On 2024-08-08 13:15:41, user F. Laclé wrote:
Also, if you can publish your model code in a repository would be great for reproducibility (the model itself is not necessary I reckon). As you know, there are much more system configuration elements to consider, which makes reproducibility efforts complicated. Publishing your model code would allow others to attempt and improve the reproducibility challenges.
On 2024-08-08 13:11:45, user F. Laclé wrote:
Hi. In Figure 6b, shouldn't the number of filters of the skip connection be equal to 4 times the number of filters in the last Xception module? You have it specified as 16, shouldn't it be 32?
On 2024-08-08 08:28:33, user Ashleigh Shannon wrote:
AUTHORS COMMENT / UPDATE <br /> 21 June 2024
Part of this work, describing the inhibition of both the NiRAN and RdRp domains by the guanosine analogue 5’-triphosphate AT-9010 has now been published in Nature Communications ( http://doi.org/10.1038/s41467-022-28113-1)11:bWV2b7IKjzmu98TO74CkaGwQqk8 "http://doi.org/10.1038/s41467-022-28113-1)1") . This includes the structural characterization of the mechanism of inhibition at both active-sites, which importantly revealed that the SARS-CoV-2 NiRAN domain contains a guanine-specific pocket. This has now been confirmed in other studies 2,3, and represents a promising avenue for future drug development studies.
Following several contradictory reports on the ability of the NiRAN to NMPylate different cofactor proteins (4–6), we have now carried out additional analysis on the protein-priming activity and NMPylation specificity. This has revealed that our nsp8 product is labeled at the primary amine of a non-native glycine residue, present at the N-terminus of the expression construct (following cleavage with TEV protease), and negating the biological relevance of these findings. Surprisingly, removal of this single residue, exposing the true N-terminal alanine, eliminates all labeling and protein-primed activity, stressing the importance for using proteins with native N- and C- termini. Of note, the current publication does not reflect these new findings, but instead has been left as the initially submitted manuscript.
Later studies have now revealed nsp9 to be the primary target for both NMPylation5,7, and RNAylation8 – a conclusion that we fully agree with.
With the exception of our finding that nsp8 can be used to prime-synthesis, albeit by a non-native residue, there was no other evidence for protein-priming until recently. In October, 2023, Schmidt et al., published the finding that nsp9 is covalently linked to the 5' end of positive- and negative-sense RNA produced during SARS-CoV-2 infection9. This linkage was found to be regulated by its interaction with the host protein, staphylococcal nuclease domain-containing protein 1 (SND1), which was found to specifically recognize the 5’ end of negative-sense RNA and be important for viral RNA synthesis. Although it is highly frustrating to have spent several years focused on the wrong protein, this finding supports the notion that protein-priming is occurring in CoVs, and opens up a plethora of options for further mechanistic and structural studies.
Of note, Schmidt et al. also showed that nsp9-linkage on the (-)sense strand mapped roughly between the genome and poly(A) tail. Intriguingly, we also found a similar specificity for this region. Here we show that the SARS-CoV mRTC (nsp12-nsp7-nsp8) can initiate synthesis through a de novo, NiRAN independent pathway, through the synthesis of a pppGpU primer. This dinucleotide is complementary to the last two nucleotides of the SARS-CoV-2 genome, located precisely at the genome-poly(A) junction. De novo initiation was found to directly compete with the (artificial) nsp8-poly(U) protein-primed synthesis. This shows that the poly(A) tail and 3’ genomic RNA sequence elements guide the positioning of the mRTC to the true 3’-end of the genome.
The specific details behind initiation of RNA synthesis, including the role of SND1 and potential coordination between protein-priming and/or de novo induction remains to be studied. Synthesis initiation, and the precise role of the NiRAN therefore appears to be a complicated story, which remains to be fully elucidated.
Ashleigh Shannon and Bruno Canard
On 2024-08-07 20:02:40, user jan wrote:
This was published in a peer-reviewed journal quite some time ago, but as of today the link is still missing: Smits, A.H., Ziebell, F., Joberty, G. et al. Biological plasticity rescues target activity in CRISPR knock outs. Nat Methods 16, 1087–1093 (2019). https://doi.org/10.1038/s41592-019-0614-5
On 2024-08-07 19:00:20, user Zheng Fu wrote:
Cells 2024, 13(15), 1258; https://doi.org/10.3390/cells13151258
On 2024-08-06 23:47:01, user Jorge Ramirez wrote:
Please add a link to the published version of the paper. The link of the journal publication is: https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2024.1375958/full . https://doi.org/10.3389/fpls.2024.1375958 . Thanks!
On 2024-08-05 20:26:55, user Zach Hensel wrote:
Summary: Zhan et al argue that nearly identical (>99.9% in the S gene or across a whole genome) sequences sampled within a single species indicate transmission within a single species subsequent to a period of host adaptation, assuming the necessity of adaptive mutations in any new host. They repeatedly claim that similar identical genomes were never sampled in different species in SARS outbreak between 2002 and 2004. This is incorrect. In fact, the data cited in this paper includes at least four examples of 100% sequence identity in samples from different species. Thus, the statement "In the SARS-CoV outbreaks, >99.9% genome or S identity was only observed among isolates collected within a narrow window of time from within the same species" was incorrect.
Example 1: Figure 5 and the manuscript discuss samples SZ3 and SZ16 collected from palm civets in 2004 in Dongmen market in Shenzhen. However, sample SZ13, reported from the same study (Guan et al, Science 2003, accession AY304487) is not mentioned. It was collected from a raccoon dog and it is 100% identical to SZ16 over 8581 bases in a partial genome sequence inclusive of S.
Furthermore, Guan et al also reported neutralization of SZ16 infection by sera from masked palm civets (3 of 6 samples), raccoon dog (1 of 1), Chinese ferret badger (1 of 2), and human (12/55; 8/20 for humans in wild animal trade). This indicates widespread infection of diverse species by SARS with >99.9% identical genomes without requiring further host adaptation. It's possible this error is inherited from Song et al (PNAS 2005), which twice states that SZ13 is a sample from a civet.
This error is perplexing since the primary source for this data is clear on what animals were sampled and sequence identity. What's less well known is that Dongmen market continued to be sampled after May (Yaqing et al, Disease Surveillance 2004). Civets, raccoon dogs, and badgers were still available for sampling and still positive by PCR for SARS in October, November, and December 2003. It wasn't until spillover from civets to humans was definitively shown for the Guangzhou outbreak (Wang et al, Emerg Infect Dis 2005) that Guangdong province acted to close wildlife markets and end the civet trade. Dr. Garry notes similar findings at Xinyuan market in Guangzhou in January 2024.
Example 2 and 3: Zhan et al write, "The human and civet isolates of the 2003/2004 outbreak, which were collected most closely in time and at the site of cross-species transmission, shared only up to 99.79% S identity.” This is incorrect. Wang et al (Emergency Infect Dis 2005) write, "The 286-bp S gene sequences from isolates from the waitress and the physician were identical to 4 of 5 S gene sequences from palm civets from the restaurant.”
Example 4: The 99.79% identical sequence described by Wang et al (Emergency Infect Dis 2005) is instead from a different patient without a known link to the civet or other animal trade — a patient identified about one month before the first patient in the restaurant cluster. However, “An isogenic strain with the same SNV pattern, B012G, was detected in a palm civet from the Xinyuan animal market” (Kan et al J Virol 2005).
Conclusion: Repeated claims of no examples of 99.9% identical viruses in different species during SARS outbreaks were provably incorrect when this manuscript was preprinted. Furthermore, the manuscript appeals to near-identity of sequences obtained within Huanan market. Subsequently, it has been shown that both lineage A and lineage B were found in environmental sampling of Huanan market. I hope that authors will revisit their conclusions given the reality of the facts they based their arguments on.
On 2024-08-05 16:25:30, user Ra Hel wrote:
Hi, thank you for the thorough article. I would like to comment on : "We then employed GB classifiers in subsequent studies and utilized them to exclude studies that cannot discriminate the disease phenotype based on microbial profile."<br /> It would be really useful to have information on what percentage of studies for each disease passed this criterion - did you need to screen 10 studies per disease to have one that would be able to discriminate the phenotype based on microbial profile or rather vice versa that there were very few odd studies that didn't pass this selection.
On 2024-08-05 11:33:13, user Josh A wrote:
Nice paper, but ignores previous work on CHD1L/ALC1 and EMT and DNA-damage response.
On 2024-08-05 08:51:01, user Bayazit Yunusbayev wrote:
Hi, this sentence is not clear to me: "the probability that a given edge carries at least one mutation is inversely proportional to its<br /> time-length (assuming mutations occur as a Poisson process along the edges)." I might be missing here something, but isn't it so that older edges are expected to encounter more mutations?
On 2024-08-04 17:58:17, user Alex wrote:
The preprint has now been published in PNAS: Alexander M. Sandercock, Jared W. Westbrook, Qian Zhang, Jason A. Holliday. A genome-guided strategy for climate resilience in American chestnut restoration populations. Proceedings of the National Academy of Sciences, 2024; 121 (30) DOI: 10.1073/pnas.2403505121
On 2024-08-03 21:35:22, user Coleen Murphy wrote:
https://www.biorxiv.org/content/10.1101/2024.06.07.597568v2.full <br /> addresses all of the choice assay issues in Gainey et al..
On 2024-06-08 13:34:05, user Coleen Murphy wrote:
On 2024-06-07 16:53:51, user Reviewer 6 wrote:
I am a C. elegans researcher with some familiarity with the topics discussed. I do not personally know, nor have I interacted with any of the authors involved. I have read in detail both the preprint and the response in the comments. Below I provide some comments in the hope that they will hone arguments from both sides. For brevity, I refer to the authors of this preprint as “the authors” and Dr. Coleen Murphy as “CM”.
Summary:<br /> In my view, there are two issues here (1): the technical reproducibility of the choice assay; and (2) the physiological importance of CM’s results in a natural setting given the points raised by the authors. While CM makes some valid arguments on (1) – the authors should really have shown at least a few assays that attempted to follow the protocol exactly as stated by CM – the deviations here are in my view minor enough to raise significant questions about the choice assay and its interpretation. I believe the authors are justified in stating that (2) if the variables discussed here indeed significantly obscure detection of the phenotype, then the ecological significance of the inherited learned avoidance in a natural setting is in question. This is especially important given that, contrary to CM’s response, the authors do in fact see learned avoidance of PA14 as well as daf-7 expression at P0 and F1 in some experiments (indicating that the learning was induced) but not beyond in the F2 progeny of these same worms which displayed learned avoidance. Below is a detailed discussion of these points.
Specific comments:<br /> - CM states that the lack of naïve PA14 preference seen by the authors is a “serious cause for concern”. In CM’s 2024 paper (Fig 1, https://journals.plos.org/p... , worms are tested for bacterial food choice between OP50 (the lab food) versus bacterial species C. elegans may be exposed to in the wild. However, it seems that worms naively avoid OP50 (i.e. ‘prefer’ test bacteria) in essentially every comparison made by CM. This is contrary to reports by other labs (PMID: 38228683, PMID: 38228683) and in my view potentially a more serious concern with the assay. Contrary to CM’s assertion, while CM’s group and others see *mild* PA14 preference in naïve worms, other groups also do not observe such a preference in naïve worms or report more variable results (e.g., PMID: 21172617, PMID: 28877481, PMID: 31371455). Overall, the authors did replicate P0 and F1 learned avoidance in some runs and had a “learning index” consistent with prior reports in these experiments, so I do not see how the lack of purported naïve PA14 preference (which is quite minor and variable to begin with) is a significant concern here. <br /> - Looking at the authors’ raw data (table S2) for individual experiments, it seems the authors used <200 worms as advised by CM for most of their plates. The “up to 770 on a spot” was from a single plate, so I do not think this would change the conclusions of the authors. The authors compared worm density with choice index and found that there is no correlation within the ranges tested here.<br /> - “no azide or other paralytic used” (CM) – the authors claim to have tested this and state that addition of azide did not affect their results. They also claim that worms make a choice within 15 minutes and do not leave the respective lawn in the first hour of the assay. But none of this data is shown (it should be). <br /> - It seems that CM’s group counts worms in proximity to lawns “if they are within a few millimeters of the bacterial spot.” (STAR protocol). This may introduce systemic bias given the OP50 and PA14 lawns are clearly visibly distinct. Again, this raises questions to me regarding the reliability of this assay for interpreting minute effects and making broad generalizations.<br /> - Aspirating worms for counting would be unlikely to affect results.<br /> - The fact that conditions tested by the authors are varied between experiments is in my view a strength of this study given they did not observe F2 effects in any of their tests (you would normally change parameters rather than keep repeating the same protocol if you were unable to reproduce something, no?). However, testing variables/conditions such as temperature, light/dark etc. are informative only in a context where the authors have first fully followed through on the exact CM protocol with no deviations. So, I do think it is crucial to show a few attempts where the protocol is followed exactly as stated by CM.<br /> - The use of Triton X after bleaching may be a concern as CM points out. Though seemingly low (0.01%), this may hypothetically make bleached (i.e. already somewhat stressed) embryos or newly hatched L1s more vulnerable to pathogenic bacteria or alter their physiology. I do not see a point in including Triton X during or after bleaching, it is not standard nor required and is certainly a confounding variable. However, given the CMC of Triton X is 0.02% and the authors use below this concentration and only during plating, I would be surprised if this led to a dramatic change in the phenotype observed.<br /> - I do not find CM’s critique on daf-7 expression to be substantive. CM asserts that the authors do not see elevated daf-7p::gfp expression. Except they do! Which is especially evident with the single copy (SC) construct Fig 2 under SC at both 20 and 25oC. The magnitude of P0 daf-7 increase with the SC construct (~2 fold) is similar to what other groups observe at this generation (albeit with the multicopy strain, so it is hard to compare). I think the use of a single copy reporter is a strength of this paper, but in the future assays of daf-7 expression should really be done using endogenous CRISPR/Cas9 reporters. That an F2 response is not observed in runs where there is a high upregulation in the F1 generation is consistent with the authors’ interpretation.<br /> - The authors should show representative images of what is being quantified as CM states, as without this we do not know which neurons are being assayed. I do not think averaging both ASI neurons in a worm is a concern – even if there is an increase in one ASI, it would still be reflected in the average (as long as the correct neuron is being quantified). It may even reduce variability or bimodality to average the two, given the brightness of reporters on a confocal image can depend on the depth of the imaging plane as the authors state. <br /> - CM states that chunking is an unusual way to maintain the fluorescent strain. But this is a genomically INTEGRATED multi copy array (ksIs2), no? The point of the authors is that the fluorescence expression and associated Rol marker are unstable in their expression, which is not unusual for such integrated repetitive multicopy arrays. This is not an extrachromosomal array wherein fluorescent worms need to be picked to maintain the array, so CM’s statement that it is “standard accepted practice” to do so is simply wrong. In fact I find it quite concerning if CM’s group picks fluorescent worms to maintain this strain as it biases the worms for an epigenetic state in which the integrant is poised for expression, which may indicate other epigenetic issues in the strain’s background (i.e., lack of silencing of repetitive sequences). The instability of this strain I assume is why the authors obtained a single copy daf-7 reporter, which in any case would supersede any results obtained from a multicopy array. CM says nothing about the single copy integrant results, and I believe that given the authors observe P0 and F1 upregulation with the single copy integrant, I think the case is solid that there is no response observed in F2 worms from F1s showing daf-7 upregulation. An endogenous CRISPR/Cas9 reporter (e.g., transcriptional/SL2::GFP if a translational fusion is not possible) would really push home this point. <br /> - CM states that the authors replicates show poor “consistency”. However, we can only see this because the authors, unlike CM, show each experiment independently! We have no idea whether every experiment CM performed actually displayed learned avoidance behaviour, given the source data for CM’s choice assays is apparently not public. CM’s reports only show all learning experiments in aggregate, and I believe if the authors aggregated all their runs herein to a single plot, they would indeed see a seemingly ‘consistent’ avoidance effect. CM could easily address this by releasing raw/source data for choice/learning assays.<br /> - CM claims that in their hands behaviour from a set of training plates is ‘always’ consistent, but data are not shown. Both sides need to avoid making important claims without showing data.<br /> - CM states that the authors use of the same population to assay and then maintain for the next generation may confound the results. Again, the authors need to do the assay exactly as stated by CM, but if a few extra minutes of suspension in buffer really so obscures the phenotype beyond any detection, then how ecologically relevant can it possibly be? To my knowledge, there is no major phenotype that is completely ablated by a few minutes additional incubation in buffer. By this standard nothing involving washing off worms in a buffer would be interpretable.<br /> - It is interesting that sid-1 and 2 mutants do not show a learned F1 avoidance, but daf-7 expression is still elevated. It may be sufficient to have one SID protein for elevated daf-7 expression in progeny but require both for the behavior. Given both sid-1 and 2 are RNA transport channels, without double mutants and reliable daf-7 readout from an endogenous reporter, it is difficult for either group to infer any epistatic relationships between these genes. <br /> - I read the protocol file with notes from CM. I did not find any changes that are severe enough to cause concern and it seems that these are more clarifications/updates than changes to the fundamental principles of the assay. I also did not find the authors’ statements on this disingenuous, as there were clearly differences between the original STAR protocol and the updates provided. It is important for both parties here to refrain from personal attacks and address the substance of the arguments made.<br /> - I did find that some details in the STAR protocol were excessive, e.g., the height of plate stacks. I appreciate the detail but again, this raises the question that if such artificial variables really influence the phenotype so severely that it is no longer at all detectable, how physiologically relevant or robust can the phenotype be? <br /> - The statistical error in the STAR protocol pointed out by the authors: it seems either CM is misinterpreting a two-way ANOVA or that this was an oversight. I did not find this point too important overall as correcting such a statistical error would not change the conclusion of CM’s papers given the magnitude of effects previously described. <br /> - CM states that expression of P11 is essential for TEI. In CM’s 2020 paper (Kaletsky et al) it is stated that: “moreover, training on a P11 mutant that disrupts the perfect match to maco-1 but conserves P11 secondary structure induced no avoidance (Fig. 4e)”. As written, it seems essential not just for TEI (F2 effect) but also the P0 learning itself (unless CM can clarify that it is only required for the F2+ effect and that in Fig 4e only F2+ are being tested). So as I understand it, if lack of P11 expression is the issue, then there should be no P0 or F1 avoidance at all in any of these runs. Given the authors do not see an F2 effect in worms with robust P0 and F1 responses, it seems that this point is moot. I also do not think the authors can be blamed for any putative lack of P11 expression as it seems that for this portion (PA14 growth) they adhered to the protocol quite closely and explored various PA14 lines including those obtained from CM’s and other labs.
In summary, I think CM’s response is insufficient to alleviate many of the key concerns raised by the authors herein. I do not believe the lack of naïve PA14 attraction is a major concern, as there are literature examples where (a quite minor) naïve PA14 attraction is not observed. Furthermore, this is also confounded by CM’s recent (2024) paper wherein their worms prefer essentially every bacterium among a panel over OP50 in a naïve test, again contrary to prior reports from other labs. This makes me question the robustness as well as any broad conclusions that can be drawn from this assay.
The authors do also observe P0/F1 learned avoidance and elevated daf-7 expression contrary to CM’s rebuttal. I agree that the effects shown are not consistent between experiments here, but we cannot say whether this is simply because we are seeing here individual runs of inherently inconsistent assays whereas looking at an aggregate of data in CM’s papers (since the source data for the choice assays are not public). The major concern is that in those populations with P0/F1 responses (meaning the learning has been successfully induced), there is no further inheritance of avoidance beyond F1, and similarly for daf-7 wherein populations expressing high daf-7 at P0 and F1 do not transmit this to progeny. I believe this precludes “basic concerns about [the authors’] bacterial and C. elegans growth conditions, assay conditions, and assay techniques”. Overall, while it is important for the authors to show a few runs where the protocol is followed exactly as described by CM, I believe the deviations here are minor enough that even if they were able to replicate the transgenerational effect successfully, the sensitivity of the effect to such minutia would greatly diminish its physiological relevance to the worms - and its importance as an adaptive paradigm of transgenerational epigenetic inheritance - in a natural setting.
I also do not find it constructive for any party involved to address anything other than the scientific substance of arguments or engage in personal attacks. Given the attention and broad reach these studies have garnered, as well as the important implications, it is essential – and the normal course of the scientific endeavor – for such claims to be rigorously tested.
I also very much appreciate that the authors have shared these observations, and find it very commendable that CM has responded in a timely and comprehensive manner (as well as been responsive to the authors in refining their protocol).
On 2024-06-06 14:21:54, user Coleen Murphy wrote:
Gainey et al. failed to use experimental and assay conditions specified in the Murphy lab's protocols and added extraneous, damaging steps; together, these resulted in the Hunter lab's failure not only to test TEI, but also their failure to replicate previous, well-established preference of C. elegans for PA14, learned avoidance of PA14 in the P0 generation, increased daf-7 expression in the ASI and ASJ, and intergenerational avoidance of PA14. To summarize, Hunter and colleagues have not in fact attempted to faithfully replicate our protocols in a manner that would have tested transgenerational epigenetic inheritance of learned pathogen avoidance, and therefore cannot make any claims about reproducibility.
On 2024-06-05 18:16:30, user Coleen Murphy wrote:
Point-by-point critique of Gainey et al. 2024:
Figure 1: <br /> 1. (A-C) It has been reported by many groups that PA14 is mildly attractive to C. elegans, that is, given a choice between PA14 and OP50, worms choose PA141,2. However, in almost every assay shown in this paper, the worms prefer OP50 over PA14 – that is, they are already avoiding PA14 - prior to training (naïve preference), which is odd. This suggests that the authors are not using conditions that are standard, either in PA14 or OP50 growth or in choice assays (see note about choice assay performance). This is a serious cause for concern that is independent of any training conditions. In fact, as far as we can see, in only one case (Fig. 1C, F1) did their experiments replicate the naïve choice results observed by other groups. <br /> 2. Choice assays: their “choice assays” involve putting 3-4x the recommended number of worms on a plate (up to 770 on a spot!), letting them roam for variable amounts of time (“30-60 minutes”) without trapping them (no azide or other paralytic used), and then putting them in a 4°C incubator (which does not immediately halt worm movement), then counting them. None of this follows our published choice assay protocols, or the standard chemotaxis assay protocol3–6. Putting more than 200 worms on a single plate can lead to altered choice because of crowding. In the absence of a paralytic, worms change their preference due to various factors, including adaptation; therefore, in this case, the worms’ first choice (which is what we measure in all our assays) is not being measured. They also count the worms by “aspirating” the worms off of the plate, which is not standard in any behavioral assays, as far as we know.<br /> 3. Table 2 and Figure 1: There are almost no true replicates, as in each experiment, at least one or more condition is changed. (For example, the authors only tested the PA14 we sent them in one replicate - Exp 3). <br /> 4. daf-7p::GFP imaging experiments (Fig. 1D, F, H) – Hunter and colleagues do not report seeing increased daf-7p::gfp expression in the P0 generation. Increased daf-7p::gfp expression after exposure to PA14 has been reported by multiple groups7, not just ours, and is usually not small or highly variable, as it is due to the combination of bacterial cues and P11 small RNA; if they cannot replicate this basic result, it suggests that something is seriously wrong with their protocols or technique, or their worms are very sick, even before trying to use our protocol to train worms. <br /> 5. Additionally, they do not report the expression of daf-7p::gfp in the ASJ neuron7, which is very strange, since we have been able to reliably replicate Meisel, et al.’s finding in the P0 generation. Therefore, it is not clear from which neuron the authors are quantifying daf-7p::gfp levels. <br /> 6. Instead of imaging and reporting fluorescence levels in individual neurons, the authors averaged fluorescence intensity/worm, which is explicitly not what we did or others have done, because different neurons in each worm can have different intensities – particularly if they are the ASI rather than ASJ neurons. <br /> 7. While we see modest decreases in fertility after PA14 training, the authors report severe decreases in fertility: about one fifth of normal egg production, and a severe developmental delay) in their F1 generation that we do not observe. Both facts indicate that their worms are very sick, even the worms that have not been exposed to PA14. If their worms are extremely sick, it might account for the small number of progeny, poor imaging results, and a developmental delay that shifted the training times. This could be a result of overbleaching, which causes developmental delays; the bleaching protocol described in Gainey et al. deviates from our published protocol. Additionally, they add Triton X100 to their final M9 wash, which is used (although at a higher concentration) to permeabilize embryos in other protocols. We are not aware of any bleaching protocols that include Triton in a wash step, and our lab certainly does not; this addition might also damage the progeny.
Figure 2 <br /> 1. P0 imaging data suggest that the daf-7p::gfp response to PA14 is not reproducible in their hands; again, this has nothing to do with our paper or protocols, but rather appears that they cannot replicate previous results in the field that precedes our work. <br /> 2. Does “25°C” mean that the worms were grown at or assayed at 25°C, or both? This high temperature is generally hard on the worms. <br /> 3. Technical note: it appears that instead of consistently picking fluorescent daf-7p::gfp animals, the authors “chunked” large groups of worms, resulting in populations of non-fluorescent animals in their experiments. <br /> 4. Scale of P0 and F1 are extremely different (due to sickness of the P0s?).
Figure 3 <br /> 1. Notes that panels A, C, and D are repeated from Figure 1.<br /> 2. The authors discuss “OP50 aversion” but this does not make sense, since both trained and untrained animals are placed on HGs after bleaching. <br /> 3. Their naïve in F1 is sometimes even lower than in the P0 (Fig. 3D).<br /> 4. There is no consistency in their results across replicates, within experiments, or across figures of the paper – not just the inability to see an F2 effect, but in their naïve chemotaxes, P0 trained choice indices, and F1 results; the authors claim that their F1 assays are reproducible, but only 3 out of the 9 assays in this figure show F1 learned avoidance. <br /> 5. In 3J, data that are not replicates, as they have been performed using different conditions, have been pooled. <br /> 6. Gainey et al. observe substantial variation in behavior between training plates (Figure 3, table 2, S2 annotated protocol), and incorrectly treat each training plate as a biological replicate, rather than a technical replicate. (Each training plate is seeded and grown in the same conditions, and worms from the same bleached population are added onto the plates, therefore these are not biological replicates but rather technical replicates; biological replicates require starting with different worm populations and carrying out the whole experiment independently.) In our hands, behavior from a set of training plates is always consistent. <br /> 7. Additionally, we note that the authors use the same population of worms for the choice assays and subsequently for bleaching, meaning that worms are held in liquid for an extended time before bleaching; this may cause worms additional stress which may interfere with behavior.
Figure 4 <br /> 1. OP50 growth conditions: this would only matter if the controls and experimentals were grown on different plate types, which is not the case (but if the authors are in fact putting the controls on different plates from experimentals, then the experiment is done incorrectly).
Figure 5 <br /> 1. We also found that sid-1 and sid-2 are required, but since their controls are inconsistent (Fig. 3) in the first place, it is hard to know how to interpret their data. <br /> 2. Other mutants (rde-1, hrde-1, sid-1, sid-2) – still show increased daf-7p::gfp in F1 – again, these data are hard to interpret since they do not show a wild-type control that worked here. This also has little bearing on our work since other training paradigms (e.g., 4- and 8-hour training that engages small RNA-independent pathways) also induce daf-7p::gfp. It is also unclear which neuron (ASI vs ASJ) they are imaging.
Discussion <br /> 1. daf-7p::gfp - Picking fluorescent worms or rollers is standard worm husbandry; it is not a “result” to say that they noticed that Rol can be lost – but it does indicate that they should have discarded any results that they obtained before noticing that the array might have been lost in the worms they assayed. The fact that they have brought this up more than once suggests that they are not using standard accepted practices to maintain transgenic lines. <br /> 2. Dennis Kim’s work on phenazine-induced avoidance has been oddly neglected in this work7. Kim’s group found that phenazine-1-carboxamide induces Pdaf-7::gfp expression in the ASJ neuron, which we see quite reliably in our assays as well. No Pdaf-7::gfp imaging of the ASJ neuron is presented in this work, suggesting that either the PA14 they grew also did not make phenazines, or their image analysis is unreliable. <br /> 3. They made a lot of changes to our protocol (temperatures, light/dark, etc). We cannot find in this paper a single example of an experiment that followed our protocol entirely. <br /> 4. The authors make a point of calling OP50 a pathogen, which is odd; C. elegans grown on OP50 typically live for 2-3 weeks. They cite Garigan et al. 20028, which showed that when worms get old (past 15 days) eventually the pharynx stops grinding up bacteria and the gut will start to fill up with OP50, and killing bacteria does slightly extend lifespan - but this is not an effect observed in young (Day 1) animals on the short timescales used in the experiments here. In any case, since both control and trained animals are grown on HG plates with OP50, it cannot explain the behavior of the control animals. <br /> 5. The authors also never replicate the “bias towards Pseudomonas in choice assays ((Ha et al., 2010; Lee et al., 2017; Moore et al., 2019)” – Those papers also used OP50 vs PA14 to demonstrate this bias towards Pseudomonas, so it is unclear how the author think that their failure to replicate this basic finding is somehow supportive of any of their arguments. It is more likely that there is something fundamentally wrong in their initial conditions that have prevented the replication of all other groups’ findings, not just ours. Moreover, in our experiments, other than the 24 hrs of training on PA14 vs OP50, our control and trained animals are always on the same plates. This argument makes no sense, unless the authors have introduced an additional variable of plating control worms on one kind of plate/bacteria and their trained animals on a different plate/bacteria (which we do not do). <br /> 6. It is unclear why the authors grew worms at different temperatures. 20°C is the standard temperature for worm growth and assays. <br /> 7. In our hands, naïve OP50-PA14 choice index is not significantly different between P0 (when NGM plates are used) and the subsequent generations (when HG plates are used). The survival assay correlates well with the idea that their worms are very sick, much sicker than we see in our assays, although the sparse intervals in both assays make it difficult to draw any conclusions – not possible to draw the conclusion that the bacteria are “more lethal” since they are trying to compare two lifespans from different labs etc. - but if they are, it might be due to their PA14 cultivation conditions or the health of their worms. But the fact that they see massive leaving and desiccation of worms, they might indeed be growing PA14 under much more pathogenic conditions. <br /> 8. The authors state: “Near the conclusion of these experiments, we received an updated protocol that included several clarifying edits and additional deviations from the published protocols (C. Murphy, Personal communication).”
We clarified our protocols, we didn’t “deviate” from them. This is a concerning way to present our email communications in which we tried to correct errors in their protocol and offer constructive advice; we even extended an invitation to Hunter to visit our lab to learn the assay. We are happy to provide these emails if necessary.
In order to help others, we continuously update our lab’s protocols to make clarifications that will help future users. Any note from the Murphy lab is an example of this type of updating. For example, later we made a new bacterial construct that used a Kan marker and constitutive promoter instead of an Ara inducible promoter and Carb marker to streamline experiments. This is not a deviation, it is a natural progression of the research in our lab and our practice of continuously improving our assays and updating protocols.
It is disingenuous for the authors to present our updates to our protocols as if we have “deviated” from them – in every instance, we gave the authors all of the information that we had available to us at the time. Our suggestions were made genuinely and in good faith, with the assumption that the authors wanted to get the assay working rather than using it to point out changes in our protocol.
Moreover, this statement corroborates our assertion that all or most of the data in this paper seem to have been generated using a protocol that differs significantly from our lab’s, as the bulk of their experiments appear to have been done before contacting us: “Incorporating these changes into our procedures did not reliably alter our results.” (no data shown)
Together, Hunter and colleagues’ failure to replicate the basic naïve attraction to PA14 over OP50 demonstrated by other labs, their failure to replicate the P0 daf-7 expression published by other labs, and their failure to reliably replicate the P0 and F1 behaviors shown by other labs suggests to us that there are more basic concerns about their bacterial and C. elegans growth conditions, assay conditions, and assay techniques independent of any of the attempts to replicate the findings from our work.
References <br /> 1. Zhang, Y., Lu, H., and Bargmann, C.I. (2005). Pathogenic bacteria induce aversive olfactory learning in Caenorhabditis elegans. Nature 438, 179–184. https://doi.org/10.1038/nat....<br /> 2. Ha, H., Hendricks, M., Shen, Y., Gabel, C.V., Fang-Yen, C., Qin, Y., Colón-Ramos, D., Shen, K., Samuel, A.D.T., and Zhang, Y. (2010). Functional Organization of a Neural Network for Aversive Olfactory Learning in Caenorhabditis elegans. Neuron 68, 1173–1186. https://doi.org/10.1016/j.n....<br /> 3. Moore, R.S., Kaletsky, R., and Murphy, C.T. (2019). Piwi/PRG-1 Argonaute and TGF-β Mediate Transgenerational Learned Pathogenic Avoidance. Cell 177, 1827-1841.e12. https://doi.org/10.1016/j.c....<br /> 4. Moore, R.S., Kaletsky, R., and Murphy, C.T. (2021). Protocol for transgenerational learned pathogen avoidance behavior assays in Caenorhabditis elegans. STAR Protoc. 2, 100384. https://doi.org/10.1016/j.x....<br /> 5. Kauffman, A.L., Ashraf, J.M., Corces-Zimmerman, M.R., Landis, J.N., and Murphy, C.T. (2010). Insulin Signaling and Dietary Restriction Differentially Influence the Decline of Learning and Memory with Age. PLoS Biol. 8, e1000372. https://doi.org/10.1371/jou....<br /> 6. Kauffman, A., Parsons, L., Stein, G., Wills, A., Kaletsky, R., and Murphy, C. (2011). C. elegans Positive Butanone Learning, Short-term, and Long-term Associative Memory Assays. J. Vis. Exp., 2490. https://doi.org/10.3791/2490.<br /> 7. Meisel, J.D., Panda, O., Mahanti, P., Schroeder, F.C., and Kim, D.H. (2014). Chemosensation of Bacterial Secondary Metabolites Modulates Neuroendocrine Signaling and Behavior of C. elegans. Cell 159, 267–280. https://doi.org/10.1016/j.c....<br /> 8. Garigan, D., Hsu, A.-L., Fraser, A.G., Kamath, R.S., Ahringer, J., and Kenyon, C. (2002). Genetic analysis of tissue aging in Caenorhabditis elegans: a role for heat-shock factor and bacterial proliferation. Genetics 161, 1101–1112. https://doi.org/10.1093/gen....<br /> 9. Kaletsky, R., Moore, R.S., Vrla, G.D., Parsons, L.R., Gitai, Z., and Murphy, C.T. (2020). C. elegans interprets bacterial non-coding RNAs to learn pathogenic avoidance. Nature 586, 445–451. https://doi.org/10.1038/s41....<br /> 10. Moore, R.S., Kaletsky, R., Lesnik, C., Cota, V., Blackman, E., Parsons, L.R., Gitai, Z., and Murphy, C.T. (2021). The role of the Cer1 transposon in horizontal transfer of transgenerational memory. Cell 184, 4697-4712.e18. https://doi.org/10.1016/j.c....<br /> 11. Sengupta, T., St. Ange, J., Kaletsky, R., Moore, R.S., Seto, R.J., Marogi, J., Myhrvold, C., Gitai, Z., and Murphy, C.T. (2024). A natural bacterial pathogen of C. elegans uses a small RNA to induce transgenerational inheritance of learned avoidance. PLOS Genet. 20, e1011178. https://doi.org/10.1371/jou....
On 2024-08-03 16:25:52, user James Hurley wrote:
The community should be aware that the structure that is reported to be predicted here was already solved by cryo-EM and preprinted on Jun. 1, 2023 https://www.biorxiv.org/content/10.1101/2023.06.01.543278v3 and the cryo-EM coordinates of the same complex were released on Jun. 23, 2023 https://rcsb.org/structure/8SOI .
On 2024-08-03 15:08:52, user Mario Stanke wrote:
That should be Supplementary Table S1, rather than Table 1. Thanks for pointing the wrong reference out. The training species are also shown as a tree in Supplementary Figure S1.
On 2024-07-31 13:32:54, user kbseah wrote:
This looks very promising, congratulations! One point was unclear to me: which genome datasets were used to train the current mammalian model? The text refers to Table 1, but that just shows benchmarking results.
On 2024-08-02 17:16:23, user Lonki wrote:
The authors have errored by assuming that pregabalin and gabapentin are GABA-receptor ligands. Despite their names, they are not.
As stated in Wikipedia; “Pregabalin inhibits certain calcium channels, namely, it blocks α2δ subunit-containing voltage-dependent calcium channels (VDCCs).[13][26].
Also from Wikipedia “Despite the fact that gabapentin is a structural GABA analogue, and in spite of its name, it does not bind to the GABA receptors, does not convert into GABATooltip γ-aminobutyric acid or another GABA receptor agonist in vivo, and does not modulate GABA transport or metabolism within the range of clinical dosing.[82]<br /> “Gabapentin is a ligand of the α2δ calcium channel subunit.[82][83] α2δ is an auxiliary protein connected to the main α1 subunit (the channel-forming protein) of high voltage activated voltage-dependent calcium channels (L-type, N-type, P/Q type, and R-type).[13] Gabapentin is not a direct channel blocker”
Please read up on these drugs and re-interpret your observations.
On 2024-08-02 16:28:00, user Ana Vasque wrote:
Dear authors,
First I'd like to congratulate you on your work. I have read your article on the unique reproductive structure of Euphorbia species with great interest. However, I have specific inquiries regarding the filiform structures that were analyzed to determine the floral identity of the cyathium, and I would appreciate further clarification
In your study, did you observe results that suggested the upregulation of the B and E genes in these filiform structures, which would indicate a implying reduction in flowering? What is the correlation between these findings and previous research, such as that of Prenner and Rudall (2007), which discusses the presence of these structures associated with individual male flowers in certain species and their absence in others? Additionally, Prenner and Rudall (2007) reference Warming (1870), who observed and interpreted these structures as trichomes, noting their formation subsequent to the initiation of staminate flowers
Could you provide deeper insights into your interpretation of the formation and functionality of these threadlike structures in your analyses?
I am grateful for your attention to my inquiries. I look forward to your explanations and further discussion on the outcomes of your study.
Sincerely,
On 2024-08-01 16:35:16, user John McCusker wrote:
I just saw ( https://www.science.org/content/article/bad-agar-killing-lab-yeast-around-world-where-it-coming ). Many years ago, I had a similar problem with S. cerevisiae and C. albicans (but not E. coli) growth on agar. (Multiple vendors/suppliers, none of whom found anything wrong.) I eventually found that exposure of agar plates to light while drying (or incubating) caused the problem. Dried/incubated plates in dark and no problem.
On 2024-08-01 12:05:39, user Kenichiro Abe wrote:
Given the result of transcriptional inhibitor treatment with DRB or THZ1 in Fig.S9 and the report of Abe et al.,2010, NSN-SN transition seems like to be occurred independently of RPB1 degradation <br /> If you have any comments about this point, I would be happy to hear that
On 2024-08-01 07:43:29, user Ben wrote:
Hi. In the graphical abstract, the mus musculus heart cartoon shows a sagittal section. I would believe you wanted to show a heart with a scar.
On 2024-07-31 11:50:30, user Leyli Borner wrote:
This article has been published in Neobiota journal: https://doi.org/10.3897/neo...
On 2024-07-29 19:25:57, user disqus_FNcjH0JLKv wrote:
This paper has been published in Plos Comp Biol, please add link: https://doi.org/10.1371/journal.pcbi.1011586
On 2024-07-27 13:29:27, user Prof. T. K. Wood wrote:
Schumacher, M.A., et al., 2009. Molecular Mechanisms of HipA-Mediated Multidrug Tolerance and 531 Its Neutralization by HipB. Science, 323 (5912), 396-401, was found to be false in that HipA is a kinase but has nothing to do with EF-Tu. You should actually read the literature about the TA system you cite.
On 2024-07-26 15:46:59, user Prof. T. K. Wood wrote:
Line 70: Dy et al. is the 3rd report of phage inhibition by TAs; please cite the seminal ref doi: 10.1128/jb.178.7.2044-2050.1996 that predates it by 18 years.
Line 69: the TA refs related to persistence in this manuscript have been retracted so the link with persistence is not justified by this ref.
On 2024-07-26 14:37:06, user Julien Racle wrote:
This is a preprint of the following book chapter: Julien Racle and David Gfeller, How to Predict Binding Specificity and Ligands for New MHC-II Alleles with MixMHC2pred, published in HLA Typing, edited by Sebastian Boegel, 2024, Humana Press reproduced with permission of Springer Science+Business Media, LLC, part of Springer Nature. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-1-0716-3874-3_14 .
On 2024-07-25 20:29:22, user disqus_FNcjH0JLKv wrote:
The paper has been published in Protein Science, please add link: https://onlinelibrary.wiley.com/doi/full/10.1002/pro.5116
On 2024-07-25 20:28:20, user disqus_FNcjH0JLKv wrote:
The paper has been published in Scientific Reports: https://www.nature.com/articles/s41598-024-60991-x
On 2024-07-25 18:45:57, user Zhongmou Chao wrote:
It has been published in here: https://www.nature.com/articles/s41467-024-49415-6
On 2024-07-25 15:52:06, user Lynda Delph wrote:
This is terrific work. The authors might want to cite Lynda F. Delph, Keely E. Brown, Luis Diego Ríos, and John K. Kelly. Sex-specific natural selection on SNPs in Silene latifolia. Evolution Letters 6:308-318.<br /> In that paper they say "Finally, alleles favored by paternity selection tended to reduce female survival (Fig. 3D). The negative correlation here (ρ = −0.10) must be driven by a highly polygenic response."
On 2024-07-25 11:46:14, user Duchenne François wrote:
a revised version is published here:<br /> https://doi.org/10.1111/icad.12769
On 2024-07-23 22:12:13, user Anthony Baptista wrote:
Hello,
Your paper is very clear and interesting; congratulations on your work. I would like to suggest adding a relevant reference to your paper:
Baptista, A., Gonzalez, A., & Baudot, A. (2022). Universal multilayer network exploration by random walk with restart. Communications Physics, 5, 170. https://doi.org/10.1038/s42005-022-00937-9
Best regards
On 2024-07-23 21:06:26, user Christian Schröter wrote:
This work has now been published in Nature Communications, pmid: 38871742, https://doi.org/10.1038/s41467-024-49380-0
On 2024-07-23 17:58:20, user Ioannis Zervantonakis wrote:
Paper accepted and published in APL Bioengineering: https://pubs.aip.org/aip/apb/article/8/3/036105/3304419/CAR-T-cell-infiltration-and-cytotoxic-killing
On 2024-07-23 17:47:50, user Eric S wrote:
Accepted at JGP:<br /> https://doi.org/10.1085/jgp.202313523
On 2024-07-23 16:05:44, user Zach Hensel wrote:
I also have one brief comment regarding the discussion of "no expected interference to biological function" for a recombination breakpoint at position 21,314. The authors suggest that mutation to an isoleucine residue at position nsp16 I219 will "occur without having a significant impact on fitness linked to a disruptive function at a protein level."
The residue I219 is well resolved in crystal structures (e.g. PDB 6WVN) and makes hydrophobic contacts with other hydrophobic sidechains, suggesting that this is unlikely to be the case. This is testable by mutational fitness analysis -- https://jbloomlab.github.io/SARS2-mut-fitness/nsp16.html -- out of possible non-synonymous mutations that are sufficiently sampled during the pandemic, I219 tolerates substitution to leucine or valine, methionine is slightly disfavored, and mutation to any of arginine, lysine, or threonine is very rare. This suggests a significant fitness impact of substitutions at this position.
On 2024-07-23 16:03:09, user ryhisner wrote:
This preprint claims that the BA.2.86 lineage, which first appeared in the sequencing record in late July 2023, evolved gradually, while cryptically circulating over the course of about 17 months, beginning in early 2022. I do not find any of the evidence presented here convincing.
Three clusters of sequences, named C1, C2, and C3, are cited as evidence of cryptic BA.2.86 circulation prior to its emergence on the world stage. Each cluster has a far simpler, more parsimonious explanation than the hypothesis presented by the authors.
I have documented and analyzed cluster C1 as they have been uploaded, beginning in October 2023, and it appears to be a classic case of a chronic infection in an immunocompromised individual who may have transmitted to one other person. Three of the four C1 sequences have matching metadata—same location, age, and sex—while the fourth has the same location and age but a different sex. Furthermore, there are two additional, closely related sequences collected in 2024 (EPI_ISL_18969735 and EPI_ISL_19259365) whose metadata also match the other three.
It seems very unlikely the C1 sequences have any relation to BA.2.86. I count approximately 17 spike substitutions and one large deletion (∆138-144) that are in two or more of these four sequences but not in BA.2.86, including P9L, H69D, K77E, T95I, ∆136-144, R158K, Q183E, G213E, D215G, R346T, L452R, F486L, V615A, V642G, H681Y, L841R, D936Y, and D1146N. None of the four C1 sequences have the most distinctive spike mutations of BA.2.86, such as ins16MPLF, the triple-nucleotide F157S-R158G, A264D, I332V, K356T, L452W, or ∆V483. All C1 sequences have ORF1a:L3201F, which is found in BA.2 but not BA.2.86, and none of the C1 sequences possess any of the seven synonymous mutations found in the BA.2.86 branch (C8293T, T13339C, T15756A, A18492G, C21622T, C25207T, C26681T).
Of the more than 30 spike mutations (relative to baseline BA.2) in BA.2.86, I only see four that are shared between BA.2.86 and the C1 sequences: R403K, A484K, R493Q (reversion), and P621S. All of these are extremely convergent in highly mutated, chronic-infection sequences. I maintain a list of such sequences, and the R493Q reversion is the single most common private mutation, occurring 304 times independently, while R403K appears 103 times, and P621S 60 times. A484K, despite being a two-nucleotide mutation, has independently evolved at least 15 times among the sequences I've recorded. (G446S—very common both in chronic-infection sequences and circulating lineages—is in 2/6 sequences from this cluster).
Furthermore, the most recently uploaded sequence from this cluster—collected on May 22, 2024, but not listed in the C1 cluster in this paper—contains 16 new spike mutations (at least two of which I suspect can be attributed to sotrovimab treatment). Four of the 16 new spike mutations are also in BA.2.86 (I332V, K356T, L486P, and S939F), a textbook example of how, through convergent intrahost evolution, chronic-infection sequences can come to acquire mutations found in other chronic infections and in unrelated circulating lineages.
I do not see any resemblance between BA.2.86 and the C1 cluster in the non-spike part of the genome, apart from M:A104V, which is commonly found in chronic-infection sequences (32 independent acquisitions by my count), and is also found in the Pango-designated GS.4/5 lineage (XBB.2.3.11.4/5). It seems to me that this is a case of a chronically infected, immunocompromised individual who developed a few mutations also found in BA.2.86—mutations which are convergent in such chronic infections—and who may have transmitted to one other person (assuming there was not a mistake in the sex assignment of EPI_ISL_18415854, in which case these sequences almost certainly all came from the same patient).
The phylogenetic relationship between these sequences, as determined by USHER (Ultrafast Sample placement on Existing tRee, created at University of California Santa Cruz and maintained by Angie Hinrichs), can be seen at the following link: <br /> https://nextstrain.org/fetch/raw.githubusercontent.com/ryhisner/posited_BA.2.86_intermediates/main/BA.2.86_C1_posited_intermediates_Mexico_6_seq.json?c=gt-S_841&gmax=25384&gmin=21563&label=id:node_3061533
The C2 cluster (12 sequences of XBB.1.5.90, 11 from Japan, one from Finland) does not seem to resemble BA.2.86 at all. It is part of a large branch of XBB.1.5.90 (>400 sequences) with S:P621S, also found in BA.2.86, and the only other private mutation I see that it shares with BA.2.86 (but not other hundreds of other XBB.1.5.90 sequences) is C26681T, which is a highly homoplasic synonymous mutation in the coding region of M. Perhaps I am overlooking something, but the C2 cluster looks like a relatively humdrum branch of XBB.1.5.90 to me.
The Usher tree for these 12 sequences from C2 can be viewed here: https://nextstrain.org/fetch/raw.githubusercontent.com/ryhisner/posited_BA.2.86_intermediates/main/BA.2.86_C2_posited_intermediates_JPN_FIN_12_seq.json?c=userOrOld&label=id:node_4041697
The C3 cluster consisting of 10 sequences from Sarawak, Malaysia, were all uploaded on the same day (2024-1-25), bear the same collection date (2022-3-11), and have spikes identical to JN.1—including S:L455S—from S:356 to S:681, while the rest of spike is identical to baseline BA.2. The remainder of the genome in these sequences is extremely odd. Two sequences contain the XBB mutation ORF1b:S959P. Seven have the universal BA.2.86 mutation ORF1a:N2526S, while three lack it. One has the BA.2.86.1 mutation ORF1a:K1973R. Seven of the ten have ORF1a:L3201F, which is absent from all BA.2.86. No dropout is indicated in any of the sequences.
The same Malaysian lab uploaded 321 other sequences (EPI_ISL_18821317-18821647), all from Sarawak, Malaysia, on the same day they uploaded the 10 C3 sequences. The collection dates of these sequences range from 2022-2-27 to 2024-1-9 and include 153 JN.1* sequences and 12 XBB* sequences. As Zach Hensel has noted, six of the ten C3 sequences have G19677T (ORF1b:2070H), which is the defining mutation of BA.2.40, a variant that made up about 60% of all sequences in Sarawak, Malaysia, in mid-March 2022. (Source: https://cov-spectrum.org/explore/Malaysia/AllSamples/from%3D2022-01-15%26to%3D2022-04-28/variants?nextcladeQcSnpClustersScoreTo=55&variantQuery=Nextcladepangolineage%3ABA.2.40*&)
Sixty-three sequences in this upload are categorized by Nextclade as being BA.2.40 and have 0-3 mutations relative to baseline BA.2.40. Most suspicious of all, 29 of the 153 JN.1* sequences in this same upload also have G19677T. From July 1, 2023 to the present, just 77 sequences categorized by CovSpectrum as BA.2.86* (from 13 different Pango-designated lineages) have had G19677T, with 30 of those coming from Malaysia. (Source: https://cov-spectrum.org/explore/World/AllSamples/from%3D2023-07-01%26to%3D2024-07-14/variants?variantQuery=Nextcladepangolineage%3ABA.2.86*+%26+G19677T&)
It seems clear that the 10 C2 sequences were BA.2 sequences contaminated by JN.1 sequences from the same upload.
The authors list 129 sequences they claim shorten the branch leading to BA.2.86, of which I was able to find 128 on GISAID. Ten of these sequences are from the C3 Malaysian cluster described above, along with one additional sequence from the same upload. Apart from these C3 sequences, there are only six sequences with collection dates preceding the first BA.2.86 sequences. All others were collected more than seven weeks after the first BA.2.86 sequences. Six sequences were collected between 7-14 weeks after the first BA.2.86, while the remaining 105 sequences were collected more than 15 weeks afterward.
It would be surprising if one could not find hundreds of such "hybrid" sequences due purely to contamination. Such sequences have frequently appeared in the sequencing record throughout the pandemic. A few sequences may result from coinfection, but the quality of these sequences, described below, along with the fact that a large proportion of them come from a small number of labs with records of quality-control issues, support the hypothesis that these sequences result from contamination or other lab errors.
All of the sequences in this list are low quality. They feature a mixture of extensive dropout (particularly in spike), frameshifts, large numbers of mixed nucleotides, clearly artifactual reversions, and mutations from multiple lineages (primarily BA.2.86 and XBB) with no distinct breakpoints. Many of these sequences come from labs known to have frequent quality-control issues. For example, there are 52 sequences from the United States, but none are from the CDC, whose sequences are virtually always first-rate. Instead, they come from smaller local and state labs, whose sequencing quality is often inconsistent.
The 28 sequences from Texas, for example, come from city hospitals. The average Nextclade qc score of these sequences is 2901 (median 2882). Anything over 100 is designated "bad" by Nextclade. The average number of ambiguous nucleotides per sequences is 17 (median 17), and they average 690 nucleotides of dropout. (EPI_ISL_16599325, EPI_ISL_16599747, EPI_ISL_18546432, EPI_ISL_18690036, EPI_ISL_18690080, EPI_ISL_18690421, EPI_ISL_18690466, EPI_ISL_18690496, EPI_ISL_18743044, EPI_ISL_18743073, EPI_ISL_18743094, EPI_ISL_18743097, EPI_ISL_18743159, EPI_ISL_18743350, EPI_ISL_18743431, EPI_ISL_18743464, EPI_ISL_18743470, EPI_ISL_18743477, EPI_ISL_18743592, EPI_ISL_18816401, EPI_ISL_18816517, EPI_ISL_18816528, EPI_ISL_18816612, EPI_ISL_18816709, EPI_ISL_18816890, EPI_ISL_18816980, EPI_ISL_18874714, EPI_ISL_18908998)
Similarly, the 17 sequences on this list from Italy are all from the same lab, have an average Nextclade qc score of 2356 (median 2253) and average 1349 nucleotides of dropout. Some sequences on the list are somewhat less bad than these, but none are high-quality. <br /> (EPI_ISL_18496352, EPI_ISL_18674020, EPI_ISL_18677248, EPI_ISL_18721993, EPI_ISL_18722001, EPI_ISL_18722007, EPI_ISL_18722009, EPI_ISL_18755145, EPI_ISL_18792827, EPI_ISL_18792828, EPI_ISL_18792829, EPI_ISL_18792831, EPI_ISL_18820147, EPI_ISL_18820149, EPI_ISL_18820150, EPI_ISL_18820154, EPI_ISL_18820157)
Finally, I also examined the list of 100 sequences from Supplementary Data 1, Table 5, containing genomes posited by the authors to be recombinants related to ancestors of BA.2.86. These sequences seem to me to fall into five different categories.
First, there are numerous sequences here that are also listed in one of the C1-C3 clusters—three sequences from C1 (EPI_ISL_18415832, EPI_ISL_18415854, EPI_ISL_18798234), three from C2 (EPI_ISL_18040349, EPI_ISL_18060516, EPI_ISL_18106303, EPI_ISL_18116248), and four from C3 (EPI_ISL_18821484, EPI_ISL_18821485, EPI_ISL_18821487).
Second, nine of the sequences appear to be fairly unremarkable XDD sequences, which is a designated JN.1/EG.5.1.1 recombinant (EPI_ISL_18617332, EPI_ISL_18706019, EPI_ISL_18706171, EPI_ISL_18553650, EPI_ISL_18653986, EPI_ISL_18531477, EPI_ISL_18569411, EPI_ISL_18695627).
The third category consists of what seem to me to be relatively normal sequences from a variety of Omicron lineages but with little resemblance to BA.2.86. Some of them have extensive dropout and come from labs known for high rates of artifacts and contamination. (EPI_ISL_18076898, EPI_ISL_17990180, EPI_ISL_18062641, EPI_ISL_18000549, EPI_ISL_18042058, EPI_ISL_18104305, EPI_ISL_18070023, EPI_ISL_18044667, EPI_ISL_18111437, EPI_ISL_15153261, EPI_ISL_17255807, EPI_ISL_15153261, EPI_ISL_16282414, EPI_ISL_16457740)
The fourth category is BA.2.86 or JN.1 sequences that either don't strike me as very unusual or else have extensive dropout and artifactual reversions. A few of these are from unreliable labs. (EPI_ISL_18097345, EPI_ISL_18556860, EPI_ISL_18567791, EPI_ISL_18682823, EPI_ISL_18705393, EPI_ISL_18635682, EPI_ISL_18503709, EPI_ISL_18400531, EPI_ISL_18717823, EPI_ISL_18446586, EPI_ISL_18584588, EPI_ISL_18631046, EPI_ISL_18700743, EPI_ISL_18675075, EPI_ISL_18659819, EPI_ISL_18713456, EPI_ISL_18636806, EPI_ISL_18704459, EPI_ISL_18686183)
The fifth and largest category is highly divergent sequences almost certainly deriving from chronic infections, but which appear to me to bear almost no resemblance to BA.2.86 apart from the possession of a few mutations that are widely convergent in such sequences. I've documented most of these, and almost all contain a large number of mutations and deletions not found in BA.2.86 and lack the vast majority of BA.2.86 mutations.
I hope I haven't misinterpreted any of the authors' hypotheses or data.
-Ryan Hisner
On 2024-07-20 14:19:32, user Zach Hensel wrote:
The cluster described in Malaysia (C3) jumped out as having identical collection dates that are earlier than those typically associated with GISAID accessions this high (and consistent with those for Malaysia sequence circa November 2023) and also differ at multiple, overlapping positions despite being sampled on the same day.
Briefly, further investigation (using cov-spectrum and UShER phyloplace) identified four sequences from Mayasia with March 2022 collection dates containing both M:D3H and M:T30A:
EPI_ISL_18821484 (in C3)<br /> EPI_ISL_18821485 (in C3)<br /> EPI_ISL_18821546<br /> EPI_ISL_18821638
These all share G19677T, which is a mutation characterizing BA.2.40 in Malaysia which was common in March 2022 (760 out of 855 sequences worldwide with G19677T were found in Malaysia that month; 52% of sequences from from Sarawak, Malaysia collected in March 2022 have this mutation).
Further, the three sequences that are placed by phyloplace are found together with other sequences from Malaysia. This identifies another sequence with M:D3H and M:T30A sampled in Malaysia, EPI_ISL_18821317. Other mutations in these sequences are shared with various other lineages prevalent in Malaysia in March 2022.
One sequence with M:D3H and M:T30A, EPI_ISL_18821638, could not be placed by phyloplace, but NextClade calls it as BA.1.1 because it contains the BA.1-defining EPE insert in S.
The manuscript notes, regarding the period of Omicron emergence, "South Africa and Botswana, where genomic surveillance was more robust than in many other parts of Africa." BA.2.86 emergence in Southern Africa is well supported: <br /> https://www.nature.com/articles/s41467-023-43703-3
It is implausible that an intermediate between BA.2 and BA.2.86 would recombine with multiple lineages circulating in Malaysia and only be detected in Malaysia without leaving a trace in southern Africa given that this surveillance continued. Rather, I suspect that these observations are likely artifacts arising from processing samples collected in March 2022 together with samples collected in late 2023.
This can be tested by comparing mutations in these sequences to those observed in BA.2.86* strains common in Malaysia in late 2023. The most common of these is JN.1, which contains S:L455S as well as the S deletion shown for the C3 sequences here.
On 2024-07-23 09:42:00, user Prof. T. K. Wood wrote:
Line 86 is false: reduction in ATP has been shown to increase persistence by 10,000-fold in 2013 (doi:10.1128/AAC.02135-12).
On 2024-07-23 09:33:40, user Prof. T. K. Wood wrote:
Lines 36 and 46 are false; please cite the relevant primary literature for the mechanism of persister cell formation in regard to ppGpp leading to ribosome dimerization and resuscitation based on reactivating ribosomes, all based on single-cell microscopy ( https://doi.org/10.1016/j.bbrc.2020.01.102 and https://doi.org/10.1016/j.isci.2019.100792 ) .
On 2024-07-22 12:47:53, user Simon Crouzet wrote:
This article has been now published in CSBJ. Link to the publication: https://doi.org/10.1016/j.csbj.2024.06.029
On 2024-07-21 18:44:35, user Terri Mitchell wrote:
While the idea of AI condensing 500 million years of evolution into a few minutes sounds very grandiose, a protein mutated in isolation is not fast forward evolution--it's just a mutated protein. AI has provided the blue print for an artificial protein situated outside of evolved life. The marine organisms that actually evolved molecules to transduce blue wavelengths of light into longer wavelengths of other colors and reemit them for a reason having to do with natural selection have done it already. They evolved the fluorescent molecules. ESM3's value is solely commercial, and no doubt it will be a hop, skip and jump from making the sequence available to researchers to commercializing it as contrast dye. Its origins will soon be forgotten, but its effects on the environment, and therefore life, will undoubtedly be persistent and deleterious.
Wrapping the report in intellectual arguments about evolution doesn't scientifically validate the claim that an AI-generated mutant is "evolved". Even if the AI endgame was reached--replacing all life with a human-devised approximation, and it was somehow achieved by pseudo-evolution--ESM3 would still have no evolutionary value since it was synthesized in isolation. AI mutated a protein: it didn't evolve a protein. Making scientifically invalid claims doesn't advance the case for AI. Just the opposite.
On 2024-07-21 16:01:56, user Min Zhu wrote:
The full version of this manuscript is online in Science Advances. https://www.science.org/doi/10.1126/sciadv.adl6366
On 2024-07-21 00:09:37, user Meet Zandawala wrote:
Manuscript title: TRPγ regulates lipid metabolism through Dh44 neuroendocrine cells
Summary: This manuscript from Youngseok Lee lab examines the role of TRP gamma channel in regulating metabolic physiology. Specifically, it focuses on the regulation of lipid metabolism via DH44 neuroendocrine cells. It is a follow-up on the work from the same lab where they showcased the importance of TRP gamma in DH44 cells in regulating post-ingestive food selection (Dhakal et al 2022: https://doi.org/10.7554/eLife.56726 ). Overall, this work adds to the growing body of work on DH44 neuroendocrine cells which appear to be crucial internal metabolic sensors. We have a few major comments and suggestions on the preprint which could help clarify the mechanisms by which TRP gamma regulates lipid metabolism.
Minor comment:<br /> 1. Stock numbers for fly strains have not been provided.
Signed by,<br /> Meet Zandawala <br /> Jayati Gera<br /> (Zandawala lab members)
On 2024-07-20 17:34:16, user Andrea Ravasio wrote:
This preprint has now been published here:<br /> https://doi.org/10.1038/s41467-024-49850-5
On 2024-07-19 21:58:04, user Matt Jones wrote:
This work has now been peer-reviewed and published in Molecular Plant- https://www.cell.com/molecular-plant/pdf/S1674-2052(24)00226-0.pdf?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1674205224002260%3Fshowall%3Dtrue
On 2024-07-19 19:06:04, user Maryam Foroozani wrote:
May I ask where I can find the supplementary figures?
On 2024-07-19 16:59:13, user Michael Silverstein wrote:
On 2024-07-19 03:05:31, user Adriana Ludwig wrote:
Congratulations on your excellent work! I'm wondering, if still possible, if you could consider citing our work ( https://doi.org/10.1186/s13100-019-0175-2 ) when you mention VIPER's potential activity, since all previous works indicated VIPER as a degenerate family. Cheers!
On 2024-07-18 19:44:19, user Jorge Cruz-Reyes wrote:
This paper in now in press. NAR-01088-C-2024.R2<br /> KREH2 helicase represses ND7 mRNA editing in procyclic-stage Trypanosoma brucei by opposite modulation of canonical and “moonlighting” gRNA utilization creating a proposed mRNA structure
On 2024-07-17 15:41:07, user Matilda wrote:
https://www.cell.com/iscience/fulltext/S2589-0042(24)01665-1
On 2024-07-17 11:55:37, user Ryan Sheldon wrote:
A peer reviewed version of this paper is now available here:<br /> https://www.nature.com/articles/s41467-024-50128-z
On 2024-07-17 09:55:16, user disqus_DPScP8M4wg wrote:
This study is now published at Nature Structural & Molecular Biology:<br /> Lange, S.M., McFarland, M.R., Lamoliatte, F. et al. VCP/p97-associated proteins are binders and debranching enzymes of K48–K63-branched ubiquitin chains. Nat Struct Mol Biol (2024). https://doi.org/10.1038/s41594-024-01354-y
On 2024-07-16 22:58:40, user Jim T wrote:
My congratulations to the authors on this impressive work! Your estimated 300kya date for the divergence of the ancestry of Khoe-San seems like a relatively good fit for the newer dates for the emergence of the Lupemban culture. Has this possible match been considered?
“Early Stone Age (ESA) archaeology is effectively absent from the rainforest zone, with the early Middle Stone Age (MSA) Lupemban industry representing the earliest sustained archaeological signature. Uranium-series dates of approximately 265 ka BP for the Lupemban at Twin Rivers (Zambia), although queried, suggest a precocious late Middle Pleistocene dispersal of early Homo sapiens into the equatorial rainforest belt.” - Taylor 2021
https://royalsocietypublishing.org/doi/full/10.1098/rstb.2020.0484
On 2024-07-16 19:03:57, user Zehua Zeng wrote:
* Published Article: OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing
* Link: https://www.nature.com/articles/s41467-024-50194-3#Ack1
On 2024-07-16 16:40:35, user Susana wrote:
This paper has now been published at Journal of Molecular Biology. It is available online at https://authors.elsevier.com/sd/article/S0022-2836(24)00320-6
On 2024-07-16 09:31:08, user Sudin Bhattacharya wrote:
Very interesting work. However, analyzing distances in high-D space is problematic. Couldn't these findings be attributed to the curse of dimensionality, where far-away points all appear equidistant?
On 2024-07-16 00:37:36, user Lana wrote:
Nice work, I didn't know ENTs could have so many phenotypes. Interesting
On 2024-07-15 17:57:37, user Sergio Verjovski-Almeida wrote:
I am glad to inform that this preprint has now been published at Molecular Biology and Evolution, Volume 41, Issue 7, July 2024, msae123, https://doi.org/10.1093/molbev/msae123 <br /> Published: 24 June 2024
On 2024-07-15 17:30:04, user priyanka.bajaj3193@gmail.com wrote:
Reviewed by Priyanka Bajaj and Christian B. Macdonald (UCSF)
Summary:
Fusion oncoproteins occurring from genomic rearrangements are commonly observed in cancers and often drive oncogenesis. Although these fusions frequently involve kinases or transcription factors, they are a diverse group at both molecular and functional levels, and a unified description of their oncogenetic properties is lacking. Robust methods for predicting oncogenicity of unknown fusions would be immediately clinically useful, making this an important gap. At a more basic level, this points to a gap in our ability to describe a key biological phenomenon. Some recent work has tackled this problem by examining the physicochemical properties of fusion oncoproteins, notably [1], but this is essentially still an open question.
In this manuscript, the authors present a language model of fusion oncoproteins, FusOn-pLM, by fine-tuning ESM-2 with two recent databases of human fusion oncoproteins. They compare random masking vs. one using their previous fine-tuned ESM-2 model SaLT&PepPr and benchmark their results on a number of tasks, demonstrating reasonably increased specificity on specific tasks and improvement with non-random masking. The model training and benchmarking are sound and convincingly demonstrate the improvement.
Despite this, the lack of clarity about what unifies fusion oncogenes is a major challenge. Language models can be powerful ways to learn these sorts of definitions in a less biased way, and in that light this is an important step towards clarifying this basic gap. However, as written, the work uses a working definition of fusion oncogene that is based on physicochemical properties that may or may not be specific to oncogenes. Examining the benchmarking tasks the authors use makes this clearer: they are almost entirely predictions of condensate and IDR properties rather than oncogenetic ones. The one truly cancer-specific benchmark, differentiating carcinoma classes, is fairly narrow and no model performs particularly well here. As a result, we are unsure how strongly this model will perform in discrimination or generalization tasks.
Another general problem for the field is the lack of negative controls. Gene fusions are relatively common mutations, but bona fide oncogenic fusions are a small fraction of all fusions, making this a class imbalance problem. Even within tumors, the majority of fusions are thought to be passengers rather than driver mutations. Any predictor should be able to discriminate between these, but the lack of good data on non-oncogenetic fusions makes this challenging. This is evident in this work, where the model’s discrimination is not strongly tested.
In summary, we believe this is technically strong work which addresses a pressing need, and which also presents some general strategies for domain-specific language model fine-tuning, but which is unfortunately hamstrung by defects in the available data and conceptualization of the field that are outside of the authors’ control. As presented, it will be of interest to AI practitioners and oncofusion researchers, but the clinical utility is unclear.
Major points:
1) As discussed, we think the concept of an “oncofusion” is somewhat diffuse, as it describes an extremely heterogeneous set of proteins. This makes the prediction task particularly difficult. While the introduction discusses the barriers to prediction of fusion oncoproteins due to their intrinsically disordered regions and large size, we believe a bit more care with the effective definition they are using is warranted. Related to this is the choice of FOdb to train their model, which is essentially a database of condensate properties of oncofusions rather than oncogenetic ones. The implications of this choice also warrant a bit more discussion.
2) We wonder if there is a class imbalance problem. The databases used to fine-tune their model have a small fraction of possible fusion proteins, and don’t contain large amounts of negative training information. We are thus unsure if FusOn-pLM’s significant improvements over ESM-2 are specific to driver fusion oncogenes.
3) The method is not contextualized with respect to prior work in computational oncofusion prediction and characterization. Such methods are few ([2],[3],[4],[5],[6] among others) but important to understand FusOn-pLM’s performance.
4) Several experimental datasets for fusion oncogenes have been published, including [7], [5], and [8]. FusON-pLM’s performance on these would be a compelling way to show its utility, as well as a more specific oncogenetic task.
Minor points:
1) Figure 2D: Although FusON-pLM is doing a slightly better job at distinguishing carcinoma prediction into two classes (BRCA vs. STAD), the performance metrics are the worst across the board. What does this mean for the prediction problem overall? Does the fact that IDR and condensate properties are much better predicted mean that the model is actually not learning an oncogenetic task? This seems worthy of more discussion.
2) Figure 4A: The authors present a FusOn-pLM embedding visualization of fusion oncoproteins, along with the corresponding head and tail protein sequences. It would be beneficial to clarify whether the protein sequences used for the head and tail counterparts are full-length sequences or only up to the exon breakpoint that forms the chimeric fusion protein. This information can be included in the Materials and Methods section.
3) Figure 4A: The authors demonstrate that FusON-pLM is able to separate out fusions from their head and tail components. To demonstrate that it is learning more specific embeddings for fusion oncoproteins, a comparison of the embeddings with untuned ESM-2 would be appropriate.
4) Figure 4B: In the main text of results section the authors write “FusOn-pLM largely clusters sequences by key properties such as the fraction of polar, charged, and disordered residues as well as the propensity to form pi-pi and pi-cation interactions and prion-like domains, via the PLAC NLLR score.” From the data shown in Figure 4B, this conclusion seems fine for polar residues and NLLR scores, but not for disordered residues and pi-pi/pi-cation interaction propensity by eye. Without quantification of the clustering, we are not sure this statement is supported.
References:<br /> 1. Tripathi S, Shirnekhi HK, Gorman SD, Chandra B, Baggett DW, Park C-G, et al. Defining the condensate landscape of fusion oncoproteins. Nat Commun. 2023;14: 6008.<br /> 2. Shugay M, Ortiz de Mendíbil I, Vizmanos JL, Novo FJ. Oncofuse: a computational framework for the prediction of the oncogenic potential of gene fusions. Bioinformatics. 2013;29: 2539–2546.<br /> 3. Abate F, Zairis S, Ficarra E, Acquaviva A, Wiggins CH, Frattini V, et al. Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer. BMC Syst Biol. 2014;8: 97.<br /> 4. Lovino M, Montemurro M, Barrese VS, Ficarra E. Identifying the oncogenic potential of gene fusions exploiting miRNAs. J Biomed Inform. 2022;129: 104057.<br /> 5. Li J, Lu H, Ng PK-S, Pantazi A, Ip CKM, Jeong KJ, et al. A functional genomic approach to actionable gene fusions for precision oncology. Sci Adv. 2022;8: eabm2382.<br /> 6. Liu J, Tokheim C, Lee JD, Gan W, North BJ, Liu XS, et al. Genetic fusions favor tumorigenesis through degron loss in oncogenes. Nat Commun. 2021;12: 6704.<br /> 7. Frenkel M, Hujoel MLA, Morris Z, Raman S. Discovering chromatin dysregulation induced by protein-coding perturbations at scale. bioRxiv. 2023. doi:10.1101/2023.09.20.555752<br /> 8. Kobayashi Y, Oxnard GR, Cohen EF, Mahadevan NR, Alessi JV, Hung YP, et al. Genomic and biological study of fusion genes as resistance mechanisms to EGFR inhibitors. Nat Commun. 2022;13: 5614.
On 2024-07-14 15:14:50, user Dd wrote:
Great work! <br /> We always wonder if the size of EVs is interfering with the binding capacity of the beads? Thus result in a lower detection maybe? Can you also share some images from the bead based flow cytometry? Thanks!
On 2024-07-13 07:51:37, user alexander_zlobin wrote:
Hi, I commented on the same issue before, but there is still one figure in the SI that retain the confusion between HID and HIE states of the catalytic His in serine triad proteases. This is figure S49, and it should be corrected.
On the unrelated topic, are you planning to provide your datasets later? I am particularly interested in all PDB entries you found and classified into GSA/TSA. As you of coarse are familiar, PDB searches are quite tiresome, and having this data already available would help tremendously.
Sincerely yours,<br /> Alexander Zlobin<br /> MeilerLab Leipzig, Germany
On 2024-07-12 23:46:41, user Alex wrote:
I hate myself for doing this, but apparently this is the only way to point this out: why doesn’t this benchmark include singleCellHaystack? Haystack was published in Nat Commun in 2020, has >75 citations now, is easy to install and run. An updated was published last year In Scientific Rep. Still, a part of this field that has apparently decided that it is completely fine to ignore this method.
On 2024-07-12 14:18:11, user Prof. T. K. Wood wrote:
DarT/DarG is better characterized as a type V TA system; this category is based on the fact that antitoxin DarG is an enzyme but does not alter the toxin (type VII). The first member of this group is GhoT/GhoS (please cite doi: 10.1038/NChemBio.1062).
Toxin/antitoxin systems were first shown to inhibit phage in 1996 (please cite doi: 10.1128/jb.178.7.2044-2050.1996).
On 2024-07-12 04:36:28, user Sam Buckberry wrote:
Our response to this preprint, titled ‘Transient Naive Treatment (TNT) iPS cells do not feature Sendai virus expression: Response to Sendai virus persistence questions the transient naive reprogramming method for iPSC generation’ is available here: https://www.biorxiv.org/content/10.1101/2024.07.10.602807v1
On 2024-07-11 13:25:32, user Pookey532 wrote:
A small correction in Table 1.<br /> CRISPR gRNA vector wrongly including PAM sequence, the consequence should say "gRNA plasmid becomes target of CRISPR cleavage" with the caveat that this would only be the case if the wrongly included PAM is followed by another PAM, which is not the case in many CRISPR plasmids such as the pX330 derived ones. This would obviously affect cleaving at the target if its PAM is not followed by a second PAM.
While some errors in the table are almost certainly errors in design (ex stop codons before a 2A sequence, mutations in ITRs, etc...) I'm curious why some of the other design "errors" are deemed errors. For example, using CMV in AAV vectors can be a perfectly acceptable choice depending on the use of the virus, especially if it isn't intended for long term expression. Likewise, use of "unstable" sequences in high copy plasmids can be a problem, however if those plasmids are maintained in bacteria that maintain plasmids at a low copy (Epi400, Stbl2, etc...), the replication origin of the plasmid becomes less relevant as the copy number becomes more dependent on the host strain. Similar to this, "Vectors containing toxic genes to E. coli host" is not necessarily a design error. Sometimes this simply the only option.
On 2024-07-10 18:49:28, user Björn Reumont wrote:
This preprint is published since Oct 2023 in BMC Biology, Open Access: Prevalent bee venom genes evolved before the aculeate stinger and eusociality, Link https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-023-01656-5
On 2024-07-10 18:05:43, user Matthias Samwald wrote:
Final article has been published in Computers in Biology and Medicine:
GPT-4 as a biomedical simulator https://doi.org/10.1016/j.compbiomed.2024.108796
On 2024-07-10 07:25:49, user Constantinos Constantinides wrote:
Published version: https://onlinelibrary.wiley...
On 2024-07-10 03:40:12, user Zach Hensel wrote:
This article does not match my experience in Okinawa and the caricature of Okinawa here is not necessary to make the point.
Some of the claims are simply wrong (e.g. the description of civil marriage registration). Others are caricatures for rhetorical effect (e.g. "14 cans of SPAM" is not what the reference says). In general, the list of supposed ills in Okinawa today has no direct connection to the longevity of today's 100-or-so-year-olds.
I hope that the author can speak with people in Okinawa and perhaps reconsider this approach.
On 2024-07-09 08:31:45, user Rouslan Efremov wrote:
This preprint has been published in Nature Communications https://doi.org/10.1038/s41...
On 2024-07-08 22:32:03, user Tara wrote:
This manuscript is now published at the Journal of Infectious Diseases<br /> https://doi.org/10.1093/inf...
On 2024-07-08 17:53:48, user David Lukac wrote:
Link to peer-reviewed publication: https://pubmed.ncbi.nlm.nih...
On 2024-07-08 16:13:36, user Agnieszka Lipinska wrote:
Just to clarify, the data provided for Fucus serratus does not correspond to 'released sperm and eggs'. We sequenced vegetative tissue as well as reproductive tissue (whole receptacles) containing sperm or eggs, but not isolated gametes. Please see https://doi.org/10.1111/nph... for reference.
On 2024-07-08 10:19:50, user Frederica Theodoulou wrote:
This paper is now published at: doi: 10.1093/plcell/koae117
On 2024-07-07 15:56:39, user Ben Davis wrote:
Now published at https://www.nature.com/arti...
On 2024-07-05 13:00:12, user Xuan Zhang wrote:
Now published in Genome Biology: https://genomebiology.biome...
On 2024-07-05 12:57:48, user Thomas BN Jensen wrote:
Please see https://zenodo.org/records/... for the additional datafiles (metagenome assemblies, metagenome bins).
On 2024-07-04 17:58:15, user Dhiman Pal wrote:
This preprint has been published recently.<br /> Please use following link to the final published version:<br /> Lin, Y., Pal, D.S., Banerjee, P. et al. Ras suppression potentiates rear actomyosin contractility-driven cell polarization and migration. Nat Cell Biol (2024). https://doi.org/10.1038/s41...
On 2024-07-04 16:16:55, user Michael F Miles wrote:
This article is now published in Neuropsychopharmacology. There is a change in the order of the first 2 authors and the first name of Jeremy Nguyen (Angel Nguyen) in the final published version.
Mignogna KM, Tatom Z, Macleod L, Sergi Z, Nguyen A, Michenkova M, Smith ML, Miles MF. Identification of novel genetic loci and candidate genes for progressive ethanol consumption in diversity outbred mice. Neuropsychopharmacology. 2024 Jun 29. doi: 10.1038/s41386-024-01902-6. Epub ahead of print. PMID: 38951586.
On 2024-07-04 13:19:42, user Gyawali, Rajan wrote:
Hi,
Could you please link this preprint to the published journal in Briefings in Bioinformatics titled "CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net". The link to the published version is https://academic.oup.com/bi...
Thank you!
On 2024-07-03 16:05:42, user Jeffrey Duncan-Lowey wrote:
Congratulations on this interesting and important work establishing phage defense systems as a widespread and abundant source of gene cassettes of unknown function in functional mobile integrons.
Some work relevant to these findings -- a group has recently studied the type I CBASS system studied here (pic135AB) demonstrating that pic135B homologs, called Cap15 (interpro entries: PF18153/IPR041208), are cyclic di-nucleotide-activated beta-barrels that embed in and disrupt the bacterial membrane to cause cell death, validating the predicted role in membrane translocation (line 148). https://pubmed.ncbi.nlm.nih...
On 2024-07-03 15:10:50, user Peter Cattini wrote:
Our preprint manuscript on bioRxiv (doi: https://doi.org/10.1101/202... has now been published in final form in the Journal of Molecular Endocrinology under the title "Increased capacity to maintain glucose homeostasis in a transgenic mouse expressing human but not mouse growth hormone with developing high-fat diet-related insulin resistance, hepatic steatosis and adipose dysfunction". This paper can be found at: https://doi.org/10.1530/JME....
On 2024-07-03 13:55:44, user Jennifer Oyler-Yaniv wrote:
Hello, this paper has since been published in PNAS. Please see the accompanying link: https://www.pnas.org/doi/fu...
On 2024-07-03 07:48:24, user Niranjan Kumar wrote:
This pre-print has been published in Nucleic Acids Research (NAR). 2024 Feb 9;52(3):1450-1470. <br /> https://doi.org/10.1093/nar...
On 2024-07-02 23:49:22, user Brian wrote:
It has been reasonably well-established that if there is sufficient water, transpiration rate must not be restricted for the purpose of conserving water early season to gain benefits late-season. Even the current study shows "Early-season water use was positively correlated with above-ground biomass, challenging the assumption that early-season water conservation can be leveraged for late-season benefits". This study explores three treatments, all fully or partially irrigated. As authors' concluded that "We question the efficacy of LT traits, highlighting the physiological link between water use and carbon gain, and the potential opportunity costs of reduced early-season growth", I am unsure whether such treatments were the best choice. LT trait has been proved beneficial when soil moisture is scarce, and/or soil profile is deep enough to store sufficient water to be used late-season.
On 2024-07-02 15:48:40, user Donald R. Forsdyke wrote:
James Mallet's comments on an earlier version of this paper, noted the authors' claim that "This theory offers a level of parsimony and generality rarely seen in biology," and excused the absence of citation of his laboratory's study because it had come out "very recently, probably after you'd done most of this work."
However, the subjects of dosage compensation, Haldane's rule and speciation was covered together in the 1990s with some level of "parsimony and generality," which also included taking into account the immunological significance of collective gene functions (1-4). The growing evidence consistent with this viewpoint was more recently summarized in a textbook (5).
Perhaps, as part of their paper, the authors might more critically evaluate earlier work that so closely matches their own.
(1) Forsdyke, D. R. (1994) J. Theor. Biol. 167, 7-12 Relationship of X chromosome dosage compensation to intracellular self/not-self discrimination: a resolution of Muller's paradox?
(2) Forsdyke, D.R. (1995) J. Theoret. Biol. 172, 335-345. Fine-tuning of intracellular protein concentrations, a collective protein function involved in aneuploid lethality, sex determination and speciation?
(3) Forsdyke, D. R. (1996) J. Theoret. Biol. 178, 405-417. Different biological species "broadcast" their DNAs at different (G+C)% "wavelengths"
(4) Forsdyke, D. R. (2000) J. Theor. Biol. 204, 443-452. Haldane's rule: hybrid sterility affects the heterogametic sex first because sexual differentiation is on the path to species differentiation
(5) Forsdyke, D. R. (2016) Evolutionary Bioinformatics, 3rd edition. Springer, New York.
On 2024-07-02 11:48:52, user Hervé Acloque wrote:
The revised and peer-reviewed version of this paper is now available in the special issue of Genomics dedicated to FAANG:<br /> https://doi.org/10.1016/j.y...
On 2024-07-01 21:00:22, user Frank Koopmans wrote:
The manuscript has been published in Nature Communications and is available at https://doi.org/10.1038/s42...
On 2024-07-01 15:29:34, user Marcos Suárez wrote:
Now published in Global Ecology and Conservation doi: https://doi.org/10.1016/j.g...
On 2024-06-29 12:04:48, user moof wrote:
a little typo: "Stochastic Gradient Decent" (and not "Descent")
On 2024-06-28 16:26:14, user Yat Ho Chan wrote:
Hi everyone,
We are excited to share that our article has been peer-reviewed and published in Nature Communications! You can find the article at the link below.
On 2024-06-28 13:20:02, user Jo Wolfe wrote:
Interesting preprint! Regarding the intro, indeed the oldest direct fossil evidence is Jurassic...but we recently found that the crown group of Brachyura are probably Triassic<br /> https://academic.oup.com/sy...
Also, in our 2021 Bioessays paper, we did suggest the pleon folding in metamorphosis may be due to Abd-A repression, so it's cool that you found support for that result
On 2024-06-28 09:25:30, user Helle Jorgensen wrote:
Published after peer review<br /> Lambert, J., Oc, S., Worssam, M.D. et al. Network-based prioritization and validation of regulators of vascular smooth muscle cell proliferation in disease. Nat Cardiovasc Res 3, 714–733 (2024). https://doi.org/10.1038/s44...
On 2024-06-27 16:17:06, user Ivana Jerkovic wrote:
The scripts from this study can be found at:<br /> https://github.com/MarcoDiS...
On 2024-06-25 00:34:52, user Jiazheng Miao wrote:
This manuscript has been published in Scientific Reports. Please access the latest published version.
Miao, J., Chen, T., Misir, M. et al. Deep learning for predicting 16S rRNA gene copy number. Sci Rep 14, 14282 (2024). https://doi.org/10.1038/s41...
On 2024-06-24 14:14:02, user Flo Débarre wrote:
Following up on my previous comment about the pangolin datasets featured in Figure 2:
As mentioned previously, according to INSDC medatadata, SRR11119760 and SRR11119761 were made public again on June 16, 2021. However, because the data were pushed to the cloud on June 18 only, which is the day the preprint was submitted to bioRxiv and shared via email with officials, it had been suggested that the data release could still be linked to the preprint submission. Careful inspection of the exact times of the different events on June 18 shows that this suggestion does not hold.
The preprint PDF was indeed generated at 17:52 EST (cf. pdf metadata), which corresponds to the time of the last Github commit on the preprint's associated repository. Communication of the results to NCBI/NIH officials took place at 19:00 EST ( source ). SRR11119760 was however public on the cloud at 14:00 EST ( source ), i.e. before the preprint's final version was compiled.
On 2024-06-21 22:08:57, user MarkC wrote:
When will OMF or others consider a controlled clinical trial for these or other simple supplements?
On 2024-06-21 15:28:02, user Yan Cui wrote:
An extensively revised version of this paper has been published in Genome Medicine https://doi.org/10.1186/s13...
On 2024-06-21 10:40:11, user JamminOnTheOne wrote:
The materials and methods section regarding the production of mRNA is insufficient: "Subsequently, the mRNA and circular RNA (circRNA) were synthesized as described previously (10; 23)." The cited reference for mRNA production (Ref 10) gives two alternative types of protocols for mRNA production (post-transcriptional and co-transcriptional capping) and it is unclear which method was used. In the discussion section, it is also indicated that "GEMORNA-generated elements exhibit enhanced translation capacity with m1Ψ modification", however there is no mention in the text or in Ref 10 of the mRNAs being tested carrying this modification. It would be preferable to include the complete mRNA sequences and all of the reagents and procedures required to produce them.
On 2024-06-21 10:08:37, user Leonard Frach wrote:
Published version: https://doi.org/10.1038/s41...
On 2024-06-20 16:05:39, user Kishore Babu wrote:
SEC- MALLS experiment (Supplementary Fig1a) appears strange: (a) While Nictaba is eluting much later than BSA monomer (Mr = 66,000) the authors claim Nictaba to be a tetramer in solution (Mr = 76,000; subunit mol.wt. = 19,000 Da), so that they can claim a difference in their protein from that of PP2 gene family of proteins all of which have been shown in at least dozen other studies to exist as dimers only. (b) Only two molecular weight markers have been used as the standards for calibrating the column. (c) Nictaba a PP2 gene family protein is expected to be impeded on the gel media of their column as in a number of studies in the past on PP2 gene family of proteins they have been shown to get retarded on on gel media ranging from Sephadex, Acrylamide, Superdex etc.(Read, SM and Northcote, DH (1983) Planta 158, 119-127; Anantharam, V. et al. (1986) J. Biol.Chem. 261,14621-27 and Bobbili, KB et al. (2023) Structure 31,1-16).
The location, geometry of the binding site, the stereochemistry of the bound chitotriose and its interaction in Nictaba are identical to that reported for Cus17- the founding member of the PP2 gene family fold (Ref. Structure (2023) vol 31 pp1-16). Moreover ,the key residues tethering chitotriose to Nictaba are Thr14, Trp15, Tyr21, Val39, Ala40 and Trp151 are identical and correspond with Thr18, Trp19, Tyr25, Val46, Ser47, Trp48 and Trp141. Given this remarkably striking level of identities of the binding residues and the groups in the sugar one fails to see any novelty in Nictaba-sugar interactions as compared to the fold founding member of the family, namely Cus17. In this context, the authors should discuss their results in comparison with the structure of Cus17.
Even the backbone Cα atoms of the subunit of Nictaba overlap within 1.06A of the Cα atoms of Cus17 indicating that Nictaba fold is not new and is a faithful copy of Cus17. This should be stated in the Results and Discussion sections of the manuscript as appropriate.
The InterPro site that curates protein folds has created a separate folder for PP2 gene family of proteins since the appearance of Cus17 structure recognising it as a novel fold. It is therefore not surprising that Nictaba fold is curated and subsequent to the fold of Cus17.
Authors do not report on study on the stoichiometry of binding by any method including ITC but they claim Nictaba has a single binding site per subunit for the sugar perhaps based on crystal structure which is not a conclusive evidence for their assumption as there are numerous examples of differences for the number of binding sites seen in crystal structure or modeling vis-a-vis what are found in solution. Extensive ITC studies on several PP2 type lectins have given a wealth of information on the binding constants and thermodynamic factors associated with the binding of chitooligosaccharides to them as well as on the binding stoichiometry (see Nareddy, PK et al. (2017) Int. J. Biol. Macromol. 95, 910-919; Bobbili, KB et al. (2018) Int. J. Biol. Macromol. 108, 1227-1236; Bobbili, KB et al. (2019) Int. J. Biol. Macromol. 137, 774-782).
Nearly 40% of the 60 references cited in this manuscript are citations to the publications of the corresponding author! On the other hand many important, relevant publications of other scientists (mentioned above) are not cited.
On 2024-06-07 04:15:26, user Swamy wrote:
This study reports the crystal structure of Nictaba, the Nicotiana tabacum lectin which is specific for chitooligosaccharides and also binds N-linked glycans. The tertiary structure of this protein is essentially the same as that of Cus17, the 17 kDa phloem exudate lectin from Cucumis sativus (Bobbili et al. (2023) Structure 31, 1-16). Hence the term “archetypal” used in the title is misleading and hence it should be removed.
Nictaba is homologous to PP2 family proteins from Cucurbitaceae and other species. Some background information about PP2 proteins is relevant here. Two major proteins, phloem proteins 1 and 2 (short form PP1 and PP2) in the sieve elements of plants were studied since early 1970s by several groups (Sabnis and Hart (1973) Planta, 142, 97-101; Allen (1979) Biochem. J. 183, 133-137; Read & Northcote (1983) Planta 158, 119-127; Read & Northcote (1983) Eur. J. Biochem. 134, 561-567). That PP2 is a lectin was well established in these studies and its activity was clearly shown to be inhibited by oligomers of GlcNAc and by N-linked glycopeptides by Allen (Biochem. J. (1979) 183, 133-137). The PP2 proteins have been found in a wide variety of plant species, both monocots and dicots. In 1986 Anantharam et al. (J. Biol. Chem. 261, 14621-14627) clearly established that the chitobiosyl core of N-linked glycopeptides is crucial for binding of the phloem exudate lectin from Luffa acutangula (ridge gourd) as treatment of the N-linked glycans with endo-β-N-acetylglucosaminidase H completely abrogated their binding. While some of these early workers did not consistently use the designation PP2 protein while describing these lectins, over the last 30 years the term ‘PP2 proteins’ is commonly used by scientists working on these proteins. In fact, Gary Thompson’s group, who have extensively investigated the PP2 family genes referred to these proteins as a Superfamily (Dinant et al. (2003) Plant Physiol. 131, 115-131) and also referred to the Nicotiana tabacum lectin as a PP2-like agglutinin. Now Els Van Damme’s group, which has been working on plant lectins for over 3 decades refers to other PP2 family lectins that were investigated from much earlier as Nictaba-related lectins. This is a gross violation of scientific propriety and Nictaba should be referred to as a member of the PP2 Superfamily of proteins.
Since the high-resolution crystal structure of Cus17 is already known, and the structure of Nictaba is highly similar to it, the same should be mentioned in the Abstract, Introduction and Discussion sections in an appropriate manner. In particular, in Discussion section (para 2) the sentence “A similar crystal structure was reported recently for the phloem lectin from Cucumis sativus (Cus17), a member of the Nictaba-related lectin family” should be modified to indicate that “the first crystal structure of the PP2 fold to which Nictaba belongs”. In fact, the narrative of referring to all PP2 family lectins as Nictaba-related lectins at various places in the manuscript should be changed and Nictaba should be referred to as PP2 family protein.
In the light of the fact that the structural fold of Nictaba is quite similar to that of Cus17, it would be appropriate to give a detailed comparison of the Nictaba structure with Cus17 structure. <br /> Since the glycan array investigations on Nictaba have been reported earlier by the same group (Lannoo et al. (2006) FEBS Lett. 580, 6329-6337; Schouppe et al. (2010) Glycoconj. J. 27, 613–623) the discussion on this aspect should be condensed. Importantly, the glycan array data is at best semi-quantitative and the authors should have used a method like ITC (Isothermal Titration Calorimetry) which gives reliable and quantitative information on not only the association (binding) constants, but also important additional information on the carbohydrate binding by the lectin, viz., stoichiometry, enthalpy and entropy associated with the binding.
Although extensive studies on the binding of chitooligosaccharides to phloem exudate lectins have been reported, especially employing ITC, the authors cited just one paper published in 2011 (Narahari et al. (2011) J. Phys. Chem. B. 115, 4110–4117). Since then several ITC studies on chitooligosaccharide binding to PP2 family lectins have been reported (reviewed by Swamy et al. (2022) Phytochemistry, Article No. 113251.) This information should be suitably cited. Also, the study of Bobbili et al. (2023) on Cus17 also reports extensive ITC studies on the binding of various chitooligosaccharides and the N-linked glycan, Man3GlcNAc2 to the lectin. It is important to cite this work while discussing the carbohydrate binding characteristics of Nictaba.
On 2024-06-19 16:20:06, user John wrote:
Where are the Supplementary Tables 1-7?
On 2024-06-19 07:46:07, user Guillermo del Angel wrote:
I was trying to see the actual list of variants referenced in Table S1 but there doesn't seem to be any link to view and download these?
On 2024-06-19 00:31:10, user Rajan K C wrote:
This article has been published. Please update the article.
K. C. R, Patel NR, Shenoy A, Scallan JP, Chiang MY, et al. (2024) Zmiz1 is a novel regulator of lymphatic endothelial cell gene expression and function. PLOS ONE 19(5): e0302926. https://doi.org/10.1371/jou...
Thank you!
On 2024-06-18 15:19:14, user Todd Gaines wrote:
This preprint has now been published in Genome Biology:<br /> https://link.springer.com/a...
On 2024-06-17 06:43:17, user Sebastian Gregoricchio wrote:
Now published on Nucleic Acids Research:<br /> https://doi.org/10.1093/nar/gkad267
On 2024-06-17 06:37:44, user Sebastian Gregoricchio wrote:
Now published on Genome Research:<br /> https://www.genome.org/cgi/doi/10.1101/gr.278680.123
On 2024-06-17 03:46:27, user mittimithai wrote:
I thought this sentence was odd:
"Excluding Physics, the highest presence of EP authors<br /> 300 after adjusting for the total number of authors in each country is seen in Arab countries<br /> 301 (Saudi Arabia, Iraq, United Arab Emirates, Pakistan) and in Malaysia and Philippines."
Pakistan is not an Arab country.
On 2024-06-16 18:39:42, user Ashley Winn wrote:
Nice to see lymphangiogenesis getting some attention in regeneration. Thought this paper would be of of interest:
Simkin, Jennifer, Ajoy Aloysius, Mike Adam, Fatemeh Safaee, Renée R. Donahue, Shishir Biswas, Zohaib Lakhani et al. "Tissue-resident macrophages specifically express Lactotransferrin and Vegfc during ear pinna regeneration in spiny mice." Developmental Cell (2024).
On 2024-06-16 07:52:20, user James wrote:
The tidyverse isn't exactly good and promotes truly awful coding practice. Why continue expanding it? It's also hard to understand what this adds besides bloat to these analyses.
On 2024-06-15 11:45:28, user Jiashun wrote:
Great works！Cogratulations, Dr Cheng. While I found there may be a small mistake. "Of the sixteen F1 double heterozygotes we derived from the cross between gpgp and the TILLING mutant heterozygotes, half had yellow pods, and all of these yellow podded F1s carried the ChlGW121* null allele (Fig. 3i-j)". I checked the figures and found 10 yellow pods rather than the half of sixteen (8). Please let me know if I misunderstood.
On 2024-06-15 08:59:37, user Marc RobinsonRechavi wrote:
In the manuscript you write:
"Supplementary information including the Python code used for the simulations is available at https://10.5281/zenodo.11562472"
but this link does not work and I did not find this data in Zenodo. Can you please provide the correct link?
On 2024-06-15 06:00:47, user Yongheng Wang wrote:
Pease check the demo here: https://youtu.be/3-RSjPakGH...
On 2024-06-14 16:27:04, user Georg wrote:
It's great work. Could you please ask ftdna or yfull or yseq to define terminal SNPs of 4 unidentified I1 samples
On 2024-06-14 09:00:46, user Markus Proft wrote:
This preprint has been published in Frontiers of Microbiology: <br /> 2023 Apr 3:14:1152249. doi: 10.3389/fmicb.2023.1152249. eCollection 2023.
On 2024-06-11 22:23:41, user Clashing_titans wrote:
Awesome database!
On 2024-06-11 13:08:39, user wonderfulponderfulponds wrote:
I feel the research design and some conclusion drawn is premature due to an overlook of the following aspects:
Lacking data on Fatty acids analysis of some representative wild capelin testis, semen or centrifuged spermatozoa: The regeneration of sperm and endurance of males largely relate to absence/ presence of enough "raw materials" (i.e., high quality lipids, phospholipids and long-chain polyunsaturated fatty acids to be precise). The original hypothesis tested would be dubious, irrespective of any male sub-cohorts or phenotypes, if the above basic requirement is missing.
Lacking data on a gastrosomatic index (gut/ visceral weight divided by body weight and expressed in %) or gut content analysis: if some capelins are not feeding in between their spawning, it is highly unlikely they would replenish depleted energy reserves, and bioenergetically channel 50% of such intake energy in food to invest in gamete/ milt production. As such the original experimental design does not take into account a careful bioenergetics point of view either. Some whole-body carcass analysis of some representative capelin would have been beneficial as an alternative.
I urge the authors to consider these in future work and good luck with the revisions.
On 2024-06-10 13:18:54, user Benoit Laventie wrote:
Final paper available in Nature Microbiology: https://doi.org/10.1038/s41...
On 2024-06-09 05:52:19, user Barend de Graaf wrote:
I found a level of confusion about the ‘SPH protein family’, and the working mechanism of the SI system in Papaver specifically, in this very interesting MS …..
In the introduction, authors mention:
“In poppy, when two members of the SPH protein family (PrsS1 and PrpS1) are cognate, they confer sporophytic self-incompatibility (Foote et al., 1994; Wheeler et al., 2009; de Graaf et al., 2012)”
This is not correct, poppy does not express ‘sporophytic SI’ but ‘gametophytic SI’.
Furthermore, authors also state ‘when two members of the SPH protein family (PrsS1 and PrpS1) are cognate’.
This is not correct either, PrpS proteins are not part of the SPH protein family, instead these are classified as the poppy SI membrane ‘receptor’ proteins that are essential for SI signalling in pollen, male component of SI system in poppy.
On 2024-06-08 16:21:26, user Reviewer 6 wrote:
I have read Gainey et al, the response by Coleen Murphy in the comments as well as the preprint here. I previously made a detailed assessment of these which are found in the comments of Gainey et al., bioRxiv 2024.
In my opinion the debate to whether the effect can be triggered under highly specific lab conditions is not particularly relevant. But I think the point is that if the effect is so sensitive to such artificial conditions (or one sRNA that is only expressed under even more specific conditions), then how physiologically important can it be in nature? CM's group points to their 2024 (Sengupta et al, plos genet) paper testing various bacteria C. elegans may be exposed to the wild. However, it seems that worms naively avoid OP50 (i.e. ‘prefer’ test bacteria) in essentially every comparison made by CM. This is contrary to reports by other labs (PMID: 38228683, PMID: 38228683) and potentially a more serious concern with the assay.
Furthermore, in the 2024 Sengupta paper, it seems that both pathogenic and non-pathogenic bacteria can trigger avoidance (or not), which is odd and makes me think the effect is rather random. If this is really something so specific or adaptive that prevents worms from infection or confers fitness - I believe CM refers to the effect as the worms "reading" bacterial sRNAs in their Nature papers (is there any evidence that the recognition sequence on maco-1 mRNA co-evolves with bacterial preference in wild nematode isolates?) - then wouldn't the worms have evolved at least some preference for avoiding pathogenic vs non pathogenic bacteria from their habitat?
To me it just seems that random bacterial sRNAs that may be complementary to some worm genes that regulate behavior (I mean, you would expect to see some matches among a panel of total bacterial small RNAs from many species worms are exposed to versus total worm mRNAs...) are being silenced through an RNAi like mechanism... It's not news that RNAi can be inherited, which was described nearly two decades ago and is a well understood process.
Perhaps Hunter et al should visit CM's lab to learn the technique, but given how meaningful the assay/readout is in my view (and how already overstudied/saturated sRNA based inheritance is), perhaps it is not the best investment of time and effort.
On 2024-06-07 14:13:23, user Sonja Grath wrote:
Please link with: https://doi.org/10.1534/g3....
On 2024-06-07 13:43:51, user marodon wrote:
Great job in line with works from other teams. May I suggest that the authors include two publications related to the subject in their discussion? <br /> Midavaine É, Moraes BC, Benitez J, Rodriguez SR, Braz JM, Kochhar NP, Eckalbar WL, Domingos AI, Pintar JE, Basbaum AI, Kashem SW. 2024. Regulatory T cell-derived enkephalin imparts pregnancy-induced analgesia. doi:10.1101/2024.05.11.593442<br /> Aubert N, Purcarea M, Fornier M, Cagnet L, Naturel M, Casrouge A, Dietrich G, Dieu-Nosjean M-C, Marodon G. 2024. Enkephalin-mediated modulation of basal somatic sensitivity by regulatory T cells in mice. eLife 13. doi:10.7554/eLife.91359.1<br /> Some other omments:<br /> -p3 Treg cells restrain exacerbated activation of peripheral neurons during early during inflammatory challenge<br /> -p6 CarboxypeptidaseE (Cpe) has been shown to process proenkephalin (Hook VYH, Eiden LE, Brownstein MJ. 1982. A carboxypeptidase processing enzyme for enkephalin precursors. Nature 295:341–342. doi:10.1038/295341a0)<br /> -Ref 50 is incomplete
On 2024-06-07 12:51:36, user Duchenne François wrote:
This work has now been peer-reviewed and published here:<br /> https://doi.org/10.1098/rsp...
On 2024-06-07 03:54:29, user Mohamed Hoballa wrote:
This preprint has been reviewed and published under the DOI: https://doi.org/10.30491/ja...
On 2024-06-06 17:27:56, user Prof. T. K. Wood wrote:
The first TA system found to inhibit phage was Hok/Sok in 1996 (that makes it seminal). So 26 years before retrons (your ref 47) and 25 years before ToxIN (your ref 48), Hok/Sok set the precedent of stopping phage by interpreting a phage process (transcription shutoff), rather than reacting to a specific phage protein. Curious as to why this discovery does not merit citation.
On 2024-06-06 12:01:12, user Elli wrote:
I am unable to see the suplementary tables the preprint refers to, where can I find these?
On 2024-06-06 12:00:30, user Elli wrote:
I am unable to see the supplementary tables the preprint refers to, where can I find these?
On 2024-06-06 09:51:33, user Asaf Levy wrote:
The paper is now published following peer review:<br /> https://academic.oup.com/is...<br /> Please cite this one.
Asaf Levy
On 2024-06-06 05:37:37, user Brian Junglen Jr wrote:
Can you please advise on the appropriate sample size required for a research study to conclusively determine the correlation between the spider gene and its impact on the snake's equilibrium?
On 2024-06-05 13:08:01, user Simon wrote:
This is an interesting analysis. I have two short comments/suggestions.
First, I wonder why authors made the more extreme Gly mutations for the binding site removal instead of the more conservative Ala mutations. Because of the special role of Glycine the quality of the input MSA is probably a lot worse for Gly instead of Ala mutations.
Second, I think authors should also report RMSD/pLDDT/PAE for the predicted structures itself and not just the ligand. Since AF3 performs the combined objective of structure prediction and docking mutation of the input has consequences for both objectives. It might be that it performs worse for docking because the overall quality of the structure prediction is reduced.
We've looked into the related problem of metal-protein interaction and there AF3 does a bit better to capture realistic physicochemical effects: https://x.com/simonduerr/st...
On 2024-06-05 07:04:18, user Si Hoffmann wrote:
The revised version of this article is published in Autophagy Reports.<br /> "Highlighting the hidden: monitoring the avidity-driven association of a fluorescent GABARAP tandem with microtubules in living cells"<br /> https://doi.org/10.1080/276...
On 2024-06-04 17:49:18, user phillip kyriakakis wrote:
Cool paper!
A few thoughts:
1) It would be great to see how this compares to the PhyB-PIF version<br /> 2) Blue light should activate PhyB/PhyA, it would be great to see different blue light doses to see how sensitive it is to blue light, not if it is sensitive to blue light. (See "Multi-chromatic control of mammalian gene expression and signaling" and "Multichromatic Control of Signaling Pathways in Mammalian Cells")<br /> 3) I am not sure what biological replicates means. Where three independent experiments done, or just three biological replicates, one experiment? If a single experiment, this should be made explicit and perhaps written as N = 1.<br /> 4) PhyA could be written as PhyA-NT instead of delta. Delta implies it is a knock out or something. Peter Quail used the "NT" notation and that has been used a lot since, so it would be easy for others to follow. <br /> 5) What are the effects of far-red light, perhaps with and without blue light? (See "Multi-chromatic control of mammalian gene expression and signaling" and "Multichromatic Control of Signaling Pathways in Mammalian Cells")<br /> 6) Would be nice to see blue and red systems multiplexed. Perhaps using DRE as in "Efficient photoactivatable Dre recombinase for cell type-specific spatiotemporal control of genome engineering in the mouse"
I am not suggesting these experiments or changes are needed to be published, but could improve the usefulness.
On 2024-06-04 07:43:30, user Wolfram Klapper wrote:
Excellent work! Congratulations! I wonder if you have checked the interdependence of HLA-I and EBV association and the effect on the microenvironment. Our own data show that TARC is a major driver and HLA-I is also an independent factor that associated with microenvironment features (see: https://onlinelibrary.wiley...<br /> Regards Wolfram
On 2024-06-04 02:45:41, user Adrian wrote:
This paper was already published in Nucleic Acid Research: https://academic.oup.com/na...
On 2024-06-03 17:49:15, user Joseph Wade wrote:
The following is a review compiled by graduate students participating in the Infectious Disease Journal Club, Department of Biomedical Sciences, University at Albany, SUNY:
This paper addresses differences in bacterial, archaeal, and fungal microbiomes within certain body sites as a function of pregnancy status. Prior to this work, changes in the maternal bacterial, archaeal, and fungal microbiomes in body sites other than the vaginal cavity and gut were poorly understood. The authors characterize the oral, urinary, stool, and vaginal microbiomes, and the urinary metabolome of non-pregnant, as well as pre- and postpartum women. They conclude that the microbiome of the oral cavity quickly rebounds after birth, whereas the vaginal microbiome takes longer to return to its pre-pregnancy state. The authors also conclude that the archaeal content of the oral microbiome correlates strongly with pregnancy status. We feel that most of the conclusions put forth in the paper are well supported. However, we have concerns about conclusions involving archaeal microbiome differences, and we have suggestions for changes in data presentation that may improve clarity.
Major Comments
Minor Comments
Suggestion for a Future Experiment
A further experiment may include collection of stool samples postpartum as well to look at multiple time-points postpartum. It would be particularly interesting to include later postpartum samples to observe how long it takes to return to the prepregnancy microbiome in each body site.
On 2024-06-03 17:29:27, user Joseph Wade wrote:
The following is a review compiled by graduate students participating in the Infectious Disease Journal Club, Department of Biomedical Sciences, University at Albany, SUNY:
This manuscript looks at the role of the TofI/R and QsmR regulators on virulence in Burkholderia glumae. Previous work suggested that TofI/R was the dominant regulator over QsmR in B. glumae quorum sensing. Here, the authors identify independent roles of TofI/R, distinct from QsmR, and suggest a regulatory effect of QsmR on TofI/R. Moreover, the authors conclude that the QsmR variant T50K substantially reduces B. glumae virulence. The conclusions regarding the hierarchy of TofI/R and QsmR are generally well-supported across multiple independent assays, although there are some inconsistencies between the RT-qPCR and the RNA-seq data. The conclusions regarding the importance of the genotype of qsmR rely heavily on control data that are not shown; in the absence of these data, it is impossible to draw a strong conclusion on the contribution of qsmR to virulence.
Major Comments
Minor Comments
Suggestion for a Future Experiment
Are strain phenotypes specific to the species of rice being used in experiments, i.e., is the hypervirulent strain more of a generalist whereas the “wild-type” strain is a specific pathogen for this rice species?
On 2024-06-03 08:51:10, user Texugo wrote:
Can I have access to the raw data ?
On 2024-06-03 08:07:01, user Marjorie Guichard wrote:
A peer reviewed version is now available in Scientific Reports: https://www.nature.com/arti...
On 2024-05-31 20:17:09, user Guest wrote:
If all counts are assumed to be true positives and FDR = FP/(FP+TP), then isn't FDR = 0? I am not a biostats person, so just confused.
On 2024-05-31 18:55:39, user Julio Neto wrote:
Could you provide additional references that support the adverse outcomes of metaplasia in endothelial cells and the transformation of these cells to have connective and contractile properties? Also, I'd like to know if the relaxation of endothelium-dependent from isolated blood vessels is impaired in hypertensive animals. What are the basal blood pressure values of these awake animals? Are SOX-2 and KLF-4 transcription factors related to pluripotent-induced stem cells so, among these, how play a major role in determining endothelial drive instead of other cell types? (cardiac, for example). Preliminary data presented here could be from the transcriptome of single-cell RNA, which led to the sequence of the study. Lastly, I suggest reducing the range of graphs in Figure 6 (e.g., U46619 from 30 pM to 10 µM) to generate the best fit Hill sigmoid with more reliable efficacy and potency values. Congratulations and good luck!
On 2024-05-31 09:07:32, user Klaus Harms wrote:
Article now published in Mol Microbiol: https://doi.org/10.1111/mmi...
On 2024-05-30 23:46:19, user Clashing_titans wrote:
Cogent, clear, well-written and an interesting piece to the Legionella effector story:<br /> Chadha et al should be proud of this work!
On 2024-05-30 19:17:48, user Sharath Tippur Narayana Iyenga wrote:
Hi,<br /> Interesting work for rapid separation and detection of bacteria from blood. However, the 2nd step of ''Selective cell lysis'' is used from the work which is already published and has a patent approval in progress. This original work has not been cited in this pre-print. This has to be added in the original paper before publishing. It is highly important to properly cite the original paper if their method is utilized in another work. The original paper citation details is below:
Narayana Iyengar S, Dietvorst J, Ferrer-Vilanova A, Guirado G, Muñoz-Berbel X, Russom A. Toward Rapid Detection of Viable Bacteria in Whole Blood for Early Sepsis Diagnostics and Susceptibility Testing. ACS Sens. 2021 Sep 24;6(9):3357-3366. doi: 10.1021/acssensors.1c01219. Epub 2021 Aug 19. PMID: 34410700; PMCID: PMC8477386.
On 2024-05-30 17:30:49, user Pawan wrote:
Where is the supplementary material of this paper?
On 2024-05-30 16:57:13, user sanalkumar rajendran wrote:
Dear Authors, this quite interesting and great effort to bring published HiChip work in one single platform. We, Riggi lab has published couple of articles in sarcoma models which includes HiChIP profiling from relevant cell lines, mesenchymal stem cells and specific oncogene knock-down condition. It would be nice to have those datasets also included in the Loop Catalogue. <br /> 1. Nature Communications volume 13, Article number: 2267 (2022). https://www.nature.com/arti...<br /> 2. SCIENCE ADVANCES, 31 Mar 2023, Vol 9, Issue 13, DOI: 10.1126/sciadv.abo3789<br /> Thanks
On 2024-05-30 16:51:25, user Djo Hasan wrote:
Dear authors of the article, entitled: “Molecular Mimicry as a Mechanism of Viral Immune Evasion and Autoimmunity” (https://doi.org/10.1101/202....
Thank you for sharing this very interesting article.
In this article, you stated that “Molecular mimicry explains portions of the multiple sclerosis auto-antibodyome”. I suggest that you should take the findings of Martins, et al. (2023) [1] into consideration. These authors pointed out that although the amount of antigenic sharing between hosts and both pathogenic and non-pathogenic parasites and bacteria is massive, molecular mimicry by itself is not a sufficient factor to disrupt intact self-tolerance mechanisms.
In this context, in my recent paper (https://www.aimspress.com/a... [2], I provided the missing link between molecular mimicry and the activation of autoimmune responses. I figured out that activation of the purinergic P2X7R expressed on regulatory T cells is potentially required for molecular mimicry to activate autoimmune responses. This occurs only after repeated or high-dose microbe infection and not after a single low-dose infection. I also presented a novel model of immune responses in mammals to foreign antigens, self-antigens and antigens with molecular mimicry.
I hope that these comments will help to improve the quality of your paper.
Kind regards,<br /> Djo Hasan
References
On 2024-05-30 10:18:07, user Prof. T. K. Wood wrote:
Again, growth on methane was achieved by reversing methanogenesis in 2016 by obtaining active Mcr for the first time in a pure culture (ref 20), so the Introduction remains misleading (line 48, 'in their natural state') and line 323 is misleading:
"...ANME-1 MCR may allow Methanosarcina to perform AOM (20 )." We used multiple lines of evidence to demonstrate growth in 2016 and subsequent papers converted methane to lactate and even created a microbial fuel cell using methane, hence both uncited works again confirm active Mcr so it is not appropriate to write "may allow" growth. Should the field refer to all of your results as "may be' valid?
Moreover, in effect, the recombinant strain we produced was the way Nature created ANME, according to your work here (by altering Mcr) so our work is relevant to your report here as validation of this study, and the Introduction in this second version is still misleading.
On 2024-05-26 21:40:46, user Prof. T. K. Wood wrote:
Line 47: this statement is false: "Though there is not yet strong evidence that backwards carbon flow can be coupled to growth in either methanogens or ANME,.." as ref 20 was seminal in reversing methanogenesis in a methanogen by cloning Mcr and showing growth for the first time on methane in the engineered methanogen.
On 2024-05-30 09:18:41, user Sam Calis wrote:
Is there list of the peptides identified with the subtiligase biotin-assay availlable somewhere?
On 2024-05-30 05:42:05, user cong wrote:
We are trying to install Nanomotif in our server. We tried all of the install methods, and the major install looks good. However, when we tried nanomotif MTase-linker install, the following error was shown. It seems that module 'snakemake' had some issues. We then checked the 'snakemake' install and found we had snakemake==8.12.0. Is there any method to solve the problem for MTase-linker install?
Thank you very much!
$ nanomotif MTase-linker install<br /> /home/miniconda3/envs/nanomotif/lib/python3.12/site-packages/nanomotif/mtase_linker/setup.smk<br /> Traceback (most recent call last):<br /> File "/home/miniconda3/envs/nanomotif/bin/nanomotif", line 10, in <module><br /> sys.exit(main())<br /> ^^^^^^<br /> File "/home/miniconda3/envs/nanomotif/lib/python3.12/site-packages/nanomotif/main.py", line 513, in main<br /> mtase_linker(args)<br /> File "/home/miniconda3/envs/nanomotif/lib/python3.12/site-packages/nanomotif/main.py", line 475, in mtase_linker<br /> snakemake_create_environments(args)<br /> File "/home/miniconda3/envs/nanomotif/lib/python3.12/site-packages/nanomotif/mtase_linker/dependencies.py", line 24, in snakemake_create_environments<br /> status = snakemake.snakemake(snakefile,<br /> ^^^^^^^^^^^^^^^^^^^<br /> AttributeError: module 'snakemake' has no attribute 'snakemake'
On 2024-05-30 05:18:38, user Severin Lechner wrote:
Thanks for looking into the downstream effects of HDAC inhibitors in various cells and on several levels.
It would be interesting to compare the results to recently published data on proteomics and phosphoproteomics response to a broad panel of HDAC inhibitors, such as: <br /> - Decrypting lysine deacetylase inhibitor action and protein modifications by dose-resolved proteomics, Cell Rep. 2024<br /> - Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics, Nat Biotech. 2024
Further, the Abexinostat selectivity data in the main text lacks a reference. The statement also does not fully agree with the recently updated target selectivity landscape of HDAC inhibitors, where Abexinostat is shown to bind HDAC10 and the off-target MBLAC2 with substantially higher affinity than HDAC1: <br /> - Target deconvolution of HDAC pharmacopoeia reveals MBLAC2 as common off-target, 2022. Nat Chem Bio
On 2024-05-29 22:16:44, user kdkorthauer wrote:
Just curious whether your analyses adjusted for variability in blood cell type composition? Thanks!
On 2024-05-29 13:09:14, user Alex Crits-Christoph wrote:
KrakenUniq reports the coverage ("breadth of coverage", the percentage of the reference genome that is covered by sequencing reads) of each reference genome that may be present in the sample. Breadth information is a key way of determining true positive from false positive hits in metagenomics: almost all false positives are characterized by low breadth of coverage, as in these cases, reads only mapped to a fraction of the reference.
The authors should report coverage from KrakenUniq for their analyses; only counts are provided in the supplementary, but coverage values would be more informative for determining whether a microbial genome is present in a sample. For a brief discussion of this see:
https://instrain.readthedoc...
Further, the authors could then consider employing a minimum breadth cutoff to further separate true from false positives.
Finally the authors could also consider comparing to approaches that incorporate breadth automatically, such as:
https://github.com/bluenote...<br /> https://sourmash.readthedoc...<br /> https://instrain.readthedoc...
On 2024-05-29 08:20:26, user Alexey Belogurov Jr. wrote:
Manuscript has been published Chernov AS, Rodionov MV, Kazakov VA, Ivanova KA, Meshcheryakov FA, Kudriaeva AA, Gabibov AG, Telegin GB, Belogurov AA Jr. CCR5/CXCR3 antagonist TAK-779 prevents diffuse alveolar damage of the lung in the murine model of the acute respiratory distress syndrome. Front Pharmacol. 2024 Feb 21;15:1351655. doi: 10.3389/fphar.2024.1351655. PMID: 38449806; PMCID: PMC10915062.
On 2024-05-29 07:40:40, user PengLong li wrote:
Dear professor Bahlburg,
Hello. I'm very sorry to bother you in your busy schedule.
My name is Penglong Li, and I am a master's student at Dalian Ocean University in China. I have been focusing on the analysis of Antarctic krill resources using echogram images, a topic that greatly interests me. I recently came across your paper titled "An open and lightweight method to analyze the vertical distribution of pelagic organisms using echogram screenshots," which has been immensely inspiring for my research.
I am currently attempting to replicate the methodology presented in your paper. However, I have encountered some difficulties, particularly with accessing the source code. The link provided in your paper (https://sandbox.zenodo.org/... appears to be inactive.
I would be extremely grateful if you could share the echogram color matching program and other source code mentioned in the paper. Having access to these resources would greatly assist me in my research and help me better understand and apply your methods.
Regardless of your decision, I wish you the very best. Thank you for your time and consideration. Your help would be immensely appreciated, and I am deeply grateful for any assistance you can provide.
Wishing you good health and continued success in your work.
Best regards,<br /> li.pen.long0506@gmail.com<br /> Penglong Li<br /> Dalian Ocean University
On 2024-05-29 06:50:45, user theNiessingLabs wrote:
The authors show in Figures 3 - 4 and in Table 2 in silico-docking studies with an alphafold2-model of PURA as template. In this model, PUR-repeat III is shown as a monomer with an awkward-looking fold. The authors use this docking to suggest a direct interaction between PURA and GLUT1. <br /> Unfortunately, the authors seem to ignore that PUR repeats do not exist as single, monomeric repeats but require dimerization. For repeat III of Drosophila PURA, a high-resolution structure of its homodimeric domain has been reported already in 2016:<br /> https://elifesciences.org/a...<br /> PDB-ID: 5FGO<br /> For repeat III of the human PURA (as used in this study), more recently the homodimeric high-resolution domain structure has also been published:<br /> https://elifesciences.org/a...<br /> PDB-ID: 8CHW<br /> Considering these experimental structures, Figures 3-4 and Table 2 refer to unphysiological folds. As a result, conclusions drawn from these figures have to be considered as entirely wrong.
On 2024-05-28 03:20:10, user Samuel W. James wrote:
As a specialist in earthworm phylogenetics and taxonomy, I would really like to see an expanded taxon set within earthworms, including several cases where aquatic to terrestrial (and back) habitat shifts have taken place. There are even some where earthworms have colonized marine shore habitats. My colleague Christer Erseus who works on non-earthworm clitellates could also make some intelligent suggestions for future work on lineages that have transitioned from fresh to marine water environments or vice versa, as well as aquatic / terrestrial shifts. <br /> Nevertheless, terrestrial soils are basically aquatic environments, in that earthworms and Enchytraeidae ( and the soil-dwelling polychaete Hrabiella (I think) depend on free water and water films on soil particles and their body surfaces.
On 2024-05-26 19:15:45, user Peter-Bram 't Hoen wrote:
Dear authors, <br /> Interesting paper. It is good to see that this paper largely confirms our findings published in 2006: https://doi.org/10.1016/j.n...<br /> Peter-Bram 't Hoen
On 2024-05-25 17:46:48, user David Hornby wrote:
This manuscript is now published at Hurd, P.J. Al-Swailem, A.M. Bin Dukhyil, A.A.A. Sheikh, Q.I. Al-Ghanim, A.A. Alfageih, L. Matin, M. Yueh Ting, L.u. Abdalgelel, A. Florence, J. Mohammed Al- Shemirti, Al Harbi, S. Brown, P.E. Hornby, D.P. Systemic Mutational Rescue in Escherichia Coli Elicited by a Valency Dependent, High Affinity Protein DNA Interaction. Journal of Bioinformatics and Systems Biology. 6 (2023): 97-109.
On 2024-05-25 13:05:40, user Leando Cruz wrote:
Very intersting work. I would like to know the opinion of the author on the paper "Modulation of alpha-synuclein phase separation by biomolecules", since the authors were the first to propose the formation of biomolecular condensates of the protein mediated by spermine
On 2024-05-24 11:13:50, user Marcelo R. S. Briones wrote:
This paper was peer reviewed and published (May 27, 2024) in the journal "Viruses" https://www.mdpi.com/1999-4...
On 2024-05-23 02:12:03, user Adrian wrote:
This article was already peer-reviewed and published in NAR https://academic.oup.com/na...
On 2024-05-22 17:31:24, user lf wrote:
A version of this paper is now published in the journal Epigenetic at the following link https://www.tandfonline.com...
On 2024-05-22 15:01:07, user Donald R. Forsdyke wrote:
The authors cite a paper in PLOS Biology that was first posted as a preprint paper here in bioRxiv see Johri et al. 2021. The four comments I added to the Johri preprint paper have now been updated, noting the intriguing new k-mer analysis of Roberts and Josephs (2024).
On 2024-05-22 14:43:59, user Donald R. Forsdyke wrote:
The SSRN preprint mentioned previously (see four comments) has now (2024) been formally published under the same ("three historians") title in Theory in Biosciences (143(1): 1-26). One of the three (William J. Provine) having died in 2015, I now sadly report the passing of Mark Boyer Adams (May 9th, 2024). The paper included the work of the remaining historian (myself). This built on the DNA studies of Erwin Chargaff and my k-mer and nucleic structure analyses.
The formally published final version of Johri et al. is available in PLOS Biology. Their admonition to "carefully define ... underlying uncertainties" has resurfaced regarding "Lewontin's paradox." Citing this, Roberts and Josephs have posted a new bioRxiv preprint (May 19th 2024) entitled: "Previously unmeasured genetic diversity explains part of Lewontin’s paradox in a k-mer-based meta-analysis of 112 plant species" (see: Roberts and Josephs 2024).
On 2024-05-22 09:19:21, user Mouille wrote:
If you download it.... and read it...please comment it ! We really need your feedback ! Thank you. Grégory et al. !
On 2024-05-22 06:46:04, user Marc RobinsonRechavi wrote:
In the methods, you write<br /> "HDF5 files with the approximations for each organism are available on FigShare at https://figshare.com/accoun...."
But the figshare link doesn't work :(
On 2024-05-21 11:13:03, user dirkfaltin wrote:
Interesting paper. However, I'm afraid you are mixing up a lot of concepts that should be kept separate. Ethnonyms like Goths, Langobards and Frisians are political terms. They are not biological categories. Terms like "Wielbark Goths" (847) are entirely nonsensical. We simply don't know how the people of the Wielbark culture identified or were identified by others. Most likely they had never heard the name Goths and were not called so by outsiders. The name Goths appears only later in an entirely different region. We also don't know of the earlier "Gutans" had anything to do with the Wielbark-people or the later historical Goths. If you investigate the remains of a person buried in a cemetary that may have belonged to the Langobards, you still don't know how the individual identified whose DNA you extracted. Historians have been very careful to workout the problems that arise from mixing up ethnic/political terminology with archaeology. This paper revives the old mistakes by mixing up ethnic/political terms with archaeological material culture and biology.
On 2024-05-20 00:22:12, user Alexis Rohou wrote:
I was asked to review a version of the manuscript for a journal. Below are my comments to the authors.
In this manuscript Shub and colleagues present MIC, a new tool for the analysis of three-dimensional macromolecular structures obtained using x-ray diffraction or cryogenic electron microscopy (cryoEM). Given an atomic model featuring water molecules and/or ions, and the corresponding 3D map data, MIC automatically labels each putative water and/or ion location with a guess water or ion identity.
Thanks to improvements in cryoEM instrumentation and data analysis, 3D maps can now frequently be obtained at resolutions better than 2.7Å, so that the problem of correctly labeling small map features as either water or ion presents itself more frequently to practictioners, myself included. In that context the availability of a well-characterized, open-source and highly performant classifier of ion/water density features is timely and most welcome.
I found the manuscript to be well written, the description of the method and how it was tested clear (though as a non-expert I had trouble following the description of the network architecture and of the feature attribution methodology), and the results convincing. Most questions that arose as I was reading early parts of the manuscript (e.g. regarding the influence of slight errors in modeling of protein atoms on the labeling of ions/water) were answered in later parts. I only have minor feedback & suggestions for the authors and otherwise am supportive of publication.
Here's the feedback I have:<br /> - lines 47-48: Perhaps... but I wonder if the authors are aware of Ravera et al (Nature, 2022)... and there may be a few other reports I'm unaware of myself... I wonder whether a radial average profile could be used as part of the fingerprint in future versions of MIC to improve the quality of the labeling by the network. Perhaps the authors could comment (in the discussion?) about whether incorporating experimental map features could be possible in future work?<br /> - lines 189-190: "this simple metric showed statistically significant separation between<br /> test set predictions that agreed and disagreed with the deposited PBD label": I found this sentence confusing at first, and still do to an extent. To me the syntax did not convey the meaning of the figure unambiguously. To spell it out: <br /> -- My understanding on first reading was: when a site lands near a boundary (i.e. the model is uncertain), the model's prediction tends to disagree with the deposited PDB label. Doesn't that mean that if the user gets a result that is assigned low confidence, they should actually assume that the identity assigned by MIC is wrong? That would seem to be problematic... wouldn't it?<br /> -- Having reviewed Fig 2e, I now think the text was a bit confusing. My interpretation of the figure: at low confidence scores, say around 0.5, it's only slighlty more likely than not that there's a disagreement with the PDB; this is more in line with the behavior I would have hoped for... i.e. when there's uncertainty, it's a close call - not necessarily was the wrong label given...<br /> - line 213: "The revised overall test set accuracy following manual annotation is 83.3%". This is impressive. How will this translate to lower-resolution structures, where there will be more error in atom positions... I am thinking back to the fact that they authors found that fingerprinting worked best when using very fine shells... Perhaps this should be discussed somewhere [I think this is touched on in the paragraph ending line 269]<br /> - line 269: Right. That touches on my earlier question. When you get to the ~3Å range, unless you happen to have your coordinating side chains modeled really well, MIC is going to be quite prone to error. [I still think this topic of accuracy as a function of resolution should be returned to in the discussion]<br /> - line 432: "MIC achieves incredible accuracy". Hah! I think the authors should aim for the readers to actually believe the claimed accuracy, and it is unhelpful to characterize the accuracy as "incredible". I found the manuscript credible overall ;)<br /> - line 495-498: "limiting all calculated (...) to be identity agnostic" - I don't understand this. Might be worth spelling things out for non-specialists like myself<br /> - line 512: "non/prune-fifp" I think should be "non-prune/fifp"<br /> - line 513: "prune-eifp" I think should be "prune/eifp"
Alexis Rohou<br /> May 2024
On 2024-05-18 21:03:14, user Camilla Forsberg wrote:
This preprint has now been revised and published in CELL:<br /> https://www.cell.com/cell/f...
On 2024-05-18 16:14:04, user Carol Greider wrote:
This paper is now published in Science<br /> DOI: 10.1126/science.ado0431
On 2024-05-17 06:43:31, user Bayden D. Russell wrote:
Now published in Science Advances doi: 10.1126/sciadv.abp8747
On 2024-05-17 05:05:22, user Julian C wrote:
Updated citation: PLoS ONE 19(5): e0302696. https://doi.org/10.1371/jou...
On 2024-05-07 17:33:00, user Julian C wrote:
(From the corresponding author) To appear in PLOS ONE.
On 2024-05-16 13:44:41, user Jiri Hulcr wrote:
Nice article, we are hoping that we could use the genome sequence for our current work. <br /> I would recommend that the authors do not replicate the standard adage of how we have to study this beetle because it is a pest that is difficult to control. There are piles of literature on this topic, including two comprehensive compendia by the Forest Service, dedicated to the biology and management of this species. Foresters know very well how to manage forests to avoid outbreaks of the Southern pine beetle. There is a multi-state program for monitoring the population of the species, and predicting its local outbreaks. Case in point - the beetle was pretty much eradicated from the state of Texas, which is presumably why the authors had to use material from Mississippi. <br /> Studying genetics in order to "kill the pest" seems mistargeted. We know nearly all bark beetle outbreaks are a symptom of excessive stand density, warming climate, or introductions of invasive species, i.e., human-caused. So justifying this great research by the need to control the insects is not very convincing. The many incredible biological features of this insect would make a much more interesting justification.
On 2024-05-15 13:15:57, user Ruben Perez wrote:
This preprint has been published in Virus Evolution (10.1093/ve/veae031). The title has been slightly modified: “Highly pathogenic avian influenza H5N1 virus infections in pinnipeds and seabirds in Uruguay: implications for bird-mammal transmission in South America”.
On 2024-05-14 04:54:31, user Erick Nedd wrote:
Limited Sample Size: In Figure 1A-E, I noticed that only 18 out of the 54 subjects were included in the comparison of biological age versus chronological age in EL subjects. Due to the already limited nature of having a large sample size of centenarians for research studies, it may be more effective to include more participants because having a smaller sample size may limit the generalizability of findings and necessitate caution in applying results to broader populations or conclusions about aging.
Including more controls: In Figure 3 where the forward programming of EL-specific iPSCs into cortical neurons was analyzed, I noticed that there was no control of an established cortical neuron cell line. Including this control, would be helpful in comparing the differences and similarities between the differentiated iPSCs and the cortical neurons, and would further help to confirm the pluripotency of the iPSCs created in this experiment.
Inclusion of Demographic Information: Including the demographic information of centenarians or the countries from which they come from would be helpful in contextualizing the study and understanding the possible influences on biological age. Considering that factors such as, geographical location, lifestyle habits and access to healthcare can all influence the aging process, including the demographic information of participants may illustrate environmental or genetic factors that may lead to exceptional longevity. Furthermore, having iPSCs from diverse populations may lead to more robust findings in that they would better represent the genetic variation across the globe.
Supplemental figures: While the inclusion of the supplemental figures was interesting in seeing the different population of immune cells in centenarians, there was not sufficient information for readers to see how these immune cell populations compared to offspring or their spouses. Having a control of an offsprings’ spouse would help your audience understand how the population of immune cells in centenarians may have lead them to living a longer life, and provide a clearer picture of the role of immune cells in longevity.
On 2024-05-13 11:39:30, user Alice Risely wrote:
This is a great experiment for looking at changes in serum metabolites over migratory stages. This is valuable information. However, it is a shame that the gut microbiome part of the study is only rudimentary - the study would be much stronger if it could link changes to metabolites with gut microbiota variation, which requires measuring the gut microbiota across all stages and using metagenomics or universal primers. As such, I think the 'gut microbiome adaptions' in the title is misleading.
On 2024-05-12 22:14:39, user Elliot Swartz wrote:
Please see a summary of problems with this study: https://gfi.org/wp-content/...
On 2024-05-11 17:42:26, user Thierry Grange wrote:
A revised version of this manuscript has been published in October 2023:
https://doi.org/10.1038/s41...<br /> Genome sequences of 36,000- to 37,000-year-old modern humans at Buran-Kaya III in Crimea<br /> E. Andrew Bennett, Oğuzhan Parasayan, Sandrine Prat, Stéphane Péan, Laurent Crépin, Alexandr Yanevich, Thierry Grange & Eva-Maria Geigl <br /> Nature Ecology & Evolution<br /> volume 7, pages 2160–2172 (2023)
On 2024-05-10 21:05:06, user disqus_gM8nbME1Vj wrote:
In discussion, para 2, 19th line, the author mentioned that the expression of "the induction of Fe uptake related genes such as FRO2, IRT1 was also not compromised in the pye mutant unlike hy5 mutant" and refered to the "Figure S2".<br /> But, in "Figure S2", it appears that FRO2 and IRT1 levels are lower in pye than in hy5 mutant as compared to the WT.
On 2024-05-10 08:11:47, user Stefano Vianello wrote:
Dear Dr. Blotenburg,
I'm Stefano, the author of REF 20 re endoderm-rich gastruloids. In the Discussion section of your manuscript you write that
[REF20] maintained mESCs in 2i-medium and reported faithful emergence of endoderm cells
. Given the importance of mESC culture conditions in your analyses and possible future interpretations (at least, re endoderm), I wanted to point out that — following the practice of the lab I was working in at the time — mESCs were not grown in the classic 2i medium (2i in N2B27), but in fact in a 2i in ES+LIF medium (exact recipe in REF20's Materials & Methods > Cell culture). Based on gastruloid end-phenotype alone (of those shown in FigS1), I would guess this atypical mESCs culture medium is most closely matched by your culture condition 3 (and possibly condition 4), and that those conditions (though they were not selected for scRNAseq) are giving rise to endoderm-rich gastruloids.
Sincerely,<br /> Stefano Vianello
On 2024-05-09 19:30:15, user Sophie Astrof wrote:
This paper has been published:
https://doi.org/10.1161/CIR... Circulation Research. 2024;134:e112–e132
On 2024-05-09 13:09:41, user Peter Ellis wrote:
Fascinating work but it doesn’t complicate the central dogma in any way regardless of what inaccurate textbooks say.
https://www.researchgate.ne...
Crick was quite specific: the central dogma simply says that translation is irreversible.
On 2024-05-09 08:52:36, user Mihail Halachev wrote:
Apologies for the late reply. The variant in the LOXHD1 gene<br /> (as all other enriched variants listed in Tables 1-5) can be found in ClinVar by searching for AlleleID = 176561, rather than by variation ID.
On 2024-05-08 16:54:50, user Jorge Soberon wrote:
Many people have used ellipsoids (Mahalanobis distance) for niche modelling in the past. I think you need to consult, at least:
Farber, O. and Kadmon, R., 2003. Assessment of alternative approaches for bioclimatic modeling with special emphasis on the Mahalanobis distance. Ecological modelling, 160(1-2), pp.115-130.
Jiménez, L., Soberón, J., Christen, J.A. and Soto, D., 2019. On the problem of modeling a fundamental niche from occurrence data. Ecological Modelling, 397, pp.74-83.
Drake, J.M., 2015. Range bagging: a new method for ecological niche modelling from presence-only data. Journal of the Royal Society Interface, 12(107), p.20150086.
Hirzel, A.H., Hausser, J., Chessel, D. and Perrin, N., 2002. Ecological‐niche factor analysis: how to compute habitat‐suitability maps without absence data?. Ecology, 83(7), pp.2027-2036.
On 2024-05-08 12:59:32, user Yuri Pavlov wrote:
"The artifacts of the dataset were removed by the authors while publishing the dataset" statement is false. The data you downloaded are raw EEG data (as stated in the dataset description. All analyses are therefore performed on data containing a lot of eye movement and muscle artifacts making your classification algorithm useless.
On 2024-05-07 17:57:42, user Dimitrius Santiago P. S. F. Gu wrote:
Hi, the manuscript has just been published with open access in the Journal of Sarcopenia, Cachexia and Muscle! Please access https://onlinelibrary.wiley... for the latest version.
On 2024-05-07 17:37:12, user Julian C wrote:
(From the author) To appear as a book chapter in: Ruiz Romero C, Calamia V and Lourido L (Eds), Protein Arrays: Methods and Applications, Electronic ISSN 1940-6029, Print ISSN 1064-3745, Springer Nature.
On 2024-05-06 11:02:33, user Roman wrote:
There is already another CRISPR method out there, called CREATE (https://pubmed.ncbi.nlm.nih... so maybe the authors want to pick a different acronym so that readers don't get confused.
On 2024-05-06 08:20:36, user Liheng Luo wrote:
Your work, CRISPR-GPT is groundbreaking, bridging the gap between complex gene-editing technology and researchers from various fields. The potential for accelerating biological discovery is immense, and I’m excited to see its impact on future research. <br /> I am eager to see this technology in action and would greatly appreciate the opportunity to explore a demo of the author’s website. Such hands-on experience would provide invaluable insight into the practical applications of CRISPR-GPT.
On 2024-05-06 08:02:44, user Daniel Guzman Llorens wrote:
Congratulations to the team, it is a great article. I found the results very insightful.<br /> While reading, I seem to have found an error in the insulin intensity histogram in Figure 3, as both A and C seem to be the same histogram.
On 2024-05-04 20:50:43, user Cameron Cohen wrote:
Fascinating read! Can’t wait to see where this project goes!
On 2024-05-04 01:52:43, user priyanka.bajaj3193@gmail.com wrote:
In this study the authors comprehensively examined the mutational effects on PLpro proteolytic activity and stability. The authors have designed a FRET-based assay composed of N-terminal mClover3 donor and C-terminal m-Ruby3 acceptor fluorophores separated by a linker containing the Nsp2/3 PLpro cleavage motif to measure the proteolytic activity of PLpro. From DMS data the authors infer PLpro active site mutations ablates activity. Their study also revealed residues required for cleavage of the Nsp2/3 site, identified features of substrate binding pocket and the sequence requirements of the blocking loop. The authors have given explanations for their observations in the Discussion section. Overall, the paper is supported with follow-up enzymology and crystallography experiments of key residues. The major limitation of this study is leaky expression of mutations can mask clinically relevant mutations that can arise due to viral evolution and might have the potential to evade inhibitor treatment. Study of such mutations can provide more information about the potential escape routes open to the virus to evade developing therapeutics. Moreover, incorporation of statistical analysis could strengthen the confidence in inferences drawn from the deep sequencing data and improve the quality of the manuscript. <br /> The following points can improve the quality of the manuscript:<br /> Major points<br /> 1. In Figure 1f, it is unclear that why is the PLpro activity increasing with increase in inhibitor concentration? Perhaps the Y axis is mislabeled as while inhibitor concentration is increasing, PLpro activity should decrease. However, FRET signal would increase (and maybe should be the axis label), since there will be no cleavage. <br /> 2. Line 175 – 178 - What does 0 represent in the normalized dataset? What is the rationale used for selecting minimum 10 reads in the unselected library as the read cut-off. 10 reads is pretty low cut-off. From the data, it seems the distribution tails off before cut-off chosen for the s.d.- by eye. 0.3 s.d and 20 as read cut-off might be a better option to eliminate sequencing artifacts.<br /> 3. Line 187-190 – What is the number of reads for the mutants that showed lower activity scores? There is a possibility that due to low read cutoff, these mutants might be lying in the range with low reads in the unselected library.<br /> 4. Line 223-224 – Authors mention they find a good correlation between activity and abundance score. Although this is noticeable from the scatter plot but supporting high-throughput data with statistical parameters like pearson correlation coefficient, a metric that provides comparison between 2 datasets will make this data reporting more quantitative and informative.<br /> 5. Line 1340- Figure 3b- What do authors mean by variants with small enough error? Please be precise.<br /> 6. Line 315-319/ Line 1550-1556- Extended data Fig 15c – It is difficult to interpret the inference reported that is based on the data in Extended Fig 15. There is no data reported for Normalized AMC cleavage for Y268W. Interpretation can be more comprehensible by plotting a scatter plot between the Normalized Activity Fitness Scores obtained from DMS data and Normalized AMC cleavage (%). Through this plot, the reader can easily make out the outlier.<br /> 7. Line 364-367 – Authors mention “M208W strikingly increases the protein melting temperature by over 5C, indicating a substantial improvement in thermal stability. Increased stability, and thus reduced turnover in cells, may provide a mechanism to explain leaky expression in our cellular assay and increased yield of recombinant protein for E.coli expression.” Since, leaky expression is a different issue, it is confusing why will leaky expression be a plausible reason for increased stability but less activity? <br /> 8. Since Extended data Fig 11a shows that variants display substantial amount of leaky expression, how have the authors taken this information into account while inferring results from DMS activity scores, especially since they are quantifying at the RNA level and not at the DNA level? Can the activity scores obtained for the mutants be normalized to leaky expression scores in some way, for example by subtracting the scores obtained from the leaky expression dataset in order to measure the true activity of each mutant?<br /> 9. Solvents are known to affect an enzyme’s activity, selectivity and stability. In Figure 5, authors should consider and comment about the role of solvent in understanding the mechanism of Michelis-Menten kinetics of M208 variants using substrates Z-RLRGG-AMC, Ubiquitin-Rhodamine and ISG15-Rhodamine.<br /> Minor points<br /> 1. Figure numbers need to be reformatted. Figure 3 onwards they are incorrectly labelled. For eg. ‘Fig 3’ is labelled as ‘Fig 1’.<br /> 2. Line 426-429 – In Figure 3b, L and R domains of papain should be labelled or highlighted in separate colors for the ease of understanding for the reader.<br /> 3. Overall, different DMS datasets obtained from different assays in the paper have different read cut-offs such as 10, 13 and 18. A consistent statistical logic for obtaining different read cut-offs across different DMS datasets will be helpful. Also, increasing the read cut-off might improve the data quality and minimize sequencing artefacts.
On 2024-05-03 21:48:51, user Michael L. wrote:
This manuscript has now been combined with https://www.biorxiv.org/con... and published as https://pubmed.ncbi.nlm.nih...