DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_41953

Curator: @scibot

SciCrunch record: RRID:BDSC_41953

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_56868

Curator: @scibot

SciCrunch record: RRID:BDSC_56868

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_55339

Curator: @scibot

SciCrunch record: RRID:BDSC_55339

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_58190

Curator: @scibot

SciCrunch record: RRID:BDSC_58190

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_38524

Curator: @scibot

SciCrunch record: RRID:BDSC_38524

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_42632

Curator: @scibot

SciCrunch record: RRID:BDSC_42632

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_56937

Curator: @scibot

SciCrunch record: RRID:BDSC_56937

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_60074

Curator: @scibot

SciCrunch record: RRID:BDSC_60074

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_58224

Curator: @scibot

SciCrunch record: RRID:BDSC_58224

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_61284

Curator: @scibot

SciCrunch record: RRID:BDSC_61284

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53692

Curator: @scibot

SciCrunch record: RRID:BDSC_53692

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53024

Curator: @scibot

SciCrunch record: RRID:BDSC_53024

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_56868

Curator: @scibot

SciCrunch record: RRID:BDSC_56868

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_60401

Curator: @scibot

SciCrunch record: RRID:BDSC_60401

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53673

Curator: @scibot

SciCrunch record: RRID:BDSC_53673

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_55339

Curator: @scibot

SciCrunch record: RRID:BDSC_55339

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_32495

Curator: @scibot

SciCrunch record: RRID:BDSC_32495

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_42632

Curator: @scibot

SciCrunch record: RRID:BDSC_42632

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_32982

Curator: @scibot

SciCrunch record: RRID:BDSC_32982

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_56937

Curator: @scibot

SciCrunch record: RRID:BDSC_56937

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_55295

Curator: @scibot

SciCrunch record: RRID:BDSC_55295

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_58224

Curator: @scibot

SciCrunch record: RRID:BDSC_58224

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_44107

Curator: @scibot

SciCrunch record: RRID:BDSC_44107

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53692

Curator: @scibot

SciCrunch record: RRID:BDSC_53692

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_36746

Curator: @scibot

SciCrunch record: RRID:BDSC_36746

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53024

Curator: @scibot

SciCrunch record: RRID:BDSC_53024

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_56999

Curator: @scibot

SciCrunch record: RRID:BDSC_56999

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_61878

Curator: @scibot

SciCrunch record: RRID:BDSC_61878

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_60401

Curator: @scibot

SciCrunch record: RRID:BDSC_60401

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53673

Curator: @scibot

SciCrunch record: RRID:BDSC_53673

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_62314

Curator: @scibot

SciCrunch record: RRID:BDSC_62314

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_32495

Curator: @scibot

SciCrunch record: RRID:BDSC_32495

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_32982

Curator: @scibot

SciCrunch record: RRID:BDSC_32982

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_58292

Curator: @scibot

SciCrunch record: RRID:BDSC_58292

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_62503

Curator: @scibot

SciCrunch record: RRID:BDSC_62503

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_55295

Curator: @scibot

SciCrunch record: RRID:BDSC_55295

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_44107

Curator: @scibot

SciCrunch record: RRID:BDSC_44107

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_55991

Curator: @scibot

SciCrunch record: RRID:BDSC_55991

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_60478

Curator: @scibot

SciCrunch record: RRID:BDSC_60478

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_36746

Curator: @scibot

SciCrunch record: RRID:BDSC_36746

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_50654

Curator: @scibot

SciCrunch record: RRID:BDSC_50654

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_62535

Curator: @scibot

SciCrunch record: RRID:BDSC_62535

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_56999

Curator: @scibot

SciCrunch record: RRID:BDSC_56999

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_51494

Curator: @scibot

SciCrunch record: RRID:BDSC_51494

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_60496

Curator: @scibot

SciCrunch record: RRID:BDSC_60496

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_61878

Curator: @scibot

SciCrunch record: RRID:BDSC_61878

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_62314

Curator: @scibot

SciCrunch record: RRID:BDSC_62314

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_58292

Curator: @scibot

SciCrunch record: RRID:BDSC_58292

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_53691

Curator: @scibot

SciCrunch record: RRID:BDSC_53691

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_57831

Curator: @scibot

SciCrunch record: RRID:BDSC_57831

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_62503

Curator: @scibot

SciCrunch record: RRID:BDSC_62503

What is this?

DOI: 10.1534/g3.119.400581

Resource: RRID:BDSC_55991

Curator: @scibot

SciCrunch record: RRID:BDSC_55991

What is this?

DOI: 10.1093/jnci/djae091

Resource: Microsoft Excel (RRID:SCR_016137)

Curator: @vtello

SciCrunch record: RRID:SCR_016137

What is this?

DOI: 10.1016/j.xpro.2024.103233

Resource: RRID:Addgene_121513

Curator: @vtello

SciCrunch record: RRID:Addgene_121513

What is this?

DOI: 10.1016/j.isci.2024.110668

Resource: (Cell Signaling Technology Cat# 12075, RRID:AB_2728830)

Curator: @vtello

SciCrunch record: RRID:AB_2728830

What is this?

adverb ❌. Rowdy is the characteristic that the behavior had. It answers to the question which characteristics do the behavior had not to how was it exhibited.

no memory

yes!

?

this statement I agree with 100%

which would necessitate training and oversight (but I'm not opposed to the concept of 'task-sharing' as I understand it, across professions --but to use a weird analogy, we can't solve the mental health provider crisis by calling everyone a therapist any more than we can solve the national debt by printing off more dollar bills. IMHO.

again, unclear to me what is implied or envisioned by 'task-sharing' here.

sounds catchy, but what the heck does this mean, exactly? And what are the multitude of implications??

what meaneth you here?

agreed, to an extent. I guess it depends on how the term 'specialist' is conceptualized in this article and beyond.

hmmm...or greater numbers of TRAINED professionals. A lot of damage is and has been done by those with limited training who step into mental health care in ways that are beyond their capacity. We can't just solve a problem by lowering professional standards and saying, 'well, actually, anyone can do this' - when there is a lot of evidence that calls for greater caution and safeguards to the public than that.

Spacing issue with the poem below.

We need a space before bullet points.

Space here before bullet points.

https://www.theguardian.com/environment/article/2024/aug/14/how-does-today-extreme-heat-compare-with-earth-past-climate

Wow, it's in Ireland too?!

I love the fact that my personal website is physically the last word in the book and therefore "gets the last word."

You have to love that one of the final sections of the book is "There is No One System". This gives the reader the confidence to explore and experiment to see what works for them.

Doto wastes no time getting into the most important aspects of note taking. Even before the book has begun, the copyright page in the front matter is getting you ready for what is about to come:

Please cite the author and book when quoting.

Doto, Bob. A System for Writing: How an Unconventional Approach to Note-Making Can Help You Capture Ideas, Think Wildly, and Write Constantly - A Zettelkasten Primer. 1st ed. New Old Traditions, 2024. https://amzn.to/3ztjrfb.

A previous version of this page contains an erroneous definition of mutual independence of events and sigma-algebra. We apologise for any confusion caused. See the following page for a more thorough discussion: https://imperialmathswiki.com/en/1st_year/MATH40005_Probability_and_Statistics/4#independence

The daily cards and journal entries are obviously indexed by chronological date and then within tabbed sections by month and year.

The rest of the other cards with notes are given individual (decimal) numbers and and then are put into numerical order. These numbered cards are then indexed by putting related subject/topic/category words from them onto a separate index card which cross references either a dated card or the numbered card to which it corresponds. These index cards with topical words/phrases are then filed alphabetically into a tabbed alphabetical section (A-Z).

As an example with the card in this post, if I wanted to remember all the books I buy from Octavia's Bookshelf, then I'd create a card titled "Octavia's Bookshelf" and list the title along with the date 2024-08-13 and file it alphabetically within the "O" tab section of the index. Obviously this might be more useful if I had more extensive notes about the book or its purchase on the 2024-08-13 card. I did create a short journal card entry about the bookstore on 08-13 because it was the first time I visited the bookstore in it's new location and decor, so there are some scant notes about my impressions of that which are cross-indexed to that Octavia's Bookshelf card. Thus my Octavia's Bookshelf card has an entry with "The Book Title, 2024-08-13 (J)(R)" where the '(J)' indicates there's a separate journal entry for that day and the '(R)' indicates there's also a receipt filed next to that day's card.

I also created an "Author Card" with the author of the book's name, the title, publication date, etc. I included the purchase date and the reason why I was interested in the book. I'll use that same card to write notes on that particular book as I read it. These author cards are filed in a separate A-Z tabbed 'Bibliography' section for easily finding them as well. (I suppose I could just put them into the primary A-Z index, but I prefer having all the authors/books (I have thousands) in the same section.)

I also have a rolodex section of people filed alphabetically, so I can easily look up Steve and Sonia separately and see what I might have gotten them on prior birthdays as well as notes about potential future gift ideas. I had tickler cards with their names on them filed in early August and now that they're in my to do list, I've moved those cards to August 2025, ready for next year's reminder. Compared to a typical Future Log I don't do nearly as much writing and rewriting when migrating. I just migrate a card forward until it's done or I don't need it anymore.

If you've used a library card index before, the general idea is roughly the same, you're just cross-indexing more than books by title, author and subject. You can index by day, idea, project, or any other thing you like. My card index cabinet is really just a large personal database made out of paper and metal.

The secret isn't to index everything—just the things you either want to remember or know you'll want to look up later and use/re-use.

A previous version of this page contains an erroneous definition of mutual independence of events and sigma-algebra. We apologise for any confusion caused. See the following page for a more thorough discussion: https://imperialmathswiki.com/en/1st_year/MATH40005_Probability_and_Statistics/4#independence

I think you want this

tbi_data_upcoded_copy <- copy(tbi_data_upcoded)

Otherwise tbi_data_upcoded_copy will act like a pointer to tbi_data_upcoded, and not like it's own dataset. If you're in data.table that is.

Read this section on Environmental Geography. Then, add a question you have about the environmental geography of our world.

Read this section on Human Geography. Then, add a question you have about the human geography of our world.

Read this section on Physical Geography. Then, add a question you have about the physical geography of our world.

You will be reading about the three kinds of geography- physical, human and environmental. Be thinking of a question you have aboout each one.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

REVIEWER 1

Reviewer #1 Evidence, reproducibility and clarity: Nornes et al. have generated a cohort of arterial enhancers based on in silico analysis and validation with transgenic lines in both zebrafish and mice. They utilized publicly available datasets for chromatin marks, including ATAC-seq on endothelial cells either from cell culture or isolated from mice, as well as EP300 binding, H3K27Ac, and H3K4Me1. Focusing on eight arterial-expressed genes, they identified a putative enhancer region marked by at least one enhancer feature. After validating the activity of these enhancers in zebrafish and mice, the authors assessed the regulatory pathways upstream of these genes. Using ChIP-seq and Cut&Run for key endothelial transcription factors, they discovered that binding sites for SoXF and ETS factors are shared in arterial enhancers, whereas binding sites for Notch, MEF2, and Fox are present only in the subset of identified enhancers. Together this study provides an arterial enhancer atlas that allows further characterisation of regulatory network behind endothelial cell identity.

__Reviewer #1 Major Comment 1: __The authors have assessed 15 enhancers for arterial-venous specificity, by assessing the expression in DA, ISV, cardinal and ventral veins at 2 dpf. Interestingly there is a clear difference in the expression patterns of these enhancers in the zebrafish axial vasculature, especially seen at the level of ISV. The co-localization of the enhancer expression in the endothelium was done using endothelial marks expressed in both venous and arterial EC (kdrl). To fully distinguish if the expression is venous or arterial endothelial compartment colocalization with Tg expressed in arterial (flt1) or venous (lyve1) EC would be informative.

RESPONSE: We agree with the reviewer that a more detailed description of arterial-venous specificity of each enhancer could be included. In the original manuscript, the expression pattern of each enhancer within the vasculature was primarily assessed at 2 days post fertilization (dpf) in Fig 1-2. This identified arteries using direction of blood flow and available descriptive information, as arterial development in 2pdf zebrafish is very stereotypical and already well characterized.

__REVISION (PLANNED): __The original Figure 3A includes a more detailed assessment of arterial-venous specificity at 3dpf for four arterial enhancers (Cxcr4+135, Cxcr4+151, Gja5-78 and Gja5-7, chosen as enhancers representing the four types of expression patterns seen). We will now extend this more detailed analysis to all arterial enhancer:GFP lines. This analysis uses kdrl-mCherry to mark the entire vasculature, comparative to the expression of the arterial enhancers (GFP). This allows us to clearly identify the intersegmental arteries (as opposed to intersegmental veins) by looking for direct connection to the dorsal aorta, and by assessing the direction of blood flow within these vessels. This analysis is done at 3dpf to give time for the intersegmental arteries to acquire identity and connect definitively with the dorsal aorta, and for the diminishment of any GFP expression originating from the initial sprouting from the dorsal aorta. By extending this analysis to the other arterial enhancer zebrafish lines shown in Figure 2, we will be able to more clearly classify the activity of each enhancer within different vascular beds. This information will also be recorded in a new Table better detailing the timing and specificity of activity of each enhancer.

We chose not to use arterial or venous "marker lines" (e.g. Flt1:reporter or Lyve1:reporter) for the simple reason that these are also enhancer:GFP transgenes, and therefore are not necessarily definitive of the arterial or venous lineage per se (e.g. Flt1:GFP expression is controlled by the transcription factors binding the Flt1 enhancer in the same way that Cxcr4+135 and the others are, with the added caveat that the transcriptional regulation of the Flt1 and Lyve enhancers are not well defined). We felt that morphological determination based on direct connections and blood flow direction was therefore more accurate.

__Reviewer #1 Major Comment 2: __In addition, it is striking that cxc4+135 drives the expression in nearly every ISV as cxcl12+269 only every other. Similarly, not all the enhancers are enriched in the DA to the same level. Is there biological significance to this? could authors discuss these results further? The pattern of expression of the unc5b-identified enhancer is also striking, does this reflect the known roles of unc5b in the vascular formation?

__RESPONSE: __We agree, the diversity of enhancer expression patterns within the arterial compartment is notable, and really very interesting. The variations in enhancer expression pattern must be largely influenced by the transcription factor motifs within each enhancer, as these patterns were seen in both transient and stable transgenic zebrafish and therefore largely independent of chromatin integration location.

__REVISION (PLANNED): __The extension of Figure 3A to all enhancer lines (see previous comment) will permit us to more clearly classify the activity of each arterial enhancer within different beds and at different time points. Currently there were no clear links between a particular transcription factor motif/binding and expression pattern, something that is discussed briefly in the original Results and Discussion sections. However, the expansion of Figure 3A to all enhancers, and the creation of a Table summarizing this more systematically will make the link (or lack of one) between expression patterns within the arterial tree and TF motifs easier to appreciate and discuss.

__Reviewer #1 Major Comment 3: __The final part of the paper focuses on defining the presence of "deeply conserved" transcription factor binding sites (TFSB), defined as TFBS that are as conserved as the enhancer sequence surrounding them. In literature, the term 'deep conservation' refers to evolutionary conservation (genomic sequence preservation) in a wide range of species. Therefore, the additional classification presented by the authors based on the surrounding sequence is not clear. As, the KLF motifs in the Ece1in1, which is conserved between mouse and human, are defined as "deeply conserved". However, the FLK motif in the following enhancer, Flk1in10 (one line below), gets classified as non-deeply conserved, despite also being conserved between mouse and human. Thus, in the current form, there is a contradiction in the way the authors use the term 'deeply conserved' and the accepted meaning of this term. To avoid confusion, it would be important to revise this nomenclature.

RESPONSE: We agree that this nomenclature should be revised. Our aim was to develop a standard approach to transcription factor motif analysis that could be applied to enhancers regardless of conservation levels and size, and easily replicated by others. Because not all functional transcription factor motifs within enhancers are necessarily conserved between species, we were careful to label both conserved and non-conserved motifs for each TF examined. Nonetheless, extra emphasis was placed on motifs with confirmatory TF binding evidence (e.g. ChIP-seq/CUT&RUN), and those conserved at the same depth as the surrounding sequence. This was because our previous work on endothelial enhancers clearly indicates that these motifs are far more likely to play a key role in regulation. However, the reviewer is correct to note that referring to such motifs as "deeply" conserved could be misinterpreted.

REVISION (COMPLETED): We have altered our nomenclature. This is explained in the relevant Results sections: "Because the level of conservation of motifs can often be an indication of their importance to enhancer activity, we classified each motif into three categories: strongly conserved (motif conserved to the same depth of the surrounding sequence), weakly conserved (motif conserved in orthologous human enhancer but not to the same depth as the surrounding sequence) and not conserved (motif is not conserved within the orthologous human sequence)".

Two enhancers (Unc5b-57 and Cdh1-1) were only conserved human-mouse, therefore each TF motif within these enhancers could be annotated as both weakly and strongly conserved. As the reviewer noted, this does create confusion. We have now adjusted Figure 5 to use a distinct shape for motifs for which no distinction between weak and strong motif can be made. This does not cover Ece1in1, which is conserved human-mouse-tenrec but was erroneously originally labelled human-mouse only. This error has been corrected.

__Reviewer #1 Minor Comment 1: __Details on how the corresponding non-coding regions between mice and humans were established are missing, what alignment tool was used?

RESPONSE AND REVISION (COMPLETED): This information has now been included in the relevant Results section: "Orthologous human enhancer sequences were identified for every enhancer using the Vertebrate Multiz Alignment & Conservation Track on the UCSC genome browser"

__Reviewer #1 Minor Comment 2: __Not sufficient details are provided for the re-analysis of siRNA data. E.g., which clustering method was used? How the clusters were assigned to cell identities?

RESPONSE AND REVISION (COMPLETED): The details regarding the re-analysis of scRNA data has been expanded in the Methods sections: "Publicly available E12 and E17.5 scRNA-seq data from EC isolated from BmxCreERT2;RosatdTomato lineage traced murine hearts54 was obtained from GEO (GSE214942) prior to processing FASTQ files with the 10X Genomics CellRanger pipeline (V7.0.0). RNA-seq reads were aligned to the mm10 genome reference downloaded from 10X Genomics with the addition of the TdTomato-WPRE sequence. Exclusion of low quality cells with either a UMI count >100,000, total gene count 10%) was performed using Scater55. Data normalisation was performed using the MultiBatchNormalisation method prior to merging of TdTomato positive and negative datasets from individual timepoints. The top 2000 most highly variable genes (excluding mitochondrial and ribosomal genes) in the merged datasets were identified using the Seurat FindVariableFeatures method and utilised to calculate principal component analysis (PCA). Normalised data was scaled using the ScaleData function. Cell clustering was performed using the standard unsupervised graph-based clustering method implemented within Seurat (V4)56. Clusters were visualised in two dimensions using UMAP based non-linear dimensional reduction following the standard Seurat (V4) workflow49. Identified clusters were assigned identities based on marker genes shown to be differentially expressed between populations previously identified in the original study47. Key markers include Npr3 (endocardial), Fabp4 (coronary vascular endothelial), and Nfatc1 (valvular endothelial). The E12.5 sinus venosus EC cluster was assigned based in Aplnr as previously described54. Arterial and venous EC clusters in the E17.5 datasets were annotated based on their enriched expression of Gja5 and Nr2f2, respectively."

__Reviewer #1 Minor Comment 3: __Details about the first HOMER analysis (in the assessment of transcription factor motifs and binding patterns at arterial enhancers) seem to be missing from the methods section.

RESPONSE AND REVISION (COMPLETED): This has been included in the methods: "Analysis of overrepresented motifs within our validated arterial enhancer cohort was performed with HOMER's findMotifsGenome tool using the full validated region of the arterial enhancers. The analysis used the hg38 masked genome and otherwise default settings for all other parameters including randomly selected background regions".

__Reviewer #1 Minor Comment 4: __Pg 12: "For ETS, 23/23 arterial enhancers contained at least one conserved motif (all "deeply" conserved to the same depth as the surrounding enhancer, see S7)". Is it S8, where conservation is indicated?

__ ____RESPONSE AND REVISION (COMPLETED):__ We have corrected this error in the text - no figure actually needed to be referenced here as the previous sentence contained the full list of relevant figures to this statement (Table 2 and Figures 5 and S9, previously called S8, are the places to see this information).

__Reviewer #1 Minor Comment 5: __Figure 1 and 2 for non-zebrafish readers it would be useful to indicate in Figures 1 and 2 the non EC expression that can be observed in the embryos.

RESPONSE AND REVISION (COMPLETED): In addition to arterial expression, a number of the enhancer:GFP transgenes also showed GFP expression within the neural tube. In addition, some transient transgenic embryos also showed ectopic expression in muscle fibres. These have now been indicated on the images in Figure 1 and 2.

__Reviewer #1 Minor Comment 6: __Table S1: Please, indicate in the legend what the asterisk in the H DNAseI column stands for

RESPONSE AND REVISION (COMPLETED): The asterisk indicates where DNaseI hypersensitivity is also seen in multiple non-EC lines. This explanation has been added to the legend.

__Reviewer #1 Minor Comment 7: __Figure S8: The phrasing "conserved to animal" in Figure S8 is misleading. There is no difference in something being conserved to tenrec or manatee, as both are Afrotherians. Hence, the data show that both Efnb2-141 and Ephb4-2 were present in the common ancestor of Afrotherians and humans, namely the ancestor of all placentals. Instead, it would be good to indicate the phylogenetic group for which the presence of the enhancer can be inferred (in this case, Placentalia).

__RESPONSE: __Whilst I appreciate the point, it is the exact sequence that is important here - obviously tenrec and manatee are similar species but still contain differences in nucleotide sequences. The information about conservation leads the reader to the exact species with which the comparison is being made. We tried to restrict this to just one species per phylogenetic group (e.g. tenrec, opossum, chicken, zebrafish) but occasionally this was not possible.

Reviewer #1 Significance

To date, a systematic approach to identifying the regulatory networks driving endothelial cell identity is missing. This study provides important datasets and validation of enhancers involved in arterial gene expression and the associated transcription factors. Although this is only the tip of the iceberg, this work represents a significant milestone in the systematic understanding of how arterial gene expression is regulated. Overall, this study offers a powerful resource for understanding arterial gene regulation and conducting genome-wide studies of arterial enhancers.

__RESPONSE: __We thank the reviewer for these kind words. Whilst we agree this is only a very small snapshot of all the arterial enhancers involved in gene regulation, we would like to stress that not only is this a massive increase to what has been known previously, but is also deliberately focused on the genes used to define arterial identity during development and in the adult, therefore these enhancers by themselves form an extremely valuable dataset with which to study the key factors driving arterial differentiation and identity.

__ __

REVIEWER 2

__Reviewer #2 Evidence, reproducibility and clarity: __In this work, Nornes and collaborators have described a cohort of arterial enhancers that drive gene expression in arteries and not in veins. The paper is very well written and it is very informative. The authors have used in silico models to identified the potential artery enhancers and then used different developmental in vivo systems, zebrafish and mice, to validate their findings. Finally, the authors have explored what transcription factors may be binding the identified enhancer sequences and thus, drive arterial gene expression. I would like to congratulate the authors for this work that it has been a pleasure to read and review.

Reviewer #2 Major Comment 1: In their identification of enhancers, the authors consider a candidate every enhancer that has a putative mark in both mouse and human. Nevertheless, all the human data comes from in vitro analysis. Considering how much cell culture affects endothelial cell identity, inducing effects like EndoMT, would this have any effect on the enhancer selection? Would it be possible to search any human in vivo data? Would this allow for even stronger and more relevant sequences?

__RESPONSE: __We agree that the use of human endothelial cells in culture raises some potential issues. However, we stress that the mouse EC enhancer marks, which played a key role in defining putative enhancers, come from in vivo analysis (E11 embryos, P6 retina and adult aorta), limiting the potential for significant impact from cell culture-induced issues. Whilst we would have enthusiastically incorporated human in vivo data had it been available, our approach was still indisputably successful at identifying arterial enriched/specific enhancers.

We consider it unlikely that culture/identity-related problems with human cultured ECs led to a significant undercount of enhancers, in part because comparatively few regions with enhancer marks in mouse in vivo ECs were excluded due to the absence of human enhancer marks. In fact, Cxcr4, Cxcl12, and Gja5 were poorly transcribed in the human cell lines studied here and consequently only enhancer marks in mouse were used to define putative enhancers for these three genes (this is clearly stated in the Results section). If a similar rational had applied to the remaining five genes, only an additional six putative enhancers would have been tested (one for Gja4, two for Nrp1 and three for Unc5b). However, we felt it made sense to include analysis of human enhancer marks for these five genes, as all were expressed in the human ECs used (as indicated by H3K1Me3 and DNaseI hypersensitivity at promoter regions) and orthologous human enhancers were identified for all. Additionally, our retrospective analysis of previously described mammalian in vivo-validated EC enhancers (Table S1 in the original manuscription, including eight arterial enhancers) found that all 32 were marked by at least one enhancer mark in human samples (1/32 did not contain mouse enhancer marks). We also tested eleven regions that did not reach our putative enhancer threshold, including five with only mouse marks. None of these directed expression in transgenic analysis.

Reviewer #2 Major Comment 2: The human data comes from vein endothelial or microvasculature endothelial cells. Specially because some of the enhancers identified by the authors drive also vein expression, could the authors discriminate whether this is due to the identification coming from vein cells. Is there available data from HAECs? Would this not be conceptually more correct that using vein endothelial cells data? This should be at least discussed in the paper.

__RESPONSE AND REVISION (COMPLETED): __We have now included a comparison with enhancer marks from HAECs, telo-HAECs and HUAECs as a new Figure S5. The enhancer marks seen in these cells were very similar to those in the HUVEC and microvascular cells already surveyed. Had enhancer marks within HAECs/telo-HAEC/HUAECs been included as a human enhancer mark in our initial survey, it would have been unlikely to have altered our analysis, although we agree it would have made it more conceptually correct. We chose not to go back and engineer this into our original enhancer selection rational however as we felt it would be intellectually dishonest. A paragraph has been added to the Results section about this analysis.

Reviewer #2 Major Comment 3: Although the authors use the mouse embryo to further validate their finding beyond the zebrafish, the expression are a bit different. While on the fish the enhancers label smaller vessels of arterial identity, in the mouse, only bigger arteries are marked. Is this defined by the time of the analysis?

__RESPONSE: __This experiment was conducted to demonstrate that these enhancers were arterial enriched in both zebrafish and mouse transgenesis, and feel this is clearly shown by the current data. Whilst I do not really agree that the expression pattern is different (for example, the Gja5 enhancers are more restricted to the major arteries in both zebrafish and mouse, compared to the more widely expressed Efnb2-333), this is challenging to ascertain at a single time-point in a transient transgenic mouse assay. Whilst it would be potentially interesting to better assess the activity of these enhancers over time in mice, we consider this a lengthy experiment (multiple stable lines would need to be established and characterized for each enhancer) which would not add particular benefit to this paper.

Reviewer #2 Major Comment 4: The analysis of the enhancers is only done during development. Is the activity of these enhancers maintained through live or only important for artery vs vein determination? Is the expression of the different enhancer reporters maintained into adulthood?

RESPONSE AND REVISION (PLANNED): We agree this would be interesting to ascertain. We plan to examine the activity of enhancer:GFP activity in adult fish fins (which are accessible even without crossing into a casper background, which is beyond the timescale of this project) in the fully revised version of this paper. We have already conducted a feasibility study on four arterial enhancers:GFP lines (Gja5-7:GFP, Gja5-78:GFP, Gja4+40:GFP and Efnb2-333:GFP), which found that all four were still active, and arterial-specific, in the adult.

Reviewer #2 Significance

This is a very well done study with potential interest for vascular biologists, in particular to those interested in the determination between artery and veins in a context of development. It advances our knowledge on the field of vascular biology as it not only proposes potential enhancers but also goes on to validation of the enhancers. Nevertheless, it is important to note that some of this enhancers have been identified from in vitro human data. In vitro culture of endothelial cells affects their cellular identity and thus, this study may have underscored many potential enhancers.

REVIEWER 3

__Reviewer #3: Evidence, reproducibility and clarity: __This manuscript by Nornes et al analyzed multiple published databases and identified a group of putative enhancers for 8 selected non-Notch arterial genes in mouse and human ECs. These enhancers were cloned and screened in fish embryos to test their effect in driving GFP reporter expression, which narrowed down a cohort of enhancers for further testing of expression activities in mouse embryonic arteries. The authors then analyzed the sequences of these enhancers, and identified binding motifs of ETS, SOX-F, FOX and MEF2 family TFs and Notch transcription regulator RBPJ commonly present in closed proximity in these arterial enhancers, suggesting interaction between these TFs in determination of arterial identity.

Reviewer #3 Major Comment : This study provides an enormous amount of bioinformatic data analysis and screening results in transgenic fish and mouse models, which led to the discovery of a group of arterial enhancers and TFs binding motifs essential in regulating arterial identity.

Reviewer #3 Other Comments ____1: Choice of arterial genes is slightly biased. Acvrl1/Alk1 is not enriched in arterial ECs. Sema3G, which is highly expressed in arterial ECs, is missing. UNC5B is enriched in arterial ECs but also expressed by sprouting ECs (PMID: 38866944).

__RESPONSE: __When we started this project, scRNA-seq datasets in the developing vasculature were less available. Consequently, we initially based our choice of genes on data from Raftrey et al., Circ Res 2021 (available earlier on bioRxiv), which was focused on mouse coronary arterial ECs at the timepoints that arteries differentiate. This found Acvrl1 to be arterial enriched (not a novel observation, many publications treat Acvrl1 as arterial specific or arterial-enriched) and did not list Sema3g. We also considered a wider dataset from mouse and human mid-gestation embryos when available (Hou et al., Cell Research 2022). However, it is important to note that we did not aim to investigate every arterial-enriched gene, rather to use these datasets to help identify loci associated with gene expression patterns which indicated a high likelihood of containing arterial enhancers active during arterial differentiation.

Sc-RNAseq data from both Raftery et al., and Hou et al., indicated that arterial ECs are subdivided into two groups, reflecting maturity but also potentially slightly different developmental trajectories. The genes studied here were therefore selected to evenly cover both subgroups, with Acvrl1, Cxcl12, Gja5 and Nrp1 primarily restricted to the mature arterial EC subgroup, while Cxcr4, Efnb2, Gja4 and Unc5b were also expressed in the less mature/arterial plexus/pre-arterial EC subgroup. It is notable that genes within the latter subgroup are also associated with angiogenic/sprouting ECs (Dll4 also belongs to this subgroup), which likely indicates biological links between angiogenesis and arterial identity rather than a problem in gene choice and specificity.

__REVISION (COMPLETED): __This is already discussed in the Results section (angiogenic expression of arterial genes is discussed within the MEF2 and RBPJ sections) and in the Discussion (paragraph 2, referring to different expression patterns within arterial ECs). However, we have now edited the relevant Results section to better explain gene selection: "It is therefore clear that a better understanding of the regulatory pathways directing arterial differentiation requires the identification and characterization of a larger number of arterial enhancers directing the expression of key arterial identity genes. To identify a cohort of such enhancers, we looked in the loci of eight non-Notch genes: Acvrl1(ALK1) Cxcr4, Cxcl12, Efnb2, Gja4(CX37), Gja5 (CX40), Nrp1 and Unc5b. Although not a definitive list of arterial identity genes, single cell transcriptomic analysis indicates these genes are all significantly enriched in arterial ECs4,20, and are commonly used to define arterial EC populations in mouse and human scRNAseq analysis4,5,20,54. Additionally, single-cell transcriptomic data indicates that arterial ECs can be divided into two subgroups4,20. The genes selected here are equally split between subgroups (Acvrl1, Cxcl12, Gja5 and Nrp1 from the mature arterial EC subgroup, Cxcr4, Efnb2, Gja4 and Unc5b from the less mature/arterial plexus/pre-arterial EC subgroup)4,20. We did not exclude genes also implicated in angiogenesis/expressed in sprouting ECs, as these genes formed that vast majority of those associated with the less mature EC subgroup".

Reviewer #3 Other Comments ____2: Exclusion of Notch genes. Although the reason for choosing non-notch genes and excluding notch genes for screening is addressed in this paper, it would be interesting to examine how the arterial enhancers identified in this study are present in the Notch genes, especially Dll4 (enriched in arterial and sprouting ECs) and Jag1 (enriched in arterial ECs).

__RESPONSE: __Previous work from our lab and others has already examined arterial enhancers for Notch pathway genes. We already included these enhancers in all our later analysis (Figure 5-6 and relevant supplemental figures), including analysis of TF motifs.

Reviewer #3 Other Comments ____3: SoxF family TFs. Among the 3 members of SoxF TFs, only Sox17 and Sox7 were assessed. Though not specific, Sox18 is highly expressed in the arteries. On the contrary, Sox7 is highly expressed in the vein and shows weak expression in arterial ECs (PMID: 26630461).

__RESPONSE AND REVISION (PLANNED): __We agree. We will include assessment of SOX18 binding in our final revised manuscript. An antibody for this analysis has been identified already.

Reviewer #3 Other Comments ____4: Minor inaccuracy in Intro/paragraph 3: though sox17 is reported as indispensable for arterial specification (PMID: 24153254), losing a single SoxF factor does not seem to completely compromise the arterial program (PMID: 24153254, PMID: 26630461). A combined loss of Sox17/18, or Sox 7/17/18, seems to do the job (PMID: 26630461).

__RESPONSE: __We have altered this section: "The evidence linking SOXF transcription factors to arterial differentiation is more extensive, with loss of either SOX17 (the SOXF factor most specific to arterial ECs) or SOX7 resulting in arterial defects21-24. Whilst losing a single SOXF factor does not entirely compromise the arterial program, arterial differentiation appears absent after compound Sox17;Sox18 and Sox7;Sox17;Sox18 deletion, although this occurs alongside significantly impaired angiogenesis and severe vascular hyperplasia21-24. PMID 24153254 is reference 23, PMID 26630461 is reference 24.

Reviewer #3 Other Comments ____5: Fig.4 e14.5 mouse embryos. If the observation aims to assess the dorsal aorta, it would be better to use mouse embryos at mid-gestation (e9.5-10.5), when the paired DAs are formed with arterial identity but haven't been remodelled and fused as one single aorta. The morphological data in this figure would be better to show the colocalization of LacZ expression and an arterial marker (e.g. Sox17) using immulfluorescence staining instead of purely lacZ.

RESPONSE: This experiment was primarily conducted to demonstrate that our enhancers were arterial enriched in both zebrafish and mouse transgenesis, and feel this is clearly shown with the e14.5 transgenic embryos originally shown. We chose e14.5 because it matched the timepoints used for the single cell transcriptomics first used to select the target arterial identity genes, and feel it is a good match to 2-3 dpf zebrafish in terms of arterial differentiation mechanisms. We agree that E9-10 would have also been an additional useful timepoint, but we do not have the resources to generate this data nor consider it essential for the conclusions of our work here.

__REVISION (PLANNED): __We are unable to perform immunofluorescence in the e14.5 transgenic embryos due to the fixation and staining solutions used for X-gal staining (which was done by an external company and could not be altered), but agree additional information is needed to demonstrate arterial endothelial specificity. We will therefore expand the analysis of sectioned embryos (currently restricted to just the Efnb2-333:LacZ transgene) to all enhancers shown in Figure 4. This analysis has some limitations due to infiltration of the X-gal solution to deeper tissues, but is anticipated it will clearly show enhancer activity in arterial endothelial cells rather than venous ECs or smooth muscle cells.

__Reviewer #3 (Significance (Required)): __This novel work establishes an important foundation for future understanding of how TFs may interact to determine arterial specification.

Other revisions

In addition to changes suggested by the reviewers, we also made one additional adjustment to the paper to include analysis of two additional putative enhancers (Efnb2-159 and Cxcr4+119). These were initially omitted in error yet both regions reach the standard of testable putative enhancers (noted in small changes to Figure S1 and Table S2). When tested in zebrafish transient transgenic embryos, Cxcr4+119 was inactive whilst Efnb2-159 was active in arterial endothelial cells. The relevant tables and figures have been adjusted to reflect these changes, the most significant of which are the inclusion of Efnb2-159 positive zebrafish in Figure 1 (and the necessity to create an additional supplemental Figure (S3) to accommodate the increased number of images), and analysis of Efnb2-159 transcription factor motifs/binding as part of Figure 5 and 6. No conclusions were altered by the inclusion of this additional data.

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

This manuscript by Nornes et al analyzed multiple published databases and identified a group of putative enhancers for 8 selected non-Notch arterial genes in mouse and human ECs. These enhancers were cloned and screened in fish embryos to test their effect in driving GFP reporter expression, which narrowed down a cohort of enhancers for further testing of expression activities in mouse embryonic arteries. The authors then analyzed the sequences of these enhancers, and identified binding motifs of ETS, SOX-F, FOX and MEF2 family TFs and Notch transcription regulator RBPJ commonly present in closed proximity in these arterial enhancers, suggesting interaction between these TFs in determination of arterial identity.

Major comments:

This study provides an enormous amount of bioinformatic data analysis and screening results in transgenic fish and mouse models, which led to the discovery of a group of arterial enhancers and TFs binding motifs essential in regulating arterial identity.

Other comments:

1. Choice of arterial genes is slightly biased. Acvrl1/Alk1 is not enriched in arterial ECs. Sema3G, which is highly expressed in arterial ECs, is missing. UNC5B is enriched in arterial ECs but also expressed by sprouting ECs (PMID: 38866944).
2. Exclusion of Notch genes. Although the reason for choosing non-notch genes and excluding notch genes for screening is addressed in this paper, it would be interesting to examine how the arterial enhancers identified in this study are present in the Notch genes, especially Dll4 (enriched in arterial and sprouting ECs) and Jag1 (enriched in arterial ECs).
3. SoxF family TFs. Among the 3 members of SoxF TFs, only Sox17 and Sox7 were assessed. Though not specific, Sox18 is highly expressed in the arteries. On the contrary, Sox7 is highly expressed in the vein and shows weak expression in arterial ECs (PMID: 26630461). Minor inaccuracy in Intro/paragraph 3: though sox17 is reported as indispensable for arterial specification (PMID: 24153254), losing a single SoxF factor does not seem to completely compromise the arterial program (PMID: 24153254, PMID: 26630461). A combined loss of Sox17/18, or Sox 7/17/18, seems to do the job (PMID: 26630461).
4. Fig.4 e14.5 mouse embryos. If the observation aims to assess the dorsal aorta, it would be better to use mouse embryos at mid-gestation (e9.5-10.5), when the paired DAs are formed with arterial identity but haven't been remodeled and fused as one single aorta. The morphological data in this figure would be better to show the colocalization of LacZ expression and an arterial marker (e.g. Sox17) using immulfluorescence staining instead of purely lacZ.

Significance

This novel work establishes an important foundation for future understanding of how TFs may interact to determine arterial specification.

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

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

In this work, Nornes and collaborators have described a cohort of arterial enhancers that drive gene expression in arteries and not in veins. The paper is very well written and it is very informative. The authors have used in silico models to identified the potential artery enhancers and then used different developmental in vivo systems, zebrafish and mice, to validate their findings. Finally, the authors have explored what transcription factors may be binding the identified enhancer sequences and thus, drive arterial gene expression. I would like to congratulate the authors for this work that it has been a pleasure to read and review.

Major comments:

1. In their identification of enhancers, the authors consider a candidate every enhancer that has a putative mark in both mouse and human. Nevertheless, all the human data comes from in vitro analysis. Considering how much cell culture affects endothelial cell identity, inducing effects like EndoMT, would this have any effect on the enhancer selection? Would it be possible to search any human in vivo data? Would this allow for even stronger and more relevant sequences?
2. The human data comes from vein endothelial or microvasculature endothelial cells. Specially because some of the enhancers identified by the authors drive also vein expression, could the authors discriminate whether this is due to the identification coming from vein cells. Is there available data from HAECs? Would this not be conceptually more correct that using vein endothelial cells data? This should be at least discussed in the paper.
3. Although the authors use the mouse embryo to further validate their finding beyond the zebrafish, the expression are a bit different. While on the fish the enhancers label smaller vessels of arterial identity, in the mouse, only bigger arteries are marked. Is this defined by the time of the analysis?
4. The analysis of the enhancers is only done during development. Is the activity of these enhancers maintained through live or only important for artery vs vein determination? Is the expression of the different enhancer reporters maintained into adulthood?

Significance

This is a very well done study with potential interest for vascular biologists, in particular to those interested in the determination between artery and veins in a context of development. It advances our knowledge on the field of vascular biology as it not only proposes potential enhancers but also goes on to validation of the enhancers. Nevertheless, it is important to note that some of this enhancers have been identified from in vitro human data. In vitro culture of endothelial cells affects their cellular identity and thus, this study may have underscored many potential enhancers.

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

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

Summary:

Nornes et al. have generated a cohort of arterial enhancers based on in silico analysis and validation with transgenic lines in both zebrafish and mice. They utilized publicly available datasets for chromatin marks, including ATAC-seq on endothelial cells either from cell culture or isolated from mice, as well as EP300 binding, H3K27Ac, and H3K4Me1. Focusing on eight arterial-expressed genes, they identified a putative enhancer region marked by at least one enhancer feature. After validating the activity of these enhancers in zebrafish and mice, the authors assessed the regulatory pathways upstream of these genes. Using ChIP-seq and Cut&Run for key endothelial transcription factors, they discovered that binding sites for SoXF and ETS factors are shared in arterial enhancers, whereas binding sites for Notch, MEF2, and Fox are present only in the subset of identified enhancers. Together this study provides an arterial enhancer atlas that allows further characterisation of regulatory network behind endothelial cell identity.

Major comments:

The authors have assessed 15 enhancers for arterial-venous specificity, by assessing the expression in DA, ISV, cardinal and ventral veins at 2 dpf. Interestingly there is a clear difference in the expression patterns of these enhancers in the zebrafish axial vasculature, especially seen at the level of ISV. The co-localization of the enhancer expression in the endothelium was done using endothelial marks expressed in both venous and arterial EC (kdrl). To fully distinguish if the expression is venous or arterial endothelial compartment colocalization with Tg expressed in arterial (flt1) or venous (lyve1) EC would be informative. In addition, it is striking that cxc4+135 drives the expression in nearly every ISV as cxcl12+269 only every other. Similarly, not all the enhancers are enriched in the DA to the same level. Is there biological significance to this? could authors discuss these results further? The pattern of expression of the unc5b-identified enhancer is also striking, does this reflect the known roles of unc5b in the vascular formation? The final part of the paper focuses on defining the presence of "deeply conserved" transcription factor binding sites (TFSB), defined as TFBS that are as conserved as the enhancer sequence surrounding them. In literature, the term 'deep conservation' refers to evolutionary conservation (genomic sequence preservation) in a wide range of species. Therefore, the additional classification presented by the authors based on the surrounding sequence is not clear. As, the KLF motifs in the Ece1in1, which is conserved between mouse and human, are defined as "deeply conserved". However, the FLK motif in the following enhancer, Flk1in10 (one line below), gets classified as non-deeply conserved, despite also being conserved between mouse and human. Thus, in the current form, there is a contradiction in the way the authors use the term 'deeply conserved' and the accepted meaning of this term. To avoid confusion, it would be important to revise this nomenclature.

Minor:

Details on how the corresponding non-coding regions between mice and humans were established are missing, what alignment tool was used?

Not sufficient details are provided for the re-analysis of siRNA data. E.g., which clustering method was used? How the clusters were assigned to cell identities?

Details about the first HOMER analysis (in the assessment of transcription factor motifs and binding patterns at arterial enhancers) seem to be missing from the methods section.

Pg 12: "For ETS, 23/23 arterial enhancers contained at least one conserved motif (all "deeply" conserved to the same depth as the surrounding enhancer, see S7)". Is it S8, where conservation is indicated?

Figure 1 and 2 for non-zebrafish readers it would be useful to indicate in Figures 1 and 2 the non EC expression that can be observed in the embryos.

Table S1: Please, indicate in the legend what the asterisk in the H DNAseI column stands for

Figure S8: The phrasing "conserved to animal" in Figure S8 is misleading. There is no difference in something being conserved to tenrec or manatee, as both are Afrotherians. Hence, the data show that both Efnb2-141 and Ephb4-2 were present in the common ancestor of Afrotherians and humans, namely the ancestor of all placentals. Instead, it would be good to indicate the phylogenetic group for which the presence of the enhancer can be inferred (in this case, Placentalia).

Significance

To date, a systematic approach to identifying the regulatory networks driving endothelial cell identity is missing. This study provides important datasets and validation of enhancers involved in arterial gene expression and the associated transcription factors. Although this is only the tip of the iceberg, this work represents a significant milestone in the systematic understanding of how arterial gene expression is regulated. Overall, this study offers a powerful resource for understanding arterial gene regulation and conducting genome-wide studies of arterial enhancers.

Perkins (Dorchester), Mildred Ave (Mattapan), Madison Park (Roxbury), Mattahunt (Mattapan), Marshall (Dorchester), Draper (West Roxbury), Clougherty (Charlestown).

This is only if the user doesn't follow the hyperlinked button. I think it should be moved to the bottom of sign in or be in a troubleshooting flow only

Teachers can adapt 'Write the Room' to suit various themes, such as seasons, holidays, or subject-specific vocabulary. By integrating this activity into daily routines, educators can create a lively and engaging classroom atmosphere that promotes both physical and cognitive development.

https://www.youtube.com/watch?v=kfdk81PkabU

yes

https://www.youtube.com/watch?v=kfdk81PkabU

https://www.youtube.com/watch?v=kfdk81PkabU

https://www.youtube.com/watch?v=kfdk81PkabU

No, it's quite easy - capital is the subject motivating externality-producing actions. absolute buffoon of a take.

incoherent separation between the social facticity of the "union" and the "job" - jobs are unionized because social forces mote them be so. author is ignorant of the very idea of a "social force" beyond individual choice.

an organization without which the institution of private property is impossible. try again.

simplistic means-ends reduction of Graeber's work. farcical drivel.

dumbass has no idea what Graeber means by bullshit

Wir sind hier übrigens auch! Daher bitte auch den Hinweis auf OS:

https://www.optimal-systems.de/termine/transformation-now-2024?_gl=1wylmhu_upMQ.._gaMTgyNzc4MjM5Mi4xNzIzNjUwNzQ3_ga_4CCG3SLXEX*MTcyMzY1MDc0Ny4xLjAuMTcyMzY1MDc0Ny4wLjAuMA..

Interessententag!

Welcher?

dient jederzeit als

irgendwie ist das Doppelt, aber du brauchst Zeichen, damit es gleich lang ist? Denn ISO steht ja für International (!) Organization for Standardization bzw. Normung. Vielleicht einfach noch so was wie: "weltweit erfolgreichste und bekannteste Managementsystem für Qualitätsmanagement" verwenden

Ist das wirklich ein einzelnes Wort oder Power User

Auf der Blogseite steht Manager? Anpasssen?

Unten auf dem Butten vielleicht eher "Zum Thema"

ich kenne es als "die richtigen Dinge zur richtigen Zeit". Ist ein kleiner Unterschied. Aber mit deiner Wahl ist der Fokus auf die Zeit mit den Workflows besser.

AI companies fudge their benchmarks to sway consumers

• Species extinction rate is up to 1,000 times higher than the past ten million years.
• Insect populations, once abundant, have significantly declined.
• Bee numbers have halved in the past 25 years; crucial for pollination.
• Lapwing birds are the most rapidly declining species in Europe.
• Biodiversity loss is driven by agricultural industrialization.
• The UK is one of the most nature-depleted countries globally.
• Urgent need to address the crisis to preserve ecosystems for future generations.

I think this justification is bullshit.

Test Annotation.

https://www.theguardian.com/environment/article/2024/aug/13/trump-musk-x-climate

https://www.youtube.com/watch?v=xq6FG4WFg5M&feature=youtu.be

for - Federico Faggin - high priority objective - find and implement ways to catalyze authentic awakening experiences for those who are ready

Federico Faggin - high priority objective - find and implement ways to catalyze authentic awakening experiences for those who are ready - Deep Humanity BEing journeys!

for - Federico Faggin - high priority objective - find and implement ways to catalyze authentic awakening experiences in a short time - ie - one week

for - answer - how to experience nondual - how to experience non-separation and the authentic self - Federico Faggin

answer - how to experience nondual - how to experience non-separation and the authentic self - Be sincere in acknowledging your unhappiness and - take responsibility for it - Be a sincere seeker - The intensity of your search is like a prayer

for - question - how to experience nondual - how to experience non-separation

for - AI - consciousness - not possible - Frederico Faggin

for - quantum physics - John Wheeler's theory - validating

for - CIP OPT integration - Federico Faggin

for - consciousness - primacy of in physics - quotations from famous scientists

for - democracy of the sacred - illusion of Maya - poverty mentality

democracy of - the sacred - illusion of Maya - Theoretically, we should all be able to awaken to the sacred, because THAT is what we all are! - And yet, most of us are so deluded that we cannot access that experience - Maya's illusion of separation is so strong - Poverty mentality is so strong

for - quote - awakening experience - Federico Faggin

quote - awakening experience - Federico Faggin - (see below)

• What I was observing was energy that previously had come out of my chest and
• It was physical energy
• It was not an imagination
• It was physical energy was
• It was a white light that
• It felt like a love that I never felt before and
• It was love, joy and peace
• I never I never had experienced peace before
• It was like like that's me this is my home this is this is who - I am that energy then now exploded now is everywhere and now I am, my consciousness is in that energy
• My feelings are in that consciousness, which is also outside inside your body and o
• Outside your body is everywhere well that experience can change your idea of who you are very quickly because
  • Apart from the fact that
    • it was so profound and
    • so deeply felt to be true
  • it was a direct experience of Consciousness that I never had before and
  • it revealed that I am the totality of reality observing itself from a one point of view

for - epoche - kensho - satori - awakening experience - Federico Faggin

for - hard problem of consciousness - Federico Faggin

for - Federico Faggin - personal journey - profound awakening experience - reorientation of consciousness - from materialist - to idealist

for - comparison of death in - material vs idealist theories

for - consciousness - takes place in quantum reality

for - quote - free will is the ultimate cause of reality - Frederico Faggin

for - book - Irreducible - author - Federico Faggin - to - book Irreducible

to - book - Irreducible - https://hyp.is/0J8C4lo8Ee-WxX-r7RiEHw/www.collectiveinkbooks.com/essentia-books/our-books/irreducible-consciousness-life-computers-human-nature

for - definition - Consciousness Information and Physicality (CIP) - definition - Operational Probabilistic Theory (OPT)

for - consciousness - quantum explanation depends on - difference between - quantum physics - and classical physics

consciousness - quantum explanation depends on - difference between - quantum physics - and classical physics - quantum state evolves in Hilbert space - enables computation of probabilities of what one measures in space-time - but doesn't tell you what you will measure - This difference is critical for describing consciousness as a quantum phenomena

https://www.youtube.com/watch?v=xq6FG4WFg5M&feature=youtu.be

https://www.youtube.com/watch?v=xq6FG4WFg5M&feature=youtu.be

https://www.youtube.com/watch?v=xq6FG4WFg5M&feature=youtu.be

https://www.youtube.com/watch?v=xq6FG4WFg5M&feature=youtu.be

una citocina previamente secretada puede generar diferentes efectos en una célula. Su receptor no está solamente en una célula

This should be: Mark J. Eisenberg.

On the 3rd page of the pdf file, the affiliation should be: 1 Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada 2 Departments of Medicine and of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada 4Department of Medicine, McGill University, Montreal, Quebec, Canada 5Division of Cardiology, Jewish General Hospital, McGill University, Montreal, Quebec, Canada

This should be: Kristian B. Filion. Also, on the 3rd page of the pdf file, the affiliation should be: 1 Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada 2 Departments of Medicine and of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

On the 3rd page of the pdf file, the affiliation should be: 1 Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada 2 Departments of Medicine and of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

Also, on the 3rd page of the pdf file, the affiliation should be: JMP Statistical Discovery, LLC, Cary, North Carolina, USA

This should be: Russell D. Wolfinger. Also, on the 3rd page of the pdf file, the affiliation should be: JMP Statistical Discovery, LLC, Cary, North Carolina, USA

On the third page of the pdf file, as indicated in the original paper, Mark J. Eisenberg should be the corresponding author. Also on the 3rd page, the authors affiliations are not correct.

These should be co-first authors

https://www.theguardian.com/environment/article/2024/aug/14/unprecedented-number-of-heat-records-broken-around-world-this-year

https://www.youtube.com/watch?v=jZMon-U1pe0

So interesting!

https://www.youtube.com/watch?v=pX5RdHT8e4c

https://www.youtube.com/watch?v=mHS982HIlNQ

gullvers travels, heart of darkness

complaint and eros

https://www.youtube.com/watch?v=poq3YVKSNqg

https://www.youtube.com/watch?v=7hZAFCRbAsQ

https://www.youtube.com/watch?v=48-9l4MZ6w8

https://www.youtube.com/watch?v=5nt2ZKNlbDw

https://www.derstandard.at/story/3000000228836/interaktive-karte-zeigt-welche-bezirke-in-oesterreich-die-hoechste-hitzebelastung-haben

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

We thank the reviewers for going through our manuscript and providing valuable feedback. We are grateful to all 3 reviewers for describing our findings as important and valuable, well-designed and robust, and of value to the Parkinson's and Crohn's disease communities studying LRRK2. Below we detail a point-by-point response to the reviewers.

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

The paper by Dikovskaya and collaborators investigated the activitiy and expression of LRRK2 in different subtypes of splenic and intestinal immune cells, taking advantage of a novel GFP-Lrrk2 knockin mouse. Interestingly, they found that T-cell-released IL-4 stimulates Lrrk2 expression in B cells. I have a few comments and suggestions for the authors. 1) Figure 1C. LRRK2 KO cells display residual Rab10 phosphorylation. Do the authors have any idea of which kinase other than LRRK2 could be involved in this phosphorylation?

As far as we are aware no other kinase is known to phosphorylate Rab10 at T73 in vivo. In vitro, recombinant Rab10 can be phosphorylated by MST3 at this site (Knebel A. et al, protocols.io https://dx.doi.org/10.17504/protocols.io.bvjxn4pn), but its relevance in vivo or in cells has not been shown. It is possible that the residual band recognised by anti-pT73 Rab10 ab in splenocytes is unspecific background, as it is mainly seen in LRRK2 KO spleen cells and not in other tissues. But to be certain that our assay assesses LRRK2-dependent Rab10 phosphorylation, we have always compared with the MLi-2 control.

2) Since there are no good antibodies for IF/IHC as pointed by the authors, the GFP-Lrrk2 mouse gives the opportunity to check endogenous LRRK2 localization, i.e. in cells untreated or treated with IL-4 or other cytokines. Also, does endogenous GFP-LRRK2 accumulate into filaments/puncta upon MLi2 inhibition? The relocalization into filaments of inhibited LRRK2 has been observed in overexpression but not under endogenous expression. This analysis would be interesting also in light of the observed side effect of type-I inhibitors.

We thank the reviewer for this suggestion. We will attempt a super-resolution microscopy using Airyscan with isolated B-cells treated with cytokine and/or LRRK2 inhibitor to address this question.

3) Figure 5. The authors need to label more clearly the graphs referring to wt mice versus GFP-Lrrk2 KI mice.

We have now labelled the panels referring to the WT mice only with "WT mice", to distinguish them from the other panels that incorporate data from both EGFP-Lrrk2 mice and their WT littermates used as a background.

They should also replace GFP-LRRK2 with GFP-Lrrk2 since they edited the endogenous murine gene.

Thank you, we have corrected it, and also the other mouse genotypes.

4) In the material and methods MLi-2 administration in mice is indicated at 60 mg/kg for 2 hr whereas in suppl. figure 5 the indicated dose is 30 mg/kg. Please correct with the actual dose used.

Thank you, we have corrected the mistake.

5) The discovery of IL-4 as a Lrrk2 activator in B cells is a very interesting and novel finding. The authors could take advantage of the GFP tag to investigate LRRK2 interactome upon IL-4 stimulation (optional). Also, is the signaling downstream of IL-4 attenuated in Lrrk2 KO cells?

We thank the reviewer for these interesting suggestions. The role of LRRK2 in IL-4 activated B-cells is currently under active research in the lab.

Reviewer #1 (Significance (Required)):

The manuscript is well designed and organized, and the experimental approaches are robust. These results are significant for the field as they add additional layers in the complex regulation and regulatory roles of LRRK2 in immunity, with implication for inflammatory disorders and Parkinson's disease.

We thank the reviewer for their positive comments and for recognising our efforts to provide some clarity to a complex field.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

The authors present a flow cytometry methodology to assess LRRK2 expression and pathway markers in mouse models and explore LRRK2 in splenic and intestinal immune cells. This is a highly valuable study given the emerging understanding that LRRK2 pathway activity in peripheral tissues may be of crucial importance to Parkinson's disease and Crohn's disease. P8 : the authors state that their results indicate 'that the effects of LRRK2-R1441C mutation and inflammation on LRRK2 activity represent two different parallel pathways'. This seems like an overinterpretation as pathway suggests the presence of additional partners in the pathway while R1441C is a LRRK2 intrinsic modification. The results can equally be explained by synergistic effects between both activation mechanisms (mutant and inflammation).

We agree with the reviewer, and have added this into the text. The sentence now reads "suggesting that the LRRK2-R1441C mutation and inflammation have different impacts on LRRK2 activity, either in parallel or in synergy."

Methods and experiment descriptions in results : the authors appear to use the terms anti-CD3 stimulation and CD3 stimulation interchangeably, although it is not always clear in the text that these are synonymous. This should be clarified.

We thank reviewer for pointing out this error on our part. We have made the necessary changes to always refer to the stimulation as anti-CD3.

One major observation in this paper is that LRRK2 is not detected in gut epithelial cells as previously has been reported. It would be useful to comment on any differences between the presented protocol and the previous reports, in particular relating to the antigen retrieval step. In order to reinforce the finding, it would be useful to include in situ hybridization data that could further strengthen the observations of which cellular subtypes express LRRK2 and which do not. Indeed, while the KO control shows that there is an unacceptable high non-specific staining, it does not prove absence of expression. Also, can any conclusions be made about expression of LRRK2 in neural cells of the gut? This important information on LRRK2 detection in gut should be mentioned in the abstract and highlighted in the discussion.

We thank the reviewer for pointing this out. In fact, we think the observation that LRRK2 is not detected in epithelial cells is so important that we have a separate manuscript exploring this point. Please see 1. Tasegian, A. et al.https://doi.org/10.1101/2024.03.07.582590 (2024). In this manuscript we have explored the expression of LRRK2 in human and murine intestinal epithelial cells using qPCR. Although we do not have in situ hybridization data, we believe that using both the EGFP-LRRK2 and the pRab10 flow cytometry, as well as qPCR and proteomics on selected cell types, corroborates our findings on the cell types that express LRRK2. We did not analyse LRRK2 expression in the neural cells of the gut, as the focus was on the immune cells, however we hope that others will use the tools developed here to explore this further.

The authors mention in the discussion that they 'show for the first time that eosinophils also express active LRRK2 at levels comparable to B-cells and DCs.' The relevance of this finding should be further developed. Why is this important?

We thank the reviewer for this point. We don't know how LRRK2 is important in these cells. However, as the role of LRRK2 in eosinophils and neutrophils has not yet been explored and both cell types play important roles in IBD, we think it is important to point out. We have now added a sentence to the discussion highlighting the importance of eosinophils in IBD. "Since eosinophils have recently been implicated as key player in intestinal defense and colitis(Gurtner et al, 2022), it will be interesting to evaluate LRRK2 functions in these cells."

In the isolation of lamina propria cells, what efforts were made to characterize the degree of purification of the lamina propria cells compared to cells of other gut wall layers such as epithelium, muscularis mucosa, or deeper layers? Please specify.

Isolation of lamina propria cells is a very well-established process (LeFrancois and Lycke, 'Isolation of Mouse Small Intestinal Intraepithelial Lymphocytes, Peyer's Patch, and Lamina Propria Cells.' Curr. Protocols in Immunology 2001), where we extensively wash off the epithelial layer before digesting the tissue for the LP. After the digestion the muscle and wall of the gut are still intact, so we do not get any contamination with other deeper layers. The subsets of cells we find in the LP are in line with isolations from other labs.

Minor comments Figure 5G, for the graphs indicating LRRK2 activity and LRRK2 phosphorylation, the specific measures should be specified in the graph titles to avoid any ambiguity (pT73-Rab10, pS935-LRRK2).

We have added the specifications to the new version of the figure.

Suppl figure 1 : please specify the figure label and abbreviation AF568 in the legend. Suppl figure 2 : please specify the figure label and abbreviation anti-rb in the legend

Thank you, we added the abbreviations to the legends. The Figure labels for both figures have been already included at the top of figure legends.

Reviewer #2 (Significance (Required)):

The authors present a flow cytometry methodology to assess LRRK2 expression and pathway markers in mouse models and explore LRRK2 in splenic and intestinal immune cells. This is a highly valuable study given the emerging understanding that LRRK2 pathway activity in peripheral tissues may be of crucial importance to Parkinson's disease and Crohn's disease.

We thank the reviewer for recognising the value of this study.

Reviewer #3

Evidence, reproducibility and clarity

The paper describes a set of experiments to analyse LRRK2 activity in tissues and despite it has very important findings and technical developments is largely descriptive. It does look like a collection of experiments more than a defined hypothesis and experiments to address that.

We thank the reviewer for recognising the importance of our findings and the technical developments. We agree that the paper's focus is to describe where LRRK2 is expressed in immune cells, and in which cells is it active or activated after inflammation in a hypothesis-free unbiased manner. We believe this is important data to share as a resource for the wider LRRK2 community and we will submit the manuscript as a Resource.

The flow cytometry assay of the first part is a great technical challenge and represents the establishment of a potentially very useful tool for the field. It would have been important to test other organs, either as controls or for example because of their relevance e.g. lungs. This first part is disconnected from the second part below.

We thank the reviewer for pointing out that the pRab10 assay would be useful to apply to other organs too. Since we are interested in the role of LRRK2 in IBD, we had focused on applying the pRab10 assay on intestinal tissue, with spleens also analysed as major lymphoid organ and a source of immune cells that can translocate to the gut in inflammation. We hope that the publication of this method would allow other researchers to analyse other tissues in the future.

The authors generated a new mouse KI mouse expressing EGFP-LRRK2 and show data the levels of LRRK2 expression are reduced in tissues at different degrees and established a flow cytometry assay to measure LRRK2 expression by monitoring the GFP signal. Interestingly they found that expression does not correlate with activity (as measured by phospho-Rabs). I suggest taking this part out as it breaks the flow of the paper. If data using this mouse is included, then microscopy should be included to complement the flow cytometry data. I understand the mice were used later with the anti-CD3 treatment, but it is very confusing that some experiments are done with EGFP-LRRK2 mice and others not. It does look in general like the mice do not behave as wild types and this is an important caveat. Without microscopy of the tissues or even cells (Figure 4) is hard to conclude much about these experiments.

We thank the reviewer for this point and would like to explain. It is true that in Suppl Figure 5, we show reduction of LRRK2 signal in the EGFP-Lrrk2-KI mice. However, based on immunoblotting, a significant reduction in EGFP-LRRK2 expression levels was seen only in the brain, but not in the tissues we analysed, that is the spleen and the intestine. Further, we have shown clearly using proteomics (Fig. 3D and 5E), that the GFP signal in immune cells correlates very well with the WT LRRK2 expression. Therefore, we think that the GFP signal in these mice reflects WT LRRK2 expression pattern. Further, despite the limitations of reduced kinase activity that we thoroughly describe, we think this model is very useful since no antibodies work to stain for LRRK2 in mice. We therefore respectfully disagree with this reviewer that the EGFP-LRRK2 data should be taken out, as it has proven to be an invaluable tool to measure and track changes in endogenous LRRK2 expression. Moreover, we think the fact that LRRK2 expression does not correlate with levels of activity, that is, LRRK2 is more active in some immune cells than in others, is a very important finding that evidences the cell-specific regulation of LRRK2 activity beyond its expression level.

We tried but failed to visualize the EGFP-LRRK2 signal using fluorescence microscopy in the tissue. This is most likely due to the low expression of LRRK2 (proteomics data suggests that even neutrophils express less than 9000 copies), confounded further by the high background autofluorescence in tissues, especially in the gut. We now explain the lack of tissue images from the EGFP-LRRK2 mice in the text. However, we can visualize the EGFP-LRRK2 in B cells, and we will provide these images in a revised version of the manuscript.

We have also added the following paragraph to the discussion:

"We complemented the pRab10 assay with the development of the EGFP-Lrrk2-KI reporter mouse. Although the reporter was initially designed as a fluorescent tracker for imaging LRRK2 localisation in cells and tissues, the low expression of LRRK2, combined with high and variable autofluorescence in tissues precluded its use for microscopy. Even in neutrophils, which express highest level of LRRK2 among immune cells, there are less than 9000 copies of LRRK2 per cell (Sollberger et al, 2024), making it difficult to identify localization. However, the EGFP signal was sufficient for flow cytometry-based measurements, where background autofluorescence of each cell type was taken into account and subtracted."

Then the authors show that LRRK2 expression and activity is different in different cell types and depends on inflammation. The anti-CD3 strategy to induce inflammation is very different from physiological inflammation such as sepsis and LPS stimulation, so experiments with other stimuli could be important here to contribute to the message of inflammatory trigger of LRRK2 activation and decoupling of cell type.

We thank the reviewer for this suggestion. We used the anti-CD3 model as it also causes intestinal inflammation, and mimics T-cell cytokine storms that happens in many diseases. However, for the revisions we will also test another model of inflammation as suggested, such as LPS stimulation, to measure how inflammation affects LRRK2 expression and activity.

The IL-4 data is intriguing but too preliminary. The lack of strong effect of IFN-gamma is expected as the promoter of LRRK2 in mice and humans is different and human cells responds much better with regards to LRRK2 expression after IFN-gamma stimulation.

We are confused by what the reviewer means by saying the IL-4 data is preliminary. We have shown by flow cytometry, immunoblotting, qPCR and proteomics that IL-4 induced LRRK2 expression in B-cells. So we are uncertain as to how else this can be shown. As to the effect of IFNγ on LRRK2 expression, it may indeed be that human cells respond better than murine cells. Importantly, the IL-4 ability to induce LRRK2 in B-cells is a novel and important finding, regardless of the effects of IFNγ.

Reviewer #3 (Significance (Required))

The paper describes a set of experiments to analyse LRRK2 activity in tissues and despite it has very important findings and technical developments is largely descriptive. It does look like a collection of experiments more than a defined hypothesis and experiments to address that.

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 authors present a flow cytometry methodology to asses LRRK2 epxression and pathway markers in mouse models and explore LRRK2 in splenic and intestinal immune cells. This is a highly valuable study given the emerging understanding that LRRK2 pathway activity in peripheral tissues may be of crucial importance to Parkinson's disease and Crohn's disease.

P8 : the authors state that their results indicate 'that the effects of LRRK2-R1441C mutation and inflammation on LRRK2 activity represent two different parallel pathways'. This seems like an overinterpretation as pathway suggests the presence of additional partners in the pathway while R1441C is a LRRK2 intrinsic modification. The results can equally be explained by synergistic effects between both activation mechanisms (mutant and inflammation).

Methods and experiment descriptions in results : the authors appear to use the terms anti-CD3 stimulation and CD3 stimulation interchangeably, although it is not always clear in the text that these are synonymous. This should be clarified.

One major observation in this paper is that LRRK2 is not detected in gut epithelial cells as previously has been reported. It would be useful to comment on any differences between the presented protocol and the previous reports, in particular relating to the antigen retrieval step. In order to reinforce the finding, it would be useful to include in situ hybridization data that could further strengthen the observations of which cellular subtypes express LRRK2 and which do not. Indeed, while the KO control shows that there is an unacceptable high non-specific staining, it does not prove absence of expression. Also, can any conclusions be made about expression of LRRK2 in neural cells of the gut? This important information on LRRK2 detection in gut should be mentioned in the abstract and highlighted in the discussion. The authors mention in the discussion that they 'show for the first time that eosinophils also express active LRRK2 at levels comparable to B-cells and DCs.' The relevance of this finding should be further developed. Why is this important ?

In the isolation of lamina propria cells, what efforts were made to characterize the degree of purification of the lamina propria cells compared to cells of other gut wall layers such as epithelium, muscularis mucosa, or deeper layers? Please specify.

Minor comments

Figure 5G, for the graphs indicating LRRK2 activity and LRRK2 phosphorylation, the specific measures should be specified in the graph titles to avoid any ambiguity (pT73-Rab10, pS935-LRRK2).

Suppl figure 1 : please specify the figure label and abbreviation AF568 in the legend.

Suppl figure 2 : please specify the figure label and abbreviation anti-rb in the legend

Significance

The authors present a flow cytometry methodology to asses LRRK2 epxression and pathway markers in mouse models and explore LRRK2 in splenic and intestinal immune cells. This is a highly valuable study given the emerging understanding that LRRK2 pathway activity in peripheral tissues may be of crucial importance to Parkinson's disease and Crohn's disease.

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

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

The paper by Dikovskaya and collaborators investigated the activitiy and expression of LRRK2 in different subtypes of splenic and intestinal immune cells, taking advantage of a novel GFP-Lrrk2 knockin mouse. Interestingly, they found that T-cell-released IL-4 stimulates Lrrk2 expression in B cells.

I have a few comments and suggestions for the authors.

1. Figure 1C. LRRK2 KO cells display residual Rab10 phosphorylation. Do the authors have any idea of which kinase other than LRRK2 could be involved in this phosphorylation?
2. Since there are no good antibodies for IF/IHC as pointed by the authors, the GFP-Lrrk2 mouse gives the opportunity to check endogenous LRRK2 localization, i.e. in cells untreated or treated with IL-4 or other cytokines. Also, does endogenous GFP-LRRK2 accumulate into filaments/puncta upon MLi2 inhibition? The relocalizaiton into filaments of inhibited LRRK2 has been observed in overexpression but not under endogenous expression. This analysis would be interesting also in light of the observed side effect of type-I inhibitors.
3. Figure 5. The authors need to label more clearly the graphs referring to wt mice versus GFP-Lrrk2 KI mice. They should also replace GFP-LRRK2 with GFP-Lrrk2 since they edited the endogenous murine gene.
4. In the material and methods MLi-2 administration in mice is indicated at 60 mg/kg for 2 hr whereas in suppl. figure 5 the indicated dose is 30 mg/kg. Please correct with the actual dose used.
5. The discovery of IL-4 as a Lrrk2 activator in B cells is a very interesting and novel finding. The authors could take advantage of the GFP tag to investigate LRRK2 interactome upon IL-4 stimulation (optional). Also, is the signaling downstream of IL-4 attenuated in Lrrk2 KO cells?

Significance

The manuscript is well designed and organized, and the experimental approaches are robust. These results are significant for the field as they add additional layers in the complex regulation and regulatory roles of LRRK2 in immunity, with implication for inflammatory disorders and Parkinson's disease.

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

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

The paper describes a set of experiments to analyse LRRK2 activity in tissues and despite it has very important findings and technical developments is largely descriptive. It does look like a collection of experiments more than a defined hypothesis and experiments to address that.

The flow cytometry assay of the first part is a great technical challenge and represents the establishment of a potentially very useful tool for the field. It would have been important to test other organs, either as controls or for example because of their relevance e.g. lungs. This first part is disconnected from the second part below.

The authors generated a new mouse KI mouse expressing EGFP-LRRK2 and show data the levels of LRRK2 expression are reduced in tissues at different degrees and established a flow cytometry assay to measure LRRK2 expression by monitoring the GFP sugnal. Interestengly they found that expression does not correlate with activity (as measured by phospho-Rabs). I suggest taking this part out as it breaks the flow of the paper. If data using this mouse is included, then microscopy should be included to complement the flow cytometry data. I understand the mice were used later with the anti-CD3 treatment, but it is very confusing that some experiments are done with EGFP-LRRK2 mice and others not. It does look in general like the mice do not behave as wild types and this is an important caveat. Without microscopy of the tissues or even cells (Figure 4) is hard to conclude much about these experiments.

Then the authors show that LRRK2 expression and activity is different in different cell types and depends on inflammation. The anti-CD3 strategy to induce inflammation is very different from physiological inflammation such as sepsis and LPS stimulation, so experiments with other stimuli could be important here to contribute to the message of inflammatory trigger of LRRK2 activation and decoupling of cell type.

The IL-4 data is intriguing but too preliminary. The lack of strong effect of IFN-gamma is expected as the promoter of LRRK2 in mice and humans is different and human cells responds much better with regards to LRRK2 expression after IFN-gamma stimulation.

Significance

The paper describes a set of experiments to analyse LRRK2 activity in tissues and despite it has very important findings and technical developments is largely descriptive. It does look like a collection of experiments more than a defined hypothesis and experiments to address that.

This is actually a handy description

diaspora wars almost. you view african americans as one way but you come and it is different

What is the moral argument against nuclear (power, not bombs)?

for - from - interview - Federico Faggin

from - interview - Federico Faggin - https://hyp.is/Bmcmblo_Ee-cuC8QnSOAYw/www.youtube.com/watch?v=MSn4t6fP_dc

i.e., informing us of where we are in space and time so as to inform future action?

qualia!!!

Changer le texte par …

for - quantum-information-based-panpsychism - consciousness - relationship - quantum information - to consciousness

consciousness - relationship - quantum information - to consciousness - classical physics supervenes on quantum physics - quantum physics supervenes on quantum information - quantum information supervenes on consciousness

for - follow up - combination problem of panpsychism

https://www.youtube.com/watch?v=hBYy-ABkLOY

https://www.youtube.com/watch?v=hBYy-ABkLOY

https://www.youtube.com/watch?v=hBYy-ABkLOY

https://www.youtube.com/watch?v=hBYy-ABkLOY

https://www.youtube.com/watch?v=hBYy-ABkLOY

https://www.kleinezeitung.at/steiermark/18754346/seen-keine-abkuehlung-bis-zu-29-grad-heiss

https://www.youtube.com/watch?v=hBYy-ABkLOY

https://www.kleinezeitung.at/home/18755519/klimaaktivisten-fordern-hitzefrei-fuer-jobs-im-freien-ab-30-grad

https://www.youtube.com/watch?v=YolCI23j-jE&t=1s

eLife assessment

This is a mechanistic study showing the effect of combining inhibition of autophagy (through ULK1/2) and KRAS (using sotorasib) on KRAS mutant NSCLC making the study valuable to cancer biologists and more broadly in a clinical setting. The evidence generated by GEM mouse models and cell lines is solid but could be further strengthened by increasing the mouse cohort size. This study holds translational relevance beyond NSCLC to other indications that carry KRAS mutations.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Ghazi et reported that inhibition of KRASG12C signaling increases autophagy in KRASG12C expressing lung cancer cells. Moreover, the combination of DCC 3116, a selective ULK1/2 inhibitor, plus sotorasib displays cooperative/synergistic suppression of human KRASG12C driven lung cancer cell proliferation in vitro and tumor growth in vivo. Additionally, in genetically engineered mouse models of KRASG12C driven NSCLC, inhibition of either KRASG12C or ULK1/2 decreases tumor burden and increases mouse survival. Additionally, this study found that LKB1 deficiency diminishes the sensitivity of KRASG12C/LKB1Null-driven lung cancer to the combination treatment, perhaps through the emergence of mixed adeno/squamous cell carcinomas and mucinous adenocarcinomas.

Strengths:

Both human cancer cells and mouse models were employed in this study to illustrate that inhibiting ULK1/2 could enhance the responsiveness of KRASG12C lung cancer to sotorasib. This research holds translational importance.

Weaknesses:

The revised manuscript has addressed most of my previous concerns. However, I still have one issue: the sample size (n) for the GEMM study in Figures 4E and 4F is too small, despite the authors' explanation. The data do not support the conclusion due to the lack of significant difference in tumor burden. Additionally, the significance labels in Figure 4E are not clearly explained.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

Given that KRAS inhibition approaches are a relatively new innovation and that resistance is now being observed to such therapies in patients with NSCLC, investigation of combination therapies is valuable. The manuscript furthers our understanding of combination therapy for KRAS mutant non-small cell lung cancer by providing evidence that combined inhibition of ULK1/2 (and therefore autophagy) and KRAS can inhibit KRAS-mutant lung cancer growth. The manuscript will be of interest to the lung cancer community but also to researchers in other cancer types where KRAS inhibition is relevant.

Strengths:

The manuscript combines cell line, cell line-derived xenograft, and genetically-engineered mouse model data to provide solid evidence for the proposed combination therapy.  The manuscript is well written, and experiments are broadly well performed and presented.

We thank Reviewer #1 (R1) for the generally favorable review of our manuscript, and also for the more detailed critique that identifies potential weaknesses in the research, which we address on a point-by-point basis below. 

Weaknesses:

With 3-4 mice per group in many experiments, experimental power is a concern and some comparisons (e.g. mono vs combination therapy) seem to be underpowered to detect a difference. Both male and female mice are used in experiments which may increase variability.

We thank R1 for pointing out concerns regarding statistical power in our various mouse models of NSCLC experiments, and agree that more mice per group would certainly increase statistical power.  However, there are certain logistical considerations that impact the generation of cohorts of experimental KrasLSL-G12C mice.  Because mice homozygous for the KrasLSL-G12C allele display embryonic lethality, we are required to generate experimental mice by crossing heterozygous male and female KrasLSL-G12C mice.  Although 66% of the progeny of such crosses are predicted to be KrasLSL-G12C/+, experience tells us that we only obtain ~40-50% heterozygous KrasLSL-G12C/+ mice with litter sizes around 6-8 mice from such crosses.  Therefore, there are usually only about 4 heterozygous KrasLSL-G12C mice per litter, which presents a substantial challenge in generating larger cohorts of age-matched mice suitable for experiments, especially under conditions where we wish to euthanize mice at multiple time points for analysis.  For the GEM model experiments, Figure 3B is the only experiment that has n=3.  All other experiments contain 4-6 mice per experimental condition.  We rationalized using both male and female mice because both human males and females have high lung cancer rates.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Ghazi et reported that inhibition of KRASG12C signaling increases autophagy in KRASG12C-expressing lung cancer cells. Moreover, the combination of DCC 3116, a selective ULK1/2 inhibitor, plus sotorasib displays cooperative/synergistic suppression of human KRASG12C-driven lung cancer cell proliferation in vitro and tumor growth in vivo. Additionally, in genetically engineered mouse models of KRASG12C-driven NSCLC, inhibition of either KRASG12C or ULK1/2 decreases tumor burden and increases mouse survival. Additionally, this study found that LKB1 deficiency diminishes the sensitivity of KRASG12C/LKB1Null-driven lung cancer to the combination treatment, perhaps through the emergence of mixed adeno/squamous cell carcinomas and mucinous adenocarcinomas.

Strengths:

Both human cancer cells and mouse models were employed in this study to illustrate that inhibiting ULK1/2 could enhance the responsiveness of KRASG12C lung cancer to sotorasib. This research holds translational importance.

We thank Reviewer #2 (R2) for the generally favorable review of our manuscript, and also for the more detailed critique that identifies potential weaknesses in the research, which we address on a point-by-point basis below. 

Weaknesses:

Additional validation of certain data is necessary.

(1) mCherry-EGFP-LC3 reporter was used to assess autophagy flux in Figure 1A. Please explain how autophagy status (high, medium, and low) was defined. It's also suggested to show WB of LC3 processing in different treatments as in Figure 1A at 48 hours.

We thank the reviewer for this comment and agree that a more thorough description of how autophagy status is assessed using the Fluorescent Autophagy Reporter (FAR) would benefit the readers of our manuscript.  Cells engineered to express the FAR are analyzed by flow cytometry in which we defined autophagy status by gating viable (based Sytox Blue staining), DMSO-treated control cells into three bins based on the ratio of EGFP:mCherry fluorescence.  We gate all live cells into the 33% highest EGFP-positive cells (autophagy low) and the 33% highest mCherry-positive cells (autophagy high), and therefore, the proportion in the middle is also approximately 33% and considered the medium autophagy status.  Again, these gates are based entirely on the DMSO-treated control cells, and all other treatments within the experiment are compared to settings on these gates.  In response to a specific manipulation (sotorasib, trametinib, DCC-3116 etc) we assess how the specific treatment changes the percentages of cells in each of the pre-specified gates to assess increased autophagy (decreased EGFP:mCherry ratio) or decreased autophagy (increased increased EGFP:mCherry ratio). 

Although LC3 processing and/or the expression of p62SQSTM1 are used by others as markers of autophagy, there is much debate in the literature as to how reliable immunoblotting analysis of LC3 processing or p62SQSTM1 expression are as measures of autophagy.  Certainly, in our hands, we find that the Fluorescent Autophagy Reporter is a much more sensitive measure of changes in autophagy in various different cancer cell lines as we have described in previous papers (Kinsey et al., PMID: 30833748, Truong et al., PMID: 32933997 and Silvis & Silva et al., PMID: 36719686).  Furthermore, in the omnibus publication that describes techniques for measuring autophagy (Klionsky et al., PMID: 33634751) the use of the FAR (or similarly configured reporters) is regarded as the gold standard for measuring autophagy status in cells.  We have amended the Materials & Methods section of our manuscript to better describe the use of the FAR in measuring autophagy. 

(2) For Figures 1J, K, and L, please provide immunohistochemistry (IHC) images demonstrating RAS downstream signaling blockade by sotorasib and autophagy blockade by DCC 3116 in tumors.

We thank the reviewer for the comment and have probed the tumors from the xenograft experiments in Figures 1J, K, and L for pERK1/2 and p62SQSTM1 to determine the biochemical activity of sotorasib or DCC-3116, respectively and have provided representative images below. We observed the expected decrease in pERK and p62 signal after sotorasib treatment in all three xenografted cell lines. We did observe the expected accumulation of p62 in the DCC-3116 treated tumors from the NCI-H2122 and NCI-H358 cell lines. There appears to be no difference between the vehicle and DCC-3116 treated tumors in the NCI-H358 cell line-derived tumors as detected by IHC.

Author response image 1.

(3) Given that both DCC 3116 and ULK1K46N exhibit the ability to inhibit autophagy and synergize with sotorasib in inhibiting cell proliferation, in addition to demonstrating decreased levels of pATG13 via ELISA assay, please include Western blot analyses of LC3 or p62 to confirm the blockade of autophagy by DCC 3116 and ULK1K46N in Figure 1 & Figure 2.

We appreciate the reviewer's comment and have performed an immunoblot analysis of cells treated with DCC-3116 or expressing ULK1K46N and probed for p62SQSTM1 and LC3 expression.  We did observe the expected accumulation of p62 SQSTM1 in NCI-H2122 (ULK1K46N) cells treated with 1ug/ml doxycycline to induce expression of ULK1K46N compared to DMSO treatment.  Additionally, we treated the human cell lines from Figure 1 with sotorasib and/or DCC-3116 and tested for p62SQSTM1 expression after 48 hours of treatment. In the human cell lines NCI-H2122 and NCI-H358, there was a decrease in the p62 signal with increasing doses of sotorasib, as expected. There was no detectable change in p62 levels in the Calu-1 cells by immunoblot. For LC3-I/LC3-II, there was only one detectable band in the NCI-H2122 cells, which makes it difficult to interpret the results and further emphasizes why we use the fluorescent autophagy reporter which is more sensitive than immunoblotting. There is no detectable change in LC3-I/LC3-II in the Calu-1 cells treated with increasing doses of sotorasib, but the expected decrease in LC3-I is observed with sotorasib treatment in the NCI-H358 cells.

Author response image 2.

(4) Since adenocarcinomas, adenosquamous carcinomas (ASC), and mucinous adenocarcinomas were detected in KL lung tumors, please conduct immunohistochemistry (IHC) to detect these tumors, including markers such as p63, SOX2, Katrine 5.

We have included IHC analysis of the adenosquamous carcinomas for the markers p63, SOX2, and Keratin 5 from the KL mouse in Figure 3 and the ASC tumors in Supplemental Figure 4, and thank the reviewer for this excellent suggestion. The straining for these markers is below. Of note, we tried two different SOX2 antibodies (cell signaling technologies #14962 and cell signaling technologies # 3728) and could not detect any staining in any section.

Author response image 3.

(5) Please provide the sample size (n) for each treatment group in the survival study (Figure 4E). It appears that all mice were sacrificed for tumor burden analysis in Figure 4F. However, there doesn't seem to be a significant difference among the treatment groups in Figure 4F, which contrasts with the survival analysis in Figure 4E. It is suggested to increase the sample size in each treatment group to reduce variation.

We have updated Figure 4E to indicate sample size for each treatment group and thank the reviewer for this suggestion.  Any mice that remained on study through the entire 8-week treatment regimen were sacrificed after the last day of treatment (Day 56).  Figure 4F indicates analysis of total tumor burden in all mice that remained on treatment for the full 8 weeks and mice that reached euthanasia criteria before the end of the 8-week treatment.  Therefore, it is important to note that the mice in Figure 4F were not all euthanized on the same day.  There is no statistically significant difference between the 3 treatment groups (sotorasib, DCC-3116, combination).  This may be due to a lower sample size as well as ending the treatment at 8 weeks as opposed to continuing the treatment for a longer period of time.  Although we agree that increasing the sample size would benefit the study, due to how long the GEMM model experiments take (12-16 weeks of breeding, 6 weeks for the mice to reach adulthood, 10 weeks of tumor formation post-initiation, 8 weeks of treatment= ~40 weeks) we would respectfully submit that the analysis of additional mice is outside the scope of the current revised manuscript.

(6) In KP mice (Figure 5), it seems that a single treatment alone is sufficient to inhibit established KP lung tumor growth. Combination treatment does not further enhance anti-tumor efficacy. Therefore, this result doesn't support the conclusion generated from human cancer cell lines. Please discuss.

We thank the reviewer for this observation.  Indeed, KP lung tumors were sensitive to single agent DCC-3116 treatment, which is reflected in the tumor burden analysis.  This was somewhat surprising to us as we have not previously detected much anti-tumor activity using 4-amino-quinoloines (chloroquine or hydroxychloroquine) or other autophagy inhibitors.  It should be noted however that the KRASG12C/TP53R175H NSCLC model has a very low tumor burden overall (~4% in vehicle-treated mice).  Additionally, our microCT imager cannot detect AAH and small tumors at the settings/resolution used.  Therefore, we were limited in our ability to detect small tumors or hyperplasia by microCT imaging.  Although there was a decrease in overall tumor burden with single agent DCC-3116 treatment, we could not demonstrate using microCT imaging that KRASG12C/TP53R175H lung tumors were actually regressing with single agent DCC-3116 treatment.  The larger tumors that were detected appeared to show a cytostatic effect (i.e. no or slow growth) with DCC-3116 monotherapy.  This may reflect our inability to detect regression of AAH or small tumors with the microCT.  In all human cell lines tested, the only cell line that responded to single agent DCC-3116 treatment was NCI-H358 cells, which do have a complete heterozygous loss of the TRP53 gene and lack TP53 protein.  However, other cells that also have a loss of expression of TP53 expression (Calu-1) are insensitive to single-agent DCC-3116 treatment. Due to the low mutational burden of the KP mouse model compared to human NSCLC cell lines driven by mutationally-activated KRASG12C and the loss of TP53 function, it is difficult to directly compare GEM models to the human cell line models.  Most of the human cell lines have alterations in other genes that are not altered in the KP mouse model which could affect the sensitivity of treatment.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Minor comments:

(1) Figure legends are currently not adequate - information about the number and nature of replicates, stats, and definitions of the labelling used for stats should be added throughout. In Figure 5B, only two lines of four are labelled with * or ns.

We thank the reviewer for this comment and have included more details in the figure legends that describe replicates, statistical analysis and definitions of labeling.  We also note that the methods section has a detailed description of the statistical analysis used.

(2) What statistical test is performed on Figure 5E to get a p < 0.05 between the vehicle and DCC group?

We performed a one-way ANOVA for all statistical analyses with more than 2 experiential groups. We thank the reviewer for pointing out this typo. These data points (vehicle vs. DCC-3116) are not statistically significant, which has been revised in the figure.

(3) The manuscript figures would be improved by the use of a colourblind-friendly palette.

We have previously published multiple manuscripts using this color scheme for the fluorescent autophagy reporter experiments and chose to use red and green as the reporter uses EGFP and mCherry.  We wanted to keep this color scheme consistent across our publications and would prefer not to change the colors.  However, we agree with the reviewer that the data should be accessible to all people and, therefore, have updated these graphs to include slashes over the red color to ease in telling the differences between the red and green colors.  Thank you to the reviewer for this excellent suggestion.

(4) The manuscript should be fully checked for mouse (sentence case) and human (caps) gene (italics) and protein (non-italics).

In this manuscript we are using the nomenclatures approved by the HUGO Gene Nomenclature Committee (https://en.wikipedia.org/wiki/HUGO_Gene_Nomenclature_Committee) in which:

Human genes are written as KRAS, TP53 etc i.e. ITALICIZED CAPS

Mouse genes are written as Kras, Trp53 etc:  i.e. Italicized and sentence case

Human and mouse proteins are written as KRAS, TP53 etc:  i.e. NON-ITALICIZED CAPS

In response to the reviewer’s suggestion, we have gone through the manuscript to check for this and make any appropriate changes.  Of note, we intentionally refer to the mouse protein changes as KRASG12C/LKB1null or KRASG12C/TP53R172H (capitalized), as this references the protein change and not the nucleotide change that occurs in the gene.

(5) Adenosquamous is the correct term for the disease.  In parts, it's referred to as adeno/squamous or adeno-squamous.  The abbreviation ADC is also defined many times.

Thank you to the reviewer for this comment.  We have corrected the manuscript text to only use adenosquamous and only define ADC in the first instance.

(6) Line 434 - "as previously described" but no reference.

Typos:

(1) Line 117 – either

(2) Line 314 – synergistic

(3) Line 317 – therefore

(4) Line 502 – medium

We thank the reviewer for pointing out these typos and have modified the text appropriately.

Reviewer #2 (Recommendations For The Authors):

(1) The statement on Page 4, Lines 119-120, lacks clarity: 'Furthermore, LKB1 silencing diminishes the sensitivity of KRASG12C/LKB1Null-driven lung cancer perhaps through the emergence of mixed adeno/squamous cell carcinomas and mucinous adenocarcinomas.  It is unclear whether this refers to the sensitivity to the combination treatment or to the KRASc inhibitor alone.

We thank the reviewer for this comment and agree that the statement lacks clarity.  The intent of this statement was to refer to both single agent sotorasib treatment as well as the combination with DCC-3116.  

(2) Page 5 Line 147 "KRASG12X ". Please correct this typo.

We thank the reviewer for this comment, but this is not a typo. We intended for this line to state KRASG12X to refer to cell lines with any KRASG12 alteration, e.g KRASG12D, KRASG12C, KRASG12S, KRASG12R etc.  

(3) The color of the dots in Figure 5B labeling does not match the dots in the graph.

For all bar graphs in the manuscript, the dots representing individual mice are black, and the bar itself is color-coded based on treatment type. The dots in Figure 5B follow this pattern and are intended to be this way.

(4) Figure 5C depicts lung weight rather than tumor growth, contrary to the text description "regression of pre-existing lung tumors was detected by microCT scanning (Figure 5C, Figure S5)".

Figure 5C does not depict lung weight but the percent body weight change in treated mice, described in the figure legend.  We thank the reviewer for pointing this out because we referenced the wrong panel in the text.  The figures referenced should be Figure 5B, Figure S5.  We have corrected this in the text.

Reviewer #1 (Public Review):

Summary:

The authors profile gene expression, chromatin accessibility and chromosomal architecture (by Hi-C) in activated CD4 T cells and use this information to link non-coding variants associated with autoimmune diseases with putative target genes. They find over a 1000 genes physically linked with autoimmune disease loci in these cells, many of which are upregulated upon T cell activation. Focusing on IL2, they dissect the regulatory architecture of this locus, including the allelic effects of GWAS variants. They also intersect their variant-to-gene lists with data from CRISPR screens for genes involved in CD4 T cell activation and expression of inflammatory genes, finding enrichments for regulators. Finally, they showed that pharmacological inhibition of some of these genes impacts T cell activation.

This is a solid study that follows a well-established canvas for variant-to-gene prioritisation using 3D genomics, applying it to activated T cells. The authors go some way in validating the lists of candidate genes, as well as explore the regulatory architecture of a candidate GWAS locus. Jointly with data from previous studies performing variant-to-gene assignment in activated CD4 T cells (and other immune cells), this work provides a useful additional resource for interpreting autoimmune disease-associated genetic variation.

Autoimmune disease variants were already linked with genes in CD28-stimulated CD4 T cells using chromosome conformation capture, specifically Promoter CHi-C and the COGS pipeline (Javierre et al., Cell 2016; Burren et al., Genome Biol 2017; Yang et al., Nat Comms 2020). The authors cite these papers and present a comparative analysis of their variant-to-gene assignments (in addition to scRNA-seq eQTL-based assignments). Furthermore, they find that the Burren analysis yields a higher enrichment for gold standard genes.

I thank the authors for their revisions in response to my initial review. The revised version now includes a more comprehensive comparative analysis of different datasets and V2G approaches and discusses the potential sources of differences in the results. Most significantly, the authors have now included an interesting comparison of their methodology with the popular ABC technique and outlined the key limitations of ABC relative to their method and other (Capture) Hi-C-based V2G approaches.

eLife assessment

This is a useful manuscript describing the competitive binding between Parkin domains to define the importance of dimerization in the mechanism of Parkin regulation and catalytic activity. The evidence supporting the importance of Parkin dimerization for an 'in trans' model of Parkin activity described in this manuscript is solid, but lacks more stringent and biochemical characterization of competitive binding that could provide more direct evidence to support the author's conclusions. This work will be of interest to those focused on defining the molecular mechanisms involved in ubiquitin ligase interactions, PINK-Parkin-mediated mitophagy, and mitochondrial organellar quality control.

Reviewer #1 (Public Review):

Summary:

The authors used structural and biophysical methods to provide insight into Parkin regulation. The breadth of data supporting their findings was impressive and generally well-orchestrated.

Strengths:

(1) They have done a better job explaining the rationale for their experiments thought-out.

(2) The use of molecular scissors in their construct represents a creative approach to examine inter-domain interactions. Appropriate controls were included.

(3) From my assessment, the experiments are well-conceived and executed.

(4) The authors do a better job of highlighting the question being addressed experimentally.

Reviewer #2 (Public Review):

In the revised manuscript, the authors tried to address some of my comments from the previous round of review. Notably, they have performed some additional ITC experiments where protein precipitation is not an issue to probe interactions between PARKIN and different domains. In addition, they have toned down some of the language in the text to better reflect their data and results. However, I still feel that the manuscript lacks some key answers regarding the relative interactions between p-PARKIN and different domains, as discussed in my previous review. A deeper dive into the underlying biophysical and biochemical features that drive these interactions is important to fully understand the importance of their work. However, this manuscript does provide some interesting potential insights into the mechanisms of PARKIN activation that could be useful for the field moving forward.