1. Last 7 days
    1. On 2021-04-11 15:40:12, user Paolo Di Tommaso wrote:

      Thanks for this extensive and detailed comparison of WfMSs. I really found extremely useful and interesting to read.

      I have however some concerns about the scaling benchmark that reports that Nextflow cannot scale more than 500 parallel tasks (fully disclosure: I'm the author of the Nextflow framework).

      I think this is not accurate and very likely the problem is caused by a wrong use of the maxForks directive, thing that also the authors have correctly identified:

      We suspect this happened because while we were controlling the maxForks directive, we used the default value of the queueSize parameter, which defines "the number of tasks the executor will handle in a parallel manner"

      If fact, the markForks should only be used to *limit* the tasks parallelisation of a specific process, and instead it should have been used the queueSize option that, as reported above, determines the number of tasks that Nextflow handleS in a parallel manner (default 100 when using Slurm or similar scheduler). I think addressing this point would result in a more fair comparison.

      Other minor points, the version of Nextflow you have used is very old, considering using a more recent one. Regarding CWL and WDL being based on the dataflow paradigm, I'm not sure this is accurate. Finally, there are several citation of works I've authored (thanks!), however the surname should be "Di Tommaso", not "Tommaso".

    1. On 2021-04-11 04:26:18, user 吉田 真明 wrote:

      Now published in Scientific Reports;<br /> Sato N, Tsuda SI, Nur E Alam M, Sasanami T, Iwata Y, Kusama S, Inamura O, Yoshida MA, Hirohashi N. Rare polyandry and common monogamy in the firefly squid, Watasenia scintillans. Sci Rep. 2020 Jul 3;10(1):10962. doi: 10.1038/s41598-020-68006-1. PMID: 32620906; PMCID: PMC7334199.

    1. On 2021-04-09 22:39:45, user kdrl nakle wrote:

      I don't trust your research at all. You concluded that 30% Ethanol is effective while 80% is not (or a lot less). This contradicts all the researches previously. You did not bother one iota to explain this huge elephant in your paper. By the way, your graphs lack clarity.

    1. On 2021-04-09 01:06:30, user Sam Smith wrote:

      https://en.wikipedia.org/wi...<br /> * On 17 February 2021, Pfizer announced that neutralisation activity was reduced by two thirds (to 1/3) for the 501.V2 variant.<br /> On 1 April 2021, an update on a South African vaccine trial stated that the vaccine was 100% effective so far (vaccinated participants saw no cases), with 6 of 9 infections in the placebo control group being the B.1.351 variant.<br /> * In February, Moderna reported that the current vaccine produced only one sixth (1/6) of the antibodies in response to the South African variant compared with the original virus.

      ....<br /> But does the following text mean that Moderna and Pfizer are likely equally good against South African variant?:

      https://www.statnews.com/20...<br /> "Feb 2, 2021.<br /> Each dose of Pfizer’s contains 30 micrograms of vaccine. Moderna went with a much larger dose of vaccine, 100 micrograms. It means the company is using a little more than three times as much vaccine per person as Pfizer is. And yet, they aren’t getting better results. <br /> Operation Warp Speed asked Moderna to test if it could lower the dosage of its vaccine without eroding the vaccine’s protection".

    1. On 2021-04-09 00:00:20, user Charles Warden wrote:

      Hi,

      Thank you for posting this preprint.

      I have a couple comments / questions:

      1) I think you have a minor typo in your "Commands Used" section:

      Current: Accuray Comparison with hap.py<br /> Proposed Correction: Accuracy Comparison with hap.py

      2) When I tested DeepVariant for my germline samples, I think there was something in the computational benchmarks that was not representative (at least for me, until I actually tried to use the program). I don't directly mention GATK, but I believe the statistics here match DeepVariant having some noticeably higher requirements than GATK (such that I could run one on my local computer but not the other).

      Would those concerns still be true? I have some experience making joint variant GATK calls, but I don't think I have strictly tested something specific for Trio analysis.

      If you can run on Google Cloud for free, I guess that might not a huge deal (except for the data transfer time could be non-trivial, and it would need to remain free to use and run indefinitely).

      For example, I am not 100% sure what is the best question to ask, but is the memory requirement for the benchmarks in Figure 6 60 GB for n1-standard-16?

      If so, is there a way to assess how well each program is making full use of what is available? Likewise, is it possible to have some sort of benchmark in computationally limited scenarios (such as having 8 GB of RAM and 2 cores)? Something closer to that limited scenario (or at least less than 32 GB of RAM and 8 cores) is what would prefer want to use (locally, not on the cloud).

      Thank you very much!

      Sincerely,<br /> Charles

    1. On 2021-04-08 22:20:07, user Charles Warden wrote:

      Hi,

      Thank you for putting together this preprint.

      I wish Genome Research had a Disqus-style comment system, similar to some other journals. I am currently taking something that I wanted to post as a comment on a different Genome Research article, and I instead will post it on PubPeer. So, in general, that is an option, even though I do not think that it is ideal for something truly intended as a comment.

      I think I would have to take a closer look to develop more of an option on this specific matter, but I did have a couple thoughts:

      1) My impression from this Tweet was different than my impression from the beginning of this preprint:

      https://twitter.com/KVittin...

      I can see certain parts of the preprint where I think the tone is more like a comment or complementary study. However, that is different than a "Contradictory Results" preprint or a PubPeer posting (assuming that the intention is to flag something about the study that may need to be corrected or retracted). I am not sure if that can still be changed for this preprint.

      My preference would probably to be something closer to my impression of the Tweet (as positive as possible), but it is not immediately clear to me if that is the intention. Essentially, I am noting that I am not entirely clear about the severity of the message.

      For example, I think there are usually limitations to simulated data. I can also believe that there are viewpoints that may benefit from being made more clear, beyond what is within the paper. However, I believe that I would agree with the idea of limitations due to extra noise in the RNA-Seq data, and I am not sure why this has to be "contradictory" instead of "alternative" results.

      I am not sure if it helps, but I have some notes about the RNA-Seq DEG method limits here. While I could see how someone could call the discordance "contradictory," I would say it is more of an overall limit (where no 1 strategy is best, and you can't lock down everything in advance). In that sense, I would say different freely available methods complement each other, rather than detract from each other.

      It is certainly possible that I missed something, since I did not have a strong opinion when I first saw the Varabyou et al. 2020 paper. However, unless I am missing something important, I wonder if a slightly different tone might help?

      In terms of material linked from my blog post (and other experiences), I think what I have seen matches some extra noise in the Salmon gene lists (relative to the TopHat2 / STAR htseq-count gene lists), but not with a horrible amount of extra noise. So, in terms of what I see in the abstract, I think my experiences might agree with the last sentence in the abstract (even though I am talking about extra noise in differential gene lists and the authors are talking about detection of expression in that particular sentence). Is there something different that you are concerned about?

      2) You say that "All data and scripts are available upon request.". I am not sure how large the intermediate files are in this situation. However, I think code and perhaps some processed data can be made available through means like GitHub, Zenodo, etc. (similar to what you have on FigShare).

      In general, I think it is best to avoid providing materials upon request, if at all possible. So, I am not sure what is the limitation (or how much you are not providing already), and I think either making more available and/or making clear what subset you couldn't provide might help.

      Best Wishes,<br /> Charles

    1. On 2021-04-07 19:09:52, user Dietmar Lohmann wrote:

      Another point: Most children with isolated unilateral rb do not show pathogenic RB1 variants in DNA from blood. However, DNA from retinoblastomas often show pathogenic RB1 variants. I wonder if it was possible to perform genetic testing on DNA from retinoblastomas first and then, as a next step, test DNA from blood for the specific alterations identified in the patient's tumor?

    2. On 2021-04-07 19:05:51, user Dietmar Lohmann wrote:

      You stated: Consanguinity of parents was very high; found in six RB out of seven cases (85.7%), the 1st degree cousins were less (28.6%) while the 2nd degree was high (57.1%). The least was no Consanguinity of parents (14.3%).<br /> Consanguinity is usually relevant in recessive traits. Heritable retinoblastoma is deemed to be autosomal dominant. What is the interpretation of the finding "Consanguinity of parents was very high"?

    1. On 2021-04-07 17:34:05, user Otakar Mach wrote:

      Considering the fact, that the report under review is a preprint, this paper is not to be accepted as peer review publication.<br /> Early immune response in mice immunized with a semi-split inactivated vaccine against SARSCoV-2 containing S protein-free particles and<br /> subunit S protein. Marek Petráš, Petr Lesný, Jan Musil, Radomíra Limberková, Alžběta Pátíková, Milan Jirsa, Daniel Krsek, Pavel Březovský,<br /> Abhishek Koladiya , Šárka Vaníková, Barbora Macková, Dagmar Jírová, Matyáš Krijt, Ivana Králová Lesná, Věra Adámková<br /> The authors set themselves a goal – to design a vaccine prototype using the protein of an inactivated virus. As a source of the virus they<br /> used a supernatant from the cell-culture of Vero E6 cells. In this place I rebuke the authors for not including detailed information about the<br /> virus origin. The virus is completely new. The reference saying that it was taken from the SZÚ archive can lead to a conclusion that the SZÚ<br /> employees isolated the virus and stocked it in the archives, the virus should be identified and named according the taxonomic rules.<br /> As a second the scale is absent in the electron microscope images. The proof of the capture of S protein is missing, only authors have<br /> supposed this capture. The authors must support their claim with using e.g. an immunochemical assay. The authors consistently worked<br /> with a low-speed supernatant of the tissue media. They used 300 g and 1800 g only.. Under these circumstances only the cells and larger<br /> parts of the cell detritus are removed from the tissue culture meidum. The virus together with a rich spectrum of the cell detritus are<br /> present in the supernatant. The authors never tried to prepare a virus specimen using differential or density gradient centrifugation.<br /> The precise data about the concentration of the protein is not present in the study, not even in the paragraph regarding the preparation<br /> thickening . The purity of the virus fraction - how much contaminants it contains- can’t be found in the study. Saying this, it makes no sense<br /> to employ ourselves with the remaining paragraphs of the preprint any further. Very much useless work was done here. Mice have been<br /> dosed a rich spectrum of protein, glycoproteins and low-molecular substances. This mixture of very immunogenic substances can never be<br /> used as a vaccine. It does not matter when used in a mouse, but one cannot envisage using it as a vaccine for human beings.<br /> If the authors intended to use their experiment as a prototype for people, they should have thought of a suitable adjuvant. Aluminium<br /> compounds are only suitable for a laboratory use.<br /> The way in which the lab work has been done brings the following result: a low-speed tissue media supernatant of undefined nature<br /> containing inactivated unspecified virus, its protein structures and also containing unspecified antigen originating from the cell culture<br /> caused an immune response in mice.<br /> The preprint can in no respect be considered a sound prototype for a human vaccine.<br /> Otakar Mach 22.3.2021

    1. On 2021-04-07 10:05:16, user Florent Lassalle wrote:

      peer-reviewed article published in Systematic Applied Microbiology:<br /> Lassalle F et al. 2021. Phylogenomics reveals the basis of adaptation of Pseudorhizobium species to extreme environments and supports a taxonomic revision of the genus. Syst Appl Microbiol 44(1):126165; doi: 10.1016/j.syapm.2020.126165.<br /> http://www.sciencedirect.co...

    1. On 2021-04-06 17:11:58, user YSR wrote:

      In the sentence below

      "Moreover, these conditioning regimens were used therapeutically in mouse models of sickle cell disease, hemophilia, Fanconi anemia, and recombinase-activating gene (RAG) deficiency" The citation numbers needs to be switched ( 20 and 21).

    1. On 2021-04-06 06:11:24, user Om Prakash Gupta wrote:

      Its good work to identify the molecular defense pathway operating during Capsicum annuum L.-Phytophthora capsici L. pathosystem.

      Suggestions are welcome.

    1. On 2021-04-05 18:27:49, user Xavier Turon wrote:

      Dear readers<br /> Note that in the BioRxiv version we noticed a mistake in the program used to perform the denoising with entropy correction. <br /> Please refer to the published final version in BMC Bioinformatics:<br /> https://doi.org/10.1186/s12... <br /> In short, more ESVs are retained once the glitch has been corrected. Conclusions remain unchanged, but numbers are corrected in the published version<br /> Sorry for the inconvenience<br /> The authors

    1. On 2021-04-05 17:08:09, user Duane wrote:

      Excellent paper with a huge amount of data. I would like to know what percent of plated cells grew enough cells to analyze by FACS for the functional output.

    1. On 2021-04-05 03:48:58, user Zohreh Khosravi wrote:

      Congratulations with your amazing paper. I have a question and really appreciate you if you could help me in this matter.<br /> when You performed a whole genome CRISPR screen in cancer cells to identify regulators of T cell killing. One of your hits leads to increased killing of your cancer cells in presence of T cells but it represents an uncharacterised protein. What is the hypothesis and which three experiments would you carry out to elucidate the function of your hit?<br /> Best Regards,<br /> Zohreh

    1. On 2021-04-05 02:39:48, user Clara B Jones wrote:

      Suggestion: ... remove first sentence of Abstract from paper ["The origin...in science."] ... it is an example of the Scala Naturae [Social Science] approach to Animal Evolution that is probably misguided, if not inaccurate ...

    1. On 2021-04-05 00:48:31, user Pablo Jenik wrote:

      This is nice work, a nice contribution to our understanding of petal morphogenesis. But I'm biased towards mosaic work! I take slight issue with the characterization of our older work: "In Arabidopsis that has simple and unfused petals, petal shape and size were never fully restored when AP3 was expressed in one cell layer only (Jenik and Irish, 2001)". Although we showed that full size required the cooperation of both layers, the L1 did appear to control organ shape in Arabidopsis. I think this is relevant because, although the authors focus mostly on growth (size), it is clear that wico (L1) flowers also have the right shape of the limbs, similar to the results in Arabidopsis. I can't tell from the pictures whether the tube shape (not size) in wico is abnormal or not, but it may be good to expand the discussion about the distinction between growth (size) and shape. I also found it thought provoking that, while in Arabidopsis cell fate (epidermal and subepidermal) is clearly cell autonomous (from our work), here it depends on which layer is wild type and the position in the petal. Different signaling or, as they mention, some protein movement in one species but not the other? Interesting!

    1. On 2021-04-03 18:31:11, user smith wrote:

      Pablo, great work! There is flaw in the paper that may change your results. I think the SC heat map is inaccurate. Feet and Fingers must be red not blue. See this paper for a reference:Emotional sweating across the body: Comparing 16 different skin conductance measurement locations.

    1. On 2021-04-02 14:33:20, user Heran Darwin wrote:

      This paper makes several overstatements about Mtb physiology. For example, narGH has not been shown to be required in vivo (the references they use have nothing to do with their statements), and the mechanisms of Cu toxicity to Mtb have not been determined. I hope the authors correct these statements rather than spread disinformation.

    1. On 2021-04-02 10:26:46, user Xiao-Pan Hu wrote:

      Very interesting work! But I have some doubts... <br /> I’m not an experimentalist, I might be wrong when interpreting experimental data.<br /> 1. Doubts on equation 2, equation 12, and equation 13. The ΦR in equation 2 (and 12), should it be ΦRfb as the author wrote in equation 13? I cannot understand why equation 12 and 13 hold at the same time, as ΦR is not equal to ΦRfb, apparently. My understanding is it depends on parameter γ (or codon elongation k). If k is the averaged elongation rate of total ribosome, there is no problem in equation 2 and 12. But if k is the elongation rate of an active ribosome, ΦR should be ΦRfb, as not all ribosomes are actively translating. When calculating degradation rate η in fig 3, k is the measured data by Dai, which is the elongation rate of active ribosome. For my understanding, it is not suitable (because all ribosomes are assumed to be active in equation 12).<br /> 2. Continuing. After a very careful reading of the whole paper, especially the section “A combined model accounting for both active ribosomes and protein turnover predicts at most 20% of inactive ribosomes at slow growth”, I noticed equation 13 is the real main equation of this theory. The active ribosome faction can be directly calculated by this equation.<br /> 3. The data from Pine 1973 in Figure 3. It is great that a lot of effort were put into searching for degradation rate. I had only a quick read of the papers by Pine in 1973 and 1970, my understanding of the experiments might be wrong. What I found a little strange is: in the 1973 paper, the data were measured under NH4+ limited conditions, as Pine wrote in the abstract “Generally, NH4+ is the most effective regulator. Its depletion progressively increases the basal proteolytic rate…”. As NH4+ starvation increase protein turnover (maybe N-limitation does not), I don’t know if it is suitable to use this dataset as “main” experimental data to verify the theory here. Moreover, under N-limitation, the elongation rate is smaller than that under C-limitation (https://www.nature.com/arti.... This dataset (Pine 1973) is not ideal, but it seems to be acceptable… <br /> 4. Continuing. I have doubts on the experimental data showed on Fig. 3. In Pine 1973 Fig 1 (also other figures), the maximum degraded protein fraction is ~ 14% in 4 hours (Is it 4 h? Am I wrong? If it is 4 h, data in fig 1 will be consistent with data in table 1). It was much smaller than the data showed in this paper (degradation rate is about 0.14 per hour at growth rate = 0.1 per hour). In the 1970 paper, protein degradation is 2.5% per hour and 3% hour on glucose and acetate, respectively. It is also smaller than the data in this paper. If the authors are correct, degradation indeed dominates (when degradation rate is faster than growth rate) the growth law at low growth rates. If degradation rate is about 0.03 or 0.04 per hour at low growth rates (my understanding of the data from Pine 1973, doubling time = 7 hours in figure 1), degradation will dominate only at very low growth rates (when growth rate < 0.04 per hour) and the active ribosome fraction in Fig 4 will be much lower than 80% at low growth rates.<br /> 5. If most of the ribosome are active at low growth rates (as the conclusion of this paper), it could update the “fast adaption theory” between growth condition transitions. When transiting E. coli from a poor medium to a rich medium, it is likely that the degradation rate will also drop. In this case, the “maintenance” ribosome can translate more “not degraded” proteins (If degradation rate does not drop, the fast adaption is unlikely to happen). The former knowledge that the “inactive” ribosome contributes to fast adaption will change to the “maintenance” ribosome contributes to fast adaption. But as comments 3-4, I’m not sure if degradation dominates or contributes partially to growth law at low growth rates.

    1. On 2021-04-01 18:00:35, user Frances Kona wrote:

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    1. On 2021-04-01 17:11:39, user Alexander Kozik wrote:

      This is very interesting and important discovery of new types of repeats in mitochondrial genomes. There are at least two parallel observations of similar tandems in other species:

      Lin et al. Comparative analysis reveals the expansion of mitochondrial DNA control region containing unusually high G-C tandem repeat arrays in Nasonia vitripennis. Int J Biol Macromol. 2021 Jan 1;166:1246-1257.<br /> https://pubmed.ncbi.nlm.nih...

      Kinkar et al. Nanopore Sequencing Resolves Elusive Long Tandem-Repeat Regions in Mitochondrial Genomes. Int J Mol Sci. 2021 Feb 11;22(4):1811.<br /> https://pubmed.ncbi.nlm.nih...

      In my opinion these tandem repeats are very different from those found in plants. Discussion about plant-like features of the quagga mussel mitogenome and recombination might be misleading.

    1. On 2021-04-01 11:06:28, user Radha Krishnan wrote:

      Hi, The article looks interesting. <br /> Could you please mention about the oligomerisation state of the nsp16 after purification ? Does the purified nsp16 forms oligomers/souble aggregates in your case ?

    1. On 2021-04-01 03:10:46, user Michael Ailion wrote:

      This manuscript investigates the maturation of secretory granules (SGs) using the glue granules of the Drosophila larval salivary gland as a model system. The authors show that these SGs dramatically increase in size during maturation, in two different growth phases<br /> with distinct kinetics. An RNAi screen of Rab proteins identifies Rab1 and Rab11 as being important for the SG size increase, and both Rabs are shown to localize to SGs. Rab11 is localized to SGs during the entire maturation process from SG formation until release and is required to recruit Rab1, which only localizes to immature SGs. Finally, it is shown that Rab11 is required for SG exocytosis, acting upstream of actin recruitment in this process . Overall, the manuscript is clearly written, the data are convincing, and the work is significant, uncovering new roles for these Rab proteins in the SG maturation process. This work is expected to be of interest to people interested in secretory granule biogenesis, maturation, or exocytosis (in many systems, not limited to Drosophila glue granules), and to people more generally interested in the function of Rab proteins. Our major critique is that much of the data is qualitative or based on single images. Though the single images are generally convincing, the paper could be improved by better quantification of the data. We also suggest a few additional experiments that could enrich the paper and strengthen some of the conclusions. However, the key claims and conclusions of the paper are not dependent on any new experiments.

      Major comments:

      1. Much of the data is not quantified and many of the results are shown by single images. Specific examples follow with suggestions for improvement:

      a. Number of times experiments are replicated and number of animals should be specified in all figures. For example, in Figs 1C and 4C, the number of granules is provided, but it is<br /> unclear if these are all from a single animal (or salivary gland) or whether data from several animals (or glands) is lumped together. The way the data are presented, there is no way to assess the variation within and between animals, or within and between salivary glands. There are also no statistics for the Rab1 and Rab11 RNAi data shown in Fig 1C.

      b. Some panels present semi-quantitative data that do not have clear rationale for the different categories.

      Fig 2A provides categories for a protein present on “most” or “some” granules (+ or +/-), but it is unclear how these categories were assessed. Were granules counted? If so, it would be<br /> better to provide the quantitative data. If these were subjective assessments, this should be stated explicitly and it should be better described how the experiment was performed. Were experimenters blinded to the genotypes? It is also unclear what criteria were used to consider a protein “on” a granule -- did it need to show a halo all around the granule?

      Table S1 shows categories for a “strong” or “moderate” reduction in granule size, but criteria for assignment to these categories is not given, nor any quantitative sense of what a “strong”<br /> or “moderate” reduction represents. If granule sizes were measured, it would be better to provide the quantitative data. If subjective, more description of how assessments were made should be provided, as well as if experimenters were blinded, and how many experiments/animals/glands were scored. It is also unclear if granule size was scored at a single time point in this screen or at multiple times during the maturation process – this should be stated.

      c. Much of the data in the paper for protein localization on granules or protein colocalization is provided as single images. Though most of these images are convincing, there should be<br /> explicit description of how many times each experiment was repeated, and how many animals and glands scored.

      1. The model that the presence of Rab1 on immature SGs acts as a checkpoint to prevent<br /> the precocious release of these SGs is an interesting idea. However, there are no data to directly support this model other than the correlational observation that Rab1 leaves the granules before they would normally be released. It is fine to present the idea that Rab1 may act as a checkpoint on SG release, but it should be made clear that this is speculative at this point, and the conclusion should be toned down (e.g. in the Discussion: “Rab1 removal signals the completion of maturation”). Many other proteins have been described as being on immature SGs and then removed during maturation so Rab1 is not unique, and any of these could act as checkpoints of maturation or merely be markers of it. The statement in the Discussion that immature granules are not released during stimulation is not entirely correct –<br /> this depends on cell type, and immature secretory granules in some cell types have been shown to be released.

      If the authors wish to strengthen the conclusion that Rab1 acts as a checkpoint on release, we would suggest performing an experiment in which Rab1 removal from SGs is impaired and assess whether exocytosis is inhibited. Possible ways to do this would be to express a GTP-locked Rab1, use a mutant in a Rab1 GAP (if this GAP is known), or artificially tether Rab1 to SGs so that it can’t be removed. Alternatively, we would suggest toning down the conclusion.

      1. The data in Fig 1 convincingly show that Rab1 and Rab11 are required for the full increase in SG size during maturation. Interestingly, the terminal size of SGs in Rab1 and Rab11 appears to match the normal size of SGs at the 4-8 hr timepoint when SGs begin the second slower phase of SG growth. This suggests that Rab1 and Rab11 may be specifically deficient in this second growth phase, which would also be consistent with the observation that Rab1 only is found on SGs during this second phase. To assess this directly, a nice experiment would be to quantitatively assess SG size at all timepoints in Rab1 and Rab11 RNAi animals (as done in WT in Fig 1C) rather than just the final timepoint.

      2. The data in Fig 4 showing that Rab11 is required for normal Rab1 recruitment to SGs are convincing, but are based on only a single Rab11 RNAi line. This conclusion would be<br /> strengthened by showing the same effect using a second way to perturb Rab11 such as Rab11 dominant negative or a Rab11 hypomorphic mutant. Given that Rab1 is still localized to SGs to some extent in the Rab11 RNAi line, it is unclear if this reflects incomplete Rab11 knockdown or suggests that Rab1 localization is only partially dependent on Rab11. Stronger Rab11 perturbation might distinguish these possibilities.

      Minor comments:

      1. The conclusion that Rab11 recruits Rab1 to SGs could be bolstered by additional experiments, such as showing that Rab11 recruits a Rab1 GEF (if such a GEF is known). It would also be interesting to see whether a GTP-locked Rab1 mutant localizes to SGs independently of Rab11. Such experiments could enrich the paper, but are not considered<br /> necessary for the major conclusions.

      2. The authors state that Fig 5A and Movie 1 demonstrate that Rab11 is transferred from the granule to the plasma membrane during the fusion event. This movie does show that Rab11 is present on granules up to, and possibly through exocytosis. However, as there is no marker for the plasma membrane, it is not clear that Rab11 actually transfers between these two membranes. More imaging experiments demonstrating the overlap of Rab11 and a PM marker after exocytosis would be required to show this convincingly. Alternatively, we would suggest toning down the statement.

      3. It is unclear how directly Rab11 participates in SG exocytosis or if its defects are indirect and due to effects on other proteins that participate more directly. One experiment that<br /> might be interesting would be to perform live imaging of exocytosis in Rab11 RNAi or mutant animals and see if SGs approach the membrane, which might possibly indicate whether there are defects in SG tethering or docking. This experiment is not considered essential for the key conclusions of the paper.

      4. In Fig 5A, many of the SGs do not seem to have Rab11 on their membrane, as compared to Fig 2C.

      5. In Fig S5A, the granules look different from others shown elsewhere in the manuscript (e.g. Fig 2C). In Fig S5A, multiple separate mucin spots appear to be found within one SNAP-24<br /> labeled membrane instead of appearing as a contiguous blob of mucin occupying the entire granule interior.

      6. Though it is a minor point in the paper, colocalization of Rab1 and Rab11 with ER exit sites and Golgi in Fig S2 is hard to assess. This could be improved by quantification of<br /> colocalization and by using arrows to point out colocalization in the images, perhaps by zooming in.

      7. Given that Rab5 and Rab10 were identified as lower-confidence hits that may affect granule maturation, it might be worth pointing out that these two proteins were also identified in C. elegans in a screen for Rab proteins that affect neuronal dense-core vesicle secretion (Sasidharan et al. 2012, PMID: 23100538).

      8. In the discussion, there is the statement that “Our unpublished observations suggest that the mucins secreted from these small granules are abnormal.” These observations should be described. What evidence is there that the mucin secreted is abnormal?

      9. The title could be more specific. We would suggest something along the lines of: “Rab1 and Rab11 localize to secretory granules and function in granule maturation”

      10. What is the Golgi marker? It is just referred to as “Golgi-RFP.”

      Reviewed (and signed) by Michael Ailion and Amy Clippinger

    1. On 2021-03-31 21:51:46, user Brett Chrest wrote:

      Was it determined whether 5.5mM glucose concentrations reflect a fasted or "starved" state in the hepatic environment?

      The fact that DMEM culture media is used in comparison makes it hard to interpret the physiological relevance with regards to the in vitro data. <br /> https://www.nature.com/arti...

    1. On 2021-03-31 21:08:19, user Marcelo Lorenzo wrote:

      I am so happy to present this new paper by Jose and collab. We find a very interesting history for insect PPK receptors, including the characterization of important expansions in synanthropic species such as Blatella germanica, Musca domestica or Culex quinx. New targets for functional genetics and control tool development!

    1. On 2021-03-31 21:04:34, user Dr. Gener wrote:

      I remember reading that bisulfite conversion wasn’t great with circular DNA. Y’all could try looking at this mtDNA with ONT as orthogonal validation.

    1. On 2021-03-31 12:29:57, user Knut M. Wittkowski wrote:

      In their extensive modelling of the evolution of SARS-CoV-2, the authors have not given enough consideration to the fact that a single mutation rarely results in immune evasion. For a virus to escape a polyclonal human immune response, several mutations need to happen and selected for in succession. This increases the time needed for immune escape to happen and, thus, needs to be considered before drawing conclusions - without direct evidence in the data and without references to the ongoing discussion in the scientific literature - about the effect of "lockdowns proven across many nations to be the most effective defense mechanism ... to contain the pandemic".

    1. On 2021-03-30 17:58:07, user Maria Log wrote:

      "Sequence data has been deposited into the Sequence Read Archive (SRA) under BioProject accession number PRJNA529876" - Am I the only one who noticed that only Illumina data are available under this accession number?

    1. On 2021-03-30 14:24:35, user Martial Marbouty wrote:

      interesting Work !!! However you have used an old version of MetaTOR and you have not performed the recursive procedure ... that why the results are so bad for MetaTOR

    1. On 2021-03-29 19:30:31, user PaleFlesh wrote:

      Interesting study. However I am concerned with the usefullness of these findings since only two species were tested, which is too small of a number to definitively say these findings are universal. It would be interesting to see if these results could be replicated with trees, grains, or even algae.

    2. On 2021-03-20 21:58:26, user Critical Dissection wrote:

      Interesting work! Would it be possible to train the classifier to diagnose the plant's condition not just on the number of sounds, but on the frequency (kHz) and intensity as well? I assume there would be substantial overlap in the number of sounds plants emit if more treatment conditions, species, and individual plants are added, potentially decreasing the accuracy of the classifier significantly. Training the classifier on multiple parameters may help maintain this accuracy.

    1. On 2021-03-28 01:08:30, user Remy Lau wrote:

      I'm a little bit confused by the loss function. Specifically, shouldn't equation (1) be maximized instead of minimized in order to have the final embedding so that nodes connected in the ontologies are closer together in the embedding space? Since if u, v are close, then d(u,v) is closer to zero, making the numerator large (closer to 1), as opposed to d(u,v) large, making the numerator closer to 0.<br /> I also checked the original Poicare Embedding paper (Nickel and Kiela, 2017) and they said the same thing, so it should not be a typo. But I'm still pretty confused by it.

    1. On 2021-03-27 16:19:31, user Charles Sanders wrote:

      The final version of this article is now published with a slightly different title:<br /> Disease-linked super-trafficking of a potassium channel.<br /> Huang H, Chamness LM, Vanoye CG, Kuenze G, Meiler J, George AL Jr, Schlebach JP, Sanders CR. J Biol Chem. 2021 Feb 15:100423. doi: 10.1016/j.jbc.2021.100423.

    1. On 2021-03-27 11:35:52, user Saaidi wrote:

      In our recent publication (sci rep 2020, https://www.nature.com/arti..., we reported other transformation products containing a sulfur atom. Another team also gave an oral communication on them at the conference dedicated to chlordecone in 2019 reporting their presence in their microcosm experiments. These compounds are not detectable by LC-MS technique. They are best formed in a closed atmosphere, like the one you usually work with. If you want to make a full assessment of chlordecone fate, I encourage you to look for these compounds as well. I can offer you to analyze your samples and detect them.

    2. On 2021-03-27 11:27:39, user Saaidi wrote:

      Hello, this work is very promising! The lack of commercial standards for chlorinated and non-chlorinated carboxyindenes is an important limitation to go further. I can offer to help with the analysis to confirm the carboxyindene assignment and determine the exact position of the carboxy group on it. There are indirect methods that we have already used.

    1. On 2021-03-26 16:19:15, user UAB BPJC wrote:

      Hello! This week our Bacterial Pathogenesis Journal Club (@UAB) discussed your pre-print and wanted to contact you in regard to our review. First, I would like to include the disclaimer that we are all bacteriologists, though some have molecular insights, so our thoughts may not line up with your team’s. On that note, it was a little difficult for us to understand the story at times. Some wordiness, along with an unclear explanation of data took away from the overall message. For instance, on page 20, 5 different figures were mentioned in a single paragraph, which made it difficult to digest. This was repeated periodically within the text.

      I must commend you for the well-thought-out storyline, as your timeline of experiments made sense with the results you described in the previous figures. Similarly, I highly appreciated your consistency in experimental design and representation, as it made each figure easier and easier to understand. Though, we did have some issues with how your data was represented. Many of us thought your data was overprocessed and could be represented in a much simpler fashion. Our most notable concern was with the violin plots. We were unsure of the rate being measured. Was it the instantaneous rate or overall? If overall measurement, we do not agree with the methodology used, as it allows for a large diversity in the measurements over time. As disclaimed previously, we do not align much with your field of expertise and are not sure if this is a common representative method for your denomination; however, we felt that representing the population, rather than the median or average, could be misleading, and would have much preferred a simple bar graph. Additionally, our group was not in favor of the microscopy used, as it had not been gated to disinclude the background. So we are slightly apprehensive to accept those figures.

      Personally, I would have preferred the inclusion of more p-values within the text. As I felt uneasy accepting fold-changes that did not properly represent significance – though I am aware it was represented in the figures themselves. Lastly, we did have some issues with the design of the figures themselves. Specifically with figures 1C, 2A, and 2B. In 1A, CK666 and the combinatorial are labeled the same. Were it not for its discussion in the literature I would not have been able to decipher which mapping represented which condition. Additionally, with figure 1A and related figures, we were not fans of the green color theme and thought more variety of colors should be used to further distinguish the conditions. For figures 2A and 2B, there were inconsistencies in the labeling, wherein 2A CK666 was represented with a green square and SMIFH2 a blue triangle, but in 2B CK666 was represented with a blue triangle and SMIFH2 with a green square. This inconsistent labeling, especially with figures of such close relation, could lead to misunderstandings with the data, should one not pay enough attention, and we, therefore, suggest it be fixed prior to publication. Overall, I very much enjoyed the story you tried to tell, however, we felt as though the improper representation of the data skews our perspective of the results and made us apprehensive to accept them. Thus, we have supplied you with a few suggestions for edits. I would like to mention that I was very appreciative of your final figure, as it helped wrap the concepts discussed well. Few people do this, so I was very pleased.

    1. On 2021-03-26 10:59:08, user Motoyuki Hattori wrote:

      Published: 19 March 2021

      Fluorescence-detection size-exclusion chromatography utilizing nanobody technology for expression screening of membrane proteins

      Communications Biology volume 4, Article number: 366 (2021)

    1. On 2021-03-26 10:37:03, user Karaj Khosla wrote:

      Pioneer search engine for #singlecell epigenome profile with large <br /> reference of singlecell transcriptome and epigenome. Applicable for

      analysis of singlecell open-chromatin and some scChIP-seq #data.

      genome # @bxv_genomics @epigen_papers @scell_papers @scRNAtools

    1. On 2021-03-26 10:35:44, user ISFMI wrote:

      The authors state that ‘Despite the significant potential, there are currently no fire management-based carbon projects in Africa. Identifying priority pilot projects will be a key part of moving forward.’ In this regard, we would like to note the work of the International Savanna Fire Management Initiative (www.isfmi.org) in Botswana, where in a project funded by the Australian Government and with the support of the Government of Botswana, Australian scientists, community development and regulatory specialists have been working with local community trusts since 2018 as part of a pilot fire management emissions reductions program in the north of the country. This project has resulted in peer reviewed findings, soon to be published in the Journal of Environmental Management, establishing the applicability of Australian style fire management emissions reductions methodologies in these landscapes. The ISFMI continues to work with these communities to put in place the necessary enabling conditions for such community based fire management activities in Botswana so as to be able to generate saleable credits in coming years, and also has the endorsement of several other governments in Southern Africa to undertake similar activities across the region with the anticipated support of the Green Climate Fund from 2021 on.

    1. On 2021-03-26 09:44:42, user Eric Kuhnert wrote:

      Amazing tool. Exactly what I was looking for especially since MultiGeneBlast is not supported anymore. Looking forward to the final publication so that I can cite it properly.

    1. On 2021-03-26 09:24:57, user Tijawi wrote:

      Fascinating stuff, need to read through again. Note that UBP9 is now class Xenobia. Also, I hate to be pedantic, but be sure to check that the names of your nereid-based taxa are correctly combined: Eudoromicrobium, Autonoimicrobium, and Amphithoimicrobium.

    1. On 2021-03-26 07:44:31, user Jorg Tost wrote:

      Please note, that the annotation files have been updated to the latest genome versions for the rhesus macaque in the final published version in Epigenomics. The article published in Epigenomcis is freely available.

    1. On 2021-03-25 22:25:59, user David Glover wrote:

      OK, let’s set that aside ….although, my understanding of gastrulation in mammals is that cells ingress from the epiblast at the primitive streak, and thereby undergo an EMT, and so form the three germ layers from what was previously two cell layers of epiblast and visceral endoderm/hypoblast. <br /> I was specifically referring to your paragraph concluding “Furthermore, there is no evidence for an amnion and one cannot have an amniotic cavity without an amnion.” <br /> In both mouse and human embryos, the first post-implantation event of the epiblast is its formation of a rosette that undergoes lumenogenesis as described in human embryos by Shahbazi and colleagues (Nature Cell Biology 2016 18:700-708 and Nature. 2017 552:239-243.). In human embryos, this lumen becomes the amniotic cavity. It effectively separates the epiblast into two parts of pluripotent cells; the part abutting the hypoblast will become the embryo proper and the other part, the amnion. In my opinion, one cannot have an amnion without an amniotic cavity. Perhaps this is also the opinion of the authors.<br /> It seems, though, that each of these three human blastoid systems has its shortcomings but nevertheless, they are, in fact, quite similar and a remarkable proof of concept.

    2. On 2021-03-16 04:15:35, user David Glover wrote:

      Correct terminology is very important. Others have named structures as gastruloids and yet there is no EMT and so no gastrulation; one cannot have a gastruloid without gastrulation.<br /> David Glover

    3. On 2021-03-14 23:13:50, user Alfonso Martinez Arias wrote:

      This is a very good attempt to recapitulate the early stages of human development from human Embryonic Stem Cells (hESCs). However, the manuscript is not clear in certain places and raises a number of questions that I summarize below by way of helping the authors and contribute to the discussion of this important research topic.

      On page 3, it would be good to know if they use an agonist or an antagonist of Wnt signalling; CHIR is an agonist and not an antagonist as stated.

      On the same page the authors state that they ‘consistently observed the emergence of cavitated cystic structures” and yet, in the methods section they state “Following completion of any given aggregation experiment (from day 4 to 6), all cystic structures those clearly displaying a cavity were included in further analyses. Non-cavitated structures were excluded from downstream analyses”. What is the<br /> frequency of the occurrence of cavitation? How is ‘clearly displaying a cavity’ decided?

      It is not at all clear whether the structures resulting from the unsupervised aggregation, in particular those selected for<br /> further study, have any Primitive endoderm/hypoblast. Along the same lines, it would be good to show a comparison of their blastocyst-like structures with ‘natural’ blastocysts to ascertain how similar they are. A comparison with images from published studies (see e.g PMID: 20123909 and PMID: 22079695) suggests that there are substantial, maybe significant, differences,

      It would also be helpful to clarify whether the structures express Sox17 or not, as there seem to be contradictory statements: “we found that<br /> the expression of the core Hypo lineage determinant genes, PDGFRA and GATA6, was highly enriched in cystic structures although SOX17 did not follow this trend (Fig. 3a). In order to confirm these results spatially and on a protein level, we performed immunofluorescence analysis with well-known lineage markers. In accord with the qRT-PCR results, we observed enrichment for KRT18 in the outside TE-like layer, and expression of OCT4/SOX17 in the Epi/Hypo-like inner compartment (Fig. 3b)”. Is Sox17 expressed or not?and, if it is expressed, how often and with what variability in pattern?. Again, a comparison with a human blastocyst would be helpful as contrasting figure 3B with published images of natural blastocysts suggests that these structures have different arrangements.

      In the same paragraph we are told that “At later time-points in culture (D6), some structures maintained GATA3 expression in the TE-like outside layer”. By now the issue of numbers becomes very important if<br /> this is to be a useful experimental system. How many of the initial aggregates cavitate? How many of these exhibit the three lineages by, say, D6? Of those with the three lineages, what is the organization of their Primitive Endoderm/hypoblast in the structure? The manuscript has an inconsistent and variable use of markers which makes it difficult to assess the relationship of these structures to the normal blastocyst.

      The experiment to test the further developmental potential of the hESC derived structures is a good one but the results are not very hopeful, at least in what is shown. A comparison of the images from Figure 4 from those of the structures generated in ref 15, and also other published<br /> similar experiments, show that after plating, the structures appear not to proliferate (have very few cells) and lack the organization of an embryo. There is no proper assessment of markers nor a comparison with a conceptus under the same conditions,

      Importantly, there is no evidence for an amniotic cavity. What the<br /> authors call amniotic cavity is, most likely, a response of epithelial cells to the culture conditions as it is well known that under conditions that provide a matrix or a substrate of sorts, hESCs will form cysts similar to those shown here (see e,g PMID: 26626176). Furthermore, there is no evidence for an amnion and one cannot have an amniotic cavity without an amnion.

      On these basis, the drawings in Fig 4A are not accurate as they represent a structure with more organization and numbers of cells than what the experiment produces (compare with Figures 4D and E). It might be a good idea to draw a more accurate representation of the experiment.

      On the basis of the evidence shown, while the structures shown here resulting from the aggregation of hESCs bear some features of a human blastocyst, there is no evidence to suggest that they resemble one; at least in my opinion. These differences increase with the culture time and are manifest afetr D6. Neverthelss, it is good progress towards the development of such structures in vitro.

    1. On 2021-03-25 21:39:56, user Madeline Ho wrote:

      Hi Dr. Alkhatib et al.,

      My name is Madeline and I was part of the group that chose your paper to look at for our Journal Club seminar. As 2 of us are involved with cancer research in our respective labs at UCLA, we wanted to look at a cancer research paper for the seminar. Your paper immediately caught our eye, and we all found it incredibly interesting.<br /> As my groupmates have already posted our constructive criticisms for the paper, I’d like to highlight the aspects of the research we were drawn to as you move forward with your research. The science behind the paper on TNBC was really intriguing and well thought out. The novelty and use of single cell surprisal analysis was well defended in the context of TNBC. Using both murine and human models in your experiments also bolstered the research and the proposition for using personalized, targeted drug therapy in addition to radiotherapy in TNBC treatment. Additionally, the various pictorial diagrams connecting the different models and the workflow were extremely helpful in understanding the experimental process. I found myself constantly going back to these figures whenever I got confused. Overall, your findings in regards to the heterogeneity of the TNBC tumor and the application of targeted treatment were exciting and I look forward to the day this research can be applied at a clinical level.

      Thank you!

    1. On 2021-03-25 21:31:09, user Sophia wrote:

      Something you might want to keep in mind: it is not logical to compare this algorithm to Seurat 3 because Seurat 3 is not intended for deconvolving mixtures, rather it provides cell type enrichment scores to "deconvolve" capture spots. Is seems as though you used their integration feature (which leverages the MNN-classifier) to evaluate its performance (given how the R^2 value is); the intended use of this integration feature is to integrate two single-cell resolution datasets (e.g. scRNA-seq and MERFISH), not for trying to align a mixture to a single scRNA-seq cell type.

    1. On 2021-03-25 14:02:08, user Magnus Kjaergaard wrote:

      Response to eLife reviewer 3. Our answer in italics.

      Reviewer #3 (General assessment and major comments (Required)):

      In this manuscript by Hansen et al., the authors describe three low (3.0 to 4.0 Å) resolution crystal structures of Ca2+-ATPase from Listeria, a gram positive bacterium. Two are crystal structures of wild type protein with B eF3- and AlF4- in the absence of Ca2+, thus, likely to represent the E2P ground state and E2~P transition state. The third one is a structure of a G4 mutant, in which 4 Gly residues are inserted into the A-domain -M1 linker, with BeF3- and Ca2+-present in crystallisation, designed to capture the E2P[Ca2+] state. Authors state, however, the three structures are virtually the same and that the E2·BeF3- crystal structure represents a state just prior to ("primed for") dephosphorylation. They also propose that proton counter transport "mechanism" is different from that of SERCA.

      ===== <br /> As Listeria Ca2+-ATPase has been studied by a single molecule FRET, its crystal structures will certainly contribute to our understanding of ion pumping. Furthermore, different from SERCA, Listeria Ca2+-ATPase transports only one Ca2+ per ATP hydrolysed. Therefore, how site I is managed is an interesting topic, although lets not forget the same 1:1 stoichiometry is observed with plasma membrane Ca2+-ATPase (PMCA), for which an EM structure appeared in 2018 (ref. 9). The authors indeed find that the Arg795 side chain extends into binding site I. This part is solid and a more elaborate (and interesting) discussion could be made than what is currently described.

      Another solid finding is that the two E2·BeF3- crystal structures are similar to the E2·AlF4- crystal structure, although how similar is unclear as a structural superimposition reporting an RMSD is not provided and the presented figure makes it difficult to judge directly; the structures are viewed from almost one direction, which makes it unfeasible to discern the differences in M1 and M2 and in the horizontal rotation of the A-domain. Two or three structures are superimposed, but with cylinders and again viewed from only one direction. As the authors designate that the structures represent H+ occluded states, it is important to clearly show the extracellular gate is really closed to H+ (not only to Ca2+ as well). For completeness, they should also examine the effect of crystal packing on the A-domain position. <br /> A new view of the structures after a 90-degree rotation has been added to Figure S2 and 6 to make it easier to judge domain orientation. Additionally, we have added a new supplementary table S2 containing RMSDs for pairwise alignments of LMCA1 and SERCA structure.<br /> A new supplementary figure S3 has been added, which shows crystal packing of the A domain in the three structures. The packing differs between G4 and WT structures. As the contacts are on the outer surface of the headpiece, we think it is unlikely that they affect any of the structural interpretation in the manuscript, but we have added the following sentence to the discussion of the headpiece orientation: <br /> “The A domain makes different crystal contacts in WT and G4 structures (Figure S3), so changes in the domain orientation should be interpreted with caution. “

      With regard to the point that the E2·BeF3- structure is "primed for dephosphorylation", only Fig. 2 (now Figure 3) is shown, in which differences appear to be the path of the TGES loop and the orientation of the Glu167/183 side chain. Their atomic models show that there is a plenty of space for the Glu167 sidechain to take an orientation similar to that of Glu183 in SERCA. The authors should, however, provide an omit annealed Fo-Fc map for the Glu167 side chain and explain why that is the preferred and only orientation. If a Glu side chain is free to move, it could adopt in less than a nanosecond a different orientation. If it does, then the difference in the orientation of the Glu side chain does not sufficiently explain "the rapid dephosphorylation observed in single-molecule studies". The authors place further emphasis on proton occlusion and countertransport. However, this part of the manuscript is more speculative and, as detailed later should, at least, be entirely moved to the Discussion section.

      We have added a new supplementary Figure S5 showing an omit annealed Fo-Fc map for Glu167. This shows that the side chain has the preferred location that we discuss. We would like to clarify that the pre-organization of the catalytic side is not merely a question of the rotamer of the side chain of Glu167, but also requires the TGES loop to break interactions to reorganize its backbone structure. This can be seen e.g. in Figure 3C. <br /> Proton occlusion and counter-transport will be addressed below.

      ===== <br /> As mentioned, the authors place a larger emphasis on proton countertransport. Here a number of issues show up. First of all, I think they have frequently used the term "occlusion" improperly. From my understanding, occlusion of a site (or ion) means that the site (or ion) is inaccessible from either side of the membrane. This means more than closure of the gates, as the two gates have to stay closed for a substantial length of time (i.e. locked). It is experimentally well established with SERCA that Ca2+ ions are occluded in E1P species. It can be shown that the lumenal gate is closed for Ca2+ in the E2 state. However, that does not necessarily mean that the gate for *H+* is also closed. As far as this reviewer knows, nobody has actually demonstrated that H+ is occluded, even in the E2 state of SERCA.

      Furthermore, the authors presume that protons enter the binding sites through a different pathway from that used for Ca2+ release, citing ref 26. However, if it does, can closure of the gate for Ca2+ really mean closure for the gate for H+? This seems a contradictorily statement as the authors designate that the E2·BeF3- state in Listeria Ca2+-ATPase as a proton occluded state (p.12). Apparent closure of the gate for Ca2+ on the extracellular side in a crystal structure seems insufficient for such a statement. One must keep in mind that a crystal structure merely provides a possible conformation in that particular state. It may not, however, represent the most populated conformation for that state. It is equally plausible that the E2·BeF3- complex takes a closed conformation for only a small fraction of the time. At this resolution it is simply not possible to determine if H+ occupies the binding site in the crystal structure. Furthermore, although it may be possible to show the gate is closed for Ca2+, it would be very difficult to show the gate is closed for H+. Thus, more experimental evidence is required to support that the structure represents a H+ *occluded* state.

      The authors write in the Abstract "Structures with BeF3- mimicking a phosphoenzyme state reveal a closed state, which is intermediate of the outward-open E2P and the proton-occluded E2-P* conformations known for SERCA". In essence this statement is fine, although what "closed" means is still unclear to me. In Figure 1 (now Figure 2), the authors state that "LMCA1 structures adopt proton-occluded E2 states". This statement is a bit misleading, because, in E2·BeF3-, the lumenal (extracellular) gate can in fact be opened and closed, at least with SERCA. As the authors recognize (p.14), the BeF3- complex of SERCA can be crystallised in two conformations, one with the lumenal gate is closed (with thapsigargin) and the other with the gate open; yet, they write "In SERCA, the calcium-free BeF3 -complex adopts an outward-open E2P state,..." p.8). This is for lumenal (extracellular) Ca2+, not for H+. Further evidence is required to establish that the extracellular gate of LMCA1 is fixed in a closed position for H+ in E2·BeF3-. Again more experimental evidence is required to support that E2·BeF3- is a H+ occluded state.

      The underlying challenge is that it is incredible difficult to demonstrate proton occlusion experimentally: The protons are invisible in most crystal structures and experimental variation of the H+ concentration affects many parts of the molecule. This means that it is not possible to get the same level of evidence for occlusion as for e.g. Ca2+, and as the reviewer states this has also not been achieved for other pumps.

      This does not mean that it is impossible to deduce information about protonation states and H+ pathways from a crystal structure. A buried side chain is thus unlikely to be charged unless it is paired with a neutralizing charge, and we can thus reasonably deduce protonation states from structure-driven pKa prediction. Second, it is known from functional studies that LMCA1 and other Ca2+-ATPases counter-transport protons, so some of the transport site residues must be protonated. We think it is reasonable to interpret the crystal structure in terms of the most likely residues involved in proton counter-transport. <br /> We agree with reviewer #3 that the crystal structure only represent a single (likely highly populated) conformation. However, this criticism is equally true of any other crystal or cryoEM structure, and does not prevent such structures from being useful. It is tricky to precisely map proton access as they can be relayed via protonatable residues, i.e. “proton wires”. It is unlikely that any experimental method would unambiguously probe proton accessibility, and molecular dynamics would be unlikely to be conclusive due to the coupling between dynamics and protonation state. As absolute proton occlusion is difficult to demonstrate, we think it is more useful to think in terms of relative rates of proton exchange. All other things being equal, a residue that is fully exposed to the solvent will exchange protons more rapidly than a residue that relies on proton relaying or breathing motions in a protein. In this context, it is reasonable to consider this state a proton occluded-state.

      To reflect this, we have edited the manuscript as follows:<br /> We have edited the “Results” section so it focuses on the immediate structural interpretation, i.e. pKa prediction and comparison of ion pathways. Discussion of the mechanisms that strays from the immediate structural interpretation has been moved to the “Discussion” section as proposed. The section headers have been updated to reflect this so now they discuss “Ion pathways and binding sites” and “Transport site protonation” rather than the “Mechanism of proton counter-transport”. Overall, we have softened the language describing proton occlusion to reflect that this is our best current interpretation and not established fact. Furthermore, we have qualified the statement about what a proton occluded state is:

      “It should be noted that occlusion has a slightly different meaning for protons than e.g. Ca2+, as it is difficult to experimentally demonstrate proton occlusion. Furthermore, a crystal structure only provide a single snapshot of a protein and it is likely that protein dynamics will allow proton access to a certain extent. In the following, we describe a state as proton occluded, if it the ion binding site is closed to direct solvent access”

      The authors write that "SERCA has two proposed proton pathways: a luminal entry pathway [26] and a C-terminal cytosolic release pathway [27] (p. 9). One has to be careful here, as the luminal entry pathway has not been experimentally confirmed in SERCA. The authors write that "The luminal proton pathway has been mapped to a narrow water channel ... [26]. But since the pathway is not confirmed in SERCA I don't think it can be used to justify that the corresponding part of LMCA1 is mainly hydrophobic and that protons cannot enter through this pathway.

      As discussed above, experimental confirmation of a proton pathway is really tricky, but the structural comparison of the different residues in this region is unambiguous. We think it is reasonable to keep this comparison in the manuscript, but have rephrased the it to the “proposed” luminal proton pathway, and rephrased to remove the word “mapped”, which suggests experimental verification.

      The description on the exit pathway for H+ also needs clarification. They describe (p. 10; first line) "In SERCA it consists of a hydrated cavity...[27]. ... M7 in LMCA1 further blocks the pathway ... and LMCA1 therefore does not appear to have a C-terminal cytosolic pathway either" and rationalize that "This may explain why no distinct proton pathways are required in LMCA1". I think it should be made clearer that this is a *proposal* rather than an established *fact*.

      This section has been re-phrased and merged into the discussion.

      As H+ release takes place in the E2 to E1 transition the authors state that the E2·BeF3- structure of LMCA1 is different from that of SERCA. However, I don't think they can confidently make such statements without E1 and E2 structures of LMCA1. Furthermore, these descriptions (discussion) should not be in the "Results" section. As they conclude that LMCA1 use the Ca2+ release pathway, which is assumed to be the same as that in SERCA (even though no Ca2+ release pathway is visualised in their crystal structures), for H+ entry, why does SERCA not use the same pathway? I think experimental evidence is required for a proposal that H+ binds to E309 from the cytoplasmic side.

      Proton release likely takes place in the E1 state, not the transitions. Getting a crystal structure of this state would be great, but falls outside the scope of a revision. We compare our crystal structures of LMCA1 to the E2 crystal structures of SERCA, and they are clearly more similar to the E2-AlF state (see new Table S2). This is a straight forward alignment of a protein to its closest homologue with an available structure, so we think it is fair to keep this in the “Results”.

      As this paper focus on LMCA1 and not SERCA, we think that both protonation of E309 and ion pathways in SERCA fall outside the scope of the manuscript except as a reference for LMCA1. However, as SERCA has additional pathways it will presumably be a question of kinetic competition.

      The issue of proton counter-transport is dealt with above.

      Additionally all the minor comments from reviewer #3 have been dealt with in the updated version 2 of the manuscript.

    2. On 2021-03-25 13:30:50, user Magnus Kjaergaard wrote:

      Response to eLife reviewer 1. Our answer in italics.

      Reviewer #1 (General assessment and major comments):

      Structural comparison is an important tool to understanding how proteins function at the molecular level. The mechanistic premise of obtaining LMCA1 structures from the gram-positive bacteria Listeria monocytogenes was to understand how Ca2+ pumps have different Ca2+ stoichometies to the mammalian SERCA and how they are proton coupled differently. Per molecule of ATP hydrolyzed, SERCA exports two Ca2+ ions in exchange for 2 or 3 protons, whereas LMCA1 exports a single Ca2+ and perhaps 1 proton in return.

      The paper describes two intermediate states of LMCA1 and from my understanding a mechanism is proposed based on structural differences in ionisable groups at the Ca2+ binding site, in particular the positioning of Arginine 795 that in SERCA is an glutamate. Since a previous crystal structure of LMCA1 was determined the new mechanistic insights rely heavily on the details achieved by the improved resolution. While this is technically an important achievement, just the assignment of side-chains in the current structures is not sufficient to reach the mechanistic conclusions reached and, as such, the current paper is unfortunately too preliminary. Proton-coupling pathways are mechanistically difficult to detangle and require extensive experimentation, such as ITC, mutagenesis and transport measurements as well as computational approaches. Indeed, ion or proton coupling pathways that alter energetics are rarely just

      the result from differences in a few residues. For example, glucose (GLUT) transporters are passive sugar transporters, whilst the bacterial counterparts are proton coupled. The proton coupling in the bacterial proteins is due to single aspartic acid residue in TM1. Whilst one can convert the bacterial sugar transporters to be no longer proton coupled by the mutagenesis of this TM1 residue to asparagine, you cannot make GLUT transporters proton coupled by mutating the corresponding asparagine residue to aspartic acid.

      For a paper in eLife one would have liked the authors to biochemically demonstrate how they could evolve LMCA1 to function similar to SERCA. This would have broader implications in our understanding of how biological systems can evolve substrate coupling and energetics.

      We appreciate that much more work could be done on this system, but as this is essentially an open-ended new project we also believe it lies outside the intended scope of the manuscript.

    1. On 2021-03-25 13:14:11, user eric brunet wrote:

      Hi,

      Another question about the increase in incidence of myocarditis. This element is not documented unless I am mistaken. On what data and criteria is this statement given?

      Sincerely

    2. On 2021-03-21 17:12:26, user Laurent Despeyroux wrote:

      Hi,

      The incidence rates presented on line 84 are inconstant : if the incidence for cats is 8.5% and 4.3% for dogs, the global incidence for "the rain" should be between 4.3% and 8.5% not the sum !

      BR.

    3. On 2021-03-20 13:58:36, user Jesse Baker wrote:

      The sentence on lines 65-66 might offer more precision if it read, “Multiple lines of evidence indicate that its enhanced transmissibility is driven by two amino acid changes in the Spike protein: substitution N501Y in the RBD and deletion Δ69/70 in the NTD.” This won’t matter to those following the virus’s evolution, but the RBD is considered to include roughly amino acids 330 to 530 while position 70, located elsewhere in the S1 subunit of Spike, doesn’t engage with ACE2 during viral entry.

    1. On 2021-03-25 09:30:16, user Florian Privé wrote:

      Two remarks:<br /> - It is "principal" components, not "principle"<br /> - PCR is not the same as "GWAS with PCs as covariates" at all

    1. On 2021-03-25 08:00:42, user Jian-Yu Jiao wrote:

      It looks that GTDB assigned them into one order, and Aggregatilinea lenta MO-CFX2 has already valid published as one order.

    1. On 2021-03-25 02:01:48, user Charles Warden wrote:

      Hi,

      Thank you for posting this preprint.

      If I look at the provided FPKM values for GSE113957, they are all small for NM_021804 (ACE2|ACEH|-|Xp22.2|protein-coding).

      I noticed a reference in the paper for downloading counts from GREIN, but I believe the values for ENSG00000130234 also tended to be small (mostly 0 and 1, with a maximum of 20).

      If I look in the GTEx portal, there are some tissues with low ACE2 expression, but others that I think would end up with higher counts than reported in this study? I think that is also similar to the ACE2 FPKM expression in various tissues from NCBI Gene with double digit FPKM values in some tissues and essentially 0 expression in other tissues.

      So, these are my questions:

      a) Can you reproduce your finding in other datasets / tissues?

      b) Is it possible that there might be some sort of confounding and/or not-optimal technical components?

      For example, I thought the scale for the Chen et al. 2020 paper using GTEx data looked noticeably different for ACE2?

      With the help of another individual, I think the Muus et al. 2021 paper might also provide references to some data that might be relevant (with both scRNA-Seq and bulk RNA-Seq).

      Best Wishes,<br /> Charles

    1. On 2021-03-24 21:14:53, user michael_in_adelaide wrote:

      Now in print in BMC Genomics under a slightly different title:

      Dong, Y., Newman, M., Pederson, S.M. et al. Transcriptome analyses of 7-day-old zebrafish larvae possessing a familial Alzheimer’s disease-like mutation in psen1 indicate effects on oxidative phosphorylation, ECM and MCM functions, and iron homeostasis. BMC Genomics 22, 211 (2021). https://doi.org/10.1186/s12...

    1. On 2021-03-24 18:20:31, user Alex Kondrashov wrote:

      Fig. 4a presents frequencies of heterozygous haplotypes (light blue) - which are impossible. Or I am missing something?

    1. On 2021-03-21 11:55:42, user Dave Gilbert wrote:

      Very proud of my student Dan for not settling for anything less than a method that actually works, is not cell type specific, doesn't require specialized equipment and doesn't strain the budget.

    1. On 2021-03-24 12:16:12, user Jerome Noailly wrote:

      This study has been published in its final form in Bioinformatics:

      Baumgartner, L., Reagh, J. J., González Ballester, M. A. & Noailly, J. Simulating intervertebral disc cell behaviour within 3D multifactorial environments. Bioinformatics (2020) doi:10.1093/bioinformatics/btaa939.

      https://academic.oup.com/bi...

    1. On 2021-03-24 10:33:51, user Edgar Simulundu wrote:

      Interesting work. Since the two countries are neighbors, is there a possibility of cross-border transmission of WNV in crocodiles between Zimbabwe and Zambia? It would have been great to compare the genomes detected in the two countries as some work was done in Zambia previously (Simulundu E, Ndashe K, Chambaro HM, et al. West Nile Virus in Farmed Crocodiles, Zambia, 2019. Emerg Infect Dis. 2020;26(4):811-814. doi:10.3201/eid2604.190954).

    1. On 2021-03-23 21:47:09, user Clara B Jones wrote:

      "Our data suggest that naked mole-rats show similar behavioural organisation to other cooperatively breeding vertebrates where involvement in different tasks is commonly positively correlated within individuals and that similarity to the obligatorily eusocial insects has been overemphasized." [Conclusions] ... after reading the above paper a second time, i think it is worthwhile making 2 additional, brief observations ... [1] in his 1992 AREnt paper on "division-of-labor" in social insects, Gene Robinson advances the idea that within-individual consistencies [sometimes referred to as, "behavioral syndromes" or "personality"] constitute a type of morphological specialization ... [2] whether or not we agree with the authors' assumptions, definitions, & conclusions/interpretations, their study has important implications for the evolution of complex sociality in mammals [as per Major Transitions approach], particularly, for the extent to which costly gestation, lactation, &, for many species, long periods of offspring development, inhibit the evolution of social complexity in the Class, particularly, the evolution of mechanisms allowing females to "decouple" Survival and Fecundity ...

    2. On 2021-03-23 00:06:38, user Clara B Jones wrote:

      ... thinking of Ants, all of which are classified, Eusocial [e.g., see Holldobler & Wilson 1990] ... [1] are we going to accept the distinction between "primitively" and "advanced" eusocial? ... [2] among ant species, traits are highly variable, for example, with re: presence or absence of "castes;" patterns of task, role, and/or morphological specialization; &/or "totipotency;" ... [3] however, "reproductive division-of-labor" is a universal ... [4] since Cooperatively Breeding taxa exhibit [a] "reproductive division-of-labor;" [b] 1 or a few "pure" breeders; and, [c] "helpers," can we classify "cooperative breeders," "primitively" eusocial? ... [5] social mole-rats exhibit "reproductive division-of-labor;" "pure" breeders; totipotency; "helpers" [role specialization]; and, unless i am mistaken, "temporal division-of-labor" ["age polyethism:" Damaraland mole-rats] and are, generally, classified, "primitively" eusocial [eusociality including "reproductive division-of-labor;" totipotency; but without (more or less) "sterile casts" and, usually, without morphological specialization] ... how does this new report deviate from a classification, "primitively" eusocial for social mole-rats or from the highly variable traits reported for Ants?

    1. On 2021-03-23 20:00:45, user Tom E Hamilton wrote:

      Why was xylitol used in the placebo? Is it just a great incedental Discovery that xylitol works so well? What were the test differences between untreated and placebo?

    1. On 2021-03-23 15:35:35, user Anchi Cheng wrote:

      Congratulation on completing a well-written manuscript. However, it is my duty to inform you that using low mag relative ice thickness to filter targets has been a feature in Leginon auto target finder since the original manuscript published in 2005(doi: 10.1016/j.jsb.2005.03.010). 2021 update only added the graph and math to correlate such values with the high-mag EF or ALS measurements. Best, Anchi Cheng

    1. On 2021-03-23 11:31:32, user POSE delenda est wrote:

      Way too much fantasy. Way too much juggling of figures. Not a single independent corroboration. Not a single critical contrast. ¿Who owns this publication?¿Who finances these "researches"?

    1. On 2021-03-22 22:22:39, user Anuradha Wickramarachchi wrote:

      Congratulations on your work.

      We would like to know if there is an implementation made available for this tool. Furthermore, could you clarify a bit more on the logistic regression classifier trained? Is it trained on k=3-7'mers or something else.

      Thanks in advance!

    1. On 2021-03-22 10:49:36, user caelum forder wrote:

      News articles are reporting this as the virus can't be killed at boiling temperature. The highest temperature they tested was 92C, and I find it very interesting that is the highest results they show. I feel like they omitted higher temperatures because it killed the virus very quickly and they wanted to make the research look meaningful. If you are reporting this paper, PLEASE do not refer to 92C as boiling water. People will think that boiled kettle water isn't safe, when in reality it will be hotter than 100C

    1. On 2021-03-22 02:24:35, user Nathan Hotaling wrote:

      Hello, I am having trouble accessing the EMIT Synapse data set. When I go to the link it says "Sorry, no access to this page. You are not authorized to access the page requested." I am logged into Synapse and can search for other papers/data. Please let me know what I am doing wrong!

    1. On 2021-03-21 13:53:24, user Vicent Pelechano wrote:

      Dear colleagues,

      I read with great interest your manuscript. Unfortunately, I fear that the main conclusion derived from your work might be a technical artifact associated to intrinsic biases of your method. In particular, the likely inclusion of untemplated C during the reverse transcription step. As all methods have biases, I would recommend performing control experiments with your own protocol using as input randomly fragmented RNAs. I am sure, that will help you better identifying the biases associated to TRESeq.

      I also found confusing your use of “cleavage sites” in your manuscript when in reality you are measuring the bulk of cap-less 5’RNA boundaries. And of course, we know that XRN1 mediated degradation is key to remove RNAs and controls its stability and abundance. In addition to checking our previous work, I would advise for example to check the nice paper from Harigaya and Parker (PNAS 2012). Using samples where one inhibits the 5’-3’ exonucleolitic decay would be more suitable to answer the question you ask.

      I normally do not comment publicly on preprints, but after reading your paper I felt with the obligation to do so. I hope you find my comments useful to improve your work

      Best regards,

      Vicent Pelechano, PhD<br /> http://pelechanolab.com/

    1. On 2021-03-21 13:27:01, user Anonymous wrote:

      Given the coincidence in timing between the emergence of the pandemic in late 2019 with the published separate episode of theorized Pneumonic Plague diagnosis in Beijing in early November 2019, investigation should be made of whether this Beijing incident was in fact the earliest but unrecognized incident of Covid19 human to human transmission. Please see this article: https://www.telegraphindia....

    1. On 2021-03-21 12:11:08, user Alina wrote:

      S. lineatus larvae feed on root nodules of pea. It could affect nitrogen content in plants and the mechanism of plant defense. Pea leaf weevils as a model of leaf-chewing herbivore in the experiment is OK, but maybe it is worth mentioning in Discussion part that the relation between S. lineatus and Pisum sativum is more complicated.

    1. On 2021-03-21 09:32:47, user shigeo_hayashi wrote:

      Congratulation on posting an interesting and very important work. I have a question on the PCR data presentation. In Fig. 1AB and S3, y axis of scattered plots are all labeled "log10 eqPFU per gram lung". I believe half of them reports the data from PCR and PFU as a unit of PCR quantity seems odd. I am also interested in knowing if infected mice release live virus from their system. Any information on analysis of saliva or airway? <br /> Thanks.

    1. On 2021-03-20 16:33:42, user Bahaifm Podcasts wrote:

      Outstaning research but the authors seem to miss the fact that this is a new Ontology, not just a taxonomic differentiation of Shannon taxa (see Dunn, Mathematical Taxonomy, p.111). -- Dr. Tommy Halstead

    1. On 2021-03-17 21:53:27, user Tex wrote:

      What was the dosage of the EPIDIOLEX administered for intervention group? From their site it seems that 10 mg/kg/day is the general recommended "standard dosing."

    1. On 2021-03-20 11:59:11, user Tim Fenton wrote:

      Really nice work - congratulations to all involved! I'm very interested in the lack of a skew towards YTCW or RTCW in the mutations seen in the viral genomes, while there is clearly a skew towards YTCW in the host genomes in HPV+ head and neck, and in cervical cancer. Do you think this is a 'real' lack of a skew or is it possible that even when doing the heroic job of sequencing viral genomes from over 5000 tumours, the overall number of TCW mutations is still a bit small to be confident about the YTCW:RTCW ratio? I'm putting together a review at the moment, so definitely planning to cite this work - do you have an idea of when it is likely to be published in final form?

    1. On 2021-03-19 17:44:20, user fischmidtlab wrote:

      Great study and important contribution! Quick remark: Our animals are not 'invariably culled' after a successful immunization campaign. After some resting time, they can be immunized again (also no need to cull them when they retire).

    1. On 2021-03-19 12:59:37, user reviwer 0 wrote:

      Interesting manuscript and very well executed science. I hope we can have a look at the models for ourselves soon.<br /> Without meaning to diminish the importance of the current work, it seems to me that conclusions about the role of the MTERF4-NSUN4 complex are largely consistent with those of a previous work by the Larsson group (PMID: 24516400), but this is not adequately reflected in the text. For example, while discussing the orientation of the active site of NSUN4, the authors “conclude” that "The active site of NSUN4 is positioned above h81... suggesting that NSUN4 does not methylate the 16S rRNA". It was, in fact, demonstrated that NSUN4 does not methylate 16S rRNA using bisulfite sequencing in the above mentioned paper. Later, on page 4, the authors conclude that their data “…also explain the dual-role of NSUN4 as a methyltransferase in mtSSU assembly and as a biogenesis factor in mtLSU maturation, as its N-terminal tail is not conserved in the homologous bacterial methyltransferase rsmB." It is not elaborated, and therefore unclear, how any of these data explain the role of NSUN4 as a methyltransferase or its dual role in general aside from suggesting a mechanism by which MTERF4-NSUN4 complex regulates late-stage mtLSU assembly. Moreover, the role of NSUN4-mediated methylation for mtSSU biogenesis has not been demonstrated nor explained by these data.

    1. On 2021-03-18 21:47:49, user Raghu Parthasarathy wrote:

      This looks useful, and I'm glad you found my work valuable! I strongly feel, though, that science doesn't need more acronyms (see e.g. here: https://elifesciences.org/a..., and simply combining my radial symmetry localization with FISH doesn't warrant a new term.

      Also, by the way, I generalized my algorithm to 3D many years ago, but never formally published it (https://pages.uoregon.edu/r.... Other people also made a 3D version, as noted in the link above. If you had contacted me, I'd have happily told you about this and saved you some work.

    1. On 2021-03-18 19:37:31, user Raidan wrote:

      Very interesting study. It has importance for how it might impact use of egg-grown reagents in testing & in interpreting PB clones from vaccinated people.<br /> Some of the questions: Were those IgG plasmablasts class switched B1 cells or what are they? & where do they class switch? <br /> -the nature of Ag or antigens inducing these Abs & location in vaccine? why are we sure it's only glycans since de-glycoslation doesn't reduce it a 100%<br /> -direct comparison to cell culture-based vaccines induced Abs in terms of level of HA-specific mAB (were there reeduced level in neutralization compared to these non-egg grown vaccines).

    1. On 2021-03-18 18:45:07, user John Carlson wrote:

      Great work, great to know there is some protection from reinfection from Covid. I assume that there is still an unknown with variant Covid strains. Thanks

    1. On 2021-03-18 08:38:33, user Joshua B Benoit wrote:

      Sorry for the delay in the response. The paper was posted for a grant panel and has now been published in Scientific Reports. These question came while the paper was under revision (so I missed them). and I only saw them this week. <br /> Vosshall questions:<br /> 1. We use a double distilled water and hold the mosquitoes within custom built desiccator to keep near 100% RH.<br /> 2. The peaks for dehydration corresponds with the increased nighttime period (usually when most active), but the impact of dehydration is so high that it washes out the spontaneous activity difference. <br /> 3. There is a high level of correlation. The significant increase in activity starts at near a 10% water loss.<br /> 4. Likely no, which was recently confirmed by Fikrig et al. Increase sugar feeding was seen in the field with a higher saturation deficit. https://journals.plos.org/p.... We have new experiments running on this right now, and the impact seems to be species-specific. <br /> 5. These experiments are currently running in the lab as part of another project, which should be complete in summer 2021.<br /> 6. Yes, but due to cost and time, we did not include. Mainly, as if we waited, the transient knockdown was reduced and represented a partial control. <br /> 7. Typo, should be at least 8, which we considered the minimum. <br /> 8. See the paper in Scientific Reports. Wet and dry refer to the prior field conditions. Mainly did it rain and was it warm. (Should be Figures S7 and S8). <br /> 9. I believe the model based the number on 1800-2000 in the US and that there was 10x more cases worldwide. In hindsight, an easier way to report would have been in increased potential cases setting the control as ). <br /> 10. We are not sure if males have similar phenotypes. <br /> 11. We have used live animals and observed the same phenotype in earlier preliminary studies.

    1. On 2021-03-18 06:53:46, user Michele Nunes wrote:

      Hello,<br /> A group of undergraduate students at UCLA had the pleasure of discussing this BioRxiv paper during one of our journal clubs. Many of us were fascinated by the background information on phosphodiesterase inhibitors in relation to lipid metabolism. However, since the background consists of all text, it was a bit difficult for some of us to truly understand the signaling pathway in regards to how natriuretic peptides, PPARα, and PDE9 were all related. We thought that including a visual aid such as a signaling map in the first figure or a visual summarizing the entire introduction would be helpful to engage readers who are not as familiar with the field.

      Specifically, in the liver photos (Figure 1f), some of us found it difficult to distinguish a change in size between the placebo and PDE9-I group solely based on the images. We thought that including a line with a known measurement or showing the livers in cylinders with weights attached would be a more helpful metric to justify the results.

      In addition, you state that these experiments were done in both OVX-female and male mice, but the only figure that includes both data is Figure 2g. The rest of the male mice data is pushed to supplementary. We were curious if there was a reason for only including a portion of male mice data? The ability to easily compare the data to OVX-female mice could bring to light important differences.

      Finally, one of my colleagues was quite interested in the notion of estrogen having a protective effect against cardiometabolic syndrome. They suggested a future rescuing experiment where if OVX-female mice with induced obesity-cardiometabolic syndrome were injected with estrogen, could estrogen reverse the effects? I thought this was a great suggestion for possible future research in this area.

      Thank you for your time!

    2. On 2021-03-17 00:35:55, user Cassandra Franco wrote:

      We recently discussed your paper in our journal club, and we wanted to share a few thoughts and questions.

      Overall, we would have liked to see more data from the male cohort of mice, as it brought up interesting conversations when it was included. We also felt that it might be beneficial to establish one method for indicating significance as it varied from figure to figure.

      Starting with Figure 1, we would like to see a quantification of the size change in the livers in Fig. 1F. While discussing Fig. 1G we wondered why there was such a large discrepancy in the movement of PDE9-I mice when compared to the placebo group. We felt that adding the control data for this experiment may alleviate this comment.

      For Figure 2, we thought it would be useful to include a signaling map to emphasize the relationship between PPARa and PDE9 as we felt this wasn’t intuitive. In Fig. 2D, we enjoyed the use of the volcano plot, as we felt it displayed the genes of interest clearly, but we were a bit curious how the cut-off for significance was determined. We thought it would be worthwhile to clarify how the cut-off was selected. For Fig. 2G, we felt that the significance symbols made the figure very busy.

      Lastly, we felt that Fig. 3C would have been better utilized in figure 4 as it relates more to the results found in figure 4.

      We’re looking forward to seeing more in the future!

    1. On 2021-03-18 06:36:59, user Anna Niewiadomska wrote:

      Hello. I have been looking at the sequences from H. Lannion (variant Breton dérivé du Clade 20C) and I noticed that they contain a mutation that disrupts the ORF7b start codon. I came across your paper as I was trying to figure out how that might affect pathology. You might be interested in taking a look... <br /> hCoV-19/France/IDF-HMN-21022230289/2021|EPI_ISL_1110211|2021-01-29<br /> hCoV-19/France/BRE-IPP04233/2021|EPI_ISL_1259297|2021<br /> hCoV-19/France/BRE-IPP03808/2021|EPI_ISL_1118892|2021-02-10<br /> hCoV-19/France/BRE-IPP03809/2021|EPI_ISL_1118893|2021-02-10<br /> hCoV-19/France/BRE-IPP03921/2021|EPI_ISL_1111064|2021-02-15<br /> hCoV-19/France/BRE-IPP04392/2021|EPI_ISL_1259307|2021-02-26<br /> hCoV-19/France/BRE-IPP04583/2021|EPI_ISL_1239370|2021-03-02<br /> hCoV-19/France/BRE-IPP04615/2021|EPI_ISL_1262772|2021-03-02

    1. On 2021-03-17 05:40:56, user Kipkemboi TELENGECH Paul wrote:

      Interesting findings!!!Were you able to observe the dsRNA profile of infected insects?Is the accumulation of the virus dsRNA sufficient to detect in native gel?

    1. On 2021-03-17 03:18:46, user Sam Kariuki wrote:

      CORRECTION on last sentence in abstract:<br /> The high rate of multidrug-resistant H58 S. Typhi, and the close phylogenetic relationships between carriers and controls, provides evidence for the role of carriers as a reservoir for the community spread of typhoid in this setting.

      Should read:<br /> The high rate of multidrug-resistant H58 S. Typhi, and the close phylogenetic relationships between cases and carriers, provides evidence for the role of carriers as a reservoir for the community spread of typhoid in this setting.

    1. On 2021-03-16 19:16:38, user Anandi Krishnan wrote:

      Posting here a unique context to this work that might be helpful for some:<br /> this preprint is the first and major culmination of a unique research re-entry award to A.K. by the NIH (specifically, the National Center for Advancing Translational Sciences, NCATS but also available from other institutes). The research re-entry awards are designed for those experiencing life-related interruptions to their careers – and for me, this work would not have been possible without this unique NIH mechanism (that has now facilitated a subsequent NIH/NHGRI career development award). Please visit this NIH link for details if interested in these diversity/re-entry supplement awards: https://ncats.nih.gov/ctsa/....<br /> More of the backstory here: https://twitter.com/anandi_...

    1. On 2021-03-16 15:52:48, user Magnus Hoffmann wrote:

      BEL-A2 cell lines were created by Professor Jan Frayne, Professor David Anstee and Dr Kongtana Trakarnsanga with funding from the Wellcome Trust (grant numbers 087430/Z/08 and 102610), NHS Blood and Transplant and Department of Health (England) and were kindly provided by Professor Frayne for this study.

    1. On 2021-03-16 15:30:48, user Rudolf A Roemer wrote:

      Excellent paper, just what I was waiting for to extend our own study on flexibility and mobility of SARS-CoV-2 proteins [Sci. Rep. 11, 4257 (2021), https://rdcu.be/cfvcQ] to the mutated spikes. I hope that the PDB structures will soon be released to general use. Do you have an estimate when this might be done?

    1. On 2021-03-16 11:51:23, user Clara Locher wrote:

      Following a report in Science Insider about our pre-print “Nepotistic' journals": a survey of biomedical journals”, Michelle Hoffman, VP Publishing American Dental Association raised some concerns about our methods.<br /> The Journal of the American Dental Association (JADA) has been identified as an outlier journal using one of the proposed metrics in the main analysis, the PPMP (percentage of publication by the most prolific author).<br /> Computation of the metrics was correct. But as Michelle Hoffman points, one author Romina Brignardello-Petersen authored 475 of 1475 articles, or roughly 33%, of articles published in JADA between 2015 and 2019. She also points that these papers were not submitted as original research articles subject to peer review. 'Rather, Brignardello-Petersen was the section editor responsible for producing the “Clinical Scans” feature that appeared in each issue of JADA during that period. Clinical Scans summarized articles in the professional literature other than JADA to keep JADA readers abreast of important advances in oral-health research.'<br /> First, we agree with Michelle Hoffman that this journal (and possibly others) is not a “nepotistic” journal and we are sorry that it seems presented as such in the Science news story. When reading the Science report, it is not stated that the journal is a “nepotistic journal” but that it was flagged as an outlier using the metrics we propose. The difference is important, but we can see how our analysis could be interpreted to create an unfairly negative impression of the journal, and we apologise for that. <br /> In our pre-print, we noted the potential for false positives from our method. In exploring a random sample of journals, we identified the problem pointed by Michelle Hoffman and explicitly state: “Among these 108 authors, this procedure also enabled identification of the 6 most prolific authors, who were professional journalists for whom high productivity is of course not an indicator of any academic misconduct, as they are professionals paid by the journal and not academics. The two proposed indicators, and their current calculation, should therefore not be used indiscriminately but could rather serve as a screening tool for potentially problematic journals that may then require careful exploration of their editorial practices.” We believe that it is explicit that our indicators should not be used indiscriminately, and we regret that it was done with little emphasis on this. In other words, PPMP alone should not be used to claim that a journal is a nepotistic journal. To be clear, the pre-print also states that “While our results are exploratory and do not yet support a widespread use of these indicators, we hope that further research will help to establish these easily computed indexes as a resource for publishers, authors, and indeed scientific committees involved in promotion and tenure, to screen for potentially biased journals needing further investigation.” After any screening using these indicators, it is needed to explore the journal in depth. In the case of JADA, there is no doubt that further exploration would have made it clear that there is no integrity problem.<br /> This case of JADA illustrates that the concurrent use of the proposed metrics (PPMP and Gini) computed for ‘all articles’ and for papers labelled as ‘journal articles’ should be more clearly discussed and may result in a reduction of false positives. Despite these efforts, we agree that the risk of being identified as an outlier journal whereas there are no questionable practices still exist and a careful look at the journal will be still necessary before claiming nepotism. We will make sure to discuss these points in depth.<br /> This paper is currently under peer review. In addition to the eventual feedback we will receive, we will clarify all these points in the next version and we sincerely thank Michelle Hoffman for raising these questions. We consider her response as a prepublication peer review and will consider all these points. We welcome additional feedback that could improve our research.

    1. On 2021-03-15 14:02:06, user James Krieger wrote:

      You need to remove or rename the Introduction section or add additional sections because your whole article isn't Introduction.

      Also, the sentence "Antibodies targeting the RBS-D, S309 and CR3022 sites are minimally or not involved in interactions with any of these three mutated residues (Figure 2A–B)" should not cite Figure 2B as this does not show these antibodies. Rather you should cite Supplementary Figure 2 here and possibly Figure 4B. I guess this reflects changes in the figure numbering that were missed.

      Likewise, the sentence about IGHV3–53/3–66 binding modes 1 and 2 should cite Figure 2C as well as 2B. You also need to mention the lower panels showing interactions as sticks.

      REGN10933 is an important antibody given its wide use therapeutically and should be given appropriate discussion. It should be mentioned with other RBS-A antibodies or better still in its own section rather than being tacked on the end of the paragraph beginning "A further group of antibodies target the back side of the RBS on the opposite side of the RBS ridge (called RBS-C)" where it doesn't fit.

      There is also no mention of RBS-D despite it being shown in Supplementary Figure 2 and including another therapeutic antibody REGN10987, which should also be discussed (this antibody is currently only mentioned in the methods). It should be given considerable emphasis that this antibody does not interact significantly with any of the residues in these variants and therefore remains a viable treatment option. Its combination with REGN10933 is also much less susceptible to RBD mutations according to deep mutational scans (Starr et al., Science 371:850-854).

      Likewise, Eli Lilly antibodies CB6 (LY-CoV016 / etesevimab) in RBS-A and LY-CoV555 (bamlanivimab) in RBS-B should be mentioned too as these are also being used therapeutically with the cocktail being approved recently. These have also been studied by deep mutational scans (Starr et al., BioRXiv preprint 10.1101/2021.02.17.431683). The former is very sensitive to mutations at K417 with all changes being highly deleterious while the latter is highly sensitive to mutations at E484 in line with your Supplmentary Figure 2, and again the cocktail is much less sensitive to mutations at these sites and more generally.

      You may also want to look at other variants and mutation sites such as L452R in the Californian variant, which the above-mentioned Starr et al. preprint shows to escape LY-CoV555.

    2. On 2021-03-15 12:03:20, user James Krieger wrote:

      Thank you for your nice paper.

      I just spotted that the last sentence of the caption to Figure 1B ("Numbers of RBD-targeting antibodies encoded by each IGHV gene is shown as black lines") is incorrect. These black lines are already described earlier in the legend as being the fold enrichment relative to baseline and they make sense with that.

      I hope that you have a chance to incorporate this and any other comments I or anyone else give during any revisions you make to this paper.

    1. On 2021-03-15 09:41:45, user Veigyabati wrote:

      Hi! I am interested to know why your propidium iodide stained as black instead of red. Dont you face any autoflouresence issue in M. abscessus biofilm? Which image of CLSM is the control?

    1. On 2021-03-15 09:25:36, user Remi wrote:

      Hello, may be a stupid question but, how the virus can change/mutate without a replication cycle? Because they use plasma, no cells are available for the virus to replicate. Does it mean these mutants ( E484K & F140) are already present from the beginning, all the other are neutralized but only them remain at the end?

    1. On 2021-03-14 05:57:58, user Aven Louis wrote:

      If u click on metrics tab for this article, u will see in yellow box at top of this page that it clearly states that these preliminary non peer reviewed reports should "...not...be reported in news media as established information."

      Yet despite this clear warning, the metrics show that 23 news outlets have still picked up on this article. Based on my media observations, I think it's highly likely that many have presented these studies as conclusive.

    2. On 2021-03-08 03:33:56, user Aven Louis wrote:

      How can the safety or efficacy studies done by these vaccine companies possibly be believed by critical thinking people when there have been no "peer reviewed studies" prior to testing on the general public?

      These vaccine makers will take billions of dollars experimenting on us before any of their mistakes or lies can be pointed out.

    1. On 2021-03-14 04:26:53, user Aripuanã Watanabe wrote:

      Dear Dr. Lopez-Rincon

      I hope you are well

      I performed an alignment test (MEGA software) with some of the primers described. There were few sequences analyzed, obtained from the GISAID database. Some sequences from Europe, USA and South America deposited in the first half of 2020.

      There was a complete alignment between the primers and these sequences. Apparently they were not of the 3 variants described (B.1.1.7, B.1.351 and P.1).

      I would like to ask if this type and analysis I performed is correct or if you would have any suggestions for another type of analysis?

      I ask because I am considering buying these primers for testing.

      Thank you very much

      Best Regards,

      Aripuana Watanabe

    1. On 2021-03-13 23:05:38, user William Muller wrote:

      Why would the letters questioning the CT values from reference 47 be cited, but not our reply to those letters that answers the question? Seems if the authors are going to question a result that may conflict with the story the paper is telling, they should be clear that there is an explanation for that concern.

    1. On 2021-03-12 15:32:20, user Simon Rasmussen wrote:

      Very interesting work and thanks for posting it on biorxiv.

      I have a couple of comments on your manuscript mainly on your comparison to the VAMB method (I am senior author on it):

      1. You compare your pipeline, which includes multiple refinement steps to Das Tool and metaWRAP pipelines - this is of course fine. However, you also compare it to a binning tool (VAMB)? Why would you not include VAMB into the binning step of your tool?

      2. The datasets you use are CAMI low (single sample of 15Gb), CAMI medium (two samples of 40Gb) and CAMI high (five samples of 75Gb). Unfortunately, these datasets are quite unrealistic (see Supplementary Figure 28 of the VAMB paper for details on CAMI high). It would be interesting to see how they perform on the toy benchmark datasets from CAMI2 (the data, taxonomy and benchmark-scripts available for download here https://codeocean.com/capsu....

      3. It would be interesting to compare performance of the pipelines on the (real) Aiding dataset using e.g. CheckM.

      4. How was the other methods run (DASTool, VAMB, metaWRAP)? In the supplementary it is indicated that VAMB was run with co-assembly and multi-split? The preferred mode when multiple samples are present is to run it using single-sample assemblies and then multi-split.

    1. On 2021-03-12 09:21:43, user David J. Pritchard wrote:

      Very cool! But quick note on the introduction in case you are still making changes: the birds relying on stereotyped routes to discriminate visual patterns (Dawkins & Woodington, 2000, lines 62-63) were chickens not pigeons. The other cited paper (Theunissan et al. 2017) is on pigeons but isn't about stereotyped routes, but rather the function of "stops" in the pigeon's approach, so I think you are referring to the chicken paper there.

    1. On 2021-03-12 09:13:57, user Kaja Kannike wrote:

      Very exciting model system to use, it definitely broadens the view! We are also studying TCF4 at Tallinn University of Technology in prof. Tõnis Timmusk's lab and therefore I'm wondering could you elaborate a bit on which TCF4 antibodies were used in ChIP of this study? <br /> TCF4 has a very complex gene structure and at least 18 N-terminally different protein isoforms can be translated. We have seen that TCF4B/C and TCF4A isoforms are indeed isoforms with the highest expression levels, however, the calculated and experimental molecular weights are 71 kDa and 54 kDa, respectively. The size of TCF4A, can be checked here: https://www.ncbi.nlm.nih.go.... There exist three TCF4 isoforms with greater molecular weight (namely TCF4K, J and L), though they seem to express only in testis (https://doi.org/10.1371/jou....

      Nevertheless the binding site you recovered from ChIP-Seq looks like an E-box and suitable for TCF4 and other bHLH facrors!

    1. On 2021-03-12 04:13:04, user Li Wu wrote:

      This paper has been published in PLoS Pathogengs in March 2021.

      Chen S, Kumar S, Espada CE, Tirumuru N, Cahill MP, Hu L, et al. (2021) N6-methyladenosine modification of HIV-1 RNA suppresses type-I interferon induction in differentiated monocytic cells and primary macrophages. PLoS Pathog 17(3): e1009421. https://doi.org/10.1371/jou...

    1. On 2021-03-11 14:26:33, user G.P wrote:

      Excellent paper. Just a question, how do you manage to get plasma membranes at 20.000 x g? It is a straightforward procedure or any precautions must be taken?

    1. On 2021-03-11 09:29:07, user Davide Bulgarelli wrote:

      Hi folks-just realised the title and abstract in the preview forms are not the up-to-date ones we have in the actual manuscript (blame the late night submission :)) We'll be fixing this by the end of the day!

    1. On 2021-03-11 06:58:58, user Elisabeth Janssen wrote:

      The article is now published peer-reviewed in Water Research - with several updates to the preprint version! https://doi.org/10.1016/j.w...<br /> It will be open access in just a few more day(s) until the license is online with the publishing office. PM me if you like to get the pre-proof version in the meantime.

      The dataset is already openly available: see link to Zenodo below: https://zenodo.org/record/4...

      Have fun!

    1. On 2021-03-10 20:05:11, user Joseph Ong wrote:

      Hadjikyriacou et al. present a novel method of drug screening across three different model research systems: Drosophila larva, C. elegans, and human cell culture (patient-derived fibroblasts). In particular, the authors devise a series of imaging-based assays to determine the effect of their library compounds against lysosomal disorders in these model systems with the goal of identifying novel drugs or drug targets against lysosomal disorders such as mucolipidosis type IV. More broadly, the authors claim that a multi-species method with the goal of identifying conserved biological pathways may lead to more viable treatment of diseases.

      The Drosophila system uses larva heterozygous or null for trmpl, an endolysosomal ion channel. In this system, trmpl-compromised pupae should not eclose and result in no living animals. Tracking movement (that is, of a properly hatched adult fly) within a 96-well plate informs whether or not a particular drug rescued the phenotype. For the C. elegans system, a strain with a mutation in cup-5, was used. The mutation resulted in the sequestering of GFP into specialized cells, so visualizing the relative area of green cells to the total cell body served as a measure of lysosomal storage disfunction. In a similar manner, the fibroblast system (with a mutation in TRMPL1) used the dye LysoTracker, and also assessed the total fluorescence signal from the dye (suggesting lysosome accumulation) as a readout of lysosomal storage disfunction.

      Screening small molecules (4,185 compounds targeting ~2000 mammalian genes) through this system, the authors find few small molecules that are "hits" among the different species: 3 between human and worm; 3 between human and fly; and 7 between fly and worm; with the addition of one compound shared among all three species [though what these drugs are is not clear; perhaps it is in the supplemental information that was not uploaded to bioRxiv]. Similarly, the shared gene targets of these drugs fell into four main categories: Cdk and Cdk-associated proteins (human and fly), nitric oxide synthesis (fly and worm), and Abl-kinase pathway proteins (human and worm). One gene, ILK, a kinase with diverse functions, was found to be a gene target of all three species. The Cdk and ILK targets were further validated via other chemical and genetic methods, and the authors conclude

      I found the multi-species approach delightfully insightful. As the authors point out, despite how similar humans and mice are, studies in humans have consistently failed to recapitulate the results seen in murine models. The approach, then, to cast a broader/wider net to analyze pathways broadly conserved between invertebrate and mammalian tissue culture seems appropriate. Of course, there is a great difference between flys/worms and humans, so care must be taken when interpreting and applying various results across species [but this is the same critique used when we analyze mouse models, so perhaps we should focus on this aspect of the approach as a novelty rather than a fault].

      However, the results of the screen were more confusing than what I would have hoped. While it is true that one target, ILK, was a target of all three systems, the Cdk and Cdk-associated proteins were only detected as "hits" within the human-fly collection and not within worms. While there may be many reasons for this discrepancy -- with species differences or using mammalian protein-targeting drugs in a worm being the most obvious -- this observation casts some doubt on the approach. Moreover, save for ILK, the targeted gene pathways between each species seemed to vary widely. Ideally, the most important pathways would have shown as "hits" across all the species tested; however, the pathways seem to have no obvious relationship to each other, except that they are all major signaling/growth pathways. Perhaps it is not surprising that the major hits are all broad signaling pathways -- but I would have hoped that this assay would have allowed convergence on a particular pathway.

      Together (that the gene pathways have poor correlation across species and that the Cdks were missed in worms), this suggests that a multi-species approach may be too wide/broad an approach -- particularly, given how well-conserved and well-studied the Cdk system is (and all the ink that has been spilled over palbociclib and its analogues). Perhaps more care in choosing model organisms (say, zebrafish instead of worms) may strengthen the screening approach and result in more physiologically relevant "hits" (as the zebrafish system might be closer to the human system such that the drugs tested may have a better efficacy in a vertebrate rather than worm system; and the "hit" pathways may more closely align with humans/fly in a vertebrate rather than worm system). Nonetheless, to the author's credit, I acknowledge that the Cdks were "hits" in both the human and Drosophila system and validated as targets in subsequent analysis. Perhaps I am too naive in believing that the Cdks should have been hits in all three systems tested -- that would make biology too easy.

      Briefer comments:<br /> There is no guarantee that the mammalian target of Drug A is actually Protein X in another organism; for example, while the authors assume that palbociclib is a Cdk4/6 inhibitor in mammalian cells, is palbo also a Cdk4/6 inhibitor in Drosophila and worms? Clarifying the protein targets of drugs in other species is particularly important to address off-target or gain-of-function-type effects of drugs.

      The decision to quantify the ratio of LC3-II (the lower band?) to LC3-I + LC3-II (lower + higher band?) is not clear to me. Also, in Figure 4A, marking the higher and lower band as LC3-I/-II would be helpful.

      Figure 5A: While I understand it is annoying to do so, the authors should demonstrate the specificity of their siRNAs and demonstrate the knockdown of the proteins of interest at least via qPCR, but preferrably via western blotting. Besides this, I find the results in Figure 5 altogether confusing. Loss of Cdk6 seems to be the only protein here that results in accumulation of LC3-II. Do the authors then suggest that between palbociclib targets Cdk4 and Cdk6, it is only Cdk6 that is involved in the lysosomal phenotype? Moreover, if drugging the kinase ILK leads to a rescue, why does knockdown of the kinase ILK not lead to a rescue? Given that ILK is a top hit in the screen, this result is starkly inconsistent. While a knockdown and inhibition are different, this discrepancy should be resolved. Some molecular biology here (for example, CRISPR to create a kinase-defective version of ILK or generating a Shokat gatekeeper mutation of ILK) may help.

      Given that some of the drug targets were B-type cyclins, the omission of Cdk1 is strange. Did the authors test loss or siRNAs against Cdk1? I imagine it would lead to some kind of death, but at least a comment on this is necessary.

    1. On 2021-03-10 19:24:17, user Petr Dvorak wrote:

      It can be interesting to see how bioinformatics can affect climate. However, the paper has really narrow focus in both methods and discussion. First, I think the paper would benefit with a comparison with the commercial computing - Netflix, Spotify, gaming, .... and many others. Just to show how important the carbon footprint is. It will perhaps turn out that bioinformatic footpring is negligable. Second, the bioinformatical programs and algorithms selected here are common, but they represent only a small part of the the tools. Thsu, the results can biased.

    1. I am a man who, from his youth upwards, has been filled with a profound conviction that the easiest way of life is the best.

      This sentence is interesting because it presents the idea that the easiest way of life is the best, which contrasts with the modern belief that success requires hard work and struggle. It makes me reflect on whether a simple and peaceful life might actually lead to greater happiness than constant ambition and pressure.

    1. On 2021-03-10 12:41:27, user Don Wellings wrote:

      Unfortunately regulators always try to justify themselves even with the simplest of solutions. good luck in getting this through.

    1. On 2021-03-09 23:04:16, user Francis Arellano wrote:

      Overall, the paper was very interesting and informative. The background information was clear and the graphical abstract was useful for visualizing the different pathways. Additionally, the consistent use of p-values across the paper was great! For Figure 1B, it may be beneficial to specify the purpose of the white arrows on the immunostain. Also, it would be a lot easier to see the localization of TAK1 if the immunostain was visualized through separate channels (TAK1, CD31, and DAPI each individually) like in figure 8A. In general, it would be nice to see you state the specific mutation lines (M or S) that are used for the experiments, as it was a bit ambiguous in the text. This also goes for the cell lines used, because as a reader I would like that to be more explicit as well. For figure 2E, it would be good to have a quantification to support the difference in the expression of NFKB in the knockout vs wild-type. Also, figure 2F was never mentioned in the figure legend so more information about that would be very helpful. For figure 3A, it would be great to elaborate more on the volcano plot. How exactly was it used and how did it lead to other experiments? Additionally, did it lead you to further explore any specific genes? For figure 3D, what is the baseline for fold change? Is it the experimental over a control value? The gene labels were on the y-axis, but were not clear about what they meant in relation to a control that was used. Lastly, it may also be worthwhile to look at if TAB1-3 can serve as potential therapeutic targets for retinal neovascularization and to explore more on how they relate to TAK1. E.g. is the therapeutic effect greater when multiple of these genes are knocked out? Looking forward to reading the next version of the manuscript!

    2. On 2021-03-09 00:43:51, user Jacob Matiyevsky wrote:

      In our recent research journal club, my colleagues and I chose to discuss your paper and we found it to be extremely interesting. I thought that overall your work did an excellent job at elucidating TAK1’s role in retinal neovascularization and showing that it’s inhibition could be a potential therapy for retinopathy. Each of my colleagues focused on a particular aspect of your paper in-depth, and my focus was on the studies done with OIR rats. I really enjoyed how your team looked at a wide range of effects stemming from TAK1 inhibition. That being said, we found ourselves craving a more comprehensive interpretation for the vaso-obliteration data in figure 7C and what you might have hoped to see with oxozeaenol injections in that case. In general, it might also be helpful to provide additional commentary on the importance of the differing results between the low and high oxozeaenol treatments across the effects you tested for readers to better understand which dose might be better. Also, in figure 6A I noticed that the hyperoxic level was illustrated to be 75%, but based on the rest of your paper I believe that was meant to be 80%. Finally, we thought that the use of immunostaining for the microglial adhesion assay was fantastic and the interpretation for it was extremely strong. We thought that perhaps doing something similar in figure 1 to characterize TAK1 expression in the human retina would strengthen your claim regarding high levels of TAK1 expression there.

    3. On 2021-03-08 23:10:15, user Amelia Andrews wrote:

      Hello! My classmates and I chose your paper to discuss during our journal club. We found the use of TAK1 as a therapeutic target to prevent retinal neovascularization very interesting and relevant. I would like to share some of the comments we had that could help improve the paper, as well as highlight parts that we thoroughly enjoyed. We thought the figures, especially Figures 4 & 5 were well put together. The color scheme was consistent throughout the paper, which aided in data visualization. In Figures 4 & 5, we recommend labeling on the figure whether TIME cells or HRMECs were used to limit any confusion. Specifically, in Figures 4C & D, we found the x-axis to be a bit busy, so we thought the addition of a legend or structuring the labels similar to the labeling in Figures 5B & C could increase readability. In Figure 5, my classmates and I thought the images were very well done, especially in the wound healing assay. We did recognize throughout the paper that the addition of the non-significant p-values made the figures more crowded, so a suggestion we had was to only include the p-values if they are leaning towards being significant. We also wondered if in Figure 5F the image could be color-contrasted to aid in visualization. Overall, we appreciate the methodology and flow to the paper as we progressed from figure to figure. I look forward to reading more about this research and future work.

    1. On 2021-03-09 18:06:46, user PM Lab wrote:

      Very nice and complete work. Congrats for the work!!

      I would like to comment some points:<br /> The SWI/SNF complex alterations in DLBCL, has been extensively reported in the work "Frequent mutations in the amino-terminal domain of BCL7A impair its tumor suppressor role in DLBCL" (Leukemia 2020), where mutations in SWI/SNF subunits were found in more of the 50% of the GC samples. I think that it should be cited in the manuscript, specifically in the text that refers to figure 5.

      Additionally, I suggest to work in the figure of the SWI/SNF complex display depicted in figure 5. We know already the assemble of the SWI/SNF complex (see the cell paper of Mashtalir, 2020) and it is not like the figure 5 is displaying. For example, BCL7A is binding to SMARCA4 directly, and in the image is far to represent that fact.

    1. On 2021-03-09 16:37:04, user David Curtis wrote:

      It would be cool to cite this paper of mine which originally proposed the use of siblings as controls in 1997:

      Ann Hum Genet. 1997 Jul;61(Pt 4):319-33. doi: 10.1046/j.1469-1809.1998.6210089.x.<br /> Use of siblings as controls in case-control association studies<br /> D Curtis

      https://onlinelibrary.wiley...

    1. On 2021-03-08 23:34:17, user Milka Kostić, PhD wrote:

      Dear authors,

      thank you for sharing this preprint with everyone. I recently decided to support research in chemical biology by providing feedback and thoughts on preprints in this field. Your preprint caught my eye, and I hope you will find the comments below useful (I hesitate to call this peer review, but if you would like to share what I wrote with a journal please feel free).

      Kind regards,

      Milka

      Comments to authors:<br /> In this preprint the authors combine genetic code expansion (a strategy that allows one to incorporate non-canonical amino acids at a specific position within the protein), with biorthogonal labeling (a type of chemical reaction executed in living systems in a way that is orthogonal to biological/physiological reactions) and optical microscopy to visualize two members of the transmembrane AMPA receptor (AMPAR) regulatory protein (TARP) family, 2 and 8 in live neurons and brain slices.

      The main problem that the authors set out to address is as follows:<br /> - The authors present evidence that antibodies can’t recognize endogenous TARP gamma2 and gamma8 in neurons because these proteins are found to be associated with AMPAR’s ligand binding domain (LBD) in a manner that masks the epitope. This suggests that strategies like immunostaining using fluorescently labeled antibodies are not appropriate for TARP imaging. Therefore, to solve this problem the authors decided to pursue a completely different strategy that does not rely on antibody use. Overall, this is an important research problem and the approach the authors chose to pursue is appropriate for addressing this problem.

      Summary of the approach:<br /> - The authors incorporated clickable trans-cyclooctene derivatized lysine into TARP gamma2 and gamma8 using established strategy for genetic code expansion. Exposing the modified TARP gamma2 and gamma8 to cell-impermeable tetrazine-dyes resulted in biorthogonal reaction called strain-promoted inverse electron-demand Diels-Alder cycloaddition reaction (SPIEDAC), whereby TARP gamma2 (or gamma8) featuring a modified lysine is covalently labeled with the fluorescent dye. The strategy does not seem to prevent TARP gamma2 and gamma8 from interacting with AMPARs, or affect TARP gamma2 and gamma8 function making this a well-tolerated modification. Additionally, the fluorescent signal is strong enough to allow visualization in primary neurons, as well as organotypic hippocampal slice cultures.

      Summary of key biological observations:<br /> - The key observations made in this study are:<br /> o Most of endogenous TARP gamma2 and gamma8 are found to be associated with AMPAR at the surface of hippocampal neurons.<br /> o TARP gamma2 was found to be mostly localized to synaptic spines as opposed to extrasynaptic sites, while TARP gamma8 had a more even distribution between the two, while still favoring synaptic spines.<br /> o Analysis of visual data allowed for identification of TARP gamma2 synaptic clusters (80 nm in size) that localized within dendritic spines. TARP gamma8 was not observed to form clusters under the conditions used in this work.

      Concluding remarks:<br /> Overall, I found the application of the genetic code expansion in this neurobiology context to be of interest and I can see the potential of this methodology (with further improvements elaborated on by the authors in their Discussion section) for imaging systems that are otherwise difficult to address using optical microscopy.

    1. On 2021-03-08 13:00:57, user Rick Sheridan wrote:

      Great work - really glad to see attention on natural plant extracts against SC2 replication such as the study of artemisia annua. I hope the comments below will be seen in that light - 80% supportive, 20% constructive critical review to support it becoming even better:

      My lab would be very happy if the relevant active phytochemicals in a. annua or a. afria for potency against SARS-CoV-2 replication were identified, whatever they are. That said, I feel that members of the flavonoids class haven't been ruled out yet: While valuable to recognize and assay flavonoids as a monolithic class, there are still very different flavonoid molecules among them that cluster to make up the different classes of flavonoids (flavans, flavanones, etc.). Then there are the glycosidic states of each flavonoid - i.e. does it have one or two sugars attached via a glycosidic linkage? Our in silico modeling shows that these states can have profound effect on limiting SARS-CoV-2 replication. (Note this critique doesn't apply to the statements made with regards to artemisinin, being one single unambiguous molecule)

      It would be very easy for a an operative flavonoid molecule to show up more in one cultivar of a. annua than another, such that even while no association could be shown to total flavonoids, rather that individual flavonoid species vary across the cultivars in such a way that studying a correlation of "flavonoids" collectively against viral inhibition would mask. Our posted work provides justification for just such flavonoid candidates specific to a.annua, and I would be happy to direct these diligent authors toward it with accompanying context.

      Rick Sheridan<br /> EMSKE Phytochem

    1. On 2021-03-07 19:03:47, user Elisabete Morais wrote:

      We are a group of PhD students from ITQB who used this paper for a journal club discussion during a course presentation. Overall we enjoyed reading the manuscript. Kropocheva et al. study discloses the Kurthia massiliensis Argonaute (KmAgo) activity mechanism by showing its relaxed specificity for nucleic acids mainly towards RNA targets. They demonstrate that KmAgo is a unique programmable nuclease that can potentially be used in a wide range of nucleic acid biotechnological applications, such as for precise nucleic acid detection and cleavage. As the in vitro results show promise, it would be interesting to address the in vivo validation.