On 2021-02-06 03:08:38, user Mark Haverford wrote:

What's the phenotype of an orf7b deletion mutant?

On 2021-02-05 22:50:32, user Steven Maere wrote:

Dear readers,

I would just like to point out that the final version of this manuscript, as published in Molecular Systems Biology (doi: 10.15252/msb.20209667), is substantially different from this preprint version, although it reaches the same overall conclusions. You might want to check out the MSB paper.

On 2021-02-05 18:43:15, user Morgan wrote:

Nice work from the Stavrou lab! I do have a question about the statement that the MARCH proteins addressed in this study target viral glycoproteins for degradation. Do you think MARCH proteins could be targeting various viral GPs through different mechanisms? For example, I noticed levels of cell lysate EBOV-GP2 was assessed in the presence of MARCH1/2/8, but did you assess the level of EBOV-GP0? Other studies on MARCH antiviral activity suggest EBOV-GP sequestration to the golgi and inhibiting processing of GP0 to GP1/2. How might you explain or reconcile conflicting reports? Also curious, do you have localization data or inhibitor experiments performed not only with MLV but also HIV-1, EBOV-GP, IAV, and the other viral GPs assessed in this study? I think those data would be interesting to see! Thanks for your time and efforts!

On 2021-02-05 17:32:45, user Edgar Gonzalez-Kozlova wrote:

Yes please!, Finally someone had the courage to make a package for this. Thank you.

On 2021-02-05 15:38:49, user sifaka wrote:

Why did you think that CAH boys would have higher prenatal androgen than non-CAH boys? It seems unlikely as the excess adrenal androgens would have a negative feedback effect on testicular androgen resulting in either lower androgen levels in CAH boys or comparable levels to non-CAH boys.Doesn't combining males and females (where elevated prenatal androgen is established) in the same analysis confound things?

On 2021-02-05 02:42:53, user Robert Flight wrote:

I downloaded the wrong years of data to compare directly with the data presented here (2012-2013) because I was following the guidelines provided in the manuscript, but it looks like a lot of problems with the JIF distributions could be avoided by simply log-transforming the counts.

I posted a proof of concept in a GitHub repo. https://github.com/rmflight...

On 2021-02-04 18:47:53, user Robert Flight wrote:

Where is the supplemental data for this paper? I'd really like to look at it without trying to regenerate it myself ...

On 2021-02-05 01:33:40, user George Santangelo wrote:

Due to a layout error introduced by bioRxiv, the watermark partially obscures some panels of Figures 3 and 5. We recommend that you access the manuscript in its entirety, including the unobscured version of those Figures, on our NIH website: <br /> https://dpcpsi.nih.gov/sites/default/files/opa/document/Yu_et_al_bioRxiv_2-2-2021_withSI.pdf

On 2021-02-05 00:28:34, user Steve Are wrote:

And still there are reports coming in from credible, knowledgable people. There will be another very interesting release about the Thylacine coming out later this year. Stay tuned...

On 2021-02-01 18:31:27, user Jurek Birds wrote:

The paper is interesting as a historical database of alleged sightings. But to my understanding, the reasoning may be circular:<br /> 1. Thylacine occured in remote and wild parts of Tasmania

1. People of Tasmania expect that the thylacine possibly survived in wildest and most remote parts of Tasmania
2. Peoples reports and wildness and remoteness match very well.

On 2021-01-28 02:06:35, user barrybrook wrote:

Thanks for those comments, Jack. Some responses:

-- The 1990s emphasis relates largely to the bioregional findings, as detailed in Table 1 (and the low-probability-weights scenario in Table 1a). The median date of extinction in Table 1b is 1991 for the NW to 1999 for the W/WHA, and the upper confidence bounds in the other regions spans through to the 1990s. I can make that clearer in a revision. But yes, the first few decades of the 2000s still have reasonable support.

-- There will always be effort bias, yes. Given this, there is strong support for an early extirpation in the midlands and eastern parts of the northern slopes. The SW is clearly badly under-sampled, so the upper confidence bounds in the region of the Gordon-Franklin Valleys and further south (see Fig 2d) is likely to be a poor representation, which is why we argued that if the species is to still find refuge, it’ll have to be therein. We can make this clearer too in a revision. We’ve written the paper for short-format journals, so had to be rather spartan with our exposition!

-- Regarding the scoring rubric, the sighting class is objective (see Table S2), and the type (Table S3) reasonably so, but within each type, the scoring of quality is necessarily subjective. It is based on the perceived reliability of the observer, the details provided, and the assessment (where relevant) of authorities of the report itself. Stephen and Cameron did most of these scores, and I think they’re as well positioned as anyone to be objective about those. However, it’s straightforward for anyone who disagrees to change a particular record (or all of them), re-run the analysis, and look at the change in results. We did various iterations in a sensitivity analysis ourselves (e.g. Tables S5 to S8), but the possible permutations are almost endless.

On 2021-01-24 10:51:46, user Jack Ashby wrote:

A very significant contribution to the field, both specifically for the thylacine and the potential for the method to be used for other species. I am no statistician, so I'll leave comments on that to others.

I couldn’t spot why the graphs show a most likely extinction date of after 2000, but the wording of the results suggest a greater emphasis on the 1990s? That post-2000 blue line in Fig 1 isn’t discussed in the text (although I think I follow where it’s come from reading the SI, but it should be explained in the main paper.

Could there be any mention of weighting for effort, or at least greater discussion of the notion that some regions are more densely populated/travelled than others, adding a potential bias to the spacing of records. At first glance of the maps, the sightings aren’t obviously correlated with population centres (quite the opposite, and for example, it’s notable that the heavily farmed Midlands are bare of sightings, while the heavily farmed northwest is not (particularly relevant for the pre-1936 sightings when farmers would<br /> have be extra vigilant, and before the protection came in)). I appreciate this is not a statistical approach like the rest of the paper, but it is something<br /> my eye was drawn to.

The significance of the value of the database, the fact that it will be updated with new records and its public-availability could be better highlighted.

I don’t think you have explained the rubric that was used to determine the quality ratings, which obviously have a big implication on your results. Was there a definition of each rating for each observation-type? Without knowing what specific criteria you used to rate the<br /> sightings, this analysis is not repeatable, and hard to unpick.

On 2021-02-04 19:34:05, user anonymus wrote:

We conclude that the memory B cell response to SARS-CoV-2 evolves between 1.3 and 6.2 months after infection in a manner that is consistent with antigen persistence. Where does one test for the above?

On 2021-02-04 17:08:43, user Daoyu Zhang wrote:

https://www.nature.com/arti...<br /> Computer modeling is the #1 worst way to spin fake results. None of your alleged “higher than human” affinities are actually higher than human when actual experiments are conducted using untagged ACE2 and RBD in a Surface Plasmon Resonance (SPR) assay. Intact spike trimers https://www.researchsquare....<br /> and transduction Assays using real virus <br /> https://www.biorxiv.org/con...<br /> Unanimously rank human ACE2 at the highest binding affinity and transduction efficiency of all ACE2 used in the experiment.

On 2021-02-04 15:41:41, user Jack wrote:

Good paper. Obviously Kimura’s neutral theory is incorrect. You should inquire with Shi Huang and run the same models with his Maximum Genetic Diversity theory (MGD), it is a competing theory to NT and Shi and team used it to solve Margolash’ equidistant result. It may solve Lewontin’s paradox.

On 2021-02-04 06:46:16, user Řajneesh Srivastava wrote:

This article has now been published in Nature Scientific Reports. Here is the link.<br /> https://www.nature.com/arti...

On 2021-02-04 05:30:17, user Megumi Iizuka wrote:

I noticed, though that the data in their presentation material is from Day 0 to Day 8.<br /> https://investors.vaxart.co...<br /> Neutralizing antibodies generally don't appear until Day 7. I just don't know why their data only shows the response for day 0 and 8. I wonder why when they started in october 2020, they would only have prelim data for 8 days. Is this a normal timeframe for a small company with 35 subjects?

On 2021-02-04 00:02:39, user Melody Zaki wrote:

Hi Dr. Alkhatib et al.,

Thank you so much for conducting this research on triple-negative breast cancer. It was so interesting to read your methodology as you approached this looming problem in the way that we treat cancer patients. I am so glad that I had the opportunity to not only learn more about TNBC through reading your paper but that I was also exposed to the surprisal analysis technique you used to evaluate single-cell responses to RT and CT. The figures that you used to describe your methodology were very helpful for students, like me, who may not have understood the nuances of your experimental approach upon first glance of the paper.

As an undergraduate student, however, there were still some things that I was left wondering and confused about after reading through your research. For example, I thought it would have been very helpful to clarify the demographics of the patients used in this study. Especially given that you were studying single-cell variations in breast cancer tumors, it may have been interesting to compare whether certain races suffered similar mutations or if they had similar cell-specific signaling signatures. I also struggled to understand some of the figures that you used to display your results because of the color changes and the inconsistent axes labeling. For example, in figure 4g I was confused as to why you decided to switch to black and white labeling of the active processes and believed it would have been more helpful to label the vertical axis as ‘process number’ and the horizontal axis as ‘CSSS.’ At first glance, it seemed as though you were now looking at 14 different CSSS instead of the CSSS in the fourteen different processes. It was also unclear why you decided to switch up the order of the CSSS (as they were no longer in alphabetical order). Small changes to the organization in your figures would be very beneficial in allowing those who do not have as much experience in research to gain a lot from your writing.

Overall, I learned so much from your work and I'm so excited to see how others will respond to your research! I also hope that others will apply your methodology to other types of cancer research as it could shed a lot of light in how we are approaching treatment options.

Thank you again!

On 2021-02-01 15:12:18, user Melissa Bu wrote:

Hello Drs. Alkhatib et al.,

My name is Melissa and I am an undergraduate biomedical sciences student at UCLA. A few classmates of mine and I chose your manuscript to present for our Journal Club seminar course. We wanted to share some of the feedback we collected from our ~15 peers and professor on your excellent work, and hope it may be of use to your revision process:

In general, we were curious about the stage of TNBC tumors obtained from patients for the gene expression profiling? We wondered if the stage of tumor would affect the selection of onco-proteins for subsequent FACS analysis.

For fig. 1, we appreciated the simple and effective coloring, as well as the use of sketches to illustrate the workflow. We thought it might be a good idea to clarify that the schematic illustrated in fig. 1 is of the experimental order, not the treatment order (since elsewhere in the manuscript the targeted therapy is described to be administered prior to radiation therapy). Additionally, what were the demographics of the patients form which the xenografts were derived? Were they from a diverse sample of patients? Furthermore, since the solution schematic is illustrated in fig. 3, we thought it would be worth considering the omission of the bottom half of figure 1. If it is kept, however, we wondered about the definition of "non-proliferative"—does this mean the tumors are still present, just no longer growing? Or, does it imply that a new subpopulation (from the original mass prior to RT and targeted therapy)? <br /> We also wanted to learn more about the 14 processes in supplementary table 1, but had trouble comprehending it and thought it could be modified to be more accessible to readers outside of the your research niche.

For fig. 2, we noticed a small typo in panel a where "patients" was mis-spelled as "pateints." We also wondered whether what the colors meant for the plot in panel b, and why R^2 was used. We thought panel b might be suitable as a supplementary figure instead. In panel c, we were unsure whether one of the red/blue outlines should read "down due to" as opposed to both "up"? In terms of coloring, we thought it may make the figure more clear if the outline color were orange and green, for example, corresponding to the red and blue solid boxes. In addition, we thought it could be beneficial to include somewhere in the text that CD326 was not participating in the processes, since we could not find this marker involved in any of the processes. For the sake of reading ease, would you consider assigning more distinct colors to EGFR and CD326 in the selected onco-markers key?

Fig. 3 was really helpful for understanding the workflow and purpose of each step in the project!

Fig. 4: in panel g, we were confused about the label placement of "CSSS" and suggest the "CSSS" label currently labeled vertically to instead be placed horizontally. In its place we suggest "process number." We were also curious bout the lettering of the CSSS barcodes—are they in temporal chronological order (curious because b and f correspond to the "Early" and "Late" sub-populations). In terms of presentation, we wondered why the squares were now black and grey as opposed to the red and blue presented in in earlier figures. <br /> In panel a, we suggest increasing the font size of the protein names. We also noticed that the tops of the error bars for 15 Gy group are detached for both Her2 and cMet plots. In part b, we suggest cleaning up the underlying blue grid structure, as well as putting up the Flow gating for more natural interpretation.

Fig. 5: We thought it might make panel a more clear if "E," "L," and "P" were written out and perhaps also represented with different colors as opposed to the line patterns currently used to differentiate between the groups. in panel b, to avoid confusion of indicating other panels, you could consider labelling the CSSSs as "Early" and "Late" instead of "b" and "f." In the figure legend, we think readers would appreciate it if RT and C could be written out in full for clarity's sake. Since the orientation of panels i and j are confusing, and there is generally lots of data packed inn fig. 5, we suggest that it can be split into two separate figures.

Fig. 6: We thought that panel a may be unnecessary, since we had little trouble comprehending the mice radiation process. Instead, we suggest replacing panel a with a timeline of the mice workflow. We thought panel d of this figure was very clear and well-done! In part e, since all groups have RT, instead of "+" across, you could consider a single line or a simple description. Importantly, for the sake of color-blind readers, it would be beneficial to use more differentiable colors for the bar colors here.

Fig. 7: We thought that the "14d post RT group" in panel a could be changed from green to a different color, since it's currently labeled as the same color as the "RT+T+C" treatment group in later panels. In part b, we thought the colors could, again, be more distinguishable for accessibility's sake. In panel c, we were curious about the arrows pointing at the green group—could you explain in the legend why these arrows were placed? Since there is a lot to look at in panel c, we believe it would be beneficial to space out the graphs. In panel e, we were curious about the use of "E" drug, and suggest, for consistency's sake (with panel c), that this group be omitted (or added to panel c). We would again suggest "Early" and "Late" instead of "b" and "f" for the CSSSs depicted in panels b and f of this figure.

In general, we learned a great deal about TNBC, single cell surprisal analysis and other valuable techniques from reading your manuscript. Thank you for sharing this exciting and important work. The writing was overall easy to understand and compelling, and we particularly appreciated your use of multiple models (i.e. human data, cell lines, and mice models). Again, my peers and I are undergraduates, so we are giving feedback from a baseline level of knowledge. We really appreciate your efforts in offering better solutions for this deadly disease. After reading about the level of specificity in and strategic approach in which you are investigating TNBC, we feel more hopeful for the future of patients with TNBC.

On 2021-02-03 19:44:15, user Nina wrote:

Where do I find the supplementary tables?

On 2021-02-03 17:47:01, user Virginia Savova wrote:

Very interesting paper. Does this mosaicism have clinical consequences?

On 2021-02-03 17:01:14, user Giulio Caravagna wrote:

There is a minor problem with this version, which are about to update. The new version contains a change to the Data Availability section; we indeed decided to open up all repositories, which can now be found at https://github.com/caravagn...

On 2021-02-03 14:38:52, user Andrea De Micheli wrote:

Paper now published here:<br /> https://journals.physiology...

On 2021-02-03 09:18:07, user Ilaria Russo wrote:

This methodology was first published in PNAS by Goldberg and collaborators regarding Pf_Calpain analysis. Associated to that paper there was the actual script for the analysis. It would be nice to acknowledge this

On 2021-02-02 22:22:55, user Pavel Montes wrote:

THE FINAL VERSION OF THIS PAPER CAN BE FOUND AT:

https://faseb.onlinelibrary...

On 2021-02-02 20:56:28, user Fraser Lab wrote:

Martynowycz and coworkers focus on GPCRs, which are both biologically important and difficult to study, as a natural next step for microED. As the authors note, the same system has previously been resolved to better than 2 Å resolution by X-ray diffraction, both with synchrotron radiation and with an X-ray free electron laser. The main improvement presented by this method is the low sample volume necessary, < 1 µm3 from a single nanocrystal, as compared with the thousands or millions of larger microcrystals required for the other two methods. This may be critical for some samples for which preparation of either large crystals or large quantities is prohibitive. Although complexes of GPCRs have also been studied by cryoEM with minute amounts of sample, the unbound, inactive state is generally too small to be resolved by single particle analysis with cryoEM (so far). The use of fusion proteins in crystallography (here, BRIL) or larger fiducial binders in EM (generally nanobodies) also highlights unique limitations of the current state of the art for each technique.

The detailed description of conversion of a suspension of nanocrystals in lipidic cubic phase (LCP) to sponge phase and successful preparation of EM grids with this media is highly informative. Given that A2A is the “lysozyme” of GPCRs, we hope it is generalizable. In this respect, we really appreciate the inclusion of protocols that did not work. Slightly more detail would be beneficial in the description of the sponge form behaving as a liquid that can be extruded from a small gauge needle without additional force. Could the authors please quantify the gauge of needle and the (approximate) amount of force? We are inferring they are comparing to an LCP extruder used for serial crystallography experiments, but this may not be obvious to all readers, who may be interested to know what kinds of forces are necessary to extrude crystals in LCP.

The figures and movies are outstanding and quite clear. We suggest the addition of a supplementary figure showing the systematically missing wedge of data using the Phenix reciprocal space viewer, which would support the authors' hypothesis that multi-crystal averaging was largely unhelpful because the datasets were missing the same reflections. We would also like to see difference density in supplementary figure S8 showing intact disulfides.

While beyond the scope of this paper, the ultimate impact of this procedure will be in how generalizable it is to other precious LCP samples and in the ability to “find” the small crystals in the LCP on grids during the FIB/SIM procedure. The isomorphism problem that is touched on here may also be even more severe in non-A2A samples. FIB milling is an obvious strategy to study this more widely with many crystals, which would be exciting! More discussion of those challenges may provide a more realistic picture of the challenges that lay ahead. As the crystallography and cryoEM communities have seen in recent years, a method need not be universally superior to another to have a place in structural biology. With a slightly more fleshed-out description of how microED of nanocrystals grown in LCP, the manuscript constitutes a significant advancement.

We identify a few minor suggested edits as well:

The authors use the phrase "precipitant solution" in a couple places. These terms are contradictory, as "precipitant" means "not in solution." We suggest the phrase "precipitant suspension" instead. <br /> The terms lamella (singular) and lamellae (plural) should be checked over to make sure each instance takes the correct form. <br /> The quantity I/σ(I) should always be formatted so that it is clear that the denominator is the entire quantity σ(I).<br /> We encourage them to release the coordinates and maps now and adopt that practice on future preprints: https://asapbio.org/asappdb

James Fraser and Iris Young (UCSF)

On 2021-02-02 19:41:01, user Pavel Valerjevich Voronov wrote:

I'm afraid to blindly guess, but it seems, that in some cases immune response becomes more efficient. Are these cases somehow related to blood type or some other factor that can be used in a fight? Every mutation happens in tradeoff for something and it looks logical that it goes in direction of Rh+ or some other blood type population (those who already have antibodies, as an option), sacrificing another.

On 2021-01-28 02:50:03, user Paul Wolf wrote:

One bright side may be that if there is convergent evolution, maybe the different strains will be similar enough for the same antibodies and vaccines to work on them. It seems like the problem is when the strains become too different, and reinfection can occur. I assume that's what happened in Manaus.

By the way, in the news today I saw that 1,400 patients are being transferred from Manaus to hospitals across the country. It seems like the most dangerous thing you could do, and the fastest possible way to spread the P.1 variant.

On 2021-02-02 17:36:34, user Julio Escribano wrote:

This paper has been published: https://doi.org/10.3390/bio...

On 2021-02-01 20:57:24, user Crypto Microbiology wrote:

Finally!!!!<br /> I was modelling the COVID infection and I thought that the infection would have been ended before.... How could I know people was submitting crappy assemblies!!! I have downloaded too many SRA sequences and I have found serious assembly problems :) Thank you for your nice work...

On 2021-02-01 17:05:51, user Eric Jorgensen wrote:

Would like to know exactly who funded the study

On 2021-01-28 16:19:30, user Fred Recchiuti wrote:

I can't believe that I'm the only one who sees the opportunity to be using this X-GSE combination spray as a prophylactic measure as soon as one arrives and also leaves a communal setting like a classroom, store, etc. especially since a 1.5 oz spray bottle costs around 9 dollars! Does anyone see a downside to this?

On 2021-01-28 04:27:29, user Mitchell Collier wrote:

For clarity, if "the compound" refers to the Xlear Nasal Spray test compound, as it appears to, state so explicitly. <br /> Clarify that "the compound preparation" refers to the commercial Xlear Nasal Spray.<br /> Document that the concentrations indicated for xylitol and GSE were validated for purposes of this experiment and not based only on the product label; or at least back track to the product batch and document the manufacturer's QC results for the batch.<br /> Further, consider stating the manufacturer's source for the xylitol and GSE active pharmaceutical ingredients.<br /> Elaborate in the discussion how an in vitro 25-minute exposure of the virus to the 90% test compound solution might theoretically compare to the microenvironment of human nasal mucosa (with associated secretions) when the Xlear Nasal Spray is applied with respect to exposure of virus particles to the test substances and their susceptibility thereof.<br /> Thank you for performing this research on a low-cost intervention against infection by SARS-CoV-2.

On 2021-02-01 16:58:25, user David Klinke wrote:

I think that this is a fraudulent manuscript. It's pretty obvious if you look closely at the figures or how unrealistic the experimental results are. For instance, it seems that the Skp2 lane is an exact copy of the p27Kip1 lane in Figure 5a.

On 2021-02-01 16:40:44, user Robert Policastro wrote:

Hello,

I was impressed by your paper and methodology, so decided to give the software a try. I was unfortunately not able to get the software running for a few reason that I will share.

COTAN currently uses a library 'rray' that is no longer on CRAN due to unaddressed build errors. You should either contact the package authors to try to get this resolved, or switch to another supported library if possible.

While running the software through docker on my data, the workflow fails once it attempts to use Python, and asks whether I want to install a conda environment with Python.

Right now the package works using a series of functions within a file that is first sourced before running. If you want wider adoption of your method I think changing this to be formatted as a proper package with roxygen2 documentation will make it much easier to install and use. See the devtools library and bioconductor package guidelines as good resources.

Cheers!<br /> Bob Policastro

On 2021-02-01 14:45:00, user Allan wrote:

Maybe complementary to this new tool here?<br /> https://www.biorxiv.org/con...<br /> I've recently used it and it works well

On 2021-02-01 02:14:52, user Hamid Gaikani wrote:

GREAT JOB!<br /> HZE stands for high (H) atomic number (Z) and energy (E)<br /> I thought maybe the actors want correct that before the papers appears in a journal.

On 2021-01-31 22:33:16, user Cindy Dunbar wrote:

Nice work which I need to read in more detail, but FYI in our recent macaque barcoding study focused on erythropoiesis- we did not study impact of EPO ex vivo, just in vivo and didn't see a change in clonal composition, at least at steady state post-transplant. DOI: 10.3324/haematol.2019.231811

On 2021-01-31 16:59:41, user Jesse Erasmus wrote:

Great data! Question about timing of peak viral loads. Previous papers by this group show peak viral load occurring variably between days 1 and 4 after challenge. Which time point was selected for comparison of viral loads in BAL and nasal swabs in this study?

On 2021-01-31 08:26:57, user Michelle M Gehringer wrote:

We submitted this manuscript to HardwareX but they are having trouble finding referees for such a technical article. If you think you can referee this paper please contact them.

On 2021-01-31 08:08:30, user Johannes Hambura wrote:

As SARS-CoV-2 can persist in the intestine for up to three months after viral infection and the pressure imposed by the antibodies on these viruses having led in vitro to the emergence of resistance mutations, it would be logical to not vaccinate first-line people who have had a positive PCR, or delay vaccination for at least 3 to 4 months.<br /> Likewise, in order to avoid suboptimal immunity which can also lead to the emergence of resistance mutations, the time periods between two vaccinations should be strictly observed, as adopted by pharmaceutical laboratories.

On 2021-01-31 08:02:24, user Carlos wrote:

I d like to know when the embryos where inoculated with the virus and when with dioxide

On 2021-01-31 02:37:45, user Michael Hall wrote:

Great work Kristoffer. I enjoyed reading this.

I have two comments/questions:<br /> 1. The example randstrobe hash values in Fig. 1B seem to be incorrect for the first two sequences - or am I missing something?<br /> 2. (Forgive my ignorance) The hash function you describe for randstrobes in the text is quite different to that in the example. In the text you say that you just concatenate the previous strobes for the current strobemer. And then I assume you take the hash of this concatenated string? If so, I am struggling to see how this would produce different strobes to the minstrobe method. Given, for randstrobes, the concatenated string of the previous strobes is fixed and you are effectively only considering the impact of the addition of the strobes in the current window. Therefore, wouldn't you end up selecting the "classical" minimizer for that window as in minstrobes?

My apologies if I have not effectively communicated my questions. I'm very happy to discuss further.

On 2021-01-30 22:18:10, user Dittmer Lab wrote:

Would this be considered a gain of function experiment?

On 2021-01-30 13:18:23, user Anon wrote:

Hello the Schulz and Creutz (2004) reference is missing.

On 2021-01-29 19:16:18, user helene banoun wrote:

Are Vero cells (green monkey kidney cells) the right model to study the entry of the virus in the presence of antibodies?

The penetration of CoV-2-SARS in Vero cells is not dependent on the furin site, unlike in humans.

On 2021-01-29 16:45:19, user David Ashbrook wrote:

A final published version is available from https://authors.elsevier.co...

On 2021-01-29 15:06:35, user Martin R. Smith wrote:

A potentially minor point, but I wonder whether the Robinson–Foulds distance is the best measure of discordance in this situation? It's possible that misplacement of just one taxa could result in a high number of edges not being recovered, and this sort of error might occur more or less frequently under different methods. I've reviewed the performance of distance measures new and old across a range of scenarios in Smith (2020, Bioinformatics): https://doi.org/10.1093/bio...

On 2021-01-29 11:55:21, user Johan Van Weyenbergh wrote:

It is not clear to me if PBMC or somehow purified monocytes were used to draw these conclusions? From the Methods section it seems only total PBMC (Ficoll separation) were used in all experiments.

On 2021-01-29 09:20:05, user Isabelle Dusfour wrote:

Erratum in the Table 1 legend : Percentages of knocked-down mosquitoes at 30 minutes (30%KD) and the standard deviation (STD) amongst replicates in CDC-bottle test for Anopheles darlingi populations collected in Blondin (BL) and La Césarée (LC). Test results are break down into the insecticidal molecule, year and week (Wk). In addition, the method of collections (CM) i.e. human landing catch (HLC) and mosquito magnet trap (MM), the number of mosquitoes tested (N) and replicates are mentioned (n). Dark grey: resistant populations with 30%KD < 90%; light grey: 90%<30%KD< 98% possible resistance; white: susceptible 30%KD>98%.

On 2021-01-29 09:05:33, user Meghamsh Teja wrote:

In fig.3A, I need some clarification. First, size exclusion chromatography was performed, fractions were collected and then subjected for SDS-PAGE. Color codes represent the type of the sample and color coded box represents their respective gel analysis result. In gel3, according to color code, only nucleosomes were added, so how did Mer2 appear on gel. Can someone explain it ?

On 2021-01-29 07:35:19, user Sarah Harden wrote:

We are pleased to say our paper has been published!<br /> https://www.frontiersin.org...

On 2021-01-29 06:22:13, user Upendra Nayek wrote:

First of all, congratulations to all of you. I am just wondering about the concentration of DNA and what about cell sizes! Could you please tell me how did you experimentally monitor these parameters? The result you have shown totally depends upon light phenomenon. From figure number 5, we could understand the similar time depended on results of your experiments. - Upendra Nayek, Research scholar, India

On 2021-01-29 05:33:26, user Jeff Bowles wrote:

The clocks aren't even the mos timportant part of this paper.....It is the fact that aging is "indeed conserved by evolutona and related to development" This throws a huge money wrench into the Selfish gene theory of aging-theose evolutionary biology professors gonna have some splainin' to do!! ANBd teh second most importna thing abotu this paper are the genes identified involved in he aigng process!! he clocks are rally just a side show compared to these two earth shaking findings!

On 2021-01-29 01:37:01, user J Paul Taylor wrote:

An updated version of this paper is now published in the Journal of Cell Biology: https://rupress.org/jcb/art...

On 2021-01-28 16:49:11, user Ajay Kumar wrote:

This article is published in eLife and can be viewed by using following URL<br /> https://elifesciences.org/a...<br /> We would love to hear any comments and feedback and answer any questions readers might have.

On 2021-01-28 15:13:00, user Laura DVR wrote:

The supplemental figures are provided under "supplementary material" and not at the end of the manuscript PDF file. I've just checked and Fig_S1 does contain the benchmarking data referred to in the text. Hopefully that clears up any confusion.

On 2021-01-27 15:29:13, user Julien wrote:

In this version, supplementary figures do not seem to be what they should be. As a result, unfortunately, there is no Figure showing superiority of the Franken pipeline compared to other clustering approaches.

On 2021-01-28 14:42:57, user Ligophorus mediterraneus wrote:

The package FuzzyQ is now available on CRAN (https://CRAN.R-project.org/...

On 2021-01-28 14:32:33, user chaohw3619 TMU wrote:

This paper has been published in Nature Communications.<br /> https://www.nature.com/arti...

On 2021-01-28 14:26:01, user Faryal Ijaz wrote:

Please check the published version in Cell Structure and Function.<br /> https://doi.org/10.1247/csf...

On 2021-01-28 03:12:03, user Dina M. Fonseca wrote:

Hi Alec et al. Great study! But can you clarify what stages of Haemaphysalis longicornis were positive for Anaplasma phagocytophilum? The legend in Table 3 states that the numbers between brackets refer to male/female/nymphs but H. longicornis in the US does not seem to have many (any) males. Thanks!

On 2021-01-28 02:51:54, user LarsN wrote:

Someone forgot to include the proper link to the software. Find it here on GitHub https://github.com/LarsNauheimer/HybPhaser

On 2021-01-28 02:02:24, user seth wrote:

could be helpful for screening a solid resistant resource

On 2021-01-27 22:50:46, user Timothy En Haw Chan wrote:

It is published on https://doi.org/10.1016/j.c...

On 2021-01-27 21:28:18, user Andrew Greenstein wrote:

Did you exclude the sarcomatoid cases from your analysis? These are highlighted in the original Zheng 2016 paper as outliers. I would recommend removing them and repeating some of your comparisons between CS and nonCS tumors.

On 2021-01-27 20:35:37, user Rath R. Weird wrote:

A few simple takeaways from this work:<br /> 1) structural biologists unconcerned with functional (e.g. biochemical) analysis of their samples are liable to determining the structure of catalytically dead enzymes;<br /> 2) there is such thing as over-optimization of expression vector;<br /> 3) soluble protein isn't necessarily the native one (just like non-denaturing doesn't always mean native, as in purification);<br /> 4) it naturally follows from the differential impact of synonymic codons on folding and activity of SARS-CoV-2/hCoV-19 RdRp in one heterologous host (E. coli) that they'd have similar (in magnitude) impact on its expression in another heterologous host (human). Which calls for as careful examination of SARS-CoV-2/hCoV-19 mutations in terms of codon replacement, as received by amino acid substitutions. Furthermore, the non-synonymic mutations may impact fitness not only through the impact of amino acid change, but the codon frequency alteration also.

On 2021-01-27 14:06:15, user Morten wrote:

Dear Dylan and co., <br /> I watched the video of yours published on Nanoporetech and read the paper with great interest! I have a few questions regarding the methods used in your study, that I hope you will take your time to respond to. <br /> 1) Was it the single Illumina reads or contigs that were taxonomically classified against the custom database? <br /> 2) What information does this approach offer not contained in the 16S rRNA amplicon approach (free of PCR bias or higher species resolution)? As I read you do not use the Illumina reads for any functional annotations? <br /> Kind regards,<br /> Morten from Denmark

On 2021-01-27 03:10:47, user Mark Konyndyk wrote:

I still think the R0 may be understated.

On 2021-01-27 03:07:54, user Mark Konyndyk wrote:

And quickly it move to Florida. Clearly the R0 was incorrect.

On 2021-01-27 00:32:01, user Fadi Abdulsater wrote:

The primers suggested in this study to detect only the B.1.1.7 are not good choice with only one mismatch in the middle of the forward primer. these primers are able to detect the Wuhan-Hu-1. you have to design primers with at least 2 mismatch at the 3'end of the primer.

On 2021-01-22 19:22:12, user alejandro wrote:

To the interested we extended this methodology to other variants, while we wait for the laboratory results.

https://www.biorxiv.org/con...

On 2021-01-20 08:25:11, user kostas wrote:

Hello and thank you for work and the interesting approach. I hope the authors understand that the first "element" behind their title, is to provide some evidence that the primers do work, and this is not totally clear to me at least in this version of the manuscript. Also as a reviewer this would be the first thing i would like to see documented.

On 2021-01-15 13:13:18, user Martin wrote:

Hello, many thanks for this work and the interesting approach. However I have doubts that these primers are able to identify the B.1.1.7 variant. The reverse primer is 100% complement to the SARS-CoV-2 reference sequence and in the forward primer there is only one mismatch in the forward primer towards the 5' end.

I'm working >15 years with real-time PCR and these primers WILL amplify the wild-type variant. There are no conditions which make the forward primer 100% specific for the new variant. The usual approach to identify a SNP is to place the SNP exactly on the 3' end of the primer (-> allel-specific PCR). In theory, this 3' mismatch cannot be extended by the Taq polymerase because there is no DNA double strand present. In reality however, you get amplification which is shifted some cycles to a higher Ct. To enhance this instability effect, a second mutation can be introduced near the 3' end of your primer.

Nevertheless, your findings are important because if this C16176T SNP is specific for B.1.1.7 there are genotyping techniques in real-time PCR which you can use to distinguish between the new variant and the "wildtype". For example, you can use two MGB-probes but with the disadvantage of blocking two fluoresence channels on your instrument only for genotyping. You can also use a molecular beacon probe with subsequent melt curve analysis.

On 2021-01-08 23:46:13, user Alejandro Marquez wrote:

Hello, honestoy I don't get how these primers can be specific for the new variant, I only found SNP variations in the middle of the primer and not in the 3'-end. Based on my experience these primers will amplify with the original and the new variant... can you explaint better...?

On 2021-01-26 23:29:47, user Edwin Alberto Pinilla Salazar wrote:

Dear Fan, below I am sending you the link of a document that correlates a lot with the research you have been carrying out and that resolves some concerns that you had, related to tests on animals and on human beings.<br /> https://www.ncbi.nlm.nih.go...

On 2021-01-26 20:23:28, user Tiago Lubiana wrote:

Now published at: https://bmcbiol.biomedcentr...

On 2021-01-26 19:39:42, user Matt wrote:

Very interesting paper! Authors, have you considered running your qpAdm result in a 3-way model with (East Asian)+Maniq+(South Asian)? Another reader of the paper has suggested to me that the time depth of divergence of the Onge from the true admixing source into South East Asian populations may lead the qpAdm results to be biased towards higher probability values for South Asian populations with high levels of ASI (ancestral South Indian) ancestry. Testing the same models with the Maniq population in place of Onge (although this population has some East Asian ancestry) might allow to test this idea. Also it would allow the use of the Onge population in the outgroup set.

On 2021-01-26 18:37:11, user Laurent Seroude wrote:

How old are the adults used? Is there also a loss of repression in old animals?

On 2021-01-26 17:00:23, user Nicholas Markham wrote:

Please find this work published at:

Markham NO, Bloch SC, Shupe JA, Laubacher EN, Thomas AK, Kroh HK, Childress KO, Peritore-Galve FC, Washington MK, Coffey RJ, Lacy DB. Murine intrarectal instillation of purified recombinant C. difficile toxins enables mechanistic studies of pathogenesis. Infect Immun. 2021 Jan 19:IAI.00543-20. doi: 10.1128/IAI.00543-20. Epub ahead of print.

PMID: 33468584.

https://iai.asm.org/content/early/2021/01/13/IAI.00543-20.long

On 2021-01-13 18:30:29, user Nicholas Markham wrote:

I'm happy this manuscript was resubmitted to Infection and Immunity and has been accepted for publication! Thank you to Borden Lacy all the co-authors!

On 2021-01-26 16:07:06, user Chris ADAM wrote:

Hello,<br /> I'm a Master student in bioinformatics working on epigenetics data. I aim to diagnose genetic diseases using machine learning. At the end of this article, it's said the code will be made available in a public repository. Has it been done yet ?<br /> Best regards,<br /> Chris

On 2021-01-26 16:04:50, user Héctor Climente wrote:

In Table 1, the number of samples for the Habib et al. dataset should read 1402, instead of 13302. This error is completely inconsequential for the results of the paper, and that number is not even referenced elsewhere in the text. Yet, it is incorrect, and might potentially confuse readers familiar with that study.

On 2021-01-26 14:33:24, user H. Chowdhury wrote:

Interesting findings using bat cell line!

On 2021-01-26 10:08:01, user Wouter De Coster wrote:

Dear authors,

Very interesting work. I wanted to bring to your attention that the 1000 genomes project samples have been resequenced to 30x and are publicly available (https://www.ebi.ac.uk/ena/b.... While obviously a lot of work to repeat your analysis this would potentially contribute to a substantially more informative study.

Best regards,<br /> Wouter

On 2021-01-26 04:19:38, user Qi Luan Lim wrote:

Dear reader,

We have published a revised version of this article in the Malayan Nature Journal 71(4): 423-437 (2019). You can contact us for more information.

Q.L. Lim

On 2021-01-25 21:39:12, user Felix Willmund wrote:

The study was recently published in Nucleic Acids Research<br /> https://doi.org/10.1093/nar...<br /> Title: The versatile interactome of chloroplast ribosomes revealed by affinity purification mass spectrometry

On 2021-01-25 13:30:04, user Al-ameen Mohammed wrote:

This is the best paper that I found explaining the Wnt / B-catenin pathway in a concise way. The paper is interesting for its relevance to the topic of B-diketones I am doing my research on.

On 2021-01-25 11:39:29, user Maria Yáñez Mó wrote:

We already published a similar approach in 2019: see Development of a quantitative method to measure EV uptake.

Toribio V, Morales S, López-Martín S, Cardeñes B, Cabañas C, Yáñez-Mó M.

Sci Rep. 2019 Jul 19;9(1):10522. doi: 10.1038/s41598-019-47023-9.

On 2021-01-24 22:49:04, user John Lisle wrote:

Unhappy news.<br /> A pragmatic regulatory approach that enables fast-cycle development within a broad structural family is essential.

On 2021-01-23 12:09:42, user Ariel Roytman wrote:

Is there a missing information in this article? <br /> I could not find the positivie control for neutralization test for non mutant variant.<br /> In addition, I would like to understand if the concetration of neutralizing antibodies was sufficient/excessive.

Without such controls there is no true meaning for those findings.

On 2021-01-24 13:28:39, user cab1967 wrote:

Most recent discussions that concluded minimal impact at the KPg boundary weren't referring to Crocodylomorpha as a whole - they were talking specifically about Crocodylia.

On 2021-01-21 18:29:53, user Roger Benson wrote:

I very much like the analysis presented in this paper. And it is clear that advances of this type have great potential to improve understanding of events in deep time. However, I think that the palaeontological understanding of the effects of the KPg on crocs is misrepresented, and there is a misinterpretation of the signal from relatively invariant standing diversity as being equivalent to an observation of ‘no extinction’ and so no turnover. For example, Mannion et al (2015) is cited as saying that effects of the KPg mass extinction were ‘minor or absent’. But in fact, Mannion et al observed substantial turnover and clearly believed that the KPg was an important event for crocodilians, as follows:<br /> “The effect of the K/Pg mass extinction on crocodylomorphs has previously been perceived as minor or non-existent19,28, with any extinction temporally staggered33. However, several non-marine groups with high biodiversity before the boundary became extinct (most notably all non-sebecid notosuchians34), and only two clades (the marine dyrosaurids and terrestrial sebecids) survived alongside crocodylians28,35. Nevertheless, the extinctions of these groups, and other non-marine crocodylomorph taxa were balanced by rapid radiations of the three surviving clades in the early Paleocene19,28,34,36, including substantial range expansions of marine dyrosaurids36,37 and terrestrial alligatoroids28 into South America.”

On 2021-01-20 09:55:56, user Eduardo Puértolas wrote:

Interesting study on how Crocodylomorpha was affected by the K/Pg extinction event, I encourage the authors to continue with this work and line of research. The approach to the problem is novel and promising, but I recommend to the authors to take a look at Puértolas-Pascual et al. (2016). In this work, based on fossil occurrence data, we already observed that Crocodylomorpha were severely affected by the crisis, at least in Europe.

Puértolas-Pascual, E., Blanco, A., Brochu, C. A., & Canudo, J. I. (2016). Review of the Late Cretaceous-early Paleogene crocodylomorphs of Europe: extinction patterns across the K-PG boundary. Cretaceous Research, 57, 565-590.

On 2021-01-24 12:48:14, user alejandro wrote:

Please cite this paper

https://www.nature.com/arti...

On 2021-01-24 10:42:27, user Ibrahima GUEYE wrote:

Very pleasant article with a rigorous scientific approach. Two peptides (P9 and P10) emerge due to their ability to completely inhibit SARS-CoV-2 without pulmonary cytotoxicity. However, I have two concerns. First: the two algorithms used; namely Agadir (to assess the helical content) and Kolaskar (to assess the antigenicity) are not applicable for sequences containing homotyrosine (hY). P9 and P10 contain it. They were forced to measure the helical content by experimental method without having to give empirical data. (disciples of Claude BERNARD may be). Therefore for the antigenicity it will require clinical studies. Second: what about kidney toxicity?<br /> Médecin-commandant Ibrahima GUEYE<br /> Spécialiste en Médecine d'urgences et de catastrophes <br /> Master 1 Biomathématique et Bioinformatique <br /> 3 PRINTING <br /> Number theory (Erdös-Straus conjecture)<br /> Médecin-chef CMIA Ziguinchor<br /> https://orcid.org/0000-0002...

On 2021-01-24 09:19:58, user fischmidtlab wrote:

Wonderful story that underscores the importance of biparatopic approaches for passive immunization!

Two questions:<br /> 1. Do you know whether Spike E484D is a genuine escape mutant (i.e. prevents neutralization with C121)? Demonstrating escape mutants with wt SARS-CoV-2 in these short infection models would be an important finding.<br /> 2. Did you get the chance to test performance of CoV-X2 against the more dramatic E484K mutant with charge reversal observed in vitro (Weisblum et al.) and in the recent variants B.1.351 (South Africa) and P.1 (Brazil)?

Great work, looking forward to see more of this!

On 2021-01-24 05:42:44, user Samuel Flores wrote:

Where is text S1?

On 2021-01-24 05:36:21, user Pengyi Yang wrote:

This paper is now published in Molecular Systems Biology doi: 10.15252/msb.20199389

On 2021-01-23 13:40:41, user Drezen wrote:

The revised version of this paper, after reviewing, has been published in Communications Biology https://doi.org/10.1038/s42...

On 2021-01-22 22:22:26, user Researcher_111 wrote:

The research question of this paper is interesting, but I wished that the sample sizes were more than n=2 per treatment.

On 2021-01-22 19:08:45, user alejandro wrote:

1) If you go to the reference 12 ( we will put a link in the bibliography ) you will see there is a section for the P.1 Variant

https://www.cdc.gov/coronav...

P.1 lineage (a.k.a. 20J/501Y.V3)

The P.1 variant is a branch off the B.1.1.28 lineage that was first<br /> reported by the National Institute of Infectious Diseases (NIID) in Japan in<br /> four travelers from Brazil, sampled during routine screening at Haneda airport<br /> outside Tokyo…

Reference 17 should be removed, thank you for your comment

On 2021-01-22 13:42:42, user Gonzalo Bello Bentancor wrote:

I detected several errors in the description of the P.1 variant in the introduction section.

1) "Recently, a new variant SARS-CoV-2 from has been identified by scientist and clinicians in Brazil, and named P.1 variant or 20J/501Y.V3 Nextrain clade (12, 16, 17)".<br /> The references 12 and 17 do not describe the P.1 variant, but the B.1.1.7 lineage (ref 12) and a second B.1.1.28 clade circulating in Brazil (designated P.2) that harbors the E848K mutation but is not the P.1 variant (ref 17).

2) "An although the rate of infection and mortality of the P.1 variant is still unknown it has been identified in different areas in Brazil including the Amazonia and Rio de Janeiro, as well internationally in Japan (16, 17)."<br /> The variant P.1 was not detected in Brazil outside the state of Amazonas and the strain described in Rio de Janeiro in ref 17 was the P.2 variant.

3) "One reinfection has been linked to P.1 (E484K mutation) (22)."<br /> Reference 22 described a case of reinfection with the P.2 variant. The only case of reinfection with P.1 described so far was described here: https://virological.org/t/s...

Although both P.1 and P.2 variants evolved from the B.1.1.28 lineage, they correspond to independent emerging variants.

On 2021-01-22 17:50:16, user Fraser Lab wrote:

This work reports two atomic models of the main protease (Mpro) from SARS-CoV-2 using serial femto-second crystallography (SFX). The goal of the paper was to use this structural information to assist drug repurposing efforts against SARS-CoV-2. To accomplish this, the authors used computational docking and molecular dynamics simulations to investigate the molecular basis for binding of three previously reported Mpro inhibitors. There is a substantial (and growing) body of work describing the structure, function and inhibition of the main protease from SARS-CoV-2, but the claims of how the current results will become part of that effort are overstated in the manuscript.

The major result of this paper is the efficient use of the new macromolecular femtosecond crystallography setup at LCLS-II: two high resolution structures were reported from <5 hours of instrument time (1.9 and 2.1 Å). The major weaknesses of this paper stem from both the disconnected nature of the primary results and the rigor of some of the analyses. Specifically: 1) the reported structures have little relevance to drug repurposing efforts (the stated goal of the paper), 2) the differences between prior conventional structures and the analysis of the molecular dynamics simulations lack rigour, by lack of comparisons of electron densities and estimations of convergence/significance 3) the implications of the new Mpro models and/or the molecular dynamics simulations for inhibitor design are not articulated, 4) the compounds highlighted have been reported as promiscuous covalent inhibitors.

Some of the results described in this manuscript may be of interest to the SFX community, particularly if revised to more solidly compare to existing data. However, to maximize the relevance to the wider structural biology and SARS-CoV-2 research communities, the manuscript should be revised significantly.

Elaborating on point 2 above:

1. The manuscript does not present a fair comparison of structural information obtained from SFX versus traditional crystallography. Electron density maps are only presented for the SFX structures (e.g. Fig. 3B). Claims of structural differences would be stronger if the structural comparison was performed using crystals grown from the same conditions and with data processed/refined/modeled in a consistent way. Isomorphous FO-FO electron density maps would be particularly helpful.

2. The authors restrict their comparison to a single previously reported structure of Mpro (e.g. 6WQF). They should extend this analysis to the ~240 previously reported structures of Mpro from SARS-CoV-2. The majority of these structures were determined using cryo-crystallography and have ligands bound, however the comparison would still be informative, and is required for their claims of novelty. In particular, active site flexibility upon ligand binding has previously been characterized (e.g. Figure 1C of https://www.nature.com/arti..., Figure 4 of https://www.nature.com/arti... - it would be helpful to know whether the structural differences reported by Durdagi et al match those previously reported.

3. The structural differences involve alternative side conformations of non-catalytic residues in the active site (e.g. Figure 2B and D). Importantly, no specific link is articulated between the alternative conformations identified and Mpro function or inhibition. The authors suggest that the new structures will help modeling efforts (e.g. P5 L20, P11 L5). The authors present modeling efforts in this manuscript. How have the structural differences identified by the authors helped their modeling efforts (compared to the previously available structural information)? There are obvious computational analysis controls here that are missing.

4. The catalytic histidine is modeled with a flipped side chain in 7CWB compared to 7CWC, however, this difference is not mentioned in the manuscript. Are the authors confident in their modeling? Looking at previously reported apo coordinates (e.g. 6WQF, 6YB7), both conformations have been modeled. The conformation modeled in 7CWB seems more compelling, based on the ability of His41 to H-bond to Cys145, and the H-bond with Wat441. The authors claim that Wat441 (W5) plays a crucial role in catalysis (P5 L28). Flipping His41 disrupts the Wat441 H-bond network, however this is not mentioned. If the authors are confident in this difference, then they should summarize their reasons and the implications for Mpro function and inhibition.

5. A substantial and growing body of work (e.g. https://scripts.iucr.org/cg..., https://scripts.iucr.org/cg..., https://pubmed.ncbi.nlm.nih..., https://www.pnas.org/conten... deals with radiation damage in X-ray crystallography. Carefully designed experiments, coupled with advances in detector technology, mean that problems associated with radiation damage can be mitigated, even at room temperature. Indeed, the authors of a recent paper reporting the room temperature model of Mpro (Ref 27 in Durdagi et al - https://www.nature.com/arti... explicitly state their efforts to mitigate radiation damage: “We grew large crystals that could be used on a home source to ensure minimal radiation damage.” If Durdagi et al are suggesting that radiation damage was a problem with previously reported data, then they need to present evidence to support their claim. One option would be to collect cryogenic and room temperature data using identical crystallization conditions, then calculate isomorphous difference maps to test for radiation damage (clearly, careful experimental design is required, and problems of non-isomorphism may be encountered). Without this experiment, claims of issues with radiation damage at room temperature are not supported by evidence and should be removed.

6. Differences in dynamics were identified with simulations performed using 7CWB and 7CWC, despite the starting coordinates being almost identical. This strongly suggests that the simulations have not achieved equilibrium sampling. Perhaps the 7CWC model was simulated with the four residue addition at the N-terminus, and this can explain the differences? This should be mentioned in the main text.

7. Differences are also highlighted between the dynamics identified from simulations of 7CWB and a previously reported cryo model (6WQF) and room-temperature model (6Y2E). As with the previous point, these coordinates are almost identical, and if simulations of the same coordinates produce different results, how can the authors be confident that simulations with different compounds will produce useful results?

James Fraser and Galen Correy (UCSF)

On 2021-01-22 13:08:36, user harshit vaish wrote:

Here it is.<br /> https://febs.onlinelibrary.wiley.com/doi/10.1111/febs.15551

On 2021-01-22 11:46:16, user Iosif Koutagiar wrote:

I would like to notice the absence of my name (Iosif Koutagiar) from the list. Unfortunately there are some greek people with a not typical greek surname.

On 2021-01-22 10:52:05, user Pietro Roversi wrote:

The paper is out in an improved form at https://doi.org/10.1016/j.s...<br /> Thanks to the referees for their constructive criticism!

On 2021-01-22 09:02:28, user Richel Bilderbeek wrote:

As an extensive user of PureseqTM [4], I disagree with the 'accurate prediction'<br /> part of the title. For example, the nonsense protein sequence '!@#$%^&*()'<br /> is predicted to have a topology '0000000000' (i.e. it does not reside<br /> in the membrane) [1]. Due to this, I predict the selenocysteins in<br /> selenoproteins to be ignored as well [2]. The TRDD1_HUMAN <br /> protein with (indeed, very short sequence) 'EI' is predicted to<br /> have topology '[nothing]', instead of 00 [3].

I put these comments here, as I cannot reach the developers of PureseqTM<br /> via the PureseqTM email address, GitHub, nor their personal email address,<br /> since May 2020.

I posted bug reports at:

* [1] https://github.com/PureseqT...<br /> * [2] https://github.com/PureseqT...<br /> * [3] https://github.com/PureseqT...<br /> * [4] I wrote an R package to call it, called pureseqtmr

On 2021-01-22 08:31:43, user Xiao Huang wrote:

A beautiful story showing the longevity benefits of synNotch controlled CAR-T cells in solid tumor treatment. Congrats @KoleRoybal !!!

On 2021-01-22 03:01:42, user Ahmed wrote:

There is a typo in the abstract "uesad" I think it should be used!

On 2021-01-22 01:55:15, user Zhiyong Liu wrote:

We have used genetic approaches to show that, in the presence of cochlear outer hair cell (OHC) damage, adult cochlear supporting cells can be transformed into OHC-like cells by simultaneous expression of Atoh1 and Ikzf2. We are looking forward to receiving comments and suggestions about how to further move forward. Thanks

On 2021-01-22 01:39:54, user Alex wrote:

Hi, this was an insightful analysis, looking forward to reading more of your (all’s) work. My question is whether there was any discrepancy in the phase III trials in the UK vs. other nations? Is this exploration by deletion signature seen in any other viruses in circulation? Thanks!

On 2021-01-21 20:40:27, user Andrew Whittaker wrote:

A humble non virologist here but can we reconstruct Ratg13? I thought that maybe an even more useful exercise than reconstructing sars Cov 2 since we got plenty of that going around!

On 2021-01-21 20:28:12, user Nenad Bartoniček wrote:

Great work! However, the authors should clarify that 5' kits from 10X do not target 5' UTRs, but target 5' end of a 300-400 bp fragment that contains polyA.

On 2021-01-21 18:35:37, user ahmed wrote:

Office National Statistics Coronavirus (COVID-19) Infection Survey data is regularly updated<br /> and available here including estimates of COVID-19 cases to 02 January for England, regions of<br /> England and by cases compatible with the new variant (VOC 202012/01)...

On 2021-01-08 23:14:39, user Martin wrote:

Hello there, I think that it should be possible to fool the virus to mutate to its next variation more quickly in the lab to see what it transforms into next. By doing this you should be able to jump one step ahead to modify the vaccine to work against the next mutation. I think of virus' DNA/RNA as a computer program that must go down a certain route i.e. it has routines & subroutines when it is attacked in certain ways. By getting the virus to change to its next mutation quicker, we can get one or two jumps in front of it to produce a new vaccine to stop it before it mutates in the real time world situation.

On 2021-01-20 22:00:30, user Giorgio Gilestro wrote:

Can you please elucidate why you used Wuhan NCIB 43740568 as a control? That strain is basically extinct and it is not the one you are trying to protect from. You should have used something that carries D614G at the very least.

Also, the data clearly show a descending trend in almost all of the sera. Now, 16 is a very small number considered the amount the samples you certainly must have but even then, a decrease in 12 out of 16 is not something I would dismiss so easily: those are potentially 12/16 = 75% of vaccinated subject that will sport lower titre and, potentially, higher transmission capabilities.

On 2021-01-20 13:48:47, user Yaniv erlich wrote:

The paper has several problems:<br /> 1. The median calculation is off. According to Supp Table 1, the median is 0.76x and NOT 0.79x. That means that 50% of the vaccinated people loss nearly quarter of the titer activity in the presence of B.1.1.7.

1. The paper says in the abstract that "[t]he immune sera had equivalent neutralizing titers to both variants". Again, this is not correct. Twelve out of sixteen individuals have a titer ratio below one when comparing B.1.1.7 activity to Wuhan strain. A conservative a-parametric test (coin-toss) show that the reduction is statistical significant (p<0.05). It is wrong to say that they have "equivalent" titers.

2. The authors mention that 0.79x (sic) reduction is not biological significant. They do not report their pre-registered hypothesis about biological significance and do not contextualize this sentence. At which level they think that the reduction is alarming and why losing almost quarter of the activity is OK?

In addition, the important thing is that the variant already have some gains. It might not escape but it might poised to escape. All of these subtle points are not communicated when tens of millions and Governments all over the world consider this vaccine as the main exit strategy.

On 2021-01-20 19:38:42, user Michael Heskett wrote:

Nice work! Figure 6 appears to be missing from this draft.

On 2021-01-20 19:09:14, user Cerith Jones wrote:

This preprint has now been peer reviewed and published in Microbial Genomics (Microbiology Society) and is available, open access, here: https://www.microbiologyres...

On 2021-01-20 18:24:44, user Maxwell Neal wrote:

A peer-reviewed, revised version of this paper has been published by Nucleic Acids Research at https://doi.org/10.1093/nar....

On 2021-01-20 17:53:06, user Patrick Jodice wrote:

*error in abstract* should be 54,700 km of surveys, not 54.7 km. 50 km would not have been much of an effort : ) <br /> Apologies to my coauthors for not catching that prior to submission.

On 2021-01-20 16:51:21, user disqus_HVx5VNpDm7 wrote:

Published in FEBS Letters journal (https://doi.org/10.1002/187...

On 2021-01-20 13:28:17, user Bjarni Halldórsson wrote:

The relationship between the ACAN VNTR and height was also noted by us here: https://www.biorxiv.org/con...

On 2021-01-20 12:09:56, user S Ramasubramanian wrote:

It's very promising to see non injectable intra nasal single dose vaccine for covid-19, which will be boon to india..hope to see it in use very soon..

On 2021-01-20 02:07:12, user Filip Fratev wrote:

It is not so collegial to not cite previous studies on the topic and to present the results in a way that make the impression that this is the first in silico study about these mutations. Furthermore, it is not clear on the basis of which method these conclusions were drawn, just higher flexability? I can't see any numbers. There are also elementary questions such as why SB14 FF, which creates much larger fluctuations, and not SB19 FF was used? <br /> There are many ambiguities and for me this is a routine study.

On 2021-01-20 00:56:04, user Masami Fujiwara wrote:

This is an interesting topic. However, use of time as covariate is tricky. For example, if the last observations in a season of late and early reproducers are different by one month, then the duration over which survival is estimated is different by one month. If the annual survival rate is 0.7 then the monthly survival is 0.97. There can be 3% difference in their survival by changing the duration by one month. It is plausible that late reproducers have higher survival rate, but it is plausible that they all have the same survival rate, but you are simply estimating survival over shorter period (11 months vs. 12 months). I recommend you develop a model accounting for differences in time unit.

On 2021-01-19 23:27:45, user Sean wrote:

Can you explain why your paper has not been published?

On 2021-01-19 22:40:05, user Fraser Lab wrote:

This manuscript by Heyne et al., studies the binding affinity and fitness landscape of three trypsin homologs (Bovine trypsin, Bovine α-Chymotrypsin, Human Mesotrypsin) to the inhibitor BPTI, to get at the question of how mutations affect protein-protein interactions (PPI) of cognate and non-cognate enzymes and inhibitors. Importantly, the three trypsin homologs have widely different binding affinities for BPTI, with the cognate BPTI being the tightest. The authors use their previously developed yeast surface display platform to express BPTI variants and measure relative binding affinities to the trypsin homologs, and further define the fitness landscape of each interaction.

While cognate PPIs typically show high binding affinities, non-cognate PPIs often exhibit much weaker affinities even despite sharing structural similarity, underscoring that sequence plays a large role in the strength of an interaction. To understand how difference in sequence affects relative binding affinities, the authors chose to generate single and double mutants of the binding interface of BPTI, affinity sort BPTI/protease variants, and normalize the NGS-based enrichment values. Binding landscapes of BPTI in the presence of all three homologs showed that single and double mutations largely lead to a destabilization effect, with mutations to the cognate protein leading to on average a greater magnitude of destabilization than non-cognate. Perhaps unsurprisingly, mutations to the lowest affinity binder MT/BPTI show the greatest frequency of affinity-enhancing mutations and their positions are nicely shown structurally. We wonder, how often do mutations affect residues interacting with sequence differences between the non-cognate homologs? Are there trends where the differences in starting residue explain the difference?

Beyond single mutations, coupling energies were determined for double mutations of BPTI and defined as being additive, having positive epistasis, or having negative epistasis. For all three homologs, positive epistasis was the second most common effect of double mutations, suggesting an increase in fitness. Several questions which come to mind (what is a potential explanation for this result, especially in the case of BT/BPTI? Is there something unique about the positions in which negative or positive epistasis dominates coupling? How do specific affinity-enhancing single mutations structurally compare to double mutations which promote fitness? are there certain explanations for epistasis that are pervasive across positions, e.g charge swaps, or small-large substitutions?).

Overall, this study expands upon previous work to target a fundamental question of how sequence mutations affect binding affinities, and they do so in an excellent protein-protein interaction system. The major weakness is a lack of greater dissection of specific BPTI mutations and their chemical interactions with the associated enzyme for both destabilizing and affinity-enhancing interactions. We are also excited by the possibility for future papers to mutate the interface from the perspective of the trypsin homologs and to look at epistasis across the interface.

Minor comments:<br /> “we employed a recently developed by our group strategy “ - we employed a strategy recently developed by our group<br /> Change color scheme to be more color blind sensitive <br /> Label axis scales of figure 1C <br /> Show the full heat maps for figure 3 in the supplement <br /> Were double mutations analyzed for the YSD assay? Is there a heat map of this?<br /> Label figure 4 plots with homolog names<br /> Change color scale bar on fig 1 completely or at least so it's more intuitive with the other figure scales bars

James Fraser and Gabriella Estevam (UCSF)

On 2021-01-19 22:24:48, user Tauras wrote:

Very interesting work and a cool idea! However, I don't see much detail about the PRSs used. Knowing the trait heritability, variance explained by the PRS, and seeing a leave-k-out cross-validation would be very helpful in evaluating the the results. For example, maybe TB doesn't display a signal because there is little genetic variance or the PRS explains a small proportion of the genetic variance.

Furthermore, there's no discussion about population turnover which we know plays a major role in changing allele frequencies at the time scales that are being considered. Immigration into Europe during the early Neolithic may explain these effects, especially in how some PRSs appear discontinuous (the pre-neolithic line doesn't meet the post-neolithic line). Changes during the neolithic/modern times may also be driven by migration. I'd be very hesitant to say "adaptation" when it can be more parsimoniously explained by gene flow. Maybe it's possible to explicitly model ancestry proportions as well as time in the linear models?

On 2021-01-19 19:53:09, user Vatsan Raman wrote:

We thank the reviewer for their thoughtful evaluation, commentary, and suggestions provided. The final published version in PNAS fully addressed all their comments.

A detailed point-by-point response was submitted to the journal.

We substantially revised the manuscript and added eight new supplementary figures to address concerns and clarify key points.

These salient changes are summarized below:

1. We extensively employing statistical tests to validate our conclusions on conservation of allosteric hotspots, relationship between centrality score and location of allosteric hotspots, and ranking of dead variant based on rescuability.
2. We have provided detailed clarification of differences between the disrupt-and-restore experiment (Fig. 1) and rescuability experiment (Fig. 2), and harmonized the data representation in both figures
3. We demonstrate that our conclusions on regions of importance for allosteric signaling is robust to changes in the quantitative thresholds defining a hotspot and classifying a residue as a dead variant.
4. We validate the molecular dynamics simulations by demonstrating agreement in small-angle X-ray scattering profiles from MD ensembles with experimental data.

On 2021-01-19 17:07:01, user Martin Styner wrote:

Overall very nice work. The only potential worry I have is that sulcal depth is used by FreeSurfer (the software that generates the cortical surfaces and measurements) to establish the location-wise correspondence across subjects. It is thus expected that sulcal depth measurements have a significantly higher bias and methodologically-induced tighter distribution as compared to cortical thickness and surface area, which might explain in part the observed effects. It would be important to see whether other, comparatively unbiased cortical folding measures (such as local gyrification index) can confirm the patterns observed here.

On 2021-01-18 18:15:16, user mauromanassi wrote:

Nice work! You may want to have a look at Pizzagalli et el 2020 https://www.nature.com/arti...

On 2021-01-19 16:53:03, user antonio_j_p_rez wrote:

It has been already publish in Briefings in Bioinformatics:<br /> https://academic.oup.com/bi...

We hope that some of the proposed regulators can be useful as a putative target in the fighting against SARS-CoV-2.

On 2021-01-19 15:51:02, user Martin R. Smith wrote:

This is an interesting article; I wonder whether there is a good justification for your choice of the Robinson–Foulds distance? In particular, its discrete nature and narrow range makes me a little nervous of using confidence intervals, particularly if generated from random trees (most of which will exhibit a near-maximum RF value). I have explored some alternative measures, which might be more robust in this context, at https://doi.org/10.1093/bio... (Smith 2020, Bioinformatics)

On 2021-01-19 09:39:52, user Andreas Ritter wrote:

Dear colleagues,<br /> Congratulations for this very nice pre-print.

Me and my lab worked quite some time on a similar topic.<br /> Since Miyamoto et al. showed in 2015 that KIF2C could be moderatly involved in the regulation of ciliogenesis, we tried to corroborate their data. <br /> We used siRNA, GFP-MCAK overexpression constructs, stable CRISPR dCas9 i/a system and looked for ciliated cells (with starvation/without starvation), cilia length, cilia stability, Cilia MT-modifications etc., but we can’t find a single parameter which was significantly changed in HeLa or hTERT RPE-1 cells on any of the above-mentioned conditions.

Do you have a quantification, how many folds you overexpressed KIF2C in these cells?

Did you verify these results in other cell lines?

Is it possible that SCFFbxw5 also stabilizes KIF2A on the basal body, which is known to have a huge impact on ciliogenesis / cilia length?

Thanks again for sharing these interesting results.

Best regards,<br /> Andreas Ritter

On 2021-01-18 22:57:41, user Charles Warden wrote:

Hi,

Thank you for posting this pre-print.

I think Bowtie1 can work well with miRNA-Seq data, but you have to trim out the adapter first.

I don't believe that I saw a step in the methods describing adapter trimming before alignment. Did I miss something?

If not, would it be possible to either add comparisons to show the effect of trimming, or possibly replace the Bowtie1 statistics include an upstream trimming step? If you are starting with 51 bp or longer reads, then I think that could be relevant.

Thank You,<br /> Charles

On 2021-01-18 14:35:44, user Paul Macklin wrote:

Published at:

https://www.nature.com/arti...

On 2021-01-07 18:55:53, user Paul Macklin wrote:

In press at Scientific Reports (2021)

On 2021-01-18 08:53:01, user The_Zman wrote:

There's an error in the liganddock.xml protocol file, there's a missing closing tag for <scorefxns>

On 2021-01-18 02:17:34, user Steven Hart wrote:

I'm not exactly seeing how this is any different than what I published in 2014....<br /> https://pubmed.ncbi.nlm.nih...