4,823 Matching Annotations
  1. Aug 2022
    1. 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

      Summary:

      Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).

      In this manuscript, Dominicus et al investigate the elusive role of calcium-dependent kinase 3 during the egress of Toxoplasma gondii. Multiple functions have already been proposed for this kinase by this group including the regulation of basal calcium levels (24945436) or of a tyrosine transporter (30402958). However, one of the most puzzling phenotypes of CDPK3 deficient tachyzoites is a marked delay in egress when parasites are stimulated with a calcium ionophore that is rescued with phosphodiesterase (PDE) inhibitors. Crosstalk between, cAMP, cGMP, lipid and calcium signalling has been previously described to be important in regulating egress (26933036, 23149386, 29030485) but the role of CDPK3 in Toxoplasma is still poorly understood.

      Here the authors first take an elegant phosphoproteomic approach to identify pathways differentially regulated upon treatment with either a PDE inhibitor (BIPPO) and a calcium ionophore (A23187) in WT and CDPK3-KO parasites. Not much difference is observed between BIPPO or A23187 stimulation which is interpreted by the authors as a regulation through a feed-back loop. The authors then investigate the effect of CDPK3 deletion on lipid, cGMP and cAMP levels. The identify major changes in DAG, phospholipid, FFAs, and TAG levels as well as differences in cAMP levels but not for cGMP. Chemical inhibition of PKA leads to a similar egress timing in CDPK3-KO and WT parasites upon A23187 stimulation.

      As four PDEs appeared differentially regulated in the CDPK3-KO line upon A23187, the authors investigate the requirement of the 4 PDEs in cAMP levels. They show diverse localisation of the PDEs with specificities of PDE1, 7 and 9 for cGMP and of PDE2 for cAMP. They further show that PDE1, 7 and 9 are sensitive to BIPPO. Finally, using a conditional deletion system, they show that PDE1 and 2 are important for the lytic cycle of Toxoplasma and that PDE2 shows a slightly delayed egress following A23187 stimulation.

      Major comments:

      -Are the key conclusions convincing?

      The title is supported by the findings presented in this study. However I am not sure to understand why the authors imply a positive feed back loop. This should be clarified in the discussion of the results. The phosphoproteome analysis seems very strong and will be of interest for many groups working on egress. However, the key conclusion, i.e. that a substrate overlaps between PKG and CDPK3 is unlikely to explain the CDPK3 phenotype, seems premature to me in the absence of robustly identified substrates for both kinases.

      I am not sure there is a clear key conclusion from the lipidomic analysis and how it is used by the authors to build their model up. Major changes are observed but how could this be linked with CDPK3, particularly if cGMP levels are not affected?

      The evidence that CDPK3 is involved in cAMP homeostasis seems strong. However, the analysis of PKA inhibition is a bit less clear. The way the data is presented makes it difficult to see whether the treatment is accelerating egress of CDPK3-KO parasites or affecting both WT and CDPK3-KO lines, including both the speed and extent of egress. This is important for the interpretation of the experiment.

      The biochemical characterisation of the four PDE is interesting and seems well performed. However, PDE1 was previously shown to hydrolyse both cAMP and cGMP (https://doi.org/10.1101/2021.09.21.461320) which raises some questions about the experimental set up. Could the authors possibly discuss why they do not observe similar selectivity? Could other PDEs in the immunoprecipitate mask PDE activity? In line with this question, it is not clear what % of "hydrolytic activity (%)" means and how it was calculated. The experiments describing the selectivity of BIPPO for PDE1, 7 and 9 as well as the biological requirement of the four tested PDEs are convincing.

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

      The claim that CDPK3 affects cAMP levels seems strong however the exact links between CDPK3 activity, lipid, cGMP and cAMP signalling remain unclear and it may be important to clearly state this.

      -Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

      I think that the manuscript contains a significant amount of experiments that are of interest to scientists working on Toxoplasma egress. Requesting experiments to identify the functional link between above-mentioned pathways would be out of the scope for this work although it would considerably increase the impact of this manuscript. For example, would it be possible to test whether the CDPK3-KO line is more or less sensitive to PKG specific inhibition upon A23187 induced?

      -Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      The above-mentioned experiment is not trivial as no specific inhibitors of PKG are available. Ensuring for specificity of the investigated phenotype would require the generation of a resistant line which would require significant work.

      -Are the data and the methods presented in such a way that they can be reproduced?

      It is not clear how the % of hydrolytic activity of the PDE has been calculated.

      -Are the experiments adequately replicated and statistical analysis adequate?

      This seems to be performed to high standards.

      Minor comments:

      -Specific experimental issues that are easily addressable.

      I do not have any comments related to minor experimental issues.

      -Are prior studies referenced appropriately?

      Most of the studies relevant for this work are cited. It is however not clear to me why some important players of the "PKG pathway" are not indicated in Fig 1H and Fig 3E, including for example UGO or SPARK.

      -Are the text and figures clear and accurate?

      While all the data shown here is impressive and well analysed, I find it difficult to read the manuscript and establish links between sections of the papers. The phosphoproteome analysis is interesting and is used to orientate the reader towards a feedback mechanism rather than a substrate overlap. But why do the authors later focus on PDEs and not on AC or CNBD, as in the end, if I understand well, there is no evidence showing a link between CDPK3-dependent phosphorylation and PDE activity upon A23187 stimulation? It is also unclear how the authors link CDPK3-dependent elevated cAMP levels with the elevated basal calcium levels they previously described. This is particularly difficult to reconcile particularly in a PKG independent manner.

      The presentation of the lipidomic analysis is also not really clear to me. Why do the authors show the global changes in phospholipids and not a more detailed analysis? As the authors focus on the PI-PLC pathway, could they detail the dynamics of phosphoinositides? I understand that lipid levels are affected in the mutant but I am not sure to understand how the authors interpret these massive changes in relationship with the function of CDPK3 and the observed phenotypes.

      Finally, the characterisation of the PDEs is an impressive piece of work but the functional link with CDPK3 is relatively unclear. It would also be important to clearly discuss the differences with previous results presented in this this preprint: https://doi.org/10.1101/2021.09.21.461320. My understanding is while the authors aim at investigating the role of CDPK3 in A23187 induced egress, the main finding related to CDPK3 is a defect in cAMP homeostasis that is not linked to A23187. Similarly, the requirements of PDE2 in cAMP homeostasis and egress is indirectly linked to CDPK3. Altogether I think that important results are presented here but divided into three main and distinct sections: the phosphoproteomic survey, the lipidomic and cAMP level investigation, and the characterisation of the four PDEs. However, the link between each section is relatively weak and the way the results are presented is somehow misleading or confusing.

      -Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      This is a very long manuscript written for specialists of this signalling pathway and I would suggest the authors to emphasise more the important results and also clearly state where links are still missing. This is obviously a complex pathway and one cannot elucidate it easily in a single manuscript.

      Significance

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

      This is a technically remarkable paper using a broad range of analyses performed to a high standard.

      -Place the work in the context of the existing literature (provide references, where appropriate).

      The cross-talk between cAMP, cGMP and calcium signalling is well described in Toxoplasma and related parasites. Here the authors show that, in Toxoplasma, CDPK3 is part of this complex signalling network. One of the most important finding within this context is the role of CDPK3 in cAMP homeostasis. With this in mind, I would change the last sentence of the abstract to "In summary we uncover a feedback loop that enhances signalling during egress and links CDPK3 with several signalling pathways together."

      The genetic and biochemical analyses of the four PDEs are remarkable and highlight consistencies and inconsistencies with recently published work that would be important to discuss and will be of interest for the field.

      While I understand the studied signalling pathway is complex, I think it would be important to better describe the current model of the authors. In the discussion, the authors indicate that "the published data is not currently supported by a model that fits most experimental results." I would suggest to clarify this statement and discuss whether their work helps to reunite, correct or improve previous models.

      Could the authors also speculate about a potential role of PDE/CDPK3 in host cell invasion as cAMP signalling has be shown to be important for this process (30208022 and 29030485)?

      -State what audience might be interested in and influenced by the reported findings.

      This paper is of great interest to groups working on the regulation of egress in Toxoplasma gondii and other related apicomplexan pathogens.

      -Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

      I am working on the cell biology of apicomplexan parasites.

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    1. https://cyberzettel.com/chris-aldrich-and-his-research-on-digital-public-zettelkasten/

      This looks exciting!

      You've also nudged me to convert my burgeoning broader top level tag of "note taking" into a full fledged category (https://boffosocko.com/category/note-taking/) which shortly will contain not only the material on zettelkasten but commonplace books and other related areas.

      Usually once a tag has more than a couple hundred entries, it's time to convert it to a category. This one was long overdue.

    1. Reviewer #2 (Public Review):

      These studies investigated the identity of cells that migrate in response to stroke from the stem cell niche, the subventricular zone (SVZ). They also showed that these cells are important in the repair processes following cortical ischemia as mice who had stem cells ablated or had age-associated reduced progenitor number had less improvement in a motor task. Finally, they identify the mechanism for this progenitor-driven repair as both synaptic plasticity and angiogenesis following ischemia that is driven by the production of trophic factors most notably VEGF. The major strengths of the paper are the use of multiple promoters to drive the lineage tracing fluorescent marker. In addition to the traditional NesinCre-ER mice with a tdTomato tag, they use an Ascl-1Cre-ER mice which is in fewer progenitors but is more specific to neural progenitors and not upregulated in activated astrocytes to support their findings that the majority of migrating cells are progenitors. To further support this finding they also show the majority of cells do not express the mature astrocyte marker S100beta. The neural stem cell ablation model is the well-established GFAP-TK mouse model which uses ganciclovir to ablate neural progenitors and most importantly they show that it is working for them which increases the rigor of the study. The mechanistic studies are convincing because not only do they use a cortical window and two-photon microscopy to measure changes in the synapsis and vasculature over time but they also do gain and loss of function studies to support that VEGF is a major driver of the reparative response.

    1. 会触发: channel.basicNack(tag, false, true);, 这样会告诉rabbitmq该消息消费失败, 需要重新入队

      重试次数跟max-attempts的配置有关,并且因为网络等原因,会导致重试次数高于设定次数, 例子:图中设置为2次,实际执行4次

    1. We want to tag only a portion of the image thus the motivation of the annotation must be tagging the body of the annotation must be TextualBody containing a text describing what we see in that portion of the X-Ray image, hence the format of the annotation must be text/plain.

      Split into two sentences. I think I would write it this way:

      We want to tag only a portion of the image and thus the motivation of the Annotation must be tagging. The body of the annotation must be a TextualBody — with a format of text/plain — that contains the text of our annotation.

    1. Reviewer #3 (Public Review):

      Wong et al. developed a new versatile approach with a robust signal to track protein dynamics by inserting a tag into the endogenous loci and different properties of fluorescent dyes for conjugation. Using this approach, the authors monitor the trafficking of Fluorescent dye and Halo-tagged GluA1 with time-lapse imaging and found that neuronal stimulation induces GluA1 accumulation surrounding stimulated synapses on dendritic shafts and actin polymerization at synapses and dendrites. Furthermore, combining with pharmacological manipulations of actin polymerization or myosin activity, the authors found that actin polymerization facilitates exocytosis of GluA1 near activated synapses. The new approach may provide broad impacts upon appropriate control experiments, and the practical application of this approach to GluA1 trafficking upon neuronal activation is significant. However, there are several weaknesses, including confirmation of activity of the tagged receptors and receptor specificity mimicking endogenous LTP machinery. If the receptor tagged by the new robust approach reflects endogenous machinery, this approach will provide a big opportunity to the community as a versatile method to visualize a protein not visualized previously.

    1. 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

      Reply to the reviewers

      1. General Statements

      It is the common view of all three reviewers that we have not utilized adequate in vitro/biochemical evidence to support the idea that SATB1 protein undergoes liquid-liquid phase separation. We do agree with the reviewers that our manuscript lacks biochemical evidence to support such notion. Though we find it quite interesting and we would like to suggest for the first time in the field of chromatin organization and function, based upon the action of SATB1, that this protein does exist in at least two polypeptide isoforms (764 and 795 amino acids long) which display different phase separation propensity and therefore confer different actions in regulating the (patho)physiological properties of a murine T cell.

      Every single research group that works on SATB1, considered so far only a single protein isoform, that is, the shorter isoform of 764 amino acids and no tools, such as isoform-specific antibodies have been developed to discriminate the two isoforms and thus being able to assign unique functions to each isoform. We do understand that such a report, suggesting the presence of two protein isoforms, with potentially quite diverse functions, would question (not necessarily by the authors of this manuscript, since no such comment is included in our manuscript) the conclusions drawn in the literature assigning all biochemical properties to a single, short isoform of SATB1. Moreover, all the genetically modified mice that have been analyzed so far (including our group), deleted both Satb1 isoforms. Our future research approaches should, from now on, consider unraveling the isoform-specific functions of SATB1 and their involvement in physiology and disease. This could also deem useful to explain the quite diverse, both positive and negative effects of SATB1 in transcription regulation. Another major objection of the reviewers was that we should provide cumulative supporting evidence for the existence of the long SATB1 isoform, or at least evaluate the specificity of our custom-made antibody.

      Taking under consideration the aforementioned constructive criticism of the three reviewers we would like to perform (most of the suggested experiments have already been performed) additional experiments to support our claims in the manuscript. These experiments are described below as a point-by-point reply to each point raised by the reviewers.

      In line with the aforementioned rationale, we propose the title of our manuscript to change into “Two SATB1 isoforms display different phase separation propensity”, if our manuscript is considered for publication.

      1. Description of the planned revisions

      **Reviewer #1**:

      4) Lack of in vitro reconstitution experiments with purified long and short SATB1

      **PLANNED EXPERIMENT #1**

      We do realize this shortcoming of our work. We have to note that purifying recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform these experiments if our work is considered for publication.

      This proposed experiment has also been requested by Reviewers #2 and #3.

      **Reviewer #2**:

      1. Moreover, an important and direct experiment would be to clone the long isoform in a suitable vector and overexpress in the cell line (as done for the canonical isoform in Supp Fig 1a). This would unequivocally show the efficacy of the antibody and thus the following usage of the same for various assays.

      **PLANNED EXPERIMENT #2**

      This is a great suggestion. We have cloned the long and short Satb1 cDNAs in pEGFP-C1 vector. We will transfect these plasmids in NIH 3T3 fibroblasts and we will perform Western blot analysis, utilizing the antibody raised against the extra 31 amino acids long peptide present only in the long SATB1 isoform, for the following samples: 1. NIH-3T3 whole cell protein extracts, 2. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-C1 plasmid, 3. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-long_Satb1_ plasmid and 4. protein extracts from NIH 3T3 fibroblasts transiently transfected with the pEGFP-short_Satb1_ plasmid.

      This experiment will consist another proof regarding the specificity of the antibody raised against the extra 31 amino acids long peptide present only in the long SATB1 isoform.

      **Minor comments:**

      1. On pg 6, related to Figure 1, the authors mention 'It should also be noted that when investigating the SATB1 protein levels, we have to bear in mind that the antibodies targeting the N-terminus of SATB1 protein cannot discriminate between the short and long isoforms'. The authors reason that their sizes are too close. It is indeed possible, and widely studied in biochemistry to assess various factors on protein migration (such as PTMs). The authors should validate this aspect (as it is important as per their premise) and perform separation based on charge as well and also use a commercial antibody to validate the same.

      (Experiments already performed)

      We have adapted the text so that it does not imply that the two isoforms cannot be separated by size. This part in lines 102-107 then reads: “It should also be noted that when investigating the SATB1 protein levels, we have to bear in mind that the antibodies targeting the N-terminus of SATB1 protein cannot discriminate between the short and long isoforms, thus we can only compare the amount of the long SATB1 isoform to the total SATB1 protein levels in vivo conditions. To overcome this limitation and to specifically validate the presence of the long SATB1 protein isoform in primary murine T cells, we designed a serial immunodepletion-based experiment (Fig. 1e, Supplementary Fig. 1a).”

      Moreover, in the revised version of the manuscript we now provide a number of additional proofs supporting the presence of the long isoform and also the specificity of the long isoform-specific antibody. As evident in the text cited above, in the revised Fig. 1e,f and revised Supplementary Fig. 1a,b; we present two immunodepletion experiments which should alone address the Reviewer’s concerns. Moreover, we added Supplementary Fig. 1c; demonstrating that the long isoform-specific antibody does not detect any protein in cells with conditionally depleted SATB1 (Satb1_fl/fl_Cd4-Cre+), supporting its specificity. The custom-made and publicly available antibodies targeting all SATB1 isoforms were also verified in Supplementary Fig. 1d. Moreover, the long isoform and all isoform antibodies display similar localization in the nucleus (Supplementary Fig. 1e; their co-localization based on super-resolution microscopy is also quantified in Supplementary Fig. 5a).

      In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we will provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoform antibodies.

      **PLANNED EXPERIMENT #3**

      Although we think that in the revised version of the manuscript, we have provided enough proof about the existence of the long isoform in primary murine thymocytes we would like to try the following approach as suggested by this Reviewer.

      The pI of the two SATB1 isoform is quite similar. The pI of the short SATB1 isoform is 6.09 and for the long SATB1 isoform is 6.18. We will perform 2D PAGE coupled to Western blotting utilizing the antibodies detecting the long and all SATB1 isoforms. Given the fact that both isoforms are post-translationally modified to a various degree, it will be extremely difficult to discriminate between the long and short unmodified versus the long and short post-translationally modified proteins especially in the absence of a specific antibody only for the short isoform.

      **Reviewer #3**

      1. Hexanediol is another assay frequently used in phase-separation studies. However, hexanediol has many deleterious effects on the cell, even at a fraction of the concentration normally used in phase-separation studies. Authors should show controls of cell viability, control proteins that do not phase-separate, etc. See https://www.jbc.org/article/S0021-9258(21)00027-2/fulltext.

      Secondly, hexanediol treatment should cause phase-separated protein aggregates to disperse. It is difficult to determine from the images whether or not the aggregates actually disperse or there is just less protein. In any case, small aggregates remain even after treatment, and this appears different from most other hexanediol experiments reported in the literature where the signals become more dispersed and uniform. This is likely because the samples are fixed.

      One of the main features of using hexanediol in phase-separation is to show that upon washout, LLPS aggregates can reform. Because the cells are fixed, the critical aspect of this assay is not performed. A washout and LLPS recovery would control for cell viability issues described above and would provide the opportunity to show that total SATB1 protein levels did not change, but its distribution did, which is the essence of this assay in the context of LLPS. This review from the Tjian group is very informative and may be a good resource:

      http://genesdev.cshlp.org/content/33/23-24/1619

      In line with our reply to point #1 of this Reviewer (page 26 of this document), we should again emphasize that we utilized the hexanediol treatment in primary murine developing T cells as this is the only way to investigate the properties of SATB1 speckles under physiological conditions. This also explains why some small insoluble structure remains after the hexanediol treatment. Note that under physiological conditions, there is a contribution of several protein variants (such as differential PTMs) out of which some will tend to form more stable structures while others could undergo LLPS. It is not clear how the washout experiment could be applied in the primary cell conditions that include cell fixation as the heterogeneity and big variation among cells would make such data analysis highly unreliable.

      **PLANNED EXPERIMENT #1**

      As we answered to point #4 of Reviewer 1 (page 2), we propose the following experiment. Although the purification of recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform in vitro reconstitution experiments if our work is considered for publication.

      1. The major difference between the long and short isoform of SATB1 is the 31aa segment within the IDR. However the authors find that neither the long or short isoform SATB1 forms LLPS aggregates, and the IDR alone forms aggregates in the cytoplasm (Fig5) but they do not respond to Cry2 light activation. When forced to localize to the nucleus, it does not form aggregates as well (Fig6). The short isoform also did not form any aggregates. These results seem to argue against any isoform specific phase-separation. This experiment seems critical for the story, yet it does not support their overall conclusions. The authors might consider using a different cell line or perhaps do an in vitro assay using purified protein.

      I am not certain what to make of the cytoplasmic aggregation, which appears to not form upon localization to the nucleus. Because of this, it is difficult to place weight on the significance of the S635A mutation and the role that a phosphorylation of SATB1 contributes to phase-separation, let alone function There are many additional points of concern, but the ones listed above are perhaps the most significant in terms of the overall conclusions of the paper.

      In Fig. 5c we show that the full length long SATB1 isoform often aggregates unlike the short isoform. These data are accompanied with the results for the IDR region, where the situation is even more obvious (Fig. 5f,g). However, in the latter, we have to bear in mind the absence of the multivalent N-terminal part of the protein which seems to be essential for the overall phase behavior of the protein as indicated in Fig. 4b,c.

      **PLANNED EXPERIMENT #1**

      To further support LLPS of SATB1, we are considering performing the following in vitro experiment, as we answered to point #4 of Reviewer 1 (page 2). Although the purification of recombinant SATB1 protein is quite a challenging task, yet we 1. cloned both Satb1 cDNAs for the long and short isoforms, 2. we successfully expressed both proteins in great quantity and quality and we are willing to perform in vitro reconstitution experiments if our work is considered for publication.

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

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

      This paper looks at an important nuclear matrix protein SATB1, which is a well known global chromatin organizer and help chromatin loop attach to the nuclear matrix. The paper starts with identification of novel short and long form of SATB1. Both the isoform consist of a prion like low complexity domains, but the long isoform additionally contain an extra EPF domain next the Prion like low complexity domain. The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform. By using STED microscopy they show SATB1 foci lie next to transcription sites in the nucleus. They conclude by looking at the spherical shape of the SATB1 foci and the susceptibility of SATB1 staining after 1,6 hexanediol treatment that SATB1 forms the small foci in the nucleus due to LLPS. The authors also use RAMAN spectroscopy to conclude a change in nuclear chemical space in absence of SATB1 but without much explanation about which chemical bond or nuclear sub structure change correspond to the change in principal component analysis from Raman spectroscopy. The authors use the light inducible aggregation cry2 tag with the PrD domain of SATB1 and compare it with the Cry2-FUS-LC domain to conclude that the SATB1 LC domain can undergo LLPS. The authors hint at involvement of RNA and also DNA in the LLPS of the SATB1 but without going into any detail. Reviewer: The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform.

      Actually, in page 5 (lines 94-96) of the manuscript we write: “We confirmed that in murine thymocytes the steady state mRNA levels of the short Satb1 transcripts were about 3-5 fold more abundant compared to the steady state mRNA levels of the long Satb1 transcripts (Fig. 1d).” Although the steady state mRNA levels of the long isoform are less abundant compared to the shorter isoforms, the long isoform protein levels are almost comparable to the short isoform as deduced based on immunofluorescence experiments. Moreover, Using our two immunodepletion experiments we quantified the difference, estimating the long isoform being 1.5× to 2.62× less abundant than the short isoform (Fig. 1f and Supplementary Fig. 1b; compare lanes 2 & 3 at the lower panel). • Regarding the RAMAN spectroscopy experiments please see Minor Comment #1 of this Reviewer (page 10).

      The key conclusions of the paper are- A) SATB1 undergoes LLPS. But this conclusion is drawn after correlative experiments as detailed below-

      This conclusion is indeed made based on correlative experiments only for the primary murine T cells, which do not allow for any targeted experiments. However, the use of in vitro cell lines allowed us to validate these findings using the optogenetic approaches, utilizing additional experimentation.

      1) observation of spherical punctae by STED-which could also seem spherical due to their small size. The resolution limit achieved by the STED microscopy used in this paper is not determined or mentioned clearly.

      In the revised version of the manuscript, we have specified the resolution of our systems, for STED in Lines 745-746: ”This system enables super-resolution imaging with 35 nm lateral and 130 nm axial resolution.” and for SIM in Lines 759-761: “Images were acquired over the majority of the cell volume in z-dimension with 15 raw images per plane (five phases, three angles), providing ~120-135 nm lateral and ~340-350 nm axial resolution for 488/568 nm lasers, respectively.” The size of the observed speckles is thus above the resolution limit with sizes ranging between 40-80 nm.

      The resolution of our systems is routinely verified by the following methods: The resolution of our OMX (SIM-3D) system was tested using ARGO-SIM slide containing a pattern of 36 µm long lines with gradually increasing spacing ranging from (left to right) 0 to 390 nm, with a step of 30 nm (Fig. 1 below). Our SIM system was able to clearly resolve two lines separated by 120 nm.

      2) No live cell FRAP experiment with fluorescent SATB1 long or short isoform to show that these foci are liquid like

      We did perform FRAP experiments for the SATB1 N-terminus optogenetic construct as demonstrated in Fig. 4f. We did not perform FRAP in the primary murine T cells as this is not technically feasible without creating a new mouse line with fluorescently labeled protein. In the revised version of the manuscript, we additionally performed FRAP experiments for the full length short and long isoform of SATB1 labeled with EGFP and transfected into the NIH-3T3 cell line (Supplementary Figure 6f).

      5) LLPS is strongly coupled to the cellular concentration of the proteins. Authors should quantify the cellular concentration of the long and short isoform in the cells.

      We did consider protein concentration in our analyses of optogenetic constructs in Fig. 4b,d,e and Supplementary Fig. 6a,b,c. Quantifying the physiological cellular concentration of short and long SATB1 protein isoforms in primary T cells is impossible due to the inherent inability to discriminate between the isoforms by two antibodies, in the absence of Satb1 isoform-specific knockout mice.

      However, an approximation of the cellular concentration can be obtained from our immunodepletion experiments. On top of the original immunodepletion experiment that we now present in Supplementary Fig. 1a,b; in the revised version of the manuscript we have repeated the experiment in Fig. 1e,f. Comparison of the two bands for the long and short SATB1 isoforms in the lower panel of the western blot figures suggest that the long SATB1 isoform protein levels are 1.5× to 2.62× less abundant than the short isoform, according to the original and new immunodepletion experiment, respectively. This is now also included in the main text in Lines 110-116: “This experiment can also be used for approximation of the cellular protein levels of SATB1 isoforms in primary murine thymocytes. Comparison of the two bands for long (lane 2) and short SATB1 (lane 3) isoform in the lower panel of Fig. 1f and Supplementary Fig. 1b, suggests that the long SATB1 isoform protein levels may be about 1.5× to 2.62× less abundant than the short isoform, according to the two replicates of our immunodepletion experiment, respectively.”

      Major conclusion B)- SATB1 regulates transcription and splicing.

      This was also shown previously and in this paper they show the close proximity of the transcription site and SATB1 foci by microscopy. Hexanediol treatment which lead to loss of colocalization between FU foci and SATB1 is also taken as an evidence in regulation of transcription is not right as the transcription foci itself can be dissolved using 1,6 Hexanediol. Although the rate of transcription is not measured quantitatively.

      As mentioned in comment #3 (page 29) of this Reviewer, unfortunately there is no better tool to investigate these questions in primary cells than using microscopy approaches in conjunction with hexanediol treatment. However, we should also note that there is an accompanying manuscript from our group that is currently being under revision in another journal (preprint available: Zelenka et al., 2021; https://doi.org/10.1101/2021.07.09.451769). In the preprint manuscript, we showed that: 1. the long SATB1 isoform binding sites have increased chromatin accessibility than what expected by chance (Fig. 3b), 2. there is a drop in chromatin accessibility at SATB1 binding sites in Satb1 cKO mouse (Fig. 3c) and 3. this drop in chromatin accessibility is especially evident at the transcription start sites of genes (Supplementary Fig. 1i)

      We believe that, together these data suggest a direct involvement of SATB1 in transcription regulation. Also note the vast transcriptional deregulation that occurs in Satb1 cKO T cells, affecting the expression of nearly 2000 genes (Fig. 2f, this revised manuscript). That is why we believe that the co-localization analysis, using super-resolution microscopy, presented in Fig. 2c and quantified in Fig. 3g, represents a nice additional support to our claims. Moreover, in the revised version of the manuscript we now present a positive correlation between SATB1 binding and deregulation of splicing (Supplementary Fig. 4d) which also supports its direct involvement in the regulation of transcriptional and co-transcriptional processes.

      In the revised version of the manuscript we have made this clear in Lines 182-194: “Satb1 cKO animals display severely impaired T cell development associated with largely deregulated transcriptional programs as previously documented19,37,38. In our accompanying manuscript19, we have demonstrated that long SATB1 isoform-specific binding sites (GSE17344619) were associated with increased chromatin accessibility compared to randomly shuffled binding sites (i.e. what expected by chance), with a visible drop in chromatin accessibility in Satb1 cKO. Moreover, the drop in chromatin accessibility was especially evident at the transcription start site of genes, suggesting that the long SATB1 isoform is directly involved in transcriptional regulation. Consistent with these findings and with SATB1’s nuclear localization at sites of active transcription, we identified a vast transcriptional deregulation in Satb1 cKO with 1,641 (922 down-regulated, 719 up-regulated) differentially expressed genes (Fig. 2f). Specific examples of transcriptionally deregulated genes underlying SATB1-dependent regulation are provided in our accompanying manuscript19. Additionally, there were 2,014 genes with altered splicing efficiency (Supplementary Fig. 4d-e; Supplementary File 3-4). We should also note that the extent of splicing deregulation was directly correlated with long SATB1 isoform binding (Supplementary Fig. 4d).”

      Major conclusion C)-Post transcriptional modification is important for SATB1 function.

      This point is just barely touched upon in the last figure of the paper

      We would not call the identification of the novel phosphorylation site as a main conclusion of our manuscript. Though, it is already known that posttranslational modifications of SATB1 are important for its function as they can function as a molecular switch rendering SATB1 into either an activator or a repressor (Kumar et al., 2006; https://doi.org/10.1016/j.molcel.2006.03.010).

      In the revised manuscript, we support the effect of serine phosphorylation on the DNA binding capacity of SATB1 by another experiment. We have performed DNA affinity purification experiments utilizing primary thymocyte nuclear extracts treated with phosphatase (Supplementary Fig. 7b). We found that SATB1’s capacity to bind DNA (RHS6 hypersensitive site of the TH2 LCR) is lost upon treatment with phosphatase (Supplementary Fig. 7c). These results are in line with the data presented in Supplementary Fig. 7d, indicating the lost ability of SATB1 to bind DNA upon mutating the discovered phosphorylation site S635. Given the importance of posttranslational modifications of proteins on LLPS, we found it relevant to include it in our manuscript. Even more so, when we identified SATB1 aggregation, upon mutation of this phospho site (Fig. 6d).

      Overall I find that the major conclusion-point A and B, is based on very indirect experiments and needs much more convincing data and the role of SATB1 LLPS in cells should be demonstrated more rigorously. And conclusion C is barely described and needs a lot more cell biological and genetic evidence.

      One of the major assets of our work is that most of our data are based on the analysis of primary murine T cells and thus investigating the biological roles of the endogenous SATB1 protein, under physiological conditions. We apologize that we did not make it clear to this Reviewer, that our system has certain inherent limitations due to the utilization of primary cells.

      I do not recommend publishing the paper in current state. The story needs much more experiment to convincingly prove the major conclusions. Further, the MS needs more careful thinking and presentation to make it streamlined.

      We hope that in the revised version we have significantly improved the quality of our manuscript by implementing the suggested changes.

      Minor comments: One of the major flaw of the paper is the use too many techniques without proper explanation. E.g. use of STED and RAMAN microscopy need controls and explanation on what is being quantified. The use of Raman microscopy to quantify the nuclear environment of nucleus is not related to the chromatin organization or LLPS of SATB1 at all. And no information is provided at all which aspect of nuclear organization is being measured in Raman and what it means for the LLPS of SATB1.

      We do provide quite a thorough explanation of Raman spectroscopy and the underlying quantification in Lines 224-231: “we employed Raman spectroscopy, a non-invasive label-free approach, which is able to detect changes in chemical bonding. Raman spectroscopy was already used in many biological studies, such as to predict global transcriptomic profiles from living cells42, and also in research of protein LLPS and aggregation43–47. Thus we reasoned that it may also be used to study phase separation in primary T cells. We measured Raman spectra in primary thymocytes derived from both WT and Satb1 cKO animals and compared them with spectra from cells upon 1,6-hexanediol treatment. Principal component analysis of the resulting Raman spectra clustered the treated and non-treated Satb1 cKO cells together, while the WT cells clustered separately (Fig. 3h).” We also do provide controls as the method was performed on both treated and untreated WT and Satb1 cKO cells.

      Regarding the RAMAN spectroscopy experiments we now provide more information on the changes of chemical bonds altered between wild type and Satb1 cKO thymocytes. Following principal component analysis, we have extracted the two main principal components that were used for the clustering of our data. The differences are presented in Supplementary Fig. 5d.

      We do realize that RAMAN spectroscopy, although a quite novel approach utilized to study LLPS, has not been used to study LLPS in live cells. If deemed proper we are willing to avoid presenting these results in this manuscript.

      Similarly for Hexanediol treatment, duration of treatment is missing. Hexanediol can also dissolve the liquid like transcription foci. And hence a decrease in correlation between SATB1 foci and FU foci cannot be taken as a measure of SATB1 foci connection to transcription alone

      The duration of hexanediol treatment was 5 minutes as presented in Line 724 and in the revised version of the manuscript also in Lines 1206-1207. We should also note that additionally, we performed experiments with different hexanediol concentrations and timing varying from 1 minute to 10 minutes with results consistent with the data presented.

      It is not very clear how many times the STED or Raman microscopy is done on how many samples and biological replicates. Similarly for RNA sequencing number of samples and description of controls are missing. Also if the sequencing data is made publicly available is not clear.

      Data availability is clearly stated in Lines 506-509: “RNA-seq experiments and SATB1 binding sites are deposited in Gene Expression Omnibus database under accession number GSE173470 and GSE173446, respectively. The other datasets generated and/or analyzed during the current study are available upon request.”

      The Reviewer’s token is “wjwtmeeeppovzqx”.

      RNA sequencing was performed in a biological triplicate for each genotype as stated in the GEO repository and now also in Line 566 of the revised manuscript.

      In Lines 180-181, we also state that it was performed on Satb1 cKO animals and WT mice as a control: “we performed stranded-total-RNA-seq experiments in wild type (WT) and Satb1fl/flCd4-Cre+ (Satb1 cKO) murine thymocytes”.

      In Lines 739-740, we now also state that all imaging approaches were performed on at least two biological replicates (different mice) and please also note the fact that all findings were based on data from both STED and 3D-SIM methods, allowing to minimize detection of artifacts. In the Raman spectroscopy figure, each point represents measurements from an individual cell and for each condition we used 2-5 biological replicates (Lines 831-832 & Line 1169).

      Similarly, in Lines 129-132 we provided a quite detailed description of differences between STED and 3D-SIM, even though these techniques are not that rare as Raman spectroscopy in biology research.

      Additional control is needed to report the resolution limit of Superresolution techniques-STED and 3D-SIM systems used by them.

      We have already provided this information in our reply to comment #1 of this Reviewer (pages 6-7): In the revised version of the manuscript, we have specified the resolution of our systems, for STED in Lines 745-746: ”This system enables super-resolution imaging with 35 nm lateral and 130 nm axial resolution.” and for SIM in Lines 759-761: “Images were acquired over the majority of the cell volume in z-dimension with 15 raw images per plane (five phases, three angles), providing ~120-135 nm lateral and ~340-350 nm axial resolution for 488/568 nm lasers, respectively.” The resolution of our systems is routinely verified by the following methods: The resolution of our OMX (SIM-3D) system was tested using ARGO-SIM slide containing a pattern of 36 µm long lines with gradually increasing spacing ranging from (left to right) 0 to 390 nm, with a step of 30 nm (Fig. 1 below). Our SIM system was able to clearly resolve two lines separated by 120 nm.

      Would be very helpful if the zonation was plotted for the FluoroUridine (FU) also to show that Zone1 (heterochromatin) is completely depleted of FU, and is present in other regions.

      In the revised version of the manuscript, we performed the suggested analysis and in Supplementary Fig. 3a we now show that indeed FU is significantly less localized to Zone 1 (heterochromatin) and has the most abundant localization in Zones 3 and 4, similar to the localization of SATB1 protein, as demonstrated in Fig. 2b.

      Scale bar needed figure 3d

      In the revised version of the manuscript, we included scale bars which are both 0.5 µm (line 1213).

      Perfectly rounded SATB1 foci- this does not mean LLPS. For LLPs measurement, protein condensate dynamics measurement by FRAP or fusion experiments is required. What is the size of condensates? and cellular concentration of SATB1? Will SATB1 undergo LLPS in vitro at similar concentrations? does SATB1 interact with DNA or RNA to undergo LLPS ?

      We toned down this sentence which now reads: “Here we demonstrated its connection to transcription and found that it forms spherical speckles (Fig. 1g), markedly resembling phase separated transcriptional condensates. (Lines 200-202)”.

      Moreover, as explained in earlier replies to comments of this Reviewer, we cannot perform FRAP on primary murine T cells without generating a new mouse line. We did, however, use FRAP and other in vitro approaches including visualization of droplet fusion in ex vivo experiments utilizing cell lines. Moreover, we are willing to demonstrate the LLPS properties of SATB1 on in vitro purified SATB1 protein as indicated in the suggested experiment of Point#4 (page 2).

      After careful reading of the MS I conclude that the main conclusions of the paper are very preliminary and need much more detailed experiments. So does not qualify to get published at all at this stage.

      **Reviewer #1 (Significance)**:

      The present manuscript tries to connect the phase separation of SATB1 to understanding the mechanism of SATB1 function in cells. One of the major hallmarks of phase separation is dynamic, liquid-like behaviour and in absence of these measurements, it is very difficult to say that the current manuscript has made any contribution to showing that SATB1 can phase separate.

      The presence of 2 isoforms of SATB1 is a novel finding and the paper could have focused more on this. E.g. elucidate expression of the isoform during thymocyte development and maturation.

      As a reviewer my expertise are cell biology experiments, microscopy, in vitro reconstitution assays, RNA binding proteins, RNA and RBP condensate formation. And I feel that the reconstitution experiments are an important tool for understanding phase behaviour of proteins and also to gauge if this behaviour can occur or not in cellular concentration and conditions.

      I do not have sufficient expertise in Raman microscopy and hence the information provided in the MS on this part was not enough to understand the experiment and conclusions drawn from it.

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

      The authors have reported the existence of a 'long' SATB1 isoform which also undergoes LLPS. The authors tried to draw multiple comparisons and pointed out distinction between phase properties of SATB1 isoforms. The authors also touch upon two functional roles of SATB1. Although a wide array of assays are used, the data presented and hence the manuscript makes multiple transitions into disparate hypotheses without diving deep into a single hypothesis. As a result, the connections drawn are unclear, and do not converge at best. The authors have used number of techniques, however, the results do not support their conclusions and they appear hastily drawn. It is not clear why the authors jump from one context to the other, discussing LLPS first, then transcription, splicing, post-translational modification and finally cancer. The link between all of these isn't clear and not fully supported by data. It appears that the authors wish to focus on Satb1's physiological role in development, hence the data on breast cancer is confusing. Thus, this work suffers from multiple pitfalls. Specific comments are given below:

      Major comments 1. Importantly, in Fig 1d, there is no statistics shown. There is no mention of number of replicates as well in the legends. Proper statistical evaluation is critical for interpreting this result.

      Please note that Fig. 1d only serves as a control to the sequencing experiment in Fig. 1b. In Line 566, we now state that for the RNA-seq: “A biological triplicate was used for each genotype.” To validate these data, we further designed a RT-qPCR experiment which was performed on three technical replicates from a male and female mouse. We now state this in Line 636. For the low number of samples, statistical tests are not accurate but we still added t test into the figure Fig. 1d and specified it also in the figure legend in Line 1169-1170.

      1. Figure 1f presents one of the weakest evidences in the manuscript. There are a number of corrections needed. Firstly, being their major and only validation figure for their custom antibody, the immunoblot is not clean, bands are fuzzy. Importantly, as the authors claim that the antibody is highly specific to 'long' SATB1, after the IP there should be only a single band (like input) of Satb1 long. But that does not seem to be the case, rather an array of bands are visible below (lane 2 top panel). This could easily mean that the shorter isoforms or non-specific protein bands are also pulled down with the 'long' form specific antibody. Therefore, raising a critical concern regarding the specificity of the antibody.

      • The long antibody was raised in mice inoculated with the extra peptide present in the long isoform only. Therefore, the capacity of this antibody precipitating the shorter isoforms, which do not express the sequence of the extra peptide (EP, Figure 1a) in not possible. • We have repeated the immunodepletion experiment and we now provide the results in Fig. 1f and Supplementary Fig. 1b. The western blot in Fig. 1f is now cleaner and supports quite convincingly the presence of a long SATB1 isoform. Given the lack of isoform-specific knockouts which we could utilize to immunoprecipitate or detect the different isoforms in a single cell (or cell population), the utilized approach of immunodepletion and subsequent western blotting is the approach we thought of implementing. • As shown in Fig. 1f and Supplementary Figure 1b, the long isoform SATB1 antibody has the capacity to recognize the long isoform in murine thymocyte protein extracts but not the short SATB1 isoform (please compare lane 3 in the two western blots utilizing either the antibody for the long isoform -top panel - or the antibody that detects both isoforms (lower panel). • We have performed Immunofluorescence experiments utilizing the antibody detecting the long SATB1 isoform in thymocytes isolated from either C57BL/6 or Satb1 cKO mice. The antibody is specific to the SATB1 protein since there is no signal in immunofluorescence experiments utilizing the knockout cells (Supplementary Figure 1c). • We have performed Immunofluorescence experiments utilizing thymocytes and the antibody detecting the long SATB1 or a commercially available antibody detecting all SATB1 isoforms. The pattern of SATB1 subnuclear localization is similar for both antibodies (Supplementary Figure 1e). • In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoforms antibodies. • Regarding the additional bands detected in the immunoprecipitation experiment presented in the original Supplementary Figure 1b (lane 2), it is not surprising that additional bands appear in a sample of protein extracts that is used for several hours for the immunoprecipitation experiments, while the “input” sample simply denotes protein extract that is frozen at -80oC right after the preparation of protein extracts until use. It is well-established that SATB1 is the target of proteases which might as well be active during the immunoprecipitation steps (2 consecutive immunoprecipitation steps take place). Therefore, the immunoprecipitated material cannot necessarily be a copy of the input material displaying a single protein band even if protease inhibitors are included in the buffers.

      Taken together the experiments described here we showed that the antibody raised against the extra 31 aa long peptide, present only in the long SATB1 isoform, is specific for this isoform.

      1. Related to Fig. 2 a, the authors state on Pg 5, '....the euchromatin and interchromatin regions (zones 3 & 4, Fig. 2a, b).' Although the DAPI correlation seems clear, there is no mention on how they reached the above said correlation. They should at least show a parallel speckle staining for HP1 or signature modification such as H3K4me9 STEDs for making supporting such a claim. DAPI alone is not sufficient. The authors should rectify the text thoroughly for many such interpretations without validation/reference or provide relevant data.

      This is a great suggestion we have again taken under consideration and we added the following experiments and the appropriate changes in the revised version of our manuscript. • We modified the text and added a reference to Miron et al., 2020 (https://doi.org/10.1126/sciadv.aba8811) supporting our claims regarding SATB1 localization in relation to DAPI staining. • We have also added new microscopy images for HP1, H3K4me3 and fibrillarin staining and quantified the localization of FU-stained sites of active transcription in nuclear zones, to further support our claims. • This whole modified part in Lines 139-167 then reads: “ “The quantification of SATB1 speckles in four nuclear zones, derived based on the relative intensity of DAPI staining, highlighted the localization of SATB1 mainly to the regions with medium to low DAPI staining (zones 3 & 4, Fig. 2a, b). A similar distribution of the SATB1 signal could also be seen from the fluorocytogram of the pixel-based colocalization analysis between the SATB1 and DAPI signals (Supplementary Fig. 2a). SATB1’s preference to localize outside heterochromatin regions was supported by its negative correlation with HP1β staining (Supplementary Fig. 2b). Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. The prevailing localization of SATB1 corresponded with the localization of RNA-associated and nuclear scaffold factors, architectural proteins such as CTCF and cohesin, and generally features associated with euchromatin and active transcription32. This was also supported by colocalization of SATB1 with H3K4me3 histone mark (Supplementary Fig. 2c), which is known to be associated with transcriptionally active/poised chromatin. Given the localization of SATB1 to the nuclear zones with estimated transcriptional activity32 (Fig. 2b, zone 3), we investigated the potential association between SATB1 and transcription. We unraveled the localization of SATB1 isoforms and the sites of active transcription labeled with 5-fluorouridine. Sites of active transcription displayed a significant enrichment in the nuclear zones 3 & 4 (Supplementary Fig. 3a), similar to SATB1. As detected by fibrillarin staining, SATB1 also colocalized with nucleoli which are associated with active transcription and RNA presence (Supplementary Fig. 3b). Moreover, we found that the SATB1 signal was found in close proximity to nascent transcripts as detected by the STED microscopy (Fig. 2c). Similarly, the 3D-SIM approach indicated that even SATB1 speckles that appeared not to be in proximity with FU-labeled sites in one z-stack, were found in proximity in another z-stack (Supplementary Fig. 3c). Additionally, a pixel-based colocalization of SATB1 and sites of active transcription is quantified later in the text in Fig. 3g, supporting their colocalization.”

      1. The authors mention, '...of the different SATB1 isoforms, uncovered by the use of the two different antibodies, relied in the heterochromatin areas (zone 1), where the long isoform was less frequently...' There is no supporting figure number mentioned. The authors need to show a zone-by-zone comparison images for 'all iso' vs 'long' iso of SATB1. Just to reiterate, there is a need for a heterochromatin mark to unambiguously call out the distinction.

      We should remind that there is an inherent difficulty to accurately compare localization of short and long SATB1 isoforms in primary cells, especially due to the lack of Satb1 isoform-specific knockout mice. There is no way to detect only the short isoform in these primary cells as there are only antibodies targeting the long or all SATB1 isoforms. Therefore, we cannot set up additional experiments probing these questions.

      In line with this, in the revised version of the manuscript, we toned down our statements regarding the differential localization of the two isoforms in primary cells. We only refer to it as an indication and we support it by adding references to the relevant figures. This part now reads: “Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. (Lines 145-150)”

      1. On the same lines, '....Given the localization of SATB1 to the nuclear zones with estimated transcriptional activity (Fig. 2b, zone 3)....' How was the region labelled as transcriptionally active? For the statistical analysis of speckle count for the two antibodies' staining, the claim posited is a bit bigger. This could simply be true for that cell. The authors thus need to statistically analyse the speckle counts for multiple cells. This needs to be done for all imaging statistics done in multiple figures throughout the manuscript.

      As mentioned in our reply to the two previous comments of this Reviewer, transcriptional activity in relation to the nuclear zonation is well established in the literature. To make this clear, we have now added the reference to Miron et al., 2020 (https://doi.org/10.1126/sciadv.aba8811) supporting our claims and additionally we have also included HP1, H3K4me3 and fibrillarin staining and quantification of FU signal in the nuclear zones. Moreover, it is not clear to which particular cell the comment refers to. The presented dots in Fig. 2b represent individual cells and the relative proportions of speckles in each nuclear zone are plotted on the y axis. In the revised version of the manuscript, we added into the figure the number of cells scored and we adapted the figure legend so that it is absolutely clear that we have analyzed multiple cells:

      “Nuclei of primary murine thymocytes were categorized into four zones based on the intensity of DAPI staining and SATB1 speckles in each zone were counted. Images used represented a middle z-stack from the 3D-SIM experiments. The graph depicts the differences between the long and all SATB1 isoforms’ zonal localization in nuclei of primary murine thymocytes. (Lines 1189-1193)”

      1. For figure 2c. the authors have used 5 Fluorouridine for nascent RNA speckles. 5FU is known to have a spread signal type (with strong association to nucleolus as well). This is not the case for the image presented 2c. The authors should resolve this by showing different sets of images.

      Developing and naive T cells are very unique in terms of their metabolic features and thus they should not be directly compared with other cell types. Therefore, we would not expect to see such a spread FU pattern as previously shown for other cell types. Having said that, we could not find any reference publication that utilized super-resolution microscopy to detect localization of FU-stained sites of active transcription in developing primary T cells. However, we performed additional immunofluorescence experiments to demonstrate the colocalization or its lack between SATB1 and HP1 (Supplementary Fig. 2b), H3K4me3 (Supplementary Fig. 2c) and fibrillarin (Supplementary Fig. 3b). Moreover, we provide additional regions of SATB1 and FU staining in Supplementary Fig. 3c. The modified text reads:

      “We unraveled the localization of SATB1 isoforms and the sites of active transcription labeled with 5-fluorouridine. Sites of active transcription displayed a significant enrichment in the nuclear zones 3 & 4 (Supplementary Fig. 3a), similar to SATB1. As detected by fibrillarin staining, SATB1 also colocalized with nucleoli which are associated with active transcription and RNA presence (Supplementary Fig. 3b). Moreover, we found that the SATB1 signal was found in close proximity to nascent transcripts as detected by the STED microscopy (Fig. 2c). Similarly, the 3D-SIM approach indicated that even SATB1 speckles that appeared not to be in proximity with FU-labeled sites in one z-stack, were found in proximity in another z-stack (Supplementary Fig. 3c). Additionally, a pixel-based colocalization of SATB1 and sites of active transcription is quantified later in the text in Fig. 3g, supporting their colocalization. (Lines 157-167)”

      1. Fig 2 d., the authors have suddenly jumped solely to 'all iso' Satb1 here for IP MS. Is there a reason for that? The authors either need to do this with 'long iso' antibody or remove the analysis from the manuscript as it does not add to their primary aim of the manuscript. Also, the authors have only selectively talked about two clusters? What about chromatin related proteins? It is quite intuitive to have highest enrichment of these given previous literature and even IP MS data by other groups. Thus, it is necessary to revise this thoroughly or remove it.

      We appreciate the acknowledgment by the Reviewer that our IP-MS data identified anticipated factors. In the revised version of the manuscript we modified the underlying text to accommodate references to these former findings revealing interactions between SATB1 and chromatin modifying complexes: “Apart from subunits of chromatin modifying complexes that were also detected in previous reports25,33–36, unbiased k-means clustering of the significantly enriched SATB1 interactors revealed two major clusters consisting mostly of proteins involved in transcription (blue cluster 1; Fig. 2d and Supplementary Fig. 4c) and splicing (yellow cluster 2; Fig. 2d and Supplementary Fig. 4c). (Lines 170-174)”

      Please note that many subunits of chromatin modifying and chromatin-related complexes are in fact characterized as transcription-related factors, therefore our statements are not in disagreement with the former findings. Note also that we provide Supplementary File 1 & 2 with comprehensive description of our IP-MS data for the readers’ convenience. Please also note that we are the first group to report on the existence of the long isoform. Therefore, we find it absolutely reasonable to perform IP-MS experiment for all SATB1 isoforms which can then be used for a comparison with other publicly available datasets. We believe that there is no contradiction in this experimental setup in relation to the rest of the manuscript. We discuss the two major clusters simply because they are the two major clusters identified as indicated in Fig. 2d. Additionally, in Supplementary Fig. 4c, we provide a comprehensive description of all significantly enriched interactors including their cluster annotation and thus anyone can investigate the data if needed.

      1. In relation to Fig. 2f, the authors have not mentioned any of the previously published work on Satb1 CD4 specific KO, not even the RNA seq studies the other groups have reported under the same condition. Only an unpublished reference of their own (preprint) is cited. It is imperative to show how much their data corroborates with other published studies. Additionally, what is the binding site status of dysregulated genes?

      In the revised version of the manuscript, we have included the references to other studies using the same Satb1 conditional knockout. Moreover, we have clarified the relationship between SATB1 binding and gene transcription. The modified part in Lines 182-194 now reads: “Satb1 cKO animals display severely impaired T cell development associated with largely deregulated transcriptional programs as previously documented19,37,38. In our accompanying manuscript19, we have demonstrated that long SATB1 isoform specific binding sites (GSE17344619) were associated with increased chromatin accessibility compared to randomly shuffled binding sites (i.e. what expected by chance), with a visible drop in chromatin accessibility in Satb1 cKO. Moreover, the drop in chromatin accessibility was especially evident at the transcription start site of genes, suggesting that the long SATB1 isoform is directly involved in transcriptional regulation. Consistent with these findings and with SATB1’s nuclear localization at sites of active transcription, we identified a vast transcriptional deregulation in Satb1 cKO with 1,641 (922 down-regulated, 719 up-regulated) differentially expressed genes (Fig. 2f). Specific examples of transcriptionally deregulated genes underlying SATB1-dependent regulation are provided in our accompanying manuscript19. Additionally, there were 2,014 genes with altered splicing efficiency (Supplementary Fig. 4d-e; Supplementary File 3-4). We should also note that the extent of splicing deregulation was directly correlated with long SATB1 isoform binding (Supplementary Fig. 4d).”

      1. In context of Figure 3a and b, the authors write .'...The long SATB1 isoform speckles evinced such sensitivity as demonstrated by a titration series with increasing concentrations of 1,6-hexanediol treatment followed...' Whereas it is apparent from the image at least that overall numbers of individual speckles are instead increased at both 2 and 5%. There is although a clear spreading of restricted speckles compared to the controls. The authors should revise their figures to substantiate the associated text. Furthermore, there needs to be 'all iso' SATB1 3D SIM imaging and not just quantitation for comparison. This is also true for panel c in order to demonstrate the effect.

      In the revised Fig. 3a we provide new images which better reflect the underlying data analysis. Moreover, in Fig. 3c and Fig. 3d we provide an additional comparison between SATB1 all isoforms and long isoform staining and their changes upon hexanediol treatment, detected by both the 3D-SIM and STED approaches. It is true that upon treatment, there tend to be more speckles, however these are much smaller as they are gradually being dissolved. Depending on the treatment duration, the cells are swollen which is reflected in increased spreading of speckles. Nevertheless, the nuclear size was considered in all the quantification analyses. We believe that the new images provide better evidence of SATB1’s sensitivity to hexanediol treatment.

      1. Fig. 3 d also does not clearly demonstrate what the authors have claimed '...hexanediol treatment highly decreased colocalization between...' The figure shows at best decreased signal intensity for both SATB1 and FU. We suggest that the authors should give a statistical analysis as well for the colocalization points between the two using multiple source images. Lastly, the two images shown (control and treated), there seems to be a clearly visible magnification difference. The authors should clarify this.

      • In the revised version of the manuscript in Figure 3d, we have provided scale bars, which are both 0.5 µm (line 1213). The difference observed by this Reviewer is actually the main reason why we provided this image. Figure 3d demonstrates that upon hexanediol treatment, the speckles are mostly missing or significantly reduced in size, for both FU and SATB1 staining. • Moreover, the suggested statistical analysis is also provided – in Figure 3e. In Figure 3e, we performed pixel-based colocalization analysis which is a method that allows both quantification and statistical comparison of colocalization between two factors and between different conditions. Please note especially the decreased colocalization between long SATB1 isoform and FU-stained sites of active transcription in the left graph, which is in agreement with our claims in the manuscript. • Moreover, our data are compared to a negative control, i.e. 90 degrees rotated samples, which is a common method in colocalization experiments as described for example in Dunn et al., 2011 (https://doi.org/10.1152/ajpcell.00462.2010). • Additionally, we provide Costes’ P values which are based on randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel’s intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. Please see Costes et al., 2004 (https://doi.org/10.1529%2Fbiophysj.103.038422) for more details.

      1. Figure 3f. The authors show the PC plot for Raman spectroscopy for phase behaviour due to Satb1. The experiment and its related text seems misinterpreted; the authors write...' ese bonds were probably enriched for weak interactions responsible for LLPS that are susceptible to hexanediol treatment. This shifted the cluster of WT treated cells towards the Satb1 cKO cells. However, the remaining covalent bonds differentiated the WT samples from Satb1 cKO cells......' whereas the clusters are clearly far away in 3D for both WT and KO while being closer to their respective treatments. Which is also intuitive given the sensitivity of Raman spectroscopy. Thus, it is more likely to be treatment effect and KO effect as separate. Treatment of WT leads to KO like spectra is far-fetched. Thus, the authors need to show separate PCs and modify their text thoroughly.

      We do not present any 3D graph hence it is not clear what the Reviewer refers to. Please also note that as stated in Lines 817-818, we used a customized Raman Spectrometer. Therefore, this approach allowed us to measure Raman spectra at cellular and even sub-cellular levels. For example, solely by utilizing Raman spectroscopy, we can now distinguish euchromatin and heterochromatin, methylated and unmethylated DNA and RNA, etc. This, together with other reports, such as Kobayashi-Kirschvink et al., 2018 (https://doi.org/10.1016/j.cels.2018.05.015) and Kobayashi-Kirschvink et al., 2022 (https://doi.org/10.1101/2021.11.30.470655), indicate a potential use of Raman in biological research. In our manuscript, we used this method as a supplementary approach, however we do find it noteworthy. We should also emphasize that in the revised Raman spectroscopy Fig. 3h, each point represents measurements from an individual cell and for each condition we used 2-5 biological replicates (Lines 831-832 & Lines 1225-1226). We specifically refer to the principal component 1 (PC1) that differentiates the samples. Therefore, there are certain spectra (representing certain chemical bonding) that allowed us to differentiate between WT and Satb1 cKO. The same type of bonding was then affected when WT samples were treated with hexanediol and we also had controls to rule out the impact of hexanediol on the resulting spectra.

      1. In Fig 4. b, The authors have shown the propensity of SATB1 N terminus to phase separate using different optodroplet constructs. Although the imaging is clear, why are the regions selected not uniform when comparing various constructs?

      We have selected images that would best represent each category. Please note that this was live cell imaging of photo-responsive constructs, thus there are many limitations regarding the area selection. Very often, even the brief time of bright light exposure to localize cells may trigger protein clustering. Upon disassembly, every new light exposure of the same cell then triggers much faster assembly which skews the overall results. It is therefore desired to work fast, while neglecting selection of equally sized cells. Moreover, it is not clear how would the proposed change improve the quality of our manuscript.

      1. Figure 5a, the disassembly should be shown for 'long' SATB1 as well. On pg 13, the authors write '....cytoplasmic protein aggregation has been previously described for proteins containing poly-Q domains and PrLDs..' no reference given.

      • In the revised version of the manuscript, we present the assembly and disassembly for both short and long full length SATB1 optogenetic constructs. To increase clarity, we present the behavior of the short and long isoforms as two separate images in Figure 5a and Figure 5b, respectively. • Moreover, we provided references to the statement regarding aggregation of PrLD and poly-Q-containing proteins in Lines 305-309, which now reads: ”Since protein aggregation has been previously described for proteins containing poly-Q domains and PrLDs8,11,38,39, we next generated truncated SATB1 constructs encoding two of its IDR regions, the PrLD and poly-Q domain and in the case of the long SATB1 isoform also the extra peptide neighboring the poly-Q domain (Fig. 1a and 4a).”

      1. Fig. 5d, Is there an amino-acid specific reasoning to support the authors claim of the phase behaviour due to extra peptide? They need to show a proper control with equal extra (unrelated) peptide to show the specificity. Are the shorter isoform aggregates responsive to light?

      • We have referred to the amino acid composition bias in Fig. 5c. In the revised version of the manuscript, we made this clear by showing the composition bias in the new revised Fig. 5e. The related part of the main text then reads: “Computational analysis, using the algorithm catGRANULE37, of the protein sequence for both murine SATB1 isoforms indicated a higher propensity of the long SATB1 isoform to undergo LLPS with a propensity score of 0.390, compared to 0.379 for the short isoform (Fig. 5d). This difference was dependent on the extra peptide of the long isoform. Out of the 31 amino acids comprising the murine extra peptide, there are six prolines, five serines and three glycines – all of which contribute to the low complexity of the peptide region3 (Fig. 5e).” (Lines 298-304) • Moreover, we should note that the low complexity extra peptide of the long SATB1 isoform directly extends the PrLD and IDR regions as indicated in Fig. 4a and which we now directly state in Lines 304-305: “Moreover, the extra peptide of the long SATB1 isoform directly extends the PrLD and IDR regions as indicated in the Fig. 4a.” • We show in Fig. 4, that the N terminus of SATB1 undergoes LLPS. Since this part of SATB1 is shared by both isoforms, it is reasonable to assume that both isoforms would undergo LLPS. This is also in line with the observed photo-responsiveness of both short and long full length SATB1 isoforms in CRY2 optogenetic constructs in revised Fig. 5a,b, and similar FRAP results for both short and long full length SATB1 isoform constructs transiently transfected in NIH-3T3 cells in the revised Supplementary Fig. 6f. However, the main reason why we think that the difference in LLPS propensity between the isoforms is important is because the long isoform is more prone to aggregate compared to the short isoform, as documented in Fig 5c,f,g and Supplementary Fig. 5f.

      1. Fig 6c., It is important that authors show the data for NLS+short iso data as well to prove their hypothesis.

      As shown in original Figure 5d, the long SATB1 isoform undergoes cytoplasmic aggregation, unlike the short SATB1 isoform (as shown in the same Figure). Therefore, an image of the NLS + short isoform would not be related to our hypothesis. Actually, we wanted to reverse the long SATB1 isoform’s relocation, from the aggregated form in the cytoplasm into the nucleus. Nevertheless, to show the complete picture, in the revised version of the manuscript in Figure 6c, we now provide data for both short and long SATB1 isoforms.

      1. Fig 6d., The authors claim that mutating a specific P site changes the phase behaviour of the 'short iso'. Does it also increase for the long isoform? The authors need to confirm this in order to verify the effect of a single P site outside of oligomerization domain. ...' phosphorylation status; when phosphorylated it remains diffused, whereas unphosphorylated SATB1 is localized to PML bodies....' This being an important premise, thus should be moved to the results text.

      In the revised version of the manuscript, we moved the part regarding PML in the results section, as suggested by the Reviewer. Moreover, we included additional experiments probing the impact of association between PML and two SATB1 full length isoforms on their dynamics. The modified section in Lines 357-368 now reads: “In relation to this, a functional association between SATB1 and PML bodies was already described in Jurkat cells64. We should note that PML bodies represent an example of phase separated nuclear bodies65 associated with SATB1. Targeting of SATB1 into PML bodies depends on its phosphorylation status; when phosphorylated it remains diffused, whereas unphosphorylated SATB1 is localized to PML bodies66. This is in line with the phase separation model as well as with our results from S635A mutated SATB1, which has a phosphorylation blockade promoting its phase transitions and inducing aggregation. To further test whether SATB1 dynamics are affected by its association with PML, we co-transfected short and long full length SATB1 isoforms with PML isoform IV. The dynamics of long SATB1 isoform was affected more dramatically by the association with PML than the short isoform (Supplementary Fig. 7e), which again supports a differential behavior of the two SATB1 isoforms.”

      Moreover, given the localization of the discussed phosphorylation site in the DNA binding region of SATB1 we did test its impact on DNA binding as documented in the revised Supplementary Fig. 7d. Additionally, as we have noted in our answer in Major Comment C of this reviewer, to further support the effect of serine phosphorylation on the DNA binding capacity of SATB1 we have performed DNA affinity purification experiments utilizing primary thymocyte nuclear extracts treated with phosphatase (Supplementary Fig. 7b) We found that SATB1’s capacity to bind DNA (RHS6 hypersensitive site of the TH2 LCR) is lost upon treatment with phosphatase (Supplementary Fig. 7c).

      1. Pg 16,. The authors have tried to explain multiple things (concepts of self-regulation, accessibility) which is quite tangential. There is no inference to Fig 6f., which is showing the opposite to what the authors had postulated. This portion should either be removed or explained with a rationale. The writing also needs to be revised thoroughly in this section. Similarly, the discussion should also be modified.

      The rationale for the original Fig. 6f (revised Fig. 6g) was described in great detail in Lines 330-343 of the original manuscript. It is not clear why the Reviewer assumes that it shows the opposite to our hypothesis. As we explained, the increased accessibility allows faster read-through by RNA polymerase, and thus the exon with higher accessibility is more likely to be skipped. The exact relationship is shown in the revised Fig. 6g where the increased accessibility is associated with the expression of the short isoform, whereas the long isoform expression needs lower chromatin accessibility which allows the splicing machinery to act on the specific exon to be included. We reason that these findings are important and relevant because: 1) we suggest a potential regulatory mechanism for the SATB1 isoforms production. This is highly relevant to this manuscript given the fact that this is the first report on the existence of the long SATB1 isoform, and 2) the differential production of the long/short SATB1 isoforms has a potential relevance to breast cancer prognosis. In the revised version of the manuscript we added Fig. 6f, which now indicates the differential chromatin accessibility in human breast cancer patients and accordingly the expression of the long SATB1 isoform are associated with worse patient prognosis as indicated in Fig. 6h and Supplementary Fig. 8a,b. In the revised version of the manuscript, we substantially modified the text in Lines 374-408, to make the relevance of all these conclusions clear. The modified text now reads: “Therefore, we reasoned that a more plausible hypothesis would be based on the regulation of alternative splicing. In our accompanying manuscript19, we have reported that the long SATB1 isoform DNA binding sites display increased chromatin accessibility than what expected by chance (Fig. 3b in 19), and chromatin accessibility at long SATB1 isoform binding sites is reduced in Satb1 cKO (Fig. 3c in 19), collectively indicating that long SATB1 isoform binding promotes increased chromatin accessibility. We identified a binding site specific to the long SATB1 isoform19 right at the extra exon of the long isoform (Fig. 6e). Moreover, the study of alternative splicing based on our RNA-seq analysis revealed a deregulation in the usage of the extra exon of the long Satb1 isoform (the only Satb1 exon affected) in Satb1 cKO cells (deltaPsi = 0.12, probability = 0.974; Supplementary File 4). These data suggest that SATB1 itself is able to control the levels of the short and long Satb1 isoforms. A possible mechanism controlling the alternative splicing of Satb1 gene is based on its kinetic coupling with transcription. Several studies indicated how histone acetylation and generally increased chromatin accessibility may lead to exon skipping, due to enhanced RNA polymerase II elongation48,49. Thus the increased chromatin accessibility promoted by long SATB1 isoform binding at the extra exon of the long isoform, would increase RNA polymerase II read-through leading to decreased time available to splice-in the extra exon and thus favoring the production of the short SATB1 isoform in a negative feedback loop manner. This potential regulatory mechanism of SATB1 isoform production is supported by the increased usage of the extra exon in the absence of SATB1 in Satb1 cKO (Supplementary File 4). To further address this, we utilized the TCGA breast cancer dataset (BRCA) as a cell type expressing SATB150. ATAC-seq experiments for a series of human patients with aggressive breast cancer51 revealed differences in chromatin accessibility at the extra exon of the SATB1 gene (Fig. 6f). In line with the “kinetic coupling” model of alternative splicing, the increased chromatin accessibility at the extra exon (allowing faster read-through by RNA polymerase) was positively correlated with the expression of the short SATB1 isoform and slightly negatively correlated with the expression of the long SATB1 isoform (Fig. 6f). Moreover, we investigated whether the differential expression of SATB1 isoforms was associated with poor disease prognosis. Worse pathological stages of breast cancer and expression of SATB1 isoforms displayed a positive correlation for the long isoform but not for the short isoform (Fig. 6g and Supplementary Fig. 6c). This was further supported by worse survival of patients with increased levels of long SATB1 isoform and low levels of estrogen receptor (Supplementary Fig. 6d). Overall, these observations not only supported the existence of the long SATB1 isoform in humans, but they also shed light at the potential link between the regulation of SATB1 isoforms production and their involvement in pathological conditions.”

      1. The authors should not draw conclusions based on any data which is not shown '....ed differences in chromatin accessibility at the extra exon of the SATB1 gene (data not shown), suggesting its potential involvement in alternative splicing regulation according to the "kinetic coupling" model...'. This has led to overspeculation and needs correction.

      In the revised version of the manuscript, we included the ATAC-seq data from human breast cancer patients in the revised Fig. 6f. The legend of this figure now reads: “Human TCGA breast cancer (BRCA) patient-specific ATAC-seq peaks51 span the extra exon (EE: extra exon; labeled in green) of the long SATB1 isoform. Note the differential chromatin accessibility in seven selected patients, emphasizing the heterogeneity of SATB1 chromatin accessibility in cancer. Chromatin accessibility at the promoter of the housekeeping gene DNMT1 is shown as a control. (Lines 1281-1285)” Accordingly, we have also modified the main text: “ATAC-seq experiments for a series of human patients with aggressive breast cancer68 revealed differences in chromatin accessibility at the extra exon of the SATB1 gene (Fig. 6f). In line with the “kinetic coupling” model of alternative splicing, the increased chromatin accessibility at the extra exon (allowing faster read-through by RNA polymerase) was positively correlated with the expression of the short SATB1 isoform and slightly negatively correlated with expression of the long SATB1 isoform (Fig. 6g).” (Lines 395-339)”

      Minor comments: 1. On pg 4, the authors state 'Here, we utilized primary murine T cells, in which we have identified two full-length SATB1 protein isoforms.' Whereas only one 'long' isoform is identified and the other is the canonical version. The authors should correct the statement.

      In the revised version of the manuscript, we modified this statement as follows: ”In this work, we utilized primary developing murine T cells, in which we have identified a novel full-length long SATB1 isoform and compared it to the canonical “short” SATB1 isoform.” (Lines 64-66)”

      1. Fig. 1 a , Is there a specific reason to generate a custom-made antibody for 'all' SATB1, using similar regions that are already commercially available. This becomes redundant otherwise, because there is no apparent difference in detection compared to the commercial one (Suppl. Fig 1a). Antibody generation strategy (1a) should be moved to supplementary. Additionally, authors have obtained the custom antibodies from a commercial source, therefore, the text should reflect the same alongside relevant details.

      The custom-made SATB1 antibody targeting the amino-terminal region of the protein has been developed in order to be utilized for detecting the native form of the protein. Unlike commercially available antibodies raised against either short peptides or denatured forms of the protein we have utilized the native form of the amino-terminal part of the protein for raising this antibody. To be honest, this antibody has been raised in order to be utilized in ChIP-seq experiments since no commercially available antibody is of high quality for this approach. Moreover, the original Figure 1a was utilized in order to provide an overview of the SATB1 protein structure which is highly relevant to understand its biophysical properties and not for presenting the strategy for raising a custom-made antibody for SATB1.

      1. Fig 3e: what is the control used here? In their Pearson correlation analysis, there seem to be significant reduction in control sets as well upon treatment. This needs to be clarified.

      We used scans rotated by 90° which served as a negative control, as stated in Line 769: “SATB1 scans rotated by 90° served as a negative control for the colocalization with FU.” Note that this is a commonly used control in colocalization experiments as described for example in Dunn et al., 2011 (https://doi.org/10.1152/ajpcell.00462.2010).

      Additionally, we provide Costes’ P values which are based on randomly scrambling the blocks of pixels (instead of individual pixels, because each pixel’s intensity is correlated with its neighboring pixels) in one image, and then measuring the correlation of this image with the other (unscrambled) image. Please see Costes et al., 2004 (https://doi.org/10.1529%2Fbiophysj.103.038422) for more details. Moreover, it was actually anticipated to see a decrease in colocalization upon hexanediol treatment even in the negative control, as hexanediol significantly reduces both SATB1 and FU speckles as established in Fig. 3a-d.

      1. Pg 10, the authors claim that '..., thus we reasoned that it may also be used to study phase separation...' But there have been numerous reports starting from 2018, which have utilized this technique in corelation to phase behaviour (albeit individual proteins). The authors should include proper citations as they are extending an idea from the same field to their specific need.

      In the revised version of the manuscript, we included relevant citations to support the use of Raman spectroscopy in LLPS research: “Raman spectroscopy was already used in many biological studies, such as to predict global transcriptomic profiles from living cells42, and also in research of protein LLPS and aggregation43–47. Thus we reasoned that it may also be used to study phase separation in primary T cells.” (Lines 225-228)”

      1. For Fig 5b, there should be a comparative image for 'short' isoform.

      In the revised Figure 5c we have included a comparative image for the short SATB1 isoform.

      1. In the context of Figure 5c, the authors claim ...' Note also the higher LLPS propensity of the human long SATB1 isoform compared to the murine SATB1...' Why suddenly human and mouse comparisons are drawn? This figure should be moved to supplementary.

      The comparison between the human and mouse SATB1 isoforms has been implemented because it is relevant for our claims regarding the increased SATB1 aggregation in human cells in relation to the revised Fig. 6f,g,h and Supplementary Fig. 6c,d. This is also discussed in Lines 479-482, which read: “This is particularly important given the higher LLPS propensity of the human long SATB1 isoform compared to the murine SATB1 (Fig. 5d). Therefore, human cells could be more susceptible to the formation of aggregated SATB1 structures which could be associated with physiological defects.”

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

      Zelenka et al., focus on a T cell genome-organizing protein, SATB1, to show that SATB1 undergoes liquid liquid phase-separation (LLPS), and distinct isoforms confer different LLPS-related biophysical properties. They generate a long-isoform specific antibody and conduct several experiments to test for LLPS and compare LLPS properties between the long-isoform relative to the whole SATB1 protein population. Given that SATB1 plays important roles in T cell development and in cancer, interrogating SATB1 biophysical properties is an important question. However, there are multiple problems with the experimental setup and data that weaken their support of the conclusions. I will detail some of the major issues below:

      Regarding phase-separation There are several assays to determine whether a protein undergoes LLPS. 1. One of the first the authors address is the spherocity or roundness. Indeed, formation of spherical droplets is one evidence of the liquid nature of a protein. However, the authors use fixed preparations (which can introduce artifacts), not free-floating protein, and determine roundness by showing a 2D image. Roundness should take into account the diffraction-limits of fluorescent imaging, as many structures can be imaged to appear round by the detector. There are quantifiable measurements that can be taken on 3D images to show roundness. This would best be shown using non-fixed protein.

      • We thank this Reviewer for several insightful comments. Although, we agree with most of them, we should highlight the main goal of our manuscript, i.e. to investigate the SATB1 protein with an emphasis on its physiological roles in primary developing murine T cells. We highlight this already in the introduction in Line 64 “In this work, we utilized primary developing murine T cells,...” and mainly also in the respective part of the result section: “To probe differences in phase separation in mouse primary cells, without any intervention to SATB1 structure and expression, we first utilized 1,6-hexanediol treatment, which was previously shown to dissolve the liquid-like droplets34.(Lines 203-205)”

      • We believe that this is a very important aspect of our study that should not be overlooked. The majority of proteins perhaps behave differently under physiological and in vitro conditions. However, due to the extensive post-translational modifications affecting the properties of SATB1, its completely different localization patterns between primary developing T cells and other cell types but especially cell lines and many other aspects, it was of utmost importance to focus our research on primary T cells. Unfortunately, this was accompanied with multiple difficulties, such as that we have to use fixed cells as this is the only way to visualize SATB1 in these cells. Alternatively, one could create a new mouse line expressing a fluorescently tagged SATB1 protein, but this is beyond the scope of our work.

      • However, we should also note that many LLPS-related studies do not pay any focus on primary physiological functions of proteins and they simply focus on the investigation of protein’s artificial behavior in in vitro conditions. Having said that, we too extended our experiments in primary cells to the ex vivo studies in cell lines to further support our claims. In these experiments, we utilized live cell imaging in Fig. 4-6, quantified the spherocity in Supplementary Fig. 6, showed the ability of speckles to coalesce in Fig. 4c and also used FRAP in Fig. 4f and also in the revised version of the manuscript in Supplementary Figure 6f. Moreover, we should note that most of these experiments were designed and performed during 2017 and 2018 conforming with the standards. We are well aware of the progress in the field and impact of fixation on LLPS, as described in Irgen-Gioro et al., 2022 (https://doi.org/10.1101/2022.05.06.490956), but after over seven months of review process in another journal we also believe that these aspects should be considered not to delay further progress of the SATB1 field.

      Regarding the isoform specificity of SATB1 biophysical properties 1. The authors generate a long isoform-specific antibody. However, the western blot is not convincing that this is indeed specific to the long isoform as there is a rather large smear. Can this be improved with antibody preabsorption? Since this is a key reagent for the manuscript, improvement in antibody quality is essential.

      The custom-made antibody for the long isoform has been raised against the unique 31 amino acids long peptide present in the long SATB1 isoform. The polyclonal serum has undergone affinity chromatography utilizing the immobilized peptide (antigen) to purify the antibody. In the revised version of the manuscript we have included another immunodepletion experiment with cleaner bands (Fig. 1f). Moreover, please read our answer to Major comment #2 of Reviewer 1 that follows: • The long antibody was raised in mice inoculated with the extra peptide present in the long isoform only. Therefore, the capacity of this antibody precipitating the shorter isoforms, which do not express the sequence of the extra peptide (EP, Figure 1a) in not possible.

      • We have repeated the immunodepletion experiment and we now provide the results in Fig. 1f and Supplementary Fig. 1b. The western blot in Fig. 1f is now cleaner and supports quite convincingly the presence of a long SATB1 isoform. Given the lack of isoform-specific knockouts which we could utilize to immunoprecipitate or detect the different isoforms in a single cell (or cell population), the utilized approach of immunodepletion and subsequent western blotting is the approach we thought of implementing.

      • As shown in Fig. 1f and Supplementary Figure 1b, the long isoform SATB1 antibody has the capacity to recognize the long isoform in murine thymocyte protein extracts but not the short SATB1 isoform (please compare lane 3 in the two western blots utilizing either the antibody for the long isoform -top panel - or the antibody that detects both isoforms (lower panel).

      • We have performed Immunofluorescence experiments utilizing the antibody detecting the long SATB1 isoform in thymocytes isolated from either C57BL/6 or Satb1 cKO mice. The antibody is specific to the SATB1 protein since there is no signal in immunofluorescence experiments utilizing the knockout cells (Supplementary Figure 1c).

      • We have performed Immunofluorescence experiments utilizing thymocytes and the antibody detecting the long SATB1 or a commercially available antibody detecting all SATB1 isoforms. The pattern of SATB1 subnuclear localization is similar for both antibodies (Supplementary Figure 1e).

      • In our accompanying revised manuscript Zelenka et al., 2022 (https://doi.org/10.1101/2021.07.09.451769), we provide yet another piece of evidence, consisting of bacterially expressed short and long SATB1 protein isoforms detected by western blot using either the long isoform-specific or the non-selective all SATB1 isoforms antibodies.

      • Regarding the additional bands detected in the immunoprecipitation experiment presented in the original Supplementary Figure 1b (lane 2), it is not surprising that additional bands appear in a sample of protein extracts that is used for several hours for the immunoprecipitation experiments, while the “input” sample simply denotes protein extract that is frozen at -80oC right after the preparation of protein extracts until use. It is well-established that SATB1 is the target of proteases which might as well be active during the immunoprecipitation steps (2 consecutive immunoprecipitation steps take place). Therefore, the immunoprecipitated material cannot necessarily be a copy of the input material displaying a single protein band even if protease inhibitors are included in the buffers.

      Taken together the experiments described here we showed that the antibody raised against the extra 31 aa long peptide, present only in the long SATB1 isoform, is specific for this isoform.

      1. Fig 4 Optodroplet experiment appears to show that the N-terminus of SATB1 can undergo LLPS. The results of this assay show that SATB1 has a domain that can undergo phase-separation in isolation, but it does not show that the protein itself is a phase-separating protein. The FRAP assay methods are not provided by the authors, but this is important, as continued light activation means proteins are continuously forming aggregates, and the bleaching for FRAP should be balanced with the levels of Cry2 activation. A very good description of the methods is described in the original Optodroplet paper: https://www.sciencedirect.com/science/article/pii/S009286741631666X?via%3Dihub#sec4

      We should note that we did follow the FRAP protocol provided by the recommended study Shin et al., 2017 (https://doi.org/10.1016/j.cell.2016.11.054). Indeed, these experiments are very tricky to perform and interpret, as every cell expresses slightly different amounts of protein which is directly associated with the different speed of optoDroplet formation, and thus its propensity to aggregate upon overactivation. On the other hand, there need to be continuous activation during the FRAP experiment as the lack of activation laser would result in fast disassembly of the optoDroplets, counteracting the FRAP results. Moreover, the optoDroplets actively move around the cell in all dimensions which makes the accurate measurement of signal intensity really challenging, even with an adjusted pinhole. Therefore, we do not think that FRAP is the best approach to examine the behavior of optoDroplets.

      Either way, we have now described the detailed FRAP protocol in Lines 889-898, which read: “For the FRAP experiments, cells were first globally activated by 488 nm Argon laser illumination (alongside with DPSS 561 nm laser illumination for mCherry detection) every 2 s for 180 s to reach a desirable supersaturation depth. Immediately after termination of the activation phase, light-induced clusters were bleached with a spot of ∼1.5 μm in diameter. The scanning speed was set to 1,000 Hz, bidirectionally (0.54 s / scan) and every time a selected point was photobleached for 300 ms. Fluorescence recovery was monitored in a series of 180 images while maintaining identical activation conditions used to induce clustering. Bleach point mean values were background subtracted and corrected for fluorescence loss using the intensity values from the entire cell. The data were then normalized to mean pre-bleach intensity and fitted with exponential recovery curve in Fiji or in frapplot package in R.”

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

      **Reviewer #1**:

      Can they use the all and long isoform antibodies together, then subtract the signal from long isoform to conclude about the localization of the shorth isoform ?

      We thank the Reviewer for the suggestion, though given the differential efficiency of antibodies and other limitations of imaging experiments, we do not find the suggested experiment to have a potential to improve the quality of our manuscript. However, we should note that we have performed a pixel-based colocalization experiment between the signal detected by all isoform and long isoform SATB1 antibodies. Fluorocytogram of the pixel-based colocalization, based on 3D-SIM data is provided on the left, with quantified colocalization on the right of the revised Supplementary Fig. 5a.

      3) Lack of better staining with antibody against the long and short SATB1 isoforms after treatment with 1,6 Hexanediol. 1,6 Hexanediol treatment can change many other chromatin associated proteins to which SATB1 can be bound to indirectly. This experiment can

      We do understand the controversy and difficulties of experiments using 1,6-hexanediol treatment. However, we have to note that there is no better approach available for the investigation of LLPS in our primary murine T cells. We did use alternative approaches in ex vivo experiments, utilizing cell lines to validate our hypothesis without the involvement of 1,6-hexanediol.

      **Reviewer #2**:

      1. The authors mention, '...of the different SATB1 isoforms, uncovered by the use of the two different antibodies, relied in the heterochromatin areas (zone 1), where the long isoform was less frequently...' There is no supporting figure number mentioned. The authors need to show a zone-by-zone comparison images for 'all iso' vs 'long' iso of SATB1. Just to reiterate, there is a need for a heterochromatin mark to unambiguously call out the distinction.

      We should remind that there is an inherent difficulty to accurately compare localization of short and long SATB1 isoforms in primary cells, especially due to the lack of Satb1 isoform-specific knockout mice. There is no way to detect only the short isoform in these primary cells as there are only antibodies targeting the long or all SATB1 isoforms. Therefore, we cannot set up additional experiments probing these questions.

      In line with this, in the revised version of the manuscript, we toned down our statements regarding the differential localization of the two isoforms in primary cells. We only refer to it as an indication and we support it by adding references to the relevant figures. This part now reads: “Localization of SATB1 speckles detected by antibodies targeting all SATB1 isoforms and/or only the long SATB1 isoform, revealed a significant difference in the heterochromatin areas (zone 1, Fig. 2b), where the long isoform was less frequently present (see also Fig. 2a and Fig. 3c). Although, this could indicate a potential difference in localization between the two isoforms, due to the inherent difficulty to distinguish the two based on antibody staining, we refrain to draw any conclusions. (Lines 145-150)”

      1. Fig. 6a, The authors wished to see the effect of RNA on Satb1 nuclear localization. This is not related to the main theme of the paper, thus should be moved to supplementary (true for b as well). Importantly, the experiments should be performed with total cells to show the divergence of localization (like the paper the authors referred to) instead of matrix for clarity.

      • We did not wish to see the effect of RNA on SATB1 localization. In fact, there is a long history of SATB1 research that is inherently linked with the concept of nuclear matrix, a putative nuclear structure which is highly associated with nuclear RNAs. SATB1 was described many times as a nuclear matrix protein (https://doi.org/10.1016/0092-8674(92)90432-c; https://doi.org/10.1128/mcb.14.3.1852-1860.1994; https://doi.org/10.1074/jbc.272.17.11463; https://doi.org/10.1128/mcb.17.9.5275; https://doi.org/10.1021/bi971444j; https://doi.org/10.1083/jcb.141.2.335; https://doi.org/10.1101/gad.14.5.521; https://doi.org/10.1038/ng1146).

      • Moreover, our data discussed in comments 4-7 of this Reviewer, such as i. the localization of SATB1 to the nuclear zones associated with RNA and nuclear scaffold factors (Fig. 2b, Supplementary Fig. 1c), ii. colocalization of SATB1 with actively transcribed RNAs (Fig. 2c, Fig. 3g, Supplementary Fig. 2a, Supplementary Fig. 2c), iii. including its association with nucleoli (Supplementary Fig. 3b), and also iv. its computationally predicted interaction with Xist lncRNA (Agostini et al., 2013; https://doi.org/10.1093/nar/gks968) as a notable factor of nuclear matrix, all suggest that the interaction between RNA and SATB1 is plausible and potentially relevant for its function and/or at least its subnuclear localization. It is relevant even more so, when considering numerous reports on the ability of RNA-binding, poly-Q and PrLD-containing proteins to undergo LLPS https://doi.org/10.1016/j.molcel.2015.08.018; https://doi.org/10.1042/bcj20160499; https://doi.org/10.1016/j.cell.2018.03.002; https://doi.org/10.1016/j.cell.2018.06.006; https://doi.org/10.1093/nar/gkaa681), including RNAs specifically regulating LLPS behavior, especially for poly-Q and PrLD-containing proteins, such as SATB1 (https://doi.org/10.1126/science.aar7366; https://doi.org/10.1126/science.aar7432; https://doi.org/10.1016/j.ceb.2019.03.007; https://doi.org/10.1038/s41598-020-57994-9; https://doi.org/10.1016/j.molcel.2015.09.017; https://doi.org/10.1038/s41598-019-48883-x; https://doi.org/10.1038/s41467-019-11241-6).

      • It should also be noted that SAF and various hnRNPs, as the most prominent proteins of nuclear matrix were many times reported to phase separate (https://doi.org/10.1016/j.molcel.2019.10.001; https://doi.org/10.1074/jbc.ra118.005120; https://doi.org/10.1016/j.celrep.2019.12.080; https://doi.org/10.1038/s41467-019-09902-7; https://doi.org/10.1016/j.molcel.2017.12.022; https://doi.org/10.1074/jbc.tm118.001189). All these aspects show that the relation between nuclear matrix, SATB1 and RNA are quite relevant to our manuscript.

      • Moreover, in light of the aforementioned information, we believe that it is much clearer to follow the protocol we did – i.e. to remove soluble proteins by CSK treatment and then, upon RNase treatment, extract the released proteins using ammonium sulfate. In an experiment utilizing whole cells, one would need to microinject RNase A into the nucleus, which 1. is very challenging for primary T cells having a radius of 3-5 micrometers, 2. is of low throughput, 3. would not allow for released protein removal which would thus make the results hard to interpret. Please note that in the reference paper, the authors used cell lines overexpressing heterologous GFP-tagged proteins, which is not related to our setup.

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

      Reply to the Reviewers

      I thank the Referees for their...

      Referee #1

      1. The authors should provide more information when...

      Responses + The typical domed appearance of a hydrocephalus-harboring skull is apparent as early as P4, as shown in a new side-by-side comparison of pups at that age (Fig. 1A). + Though this is not stated in the MS 2. Figure 6: Why has only...

      Response: We expanded the comparison

      Minor comments:

      1. The text contains several...

      Response: We added...

      Referee #2

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

      Learn more at Review Commons


      Referee #1

      Evidence, reproducibility and clarity

      This paper looks at in important nuclear matrix protein SATB1, which is a well known global chromatin organizer and help chromatin loop attach to the nuclear matrix. The paper starts with identification of novel short and long form of SATB1. Both the isoform consist of a prion like low complexity domains, but the long isoform additionally contain an extra EPF domain next the Prion like low complexity domain. The paper reports that in murine cells the long isoform is 3-4 fold more abundant than the short isoform. By using STED microscopy they show SATB1 foci lie next to transcription sites in the nucleus. They conclude by looking at the spherical shape of the SATB1 foci and the susceptibility of SATB1 staining after 1,6 hexanediol treatment that SATB1 forms the small foci in the nucleus due to LLPS. The authors also use RAMAN spectroscopy to conclude a change in nuclear chemical space in absence of SATB1 but without much explanation about which chemical bond or nuclear sub structure change correspond to the change in principal component analysis from Raman spectroscopy. The authors use the light inducible aggregation cyr2 tag with the PrD domain of SATB1 and compare it with the Cry2-FUS-LC domain to conclude that the SATB1 LC domain can undergo LLPS. The authors hint at involvement of RNA and also DNA in the LLPS of the SATB1 but without going into any detail.

      The key conclusions of the paper are- A) SATB1 undergoes LLPS. But this conclusion is drawn after correlative experiments as detailed below-

      1. observation of spherical punctae by STED-which could also seem spherical due to their small size. The resolution limit achieved by the STED microscopy used in this paper is not determined or mentioned clearly.
      2. No live cell FRAP experiment with fluorescent SATB1 long or short isoform to show that these foci are liquid like
      3. Lack of better staining with antibody against the long and short SATB1 isoforms after treatment with 1,6 Hexanediol. 1, 6 Hexanediol treatment can change many other chromatin associated proteins to which SATB1 can be bound to indirectly. This experiment can
      4. Lack of in vitro reconstitution experiments with purified long and short SATB1
      5. LLPS is strongly coupled to the cellular concentration of the proteins. Authors should quantify the cellular concentration of the long and short isoform in the cells.

      Major conclusion B)- SATB1 regulates transcription and splicing.

      This was also shown previously and in this paper they show the close proximity of the transcription site and SATB1 foci by microscopy. Hexanediol tretamnt which lead to loss of colocalization between FU foci and SATB1 is also taken as an evidence in regulation of transcription is not right as the transcription foci itself can be dissolved using 1,6 Hexanediol. Although the rate of transcription is not measured quantitatively.

      Major conclusion C)-Post transcriptional modification is important for SATB1 function.

      This point is just barely touched upon in the last figure of the paper

      Overall I find that the major conclusion-point A and B , is based on very indirect experiments and needs much more convincing data and the role of SATB1 LLPS in cells should be demonstrated more rigorously. And conclusion C is barely described and needs a lot more cell biological and genetic evidence.

      I do not recommend publishing the paper in current state. The story needs much more experiment to convincingly prove the major conclusions. Further, the MS needs more careful thinking and presentation to make it streamlined.

      Minor comments:

      One of the major flaw of the paper is the use too many techniques without proper explanation. E.g. use of STED and RAMAN microscopy need controls and explanation on what is being quantified. The use of Raman microscopy to quantify the nuclear environment of nucleus is not related to the chromatin organization or LLPS of SATB1 at all. And no information is provided at all which aspect of nuclear organization is being measured in Raman and what it means for the LLPS of SATB1.

      Similarly for Hexanediol treatment, duration of treatment is missing. Hexanediol can also dissolve the liquid like transcription foci. And hence a decrease in correlation between SATB1 foci and FU foci cannot be taken as a measure of SATB1 foci connection to transcription alone

      It is not very clear how many times the STED or Raman microscopy is done on how many samples and biological replicates. Similarly for RNA sequencing number of samples and description of controls are missing. Also if the sequencing data is made publicly available is not clear.

      Can they use the all and long isoform antibodies together, then subtract the signal from long isoform to conclude about the localization of the shorth isoform ?

      Additional control is needed to report the resolution limit of Superresolution techniques-STED and 3D-SIM systems used by them.

      Would be very helpful if the zonation was plotted for the FluoroUridine(FU) also to show that Zone1 (heterochromatin) is completely depleted of FU, and is present in other regions.

      Scale bar needed figure 3d

      Perfectly rounded SATB1 foci- this does not mean LLPS. For LLPs measurement, protein condensate dynamics measurement by FRAP or fusion experiments is required. What is the size of condensates? and cellular concentration of SATB1 ? Will SATB1 undergo LLPS in vitro at similar concentrations? does SATB1 interact with DNA or RNA to undergo LLPS ?

      After careful reading of the MS I conclude that the main conclusions of the paper are very preliminary and need much more detailed experiments. So does not qualify to get published at all at this stage.

      Significance

      The present manuscript tries to connect the phase separation of SATB1 to understanding the mechanism of SATB1 function in cells. One of the major hallmarks of phase separation is dynamic, liquid-like behaviour and in absence of these measurements, it is very difficult to say that the current manuscript has made any contribution to showing that SATB1 can phase separate.

      The presence of 2 isoforms of SATB1 is a novel finding and the paper could have focussed more on this. E.g. elucidate expression of the isoform during thymocyte development and maturation.

      As a reviewer my expertise are cell biology experiments, microscopy, in vitro reconstitution assays, RNA binding proteins, RNA and RBP condensate formation. And I feel that the reconstitution experiments are an important tool for understanding phase behaviour of proteins and also to gauge if this behaviour can occur or not in cellular concentration and conditions. I do not have sufficient expertise in Raman microscopy and hence the information provided in the MS on this part was not enough to understand the experiment and conclusions drawn from it.

    1. automatically tag some of it as important

      For Outlook, the Flag for Follow-up feature could prove as an equivalent. Atm, there is no AI/Auto prioritization, but this can be achieved using Filters.

    1. Reviewer #2 (Public Review):

      Here Wang et al have studied the role of the actin cytoskeleton in Trichomonas vaginalis pathogenicity with a focus on understanding the role of the actin cytoskeleton in transitioning from fast-moving flagellates to adherent ameboid cells. Intriguingly they determined that the adherent TH17 strain contains more actin and the actin-bundling protein alpha-actinin than the less adherent T1 strain. The adherent strain more readily morphs into the adherent ameboid form which has more polymerized F-actin than the flagellated form. Disruption of actin polymerization with LatB prevents ameboid morphogenesis and blocks adhesion. Although LatB treatment interferes with adhesion the authors show that their relatively short LatB treatments do not alter the distribution of adhesive molecules such as AP, PFO, and CLP on the cell surface.

      To understand how actin is being regulated in T. vaginalis the authors pulldown HA-tagged Tvactin and identify interacting partners with mass spectroscopy. They identify TVAG_47023 as a potential protein of interest due to homology with capping protein and name this protein TvFACP. The authors demonstrate that TvFACP can IP actin from cell extracts. They then proceed to purify His-TvFACP and GST-Tvactin to demonstrate direct interaction. Their approach of using bacterial-expressed actin is non-conventional since it is well known that eukaryotic actin requires several chaperones not present in prokaryotes for proper folding. As expected Tvactin was insoluble and was found in inclusion bodies. The authors used urea to solubilize the protein some of which re-folded into soluble protein after buffer exchange. A major concern with this experiment is that the authors did not use any other assay to confirm that their bacterially expressed actin behaved as expected. They should have verified filament formation by negative EM staining or labeled some of the actin for TIRF microscopy assays. Additionally, the 26 kD GST tag has the potential to interfere with actin dynamics which is why most studies remove affinity tags. Alternatively, the authors could have tested binding with commercially available actin. The authors then proceeded to use the purified components to determine the Kd for Tvactin and TvFACP. Intriguingly the authors determine the Kd is lower for G-actin than F-actin indicating that TvFACP preferentially binds to non-filamentous G-actin which is in contrast to canonical capping protein. However, since the quality of this actin is not verified it is not clear that the assay results can be trusted. Despite the preferential association of TvFACP for G-actin in the in vitro assays, localization studies indicate that TvFACP is associated with phalloidin stained structures which indicates that there is an association of TvFACP with filamentous actin structures. Overexpression of TvFACP reduces the ratio of polymerized to unpolymerized actin.

      The authors then explore whether TvFACP might have a role in regulating the transition between flagellated trophozoites and ameboid trophozoites. It was determined that TvFACP has a role in preventing F-actin formation in flagellates. The authors then determined that Ser2 is a phosphosite that regulates the association of TvFACP with actin. An S2A mutant that cannot be phosphorylated associates with actin and prevents ameboid morphogenesis while an S2D mutant does not associate with actin or alter morphogenesis. Since TvFACP S2 is a predicted Casein kinase II (CKII) phosphorylation site, the authors tested the ability of the CKII inhibitor TBB to alter phosphorylation and the association of TvFACP with actin. They found that TBB inhibited phosphorylation and increased the association of TvFACP with actin consistent with the S2A point mutation. Although the result is consistent with the alanine and phosphomimetic mutants, the authors used 250uM of inhibitor which could certainly result in off-target results. As a point of comparison, the IC50 for TBB is reported to be 0.5 uM so here the inhibitor was used at 500x the reported IC50, and at this high level the reduction in phosphorylation may be non-specific for CKII.

      Overall, the results of the manuscript align to support a role for TvFACP in regulating morphogenesis between fast swimming flagellated trophozoites and slow crawling adherent ameboid trophozoites and points toward a potential signaling pathway that regulates this transition. However, in addition to the two technical issues raised above, the relationship between TvFACP and its binding to F- and G- actin remains incompletely resolved. To determine if Tv F-actin capping protein truly binds F-actin the authors should perform TIRF microscopy to determine if TvFACP would be found at the end of filaments and also reveal the extent to which TvFACP alters actin organization and dynamics.

    1. Author Response

      Reviewer 2

      The manuscript by Huisjes et al presented an open-source platform for the storage and processing of imaging data, particularly for single-molecule imaging experiments. Compared to sequencing data, which have a more standardized format for data storage, imaging data have more diverse formats due to the fact that different research labs tend to use different instruments and software (either commercial or home-built) for data collection and analysis. Manual input is almost always necessary at certain steps of data analysis. All these create difficulties in data storage and reproducibility. The authors provide a practical solution to this problem by the molecular archive suite, "Mars". This platform is integrated into imageJ/Fiji, and can be used for storing detailed description of experimental settings, performing standard imaging processing steps, and recording manual input information during data analysis. I judge this platform, if fully functional and generalizable, will be very useful to many labs who are using single-molecule imaging methods in the research.

      Strength:

      1. The work presented a fairly user friendly interface (using Fiji directly), and fairly detailed protocol and other documentations in a very nicely designed website. I was able to download and use it based on the tutorial.

      2. It is integrated very well with Fiji, and some analysis modules are directly from existing Fiji analysis/plugins.

      Weakness:

      I invited one of my students to co-test the suite. We tried on both Mac and Windows systems, using the example FRET data set described in the manuscript and one of our own single-molecule images. We encountered some technical issues.

      We are very happy with the overall positive assessment of the reviewer that Mars could offer a common format that helps to enforce reproducible analysis workflows that can easily be shared with others.

      We are grateful for the additional feedback and testing done by the reviewer and her student. Ensuring that Mars works as expected on all computers and configurations is difficult given that we don’t have them at hand for testing ourselves. During the revision period, we have done more testing on more computer systems and we hope we have addressed the issues. We believe it will be impossible for us to guarantee that Mars works without problems on the first try for everyone. Therefore, Mars is a community partner on the Scientific Community Image Forum where users can report their problems in posts with the mars tag and we can help troubleshoot them (https://forum.image.sc/tag/mars). We believe this approach will offer the best support going forward. Nevertheless, we continue to make improvements and test to make sure all bugs we discover are addressed.

      In the revision, we completely reworked the smFRET example workflow and added two additional workflows to address all the comments from the reviewers and reviewing editor. In addition to expanding the explanations, and troubleshooting information on the Mars documentation website, we also created a YouTube channel with tutorial and example videos (https://www.youtube.com/channel/UCkkYodMAeotj0aYxjw87pBQ). We go through the new dynamic smFRET workflow from start to finish in one of the videos provided (https://www.youtube.com/watch?v=JsyznI8APlQ). We hope this will make it clear what inputs and outputs are expected and how the workflow should proceed. This was done on a mac but we have also tested this workflow on windows without encountering problems.

  2. Jul 2022
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Your email has been sent by Franklin Okeke in Developer on July 7, 2022, 7:48 AM PDT The 12 best IDEs for programming IDEs are essential tools for software development. Here is a list of the top IDEs for programming in 2022. Image: Chaosamran_Studio/Adobe Stock Software developers have battled with text editors and command-line tools that offered little or nothing in the automation, debugging and speedy execution of codes. However, the software development landscape is rapidly changing, and this includes programming tools. To accommodate the evolution in software development, software engineers came up with more sophisticated tools known as integrated development environments. To keep up with the fast pace of emerging technologies, there has been an increasing demand for the best IDEs among software development companies. We will explore the 12 best IDEs that offer valuable solutions to programmers in 2022. Jump to: What is an IDE? The importance of IDEs in software programming Standard features of an IDE Classifications of IDEs Best IDEs for programmers Factors to consider when picking an IDE What is an IDE? IDEs are software development tools developers use to simplify their programming and design experience. IDEs come with an integrated user interface that combines everything a developer needs to write codes conveniently. The best IDEs are built with features that allow developers to write and edit code with a code editor, debug code with a debugger, compile code with a code compiler and automate some software development tasks. SEE: Hiring kit: Back-end Developer (TechRepublic Premium) The best IDEs come with class browsers to examine and reference properties, object browsers to investigate objects and class hierarchy diagrams to see object-oriented programming code. IDEs are designed to increase software developer productivity by incorporating close-knit components that create a perfect playground where they can write, test and do whatever they want with their code. Why are IDEs important in software programming? IDEs provide a lot of support to software developers, which was not available in the old text editors. The best IDEs around do not need to be manually configured and integrated as part of the setup process. Instead, they enable developers to begin developing new apps on the go. Must-read developer coverage The 12 best IDEs for programming Best DevOps Tools & Solutions 2022 CI/CD platforms: How to choose the right system for your business Hiring kit: Python developer Additionally, since every feature a programmer needs is available in the same development environment, developers don’t have to spend hours learning how to use each separately. This can be extremely helpful when bringing on new developers, who may rely on an IDE to familiarize themselves with a team’s standard tools and procedures. In reality, most IDE capabilities, such as intelligent code completion and automatic code creation, are designed to save time by eliminating the need to write out entire character sequences. Other standard IDE features are designed to facilitate workflow organization and problem-solving for developers. IDEs parse code as it is written, allowing for real-time detection of human-related errors. As such, developers can carry out operations without switching between programs because the needed utilities are represented by a single graphical user interface. Most IDEs also have a syntax highlighting feature, which uses visual clues to distinguish between grammar in the text editor. Class and object browsers, as well as class hierarchy diagrams for certain languages, are additional features that some IDEs offer. All these features help the modern programmer to turn out software development projects fast. For a programming project requiring software-specific features, it’s possible to manually integrate these features or utilities with Vim or Emacs. The benefit here is that software developers can easily have their custom-made IDEs. However, for enterprise uses, the above process might take time and impact standardization negatively. Most enterprises encourage their development teams to go for pre-configured IDEs that suit their job demands. Other benefits of IDEs An IDE serves as a centralized environment for the needs of most software developers, such as version control systems, Platform-as-a-Service and debugging tools. An IDE improves workflow due to its fast code completion capabilities. An IDE automates error-checking on the fly to ensure top-quality code. An IDE has refactoring capabilities that allow programmers to make comprehensive and renaming changes. An IDE ensure a seamless development cycle. An IDE facilitates developer efficiency and satisfaction. Standard features of an IDE Text editor Almost all IDEs will offer a text editor made specifically for writing and modifying source code. While some tools may allow users to drag and drop front-end elements visually, the majority offers a straightforward user interface that emphasizes language-specific syntax. Debugger Debugging tools help developers identify and correct source code mistakes. Before the application is published, programmers and software engineers can test the various code parts and find issues. Compiler The compiler feature in IDE assists programmers in translating programming languages into machine-readable languages such as binary code. The compiler also helps to ensure the accuracy of these machine languages by analyzing and optimizing them. Code completion This feature helps developers to intelligently and automatically complete common code components. This process helps developers to save time and reduces bugs that come from typos. Programming language support Although some IDEs are pre-configured to support one programming language, others offer multi-programming language support. Most times, in choosing an IDE, users have to figure out which programming languages they will be coding in and pick an IDE accordingly. Integrations and plugins Integration capability is one feature that makes an IDE stand out. IDEs support the integration of other development tools through plugins to enhance productivity. Classifications of IDEs IDEs come in different types and according to the programming languages they support. While some support one language, others can support more than one. Multi-language IDE Multi-language IDEs are IDE types that support multiple programming languages. This IDE type is best suited for beginner programmers still at the exploration stage. An example of this type of IDE is the Visual Studio IDE. It’s popular for its incredible supporting features. For example, users can easily code in a new programming language by adding the language plugin. Mobile development IDE As the market for mobile app development grows, numerous programming tools are becoming available to help software developers build efficient mobile apps. Mobile development IDEs for the Android and iOS platforms include Android Studio and Xcode. Web/cloud-based IDE If an enterprise supports a cloud-based development environment, it may need to adopt a cloud-based IDE. One of the advantages of using this type of IDE is that it can run heavy projects without occupying any computational resources in a local system. Again, this type of IDE is always platform-independent, making it easy to connect to many cloud development providers. Specific-language IDE This IDE type is a typical opposite of the multiple-language IDE. They are specifically built to support developers who work on only one programming language. Some of these IDEs include Jcreator for Java, Idle for Python and CodeLite for C++. Best IDEs for programmers in 2022 Visual Studio Microsoft Visual Studios The Visual Studio IDE is a Microsoft-powered integrated development interface developed to help software developers with web developments. The IDE uses artificial intelligence features to learn from the edit programmer’s make to their codes, making it easy for it to complete lines of code automatically. One of the top features many developers have come to like about Visual Studio is that it aids collaborative development between teams in live development. This feature is very crucial, especially during the debugging process. The IDE also allows users to share servers, comments and terminals. Visual Studio has the capability to support mobile app, web and game development. It also supports Python language, Node.js, ASP.NET and Azure. With Visual Studio, developers can easily create a development environment in the cloud. SEE: Hiring kit: Python developer (TechRepublic Premium) With its multi-language support, Visual Studio has features that integrate flawlessly with Django and Flask frameworks. It can be used as an IDE for Python on the Mac, Windows and Linux operating systems. IntelliJ IDEA IntelliJ IDEA IntelliJ Idea has been around for years and has served as one of the best IDEs for Java programming. The IntelliJ Idea UI is designed in a sleek way that makes coding appealing to many Java developers. With this IDE, code can get indexed, providing relevant suggestions to help complete code lines. It also takes this suggestive coding further by automating several tasks that may be repetitive. Apart from supporting web, enterprise, and mobile Java programming, it is also a good option for JavaScript, SQL and JPQL programming Xcode Xcode Xcode might be the best IDE tool for Apple product developers. The tool supports iOS app development with its numerous iOS tools. The IDE supports programming languages such as Swift, C++ and Object-C. With XCode, developers can easily manage their software development workflow with quality code suggestions from the interface. Android Studio Android Studio The Android Studio is one of the best IDEs for Android app development. This IDE supports Kotlin and Java programming languages. Some important features users can get from the Android Studio are push alerts, camera integrations and other mobile technology features. Developers can also create variants and different APKs with the help of this flexible IDE, which also offers extended template support for Google Services. AWS Cloud9 IDE AWS Cloud9 The AWS Cloud9 IDE is packed with a terminal, a debugger and a code editor, and it supports popular programming languages such as Python and PHP. With Cloud9 IDE, software developers can work on their projects from almost anywhere in the globe as long as they have a computer that is connected to the internet, because it is cloud-based. Developers may create serverless applications using Cloud9 and easily collaborate with different teams in different development environments. Eclipse Eclipse Eclipse is one of the most popular IDEs. It’s a cross-platform tool with a powerful user interface that supports drag and drop. The IDE is also packed with some important features such as static analysis tools, debugging and profiling capabilities. Eclipse is enterprise development-friendly and it allows developers to work on scalable and open-source software development easily. Although Eclipse is best associated with Java, it also supports multiple programming languages. In addition, users can add their preferred plugins to the IDE to support software development projects. Zend Studio Zend Studio Zend Studio is a leading PHP IDE designed to support PHP developers in both web and mobile development. The tool features advanced debugging capabilities and a code editor with a large community to support its users. There is every possibility that PHP developers will cling to the Zend IDE for a long time as it has consistently proven to be a reliable option for server-side programming. Furthermore, programmers can take advantage of Zend Studio’s plugin integrations to maximize PHP applications’ deployment on any server. PhpStorm PhpStorm PhpStorm is another choice to consider if users use PHP for web development. Although it focuses on the PHP programming language, front-end languages like HTML 5, CSS, Sass, JavaScript and others are also supported. It also supports popular website-building tools, including WordPress, Drupal and Laravek. It offers simple navigation, code completion, testing, debugging and refactoring capabilities. PhpStorm comes with built-in developer tools that help users perform routine tasks directly from the IDE. Some of these built-in tools serve as a version control system, remote deployment, composer and Docker. Arduino IDE Arduino Arduino is another top open source, cross-platform IDE that helps developers to write clean code with an option to share with other developers. This IDE offers both online and local code editing environments. Developers who want to carry out sophisticated tasks without putting a strain on computer resources love it for how simple it is to utilize. The Arduino IDE includes current support for the newest Arduino boards. Additionally, it offers a more contemporary editor and a dynamic UI with autocompletion, code navigation and even live debugger features. NetBeans NetBeans You can’t have a list of the best IDE for web development without including NetBeans. It’s among one of the most popular options for the best IDE because it’s a no-nonsense software for Java, JavaScript, PHP, HTML 5, CSS and more. It also helps users create bug-free codes by highlighting code syntactically and semantically. It also has a lot of powerful refactoring tools while being open source. RubyMine RubyMine Although RubyMine primarily supports the Ruby, it also works well with JavaScript, CSS, Less, Sass and other programming languages. The IDE has some crucial automation features such as code completion, syntax and error-highlighting, an advanced search option for any class and symbol. WebStorm WebStorm The WebStorm IDE is excellent for programming in JavaScript. The IDE features live error detection, code autocompletion, a debugger and unit testing. It also comes with some great integrations to aid web development. Some of these integrations are GitHub, Git and Mercurial. Factors to consider when picking an IDE Programming language support An IDE should be able to support the programming language used in users’ software development projects. Customizable text editors Some IDEs offer the ability to edit the graphical user interface. Check if the preferred IDE has this feature, because it can increase productivity. Unit testing Check if the IDE can add mock objects to some sections of the code. This feature helps test code straight away without completing all the sections. Source code library Users may also wish to consider if the IDE has resources such as scripts and source code. Error diagnostics and reports For new programmers, sometimes it’s good to have an IDE that can automatically detect errors in code. Have this factor in mind if users will need this feature. Code completion Some IDEs are designed to intelligently complete lines of code, especially when it comes to tag closing. If developers want to save some coding time from tag closing, check for IDEs that offer this option. Integrations and plugins Do not forget to check the integration features before making a choice. Code search Some IDEs offer the code search option to help search for elements quickly in code. Look for IDEs that support this productivity feature. Hierarchy diagrams If users often work on larger projects with numerous files and scripts that all interact in a certain way, look for IDEs that can organize and present these scripts in a hierarchy. This feature can help programmers observe the order of file execution and the relationships between different files and scripts by displaying a hierarchy diagram. Model-driven development Some IDEs help turn models into code. If users love creating models for the IDE, consider this factor before choosing an IDE. 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      and seriously you don't mention visual code???

    1. A CMS for hosting, editing and maintaining markdown files AND a hosting service for publishing these as blogs.

      Another solution, in two steps:

      1. make your SOPs executable
      2. give them a promotion; make them first-class content (they should live on the site that you're publishing—although not necessarily front-and-center—not hidden away in the README of some ghost repo)

      See also: A New Publishing Discipline.

    1. To synchronize BMC Helix common services container images

      I've tried to run this section while harbor runs on http. This fails as docker login command is issued and thinks harbor is on SSL.

      The workaround is to do the following

      1. Create 4 replication rules.

      Name ade_part_01 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {4.2.2-debian-10-r50,ade-authz-service-149,ade-file-service-e2830be-7,ade-identity-management-portal-12,ade-identity-management-service-15,ade-notification-service-9,adeops-util-v012,adeops-util-v013,adeops-util-v016,adeops-util-v019,adeops-util-v024,adereporting-21.3.02.02,adereporting-content-e0ab22f-251,adereporting-initdb-v001,adereporting-kafkacli-v002,adereporting-puller-7e41b3d-274,adereporting-renderer-dd91f81-216,adereporting-runner-7e41b3d-274,ade-tenant-management-automation-273,ade-tenant-management-portal-14,ade-tenant-management-service-7,ade-ui-content-service-18,aif-api-service-8150462-9,aif-clustering-ingestion-service-3a4ce1d-12,aif-clustering-query-service-3dfbda3-9,aif-clustering-service-08fa171-9,aif-core-service-fdfb78d-6,aif-incident-ingestion-service-3a0f0e2-8,aif-job-manager-service-ab85bfb-8,aif-machine-learning-utilities-8a08716-57,aif-ticket-service-d71f457-11,anomaly-detection-service-58e6996-5}

      Name ade_part_02 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {authproxy-RSSO_Auth_Proxy_101,authproxy-RSSO_Auth_Proxy_110,authproxy-RSSO_Auth_Proxy_112,authproxy-RSSO_Auth_Proxy_80,bitnami-kafka-2.7.0-debian-10-r124,bitnami-minio-2021.4.18-debian-10-r0,bitnami-zookeeper-3.7.0-debian-10-r25,custom-elasticsearch-1.13.3,custom-postgresql-repmgr-12.9.0,custom-sec-ade-infra-clients-1,custom-sec-redis-5.0.12-alpine,custom-sec-victoriametrics-vminsert-v1.63.0-cluster,custom-sec-victoriametrics-vmselect-v1.63.0-cluster,custom-sec-victoriametrics-vmstorage-v1.63.0-cluster,es-proxy-nginx-service-6d2eb81-6,es-proxy-service-6d2eb81-6,event-ingestion-service-4c0353c-4,event-mgmt-service-fc008be-6,event-processor-service-199851c-10,event-service-a21ce51-7,haproxy-2.0.4,justwatch-elasticsearch_exporter-1.1.0,kibana-proxy-service-c4f46f6-6,kibana-service-c4f46f6-6,kubectl-latest,log-ingestion-service-ff04217-99,log-mgmt-service-ceb53d1-4,log-processing-service-726afae-6,logs-portal-eb0d3a5-8}

      Name ade_part_02 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {metric-aggregation-service-6c4b171-9,metric-configuration-service-2b5ba78-7,metric-gateway-service-4a6caae-8,metricservice-6b50628-8,prometheus-ingestion-service-8659793-7,RSSO_21.3.00-DRRS0-3893,smart-graph-api-r841442-642-daas_ship-tkn_ship,smart-graph-controller-api-r841442-642-daas_ship-tkn_ship,smart-graph-controller-efsinit-r841442-642-daas_ship-tkn_ship,smart-graph-controller-security-r841442-642-daas_ship-tkn_ship,smart-graph-environment-controller-r841442-642-daas_ship-tkn_ship,smart-graph-instance-controller-r841442-642-daas_ship-tkn_ship,tctlrest-14,thirdparty-ingestion-service-6add794-5,truesight-credential-service-267,truesight-featureflag-service-272,0.9.0-debian-10-r35,bitnami-shell-10,bitnami-bitnami-shell-10-debian-10-r61,custom-sec-busybox-1.27.2,webhook-2102_20210218,elasticsearch-7.16.2-debian-10-r0,bitnami-elasticsearch-curator-5.8.4,kibana-7.16.2-debian-10-r0,fluentd-1.12.3-debian-10-r4}

      Name ade_part_02 Source resource registry https://containers.bmc.com Source resource filter Name bmc/lp0lz Source resource filter Tag {ade-ims-webhook-114,ade-itsm-identity-sync-199}

      1. Then you can synchronize them at will
    1. Oh dear, how hard it was to be indifferent like the others! She tried not to smile too much; she tried not to care. But every single thing was so new and exciting...

      Reading this passage reminded me of a young girl getting the chance to tag along with her older sister and friends to a night out - the way she tries to appear nonchalant like the others when everything is "so new and exciting" to her. She might be younger than the other girls, or maybe she is not as wealthy and therefore doesn't participate in these events as often.

    1. Does/did + Subject + verb + object (optional)+ question tag

      This is incorrect! Should be:

      *Do/Does + subject + base verb? *

      Do you like pizza? Does Sam like pizza?

    1. Review coordinated via ASAPbio’s crowd preprint review

      This review reflects comments and contributions by Oana Nicoleta Antonescu, Ruchika Bajaj, Sree Rama Chaitanya and Akihito Inoue. Review synthesized by Ruchika Bajaj.

      This study has characterized the function of Hero proteins in improving the recombinant expression of TAR DNA-binding protein in E. coli and restoration of enzymatic activity of firefly luciferase during heat and stress conditions. This study may be useful for future applications of Hero proteins in life sciences research. Please see below a few points offered as suggestions to help improve the study.

      • In introduction, 3rd paragraph, in context with “amino acid composition and length of Hero proteins”, please elaborate on the effect of these two factors on the function and stability of hero proteins.
      • The manuscript refers to “cis and trans” terms on several occasions. Please explain these terms in context with the association of Hero protein with the target proteins.
      • Introduction - A paragraph describing the origin of Hero proteins and the differences between the types of Hero proteins in the introduction section would be helpful for readers to understand the background on these proteins. For example, please explain the background on naming these proteins as Hero 7, 9, 11 etc. The genes SERF2, C9orf16, C19orf53, etc are mentioned in the plasmid construction section in the Material and methods. Please provide a brief explanation for the relationship between these genes and Hero proteins.
      • Please add more details in the Material and methods section, especifically in western blotting and the luciferase assay, to support the reproducibility of these experiments.
      • Figure 1A. Please explain the role of each component (for example factorXa) either in the text or the legend.
      • Figure 1B: Please add clarification regarding the normalization of lanes by total protein concentration.
      • Fig 1C. Please provide an explanation for the higher order bands in the western blot. The western blot using anti-FLAG antibodies shows non-specific bands. Alternative tags or antibodies or detection methods may be used, for example, GFP tag and in-gel fluorescence can be used to check the expression.
      • Figure 1D and 1E, the error bars are high. Suggest checking the data and providing the mathematical expressions used to calculate relative yields.
      • Figure 2D and E, the error bars are high, access to the raw data behind the graphs may aid interpretation. An explanation for the choice of temperatures 33 C and 37 C would be helpful. Is there any relation between the choice of temperature and the Tm of the protein? The protein is directly being treated at high temperature, similar experiments with cell-based assays would be helpful to understand the effect of the Hero proteins on the stability of Fluc. Would it be possible to report the mathematical expressions used to calculate “Remaining Fluc activity”. Recommend indicating n if these activities are calculated per mg of the protein. Please explain if the reduction in activity is due to loss of protein or loss of luminescence activity from each molecule of the protein.
      • Figure S1, access to the raw data would be helpful to understand the signal to noise ratio for activity.
      • Figure 2 and 3 show similar experiments with wild type and mutants, it may be possible to combine the figures (for example, to avoid the redundancy in Figure 2C and 3A).
      • Figure 3D and G, access to the raw data would be helpful to interpret the signal and noise ratio especially given the low values.
      • Figure 4, Can some further discussion be provided for the reason for higher residual activity for SM and DM than wild type? Tm experiments during stress conditions (heat shock and freeze thaw cycles) may be helpful to define the stability of Fluc and Fluc mutants.
      • Figure 5: Suggest including an explanation for choosing Proteinase K -among other proteases- for these experiments.
      • The residual activity is different in Figure 4 and 5, which could be due to different stress conditions. Please include some discussion about possible explanations.
      • In section “Hero proteins protect Fluc activity better in cis than in trans”, ‘When the molarity of recombinant GST, Hero9, and Hero11 proteins was increased by 10-fold...’ does molarity refer to the concentration of protein ?
      • In the first paragraph of the discussion, “physical shield that prevents collisions of molecules leading to denaturation” and “maintaining the proper folding” is mentioned. Is it the hypothesis for the mechanism behind the stability provided by Hero proteins? Can further discussion on this be provided, along with a relevant reference.
      • In the discussion section, it is mentioned that “Hero may be reminiscent of polyethylene glycol (PEG)”. Please provide further explanation for why hero proteins are correlated with PEG in this fragment.
      • A discussion on why specific Hero proteins may be better for specific target proteins may be helpful.
      • In the second paragraph, of the Discussion “Hero protein can behave differently depending on the client protein and condition” and “important to test multiple Hero proteins to identify one that best protects the protein of interest” are mentioned. Suggest adding further discussion of these points, for example around any alternatives or computational predictions or simulations to test individual Hero proteins for specific client proteins.
    1. He explains the purpose of his "waste book" in his notebook E: Die Kaufleute haben ihr Waste book (Sudelbuch, Klitterbuch glaube ich im deutschen), darin tragen sie von Tag zu Tag alles ein was sie verkaufen und kaufen, alles durch einander ohne Ordnung, aus diesem wird es in das Journal getragen, wo alles mehr systematisch steht ... Dieses verdient von den Gelehrten nachgeahmt zu werden. Erst ein Buch worin ich alles einschreibe, so wie ich es sehe oder wie es mir meine Gedancken eingeben, alsdann kann dieses wieder in ein anderes getragen werden, wo die Materien mehr abgesondert und geordnet sind.[2] "Tradesmen have their 'waste book' (scrawl-book, composition book I think in German), in which they enter from day to day everything they buy and sell, everything all mixed up without any order to it, from there it is transferred to the day-book, where everything appears in more systematic fashion ... This deserves to be imitated by scholars. First a book where I write down everything as I see it or as my thoughts put it before me, later this can be transcribed into another, where the materials are more distinguished and ordered."
    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      __Manuscript number: __RC-2022-01357

      __Corresponding author(s): __Peter Novick and Gang Dong

      1. General Statements [optional]

      We would like to thank both reviewers for their thorough and constructive evaluation and comments on our manuscript. Following their suggestions, we have reworked our manuscript and added several pieces of new data to address questions from them, including (1) evaluation of how M7 mutant of Sso2 affects its interaction with Sec3 using three independent methods (in vitro); (2) investigation of how the M7 mutant affects the interaction of Sso2 with Sec3 by co-immunoprecipitation (in vivo). We hope that, with all these further introduced changes, this manuscript will be suitable for publication in your journal. Detailed point-to-point responses are shown below.

      2. Point-by-point description of the revisions

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

      Using the entire cytoplasmic domain of Sso2 and protein crystallization, Peer and colleagues show that two N-terminal peptides (NPY) of Sso2 synergistically interact with the Sec3 PH domain. This interaction provides an additional low affinity binding site to the previously published interface between the Sso2 four-helix bundle and the PH domain. Mutagenesis, in particular of both NPY motifs, results in reduced cell growth, in the accumulation of transport vesicles at the budding site, and in decreased secretion of invertase and Bgl2. The paper is well written, the data are convincing and the characterization of these novel peptide interaction sites clearly advances the field. Although, the exact role of the Sec3 NPY - Sec3 interaction still needs to be established, the overall functional relevance is apparent and thus the paper could be published with minor changes. *

      __Response: __We really appreciate the reviewer for his/her positive comments and clear/constructive feedbacks.

      *Nevertheless, the authors may consider to address the following issues to improve the manuscript. - To strictly exclude the possibility that the Sso2 NPY motif also interacts with other components of the exocytosis machinery (e.g. Sec1), thereby causing the observed phenotypes, Sec3 mutagenesis of the NPY motif-binding site would be required. *

      __Response: __It would be a good idea to generate reverse mutants on Sec3. However, the pocket on Sec3 bound by the NPY motifs of Sso2 is mostly hydrophobic and contains many semi-buried residues that are in close contact with other residues in the hydrophobic core of structure (including L78, Y82, I109, V112, V208, etc.; see Fig. S3D, E) and thus essential in maintaining the folding of Sec3. Making mutations on these residues would destabilize the folding of Sec3. This was why we have not done this as suggested by the reviewer.

      *- The authors suggest that the NPY-peptide binding contributes to the initial interaction/recruitment of Sso2 to the exocytosis site, defined by the localization of Sec3 (exocyst). Further data sustaining this concept/hypothesis could improve the impact of the manuscript. Thus, an experiment analyzing the co-distribution of the Sec3 with Sso2 would directly support the authors' conclusion. (In Figure 7, the authors already show the highly polarized distribution of Sec3-3xGFP.) The M7 mutant could impact the distribution of Sso2. In addition, it would be helpful to determine to which degree the Sso2 NPY - Sec3 PH domain interaction increases the overall affinity of Sso2 for the Sec3 PH domain; e.g. comparison of the binding of Sso2 (1-270) wt and M7 to Sec3 PH domain using ITC. *

      Responses:

      • We greatly value the reviewer’s suggestion. For the suggestion to investigate how the M7 mutant affects the co-distribution of Sso2 with Sec3 in yeast, we have tried a variety of conditions with both the original serum and affinity purified Sso antibodies. In neither case did we see a clear concentration at sites where we would expect to see Sec3, such as the tips of small buds. We were able to see some detectable concentration of HA-tagged Sso2 in small buds using anti-HA Ab, but it would be difficult to tag the M7 mutant at the same site since it is so close to the M7 mutation. We are also worried that the tag might interfere with Sec3 binding due to the proximity. Given the lack of detectable concentration of WT Sso2, it would not be possible to see a loss of localization in M7.
      • For the suggestion to check the binding of Sec3 with either the WT or M7 mutant of Sso2 (aa1-270), we have generated M7 mutant within the same fragment of Sso2 as the WT (i.e. aa1-270) and carefully checked how this M7 mutant affects the interaction of Sso2 with the Sec3 PH domain using three independent methods. Our ITC data show that WT Sso2 bound Sec3 very robustly, with a Kd of approximately 2 µM (Fig. 8C). Surprisingly, however, the M7 mutant of Sso2 (aa1-270) completely abolished its interaction with Sec3 (Fig. 8D). To further verify this observation, we carried out electrophoresis mobility shift assays (EMSA) and size-exclusion chromatography (SEC). Our EMSA data on a native PAGE gel shows that WT Sso2 (aa1-270) bound Sec3, whereas the M7 mutant did not (Fig. S5A, B). Similarly, our SEC data demonstrate that Sec3 was co-eluted with WT Sso2 in the higher molecular weight peak; in contrast, Sec3 and the M7 mutant of Sso2 (aa1-270) were eluted in separate peaks and no stable complex of the two was formed (Fig. S5C, D). All these new data confirm that the NPY motifs play an essential role in maintaining the stable interaction between Sso2 and Sec3, which would explain why the M7 mutant gave such dramatic phenotype in vivo (Fig. 4B-E; Fig. 5D-F; Fig. 6D, E). *Minor point: In the discussion, the authors should mention to which degree the NPY binding site within Sec3 is accessible for / occupied by other known exocyst components, or PI(4,5)P2, etc. *

      Response: __Thank you for the suggestion. A new diagram has been added to __Fig. 9E to compare the structures of the previously reported Sec3/Rho1 complex and the Sso2/Sec3 complex determined by us. It shows that the NPY binding site on Sec3 is on the opposite side of the membrane-binding surface patch. The NPY binding site is also far away from the Rho1 interacting site on Sec3 and thus does not interfere with Rho1 binding either.

      *Reviewer #1 (Significance (Required)):

      The manuscript significantly contributes to our understanding of how the vesicle tethering machinery interacts and coordinates the assembly of the membrane fusion machinery and will be of broad interest in the field of membrane trafficking. I am not an expert in X-ray crystallography. *

      __Response: __We sincerely appreciate this reviewer’s positive feedbacks.

      ***Referees cross-commenting**

      I agree with the comments of the other reviewer. It would be nice to show the effect of the M7 mutant in a reconstituted liposome fusion assay, but as already mentioned this may require an additional collaboration. Whether the relatively weak Sec3 - NPY interaction can be resolved in the liposome fusion assay needs to be shown.*

      __Response: __Please check our detailed answer to the other reviewer’s question about this.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): * The manuscript of Peer et al. Describe the structural characterization of the interaction of the syntaxin-like Sso2 protein with the exocyst subunit Sec3. The authors identify here a dual NPY motif at the N-terminal part of Sso2 that binds to Sec3 and thus confers functionality. Using x-ray crystallography, they show a nearly full-length Sso2 in complex with Sec3, which reveals how Sso2 binds to Sec3. Subsequent mutagenesis shows that both NPY motifs act together in binding, and are both required for functionality in vivo, using established assays in localization of exocyst subunits, secretion assays and growth tests. Their data suggest an overall model how Sso2 is efficiently recruited by exocyst to promote vesicle secretion.

      This is__ an overall very complete and clear manuscript__, where the authors nicely demonstrate, how the two NPY motifs both contribute to efficient Sso2 interaction with Sec3. Their data further show that each motif alone can contribute to function, whereas loss of both motifs (the M7 mutant) result in deficient binding. Likewise, their established assays to determine cellular importance of the NPY motifs in Sso2 show that trafficking and localization in the secretory pathway is strongly impaired in the mutant. I only have a few questions and suggestions. *

      __Response: __Thank you for the positive feedback.

      *1. The authors present in Figure 4 the mutants. I recommend to show the alignment of the mutants (M5,M6,M7) similar to panel A in Figure S4 here to orient the reader. They could also be listed in Figure 3, since the authors have here the sequences. *

      Response: __Alignment of M5-M7 has been added in __Fig. 4A as suggested. Thank you.

      2. The authors previously showed that Sso2 mutants affect the Sec3 driven assembly and also the fusion. I am wondering if they have the tools ready to also conduct this assay with their M7 mutant, which has the strongest defect. I am aware that this may be challenging if the tools are not established here as in the previous collaboration (Yue et al., 2017). It may provide additional information on the functional crosstalk.

      Responses:

      • Thank you for the suggestion. However, we do not think it is necessary to perform such assay based on our new results. As shown in 8C&D and Fig. S5, we found that the M7 mutant of Sso2 (aa1-270) completely abolished its interaction with Sec3, which is in contrast to the robust interaction between the WT Sso2 (aa1-270) and Sec3. Therefore, we expect that the M7 mutant would fail to accelerate liposome fusion in the same way as we had previously seen for the WT Sso2.
      • On the other hand, we have to admit that to perform such assay would indeed be challenging for us as the PhD student who had carried out the in vitro liposome fusion assay has left our previous collaborator’s lab and it would take quite a while to re-establish the assay in our own group and to optimize various parameters in that assay. *3. Along the same line, it would be good if the authors show that the mutation also impairs the interaction of Sec3 and Sso2 in vivo. *

      Response: __We appreciate the reviewer’s suggestion and have carried out co-immunoprecipitation of Sec3-3×Flag and Sso2 from yeast extract to find out how the M7 mutant affects Sso2’s interaction with Sec3 (__Fig. S6). Our results show that in contrast to the clear signal of WT Sso2 pulled down by Sec3-3×Flag, the pull-down band for the M7 mutant was much weaker and at a similar level to the negative control. This is consistent with what we saw in our in vitro binding assays (Fig. 8D; Fig. S5).

      *4. I really like the similarity of the different Munc18-Syntaxin interactions and the Sec3-Sso2 interaction. Do the authors think that Sec3 is an ancestral fragment of a Sec1 like protein, which just maintained this interaction? *

      __Response: __This is a very interesting idea. However, it seems too speculative to us to draw such conclusion. It could also be due to co-evolution in function for Sec3 to use a simpler structure (i.e. PH domain) to mimic syntaxin binding of SM proteins and to employ the extra “add-on” NPY motifs as a handle to facilitate and regulate their interaction.

      1. *Small mistake in the discussionResponses: "plasmas membrane" *

      __Response: __This has been corrected. Thank you.

      *Reviewer #2 (Significance (Required)): Important advance in our understanding of Exocyst function, which deserves publication. I only had minor issues that can be addressed quickly. *

      __Response: __We sincerely appreciate the reviewer’s positive feedbacks and constructive suggestions.

    1. Most existing tools and browsers treat web pages and pieces of notes like complete black boxes of information. These tools know how to scan for keywords, and they have access to the metadata we use to tag our information like hashtags and timestamps, but unlike a human, most current tools don’t try to peer into the contents of our notes or reading materials and operate with an understanding of our information. With ratcheting progress in machine understanding of language, I think we have good high-quality building blocks to start building thinking mediums and information systems that operate with some understanding of our ideas themselves, rather than simply “this is some text”.
    1. “Conspiracy theory, like causality, works fantastically well as an explanatory model but only if you use it backwards. The fact that we cannot predict much about tomorrow strongly indicates that most of the explanations we develop about how something happened yesterday have (like history in general) a high bullshit content.” ― Peter J. Carroll, Psybermagick: Advanced Ideas in Chaos Magick
    1. Reviewer #1 (Public Review):

      In this Research Advance, the authors build on two earlier eLife papers that described and experimentally validated a mathematical model of the transcriptional response of yeast to heat shock in which unfolded proteins sequester Hsp70 away from Hsf1 promoting an Hsf1-driven transcriptional program, and report two new findings. First, they provide evidence that upon heat shock it is newly synthesized proteins rather than denatured mature proteins that sequester the Hsp70 chaperone away from Hsf1 permitting Hsf1 to bind to target genes and drive the heat shock-induced gene transcription program during the heat shock response (HSR), and, second, by analyzing the role of the Sis1 Hsp70 co-chaperone in the HSR they showed that Sis1 does not have a direct negative role in the HSR, but rather is needed for fitness during prolonged stress.

      Because recent studies using cycloheximide to block protein synthesis have suggested that it is newly synthesized proteins in the process of folding rather than denatured mature proteins that are the clients for Hsp70 responsible the HSR, the authors reconfigured their model by assuming that heat shock slows the folding of newly synthesized proteins and adding the rate of translation as a new input function. They validated their new model using a yeast strain that has an HSE-YFP reporter gene as an HSR readout, and showed that rapamycin treatment, which reduces the rate of translation, resulted in a decrease in the HSR, that is predicted with kinetics predicted by their new model. In addition, based on their own recent work showing that the Sis1, a J-protein chaperone, regulates the HSR by promoting Hsf1-Hsp70 association in the nucleus to repress Hsf1 activity under non-heat shock conditions, they also incorporated Sis1, a Hsp70 co-chaperone, as a new component of their model circuitry. By experimentally induced eviction of Sis1 from the nucleus, they observed reduced Hsf1 activity towards the HSE-YFP reporter in the absence of a temperature shift, as predicted by the model. The new model also accounted for the rapid initial and then subsequent slowing kinetics of the HSR as it reached a maximum, as well as the different levels of HSR induction at increasing temperatures above 35oC. Moreover, even though the SIS1 promoter has an HSE and its basal transcription is driven by Hsf1, the elimination of this regulatory step experimentally showed that Hsf1-driven Sis1 transcription was not required for temperature shift-induced HSR output, implying, as the model predicted, that increased Sis1 expression is not important and not needed for negative feedback inactivation of Hsf1. This was tested directly by generating a strain in which the SIS1 promoter was replaced with two copies of the SUP35 promoter to maintain the basal expression level of Sis1, which showed normal kinetics of HSR inactivation under several experimental conditions. Using a Halo-tag pulse protocol, they demonstrated that heat shock induction of newly synthesized Sis1-halo was delayed and that the new Sis1 protein was preferentially localized around the nucleolus away from Hsf1, as determined using an Nsr1-mScarlet nucleolar marker, and thus Sis1 would presumably not be in a position to promote Hsp70/Hsf1 interaction and repression of Hsf1 activity. Finally. to investigate what role Sis1 plays in heat-stressed cells, they showed that the 2xSUP35pr-SIS1 yeast strain had reduced fitness compared to the other strains after 4 hours at 37ºC, suggesting that Sis1 has an undefined role in maintaining fitness in heat-stressed cells. Consistent with this, they showed that Sis1 also has a role in maintaining fitness in yeast cells growing on a non-preferred carbon source.

      The updated model of the HSR, which still retains the two-component feedback loop consisting of the chaperone Hsp70 and the transcription factor Hsf1 of the original model but replaces the unfolded protein activation step with an equivalent step involving unfolded newly synthesized proteins, appears to be able to model cellar responses to heat shock quite accurately. This refinement of their model, coupled with the demonstration that the Sis1 J protein chaperone does not appear to play a direct role in the inactivation phase of the HSR, provide a significant advance over their earlier work.

      A main weakness is that while the evidence that Sis1 is important for fitness of heat-stressed yeast cells is reasonable, exactly how Sis1 achieves this is not clear. In a single sentence the authors suggest that Sis1 might be an orphan ribosome chaperone, partly based on its nucleolar localization, but provide no evidence for this. If this were true, then one might expect a reduction in ribosome content under stress conditions and a decreased rate of protein synthesis, which could be tested. Some further insights into this more general role of Sis1 would strengthen the authors' conclusions.

      Moreover, whether Sis1 plays a general role in the fitness of cells under stress has not been firmly established, i.e., is its mechanistic role the same in heat shock conditions and under nutrient stress conditions? Without knowing the mechanistic basis for how Sis1 maintains the fitness of heat-stressed cells, it is not possible to conclude that the same mechanism is at play in cells grown on a non-preferred carbon source.

      Figure 4: This is an ingenious experiment to study the subcellular localization of newly synthesized Sis1 in response to heat shock, compared to that of the heat-shock inducible Hsp70 Ssa1. However, based on the images presented in panel B it is hard to know how discrete the subnuclear distributions of Sis1 and Ssa1 really are, and ideally what is needed is to be able to analyze their localizations when both tagged proteins are expressed in the same cell, although this would obviously not be possible using the halo-tagged protein system. In addition, one would like to know the localization of Hsf1 in the cell at the same time. As it stands, these data seem overinterpreted, and it remains possible that dome other event such as an inactivating post-translational modification of Sis1 under heat shock conditions might be involved in inactivating its function.

      One way to establish whether Sis1 nucleolar sequestration prevents it from acting on Hsf1 during the inactivation phase of the HSR would be to selectively disrupt its nucleolar localization signal eliminated while retaining its nuclear localization and determine how expression of such a mutant perturbed the inactivation kinetics of the HSR.

    1. The Map Is Not The Territory

      • The map is not the territory metaphorically illustrates the differences between belief and reality.
      • The phrase was coined by Alfred Korzybski.

      Scribbling on the map does not change the territory

      • If you change what you believe about an object, that is a change in the pattern of neurons in your brain.
      • The real object will not change because of this edit.

      The map is a separate object from the territory and the map exists as an object inside the territory

    1. Author Response

      Reviewer #1 (Public Review):

      Cheng et al. address one of the fundamental questions of gene expression regulation - what are the relative contributions of RNA-level and protein-level regulation to the final gene expression levels. In order to do that they take advantage of mainly published datasets, especially tumor datasets where matching somatic copy number alterations (SCNAs), RNA expression and protein expression data is available. Performing proteogenomic analysis (taking DNA, RNA and protein into account) they address several open questions, such as: Is gene compensation happening mainly at the RNA level, protein level or both for each gene? Is this the same across different tissue types and also cellular pathways? Taking advantage of the SCNAs in the DNA, the authors use correlation analysis of DNA to RNA and RNA to protein to determine if the expression of a gene is regulated mainly at the level of RNA or protein in the respective samples.

      Although it is mainly a very descriptive study, the meta-analysis of existing datasets (and one smaller dataset that was newly generated) yields very interesting observations, which will be of interest to the cancer and gene expression community. However, there is limited mechanistic insight into how the observations can be explained. This is not a problem in my view as the observations are interesting enough in themselves.

      The main findings of the study are:

      • In general genes are either regulated at the RNA-level or at the protein level, but rarely at both.

      • This is the first study (at least as far as I know) to look at tissue-specific RNA-level and protein-level compensation across several different tumor types. Interestingly, the authors show tissue specificity of RNA and protein-level compensation - for example lung adenocarcinoma does not show nearly any compensation.

      • Protein complex genes show stronger protein-level regulation than non-complex genes and the opposite trend in regards to RNA level regulation.

      • There seems to be an agreement for genes within the same pathway that they show a similar regulatory mode (either RNA level or protein level).

      • Genes involved in RNA processing, mRNA translation and mitochondrial regulation are generally upregulated at the protein-level in highly aneuploid primary tumor samples.

      However, I do think that two points need to be addressed by additional analyses to strengthen the findings.

      • The authors show that SCNAs are often significantly compensated at the protein-level in most tumor types. This compensation is also normally stronger than RNA level compensation. A technical issue about this finding that needs to be addressed is that this is mainly based on proteomics data that used TMT for quantification. TMT-based quantifications, although quite precise, are not always the most accurate measurements in the sense of capturing the true amplitude of changes. This is due to the so-called ratio compression of TMT mass spec data. The authors need to account for that in order to exclude that this technical limitation of TMT-based proteomics measurements is a main contributor to the protein-level compensation seen. Do the authors also have some proteomics data where label-free quantification of SILAC quantification was used? Do the same conclusions hold true when such data sets are used?

      We thank the reviewer for this comment and point which we have now addressed through the following literature search or analyses:

      • First, we found there are some previous studies which observed the similar protein-level compensation in yeast and human cells by different detection methods. Dephoure et al. compared two different methods, stable isotope labeling by amino acids in cell culture (SILAC) and tandem mass tag (TMT) based proteomics. The protein-level compensation of gained genes in yeast was discovered by both methods (Figure 2 and Figure 2 – figure supplement 1 of Dephoure et al., 2014). Similarly, Stingele et al. identified the protein-level compensation in pairs of isogenic diploid and aneuploid human cell lines by SILAC (Figure 2B of Stingele et al., 2012). Another group also found the protein-level compensation in primary human fibroblasts from individuals with Patau (trisomy 13), Edwards (trisomy 18) or Down (trisomy 21) syndromes by MS3-based approach (Hwang et al., 2021), which should eliminate the interference of ratio distortion (Ting et al., 2011). Taken together, those previous studies suggest the protein-level compensation should not be just the artifacts induced by the technical limitation of TMT-based proteomics.

      • To further validate the protein-level compensation, we performed the same analysis on TCGA (The Cancer Genome Atlas Program) (Research Network et al., 2013) COAD samples for which label-free proteomics data is available (Zhang et al., Nature, 2014). Consistent with TMT-based proteomics, significant compensation at the protein level was found, which is higher for complex genes than non-complex genes (Figure 1 – figure supplement 1C, Supplementary File 1G). As we observed before for COAD (Figure 1C), RNA-level compensation was shown in all groups of DNA change, and was stronger for non-complex genes (deep loss and high gain, FDR<0.005, Figure 1 – figure supplement 1C, Supplementary File 1G). These results suggest that the limitations imposed by the TMT quantification do not alter the conclusions of our analysis on gene compensation. We have now added this data in Figure 1 – figure supplement 1C and Supplementary File 1G and corresponding text at page 5.

      • Many of the statistically significant differences seen - e.g complexed proteins versus non-complexed proteins, highly conserved proteins versus less conserved proteins - have actually a relatively small effect size. It is not 100% clear to me that the authors apply always the most stringent and appropriate statistical evaluation. For example, when two density plots are compared and it is evaluated if the distributions differ significantly from each other (e.g. the median), the authors constantly use a bootstrapping strategy (most plots in Fig 2 and Fig S2). Due to the high number of iterations, bootstrapping is very sensitive to picking up statistical differences, even if there are very small effect size differences (as is the case for many of the comparisons). Would not a KS test be more appropriate to compare two density distributions? If a KS test is applied - do the authors still recapitulate the same statistical significance tendencies as seen with their bootstrapping strategy?

      We thank the reviewer for this comment, and we have addressed it in detail. We have performed the analyses using Mann-Whitney U test and Kolmogorov-Smirnov (KS) test (Supplementary File 2K). Compared with bootstrapping, the p-values calculated by Mann-Whitney U test or KS test were much smaller, close to zero. Therefore, the same statistical significance tendencies were observed no matter which statistic method was used (bootstrapping, Mann-Whitney U test or Kolmogorov-Smirnov test). While Mann-Whitney U test or KS test carries the risk of p-value inflation due to the high sample number, the bootstrapping method can solve the problem as it is independent from the sample number. Initially we had used Mann-Whitney U test for all our analyses and were suggested to include bootstrapping method after consultation with the NYU Biostatistics Resource.

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

      Learn more at Review Commons


      Reply to the reviewers

      1. General Statements

      We would like to thank the reviewers for their insightful and useful comments about our manuscript. Based on these comments and as outlined in our revision plan, we plan to strengthen our findings by performing new experiments and quantitative analyses. This particularly applies to our nanoscale (dSTORM) imaging dataset which was discussed by multiple reviewers.

      We also appreciate the reviewers’ overall positive evaluation of the significance of our labeling method for the axon initial segment studies. With regards to this, we would like to highlight that this manuscript particularly addresses the labeling of “difficult-to-label” neuronal proteins, such as large ion channels and transmembrane proteins. Although we and another group have recently reported click labeling of neurofilament light chain (PMID: 35031604) and AMPAR regulatory proteins (PMID: 34795271) in primary neurons, both of these proteins have a small size between ~30-68 kDa and compared to larger ion channels/transmembrane proteins are “easier” to express in primary neurons. The novelty in the current manuscript is that we successfully applied this method for the labeling of large and spatially restricted AIS components, such as NF186 and Nav1.6 (186 and 260 kDa, respectively). As some of the reviewers also pointed out, the size and complexity of these proteins makes labeling of the AIS rather challenging. We also used our approach to study the localization of epilepsy-causing Nav1.6 variants and could exclude the retention in the cytoplasm as a possible cause of their loss of function. Finally, we improved the efficiency of genetic code expansion in primary neurons by developing AAV-based viral vectors. Although AAVs are routinely used for gene delivery to neurons, AAVs for click-based labeling need to encode multiple components of the orthogonal translational machinery for genetic code expansion. By trying different promoters and gene combinations, we developed several variants that enable high efficiency of the genetic code expansion in neurons. On their own, these findings will facilitate further genetic code expansion and click chemistry studies, beyond the labeling of the axon initial segment.

      2. Description of the planned revisions

      Reviewer #2

      • On lines 107 and 108, the sentence "The C-terminal HA-tag allowed us to detect the full-length NF-186 protein by immunostaining it with an anti-HA antibody" would have a better place just after lines 104-105 " [...] we modified the previously described plasmid (Zhang et al., 1998) by moving the hemagglutinin (HA) tag from the N terminus to the C terminus".

      We will modify the text as the reviewer suggested.

      • Fig.2b: the AnkG staining looks substantially longer than that showed in c. However, the results on AIS length show no significant changes in between the groups. This is visually misleading, the authors should choose a picture for the WT construct that is representative of the data.

      We thank the reviewer for bringing this up. We will replace the panel in Fig.2b with a more representative image of NF186 WT construct in the revised version of the manuscript.

      • Line 238: what is the rationale behind choosing these cells? For example, have they been used in other studies for similar purposes? If so, please provide the reference.

      We initially probed neuroblastoma ND7/23 which are commonly used for the electrophysiological recordings of recombinant Nav1.6 (PMID: 30615093, 22623668, 25874799, 27375106). Although we were able to record Na+ currents in those cells, only a small portion of channels was detected on the cell surface by microscopy (Suppl. Fig. 5a). As we discuss in the manuscript (lines 237-240), we then switched to N1E-115-1 cells in which we obtained a higher level of expression of the recombinant NaV1.6 channels on the cell surface (Suppl. Fig. 5b). These cells have also been previously used for the electrophysiological studies of voltage-gated sodium channels, including Nav1.6 (PMID: 8822380, 24077057). We will modify the text and include these references in the revised manuscript.

      • Figure 3c, the authors omitted the comparison with the WT construct this time, as opposed to the neurofascin experiments. What is the reason?

      As shown by others (PMID: 31900387) and us in this manuscript, one of the main issues with the expression of the recombinant NF186 in neurons was that overexpression led to mislocalization of NF186 in neuronal soma and processes. This was particularly true for WT construct and certain amber mutants (e.g. K809TAG). Based on previous reports (PMID: 31900387), we then tested a weak human neuron-specific enolase promoter. This reduced expression level and improved localization of NF186. However, since we still observed some neurons with mislocalized NF186 WT even with the enolase promoter, we found it important to quantitively compare the AIS length of WT construct and amber mutants to surrounding untransfected cells. On the other hand, since we did not have overexpression and mislocalization problem with Nav1.6 WT construct (all observed neurons have signal localizing in the AIS), we measured only the AIS length of the amber mutants. However, to avoid any confusion, we will also measure the AIS size of the neurons expressing Nav1.6 WT construct and compare it to surrounding cells and amber mutants. For this, we will need to perform new experiments and acquire new images. We will include the data in the revised manuscript.

      • Fig. 4: why did the authors chose these cells for electrophysiology experiments and not neurons? Explain the rationale in the text or, alternatively, cite similar studies using the same tool.

      Due to the branched neuronal processes which cause the space clamp problem in voltage clamp experiments with neurons, round and none-branching cells are frequently used to examine the biophysical properties of ion channels, including Nav1.6. By far, most of studies investigating the biophysical properties of NaV1.6 channels were performed in neuroblastoma cells e.g. ND7/23 and N1E-115-1 cells (PMID: 25874799; 25242737). We tested these two types of cells and found that N1E-115-1 cells supported higher expression level of the recombinant NaV1.6 channels on the cell surface than the ND7/23 cells (Suppl. Fig 5). Hence, N1E-115-1 were more suitable to get robust and reliable recordings (as we also discuss above in the response to reviewer’s comment). We will clarify this in the revised manuscript.

      • Fig.4, biophysical properties: did the authors find differences in passive properties? Measures of resting potential, membrane resistance and cell capacitance should be reported.

      Passive properties such as resting membrane potential and membrane resistance are important functional features in neurons measured in current clamp experiments, but not applicable for ND7/23 and N1E-115-1 cells used in our voltage clamp experiments. To measure the Na+ current mediated by WT or mutant NaV1.6 channels expressed in N1E-115-1 cells, the endogenous Na+ channels were blocked by tetrodotoxin and the endogenous K+ channels were blocked by tetraethylammonium chloride, CsCl and CsF in extracellular and intracellular solutions. Under these conditions, resting potential and membrane resistance are not relevant for experiments. Cell capacitance reflects the size of the cell surface area, which can affect the number of channels expressed on the cell surface. To eliminate the effect of different cell sizes, Na+ current densities normalized by cell capacitances were used in our experiments. We will report on these values in the revised manuscript.

      • Fig 4, STORM images. The periodic distribution of the dots should be enhanced with some sort of arrows or lines, for the non-specialist audience.

      Based on the comments from multiple reviewers, we plan to obtain additional dSTORM images of the neurons expressing recombinant Nav1.6 WT or amber mutants. We also intend to improve the visualization of these results by updating/modifying existing figures and including quantitative data.

      • Line 374: rat or mouse primary neurons?

      We are here referring to both, rat and mouse neurons. The images shown in Fig. 06 and Suppl. Fig. 08 were obtained from rat cortical neurons expressing Nav1.6 or fluorescent reporter. However, we were also able to successfully transduce mouse neurons with AAV92A carrying orthogonal translational machinery (data not shown). We will clarify this in the revised manuscript.

      **Referees cross-commenting**

      I fully agree with the following remarks from Reviewers #3, #4 and #5. This is a point that I have raised in my report too. The authors need better images to show the periodicity we visualization, and a quantification would be of great benefit to support the claim with numbers (and how these compare to similar studies in the literature):

      R3: 2. For the dSTORM analysis of the tagged Nav1.6 protein, I also cannot tell there is periodic organization from the image directly. Some analysis is needed there. R4: 2."As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports. R5: 3. The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.

      As we outlined in our responses to the individual reviewers’ comments below, we will address these questions by performing new experiments and quantifications.

      I also agree with these comments from Reviewers #3 and #5:

      R3: 4. It is unclear, for all the presented data, whether all the cells are collected from a single biological replicate or from multiple replicates. At least 2-3 replicates are needed to see the reproducibility in terms of labeling efficiency, and other related conclusions. R5: 1. The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.

      We thank the reviewers for bringing this up. By mistake, we omitted this important information. We will include it in the revised manuscript, but we would like to highlight here that each experiment was repeated at least 3 times.

      Reviewer #3

      1. There is some patch-like background from the 488 channel from the click reaction, some of which have very as strong signal as the staining on the neurons. What is the potential cause for this? With immunostaining on HA, the background doesn't affect too much on the image data interpretation. However, the major goal of this method development is to use it in live-cell without immunostaining. Without another reference, the high background might cause issues in data interpretation. Can the author also suggest way to avoid or lower this in the discussion?

      We thank the reviewer for bringing this up. We have occasionally observed patch-like background in what appears to be the cell debris. Such dead cells do not have an intact cell membrane and therefore can absorb cell-impermeable ATTO488-tetrazine dye during click labeling. This kind of background is also present in the control neurons transfected with the WT Nav1.6, which suggests that it originates from the UAA and tetrazine-dye accumulations. Additionally, since these patches are not visible with the immunostaining, they do not contain our protein of interest, which further confirms that they contain only dye and UAA accumulations. Depending on the neuron prep/quality before and after transfections, the presence of these patches is more or less obvious. However, despite the background we did not have problems identifying AIS during live cell imaging. Especially when overall neuronal health is optimal after transfections, AIS can easily be distinguished from patches that are positioned outside of labeled neurons. We will investigate this further and discuss it in the revised manuscript.

      1. For the dSTORM analysis of the tagged Nav1.6 protein, I also cannot tell there is periodic organization from the image directly. Some analysis is needed there.

      We will address this in the revised manuscript by performing additional experiments and quantifications. We also wrote a detailed answer below, in the response to the other reviewers.

      1. The authors use the AIS length as a parameter to evaluate the function of the clickable mutant of NF186, and using patch clamp for functional validation of the clickable mutant of Nav1.6. In both cases, the comparison is done between the mutant and the WT construct, but both in transfected cell and exogenously expressed. It's also worth comparing with untransfected cells as the true native situation.

      We agree with the reviewer that it is important to compare transfected cells with untransfected cells. As the reviewer points out, we have already performed some of these comparisons. When it comes to the NF186, we used the AIS length as a parameter to estimate if the expression of clickable mutant affected the AIS structure. As we show in the Fig. 02, we co-immunostained neurons transfected with NF186-HA WT or TAG constructs. We used HA antibody to detect neurons expressing NF186, while the ankG was used as a marker of the AIS length. To check if the AIS length of transfected cells is affected, we compared the length of transfected cells (expressing NF186, HA+) to surrounding untransfected cells (HA-). When it comes to the Nav1.6, we also compared the AIS length of cells expressing Nav1.6 (HA+) to surrounding untransfected cells (HA-). Similarly to the experiments with NF186, this allowed us to check if the expression of the recombinant Nav1.6 affect the AIS structure. What is missing is the comparison with untransfected conditions (i.e. neurons that are simply stained with ankG). We assume that is what the reviewer is referring to? We will also include these data in the revised manuscript. Furthermore, since we introduced a labeling modification in NaV1.6, we wanted to check if such modification would affect its function. To do so, as routinely done in the field (PMID: 25874799), we rendered the WT and TAG channels TTX-resistant and recorded only recombinant Na+ currents in neuroblastoma cells in the presence of TTX. Perhaps we misunderstand the reviewer’s comment, but in this regard measurements of untransfected cells are not relevant since they would not allow us to compare WT and TAG mutants.

      1. It is unclear, for all the presented data, whether all the cells are collected from a single biological replicate or from multiple replicates. At least 2-3 replicates are needed to see the reproducibility in terms of labeling efficiency, and other related conclusions.

      We thank the reviewer for the observation. By mistake, we omitted this important information. We will include in the revised version of the manuscript. We would like to highlight here that each experiment was repeated at least 3 times.

      Reviewer #4

      1."Confocal microscopy revealed that the hNSE promoter lowered the WT and clickable NF186-HA expression levels and consequently improved the localization of these proteins." Is the lower expression level a measure of localization improvement? How does the author conclude that the localization has improved?

      Previous report (PMID: 31900387) suggested that the overexpression of the recombinant WT NF186 can affect its trafficking, leading to the NF186 mislocalization. We observed the same in our experiments with CMV NF186 (in particular for NF186 WT). Hence, based on the PMID: 31900387 we probed weak neuron specific enolase promoter. Since the WT was the most problematic in terms of the ectopic expression, we checked if AIS localization was improved with enolase promoter for this construct. To this aim, we counted number of neurons that with mislocalized signal or with the signal in the AIS for both, CMV and enolase promoter. We could observe that number of neurons with mislocalized signal was lower for enolase promoter. Since there were more neurons with the AIS-specific signal when NF186 was expressed from enolase promoter compared to CMV, we concluded that enolase promoter lowered expression and improved localization of the NF186. Therefore, we used enolase promoter for click labeling of NF186 amber mutants. We will include the results of this analysis in the revised version of the manuscript.

      2."As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports.

      We thank the reviewer for these suggestions. We will address these remarks by performing additional new experiments and quantifications. The difference in the level of the expression of the recombinant Nav1.6 might explain differences in the spot density for WT vs. TAG clickable mutants. However, as the reviewer suggested quantitative analysis is needed to address these concerns. We also intend to quantify the periodicity and compare it among different variants and with previous reports. It is just important to note that in the current version of the manuscript we looked at the nanoscale organization of the subset of Nav1.6 channels. The reason being that we used anti-HA antibody which will only detect our recombinant protein which got incorporated into the AIS and not the endogenous Nav1.6.

      Minor comments

      1."Although NF186K809TAG 158 -HA (Supplementary Fig. 4) showed bright click labeling, we excluded it from the analysis due to its frequent ectopic expression along the distal axon." How frequently is this bright click labeling observed for this mutation? Is it not observed for other mutations at all? The authors should state this point clearly with some statistics.

      We are not sure what is the exact question from the reviewer. If we understand it correctly, the reviewer is asking us to quantify how frequent was the ectopic expression of this amber mutant compared to other mutants? And not the click labeling (as written in their original comment), since click labeling was observed for all the mutants independently of their ectopic expression?

      2."Immunostaining with anti-HA antibody revealed that the expression of NaV1.6WT 239 -HA on the membrane of the N1E-115-1 cells was higher than on the ND7/23 cells (Supplementary Fig. 5a-c). However, click labeling of both NaV1.6K1425TAG 240 -HA and NaV1.6K1546TAG 241 -HA with ATTO488-tz was not successful (Supplementary fig. 5d) indicating insufficient expression of the clickable constructs." Is this due to insufficient expression level or accessibility? The author should make this statement clear.

      We thank the reviewer for bringing this up. We will clarify this in the revised version of the manuscript. We believe that the click labeling of the K1546TAG mutant in N1E-115-1 cells is absent due to the insufficient expression of the channels on the membrane, since this mutant was successfully labeled in the primary neurons that represent more native environment and where Nav1.6 form high-density clusters. K1425TAG mutant is not labeled due to the insufficient expression on the membrane in N1E-115-1 cells as well. However, since this mutant is also poorly labeled in primary neurons, we can speculate that K1425TAG position might be less accessible for the tetrazine-dye compared to K1546TAG. To further support our claim that due to the insufficient expression click labeling is low/absent in neuronal cells, we can use NF186 as an additional example. When NF186 was expressed from strong CMV promoter, we observed click labeling for all the mutants in ND7/23 cells (Suppl. Fig.01). However, when CMV was replaced with neuron specific enolase promoter, the expression was of NF186 was substantially lower in ND7/23 cells and click labeling was absent (data not shown). We will clarify this in the revised manuscript.

      1. Authors should clearly state the drift correction procedure of 3D STORM data. What are the localization precision and photon count for 3D STORM experiments?

      We processed 3D dSTORM data in NIS-elements AR software. We used the automatic drift correction from the NIS-elements software that is based on the autocorrelation. We will provide further and updated information in the revised manuscript, including the localization precision and photon count for the new dSTORM images.

      1. "Click labeling of NaV1.6 channels in living primary neurons" What kind of primary neurons have been used for click labeling of NaV1.6 channels? Is there any specific reason why authors have chosen cortical neurons for labeling NF186? Does this labeling strategy depend on primary neuron type?

      For the establishment and click labeling of Nav1.6 we used primary rat cortical neurons (Fig. 03, Fig. 06). The same neuronal type has been used for click labeling of NF186 (Fig. 02). We established labeling of the AIS components in cortical neurons because we use those routinely in the laboratory. However, this labeling strategy does not depend on the neuronal type. As we show in Fig. 05, to study localization of the loss-of-function pathogenic Nav1.6 variants we used mouse hippocampal neurons. The reason for this is that in previous study the same neuronal type was used to characterize these two mutations (lines 361-362). This demonstrates nicely that method can be easily transferred to any neuronal type. Furthermore, we were also able to label Nav1.6 and NF186 in mouse cortical neurons (data are not shown in the manuscript). We will clarify this in the revised manuscript.

      Reviewer #5

      1.Throughout the manuscript, only one representative image containing one AIG is shown for each condition without statistics and quantifications, so the conclusions are not sufficiently convincing. For example, in Fig. 1b, c, e; Fig. 2b,c,d,e; Fig. 3b,c,d,e ; Fig. 5c; and Supplementary Fig.1-6, the authors should quantify the average fluorescence intensities both for HA immunostaining and ATTO488-tz labeling in different conditions, as well as the labeling ratios (fluorescence intensity ratios between ATTO488 and AF647/AF555) . Without statistics and quantifications, it is unclear whether there is any significant difference between the constructs with different TAG positions, or between different transfection methods (e.g., lipofectamine 2000 vs 3000).

      We agree with the reviewer that the quantitative analysis is important and we will provide more quantitative data in the revised manuscript. At the same time, we are a bit confused by this comment which seems to refer to missing quantifications in one of the schemes (Fig. 1) and overlooks existing quantifications (e.g. quantitative analysis of the data set from Fig. 5c is shown in Fig. 5d). However, as suggested by the reviewer and to strengthen our data, in addition to the quantifications already provided in the manuscript (e.g. Fig. 2d: AIS length of NF186TAG constructs; Fig. 3f: AIS length of Nav1.6 TAG constructs; Fig. 5d: click-labeling intensity of LOF mutants), we intend to quantify the differences between labeling ratios of different mutants and transfection methods. When it comes to the different transfection methods, some data is already provided in the manuscript (e.g. we counted number of transfected versus transduced neurons) but we intend to clarify and expand on this in the revised manuscript.

      1. The only quantification done was for the average AIS length, but the statistical tests should be performed between different conditions and the corresponding P values should be provided. It seems that the transfected neurons generally have a longer AIS length than the transfected neurons (Fig. 2d and 3f). Could the authors provide an explanation for this?

      We are a bit confused by the first part of this comment. We measured the AIS lengths of NF186 WT or NF186 TAG as well as Nav1.6 TAG and compared it to the AIS lengths of surrounding untransfected cells (Fig. 2d and Fig.03f). In addition, we compared the AIS lengths of the NF186 WT and TAG to each other, and Nav1.6 TAG to each other. To analyze the differences, we performed statistical tests and provided the corresponding p values in the figure legends (Fig. 02 and 03). Further details on the statistical analysis are provided in supplementary tables (Suppl. table 01 and 02). Regarding the 2nd question, we have also noticed that the AIS lengths of transfected neurons appear longer than those of untransfected cells. This seems to be more pronounced in the case of NF186 which is expressed at the higher level compared to the Nav1.6. The appearance of slightly longer AIS is most likely the consequence of the fact that recombinant constructs are overexpressed in the neurons that express endogenous NF186 and Nav1.6. However, this difference in the AIS length is not significant to the controls. We will discuss this further in the revised manuscript.

      1. The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.

      We are thankful to the reviewer for suggestions on how to quantify the periodicity of recombinant sodium channels and how to more accurately compare WT and TAG mutants at the nanoscale level. We will perform additional experiments and analysis in order to address the concerns of this and other reviewers.

      1. The authors should also obtain dSTORM images for the click labeled neurons to demonstrate if the click labeling method would provide sufficient labeling efficiency for dSTORM, compared to immunostaining (HA and Ankyrin G immunostaining).

      We would like to thank the reviewer for this suggestion. We have already shown in our previous work that STED can be performed with click labeled neurons (PMID: 35031604). When it comes to this manuscript and AIS labeling, we have already obtained preliminary dSTORM images of click-labeled NF186. Since the expression of Nav1.6 is lower compared to NF186, the labeling is also less bright and dSTORM is a bit more challenging. To try to overcome this issue, in addition to dSTORM of click-labeled Nav1.6, we are planning to try click-PAINT (PMID: 27804198). Click-PAINT has been used for super-resolution imaging of less abundant targets in cells and could possibly allow super-resolution imaging of Nav1.6. We will report on these new experiments in the revised version of the manuscript.

      1. It seems that the click labeling has a off-target/background labeling in the soma of the neuron (see Fig. 3c,d. Could the authors quantify and determine the sources of such off-target labeling?

      We thank the reviewer for pointing this out. We will clarify this in the revised manuscript, but by looking at the other examples from our dataset it appears to us that this background is present in WT constructs as well. In the current version of the manuscript, this is not clear since the WT image that is shown in the Fig. 03b is a single plane confocal image. Therefore, we will replace it in the revised manuscript with a z-stack in which the presence of the background is more obvious (due to the maximum intensity projection). In addition, we will conduct additional control experiments to clarify this.

      Minor comments:

      1. The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.

      We thank the reviewer for bringing this up. By mistake, we omitted this important information. We will include this information in the revised manuscript, but we would like to highlight here that each experiment was repeated at least 3 times.

      1. The display range (i.e., intensity scale bar) was indicated only for a small portion of the fluorescence images. It is better to be consistent and show the display range for all images presented.

      We will include intensity scale bars in all the images in the revised version of the manuscript.

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

      Not applicable.

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

      Reviewer #3, comment #5. One application presented in this manuscript is to evaluate the effect of epilepsy-causing mutations of Nav1.6. By comparing the intensity of ATTO488, the result suggests that there is no significant impact of these mutations on membrane tracking. I am wondering if the author should study the membrane tracking by also looking at the diffusion in live-cell with the labeling method. The comparison of the intensity only can be achieved by just immunostaining. It doesn't really demonstrate the benefit of live-cell labeling and imaging with the presented method.

      Generally speaking, one of the advantages of click labeling is its compatibility with live cell labeling. As the reviewer also points out, this is especially useful for live-cell imaging but is not limited to it. In addition, click labeling allows selective labeling of membrane population of Nav1.6 in living neurons. We took advantage of this and used cell-impermeable dyes to label unnatural amino acids incorporated into extracellular part of Nav1.6 (Scheme 03a). On the contrary, HA tag that allows immunodetection of recombinant Nav1.6 is added to the intracellular C terminus. Hence, by anti-HA immunostaining total (intra- and extracellular) epilepsy-causing Nav1.6 channel population will be detected. That is why in this case live-cell click labeling was advantageous compared to the conventional immunostaining. We will clarify this in the revised manuscript. In addition, we would like to note that when we started the experiments with the epilepsy-causing mutations, we wanted to a) check if they are present on the membrane and b) depending on the outcome of those experiments follow the trafficking of these LOF Nav1.6 mutants. Since patch clamp recordings of pathogenic Nav1.6 showed loss of Na+ currents, we at first assumed that they are not properly expressed on the membrane. However, our click labeling showed that the pathogenic channels were detected at the AIS membrane despite the loss of Na+ currents. This was also somewhat surprising to us and we would love to investigate this further. We also appreciate the reviewer’s suggestion in this regard and we hope to be able to use all the advantages of our labeling approach in our follow-up studies. However, keeping in mind time and resources limitations, live-cell trafficking study might be beyond the scope of this revision.

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      Referee #5

      Evidence, reproducibility and clarity

      Summary:

      In this manuscript, Nevena Stajković et al. present a method for live labeling of the proteins localized at the axon initial segment (AIS) of cultured neurons using unnatural amino acids (UAAs) carrying strained alkenes and click chemistry. Using this method, the authors showed the successful labeling of two AIS-localized proteins, the 186 kDa isoform of neurofascin (NF186) and the 260 kDa voltage-gated sodium channel (NaV1.6). The authors also showed the transduction of neurons using adeno-associated viruses (AAVs) had higher efficiency than transfection by lipofectamine in delivering the vectors expressing required components for the click labeling.

      Major comments:

      1. Throughout the manuscript, only one representative image containing one AIG is shown for each condition without statistics and quantifications, so the conclusions are not sufficiently convincing. For example, in Fig. 1b, c, e; Fig. 2b,c,d,e; Fig. 3b,c,d,e ; Fig. 5c; and Supplementary Fig.1-6, the authors should quantify the average fluorescence intensities both for HA immunostaining and ATTO488-tz labeling in different conditions, as well as the labeling ratios (fluorescence intensity ratios between ATTO488 and AF647/AF555) . Without statistics and quantifications, it is unclear whether there is any significant difference between the constructs with different TAG positions, or between different transfection methods (e.g., lipofectamine 2000 vs 3000).
      2. The only quantification done was for the average AIS length, but the statistical tests should be preformed between different conditions and the corresponding P values should be provided. It seems that the transfected neurons generally have a longer AIS length than the transfected neurons (Fig. 2d and 3f). Could the authors provide an explanation for this?
      3. The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.
      4. The authors should also obtain dSTORM images for the click labeled neurons to demonstrate if the click labeling method would provide sufficient labeling efficiency for dSTORM, compared to immunostaining (HA and Ankyrin G immunostaining).
      5. It seems that the click labeling has a off-target/background labeling in the soma of the neuron ( see Fig. 3c,d. Could the authors quantify and determine the sources of such off-target labeling?

      Minor comments:

      1. The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.
      2. The display range (i.e., intensity scale bar) was indicated only for a small portion of the fluorescence images. It is better to be consistent and show the display range for all images presented.

      Significance

      Unnatural amino acid (UAA)-based minimal tags for live-cell protein labeling in mammalian cells were invented about ten years ago (Lang et al., 2012b, Lang et al., 2012a, Nikic et al., 2014, Plass et al., 2012, Uttamapinant et al., 2015), and these authors recently introduced this labeling method to label live cultured neurons (Arsić et al., 2022). Therefore, it is unclear whether the method present in this manuscript has any significant advance compared to the Arsić et al. paper, given that the major difference between the two papers is that in the current manuscript, AIS localized proteins were labeled, whereas in the Arsić et al. paper, neurofilaments were labeled in the neurons. Therefore, the method presented in the current manuscript does not provide much novelty or technical advance compared to what has been described in the Arsić et al. paper.

      My expertis is super-resolution flurescence imaging, cell labeling methods, and neurobiology.

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      Referee #4

      Evidence, reproducibility and clarity

      The manuscript demonstrates a novel method of labeling two large components of the initial axon segment, neurofascin (NF186) and Nav1.6 using unnatural amino acids and click chemistry in live cells. They have applied their method for epilepsy causing two Nav1.6 variants without affecting their functionality. Since these proteins are larger in size, selecting the labeling sites and transfection efficiency become critical factors. They have targeted different lysine sites and shown the best performing labeling site. Also, they have developed a viral vector to improve transfection efficiency.

      The experiments are well designed, and the manuscript is nicely written. In my opinion, the manuscript can be accepted, but the author should address the following comments.

      Major comments

      1. "Confocal microscopy revealed that the hNSE promoter lowered the WT and clickable NF186-HA expression levels and consequently improved the localization of these proteins." Is the lower expression level a measure of localization improvement? How does the author conclude that the localization has improved?
      2. "As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports.

      Minor comments

      1. "Although NF186K809TAG 158 -HA (Supplementary Fig. 4) showed bright click labeling, we excluded it from the analysis due to its frequent ectopic expression along the distal axon." How frequently is this bright click labeling observed for this mutation? Is it not observed for other mutations at all? The authors should state this point clearly with some statistics.
      2. "Immunostaining with anti-HA antibody revealed that the expression of NaV1.6WT 239 -HA on the membrane of the N1E-115-1 cells was higher than on the ND7/23 cells (Supplementary Fig. 5a-c). However, click labeling of both NaV1.6K1425TAG 240 -HA and NaV1.6K1546TAG 241 -HA with ATTO488-tz was not successful (Supplementary fig. 5d) indicating insufficient expression of the clickable constructs." Is this due to insufficient expression level or accessibility? The author should make this statement clear.
      3. Authors should clearly state the drift correction procedure of 3D STORM data. What are the localization precision and photon count for 3D STORM experiments?
      4. "Click labeling of NaV1.6 channels in living primary neurons" What kind of primary neurons have been used for click labeling of NaV1.6 channels? Is there any specific reason why authors have chosen cortical neurons for labeling NF186? Does this labeling strategy depend on primary neuron type?

      Significance

      Although the use of unnatural amino acids and click chemistry for labelling has been shown before from the same group, labelling large proteins, especially ion channels, without affecting their function is always challenging because of the accessibility of the labelling site as well as poor transfection efficiency. Here, they have selected two such large essential proteins: NF186 and Nav1.6, which are associated with epilepsy, and developed a method for fluorophore labelling with minimal perturbation. Other approaches namely using fluorescent proteins, biotin-streptavidin chemistry and halo-tag have been reported before to label these proteins, but these have a strong impact on their mislocalisation and perturbing their functionality. Therefore, this method will be of great importance in the field of studying these proteins.

      Expertise: Live-cell confocal and multi-photon microscopy imaging, Super-resolution microscopy imaging, Live-cell labelling, and Amyloid aggregations

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      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      This study proposes a novel tool for AIS live and fixed labelling based on biorthogonal click chemistry. Stajkovic and colleagues used this method to specifically label the AIS proteins NF186 and Nav1.6 of mouse and rat neurons, and did a thorough process of optimization to get convincing results. The authors considered different promoters, transfection strategies and the use of AAVs to get the most efficient labelling strategy for both proteins. They have also gone through a strong validation process based on transfection efficiency, quality of staining, potential effects on AIS length and nanostructure, and electrophysiological properties. Finally, Stajkovic and colleagues used this tool to study how two epilepsy-causing Nav1.6 mutant variants affect AIS function, providing interesting data to the understanding of this pathology. In summary, this method convincingly overcomes some well-described issues associated with pre-existing AIS live cell labelling tools by being minimally "invasive" to the proteins of interest. Besides the scientific content, another strong point of this article is the clarity of the manuscript and the figures: the presence of schematics (i.e. Fig. 1) and the detailed description of experiments and results will help non-specialist readers to follow the study. I strongly recommend this article for journal publication.

      Major comments:

      I have no major comments

      Minor comments:

      I have some minor comments:

      • On lines 107 and 108, the sentence "The C-terminal HA-tag allowed us to detect the full-length NF-186 protein by immunostaining it with an anti-HA antibody" would have a better place just after lines 104-105 " [...] we modified the previously described plasmid (Zhang et al., 1998) by moving the hemagglutinin (HA) tag from the N terminus to the C terminus".
      • Fig.2b: the AnkG staining looks substantially longer than that showed in c. However, the results on AIS length show no significant changes in between the groups. This is visually misleading, the authors should choose a picture for the WT construct that is representative of the data.
      • Line 238: what is the rationale behind choosing these cells? For example, have they been used in other studies for similar purposes? If so, please provide the reference.
      • Figure 3c, the authors omitted the comparison with the WT construct this time, as opposed to the neurofascin experiments. What is the reason?
      • Fig. 4: why did the authors chose these cells for electrophysiology experiments and not neurons? Explain the rationale in the text or, alternatively, cite similar studies using the same tool.
      • Fig.4, biophysical properties: did the authors find differences in passive properties? Measures of resting potential, membrane resistance and cell capacitance should be reported.
      • Fig 4, STORM images. The periodic distribution of the dots should be enhanced with some sort of arrows or lines, for the non-specialist audience.
      • Line 374: rat or mouse primary neurons?

      Referees cross-commenting

      I fully agree with the following remarks from Reviewers #3, #4 and #5. This is a point that I have raised in my report too. The authors need better images to show the periodicity visualization, and a quantification would be of great benefit to support the claim with numbers (and how these compare to similar studies in the literature):

      R3: 2. For the dSTORM analysis of the tagged Nav1.6 protein, I also cannot tell there is periodic organization from the image directly. Some analysis is needed there. R4: 2."As there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), these experiments confirmed that the NaV1.6 overexpression, TCO*A319 Lys incorporation, and click labeling did not affect the nanoscale periodic organization of the sodium channels in the AIS." It is clearly noticeable that for WT, the spot density is more compared to the other two mutants. Why is that so? Using cluster analysis, one can quantify spot density and discuss nanoscale organization quantitatively. The author should quantify the periodicity and compare it among different variants and with previous reports. R5: 3. The authors claim that there was no obvious difference in the nanoscale organization of the NaV1.6WT 317 -HA or NaV1.6TAG 318 -HA channels (Fig. 4. e-g), but it is hard to conclude this without any quantification and statistical analysis. Sodium channels have been shown to be associated with the membrane-associated periodic skeleton structures in neurons and average autocorrelation analysis has been developed to quantify the degree of periodicity of such structural organizations (Han et al. PNAS 114(32)E6678-E6685, 2017). The authors should use this approach to quantify and compare the average autocorrelation amplitudes.

      I also agree with these comments from Reviewers #3 and #5:

      R3: 4. It is unclear, for all the presented data, whether all the cells are collected from a single biological replicate or from multiple replicates. At least 2-3 replicates are needed to see the reproducibility in terms of labeling efficiency, and other related conclusions. R5: 1. The authors should indicate how many replicates were performed and how many cells were analyzed for each experiment.

      Significance

      The proposed tool in this article represents a big step forward in the field of AIS live cell imaging. As stated by the authors in the introduction, previous studies have described methods based on tagging fluorescent proteins to the protein of interest or labelling the extracellular part of proteins with antibodies. The same studies reported several issues: the interference with important domains of the protein due to the size and the position of the tag in the case of fluorescent proteins (Dumitrescu et al., 2016, PMID: 27932952; Dzhashiashvili et al., 2007, PMID: 17548513), or the failure to report plasticity changes in the AIS in the case of antibodies (Dumitrescu et al., 2016, PMID: 27932952). This tool can be useful for research teams aiming to understand, for example, the live development of the AIS or understanding the trafficking of its proteins. The authors have applied this method to two transmembrane proteins (NF186 and Nav1.6), but as they state in their discussion, it will be useful to tag other candidates, including cytoplasmic proteins. One of the main problems of immunocytochemistry is to find the right antibody to detect your protein. Sometimes, absence of proof is not proof of absence: just because the protein is not detected via immunostaining does not mean that the protein is not expressed there. This tool offers an alternative to these challenging scenarios.

      My expertise keywords: axon initial segment, neuronal polarity, axon biology, super resolution microscopy.

    1. When the HTML parser finds a <script> tag, it pauses the parsing of the HTML document and has to load, parse, and execute the JavaScript code. Why? because JavaScript can change the shape of the document using things like document.write() which changes the entire DOM structure

      This is why you put script tags at the bottom of an html document.

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      Reply to the reviewers

      We are sincerely grateful to the reviewers for several key comments that led us to correct some mistakes and better appreciate how to put our findings in the context of recently published data. These changes undoubtedly improved the manuscript.

      Many other reviewer comments seem to equate chaperone binding with a functional chaperone role in de novo folding. These are not the same. Cytosolic chaperones presumably “sample” nearly every protein that is synthesized by cytoplasmic ribosomes. This does not mean that every such protein would misfold if even one of those chaperones failed to bind it. If we want to understand what chaperone mutations might cause human disease due to septin misfolding, for example, it will not be enough to catalog all the chaperones that bind septins. We have already done that. What will help is to understand which chaperones make functional contributions to septin folding and complex assembly. Our study is the first to experimentally address chaperone roles in de novo septin folding, period. We take responsibility for not being sufficiently clear about the goals of our work, and, to emphasize these points, we added one sentence to the Introduction and revised another.

      Another consistent criticism was that the use of the E. coli system, both in vivo and in vitro, limited our ability to gain insight into the folding of septins in eukaryotic cells and led to a “tessellated view”. For example, reviewers claimed that our model about translation elongation rates for Cdc12 were “based mainly on the E. coli system and bioinformatics analysis”. We disagree with this interpretation. Key evidence in support of our model come from published data in yeast, specifically the much higher density of ribosomes on Cdc12 and the accumulation of ribosomes on the Pro-rich cluster near the Cdc12 N terminus. These are precisely the kinds of “more stringent analysis” in “authentic yeast” (to use Reviewers’ language) that we would have wanted to do to test our model, had they not already been done by others. Without specific suggestions, we struggle to imagine what other kinds of experiments the Reviewers have in mind, apart from a eukaryotic version of a reconstituted cell-free translation system, which Reviewer #1 admits “would be substantially difficult” and “time consuming”. While we are intrigued by the reconstituted eukaryotic cell-free translation system that was published last year (which we mentioned on lines 994-995) and look forward to exploring it in future studies, it is not commercially available and we agree that the amount of effort required to prepare it ourselves is unrealistic for the current study. Most importantly, we do not find in the critiques provided any specific reason why our E. coli-based systems experiments are intrinsically less “stringent” or “rigorous”.

      Accordingly, we think that, together with the results of multiple new experiments (detailed below), the extensive re-writing and re-ordering that we have done in the revised manuscript will be enough to better emphasize the importance and rigor of our findings and thus to address all of the Reviewers’ specific concerns.

      Reviewer 1 thought that our manuscript “does not even provide new information, since the involvement of CCT and the Hsp70 system is not novel” and thought that “the key finding of this manuscript is how chaperones are involved in the de novo folding of septins, which is not conceptually new because of previous findings, including those of the authors”. Reviewer #3 also stated that “the function of Tric/CCT in septin folding and assembly is well documented”.

      We were quite surprised at this reaction, since we dedicated a significant portion of the original manuscript (lines 68-76 and 319-322) to explicitly discussing the only other paper in the literature that specifically addresses the question of whether or not CCT is required for de novo septin folding. As a reminder, that paper explicitly stated that “it is unlikely that CCT is required to fold septins de novo” and “septins probably do not need CCT for biogenesis or folding”. With regard to involvement of the Hsp70 system, the only existing evidence in the literature on this subject is the aggregation of some septins in ssb1∆ ssb2∆ cells. Like the CCT study, that study did not distinguish whether this was a result of problems during septin synthesis and before septin complex assembly, or, alternatively, whether pre-folded and assembled septins were subject to disassembly, misfolding, and aggregation. Our experiments specifically test the fate of newly-synthesized septins prior to assembly in living cells. Our previous findings documented physical interactions between wild-type septins and multiple chaperones but did not address whether these interactions had any functional relevance. We previously reported functional effects of interactions between chaperones and MUTANT septins but, again, these studies did not address functional chaperone requirements for WILD-TYPE septins. While we did our best to highlight these points in the original document without devoting excessive amounts of text, we accept responsibility for not making these points sufficiently clear and to address this issue we added additional text, including the text quoted above, to the Introduction.

      While Reviewer #3 commented that the manuscript “is overall well presented”, Reviewer 1 thought that the manuscript was “complicated to read” with “no logical connections, just a list of many results” and mentioned that part of the difficulty was “that it contains many negative results”.

      In addition to reorganizing the manuscript, as suggested by the reviewers, we added more text at the beginning and end of nearly every section to even more explicitly state the logical connections between results. In our opinion, negative results of properly controlled experiments are valuable to the research community, and we do not understand what it is about negative results that makes them difficult to read about. Many of the extra experiments we performed were in anticipation of being asked to perform them by reviewers, some of which generated negative results. We are reluctant to remove negative results unless there is a more compelling reason. For example, to address another reviewer concern, we did remove the negative results with the Ydj1–Ssa2 compensatory mutants.

      Reviewer #2: “4) Figure 2: The labeling on the protein structure makes it seem like the exact region for Ydj1 and Hsp70 was experimentally identified, when it hasn’t.”

      We acknowledge that the first sentence of the figure legend (“the colored ribbon follows the color scheme in the sequences at right for overlapping β-aggregation, Ydj1 and Hsp70-binding sites”) could be misinterpreted, since only in the second sentence does it say “Sequence alignments show predicted binding sites”. We corrected this mistake, and added the text “Predicted chaperone binding sites” as the first words in the legend to this figure.

      Reviewer #2: “8) The authors confusingly jump back and forth between different Septins and different chaperone (Ssa1-4, Ydj1, Sis1, Hsp104). We would ask the authors to re-arrange the manuscript, collating all the yeast work in one section and bacterial work in another.”

      We re-arranged the manuscript and put all the yeast work in one section and all the bacterial work in another, with the exception of the studies of individually purified Cdc3 and Cdc12, which we put in between the yeast studies of the kinetics of de novo assembly and the yeast studies of post-translational assembly. Our reasoning is that the studies with the purified proteins demonstrate challenges with maintaining native conformations in the absence of chaperones and other septins, which flows naturally into the yeast studies asking about the ability of “excess” septins to maintain oligomerization-competent conformations in the absence of other septins and when we experimentally eliminate specific chaperones. All of the work actually manipulating E. coli genes/proteins is now together.

      Reviewer #3: “1. The co-translational binding of CCT to nascent polypeptide chains has been studied (Stein et al., Mol Cell 2019). While the authors indicate that septin subunits are engaged co-translationally, they do not comment which ones are interacting with CCT and at which state of translation. This information is crucial and should also be mentioned in the discussion section.”

      We are grateful to the Reviewer for bringing up this point, which we had overlooked. We hadn’t noticed that, in the end, only Cdc3 met the CCT confidence threshold to be included in the supplemental data of the Stein et al. paper. All septins co-purified with CCT in an earlier Dekker et al proteomic study, so we strongly suspect that the failure of the other septins to meet the confidence threshold in the Stein et al paper reflects the sensitivity of that assay, rather than a significant difference in how septin GTPase domains interact with CCT. We also hadn’t appreciated that according to that study, the main sites in the Cdc3 GTPase domain bound by CCT and Ssb are the same. Hence our statement that Ssb bound to septins “earlier” during translation, and CCT bound “later” was wrong. Instead, the overlapping Ssb and CCT site in Cdc3 turns out to be remarkably consistent with a conclusion from Stein et al paper, that CCT binds Rossmann-fold proteins like septins at sites where “early” beta strands have been translated and expose a chaperone-binding surface that later becomes buried by an alpha helix. We corrected our mistake in the text and in our model figure and added: (1) a new supplemental figure with predicted septin structures and a sequence alignment indicating where CCT and Ssb bound; and (2) text discussing the confidence thresholds for “calling” septin-CCT interaction, the Rossmann-fold binding, and how we interpret Ssb and CCT binding to the same site.

      Reviewer #3 “3. Figure 3: It is recommended to also follow Cdc10-GFP and Cdc12-GFP fluorescence. This will on the one hand generalize the presented findings and provide a direct link to other parts of the study (e.g. crosslinking analysis of Cdc10).

      We carried out the requested experiment for Cdc12, using Cdc12-mCherry rather than Cdc12-GFP because of the formation of non-native foci that we observed with Cdc12-GFP. We also attempted to analyze Cdc10, using an existing GAL1/10-promoter-driven Cdc10-mCherry plasmid that we’d made a few years ago, but it did not behave as expected, with high expression even in the absence of galactose (not shown), which prevented us from performing the requested experiment. We have a Cdc10-GFP plasmid with the inducible MET15 promoter, but this promoter does not provide sufficiently low levels of expression in repressive conditions, so there would be too much expression at the beginning of the experiment for us to accurately follow accumulation thereafter. Instead, we tried the only other plasmid we had with the GAL1/10-promoter controlling a tagged septin: Cdc11-GFP. Above a certain threshold of expression, Cdc11-GFP formed unexpected cortical foci, but we were still able to perform the analysis and found a clear delay in septin ring signal in cct4 cells, providing the requested generalization to other septins, if not Cdc10.

      Reviewer #3 “5. Figure 4C: The finding that only ssb1 but not ssb2 knockouts have an effect on joining of free Cdc12-mCherry subunits into septin rings is puzzling. Similarly, Ssb1 largely acts co-translationally, while in this assay post-translational septin ring assembly is monitored. The authors need to comment on these two points.”

      We did not examine ssb2 knockouts, so we do not know to what the Reviewer is referring in the first point. If the Reviewer means that they are puzzled by the fact that we saw a phenotype in cells in which only SSB1 was deleted and SSB2 remained, we offer two explanations. As can be seen in the Saccharomyces Genome Database entry for SSB1 (https://yeastgenome.org/locus/S000002388/phenotype), there are at least a dozen known phenotypes associated with deletion of SSB1 in cells with wild-type SSB2. We even showed a very clear septin misfolding/mislocalization phenotype in Supplemental Figure 4D. Thus while our findings are new and provide novel insights into Ssb function, they are not unprecedented. The Reviewer is correct that most Ssb is ribosome-bound and thus Ssb1 “largely acts co-translationally” but ~25% of Ssb is not ribosome-associated (PMID: 1394434). Furthermore, the lack of a strong phenotype for ssb1∆ cells in our new kinetics-of-folding experiment (see below), plus the realization that Ssb and CCT both bind the same site in Cdc3, leads us to a new model: Ssb acts both co- and post-translationally in septin folding, but only the post-translational function is associated with a phenotype in ssb1∆ cells, because in that assay we drastically overexpress a tagged septin and thereby exceed the Ssb chaperone capacity that remains when we delete SSB1. This logic also explains the first ssb1∆ phenotype we saw, when overexpressing Cdc10(D182N)-GFP. In the kinetics-of-folding assay, on the other hand, tagged septin expression is much lower and reducing the amount of total Ssb by ~50% (via SSB1 deletion) likely does not compromise Ssb function in folding the tagged septin. We therefore removed our statement that “Ssb dysfunction leaves nascent septins in non-native conformations that are aggregation-prone and unrecognizable to CCT”, revised our model figure accordingly, and added new text and citations to explain our new model.

      Reviewer #3 “Additionally, they should test whether the appearance of septin ring fluorescence is slowed down in ssb1 mutants (as shown for cct4-1 mutant cells in Figure 3B).”

      We agree that slower septin folding in ssb1∆ cells is a prediction of our model, and we performed the requested experiment and include the results in our revised manuscript. The new data show that the appearance of septin ring fluorescence is not delayed in ssb1∆ mutants, which is easily explained by the ability of Ssb2 to chaperone the folding of the low levels of tagged septin that we express in these kinds of experiments (see above).

      Reviewer #3: “7. Figure 5G: The data is not convincing. This reviewer cannot detect a specific Cdc12 band accumulating in presence of GroEL/ES.”

      We re-ran the reactions again with fresh reagents and this time ran the gel longer to reduce excess signal from free fluorescent puromycin and the bright Cdc10 bands. We now see a very clear band for full-length Cdc12 in the reaction with added GroEL/ES, fully consistent with our mass spectrometry results. We updated the figure with the new results.

      Reviewer #3: “Furthermore, the activity tests done for the chaperonin system are confusing (Supplemental Figure 7). The ATPase rate (slope!) of GroEL/GroES seems higher as compared to GroEL but according to the authors it should be opposite.”

      In our assays, the ATPase activity is so fast that for our “time 0” timepoint, much of it has already occurred by the time the reaction can be physically stopped and measured. In other words, the handling time is such that we can’t visualize what happened in the earliest stages of the reaction, where the rates could accurately be estimated as slopes. This is obvious from the fact that at time 0, the absorbance for the “GroEL alone” reaction is already more than twice the absorbance for GroEL+ES. We added clarifying text to the figure legend.

      Reviewer #3: “The refolding assay using Rhodanese as substrate is also confusing: What is the activity of native Rhodanese? The aggregated Rhodanese sample seems to have substantial activity that is not too different from a GroEL/ES-treated one. From the presented data it is not clear to the reviewer to which extend GroEL/ES prevents aggregation and supports folding of denatured Rhodanese.”

      We thank the Reviewer for bringing this to our attention, because made we mistakenly left out the values for native Rhodanese with the reporter. With regard to the aggregated Rhodanese, we failed to note that this sample contains urea. When the urea absorbance is subtracted, it is clear that the GroEL/ES-treated sample has higher activity. Furthermore, some native enzyme is likely still active within the aggregated sample, explaining the “substantial activity” that the Reviewer correctly notes. We corrected the figure and added clarifying text to the figure legend.

      Reviewer #3: “the study goes astray following aspects that does not seem relevant to this reviewer (e.g. the role of N-terminal proline residues for Cdc12 translation, Fig. 5E/F).”

      We acknowledge that we did a poor job of introducing the N-terminal Pro-rich cluster in Cdc12 with relation to our model of slow Cdc12 translation. Instead, we have revised and reorganized the manuscript to set up these experiments as a direct test of our model: if ribosome collisions on the body of the ORF drive mRNA decay, then decreasing the spacing of those ribosomes should exacerbate the problem, and eliminating the Pro-rich cluster (where published yeast data already show ribosomes accumulate) is the most logical way to test the prediction. Far from being irrelevant, the results fit the prediction perfectly and thus support the model. We expect that this change will highlight the importance of these experiments for the reader.

      Reviewer #2: “1) Fig. 1 Is the folding of Cdc3 being measured in cells lacking chaperones mentioned towards the end of the paper or are the authors referring to the lack of yeast proteins?”

      We are unclear as to what the Reviewer is asking here. The title of Figure 1 states that these are “purified yeast septins” and the figure legend further emphasizes this fact. Additionally, the Coomassie-stained gel in Figure 1A shows a single band, corresponding to purified 6xHis-Cdc3. The proteins were purified from wild-type E. coli cells, so all E. coli chaperones were present when Cdc3 initially folded, but chaperones and all other proteins were removed during the purification and prior to the analysis. We do not know what change to make.

      Reviewer #2 asked “How do the authors account for the septin defect in Ssa4 delete cells in unstressed conditions where Ssa4 would be very low already? According to the authors previous work, Ssa2 and 3 should be able to compensate.”

      We explicitly addressed this point in the original manuscript (lines 893-898). Again, we think here the Reviewer is equating chaperone binding with chaperone function. According to our previous work, Ssa2 and Ssa3 are able to bind septins, but this does not mean that they can fold septins the same way as Ssa4. We cite several papers that discuss the distinct functional roles for the different Ssa proteins. We do not think that additional clarification of this point would strengthen the manuscript.

      Reviewer #3: “6. Figure 5B: It is unclear why Cdc3 is observed in the pulldown of His-tagged Cdc12 (37˚C), although no Cdc12 was isolated under these conditions. How is that possible?”

      That is not possible. As we indicate in the figure legend and with the red asterisk, the only band appearing in that lane is a non-specific band that cross-reacts with the anti-Cdc3 and/or anti-Cdc11 antibodies. This is why it is also present in the “No septins” control lanes. We made the asterisk larger to help accentuate this point.

      Reviewer #3: “Furthermore, the authors observe a specific effect on Cdc12-Cdc11 assembly in the E. coli groEL mutant. How do they rationalize this specific effect as Cdc12-Cdc3 assembly remained unchanged? This observation also seems in conflict with the suggestion of the authors that Cdc12 preferentially recruits Cdc11 before interacting with Cdc3 (page 45, lane 1024).”

      Cdc11 was not expressed in the groEL mutants because no Cdc11 gene was present in those cells, as explained in the body text and indicated in the labeling above the lanes in Figure 5A. The band near the size of Cdc11 is a non-septin protein that bound to the beads in the groEL-mutant cells, as is shown in the immunoblot using anti-Cdc11 antibodies in Figure 5B. Thus there is no conflict to rationalize.

      Reviewer #1: “The only evidence that CCT binds to septin is the list of LC-MS/MS. Western blotting would provide more solid data.” and “2) The cross-linking experiments appears not to have been successful. Why are the Ssas, Ydjs etc not detected here? “

      First, CCT subunits are relatively low-abundance, expressed at 5- to 50-fold lower levels than other chaperone families in the yeast cytosol (see PMID: 23420633). To the Reviewer’s second point, we did in fact detect other chaperones in our crosslinking mass spectrometry experiments, including Ydj1, multiple Ssa and Ssb chaperones, Hsp104, etc., as can be seen in Table S1. However, they were also detected in negative control experiments. This is not surprising, given that these chaperones are among the most common “contaminants” of affinity-based purification schemes (see the CRAPome database at https://reprint-apms.org/). It was for this reason we had to perform so many negative control experiments, which likely produced some false negative results, as some “real” interactions were likely discarded when the same chaperone showed up in our controls. We added a figure panel with a Venn diagram of overlap between experimental and control samples, and text pointing out this caveat of our approach.

      Second, in this experiment we attempted to identify proteins that transiently interact with a specific region of Cdc10 that will later become buried in a septin-septin oligomerization interface. Due to the transient nature of the interaction, we do not expect to detect high levels of crosslinked chaperones. Mass spectrometry is significantly more sensitive than immunoblotting, so there is no guarantee that we would be able to detect a band even if the crosslinking works as desired. Indeed, the crosslinked bands we saw by immunoblot for GroEL were quite faint (see Figure 2F), despite the fact that GroEL and the T7-promoter-driven Cdc10 were among the most abundant proteins in those E. coli cells.

      Third, there is no commercially available, verified antibody recognizing yeast Cct3 for which to perform the requested immunoblot experiment. Since both the N and C termini of CCT subunits project into the folding chamber, it is unwise to use a standard epitope tagging approach, as the tags may compromise function. Indeed, for purification purposes others inserted an affinity tag in an internal loop in Cct3 (PMID: 16762366). We have a yeast strain with Cct6 tagged in an analogous way, but to perform the requested immunoblot experiment with Cct3 would require creating or obtaining the Cct3-tagged strain, deleting NAM1/UPF1, and introducing our Bpa tRNA/synthetase and GST-6xHis-Cdc10 plasmids. Given the sensitivity of detection concerns stated above, we doubt this would help.

      In summary, we prefer not to attempt the requested immunoblot experiments.

      Reviewer #1: “-Fig. 3B ant related Figures: The experiment to see if GFP-tagged septin accumulates in the bud neck is important, but only the graphs after the analysis are shown. The authors should provide the readers with representative examples from imaging data.”

      We are confused, because the images at the bottom of Figure 3A already show what the Reviewer requests. As stated in the figure legend, these are representative examples of the imaging data from a middle timepoint of one of the experiments. It would be nearly impossible (for space reasons) to provide representative images for all of the timepoints for all of the genotypes for all of the experiments. Since in our new experiments we introduce new tagged septins (Cdc11-GFP and Cdc12-mCherry), we also now include representative images of cells expressing these proteins, as well.

      Reviewer #2: “3) If the authors had evidence of chaperone interaction from their previous study, why did they not simply do IPs with fragments of the septins/chaperones?”

      We are unclear why the Reviewer is suggesting IPs after referring to our previous study. IPs are a poor choice for transient interactions, which is why we mostly avoided them in previous studies, and instead used a novel approach (BiFC) to “trap” chaperone–septin interactions. Moreover, we seek to identify chaperones that bind wild-type septins at future septin-septin interfaces on the path towards the native conformation. Fragments of septin proteins would likely misfold and would therefore likely attract chaperones that wouldn’t normally bind the full-length septin. Indeed, our previous studies demonstrated that even a single non-conservative amino acid substitution was sufficient to alter chaperone-septin binding. Thus IPs with fragments of septins or chaperones would be highly unlikely to yield informative results for the questions we seek to answer. We strongly prefer not to attempt these suggested experiments.

      Reviewer #2: “5) While differences between Ssa paralogs are highly interesting, using deletions of Ssas is not useful, given that yeast compensate by overexpressing other paralogs. The yeast GFP Septin assays should be repeated in yeast lacking all Ssas and expressing one paralog on a constitutive promoter (See numerous papers by Sharma and Masison).”

      We disagree that ssa deletions are “not useful”, since if the overexpressed paralogs cannot fulfill the same function as the deleted SSA, then we will see a phenotype. Which we do. Furthermore, we had already obtained and thoroughly tested a strain like the ones mentioned by the reviewer (ECY487, a.k.a. JN516, from Betty Craig’s lab, with ssa2∆ ssa3∆ ssa4∆ and SSA1, which is constitutively expressed, PMID: 8754838), but we found that, as published, it divides slightly more slowly even under the most permissive of conditions. The requested strain cannot be analyzed using our method, because slow accumulation of ring fluorescence could be attributed to other defects unrelated to septin folding. Thus we strongly prefer not to attempt the suggested experiments.

      Reviewer #2: “7) The authors need to clarify the experiment with the Ydj1 D36N and Ssa2 R169H. In Reidy et al, they never fully biochemically test this system and it was never examined for Ssa2-Ydj1. The authors would need to do some fundamental experiments to demonstrate the validity and functionality of this double mutant in yeast.”

      Given that this experiment was unable to generate meaningful data, since the mutations affected the kinetics of induction of the GAL1/10 promoter, we do not think the requested biochemical experiments would add any value to the study. Instead, we removed these studies from the manuscript.

      Reviewer #3: “4. Figure 3B: The difference between wt and cct4-1 cells in appearance of septin ring fluorescence is observed at one timepoint. Since this experiment is considered highly relevant, the authors are asked to include another timepoint to bolster the conclusion that Cdc3-GFP folding and thus septin ring assembly is delayed in the CCT mutant.”

      We carried out new experiments with cct4-1 cells using Cdc12-mCherry and Cdc11-GFP with more timepoints than in our original cct4-1 experiments with Cdc3-GFP. Since these experiments provide the same kinds of results, but at multiple timepoints, we do not see the value in repeating the Cdc3-GFP experiment.

      Reviewer #3: “If Ssb1 functions to maintain Cdc12 in an assembly competent state preventing misfolding, one would expect either enhanced degradation or aggregation of Cdc12-mCherry in ssb1 mutant cells. Did the authors check for such scenario? Septin aggregation has been shown in a ssb1 ssb2 double deletion strain (Willmund et al., 2013), yet the data shown here predict that aggregation might already occur in single ssb1 mutants.”

      We already examined septin aggregation in single ssb1 mutants and showed these data (Supplementary Figure 4D). Indeed, this phenotype was the rationale for testing post-translational septin assembly in ssb1 single mutants. We have seen no evidence of septin degradation in any context (as we mentioned on line 889), so we would not expect it here. While we added new text and a very new citation showing that many “misfolded” conformations of wild-type E. coli proteins avoid aggregation and degradation, we do not think that the suggested experiments would add enough value to the current study to justify the effort, time and expense.

      Reviewer #3: “Fig. 3C: The figure showing septin ring fluorescence does not include error bars. This is crucial, also because the difference between wt and ssa4 mutant cells is not large.”

      There are, in fact, error bars included in the figure, as can be most clearly seen for the final timepoint for the ssa4∆ cells. For most of the other timepoints the error bars are smaller than the data point symbols (the circles and squares). We do not think that adjusting the size or opacity of the symbols to better show the error bars will be sufficiently valuable to justify the effort.

    1. I found this comment to be surprising as I have never heard of the "Black Identity Extremist" tag. Because I was interested in this, I did further research using Caulfield's “check for other coverage” technique and looked into it.

    2. The FBI said it has stopped using the "Black Identity Extremist" tag and acknowledged that white supremacist violence is the biggest terrorist threat this country faces. https://trib.al/OepGw2S

      To my understanding this is not exactly accurate and by that I mean, it is from multiple people and not organically sourced which can make it unreliable.

    3. The FBI said it has stopped using the "Black Identity Extremist" tag and acknowledged that white supremacist violence is the biggest terrorist threat this country faces.

      The Root was a black justice community organizer, but after scrolling over the check, I discovered it is a digital magazine platform something which shares previously believed information from numerous black perspectives. I was using the majority opinion for other coverage and discovered that there is no actual news on this and that the link in the tweet shared is to their blog post.

    4. The FBI said it has stopped using the "Black Identity Extremist" tag and acknowledged that white supremacist violence is the biggest terrorist threat this country faces.

      This article is so true. White terrorism and White supremacy has been the biggest threat to our American citizens. The basis of being an all white society and hurting or harming those who do not fit is blatant terrorism.

    1. we're gonna sanction the periodic table original question alex which is that these people live in a land of illusions 00:21:08 they live in a relationship in a fantasy world that you know you know i last i checked you can't tag atoms of gold with um with nfps or with little markers on the blockchain in order to figure out where they came from

      sanction the periodic table

      fantasy world

      can't tag atoms of gold with urn nfts

    1. https://www.zylstra.org/blog/2022/06/spring-83/

      I've been thinking about this sort of thing off and on myself.

      I too almost immediately thought of Fraidyc.at and its nudge at shifting the importance of content based on time and recency. I'd love to have a social reader with additional affordances for both this time shifting and Ton's idea of reading based on social distance.

      I'm struck by the seemingly related idea of @peterhagen's LindyLearn platform and annotations: https://annotations.lindylearn.io/new/ which focuses on taking some of the longer term interesting ideas as the basis for browsing and chewing on. Though even here, one needs some of the odd, the cutting edge, and the avant garde in their balanced internet diet. Would Spring '83 provide some of this?

      I'm also struck by some similarities this has with the idea of Derek Siver's /now page movement. I see some updating regularly while others have let it slip by the wayside. Still the "board" of users exists, though one must click through a sea of mostly smiling and welcoming faces to get to it the individual pieces of content. (The smiling faces are more inviting and personal than the cacophony of yelling and chaos I see in models for Spring '83.) This reminds me of Stanley Meyers' frequent assertion that he attempted to design a certain "sense of quiet" into the early television show Dragnet to balance the seeming loudness of the everyday as well as the noise of other contemporaneous television programming.

      The form reminds me a bit of the signature pages of one's high school year book. But here, instead of the goal being timeless scribbles, one has the opportunity to change the message over time. Does the potential commercialization of the form (you know it will happen in a VC world crazed with surveillance capitalism) follow the same trajectory of the old college paper facebook? Next up, Yearbook.com!

      Beyond the thing as a standard, I wondered what the actual form of Spring '83 adds to a broader conversation? What does it add to the diversity of voices that we don't already see in other spaces. How might it be abused? Would people come back to it regularly? What might be its emergent properties?

      It definitely seems quirky and fun in and old school web sort of way, but it also stresses me out looking at the zany busyness of some of the examples of magazine stands. The general form reminds me of the bargain bins at book stores which have the promise of finding valuable hidden gems and at an excellent price, but often the ideas and quality of what I find usually isn't worth the discounted price and the return on investment is rarely worth the effort. How might this get beyond these forms?

      It also brings up the idea of what other online forms we may have had with this same sort of raw experimentation? How might the internet have looked if there had been a bigger rise of the wiki before that of the blog? What would the world be like if Webmention had existed before social media rose to prominence? Did we somehow miss some interesting digital animals because the web rose so quickly to prominence without more early experimentation before its "Cambrian explosion"?

      I've been thinking about distilled note taking forms recently and what a network of atomic ideas on index cards look like and what emerges from them. What if the standard were digital index cards that linked and cross linked to each other, particularly in a world without adherence to time based orders and streams? What does a new story look like if I can pull out a card either at random or based on a single topic and only see it or perhaps some short linked chain of ideas (mine or others) which come along with it? Does the choice of a random "Markov monkey" change my thinking or perspective? What comes out of this jar of Pandora? Is it just a new form of cadavre exquis?

      This standard has been out for a bit and presumably folks are experimenting with it. What do the early results look like? How are they using it? Do they like it? Does it need more scale? What do small changes make to the overall form?


      For more on these related ideas, see: https://hypothes.is/search?q=tag%3A%22spring+%2783%22

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

      Learn more at Review Commons


      Reply to the reviewers

      Response to the reviewers

      Manuscript number: RC-2022-01407

      Corresponding author(s): Ivana, Nikić-Spiegel

      1. General Statements

      We would like to thank the reviewers for careful reading of our manuscript and for their insightful and useful comments. We are happy to see that the reviewers find these results to be of interest and significance. The way we understand reviewers’ reports, their main concerns can be roughly divided in following categories: 1) providing more quantitative data 2) interpretation of the Annexin V/PI assay 3) additional evidence for calpain involvement. We intend to address these experimentally or by modifying the text, as outlined below.

      2. Description of the planned revisions

      Reviewer #1

      Fig1A/B o SYTO 16 staining suggests slight reshaping of nucleus upon spermine NONOate, showing less blurry punctae. From the SYTO 16 profile, this should be quantifiable.

      By looking at the shown examples and the entire dataset, it appears to us as if neuronal nuclei are shrinking upon spermine NONOate treatment resulting in their less blurry appearance. We are not sure if this is what the reviewer is referring to, but this can also be quantified by measuring changes in neuronal nuclear size. We already have this data from the measurements shown in Fig4 and we intend to show it in the revised version of the manuscript. Line profile measurements are also possible, but the nuclear size quantification might be more suitable for this purpose.

      o There is a subset of neuron nuclei that are SYTO 16 positive. Please quantify the ratio

      We will use our existing dataset to quantify the ratio of NFL positive and SYTO16 positive nuclei.

      FigS1A o Show NeuN with Anti-NFL merged figures

      We will show merged NeuN and anti-NFL images, which might require rearrangement of the existing figures and figure panels. We will do this in the revised manuscript.

      FigS1C o Show quantification and timeline. I want to know whether there is also a plateau reached here.

      As the data shown in the FigS1C do not include NeuN staining, we will do additional experiments and perform proposed quantifications.

      FigS2A-F o Though the statements might be true, selecting one nucleus for a line profile as a statement for the whole dataset seems problematic. Average a larger number of unbiased selected nuclei profiles across multiple cultures to make a stronger statement, or a percentage of positive nuclei as in FigS1b.

      Corresponding images and line profiles are representative of the entire dataset. However, we agree with the reviewer that this is not obvious from the current manuscript version. Thus, to strengthen our findings, we intend to quantify the percentage of positive nuclei as in FigS1b. The only difference will be that instead of NeuN, we will use SYTO16 as a nuclear marker. The reason being that the existing datasets contain images of NFL and SYTO16 and not NeuN.

      FigS3 • There are no fluorescence profiles, no quantification

      As the reviewer suggests, we will quantify the ratio of NFL positive and SYTO16 positive nuclei, and include the quantifications in the revised manuscript.

      General statement: There do seem to be punctated patterns of non-nucleus accumulating NFL fragments. Can they be localized to any specific structure?

      We assume that the reviewer is referring to neuronal/axonal debris. They are present after injury but they do not colocalize with nuclear stains. We will address this in the revised manuscript.

      Fig1C-F • I find it too simplistic to categorize c+f and d+e together. There is a huge difference in the examples of nuclear localization between d and e. To not comment on their distinction (if that is consistent) is problematic. Also, since we don't see a merge with either NeuN or SYTO 16, reader quantification is difficult.

      We thank the reviewer for bringing this up. We will carefully check our entire dataset and we will update the figures and the text accordingly. We will also show the corresponding SYTO16 images, as the reviewer suggested.

      Would the microfluidic device construction allow for time to transport any axonally damaged fragments to the soma?

      Yes, the construction of the microfluidic devices allows the transport of axonal proteins back to the soma. Based on our experiments, it seems that damaged NFL from the axonal compartment could be contributing to the accumulation of NFL fragments in the nuclei. However, this contribution seems to be minimal as we cannot detect nuclear NFL upon the injury of axons alone. Alternatively, it could be that the processing of axonal NFL fragments proceeds differently if neuronal bodies are not injured and that this is the reason we don’t detect the NFL nuclear accumulation upon injury of axons alone. We will discuss this in the revised manuscript.

      Fig2C+D • The statement ".... no annexin V was detected on the cell membrane" needs to be shown more clearly

      We will modify figures to address this comment.

      • Please provide merged AnnexinV/PI images

      We will modify figures to address this comment.

      • The conclusion about 2D, that nuclear accumulated NFL overlaps with PI is not supported by the example image shown. There are plenty of PI positive spots that are not NFL positive and even several NFL positive ones that do not have a clear PI staining. Please quantify and then show a very clear result in order to be able to suggest necrosis as the underlying process.

      We are not sure if we understand the reviewer’s concern correctly. We will try to clarify it here and in the revised text. If necessary, we will tone down our conclusion, but the reason why not all of PI positive spots are NFL positive is most likely due to the fact that not all injured nuclei are NFL positive. We quantified in FigS1 that up to 60% of nuclei under injury conditions show NFL accumulations. That is why we are not surprised to see some PI positive/NFL negative nuclei. And the fact that there are some NFL positive nuclei which appear to be PI negative is most likely related to the fact that the PI binding is affected. In addition, upon closer inspection of NFL and PI panels in Fig2d it can be observed that NFL positive nuclei are also PI positive, albeit with a lower PI fluorescence intensity. We will modify the figure to show this clearly in the revised manuscript.

      FigS5 C+D • If the case is made that nitric oxide damage induces necrosis, then why is it that the AnnexinV example of Staurosporine exposure (which induces apoptosis) looks similar to that of nitric oxide damage in Fig2d and necrosis induction with Saponin looks very different?

      We thank the reviewer for bringing this up. We will try to clarify this in the revised manuscript. Regarding the specific questions, the most likely explanation why staurosporine treated neurons look similar to the ones treated with spermine NONOate is that in the late stages of apoptosis cell membrane ruptures and allows for the PI to label nuclei. This is probably the case here as illustrated by the nucleus in the middle of the image (FigS5c) that shows the fragmentation characteristic for the apoptosis. This is not happening in early apoptotic cells due to the presence of an intact plasma membrane. On the other hand, the reason why saponin treated cultures look different compared to spermine NONOate is that membranes are destroyed by saponin so that the PI can enter the cell. For that reason, there could have not been any AnnexinV binding to the membrane which would correspond to the AnnexinV signal of spermine NONOate treated neurons. As we will discuss below, we did not try to mimic spermine NONOate-induced injury with saponin treatment. Instead this was a control condition for PI labeling and imaging. We also used a rather high concentration of saponin which probably destroyed all the membranes which was not the case with spermine NONOate treatment. We intend to do additional control experiments to address this.

      • Additionally, does necrosis induction with Saponin also cause NFL fragment accumulation in the nucleus? Please show a co-staining of them. Also, the authors want to make a claim about reduce PI binding in NFL accumulated necrotic cells. In these examples, the intensity of the nuclear stain of PI with Saponin looks dimmer than with Staurosporine. Are the color scalings similar? It might be that the necrotic process itself causes reducing binding of PI and is not related to the presence of NFL.

      With regards to this question, it is important to note that Annexin V and PI imaging was done in living cells. To obtain the corresponding anti-NFL signal as shown in Fig 2c,d we had to fix the neurons, perform immunocytochemistry and identify the same field of view. We tried to do the same procedure after saponin treatment (Supplementary Figure 5d) but the correlative imaging was very difficult due to the detachment of neurons from the coverslip after the saponin treatment. For this reason, we could not identify the same field of view co-stained with NFL. However, other fields of view did not show NFL fragment accumulation. This could also be the consequence of the high saponin concentration that we used as we discuss above. We have also noticed the reduced intensity of PI binding in the nuclei of saponin-treated neurons. However, if the necrotic process itself reduces the binding of PI to the DNA, then all of the neurons treated with spermine NONOate would have an equally low PI signal. In our experiments, only the nuclei which contained NFL accumulations had a low PI signal, while the signal of NFL-negative nuclei was higher (as shown in Fig2d). We would also like to point out again that the saponin treatment was our control of the PI’s ability to penetrate cells and bind the DNA, as well as our imaging conditions, and not the control of the necrotic process itself. This is the reason why we didn’t go into details about neuronal morphology and NFL localization upon saponin treatment. We thank the reviewer for pointing this out since it prompted us to reevaluate what we wrote in the corresponding paragraph of the manuscript. We realized that the confusion might stem from our explanation of the AnnexinV/PI assay controls in the lines 196-198 (“Additional control experiments in which neurons were treated with 10 μM staurosporine (a positive control for induction of apoptosis) or with 0.1% saponin (a positive control for induction of necrosis) confirmed the efficiency of the annexin V/PI assay (Supplementary Fig. 5c,d).”). We will modify this portion of the text to clearly state that staurosporine and saponin treatments were controls of the AnnexinV and PI binding to their respective targets and not of the apoptosis/necrosis process. When it comes to the saponin treatment, our intention was only to permeabilize the membranes in order to allow PI penetration and DNA binding and not to induce necrosis or to mimic the effect of the spermine NONOate. We also intend to perform experiments with lower concentration of saponin to try to address this experimentally in addition to the text modifications.

      Fig3d • Please show similarly scaled images from controls for proper comparison

      We will show similarly scaled images of the control neurons so that they can be properly compared. They were initially not scaled the same for visualization purposes, but we will modify this in the revised manuscript.

      • How do the authors scale the degree and kinetics of induced damage between application of hydrogen peroxide/CCCP and glutamate toxicity? Does glutamate toxicity take longer to affect the cell, not allowing enough time to accumulate NFL fragments in the nucleus?

      It is challenging to scale the degree and kinetics of induced damage with different stressors. That is why we did not intend to do this. Instead we set different injury conditions based on the published literature. That is why can only speculate when it comes to this. In this regard, it can be that the glutamate toxicity takes “longer” to affect the cells even though it is very difficult to compare them on a timescale, especially when considering different mechanisms of action. We will discuss this limitation in the revised manuscript.

      Fig4B • Some groups (like NO and NO + emricasan) have much larger numbers of close to 0 intensity, compared to the control group. Why?

      We were wondering the same when we analyzed the data. The fact that our nuclear fluorescence intensity analysis picked up NFL signal in control neurons which had no nuclear NFL accumulation made us realize that the intensity measured in the nuclei of control group comes entirely from the out of focus fluorescence – from neurofilaments in cell bodies, dendrites and axons (an example can be seen in the FigS6). That is why we presented the corresponding data with a cut-off value based on the control signal (as mentioned in lines 238-240). Since the oxidative injury causes NFL degradation (not only in neuronal soma, but also neuronal processes), the overall fluorescence intensity of the NFL immunocytochemical staining is reduced in injured neurons. We can see that in all of our images. Consequently, there is no contribution of out of focus fluorescent signal to the measured fluorescence intensity in the majority of nuclei. Due to that, the nuclei without NFL accumulation (at least 40% of injured nuclei) will appear to have a close to 0 intensity of the fluorescent signal. We will discuss and clarify this additionally in the revised manuscript.

      • Please add the ratio of above/below threshold (50/50 obviously in controls)

      We will update the figure in the revised manuscript.

      • The description of the CTCF value calculation seems a little... muddled? Several parameters are described whereas "integrated density" is not even used. Why not simply mean intensity of nuclear ROI-mean intensity of background ROI?

      We included the integrated density in the description since it is measured together with the raw integrated density and can also be used for the CTCF value calculation. However, since we didn’t use it for the CTCF calculation, we will remove it from the corresponding section of the manuscript. We calculated the CTCF value instead of calculating mean intensity of the nuclear ROI - mean intensity of the background ROI, since the CTCF value also takes into account the area of the ROI and not just the mean intensity.

      • Also, please tell me if the areas for nuclear ROIs change, as I noted for Fig1A/B

      We will include this information in the revised manuscript.

      • To make sure that one of the 3 experimental repeats didn't skew the results, please show the median fluorescence intensity for each individual experiment to clarify that the supposed effect is repeated across experiments.

      We have already noticed that in the earliest of the three experiments overall fluorescence intensity was higher, but this was consistent across all the experimental groups and did not skew the results or affect the overall conclusion. However, we will double-check this and revise the figure.

      • From the text "...and due to the NFL degradation during injury...": this seems to contradict the process? Either the NFL fragment accumulates in the nucleus or it is degraded during injury. And isn't the degradation through calpain what supposedly allows this fragment of NFL to go to the nucleus in the first place? I reckon that the authors are possibly trying to reconcile why there are many close-to-0 intensity nuclei in the NO and NO + emricasan groups, but I don't feel the explanation given here fits.

      As we tried to explain in our response above, we think that the overall degradation of neurofilaments in neurons affects the fluorescence intensity originating from the out of focus neurofilaments. Therefore, the nuclei without NFL accumulation in injured conditions have a close to 0 fluorescence intensity. Additionally, we think that this is not an either/or situation, but that both degradation and nuclear accumulation of NFL happen simultaneously. We also think that degradation of axonal NFL and the transport of its tail domain to the soma will at least partially contribute to the accumulation in the nucleus. In any case, degradation and nuclear accumulation seem to be differentially regulated in individual neurons, as some of them show nuclear NFL accumulation and some not. Furthermore, calpain and other mechanisms could also cause NFL degradation up to the point at which these fragments can no longer be recognized by the anti-NFL antibody leading to the loss of signal. We will try to clarify this in the revised version of the manuscript.

      Fig5 • Does the distribution of this GFP in B match any of the various antibody stainings of different NFL fragments? Perhaps this is still a valid fragment of NFL, just not picked up by any AB?

      The GFP signal in B appears rather homogenous and it does not match any of the various antibody stainings of different NFL fragments. As the reviewer points out, this could also be a valid fragment of NFL fused to GFP that none of our antibodies is recognizing. We will clarify this in the revised manuscript.

      • "... and was indistinguishable from the full277 length NFL-GFP." Based on what parameters?

      We will clarify this in the revised text, but we meant in terms of overall neurofilament network and cell appearance, which is commonly used to test the effect of NFL mutations.

      • The authors claim that b is different from d, but I am not convinced. I would like to see a time dependent curve from multiple cells showing a differential change in nuclear and cytosolic GFP signal.

      As we also wrote in the manuscript, in the majority of neurons that were monitored during injury we were not able to detect an increase in the GFP fluorescence intensity in the nucleus. This is what prompted further experiments with NFL(ΔA461–D543)-FLAG. We will clarify this additionally in the revised manuscript and perform line profile intensity measurements to show the difference in nuclear and cytosolic GFP signal.

      • Secondly, the somatic GFP intensity for NFL increases for full length NFL-GFP. How is this explained, if it is only a separation of NFL and GFP? If anything, GFP should float away. And if the answer is that NFL is recruited to the nucleus, you showed that inhibition of calpain activity partially prevents that. So, if calpain activity is necessary for the transport of NFL to the nucleus, then wouldn't it also cut the GFP from NFL before it reaches the nucleus?

      We thank the reviewer for bringing this up and we apologize for the confusion. This can be explained by the fact that the images were scaled in a way that the GFP signal over time could still be seen easily (i.e. differently across different time points which we unfortunately forgot to mention in the figure legend). In the revised manuscript, we will either scale the images the same or we will alternatively show the displayed grey values in individual panels.

      Fig6 • It is recommended to overlap the transfected cells with a stain for endogenous NFL to show that despite the absence of the FLAG-tag, there is still NFL.

      We did not overlap the anti-NFL with anti-FLAG and SYTO16 staining, due to the space constraint and the intent to clearly show the overlap of FLAG and SYTO16 signals in the merged images above the graphs. However, the line profile intensity measurements were done in all three channels and show that despite the absence of FLAG, there is still NFL in the nucleus (Fig6b), or that both FLAG and NFL are present in the nucleus (Fig6d, NFL signal shown in gray). However, as this is not obvious and can easily be overlooked, we will show the endogenous NFL staining overlap in the revised version of the manuscript.

      Fig7 • „ ...all disrupted neurofilament assembly...": this sounds like the staining for native NFL supposedly shows a distortion due to a dominant negative effect of the expression of these constructs? Please clarify.

      Yes, we were referring to the disruption of neurofilament assembly due to a dominant negative effect of the expression of NFL domains. We will clarify this in the revised version of the manuscript.

      Discussion: • The authors show that after overepression of the head domain only, it possibly passively diffuses into the nucleus even in the absence of oxidative injury. However, it seems to be suggested as well that the head domain would not be freely floating around if it wouldn't be for increased calpain activity as a result of oxidative injury in the first place. Therefore, a head domain fragment localized in the nucleus would still more prominently happen upon oxidative injury and interact with DNA through prior identified putative DNA interaction sites from Wang et al. Please comment.

      That is correct. Upon injury and calpain cleavage, it is conceivable that a fragment containing the NFL head domain would also be present in the cell and could potentially diffuse to the nucleus and interact with the DNA. However, by staining injured neurons with an antibody that recognizes amino acids 6-25 of the NFL head domain, we were not able to detect an NFL signal in the nucleus (FigS2a,b). It could be that either the NFL head domain does not localize in the nuclei upon injury, or that the fragment localizing in the nucleus does not contain amino acids 6-25 of the NFL head domain. As the putative DNA-binding sites described by Wang et al involve 7 amino acids located in the first 25 residues of the NFL head domain, we would expect to detect it with the aforementioned antibody. However, as that was not the case we speculated that the interaction of NFL and DNA occurs differently in living cells, as opposed to the test tube conditions utilized by Wang et al. We will comment and clarify this in the revised version of the manuscript.

      • Reviewer #2*

      • Major Comments:

      • The initial data presented in the paper is good, does response of oxidative damage with proper controls, testing the antibodies to NF-L and etc. (Fig. 1-Fig. 4). *

      We thank the reviewer for their positive feedback.

      1. The evidence for calpain involvement in NF-L cleavage during oxidative damage is missing. Provide the evidence for full length NF-L construct and deletion mutants transfected into cells by immunoblot for cleavage of NF-L, perform nuclear and cytoplasmic extract preparations and show that enrichment of the tagged cleaved NF-L fragment in nuclear fraction.

      We thank the reviewer for their comments and suggestions. Since we saw in our microscopy experiments that calpain inhibition reduced the accumulation of NFL in the nucleus, and since it is known that NFL is a calpain substrate (Schlaepfer et al., 1985; Kunz et al., 2004 and others), we did not perform additional experiments to confirm the involvement of calpain in NFL degradation during injury. However, to strengthen our findings, we intend to perform the suggested experiments and include the results in the revised manuscript.

      1. Show calpain activation during oxidative damage by performing alpha-Spectrin immunoblots identify calpain specific 150-kda Spectrin and caspase specific 120-kDa fragment generation in these cells. Also, calpain activation can be measured by MAP2 level alteration and p35 to p25 conversion. Without this evidence it's very hard to believe if the calpain activity is increased or decreased during oxidative damage and these markers are altered by using calpain inhibitors.

      To confirm the calpain activation, we intend to perform anti-alpha spectrin and/or anti-MAP2 blots in lysates of control and injured neurons and include the results in the revised manuscript.

      1. The premise that NF proteins are absent in cell bodies and present only in axons is not correct. It has been demonstrated by multiple investigators that NFs are present in the perikaryon and dendrites of many types of neurons (Dahl, 1983, Experimental Cell Research)., Dr. Ron Liem's group showed NF protein expression in cell bodies of dorsal root ganglion cells (Adebola et ., 2015, Human Mol Genetics) and also showed N-terminal antibodies for NF-L, NF-M and NF-H stain rat cerebellar neuronal cell bodies and dendrites (Kaplan et al., 1991, Journal of Neuroscience Research) when NFs are less phosphorylated. (Schlaepfer et al., 1981, Brain Research) show staining of cell bodies of cortex and dorsal root ganglion cell bodies with NF antibody Ab150, and Yuan et al., 2009 in mouse cortical neurons with GFP tagged NF-L.

      We are not sure what the reviewer is referring to since we cannot find a corresponding section in which we claim that NF proteins are absent in cell bodies. We wrote the following “Anti-NFL antibody staining of neurons treated with the control compound showed the expected neurofilament morphology, that is, a strong fluorescence intensity in axons and lower intensity in cell bodies and dendrites (Fig. 1a)” in our results section (lines 119-121), but the claim we were trying to make there was that NF proteins are particularly abundant in axons. We will clarify this in the revised manuscript.

      1. Quantifying NF-L signal or tagged NF-L fragment signals in the cell body by ICC has many problems and making conclusions. It's extremely difficult to have control over levels of proteins in transfected overexpression models and comparing two or three different constructs with each other by ICC. Not every cell expresses same levels of protein in transfected cells and quantifying it by ICC again has a major problem. This can be addressed if there are stable lines that express equal levels of protein in all cells that comparisons can be made. Under thesese circumstances validation of the hypothesis presented in the study has no strong direct evidence to demonstrate that calpain is activated and NF-L fragment translocate to the nucleus.

      We agree that the results from overexpression-based experiments should be interpreted with caution as levels of expression vary between the cells. We intend to discuss this in the revised manuscript. However, we find it difficult to experimentally address this comment since we are not sure which specific experiments the reviewer is referring to. With regards to this, we would like to emphasize that most of the initial experiments in which we observed NFL accumulation in the nuclei of injured neurons were based on the ICC labeling of endogenous NFL and didn’t involve its overexpression. This includes labeling of endogenous NFL in various types of neurons, comparing the effects of different types of oxidative injury, as well as testing the effects of calpain inhibition on the observed nuclear accumulation (Figures 1-4; Supplementary Figures 1-6). We later resorted to the overexpression experiments in primary neurons (Figures 5-7; Supplementary Figure 7, 10) to gain more information about the identity of NFL fragment which was detected in the nucleus. Due to the low transfection efficiency of primary neurons, we performed an additional set of overexpression experiments in neuroblastoma ND7/23 cells (Figure 8; Supplementary Figures 8,9) and obtained similar results in a higher number of cells. We agree that having stable cell lines which e.g. express same levels of NFL domains would be a more elegant approach and we intend to make them for our follow-up studies, however the generation of said stable cell lines might be beyond the scope of this revision. Furthermore, looking at our data with overexpression of NFL domains in ND7/23 cells (Supplementary Figure 8,9), it appears to us as if different domains are rather homogenously expressed in different cells. While the expression levels might vary, it seems that they all show the same trend when it comes to their localization (which was the main point of those experiments).

      1. The interpretation that NF-L preventing DNA labeling cells is misinterpretation. NFs have very long half-life compared to other proteins. Due to oxidative damage, DNA is degraded in the cells but NFs that have very long half-life you see as NFs rings in the dead cells. So, NFs do not prevent DNA labeling, but DNA or chromatin is degraded in dead cells.

      We thank the reviewer for their useful insight. DNA degradation could certainly be the reason why we observe a lower fluorescence intensity of the propidium iodide fluorescence in the nuclei of injured neurons. We intend to discuss this in the revised manuscript. However, if the DNA degradation is the only reason for the lower PI fluorescence intensity, then the PI fluorescence intensity would be the same in all injured nuclei. In our experiments, we saw the reduced PI fluorescence intensity in nuclei that contained NFL accumulations and not in other nuclei. Additionally, we observed a reduction of SYTO16 fluorescent labeling of nuclei which contained accumulations of the NFL tail domain, even in the absence of oxidative injury. Due to these reasons we speculated that NFL accumulation in the nucleus might hinder nuclear dyes from interacting with the DNA. But this is only a speculation and we will try to clarify this further in the revised manuscript including alternative explanations.

      Minor comments: 1. In the introduction on page 4 reference is missing for NF transport, aggregation and perikaryal accumulation (on line 93).

      We will add a reference to the revised manuscript.

      1. The statement in discussion on page 14 line 454 for Zhu et al., 1997 study is not accurate. It should be modified to sciatic nerve crush not spinal cord injury.

      We will correct this mistake in the revised manuscript.

      1. What is the size of the calpain cleaved NF-L tail domain? If you perform immunoblots on cell extracts treated with oxidative agents one would know it.

      We will perform immunoblots on cell lysates and incorporate the corresponding results in the revised manuscript.

      1. Authors could make their conclusions clear. This is particularly true for the experiments in Figure 4 panels c and d. It is very difficult to understand the conclusions of the experiments. First state the expectation and then described whether the expectation is true or different.

      We will do as the reviewer suggested in the revised manuscript.

      1. The ICC images are at extremely low magnification. They should be shown at 100x or 120x so that details of the cell body and the nucleus can be seen.

      Our intention was to show larger fields of view and wherever appropriate insets, but we will try to improve this in the revised manuscript by either zooming in, cropping or adding additional insets with individual cell bodies and nuclei. In general, images were taken with an optimal resolution/pixel size in mind for any of the used objectives (60x/1.4 NA or 100x/1.49 NA) and we can easily modify our figure panels to show more details.

      1. Oxidative damage leads to beaded accumulation of NF-L in neurites and axons. Authors should address this issue.

      We will discuss this in the revised manuscript.

      1. The combination treatment of the inhibitors (last 3 sets of the Fig. 4 b) has no statistical significance should be removed.

      Actually, these differences were statistically significant (Supplementary Table 1). For clarity and as described in the figure legend (line 516: “The most relevant significant differences are indicated with an asterisk”) we showed only a subset of them on the graph, but we will change this in the revised manuscript.

      1. Why only two antibodies recognize cleaved NF-L? If the antibodies at directed at tail region, they should recognize it unless the phosphorylated tail at Ser473 may inibit the antibody binding. In that case NF-L Ser473 specific antibody (EMD Millipore: MABN2431) may be used to test this idea.

      This is a very good point that we also wonder about. Even if all antibodies are directed at tail region, exact epitopes are not described for all of them. That makes it also difficult for us to understand and speculate on this. However, we have already ordered the new antibody as suggested by the reviewer and we will experimentally test it.

      **Referees cross-commenting**

      I agree with the reviewer#1 about presenting the quantification data for the indicated figures to make conclusions strong and see how much of variation is there among sampled cells.

      As discussed in our response to reviewer #1, we will provide additional quantifications.

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

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

      Reviewer #2, major comment 7. Authors could do chromatin immunoprecipitation (chip) analysis to identify NF-L binding sites on chromatin and perform gel shift assays to show NF-L tail domain binding to specific consensus DNA sequences.

      We thank the reviewer for their suggestion. We are very interested in performing additional experiments and identifying the NFL binding sites on the DNA (either by chromatin immunoprecipitation or DamID-seq) and we intend to perform these experiments as soon as possible. Unfortunately, at the moment we do not have the expertise to perform such experiments in our lab. Instead, this type of follow-up project requires establishing a collaboration which is beyond the scope of this revision.

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

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      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      The manuscript presented by Arsić and Nikić-Spiegel investigates a physiological consequence when neurons in vitro are exposed to oxidative stress injury, specifically a supposed interaction of the tail subdomain of the neurofilament light chain (NFL), after cleavage of the full NFL protein by calpain.

      General comments:

      The conclusions the authors draw from individual non-quantified example images are sometimes seen to be too simplistic when the shown examples ask for a more thorough investigation, especially when specific merged images are not available. It is highly recommended that the authors use the available data to come to more comprehensive answers across the entire acquired dataset. This for instance happens only in figures 4 and 8 and should be extended to other figures as well. There is not necessarily doubt about the author's general claims, but convincing the reader requires showing the variability and effect size of the entire group beyond a single selected example.

      If these more thorough quantifications continue to support the author's claims, then I find no objections for publication of this data.

      Specific comments:

      Fig1A/B - SYTO 16 staining suggests slight reshaping of nucleus upon spermine NONOate, showing less blurry punctae. From the SYTO 16 profile, this should be quantifiable. - There is a subset of neuron nuclei that are SYTO 16 positive. Please quantify the ratio

      FigS1A - Show NeuN with Anti-NFL merged figures

      FigS1C - Show quantification and timeline. I want to know whether there is also a plateau reached here.

      FigS2A-F - Though the statements might be true, selecting one nucleus for a line profile as a statement for the whole dataset seems problematic. Average a larger number of unbiased selected nuclei profiles across multiple cultures to make a stronger statement, or a percentage of positive nuclei as in FigS1b.

      FigS3 - There are no fluorescence profiles, no quantification

      General statement:

      There do seem to be punctated patterns of non-nucleus accumulating NFL fragments. Can they be localized to any specific structure?

      Fig1C-F - I find it too simplistic to categorize c+f and d+e together. There is a huge difference in the examples of nuclear localization between d and e. To not comment on their distinction (if that is consistent) is problematic. Also, since we don't see a merge with either NeuN or SYTO 16, reader quantification is difficult. - Would the microfluidic device construction allow for time to transport any axonally damaged fragments to the soma?

      Fig2C+D - The statement ".... no annexin V was detected on the cell membrane" needs to be shown more clearly - Please provide merged AnnexinV/PI images - The conclusion about 2D, that nuclear accumulated NFL overlaps with PI is not supported by the example image shown. There are plenty of PI positive spots that are not NFL positive and even several NFL positive ones that do not have a clear PI staining. Please quantify and then show a very clear result in order to be able to suggest necrosis as the underlying process.

      FigS5 C+D - If the case is made that nitric oxide damage induces necrosis, then why is it that the AnnexinV example of Staurosporine exposure (which induces apoptosis) looks similar to that of nitric oxide damage in Fig2d and necrosis induction with Saponin looks very different? - Additionally, does necrosis induction with Saponin also cause NFL fragment accumulation in the nucleus? Please show a co-staining of them. Also, the authors want to make a claim about reduce PI binding in NFL accumulated necrotic cells. In these examples, the intensity of the nuclear stain of PI with Saponin looks dimmer than with Staurosporine. Are the color scalings similar? It might be that the necrotic process itself causes reducing binding of PI and is not related to the presence of NFL.

      Fig3d - Please show similarly scaled images from controls for proper comparison - How do the authors scale the degree and kinetics of induced damage between application of hydrogen peroxide/CCCP and glutamate toxicity? Does glutamate toxicity take longer to affect the cell, not allowing enough time to accumulate NFL fragments in the nucleus?

      Fig4B - Some groups (like NO and NO + emricasan) have much larger numbers of close to 0 intensity, compared to the control group. Why? - Please add the ratio of above/below threshold (50/50 obviously in controls) - The description of the CTCF value calculation seems a little... muddled? Several parameters are described whereas "integrated density" is not even used. Why not simply mean intensity of nuclear ROI-mean intensity of background ROI? - Also, please tell me if the areas for nuclear ROIs change, as I noted for Fig1A/B - To make sure that one of the 3 experimental repeats didn't skew the results, please show the median fluorescence intensity for each individual experiment to clarify that the supposed effect is repeated across experiments. - From the text "...and due to the NFL degradation during injury...": this seems to contradict the process? Either the NFL fragment accumulates in the nucleus or it is degraded during injury. And isn't the degradation through calpain what supposedly allows this fragment of NFL to go to the nucleus in the first place? I reckon that the authors are possibly trying to reconcile why there are many close-to-0 intensity nuclei in the NO and NO + emricasan groups, but I don't feel the explanation given here fits.

      Fig5 - Does the distribution of this GFP in B match any of the various antibody stainings of different NFL fragments? Perhaps this is still a valid fragment of NFL, just not picked up by any AB? - "... and was indistinguishable from the full277 length NFL-GFP." Based on what parameters? - The authors claim that b is different from d, but I am not convinced. I would like to see a time dependent curve from multiple cells showing a differential change in nuclear and cytosolic GFP signal. - Secondly, the somatic GFP intensity for NFL increases for full length NFL-GFP. How is this explained, if it is only a separation of NFL and GFP? If anything, GFP should float away. And if the answer is that NFL is recruited to the nucleus, you showed that inhibition of calpain activity partially prevents that. So, if calpain activity is necessary for the transport of NFL to the nucleus, then wouldn't it also cut the GFP from NFL before it reaches the nucleus?

      Fig6 - It is recommended to overlap the transfected cells with a stain for endogenous NFL to show that despite the absence of the FLAG-tag, there is still NFL.

      Fig7 - „ ...all disrupted neurofilament assembly...": this sounds like the staining for native NFL supposedly shows a distortion due to a dominant negative effect of the expression of these constructs? Please clarify.

      Discussion:

      • The authors show that after overepression of the head domain only, it possibly passively diffuses into the nucleus even in the absence of oxidative injury. However, it seems to be suggested as well that the head domain would not be freely floating around if it wouldn't be for increased calpain activity as a result of oxidative injury in the first place. Therefore, a head domain fragment localized in the nucleus would still more prominently happen upon oxidative injury and interact with DNA through prior identified putative DNA interaction sites from Wang et al. Please comment.

      Significance

      This in vitro study, despite its acknowledged caveats, can provide novel support for the claim that calpain induced cleavage of the NFL may play a role in downstream gene expression in order to regulate a neural response upon oxidative injury. Further investigation into this topic may provide further understand of physiological gene expression through interaction with cleavage products as well as yield possible therapeutic targets for pathological conditions. This study therefore may be of interest to a broad audience.

  3. Jun 2022
    1. Es gilt daher, diese digitale Affinität der Studie-renden methodisch und inhaltlich zu motivieren und philosophisch fruchtbar zumachen

      Das sagt Will Richardson auch für den Bereich der Schule so. Es muss, in der Schule noch mehr, v.a. pädagogische und didaktische Expertise in digitale Transformationen einfließen. Man läuft sonst Gefahr u.a. Konsumtendenzen nicht kritisch gegenüber treten zu können und unmündiges Verhalten an den Tag zu legen und im schlimmsten Falle zu lehren.

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    1. h0p3 has a home page entry point that is carefully curated and groomed, but which is several layers up from a complete chaos of link dumps, raw drafts and random introspections […] These layers run a spectrum of accessibility—there is always a learning curve before you hit the bottom. You start with a doorway before entering a maze.

      carefully cureated groomed

      chaos of link dumps

      you start with a door way before entering a maze

    1. 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

      Reviewer #1 (Evidence, reproducibility and clarity (Required)): **Summary:** Techniques to probe the local environment of membrane proteins are sparse, although the influence of lipids on the membrane protein's function are known since many years. Therefore, the paper by Umebayashi et al. is important. The environment-sensitive dye Nile red (NR) coupled to a membrane protein is an appropriate sensor for monitoring the local membrane fluidity. Linking of Nile red to the receptor via a flexible tether was achieved with the acyl carrier protein (ACP)-tag method. Experiments showed that depending on the ACP site a certain linker length is required to have NR inserted in the membrane and thus be an effective sensor for lipid disorder. This technology could be of general usability to study the environment of membrane proteins in the context of their function. As an example, the technique allowed insulin induced membrane disorder in the close insulin receptor vicinity to be observed. Further, results suggested that tyrosine activity is required for this disorder to happen. The experimental results appear to be complete and controls were made.

      **Major comments:** 1) Sometimes technical terms are used without explanation: What is the GP value? What is ACP-IR? The spectrum was measured in number of rois? The reader can find those abbreveations out, but it would be nice to have them defined.

      We have made a list of abbreviations.

      2) Fig. 1d) is confusing. The ACP-IR labelling is evident in 3 panels, but there is no difference in the color (emission spectra of 1992-ACP-IR vs 2031-ACP-IR should be visible??). The DAPI staining is very different. When doing the latter, how difficult is it to get the staining equal?

      The differences in spectra cannot be seen because we used pseudo colors for display of the DAPI and CoA-PEG-NR staining. The reviewer’s comments about the unequal DAPI staining is correct. The reason for this is most likely that the cell membrane is unequally permeabilized by PFA treatment. As the point of this figure is just to show that the plasma membrane is labeled, dependent upon the expression of the ACP-tagged insulin receptor, we don’t think that the variable intensities of the DAPI staining is important. DAPI is simply used to indicate the position of the cells.

      3) How can one interpret Fig. 4: a) Control goes over 4 frames, at 240" insulin is added, and 10 frames should show a fluctuation difference?

      We showed 4 frames after control treatment that showed no significant change was observed by control treatment. We expected that clear changes would be invoked by insulin treatment in GP images, however these changes, while visible in the GP images, are difficult to see for the untrained observer. This is the reason why we used the ZNCC method in the subsequent figures to better visualize the changes.

      1. b) A color shift from blue to green is visible after insulin addition. But it is faint - difficult to assess from the pseudo color scheme. What does 1000 pixel top/1000 pixel bottom mean in c). Is it an attempt to better visualize the fluctuation? It is difficult to recognize a difference before and after adding insulin. d) It seems that the kymograph set should show this. What is the color scale? Why is 3 so untypical, i.e., no change? Box 6 is also peculiar: the left side does not show a strong change upon insulin administration, the right side does. Why? We appreciate the helpful comments for improving our manuscript.

      As pointed out, the change of GP value is extremely small before and after insulin addition, so it is difficult to fully visualize the change with normal pseudo-color expression. To deal with this, we adopted the following two methods to visualize minute changes.

      1) Visualization of local changes of the statistical GP value showed by ZNCC throughout the time-lapse images (Fig. 6 and Fig. S2B).

      2) Visualization of the top/bottom 1000 pixels of the sorting ZNCC value in each image (Fig. 7 and Fig. S2C). The top 1000 pixels are the ones that showed the largest changes. The bottom 1000 pixels are the ones that showed the smallest changes.

      Owing to these expressions, we found out that the level of the response against the insulin signal was spatially and temporally heterogeneous in the membrane.

      As for the color scale, in order to clarify the meaning of the difference of color, we have added the description about the relationship between the color and the ZNCC value in the results section.

      4) How is the kymogram calculated? The legend says 'The horizontal dimension represents the averaged ZNCC inside the rectangular area, and the vertical dimension represents time'. The averaged ZNCC is a single value, so it is not clear why the kymogram shows a variation from left to right. May it be the ZNCC was averaged just vertically?

      We apologize that we did not provide information regarding making the kymograph.

      In the yellow rectangular area (Fig. 6B), the ZNCC values of the pixels with the same x coordinate value were vertically averaged, which were represented as the horizontal direction of the kymograph. That is, one horizontal line of the kymograph holds the spatial distribution of the ZNCC value along the horizontal direction of the membrane, and the vertical direction shows their time changes. To make it easier to understand, we refined the description about the kymograph in the legend of Fig. 6.

      5) When calculating cross-correlation values on images, they need to be aligned. What fraction of the total image does the selected 19x19 box represent? As described, I imagine that a rolling CC over 19x19 pixels is calculated over an image from the time lapse series comparing it with the reference Iave(x,y). Compared to the 3x3 median filtered CP image, the ZNCC image should then be much more blurred??

      Below we provide more information regarding the calculation of ZNCC.

      Each local window for ZNCC calculation is set to a 19x19 pixels centered on every single pixel excluding the edges of an image. The ZNCC value calculated in that window is set to a center pixel of that area. After that, a new window centered on the adjacent pixel is set and calculate the new ZNCC. That is, the calculation window is slid throughout the image. Also, the calculated ZNCC value is not set to all the pixels of the window, but is set to only the center pixel of the window, so there is no blur effect like median filtering.

      The figure below shows a schematic view of our ZNCC calculation.

      Schematic view of our ZNCC calculation

      **Minor comment:** On page 16 supplementary is not spelled properly.

      corrected

      Reviewer #1 (Significance (Required)):

      The key point of this paper is convincing and the new technology appears to have a lot of potential. It can be applied to study membrane protein function in the context of its environment, the lipid bilayer.

      Membrane fluidity measurements have been developed (e.g., using fluorescent probes like laurdan). However, the trick to link a probe like nile red by ACP technology to the insulin receptor and to observe its activity is quite new.

      A most recent description of such a technology is in TrAC Trends in Analytical Chemistry Volume 133, December 2020, 116092.

      This is an interesting review, but not directly impacting on our work.

      **Referees cross-commenting**

      All comments are constructive and important. The paper is important but needs to be amended as proposed.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): **Summary:** In this manuscript, authors generated an ACP-attached Nile Red probe in order to specifically label Insulin receptor in the membrane. Owing to this specificity, one can measure the lipid membrane properties around a specific protein in the membrane. **Major comments:**

      For the conclusions in the manuscript to be convincing, in my opinion, these additional data need to be added. Some of these are new experiments, and some are detailed analysis of existing data. The new experiments are not for new line of investigation, instead it is to confirm their statements and conclusions. The major point is the reliability of spectral shift. In usual environment sensitive probes, it is certain that they are in the membrane whatever is done to the membrane. However, when the probe is attached to a protein, it is not trivial to have the same confidence that the probe is always inside the membrane, and it is in the same plane of the membrane. 1992-ACP-IR is a good example; authors state that it binds to the protein outside the membrane, but when there is cholesterol addition and -maybe more interestingly- cholesterol removal, the dye still reacts and changes its emission (even PreCT changes its emission quite a bit at the 570 nm region). This is a clear indication of a change in localization of the probe upon some changes in the membrane. This implies that observed spectral shifts may not be due to lipid packing differences, but due to localization of the probes. For this reason, it is crucial to know where any environment sensitive probe localize in the membrane with respect to membrane normal, and this knowledge is more important for this probe. Related to this, the spectral difference upon insulin treatment and activation of insulin receptor could be due to changes in probe's localization in the membrane. Especially because authors show in Fig1e, the spectra can change depending on the probe localization. Relatedly, quantum yield of NR should be significantly different when it is inside vs outside membrane. Authors should show QY for 1992-ACP-NR and 2031-ACP-NR with different PEG lengths and upon insulin treatment.

      We understand the logic of the request to measure the QY, since the QY of Nile red is much higher in organic solvents than in aqueous solutions, so it might be predicted that the QY of Nile red is higher in a lipid bilayer than when covalently bound to the protein in an aqueous environment. However, this argument depends upon the mechanism for the increase in quantum yield when going from aqueous to a non-polar solution. One possible explanation is based on the intrinsic properties of the dye under the two conditions. The alternative explanation would be that the dye would aggregate (be insoluble) in aqueous solution and therefore either not fluoresce or self-quench. In this case, we believe that the latter is the explanation because we and others have previously shown the turn-on properties of the probe when binding to proteins (SNAP-tag and others). It is not simple to measure QY in the cell under a microscope, but we have done something similar shown in supplementary figure 4. We labeled the three ACP-receptor complexes with PEG11-Nile red and co-stained with antibody to the Insulin Receptor. We then calculated a relative quantum yield. There were very little differences at all between the relative quantum yields, so we conclude that it is not the environment of the probe, which affects the quantum yield under these conditions, but the fact that it is covalently attached to a protein and incapable of forming aggregates. What distinguishes these constructs is the emission spectrum, not the quantum yield. In supplementary Table 2 we also did QY measurements in vitro and we could reproduce the increase of quantum yield by association with liposomes or in organic solvents. We tested whether non-covalent association with a protein would increase the QY by incubation with the lipid binding protein, BSA, in PBS. This was not the case, strongly pointing to the conclusion that it is the covalent association with the protein that increases the QY, not association with a protein. We believe that our demonstration of changes in fluorescent spectra with changes in cholesterol, large changes in fluorescent spectra with linker length for the 1992 construct and voltage sensitivity using patch-clamp prove that the Nile red is reporting on the membrane environment under the conditions we propose.

      **Minor comments:** - Fig 1d requires quantification We do not agree on this. This is simply to show that the labeling is dependent upon expression of the relevant ACP-IR constructs. There is no detectable labeling of the control.

      • Voltage sensitivity of different PEG length of 2031-ACP probe should be added. We have added this data in figure 2 panel E.

      • Fig 3a graph should show all data points, not only bar graphs. Also, the band in 3a for +CoA-PEG-NR is dimmer than other bands, is it specific to this particular gel since quantification does not show any difference?

      There is no significant difference- Fig 4d, colour code is needed.

      Done

      • Fig 5b and Fig3d are basically the same experiments in terms of control measurement, why is the difference in 3b is 0.04 GP unit while it is 0.007 GP unit?

      We explain in the MS, but have improved the title of Y-axis in Fig.5 b graph so that the difference in what is plotted is clear. - Why is inhibitor data so noisy? We should discuss.

      We don’t know the exact reason why inhibitor data is noisy, but we speculate that the actin cytoskeleton and phosphoinositide-dependent signaling could affect the membrane stability, and the membrane environment would be fluctuated in the presence of latrunculin B or PI3K inhibitor.

      Reviewer #2 (Significance (Required)): Overall, this is a very useful approach, and this line of research will yield very useful tools to shed light on how lipids surrounding proteins can change their function. Major advance of the paper is the new chemical biology tool. There is also biological data on how insulin can change the insulin receptor's membrane environment which is contradictory to some old literature claiming that InsR becomes more "rafty" upon insulin treatment (e.g., PMID: 11751579).

      If this type of tagging proves robust and reproducible (limitations and concerns listed above and below), it could be used by other researchers to tag their protein of interest and investigate the lipid environment around those proteins.

      The downside of this method is that the probe requires ACP tag, a relatively less used tag than others in biology, therefore researchers interested in using this probe should have their proteins with ACP tag. Moreover, the linker length and ACP-tag position are quite crucial parameters (and probably should be optimized for each protein). Longer PEG lengths cannot report on changes efficiently (Fig3b), while shorter lengths are prone to artefacts as they can go out of membrane (Fig1 and Fig2). This might limit its widespread use.

      The reason for using the ACP tag is that neither the SNAP tap nor the HALO tag working. The tethered Nile Red preferred to bind to the tqg rather than inserting into the membrane.

      **Referees cross-commenting** I agree with all comments and concerns of other reviewers. I see the usability and potential of this new technology along with its limitations as all three reviewers pointed out.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)): See below. No concerns on any of these issues.

      Reviewer #3 (Significance (Required)): **Critique:** This MS reports a proof-of-principle for using site-directed environmentally sensitive probe technology to assess the local membrane environment of a receptor tyrosine kinase (IR) upon activation. This technology addresses a major gap in our arsenal of tools to study the mechanisms of membrane signaling as the parameters of interest are biophysical parameters rather than purely biochemical ones. How to do this with spatial and temporal resolution is a major challenge. This study builds on previous work by the Riezman group that develops an extrinsic labeling system to tether Nile Red to specific sites on the ectodomain of a signaling receptor and then probe local membrane environments as a function of receptor activity. This is a carefully done study is well-controlled, is clever in design and is well-described. Although the major issues to which such a general technology could contribute involve intracellular (and not extracellular) event, the advances described will be of general interest -- particularly that local membrane order decreases when IR becomes activated. Specific comments for the authors' consideration follow:

      **Specific Comments:** (i) As a general comment, the authors are measuring extracellular plasma membrane leaflet properties that may or may not translate to what is happening in the local inner leaflet environment. A general reader may well miss the significance of this. This point needs to be more explicitly emphasized in the Discussion.

      This has been discussed in the revised version.

      (ii) Why not treat cells with a PLC inhibitor to block PIP2 hydrolysis and ask if that inhibits membrane disorder. It is PIP2 hydrolysis/resynthesis that regulates the actin cytoskeleton at signaling receptors and this seems an attractive candidate for study.

      There is a long list of attractive post-signaling events of the insulin receptor and how this works in different cell types that could be tested. We believe that this is beyond the scope of this study and we encourage others to do this.

      (iii) The data acquisition time is at least 4 min which is long enough for activated receptors to be recruited to sites of endocytosis. Can the authors exclude the possibility that what they are measuring isn't reflective of such spatial reorganization? Does a clathrin inhibitor block the observed change in local membrane order for activated IR? We determined localization to AP2 adaptor containing clathrin coated pits at the cell surface and showed that during the time-course of the experiment that there is no significant change in co-localization or evidence for endocytosis (new figure 9). Therefore, we decided not to do the clathrin inhibitor blocking experiment because we believe that it could only lead to indirect effects.

      (iv) Receptor activation is accompanied by other transitions such as dimerization, etc. Can the authors exclude the possibility that what they are measuring is related to changes in depth of insertion of the NR probe into the plasma membrane outer leaflet that is a consequence of IR conformational transitions associated with activation? This is highly unlikely given the fact that fluidification of the membrane environment is found with all length linkers. Given the intervals in increases in linker length on the 2031 construct, which is the closest to the membrane, it is very difficult to conceive that any of the ones larger than 5 PEGs restrict significantly the membrane insertion of the dye. **Referees cross-commenting**

      I think we have a consensus opinion

    2. 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

      Summary:

      In this manuscript, authors generated an ACP-attached Nile Red probe in order to specifically label Insulin receptor in the membrane. Owing to this specificity, one can measure the lipid membrane properties around a specific protein in the membrane.

      Major comments:

      For the conclusions in the manuscript to be convincing, in my opinion, these additional data need to be added. Some of these are new experiments, and some are detailed analysis of existing data. The new experiments are not for new line of investigation, instead it is to confirm their statements and conclusions. The major point is the reliability of spectral shift. In usual environment sensitive probes, it is certain that they are in the membrane whatever is done to the membrane. However, when the probe is attached to a protein, it is not trivial to have the same confidence that the probe is always inside the membrane, and it is in the same plane of the membrane. 1992-ACP-IR is a good example; authors state that it binds to the protein outside the membrane, but when there is cholesterol addition and -maybe more interestingly- cholesterol removal, the dye still reacts and changes its emission (even PreCT changes its emission quite a bit at the 570 nm region). This is a clear indication of a change in localization of the probe upon some changes in the membrane. This implies that observed spectral shifts may not be due to lipid packing differences, but due to localization of the probes. For this reason, it is crucial to know where any environment sensitive probe localize in the membrane with respect to membrane normal, and this knowledge is more important for this probe. Related to this, the spectral difference upon insulin treatment and activation of insulin receptor could be due to changes in probe's localization in the membrane. Especially because authors show in Fig1e, the spectra can change depending on the probe localization. Relatedly, quantum yield of NR should be significantly different when it is inside vs outside membrane. Authors should show QY for 1992-ACP-NR and 2031-ACP-NR with different PEG lengths and upon insulin treatment.

      Minor comments:

      • Fig 1d requires quantification
      • Voltage sensitivity of different PEG length of 2031-ACP probe should be added.
      • Fig 3a graph should show all data points, not only bar graphs. Also, the band in 3a for +CoA-PEG-NR is dimmer than other bands, is it specific to this particular gel since quantification does not show any difference?
      • Fig 4d, colour code is needed.
      • Fig 5b and Fig3d are basically the same experiments in terms of control measurement, why is the difference in 3b is 0.04 GP unit while it is 0.007 GP unit?
      • Why is inhibitor data so noisy?

      Significance

      Overall, this is a very useful approach, and this line of research will yield very useful tools to shed light on how lipids surrounding proteins can change their function. Major advance of the paper is the new chemical biology tool. There is also biological data on how insulin can change the insulin receptor's membrane environment which is contradictory to some old literature claiming that InsR becomes more "rafty" upon insulin treatment (e.g., PMID: 11751579).

      If this type of tagging proves robust and reproducible (limitations and concerns listed above and below), it could be used by other researchers to tag their protein of interest and investigate the lipid environment around those proteins.

      The downside of this method is that the probe requires ACP tag, a relatively less used tag than others in biology, therefore researchers interested in using this probe should have their proteins with ACP tag. Moreover, the linker length and ACP-tag position are quite crucial parameters (and probably should be optimized for each protein). Longer PEG lengths cannot report on changes efficiently (Fig3b), while shorter lengths are prone to artefacts as they can go out of membrane (Fig1 and Fig2). This might limit its widespread use.

      Referees cross-commenting

      I agree with all comments and concerns of other reviewers. I see the usability and potential of this new technology along with its limitations as all three reviewers pointed out.

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

      Learn more at Review Commons


      Referee #1

      Evidence, reproducibility and clarity

      Summary:

      Techniques to probe the local environment of membrane proteins are sparse, although the influence of lipids on the membrane protein's function are known since many years. Therefore, the paper by Umebayashi et al. is important. The environment-sensitive dye Nile red (NR) coupled to a membrane protein is an appropriate sensor for monitoring the local membrane fluidity. Linking of Nile red to the receptor via a flexible tether was achieved with the acyl carrier protein (ACP)-tag method. Experiments showed that depending on the ACP site a certain linker length is required to have NR inserted in the membrane and thus be an effective sensor for lipid disorder. This technology could be of general usability to study the environment of membrane proteins in the context of their function. As an example, the technique allowed insulin induced membrane disorder in the close insulin receptor vicinity to be observed. Further, results suggested that tyrosine activity is required for this disorder to happen. The experimental results appear to be complete and controls were made.

      Major comments:

      1) Sometimes technical terms are used without explanation: What is the GP value? What is ACP-IR? The spectrum was measured in number of rois? The reader can find those abbreveations out, but it would be nice to have them defined.

      2) Fig. 1d) is confusing. The ACP-IR labelling is evident in 3 panels, but there is no difference in the color (emission spectra of 1992-ACP-IR vs 2031-ACP-IR should be visible??). The DAPI staining is very different. When doing the latter, how difficult is it to get the staining equal?

      3) How can one interpret Fig. 4: a) Control goes over 4 frames, at 240" insulin is added, and 10 frames should show a fluctuation difference? b) A color shift from blue to green is visible after insulin addition. But it is faint - difficult to assess from the pseudo color scheme. What does 1000 pixel top/1000 pixel bottom mean in c). Is it an attempt to better visualize the fluctuation? It is difficult to recognize a difference before and after adding insulin. d) It seems that the kymograph set should show this. What is the color scale? Why is 3 so untypical, i.e., no change? Box 6 is also peculiar: the left side does not show a strong change upon insulin administration, the right side does. Why?

      4) How is the kymogram calculated? The legend says 'The horizontal dimension represents the averaged ZNCC inside the rectangular area, and the vertical dimension represents time'. The averaged ZNCC is a single value, so it is not clear why the kymogram shows a variation from left to right. May it be the ZNCC was averaged just vertically?

      5) When calculating cross-correlation values on images, they need to be aligned. What fraction of the total image does the selected 19x19 box represent? As described, I imagine that a rolling CC over 19x19 pixels is calculated over an image from the time lapse series comparing it with the reference Iave(x,y). Compared to the 3x3 median filtered CP image, the ZNCC image should then be much more blurred??

      Minor comment:

      On page 16 supplementary is not spelled properly.

      Significance

      The key point of this paper is convincing and the new technology appears to have a lot of potential. It can be applied to study membrane protein function in the context of its environment, the lipid bilayer.

      Membrane fluidity measurements have been developed (e.g., using fluorescent probes like laurdan). However, the trick to link a probe like nile red by ACP technology to the insulin receptor and to observe its activity is quite new.

      A most recent description of such a technology is in TrAC Trends in Analytical Chemistry Volume 133, December 2020, 116092.

      Referees cross-commenting

      All comments are constructive and important. The paper is important but needs to be amended as proposed.

    1. Author Response

      Reviewer #2 (Public Review):

      -Were there any post-translational modifications (phosphorylation etc) or endogenous lipids that need to be quantified to make sense of the data?

      A percentage of receptors could be phosphorylated; therefore, our results represent the average behavior of the population. This is a noteworthy point and we have now explicitly discussed this idea in the revised the manuscript.

      In the in vivo experiments, heterogeneity in PTMs or local lipid environment of receptors could affect conformational change at the individual receptor level. For our analysis we integrate the intensities over the whole cell membrane, so the results represent the average behavior. Likewise, in the single-molecule FRET experiments many individual receptors are included in the analysis. Additionally, since the receptors are purified in the in vitro experiments, there is no further change in PTMs with application of drugs. We have added a sentence in the discussion to highlight the potential heterogeneity in PTMs and local lipid environment. We have also added a sentence to the methods to clarify how in vivo experiments are analyzed.

      Added to line 512 in discussion section: “Potential sources of heterogeneity arising from differences in post-translational modifications or differences in the local lipid environment, may affect receptor conformation. Therefore, our results represent the average of a heterogeneous population of such receptors.”

      Changed line 667 to: “ROIs used for analysis included the whole cell membrane for individual cells.”

      -mGLUR2 is a dimer. I was expecting that at 15 uM of Glutamate, for example, one might see effects of a single protomer-bound receptor. If I'm not mistaken, some class C receptors don't activate their CRDs until both ligand binding sites in the VFT are bound. Looking at all of the profiles in the VFT, CRD, and 7TM, I don't see any evidence of the 2-site binding of glutamate at the VFT. Presumably, there are Hill slopes for all of these profiles?

      Based on our previous work with the wildtype and with the receptor containing one glutamate binding deficient monomer, and available structures, indeed CRD domains do not significantly visit the active state unless both VFT domains are bound to glutamate and in the closed conformation. However, because activations involve progression through 2 intermediate states, we still expect to see FRET change even when both VFT domains are not occupied simultaneously. We have now revised Table 1 to included Hill slope. This data shows that cooperativity is generally observed for the FRET sensors for all the ligands tested.

      Reviewer #3 (Public Review):

      -The main concerns I had were with respect to labelling stoichiometry of the mixed Cy3/Cy5 compounds or SNAP-tag labels. How was this controlled? Clearly, both label cells, as shown in supplemental data and the single molecule FRET data support that both sites are labelled. Are there any concerns about larger molecular complexes such as oligomers that may confound the simple interpretation of interactions between the dimers?

      Among class C GPCRs, only GABA receptors have been shown to be able to potentially form efficient oligomers. Subunit counting experiments have shown that mGluR2 is predominantly dimer (> 90%) on the plasma membrane for the experimental conditions used in this manuscript (Levitz et al., 2016). The same result was obtained from live-cell FRET utilizing a dimer trafficking-control system (Maurel et al., 2008). This work also demonstrated that FRET occurred strictly for dimeric receptors labeled by both donor and acceptor fluorophores and not between neighboring receptors at the plasma membrane. Thus, receptors labeled with donor-only or acceptor-only do not contribute to the relative ΔFRET signal in response to treatment.

      -Some additional context might be a discussion of approaches used and results obtained for other types of conformational biosensors for GPCRs in other classes? Can we learn anything by comparison?

      We have revised the manuscript to include further discussion of results obtained from the use of other conformational sensors.

      Added to line 502: “Recent experiments have shown that GPCRs are dynamic (Nygaard et al., 2013) and undergo transition between multiple conformational states, including multiple intermediate states. For class A GPCRs, studies using conformational biosensors based on nuclear magnetic resonance (NMR) spectroscopy (Huang et al., 2021), double electron-electron resonance (DEER) spectroscopy (Wingler et al., 2019), smFRET (Gregorio et al., 2017), and fluorescent enhancement (Wei et al., 2022) have revealed the importance of conformational dynamics for receptor activation, ligand efficacy, and biased signaling.”

      Added to line 536: “Interestingly, the regulation of intermediate state occupancy has recently been shown to be a mechanism of allosteric modulation for other classes of GPCRs as well. NMR studies on the μ-opioid receptor (Kaneko et al., 2022) and cannabinoid receptor 1 (Wang et al., 2021) revealed that PAMs and NAMs regulate receptor function by acting on intermediate conformations in a manner similar to our findings for BINA and MNI-137. Collectively, these results suggest that designing compounds that regulate intermediate state occupancy is a plausible strategy for the development of allosteric modulators for mGluR2 and other families of GPCRs.”

    2. Reviewer #3 (Public Review):

      The authors used a combination of site-specific labelling at distinct sites within the mGluR2- the VFT domain in the ligand binding site, ECL2 (newly developed here), and the cysteine-rich domain (CRD) the latter of which is located between the VFT and ECL2. Using live cell FRET based on SNAP-tagged or unnatural amino acids, site-labeled with Cy3 or Cy5 tags, they validate that orthosteric ligands generate FRET changes consistent with their know efficacies and potencies, validating them for use in studying the effects of allosteric modulators. They next use single-molecule FRET to study the effects of the allosteric modulators on the receptor in the presence or absence of the orthosteric ligand, glutamate.

      Major strengths include the careful design, conduct, and analysis of the experiments and the validation of the effects of orthosteric ligands alone before proceeding to measurements of allosteric effects. They produce some very interesting results with the allosteric modulators in both experimental formats - the whole cell FRET consistent with known allosteric effects and the single molecule FRET identifying some independent effects of the allosteric modulators - this was quite striking. The approach is scalable to other GPCRs and to other membrane proteins in general.

      The main concerns I had were with respect to labelling stoichiometry of the mixed Cy3/Cy5 compounds or SNAP-tag labels. How was this controlled? Clearly, both label cells, as shown in supplemental data and the single molecule FRET data support that both sites are labelled. Are there any concerns about larger molecular complexes such as oligomers that may confound the simple interpretation of interactions between the dimers?

      Some additional context might be a discussion of approaches used and results obtained for other types of conformational biosensors for GPCRs in other classes? Can we learn anything by comparison?

    1. Reviewer #3 (Public Review):

      In this manuscript Houy and coworkers report new experiments regarding the role of phorbolester-activated Munc13 paralogs, Munc13-1 and ubMunc13-2, on the secretion response of mouse chromaffin cells. They report that expression of either paralog enhanced secretion. Using single knock outs (Figs. 1, 2) or with the expression of either paralog (Figs 3, 4) they found that treatment with the phorbolester PMA was stimulatory when ubMunc13-2 was the predominating paralog, but inhibitory when Munc13-1 dominated. The opposing PMA effects in the presence of either Munc13-1 or ubMunc13-2 were interpreted in the context of a potential competition of both proteins in essential priming reactions (Fig. 5). In simultaneous fluorescence recordings of EGFP tagged Munc13 variants they studied the Ca2+- and PMA-dependent translocation of Munc13 to the plasma membrane (PM). They found that only Munc13-2 (Fig. 3) but not Munc13-1 (Figs. 4, 5) is translocated to the PM in response an intracellular Ca2+-elevation. In this context, they also report that Ca2+ -dependent recruitment of ubMunc13-2 is independent of Synaptotagmin-7 (Fig. 6) and that in the absence of Synaptotagmin-7, ubMunc13-2-dependent secretion is inhibited by PMA (Fig. 7). Based on these results the authors argue that ubMunc13-2, Synaptotagmin-7 and DAG/phorbolester form a stimulatory entity to facilitate dense core vesicle fusion.<br /> Although the manuscript presents interesting observations, some conclusions appear to be compromised by methodological and conceptual concerns.

      Major criticism<br /> 1. In order to track Munc13 translocation the authors have chosen EGFP-tagged variants which overlap in the emission with the standard FuraII/Furaptra emission. Consequently, the authors omitted Ca2+-imaging in these experiments and thereby lost crucial information regarding the development of [Ca]I before and after the uncaging flash. These parameters are of central importance for the Ca2+-dependent priming and exocytosis timing, respectively. This is particularly worrisome, because in several experiments with Munc13 expression hardly any RRP component is apparent in the displayed capacitance traces, which may indicate insufficient Ca2+-dependent vesicle priming (Fig. 4). Under proper calcium control, both Ashery et al 2000 (Fig. 2) and Betz et al 2001 (Fig. 6) reported that Munc13-1 overexpression in wt chromaffin cells causes at least a 300% increase in the size of the EB compared to wt cells. Performing the same experiment, but without calcium imaging, the authors in Fig4-Sup1 show hardly any increase in the size of the EB (violet trace Fig4-Sup1) but a rather strong increase in the sustained phase of exocytosis, a phenotype that could be a result of low intracellular pre-flash calcium levels leading to insufficient vesicle priming. I do not understand why the authors have not chosen any other red-shifted protein tag to prevent such uncertainties. Furthermore, the display of the capacitance traces in several figures does not allow the appreciation of changes in the EB size or its components (e.g. RRP).<br /> 2. The authors speculate about the possibility, that PMA treatment PMA-treatment of Unc13b KO cells may lead to spontaneous release, depleting the cells of secretory vesicles. To test this, they determined the integrated CgA-fluorescence over the entire cell (Fig. 1M, N) rather than analyzing submembrane CgA-fluorescence. With the latter strategy, they will be able to focus on a potential subcellular depletion of release-ready vesicles.<br /> 3. After showing a detailed analysis of the exocytotic burst components and their kinetics in Fig. 1 and 2 the authors argue on page 9 Line 275 'Since the measurements above indicated that the main effect of PMA is on secretion amplitude, not kinetics (see also (Nagy et al., 2006)), we only distinguished between burst secretion (first 1s secretion after Ca2+ uncaging, corresponding approximately to RRP and SRP fusion) and sustained secretion (last 4 s of secretion), as well as total secretion (the sum of burst and sustained release). '<br /> I have some concerns with this argumentation because the expression of Munc13 paralogs apparently leads to changes in the burst components and/or it kinetics (e.g. Fig. 4B compare to Fig. 1 or 2). In fact, these differences cannot be directly appreciated, because experiments like in Fig. 3 and 4 lack the littermate wt control without and with PMA.<br /> Moreover, Munc13 expression leads to a disproportionate increase in the sustained phase of release, which is not present with PMA.<br /> I would recommend at least to include detailed analyses of the exocytotic burst components and their kinetics to address these uncertainties.

      4. As central hypothesis, the authors propose that they have identified a unique stimulatory triad of ubMunc13-2, Syt7 and DAG/phorbolesters, which is needed for dense core vesicle priming and fusion. For example, in contrast to the behavior of wt cells (e.g. Fig 1A) phorbolester treatment becomes inhibitory in cells lacking Syt7 and expressing ubMunc13-2 (Fig. 7). Nonetheless, previously published data by Sorensen's group, obtained under similar preflash [Ca]I conditions (Tawfik et al., 2021; Fig 6-figure supplement 2 E-H), clearly show that PMA strongly potentiates exocytosis even in the absence of Syt7. Therefore, these previous findings by Tawfik et al. clearly counter the central hypothesis of the manuscript. The authors should clarify these disparate results.

    1. Author Response:

      Reviewer #1 (Public Review):

      The manuscript by Kanca et al. presents a variety of valuable resources for the use of the Drosophila research community. As an update to the ongoing work of the Drosophila Gene Disruption Project, it includes hundreds of new transgenic fly lines each of which simultaneously knocks out a targeted gene and generates a driver that expresses the Gal4 transcription factor specifically in the pattern of that gene. The "KozakGal4" approach described supplements previous approaches of the GDP, including the powerful "CRIMIC" method, which inserts a synthetic exon containing a T2AGal4 module into an intron of the targeted gene. In the KozakGal4 method, the coding sequence of the native gene is completely replaced by Gal4, which the authors point out will allow them to target genes lacking (suitable) introns. In the KozakGal4 method, gene replacement is accomplished by targeted excision of the native gene using CRISPR-based technology and subsequent incorporation of a Gal4-encoding cassette by homologous recombination. The vectors developed by the authors to effect gene replacement are elegantly optimized to include all components necessary for native gene excision and efficient recombination of Gal4. These components include the guide RNAS (sgRNAs) that cleave flanking regions of the native gene, an sgRNA that liberates the Gal4 cassette from the vector, and short synthetic homology arms that provide effective, site-specific recombination. Importantly, the vectors are designed so that all gene-specific components can be synthesized in a single fragment that can be readily incorporated into the vector backbone followed by insertion of the Gal4 cassette.

      Overall, the technical advances described in the manuscript are impressive and the utility of the method is well demonstrated. The one exception is in the validation of Gal4 expression fidelity. As the authors note, fidelity could be compromised if regulatory information is removed along with sequences in and around a targeted gene. In addition, the introduction of new DNA at a particular locus may alter the regulation of gene expression. In any case, establishing the fidelity of expression of KozakGal4 lines is important and the data presented on this point is both confusing and incomplete. Rather than directly comparing the expression of selected KozakGal4 lines against the expression of the endogenous gene (e.g. by immunostaining, in situ hybridization, or by comparing tissue-specific reporter expression against expression in microarray-derived datasets such as Fly Atlas or modEncode), the authors use two indirect methods to demonstrate fidelity. One method uses VNC scRNAseq data together with the expression patterns of T2AGal4 lines that target genes co-expressed (at least in certain cell types) with the KozakGal4 line, while the other method uses phenotypic rescue by driving UAS-cDNA transgenes. The demonstrations are at best suggestive, and the rescue results presented are minimal, with no description of phenotypes, methods used to assay them, or quantification of rescue. There is thus insufficient information to form a judgment about fidelity and a more direct demonstration is needed.

      We appreciate that the manuscript can be strengthened by adding supporting evidence about the fidelity of GAL4 expression to the expression pattern of the targeted gene. The direct comparison of the GAL4 expression pattern to the expression pattern of the gene is a complex issue. The seemingly straightforward experiments of comparing the GAL4‐UAS reporter fluorescent protein expression pattern to the antibody staining of the targeted gene product suffers from multiple technical and practical issues: 1) Majority of the genes that we targeted are understudied and do not have a readily available antibody that would work for immunostaining. 2)Even if the antibodies were available, and even if the antibodies were completely specific, the staining pattern would likely be different from the GAL4‐UAS reporter expression pattern due to the subcellular localization of the gene product differing from the subcellular localization of the reporter. 3) GAL4‐UAS system introduces very high level of amplification of the signal compared to the expression of the gene product. We have reported the extent of this difference in the Lee et al. 2018 eLife paper where we used RMCE to convert the same MiMIC lines to EGFP protein trap alleles or T2AGAL4 gene trap alleles. The signals that we could detect in larval or adult brains looked qualitatively different. Comparing the expression pattern of the targeted genes product to the KozakGAL4‐UAS reporter gene signal would suffer from the same issue.<br /> To overcome these issues, we decided to compare GAL4 mRNA expression pattern of KozakGAL4 alleles to the mRNA expression pattern of the targeted gene. We employed smiFISH (single molecule Fluorescent In‐Situ Hybridization) in 3rd instar larval brains for 8 genes. We crossed the KozakGAL4 alleles of these genes to yw flies and performed co‐staining of GAL4 mRNA and targeted genes mRNA. In 7 cases where we could detect the mRNA expression of the gene product reliably, GAL4 mRNA expression pattern was overlapping with the mRNA expression pattern of the targeted gene, suggesting the transcriptional regulation of KozakGAL4 in the locus reflects the transcriptional regulation of the targeted gene. We note that the signal to noise level is quite low for some of the in situ hybridization results. Hence, we attenuated the language about the expression patterns of KozakGAL4 alleles reflecting the expression domain of the targeted genes by adding that there is a caveat that the regulatory elements in the coding regions and UTRs would be removed in these alleles. We include the smiFISH results as a supplementary figure and we add a paragraph describing methodology to the text.

      The manuscript could be strengthened in a couple of other spots as well. There is little to no description in either the Introduction or Results/Discussion of similar knock-out/knock-in approaches, although gene-specific knock-ins of Gal4 have been generated in Drosophila using homologous recombination for some time-typically into the site of ATG start codons. CRISPR technology has only facilitated this approach, which has also been used to create gene-specific cre knock-ins in rodents. This is of potential interest since the authors mention that their approach can be generalized for use in other animals. A short overview of existing knock-in approaches and their limitations relative to KozakGal4 would therefore be useful. Also, the authors motivate the need for the KozakGal4 method by asserting that over 50% of Drosophila genes lack "suitable" coding introns for the integration of artificial T2AGal4 exons such as CRIMIC. This seems to unnecessarily overstate the actual need. The authors define a "suitable" gene as one that has an intron common to all its isoforms that is at least 100 nt long. The length requirement is justified based on the need for suitable sgRNA targets within the intron, but it's possible to use sgRNA targets outside the intron (as long as the homology domains replace this sequence). Also, the requirement of a sufficiently long intron common to all isoforms is quite stringent and could be relaxed if multiple T2AGal4 lines were made to target multiple isoforms. Presumably, multiple KozakGal4 lines will, in fact, also be required for genes that have multiple transcription start sites, if the expression patterns of all isoforms are to be reproduced. In general, there's no doubt about the utility of the KozakGal4 approach, but a more balanced presentation of its merits relative to other approaches seems warranted.

      We agree with the reviewers that the presence of 100 nt long coding intron in all annotated isoforms is a relatively stringent criterion for deeming a gene to be a suitable target for T2AGAL4 methods. This requirement can indeed be relaxed if the same gene is targeted with multiple T2AGAL4 alleles. Nevertheless, for the GDP project, our aim is to generate genetic reagents for as many conserved genes as possible to make them accessible to the research community. Multiple T2AGAL4 that target individual splice isoforms can be done by the laboratories that work on those genes, using the methodology that we describe in this paper. We attenuate the language about the intron length requirements and included our justification for this requirement for the GDP project in the text.

      Reviewer #2 (Public Review):

      In this interesting paper, Kanca and coworkers present a set of updated constructs for the replacement of gene coding regions for instance by a Gal4 expression cassette or a GFP protein trap allele, enabling multiple research applications with the generated fly strains. The novel design now allows for the CRISPR-based targeting of almost any gene in Drosophila. The authors apply these novel tools and generate hundreds of fly lines that complement the pool of already existing strains in the Drosophila Gene Disruption Project. The authors report a high success rate for their HDR-mediated gene targeting strategy and show that they can even target genes that previously proved to be difficult to engineer. The authors validate the expression patterns of a set of lines - supported even by single-cell sequencing experiments - and provide strong evidence that the updated toolkit functions as expected.

      What may confuse the reader is that there are different targeting strategies that are presented with a strong focus on the validation of the expression cassettes used in combination with a specific targeting strategy (i.e., KozakGal4 or GFP protein trap). This leaves the reader with the impression that the insertion of a particular expression cassette would require a tailored targeting strategy, which is not the case. In fact, the majority of the paper deals with the description and extensive validation of small updates on already published methods for the insertion for the generation of additional KO/Gal4 or eGFP trap lines. However, neither the updated knock-in/knock-out strategies described for the insertion of the KOZAKGal4 cassette at the beginning of the results section nor the experiments to GFP tag proteins at different positions in the open reading frames (Figure 5) are of sufficient novelty and technical advancement.

      What really warrants publication is the very elegant and universal method described in Figure 4 that requires only a single vector to be injected into fly embryos. The method is suited to precisely engineer any gene at will in combination with any HDR template. The very smart vector design allows for the directed insertion of custom and commercially synthesized HDR constructs as well as of a specific guide required to target and cut the gene of interest. This makes the method versatile, fast and cheaper with the benefit of being very efficient. This gRNA_int200 targeting strategy will be of broad interest, is straightforward to use and is expected to have a large impact - far beyond the fly community.

      We thank the reviewer for the constructive criticism and for seeing the benefits in our methodology. Although the KozakGAL4 and GFP knock‐ins in the genome are not conceptually new, the combination of our vector design makes the application of these concepts straightforward. Additionally, the extent of application and verification of GAL4 knock‐ins was limited compared to what we include in this manuscript which prompted us to include the KozakGAL4 and GFP knock‐in methodology in this manuscript.

    2. Reviewer #2 (Public Review):

      In this interesting paper, Kanca and coworkers present a set of updated constructs for the replacement of gene coding regions for instance by a Gal4 expression cassette or a GFP protein trap allele, enabling multiple research applications with the generated fly strains. The novel design now allows for the CRISPR-based targeting of almost any gene in Drosophila. The authors apply these novel tools and generate hundreds of fly lines that complement the pool of already existing strains in the Drosophila Gene Disruption Project. The authors report a high success rate for their HDR-mediated gene targeting strategy and show that they can even target genes that previously proved to be difficult to engineer. The authors validate the expression patterns of a set of lines - supported even by single-cell sequencing experiments - and provide strong evidence that the updated toolkit functions as expected.

      What may confuse the reader is that there are different targeting strategies that are presented with a strong focus on the validation of the expression cassettes used in combination with a specific targeting strategy (i.e., KozakGal4 or GFP protein trap). This leaves the reader with the impression that the insertion of a particular expression cassette would require a tailored targeting strategy, which is not the case.<br /> In fact, the majority of the paper deals with the description and extensive validation of small updates on already published methods for the insertion for the generation of additional KO/Gal4 or eGFP trap lines. However, neither the updated knock-in/knock-out strategies described for the insertion of the KOZAKGal4 cassette at the beginning of the results section nor the experiments to GFP tag proteins at different positions in the open reading frames (Figure 5) are of sufficient novelty and technical advancement.

      What really warrants publication is the very elegant and universal method described in Figure 4 that requires only a single vector to be injected into fly embryos. The method is suited to precisely engineer any gene at will in combination with any HDR template. The very smart vector design allows for the directed insertion of custom and commercially synthesized HDR constructs as well as of a specific guide required to target and cut the gene of interest. This makes the method versatile, fast and cheaper with the benefit of being very efficient. This gRNA_int200 targeting strategy will be of broad interest, is straightforward to use and is expected to have a large impact - far beyond the fly community.

    1. The meta description is a snippet of up to about 155 characters – a tag in HTML – which summarizes a page’s content.

      What is meta description? The meta description is a snippet of up to about 155 characters – a tag in HTML – which summarizes a page’s content.

    1. n the IndieWeb we’ve talked a bunch about following people rather than feeds, and wanting to be able to see that in one place rather than going to each service.

      I don't love this, of course, even as I've taped on every Indieweb accoutrement to my own site. It's so prescriptive -- like the converse of the idea that one should slice up one's own posts into neat tag-based filtered feeds for the convenience of The Consumer. Maybe I like that there's some friction in getting from my hypertexting to my more social nattering. To say it must be otherwise feels... real-name-policy-esque.

    1. Reviewer #2 (Public Review):

      Motile cilia generate rhythmic beating or rotational motion to drive cells or produce extracellular fluid flow. Cilia is made of nine microtubule doublets forming a spoke-like structure and it is known that dynein motor proteins, which connects adjacent microtubule doublet, are the driving force of ciliary motion. However the molecular mechanism to generate motion is still unclear. The authors proved that a pair of microtubules stably linked by DNA-origami and driven by outer dynein arms (ODA) causes beating motion. They employed in vitro motility assay and negative stain TEM to characterize this complex. They demonstrated stable linking of microtubules and ODAs anchored on the both microtubules are essential for oscillatory motion and bending of the microtubules.

      Strength<br /> This is an interesting work, addressing an important question in the motile cilia community: what is the minimum system to generate a beating motion? It is an established fact that dynein power stroke on the microtubule doublet is the driving force of the beating motion. It was also known that the radial spoke and the central pair are essential for ciliary motion under the physiological condition, but cilia without radial spokes and the central pair can beat under some special conditions (Yagi and Kamiya, 2000). Therefore in the mechanistic point of view, they are not prerequisite. It is generally thought that fixed connection between adjacent microtubules by nexin converts sliding motion of dyneins to bending, but it was never experimentally investigated. Here the authors successfully enabled a simple system of nexin-like inter-microtubule linkage using DNA origami technique to generate oscillatory and beating motions. This enables an interesting system where ODAs form groups, anchored on two microtubules, orienting oppositely and therefore cause tag-of-war type force generation. The authors demonstrated this system under constraints by DNA origami generates oscillatory and beating motions.<br /> The authors carefully coordinated the experiments to demonstrate oscillations using optical tweezers and sophisticated data analysis (Fourier analysis and a step-finding algorithm). They also proved, using negative stain EM, that this system contains two groups of ODAs forming arrays with opposite polarity on the parallel microtubules.<br /> The manuscript is carefully organized with impressive movies. Geometrical and motility analyses of individual ODAs used for statistics are provided in the supplementary source files. They appropriately cited similar past works from Kamiya and Shingyoji groups (they employed systems closer to the physiological axoneme to reproduce beating) and clarify the differences from this study.

      Weakness<br /> The authors claim this system mimics two pairs of doublets at the opposite sites from 9+2 cilia structure by having two groups of ODAs between two microtubules facing opposite directions within the pair. It is not exactly the case. In the real axoneme, ODA makes continuous array along the entire length of doublets, which means at any point there are ODAs facing opposite directions. In their system, opposite ODAs cannot exist at the same point (therefore the scheme of Dynein-MT complex of Fig.1B is slightly misleading). If they want to project their result to the ciliary beating model, more insight/explanation would be necessary. For example, arrays of dyneins at certain positions within the long array along one doublet are activated and generate force, while dyneins at different positions are activated on another doublet at the opposite site of the axoneme. This makes the distribution of dyneins and their orientations similar to the system described in this work. Such a localized activation, shown in physiological cilia by Ishikawa and Nicastro groups, may require other regulatory proteins.<br /> They attempted to reveal conformational change of ODAs induced by power stroke using negative stain EM images, which is less convincing compared to the past cryo-ET works (Ishikawa, Nicastro, Pigino groups) and negative stain EM of sea urchin outer dyneins (Hirose group), where the tail and head parts were clearly defined from the 3D map or 2D averages of two-dynein ODAs. Probably three heavy chains and associated proteins hinder detailed visualization of the tail structure. Because of this, Fig.2C is not clear enough to prove conformational change of ODA. This reviewer imagines refined subaverage (probably with larger datasets) is necessary. It is not clear, from the inset of Fig.2 supplement3, how to define the end of the tail for the length measurement, which is the basis for the authors to claim conformational change (Line263-265). The appearance of the tail would be altered, seen from even slightly different view angles. Comparison with 2D projection from apo- and nucleotide-bound 3-headed ODA structures from EM databank will help.

      In Fig.5B (where the oscillation occurs), the microtubule was once driven >150nm unidirectionally and went back to the original position, before oscillation starts. Is it always the case that relatively long unidirectional motion and return precede oscillation? In Fig.7B, where the authors claim no oscillation happened, only one unidirectional motion was shown. Did oscillation not happen after MT returned to the original position?

      Line284-290: More characterization of bending motion will be necessary (and should be possible). How high frequency is it? Do they confirm that other systems (either without DNA-origami or without ODAs arraying oppositely) cannot generate repetitive beating?

    1. Author Response

      Reviewer #1 (Public Review):

      The authors attempt to optimize the FluoroSpot assay to allow for the assessment of cross-reactive antibodies targeting conserved epitopes shared by multi-allelic antigens and those specific to unique antigen variant at the B cells level. This is a critical aspect to consider when identifying targets of a broad range of cross-reactive antibody for vaccine development and the antigen VAR2CSA used in this work is one that will benefit from the method described in the manuscript.

      Overall, this is a method manuscript with extensive detail of the assay validation process. The description of the assay performance steps using, first monoclonal antibodies and later hybridoma/immortalized B cells was important to understand conditions that can influence the antigen-antibody interactions in the assay. This multiplex approach can assess the cross-reactivity of antibody to up four allelic variants of an antigen with the possibility to explore the affinity of antibody to a particular variant using the RSV measurements. The validation of the assay with PBMC from malaria exposed donors both men and women (that naturally acquired high titer of antibodies to VAR2CSA during pregnancy) is a strength of this work as this is in the context of polyclonal antibodies with more heterogenous antibody binding specificities.

      The ability of the assay to detect cross-reactive antibodies using all four tags appear highly variable even in the context of monoclonal antibody targeting the homologous antigen labelled with all 4 tags.

      We understand the concern for variability, but we think that in general the assay was very consistent. Regardless of the configuration used, we detected strikingly comparable number of spots/well, especially when the homologous antigen labelled with four tags was used (Figure 2A). Similar consistency has been previously reported when a similar assay was used to study cross-reactivity in dengue-specific antibodies.

      Overall, it appears that the assessed antibody reactivity with TWIN tagged antigens was relatively low and this needs to be explained and discussed as the current multiplex method, as it is, might just be optimized for study of cross-reactive antibodies to 3 antigens.

      The LED380 (used to detect and visualize the TWIN tag) indeed gave more background than the other three detection channels. We normally observed a ring of fluorescence at the edge and the middle of the wells, accompanied by lower intensity of the spots. These two characteristics are apparent in the figures and RSV plots presented in the manuscript. In an attempt to reduce these issues, we attempted to substitute the TWIN tag for a BAM tag detected with a peptide-specific antibody (data not presented). However, that approach did not improve the readout and we therefore decided to keep the TWIN-StrepTactin pair for all the experiments. Importantly, even with these issues, routine manual inspection of the wells confirmed the Apex software automatically and efficiently counted “real” spots giving us confidence on the performance of the assay. We acknowledge that exclusion of the LED380 data would lead to higher assay accuracy. However, it would result in reduced ability to assess broad antibody cross-reactivity, which was the primary objective of our study. We have added text briefly discussing this to the revised manuscript (lines 154-160).

      As acknowledged by the authors, the validation of this assay on PBMC from only 10 donors (7 women and 3 men) is a caveat to the conclusion and increasing this number of donors (the authors have previously excelled in B cells analyses of PfEMP1 proteins and would have PBMC readily available) will strengthen the validity of this assay.

      We thank the reviewer for this comment and agree the number of donors tested is far from sufficient to provide any conclusive evidence regarding frequencies of VAR2CSA-specific and cross-reactive B cells in the context of placental malaria. However, we firmly believe that the validation of the assay – which was the objective of the study – is sufficient, especially because we included human B-cell lines isolated from donors naturally exposed to VAR2CSA-expressing parasites. Futures studies including more donors and full-length VAR2CSA antigens are certainly warranted. As the performance of assay has now been validated (this manuscript) to our satisfaction, we are indeed planning such studies.

      Reviewer #2 (Public Review):

      The manuscript describes the development of a laboratory-based assay as a tool designed to identify individuals who have developed broadly cross-reactive antibodies with specificity for regions that are common to multiple variants of a given protein (VAR2CSA) of Plasmodium falciparum, the parasite that causes malaria. The assay has potential application in other diseases for which the question ofacquisition of antibody-mediated immunity, either through natural exposure or through vaccination, remains unresolved.

      From a purely technical/methodological viewpoint, the work described is of high quality, relying primarily on the availability of custom-designed, in-house-derived protein and antibody reagents that had, for the most part, been validated through use in earlier studies. The authors demonstrate a high degree of rigour in the assay development steps, culminating in a convincing demonstration of the ability to accurately and reproducibly quantify cross-reactive antibody types under controlled conditions using well-characterized monoclonal antibodies.

      In a final step, the authors used the assay to assess the content of broadly cross-reactive antibodies in samples from a small number of malaria-exposed African men and women. Given that VAR2CSA is a parasite-derived protein that is exclusively and intimately involved in the manifestation of malaria during pregnancy, with specific localisation to the maternal placental space, the premise is that antibodies -including those with cross-reactive specificities - should be almost exclusively detectable in samples from women, either pregnant at the time of sampling or having been pregnant at least once. The assay functioned technically as expected, identifying antibodies predominantly in women rather than men, but it failed to identify broadly cross-reactive antibodies in the women's samples used, only revealing antibodies with specificity for just one of the different variants used. The latter result could have two mutually non-exclusive explanations. On the one hand, the small number of women's samples (7) screened in the assay could simply be insufficient, demanding the use of a much larger panel. On the other hand, for technical reasons the assay involves the use of only relatively restricted parts of the VAR2CSA protein, and this particular aspect may represent its primary limitation. In earlier work, the authors did identify broadly cross-reactive antibodies in samples from African women, but that work relied on the use of the whole VAR2CSA protein present in its natural state embedded in the membrane of the infected red cell, or as a complete protein produced in the laboratory. The important point being that the whole protein likely interacts with antibodies that recognize protein structures that the isolated smaller parts of the whole protein used in the assay fail to reproduce, and that the cross-reactive antibodies identified recognize these structures that are conserved across different VAR2CSAvariants. The authors recognize these potential weaknesses in their discussion of the results. It is also possible that VAR2CSA variants expressed by parasites from geographically-distinct regions (Africa, Asia, South America) are themselves distinct, and this aspect could also have affected the outcome, since the variant protein sequences used in the assay were derived from parasites originating in these different regions.

      The assay could find application in the malaria research field in the specific context of assessments of antibody responses to a range of different parasite proteins that are, or have been, considered candidates for vaccine development but for which their extensive inherent allelic polymorphism has effectively negated such efforts.

      We thank the reviewer for the kind evaluation. We fully acknowledge the need for more comprehensive studies to assess the robustness of the pilot data regarding antibody cross-reactivity after natural exposure in the present study, which was aimed to document the performance of the complicated multiplexed assay rather than to provide such evidence. As mentioned above, we are currently planning such a study. We also acknowledge the need to assess the degree of cross-reactivity to full-length antigens rather than domain-specific components of them. This is obviously particularly true for large, multi-domain antigens such as PfEMP1 (including VAR2CSA). Such an exercise is complicated by the need for appropriately tagged antigens. We are intrigued by the apparent discrepancy between the degree of antibody cross-reactivity in depletion experiments using individual DBL domains of VAR2CSA (low cross-reactivity) versus full-length VAR2CSA antigens (very substantial cross-reactivity) reported by Doritchamou et al., and are keen to apply our approach to explore that finding. Therefore, as also mentioned above, we are currently planning a study employing tagged full-length VAR2CSA allelic variants as well.

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      Reply to the reviewers

      We thank the reviewers for their constructive comments and are pleased that all reviewers share our opinion, that the present study “makes an important contribution to the molecular architecture of mitochondria”, is in addition “an important advancement in our understanding of the mechanism by which Cqd1 regulates CoQ distribution” and will “thereby appealing to the broad readership of the journals”. We are convinced that addressing the important points raised by the reviewers will further strengthen the manuscript and result in additional significant insights in the molecular function of Cqd1.

      Reviewer #1:

      The major concerns affecting the conclusions are: 1) Experimental evidence is lacking on the contribution of contact site formation by Cqd1 to the effects on mitochondrial architecture and respiration-dependent growth. Determining the effects of the overexpression of the kinase-dead mutant on mitochondrial morphology and contact site formation with Por1-Om14 can address that.

      We thank reviewer #1 for raising these important points. Indeed, the various functions of Cqd1 might be independent from each other and so far we cannot distinguish between them. As suggested by the reviewer we will analyze the effect of overexpression of CQD1 in the Dups1 deletion mutant and make use of the point mutant in the conserved ATP binding domain which cannot complement the phenotype of the Dups1 Dcqd1 double deletion mutant. We generated a yeast mutant strain expressing Om14-3xHA in the absence of wild type Cqd1. Expression of the cqd1(E330A) mutant in the Om14-3xHA background and subsequent immunoprecipitation will allow us to test whether ATP binding is also essential for contact site formation. Preliminary experiments showed that the overexpression of cqd1(E330A) in the Dcqd1 deletion background results in a growth defect comparable to that caused by overexpression of CQD1 WT. Therefore, we think it might be more promising to analyze the interaction of Om14 and Cqd1 E330A at wild type level in order to avoid pleiotropic effects.

      In addition, we will further characterize the cqd1(E330A) mutant by analyzing the effect of its overexpression on mitochondrial morphology, cell growth and assembly of MICOS and F1FO ATP synthase in the Dcqd1 deletion background.

      2) Related to point #1, Cqd1 overexpression in deltaUsp1 cells could have addressed whether the role of Cqd1 in contact sites and mitochondrial architecture is independent of its role on CoQ distribution and phospholipid metabolism. Further characterization of the kinase-dead Cqd1 mutant on CoQ distribution, contact sites, mitochondrial archictecture and phsophsolipid metabolism might help discerning how these activities can be separated.

      We agree that the related points 1) and 2) raised by reviewer #1 are important and addressed our plans in the response on point 1).

      3) It is unclear how both Cqd1 overexpression and deletion induce mitochondrial fragmentation. Performing live cell imaging with a mitochondrial-phoactivatable GFP to measure mitochondrial fusion rates could help discerning the causes for fragmentation. It is a possibility that overexpression induced fragmentation by activating fission without changing fusion, while deletion induced fragmentation by blocking fusion.

      We thank reviewer #1 for bringing up this point. Perhaps our explanation in this respect was too short. Fig. 4E shows that deletion of CQD1 does not result in altered mitochondrial morphology, however, deletion of CQD1 in the Dups1 background leads to virtual complete fragmentation of the mitochondrial network. This is likely due to inhibition of mitochondrial fusion through disturbed processing of the fusion protein Mgm1 (see Fig. 4D). In contrast, overexpression of CQD1 does NOT result in formation of small mitochondrial fragments, but in formation of huge mitochondrial clusters which in addition contain a large proportion of ER membranes. So, we don’t think that this phenotype is related to either enhanced fission or reduced fusion. We will clarify this point in text of the revised manuscript.

      Minor comment:

      1) Figure 4 claims that mitochondrial function is impaired by ups1 deletion, which Cqd1 deletion exacerbates. However, no respiration data is shown in figure 1, only measurements of mitochondrial architecture are shown. Thus, oxygen consumption measurements are needed to claim effects on mitochondrial function.

      We did not want to claim that mitochondria lose respiratory competence upon simultaneous deletion of CQD1 and UPS1. Actually, our results indicate that the Dups1 Dcqd1 double deletion mutant grows like wild type on complete medium containing glycerol. Therefore, respiration is not impaired in this mutant. However, mitochondrial function is not restricted to ATP production by oxidative phosphorylation. The reviewer probably refers to Figure 4 where we show that mitochondrial biogenesis and dynamics are impaired in the Dups1 Dcqd1 double deletion mutant – the heading of the legend summarizes this as "mitochondrial function". We will be more precise in the revised version on this point and add a panel showing growth of the mutant strain on non-fermentable carbon source to avoid any further confusion.

      2) Some Western blots lack quantifications and statistical analyses of independent experiments.

      It is correct that some quantification and the respective statistics were missing in the initially submitted manuscript. We will add the requested information in the revised version of the manuscript.

      Reviewer #2:

      I have the following concerns for the authors to consider. (1) Although biochemical evidence shows that Cqd1 is likely a factor that forms CS structures in mitochondria, it would make the manuscript stronger if the authors can observe uneven distribution of Cqd1 in the mitochondrial membranes (assessed by fluorescent microscopy or ideally high-resolution microscopy) and the presence of Cqd1 in the region of close apposition of the OM and IM by immunogold labeling for electron microscopy.

      Two independent lines of evidence show that Cqd1 is a novel contact site protein: (i) it is found in the contact site fraction in density gradients (Fig. 6A), and (ii) it can be co-immunoprecipitated with outer membrane proteins (Fig. 6G, H, I). Furthermore, the co-IP is supported by cross-links of expected size (Fig. 6F). In sum, we feel that this is solid evidence to support our claim that Cqd1 is present in mitochondrial contact sites. However, it still might be interesting to check an uneven distribution of Cqd1 in mitochondria, as suggested by the reviewer. We will do this by 3D deconvolution fluorescence microscopy.

      (2) Since the structural characterization of Cqd1 is important to understand its interactions with the OM proteins and other UbiB protein kinase-like family proteins, Coq8 and Cqd2, take different orientations, the membrane topology of Cqd1 should be experimentally analyzed. The authors state, "two hydrophobic stretches can be identified in the Cqd1 sequence, of which the first one (amino acids 125-142) might be a bona fide transmembrane segment" (lines 97-100); then is Cqd1 a single membrane spanning protein or two-membrane spanning protein?  

      Unfortunately, it was not possible to test the location of the N terminus experimentally because an N-terminally tagged variant of Cqd1 (tag inserted between presequence and mature part) turned out to be unstable. We consider it very unlikely that the second hydrophobic stretch is a transmembrane domain as it is rather short (only 11 amino acids). Furthermore, several Cqd1 homologs in other fungi, including Yarrowia lipolytica, Aspergillus niger and Schizosaccharomyces pombe, are lacking the second hydrophobic stretch. Therefore, we propose that the major part of Cqd1 including the protein kinase-like domain is exposed to the intermembrane space. We will point out this more clearly in the revised manuscript.

      (3) The authors state, "conserved GxxxG dimerization motif (amino acids 504‐508)" (Fig. 1A caption), but this description needs a reference. The GxxxG motif was proposed to mediate transmembrane helix-helix association (https://doi.org/10.1006/jmbi.1999.3489), which is not consistent with the membrane topology proposed by the authors.

      We thank reviewer #2 for this comment. It is correct that GxxxG motifs are usually present in transmembrane a-helices. However, there is information available indicating that these motifs may also be present in soluble proteins and are stabilizing dimeric interactions for instance in the homodimeric Holliday-junction protein resolvase (Kleiger et al., 2002; doi: 10.1021/bi0200763.). However, as this point is not critical for our conclusions we will remove the discussion of the GxxxG motif from the revised manuscript.

      (4) What is the role of the kinase activity of Cqd1 in the CS formation? The effects of overexpression of Cqd1 (Fig. 7) should be tested for its E330A mutant.

      We also thank reviewer #2 for raising this important point similar to reviewer #1. Please see our response to point 1) of reviewer #1.

      (5) Is there stoichiometric as well as quantitative information on the 400 kD complex consisting of Cqd1, Por1 and Om14? Does the stoichiometry and amount of the complex depend on the growth condition? Does the complex contain other Por1 interacting IM proteins like Mdm31?

      We appreciate that reviewer #2 points out this important aspect. It might well be that the amount of the Cqd1 containing complex depends on growth conditions since its presence might be important for phospholipid homeostasis, CoQ distribution and mitochondrial architecture and morphology which for sure strongly depend on growth conditions. Therefore, we will try to analyze the amount of the Cqd1 complex present in mitochondria isolated from yeast cells grown on different media by BN-PAGE. So far we do not have any information on the stoichiometry of this complex and we feel that an analysis would go beyond the scope of this study. We agree with reviewer #2 that Mdm31 is an obvious candidate for an interaction partner of Cqd1. We actually tested this by co-immunoprecipitation using Cqd1-3xHA or Mdm31-3xHA. However, none of these approaches resulted in successful co-isolation of the potential interaction partner. We will mention this result in the revised manuscript.

      (6) For Fig. 7E, the authors state, "consistently, we observed dramatically increased mitochondria‐ER interactions Cqd1 overexpression", but this observation could be due to secondary effects because overexpression of Cqd1 itself already caused abnormal morphology of mitochondria.

      We thank reviewer #2 for bringing up this important point. To check whether the increased mitochondria‐ER interactions are a secondary effect due to altered mitochondrial morphology we will analyze the mitochondria‐ER interactions in other mitochondrial morphology mutants by fluorescence microscopy. This will reveal whether abnormal mitochondrial morphology generally leads to disturbed ER structure.

      (7) Since the antagonistic role of Cqd2 to Cqd1 was proposed, the results of the experiments for Cqd1 can be compared with those for Cqd2. For example, what will become of overexpression of Cqd2 instead of Cqd1 for Fig. 7? What is the lipid composition of the cqd1Dcqd2D double deletion mutant cells (the decreased PA level is recovered?)? Lines 424-425: In summary, overexpression of Cqd1 causes severe phenotypes on growth, formation of mitochondrial structural elements, and mitochondrial architecture and morphology. Is this phenotype affected by overexpression of Cqd2?

      This point raised by reviewer #2 is very interesting. Our preliminary experiments and previously published data (Tan et al., 2013) indicate that overexpression of Cqd2 is also toxic and results in the formation of huge mitochondrial clusters. Therefore, we will extend our study and analyze the effect of overexpression of CQD2, either alone or in combination with overexpression of CQD1.

      Reviewer #3:

      1) The central point of the paper is that Cqd1 is part of a novel contact site between the inner and the outer membrane. Om14 and Por1 were identified as outer membrane components of this contact site by immunoprecipitation. The data look convincing but they were generated from targeted experiments to test the involvement of suspected proteins. Ideally, one would like to see a cross-linking mass spectrometry (XL-MS) experiment that identifies the physical interactions of Cqd1 without bias.

      We thank reviewer #3 for acknowledging the presented data as convincing. Considering the significant amount of experiments planned for the revised version of the manuscript, we hope that reviewer #3 agrees that this point is not essential.

      2) Could an analogous blot of the MICOS complex be added to Figure 6D?

      Of course, we are happy to include BN-PAGE analysis showing the running behavior of MICOS next to the Cqd1 containing complex in Fig. 6D.

      3) In the Introduction, a host of contact sites is mentioned, which are partly from older papers. I'm not sure whether this is the accepted view of the field. Also, newer data suggest that the permeability transition pore is derived from complex V rather than ANT, CK, and VDAC. The authors should double check in order to represent the current state of the art

      We thank reviewer #3 for this comment. We will update this part according to the more recent literature.

    1. 将第一原理这个概念带火的是埃隆∙马斯克——一个改变游戏规则,不断颠覆传统的创业者

      第一原理是马斯克的标签tag,就像多元思维模型是查理芒格的一样!

    Tags

    Annotators

    1. The addressing system that many digital note taking systems offer is reminiscent of Luhmann's paper system where it served a particular use. Many might ask themselves if they really need this functionality in digital contexts where text search and other affordances can be more directly useful.

      Frequently missed by many, perhaps because they're befuddled by the complex branching numbering system which gets more publicity, Luhmann's paper-based system had a highly useful and simple subject heading index (see: https://niklas-luhmann-archiv.de/bestand/zettelkasten/zettel/ZK_2_SW1_001_V, for example) which can be replicated using either #tags or [[wikilinks]] within tools like Obsidian. Of course having an index doesn't preclude the incredible usefulness of directly linking one idea to potentially multiple others in some branching tree-like or network structure.

      Note that one highly valuable feature of Luhmann's paper version was that the totality of cards were linked to a minimum of at least one other card by the default that they were placed into the file itself. Those putting notes into Obsidian often place them into their system as singlet, un-linked notes as a default, and this can lead to problems down the road. However this can be mitigated by utilizing topical or subject headings on individual cards which allows for searching on a heading and then cross-linking individual ideas as appropriate.

      As an example, because two cards may be tagged with "archaeology" doesn't necessarily mean they're closely related as ideas. This tends to decrease in likelihood if one is an archaeologist and a large proportion of cards might contain that tag, but will simultaneously create more value over time as generic tags increase in number but the specific ideas cross link in small numbers. Similarly as one delves more deeply into archaeology, one will also come up with more granular and useful sub-tags (like Zooarcheology, Paleobotany, Archeopedology, Forensic Archeology, Archeoastronomy, Geoarcheology, etc.) as their knowledge in sub areas increases.

      Concretely, one might expect that the subject heading "sociology" would be nearly useless to Luhmann as that was the overarching topic of both of his zettelkästen (I & II), whereas "Autonomie" was much more specific and useful for cross linking a smaller handful of potentially related ideas in the future.

      Looking beyond Luhmann can be highly helpful in designing and using one's own system. I'd recommend taking a look at John Locke's work on indexing (1685) (https://publicdomainreview.org/collection/john-lockes-method-for-common-place-books-1685 is an interesting source, though you're obviously applying it to (digital) cards and not a notebook) or Ross Ashby's hybrid notebook/index card system which is also available online (http://www.rossashby.info/journal/index.html) as an example.

      Another helpful tip some are sure to appreciate in systems that have an auto-complete function is simply starting to write a wikilink with various related subject heading words that may appear within your system. You'll then be presented with potential options of things to link to serendipitously that you may not have otherwise considered. Within a digital zettelkasten, the popularly used DYAC (Damn You Auto Complete) may turn into Bless You Auto Complete.

    1. SciScore for 10.1101/2022.06.01.494385: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Consent: Sera were collected at the U.S. Food and Drug Administration with written consent under an approved Institutional Review Board (IRB) protocol (FDA IRB Study # 2021-CBER-045).<br>IRB: Sera were collected at the U.S. Food and Drug Administration with written consent under an approved Institutional Review Board (IRB) protocol (FDA IRB Study # 2021-CBER-045).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Membranes were probed for the V5-tag and γ-actin using V5 epitope tag antibody (Novus Biologicals, Centennial, CO), and mouse gamma actin polyclonal antibody (Thermofisher), respectively.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>V5-tag</div><div>suggested: (Novus Cat# NB100-62264, RRID:AB_965837)</div></div><div style="margin-bottom:8px"><div>V5 epitope tag antibody (Novus Biologicals, Centennial, CO)</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>mouse gamma actin</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">ACE2 genes of various species (African green monkey (AGM), Chinese rufous horseshoe bat (Rhinolophus sinicus), ferret, mouse, Chinese hamster, Syrian golden hamster, white-tailed deer, swine, bovine, and pangolin) with a C-terminal V5 tag were synthesized by GenScript as described previously 42. 293T (ATCC, Manassas, VA, USA; Cat no: CRL-11268), 293T.ACE2 (BEI Resources, Manassas, VA, USA; Cat no: NR-52511) 64 and 293T.ACE2.TMPRSS2 cells stably expressing human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) (BEI Resources, Manassas, VA, USA; Cat no: NR-55293) 34 were maintained at 37°C in Dulbecco’s modified eagle medium (DMEM) supplemented with high glucose, L-glutamine, minimal essential media (MEM) non-essential amino acids, penicillin/streptomycin, HEPES, and 10% fetal bovine serum (FBS).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T.ACE2.TMPRSS2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudoviruses comprising the spike glycoprotein and a firefly luciferase (FLuc) reporter gene packaged within HIV capsid were produced in 293T cells by co-transfection of 5 μg of pCMVΔR8.2, 5 μg of pHR’CMVLuc and 0.5 μg of pVRC8400 or 4 μg of pcDNA3.1(+) encoding a codon-optimized spike gene.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Soluble ACE2 Protein Production: His-tagged soluble human ACE2 was produced in FreeStyle™ 293-F cells by transfecting soluble human ACE2 (1-741 aa) expression vector plasmid DNA using 293fectin (Thermo Fisher) and purified using HiTrap Chelating column charged with nickel (GE healthcare) according to the manufacturer’s instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293-F</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids and Cell Lines: Codon-optimized, full-length open reading frames of the spike genes of B.1 (D614G) and Omicron variants in the study were synthesized into pVRC8400 (B.1, BA.1, BA.2, and BA.3) or pcDNA3.1(+) (BA.1.1) were obtained from the Vaccine Research Center (National Institutes of Health, Bethesda, MD) and GenScript (Piscataway, NJ, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pVRC8400</div><div>suggested: RRID:Addgene_63163)</div></div><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The HIV gag/pol packaging (pCMVΔR8.2) and firefly luciferase encoding transfer vector (pHR’CMV-Luc) plasmids 62,63 were obtained from the Vaccine Research Center (National Institutes of Health, Bethesda, MD, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pHR’CMV-Luc</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudoviruses comprising the spike glycoprotein and a firefly luciferase (FLuc) reporter gene packaged within HIV capsid were produced in 293T cells by co-transfection of 5 μg of pCMVΔR8.2, 5 μg of pHR’CMVLuc and 0.5 μg of pVRC8400 or 4 μg of pcDNA3.1(+) encoding a codon-optimized spike gene.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMVΔR8.2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Titers were calculated using a nonlinear regression curve fit (GraphPad Prism Software Inc., La Jolla, CA, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The ACE2 concentration causing a 50% reduction of luciferase activity compared to untreated control was reported as the IC50 using a nonlinear regression curve fit (GraphPad Prism software Inc., La Jolla, CA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:


      Our study has several caveats, including the use of pseudoviruses instead of authentic SARS-CoV-2 for conducting experiments. However, our findings using pseudoviruses agree with those reported using authentic SARS-CoV-2. For instance, authentic BA.1 /BA.1.1 VOCs were shown to undergo attenuated replication in TMPRSS2-expressing cells compared to ancestral Wuhan-Hu-1, and Alpha, Beta, and Delta VOCs 6,36. These reports also showed greater sensitivity of BA.1 pseudovirus entry to endosomal inhibitor E64d. While we used pseudovirus entry assays to determine Omicron variant usage of ACE2 receptors of various animal species, it remains unknown whether there may be intrinsic and/or innate host-specific factors that might act to inhibit live Omicron VOCs at an entry or post entry step. Furthermore, although we identified RBM substitutions in Omicron spike that conferred the ability to use mouse or horseshoe bat ACE2, we didn’t confirm ACE2 substitutions that permit or prevent Omicron spike binding. For instance, introducing K35E substitution in horseshoe bat ACE2 should permit Omicron variants’ usage. Finally, analysis of a limited number of serum samples and short follow up after the receipt of three doses of the Pfizer/BNT162b2 mRNA vaccine do not give us insights into the durability of the antibody response. While studies of antibody durability are ongoing, our findings indicate that three dose immunization with the Pfizer/BNT162b2 will likely contribute to protection from sever...


      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • No funding statement was detected.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.06.01.494101: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Protein samples were resolved by SDS polyacrylamide gel electrophoresis and transferred onto a nitrocellulose membrane using Trans-Blot Turbo Transfer System (Bio-Rad, Hercules, CA), followed by blocking for 1 h with 5% nonfat milk in Tris-buffered saline-Tween 20 buffer and probing with antibodies against Strep Tag (SAB2702215, Sigma-Aldrich), γ-catenin (sc-514115, Santa Cruz Biotechnology) and GAPDH (A00084, GenScript) (Supplementary Table 6).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>γ-catenin</div><div>suggested: (Immunological Sciences Cat# AB-90215, RRID:AB_2892157)</div></div><div style="margin-bottom:8px"><div>sc-514115, Santa Cruz Biotechnology</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>GAPDH</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The washed membranes were incubated with secondary antibody StarBright Blue 700 Goat anti-mouse IgG (Bio-rad).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Coverslips were washed three times with PBS before secondary anti-mouse antibodies incubation (1:1000 dilution).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For staining, cells were resuspended in PBS 0.1% BSA 0.01% NaN3 containing the monoclonal antibody PE mouse anti-human CD54 (BD Pharmingen) or its isotype control at a concentration of 1/500.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human CD54</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The primary anti-ZO-1 antibody (ref. 61-7300, Invitrogen) was diluted at 1:100 in PBS containing 1% BSA and incubated for 3 h at RT.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-ZO-1</div><div>suggested: (Innovative Research Cat# 61-7300, RRID:AB_138452)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The secondary antibody (anti-rabbit IgG-FITC, ref. 9887, Sigma) was diluted 1:200 in PBS and incubated for 1 h at RT.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: (Sigma-Aldrich Cat# F9887, RRID:AB_259816)</div></div><div style="margin-bottom:8px"><div>anti-rabbit IgG-FITC</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, VSV-G pseudotyped ORF7a or ORF7b lentivirus was produced by co-transfection of HEK293T cells with the pLVX-ORF7a or pLVX-ORF7b plasmids, pCMV-Gag-Pol and pCMV-VSV-G using Lipofectamine 2000 Reagent (Thermo Fisher Scientific) as per manufacturer instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">RNA isolation and sequencing: WT A549, A549-ORF7a and A549-ORF7b cells were seeded (3×10E5) in 6-well plates and lysed using RLT buffer for RNA isolation (RNeasy mini kit, Qiagen).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>A549-ORF7b</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After 24 h incubation, A549 cells were labeled with calcein-AM.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>A549</div><div>suggested: NCI-DTP Cat# A549, RRID:CVCL_0023)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Lentivirus production, cell culture and transduction: ORF7a or ORF7b coding sequences (codon-optimized for mammalian expression) were cloned into pLVX-EF1α-IRES-Puro Cloning and Expression Lentivector (System Biosciences) to generate pseudotyped lentiviral particles encoding the ORF7a or ORF7b accessory proteins of SARS-CoV-2 (Wuhan-Hu-1 isolate) at the CNIC (Centro Nacional de Investigaciones Cardiovasculares) Viral Vector Unit (ViVU).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLVX-EF1α-IRES-Puro</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, VSV-G pseudotyped ORF7a or ORF7b lentivirus was produced by co-transfection of HEK293T cells with the pLVX-ORF7a or pLVX-ORF7b plasmids, pCMV-Gag-Pol and pCMV-VSV-G using Lipofectamine 2000 Reagent (Thermo Fisher Scientific) as per manufacturer instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLVX-ORF7a</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pLVX-ORF7b</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pCMV-Gag-Pol</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pCMV-VSV-G</div><div>suggested: RRID:Addgene_8454)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Raw counts were transformed with the vst function in the DESeq2 package (Love et al., 2014) of the R software version 3.6.3 (R Core Team, 2020), and subsequent PCA was performed with the prcomp function.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>DESeq2</div><div>suggested: (DESeq, RRID:SCR_000154)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Finally, the PCA graph was made with Graphad Prism software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Graphad Prism</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All sequencing data sets are available in the NCBI BioProject database under accession number PRJNA841835.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BioProject</div><div>suggested: (NCBI BioProject, RRID:SCR_004801)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Enrichment analyses were carried out by selecting the genomics sources: KEGG Pathway, GO Biological Processes, Reactome Gene Sets, Canonical Pathways, and CORUM.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GO Biological</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Relative expression results were calculated using GenEx6 Pro software (MultiD-Göteborg, Sweden), based on the Cq values obtained.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GenEx6 Pro</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For these experiments, a CytoFLEX flow cytometer (Beckman Coulter) was used and data was analyzed using FlowJo v10 (BD Biosciences).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.05.27.493767: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The pGEX-6P-1-nsp5 (or Mpro) plasmid was a kind gift from Dr. Martin Walsh, Diamond Light Source. pGBWm4046979 (coding for full-length nsp7, NCBI Reference Sequence: YP_009725303.1, codon-optimized, with an initial Met and a cleavable C- terminal TEV 6x-His tag was a gift from Ginkgo Bioworks (Addgene plasmid 145611; http://n2t.net/ addgene:145611; RRID: Addgene_145611).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pGEX-6P-1-nsp5</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pGBWm4046979</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_145611)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pGBWm4046852 (coding for full- length nsp8, NCBI Reference Sequence: YP_009725304.1, codon-optimized, with an initial Met and a cleavable C-terminal TEV 6x-His tag) was a gift from Ginkgo Bioworks (Addgene plasmid 145584; http://n2t.net/ addgene:145584; RRID: Addgene_145584).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pGBWm4046852</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_145584)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The gene encoding SARS-CoV-2 nsp10 was cloned into the pGEX-6P-1 vector to generate an expression construct containing an N-terminal GST tag and an HRV 3C protease cleavage site (GST3CNsp10).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pGEX-6P-1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids for codon-optimized pET-28a- His6-nsp7-8 and pET-28a-His6-nsp7-11 (with an HRV 3C protease cleavage site between the 6x- His tag and the coding sequence) were obtained from GenScript (Piscataway, NJ).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET-28a-</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pET-28a-His6-nsp7-11</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The pGEX- 6P-1-nsp5 expression plasmid was transformed into E. coli Rosetta gami competent cells and cultured in LB media at 37 °C with 100 μg/mL ampicillin.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pGEX-</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>6P-1-nsp5</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The gene encoding SARS-CoV-2 nsp10 was cloned into the pGEX-6P-1 vector to generate an expression construct containing an N-terminal GST tag and an HRV 3C protease cleavage site (GST3CNsp10).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2</div><div>suggested: (Active Motif Cat# 91351, RRID:AB_2847848)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The gel band intensity for nsp7-11 was calculated using ImageJ software (https://imagej.nih.gov/ij/index.html) and plotted against the concentration of binders using the GraphPad Prism Version 9.3.1 (GraphPad Software, La Jolla California USA, www.graphpad.com).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Crosslink spectral matches found in Proteome Discoverer were exported and converted to sequence spectrum list format using Excel (Microsoft).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Proteome Discoverer</div><div>suggested: (Proteome Discoverer, RRID:SCR_014477)</div></div><div style="margin-bottom:8px"><div>Excel</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The data was reduced using BioXTAS RAW 2.0.3 (81).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BioXTAS</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">They are also provided in the SM as PyMOL sessions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PyMOL</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
  4. May 2022
    1. ever attempted commenced operations. Now that the telescope has been successfully deployed in its unique position in space, its advanced instruments will be able to gather data on questions that scientists once could only dream of answering. Is there life on other planets?

      Yeah!

    1. SciScore for 10.1101/2022.05.27.493400: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The mammalian cell line HEK 293/T served as host for recombinant production of the glycoprotein.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK 293/T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">, pCAGGS based, NCBI accession number: LT727518) was chosen for the mammalian expression system.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAGGS</div><div>suggested: RRID:Addgene_127347)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The amplicon was digested with the respective restriction enzymes (ThermoFisher) and ligated with T4 Ligase (ThermoFisher) into the linearised πα-SHP-H vector to clone πα-SHP-H–Sgene with an N-terminal octahistidin tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>πα-SHP-H</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Raw data (dot mean fluorescence intensity) was processed by GraphPad Prism 9 (GraphPad Software, USA)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. A shiny tag is defined by: A name such as span, div, h1 …, accessed with tag$name. Some attributes, which can be accessed with tag$attribs. Children, which can be accessed with tag$children. A class, namely shiny.tag.

      Shiny tags are stored in R as a list with three name values: name ( name of tag), attribute (list of key pairs), children (other html components inside), class usually R object class shiny.tag

    1. SciScore for 10.1101/2022.05.27.493682: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Euthanasia Agents: At the end point of the experiment, all remaining animals in the monoclonal antibody-administered group received an overdose of isoflurane and were humanely euthanized.<br>IACUC: Ethics statement: This study was approved by the Experimental Animal Welfare and Ethical Review Board of Wuhan Institute of Biological Products Co.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Male K18-hACE2 mice (6–8 weeks old, purchased from GemPharmatech Co., Ltd. Company.) were randomly distributed into groups (n = 3–6 mice per group).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">Male K18-hACE2 mice (6–8 weeks old, purchased from GemPharmatech Co., Ltd. Company.) were randomly distributed into groups (n = 3–6 mice per group).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then cells were stained with anti-mouse IgG Taxes red conjugated antibody and anti-human IgG FITC-conjugated antibody (Sigma, USA) for another 30 min then analyzed by FACS Aria II (BD, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody Binding Kinetics Measured by SPR: The binding kinetics of mAbs to SARS-CoV-2 Delta-RBD or Omicron-RBD monomer were analyzed using SPR (Biacore 8K; GE Healthcare).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Delta-RBD</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells, Viruses and Proteins: Cell lines (HEK293T and Vero E6 cells) were initially acquired from the American Type Culture Collection (ATCC; USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: RRID:CVCL_XD71)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293T-hACE2-cells were generated via the overexpression of the human ACE2 receptor in HEK293T cells and were used in the neutralization assays of pseudoviruses.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T-hACE2-cells</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then mixtures were added to 2.5 × 105 HEK293T cells expressing ACE2 and incubated at 4 °C for another hour.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: RRID:CVCL_HA71)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293-hACE2 cells (2.5 × 104 cells/100μL per well) were then added into the mixture and incubated at 37 °C in a humidified atmosphere with 5% CO2 for 23 h to 25 h.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293-hACE2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Male K18-hACE2 mice (6–8 weeks old, purchased from GemPharmatech Co., Ltd. Company.) were randomly distributed into groups (n = 3–6 mice per group).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>K18-hACE2</div><div>suggested: RRID:IMSR_GPT:T037657)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The SARS-CoV-2 Spike ectodomain (1-1208) with a C-terminal Strep tag for purification and a foldon tag for trimerization was inserted into the pFastBac-Dual vector (Invitrogen) and was expressed using Bac-to-Bac baculovirus system (Invitrogen).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pFastBac-Dual</div><div>suggested: RRID:Addgene_137166)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cDNA encoding SARS-CoV-2 Omicron Spike was synthesized (GenBank ID: ULC25168.1) and cloned into the pCAG vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAG</div><div>suggested: RRID:Addgene_74288)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All of these data were analyzed using Flow Jo.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Flow Jo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All statistical analysis was performed using GraphPad Prism 8.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Coot v.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Figures were generated using PyMOL 2.0.779</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PyMOL</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.05.26.493517: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Spike proteins were captured through their C-terminal His-tag over an anti-His antibody surface.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-His</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For each residue within the RBD, the frequency of antibody recognition was calculated as the number of contact antibodies32.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>antibodies32</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The structures of antibody-spike complexes for modeling were also obtained from PDB (7L5B (2-15), 6XDG (REGN10933), and 7KMG (LY-CoV555)).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>REGN10933</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Heavy chain variable (VH) and light chain variable (VL) genes for each antibody were synthesized (GenScript), then transfected into Expi293 cells (Thermo Fisher Scientific), and purified from the supernatant by affinity purification using rProtein A Sepharose (GE).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Expi293</div><div>suggested: RRID:CVCL_D615)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A14527); Vero-E6 cells were obtained from the ATCC (</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero-E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">CRL-1586); HEK293T cells were obtained from the ATCC (CRL-3216).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Neutralization curves and IC50 values were derived by fitting a nonlinear five-parameter dose–response curve to the data in GraphPad Prism v.9.2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">PyMOL v.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PyMOL</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. Our build bots do it by parsing your HTML files directly at deploy time, so there’s no need for you to make an API call or include extra JavaScript on your site. # HTML forms Code an HTML form into any page on your site, add data-netlify="true" or a netlify attribute to the <form> tag

      gross

    1. SciScore for 10.1101/2022.05.26.493539: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To measure the surface expression level of S protein, effector cells were stained with rabbit anti-SARS-CoV-2 S S1/S2 polyclonal antibody (Thermo Fisher Scientific, Cat# PA5-112048, 1:100)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 S</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Normal rabbit IgG (SouthernBiotech, Cat# 0111-01, 1:100) was used as negative controls, and APC-conjugated goat anti-rabbit IgG polyclonal antibody (Jackson ImmunoResearch, Cat# 111-136-144, 1:50) was used as a secondary antibody.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit IgG</div><div>suggested: (Jackson ImmunoResearch Labs Cat# 111-136-144, RRID:AB_2337987)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The deparaffinized sections were exposed to EnVision FLEX target retrieval solution high pH (Agilent, Cat# K8004) for 20 minutes at 97°C to activate, and mouse anti-SARS-CoV-2 N monoclonal antibody (clone 1035111, R&D systems, Cat# MAB10474-SP, 1:400) was used as a primary antibody.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 N</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell culture: HEK293T cells (a human embryonic kidney cell line; ATCC, CRL-3216)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">, HEK293 cells (a human embryonic kidney cell line; ATCC, CRL-1573) and HOS-ACE2/TMPRSS2 cells (HOS cells stably expressing human ACE2 and TMPRSS2) (Ferreira et al., 2021; Ozono et al., 2021) were maintained in DMEM (high glucose) (Sigma-Aldrich, Cat# 6429-500ML) containing 10% fetal bovine serum (FBS, Sigma-Aldrich Cat# 172012-500ML), and 1% penicillin-streptomycin (PS) (Sigma-Aldrich, Cat# P4333-100ML).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HOS-ACE2/TMPRSS2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293-ACE2/TMPRSS2 cells (HEK293 cells stably expressing human ACE2 and TMPRSS2) (Motozono et al., 2021) was maintained in DMEM (high glucose) containing 10% FBS, 1 µg/ml puromycin, 200 ng/ml hygromycin (Nacalai Tesque, Cat# 09287-84) and 1% PS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293-ACE2/TMPRSS2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HEK293</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293-C34 cells (IFNAR1 KO HEK293 cells expressing human ACE2 and TMPRSS2 by doxycycline treatment) (Torii et al., 2021) were maintained in DMEM (high glucose) containing 10% FBS, 10 μg/ml blasticidin (InvivoGen, Cat# ant-bl-1) and 1% PS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293-C34</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Vero cells [an African green monkey (Chlorocebus sabaeus) kidney cell line; JCRB Cell Bank, JCRB0111] were maintained in Eagle’s minimum essential medium (EMEM) (Sigma-Aldrich, Cat# M4655-500ML) containing 10% FBS and 1% PS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">VeroE6/TMPRSS2 cells (VeroE6 cells stably expressing human TMPRSS2; JCRB Cell Bank, JCRB1819) (Matsuyama et al., 2020) were maintained in DMEM (low glucose) (Wako, Cat# 041-29775) containing 10% FBS, G418 (1 mg/ml; Nacalai Tesque, Cat# G8168-10ML) and 1% PS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VeroE6</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Calu-3 cells (a human lung epithelial cell line; ATCC, HTB-55) were maintained in EMEM (Sigma-Aldrich, Cat# M4655-500ML) containing 20% FBS and 1% PS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu-3</div><div>suggested: ATCC Cat# HTB-55, RRID:CVCL_0609)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Calu-3/DSP1-7 cells (Calu-3 cells stably expressing DSP1-7) (Yamamoto et al., 2020) were maintained in EMEM (Wako, Cat# 056-08385) containing 20% FBS and 1% PS. 293S GnTI(-) cells (HEK293S cells lacking N-acetylglucosaminyltransferase (Kubota et al., 2016) were maintained in DMEM (Nacalai tesque, #08458-16 containing 2% FBS without PS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293S</div><div>suggested: RRID:CVCL_A784)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, the amount of pseudoviruses prepared was quantified by the HiBiT assay using Nano Glo HiBiT lytic detection system (Promega,Cat# N3040) as previously described (Ozono et al., 2021; Ozono et al., 2020), and the same amount of pseudoviruses (normalized to the HiBiT value, which indicates the amount of p24 HIV-1 antigen) was inoculated into HOS-ACE2/TMPRSS2 cells, HEK293-ACE2 cells or HEK293-ACE2/TMPRSS2 and viral infectivity was measured as described above (see “Neutralization assay” section).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293-ACE2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">On day 3 (24 hours posttransfection), 16,000 effector cells were detached and reseeded into 96-well black plates (PerkinElmer, Cat# 6005225), and target cells (VeroE6/TMPRSS2 or Calu-3/DSP1-7 cells) were reseeded at a density of 1,000,000 cells/2 ml/well in 6-well plates.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu-3/DSP1-7</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 infection: One day before infection, Vero cells (10,000 cells) and VeroE6/TMPRSS2 cells (10,000 cells) were seeded into a 96-well plate.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VeroE6/TMPRSS2</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Preparation of mouse sera: BALB/c mice (female, 7 weeks old) were immunized with 1 μg SARS-CoV-2 BA.2 RBD protein in 50% AddaVax (Invivogen, Cat# vac-adx-10) at day 0 and 14.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BALB/c</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The resulting PCR fragment was digested with KpnI and NotI and inserted into the corresponding site of the pCAGGS vector (Niwa et al., 1991).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAGGS</div><div>suggested: RRID:Addgene_127347)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">2 S RBD (residues 322-536) was cloned into the expression vector pHLsec containing the N-terminal secretion signal sequence and the C-terminal His6-tag sequence (Aricescu et al., 2006).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pHLsec</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">kit (Roche, Cat# KK2601) and assembled in vivo by yeast [Saccharomyces cerevisiae strain EBY100 (ATCC, MYA-4941)] homologous recombination with pJYDC1 plasmid (Addgene, Cat# 162458) as previously described (Dejnirattisai et al., 2022; Kimura et al., 2022a; Kimura et al., 2022b; Motozono et al., 2021; Yamasoba et al., 2022a; Zahradnik et al., 2021a)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pJYDC1</div><div>suggested: RRID:Addgene_162458)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To prepare effector cells, HEK293 cells were cotransfected with the S-expression plasmids (500 ng) and pDSP8-11 (500 ng) using PEI Max (Polysciences, Cat# 24765-1).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pDSP8-11</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To prepare target cells, HEK293 and HEK293-ACE2/TMPRSS2 cells were transfected with pDSP1-7 (500 ng) (Kondo et al., 2011).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pDSP1-7</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sequencing reads were trimmed using fastp v0.21.0 (Chen et al., 2018) and subsequently mapped to the viral genome sequences of a lineage A isolate (strain WK-521; GISAID ID: EPI_ISL_408667) (Matsuyama et al., 2020) using BWA-MEM v0.7.17 (Li and Durbin, 2009).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BWA-MEM</div><div>suggested: (Sniffles, RRID:SCR_017619)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Variant calling, filtering, and annotation were performed using SAMtools v1.9 (Li et al., 2009) and snpEff v5.0e (Cingolani et al., 2012).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SAMtools</div><div>suggested: (SAMTOOLS, RRID:SCR_002105)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The viral genome sequences were mapped to the reference sequence of Wuhan-Hu-1 (GenBank accession number: NC_045512.2) using Minimap2 v2.17 (Li, 2018) and subsequently converted to a multiple sequence alignment according to the GISAID phylogenetic analysis pipeline (https://github.com/roblanf/sarscov2phylo).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Minimap2</div><div>suggested: (Minimap2, RRID:SCR_018550)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Tree reconstruction was performed by RAxML v8.2.12 (Stamatakis, 2014) under the GTRCAT substitution model.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RAxML</div><div>suggested: (RAxML, RRID:SCR_006086)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Parameter estimation was performed via the MCMC approach implemented in CmdStan v2.28.1 (https://mc-stan.org) with CmdStanr v0.4.0 (https://mc-stan.org/cmdstanr/).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CmdStan</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>https://mc-stan.org</div><div>suggested: (Stan, RRID:SCR_018459)</div></div><div style="margin-bottom:8px"><div>CmdStanr</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The assay of each serum was performed in triplicate, and the 50% neutralization titer (NT50) was calculated using Prism 9 software v9.1.1 (GraphPad Software).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">RBD expression and ACE2 signal were recorded by using a FACS S3e cell sorter device (Bio-Rad), background binding signals were subtracted and data were fitted to a standard noncooperative Hill equation by nonlinear least-squares regression using Python v3.7 (https://www.python.org) as previously described (Kimura et al., 2022a; Kimura et al., 2022b; Motozono et al., 2021; Yamasoba et al., 2022a; Zahradnik et al., 2021b).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Python</div><div>suggested: (IPython, RRID:SCR_001658)</div></div><div style="margin-bottom:8px"><div>https://www.python.org</div><div>suggested: (CVXOPT - Python Software for Convex Optimization, RRID:SCR_002918)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Surface expression level of S proteins (Figures 3C and S2B) was measured using FACS Canto II (BD Biosciences) and the data were analyzed using FlowJo software v10.7.1 (BD Biosciences).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The size of syncytium (GFP-positive area) was measured using Fiji software v2.2.0 (ImageJ) as previously described (Suzuki et al., 2022; Yamasoba et al., 2022a).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Fiji</div><div>suggested: (Fiji, RRID:SCR_002285)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The stained cells were washed with tap water and dried, and the size of plaques was measured using Fiji software v2.2.0 (ImageJ).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Images were incorporated as virtual slide by NDP.scan software v3.2.4 (Hamamatsu Photonics).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>NDP.scan</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">These analyses were performed in R v4.1.2 (https://www.r-project.org/).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>https://www.r-project.org/</div><div>suggested: (R Project for Statistical Computing, RRID:SCR_001905)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your code and data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • No funding statement was detected.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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

      Learn more at Review Commons


      Referee #3

      Evidence, reproducibility and clarity

      In this manuscript, the authors address the important topic of post-transcriptional gene regulation using the larval nervous system in Drosophila. They utilize a novel approach taking advantage of existing protein trap library, which permits use of the same smFISH probe to detect an array of 200 RNAs and visualize their corresponding protein expression. Furthermore, the authors developed a computational pipeline to visualize and analyze the resulting data, which should enhance the application of this method by other researchers. A major strength of the data comes from the analysis of multiple cell types in distinct compartments of the nervous system, cell types (neuron, glia, neuroblast), and subcellular domains. From the cumulative data, the authors are able to describe several interesting observations relating to cell-specific post-transcriptional regulation, regulation within a central-neuroblast lineage and glial post-transcriptional regulation, among others.

      However, in spite of these strengths, there are several concerns related to the organization and interpretation of the manuscript that the authors should address in order to improve the manuscript:

      General concerns:

      1. The approach relies on gene traps that often fail to be made homozygous, presumably due to deleterious function of the YFP insert. This is an obvious limitation of the study, which the authors address, but do so insufficiently by only analyzing a single case Dlg1. The authors should report how many of the 200 YFP-traps can produce viable homozygous animals, whether phenotypes can be observed, and any other relevant information to assess the functional properties of the tagged genes.
      2. The term "discordant" is used for non-congruous RNA/Protein levels in soma and distal processes, and sometimes the two are analyzed in the same figure (e.g Fig 3A). When it is stated that 98% of genes are discordant, this is an over-simplification as what the authors describe as "discordant" is expected to occur frequently in the distal process, but less often in the soma (which is what the authors find when presenting the data for individual compartments - Fig 3B-C). This is confusing because the observation means completely different things in the two compartments, though both are interesting to describe. These analyses, and their interpretation, should be kept separate.
      3. There is not enough emphasis placed on the cell-type specific regulation of RNAs. There are very few studies that have investigated how localization of individual RNAs changes in different cell types or regions of the nervous system, and the authors find that this is quite prevalent. Therefore, the rather superficial analysis of these data fails to take advantage of a major strength of the data. For example, for the discordant genes that differ in neuropil localization between different regions of the CNS, what types of molecules do they encode, what is their function in neurons (if known), and why might they be required locally in one region of the CNS but not the other?
      4. The authors conclude that mRNA and protein co-localization in glia processes shows that mRNA localization makes a major contribution of the proteome in processes. However, there is not enough evidence for such conclusion since neither translation of these mRNAs nor lack of protein trafficking from the somas was shown.
      5. An important caveat of this technique that should be discussed is the lack of knowledge about the translation of these mRNAs, if the mRNA that is being detected is the same as the one that is translated. While the authors emphasize the discordance between mRNA and protein localization, it is not possible to know whether these mRNAs are being translated where they are found, e.g. soma vs neuropil. Moreover, there are many examples (e.g. BDNF) where the isoform influences the subcellular localization of the mRNA. There is no way of studying the isoforms here, and we could be looking for a different mRNA isoform localized to a specific compartment compared to the protein. These points must be discussed.

      Minor suggestions:

      • The authors should identify GO terms to understand what types of molecules are subjected to RNA regulation. They provide a supplementary table for all genes, but it would be useful to have a chart showing the proportion of different GO terms represented in the overall gene set, genes that show cell-specific regulation, genes that show neuron vs glia specific regulation, etc.
      • "However, post-transcriptional regulation can also manifest itself within a cell, so that a protein is localised to a distinct site from the mRNA that encodes it". While subcellular RNA localization may represent a regulatory layer, I do not agree that proteins that function in the cell at a different location than their translation site represents regulation per se. Many such cases exist for proteins that are trafficked!
      • "The majority of individual puncta appearing in the dlg1::YFP line (51% in the brain, 64% in larval muscles". Why is the agreement between YFP and endogenous FISH so low? Do many individual RNAs fail to hybridize? This should be discussed.
      • "However, one gene, indy, is highly transcribed in neuroblasts and a single ganglion mother cell before it is rapidly shut off (Figure S1A)". This figure does not exist. Where are the data?
      • The authors should be consistent about calling perineurial or perineural glia (both correct) in their images and text.
      • "We only observe a minority of localised axonal mRNAs that lack the protein they encode at the axon extremities, in contrast to our findings in the mushroom body, optic lobe, and ventral nerve cord neuropils" These results are not contrasted, as in all neuropils the minority of localized mRNAs are those lacking their corresponding proteins. For example, 9% in NMJ vs 7.5% in OL neuropil according to Fig. 1B. What is conflicting with the conclusion?
      • "These results suggest that motor axons are more selective than the other neuronal extensions in the mRNAs that are transported over their very long distances from the soma to the neuromuscular synapse" The current literature says that the same mechanism (cis-elements) is used to transport mRNAs to subcellular compartments, which would be inconsistent with the idea of motor axons being "more selective" than other neurons for the same mRNA, but just a result of fewer mRNAs being found in motor neurons: 34.% of the mRNAs are found in motor neurons soma vs 83% in OL soma, 86.5% in VNC soma, and 70.5% in MB soma. To get to this conclusion, the authors should show that mRNAs previously found in the neuronal extensions of other neurons are not found in the axons of motor neurons but are still expressed in thesir somas. They might want to suggest different RBPs involved in the transport or discussing the very long distance they need to travel which can influence their detection in the tips. Figures
      • Figure 1. Experimental approach summary
        • Some colors do not show well and should be changed, e.g: grey in Fig. 1A, and Fig. 1B probe sites indicated in light blue and pink within the introns of dlg1.
        • Fig. 1E': There appears to be a large discrepancy in co-detection % for CNS and muscle in the graph judging by the size of circles, yet in the text, it is stated that there is average of 51% and 64% in the two, respectively. I don't see any green circles with over 25% agreement in the graph. Are the colors correct here?
        • Fig. 1D-I: It's difficult to identify where the zoomed panels come from. E has its own square (indicating zoom in E'). Please make this square dashed or a different color in E so it is clear F and G do not come from there.
        • Comparing Fig. 1F vs K: Why does there appear to be so much more dlg1 mRNA in the YFP-tag condition? If this is due to selection of imaging area, please choose a more similar region to image so the RNA levels are comparable. Otherwise it indicates the YFP-tag line has more RNA expression, which is likely not the case.
      • Figure 2. Analysis pipeline overview
        • The lines for the first two zoomed panels are switched: The optic lobe is going to VNC and vice-versa.
      • Figure 3. Overall summary of results
        • Figure 3A: Soma/Neuropil/muscle should be separate or at least ordered such that they are next to each other to facilitate direct comparison of genes in the same region of the cell in neurons from different CNS areas. Why are glia not included in this summary? A third color should be used to indicate when there is neither mRNA nor protein expression.
        • "Compiling all the information together shows that there are that 196/200 or 98% of the genes show discordance between RNA and protein expression" However, 5 genes shown in Fig. 3A do not show "discordance": CG9650, cup, Lasb, rg, and vsg!!
      • Figure 4. Neuroblast lineage analysis
        • Is clustering around the NB sufficient to determine lineage relationship? There seems to be other neurons around the NB.
        • More examples should be shown for the post-transcriptional category, as it is the most interesting category, and there are many different possible outcomes. Are there cases of transcriptional control and post-transcriptional regulation? Are there cases where the youngest neurons (closer to the NB) in the progeny are expressing the protein while the oldest are not? If not, could this be an artifact from a slow translation and the protein being detected only after building up in the cell? Top1 protein (Fig. 4D) seems to be less expressed in the youngest neurons.
        • "The transcription rate of these genes, as indicated by the relative intensity of smFISH nuclear transcription foci, is similar across the neuroblast lineage, however protein signal is only detectable in a minority of the progeny cells (Figure 4E)". Many nuclei lack clear large spots, but have small spots indicative of RNA; how is this interpreted? Do they lack transcription, or is this due failure of the smFISH to capture all transcription sites? Were transcripts actually counted to assess cell-specific differences? This should be possible with smFISH
      • Figure 5. RNA synaptic localization
        • A have global analysis comparison of all neuropil areas would be welcome in this figure.
        • "Surprisingly, another 59 transcripts are present at synapses without detectable levels of protein (Figure 5E-H)" This text does not correspond to Fig 5E-H but 5I-L. Where is the text about 5E-H?
        • For Fig. 5J and 5N RNA appears scattered regularly throughout the entire panel area. How sure are the authors that this is not due to poor signal/noise? For example, perhaps too much probe being used for these targets.
        • Fig. 5R is not cited in the text.
      • Figure 6. RNA localization in glia
        • For Fig. 6B-G it is hard to tell if there is any overlap of the RNA and Glia. Maybe show multiple zoomed-in merged images and/or highlight the structures with lines that are present in all panels.
        • For Fig. 6L-O: How reproducible is this small amount of RNA puncta in the NMJ glia? Is this possibly biologically important?
        • Why do cartoons labelling subnuclear/perinuclear glia in Fig.6 and Fig.S6 show different localization?
        • The cartoons seem to extrapolate from the data: While in Fig 6B-D, we see neither the big bright spot of transcription in the glial nucleus nor as many transcripts in the neuropil, they are both present in the cartoon. In Fig. 6E-G there is no indication of cortical glia soma nor the transcription spot only in glia nuclei.
        • "To assess glial localisation for the 200 genes of interest, we used a pan-glial gal4 driving a membrane mCherry marker (repo-GAL4>UAS-mcd8-mCherry) to learn the expression pattern of all glial cells, and then classified the pattern in the YFP lines (without the marker) based on knowledge of that expression pattern. We validated this approach by combining the RFP marker" Did the authors use mCherry or RFP for these experiments? Also, the previous sentence is redundant.
      • Figure 7. RNA localization at neuromuscular synapse
        • RNA for these genes seems far too spread throughout the muscle to draw any conclusions
        • Also with so many RNAs distributed in the muscle, specific localization of RNA molecule to the precise PSD would have no conceivable benefit
        • I suggest drawing lines around the protein expression to facilitate visualization of the mRNA localization for panels B, F and J. It is especially hard to conclude anything from panels B and F.
        • Light grey with white dots is hard to see in the cartoons
      • Figure 8. Role of khc and activity in sgg localization
        • Presumably there is a huge number of developmental problems associated with this mutant that could cause decrease in sgg localization
        • If the authors include this, then they should characterize the mutant NMJs: what is the change in size, synapse number, etc..
        • Is there more sgg accumulated in soma as a result of less transport? Is sgg being expressed at the same level?
        • Fig. 8F-H: Why is Dlg1 accumulated in the entire axon, not just the presume synapse?
        • Fig. 8J: Why is sgg signal occurring in circles disconnected from the main axon? The authors should show a different image

      Significance

      This is a significant and complex paper that contributes with novel tools to an important issue

    1. indie thinkers are making a living from conducting online research; tools are becoming more integrated; apps encourage active creation over passive collection of knowledge. This 40-page report reviews the current state of the

      indie thinkers

    1. SciScore for 10.1101/2022.05.23.493138: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">Polarization Anisotropy: Fluorescent RNA was ordered from IDT as a 10-nt degenerate sequence (random nucleotide at every position) with a 3’-FAM modification.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, a codon-optimized synthetic DNA (Integrated DNA Technologies, IDT) was inserted into a pET28 expression vector by Gibson assembly, fused to DNA encoding an N-terminal 6xHis-SUMO tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET28</div><div>suggested: RRID:Addgene_21766)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The template for in vitro transcription of 5’-600 RNA was a synthetic DNA (IDT), inserted by Gibson assembly into a pUC18 vector with a 5’ T7 promoter sequence.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pUC18</div><div>suggested: RRID:Addgene_50004)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data from three independent N protein titrations were fit to a one-site binding curve using GraphPad Prism to determine KD.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.05.22.492693: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After blocking with 3% albumin (Sigma-Aldrich) and primary antibody incubation RAGE (ab3611, Abcam), ACE2 (XXX), ADAM17 (ab2051, Abcam)), TMPRSS2 (ab109131, Abcam), the membranes were incubated with an anti-rabbit peroxidase-conjugated secondary antibody (GE healthcare).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>ADAM17</div><div>suggested: (Abcam Cat# ab2051, RRID:AB_302796)</div></div><div style="margin-bottom:8px"><div>TMPRSS2</div><div>suggested: (Abcam Cat# ab109131, RRID:AB_10863728)</div></div><div style="margin-bottom:8px"><div>anti-rabbit peroxidase-conjugated secondary</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">500 μg of protein lysate was incubated with Anti-6X His tag® antibody [HIS.H8] (ab18184, Abcam) overnight at 4°C, anti-Mouse IgG (Invitrogen) was used as isotype control.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-6X</div><div>suggested: (Abcam Cat# ab18184, RRID:AB_444306)</div></div><div style="margin-bottom:8px"><div>anti-Mouse IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">P4417-100TAB-Sigma-Aldrich) plus 1% Bovine Serum Albumin (BSA) (Cat.A9647-500G-Sigma-Aldrich) and 0,02% NP-40 alternative (Cat.492016-100ML) for 1h at room temperature prior to overnight incubation at 4°C with primary antibody 1:100 (6xHisTag clone#HIS.H8 Cat.ab18184-Abcam or SARS-CoV-2 spike polyclonal antibody, GeneTex).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>6xHisTag</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells were collected and stained using primary RAGE antibody 1:100 (PA5-24787, Thermo Scientific) for FACS analysis.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RAGE</div><div>suggested: (Thermo Fisher Scientific Cat# PA5-24787, RRID:AB_2542287)</div></div><div style="margin-bottom:8px"><div>PA5-24787</div><div>suggested: (Thermo Fisher Scientific Cat# PA5-24787, RRID:AB_2542287)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">1 × 105 THP-1 cells were seeded on a 24-well plate in their culture medium.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP-1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">THP1 and Monocytes infection with SARS-CoV-2: THP1 cells were plated at 5×105 cell/ml in 48-well plates in 200 μl of RPMI-1640 supplemented with 1% fetal bovine serum (FBS) (Euroclone).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell culture supernatants were collected 24, 48, 72 and 144 h post-infection and stored at – 80°C until the determination of the viral titers by a plaque-forming assay in Vero cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The following day, cells were pretreated or not with 2μM Azeliragon (Cat.S6415-Selleckchem) for 30 minutes before adding 100 ng/mL of Sars-CoV-2 spike protein (RBD, HisTag) (Cat. ZO3483-1-GenScript) or infected using Heat-inactivated SARS-CoV-2 (VR-1986HK, ATCC) at 4 TCID50/mL for 2h at 37°C 5%CO2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VR-1986HK</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sequencing: Different library types were pooled at different ratios based on their targeted reads per cell and the nanomolarity of the library pools was confirmed using the Agilent Bioanalyzer 2100.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Agilent Bioanalyzer</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Separately for the two selected categories of disease severity (mild vs severe/critical), the pseudo-bulk counts were then fitted with a generalised linear model using the EdgeR package, to identify those genes characterised by a well-defined decreasing or increasing trend of the expression over the sample time-points.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>EdgeR</div><div>suggested: (edgeR, RRID:SCR_012802)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Among these sets, the GO:0050786 genelist was then expanded using the Cytoscape ‘stringApp’ (81) in order to identify among the nearest neighbours with confidence score > 0.7 the ones showing the highest absolute FC values in Myeloid cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Cytoscape</div><div>suggested: (Cytoscape, RRID:SCR_003032)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The GSEA has been done with the clusterProfiler library (82, 83), using gene lists ranked by the FDR of the differential analysis and the sign of the logFC.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GSEA</div><div>suggested: (SeqGSEA, RRID:SCR_005724)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The gating strategy and the relative analysis were performed with FlowJo software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your code and data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.05.21.492554: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Consent: A blood sample was taken following consent at least 14 days after symptom onset.<br>IRB: Sera from Beta, Gamma and Delta and BA.1 infected cases: Beta and Delta samples from UK infected cases were collected under the “Innate and adaptive immunity against SARS-CoV-2 in healthcare worker family and household members” protocol affiliated to the Gastro-intestinal illness in Oxford: COVID sub study discussed above and approved by the University of Oxford Central University Research Ethics Committee.<br>Field Sample Permit: The study was approved by the Human Research Ethics Committee of the University of the Witwatersrand (reference number 200313) and conducted in accordance with Good Clinical Practice guidelines.<br>IACUC: Gamma samples were provided by the International Reference Laboratory for Coronavirus at FIOCRUZ (WHO) as part of the national surveillance for coronavirus and had the approval of the FIOCRUZ ethical committee (CEP 4.128.241) to continuously receive and analyse samples of COVID-19 suspected cases for virological surveillance.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">The mean age of vaccinees was 37 years (range 22-66), 21 male and 35 female.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">AstraZeneca-Oxford vaccine study procedures and sample processing: Full details of the randomized controlled trial of ChAdOx1 nCoV-19 (AZD1222), were previously published (PMID: 33220855/PMID: 32702298).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">EXPERIMENTAL MODEL AND SUBJECT DETAILS: Bacterial Strains and Cell Culture: Vero (ATCC CCL-81) and VeroE6/TMPRSS2 cells were cultured at 37 °C in Dulbecco’s Modified Eagle medium (DMEM) high glucose (Sigma-Aldrich) supplemented with 10% fetal bovine serum (FBS), 2 mM GlutaMAX (Gibco, 35050061) and 100rnU/ml of penicillin– streptomycin.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>VeroE6/TMPRSS2</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293T (ATCC CRL- 11268) cells were cultured in DMEM high glucose (Sigma-Aldrich) supplemented with 10% FBS, 1% 100X Mem Neaa (Gibco) and 1% 100X L-Glutamine (Gibco) at 37 °C with 5% CO2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: ATCC Cat# CRL-11268, RRID:CVCL_1926)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The resulting S gene-carrying pcDNA3.1 was used for generating pseudoviral particles together with the lentiviral packaging vector and transfer vector encoding luciferase reporter.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The gene fragment was amplified with pNeoRBD333Omi_F (5’- GGTTGCGTAGCTGAAACCGGTCATCACCATCACCATCACACCAATCTGTGCCCTTTCGAC-3’) and pNeoRBD333_R (5’-GTGATGGTGGTGCTTGGTACCTTATTACTTCTTGCCGCACACGGTAGC-3’), and cloned into the pNeo vector (Supasa et al., 2021).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNeo</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To generate the BA.4/5 RBD construct containing a BAP- His tag, the gene fragment was amplified with RBD333_F (5’- GCGTAGCTGAAACCGGCACCAATCTGTGCCCTTTCGAC-3’) and RBD333_BAP_R (5’-GTCATTCAGCAAGCTCTTCTTGCCGCACACGGTAGC-3’), and cloned into the pOPINTTGneo-BAP vector (Huo et al., 2020a).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pOPINTTGneo-BAP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To express biotinylated RBDs, the RBD-BAP plasmid was co-transfected with pDisplay-BirA-ER (Addgene plasmid 20856; coding for an ER-localized biotin ligase), in the presence of 0.8 mM D-biotin (Sigma-Aldrich).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RBD-BAP</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pDisplay-BirA-ER</div><div>suggested: RRID:Addgene_20856)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sensorgrams were plotted using Prism9 (GraphPad).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The percentage reduction was calculated and IC50 determined using the probit program from the SPSS package.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SPSS</div><div>suggested: (SPSS, RRID:SCR_002865)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04324606</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Active, not recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">A Study of a Candidate COVID-19 Vaccine (COV001)</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04400838</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Active, not recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Investigating a Vaccine Against COVID-19</td></tr></table>


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.05.21.492920: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IACUC: , Radiation Safety, and Animal Care and Use Committees.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Male golden Syrian hamsters (7 to 8 weeks of age) were purchased from Envigo (Haslett, MI).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The wells were washed and then incubated with rabbit anti-ERα (1:2000, 1 h, RT) and horseradish-conjugated secondary antibody (1:2000, 1 h, RT) that were provided with the kit.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-ERα</div><div>suggested: (Santa Cruz Biotechnology Cat# sc-542, RRID:AB_631470)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cells were then incubated at 4°C overnight with 2 μg/ml each of anti-ERα(H222) rat IgG1 monoclonal antibody (mAb) (Santa Cruz Biotech, sc-5349, 1:100) and HA-probe (</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-ERα(H222</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>rat IgG1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Afterwards, the cells were washed 4 times with PBS + 0.1% Tween-20 (PBS-T) for 5 minutes and incubated at room temperature for 1 hour in the dark with a fluorescent secondary antibody mixture contaning mouse IgGk BP-CFL594 (Santa Cruz Biotech, sc-516178, 1:100) and anti-rat IgG AF488 (ThermoFisher Scientific, cat no. A-11006, 1:500).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rat IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then, cells were washed and were incubated with detector anti-BrdU antibody for 1 hour at RT.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-BrdU</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After the incubation cells were washed and incubated with the horseradish peroxidase conjugated goat anti-mouse antibody for 30 minutes at RT.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 50 μl of standard were added to standard wells and 40 μl of sample-to-sample wells and then added 10 μl of anti-TRAP antibody to sample wells and 50 μl of streptavidin-HRP to sample wells and standard wells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-TRAP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After 72 hours, cells were washed, fixed with 4% formaldehyde, permeabilized with 0.1% Triton X-100 in PBS and stained overnight at 4°C with ACE2 protein-specific antibody (Abcam Ab15348).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells were then incubated with anti-rabbit secondary antibody (Alexa Fluor 536 anti-rabbit, Invitrogen Life Technologies) for 1 hour at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sections were then incubated with cocktails of primary antibodies: rabbit anti-SARS-CoV-2 Spike Protein (1:100, Invitrogen, #MA5-36087) + rat anti-ERα H222 (1:100, Santa Cruz Biotechnology, #sc53492) overnight at 4°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 Spike Protein ( 1:100 , Invitrogen , #MA5-36087 )</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sections were then incubated with the primary antibodies rat anti-ERα H222(1:100, Santa Cruz Biotechnology, #sc53492), diluted in 1% normal goat serum (NGS), 4% BSA, 0.02% saponin in PB at 4°C overnight.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-ERα H222</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sections were rinsed and incubated overnight at 4°C in the secondary antibody Nanogold-Fab’ goat anti-rat-IgG (1:100</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rat-IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">On day one, slides were blocked with a peroxidase blocker (Bio SB Catalog No. BSB 0054), washed with an immunoDNA washer buffer (Bio SB, Catalog No. BSB 0150); then, incubated with 0.2 μg/mL of anti-SARS-CoV-2 spike glycoprotein antibody (abcam, Catalog No. ab272504) for 1 hour.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 spike glycoprotein</div><div>suggested: (Abcam Cat# ab272504, RRID:AB_2847845)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, MCF-7 nuclear extracts (5 μg; ab14860, Abcam) were treated with either S (0.01-300 nM; Acro Biosystems)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MCF-7</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Proliferation assays: MCF-7 and MDA-MB-23 cells were obtained from ATCC and growth in DMEM without phenol red, supplemented with 10% fetal bovine serum (FBS), penicillin/streptomycin at 37 °C in a 5% CO2 and 95% humidified atmosphere.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MDA-MB-23</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">TRAP activity by ELISA assay in RAW-OCs: RAW264.7 (murine macrophages ATCC, USA) were cultured as manufacturer’s protocol.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RAW264.7</div><div>suggested: CLS Cat# 400319/p462_RAW-2647, RRID:CVCL_0493)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">ACE2 expression in Calu-3 cells: Calu-3 cell line was obtained from ATCC and maintained in Eagle’s Minimum Essential Medium(EMEM; Lonza) supplemented with 10% fetal bovine serum (FBS), 1% L-glutamine and 1% penicillin/streptomycin solution at 37°C in a humidified atmosphere of 5% CO2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu-3</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The next day, cells in each well were transfected with 1.5 μl of ViaFect reagent (Promega, cat no. E498A) and 0.5 μg of empty pcDNA3.1 vector, or an expression vector for the wild-type (WT) SARS-CoV2 S with a C-terminal hemagglutinin (HA) epitope tag (pBOB-CAG-SARS-CoV2-S-HA) or the double mutant (R682S,R685S) SARS-CoV2 S with a C-terminal flag epitope tag (pCAGGS-SARS2-S-FKO).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div><div style="margin-bottom:8px"><div>pBOB-CAG-SARS-CoV2-S-HA</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pBOB-CAG-SARS-CoV2-S-HA was a gift from Gerald Pao (Addgene plasmid # 141347; http://n2t.net/addgene:141347; RRID:Addgene_141347).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_141347)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pCAGGS-SARS2-S-FKO (C-flag) was a gift from Hyeryun Choe & Michael Farzan (Addgene plasmid # 159364; http://n2t.net/addgene:159364; RRID:Addgene_159364).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_159364)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data were fitted using the non-linear curve fitting routines in Prism® (Graphpad Software Inc).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Graphpad</div><div>suggested: (GraphPad, RRID:SCR_000306)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The digitized images were also analyzed using ProtoArray Prospector v5.2 and potential hits were identified using the software’s algorithm.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ProtoArray Prospector</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Protein binding responses were analyzed using BiaEval software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BiaEval</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Interactome analysis: The STRING database52, that integrates all known and predicted associations between proteins, including both physical interactions as well as functional associations has been used to analyses functional associations between biomolecules.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>STRING</div><div>suggested: (STRING, RRID:SCR_005223)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Images were prepared for presentation using ImageJ v.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After three washes, the Mouse/Rabbit PolyDetector Plus link &HRP label (Bio SB, Catalog No. BSB 0270) were applied.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Mouse/Rabbit PolyDetector Plus</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>PolyDetector</div><div>suggested: None</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.05.16.22275163: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Consent: Individuals provide written, informed consent for collection of demographic and clinical variables as well as blood for biobanking on up to 5 occasions every 6 months</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The plate containing the samples and standard curves were then incubated for 30 minutes at room temperature, washed, following which MSD SULFO-TAG-labelled goat anti-human IgG secondary antibody was added at a concentration of 1ug/ml and the plate was further incubated for one hour.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">These kits comprise 96 well plates, precoated with antigens, proprietary blocker, diluent, wash buffer, detection antibody, read buffer, control sera and reference standard.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>antigens,</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In addition, assay performance was compared with the Abbott SARS-CoV-2 IgG assay and the Abbott SARS-CoV-2 IgG II assay, chemiluminescent microparticle immunoassays (CMIA) (Abbott laboratories, IL, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Abbott</div><div>suggested: (Abbott, RRID:SCR_010477)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:


      Although the CEPHR COVID19 Serology Assay has many advantages, it is not without limitations. The assay employs RBD derived from the Wuhan-Hu-1 reference strain of SARS-CoV-2. Although the test has been validated in convalescent plasma from individuals with confirmed SARS-CoV-2, these individuals were infected with the variants circulating in the first wave of infections in early 2020 and the performance of this assay against the different SARS-CoV-2 variants of concern (VOCs) that have emerged since is still under investigation. In addition, the vaccinated population was relatively small, with the majority of individuals less than 3 months from second dose vaccine. Given waning of post vaccine protection22, sensitivity of the assay may alter as time post vaccination increases. Additionally binding assays do not evaluate antibody function, such as neutralising capacity or antibody effector function, although these gold standard assays are time consuming and expensive and do not lend themselves to high throughput. However, correlation of the CEPHR COVID19 Serology Assay with these gold standard functional assays is ongoing. Despite these limitations, the CEPHR SARS-CoV-2 Serology Assay is a robust, customisable, multiplex serologic assay for the detection of several different IgG specific to SARS-CoV-2, with multiple potential real world applications and performance characteristics that support its further development for use in both research and clinical settings.


      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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

      Learn more at Review Commons


      Reply to the reviewers

      Reviewer #1 (Evidence, reproducibility and clarity (Required)): Excellent quality of cell biology and biochemistry. the additional supports are needed for the claim of actin elongation using different formin variants.

      Reviewer #1 (Significance (Required)): Ingrid Billault-Chaumartin and co-authors described interesting research that provides insights on formin-isoform specific function in fission yeast and a new role of Fus1 FH2 domain in cell-cell fusion event. While three formin isoforms have different localization, research proposed an additional dissection in their functional differences by having different functions in C-terminus, including FH1 FH2 and formin C-terminus. The work also described additional factors that regulate cell fusions from autotrophy effect and formin expression level, in addition to the well-accepted formin biochemical activities. Here are my comments regarding the strengths of the work and improvements that could further strengthen the story.

      Major comments 1. Fig.1 shows Cdc12C could recapitulate Fus1 function by ~80% if fused with Fus1C, whereas deletion of the C-terminal tail of Cdc12 following FH2 introduces drastic dysfunction. Together with Fig. 3, these results indicate Cdc12 Cter plays more important roles than Fus1 Cter for there respective functions. Such results suggested a Cter-mediated mechanism that differentiates the functions of three fission yeast formin isoforms. The authors examined contributions from the difference in FH1 (Figs 4,5) and FH2 residues (Fig. 6). Whereas the obvious phenotype of Cter was not further investigated and not much discussed. The Cter of budding yeast formins interacts with nucleation-promoting factors, Bud6 and Aip5. Although S. Pombe does not have orthologs of budding yeast Bud6 and Aip5, I wonder would the author discuss the potential contribution of Cter in differentiating S. Pombe formins.

      The reviewer is correct that the C-terminal tail region of Cdc12 beyond the FH1-FH2 domains has a strong influence on the ability of Cdc12C to replace Fus1C. This is one reason why we specifically investigated the possible role of Fus1 C-terminal tail, which is much shorter than that of Cdc12. We found that Fus1 C-terminal tail plays only very minor role in regulating Fus1 function, as described in Figure 3. We note that contrary to what the reviewer states, Bud6 exists in S. pombe and binds the C-terminal tail of the formin For3 (see Martin et al, MBoC 2007), but whether it binds Fus1 is unknown. We have expanded our discussion to include a paragraph on the role of formin C-termini.

      Because the manuscript is focused on the function of Fus1 formin, we did not explore further the role of the Cdc12 C-terminal tail. It was previously shown that this region of Cdc12 contains an oligomerization domain that promotes actin bundling (Bohnert et al, Genes and Dev 2013). It is thus likely that this helps Cdc12 FH1-FH2 perform well in replacement of Fus1. In fact, it is likely that oligomerization boosts formin function, as we have discovered that Fus1 N-terminus contains a disordered region that fulfils exactly this function. This is described in a distinct manuscript under review elsewhere and just deposited on BioRxiv (Billault-Chaumartin et al, BioRxiv 2022; DOI: 10.1101/2022.05.05.490810). We have now cited this point in the discussion.

      1. Here, the study focuses on the FH1 between Fus1 and Cdc12 to understand their different functions in actin polymerization. FH1 mediated actin elongation through its interaction with profilin via polyP. The transfer rate of G-actin from profilin and profilin sliding depends on the polyP patterns regarding the length of each polyp motif and their distance to FH2 (Naomi Courtemanche and Thomas D. Pollard, JBC, 2012). To better understand the mechanisms by which these engineered FH1 variants on both Fus1 and Cdc12 in Fig. 4, the author may want to list the sequence of these engineered FH1 domains, including the information of the number and length of polyp motifs, and discuss these patterns.

      This list and discussion were available in the initial paper that characterized each of the constructs in vitro (Scott et al, MBoC 2011). We have now re-drawn it in a supplemental figure for convenience (as also answered in response to minor point 2), which is already provided in the revised manuscript as Figure S1. (Previous supplementary figures are re-numbered S1>S2, S2>S3 and S3>S4).

      1. Figs.4,5 cell biology results do not directly support the point of specific elongation rate unless the LifeAct-labeled actin cable elongation speed could be followed and quantified. The fluorescent tagging of tropomyosin does not show the actin cable pattern, which makes it very difficult to be used to study actin cable dynamics, such as elongation. Therefore, I feel the data in current Fig. 4 and Fig. 5 could not claim the differences in actin elongation without a quantitative comparison of elongation rate. I suggest a CK666 treatment to increase the visibility of the actin cable pattern of LifeAct, used before in both fission and budding yeasts, which would allow the author to quantify the actin cable elongation rate. Another way is to use the TIRF assay used in this study, which would give a better quantitation of formin nucleation and profilin-aided elongation.

      We respectfully disagree with the reviewer on this point. All the constructs we use in vivo have been characterized in vitro and their elongation rate carefully measured (Scott et al, MBoC 2011). These values are thus known and can be directly compared to our results in vivo.

      Of course, it would be fantastic to be able to directly measure formin elongation rates in vivo, but we are not aware that this has been done in any system. The proxy experiments that the reviewer suggests would be good ones, but each faces technical challenges that make them impossible in our system. First, because the fusion focus is a structure that forms in response to cell-cell pheromonal communication, we cannot add CK-666 or any other drug during this phase, as this perturbs the pheromone signal. Indeed, we had shown that simple buffer wash leads to loss of the fusion focus (see Dudin et al, Genes and Dev 2016). Second, the fusion focus is at the contact site between partner cells, i-e somewhat distant (1-2µm) from the coverslip during imaging. It is thus impossible to use TIRF. Finally, the fusion focus is a tightly packed actin structure. This is the reason why (rather than use of the tropomyosin marker) we cannot image single actin filaments (or even bundles) of which we could follow the dynamics as has been done to measure the retrograde flow of actin cables in yeast.

      What we have done is to use a better tropomyosin tag, mNeonGreen-Cdc8, which was just described (Hatano et al, BioRxiv 2022; DOI: 10.1101/2022.05.19.492673) to quantify amounts of linear actin. Although this is not a measure of elongation rate, it would give some sense about amounts of polymer assembled. We have obtained images with mNeonGreen-Cdc8 of all experiments previously conducted with GFP-Cdc8 and have replaced them in Figure 4C, Figure 5E, Figure 6E and Figure S2B. We have also quantified the relevant strains. The relative intensities of mNeonGreen-Cdc8 at the fusion focus at fusion time reflect remarkably well the measured elongation rates of the various formin constructs characterized in vitro. These data are now provided as new panels Figure 4F and Figure 5F.

      1. I appreciated the detailed biochemical dissections of multiple aspects of WTFus1 and Fus1R1054E, although the biochemical assays could not identify the mechanism by which R1054E causes the cell fusion. In many cases, the formin functions are diverse in diverse biological processes and sophisticated that cannot be explained well only from its biochemical activities in actin polymerization, such as the bundling, nucleation, and elongation studied in this story regarding fusion. This exciting information allows us to think of more possibilities that might regulate formin function rather than a direct change of formin activities in actin polymerization. I think a discussion of different aspects of functional regulation of formin might inspire society to investigate new possibilities to solve the mysteries. For example, the changes in formin behaviors and functions could be regulated by stress-induced formin turnover by degradation, cell signaling-regulated formin clustering and complex assembly, and their potential relevance to recruit protein constituents for fusion progression.

      We have added a paragraph on the role of Fus1 C-terminus. If you feel we should expand more on the diverse modes of regulation of formins, we could, but we have so far kept the discussion centred around the points of investigation in this paper, whose aim was to probe how changes in nucleation and elongation rates, rather than other regulations, affect the in vivo function of Fus1.

      Minor comments. 1. There are two types of "C", one includes FH1/FH2 and one following FH2, used in the manuscript, and it is a bit confusing. Better to differentiate them that allows an easy following. Fig. 1 uses Cdc12C-deltaC, Fig. 3 uses Fus1-delta Cter.

      We have updated the nomenclature to make this clearer: the C-terminal region beyond the FH1-FH2 domains is now called Cter throughout the manuscript.

      1. It's better to specify the amino acid position on the schematic of formins, such as panel A in many figures. It's always more informative to compare formin activities by considering the domain lengths, especially for the C-terminal tail that is variable in lengths and sequences. With similar thoughts, I suggest a supplementary figure that lists the sequence of all FH1 domains variants and Cter domains, such as the FH2 domain in Fig. S1.

      We have made a supplementary figure (new Figure S1) listing all constructs with specific aa positions as well as the FH1 domain variants and their sequences (see also answer to point 2 above). We have not added the sequence of the Cter domains in this figure, as these are extremely divergent and not particularly informative at this point.

      1. "n" for the statistic needs to be provided for Fig. S3.

      We have added the information to the legend of the figure (now Fig S4).

      1. The SDS-PAGE staining gel of the purified recombinant proteins for biochemical assays should be provided, particularly for these newly reported mutant variants.

      This is now provided as new panel S4C. We show the purified recombinant Cdc122FH1-Fus1FH2 proteins, which are the newly reported ones.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): In this study, Billaut-Chaumartin and colleagues investigate the molecular specialization of the S. pombe formin, Fus1. The authors systematically modulate the actin filament elongation and nucleation activities of Fus1 by expressing chimeric constructs that contain Formin Homology 1 and 2 domains from two other formins with known polymerization activities. By characterizing the architecture of the fusion focus and the efficiency of cell fusion, they find that both the elongation and nucleation properties of Fus1 are specifically tailored for its cellular role. Comparison of formin constructs with similar elongation and nucleation activities also reveals that the Fus1 FH2 domain possesses a specific property that promotes efficient cell fusion. Using sequence alignment and homology modeling, the authors identify R1054 as the residue that confers this novel, fusion-specific activity to Fus1, despite producing no effect on its bundling or polymerization properties in vitro.

      Overall, this study is well motivated, and the results support the conclusions that are drawn. I have only minor suggestions, as described below.

      Minor comments: (1) The schematic diagrams of the chimeric formin constructs are very helpful. However, it is difficult to distinguish the colors from one another, especially in the case of the Cdc12FH1-Fus1FH2 variant, which requires discernment of the relatively small purple region within the dark blue molecule. Would it be possible to modify the colors to increase their contrast? Similarly, the blue and gray data sets in Figure 3B are very difficult to discern.

      We have changed the colours to improve contrasts.

      (2) The affinities (Kd) with which the formins bind the barbed ends as described in the second-to-last paragraph on page 8, in Figure Legend 7G, and in the "Analysis of pyrene data" section of the Materials and Methods should be defined as dissociation "constants", rather than dissociation "rates". Also, these affinities are lacking units in the following sentence on page 8.

      We have corrected this. The unit is nM.

      (3) When comparing the TIRF micrographs in Figure S3A, it looks as though both formins (but especially the R1054E variant) nucleate more filaments in the presence of profilin than in its absence. Is this a reproducible effect? If so, can the authors provide an explanation for this?

      There is strong variability in the filament numbers observed by TIRF in replicate experiments, which makes it difficult to use this technique to determine the nucleation efficiency. This may be due for instance to the stickiness of the glass, which may influence the number of observed filaments. We have measured the number of filaments after 130s of polymerization for each condition to test whether there are any significant differences between conditions despite overall variability. The measurements suggest that the addition of profilin increases the number of actin filaments. However, these results should be taken very carefully due to the experimental variations (very large error bars). Additionally, because Fus1-associated filaments are very short in absence of profilin, it is quite likely that this influences their crowding at the glass surface compared to longer filaments (in presence of profilin). Since in TIRF we can only observe the filaments at the glass surface, we may miss a portion of short Fus1-bound actin filaments in absence of profilin.

      For these reasons, and because the possible role of profilin in modulating nucleation efficiency by formins is not the object of the work here, would thus prefer not to include this graph in the manuscript.

      Reviewer #2 (Significance (Required)): This study contributes a key advancement towards understanding how the polymerization activities of formins are tailored to support diverse and specific cellular functions. The results in this study nicely complement and expand upon similar recent work that dissected the polymerization requirements of the formin Cdc12, which mediates cytokinetic ring assembly in S. pombe, and For2, which drives the assembly of apical networks that are necessary for polarized growth in Physcomitrella patens. As such, this work will likely be of significant interest to scientists who study mechanisms of actin dynamics regulation. The identification of R1054 as a residue that confers a novel regulatory activity to the FH2 domain of Fus1 will also likely be of great interest to biochemists and other scientists who study formins at the molecular level.

      My expertise is in the field of formins and actin polymerization.

    1. To select an element tag or attribute defined in a specific namespace, you declare a namespace prefix with an @namespace rule, then use it in your selector. The namespace is separated from the tag name with a | (vertical bar or pipe) character; if there is no tag name in the selector, use a universal * selector:

      ```css @namespace svg "http://www.w3.org/2000/svg";

      a { / These rules would apply to any a elements. / text-decoration: underline; color: purple; } svg|a { / These rules would apply to SVG a elements, but not HTML links. / stroke: purple; } svg| { / These rules apply to all SVG-namespaced elements, but not HTML elements. */ mix-blend-mode: multiply; } ```

    1. Reviewer #2 (Public Review):

      In this manuscript by Ma et al., the authors develop a mass cytometry that includes 5 heavy metal conjugated lectins. After some validation of this panel, the authors use the panel to analyze human PBMCs, tonsils and endometrial CD4 T cells before and after infection with an HIV virus with HSA reporter tag. They found that HIV infection was associated with higher levels of staining with 4 out of 5 lectins (sialic acid and fucose binders). Using the PP-SLIDE algorithm they previously developed, and they predicted that HIV preferentially infected higher cells with higher lectin binding and led to an increase in staining after infection. To validate this hypothesis, sorting of high vs. low lectin staining cells was performed to show that cells with higher lectin staining also had higher rates of HIV infection. They also used sialidase to reduce sialic acid levels and showed that it reduced HIV infection in PBMCs from two different donors. In addition to the development, validation and demonstration of mass cytometry lectin staining, the finding that glycosylation can influence HIV infectivity is novel and could open up new avenues for investigation. I think this work will be generally useful to the mass cytometry and HIV communities.

    1. GWG, Some random thoughts:

      Your challenge question is tough, not just for the mere discovery portion, but for the multiple other functions involved, particularly a "submit/reply" portion and a separate "I want to subscribe to something for future updates".

      I can't think of any sites that do both of these functionalities at the same time. They're almost always a two step process, and quite often, after the submission part, few people ever revisit the original challenge to see further updates and follow along. The lack of an easy subscribe function is the downfall of the second part. A system that allowed one to do both a cross-site submit/subscribe simultaneously would be ideal UI, but that seems a harder problem, especially as subscribe isn't well implemented in IndieWeb spaces with a one click and done set up.

      Silo based spaces where you're subscribed to the people who might also participate might drip feed you some responses, but I don't think that even micro.blog has something that you could use to follow the daily photo challenges by does it?

      Other examples: https://daily.ds106.us/ is a good example of a sort of /planet that does regular challenges and has a back end that aggregates responses (usually from Twitter). I imagine that people are subscribed to the main feed of the daily challenges, but I don't imagine that many are subscribed to the comments feed (is there even one?)

      Maxwell's Sith Lord Challenge is one of the few I've seen in the personal site space that has aggregated responses at https://www.maxwelljoslyn.com/sithlordchallenge. I don't think it has an easy way to subscribe to the responses though an h-feed of responses on the page might work in a reader? Maybe he's got some thoughts about how this worked out.

      Ongoing challenges, like a 30 day photography challenge for example, are even harder because they're an ongoing one that either requires a central repository to collect, curate, and display them (indieweb.xyz, or a similar planet) or require something that can collect one or more of a variety of submitted feeds and then display them or allow a feed(s) of them. I've seen something like this before with http://connectedcourses.net/ in the education space using RSS, but it took some time to not only set it up but to get people's sites to work with it. (It was manual and it definitely hurt as I recall.)

      I don't think of it as a challenge, but I often submit to the IndieWeb sub on indieweb.xyz and I'm also subscribed to its output as well. In this case it works as an example since this is one of its primary functions. It's not framed as a challenge, though it certainly could be. Here one could suggest that participants tag their posts with a particular hashtag for tracking, but in IndieWeb space they'd be "tagging" their posts with the planet's particular post URL and either manually or automatically pinging the Webmention endpoint.

      Another option that could help implement some fun in the system is to salmention all the prior submissions on each submission as an update mechanism, but one would need to have a way to unsubscribe to this as it could be(come) a spam vector.

    1. Using JSX is not mandatory for writing React. Under the hood, it's running createElement, which takes the tag, object containing the properties, and children of the component and renders the same information. The below code will have the same output as the JSX above.

      JSX的底层实现逻辑实际上是调用了React.createElement函数

    1. Reviewer #1 (Public Review):

      In this manuscript, authors found Halo tag become resistant to lysosome degradation upon ligand binding, using this unique property, they developed a highly sensitive assay to monitor the autophagy flux. Measuring autophagy flux is one of the most important assays for studying autophagy, there are a few widely used assays to monitor the autophagy flux, such as p62 degradation, and LC3 processing, however, each of them has its own limitation, which is well known in the field. In this regard, this assay provides a simple, straight forward and sensitive assay for measuring autophagy flux, which I personally think is very likely it will be widely used by the autophagy community. This is a well-controlled, rigorous study and the manuscript is clearly written.

    2. Reviewer #2 (Public Review):

      Yim et al have utilised the HaloTag system to generate tools and assays to measure autophagy flux. The assays are highly accessible and straight forward to conduct. The study does not have any major weaknesses, with all key conclusions strongly supported by clear data. A major strength of the study is the robustness of the assay and its ease of use across SDS-PAGE and imaging techniques that I expect will help with its uptake by the research community. The assay utilises the HaLo tag and its inherent stability within lysosomes once pulsed with a HaLo ligand. This enables analysis of autophagy flux over a set period of time. The approach is highly complementary to the recently published study by Rudinskiy et al (2022) MBoC, but also includes additional tools to measure different types of selective autophagy and bulk autophagy. The inclusion of limitations of their approach within the discussion will be very useful for researchers planning to use the assay in their work. Overall, this is an excellent study that has generated very valuable tools for the study of autophagy.

    3. Reviewer #3 (Public Review):

      Monitoring autophagy induction and flux in mammalian cells is challenging and depends largely on the mammalian ATG8 proteins (LC3 and GABARAP), typically tagged at the N-terminus with a small tag (HA, flag, myc) or a range of fluorescent tags. When autophagy is induced these ATG8 proteins get captured into autophagosomes and delivered to lysosomes for degradation. Monitoring flux by western blots relies on a molecular weight shift caused by lipidation, and quantification of loss of signal from degradation (analysis of initiation), or accumulation by the addition of inhibition of lysosomal inhibitors (analyses of flux). Fluorescent tags provide similar results but the measurements rely on counting degradation sensitive or resistant fluorescent signals. Image-based analysis is more challenging than western blot but both require significant optimization. In this manuscript these existing assays are modified by the use of a probe (Halo tag) again appended to the N-terminus of ATG8s which becomes resistant to lysosomal degradation after binding a ligand (TMR). The ligand can be pulsed-in to allow detection of acute induction of autophagy eliminating the background from basal accumulation. Generation of the Halo-TMR is then monitored by western blot or using an in gel-fluorescent assay. The authors present data which shows the adaptability of the system for imaging analysis, and for both quantitative analysis using western blot and imaging of selective autophagy or bulk, non-selective autophagy. The authors have developed a robust, useful alternative to existing assay and present the results in a careful, well described brief manuscript. These modifications are important for the field and for those who require quantitative results. The drawbacks are similar to existing assays and will usually require the generation of stable cell lines because over-expressed ATG8s can aggregate and confound the measurements.

    1. SciScore for 10.1101/2022.05.13.491770: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">4 colonies from each transformed plate were randomly picked and the insert was checked by performing colony PCR using nested PCR primers.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells were incubated with an anti-SARS-CoV spike primary antibody directly conjugated with alexaflour-647 (CR3022-AF647) for up to 4 hours at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV spike</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Ten million PBMCs of select COVID-19 recovered donors were stained with RBD-Alexa Fluor 488 for 1 hour at 4°C, followed by washing with PBS containing 2% FBS (FACS buffer) and incubation with efluor780 Fixable Viability (Live Dead) dye (Life Technologies, #65-0865-14) and anti-human CD3, CD19, CD20, CD27, CD38 and IgD antibodies (BD Biosciences) for 30 minutes.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human CD3</div><div>suggested: (RayBiotech Cat# CS-11-0105, RRID:AB_1227994)</div></div><div style="margin-bottom:8px"><div>CD19</div><div>suggested: (Agilent Cat# TC67401, RRID:AB_579635)</div></div><div style="margin-bottom:8px"><div>CD20</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>CD27 , CD38</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>IgD</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">mAb antibody binding was then detected with 50 μl/well of MSD SULFO-TAG anti-human IgG antibody (diluted 1:200) incubated for one hour at room temperature with shaking at 700rpm.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 100 pfu of SARS-CoV-2 (2019-nCoV/USA_WA1/2020), Alpha, Beta, Gamma, Delta and Omicron (BA.1 and BA.2) were used on Vero TMPRSS2 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero TMPRSS2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">IC50 titers were calculated by non-linear regression analysis using the 4PL sigmoidal dose curve equation on Prism 9 (Graphpad Software).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Graphpad</div><div>suggested: (GraphPad, RRID:SCR_000306)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data were analyzed using FlowJo software 10</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">CryoEM data analysis and model building: CryoEM movies were motion-corrected either in Motioncorr2 in Relion3.0 (30) or using Patch motion correction implemented in Cryosparc v3.3.1 (31).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Cryosparc</div><div>suggested: (cryoSPARC, RRID:SCR_016501)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The combined Focused Map tool in Phenix was used to integrate high resolution locally refined maps into an overall map.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Phenix</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Glycans with visible density were modelled in Coot (36).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Model validation was performed using Molprobity (37).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Molprobity</div><div>suggested: (MolProbity, RRID:SCR_014226)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Figures were prepared in ChimeraX(34) and PyMOL (39).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PyMOL</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. Instead of being parsed, it was `import`-ed and `include`-d

      Flems does something like this:

      To allow you to use Flems with only a single file to be required the javascript and the html for the iframe runtime has been merged into a single file disguised as flems.html. It works by having the javascript code contained in html comments and the html code contained in javascript comments. In that way if loaded like javascript the html is ignored and when loaded as html the javascript part is ignored.

      https://github.com/porsager/flems#html-script-tag

    1. SciScore for 10.1101/2022.05.10.491349: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Protein expression of Nsp15 variants: WT Nsp15 was previously synthesized by Genscript (Piscataway, NJ), and contains an N-terminal His tag with thrombin and TEV cleavage sites in pET14b [28].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET14b</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sequences of Nsp15 isolates were then aligned to that of the original Wuhan isolate (GenBank NC_045512.2) using the nucmer command from MUMmer 4.0 package [53] with default parameters.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MUMmer</div><div>suggested: (MUMmer, RRID:SCR_018171)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.05.10.491295: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: The study was carried out following a protocol approved by the ANSES/EnvA/UPEC Ethics Committee (CE2A-16) and authorized by the French ministry of Research under the number APAFIS#25384-2020041515287655 v6 in accordance with the French and European regulations.<br>IRB: The study was carried out following a protocol approved by the ANSES/EnvA/UPEC Ethics Committee (CE2A-16) and authorized by the French ministry of Research under the number APAFIS#25384-2020041515287655 v6 in accordance with the French and European regulations.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Golden Syrian hamster infections and assessment of αREPs antiviral activity: Hamster infections: Thirty-two specific-pathogen-free (SPF) 8 weeks-old Golden Syrian hamsters (Mesocricetus auratus, males, provided by Janvier-Labs, Le Genest-Saint-Isle, France) housed under BSL-III conditions were kept according to the standards of French law for animal experimentation.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sections were then incubated overnight in PBS with 0.2% BSA and 0.05% Tween-20 with primary antibodies directed against SARS-CoV-2 Nucleocapsid Protein (1:500; mouse monoclonal, # ZMS1075, Merck);</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2 Nucleocapsid Protein ( 1:500</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Fluorescence staining was performed using goat anti-rabbit Alexa-Fluor-488 (1:800; Molecular Probes – A32731; Invitrogen, Cergy Pontoise, France) and donkey anti-mouse Alexa-Fluor 555 (1:800; Molecular Probes – A32773; Invitrogen, Cergy Pontoise, France) secondary antibodies.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: (Thermo Fisher Scientific Cat# A32731, RRID:AB_2633280)</div></div><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: (Thermo Fisher Scientific Cat# A32773, RRID:AB_2762848)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, HEK-293TT cells (106 cells per P6 well) were transfected with plasmids encoding GAG-POL, F-LUC and SARS-CoV-2 spikes.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK-293TT</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Viral stocks were prepared by propagation in Vero E6 cells in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 2% (v/v</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: RRID:CVCL_XD71)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">This mixture was added to Vero-E6 cells (CRL-1586, ATCC) seeded in a 96-well plate one day before.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero-E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To prepare the virus working stocks, a 25cm2 culture flask of confluent VeroE6 TMPRSS2 cells growing with MEM medium with 2.5% FCS was inoculated at a multiplicity of infection (MOI) of 0.001.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VeroE6 TMPRSS2</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">EC50 and EC90 determination: One day prior to infection, 5×104 VeroE6/TMPRSS2 cells per well were seeded in 100 µL assay medium (containing 2.5% FCS) in 96 well culture plates.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VeroE6/TMPRSS2</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS CoV-2 Beta (SA lineage B 1.351) was isolated in France in 2021, The strain is available through EVA GLOBAL: UVE/SARS-CoV-2/2021/FR/1299-ex SA (lineage B 1.351) at https://www.european-virus-archive.com/virus/sars-cov-2-uvesars-cov-22021fr1299-ex-sa-lineage-b-1351. Sars-Cov-2 Gamma (SARS-CoV-2/2021/JP/TY7-503 lineage P.1, ex Brazil) was isolated in Japan in January 2021.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Sars-Cov-2 Gamma</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Production of the receptor binding domain (RBD) of the SARS-CoV-2 spike: The RBD (223 amino acids starting at position 319 of the spike sequence) coding sequence was cloned in frame behind a sequence encoding a signal peptide and in front of a His-tag coding sequence in the eukaryotic pYD11 expression plasmid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pYD11</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">αReps expression and purification: The αRep genes encoding the RBD binders were subcloned in the bacterial expression vector pQE81 and resulting plasmids used for transforming Rosetta cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pQE81</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sections were then incubated overnight in PBS with 0.2% BSA and 0.05% Tween-20 with primary antibodies directed against SARS-CoV-2 Nucleocapsid Protein (1:500; mouse monoclonal, # ZMS1075, Merck);</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Merck)</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Images were quantified using ImageJ (Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, http://imagej.nih.gov/ij/, 1997–2012) to threshold specific staining of SARS-CoV-2 in the dorso-medial area of the nasal cavity.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All data obtained were analyzed using GraphPad Prism 8 software (Graphpad software).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div><div style="margin-bottom:8px"><div>Graphpad</div><div>suggested: (GraphPad, RRID:SCR_000306)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.05.09.491254: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: EXPERIMENTAL MODELS AND SUBJECT DETAILS: MATERIALS AND METHODS: Human subjects: This study was approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (Ref No. UW 21-452).<br>Consent: Written informed consent and questionnaire of vaccination and infection were obtained from these subjects.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antigen-specific B cells: To characterize the SARS-CoV-2 Spike-specific B cells, PBMCs from each vaccinee were first stained with an antibody cocktail contained dead cell dye (Zombie aquae), CD3-Pacific Blue, CD14-Pacific Blue, CD56-Pacific Blue, CD19-BV785, IgD-BV605, IgG-PE, CD27-BV711, CD21-PE/Cy7, CD38-Percp/Cy5.5, CD11C-APC/Fire750 and His-tag Spike protein.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgD-BV605, IgG-PE</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>CD38-Percp/Cy5.5</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>CD11C-APC/Fire750</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>His-tag Spike protein.</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells were then washed with FACS buffer (PBS with 2% FBS) and further stained with the secondary antibodies including APC anti-His and DyLight 488 anti-his antibodies.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-His</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In brief, different SARS-CoV-2 pseudotyped viruses were generated through co-transfection of 293T cells with 2 plasmids, pSARS-CoV-2 S and pNL4-3Luc_Env_Vpr, carrying the optimized SARS-CoV-2 S gene and a human immunodeficiency virus type 1 backbone, respectively.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The plasma-virus mixtures were then added into pre-seeded HEK293T-hACE2 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T-hACE2</div><div>suggested: RRID:CVCL_A7UK)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In brief, different SARS-CoV-2 pseudotyped viruses were generated through co-transfection of 293T cells with 2 plasmids, pSARS-CoV-2 S and pNL4-3Luc_Env_Vpr, carrying the optimized SARS-CoV-2 S gene and a human immunodeficiency virus type 1 backbone, respectively.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNL4-3Luc_Env_Vpr</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For intracellular staining, cells were fixed and permeabilized with BD Cytofix/Cytoperm (BD Biosciences) prior to staining with the mAbs against IFN-γ-PE, TNF-α-AF488 and IL-2-PE-Cy7.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BD Cytofix/Cytoperm</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Stained cells were acquired by FACSAriaIII Flow Cytometer (BD Biosciences) and analyzed with FlowJo software (v10.6) (BD Bioscience).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Correlation plots and heatmap visualizations: Correlograms plotting the Spearman rank correlation coefficient (r), between all parameter pairs were generated with the corrplot package (v0.84) (Wei and Sikmo, 2017) running under R (v3.6.1) in Rstudio (1.1.456).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Rstudio</div><div>suggested: (RStudio, RRID:SCR_000432)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Spearman rank two-tailed P values were calculated using corr.test (psych v1.8.12) and graphed (ggplot2 v3.1.1) based on *p<0.05, **p<0.01, ***p<0.001.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ggplot2</div><div>suggested: (ggplot2, RRID:SCR_014601)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analysis: Statistical analysis was performed using PRISM 8.0.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PRISM</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:


      Limitations of the study: There are some limitations in our study. First, we were unable to obtain blood samples from our subjects after they became infected and quarantined. We, therefore, could not determine the B and T cell activation post BA.2 infection. Nevertheless, vaccine breakthrough infections often recall rapid NAbs and T responses against various VOCs, including Omicron (Collier et al., 2022; Suntronwong et al., 2022; Zhou et al., 2022). Second, most of our infected vaccinees were confirmed infection by self-RAT, thus the effect of different vaccine regimens on controlling viral loads was not determined. It remains necessary to compare the dynamics and magnitudes of recalled immune responses among vaccinees with BA.2 breakthrough infection patients in the future. In summary, we report that 3×BNT and 3×CorV provided better protection against SARS-COV-2 BA.2 than 2×BNT and 2×CorV. High frequencies of S-specific activated memory B cells and cross-reactive T cell responses induced by the third vaccination are critical for protection and illness reduction during the Omicron BA.2 breakthrough infection.


      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.05.10.491301: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: All experiments with mice, hamsters, and macaques were carried out in accordance with the Regulations in the Guide for the Care and Use of Laboratory Animals of the Ministry of Science and Technology of the People’s Republic of China.<br>IACUC: All animal procedures were approved by the Institutional Animal Care and Use Committee of the Institute of Medical Biology, Chinese Academy of Medical Science.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">The 6- to 8-year-old male or female rhesus macaque experiments were performed in the animal biosafety level 4 (ABSL-4) facility at Wuhan Institute of Virology (WIV), Hubei, China.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The following primary antibodies were used in this study: anti-SARS-CoV-2 (2019-nCoV) Spike Antibody (40589-T62, Sino Biological), and anti-GAPDH Antibody (60004, Proteintech).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-GAPDH</div><div>suggested: (Proteintech Cat# 60004-1-Ig, RRID:AB_2107436)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The secondary antibodies used were Peroxidase AffiniPure Goat Anti-Rabbit IgG (H+L) (111-035-003, Jackson ImmunoResearch), Peroxidase</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-Rabbit IgG</div><div>suggested: (Jackson ImmunoResearch Labs Cat# 111-035-003, RRID:AB_2313567)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For determination of S-specific antibody response, plates were incubated with goat anti-mouse IgG HRP (for mouse sera, Proteintech Cat: SA00001-1) or goat anti-Syrian hamster IgG HRP (for hamster sera, abcam Cat: ab6892) or goat anti-monkey IgG HRP (for NHP sera, Invitrogen Cat: PA1-84631) at 37°C for 1 hour and then substrate tetramethylbenzidine (TMB) solution (Invitrogen) was used to develop.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse IgG</div><div>suggested: (Proteintech Cat# SA00001-1, RRID:AB_2722565)</div></div><div style="margin-bottom:8px"><div>anti-Syrian hamster IgG</div><div>suggested: (Abcam Cat# ab6892, RRID:AB_955427)</div></div><div style="margin-bottom:8px"><div>anti-monkey IgG</div><div>suggested: (Thermo Fisher Scientific Cat# PA1-84631, RRID:AB_933605)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell lines and antibodies: HEK 293F cells were grown in FreeStyle Media (Gibco-Thermo Fisher Scientific) and transiently transfected using polyethylenimine (PEI) (Polysciences, Inc.) in an 8% CO2 environment at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK 293F</div><div>suggested: RRID:CVCL_6642)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK 293A and Vero E6 cells were maintained in high glucose DMEM(GIBCO) supplemented with 10% FBS(GIBCO) and 1% penicillin/streptomycin (P/S) (GIBCO) in a 5% CO2 environment at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK 293A</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Virus titration: Virus titrations were performed by endpoint titration in Vero E6 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: RRID:CVCL_XD71)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After 1 hour of incubation, 100 μL mixtures were inoculated onto monolayer Vero cells in a 24- well plate for 1 hour with shaking every 15 minutes.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Animal vaccination and serum collection: Mice: For mouse vaccination, groups of 6- to 8-week-old female BALB/c mice or female K18-hACE2 Transgenic Mice were intramuscularly immunized with LNP vaccine candidates or a placebo in 50 μL, and 3 weeks later, a second dose was administered to boost the immune responses.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BALB/c</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cloning, expression, and preparation of the RQ3013 encoded Spike proteins: The gene encoding the RQ3013 was fused with a C-terminal twin Strep-tag (LEVLFQGPSGS WSHPQFEK GGGSGGGSGGSA WSHPQFEK) and cloned into a mammalian cell expression vector pcDNA3.1.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The resulting plasmid, pcDNA3.1-RQ3013-Twinstrep, was transformed into HEK 293F cells using polyethylenimine (PEI) in FreeStyle Media (Gibco-Thermo Fisher Scientific).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1-RQ3013-Twinstrep</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Other procedures of cryo-EM data processing were performed within RELION v3.1 or CryoSPARC v3 using the dose-weighted micrographs23, 24.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RELION</div><div>suggested: (RELION, RRID:SCR_016274)</div></div><div style="margin-bottom:8px"><div>CryoSPARC</div><div>suggested: (cryoSPARC, RRID:SCR_016501)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, the initial templates were fit into the map using Chimera and Coot28, followed by a ten-cycle rigid body refinement using Phenix.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Phenix</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then, a combined manual refinement and real-space refinement were carried out for both prefusion state and postfusion state S structures in Coot and Phenix29.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The dose-response curves were plotted from viral RNA copies versus the drug concentrations using GraphPad Prism 8.0 software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical Analysis: All statistics data were performed and graphed using GraphPad Prism8.0.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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

      Learn more at Review Commons


      Reply to the reviewers

      Manuscript number: RC-2021-01219

      Corresponding author(s): Rajan, Akhila

      1) General Statements [optional]

      This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

      The goal of this study is to:

      • Define how prolonged exposure to a high-sugar diet (HSD) regime alters both the lipid landscape and feeding behavior.
      • Determine how changes in lipid classes within the adipose tissue regulates feeding behavior. Key findings:

      In this study, by taking an unbiased systems level and genetic approach, we reveal that phospholipid status of the fat tissue controls global satiety sensing.

      Impact of Key findings:

      By uncovering a critical role for adipose tissue phospholipid balance as a key regulator of organismal feeding, our work raises the possibility that the rate-limiting enzymes in phospholipid synthesis, including Pect, are potential targets for therapeutic interventions for obesity and feeding disorders.

      Peer review comments:

      This study has immensely benefited from the thoughtful peer-review of three reviewers. As per their recommendations, we have performed a major revision by performing additional experiments (see summary table below in next section) and strived to address the major concerns raised. Based on our reading, there were two major concerns that overlapped between all three reviewers raised. They are as follows:

      • Does the genetic disruption of Pect in fly fat body alter phospholipid levels? Two reviewers (#2 and #3) recommended that we perform lipidomic analyses on adult flies with adipose tissue specific knockdown of For the revised version, we have completed this lipidomic experiment, and present results as a new main Figure 6, Supplemental S7 and S9.
      • Is the dampened HSD induced hunger-driven feeding (HDF) behavior because of increased baseline feeding (#1 and #3)? In addition, reviewer #1, asked us whether HSD flies experience an energy-deficit? In other words, we were asked to uncouple whether what we observed was HSD-driven allostasis or indeed, as we had interpreted, that HSD dampened hunger-driven feeding response.

      Hence, they recommended that we:

      1. Re-analyze our hunger-driven feeding datasets and present non-normalized data (also requested by Reviewer #3) and show baseline feeding behavior on HSD. To address this, we have completed this analysis and present our results in Figure 1B-D and S1.
      2. Determine whether the HSD fed flies display an energy deficit on starvation. To this end, we performed an assayed starvation-induced fat mobilization on HSD, results for this are now presented on Figure 1E-G and S2. Conclusions after the revision:

      First, it is important to note here that the additional experiments have not caused a significant revision of the major conclusions of the original version of our study. In fact, we hope that the revised version provides clarity and further substantiation to our original arguments.

      • The lipidomics experiments on Pect fat-specific knock-down flies show that reducing Pect in fat-body causes a significant reduction in certain PE lipid species (PE 36.2 specifically- Figure 6B). This is consistent with a prior report on lipidomics of the Pect null allele by Tom Clandinin’s group (PMID: 30737130). Furthermore, we note that when Pect is knocked down in the fat body, there is a significant increase in two other classes of phospholipids LPC and LPE (Figure 6A). Together, this suggests that an imbalance in phospholipid composition in the absence of Pect activity in fat.
      • The starvation-induced fat mobilization experiments show that despite being fed a prolonged HSD, adult flies sense starvation and effectively mobilize fat stores, at a level comparable to Normal food (NF) fed adult flies, suggesting that even despite HSD exposure, adult flies experience an energy deficit on starvation.
      • In our non-normalized data, we find that the baseline feeding events are not significantly altered between HSD and NF-fed flies (Figure 1D). This suggests that the effects we observe are not due to an increase in the “denominator”, but a dampening of hunger-driven feeding on HSD. With regard to our original version, all three peer-reviewers found that the study was interesting, significant, important, and novel – Reviewer #1: “The work is potentially novel and interesting”; #2 : “I find the study to be potentially very important - the authors combine a longitudinal study that would be difficult in any other model with the powerful genetic tools available in the fly. The conclusions are mostly convincing”; #3: “This manuscript demonstrates how fat body Pect levels affect HSD induced changes in hunger-driven feeding response. I agree with all the reviewers points; potentially very interesting”. But had requested that we provide further substantiation and clarification.

      We sincerely hope that the peer-reviewers find that our revised version with additional new experimental datasets, improved data visualization, and the presentation of non-normalized raw data points, makes this study clear, compelling, and well-substantiated.

      • 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. *

      Below we summarize in Part A, the key experiments that were performed to address the major concerns. In Part B, we provide a point-point response to each reviewer with embedded datasets.

      Part a:

      We performed several new experiments, including:

      • To address the primary concern of Reviewer #1 regarding whether the HSD flies have a similar energy deficit to Normal food (NF) fed flies, we performed analysis of stored neutral fat Triacylglycerol (TAG) reserves and how HSD fed flies mobilized fat stores on starvation. We present these results in Figure 1E-G, S2. These results show that HSD-flies despite accumulating more TAG (S2), breakdown a similar amount of fat reserves as NF-fed flies on starvation at any time-point (Figure 1E-G). This suggests that HSD-fed flies do sense and respond to energy deficit.
      • To address concerns of reviewer #2 and #3 on whether Pect genetic manipulation affects specific phospholipid classes, we performed lipidomic analyses. The table below summarizes the new 3 new figures and 4 supplemental figures (blue text are all new figure numbers and figure panels) and three new Supplementary files as per reviewer’s request.

      Figure #

      Main point

      New datasets in revision

      Companion Supplement

      1

      HSD alters feeding behavior, but flies still breakdown TAG on starvation.

      TAG storage and breakdown over longitudinal HSD shows that HSD and NF fed flies show similar levels of TAG breakdown on starvation, despite consistently elevated TAG on HSD. This supports the idea that flies do sense starvation even on HSD, but there is a uncoupling of the feeding behavior after Day 14. Revised the data representation of Figure 1 to show non-normalized data over time. S1 and S2 companions are new in the revision. Panels 1D to 1E are new for the revision.

      S1- Raw data of feeding events plotted.

      S2 Elevated TAG at all time points.

      2

      HSD causes insulin resistance

      S3A added to show that insulin transcript levels remain the same in response to reviewer #3’s concerns.

      S3

      3

      Phospholipid concentration raw data from lipidomic on Day 7 and Day 14 HSD suggest that PC, PE levels are increased on Day 14 HSD.

      Figure 3 revamped to show new data visualization and non-normalized raw data to address Reviewer #2’s major concerns. S4A and S4B added. In addition Supplementary File 1 and 2 provided with raw lipidomics data as per reviewer #2’s request.

      S4.

      S4A- non normalized raw data of all other lipid classes on HSD.

      S4B- fatty acid species data on Day 14 added as per request of rev.#2.

      4

      HSD regulate Apo-I levels in the IPCs and phenocopies Pect KD.

      Added Figure 4A to show that HSD phenocopies Pect-KD in terms of delivery to brain

      S5 showing the validation of the Apo-I antibody.

      S6 validation of Pect KD and over-expression and Pect mRNA levels dysregulation on HSD.

      5

      Pect RNAi is insulin resistant

      N/A

      N/A

      6

      Pect knockdown shows significant increase in LPC and LPE, and a non-significant reduction in PC, PE levels. Specifically, the PE lipid class PE36.2 is downregulated.

      Fig 6, S7, S9 are completely new based on reviewer #2 and #3 requests. In addition Supplementary File 3 provided with raw lipidomics data as per reviewer #2’s request

      S7, S8, S9#.

      S7- new Pect KD other classes

      S8- new PE classes for day 14 and Pect associated classes.

      S9- Pect OE lipidomics

      7

      Pisd and Pect activity in adipocytes are required for hunger-driven feeding behavior in normal diets

      Pisd RNAi data was moved from supplement to main figure.

      N/A

      Note on revised text: We have revised text not only in the results section, but also as per reviewer #2’s recommendation, we have revamped our introduction and discussion as well. Since the manuscript has been significantly revised to include a main figure 6, fully altered Figure 1 and 3, multiple new supplemental figures, the changes in text are extensive. Hence, they are unmarked in the main text. Nonetheless, we hope that the reviewers will be able to evaluate these changes, as we have provided the specific locations in text and embed key figures in the point-point response below.

      __Part B: __Point-Point responses to reviewer comments.

      Reviewer #1 comments in Blue, author response in black.

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

      In this manuscript, Kelly et al. show that the difference between the feeding behavior of fed and starved flies (hunger-driven feeding; HDF) is absent in animals fed a high-sugar diet (HSD) for two weeks or more. The disappearance of HDF with HSD coincides with changes in phospholipid profiles caused by HSD. Furthermore, RNAi-mediated downregulation of Pect in the fat body-a key enzyme in the PE biosynthesis pathway-phenocopies physiological effects of HSD. Moreover, downregulation or overexpression in the fat body abolishes or induces HDF, respectively, abolishes or induces HDF, respectively, independent of HSD treatment.

      Overall, the manuscript is well-written and the phenotypes are clear. However, I have major concerns regarding the authors' interpretation of the data and their conclusion. Most importantly, while it is clear that the authors' high-sugar dietary treatment affects feeding behavior and physiology, I am not convinced that the changes can be considered "hunger-driven"-which is central to the main point of the manuscript. Therefore, it is my recommendation that the authors substantially revise the manuscript by either showing additional/re-analyzed data that rule out alternative hypotheses, or rewriting the manuscript keeping alternative interpretations in mind.

      We are thankful to this reviewer for their thoughtful critique, and constructive and specific suggestions on how we can redress these concerns. We have taken on board the concerns of this reviewer regarding our interpretation of whether the changes in feeding behavior can be considered hunger-driven or not. Based on their advice, we have made significant changes by addressing: i) does HSD increased baseline feeding- we now show non-normalized raw data and data supports conclusion that baseline feeding is not higher; ii) whether HSD- fed flies can sense an energy deficit at levels similar to NF fed flies- we show that HSD flies sense energy deficit. We have provided detailed response below, and we hope the reviewer finds the additional datasets and re-analyzed data are consistent with the interpretation that prolonged HSD dampens starvation induced feeding. In addition to this key concern this reviewer has made a many other salient points that we have addressed with additional data or by clarifying the text.

      Major comments: 1) The data do not sufficiently show that the long-term HSD regime disrupts "hunger-sensing." The manuscript should address alternative hypotheses by showing raw instead of normalized data, rewriting the manuscript with a new central conclusion, or running additional experiments that actually show a defect in hunger-driven response. a. The main results that the authors rely on for the argument is that the ratio of feeding events that the starved and non-starved flies eat is different between the groups fed normal or HSD. However, because the authors only show normalized data (normalized to non-starved flies; Fig. 1), it is difficult to tell whether the change is due to a chronically increased feeding in non-starved HSD flies-maybe in perpetual hunger-like allostasis-or dampened starvation response. Indeed, the data shown in Fig S1 show that flies fed HSD for as short as 5 days show more frequent feeding events compared to age-matched controls fed normal food. It is possible that because the HSD-fed flies eat more than NF-fed flies, even without being starved, the ratio of starved/non-starved feeding is lower in the HSD-fed group-due to changes in the denominator, rather than the numerator.

      We have taken onboard this concern regarding presenting only normalized data, and that clouded the interpretation and left open other possibilities. In the completely revised figure 1 and S1. We now show non-normalized data, as a function of time. First we note that HSD-fed flies, do not show higher baseline feeding that NF fed flies, except on Day 10 of HSD, when there is a modest but significant elevation (Figure 1D).

      Nonetheless, on Day 10 HSD, flies still display increased hunger-driven feeding HDF (Figure 1C), it is only after Day 14 HSD that HSD dampens the starvation induced feeding.

      1. It is also possible that the HSD-fed flies are simply not in as big an energy deficit physiologically, due to the increased fat deposits they've accumulated (as the authors show later in the manuscript). It may take longer for the fat HSD flies to reach substantial energy deficiency than the NF flies, but they still may eventually be able to appropriately respond to hunger, just like NF flies. In such case, it would be a misnomer to call this behavioral change a 'defect in hunger-driven feeding behavior.' Maybe an experiment with a dose-response curve of "hunger driven feeding response" as a function of duration of starvation would help? Prompted by this reviewers question, we asked whether HSD fed flies, that have a higher baseline neutral fat store (Triacylglycerol-TAG) level, and if HSD-fed flies can sense energy deficit. For this, we revisited the longitudinal assays for neutral fat triacylglycerol (TAG) storage that our lab had generated, along with the HSD-HDF studies. We now present this evidence as Figure 1E-1G and Figure S2. Overall, our experiments point to the idea that adult flies fed HSD, are able to sense and mobilize TAG stores effectively throughout the 28-day time point that we analysed.

      First as shown in Figure S2, flies fed HSD display an increase in TAG levels. But it is to be noted that while TAG stores increase, the increase is not linear with time. This suggests that adult flies exposed to HSD store excess energy as TAG, but the increased TAG stores stay within a certain range despite the length of HSD exposure. This suggests that adult flies on HSD still display TAG homeostasis.

      Next, to directly address the reviewers point about HSD fed flies not sensing an energy deficit, we subject HSD-fed flies to an overnight starvation, same regime as used in the overnight feeding experiments, and asked whether they mobilize TAG. We noted that flies exposed to HSD breakdown TAG throughout the 28-day exposure at statistically significant levels for Day 3- Day 28, except on 14 and 21 days (Figure 1F). While there is TAG mobilization on Day 14 and 21, the difference is not statistically significant. Nonetheless, we note the same levels TAG breakdown for normal lab food (NF) fed flies on Day 14 and 21 (Figure 1E). Overall, HSD fed flies sense and display energy deficit, as measured by TAG store mobilization, throughout the 28 days of HSD exposure, at levels comparable to NF-fed flies (Figure 1G).

      Taken together, these results suggest that while HSD-fed flies experience an energy deficit on starvation, at levels comparable to NF-fed flies, throughout the 28-day time point assayed. But, their starvation driven feeding-response is dampened by Day 14 and by Day 28, the HSD-fed flies display more feeding events than HSD starved flies. These results are consistent with the interpretation that in HSD-fed flies the starvation-induced feeding behavior becomes desynchronized from the starvation induced TAG-mobilization, suggesting that there is an absence of hunger-driven feeding.

      2) How can you be sure that lower Dilp5 immunofluorescence is indicative of increased Dilp5 secretion? Wouldn't decreased production of dilp5 also have the same results?

      It has been shown previously in HSD fed larvae are hyperinsulinemic, i.e., they have 55% increase in circulating Dilp2 ( PMID: 22567167). Additionally, we have shown that ectopic activation of the insulin-producing neurons by expressing TRPA1, an ion channel that activates neurons, reduces Dilp5 accumulation without a change in Dilp5 mRNA levels (PMID: 32976758), suggesting that reduced Dilp5 accumulation, without alterations to mRNA levels is a proxy for increased secretion. Now, in response to this concern, in the revised manuscript, we have added qPCR data of Dilp2 and 5 (Figure S3A), which show no difference in expression levels after 14 days on HSD. Therefore, there is no dip in Dilp5 mRNA production. Given that Dilp2 and Dilp5 mRNA levels remain the same, but we see reduced Dilp5 accumulation, we interpret this to mean that Dilp5 secretion is increased.

      1. Also, the authors should state in the main text that it is Dilp5, not just any Dilp. Thanks for this suggestion and we have fixed this and referred to Dilp5 specifically throughout the text in the results section.

      3) Data presentation: a. Sometimes the data are normalized to NF (Fig 4B-C), sometimes not (ex. Fig 4A, S4C). Unless there is a specific rationale for the data transformation, it would be more appropriate to show untransformed data (ex. Fig 4A, S4C), especially as the authors use two-way ANOVA to determine significance. Only showing the differences implies comparison against a hypothetical mean (i.e. μ0=0), not between two group means.

      We thank the reviewers for bringing this issue to our attention. We updated all the figures to show untransformed data in the revised manuscript.

      1. Some figures show both individual data points and summary statistics (mean, SD, ... ex. Fig 2A)-which I believe is ideal-but some show only one or the other (ex. Fig 2B, no summary statistics; Fig. 3, no data points. The manuscript would read more convincing if data visualization is consistent across figures. We thank the reviewers for their feedback. We have made changes to all the figures in the revised manuscript to improve visual consistency.

      Minor comments: 1) High sugar diet: what is the actual sugar concentration in the NF v. HSD diets? The authors write that the HSD diet contains "30% more sugar" than the NF, but providing the final sugar concentrations-sucrose or others-would be informative for other scientists studying the effect of high sugar diets.

      We thank the reviewer for their suggestion and now we have updated the methods to include this sentence. After 7 days, flies were either maintained on normal diet or moved to a high sugar diet (HSD), composed of the same composition as normal diet but with an additional 300g of sucrose per liter”.

      1. Additionally, the definition of HSD is inconsistent. Main text (Page 5, line 17) states that their HSD is "60% more sugar than normal media," whereas the figure legend (Fig 1) and the Methods state that the HSD contains "30% more sugar." We apologize for this egregious typo in the figure legend! We have now fixed this to say 30% HSD. Only 30% HSD was used throughout this study.

      2) Starvation medium: please provide justification for why the authors used 1% sucrose/agar for starvation medium, instead of plain agar/water that most labs use. At least clarify and provide a reference for the claim that the 1% sucrose/agar "is a minimal food media to elicit a starvation response."

      We are very grateful for this reviewer identifying this this methods description error and bring it to our attention. We used 0% sucrose agar for overnight starvation in this study as most labs do. The error occurred because we were using another manuscript from the lab to help draft the methods section (PMID: 29017032). In that study, where we assayed the effect of chronic starvation our lab used: “1% sucrose agar for 5 days at 25C”. However, in this current study, because we are testing acute effects of overnight starvation, we are using 0% sucrose agar.

      3) Pect mRNA level is higher with HSD. This is surprising because not only, as authors mention, is increased PC32.2 with HSD suggests lower Pect activity, but also because Pect RNAi phenocopies long-term HSD in HDF behavior, lipid morphology, FOXO accumulation in fat body. The authors speculate that the data "likely shown an upregulation in an attempt to mediate the Pect dysregulation occurring at the protein level." If that were true, a western blot may be informative. Zhao and Wang (2020, PLoS Genetics) generated a Pect antibody that seems compatible with western blot applications. That being said, I don't think such data is critical for the manuscript. I mention this simply as a suggestion for the authors. a. page 8, line 22-23, did you mean to write "Given how PC32.2 is elevated after 14 days of exposure to HSD, we assumed that Pect levels would be low for flies under HSD," not "high?" Otherwise the subsequent 2 sentences don't make sense.

      We agree that the most confusing aspect of the study was that Pect mRNA levels being very high on Day 14 HSD, but nonetheless the effects of Pect-KD phenocopied HSD. To resolve this, we have now performed lipidomic analyses on whole adult flies, when Pect is knocked-down (KD) by RNAi in the fat tissue. We now present a new dataset in Figure 6. Two striking changes occur. They are:

      1. Pect-KD shows increase in the phospholipid classes LPC and LPE (Figure 6A). In contrast, LPE is significantly downregulated on HSD Day 14 (Figure 3).
      2. Pect-KD shows a significant reduction in specific class of PE 36.2 (Figure 6B). Our data regarding increase in PE 36.2 agree with a previous lipidomic analyses of Pect mutant retina (PMID: 30737130). In contrast, PE 36.2 trends upwards on 14 day HSD (Figure S7C) though not significantly. On 14-day HSD consistent with extreme upregulation of Pect mRNA fed flies (Figure S6A; Pect mRNA 200-250 fold), PE trends upwards on 14-day HSD (Figure 3) and PE 36.2 trends higher (Figure S7C). We note that on the surface of it PE and LPE per se are contrasting between 14-day HSD lipidome and fat-specifc Pect-KD. But there is a significant commonality that under both states there is an imbalance of phospholipids classes PE and LPE. Hence, we propose that maintaining the compositional balance of phospholipid classes PE and LPE is critical to hunger-driven feeding and insulin sensitivity. Hence, either increase or decrease, of these key phospholipid species, may lead to abnormal hunger-driven feeding.

      We agree that a western blot would be informative as well, but we were unable to obtain the reagent from Dr. Wang’s group, precluding us from performing this request. See email snapshot.

      To ensure that we appropriately discuss and clarify this issue, we have now included a section in the discussion - Page 14 Lines 26-34- under the subtitle “The implications of relationship between Pect levels and HSD”. We have pasted an excerpt from that subsection below for this reviewers assessment.

      Also, we note that over-expression of Pect cDNA in the fat-body does not alter phospholipid balance (Figure S9) and indeed improves HDF on HSD (Figure 7B). While this may appear inconsistent, it is critical to note that over-expression of Pect cDNA using UAS/Gal4 only increases Pect mRNA expression by 7-fold (Figure S6A), whereas HSD causes its upregulation by 250-fold (Figure S6B). Hence, we speculate that an increased ‘basal’ level of Pect such as by that provided by a cDNA over-expression in fat, may be protective to the negative effects of HSD (Figure 7B) without affecting overall phospholipid levels (Figure S9) , but extreme upregulation Pect on HSD affects the PE and LPE balance (Figure 3).”

      Reviewer #1 (Significance (Required)):

      The work is potentially novel and interesting, but at this stage it's difficult to interpret what the phenotype signifies. Although the manuscript could be revised simply by modifying the text, experimentally addressing the concerns would significantly improve the work.

      In sum, we hope we have addressed the key concern for Reviewer #1 as to whether the behavior we report here is indeed a dampening of starvation-induced feeding, or an effect of increase in baseline feeding. We hope that by reviewing our non-normalized data, they can appreciate that it is the former. Also, we hope that Reviewer #1 appreciates that we have strived to address the concerns by additional experiments, to clarify our findings and improve the impact of the work.

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

      This intriguing manuscript by Kelly and colleagues uses the fruit fly Drosophila melanogaster as a model to understand how diet-induced obesity alters the feeding response over time. In particular, the authors findings indicate that chronic exposure to a high-sugar diet significantly alters the starvation-induced feeding response. These behavioral studies are complemented by a lipidomics approach that reveals how a chronic high sugar affects many lipid species, including phospholipids. The authors then pursue mechanistic studies that indicate phospholipid metabolism within the fat body appears to remotely affect insulin secretion from the insulin producing cells. Moreover, the changes in phospholipid abundance are associated with changes in insulin-signaling, including increased insulin secretion from the IPCs and elevated levels of FOXO within the nucleus.

      I find the study to be potentially very important - the authors combine a longitudinal study that would be difficult in any other model with the powerful genetic tools available in the fly. The conclusions are mostly convincing, but a few follow-up experiments are required:

      We are grateful for the reviewers constructive, detail-oriented, and balanced feedback, and their recognition of the value of this study. Now, we have performed additional experiments to address the key concerns raised by all reviewers. We hope that on reading the revised version of our study, that the reviewer continues to feel positive about the message of this study and its potential impact.

      1. The key conclusions from the manuscript assume that manipulation of Pect expression levels alters phosphatidylethanolamine (PE) levels. However, the authors make no attempt to verify that the genetic experiments described herein actually affect PE levels. At a minimum, changes in PE levels should be verified for the Pect knockdown and overexpression lines. Similarly, there is no evidence that manipulation of either EAS or Pcyt2 induces the expected metabolic effects. I'm not asking that the longitudinal feeding experiments be repeated, simply that the authors measure the relevant lipid species, preferably with a targeted LC-MS approach.

      Prompted by this reviewer, we performed targeted LC-MS on whole adult flies, on normal diet, to assess lipid levels for fat-specific Pect-KD and overexpression. We decided to focus on Pect, as its knock-down even on normal diet causes a dampened hunger-driven feeding behavior (Figure 7A) and phenocopied a 14-day HSD feeding phenotype.

      We now present a new dataset in Figure 6. Two striking changes occur:

      They are:

      Pect-KD shows a significant reduction in specific class of PE 36.2 (Figure 6B). Our data regarding decrease in PE 36.2 agree with a previous lipidomic analyses of Pect mutant retina (PMID: 30737130). It is to be noted that though overall levels of all PE species trend downwards, like the Clandinin lab study on Pect (PMID: 30737130), we did not find a significant change in the overall PC and PE levels.

      • Pect-KD shows increase in the phospholipid classes LPC and LPE (Figure 6A). In contrast, LPE is significantly downregulated on HSD Day 14 (Figure 3). On 14-day HSD consistent with extreme upregulation of Pect mRNA fed flies (Figure S6A; Pect mRNA 200-250 fold), PE trends upwards on 14-day HSD (Figure 3) and PE 36.2 trends higher (Figure S7C). We note that on the surface of it PE and LPE per se are contrasting between 14-day HSD lipidome and fat-specifc Pect-KD. But there is a significant commonality that under both states there is an imbalance of phospholipids classes PE and LPE. Hence, we propose that maintaining the compositional balance of phospholipid classes PE and LPE is critical to hunger-driven feeding and insulin sensitivity. Hence, either increase or decrease, of these key phospholipid species, may lead to abnormal hunger-driven feeding.

      Finally, fat-specific Pect-OE did not cause significant changes to lipid species (Figure S9). This could either be due to the fact that in fat-specific Pect-OE flies under normal food and that we were assaying whole body lipid levels and not fat-specific lipid changes. But to counter that, even a 60% reduction in Pect mRNA levels (Figure S6A), was sufficient to produce an effect on whole body phospholipid balance (Figure 6). Hence, we speculate that by maintaining a basally higher (7-fold higher Pect mRNA level Figure S6A), might allow 14-day HSD-fed flies to buffer the negative effects of HSD and we predict that it might take longer to disrupt the phospholipid balance and HDF response.

      We have now included a section in the discussion - Page 14 Lines 26-34- under the subtitle “The implications of relationship between Pect levels and HSD”. We have pasted an excerpt from that subsection below for this reviewers assessment.

      Also, we note that over-expression of Pect cDNA in the fat-body does not alter phospholipid balance (Figure S9) and indeed improves HDF on HSD (Figure 7B). While this may appear inconsistent, it is critical to note that over-expression of Pect cDNA using UAS/Gal4 only increases Pect mRNA expression by 7-fold (Figure S6A), whereas HSD causes its upregulation by 250-fold (Figure S6B). Hence, we speculate that an increased ‘basal’ level of Pect such as by that provided by a cDNA over-expression in fat, may be protective to the negative effects of HSD (Figure 7B) without affecting overall phospholipid levels (Figure S9), but extreme upregulation Pect on HSD affects the PE and LPE balance (Figure 3).”

      A central hypothesis in the study is that the HSD over a period of 14 days results in insulin resistant and that these changes are leading to changes in hunger dependent feeding. I would encourage the authors to determine if Foxo mutants are resistant to these HSD-induced effects on HFD.

      We thank the reviewers for this suggestion. However, given that dFOXO nuclear localization rather than expression levels regulate insulin sensitivity, we feel that disrupting dFOXO levels via mutation or knockdown will produce a plethora of indirect effects including developmental abnormalities (PMID: 24778227, PMID: 16179433, PMID: 29180716, PMID: 12893776). Our data suggest that chronic HSD treatment and Pect affect insulin sensitivity in fat tissue. However, we feel that investigating whether insulin sensitivity/FOXO signaling in fat tissue regulates feeding behavior is outside the scope of our work.

      1. In lines 25-30, the authors draw the conclusion that an increase in unsaturated fatty acid species is associated with the HSD and that these changes results in a more fluid lipid environment. While I agree with the model, the manuscript contains no evidence to support such a model. Either test the hypothesis or move the last line of the section to the discussion.

      We thank the reviewer for this important and insightful comment. We agree that the data we presented and discussed in the original version is at the moment speculative. Addressing the hypothesis that increase in unsaturated fatty acid species result in a more fluid lipid environment will require us to build tools and expertise. Hence, this hypothesis is better suited for exploration in a future study. Given this, we have moved this out of the results section into the Discussion section titled “HSD and fat-specific PECT-KD causes changes to phospholipid profile” (See excerpt below from page 13, lines 24-35).

      In addition to changes in phospholipid classes, we found that HSD caused an increase in the concentration of PE and PC species with double bonds (Figure S4C and S4D). Double bonds create kinks in the lipid bilayer, leading to increased lipid membrane fluidity which impacts vesicle budding, endocytosis, and molecular transport14,92. Hence it is possible that a mechanism by which HSD induces changes to signaling is by altering the membrane biophysical properties, such as by increased fluidity, which would have a significant impact on numerous biological processes including synaptic firing and inter-organ vesicle transport.”

      Also, as per the reviewer’s guidance, given that we are speculating here, we have also shifted this dataset from Main figure 4 to supplement S4C and S4D.

      In addition, lines 25-30 state that FFAs are increased after 14 days of a HSD. Figure 3A shows the exact opposite - FFAs are significantly decreased in 14 day fed animals despite being elevated in the 7 day fed animals. This is an interesting result that warrants discussion. Moreover, I would encourage to examine the lipidomic data more carefully to ensure that the text accurately portrays the lipid profiles.

      We apologize for misstating that FFAs are decreased on 14-day HSD in the lines 25-30. It was an error and we have corrected this. We agree with the reviewer that the reduction of FFA on Day 14-HSD is an intriguing and unexpected observation that needs to be emphasized and further discussed. To this end, we have added figure S4B, wherein we have provided the difference in FFA concentration (by species) after days 7 and 14.

      Furthermore, we have discussed what the potential meaning of reduced FFA at Day 14 implies in page 12, lines 19-27 of the Discussion section titled “HSD and fat-specific PECT-KD causes changes to phospholipid profile”. We have stated the following-

      We speculate that this reduction in FFA maybe due to their involvement in TAG biogenesis (PMID: 13843753). We were interested to see if the decrease in FFA correlated to a particular lipid species, as PE and PC are made from DAGs with specific fatty acid chains. However, further analysis of FFAs at the species level did not reveal any distinct patterns. The majority of FFA chains decreased in HSD, including 12.0, 16.0, 16.1, 18.0, 18.1, and 18.2 (Figure S4B). This data was more suggestive of a global decrease in FFA, likely being converted to TAG and DAG, rather than a specific fatty acid chain being depleted.”

      The processed lipidomics data should also be included as supplementary data table so that they can be independently analyzed by the reader.

      We thank the reviewer for this suggestion. As per the reviewers request, we have included the raw data as an attachment in our supplementary material (Supplementary Files 1-3.), so that interested readers can use the datasets generated in this study for future work and further analysis.

      Beyond these experimental suggestions, the manuscript needs significant editing for clarity. While I won't provide a comprehensive list, the authors need to provide accurate descriptions and annotation of genotypes (including w[1118], which is written as W1118), typos, and formatting. I've listed a few examples below:

      1. Page 3, Line 1 and 2: "...have been shown to impact feeding behavior and metabolism that leads to..." This is an awkward and grammatically incorrect sentence.
      2. Page 3, Lines 7-32 is one very large paragraph but contains concepts that should be broken down over at least three paragraphs.
      3. Page 3, Line 25: A description of the reaction catalyzed by Pect would be helpful for a manuscript focused on Pecte activity.
      4. Page 4, Line 10: "previously characterized method of eliciting diet induced feeding behavior." As stated in the text, the method is previously described yet the manuscript characterizing the method isn't cited.
      5. Figure legend 3 contains a random assortment of capitalized lipid species. Also, the names of lipid species are inappropriately broken into multiple names. Please use correct nomenclature throughout the manuscript.

      The list above is nowhere near comprehensive. The manuscript requires significant editing.

      We are grateful to the reviewer for drawing our attention to these errors. We have made significant edits to the revised manuscript to address the above-mentioned concerns, as well as made additional textual changes throughout and copyedited it. We hope that the reviewer will find the manuscript reads better and the clarity and preciseness is significantly improved.

      Reviewer #2 (Significance (Required)):

      I find the study to be potentially very important - the authors combine a longitudinal study that would be difficult in any other model with the powerful genetic tools available in the fly. The findings will significantly advance our understanding of how lipid metabolism links dietary nutrition with feeding behavior.

      Once again, we are grateful for this reviewer’s thoughtful critique and encouraging words regarding our work and its potential impact.

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

      Summary: This manuscript uses Drosophila to investigate how diet-induced obesity and the changes in the lipid metabolism of the fat boy modulate hunger-driven feeding (HDF) response. The authors first demonstrate that chronic exposure (14 days) of high sugar diet (HSD) suppresses HDF response. Through lipidome analysis, the authors identify a specific class of lipids to be elevated upon chronic HSD feeding. This coincided with the changes in expression of Pect, an enzyme that regulates the biosynthesis of these lipids. Modulating the expression of Pect specifically in the fat body affected HDF response.

      We thank this reviewer for their rigorous and thoughtful critique and for identifying a key issue with our original study pertaining to a gap in how Pect mRNA levels on 14-day HSD are elevated but the Pect-KD phenocopies the HDF. Now by performing whole-body adult fly lipidomic on fat-specific Pect-KD we have resolved this issue and provided clarity on role of Pect in maintaining phospholipid homeostasis and thus subsequently impacts hunger-driven feeding. We hope the reviewer finds that the revised manuscript provides further clarity to the functional link between Pect’s role in fat-body and hunger-driven feeding.

      Major comments: The author claim that the HDF response in HSD is distinct between early (5d, 7d) and chronic (day 14) HSD feeding. However, the data seem to indicate that HDF response is significantly decreased at all time points in HSD. For example, at day 5 HDF response was increased only 3-fold in HSD (Figure 1C) compared to around 50-fold increase in NF (Figure 1B). The scale of the Y-axis in Figure 1B and 1C is an order of magnitude different. Including the starved data (NFstv and HSDstv) in Figure S1, normalized to NF fed group, would better visualize the overall trends. Related to this, having the source data for the actual number of feeding events would be useful (e.g., to see the baseline changes in feeding in different time points in Figure 1 and the effect of genetic manipulations in Figure 7).

      As per the reviewers request, we now have modified our graphs to show source data (Figure S1) and show the raw feeding events.

      Then in the non-normalized graphs we plot, over a longitudinal time course, baseline and hunger-driven feeding events (Figure 1B-D). We also show that HSD fed flies do not display increased baseline feeding (Figure 1D) suggesting that the effect we see on HDF are no clouded by increased baseline feeding.

      Yes, the reviewer makes an important point that HDF response on HSD fed flies is of a lower magnitude than NF fed flies. We think that is a biologically meaningful observation, as it suggests that flies have a remarkably fine-tuned ability to coordinate food-intake with nutrient store levels.

      ­­Now we have included a paragraph in the Discussion, Page 11 Lines 23-27, that say the following to ensure the readers appreciate this salient point raised by this reviewer.

      *It is to be noted that the HDF response of HSD-fed flies (Figure 1C, Days 3-10) is of lower order of magnitude than the NF-fed flies. This suggests that that in addition to sensing an energy deficit and mobilizing fat stores (Figure 1F, 1G, S1), HSD fed flies calibrate their starvation-induced feeding to compensate only for the lost amount of fat. Overall, this suggests that flies have a remarkably fine-tuned ability to coordinate food-intake with nutrient store levels. *

      The association between fat body Pect level and phospholipid levels is not clear. Day 14 of HSD feeding shows high expression of Pect in the fat body and elevated levels of PC32.0 and PC32.2. The authors assume the high expression of Pect in the fat body is due to the compensatory response, but there are no data indicating downregulation of Pect levels at the earlier time points of HSD feeding. A previous study demonstrated that Pect mutant flies have lower levels of PC32.0 but higher PC32.2 (PMID: 30737130).

      We agree that one puzzling aspect of the original version of this study was that Pect mRNA levels being very high on Day 14 HSD, but nonetheless the effects of Pect-KD phenocopied HSD. To resolve this, prompted by Reviewer #2 and #3 concerns, for this revised version we have now performed lipidomic analyses on whole adult flies, when Pect is knocked down (KD) by RNAi in the fat tissue. We now present a new dataset in Figure 6. Two striking changes occu. They are:

      1. Pect-KD shows increase in the phospholipid classes LPC and LPE (Figure 6A). In contrast, LPE is significantly downregulated on HSD Day 14 (Figure 3).
      2. Pect-KD shows a significant reduction in specific class of PE 36.2 (Figure 6B). Our data regarding increase in PE 36.2 agree with a previous lipidomic analyses of Pect mutant retina (PMID: 30737130). In contrast, PE 36.2 trends upwards on 14 day HSD (Figure S7C) though not significantly. On 14-day HSD consistent with extreme upregulation of Pect mRNA fed flies (Figure S6A; Pect mRNA 200-250 fold), PE trends upwards on 14-day HSD (Figure 3) and PE 36.2 trends higher (Figure S7C). We note that on the surface of it PE and LPE per se are contrasting between 14-day HSD lipidome and fat-specifc Pect-KD. But there is a significant commonality that under both states there is an imbalance of phospholipids classes PE and LPE. Hence, we propose that maintaining the compositional balance of phospholipid classes PE and LPE is critical to hunger-driven feeding and insulin sensitivity. Hence, either increase or decrease, of these key phospholipid species, may lead to abnormal hunger-driven feeding.

      On day 14, HDF response was increased 70-fold in w1118 flies in NF (Figure 1B; w1118), but only 2.5-fold in lpp>LucRNAi control flies in NF (Figure 7A). This suggests that lpp-gal4 driver lines have a significant effect on HDF response. Using a different fat-body specific Gal4 line would be necessary to validate conclusions.

      Regards reduced HDF magnitude, in our experience using UAS-Gal4 reduces HDF response magnitude consistently and cannot be compared to w1118 which is more robust. To account for background differences, we use Uas-Gal4 with control RNAi. It clearly shows differences in HDF response on starvation, but Pect and Pisd RNAi does not (Figure 7A). Hence, given that this experiment internally controls for any changes in HDF response for UAS-Gal4>RNAi, we conclude that HDF response in disrupted in Pect and PISD KD (Figure 7).

      We only presented the Lpp-driver in our study, as this driver is the only fat-specific driver that has no leaky expression in other tissues, and is specific to fat as apolpp promoter used to generate this Gal4 line is only expressed in fat tissue (Eaton and colleagues, PMID: 22844248). Other widely used fat-specific drivers, including the pumpless-Gal4 (ppl-Gal4) driver has leaky expression in gut or other tissues (See Table 2 of this detailed study by Dr. Drummond- Barbosa https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642949/). If the reviewer is aware of a fat-specific Gal4 line, other than Lpp-Gal4, which has a highly specific expression in the fat tissue without leaky expression in other tissues, then we are happy to take onboard the reviewer’s suggestion and try that fat-specific Gal4 that they suggest.

      HSD feeding promotes Pect expression (Figure S3C) and global changes in phospholipid levels (Figure 3, 4). Therefore, shouldn't Pect overexpression (not Pect RNAi) in a normal diet mimic HSD feeding state and promote loss of HDF response? Conversely shouldn't knockdown of Pect in HSD rescue loss of HDF response?

      We agree that a puzzling aspect is that Pect mRNA levels are significantly elevated in HSD Day-14, but Pect-KD showed displays the inappropriate HDF response. As we have described in our response to this reviewer on Page 19, we believe that Pect-KD and HSD disrupt PE and LPE balance overall but in different ways. Whereas Pect-OE using cDNA expression in fat body does not cause a significant change to any lipid class (Figure S9), and our results suggest that basally higher level of PECT is likely to be protective on HSD with respect to HDF(Figure 7B).

      To ensure that we appropriately discuss and clarify this issue, we have now included a section in the discussion - Page 14 Lines 26-33- under the subtitle “The implications of relationship between Pect levels and HSD”. We have pasted an excerpt from that subsection below for this reviewers assessment.

      Also, we note that over-expression of Pect cDNA in the fat-body does not alter phospholipid balance (Figure S9) and indeed improves HDF on HSD (Figure 7B). While this may appear inconsistent, it is critical to note that over-expression of Pect cDNA using UAS/Gal4 only increases Pect mRNA expression by 7-fold (Figure S6A), whereas HSD causes its upregulation by 250-fold (Figure S6B). Hence, we speculate that an increased ‘basal’ level of Pect such as by that provided by a cDNA over-expression in fat, may be protective to the negative effects of HSD (Figure 7B) without affecting overall phospholipid levels (Figure S9) , but extreme upregulation Pect on HSD affects the PE and LPE balance (Figure 3).”

      We would have liked to test Pect protein expression on HSD, but since we were unable to access antibodies for Pect published in a prior study (PMID: 33064773) from Dr. Wang’s lab (see Page 10-11, of response to Reviewer #1). Hence, we were unable to test how the proteins levels of Pect correlate with the 250-fold increase mRNA expression.

      In conclusion, we hope the reviewer appreciates that our results regarding Pect function are consistent with the main conclusion that achieving the right phospholipid balance between PE and LPE, is critical for an organism to display an appropriate HDF response.

      Minor comments: All graphs should plot individual data points and showed as box and whisker plot as much as possible.

      Thanks for this suggestion, we have added individual data points to the vast majority of figures in the paper. We have made exceptions to graphs such as seen in figure 1 and FigureS4B-D where we find individual data points add an unnecessary layer of complexity. We hope these changes provide additional clarity and strength to the claims made in this manuscript.

      Data for day 14 missing in Figure S4A and S4B.

      We have provided Day 14 for the PC composition and PE composition, due to changes in Figures, they are now S7A and S7B.

      Reviewer #3 (Significance (Required)):

      The interactions between diet-induced obesity, peripheral tissue homeostasis and feeding behavior is an interesting topic that can be addressed using Drosophila. This manuscript demonstrates how fat body Pect levels affect HSD induced changes in hunger-driven feeding response. However, at this point, the functional association between fat body Pect level, global phospholipid level, and loss of hunger-driven feeding response in chronic HSD feeding is not clear.

      We hope the revised data, and discussion of the paper, provides well-substantiated functional association on the importance of maintaining phospholipid balance, driven by Pect enzyme, as a critical regulator of hunger-driven feeding behavior. As stated in the revised discussion, the key take home message of our manuscript is that on prolonged HSD exposure PC, PE and LPE levels are dysregulated, the loss of phospholipid homeostasis coincided with a loss of hunger-driven feeding. Following this lead on phospholipid imbalance, we then uncovered a critical requirement for the activity of the rate-limiting PE enzyme PECT within the fat tissue in controlling hunger-driven feeding.

    1. Reviewer #1 (Public Review):

      The work, mostly performed in yeast S. cerevisiae, shows that the knockout of DIP2 leads to accumulation in cells of some DAG subspecies (36:0 and 36:1), and also a deficit of similar TAG subspecies (something which mostly occurs, as they showed, in early to mid log growth phase). Accordingly, over-expression of DIP2 leads to the opposite outcome (lower DAG and higher TAG subspecies levels). ∆DIP2 cells showed increased ER stress and UPR, which can be counterbalanced by incubating cells with oleic acid. Moreover, the authors show that the absence of DIP2 causes vacuole fusion defects, which they ascribe to a localization of the protein in the vacuole and possibly to the fact that enhanced levels of DAG in the vacuole membrane can promote vacuole fusion. Although it is true that neither of these claims are fully supported by the experimental results, the data that the authors show serves as a starting point for future, more robust studies to test those claims. Finally, the authors show that the DBD1 domain is not necessary and that the two FLD domains are key for the observed lipid metabolism induced by DIP2 expression. Altogether this manuscript presents interesting new data on an uncharacterized protein that seems to be regulating the metabolism of relatively low abundant DAG/TAG subspecies in cells, and by doing so possibly control cell homeostasis.

    2. Reviewer #3 (Public Review):

      This study examines a family of poorly defined enzymes that contain fatty acyl-AMP ligase like domains (FAALs). The study reveals that these DISCO-interacting protein 2 (DIP2) enzymes are required to maintain a specific pool of diacylglycerol (DAG) lipids containing primarily C36 acyl chain lengths in budding yeast. Using primarily yeast, the study shows that deletion of ScDIP2 significantly increases C36 DAG pools while leaving the more abundant C32 and C34 DAG pools generally unaltered. Triglyceride (TAG) is also reduced in this deletion. Conversely, ScDIP2 over-expression promotes C36 inclusion in TAG. The ScDIP2 KO yeast manifests ER stress that can be relieved by the addition of oleic acid, but not other fatty acids. In the last section of the study, ScDIP2 is proposed to localize to the vacuole and mitochondria, where it maintains a specific DAG pool to enable proper vacuole morphology and fusion, as well as proper osmoregulation of the vacuole.

      This is a well executed study that begins to characterize a conserved and generally poorly understood family of enzymes. However, questions still remain about some of the conclusions of the study. There are two general issues with the study. The first is the specificity of the effect of loss of ScDIP2. The study beautifully shows that loss of ScDIP2 (or its over-expression) affects a specific sub-pool of DAG (mainly the C36 species). TAG levels are also somewhat lower. However, how ScDIP2 impacts other lipid precursors to DAG synthesis such as PA and lyso-PA is under-examined, and should be looked at as they can also affect ER stress. Whether the change in DAG/TAG is primarily driven by decreased synthesis versus increased lipolysis also required additional analysis.

      The second issue relates to how ScDIP2 relates to the yeast vacuole. It is proposed that some of the ScDIP2 enzyme is vacuole localized, and influences vacuole morphology. The evidence presented here does not strongly support that model. From imaging at least, it appears that ScDIP2 is primarily mitochondria localized. It is therefore possible that it influences vacuole lipid composition and morphology distally from the mitochondria. Resolving ScDIP2's native subcellular localization would strengthen the manuscript.

    1. Machine Tags

      A new kind of tags — machine tags — are supported now. A machine tag, e.g. meta:language=python consists of a namespace (meta), a key (language) and a value (python). Everyone can created machine tags, but the meta: namespace is protected and tags in there will be created by the site itself.

      The codesite itself uses machine tags to make various properties of recipes accessible to the search:

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        The programming language of the recipe, e.g. python, perl or tcl.

      • meta:min_$lang_$majorver

        Those tags describe the minimum language version. If a recipe requires Python 2.5 it would have the tag meta:min_python_2=5.

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        The license that was selected by the author, e.g. psf, mit or gpl.

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        This tag contains a number describing the lines of code in a recipes. It counts only the number of lines in the code block but not any lines in the discussion of in comments. This makes it possible to search for short recipes with less than ten lines or very large ones.

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      • meta:requires

        Stores information about additional requirements of the recipes, e.g. required python modules. You can find recipes using python's collections module that way.

      All those tags cannot be changed directly because they are generated from a recipe's properties.

    1. Your JavaScript, for the most part, is run whenever the JS file is run, or when the script tag is encountered in the HTML. If you are including your JavaScript at the top of your file, many of these DOM manipulation methods will not work because the JS code is being run before the nodes are created in the DOM. The simplest way to fix this is to include your JavaScript at the bottom of your HTML file so that it gets run after the DOM nodes are parsed and created.

      Sometimes you want the javascript to run after, so make sure to add "defer" in the <script src"js-file.js" defer></script>

    2. document.createElement(tagName, [options]) creates a new element of tag type tagName.

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      that will NOT put the element in the DOM, it just creates the possibility of it. You gotta put it manually.

    1. SciScore for 10.1101/2022.05.07.491022: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">Contamination: Reagents: Cell lines: All cells were maintained in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% fetal calf serum (FCS), 100 U ml−1 penicillin and 100 mg ml−1 streptomycin and regularly tested and found to be mycoplasma free.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-rabbit IgG, HRP-linked Antibody (7074); Cyclin D3 Mouse mAb (DCS22, 2936); from Cell Signaling.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-rabbit IgG</div><div>suggested: (Cell Signaling Technology Cat# 7074, RRID:AB_2099233)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Goat anti-Mouse IgG (H+L) Cross-Adsorbed Secondary Antibody: Alexa 488 (A-11001), Alexa 594 (A-11032), Alexa 647 (A-21236); Goat anti-Rabbit IgG (H+L) Cross-Adsorbed Secondary Antibody: Alexa 488 (A-11034), Alexa 405 (A-48254); Rabbit polyclonal SARS-CoV-2 Spike (PA1-41165); Rabbit monoclonal SARS-CoV-2 Nucleocapsid (MA5-29982) from Thermo Fisher Scientific.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-Mouse IgG</div><div>suggested: (Thermo Fisher Scientific Cat# A-11001, RRID:AB_2534069)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Rabbit Polyclonal Cyclin A2 antibody (GTX103042); Rabbit Polyclonal Cyclin D1 antibody (N1C3, GTX108824); Rabbit Polyclonal Cyclin E1 antibody (GTX103045); Rabbit Polyclonal Cyclin B1 antibody (GTX100911); monoclonal SARS-CoV-2 Spike (GTX632604) from GeneTex.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Cyclin A2</div><div>suggested: (GeneTex Cat# GTX103042, RRID:AB_1949884)</div></div><div style="margin-bottom:8px"><div>Cyclin D1</div><div>suggested: (GeneTex Cat# GTX108824, RRID:AB_10618686)</div></div><div style="margin-bottom:8px"><div>Cyclin E1</div><div>suggested: (GeneTex Cat# GTX103045, RRID:AB_10731259)</div></div><div style="margin-bottom:8px"><div>Cyclin B1</div><div>suggested: (GeneTex Cat# GTX100911, RRID:AB_1949886)</div></div><div style="margin-bottom:8px"><div>GTX632604</div><div>suggested: (GeneTex Cat# GTX632604, RRID:AB_2864418)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pre-cleared cell lysates were incubated with a-HA magnetic beads, MagStrep beads (IBA-Lifescience, Gottingen, Germany) or anti-cyclin D3 monoclonal antibody (sc-xx) bound Protein G Dynabeads for 1h at 4°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-cyclin D3</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Following cells were a gift from: A549 ACE2/TMPRSS2 40 Massimo Palmerini, Vero E6 ACE2/TMPRSS2 from Emma Thomson, HeLa-ACE2 from James Voss, 293T (a human embryonic kidney cell line, ATCC CRL-3216).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>A549</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">293T GFP11 cells and Vero-GFP10 cells for Split GFP assay were a gift from Leo James41.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T GFP11</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Vero-GFP10</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">293Tv cells were transfected with pEXN-MNCX-Fucci, CMVi and pMD2.G.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293Tv</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids: pBOB-EF1-FastFUCCI-Puro was a gift from Kevin Brindle & Duncan Jodrell (Addgene plasmid # 86849 ; http://n2t.net/addgene:86849 ; RRID:Addgene_86849) 29. pCMV5 cyclin D3 HA was obtained from MRC-PPU Reagents and Services. Rc/CMV cyclin D1 HA was a gift from Philip Hinds (Addgene plasmid # 8948 ; http://n2t.net/addgene:8948 ; RRID:Addgene_8948) 44. pLVX-EF1alpha-SARS-CoV-2-E-2xStrep-IRES-Puro (Addgene plasmid # 141385 ; http://n2t.net/addgene:141385 ; RRID:Addgene_141385); pLVX-EF1alpha-SARS-CoV-2-M-2xStrep-IRES-Puro (Addgene plasmid # 141386 ; http://n2t.net/addgene:141386 ; RRID:Addgene_141386).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_86849)</div></div><div style="margin-bottom:8px"><div>pCMV5</div><div>suggested: RRID:Addgene_15002)</div></div><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_8948)</div></div><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_141385)</div></div><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_141386)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pLVX-EF1alpha-SARS-CoV-2-nsp9-2xStrep-IRES-Puro (Addgene plasmid # 141375 ; http://n2t.net/addgene:141375 ; RRID:Addgene_141375); pLVX-EF1alpha-SARS-CoV-2-N-2xStrep-IRES-Puro (Addgene plasmid # 141391 ; http://n2t.net/addgene:141391 ; RRID:Addgene_141391) were a gift from Nevan Krogan 34. pEXN-MNCX, MLV vector encoding N-terminal double HA tag 45.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_141375)</div></div><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_141391)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pCAGGS_SARS-CoV-2_Spike was obtained from NIBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAGGS_SARS-CoV-2_Spike</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell cycle analysis using fluorescence ubiquitination cell cycle indicator (Fucci): Fucci cassete was cloned from pBOB-EF1-FastFucci-Puro vector to pEXN-MNCX using BamHI/NotI restriction sites.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pEXN-MNCX</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">293Tv cells were transfected with pEXN-MNCX-Fucci, CMVi and pMD2.G.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pEXN-MNCX-Fucci</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pMD2.G</div><div>suggested: RRID:Addgene_12259)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell to cell fusion assay: 293T GFP11 cells were transfected with WT full length Spike, and/or with WT Envelope, Membrane, cyclin D3, and empty vector (pCDNA, to ensure equal amount of transfected DNA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCDNA</div><div>suggested: RRID:Addgene_66792)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Harmony (PerkinElmer, Waltham, MA, USA) and ImageJ software were used to measure MFI for each protein in each region.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell populations positive or negative for SARS-CoV-2 nucleocapsid staining were gated and Cdt1-RFP positive (G1 phase), Geminin-GFP positive (S/G2/M phase), and Cdt1-RFP/ Geminin-GFP positive (early S phase) populations were identified using flow cytometry using LSRFortessa X-20 (BD Biosciences, UK) and FlowJo software (Tree Star, OR, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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

      Learn more at Review Commons


      Reply to the reviewers

      1. General Statements [optional]

      We would like to thank the reviewers for their helpful and constructive comments.

      2. Point-by-point description of the revisions

      Reviewer #1

      This reviewer thought our findings would be of interest to a broad range of scientists from both the centrosome and mitosis fields, but noted some important aspects for improvements.

      Additional Experiments (we number these points for ease of discussion).

        • Figure 3. The reviewer points out that because our analysis of Ana2-∆CC and Ana2-∆STAN mutant proteins was conducted in the presence of endogenous WT protein, we should be more cautious in our interpretation.* We agree and apologise for overstating these findings. We have now rewritten the title and text of this section to be more cautious (p11, para.2)
      1. Figure 5A. The reviewer wonders whether the reduced recruitment of Sas-6 in the presence of Ana2(12A) is due to reduced binding, and they request we test this biochemically. This is our favoured interpretation, but we have been unable to test this biochemically for two reasons. First, although we have successfully purified several recombinant Sas-6 and/or Ana2 fragments (Cottee et al., eLife, 2015), the full-length proteins are poorly behaved (tending to precipitate, likely due to their inherent ability to self-oligomerise). Thus, we have been unable to reconstitute their interaction in vitro*. Second, as we show here, the proteins are normally expressed in embryos at surprisingly low concentrations (~5-20nM), and we can detect no interaction between them in coimmunoprecipitation experiments from embryo extracts (not shown). Indeed, this concentration is so low that Sas-6 does not even appear to form a homo-dimer in the embryo, even though Sas-6 clearly functions as a homo-dimer in centriole assembly (new Figure S4A). We now explain these points, and state that our favoured hypothesis that Ana2(12A) has reduced affinity for Sas-6 (or other core duplication proteins) remains to be tested (p22, para.2).

      2. The Reviewer wonders if all 12 of the potential Cdk1 phosphorylation sites that we mutate in Ana2(12A) are important in vivo, and whether we have tested whether mutating fewer sites (e.g. the two sites [S284/T301] that we show are phosphorylated by Cdk1/Cyclin B in vitro) might be sufficient to recapitulate the Ana2(12A) phenotype. *We have now tested this by mutating just the S284/T301 sites to Alanine [Ana2(2A)], but the results were not very informative (Reviewer Figure 1 [RF1]). Whereas Ana2(12A) is recruited to centrioles for a longer period and to higher levels than WT Ana2 (Figure 4A), Ana2(2A) is recruited to centrioles for a normal period but to lower levels (RF1A,B). The interpretation of this result is complicated because western blots show that Ana2(2A) is also present at lower-levels than normal (RF1B). Thus, it is clear that Ana2(2A) does not recapitulate well the behaviour of Ana2(12A). We have decided not to present this data as it is difficult to interpret and it does not change any of our conclusions.

      3. Figure 6. The reviewer asks whether the 12A mutations impair the interaction with Plk4, influence Plk4’s kinase activity or the ability of Plk4 to phosphorylate Ana2. These are excellent questions but, for the same reasons described in point 2 above, we cannot address them biochemically as we cannot purify well-behaved recombinant full-length Ana2 or active Plk4 in vitro, and both proteins are present at such low levels in the embryo that we cannot detect any interaction between them in embryo extracts. We are working hard to reconstitute in vitro* systems to probe these important points, but it may be sometime before we are able to do so.

      4. Figure 7. The reviewer suggests that the 12D/E phosphomimetic substitutions introduce more negative charge than the putative phosphorylation of Ser/Thr residues and they ask if the Ana2(2D/E) [stated as Ana2(3D/E)] is, like the Ana2(12D/E) mutant, not efficiently recruited to centrioles.* This is a fair comment, but we have not analysed an Ana2(2D/E) mutant because, as described in point 3 above, the Ana2(2A) mutant did not recapitulate well the Ana2(12A) phenotype.

      Minor comments

        • Figure S1. The reviewer requests that we show that the mNG tag on its own is not recruited to centrioles.* We do not show this (as it would create a lot of white space in this Figure), but now state that mNG and dNG do not detectably localise to centrioles (p7, para.1).
        • Figure S4C.* We have included the missing error bars (now Figure S4B).
        • Figure S5A. The reviewer asks about the expression levels of the Ana2(12A) mutant, which are not shown in this Figure. They also state that the expression levels of the transgenes shown in Figure 5A are not similar.* The expression level of Ana2(12A) is shown in Figure S9, as this data was analysed independently of the other mutant proteins shown in Figure S5. We agree that it was overly simplifying the situation to state that the expression levels of WT Ana2-mNG, eAna2(∆CC)-mNG and eAna2(∆STAN)-mNG were “similar” (Figure S5), and we now specifically mention the differences between them (p11, para.3). Reviewer #2

      This reviewer found this a rigorous study that advances our understanding of the regulation of centriole duplication, but raised some minor points.

      Minor Points

      The reviewer requests that we mention the literature describing how Ana2/STIL can influence the abundance and centriolar localisation of Plk4. We apologise for this omission, and have amended our description of this literature in the Introduction to include this point (p3, para.2).

      The reviewer notes that we interpret the ability of the Ana2(12A) mutant to keep incorporating into the centrioles for a longer period as being consistent with our idea that rising levels of Cdk activity during S-phase normally reduce the ability of WT Ana2 to bind to the centriole. They ask us to show how Cdk activity increases over this time-course, and to test whether dampening Cdk has the same effect on Ana2 recruitment (i.e. allows Ana2 to be recruited for a longer period). The time-course of Cdk activation in these embryos has been reported previously (Deneke et al., Dev. Cell, 2016; we present the relevant data from this paper in RF#2A [black line]). This reveals how Cdk activity rises throughout S-phase, which is crucial for our model. To assess the effect of dampening Cdk activity in these embryos we have now analysed the effect of halving the genetic dose of Cyclin B (RF#2B). This perturbation extends S-phase length, but has a complicated effect on the recruitment dynamics of Ana2 (RF#2B). As we would predict, Ana2 is recruited to centrioles for a longer period in these embryos, but it is also recruited more slowly (so it accumulates to lower levels). This is consistent with our hypothesis that Cdk1 activity might first stimulate and then ultimately inhibit the centriolar recruitment of Ana2. The interpretation of this experiment is not straightforward, however, as dampening Cdk1 activity alters Ana2 recruitment dynamics (and many other processes in the embryo) in complicated ways, so we have decided not to include it in the manuscript.

      The reviewer suggests that it would be valuable to show that all 12 of the potential Cdk1 phosphorylation sites in Ana2 can be phosphorylated by Cdk1 in vitro. We think this would not be particularly informative as our hypothesis does not rely on all 12 sites being phosphorylated to generate the Ana2(12A) phenotype. We simply mutate all 12 sites because we don’t know which, if any, are relevant. Thus, showing that some/all of the 12 sites can/cannot be phosphorylated in vitro does not test any hypothesis and would not change any of our conclusions. We now explain our thinking on this in more detail (p12, para.2)

      Other points

      Figure 3. We have corrected the amino-acid numbering mistakes.

      Figure 5Aii. We have changed the x-axis (time) labelling in this and all other Figures.

      Figure Legends. We have tried to eliminate the typos from the Figure legends, and apologise that these errors made it through to the final submitted version of our manuscript.

      Reviewer #3

      This reviewer thought our manuscript would be of great interest to not only the centrosome field but also to cell biologists more generally. Although they had no major concerns, they made a number of suggestions for improvements.

      1. As the reviewer suggests, we now explicitly state that although the Ana2(12A) mutant appears to be largely functional, the overall conformation of the protein may be altered, changing its function in ways we do not appreciate (p21, para.2).

      2. The reviewer suggests we include a multiple sequence alignment of Ana2/STIL proteins to provide more context about the distribution and conservation of the 12 S/T-P sites mutated in Ana2(12A).* This is an excellent idea, and we now include this in a new Figure S6, where we also provide more information about which of these sites have been shown to be phosphorylated in embryo or S2-cell extracts

      3. The reviewer is confused as to why the 12A and 12D/E mutants rescue the ana2-/- mutant flies so well, which suggests that the mechanism we propose here cannot be essential for centriole duplication. We understand this confusion and we now make this point more clearly and explain why we think this occurs in more detail (e.g. p22, para.1). We propose that Cdk normally phosphorylates Ana2 to inhibit its ability to promote centriole duplication, but this phosphorylation does not entirely block this function. So, if all other elements of the system are functional, Ana2(12A) is recruited to centrioles for longer than normal, but this does not dramatically perturb centriole duplication because the many other factors that regulate centriole duplication (such as the pulse of Plk4 recruitment to centrioles [Aydogan et al., Cell, 2020]) still occur normally and are sufficient to ensure that centrioles still duplicate normally. When Ana2 phosphorylation is mimicked [Ana2(12D/E)], the ability of Ana2 to promote centriole duplication is perturbed (but not abolished). This perturbation is lethal in the early embryo—where the centrioles must duplicate in just a few minutes to keep pace with the rapid nuclear divisions. In somatic cells S-phase is much longer, so these cells can still duplicate their centrioles (as we observe) even though Ana2(12D/E) does not function efficiently. As we now explain, this phenotype (being lethal in the early embryo, but not in somatic cells) is a common feature of mutations that influence the efficiency* of centriole and centrosome assembly (p17, para.2).

      4A. The reviewer asks us to comment in more detail on why centrioles do not seem to be elongated in the Ana2(12A) mutant wing disc cells (now Figure S8C), even though we show that Ana2(12A) (Figure 4A), and also Sas-6 (Figure 5), are recruited to centrioles for an abnormally long period. This is an excellent question and, although we do not know the answer, we now discuss this interesting point in more detail (p16, para.1). We think this is likely due to the “homeostatic” nature of centriole growth: in our hands, almost any perturbation that makes centrioles grow for a longer/shorter period, also makes them grow more slowly/quickly, so that they tend to grow to a similar size (Aydogan et al., JCB, 2018; Cell, 2020). This is fascinating, but poorly understood. When we perturb the system by expressing Ana2(12A), both Ana2(12A) and Sas-6 incorporate into centrioles for a longer period, as we predict (Figure 4A and 5A). Unexpectedly, however, Sas-6 is also recruited to centrioles much more slowly. Thus, as so often happens, when we perturb the system so the centrioles grow for a longer time, the centrioles “adapt” by growing more slowly. We do not currently understand why this occurs (although we speculate that Ana2 may also be regulated by Cdk/Cyclins to help recruit Sas-6 to centrioles in early S-phase). In the embryo, where S-phase is very short, this homeostatic compensation is not perfect, and the centrioles appear to actually be shorter than normal. In somatic wing-disc cells, where S-phase is much longer, we suspect that there is more scope for homeostatic compensation and so the centrioles grow to the correct size.

      4B. In this point (also labelled [4] by the reviewer, so we have retained this numbering but labelled the points A and B) the reviewer asks why levels of Ana2(12A) eventually decline at centrioles once the embryos actually enter mitosis. The reviewer notes our rheostat theory, but suggests a discussion of other mechanisms might be interesting. This is a good point, and we agree that the observation that Ana2(12A) levels ultimately still decline at centrioles during mitosis is likely to be important in explaining why centriole duplication is not more dramatically perturbed by Ana2(12A). We now expand our discussion of this point, highlighting that other mechanisms must help to ensure that Ana2 is not recruited to centrioles during M-phase, and discussing the possibility that the receptors that recruit Ana2 to centrioles are themselves inactivated during mitosis by high levels of Cdk activity (p15, para.1). In such a model, the rapid drop in WT Ana2 centriolar levels is due to a combination of switching off Ana2’s ability to bind to centrioles (as we propose here) and switching off the ability of the centrioles to recruit Ana2. For Ana2(12A), only the latter mechanism would operate, so Ana2(12A) levels would start to drop later in the cycle (as the inflexion point at which Ana2 recruitment and loss balances out would be moved to later in the cycle), and these levels would drop more slowly—as we observe.

      • The reviewer is confused to how the Ana2(12D/E) mutant can rescue the mutant phenotype when it is recruited to centrioles so poorly. Ana2(12D/E) is indeed recruited very poorly to centrioles in the experiment shown in Figure 7. However, this experiment had to be conducted in the presence of WT untagged Ana2—as the embryos do not develop in the presence of only Ana2(12D/E). We would predict that WT Ana2 would bind more efficiently to centrioles than Ana2(12D/E) (which appears to behave as if it has been phosphorylated by Cdk/Cyclins, and so cannot be recruited to centrioles efficiently). Thus, in the experiment we show in Figure 7, the Ana2(12D/E) protein is probably being “outcompeted” for binding to the centriole by the WT protein. In somatic cells expressing only* Ana2(12D/E) presumably sufficient mutant protein can be recruited to centrioles to support normal centriole duplication (as it no longer has to compete with the WT protein). We now explain our thinking on this point (p18, para.1).

      • The reviewer wonders whether Ana2(12D/E) may be unable to homo-oligomerize, and this may explain why the protein is not recruited to centrioles efficiently even in the presence of WT protein. This is indeed a possibility, but we think it unlikely as it is widely believed that Ana2/STIL proteins must multimerize to be functional (Arquint et al., eLife, 2015; Cottee et al., eLife, 2015; Rogala et al., eLife, 2015; David et al., Sci. Rep., 2016). As Ana2(12D/E) strongly restores centriole duplication in ana2-/-* mutant somatic cells, it seems unlikely that it cannot multimerize. Nevertheless, we now specifically highlight that the 12D/E (and 12A) mutations might alter the ability of Ana2 to multimerise (p21, para.2).

      We thank the reviewers again for their thoughtful and constructive comments. We hope they will agree that the revised manuscript is now improved and would be appropriate for publication in The Journal of Cell Biology.

      With best wishes,

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

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      Referee #1

      Evidence, reproducibility and clarity

      Centriole duplication is a conserved pathway that need to be tightly regulated. The key enzyme of centriole assembly is Plk4 which is recruited to the centrioles and undergoes dynamic re-localization from a ring-like pattern around a centriole to a dot-like morphology at the daughter centriole assembly site. This event is central for inducing centriole biogenesis. Plk4 then phosphorylates Ana2/STIL which allows recruitment of Sas-6 to form the cartwheel structure for centriole assembly.

      In the present study, Steinacker, Wong et al. monitor how cytoplasmic concentrations of the key proteins in centriole assembly, Plk4, Asl/Cep152, Ana2/STIL, Sas-6 and Sas-4/CPAP change during the centriole assembly process in the Drosophila embryo by using fluorescence correlation spectroscopy (FCS) and Peak Counting Spectroscopy (PeCoS). They find that their concentrations remain constant with exception of Ana2/STIL of which cytoplasmic diffusion rate increased at the end of S-phase and is dependent on phosphorylation by Cdk1/CyclinB. Phosphorylated Ana2/STIL blocks centriole duplication thus preventing premature initiation of centriole duplication in mitosis.

      Major comments

      The manuscript is interesting and very well written. Most of the experiments are carefully performed. However, there are some important aspects for improvements that are listed below

      Additional experiments:

      • Figure 3: the transgenic flies that were generated here, CC and STAN, still contain wild-type Ana2. So, the authors therefore need remove or dampen their claim that the change in Ana2's cytoplasmic diffusion does not depend on its interaction with Sas-6 (page 11).
      • Figure 5A: is the observed reduced recruitment of Sas-6 by Ana2(12A) due to a decrease in binding affinity? This should also be shown by analyzing protein-protein interactions between Ana2(12A) and Sas-6 biochemically.
      • The authors use an Ana2(12A) mutant which comprises putative Cdk1 phosphorylation sites that have been identified in Mc Lamarrah et al. JCB 2018. However, only three of them were phosphorylated by Cdk1/cyclin B in vitro (Fig. S6). Are all these 12 putative Cdk1 phosphorylation sites important in vivo? Did the authors generate the Ana2(3A) or the S284A/T301A mutants to see whether it can rescue the ana2-/- mutant phenotype similar to the 12A mutant? These might be sufficient to observe the phenotype.
      • Figure 6: is the interaction between Plk4 and Ana2(12A) impaired? Similarly, Plk4 activity and phosphorylation of Ana2(12A) by Plk4
      • Figure 7: Phosphomimetics, in this case 12 amino acid changes, have the disadvantage of introducing more negative charge than the phosphorylated residue. The Ana2/(12D/E)-mNG is not efficiently recruited to centrioles. Is effect also observed for the Ana2/(3D/E) mutant?

      Minor comments

      Figure S1: only mNG-tagged centriolar proteins are shown. An empty mNGtag or an mNG-tagged non-centriolar protein should be shown to exclude that the tag by itself shows centriolar localization or somehow affects the localization

      S4C: Sas6-mNG CPM error bars are missing for the 10min time point

      S5A: What are the expression levels of the Ana2(12A) mutant? The expression levels shown in this Figure are not similar.

      Significance

      Centriole duplication normally begins at the G1/S phase transition. An important question in the field is how premature centriole duplication in mitosis is prevented. The authors used fluorescence correlation spectroscopy (FCS) and Peak Counting Spectroscopy (PeCoS) to study the major conserved proteins in the centriole assembly pathwayq and found that only Ana2/STIL's cytoplasmic diffusion increases at the end of S-phase. It is known from the literature that Cdk1 prevent Plk4-STIL complex assembly in centriole biogenesis by directly competing with Plk4 for the CC domain of Ana2/STIL (Zitouni et al. Curr Biol 26, 1127-1137 (2016). However, Ana2/STIL can also bind to Plk4 via its conserved C-terminal region of STIL (Ohta et al., Cell Reports 11, 2018; McLamarrah et al., J Cell Biol 2018, 217, 1217-1231). The work by Steinacker, Wong et al. suggest that at least in fly embryos, growth of the daughter centriole is regulated though phosphorylation of Ana2 by Cdk1/CyclinB rather than binding. The findings described in this manuscript are interesting for a broad range of scientists from both the centrosome and mitosis fields

      Expertise of the reviewer: centriole biogenesis, structural and numerical centrosomal aberrations in disease

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

      Learn more at Review Commons


      Referee #1

      Evidence, reproducibility and clarity

      In this manuscript, Dantas and colleagues report that confinement is sufficient to restore G2/M transition in cells than can't adhere to their matrix. Exploring further the mechanisms involved, they show that confinement (dynamic cell compression) stimulates nuclear import of cyclin B1 and nuclear envelope permeability using cells in 2D culture. The authors observed that actomyosin contractility increases NE tension in cells preparing for prophase, leading to an increase in nuclear translocation of cyclin B1. However, a few inconsistencies between the data and the conclusion make the current report too preliminary for publication. It may require significant additional work to consolidate the authors' model.

      • The specific contribution of Nuclear Envelope tension. The authors conclude that confinement acts through increasing NE tension, although confinement may affect cytoplasmic signaling, which could contribute to G2/M transition. The authors should test whether compressing the nucleus versus compressing the cytoplasm have distinct effects on cyclin B1 nuclear translocation and G2/M, as it has been done by others when addressing nuclear mechanosensitive mechanisms (Elosegui-Artola et al. or Lomakin et al.). To consolidate their model, the authors should also test whether decreasing NE tension (independently of actomyosin tension) has opposite effect on G2/M (for example using LBR overexpression). Increase in nuclear membrane tension has been shown to trigger cPLA2 recruitment to the NE (Enyeidi et al, 2013; Lomakin et al. 2020), although the authors show here that confinement does not induce cPLA2 recruitment (but still increases NE tension figure 4G) in the absence of Rock activity or when the LINC complex is disrupted. This is surprising considering that confinement should increase NE tension independently of actomyosin contractility and should increase cPLA2 recruitment at the NE, unless in this case cPLA2 recruitment is not mediated by an increase in NE tension.
      • NPC transport versus NE permeability. The authors suggest that confinement increases cyclin B1 transport via NPC-mediated transport and rule out that confinement may affect NE permeability based on the absence of NE rupture using the INM marker lap2. However, the sample size for this observation is missing and NE permeability could be altered even in the absence of major INM rupture observed by confocal. The authors should use a reporter of nuclear permeability (fluorescent cytoplasmic marker or nuclear marker as previously used by Denais et al or, 2016 or Raab et al., 2016) to make sure that NE permeability is not affected by confinement. In addition, NPC function should be tested in parallel with other fluorescent reporter (such as NLS-GFP constructs) to test whether global NPC-mediated transport is changed during prophase (with or without confinement).
      • Effect of confinement on cyclin B transport (NEP) in adherent cells. In figure 1D, we can see that confinement enhances cyclin B1 nuclear translocation in cells adhering on fibronectin. Although it is unclear whether confinement has a significant effect in other figures, for example in figure 2F: DMSO is not significantly different from confiner+CDKi (same thing in 3i and 3j with Rock inhibitor and Kash construct). In these figures the untreated+confiner (or control in 3j) is missing, and the absence of difference between treated+confiner and control is puzzling. Either there is no difference between confiner and CDKi+confiner and it means there is no difference between control and confiner (surprising considering figure 1D); or there is a difference between CDKi+confiner and confiner, indicating that CDK inhibition affects confinement-induced cyclin B import. Both possibilities suggest that the authors should significantly revisit their model. In any case, all control (untreated, treated +/- confiner should be in all figures to avoid any misunderstanding).
      • Consequences of cPLA2 recruitment at the NE. The authors state that "Active cPLA2 then stimulates actomyosin contractility creating a positive feedback loop" But the NE is already unfolded and distance between NPR is increased before cPLA2 recruitment. Does PLA2 inhibition affect nuclear irregularity (or distance between NPC)? Or does cPLA2 impact cyclin B1 transport via a distinct mechanism? Did the author analyze CDK1 phosphorylation in presence of PLA2 inhibitor?
      • Robustness of the main observation. On page 4, the authors report that cells enter mitosis after 140 sec (+/- 80 sec) of confinement, although in the example showed in figure 1b, the cell enters at least 420 sec min after confinement, as we can see that the cell is already confined -420 sec (compressed shape) and NEP occurs at 0. Did the author showed a cell that was not included in their statistics? This would be very surprising considering the very low sample size used for this experiment (n=6 and 10). In addition, many observations have been made on small sample size (n=6 for figure 1) or/and not from independent experiments. The authors should increase their sample size and compare results from independent experiments to consolidate their model.
      • 2h shows nuclear signal (cyclin in grayscale), while 2e does not, why?
      • starting point to quantify cyclin entry is the lowest intensity, which may depend on many factors (and could be affected by experimental design). It would be necessary to have synchronized cells to homogenize the starting point of these experiments.
      • DN-KASH have been transiently transfected for single cell experiments, how does the authors unsure that cell observed are transfected? Does it have a fluorescent tag, if so which one?
      • "requires contact with external stimuli" or "that mechanical confinement is sufficient to overcome the lack of external stimuli." (page 4): external stimuli is vague here and it could be better to replace it with a more specific description

      Significance

      While the physiological relevance of these findings remain to be determined, the authors report an interesting observation that could have a significant impact in the field. The authors do not comment the potential overlap of their findings with other reports involving the LINC complex (Booth et al., ELife) or CDK-mediated actin remodeling (Ramanathan et al., NCB 2015) during prophase.

    1. Reviewer #3 (Public Review):

      Four decades after the seminal work of the Schekman's lab on the genetic identification of the core eukaryotic secretory machinery the molecular roles of the individual components have been largely characterized. Yet our understanding of how these components are organized to define processes is wanting, with notable controversies still hovering over at several levels of the secretory pathway, including the events that take place in the ER/Golgi interface, the transit across the Golgi, the biogenesis of secretory vesicles and the delivery, tethering and docking of these vesicles to the membrane. This manuscript mostly addresses the latest steps of this chain of events and makes some incursions into the biogenesis of vesicles at the TGN. It represents a serious and honest attempt to define the timeline of events that, driven by key components such as the Sec4 ras-in-brain (Rab) GTPase, its effectors myosin-5, Sro7 and the exocyst, its GEF, Sec2 and the prototypic Sec/Munc protein Sec1, a regulator of trans-SNARE complex formation, ultimately result in the tethering, docking and fusion of vesicles with the membrane of the polarized bud of the ascomycete yeast Saccharomyces cerevisiae. Tethering, as defined by light microscopy appears to be a robust process reproducibly lasting for five seconds, before fusion, as defined by the loss of vesicle components, takes place. Important evidence is provided that the exocyst is incorporated as an holo-complex to secretory vesicles. Overall, even though this work will likely suffer modifications and amendments as knowledge and technology progress, it will nevertheless become the reference blueprint around which any future work in the field will pivot.

      This work represents a very substantial advance in the field of exocytosis. Besides reporting with unmatched time resolution the tethering of vesicles with the membrane, it describes a herculean effort to gain mechanistic understanding of the process by using a score of genetic perturbations and fluorescent reporters. I feel that evidence that Sec3 travels with the exocyst rather than contributing a milestone for exocyst landing will be disputed, but this referee finds it as convincing as appealing. Nearly as important is the timing of Sec1 action in the fusion step. However, it is the delineation of a timeline that will make this paper a reference in the field.

      Understanding the technology for image acquisition is critical to appreciating the strengths of this MS (333 ms/Z-stack time point may be considered super-resolution - in the time dimension. Therefore, its description requires clarification in places. The experimental work is almost exclusively based on live microscopy using fluorescent proteins tagged by allelic replacement. The microscopy routine for single fluorophore analysis provides time series with a resolution of 3-5 fps that enables authors to resolve, using robust statistical tests, events separated by seconds. In this context, it is notable that dual-channel imaging appears to be made by sequential, not simultaneous, acquisition, which deserves a currently missing comment. Moreover, given the weight that image acquisition plays in this project, it might be described and justified better. The Materials and methods lack detail, for example, the laser lines & power used for excitation. This referee could not fully understand the routine of image acquisition, specifically, the continuous movement of the stage in the Z-axis as images are streamed (to the RAM or to the disk? the latter takes time, line 177); does it mean that Z-stepping is solely governed by the exposure time? The CCD camera penalizes pixel size (16 µm) at the expense of achieving outstanding quantum efficiency. The optical path includes a 100x objective and a 2x magnification lens to compensate for the large camera pixel size, thereby achieving 0.085 µm/pixel, but these lenses 'waste' part of the fluorescent signal. One wonders if the CMOS camera (6.5 µm pixel size) coupled with a 63x objective wouldn't be appropriate? A brief discussion on this choice would be helpful for readers.

      There is an elephant in the room of in vivo microscopy that no one dares to comment on: reporter proteins are mutant versions carrying a heavy and potentially oligomerising rucksack - the fluorescent protein tag. The authors take the honest approach of acknowledging that some of the tagged proteins such as Sec4 are disfunctional and that certain reporters are incompatible with each other as they give rise to synthetic negative effects. In the end, they conclude that using diploids carrying the GFP-tagged allele in heterozygosis with the wt represents the most physiological approach to track proteins until less intrusive fluorescent tags are developed.

      It is remarkable that Sec2 and Sec4 are recruited to membranes even before a vesicle is formed (Fig 6I). I find somewhat weak the evidence that RAB11s 'mark' the TGN, and disturbing the fact that RAB11 reaches the PM (does GFP tagging prevent GAP accession?). I should like to recommend strongly that the authors integrate into the introduction/discussion information on the late steps of exocytosis available for Aspergillus nidulans, another ascomycete that is particularly well suited for studying this process. Here RAB11 is not a late Golgi resident but is transiently (20 s) recruited to TGN cisternae in the late stages of their 120 s maturation cycle to drive the transition between Golgi and post-Golgi (Pantazopoulou MBoC, 2014). Recruitment of RAB11 to the TGN is preceded by the arrival of its TRAPPII GEF (Pinar, PNAS 2015; Pinar PLOS Gen 2019), a huge complex that is incorporated en bloc to the TGN (Pinar JoCS, 2020). Upon RAB11 acquisition RAB11 membranes engage molecular motors (Penalva, MBoC 2017) to undertake a several-micron journey that transports them to a vesicle supply center located underneath the apex (review, Pinar & Penalva, 2021). Here is where Sec4 is located, strongly indicating that there is a division of work between two Rabs each mediating one of the two stages between the TGN and the membrane (Pantazopoulou, 2014, MBoC).

    1. SciScore for 10.1101/2022.05.03.22274395: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: PCR confirmed and clinically suspected severe COVID-19 cases admitted to hospital were recruited into the DISCOVER study at North Bristol NHS Trust for which HRA Approval was granted by the South Yorkshire Research Ethics Committee (20/YH/0121).<br>Consent: All samples were used in accordance with the Human Tissue Act (2004) with appropriate consent and ethical approvals in place.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">Blinding of validation set: The validation set of samples (n=807) were split into multiple aliquots (n=5) for randomisation and blinding by assigning a new barcode ID for each aliquot.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">Blinding of validation set: The validation set of samples (n=807) were split into multiple aliquots (n=5) for randomisation and blinding by assigning a new barcode ID for each aliquot.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Purified proteins were analysed by SDS-PAGE and by Western-blots assays using an anti-His tag antibody (Sigma).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-His tag</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washing, HRP-conjugated anti-human Pan-Immunoglobulin (Pan) (Sigma), IgG (Southern Biotech), IgA (Sigma) or IgM (Sigma) secondary antibody, in the same dilution buffer as the samples, was added (50 µl per well) and incubated for 1 hour.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgG ( Southern Biotech)</div><div>suggested: (SouthernBiotech Cat# 1050-01, RRID:AB_2737431)</div></div><div style="margin-bottom:8px"><div>IgA ( Sigma )</div><div>suggested: (Sigma-Aldrich Cat# I1010, RRID:AB_1163625)</div></div><div style="margin-bottom:8px"><div>IgM ( Sigma ) secondary antibody</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>IgM</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Roche SARS-CoV-2 anti-nucleocapsid antibody assay: Serum samples from PCR-confirmed cases were analysed using the commercial Elecsys® Anti-SARS-CoV-2 (Roche) in the Department of Microbiology, Infection Sciences, Southmead Hospital, North Bristol NHS Trust, Southmead Road, BS10 5NB, UK following manufacturer’s instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-nucleocapsid</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Anti-SARS-CoV-2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Transfected 293T cells were then infected with VSV*G-FLuc particles for 2 hours, washed with PBS, then incubated with fresh DMEM, supplemented with 10% FBS and 1:2000 (v/v) I1 (anti-VSV-G) antibody (absolute antibody Ab01401-10.3).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>I1</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-VSV-G</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">VSV-G-harbouring BHK21 cells were infected with VSV*ΔG- FLuc particles to generate complemented VSV*G-FLuc particles as previously described (35).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BHK21</div><div>suggested: ATCC Cat# CRL-6281, RRID:CVCL_1914)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">, 293T cells were seeded and transiently transfected with a plasmid corresponding to the original Wuhan strain Spike protein (pCAGGS-S2-spike) using Turbofect transfection reagent (ThermoFisher R0532) for 16 hours following the manufacturer’s instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Optimal pseudotype cell entry was achieved using VeroE6 cells stably expressing the human angiotensin-converting enzyme 2 (ACE2) receptor and the cell surface protease TMPRSS2 (Vero ACE2 TMPRSS2 (VAT) cells, which were a kind gift from Dr Suzannah Rihn, MRC-University of Glasgow Centre for Virus Research (36)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VeroE6</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div><div style="margin-bottom:8px"><div>Vero ACE2</div><div>suggested: RRID:CVCL_A7UJ)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sequence was synthesized with an NdeI restriction site at the 5’ end and the BamHI site at the 3’ end and cloned into pET28a expression vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET28a</div><div>suggested: RRID:Addgene_139598)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The recombinant plasmids (pET28a-NP-FL) were transformed into E. coli strain BL21 (DE3)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET28a-NP-FL</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">, 293T cells were seeded and transiently transfected with a plasmid corresponding to the original Wuhan strain Spike protein (pCAGGS-S2-spike) using Turbofect transfection reagent (ThermoFisher R0532) for 16 hours following the manufacturer’s instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAGGS-S2-spike</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Images were acquired on the ImageXpress Pico Automated Cell Imaging System (Molecular Devices) using a 10X objective and infected cells detected and quantified using Cell ReporterXpress software (Molecular Devices).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Cell ReporterXpress</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical Analysis: Data analyses were performed using either R software with R Studio, and GraphPad Prism (version 9) as detailed below.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">However, sample readouts using other methods including interpolated unit values (from a 4- parameter logistic regression model fit (on Prism or within BMG software) to the 7- point standard pool dilution series) and AUC from sample dilution series were used in the development stage.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:


      Strengths of this study include rigorous development of high performance, low blood volume, cost-effective tests which can be easily deployed in a variety of settings, but our approach also has several limitations. Firstly, whilst samples from pre-pandemic children were included, samples from children with COVID-19 were not available to us and as such, assay performance for detecting recent paediatric infections cannot be reported. However, since widespread vaccination of children is not currently common in many countries while asymptomatic/mild paediatric infections are, antibody assays offer a useful tool for monitoring infection in this age group. The antigens used in the in-house assays were generated using the genetic sequence from the parent Wuhan strain of SARS-CoV-2 first described in 2020 (7) from which several new variants of concern (VOC) have evolved and have caused significant waves of infection globally. Some of these variants, especially Omicron, include multiple mutations in these target antigens and as such, may lead to antibody responses with differential binding to the target antigens. Indeed, antibodies responses raised to antigens from one SARS-CoV-2 variant genetic sequence lead to differential ability to neutralise VOC strains. However, whilst others have shown reduced binding to antigens from sequences of VOCs, rates of seropositivity when using different antigens, and/or from people who were infected with non-Wuhan variants, appear to be relatively un...


      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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    1. 7.1.2 Forwarding from Inbox Note: Forwarding to avoid the ghost replies problem The following section is to mitigate the "ghost replies" problem which occasionally causes problems on federated networks. This problem is best demonstrated with an example. Alyssa makes a post about her having successfully presented a paper at a conference and sends it to her followers collection, which includes her friend Ben. Ben replies to Alyssa's message congratulating her and includes her followers collection on the recipients. However, Ben has no access to see the members of Alyssa's followers collection, so his server does not forward his messages to their inbox. Without the following mechanism, if Alyssa were then to reply to Ben, her followers would see Alyssa replying to Ben without having ever seen Ben interacting. This would be very confusing! When Activities are received in the inbox, the server needs to forward these to recipients that the origin was unable to deliver them to. To do this, the server MUST target and deliver to the values of to, cc, and/or audience if and only if all of the following are true: This is the first time the server has seen this Activity. The values of to, cc, and/or audience contain a Collection owned by the server. The values of inReplyTo, object, target and/or tag are objects owned by the server. The server SHOULD recurse through these values to look for linked objects owned by the server, and SHOULD set a maximum limit for recursion (ie. the point at which the thread is so deep the recipients followers may not mind if they are no longer getting updates that don't directly involve the recipient). The server MUST only target the values of to, cc, and/or audience on the original ob

      Here's where things get spicy

    1. SciScore for 10.1101/2022.05.04.490614: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Staining antibodies are as follows (Hu Fc Block Pure Fc1.3216 (BD, Cat# 564220), APC anti-HLA-ABC (Thermofisher, Cat# 17- 9983-42), APC/Cy7 anti-HLA-DR (BioLegend, Cat# 307618), PE anti- DYKDDDDK Tag (BioLegend, Cat# 637309), AF488 anti-SARS-CoV-2 Spike S1 Subunit (R&D Systems,Cat# FAB105403G), FITC anti-Influenza A NP (Thermofisher, Cat# MA1-7322), PE anti-mouse CD45 (BioLegend, Cat# 109808), BV421 anti-mouse CD31 (BioLegend, Cat# 102423), APC anti-mouse EpCAM (BioLegend, Cat# 118213), PerCP/Cy5.5 anti-H-2Kb/H-2Db (BioLegend,Cat# 114620)).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-HLA-ABC</div><div>suggested: (Thermo Fisher Scientific Cat# 17-9983-41, RRID:AB_10753773)</div></div><div style="margin-bottom:8px"><div>anti-HLA-DR</div><div>suggested: (BioLegend Cat# 307618, RRID:AB_493586)</div></div><div style="margin-bottom:8px"><div>anti-SARS-CoV-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-Influenza</div><div>suggested: (Thermo Fisher Scientific Cat# MA1-7322, RRID:AB_1017747)</div></div><div style="margin-bottom:8px"><div>anti-H-2Kb/H-2Db</div><div>suggested: (BioLegend Cat# 114620, RRID:AB_2750200)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids: pDONR207-SARS-CoV-2 E (#141273), pDONR207-SARS-CoV-2 M (#141274), pDONR207-SARS-CoV-2 ORF7a (#141276), pDONR223-SARS-CoV-2 ORF7b (#141277), pDONR223-SARS-CoV-2 ORF8 (#141278) were purchased from addgene (Kim et al., 2020) and used as templates for construction of plasmids expressing SARS-CoV-2 viral proteins.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pDONR207-SARS-CoV-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pDONR223-SARS-CoV-2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For HIV Nef expressing plasmid construction, NL4-3-dE-EGFP (kindly provided by Dr. Ya-Chi Ho) was used as a template.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>NL4-3-dE-EGFP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For construction of plasmids expressing SARS-CoV viral proteins, oligonucleotides corresponding to both strands of SARS-CoV Tor2 (GenBank accession: NC_004718.3) ORF8a and ORF8b containing XhoI and BamHI sites at the 5’ and 3’ ends were synthesized (IDT) and cloned into XhoI-BamHI site of c-Flag pcDNA3 vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3</div><div>suggested: RRID:Addgene_15475)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To investigate the prevalence of amino acid mutations, we downloaded up to 965 sequences of each lineage and aligned the ORF8 nucleotide sequences using Jalview software (http://www.jalview.org/) (Waterhouse et al. Bioinformatics. 2009) by MUSCLE algorithm (Edgar RC.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Jalview</div><div>suggested: (Jalview, RRID:SCR_006459)</div></div><div style="margin-bottom:8px"><div>MUSCLE</div><div>suggested: (MUSCLE, RRID:SCR_011812)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">FlowJo software (Tree Star) was used for the data analysis.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.05.03.490428: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: Human convalescent serum samples: Human convalescent serum samples from recovered COVID-19 patients were obtained from Public Health Clinical Center of Chengdu in Chengdu, China, under approved guidelines by the Institutional Review Board (IRB), and all patients had provided written informed consent before serum sample were collected.<br>Consent: Human convalescent serum samples: Human convalescent serum samples from recovered COVID-19 patients were obtained from Public Health Clinical Center of Chengdu in Chengdu, China, under approved guidelines by the Institutional Review Board (IRB), and all patients had provided written informed consent before serum sample were collected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Animal studies, facilities and ethics statements: Specific pathogen-free (SPF) BALB/c female mice (6-8 weeks old) for immunogenicity studies were purchased from Charles River Experimental Animals Co.,</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Serum was collected on D35 (2 weeks PD2), D56 (Day of 3rd dose boost), D85 (1 month post dose 3), D113 (2 months post dose3) and D141 (3 months post dose 3) for pseudovirus neutralizing antibody test.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>D56</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>D85</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>D113</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>D141</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudovirions were produced by co-transfection HEK 293T cells with psPAX2, pLVX-AcGFP-N1-Fluc, and plasmids encoding various S genes by using Lipofectamine 3000 (Invitrogen, L3000-015).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK 293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudoviruses stock were titrated by infecting 293T-ACE2 cells and luciferase activity was determined following a 44-48 h incubation period at 37°C and 5% CO2 by addition Bright-Glo Luciferase Assay System (Promega, E2650) using a microplate reader (TECAN, Spark).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T-ACE2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For three dose boost study, Balb/c mice, female (n=10/group) prime and boost with SCB-2019 3 μg adjuvanted with 75 μg alum plus 150 μg CpG 1018 twice on Day 0 and Day 21, then boosted with 3 μg SCB-2019, or SCB-2022B or Bivalent adjuvanted with 75 μg alum plus 150 μg CpG 1018 on Day 57 via intramuscular injection.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Balb/c</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cDNA was subcloned into pTRIMER expression vector (GenHunter Corporation) at Hind III and Bgl II sites to allow in-frame fusion of the soluble S protein to Trimer-Tag (amino acid residue 1156-1406 from human Type I(α) collagen).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pTRIMER</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudovirus construction and production: The variants of concern of SARS-CoV-2 spike protein genes were optimized using mammalian codon and synthesized by Genscript, then cloned into pcDNA3.1(+) eukaryotic expression vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudovirions were produced by co-transfection HEK 293T cells with psPAX2, pLVX-AcGFP-N1-Fluc, and plasmids encoding various S genes by using Lipofectamine 3000 (Invitrogen, L3000-015).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>psPAX2</div><div>suggested: RRID:Addgene_12260)</div></div><div style="margin-bottom:8px"><div>pLVX-AcGFP-N1-Fluc</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analysis: Data arrangement was performed by Excel and statistical analyses were performed using the Prism 9.2.0 (GraphPad Software).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Excel</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04405908</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Completed</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">SCB-2019 as COVID-19 Vaccine</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04672395</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">A Controlled Phase 2/3 Study of Adjuvanted Recombinant SARS-…</td></tr></table>


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. The only reasonable implementation options are JavaScript and PHP.

      I argue that PHP is not reasonable here. The only appropriate thing for this use case is (unminified) JS—or some other program text encoded as a document resource permitting introspection and that the user agent just happens to be able to execute/simulate.*

      • Just like the advocates of "a little jQuery", author here doesn't seem to realize that the use of PHP was the first step towards what is widely acknowledged to be messed up about the "modern" Web. People can pine for the days of simple server-side rendering, but there's no use denying that today's Web is the natural result of an outgrowth that began with abuses of the fundamental mechanisms underpinning the Web—abuses that first took root with PHP.

      * Refer to the fourth and sixth laws of "Sane Personal Computing, esp. re "reveals purpose"

    2. how does one support comments? Answer: Specialist third-party services like Disqus come into existence. Now, you can have comments on your website just by adding a <script> tag, and not have to traverse the painful vertical line of making your website itself even slightly dynamic.

      Controversial opinion: this is actually closer to doing the Web the way that it should be done, taking the intent of its design into account. NB: this is not exculpatory of minified JS bundles (where "megabyte" is the appropriate unit order of magnitude for measuring their weight) or anything about "modern" SPAs that thumb their nose at graceful degradation.

    1. The biggest mistake—and one I’ve made myself—is linking with categories. In other words, it’s adding links like we would with tags. When we link this way we’re more focused on grouping rather than connecting. As a result, we have notes that contain many connections with little to no relevance. Additionally, we add clutter to our links which makes it difficult to find useful links when adding links. That being said, there are times when we might want to group some things. In these cases, use tags or folders.

      Most people born since the advent of the filing cabinet and the computer have spent a lifetime using a hierarchical folder-based mental model for their knowledge. For greater value and efficiency one needs to get away from this model and move toward linking individual ideas together in ways that they can more easily be re-used.

      To accomplish this many people use an index-based method that uses topical or subject headings which can be useful. However after even a few years of utilizing a generic tag (science for example) it may become overwhelmed and generally useless in a broad search. Even switching to narrower sub-headings (physics, biology, chemistry) may show the same effect. As a result one will increasingly need to spend time and effort to maintain and work at this sort of taxonomical system.

      The better option is to directly link related ideas to each other. Each atomic idea will have a much more limited set of links to other ideas which will create a much more valuable set of interlinks for later use. Limiting your links at this level will be incredibly more useful over time.

      One of the biggest benefits of the physical system used by Niklas Luhmann was that each card was required to be placed next to at least one card in a branching tree of knowledge (or a whole new branch had to be created.) Though he often noted links to other atomic ideas there was at least a minimum link of one on every idea in the system.

      For those who have difficulty deciding where to place a new idea within their system, it can certainly be helpful to add a few broad keywords of the type one might put into an index. This may help you in linking your individual ideas as you can do a search of one or more of your keywords to narrow down the existing ones within your collection. This may help you link your new idea to one or more of those already in your system. This method may be even more useful and helpful for those who are starting out and have fewer than 500-1000 notes in their system and have even less to link their new atomic ideas to.

      For those who have graphical systems, it may be helpful to look for one or two individual "tags" in a graph structure to visually see the number of first degree notes that link to them as a means of creating links between atomic ideas.

      To have a better idea of a hierarchy of value within these ideas, it may help to have some names and delineate this hierarchy of potential links. Perhaps we might borrow some well ideas from library and information science to guide us? There's a system in library science that uses a hierarchical set up using the phrases: "broader terms", "narrower terms", "related terms", and "used for" (think alias or also known as) for cataloging books and related materials.

      We might try using tags or index-like links in each of these levels to become more specific, but let's append "connected atomic ideas" to the bottom of the list.

      Here's an example:

      • broader terms (BT): [[physics]]
      • narrower terms (NT): [[mechanics]], [[dynamics]]
      • related terms (RT): [[acceleration]], [[velocity]]
      • used for (UF) or aliases:
      • connected atomic ideas: [[force = mass * acceleration]], [[$$v^2=v_0^2​+2aΔx$$]]

      Chances are that within a particular text, one's notes may connect and interrelate to each other quite easily, but it's important to also link those ideas to other ideas that are already in your pre-existing body of knowledge.


      See also: Thesaurus for Graphic Materials I: Subject Terms (TGM I) https://www.loc.gov/rr/print/tgm1/ic.html

    1. Author Response

      *Reviewer #2 (Public Review):

      This manuscript describes studies on the structural determinants of activation for the adhesion GPCR (aGPCR) GPR116 both in vitro and in vivo. The authors define key residues for activation on the receptors' N-terminus (the "tethered agonist") and the extracellular loops. Thus, the studies provide novel insights into the structural determinants of GPR116 activation. However, some interpretational issues (detailed below) complicate some of the authors' conclusions. Specific comments are as follows:

      1. Results section, first paragraph, last sentence: The authors write, "These results taken together indicate that the H991A mutant is capable of proper trafficking to the membrane, is able to response to exogenous peptide, but is unable to be cleaved and activated by endogenous ligands in vivo." The last part of this sentence represents an over-interpretation, as the data shown in Figure 1 do NOT show that the non-cleavable receptor is unable to be activated by endogenous ligands in vivo. It is entirely conceivable that a non-cleavable aGPCR could still be activated by endogenous adhesive ligands if those ligands were to change the position of the tethered agonist in manner that alters receptor signaling activity.

      Thank you for highlighting this misleading wording. We rephrased the sentence to read as follows: Taken together, these results demonstrate that the H991 residue within the GAIN domain is critical for cleavage of GPR116 into NTF and CTF fragments but dispensable for trafficking of the receptor to the plasma membrane and response to exogenous peptide activation in vitro.

      1. The data shown in Fig. 1B (surface expression of non-cleavable H991A mutant) need to be quantified in some way in order to be interpretable.

      As the H991A construct does not contain a cell surface epitope tag, it is difficult to directly quantitate surface expression of this protein. The data in transiently transfected HEK293 cells (Figure 1, panels C and D) and in primary alveolar epithelial cells (Figure 2, panels C&D) clearly demonstrate that the H991A mutant is activated to comparable levels as the wild-type receptor in response to exogenous peptide stimulation. In light of these functional data, we are confident that the surface expression of H991A is comparable to that of the WT receptor in vitro and in vivo.

      1. Results section, second paragraph, penultimate sentence: The authors write, "These data demonstrate that while the non-cleavable receptor is fully activated in vitro by exogenous peptides corresponding to the tethered agonist sequence, cleavage of the receptor and unmasking of the tethered agonist sequence is critical for GPR116 activation in vivo." However, the non-cleavable GPR116 mutant actually has two key differences from WT: i) lack of full liberation of the tethered agonist sequence, and ii) lack of liberation of a free NTF, which might dissociate from the CTF and have important in vivo physiological actions on its own. Isn't it conceivable that the lack of a freely mobile NTF contributes to the similarity in lung phenotype between the non-cleavable knock-in mutant and the GPR116 knockout? Based on the data shown in Figure 2, how can the authors claim these data demonstrate that unmasking of the tethered agonist is critical for GPR116 activation? The data could equally be interpreted as showing that liberation of a free NTF is critical for the physiological effects of GPR116 in vivo.

      We thank the reviewer for this comment and, in retrospect, agree that we may have overstated the interpretation of our results for the H991A transgenic mouse. While it is possible that the free NTF may be responsible for the physiological effects of GPR116 in vivo, in light of recently published data by Mitgau et al. (BioRxiv https://doi.org/10.1101/2021.09.13.460127), we believe this not to be the case for the following reasons. First, the H991A and WT receptors are activated to an identical level by exogenous peptide stimulation in a transformed cell line (HEK293) and in primary alveolar type 2 epithelial cells (Figures 1 and 2), irrespective of if the NTF is free floating in solution in the context of the WT receptor. These data would argue against a role of the free NTF in receptor activity. Second, in a recent publication by Mitgau et al., the authors clearly demonstrate that activation of GPR126, an adhesion GPCR that is also cleaved at the GPS and activated by exogenous peptides corresponding to the tethered agonist, by antibodies that bind and crosslink the NTF is completely dependent on cleavage at the GPS. They further demonstrate that antibody-mediated activation does not lead to liberation of the NTF from the CTF. Rather, they postulate that proper GPS processing, as occurs for the WT receptor, leads to a favorable protein confirmation of the tethered agonist, which is indispensable for GPR126 activity. Given these results, we postulate that cleavage at the GPS of WT GPR116 results in a conformation that is critical for the tethered agonist sequence to reach and bind the ECLs, resulting in activation of the receptor, similar to that observed with GPR126. We have edited our interpretation of these data in the revised manuscript.

      1. Figure 3: If the authors' hypothesis is that the tethered agonist must be liberated in order to allow activation of GPR116, then why do ANY of the Flag-tagged mutant constructs exhibit constitutive signaling activity? Doesn't the N-terminal Flag tag prevent the tethered agonist from being exposed? How can these data be reconciled with the authors' model?

      It is unlikely that the 27 amino acid N-terminal FLAG epitope tag envelopes the tethered agonistic peptide to the same extent as the tertiary structure of the carboxy terminus of the NTF (based on published structures for other aGPCRs). Additionally, we provided data demonstrating that an untagged version of the CTF protein is activated to a similar extent at FLAG-tagged CTF in response to activating peptides (Supplemental Figure 2A). Based on our data from mutagenesis experiments and modeling of GPR116 with the agonist, we do not believe the tethered agonist dives deeply within the binding pocket but rather interacts with critical amino acids at the surface of ECL2 to induce conformational changes to the receptor and downstream activation.

      1. The data shown in Fig. 3D are lacking statistical comparisons, so it is not possible to tell whether any of the differences between the mutants are statistically significant.

      Statistical analyses for data in this panel have been added

      1. The data shown in Fig. 4D (surface expression of the ECL mutants) need to be quantified in some way.

      We have added additional data to this figure (Fig4 F-G-H) using the V5-tagged mFL construct as control. As the tag is C-terminal, we quantified by flow cytometry the total expression using an anti-V5 antibody, to complement to immunocytochemistry data showing membrane expression.

      1. In interpreting the results of the ECL mutations on GPR116 signaling activity, it is unclear why the authors so explicitly propose that these data demonstrate that the tethered agonist must be interacting with ECL2. Isn't it possible that ECL2 mutants with impaired receptor signaling activity simply lock the receptor in an inactive state? In this way, the effects of the ECL2 mutations could be explained without invoking a physical interaction between the putative tethered agonist and ECL2.

      Yes, this interpretation is also possible. We have rephrased the Results and Discussion sections accordingly to reflect this possibility.

    1. SciScore for 10.1101/2022.04.28.489772: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Euthanasia Agents: 2 variant at 100 TCID50/mouse under isoflurane anesthesia.<br>IACUC: All procedures were performed according to the animal study protocols approved by the FDA White Oak Animal Program Animal Care and Use Committee.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">In the ABSL-3 lab, K18-hACE2 mice were randomly grouped and were inoculated intranasally with NY (G614), Delta, Omicron BA.1 or Omicron BA.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Western blot: Western blot was performed using an anti-SARS-COV-2 S antibody following a protocol described previously (58).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-COV-2 S</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Alkaline phosphatase conjugated anti-Rabbit IgG (1:5000) (Sigma-Aldrich, St. Louis, MO) was used as a secondary antibody.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-Rabbit IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Control sensors with no ACE2 or antibody were also dipped in the S protein solutions and the running buffer as references.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For antibody staining, an Alexa Fluor 647 conjugated donkey anti-human IgG Fc F(ab’)2 fragment (Jackson ImmunoResearch, West Grove, PA) was used as secondary antibody at 5 μg/ml concentration.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washing, plates were probed with 1 μg/ml of inhouse developed rabbit polyclonal antibody specific for SARS-CoV-2 membrane/nucleocapsid (33) at 4°C overnight followed by peroxidase-conjugated goat anti-rabbit secondary antibody (SeraCare #5220-0336, 1:2000) for 2h at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: (SeraCare KPL Cat# 5220-0336, RRID:AB_2857917)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, Expi293F cells transfected with monomeric ACE2 or dimeric ACE2 expression construct and the supernatant of the cell culture was collected.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Expi293F</div><div>suggested: RRID:CVCL_D615)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Murine Leukemia Virus (MLV) particles (plasmids of the MLV components kindly provided by Dr. Gary Whittaker at Cornell University and Drs. Catherine Chen and Wei Zheng at National Center for Advancing Translational Sciences, National Institutes of Health), pseudotyped with various SARS-CoV-2 S protein constructs, were generated in HEK 293T cells, following a protocol described previously for SARS-CoV (59, 60).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK 293T</div><div>suggested: KCB Cat# KCB 200744YJ, RRID:CVCL_0063)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To prepare for infection, 7.5×103 of HEK 293 cells, stably transfected with a full-length human ACE2 expression construct, in 15 μl culture medium were plated into a 384-well white-clear plate coated with poly-D-Lysine to enhance the cell attachment.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK 293</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudotyped virus particles were produced in 293T/17 cells (ATCC) by co-transfection of plasmids encoding codon-optimized SARS-CoV-2 full-length S constructs, packaging plasmid pCMV DR8.2, and luciferase reporter plasmid pHR’ CMV-Luc.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T/17</div><div>suggested: ATCC Cat# CRL-11268, RRID:CVCL_1926)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The 293T cell line stably overexpressing the human ACE2 cell surface receptor protein was kindly provided by Drs.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: KCB Cat# KCB 200744YJ, RRID:CVCL_0063)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Seed viruses were amplified in Vero E6 (ATCC CRL-1586) or Vero E6 with TMPRSS2 overexpression (BPS Bioscience #78081)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In vitro virus replication and focus-forming assay: Vero-E6 cells were pre-seeded in 12-well tissue culture plates overnight and were infected with authentic viruses (G614, Delta, Omicron BA.1 or BA.2) at MOI of 0.01 in Gibco™ high glucose DMEM containing 3% FBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero-E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 10-fold serially diluted postinfection were added at 100 μl/well to Vero E6-TMPRSS2 cells pre-seeded in 96-well tissue culture plates.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6-TMPRSS2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Mouse study: Hemizygous B6.Cg-Tg(K18-ACE2)2Prlmn/J (K18-hACE2</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>B6.Cg-Tg(K18-ACE2)2Prlmn/J</div><div>suggested: RRID:IMSR_JAX:034860)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In the ABSL-3 lab, K18-hACE2 mice were randomly grouped and were inoculated intranasally with NY (G614), Delta, Omicron BA.1 or Omicron BA.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>K18-hACE2</div><div>suggested: RRID:IMSR_GPT:T037657)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The S gene was fused with a C-terminal twin Strep tag (SGGGSAWSHPQFEKGGGSGGGSGGSSAWSHPQFEK) and cloned into a mammalian cell expression vector pCMV-IRES-puro (Codex BioSolutions, Inc, Gaithersburg,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV-IRES-puro</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudotyped virus particles were produced in 293T/17 cells (ATCC) by co-transfection of plasmids encoding codon-optimized SARS-CoV-2 full-length S constructs, packaging plasmid pCMV DR8.2, and luciferase reporter plasmid pHR’ CMV-Luc.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV DR8.2 , and luciferase reporter</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pHR’</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Serially diluted pCMV6-AC-ACE2-GFP plasmid or pCC1-CoV2-F7 plasmid expressing SARS-CoV-2 N (62) was used to construct a standard curve.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV6-AC-ACE2-GFP</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pCC1-CoV2-F7</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The KD was obtained by fitting Req value and its corresponding concentration to the model: “one site-specific” using GraphPad Prism 8.0.2 according to H.J. Motulsky, Prism 5 Statistics Guide, 2007, GraphPad Software Inc.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Automated data collection was carried out using SerialEM version 3.8.6 (63) at a nominal magnification of 105,000× and the K3 detector in counting mode (calibrated pixel size, 0.83 Å) at an exposure rate of 13.761 electrons per pixel per second.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SerialEM</div><div>suggested: (SerialEM, RRID:SCR_017293)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Local resolution was also determined using cryoSPARC.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>cryoSPARC</div><div>suggested: (cryoSPARC, RRID:SCR_016501)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Several rounds of manual building were performed in Coot.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Iteratively, refinement was performed in both Phenix (real space refinement) and ISOLDE (66), and the Phenix refinement strategy included minimization_global, local_grid_search, and adp, with rotamer, Ramachandran, and reference-model restraints, using 7KRQ and 7KRR as the reference models.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Phenix</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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  5. Apr 2022
    1. SciScore for 10.1101/2022.04.22.22274032: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: Subjects or households with suspected or confirmed SARS-CoV-2 infection were recruited from the Greater New Orleans community under Tulane Biomedical Institutional Review Board (federalwide assurance number FWA00002055, under study number 2020-585).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Determination of antigen-specific antibody reactivity by multiplexed Luminex analysis: Recombinant SARS-CoV-2 antigens (full-length spike, RBD, and N) and the recombinant spike protein from OC43, HKU1, 229E, and NL63 (Frederick National Laboratories) were coupled with MagPlex beads (Luminex) via sulfo-NHS coupling chemistry.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>antigen-specific</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HKU1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The Spike protein ELISA for IgG antibodies has been validated by testing a standard set of positive and negative samples provided by NCI SeroNet staff.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">NK92 cells in complete alphaMEM culture medium were added at 5 × 104 cells/well in the presence of 4 µg/ml brefeldin A (Biolegend Cat# 420601), 5 µg/ml GolgiStop (BD Biosciences Cat# 554724) and 0.15µg of anti-CD107a antibody (Clone H4A3 PE-Cy7, Biolegend Cat# 328618) for 5 hours at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-CD107a</div><div>suggested: (BioLegend Cat# 328618, RRID:AB_11147955)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody-dependent neutrophil phagocytosis (ADNP): Protocol was adapted from [72]</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Antibody-dependent neutrophil phagocytosis</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Beads were washed with PBS containing 15 mM EDTA and stained with an FITC-conjugated anti-guinea pig C3 antibody (MP Biomedicals).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-guinea pig C3</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Neutralization of SARS CoV-2 in Pseudovirus Assay: CHO cells were generated and stably expressed ACE2 by transfecting CHO cells with an ACE2 expression plasmid containing the blasticidin resistance gene.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CHO</div><div>suggested: CLS Cat# 603479/p746_CHO, RRID:CVCL_0213)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">CHO-ACE2 cells were similar in SARS CoV-2 susceptibility to the 293T/ACE2 cell line developed by Dr.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CHO-ACE2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Virus neutralization was measured in CHO/ACE2 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CHO/ACE2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudoviruses were produced by co-transfection of the four plasmids into 293T cells grown in T75 flasks with Fugene 6 as transfection reagent.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Unbound antibodies were removed by centrifugation before adding THP-1 cells at 2.5×104 cells/well.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP-1</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">RBD (aa321-535) was similarly expressed in the phCMV plasmid and purified on Streptactin X affinity columns.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>phCMV</div><div>suggested: RRID:Addgene_15802)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A DNA fragment encoding SARS CoV-2 N protein, including its natural leader sequence was generated by PCR of full-length N protein gene from a lentiviral N Protein expression vector (pLVX-EF1alpha-SARS-CoV-2-N-2xStrep-IRES-Puro, which was a gift from Nevan Krogan (Addgene plasmid # 141391 ; http://n2t.net/addgene:141391; RRID:Addgene_141391, [68]).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_141391)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">These included an expression plasmid for full-length spike protein of the Wuhan-1 strain containing the D614G amino acid chain (VRC7480.G614) [70], a pCMV ΔR8.2 lentivirus backbone plasmid (VRC5602) [71], the VRC5601 plasmid pHR’ CMV Luc containing the firefly luciferase reporter gene [71], and VRC9260 for TMPRSS2 expression.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV ΔR8.2 lentivirus</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>VRC5601</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pHR’</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Neutralization titers were defined as the serum dilution (ID50) at which relative luminescence units (RLU) were reduced by 50% compared to virus control wells after subtraction of background RLUs (determined by GraphPad Prism, version 9 for macOS, GraphPad Software, San Diego, California USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Spike Glycoprotein (stabilized) from SARS-Related Coronavirus 2, Wuhan-Hu-1 with C-Terminal Histidine Tag, Recombinant from Baculovirus), and SARS-CoV-2 specific mega pools at 0.2 μg/well including PepTivator SARS-CoV-2 Prot_S (Miltinyi - 130-126-700), SARS-CoV-2 Prot_M (130-126-702), SARS-CoV-2 Prot_N (130-126-699) in 96-well U bottom tissue culture plate (CytoOne CC7672-7596) in 200 μl RPMI-1640 with 10% FBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PepTivator</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">) GraphPad Prism (version 9.0.0, GraphPad Software, San Diego, CA), JMP (version 16.2.0, SAS Institute, Inc.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">, Cary, NC), and SAS (version 9.4, SAS Institute, Inc.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SAS Institute</div><div>suggested: (Statistical Analysis System, RRID:SCR_008567)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:


      Study limitations primarily involved using SARS-CoV-2 infection to differentiate subjects rather than pre-pandemic samples. In addition, the assays were limited to peripheral blood samples and not tissue-specific responses, which included only effector functions to spike protein and cytokine secretion instead of T-cell subset analyses. Detection of secreted cytokines allowed a greater number of cytokines to be evaluated but prevented confirmation of cells producing cytokines as would be observed intracellular stained cytokines for specific T-cell populations. However, cytokines between spike or peptide pools were highly correlated (Figure S5), indicating T-cell production. Also, high expression of IL-2 has been routinely observed from CD4+ T-cell and not CD8+ T-cells after SARS-CoV-2 infection [28, 38]. In this study, IL-17A secretion was closely correlated to IL-2 and Th1 cytokine release after stimulation with protein or peptide pools, suggesting that IL-17A may be serving as a proxy for a Th1/Th17 subset, as identified in other post-vaccination studies [61] which should be more closely examined. Finally, while the critical role for age in SARS-CoV-2 immunity was validated, it remains an ongoing question of why children exhibit less severity with infection and how differences in qualitative features of immunity depend on patient age. Our study used samples collected from subjects only shortly after the pandemic which will be difficult to perform as COVID subsides and vaccin...


      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.04.21.489021: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cells were incubated with 100μM of the respective peptide and 1:200 dilution of rabbit anti-HA tag antibody (Sigma; catalogue no. Cat # H6908) at 4°C for 1hr.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-HA</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells were incubated with 1:200 dilution of goat anti-rabbit Alexa fluor-647 antibody (Invitrogen) and 1:100 dilution of neutravidin fluorescein conjugate (Invitrogen; FITC, catalogue no. A2662, used for the first FACS) at 4°C for 30min.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>antibody (Invitrogen)</div><div>suggested: (Rockland Cat# 00-8844-25, RRID:AB_2610705)</div></div><div style="margin-bottom:8px"><div>30min</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cells were incubated with 1:500 dilution of mouse anti-FLAG monoclonal antibody (Merck, catalogue no. F3165) overnight at 4°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-FLAG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The blots were probed with 1:5000 anti Flag antibody (Sigma, F3165) overnight at 4□C followed by 1:10000 anti-mouse secondary at room temperature for 1hr.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti Flag</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The surface of the well was washed twice with blocking buffer and incubated with HRP-conjugated rabbit anti-6xHis tag antibody (Abcam; catalogue no. AB1187), 1:10,000 dilution at 4°C overnight.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-6xHis tag</div><div>suggested: (Abcam Cat# ab1187, RRID:AB_298652)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">eGFP-ACE2/HEK293T immunostained with FLAG antibody was imaged at 60x oil objective of FV3000 confocal microscope (Figure 2B) and 100x oil objective of H-TIRF microscope (Supplementary Figure 2A) using 405nm, 488nm and 647nm laser lines for DAPI, eGFP, and Alexa fluor-647 fluorophores.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>eGFP</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell culture experiments: Wild type mammalian HEK293T cells and LentiX-293T cells (Takara Bio, catalogue no. 632180) were used in this study for pseudotyped spike virus production and viral transduction assay.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>LentiX-293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Caco2 cells were lysed for total RNA purification using the Trizol method.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Caco2</div><div>suggested: CLS Cat# 300137/p1665_CaCo-2, RRID:CVCL_0025)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudoviral transduction assay: The GFP/HEK293T cells or eGFP-ACE2/HEK293T cells were grown up to 60-70% confluency in complete media before viral transduction.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GFP/HEK293T</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>eGFP-ACE2/HEK293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In this assay, the viral titre was used in a concentration such that to obtain more than 70% transduction efficiency in the eGFP-ACE2/HEK293T or eGFP/HEK293T cell line.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>eGFP/HEK293T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cloning and protein purification: The nanobody gene was amplified from isolated yeast colonies and cloned between HindIII and XhoI sites in a pET-22b(+) plasmid containing a C-terminal 6x histidine tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET-22b(+)</div><div>suggested: RRID:Addgene_12651)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For viral particle production, 5 µg pHR lentiviral vector cloned with mCherry fluorescent protein, 3.75 µg packaging plasmid psPAX2 (Addgene; #12260), and 2.5 µg envelope plasmid for the expression of Spike glycoprotein (obtained as a kind gift from Prof. Nevan Krogan, UCSF, USA) of SARS-CoV-2 were mixed in 500 µl OptiMEM media and 20 µl PLUS reagent (Invitrogen; LTX transfection reagent, catalogue no. L15338100) and kept for incubation at room temperature for 5min.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pHR</div><div>suggested: RRID:Addgene_16514)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">We also generated control lentiviral particles by replacing Spike plasmid with VSV-G envelope protein, pmDG2 (Addgene; #12259) plasmid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pmDG2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Omicron pseudotyped virus production: Omicron pseudotyped viruses were produced similarly as described above for spike pseudoviruses but instead used omicron envelope plasmid along with packaging plasmid (psPAX2) and lentiviral plasmid (pHR mCherry) in the following ratio: psPAX2 (1.3pmol), pHR mCherry: 1.64pmol, SARS-CoV-2 Omicron Strain S gene (Genscript, Cat # MC_0101274): 0.72pmol.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>psPAX2</div><div>suggested: RRID:Addgene_12260)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">This construct contains amino-terminus EGFP followed by self-cleaving 2A peptide sequence followed by ACE2 and carboxy-termini SNAP-tag and FLAG tags (eGFP-ACE2/HEK293T) Generation of stable HEK293T cell line for over-expression of ACE2: The lentiviral pTRIP vector cloned with eGFP-ACE2/HEK293T under CMV enhancer and chicken β-actin promoter (CAG promoter) flanked with 5′and 3′ long terminal repeat (LTR) sequences (39), were used to produce lentiviral particles as per the method described before (35).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pTRIP</div><div>suggested: RRID:Addgene_127663)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The following peptide sequences from the receptor-binding domain (RBD) of the spike were synthesized from LifeTein with a biotin tag: Peptide-1: [FNCYFPLQS]S-K-Biotin Peptide-2: Biotin-[GFQPTNGVGY] Sequence Alignment for Covid Variants The hCoV19 spike (Wuhan/WIV04/2019), GISAID (EPI_ISL_402124) construct is a kind gift from Prof. Nevan Krogan, UCSF, USA (38).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>LifeTein</div><div>suggested: (LifeTein, RRID:SCR_012626)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For viral particle production, 5 µg pHR lentiviral vector cloned with mCherry fluorescent protein, 3.75 µg packaging plasmid psPAX2 (Addgene; #12260), and 2.5 µg envelope plasmid for the expression of Spike glycoprotein (obtained as a kind gift from Prof. Nevan Krogan, UCSF, USA) of SARS-CoV-2 were mixed in 500 µl OptiMEM media and 20 µl PLUS reagent (Invitrogen; LTX transfection reagent, catalogue no. L15338100) and kept for incubation at room temperature for 5min.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Addgene</div><div>suggested: (Addgene, RRID:SCR_002037)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Images were analysed on Fiji software to calculate mean fluorescence intensity (MFI) for eGFP (ACE2 expression) and mCherry (viral transduction) channel from the z-projected stacks.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Fiji</div><div>suggested: (Fiji, RRID:SCR_002285)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. Author Response:

      Reviewer #2:

      The authors investigated changes in the unstressed and stressed oligomeric states of the mammalian endoplasmic reticulum (ER) stress sensor, IRE1a. Previous biochemical and microscopy studies in mammalian cells and studies of the related protein Ire1 in yeast, describe an increase in oligomerization of the stress sensor upon treatment of cells with chemical agents that impair the ER protein folding environment. The general view has been that IRE1 in unstressed cells is a monomer and varying degrees of misfolded protein stress stimulate dimerization, activation, and higher order oligomerization. Distinguishing between monomers and dimers, as well as tetramers or other small oligomers is technically challenging, especially for integral membrane proteins. To address this challenge, the authors turned to single particle tracking fluorescence microscopy of Halo-tagged endogenous IRE1. Using a clever combination of random labeling with two fluorescent dyes and oblique angle illumination to visualize single molecules, as well as dimers, the authors surprisingly find that their endogenous IRE1 reporter appears to be dimeric in homeostatic cells. This observation challenges the predominant model in which IRE1 is monomeric in unstressed cells and that even dimerization represents a switch into an active state. The authors claim to detect evidence for higher order oligomers following treatment with stressors. The authors then use a series of IRE1 mutants to identify how oligomerization is regulated and present a new model to reconcile the different models of IRE1 activation in the literature.

      The authors have extensively characterized their novel experimental system in terms of protein expression levels, functionality, and ability to distinguish monomers and dimers. The data are well presented and the authors are clearly familiar with the arguments that have surrounded the IRE1 oligomer question. That the authors observe the characteristic XBP1 mRNA splicing activity in the absence of visible large IRE1 clusters may suggest that the large clusters reported by others may have distinct roles, perhaps in more permissive mRNA cleavage.

      The present study is undermined by two major weaknesses. First, while the authors persuasively demonstrate that they can detect IRE1a dimers, a major claim of the manuscript rests upon detection of tetramers and possibly higher order oligomers. Unfortunately, the authors provide no independent controls to show what tetramer or higher order oligomer data would look like. Thus, the authors can only infer that higher order oligomers are detected, based on modest shifts in the percent of correlated particle trajectories observed in some cells. More robust evidence is needed to make claims of oligomerization. Tools have been developed by others that can induce reversible oligomerization of proteins. Application of these tools would provide powerful controls for tetramers or even higher order oligomers in this study.

      The second, deeper concern, is the discrepancy between the Halo Tag clustering results in this study and studies by this lab and several other labs that report a distinct stress phenotype. In mammalian cells and yeast, IRE1 and Ire1, tagged with different fluorescent proteins or even a small HA peptide epitope tag, undergo quantitative visible formation of puncta or clusters upon treatment with stressors. The small number of bright clusters that form effectively deplete the rest of the ER of IRE1 signal. In the present study, the authors observe no visible change in IRE1-Halo localization in stress cells. The authors do not investigate the cause of this difference. While one might argue that the presence of stress-inducible IRE1 activity is sufficient to argue that the reporter in this study is functional, IRE1 reporters (that do cluster) described in previous studies by the Walter lab and other groups are also demonstrably functional. Does IRE1 normally cluster? Is it cell-type dependent? Tag-dependent? Notably, the Pincus et al. PLoS Biology paper from the Walter lab used two different fluorescent protein tags that do not heterozygously dimerize. Robust colocalization and FRET signals were detected upon treatment of cells with stressors and clustering was subsequently observed. A 2007 Journal of Cell Biology study from Kimata et al. reported clustering in yeast with an Ire1 tagged with an HA epitope peptide. The HA peptide seems unlikely to be prone to any oligomerization propensities that GFP tagged reporters might experience. Importantly, a 2020 PNAS paper from the Walter lab (Belyy et al.) studied clustering of a robustly monomeric mNeonGreen-tagged IRE1 in U2-OS cells and mouse embryonic fibroblasts and this construct readily clustered following stress induction.

      When evaluated against the backdrop of the extensive literature describing the visual behavior of IRE1a in live cells, the absence of stress-induced clustering is both puzzling and disconcerting. Given the focus of this study is to use visual techniques to study IRE1a interactions, the burden of proof is on the authors to resolve this significant discrepancy with the rest of the IRE1a literature. One can easily imagine that incorporation of the majority of the pool of IRE1a into 10-100 clusters could produce very different correlated trajectory behavior. Until the authors can determine why their reporters behave differently from other IRE1a reporters and establish which version accurately reflects physiologic IRE1a behavior, the potential impact of the findings of this manuscript are of unknown value.

      We thank the reviewer for this detailed assessment of our work. We agree that the question of apparent discrepancy in the formation of observable IRE1 clusters between this manuscript and earlier work is important. We have now addressed this issue both in the revised version of the manuscript and in specific point-by-point responses to reviewers’ comments. As a brief summary, we addressed the reviewer’s first concern (lack of controls larger than dimers) by cloning and validating a tetrameric HaloTag construct, the measurements from which were entirely consistent with the model we presented in the original version of the manuscript. To address the reviewer’s second concern, we present several lines of evidence showing that the discrepancy between the formation of microscopically visible IRE1 clusters in earlier studies and the absence of such clusters in the present work almost certainly results from differences in expression levels. First, our IRE1-HaloTag construct is perfectly capable of forming stress- induced clusters, as we show in the new Figure 1 – Figure Supplement 3. Second, we point to a parallel study by Gómez-Puerta et al., who demonstrate that a more “conventional” IRE1-GFP construct does not form visible stress-dependent puncta when it is expressed at a low level comparable to that of untagged IRE1 in HeLa cells, despite being fully active. Third, our earlier work in the 2020 PNAS paper referenced by the reviewer actually showed that even in the overexpression context, IRE1-mNeonGreen only forms visible puncta in just over half of all cells, despite the fact that XBP1 processing is nearly 100% effective in bulk assays. Furthermore, in the same paper we show that, rather than all IRE1 molecules being sequestered in clusters, only a small fraction (~5%) of IRE1-mNeonGreen assembles into large puncta while the remaining 95% of IRE1 stays uniformly distributed throughout the ER. Taken together, we believe that IRE1 does have the propensity to assemble into larger clusters when its expression levels are high (regardless of the tag used), but that these clusters are not strictly required for its activation. We have made significant changes to the discussion section of the manuscript to clarify the above points and directly address the apparent discrepancy between the present work and earlier studies.

      Reviewer #3:

      In this paper, the authors' aim was to test how IRE1's oligomerization state relates to its activation status without relying on ectopic overexpression. The principle underlying the work is a rather simple one, which is that, if the population of IRE1 can be labeled stochastically with either of two different fluorescent probes, then if the protein dimerizes, presuming single molecules can be visualized, correlated migration of a spot of each fluorophore should be observed for some of those dimers. Any correlated migration, maintained for long enough, will by necessity by some sort of dimer or multimer. In principle, if my math is right, the correlation should be 50% of spots of each color, assuming all the molecules are in a dimer, all molecules are labeled with one fluorophore or the other, and the koff of the fluorophores is very low. In practice, the correlation appears closer to 10%, which the authors establish using a control molecule that should not dimerize except by chance, and another for which pseudo-dimerization is enforced due to the two HALO domains used to bind the fluorophores being conjugated to the same molecule in cis. Much of the paper is devoted to establishing the fundamentals of the system. For these experiments, the authors replaced endogenous IRE1 with the HALO-tagged version to generate near-normal expression and show that the IRE1-HALO behaves similarly to endogenous. They also show that correlated migration is observed in the dimer control to a much greater extent than in the monomer.

      Using these findings, they demonstrate, in my mind quite conclusively, that IRE1 exists as a dimer even in the unstimulated state. During ER stress, the authors observe a state that is more highly ordered. Mathematical modeling suggests a transition from predominantly dimers to a mix of dimers and something more highly ordered, with tetramers being the simplest explanation. Satisfyingly, a mutation that breaks the known dimer interface causes the protein to exist solely in monomers, as does deletion of the IRE1 lumenal domain, while disrupting the oligomerization interface keeps the protein as dimers. Mutation or deletion of the kinase and RNase domains does not affect higher order status, suggesting that activation of these domains is not a prerequisite for assembly. It is clear from this that the central claims of the paper, which is that IRE1 exists in a dimer in the basal state and transitions to a higher ordered structure in the activated state, are supported. Moreover, the general approach is likely to be appealing to the study of other molecules activated by multimerization.

      We thank the reviewer for this thoughtful and helpful analysis of our work.

      The principal advance of the paper is the technological approach for tracking IRE1 (and, presumably, other molecules whose activity is regulated by dimerization). The approach is quite elegant for that purpose. Its impact in terms of conclusions about IRE1 is perhaps less clear. The authors rationalize their endogenous-replacement approach by describing how their previous efforts and those of others relied on ectopic overexpression of GFP-tagged IRE1. The authors take great pains to claim that the observed multimerization status of the IRE1-HALO constructs is not a function of expression level, which would imply then that expression level alone is not responsible for the previously observed IRE1 oligomeric puncta. It is not clear why exactly the authors' results differ from this group's previous studies on the topic nor where the truth lies, including whether something inherent to the GFP-tagged overexpression approach favors non-physiologic structures, whether the difference is fundamentally one of cell type, or whether multimerization and activation are correlated but not causally related, with multimer-breaking mutations killing IRE1 by some other mechanism.

      The question of reconciling our present data with earlier work (including work from our group) is clearly and understandably a central question for all three reviewers. As we detailed above in our responses to reviewers 1 and 2, we are convinced that the formation of large IRE1 clusters is largely dependent on expression level rather than the differences between fluorescent protein tags and the HaloTag. We added new supplementary figures and substantially revised the text of the manuscript to address this question directly.

      Interpreting the data is also complicated by the fact that, while the authors point out that the percent of correlated trajectories (i.e., the measurement of multimerization state) does not itself correlate with expression level (using trajectories-per-movie as a proxy), the proper conclusion from that lack of correlation is not that variance in expression level does not account for the changes in apparent multimerization status, but instead that it cannot be the only factor. In some sense, the authors are attempting to play the argument both ways, by arguing that expression level matters for IRE1 activation (from previous studies) and that it doesn't (from this study). I think to address this the authors will need to better account, one way or another, for why the findings presented here differ from their previous findings and why these are the more salient (if in fact they are).

      This is a very important point, and we thank the reviewer for raising it. We are not arguing that expression levels do not matter for the formation of oligomers; quite the contrary, as detailed above and in the revised version of the text, we believe that the formation of massive IRE1 oligomers observed in previous studies and in the new Figure 1 – Figure Supplement 3 is mainly a function of elevated concentration. What we do claim is that our approach can reliably pick out oligomeric differences within the relatively narrow range of concentrations used for single-particle tracking experiments in this paper. We are using the very weak truncated CMVd3 promoter in all transient transfection experiments, and we are only analyzing data from cells that have a comparable density of single-molecule spots to the density we observe in endogenously tagged IRE1-HaloTag cells. In fact, the metric of “trajectories per movie” used as a proxy for expression levels in Figure 5 – Figure Supplement 1 is an overestimation of the true variability of expression levels, since each movie only covers a small fraction of each cell’s area and the number of observed molecules varies depending on cell morphology. Practically speaking, all cells that we image have expression levels that are clustered together rather narrowly, roughly within differences of no more than a factor of 3. These levels, in turn, are significantly lower than the expression levels used in earlier papers by our group and others.

      The other somewhat substantial issue is that there is no control for what higher order structures look like. The authors give no sense for the dynamic range of the multimerization assay. I would presume that tetramers would show a higher percentage of correlated trajectories than dimers, and octamers higher still, and that the mathematical model accounts for this theoretical possibility in calculating an average protomer number of 2.7 in the stress condition, but it would be better to see that in practice; at first glance it would seem that engineering a tetrameric and/or higher order control and validating it would be straightforward.

      This is another great point raised by all reviewers. In the revised version of the manuscript, we engineered a new tetrameric control construct (See Figure 2 – Figure Supplement 1), the results from which agree remarkably well with the mathematical model we developed in the original version of the manuscript (see Figure 2 – Figure Supplement 3)

      Lastly, the data analysis lacks statistical justification for its conclusions. I presume given the high number of readings that the observed changes are all statistically significant, but that should be indicated, as in most cases the 95% confidence intervals shown are overlapping.

      This is another excellent point. The reviewer is correct that all relevant conclusions are statistically supported by the data, and our analysis code immediately calculates pairwise p- values for every plot using one of several relevant tests. Our preferred test is the permutation test, since it makes no assumptions about the underlying distributions being compared. To avoid cluttering the main plots, we have included tables of pairwise p-values for each plot in the revised version of the manuscript.

    2. Reviewer #1 (Public Review): 

      In this manuscript, the authors sought to define the early events associated with activation of the ER stress-responsive membrane protein IRE1. Towards that aim, they used CRISPR to integrate a HALO tag into the genomic locus of IRE1 at the C-terminus of the protein. The authors then adapted a single molecule fluorescence microscopy approach where the HALO tag is liganded with two different fluorophores to define the oligomeric state of membrane proteins in cellular models. They validated this approach using ER membrane proteins containing defined number of HALO tags (single or double) and imaged with oblique angle illumination microscopy to confirm their ability to detect effect monomer and dimers of these tags. Using this approach with IRE1, they showed that in the absence of stress, there is a high fraction of apparent IRE1 dimers in the membrane. In response to ER stress, this oligomer size (calculated by correlated trajectories) increased, suggesting that ER stress promotes IRE1 oligomerization, eventually returning to dimers at longer treatment times. Intriguingly, using the ER stressor thapsigargin, the authors indicate that oligomerization precedes auto-phosphorylation of IRE1, suggesting that oligomerization is a key step in the activation of this enzyme. Extending this, the authors then transition to an overexpression model where they incorporate IRE1 constructs containing mutant that disrupt specific parts of the protein or prevent dimeric or oligomeric interactions to probe their importance in this early oligomerization observed in response to ER stress. This demonstrated that the oligomerization was primarily dictated by the ER luminal domain and involved two distinct interfaces specifically required for IRE1 dimer formation (in the absence of stress) and oligomer formation (following ER stress). Ultimately, with these results, the authors propose a model whereby IRE1 exists primarily as a autophosphorylation-deficient, back-to-back dimer that upon ER stress oligomerizes to a phosphorylation competent oligomer that allow autophosphorylations and IRE1 activation. 

      Overall this is an interesting approach and study to define early stages of IRE1 activation. Notably, it reveals a different model of these early stages of IRE1 activation than those previously reported by this group and others using GFP-tagged IRE1 overexpression constructs (something that was enabled by the integration of HALO tags into the genomic locus). The experiments are well performed and the data appear to all be interpreted correctly, although there are a few remaining questions that should still be addressed.

    3. Reviewer #2 (Public Review): 

      The authors investigated changes in the unstressed and stressed oligomeric states of the mammalian endoplasmic reticulum (ER) stress sensor, IRE1a. Previous biochemical and microscopy studies in mammalian cells and studies of the related protein Ire1 in yeast, describe an increase in oligomerization of the stress sensor upon treatment of cells with chemical agents that impair the ER protein folding environment. The general view has been that IRE1 in unstressed cells is a monomer and varying degrees of misfolded protein stress stimulate dimerization, activation, and higher order oligomerization. Distinguishing between monomers and dimers, as well as tetramers or other small oligomers is technically challenging, especially for integral membrane proteins. To address this challenge, the authors turned to single particle tracking fluorescence microscopy of Halo-tagged endogenous IRE1. Using a clever combination of random labeling with two fluorescent dyes and oblique angle illumination to visualize single molecules, as well as dimers, the authors surprisingly find that their endogenous IRE1 reporter appears to be dimeric in homeostatic cells. This observation challenges the predominant model in which IRE1 is monomeric in unstressed cells and that even dimerization represents a switch into an active state. The authors claim to detect evidence for higher order oligomers following treatment with stressors. The authors then use a series of IRE1 mutants to identify how oligomerization is regulated and present a new model to reconcile the different models of IRE1 activation in the literature. 

      The authors have extensively characterized their novel experimental system in terms of protein expression levels, functionality, and ability to distinguish monomers and dimers. The data are well presented and the authors are clearly familiar with the arguments that have surrounded the IRE1 oligomer question. That the authors observe the characteristic XBP1 mRNA splicing activity in the absence of visible large IRE1 clusters may suggest that the large clusters reported by others may have distinct roles, perhaps in more permissive mRNA cleavage. 

      The present study is undermined by two major weaknesses. First, while the authors persuasively demonstrate that they can detect IRE1a dimers, a major claim of the manuscript rests upon detection of tetramers and possibly higher order oligomers. Unfortunately, the authors provide no independent controls to show what tetramer or higher order oligomer data would look like. Thus, the authors can only infer that higher order oligomers are detected, based on modest shifts in the percent of correlated particle trajectories observed in some cells. More robust evidence is needed to make claims of oligomerization. Tools have been developed by others that can induce reversible oligomerization of proteins. Application of these tools would provide powerful controls for tetramers or even higher order oligomers in this study. 

      The second, deeper concern, is the discrepancy between the Halo Tag clustering results in this study and studies by this lab and several other labs that report a distinct stress phenotype. In mammalian cells and yeast, IRE1 and Ire1, tagged with different fluorescent proteins or even a small HA peptide epitope tag, undergo quantitative visible formation of puncta or clusters upon treatment with stressors. The small number of bright clusters that form effectively deplete the rest of the ER of IRE1 signal. In the present study, the authors observe no visible change in IRE1-Halo localization in stress cells. The authors do not investigate the cause of this difference. While one might argue that the presence of stress-inducible IRE1 activity is sufficient to argue that the reporter in this study is functional, IRE1 reporters (that do cluster) described in previous studies by the Walter lab and other groups are also demonstrably functional. Does IRE1 normally cluster? Is it cell-type dependent? Tag-dependent? Notably, the Pincus et al. PLoS Biology paper from the Walter lab used two different fluorescent protein tags that do not heterozygously dimerize. Robust colocalization and FRET signals were detected upon treatment of cells with stressors and clustering was subsequently observed. A 2007 Journal of Cell Biology study from Kimata et al. reported clustering in yeast with an Ire1 tagged with an HA epitope peptide. The HA peptide seems unlikely to be prone to any oligomerization propensities that GFP tagged reporters might experience. Importantly, a 2020 PNAS paper from the Walter lab (Belyy et al.) studied clustering of a robustly monomeric mNeonGreen-tagged IRE1 in U2-OS cells and mouse embryonic fibroblasts and this construct readily clustered following stress induction. 

      When evaluated against the backdrop of the extensive literature describing the visual behavior of IRE1a in live cells, the absence of stress-induced clustering is both puzzling and disconcerting. Given the focus of this study is to use visual techniques to study IRE1a interactions, the burden of proof is on the authors to resolve this significant discrepancy with the rest of the IRE1a literature. One can easily imagine that incorporation of the majority of the pool of IRE1a into 10-100 clusters could produce very different correlated trajectory behavior. Until the authors can determine why their reporters behave differently from other IRE1a reporters and establish which version accurately reflects physiologic IRE1a behavior, the potential impact of the findings of this manuscript are of unknown value.

    1. SciScore for 10.1101/2022.04.12.22273675: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: This study was approved by the institutional review board at Emory University under protocols STUDY00000260, 00022371, and 00045821.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">anti-SARS monoclonal antibody CR302240 was generously provided by Jens Wrammert</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Spike Trimer Capture ELISA: The following ELISA was adapted from previously published methods17: 96-well half area, high binding plates (Corning #3690) were coated with anti-6x-His-tag monoclonal antibody (#MA1-21315MG, ThermoFisher) at 2 µg /mL in PBS at 4°C overnight.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-6x-His-tag</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Approximately one million viable PBMCs were stained with Zombie aqua fixable cell viability dye (BioLegend) to exclude dead cells; washed with PBS containing 2% FBS, referred to as FACS buffer; surface-stained with the following fluorescent monoclonal antibodies: CD3 (clone SK7, BioLegend),</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CD3</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washing with FACS buffer and fixing and permeabilizing cells with Cytofix/Cytoperm (BD Biosciences), the cells were stained intracellularly with the following fluorescent monoclonal antibodies: CD154 (clone CD40L 24-31, BioLegend),</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CD154</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washing with FACS buffer and fixing and permeabilizing cells with Cytofix/Cytoperm (BD Biosciences), the cells were stained intracellularly with the following fluorescent monoclonal antibodies: CD154 (clone CD40L 24-31, BioLegend), IL-2 (clone MQ1-17H12, BD Biosciences), IFN-γ (clone 4S.B3, eBioscience), TNF (clone Mab11, BD Biosciences).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IL-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>IFN-γ</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>TNF</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">IFN-γ spots were detected with biotinylated murine anti-human IFN-γ antibody (clone 7-B6-1, Mabtech), followed by incubation with streptavidin-HRP (BD) and then developed using AEC substrate (EMD Millipore).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IFN-γ</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A HeLa cell line transduced to stably express the human ACE2 receptor (ACE2-HeLa) was generously provided by David Nemazee17.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HeLa</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Wuhan-Hu-1 spike trimer protein expression: Spike trimer plasmids were transiently transfected into Expi293 cells (ThermoFisher) with 5 mM kifunensine (Mfr), purified with His-Trap columns (Cytiva), trimers selected with a Superdex 200 gel filtration column (Mfr), and finished product dialyzed into 20 mM Tris pH 8.0, 200 mM sodium chloride, 0.02% sodium azide by the BioExpression and Fermentation Facility at the University of Georgia.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Expi293</div><div>suggested: RRID:CVCL_D615)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudovirus production: Pseudoviruses were produced by seeding 16 million 293T cells (ATCC CRL-3216) into DMEM with 10% heat-inactivated FBS and 1% GlutaMAX (ThermoFisher) (DMEM-10) in a T-150 flask the night prior to transfection and incubating at 37°C in a humidified 5% CO2 incubator.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">DMEM-10 media was then removed from plates with cells and 50 µl pseudovirus dilutions added onto ACE2-HeLa cells and incubated for two hours at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2-HeLa</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids pCMV ΔR8.2 (</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV ΔR8.2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmid nCoV-2P-F3CH2S43 expressing a His-tagged, pre-fusion stabilized SARS-CoV-2 spike trimer from Wuhan-Hu-1 isolate was generously provided by Jason McLellan.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>nCoV-2P-F3CH2S43</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">On the day of transfection, the HIV-1 lentiviral packaging plasmid, pCMV R8.2 (17.5</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV</div><div>suggested: RRID:Addgene_16459)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sequences from immunocompromised patients were aligned with 301 reference sequences collected from patients within the Emory Healthcare System between 1/1/2021 and 4/30/2021 using MAFFT as implemented in geneious (geneious.com).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MAFFT</div><div>suggested: (MAFFT, RRID:SCR_011811)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A maximum-likelihood tree was constructed using a general time reversible model with empirical base frequencies and a 3 rate model in IQ-TREE version 2.0 with 1,000 ultrafast boostraps38 and visualized in FigTree (http://tree.bio.ed.ac.uk/software/figtree).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IQ-TREE</div><div>suggested: (IQ-TREE, RRID:SCR_017254)</div></div><div style="margin-bottom:8px"><div>FigTree</div><div>suggested: (FigTree, RRID:SCR_008515)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To identify iSNVs, reads were mapped to reference sequence NC_045512.1 using minimap2, variants were called using vphaser2 with maximum strand bias of 5, and variants annotated with SNPeff, all as implemented in viral-ngs version 2.1.19.0-rc119.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SNPeff</div><div>suggested: (SnpEff, RRID:SCR_005191)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To ascertain a precise endpoint titer (ET), curve data (best fit values for the bottom, top, logEC50, and hill slope) were processed by a MATLAB program designed to determine the sample dilution at which each regression curve intersected the healthy control cutoff value.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MATLAB</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washing with FACS buffer and fixing and permeabilizing cells with Cytofix/Cytoperm (BD Biosciences), the cells were stained intracellularly with the following fluorescent monoclonal antibodies: CD154 (clone CD40L 24-31, BioLegend), IL-2 (clone MQ1-17H12, BD Biosciences), IFN-γ (clone 4S.B3, eBioscience), TNF (clone Mab11, BD Biosciences).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BD Biosciences</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Flow cytometry data were collected on an LSR Fortessa (BD Biosciences) and analyzed using FlowJo software V10 (Tree Star).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:


      Limitations to our study include a small number of patients and the use of convenience samples. Larger clinical studies in immunocompromised populations are needed, including serial sampling to further elucidate therapies that promote immune evasion. Our work and others’ emphasize the need to both protect immunocompromised patients from acquiring infection, and to prevent the forward spread of viruses with immune escape mutations. Such needs might be met with broad spectrum monoclonal antibodies and next generation SARS-CoV-2 vaccines that induce potent neutralizing antibody responses to prevent infection and memory CD8+ T cell responses to control breakthrough.


      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.04.19.488806: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">16 Anti-His tag and microtubule-associated protein 1 light chain 3 beta (LC3) Antibodies were purchased from Millipore Sigma (Burlington, MA, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>16 Anti-His tag</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>microtubule-associated protein 1 light chain 3 beta (LC3) Antibodies</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-Adipose Differentiation-Related Protein (ADRP, or Perilipin-2, PLIN2), Nrf2, prostaglandin E synthase 2 (PTGS2), and PI3K-beta antibodies were obtained from ProteinTech (Rosemont, IL, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-Adipose Differentiation-Related Protein ( ADRP</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>PLIN2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Nrf2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>PTGS2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>PI3K-beta</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-ATG7 antibody was purchased from Abcam (Waltham, MA, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-ATG7</div><div>suggested: (Abcam Cat# 2054-1, RRID:AB_991677)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-SRB1 antibody was obtained from Novus (Centennial, CO, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-SRB1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-Fth1, HRP-anti-rabbit or mouse secondary antibodies, and RIPA lysis buffer were obtained from Santa Cruz Biotech (Dallas, TX, USA)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-Fth1 , HRP-anti-rabbit or mouse secondary antibodies</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Anti-Fth1 ,</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HRP-anti-rabbit</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Palmitic acid (PA)-induced lipotoxicity assay: The HEK293, HEK_pcDNA and HEK_Spike cells were cultured in a 96-well plate and reached 80% confluence on the next day before treatment.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HEK_Spike</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">H9C2 cells (ATCC, Manassas, VA, USA) were cultured in DMEM (10% FBS) medium in a 96 well-plate with 80% confluence.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>H9C2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">16 The sequence was cloned into a pcDNA3.1 vector to obtain pcDNA-Spike.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The individual colonies with stable integration of the pcDNA-Spike (HEK_Spike) or pcDNA vector (HEK_pcDNA) were selected and expanded.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA-Spike</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pcDNA</div><div>suggested: RRID:Addgene_66792)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Viral production and H9C2 cell culture: The Spike gene was cleaved from pcDNA-Spike plasmid and cloned into lentiviral vector pLV-mCherry (Addgene, Watertown, MA, USA) with removal of mCherry gene to generate pLV-Spike plasmid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLV-Spike</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The control virus with VSV-G as the tropism and expression of mCherry was generated by co-transfection of pLV-mCherry and pMD2.G vector (Addgene, Watertown, MA, USA) into the Phoenix cells, which was referred to as VSV-G virus.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLV-mCherry</div><div>suggested: RRID:Addgene_36084)</div></div><div style="margin-bottom:8px"><div>pMD2.G</div><div>suggested: RRID:Addgene_12259)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • No funding statement was detected.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.04.19.488067: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Each Newick file is parsed by a python script which generates a CSV file of edges in the TAG.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>python</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Another option is to use Gephi, but to use this tool, users need to start listening for data streams in Gephi before executing an APOC graph streaming query to push the data to the app.[6] Alternatively, users can connect using the Neo4j plugin for Cytoscape.[7] We found this option to be the most intuitive and sustainable for ad-hoc visualization since you can remotely connect to the graph using a read only user account on the database.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Gephi</div><div>suggested: (Gephi, RRID:SCR_004293)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • No funding statement was detected.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.04.19.488843: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IACUC: All animal experiments were approved by the Academia Sinica Institutional Animal Care and Use Committee (IACUC protocol No.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Four- to six-week-old female BALB/c mice were immunized with 5 μg of the Kappa spike and RBD mRNA-LNP by intramuscular (I.M.) injection.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-RBD and control antibodies were added to the plates and incubated for 1 h at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-RBD</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then, the cells were washed and horseradish peroxidase-conjugated anti-human antibody (1:2000) was added for 1 h at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human antibody</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After four inoculations with the same concentration of mRNA-LNP, the splenocytes from immunized mice were harvested and fused with mouse myeloma NS-1 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>NS-1</div><div>suggested: RRID:CVCL_IV58)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The pseudovirus neutralization assays were performed using HEK293T cells that expressed human ACE2 (HEK293T/hACE2)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The mixtures were then added to pre-seeded HEK293T/hACE2 cells for 24 h at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T/hACE2</div><div>suggested: RRID:CVCL_A7UK)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Four- to six-week-old female BALB/c mice were immunized with 5 μg of the Kappa spike and RBD mRNA-LNP by intramuscular (I.M.) injection.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BALB/c</div><div>suggested: RRID:IMSR_ORNL:BALB/cRl)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The PCR products were cloned using the pGEM-T Easy Vector System (Promega) and analyzed by DNA sequencing.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pGEM-T Easy</div><div>suggested: RRID:Addgene_86229)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The resulting VH was cloned into a modified pcDNA5-FRT-Gamma1 expression vector with human IgG1 constant region.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA5-FRT-Gamma1</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Recombinant protein-based ELISA: Recombinant RBD and spike-His tag proteins for different SARS-CoV-2 variants were purchased from ACROBiosystems.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACROBiosystems</div><div>suggested: (ACRObiosystems, RRID:SCR_012550)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The half maximal inhibitory concentration (IC50) was calculated by nonlinear regression using Prism software version 8.1.0 (</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">GraphPad Software Inc.)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">From the sequences, the framework regions (FRs) and complementarity determining regions (CDRs) were defined by searching with the NCBI IgBLAST program (https://www.ncbi.nlm.nih.gov/igblast/).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgBLAST</div><div>suggested: (IgBLAST, RRID:SCR_002873)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After analyzing the structure with PyMOL software, we identified the key amino acid residues at which mutations may impact the original conformation of the CDRs.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PyMOL</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. On 26 November 2021, WHO designated the variant B.1.1.529 a variant of concern, named Omicron, on the advice of WHO’s Technical Advisory Group on Virus Evolution (TAG-VE).  This decision was based on the evidence presented to the TAG-VE that Omicron has several mutations that may have an impact on how it behaves, for example, on how easily it spreads or the severity of illness it causes. Here is a summary of what is currently known.  
    1. I thank researchers from and for sharing information with @WHO & the world about B.1.1.529 variant that has been recently detected. We will convene our TAG-VE again today to discuss Everyone out there: do not discriminate against countries that share their findings openly
    1. Finally, among your data, if an apperance set contains any reserved roles, then the posits containing the set are classified as peridata.

      reserved roles

      peridata

    1. • When the customer's payment details are successfully authenticated by the bank, the Payment state changes to Authorized. • The amount deducted from the customer’s account by Razorpay is not settled to your account until the payment is captured, either manually or automatically. • There can be scenarios where payment is interrupted due to external factors, such as network issues or technical errors at the customer's or bank's end. In this case, the amount may get debited from the customer's bank account but the payment status is not received by Razorpay from the bank. This is termed as Late Authorization.

      check if the bullet symbol has been used, or it is ul li tag I had replaced the bullets. I hope the content has not been overwritten

    1. SciScore for 10.1101/2022.04.12.488087: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: Immunization of alpaca, construction of yeast display VHH library, and isolation of VHH yeasts specific for SARS-CoV-2 and SARS-CoV-1 spikes: The animal experiment protocol involving immunization, collection of blood samples, and construction of VHH library was approved by IACUC at NBbiolab, Inc. in Chengdu, China.<br>IACUC: Immunization of alpaca, construction of yeast display VHH library, and isolation of VHH yeasts specific for SARS-CoV-2 and SARS-CoV-1 spikes: The animal experiment protocol involving immunization, collection of blood samples, and construction of VHH library was approved by IACUC at NBbiolab, Inc. in Chengdu, China.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Eight-week-old female K18-hACE2 transgenic mice (InVivos Ptd Ltd, Lim Chu Kang, Singapore) were used for this study.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After extensive wash with cold PBS+1%FBS, the yeast clones were incubated with HA-Tag (6E2) mouse monoclonal antibody conjugated with Alexa Fluor® 488 (1:100 dilution) and eBioscience™ streptavidin conjugated with PE Conjugate (1:200 dilution) on ice for 30 min.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HA-Tag</div><div>suggested: (Cell Signaling Technology Cat# 2350, RRID:AB_491023)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cells were then fixed, permeabilized, and incubated with cross-reactive rabbit anti-SARS-CoV-N IgG (Sino Biological, Inc., China) for 1 h at room temperature before adding an HRP-conjugated goat anti-rabbit IgG antibody (Jackson ImmunoResearch, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-N IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-rabbit IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sections were then covered with rabbit anti-SARS-CoV-2 N protein monoclonal antibody (Abcam; 1:1000) for 1 h at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 N protein</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell lines: HEK293T cells (ATCC, CRL-3216) and HeLa cells expressing hACE2 were kindly provided by Dr. Qiang Ding at Tsinghua University.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HeLa</div><div>suggested: CLS Cat# 300194/p772_HeLa, RRID:CVCL_0030)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sf9 cells (ATCC) were maintained at 27°C in Sf-900 II SFM medium.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Sf9</div><div>suggested: RRID:CVCL_4U10)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression and production of nanobodies were conducted by transfecting the expression vectors into the HEK293F cells using polyethyleneimine (PEI) (Polysciences).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293F</div><div>suggested: RRID:CVCL_6642)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Specifically, human immunodeficiency virus backbones expressing firefly luciferase (pNL4-3-R-E-luciferase) and pcDNA3.1 vector encoding either SARS-CoV-2 or sarbecovirus spike proteins were co-transfected into the HEK-293T cells (ATCC).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK-293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HeLa-ACE2 cells were then added to the mixture of nanobody-pseudovirus, incubated at 37°C for additional 48 h, and lysed for measuring luciferase-activity.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HeLa-ACE2</div><div>suggested: JCRB Cat# JCRB1845, RRID:CVCL_B3LW)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Tissues were homogenized with 0.5 mL DMEM supplemented with antibiotic and antimycotic (Gibco, Waltham, MA, USA) and titrated in Vero E6 cells using plaque assays.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: RRID:CVCL_XD71)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Eight-week-old female K18-hACE2 transgenic mice (InVivos Ptd Ltd, Lim Chu Kang, Singapore) were used for this study.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>K18-hACE2</div><div>suggested: RRID:IMSR_GPT:T037657)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell lines: HEK293T cells (ATCC, CRL-3216) and HeLa cells expressing hACE2 were kindly provided by Dr. Qiang Ding at Tsinghua University.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>hACE2</div><div>suggested: RRID:Addgene_1786)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">VHH sequences were amplified by PCR, cloned into a yeast surface display vector pYD1, and introduced into the electrocompetent EBY100 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pYD1</div><div>suggested: RRID:Addgene_73447)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For the former, VHH genes were cloned into the multiple cloning sites of pMD18T containing the upstream CMV promoter, the secretory signal sequence from the mouse Ig heavy chain, and the downstream human IgG1 Fc gene fragment and SV40 poly (A) signal sequence.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pMD18T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For the latter, selected VHH genes were cloned into pVRC8400 vector with a 6xHis tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pVRC8400</div><div>suggested: RRID:Addgene_63163)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Specifically, human immunodeficiency virus backbones expressing firefly luciferase (pNL4-3-R-E-luciferase) and pcDNA3.1 vector encoding either SARS-CoV-2 or sarbecovirus spike proteins were co-transfected into the HEK-293T cells (ATCC).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNL4-3-R-E-luciferase</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The IC50 values were calculated based on the reduction of 50% relative light units (Bright-Glo Luciferase Assay Vector System, Promega, USA) compared to the virus-only control, using Prism 8.0 (GraphPad Software Inc., USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Phylogenetic tree and genetic analysis of nanobodies: Neighbor-joining phylogenetic trees were generated using MEGA version 10.1.8 with 1000 bootstrap replicates 68.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MEGA</div><div>suggested: (Mega BLAST, RRID:SCR_011920)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Chord diagrams showing the germline gene usages and V/J gene pairing were analyzed and presented by the R package circlize version 0.4.13 69.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>circlize</div><div>suggested: (circlize, RRID:SCR_002141)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sequence logo were plotted using Python package Logomaker 70</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Python</div><div>suggested: (IPython, RRID:SCR_001658)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Subsequent model building and refinement were performed using COOT (PMID: 15572765) and PHENIX (PMID: 12393927), respectively.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>COOT</div><div>suggested: (Coot, RRID:SCR_014222)</div></div><div style="margin-bottom:8px"><div>PHENIX</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All structure figures were generated with ChimeraX and Pymol (PMID: 28158668)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ChimeraX</div><div>suggested: (UCSF ChimeraX, RRID:SCR_015872)</div></div><div style="margin-bottom:8px"><div>Pymol</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Half-maximal inhibitory concentration (IC50) of nanobodies was calculated by the equation of four-parameter dose inhibition response using Graphpad Prism 8.0.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Graphpad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. dstillman May 11, 2020 You can see JavaScript API, but there's not much documentation currently.Not tested, but running this from Tools → Developer → Run JavaScript will probably work:var items = await Zotero.Items.getAll(Zotero.Libraries.userLibraryID, true);for (let item of items) { if (!item.isRegularItem()) continue; let ids = item.getAttachments(); for (let id of ids) { let attachment = await Zotero.Items.getAsync(id); let tags = attachment.getTags(); for (let tag of tags) { item.addTag(tag.tag); } attachment.setTags([]); await item.saveTx({ skipDateModifiedUpdate: true }); await attachment.saveTx({ skipDateModifiedUpdate: true }); }}
      • EXAMPLE
    1. SciScore for 10.1101/2022.04.09.487739: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The membrane was incubated with ACE-2 Antibody (1:2,000, Novus Biologicals, CO, USA), Myc-Tag (9B11</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Myc-Tag</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The membrane was then incubated with secondary HRP-linked, Anti-rabbit IgG (1:10,000, Cell Signaling Technology, MA, USA) and Goat anti-Mouse IgG (H+L) Cross-Adsorbed Secondary Antibody, HRP (1:2,000, Thermo Fisher Scientific, MA, USA) for 1 h at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-rabbit IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-Mouse IgG</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293T cells were cultured in FP medium (DMEM containing 10% FBS, 2 mM GlutaMAX™ Supplement, 0.1 mM MEM Non-Essential Amino Acids, 50 U/mL and 50 μg/mL Penicillin-Streptomycin).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To establish ACE2-expressed cell line (ACE2-HEK293T cells), HEK293T cells were infected with ACE2-expressing lentivirus and ACE2-positive cells were selected by 2 ug/mL of puromycin.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2-HEK293T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For protein expression, the cell membrane penetrating peptide (TAT), red fluorescence protein (DsRed) and NK-NT or NKN1 fragments were cloned into pET6xHN-N Vector (Takara, CA, USA)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET6xHN-N</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For ACE2-expressing lentivirus packaging, pscALPSpuro-HsACE2 (human) (Addgene, MA, USA) were co-transfected with psPAX2 and pCMV-VSV-G packaging plasmids into HEK293T cells using FuGENE 6 (Promega, WI, USA)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV-VSV-G</div><div>suggested: RRID:Addgene_8454)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For doxycycline (Dox) inducible, Spike protein pseudotyped luciferase-expressing lentivirus preparation, HEK293T cells were transfected with FUW-RLuc-T2A-PuroR(Kanarek et al., 2018) (Addgene, MA), psPAX2 and pUNO1-SARS2-S (D614G) (InvivoGen, CA) packaging plasmids using FuGENE 6.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>psPAX2</div><div>suggested: RRID:Addgene_12260)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In competition BiFC Assay, HEK293T cells were co-transfected with 0.5 μg of each construct expressed in pBiFC-VN155 (I152L) and 0.5 μg pBiFC-VC155 vectors, together with and 5 μg competitor constructs with stop codon in pBiFC-VN155 (I152L) vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pBiFC-VC155</div><div>suggested: RRID:Addgene_22011)</div></div><div style="margin-bottom:8px"><div>pBiFC-VN155</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Fluorescence images were taken at 24 h and 48 h after transfection using a Nikon fluorescence microscope and fluorescence intensity was quantified by Image J.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Image J</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.04.11.487660: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">C5 affinity maturation library construction: The sequence of C5 in phagemid pComb3XSS were used as template for library construction.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pComb3XSS</div><div>suggested: RRID:Addgene_63890)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Nanobody expression and purification: The cDNA encoding the nanobodies in the pComb3XSS vector were PCR amplified and subcloned into vector pET22b to express 6×His tagged proteins.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET22b</div><div>suggested: RRID:Addgene_84863)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The coding cDNA of 1ZVH was chemically synthesized and subcloned into a modified phage display vector of pComb3XSS, in which the amber stop codon (TAG) were mutated to CAG to facilitate nanobody display in E. coli without gene supE, e.g. SS320(Genentech).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Genentech</div><div>suggested: (Genentech, RRID:SCR_003997)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Standard variation values were calculated using a 3-parameter logistic regression fit using Prism Software (GraphPad).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data were acquired using the SerialEM software on an FEI Tecnai F30 transmission electron microscope (ThermoFisher Scientific) operated at 300 kV and equipped with a Gatan K3 direct detector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SerialEM</div><div>suggested: (SerialEM, RRID:SCR_017293)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Image processing and 3D reconstruction: Drift and beam-induced motion correction were performed with MotionCor2 [61] to produce a micrograph from each movie.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MotionCor2</div><div>suggested: (MotionCor2, RRID:SCR_016499)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Contrast transfer function (CTF) fitting and phase-shift estimation were conducted with Gctf [62].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Gctf</div><div>suggested: (GCTF, RRID:SCR_016500)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Local map resolution was estimated with ResMap [65].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ResMap</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">We initially fitted the templates models into the corresponding final cryo-EM map using Chimera [67], and further corrected and adjusted them manually by real-space refinement in Coot [68].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Chimera</div><div>suggested: (Chimera, RRID:SCR_002959)</div></div><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The resulting models were then refined with phenix.real_space_refine in PHENIX [69].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PHENIX</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The final atomic models were validated with Molprobity [70, 71].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Molprobity</div><div>suggested: (MolProbity, RRID:SCR_014226)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All figures were generated with Chimera or ChimeraX [72, 73].</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ChimeraX</div><div>suggested: (UCSF ChimeraX, RRID:SCR_015872)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • No funding statement was detected.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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    1. SciScore for 10.1101/2022.04.11.487879: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Consent: All participants in the convalescent cohort provided informed consent for their blood products to be used for research purposes by signing the standard New York Blood Center (NYBC<br>IRB: For participants who received the SARS-CoV-2 mRNA-1273 vaccine (Moderna), whole blood, plasma and serum samples were obtained at the NIH Clinical Research Center in Bethesda, MD under protocols approved by the NIH Institutional Review Board, ClinicalTrials<br>IACUC: Animal ethics statement: Animal research was conducted under an IACUC approved protocols at the Integrated Research Facility, Frederick, Maryland, in compliance with the Animal Welfare Act and other federal statutes and regulations relating to animals and experiments involving animals.<br>Field Sample Permit: Animal ethics statement: Animal research was conducted under an IACUC approved protocols at the Integrated Research Facility, Frederick, Maryland, in compliance with the Animal Welfare Act and other federal statutes and regulations relating to animals and experiments involving animals.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Hamsterization of human monoclonal antibodies: Genomes corresponding to the mouse IgG2a heavy and light chains were aligned to the genome assembly MesAur1.0 (GCA_000349665.1) for a female Syrian golden hamster downloaded from Genbank.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">No randomization or blinding was applied to the analysis of participants’ plasma, serum or PBMC samples, but all samples were anonymized before being used in this study.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">No randomization or blinding was applied to the analysis of participants’ plasma, serum or PBMC samples, but all samples were anonymized before being used in this study.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Binding of secreted antibody to the beads was detected in the CY5 or TRED channels by capturing images at 6 min intervals over a 30 min time course.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CY5</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Shotgun mutagenesis epitope mapping of antibodies by alanine scanning: Epitope mapping was performed essentially as previously described (43), using a SARS-CoV-2 (Wuhan Hu-1 strain) S2 subunit shotgun mutagenesis mutation library, made using a full-length expression construct for the SARS-CoV-2 spike glycoprotein.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2 spike glycoprotein .</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Vaccinee and convalescent plasma binding to peptides: Polyclonal IgG antibodies from plasma or sera of vaccinated, convalescent, or naïve donors were purified using the Pierce Protein G Spin Plate (Thermo Scientific).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Polyclonal IgG</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Baculoviruses were produced by transfection of bacmid DNA into Sf9 cells and used to infect High Five cells (Life Technologies) at high (5 to 10) multiplicity of infection (MOI).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Sf9</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasma IgG reactivity to human coronaviruses and donor selection: Multiplexed beads for SARS-CoV-2, SARS-CoV-1, MERS-CoV, HCoV-OC43, HCoV-HKU1, HCoV-229E and HCoV-NL63 spike proteins, as well as CD4 as a negative control, were incubated with donor plasma diluted at 1/50, 1/250 or 1/1250 for 30 min at room temperature, then washed and stained with 2.5 μg/mL goat anti-human IgG Alexa Fluor 647 (Jackson ImmunoResearch, 109-606-170).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HCoV-229E</div><div>suggested: JCRB Cat# JCRB1838, RRID:CVCL_B3M4)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">mAbs were also expressed in-house by transient transfection of Expi293 cells (Gibco, A14527) using the ExpiFectamine 293 Transfection Kit (Gibco, A14524) according to manufacturer’s instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Expi293</div><div>suggested: RRID:CVCL_D615)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To generate green fluorescent protein (GFP)-tagged receptor cell lines, HeLa-ACE2 cells were transduced with lentivirus encoding GFP and sorted to collect the GFPhigh/ACE2high population.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HeLa-ACE2</div><div>suggested: JCRB Cat# JCRB1845, RRID:CVCL_B3LW)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">mAbs were added to the wells at a final concentration of 200 μg/mL and cultures were further incubated at 37 °C for 1h. 8,000 GFP+/ACE2+ HeLa cells were then added to each well and the co-cultures were maintained overnight to allow for syncytia development.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HeLa</div><div>suggested: CLS Cat# 300194/p772_HeLa, RRID:CVCL_0030)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A plasmid encoding cDNA for each spike protein mutant was transfected into HEK-293T cells and allowed to express for 22 h.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK-293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For neutralization assays, 5 × 104 RD cells were inoculated at TCID75% OC43-GFP virus and incubated for 1h at 35°C. 4-fold serial dilutions (73 ng/mL - 300 μg/mL) of each mAb were incubated with TCID75 OC43-GFP virus for 1h at 35°C. 60 μL of mAb- virus mixture was used to inoculate each well containing 5 × 104 RD cells and cultures were incubated for 24 h at 35°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RD</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">transducing plasmid pHR’ CMV-Luc, a TMPRSS2 plasmid and full-length spike plasmids from SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-NL63 and HCoV-229E into 293T cells using Lipofectamine 3000 transfection reagent (ThermoFisher Scientific, Asheville, NC, L3000-001) (49). 293 flpin-TMPRSS2-ACE2 cells (provided by Dr. Adrian Creanga, VRC/NIH) were used for SARS-CoV-2, SARS-CoV and hCoV-NL63 while HuH7.5 cells were used for MERS-CoV and hCoV-229E neutralization assay.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HCoV-NL63</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>293T</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HuH7.5</div><div>suggested: RRID:CVCL_7927)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS: Addgene #170447; SARS2 #170442; MERS #170448; NL63 #172666; alpha strain #170451; beta #170449; gamma #170450; delta #172320; omicron 180375) were co-transfected in HEK293T with Lipofectamine 2000 (ThermoFisher Scientific, 11668019) to produce single-round infection-competent pseudoviruses.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS: Addgene #170447; SARS2 #170442; MERS #170448; NL63 #172666; alpha strain #170451; beta #170449; gamma #170450; delta #172320; omicron 180375) were co-transfected in HEK293T with Lipofectamine 2000 (ThermoFisher Scientific, 11668019) to produce single-round infection-competent pseudoviruses.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>#172666</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pre-fusion stabilized constructs for CCoV HuPn-2018 (Accession # QVL91811.1, aa1-1384 with E1140P and E1141P mutations) and PdCoV0081-4 ( Accession # MW685622.1, aa1-1092 with E854P and V855P mutations) were synthesized and cloned into pCDNA3.1- vectors (Genscript) with the following C-terminal modifications: T4 fibritin trimerization motif, HRV3C protease cleavage site, poly-GS linker, Avi-tag, and 8× His tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCDNA3.1-</div><div>suggested: RRID:Addgene_52535)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, the SARS-CoV-2 NTD and RBD were cloned into an in-house pFastBac vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pFastBac</div><div>suggested: RRID:Addgene_1925)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The spike S2 domain (699 to 1207 with F817P, A892P, A899P, A942P, K986P, V987P) was constructed into phCMV3 vector which contained an N-terminal secreting signal peptide, and C-terminal thrombin cleavage site and His6 tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>phCMV3</div><div>suggested: RRID:Addgene_173431)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 RBD, SARS- CoV-2 NTD, SARS-CoV-1 spike and SARS-CoV-1 RBD, MERS-CoV spike, OC43-CoV spike, CCoV-HuPn-2018 spike, pPDCoV-0081-4 spike, HCoV-NL63 spike, HCoV-229E spike, HCoV- HKU1 spike, H1 HA and recombinant CD4 (gifted by Gavin Wright, (35)).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pPDCoV-0081-4</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Spike-containing lentiviral pseudovirions were produced by co-transfection of packaging plasmid pCMVdR8.2,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMVdR8.2</div><div>suggested: RRID:Addgene_8455)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">transducing plasmid pHR’ CMV-Luc, a TMPRSS2 plasmid and full-length spike plasmids from SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-NL63 and HCoV-229E into 293T cells using Lipofectamine 3000 transfection reagent (ThermoFisher Scientific, Asheville, NC, L3000-001) (49). 293 flpin-TMPRSS2-ACE2 cells (provided by Dr. Adrian Creanga, VRC/NIH) were used for SARS-CoV-2, SARS-CoV and hCoV-NL63 while HuH7.5 cells were used for MERS-CoV and hCoV-229E neutralization assay.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pHR’</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>TMPRSS2</div><div>suggested: RRID:Addgene_53887)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">2.5μg 2nd generation lentivirus backbone plasmid pCMV-dR8.2 dvpr (Addgene, 8455), 2μg pBOBI-FLuc (Addgene, 170674) and 1μg truncated coronavirus spike expressing plasmids (</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV-dR8.2</div><div>suggested: RRID:Addgene_8455)</div></div><div style="margin-bottom:8px"><div>pBOBI-FLuc</div><div>suggested: RRID:Addgene_170674)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Hamster genes with the highest homology to the mouse IgG2a heavy chain, lambda and kappa light chains genes were cloned into a pCDNA3.4 vector (Genscript) and expressed in Expi293 cells as described above.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCDNA3.4</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">) high-throughput flow cytometer and FACS data were analysed with FlowJo (Version 10.8.1</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Analyses of the VH and Vλ/Vκ genes, CDR3 sequences, and percentage of somatic mutations were carried out using Geneious Prime (Version 2021.0.3, https://www.geneious.com) and the International Immunogenetics Information System database (IMGT, http://www.imgt.org/) (40).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>https://www.geneious.com</div><div>suggested: (Geneious, RRID:SCR_010519)</div></div><div style="margin-bottom:8px"><div>http://www.imgt.org/</div><div>suggested: (IMGT - the international ImMunoGeneTics information system, RRID:SCR_012780)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Recombinant IgG mAbs were purified using HiTrap Protein A columns (Cytiva/GE Healthcare Life Sciences, 17040303).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Cytiva/GE Healthcare</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Phylogenetic tree generation: Full-length amino acid sequences of SARS-CoV-2 (accession #NC_045512.2), SARS-CoV (accession # AY278741.1), MERS-CoV (accession # NC_019843) , HCoV-NL63 (accession #NC_005831.2), HCoV-229E (accession #NC_002645.1), CCoV HuPn-2018 (accession #MW591993.2) and PDCov-0081-4 (accession #MW685622) were aligned using the L-INS-i method of MAFFT version 7.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MAFFT</div><div>suggested: (MAFFT, RRID:SCR_011811)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sequence alignment was used to generate a sequence logo plot using the Weblogo 3.0 server and to color conserved amino acid residues on a pre-fusion stabilized spike protein (PDB 6VSB).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Weblogo</div><div>suggested: (WEBLOGO, RRID:SCR_010236)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Images were acquired in A488, A568 and DAPI channels using a BZ-X fluorescence microscope (KEYENCE) and processed using Fiji ImageJ (42)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Iterative model building and refinement were carried out in Coot (46) and PHENIX (47), respectively.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div><div style="margin-bottom:8px"><div>PHENIX</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Authentic OC43-CoV-GFP virus propagation and neutralization assay: Rhabdomyosarcoma cells (RD, ATCC CCL-136) were maintained at 37°C and 5% CO2 in No-glucose DMEM (Gibco, 11966-025), supplemented with 10% HI-FBS, 4500 mg/mL glucose, 1 mM sodium pyruvate (Gibco, 11360-070), 1 mM HEPES (Gibco, 15630-080) and 50 μg/mL gentamycin (Quality Biological, 120-098-661)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Quality Biological</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">50% neutralization titers (NT50) were calculated using the dose- response-inhibition model with 5-parameter Hill slope equation in GraphPad Prism 9.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Descriptive statistics (mean ± SEM or mean ± SD) and statistical analyses were performed using Prism version 9.3.1 (GraphPad).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT00001281</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Studies of Blood and Reproductive Fluids in HIV-Infected and…</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT05078905</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Vaccine Responses to SARS-CoV-2 and Other Emerging Infectiou…</td></tr></table>


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a protocol registration statement.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. Are you ready to annotate?

      Hello friends, colleagues, and all others that I hope become part of the first two categories. I am Alan Levine, coming to you from central Canada. Welcome to my unorthodox workshop. I am so web old I can remember annotations in the first Mosaic browser.

      Please reply with your own introduction, and share your experience, interest in web annotation.

      Do not forget to tag all responses oer22 in this workshop !

    1. These callbacks are focused on the transactions, instead of specific model actions.

      At least I think this is talking about this as limitation/problem.

      The limitation/problem being that it's not good/useful for performing after-transaction code only for specific actions.

      But the next sentence "This is beneficial..." seems contradictory, so I'm a bit confused/unclear of what the intention is...

      Looking at this project more, it doesn't appear to solve the "after-transaction code only for specific actions" problem like I initially thought it did (and like https://github.com/grosser/ar_after_transaction does), so I believe I was mistaken. Still not sure what is meant by "instead of specific model actions". Are they claiming that "before_commit_on_create" for example is a "specific model action"? (hardly!) That seems almost identical to the (not specific enough) callbacks provided natively by Rails. Oh yeah, I guess they do point out that Rails 3 adds this functionality, so this gem is only needed for Rails 2.

    1. SciScore for 10.1101/2022.04.11.487828: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For detection of S protein, the membrane was incubated with anti-HA tag mouse monoclonal antibody (bimake, USA,1:2000), and the bound antibodies were detected by Horseradish Peroxidase (HRP)-conjugated goat anti-mouse IgG (Abbkine, China, 1:5,000).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-HA</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For detection of HIV-1 p24 in supernatants, monoclonal antibody against HIV p24 (p24 MAb) was used as the primary antibody at a dilution of 1:8,000, followed by incubation with HRP-conjugated goat anti-mouse IgG at the same dilution.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HIV-1</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HIV</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-mouse IgG</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell lines and plasmid construction: HEK293T and Hela cells were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 100 units of penicillin and 0.1 mg/ml of streptomycin in 5% CO2 at 37 °C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Hela</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In brief, one day prior to transfection for virus production, HEK293T cells were digested and adjusted to an amount of 7×106 cells in a 10cm culture medium and incubated overnight in an incubator at 37 °C with 5% CO2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">pcDNA3.1-S2 plasmid was used as the template to generate the plasmid with mutagenesis in S gene.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1-S2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">When cells reached 80%-90% confluence, HEK293T cells were co-transfected with a luciferase-expressing HIV-1 plasmid (pNL4-3.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HIV-1</div><div>suggested: RRID:Addgene_115809)</div></div><div style="margin-bottom:8px"><div>pNL4-3</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The P24 gene of HIV virus was cloned into the vector pCDNA3.1(+) as a plasmid standard, with the viral copy number calculated accordingly.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Phylogenetic analysis and sequence alignment: The ACE2 aa sequences were aligned by MAFFT v7.149 in BioAider.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MAFFT</div><div>suggested: (MAFFT, RRID:SCR_011811)</div></div><div style="margin-bottom:8px"><div>BioAider</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then we constructed the maximum likelihood phylogenetic tree of ACE2 by IQ-tree v1.6.10 program with 10,000 ultrafast bootstraps (https://academic.oup.com/mbe/article/32/1/268/2925592), and the most appropriate evolutionary model was JTTDCMut+G4 which calculated using ModelFinder according to the bayesian information criterions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IQ-tree</div><div>suggested: (IQ-TREE, RRID:SCR_017254)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The mutations in the models were aligned, and the interactions between the SARS-CoV-2 S and ACE2 proteins were compared in PyMOL.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PyMOL</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. Im Mittelpunkt der emanzipatorischen Kritiksteht die Praxis. Als Gegenwartskritik stellt sie Diagnosen von Un-recht und greift in das Geschehen durch Stellungnahmen ein, denenüber eine Wissenschaftsgemeinschaft hinaus Gehör verschafft wird.

      hashtag metoo, FFF, Feministischer Kampftag, Tag der Arbeiter*innen, weitere Beispiele?

    Annotators

    1. Author Response:

      Reviewer #1 (Public Review):

      The integrated stress response (ISR) controls cellular protein synthesis in response to diverse stimuli. A set of related protein kinases, with distinct regulatory domains that respond to different stress conditions, share a common kinase domain that specifically phosphorylates the translation factor eIF2 on its alpha subunit. Phosphorylation of eIF2 inhibits translation by inactivating eIF2B, the guanine nucleotide exchange factor (GEF) for eIF2. The decameric eIF2B, a dimer of heteropentamers, is the key control hub of the ISR. Previously, a small molecule inhibitor of the ISR called ISRIB was found to bind to eIF2B and was proposed to reverse the impacts of eIF2 phosphorylation by increasing stabilizing the association of eIF2B heteropentamers into the functional decameric complex. However, more recently, an alternative model ISRIB action has been proposed. eIF2B is proposed to toggle between inactivate and active states. Binding of phosphorylated eIF2 to a regulatory site is proposed to trigger the inactive state by allosterically weakening binding of eIF2 at the active site. In the new model, ISRIB has been proposed to favor the active state conformation of eIF2B and thereby overcome the effects of eIF2 phosphorylation.

      In this paper, the authors further study a previously described H160D mutation in the eIF2Bbeta subunit. This mutation at one of the dimer interfaces in eIF2B was previously proposed to inhibit eIF2B by weakening dimerization. Consistent with this hypothesis, the H160D mutation impaired dimerization of eIF2B(beta, gamma, delta, epsilon) tetramers. However, in this study, the authors show that the H160D mutation does not impair dimerization when eIF2Balpha is included; thus, the mutation impairs eIF2B activity without impairing dimerization. Using biochemical assays, the authors show that the H160D mutation impairs nucleotide exchange by eIF2B decamers and weakens the binding eIF2 to eIF2B. However, the binding of phosphorylated eIF2 to eIF2B is not weakened.

      Cryo-EM structural analysis of the mutant eIF2B complex reveals a partial rocking of the decameric structure that resembles the structure of the eIF2B complex when bound to its inhibitor phosphorylated eIF2. In this partially rocked structure, both the ISRIB binding site at the dimer interface and the functional eIF2alpha binding sites are widened, providing a structural solution to why the mutation weakens eIF2 binding. Interestingly, the inhibitory binding site for phosphorylated eIF2 is not affected the H160D mutation. The authors propose that the H160D mutation in eIF2Bbeta induces an allosteric conformational change that mimics the effects of phosphorylated eIF2 binding to eIF2B.

      Finally, the authors generated cell lines that exclusively express the mutant eIF2Bbeta subunit. The mutation impairs total protein synthesis and cell growth rate and leads to elevated expression of the ISR marker ATF4.

      This is a high-quality study, the results are convincing and the authors conclusions are supported by the data. As the ISR has been implicated in a variety of diseases, further elucidation of the mechanism of action of eIF2B and ISRIB will be critical in the development of therapeutic interventions.

      A weakness of the paper (that hopefully can be easily remedied) would be to show the quality control data to verify the mutant cell lines used in Figure 6. It would be good to see that the mutant allele is present in the cells and that no WT alleles remain. In addition, examination of eIF2alpha Ser51 phosphorylation in Figure 6A would strengthen the conclusion that the eIF2Bbeta mutation is activating ATF4 expression independent of changes in eIF2 phosphorylation. Also, use of ATF4 reporters in Figure 6A, in addition to the presented Western data, would provide a nice quantitative read-out for the impact of the H160D mutation on ATF4 mRNA translation. Finally, as the biochemical and structural data indicate that the H160D mutation impairs ISRIB activity, it would be worthwhile testing whether ISRIB will rescue the slow-growth of the H160D cell lines in Figure 6D (the anticipation is that this slow-growth phenotype will not be rescued by ISRIB).

      • The genotype of our cell lines at the EIF2B2 target locus was screened for by PCR + restriction enzyme digest, and later sequence verified by deep sequencing. We used the CRISPResso2 pipeline to calculate allele frequencies and HDR editing efficiencies from the sequencing data, and now also include those results in a supplementary figure (Figure 6 – supplementary figure 1).

      • The levels of baseline eIF2 phosphorylation are indeed the same in WT and both H160D clones, both when assessed using a phospho-specific antibody (for eIF2alpha Ser51-P) or through band shift using phospho-retention gels (Phos-tag). We now include a new supplementary figure with this data (Figure 6 – figure supplement 3A-B).

      • It is well-established in the field that ATF4 is regulated at the translational level during acute ISR activation, and indeed, reporters with the ATF4 5’ UTR have been instrumental in studying and quantifying this, allowing scientists to forego time-intensive western blots and perform high throughput analyses. Stable integration, however, can notoriously affect genomic integrity and otherwise introduce clonal variation, even when the construct is targeted to a specific locus (for example when using the FlpIn system). We have observed heterogeneity in baseline ATF4 reporter signal even when comparing polyclonal cell lines generated by lentiviral integration. As it is best practice to avoid comparing between reporter cell lines generated in different backgrounds (WT vs H160D), particularly when investigating basal conditions, we consider it more appropriate to directly measure the levels of proteins of interest by western blot, as is also commonly done in the field. By showing that ATF4 protein levels increase (Figure 6A) but its transcript levels do not (Figure 6B), while those of its target genes do (Figure 6B), we equally confirm that ATF4 is translationally upregulated in the eIF2B H160D mutant. Moreover, our Western blot conditions provide enough sensitivity to differentiate no stress (lane 1) from mild stress (lanes 5 and 9) and high stress (lanes 7 and 11). We have added notation of these specific relevant lanes to the text to make the point more accessible to the reader. We therefore consider the generation of reporter cell lines in different genetic backgrounds to be a redundant abstraction of a phenotype that we already directly show.

      • Indeed, as predicted from both our in vitro and cellular work, ISRIB did not alter growth half-life of H160D cells. We included these new data in Figure 6 – supplementary figure 3C.

    1. SciScore for 10.1101/2022.04.07.22273565: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: Ethics: This study was approved (EK Nr: 1064/2021) by the Institutional Review Board (IRB) of the Office of Research Oversight/Regulatory Affairs, Medical University of Innsbruck, Austria, which is responsible for all human research studies conducted in the State of Tyrol (Austria).<br>IRB: Ethics: This study was approved (EK Nr: 1064/2021) by the Institutional Review Board (IRB) of the Office of Research Oversight/Regulatory Affairs, Medical University of Innsbruck, Austria, which is responsible for all human research studies conducted in the State of Tyrol (Austria).<br>Consent: Study population, study design and recruitment: A total of 74 patients infected with Omicron were recruited for the study under informed consent.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody assay: End-point binding IgG antibody titers to various SARS-CoV-2–derived antigens were measured using the Meso Scale Discovery (MSD) platform.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>End-point binding IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plates were coated with the specific antigen on spots in the 96 well plate and the bound antibodies in the samples (1:50000 dilution) were then detected by anti-human IgG antibodies conjugated with the MSD SULPHO-TAG which is then read on the MSD instrument which measures the light emitted from the tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">ACE2 binding inhibition (Neutralization) ELISA: The V-PLEX COVID-19 ACE2 Neutralization kit (Meso Scale Discovery, Panel 23 (ACE2) Kit, K15570U) was used to quantitatively measure antibodies that block the binding of ACE2 to its cognate ligands (SARS-CoV-2 and variant spike subdomains).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analysis: For comparison of samples, data were presented as standard deviation in each group and were evaluated with 2-way ANOVA followed by Tukey’s multiple comparisons test on GraphPad Prism software (version 9.0.0).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.04.08.487674: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: The protocol and consent document were reviewed and approved by ethical review boards for all sites, and all subjects provided written informed consent.<br>Consent: The protocol and consent document were reviewed and approved by ethical review boards for all sites, and all subjects provided written informed consent.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Human Subjects: Peripheral blood mononuclear cells (PBMC) were obtained from subjects in study 2019nCoV-101, a phase I/II clinical trial of NVX-CoV2373 carried out in male and female adult subjects in Australia and the United States.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">Donors of peripheral blood mononuclear cell fractions for the studies reported here were selected randomly from among subjects who had adequate specimens at all three specified dates (baseline, 7 days after dose 1 and 7 days after dose 2) and were treated twice with 5µg SARS-CoV-2 rS antigen plus 50µg Matrix-M™ adjuvant at a 21-day interval, as this was the dose and regimen selected to go forward for further clinical development.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">PBMC from 5 recipients of placebo were included among the study samples in a blinded fashion.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-S IgG ELISAs: Recombinant SARS-CoV-2 S protein was immobilised onto the surface of the 96-well microtiter plates by direct adsorption at 2°C to 8°C, followed by washing and blocking, Diluted reference standard (2-fold dilution series of 12 dilutions starting 1:1000) and human serum samples (3-fold dilution series of 12 dilutions) in assay buffer were then added in duplicate (100 µL per well) to the S protein-coated wells and specific antibodies are allowed to complex with the coated antigen for 2 hours ± 10 minutes at 24°C ± 2°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-S IgG</div><div>suggested: (LSBio (LifeSpan Cat# LS-C132241-1000, RRID:AB_10835882)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washing, IgG bound to the rSARS-CoV-2 S protein was detected using a horseradish peroxidase (HRP)-conjugated goat anti-human IgG antibody (Southern Biotech) incubated for 1 hour ± 10 minutes at 24°C ± 2°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Anti-rSARS-CoV-2 S protein IgG antibody level in clinical serum samples was quantitated in ELISA unit, EU/mL, by comparison to a reference standard curve.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-rSARS-CoV-2 S protein IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">hACE2 Binding Inhibition Assay: SARS-CoV-2 (rSARS-CoV-2) S protein was immobilised onto the surface of the 96-well microtiter plates by direct adsorption at 2°C to 8°C, followed by washing and blocking, Serial dilutions of human serum samples, including assay quality controls (QCs), were then added to the spike-coated wells and any molecules that could bind to the S protein, presumptively primarily spike-specific antibodies, were allowed to complex with the immobilized S protein (for 1 hour at 24±2°C) After a plate wash step, a fixed concentration of human ACE2 receptor (hACE2) with a polyhistidine-Tag (His-Tag) (SinoBiological) was added to the plate for incubation (1 hour at 24±2°C) during which the hACE2 bound to the S protein residues with binding sites not obstructed by bound antibody.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>His-Tag</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After incubation of the mixtures at 37°C and 5% CO2 for 1 hour, the mixtures were transferred to 96-well plates with confluent VeroE6 cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VeroE6</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Samples were diluted inn duplicate to a base dilution of 1:5 or 1:10, followed by 11 × 1:2 serial dilutions in Dulbecco’s minimal essential medium (DMEM, Quality Biologicals) supplemented with 10% fetal bovine serum (heat inactivated, Sigma), 1% penicillin/streptomycin)(Gemini Bio-products) and 2mM L-glutamine (Gibco) resulting in 100µL per well.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Quality Biologicals</div><div>suggested: (Aldevron, RRID:SCR_011017)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. 3. Who are you annotating with? Learning usually needs a certain degree of protection, a safe space. Groups can provide that, but public space often less so. In Hypothes.is who are you annotating with? Everybody? Specific groups of learners? Just yourself and one or two others? All of that, depending on the text you’re annotating? How granular is your control over the sharing with groups, so that you can choose your level of learning safety?

      This is a great question and I ask it frequently with many different answers.

      I've not seen specific numbers, but I suspect that the majority of Hypothes.is users are annotating in small private groups/classes using their learning management system (LMS) integrations through their university. As a result, using it and hoping for a big social experience is going to be discouraging for most.

      Of course this doesn't mean that no one is out there. After all, here you are following my RSS feed of annotations and asking these questions!

      I'd say that 95+% or more of my annotations are ultimately for my own learning and ends. If others stumble upon them and find them interesting, then great! But I'm not really here for them.

      As more people have begun using Hypothes.is over the past few years I have slowly but surely run into people hiding in the margins of texts and quietly interacted with them and begun to know some of them. Often they're also on Twitter or have their own websites too which only adds to the social glue. It has been one of the slowest social media experiences I've ever had (even in comparison to old school blogging where discovery is much higher in general use). There has been a small uptick (anecdotally) in Hypothes.is use by some in the note taking application space (Obsidian, Roam Research, Logseq, etc.), so I've seen some of them from time to time.

      I can only think of one time in the last five or so years in which I happened to be "in a text" and a total stranger was coincidentally reading and annotating at the same time. There have been a few times I've specifically been in a shared text with a small group annotating simultaneously. Other than this it's all been asynchronous experiences.

      There are a few people working at some of the social side of Hypothes.is if you're searching for it, though even their Hypothes.is presences may seem as sparse as your own at present @tonz.

      Some examples:

      @peterhagen Has built an alternate interface for the main Hypothes.is feed that adds some additional discovery dimensions you might find interesting. It highlights some frequent annotators and provide a more visual feed of what's happening on the public Hypothes.is timeline as well as data from HackerNews.

      @flancian maintains anagora.org, which is like a planet of wikis and related applications, where he keeps a list of annotations on Hypothes.is by members of the collective at https://anagora.org/latest

      @tomcritchlow has experimented with using Hypothes.is as a "traditional" comments section on his personal website.

      @remikalir has a nice little tool https://crowdlaaers.org/ for looking at documents with lots of annotations.

      Right now, I'm also in an Obsidian-based book club run by Dan Allosso in which some of us are actively annotating the two books using Hypothes.is and dovetailing some of this with activity in a shared Obsidian vault. see: https://boffosocko.com/2022/03/24/55803196/. While there is a small private group for our annotations a few of us are still annotating the books in public. Perhaps if I had a group of people who were heavily interested in keeping a group going on a regular basis, I might find the value in it, but until then public is better and I'm more likely to come across and see more of what's happening out there.

      I've got a collection of odd Hypothes.is related quirks, off label use cases, and experiments: https://boffosocko.com/tag/hypothes.is/ including a list of those I frequently follow: https://boffosocko.com/about/following/#Hypothesis%20Feeds

      Like good annotations and notes, you've got to put some work into finding the social portion what's happening in this fun little space. My best recommendation to find your "tribe" is to do some targeted tag searches in their search box to see who's annotating things in which you're interested.

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    1. SciScore for 10.1101/2022.04.06.487306: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After binding, samples were washed twice in sort buffer and incubated with a 1:100 dilution of α-Myc-FITC (Abcam, #Ab1263) and α-His-PE (Abcam, #Ab72467) antibody at room temperature for 10 minutes.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>α-His-PE ( Abcam , #Ab72467 )</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After 1 hour at 4 °C, cells were washed twice in sort buffer and stained with α-His-PE antibody (1:100).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>α-His-PE</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 293T cells expressing scFv on the cell surface were detached with trypsin-EDTA (Thermo Fisher Scientific) and washed twice in prechilled sort buffer (1% FCS, 25 mM HEPES-KOH pH 7.9, 1 mM EDTA in PBS).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293T</div><div>suggested: KCB Cat# KCB 200744YJ, RRID:CVCL_0063)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">An expression vector for the secretion and purification of His-tagged proteins from mammalian cells was generated by insertion of DNA encoding an IGK leader and 8xHis tag into pCS2-MT+.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCS2-MT+</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A DNA fragment encoding the SARS-CoV-2 RBD (aa 319-591) was amplified from pCAGGS-SARS-CoV-2-Spike vector (a kind gift from Keith Grehan) and cloned in frame with the N-terminal IGK leader sequence and C-terminal 8xHis tag using NheI and XhoI sites.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAGGS-SARS-CoV-2-Spike</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The round 3 enriched ultralong scFv library was transferred from pBovShow into this lentiviral vector and lentiviruses were generated by transient transfection of 293T cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pBovShow</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The next day, 4 μg Lenti-BovShow-IRES-PuroR, 4 μg of pCMVR8.74 packaging vector (Addgene plasmid #22036) and 2 μg of pMD2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMVR8.74</div><div>suggested: RRID:Addgene_22036)</div></div><div style="margin-bottom:8px"><div>pMD2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">G coat protein vector (Addgene plasmid #12259; both gifts from Didier Trono) were mixed with PEI at a 1:3 molar ratio and added to the 10 cm2 dish.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>#12259</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudotype Neutralisation assays: Pseudotyped lentiviral particles were generated by transfecting 3 × 106 293T cells in a 10 cm2 dish with a lentivirus backbone plasmid encoding a luciferase reporter gene (BEI: NR-52516 pHAGE-CMV-Luc2-IRES-ZsGreen-W), a plasmid encoding either the SARS-CoV Spike (pCAGGS-SARS-CoV-Spike_Urbani), SARS-CoV-2 Spike (BEI: NR-52514) or VSV glycoprotein (VSV-G; pMD2.G) and the packaging vectors HDM-Hgpm2 (BEI: NR-52517), HDM-tat1b (BEI: NR-52518) and pRC-CMV-Rev1b (BEI: NR-52519).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pHAGE-CMV-Luc2-IRES-ZsGreen-W</div><div>suggested: RRID:Addgene_164432)</div></div><div style="margin-bottom:8px"><div>pCAGGS-SARS-CoV-Spike_Urbani</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pMD2 . G</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pRC-CMV-Rev1b</div><div>suggested: RRID:Addgene_164443)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">293T cells were transfected with either B9-WT or B9-Mut plasmid DNA and cell-surface expressed scFvs were tested for binding to purified SARS-CoV RBD (200 nM) using the standard staining protocol.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>B9-Mut</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The raw HDX-MS data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset: PXD032965.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>PRIDE</div><div>suggested: (Pride-asap, RRID:SCR_012052)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Disruption of the B9-scFv knob domain: The sequence encoding B9-scFv was mutated in the BovShow cell surface expression vector; residues 123YNCRPAVWY131 of the B9-scFv knob domain (B9-WT) were replaced with the irrelevant amino acid sequence 123ETCYYGSGL131 by site-directed mutagenesis (B9-Mut) with Q5 polymerase (New England Bioloabs)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>New England Bioloabs</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The KD for interactions between cell surface scFvs and recombinant RBD proteins was estimated by non-linear analyses of the log(molarity)-response plots on GraphPad.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. This work has been peer reviewed in GigaScience (https://doi.org/10.1093/gigascience/giac007), which carries out open, named peer-review.

      These reviews are published under a CC-BY 4.0 license and were as follows:

      Reviewer 3: Mudra Hegde

      Summary:

      In this manuscript, Poudel et al. present a software, GuideMaker, to rapidly design sgRNAs targeting non-model genomes. Various input parameters such as PAM motif, guide length, length of seed region for off-target searching and so on can be toggled to design a panel of sgRNAs for pooled screening projects. The tool also helps pick control sgRNAs to include in the sgRNA pool. To benchmark the computational performance of their tool, the authors used GuideMaker to design sgRNAs targeting E.coli, P.aeruginosa, Aspergillus fumigatus and Arabidopdis thaliana. They also compared GuideMaker to the existing design tool, CHOPCHOP and reported that the targets identified by GuideMaker were mostly similar to those identified by CHOPCHOP. This tool can be used as a stand-alone web application, command-line software or in the CyVerse Discovery Environment.

      Overall, the tool is very well documented and easy to use. In the current version of the manuscript, GuideMaker does not show a clear improvement over the state-of-the-art design tool, CHOPCHOP. The authors do not implement any existing on-target scoring methods to determine the targeting efficacy of the picked sgRNAs. This can lead to picking guides that are highly specific but not effective enough.

      Major points:

      1. Implementing on-target scoring methods, at least for the Cas enzymes that have on-target efficacy information, can help improve the process of picking sgRNAs. This tool will probably be used more often with standard Cas enzymes and it will be useful to have on-target efficacy scores attached to the guide RNAs.

      2. The authors do a thorough analysis of the computational performance of GuideMaker with various genomes and Cas enzymes but including a comparison of the computational performance of GuideMaker vs. CHOPCHOP will strengthen the manuscript.

      3. The authors define the PAM sequence of SaCas9 to be NGRRT whereas the canonical PAM sequence of SaCas9 is NNGRRT. This should be modified throughout the manuscript and analyses involving SaCas9 should be redone.

      4. A good addition to the tool would be to output a file with all the sequences that were designed targeting the region of interest with the specific PAM sequence. This gives the user a sense of the universe from which the final guides were picked.

      5. Another useful input parameter would be to specify a target region that the user wants to focus on such as letting the user input genomic coordinates or a gene name or locus tag. For example, CRISPy by Blin et al., 2016 takes a GenBank file as input and allows the user to input features specific to the uploaded genome.

      Minor points:

      1. "CyVerse" is misspelled as "CyCVerse" in multiple places in the manuscript.

      2. Reference Figure 2 in Line 92.

      3. Line 154: "Ratios between tools were calculated by dividing the number of gRNA identified.."

      4. In Supplementary Figure 3 "wit haVX2" should be "with aVX2".

      5. GitHub link in Line 336 does not work.

      6. Line 225-226: "GuideMaker also creates off-target gRNAs for use as negative controls in highthroughput experiments." "Off-target gRNAs" is misleading in this context.

    1. SciScore for 10.1101/2022.04.05.487060: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">Aminoadamantane and aminoadamantane nitrate drugs: Aminoadamantane nitrate compounds (blindly coded NMT2, NMT3, NMT5-NMT9, and NMT5-Met (metabolite, sans nitro group) were synthesized by and obtained from EuMentis Therapeutics, Inc. (Newton, MA), and have been described previously6–9, 33.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After incubation with secondary antibodies (IR-dye 680LT-conjugated goat anti-mouse [1:20,000; Li-Cor, 926-68020] or IR-dye 800CW-conjugated goat anti-rabbit [1:15,000; Li-Cor, 926-32211]), membranes were scanned with an Odyssey infrared imaging system (Li-Cor)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: (LI-COR Biosciences Cat# 926-68020, RRID:AB_10706161)</div></div><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: (Santa Cruz Biotechnology Cat# sc-53804, RRID:AB_783976)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Immunoprecipitants were eluted and subjected to immunoblotting with anti-ACE2 antibody (1:1000, Cell Signaling, #15983) and anti-SARS-CoV-2 Spike protein antibody (1:2000, Abcam, ab275759)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 Spike protein</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Primary antibodies and dilutions were as follows: Mouse anti-TNFα (5 µg/ml, Abcam, #ab1793) and rabbit anti-macrophage inflammatory protein 1α (MIP-1α)/CCL3+CCL3L1 (1:250</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-TNFα</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-macrophage inflammatory protein 1α ( MIP-1α)/CCL3+CCL3L1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After 30 min, all cells were collected and subjected to biotin switch-assay and immunoblotting with anti-ACE2 antibody to assess the levels of SNO-ACE2 and total input ACE2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-ACE2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>total input ACE2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cell lines: HEK293T (System Biosciences, LV900A-1) and HEK293-Spike cells (SARS-CoV-2 Spike (D614)-expressing 293 cells [293-SARS2-S cells, InvivoGen]) were maintained in Dulbecco’s modified Eagle’s medium (DMEM) with GlutaMAX™ (DMEM, high glucose, GlutaMAX™ Supplement, Life Technologies, 10566016) supplemented with 10% fetal bovine serum (FBS; Sigma, F7524), 100 IU/ml, and 100 µg/ml penicillin-streptomycin (Thermo Fisher Scientific, 10378016) at 37 °C in a 5% CO2 incubator.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>HEK293-Spike</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>293</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 virus generation: Monkey Vero E6 cells were plated in a T225 flask with complete DMEM containing 10% FBS, 1×PenStrep, 2 mM L-glutamine and incubated for overnight at 37 °C in a humified atmosphere of 5% CO2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HeLa-ACE2 cells were seeded in the assay-ready plates at 1.6×103 cells/well in assay medium, and plates were incubated for 24 h at 37 ℃ with 5% CO2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HeLa-ACE2</div><div>suggested: JCRB Cat# JCRB1845, RRID:CVCL_B3LW)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Homogenized lungs were titrated 1:10 over 6 steps and layered over Vero cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">. Monkey Vero E6 cells (ATCC CRL-1586) were maintained in complete DMEM (Corning, 15-013-CV) containing 10% FBS, 1×PenStrep (Corning 20-002-CL), 2 mM L-glutamine (Corning, 25-005-CL) at 37 °C in a 5% CO2 incubator. Plasmids: hACE2 was a gift from Hyeryun Choe (Addgene plasmid #1786; http://n2t.net/addgene:1786 ; RRID:Addgene_1786)46.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_1786)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The C262A, C498A, C261/498A mutant ACE2 constructs were generated using the QuikChange Lightning Multi Site-Directed Mutagenesis Kit (Agilent Technologies, 210514) according to the manufacturer’s protocol. pGBW-m4252984 (SARS-CoV-2 E [envelope]) was a gift from Ginkgo Bioworks (Addgene plasmid #153898; http://n2t.net/addgene:153898; RRID:Addgene_153898).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div></div><div>detected: RRID:Addgene_153898)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">MLV-gag/pol, MLV-CMV-Luciferase, SARS-CoV-2, and VSV-G plasmids were a gift from David Nemazee</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VSV-G</div><div>suggested: RRID:Addgene_138479)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression and purification of human ACE2 protein: The N-terminal peptidase domain of human ACE2 (residues 19 to 615, GenBank: BAB40370.1) was cloned into phCMV3 vector and fused with C-terminal His-tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>phCMV3</div><div>suggested: RRID:Addgene_173431)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In brief, HEK293T cells were transiently co-transfected with MLV-gag/pol, MLV-CMV-Luciferase plasmid, and SARS- CoV-2 Spike (D614) or VSV-G plasmid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MLV-CMV-Luciferase</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For transient expression in HEK293T cells, we used a transfection reagent (Fugene® HD, Promega) to co-transfect plasmids containing cDNAs for SARS-CoV-2 E protein (pGBW-m4133502, Addgene) and green fluorescent protein (GFP) at a ratio of 1:0.1 (0.5:0.05 µg/well, respectively).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pGBW-m4133502</div><div>suggested: RRID:Addgene_153565)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Maximum intensity projection of images was generated, and fluorescence intensity was analyzed with ImageJ software (https://imagej.nih.gov/ij/download.html) as previously described50.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Molecular dynamics (MD) simulations were performed on the Frontera supercomputer at the Texas Advanced Supercomputing Center (TACC) using NAMD 2.1461 and CHARMM36m all-atom additive force fields62–64.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>NAMD</div><div>suggested: (NAMD, RRID:SCR_014894)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Molecular Devices) with a 10× objective, and total live cells per well quantified in the acquired images using the Live Dead Application Module (MetaXpress).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MetaXpress</div><div>suggested: (MetaXpress, RRID:SCR_016654)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analyses were performed using GraphPad Prism software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.04.03.486854: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: Data collection, structure determination, and refinement: The X-ray diffraction data were collected at the beamlines BL18U (RBD-Fab2303) and BL02U (Fab2212) of the Shanghai Synchrotron Research Facility.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">Authentication: Immunofluorescence imaging and analysis: For viral nucleocapsid detection in Vero-TMPRSS2 cells by immunofluorescence, cells were washed twice with PBS x1 and fixed in 4% formaldehyde for 30 min at RT.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The plates were then washed 3 times with washing buffer before adding secondary anti-IgG (Jackson ImmmunoResearch) antibody conjugated to horseradish peroxidase (HRP) diluted 1:5000 in blocking buffer, and incubation for 1 h at RT.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-IgG</div><div>suggested: (Vector Laboratories Cat# FI-5000, RRID:AB_2336128)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Monolayers were observed for at least 4 days for appearance of CPE and then fixed as above and stained with antibody against SARS-CoV-2 Nucleocapsid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>antibody against SARS-CoV-2 Nucleocapsid.</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Fixed cells were washed with PBS x1 and permeabilized for immunofluorescence using BD Cytofix/Cytoperm according to the manufacturer’s protocol for fixed cells, and then stained for SARS-CoV-2 with a primary nucleocapsid antibody (GeneTex GTX135357) and a secondary anti-rabbit AF647 antibody (ThermoFisher A20185), The nuclei were counterstained with Sytox Green.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit AF647</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression and purification of soluble RBD, spike and antibodies for crystallization: SARS-CoV-2 RBD (residues Arg319 to Lys529) was expressed by using the Bac-to-Bac Baculovirus System (Invitrogen)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Lys529</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Supernatant containing S2P was collected four days after transfection, S2P was affinity purified by anti-Flag antibody beads and was eluted by 0.1 mg/mL 3×Flag peptide in 20 mM HEPES at pH 7.6 and 150 mM NaCl.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-Flag</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK-293 cells stably expressing hACE2 were seeded into 0.1% gelatin-coated 96-well plates (Greiner) at an initial density of 0.75 × 105 cells per well.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK-293</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Virus titers were validated using a combination of fluorescent focus assay and tissue culture infectious dose (TCID)50 assays on Vero-TMPRSS2 and Calu-3 (ATCC) monolayers.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu-3</div><div>suggested: KCLB Cat# 30055, RRID:CVCL_0609)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For TCID50 assays, Vero-TMPRSS2 or Calu3 cells were infected as above and 100µL DMEM or MEM with 2% FBS was subsequently added per well.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu3</div><div>suggested: RRID:CVCL_EQ19)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Immunofluorescence imaging and analysis: For viral nucleocapsid detection in Vero-TMPRSS2 cells by immunofluorescence, cells were washed twice with PBS x1 and fixed in 4% formaldehyde for 30 min at RT.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero-TMPRSS2</div><div>suggested: JCRB Cat# JCRB1818, RRID:CVCL_YQ48)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The S2P or S6P pCMV plasmids were used to transiently transfect HEK293F cells with polyethylenimine (PEI) (Polysciences, #24765).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293F</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression and purification of soluble RBD, spike and antibodies for crystallization: SARS-CoV-2 RBD (residues Arg319 to Lys529) was expressed by using the Bac-to-Bac Baculovirus System (Invitrogen)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2 RBD</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data collection, structure determination, and refinement: The X-ray diffraction data were collected at the beamlines BL18U (RBD-Fab2303) and BL02U (Fab2212) of the Shanghai Synchrotron Research Facility.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RBD-Fab2303</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody inhibition of hACE2 binding to cell-expressed spike: Expi293F cells were transfected with pcDNA 3.1 containing SΔC19 of wild type, Alpha, Beta, or Delta variants, using the ExpiFectamine 293 Transfection Kit (Thermo Fisher).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA 3.1</div><div>suggested: RRID:Addgene_20407)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Pseudo-particle preparation and neutralization assays: SARS-CoV-2-spike pseudo-particles were obtained by co-transfecting Expi293F cells with pCMV delta R8.2, pLenti-GFP (Genecopoeia), and pcDNA 3.1 SΔC19 (Thermo Fisher) at a ratio of 1:2:1, respectively, according to the manufacturer’s instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCMV</div><div>suggested: RRID:Addgene_16459)</div></div><div style="margin-bottom:8px"><div>pLenti-GFP</div><div>suggested: RRID:Addgene_172394)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">RBD containing the gp67 signal peptide and a C-terminal 6×His tag was inserted into pFastBac1 to form the plasmid pFastBac1-RBD.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pFastBac1</div><div>suggested: RRID:Addgene_1956)</div></div><div style="margin-bottom:8px"><div>pFastBac1-RBD</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Fixed cells were washed with PBS x1 and permeabilized for immunofluorescence using BD Cytofix/Cytoperm according to the manufacturer’s protocol for fixed cells, and then stained for SARS-CoV-2 with a primary nucleocapsid antibody (GeneTex GTX135357) and a secondary anti-rabbit AF647 antibody (ThermoFisher A20185), The nuclei were counterstained with Sytox Green.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BD Cytofix/Cytoperm</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data were logged from the Incucyte analysis modules and graphed with GraphPad Prism 8.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SerialEM was used for the data collection.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SerialEM</div><div>suggested: (SerialEM, RRID:SCR_017293)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The CTF parameters of the micrographs were determined by using the program Gctf with local defocus variations taken into consideration59.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Gctf</div><div>suggested: (GCTF, RRID:SCR_016500)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">90569 particles were picked by Gautomatch and then were subjected to 2D classifications with RELION 3.0.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RELION</div><div>suggested: (RELION, RRID:SCR_016274)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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    1. SciScore for 10.1101/2022.04.01.486719: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">B cells were incubated for 30 min at 4°C with biotinylated tri-S and DyLight 650-coupled RBD, washed once with 1% FBS-PBS (FACS buffer), and incubated for 30 min at 4°C with a cocktail of mouse anti-human antibodies: CD19 Alexa 700 (HIB19, BD Biosciences, San Jose,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human antibodies: CD19</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cTfh antibody panel included: CD3 BV605 (SK7), CD4 PE-CF594 (RPA-T4), CD185/CXCR5 AF-488 (RF8B2), CD183/CXCR3 PE-Cy™5 (1C6/CXCR3), CD196/CCR6 PE-Cy™7 (11A9), CD197/CCR7 AF647 (3D12) (BD Biosciences), CD279/PD1 BV421 (EH12.2H7, BioLegend), and CD278/ICOS PE (ISA-3, Thermo Fisher Scientific).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CD3</div><div>suggested: (SouthernBiotech Cat# 9515-31, RRID:AB_2796843)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The purified parental IgG1 antibody versions of benchmarked mAbs [REGN10933, REGN10987 (Hansen et al., 2020), CB6 (Shi et al., 2020), LY-CoV555 (Jones et al., 2021), CT-P59 (Kim et al., 2021), COV2-2196, COV2-2130 (Zost et al., 2020b), ADG-2 (Garrett Rappazzo et al., 2021) and S309 (Pinto et al., 2020)] were prepared as described above after cloning of synthetic DNA fragments (GeneArt, Thermo Fisher Scientific) coding for the immunoglobulin variable domains.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgG1</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>CB6</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>LY-CoV555</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>S309</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Comparative ELISA binding of Cv2.1169 IgG1 and IgA1 antibodies was performed at a concentration of 70 nM, and 7 consecutive dilutions in PBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgA1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To quantify blood-circulating human Cv2.1169 IgA1 and IgG1 in treated K18-hACE2 mice and golden hamsters, high-binding 96-well ELISA plates (Costar, Corning) were coated overnight with 250 ng/well of purified goat anti-human IgA or IgG antibody (Jackson ImmunoResearch, 0.8 µg/ml final).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>purified goat anti-human IgA</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>IgG antibody</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After washings, the plates were revealed by incubation for 1 h with goat HRP-conjugated anti-mice IgG, anti-golden hamster IgG, anti-human IgG or anti-human IgA antibodies (Jackson ImmunoReseach, 0.8 µg/ml final) and by adding 100 µl of HRP chromogenic substrate (ABTS solution, Euromedex) after washing steps.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mice IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-golden hamster IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-human IgA</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEp-2 IFA assay: Recombinant SARS-CoV-2 S-specific and control IgG antibodies (mGO53 and ED38) at 100 µg/ml were analyzed by indirect immuno-fluorescence assay (IFA) on HEp-2 cells sections (ANA HEp-2 AeskuSlides®, Aesku.Diagnostics, Wendelsheim, Germany) using the kit’s controls and FITC-conjugated anti-human IgG antibodies as the tracer according to the manufacturer’ instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>control IgG</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>ED38</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Membranes were inserted into a Miniblot apparatus (Immunetics) and then incubated with human mAbs (at a concentration of 1 µg/ml) and mouse anti-Hisx6 antibody (1 µg/ml, BD Biosciences) in PBS-T 5% dry milk in each channel for 2 h.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-Hisx6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Microarrays were blocked for 1 h in blocking solution (Thermo Fisher), washed and incubated for 1h30 with IgG antibodies at 2.5 µg/ml as previously described (Grzelak et al., 2020).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibodies (Cv2.1169, Cv2.1353, Cv2.3194, Cv2.3235 and Cv2.5213) and ACE2 ectodomain were covalently coupled to CM5 sensor chips (Biacore) using amino-coupling kit (Biacore) according to the manufacturer’s procedure.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody-dependent cellular phagocytosis (ADCP) assay: PBMC were isolated from healthy donors’ blood (Etablissement Français du Sang) using Ficoll Plaque Plus (GE Healthcare)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Antibody-dependent cellular phagocytosis ( ADCP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Phagocytic scores were calculated by dividing the fluorescence signals (% FITC-positive cells x geometric MFI FITC-positive cells) given by anti-SARS-CoV-2 spike antibodies by the one of the negative control antibody mGO53.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody-dependent cellular cytotoxicity (ADCC) assay: The ADCC activity of anti-SARS-CoV2 S IgG antibodies was determined using the ADCC Reporter Bioassay (Promega) as previously described (Dufloo et al., 2021).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV2 S IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 5×104 Raji-Spike cells were co-cultured with 5×104 Jurkat-CD16-NFAT-rLuc cells in presence or absence of SARS-CoV2 S-specific or control mGO53 IgG antibody at 10 µg/ml or 50 µg/ml and 10 consecutive 1:2 dilutions in PBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>control mGO53 IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Crystallization and structure determinations: The Fab of anti-SARS-CoV-2 S antibody CR3022 (Ter Meulen et al., 2006), served as a crystallization chaperone molecule, and was produced and purified as described above (section with heading Single B-cell FACS sorting and expression-cloning of antibodies) (Koide, 2009).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 S</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Six or 22 h post-inoculation, mice received an intraperitoneal (i.p.) injection of 5, 10, 20 or 40 mg/kg of Cv2.1169 IgG or IgA antibody, and of mGO53 control IgG or IgA antibody.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>IgA</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Four or 24 h post-intranasal inoculation, hamsters received an intraperitoneal (i.p.) injection of 10 or 5 mg/kg of Cv2.1169 IgG or IgA antibody, as well as the mGO53 control antibody or PBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>mGO53</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Viruses were amplified by one or two passages in Vero E6 cell cultures and titrated.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: RRID:CVCL_XD71)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Drosophila S2 cells were stably co-transfected with pT350 and pCoPuro (for puromycin selection) plasmids.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>S2</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEp-2 IFA assay: Recombinant SARS-CoV-2 S-specific and control IgG antibodies (mGO53 and ED38) at 100 µg/ml were analyzed by indirect immuno-fluorescence assay (IFA) on HEp-2 cells sections (ANA HEp-2 AeskuSlides®, Aesku.Diagnostics, Wendelsheim, Germany) using the kit’s controls and FITC-conjugated anti-human IgG antibodies as the tracer according to the manufacturer’ instructions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEp-2</div><div>suggested: CLS Cat# 300397/p694_Hep-2, RRID:CVCL_1906)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 5×104 Raji-Spike cells were co-cultured with 5×104 Jurkat-CD16-NFAT-rLuc cells in presence or absence of SARS-CoV2 S-specific or control mGO53 IgG antibody at 10 µg/ml or 50 µg/ml and 10 consecutive 1:2 dilutions in PBS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Jurkat-CD16-NFAT-rLuc</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, 5×104 Raji-Spike cells were cultivated in the presence of 50% normal or heat-inactivated human serum, and with or without IgG antibodies (at 10 µg/ml or 50 µg/ml and 10 consecutive 1:2 dilutions in PBS).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Raji-Spike</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The supernatants were titrated on Vero-E6 cells by classical plaque assays using semisolid overlays (Avicel, RC581-NFDR080I, DuPont) and expressed and PFU/100 mg of tissue (Baer and Kehn-Hall, 2014).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero-E6</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 infection and treatment in K18-hACE2 mice: B6.Cg-Tg(K18-ACE2)2Prlmn/J mice (stock #034860) were imported from The Jackson Laboratory (Bar Harbor, ME, USA) and bred at the Institut Pasteur under strict SPF conditions.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>B6.Cg-Tg(K18-ACE2)2Prlmn/J</div><div>suggested: RRID:IMSR_JAX:034860)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression and purification of viral proteins: Codon-optimized nucleotide fragments encoding stabilized versions of SARS-CoV-2, SARS-CoV-1, MERS-CoV, OC43-CoV, HKU1-CoV, 229E-CoV, NL63-CoV (2P) and BA.1 spike (HexaPro) (S) ectodomains, and SARS-CoV-2 S2 domain, followed by a foldon trimerization motif and C-terminal tags (Hisx8-tag, Strep-tag, and AviTag) were synthesized and cloned into pcDNA3.1/Zeo(+) expression vector (Thermo Fisher Scientific).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1/Zeo(+</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For crystallographic experiments, a codon-optimized nucleotide fragment encoding the SARS-CoV-2 RBD protein (residues 331-528), followed by an enterokinase cleavage site and a C-terminal double strep-tag was cloned into a modified pMT/BiP expression vector (pT350, Invitrogen)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pMT/BiP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Drosophila S2 cells were stably co-transfected with pT350 and pCoPuro (for puromycin selection) plasmids.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pT350</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pCoPuro</div><div>suggested: RRID:Addgene_17533)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For Cryo-EM experiments, a codon-optimized nucleotide fragment encoding the SARS-CoV-2 spike (S) protein (residues 1-1208) was cloned with its endogenous signal peptide in pcDNA3.1(+) vector, and expressed as a stabilized trimeric prefusion construct with six proline substitutions (F817P, A892P, A899P, A942P, K986P, V987P), along with a GSAS substitution at the furin cleavage site (residues 682–685), followed by a Foldon trimerization motif (Hsieh et al., 2020), and C-terminal tags (Hisx8-tag, Strep-tag and AviTag).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1 ( + )</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The dimeric form of Cv2.1169 IgA1 was produced by co-transfection of Freestyle™ 293-F cells with a human J chain pcDNA™3.1/Zeo(+) vector as previously described (Lorin and Mouquet, 2015)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA™3.1/Zeo(+</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To evaluate spike cross-reactivity, Freestyle™ 293-F were transfected with pUNO1-Spike-dfur expression vectors (Spike and SpikeV1 to V11 plasmids, Invivogen) (1.2 µg plasmid DNA per 106 cells) using PEI-precipitation method.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pUNO1-Spike-dfur</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 S-Fuse neutralization assay: S-Fuse cells (U2OS-ACE2 GFP1-10 or GFP 11 cells) were mixed (ratio 1:1) and plated at a density of 8 × 103 per well in a μClear 96-well plate (Greiner Bio-One) as previously described (Buchrieser et al., 2020).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GFP1-10</div><div>suggested: RRID:Addgene_68715)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cv2.1169 were also cloned into human Igγ1NA, Igγ1LALA [N297A and L234A/L235A mutations introduced by Site-Directed Mutagenesis (QuickChange, Agilent Technologies)], Igα1 and Fab-Igα1-expressing vectors (Lorin and Mouquet,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Agilent Technologies</div><div>suggested: (Agilent Technologies, RRID:SCR_013575)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Flow cytometry binding assays: SARS-CoV-2 specificity validation of cloned human IgG antibodies was performed using the S-Flow assay as previously described (Grzelak et al., 2020).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2</div><div>suggested: (Active Motif Cat# 91351, RRID:AB_2847848)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data were acquired using a CytoFLEX flow cytometer (Beckman Coulter), and analyzed using FlowJo software (v10.7.1; FlowJo LLC).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEp-2 sections were examined using the fluorescence microscope Axio Imager 2 (Zeiss, Jena, Germany), and pictures were taken at magnification x 40 with 5000 ms-acquisition using ZEN imaging software (Zen 2.0 blue version, Zeiss) at the Imagopole platform (Institut Pasteur)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Zen</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For each antibody, Z-scores were calculated using ProtoArray® Prospector software (v5.2.3, Thermo Fisher Scientific), and deviation (σ) to the diagonal, and polyreactivity index (PI) values were calculated as previously described (Planchais et al., 2019).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ProtoArray® Prospector</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The evaluation kinetic parameters of the studied interactions were performed by using BIAevaluation version 4.1.1 Software (Biacore).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BIAevaluation</div><div>suggested: (BIAevaluation Software, RRID:SCR_015936)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">IC50 values were calculated using Prism software (v.9.3.1,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The final models were built by combining real space model building in Coot (Emsley et al., 2010) with reciprocal space refinement with phenix.refine.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Coot</div><div>suggested: (Coot, RRID:SCR_014222)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The final models were validated with Molprobity (Williams et al., 2018).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Molprobity</div><div>suggested: (MolProbity, RRID:SCR_014226)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Superpositions and figures were rendered using Pymol and UCSF Chimera (Pettersen et al., 2004)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Pymol</div><div>suggested: (PyMOL, RRID:SCR_000305)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">CryoSPARC blob picker was used for automated particle picking and the resulting particles used to obtain initial 2D references, which were then used to auto-pick the micrographs.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CryoSPARC</div><div>suggested: (cryoSPARC, RRID:SCR_016501)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Volcano plot comparing gene features (n=206 parameters) of tri-S+ B cells and normal memory B-cells (mB) was also performed using GraphPad Prism software (v.8.4,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Circos plot linking antibody sequences with at least 75% identity within their CDRH3 was performed using online software at http://mkweb.bcgsc.ca/circos.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Circos</div><div>suggested: (Circos, RRID:SCR_011798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">GraphPad Prism Inc.)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Principal component analysis (PCA) was performed using the prcomp() function in R Studio Server (v1.4.1103)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>R Studio Server</div><div>suggested: None</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04325646</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sero-epidemiological Study of the SARS-CoV-2 Virus Responsib…</td></tr></table>


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.03.30.486313: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Membranes were first incubated with the primary antibody (Anti-Glutathione antibody [D8], ab19534,</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Anti-Glutathione</div><div>suggested: (Abcam Cat# ab19534, RRID:AB_880243)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">; Mouse anti DDDDK-Tag (FLAG-tag) mAb, AE005, ABclonal) in 5% BSA TBST for 16 h at 4 °C, washed with TBST three times, then incubated with the secondary antibody (HRP-labeled Goat Anti-Mouse IgG(H+L), A0216, Beyotime) in 5% BSA TBST (1 h, 25 °C), and washed with TBST three times.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti DDDDK-Tag (FLAG-tag</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Anti-Mouse IgG(H+L)</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">In the present study, HEK293T cells were seeded in 12-well plates overnight.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For bacterial expression, the cDNA encoded the SARS-CoV-2 PLpro with E. coli codon optimization was ordered from GenScript and cloned into the pET15b expression vector with an N-terminal 6 × His-SUMO2 fusion tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET15b</div><div>suggested: RRID:Addgene_129689)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For transfection of mammalian cell, the cDNA encoded the SARS-CoV-2 PLpro with mammalian codon optimization was also ordered from GenScript and cloned into the pcDNA 3.1 with an C-terminal FLAG tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA 3.1</div><div>suggested: RRID:Addgene_20407)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The sequence of pcDNA3-PL-flipGFP-T2A-mCherry was designed based on plasmid pcDNA3-TEV-flipGFP-T2A-mCherry (Addgene catalog NO.124429) where TEV cleave site was replaced by SARS-CoV-2 PLpro cleavage site (LRGGAPTK), and ordered from GenScript.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3-PL-flipGFP-T2A-mCherry</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pcDNA3-TEV-flipGFP-T2A-mCherry</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The resulting kobs values were then plotted versus compound concentrations ([C]), then kinact and Ki or Ka values were calculated according to the equation: kobs = kinact × ([C]/([C] + Ki or Ka)) using GraphPad Prism.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.03.24.22272837: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: Ethics: This study was approved (EK Nr: 1064/2021) by the Institutional Review Board (IRB) of the Office of Research Oversight/Regulatory Affairs, Medical University of Innsbruck, Austria, which is responsible for all human research studies conducted in the State of Tyrol (Austria).<br>IRB: Ethics: This study was approved (EK Nr: 1064/2021) by the Institutional Review Board (IRB) of the Office of Research Oversight/Regulatory Affairs, Medical University of Innsbruck, Austria, which is responsible for all human research studies conducted in the State of Tyrol (Austria).<br>Consent: Study population, study design and recruitment: A total of 57 patients infected with Omicron, 34 with no history of prior vaccination and 23 patients who had received 2-3 doses of the BNT162b2 vaccine (Table S1), were recruited for the study under informed consent.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Antibody assay: End-point binding IgG antibody titers to various SARS-CoV-2–derived antigens were measured using the Meso Scale Discovery (MSD) platform.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>End-point binding IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plates were coated with the specific antigen on spots in the 96 well plate and the bound antibodies in the samples (1:50000 dilution) were then detected by anti-human IgG antibodies conjugated with the MSD SULPHO-TAG which is then read on the MSD instrument which measures the light emitted from the tag.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-human IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">ACE2 binding inhibition (Neutralization) ELISA: The V-PLEX COVID-19 ACE2 Neutralization kit (Meso Scale Discovery, Panel 23 (ACE2) Kit, K15570U) was used to quantitatively measure antibodies that block the binding of ACE2 to its cognate ligands (SARS-CoV-2 and variant spike subdomains).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The raw data were subjected to QC analyses using the FastQC tool (version 0.11.9) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FastQC</div><div>suggested: (FastQC, RRID:SCR_014583)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">mRNA-seq read quality control was done using Trimmomatic11 (version 0.36) and STAR RNA-seq12 (version STAR 2.5.4a) using 150 bp paired-end mode was used to align the reads (hg19).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>STAR</div><div>suggested: (STAR, RRID:SCR_004463)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HTSeq13 (version 0.9.1) was to retrieve the raw counts and subsequently, Bioconductor package DESeq214 in R (https://www.R-project.org/) was used to normalize the counts across samples and perform differential expression gene analysis.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Bioconductor</div><div>suggested: (Bioconductor, RRID:SCR_006442)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Quantification and statistical analysis: Differential expression gene (DEG) identification used Bioconductor package DESeq2 in R.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>DESeq2</div><div>suggested: (DESeq, RRID:SCR_000154)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">P-values of antibody between two groups were calculated using one-tailed Wilcoxon rank t-test on GraphPad Prism software (version 9.0.0).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.03.29.486190: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: Ethics statement: This research has been determined to be exempt by the Institutional Review Board of the Boston University Medical Center since it does not meet the definition of human subjects research, since all human samples were collected in an anonymous fashion and no identifiable private information was collected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">Contamination: All cell lines are routinely tested for mycoplasma contamination and confirmed negative.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For CD169 blocking experiments, primary MDMs from 3 different donors were pre-incubated with 20 μg/ml anti-CD169 antibody (HSn 7D2, Novus Biologicals) or IgG1k (P3.6.2.8.1, eBioscience) for 30 min at 4°C prior to infection.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-CD169</div><div>suggested: (Thermo Fisher Scientific Cat# MA1-16891, RRID:AB_568734)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">This is followed by secondary staining for 30 min at 4°C with APC-conjugated mouse anti-His antibody (BioLegend, #362605, 1:50) or isotype control.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-His</div><div>suggested: (BioLegend Cat# 362605, RRID:AB_2715818)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cells were incubated overnight at 4°C with a rabbit antibody directed against the SARS-CoV nucleocapsid protein (Rockland; 1:1000 dilution in 5% goat serum), which cross-reacts with the SARS-CoV-2 nucleocapsid protein, as previously described (99).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV nucleocapsid protein</div><div>suggested: (Creative Diagnostics Cat# DMAB8869, RRID:AB_2392503)</div></div><div style="margin-bottom:8px"><div>SARS-CoV-2 nucleocapsid protein</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cells were washed four times in PBS and incubated with goat anti-rabbit antibody conjugated with AlexaFluor594 for 1 hour at room temperature (Invitrogen; 1:200 dilution in blocking reagent). 4’,6-diamidino-2-phenylindole (DAPI; Sigma-Aldrich) was used at 200 ng/ml for nuclei staining.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For dsRNA staining (61), anti-dsRNA (Pan-Enterovirus Reagent, clone 9D5, Light Diagnostics, Millipore) antibody was used 1:2 overnight and anti-mouse-AF488 (Invitrogen) 1:200 dilution as secondary antibody with DAPI.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-dsRNA ( Pan-Enterovirus Reagent , clone 9D5 , Light Diagnostics , Millipore )</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-dsRNA ( Pan-Enterovirus Reagent ,</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-mouse-AF488</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Flow cytometry: To examine cell surface expression of CD169 or ACE2 in transduced THP1 or primary MDMs, approximately 0.5x106 cells were harvested with CellStripper (Corning), stained with Zombie-NIR (BioLegend, #423105, 1:250) followed by staining for 30 min at 4°C with the following antibodies; Alexa647-conjugated mouse anti-CD169 antibody (BioLegend, #346006, 1:50), Alexa647-conjugated</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: (Enzo Life Sciences Cat# BML-SA445, RRID:AB_2273641)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">mouse anti-ACE2 antibody (R&D systems, 1:200), or unconjugated goat anti-ACE2 polyclonal antibody (R&D systems, #AF933, 1:200) followed by Alexa488-conjugated chicken anti-goat antibody (Invitrogen, #A-21467, 1:100).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-goat</div><div>suggested: (Molecular Probes Cat# A-21467, RRID:AB_141893)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Immunoblot Analysis: To assess expression of endogenous or transduced proteins, cell lysates containing 30- 40 µg total protein were separated by SDS-PAGE, transferred to nitrocellulose membranes and the membranes were probed with the following antibodies: mouse anti- TMPRSS2 (Santa Cruz, #515727, 1:1000), mouse anti-Cathepsin-L (Santa Cruz, #32320, 1:1000), goat anti-ACE-2 (R&D systems, #AF933, 1;1000), rabbit anti-STING (Cell Signaling, #13647, 1:1000), rabbit anti-MAVS (Thermo Fisher, #PA5-17256, 1:1000), mouse anti-RIG-I (AdipoGen, #20B-0009, 1:1000)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti- TMPRSS2 ( Santa Cruz , #515727</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-Cathepsin-L ( Santa Cruz , #32320</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-ACE-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-STING ( Cell Signaling , #13647</div><div>suggested: (Cell Signaling Technology Cat# 13647, RRID:AB_2732796)</div></div><div style="margin-bottom:8px"><div>anti-MAVS</div><div>suggested: (Thermo Fisher Scientific Cat# PA5-17256, RRID:AB_10979584)</div></div><div style="margin-bottom:8px"><div>anti-RIG-I ( AdipoGen , #20B-0009</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Specific staining was visualized with secondary antibodies, goat anti-mouse-IgG-DyLight 680 (Thermo Scientific, #35518, 1:20000), goat anti-rabbit-IgG-DyLight 800 (Thermo Scientific, #SA5-35571, 1:20000), or a donkey anti-goat-IgG-IR-Dye 800 (Licor, #926-32214, 1:20000).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse-IgG-DyLight 680</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-rabbit-IgG-DyLight</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>#SA5-35571</div><div>suggested: (Thermo Fisher Scientific Cat# SA5-35571, RRID:AB_2556775)</div></div><div style="margin-bottom:8px"><div>anti-goat-IgG-IR-Dye</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">THP1 cells (ATCC) were maintained in RPMI/1640 (Gibco) containing 10% FBS and 1% pen/strep (50)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">To generate HEK293T/ACE2+, THP1/ACE2+ and THP1/CD169+/ACE2+ cells, HEK293T, THP1 or THP1/CD169 cells were transduced with pLenti-ACE2-IRES-puro lentivector and cultured in puromycin-containing media (2 μg/ml).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP1/CD169</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 titer was determined in Vero E6 cells by tissue culture infectious dose 50 (TCID50) assay using the Spearman Kärber algorithm.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Infection: For RNA analysis, 1x106 cells (THPI/PMA, MDMs, HEK293T) were seeded in 12-well plates.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">S binding: To evaluate SARS-CoV-2 S binding to various THP1 monocytes expressing different surface receptors, approximately 0.25x106 cells from parental THP1 or those expressing wt CD169, mutant CD169 (R116A), ACE2, or both wt CD169 and ACE2 were incubated for 30 min at 4 °C with 2 μg of spike glycoprotein (stabilized) from Wuhan-Hu-1 SARS- CoV-2 containing a C-terminal Histidine Tag, recombinant from HEK293F cells (BEI resources, #NR-52397).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293F</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For ACE2 cloning, the NotI-XhoI fragment from pLenti-ACE2- IRES-puro was inserted into the LV-3’LTR backbone.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLenti-ACE2- IRES-puro</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For cloning CD169 into LV-3’LTR vector, a BglII-AgeI fragment from LNC-CD169 was inserted into LV-3’LTR vector.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>LV-3’LTR</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HIV-1 packaging plasmid psPAX2 and VSV-G expression constructs have been previously described (39).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>psPAX2</div><div>suggested: RRID:Addgene_12260)</div></div><div style="margin-bottom:8px"><div>VSV-G</div><div>suggested: RRID:Addgene_138479)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">All lentiviral vectors (pLKO.1) expressing shRNAs used for knockdown of host proteins were purchased from Sigma</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLKO.1</div><div>suggested: RRID:Addgene_13425)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data analysis was performed using FlowJo software (FlowJo).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">63x oil immersion objective; numerical aperture 1.4) controlled by Metamorph image acquisition software (Molecular Devices, San Jose, CA)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Metamorph</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistics: All the statistical analysis was performed using GraphPad Prism 9.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. This tool watches Hypothesis URLs, groups, tags, or users, and alerts on new annotation activity to Slack, email, or RSS. It runs as a standalone Python program, ideally on a server, but alternatively on an always-connected desktop computer. It periodically queries the Hypothesis API along one or more axes -- url (or wildcard_uri), user, group, tag -- and sends notifications by way of Slack, email, or RSS.

  6. Mar 2022
    1. If I use tags for topics I would tag everything that is relevant for the topic of diet with #diet. A note about carbohydrate intake and insulin sensitivity would definitely fulfill this criterion. If I use tags for objects, I would only tag notes with #diet when these notes are specifically on the concept of dieting. I would not tag the note on insulin sensitivity with #diet.

      Tags linked in the body of my notes are for topics, this note is somehow related to that. Tags linked in the "Topics:": field are for objects, this note is primarily about this topic.

    1. SciScore for 10.1101/2022.03.27.485958: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IACUC: All animal studies were approved in accordance with the Weizmann Institute’s Animal Care and Use Committee (IACUC) guidelines and regulations (approval number 00580120-3).<br>Euthanasia Agents: The mice were measured under general isoflurane inhalation anesthesia (5% induction, 1% maintenance) up to four hours after EVs injection using a gradient echo Fast Low Angle Shot (FLASH) with the following parameters: TR = 300 ms; TE = 2 ms; resolution of 0.23×0.23×0.7 mm3.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After overnight blocking in 5% milk in TBST, specific antibodies were applied to the membranes for 1 h to detect markers: CD81 (B-II, Santa Cruz, USA); c-myc (9E10, Santa Cruz, USA) (all 1:500); and beta-actin (C4, Santa Cruz, USA) (1:1000).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CD81 (B-II, Santa Cruz, USA)</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>c-myc</div><div>suggested: (Covance Cat# MMS-150P-1000, RRID:AB_291322)</div></div><div style="margin-bottom:8px"><div>9E10</div><div>suggested: (Covance Cat# MMS-150R-500, RRID:AB_291327)</div></div><div style="margin-bottom:8px"><div>beta-actin</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>C4</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HRP-conjugated anti-mouse secondary HRP goat anti-mouse IgG antibody (#4053, Biolegend, USA) (1:5000 in TBST) was applied for 1 h before imaging using enhanced chemiluminescence substrate EZ-ECL Kit (Biological industries, catalog no. 20-500-120).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>anti-mouse IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The expression of ACE2 protein in cells was also confirmed by Western blot analysis, as described above, using a rabbit monoclonal ACE2 antibody (ab239924; 1:1000; Abcam, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ACE2</div><div>suggested: (Abcam Cat# ab239924, RRID:AB_2861381)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Then the cells were detached from wells by PBS and incubated with ACE2 primary antibody (ab239924; 1:1000; Abcam, USA) for 1 hour on ice, washed with PBS and then incubated with anti-rabbit fluorescently-conjugated secondary antibody (Alexa Fluor 647 nm) for 1 hour on ice.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit fluorescently-conjugated secondary</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The stably expressing ACE2 HEK293T cell line was kindly obtained from the lab of Dr. Ron Diskin (Weizmann Institute of Science) and kept under puromycin antibiotics (0.5 μg/ml, Invitrogen, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293T</div><div>suggested: RRID:CVCL_HA71)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK-pAGDisplay-RBD stable cell line generation: The pAGDisplay-based plasmids expressing RBD (1 ug of DNA) were transfected in a 60 mm culture dish with 80% confluent HEK293 cells by a JetPrime transfection reagent (Polyplus, France) according to the manufacturer’s protocol.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293</div><div>suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Binding assays and affinity curve determination using cell-display: The HEK-pAGDisplay-RBD stable cells grown to 80% confluency were gently detached by Accutase (1/2 solution in PBS, 3 min, Sigma Aldrich cat.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK-pAGDisplay-RBD</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Colony PCR and sequencing were used for analysis and verification. pAGDisplay vector construction: pDisplay Mammalian Expression vector was purchased from Invitrogen (V66020).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pAGDisplay</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The pAGDisplay vector backbone was assembled by combining a pET28b fragment bearing KanR and origin of replication, a pLVX vector fragment bearing WPRE, PuroR, and IRES sequences, and a pDisplay CMV promoter with a PDGFRβ expression cassette by a restriction-free three-component assembly 58.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLVX</div><div>suggested: RRID:Addgene_174088)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Protein production, purifications, and labeling procedures: The designed ALFA-tag binding nanobody (DnbALFA) and its mNeonGreen fusion were expressed by using expression plasmid pET28bdSUMO 62 and E.coli BL21(DE3) cells as described previously 60.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pET28bdSUMO</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Soluble his-tagged peptidase domain of ACE2 protein (Q18 – S740), inserted in pHLsec plasmid, was expressed in an Expi293F cell system with an ExpiFectamine 293 Transfection Kit (ThermoFisher, USA) according to the manufacturer’s protocol and purified as described previously 45.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pHLsec</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK-pAGDisplay-RBD stable cell line generation: The pAGDisplay-based plasmids expressing RBD (1 ug of DNA) were transfected in a 60 mm culture dish with 80% confluent HEK293 cells by a JetPrime transfection reagent (Polyplus, France) according to the manufacturer’s protocol.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pAGDisplay-based</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Mean FL-4 fluorescence signal values of RBD+ cells, subtracted by RFnano and the nonspecific signal of the RBD-population, were used to determine the KD of binding constants using a non-cooperative Hill equation and a nonlinear least-squares regression using Python 3.7 45.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Python</div><div>suggested: (IPython, RRID:SCR_001658)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The fluorescence signal (APC filter) of cells was measured by a FACS machine (LRS-II) and analyzed by the FlowJo software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">MR images were analyzed by the ImageJ software or by a custom-made script written in MATLAB (MathWorks, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MATLAB</div><div>suggested: (MATLAB, RRID:SCR_001622)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After tuning and matching to the1H frequency, shimming of the magnetic field, and B0 correction, the tumor area was measured with the following parameters: both axial and coronal images were acquired; T2 and T2* maps were reconstructed in the Paravision software; and were followed by analysis in the ImageJ software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>ImageJ</div><div>suggested: (ImageJ, RRID:SCR_003070)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analysis was performed using GraphPad Prism 8.0 software (GraphPad Software Inc., USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.03.25.485832: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">Field Sample Permit: Animals: Animal research was conducted at the United States Army Medical Research Institute of Infectious Diseases (USAMRIID).<br>IACUC: Ethics statement: These experiments and procedures were reviewed and approved by the United States Army Medical Research Institute for Infectious Diseases Institutional Animal Care and Use Committee (IACUC).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Genders were mixed male and female, and all animals were SARS-CoV-2 naïve at the outset of the study.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">Contamination: R4719 was determined to have no detectable mycoplasma, endotoxin or adventitious agents based on the assays and techniques used.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Serum binding and ACE-2 inhibitory antibody assessment: SARS-CoV-2-specific binding IgG antibody responses were measured using MULTI-SPOT® 96-well plates, V-PLEX SARS-CoV-2 Panel 7 Kit (Meso Scale Discovery (MSD), Rockville, MD).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2-specific binding IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">MSD SULFO-TAG™ conjugated anti-IgG antibody was added to each well.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-IgG</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Stimulations consisted of two pools of peptides spanning the S protein of SARS-CoV-2 or SARS-CoV-1 (1 µg/mL, JPT, PM-WCPV-S and PM-CVHSA-S respectively) in the presence of Brefeldin A (0.65 µL/mL, GolgiPlug™, BD Cytofix/Cytoperm Kit, Cat. 555028), co-stimulatory antibodies anti-CD28 (BD Biosciences Cat.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-1 (1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Following stimulation, cells were stained serially with LIVE/DEAD Fixable Blue Dead Cell Stain (ThermoFisher #L23105) and a cocktail of fluorescent-labeled antibodies (BD Biosciences unless otherwise indicated) to cell surface markers CD4-PE-Cy5.5 (S3.5, ThermoFisher #MHCD0418, Lot 2118390 and 2247858), CD8-BV570 (RPA-T8, BioLegend #301038, Lot B281322), CD45RA BUV395 (5H9, #552888, Lot 154382 and 259854), CD28 BUV737 (CD28.2, #612815, Lot 0113886), CCR7-BV650 (GO43H7, # 353234, Lot B297645 and B316676) and HLA-DR-BV480 (G46-6, # 566113, Lot 0055314).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>CD8-BV570</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>RPA-T8</div><div>suggested: (BD Biosciences Cat# 563795, RRID:AB_2722501)</div></div><div style="margin-bottom:8px"><div>CD45RA</div><div>suggested: (BD Biosciences Cat# 552888, RRID:AB_394517)</div></div><div style="margin-bottom:8px"><div>CD28</div><div>suggested: (BD Biosciences Cat# 612815, RRID:AB_2870140)</div></div><div style="margin-bottom:8px"><div>CCR7-BV650</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>B316676</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>G46-6</div><div>suggested: (BD Biosciences Cat# 566113, RRID:AB_2739515)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Infectivity and neutralization titers were determined using ACE2-expressing HEK293 target cells (Integral Molecular, Philadelphia, PA) in a semi-automated assay format using robotic liquid handling (Biomek NXp Beckman Coulter, Brea, CA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293</div><div>suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, biotinylated SARS-CoV-2 Spike trimer (Hexapro) was incubated with red streptavidin-fluorescent beads (Molecular Probes, Eugene, OR) for 2h at 37°C. 10 μl of a 100-fold dilution of beads–protein was incubated 2h at 37°C with 100μl 900-fold diluted plasma samples before addition of THP-1 cells (25,000 cells per well; Millipore Sigma, Burlington, MA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP-1</div><div>suggested: CLS Cat# 300356/p804_THP-1, RRID:CVCL_0006)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">293F-Spike-S2-WT cells were incubated with 10-fold diluted heat-inactivated (56°C for 30 min) plasma samples for 30 min at 37°C.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>293F-Spike-S2-WT</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">SARS-CoV-2 pseudovirions (PSV) were produced by co-transfection of HEK293T/17 cells with a SARS-CoV-2 S plasmid (pcDNA3.4), derived from the Wuhan-Hu-1 genome sequence (GenBank accession number: MN908947.3) and an HIV-1 (pNL4-3.Luc.R-E-, NIH HIV Reagent Program, Catalog number 3418).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.4</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pNL4-3.Luc.R-E-</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, SARS-CoV-2 Spike-expressing 293 FreeStyle (293F) cells were generated by transfection with linearized plasmid (pcDNA3.1) encoding codon-optimized full-length SARS-CoV-2 Spike protein matching the amino acid sequence of the IL-CDC-IL1/2020 isolate (GenBank ACC# MN988713).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Reduced data in the NSS files was extracted into Microsoft Excel workbooks using Notocord-derived formula add-ins, and the 30-minute (min) averages were calculated for each parameter for each subject.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Microsoft Excel</div><div>suggested: (Microsoft Excel, RRID:SCR_016137)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Assay equivalency was established by participation in the SARS-CoV-2 Neutralizing Assay Concordance Survey (SNACS) run by the Virology Quality Assurance Program and External Quality Assurance Program Oversite Laboratory (EQAPOL) at the Duke Human Vaccine Institute, sponsored through programs supported by the National Institute of Allergy and Infectious Diseases, Division of AIDS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Quality Assurance Program</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>Quality Assurance Program Oversite Laboratory</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Sample staining was measured on a FACSymphony(tm) A5 SORP (Becton Dickenson) and data was analyzed using FlowJo v.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>FlowJo</div><div>suggested: (FlowJo, RRID:SCR_008520)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Display of multicomponent distributions were performed with SPICE v6.0 (NIH, Bethesda, MD).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SPICE</div><div>suggested: (SPICE, RRID:SCR_016603)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04784767</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Active, not recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">SARS-COV-2-Spike-Ferritin-Nanoparticle (SpFN) Vaccine With A…</td></tr></table>


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. To investigatethis possibility, we performed ChIP-seq experiments on WT andmutant T-47D and MCF7 clones, grown for 5 days in hormone-depleted media followed by 1-hour E2 or DMSO treatments, using anantibody that recognizes the FLAG epitope tag.

      1 hour after E2 treatment --> To see where it's binding, no second effects from downstream.

    2. To characterizeendogenous ER mutations, we created multiple isogenic clonal linesthat heterozygously express FLAG-tagged mutant or WT (control) ERfrom the endogenous locus (Supplementary Fig. S1A; ref. 22). Wedeveloped two clones each for WT and the two most common ER LBDmutations (Y537S and D538G) in both T-47D and MCF7 breast cancercell lines (Supplementary Fig. S1B). Engineered lines included a FLAGepitope tag at the C-terminus to allow for downstream analyses. Theheterozygous expression of FLAG-tagged mutant or WT ER and theavailability of multiple clones per genotype provided a robust system toinvestigate mutant ER’s molecular effects.

      ER is an ER regulated gene, gives the extent of estrogen receptor effects. Uses multiple clones because all of the cells are genetically identical. Want to rule out that clones are doing something that is a clone effect independent of your study. This also helps to reduce likelihood that the CRISPR mutation didn't have off target effects that influenced the results.

    Annotators

    1. SciScore for 10.1101/2022.03.23.485576: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression of different coronavirus E proteins, the SARS-CoV-2 S, and SARS-CoV S protein were confirmed by transfection with the Turbofect transfection reagent (ThermoFisher) followed by radiolabeling and immunoprecipitation analysis using a mouse monoclonal antibody directed against the HA-tag (Thermo-Fisher, #26183) or an antibody against SARS-CoV Spike protein (Sino Biologicals, #40590-T62).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>antibody against SARS-CoV Spike protein</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cultures were then incubated at 4C overnight with an and a rabbit monoclonal antibody against either Golgin-97 (Abcam, #ab84340) or Calnexin (Cell Signaling Technology, #2679).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calnexin (Cell Signaling Technology, #2679</div><div>suggested: (Cell Signaling Technology Cat# 2679, RRID:AB_2228381)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The cells were washed in PBS, incubated with a secondary goat anti-rabbit antibody conjugated to AlexaFluor™-488 (Invitrogen, A11008) for 1 h at room temperature, washed, and reacted with rabbit anti-mouse conjugated to AlexaFluor™- 594 (Invitrogen, A11062) for 1 h.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-rabbit</div><div>suggested: (Thermo Fisher Scientific Cat# A-11008, RRID:AB_143165)</div></div><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: (Innovative Research Cat# A11062, RRID:AB_1500656)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression of E was detected using an HA-tag antibody (Invitrogen).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HA-tag</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Aliquots of cells from the same co-transfections were also analyzed for protein expression by immunoblots using antibodies directed against the HA-tag (E proteins, SARS-CoV-2 S protein, and Vpu), the SARS-Cov-1 S protein, or against GFP to monitor SARS-CoV-2 N-GFP expression.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2 S protein,</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>GFP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The lysates were transferred to new tubes and BST-2 (using an anti-BST-2 antibody), the E proteins (all having a C-terminal HA-tag), and SARS-CoV and SARS-CoV-2 S proteins, and N-GFP proteins, or GAPDH (to equalize loading) immunoprecipitated using appropriate antibodies.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-BST-2</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>GAPDH</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Immunofluorescence studies: To examine the intracellular localization of the SARS-CoV-2 E protein, COS-7 cells grown on 13 mm cover slips were transfected with either the empty pcDNA3.1(+) vector or one expressing the SARS-CoV-2 E protein using Turbofect transfection reagent (ThermoFisher).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>COS-7</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">At 48 h post-transfection (pt), the culture medium was collected, clarified by low-speed centrifugation, and the supernatants analyzed for infectious virus by titration on TZM-bl cells (29, 30, 91–95).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>TZM-bl</div><div>suggested: RRID:CVCL_B478)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Levels of infectious virus were determined by preparing a series of 10-fold dilutions of the culture supernatant followed by inoculation of Vero cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">At 24 h, equal levels of HIV-1ΔEnv-/VSV-G pseudotyped virus (M.O.I. of 0.1) were used to infect HEK293 cells for 48h.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids with the entire HIV-1 NL4-3 genome (pNL4-3) and pNL4-3Δvpu were obtained from the NIH AIDS Reagent Branch.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNL4-3Δvpu</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293 cells were co-transfected with empty pcDNA3.1(+) or the vector expressing E proteins and pNL4-3.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNL4-3</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293 cells were transfected with either the empty pcDNA3.1(+) vector or one expressing SARS-CoV-2 E protein.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1(+)</div><div>suggested: RRID:Addgene_129020)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Analysis of the phosphorylation of eIF-2α: To determine if the expression of the E protein of SARS-CoV-2 resulted in phosphorylation of eIF2α, HEK293 cells seeded in 6-well plates were either left untransfected or transfected with 1 μg of pUC19 or of a SARS-CoV-2 E-expressing plasmid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pUC19</div><div>suggested: RRID:Addgene_50005)</div></div><div style="margin-bottom:8px"><div>SARS-CoV-2 E-expressing</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK293 cells were co-transfected with either empty pcDNA3.1(+) vector and pcDNA3.1(+) expressing the human BST-2 protein, or pcDNA3.1(+) expressing each of the proteins described above and BST-2.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plasmids expressing the SARS-CoV and SARS-CoV-2 S proteins were purchased from Sino Biologicals (catalog # VG40150-G-N; VG40589-CY).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Sino Biologicals</div><div>suggested: None</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.03.21.485247: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IACUC: Animal experiments: All the animal experiments were performed in accordance with protocols approved by the Icahn School of Medicine at Mount Sinai (ISMMS) Institutional Animal Care and Use Committee (IACUC).</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">Mouse immunization and challenge studies: Female BALB/c mice were used in all studies.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">All samples were analyzed in a blinded manner.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Antibodies</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The HN protein was detected by a mouse monoclonal antibody 8H2 (MCA2822, Bio-Rad).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MCA2822</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">ELISA plates were afterwards washed 3 times with PBST and 50 μL of anti-mouse IgG-horseradish peroxidase (HRP) conjugated antibody (Cytiva, GE Healthcare) was added at a dilution of 1:3,000 in blocking solution.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse IgG-horseradish</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">During this time the primary antibody was biotinylated according to manufacturer protocol (Thermo Scientific EZ-Link NHS-PEG4-Biotin)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>NHS-PEG4-Biotin</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Blocking solution was removed and 100 μl/well of biotinylated mAb 1C7C7, a mouse anti-SARS nucleoprotein monoclonal antibody generated at the Center for Therapeutic Antibody Development at The Icahn School of Medicine at Mount Sinai ISMMS</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The plaques were immuno-stained with an anti-SARS-CoV-2 NP primary mouse monoclonal antibody 1C7C7 kindly provided by Dr. Thomas Moran at ISMMS.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-SARS-CoV-2 NP</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">An HRP-conjugated goat anti-mouse secondary antibody was used at 1:2000 and the plaques were visualized using TrueBlue™ Peroxidase Substrate (SeraCare Life Sciences Inc.)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>anti-mouse</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">VERO-TMPRSS2 cells (BPS Biosciences, #78081) were maintained in DMEM (Gibco) containing 10% (vol/vol)</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>VERO-TMPRSS2</div><div>suggested: JCRB Cat# JCRB1818, RRID:CVCL_YQ48)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Specifically, transfected BSRT7 and DF-1 cells were washed with warm PBS and trypsinized.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>DF-1</div><div>suggested: RRID:CVCL_XF08)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">BSRT7 cells were mixed with DF-1 cells (~1: 2.5) in a 10-cm dish.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BSRT7</div><div>suggested: CCLV Cat# CCLV-RIE 0583, RRID:CVCL_RW96)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Vero-E6 cells or Vero-TMPRSS2 were seeded onto 12-well plates in growth media at 1:5 and cultured for two days.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero-E6</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Organisms/Strains</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Mouse immunization and challenge studies: Female BALB/c mice were used in all studies.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>BALB/c</div><div>suggested: RRID:IMSR_ORNL:BALB/cRl)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, the variant HXP-S were inserted into the pNDV_LS/L289A rescue plasmid (between P and M genes) by in-Fusion cloning (Clontech, CA, USA).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNDV_LS/L289A</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The recombinant product was transformed into MAX Efficiency™ Stbl2™ Competent Cells (Thermo Fisher Scientific, MA, USA) to generate the pNDV-HXP-S rescue plasmid.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pNDV-HXP-S</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The next day, cells were transfected with 2 μg of pNDV-HXP-S, 1 μg of pTM1-NP, 0.5 μg of pTM1-P, 0.5 μg of pTM1-L and 1 μg of pCI-T7opt and were re-suspended in 250 μl of a modified Eagle’s Minimum Essential Medium (Opti-MEM; Gibco).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pTM1-NP</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pTM1-P</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pTM1-L</div><div>suggested: None</div></div><div style="margin-bottom:8px"><div>pCI-T7opt</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, the mammalian-cell codon-optimized nucleotide sequence of a soluble spike protein (amino acids 1-1,213) lacking the polybasic cleavage site, carrying two stabilizing mutations (K986P and V987P), a signal peptide, and at the C-terminus a thrombin cleavage site, a T4 fold-on trimerization domain, and a hexahistidine tag was cloned into the mammalian expression vector pCAGGS. https://www.beiresources.org/).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pCAGGS.</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, the mammalian-cell codon-optimized nucleotide sequence of a soluble spike protein (amino acids 1-1,213) lacking the polybasic cleavage site, carrying two stabilizing mutations (K986P and V987P), a signal peptide, and at the C-terminus a thrombin cleavage site, a T4 fold-on trimerization domain, and a hexahistidine tag was cloned into the mammalian expression vector pCAGGS. https://www.beiresources.org/).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>https://www.beiresources.org/</div><div>suggested: (BEI Resource Repository, RRID:SCR_013698)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Analysis was performed using GraphPad Prism 7 software.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical analyses were performed using Prism software (GraphPad).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: We found the following clinical trial numbers in your paper:<br><table><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Identifier</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Status</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Title</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04871737</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Active, not recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Study of a Live rNDV Based Vaccine Against COVID-19</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT05181709</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">A Live Recombinant Newcastle Disease Virus-vectored COVID-19…</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04830800</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">A Phase 1/2 Safety and Immunogenicity Trial of COVID-19 Vacc…</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04764422</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Assess the Safety and Immunogenicity of NDV-HXP-S Vaccine in…</td></tr><tr><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">NCT04993209</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Recruiting</td><td style="min-width:95px; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Clinical Trial of the COVID-19 Vaccine (Recombinant, Inactiv…</td></tr></table>


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

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    1. SciScore for 10.1101/2022.03.21.485243: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      NIH rigor criteria are not applicable to paper type.

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Expression and Purification of recombinant antibodies: A pair of plasmids separately expressing the heavy- and the light-chain of antibodies were transiently co-transfected into HEK293F cells.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK293F</div><div>suggested: RRID:CVCL_6642)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Serial 1/3 dilutions of antibodies were incubated with pseudoviruses at 37°C for 1 hour, and then the mixtures were added in ACE2 expressed Huh-7 cells (104 per well in 96-well plates).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Huh-7</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Production of recombinant D614G and variants spike ectodomain: The gene encoding SARS-CoV-2 S ectodomain (residues 1-1208, Gene Bank: MN908947) was synthesized (GeneScript) and cloned into mammalian expression constructs pcDNA-3.1, proline substitutions at residues 986 and 987, “GSAS” substitution at furin cleavage site (residues 682-685), a T4 fibritin trimerization motif, an HRV3C protease cleavage site, a TwinStrepTag, and an 8XHisTag at C-terminal were introduced simultaneously by MultiS one step cloning kit (Vazyme).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA-3.1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Using the SARS-CoV-2 WT plasmid as the template, mutations such as D614G, B.1.17 (Del 69H70V, N501Y, P681H, S982A, Del 145Y, A570D, T716I, D1118H), B.1.351 (K417N, E484K, N501Y) and P1 (K417T, E484K, N501Y) was introduced by Multi Site-Directed Mutagenesis Kit (Yeasen).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SARS-CoV-2 WT</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The expression plasmid of Omicron S with HexaPro mutations(26), “GSAS” substitution at furin cleavage site (residues 682-285), a T4 fibritin trimerization motif, a TwinStrep Tag, and a C-terminal 8 × His Tag was constructed into pcDNA3.1 vector by MultiS one step cloning kit (Vazyme).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1</div><div>suggested: RRID:Addgene_79663)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Briefly, whole spike glycoprotein sequences of SARS-CoV, wild type or variants of SARS-CoV-2 were inserted into the vector of pcDNA3.1+ and severally co-transfected into 293 T cells (ATCC, Manassas, VA, USA) with a defective HIV-1 genome that encodes luciferase reporter.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pcDNA3.1+</div><div>suggested: RRID:Addgene_117272)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">A nonlinear regression analysis was performed on the resulting curves using Prism (GraphPad) to calculate half-maximal inhibitory concentration (IC50) values.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Prism</div><div>suggested: (PRISM, RRID:SCR_005375)</div></div><div style="margin-bottom:8px"><div>GraphPad</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Automated data acquisition was carried out with SerialEM software(27).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>SerialEM</div><div>suggested: (SerialEM, RRID:SCR_017293)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Cryo-EM image processing: All the data processing was carried out using either modules on, or through, RELION v3.0 and cryoSPARC(28).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>RELION</div><div>suggested: (RELION, RRID:SCR_016274)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For S-15 complex (Fig.S10), a total of 6,943 movie stacks was binned 2 × 2, dose weighted, and motion corrected using MotionCor2(29).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MotionCor2</div><div>suggested: (MotionCor2, RRID:SCR_016499)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">After blob-picking in cryoSPARC and 2D classification, trimer and monomer particles were observed.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>cryoSPARC</div><div>suggested: (cryoSPARC, RRID:SCR_016501)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For model building of S-15 and S-60, the apo-S trimer model and the antibody (15 and 60) model generated by swiss-model were fitted into the map using UCSF Chimera(31) and followed by manually adjustment in COOT(33), as well as real space refinement in Phenix.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Phenix</div><div>suggested: (Phenix, RRID:SCR_014224)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Model validation was performed using MolProbity.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>MolProbity</div><div>suggested: (MolProbity, RRID:SCR_014226)</div></div></td></tr></table>

      Results from OddPub: Thank you for sharing your data.

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


      <footer>

      About SciScore

      SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

      </footer>
    1. SciScore for 10.1101/2022.03.22.485248: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      <table><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Ethics</td><td style="min-width:100px;border-bottom:1px solid lightgray">IRB: Studies using primary human cells were approved by the University of Queensland Human Medical Research Ethics Committee.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Sex as a biological variable</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Randomization</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Blinding</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Power Analysis</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr><tr><td style="min-width:100px;margin-right:1em; border-right:1px solid lightgray; border-bottom:1px solid lightgray">Cell Line Authentication</td><td style="min-width:100px;border-bottom:1px solid lightgray">not detected.</td></tr></table>

      Table 2: Resources

      <table><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Experimental Models: Cell Lines</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">THP-1 cells (TIB-202; ATCC) were maintained in RPMI 1640 medium supplemented with 10% heat-inactivated foetal bovine serum (FBS), 2 mM GlutaMAX (Life Technologies) and 50 U/ml penicillin–streptomycin (Life Technologies).</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>THP-1</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Calu-3 cells purchased from ATCC (HTB-55) were maintained in Minimal Essential Media (Invitrogen), containing 10% heat-inactivated foetal bovine serum (Cytiva), 50 U/ml penicillin and streptomycin (Life Technologies Australia), and were seeded at 300 000 cells per well in a 12-well plate 48 h prior to experiments.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu-3</div><div>suggested: ATCC Cat# HTB-55, RRID:CVCL_0609)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">HEK-293T cells were transfected with the expression vectors according to the manufacturer’s protocol with PEI 2500 (BioScientific) and transduced target THP-1 cells were selected with puromycin (1 μg/mL) after 24 h and used for assays after 72 h.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>HEK-293T</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Virus was grown on Vero E6 TMPRSS2 cells for 48 h in DMEM with 2% FBS, and cell debris was cleared by centrifugation at 500G for 5 minutes at room temperature.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero E6 TMPRSS2</div><div>suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For Calu3 cells, virus was added to cells to give a total volume of 500 μL of RPMI 1640 with 2% FBS (HMDM and THP-1) or MEM with 2% FBS (Calu3) per well.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Calu3</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">For studies involving SARS-CoV-2 infection of BAL macrophages, the SARS-CoV-2 isolate hCoV-19/Australia/VIC01/2020 (kindly provided by the Victorian Infectious Diseases Reference Laboratory) was grown in Vero cells for 72 h in serum-free MEM with 1 μg/ml TPCK trypsin.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>Vero</div><div>suggested: None</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Recombinant DNA</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Lentiviral transduction: A lentiviral construct containing human ACE2 (Addgene 155295), or mScarlet (Addgene 85044) was cloned into pLV-CMV-MCS-IRES-Puro-Sin (48) and packaged into lentivirus in HEK-293T cells by means of third generation lentiviral packaging plasmids (</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pLV-CMV-MCS-IRES-Puro-Sin</div><div>suggested: None</div></div></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">The Mpro expression vector was generated by cloning the Mpro PCR product into a modified pEF6 plasmid, with an HA-tag N-terminal of the multiple cloning site, by standard restriction digest cloning techniques.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>pEF6</div><div>suggested: RRID:Addgene_70765)</div></div></td></tr><tr><th style="min-width:100px;text-align:center; padding-top:4px;" colspan="2">Software and Algorithms</th></tr><tr><td style="min-width:100px;text=align:center">Sentences</td><td style="min-width:100px;text-align:center">Resources</td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Statistical Analysis: Statistics were calculated using GraphPad Prism using tests indicated in figure legends.</td><td style="min-width:100px;border-bottom:1px solid lightgray"><div style="margin-bottom:8px"><div>GraphPad Prism</div><div>suggested: (GraphPad Prism, RRID:SCR_002798)</div></div></td></tr></table>

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.



      Results from TrialIdentifier: No clinical trial numbers were referenced.


      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:


      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
      • No protocol registration statement was detected.

      Results from scite Reference Check: We found no unreliable references.


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    1. I’ve established the habit of asking myself: Is this information or oppor-tunity to communicate worth my attention at all, given my goal for today? Is it something I want to look at later, but not right now while I am focus-ing on a task toward a larger goal (in which case, maybe I’ll open a tab on my browser)? Is it information that I don’t want to distract myself with at the moment and don’t want to burden my near-term reading agenda, but might want to refer to later, because it is about a subject that interests me (in which case I’ll tag and bookmark)? Like basic mindfulness, paying attention to microdecisions—and learning to make them more and more quickly—is easy enough to start, and yields increasing power to diligent, regular practitioners. It’s an exercise in strategic goals (What am I setting out to do?), attention (What am I about to click on?), and intention (I’m going to ignore this, or open a tab or bookmark, because I intend to return to focus) that deepens the more you do it.

      Beispiel für eine Gewohnheit und für konkrete Fragen, die man sich während seiner online/onlife Zeit stellen kann

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