprouting front, whereas the loss of Rac1 has relatively minor effects in vivo. Loss of Rac1 slows the cells but they maintain their directionality towards arteries. The discussion section and integration of these paper findings with previous work in the field is excellent. Overall, this work provides a much higher level of quantitative analysis of endothelial cell dynamics in the developing vasculature of the mouse retina. It also provides mathematical models that can be useful to explain and predict the impact of other genetic mutations or pharmacological interventions during vascular development.

Major comments:

1 - This work provides one of the finest examples of quantitative biology in the vascular biology field. The conclusion on cell dynamics is however largely based on static images measurements and pre-defined mathematical models given also previous work and the proposed model of a dual-force field. The authors conclude that sprouting front cells mainly migrate away towards VEGF, whereas remodelling plexus cells migrate towards arteries. However, this is based on the entire EC population measurements/displacement and averaging, and does not account for the possibility of a few ECs having a different behaviour from most of their neighbours. This comment is related with the fact that arteries are formed mainly by tip-derived ECs, the cells closest to the VEGF source and further away from the flow/shear stress force. It seems the authors model presented here would not allow this to happen. According to the model presented, it seems that an EC close to the VEGF source, and subjected to low flow (shear stress), would always migrate to the front and never turn back towards arteries. Can a more complex model enable the consideration of the stochastic loss of VEGF signalling (or gain of shear stress sensing) by some ECs at the sprouting front ? And their subsequent formation of arteries ?

2 - Previous work by Laviña et al showed that Cdc42 is required for the migration of ECs to the sprouting front. The authors data suggest that Cdc42 is not necessary for this process. Could the difference between previous and the authors results be technical and related with the different stage of induction/analysis or the extent of Cdc42 deletion ? Did the authors tried inducing at P1 and collecting at P6/P7 ? The reporters used were also different and they may have different sensitivities to tamoxifen (and hence report Cdc42 deletion differently).

3 - In the last section, some of the junctional/polarity/actin markers and analysis done in vitro could be also done in vivo.

4 - The extent of Rac1 deletion in the mosaic experiments (done with suboptimal doses of tamoxifen) could be analysed. This is especially relevant since minor effects for Rac1 were observed in these in vivo experiments.

Minor comments:

1 - Lee et al., 2022 is a review. Better cite the original papers if possible: Some examples: Xu et al., 2014, Pitulescu et al 2017 and Lee et al., 2021.

2 - Figure 1A: Stage of induction with tamoxifen is missing. Likely P5.

3 - Figure 3 and 4 data would be easier to compare/understand by readers if part of the Wt data in Figure 1 was also plotted here. Or at least a Wt trend/average line on top of the mutant data, for us to see how much Cdc42 or Rac1 deletion changes the behaviour of the mutant cells versus the Wt cells.

4 - Overall, for all dot plots and heatmaps, would be better to indicate the total number of cells analysed/plotted since the power of the analysis is related with cell number rather than number of retinas.

Significance

Significance

General assessment: This paper is very strong on the quantitative analysis and mathematical modelling. Methods used and the model proposed may be of broad relevance for the field of vascular biology. It is however based on certain author-defined parameters and assumptions. EC dynamics in vivo can be much more complex than what can be modelled by equations. For example, heterogenous single cell genetics and signalling inputs can induce changes in cells that override the normal/average behaviour of the cells that are modelled. Despite the high level of quantitative analysis and modelling, the main findings here presented are not entirely novel, given previous work. For example, it was previously known that arteries are formed by vein/tip/capillary cells. It was also known that Cdc42 was required for proper EC migration away from veins (Laviña et al., 2018). However, the better quantitative analysis here presented does provide a higher level of detail and reliability. The mosaic genetics used to delete Cdc42 is in general clear since few reporter positive cells can make arteries, suggesting efficient deletion of this gene. The data also goes in line with previous work. However for Rac1, given that a much weaker phenotype was observed, is not possible to be sure that all GFP+ ECs had deletion of Rac1. This is especially important in mosaic genetic experiments, using a suboptimal dose of tamoxifen. The extent of Rac1 deletion in GFP+ cells was not analysed. Which leaves the open question if Rac1 is really dispensable for EC migration and arterialization. Embryos lacking Rac1 in endothelial cells die early during development. Therefore ECs fully lacking Rac1 may have stronger defects than the ones shown here. All this data was obtained in the postnatal retina angiogenesis system. Other organ vessels may develop differently. Future work will tell if the models proposed can explain the dynamics of ECs during the growth of other vascular beds.

Audience: Vascular/Cell biology researchers and bioinformaticians developing tools for image analysis and/or cell migration/dynamics modelling.

Expertise of Reviewer: Vascular Biology. I do not have sufficient expertise to evaluate the mathematical modelling part of this paper.

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Reply to the reviewers

Planned Revisions based on comments from Reviewer #1

• The introductory material and the title of the paper emphasize the ring canal scaling question. This problem is somewhat obscured in the text by the side problem of nuclear scaling, which comes up frequently even though the results are not as thoroughly explored. Could the authors think about moving these data into a different, single figure for the sake of coherence? This is not a required revision. Just a thought.
• *We have moved the nuclear scaling data from Fig. 5 into Fig. S3, and once we have analyzed the data from the planned experiments (over-expressing either HtsRC or the active form of myosin), then we will have a better idea of whether we should move the rest of the nuclear scaling data out of the main part of the paper, consolidate it into a single figure (as Reviewer #1 suggests), or keep some of it in the main figures. *

Planned Revisions based on comments from Reviewer #3

• I cannot see differences in RC size in the panel A images. More importantly, this method altering ring canal size is limited. A more direct way is overexpression of HtsRC (https://doi.org/10.1534/genetics.120.303629).
• We have requested and just recently received the line to over-express HtsRC in the germline. We plan to cross this UAS line to the mataTub-GAL4 which expresses GAL4 beginning around stage 3 of oogenesis. Because crossing this UAS line with this GAL4 line produced egg chambers with larger ring canals in the original study2*, we do not anticipate any technical issues with this experiment. We will incorporate the results from analysis of these egg chambers in the revised manuscript. *

• To further explore the effect of ring canal size on scaling, we will also be testing a condition that we hope will have the opposite effect on ring canal size; expression of a phosphomimetic version of the non-muscle myosin II regulatory light chain, encoded by spaghetti squash (Sqh)(UAS-sqhE20E21). We plan to cross this UAS line to two different GAL4 drivers (nos-GAL4, which expresses GAL4 in a pulse during early oogenesis and then in another pulse in mid-oogenesis and the mataTub-GAL4 which expresses GAL4 beginning around stage 3 of oogenesis). We know that expression of sqhE20E21will reduce the size of the ring canals that connect the nurse cells to each other, but it is possible that the posterior ring canals will not show a strong phenotype. In a study that looked at egg chambers homozygous for a mutation in the myosin binding subunit of the myosin phosphatase, DMYPT, which should also increase sqh phosphorylation, it was shown that the posterior ring canals were larger than those connecting nurse cells 1*. Therefore, it is possible that this condition may not allow us to consistently reduce the size of all ring canal types; however, if we do see a significant reduction in posterior ring canal size in these egg chambers, we will include these data in the revised manuscript. *

• In panel 2E, it would be helpful to plot the y-intercepts separately, too.

• Based on the analysis of the data from the proposed experiments, we will consider plotting the y-intercepts separately for the various conditions.

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

Revisions made based on comments from Reviewer #1

• One way to think about the dhc-64C experiments presented in Figure 2 is that they are meant to test the hypothesis that ring canal size impacts scaling in such a way that transport across the four ring canals tends towards equilibrium over time. One possibility would therefore be that ring canals aren't programmed to grow to a particular final size but rather they grow at different rates until their diameters are the same. This seems to me an important distinction. It might be made by analysis of the arpC2-RNAi cells, since those ring canals are meant to be initially larger. Unfortunately, I can't see the answer.
• *Reviewer #3 suggested determining the ratio of the diameter of the M1 ring canal to the M4 ring canal. If ring canals grow toward equilibrium (to achieve a similar final size), then we would expect to see this ratio approach 1; when we performed this analysis, we saw that the ratio did decrease as the egg chambers increased in volume, but it never quite reaches a ratio of 1. We have added a supplemental figure (Fig. S1) showing these data and incorporated this idea into the text within the results and discussion sections. *
• *Although it would be informative to determine whether ring canals that all started with a similar diameter would grow at the same rate, we have not found a condition that would provide the opportunity to test this hypothesis. We hope that the planned experiments will provide us with a way to test this hypothesis; we will determine the M1/M4 ratio in egg chambers over-expressing either HtsRC or sqhE20E21 and see whether this ratio still decreases as egg chamber volume increases. *

• *Once we perform the planned experiments to either increase or decrease ring canal size, then we can determine whether we need to further modify Fig. 3 to highlight these size differences between ring canals in the arpC2-RNAi egg chambers or whether we will instead focus more on the results of the planned experiments. *

• The authors write that arpC2-RNAi "ring canals tended to be larger than those in similarly-sized control egg chambers," but that conclusion isn't obvious to me from the data in Figure 3B. The only difference I can see is that the M4 ring canals look to be consistently smaller in the experimental versus control egg chambers, especially at the final timepoint.

• *To further clarify the difference in ring canal size between the control and the arpC2-RNAi egg chambers, we have added additional explanation to the results section to highlight that the y-intercepts of the lines of best fit are significantly higher in the arpC2-RNAi egg chambers at each stage. This demonstrates that given an egg chamber volume, the ring canals will be larger in egg chambers depleted of ArpC2 than in the controls. *

• The authors write that "there was a consistent, but not significant decrease in the scaling exponents for the arpC2-RNAi egg chambers compared to controls," but I don't see this in the M1 (identical) or M2 (almost the same) ring canals. The scaling decrease is most pronounced at M4. All the other ring canals seem to reach a final size that's equivalent to controls. What does this tell us about scaling? Is the M4 more sensitive to the effect of arpC2-RNAi? I note and appreciate that the data for M4 show a wide distribution and might have been impacted by outliers, which could be discussed.

• *We have separated the arpC2-RNAI ring canal scaling data by lineage (Fig. S2), and we have color-coded the data in Fig. 3B (as suggested by Reviewer #3). *

• We have expanded the discussion of these results and their implications, and we have added a line in the results section to address this wide distribution of the M4 ring canal sizes.

• The possibility that ring canal scaling "could generate eggs of different sizes" could use some elaboration (at least) as it does not seem to be especially well supported:

• Only one of the small egg lines had lower scaling exponents than the big egg lines, and it's a struggle for me to understand the extent of that difference based on the data shown. (Is it significant?).

• *We have restructured this section of the results and modified Fig. 5 to highlight similarities and differences between the four lines. In the results section (and in the figure legend), we have stated that when we compared the slopes of the regression lines for all four lines, there was a significant difference for M1, M2, and M4 (Fig. 5C, D, and F). We have also modified the results section to highlight that although the slopes for line 9.31.4 was not different from the two big egg lines, the intercepts were significantly different for M1, M2, M3, and M4 ring canals. We moved the nuclear scaling data to Fig. S3 to simplify the figure. *

• The authors conclude that "the effect of lineage on ring canal scaling is conserved, and it suggests that at least in one line, reducing posterior ring canal scaling could provide a mechanism to produce a smaller mature egg." The first part of this sentence is confusing for me since I don't know what is meant here by "conserved." The second part of the sentence is technically correct but disguises what I would consider the more meaningful and exciting finding. The 9.31.4 line produces the smallest eggs but does not demonstrate scaling differences in comparison to the big egg lines examined (1.40.1 and 3.34.1). The authors have therefore avoided/solved a "chicken and egg" ("fruit fly and egg"?) problem by showing that scaling and egg size can be decoupled!

• We have modified the first part of the sentence to clarify our point. We appreciate this suggestion and have modified the text in the results section to further elaborate on the results.

• This point is not made very clearly in the discussion, which concludes with the suggestion that scaling could help explain why some insects produce much larger or much smaller eggs that fruit flies. I can only understand this to be the case if - as the authors point out - scaling "affect the directed transfer of materials into the oocyte." That argument seems predicated on the possibility that these insects make the same amount of initial material then regulate how much is transferred. Seems like a costly way to go about it.

• *We have modified this section of the discussion. *

• I really had to look very closely to distinguish the little blue boxes from the little blue circles in panels 2C and especially 2D. I suggest using a different color instead of a different shape, or maybe splitting the graphs up.

• *We have made the shapes larger in Fig. 2C (nuclear sizes), and we have split the ring canal size data into Fig. 2D, E and made the shapes larger. The legend has been modified to reflect this change. *

• "Depletion of the linker protein, Short stop (Shot), or dynein heavy chain (Dhc64C), significantly reduced the biased transport at the posterior, which reduced oocyte size (Lu et al., 2021)." I suggest this sentence might be clearer if it was rewritten as "Depletion of either dynein heavy chain (Dhc64C) or the linker protein Short stop (Shot) significantly reduces biased transport at the posterior, in turn reducing oocyte size (Lu et al., 2021).

• We have made this change.

• "Because nuclear growth has been shown to be tightly coupled to cell growth (Diegmiller et al., 2021), we can use nuclear size as a proxy for nurse cell size." I think it would help the reader to know that the Diegmiller study was performed using germline cysts in the Drosophila ovary; I paused when I got to this sentence because I initially read it as overly broad. I suggest "Recent work in demonstrates that nuclear growth is tightly coupled to cell growth in this system (Diegmiller et al., 2021), and we can therefore use nuclear size as a proxy for nurse cell size" or similar. This is certainly not a required revision, just a suggestion.

• We have made this change.

Planned Revisions based on comments from Reviewer #3

• Reviewer #3 asked: Does the ratio of the diameter of M1 to M4 stay the same?

• *We have performed this analysis in the control egg chambers (from Fig. 1), and we found that the ratio does not stay the same, but that it tends to decrease as the egg chamber increases in volume. We plotted the log of egg chamber volume versus this ratio, and the equation for the regression line was y = -0.166x + 2.32, which was significantly different from a slope of 0 (included in Fig. S1). *

• It would be helpful to explain that the log-log plots were used to derive a line equation (y=mx + b) and why that is useful in this context. In the case of a log-log plot, what does the y-intercept mean biologically? Is it simply a way to compare two things or does it indicate real measurements such as volume or ring canal size? Also, the slope of the line is being used as a scaling value. Be careful to define the terms "scaling" and "scaling exponent".

• We have added additional explanation in the results section.

• Are four significant digits called for in calculating slope? The figure has 4 significant digits, the text has three.

• *We have modified all figures and text to include only 3 significant digits. *

• Why is isometric scaling 0.66 - is that microns squared over microns cubed? Please explain.

• We have added additional explanation to the results section.

• Were all four posterior nuclei measured? The figure indicates just M1 and M4.

• We apologize that it was not clear that all four posterior nuclei were measured in Fig. 1. For the sake of space, we only showed images of the M1, M4, and Anterior ring canals and nuclei (in Fig. 1A), but all four nuclear measurements were included in the graph in Fig. 1B. We have added M1-M4 to the legend to clarify and revised the text of the legend.

• It is hard to explain why all four posterior nuclei are bigger than anterior when one of the four is the same age as the anterior nucleus.

• The posterior nuclei are larger than the anterior nuclei due to their proximity to the oocyte. Multiple recent studies have described this hierarchical nurse cell size relationship in which the nurse cells closest to the oocyte are larger than those separated from the oocyte by additional intercellular bridges 3–5*. *

• In panel D, a conclusion is, "Further, the scaling exponent [slope] for the anterior ring canals, which are also formed during the fourth mitotic division, was not significantly different from that of the posterior M4 ring canals". Anterior is 0.23, M4 is 0.25. These seem different to me. How is significance determined? Were any of the scaling exponents in M1, M2, M3, M4 or Anterior significantly different?

• *Significance was determined within the Prism software using a method equivalent to an ANCOVA. If the slopes are compared, M1 is significantly different from M2, M3, and M4, and M2 is significantly different from M4. M4 is not significantly different from the slope for the anterior ring canals, which supports the correlation between scaling and lineage. *

• References are needed for the statements about biased transport to the oocyte.

• *There was a reference to the Lu (2021) paper in that paragraph, but we have added an additional reference to that paper to this part of the results section. *

• In panel 2C, why are the scaling exponents (slopes) of the controls bigger than in Figure 1B? The controls look hyper allometric in Fig. 2.

• *This experiment was done with a different GAL4 driver, so it is possible that there are some differences in scaling based on genetic background. *

• In panel 2D it is impossible to pick out the control posterior vs anterior lines - use different colors as in Figure 1. Why do the control lines for posterior and anterior merge?

• *We have split the ring canal scaling data from Fig. 2D into different separate panels (Fig. 2D,E), as suggested by Reviewer #1. *

• These lines likely approach each other because the slope of the line for the anterior ring canals (M4 type) is always larger than the slope for the combined posterior ring canals.

• Re: Fig. 3: Scaling of what? RC size?

• *We assume that this comment is related to the heading for this section of the results, so we have added “ring canal to the end of this title, so that it now reads: “Increasing initial ring canal size does not dramatically alter ring canal scaling” *

• Since there was no effect, "dramatically" should be deleted from the section title.

• This change has been made.

• Clarify this sentence: If ring canal size inversely correlates with scaling, then increasing initial ring canal diameter should reduce the scaling exponent.

• We have made this change in the text.

• How does panel B show that RCs are larger in arpC2 KD? Fig. S1A has smaller y-intercept for control. Again, it is impossible to see which lines go with which M and which genotype.

• *As mentioned above, we have modified Fig. 3 to highlight these differences and added additional explanation to the results section. *

• Panels 4D & 4G are clear - should include significance indications.

• *We have added asterisks to indicate significant differences. *

• The conclusion from panels 5B and 5C that reducing RC scaling could lead to smaller mature eggs is a stretch. Without looking at the rest of the lines these data are preliminary and detract from the rest of the paper.

• *As suggested by Reviewer #1, we have modified the results and discussion sections, and we have added a statement about the need for analysis of additional lines. *

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

Comment from Reviewer #2

• I am surprised that the author has not considered controlling the impact of cell cycle regulation on this scaling process, especially as the work of Dorherty et al. has shown that this type of regulation is essential for regulating the size of nurse cell nuclei. The authors should test the impact of at least dacapo and cyclin E in this process.
• We have attempted to deplete Dacapo from the germline by crossing two different RNAi lines to multiple germline drivers; however, we have been unable to see a consistent effect on nurse cell nuclear size, which suggests that these RNAi lines may not effectively reduce Dacapo protein in the germline. Although we agree with the reviewer that this is an obvious mechanism that should be explored, we believe that it is not necessary for it to be included in this manuscript, because altering Dacapo levels in the germline would not provide a mechanism to explain our model that ring canal lineage impacts ring canal scaling. Dacapo has been shown to contribute to the hierarchical pattern of nurse cell size observed in the germline. Dacapo mRNA produced in the nurse cells is transported into the oocyte, where it is translated. Then, the Dacapo protein diffuses back into the nurse cells, producing a posterior to anterior gradient 4. Doherty (2021) showed that reducing the levels of the Dacapo protein using the deGradFP system eliminated the nurse cell size hierarchy. If our data had supported a model in which proximity to the oocyte was a strong predictor of ring canal size and scaling (as shown for the nurse cells and their nuclei3,5*), then this would have been an excellent way to dig further into the mechanism. Instead, our data supported a role for ring canal lineage in predicting ring canal growth, since the M4 ring canals at the posterior and anterior showed similar scaling with egg chamber volume. *
• We believe that performing the proposed experiments (over-expressing HtsRC to increase ring canal size or expressing the phosphomimetic form of the myosin regulatory light chain, sqhE20,E21 to reduce ring canal size) will allow us to determine how ring canal size affects scaling, which will provide additional mechanistic insight into this scaling behavior.*

*

Comment from Reviewer #3

• Panel 3E is interesting and would fit better in Figure 1.
• *This panel is from a different genetic background than the data in Fig. 1. Therefore, we do not think it would be appropriate to move it to Fig. 1. *

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Referee #3

Evidence, reproducibility and clarity

Coordinating subcellular size of organelles is important for normal cell function. This research investigates how the size of intercellular bridges called ring canals in Drosophila egg chambers is regulated. The work builds on previous research in Change Tan's lab that reported ring canal size varies by lineage - the ring canal from the first germ cell mitotic division (M1) is larger than those resulting in subsequent divisions during egg chamber formation. Shaikh et al. probe this linkage between lineage and ring canal size during egg chamber development by testing the relationship with flow through the ring canals, initial ring canal size, and number of mitotic divisions. They also investigate whether ring canal size per se affects egg size. The quantification is carefully done.

The results strongly reinforce the overall conclusion that lineage is the main driver of ring canal size. They report that growth of younger ring canals is slightly faster than old ones, suggesting a "catch-up" mechanism. However, neither the flow through ring canals nor their initial size has an apparent effect on the relationship with lineage.

General comments:

The authors derive scaling relationships between nurse cell or ring canal size and egg chamber volume to address their hypotheses. The most interesting observation is the relatively accelerated growth of young versus old ring canals attaching the oocyte to nurse cells, each from a different mitosis. Another perhaps simpler way to do this is to determine the ratios of the diameters of M1 to M4 ring canals as egg chambers develop. Does the ratio stay the same?

Specific comments:

Fig. 1:

1. For those who forgot their algebra, it would be helpful to explain that the log-log plots were used to derive a line equation (y=mx + b) and why that is useful in this context. In the case of a log-log plot, what does the y-intercept mean biologically? Is it simply a way to compare two things or does it indicate real measurements such as volume or ring canal size? Also, the slope of the line is being used as a scaling value. Be careful to define the terms "scaling" and "scaling exponent".
2. Are four significant digits called for in calculating slope? The figure has 4 significant digits, the text has three.
3. Why is isometric scaling 0.66 - is that microns squared over microns cubed? Please explain.
4. Were all four posterior nuclei measured? The figure indicates just M1 and M4. It is hard to explain why all four posterior nuclei are bigger than anterior when one of the four is the same age as the anterior nucleus.
5. In panel D, a conclusion is, "Further, the scaling exponent [slope] for the anterior ring canals, which are also formed during the fourth mitotic division, was not significantly different from that of the posterior M4 ring canals". Anterior is 0.23, M4 is 0.25. These seem different to me. How is significance determined? Were any of the scaling exponents in M1, M2, M3, M4 or Anterior significantly different? Fig. 2: Less flow through M4 drives faster RC growth? No.
6. References are needed for the statements about biased transport to the oocyte.
7. In panel C, why are the scaling exponents (slopes) of the controls bigger than in Figure 1B? The controls look hyper allometric in Fig. 2.
8. In panel D it is impossible to pick out the control posterior vs anterior lines - use different colors as in Figure 1. Why do the control lines for posterior and anterior merge?
9. In pane E, it would be helpful to plot the y-intercepts separately, too. Fig. 3: increasing initial RC size does not dramatically alter scaling.
10. Scaling of what? RC size?
11. Since there was no effect, "dramatically" should be deleted from the section title.
12. Clarify this sentence: If ring canal size inversely correlates with scaling, then increasing initial ring canal diameter should reduce the scaling exponent.
13. I cannot see differences in RC size in the panel A images. More importantly, this method altering ring canal size is limited. A more direct way is overexpression of HtsRC (https://doi.org/10.1534/genetics.120.303629).
14. How does panel B show that RCs are larger in arpC2 KD? Fig. S1A has smaller y-intercept for control. Again, it is impossible to see which lines go with which M and which genotype.
15. Panel E is interesting and would fit better in Figure 1.

Fig. 4: Additional mitotic division doesn't affect RC or nuclear scaling. 16. Panels D & G are clear - should include significance indications.

Fig. 5: small and big lines 17. The conclusion from panels B and C that reducing RC scaling could lead to smaller mature eggs is a stretch. Without looking at the rest of the lines these data are preliminary and detract from the rest of the paper.

Significance

Overall, this work is an extension and reinforcement of information previously available rather than providing significant new insight. Researchers in Drosophila oogenesis will be interested.

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Referee #2

Evidence, reproducibility and clarity

In this manuscript, Umayr Shaikh and colleagues study the evolution of the size of subcellular structures during tissue growth. To do this, the authors use the Drosophila egg chamber as a model system, studying the growth rate of the intercellular bridges, also known as ring canals, connecting the oocyte to the nurse cells and the growth rate of the nurse cell nuclei during the development of the egg chamber. In particular, they focused their study on the ring canals and the nuclei of the 4 nurse cells, both of which are in direct contact with the oocyte but have a different lineage history. They show that first born ring canal ring grow more slowly than smaller ring canal that are the result of subsequent mitotic divisions. This scaling process is maintained when polarised transport between the nurse cells and the oocyte is reduced by decreasing the level of dynein. They demonstrate that manipulation of the size of the ring canals by arpC2 RNAi does not radically alter scaling. Furthermore, by inactivating an uncharacterised gene CG34200, they show that additional mitotic division does not affect the scaling of the annular canal and nucleus.

Significance

Major comment

These results are based on new and original observations. The results are clear and well documented. However, this work is very descriptive in its current state and in the absence of a mechanism for this lineage-based scaling process.

I am surprised that the author has not considered controlling the impact of cell cycle regulation on this scaling process, especially as the work of Dorherty et al. has shown that this type of regulation is essential for regulating the size of nurse cell nuclei. The authors should test the impact of at least dacapo and cyclin E in this process.

Without a mechanism for the scaling process, this manuscript is more suitable for a specialize journal

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Referee #1

Evidence, reproducibility and clarity

The relationship between nuclear size and cell size has received a lot of attention. Less well-recognized is the problem of how other structures within the cell scale with size. This is a good question and the authors have a nice system - Drosophila female germline cysts - in which to study it. Here the authors show that lineage impacts ring canal scaling. This is an interesting finding that makes for neat biology; a simple way to think about it is that older ring canals have more time to mature (grow) than younger ones. The manuscript is beautifully and carefully written! It was fun to read. The experiments are straightforward, performed to a high standard, and generally well-presented.

Comments:

One way to think about the dhc-64C experiments presented in Figure 2 is that they are meant to test the hypothesis that ring canal size impacts scaling in such a way that transport across the four ring canals tends towards equilibrium over time. One possibility would therefore be that ring canals aren't programmed to grow to a particular final size but rather they grow at different rates until their diameters are the same. This seems to me an important distinction. It might be made by analysis of the arpC2-RNAi cells, since those ring canals are meant to be initially larger. Unfortunately I can't see the answer. The authors write that arpC2-RNAi "ring canals tended to be larger than those in similarly-sized control egg chambers," but that conclusion isn't obvious to me from the data in Figure 3B. The only difference I can see is that the M4 ring canals look to be consistently smaller in the experimental versus control egg chambers, especially at the final timepoint. Related to this concern, the authors write that "there was a consistent, but not significant decrease in the scaling exponents for the arpC2-RNAi egg chambers compared to controls," but I don't see this in the M1 (identical) or M2 (almost the same) ring canals. The scaling decrease is most pronounced at M4. All of the other ring canals seem to reach a final size that's equivalent to controls. What does this tell us about scaling? Is the M4 more sensitive to the effect of arpC2-RNAi? I note and appreciate that the data for M4 show a wide distribution and might have been impacted by outliers, which could be discussed.

The possibility that ring canal scaling "could generate eggs of different sizes" could use some elaboration (at least) as it does not seem to be especially well supported:

• Only one of the small egg lines had lower scaling exponents than the big egg lines, and it's a struggle for me to understand the extent of that difference based on the data shown. (Is it significant?).
• The authors conclude that "the effect of lineage on ring canal scaling is conserved, and it suggests that at least in one line, reducing posterior ring canal scaling could provide a mechanism to produce a smaller mature egg." The first part of this sentence is confusing for me since I don't know what is meant here by "conserved." The second part of the sentence is technically correct but disguises what I would consider the more meaningful and exciting finding. The 9.31.4 line produces the smallest eggs but does not demonstrate scaling differences in comparison to the big egg lines examined (91.40.1 and 3.34.1). The authors have therefore avoided/solved a "chicken and egg" ("fruit fly and egg"?) problem by showing that scaling and egg size can be decoupled!
• This point is not made very clearly in the discussion, which concludes with the suggestion that scaling could help explain why some insects produce much larger or much smaller eggs that fruit flies. I can only understand this to be the case if - as the authors point out - scaling "affect[s] the directed transfer of materials into the oocyte." That argument seems predicated on the possibility that these insects make the same amount of initial material then regulate how much is transferred. Seems like a costly way to go about it.

Minor comments:

I really had to look very closely to distinguish the little blue boxes from the little blue circles in panels 2C and especially 2D. I suggest using a different color instead of a different shape, or maybe splitting the graphs up.

The introductory material and the title of the paper emphasize the ring canal scaling question. This problem is somewhat obscured in the text by the side problem of nuclear scaling, which comes up frequently even though the results are not as thoroughly explored. Could the authors think about moving these data into a different, single figure for the sake of coherence? This is not a required revision. Just a thought.

I have two trivial comments regarding sentence structure in the text: "Depletion of the linker protein, Short stop (Shot), or dynein heavy chain (Dhc64C), significantly reduced the biased transport at the posterior, which reduced oocyte size (Lu et al., 2021)." I suggest this sentence might be clearer if it was rewritten as "Depletion of either dynein heavy chain (Dhc64C) or the linker protein Short stop (Shot) significantly reduces biased transport at the posterior, in turn reducing oocyte size (Lu et al., 2021).

"Because nuclear growth has been shown to be tightly coupled to cell growth (Diegmiller et al., 2021), we can use nuclear size as a proxy for nurse cell size." I think it would help the reader to know that the Diegmiller study was performed using germline cysts in the Drosophila ovary; I paused when I got to this sentence because I initially read it as overly broad. I suggest "Recent work in demonstrates that nuclear growth is tightly coupled to cell growth in this system (Diegmiller et al., 2021), and we can therefore use nuclear size as a proxy for nurse cell size" or similar. This is certainly not a required revision, just a suggestion.

Significance

The manuscript is beautifully and carefully written! It was fun to read. The experiments are straightforward, performed to a high standard, and generally well-presented. The problem it addresses is an important/useful complement to other studies on the relationship between nuclear size and cell size. The paper identifies and characterizes differential scaling of ring canals, raising exciting mechanistic questions that can be addressed in future studies. I think it will be of interest to an audience cell and developmental biologists.

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Reply to the reviewers

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

*

*Major comments: 1. Mirc56_2 and 4 showed lower integration rates, and the authors suggest that this could be due to sgRNA pool imbalance. The authors should validate this by performing sequencing of the input sgRNA and cassettes. *

→Thank you very much for your comment, and we agree with your suggestion.

We are going to confirm sgRNA pool imbalance in donor vector library by amplicon short-read NGS.

In addition, to confirm another possibility that we raised, we re-sequenced sgRNA donor vector for Mirc56_2 and 4, and will add the following sentences:

“We firstly doubted that their low integration frequencies were caused by any mutations on PB transposon of sgRNA donor vector, on especially ITR or ID that are important for integration efficiency [PMID: 15663772]. Therefore, we sequenced PB transposons for Mirc56_2 and 4 again. However, we could not find any mutations on their PB transposon.” following to “…efficiency or cell growth.” in the Discussion (page14, line 346)

*2. Clonal analysis in Figure 5c is unclear a. Figure 5c indicates that all changes were homozygous (e.g. both alleles were deleted). Was this the case in all clones? Or were some mutations heterozygous? *

→Thank you very much for your comment.

We apologize for the misleading context.

We targeted mono allele on X chromosome in male mES cells so that all mutations should be hemizygous as mentioned in the Result (page11, line 259-260)

To enhance our study is monoallelic assessment, we will add the following sentence:

“This study targeted mono allele on X chromosome in male mES cells so that all genotype on Mirc56 should be hemizygous and these mutations induced might be cis-mutation.” following to“…owing to six tandem repeats [37]” in the Result (page12, line 302)

*b. Many clones in Figure 5c show that the entire region was deleted (all black dots). Could this be due to some experimental error or misinterpretation of the sequencing data, or could it be validated using some orthogonal method? This is especially surprising for clones in which the final guide (Mirc56_13) was not detected yet the final site (Mirc56_13) was reported as "Regional deletion". *

→Thank you very much for your comment.

We apologize for the misleading context.

Firstly, we just confirmed and sequenced the mature-miRNA genomic regions by amplifying approximately 200 bp around the target sites. Therefore, we defined unamplified regions as “miRNA deletion”. In addition, to make the Figure 5C easy to understand, we added “predicted regional deletion” and each name of clones as attached.

In fact, only 4 clones harbored entire Mirc56_X deletions on all analysed Mirc56_X genomic region (Mirc56_1 to 13). Besides, these clones could be PCR-amplified by sgRNA cassettes and Sry on Y chromosome so that these results suggested we could successfully obtain their genomic DNA and at least mature-miRNA genomic regions were deleted.

Moreover, Mirc56_13 deletions without target sites on Mirc56_13 are always within predicted regional deletions that are induced from upstream and downstream of sgRNA target sites. Therefore, it could be estimated that these deletions were induced from the target sites on Mirc56_14, 15, 16, or 17 and upstream of Mirc56_13.

To clarify them, we will add the following sentences:

• “Four clones (#2_066, #1_021, #1_029 and #1_046) harboured entire Mirc56_X deletions on all analysed Mirc56_X genomic region. In addition to these clones, only 3 pairs (#2_019 and #2_084, #2_038 and #1_023, #1_016 and #1_027) harboured same combination of mutations.” following to “…combinations of mutations (Figure 5C).” in the Result (page16, line 378-380)
• “Meanwhile, focusing on relationship between mutations and target sites that targeted by sgRNA cassettes in each clone, all Mirc56_X genomic regions harbouring Indel mutations were target Micr56_X In addition, if sequential Mirc56_Xs on the genome were deleted, the most upstream and downstream of Mirc56_Xs deleted were always on the target Mirc56_X sites except for #2_025 and #1_41.” following to “…combinations of mutations (Figure 5C).” in the Result (page12, line 304)
• “Genotyping PCR amplified approximately 200 bp around the mature-miRNA genomic region. Unamplified region is defined as miRNA deletion (Black circle) and amplified region was determined as Indel mutation (Gray circle) or Intact by short-NGS. If sequential Mirc56_Xs on the genome were deleted, black translucent square indicates predicted regional deletion assumed that the genomic region flanked by miRNA deletions was also deleted. Besides, if miRNA deletion was induced in Mirc56_13 and the clone have target Mirc56_X on Mirc56_14, 15, 16, or 17” following to “…in each PB mES clone.” in the Figure legend (page23, line 575) Moreover, because we defined “miRNA deletion”, we will change ”regional deletion” to “miRNA deletion” where I mean “deletion of the mature-miRNA genomic regions” in the Result (page13, line 312) and the Discussion (page14, line 363)

*3. Next-generation targeted sequencing of clones should be made publicly accessible. *

→Thank you very much for your comment. We apologize for the inconvenience.

We already informed Review commons that we made publicly available.

We already described BioProject ID PRJNA996747 in the Data Availability (page16, line 383-384)

4. OPTIONAL - Cassette integration number is understudied. One important aspect of tiling mutagenesis is the control over how many guides are present in each cell. The authors report an average of 4.7 cassettes/cell. This could be modulated by the amount of donor vector added, and indeed the authors performed titration experiments, but only with a fluorescent reporter readout. It would be very useful to know how the concentration of donor vector corresponds to the number of cassettes/cell - perhaps genotyping of clones from one or two additional experiments would be sufficient.

→ Thank you very much for your suggestion.

We agree that cassette integration number is one important aspect of tiling mutagenesis.

To investigate how many copies our concentration of donor vector could integrate, we are going to check actual copy numbers in several clones by qPCR.

We think that it is other research to confirm “how the concentration of donor vector corresponds to the number of cassettes/cell”. The correlation might not be liner due to transposase overproduction inhibition (OPI) so that it would require huge amounts of experiments to confirm it. Our research is how CTRL-Mutations induce diverse mutations but not how property PB system have.

Minor comments: 1. The background fails to acknowledge the work of CRISPR-Cas tiling screens (e.g. https://doi.org/10.1038/nbt.3450) or CRISPR-Cas in creating mutagenesis in cell lines (e.g. https://doi.org/10.1007/978-1-0716-0247-8_29*) *

→ Thank you very much for your suggestion, and we agree with your suggestion.

We will add to acknowledge previous studies for CRISPR-Cas tilling screens.

• “Recently, targeted mutagenesis combined forward genetics and reverse genetics has been developed such as saturating mutagenesis and tiling mutagenesis that induce random mutation within target gene(s) [PMID: 25141179, 31586052, 27260157, 28118392]. This targeted mutagenesis can construct a mutant library harbouring subtly different mutations within a target gene(s) so that comparative analysis through the mutant library can screen out critical mutation(s) for biological processes. These random mutagenesises have also revealed the function of numerous coding genes” following to “…list of coding genes [6–8].” in the Introduction (page3, line 55-56)
• “In addition, the saturating mutagenesis are limited in the length of target region due to an approach basing homology-directed repair although it could introduce random mutations on donor template library harbouring any combination and variety of mutations [PMID: 25141179]. On the other hand, the tiling mutagenesis could expand target length in principle because the length depends on multiplex guide RNA (gRNA) designed to target genomic region. Therefore, tiling mutagenesis has been employed to identify critical regions embedded in cis-elements [PMID: 26375006, 30612741, 26751173, 27708057, 28416141, 31784727]. Tiling mutagenesis requires editor such as Cas9 or epigenetic modifier fused to catalytically dead Cas9 (e.g. KRAB-dCas9), and a library containing multiplex gRNA tiling across target genomic region. In general, random single guide RNA (sgRNA) expression cassette are integrated into chromosomes of host cells by retrotransposon system.” following to “…within a narrow region.” in the Introduction (page4, line 82) However, we do not agree that we have to acknowledge previous report about KI or KO by single or double cut in cell lines (as you suggested that https://doi.org/10.1007/978-1-0716-0247-8_29) because it is obvious knowledge. Therefore, we will not add this paper.

2. Figure 1 left 'ROI random mutant PB mES cell' should be horizontally aligned so Mir_1, Mir_2 and MirX align with the upper figure.

→ Thank you very much for your kind comment, and we agree with your suggestion.

Therefore, we changed it in the Figure 1.

*3. It is interesting and unexpected that some guides never induce indels, even in the absence of a regional deletion (e.g. Mirc56_3, Mirc56_7). Why might this be? Was there perhaps an error in the assignment of these guides to these cells? *

→ Thank you very much for your comment.

As you mentioned, Mirc56_3, 4 and 7 had no indel. We appreciate that we can correct our mistakes by your suggestion. We corrected Figure 5D as attached. In addition, we will correct average Mirc56_X site as 22.6 from 22.7.

These sgRNA also induced miRNA deletion with low frequency (Mirc56_3: 38.9%, Mirc56_4: 25.0% and Mirc56_7: 68.0%, Figure 5D). Moreover, every deleted Mirc56_3, 4 and 7 was within predicted regional deletion except for target Mirc56_3 of PB mES clone #2_080 (revised Figure 5C).

Therefore, we raised why some guides never induce indels even in the absence of a regional deletion, as “In addition to low frequencies, Indel mutation might disappear due to regional deletion if these sgRNAs could induce Indel mutation”.

To clarify them, we will add the following sentences:

• “In particularly, middle target sites such as Mirc56_3, 4 and 7 were induced only miRNA deletion or Intact (Figure 5D)” following to “…in our mutant library (Figure 5C, D).” in the Discussion (page14, line 364)
• “In fact, every deleted Mirc56_3, 4 and 7 was within predicted regional deletion except for target Mirc56_3 of PB mES clone #2_080 (Figure 5C). In addition, these sgRNA induced mutation with low frequency (Mirc56_3: 38.9%, Mirc56_4: 25.0% and Mirc56_7: 68.0%, Figure S6). Therefore, we suspected that regional deletion and their low mutation introduction rate facilitated to disappear Indel mutation.” following to “…induced at target sites.” in the Discussion (page14, line 366)

  *4. Regarding Mirc56_2 and 4 integration, on line 34 the authors suggest that "We suspect this was caused by a technical error, such as an unequal amount of sgRNA donor vector or the sequence in sgRNA cassettes affecting integration efficiency or cell growth." sgRNA library imbalance would be a technical error, but integration affecting cell growth is not a technical error. This sentence should be reworded. *

→ Thank you very much for your comment.

We apologize for the misleading sentence even though this paper was already English-reviewed by English language editor.

We will reword that “We suspect this was caused by the sequence in sgRNA cassettes affecting integration efficiency or cell growth, or a technical error such as an unequal amount of sgRNA donor vector.” following to “…PB mES clones via FACS..” in the Discussion (page14, line 344)

*5. Line 540 "ration" is the incorrect word - perhaps "ratio"? *

→ Thank you very much for your kind comment, and we are sorry for the typo.

We will correct it in the Figure legend (page22, line 540).

6. Plot 5b should be shown as a histogram rather than a swarm plot to show how many clones were in each category.

→ Thank you very much for your suggestion.

In Figure 5B, we aimed to indicate the number of sgRNA cassette varieties in each clone but not distribution of the number of integrated sgRNA cassettes. Distribution of the number of integrated sgRNA cassettes in clone library matched with the frequency of target sites in Figure 5D.

We already described the distribution data as “In addition, an average of 22.7 Mirc56_X sites … the same frequency except for the Mirc56_2- and 4-targeting cassettes.” in the Result (page13, line 312-315)

*Reviewer #1 (Significance (Required)):

1. General assessment: The authors are successful in creating clonal cell lines bearing a variety of mutations. Unfortunately, the cell lines also have transposase-mediated insertion events of the sgRNA cassettes at unknown positions in the genome, which will hamper the interpretability of any experiment using these cell lines. The authors fail to justify the use of the transposase and integration of the sgRNA, especially compared to lentiviral transfection or RNPs which would produce edits at the region of interest. Alternately, integrated sgRNA cassettes could have been excised with Flp recombinase as in https://doi.org/10.1007/978-1-0716-0247-8_29. *

→ Thank you very much for your suggestion.

We agree that we did not mention why we choose PiggyBac system compared to lentiviral delivery.

Therefore, we will add the following sentences:

• “In general, random single guide RNA (sgRNA) expression cassette are integrated into chromosomes of host cells by retrotransposon system. To identify combinations of critical region embedded in target regions, it would require diverse combinations of mutations or inactivation sites. To induce multiple mutations or inactivated sites, it requires multiple sgRNA cassettes integration. However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis [PMID: 23435812].” in the Introduction.
• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction. However, we are not going to mention comparison to RNPs because it is obvious that random sgRNA expressions is important key for random mutagenesis and design of random sgRNA treatments by RNP is difficult. The reason is that the target region might be cleaved by almost all sgRNA incorporated into cells. On the other hand, it is easier to design the number of sgRNA expression variety using the delivery system via integration into the chromosome because only integrate sgRNA are expressed.

In addition, we could not agree that “integrated sgRNA cassettes could have been excised with Flp recombinase as in https://doi.org/10.1007/978-1-0716-0247-8_29.”

This paper reports the concept that one EM7>neoR expression cassette flanked by Frt within KI allele could select intended-KI clone and then the cassette could remove by Flp recombinase. However, this approach is not suitable for our method because it causes structural mutation by recombination of multi Frt cassettes that are integrated into nearby genomic regions. Therefore, we will not mention it.

*2. Additionally, the genotyping analysis is unclear, and seems to indicate that each clone bears homozygous mutations, with several clones showing deletions of the entire region. *

→ Thank you very much for your suggestion.

We will revise them in Reviewer #1 Major comment 2a and b.

3. Advance: The authors are motivated to create clones using tiling mutagenesis. Tiling mutagenesis has already been performed without transposases (e.g. https://doi.org/10.1038/nbt.3450, https://doi.org/10.1371/journal.pone.0170445, https://doi.org/10.1038/s41467-019-12489-8*) in the context of a screen, and clones have already been created using CRISPR/Cas9 mutagenesis so the advance presented in this manuscript over previous published work is unclear. *

→Thank you very much for your suggestion, and we agree with your suggestion.

We will add to acknowledge previous studies for CRISPR-Cas tilling screens.

We will add the following sentences:

• “Recently, targeted mutagenesis combined forward genetics and reverse genetics has been developed such as saturating mutagenesis and tiling mutagenesis that induce random mutation within target gene(s) [PMID: 25141179, 31586052, 27260157, 28118392]. This targeted mutagenesis can construct a mutant library harbouring subtly different mutations within a target gene(s) so that comparative analysis through the mutant library can screen out critical mutation(s) for biological processes. These random mutagenesises have also revealed the function of numerous coding genes” following to “…list of coding genes [6–8].” in the Introduction (page3, line 55-56)
• “In addition, the saturating mutagenesis are limited in the length of target region due to an approach basing homology-directed repair although it could introduce random mutations on donor template library harbouring any combination and variety of mutations [PMID: 25141179]. On the other hand, the tiling mutagenesis could expand target length in principle because the length depends on multiplex guide RNA (gRNA) designed to target genomic region. Therefore, tiling mutagenesis has been employed to identify critical regions embedded in cis-elements [PMID: 26375006, 30612741, 26751173, 27708057, 28416141, 31784727]. Tiling mutagenesis requires editor such as Cas9 or epigenetic modifier fused to catalytically dead Cas9 (e.g. KRAB-dCas9), and a library containing multiplex gRNA tiling across target genomic region. In general, random single guide RNA (sgRNA) expression cassette are integrated into chromosomes of host cells by retrotransposon system.” following to “…within a narrow region.” in the Introduction (page4, line 82) The paper you raised as DOI: https://doi.org/10.1038/nbt.3450 applied CRISPRko tiling mutagenesis to find out critical region embedded 2 kb of p53 binding enhancer region by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions. In addition, we expand the length of target region to more than 50 kb. This is one of the advances.

The paper you raised as DOI: https://doi.org/10.1371/journal.pone.0170445 applied CRISPRko tiling mutagenesis to find out critical mutation on MAP2K1 and BRAF protein coding sequence by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions.

The paper you raised as DOI: https://doi.org/10.1038/s41467-019-12489-8 applied CRISPRko tiling mutagenesis for to find out critical domain from protein coding sequence by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions.

To clarify the advantages, we will add the following sentences:

• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction.
• “CRISPRko tiling mutagenesis is conducted for less than 15 kb target genomic region so far [PMID: 26375006, 30612741], while CRISPRi tiling mutagenesis can target more than 70 kb [PMID: 27708057], it is reported that. Hence, it remains unknown unclear how length CRISPRko tiling mutagenesis could expand” in the Introduction. In addition, we are going to conduct transposon removal by exicision-only-PBase treatment with several PB mES clones, for the proof of concept that CTRL-Mutagenesis can generate mutant library with no sgRNA cassettes.

*4. Audience: The manuscript is written for the basic research audience, and the method could be applied to the study of regions of interest in many diseases. However, the unexcised use of transposases make the method less desirable than other methods. *

→ Thank you very much for your suggestion.

We do not agree that the PiggyBac make the method less desirable than other methods.

As mentioned in our response for reviewer #1 Significance 3, only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis. However, sgRNA cassettes by lentiviral delivery is never removed from the genome. In addition, other approaches such as Flp recombinase that reviewer #1 proposed in Significance 1 is not better than PiggyBac because Flp recombinase causes stratal mutation by recombination of multi Frt cassettes that are integrated into nearby genomic regions.

To clarify them, we will add the following sentences:

• “However, multiple integration of single guide RNA (sgRNA) cassettes has higher risk of non-targeted endogenous gene disruptions and may impair functional analysis.” in the Abstract.
• “However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis [PMID: 23435812]. To eliminate the risk that integrated sgRNA cassettes disrupt non-targeted endogenous genes, it is best way to remove the sgRNA cassettes from the chromosome.” in the Introduction.
• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction. In addition, we are going to conduct transposon removal by exicision-only-PBase treatment with several PB mES clones, for the proof of concept that CTRL-Mutagenesis can generate mutant library with no sgRNA cassettes.

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

Major concerns:

1) Concern about the Novelty of Functional Analysis Platforms: The authors claim that there are no established platforms for the study of cis-elements or microRNA clusters. This assertion seems inaccurate, as previous studies have utilized Cas9 tiling screens to investigate cis-regulatory elements (CREs) and large-scale screens to probe microRNA functions, as exemplified by the works of Canver et al. in Nature 2015, Gasperini et al. in Cell 2019, and others. *

→ Thank you very much for your suggestion, and we agree with your suggestion.

We apologize our false claim so that we will delete the following sentences:

• “In contrast, no functional analysis platforms have been established for the study of cis-elements or microRNA cluster regions consisting of multiple microRNAs with functional overlap” in the Abstract (page2, line 28-30)
• “While loss-of-function analysis has been conducted for numerous coding genes, very limited progress has been made on non-coding genes and cis-elements.” in the Introduction (page3, line 47-49) The paper you raised as DOI: https://doi.org/10.1038/nature15521 (Canver et al. in Nature 2015) applied CRISPRko tiling mutagenesis to find out critical region embedded 12 kb of BCL11A enhancer region by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions. In addition, we expand the length of target region to more than 50 kb. This is one of the advances.

The paper you raised as DOI: https://doi.org/10.1016/j.cell.2018.11.029 (Gasperini et al. in Cell 2019) applied CRISPRko tiling mutagenesis to find out critical region embedded maximum 12 kb enhancer candidates, in addition to CRISPRi tilling candidate screening through one sgRNA by one candidate enhancer, by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions. In addition, we expand the length of target region to more than 50 kb. This is one of the advances. Additionally, to identify combinations of critical region embedded in target regions, it would require diverse combinations of mutations or inactivation sites. To induce multiple mutations or inactivated sites, it requires multiple sgRNA cassettes integration. However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis. To eliminate the risk that integrated sgRNA cassettes disrupt non-targeted endogenous genes, it is best way to remove the sgRNA cassettes from the chromosome. Thus, to identify combinations of critical region embedded in target regions with no artifact owing to no footprint by removal of sgRNA cassettes, CRISPRko tiling mutagenesis rather than CRISPRi is better method because CRISPRi requires integrated cassettes that stably expressed sgRNA and epigenetic modifier fused to dCas9. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions to find out combinations of critical region embedded in target regions.

Therefore, to add to acknowledge previous studies and clarify the advantages, we will add the following sentences:

• “In addition, the saturating mutagenesis are limited in the length of target region due to an approach basing homology-directed repair although it could introduce random mutations on donor template library harbouring any combination and variety of mutations [PMID: 25141179]. On the other hand, the tiling mutagenesis could expand target length in principle because the length depends on multiplex guide RNA (gRNA) designed to target genomic region. Therefore, tiling mutagenesis has been employed to identify critical regions embedded in cis-elements [PMID: 26375006, 30612741, 26751173, 27708057, 28416141, 31784727]. Tiling mutagenesis requires editor such as Cas9 or epigenetic modifier fused to catalytically dead Cas9 (e.g. KRAB-dCas9), and a library containing multiplex gRNA tiling across target genomic region. In general, random single guide RNA (sgRNA) expression cassette are integrated into chromosomes of host cells by retrotransposon system.” following to “…within a narrow region.” in the Introduction (page4, line 82)
• “To identify combinations of critical region embedded in target regions, it would require diverse combinations of mutations or inactivation sites. To induce multiple mutations or inactivated sites, it requires multiple sgRNA cassettes integration. However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis [PMID: 23435812]. To eliminate the risk that integrated sgRNA cassettes disrupt non-targeted endogenous genes, it is best way to remove the sgRNA cassettes from the chromosome. Thus, to identify combinations of critical region embedded in target regions with no artifact owing to no footprint by removal of sgRNA cassettes, CRISPRko tiling mutagenesis rather than CRISPRi is better method because CRISPRi requires integrated cassettes that stably expressed sgRNA and epigenetic modifier fused to dCas9.” in the Introduction.
• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction.
• “CRISPRko tiling mutagenesis is conducted for less than 15 kb target genomic region so far [PMID: 26375006, 30612741], while CRISPRi tiling mutagenesis can target more than 70 kb [PMID: 27708057], it is reported that. Hence, it remains unknown unclear how length CRISPRko tiling mutagenesis could expand” in the Introduction. On the other hand, we could not find previous studies employing Cas9 tiling mutagenesis to investigate miRNA functions. The application for miRNA cluster is also one of the advances.

2) Advantages of PiggyBack System Over Lentiviral Integration: The paper does not clearly articulate the advantages of their proposed PiggyBack-based system for sgRNA integration over traditional lentiviral integration. Both methods facilitate the random integration of multiple gRNAs, but the paper lacks a comparative analysis or justification for choosing the PiggyBack system.

→ Thank you very much for your suggestion, and we agree with your suggestion.

We agree that we did not mention why we choose PiggyBac system compared to lentiviral delivery.

Therefore, we will add the following sentences:

• “In general, random single guide RNA (sgRNA) expression cassette are integrated into chromosomes of host cells by retrotransposon system. To identify combinations of critical region embedded in target regions, it would require diverse combinations of mutations or inactivation sites. To induce multiple mutations or inactivated sites, it requires multiple sgRNA cassettes integration. However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis [PMID: 23435812].” in the Introduction.
• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction.

  *3) Lack of Comparative Analysis with Alternative Methods: The authors did not provide a comparison of CTRL-Mutagenesis with other existing screening methods. Such a comparison is crucial for understanding the effectiveness and efficiency of the new method in relation to established techniques. *

→ Thank you very much for your suggestion.

We agree with the comparison is one of important experiments.

However, our main claim is validation of tiling mutagenesis using PiggyBac that is only integration system with no footprint. Therefore, we propose our novelty without the comparison and not argue higher / lower efficiency of CTRL-Mutagenesis compared to exiting methods.

*4) Limitations in Library Resolution: The paper acknowledges the limited resolution of their proposed library. The authors might have explored the use of base editors for enhanced resolution in such screens, as base editing could potentially offer more precise and controlled mutagenesis as briefly mentioned in the discussion. *

→ Thank you very much for your suggestion.

We agree with your suggestion.

Base editing is occurred within only editing window. In addition, a major limitation of prime editing is low efficiency (https://doi.org/10.1016/j.tibtech.2023.03.004). Therefore, design of sgRNA for base editor or pegRNA and its editing efficiency requires huge amounts of experiments.

Our study is proof of concept to validate PiggyBac system for CRISPRko tilling mutagenesis and expanded the length of target regions. Thus, we just discussed limited resolution of our mutant library and proposed the use of base editors for enhanced resolution in the Discussion (page14, line 366-370).

5) Absence of Functional Data Post-Mutagenesis: A significant limitation of the study is the absence of functional data following the creation of cells with different mutations. While the authors speculate about using differentiation systems or organoids for practical applications, they do not provide empirical data to demonstrate the utility of the CTRL-Mutagenesis approach. This lack of functional validation raises questions about the practical applicability of the method.

→ Thank you very much for your suggestion.

We agree with your suggestion.

We would make functional analysis future research.

In this paper, we just validated PiggyBac system for CRISPRko tilling mutagenesis and expanded the length of target regions.

To change our tone that claiming usability of our method for functional analysis, we will change the following sentences:

• Change “to identify functionally important elements in non-coding regions” to “to induce diverse combination and variety of mutations within more than 50 kb non-coding region” in the Title.
• Add “However, not much loss-of-function screens of non-coding regulatory elements has been conducted due to ambiguous annotations compared with protein-coding genes. Tiling mutagenesis has been employed to identify critical regions embedded in non-coding regulatory elements by comparative analysis through a mutant library harbouring subtly different regions mutated within less than 15 kb region. Conventional tiling mutagenesis construct a mutant library integrated multiple sgRNA cassettes by retroviral delivery. However, multiple integration of single guide RNA (sgRNA) cassettes has higher risk of non-targeted endogenous gene disruptions and may impair functional analysis. Herein, combining tiling mutagenesis and PiggyBac transposon that can be removed with no footprint on integrated sites, we established an expanded tilling mutagenesis method named CRISPR- & Transposase-based RegionaL Mutagenesis (CTRL-Mutagenesis). We demonstrated that PiggyBac system could integrated diverse combinations and varieties of sgRNA cassettes.and then CTRL-Mutagenesis randomly induces diverse combination and variety of mutations within more than 50 kb non-coding region in murine embryonic stem cells. CTRL-Mutagenesis would apply for wider non-coding regulatory elements with no risk of non-targeted endogenous gene disruptions.” in the Abstract.
• Delete “Comparative analysis of mutants harbouring subtly different mutations within the same region would facilitate the further study of cis-element and microRNA clusters.” in the Abstract (page2, line 38-40).
• Change “The generated random mutant mES clone library could facilitate further functional analyses of non-coding regulatory elements within the genome.” to “The generated random mutant mES clone library could develop to investigate critical regions of non-coding regulatory elements within the genome.” In the Introduction (page4, line 88-90)

  *Reviewer #2 (Significance (Required)):

  1. In summary, while the idea to integrate sgRNA in the genome by the PiggyBack system is interesting the claim of novelty is questionable due to existing methods in the field. The advantages of their system over existing technologies are not clearly articulated, and a lack of comparative analysis with other methods leaves the efficiency of CTRL-Mutagenesis uncertain. *

→ Thank you very much for your suggestion.

Previous studies about CRISPRko and CRISPRi tiling mutagenesis employ lentiviral delivery of sgRNA cassettes into the genome. However, multi sgRNA cassette integrations have higher risk to disrupt non-targeted endogenous functions. To eliminate the risk that integrated sgRNA cassettes disrupt non-targeted endogenous genes, it is best way to remove the sgRNA cassettes from the chromosome. Nevertheless, lentiviral transposon, one of retrotransposon, cannot be removed from the chromosome. On the other hand, only PiggyBac transposon can be removed with no footprint. Therefore, we aimed to validate PiggyBac system for tiling mutagenesis. Moreover, there is no report that CRISPRko tiling mutagenesis apply for more than 15 kb genomic region. Therefore, we aimed to expand the length of target region.

Therefore, we will change our claim that our method could expand CRISPRko tiling mutagenesis to more than 50 kb with no risk of non-targeted endogenous gene disruption.

We will add the novelty and advantage of our method.

• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction.
• “CRISPRko tiling mutagenesis is conducted for less than 15 kb target genomic region so far [PMID: 26375006, 30612741], while CRISPRi tiling mutagenesis can target more than 70 kb [PMID: 27708057], it is reported that. Hence, it remains unknown unclear how length CRISPRko tiling mutagenesis could expand” in the Introduction. However, our main claim is validation of tiling mutagenesis using PiggyBac that is only integration system with no footprint. Therefore, we will propose our novelty without the comparison and not argue higher / lower efficiency of CTRL-Mutagenesis compared to exiting methods.

In addition, we are going to conduct transposon removal by exicision-only-PBase treatment with several PB mES clones, for the proof of concept that CTRL-Mutagenesis can generate mutant library with no sgRNA cassettes.

2. Moreover, the limited resolution of their library and the absence of functional data post-mutagenesis are significant drawbacks that need to be addressed in future research to ascertain the method's practical utility.

→ Thank you very much for your suggestion.

We agree with your suggestion.

We would make functional analysis future research.

Base editing is occurred within only editing window. In addition, a major limitation of prime editing is low efficiency (https://doi.org/10.1016/j.tibtech.2023.03.004). Therefore, design of sgRNA for base editor or pegRNA and its editing efficiency requires huge amounts of experiments.

Our study is proof of concept to validate PiggyBac system for CRISPRko tilling mutagenesis and expanded the length of target regions. Thus, we just discussed limited resolution of our mutant library and proposed the use of base editors for enhanced resolution in the Discussion (page14, line 366-370).

Therefore, we just claimed that we validated PiggyBac system for CRISPRko tilling mutagenesis and expanded the length of target regions.

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

Major comments: 1. Authors claim that "CTRL-mutagenesis randomly induces diverse mutations only within the targeted regions in murine embryonic stem (mES) cells.", however, the outcome of mutations is not entirely random since most of the mutations are regional deletions. For example, despite the random distribution of gRNAs per cell, the inner regions like Mirc56_5 or Mirc56_8 are mutated with >80% efficiency.*

→ Thank you very much for your comment.

We agree that middle regions are tending to be deleted and mutation type induced is not entirely random. However, we do not agree that “the outcome of mutations is not entirely random since most of the mutations are regional deletions.” Focusing on the combinations of mutations as mentioned in the Result (page12, line 302-304), CTRL-Mutagenesis could induce diverse mutation combinations randomly at a moderate degree. In fact, 79.2% of clones harboring multiple mutations were induced different combinations of mutations. In addition, to confirm how mutations occurred within Mirc56 by CTRL-Mutagenesis, we constructed only 87 mutant clones though single cloning. Therefore, it is not completely understanded due to fewer clones compared with conventional CRISPRko tiling mutant library. Of course, we should improve the randomness of mutation combinations, but we already discussed it and proposed solutions in the Discussion (page14, line 366-370).

Certainly, CTRL-Mutagenesis would be difficult to identify necessary and sufficient genomic region due to incomplete randomness. Nevertheless, there is no report to induce diverse combination and variety of mutations within more than 50 kb genomic region. Hence, CTRL-Mutagenesis should be worth screening out critical regions within more than 50 kb regions.

To clarify them, will add the following sentences:

• “CRISPRko tiling mutagenesis is conducted for less than 15 kb target genomic region so far [PMID: 26375006, 30612741], while CRISPRi tiling mutagenesis can target more than 70 kb [PMID: 27708057], it is reported that. Hence, it remains unknown unclear how length CRISPRko tiling mutagenesis could expand” in the Introduction.
• “Four clones (#2_066, #1_021, #1_029 and #1_046) harboured entire Mirc56_X deletions on all analysed Mirc56_X genomic region. In addition to these clones, only 3 pairs (#2_019 and #2_084, #2_038 and #1_023, #1_016 and #1_027) were induced same combination of mutations. Besides, 26 clones had only one mutation from Mirc56_1 to Mirc56_13. On the other hand, there was no mutation on Mirc56_1 to 13 in 11 clones including 5 clones (#2_012, #2_015, #2_054, #2_092 and #2_102) carried no sgRNA cassette for Mirc56 _1 to 13 and 6 clones (#2_017, #2_053, #2_098, #1_003, #1_012 and #1_044) even carried any one of sgRNA cassettes for Mirc56 _1 to 13. Among 48 clones carrying multiple mutations except for clones carrying only one mutation or Intact, 38 clones (79.2%) harboured different combinations of mutations. These results suggested that CTRL-Mutagenesis could induce diverse combinations of mutations.” following to “…different combinations of mutations (Figure 5C).” in the Result (page12, line 304)
• “Note that CTRL-Mutagenesis would be difficult to identify necessary and sufficient genomic region due to incomplete randomness. Nevertheless, CTRL-Mutagenesis should be worth screening out critical regions within more than 50 kb regions” following to “…to induce regional deletions.” in the Discussion (page15, line 378)
• Change “diverse mutations” to “diverse combination and variety of mutations” in the Title, Abstract (page2, line 37), Introduction (page4, line 87), Result (page13, line 318), Discussion (page13, line 325), (page14, line 363) Additionally, we do not agree with your suggestions that “the inner regions like Mirc56_5 or Mirc56_8 are mutated with >80% efficiency”. We apologize for the misleading context. These high mutation rates were calculated on only the target sites. Actually, maximum mutation rate on all MIrc56_X genomic regions are 44.8% on Mirc56_10, minimum is 14.9% on Mirc56_2 and an average is 30.9% (attached Figure).

We appreciate that we can recognize our misleading context by your suggestion. It is more important that the analysis focusing all Mirc56_X genomic regions rather than target Mirc56_X. Therefore, we newly made figure about event occurrence in Mirc56_X genomic regions (attached Figure) as Figure 5D and replaced previous Figure 5D about event occurrence in target Mirc56_X to Supplemental Figure S6.

To clarify them, we will add the following sentences:

• “As for event occurrences on each Mirc56_X genomic region, miRNA deletions were dominant and an average of 26.7 Mirc56_X genomic region were induced mutations in 87 clones (Figure 5D). Maximum mutation rate on all MIrc56_X genomic regions was 44.8% (39/87) on Mirc56_10, minimum was 14.9% (13/87) on Mirc56_2” following to “…on the same strand” in the Result (page12, line 309)
• “__D, __Mutations in 87 Mirc56 random mutant clones. The target sites do not include Mirc56_14, 15, 16, and The vertical axis and bar graphs show event occurrence on each Mirc56 genomic region in 87 Mirc56 random mutant clones. The bar colour indicates each event (Black: Regional deletion, Gray: Indel mutation, White: Intact).” in the Figure legend.

  2. Also, although the authors discuss that the lower mutation frequency observed for Mirc56_2 and 4 may be due to a technical error, confirming this by repeating the experiment would be important to prove the usability of this method.

→Thank you very much for your comment, and we agree with your suggestion.

We had already constructed bulk PB mES cells twice and showed Figure 4B combined these experimental replicates.

To clarify that we constructed bulk PB mES cells twice, we changed Figure 4B as attached and will add the following sentences:

• “Even though these bulk PB mES cells were constructed twice, it seemed that sgRNA cassettes for Mirc56_2 and 4 were difficult to integrate into the genome.” following to “…were rarely detected” in the Result (page11, line 273)
• “In addition, we suspected technical errors so that we constructed bulk PB mES cells twice. Unfortunately, their low integration frequencies were not improved.” following to “…efficiency or cell growth.” in the Discussion (page14, line 346)
• “Bulk1 and Bulk2 indicate the experimental replicate.” following to “…next-generation sequencing (NGS).”in the Figure legend (page22 line 563) In addition, we re-sequenced sgRNA donor vector for Mirc56_2 and 4, and will add the following sentences:

“We firstly doubted that their low integration frequencies were caused by any mutations on PB transposon of sgRNA donor vector, on especially ITR or ID that are important for integration efficiency [PMID: 15663772]. Therefore, we sequenced PB transposons for Mirc56_2 and 4 again. However, we could not find any mutations on their PB transposon.” following to “…efficiency or cell growth.” in the Discussion (page14, line 346)

Moreover, to confirm the technical error, we are going to confirm sgRNA pool imbalance in donor vector library by amplicon short-read NGS.

*3. Additionally, the experiments were performed on the haploid X chromosome of a male cell line. It is questionable whether this method can be generalized to other regions located in the other chromosomes. Clarifying These points would be essential especially because the focus of this manuscript is to describe the efficiency of this novel methodology. *

→Thank you very much for your comment.

We expect that CTRL-Mutagenesis could be valid on other biallelic locus.

Therefore, we raised predicted issue such as complex genotyping and proposed one solution.

When we target other biallelic locus, we must determine whether the combination of mutations induced are cis- or trans-mutations. Haplotype phasing, combined long-read sequencing with SNP markers within ROI on maternal/paternal chromosome, assembles each allele via SNP markers on each read [PMID: 35710642]. Therefore, combining CTRL-Mutagenesis on heterozygotic alleles of cells derived from such as human or murine hybrid with haplotype phasing might simplify genotyping.

We will add the following sentences:

“In this study, CTRL-Mutagenesis was validated by genotyping on mono allele in male mES cells to avoid investigating whether the combination of mutations induced are cis- or trans-mutations. All genotypes on Mirc56 should be hemizygous and these mutations induced might be cis-mutations so that we determined the genotypes by amplifying approximately 200 bp around the target sites. However, we did not confirm large mutations such as deletion of the genomic region between target sites and inversion. Long-read sequencing might capture their large mutations. Besides, we also expect that CTRL-Mutagenesis could be valid for ROI on biallelic autosome and X chromosome in female. Therefore, it is required to determine whether the combination of mutations induced are cis- or trans-mutation. Haplotype phasing, combined long-read sequencing with SNP markers within ROI on maternal/paternal chromosome, assembles each allele via SNP markers on each read [PMID: 35710642]. Therefore, combining CTRL-Mutagenesis on heterozygotic alleles of cells derived from such as human or murine hybrid with haplotype phasing might simplify genotyping.” in the Discussion.

*4. The limitations of the methods seem not to be fully described in the manuscript and must be clarified. Compared to the previous studies (see "significance" section for details), this method is inferior in that (1) it is time-consuming because it requires clonal expansion of single cells and (2) it has low throughput because it requires genome sequencing due to the occurrence of deletions. These points should be described for the potential users of this methodology. For example, it may be useful to detail the time consumption in each experimental step in Fig. 4A. *

→Thank you very much for your comment.

We do not agree that (1) it is time-consuming because it requires clonal expansion of single cells.

To confirm the mutations that CTRL-Mutagenesis induced, we did not conduct phenotyping screening such as dropout screening in this study. For further high-throughput screening, CTRL-Mutagenesis could apply bulk mutant mES cells, that is treated with Cas9 and EGFP-positive, for phenotyping screening.

Additionally, we do not agree that (2) it has low throughput because it requires genome sequencing due to the occurrence of deletions. In this study, to prove our concept that CTRL-Mutagenesis could induce diverse combinations and varieties of mutations such as Indel and regional deletion, we conducted genotyping in all random mutant clones. On the other hand, there are alternative comparative method to improve throughput without genotyping. Combination of phenotyping screening and gene expression assay for target miRNAs or transcript regulated by target cis-element help us obtain clones harboring mutations on functionally critical regions within target region. Finally, we should conduct genotyping to identify critical regions embedded in non-coding regulatory elements.

Even so, we will add the time consumption in Figure 4A as attached because the information may be useful for potential users as you mentioned.

*Minor comments: 1. Data and methods are well-presented for reproducibility. The EGFP-positive ratio may be added to Fig. 4C for clarity. *

→Thank you very much for your kind comment.

We added the EGFP-positive ratio to Figure 4C and will add the following sentence:

“The percentage above the box indicates the EGFP-positive ratio.” following to “…the gates of the EGFP filter.” in the Figure legends (page23, line 567)

2. Enhance referencing accuracy, rectify DOI format in ref 21, and ensure consistency in citation formatting, e.g., ref 32.

→Thank you very much for your kind comment.

Along with the transfer, we will modify the style of references and have already confirmed the referencing accuracy in the Reference.

3. It seems that the experimental condition (e.g. The amount of vectors used for transfection) should be re-considered every time the researcher wants to set up an experiment changing target genomic regions, cell types etc. If so, this also should be described in the text for potential users of this method.

→Thank you very much for your comment, and we agree with your suggestion.

We will add the following sentences:

“This study just validated CTRL-Mutagenesis for 17 target sites in mES cells. Therefore, it might be better to adjust the number of integrated sgRNA cassettes according to the number of target sites and cell types.” following to “…sgRNA cassettes to be integrated.” in the Discussion (page14, line 355)

*Reviewer #3 (Significance (Required)):

There were various methods described in the late 2010's which aimed to screen for the functional non-coding regions using approaches such as KO-based, HDR-based, and epigenetic silencing using dCas9 (for example, PMID: 25141179, 26751173, 27708057, 28416141, 31784727). The authors should summarize what would be the strength of their method compared to these previously described methodologies. The strength of this methodology seems to be moderate complexity and cost-effectiveness compared to these previous techniques. It may be difficult for this methodology to become a state-of-the-art method to evaluate cis-element combinations, but it can be beneficial to researchers wanting to set up a low-cost system that can produce moderately complex cell libraries.*

→Thank you very much for your suggestion.

We will add to acknowledge previous studies for CRISPR-Cas tilling screens.

• “Recently, targeted mutagenesis combined forward genetics and reverse genetics has been developed such as saturating mutagenesis and tiling mutagenesis that induce random mutation within target gene(s) [PMID: 25141179, 31586052, 27260157, 28118392]. This targeted mutagenesis can construct a mutant library harbouring subtly different mutations within a target gene(s) so that comparative analysis through the mutant library can screen out critical mutation(s) for biological processes. These random mutagenesises have also revealed the function of numerous coding genes” following to “…list of coding genes [6–8].” in the Introduction (page3, line 55-56)
• “In addition, the saturating mutagenesis are limited in the length of target region due to an approach basing homology-directed repair although it could introduce random mutations on donor template library harbouring any combination and variety of mutations [PMID: 25141179]. On the other hand, the tiling mutagenesis could expand target length in principle because the length depends on multiplex guide RNA (gRNA) designed to target genomic region. Therefore, tiling mutagenesis has been employed to identify critical regions embedded in cis-elements [PMID: 26375006, 30612741, 26751173, 27708057, 28416141, 31784727]. Tiling mutagenesis requires editor such as Cas9 or epigenetic modifier fused to catalytically dead Cas9 (e.g. KRAB-dCas9), and a library containing multiplex gRNA tiling across target genomic region. In general, random single guide RNA (sgRNA) expression cassette are integrated into chromosomes of host cells by retrotransposon system.” following to “…within a narrow region.” in the Introduction (page4, line 82) The paper you raised as DOI: https://doi.org/10.1038/nature13695 (PMID: 25141179) applied saturation mutagenesis to find out critical mutation on BRCA1 and DBR1 protein coding sequence by HDR-based strategy using donor template library. This method based homologous recombination repair, so that the length of target region is limited. Our method employs tiling mutagenesis whose target length depends on sgRNA designed. We expand the length of target region to more than 50 kb from less than 15 kb previously reported. This is our strength compared with this report.

The paper you raised as DOI: https://doi.org/10.1038/nbt.3450 (PMID: 25141179) applied CRISPRko tiling mutagenesis to find out critical region from 2 kb of p53 binding enhancer region by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions. In addition, we expand the length of target region to more than 50 kb. This is one of the advances.

The paper you raised as DOI: https://doi.org/10.1126/science.aag2445 (PMID: 27708057) applied CRISPRi tiling mutagenesis to find out critical region from 74 kb genomic region around GATA1 and MYC by lentiviral delivery of sgRNA cassettes. Our method employs CRISPRko and PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. To identify combinations of critical region embedded in target regions, it would require diverse combinations of mutations or inactivation sites. To induce multiple mutations or inactivated sites, it requires multiple sgRNA cassettes integration. However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis. To eliminate the risk that integrated sgRNA cassettes disrupt non-targeted endogenous genes, it is best way to remove the sgRNA cassettes from the chromosome. Thus, to identify combinations of critical region embedded in target regions with no artifact owing to no footprint by removal of sgRNA cassettes, CRISPRko tiling mutagenesis rather than CRISPRi is better method because CRISPRi requires integrated cassettes that stably expressed sgRNA and epigenetic modifier fused to dCas9. PiggyBac system can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions to find out combinations of critical region embedded in target regions.

The paper you raised as DOI: https://doi.org/10.1016/j.molcel.2017.03.007 (PMID: 28416141) reported applied CRISPRi tiling mutagenesis to find out critical region from TAD scale (about 200 kb) with low magnification by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions.

The paper you raised as DOI: https://doi.org/10.1038/s41588-019-0538-0 (PMID: 31784727) reported applied CRISPRi tiling mutagenesis to develop method that can find out novel regulatory element around protein coding by lentiviral delivery of sgRNA cassettes. Our method employs PiggyBac system that can remove the sgRNA cassettes from the chromosome with no footprint. Therefore, our method should be novel method that generates mutant library with no risk of non-targeted endogenous gene disruptions.

To clarify the advantages, we will add the following sentences:

• “To identify combinations of critical region embedded in target regions, it would require diverse combinations of mutations or inactivation sites. To induce multiple mutations or inactivated sites, it requires multiple sgRNA cassettes integration. However, multiple integration of sgRNA cassettes have higher risk of non-targeted endogenous gene disruptions and may impair functional analysis [PMID: 23435812]. To eliminate the risk that integrated sgRNA cassettes disrupt non-targeted endogenous genes, it is best way to remove the sgRNA cassettes from the chromosome. Thus, to identify combinations of critical region embedded in target regions with no artifact owing to no footprint by removal of sgRNA cassettes, CRISPRko tiling mutagenesis rather than CRISPRi is better method because CRISPRi requires integrated cassettes that stably expressed sgRNA and epigenetic modifier fused to dCas9.” in the Introduction.
• “Here, we proposed that DNA transposon system rather than retrotransposon system is more suitable to remove sgRNA cassettes from a mutant library. Transposons are genetic elements that can relocate between genomic sites and there are two types of transposons: (1) DNA transposon is transferred by a "cut and paste" mechanism in which the transposon sequence is cut directly from the genome, and (2) retrotransposon is transferred by a "copy and paste" mechanism in which the transposon sequence is transcribed into RNA and then integrated by reverse transcribed [PMID: 21958341]. Therefore, retrotransposon is never removed from the genome. DNA transposon such as PiggyBac, Sleeping Beauty and Tol2 systems are also used as gene transfer tools in vertebrates [PMID: 26481584]. Especially, PiggyBac leaves no footprint on integrated sites after transposons relocated while other DNA transposon system leaves small insertion on integrated sites [PMID: 34064900]. In addition, excision-only-PiggyBac transposase that can remove transposons but not integrate them, is developed [PMID: 27929521]. Only PiggyBac system can remove transposons carrying sgRNA cassettes from mutant library with no footprint. Therefore, we aimed to validate PiggyBac system for CRISPRko tilling mutagenesis.” in the Introduction.
• “CRISPRko tiling mutagenesis is conducted for less than 15 kb target genomic region so far [PMID: 26375006, 30612741], while CRISPRi tiling mutagenesis can target more than 70 kb [PMID: 27708057], it is reported that. Hence, it remains unknown unclear how length CRISPRko tiling mutagenesis could expand” in the Introduction. In addition, we are going to conduct transposon removal by exicision-only-PBase treatment with several PB mES clones, for the proof of concept that CTRL-Mutagenesis can generate mutant library with no sgRNA cassettes.

*Reviewer #4 (Evidence, reproducibility and clarity (Required)):

Major concerns, 1, Authors claim "to identify functionally important elements in non-coding regions in the title but there is no evidence of any functional analysis in the manuscript.*

→ Thank you very much for your suggestion, and we agree with your suggestion.

In this paper, we just validated PiggyBac system for CRISPRko tilling mutagenesis and expanded the length of target regions.

To change our tone that claiming usability of our method for functional analysis, we will change the following sentences:

• Change “to identify functionally important elements in non-coding regions” to “to induce diverse combination and variety of mutations within more than 50 kb non-coding region” in the Title.
• Add “However, not much loss-of-function screens of non-coding regulatory elements has been conducted due to ambiguous annotations compared with protein-coding genes. Tiling mutagenesis has been employed to identify critical regions embedded in non-coding regulatory elements by comparative analysis through a mutant library harbouring subtly different regions mutated within less than 15 kb region. Conventional tiling mutagenesis construct a mutant library integrated multiple sgRNA cassettes by retroviral delivery. However, multiple integration of single guide RNA (sgRNA) cassettes has higher risk of non-targeted endogenous gene disruptions and may impair functional analysis. Herein, combining tiling mutagenesis and PiggyBac transposon that can be removed with no footprint on integrated sites, we established an expanded tilling mutagenesis method named CRISPR- & Transposase-based RegionaL Mutagenesis (CTRL-Mutagenesis). We demonstrated that PiggyBac system could integrated diverse combinations and varieties of sgRNA cassettes.and then CTRL-Mutagenesis randomly induces diverse combination and variety of mutations within more than 50 kb non-coding region in murine embryonic stem cells. CTRL-Mutagenesis would apply for wider non-coding regulatory elements with no risk of non-targeted endogenous gene disruptions.” in the Abstract.
• Delete “Comparative analysis of mutants harbouring subtly different mutations within the same region would facilitate the further study of cis-element and microRNA clusters.” in the Abstract (page2, line 38-40).
• Change “The generated random mutant mES clone library could facilitate further functional analyses of non-coding regulatory elements within the genome.” to “The generated random mutant mES clone library could develop to investigate critical regions of non-coding regulatory elements within the genome.” In the Introduction (page4, line 88-90)

  2, Genotypes of mutant library, especially Mirc56, 14,15, 16, 17 were not determined due to six tandem repeats. Thus, analysis of the relationship between genotype and biological functions is not possible. Moreover, the authors did not show any phenotypic analysis.

→ Thank you very much for your suggestion.

The 6 tandem repeats consisted of each approximately 3.3 kb are hard to determine mutations and are uncommon.

Therefore, we skipped genotyping Mirc56_14, 15, 16, and 17

Certainly, it is drawback that we did not determine all mutations induced by CRTL-mutagenesis.

Even so, we could determine the properties of mutant library within 37 kb genomic region from Mirc56_1 to Mirc56_13.

Therefore, we could conclude that CTRL-mutagenesis could induce diverse combinations and variations of mutations into more than 50 kb.

3, Multiple gRNA may cause deletion and inversion to targeted loci. With local PCR based amplification, detection of large deletion and inversion can be very difficult. I think the authors should examine and address this possibility more carefully. The definition of indel in Fig 5C should be explained in more detail.

→ Thank you very much for your comment, and we agree with your suggestion.

We did not confirm inversion and large deletion.

To confirm whether inversions were happened, we are going to perform PCR walking in several clones and long-read sequencing.

4, Although the authors showed a variety of PB cassettes (Max is 17), more importantly would be to determine the actual copy number of PB cassettes. Difference between the highest and the lowest EGFP intensities in Fig 2C (Donor 300ng Effector 350ng) is approximately ~100 fold, thus ES clone bearing highest PB vector may contain ~100 copies of PB vector. PB transposon prefers insertion in active genes compared to other transposon system such as Sleeping Beauty and Tol2 transposon. (Yoshida J et al Sci Rep. 2017 Mar 2;7:43613. doi: 10.1038/srep43613.). Higher integration rates of PB vectors have a higher chance of endogenous gene disruptions and may impair functional analysis.

→ Thank you very much for your suggestion.

We agree that cassette integration number is one important aspect of tiling mutagenesis. To determine actual copy number of PB transposon is useful information when potential user consider optimizing our method for own target region. However, to confirm whether the relationship between mutations induced and sgRNA cassettes integrated, the number of integrated cassette variety is more important because the diversity of sgRNAs variety expressed is more related to the diversity of mutations induced. Therefore, we identified the number of integrated cassette variety.

To clarify this point, we will add we the following sentences:

“rather than the copy number of sgRNA cassettes because the diversity of sgRNAs variety expressed is more related to the diversity of mutations induced” following to “…the number of sgRNA cassette varieties.” in the Result (page12, line 297)

Certainly, we apologize that it is not accurate that “EGFP signal intensity correlated with the copy number of EGFP cassettes integrated into genomes[23]” in the Result (page11, line 249-250). EGFP expression levels are affected by cell cycle so that the paper reported that “Median EGFP intensities correlated with the copy number of EGFP cassettes integrated into genomes”.

Therefore, we will delete the following sentence:

“EGFP signal intensity correlated with the copy number of EGFP cassettes integrated into genomes[23]” in the Result (page11, line 249-250).

To investigate how many copies our concentration of donor vector could integrate, we are going to check actual copy numbers in several clones by qPCR.

Besides, we agree with your suggestion that “PB transposon prefers insertion in active genes compared to other transposon system such as Sleeping Beauty and Tol2 transposon. (Yoshida J et al Sci Rep. 2017 Mar 2;7:43613. doi: 10.1038/srep43613.)”

Therefore, we will change the following sentence:

“random TTAA sites across genomes [24]” to “random TTAA sites of transcribed region rather than intergenic region [PMID: 28252665]” in the Discussion (page14, line 357).

However, Sleeping Beauty and Tol2 transposon remain footprint at integration sites when these transposons move [PMID: 15133768, 23143102]. Especially, SB transposon leaves canonical 5 bp insertion at integration sites so that the canonical 5bp insertion into coding sequence could disrupt the function of endogenous protein frequently. On the other hand, PB transposon remains no footprint. Therefore, excision-only-PBase can remove the PB transposon from mutant library clearly. Thus, it is no worry about that PB transposon disrupt non-targeted endogenous gene impair functional analysis if PB mutant library is treated with excision-only-PBase.

In addition, we are going to conduct transposon removal by exicision-only-PBase treatment with several PB mES clones, for the proof of concept that CTRL-Mutagenesis can generate mutant library with no sgRNA cassettes.

5, Most non-coding regions are located at autosomes. Genotyping would be very difficult or even impossible by the current PCR based strategy.

→ Thank you very much for your comment, and we agree with your suggestion.

This is one of our issues.

We expect that CTRL-Mutagenesis could be valid on other biallelic locus.

Therefore, we raised predicted issue such as complex genotyping and proposed one solution.

When we target other biallelic locus, we must determine whether the combination of mutations induced are cis- or trans-mutations. Haplotype phasing, combined long-read sequencing with SNP markers within ROI on maternal/paternal chromosome, assembles each allele via SNP markers on each read [PMID: 35710642]. Therefore, combining CTRL-Mutagenesis on heterozygotic alleles of cells derived from such as human or murine hybrid with haplotype phasing might simplify genotyping.

We will add the following sentences:

“In this study, CTRL-Mutagenesis was validated by genotyping on mono allele in male mES cells to avoid investigating whether the combination of mutations induced are cis- or trans-mutations. All genotypes on Mirc56 should be hemizygous and these mutations induced might be cis-mutations so that we determined the genotypes by amplifying approximately 200 bp around the target sites. However, we did not confirm large mutations such as deletion of the genomic region between target sites and inversion. Long-read sequencing might capture their large mutations. Besides, we also expect that CTRL-Mutagenesis could be valid for ROI on biallelic autosome and X chromosome in female. Therefore, it is required to determine whether the combination of mutations induced are cis- or trans-mutation. Haplotype phasing, combined long-read sequencing with SNP markers within ROI on maternal/paternal chromosome, assembles each allele via SNP markers on each read [PMID: 35710642]. Therefore, combining CTRL-Mutagenesis on heterozygotic alleles of cells derived from such as human or murine hybrid with haplotype phasing might simplify genotyping.” in the Discussion.

Moreover, genome-wide NGS and nanopore Cas9-treated sequencing (nCATs) could also help us to read the mutations without PCR-amplification. However, both methods can obtain reads of target regions with low frequency. Therefore, it is difficult to perform multiplex samples for mutant library.

*6, Fig 4C, large amounts of Cas9 independent EGFP positive cells suggest the current system is not efficient. *

→ Thank you very much for your comment.

We cannot agree with your indication.

In fact, by the cutoff set in Cas9-untreated cells, the EGxxFP system successfully selected at least 76 mutant clones (87.4%) harboring mutations within Mirc56_1 to Mirc56_13. Moreover, we could seed 180 single-cells for single cloning by FACS once.

To enhance this point, we added the following sentences:

“Moreover, at least 76 out of 87 PB mES clones have mutations within all analysed Mirc56_Xs (Figure 5C). Therefore, the EGxxFP system could selected ROI mutant mES clones efficiently.” following to “…depended on integrated sgRNA cassettes.” in the Discussion (page13, line 355)

*Reviewer #4 (Significance (Required)):

The authors claim "Functional analysis" in the manuscript title but there is no evidence of functional analysis in the manuscript.*

→ Thank you very much for your suggestion, and we agree with your suggestion.

In this paper, we just validated PiggyBac system for CRISPRko tilling mutagenesis and expanded the length of target regions.

To change our tone that claiming usability of our method for functional analysis, we will change the following sentences:

• Change “to identify functionally important elements in non-coding regions” to “to induce diverse combination and variety of mutations within more than 50 kb non-coding region” in the Title.
• Add “However, not much loss-of-function screens of non-coding regulatory elements has been conducted due to ambiguous annotations compared with protein-coding genes. Tiling mutagenesis has been employed to identify critical regions embedded in non-coding regulatory elements by comparative analysis through a mutant library harbouring subtly different regions mutated within less than 15 kb region. Conventional tiling mutagenesis construct a mutant library integrated multiple sgRNA cassettes by retroviral delivery. However, multiple integration of single guide RNA (sgRNA) cassettes has higher risk of non-targeted endogenous gene disruptions and may impair functional analysis. Herein, combining tiling mutagenesis and PiggyBac transposon that can be removed with no footprint on integrated sites, we established an expanded tilling mutagenesis method named CRISPR- & Transposase-based RegionaL Mutagenesis (CTRL-Mutagenesis). We demonstrated that PiggyBac system could integrated diverse combinations and varieties of sgRNA cassettes.and then CTRL-Mutagenesis randomly induces diverse combination and variety of mutations within more than 50 kb non-coding region in murine embryonic stem cells. CTRL-Mutagenesis would apply for wider non-coding regulatory elements with no risk of non-targeted endogenous gene disruptions.” in the Abstract.
• Delete “Comparative analysis of mutants harbouring subtly different mutations within the same region would facilitate the further study of cis-element and microRNA clusters.” in the Abstract (page2, line 38-40).
• Change “The generated random mutant mES clone library could facilitate further functional analyses of non-coding regulatory elements within the genome.” to “The generated random mutant mES clone library could develop to investigate critical regions of non-coding regulatory elements within the genome.” In the Introduction (page4, line 88-90).