On 2021-01-04 15:07:33, user Дмитрий Карабанов wrote:

Karabanov D.P., Pavlov D.D., Bazarov M.I., Borovikova E.A., Gerasimov Yu.V., Kodukhova Yu.V., Smirnov A.K., Stolbunov I.A. Alien species of fish in the littoral of Volga and Kama reservoirs (Results of complex expeditions of IBIW RAS in 2005–2017) // Transactions of IBIW RAS. 2018. Issue 82(85). P. 67-80.

On 2021-01-04 08:07:16, user Blue Horizon wrote:

Removing this paper is neither the wise nor scientific way of handling it (censorship never is). Rationally and evidence-based tearing it apart is. If neccessary explain in relatable terms to the public why this is irrelevant and/or nonsensical. Yes this appears to be a highy speculative low quality piece of work. But let's just assume for a second it was a valid assumption and the sars-cov2 virus could integrate into the host genome. First of all this would not be a sensational result, other viruses are doing this for a long time and not always with negative consequences for the host. Second: if this was the case it would be an additional argument in favor of vaccination because the apparent problem would be the virus integrating into the genome, not the (in itself harmless) spike protein alone (as in the vaccines in question). And the longer you let the virus roam and replicate (naturally) in the host, the higher the likelihood of it reverse transcribing into the host genome. Also the main scare-argument of anti-vaxxers is the speculative claim of potential carcinogenicity<br /> while there is no evidence of such in regards to this specific process of sequence integration.

On 2020-12-31 14:32:19, user Berry Van Rossum wrote:

Dear authors, while not being an expert in this field, thus I am probably mistaken here, but think I see a misalignment in the base-pair coding in example fig1c. The fifth one, being T in the human chromosoom, links to a G in the 92nt mapped SARS-COV-2 genome. Again, I am no expert in this field, but maybe something to verify? With highest regards, Berry van Rossum, Organic Chemist, The Netherlands.

On 2020-12-28 09:41:45, user Alberto Villena wrote:

At the end of the Results, they say: “In summary, our results show induced LINE-1 expression in cells stressed by viral infection or exposed to cytokines, SUGGESTING a molecular mechanism for SARS-CoV-2 retro-integration in human cells.”

And then, in the first paragraph of the Discussion: “In this study, we showed evidence that SARS-CoV-2 RNAs CAN be reverse-transcribed and integrated into the human genome...”

How it is possible to go from “suggesting” to “can”?

I would suggest that recurrent PCR positive results would also come from stress granules that accumulated mRNA when produced in excessive amounts, which is a typical result of viral infection and replication. Stress granules are quite resistant and may remain in the tissues for long times.

On 2020-12-22 16:14:17, user Melissa Booth@The Science Comm wrote:

This paper should be removed from this PRE-PRINT (non-peer-reviewed) server. The experiments used in this study do NOT address the question that the authors’ are posing about integration of genomic material from SARS-CoV-2 into host (human) cells.

Regardless of the authors’ intent, the premature posting of this study appears to be pandemic band-wagoning, or worse, scientific grandstanding. The intent of pre-print servers is to make the iterative nature of human scientific endeavor more inclusive and transparent. However, the information ecosystems that we all share are polluted by social media algorithms and malicious actors which propagate misinformation faster than facts. As scientists, we must consider how we interact with contemporary information systems.

As a microbiologist and molecular geneticist, it is clear to me that the experiments in this PREPRINT (not peer-reviewed) paper, do not support the claims in the title.

Chimeric sequence reads that the researchers found in the sequence databases are likely artifacts from the preparation of the RNA libraries. These chimera artifacts are a common phenomenon in total RNA sequence library construction from complex samples whether the source material is from humans, soil, sewage, ocean water, etc., and these artifacts end up in sequence databases. The other lab bench experiments DO NOT show that SARS-CoV-2 RNA is reverse transcribed to DNA, transported into the nucleus and then integrated into the host genome under NORMAL conditions. However, there are assays that could answer the question about viral integration. The authors could collect samples from infected patients that are still shedding virus but are non-infectious (as they mention in their summary) and perform Southern Blot analysis to determine if viral sequences have indeed been integrated into the host genome. And ultimately, IF the researchers find integration under normal conditions, the next questions follow: Are infected cells persistent? Do these integrated elements propagate in host cells? These are the questions that get to their hypothesis about purported viral integration elements being responsible for persistent detection of virus in non-infectious, post-COVID patients.

P.S. If the authors do not have clearance/desire for human clinical research, how about looking for integration in minks or other animals that are currently suffering from SARS-CoV-2 infections?

On 2020-12-20 19:53:05, user Marie-Louise Hammarskjold wrote:

If there ever was a preprint that should be deleted, it is this one! It was irresponsible to even put it up as a preprint, considering the complete lack of relevant evidence. This is now being used by some to spread doubts about the new vaccines. If you want to hear a much longer explanation, listen to the latest episode of TWiV #696.

On 2020-12-20 15:05:12, user andreagradidge wrote:

Please see https://www.microbe.tv/twiv... for explanation, debunk, plus a really good scold for lack of data.

On 2020-12-18 17:33:30, user Leandro de Mattos Pereira wrote:

In my opinion, this type of research that involves the genetic manipulation of sarcov-2 should be banned, given the little knowledge we have of genetic recombination between sarcov-2 and exogenous sequences is yet limited. The ethics committee should not approve this type of exploratory research using vectors with reverse transcriptase together with cells infected with sarcov-2.

On 2020-12-16 14:27:27, user Albert Heim wrote:

As a clinical virologist I am suprised about the introduction and background of the study which resulted in a (form my view) peculiar hypothesis (genomic integration of SARS-CoV-2). I don't want to comment on the way this hypothesis was tested, merely on its background.<br /> Long term detection (several weeks to a few months) of any respiratory virus (e.g. Rhinovirus, Influenzavirus) after an acute infection is "business as usual". However, systematic follow up testing of these patients was not usual, but if a patient was diagnosed with Flu A in January and comes down with another respiratory infection in March, it is not surprising to detect e.g. HMPV and Flu A in March. If the analysis is done with real time PCR, you will find e.g. Ct 18 for HMPV and CT 37 for Flu A, so the diagnosis in March is "HMPV infection" and the detected Flu A is a little bit "left overs" from January. <br /> In general: If you use multiplex PCR diagnostics about 5 to 10% of all diagnostic respiratory samples can be positive for two or three viruses, usually one of these is highly positive (the real culprit) and the other(s) are found close to the LOD (left overs of previous infections). <br /> In COVID-19 patients, we follow up virus loads in respiratory specimens. These decline rapidly with convalescence but remain at levels close to the LOD (and therefore intermittently positive) for many weeks. This is an anticipated result as with other respiratory viruses. The respiratory tract contains hairs, mucus, tonsillary clefts, sinus and many other structures where a little bit of any "dirt" (e.g. a few of the billions of capsids produced in an infection) can persist. Even on "clean" surfaces (e.g. stainless steel) of a laboratory, you can find these viral contaminations by highly sensitive PCR if not meticulous decontamination measures were performed. No one would however build a hypothesis from this finding that SARS-CoV-2 has a specific mechansm to perist on (or: integrate in) stainless steel. Such a PCR result merely shows imperfect decontamination of a surface (but there are no decontamination at all done in the respiratory tract, neither brushing with SDS nor with sodium hypochloride nor flushing with fresh water as the least cleaning measure). Anyway, these results do not show infectious particles. Even if a few of these capsids were (theoretically) infectious, these were too few to cause an infection.

On 2020-12-15 13:13:04, user Χρίστος Δαγρές wrote:

The authors cited Bo Yuan et al ("Recurrence of positive SARS-CoV-2 viral RNA in recovered COVID-19 patients during medical isolation observation") where the case of approx. 20 patients from China were re-tested positive after they had recovered from COVID-19. <br /> The authors suggest as a possible explanation the possibility that parts of SARS-CoV-2 RNA were reverse transcribed in human genome and then they were expressed later leading to positive PCR-tests.

What's interesting though in the paper of Bo Yuan et al is that none of the 39 pts with severe COVID-19 symptoms were re-tested positive. Given that pts with severe clinical symptoms are expected to have a higher viral load, wouldn't the authors expect that patients with severe symptoms should have higher risk for SARS-CoV-2 RNA intergration in their genome and thus, lead to higher re-positive rates?

On 2020-12-15 11:05:02, user Dominik wrote:

As others pointed out, this paper is seriously flawed in many aspects and should be retracted, especially considering that many people are afraid of a new type of vaccine (mRNA) and conspiracy theorists certainly will take this paper to "proof" that mRNA vaccines can in fact alter your genetic code.

On 2020-12-15 04:33:03, user Cedric Feschotte wrote:

The authors tackle an important question, but the data presented in this preprint are unconvincing and insufficient to claim SARS-CoV-2 is reverse-transcribed and integrated in the human genome. Others in this thread have already pointed at some of the flaws, but here is my own take.

To prove retrotransposition events, the standard in the field is to isolate and report the sequence of the integrants along with flanking genomic sequences (junction sequences spanning both viral and flanking DNA). This can be achieved using a number of approaches, including a variety of PCR-based assays (inverse, vectorette, adapter-ligation, Alu-anchored, etc.), whole genome sequencing (ideally using long reads), or capture high-throughput sequencing (e.g. akin to RC-seq). None of these approaches is flawless, so multiple, orthogonal approaches are requisite to draw firm conclusions. Here, the authors do not report any junction sequences of integrants or the sites of chromosomal integration.

Obtaining junction sequences is critical because it provides not only validation of chromosomal integration, but also important clues about the mechanism of integration. If LINE1 (L1) is involved one expect to see: target site duplications (short direct repeats flanking integrant), integration at preferred L1 endonuclease cleavage site (TTTT/AA), polyA tail at the 3’ end (or chimera with the 3’ end of endogenous L1/Alu). The authors suggest that the L1 machinery is involved in the alleged retrotransposition events, but do no report any of the hallmarks of L1-mediated retrotransposition. Again, this is because they do not report sequences for any integration events, neither from infected patient nor cell culture experiments. qPCR and RNA-FISH are inadequate approaches to prove genomic integration.

There are pitfalls with the analysis of chimeric reads in Fig. 1 that the authors can and should address. These reads seem exceedingly rare and could represent artifacts of RNA-seq library prep or aberrant template-switching events from Cov-2 subgenomic RNAs to cellular mRNAs. The latter would not be surprising because coronaviruses use a process of discontinuous transcription during replication involving template switching. Both library prep artifacts and template switching mechanisms predict that SARS-CoV-2 RNA would form chimeras with human mRNAs and therefore largely exonic sequences (which derive from only 1-2% of the human genome sequence). By contrast, if chimeric RNAs originate from readthrough transcription of integrated SARS-Cov-2 sequences, as the authors evoke, they would most likely form chimera with a variety of inter and intragenic human sequences. The authors should provide a more detailed analysis of the chimeric transcripts and the host sequences involved. In any case, the detection of human-SARS chimeric RNAs, even if substantiated, does not constitute evidence for viral reverse transcription or integration into the genome.

Experiments in cell culture (Fig 2) with L1 overexpression vectors are highly artificial and no more convincing than those in human patient samples: no integrants are isolated/sequenced and they lack important controls (e.g. RT mutant constructs, which are available). While these experiments would be important in establishing proof-of-principle that retrotransposition of SARS-CoV-2 RNA is possible in a cell culture system, of course it would still be premature to conclude that the phenomenon occurs in infected individuals and has clinical relevance. Thus, even if the results in cell lines were to be substantiated, the title should reflect the in vitro nature of the work and the abstract should state explicitly that in vivo integration of SARS-CoV-2 sequences remains a matter of speculation.

On 2020-12-15 00:07:54, user bahaa wrote:

I have some questions to the author regarding the samples and procedures of collection and analysis of these data to be sold in front of discussion and evidence bases article

On 2020-12-14 23:38:15, user Michael Eisen wrote:

I am skeptical of these claims, and surprised by the timing of this paper's release.

This is obviously a topic of great interest and extreme import, given the release of this preprint right as an RNA based COVID vaccine is entering wide distribution and another is on the way. The authors have raised the possibility that host retrotransposes have to potential to integrate viral RNAs into the host genome (an unsurprising result) but have not demonstrated that this occurs with appreciable frequency in infected individuals or that it has any clinical relevance.

The idea that endogenous RTs could integrate viral RNAs into the host genome is not surprising. Indeed it is seems almost certain that it happens at at least low frequency given the presence of intronless paralogs and pseudogenes. So the experimental observations that it can happen under ectopic conditions isn't of significant clinical relevance.

The real question is whether this is a rare curiosity, or if it is sufficiently common to warrant public health concern. And here the only evidence presented is the presence of chimeric (human:COVID) reads in a handful of infected cell lines and a couple of clinical samples. The problem with this observation, as the authors allude to but only passingly address, is that chimeric reads are a well-known artifact in RNA sequencing data. And several of the observations - the increased frequency of such reads with increasing viral loads, and the bias of such reads towards the most abundant viral RNAs - are exactly what you'd expect if they were artifacts. There are a number of things the authors could do to rule this possibility out and make a more compelling case, but none of them were presented here.

Given the absence of any other data to support the clinical relevance of this observation, all of the speculation about how this might impact testing, vaccination, drug screening etc.. and how this might be an adaptive strategy to store viral antigens to guard against future infections is pure speculation and should be treated as such by anyone with interest in the topic.

It is unfortunate that a paper is making highly speculative yet frightening claims of COVID integration into the human genome was released right as an RNA vaccine is being introduced to the population, and amidst well-known, and widespread, opposition to vaccination. Obviously, if the authors feel they possess evidence of clinical relevance, it is their duty to release it as expediently as possible. However, the paper makes it clear that even the authors agree they have not proven their case. Given that this is one of those rare circumstance where a scientific result has the potential to immediately impact public behavior in a way that undermines critical public health measures, I think both more thorough experiments and analyses, and more caution, were warranted.

On 2020-12-14 22:35:27, user Stuart wrote:

This preprint has the unfortunate character of having a title that over-reaches the data presented. The model systems are contrived, and the central data are unconvincing.

On 2020-12-14 22:09:59, user Stylianos Antonarakis wrote:

The data are not sufficient to support the conclusions. The authors should show genomic DNA sequencing with the integration site. And also the fraction of somatic cells with the integration.

On 2020-12-14 18:30:37, user Rachael Tarlinton wrote:

As others with more experience in Bio-informatics than me have pointed out the chimeric reads reported here are likely an artifact of the sequencing method. The authors have also used a very artificial cell culture system to specifically drive the phenomenon they were seeking and even then have not actually demonstrated integration of virus into the genome (this would as others have pointed out require sequencing of the DNA of the cells rather than the RNA to capture the integration sites between cellular and viral DNA). <br /> There does seem to be a case (in general) that viral infections in cells lead to increased expression of retroelements (we have reported on this ourselves) but in no case that I am aware of has anyone demonstrated that this then leads to integration of the virus (or the retroelement) into the genome. In people the accumulation of new retroelement integrations is a very rare occurrence indeed (these types of evolutionary events are measured in millions of years, not an individuals life span) . This is not the case in species with more recent and active retroviruses (such as pigs, sheep, koalas, mice, chickens) but even in those species they do not typically pick up or insert sequences from other virus classes (these types of events are even rarer than new retroelement insertions). The mechanisms speculated here have also never been known to occur with HIV infections in people (an incredibly well studied retroviral infection). <br /> This paper certainly does not demonstrate that SARs-Cov-2 is or is likely to become integrated in a human genome.

On 2020-12-14 17:47:26, user Kevin McKernan wrote:

This is an important topic for qPCR fidelity and our ability to discern infectious versus non-infectious patients.

The majority of the qPCR assays are targeting the N gene and as a result we have an atrocious process of quarantining society on non-infectious qPCR positivity and this work may shed important light on this egregious human rights problem.

It would be helpful to know if the sgRNA in DMVs persists longer than chromosomal integrations. It may help the general public to speak about epithelial cell turn over as I have seen several people mistake these integration events as a permanent addition to their germline when these cells likely turn over in a few weeks to months.

Some discussion on SARs-CoV-2 long persistence in the GI where there is high cell turn over but not successful viral culture in Vero cells may also be in order.

Some discussion on the propensity of Spike protein mRNA in vaccines and their capacity to do or not do this may help address the public confusion on the applicability of this work to mRNA vaccines.

Despite other comments on this thread, the authors do provide evidence of genomic integration with FISH and chromosomal isolations. Their comments would be more productive detailing why these methods are unconvincing.

To nevertheless address their concerns, the manuscript would be enhanced with more scrutiny on the RNAseq methods in particular the ligation methods used to make these libraries to rule out Chimera formation in RNA-Seq. Perhaps RNase and DNase studies to prove the DNA integrations are not artifacts of library construction methods?

The integration events correlate nicely with Kim et al sgRNA expression patterns. This biological signal likely rules out random chimeric formations but might support higher copy number sgRNAs being more prone to chimeric formation in RNA-Seq libraries.

Calls to censors this are unscientific and political.

There is a typo on line 142 with SRAs instead of SARs.

On 2020-12-14 16:00:32, user Jim Woodgett wrote:

Since this preprint has already attracted the attention of the anti-vaccine crowd, it is important to note that the evidence shown for reverse transcription of SARS-CoV2 into the genome is a proof of principal that used some extraordinary and non-natural steps to achieve in isolated cells. This included specific over-expression of exogenous reverse transcriptase derived from HIV1 and LINE-1. The strength of the scientific evidence for direct integration is not entirely compelling as artifactual formation of chimeras between genomic fragments and the viral sequences during library generation isn't excluded. There are no data on whether there are common integration sites. Moreover, as the authors state in their discussion (page 7, line 146), even under these artificially forced conditions, "The retro-inserted SRAS-CoV-2 (sic) sequences are most likely sub-genomic fragments, as the integration junctions are mostly enriched at the N sequence (Fig. 1d-e), excluding the production of infectious virus." Indeed, their primary message of the implications of the results is that this may account for examples of PCR tests remaining positive long after infection. There's no direct evidence for this being a mechanism (rather than, for example, low level re-infection, trapping of viral debris, etc.).

Before coming to the conclusion that SARS-CoV2 can be incorporated into the genome under non-laboratory forced conditions, there needs to be evidence presented of such integration in cells derived from SARS-CoV2 infected patients with careful control of the possibility of contamination. Moreover, it really should be clarified that RNA based vaccines such as Pfizer/BioNTech and Moderna pose no risk in terms of genomic incorporation as they express, transiently, an RNA that encodes a single viral gene (Spike) with no associated genomic expression sequences. This is part of their intrinsic design for safety.

On 2020-12-14 15:49:23, user Dan Harkness wrote:

It's an intriguing observation. It would have been nice to see some longitudinal data. Is this a persistent or transient event? It seems like LINE-1 up-regulation is associated with "disease" via general genome instability perhaps mediated by its RT activity. This would make sense if these datasets came from productively infected individuals. What's missing is the follow up data e.g. 1-week, 4-week, 16-week post-infection, to demonstrate and quantify the persistence. The counter-hypothesis is that of the 100s of millions of cells that contributed to these single-snapshot sequencing libraries, there are some reads from a group of sick cells who are being actively cleared from the body via standard immune response. Is this particular group of cells the ones with the integrated COVID-19 sequences? Utilizing single-cell RNA and DNA approaches - in addition to follow-up time-points - would make a very elegant dataset. Cheers.

On 2020-12-14 15:47:40, user Jonathan Sebat wrote:

The evidence supporting the claims is not compelling and consists of (1) observation of chimeric transcripts of SARS-CoV-2 (a common artifact of RNA-Seq) and (2) correlation (not causation) of LINE element expression with infection. Weak IMO. The genomic sequences could be inferred from the chimeras and then confirmed. However there is no evidence of the actual genomic integration sites.

On 2020-12-14 15:23:10, user Ben wrote:

@reporters<br /> Please read the abstract (or even just some tweets from scientists) before you write your report. The title is overstated and walked back immediately in the abstract. Please be mindful of your influence.

On 2020-12-14 08:37:18, user Mick Watson wrote:

The evidence provided in the paper does not support the conclusions, and the most likely explanation is PCR artefacts. I highly recommend this preprint be taken down.

On 2020-12-13 23:49:19, user marius w wrote:

Can you show that the chimeric reads are with intron or intergenic sequences, and not only with exons?

On 2020-12-13 23:25:13, user Alex Crits-Christoph wrote:

Could the authors release a BAM or list of mapped reads (including read quality information and mapping information) of the chimeric sequences they show? Ideally a BAM filtered to just chimeric sequences would be good. This would help evaluate whether these sequencing reads represent real biological events.

On 2021-01-04 07:58:33, user Robert wrote:

Dear Gabriele, thanks for sharing this pre-print! I assume (because it's a preprint...) you also want to discuss your findings, and I would like to enter that discussion.

First and foremost, I would like to thank you for posting your findings! I was not aware of the geometric relationship you highlight, and also you share data about kinetic measurements of enzymes in your manuscript. You provided a graphical interface to some calculations, that I am sure is helpful for people doing that calculations regularly. Thanks!

I would like to hook into the geometric relationship first: you present it as a viable alternative other fitting algorithms. Could you elaborate how it is different from conventional linear fitting, i.e. applying the relationship often-presented-as "y = a*x + b"?

Further, the Lineweaver-Burk plotting is known for introducing errors of variable size into the parameters, depending on the location of measurement points; this can be greatly shown in your geometric elucidation, because the tangens function will react very sensitively to some points, and less sensitive to other combinations. Good reviews of the Lineweaver-Burk "problems" are for example found by Athel Cornish-Bowden (and discussed together with other plot forms).

I fear that your algorithm will produce -- for some experimental set-ups, not for all! -- parameters with very large deviation from the "true" ones. That is why non-linear regression (i.e. direct fitting of the data to the actual function, without any linearization steps) is actually a good thing.

What I value very much is that you present (probably new?) data about aldehyde dehydrogenase and xanthine oxidase. You also share the raw data, which I value even more! Could you also provide some methodological details about how you generated those values? Being two-substrate enzymes, e.g. the concentration of the non-varied substrate would be interesting, but of course also the exact enzyme identity, etc. You might find the STRENDA guidelines a helpful read, they present things to report to make the enzymology field more reproducible: https://www.beilstein-insti...

Looking forward to enter a discussion with you, Robert

On 2021-01-03 22:23:36, user Nichollas Scott wrote:

Hi Philipp

Really nice paper, just had two comments

The difference in size of biotin vs non-biotinylated peptides) You guys see a significant difference here but are you sure thats not an artefact of the standard MQ settings limiting the size of the peptides to 5000 Da? As the Biotinylated peptides are +226 Da heavier thats about two amino acids and maybe just skewing the observed peptide distribution down by ~2 amino acids.

low id rate of NHS-SS-Biotin) Thats super interesting that the Id rate is so low here, have you checked using an open search if something strange/unexpected has formed?

Cheers<br /> Nick Scott

On 2021-01-03 21:06:37, user Stuart wrote:

From figure S2 panel A: does it seem plausible to obtain an R² = 0.81 from these data?<br /> https://twitter.com/soupvec...

On 2020-12-31 08:29:23, user Callum J.C Parr wrote:

If the escape variant could be neutralized by other convalescent sera is it naive to say that may not be such an issue at population level as we are all going to have unique polyclonal Abs raised either from natural infection or from immunization.

On 2020-12-30 01:04:52, user Manuel Ricci wrote:

This can confirm that these functional mutations can happen in long term infections under a selective pressure applied by antiviral drugs, plasma, etc...not in normal infections that resolve, for the best or the worst, within 30 day

On 2021-01-03 12:04:09, user Carsten Schradin wrote:

Published version here

https://www.thebhs.org/publ...

On 2021-01-01 06:20:38, user Raghu Parthasarathy wrote:

Isn't it very well known that, for example, smelling perfume across a room is not due to diffusion -- far too slow for any reasonable diffusion coefficient -- but rather due to convection and other active flows?

On 2020-12-31 19:26:40, user Mirosław Grzesik wrote:

Comments on kinetic and equilibrium data descripttion:

The given function is either linear or non-linear. All functions/equations used in the work to describe kinetic and equilibrium data, except the Nernst (Henry) isotherm, are nonlinear. The use of the terms "linear form" or "linearized form" in relation to nonlinear functions (9) and (10) is unjustified. It is also difficult to accept the terms "non-linear form of linear (Nernst)" and "linear form of Langmuir ......" in Table 1.<br /> The only isotherm that can be used to describe the equilibrium data illustrated in Fig.9a is the Nernst (Henry) isotherm. The use of other<br /> isotherms, even for comparative purposes, is unjustified. As a result of the fit, it is sufficient to enter the value of the Klinear constant and the value of the coefficient of determination R2. All other results in<br /> Table 1 are unnecessary. In the future, it is worth considering extending the research for larger Co values. Only then will it be<br /> possible to describe the equilibrium data using isotherms with an upper limit (Langmuir, Langmuir-Freundlich, Jovanovic etc.) and to determine the value of the maximum adsorption capacity. This is impossible for the current data.<br /> The only function that can be associated with the Nernst (Henry) linear isotherm in terms of physicochemistry is the exponential function: da/dt=ae(1-exp(-kt)), a=(Co-C)/Co.It results from the mass balance from which the Nernst isotherm can also be obtained. The use of the other two functions: hyperbolic and power is therefore<br /> unjustified. <br /> All the results presented in Table 2 are unreliable. The negative values ​​of the lumped parameter k1 are unreliable and, moreover, they contradict the slope of the straight lines in Fig.10b. The qecal values ​​for the PFO, which should be approximately equal to the qeexp value, are unbelievable. All R2 values ​​calculated on the basis of graphical methods are unreliable. I advise you to remove all results from Table 2 and Figures 10bcd. I also advise you to remove the false conclusion about the association of PSO with chemisorption.

I propose to use nonlinear methods, commonly known as nonlinear regression, to determine the parameters of the exponential function. It also seems that the experimental points for long times should be omitted in the calculations. The slow increase in q in this time range is probably the result of adsorbent particles decay due to long-term mechanical impact. This behavior is not described by standard functions. I would also consider supplementing the kinetic tests with points for t<16 min. In addition, R2 values ​​should be determined for data in the q vs t coordinate system, not in nonlinearly transformed systems such as ln(qe-q) vs t, t/q vs t and q vs t^1/2. Only then can we avoid serious mistakes and erroneous conclusions based on them.

On 2020-12-31 12:03:40, user Divon Lan wrote:

What an excellent paper! This is really state of the art in genomic compression. Also, thanks for pointing out the files that were rejected by Genozip: I fixed these issues (they were mostly due to the number of INFO subfields exceeding Genozip's limit) and also corrected the issue that caused the low compression ratio on AT. All files should compress now.

I have packaged these fixes as Genozip 10.0 and pushed it to https://github.com/divonlan... and Conda.

Other comments related to Genozip usage:<br /> 1. I would advise to use --gtshark only for files where samples have no other subfields but GT - in other cases --gtshark's contribution to the compression ratio is expected to be minor while its performance penalty is significant. <br /> 2. It would be nice to see a benchmark on a more realistic compute environment, eg 32 or 64 cores, without limiting threads. On Genozip's side, it is designed with an explicit objective of core-scalability and has been tested to scale up to 128 cores. I am very curious to see how VCFShark compares.

There's nothing like some friendly competition to advance science :) Well done!

On 2020-12-30 17:16:47, user Graham Dellaire wrote:

There is a lot in this paper to digest and like, including the CRISPR knock-in of EYFP into the PML gene using the same strategy and guide RNA as in Pinder et al., 2015 NAR PMID: 26429972 (i.e. PML-gRNA2), which could be cited to indicate this approach works well and doesn't compromise PML function or protein localizations to PML bodies.

It was also great to see so many BioID approaches employed, in particular the dox-inducible system and split TurboID. However as someone working on PML for nearly 20 years, I found the paper was light on previous PML and SUMO interaction literature and citations. This is an important point as it gives the impression that all the interactions disclosed in the pre-print are new and doesn't provide citations for known interactions. In particular, several PML-interactions are already known and described in the literature but these studies are not acknowledged. These include (non-exhaustive list):

*ARID3B *ARID3A is a known interactor: Fukuyo Y (2004)<br /> CREBBP (Doucas V 1999, Zhong S 1999, Matsuzaki K 2003)<br /> BLM (Bischof et al., 2001 JCB)<br /> IFI16 (Diner BA 2015, Merkl P 2018)<br /> JUN (Vallian S 1998, Yasuda S 1999, Salomoni P 2005) <br /> LMNA (Roux KJ 2012, Serebryannyy LA 2019)<br /> PIAS1 (Brown et al., 2016 J. Virol)<br /> PIAS2 (Cuchet-Lourenco D 2011, Rabellino A et al., 2012 Cancer Res.)<br /> RPA1 (Boe et al. 2006 JCS; Dellaire et al. 2006 JCB)<br /> SLX4 (González-Prieto R et al., 2015 EMBO Rep )<br /> TRIM24 (Zhon S 1999) <br /> TRIM28*(KAP1) *PMLNB adjacent foci (Briers et al., 2009 JCS)<br /> UBC9 (Duprez 1999, Maroui 2018 and MANY more)

Perhaps a table could be included with all the high-confidence "hits" shown with a column for citations for previous work that have found the same interactions/localization to PML bodies, as well as links to BioGrid, Nuclear Protein Database (npd.hgu.mrc.ac.uk), and NCBI datasets for known interactions.

A venn diagram could also be used in the manuscript to indicate overlap with BioGrid, Nuclear Protein Database, and NCBI interaction data. This serves both to acknowledge previous work but also show how well the screening system worked. From the large number of overlapping interactions that I can see from NPD, BioGrid and the literature, the screen worked quite well.

Finally, in addition to PML interaction data in the literature, it would be nice to see a comparison to other SUMO-interaction data sets, including that of Ali Maroui et al., 2018 Mol. Cell Proteomics PMID: 29535160.

Hope this post is useful to community and the authors.

All the best and wishing you luck for swift (and thoughtful) peer-review and publication,

Graham Dellaire

On 2020-12-30 16:10:06, user YLIABC wrote:

Hi - Just to point out that the line <br /> "and a covalent amide linkage is automatically formed between a lysine on ST and an asparagine on SC (33, 34)"<br /> is incorrect the bond is formed between lysine on SpyCatcher (SC) and aspartate/aspartic acid on SpyTag (ST)

On 2020-12-30 15:01:56, user Matthew Baron-Chapman wrote:

By this formula, a 25 year old Labrador would translate to an age of 83 years old. I know of know record of a Labrador living to be 25 years old, yet many people live to be 83. A 30 year old labrador would be the equivalent of an 85 year old human. This formula calculator seems to be garbage to me. Anyone know of any 30 year old labradors out there?

On 2020-12-30 14:00:35, user Stefan Bidula wrote:

Hi,

Just making you aware of a potential error in case you hadn't noticed.

'Recently Kawano and collaborators have shown that a positive modulator of P2RX4, the ginsenoside CK compound 25, calibrates P2RX7-dependent cell death in macrophages 26'.

Kawano was involved in neither of these findings. The P2X7 calibration is referring to Bidula et al (your reference 24). My guess is the Kawano reference is for the previous sentence ''P2RX4 is another member of the P2X family that is described to regulate P2RX7’s activities in macrophages''?

Nice paper though!

On 2020-12-30 10:16:11, user MooChoo wrote:

Can someone confirm that isolation of the Sars Covid 2 was from diseased human tissue and not contaminated with monkey kidney tissue or use of a PCR TEST?

On 2020-12-30 10:13:54, user MooChoo wrote:

Can someone confirm the isolation of Sars Covid 2 was taken from diseased human tissue and not from monkey’s kidneys or any other contaminant or by the use of a PCR test?

On 2020-12-30 08:14:17, user Yukio Nagano wrote:

References 42 and 47 are the same paper (our paper). Please correct them.

On 2020-12-02 09:56:01, user Martin R. Smith wrote:

This looks like a very promising new method. In evaluating its performance, I wonder whether you considered using alternatives to the Robinson–Foulds distance, e.g. Smith 2020, https://doi.org/10.1093/bio... ? As the RF distance suffers from a number of potential biases, it would be interesting to see whether a more robust tree distance measure would make the case for wQFM even stronger, and whether the seemingly better performance of ASTRAL on the avian dataset is robust to the choice of tree distance method.

On 2020-12-30 04:37:18, user Raghu Parthasarathy wrote:

There are many problems with the paper. Perhaps most obviously, Figure 1 plots Tg/Mass vs. Mass, and finds a power-law slope of around -1. Tg is roughly organism-independent -- by construction, it can't vary much -- so this is roughly a plot of constant/Mass vs Mass, which trivially has a power-law of slope -1.

On 2020-12-30 01:37:53, user Sam Cronnlle wrote:

New method in molecular sexing of skinks<br /> https://bmcgenomics.biomedc...

On 2020-12-29 22:51:50, user Marco Fumasoni wrote:

Erratum: Authors and DOI listed in reference 48 belong to another publication. The correct reference is:<br /> 48. Wiser MJ, Ribeck N, Lenski RE. Long-term dynamics of adaptation in asexual populations. Science 2013;342: 1364–1367. doi:10.1126/science.1243357

On 2020-12-29 21:18:10, user Arkady Pertsov wrote:

Dear Dr. Rubenstein, You may want to look at a 1996 paper dealing with Doppler peculiarities in excitable media, which is not on your references list and which may be of some relevance to what you are doing:<br /> Spatial Doppler anomaly in an excitable medium. M. Wellner, A. M. Pertsov, and J. Jalife<br /> Phys. Rev. E 54, 1120 – Published 1 August 1996; Erratum Phys. Rev. E 54, 4483 (1996)

On 2020-12-29 17:16:17, user sven wrote:

Interesting paper! We have seen that AGO2 has a role in APA in neuronal cells - also affecting RET (TREND-DB: shiny.imbei.uni-mainz.de:3838/trend-db/ https://academic.oup.com/na... ). This paper provides further insights into the consequences. Congratulations.

On 2020-12-29 12:45:08, user Saad Alqahtani wrote:

Sir,<br /> Kindly let me know that when will my article get accepted,<br /> Regards

On 2020-12-29 02:45:36, user P. F. wrote:

* convalescent

On 2020-12-29 00:34:47, user Olga Matveeva wrote:

Several recent preprints support some of this manuscript findings.<br /> 1. Authors from Sweden and China in a study entitled “Pulmonary stromal expansion and intra-alveolar coagulation are primary causes of Covid-19 death” demonstrated that “The virus was replicating in the pneumocytes and macrophages but not in bronchial epithelium, endothelial, pericytes or stromal cells. doi: https://doi.org/10.1101/202...<br /> 2. Researchers in China concluded that “Collectively, these results demonstrate that SARS-CoV-2 directly neutralizes human spleens and LNs through infecting tissue-resident CD169+ macrophages.” They published a preprint entitled “The Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Directly Decimates Human Spleens and Lymph Node” doi: https://doi.org/10.1101/202...<br /> 3. Researchers in Brasil investigated SARS-CoV-2 infection of PBMCs and found that in vitro infection of whole PBMCs from healthy donors was productive of virus progeny. They also found that “SARS-CoV-2 was frequently detected in monocytes and B lymphocytes from COVID-19 patients, and less frequently in CD4+T lymphocytes” The preprint is entitled “Infection of human lymphomononuclear cells by SARS-CoV-2”. <br /> doi: https://doi.org/10.1101/202...<br /> 4. SARS-CoV-2 infection of macrophages and some other immune cells in deceased patients was suggested in other autopsy related preprint entitled “Broad SARS-CoV-2 cell tropism and immunopathology in lung tissues from fatal COVID-19” doi: https://doi.org/10.1101/202... The study was done by US researchers from Pittsburgh.

On 2020-12-29 00:30:23, user Olga Matveeva wrote:

Several recent preprints support some of this manuscript findings.<br /> 1. Authors from Sweden and China in a study entitled “Pulmonary stromal expansion and intra-alveolar coagulation are primary causes of Covid-19 death” demonstrated that “The virus was replicating in the pneumocytes and macrophages but not in bronchial epithelium, endothelial, pericytes or stromal cells. doi: https://doi.org/10.1101/202...<br /> 2. SARS-CoV-2 infection of macrophages and some other immune cells in deceased patients was suggested in other autopsy related preprint entitled “Broad SARS-CoV-2 cell tropism and immunopathology in lung tissues from fatal COVID-19” doi: https://doi.org/10.1101/202... The study was done by US researchers from Pittsburgh. <br /> 3. Researchers in China concluded from their findings that “Collectively, these results demonstrate that SARS-CoV-2 directly neutralizes human spleens and LNs through infecting tissue-resident CD169+ macrophages.” They published a preprint entitled “The Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Directly Decimates Human Spleens and Lymph Node” doi: https://doi.org/10.1101/202...<br /> 4. Researchers in France demonstrated “that SARS-CoV-2 efficiently infects monocytes and macrophages without any cytopathic effect.” Their findings are reported in the preprint entitled “Monocytes and macrophages, targets of SARS-CoV-2: the clue for Covid-19 immunoparalysis” doi: https://doi.org/10.1101/202...

On 2020-12-28 23:36:22, user drmichaelpollak wrote:

is it certain that SARS-CoV-2 does not encode a protein with diesterase activity?

On 2020-12-28 22:00:24, user Alberto Villena wrote:

Also, I noted some misstapes in fig. 7 legend. I think it should be:

Figure 7. Vitro study of isolated virus Isolation of the virus from the lung of C9<br /> using Vero E6 cells (A - uninfected). Cytopathic effect on the VeroE6 48 hours after infection (B). Phase contrast (A and B) Scanning electron microscopy (SEM) images of the surface of uninfected Vero E6 cells (C) and infected Vero E6 cells 48 hours post infection (D). Intra-alveolar coagulum (E). Budding virus particles on the surface of a type II pneumocyte (F). Virus infected dead cell in the bronchiolar lumen, on the top of ciliated epithelium (G). Virus particles on the alveolus wall (H).E,F,G and H SEM images from the lung of patient C9.<br /> Size markers A and B 10 micrometer, C and D 300 nanometer, E 10 micrometer, F<br /> 100 nanometer, G 2 micrometer, H 100 nanometer

On 2020-12-28 21:16:31, user Alberto Villena wrote:

Very interesting paper.<br /> Just two comments to the authors:<br /> 1) Is Table 1 the same that is showed as "Supplemental Table 1"?<br /> If so, the age of the cases is lacking. And such informations is important, particularly for the young patients.

2) About the section "Circulatory system", the description of the cardiac chambers is confusing to me: when you say "hypertrophy of the wall of the left cardiac chamber", it refers to the auricle or the ventricle, or both?<br /> Thanks

On 2020-12-28 00:31:57, user Olga Matveeva wrote:

Great manuscript! Several recent preprints support some of its findings. <br /> SARS-CoV-2 infection of macrophages and some other immune cells in deceased patients was suggested in other autopsy related preprint entitled “Broad SARS-CoV-2 cell tropism and immunopathology in lung tissues from fatal COVID-19” https://www.medrxiv.org/con... The study was done by US researchers from Pittsburgh. <br /> Researches from China concluded from their findings that “Collectively, these results demonstrate that SARS-CoV-2 directly neutralizes human spleens and LNs through infecting tissue-resident CD169+ macrophages.” They published a preprint entitled “The Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Directly Decimates Human Spleens and Lymph Node” https://www.medrxiv.org/con...<br /> Researches form France demonstrated “that SARS-CoV-2 efficiently infects monocytes and macrophages without any cytopathic effect.” Their findings are reported in the preprint entitled “Monocytes and macrophages, targets of SARS-CoV-2: the clue for Covid-19 immunoparalysis” https://www.biorxiv.org/con...<br /> Researches form BRASIL investigated SARS-CoV-2 infection of PBMCs and found that in vitro infection of whole PBMCs from healthy donors was productive of virus progeny. They also found that “SARS-CoV-2 was frequently detected in monocytes and B lymphocytes from COVID-19 patients, and less frequently in CD4+T lymphocytes” The preprint is entitled “Infection of human lymphomononuclear cells by SARS-CoV-2”. https://www.biorxiv.org/con...

On 2020-12-28 15:58:00, user Dilip De Sarker wrote:

It will open new vistas in rice breeding

On 2020-12-28 15:25:57, user Sadik wrote:

Gap-free rice genome! Overlapping repeats classes filtering in the method section caught my attention and wanted to learn the how-to's in suppl. methods.

On 2020-12-28 11:18:09, user Camila Fonseca Amorim da Silva wrote:

Hi, I'm a biotechnology student and I'd like to do a molecular docking study based on the compounds tested in this work (to verify how predictive is the algorithm in the docking program for experimental data), but I have a question: when I was looking for some of the compounds in ChemSpider, for example, Evans Blue, the corresponding molecule had sodium ions in it, but there aren't any sodium ions in Evans Blue in figure 1. Is there a reason for this difference, just a different kind of representation? Thank you.

On 2020-12-28 09:53:11, user Neil Cobb wrote:

The fundamental point that focused, standardized inventories are important is well supported in this manuscript. However, the comparison between completed inventories and specimen data seems to be a false comparison in a number of ways. About 6% arthropod specimens have been digitized in u.s. collections, although for bees gets closer to 30%. So, it is highly unlikely that any species has had all of their specimen data completely digitized and so the authors have no idea how much data is still available but not transcribed. This should at least be mentioned as a qualifier in the discussion. Specimen data should come from a variety of sources including inventories, so it seems like a lot of their data from the inventories would have been considered specimen data had somebody else used it. Rather than bashing specimen data, why not simply emphasize the importance of inventories in making specimen based research a lot better

On 2020-12-28 08:20:40, user Oksana Stoliar wrote:

Very urgent paper. it utilize valid bioindicative species from the intertidal area that is corresponding to the goal and conclusions of study. Indeed, the understanding of the interactions between different drivers and the limits of adaptive responses are the item of priority to provide the environmental forensics.

On 2020-12-27 17:18:44, user Nikolai Slavov wrote:

Dear Matthias and colleagues,

I found your preprint interesting, especially as it focuses on an area that recently has received much attention. Methods for single-cell protein analysis by label-free mass-spectrometry have made significant gains over the last few years, and the method that you report looks promising. Below, I suggest how it might be improved further and benchmarked more rigorously.

To analyze single Hela cells, you combined the recently reported diaPASEF method with Evosep LC and timsTOF improvements developed in collaboration with Bruker. This is a logical next step and sounds like a good approach for label-free MS. The method quantifies about 1000 proteins per Hela cell, a coverage comparable to published DDA label-free methods (doi: 10.1039/D0SC03636F) and reported by the Aebersold group for a DIA method performed on a Lumos instrument (data presented at the third Single-Cell Proteomics Conference https://single-cell.net/pro.... This is a good coverage, though given the advantages of diaPASEF and the timsTOF improvements, there is potential for even better performance. I look forward to exploring the raw data.

The major advantage of your label-free MS approach is its speed. It is faster than previously reported label-free single-cell proteomics methods, which allowed you to analyze over 400 single Hela cells, generating the largest label-free dataset to date. This increased speed is a major advance for label-free single-cell proteomics. The speed (and thus throughput) could be increased further based on multiplexing using the isobaric carrier approach.

You combine Hela data from single-cell MS analysis with Hela data from two scRNA-seq methods. This is good, and I think such joint analysis of protein and RNA should be an integral part of analyzing single-cell MS proteomics data. The results shown in Fig. 5A,B are straightforward to interpret and indicate that your method compares favorably to scRNA-seq in terms of reproducibility and missing data. The interpretation of Fig. 5A, B is more confounded by systematic biases. Both mass-spec and sequencing have significant biases, such as sequence-specific biases and peptide-specific ionization propensities. These biases contribute to estimates of absolute abundances (doi: 10.1038/nmeth.2031, 10.1038/nbt.2957) and might contribute to the variance captured by PC2 in Fig. 5C, and thus may alter your conclusion.

I have possible suggestions: <br /> -- Benchmark the accuracy of relative quantification. Ideally, this can be done by measuring protein abundance in single cells by an independent method (such as fluorescent proteins measured by a FACS sorter) and comparing the measurements to the MS estimates. You may possibly choose other methods, such as spiked in protein/peptide standards. Benchmarks of accuracy (rather than merely reproducibility) would strengthen your study. <br /> -- Order the unperturbed Hela cells by the cell division cycle (CDC) phase and display the abundances of the periodic proteins. <br /> -- Provide more discussion positioning your work in the context of the field and other approaches, in terms of technology, depth of coverage, throughput, and biological applications.

Nikolai Slavov<br /> https://slavovlab.net

On 2020-12-27 11:23:23, user Joachim Berner wrote:

Could Bemcentinib from BerGenBio stabilise AXL and promote epithelial-mesenchymal transition?

https://www.bergenbio.com/p...

On 2020-12-27 10:26:11, user Paul Wolf wrote:

This paper needs a better translation. I had never heard of STE90-C11 before. Here's a link to an article about the discovery of it. https://t.co/drDpV3aeUp?amp=1

On 2020-12-26 17:12:03, user Thomas Clavel wrote:

Dear authors,

I went through your story on cholestyramine in DOI mice with great interest.<br /> I have a few comments that I hope will be helpful to you.

1) The taxonomic statements about Muricabulum intestinale in your paper are erroneous. It neither belongs to the family Porphyromonadaceae, nor S24-7. The family Muribaculaceae has been described recently: https://pubmed.ncbi.nlm.nih.... Similarly, the family Coriobacteriaceae has been split into several families recently. This may indicate that your reference database used for taxonomic classification of amplicon is not up-to-date.

2) On a related note, the percentages of 16S rRNA gene sequence identities that you mention in the text for your ASVs of interest (< 94%) do not allow you to secure an identification at the species level. At best genus, but even this may be inaccurate. This impacts in my opinion many statements/interpretations in your paper, as you stress the importance of A. muris and M. intestinale on multiple instances.

3) It may be worth acknowledging the fact that the daily amount of cholestyramine (relative to body weight) used in these mouse experiments is approx. 20-fold of that usually utilized in human medicine.

Thanks for your consideration.<br /> Kind regards, Thomas Clavel

On 2020-12-25 23:29:43, user Robert Jay Rowen wrote:

I might have missed something. I cannot tell the details of the exposure of the embryos to the ClO2. Can someone please describe the exposure or treatment with ClO2? Thank you.

On 2020-12-25 23:03:38, user Björn Brembs wrote:

This is a very interesting piece of work on a behavior that couldn't be more iconic, insect flight. Congratulations!<br /> I only have a short remark about a citation of two of our publications:

In line 415-418 you write: "PKC-d, a member of the Protein Kinase C <br /> family and is known to modulate flies ability to learn from their <br /> environment, especially during flight."<br /> WRT our two publications, the Gorostiza et al. paper does not treat PKC at all, and Colomb and Brembs is work on not learning from the environment, but the opposite of what you write, the fly learning about its own behavior without any other environmental cues.<br /> Best regards,<br /> Björn

On 2020-12-24 18:56:48, user Charles Warden wrote:

Thank you for posting this preprint.

I noticed that there was highlighting of sentences throughput the manuscript. Was this intentional, or should those be removed after editing and discussion?

On 2020-12-24 17:38:00, user Dong wrote:

Interesting paper. The GitHub link https://github.com/SydneyBi... does not exist, and can you modify the shiny maximum data upload size limit? The default one accepts only max. 5MB.

On 2020-12-24 03:58:23, user Tiago Lubiana wrote:

I guess this was published in Nature: https://www.nature.com/arti...

On 2020-12-24 03:50:13, user Tiago Lubiana wrote:

I guess this preprint has been published here: https://genomebiology.biome...

Shouldn't this page have a link to the published version?<br /> Att<br /> Tiago

On 2020-12-24 02:49:38, user AJ wrote:

Great news. Please look at other blood and bone marrow populations as well!

On 2020-12-24 00:40:38, user Alan Herbert wrote:

Congrats on a really nice paper! Did you look at the cellular localization for the tryptophan ADAR mutant?

On 2020-12-23 15:12:33, user Corinne Vacher wrote:

The revised version of this article is now published in New Phytologist: "Maternal effects shape the seed mycobiome in Quercus petraea" by Fort et al. <br /> https://doi.org/10.1111/nph...

On 2020-12-23 08:58:35, user Ellis Patrick wrote:

This is fantastic! How/where are you planning on sharing your data?

On 2020-12-23 01:49:32, user Jingbo Nan wrote:

Great work! I often see similar intense luminescence during Raman analysis of carbonaceous materials in rocks. I can even get Raman peaks around 1350 cm-1 and 1580 cm-1 (similar to D and G band position) on metal-coated inorganic sample surface, which should be caused by luminescence. It's important to show the whole Raman spectrum in the paper since the luminescence is common.

On 2020-12-22 22:25:42, user Max Fazio wrote:

Fazio et al. in https://www.nature.com/arti...<br /> studied the response of the ONH as independently affected by IOP and CSFP in human.<br /> Great article otherwise. Congrats!

On 2020-12-22 22:10:06, user Praveen patnaik wrote:

Excellent findings. Really enjoyed reading the paper. I just like to inform the authors that the supplementary Figure 7 is mentioned as supplementary figure 6. Please make the corrections.

On 2020-12-22 20:15:06, user Kirill Gorshkov wrote:

Now published at https://pubs.acs.org/doi/10...

On 2020-12-22 16:22:22, user Richard Durbin wrote:

The lineage of an ancient individual will have diverged from the tree of present day individuals at a point part way along some branch of the present day tree. For mutations on that branch below that divergence point, they will be derived in all present day individuals but ancestral in the ancient individual. I believe this explains the observations that you make. (Alternatively they may be miscalls in Mota.)

On 2020-12-21 11:54:11, user Shi Huang wrote:

The same pattern is also found for rs73621775, which has 9 reads coverage. Impossible for sequencing or calling errors to explain.

On 2020-12-21 11:49:28, user Shi Huang wrote:

Why ignore the glaring inconsistencies! Check the data file, find rs1973664. All present day E1b have the alt allele C but the ancient Mota-E1b has ref T. We have this reported in a submitted manuscript a month ago. Ancient DNAs are supposed to be more informative than extant DNAs with regard to past events and could thus serve as the best evidence to either verify or invalidate any phylogenetic trees that are built by using extant DNAs. It is therefore surprising that the field has yet to use the now abundant ancient DNAs to verify the standard model of modern human origins, the OoA model. Is it because the model cannot pass the ancient DNA test? We found it can't!

On 2020-12-22 14:54:33, user Dirk wrote:

This is an interesting paper that is centered around Swiprosin-1/EFhd2. The data support previous data by Fan and colleagues (2017) that show an involvement of EFhd2 in invadipodia formation and migration of lung tumour cells. The results of this paper may also explain why Swiprosin-1/EFhd2KO B cells establish less contact with follicular dendritic cells in germinal centers (Reimer and colleagues, 2020). The actin bundling function of Swiprosin-1/EFhd2, identified by Kwon et al. (2013), may be involved.

On 2020-12-22 14:48:33, user Nicole C wrote:

This is a clear, well-written article about an important and timely topic: Ozone (O3) exposure. While the gene expression changes in the airway in response to O3 are becoming clearer, the precise mechanisms regulating airway gene expression responses to O3 remain unknown. Thus, this paper investigates the effects of in vivo O3 exposure in C57BL/6J mice on bronchoalveolar lavage (BALF) extracellular vesicle (EV) microRNAs (miRNAs) and found that increasing O3 concentrations alter BALF EV miRNA expression. The finding that certain EV miRNA expression changes correlate with changes in their target mRNA expression changes in airway cells, identified in previous work, suggest that lung EV miRNAs may regulate gene expression in cells of the airway.

Thank you for providing the first report of small RNA-seq data for murine BALF EV samples, which will no doubt be useful for future studies. This study has many strengths, including:

1. The in vivo study design, which exposed mice to two doses of O3. The finding of a dose-response relationship among some of the most variable EV miRNAs makes claims about altered EV miRNA more impactful.

2. Building on their previous work that identified O3-responsive genes in the airway, the authors used the O3-responsive tissue mRNA as input to miRhub to identify targets of differentially expressed EV miRNAs in this study to identify putative miRNA-mRNA regulatory networks. This is progress towards understanding functional downstream effects of altered BALF EV miRNA expression.

3. The authors performed an EV characterization method to describe the population of murine BALF EVs.

This article did have weaknesses, namely pooling the BALF EV RNA samples prior to sequencing, resulting in a smaller sample size for the RNA sequencing results. However, principal components analysis was able to detect distinct EV miRNA expression patterns by exposure group. Also, the authors acknowledge the exploratory and hypothesis-generating nature of this study and interpret results appropriately. I would be interested to see subsequent work that builds on these findings.

I would also recommend refining the interpretation of the NTA results. The current NTA data do not demonstrate a “clear increase” in the number of EVs in the BALF of mice exposed to 2ppm O3 compared to the other exposure groups. I am skeptical of these results for the following reasons: 1) NTA was performed on the BALF supernatant prior to EV isolation and not on a pure EV prep; 2) Conventional NTA will detect any particles in solution. In addition to EVs, it will detect membrane fragments, protein complexes, lipoproteins, and other background particles. I would recommend labeling EVs with a dye for intact membranes and performing fluorescent NTA to achieve an EV-specific size distribution and particle concentration; 3) NTA was the only method performed to characterize the EVs of these samples. Again, conventional NTA will detect any EV-sized particles and this data alone does not confirm the presence of EVs. Indeed, even commercial kits such as the Qiagen kit used here may not fully separate non-vesicular entities from EVs and can also co-isolate other molecules such as RNA-protein complexes. I would recommend a complementary method to confirm the presence of EVs as recommended by MISEV2018 guidelines, such as a proteomic analysis to detect and/or quantify levels of expected EV-enriched proteins. I would also recommend that in the discussion section, the authors address that these results of altered miRNA expression could be explained in part by contribution of particles other than EVs. It also appears that there is an outlier in the particle concentration within the 2 ppm O3 exposure group that may be skewing the particle counts.

Furthermore, since the “EV” particle count was significantly different across groups, should this have been accounted for in the small RNA normalization approach?

Lastly, to further improve this article and make it even more impactful to the field, I would implement the following minor changes: 1. Provide a supplemental table of the full Malvern Nanosight NTA recording and analysis parameters for transparency and as an effort to increase rigor and reproducibility in the area of EV characterization. 2. In the statistical analysis section, specify the method for multiple comparisons adjustment (i.e. Benjamini Hochberg, or FDR?) and the post-hoc test applied following ANOVA.

Thank you for making this pre-print available!

On 2020-12-22 13:08:44, user 上羽 瑠美 wrote:

This manuscript has published online in the Rhinology journal website.<br /> https://www.rhinologyjourna...

After reviewing, we made some important changes to the content of the paper that reflected the results. Unfortunately, bioRxiv said they was not able to link it to the website, because the manuscript was published as "letter", not "original article".<br /> Please see the following link. https://www.rhinologyjourna...<br /> Thank you.

On 2020-12-22 12:28:44, user Alexis Verger wrote:

This is a very interesting work that confirms and nicely extend previous finding (https://www.cell.com/cell-s... https://www.cell.com/cell/f... https://www.cell.com/molecu... https://www.embopress.org/d... https://www.embopress.org/d... https://www.embopress.org/d....

• I have always a small concern in all these high-throughput screen for TADs. The TADs are studied outside the context of the full length proteins and do not take into account their accessibility and the structural constraints of adjacents sequences/domains. Do the authors have any comments ?

• It could be interesting to perform the quantitative screen in a med15 knockout yeast strain.

• What is the rationale behind the 12-13 amino acids step size in the pooled screen ?

• For MED15, it is not clear to me if the yeast ABDs domains are conserved in metazoan. There are only few human transcription factors known to recruit MED15. Do the authors think that their data with MED15 is restricted to yeast ?

On 2020-12-21 19:58:35, user Enrico Klotzsch wrote:

The article is now published here:<br /> https://pubs.acs.org/doi/10...

On 2020-12-21 18:00:49, user Randy Oliver, beekeeper wrote:

The findings of this excellent set of experiments confirm what I observed in the field when we experimented with scratching all the sealed brood in mite-infested colonies to create a brood break for varroa management. The colonies quickly dwindled, from what I suspect was the transmission of DWV as the adult bees cannibalized/cleaned the damaged pupae from the combs. Randy Oliver

On 2020-12-21 17:00:51, user AG wrote:

Survival of the fittest. Parasite or not all depends whether the social condition allows such survival. With extreme low productivity without surplus, no parasitic lifestyle can exist. With surplus, "parasite" might come to existence. But "parasites" true contribution to community might be unknown to us due to our ignorance. We human tend to use simple logic to explain complex biological world.

On 2020-12-21 16:58:17, user Ronan Chaligné wrote:

This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 750345.

On 2020-12-21 15:35:05, user David Scheuring wrote:

Happy about comments and critics!

On 2020-12-21 14:51:47, user Arlin Stoltzfus wrote:

I enjoyed reading the paper. I noticed one mistake in "We also present evidence previous ..." Adding a "that" would make it clearer. Also there is verb-subject disagreement: "previous conclusions ... was."

On 2020-12-21 14:18:14, user Charlotte Francoeur wrote:

Hi,

I just noticed what I think is a typo - the PFAM ID for OTU should be PF02338 not PF02328. When I type PF02328 it brings me to a page that says "Dead Pfam-A family." Great paper!!

On 2020-12-21 14:16:34, user DR.Muratt, MD wrote:

Virus-specific antibodies are considered antiviral and play an important role in the control of virus infections in a number of ways. However, in some instances, the presence of specific antibodies can be beneficial to the virus..Could Antibody dependent enhancement (ADE) be a major problem with any vaccine developed for coronaviruses?

On 2020-12-21 13:25:15, user Christoph Lange wrote:

Great paper. The importance of mutations on disease outcome and for surveillance/containment of strains that are potentially highly pathogenic has been underestimated. In our analysis, we found mutations associated with mortality of Covid-19<br /> https://www.biorxiv.org/con...

On 2020-12-21 13:13:16, user raphalleluisier wrote:

Hi it would be nice if you could upload a complete PDF including the Supplementary Figures.<br /> Interesting read!

On 2020-12-21 05:53:06, user deloris vandivort wrote:

in the discussion of the cancer patient dying from the so called mutation has too many variables to prove accurate. why were other treatment modalities not attempted over the remdesivir that has failed in other pandemic outbreaks and also this was a cancer patient that RNA is used for treatment could also alter outcomes I am personally am disappointed in the narrow sightedness of treatment given to patients or lack of treatment. I do agree that mutation usually doesn't occur at the rates they are being stated here. I also would like to know that those they found with the so called mutated virus ever had the virus in the first round or not. I am skeptical of a lot of the information given on all of this because I am missing the use of control groups so necessary in proper scientific method. I have yet to hear about reinfection of a person with the virus and if so I am sure it is a very minimal number. I am still showing antibodies at six to seven months post the virus that is not suppose to happen.

On 2020-12-11 17:58:16, user Steven Burden wrote:

Have the authors tested whether the mutated virus is infectious (e.g. in cultured cells), and if so whether infectivity is attenuated? Have the authors tested whether sera from vaccinated individuals carry antibodies that recognize the mutated virus and block infection?

On 2020-12-20 20:33:37, user Giorgio Cattoretti wrote:

We investigated in detail and published NaBH4 (sodium borohydride) in our multiplexing method paper (https://journals.sagepub.co....<br /> Sodium borohydride is reported to be a weaker reducing agent, compared to the lithium compound (https://en.wikipedia.org/wi..., yet at 1mg/ml concentration had deleterious effects on FFPE section integrity. At lower concentration, removes antibodies bound to tissue, however below 15 mM do not affect tissue antigens. To test NaBH4 in a controlled fashion we dissolved the compound in a buffer at pH 9, where the half life is 6.1 min, short, but enough for an experiment. At pH between 5.5 and 7, the pH of distilled water, half life is mere seconds or fractions of seconds. We could not find stability data for LiBH4 in water, but we found a striking similarity between this manuscript and a highly quoted recipe for autofluorescence quenching with NaBH4 (refs 52-53 of our paper): bubbles forming long time after there is no longer any active compound in the solvent (distilled water). Lithium sits next to sodium in the periodic table and LiBH4 is very sensitive to moisture. We believe that LiBH4, as NaBH4, require a buffered solution in order to yield reproducible results with IBEX.

On 2020-12-20 15:00:33, user Eve Beavers Fain wrote:

According to much research I have read, the Neanderthal were eating quite a bit of fiber in their diet so naturally you will find expressed DPP-4 variants. Fiber is digested further down in the intestines which causes increased incretin activity. Any connection to covid19 is hearsay.

Please see this open access paper: https://www.frontiersin.org...

On 2020-12-20 12:03:45, user GoranM wrote:

You write that "The study cohort consists of 147 unrelated individuals from Serbia". However, Serbia has a significantly diverse population (nationally) and it would be of interest to know from which regions of Serbia they were. Were the recruited only from the Belgrade region or did you also recruit subjects from Northern Serbia, Eastern Serbia, South-East Serbia, South Serbia (of Romanian, Bulgarian, Albanian, Hungarian, Czech ... descent)? If yes, that would mean that "Serbian" genom, which you showed nicely, overlap perfectly with the European, and that observed changes and differences might mainly be attributed to the epigenetic changes. Serbia is, unfortunately, one of the mots polluted European countries with no enforcement of environment protection laws and very rudimentary public health protection, and with extremely high air pollution and the country with the most active cigarette smokers.

On 2020-12-19 18:35:43, user Clara B. Jones wrote:

really useful treatment... how do these ideas relate to hypothesis that evolution of sexual dimorphism in body size between the sexes "allows" males to ESCAPE direct competition for limiting resources with females [in the same conditions] which reduces fitness, impacting males? clara b. jones @cbbjones1943 foucault03 at gmail dot com

On 2020-12-18 20:40:29, user Gavin Douglas wrote:

Hi Pat,

My lab discussed this preprint at a recent journal club because we definitely agree this is an important area to investigate. However, overall we disagreed with the conclusions and we had issues with several key analysis steps. We have written up a review of the preprint with specific comments, which we hope is of some use: http://dalmug.org/filter-re...

All the best,

Gavin

On 2020-12-15 10:36:24, user Julian Marchesi wrote:

Can anyone answer me this<br /> 1: what % of singletons i.e. 1 read in one sample are real and what % are due to sequencing errors and bioinformatic artefacts? It always amazes me how people grab the latest idea like it must be right, so ASVs are in and OTUs are out. Well if you missed the memo, we don't even have a robust definition of what a bacterial species is, so anything we use is always a compromise and biases out analysis.<br /> 2: if you don't sample to the same read depth how can you create comparable alpha diversity indices? Won't a sample with a read depth of 20,000 reads have a different Shannon index to one with 1500 reads?

On 2020-12-18 16:14:26, user Sam Smith wrote:

Here is a similar study. Also this study was in vitro and I don't know are they going to test the mouth washes/rinses in vivo. Perhaps they didn't publish at a very high-quality journal?<br /> https://www.ijeds.com/journ...<br /> Volume 9, Number 1, January-June 2020<br /> Comparative Analysis of Antiviral Efficacy of Four Different Mouthwashes against Severe Acute Respiratory Syndrome Coronavirus 2: An In Vitro Study

On 2020-12-18 15:49:32, user AG wrote:

Social selection can also produce consequence. The very fact of y-chromosome with high mortality rate during world war 2 can result a population which tend to produce more female offsprings since y-chromosome functions as unfit genes for survival in population went through major selection by wars. Russia has extraordinary high female offspring birth rate, which might be the historical selection against y carriers during ww2.

On 2020-12-18 15:38:26, user AG wrote:

Earlier studies indicated that older fathers also produced offsprings with longer telomeres. It is very likely that same mechanism affect both female and male parents to produce gametes at older age. My hypothesis is that gametes produced in older age parents are from the pool of primordial germ cells with longer telomeres than younger parents. Or at least sperm and oocytes from younger parents have higher proportion of shorter telomeres.

On 2020-12-18 10:07:47, user disqus_32giU6NoIA wrote:

Really nicely written and helpful paper. It would be good if you stated in the paper what PacBio technology you used. Is it correct in assuming you used CLR data, rather than CCS/HiFi?

On 2020-12-18 07:44:50, user herbette wrote:

Their results confirm those of this study: https://doi.org/10.1104/pp....

On 2020-12-17 20:05:29, user Colm Ryan wrote:

Somehow dropped the supplemental tables from submission - they're all available here: http://www.cancergd.org/sta...

On 2020-12-17 18:25:18, user Hanjoong Jo wrote:

A revised version with additional validation of the single cell RNAseq and ATACseq results is now published in Cell Reports. PMID: 33326796 DOI: 10.1016/j.celrep.2020.108491

On 2020-12-17 17:30:30, user Sui Huang wrote:

I noticed that the controls are just saline buffer, and not some empty lipid nanoparticle, which would have been a more stringent control (even better: LNP carrying an unrelated, or non-coding mRNA). It may be that the LNP alone exerts some non-specific adjuvant effect tat would have protected recipients if infected with the real virus? (A similar mechanism as postulated for BCG). Also in the human trial, the placebo is just saline solution. This also prevents us from knowing if the LNP has some biological (beneficial or adverse) effect... unless this has been shown before separately?

On 2020-12-17 16:53:38, user Raffi Aroian wrote:

This article is now published: https://aac.asm.org/content...

On 2020-12-17 16:02:34, user Lamya Ghenim wrote:

The text has been improved as well as some of the figures, and that a link will be forthcoming to the accepted version shortly. The paper has been accepted in Scientific reports (Nature).

On 2020-12-17 12:39:56, user Javi wrote:

Interesting approach to tackle antimicrobial resistance

On 2020-12-17 08:52:05, user Priyanka Kadam wrote:

Congratulations to Kartik and team for this very important paper. Great to see the new species of Krait named after Rom Whitaker :)

On 2020-12-17 08:04:10, user Joerg Schneider wrote:

Can you please point me to or post supplemental material referred to in the text? (supplemental Table 1, supplemental information 1, supplement information 2). Thank you.

On 2020-12-16 16:03:37, user Mattia Matasci wrote:

We are pleased to announce that this manuscript has been accepted for publication in "Experimental Biology and Medicine"

On 2020-11-30 16:52:59, user Baptiste Gouyou wrote:

I am pleased to announce that this manuscript has been accepted for publication in Experimental Biology and Medicine.

On 2020-12-16 09:58:50, user Jean Marie Frachisse wrote:

SUPER , MSLs are spreading in the green world with FLYC1 of Venus flytrap

On 2020-12-16 06:06:23, user Boris E. wrote:

The github link is not working.

On 2020-12-16 01:00:27, user Ziqiao Yin wrote:

Hi, everyone! The revised version of this article has been published on Briefings in Bioinformatics, https://doi.org/10.1093/bib...

This version has not been linked to the published one, welcome to the website above the access the latest version!

On 2020-12-15 19:21:33, user johnLK wrote:

Surprised that there's not more mention of hippocampal maps. As I see it, the "contexts" long-described in the place-cell literature are essentially "models", making virtually all notions of how hippocampal place cells contribute to navigation, "model-based" theories. Pfiefer and Foster points that direction, but the literature is deeper than that.

On 2020-12-15 16:50:22, user Olivier Le Gall wrote:

Another form of SARSr-CoV previously epidemic in humans, SARS-CoV, is found in sweat glands and possibly excreted (DOI:10.1002/path.1560). More recently, this has also been suggested for SARS-CoV-2 itself (DOI:10.1038/s41421-020-00229-y). <br /> Therefore, maybe the affirmation that "Sweat does not appear to be a route of excretion for SARS-CoV-2 virus", relying on two articles not directly focused on this particular question, should be somewhat tuned down?

On 2020-12-15 13:49:25, user Matteo Vecellio wrote:

This mansucript has now been accepted in Arthritis and Rheumatology and will be published online soon. A link will be fortcoming

On 2020-12-15 08:28:37, user TN wrote:

I found a typo. Not perosin, peropsin.

On 2020-12-15 07:00:51, user zj wrote:

maybe SNV not SNP？

On 2020-12-15 04:51:49, user Jaelyn Rae wrote:

Does this suggest how Covid-19 might impact those with rare metabolic conditions, such as acute hepatic Porphyrias, or more specifically, Hereditary Coproporphyria? Would the metabolic disruption caused by Covid-19 cancel the overproduction of porphyrins in those with these rare genetic mutations?

On 2020-12-15 02:06:55, user richieju520 wrote:

First genome-centric quantitative metatranscriptomic analysis of WWTPs microbiome and key functional and antibiotic-resisant populations

On 2020-12-14 22:47:21, user Stephanie Gogarten wrote:

Really interesting paper and visualization approach! Grouping populations by current residence rather than ancestral origin makes a lot of sense, but I'm curious why you didn't group the GIH (Gujarati Indians in Houston) in the AMR super-population as well.

On 2020-12-14 18:41:06, user Daniel Schachtman wrote:

Be sure to check out and cite the published version of this paper as there were substantial changes/additions made during the review process.

On 2020-12-14 04:04:12, user Kevin McKernan wrote:

Folks,<br /> There is a >3Mb N50 Type II cannabis plant in NCBI with 97% BUSCO scores. <br /> The Male genome is in NCBI as well. <br /> Its been there for a 10 months. <br /> https://www.biorxiv.org/con...

On 2020-12-14 00:11:14, user Corinne Vacher wrote:

Justin Byrne Thank you very much for your constructive comments. Our article is now published in Molecular Ecology Resources: Barroso-Bergada et al. 2020. Microbial networks inferred from environmental DNA data for biomonitoring ecosystem change: strengths and<br /> pitfalls. Molecular Ecology Resources,online https://doi.org/10.1111/1755-0998.13302

On 2020-12-13 21:18:43, user Patrick Sexton wrote:

I have some questions where additional information would help me interpret the presented data:

The in vitro experiment is poorly described and does not appear to be robustly performed...<br /> What is the scale (axis labels)? Is this an accumulation assay (+IBMX)? <br /> Were the data converted to actual cAMP levels?<br /> How long is the antagonist pre-incubation? How long is the total stimulation with GIP?<br /> This looks like a single experiment with duplicate repeats - what is the experimental "n"?

Is there anything known of potential activities of the antagonists for other signaling/regulatory processes for the mGIPR (e.g. pERK, receptor internalisation)?

Caveat on the next comments - I am not a physiologist, so it might just be my ignorance: <br /> Fig. 1H. Why does the GIP2-A antagonist "increase" blood glucose in the IPGTT in fasted, lean mice? Isn't this experimental design supposed to bypass the endogenous GIP response?<br /> Fig. 1J. Why does exogenous mGIP stimulate insulin secretion in 4 h-fasted lean mice, prior to IP glucose bolus? Why is there no rise in insulin secretion with mGIP with high glucose from the IP bolus? Is the administered GIP below effective concentration by this time?

It would also be good to understand the metabolism and clearance of the antagonists used in the chronic studies.<br /> What is the mouse PK on the GIP1-A? On what basis is the claim made that the osmotic mini-pumps will maintain an effective antagonist dose? Where is the evidence that this occurs?

What is the mouse PK for the GIP2-A? How does this compare to the PK for liraglutide?

On 2020-12-13 21:07:59, user Nikhil M wrote:

Interesting work, Could you please tell me that this method work to model ssDNA structure which is not solved experimentally.? Also, the CMD doest shows mcuh folding of the structure, why?

On 2020-12-13 17:30:59, user Imre Kovesdi wrote:

The cassette design consists of 2 CMV promoters and 2 SV40<br /> poly A signals. This design has been shown<br /> before to result in an unstable virus configuration that recombines and eliminates<br /> one of the transgenes. Two different<br /> promoters (eg. CMV & RSV) and two different poly a sequences (eg SV40 &<br /> BGH) should have been used.

On 2020-12-13 11:22:04, user Nimrod Shteindel wrote:

Very nice work - you might find this method useful in future work - it allows kinetic high throughput quontification of adhesion in a standard microtiter plate using a commecially availeble plate fluorimeter<br /> https://link.springer.com/a...

On 2020-12-13 10:29:54, user Matt wrote:

1) Is there any potential to test your topology by adding WGS of Ust-Ishim (45kya) or Sunghir (36kya)?

These Whole Genome Sequence samples precede the estimated 23kya divergence date within your model, and therefore a test of whether subsequent samples form a clade to them would provide a test the validity of your model in which the later samples within your model are descended from a population which was unstructured until 23kya.

2) The PRS score for height is estimated from the paper 2015 Chan et al (inc. GIANT Consortium), which identifies variants in a population of "3,545 African Americans and 21,590 individuals of European ancestry". Could you include any explanation within your paper for your choice of this set of SNPs?

Significant concerns have emerged in more recent papers testing the validity of SNP sets identified under GIANT on European populations on the larger and more homogenous population of the UK Biobank (and within sibling sets within this set). See Berg 2019 - https://elifesciences.org/a.... This suggests that GIANT Consortium's SNP identification is confounded by European population stratification. A similar paper by Sohail 2019 - https://elifesciences.org/a... - explicitly identifies this effect as driving a previous estimated polygenic height score difference between Early Farmers and later populations of Steppe ancestry.

Would it be possible to extend this section to add estimation of PRS using SNPs identified under UK Biobank (WB subset / sibs), as in Berg above, and/or identified using Biobank Japan, as in Chen 2020 - https://www.sciencedirect.c...

On 2020-12-12 14:26:48, user Specious Allegations wrote:

This cannot be applied in a rehabilitation context as in it cannot be applied to a dog who already has significant issues with behavior (ie the dogs in the exclusion criteria). So for anyone reading it, be aware that it *only* applies to a dog that has been raised correctly from birth with impeccable breeding history in terms of temperament. It doesn't apply when you've got a nearly grown up dog where you've made mistakes or the rescue you've brought home and they didnt tell you the truth about their aggression issues.

On 2020-12-12 12:26:33, user David Peters wrote:

Pterosaurs are not archosaurs (Peters 2000) and nest within a third clade of lepidosaurs (Peters 2007). A valid phylogeentic context is needed in these studies. Details and links here: https://pterosaurheresies.w...

On 2020-12-12 11:16:08, user M Hahn wrote:

Now published https://doi.org/10.1289/ehp...

On 2020-12-11 18:07:03, user Georgie Metters wrote:

Interesting stuff, looks like this measurement could be of use in my work!

On 2020-12-11 13:37:08, user george mcnamara wrote:

Zeiss does not sell a 1.55 NA objective lens (re: historially and current search at https://www.micro-shop.zeis... ). I hope the authors start proofreading their work. <br /> Since they have an LSM880,if it has AiryScan, they could acquire at "better than standard" confocal microscope resolution (approximately sqrt(2) better than 1.0 Airy unit pinhole size on standard confocal microscope - pinhole size not specifed in methods). The methods section does not specify the pixel size and Z step 0.75 um under-samples voxels. <br /> For those with confocal microscopes, I also note: (i) shorter wavelength fluorophore better resolution; Brilliant Violet 421 (BV421) fluorescence enables ~20% better resolution than 520 nm (Alexa Fluor 488, AausFP1 GFP, etc) if all settigns optimized, (ii) pinhole ~0.666 about ~10% better OR pinnhole ~0.333 ~15% better [Zeiss published nice application note loing ago on this]{photon throughput goes down by pi*r^2 so stable fluorophore best, or even better nanoparticle that reflects=backscatters light, and light path optimized for reflection confocal}, (iii) quantitative deconvolution is superior to unsharp masking (deconv ~10% better resolution), (iv) ALL can be combined: wavelength (0.9) * pinhole (0.85) * deconv (0.9) = 0.685, inverse: 1.45, about the same as Zeiss LSM880 AiryScan.

On 2020-12-11 17:34:27, user kfos wrote:

Just when I think I have a hold on one part of single-cell RNAseq analysis... Another cool new papers comes out... Overwhelming!

On 2020-12-11 02:03:12, user Rahul Satija wrote:

Thanks for posting this! We’ve written a brief response that compares the results of the sctransform model with the modifications proposed here (‘offset model’) at https://satijalab.org/pdf/s...

On 2020-12-11 16:49:31, user Roeland Nusse wrote:

Comments from Bruce Wang, Ludan Zhao, Matt Fish, Catriona Logan, Roel Nusse

In this manuscript, the authors raise a number of issues related to our publication from 2015 [1]. Most importantly, they report varying degrees of labeling of Axin2 expressing cells in the liver as well as dominant phenotypes in mice in which one or both Axin2 alleles are disrupted by insertion of the CreERT2 cassette.

May et al. report that in their hands, Axin2-CreERT2 homozygous mice could not be generated at all and that Axin2-CreERT2 heterozygous mice are born at sub-Mendelian ratios. In various labs, including our own, mice that are homozygous mutant for Axin2 have been used and characterized. The first such mice were generated by the Birchmeier lab [2], which have a LacZ insert at the exact same nucleotide position where we later inserted the CreERT2 cassette [3]. Both Axin2-CreERT2 and Axin2-LacZ, as well as other 5’ Axin2 knock-in strains, are considered to be null alleles of Axin2. Nevertheless, homozygous Axin2-LacZ animals are viable and fertile with relatively minor phenotypes reported in the literature (including a shortened head, abnormal eye morphology and enhanced osteoblast differentiation; see http://www.informatics.jax....:gUBZYT9emZ6SC9C7gbkwv4OS-ug "http://www.informatics.jax.org/allele/MGI:3579503)").

In our lab, all records from previous personnel spanning 2012-2016 have demonstrated that Axin2-CreERT2 homozygotes could be obtained despite mild phenotypes, and these animals were generated at expected frequencies. Axin2-CreERT2 heterozygotes bred to wild type mice also gave progeny at expected Mendelian ratios. Current crosses of Axin2-heterozygotes to wild-type continue to give expected ratios.

That being said, it is conceivable that rederivation and backcrossing of Axin2-CreERT2 animals to different backgrounds and their maintenance in different facilities might change the penetrance of Axin2 loss-of-function phenotypes via as of yet unknown modifier loci or other, non-genetic variables. This was recently described by the van Amerongen lab [4], which reported non-Mendelian offspring ratios from Axin2-CreERT2 mice (two rederivations removed from the line at our facility and three rederivations removed from the mice originally described in [3] or the mice deposited at Jackson labs) in heterozygous backcrosses to C57Bl/6 but not FVB/N (see Supplementary Table 2 in [4]). In August of 2017, we added this information to the description of the Axin2-CreERT2 mouse line on the Jackson Laboratory website (https://www.jax.org/strain/.... These results are in line with what is seen by May et al. and they underscore the importance of keeping track of the strain background and on using wildtype littermate controls for experiments.

With respect to the differences in the subset of cells that is labelled and the degree of labeling as reported by May et al., in our study we used both low (1 x 4mg tamoxifen/25gm body weight) and high (5 x 4mg tamoxifen/25gm body weight) tamoxifen dosing aimed at low and higher frequencies of labelling. With both doses we continued to see long-term expansion of labeled cells more than 300 days after initial tamoxifen dosing. Unlike May, with the high dose labeling we saw no displacement of pericentral labeled cells by unlabeled cells and this was the dosing used to quantify expansion of labeled cells. We interpret this as evidence that the Axin2 labeled cells in zone 3 expand, more so than other cells, and that lingering tamoxifen (which should be long gone from the system) was not the cause of the increased labeling over time.

Moreover, in our original publication [1] we wondered whether Axin2 heterozygosity affected our results but found no evidence that this was the case. First, we measured cell cycle parameters by EdU incorporation in heterozygous Axin2-CreERT2 mice compared to wild type and found no difference in proliferation rate with EdU labeling for 7 days. While we did not discriminate between male and female animals in Wang et al. [1], the results by May et al. suggest that this could be important. This is also part of a larger debate and movement towards appreciating sex as a biological variable. Particularly in the case of stem cells, a difference between males and females has been reported earlier [5], and it is tempting to speculate that this might actually be directly due to a difference in Wnt/beta-catenin pathway activity, as the results by May et al. would seem to suggest.

In addition to our lineage tracing experiments with Axin2-CreERT2, we also used the Axin2-rtTA transgenic mouse in which rtTA expression is driven by an Axin2 promoter fragment and where the wildtype Axin2 gene locus is kept intact. Using this model, we found a similar pattern of initial labeling of pericentral hepatocytes followed by expansion of labeled cells as with Axin2-CreERT2 mice, further supporting the importance of this cell population in particular, and arguing against reduced gene dosage of Axin2 as the reason for the observed proliferation of zone 3 cells and their progeny. However, we acknowledge that these were relatively short-term experiments.

Cre/lox mediated lineage tracing is a powerful method, but there are challenges and limitations in its design and interpretation [6, 7] which could affect our own as well as May et al.’s experiments. We emphasize that apart from our data, independent DNA label dilution experiments performed almost twenty years ago also indicate that the pericentral area (or zone 3) has a higher rate of DNA replication compared to other zones [8]. In the adult liver, both Wnt signaling and expression of the Wnt target gene Tbx3, known to be essential for embryonic hepatocyte proliferation [9, 10], continue to be active in pericentral cells [11]. Moreover, in adult liver tissue, pericentral cells express relatively high levels of c-Myc and CyclinD, hallmarks of cells that are active in the cell cycle [11]. In experimental models of mouse hepatocellular carcinomas, the cells of origin of the tumors are located pericentrally [12, 13]. We therefore believe our findings are consistent with the important role of Wnt/beta-catenin signaling in postnatal growth of the liver [14] and for the repair of liver tissue after chemical injury [15, 16]. Whether pericentral cells in adult livers are quiescent or divide and at which rate will depend on the specific context the cells are in and this will likely be affected by uncontrolled variables and environmental parameters.

References<br /> 1. Wang, B., et al., Self-renewing diploid Axin2(+) cells fuel homeostatic renewal of the liver. Nature, 2015. 524(7564): p. 180-5.<br /> 2. Lustig, B., et al., Negative Feedback Loop of Wnt Signaling through Upregulation of Conductin/Axin2 in Colorectal and Liver Tumors. Molecular and Cellular Biology, 2002. 22(4): p. 1184-1193.<br /> 3. van Amerongen, R., A.N. Bowman, and R. Nusse, Developmental stage and time dictate the fate of Wnt/beta-catenin-responsive stem cells in the mammary gland. Cell Stem Cell, 2012. 11(3): p. 387-400.<br /> 4. van de Moosdijk, A.A.A., et al., A novel Axin2 knock-in mouse model for visualization and lineage tracing of WNT/CTNNB1 responsive cells. Genesis, 2020. 58(9): p. e23387.<br /> 5. Nakada, D., et al., Oestrogen increases haematopoietic stem-cell self-renewal in females and during pregnancy. Nature, 2014. 505(7484): p. 555-8.<br /> 6. Becher, B., A. Waisman, and L.F. Lu, Conditional Gene-Targeting in Mice: Problems and Solutions. Immunity, 2018. 48(5): p. 835-836.<br /> 7. Kretzschmar, K. and F.M. Watt, Lineage Tracing. Cell, 2012. 148(1-2): p. 33-45.<br /> 8. Magami, Y., et al., Cell proliferation and renewal of normal hepatocytes and bile duct cells in adult mouse liver. Liver, 2002. 22(5): p. 419-25.<br /> 9. Ludtke, T.H., et al., Tbx3 promotes liver bud expansion during mouse development by suppression of cholangiocyte differentiation. Hepatology, 2009. 49(3): p. 969-78.<br /> 10. Suzuki, A., et al., Tbx3 controls the fate of hepatic progenitor cells in liver development by suppressing p19ARF expression. Development, 2008. 135(9): p. 1589-95.<br /> 11. Bahar Halpern, K., et al., Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature, 2017. 542(7641): p. 352-356.<br /> 12. Nicholes, K., et al., A mouse model of hepatocellular carcinoma: ectopic expression of fibroblast growth factor 19 in skeletal muscle of transgenic mice. Am J Pathol, 2002. 160(6): p. 2295-307.<br /> 13. Wang, R., et al., Activation of the Met receptor by cell attachment induces and sustains hepatocellular carcinomas in transgenic mice. J Cell Biol, 2001. 153(5): p. 1023-34.<br /> 14. Apte, U., et al., beta-Catenin is critical for early postnatal liver growth. Am J Physiol Gastrointest Liver Physiol, 2007. 292(6): p. G1578-85.<br /> 15. Walesky, C.M., et al., Functional compensation precedes recovery of tissue mass following acute liver injury. Nat Commun, 2020. 11(1): p. 5785.<br /> 16. Zhao, L., et al., Tissue Repair in the Mouse Liver Following Acute Carbon Tetrachloride Depends on Injury-Induced Wnt/beta-Catenin Signaling. Hepatology, 2019. 69(6): p. 2623-2635

On 2020-12-11 16:06:50, user José L Medina-Franco wrote:

Very nice work! Two previous diversity analysis of fungal products and metabolites have been published in Chemoinformatic expedition of the chemical space of fungal products FUTURE MEDICINAL CHEMISTRY, 2016 8, 1399-1412. http://dx.doi.org/10.4155/f... and Scaffold Diversity of Fungal Metabolites FRONTIERS IN PHARMACOLOGY, 2017, 8, 180. http://dx.doi.org/10.3389/f...

On 2020-12-11 08:54:13, user Mauro Maver wrote:

The previous reported issue:

The on-line resolution of Figure 1C was sub-optimal: we have now provided the repository with a newer version of it.

is now fixed!

On 2020-12-09 10:11:23, user Davide Bulgarelli wrote:

Hi-there seems to be an issue with Fig 1C (the heatmap) when opened in a browser-please do download the doc and visualise it with a pdf reader for a better resolution.

@Stramon1um and I are working to fix it-apologies for any inconvenience this may cause!

On 2020-12-11 02:24:54, user theasdgamer wrote:

This paper is very much needed to put to rest the asymptomatic covid superspreader myth.

On 2020-12-11 02:21:34, user Jim Edmonds wrote:

How long can you use the peptide without side effects?

On 2020-12-06 01:12:37, user James Eichenbaum wrote:

Congratulations on this great work! I am intrigued to see how you continue the study. I especially appreciate how approachable the writing and data presentation is to a general audience. What you propose could have a great impact in prophylactic treatment against SARS-2.

I believe you can further improve the clarity of the results section by including qualitative data, namely some images demonstrating the transition threshold for cytopathic effect used for TCID50 and viral neutralization. Additional quantitative analysis of cytopathic cell signals could make this even more convincing. As it stands, these sections are vague and rely on the reader to make assumptions about cytopathic effect or have prior knowledge of the subject.

You could provide statistical methods for more sections, similarly to how you present it in figure 1. Figure 4 and S4 would be more clear if significance/non-significance was explicitly stated.

I would be interested to see a further study in which the vulnerable population, which received mock doses, were continually separated. The abstract states that the mock group were 100% infected, but does not clarify that this was accomplished in the designated transmission period as one might infer from Figure 3.

Further investigation of the leukocytes and antibodies would be helpful to demonstrate the compound's prophylactic effect. Antibody presence is only indirectly demonstrated, so you could potentially use ELISA for a direct assay. Immune cell markers and inflammation signals could distinguish the mock treatment group from the compound-treated group.

Excited to see your future work!

On 2020-12-03 07:49:55, user Natalie Noble wrote:

Thank you this was an enjoyable paper to read! The implications of it are exciting. There were a few minor suggestions for the paper. The paper could be structured better, as it stands if feels unfinished. Separating your information into sections (introduction, results, discussion, etc) would help organize the paper, making it easier to understand and navigate. There were only two sentences discussing figure 4, adding to the unfinished feel of the paper (Figure 4 could use more analysis or perhaps discuss the implications of its results). The basis of the paper is that this peptide prevents infection of SARS-CoV-2 into the cell by disrupting the spike protein S, however the mechanism is unclear. It would be great to include a figure detailing the molecular mechanism of inhibition between the peptide and S, and the host cell. I don't understand why the ferrets were given the peptide in DMSO instead of the sucrose. Not only is the sucrose relevant to human application (since humans can’t have DMSO), but it looked like in the sucrose the peptide had a higher percentage inhibition of infection at a lower peptide concentration than in the DMSO (figure 2B). It just seems more effective. The implication of this work is intriguing. As potential vaccines are in the works for the general population, maybe these findings would be applicable to protect at risk populations that are unable to receive a vaccine.

On 2020-12-02 22:44:20, user Emma Leshan wrote:

Thank you for this wonderful work! This seems very promising.

In figure 1D, it seems that some of the data points don't have error bars, and it would be good to be consistent with the inclusion of error bars in all data points. It would also be nice to see a ribbon diagram showing how the spike protein and HRC peptides interact if possible.

In figure 2A, it would be good to label the x-axis as well so it is more clear that you are comparing different peptide concentrations.

I also wondered why you used DMSO in the buffer given to the ferrets, when using sucrose would be more relevant for translational potential in humans.

It would also be interesting to discuss the relevance of this technology now that vaccines are on the horizon. It would likely be applicable for use in cancer patients, babies, the elderly, etc.