On 2021-12-06 16:21:53, user Domenico Maiorano wrote:

This preprint has been now accepted for publication in Nucleic Acids Research and a link will be forthcoming. Of note, the implication of translesion DNA synthesis in replication of pericentromeric heterochromatin is laso now reported in human cells by Ben Yamin et al., EMBO J 2021, PMID: 34533226. Further, Twayana et al., PNAS 2021, PMID: 34815340, also now report an implication of TLS pol eta in promoting genetic variation at common fragile sites, suggesting conservation of function during evolution.

Domenico Maiorano

On 2021-12-06 15:49:22, user Simon wrote:

Many experts in the fields are skeptical of the validity and accuracy of the methods used in this work and therefore of the conclusions drawn in the article.

Criticisms:

The structure of the Omicron RBD made using mutations in Pymol cannot be trusted without proper structural data on the omicron RBD, because Omicron contains a high amount of mutations, the mutations cluster in a very disordered region of the RBD and influence of the glycans is disregarded (See e.g for their importance https://pubs.acs.org/doi/10....

The methods used to predict stability generally tend to work better on decreased stability than for gain of function. There is no benchmark against existing biophysical assays (e.g from deep mutational scanning) to show that the used method (i-mutant3.0) works on the RBD. In addition, the effect of multiple mutations are likely not additive but subject to epistasis. The used predictor is quite old and should be compared with newer approaches.

In general, protein docking is unreliable to estimate binding affinity in absolute terms. Especially in this case because the structures used were obtained by simple mutagenesis in PyMol without any equilibration/relaxation. The conclusions are not be trusted without additional experimental or more reliable computational analysis that includes the proper glycan shield of the protein and relaxed structures.

It is unclear how a table of amino acid composition and corresponding secondary structure prediction is useful or has any meaning for the conclusions of the article. The fact that the RBD is mainly alpha helical is not an indicator for high structural stability. The differences between the predicted fractions of alpha helices are meaningless and very small.

Some experts expressing their criticisms:

https://twitter.com/ElisaTe...<br /> https://twitter.com/RolandD...<br /> https://twitter.com/jpglmro...

On 2021-12-06 14:59:51, user Jasper Michels wrote:

A somewhat revised version of this manuscript has now been accepted by <br /> the ACS journal Biomacromolecules. An official link will be forthcoming.<br /> Regards, Jasper J. Michels

On 2021-12-06 11:51:44, user Martin R. Smith wrote:

Congratulations on this very useful test between these approaches, which is clearly a very important thing to do! Apologies if I've missed something in my quick read of the paper, but one concern I have about the interpretation of the findings is that low RF distances might be reflecting a lack of precision (i.e. more nodes collapsed to polytomies) rather than higher accuracy; see Smith 2019, Biol Lett, 10.1098/rsbl.2018.0632 – would this really make a tree "better"?

And I didn't quite follow whether collapsing nodes at random with -R might resolve nodes in a fashion that is not consistent with the original analyses; if so, this could potentially inflate RF distances.

Presumably the size of the simulated trees precluded the use of any of the more robust alternatives to the RF distance (e.g. Smith 2020, Bioinformatics, 10.1093/bioinformatics/btaa614)?

On 2021-12-05 07:06:57, user Anat Kahan wrote:

Please check out our paper: <br /> https://www.researchgate.ne...

On 2021-12-04 23:51:27, user Raghu Parthasarathy wrote:

Fascinating work! You note (p. 22) preservation of membranes by trehalose and other sugars and comment on the surface glycans in HA possibly playing a similar role. You might find interesting the ability of trehalose-decorated lipids from mycobacteria to protect membranes from dehydration: <br /> Christopher W. Harland, David Rabuka, Carolyn R. Bertozzi, and Raghuveer Parthasarathy. "The M. tuberculosis virulence factor trehalose dimycolate imparts desiccation resistance to model mycobacterial membranes," Biophys. J. 94: 4718-4724 (2008). http://www.cell.com/biophys...

Dehydration-resistance is fascinating, and (I think) under-studied.

On 2021-12-04 15:48:42, user Donald R. Forsdyke wrote:

TARGETING PATHOGEN NUCLEIC ACIDS

The study of Rouse et al. (1) is an extension of nucleic acid structural studies aimed at targeting pathogens at the genome or transcript level, rather than at the protein level (2, 3). Furthermore, having identified sites of interest, they explore ways of predicting whether an 18-base antisense oligonucleotide (ASO) is likely to be therapeutically effective. This is a promising first step in dealing with a long-neglected disease.

While some metric abbreviations (e.g. minimum free energy; MFE) are in general use, a table showing how their abbreviations correspond to historical usages would facilitate comparison with other works. For example, the contribution of base order (rather than base composition) to structure, which is here assessed as the Z-score (1), relates to the "folding of randomized sequence difference" (FORS-D) values of one group (2, 3) and the "genome-scale ordered RNA structure" (GORS) values of another (4).

For controls, the "Scanfold" technology includes the controversial shuffling of single bases so destroying base order (rather than of dinucleotides or trinucleotides that would have kept a degree of base order). The authors could point out that, for their purposes, randomizing base order by single base shuffling (5) is now generally accepted.

The authors note that the coding region of a gene can appear "to be unstructured (as evidenced by mediocre MFEs and positive Z-scores)". This is attributed to factors such as "to promote rapid translation," or "modulating accessibility to regulatory molecules." However, it has long been known that, whether genomes are DNA or RNA, the potential for stem-loop structures is a pervasive, genome-wide, property (4), which is likely to facilitate "kissing-loop" recombination. A need to encode proteins conflicts with this, especially in genes under positive Darwinian selection (5, 6). Thus, despite synonymous flexibility at third codon positions, there is generally greater structure potential in non-genic genome regions and, for eukaryotes, also in introns (rather than exons that tend to be purine-rich; 7).

Finally, for a discovered target site to retain its therapeutic vulnerability, it should be conserved from generation to generation within a species. At present, it appears that there are insufficient M. ulcerans sequences for detailing within-species conservation. The authors rely on inter-species data from other mycobacterial species. While this might facilitate the discovery of general anti-mycobacterial ASOs, they would not be optimized for an individual species.

1. Rouse WB et al. (2021) Analysis of RNA sequence and structure in key genes of Mycobacterium ulcerans reveals conserved structural motifs and regions with apparent pressure to remain unstructured. bioRxiv: doi.org/10.1101/2021.11.23.... (Nov 23)
2. Forsdyke DR (1995) Reciprocal relationship between stem-loop potential and substitution density in retroviral quasispecies under positive Darwinian selection. J Mol Evol 41:1022-1037.
3. Zhang C, Forsdyke DR (2021) Potential Achilles heels of SARS-CoV-2 are best displayed by the base order-dependent component of RNA folding energy. Comput Biol Chem 94:107570.
4. Simmonds P (2020) Pervasive RNA secondary structure in the genomes of SARS-CoV-2 and other coronaviruses. mBio 11:e01661-20.
5. Forsdyke DR (2007) Calculation of folding energies of single-stranded nucleic acid sequences: conceptual issues. J Theor Biol 248:745-753.
6. Forsdyke DR (1995) A stem-loop "kissing" model for the initiation of recombination and the origin of introns. Mol Biol Evol 12:949-958.
7. Lao PJ, Forsdyke DR (2000) Thermophilic bacteria strictly obey Szybalski's transcription direction rule and politely purine-load RNAs with both adenine and guanine. Genome Res 10, 228-236.

On 2021-12-02 21:31:49, user Matthias König wrote:

Hi Shin et al,

very interesting work.

Here some minor points to consider

• you do not mention MIRIAM identifiers. I assume all of your analysis is focused on the subset of BQB\_IS. This should be clearly stated and also be discussed how the metrics would work or could be extended to handle all of the MIRIAM qualifiers

• you mention the large set BiGG annotated models. One issue with the model collection is that many of the models are variants of a single ecoli model with minimal changes. Also all models are build from a common parts repository (the universal model), so that annotations are shared between the models. So despite being a collection of annotated models it is not very representative. In addition the model annotations are created based on a tool (https://github.com/draeger-...

• A comparison between the curated and uncurated models in biomodels would be very informative. An important part of the curation process is the addition of annotation at biomodels. Performing your analysis on the uncurated branch should provide a good estimation of the real annotation coverage/metrics.

• Uniprot annotations are important annotations for reactions which allow to encode the catalyzing protein. This information is very important to map protein data on reactions, e.g., in the context of FBA models. These should probably be encoded via the qualifier BQB\_HAS\_PART. This is crucial information and part of many models.

• a correlation plot between the metrics could be very interesting. It would be interesting to see color coded scatter plots of different subsets of the models (e.g. model size, domain, metabolism/signalling, year of submission)

Best Matthias

On 2021-12-02 20:18:22, user Stefano D. Vianello wrote:

Some of the statements and assumptions in this paper are very odd to read as a non-US reader.

"the fact that the U.S. has the best science education system in the world" is a very strong statement that surely would need references, or at least contextualisation vs the criteria used for this assessment. How did the authors reach the conclusion that the US science education system is better than that of every single other country in the planet? Have these analyses been performed in other countries? Which studies are the authors sourcing from?

"By almost any measure, the U.S. remains the world leader in basic and applied research. Individuals affiliated with U.S. institutions or companies have received 47% of all Nobel Prizes in physics, chemistry, and physiology or medicine and 51% of all patents awarded by the U.S. Patent and Trademark Office. U.S. scholars were the largest share of top cited authors published in the 2020 H5 citation index of the top five life science journals".

In the same way that the majority of Nobel Prizes have been won by men and this does not mean that men are leaders in the life sciences, the majority of US Nobel winners does not necessary imply that the US is a leader in the life science. Rather, it likely tells more about structural biases in the evaluation of science and in scientific participation and output in the life sciences, and bias in the Nobel attribution process. Similarly, papers in the life science are already heavily skewed towards US representation. Even with equal citation numbers, the majority of papers within any citation tier would thus also be from the US. The definition of what "top life science journals" are is also clearly built on anglophony and US-centric axiologies. The authors seem to see meritocracy in academic aspects that are clearly not acritically so, and that are in fact rife with Matthew effect and US-favourable biases. In the absence of more comprehensive considerations on these topics, these passages of the paper read very odd. Because the main conclusions and recommendations in this paper do not in fact even seem to need such forceful prescriptions of US supremacy, I feel these passages could even be removed.<br /> .

On 2021-12-02 15:34:05, user Ester Eckert wrote:

Great article! Super interesting data. I would not say that it disagrees<br /> with our results, it just further zooms in and shows how amazingly complex zooplankton<br /> microbe interactions are and how much we still have to discover.

On 2021-12-02 12:18:30, user Mateusz Iskrzyński wrote:

Dear Authors,<br /> just a short remark while browsing through many papers. Your research is of public interest and therefore you could increase its impact if the language of the abstract would not create unnecessary obstacles. It would be better to replace "subsidies" at least once with something less technical, like "Flows of chemical elements that enter an ecosystem from outside, called subsidies, are both natural and anthropogenic"

On 2021-12-01 14:45:16, user Firoz K. Bhati wrote:

hey i have gone through this manuscript since i also had some exposure of this field i have a question to ask, did you check the expression of OCT-1 and OCT-3 in these 3 cell lines?. these transporter involve in the influx of metformin in the cells. the progesteron is an inhibitor of these transporter, so my question is, it might be possible that the effect of metformin is reversed because these transporters were inhited by progesteron.Please Check this article<br /> https://www.ncbi.nlm.nih.go...

On 2021-12-01 14:42:51, user Claudia Tomes wrote:

This excellent paper describes a high-speed imaging protocol to reveal fusion pore characteristics during DCV exocytosis in primary mouse adrenal chromaffin cells. The Introduction addresses what is known/inferred regarding the heterogeneity of exocytotic responses in neuroendocrine cells and sets up the framework to investigate what is not known. The authors make a good case at comparing the strengths and limitations of TIRF with conventional fluorophores and amperometric recordings and at how the read outs of both methods are not easy to integrate or reconcile. The regulation of secretion by the fusion pore itself was, until now, assigned to size, behavior as a sieve, and commitment to full fusion versus kiss and run. The findings reported here by Zhang et al add a layer of complexity by revealing that the duration of the fusion pore is bimodal and regulated rather than stochastic, as previously assumed. In doing so, this paper opens the door to future work on the molecular mechanisms that underlie the bimodal nature of regulated DCV exocytosis.<br /> The experiments are elegant and very meticulous, many possible hypotheses and interpretations are offered and justified. Each conclusion is supported by more than one experimental approach and by numerous, rigorous, original controls. <br /> Interpretation of the results includes deep insights in addition to the primary description, such insights may or may not have been contemplated when outlining the experiments, but there they are, exquisitely capitalising on the findings. Examples that illustrate this point are: i) slow events derive exclusively from docked vesicles, which means that the state of docking influences subsequent behavior of the pore. ii) Release by newcomers is always fast, which implies that tethering, priming, docking and fusion occur within a few milliseconds of granule arrival at the fusion site. iii) Rapid efflux of luminal cargo through a narrow pore delays external dye entry, and so on and so forth.<br /> I can´t wait to see what the authors will do next with the new imaging technique reported here.

On 2021-11-30 12:21:10, user David Curtis wrote:

You might be interested in this paper which has now been published:

Exploration of weighting schemes based on allele frequency and annotation for weighted burden association analysis of complex phenotypes<br /> https://www.sciencedirect.c...

It applies weighted burden analyses to the same dataset as you have used to test for association with some common clinical phenotypes. I think it throws further light on the issues you address. Also, I think the notion of weighting variants differentially prior to collapsing them is an attractive prospect and I think it would be good if more attention was paid to such approaches.

On 2021-11-29 22:42:36, user Martin Rouse wrote:

Flower et al. PNAS 2021 showed that deletion of the 'ARK' of ORF8 is involved in dimerization. Wouldn't deletion of this sequence affect ORF8 dimerization? If the 'ARK' sequence is really acting as a 'histone mimic' and getting acetylated, wouldn't mutation of the 'K' to anything abolish its function? If acetylation of the 'K' is actually important for SARS-CoV-2 biology, generating a K-to-anything substitution should work to generate a damaged ORF8 protein. Perhaps the phenotypes observed have nothing to do with a H3K9-like sequence, and rather deletion of this sequence simply abolishes the function of ORF8 dimers...

On 2021-11-29 22:16:10, user Iain Cheeseman wrote:

My co-authors and I welcome additional public comments on this work, ideally by the end of December, 2021! #FeedbackASAP

On 2021-11-29 16:45:54, user Shourya Sonkar Roy Burman wrote:

It doesn't seem very complete. e.g. none of the zinc fingers have Zn ions predicted, even those with PDB structures.

On 2021-11-25 15:15:16, user Christophe Grosset wrote:

Our preprint has been accepted for publication in Communications Biology journal (Nature group) and a link will be provided very soon

On 2021-11-25 10:34:24, user Pedro Sánchez-Sánchez wrote:

Cool method! Will take a deeper look in the future :D

Just if it helps... I think the visualization of figure2 results would be clearer if the scale is the same for every violin plot!

On 2021-11-24 16:02:02, user poosapati sowmya raju wrote:

Dear Readers,<br /> The article is now published in "Journal of Fungi" and can be accessed using the link -https://doi.org/10.3390/jof... or https://www.mdpi.com/2309-6....<br /> Thanks

On 2021-11-24 06:56:19, user Gal Haimovich wrote:

My comments and suggestions are here:<br /> https://greenfluorescentblo...

On 2021-11-24 04:45:24, user Tianyu Liu wrote:

Hi, do you have plan to upload your codes for Polarbear to github? Thanks a lot.

On 2021-11-22 22:20:24, user Alizée Malnoë wrote:

The manuscript by Lei Li et al. reveals how plants maintain proteostasis under high light stress via a combined analysis of protein degradation rates, transcripts and proteins abundance in Arabidopsis. The authors performed a partial 13C labeling assay and identified 74 proteins with significant turnover rate changes in high light compared to standard light. Then they compared the transcriptional level and protein abundance of those 74 proteins and found negligible correlation between them, but a strong correlation between the turnover rate of the proteins encoded by nuclear genes and their transcripts. This study significantly advances the field of stress responses in plant biology with the findings of new direct or indirect targets of photodamage and how transcriptional processes counteract protein degradation to maintain proteostasis under high light.

Major comments<br /> - Please provide qPCR data to verify the RNA-seq results on representative genes showing significant changes e.g. RH2A2A, FTSH8, PARG2, BCS1, PUB54 in Fig 2C. For Fig 2A, a Venn diagram or an intersection analysis would be more informative.<br /> - Please describe in more detail how the LPF and especially PTO values were calculated based on the 13CO2 labeling experiment in the method.<br /> - Please explain the lack of change in D1 accumulation in Fig 5B and provide D1 immunoblot for each time point. Also indicate the meaning of NA in the legend.<br /> - In Fig 3, clarify the reasoning behind using the same peptide for THI1 and PIFI to calculate LPF in the two light conditions but different peptides for PSBA. Please provide an explanation in the text for calculating LPF using 2h HL for PSBA, 5h for THI1 and 8h for PIFI. What about the LPF from the same protein, such as PSBA, at different time points? Please provide an explanation of the absence of time points for PSBA, THI and PIFI.<br /> - Line 209, please add a sentence to explain that you are assuming that the translation rates are similar for all the detectable proteins in your manuscript. Indeed if the translation rate is different in HL compared to normal light for a given protein, then this will affect its labeling and thus estimation of the degradation rate.<br /> - Line 128-131, phenylalanine, tryptophan, and tyrosine are not abundant throughout high light treatment, and especially at 8h high light, they are back to the level in standard light. Rewrite these sentences to better reflect the results.<br /> - Line 168, comment on down-regulated proteolytic pathways in cytosol.<br /> - Abstract about plastid-encoded proteins, it should be noted that the distinction is made based on four observed proteins, do you think a generalization can be made for other plastid-encoded proteins?

Minor comments<br /> - Fig 1, A, B, C, D, the Y-axis and ticks on the axes should be added for more readability; A,B, add x-axis legend D, Y-axis should start at 0.<br /> - Line 118, do you mean that heat can induce NPQ by “contribute”? Please provide a reference and the leaf surface temperature measurements.<br /> - In Fig2 C, define pink color for p-values.<br /> - In Fig 3, it is difficult to distinguish the light green and dark green in the histogram. We suggest changing the color for the natural abundance (NA) or the newly synthesized peptides, label the x-axis and to use another acronym for "natural abundance".<br /> - Line 211, "one-third to one-half". Three LPF are presented in standard light conditions, the lowest being 28.5% and the highest 41.2%, that’s not “one-half” or does this refer to other proteins with LPF of 50%? In that case, data is not presented. Clarify or include the data in Table S4.<br /> - Line 216, how is the KD value calculated?<br /> - Line 235, it is difficult to identify PSBP in Fig 4. Please make it clearer.<br /> - Please show your protein Coomassie Blue staining results from the in-gel digestion for MS as a supplementary figure to see the amount of total proteins compared to explain the variation shown in Fig S2A.<br /> - Throughout text, make sure when you say "high light" to specify which time point (2h, 5h or 8h?).<br /> - Line 301-303, ferredoxin thioredoxin reductase also showed a significant abundance decrease after 8 hours. Please comment this in the text.<br /> - Line 344-347, the lower Fv/Fm level after longer high light exposure is not only due to the uncoupling of D1 degradation from its synthesis rate but also due to sustained NPQ forms such as qI (see Malnoë EEB 2018, doi.org/10.1016/j.envexpbot.2018.05.005).<br /> - RNA-seq method: which fold-change threshold was selected to consider the candidates? How many technical replicates were used?<br /> - Line 352, you state that protein degradation is supported by up-regulation of protease gene expression, but what about their degradation rates? In Chlamydomonas, FtsH transcript is upregulated in high light but its rate of degradation is also faster resulting in a modest higher accumulation of the FtsH protease (see Wang et al. Mol Plant 2017, doi: 10.1016/j.molp.2016.09.012).<br /> - Line 374, you state that translation failed to keep pace with protein degradation, you could cite work on chloroplastic translation rate being affected by oxidation of translation factors in cyanobacteria (see Jimbo et al. PNAS 2019, doi.org/10.1073/pnas.1909520116).

Jianli Duan, Jingfang Hao  (Umeå University) - not prompted by a journal; this review was written within a preprint journal club with input from group discussion including Alizée Malnoë, Maria Paola Puggioni, André Graça, Aurélie Crepin, Pierrick Bru.

On 2021-11-22 11:56:10, user Juhana Kammonen ⚡️ wrote:

Hi,

Thanks for the great story, I hope this gets accepted very quickly! I'm the head developer of gapFinisher. I'd be happy to help you investigate why gapFinisher failed to fill any gaps in the final scaffolds. For this I would need the long-read dataset you used and the SSPACE-LR output folder named "inner-scaffold-sequences" by default, I can then use my own HPC resources to re-run the filling and investigate. If this suits you, please throw an email to juhana.kammonen{ät}helsinki.fi so we can discuss details.

On 2021-11-22 09:54:23, user Tanai Cardona Londoño wrote:

Hi, thank you. Fascinating stuff. I love the many interesting ways in which ASR can be applied!

Just wanted to comment on the following statement:

“Photosystems, however, are complicated, specific structures with a relatively limited capacity for functional variability or spectral tunability.”

All photosystems have a common origin. And from that origin you have the emergence of a photosystem that can split water to oxygen generating over one volt of oxidative power, reducing quinones. On the other hand, you have a second photosystem that evolved to generate over -1 volt of reductive power to reduce ferredoxins and at a potential that allows the fixing of carbon dioxide, both spectrally tuned to a level of precision that still blows the mind of scientists. These can be “spectrally tuned” to do the same function as efficiently using far-red red light, shifted about 40nm beyond the standard PAR, in what’s known as the FaRLiP, widespread in cyanobacteria. You have the evolution of the spectrally tuned photosystems of the Prochlorococcus optimized to work with just blue light.

From the same origin, you have the anoxygenic photosystems that have been spectrally tuned to use infrared light all the way from 800 to 1000 nm. They all have evolved to use different type of pigments and cofactors as it is characteristic of each phyla or group.

Within cyanobacteria, you have other mechanisms of tunability and adaptability that allows the photosystem to be dynamically optimized to changing functions. So, for example, a cyanobacteria may carry encoded in their genomes a set of subunits that can be replaced to optimize the photosystem to low light, or high light, or low oxygen, and even far-red light. In fact, Photosystem II can be changed from water oxidation to chlorophyll-f synthesis. A single cyanobacteria strain, like Chroococcidiopsis or Nostoc can encode in their genomes the capacity to assemble over a dozen of differently of optimized photosystems II and photosystem I. Some of these photosystem II versions may have functions beyond water oxidation. The vast majority of these variant forms have not even been characterized yet.

So, what you say in the statement, is not really accurate… and in comparison with rhodopsins, it may be the exact opposite. I could argue that the functional variability and spectral tunability of rhodopsins pale in comparison with what photosystems can actually do... but a single pigment can only take you so far! :D

Think about it ;)

Again, thank you for the fascinating work!

Tanai

On 2021-11-22 07:41:27, user Danielle Swaney wrote:

Not sure if I made a mistake, but I tried to recreate your V2 method on a Q-Exactive plus and the duty cycle is quite long (6+ seconds), such that even with inferior chromatography (~15cm column) I only only get an average of 4 points/peak.

On 2021-11-21 06:54:31, user Chuck Norris wrote:

Is it possible that there's a deeper cycle? Maybe frogs, birds or even spiders could be a victim to the tasty snack dangling on a thread of grass that could effect them or help spread the fungus?

On 2021-11-19 13:27:22, user UAB BPJC wrote:

We (the Bacterial Pathogenesis and Physiology Journal Club at the University of Alabama at Birmingham) read this manuscript this week with great interest. Our compiled comments are listed below. We hope the authors will find them helpful.

Introduction<br /> 1) The authors make the claim that “While several hundred ISGs with various known functions have been identified, IFN has primarily been studied in its role in orchestrating anti-viral immunity. The role of IFN signaling in response to bacterial products, and how this may influence immune homeostasis in particular, is poorly understood.” There is a great deal of literature about the role of IFN signaling in non-viral responses, including bacteria (some of which the authors then go on to discuss). Several reviews in the recent years have collected this data in a way that gives a more complete understanding, including Gutierrez et al who seem to have published data in 2020 describing a mechanistic pathway by which beneficial bacteria activate Type I IFN signalling [1-4]. Perhaps the authors had a specific instance in mind (such as a mechanism, a specific type of response, or specific T-reg response), but in saying the role of IFN signaling in response to bacterial products is poorly understood in general dismisses a great body of work in the field.<br /> 2) The use of “tonic signaling” “tonic IFN expression”, and “basal IFN expression” is a little confusing. Consider clarifying what is meant by “tonic” and whether it is different from “basal” expression of IFN. <br /> 3) The final sentence in the authors’ introduction seems to be reversed, in that their data suggests that commensal microbiota promotes intestinal homeostasis via type I IFN signaling, whereas they say that type I IFN signaling promotes homeostasis via commensal microbiota.

Results<br /> 1) The authors discuss the expression of IfnB and Mx1 in their germ-free/monocolonized/specific pathogen-free experiment. Why is Mx1 important? What is it? Later on the authors identify it as an IFN-induced gene, but best practice would be to do so as part of the rational behind the experiment, rather then waiting until later to explain its significance. <br /> 2) Sample size irregularity and lack of error bars makes Figure 1A difficult to believe. <br /> 3) The “specific pathogen-free” mouse description is questionable for several reasons. Firstly, what pathogen is lacking? This is not addressed in the paper. Secondly, how were these mice developed? Were they developed by colonizing germ-free mice with a cocktail of microbes minus a specific one? Germ-free mice have many issues with immunological development that may skew or complicate the data, including issues in innate and adaptive immune cell development. In the methods the authors say they were ordered from Jacksons Laboratory, but there is no stock number given for these mice and a basic search does not return results that are “specific pathogen-free”.<br /> 4) In Figure 1A, there is no unmanipulated positive control (ideally a non-germ free WT mouse) for comparison. While the Specific Pathogen Free samples are a good indicator, they are still a manipulated strain. The authors would benefit from having a non-germ free WT mouse line as a control, especially considering the immunological developmental issues in a germfree mouse.<br /> 5) For Figure 1B, the Y axis is labeled mIFNb (pg/ml). For consistency with Figure 2B, the axis should be labeled “IFN? (pg/mL)”.<br /> 6) In Figure 1C there is no description of how the authors ensured only CD11c+ cells were being screened from the lamina propria tissue isolation. There is no described enrichment step in the paper, nor an isolation method. Additionally, the methods do not list a CD11c antibody in the flow cytometry list, which makes it difficult to interpret if the flow cytometry results of the pSTAT1 expression is gated off a CD11c+ population, a different population (such as CD4+ T cells), or total cells.<br /> 7) For Figure 2, the authors title the figure “B. fragilis induces IFN? expression in dendritic cells to coordinate Treg response”, but nothing in the figure discusses CD4+ cells, let alone Tregs. This figure specifically demonstrates that culturing with B. fragilis induces IFN? expression and downstream STAT1 phosphorylation in dendritic cells. While this may be involved in Treg development/activation, the data presented in no way demonstrates a direct connection between B. fragilis and Treg responses. Later on, the authors demonstrate this result, but in this figure the data does not support the claim made by the title.<br /> 8) From Figure 3 on, the authors no longer use the GF cells in their experiments, which is a disappointment, as they had such a district deficit in type I IFN signaling. Using the IFNAR-/- mice accomplish the effect of preventing type I IFN signaling but doing the same experiments using BMDCs from GF mice with and without a B. fragilis pulse would be interesting and would perhaps strengthen the argument that the commensal bacteria are important in both priming and driving type I IFN signaling. <br /> 9) For figure 3A, the axis is confusing, as the total population is not clear – is it 10% of all cells in the well are CD4+, Foxp3, and IL10 positive? Is it 10% of all CD4+ Foxp3+ T cells are IL-10+? If the axis was renamed to be more in-line with the text, that would help clear up the message of the figure. The text indicates that you are discussing the % of Tregs that are producing IL-10, which seems most reasonable, but the current axis could suggest that it’s 10% of all cells in the culture, and the figure legend suggests that the y axis represents the % of CD4 T cells in the culture that are Foxp3+ IL-10+. <br /> 10) For Figure 3C, it seems as though this should be a figure by itself that comes before Figure 3, or at the very least be Figure 3B, because the claim of Figure 3 is demonstrated in the current Figure 3B, which shows that IFNAR signaling in BMDCs is required for IL-10 production in Tregs. The current figure 3C shows the effect of losing IFNAR signaling in DCs alone, and should therefore go before the effect of this loss in DCs on Tregs. By changing the arrangement of figures the story flows more cleanly: B. fragilis treatment of DCs drastically increases their ability to trigger IL-10 production in Treg cultures > Loss of IFNAR signaling in BMDCs drastically affects the expression of many IFN-regulated genes and eliminates the effect of B. fragilis treatment > The loss of IFNAR signaling also impairs the ability of DCs to trigger IL10 production in Tregs, regardless of B. fragilis treatment. Conclusion: B. fragilis primes DCs to trigger IL-10 production in Tregs in an IFNAR-dependent manner.<br /> 11) Also for Figure 3 in its entirety, the DCs used in this experiment (according to the methods) are IFNAR1-/-, while in the text and in the figure they are listed as “IFNAR-/-“. They still have IFNAR2 and this should be noted. <br /> 12) For Figure 4B, a more detailed explanation of how the authors developed this analysis and what it is intending to show needs to be provided. There is next to no explanation of this particular result, only what the authors take it to mean. There’s no explanation of what the parameters of tSNE1 and tSNE2 are, or why the MLN seems to have a cluster of BF cells in the lower left region while the cLP has them disbursed. Indeed, the text suggests that both the MSN and cLP have BF cells clustered, but the cLP plot shows a disbursement of these cells in all the regions… In all this is a confusing figure that doesn’t really add anything to the paper without clarification as to what it is supposed to be showing.<br /> 13) For Figure 4C, the genes need to be listed in the same order for effective comparison between the two tissues. At a glance, it appears that MLN and cLP cells have a highly similar expression pattern… however, the genes are not the same in these two datasets. BP treated MLN cells have Oas2 as the most upregulated gene while BP treated cLP cells have Ifit3 as the most upregulated gene. Looking at the figure as is now would suggest that the two populations are fairly similar, but in reality there are several genes that are differentially expressed between.<br /> 14) Also in Figure 4C, the gene set offered is a very small subset of the type I interferon responding gene family. While a small set of this subset are differentially expressed, what is the significance overall? This dataset needs more gene expression data to show a more complete picture and justify the claim that bacterial colonization induces type I IFN signatures in intestinal Tregs.

Overarching Comments<br /> 1) The general conclusion of this paper is that type I IFN signaling in DCs, induced by commensal bacteria, is essential for Treg activation:<br /> a. From the summary: “Bacteroides fragilis induced type I IFN response in dendritic cells (DCs) and this pathway is necessary for the induction of IL-10-producing Foxp3+ regulatory T cells (Tregs).” <br /> b. From the Introduction: “Notably, B. fragilis induced IFN? and type I IFN signaling in dendritic cells (DCs) are required for commensal induced Foxp3+ Treg responses”<br /> c. From the Results: “Thus, type I IFN signaling in DCs is critical for commensal bacteria to direct Treg responses, even when IFN signaling is intact in T cells.”<br /> However, Figure 3B shows that while it is important for activation, these T cells are still activated and IL-10 production is still triggered at substantially higher levels over the untreated controls. Essential would suggest that the inability to perform this signaling would completely inhibit the DCs’ ability to trigger IL-10 production, or at the very least bring the expression level of IL-10 down closer to untreated controls.

2) This paper represents a good first pass of the data, but the authors need to reevaluate the extent of their claims. There are several experiments that need to be either repeated with higher sample sizes (Figure 1A for example) or re-evaluated for a less broad interpretation (Figure 3B).

3) Figure colors should be reworked to make the differences more distinct. In Figure 1, for example, it is difficult to tell that the Bf samples are blue while the SPF samples are black. The RNA-seq data colors make it difficult to compare differences in expression in the middle of the spectrum (Yellow is different from blue, but blue-green is difficult to detect from green-blue).

4) In general, the authors show convincing data for commensal bacteria playing a role in this type I IFN – DC – Treg process. However, there are two major issues with the authors’ interpretations. The first is that they only show priming with commensal bacteria is necessary for these effects – maintenance is not discussed. Secondly, the use of words like “essential”, “necessary”, “inhibit”, and “required” are not appropriate in many conclusions, such as the title of Figure 3. While the lack of IFNAR1 signaling impairs IL-10 production, it does not inhibit it. There is a reduction but not a loss of function.

Summary Response:<br /> The authors make a good effort in unraveling a complicated mechanism of commensal microbes’ effects on host immunity. The authors present a good deal of convincing data that show that commensal bacteria effect the ability of dendritic cells to trigger Treg IL10 expression. A more rigorous investigation into the mechanism of this phenotype is warranted, however, as the data does not show this activity to be essential the Treg activation. <br /> From the data presented, the authors are safe in arguing that commensal bacteria like B. fragilis prime dendritic cells, making them more sensitive to type I interferon signaling and more capable of inducing type I interferon signaling in a manner that more effectively drives Treg activation (as measured by IL10 production). Additional experiments to measure other factors of Treg activity would bolster the authors’ claims. <br /> 1. Ma, Y. et al. (2020) The Roles of Type I Interferon in Co-infections With Parasites and Viruses, Bacteria, or Other Parasites. Front Immunol 11, 1805.<br /> 2. Kim, B.H. et al. (2011) A family of IFN-gamma-inducible 65-kD GTPases protects against bacterial infection. Science 332 (6030), 717-21.<br /> 3. Gottschalk, R.A. et al. (2019) IFN-mediated negative feedback supports bacteria class-specific macrophage inflammatory responses. Elife 8.<br /> 4. Gutierrez-Merino, J. et al. (2020) Beneficial bacteria activate type-I interferon production via the intracellular cytosolic sensors STING and MAVS. Gut Microbes 11 (4), 771-788.

On 2021-11-19 00:01:06, user MRR wrote:

Congrats to the authors for the great work! I was wondering about Supplemental table 3. I cannot find its content even if introduced in the supplementals section. Also, where can one see the raw data for the accessions that were included in the GWA study, the values for the nine traits? Looking forward to hear from you. Thank you!

On 2021-11-18 19:04:36, user S. Olschewski and M. Rosenthal wrote:

This is a very interesting and timely study investigating the host interactome of Lassa virus L protein. Bunyavirus proteins need to interact with the host cell in order to get access to the

translation machinery, transport systems etc. The L protein contains the viral polymerase and is thus central to the viral replication cycle. Together with viral RNA and the nucleoprotein NP it constitutes the viral ribonucleoparticles, which are the structural and functional units for genome replication and transcription. So far only nucleoprotein and Z protein interactomes have been reported. The authors address this gap by inserting a

biotin ligase internally into the L protein, a position previously reported by Vogel and Rosenthal et al. 2019 (PMID: 30926610), and biotinylating all proteins in proximity to the L protein in a mini-replicon experiment, which recapitulates the steps of viral genome replication and transcription. The authors complement this dataset by silencing experiments using siRNAs. One of the proviral factors identified, GSPT1 – eucaryotic peptide chain release factor subunit 3a – was further validated by co-immunioprecipitation, co-localization and mini-replicon experiments as well as in infection experiments. This study will be of high interest for the scientific community and suggests GSPT1 as a potential drug target against Lassa virus infection. <br /> We have a few comments on the manuscript we hope the authors find useful and might want to consider:<br /> 1. We would appreciate mentioning, if in the constructs linkers have been used before or after the tags and which sequence those linkers would have.<br /> 2. In Figure 1B the authors used the term “polymerase activity” to label the y-axis while in Figure 5B its “minigenome activity”. If it’s the same assay and the same readout the<br /> terms should be consistent.<br /> 3. In line 135 the authors describe a slightly lower expression level of L-407-HA-TurboID. However, Figure 1B shows at least less than 50% expression level which is significantly<br /> lower. Was the detection of L performed with the same samples as the minigenome readout? If yes, the authors might want to discuss this discrepancy between<br /> expression and measured activity. <br /> 4. Only a small fraction of NP was biotinylated. The conclusion from the authors is that this “may reflect that only a low percentage of the total NP participates in the formation of a functional vRNP, or that in the vRNP, the majority of NP was not accessible to biotinylation or remained insoluble under the lysis conditions we used to prepare the proteomic samples”. This could easily be tested with Western blot analysis of the insoluble fraction after cell lysis.<br /> 5. In Fig. 2c it is not clear which factors occurred in more than one screen. A supplementary figure in which the hits in Fig. 2c are labeled (+ zoom into graph) would help to understand which of the hits are highly enriched.<br /> 6. Why haven’t the authors used a control in which TurboID-HA was transfected separately from the tagged L protein in the minigenome assay? <br /> 7. In the abstract and text 6 factors that influenced LASV infection are mentioned but in the figure 3C & S2B there are actually 7 factors labeled with “siRNAs significantly affected infection across two experiments”<br /> 8. In the two figures 3 and S2 (siRNA screen experiment, one for MOI 0.5 and one for MOI 1) it is unclear if for both MOIs biological repeats have been performed or if these were single experiments (in technical triplicates) that were analyzed together (MOI 0.5 and 1). It’s also not clear if the infection rate was similar for both MOIs. The authors might want to discuss the differences between the MOI 0.5 and MOI 1. <br /> 9. In the two figures 3 and S2 it is unclear why some dots have a white outline and other don’t. In Fig. S2 the upper UPF1 bubble is not completely with color.<br /> 10. For the siRNA experiments, LAMP1 and DDX3X knock-down as controls were only tested or displayed for MOI 1 (Fig S2) and not discussed at all. How do the authors explain that these siRNAs didn’t show any effect? DDX3 showed an effect in LCMV siRNA knockdown studies and effects upon knock-out for LASV and LCMV (PMID: 30001425). Although LAMP1 is described as an entry factor, Lassa pseudovirus infection studies with LAMP1 knock-down (approx. 15% remaining expression) showed no differences compared to wildtype cells (PMID: 29295909). The authors might want to discuss their results regarding LAMP1 and DDX3X.<br /> 11. The authors should confirm knock-down of their 6 or 7 hits via Western blotting.<br /> 12. In figure S2 the caption lists “C” instead of “B”.<br /> 13. The authors might want to compare their results also to the LASV NP interactome dataset available (PMID: 30001425). It seems strange that they compare to the LCMV NP interactome dataset but not to the LASV one. In Addition, also the LASV Z AP-MS dataset could be used for comparison since it is known that L and Z interact (PMIDs: 34226547, 34697302, and https://doi.org/10.1038/s41... and although in the replicon system Z is of course not present it would have been interesting to have a look at possible commonalities.<br /> 14. In the validation experiments for GSTP1 via CoIP (Figure 5) the “Input” amount of L-HA differs strongly between the different samples. Problematic here is that the input for the control transfection without FLAG-GSPT1 shows a lower expression of L compared to the conditions with FLAG-GSPT1 and after FLAG-IP there is also IP of L detected in absence of FLAG-GSPT1. Like this it is hard to reliably conclude anything from these blots. The Co-IPs could be also repeated via pull-down of LASV L-HA.<br /> 15. As the bands in the blots of Figure 6c are quite smeary, the knock-down effect of GSPT1 compared to NSC is not clearly visible. Therefore, it is hard to conclude that the inhibitory effect is due to the GSPT1 knock-down if the knock-down isn’t confirmed. Similarly, the smear for LASV GP2 makes it hard to compare the GP2 levels. Therefore, to conclusion that GP2 levels have decreased 72 h.p.i. (lines 231-236) is not convincing. Since the authors have a functional NP antibody for Western blot, the blots from Fig 6c could be repeated additionally detecting NP. This would also help investigate if the effect the authors seem to observe is limited to the secreted GP or also valid for cytoplasmic proteins such as NP.<br /> 16. For the inhibitor studies in figure 6G, the actin control bands are also less intense in presence of the inhibitor, this makes conclusions about the specific targeting of GSTP1 difficult. This should be discussed. Also, (G) is not mentioned in the respective caption, instead (D) is listed twice.<br /> 17. In their hypothetical models the authors refer to NP as the cap-binding protein despite the fact that the respective reference (PMID: 21085117) fails to provide any hard evidence<br /> for a cap-binding function of LASV NP and other groups could not confirm a role of the proposed cap-binding residues during viral transcription (PMID: 21917929).<br /> 18. Since L, NP and the viral genome are sufficient for viral genome replication, transcription and viral protein translation – viral protein translation can’t depend on the eIF4E-Z interaction the authors propose in Fig S5. Also, the authors didn’t mention the role of L- eiF3CL interaction in any of their model.

Written by<br /> Silke Olschewski and Maria Rosenthal

On 2021-11-18 17:47:05, user Giovanni Giobbe wrote:

The article has been published in Nature Communications on 16.11.2021

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

DOI: https://doi.org/10.1038/s41...

Please cite the revised and published version

On 2021-11-18 11:28:27, user Kresten Lindorff-Larsen wrote:

The manuscript by Bock & Grubmüller describes a detailed, multi-pronged computational study of the complex and important effects of cooling during sample preparation for cryo-EM. The paper is generally easy to read, appears technically sound and provides relatively clear results that will be of interest both to theoreticians and practitioners of cryo-EM.

Over the last 10 years cryo-EM has delivered increasingly high-resolution structures that in some cases now rival those of e.g. X-ray crystallography. In addition to examining the structures of macromolecules, cryo-EM may also provide more detailed insights into their energy landscapes because it in principle is a single-molecule technique that enables the visualization of the conformational distribution of molecules.

These advances leave two questions that have been difficult to answer. First, to what extent does the “average” structure under cryogenic conditions reflect the ambient temperature “average” structure [realizing that the term average here is somewhat misleading, the authors will understand what is meant]. Second, to what extent does the distribution of conformations (conformational ensemble) present in the cryo-EM sample reflect the distribution at ambient temperatures [leaving aside the technical difficulties of determining structural models of these ensembles from experiments]. While the first question can to a certain extent be answered by comparing structures solved at cryo-conditions with those at ambient temperature (by crystallography), the second question lies at the heart of the utility (and large potential) for cryo-EM to study conformational ensembles.

This study provides welcomed data in an area that has been lacking detailed and quantitative modelling, and where experiments are difficult. The results are promising in the sense that they support the idea that cryo-EM can to a large extent capture conformational ensembles at ambient temperatures. Importantly, the study provides a framework to think about these problems in a more quantitative manner that will hopefully spur additional experiments and analyses.

Specific comments:

Major<br /> p. 4:<br /> I must admit that I found the RMSF-based analysis somewhat difficult to follow in places. First, just to be sure could the authors confirm that in each case the RMSF is calculated “locally” that is using an average over the specific simulation as reference. Second, when I look at Fig. S1 it appears that there are still some changes in the RMSF curves even towards the end of the simulations that are of the same magnitude (but in the opposite direction) as those observed during cooling. Is that correct or am I looking at the figure in the wrong way?

Also, while I realize that it is difficult to boil down a complex ensemble to one or a few numbers that can be tracked, it would be useful with alternative ways of looking at the ensembles. Are there local differences that are not captured by RMSF? What about rotamer distributions. I will leave it up to the authors whether to explore these issues further in this paper.

p. 11:<br /> In terms of future experimental studies, what kinds of tests of the models could the authors envision? For example, the authors discuss work by Chen et al (Ref 24) on differences depending on the starting conditions. Do the authors’ analytical model capture such effects? Do the authors’ results lead to specific criteria for selecting good model systems to test the effects of cooling on conformational ensembles?

p. 11/12:<br /> Maybe the authors could also briefly discuss the relationship to other techniques that rely on (rapid) cooling including ssNMR and EPR. I realize that the cooling process is different, but it might still be worth speculating on how the approaches and models the authors present could be extended to other situations. In this context I’d also like to point out relevant work from Rob Tycko studying protein folding by ssNMR with rapid injection into a cold isopentane bath (https://dx.doi.org/10.1021%....

Minor<br /> p. 1/2: In the discussion of molecules settling into the lowest free energy minima at slow cooling rates, it might be worth making it clear that these minima may well be different from the minima at ambient temperatures.

p. 4: In the T-quenching MD simulations I couldn’t easily find whether the simulations were performed using pressure control and if so how.

p. 6: “the atoms are subjected to harmonic potentials with a force constant c which are uniformly distributed in an interval from −d to d” makes it sound like it is the force constants that are between -d and d. Consider rephrasing.

p. 6 “Model3 is a combination of model2 and model3,” should be, I guess, “Model3 is a combination of model1 and model2,”

p. 6: It is not clear what value of the pre-exponential factor that the authors use. I did not go through the maths, but I would assume that the choice would affect the “effective” barrier heights e.g. in Fig. 4. It would be useful if the authors would clarify this, given that there has/is some discussion about what pre-exponential factors are relevant for conformational changes in biomolecules.

p. 11: The authors write “Biomolecules can thermodynamically access more conformations at room temperature than at the cryogenic temperature”. While that is probably mostly true, examples such as cold-denaturation suggest it isn’t universally true.

Kresten Lindorff-Larsen, University of Copenhagen

On 2021-11-16 02:38:55, user Iris Young wrote:

The capability of cryo-electron microscopy (cryoEM) to capture multiple and native-like conformations of large macromolecules is transforming structural biology. This manuscript explores intricacies of the cooling process as it relates to structural ensembles. Specifically, how do variations in starting sample conditions (water layer thickness, water/sample starting temperature) and cooling (ethane layer thickness, rate of cooling) affect the distribution of structural states captured in the resulting micrographs? Can we be confident that the results of "time-resolved" cryoEM experiments are representative of barriers and basins we hope to capture? By a combination of molecular dynamics simulations and cryoEM experiments, the authors guide us to an empirical understanding of these questions.

To understand the relationship between cooling and structural ensembles, we must begin with the thermodynamic principles in play. Ensembles represent the many possible conformational states of a structural unit, and the occupancies of the individual states depend on the energy landscape across which they are related. At the extremes, we may imagine an ensemble cooled instantaneously to 0 K, whose component structures would not be able to traverse the energy landscape in any direction, as well as an ensemble injected with enough energy to overcome any energy barrier on the landscape (i.e. a system at thermal equilibrium), whose component structures would move freely to occupy all possible states. In the latter case we would not expect all states to be occupied by the same number of particles, however — particles with exactly enough energy to breach a particular energy barrier are equally likely to fall to either side of it, but particles at different starting points with the same starting energy have different likelihoods of escaping their local energy minima. In aggregate, this produces the Boltzmann distribution, in which the populations of different states depend entirely on their relative energies.

For intermediate temperatures, it is useful to speak in shorthand of energy barriers and a system's ability to overcome them. We believe the introduction of this manuscript deserves a more complete illustration of the fundamental principles, however, and would encourage the authors to possibly even add a diagram or two to aid in this effort. It is too easy to confuse the fact that cooled structures move toward global energy minima with the idea that cooling gives them the energy needed to overcome energy barriers, which is precisely the opposite of the truth. The abstract in particular ought to be reworded to avoid this misinterpretation.

The design of the computational and wet lab experiments is carefully geared toward isolating the relevant variables and reproducing the relevant states and processes. For example, to choose the equilibration times to use in MD simulations, the authors first simulated how long it would take for samples of various thicknesses to vitrify. By and large we are satisfied with the parameters of these experiments, but we question one unsupported assumption: the authors enforced an ethane bath outer boundary held at constant temperature. This could be possible if the ethane bath remains in contact with a heat sink and the equilibration time between ethane and the heat sink is negligible compared with that between ethane and the sample, but we do not see this discussed or justified, nor is this standard practice when freezing grids, as the ethane bath is isolated from the standard liquid nitrogen heat sink after reaching the desired temperature to prevent the ethane from freezing solid. We were confused by the plot of equilibration times for ethane layers of different thicknesses, and hypothesize that the unexpected (to us) trend is a result of this boundary condition: we would have imagined a thicker ethane layer to allow quicker absorption of heat from the water layer, but the opposite is shown. Moreover, there is often a cold gas layer (see work by Rob Thorne on hyperquenching: https://pubmed.ncbi.nlm.nih... and https://journals.iucr.org/m.... While this complication might be very difficult to simulate, it should be explained how it might affect the interpretation of results.

Although it does not impact the methods or results of this paper, we are also unconvinced that the use of any vitrification bath held at a lower temperature than the commonly used ethane bath would necessarily result in faster freezing, as heat transfer is also dependent on heat capacity (hence the selection of ethane for plunge-freezing rather than liquid nitrogen!) Propane does indeed appear to have a higher heat capacity than ethane at similar cryogenic temperatures, so in the case of an ethane-propane mixture, this assumption does hold, but we would prefer the authors include this detail.

As for the results of the study, it is well-evidenced and clearly presented that conformational distributions present before plunge-freezing are reflected in vitrified samples when a standard vitrification protocol is followed, and that the rate of cooling does indeed impact the degree to which these distributions are preserved. We especially applaud the authors' careful wording around what interpretations are supported or suggested by the data, leaving open the remote possibility of other explanations — they draw very clear distinctions between observations and analyses. This is good science!

Finally, we find the implications of the study meaningful. The selection of a ribosomal complex as an example particle perfectly illustrates the biologically relevant range of flexibilities and temperature-dependent conformational ensembles. This example gives us an intuitive measuring stick for other types of structures. Taken as a whole, the analyses inform future "time-resolved" studies using cryoEM and the design of other experiments that depend on the preservation of a conformational ensemble by rapid cooling. This is a very exciting direction of inquiry that we will continue to watch with great interest!

Minor points:<br /> - The authors could make the introduction even more clear and accessible by specifying that liquid specimens present a challenge because their vapor pressure is incompatible with high vacuum.<br /> - We favor the wording "most often liquid ethane" over "mostly liquid ethane" for describing the standard vitrification setup.<br /> - Sentences such as the second to last sentence in the second paragraph of the introduction could be broken into multiple sentences or otherwise simplified to avoid confusion among the several "which," "from" and "and" clauses. <br /> - Sobolevsky’s work on TRP channels and vitrification probably deserves a mention in the intro alongside the other examples, esp. because those probe a natural temperature sensor! (https://www.nature.com/arti..., https://www.nature.com/arti...<br /> - Tomography can be used to resolve position in ice layer, “Apart from the water-layer thickness, the temperature drop also depends on the position within the layer with the slowest drop in the center (Fig. 1a), which is relevant, because in the time between the spreading of the sample onto the grid and the plunging, the biomolecules tend to adsorb to the air-water interface 62.” (https://pubmed.ncbi.nlm.nih...<br /> - The authors could comment on whether the effects of being in different parts of the ice layer would affect RMSF values. If the effects are not too small, reconstructions from different layers could yield B-factors that could deconvolute different effects! <br /> - Are there local effects to their RMSF kinetic/thermodynamic models in the ribosome? For example, could they subdivide RNA/Protein, small/large subunit, exterior/interior sites, etc? Are there any regions that increase conformational heterogeneity upon cooling (as we have seen often in multi temperature crystallography)? Using a global RMSF metric may be leaving out interesting phenomena. <br /> - Are the frames and code deposited somewhere for others to examine?

Iris Young and James Fraser (UCSF)

On 2021-11-18 00:31:40, user Iris Young wrote:

This manuscript describes the first use of microED diffraction data for ab initio phasing and the instrumental setup necessary to achieve it. While the authors have presented phasing as the major accomplishment here, we find the modifications to the data collection process much more interesting. Firstly, any diffraction dataset at this resolution should be amenable to ab initio phasing, if the intensities are measured accurately enough. Secondly, the conditions under which such accurate intensity measurements can be made and how accurate they need to be to enable phasing are not adequately explored here; this is a proof-of-concept but not yet fleshed out in a way that lets us know how useful it will be. The description of how this was enabled, by contrast, is very well-detailed and immediately valuable to the scientific community. We will address both foci of the paper but will recommend the authors either shift the narrative to better center this work's strengths or carry out additional computational experiments.

First, regarding phasing/the accuracy of the intensities: Building on this group's tremendous effort to advance the capability of microED to produce high-resolution crystal structures from nanocrystals on TEM grids from only minutes of data collection, the authors now present proof of concept for ab initio phasing of small proteins from such datasets. Whereas molecular replacement has all but obsoleted ab initio phasing of proteins with known structures or homologs, truly new structures remain nontrivial to determine by crystallography, where unmeasured phases limit us. Still, the short data collection times for microED, relative ease of preparation of nanocrystalline samples, and increasing accessibility of electron microscopes could make ab initio phasing a powerful option. The capability for ab initio phasing of macromolecules is therefore, in this context, another core strength of the method.

The prospect of using direct methods for phasing structures missing easily discernible secondary structures is a natural next step. The authors probe the limits of the datasets in the current manuscript, describing multiple attempts at phasing and detailing which did and did not come to fruition, and suggest further routes for optimization. There is further analysis possible here that we would very much like to see:<br /> - Why are the resulting R-factors so poor compared with X-ray crystallographic structures of comparable resolution? If the authors apply the same phasing methods to X-ray and microED datasets of the same molecule side-by-side, what differences emerge? What fundamental differences can we expect between datasets from these two methods, including major sources of error, and how should we plan to account for them? The availability of HEWL structure factors from XRD (http://scripts.iucr.org/cgi-bin/paper?S0907444997013656), with very low R-factors, could also enable an analysis of the errors in the intensities derived from microED, with very high R-factors, which we would be very keen to read.<br /> - Thinking now of applicability beyond model systems, at what resolution/accuracy of intensity measurements (both of which might be limiting in other cases for microED) should we expect ab initio phasing to be possible? While the space of potential fragment inputs is explored, the only exploration of the structure factor inputs are the lysozyme or proteinase K datasets. Truncations and noise additions to these datasets can provide a guide of the applicability of the method and the importance of the new, more accurate, data collection setup.

We find the very thorough description of all stages of instrument setup, sample preparation and data processing to be indispensable. The authors describe in detail what steps were taken to ensure the experiment was physically possible and why they were necessary. Most importantly, using the microscope in diffraction mode is normally incompatible with the dynamic range of the detector, so the authors describe overriding an engineering control that disables the camera in diffraction mode and selecting a variety of instrument settings (spot size, C2 aperture, beam size, microprobe mode, and exposure time) to keep the dose per frame as low as possible. Their successful ab initio structure solution of proteinase K and lysozyme using this setup and standard crystallography data processing software is a convincing proof of concept of this setup. Framed a little differently, this work could certainly stand on its own as a description of the instrumental setup necessary to produce these datasets.

In summary, the manuscript is generally well-written, detailed and clear. It is accessible to the average cryoEM microscopist as well as sufficiently complete from the perspective of a methods developer. Aside from our concerns with the framing of the limits of applicability to different resolutions and intensity accuracies, we find no major issues with the work that should delay its wider adoption.

One minor comment:

• “For MicroED data from three-dimensional macromolecular crystals, phases have thus far only been determined by molecular replacement.” We note that this group has used radiation damage for phasing too: https://pubmed.ncbi.nlm.nih.gov/32023481/

Iris Young and James Fraser (UCSF)

On 2021-11-17 22:50:42, user Mattia Deluigi wrote:

Congratulations on this major breakthrough. The new cryo-EM structures of inactive-state GPCRs are a great advancement and certainly overcome several inherent limitations of crystal structures, which so far have been the only way to solve these receptor conformations. However, we would like to point out two issues with the current version of the manuscript:

1) To compare the cryo-EM approach with crystallography, the new cryo-EM structure of the hNTSR1:SR48692 complex is compared with a crystal structure of rNTSR1 bound to the same ligand, which has recently been reported by our lab (ref. 16; DOI: 10.1126/sciadv.abe5504; PDB ID: 6ZIN). However, we have to note that an essential part of our work was not considered in this comparison of cryo-EM and crystallography, resulting in (i) a potentially misleading description of some differences and (ii) an unnecessary downplay of the crystallographic approach.

As mentioned by the authors, most crystal structures of GPCRs require prior protein stabilization. This has also been the case in our study, which resulted in a first structure of the rNTSR1:SR48692 complex (PDB ID: 6ZIN) using the NTSR1-H4<br /> mutant. However, we realized that four stabilizing mutations were likely to affect some of the receptor structural features. Thus, in the same study, we reverted those four mutations to the wild-type residues, giving rise to NTSR1-H4bm and a second structure of the rNTSR1:SR48692 complex (PDB ID: 6Z4S). The structure of this back-mutant represents a more native-like rNTSR1:SR48692<br /> complex, obtained already prior to the cryo-EM structure. Consequently, we believe that a fair comparison of the cryo-EM structure with a crystal structure requires the consideration of the back-mutant in the first place, which is not the case in the current manuscript. Comparison with the back-mutant would allow, e.g., a better discrimination of which differences naturally occur between human and rat NTSR1, which is crucial for drug design.

Thus, some structural aspects detailed in the current manuscript need to be reconsidered:

• The difference in the position of TM1. As stated in our study (ref. 16; DOI: 10.1126/sciadv.abe5504), we suspected that the position of TM1 was affected by crystal packing forces in the structure of NTSR1-H4. However, this is not the case in the back-mutated construct (NTSR1-H4bm), as has been nicely confirmed by the cryo-EM structure. The conformation of ECL2 and the intracellular half of TM7 are also more native-like in the back-mutant structure (the difference at Y7.53 between cryo-EM and crystal structure discussed by the authors is nonetheless present, and we agree that the DARPin fusion can influence the NPxxY region).

• The differences in the residues beneath the ligand’s carboxylate group (e.g., 6.51, 6.54, 6.55, 7.42). We reverted the mutations at positions 2.61, 3.33, and 7.42 to their wild-type counterparts explicitly to provide a more native environment in these regions. Accordingly, the differences between the back-mutant structure and the cryo-EM structure are smaller or absent. It should also be considered that the cryo-EM and crystal structures could have captured partially different inactive receptor conformations.

• In the structure of the back-mutant, we were able to model ECL3 and the sidechains of F344(7.28), Y347(7.31), and W339(ECL3) (although the electron density for the latter was weak). Nonetheless, as pointed out in the preprint, some differences in the sequence between human and rat NTSR1 probably induce a slightly different conformation of the extracellular tip of TM7 and ECL3. The description of these differences is of great relevance to drug design.

Crucially, the ligand-binding mode is nearly identical in the cryo-EM and crystal structures underlining the validity of both approaches. In addition, the observation that the inverse agonist SR48692 is accommodated in a substantially wider binding site compared to the agonist-bound structures, as pointed out in our study, has now been nicely confirmed. It is correct that the gain of knowledge from the crystal structures of our engineered NTSR1-DARPin fusion is mostly limited to the extracellular receptor portion — as explicitly stated in our study — and that the cryo-EM structure now overcomes this limitation (e.g., by describing the Na+ pocket) and confirms the validity of the ligand-binding site.

2) The second problem is related to the comparison between the density of the hNTSR1:SR48692 cryo-EM structure and the electron density of the rNTSR1:SR48692 crystal structure. While the quality of the density in the cryo-EM structure certainly allows<br /> one to overcome the limitations of the crystal structure (e.g., modeling of ECL1, Na+ and H2O), we believe that the current<br /> comparison is not entirely fair.

If the crystallographic 2Fo−Fc map for the ligand (Fig. 2b) is contoured at a typical sigma=1.0, it also clearly features the chlorine atom of the chloroquinoline ring of SR48692. This is also true for the structure of the back-mutant mentioned above (PDB ID: 6Z4S), see fig. S5D and fig. S11A in ref. 16 (DOI: 10.1126/sciadv.abe5504). Thus, we believe that a fair comparison must include the 2Fo−Fc map contoured at sigma=1.0 and not only at sigma=1.25. In the end, it should be acknowledged that the electron density maps allowed unambiguous modeling of the ligand, and indeed the ligand-binding mode is nearly identical in the cryo-EM and crystal structures. To reiterate point 1 above, a comparison with the back-mutant in the first place makes more sense, and it does not reduce the impact of the cryo-EM structure (although the differences are vanishingly small, the ligand also adopts a more native binding mode in the back-mutant). Compared to the non-backmutated structure, the resolution of the back-mutant is very similar (2.71 Å), and the quality of the electron density allowed unambiguous modeling of most key residues (see fig. S12, A–C, in ref. 16 (DOI: 10.1126/sciadv.abe5504)).

Minor suggestions:

• In the legend of Fig. 2d, “ECL2” should be corrected to “ECL3”.

• In the legend of Fig. 2e, “rNSTR-H4” should be corrected with “rNTSR1-H4”. Note that in the back-mutant (PDB ID: 6Z4S), the F7.42V mutation has been reverted to the wild-type Phe residue.

• “Fig. 2c” should be corrected with “Fig. 2d” at the end of the following sentence: “First, the remodeling of the TM7-ECL3 region allows W334 in ECL3 to be resolved in the hNTSR1 structure loosely capping the top of the hydrophobic chloro-naphthyl and dimethoxy-phenyl moieties of SR48692 (Fig. 2c).”

• In Extended Data Fig. 3, the legend of panel a actually describes panel c. The legend of panel b describes panel d. The legend of panel c describes panel b. The legend of panel d describes panel e. In the name of the crystallographic construct, a hyphen is missing between “NTSR1” and “H4”.

• In both the main text and Supplement, “NTSR” is sometimes written instead of “NTSR1”.

Best regards,

Mattia Deluigi, Christoph Klenk, and Andreas Plückthun

On 2021-11-15 19:14:55, user DaviesLabIowa wrote:

This preprint was eventually splint into two publications. The one linked at the top of the page as well as one published in Scientific Reports: https://doi.org/10.1038/s41...

On 2021-11-15 12:32:07, user °christoph wrote:

Q : does your ICOR model include learning of the (predicted) mRNA secondary structure of the codon context that might influence the choice of synonymous codons? see here for an example.

On 2021-11-12 18:37:39, user Subhamoy Mahajan wrote:

Please visit https://github.com/subhamoy... for associated code and tutorials. There has been several updates since the pre-print was posted: two new depth-variant PSF, compatibility with TIFF format to generate multi-dimensional images compatible with ImageJ, and addition of Gaussian and Poisson noise, etc.

On 2021-11-12 09:09:25, user Jeroen Demmers wrote:

The paper is now published in PLOS ONE: https://doi.org/10.1371/jou...

On 2021-11-12 03:34:16, user meng dawn wrote:

A new result we just proposed. We hope to have more exchanges with colleagues in the field of single-cell metabolomics and microbiology. Thanks for your attention.

On 2021-11-11 13:38:28, user Wasim Khan wrote:

The manuscript by Chiu et al studies the role of mitochondrial calcium in tumor progression

General comments:

1. MCU is the not only player in mitochondrial calcium flux. Transport of ca2+ from the ER has not been discussed in the introduction.

2. ER and not cytosolic ca2+ is important for mitochondrial calcium flux.

3. The MCU has contrasting roles in cancer progression as it all depends on how the cancer cells were reprogrammed and what is their site of origin.

4. HSP60 is not a marker of mitochondrial mass. A better alternative would be VDAC or COXIV

5. Since cells die upon MCU knockdown, how did the authors differentiate between live and dead cells in their mitochondrial assays. More dead cells in shMCU would lead to less mito ca2+, ROS and OCR.

6. MCU over expression promotes oncogenic paragraph contains results that describe MCU knockdown and not over expression.

7. The study describes a well known fact that MCU regulates calcium flux in the mitochondria and confirms this observation in ERMS.

8. The connection between MCU and TGF beta pathways is interesting and should be commented on more.

9. More ROS generation is not always beneficial to cancer cells. There has to be a balance as in normal cells its just that in cancer cells the levels of ROS are higher.

10. Mitochondrial calcium is essential to run the TCA cycle and the authors have not commented on this aspect.

11. The study is well designed to achieve what the authors want to investigate.

12. The manuscript is well written with only minor adjustments required to improve readability.

13. Data is clear and very well represented.

On 2021-11-11 09:11:31, user Toan Phan van wrote:

This is a nice work. However, I wonder that why didn't the authors check the protein expression of epithelial acinar cell markers such as Aqp5, Mist1 in section 3.4, figure 8?

On 2021-11-11 03:33:53, user michael_in_adelaide wrote:

This is now published in the Journal of Alzheimer's Disease with DOI: 10.3233/JAD-210200

On 2021-11-11 00:27:38, user Kenta Watanabe wrote:

This paper has been published in "PeerJ" after peer review (on 10Nov, 2021). https://doi.org/10.7717/pee...

On 2021-11-11 00:15:52, user Joshua Mylne wrote:

This work was published 11-Nov-2021 in RSC Chemical Biology https://doi.org/10.1039/D1C...

On 2021-11-10 21:15:44, user Sean Munro wrote:

This is a fantastic resource, but there seems to be a serious problem with one of the Data Files. In the Summary Data file, each protein pair is identified by their Uniprot IDs. However in the large file with the predicted structures for the dimers from the HuRI dataset, the pairs are identified by Ensembl IDs, which makes it very hard to find a .pdb file for a pair shown in the Summary Data File. Moreover, even if you look up the Ensembl ID from the Uniprot ID, then some cannot be found in the HuRI dataset. For instance, USO1 is UniProt ID O60763, and is Ensembl ID ENSG00000138768, but this is not to be found in the HuRI dataset.

Please could the HuRI dataset be reformated so that the .pdb files are identified with the UniProt IDs, in the same way that they has been done for the Hu.Map data set.

I hope that this is clear, but do let me know if not.

Many thanks,

Sean Munro

On 2021-11-10 09:58:10, user Marc RobinsonRechavi wrote:

Under Data and materials availability, the authors write:

Additional script and raw data are available on Github upon publication.

This is a publication, i.e. it is made public as part of the scientific record and is citable, thus I strongly invite the authors to make the corresponding scripts and raw data available without delay.

On 2021-11-09 16:29:05, user Lainie Brice wrote:

The preprint has been published in Ecology Letters, and the final article will be linked to the preprint soon. In the meantime, you can find the article here: https://onlinelibrary.wiley....

On 2021-11-09 14:49:40, user Doyonlab wrote:

Authors should disclose the target sequences for their gRNAs within the manuscript.

On 2021-11-08 16:42:36, user Nicolas wrote:

The current Preprint has been accepted for publication and a revised version can be accessed here: https://doi.org/10.1111/nph...

On 2021-11-06 20:07:56, user Binks Wattenberg wrote:

We find this to be a very exciting and compelling study that establishes that the turnover of the ORMDL proteins is regulated by sphingosine-1-phosphate signaling in vascular endothelial cells. We do, however, have a different model as to the role of this system as a homeostatic mechanism controlling sphingolipid biosynthesis.

We consider the ORMDLs to be regulatory subunits of SPT which, like many regulatory subunits, are not intrinsically inhibitory until they are triggered by a ligand. Our evidence strongly indicates that the ligand for the SPT/ORMDL complex is ceramide. With this in mind, we envision that the S1P regulation of ORMDL stability overlays an acute and direct ORMDL-dependent regulation of SPT by ceramide. In our view, the S1P-dependent stabilization of the ORMDLs maintains them as ceramide-sensitive regulators of SPT. In the absence of S1P signaling, degradation of the ORMDLs renders the SPT complex insensitive to ceramide and therefore strongly increases SPT activity.

Below we outline evidence which brings us to this view. But before doing so, we would like to emphasize one of the exciting and important aspects of the work outlined in this pre-print. Considering that S1P signaling is mediated by the G-protein linked S1P receptors (in this case S1PR1), it is an interesting possibility that other cell types with different requirements for control of sphingolipid biosynthesis will utilize the same downstream signaling, perhaps mediated by other G-protein receptors, to control ORMDL levels. A hint of this is found in the regulation of ORMDL turnover by cholesterol loading reported by Gulshan and colleagues (Autophagy. 2015;11(7):1207-8).

The experiments that underlie our view of that the enzymatic activity of the SPT/ORMDL complex is directly responsive to ceramide levels is as follows. It is important to emphasize that the bulk of these studies were performed in Hela cells. The biochemistry of the SPT/ORMDL complex itself is likely independent of cell type, but additional regulatory mechanisms, such as those presented in this pre-print, are doubtless cell-type dependent:

1. Sphingoid bases do not mediate an acute ORMDL-dependent regulation of SPT. We tested the identity of the sphingolipid that triggers ORMDL inhibition of SPT by feeding Hela cells sphingosine. This results in an almost complete inhibition of SPT. This is consistent with the sphingosine inhibition of SPT activity in intact cells originally reported by Kondrad Sandhoff’s group (Mandon EC, van Echten G, Birk R, Schmidt RR, Sandhoff K.Eur J Biochem. 1991 Jun 15;198(3):667-74). This inhibition is entirely ORMDL-dependent. Importantly, we demonstrated that sphingosine inhibition of SPT was completely blocked by preventing ceramide generation with the ceramide synthase inhibitor Fumonisin B1 (Figure 2 of J Biol Chem. 2012 Nov 23;287(48):40198-204 and Figure 2 of J Biol Chem. 2019 Mar 29;294(13):5146-5156. ). Thus, inhibition by sphingosine requires its conversion to ceramide. S1P generation, enhanced by sphingosine feeding, is not blocked by Fumonisin B1, yet SPT inhibition is ablated. Therefore, in this system, S1P does not appear to have a role in regulating SPT activity in Hela cells under the short-term conditions that we used. We concluded from these experiments that the triggering sphingolipid is ceramide or a complex sphingolipid such as sphingomyelin or a glycosphingolipid, but not a sphingoid base.

2. Elevation of ORMDL levels alone does not lead to SPT inhibition. We have shown that inhibition of SPT by ceramide In Hela cells and human bronchial epithelial cells (HBEC) cannot be explained by increased ORMDL protein expression. We do not observe an increase in ORMDL protein expression in response to C6-ceramide treatment of Hela Cells (Figure 5, Siow et al 2015), under conditions in which SPT activity is strongly inhibited. And we demonstrate that ectopically increasing ORMDL protein expression in either Hela cells or HBEC does not result in inhibition of SPT activity (J Lipid Res. 2015 Apr;56(4):898-908). In both of these cells there is sufficient ORMDL at steady state to serve the needs of SPT regulation, yet ceramide is strongly inhibitory. We make the point in this paper that the stoichiometry of ORMDL to SPT expression is important and make clear that it is likely that in some cell types changes in ORMDL expression will impact on SPT regulation. This is consistent with the response reported in this pre-print in response to S1P signaling.

3. Biochemical reconstitution demonstrates a direct inhibitory effect of ceramide. We have reconstituted ceramide-triggered, ORMDL-dependent inhibition of SPT in isolated membranes in a biochemical assay in which neither protein synthesis, turnover, nor post-translational modifications can occur. We are confident that this biochemical reconstitution reflects a physiological response of the SPT/ORMDL complex to ceramide. We demonstrated that the response to ceramide is strictly stereospecific with respect to ceramide stereoisomers. Only the native, D-erythro ceramide stereoisomer triggers ORMDL-dependent inhibition of SPT. Moreover, we addressed the possibility that the short-chain ceramides that we routinely use (for their solubility properties) might not reflect physiological inhibition. We generated native chain-length ceramide in the isolated membranes using the endogenous ceramide synthases. This ceramide was strongly inhibitory (Figure 2 of J Biol Chem. 2019 Mar 29;294(13):5146-5156).

4. The recently published structures of SPT/ORMDL complexes reinforces the view of the ORMDLs as regulatory subunits. The ORMDLs are firmly embedded in the structure. Moreover, comparison of the structures in the substrate-free and substrate-bound state indicates that the ORMDLs inhibit SPT via an amino-terminal sequence that reversibly inhabits the substrate binding site of SPT. These structures suggest that the inhibitory sequence must be stabilized in the active site of the protein to achieve inhibition. We propose that ceramide binding to the complex accomplishes this stabilization.

Taken together, our data and that presented in this pre-print form the picture that the ORMDLs are involved in multiple levels of regulation of SPT. A direct and rapid inhibition by ceramide, and the loss of that regulation when the ORMDLs are degraded as a result of interrupted S1P signaling. There is doubtless more to come and we look forward to further discoveries illuminating regulation of this essential system and the physiological impact of that regulation.

On 2021-10-28 14:56:26, user USHA MAHAWAR wrote:

Really really interesting paper about the ORMDLs and SPT regulation. I am curious to know that whether half-life of over expressed ORMDL3 is similar to that of endogenous ORMDL3. And does all the three ORMDL isoforms have same or similar half-lives . I know that ORMDL3 is emerging as a center of attraction in the field of SPT regulation studies but question is why do cells have three ORMDL isoforms ( when all the three ORMDL isoforms have more that 90% amino acid sequence similarity).

On 2021-11-06 02:27:49, user Quan Long wrote:

This paper has been accepted for publication by Genetics

On 2021-11-06 01:04:21, user Campbell Lab wrote:

Congratulations on the great work! Inspired by your previous contributions, we attempted something similar a few years ago but never got it to work as well as you did. In our design, the two strands were linked in tandem rather than appended to the ends of the GFP. If you are interested, you can access the published thesis here: https://era.library.ualbert...

On 2021-11-05 20:01:25, user Morgane Boone wrote:

The final peer-reviewed version of this paper was published in Nature Communications (https://doi.org/10.1038/s41....

On 2021-11-05 16:17:02, user Alizée Malnoë wrote:

The manuscript by Seydoux et al. investigates the role of proton potassium antiporter KEA3 in diatoms. The authors first demonstrated the pH dependence on photoprotection, specifically non photochemical quenching (NPQ) and showed that NPQ can be induced in the dark by acidic pH. They found that KEA3 modulates NPQ by impacting the proton motive force (PMF); indeed generated kea3 mutants showed increased partitioning into deltapH. Importantly they showed that diatom KEA3 in contrast to plant KEA3 possesses an EF hand motif which can bind Ca2+ and proposed that it controls KEA3 activity. The role of KEA3 and pH in affecting the NPQ response has been previously shown in other photosynthetic organisms however the novelty of this study lies in the demonstration that NPQ can be induced in the dark by acidic pH and the proposed role of Ca2+ in regulating KEA3 function.

Major comments<br /> - Page 5, you state that pH-induced quenching in the dark was accompanied by the conversion of DD into DT. Please provide de-epoxidation state (DES) at t15 time (Fig. 1B) to substantiate this statement. Starting DES would also be informative to ensure there was no retention of DT/zeaxanthin in the dark. <br /> - Also to ensure there is no sustained NPQ (and/or damage or disconnected antenna) at t0, please provide Fo and Fm levels for all NPQ kinetics experiments. Assessing PSII accumulation by D1 immunoblot could be done to ensure PSII damage does not occur.<br /> - In Fig. 2F, it is not clear which data points represent HL or ML treatment as well as which ones come from light or dark period. Please indicate them in different colors or symbols. Also clarify whether you have averaged data from the kea3 mutant alleles.<br /> - To confirm that lack of complementation by deltaEF is not due to mislocalization, please show whether deltaEF accumulates at the thylakoid membrane.

Minor comments<br /> - Page 3, Introduction, specify qE after NPQ response; PSBS should be written PsbS<br /> - Page 4, DD-dependent NPQ should be DT-dependent<br /> - Page 4, we suggest changing “crucial” to “Given the unknown role” if pH-dependence of NPQ in diatoms hasn’t been fully established before<br /> - Page 8, KEA3 most likely homolog, were there other homologs than the two shown in Fig. S5? also discuss conservation of other ion channels (is Phatr J11843 thylakoid-localised?) and if they could compensate for the absence of KEA3 in KO mutant (by being upregulated for instance).<br /> - Fig2B, comment on the band at ~80kDa in OE, is that from cleavage of GFP?<br /> - Fig2G, shouldn’t you expect a lower dpH in the OE? Please comment.<br /> - Page 13, for the statement that only dpH can modulate NPQ, we would suggest to tone down or specify that this is the assumption made here as it could be that dpsi modulates NPQ but has yet to be shown!<br /> - Most of the protein analyses were performed loading samples based on protein content, when possible please provide proof that chlorophyll levels are comparable between the genotypes (at least for the native gels)<br /> - Abstract, extra ‘of’ between capacity and via; page 23, extra ‘being’ between likely and less important<br /> - Define acronyms when used for the first time<br /> - There is a lot of ‘peculiar’ in the text ;-)<br /> - Fig. 2D, star symbol instead of square symbol, check consistency of symbols

Pushan Bag, Pierrick Bru (Umeå University) - not prompted by a journal; this review was written within a preprint journal club with input from group discussion including Alizée Malnoë, Maria Paola Puggioni, Jingfang Hao, Jack Forsman, Wolfgang Schröder, Emma Cocco, Jianli Duan.

On 2021-11-05 11:28:22, user Ben Dubin-Thaler wrote:

Great work NYC virus hunters!

On 2021-11-04 19:54:56, user Rahul Patharkar wrote:

Is the thesis of this abstract valid? It appears to be a misinterpretation of the point of the Patharkar and Walker 2016 paper and is quite sensationalistic. Everyone in the abscission fields knows that ethylene plays a role in abscission (this has been known for decades). The point of the 2016 paper is that it shows that drought can trigger leaf abscission in Arabidopsis and it defines some of the molecular basis for that. When we first observed that Arabidopsis cauline leaves abscised in our growth chamber, we wanted to know why this was happening because it was not described in the literature. We did not find evidence of ethylene build up in our chamber and we found that exogenous application of ACC did not trigger abscission, rather we found water-deficit triggered the abscission. We make no claim that ethylene is "not involved" in abscission rather it is not the external stimuli that triggers abscission. Regardless of how our words are interpreted, our firm stance is that ethylene "is involved" in abscission as a hormone that positively regulates abscission. We have published multiple review articles that have diagrams that show this point. Here is the actual sentence that from the 2016 paper that uses the word "triggered" rather than "involved": "After sequentially ruling out differences in genotypes, pesticide treatment, and ethylene accumulation, we found leaf abscission can be triggered by withholding water until the plants began to wilt followed by rewatering (Fig. 1)."<br /> Again, our view is that ethylene is a positive regulator of abscission but external stimuli like water-deficit or pathogen attack initiate the cauline leaf abscission pathway.<br /> Sincerely,<br /> Rahul Patharkar

On 2021-11-04 18:51:39, user Run Zhou Ye wrote:

Please cite this article as: R.Z. Ye, C. Noll, G. Richard et al., DeepImageTranslator: A free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis, SLAS Technology, https://doi.org/10.1016/j.s...

On 2021-11-04 18:06:08, user Donald R. Forsdyke wrote:

Macroevolution versus Microevolution

Presumably this paper (1) has been released in preprint form to obtain feedback before formal publication. Coauthored by a consortium of current leaders in the field of population genetics, it states that "the ability to fit the parameters of one's preferred model to data does not alone represent proof of biological reality." They hope fellow practitioners, having been alerted by this "simple truism," will avoid various pitfalls. Apart from concerns on synonymous site neutrality (2), calls to reconsider evolutionary fundamentals (3, 4) are not mentioned.

The historical authority of William Provine is referred to (5). He described the early 20th century dispute between geneticist William Bateson and the "Biometricians" (Pearson and Weldon). While disputing Mendelism, the latter made outstanding contributions to statistics. However, Provine concluded The Origins of Theoretical Population Genetics diffidently: "With the gap between theoretical models and available observational data so large, population genetics began and continues with a theoretical structure containing obvious internal consistencies."

Despite these 1971 words and "the wealth of data" now available, that gap remains. To bridge, the authors appeal to "interdisciplinarity … in order to connect genotype to phenotype" (1). This should remind us that in the 1920s Bateson foresaw (3) "that before any solution is attained, our knowledge of unorganized matter must first be increased." So sadly, regarding his topic, genetics: "For a long time we may have to halt." It was only following great progress in molecular biology, that in the 1970s WWII bomber pilot Richard Grantham, at the Université de Lyon, was able to ask the very question the authors pose (1): "Whether, and if so how, accurate evolutionary inferences can be extracted from DNA sequences sampled from a population?" In the authors' words (1), Grantham was able to use "molecular variation and divergence data to infer evolutionary processes." What Grantham called his "genome hypothesis" (6) was later related to the earlier ideas of Darwin's research associate, George Romanes, and Bateson (3).

While readily adopting Bateson's coinages – homozygote, heterozygote, allelomorph, epistasis, homeotic, meristic – the modern-day biometricians (1) have overlooked the most fundamental of his ideas, the "residue" (3), as they did Grantham's "genome hypothesis" and Romanes' "collective variation." Likewise, to make the mathematics easier, they embraced the neutral ideas of Kimura (2), instead of the "homostability" ideas of his compatriot, Akiyoshi Wada (7), who pressed unsuccessfully for a Japanese "genome project," which would have anticipated by many years that of the USA (8).

The works of Grantham, Romanes and Bateson, together with those of various Russian evolutionists and Richard Goldschmidt, focus on the fundamental distinction between inter-species "macroevolution" and intra-species "microevolution" (7). This crystallized historically in 1990 in the lectures and writings of the Russian specialist, Mark Adams. He stressed that the understanding of macroevolution would demand "a radically new interpretation of the history of Darwinism, population genetics and the evolutionary synthesis." For "if intra- and inter-specific variation differ not in kind, but only in degree, then it is possible, by extension, to envision selection as the creator of a new species. But if varieties are fundamentally different from species – if the fundamental character of intraspecific and interspecific variation is essentially different – then the effect of selection on a population cannot explain evolution." Initially published in French in 1990, Adams' work is now available in English (4).

1. Johri et al. (2021) Statistical inference in population genomics. bioRxiv: doi.org/10.1101/2021.10.27.... Nov 2.
2. Kern AD, Hahn MW (2018) The neutral theory in light of natural selection. Mol Biol Evol 35:1366–1371.
3. Cock AG, Forsdyke DR (2008) Treasure Your Exceptions. The Science and Life of William Bateson. Springer, New York.
4. Adams MB (2021) Little evolution, big evolution. Rethinking the evolution of population genetics. In: Delisle RG (ed), Natural Selection. Revisiting its Explanatory Role in Evolutionary Biology. Springer Nature, Switzerland, pp. 195-230.
5. Provine WB (1971) The Origins of Theoretical Population Genetics. University of Chicago Press.
6. Grantham R, Perrin P, Mouchiroud D (1986) Patterns in codon usage of different kinds of species. Oxford Surveys in Evolutionary Biology 3:4 8-81.
7. Forsdyke DR (2016) Evolutionary Bioinformatics, 3rd edn. Springer, New York.
8. Cyranoski D (2009) Reading, writing and nanofabrication. Nature 460:171-2.

On 2021-11-03 19:53:58, user Raphael Kopan wrote:

The paper is now in print on Nature Communication web site: https://www.nature.com/arti...

Note the review history is included and will explain the evolution of the submitted form in BioRxiv to the published product. We wish to publicly thank the reviewers for greatly improving our manuscript.

On 2021-11-03 14:33:03, user antibodies-online wrote:

ABIN101961 used for CUT&Tag/MulTI-Tag in this preprint

On 2021-11-03 14:11:34, user Raghu Parthasarathy wrote:

Fascinating study, but I think there are several issues of data presentation and analysis that need to be addressed. Figure 2 *really* needs to have a plot of effect sizes, not p-values. Figure 1 needs corrections for multiple comparisons. (I elaborate on these, especially the first, here: https://eighteenthelephant.... ). I'd also like to see a better discussion of robustness to cluster number -- the kinks in Figure S3 are pretty weak.

On 2021-11-03 13:53:58, user Prof. T. K. Wood wrote:

L 59: Both “there is little evidence for a clear genetic basis or the molecular mechanisms involved for the persistence trait” and “…the genetics and mechanisms of persistence are yet unknown” are patently false statements. Persistence is an elegant response to myriad stresses, as shown already through single-cell studies, though not reported here. See doi 10.1016/j.bioflm.2019.100018.

Persistence non-heritable; that is the whole point. There are no genetic changes in persister cells and they don’t require 19 years to form. Resistance arises from mutation and often the mutations are cumulative without noticeable changes in MIC. So authors must use genome sequencing and show no genetic change before calling cells “persisters” as they do in this manuscript.

L 190: how long were the cells treated with Abs prior to plating to measure CFU? Should be at least 3 hr and kill curves should be added to demonstrate these are persister cells; i.e., that prolonged exposure does not lead to a reduction in CFU.

Persistence is no more “a stepping stone to resistance” than any other cell type: persisters wake and when they wake, these non-persister cells mutate like all microorganisms. But dormant cells don’t mutate.

On 2021-11-02 17:55:46, user Nicole Reynolds wrote:

Lichtheimia is not in the Zoopagomycota, it is in the Mucoromycota. Please fix this before publication.

On 2021-11-02 09:56:52, user David Bhella wrote:

To help readers understand the path to publication, I am adding an account of the peer review process to each preprint.

This article was initially rejected without peer-review by PLOS Pathogens. We then submitted to Scientific Reports, where the paper was accepted following review:

Reviewer comments:

Reviewer #1 (Technical Comments to the Author):

In this manuscript, Ho et al. reported a 7-Å resolution cryoEM reconstruction model of MrNV VLP expressed in insect cells. MrNV could cause white tail disease in the giant freshwater prawn with high mortality rate, therefore is a serious threat to aquaculture. Together with PvNV infecting marine shrimp, MrNV may represent a new genus in the Nodaviridae family. The structure presented here shows a different arrangement of protruding spikes on the icosahedral capsid surface, compared to other nodaviruses, supporting this classification. The most significant difference is that the protrusions are dimeric, instead of trimeric as in other nodaviruses.

This manuscript is well written. The methodology from VLP expression, purification, to imaging and 3D reconstruction is standard and clearly explained. The conclusions are logical based on the results. Some discussions could be better elaborated:

1.The authors devoted a lot of space (especially figures) to the homology modeling which did not provide much information besides that the P domain of MrNV capsid protein is different from the input homologous models. It would be more helpful to instead show figures of the models fitted in the MrNV map, to directly show the discrepancies and suggest possible location of the MrNV P domain.

2.Given the current information, there is not sufficient evidence to say whether the fuzzy density beneath 5-fold symmetry axis is RNA. The authors could discuss the possibility of it being protein, such as the N-terminal region of capsid, which is usually disordered in other nodaviral structures.

3.Literature (ref. 14 &15) has shown two different assembly states of MrNV VLP expressed in E. coli and sf9 cells respectively. Could the structural information reported here help to explain the differences?

4.Structural characterization of MrNV is in need due to the threat from white tail disease. Now with the 7-Å resolution available, the authors could discuss more about followup studies and/or downstream applications leading to potential intervention against white tail disease.

Some minor points:

1.Has the final map been deposited to the EMDataBank?

2.With the current figures, the comparison between AB and CC dimers is a little hard to follow. It would help to label the A, B, C subunits. It is fine to label the dimers with colored arrows, but it would be more clear if the coloring is consistent between Figures 2 and 3. Please also consider including the measurements of angles and lengths in the figures, and labeling the supporting legs of CC dimer with an arrow or asterisk.

Reviewer #2 (Technical Comments to the Author):

The authors present work showing a cryo-EM 3D reconstruction of MrNV virus-like particles with the finding that “pronounced dimeric blade-shaped spikes" protruding above the surface of the particle are arranged differently than canonical structures of Alphanodaviruses. Thus the authors believe the new structure supports the prior assertion that MrNV belongs to a new genus of Nodaviridae designated Gammanadovirus.

The authors use a generally accepted approach during the reconstruction process although the use of a crystal structure as an initial model rather than using an initial model generated from their experimental 2D class averages could possibly confound the interpretation. Whenever a known structure is used it can lead to potential model bias. It is this reviewer’s assumption that the authors used FHV for the initial model since FHV doesn’t have significant spikes on the surface. The authors also used a low-pass filter of 60 angstroms to the FHV initial model to partially mitigate model bias. In both of these cases this is typically an ok approach if significant homology exists. However the authors force icosahedral symmetry during reconstruction and they themselves highlight the fact that MrNV and FHV share only 20% homology. The manuscript could therefore be greatly strengthened by a reference-free 3D reconstruction where the initial model is created from the experimental 2D class averages rather than the FHV crystal structure. If the final reconstruction for the reference-free approach remains similar/identical to the current reconstruction, then the authors will have demonstrated conclusively that the interpretation is sound. Therefore it is suggested that the authors incorporate the results of a reference-free reconstruction into the manuscript (a supplemental figure will be fine). As this requires a rerun of only the 3D refinement image processing step and not new data acquisition, this should not be considered a major modification and if this is successfully implemented then this reviewer recommends publication.

A few other minor comments to be addressed:

According to Reference #9 (NaveenKumar et al. 2013) the capsid protein of MrNV and PvNV only share 44.6% homology but that drops to 22% for the last 115 amino acids at the C-terminus which is the region the author attribute to forming the protruding spikes. Thus, it seems possible that the structure of PvNV may be different. It is this reviewer’s suggestion that the authors refrain from extending their interpretation towards PvNV and simply focus on MrNV throughout the manuscript.

Please define “VLPs” as “virus-like particles” in the abstract rather than just using the acronym.

There appears to be a 6xHis-tag on the capsid protein but it is not used for purification scheme. A sentence should be added to describe why it is included and whether the additional amino acids are anticipated to be present within the dimeric spikes or otherwise impact the interpretation.

During the post-processing steps, a b-factor of -890 square angstroms was applied. Was this calculated automatically using Relion or was it manually chosen?

Figure 1, it would be helpful to see a sampling of the refined 2D class averages in addition to the central slice of the reconstruction.

On line 120, suggest deleting “sharply resolved” to leave sentence as “Inspection of figure 1(b) reveals a capsid shell measuring between 2 and…” since “sharply resolved” is a qualitative term that others may feel is only appropriate for truly atomic resolution structures.

Finally, the homology modelling is an interesting addition to the paper. However, since no conclusive results can really be drawn from the models at this time, it seems more appropriate for figure 4 to move to a supplemental figure.

On 2021-11-02 07:58:51, user David Bhella wrote:

To help readers understand the process of peer-review, I am adding the peer-reviewer comments and article submission history for all of my preprints.

This article describes one of the most significant discoveries of my career and I started out sending a presubmission enquiry to Nature, where it was taken forward for review.

Review round 1<br /> Referee #1 (Remarks to the Author):

This work by Conley et al. addresses a long-time enigma in the calicivirus field: elucidating the unknown function of the small basic protein, VP2, encoded near the 3’-end of every genome. This protein had no detectable sequence homology with other known viral or eukaryotic proteins and was highly variable in sequence and mass among members of the Caliciviridae genera. In a stunning piece of cryo-EM structural detective work enabled by knowledge of the feline calicivirus receptor (fJAM-A) and capsid architecture, the authors pursued the identity of an unexpected density that appeared only when the FCV capsid was bound with its cognate receptor ectodomain. This density was shown to be a dodecameric arrangement of VP2 to create a unique structure at one 3-fold symmetry axis of each virus particle. Evidence was presented that this structure was involved in the creation of a portal assembly at the unique 3-fold axis for release of the RNA genome from the virion into the cell (likely from within an endosomal compartment). The paper is well-written and the figures and movies are of excellent quality. This original work should create interesting new avenues of research, not only in the calicivirus field, but potentially for other viruses as well.

1. This discovery is exciting, and deserves further discussion in context of the published literature. Perhaps there is a stringent word limit, but, if possible, please elaborate briefly on a couple points. Direct VP1 and VP2 interactions had been reported in the literature (e.g., Kaiser et al., JGV, 2006 and Vongpunsawad et al., JVI, 2013), and the VP2 was proposed to play a role in viral assembly and stability. Are the interaction sites mapped in previous studies consistent with the new model and how might VP2 enhance stability of the particle? In addition, it is noteworthy that the virion-incorporated VP2 (now 12 copies) is more abundant in the particle than previous stoichiometric studies suggested (such as the approx. 1.5 copies per norovirus VLP of Glass et al., JVI 2000 or the 1-2 copies per FCV virion of Sosnovtsev and Green, Virology 2000). One early study of FCV could not detect the ORF3 product in virions at all (Tohya et al., JVM, 1999). Does the new model provide a possible explanation for this discrepancy?

The putative metal binding site in the VP1 is new and of interest. Will this be explored further with crystallography and metal soaking experiments? Is mutagenesis of the putative potassium binding site lethal for F9?

1. The time of incubation at each of the conditions shown in Figures S13 and S15 would be helpful to include in the figure legend. Please use an arrow or two in Figure S15 to show a representative ball of density said to likely reflect the viral RNA.

2. Are the six tyrosine residues that line the capsid pore conserved in all FCV strains? Other caliciviruses? Can VP2 proteins among the other calicivirus genera be modeled to interact in a similar dodecameric arrangement?

3. The VPg is not mentioned in the model of viral entry. Was anything learned about the orientation of the viral genome as it exits the portal, and can it be predicted? There has been no reported evidence that VP2 binds RNA. How might interaction with the genome occur?

4. The first demonstration of VP2 as a minor calicivirus structural protein was shown with RHDV by Wirblich, Thiel and Meyers (JVI, 1996). Perhaps this work should be cited along with Glass et al. (reference 9).

Referee #2 (Remarks to the Author):<br /> This is a potentially interesting paper that provides structural evidence for the existence of a 12-fold symmetric tube, similar to a portal protein, in caliciviruses. My fundamental problem with this work is that the identification of a tube that ‘looks’ like a portal protein is solely based on the structural similarity with the barrel domain of P22 portal protein (by the way this work is not even referenced!).

There are no ‘hard’ data supporting the various speculative hypotheses that VP2 functions in DNA ejection(like a portal protein) and that VP2 hydrophobic N- termini insert into the endosomal membrane forming a channel (like protein H in phiX174).

In essence, this paper is speculative, preliminary and stuffed with hypotheses that could be tested experimentally. At the current stage, this work is of medium impact and should find publication in a specialized journal like the Journal of Virology, Virology, etc.

Specific comments

• Figure 1. This figure could go to the Supplementary Information or, at least, be deemphasized.

• Figure 2. Panel b and c are redundant and provide the same information. Instead this figure lacks a clear description of the putative portal protein. All I see is a 12-fold symmetric tube of density that looks like the barrel domain of P22 portal protein (e.g. again, the authors don’t even reference the various papers that describe P22 portal protein and its barrel domain). B

• Figure 2a. The tube of density in panel b is after applying averaging. It's not clear if the authors used 3-fold or local 12-fold averaging. In either case, how does the unaverage density look like?

• What percentage of particles shows the portal-like structure?

• Figure 3C. What metal ion is shown in this panel? What is the evidence to assign a metal ion rather than a water molecule? Dedicating two panels to a ‘yet to be determined ‘ metal ion seems inappropriate

• Figure 5 is overcrowded and somewhat incremental.

Referee #3 (Remarks to the Author):<br /> Using asymmetric reconstruction techniques on cryo electron microscopy data, Colney et al show that one vertex of icosahedral feline calicivirus recognizes the cellular receptor, namely junctional adhesion molecule A. The vertex is formed by six copies of the VP2 minor capsid protein. Presumably the virus assembles with six VP2 molecules decorating each 3-fold vertex, but association with receptor at one vertex modifies the icosahedral structure of this vertex to create a portal and channel wide enough to allow the +RNA genome to escape into the potential host cell.

The paper is mostly well written although the figures and figure captions need improvement and clarification. The frequent use of the word “reveal” (“show” would be better to avoid spiritual implications) and “interest” (the reader should judge for him/her self to determine what is interesting) should be avoided. The asymmetric cryoEM analysis was well executed. Reference to the earlier publication on calicivirus structure (Prasad et al Science, 286, 287-288, 1999) would have been helpful for an explanation of “AB” and “CC” dimers and a description of the protruding P domain.

It is not clear whether VP2 is present at all 20 3-fold vertices in the assembled, mature virus or whether the virus assembles with VP2 present only at one unique vertex. In the former case the act of binding the receptor would create the unique portal vertex. In the latter case the uniqueness of one vertex would have been established during the assembly process. This needs to be clarified. However, the presence of a unique vertex in a calicivirus, no matter by what mechanism, suggests that similar situations might exist in many other apparently icosahedral viruses. Thus this opens the door to a vast new appreciation of “icosahedral” virus assembly processes and cell entry mechanisms. This is therefore an extremely important paper

Round 2

Referees' comments:<br /> Referee #1 (Remarks to the Author):<br /> This is a revised version of a manuscript by Conley et al. that utilizes cryo-EM and structural modeling to define a proposed function for the minor calicivirus capsid protein, VP2. The authors have added helpful new references, modified or added figures, and clarified a number of points suggested by the referees. The authors have not provided additional experimentation that would directly support their proposed function of the VP2, citing an expected prolonged delay in the publication of this structure. Although compelling evidence for interaction of the VP2 portal with an endosomal membrane bilayer would indeed be a crowning achievement of this work, the new insight into the conformational changes in the structure of a calicivirus particle following binding to its cognate receptor remains an important advance. Please clarify the following:

1. In the response to Referee 2, the authors note the following: “This was addressed in the legend to supplemental figure S7 (now S8), 81.6% of particles showed one or more portals.” Were there indeed certain particles that appeared to contain more than one portal? How commonly were these observed? Please clarify what this observation implies because it is somewhat inconsistent with the model of a single exit point for the genome.

2. The citation of work that shows the importance of Leucine 7 in the FCV VP2 is appropriate, but this new text should be re-written and clarified. For example, without context that this is mutagenesis of the FCV genome by reverse genetics and virus recovery studies, the concept of “strongly selected for” and the meaning of the other amino acid substitutions is unclear.

On 2021-11-01 16:46:16, user Edward Emmott wrote:

Please note, this preprint has now been published in Nature Protocols as: https://www.nature.com/arti...

On 2021-11-01 14:59:09, user David Bhella wrote:

To help readers understand the process from preprint to published articles, I have decided to share details of peer review and reviewers comments for my articles.

This paper was submitted to PLOS Biology, where after peer review it was eventually accepted.<br /> Reviewers comments:

Reviewer 1

The portal vertex is the aperture located within many virus capsids that allows the nucleic acid to enter and exit. It is an essential feature but in herpesviruses has escaped high resolution observation because of its similarity with the 11 other pentonic vertices located in herpesvirus capsids. This paper describes a structure of the portal vertex of herpes simplex at the highest resolution to date. New features are revealed including a novel 5-fold symmetric bridge between the external surface of the capsid and the inner portal comprising copies of UL6, and a large structure on the surface that borders the portal vertex, presumably helping to anchor it in place. Density consistent with viral DNA is located within the pore located within the portal, which is similar to some tailed bacteriophages, confirming a longstanding hypotheses that the herpesvirus capsid and some phage capsids work in similar ways. The work is particularly timely given recent publications in Science magazine (Volume 360, April issue) that show high resolution structures of the capsid; but those structures lack the portal shown here.

This will be of interest to virologists in general and herpesvirologists in particular. The interest to scientists outside the field includes the novel methods used with the Titan cryoelectron microscope to reconstuct this asymmetrical feature at high resolution in the face of similar but functionally, and as it turns out, structurally distinct pentonic vertices. The novel approach in which focusing on each facet was used to classify capsids into 10 groups, one of which led to the appearance of a novel pentonic vertex in the reconstruction was clever and could be used more broadly for other asymmetric structures thath are less than obvious at first glance. Thus, structural biologists, nanotechnologists and materials scientists may also find this paper intriguing.

This paper is outstanding in the discipline and has presented data that answers a longstanding problem in the field, with appropriate posing of new questions. The authors have reached reasonable conclusions based on the data, with reasonable speculation of the identity of the protein comprising the 5-fold symmetric bridging structure based on what is currently known. There will be great interest to identify what this protein is.

The paper is well witten with only a few Typos:

Line 140 does not read correctly.

Lines 78, 155, 256. The word comprise is misused. “The apartment comprises 4 rooms” is correct. “An apartment is composed of 4 rooms” is also correct. “The apartment is comprised of 4 rooms” is incorrect.

Reviewer 2

Several major articles in recent years have revealed the high resolution structures of herpesviruses icosahedral capsids. However, information on the portal vertex that is essential for both viral genome encapsidation and decapsidation is still missing. In this article, McElwee et al. describe a subnanometer structure of the portal vertex and reveal several previously unknown structural features surrounding it. Such data should be useful for any researcher aiming at understanding the essential processes involving this vertex. The resolution is still insufficient for assigning unambiguously some of these different features to HSV1 proteins limiting its mechanistic implications.

Major points:

• The PVAT unique structural organization in the icosahedral capsid is the novelty of this work. The five-fold symmetric features of the portal vertex are enhanced by C5 symmetry reconstruction. Clear densities of the purple and magenta regions of the vertex in Figure 2e,f support that they follow a five-fold symmetric organization. This is less obvious for the region exposed to the capsid outside where 2x5copies of the UL25 Cter structure were docked (film 2) which appears somehow blurred in cut-open structures (Figure 2a,c,e and film 3). The 12-fold symmetric portal protein UL6 is smeared-out, as expected, by the C5 symmetrisation. This raises a number of structural and biological questions that the authors shall address. How is the portal protein position maintained in the portal vertex (very few contacts are observed) to establish a continuous channel with the portal vertex pentameric protein for DNA passage in spite of their symmetry mismatch? How are the two UL25 Cter rings maintained in place and where do their Nter extensions fit in the portal vertex densities? The assignment as show in figure 2e (portal vertex in mauve, CATC in cyan) does not seem compatible with the observation by Pasdeloup et al. (2009; J Virol 83:6610) that UL6 and UL25 are directly interacting. How do the authors reconcile this discrepancy?

• Figure 2 does not optimally illustrate the different novel features highlighted in the text. This information is present in the supplementary movies but it would be probably useful to have these points illustrated in the main figures. Probably the most important would be to show a comparison between the portal vertex and the other vertices, this would show the extension of the specificities of the portal vertex. A closer view of the newly described pentameric portal vertex protein would also be useful. This could even grow into an additional figure to better document differences between the portal and other penton vertices. Across these lines Figure 3, which deals with DNA packing inside the capsid, might be of less interest and eventually used as a Supplementary figure.

• Line 355 and throughout the manuscript, including figure legends and movies: the authors use the expression "a sharpened map" to designate high threshold rendering of the reconstructions and use different thresholds in the figures. They shall define what they mean by ‘sharpened map” and specify the threshold used in each figure panel, as this varies, and probably also in the movie parts.

Minor points :

1- Line 56 : "dense proteinaceous layer". "dense" is unclear and should either be removed or precised.

2- Line 66: "preformed procapsids" is more correct than "nascent capsids"

3- Lines 77-95: references to more recent high resolution structures of herpesvirus capsids are needed (CMV: Yu et al. 2017, Science 356:1350KHSV: Dai et al 2018, Nature 553:521). They provide also useful up-to-date information for interpretation of the pentons molecular organization. After the authors submitted their manuscript there were also two publications on the 6 April issue of Science that report atomic models of the HSV-1 and HSV-2 icosahedral capsids. These structures do not reveal the portal vertex structure but could be useful to refine the quality of the other capsid pentons structure shown in the present manuscript and their description (e.g. in the paragraph starting in line 97; in the refs given in lines 131, 134…).

4 - the authors shall define or give a reference for “focused-classification” (line 98 and thereafter) for the non-initiated.

5 – line 140: “a metadata file was created with expanded the icosahedral symmetry…” ?!

6 - The authors should describe in greater detail how the CATC could close the portal pore. In particular, they could compare the diameter of the gap through the UL25 rings with the diameter of a double stranded DNA and discuss whether this is sufficient for blocking DNA or not. This comparison could also be performed with the PVAT.

7- the CATC seems different in figure 2d and 2e, is it due to a different segmentation, a different density threshold or to another reason ?

8- Line 167-176: the authors should explain how they docked UL25 in the CATC density shown in movie 2, especially in the distal tier that seems to be less resolved.

9- Lines 208 to 231 : this discussion seems particularly long with regard to its interest for the work presented (the main issue is to propose that pUL33 could be the unidentified portal-vertex protein), it should probably be significantly shortened.

10 – line 235: the authors shall explain in Methods how they determine the handedness of DNA organization inside the capsid based on their cryoEM reconstruction.

11 – line 272: the packing of DNA is very tight inside viral capsids reaching a high concentration but its density does not change.

Reviewer 3

The MS “Structure of the herpes-simplex 1 virus portal-vertex” by McElwee, Vijayakrishnan, Rixon and Bhella reports structures of a pathogenic herpes simplex virus (HSV-1) focusing on the organization of its portal-vertex where is a portal protein complex located. The portal complex is a nano-motor accomplishing the packaging of the viral genome into the viral capsid during maturation process and later participating in the genome release into a host cell during infection. In this MS the authors shared their method of how to move from highly symmetrical models to the less symmetrical complexes. This important approach will definitely be used by other labs. The authors obtained two structures of the virus one with the icosahedral symmetry and another with symmetry C5. The last one revealed the portal vertex position. The novelty of the MS is in a detail description of how the orientations of particle images where analysed and modified to be applied to the structure with C5 symmetry. Usage of the lower symmetry during the reconstruction process has enabled the authors to see the handiness of the packaged DNA.

The MS is sufficiently well written and explains the methodology used to obtain the C5 structure. However there are some questions related to the figures. While the overall view of the HSV-1 is consistent with well-established facts, the details that are discussed in the MS are not seen on the presented pictures of the capsids and not shown or indicated on enlarged figures. The authors are discussing such fine details of the huge virus as bundles of four helices, but they (in spite a huge size of the figure attached) are not seen in the figures, and in the printed version of them, they are too small and they will be small in the final published version of the manuscript. All figures are poorly labelled.

Lines 130-131 -> “a clear four-helix bundle that has been attributed to pUL17, pUL25 and pUL36” One can wonder why the authors did not provide any fitting of atomic models. The authors have to label where are these proteins are located. So these parts have to enlarged and clearly indicated, showing the differences between the icosahedral symmetry and C5. Figures 1a, 1b can be removed, surroundings in 1e -1h could be reduced allowing to make 5-fold views bigger and give room for labels.

Figures are repetitive to the high extend. The authors have to show firstly the overall structures and then go to the details indicating the helices and position of proteins.

The movies were unloadable. So it is unknown what do they show.

Minor comments:<br /> Line 99. “replaced by a unique five-fold symmetric assembly” - >The authors have to be cautious, if the C5 symmetry has been imposed during the reconstruction process they will be not able to see if there are symmetry mismatches in the portal vertex. Overall symmetry will still be C5, but it is has been suggested while ago that the portal complex itself highly possible has symmetry C12, while the proteins that provide connections with the viral envelope and a host cell outer membranes may have a number of different symmetries varying from asymmetrical ring complexes via C2 to C6 rotational symmetric and may be other symmetries as well. Please rephrase the sentence,

Line 144. Please explain what is that: “grouping the data into self-similar classes”. References would be helpful.

Lines 155,161 and 164. How positions of the pUL17, pUL25 and pUL36 proteins were identified? How the authors assessed where and which part of densities were assigned to pUL36?

Lines 172-173, “The distal (outermost) tier being rotated ~36o relative to the proximal one (movie S2)”. Possibly will be good to have a figure, the movie was unloadable.

Line 180. Some confusion. What the authors mean: “we can see noisy density that we attribute to the porta protein pUL6”. How noise can be attributed to a protein? Possibly it was some indications of presence of the signal related to the Portal complex? Please explain and rephrase lines 180-185.

Line 195. Please rephrase “Lying between the portal and the pUL25 PVAT density, a novel five-fold symmetric assembly replaces the usual pUL19 penton.” It is not a new assembly that replaces the penton, this is a complex that has been eventually found. It is highly possible that it does not have the 5-fold symmetry; otherwise it would be resolved better.

Helices have to be shown and indicated in the figure.

Lines 208-223 possibly should be moved into introduction, they are bit out of place.

Lines 233-249 possibly fit better to the conclusions.

Lines 243-245 “Our data suggest a reason for this, showing that pUL25 forms a double-layered cap on the outer face of the portal-vertex (the PVAT).” Figure would be helpful. One cannot see that cap in any of the figures. The authors have to illustrate their text and possibly provide a better explanation.

Line 247 “pentameric portal-vertex protein complex” the authors do not have any proves, that the complex is pentameric. The symmetry has been imposed. Please rephrase the sentence in a more careful way.

The authors repeat that again in the conclusions, but the emphasis on the 5-fold symmetry should to be avoided.

Line 303. The dose has to be not per linear angstrom, but per square angstrom.

Reviewer 4<br /> The manuscript “Structure of the herpes-simplex 1 virus portal-vertex” by McElwee et al describes their structural analysis of the herpesvirus capsid portal vertex using cryo-electron microscopy to image capsids inside intact virions. This is a significant step forward for the field after a number of conflicting and low-resolution reports on the portal structure, and the present work answers several questions about this very important part of the herpesvirus capsid. The manuscript is well written and generally focused and rational. A significant limitation is that the 12-fold symmetry of the portal itself was not resolved and so the main conclusions are about the organization of the 5-fold symmetric capsid features around the vertex where they don’t interact directly with the symmetry-breaking portal itself. This is not to diminish the value of this work, and the title accurately reflects this situation, but I feel the authors may have made some inferences that are on less sound ground and which they may wish to reconsider. That aside, I believe the relevance of their work and its potential impact on the field well justifies publication by PLoS Biology.

Of several points that would benefit from additional thought, the first is perhaps trivial but bears on the concept of capsid and tegument. The capsid proteins co-assemble and remain associated in the virion. Terminase subunits are clearly not capsid proteins because of their transitory association, and neither are tegument proteins because they form a compact but largely disordered layer outside the capsid and serve no known structural role in the capsid. Proteins that are intimately, specifically and symmetrically associated with the capsid would seem to include the variously named CCSC, CVSC and now CATC where the T stands for tegument. The subunits include pUL17 that is implicated in capsid assembly, and pUL25 that maintains the genome inside the capsid amongst other functions, and its not clear why the authors describe them as “tegument”. Certainly, adding another name to the list seems unnecessary. Similarly, is the PVAT that is composed of 10 copies of pUL25 really tegument since it is integral to the capsid portal vertex?

The imposition of 5-fold symmetry naturally obscures interpretation of the 12-fold symmetric portal, but it also affects any interface where the symmetry of either side may be affected locally. This is evident, for example, in the asymmetric map of phi29 (ref [32]) where neither symmetry is appropriate in this region. Interpreting weaker density is fraught with the difficulty of knowing whether the symmetry mismatch or flexibility is responsible for fuzziness, and this bears on the identification of the density at the Ta position as another protein(s), the identification of pUL25 with the PVAT despite the poor quality of the fits (Supplemental Movie 2), and the claim of highly-ordered DNA packing in a left-handed spool. Indeed, imposition of 5-fold symmetry may be enhancing a spurious signal for the DNA – spherical sections might demonstrate the soundness of this density as surfaces such as those in Figure 3 may be misleading. In general, I feel the authors may want to moderate text about the weaker density in case their interpretations don’t hold up.

A technical question – the so-called “gold-standard” Fourier shell correlation of 0.143 is used as a cut-off to give the most optimistic measure of resolution. However, the Methods do not state that the gold-standard method was applied during analysis, and this is essential to justify such a low correlation limit. Was the gold-standard method followed from start to finish? Alternatively, at 6.3 Å for the icosahedrally symmetrized map, helices should be evident as tubes, possibly with chirality and even possibly with density corresponding to large side-chains. Are such features observed in the density map? Further, with the reduction from 60-fold to 5-fold symmetry, the resolution was changed only to 7.7Å – wouldn’t a greater loss have been expected? How do the density maps compare to X-ray structures that have been filtered to these resolutions?

A minor point on lines 91-95 – another significant reason why the herpesvirus portal has been hard to find is that it resembles a penton in size and mass, unlike in the dsDNA tailed phages where the portal is generally more massive relative to the pentamers of major capsid protein.

Reference is made to the pUL6 portals being decameric (eg, line 183) and I believe the structure of the isolated portal by Trus et al, 2004, is relevant here, and could be compared with the density maps in general terms (recognizing that the Trus structure has 12-fold symmetry and the density map has 5-fold) – ie, would it fit, and can it be placed in the density? Can its directionality be assigned?

Wording. There are a number of semantic and grammatical errors, including:

Line 19: suggests virions may contain several capsids, which is possible but rare.

Line 72: the colon should be a comma.

Line 132: “one on top of the pUL19” means the pUL19 of a penton, as opposed to a hexon.

Line 134: Reference [16] is not to PRV but instead to KSHV.

Line 140: “…with expanded the…” needs correction.

On 2021-11-01 11:10:19, user David Bhella wrote:

Some papers live a seemingly charmed life, while others encounter considerable resistance under peer review. To help readers understand the path to publication I have decided to share the reviews for all of my papers on BiorXiv.

We first submitted this article to Nature Structural Molecular Biology, where it was declined without review. We then submitted it to PLOS Biology, where it received favourable reviews:

Reviewer #1: (Signed review - reviewer name is redacted)<br /> Ho et al provide a detailed structural description of Macrobrachium rosenbergii nodavirus (MrNV), a pathogen of fresh water prawns based on Virus-like-particles made with a baculovirus system programmed with the capsid protein gene of the virus. The close similarity between the VLP structure determined at 3.3Å and the authentic virus particles determined at 6.6Å resolution provide convincing evidence that the VLPs are good representations of the authentic virus. The highlight of the paper is the close similarity of the subunit organization and the capsid morphology to that of tomato bushy student virus (TBSV). Key features are the Arginine Rich Motifs (ARMs) of the C subunits that interact with RNA and are not visible, but sequentially precede an intricate series of subunit interactions mediated by residues following this region; the N-proximal shell (S) domain and the C-proximal protruding (P) domain. All of these features, as well as the dimer organization of the protruding domains and the metal ion stabilized shell domain interaction are far more reminiscent of the TBSV structure than the structure of other reported insect nodavirus structures.

The technical quality of the paper is high and it is well written and illustrated. The arguments are convincing that the family nodaviridae, comprised of the alpha (primarily insect infecting viruses) and beta (primarily infecting aquatic species) genera, result from convergent evolution of these genera toward bipartite RNA particles that clearly display subunits and capsid organization that are distinctly different from each other, with the beta particles showing much closer similarity to TBSV-like viruses than the alpha nodavirus structure.

The paper will be improved if the authors address the following points.

1. They should reference Tang, L., Lin, C., Krishna, N., Yeager, M., Schneemann, A., and Johnson, J. 2002. Virus-like-particles of a fish nodavirus display a capsid subunit domain organization different from insect nodaviruses. J. of Virology 76:6370-6375. While these subunits formed trimeric interacting surface domains, the organization of the subunit domain structure was described as TBSV-like.

2. The authors should provide more comparison with the beta nodavirus structure previously reported that they reference but do not discuss (Chen N-C, Yoshimura M, Guan H-H, Wang T-Y, Misumi Y, Lin C-C, et al. (2015) Crystal Structures of a Piscine Betanodavirus: Mechanisms of Capsid Assembly and Viral Infection. PLoS Pathog 11(10): e1005203).

3. Inter S-domain stabilization by divalent cations is not unique to TBSV and was described in some detail for Flock House Virus (Banerjee, M., Speir, J. A., Kwan, M. H., Huang, R., Aryanpur, P. P., Bothner, B., and Johnson, J. E. 2010. Structure and function of a genetically engineered mimic of a nonenveloped virus entry intermediate. J Virol 84:4737-46.). The similarity between MrNV and TBSV is convincing, but the discussion could be expanded a bit.

4. A striking difference between alpha and beta nodaviruses is that the former undergo a post assembly maturation cleavage that is required for infectivity. This activity does not appear to be present in beta nodaviruses and this should be pointed out and possibly commented on in terms of any potential homologous residues in the two genera now that there are two high resolution structures of beta nodavirses.

Reviewer #2:

The authors report the structure of a nodavirus infecting fresh water prawns, MrNV. The structure of virus-like particles (VLPs) reached 3.3 A resolution and the biological significance of this structure was validated by repeating the structure determination on the virus itself, purified from prawn post-larvae, at 6.6 A resolution. The VLP structure allowed modelling the atomic structure of the viral capsid.

The manuscript discusses evolutionary considerations that are interesting to those working in the field of structural virology and viral evolution: Unlike other nodavirus capsids that are built from trimeric capsomers, then MrNV capsid is built from dimeric capsomers. This structural difference reported by the authors earlier has raised the question whether the MrNV should be allocated to a new genus within Nodaviridae. This manuscript highlights further differences and intriguing parallels to the members of the Tombusviridae family.

The work is technically of excellent quality and the manuscript is clearly written. However, I would move most of the detailed methods from the Results section to the Methods section (especially cryoEM).

It would be beneficial if the Discussion could be developed further as now it somewhat just summarizes the results and has several unrelated minor points. For instance it could be focused more around the evolutionary differences and similarities. Where are the Ca2+ sites in tombusviruses and what is the similarity in other parts of the capsid protein? The strand-swapping seems unique to MrNV. It would be interesting to discuss the possible evolutionary origins of this – for instance are the interactions that this strand has with the neighbouring CP capsomer in MrNV similar to those that the equivalent strand has within the same capsomer in tombusviruses (see Bennett, et al. 1995 Protein Sci. 4, 2455–2468).

Finally, it is not clear from the figures if the topology of the MrNV P-domain can be clearly seen in the EM map. As comparison to tombusviruses and similarity of the fold is a key part of the paper, it is essential to provide stronger evidence for this.

Minor comments:<br /> Line 229: Please clarify what is meant by “unsupervised 3D refinement”?

Please add FSC curve for the 6.6 A map and validation curves (phase randomization) for all FSC curves.

Add supplementary Table for all EM statistics, including the B-factors used for sharpening of the maps.

Reviewer #3:

The authors present an atomic-resolution model of the Macrobrachium rosenbergii nodavirus calculated by cryo EM of virus-like particles (VLPs). MrNV is a pathogen of freshwater prawns that poses a threat to food-security and causes significant economic losses in the aquaculture industries of many developing nations. VLP were produced in insect cells, and data were reconstructed to 3.3 Å resolution map. CryoEM of MrNV virions purified from infected freshwater prawn post-larvae yielded a 6.6 Å resolution structure confirming the biological relevance of the VLP structure. The manuscript is well written with especially clear descriptions of the structural organization and comparisons to other structures. Figure 3 in particular is nicely presented. This is an important and impressively reported effort.

Minor:

“S” and “P” domains are used first in Results section at about line 277 without definition. Fig 1 b (central section) is called to illustrate fuzzier density of P domain, but there is no label/arrow in Fig 1 b to show P domain location.

For surface rendered maps in all figures, please add some type of label or axis indicator to designate symmetry axes to orient the reader. A description of the orientation might be sufficient, if it is preferred by authors and editor in order to preserve the visual integrity of the maps.

There is a clear and accurate statement in Results: “At this resolution, the (6.6Å) map appears identical to that of the MrNV VLP in all respects.” However, elsewhere, the same accuracy is required. Please adjust the Fig 7 legend where it states that “The authentic MrNV virion has an identical capsid structure to that of the VLP,” and “…. was indistinguishable from the VLP reconstruction” since both statements need to include some mention of the qualification of achieved resolution or other softening term to acknowledge that your conclusion that these are identical structures is highly probable, but cannot be stated conclusively due to the 6.6Å map.

On 2021-11-01 09:15:53, user Marius L wrote:

Congrats to releasing MARGARET. Please consider citing CellRank (see cellrank.org or the preprint), which has many conceptual similarities with MARGARET, e.g. CellRank automatically detects initial and terminal states, computes absorption probabilities on the Markov chain and charts gene expression trends using GAMs. Interesting to you might also be CellRank's efficient computation of absorption probabilities, which uses iterative linear solvers to exploit sparsity, circumventing the need to sample waypoint cells while being much more efficient than Palantirs implementation both in terms of time & memory (see preprint benchmarks). Recent releases generalize CellRank beyond RNA velocity, including e.g. a PseudotimeKernel to assign directionality based on any pseudotime (Palantir inspired) or a Real-time kernel to link cells across experimental time-points (Waddington OT inspired).

On 2021-11-01 07:26:38, user Prof. T. K. Wood wrote:

Authors also make common mistake of thinking lack of PI staining indicates viability (see doi:10.1111/1462-2920.14075).

On 2021-10-29 20:26:02, user Prof. T. K. Wood wrote:

Just exceedingly-poor title as the persisters are not "actively growing" but instead originate from formerly actively-growing cells. Persisters form, as shown repeatedly, from stress.

Also, it is already known stress induces persisters = main cause (see doi:10.1128/AAC.02135-12).

Key problem: reliance on the 2004 report that indicates there are different kinds of persisters and that they arise spontaneously.

Persistence is an elegant response to myriad stresses, as shown already through single-cell studies, though not reported here. See https://doi.org/10.1016/j.b... .

Already shown through single cell studies that the E. coli cell morphology becomes round (see doi:10.1111/1462-2920.14093).

On 2021-10-31 05:03:02, user Sandhya S wrote:

Supplemental Information is not complete. Only movies are uploaded.

On 2021-10-29 18:46:31, user Kevin Tyler wrote:

This is lovely work and credibly resolves a lot of discussion about what might be going on in a robust and well evidenced piece of work.

On 2021-10-29 13:45:32, user Angelino Carta wrote:

our preprint has been accepted for publication and a link will be forthcoming

On 2021-10-29 12:04:21, user FranziG wrote:

Impressive work confirming some important concepts in the transcription and GR field. I think the single cell part is very relevant. I am just wondering if changes in enhancer-promoter interactions profiled by H3K27ac HiChIP can be interpreted when the 'chipped' mark itself is changing. I would expect loosing contacts whenever H3K27ac is lost after Dex and gain contacts where H3K27ac is gained. Meaning that the observed gain/loss is not necessarily due to changes in contact frequencies. Somehow what you see in Fig. 3B and C. I am not a HiCHIP expert so ;) Do you normalize for epitope changes upon treatment during the HiChIP analysis?

On 2021-10-28 14:02:42, user Boyi wrote:

Is there a supplementary file? Thanks.

On 2021-10-28 10:08:07, user Thomas van Gurp wrote:

Hi Patrick, I would love to try this protocol, I'm curious to hear what you have learned and what you struggled with.

On 2021-10-28 09:34:38, user Peter Ellis wrote:

What an ABSOLUTELY fascinating system! This paper blew my mind clean out my ears. Excellent work :-)

I have only one quibble, relating to lines 329-333, i.e. the potential for conditional Y-linked drive.

You show that it is possible for a Y-borne gene to favour transmission of the paternal X (and oppose transmission of the paternal Y) in matings between XY males and X*Y females. I think it would be worth pointing out that the paternal Y cannot be selected to drive against itself. Rather, in this case the maternal Y is being selected to drive against the paternal Y.

In the case of the two-step pathway (b2'+3), a Y-borne drive modifier can only invade the population if it acts in X*Y females, not if it acts in XY males, because it is the maternal copy of the Y that is favoured by the drive in these matings - the paternal copy is disfavoured.

The same applies to the one-step pathway b2. Even if a single Y-linked gene is responsible for both directions of conditional drive, if its only mode of action is by perturbing sperm function, then it will be rapidly selected to become an unconditional driver. It must therefore act in X*Y females as well.

This means that conditional drive almost certainly has two separate mechanisms of action: one acting paternally, and the other acting maternally. This makes the two-step pathway much more likely than the one-step pathway, and may give some clue towards tracking down the mechanism of action - the proposed mandarin vole system in ref 11 (maternal Y acts via imprinting to inactivate an essential gene on the X*, so only embryos that inherit a paternal X can survive) is a beautifully elegant solution, and blew my mind for a second time in one evening.

I personally think the most likely course of events is:

1) Acquisition of unconditional Y-drive, acting paternally. <br /> We know that there is a paternally-acting sex ratio drive system in mus musculus, and some of the interacting partners (Sstx and Ssty) are also present in rat. So this is likely quite ancient. We also recently showed that the proximate mechanism for this is probably differential motility of X and Y-bearing sperm.<br /> https://pubmed.ncbi.nlm.nih...

2) Appearance of a feminising X*, facilitated by the presence of Y drive

3) Development or enhancement of compensation in X*Y females to improve fertility via polyovulation.<br /> In a transgenic system that eliminates male embryos in the peri-implantation, we show that there is some inherent compensation of litter size in mus musculus. So it seems some element of poly-ovulation may be common in rodents, allowing for a certain amount of pre-/peri-implantation attrition without reducing litter size. This seems like the sort of phenotype that could relatively easily be increased to allow greater levels of compensation.<br /> https://www.biorxiv.org/con...

4) Development of conditional drive in which X*Y females drive against the paternal Y<br /> Once compensation is well established in step 3, the X*Y mothers have more scope to eliminate even more embryos prior to implantation and thus select only the ones they want.

Mechanistically, all this can be most readily tested by IVF and/or embryo transplantation experiments - are these techniques established for mus minutoides yet?

Once again, thanks for one of the most enjoyable papers I've read in a long time!

On 2021-10-28 08:34:48, user Patrick Deelen wrote:

Very nice manuscript, congratulations. Can you elaborate on how this method compares to: https://pubmed.ncbi.nlm.nih...

On 2021-10-27 21:18:16, user Jennifer Wenger wrote:

Were the antibody lineages used for the study from unvaccinated people?

On 2021-10-27 13:53:05, user antibodies-online wrote:

Proteins used for validating In Silico Driven Prediction of MAPK14 Off-Targets (among others): NMNAT1, FABP4, MEN1

On 2021-10-27 11:11:24, user Sebastian Lobentanzer wrote:

Hi there,<br /> cool paper! I have a minor comment on Natalizumab: it targets integrin alpha 4, which is a receptor for VCAM1. I am not aware of an association to ICAM1, could you elaborate on that?

On 2021-10-27 09:05:18, user Dong wrote:

The R package Miso also allows for user-defined isotopologue pattern search. Maybe you could consider citing this package: https://academic.oup.com/bi...

On 2021-10-26 23:22:30, user Xin Chen wrote:

We appreciate that the authors tested our previous results using new reagents and methods. However, we have to point out that there is a big misunderstanding of our published work. First of all, asymmetric histones do NOT imply the existence of “immortal histones” as the authors hypothesized and used to make predictions in their experimental design. In fact, distinguishing old versus new canonical histone must be in the context of cell cycle progression: Old refers to the pre-existing histones before S phase and new refers to newly incorporated ones during S phase. These two populations can be distinguished by the tag-switch or photoconversion methods only after the switched or converted cell goes through one complete S phase and enters the subsequent M phase. Moreover, the new histones with switched or converted labels will mature over time during cell cycle and gain old histone features, and thus there are no “immortal” histones. However, we are not seeing any labels in this work that indicate active cell cycle progression, which is very concerning given these tissues are ex vivo for more than 40 hours.<br /> Second, it would be highly appreciated if the authors include germline versus somatic cell markers in their figures. As of now, it is impossible to tell whether the weak H3 signals in Figure 1C and 1E come from germ cells or somatic gonadal cells. The bright spot in Figure 3E was interpreted as hub cells, which are quiescent somatic cells. If this is the case, it would be very strange that such a quick old to new H3 turn-over occurs in these cells, as indicated in Figure 3E legend.<br /> Finally, we have to point out that our previous results were entirely misinterpreted in the “Alternative Hypothesis 2” in Figure 2, because we are not assigning random stem cells (GSC) and progenitor cells (SG) together as pairs — all GSC-GB pairs we analyzed are still connected by the spectrosome structure (Tran et al., 2012; Xie et al., 2015; Wooten et al., 2019), indicating that they are daughter cells derived from one GSC division. Furthermore, our previous conclusions were not solely based on the post-mitotic GSC-GB pairs, but also on stem cells undergoing asymmetric cell divisions, based on fixed and live cell imaging.<br /> In summary, this work is based on both misunderstanding and misinterpretation of our work, leading to an incorrect hypothesis. Additionally, there is no single dividing stem cell or a pair of daughter cells derived from stem cell division shown in this work that can lead to the conclusion of “Symmetric Inheritance of Histones H3 in Drosophila Male Germline Stem Cell Divisions”. We hope these comments clarify several critical points for both the authors and the readers of this preprint. Thank you for your attention!<br /> Xin Chen<br /> Johns Hopkins University

On 2021-10-26 21:56:12, user Swastik Phulera wrote:

Great publication, the reference numbering seem to be a bit off. Eg ref 73 (in text) should be 70

On 2021-09-27 18:29:26, user anna moroni wrote:

Dear Authors, very interesting results. I noticed that in C-type inactivated Shaker channels, the selectivity filter is impressively similar to that of HCN4 channels in their non-conductive form (Saponaro et al, Mol Cell 2021,DOI:10.1016/j.molcel.2021.05.033). The comparison between WT and W434F mutant in Shaker highlights the large movement of Y445 and D447 sidechains, similar to those of Y482 and R484 observed by comparing conductive and non-conductive HCN4 SF. Further, C-type inactivated Shaker channels show two ion binding sites only and low conductance, two typical features of HCN, as well as reduced selectivity for K over Na (Kiss et al, 1999, DOI:10.1016/S0006-3495(99)77194-8). So, really striking similarities!

On 2021-10-26 03:30:22, user Manasi Datar wrote:

Dear authors,

Thank you so much for sharing your valuable <br /> research. It was indeed an insightful paper which has a remarkable application in future bio monitoring of terrestrials. It would have been nice to know the reasons behind using the specific COI forward and reverse primers in your experiment and some more information regarding the target genes. Also, hedgehogs that are present in the vicinity don't visit the zoo as they may be hibernating during winters, but will still keep physically shedding DNA in the air which may have been detected in your samples. Overall, I enjoyed reading your paper and am intrigued with the efforts taken to conserve biodiversity.

On 2021-10-26 02:19:49, user Amelia wrote:

This is a fascinating paper! I'm writing as a social scientist, and not a biologist, but I was curious about the potential impacts of this approach for the collection of human DNA. I read an interview in LiveScience where you describe the contamination of samples with human DNA as a "hurdle" and a source of contamination. Yet, I was wondering if there are any ethical concerns about this kind of passive DNA collection without consent?

On 2021-10-25 08:35:03, user CDSL JHSPH wrote:

Dear Dr. Clare et. al.,

It is my pleasure to review your paper! Thank you for contributing to global terrestrial biomonitoring and ecological analysis. Using airDNA as a biomonitoring tool under natural settings show great potential. The decline in biodiversity throughout the world urges the development of non-invasive techniques that could offer rapid and accurate results. Your study successfully reveals the power of airDNA sampling at distance, and from my perspective, the new technique would truly revolutionize terrestrial biodiversity surveys.

My question would be, do you anticipate any difference of conducting airDNA sampling between zoo setting and real natural environment? As in the zoo, animals are gathering together and each kind of them have their own enclosures. While in the natural environment, animals will move more freely as there will be no space limit. Also, we know that some endangered species actually live under extreme conditions. For example, the weather might be extreme. Will the study results be influenced by extreme weathers?

Moreover, I am wondering if we need more intermediate steps to shift from zoo setting to actual field as zoo setting can evoke less complex behaviors and is still involved by human. Since we are aiming at non-invasive technique, what future steps could be done?

All in all, I think the paper makes significant contribution to the biomonitoring field, the methodology is quite convincing. I am just curious about the actual application of airDNA in the wild and the future plans regarding this study.

Thank you for your work and I am looking forward to future outcomes on this topic!

On 2021-10-24 23:25:38, user CDSL JHSPH wrote:

This paper has so much potential in innovating the yield of ecology with a new biomonitoring technique. However, there are some parts of the paper that need further clarity. For instance, in figure 1, if there was more clarity on the enclosures and their distances from one another that can give a better understanding of the relationships between the animals and the number of reads given. Also, if there was a supplementary portion of what each of these target animals consume and the typical amount, it can perhaps clarify the large amount of recovered sequences coming from the farm animals. Additionally, depending on the season of when sampling is done, do you believe that played an impact on the sequence levels?

On 2021-10-24 15:04:18, user Kayla Hess wrote:

This investigation will surely revolutionize the field of terrestrial biomonitoring as it establishes the successful use of airDNA outside of a controlled laboratory setting. Collecting samples at multiple locations inside and outside of the park provided a large and diverse pool of data, thus supporting the validity of the investigation. The read count variability of airDNA inside the enclosures in comparison to outside seemed unexpected. Especially since there was so much drift between the closures, I expected there to be a similar amount of drift to outside the park as well. What might account for this difference? Wouldn’t the same weather and climate patterns that caused airDNA to drift between the enclosures also cause it to drift outside? I figured that maybe most of the drift could have been due to human activity rather than weather events but I could be mistaken. In addition, how might human activity affect the accuracy and precision of airDNA terrestrial biomonitoring in the wild?

On 2021-10-24 14:07:57, user SC wrote:

Such an interesting preprint, it really has set the stage for further developments in measuring terrestrial biodiversity! Out of curiosity though, I was wondering if you had any additional data on the wind speeds or wind patterns at the time of testing, especially given the range of eDNA findings presented in the tables – as your abstract notes on airDNA dispersal away from sources, the "ecology" of this airDNA traffic in air could possibly benefit from anemometric readings, wind–mapping, or general information relevant to climate and seasonality when having tested. A satellite map of wind patterns could possibly elucidate dispersal of this airDNA to places far from its origin!

On 2021-10-24 02:45:04, user Ashlyn Blevins wrote:

This is an exciting study!!! I am very much looking forward to reading more of your work and about airDNA. This could be a great new way of biomonitoring. I am not very familiar with ecology field work and would like to know more about how you took your samples. The orange rings in figure 1 look quite large. Did you just walk around with your sampling apparatus, use a drone, etc? I also noticed that two samples of mole rat DNA were excluded due to cross contamination of tubing from prior use. Was the tubing in this experiment cleaned or changed between each sampling area or would the filters you used catch everything? Thanks for any insight - I am really looking forward to learning more! :-)

On 2021-10-24 01:08:38, user CDSL JHSPH wrote:

The method of this study is creative and unique, and the experiments are well designed and set a precedent in detecting eDNA directly from the air to achieve terrestrial biomonitoring. The claims and conclusions are mostly reliable, except for the "versatility" of this biomonitoring method. But more improvements and research need to be done to refine the method to get more accurate data, before this biomonitoring method can be used in absolute natural conditions where animals are not spatially confined and certain. The writing of the introduction is great. The context of this field, as well as the need and importance of their study are well stated. Regarding figures and tables, I think the best way to present data like the tables in the paper is to summarize and simplify numbers into straightforward diagrams like figure 1.

On 2021-10-18 19:24:43, user CDSL JHSPH wrote:

This is a great potential application of airDNA being used for bio monitoring. The tables certainly show the specificity and range of this technique being used on various types of animal species in a natural setting. I’m just curious if you think the time of sampling has any impact on what DNA samples are detected? I ask mainly because it was noted how the hedgehog DNA was detected in certain enclosures despite it being more absent during the time of sampling. Do you think there is a certain range of time that these samples are representative of? Are they detecting animals that are present the day of sampling or possibly animals that were there a few days or even weeks prior to sampling?

On 2021-10-26 02:55:59, user CDSL JHSPH wrote:

This is a good introductory body of work regarding how mitochondria are acting as a signaling source to promote cellular proliferation instead of working to promote favorable bioenergetics. When analyzing what you are commenting upon I am curious as to why you chose to include the methods and materials section within the supplementary materials portion of you manuscript? I also am curious about the organoid model utilized to test this concept. Was there any other differences observed to make sense of the bone tissue migration compared to the breast cancer tissue migration? Does it overall seem like this process could very well happen in all types of cancer outside of the breast cancer cells tested? This specific data, while very important to understanding mechanistically what is going on with this mitochondrial transfer, I think needs more clarity quantitatively or qualitatively. If we were too look at this phenomenon in vivo are there going to be confounding factors that perhaps change this transfer process? This could potentially start to explain why there are differences in transference patterns observed between tissue types. I believe that overall this body of work is a great stepping stone for further investigation and understanding of what this process could mean for both "healthy" cells as well as "diseased" cells such as cancer cells as well as tissue health.

On 2021-10-25 06:55:40, user Sneha Pramod wrote:

This experimental study was performed to understand the mechanism by which laterally transferred macrophage mitochondria promote cancer cell proliferation. The results of the research study have been documented meticulously and clearly. One of the key findings of the study is that the transferred mitochondria lose their membrane potential and become depolarized within the cancer cell. They also report that the transferred mitochondria act as a signalling source and induce ROS generation. I would like the authors to elaborate on whether there is a link between loss of membrane potential and increased ROS production. Additionally, I was wondering if the authors explored the dysregulation/mutation of mtDNA in transferred mitochondria and whether it contributes to the signalling capacity in any way.

On 2021-10-25 06:21:23, user Suchitra Magesh wrote:

The study was novel and used different methodologies to test the transfer and function of mitochondria in tumor cells. The figures that depicted the methodology especially were detailed and neatly presented. I had a query regarding the correlation of the Warburg effect with the results of this study. Warburg effect, one of the hallmark of cancer, explains the use of aerobic respiration in the mitochondria of tumor cells resulting in the generation of ROS. Does the transferred mitochondria undergo the Warburg effect? In addition does the increase in ROS, as well as proximity of mitochondria to ROS, result in increase of risk of mtDNA damage?

On 2021-10-22 19:08:45, user Anissa Cervantez wrote:

Hi there!

I agree with the comments below, if you could further explain how you were able to connect that ROS lead to increased cell proliferation. I understand that due to the increased ERK-KTR translocation that this means theres an increase in proliferation but I am confused about how from your data (Figure 4D) how you are then concluding that ROS is the reason behind the increased proliferation.

Overall, I think this paper has great clinical relevance and am wondering what future work you could see being done. I know you had mentioned that these macrophage mitochondria are not being degraded and am wondering if you have any indication as to why this is? Also do you foresee this having implication in many cancer cell lines? It looks like this could have implications in bone and breast cancer but what other types of cancer do you think could be affected by this process?

On 2021-10-21 14:07:25, user Iris Chen wrote:

Great analysis and synthesis of ideas pertaining to the mechanism by which macrophages stimulate cancer cell proliferation. The findings are interesting and innovative, and the arrange of figures and conclusions is also great! And I am just a little bit confused with Figure2A, so why you chose to observe the recipient cancer cells for 15 hours? Because I find in some experiments, the data was collected after cells were co-cultured for 24 hours, so maybe you can also lengthen the observation time in 2A to 24 hours, in this way I think your conclusions will be better supported. And another possible advice is for Figure4D, I think here you can also add a figure to show the number of mito fragments with in the artifact macrophages, just like Figure4B. And I also think you could add more details in the introduction part, like the proliferation of breast cancer cells (why you chose to get the data after 24 hours), the relation of ROS and ERK (is there any previous studies about this pathway? are there other possible pathways?), and the mitochondrial network in macrophages (has anyone also found M2 with smaller mitochondrial fragments before? and does the mitochondrial phenotype influence the cell functions?). Anyway I think this is a really good preprint, thank you for presenting your work here.

On 2021-10-20 06:09:07, user Seb Wang wrote:

Hi, I have a doubt about using photobleaching to generate ROS to test ERK activation. I feel like it is hard to draw comprehensive conclusions based on this experimental design. Even if under this condition, cell proliferation decreased, you can only conclude that ROS leads to increased cell proliferation, so transferred mitochondria can lead to cell proliferation through ROS accumulation, but you cannot eliminate the possibility that transferred mitochondria can induce cell proliferation through other mechanisms. I think another way to do it would be in cancer cells transferred or not transferred with mitochondria, either somehow knocking out all ROS or not knocking out all ROS, and comparing four experimental group’s proliferation state with each other. Then, we can know if transferred mitochondria induced proliferation is completely ROS dependent or not. I might be wrong, but I hope my comment makes sense!

On 2021-10-26 02:41:51, user CDSL JHSPH wrote:

Thank you for sharing your research. I found the paper to be very well-structured and I think the organized layout of the paper helps build a narrative that can be read by a wider, non-scientific audience as well. <br /> It was interesting to find that neutrophils in older adults had increased uptake and oxidative capacity, compared to younger adults (Fig 2B). I liked that you referenced research articles with findings that were in contrast to your own finding regarding neutrophil oxidative capacity in older adults. I think including such references is a great way to avoid confirmation bias in research.<br /> I hope to see future studies that build upon this research theme by using cohorts that span the entire age range of 1-80 years. It would also be interesting to see the variation in dendritic cells and B cells at human nasal mucosa with age. In addition to the challenge of obtaining human tissue samples, did you face any other challenges while investigating the immune cell composition at nasal mucosa? Also, were there any factors that led you to focus mainly on T cells and neutrophils for this study?

On 2021-10-26 02:22:47, user Lisa Pieterse wrote:

Very impressive and comprehensive work published on the changing immune landscape as a factor of ageing. Inclusion of immune cell composition and activation states provided an interesting gauge into the diminished nasal mucosal T cell reservoir, and perhaps overdependence on granulocyte function, in older adults. Has your group considered looking into Th17 subset composition amongst colonized and uncolonized children, young adults, and older adults? It would be immensely interesting to see if there would be a difference in Th17 populations within the nasal mucosa of older adults with or without S. pneumoniae colonization especially. As you point out in your paper, your group observed diminished T cell density and activation within older adults (Figures 1C, 1E, 1I), but did not include data on Th17 composition or Th17-producing cytokines such as IL-17, IL-21, or IL-22, although I may have missed this. Thanks in advance!

On 2021-10-26 01:54:16, user CDSL JHSPH wrote:

This was an interesting study to read, and a great analysis of how the immune system reacts as people age in their mucosal surfaces. After reading this study, I have a couple of questions regarding your experiment. In Figure.3 I understand that the data focuses on Spn colonization causes of inflammation in children. This test included young adults, but I noticed older adults were not included. Is there a specific reason older adults were not tested for this part of the experiment? Figure. 4G also omitted the older adults from this study. Lastly, the discussion noted that children ages 6 to 17 years old were not included in this study. Was there a particular reason for the age gap in subjects? Thank you for your responses in advance!

On 2021-10-25 21:17:54, user CDSL JHSPH wrote:

A novel and interesting read characterizing effect of age on the composition of immune cells in nasal mucosa. The paper certainly supports the authors’ argument of needing further mucosal studies to understand the changes in immune responses and risk of individuals with age. The key findings of reduced granulocytes and T cells in children and older adults respectively suggest new directions to explore the increased susceptibility to infections in these individuals. The figures were beautiful representations of the results and great analysis.<br /> The only source of confusion I encountered are the monocyte and neutrophil functional blood assays. Since it is presented in the abstract and experimentally shown in the latter figures that the immune functions in the blood are not reflected in the mucosal tissues, how is the importance of these functional blood assays to the paper justified? A few minor suggestions I would propose are to include a few lines explaining the intention behind an experiment and possible future studies in advancing the field.

On 2021-10-22 14:29:18, user Trupti Tripathi wrote:

I really enjoyed reading the paper. The main objective to investigate the composition, activation, and functionality of immune cells in the nasal mucosa was accomplished with sufficient supporting data. However, a lot of statistical data was represented in the figures with little or no information about how it was calculated, such as the Kruskal stress values and the multi-dimensional plots with Euclidian distances. The violin plots with box plots were the best way to represent the data in the paper and were easy to interpret. The correlation between the reduced number of nasal granulocytes and increased expression levels of CD66b, and increased MPO in children is profound. I wanted to know if it was challenging to collect nasal biopsies in so many individuals to measure monocyte functionality that you had to switch to blood. Could this comparison of immune cell functionality in mucosa samples vs. blood be made using mouse models? Do you think this study can be used for making personalized medicines against respiratory tract infections in children or older adults with underlying conditions? What would be the usefulness of this study during the current COVID-19 pandemic, where newer strains of viruses are growing rapidly? Thank you so much for this great read.

On 2021-10-21 01:28:21, user jt4444 wrote:

Great analysis of granulocyte and T-cell distribution with respect to ages. This paper also had a great introduction relating previous studies of pneumonia cases in children and adults. I do have some confusion, most of the data analyzing granulocyte are mainly subjected to neutrophils in this paper; however, there are many other immune cells with this that contains granulation activities and the same markers? <br /> Also, I understand that Spn are able to colonize the nasal cavity, but does this necessarily count for the colonization in lower respiratory tract (where most pneumonic activities happen). Also, it would have been great to analyze and differentiate adaptive activities such as immunoglobulin levels at this site since they do seem to occupy these linings. Lastly, could this also be tested in mice (i.e. acquiring respiratory tract samples even in the lower region with respect to lifetime and maintaining the same number of people for each group)? Overall, a good paper focusing on a subset of immune population and characteristics within the nasal lining cavity!

On 2021-10-25 19:58:44, user Joseph Binder wrote:

I think you had a great paper and it was quite insightful. These findings will help with conservation efforts in these regions. I know the focus of this study was in deserts. The extreme temperatures drive mammals to wetlands. Do you think that by going into a different environment such as a rocky mountainous region would provide similar results? Could this be a potential follow up study? For figure 1 I know that the x-axis was shared among each sub-figure. I think to make the figure more clear to the reader having the x-axis under each figure would have helped.

On 2021-10-25 18:36:26, user Michael Matthew wrote:

This was a great examination of the factors affecting ecosystem food webs. I have one question about predator-prey balance. While a major concern is the removal of feral donkeys and similar invasive megafauna, you also mentioned the importance of maintaining predator populations. Regarding optimal food ecosystem and web structure, what are the most effective methods of maintaining predator populations and introducing supplementary predators if needed? Does this depend on predator-prey relationship, time of year, or biome?

On 2021-10-25 19:52:39, user Mike Anderson wrote:

We are happy to say that we have just been notified that a peer-reviewed version of this manuscript has been considered acceptable for publication in TVST. We will be working with their Editorial Office to submit the final files for publication. We welcome any comments the community may have as this line of work and field continue to evolve!

On 2021-10-25 18:16:45, user Peter Rogan wrote:

This article is in press in the International Journal of Radiation Biology. DOI: 10.1080/09553002.2021.1998709

On 2021-10-25 12:35:33, user Maiwenn KERSAUDY-KERHOAS wrote:

Video of assembly and demo available here on Youtube https://www.youtube.com/wat...

On 2021-10-25 04:06:16, user Critical Dissections wrote:

Great article, I particularly appreciate that the research wishes to address SARS-CoV-2 viral transmission post-vaccination by stimulating mucosal immunity in addition to systemic immunity. Not to mention, the production of a shelf-stable, oral vaccine would be a great contribution to current global vaccination efforts.

The experiment design was planned and executed well to imitate and evaluate post-vaccination transmission of SARS-CoV-2. However, after thoroughly reading the paper, I was left searching for answers that would provide clarity to readers such as myself should they be addressed.

The first is regarding the use of an adenovirus type 5 vector when a large proportion of the population already has natural immunity to this serotype. Is there a benefit to using this vector as opposed to another subtype with less seroprevalence in the population?

The second unanswered question is regarding the IM vaccine used. Why was a SARS-CoV-1 spike protein vaccine used instead of a vaccine that expresses the SARS-CoV-2 spike protein, such as one of the current mRNAs vaccines currently in use?

My third unanswered question is regarding the high virus titer used to inoculate index hamsters. What was the rationale behind inoculating hamsters with a high physiological dose as opposed to a moderate dose that may better represent the amount that humans are actually exposed to?

A thought, not a question, but many of the experiments performed on samples were collected at several timepoints, yet the sVNT was performed at only 1 timepoint following full vaccination. It would have been informative had the sVNT been performed on samples from week 4 to determine the neutralizing ability of antibodies in between vaccinations and to compare to IgA and IgG levels which were determined at that time point.

As a final lingering question, IN- and oral- vaccinated index hamsters inoculated with the high dose viral titer showed more effective viral clearance than naïve hamsters that were exposed to these same index hamsters in the aerosol chambers. And as seen in figures 4b-g, though high viral and infectious viral loads were detected in the naïve hamsters they were protected from severe clinical disease outcomes at day 5 post-challenge. However, the same data from figure 4 b-d also seem to show that the unvaccinated, naïve hamsters were not protected from viral infection transmitted via aerosols from the infected, IN- and oral- vaccinated index hamsters. Yet, one of the conclusions from the paper is that IN- and oral- vaccinated index hamsters transmitted less aerosolized infectious virus to unvaccinated naïve hamsters. Have I misinterpreted the data from figures 4b-d?

The results of the study make a strong case for adenoviral-vectored SARS-CoV-2 vaccine candidate that induces mucosal immunity and I look forward to reading more studies from this team.

On 2021-10-24 17:46:08, user banksinoma spinifera wrote:

This is an interesting study about the effect of propionate on diabetes-induced neurological dysfunction.

Two small suggestions for the authors:<br /> - The title is a bit misleading. The role of PI3K-AKT-eNOS is not demonstrated. The changes are associated with the improvement but there is no loss-of-function or gain-of-function study to demonstrate it.<br /> - In Fig. 13a, the blots for p-PI3K and p-AKT are identical. Authors should check that out.

Best regards!

On 2021-10-24 04:52:42, user Kumiko Hayashi wrote:

Now published in Biophysical Journal https://doi.org/10.1016/j.b...

On 2021-10-23 10:13:43, user Michael Ailion wrote:

This manuscript examines the role of steroid hormones in<br /> regulating exit from the dauer diapause state in C. elegans. The manuscript presents a careful examination of partial dauers made by daf-9 mutants that are deficient in dafachronic acid (DA) steroid hormone production, concluding that these partial dauers are dauers that have initiated but failed to complete dauer exit, and that thus, complete exit from dauer requires DA steroid hormones. These major conclusions of the paper are well-supported by the<br /> experimental evidence. Convincing experiments demonstrate that daf-9 mutants make full dauers in unfavorable conditions, that these animals then become partial dauers when shifted to favorable conditions, and that many daf-9 partial dauers formed in favorable conditions transit through a transient full dauer state on their way to becoming partial dauers. Finally, it is shown that DA steroid hormones promote exit of arrested daf-9 partial dauers. This is a solid study and my critiques are all relatively minor.

Minor Points

1. The paper could be clearer on precisely how daf-9 and DA steroid hormones are required for dauer exit. Though it is true that daf-9 and DA are required for “complete” dauer exit as accurately stated in the Abstract, the take-home message of the paper often seems to be that daf-9 and DAs are required for “dauer exit” without getting into the nuance of which aspect of exit (e.g. lines 143-144 and elsewhere). The idea that DA hormones are required<br /> for exit is unintuitive and paradoxical given that daf-9 mutants actually initiate dauer exit rapidly under favorable conditions. Though the paper is generally careful in the precise way it talks about exit, I think it would be clearer to explicitly state the precise role of daf-9 and DA in dauer exit as<br /> follows. Based on the data in this paper, I would argue that there are two steps to dauer exit, only one of which depends on daf-9 and steroid hormones. First, an animal needs to initiate dauer exit, which leads it from the full dauer state to the partial dauer state. This step does not seem to require DA steroid hormones as daf-9 mutants initiate dauer exit from the full dauer state to the partial dauer state rapidly. Instead, this initial exit is likely regulated in a similar way as dauer entry – it is blocked by high levels of dauer<br /> pheromones, or in Daf-c mutants like daf-2 and daf-7. When pheromone is low (“favorable conditions”) initial exit occurs to the partial dauer state in a DA-independent fashion, and then there is a second stage of regulation going from partial dauers to non-dauers. daf-9 and DA steroid hormones are both necessary and sufficient for this second step, exiting from the partial dauer stage and<br /> resuming reproductive development. In one sense, it could be argued that daf-9 and DAs are required for full “execution” of dauer exit, not the “decision” to exit (just as daf-16 partial dauers are sometimes suggested to be defective in the execution of dauer formation rather than the decision). So ultimately, the action of DA hormones is required for reproductive development, whether it is<br /> to bypass dauer entirely at the L2 stage or whether it is to fully recover after forming dauers.

2. Some figures would benefit from non-dauer controls. For example, in Fig 2, it would be nice to see the pharynx width, speed, and pumping frequency of non-dauer L3s as a comparison. Without these controls, it isn’t clear which aspects of the daf-9 phenotype are dauer-like vs. non-dauer. Similarly, in Fig 3E, the daf-9 partial dauers have a speed similar to the recovered WT dauers. After 24 hours in favorable conditions, I would think the WT would be at L4 stage (i.e. fully non-dauer), yet this is one piece of evidence that<br /> daf-9 full dauers can become partial dauers upon a shift to favorable conditions. So does a partial dauer move at the same speed as an L4? If so, speed would not be a very useful measure in defining an animal as a partial dauer because it wouldn’t distinguish partial dauers and non-dauers. Including a WT L4 control would be useful. Pumping frequency in 3F is clearly less for daf-9 partial dauers than recovered WT dauers (presumed L4), but what about pharynx width shown in 3G? Is that more like a dauer or a non-dauer? Again, a WT L4 control would be useful.

3. Related to point 2 above, it would be nice to show that WT dauers at early stages of recovery (much less than 24 hours) resemble daf-9 partial dauers. That would demonstrate there is likely nothing abnormal or incomplete about daf-9 partial dauers and really nail the idea that the daf-9 partial dauer phenotype is due to defects in dauer exit rather than dauer formation.

4. Though strong evidence is presented that some daf-9 partial dauers transit through a transient dauer state (Fig. 4), it also seems<br /> likely based on the data in Figs 4 and S2 that daf-9 can also go from an L2d to a partial dauer without becoming a full dauer, though this possibility is not discussed. This raises several questions. Are the daf-9 partial dauers formed at 20° without going through a full dauer state (Fig S2) different than those formed at 25.5° (Fig 4)? If WT L2d are shifted to favorable growth conditions before becoming dauer, do they go through a partial dauer state that resembles daf-9<br /> mutants? Do daf-9 L2d look the same as WT L2d?

5. Related to point 4 above, the presumed daf-9 mutant L2d<br /> pharynx shown in Fig 4B looks somewhat slim – a WT L2d pharynx photo would be useful as comparison.

6. It is stated twice (lines 130 and 157) that there is only “anecdotal evidence” that daf-9(dh6) and daf-12(rh273) mutants form full dauers under unfavorable conditions. However, the two papers cited (Antebi et al.1998; Gerisch et al. 2001) both have tables with quantitative data showing full dauers formed in these mutants under starvation conditions. I would suggest to not use the phrase “anecdotal evidence.”

7. Lines 348-350: it is suggested that DA does not promote exit of full daf-9 dauers in the presence of pheromone because of<br /> inaccessibility of DA. Though this is possible, another possibility is that DA only promotes dauer exit after an initial decision to exit that does not occur in the presence of pheromone (see point 1 above).

8. It appears that the WT and daf-9 full dauer speed data shown in Fig 2C may be the same data shown in Fig 3E. If so, this should be<br /> stated explicitly, and any other data reused between different figure panels should be stated. Were all the data in Fig 3E from experiments performed in parallel? If not, this should be stated.

9. It would be helpful to show DIC micrographs of the pharynx without the yellow outline drawn on top since it is very hard to see<br /> the pharynx boundaries with the drawn outline (Figs 2A, 3G, 4B, S3). I would recommend a supplementary figure showing the same images without the outline.

10. It is unclear which daf-9 mutant is shown in Fig 3G<br /> (presumably dh6 but not stated). Please state this in the legend.

11. It would be helpful to state in the Fig 6C legend that these are WT dauers, not daf-9 dauers.

12. I was confused by Fig 7D. It seems that the presence of the UAS::ICE transgene promotes dauer exit, regardless of the presence of the XXX cGAL driver, which seems odd. Then I read in the Methods that dauers with the UAS::ICE transgene are SDS-sensitive. Are these real full dauers or partial dauers? If they aren’t normal full dauers, it seems questionable using them in an assay on dauer exit. Perhaps the UAS::ICE integration site or a mutation in<br /> that background caused by integration affect the dauer state? Given these concerns, I would recommend cutting this experiment from the paper. The laser ablation experiment in Fig 7C is much cleaner.

13. In Fig S3, it is stated that the labeled neuron is actually due to bleedthrough of RFP in a coinjection marker. This coinjection<br /> marker should be listed in the genotype of this strain in Table S1. Also, it appears that there might also be some GFP in the posterior pharynx in this image. Any explanation?

Reviewed (and signed) by Michael Ailion

On 2021-10-22 17:33:40, user Gregory Way wrote:

Thanks for posting this paper - there is a lot here to digest! I have one comment about, perhaps, a critical assumption that may not be true.

You cite reference 23, which is Cutiongco et al. 2019 (https://doi.org/10.1038/s41..., and state: "The assumption is that cells with more similar morphological features (e.g. cell size, nuclei size, granularity, or distribution) also have more similar transcriptional profiles23"

In Cutiongco et al., they tested 14 genes, and observed that they were associated with concomitant morphological changes as a result of different nanotopographies. I am not sure if this relationship will hold true for other genes and especially, outside of using nanotopography as an environmental stimulus. Also, evidence from other domains indicates that morphological differences may not necessarily indicate large gene expression differences (see Que et al. 2020: https://doi.org/10.1038/s41... where they found only 9 genes differentially expressed between neurons with different morphologies).

I suppose my point is that the field needs more evidence of the linkage expectation between expression and morphology, and, to the extent that this assumption impacts normalization, I would be a bit weary of over-interpretation.

On 2021-10-22 13:42:27, user disqus_ZTJxGjMaUL wrote:

what was the origin sample of the RNA fragments this test is tuned to?

On 2021-10-22 09:59:50, user Marc Gielen wrote:

Interesting read, thanks!<br /> Just two quick comments on figure 6 suppl 4 :<br /> 1) there is a microscopic reversibility issue in the kinetic scheme, which would be solved by increasing the AD --> ADI by 10^3 fold (i.e. k'on.10^3 rather than k'on)<br /> 2) by increasing 1000 fold the desensitization on-rate, it seems you are decreasing the lifetime of the open state rather than stabilizing the desensitized state (of course, there is a thermodynamic shift in favour of the desensitized state, but it doesn't sound to me like a stabilization in a kinetic sense). My bet is that if you rather decrease the desensitization recovery rate (d-), akin what you did for the flipped state in fig 6 suppl 3, you will end up with a similar observation to what we had for our 2018 review (GLIC & DHA): pretty much no effect on the peak current following preapplication of the inhibitor.<br /> Best,<br /> Marc

On 2021-10-22 06:28:34, user CC C wrote:

This is the first AI-designed PETase and it works so great with Microbes

On 2021-10-21 17:34:05, user Iklwa wrote:

Chimera formation during PCR is common.

On 2021-10-20 20:47:30, user Simón Villanueva Corrales wrote:

Hi, exciting development! As I was reading the paper and the main point of Polypolish is to reduce errors in repetitive regions, I was almost sure that Merqury was going to be used to assess the error reduction. Have you heard about it before?

I have not heard of ALE before, but by your description, it seems a mapping-based score, which would skew to non-repeats. I think Merqury might be a better fit because it is kmer-based, and thus it does not suffer from the mapping bias. Among other things, Merqury can provide a global QV score for your assembly, comparing the assembly kmer spectra to the short-reads kmer spectra. I suspect Merqury's QV scores can better reflect the reduction in repeat regions.

Furthermore, I wonder what one can achieve if you use both metrics. Being ALE a good representative of non-repetitive error reduction and Merqury's QVs of the global error reduction, one might think that something like the ratio or the difference of both could directly correlate to error reduction in repetitive regions. Although one would have to think about how to normalize the metrics to make them comparable, I think it is still an idea worth exploring.

I hope this comment helps and I wish you the best.

Regards,

Sivico

On 2021-10-20 20:03:08, user luis carlos LOPEZ GARCIA wrote:

This preprint was published on October 13th in Biomedicines (https://www.mdpi.com/2227-9....

On 2021-10-20 12:09:55, user Marcelo Briones wrote:

This work has been published in the journal "Viruses" (MDPI): https://www.mdpi.com/1999-4...

On 2021-10-20 01:58:44, user Joshua Mylne wrote:

I commend the authors for putting this openly online and I have some suggestions:

With the data shown, pqt11 does not to me seem hypersensitive to PQ. The error bars overlap and the images not compelling. Could I suggest you try more than one concentration of PQ and several sub-lethal doses? Also, only one pqt11 SALK allele is used. Others are available e.g. SALK_109667, SALK_148492 (confirmed homozygous) and more. Although it makes sense loss-of-function is sensitive if OX is resistant, it does not alway happen like that and needs better proof.

It would be nice to see the proteins are actually made in E. coli. There are no protein gels. Also, were you surprised that without adding IPTG you got life-saving expression of PQT11 from pET28a in E. coli on plates? I didn't think it was a very leaky plasmid?

Also, the in vitro assays you did not include a NADPH-cytochrome P450 reductase (e.g. ATR1 or ATR2)? I thought that was required for in vitro assays with P450s?

Finally. Did you consider trying to detect the N-demethyl paraquat in planta for WT vs pqt11 vs OX PQT11?

Happy to discuss offline if you prefer. Thanks for sharing your work openly online. I thought it very exciting.

On 2021-10-19 18:37:14, user Jin Yu wrote:

Accepted version:<br /> https://escholarship.org/uc...

On 2021-09-30 17:05:14, user Jin Yu wrote:

Published with MSDE from Royal Society of Chemistry:<br /> https://doi.org/10.1039/D1M...

On 2021-10-19 15:41:45, user Maria Paula Volpi wrote:

This preprint has just been accepted for publication in the journal Applied Microbiology and Biotechnology. Once the DOI is out, it will be posted here

On 2021-10-19 14:28:40, user Kimmo Palin wrote:

As pointed out in Twitter, competing interest statement needs updating

https://twitter.com/passDan...

On 2021-10-19 09:48:52, user Paul Macklin wrote:

Paper is now published as:

https://doi.org/10.1016/j.i...

On 2021-10-19 07:11:57, user Stefan Barakat wrote:

the peer reviewed version of this paper appeared now in Genome Medicine: <br /> Genome Med 13, 162 (2021). https://doi.org/10.1186/s13...

On 2021-10-18 07:49:31, user Ken Shirato wrote:

This preprint has been peer-reviewed and published as an article in Molecules. The information of the paper is shown below:

Title: "Standardized Extract of Asparagus officinalis Stem Attenuates SARS-CoV-2 Spike Protein-Induced IL-6 and IL-1β Production by Suppressing p44/42 MAPK and Akt Phosphorylation in Murine Primary Macrophages" by Shirato K, Takanari J, and Kizaki T<br /> Journal: Molecules 26(20), 6189, 15 pages, 2021.<br /> Doi: 10.3390/molecules26206189<br /> URL: https://www.mdpi.com/1420-3...

Ken Shirato, Ph.D.<br /> Kyorin University School of Medicine

On 2021-10-18 00:11:14, user Ellis Patrick wrote:

We also found that the choice of signature database made a big difference https://journals.plos.org/p...

I'm not sure if our dataset would help your validation?

On 2021-10-16 22:53:39, user Kaotic wrote:

Any update on when this may be peer reviewed?

On 2021-10-16 12:38:42, user Amartya Sanyal wrote:

This preprint is now published in Cancer Informatics (2021) and a link to the publication will be forthcoming.

Analysis of Aneuploidy Spectrum From Whole-Genome Sequencing Provides Rapid Assessment of Clonal Variation Within Established Cancer Cell Lines.

Ahmed Ibrahim Samir Khalil, Anupam Chattopadhyay, Amartya Sanyal

Cancer Inform. 2021; 20: 11769351211049236. Published online 2021 Oct 16.<br /> https://doi.org/10.1177/117...

PMCID: PMC8521761<br /> https://www.ncbi.nlm.nih.go...