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Reply to the reviewers

To the Editor,

We thank the reviewers for their generous efforts on behalf of our manuscript. We were very pleased to see that reviewer #1 considered our manuscript a “very detailed, high quality paper” that “serves as an important resource for the field.” And that Reviewer #2 concurred, writing that our manuscript is “valuable because it generates large datasets on the NK/ILC family from human blood that can be deposited in repositories”, and that it is of “special relevance to the HIV field because it examines viral infection effects on these subsets.”

We believe the revisions made in response to the reviewers suggestions have improved the presentation of our data. Our responses to each reviewer comment are listed below in bold font. References mentioned here are listed in a bibliography at the end of this document.Changes to the text are also highlighted in the manuscript.

1. Point-by-point description of the revisions

This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

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

Wang and colleagues present a very detailed, high quality paper describing phenotyping, transcriptional, epigenetic and functional differences between NK cells and ILCs in human peripheral blood. They overlay these studies which descriptions of differences in these populations in healthy and HIV infected (viremia, ART-treated, controllers), extending a their previous 2020 study.

Overall, this paper serves as an important resource for the field. There are areas in which the manuscript could be modified to improve clarity and detail regarding rigor.

My comments below are all addressable and therefore I class them all as 'major'.

1. The authors describe ILCs as being 'permanently deleted' in HIV infection. As written, this can be misinterpreted to suggest complete ablation of this cell subset. This is clearly not the case. Moreover, there looks to be some restoration of ILCs in ART-treated participants. I suggest revising text to quantify the level of cell loss or replace the word deleted with reduced. The reviewer is correct that ILCs are not completely ablated. In response to this important point we have clarified the text, as follows:

- As indicated on page 5, we have changed the text to, “ILCs are decreased in the blood and intestinal lamina propria in people living with HIV-1, even after viremia has been suppressed by antiviral therapy”.

- In the Results on page 13, we have changed the text to “ILCs were decreased in all subgroups of people living with HIV-1”.

__- The text on page 18 was changed to, “The percentage of ILCs in the Lin–CD56– population decreased from 37.5% in HIV-1– controls to 7.34% in people living with HIV-1 who are viremic; the reduction in ILCs was not fully restored by ART (24.38%) or in spontaneous controllers (18.16%)” __

- As indicated on page 26 in the Discussion, we have changed the text to “HIV-1 infection permanently reduces ILCs but not NK cells”.

1. The HIV EC are not clearly discussed in the paper and are not distinguished from viremic controllers. If ILCs are permanently reduced in this group, what does this suggest for the role of this cell subset in HIV control? Plasticity between ILC and NK cells is described. Is this plasticity relevant at all for HIV control, elite or otherwise? We thank the reviewer for asking us to clarify these important points in the manuscript:

2. Though elite controllers suppress HIV-1 viremia to undetectable levels, ILC numbers are still decreased in these individuals. Additionally, we do not detect an inverse correlation between ILC numbers and viremia. Further, our previous publication showed that ILC reductions in HIV-1 infection correlate inversely with markers of systemic inflammation, for example sCD14 _(Wang et al_, 2020b)_. Like other people living with HIV-1 infection, elite controllers have elevated microbial translocation, suggestive of disturbed gut homeostasis (Brenchley _et al, 2006)_. Some studies have even reported higher rates of cardiovascular disease in elite controllers, presumably as a result of higher levels of systemic inflammation_ (Crowell et al. 2015; Caetano et al. 2022).____ Taken together, these observations suggest that ILCs play no direct role in control of HIV-1 replication. These points are discussed on page 26-27. __

3. The fascinating question of plasticity between ILCs and NK cells is one we have explored extensively, both in our previous work and in the current manuscript. Plasticity has been reported between intraepithelial ILC1s and NK cells from tumor tissue, and between ILC3s and NK cells in tonsil _(Moreno-Nieves et al_, 2021; Raykova _et al, 2017; Cortez _et al, 2017)_. When ILC2s are cultured in vitro with IL-12, IFN-γ and TBX21 expression are upregulated to the levels of CD56hiNK cell (Lim _et al, 2016)_, indicating possible plasticity between ILC2 and CD56hiNK cells under certain inflammatory conditions. In HIV-1 infection, we do not detect correlations between the decrease in ILCs and increase in NK cells. In fact, the total NK cells did not change in HIV-1+ people who are viremic, on ART, or viremic controllers [(Figure 2A and 2B in (Wang _et al, 2020b)____]. Our transcriptome analysis indicates that, during HIV-1 infection, ILCs are likely depleted by inflammation-induced apoptosis (Figure 4I and Supplemental Table 6). However, whether blood ILCs (ILCPs or ILC2s) can upregulate TBX21 and EOMES to give rise to NK cells during HIV-1 infection is an interesting question worth further investigation. We now discuss the reviewer’s question on pages 27. __ III. The authors write that ILCs have a primary role in cytokine secretion and then distinguish the ILCs from NKs....but NKs also secrete cytokines. Can the authors please clarify their text?

__The reviewer is correct that, in this context, our statement is confusing. We have therefore deleted the sentence “Typical of cells with a primary role in secretion of cytokines…” on page 10. This change helps to focus the text on the specific genes that distinguish these subsets. __

1. Discussion (an also Results) - The authors use pseudotime analysis to show that CD56+NK cells sit between the ILCs and CD56-NKs. When initially described in the Discussion they don't really interpret this in terms of their (and others' observations) that CD56-NKs are increased in disease. Other groups have suggested CD56-NKs are dysfunctional. Here you show different granzyme profiles between CD56+ and CD56- NKs. Elsewhere you distinguish CD56dim and CD56- NKs in terms of functionality in HIV+ donors, though these cells cluster on the pseudotime analysis. The IL-2 and CD4+ T cell data add another layer of complexity.
2. Altogether, I am unclear on the authors' interpretation of their collective data.
3. Can you please clarify whether you are suggesting that CD56dimNKs are a distinct from CD56+ NKs but functional as opposed to CD56-NKs that are dysfunctional? __It would be best to respond to these two questions together. It is important to remember that our manuscript describes the characterization of these cells using several techniques. __

- By flow cytometry, NK cells can be separated into CD56hi, CD56dim, and CD56neg populations (Figure 1F). Pseudotime analysis of our single cell RNA-Seq data showed that, at the transcriptional level, CD56dim and CD56neg NK cells are very similar to each other and cluster together (Figures 3A and 3F). Nonetheless, as compared with CD56dim NK cells, CD56neg NK cells express lower levels of GZMA and PRF1 (Supplemental Figure 4A), and produce less IFN-γ upon cytokine stimulation (Figures 8H and 8J). And when CD56neg NK cells are sorted and assessed by Bulk RNA-Seq, which gives deeper coverage than single cell RNA-Seq, metabolic gene expression is altered with respect to CD56dim NK cells (Figure 9).

__- Our pseudotime analysis based on single cell RNA-Seq showed that CD56hiNK cells form a distinct cluster, but that they share some transcriptional features with both the ILC cluster and the CD56dim/CD56–NK cell cluster (Figures 3A-3C and 3F). __

- In people living with HIV-1, as assessed by flow cytometry, CD56neg NK cells increase in number at the expense of CD56dim NK cells (Figure 7C). And yes, we show here that CD56neg NK cells expand in tissue culture if CD4+ T cells are depleted from the PBMCs, and addition of exogenous IL-2 prevents the switch from CD56dimNK cells to CD56–NK cells (Figures 8A-8C). These points are covered in the Results and Discussion on pages 11 and page 29-30.

1. Are CD56-NKs end-stage or can they be rescued? IL-2 treatment of CD56–NK cells from people living with HIV-1 can be converted back to CD56dimNK cells, though function is not fully restored to the level of CD56dimNK cells ____(Mavilio ____et al_, 2005)_. ____In our manuscript, we showed that IL-2 or IL-15 treatment can prevent CD56dimNK cells from becoming dysfunctional CD56–NK cells, and that these cytokines maintain mTOR activity (Figure 8A-D, 8G, 8I and Figure 10). Taking together our data with the published data, CD56–NK cells appear to be an end-stage dysfunctional cell. Whether conditions can be found for full restorage of function is an important question that is worth pursuing. This point is now stated on page 30.

2. CD8 T cell number remain high post ART and very much drive the ongoing inverted CD4:CD8 ratio. Have the authors consider how and if the need of these cells for IL-2 impact recovery of NK cell populations? __Two orthogonal experiments indicate that IL-2 secreted by CD4+ T cells, but not from CD8+ T cells, is responsible for the recovery of CD56dimNK cells after treatment with ART. In our ex vivo culture of PBMCs, depletion of CD4+ T cells , but not of CD8+ T cells, was associated with increased numbers of CD56–NK cells (Supplemental Figure 6A). Additionally, the IL-2 concentration in plasma from people living with HIV-1 correlated with CD4+ T cell numbers, but not with CD8+ T cell numbers (Figures 8N and 8O). __

3. Discussion: It would be very helpful if the authors can pull this large volume of data together in a summary paragraph and possibly also a graphic. __We thank the reviewer for the suggestion. We have now summarized our data in the discussion (page 31). Additionally, we have added bullet points with a 2 sentence summary to accompany our graphic abstract (page 3). __

4. "Thus, GZMK+CD8+T cells appear to be the adaptive counterpart of CD56hiNK cells, representing an intermediate state between cytokine producing CD4+T cells and cytotoxic CD8+T cells" For me, the 'cytokine-producing CD4+ T cells' comes from in from left field here. Can the authors please clarify or was the intent to write cytokine-producing CD8+ T cells? To clarify what we meant we need to discuss two points:

First, NK cells can be considered as the innate immune counterparts of CD8+T cells, in that both cell types are cytotoxic killer cells. In contrast, ILCs may be considered as the innate counterparts of non-cytotoxic CD4+ T helper cells. For example, like Th1 cells, ILC1 cells are TBX21+ producers of IFN-γ. And like Th2 cells, ILC2s are GATA3+ producers of IL-13. The relationship between ILCs and NK cells is similar to the relationship between CD4+T help cells and CD8+ cytotoxic T cells _(Vivier et al_, 2018)____. __

Second, previous studies showed that GZMK+CD8+T cells are distinguished from other CD8+T cells by higher expression of IL7R, TCF7, IFN-γ and TNF-α, and by decreased cytotoxic activity ____(Jonsson ____et al_, 2022)_. Thus, the relationship between GZMK+CD8+T cells and GZMK–CD8+T cells may be similar to the relationship between CD56hiNK cells (GZMK+, IL7R+, TCF7+, higher IFN-γ production and lower cytotoxicity) and cells from the CD56dim and CD56–NK cell cluster (GZMK–, IL7R–, TCF7–, lower IFN-γ production and higher cytotoxicity). In response to this comment we have modified the text on page 25-26 to make these points more clear.

VII. Methods: Were Pearson correlations applied because of the large 'n' or were data first tested for normality?

After checking the normality, nonparametric spearman correlation was performed for panels that failed the normality test. For panels with smaller n, the normality test may be not applicable, and Pearson correlation was performed.

VIII. Methods: Please clearly justify the use of t-tests throughout the manuscript rather than non-parametric based tests.

We tested the normality before performing parametric or nonparametric test. The t-test, Wilcoxon test or Mann-Whitney test used in our analysis was now specified for each panel in the legend. For panels that calculate cell percentage or numbers with smaller n, normality test may be not applicable, t-test was performed as done previously in these papers, Figure 7C and 7D in _(Wang et al_, 2020a)_, and in Figure 3 and 4 in (Xue _et al, 2022)____. We confirmed these analyses with two statisticians in our institute. __

1. Methods: How many cells were acquired in flow cytometry? How many ILCs were acquired in healthy/HIV+ donors for these studies? Did this create limitations on interpretation of phenotypic data? ILCs constitute roughly 1,000 cells per million PBMCs. To assess ILCs, we acquired data from 500,000 PBMCs, or roughly 500 ILCs per sample. NK cells constitute roughly 100,000 cells per million PBMCs, we acquired data from 200,000 PBMCs, or roughly 20,000 NK cells per sample. For each patient group, whether HIV-1-negative, HIV-1 viremic, etc, we analyzed PBMCs from at least 19 blood donors. This information is now stated in the “Flow cytometry” section in “Methods”, on page 35.

2. Methods: How was the cytokine concentrations used for in vitro assays determined? The cytokine concentrations were determined according to previous publication and our previous studies ____(Romee ____et al_, 2016, 2012; Wang _et al_, 2020b; Silverstein _et al_, 2022)_. We have added the related references to the “Stimulation conditions” section in “Method”, on page 36.

3. Figure: In Figure 4A, should it be '+ILC- ' or '+ILC' (no negative symbol)? __Yes, the reviewer is correct. We have deleted the typo “-”. __

XII. It's unclear from you single cell analysis how many cells were acquired for each of the 4 subsets. I assume less ILCs were analyzed. If so, can you please clarify for the non-bioinformatician how your bioinformatic analysis took these differences into account?

Indeed, we were concerned that we might have too few ILCs and therefore set up conditions so that similar numbers of each cell type were assessed. To accumulate enough ILCs for single cell analysis, ILCs were sorted from 3 donors. ILCs, CD56hi, CD56dim and CD56–NK cells were sorted in parallel from the same 3 donors. The sorting strategy is shown in Supplemental Figure 1D. Equal numbers of ILCs, CD56hi, CD56dim and CD56–NK cells were sorted and then mixed together before library preparation. In total, libraries were generated from 5,210 single cells using 10 x genomics. 1,478 ILC2s, 897 ILCPs, 1,116 CD56hiNK cells, and 1,486 CD56dim and CD56–NK cells were shown in UMAP. We have added this information in Figure 3 legend.

Reviewer #1 (Significance (Required)):

Overall, this paper serves as an important resource for the field.

There are areas in which the manuscript could be modified to improve clarity and detail regarding rigor (see above). The overall message of this work for understanding HIV pathogenesis is unclear but can be addressed.

__We appreciate the reviewer’s efforts on behalf of our manuscript. By carefully addressing the reviewer’s questions and comments, we believe that the rigor of our manuscript is improved and that the message regarding HIV-1-induced abnormalities of ILCs and NK cells are clarified. __

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

Summary: This manuscript makes use of RNA sequencing, ATAC-Seq and single cell sequencing to compare transcriptomes and identify relationships between various ILC/NK cell subsets in blood from uninfected controls. The authors describe differences in genes and pathways between subsets and determine that CD56high NK cells are an intermediate-connecting cell type between ILC progenitors and CD56dim NK cells. The authors show how HIV infection (viremic, ART+ or controllers) effect ILC/NK cell gene expression and pathways. One of the genes enhanced in NK cells is AREG which the authors demonstrate to be upregulated in IL/NK subsets in response to PMAI/I stimulation or stimulation with IL-2 or IL-15. The authors demonstrate that TGFB1 or knockout of RUNX3 modulates the frequency of AREG+ NK cells, implicating the Wnt signaling pathway in AREG regulation. Authors show that in PLWH, the frequency of AREG+ NK cells is altered. Authors also report that with HIV infection there is an increase in CD56neg NK cells with corresponding loss of CD56dim cells. Using healthy control PBMCs, the authors suggest differentiation of CD56dim into CD56neg is prevented by CD4 T cell production of IL-2 but promoted by TGFB1. Also in healthy controls, the authors run metabolomics to describe how CD56dim are more metabolically functional than CD56neg and link this to MTOR activity.

Major:

• Which population(s) of NK cells (high, dim or negative for CD56) are responding to stimulation with IL-2 and IL-15 by upregulating AREG in Figure 5? Does this NK population have higher expression of receptors for IL-2 and IL-15 (in single cell seq data or by flow) and if so how does receptor expression change in PLWH? We thank the reviewer for these excellent questions. In response, we have added the new figure below to Supplemental Figure 4E. In general, CD56hi NK cells have higher AREG RNA and protein than do the other NK cell subsets. After IL-2 or IL-15 stimulation, all three NK cell populations upregulate AREG, though CD56hiNK cells produce significantly higher levels of AREG than do either CD56dim or CD56negNK cells.

__Consistent with the above results, the expression of IL2RB, IL2RG and IL15RA was higher in CD56hiNK cells than in CD56dimNK cells (new Supplemental Figure 4F). __

We examined IL2RA, IL2RB, IL2RG, and IL15RA expression in the different NK cell subsets from the three groups of people living with HIV-1, ART, viremic, and controllers. As compared with cells from HIV-1-negative people, the only clearly significant difference for these four genes was a reduction in IL2RB expression in CD56– and CD56dim NK cells from viremic people. These points are now mentioned on page 15.

• Does signaling through IL-2 or IL-15 converge on the TCF7/Wnt signaling pathway? For example, is it possible to knockdown TCF7 then stimulate with IL-2 or IL-15 and measured AREG+ cells with the idea that loss of TCF7 would result in reduced cytokine-induced activation of AREG if mediated through the Wnt pathway? Indeed, this question was very important to us and we attempted to answer it with lentiviral vector-mediated knockdown with shRNA and with electroporation of Cas9 ribonucleoprotein complexes (RNPs). Though we were successful in decreasing TCF7 protein, to render NK cells competent for lentiviral transduction or for electroporation with the Cas9 RNPs, NK cells must first be cultured for at least 7 days in high concentration IL-2. This treatment with IL-2 activates AREG production before TCF7 protein is decreased. These points are now discussed in the manuscript on page 29.

• In Figure 8 the authors demonstrate that CD4 T cells promote the maintenance of CD56dim NK cells likely through production of IL-2. Was AREG expression examined in these studies and if so could you conclude that CD4 T cells also promote AREG expression in this population? Yes, indeed, CD4+T cells, or IL-2, promote AREG production by CD56dimNK cells. Depletion of CD4+T cells from PBMCs decreased AREG production and addition of exogenous IL-2 was sufficient to restore AREG production by NK cells when CD4+ T cells were depleted (see figure below, left panel). Additionally, IL-2 neutralizing antibodies decreased AREG production by NK cells in total PBMC cultures (right panel). These results are now included as Supplemental Figure 6G and 6H in the revised manuscript.

• In Figure 8D, although significant, the increase in percentage from 2-4% of the CD56neg is a minimal change. Could a higher dose of IL-2 be tested to see more substantial changes? Similar comment for Figure 10D, although significant, the increase in percentage from 2-4% of the NK population to CD56neg is not a large change with rapamycin. Could a higher dose be tested (that does not kill the cells) or a different inhibitor be used to see more substantial changes? More robust changes would strengthen the conclusions. First to clarify, as concerns figure 8D, we believe the reviewer is referring to IL-2 neutralizing antibody, not IL-2. Regarding Figure 8D, which used IL-2 neutralizing antibody at 4 ug/ml, we tried a higher dose (10 ug/ml) but this caused cell death. We also tried longer culture time with 4 ug/ml IL-2 neutralizing antibody, and found the cell viability decreases after 7 days culture. Similarly, the limited in vitro culture time in the presence of anti-IL-2 antibody restricted experimental conditions in Figure 10D.

• In Figure 10, was the increase in pmTOR with IL-2/IL-15 stimulation specifically observed in CD56dim cells (rather than total NK cells or CD56neg cells)? This would strength the conclusion that CD56dim is more metabolically functional than CD56neg. Our data indicate that the mTOR response to IL2 in CD56–NK cells was similar to that in CD56+NK cells (including CD56dim and CD56hi) (see figure below). This result is consistent with a previous report showing that, when stimulated with exogenous IL-2, sorted CD56– NK cells become CD56dimNK cells ____(Mavilio ____et al_, 2005)_. Our data extend this observation by showing that upregulation of CD56 on CD56neg NK cells by IL-2 correlates with mTOR upregulation.

Minor

• Approximately how many ILC from PLWH were submitted for single cell sequencing: Since this cell population was depleted in HIV+, was there a sufficient number of cells to interpret/publish DEG results in Figure 4? In Figure 4, ILCs were sorted from HIV-1 negative donors and different groups of PLWH, and then these cells were subjected to bulk-RNA seq using CEL-Seq2. In Figure 4, for most blood donors, whether HIV-1 negative or PLWH, well over 1,000 ILCs were sorted and used to construct high quality libraries (see figure below, was included as new Supplemental Figure 3C). PCA plots also showed that all ILC libraries clustered together as a distinct population (Figure 4A), indicating the quality of all ILC libraries was comparable.

• On page 13 of text, it is a bit disconcerting to jump to Figure 7 then back to Figure 4. Would recommend reorganizing text or figure panels to flow better. __We have deleted the premature mention of Figure 7A. __

• Supplemental Figure 1 and 2: Dots for ILC population are purple in color but legend is mislabeled as pink color.

• Supplemental Figure 4: Dots for HIV+ controller are purple in color, but legend is mislabeled as pink in color. Thank you, these mistakes in the labeling of the colors have been corrected.

• Would recommend adding quantification of Figure 5A for all donors tested. In fact, the AREG production by CD56hi, CD56dim, CD56–NK cells and ILCs from HIV-1 negative donors were quantified in Figure 6A.

• Figure 5B for IFNg it appears that part of the positive population is not gated on and thus percentages are likely higher if the gate is adjusted. We thank the reviewer for the suggestion. The gating for IFN-γ has been adjusted in the revised manuscript, as suggested. The original Figure 5B and associated histogram Figure 5C were replaced accordingly. Please see the newly gated figure below:

• For Figure 5F, need to add to text and panel that PMA/I was used to stimulate as described in figure legend. Current figure and text read that the Wnt agonist alone was responsible for levels depicted in NK subsets. We now state that PMA+ionomycin was used to stimulate the cells in Figure 5F and 5G, and in the text (page 16 and 28).

• On the x-axis of Figure 6F-J does "Lin-TBX21+" refer to Total NK cells? If so then would recommend sticking with nomenclature "Total NK" as in Figure 6A-B. The x-axis of Figure 6F-J was changed to “total NK (Lin–TBX21+)”.

• Would recommend labeling gates for populations of interest in Supplemental Figure 5B-C, Supplement Figure 6A, Figure 8A. The populations of interest (CD56dimNK, CD56–NK, and ILCs) were labeled as suggested.

• Other groups have shown that CD56neg are increased in HIV, functionally impaired and correlate with loss of CD4 T cells. Would recommend citing their studies. The original manuscript had mentioned only Mavilio et al. The revised manuscript now has a more complete list of references ____(Cao ____et al_, 2021; Mavilio _et al_, 2005; Cocker _et al_, 2022; Alter _et al_, 2005; Barker _et al_, 2007)_. These references are cited in the Introduction (page 5) and in the Results (page 20).

• Would recommend adding quantification of Figure 8A for all donors tested. Also, for the 3rd flow plot does "NK+CD4" mean purified NK cells + autologous CD4 T cells? If so, then would clarify in figure legend. It may strengthen conclusion for IL-2/IL-15 to show differentiation of NK cells is not contact dependent with T cell via transwell assay. __Quantification for all donors in Figure 8A has been added to the revised manuscript (Figure 8A, right panel). The figure legend has been modified accordingly. As far as the comment about contact-dependence, the fact that CD56dimNK cells were maintained by IL-2 in the absence of CD4+ T cells demonstrates that direct contact with CD4+ T cells is not required. __

Reviewer #2 (Significance (Required)):

Significance: This study is valuable because it generates large datasets on the NK/ILC family from human blood that can be deposited in repositories and of special relevance to the HIV field because it examine show viral infection (controlled or not) effects these subsets.

The strengths of the study are the cohort of PBMC samples utilized (HIV-, HIV+ viremic, HIV+ ART+ and HIV+ controlled), the multi-omics approach for transcriptome and epigenetics and the in vitro mechanistic studies identifying key regulators of NK cell differentiation/function.

The study advances the field "mechanistically" by providing key targets that may be subject to therapeutic modulation in PLWH such as AREG, IL-2 signaling, IL-15 signaling, Wnt signaling, and mTOR activity (although more work will need to be done to examine these pathways using PBMCs from HIV+). This study advances the field "conceptually" by providing large datasets for others to mine if deposited.

The audience for this study "basic research" such as immunologists in the HIV field or immunologist interested in ILC/NK biology.

My field of expertise is infectious disease (HIV, SARS-CoV-2), basic immunology (ILC, NK, B cell) and autoimmune disease. Would recommend additional reviewers for assessment of metabolic genes/pathways in Figure 9-10.

__We were very pleased to see that the reviewer thought our manuscript makes a valuable contribution to HIV-1 immunology and ILC/NK biology, that it advances mechanistic understanding of pathogenesis in people living with HIV-1, and that it provides a valuable data resource. __

- In Figure 9, the metabolism related genes were defined as canonical targets of, or regulated by, MTOR signaling, in previous publications ____(Saxton & Sabatini, 2017; Bayeva ____et al_, 2012)_.

- In Figure 10, we used pMTOR, pAKT, p4EBP1, pS6 and CD71 to monitor MTOR pathway activation as reported previously by others ____(Marçais ____et al_, 2014)_. We have cited this paper on pages 23 and 24.

References for Response to Reviewers

Alter G, Teigen N, Davis BT, Addo MM, Suscovich TJ, Waring MT, Streeck H, Johnston MN, Staller KD, Zaman MT, et al (2005) Sequential deregulation of NK cell subset distribution and function starting in acute HIV-1 infection. Blood 106: 3366–3369

Barker E, Martinson J, Brooks C, Landay A & Deeks S (2007) Dysfunctional natural killer cells, in vivo, are governed by HIV viremia regardless of whether the infected individual is on antiretroviral therapy. AIDS 21: 2363–2365

Bayeva M, Khechaduri A, Puig S, Chang H-C, Patial S, Blackshear PJ & Ardehali H (2012) mTOR regulates cellular iron homeostasis through tristetraprolin. Cell Metab 16: 645–657

Brenchley JM, Price DA, Schacker TW, Asher TE, Silvestri G, Rao S, Kazzaz Z, Bornstein E, Lambotte O, Altmann D, et al (2006) Microbial translocation is a cause of systemic immune activation in chronic HIV infection. Nat Med 12: 1365–1371

Caetano DG, Ribeiro-Alves M, Hottz ED, Vilela LM, Cardoso SW, Hoagland B, Grinsztejn B, Veloso VG, Morgado MG, Bozza PT, et al (2022) Increased biomarkers of cardiovascular risk in HIV-1 viremic controllers and low persistent inflammation in elite controllers and art-suppressed individuals. Sci Rep 12: 6569

Cao W-J, Zhang X-C, Wan L-Y, Li Q-Y, Mu X-Y, Guo A-L, Zhou M-J, Shen L-L, Zhang C, Fan X, et al (2021) Immune Dysfunctions of CD56neg NK Cells Are Associated With HIV-1 Disease Progression. Front Immunol 12: 811091

Cocker ATH, Liu F, Djaoud Z, Guethlein LA & Parham P (2022) CD56-negative NK cells: Frequency in peripheral blood, expansion during HIV-1 infection, functional capacity, and KIR expression. Front Immunol 13: 992723

Cortez VS, Ulland TK, Cervantes-Barragan L, Bando JK, Robinette ML, Wang Q, White AJ, Gilfillan S, Cella M & Colonna M (2017) SMAD4 impedes the conversion of NK cells into ILC1-like cells by curtailing non-canonical TGF-β signaling. Nat Immunol 18: 995–1003

Crowell TA, Gebo KA, Blankson JN, Korthuis PT, Yehia BR, Rutstein RM, Moore RD, Sharp V, Nijhawan AE, Mathews WC, et al (2015) Hospitalization Rates and Reasons Among HIV Elite Controllers and Persons With Medically Controlled HIV Infection. J Infect Dis 211: 1692–1702

Jonsson AH, Zhang F, Dunlap G, Gomez-Rivas E, Watts GFM, Faust HJ, Rupani KV, Mears JR, Meednu N, Wang R, et al (2022) Granzyme K+ CD8 T cells form a core population in inflamed human tissue. Sci Transl Med 14: eabo0686

Lim AI, Menegatti S, Bustamante J, Le Bourhis L, Allez M, Rogge L, Casanova J-L, Yssel H & Di Santo JP (2016) IL-12 drives functional plasticity of human group 2 innate lymphoid cells. J Exp Med 213: 569–583

Marçais A, Cherfils-Vicini J, Viant C, Degouve S, Viel S, Fenis A, Rabilloud J, Mayol K, Tavares A, Bienvenu J, et al (2014) The metabolic checkpoint kinase mTOR is essential for IL-15 signaling during the development and activation of NK cells. Nat Immunol 15: 749–757

Mavilio D, Lombardo G, Benjamin J, Kim D, Follman D, Marcenaro E, Angeline O’Shea M, Kinter A, Kovacs C, Moretta A, et al (2005) Characterization of CD56–/CD16+ natural killer (NK) cells: A highly dysfunctional NK subset expanded in HIV-infected viremic individuals. Proc Natl Acad Sci U S A 102: 2886–2891

Moreno-Nieves UY, Tay JK, Saumyaa S, Horowitz NB, Shin JH, Mohammad IA, Luca B, Mundy DC, Gulati GS, Bedi N, et al (2021) Landscape of innate lymphoid cells in human head and neck cancer reveals divergent NK cell states in the tumor microenvironment. Proc Natl Acad Sci U S A 118

Raykova A, Carrega P, Lehmann FM, Ivanek R, Landtwing V, Quast I, Lünemann JD, Finke D, Ferlazzo G, Chijioke O, et al (2017) Interleukins 12 and 15 induce cytotoxicity and early NK-cell differentiation in type 3 innate lymphoid cells. Blood Adv 1: 2679–2691

Romee R, Rosario M, Berrien-Elliott MM, Wagner JA, Jewell BA, Schappe T, Leong JW, Abdel-Latif S, Schneider SE, Willey S, et al (2016) Cytokine-induced memory-like natural killer cells exhibit enhanced responses against myeloid leukemia. Sci Transl Med 8: 357ra123

Romee R, Schneider SE, Leong JW, Chase JM, Keppel CR, Sullivan RP, Cooper MA & Fehniger TA (2012) Cytokine activation induces human memory-like NK cells. Blood 120: 4751–4760

Saxton RA & Sabatini DM (2017) mTOR Signaling in Growth, Metabolism, and Disease. Cell 169: 361–371

Silverstein NJ, Wang Y, Manickas-Hill Z, Carbone C, Dauphin A, Boribong BP, Loiselle M, Davis J, Leonard MM, Kuri-Cervantes L, et al (2022) Innate lymphoid cells and COVID-19 severity in SARS-CoV-2 infection. Elife 11

Vivier E, Artis D, Colonna M, Diefenbach A, Di Santo JP, Eberl G, Koyasu S, Locksley RM, McKenzie ANJ, Mebius RE, et al (2018) Innate Lymphoid Cells: 10 Years On. Cell 174: 1054–1066

Wang J, Xu Y, Chen Z, Liang J, Lin Z, Liang H, Xu Y, Wu Q, Guo X, Nie J, et al (2020a) Liver Immune Profiling Reveals Pathogenesis and Therapeutics for Biliary Atresia. Cell 183: 1867–1883.e26

Wang Y, Lifshitz L, Gellatly K, Vinton CL, Busman-Sahay K, McCauley S, Vangala P, Kim K, Derr A, Jaiswal S, et al (2020b) HIV-1-induced cytokines deplete homeostatic innate lymphoid cells and expand TCF7-dependent memory NK cells. Nat Immunol 21: 274–286

Xue R, Zhang Q, Cao Q, Kong R, Xiang X, Liu H, Feng M, Wang F, Cheng J, Li Z, et al (2022) Liver tumour immune microenvironment subtypes and neutrophil heterogeneity. Nature 612: 141–147

It's difficult to wrap your head around this, but it's true, there are more sources on YouTube and other media, possibly more variety of people to agree with. But interestingly the loss of credibility and journalism is ok with this source. There are some social media based journalists that do a good job, but almost three times as much online that spread misinformation.

This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.79), and has published the reviews under the same license. These are as follows.

**Reviewer 1. Xuanmin Guang **

Han et al. had carried out genome assembly of Aplectana chamaeleonis, analysised the genome’s repeat content and annotated the genome. They descripted the geneset’s function and done a PSMC analysis. The genome is a key source for research, but there are so many mistakes in the manuscript, I suggest the author to revies the manuscript carefully and the grama and content should be re-organized. Some suggestions have been listed below:

1. In the context part, the first two sentence lacks continuity in logic, please change them.
2. The author didn’t mention which sequence platform they had used in the context, I think this should be added.
3. The average sequence length in the table is 496kbp, but the author it as 496Mbp , this is a mistake.
4. In table 1, why there aren’t any gaps in the scaffold genome?
5. The author said that “This suggests that the significant expansion of repeating elements is an important manifestation of species differences”. Its unreasonable to get this conclusion only based your genome repeat analysis.
6. In the text they claim that 12887 function gene had annotated, I want to know how much gene they have annotated? Please add this in the manuscript.
7. Too many decimal places have been used in the Table2.

Re-review: The author revised the paper as I concerned in the report and the paper could be accepted now.

Reviewer 2. Jianbin Wang

In this manuscript, Hou et al. present a genome assembly for Aplectana chamaeleonis, a parasitic nematode that infects amphibians. They report a genome of ~1 Gb, most of which is composed of repetitive elements. This genome draft is significant as it is the first assembled for this or any Cosmocercidae species. It may provide insights into the evolution of the nematodes – if it is thoroughly compared to other nematode genomes. It may also allow for better species identification than previous morphological methods. While the conclusions on genome size and composition described in the paper appear sound, there are many questions that go unanswered. The reasoning behind why this research was undertaken is not clear. What is the ecological or agricultural and economic impact of the species? How would the genome provide a better understanding of this species? More specific information is also needed to better understand the genome. How many chromosomes does this species have? Is there any cytology to help answer this question? Any notion of sex chromosome vs. autosome? This genome is much bigger than most of the assembled parasitic nematodes. The author did not make any efforts to explain what might contribute to this. Could the big size due to contamination in the samples used? Judging from the images, it does not look very convincing to me how clean the sample was for the genomic DNA extraction. Overall, there is a lack of in-depth data analysis and comparison between this genome and many other available nematode genomes. About the overall presentation and organization of the manuscript, the context is often lacking from results. How do these results compare to related species? How does figure 4/the demographic history fit in to this story? A round of general proofreading needs to be done for grammar, punctuation, capitalization, italics, etc – see below for some specific examples. In the Abstract, the repeat content in the Ascaris genome is 72.45%, and the total length is more than 742 Mb. The math does not add up (1.1 Gb x 72.45% = 797 Mb). Or do you mean the Aplectana genome? Should say total length of repeats. Why is this “Ascaris” genome? Ascaris is a parasite that infects pigs and human. Some sentences need addressing/clarification: Page 1. “and their diversity is also very high, many of which are above the national second-level protected animals” – what is the significance of this/how are these ideas related? Page 2. “Through the characteristics of the genome sequence, it shows that the genome is a highly continuous genome” – need to be more specific with metric and data. Page 4. “In addition, the enrichment of A. chamaeleonis genes in all metabolic pathways was found in twelve metabolic pathways.” – not sure what you are trying to say about the all or 12 pathways. Figure 1. - Images need scalebars. In A, what is the mat of material? For A, crop out area around the worm and enlarge the worm image. In B the worm is dark/shows little contrast or detail. In C, label which image is the head and which is the tail (or specify left vs. right in the legend text). The images in B and C look like they were taken using a cell phone pointed at a computer monitor – are there higher quality images? Table 1. – Why is the data in all four columns the exact same? What is the difference between each column? This appear to be a mistake when preparing the table. Very sloppy and unfortunate! Table 2 – Significant figures on the %s?. Is the “other” category needed (same for Fig2C)? Table 3 – Check text spacing (e.g. % in genome). Figure 3 – Recommend to redo the spacing of figures, increase size of text in each part of this figure. Need to refer to parts of figures in the body/text (Fig 3a vs. 3b vs. 3c). Can 3b be sorted from most number of genes to least? Figure 4 is not referenced in the body text. Consider merging Fig 4 with Fig 3. Figure 4 is lacking a description in the legend – what are the grey lines, definition of LGM? The x-axis scale and orientation are unintuitive – is the present on the left and the past on the right? Past should be on the left. Methods Genomic DNA was purification for Long-reads libraries preparation – should say purified What is the meaning of “The generation we used was 0.17” – what generation is this? and “the mutation rate was 9×10-9” needs units. The sentence “we used the pairwise sequentially Markovian coalescent (PSMC) model to estimate the effective population size of A. chamaeleonis within last million years.” should be moved to the section immediately after its current location.

Re-review: Overall, the writing has been improved in several places and is somewhat clearer than in the previous draft. These changes are mostly related to the minor concerns raised. However, many questions related to the broader impact of this research and how the new genome compares to other nematode species remain unanswered. The following comments were largely ignored. 1. The reasoning behind why this research was undertaken is not clear. 2. What is the ecological or agricultural and economic impact of the species? How would the genome provide a better understanding of this species? 3. More specific information is also needed to better understand the genome. How many chromosomes does this species have? Is there any cytology to help answer this question? Any notion of sex chromosome vs. autosome? 4. This genome is much bigger than most of the assembled parasitic nematodes. The author did not make an effort to explain what might contribute to this. 5. Overall, there is a lack of in-depth data analysis and comparison between this genome and many other available nematode genomes. How do these results compare to related species? 6. About the overall presentation and organization of the manuscript, the context is often lacking from results. Another round of general proofreading needs to be done for grammar, punctuation, capitalization, italics, etc. – see below for additional specific examples. The authors, not the reviewers, need to make a concerted effort to read and proofread their own manuscript.

In addition to the big picture points raised above, several other issues that were either brought up last time or are new and need to be addressed: 1. Not sure Table 1 is present the right way. The columns and rows should be reversed, I think. If so, there will be only one column - do you still need a table? 2. “Through the characteristics of the genome sequence, it shows that the genome is a highly continuous genome.” Unclear. The authors mentioned that they have fixed this in their response to the reviewers, but no change was seen in the updated manuscript. 3. “The generation we used was 0.17, and the mutation rate was 9×10-9 [8].” These numbers need units after them. Again, this was addressed in the response but not written out or clarified in the revised text. 4. “In addition, the enrichment of A. chamaeleonis genes in all metabolic pathways was found in twelve metabolic pathways.” Not sure what the authors were trying to say about the all or 12 pathways. Still confusing. 5. Photographs of the worms are still lacking scale bars. 6. Make sure that all genus and species names are italicized (in body text and in Fig.3). 7. Make section heading format is consistent (check capitalization). 8. “The results showed that 91 % of the sequences were compared to Arthropoda (1898/2088) and 7 % were compared to Arthropoda (122/2088).” Both of these say Arthropoda - is that a mistake? Also "compared to" is not the correct word, maybe "similar to"? 9. LGM acronym is defined after the second use of "last glacial period", should appear after the first use. Also, LGM stands for last glacial maximum, not period. This should be corrected.

Reviewer #3 (Public Review):

The author is trying to identify the mefenamic (Mef) binding site and DIDS binding site on the KCNQ1 KCNE1 complex. The authors also try to identify the mechanism of interactions using electrophysiological recording, calculating V1/2 of different mutants, and looking at the instantaneous current and the tail current. The contribution of each residue within the binding pocket was analysed using GBSA and PBSA and traditional molecular dynamics simulation. The author is trying to argue that they share the same binding pocket and their mechanism of activation.

Strengths:

1. The effect of the WT channel in the presence of 100 uM Mef is very clear, and such an effect is clearly decreased with the E1-K41C and W323A mutation. The milder effect was observed with Q147C and Y148C mutants.

2. The effect of the WT channel in the presence of 100 uM DIDS is, again, very clear, and such an effect is clearly decreased with the E1-Y46C.

3. The author has indeed achieved their aim in addressing that the binding site for both DIDS and Mef are adjacent to each other and may indeed share a pocket in the S1-E1-pore pocket. This may help the field with drug development, targeting that region in the future.

Weaknesses:

1. The computational aspect of the work is rather under-sampled - Figure 2 and Figure 4. The lack of quantitative analysis on the molecular dynamic simulation studies is striking, as only a video of a single representative replica is being shown per mutant/drug. Given that the simulations shown in the video are extremely short; some video only lasts up to 80 ns. Could the author provide longer simulations in each simulation condition (at least to 500 ns or until a stable binding pose is obtained in case the ligand does not leave the binding site), at least with three replicates per each condition? If not able to extend the length of the simulations due to resources issue, then further quantitative analysis should be conducted to prove that all simulations are converged and are sufficient. Please see the rest of the quantitative analysis in other comments.

2. Given that the protein is a tetramer, at least 12 datasets could have been curated to improve the statistic. It was also unclear how frequently the frames from the simulations were taken in order to calculate the PBSA/GBSA.

3. The lack of labels on several structures is rather unhelpful (Figure 2B, 2C, 4B). The lack of clarity of the interaction map in Figures 2D and 6A.

4. The RMSF analysis is rather unclear and unlabelled thoroughly. In fact, I still don't quite understand why n = 3, given that the protein is a tetramer. If only one out of four were docked and studied, this rationale needs to be explained and accounted for in the manuscript.

5. For the condition that the ligands suppose to leave the site (K42C for Mef and Y46A for DIDS), can you please provide simulations at a sufficient length of time to show that ligand left the site over three replicates? Given that the protein is a tetramer, I would be expecting three replicates of data to have four data points from each subunit. I would be expecting distance calculation or RMSD of the ligand position in the binding site to be calculated either as a time series or as a distribution plot to show the difference between each mutant in the ligand stability within the binding pocket. I would expect all the videos to be translatable to certain quantitative measures.

6. Given that K41 (Mef) and Y46 are very important in the coordination, could you calculate the frequency at which such residues form hydrogen bonds with the drug in the binding site? Can you also calculate the occupancy or the frequency of contact that the residues are making to the ligand (close 4-angstrom proximity etc.) and show whether those agree with the ligand interaction map obtained from ICM pro in Figure 2D?

7. Given that the author claims that both molecules share the same binding site and the mode of ligand binding seems to be very dynamic, I would expect the authors to show the distribution of the position of ligand, or space, or volume occupied by the ligand throughout multiple repeats of simulations, over sufficient sampling time that both ligand samples the same conformational space in the binding pocket. This will prove the point in the discussion - Line 463-464. "We can imagine a dynamic complex... bind/unbind from Its at a high frequency".

8. I would expect the authors to explain the significance and the importance of the PBSA/GBSA analysis as they are not reporting the same energy in several cases, especially K41 in Figure 2 - figure supplement 2. It was also questionable that Y46, which seems to have high binding energy, show no difference in the EPhys works in figure 3. These need to be commented on.

9. Can the author prove that the PBSA/GBSA analysis yielded the same average free energy throughout the MD simulation? This should be the case when the simulations are converged. The author may takes the snapshots from the first ten ns, conduct the analysis and take the average, then 50, then 100, then 250 and 500 ns. The author then hopefully expects that as the simulations get longer, the system has reached equilibrium, and the free energy obtained per residue corresponds to the ensemble average.

10. The phrase "Lowest interaction free energy fort residues in ps-KCNE1 and selected KCNQ1 domains are shown as enlarged panels (n=3 for each point)" needs further explanation. Is this from different frames? I would rather see this PBSA and GBSA calculated on every frame of the simulations, maybe at the one ns increment across 500 ns simulations, in 4 binding sites, in 3 replicas, and these are being plotted as the distribution instead of plotting the smallest number. Can you show each data point corresponding to n = 3?

11. I cannot wrap my head around what you are trying to show in Figure 2B. This could be genuinely improved with better labelling. Can you explain whether this predicted binding pose for Mef in the figure is taken from the docking or from the last frame of the simulation? Given that the binding mode seems to be quite dynamic, a single snapshot might not be very helpful. I suggest a figure describing different modes of binding. Figure 2B should be combined with figure 2C as both are not very informative.

12. Similar to the comment above, but for figure 4B. I do not understand the argument. If the author is trying to say that the pocket is closed after Mef is removed - then can you show, using MD simulation, that the pocket is openable in an apo to the state where Mef can bind? I am aware that the open pocket is generated through batches of structures through conformational sampling - but as the region is supposed to be disordered, can you show that there is a possibility of the allosteric or cryptic pocket being opened in the simulations? If not, can you show that the structure with the open pocket, when the ligand is removed, is capable of collapsing down to the structure similar to the cryo-EM structure? If none of the above work, the author might consider using PocketMiner tools to find an allosteric pocket (https://doi.org/10.1038/s41467-023-36699-3) and see a possibility that the pocket exists.

13. Figure 4C - again, can you show the RMSF analysis of all four subunits leading to 12 data points? If it is too messy to plot, can you plot a mean with a standard deviation? I would say that a 1-1.5 angstroms increase in the RMSF is not a "markedly increased", as stated on line 280. I would also encourage the authors to label whether the RMSF is calculated from the backbone, side-chain or C-alpha atoms and, ideally, compare them to see where the dynamical properties are coming from.

14. In the discussion - Lines 464-467. "Slowed deactivation of the S1/KCNE1/Pore domain/drug complex ....... By stabilising the activated complex. MD simulation suggests the latter is most likely the case." Can you point out explicitly where this has been proven? If the drug really stabilised the activated complex, can you show which intermolecular interaction within E1/S1/Pore has the drug broken and re-form to strengthen the complex formation? The authors have not disproven the point on steric hindrance either. Can this be disproved by further quantitative analysis of existing unbiased equilibrium simulations?

15. Figure 4D - Can you show this RMSF analysis for all mutants you conducted in this study, such as Y46C? Can you explain the difference in F dynamics in the KCNE3 for both Figure 4C and 4D?

16. Line 477: the author suggested that K41 and Mef may stabilise the protein-protein interface at the external region of the channel complex. Can you prove that through the change in protein-protein interaction, contact is made over time on the existing MD trajectories, whether they are broken or formed? The interface from which residues help to form and stabilise the contact? If this is just a hypothesis for future study, then this has to be stated clearly.

17. The author stated on lines 305-307 that "DIDS is stabilised by its hydrophobic and vdW contacts with KCNQ1 and KCNE1 subunits as well as by two hydrogen bonds formed between the drug and ps-KCNE1 residue L42 and KCNQ1 residue Q147" Can you show, using H-bond analysis that these two hydrogen bonds really exist stably in the simulations? Can you show, using minimum distance analysis, that L42 are in the vdW radii stably and are making close contact throughout the simulations?

18. Discussion - In line 417, the author stated that the "S1 appears to pull away from the pore" and supplemented the claim with the movie. This is insufficient. The author should demonstrate distance calculation between the S1 helix and the pore, in WT and mutants, with and without the drug. This could be shown as a time series or distribution of centre-of-mass distance over time.

19. Given that all the work were done in the open state channel with PIP2 bound (PDB entry: 6v01), could the author demonstrate, either using docking, or simulations, or alignment, or space-filling models - that the ligand, both DIDS and Mef, would not be able to fit in the binding site of a closed state channel (PDB entry: 6v00). This would help illustrate the point denoted Lines 464-467. "Slowed deactivation of the S1/KCNE1/Pore domain/drug complex... By stabilising the activated complex. MD simulation suggests the latter is most likely the case."

20. I struggle with the term "normalised response" on Line 208. What is it being normalised to? Can this be put more explicitly in the text? If normalised to WT, why is WT EQ response only 0.8?

21. The author stated that the binding pose changed in one run (lines 317 to 318). Can you comment on those changes? If the pose has changed - what has it changed to? Can you run longer simulations to see if it can reverse back to the initial confirmation? Or will it leave the site completely?

22. Binding free energy of -32 kcal/mol = -134 kJ/mol. If you try to do dG = -RTlnKd, your lnKd is -52. Your Kd is e^-52, which means it will never unbind if it exists. I am aware that this is the caveat with the methodologies. But maybe these should be highlighted throughout the manuscript.

Reviewer #2 (Public Review):

In this study, Lamire et al. use a calcium imaging approach, behavioural tests, and pharmacological manipulations to identify the molecular mechanisms behind visual habituation. Overall, the manuscript is well-written but difficult to follow at times. They show a valuable new drug screen paradigm to assess the impact of pharmacological compounds on the behaviour of larval zebrafish, the results are convincing, but the description of the work is sometimes confusing and lacking details.

The volumetric calcium imaging of habituation to dark flashes is valuable, but the mix of responses to visual cues that are not relevant to the dark flash escape, such as the slow increase back to baseline luminosity, lowers the clarity of the results. The link between the calcium imaging results and free-swimming behaviour is not especially convincing, however, that is a common issue of head-restrained imaging with larval zebrafish.

The strong focus on GABA seems unwarranted based on the pharmacological results, as only Picrotoxinin gives clear results, but the other antagonists do not give a consistent results. On the other hand, the melatonin receptor agonists, and oestrogen receptor agonists give more consistent results, including more convincing dose effects.

The pharmacological manipulation of the habituation circuits mapped in the first part does not arrive at any satisfying conclusion, which is acknowledged by the authors. These results do reinforce the disconnect between the calcium imaging and the behavioural experiments and undercut somewhat the proposed circuit-level model.

Overall, the authors did identify interesting new molecular pathways that may be involved in habituation to dark flashes. Their screening approach, while not novel, will be a powerful way to interrogate other behavioural profiles. The authors identified circuit loci apparently involved in habituation to dark flashes, and the potentiation and no adaptation clusters have not been previously observed as far as I know.

The data will be useful to guide follow-up experiments by the community on the new pathway candidates that this screen has uncovered, including behaviours beyond dark flash habituation.

Shit this is a real steal man of the situtation. It is corruption all the way down, but isin't that the same for our institutions as well? Whatever is happening right now will likely get rewritten after the regieme change, weather is be the GAE or set of Crypto DAO Protocols we will see

The use of Priests, v.s. Pastors is a common theme seen in the textbook in later chapters. Protestants (which is the perspective we see the most given that the US formed out of British control) use pastors, which for many, but not all denominations serve as a sort of coach and for lack of a better term "qualified teacher". They assist in interpreting scripture, head services, but don't possess any position or power that separates them from the laity. In Catholic theology, Priests are not only an authority in our church, but have the ability to say Mass, administer The Holy Eucharist, hear confession, give The Last Rites etc.

I think she refers to the crazies because of the culture she grew up in and continues to live in, One of Mexico's biggest values is religious, Catholic beliefs are very strong with their faith in God as for Americans as well, from all different colors, including whites. Because the bible states it is a sin to lay with the same gender, I can totally see how this can be difficult for queer people and how it would be chalked up to "loqueria"

This makes me incredibly sad. His life was severely diminished because of the careless words of another.

I chuckled reading this because I feel like quite a few people will read this and think of their own picture that may be similar to this one.

I think everyone can relate to the opening of this story. Everyone has that one photo that they own that they can tell you everything about.

This was an area that built a community together. It was an area where to cultures came together to make one and even built on each others language.

Night's notes - play them soft -

in tension with the upward design

of day's sweet melody, and write

what you hear, even if it's silence

tucked inside your solitary head

I think this information is interesting because we are being told that more than 1/3 of school children fail to progress to the next grade. I think we need to incorporate different learning styles because what if the individual doesn't understand the concept the way it is being taught. Many people learn in different ways such as hands on learning, auditory learning, and visual learning. I think the reason 10% of $400,000,000 is going into teaching children what they have learned but have failed to learn is because there maybe something up head in learning that they might need to understand for the future. I have been retaught certain things when I moved up to the next grade level and I think it is to help refresh memory. I think another reason 10% goes to reteaching is because the students didn't understand the concept and needs to be retaught so they can understand for future uses.

This song is about graduating and the coming to understanding that you will never be this young and reckless again so long live as a young kid,

The description of his clothing and appearance highlights the humble and simple nature of his attire, with his flat collar, unadorned leggings, and waxed shoes. His sword is also described as being hung from a sealskin strap, which further emphasizes his lack of extravagance.

The license to sell marijuana licenses would be given to big players in the industry first, giving them a massive head start over small businesses and storefronts. I now definitely see the issue with amendment 3.

Laurence Doud, 79, spent 25 years as chief executive officer of Rochester Drug co-operative. He is the head of a major generic- drug distributor. was sentenced to 2 1/4 tears in prison for conspiring to sell opioids to crooked pharmacies.

Lamont did in fact seek revenge for his father but at what cost?

I always liked when the cocky cop got his ego and head knocked back into place

This escalated really quickly; sister leopolda is also physically abusive.

This imply that lust is the most difficult one for humans to overcome.

I keep coming back to the individual-focused worldview we have in the west. I think our culture generally promotes the idea of individual accomplishment and ownership, while disregarding the deeply collaborative process of creating art. I wonder if this has anything to do with the conflict?

This tool seems amazing and is a renowned form of assistive technology I had not previously heard of. I struggle with an autoimmune disease which affects my fingers and makes it hard to click and drag on my touchpad. This feature is amazing for students with more severe physical disabilities

After taking a course last semester all about physical and other disabilities and the way universal design is created to accommodate and make things accessible to all-- this list here, is a big help just like universal design. As the teacher you may come across things you want to do but know that they aren't accessible to everyone when you want them to be, this list can also help you create ways to identify what is accessible, what is not, and how you can make it be! I think it is great that disability is becoming a more open term to use by many because finally the world is catching up with accessibility. There is much to imrove, but finding accessible digital tools and apps is just one way to start.

I had never thought of this before. I wonder if there is a way to turn down the sensitivity on certain devices so that people with loss of motor functioning skills can use these technology tools as well.

tmeporary migration for work

work within the public sphere alongside public sector workers

from https://learn.microsoft.com/en-us/archive/msdn-magazine/2012/june/don-t-get-me-started-the-silent-majority-why-visual-basic-6-still-thrives

This is the county's singular argument, and provided 93 pages of evidence to illustrate the facts of our life situation, namely that my daughter is in "temporary custody" by DHS and not currently in my physical custody. However, my case and argument has nothing to do with arguing those facts. I generally concede those facts as true and don't dispute them. What I dispute is that those facts, per the eligibility rules of the benefit programs, do not disqualify us from the programs, and further, specifically provide language that speaks to our life situation to make sure it is clear we are to be declared eligible and my daughter is not to be disqualified on the basis of "not living in home and not in the dependent care of her Head of Household [me]"

head asplode emoji

I am the obvious "Head of Household" between my daughter and myself as she is my biological daughter, under 18, whom I am the sole caretaker, and whom my parental rights have not been terminated. And, the open DHS child welfare case is still pre-adjudication, meaning DHS has not proven grounds for their claimed allegations they used to defend taking temporary custody, and which I strongly contest and know are not founded. Point being I have never stopped for one day, up through current day, taking daily responsibility for and being the ultimate manager of my daughter's care for all needs, that DHS's involvement was not at my doing or consent, and DHS should and I expect DHS to remove themselves immediately from infringing any further in our family.

The imagery she uses to describe this situation makes you feel like you are there with her. This quote makes you horrified of the treatment her and many others endured.

I definitely think these methods are effective i write whenever i feel angry or in my head about my fathers addiction and being able to escape to the one place you love or by doing something you love can definitely settle your mind and allow you to get ur stress or anger relived.

Author Response:

What is novel here is that we calculated the time-varying retinal motion patterns generated during the gait cycle using a 3D reconstruction of the terrain. This allows calculation of the actual statistics of retinal motion experienced by walkers over a broad range of normal experience. We certainly do not mean to claim that stabilizing gaze is novel, and agree that the general patterns follow directly from the geometry as worked out very elegantly by Koenderink and others.  We spend time describing the terrain-linked gaze behavior because it is essential for understanding the paper. We do not claim that the basic saccade/stabilize/saccade behavior is novel and now make this clearer.

The other novel aspect is that the motion patterns vary with gaze location which in turn varies with terrain in a way that depends on behavioral goals. So while some aspects of the general patterns are not unexpected, the quantitative values depend on the statistics of the behavior.  The actual statistics require these in situ measurements, and this has not previously been done, as stated in the abstract.

The measured statistics provide a well-defined set of hypotheses about the pattern of direction and speed tuning across the visual field in humans. Points of comparison in the existing literature are hard to find because the stimuli have not been closely matched to actual retinal flow patterns, and the statistics will vary with the species in question. However, recent advances allow for neurophysiological measurements and eye tracking during experiments with head-fixed running, head-free, and freely moving animals. These emerging paradigms will allow the study of retinal optic flow processing in contexts that do not require simulated locomotion. While the exact the relation between the retinal motion statistics we have measured and the response properties of motion-sensitive cells remains unresolved, the emerging tools in neurophysiology and computation make similar approaches with different species more feasible.

A more detailed description of the methods including the photogrammetry and the reference frames for the measurements has been added primarily to the Methods section.

Reviewer #1 (Public Review):

Much experimental work on understanding how the visual system processes optic flow during navigation has involved the use of artificial visual stimuli that do not recapitulate the complexity of optic flow patterns generated by actual walking through a natural environment. The paper by Muller and colleagues aims to carefully document "retinal" optic flow patterns generated by human participants walking a straight path in real terrains that differ in "smoothness". By doing so, they gain unique insights into an aspect of natural behavior that should move the field forward and allow for the development of new, more principled, computational models that may better explain the visual processing taking place during walking in humans.

Strengths:

Appropriate, state-of-the-art technology was used to obtain a simultaneous assessment of eye movements, head movements, and gait, together with an analysis of the scene, so as to estimate retinal motion maps across the central 90 deg of the visual field. This allowed the team to show that walkers stabilize gaze, causing low velocities to be concentrated around the fovea and faster velocities at the visual periphery (albeit more the periphery of the camera used than the actual visual field). The study concluded that the pattern of optic flow observed around the visual field was most likely related to the translation of the eye and body in space, and the rotations and counter-rotations this entailed to maintain stability. The authors were able to specify what aspects of the retinal motion flow pattern were impacted by terrain roughness, and why (concentration of gaze closer to the body, to control foot placement), and to differentiate this from the impact of lateral eye movements. They were also able to identify generalizable aspects of the pattern of retinal flow across terrains by subsampling identical behaviors in different conditions.

Weaknesses:

While the study has much to commend, it could benefit from additional methodological information about the computations performed to generate the data shown. In addition, an estimation of inter-individual variability, and the role of sex, age, and optical correction would increase our understanding of factors that could impact these results, thus providing a clearer estimate of how generalizable they are outside the confines of the present experiments.

Properties of gait depend on the passive dynamics of the body and factors such as leg length and subject specific cost functions which are influenced by image quality and therefore by optical correction. In this experiment all subjects were normal acuity or corrected to normal (with no information regarding their uncorrected vision). This is now noted in the Methods. The goal of the present work was to calculate average statistics over a range of observers and conditions in order to constrain the experience-dependent properties one might see in neurophysiology. We have added between-subjects error bars to Figure 2 and added gaze angle distributions as a function of terrain for individual observers in the Supplementary materials. Figure 4 b and d now show standard errors across subjects. Individual subject plots are shown in the Supplementary materials. For Figure 2, most variability between subjects occurs in the Flat and Bark terrains where one might expect individual choices of energetic costs versus speed and stability etc might come into play. This is supported by our subsequent unpublished work on factors influencing foothold choice. We have also found that leg length determines path choices and thus will influence the retinal motion. Differences between observers are now noted in the text. These individual subject differences should indicate the range of variability that might be expected in the underlying neural properties and perhaps in behavioral sensitivity. Because of the size of our dataset (n=11) it is not feasible to make comparisons of sex or age. There were equal numbers of males and females and age ranged from 24 to 54. Now noted in the Methods section.

Reviewer #2 (Public Review):

The goal of this study was to provide in situ measurements of how combined eye and body movements interact with real 3D environments to shape the statistics of retinal motion signals. To achieve this, they had human walkers navigate different natural terrains while they measured information about eyes, body, and the 3D environment. They found average flow fields that resemble the Gibsonian view of optic flow, an asymmetry between upper and lower visual fields, low velocities at the fovea, a compression of directions near the horizontal meridian, and a preponderance of vertical directions modulated by lateral gaze positions.

Strengths of the work include the methodological rigor with which the measurements were obtained. The 3D capture and motion capture systems, which have been tested and published before, are state-of-the-art. In addition, the authors used computer vision to reconstruct the 3D terrain structure from the recorded video.

Together this setup makes for an exciting rig that should enable state-of-the-art measurements of eye and body movements during locomotion. The results are presented clearly and convincingly and reveal a number of interesting statistical properties (summarized above) that are a direct result of human walking behavior.

A weakness of the article concerns tying the behavioral results and statistical descriptions to insights about neural organization. Although the authors relate their findings about the statistics of retinal motion to previous literature, the implications of their findings for neural organization remain somewhat speculative and inconclusive. An efficient coding theory of visual motion would indeed suggest that some of the statistics of retinal motion patterns should be reflected in the tuning of neural populations in the visual cortex, but as is the present findings could not be convincingly tied to known findings about the neural code of vision. Thus, the behavioral results remain strong, but the link to neural organization principles appears somewhat weak.

We agree, but we think that strengthening the neural links requires future studies. As mentioned above, it is very difficult to relate the measured statistics to existing neurophysiological literature and we have tried to make this clearer in the Discussion (p14, 15, 16). This is because the stimuli chosen are typically arbitrary and not chosen to be realistic examples of patterns consistent with natural motion across a ground plane. Other stimuli are simply inconsistent with self-motion together with gaze stabilization (eg not zero velocity at the fovea). It has also been technically difficult to map cell properties across the visual field. We have made the comparisons we thought were useful. The point of the paper is to provide a hypothesis about the pattern of direction and speed tuning across the visual field. So the challenge for neurophysiology is to show how the observed cell properties vary across the visual field. Note also that the motion patterns will be influenced by the body motion of the animal in question, and because of this we are now collaborating with a group who are attempting to record from monkey MT/MST during locomotion while tracking eyes and body. Similarly we are training neural networks to learn the patterns generated by human gait to develop more specific hypotheses about receptive field properties.

Reviewer #3 (Public Review):

Gaze-stabilizing motor coordination and the resulting patterns of retinal image flow are computed from empirically recorded eye movement and motion capture data. These patterns are assessed in terms of the information that would be potentially useful for guiding locomotion that the retinal signals actually yield. (As opposed to the "ecological" information in the optic array, defined as independent of a particular sensor and sampling strategy).

While the question posed is fundamental, and the concept of the methodology shows promise, there are some methodological details to resolve. Also, some terminological ambiguities remain, which are the legacy of the field not having settled on a standardized meaning for several technical terms that would be consistent across laboratory setups and field experiments.

Technical limits and potential error sources should be discussed more. Additional ideas about how to extend/scale up the approach to tasks with more complex scenes, higher speed or other additional task demands and what that might reveal beyond the present results could be discussed.

This issue is addressed in more detail in the Discussion, second paragraph, and also the second last paragraph.

eLife assessment

This important study should be of interest to vision scientists and those seeking to model naturalistic image processing for humans in simulated or real navigational [walking] situations. The experiments aim to provide information about the statistics of "retinal" motion patterns generated by human participants physically walking a straight path in real terrains that differ in "smoothness". State-of-the-art eye, head, and body tracking allowed simultaneous assessment of eye movements, head movements, and gait, with convincing evidence for an asymmetrical gradient of flow speeds during walking, tied predominantly to vertical gaze angle, together with a radial motion direction distribution tied most critically on horizontal gaze angle. While not a major weakness per se, additional details on analytical methods used and estimations of variance across observers would strengthen these results and clarify the basis of the global claims made about visual motion information across the visual field in walking humans.

Reviewer #1 (Public Review):

Much experimental work on understanding how the visual system processes optic flow during navigation has involved the use of artificial visual stimuli that do not recapitulate the complexity of optic flow patterns generated by actual walking through a natural environment. The paper by Muller and colleagues aims to carefully document "retinal" optic flow patterns generated by human participants walking a straight path in real terrains that differ in "smoothness". By doing so, they gain unique insights into an aspect of natural behavior that should move the field forward and allow for the development of new, more principled, computational models that may better explain the visual processing taking place during walking in humans.

Strengths:<br /> Appropriate, state-of-the-art technology was used to obtain a simultaneous assessment of eye movements, head movements, and gait, together with an analysis of the scene, so as to estimate retinal motion maps across the central 90 deg of the visual field. This allowed the team to show that walkers stabilize gaze, causing low velocities to be concentrated around the fovea and faster velocities at the visual periphery (albeit more the periphery of the camera used than the actual visual field). The study concluded that the pattern of optic flow observed around the visual field was most likely related to the translation of the eye and body in space, and the rotations and counter-rotations this entailed to maintain stability. The authors were able to specify what aspects of the retinal motion flow pattern were impacted by terrain roughness, and why (concentration of gaze closer to the body, to control foot placement), and to differentiate this from the impact of lateral eye movements. They were also able to identify generalizable aspects of the pattern of retinal flow across terrains by subsampling identical behaviors in different conditions.

Weaknesses:<br /> While the study has much to commend, it could benefit from additional methodological information about the computations performed to generate the data shown. In addition, an estimation of inter-individual variability, and the role of sex, age, and optical correction would increase our understanding of factors that could impact these results, thus providing a clearer estimate of how generalizable they are outside the confines of the present experiments.

Welcome to the <span class="npf_color_monica">Fever Dream of the Folder Sorter</span>

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The Context -

I found a script that did something close to what I wanted to do. So I decided to ask ChatGPT to modify the code to add the features that I wanted. This was an arduous 24-hour process.

However, in the course of that, a new idea started in my head. I want to use Github's Commits interface as the stage to perform the story of those 24 hours.

Instructions

1. You can read the main chapter by expanding the <figure data-orig-height="10" data-orig-width="20"></figure>button.

2. The code is used as both a setting for the story as well as code as illustration. You can see the code and comments by click on the button that looks like this <figure data-orig-height="10" data-orig-width="20"></figure>

Additional Notes

I added * Hypothesis' Via as the narrator * Github's different features for branching and commenting as the narrative spine

<small>The code conflicts in each new revision, the way the code is presented and the comments are all elements of the story.</small> <small>The split view might be better to view the code with to compare from one version to another</small>

Read what this code was supposed to do

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Creating the help that actually helps people with these issues

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Reply to the reviewers

We would like to thank the reviewers for their extensive review of our manuscript and constructive criticism. We have attempted to address the points raised in the reviewer's comments and have performed additional experiments and have edited the text of the manuscript to explain these points. Please see below, our point-by-point response to the reviewer’s comments. In the submitted revised manuscript, some figure numbers have changed from the prior reviewed version.

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

In this MS, Mrj - a member of the JDP family of Hsp70 co-chaperones was identified as a regulator of the conversion of Orb2A (the Dm ortholog of CPEB) to its prion-like form.

In drosophila, Mrj deletion does not cause any gross neurodevelopmental defect nor leads to detectable alterations in protein homeostasis. Loss of Mrj, however, does lead to altered Orb2 oligomerization. Consistent with a role of prion-like characteristics of Orb2 in memory consolidation, loss of Mrj results in a deficit in long-term memory.

Aside from the fact that there are some unclarities related to the physicochemical properties of Orb2 and how Mrj affects this precisely, the finding that a chaperone could be important for memory is an interesting observation, albeit not entirely novel.

In addition, there are several minor technical concerns and questions I have that I feel the authors should address, including a major one related to the actual approach used to demonstrate memory deficits upon loss of Mrj.

Reviewer #1 (Significance (Required)):

Figure 1 (plus related Supplemental figures): • There seem to be two isoforms of Mrj (like what has been found for human DNAJB6). I find it striking to see that only (preferentially?) the shorter isoform interacts with Orb2. For DNAJB6, the long isoform is mainly related to an NLS and the presumed substrate binding is identical for both isoforms. If this is true for Dm-Mrj too, the authors could actually use this to demonstrate the specificity of their IPs where Orb2 is exclusively non-nuclear?

According to Flybase, Mrj has 8 predicted isoforms of which four are of 259 amino acids (PA, PB, PC, and PD), 3 are of 346 amino acids (PE, PG, and PH) and one is of 208 amino acids (PF) length (Supplementary data 1). We isolated RNA from flyheads and used this in RT-PCR experiments to check which Mrj isoforms express in the brain. Since both the 346 amino acid (1038 nucleotide long) and 259 amino acids (777 nucleotides long) form, which we refer to as the long and middle isoform, has the same N and C terminal sequences we used the same primer pair for this, but on RT-PCR the only amplicon we got corresponds to the 259 amino acid form. For the 208 amino acids (624 nucleotides long) form we designed a separate forward primer and attempted to amplify this using RT-PCR but were unable to detect this isoform also. This data is now presented in Supplemental Figure 4B. Since the only isoform detected from fly head cDNA corresponded to the 259 amino acid form, we think this is the predominant isoform of Mrj expressing in Drosophila and this is what is in our DnaJ library and what we have used in all our experiments here. This is also the same isoform described in previous papers on Drosophila Mrj (Fayazi et al, 2006; Li et al, 2016b). For this 259 amino acid Mrj isoform, we see its expression in both the nucleus and cytoplasm (Supplemental Figure 4C). As the long 346 AA fragment was undetectable in the brain, it was not feasible to address the reviewer’s point of using the long and short forms of Mrj for IP with Orb2. However, we have performed IP of human CPEB2 (hCPEB2) with the long and short isoforms of human DnaJB6 and have detected interaction of hCPEB2 with both the long and short isoforms of DnaJB6 (Supplemental Figure 6E).

• I would be interested to know a bit more about the other 5 JDPs that are interactors with Orb2: are the human orthologs of those known? It is striking that these other 5 JDPs interact with Orb2 in Dm (in IPs) but have no impact on Sup35 prion behavior. Importantly, this does not imply they may not have impact on the prion-like behavior of other Dm substrates, including Dm-Orb2.

We have performed BlastP analysis of CG4164, CG9828, CG7130, DroJ2, and Tpr2 protein sequences against Human proteins. Based on this we have listed the highest-ranking candidate identified here for each of these genes.

Drosophila Gene

Human gene

Query cover

Percent identity

E value

CG4164

dnaJ homolog subfamily B member 11 isoform 1

98 %

62.96%

2e-150

CG9828

dnaJ homolog subfamily A member 2

92%

39.41%

3e-84

CG7130

dnaJ homolog subfamily B member 4 isoform d

56%

69.44%

2e-30

Tpr2

dnaJ homolog subfamily C member 7 isoform 1

93%

46.22%

6e-139

DroJ2

dnaJ homolog subfamily A member 4 isoform 2

98%

60.60%

2e-169

In the context of the chimeric Sup35-based assay where Orb2A’s Prion-like domain (PrD) is coupled with the C-terminal domain of Sup35, the only protein which could convert Orb2A PrD-Sup35 C from its non-prion state to prion state was Mrj. Within the limitations of this heterologous-system based assay, the other 5 DnaJ domain proteins as well as the Hsp70’s were unable to convert the Orb2A PrD from its non-prion to prion-like state. What these other 5 interacting JDP proteins are doing through their interaction with Orb2A and if they are even expressing in the Orb2 relevant neurons will need to be tested separately and will be the subject of our future studies.

• The data in panels H, I indeed suggest that Mrj1 alters the (size of) the oligomers. It would be important to know what is the actual physicochemical change that is occurring here. The observed species are insoluble in 0.1 % TX100 but soluble in 0.1% SDS, which suggest they could be gels, but not real amyloids such as formed by the polyQ proteins that require much higher SDS concentrations (~2%) to be solubilized. This is relevant as Mrj1 reduces polyQ amyloidogenesis whereas is here is shown to enhance Orb2A oligomerization/gelidification. In the same context, it is striking to see that without Mrj the amount of Orb2A seems drastically reduced and I wonder whether this might be due to the fact that in the absence of Mrj a part of Orb2A is not recovered/solubilized due to its conversion for a gel to a solid/amyloid state? In other words: Mrj1 may not promote the prion state, but prevents that state to become an irreversible, non-functional amyloid?

On the reviewer’s point to address what is the actual physicochemical change occurring here, we will need to develop methods to purify the Orb2 oligomers in significant quantities to examine and distinguish if they are of gel or real amyloid-like nature. Currently, within the limitations of our ongoing work, this has not been possible for us to do and we can attempt to address this in our future work. Cryo-EM derived structure of endogenous Orb2 oligomers purified from a fly head extract from 3 million fly heads, made in the TritonX-100 and NP-40 containing buffer, the same buffer as what we have used here for the first soluble fraction, showed these oligomers as amyloids (Hervas et al, 2020). If the oligomers extracted using 0.1% and 2% SDS are structurally and physicochemically different, within the limitations of our current work, had not been possible to address.

The other point raised by the reviewer is, if in the absence of Mrj (in the context of Figure 4 of our previously submitted manuscript), a part of Orb2 is not solubilized due to us using a lower 0.1% SDS for extraction. To address this, we attempted to see how much of leftover Orb2 is remaining in the pellet after extraction with 0.1 % SDS. Towards this, according to the reviewers’ suggestion, we used a higher 2% SDS containing buffer to resuspend the leftover pellet after 0.1% SDS extraction, and post solubilisation ran all the fractions in SDD-AGE. We did this experiment with both wild-type and Mrj knockout fly heads. Under these different extractions, we first observed while there is more Orb2 in the soluble fraction (Triton X-100 extracted) of Mrj knockout, this amount is reduced in both the 0.1% SDS solubilized and 2% SDS solubilized fractions. So, even though there is leftover Orb2 after 0.1% SDS extraction, which can be extracted using 2% SDS, this amount is reduced in Mrj knockout. The other observation here is the Orb2 extracted using 2% SDS shows a longer smear in comparison to the 0.1% SDS extracted form suggesting a possibility of more and higher-sized oligomers present in this fraction. Since we do not have the exact physicochemical characterization of these oligomers detected with 0.1% and 2% SDS-containing buffer, we are not differentiating them by using the terms gels and real amyloids, but refer to them as 0.1% SDS soluble Orb2 oligomers and 2% SDS soluble Orb2 oligomers. Overall, our observations here suggest in absence of Mrj, both of these kinds of Orb2 oligomers are decreased and so Mrj is most likely promoting the formation of Orb2 oligomers. It is possible that the 0.1% SDS soluble Orb2 oligomers gradually accumulate and undergo a further transition to the 2% SDS soluble Orb2 oligomers, so if in absence of Mrj, the formation of the 0.1% SDS soluble Orb2 oligomers is decreased, the next step of formation of 2% SDS soluble Orb2 oligomers also be decreased. This data is now presented in Figure 5H, I and J).

On the other possibility raised by the reviewer that Mrj can prevent the oligomeric state of Orb2 to become an irreversible non-functional amyloid, we think it is still possible for Mrj to do this but this could not be tested under the present conditions.

• It may be good for clarity to refer to the human Mrj as DNAJB6 according to the HUGO nomenclature. Also, the first evidence for its oligomerization was by Hageman et al 2010.

We have now changed mentions of human Mrj to DNAJB6. We apologize for missing the Hageman et al 2010 reference and have now cited this reference in the context of Mrj oligomerization.

• It is striking to see that Mrj co-Ips with Hsp70AA, Hsp70-4 but not Hsp70Cb. The fact that interactions were detected without using crosslinking is also striking given the reported transient nature of J-domain-Hsp70 interactions Together, this may even suggest that Mrj-1 is recognized as a Hsp70 substrate (for Hsp70AA, Hsp70-4 but not Hsp70Cb) rather than as a co-chaperone. In fact, a variant of Mrj-1 with a mutation in the HPD motif should be used to exclude this option.

In IP experiments we notice Mrj interacts with Hsp70Aa and Hsc70-4 but not with Hsc70-1 and Hsc70Cb. In our previously submitted manuscript, we realized we made a typo on the figure, where we referred to Hsp70Aa as Hsc70Aa. We have corrected this in the current revised manuscript. On the crosslinking point raised by the reviewer, we reviewed the published literature for studies of immunoprecipitation experiments which showed an interaction between DnaJB6 and Hsp70. We noted while one of the papers (Kakkar et al, 2016) report the use of a crosslinker in the experiment which showed an interaction between GFP-Hsp70 and V5-DnaJB6, in another two papers the interaction between endogenous Mrj and endogenous Hsp/c70 (Izawa et al, 2000) and Flag-Hsp70 and GFP-DnaJB6 (Bengoechea et al, 2020) could be detected without using any crosslinker. Our observations of detecting the interaction of Mrj with Hsp70Aa and Hsc70-4 in the absence of a crosslinker are thus similar to the observations reported by (Izawa et al, 2000; Bengoechea et al, 2020).

On the point of if Mrj is a substrate for Hsp70aa and Hsc70-4 and not a co-chaperone, we feel in the context of this manuscript, since we are focussing on the role of Mrj in the regulation of oligomerization of Orb2 and in memory, the experiment with HPD motif mutant is probably not necessary here. However, if the reviewers suggest this experiment to be essential, we can attempt this experiment by making this HPD motif mutant.

• The rest of these data reconfirm nicely that Mrj/DNAJB6 can suppress polyQ-Htt aggregation. Yet note that in this case the oligomers that enter the agarose gel are smaller, not bigger. This argues that Mrj is not an enhancer of oligomerization, but rather an inhibitor of the conversion of oligomers to a more amyloid like state.

Figure 2 and Supplemental Figure 4 discuss the effect of Mrj on Htt aggregation. We have used 2 different Htt constructs here. For Figure 2I, we used only Exon1 of Htt with the poly Q repeats. Here in SDD-AGE, for the control lane, we see the Htt oligomers as a smear for the control. For Mrj, we see only a small band at the bottom which can be interpreted most likely as either a monomer or as small oligomers since we do not observe any smear here. However, for the 588 amino acid fragment of HttQ138 in the SDD-AGE we do not see a difference in the length of the smear but in the intensity of the smear of the Htt oligomers (Supplemental Figure 4E). Based on this we are suggesting in presence of Mrj, there are lesser Htt oligomers. On the point of Mrj is not an enhancer of oligomerization, but rather an inhibitor of the conversion of oligomers to a more amyloid-like state, our experiments with the Mrj knockout show reduced Orb2 oligomers (both for 0.1% and 2% SDS soluble forms), suggesting Mrj plays a role in the conversion of Orb2 to the oligomeric state. If Mrj inhibits the conversion of oligomers to a more amyloid-like state, this is possible but we couldn’t test this hypothesis here. However, for Htt amyloid aggregates, previous works done by other labs with DnaJB6 as well as our experiments with Mrj suggest this as a likely possibility.

Figure 3: • The finding that knockout of DNAJB6 in mice is embryonic lethal is related to a problem with placental development and not embryonic development (Hunter et al, 1999; Watson et al, 2007, 2009, 2011) as well recognized by the authors. Therefore, the finding that deletion of Dm-Mrj has no developmental phenotype in Drosophila may not be that surprising.

We agree with the reviewer’s point that DNAJB6 mutant mice have a problem with placental development. However, one of the papers cited here (Watson et al, 2009) suggests DNAJB6 also plays a crucial role in the development of the embryo independent of the placenta development defect. The mammalian DNAJB6 mutant embryos generated using the tetraploid complementation method show severe neural defects including exencephaly, defect in neural tube closure, reduced neural tube size, and thinner neuroepithelium. Due to these features seen in the mice knockout, and the lack of such developmental defects in the Drosophila knockout, we interpreted our findings in Drosophila as significantly different from the mammals.

• It is a bit more surprising that Mrj knockout flies showed no aggregation phenotype or muscle phenotype, especially knowing that DNAJB6 mutations are linked to human diseases associated with aggregation (again well recognized by the authors). However, most of these diseases are late-onset and the phenotype may require stress to be revealed. So, while important to this MS in terms of not being a confounder for the memory test, I would like to ask the authors to add a note of caution that their data do not exclude that loss of Mrj activity still may cause a protein aggregation-related disease phenotype. Yet, I also do think that for the main message of this MS, it is not required to further test this experimentally.

We agree with the reviewer and have added this suggestion in the discussion that loss of Mrj may still result in a protein aggregation-related disease phenotype, probably under a sensitized condition of certain stresses which is not tested in this manuscript.

Figure 4:

• IPs were done with Orb2A as bite and clearly pulled down substantial amounts of GFP-tagged Mrj. For interactions with Orb2B, a V5-tagged Mrj was use and only a minor fraction was pulled down. Why were two different Mrj constructs used for Arb2A and Orb2b?

In the previously submitted manuscript, we have used HA-tagged Mrj (not V5) for checking the interaction with full-length Orb2B tagged with GFP. This was done with the goal of using the same Mrj-HA construct as that used in the initial Orb2A immunoprecipitation experiment. Since this has raised some concern as in the IPs to check for interaction between truncated Orb2A constructs (Orb2A325-GFP and Orb2AD162-GFP) and Mrj (Mrj-RFP), we used a different GFP and RFP tag combination. To address this, we have now added the same tag combinations for the IPs (Mrj-RFP with Orb2A-GFP and Orb2B-GFP). In these immunoprecipitation experiments where Mrj-RFP was pulled down using RFP Trap beads, we were able to detect positive interaction with GFP-tagged Orb2A and Orb2B. This data is now added in Figure 4F and 4I. We also have added the IP data for interaction between Mrj-HA and untagged Orb2B in Figure 4K, similar to the combination of initial experiment between Mrj-HA and untagged Orb2A.

• In addition, I think it would be important what one would see when pulling on Mrj1, especially under non-denaturing conditions and what is the status of the Orb2 that is than found to be associated with Mrj (monomeric, oligomeric and what size).

We have now performed IP from wild-type fly heads using anti Mrj antibody and ran the immunoprecipitate in SDS-PAGE and SDD-AGE followed by immunoblotting them with anti-Orb2 antibody. Our experiments suggest that immunoprecipitating endogenous Mrj brings down both the monomeric and oligomeric forms of Orb2. This data is now added in Figure 4L, M and N.

• This also relates to my remark at figure 1 and the subsequent fractionation experiments they show here in which there is a slight (not very convincing) increase in the ratio of TX100-soluble and insoluble (0.1% SDS soluble) material. My question would be if there is a remaining fraction of 0.1% insoluble (2% soluble) Orb2 and how Mrj affects that? As stated before, this is (only) mechanistically relevant to understanding why there is less oligomers of Orb2 in terms of Mrj either promoting it or by preventing it to transfer from a gel to a solid state. The link to the memory data remains intriguing, irrespective of what is going on (but also on those data I do have several comments: see below).

We have addressed this in response to the reviewer’s comments on Figure 1. We find in both wild type and Mrj knockout fly heads, there are Orb2 oligomers that can be detected using 0.1% SDS extraction and with further extraction with 2% SDS. The 2% SDS soluble Orb2 oligomers were previously insoluble during 0.1% SDS-based extraction. However, the amounts of both of these oligomers are reduced in Mrj knockout fly heads. Since we do not have the physicochemical characterization of both of these kinds of oligomers, we are not using the terms gel or solid state here but referring to these oligomers as 0.1% SDS soluble Orb2 oligomers and 2% SDS soluble Orb2 oligomers. We speculate that the 0.1% SDS soluble Orb2 oligomers over time transition to the 2% SDS soluble Orb2 oligomers. As in the absence of Mrj in the knockout flies, both the 0.1% SDS soluble and 2% SDS soluble Orb2 oligomers are decreased, this suggests Mrj is promoting the formation of Orb2 oligomers. On the reviewer’s point, if Mrj can prevent the transition from 0.1% SDS soluble to 2% SDS soluble Orb2 oligomers, we think it is possible for Mrj to both promote oligomerization of Orb2 as well as prevent it from forming bigger non-functional oligomers, but the second point is not tested here. The relevant data is now presented in Figure 5H, I and J.

• I also find the sentence that "Mrj is probably regulating the oligomerization of endogenous Orb2 in the brain" somewhat an overstatement. I would rather prefer to say that the data show that Mrj1 affects the oligomeric behavior/status of Orb2.

Based on the reviewer’s suggestion we have now changed the sentence to Mrj is probably regulating the oligomeric status of Orb2

Figure 5:

• To my knowledge, the Elav driver regulates expression in all neurons, but not in glial cells that comprise a significant part of the fly heads/brain. The complete absence of Mrj in the fly-heads when using this driver is therefore somewhat surprising. Or do we need to conclude from this that glial cells normally already lack Mrj expression?

On driving Mrj RNAi with Elav Gal4, we did not detect any Mrj in the western. We attempted to address the glial contribution towards Mrj’s expression we used a Glia-specific driver Repo Gal4 line to drive the control and Mrj RNAi line and performed a western blot using fly head lysate with anti-Mrj antibody. In this experiment, we did not observe any difference in Mrj levels between the two sets. As the Mrj antibody raised by us works in western blots but not in immunostainings, we could not do a colocalization analysis with a glial marker. However, we used the Mrj knockout Gal4 line to drive NLS-GFP and performed immunostainings of these flies with a glial marker anti-Repo antibody. Here we see two kinds of cells in the brain, one which have GFP but no Repo and the other where both are present together. This suggest that while Glial cells have Mrj but probably majority of Mrj in the brain comes from the neurons. We also found a reference where it was shown that Elav protein as well as Elav Gal4 at earlier stages of development expresses in neuroblasts and in all Glia (Berger et al, 2007). So, another possibility is when we are driving Mrj RNAi using Elav Gal4, this knocks down Mrj in both the neurons as well as in the glia. This coupled with the catalytic nature of RNAi probably creates an effective knockdown of Mrj as seen in the western blot. This data is now added in Supplementary Figure 5G and H.

• Why not use these lines also for the memory test for confirmation? I understand the concerns of putative confounding effects of a full knockdown (which were however not reported), but now data rely only on the mushroom body-specific knockdown for the 201Y Gal4 line, for which the knockdown efficiency is not provided. But even more so, here a temperature shift (22oC-30oC) was required to activate the expression of the siRNA. For the effects of this shift alone no controls were provided. The functional memory data are nice and consistent with the hypothesis, but can it be excluded that the temperature shift (rather than the Mrj) knockdown has caused the memory defects? I think it is crucial to include the proper controls or use a different knockdown approach that does not require temperature shifts or even use the knockout flies.

We have now performed the memory experiments with Mrj knockout flies. Our experiments show at 16 and 24-hour time points Mrj knockout flies have significantly reduced memory in comparison to the control wildtype. This data is now added in Figure 6B.

Figure 6:

The finding of a co-IP between Rpl18 and Mrj (one-directional only) by no means suffices to conclude that Mrj may interact with nascent Orb2 chains here (which would be the relevant finding here). The fact that Mrj is a self-oligomerising protein (also in vitro, so irrespective of ribosomal associations!), and hence is found in all fractions in a sucrose gradient, also is not a very strong case for its specific interaction with polysomes. The finding that there is just more self-oligomerizing Orb2A co-sedimenting with polysomes in sucrose gradients neither is evidence for a direct effect of Mrj enhancing association of Orb2A with the translating ribosomes even though it would fit the hypothesis. So all in all, I think the data in this figure and non-conclusive and the related conclusions should be deleted.

We have now performed the reverse co-IP between Rpl18-Flag and Mrj-HA using anti-HA antibody and could detect an interaction between the two. This data is now added in Supplementary Figure 6A.

To address if Mrj is a self-oligomerizing protein that can migrate to heavier polysome fractions due to its size, we have loaded recombinant Mrj on an identical sucrose gradient as we use for polysome analysis. Post ultra-centrifugation we fractionated the gradients and checked if Mrj can be detected in the fraction numbers where polysomes are present. In this experiment, we could not detect recombinant Mrj in the heavier polysome fractions (data presented in Supplementary Figure 6B). Overall, our observations of Mrj-Rpl18 IPs, the presence of cellularly expressed Mrj in polysome fractions, and the absence of recombinant Mrj from these fractions, suggest a likelihood of Mrj’s association with the translating ribosomes.

On the reviewer’s point of us concluding Mrj may interact with nascent Orb2 chains, we have not mentioned this possibility in the manuscript as we don’t have any evidence to suggest this. We have also added a sentence: This indicates that in presence of Mrj, the association of Orb2A with the translating ribosomes is enhanced, however, if this is a consequence of increased Orb2A oligomers due to Mrj or caused by interaction between polysome-associated Orb2A and Mrj will need to be tested in future.

Based on these above-mentioned points, we hope we can keep the data and conclusions of this section.

Overall, provided that proper controls/additional data can be provided for the key experiments of memory consolidation, I find this an intriguing study that would point towards a role of a molecular chaperone in controlling memory functions via regulating the oligomeric status of a prion-like protein and that is worthwhile publishing in a good journal.

However, in terms of mechanistical interpretations, several points have to be reconsidered (see remarks on figure 1,4); this pertains especially to what is discussed on page 13. In addition, I'd like the authors to put their data into the perspective of the findings that in differentiated neurons DNAJB6 levels actually decline, not incline (Thiruvalluvan et al, 2020), which would be counterintuitive if these proteins are playing a role as suggested here in memory consolidation.

We have addressed the comments on Figures 1 and 4 earlier. We have also added new memory experiment’s data with the Mrj knockout in Figure 6.

We have attempted to put the observations with Drosophila Mrj in perspective to observations in Thiruvalluvan et al, on human DnaJB6 in the discussions as follows:

Can our observation in Drosophila also be relevant for higher mammals? We tested this with human DnaJB6 and CPEB2. In mice CPEB2 knockout exhibited impaired hippocampus-dependent memory (Lu et al, 2017), so like Drosophila Orb2, its mammalian homolog CPEB2 is also a regulator of long-term memory. In immunoprecipitation assay we could detect an interaction between human CPEB2 and human DnaJB6, suggesting the feasibility for DnaJB6 to play a similar role to Drosophila Mrj in mammals. However, as the human DnaJB6 level was observed to undergo a reduction in transitioning from ES cells to neurons, (Thiruvalluvan et al, 2020) how this can be reconciled with its possible role in the regulation of memory. We speculate, such a reduction if is happening in the brain will occur in a highly regulatable manner to allow precise control over CPEB2 oligomerization only in specific neurons where it is needed and the reduced levels of DnaJB6 is probably sufficient to aid CPEB oligomerization Alternatively, there may be additional chaperones that may function in a stage-specific manner and be able to compensate for the decline in levels of DNAJB6.

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

Summary: The manuscript describes the role of the Hsp40 family protein Mrj in the prion-like oligomerization of Orb2. The authors demonstrate that Mrj promotes the oligomerization of Orb2, while a loss in Mrj diminishes the extent of Orb2 oligomerization. They observe that while Mrj is not an essential gene, a loss in Mrj causes deficiencies in the consolidation of long-term memory. Further, they demonstrate that Mrj associates with polysomes and increases the association of Orb2 with polysomes.

Major comments: None

Minor comments:

1. In the section describing the chaperone properties of Mrj in clearing Htt aggregates (Fig 2), the legend describes that "Mrj-HA constructs are more efficient in decreasing Htt aggregation compared to Mrj-RFP". It would be helpful to add Mrj-RFP to the quantification in Fig 2G to know exactly the difference in efficiency. Is there an explanation for why the 2 constructs behave differently?

We have added the quantitation of Htt aggregates in presence of Mrj-RFP in the revised version (Data presented in Figure 2G). While the efficiency of Mrj-RFP to decrease Htt aggregates is significantly less in comparison to Mrj-HA, it is still significantly better in comparison to the control CG7133-HA construct. It is possible, due to the tagging of Mrj with a larger tag (RFP), this reduces its ability to decrease the Htt aggregates in comparison to the construct where Mrj is tagged with a much smaller HA tag.

Figs A, B, C, G need to have quantification of the percentage of colocalization with details about the number of cells quantified for each experiment.

We have now added the intensity profile images and colocalization quantitation (pearson’s coefficient) in the Supplemental Figure 5A and B. This quantitation is done from multiple ROI’s taken from at 4-6 cells.

In Fig 6 B, C, F, G it would be helpful to label the 40S, 60S and 80S peaks in the A 254 trace.

We have now labeled the 80S, and polysome peaks in the Figure 7B, C, F and G. We could not separate the 40S and 60S peaks in the A254 trace.

It's interesting that Mrj has opposing functions with regard to aggregation when comparing huntingtin with Orb2. From the literature presented in the discussion, it appears as though chaperones including Mrj have an anti-aggregation role for prions. It would be helpful to have more discussion around why, in the case of Orb2, this is different. The discussion states that "The only Hsp40 chaperone which was found similar to Mrj in increasing Orb2's oligomerization is the yeast Jjj2 protein" - this point needs elaboration, as well as a reference.

In the discussions section we have now added the following speculations on this:

One question here is why Mrj behaves differently with Orb2 in comparison to other amyloids. Orb2 differs from other pathogenic amyloids in its extremely transient existence in the toxic intermediate form (Hervás et al, 2016). For the pathogenic amyloids, since they exist in the toxic intermediate form for longer, Mrj probably gets more time to act and prevent or delay them from forming larger aggregates. For Orb2, Mrj may help to quickly transition it from the toxic intermediate state, thereby helping this state to be transient instead of longer. An alternate possibility is post-transition from the toxic intermediate state, Mrj stabilizes these Orb2 oligomers and prevents them from forming larger aggregates. This can be through Mrj interacting with Orb2 oligomers and blocking its surface thereby preventing more Orb2 from assembling over it. Another difference between the Orb2 oligomeric amyloids and the pathogenic amyloids is in the nature of their amyloid core. For the pathogenic amyloids, this core is hydrophobic devoid of any water molecules, however for Orb2, the core is hydrophilic. This raises another possibility that if the Orb2 oligomers go beyond a certain critical size, Mrj can destabilize these larger Orb2 aggregates by targeting its hydrophilic core.

On the Jjj2 point raised by the reviewer, we have added the (Li et al, 2016a) reference now and elaborated as:

The only Hsp40 chaperone which was found similar to Mrj in increasing Orb2’s oligomerization is the yeast Jjj2 protein. In Jjj2 knockout yeast strain, Orb2A mainly exists in the non-prion state, whereas on Jjj2 overexpression the non-prion state could be converted to a prion-like state. In S2 cells coexpression of Jjj2 with Orb2A lead to an increase in Orb2 oligomerization (Li et al, 2016a). However, Jjj2 differs from Mrj, as when it is expressed in S2 cells, we do not detect it to be present in the polysome fractions.

The Jjj2 polysome data is now presented in Supplementary Figure 6C.

Reviewer #2 (Significance (Required)):

General assessment:

Overall, the work is clearly described and the manuscript is very well-written. The motivation behind the study and its importance are well-explained. I only have minor comments and suggestions to improve the clarity of the work. The study newly describes the interaction between the chaperone Mrj and the translation regulator Orb2. The experiments that the screen for proteins that interact with Orb2 and promote its oligomerization are very thorough. The experiments that delve into the role of Mrj in protein synthesis are a good start, and need to be explored further, but that is beyond the scope of this study.

Advance: The study describes a new interaction between the chaperone Mrj and the translation regulator Orb2. The study is helpful in expanding our knowledge of prion regulators as well factors that affect memory acquisition and consolidation.

Audience: This paper will be of most interest to basic researchers.

My expertise is in Drosophila genetics and neuronal injury.

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

The manuscript submitted by Desai et al. identifies a chaperone of the Hsp40 family (Mrj) that binds Orb2 and modulates its oligomerization, which is critical for Orb2 function in learning and memory in Drosophila. Orb2 are proteins with prion-like properties whose oligomerization is critical for their function in the storage of memories. The main contribution of the article is the screen of Hsp40 and Hsp70-family proteins that bind Orb2. The authors show IP results for all the candidates tested, including those that bind Fig. 1) and those that don't (Supp Fig 3). There is also a figure devoted to examining the interaction of Mrj with polyglutamine models (Htt). They also generate a KO mutant that is viable and shows no gross defects or protein aggregation. Lastly, they show that the silencing of Mrj in the mushroom body gamma neurons results in weaker memories in a courtship paradigm. Although the data is consistent and generally supportive of the hypothesis, key details are missing in several areas, including controls. Additionally, the interpretation of some results leaves room for debate. Overall, this is an ambitious article that needs additional work before publication.

Specific comments:

1. General concern over the interpretation of IP experiments and colocalization. These experiments don't necessarily reflect direct interactions. They are consistent with direct interaction but not the only explanation for a positive IP or colocalization.

This paper is centred on the interaction between Orb2A and Mrj, which we have detected using immunoprecipitation. The reviewer’s concern here is, this experiment is not able to distinguish if this can be a direct protein-protein interaction or if the two proteins are part of a complex.

To address this concern we have used purified recombinant protein-based pulldowns. Our experiments with purified protein pulldowns (GST tagged Mrj from E.coli with Orb2A from E.coli or Orb2A-GFP from Sf9 cells) suggest Orb2A and Mrj can directly interact amongst themselves. This data is now presented in Figure 1J and K.

The Huntingtin section has a few concerns. The IF doesn't show all controls and the quantification is not well done in terms of what is relevant. A major problem is the interpretation of Fig 2F. The idea is that Mrj prevents the aggregation of Htt, which is the opposite of what is observed with Orb2. The panel actually shows a large Htt aggregate instead of multiple small aggregates. This has been reported before in Drosophila and other systems with different polyQ models. Mrj and other Hsp40 and Hsp70 proteins modify Htt aggregation, but in an unexpected way. This affects the model shown in Fig. 6H. Lastly, Fig 2H and 2I show very different level of total Htt.

In Figure 2F of the previously submitted manuscript, we have shown representative images of HttQ103-GFP cells coexpressing with a control DnaJ protein CG7133-HA and Mrj-HA. In Figure 2G we quantitated the number of cells showing aggregates within the population of doubly transfected cells. On the reviewer’s point of figure 2F showing large Htt aggregates instead of multiple small aggregates, we do not see a large Htt aggregate in presence of Mrj in this figure, the pattern looks diffused here and very different from the control CG7133 where the aggregates are seen. We have performed the same experiment with a different Htt construct (588 amino acids long fragment) tagged with RFP, and here also we notice in presence of Mrj, the aggregates are decreased and the expression pattern looks diffused (Supplementary Figure 4E, 4F).

If the comment on large Htt aggregates in presence of Mrj is concerning figure 2E, here we show Mrj-RFP to colocalize with the Htt aggregates. Here, even though Mrj-RFP colocalizes with Htt aggregates, it rescues the Htt aggregation phenotype as in comparison to the control CG7133, the number of cells with Htt aggregates is still significantly less here. We have added this quantitation of rescue by Mrj-RFP in the revised manuscript now. The observation of colocalization of Mrj-RFP with Htt aggregates is similar to previous reports of chaperones rescuing Htt aggregation and yet showing colocalization with the aggregates. Both Hdj-2 and Hsc70 suppress Htt aggregation and yet were observed to colocalize with Htt aggregates in the cell line model as well as in nuclear inclusions in the brain (Jana et al, 2000). In a nematode model of Htt aggregation, DNJ-13 (DnaJB-1), HSP-1 (Hsc70), and HSP-11 (Apg-2) were shown to colocalize with Htt aggregates and yet decrease the Htt aggregation (Scior et al, 2018). Hsp70 was also found to colocalize with Htt aggregates in Hela cells (Kim et al, 2002).

Regarding Figures 2H and 2I, while figure 2H is of an SDS-PAGE to show no difference in the levels of monomeric HttQ103 (marked with *) in presence of Mrj and the control CG7133, figure 2I is for the same samples ran in an SDD-AGE where reduced amount of Htt oligomers as seen with the absence of a smear in presence of Mrj. The apparent difference in Htt levels between 2H and 2I is due to the detection of Htt aggregates/oligomers in the SDD-AGE which are unable to enter the SDS-PAGE and hence undetected. In Supplementary Figure 4E, similar experiments were done with the longer Htt588 fragment and here we notice in the SDD-AGE reduced intensity of the smear made up of Htt oligomers, again suggesting a reduction in Htt aggregates. Thus our results are not in contradiction to previous studies where Mrj was found to rescue Htt aggregate-associated toxicity.

Endogenous expression of Mrj using Gal4 line: where else is it expressed in the brain / head and in muscle. Fig 3G shows no muscle abnormalities but no evidence is shown for muscle expression. It is nice that Fig 3E and F show no abnormal aggregates in the Mrj mutant, but this would be maybe more interesting if flies were subjected to some form of stress.

We have now added images of the brain and muscles to show the expression pattern of Mrj. Using Mrj Gal4 line and UAS- CD8GFP, we noticed enriched expression in the optic lobes, mushroom body, and olfactory lobes. We also noticed GFP expression in the larval muscles and neuromuscular junction synaptic boutons. This data is now presented in Supplementary Figure 5C, D, E and F.

On the reviewer’s point of subjecting the Mrj KO flies to some form of stress, we have not performed this. We have added in the discussions a note of caution, that loss of Mrj may still result in a protein aggregation-related disease phenotype, probably under a sensitized condition of certain stresses which is not tested in this manuscript.

Fig. 5B shows no Mrj detectable from head homogenates in flies silencing Mrj in neurons with Elav-Gal4. It would be nice if they could show that ONLY neurons express Mrj in the head. Also noted, Elav-Gal4 is a weak driver, so it is surprising that it can generate such robust loss of Mrj protein

We have used an X chromosome Elav Gal4 driver to drive the UAS-Mrj RNAi line and here we could not detect Mrj in the western. To address the reviewer’s point on the glial contribution towards expression of Mrj, we used a Glial driver Repo Gal4 to drive Mrj RNAi. In this experiment, we did not detect any difference in Mrj levels between the control and the Mrj RNAi line (presented now in Supplementary Figure 5G). We also used the Mrj knockout Gal4 line to drive NLS-GFP and immunostained these using a glial marker anti-Repo antibody. Here, we were able to detect cells colabelled by GFP as well as Repo, suggesting Mrj is likely to be present in the glial cells (presented now in Supplementary Figure 5H). We also looked in the literature and found a reference where it was shown that Elav protein as well as Elav Gal4 at earlier stages of development expresses in neuroblasts and in all Glia (Berger et al, 2007). So, another possibility is when we are driving Mrj RNAi using Elav Gal4, this knocks down Mrj in both the neurons as well as in the glia.

Fig 4-Colocalization of Orb2 with Mrj lacks controls. The quantification could describe other phenomena because the colocalization is robust but the numbers shown describe something else.

We have now added the intensity profile and colocalization quantitation (pearson’s coefficient) in Supplemental Figure 5A and B. This quantitation is done from multiple ROI’s taken from 4-6 cells. Also, to suggest the interaction of Orb2 isoforms with Mrj, we are not depending on colocalization alone and have used immunoprecipitation experiments to support our observations.

Fly behavior. The results shown for Mrj RNAi alleles is fine but it would be more robust if this was validated with the KO line AND rescued with Mrj overexpression.

We have now performed memory assays with the Mrj knockout. Our experiments showed Mrj knockouts to show significantly decreased memory in comparison to wild-type flies at 16 and 24-hour time points (presented in Figure 6B). We have not been able to make an Mrj Knockout-UAS Mrj recombinant fly, most likely due to the closeness of the two with respect to their genomic location in second chromosome.

Minor comments:

Please, revise minor errors, there are several examples of words together without a space.

We have identified the words without space and have corrected them now.

Intro: describe the use of functional prions. Starting the paragraph with this sentence and then explaining what prion diseases are is a little confusing. Also "prion proteins" can be confusing because the term refers to PrP, the protein found in prions.

We have now altered the introduction and have described functional prions.

Results, second subtitle in page 5. This sentence is quite confusing using prion-like twice

We have now changed the heading to “Drosophila Mrj converts Orb2A from non-prion to a prion-like state.”

Page 6: "conversion from non-prion to prion-like form...". This can be presented differently. Prion-like properties are intrinsic, proteins don't change from non-prion to prion-like. They may be oligomeric or monomeric or highly aggregated but the prion-like property doesn't change

We agree with the reviewer's point of Prion-like properties are intrinsic, but the protein might or might not exist in the prion-like state or confirmation. When we are using the term conversion from non-prion to prion-like form we mean to suggest a conformational conversion leading to the eventual formation of the oligomeric species. We also noted the terminology of non-prion to prion-like state change is used in several papers (Satpute-Krishnan & Serio, 2005; Sw & Yo, 2012; Uptain et al, 2001).

Scale bars and text are too small in several figures

We have now mentioned in the figure legends the size of the scale bars. For several images we have made the scale bars also larger.

Not sure why Fig 4C is supplemental, seems like an important piece of data.

We have kept this data in the supplemental data as we performed this experiment with recombinant protein which is tagged with 6X His and we are not sure if this high degree of oligomerization/aggregation of recombinant Mrj and further precipitation over time, happens inside the cells/ brain.

Intro to Mrj KO in page 7 is too long. Most of it belongs in the discussion

We have now moved the portions on mammalian DNAJB6 which were earlier in the results section to the discussions section.

Change red panels in IF to other color to make it easier for colorblind readers.

We have now changed the red panels to magenta. We apologize for our figures not being colorblind friendly earlier.

The discussion is a little diffuse by trying to compare Orb2 with mammalian prions and amyloids and yeast prions.

We looked into the functional prion data and couldn’t find much on chaperone mediated regulation of these. Also, we felt comparing with the amyloids and yeast prions brings out the contrast with respect to the Mrj mediated regulatory differences between the two.

Reviewer #3 (Significance (Required)):

This is a paper with a broad scope and approaches. The paper describes the role of Mrj in the oligomerization of Orb2 by protein biochemistry techniques and determine the role of loss of Mrj in the mushroom bodies in fly behavior.

The audience for this content is basic research and specialized. The role of Mrj in Orb2 aggregation and function sheds new light on the mechanisms regulating the function of this protein involved in a novel mechanism of learning and memory.

References:

Bengoechea R, Findlay AR, Bhadra AK, Shao H, Stein KC, Pittman SK, Daw JA, Gestwicki JE, True HL & Weihl CC (2020) Inhibition of DNAJ-HSP70 interaction improves strength in muscular dystrophy. J Clin Invest 130: 4470–4485

Berger C, Renner S, Lüer K & Technau GM (2007) The commonly used marker ELAV is transiently expressed in neuroblasts and glial cells in the Drosophila embryonic CNS. Dev Dyn 236: 3562–3568

Fayazi Z, Ghosh S, Marion S, Bao X, Shero M & Kazemi-Esfarjani P (2006) A Drosophila ortholog of the human MRJ modulates polyglutamine toxicity and aggregation. Neurobiol Dis 24: 226–244

Heinrich SU & Lindquist S (2011) Protein-only mechanism induces self-perpetuating changes in the activity of neuronal Aplysia cytoplasmic polyadenylation element binding protein (CPEB). Proc Natl Acad Sci U S A 108: 2999–3004

Hervás R, Li L, Majumdar A, Fernández-Ramírez MDC, Unruh JR, Slaughter BD, Galera-Prat A, Santana E, Suzuki M, Nagai Y, et al (2016) Molecular Basis of Orb2 Amyloidogenesis and Blockade of Memory Consolidation. PLoS Biol 14: e1002361

Hervas R, Rau MJ, Park Y, Zhang W, Murzin AG, Fitzpatrick JAJ, Scheres SHW & Si K (2020) Cryo-EM structure of a neuronal functional amyloid implicated in memory persistence in Drosophila. Science 367: 1230–1234

Izawa I, Nishizawa M, Ohtakara K, Ohtsuka K, Inada H & Inagaki M (2000) Identification of Mrj, a DnaJ/Hsp40 family protein, as a keratin 8/18 filament regulatory protein. J Biol Chem 275: 34521–34527

Jana NR, Tanaka M, Wang G h & Nukina N (2000) Polyglutamine length-dependent interaction of Hsp40 and Hsp70 family chaperones with truncated N-terminal huntingtin: their role in suppression of aggregation and cellular toxicity. Hum Mol Genet 9: 2009–2018

Kakkar V, Månsson C, de Mattos EP, Bergink S, van der Zwaag M, van Waarde MAWH, Kloosterhuis NJ, Melki R, van Cruchten RTP, Al-Karadaghi S, et al (2016) The S/T-Rich Motif in the DNAJB6 Chaperone Delays Polyglutamine Aggregation and the Onset of Disease in a Mouse Model. Mol Cell 62: 272–283

Kim S, Nollen EAA, Kitagawa K, Bindokas VP & Morimoto RI (2002) Polyglutamine protein aggregates are dynamic. Nat Cell Biol 4: 826–831

Li L, Sanchez CP, Slaughter BD, Zhao Y, Khan MR, Unruh JR, Rubinstein B & Si K (2016a) A Putative Biochemical Engram of Long-Term Memory. Curr Biol 26: 3143–3156

Li S, Zhang P, Freibaum BD, Kim NC, Kolaitis R-M, Molliex A, Kanagaraj AP, Yabe I, Tanino M, Tanaka S, et al (2016b) Genetic interaction of hnRNPA2B1 and DNAJB6 in a Drosophila model of multisystem proteinopathy. Hum Mol Genet 25: 936–950

Liebman SW & Chernoff YO (2012) Prions in yeast. Genetics 191: 1041–1072

Lu W-H, Yeh N-H & Huang Y-S (2017) CPEB2 Activates GRASP1 mRNA Translation and Promotes AMPA Receptor Surface Expression, Long-Term Potentiation, and Memory. Cell Rep 21: 1783–1794

Prusiner SB (2001) Neurodegenerative Diseases and Prions. New England Journal of Medicine 344: 1516–1526

Satpute-Krishnan P & Serio TR (2005) Prion protein remodelling confers an immediate phenotypic switch. Nature 437: 262–265

Scior A, Buntru A, Arnsburg K, Ast A, Iburg M, Juenemann K, Pigazzini ML, Mlody B, Puchkov D, Priller J, et al (2018) Complete suppression of Htt fibrilization and disaggregation of Htt fibrils by a trimeric chaperone complex. EMBO J 37: 282–299

Si K (2015) Prions: what are they good for? Annu Rev Cell Dev Biol 31: 149–169

Si K, Choi Y-B, White-Grindley E, Majumdar A & Kandel ER (2010) Aplysia CPEB can form prion-like multimers in sensory neurons that contribute to long-term facilitation. Cell 140: 421–435

Si K, Lindquist S & Kandel ER (2003) A neuronal isoform of the aplysia CPEB has prion-like properties. Cell 115: 879–891

Sw L & Yo C (2012) Prions in yeast. Genetics 191

Thiruvalluvan A, de Mattos EP, Brunsting JF, Bakels R, Serlidaki D, Barazzuol L, Conforti P, Fatima A, Koyuncu S, Cattaneo E, et al (2020) DNAJB6, a Key Factor in Neuronal Sensitivity to Amyloidogenesis. Mol Cell 78: 346-358.e9

Uptain SM & Lindquist S (2002) Prions as protein-based genetic elements. Annu Rev Microbiol 56: 703–741

Uptain SM, Sawicki GJ, Caughey B & Lindquist S (2001) Strains of [PSI(+)] are distinguished by their efficiencies of prion-mediated conformational conversion. EMBO J 20: 6236–6245

Watson ED, Mattar P, Schuurmans C & Cross JC (2009) Neural stem cell self-renewal requires the Mrj co-chaperone. Dev Dyn 238: 2564–2574

Wickner RB (2016) Yeast and Fungal Prions. Cold Spring Harb Perspect Biol 8: a023531

Wickner RB, Edskes HK, Maddelein ML, Taylor KL & Moriyama H (1999) Prions of yeast and fungi. Proteins as genetic material. J Biol Chem 274: 555–558

Wickner RB, Masison DC, Edskes HK & Maddelein ML (1996) Prions of yeast, [PSI] and [URE3], as models for neurodegenerative diseases. Cold Spring Harb Symp Quant Biol 61: 541–550

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Referee #3

Evidence, reproducibility and clarity

The manuscript submitted by Desai et al. identifies a chaperone of the Hsp40 family (Mrj) that binds Orb2 and modulates its oligomerization, which is critical for Orb2 function in learning and memory in Drosophila. Orb2 are proteins with prion-like properties whose oligomerization is critical for their function in the storage of memories. The main contribution of the article is the screen of Hsp40 and Hsp70-family proteins that bind Orb2. The authors show IP results for all the candidates tested, including those that bind Fig. 1) and those that don't (Supp Fig 3). There is also a figure devoted to examining the interaction of Mrj with polyglutamine models (Htt). They also generate a KO mutant that is viable and shows no gross defects or protein aggregation. Lastly, they show that the silencing of Mrj in the mushroom body gamma neurons results in weaker memories in a courtship paradigm. Although the data is consistent and generally supportive of the hypothesis, key details are missing in several areas, including controls. Additionally, the interpretation of some results leaves room for debate. Overall, this is an ambitious article that needs additional work before publication.

Specific comments:

1. General concern over the interpretation of IP experiments and colocalization. These experiments don't necessarily reflect direct interactions. They are consistent with direct interaction but not the only explanation for a positive IP or colocalization.
2. The Huntingtin section has a few concerns. The IF doesn't show all controls and the quantification is not well done in terms of what is relevant. A major problem is the interpretation of Fig 2F. The idea is that Mrj prevents the aggregation of Htt, which is the opposite of what is observed with Orb2. The panel actually shows a large Htt aggregate instead of multiple small aggregates. This has been reported before in Drosophila and other systems with different polyQ models. Mrj and other Hsp40 and Hsp70 proteins modify Htt aggregation, but in an unexpected way. This affects the model shown in Fig. 6H. Lastly, Fig 2H and 2I show very different level of total Htt.
3. Endogenous expression of Mrj using Gal4 line: where else is it expressed in the brain / head and in muscle. Fig 3G shows no muscle abnormalities but no evidence is shown for muscle expression. It is nice that Fig 3E and F show no abnormal aggregates in the Mrj mutant, but this would be maybe more interesting if flies were subjected to some form of stress.
4. Fig. 5B shows no Mrj detectable from head homogenates in flies silencing Mrj in neurons with Elav-Gal4. It would be nice if they could show that ONLY neurons express Mrj in the head. Also noted, Elav-Gal4 is a weak driver, so it is surprising that it can generate such robust loss of Mrj protein
5. Fig 4-Colocalization of Orb2 with Mrj lacks controls. The quantification could describe other phenomena because the colocalization is robust but the numbers shown describe something else.
6. Fly behavior. The results shown for Mrj RNAi alleles is fine but it would be more robust if this was validated with the KO line AND rescued with Mrj overexpression.

Minor comments:

Please, revise minor errors, there are several examples of words together without a space.

Intro: describe the use of functional prions. Starting the paragraph with this sentence and then explaining what prion diseases are is a little confusing. Also "prion proteins" can be confusing because the term refers to PrP, the protein found in prions.

Results, second subtitle in page 5. This sentence is quite confusing using prion-like twice

Page 6: "conversion from non-prion to prion-like form...". This can be presented differently. Prion-like properties are intrinsic, proteins don't change from non-prion to prion-like. They may be oligomeric or monomeric or highly aggregated but the prion-like property doesn't change

Scale bars and text are too small in several figures

Not sure why Fig 4C is supplemental, seems like an important piece of data.

Intro to Mrj KO in page 7 is too long. Most of it belongs in the discussion

Change red panels in IF to other color to make it easier for colorblind readers.

The discussion is a little diffuse by trying to compare Orb2 with mammalian prions and amyloids and yeast prions.

Significance

This is a paper with a broad scope and approaches. The paper describes the role of Mrj in the oligomerization of Orb2 by protein biochemistry techniques and determine the role of loss of Mrj in the mushroom bodies in fly behavior.

The audience for this content is basic research and specialized. The role of Mrj in Orb2 aggregation and function sheds new light on the mechanisms regulating the function of this protein involved in a novel mechanism of learning and memory.

eLife assessment

This study provides valuable insights into the role of two under-researched sperm-specific proteins (Cylicin 1 and Cylicin 2). The authors provide convincing evidence that they have an essential role in sperm head structure during spermatogenesis, and that their loss leads to subfertility or infertility, with a dose-dependent phenotype. The authors identify infertile males with mutations in both Cylicin1 and Cylicin2: thus the findings from the mouse models might be applicable to understanding human male infertility with similar structural defects.

Reviewer #1 (Public Review):

Mice and humans have two Cylicin genes (X-linked Cylicin 1 and the autosomal Cylicin 2) that encode cytoskeletal proteins. Cylicins are localized in the acrosomal region of round spermatids, yet they resemble a calyx component within the perinuclear theca of mature sperm nuclei. The function of Cylicins during this developmental stage of spermiogenesis (tail formation and head elongation/shaping) was not known. In this study, using CRISPR/Cas genome editing, the authors generated Cylc1-and Cylc2-knockout mouse lines to study the loss-of-function of each Cylicin or all together.

The major strengths of the study are the rigorous and comparative phenotypic analyses of all the combinatorial genotypes from the cross between the two mouse lines (Cylc1-/y, Cylc2-/-, Cylc1-/y Cylc2+/- and Cylc1-/y Cylc2-/-) at the levels of male fertility, cellular, and subcellular levels to support the conclusion of the study. While spermatogenesis appeared undisturbed, with germ cells of all types detected in the testis, low sperm counts in epididymis were observed. Mice were subfertile or infertile in a dose-dependent manner where fewer functional alleles had more severe phenotypes; the loss of Cylc2 was less tolerated than the loss of Cylc1. Thus, loss of Cylc1, and to an even greater extent, loss of Cylc2, leads to sperm structure anomalies and decrease sperm motility. Particularly, the sperm head and sperm head-neck region are affected, with calyx not forming in the absence of Cylicins, the acrosomal region being attached more loosely, and the sperm head itself appearing structurally rounder and shorter. Furthermore, manchette, which disassembles during spermiogenesis, persists in mature sperm of mice missing Cylc2. It is interesting that the study identifies a human male that has mutations in both CYLC1 and CYLC2 genes, and suffers from infertility, with similar motility and sperm structure defects compared to the mouse models. CYLC1 in the sperm from the infertile patient sperm is absent, providing evidence that in both rodents and primates, Cylicins are essential for male fertility.

The major weakness of the study is the less robust or absent of statistical analyses determining the statistical significance of some of the morphological phenotypes observed (e.g., the roundness/shortening of sperm head). Evolutionary analysis of two genes-while interesting- is less congruent with the other parts of the study and disrupts the overall flow of the functional studies. The authors show that the reason for the loss of Cylc2 being more severe is due to the higher conservation of Cylc2 compared to Cylc1 in rodents and primates, however, the conservation of these genes in other species is not discussed.

Overall, the work highlights the relevance and importance of Cylicins in male infertility and advances our understanding of perinuclear theca formation during spermiogenesis.

By way of example, category information may include categories and corresponding criteria to qualify for particular categories such as viewer difficulty in seeing content displayed which may be linked with detected viewer states such squinting, leaning forward, head tilting, looking over glasses, and/or the like. Other categories could include sleepiness, disinterestedness, distraction, and/or the like, with corresponding criteria directed to eye state, facial state, and/or the like. In some embodiments, the rules 358 may include criteria for matching a set of indicia of viewer state to a set of one or more categories.

Well written

This is very interesting. How can “reading” and “listening” be the same thing? Could this be because we are listening to the interpretations or the arrangement made by the computer instead of us having to read it and process it in our head? Curious.

Author Response

Reviewer #1 (Public Review):

Collins et al use mesoscopic two-photon imaging to simultaneously record activity from basal forebrain cholinergic or noradrenergic axons in several distant regions of the dorsal cortex during spontaneous behavior in head-fixed awake mice. They find that activity in axons from both neuromodulatory systems is closely correlated with measures of behavioral state, such as whisking, locomotion and face movements. While axons were globally correlated with these behavioral state-related metrics across the dorsal cortex, they also find evidence of behavioral state independent heterogenous signals.

The use of simultaneous multiarea optical recordings across a large extent of dorsal cortex with single axon resolution for studying the coherence of neuromodulatory afferents across cortical areas is novel and addresses important questions regarding neuromodulation in the neocortex. The manuscript is clearly written, the data is well presented and, for the most part, carefully analyzed. Parts of the manuscript confirm previous results on the influence of behavioral state on norepinephrine and acetylcholine cortical afferents. However, the observation that these modulations are globally broadcasted to the dorsal cortex while behavioral state independent heterogenous signals are also present in these axons is novel and important for the field.

While the evidence for a behavioral state driven global modulation of activity in both neuromodulatory systems is quite clear, I have concerns that the apparent heterogeneity in axonal responses might be driven by movement-induced artifacts. Moreover, even in the case that the heterogeneity in calcium activity across axons is confirmed, it might not be driven by differences in spiking activity across neuromodulatory axons as concluded, but by other mechanisms that are not explicitly discussed or considered.

1) Motion artifacts are always a concern when imaging from small structures in behaving animals. This issue is addressed in the manuscript in Fig 2A-C by comparing axonal responses to "autofluorescent blebs that did not have calcium-dependent activity" (line 1011). Still, as calcium-dependent activity and motion artifacts can both be locked to behavioral variables the "bleb" selection criterion seems biased and flawed with a circular logic. "Blebs" presenting motion-induced changes in fluorescence that may pass as neural activity will be wrongly excluded when from the "bleb" control group using this criterion. This will result in an underestimation of the extent of the contamination of the GCaMP signals by movement-induced artifacts. This potential confound might generate apparent heterogeneity across axons and regions as some axons and some cortical areas might be more prone to movements artifacts than others.

Thank you for the suggestion. We agree that motion artifacts are a reasonable concern. We rigorously addressed this concern by introducing non-calcium-dependent mCherry into cholinergic cortical axons and demonstrating that motion cannot explain our results (see Fig. 2F, Fig. 4H,L,P, Fig. 4 - figure supplement 1G, Video 3, and response above). These axons were chosen for analysis based solely on their ability to be imaged, in a manner identical to that of GCaMP6s containing axons.

We agree that the observed evidence of heterogeneity is not as clear as the evidence of a common signal. We now carefully present our evidence. Heterogeneity may arise from variations in activity between single axons that is not explained by a common signal such as behavioral state. Heterogeneity could also be signaled by variations in correlated activity between axons. We now address these two possibilities in our manuscript. Our new analysis reveals that the correlated activity between axons is as expected for axons that are variably correlated to a common signal, such as behavioral state. Although we do find some evidence of correlation outside this common signal, we are not able to discern if this is related to imaging axon segments that are part of the same axon, or if it truly represents an independent signal. This is now stated in the text. On the other hand, strong variations in axonal activity from trial to trial that appear to be separate from the common signal is also prevalent. We now point out this variation as a possible source of heterogeneity. Since we do not know the source or meaning of this heterogeneous activity, we discuss only the possibility that it may hold behaviorally relevant information in these modulatory systems.

2) In the case that the heterogeneity is indeed due to differences in calcium activity, it might be not due to modularity in spiking activity within the LC or the BF as interpreted and discussed in the manuscript. As calcium signaling in axons not only relates to spiking activity but can also reflect presynaptic modulations, the observed heterogeneity might be due to local action of presynaptic modulators in a context of global identical broadcasted activity. The current dataset does not allow distinguishing which of the two different mechanisms underlies the observed signal heterogeneity.

It is true that our data set is unable to determine whether presynaptic modulations contribute to any observed heterogeneity. We have adjusted our interpretation of heterogeneity throughout the manuscript and have specifically addressed this comment in the discussion by presenting the possibility that a global signal could be locally modulated.

Reviewer #3 (Public Review):

Acetylcholine and Norepinephrine are two of the most powerful neuromodulators in the CNS. Recently developments of new methods allow monitoring of the dynamic changes in the activity of these agents in the brain in vivo. Here the authors explore the relationship between the dynamic changes in behavioral states and those of ACh and NE in the cortex. Since neuromodulatory systems cover most of the cortical tissue, it is essential to be able to monitor the activity of these systems in many cortical areas simultaneously. This is a daunting task because the axons releasing NE and ACh are very thin. To my knowledge, this study is the first to use mesoscopic imaging over a wide range of the cortex at the single axon resolution in awake animals. They find that almost any observable change in behavioral state is accompanied by a transient change in the activity of cortical ACh and NE axonal segments. Whisking is significantly correlated with ACh and NE. The authors also explore the spatial pattern of activity of ACh and NE axons over the dorsal cortex and find that most of the dynamics is synchronous over a wide spatial scale. They look for deviation from this pattern (which I will discuss later). Lastly, the authors monitor the activity of cortical interneurons capable of releasing ACh.

Comments:

1) On a broad overview, I find the discussion of behavioral states, brain states, and neuromodulation states quite confusing. To begin with, I am not convinced by the statement that "brain states or behavioral states change on a moment-to-moment basis." I find that the division of brain activity into microstates (e.g., microarousal) is counterproductive. After all, at the extreme, going along this path, we might eventually have an extremely high dimensional space of all neuronal activity, and any change in any neuron would define a new brain state. Similarly, mice can walk without whisking, can whisk without walking, can walk and whisk, are all these different behavioral states? And if so, are they all associated with different brain states? And if so, are they all associated with different brain states? Most importantly, in the context of this manuscript, one would expect that different states (brain, behavior) would be associated with at least four potential states of the ACh x NE system (high ACh and High NE, High ACh and Low NE, etc.). However, the reported findings indicate that the two systems are highly synchronized (or at least correlated), and both transiently go on with any change from a passive state to an active state. Therefore, the manuscript describes a rather confined relationship of the neuromodulation systems with the rather rich potential of brain and behavioral states. Of course, this is only my viewpoint, and the authors are not obliged to accept it, but they should recognize that the viewpoint they take for granted is not shared by all and consider acknowledging it in the manuscript.

We thank this reviewer for this thoughtful comment. While it is clear that animals do in fact exhibit distinct and clear brain and behavioral states (e.g. sleep, waking, grooming, still, walking, etc.), it is beyond the scope of the present manuscript to attempt to tackle this complex field - rather, we refer the reader to a recent review that we have published on this important topic (McCormick, Nestvogel, and He 2020). We agree that properly delineating brain and behavioral states is of great importance, as it could significantly impact experimental design and interpretation of results. Since all of the relevant substates that a mouse may exhibit have not yet been determined, we decided to use changes in whisking and walking behaviors to differentiate between distinct behavioral states owing to: 1) historical use of these measures in behavioral and neural states in head-fixed mice, 2) relative ease of measurement of these variables, 3) a clearly observable relationship with cholinergic and noradrenergic activity with these measures of behavior, and, arguably most importantly, 4) assumed relevance to the animal (Musall et al. 2019; Reimer et al. 2016; Salkoff et al. 2020; Stringer et al. 2019).

Our manuscript seeks to simply relate the activity of cholinergic and noradrenergic axons across the dorsal surface of the cortex in comparison to these commonly used measures of spontaneous behavior in head-fixed mice to discern to what relative degree there are common, global signals in these two modulatory systems and how they relate to changes in the measured behaviors. Somewhat surprisingly, previous studies have found that neural activity throughout the dorsal cortex of mice is strongly related to movements of the face and body as well as behavioral arousal (Stringer et al. 2019; Musall et al. 2019; Salkoff et al. 2020). Here we determine to what degree these commonly used measures of “state” are already reflected in the GCaMP6s activity of cholinergic and noradrenergic axons (and local cortical interneurons).

We agree with the interpretation that our results suggest a confined relationship between spontaneous cholinergic and noradrenergic activity in the cortex within the spontaneous behaviors that we observe. We, by no means, mean to suggest that this confined relationship is the only relationship cholinergic and noradrenergic systems exhibit to each other or to behavior. It seems very likely that in the wide variety of behavior exhibited by freely moving mice in their lifetime, there are times in which the activity of cholinergic and noradrenergic systems exhibit a radically different relationship to each other and to behavior. We simply cannot know this without experimental examination. We now mention this possibility in the discussion and give a few appropriate references.

2) Most of the manuscript (bar one case) reports nearly identical dynamics of ACh and NE. Is that a principle? What makes these systems behave so similarly? Why have two systems that act nearly the same? Still, if there is a difference, it is the time scale of the ACh compared to the NE. Can the authors explain this difference or speculate what drives it?

Perhaps one of the most striking findings in recent years from examination of mouse brain activity is the prominence and prevalence of a general signal in nearly all neural systems that relates to movement and arousal of the animal (Stringer et al. 2019; Salkoff et al. 2020). Here we report that this signal is also strongly present within the cholinergic and noradrenergic systems. Perhaps this is unsurprising, since everywhere one looks, one finds this global signal. However, we feel that understanding the presence and nature of this large signal is critical to deciphering behavior-related signals in these systems in the future. We discuss this point in the discussion. The one difference we did find is in the more transient nature of NE axonal activity versus both behavior and cholinergic axon activity. We now speculate on this difference in the discussion.

3) Whisker activity explains most strongly the neuromodulators dynamics, but pupil dilation almost does not (in contrast to many previous reports including reports of the same authors). If I am not mistaken, this was nearly ignored in the presentation of the results and the discussion section. Could the author elaborate more on what is the reason for this discrepancy?

We apologize for the misleading presentation of our results. In Fig. 3C and D it is clear that pupil diameter is highly coherent with both cholinergic and noradrenergic axon activity, as published previously. In the present study, this coherence peaks at 0.4 to 0.5 for both. In our previous study (Reimer et al. 2016), the cholinergic activity also peaked in coherence at low frequencies at around 0.4 to 0.5 (Reimer et al., Fig. 1H) while the noradrenergic activity coherence peaked at 0.6 to 0.7. The present study was not optimized for pupil diameter examination, since we kept the light levels as low as possible (resulting in low dynamic range of pupil dilations since they were nearly always enlarged to near maximum) in order to increase the S/N of cortical axon activity. We now mention these similarities and differences and caveats in the manuscript. An additional important point is that the kinetics of pupil diameter changes are slow in comparison to whisker movements, reducing the ability of pupil dilation to accurately track changes in axonal activity at frequencies greater than approximately 0.2 Hz (Fig. 2 - figure supplement 2). This is now mentioned in the text.

4) I find the question of homogenous vs. heterogenous signaling of both the ACh and NE systems quite important. It is one thing if the two systems just broadcast "one bit" information to the whole brain or if there are neuromodulation signals that are confined in space and are uncorrelated with the global signal. However, the way the analysis of this question is presented in the manuscript is very difficult to follow, and eventually, the take-home message is unclear. The discussion section indicates that the results support that beyond a global synchronized signal, there is a significant amount of heterogeneous activity. I think this question could benefit from further analysis. I suggest trying to demonstrate more specific examples of axonal ROIs where their activity is decorrelated with the global signal, test how consistent this property is (for those ROIs), and find a behavioral parameter that it predicts.

Also, in the discussion part, I am missing a discussion of the potential mechanism that allows this heterogeneity. On the one hand, an area may receive NE/ACh innervation from different BF/LC neurons, which are not completely synchronized. But those neurons also innervate other areas, so what is the expected eventual pattern? Also, do the results support neuromodulation control by local interneuron circuits targeting the axons (as is the case with dopaminergic axons in the Basal Ganglia)?

Our results clearly demonstrate a robust global signal that is common across cholinergic and noradrenergic axons which is related to behavioral state. We have less strong, but still present, evidence for a heterogeneous signal in addition to this global signal. This evidence is based largely upon the large variation in activities in different axon segments during behavioral events that appear similar. This result suggests that the axon segments we monitored do not all act as if they are members of the same axon. We now discuss the strong evidence for the global signal present in our data, and leave open the possibility of a heterogeneous signal whose mechanisms and importance remains to be determined.

5) The axonal signal seems to be very similar across the cortex. I am not sure this is technically possible, but given that NE axons are thin and non-myelinated and taking advantage of the mesoscopic scale, could the author find any clue for the propagation of the signal on the rostral to caudal axis?

We were unable to detect propagation across the cortical sheet and believe this is beyond the scope of the present study.

6) While the section about local VCIN is consistent with the story, it is somehow a sidetrack and ends the manuscript on the wrong note. I leave it to the authors to decide but recommend them to reconsider if and where to include it. Unfortunately, the figure attached was on a very poor resolution, and I could not look into the details, so I am afraid that I could not review this section properly.

We believe this adds to the manuscript and therefore have decided to include this data.

eLife assessment

This study uses behavioral monitoring and cutting-edge calcium imaging approaches to track the activity of cholinergic and noradrenergic axons in cortex of head-fixed mice, and correlate activity with behavioral state. While the evidence that behaviorally related signals are broadly broadcasted to the dorsal cortex is clear from the data, the conclusion that there is also heterogeneity across axons and areas is of less certain significance and might be undermined by methodological artifacts.

Reviewer #1 (Public Review):

Collins et al use mesoscopic two-photon imaging to simultaneously record activity from basal forebrain cholinergic or noradrenergic axons in several distant regions of the dorsal cortex during spontaneous behavior in head-fixed awake mice. They find that activity in axons from both neuromodulatory systems is closely correlated with measures of behavioral state, such as whisking, locomotion and face movements. While axons were globally correlated with these behavioral state-related metrics across the dorsal cortex, they also find evidence of behavioral state independent heterogenous signals.

The use of simultaneous multiarea optical recordings across a large extent of dorsal cortex with single axon resolution for studying the coherence of neuromodulatory afferents across cortical areas is novel and addresses important questions regarding neuromodulation in the neocortex. The manuscript is clearly written, the data is well presented and, for the most part, carefully analyzed. Parts of the manuscript confirm previous results on the influence of behavioral state on norepinephrine and acetylcholine cortical afferents. However, the observation that these modulations are globally broadcasted to the dorsal cortex while behavioral state independent hetetogenous signals are also present in these axons is novel and important for the field.

While the evidence for a behavioral state driven global modulation of activity in both neuromodulatory systems is quite clear, I have concerns that the apparent heterogeneity in axonal responses might be driven by movement-induced artifacts. Moreover, even in the case that the heterogeneity in calcium activity across axons is confirmed, it might not be driven by differences in spiking activity across neuromodulatory axons as concluded, but by other mechanisms that are not explicitly discussed or considered.

1) Motion artifacts are always a concern when imaging from small structures in behaving animals. This issue is addressed in the manuscript in Fig 2A-C by comparing axonal responses to "autofluorescent blebs that did not have calcium-dependent activity" (line 1011). Still, as calcium-dependent activity and motion artifacts can both be locked to behavioral variables the "bleb" selection criterion seems biased and flawed with a circular logic. "Blebs" presenting motion-induced changes in fluorescence that may pass as neural activity will be wrongly excluded when from the "bleb" control group using this criterion. This will result in an underestimation of the extent of the contamination of the GCaMP signals by movement-induced artifacts. This potential confound might generate apparent heterogeneity across axons and regions as some axons and some cortical areas might be more prone to movements artifacts than others.

2) In the case that the heterogeneity is indeed due to differences in calcium activity, it might be not due to modularity in spiking activity within the LC or the BF as interpreted and discussed in the manuscript. As calcium signaling in axons not only relates to spiking activity but can also reflect presynaptic modulations, the observed heterogeneity might be due to local action of presynaptic modulators in a context of global identical broadcasted activity. The current dataset does not allow distinguishing which of the two different mechanisms underlies to the observed signal heterogeneity.

Reviewer #2 (Public Review):

This study uses behavioral monitoring and cutting-edge calcium imaging approaches to track the activity of cholinergic and noradrenergic axons in cortex of head-fixed mice, and correlate activity with behavioral state. The data confirm that much of this activity is dependent on behavioral state, and in particular is strongly correlated with arousal of the animal and is highly coordinated across axons. They also show that a small fraction of axonal activity is heterogenous, and does not seem to be dependent on global behavioral state. They describe additional details of this activity, such as that whisking activity is the best predictor of cholinergic and noradrenergic axon activity, and that noradrenergic activity is more transient during bouts of arousal (whisking) than cholinergic activity. Altogether this manuscript is generally very thorough analytically, most of the data appear technically sound, and the presentation is largely clear. However, the significance of the findings - exactly how much they enhance what is already known - is less clear.

The main advanced novelty of the approach is the use of mesoscale imaging, giving them the ability to analyze the degree to which neuromodulatory cholinergic and noradrenergic signals are uniform across cortex, or might be correlated with distinct behavioral states or events. They attempt to get at this in Figure 4, by determining how much of their detected signal from cholinergic and noradrenergic axon activity comes from a 'common signal' versus how much of the signal is residual once the common signal is subtracted, so presumably reflects a unique influence. This analysis and the reasoning behind it is very hard to follow, and it is not clear to us that these residual signals are truly meaningful (i.e. not coming just from some source of noise). The authors try to get at this meaning in Figure 4K by plotting partial minus ordinary correlations in different arousal states, but it is not clear to us what exactly this difference means, considering the ordinary correlation itself is different in those comparisons as well. The fact that there is a bigger difference between partial and ordinary correlations during whisking than in other states does not give us real information about where the partial correlation is from.

eLife assessment

Gordon-Fennell et al. present a low-cost, open-source platform for measuring action elicitation and consummatory behavior in head-fixed animals. The findings are important because they allow animals to perform a truly voluntary action whilst their head is held still, and the evidence supporting them is both comprehensive and compelling (in some cases even exceptional). The results have the potential to have a broad impact in the field as many labs start to move towards measuring head-fixed behavior effectively, although this is said with the caveat that such behavior will never be an ideal replication of naturalistic behavior.

Reviewer #1 (Public Review):

Gordon-Fennell et al., here present a relatively low-cost, open-source platform for head-fixed operant and consummatory behaviour, called OHRBETS (prounounced Orbitz). This setup provides a great advantage over other systems in that it enables the animal to perform a truly operant response (i.e.one that fulfills the criterion of bidirectionality) whilst head-fixed. The authors provide thorough evidence of the utility of this setup, showing that a number of behavioural paradigms can be performed whilst the animal is head-fixed, as well as consummatory behaviours, optogenetic manipulations, and photometry recordings. These findings will be of broad interest to neuroscientists across multiple fields.

Strengths:<br /> 1. The work presented here is extremely thorough and explores multiple different types of paradigms. There is a huge amount of data that will be immensely useful to individuals who hope to use this setup and build on these findings. The setup is generally well-explained.<br /> 2. The statistics reported are generally quite strong and the sample sizes are sufficient (although strictly speaking ANOVA and Tukey should not be used together - Tukey's 'overall' test is a test of the maximal comparison, if the maximal comparison is not significant then no other pairwise comparison will be).<br /> 3. The open-source nature of the system is a great advantage as the fact that it is relatively low cost (as long as a lab has access to a 3D printer). This and similar endeavours will promote equality throughout the field.<br /> 4. The response here is truly operant as it is bidirectional. In other words, the animal shows that its response is governed by the relation between that response and the outcome, not stimulus-outcome associations like so many other so-called 'operant' responses (e.g. licking, food approach behaviours). Here, the stimuli are kept constant but the animal will either turn the wheel to the left or to the right to receive the food, depending on which direction is reinforced. This means that the animal cannot be governed solely by a stimulus-outcome response as in Pavlovian conditioning, because their response would not flexibly reverse the way that it is shown to here, particularly in Figure 1Q.<br /> 5. The accumbens shell recordings are interesting data in their own right (i.e. not simply to demonstrate the viability of the system), particularly the heterogeneity of the responses in the medial and lateral shells. This could be interesting for future studies to follow up on.<br /> 6. The correlational data between the head-fixed and free-moving versions of paradigms is, for the most part, quite convincing.

Weaknesses<br /> 1. I was curious as to how novel this setup is. Although I do not do head-fixed research myself, I thought there were already some open-source, relatively cheap systems available. I'm not sure how the current setup differs from those already available. Personally, even if this system involves only the wheel turning, as this is a truly operant response, that is novel enough for my liking.<br /> 2. It would be useful to have a bit more detail in the manuscript (not just on the GitHub link - in supplemental material perhaps?) on how to build such a system, just to get a sense of how difficult building such a system might be and how many components it has.<br /> 3. I wasn't sure how to feel about the comparisons across experimental set-ups in Figures 2 and 3. Usually, these sorts of comparisons are not considered statistically valid due to the many variables that differ between set-ups. However, I do see that the intent here is a bit different - i.e. is to show that despite all these alterations in variables the behavioural outputs are still highly correlated. However, without commenting on this intent, I did find these comparisons a little jarring to read.<br /> 4. The only dataset I was not wholly convinced by was that in Figure 3 (real-time place preference and aversion). I think the authors have done the best job that they can of replicating such a procedure in a head-fixed mouse, but the head-fixed version is going to necessarily differ from the freely moving version in a fundamental way when the contextual cues and spatial navigation form part of the RTPT task. Giving a discrete cue, such as a tone, just is not a sufficient substitute for contextual cues, and I think the two types of task would engage fundamentally different brain cells and circuits (e.g. only the free-moving version is likely to engage place cells in the hippocampus).<br /> 5. Personally, I found having the statistics in a separate file confusing.<br /> 6. Line 589-594. Suggesting the medial/lateral shell recording results mean that the medial shell 'tracks value, and the range of values during the multi-spout consumption of gradients of NaCl is greater than the range of values during multi-spout consumption of gradients of sucrose" seems to engage in circular logic to me. That is, the authors should use behavioural data to infer what the animal is experiencing and whether it is a change in value, and/or a greater change in value during NaCl vs. sucrose consumption, and only then should they make an inference about what the larger medial shell response means.

Overall this is a very solid paper in which the authors achieve their aims of demonstrating an open-source system for head-fixed operant and consummatory behavioural assessment, that is successfully employed across a number of different behavioural assays as well as in conjunction with optogenetic manipulations and fibre photometry recordings.

Reviewer #2 (Public Review):

The manuscript by Gordon-Fennell et al. presents an open-source platform for the analysis of behavior in a head-fixed apparatus (termed OHRBETS). In addition to providing instruction on how to assemble and implement the apparatus itself, the authors validate its use across a set of procedures broadly relevant to the field of behavioral neuroscience - including operant conditioning and fluid consumption protocols run in conjunction with optical manipulation and/or recording of neural activity.

The manuscript is comprehensive and clearly very strong. It also has the potential to have a broad impact in the field as many labs start to move towards effective head-fixed behavior. I also appreciate the fact that this manuscript includes a range of very strong behavioral tests - including experiments where several reinforcer options are available. This could be used for studies assessing taste, preference, reinforcer value, etc. Overall, the manuscript is impactful and my enthusiasm for it is high.

Reviewer #3 (Public Review):

Head-fixed preparations should always be conceived more as a necessity (for example, to avoid damaging expensive lab equipment) than as a final path towards which the entire field of neuroscience must go. The ideal will always be to move towards a more naturalistic and ecological approach to understanding behavior. Said that. The Davis Rig seems to be a thing of the past, welcome the Open-Source Head-fixed Rodent Behavioral Experimental Training System (OHRBETS). OHRBETS represents a significant advantage over the Davis Rig equipment to measure oromotor palatability responses in a brief access test, to perform positive and negative reinforcement, and even real-time place preference in a head-fixed preparation.

This is a well-written manuscript; the work and results are impressive. The manuscript is quite relevant to the Neuroscience field and will be of general interest. The experiments were carefully done. It is expected that OHRBETS will be widely used in multiple Neuroscience labs.

a really sweet visual, i like this ending, but neither character has enough of an arc.

what is this scene doing?

She's missing her family. Yet they are always there. Just out of reach.

He never loved her in the way she wanted to be loved. This is usually how young love goes.

The theme of family is huge. No matter what your family is always there for you. Even if they can't be right with you.

She was not going to let him die!

She is experiencing the scary stuff as well on the surface. Beautiful, yet frightening. Is that' a beautiful metaphor for love?

Her first glimpse of the surface was just as detailed as the every detail throughout. You can almost see it through her eyes!

Still wondering what the Little Mermaid is putting together in her head of what the world is like. Is she okay mentally waiting so long? Does her sister's going to the top help or hurt her?

The Little Mermaid was learning more and more.

Journalling is a great way for me to release everything that has been stressing me out so I agree with this statement.

How to ascertain it was not in the PBL as of 3 weeks ago?

Next paragraph:

“How do you know this if the Problem Bank List is a state secret?” Because they report the aggregate total of the assets of all banks on the list and publicly available data plus math a 4th grader can do in their head suffices to prove this claim.

The paragraph provides an interesting perspective on the emergence of radio programs and their impact on traditional print media. It highlights how the novelty of radio programs initially attracted the attention of publishers, but they soon realized that it was affecting their business negatively. This example underscores the importance of being aware of the unintended consequences of new technologies and the need to carefully assess their potential impact on existing business models. It also highlights the role of competition in shaping media industries and the need for publishers to adapt to changing market conditions.

This is a Induction Head at work, yes?

Reviewer #2 (Public Review):

In this work, the authors tackle the question of how a non-linear decay in a morphogen gradient might affect downstream patterning specificity. In the first section of the paper, they address this theoretically, by examining the nature of morphogen gradients assuming either linear or non-linear degradation of the morphogen, using previously-established equations. Assuming variation in the concentration of morphogen at the source, they show that a linear decay model results in uniform shifts in the location of a threshold concentration of morphogen that only depend on the relative concentration changes, while a non-linear decay model yield shifts with more complex dependencies on concentration.

The next section of the paper addresses gradient patterning precision by accounting for not only variation in the source concentration of morphogen, but also in the parameters that describe the production, degradation, diffusion, and cell size, for both a linear and non-linear decay model. The key finding from this section is that, while non-linear decay can produce some improvements in patterning reliability near the morphogen source, it fares far worse than linear decay in regions far from the morphogen gradient. Simulations that include explicit morphogen-producing cells demonstrate that simpler models that exclude this detail may have overestimated the benefits of a non-linear morphogen decay.

The strength of this work is tackling head-on the question of how a non-linear decay of morphogen affects patterning precision using both theory and simulations. Non-linear decays have been observed in nature, and therefore this question is one of interest. The methods used by the authors provide convincing evidence for their claims, and the results, particularly the importance of simulating morphogen-producing cells, are likely to be of interest to the community interested in the design principles of morphogens and developmental patterning.

Reviewer #1 (Public Review):

The article is a straightforward continuation of their previous 2016 study. The authors demonstrate an organism-level role of intermediate filaments (IFs) in C. elegans with a model highlighting intermediate filament functions in organism development, larval development, oxidative stress-resilience, size, and lifespan.

The study uses endotube morphogenesis in C. elegans as an elegant model to examine the effect of aberrant IF network morphogenesis on endotube morphology and how these effects are reflected in terms of progeny growth and development.

The study identifies the C. elegans IF protein IFB-2 as a core component of IF network morphogenesis where any mutation or dysfunction of IF interacting proteins such as SMA-5, IFO-1, and BBLN1 can be mostly rescued by silencing of IFB-2.

The observed mutations cause a range of systemic and functional defects of which endotube-related defects that include luminal widening and cytoplasmic invaginations are regarded as the key parameters to observe the direct result of IF network perturbation in the study. Based on these parameters authors narrowed down on IFB-2 head domain as a critical interactor in IF network morphogenesis and function.

On the whole, very interesting findings and an elegant study with excellent data that would be of broad interest for cytoskeletal research. The study has clear ramifications also for the understanding of the evolutionary development and roles of IF, both IF aspects that are still very poorly understood.

I think I've heard of the moon being jealous of the stars for shinning brighter than her but I never thought of them all as a family.

We should consider listing Stevens' other locations where they stock Prevail (e.g. BC, Calgary, Quebec, Halifax)

This seems like a bit of a stretch but I get the point they are trying to make.

These chimera are mentioned by many other Jewish writings, including the book of Jasher (Jasher 61:15-16). The concept was globally accepted that these creatures existed. All ancient cultures understood this as their reality.

https://www.projecteleazar.com/the-3-races/ http://www.pseudepigrapha.com/pseudepigrapha/jasher.html

A stanza that consists of three lines and is known as a tercet is used here by Larkin. In a tercet, either all three lines rhyme or the first and third lines rhyme, and in this particular tercet, the words "piss" and "cleanliness" rhyme with lines 1 and 3, respectively. He does this by using a strong sibilance, which leaves the hiss sound in the head of the reader, which in turn gives the reader the picture of Larkin as a serpent.

In Medieval Europe, a minstrel was a singer or musician who recited heroic poetry for the nobility. Minstrels created their own tales, but would often embellish the works of others in their performance. They were commonplace in courts, entertaining lords and courtiers with chansons de geste, or epic poems. After Sir Gawain's success cutting off the Green Knight's head, King Arthur and the rest of the court return to their festivities, referred to as minstrelsy due to their entertaining nature.

https://www.britannica.com/art/minstrel

This passage from "The Green Knight" is an interesting one, as it highlights the theme of gender roles that are present throughout the poem. Lady Bertilak is clearly in a position of vulnerability as she is alone and seeking Gawain's instruction, while Gawain is in a position of power as a knight and a man. The lady's words suggest that she wants to learn from Gawain, but also that she expects him to be a teacher and a mentor to her. Nevertheless, the passage raises interesting questions about the role of women in medieval society and how they were expected to behave in relation to men.

https://www.litcharts.com/lit/sir-gawain-and-the-green-knight/themes

Colors are a way for people to express themselves. It's common knowledge that royals only wore purple due to how expensive and difficult receiving the pigment was. In this instance, the author used green to express the knight's purpose. In the 14th century, green was commonly used to show growth and "the life of God" ("The Greatness of Green"). Gawain's journey helped him grow as a person, and in the end, when the Green Knight held an axe to his head to fulfill his promise, he blessed Gawain with keeping his life. The green color was used to help Gawain reflect on his character and become a better person because of it. Even at the very end, Gawain holds onto the green girdle to stay aware of his sin and grow from that poor decision.

Still, Carly. “The Greatness of Green.” The Medieval Garden Enclosed, The Metropolitan Museum of Art, 28 Aug. 2013, https://blog.metmuseum.org/cloistersgardens/2013/08/28/the-greatness-of-green/#:~:text=In%20the%20Middle%20Ages%20the,life%2C%20nature%2C%20and%20spring.

Our first site at Guinevere as a character immediately characterizes her as the ideal feminine picture of beauty and grace. Described as the fairest woman that may have ever been seen, Guinevere is perfection. This perfection, however, portrays Guinevere as a "fetishized object" (Heng 502). She is, however, bound to her husband and therefore untouchable. The gender representation here is telling.

Heng, Geraldine. “Feminine Knots and the Other Sir Gawain and the Green Knight.” PMLA, vol. 106, no. 3, 1991, pp. 500–14. JSTOR, https://doi.org/10.2307/462782. Accessed 10 Mar. 2023.

The supernatural is primarily represented through the Green Knight, who is able to perform feats beyond human comprehension. While he is a being beyond nature, his powers are seemingly linked to the cycle of the seasons and regeneration that defines nature. These small glimpses of his power contrast the rigid structures of chivalry and civility that define Arthur's court. When Gawain crosses over to the wilderness, the ideals of chivalry gradually wane as he is challenged to live with nature's unpredictability and overarching power. His mounting confusion and doubt in the face of nature's chaos culminates in him betraying the very ideals he represents when he hides the girdle away from Bertilak. By the end of the poem, he quietly recognizes the true nature of the world outside of the court, seemingly embracing it when he wears the green girdle.

Parfitt, Georgina. "Sir Gawain and the Green Knight Themes: The Natural and the Supernatural." LitCharts. LitCharts LLC, 3 Sep 2013. Web. 10 Mar 2023, https://www.litcharts.com/lit/sir-gawain-and-the-green-knight/themes/the-natural-and-the-supernatural.

Taken at face value, Morgain le Fay appears to be the instigator of the entire situation Gawain is facing. However, it is important to consider perspective. It is impossible to be certain that Bertilak is telling the full truth (Warner). While the simplicity of one person orchestrating the entire situation is satisfyingly conclusive, Bertilak has already proven himself to be deceitful in his disguises (Warner). It is difficult to trust what he is accusing Morgain of when he himself has played such a deceitful role throughout the story. Works Cited: Warner, Lawrence. “The Lady, the Goddess, and the Text of Sir Gawain and the Green Knight.” The Chaucer review 48.3 (2014): 334–351. Web.

The beginning of the tale started with Christian traditions, a Christmas-tide, and continued to hold Christian values throughout the entirety of the poem. It is only fitting that the tale of Sir Gawain and the Green Knight ends with Christian morals. The "crown of thorn", in this case, symbolizes Sir Gawain's atonement for his dishonesty and also represents his guilt through Christian symbols. This is a significant tie into Christianity because the "crown of thorn" is "wreath of thorns that was placed on the head of Jesus Christ at his crucifixion, whereby the Roman soldiers mocked his title “King of the Jews"." While Sir Gawain is not literally wearing a crown of thorns, his memories and actions will always be present along with the girdle that will constantly remind him of the metaphoric crown he wears for the dishonesty, even if he was forgiven by his accompaniment.

source on crown of thorns: https://www.britannica.com/topic/Crown-of-Thorns-religious-relic

This section foreshadows multiple aspects of the poem. Obviously, this is the act that foreshadows the Green Knight's true power. By resurrecting immediately following decapitation, we are seeing a glimpse into the supernatural power this mysterious figure possess. Additionally, this section foreshadows the intellect and followthrough of the Green Knight, by reciting (for the third time in the poem, via dialogue) the terms of the oath being made by Sir Gawain - the language used even indicates that the Green Knight views this as law-like and now guaranteed to play out. Effectively showcasing the Knight's "game master" level of thinking and Sir Gawain's "in over his head" level of unpreparedness for the remainder of the work.

Citation: Acosta, L. (n.d.). Sir Gawain and the green knight. Passage Analysis. Retrieved March 8, 2023, from http://csis.pace.edu/grendel/prjs2c/analysis.htm

The Green Knight proposes the question that someone plays a "game" with him that involves a contract. These lines in the poem explores the themes of chivalry as the contract alludes to bravery and probity since it deals with an agreement. He fools Gawain into this contract by disclosing that he will grant him the initial strike, allowing him to slice his head off. Ironically, the Green Knight's characteristics of "Trickery and deceit" are in opposition to the traditional attributes of chivalry (Maldonado 13). This deceit comes as the Green Knight fails to tell Gawain that after he strikes him, he will still be alive. The Green Knight essentially disguises his true identity which "feigns ignorance about Gawain and his quest" (Maldonado 13). In other words, the Green Knight fails to inform Gawain of his immortal-like characteristics considering he survives decapitation, and through his inability to speak the truth, he breaks the chivalric code.

Maldonado, Joshua David, "The Game at the Green Chapel: A Game-Oriented Perspective on Chivalry in Sir Gawain and the Green Knight" (2020). Senior Projects Spring 2020. 122. https://digitalcommons.bard.edu/senproj_s2020/122

Hunting was a sport in medieval times. Hunts were reserved to the people of the ruling class as opposed to the lower class. So, the land in which the lord is hunting is exclusively for him and he has full permission to hunt as he pleases. There are two types of hunting: At force and ‘Bow and stable’ hunt. The type of hunting presented in the story is “At Force' Hunting and these hunts were the most strenuous forms of Medieval hunting. The 'At Force' hunts were designed for fit, young and very active men.” The men are injured and hurt before they capture the animal. A boar moves fast, so active men is needed to perform the hunt mentioned in the story. The huntsmen cutting off the head and giving it to their lords signifies a conquest or win for the lord. So, this further asserts that hunts are a sport in medieval times. The article also mentions that the boar is the prey hunted in this type of hunt. Medieval Hunting History, https://m.medieval-life-and-times.info/medieval-life/medieval-hunting-history.htm.

Sounds like the story walker brothers cowboy initially opens with a family of four. It appears one evening after the families supper the father and eldest son take a walk to down to the lake.

Funny thing I thought this was the eldest son but this is the eldest daughter

carelessness is a concern Jonathan has seen someone else loose their money to a thief.

Jonathan Iwegbu and his family escaped with their lives and the miracle of their story is what blesses us as we come to hear a story of faith.

Reviewer #1 (Public Review):

Elbaz-Hayoun et al. investigate the role of macrophages in the gliotic response of retinal Müller glia and photoreceptor cell death. Monocytes (a precursor of macrophages) were isolated from age-related macular degeneration (AMD) patients. When injected into light-damaged retinas, a reduction in the number of photoreceptors and ERG b-wave strength (evidence of abnormal photoreceptor function) was observed. The authors reasoned that macrophages generated from the injected monocytes might be responsible for the retinal damage. To test this hypothesis, macrophage subtypes were generated from AMD-derived human monocytes and injected into light-damaged mouse eyes. Interstingly, only the human hM2a macrophage subclass mimicked the retinal degeneration of monocyte injection in mouse retinas. Similarly, human M2a (hM2a) cells cultured on mouse retinal explants and even serum-free hM2a culture supernatant were sufficient to induce photoreceptor apoptosis. These effects were not observed with hM1 cells. To identify possible diffusible factors responsible, proteins present in hM2a and hM1 culture supernatants were identified. Nine cytokines were found at higher levels in the hM2a supernatant, and three of these were ligands for the C-C chemokine receptor CCR1. The authors confirmed CCR1 expression in the retina, which was predominantly detected in Müller glia. Importantly, Müller cell expression of CCR1 in the mouse retina was significantly increased following light damage. In contrast, CCR2 and CCR5 levels were unchanged in Müller cells. The increase in CCR1 expression, gliosis, and photoreceptor death was also observed in the rd10 mouse model of retinitis pigmentosa. Inhibiting CCR1 activity in light-damaged eyes using the drug BX471 had impressive effects. Müller activation and photoreceptor cell death were reduced and ERG b-wave levels were partially recovered - clearly indicating a role for CCR1 in retinal degeneration. Additional evidence was provided suggesting that CCR1 activation in M2a macrophages might also play a role in stimulating the movement of other macrophages into the retina and activating retinal microglia, which migrate to the ONL. These data identify a new link between cells of the immune system and those within the retina which contribute to the progression of retinal degeneration.

The data mostly support the conclusions of this paper. However, additional controls need to be added to some experiments.

Concerns:

1) To determine the effect of diseased monocytes on retinal health, light-injured mouse retinas were injected with monocytes isolated from AMD patients (Figure 1 - figure supplement 1). This resulted in a reduction in photoreceptor number and ERG b-wave amplitude. However, the light-injured control eye was injected with PBS only, so no cells were present. The reasoning for using this control was not provided. The appropriate injection control would include monocytes isolated from non-AMD patients. This control should be performed side-by-side with cells from AMD patients.

2) The authors hypothesize, from the experiments presented in Figure 1 - figure supplement 1, that the injected monocytes generated macrophages in the retina, which were responsible for the observed neurotoxicity (Lines 143-145). However, no direct evidence was presented. This idea should be tested in vivo. This could be done by injecting tracer-labeled human AMD-derived monocytes into light-injured mouse retinas. If the authors' hypothesis is true, collected retinas should contain tracer-labeled cells that express macrophage markers. Tracer-labeled M2a macrophage cells should be present since subsequent experiments identify this subclass as being associated with retinal cell death.

3) Photoreceptor number and b-wave amplitudes were measured in light-injured retinas injected with one of four macrophage cell types generated from human AMD-derived monocytes. The authors conclude that only injection of M2a cells reduced photoreceptor number and b-wave amplitudes (Figure 1C, E). This may be true, but it is difficult for the reader to make a conclusion (especially in Fig. 1E) due to the large error bars and five different traces overlapping each other. To make these results easier to interpret, graph control cells with only one experimental sample (cell type) at a time.

4) Most injected macrophages were located in the vitreous. In the case of M2a cells, the authors note that "several of the cells migrated across the retinal layers reaching the subretinal space" (Lines 167,168). One possible explanation for why M0, M1, and M2c macrophages did not induce retinal degeneration is that they did not migrate to the subretinal space and around the optic nerve head. Supplementary figures should be added to demonstrate that this is not the case.

5) Figure 1 - figure supplement 2: Panel A, B cells were stained with CD206 to demonstrate the presence of M2a macrophages (panel B). The authors conclude that panel A contains M1 and panel B contains M2a cells. The lack of CD206 expression illustrates that panel A cells are not M2a macrophages but do not demonstrate they are M1 macrophages. A control using an M1 cell marker is necessary to show that panel A cells are M1 and M1 cells are not detected in M2a cultures.

6) Ex vivo, apoptotic photoreceptor and RPE cells are observed when cultured with M2a macrophages (Figure 2). Do injected M2a cells also induce apoptosis of RPE cells in vivo? This is important to establish that retinal explants are a good model for in vivo experiments.

7) Reactive oxygen species (ROS) production was measured to determine if M2a cell-mediated neurotoxicity was due to oxidative stress. It is concluded that a ROS increase is partly responsible (Line 218). The data do not support this conclusion. ROS was detected in cultured M2a macrophages. More importantly, however, there was no increase in oxidative damage in vivo. The in vivo and cell culture results contradict each other so no conclusion can be made. The lack of in vivo confirmation weakens the argument that ROS drives M2a neurotoxicity. Text suggesting a role for ROS in neurotoxicity should be appropriately edited (Lines including 218, 244, 401,406,481).

8) The authors ask if the photoreceptor cell death is cytokine-mediated. Multiple cytokines were enriched in M2a-conditioned media. Of particular interest were CCR1 ligands MPIF1 and MCP4. The implication is that these two ligands mediate the M2a macrophages to photoreceptor cell death through CCR1. However, there is no attempt to show that either MPIF1 or MCP4 are present in vivo, or are sufficient to induce the retinal response observed. This could be demonstrated by injection of MPIF1 or MCP4. Evidence that either ligand phenocopies M2a macrophage injection would be direct evidence that CCR1 ligands activate the retinal response. Furthermore, co-injection with BX174 should block the effect of these ligands if they work through CCR1.

The ninth circle of hell is reserved for those who have betrayed God or those who have supported them. Judas being found in the ninth circle is no coincidence, as it represents both Dante's faith and his feelings about betrayal. In Christianity, Judas is known "as the man who betrayed Jesus" (Roat) in return for 30 silver coins. Due to this deed, he must suffer eternal punishment in hell. Not only that, but he was placed in the final, and most extreme circle, where Satan resides. He endures the most painful of punishments due to his lack of loyalty to not only God, but also a friend during his life. In Dante's mind, this is the fair punishment for people that complete an action like this.

Works Cited: Roat, Alyssa. “Who Was Judas Iscariot? His Life and Betrayal.” Christianity.Com, Christianity.com, 21 June 2019, https://www.christianity.com/wiki/people/who-was-judas-iscariot.html.

A length of cloth worn by women as a covering for the head and shoulders and often especially in Eastern countries for the face. 面紗

Assegai: "A slender, iron-tipped, hardwood spear used chiefly by southern African peoples"

Essentially, it is a Pole/weapon used by African people for throwing- a native weapon. Maybe she feels connected to her roots? She feels wild and real and her culture comes out within her?

eLife assessment

In this study, neurons were recorded and combined across the parahippocampal area while rats performed a memory-guided spatial navigation task. Sophisticated analytical tools were used to provide convincing evidence that neuronal populations in these areas show behavior-related changes that might indicate the encoding of errors by the system. The valuable results suggest that rate remapping is a likely mechanism to support changes in representations that support memory-guided behavior in these regions, most interestingly in neurons that code head direction.

Reviewer #1 (Public Review):

In this study, single neurons were recorded, using tetrodes, from the parahippocampal cortex of 5 rats navigating a double-Y maze (in which each arm of a Y-maze forks again). The goal was located at any one of the 4 branch terminations, and rats were given partial information in the form of a light cue that indicated whether the reward was on the right or left side of the maze. The second decision point was uncued and the rat had no way of knowing which of the two branches was correct, so this phase of the task was more akin to foraging. Following the outbound journey, with or without reward, the rat had to return (inbound journey) to the maze and start to begin again.

Neuronal activity was assessed for correlations with multiple navigation-relevant variables including location, head direction, speed, reward side, and goal location. The main finding is that a high proportion of neurons showed an increase in firing rate when the animal made a wrong turn at the first branch point (the one in which the correct decision was signalled). This increase, which the authors call rate remapping, persisted throughout the inbound journey as well. It was also found that head direction neurons (assessed by recording in an open field arena) in the same location in the room were more likely to show the rate change. The overall conclusion is that "during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance" or are "nodes in the transmission of behaviorally relevant variables during goal-directed navigation."

Overall I think this is a well-conducted study investigating an important class of neural representation: namely, the substrate for spatial orientation and navigation. The analyses are very sophisticated - possibly a little too much so, as the basic findings are relatively straightforward and the analyses take quite a bit of work to understand. A difficulty with the study is that it was exploratory (observational) rather than hypothesis-driven. Thus, the findings reveal correlations in the data but do not allow us to infer causal relationships. That said, the observation of increased firing in a subset of neurons following an erroneous choice is potentially interesting. However, the effect seems small. What were the actual firing rate values in Hz, and what was the effect size?

I also feel we are lacking information about the underlying behavior that accompanies these firing rate effects. The authors say "one possibility is that the head-direction signal in the parahippocampal region reflects a behavioral state related to the navigational choice or the lack of commitment to a particular navigational route" which is a good thought and raises the possibility that on error trials, rats are more uncertain and turn their heads more (vicarious trial and error) and thus sample the preferred firing direction more thoroughly. Another possibility is that they run more slowly, which is associated with a higher firing rate in these cells. I think we, therefore, need a better understanding of how behavior differed between error trials in terms of running speed, directional sampling, etc. A few good, convincing raw-data plots showing a remapping neuron on an error trial and a correct trial on the same arm would also be helpful (the spike plots were too tiny to get a good sense of this: fewer, larger ones would be more helpful). It would be useful to know at what point the elevated response returned to baseline, how - was it when the next trial began, and was the drop gradual (suggesting perhaps a more neurohumoral response) or sudden.

We can see that this reaction she is being given is of one that causes extreme despair. Also comparing the melancholy to a child who has cried themselves to sleep is one that has great significance. The "wild abandonment" is the way she is described mourning since the news of her husbands passing one she thought that was very visible, is one she is not taking lightly. Being surrounded by family she is able to let loose and to completely break down and start bawling down at the loss of her husband and it is a complete mess. She sees her life as unfit to be lived without her husband and it was difficult for a woman of her time to move on without a husband. Knowing what is coming for her and that her entire life has been a cage and that with the presumed death of her husband because of all the emotions and everything else she has to process. During this time period women were oppressed and have limited if any freedom, so with the death of her husband there is so many different emotions and so many situations to contemplate due to new found freedom in a sense.

2020 წელს ციურიხის უნივერსიტეტისა და თბილისის სახელმწიფო უნივერსიტეტის თანამშრომლობით შეიქმნა ახალი, ინოვაციური კურსი ორივე უნივერსიტეტისათვის. გარდა ამისა, შვეიცარიის მეცნიერებათა და ტექნოლოგიის დაწესებულებისა და ჟენევის უნივერსიტეტის თანადაფინანსებით შეიქმნა აპლიკაცია, რომელიც ხელს შეუწყობდა სწავლების გამართულ ფუნქციონირებას. კურსის მთავარი მიზანია კრიტიკული აზროვნების განვითარება და სოციალურ-პოლიტიკური საკითხების განხილვა/მსჯელობა, რომელიც ხელს შეუწყობს მაღალმთიან რეგიონის განვითარებას. სტუდენტების პირველი ჯგუფის მიღება მოხდა 2022 წლის შემოდგომას. სწავლება მოიცავდა როგორც დისტანციურ ლექციებს, ასევე სალექციო საათებს ციურიხისა და თბილისის სახელმწიფო უნივერსიტეტებში.

არსებული ბლოგი, რომელიც ეხება მთის მიგრაციას შვეიცარიასა და საქართველოში, რამდენიმე საკვანძო ნაწილისგან შედგება, კერძოდ ცალ-ცალკეა ჩაშლილი ის ძირითადი მდგომარეობა და მიზეზები, რაც იწვევს ამ ორ ეკონომიკურად და კულტურულად განსხვავებულ ქვეყნებში მთის მიგრაციას.

შვეიცარია, რომელიც ერთი შეხედვით ტურისტულად განვითარებული და მიმზიდველია თავისი მთიანი რეგიონებითა და კულტურით, დგას ამ პრობლემების წინაშე.მთის მიგრაცია ამ ქვეყანაში ახლა არ დაწყებულა, მაშინ როცა ინდუსტრია ვითარდებოდა, მთის მოსახლეობამ არჩია პროფესიული თუ სტაბილური ეკონომიკური მდგომარეობის გამო მთიანი რეგიონი დაეტოვებინა და აგლომერაციაში ჩართულიყო. ისე როგორც შვეიცარიაში, ასევე საქართველოშიც, რომლის ტერიტორიების უმეტეს ნაწილს მთიანი ზონა წარმოადგენს, მთის მიგრაცია ახალი დაწყებული არ არის, ის დიდი ხანია მიმდინარეობს და ამის რამდენიმე მთავარი მიზეზი არსებობს. შვეიცარიის მსგავსად საქართველოშიც მთის მიგრაციის მიზეზი არის საჭირო სერვისებზე მიუწვდომლობა, როგორიც არის განათლება, ჯანდაცვა, კარიერული განვითარება და სხვა საჭირო სერვისები, რომელიც ხელმისაწვდომი არ არის მთის მოსახლეობისთვის მათი ასაკის შესაბამისად.

განსაკუთრებით, ახალგაზრდა თაობას უჭირს მთიან რეგიონში ცხოვრება, შესაბამისად იძულებულნი ხდებიან დატოვონ მშობლიური მხარე და ურბანულ ზონებში დასახლდნენ პირადი სარგებლის მიღების მიზნით.

ეს ბლოგი ნათლად ასახავს იმ საერთო მახასიათებლებს და მიზეზებს, რომელიც ამ ორ განსხვავებულ ქვეყანას აერთიანებს. მიუხედავად იმისა რომ განვითარების სხვადასხვა ეტაპზე ვიმყოფებით , საერთო პრობლემის წინაშე ვდგავართ და ამ პრობლემის გამომწვევი მიზეზებიც საერთოა გარკვეულ ჭრილში. საკმაოდ საინტერესოა არსებული საკითხის შესწავლა იმ გადმოსახედიდან, რომ ქალაქებში მოსახლეობის რაოდენობა იზრდება და ეს დამატებით პრობლემებს წარმოშობს, მთის მოსახლეობის მდგომარეობა მძიმეა, რადგან არ აქვთ შესაძლებლობა ისე როგორც ქალაქის და დაბის მოსახლეობას, მიიღონ საგანმანათლებლო სერვისები, საჭიროების დროს სწრაფად მიუწვდებოდეთ ხელი ჯანდაცვის სერვისებზე, შეძლონ სხვადასხვა საქმიანობაში ჩართვა და საკუთარი თავის განვითარება. ამ რთული სიტუაციიდან გამოსვლისვლისთვის მნიშვნელოვანია გარკვეული პროგრამებისა და ღონისძიებების გატარება, მთიანი რეგიონის პოპულარიზებისა და განვითარების მიზნით.

სტატია შეეხება შვეიცარიისა და საქართველოს მთებიდან მიგრაციის საკითს . ის დაწერილია სიმონ დუფნერის, ხატია გორგიშელის და ანნიკა სპარის მიერ, თბილისის სახელმწიფო უნივერსიტეტისა და ციურიხის უნივერსიტეტის სტუდენტების თანამშრომლობის შედეგად და გამოქვეყნებულია 2022 წელს .

სტატია შედგება ოთხი ქვესათაურისგან . პირველია შესავალი, სადაც ზოგადადაა განმარტებული მიგრაცია, როგორც ფენომენი , რომელიც მსოფლიოში სხვადასხვა მთიანი რეგიონებისთვისაა დამახასიათებელი და მისი სპეციფიკა და გამომწვევი მიზეზები დამოკიდებულია რეგიონის პოლიტიკურ და კულტურულ სტრუქტურაზე .

მეორე აბზაცში უკვე კონკრეტულადაა განხილული შვეიცარიის მთებიდან მიგრაციის საკითხი , სადაც ვიგებთ , რომ შვეიცარიში მთებიდან მოსახლეობის მიგრაცია ჯერ კიდევ მე-17 საუკუნის ბოლოდან დაიწყო რისი გამოწვევი მიზეზიც საათების დამზადებისა და ტექსტილის ინდუსტრიის განვითარება გახდა . მიგრაციის პრობლემა ქვეყანაში ჯერ კიდევ აქტუალური თემაა რადგან მთიან რეგიონებში არაა დასაქმებისა და განვითარების პერსპექტივა , ამიტომ ახალგზრდები ტოვებენ მთიან რეგიონებს და მიდიან დიდ ქალაქებში სადაც განვითარების მეტი პერსპექტივა აქვთ.

მესამე აბზაცი საქართველოს მთიანი რეგიონებიდან მიგრაციას ეხება . ყურადღება გამახვილებულია იმაზე , რომ ქვეყნის ტერიტორიის 65%-ზე მეტი მთიან ზონებს უკავია და მიუხედავად ამისა მრავლადაა მაღალმთიან რეგიონებში ისეთი პრობლემები , როგორიცაა უმუშევრობა, განათლებაზე ხელმიუწვდომლობა , გარემოს დეგრადაცია და დაზიანებული გზები, რაც იქ მცხოვრებებს სრულყოფილად ცხოვრებაში უშლის ხელს .

ბოლო, მეოთხე აბზაცში კი დასკვნის სახით წერია , რომ მიუხედავად პოლიტიკური და ისტორიული სტრუქტურების განსხავავებისა მთიანი რეგიონებიდან მიგრაცია საქართველოსა და შვეიცარიის საერთო პრობლემაა , რომლის ძირითადი განმაპირობებელი ფაქტორებიც სამუშაოს ან განათლების უკეთესი შესაძლებლობებია.

მიმაჩნია , რომ სტატიაში განხილული პრობლემა საყურადღებოა ორივე ქვეყნისთვის , იმიტომ , რომ მიგრაციის პროცესი განსაკუთრებულ სირთულეს წარმოადგენს თავად მიგრირებული მოსახლეობისათვის , რადგან ისინი რიგ ფინანსურ და სიციალურ პრობლემებს აწყდებიან . ამასთან სახელმწიფოსთვის პრიორიტეტი უნდა იყოს მსგავსი რეგიონების განვითარება და მათი პოტენციალის სწორად გამოყენება .

this feels symbolic of how he simply can't see how she suffers, because he can't see through her point of view

just articulate. damn

Link all these back to the title "Clocks"! What is significant about the title?

from my comment in the abstract - this seems like the perfect place to talk a little more about the "adult sea stars are heads" hypothesis

This is a really exciting idea - I was hoping to read more about why you felt like this was the key take-away based on the data of the patterning system of the ambulacral ectoderm in the discussion section? Also, this is reminiscent of tardigrades as head-like animals, missing the Hox trunk genes from Bob Goldstein's lab and I think some of Andi Hejnol's work on many spiralian taxa - it feels like something important evolutionary is going on here with a many metazoan taxa utilizing the deuterostome/vertebrate "head" patterning system, though perhaps we should be thinking about the deuterostome/vertebrate co-option of this system???

This manuscript explores how the AP axis is patterned in the derived body plan of echinoderms. The authors use RNA tomography in multiple sequential sections of juvenile starfish limbs to evaluate the expression of canonical groups of AP genes with respect to the proximal-distal, oral-aboral, and medial-lateral axes. The authors visualize the gene expression patterns of canonical AP marker genes using HCR in starfish juveniles.

Based on these data, the authors build a model of the starfish body plan that places anterior genes in the ambulacral region of the ectoderm (the ambulacral-anterior hypothesis). The authors show that a large portion of the starfish ectoderm – the interambulacral region – does not appear to express canonical ectodermal markers of the AP axis. Most of the trunk markers used in this study were Hox genes, which in this study and other echinoderm studies appear to be primarily restricted to the mesoderm. HCR of additional ectodermal trunk markers would help clarify the identity of the interambulacral region.

It will be very interesting to understand what genes are expressed in the interambulacral region to determine whether starfish are indeed "mostly head-like animals."

It might be helpful to have this figure also elaborated as a schematic with corresponding colors, such as in Supp. Fig. 3. As someone without familiarity with the anatomy, it's a little difficult to wrap my head around this image. It would also be helpful to indicate where the ambulacral boundary is with respect to the other features, to be able to more easily interpret panels u-b'. Adding schematics of the classified expression pattern to the left of each row of images could help ease interpretation.

I do like the the length of the sentence and its difficulties mirror the confusion in his head, so I would recommend keeping some of that while still cleaning up the sentence a bit.

yes, good to get quote, also let Jesse know when y'all will be thee and you will get access to athletes after the games, for quotes

im stuck guys pls help!

What would be to prevent them from acting outside of their powers?

Some stats would help here. Would the author also argue that they should be stripped of their lands, the profits for which currently go to the government. If so, would they argue the same for all billionaires. Perhaps a good idea, but I don't see why the royals should be singled out.

A slightly odd article for Declassified, being an opinion rather than fact piece.

I've heard how physical humidity in the weather can have an impact on your mood, but never heard about humidity in the brain causing mental disorders to appear. That is an interesting thought....

This sentence is using an analogy to explain the role of sovereignty in a contract and its relationship to an artificial person.

The sentence begins by stating that the "sovereign" is the ruling force behind the contract, meaning that the person or entity with the highest authority or power is responsible for creating and enforcing the terms of the contract.

Then, the sentence introduces an analogy between the contract and an artificial person. An artificial person is a legal concept used to describe a non-human entity, such as a corporation or government, that has certain legal rights and obligations.

The sentence goes on to say that in this analogy, the concept of sovereignty is the "soul" of the artificial person. This is because sovereignty refers to the supreme power or authority that is held by the entity, much like the soul is considered to be the essence or defining characteristic of a living being.

Finally, the sentence states that the sovereign itself is like the "head" of the artificial person, suggesting that the sovereign is the highest authority within the entity and is responsible for making decisions and enforcing the entity's will.

Overall, the sentence is using an analogy to explain the important role of sovereignty in a contract and how it relates to the concept of an artificial person.

NOW I SAY, "OKAY, THIS IS DONE." I READ IT. IT FEELS LIKE A MOVIE. AND I'M GONNA PUT IT IN THE BOX. AND I'M GONNA PUT IT IN THE BOX IN THIS ORDER, AND THIS IS THE ORDER THAT I'M GONNA WRITE IT IN IN MY FIRST DRAFT. OVER THE NEXT NUMBER OF WEEKS, I START WRITING. WHAT I'VE BEEN DOING, I'VE BEEN SEEING THE SCENES IN MY HEAD FOR SO LONG AT THIS POINT THAT IT'S ALMOST LIKE JUST REGURGITATION. LIKE, I'M JUST GETTING OUT. AND I CALL IT MY VOMIT DRAFT. #

Dustin Lance Black's "vomit draft" is similar to Mozart's peeing his music out like a cow. His method is also similar to Victor Margolin who's gone over the material several times by the time he's finally writing out his draft.

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

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Reply to the reviewers

We thank all the reviewers for having raised constructive criticism to fortify the main message and improve the clarity of the manuscript. We appreciate that all reviewers found that our work addresses an important topic and is of interest to a broad audience. We believe that we have thoroughly addressed the concerns of the reviewers, especially with regard to 1) performing another SMC3 chromatin immunoprecipitation and sequencing (ChIP-seq) replicate and control, 2) including a later time point for the transcriptional data, and 3) performing additional characterization of the growth phenotype of the SMC3 conditional knockdown.

Reviewer #1

(Evidence, reproducibility and clarity (Required)):*

Summary The present work by Rosa et al., provides convincing data about the presence and functional relevance of the cohesin complex in Plasmodium falciparum blood stages. In accordance with other organisms, the composition of the cohesin complex containing SMC1, SMC3 RAD21 and putatively STAG could be confirmed via pulldown and mass spectrometry. Basic characterization of endogenous tagged SMC3 demonstrated the expression and nuclear localization during IDC, as well as the relatively stable accumulation at centromeric regions, consistent with the known cohesin function in chromatid separation. Furthermore, dynamic and stage-dependent binding to intergenic regions observed in ChIPseq and major transcriptome aberrations upon knockdown of SMC3 (__Response: __As we regularly perform ChIP-seq experiments in the lab, we have generated multiple negative control datasets. In our opinion, the most stringent negative control for an HA-tagged protein is performing ChIP with an HA antibody in a WT strain. We have recently published an in-depth analysis of this (and other) negative ChIP-seq controls (Baumgarten & Bryant, 2022, https://doi.org/10.12688/openreseurope.14836.2). We show in this publication that non-specific ChIP-seq experiments (such as negative controls) result in an over-representation of HP1-heterochromatinized regions due to differences in sonication efficiency of heterochromatin and technical challenges with mapping regions with high levels of homology. In the anti-HA in WT ChIP negative control (performed at 12hpi), we do not see any enrichment at centromeric regions, but rather at heterochromatinized regions where clonally variant gene families are located. We performed peak calling analysis and found no significant overlap between the negative control ChIP-seq and the SMC3-3HA ChIP-seq data at 12hpi.

In addition, we have now performed a second biological replicate of the SMC3-3HA ChIP-seq with a different clone at all time points. We compared this data to that from the original clone and found significant overlap of the peaks called (see what is now Table 4 and Supp. Fig. 3A). We generated a stringent list of peaks that were shared between both clones at each time point and repeated all downstream analyses (see what are now Tables 5-8). We found that our conclusions were largely unchanged. Text describing these experiments and analyses have been added throughout the results section.

• Proposed mechanism of repressive effect of SMC3 early in IDC on genes, that get de-repressed in late stages: To claim this mode of function, it would be necessary to include a KD on late stage parasites. If there is an early repressive role of SMC3, upregulated genes should not be affected by late SMC3-KD. __Response: __To be clear, we are most interested in the transcriptional role of SMC3 during interphase, where results are not confounded by its potential role in mitosis. However, we did collect a 36hpi time point in the SMC3-3HA-glmS and WT strain, with and without glucosamine. We have added this last time point and the WT data from the other two time points to the manuscript (see Tables 11-13). Unfortunately, and for reasons unknown, the WT replicates treated with glucosamine showed a significantly advanced “transcriptional age” compared to the other replicates at 36hpi (see what is now Supp. Fig. 5B). Thus, we did not feel comfortable performing the RNA-seq analysis as we did with the other two time points (i.e. subtracting up- and down-regulated genes from the WT control from the SMC3-3HA-glmS data sets). We have added this information to the results section (Lines 256 and 261). As the WT parasites treated with glucosamine were approximately 8 hours in advance of the untreated WT parasites for the 36hpi time point, any up- and down-regulated genes might have been due to differences in the cell cycle rather than due to glucosamine treatment. The glmS system of inducible knockdown is widely used in P. falciparum; however, to our knowledge, no lab has investigated whether glucosamine treatment affects transcription in wildtype cells over the course of the IDC. Thus, for accurate phenotypic characterization of any protein with this system with regard to transcriptomics, we thought it was important to provide an RNA-seq dataset to define the cohort of genes affected by glucosamine treatment in WT parasites. We hope that our study will demonstrate the importance of using stringent controls when using inducible knockdown systems.

To address the question of whether genes that are upregulated upon depletion of SMC3 at early stages are affected at the 36hpi time point, we performed differential expression analysis of the SMC3-3HA-glmS parasites with and without glucosamine at 36hpi (we have added this data in Table 11). Again, significantly up- and down-regulated genes were not filtered using the WT dataset. With this analysis, we see only three genes from the list of invasion-related genes (Hu et al., 2010) that are up-regulated, but none of them have a significant q-value (Tab 5 of Table 18). Thus, depletion of SMC3 in late stage parasites does not lead to up-regulation of the same genes that are upregulated at 12 and 24hpi. We have added this information to the text (Line 273).

Furthermore, the hypothesized repressive effect of SMC3 does not explain the numerous genes downregulated in KD.

__Response: __As we state on line 350, we do not observe enrichment of SMC3 at downregulated genes, suggesting an indirect or secondary effect of SMC3 KD on these genes.

• Due to the fact, that the KD was induced at the exact same timepoint and analysed 12h and 24h after induction it is possible that identified, differentially expressed genes at 24h are not directly regulated by SMC3, but rather due to a general deregulation of gene expression. Did the authors attempt to analyse gene expression upon induction at ring, trophozoite and schizont stage? Response: __As we state on line 230, in order to achieve SMC3 KD at the protein level, we had to treat the parasite with glucosamine for two cell cycles (approximately 96 hours). After two cell cycles of glucosamine treatment, the parasites were tightly synchronized and sampled 12 and 24 hours later. Thus, SMC3 KD takes place over the course of multiple days, but parasites are collected after stringent synchronization. Giemsa staining and bioinformatic analysis (line 250) of the RNA-seq data from parasites (with or without glucosamine) harvested at 12 and 24 hpi show that these parasites were synchronous and that there were no gross differences in genome-wide transcript levels. It is certainly possible that differentially expressed genes at 12 or 24hpi are not directly regulated by SMC3, and this is precisely why we perform ChIP-seq of SMC3: to provide evidence of direct involvement via binding, as stated on line 281. __

• *Based on rapid parasite growth, the authors hypothesize a higher invasion rate due to upregulation of invasion genes. This hypothesis is not supported by quantitative invasion assays or quantification of invasion factors on the protein level. An alternative explanation could be a shorter cell cycle (__Response: __We have repeated the growth curve analysis with additional clones and no longer observe a growth phenotype in the SMC3 knockdown condition. We have added images of Giemsa-stained parasites from the knockdown time course we performed to what is now Supp. Fig. 5A. We see no obvious differences in cell morphology caused by glucosamine treatment in the WT or SMC3-3HA-glmS parasites.

• Correlation of SMC3-occupancy/ATAC/expression profile of the exemplary genes rap2 and gap45 (Figure 4C,D,E): is this representative for all upregulated genes? __Response: __SMC3 occupancy shown at rap2 and gap45 is representative for all upregulated genes (see Fig. 4A and B). It is difficult to provide a general representation of the average expression profiles of all up-regulated genes over the course of the IDC, but Fig. 3E shows that the vast majority of up-regulated genes normally reach their peak expression in late stage parasites. With regard to ATAC-seq profiles, we have performed a metagene analysis of chromatin accessibility (data taken from (Toenhake et al., 2018)) at all up-regulated genes at time points that closely correspond to the time points used in our study: 15, 25, and 35, and 40 hpi (new Fig. 4C). This metagene analysis confirms what we observe at individual genes: increasing chromatin accessibility over the course of the IDC at these genes’ promoters. While metagene analyses offer important information, we always try to show the raw data (as in new Figs. 4D-F) from individual examples as proof of principle.

• Given that SMC3 appears to be not essential for parasite growth, the authors could generate a null mutant for SMC3, which might allow for easier analysis of differences in gene regulation, cell cycle progression and/or invasion efficiency. __Response: __As we explain on line 327, very little cohesin is required for normal growth and/or mitosis in our study and two studies in S. cerevisiae and D. melanogaster. However, SMC3 is essential in S. cerevisiae. We were unable to knock out SMC3, and a recent mutagenesis study suggests that SMC3 and SMC1 are essential to the parasite during the intraerythrocytic developmental cycle (Zhang et al. Science, 2018). This is why we chose an inducible knockdown system.

*Reviewer #1 (Significance (Required)):

Own opinion The authors provide a basic characterization of the cohesin component SMC3 using NGS methods to investigate chromatin binding sites and its potential influence on gene expression. *

__Response: __We respectfully disagree that our study offers only a basic characterization of SMC3. We combine IFA, mass spectrometry, and both ChIP-seq and RNA-seq of SMC3 across the entire intraerythrocytic developmental cycle to provide the most detailed and comprehensive functional analysis of SMC3 in P. falciparum to date.

The localisation of SMC3 at centromers as described previously (Batugedara 2020) was confirmed. However, the dynamic binding to other regions in the genome, potentially mediated by other proteins, could not be resolved unequivocal with only one replicate of ChIPseq per time point.

__Response: __With regard to the replicates for ChIP-seq, please see our response to this same point above.

Similarly, the RNAseq data demonstrate the relevance of SMC3 for gene expression, but no clear picture of a regulatory mechanism can be drawn at his point. Lacking information about the mode of binding as well as the setup of transcriptome analysis (only two time-shifted sampling points after simultaneous glmS treatment for 96h resulting in incomplete knockdown) cannot definitely elucidate, if SMC3/cohesin is a chromatin factor that affects transcription of genes in general or a specific repressor of stage-specific genes. __Response: __We agree that we have not established a regulatory mechanism for how SMC3 achieves binding specificity. However, the combination of inducible knockdown (as SMC3 is essential to the cell cycle) and differential expression analysis with ChIP-seq from the same time points across the intraerythrocytic developmental cycle is the most stringent and standard approach in the field of epigenetics for determining the direct role of a chromatin-associated protein in gene expression. We provide a detailed explanation of how the transcriptome analysis was set up in the Results (lines 229-234) and Materials and Methods (lines 715-719) section. With regard to our sampling points being “time-shifted,” we provide bioinformatic analysis (line 246-251, what is now Supp. Fig. 5B) of the RNA-seq data from untreated and glucosamine-treated parasites showing highly similar “ages” with regard to progression through the intraerythrocytic developmental cycle. While we of course also monitor progression through the cell cycle with Giemsa staining (Supp. Fig. 5A), this bioinformatic analysis is the most stringent method of determining specific times in the cell cycle.

*The work will be interesting to a general audience, interested in gene regulation and chromatin remodelling

The reviewers are experts in Plasmodium cell biology and epigenetic regulation.*

Reviewer #2

(Evidence, reproducibility and clarity (Required)):

Rosa et al, Review Commons The manuscript by Rosa et al. addresses the function of the cohesion subunit Smc3 in gene regulation during the asexual life cycle of P. falciparum. Cohesin is a conserved protein complex involved in sister chromatin cohesion during mitosis and meiosis in eukaryotic cells. Cohesin also modulates transcription and DNA repair by mediating long range DNA interactions and regulating higher order chromatin structure in mammals and yeast. In P. falciparum, the Cohesin complex remains largely uncharacterized. In this manuscript, the authors present mass spectrometry data from co-IPs showing that Smc3 interacts with Smc1 and a putative Rad21 orthologue (Pf3D7_1440100, consistent with published data from Batugedara et al and Hilliers et al), as well as a putative STAG domain protein orthologue (PF3D7_1456500). Smc3 protein appears to be most abundant in schizonts, but ChIPseq indicates predominant enrichment of Smc3 in centromers in ring and trophozoite stages. In addition, Smc3 dynamically binds with low abundance to other loci across the genome; however, the enrichment is rather marginal and only a single replicate was conducted for each time point making the data interpretation difficult. Conditional knock-down using a GlmS ribozyme approach indicates that parasites with reduced levels of Smc3 have a mild growth advantage, which is only evident after five asexual replication cycles and which the authors attribute to the transcriptional upregulation of invasion-linked genes following Smc3 KD. Indeed, Smc3 seems to be more enriched upstream of genes that are upregulated after Smc3 KD in rings than in downregulated genes, indicating that Smc3/cohesin may have a function in supressing transcription of these schizont specific genes until they are needed. The manuscript is concise and very well written, however it suffers from the lack of experimental replicates for ChIP experiments and a better characterization of the phenotype of conditional KD parasites. * Major comments • In the mass spectrometry analysis, many seemingly irrelevant proteins are identified at similar abundance to the putative rad21 and ssc3 orthologues, and therefore the association with the cohesion complex seems to be based mostly on analogy to other species rather than statistical significance. Hence, it would be really nice to see a validation of the novel STAG domain and Rad21 proteins, for example by Co-IP using double transgenic parasites.*

__Response: __While our IP-MS data did not yield high numbers of peptides, the top most enriched proteins were SMC3 and SMC1. As we state on line 157, two previous studies have already shown a robust interaction between SMC1, SMC3, and RAD21 in Plasmodium, supporting the existence of a conserved cohesin complex. While the identification of the STAG domain-containing protein is interesting, the purpose of our IP-MS was less about redefining the cohesin complex in P. falciparum and more about confirming that the epitope-tagged SMC3 we generated was incorporated correctly into the cohesin complex and was specifically immunoprecipitated by the antibody we later use for western blot, immunofluorescence, and ChIP-seq analyses. However, to validate the results of ours and others’ mass spectrometry results, we generated two new parasite strains – SMC1-3HA-dd and STAG-3HA-dd – and an antibody against SMC3 (see what is now Supp. Fig. 1). We performed co-IP and western blot analysis with these strains and show an interaction between SMC1 and SMC3 and STAG and SMC3 (see what is now Supp. Fig. 2). This information has been added to the manuscript on lines 162-167.

• *The ChIPseq analysis presented here is based on single replicates for each of the three time points. The significance cutoffs for the peaks are rather high (q __Response: __In our experience, a significance cutoff of FDR As we regularly perform ChIP-seq experiments in the lab, we have generated multiple negative control datasets. In our opinion, the most stringent negative control for an HA-tagged protein is performing ChIP with an HA antibody in a WT strain. We have recently published an in-depth analysis of this (and other) negative ChIP-seq controls (Baumgarten & Bryant, 2022, https://doi.org/10.12688/openreseurope.14836.2). We show in this publication that non-specific ChIP-seq experiments (such as negative controls) result in an over-representation of HP1-heterochromatinized regions due to differences in sonication efficiency of heterochromatin and technical challenges with mapping regions with high levels of homology. In the anti-HA in WT ChIP negative control (performed at 12hpi), we do not see any enrichment at centromeric regions, but rather at heterochromatinized regions where clonally variant gene families are located. We performed peak calling analysis and found no significant overlap between the negative control ChIP-seq and the SMC3-3HA ChIP-seq data at 12hpi.

In addition, we have now performed a second biological replicate of the SMC3-3HA ChIP-seq with a different clone at all time points. We compared this data to that from the original clone and found significant overlap of the peaks called (see what is now Table 4 and Supp. Fig. 3A). We generated a stringent list of peaks that were shared between both clones at each time point and repeated all downstream analyses (see what are now Tables 5-8). We found that our conclusions were largely unchanged. Text describing these experiments and analyses have been added throughout the results section.

The SMC3 ChIP from Batugedara et al., 2020 was performed with an in-house generated antibody (not a commercially available, widely validated antibody as we use) at a single time point in the IDC: trophozoites. Batugedara et al. performed one replicate and did not have an input sample for normalization. Rather, it seems that they incubated beads, which were not bound by antibody or IgG, with their chromatin and used any sequenced reads from this beads sample to subtract from their SMC3 ChIP signal as means of normalization. According to ENCODE ChIP-seq standards, this is not a standard nor stringent way of performing ChIP-seq and the subsequent analysis. Because they did not generate a dataset for their ChIP input, it is not possible to call peaks as we do in our study and compare those peaks with ours.

• The authors argue that during schizogony, cohesin may no longer be required at centromers, explaining the low ChIPsignal at this stage (Line 301). However, during schizogony parasites undergo repeated rounds of DNA replication (S-phase) and mitosis (M-phase) to generate multinucleated parasites; and concentrated spots of Smc3 are observed in each nucleus in schizonts by IFA. In turn, the strong presence of Smc3 at centromers in ring stage parasites is surprising, particularly since the Western Blot in Figure 1D shows most expression of Smc3 in schizonts and least in rings; and Smc3 is undetectable in rings by IFA. Yet, the ChIP signal shows very strong enrichment at centromers, long before S phase produces sister chromatids. What could be the reason for this discrepancy? Again, ChIP replicates and controls would be helpful in distinguishing technical problems with the ChIP from biologically relevant differences. __Response: __We discuss in lines 337-342 not that cohesin is no longer required at centromeres during schizogony, but that its removal from centromeres may be required specifically for separation of sister chromatids, as is seen in other eukaryotes. We also discuss that the unique asynchronous mitosis in Plasmodium may lead to a mixed population of parasites at the time point sampled where there may be some centromeres with SMC3 present and some where it is absent to promote sister chromatid separation. Even though SMC3 may be evicted from centromeres to promote sister chromatid separation, it is likely re-loaded onto centromeres once this process is complete. This is most likely why we see foci of SMC3 in each nucleus of mature schizonts by IFA. With regard to the discrepancy between SMC3 levels in rings seen in total nuclear extracts (by western blot) and at centromeres (by ChIP-seq): the total level of a protein in the nucleus does not necessarily dictate the genome-wide binding pattern or the level of enrichment of that protein at specific loci in the genome. Moreover, if one molecule of SMC3 binds to each centromere, 14 molecules would be needed in a ring stage parasite while over 500 would be needed in a schizont (assuming that there are ~36 merozoites present). SMC3 binds to centromeres in interphase cells in other eukaryotes as well, and we speculate that this binding may play a role in the nuclear organization of centromeres, as we discuss starting on line 333.

• It is surprising that a conserved protein like Smc3 shows such a subtle phenotype, given that it is predicted to be essential and its orthologues have a function in mitosis. Generally, only limited data are presented to characterize the Smc3 KD parasites, and more detail should be included. For example validation of the parasite line using a PCR screen for integration and absence of wt, parasite morphology after KD, and/or analysis of the KD parasites for cell cycle status. __Response: __First, we have repeated our growth curve analysis several times and with more clones and have concluded that there is not a significant growth phenotype in SMC3 KD parasites (see what is now Supp. Fig. 4B). As we discuss on line 342, very little intact cohesin complex seems to be required for normal growth and mitosis in S. cerevisiae and D. melanogaster, which is probably why we do not see an obvious growth or morphological phenotype. Because we could not generate SMC3 knockout parasites, there may be just enough SMC3 left to perform its vital function in our KD strain. We have added PCR data to demonstrate integration of the 3HA tag- and glmS ribozyme-encoding sequence in the clonal strains we are using for all experiments (see what is now Supp. Fig. 1A). Sanger sequencing was performed on these PCR products to confirm correct sequences. We also added images of Giemsa-stained parasites in untreated and glucosamine-treated parasites at all time points to demonstrate a lack of an obvious morphological phenotype in SMC3 KD parasites (see what is now Supp. Fig. 5A).

• Synchronization was performed at the beginning of the growth time course, which would be expected to result in a stepwise increase in parasitemia every 48 hours; however, the parasitemia according to Fig. 4F rises steadily, which would indicate that the parasites are actually not very synchronous. __Response: __We did indeed tightly synchronize these parasites and hope that the stepwise increase in parasitemia is seen better in our new growth curve analysis (see what is now Supp. Fig. 4B).

• The question of whether Smc3 causes a shorter parasite life cycle (quicker progression) or more invasion is important and could be experimentally addressed by purifying synchronous schizont stage parasites and determining their invasion rates as well as morphological examination of the Giemsa smears over the time course. __Response: __We have repeated our growth curve analysis several times and with more clones and have concluded that there is not a significant growth phenotype in SMC3 KD parasites (see what is now Supp. Fig. 4B).

• Please also compare Smc3 transcriptional levels in transgenic parasites to those in wt parasites to rule out that the genetic modification has lead to artificial upregulation of Smc3 transcription. __Response: __We have added this data to what is now Supp. Fig. 4C, showing that there is no significant difference in SMC3 transcript levels between WT and SMC3-3HA-glmS strains. We have added this information to the text of the manuscript (Line 243). As we also generated an SMC3 antibody, we could demonstrate that there is no appreciable difference in SMC3 protein levels between WT and SMC3-3HA-glmS strains (see what is now Supp. Fig. 1D).

• According to Figure S2, even more genes were deregulated at the 12 hpi time point in the WT parasites than in Smc3 parasites, and even to a much higher extent. What "transcriptional age" did the WT control parasites have at each time point? __Response: __We have now included the transcriptional age of all strains, replicates, and treatments in what is now Supp. Fig. 5B. At the 12 hpi time point in particular, regardless of glucosamine treatment, the SMC3-3HA-glmS and WT parasites were highly synchronous. The only large discrepancy we see in transcriptional age is between untreated and glucosamine-treated WT parasites at 36 hpi, which is why we did not include this time point in our transcriptional analysis. We were also surprised by the number of genes that were de-regulated with simple glucosamine treatment. The glmS system of inducible knockdown is widely used in P. falciparum; however, to our knowledge, no lab has investigated whether glucosamine treatment affects transcription in wildtype cells over the course of the IDC. Thus, for accurate phenotypic characterization of any protein with this system with regard to transcriptomics, we thought it was important to provide an RNA-seq dataset to define the cohort of genes affected by glucosamine treatment in WT parasites. We hope that our study will demonstrate the importance of using stringent controls when using inducible knockdown systems.

• A negative correlation with transcription is well established in S. cerevisiae, particularly at inducible genes. How does Smc3 enrichment generally look like for genes that show maximal expression at each of the time point? __Response: __We have performed a metagene analysis of SMC3 enrichment at all genes at each respective time point, which we divided into quartiles of expression based on their FPKM values in the RNA-seq data from the corresponding time point in untreated SMC3-3HA-glmS parasites. This quartile analysis considers all genes, including genes that are not transcribed at all and regardless of whether a gene has a significant SMC3 peak or is differentially expressed upon SMC3 knockdown. At the 12 hpi time point, we do see an inverse correlation between SMC3 enrichment and gene transcription level, but this enrichment is most pronounced across genes bodies. We see the highest SMC3 enrichment at genes in the 4th (lowest) quartile category. For the other two time points, we do not see any obvious pattern of SMC3 enrichment with regard to transcriptional status.

• Line 590: according to the methods, a 36 hpi KD time point was also harvested. Why are the data not shown/analysed? __Response: __To be clear, we are most interested in the transcriptional role of SMC3 during interphase, where results are not confounded by its potential role in mitosis. However, we did collect a 36hpi time point in the SMC3-3HA-glmS and WT strain, with and without glucosamine. We have added this last time point and the WT data from the other two time points to the manuscript (see Tables 11-13). Unfortunately, and for reasons unknown, the WT replicates treated with glucosamine showed a significantly advanced “transcriptional age” compared to the other replicates at 36hpi (see what is now Supp. Fig. 5B). Thus, we did not feel comfortable performing the RNA-seq analysis as we did with the other two time points (i.e. subtracting up- and down-regulated genes from the WT control from the SMC3-3HA-glmS data sets). We have added this information to the results section (Lines 256 and 261). As the WT parasites treated with glucosamine were approximately 8 hours in advance of the untreated WT parasites for the 36hpi time point, any up- and down-regulated genes might have been due to differences in the cell cycle rather than due to glucosamine treatment. The glmS system of inducible knockdown is widely used in P. falciparum; however, to our knowledge, no lab has investigated whether glucosamine treatment affects transcription in wildtype cells over the course of the IDC. Thus, for accurate phenotypic characterization of any protein with this system with regard to transcriptomics, we thought it was important to provide an RNA-seq dataset to define the cohort of genes affected by glucosamine treatment in WT parasites. We hope that our study will demonstrate the importance of using stringent controls when using inducible knockdown systems.

Minor Comments • Line 103/104: the hinge domain and ATPase head domain are mentioned, please annotate these in Figure 1A.

__Response: __We have annotated the hinge and ATPase domains.

• Figure 1D: the kDa scale is missing from the H3 WB. __Response: __We have added a kDa scale.

• What is the scale indicated by different colors in Fig. 2A? __Response: __The different colors (blue, coral, and green) only represent the 12, 24, and 36hpi time points, respectively. This color scheme is used throughout the manuscript. If the reviewer is referring to the color gradation within each circos plot, this does not indicate a specific scale. The maximum y-axis value for all circos plots is 24, as indicated in the figure legend.

• Line 189: it would also be interesting how many peaks are "conserved" between the different time points studied, so not only to compare the gene lists of closest genes but also the intersecting peaks and then the closest genes to the intersecting peaks. __Response: __We have added this information in Table 7 and in the manuscript starting on Line 203. Using the new dataset of consensus peaks between two replicates, there were 88 genes associated with an SMC3 peak across all three time points, most of which were close to a centromeric region.

• What is the distribution of the peaks over diverse genetic elements, such as gene bodies, introns, convergent/ divergent/ tandem intergenic regions? In yeast, cohesion is particularly enriched in convergent intergenic regions, so it would be interesting to see how this behaves in P. falciparum. __Response: __We would have liked to define how many peaks were in intergenic versus genic regions of the genome, but the dataset of “genes” from PlasmoDB includes UTRs. Thus, we would need a better annotation of the genome to perform this analysis. Regardless, we calculated the average SMC3 peak enrichment (shared between both replicates) in intergenic regions between convergent and divergent genes (see what is now Supp. Fig. 3B and Table 6). As we now state in the manuscript on line 198, we see a slight enrichment in regions between convergent genes at all time points, but the differences were not significant.

• Line 130 intra-chromosomal interactions (word missing) __Response: __Thank you for pointing this out. We have corrected this.

• Contrary to Figure 1D, the WB in Figure 3A indicates strong expression of Smc3 in rings. Please comment on this discrepancy. __Response: __While extracts from all time points were run on the same western blot in Fig. 1D and thus developed for the same amount of time, this was not the case for Fig. 3A. In Fig. 3A, the samples were run on different blots and exposed for different times, so while we can compare SMC3-HA levels between – and + glucosamine for each time point, the levels at 12 hpi cannot be quantitatively compared to those at 24 or 36hpi.

• What time point after glucosamine addition represents the WB in Fig. 3A? __Response: __The “12hpi” parasites were sampled approximately 108 hours post glucosamine addition and the “24hpi” parasites sampled approximately 120 hours post glucosamine addition. Basically, the parasites were treated with glucosamine for 96 hours, synchronized, and then harvested 12 and 24 hours later.

• Line 233 / Suppl Figure 3: Isn't it a bit concerning that the untreated control parasites at 24 hpi statistically corresponded to 18-19 hpi? And to what timepoint did the wt parasites correspond? __Response: __We are not concerned by this, and we have included the WT parasites in what is now Supp. Fig. 5B for better comparison. In the analysis presented in Supp. Fig. 5B, regardless of glucosamine presence or absence, the differences among replicates and strains at 12 and 24hpi are, in our opinion, minimal, amounting to one or two hours of the 48-hour IDC. In our extensive experience with RNA-seq across the P. falciparum lDC, this synchronization is extremely tight. As we describe on line 430 of the Materials and Methods, there is a ±3 hour window in our synchronization method, meaning that parasites harvested at 24hpi could be anywhere from 21-27hpi. In addition, the dataset that was used for comparison (from Bozdech et al., 2003) was generated in 2003 in a different laboratory using different strains with microarray. While comparing more recent RNA-seq data to this classic study has become well-established practice and is useful for comparing transcriptional age between replicates and strains, it is inevitable that the calculated “hpi” from (Bozdech et al., 2003) will differ somewhat from our experimental “hpi”. We have indeed seen this small discrepancy in predicted transcriptional age in several of our RNA-seq datasets (unrelated to this study) from trophozoites harvested at 24hpi.

• Line 264: "whether naturally or via knockdown" - the meaning of this sentence is not entirely clear __Response: __We are referring to depletion of SMC3 at promoters, either naturally (i.e. lack of binding at the promoter at 36hpi that is not the result of SMC3 knockdown, as we show in Fig. 4B) or via SMC3 knockdown, which is not natural but artificial.

• Figure 4 Legend: A, B, C etc. are mixed up. Response: Thank you for pointing this out. We have corrected this.

• Figure 4D: the differences seem to be marginally significant, even not significant at all (q=0.8) for gap45 at 12hpi. __Response: __If one defines a significance cutoff of q = 0.05 (as is common practice in differential expression analyses), then the differences are significant. For a small minority of invasion genes (such as gap45), we do observe significance at either 12 hpi or 24 hpi, but not both. Thus, we have removed the word “significant” from the descriptions of each dataset in Tab 1 of what is now Table 18. however, we do not believe that this rules out a role for SMC3 at such a gene during interphase. What is now Table 18 offers a longer list of invasion-related genes, most of which are more “significantly” affected than rap2 and gap45.

• Figure 4F shows FACS data using SYBR green as a DNA stain. The authors could exploit this data to look at the relative DNA content per cell as a measure of parasite stage, since more mature parasites will have more DNA (mean fluorescence intensity). How did the corresponding parasite cultures look in Giemsa smears? Response: We have repeated our growth curve analysis several times and with more clones and have concluded that there is not a significant growth phenotype in SMC3 KD parasites (see what is now Supp. Fig. 4B). We have added images of Giemsa-stained parasites in untreated and glucosamine-treated parasites at all time points to demonstrate a lack of an obvious morphological phenotype in SMC3 KD parasites (see what is now Supp. Fig. 5A).

• Are RNAseq replicates biological replicates from independent experiments or technical replicates? __Response: __RNA-seq replicates are technical replicates from the same parasite clone.

• Why does the number of genes analysed for differential gene expression differ between the comparisons? __Response: __If the reviewer is referring to the discrepancy between the total number of genes for different time points [for example, between what is now Table 9 (12hpi) and Table 10 (24hpi)], this is because in the RNA-seq/differential expression analysis, there have to be reads mapping back to a gene in order for that gene to be included in the analysis. Thus, if a gene is not transcribed at a given time point in the treated or untreated samples, it will not be included in the analysis. Gene transcription fluctuates significantly over the course of the IDC, so different time points will have different total numbers of transcribed genes.

• Line 372: Do you mean the proteins or the genes? AP2-I has a peak at 24 hpi and 36 hpi, and its interacting AP2 factor Pf3D7_0613800 at all time points. __Response: __We are referring to the genes. With the new ChIP-seq analysis including the second replicate, there are no consensus SMC3 peaks associated with ap2-I, bdp1, or Pf3D7_0613800 (see what is now Table 7).

• Line 480: no aldolase was shown. __Response: __We have removed this sentence.

• Line 838: include GO analysis in methods __Response: __We have added this.

Reviewer #2 (Significance (Required)): The paper addresses the function of the cohesin complex in gene regulation of malaria parasites for the first time. Due to the conserved nature of the complex, the data may be interesting for a broad audience of scientists interested in nuclear biology and cell division/ gene regulation.

Reviewer #3

(Evidence, reproducibility and clarity (Required)):

*Summary:

In the presented manuscript by Rosa et al. the authors investigate the longstanding question of how P. falciparum achieves the tight transcriptional regulation of its genome despite the apparent absence of many canonical sequence specific transcription factor families found in other eukaryotes. To do this the authors investigate the role of the spatial organization of the genome in this context, by performing a functional characterization of the conserved cohesion subunit SMC3 and its putative role in transcriptional regulation in P. falciparum. Using Cas9 mediated genome editing the authors generated a SMC3-3xHA-glmS parasite line, which they subsequently used to show expression of the protein over the asexual replication cycle by western blot and IFA analysis. In addition, using co-IP experiments coupled with mass spectrometry they identified the additional components of the cohesion complex also found in other eukaryotes as interaction partners of SMC3 in the parasite, thereby confirming the presence of the conserved cohesin complex in P. falciparum. By using a combination of ChIP-seq and RNA-seq experiments in SMC3 knockdown parasites the authors furthermore show that a reduction of SMC3 resulted in the up-regulation of a specific set of genes involved in invasion and egress in the early stages of the asexual replication cycle and that this up-regulation in transcription is correlated with a loss of SMC3 enrichment at these genes. From these observations the authors conclude, that SMC3 binds dynamically to a subset of genes and works as a transcriptional repressor, ensuring the timely expression of the bound genes. Overall, the presented data is intriguing, of high quality and very well presented. However, there are some points, which should be addressed to bolster the conclusions drawn by the authors.

Major points: I was not able to find the deposited datasets in the BioProject database under the given accession number. This should obviously be addressed and would have been nice to be able to have a look at these datasets also for the review process. *__Response: __We apologize for not giving the reviewers access. As the manuscript has been made available as a pre-print (which includes data accession numbers), but has not yet been published, we have not activated access to the data on the database.

*SMC3-ChIP-seq experiments:

"168 were bound by SMC3 across all three time points (Fig. 2D). However, most SMC3-bound genes showed a dynamic binding pattern, with a peak present at only one or two time points (Fig. 2B,D)."

Here it would be interesting to actually have more than one replicate of each of these ChIP-seq time points. This could provide a better idea of how "dynamic" these binding patterns actually are. Furthermore, I was missing a list of these 168 genes, which are constantly bound by SMC3. Anything special about those? What actually happens to this subset of genes in the SMC3 knockdown parasites? Do they show similar transcriptional changes?*

__Response: __We have now performed a second biological replicate of the SMC3-3HA ChIP-seq with a different clone at all time points. We compared this data to that from the original clone and found significant overlap of the peaks called (see what is now Table 4 and Supp. Fig. 3A). We generated a stringent list of peaks that were shared between both clones at each time point and repeated all downstream analyses (see what are now Tables 5-8). We found that our conclusions were largely unchanged. Text describing these experiments and analyses have been added throughout the results section. Using the new dataset of consensus peaks between two replicates, there were 88 genes associated with an SMC3 peak across all three time points (see what is now Table 7). The genes that are associated with an SMC3 peak at all time points are, in general, those closest to centromeric/pericentromeric regions and show no obvious functional relationship to each other. Out of these 88 genes, four are significantly up- or downregulated at 12 hpi and 26 are significantly up- or downregulated at 24 hpi. The most significantly downregulated of these genes in both datasets is smc3 itself.

*SMC3-knockdown experiments:

In Sup. Fig. 1 there is a double band in the HA-western blot in the 2nd cycle -GlcN. sample. This second band is absent in all other HA-western shown. Have the authors any idea where that second band comes from?*

__Response: __As the reviewer says, we do not see this second band in most of our western blots. It is possible that it is just a small amount of degradation in the lysate.

In Figure 3A, the WB data shown is slightly contrasting the RNA-seq quantification (3B). The knock-down on protein level seems to be stronger in the 12 hpi samples here than in the 24 hpi samples. Although the band for HA-SMC3 is stronger at the 12 hpi TP there's no band visible in the + GlcN. sample. There's however in the 24 hpi samples. Could the authors comment on this?

Response: __With regard to the discrepancy of the knockdown and protein versus RNA level, it is quite common for transcript levels to not agree with protein levels. This is why we always confirm a transcriptional knockdown with western blot analysis using appropriate loading controls. We are not sure why there is a more dramatic knockdown of SMC3 at 12hpi than at 24hpi, as these samples came from the same culture, but were simply harvested 12 hours apart. __

*"Comparison of our RNA-seq data to the time course transcriptomics data from (Painter et al., 2018) revealed that SMC3 depletion at 12 hpi caused downregulation of genes that normally reach their peak expression in the trophozoite stage (18-30 hpi), with the majority of upregulated genes normally reaching their peak expression in the schizont and very early ring stages (40-2 hpi) (Fig. 3E). At 24 hpi, a similar trend is observed, with most downregulated genes normally peaking in expression in trophozoite stage (24-32 hpi) and the majority of upregulated genes peaking in expression at very early ring stage (2 hpi) (Fig. 3F)."

I'm not fully convinced by these presented results/conclusions. This dataset would greatly benefit from the inclusion of additional later time points.*

__Response: __To be clear, we are most interested in the transcriptional role of SMC3 during interphase, where results are not confounded by its potential role in mitosis. However, we did collect a 36hpi time point in the SMC3-3HA-glmS and WT strain, with and without glucosamine. We have added this last time point and the WT data from the other two time points to the manuscript (see Tables 11-13). Unfortunately, and for reasons unknown, the WT replicates treated with glucosamine showed a significantly advanced “transcriptional age” compared to the other replicates at 36hpi (see what is now Supp. Fig. 5B). Thus, we did not feel comfortable performing the RNA-seq analysis as we did with the other two time points (i.e. subtracting up- and down-regulated genes from the WT control from the SMC3-3HA-glmS data sets). We have added this information to the results section (Lines 256 and 261). As the WT parasites treated with glucosamine were approximately 8 hours in advance of the untreated WT parasites for the 36hpi time point, any up- and down-regulated genes might have been due to differences in the cell cycle rather than due to glucosamine treatment. The glmS system of inducible knockdown is widely used in P. falciparum; however, to our knowledge, no lab has investigated whether glucosamine treatment affects transcription in wildtype cells over the course of the IDC. Thus, for accurate phenotypic characterization of any protein with this system with regard to transcriptomics, we thought it was important to provide an RNA-seq dataset to define the cohort of genes affected by glucosamine treatment in WT parasites. We hope that our study will demonstrate the importance of using stringent controls when using inducible knockdown systems.

We performed differential expression analysis of the SMC3-3HA-glmS parasites with and without glucosamine at 36hpi (we have added this data in Table 11). Again, significantly up- and down-regulated genes were not filtered using the WT dataset. With this analysis, we see only three genes from the list of invasion-related genes (Hu et al., 2010) that are up-regulated, but none of them have a significant q-value (Tab 5 of Table 18). Thus, depletion of SMC3 in late stage parasites does not lead to up-regulation of the same genes that are upregulated at 12 and 24hpi. We have added this information to the text (Line 277).

*The presented upregulation of the egress and invasion related genes is hard to pinpoint to be a direct effect of transcriptional changes due to the SMC3 knockdown. While there's a slight upregulation of these genes they still seem to be regulated in their normal overall transcriptional program as shown in Figure 4D/E. *

__Response: __We provide evidence of a direct effect of SMC3 binding by combining differential expression analysis performed upon SMC3 knockdown with SMC3 ChIP-seq at corresponding time points. As we show in what is now Fig. 4C and D, promoter accessibility of these egress/invasion genes correlates with their transcriptional activity. However, SMC3 binding to the promoters of these same genes shows inverse correlation with their transcriptional activity (what is now Fig. 4B and D). While we believe that SMC3 does contribute to the repression of these genes at specific time points during the cell cycle, it is highly likely that SMC3 is just one protein of many that regulates these genes. Moreover, and especially since we do not see a growth phenotype in the SMC3 KD, it is possible that another protein or even SMC1 could compensate for loss of SMC3 at these promoter regions. We now state these possibilities on lines 346 383 of the Discussion.

*So the changes could in theory also be explained by the differences in cell cycle progression which are present between +/- GlcN. cultures (Sup. Fig. 3). The presented normalization to the microarray data is a well-established practice to correct for this but, as presented seems to have its limitation with these parasite lines (line 233, glucosamine treated parasites harvested at 24 hpi correspond statistically to approximately 18-19 hpi (Supp. Fig. 3).) *

__Response: __In the analysis presented in what is now Supp. Fig. 5B, regardless of glucosamine presence or absence, the differences among replicates and strains at 12 and 24hpi are, in our opinion, minimal, amounting to one or two hours of the 48-hour IDC. In our extensive experience with RNA-seq across the P. falciparum lDC, this synchronization is extremely tight. As we describe on lines 416-421 of the Materials and Methods, there is a ±3 hour window in our synchronization method, meaning that parasites harvested at 24hpi could be anywhere from 21-27hpi. In addition, the dataset that was used for comparison (from Bozdech et al., 2003) was generated in 2003 in a different laboratory using different strains with microarray. While comparing more recent RNA-seq data to this classic study has become well-established practice and is useful for comparing transcriptional age between replicates and strains, it is inevitable that the calculated “hpi” from (Bozdech et al., 2003) will differ somewhat from our experimental “hpi”. We have indeed seen this small discrepancy in predicted transcriptional age in several of our RNA-seq datasets from trophozoites harvested at 24hpi.

By including additional later time points, one could actually follow the expression profiles over the whole cycle and elucidate if there's an actual transcriptional up-regulation of the genes, or if the + GlcN. parasites show a faster cell cycle progression, with a shifted peak expression timing compared to the - GlcN. parasites. __Response: __We did collect a 36hpi time point in the SMC3-3HA-glmS and WT strain, with and without glucosamine. We have added this last time point and the WT data from the other two time points to what is now Supp. Fig. 5. Unfortunately, and for reasons unknown, the WT replicates treated with glucosamine showed a significantly advanced “transcriptional age” compared to the other replicates at 36hpi. Thus, we did not feel comfortable performing the RNA-seq analysis as we did with the other two time points (i.e. subtracting up- and down-regulated genes from the WT control from the SMC3-3HA-glmS data sets). We have added this information to the results section (Lines 256 and 261). As the WT parasites treated with glucosamine were approximately 8 hours in advance of the untreated WT parasites for the 36hpi time point, any up- and down-regulated genes might have been due to differences in the cell cycle rather than due to glucosamine treatment. The glmS system of inducible knockdown is widely used in P. falciparum; however, to our knowledge, no lab has investigated whether glucosamine treatment affects transcription in wildtype cells over the course of the IDC. Thus, for accurate phenotypic characterization of any protein with this system with regard to transcriptomics, we thought it was important to provide an RNA-seq dataset to define the cohort of genes affected by glucosamine treatment in WT parasites. We hope that our study will demonstrate the importance of using stringent controls when using inducible knockdown systems.

*"These genes show SMC3 enrichment at their promoter regions at 12 and 24 hpi, but not at 36 hpi (Fig. 4C), and depletion of SMC3 resulted in upregulation at both 12 and 24 hpi (Fig. 4D). Comparison of the SMC3 ChIP-seq data with published Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data (Toenhake et al., 2018) and mRNA dynamics data (Painter et al., 2018) from similar time points in the IDC revealed that SMC3 binding at the promoter regions of these genes inversely correlates with chromatin accessibility (Fig. 4C) and their mRNA levels (Fig. 4E), which both peak in schizont stages. These data are consistent with a role of SMC3 in repressing this gene subset until their appropriate time of expression in the IDC."

The presented correlations certainly make an intriguing point towards the authors conclusion that SMC3/cohesin depletion from the promoter regions of the genes results in a de-repression of these genes and their transcriptional activation. However, the SMC3 knockdown is not complete and only up to 69% as presented on RNA level in these parasites. Therefore a control experiment which needs to be done is to actually show the loss of SMC3 from the presented activated example genes in the knockdown parasites. This could easily be done by ChIP-qPCR or even ChIP-seq, to get a global picture of the actual changes in SMC3 occupation in the knockdown parasites in correlation with changes in transcript levels. *__Response: __While SMC3-3HA-glmS knockdown is not complete at the RNA level, it is fairly robust at the protein level, especially at 12hpi (Fig. 3A).

*"These data suggest that SMC3 knockdown results in a faster progression through the cell cycle or a higher rate of egress/invasion."

The authors could greatly strengthen their conclusions by investigating this thoroughly. Pinpointing the observed phenotype to an actual increase in invasion or egress would add to the authors main conclusion that the loss of SMC3 de-regulates the timing of gene expression for these invasion related genes thereby increasing their transcript levels and thus leading to a higher rate of egress/invasion. To determine cell cycle progression simple comparisons between DNA content using a flow cytometer at timepoints together with visual inspection of Giemsa stained blood smears would give a ggod indication towards changes in cell cycle progression. In addition invasion/egress assays by counting newly invaded rings per schizont could reveal, if there are changes in the rate of egress/invasion upon SMC3 knockdown.*

Response: __We have repeated our growth curve analysis several times and with more clones and have concluded that there is not a significant growth phenotype in SMC3 KD parasites (see what is now Supp. Fig. 4B). We have added images of Giemsa-stained parasites from the knockdown time course we performed to what is now Supp. Fig. 5A. We see no obvious differences in cell morphology caused by glucosamine treatment in the WT or SMC3-3HA-glmS parasites. As we discuss on line 327, very little intact cohesin complex seems to be required for normal growth and mitosis in S. cerevisiae and D. melanogaster, which is probably why we do not see an obvious growth or morphological phenotype. We believe that SMC3 is probably only a part of a complex controlling transcription of these invasion or egress genes. Thus, the up-regulation of these genes upon SMC3 KD might not be enough to lead to a significant growth or invasion phenotype. __

*Minor points:

In the MM section on the Cas9 experiments it says dCas9 where it should be Cas9 (line 425)*

__Response: __Thank you for pointing this out. We have corrected this.

It would be great to add which HP1 antibody was used in which dilution in the IFAs to the MM section. __Response: __We have added this information to the Materials and Methods section.

In Figure 4C for the gap45 gene there's is some green peak floating around which should not be there. __Response: __Thank you for pointing this out, we have corrected it.

*Reviewer #3 (Significance (Required)):

Significance: The manuscript investigates a very timely topic by trying to uncover new molecular mechanisms of transcriptional regulation in P. falciparum. Investigating the role of the cohesin complex/SMC3 in this context provides valuable new insights to the field. While the first part with the description of the SMC3 cell line and the co-IP experiments largely confirms published data on the existence and composition of the cohesin complex in Plasmodium and its enrichment at the centromeres, the second part is especially intriguing since it investigates the molecular function of SMC3 in more detail. The results pointing to a role of SMC3/cohesin as a transcriptional repressor are of great interest to the field and will open up new concepts for future investigation.*

*Audience: The work is particularly interesting for people interested in gene regulatory processes in Plasmodium and Apicomplexan parasites in general. At the same time it also nicely points towards shared principles of gene regulation to other eukaryotes in relation to the spatial organization of the genome making the work also very interesting for a broader audience with interest in the general principles of gene regulatory processes in eukaryotic organisms.

Expertise: P. falciparum epignetics and chromatin biology / gene regulation / Cas9 gene editing*

CROSS-CONSULTATION COMMENTS

All reviewers agree that the paper addresses an important topic and provides convincing evidence for enrichment of the cohesin component Smc3 at P. falciparum centromers. In contrast, evidence for a function of Smc3 as a transcriptional repressor of genes in the first part of the parasite life cycle is less well supported. All reviewers agree that the statistical significance of the ChIP experiments needs to be impoved by including biological replicates. In addition, the phenotype of the conditional knock-down should be analysed in more detail by clarifying whether faster cell cycle progression or higher invasion rate are responsible for the observed growth adavantage. Inclusion of transcriptional data from a later time point in addition to the presented data for 12 hpi and 24 hpi was also requested by all reviewers. Finally, several inconsistencies require clarification.

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

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Referee #2

Evidence, reproducibility and clarity

Rosa et al, Review Commons

The manuscript by Rosa et al. addresses the function of the cohesion subunit Smc3 in gene regulation during the asexual life cycle of P. falciparum. Cohesin is a conserved protein complex involved in sister chromatin cohesion during mitosis and meiosis in eukaryotic cells. Cohesin also modulates transcription and DNA repair by mediating long range DNA interactions and regulating higher order chromatin structure in mammals and yeast. In P. falciparum, the Cohesin complex remains largely uncharacterized. In this manuscript, the authors present mass spectrometry data from co-IPs showing that Smc3 interacts with Smc1 and a putative Rad21 orthologue (Pf3D7_1440100, consistent with published data from Batugedara et al and Hilliers et al), as well as a putative STAG domain protein orthologue (PF3D7_1456500). Smc3 protein appears to be most abundant in schizonts, but ChIPseq indicates predominant enrichment of Smc3 in centromers in ring and trophozoite stages. In addition, Smc3 dynamically binds with low abundance to other loci across the genome; however, the enrichment is rather marginal and only a single replicate was conducted for each time point making the data interpretation difficult. Conditional knock-down using a GlmS ribozyme approach indicates that parasites with reduced levels of Smc3 have a mild growth advantage, which is only evident after five asexual replication cycles and which the authors attribute to the transcriptional upregulation of invasion-linked genes following Smc3 KD. Indeed, Smc3 seems to be more enriched upstream of genes that are upregulated after Smc3 KD in rings than in downregulated genes, indicating that Smc3/cohesin may have a function in supressing transcription of these schizont specific genes until they are needed. The manuscript is concise and very well written, however it suffers from the lack of experimental replicates for ChIP experiments and a better characterization of the phenotype of conditional KD parasites.

Major comments

• In the mass spectrometry analysis, many seemingly irrelevant proteins are identified at similar abundance to the putative rad21 and ssc3 orthologues, and therefore the association with the cohesion complex seems to be based mostly on analogy to other species rather than statistical significance. Hence, it would be really nice to see a validation of the novel STAG domain and Rad21 proteins, for example by Co-IP using double transgenic parasites.
• The ChIPseq analysis presented here is based on single replicates for each of the three time points. The significance cutoffs for the peaks are rather high (q < 0.05). Therefore, the relevance of the marginally enriched dynamic peaks (average relative enrichment of <1.2 fold for genes upregulated in rings 12 hpi in Figure 4A and B) does not appear to be very robust. Even in ChIPseq experiments using non-immune IgG, hundreds of peaks are usually called with MACS2 with a similar magnitude. So, to substantiate the data for extra-centromeric peaks convincingly, replicates and more stringent statistics are necessary. In addition, the authors should also compare their data to published PfSmc3 ChIP data from Batugedara et al 2020 (GSE116219).
• The authors argue that during schizogony, cohesin may no longer be required at centromers, explaining the low ChIPsignal at this stage (Line 301). However, during schizogony parasites undergo repeated rounds of DNA replication (S-phase) and mitosis (M-phase) to generate multinucleated parasites; and concentrated spots of Smc3 are observed in each nucleus in schizonts by IFA. In turn, the strong presence of Smc3 at centromers in ring stage parasites is surprising, particularly since the Western Blot in Figure 1D shows most expression of Smc3 in schizonts and least in rings; and Smc3 is undetectable in rings by IFA. Yet, the ChIP signal shows very strong enrichment at centromers, long before S phase produces sister chromatids. What could be the reason for this discrepancy? Again, ChIP replicates and controls would be helpful in distinguishing technical problems with the ChIP from biologically relevant differences.
• It is surprising that a conserved protein like Smc3 shows such a subtle phenotype, given that it is predicted to be essential and its orthologues have a function in mitosis. Generally, only limited data are presented to characterize the Smc3 KD parasites, and more detail should be included. For example validation of the parasite line using a PCR screen for integration and absence of wt, parasite morphology after KD, and/or analysis of the KD parasites for cell cycle status.
• Synchronization was performed at the beginning of the growth time course, which would be expected to result in a stepwise increase in parasitemia every 48 hours; however, the parasitemia according to Fig. 4F rises steadily, which would indicate that the parasites are actually not very synchronous.
• The question of whether Smc3 causes a shorter parasite life cycle (quicker progression) or more invasion is important and could be experimentally addressed by purifying synchronous schizont stage parasites and determining their invasion rates as well as morphological examination of the Giemsa smears over the time course.
• Please also compare Smc3 transcriptional levels in transgenic parasites to those in wt parasites to rule out that the genetic modification has lead to artificial upregulation of Smc3 transcription.
• According to Figure S2, even more genes were deregulated at the 12 hpi time point in the WT parasites than in Smc3 parasites, and even to a much higher extent. What "transcriptional age" did the WT control parasites have at each time point?
• A negative correlation with transcription is well established in S. cerevisiae, particularly at inducible genes. How does Smc3 enrichment generally look like for genes that show maximal expression at each of the time point?
• Line 590: according to the methods, a 36 hpi KD time point was also harvested. Why are the data not shown/analysed?

Minor Comments

• Line 103/104: the hinge domain and ATPase head domain are mentioned, please annotate these in Figure 1A.
• Figure 1D: the kDa scale is missing from the H3 WB.
• What is the scale indicated by different colors in Fig. 2A?
• Line 189: it would also be interesting how many peaks are "conserved" between the different time points studied, so not only to compare the gene lists of closest genes but also the intersecting peaks and then the closest genes to the intersecting peaks.
• What is the distribution of the peaks over diverse genetic elements, such as gene bodies, introns, convergent/ divergent/ tandem intergenic regions? In yeast, cohesion is particularly enriched in convergent intergenic regions, so it would be interesting to see how this behaves in P. falciparum.
• Line 130 intra-chromosomal interactions (word missing)
• Contrary to Figure 1D, the WB in Figure 3A indicates strong expression of Smc3 in rings. Please comment on this discrepancy.
• What time point after glucosamine addition represents the WB in Fig. 3A?
• Line 233 / Suppl Figure 3: Isn't it a bit concerning that the untreated control parasites at 24 hpi statistically corresponded to 18-19 hpi? And to what timepoint did the wt parasites correspond?
• Line 264: "whether naturally or via knockdown" - the meaning of this sentence is not entirely clear
• Figure 4 Legend: A, B, C etc. are mixed up.
• Figure 4D: the differences seem to be marginally significant, even not significant at all (q=0.8) for gap45 at 12hpi.
• Figure 4F shows FACS data using SYBR green as a DNA stain. The authors could exploit this data to look at the relative DNA content per cell as a measure of parasite stage, since more mature parasites will have more DNA (mean fluorescence intensity). How did the corresponding parasite cultures look in Giemsa smears?
• Are RNAseq replicates biological replicates from independent experiments or technical replicates?
• Why does the number of genes analysed for differential gene expression differ between the comparisons?
• Line 372: Do you mean the proteins or the genes? AP2-I has a peak at 24 hpi and 36 hpi, and its interacting AP2 factor Pf3D7_0613800 at all time points.
• Line 480: no aldolase was shown.
• Line 838: include GO analysis in methods

Referees cross-commenting

All reviewers agree that the paper addresses an important topic and provides convincing evidence for enrichment of the cohesin component Smc3 at P. falciparum centromers. In contrast, evidence for a function of Smc3 as a transcriptional repressor of genes in the first part of the parasite life cycle is less well supported. All reviewers agree that the statistical significance of the ChIP experiments needs to be impoved by including biological replicates. In addition, the phenotype of the conditional knock-down should be analysed in more detail by clarifying whether faster cell cycle progression or higher invasion rate are responsible for the observed growth adavantage. Inclusion of transcriptional data from a later time point in addition to the presented data for 12 hpi and 24 hpi was also requested by all reviewers. Finally, several inconsistencies require clarification.

Significance

The paper addresses the function of the cohesin complex in gene regulation of malaria parasites for the first time. Due to the conserved nature of the complex, the data may be interesting for a broad audience of scientists interested in nuclear biology and cell division/ gene regulation.

Passive aggressive parenting can really be traumatizing. It is a shame tactic

trying so hard to feed herself a fake situation and a fake love to try to survive her situation, this happens way to often to people in toxic relationships.

He wanted that baby so much I'm so sad they didn't have a kid and the ghost of one just remains, echoing in his head.

She is trying to convince her self that he is a good man or probably even more difficult- that she didn't make a terrible decision. He is clearly an angry, abusive man.

More of the "be a good woman" theme, stand by your man regardless

A direct humanist rant towards Christianity

Twyla mentions the movie "The Wizard of Oz" Now this could just simply be a fun movie to enjoy but what is its plot. Dorothy makes friends with a scarecrow, lion, and the tin man. A group of oddballs perhaps, just like how Twyla and Roberta must've looked when the other kids saw them together. Even decided to give them the nickname salt and pepper because of the color of the different color of their skin. Hell even Twylas mother Mary would not be too fond of the girl's being roommates as Twlya mentions to herself.

"The state of being “in love” is clearly fueled more by one’s imagination than by other person’s reality"

I totally agree with this since I've seen it happen in real life. For example when you have a crush or you like someone, then when you actually get to know them you realize that the personality you've created for them in your head is totally different from their real personality.

Conversation Hey, JB, I played a pickup game at the Rec today. At first, the older guys laughed and wouldn’t let me in unless I could hit from half-court . . . Of course, I did. All net. I wait for JB to say something, but he just smiles, his eyes all moony. I showed them guys how the Bells ball. I scored fourteen points. They told me I should try out for junior varsity next year ’cause I got hops . . . JB, are you listening? JB nods, his fingers tapping away on the computer, chatting probably with Miss Sweet Tea. I told the big guys about you, too. They said we could come back and run with them anytime. What do you think about that? HELLO—Earth to JB? Even though I know he hears me, the only thing JB is listening to is the sound of his heart bouncing on the court of love.

Conversation Dad, this girl is making Jordan act weird. He’s here, but he’s not. He’s always smiling. His eyes get all spacey whenever she’s around, and sometimes when she’s not. He wears your cologne. He’s always texting her. He even wore loafers to school. Dad, you gotta do something. Dad does something. He laughs. Filthy, talking to your brother right now would be like pushing water uphill with a rake, son. This isn’t funny, Dad. Say something to him. Please. Filthy, if some girl done locked up JB, he’s going to jail. Now let’s go get some doughnuts.

Basketball Rule #5 When you stop playing your game you’ve already lost.

Showoff UP by sixteen with six seconds showing, JB smiles, then STRUTS side steps stutters Spins, and SI NKS a sick SLICK SLIDING SWeeeeeeeeeeT SEVEN-foot shot. What a showoff.

Out of Control Are you kidding me? Come on. Ref, open your eyes. Ray Charles could have seen that kid walked. CALL THE TRAVELING VIOLATION! You guys are TERRIBLE! Mom wasn’t at the game tonight, which meant that all night Dad was free to yell at the officials, which he did.

Mom calls me into the kitchen after we get home from beating St. Francis. Normally she wants me to sample the macaroni and cheese to make sure it’s cheesy enough, or the oven-baked fried chicken to make sure it’s not greasy and stuff, but today on the table is some gross-looking orange creamy dip with brown specks in it. A tray of pita-bread triangles is beside it. Maybe Mom is having one of her book club meetings. Sit down, she says. I sit as far away from the dip as possible. Maybe the chicken is in the oven. Where is your brother? she asks. Probably on the phone with that girl. She hands me a pita. No thanks, I say, then stand up to leave, but she gives me a look that tells me she’s not finished with me. Maybe the mac is in the oven. We’ve talked to you two about your grandfather, she says. He was a good man. I’m sorry you never got to meet him, Josh. Me too, he looked cool in his uniforms. That man was way past cool. Dad said he used to curse a lot and talk about the war. Mom’s laugh is short, then she’s serious again. I know we told you Grandpop died after a fall, but the truth is he fell because he had a stroke. He had a heart disease. Too many years of bad eating and not taking care of himself and so— What does this have to do with anything? I ask, even though I think I already know. Well, our family has a history of heart problems, she says, so we’re going to start eating better. Especially Dad. And we’re going to start tonight with some hummus and pita bread. FOR MY VICTORY DINNER? Josh, we’re going to try to lay off the fried foods and Golden Dragon. And when your dad takes you to the recreation center, no Pollard’s or Krispy Kreme afterward, understand? And I understand more than she thinks I do. But is hummus really the answer?

35–18 is the final score of game six. A local reporter asks JB and I how we got so good. Dad screams from behind us, They learned from Da Man! The crowd of parents and students behind us laughs. On the way home Dad asks if we should stop at Pollard’s. I tell him I’m not hungry, plus I have a lot of homework, even though I skipped lunch today and finished my homework during halftime.

Too Good Lately, I’ve been feeling like everything in my life is going right: I beat JB in Madden. Our team is undefeated. I scored an A+ on the vocabulary test. Plus, Mom’s away at a conference, which means so is the Assistant Principal. I am a little worried, though, because, as Coach likes to say, you can get used to things going well, but you’re never prepared for something going wrong.

I’m on Free Throw Number Twenty-Seven We take turns, switching every time we miss. JB has hit forty-one, the last twelve in a row. Filthy, keep up, man, keep up, he says. Dad laughs loud, and says, Filthy, your brother is putting on a free-throw clinic. You better— And suddenly he bowls over, a look of horror on his face, and starts coughing while clutching his chest, only no sound comes. I freeze. JB runs over to him. Dad, you okay? he asks. I still can’t move. There is a stream of sweat on Dad’s face. Maybe he’s overheating, I say. His mouth is curled up like a little tunnel. JB grabs the water hose, turns the faucet on full blast, and sprays Dad. Some of it goes in Dad’s mouth. Then I hear the sound of coughing, and Dad is no longer leaning against the car, now he’s moving toward the hose, and laughing. So is JB. Then Dad grabs the hose and sprays both of us. Now I’m laughing too, but only on the outside.

He probably just got something stuck in his throat, JB says when I ask him if he thought Dad was sick and shouldn’t we tell Mom what happened. So, when the phone rings, it’s ironic that after saying hello, he throws the phone to me, because, even though his lips are moving, JB is speechless, like he’s got something stuck in his throat.

i·ron·ic [AY-RON-IK] adjective Having a curious or humorous unexpected sequence of events marked by coincidence. As in: The fact that Vondie hates astronomy and his mom works for NASA is ironic. As in: It’s not ironic that Grandpop died in a hospital and Dad doesn’t like doctors. As in: Isn’t it ironic that showoff JB, with all his swagger, is too shy to talk to Miss Sweet Tea, so he gives me the phone?

This Is Alexis—May I Please Speak to Jordan? Identical twins are no different from everyone else, except we look and sometimes sound exactly alike.

Phone Conversation (I Sub for JB) Was that your brother? Yep, that was Josh. I’m JB. I know who you are, silly—I called you. Uh, right. You have any siblings, Alexis? Two sisters. I’m the youngest. And the prettiest. You haven’t seen them. I don’t need to. That’s sweet. Sweet as pomegranate. Okay, that was random. That’s me. Jordan, can I ask you something? Yep. Did you get my text? Uh, yeah. So, what’s your answer? Uh, my answer. I don’t know. Stop being silly, Jordan. I’m not. Then tell me your answer. Are y’all rich? I don’t know. Didn’t your dad play in the NBA? No, he played in Italy. But still, he made a lot of money, right? It’s not like we’re opulent. Who says “opulent”? I do. You never use big words like that at school . . . I have a reputation to uphold. Is he cool? Who? Your dad. Very. So, when are you gonna introduce me? Introduce you? To your parents. I’m waiting for the right moment. Which is when? Uh— So, am I your girlfriend or not? Uh, can you hold on for a second? Sure, she says. Cover the mouthpiece, JB mouths to me. I do, then whisper to him: She wants to know are you her boyfriend. And when are you gonna introduce her to Mom and Dad. What should I tell her, JB? Tell her yeah, I guess, I mean, I don’t know. I gotta pee, JB says, running out of the room, leaving me still in his shoes. Okay, I’m back, Alexis. So, what’s the verdict, Jordan? Do you want to be my girlfriend? Are you asking me to be your girl? Uh, I think so. You think so? Well, I have to go now. Yes. Yes, what? I like you. A lot. I like you, too . . . Precious. So, now I’m Precious? Everyone calls you JB. Then I guess it’s official. Text me later. Good night, Miss Sweet— What did you call me? Uh, good night, my sweetness. Good night, Precious. JB comes running out of the bathroom. What’d she say, Josh? Come on, tell me. She said she likes me a lot, I tell him. You mean she likes me a lot? he asks. Yeah . . . that’s what I meant.

JB and I eat lunch together every day, taking bites of Mom’s tuna salad on wheat between arguments: Who’s the better dunker, Blake or LeBron? Which is superior, Nike or Converse? Only today I wait at our table in the back for twenty-five minutes, texting Vondie (home sick), eating a fruit cup (alone), before I see JB strut into the cafeteria with Miss Sweet Tea holding his precious hand.

Boy walks into a room with a girl. They come over. He says, Hey, Filthy McNasty like he’s said forever, but it sounds different this time, and when he snickers, she does too, like it’s some inside joke, and my nickname, some dirty punch line.

At practice Coach says we need to work on our mental game. If we think we can beat Independence Junior High— the defending champions, the number one seed, the only other undefeated team— then we will. But instead of drills and sprints, we sit on our butts, make weird sounds— Ohmmmmmmmm Ohmmmmmmmm— and meditate. Suddenly I get this vision of JB in a hospital. I quickly open my eyes, turn around, and see him looking dead at me like he’s just seen a ghost.

Second-Person After practice, you walk home alone. This feels strange to you, because as long as you can remember there has always been a second person. On today’s long, hot mile, you bounce your basketball, but your mind is on something else. Not whether you will make the playoffs. Not homework. Not even what’s for dinner. You wonder what JB and his pink Reebok–wearing girlfriend are doing. You do not want to go to the library. But you go. Because your report on The Giver is due tomorrow. And JB has your copy. But he’s with her. Not here with you. Which is unfair. Because he doesn’t argue with you about who’s the greatest, Michael Jordan or Bill Russell, like he used to. Because JB will not eat lunch with you tomorrow or the next day, or next week. Because you are walking home by yourself and your brother owns the world.

Third Wheel You walk into the library, glance over at the music section. You look through the magazines. You even sit at a desk and pretend to study. You ask the librarian where you can find The Giver. She says something odd: Did you find your friend? Then she points upstairs. On the second floor, you pass by the computers. Kids checking their Facebook. More kids in line waiting to check their Facebook. In the Biography section you see an old man reading The Tipping Point. You walk down the last aisle, Teen Fiction, and come to the reason you’re here. You remove the book from the shelf. And there, behind the last row of books, you find the “friend” the librarian was talking about. Only she’s not your friend and she’s kissing your brother.

tip·ping point [TIH-PING POYNT] noun The point when an object shifts from one position into a new, entirely different one. As in: My dad says the tipping point of our country’s economy was housing gamblers and greedy bankers. As in: If we get one C on our report cards, I’m afraid Mom will reach her tipping point and that will be the end of basketball. As in: Today at the library, I went upstairs, walked down an aisle, pulled The Giver off the shelf, and found my tipping point.

The main reason I can’t sleep is not because of the game tomorrow tonight, is not because the stubble on my head feels like bugs are break dancing on it, is not even because I’m worried about Dad. The main reason I can’t sleep tonight is because Jordan is on the phone with Miss Sweet Tea and between the giggling and the breathing he tells her how much she’s the apple of his eye and that he wants to peel her and get under her skin and give me a break. I’m still hungry and right about now I wish I had an apple of my own.

Surprised I have it all planned out. When we walk to the game I will talk to JB man to man about how he’s spending way more time with Alexis than with me and Dad. Except when I hear the horn, I look outside my window and it’s raining and JB is jumping into a car with Miss Sweet Tea and her dad, ruining my plan.

Conversation In the car I ask Dad if going to the doctor will kill him. He tells me he doesn’t trust doctors, that my grandfather did and look where it got him: six feet under at forty-five. But Mom says your dad was really sick, I tell him, and Dad just rolls his eyes, so I try something different. I tell him that just because your teammate gets fouled on a lay-up doesn’t mean you shouldn’t ever drive to the lane again. He looks at me and laughs so loud, we almost don’t hear the flashing blues behind us.

Game Time: 6:00 p.m. At 5:28 p.m. a cop pulls us over because Dad has a broken taillight. At 5:30 the officer approaches our car and asks Dad for his driver’s license and registration. At 5:32 the team leaves the locker room and pregame warm-ups begin without me. At 5:34 Dad explains to the officer that his license is in his wallet, which is in his jacket at home. At 5:37 Dad says, Look, sir, my name is Chuck Bell, and I’m just trying to get my boy to his basketball game. At 5:47 while Coach leads the Wildcats in team prayer, I pray Dad won’t get arrested. At 5:48 the cop smiles after verifying Dad’s identity on Google, and says, You “Da Man”! At 5:50 Dad autographs a Krispy Kreme napkin for the officer and gets a warning for his broken taillight. At 6:01 we arrive at the game but on my sprint into the gym I slip and fall in the mud.

This is my second year playing for the Reggie Lewis Wildcats and I’ve started every game until tonight, when Coach tells me to go get cleaned up then find a seat on the bench. When I try to tell him it wasn’t my fault, he doesn’t want to hear about sirens and broken taillights. Josh, better an hour too soon than a minute too late, he says, turning his attention back to JB and the guys on the court, all of whom are pointing and laughing at me.

Basketball Rule #6 A great team has a good scorer with a teammate who’s on point and ready to assist.

Josh’s Play-by-Play At the beginning of the second half we’re up twenty-three to twelve. I enter the game for the first time. I’m just happy to be back on the floor. When my brother and I are on the court together this team is unstoppable, unfadeable. And, yes, undefeated. JB brings the ball up the court. Passes the ball to Vondie. He shoots it back to JB. I call for the ball. JB finds me in the corner. I know y’all think it’s time for the pick-and-roll, but I got something else in mind. I get the ball on the left side. JB is setting the pick. Here it comes— I roll to his right. The double-team is on me, leaving JB free. He’s got his hands in the air, looking for the dish from me. Dad likes to say, When Jordan Bell is open you can take his three to the bank, cash it in, ’cause it’s all money. Tonight, I’m going for broke. I see JB’s still wide open. McDonald’s drive-thru open. But I got my own plans. The double-team is still on me like feathers on a bird. Ever seen an eagle soar? So high, so fly. Me and my wings are— and that’s when I remember: MY. WINGS. ARE. GONE. Coach Hawkins is out of his seat. Dad is on his feet, screaming. JB’s screaming. The crowd’s screaming, FILTHY, PASS THE BALL! The shot clock is at 5. I dribble out of the double-team. 4 Everything comes to a head. 3I see Jordan. 2 You want it that bad? HERE YA GO! 1 . . .

Before Today, I walk into the gym covered in more dirt than a chimney. When JB screams FILTHY’S McNasty, the whole team laughs. Even Coach. Then I get benched for the entire first half. For being late. Today, I watch as we take a big lead, and JB makes four threes in a row. I hear the crowd cheer for JB, especially Dad and Mom. Then I see JB wink at Miss Sweet Tea after he hits a stupid free throw. Today, I finally get into the game at the start of the second half. JB sets a wicked pick for me just like Coach showed us in practice, And I get double-teamed on the roll just like we expect. Today, I watch JB get open and wave for me to pass. Instead I dribble, trying to get out of the trap, and watch as Coach and Dad scream for me to pass. Today, I plan on passing the ball to JB, but when I hear him say “FILTHY, give me the ball,” I dribble over to my brother and fire a pass so hard, it levels him, the blood from his nose still shooting long after the shotclock buzzer goes off.

Undergraduate homework question. Description from the assignment sheet:

Order the nodes 1,...,7, and order the arcs with tail node i, A(i), increasing by their head nodes. See next page for the algorithm.

The graph is at the same page. The FIFO Label-Correcting algorithm is exactly the same as Moore Bellman Ford Algorithm. Labels at the end should be: [0, -5, 15, -5, -10]

This is what you call spiraling and I definitely do it all the time

Putin is convinced that he is right

Another official points out that Putin claims that he had to start the war, as if the rules that were broken were not broken by him. Putin is paranoid, insulted, and apparently sincerely believed that he had initially put effort into building relationships with the West.

The foreign intelligence head, the Moscow mayor, the deputy Kremlin administration head, all seemed confused.

Reviewer #3 (Public Review):

This important study continues the development of normative models of neuroimaging-derived features initiated by themselves (Rutherford et al., 2022a) in two directions. First, the existing models - which were developed on structural imaging features - are complemented with features derived from functional networks. Second, these models are compared with the utilization of the features themselves in three different inference settings. Overall, the evaluation of the functional networks modeling yielded similar benchmarking metrics in agreement with their previous structural modeling. The study delivers strong evidence that normative models efficiently increased the statistical power in mass univariate group difference testing. The improvement in the other two inferential scenarios was less evident. However, normative modeling was not comparatively detrimental and should continue to be investigated.

The study showcases several major strengths:<br /> - The methodological approach is robustly supported by previous work and protocol definitions by the authors, mainly (Rutherford, 2022a; 2022b).<br /> - The intent of the manuscript is very clear, structured first with a confirmation of the soundness of their functional-networks model and second the "head-to-head" comparison (a term used in the abstract which effectively describes the aim) to alternative inference approaches.<br /> - The results of task 1 are very compelling. The other two tasks, while perhaps less robust, are definitely relevant to be part of the communication and help draw a more accurate picture of the role of normative models in years to come.<br /> - The manuscript is accompanied by a comprehensive set of tutorials, examples, documentation, and the sharing of code, models, and data. Sharing all these resources is a decisive effort toward research transparency that deserves full recognition as scientific scholarship.

As major weaknesses, I will speculate that some researchers could understand this work as incremental. Although there's continuity with the previous work of the authors (otherwise would be a weakness, in my opinion), my assessment is that the science in this manuscript should be considered new results and hence deserve independent communication.

Finally, I would like to highlight how normative modeling outperformed its "direct" (saving the removal of confounding factors) inference counterpart in task 1, providing solid evidence of the usefulness of normative models beyond the classical application in "easy" clinical decisions (I refer the readers to the manuscript, which elaborates on these aspects more appropriately and comprehensively).

Description of an Okapi

• dr chantal echen felder
• head of education and digital collection
• Stadl museum in Frankfurt
• she has been collaborating with cognitive scientists for the last years

He has publicly demonstrated his distaste for part of his older circle, e.g. when he humiliated the head of the Foreign Intelligence Service on TV.

Constant on Montesquieu: Montesquieu was observant since he knew there were differences between contemporary and ancient ideas of liberty. But, Montsquieu believed the difference was honor/virtue. M views the evolution of liberty to be differences between Republic and Monarchy, but it should really be between the spirit of ancient times vs modern times.

This is a posture or the way the body/head is being held. In this context I take it to mean the pose or any material we have once we pass does not matter after time passes

this is one scene where iago and othello are equal in importance. we see iago's presence pervade everything, every little action, there is nothing that happens that is not a direct consequence of something he has done. Othello plays a similar role here, he is not physically present but casts a shadow over the events of the scene. the fact that the hero and the villain are coming head to head here, can indicate that there is about to be an explosion of sorts- that one of them will emerge victorious. and due to the nature of the play- tragedie- we know it will be othello. this gives a foreboding air to the scene.