- Jul 2024
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This is a fantastic, comprehensive, timely, and landmark pan-species work that demonstrates the convergence of multiple familial PD mutations onto a synaptic program. It is extremely well written and I have only a few comments that do not require additional data collection.
Major Comments:
(1) In the functional experiments performing calcium imaging on projection neurons I could not find a count of cell bodies across conditions. Since the loss of OPNs could explain the reduced calcium signal, this is a critical control to perform. A differential abundance test on the single-cell data would also suffice here and be easy for the authors to perform with their existing data.
(2) One of the authors' conclusions is that cholinergic neurons and the olfactory system are acutely impacted by these PD mutations. However, I wonder if this is the case:<br /> a. Most Drosophila excitatory neurons are cholinergic and only a subpopulation appear to be dysregulated by these mutations. The authors point out that visual neurons also have many DEGs, couldn't the visual system also be dysregulated in these flies? Is there something special about these cholinergic neurons versus other cholinergic neurons in the fly brain? I wonder if they can leverage their nice dataset to say something about vulnerability.<br /> b. As far as I can tell, the cross-species analysis of DEGs (Figure 3) is agnostic to neuronal cell type, although the conclusion seems to suggest only cholinergic neurons were contrasted. Is this correct? Could you please clarify this in the text as it's an important detail. If not, Have the authors tried comparing only cholinergic neuron DEGs across species? That would lend strength to their specificity argument. The results for the NBM are impressive. Could the authors add more detail to the main text here about other regions to the main text?<br /> c. Uniquely within the human data, are cholinergic neurons more dysregulated than others? I understand this is not an early timepoint but would still be useful to discuss.<br /> d. In the discussion, the authors say that olfactory neurons are uniquely poised to be dysregulated as they are large and have high activity. Is this really true compared to other circuits? I didn't find the references convincing and I am not sure this has been borne out in electron microscopy reconstructions for anatomy.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This is an important and interesting study that uses the split-GFP approach. Localization of receptors and correlating them to function is important in understanding the circuit basis of behavior.
Strengths:
The split-GFP approach allows visualization of subcellular enrichment of dopamine receptors in the plasma membrane of GAL4-expressing neurons allowing for a high level of specificity.
The authors resolve the presynaptic localization of DopR1 and Dop2R, in "giant" Drosophila neurons differentiated from cytokinesis-arrested neuroblasts in culture as it is not clear in the lobes and calyx.
Starvation-induced opposite responses of dopamine receptor expression in the PPL1 and PAM DANs provide key insights into models of appetitive learning.
Starvation-induced increase in D2R allows for increased negative feedback that the authors test in D2R knockout flies where appetitive memory is diminished.
This dual autoreceptor system is an attractive model for how amplitude and kinetics of dopamine release can be fine-tuned and controlled depending on the cellular function and this paper presents a good methodology to do it and a good system where the dynamics of dopamine release can be tested at the level of behavior.
Weaknesses:
LI measurements of Kenyon cells and lobes indicate that Dop2R was approximately twice as enriched in the lobe as the average density across the whole neuron, while the lobe enrichment of Dop1R1 was about 1.5 times the average, are these levels consistent during different times of the day and the state of the animal. How were these conditions controlled and how sensitive are receptor expression to the time of day of dissection, staining, etc.
The authors assume without discussion as to why and how presynaptic enrichment of these receptors is similar in giant neurons and MB.
Figures 1-3 show the expensive expression of receptors in alpha and beta lobes while Figure 5 focusses on PAM and localization in γ and β' projections of PAM leading to the conclusion that pre-synaptic dopamine neurons express these and have feedback regulation. Consistency between lobes or discussion of these differences is important to consider.
Receptor expression in any learning-related MBONs is not discussed, and it would be intriguing as how receptors are organized in those cells. Given that these PAMs input to both KCs and MBONs these will have to work in some coordination.
Although authors use the D2R enhancement post starvation to show that knocking down receptors eliminated appetitive memory, the knocking out is affecting multiple neurons within this circuit including PAMs and KCs. How does that account for the observed effect? Are those not important for appetitive learning?
The evidence for fine-tuning is completely based on receptor expression and one behavioral outcome which could result from many possibilities. It is not clear if this fine-tuning and presynaptic feedback regulation-based dopamine release is a clear possibility. Alternate hypotheses and outcomes could be considered in the model as it is not completely substantiated by data at least as presented.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
The study made fundamental findings in investigations of the dynamic functional states during sleep. Twenty-one HMM states were revealed from the fMRI data, surpassing the number of EEG-defined sleep stages, which can define sub-states of N2 and REM. Importantly, these findings were reproducible over two nights, shedding new light on the dynamics of brain function during sleep.
Strengths:
The study provides the most compelling evidence on the sub-states of both REM and N2 sleep. Moreover, they showed these findings on dynamics states and their transitions were reproducible over two nights of sleep. These novel findings offered unique information in the field of sleep neuroimaging.
Weaknesses:
The only weakness of this study has been acknowledged by the authors: limited sample size.
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Reviewer #1 (Public Review):
Summary:
This work studies representations in a network with one recurrent layer and one output layer that needs to path-integrate so that its position can be accurately decoded from its output. To formalise this problem, the authors define a cost function consisting of the decoding error and a regularisation term. They specify a decoding procedure that at a given time averages the output unit center locations, weighted by the activity of the unit at that time. The network is initialised without position information, and only receives a velocity signal (and a context signal to index the environment) at each timestep, so to achieve low decoding error it needs to infer its position and keep it updated with respect to its velocity by path integration.
The authors take the trained network and let it explore a series of environments with different geometries while collecting unit activities to probe learned representations. They find localised responses in the output units (resembling place fields) and border responses in the recurrent units. Across environments, the output units show global remapping and the recurrent units show rate remapping. Stretching the environment generally produces stretched responses in output and recurrent units. Ratemaps remain stable within environments and stabilise after noise injection. Low-dimensional projections of the recurrent population activity forms environment-specific clusters that reflect the environment's geometry, which suggests independent rather than generalised representations. Finally, the authors discover that the centers of the output unit ratemaps cluster together on a triangular lattice (like the receptive fields of a single grid cell), and find significant clustering of place cell centers in empirical data as well.
The model setup and simulations are clearly described, and are an interesting exploration of the consequences of a particular set of training requirements - here: path integration and decodability. But it is not obvious to what extent the modelling choices are a realistic reflection of how the brain solves navigation. Therefore it is not clear whether the results generalize beyond the specifics of the setup here.
Strengths:
The authors introduce a very minimal set of model requirements, assumptions, and constraints. In that sense, the model can function as a useful 'baseline', that shows how spatial representations and remapping properties can emerge from the requirement of path integration and decodability alone. Moreover, the authors use the same formalism to relate their setup to existing spatial navigation models, which is informative.
The global remapping that the authors show is convincing and well-supported by their analyses. The geometric manipulations and the resulting stretching of place responses, without additional training, are interesting. They seem to suggest that the recurrent network may scale the velocity input by the environment dimensions so that the exact same path integrator-output mappings remain valid (but maybe there are other mechanisms too that achieve the same).
The clustering of place cell peaks on a triangular lattice is intriguing, given there is no grid cell input. It could have something to do with the fact that a triangular lattice provides optimal coverage of 2d space? The included comparison with empirical data is valuable, although the authors only show significant clustering - there is no analysis of its grid-like regularity.
Weaknesses:
The navigation problem that needs to be solved by the model is a bit of an odd one. Without any initial position information, the network needs to figure out where it is, and then path-integrate with respect to a velocity signal. As the authors remark in Methods 4.2, without additional input, the only way to infer location is from border interactions. It is like navigating in absolute darkness. Therefore, it seems likely that the salient wall representations found in the recurrent units are just a consequence of the specific navigation task here; it is unclear if the same would apply in natural navigation. In natural navigation, there are many more sensory cues that help inferring location, most importantly vision, but also smell and whiskers/touch (which provides a more direct wall interaction; here, wall interactions are indirect by constraining velocity vectors). There is a similar but weaker concern about whether the (place cell like) localised firing fields of the output units are a direct consequence of the decoding procedure that only considers activity center locations.
The conclusion that 'contexts are attractive' (heading of section 2) is not well-supported. The authors show 'attractor-like behaviour' within a single context, but there could be alternative explanations for the recovery of stable ratemaps after noise injection. For example, the noise injection could scramble the network's currently inferred position, so that it would need to re-infer its position from boundary interactions along the trajectory. In that case the stabilisation would be driven by the input, not just internal attractor dynamics. Moreover, the authors show that different contexts occupy different regions in the space of low-dimensional projections of recurrent activity, but not that these regions are attractive.
The authors report empirical data that shows clustering of place cell centers like they find for their output units. They report that 'there appears to be a tendency for the clusters to arrange in hexagonal fashion, similar to our computational findings'. They only quantify the clustering, but not the arrangement. Moreover, in Figure 7e they only plot data from a single animal, then plot all other animals in the supplementary. Does the analysis of Fig 7f include all animals, or just the one for which the data is plotted in 7e? If so, why that animal? As Appendix C mentions that the ratemap for the plotted animal 'has a hexagonal resemblance' whereas other have 'no clear pattern in their center arrangements', it feels like cherrypicking to only analyse one animal without further justification.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors aimed to enhance the effectiveness of PARP inhibitors (PARPi) in treating high-grade serous ovarian cancer (HGSOC) and triple-negative breast cancer (TNBC) by inhibiting PRMT1/5 enzymes. They conducted a drug screen combining PARPi with 74 epigenetic modulators to identify promising combinations.
Zhang et al. reported that protein arginine methyltransferase (PRMT) 1/5 inhibition acts synergistically to enhance the sensitivity of Poly (ADP-ribose) polymerase inhibitors (PARPi) in high-grade serous ovarian cancer (HGSOC) and triple-negative breast cancer (TNBC) cells. The authors are the first to perform a drug screen by combining PARPi with 74 well-characterized epigenetic modulators that target five major classes of epigenetic enzymes. Their drug screen identified both PRMT1/5 inhibitors with high combination and clinical priority scores in PARPi treatment. Notably, PRMT1/5 inhibitors significantly enhance PARPi treatment-induced DNA damage in HR-proficient HGSOC and TNBC cells through enhanced maintenance of gene expression associated with DNA damage repair, BRCAness, and intrinsic innate immune pathways in cancer cells. Additionally, bioinformatic analysis of large-scale genomic and functional profiles from TCGA and DepMap further supports that PRMT1/5 are potential therapeutic targets in oncology, including HGSOC and TNBC. These results provide a strong rationale for the clinical application of a combination of PRMT and PARP inhibitors in patients with HR-proficient ovarian and breast cancer. Thus, this discovery has a high impact on developing novel therapeutic approaches to overcome resistance to PARPi in clinical cancer therapy. The data and presentation in this manuscript are straightforward and reliable.
Strengths:
(1) Innovative Approach: First to screen PARPi with a large panel of epigenetic modulators.<br /> (2) Significant Results: Found that PRMT1/5 inhibitors significantly boost PARPi effectiveness in HR-proficient HGSOC and TNBC cells.<br /> (3) Mechanistic Insights: Showed how PRMT1/5 inhibitors enhance DNA damage repair and immune pathways.<br /> (4) Robust Data: Supported by extensive bioinformatic analysis from large genomic databases.
Weaknesses:
(1) Novelty Clarification: Needs clearer comparison to existing studies showing similar effects.<br /> (2) Unclear Mechanisms: More investigation is needed on how MYC targets correlate with PRMT1/5.<br /> (3) Inconsistent Data: ERCC1 expression results varied across cell lines.<br /> (4) Limited Immune Study: Using immunodeficient mice does not fully explore immune responses.<br /> (5) Statistical Methods: Should use one-way ANOVA instead of a two-tailed Student's t-test for multiple comparisons.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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32186
DOI: 10.1117/1.JBO.28.6.066501
Resource: (BDSC Cat# 32186,RRID:BDSC_32186)
Curator: @anisehay
SciCrunch record: RRID:BDSC_32186
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Herneisen et al characterise the Toxoplasma PDK1 orthologue SPARK and an associated protein SPARKEL (cute name) in controlling important fate decisions in Toxoplasma. Over recent years this group and others have characterised the role of cAMP and cGMP signalling in negatively and positively regulating egress, motility and invasion, respectively. This manuscript furthers this work by showing that SPARK and SPARKEL likely act upstream, or at least control the levels of the cAMP and cGMP-dependent kinases PKA and PKG, respectively, thus controlling the transition of intracellular replicating parasites into extracellular motile forms (and back again).
The authors use quantitative (phospho)proteomic techniques to elegantly demonstrate the upstream role of SPARK in controlling cAMP and cGMP pathways. They use sophisticated analysis techniques (at least for parasitology) to show the functional association between cGMP and cAMP signalling pathways. They therefore begin to unify our understanding of the complicated signalling pathways used by Toxoplasma to control key regulatory processes that control the activation and suppression of motility. The authors then use molecular and cellular assays on a range of generated transgenic lines to back up their observations made by quantitative proteomics that are clear in their design and approach.
The authors then extend their work by showing that SPARK/SPARKEL also control PKAc3 function. PKAc3 has previously been shown to negatively regulate differentiation into bradyzoite forms and this work backs up and extends this finding to show that SPARK also controls this. The authors conclude that SPARK could act as a central node of regulation of the asexual stage, keeping parasites in their lytic cell growth and preventing differentiation. Whether this is true is beyond the scope of this paper and will have to be determined at a later date.
Strengths:
This is an exceptional body of work. It is elegantly performed, with state-of-the-art proteomic methodologies carefully being applied to Toxoplasma. Observations from the proteomic datasets are masterfully backed up with validation using quantitative molecular and cellular biology assays.
The paper is carefully and concisely written and is not overreaching in its conclusions. This work and its analysis set a new benchmark for the use of proteomics and molecular genetics in apicomplexan parasites.
Weaknesses:
There are no weaknesses in this paper.
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www.biorxiv.org www.biorxiv.org
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Joint Public Review:
Ewing sarcoma is an aggressive pediatric cancer driven by the EWS-FLI oncogene. Ewing sarcoma cells are addicted to this chimeric transcription factor, which represents a strong therapeutic vulnerability. Unfortunately, targeting EWS-FLI has proven to be very difficult and better understanding how this chimeric transcription factor works is critical to achieving this goal. Towards this perspective, the group had previously identified a DBD-𝛼4 helix (DBD) in FLI that appears to be necessary to mediate EWS-FLI transcriptomic activity. Here, the authors used multi-omic approaches, including CUT&tag, RNAseq, and MicroC to investigate the impact of this DBD domain. Importantly, these experiments were performed in the A673 Ewing sarcoma model where endogenous EWS-FLI was silenced, and EWS-FLI-DBD proficient or deficient isoforms were re-expressed (isogenic context). The authors found that the DBD domain is key to mediate EWS-FLI cis activity (at msat) and to generate the formation of specific TADs. Furthermore, cells expressing DBD deficient EWS-FLI display very poor colony forming capacity, highlighting that targeting this domain may lead to therapeutic perspectives.
This new version of the study comprises as requested new data from an additional cell line. The new data has strengthened the manuscript. Nevertheless, some of the arguments of the authors pertaining to the limitations of immunoblots to assess stability of the DBD constructs or the poor reproducibility of the Micro C data remain problematic. While the effort to repeat MicroC in a different cell line is appreciated, the data are as heterogeneous as those in A673 and no real conclusion can be drawn. The authors should tone down their conclusions. If DBD has a strong effect on chromatin organization, it should be reproducible and detectable. The transcriptomic and cut and tag data are more consistent and provide robust evidence for their findings at these levels.
Concerning the issue of stability of the DBD and DBD+ constructs, a simple protein half-life assay (e.g. cycloheximide chase assay) could rule out any bias here and satisfactorily address the issue.
Suggestions:
The Reviewing Editor and a referee have considered the revised version and the responses of the referees. While the additional data included in the new version has consolidated many conclusions of the study, the MicroC data in the new cell line are also heterogeneous and as the authors argue, this may be an inherent limitation of the technique. In this situation, the best would be for the authors to avoid drawing robust conclusions from this data and to acknowledge its current limitations.
The referee and Reviewing Editor also felt that the arguments of the authors concerning a lack of firm conclusions on the stability of EWS-FLI1 under +/-DBD conditions could be better addressed. We would urge the authors to perform a cycloheximide chase type assay to assess protein half-life. These types of experiments are relatively simple to perform and should address this issue in a satisfactory manner.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript entitled "Association with TFIIIC limits MYCN accumulation in hubs of active promoters and chromatin accumulation of non-phosphorylated RNA polymerase II" the authors examine how the cohesin complex component (and RNA pol III associated factor) TFIIIC interacts with MYCN and controls transcription. They confirm that TFIIIC co-purifies with MYCN, dependent on its amino terminus, as shown in previous work. The authors also find that TFIIIC and MYCN are both found in promoter hubs and suggest that TFIIIC inhibits MYCN association with these hubs. Finally, the authors indicate that TFIIIC/MYCN alter exosome function, and BRCA1 dependent effects, at MYCN regulated loci.
In the revised manuscript the authors have adequately addressed or responded to our questions and comments. The exception concerns point #2 in our initial review:
(2) The authors indicate in Figure 2 that TF3C has essentially no effect on MYCN- dependent gene expression and/or transcription elongation. Yet a previous study (PMID: 29262328) associated with several of the same authors concluded that TF3C positively affects transcription elongation. The authors to not attempt to reconcile these disparate results and the point still needs to clarified.
Authors' Response<br /> We agree that the data in this manuscript do not support the role on transcription elongation. This point was also raised by Reviewer 3. Comparing our new results to the data published previously we can summarize that the data sets in the two studies show three key results: First, the traveling ratio of RNAPII changes upon induction of MYCN. Second, RNAPII decreases at the transcription start side and third, it increases towards the end side.
We agree that in the previous study we linked the traveling ratio directly to elongation. However performing ChIP-seq with different RNAPII antibodies showed us that for example RNAPII (N20), which is unfortunately discontinued, gives different results compared to RNAPII (A10). Combining our new results using the RNAPII (8WG16) antibody shows that the traveling ratio is not only reflecting transcription elongation but also includes that the RNAPII is kicked-off chromatin at the start side.
Reviewer revised response:<br /> The explanation for the change in interpretation of the previous study (Buchel, et. al., 2017) in light of the differing results using different RNA pol2 antibodies used in the present study seems reasonable. However the final manuscript may well result in some confusion in the literature in regards to TF3C and elongation. This is because, while the authors refer to the earlier paper frequently, they do not directly discuss the re-interpretation of the elongation conclusion of the earlier paper. It seems likely that a reader of the present paper will find this issue confusing when trying to reconcile the results of the two papers.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This is a nice paper taking a broad range of aspects and endpoints into account. The effect of GAHT in girls has been nicely worked out. Changes in Sertoli and peritubular cells appear valid, less strong evidence is provided for Leydig cell development. The recovery of SSCs appears an overjudgement and should be rephrased. The multitude and diversity of datasets appear a strength and a weakness as some datasets were not sufficiently critically reviewed and a selection of highlights provides a certain bias to the interpretation and conclusion of the study.
The authors need to indicate that the subset of data on SSCs has been reported previously (Human Reprod 36: 5-15 (2021) and is simply re-incorporated in the present paper. as Fig. 1C. There are sufficient new results to publish the remaining datasets as a separate paper. Authors could refer to the SSC data with reference to the previous publication.
Strengths:
The patient cohort is impressive and is nicely characterized. Here, histological endpoints and endocrine profiles were analyzed appropriately for most endpoints. The paper is well-written and has many new findings.
Weaknesses:
The patients and controls are poorly separated in regard to pubertal status. Here additional endpoints (e.g. Tanner status) would have been helpful especially as the individual patient history is unknown. Pre- and peri-puberty is a very rough differentiation. The characterization and evaluation of Leydig cells is the weakest histological endpoint. Here, additional markers may be required. Fig. 1 suffers from suboptimal micrograph quality.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, Gholamalamdari et al. described various aspects of genome organization in relation to nuclear speckles, the nuclear lamina, and nucleoli. Their findings were drawn from the analysis of genomic data sourced from four distinct human cell types. The authors observed significant variation in genome positioning at the lamina and nucleoli across different cell types, whereas contacts with nuclear speckles showed less variability. The data revealed a correlation between gene expression levels and proximity to nuclear speckles, with regions in contact with these speckles coinciding with DNA replication initiation zones. Additionally, the results indicated that the loss of Lamin A and LBR leads to a redistribution of H3K9me3-enriched LADs from the lamina to the nucleolus. Furthermore, a portion of H3K27me3-enriched, partially repressed intergenic LADs (iLADs) was observed to relocate from the nucleolus to the lamina. The study also proposed that these repressed iLADs may compete with LADs for attachment to the nuclear lamina.
Strengths:
The datasets have been thoroughly integrated and exhibit various features of genomic domains interacting with nuclear speckles, the nuclear lamina, and nucleoli, which will be of interest to the field.
Weaknesses:
The weakness of this study lies in the fact that many of the genomic datasets originated from novel methods that were not validated with orthogonal approaches, such as DNA-FISH. Therefore, the detailed correlations described in this work are based on methodologies whose efficacy is not clearly established. Specifically, the authors utilized two modified protocols of TSA-seq for the detection of NADs (MKI67IP TSA-seq) and LADs (LMNB1-TSA-seq). Although these methods have been described in a bioRxiv manuscript by Kumar et al., they have not yet been published. Moreover, and surprisingly, Kumar et al., work is not cited in the current manuscript, despite its use of all TSA-seq data for NADs and LADs across the four cell lines. Moreover, Kumar et al. did not provide any DNA-FISH validation for their methods. Therefore, the interesting correlations described in this work are not based on robust technologies.<br /> An attempt to validate the data was made for SON-TSA-seq of human foreskin fibroblasts (HFF) using multiplexed FISH data from IMR90 fibroblasts (from the lung) by the Zhuang lab (Su et al., 2020). However, the comparability of these datasets is questionable. It might have been more reasonable for the authors to conduct their analyses in IMR90 cells, thereby allowing them to utilize MERFISH data for validating the TSA-seq method and also for mapping NADs and LADs.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study from Belato, Knight, and co-workers, the authors investigated the Rec domain of a thermophilic Cas9 from Geobacillus stearothermophilus (GeoCas9). The authors investigated three constructs, two individual subdomains of Rec (Rec1 and Rec2) and the full Rec domain. This domain is involved in binding to the guide RNA of Cas9, as well as the RNA-DNA duplex that is formed upon target binding. The authors performed RNA binding and relaxation experiments using NMR for the wild-type domain as well as two-point mutants. They observed differences in RNA binding activities as well as the flexibility of the domain. The authors also performed experiments on full-length GeoCas9 to determine whether these biophysical differences affect the RNA binding or cleavage activity. Although the authors observed some changes in the thermal stability of the mutant GeoCas9-gRNA complex, they did not observe substantial differences in the cleavage activities of the mutant GeoCas9 variants.
Overall, this manuscript provides a detailed biophysical analysis of the GeoCas9 Rec domain. The NMR assignments for this construct should prove very useful, and the results may provide the grounds for future engineering of higher fidelity variants of GeoCas9. While the NMR results are generally well presented, it is unclear how the results on the isolated Rec domain related to the overall function of full-length GeoCas9. In addition, some conclusions are overstated and not fully supported by the evidence provided. The following major points should be addressed by the authors.
(1) Many of the results rely on the backbone resonance assignments of the three constructs that were used, and the authors have done an excellent job of assigning the Rec1 and Rec2 constructs. However, it is unclear from the descriptions in the text how the full-length Rec construct was assigned. Were these assignments made based on assignments for the individual domains? The authors state that the spectra of individual domains and RecFL overlay very well, but there appear to be many resonances that have chemical shift differences or are only present in one construct. As it stands, it is unclear how the resonances were assigned for residues whose chemical shifts were perturbed, making it difficult to interpret many of the results.
(2) The minimal gRNA that was used for the Rec-gRNA binding experiments is unlikely to be a good mimic for the full-length gRNA, as it lacks any of the secondary structure that is most specifically recognized by the REC lobe and the rest of the Cas9 protein. The majority of this RNA is a "spacer" sequence, but spacers are variable, so this sequence is arbitrary. Thus, the interactions that the authors are observing most likely represent non-specific interactions between the Rec domains and RNA. The authors also map chemical shift perturbations and line broadening on structural models with an RNA-DNA duplex bound, but this is not an accurate model for how the Rec domain binds to a single-stranded RNA (for which there is no structural model). Thus, many of the conclusions regarding the RNA binding interface are overstated.
(3) The authors include microscale thermophoresis (MST) data for the Rec constructs binding to the minimal gRNA. These data suggest that all three Rec variants have very similar Kd's for the RNA. Given these similarities, it is unclear why the RNA titration experiments by NMR yielded such different results. Moreover, in the Discussion, the authors state that the NMR titration data are consistent with the MST-derived Kd values. This conclusion appears to be overstated given the very small differences in affinities measured by MST.
(4) While the authors have performed some experiments to help place their findings on the isolated Rec domain in the context of the full-length protein, these experiments do not fully support the conclusions that the authors draw about the meaning of their NMR results. The two Cas9 variants that were explored via NMR have no effect on Cas9 cleavage activity, and it is unclear from the data provided whether they have any effect on GeoCas9 binding to the full sgRNA. This makes it difficult to determine whether the observed differences in RNA binding and dynamics of the isolated Rec domain have any consequence in the context of the full protein.
(5) The authors state in multiple places that the K267E/R332A mutant enhanced GeoCas9 specificity. Improved specificity refers to a situation in which the efficiency of cleavage of a perfectly matched target improves in comparison to a mismatched target. This is not what the authors observed for the double mutant. Instead, the cleavage of the perfect target was drastically reduced, in some cases to a larger degree than for the mismatched target. The double mutant does not appear to have improved specificity, it has simply decreased cleavage efficiency of the enzyme.
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www.medrxiv.org www.medrxiv.org
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Reviewer #2 (Public Review):
Summary:
The authors generated a DNA methylation score in cord blood for detecting exposure to cigarette smoke during pregnancy. They then asked if it could be used to predict height, weight, BMI, adiposity and WHR throughout early childhood.
Strengths:
The study included two cohorts of European ancestry and one of South Asian ancestry.
Weaknesses:
(1) Numbers of mothers who self-reported any smoking was very low likely resulting in underpowered analyses.
(2) Although it was likely that some mothers were exposed to second-hand smoke and/or pollution, data on this was not available.
(3) One of the European cohorts and half of the South Asian cohort had DNA methylation measured on only 2500 CpG sites including only 125 sites previously linked to prenatal smoking.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors use fluorescence lifetime imaging (FLIM) and tmFRET to resolve resting vs. active conformational heterogeneity and free energy differences driven by cGMP and cAMP in a tetrameric arrangement of CNBDs from a prokaryotic CNG channel.
Strengths:
The excellent data provide detailed measures of the probability of adopting resting vs. activated conformations with and without bound ligands.
Weaknesses:
Limitations are that only the cytosolic fragments of the channel were studied, and the current manuscript does not do a good job of placing the results in the context of what is already known about CNBDs from other methods that yield similar information.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Experiments in model organisms have revealed that the effects of genes on heritable traits are often mediated by environmental factors---so-called gene-by-environment (or GxE) interactions. In human genetics, however, where indirect statistical approaches must be taken to detect GxE, limited evidence has been found for pervasive GxE interactions. The present manuscript argues that the failure of statistical methods to detect GxE may be due to how GxE is modelled (or not modelled) by these methods.
The authors show, via re-analysis of an existing dataset in Drosophila, that a polygenic 'amplification' model can parsimoniously explain patterns of differential genetic effects across environments. (Work from the same lab had previously shown that the amplification model is consistent with differential genetic effects across the sexes for several traits in humans.) The parsimony of the amplification model allows for powerful detection of GxE in scenarios in which it pertains, as the authors show via simulation.
Before the authors consider polygenic models of GxE, however, they present a very clear analysis of a related question around GxE: When one wants to estimate the effect of an individual allele in a particular environment, when is it better to stratify one's sample by environment (reducing sample size, and therefore increasing the variance of the estimator) versus using the entire sample (including individuals not in the environment of interest, and therefore biasing the estimator away from the true effect specific to the environment of interest)? Intuitively, the sample-size cost of stratification is worth paying if true allelic effects differ substantially between the environment of interest and other environments (i.e., GxE interactions are large), but not worth paying if effects are similar across environments. The authors quantify this trade-off in a way that is both mathematically precise and conveys the above intuition very clearly. They argue on its basis that, when allelic effects are small (as in highly polygenic traits), single-locus tests for GxE may be substantially underpowered.
The paper is an important further demonstration of the plausibility of the amplification model of GxE, which, given its parsimony, holds substantial promise for the detection and characterization of GxE in genomic datasets. However, the empirical and simulation examples considered in the paper (and previous work from the same lab) are somewhat "best-case" scenarios for the amplification model, with only two environments, and with these environments amplifying equally the effects of only a single set of genes. It would be an important step forward to demonstrate the possibility of detecting amplification in more complex scenarios, with multiple environments each differentially modulating the effects of multiple sets of genes. This could be achieved via simulations similar to those presented in the current manuscript.
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public Review):
Tu et al investigated how LFPs recorded simultaneously with rsfMRI explain the spatiotemporal patterns of functional connectivity in sedated and awake rats. They find that connectivity maps generated from gamma band LFPs (from either area) explain very well the spatial correlations observed in rsfMRI signals, but that the temporal variance in rsfMRI data is more poorly explained by the same LFP signals. The authors excluded the effects of sedation in this effect by investigating rats in the awake state (a remarkable feat in the MRI scanner), where the findings generally replicate. The authors also performed a series of tests to assess multiple factors (including noise, outliers, etc., and nonlinearity of the data...) in their analysis.
This apparent paradox is then explained by a hypothetical model in which LFPs and neurovascular coupling are generated in some sense "in parallel" by different neuron types, some of which drive LFPs and are measured by ePhys, while others (nNOS, etc.) have an important role in neurovascular coupling but are less visible in Ephys data. Hence the discrepancy is explained by the spatial similarity of neural activity but the more "selective" LFPs picked up by Ephys account for the different temporal aspects observed.
This is a deep, outstanding study that harnesses multidisciplinary approaches (fMRI and ephys) for observing brain activity. The results are strongly supported by the comprehensive analyses done by the authors, that ruled out many potential sources for the observed findings. The study's impact is expected to be very large.
There are very few weaknesses in the work, but I'd point out that the 1-second temporal resolution may have masked significant temporal correlations between LFPs and spontaneous activity, for instance, as shown by Cabral et al Nature Communications 2023, and even in earlier QPP work from the Keilholz Lab. The synchronization of the LFPs may correlate more with one of these modes than the total signal. Perhaps a kind of "dynamic connectivity" analysis on the authors' data could test whether LFPs correlate better with the activity at specific intervals. However this could purely be discussed and left for future work, in my opinion.
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Reviewer #1 (Public Review):
Summary
In their manuscript, Ho and colleagues investigate the importance of thymic-imprinted self-reactivity in determining CD8 T cell pathogenicity in non-obese diabetic (NOD) mice. The authors describe pre-existing functional biases associated with naive CD8 T cell self-reactivity based on CD5 levels, a well-characterized proxy for T cell affinity to self-peptide. They find that naive CD5hi CD8 T cells are poised to respond to antigen challenge; these findings are largely consistent with previously published data on the B6 background. The authors go on to suggest that CD5hi CD8 T cells are more diabetogenic as 1) the CD5hi naive CD8 T cell receptor repertoire has features associated with autoreactivity and contains a larger population of islet-specific T cells, and 2) the autoreactivity of "CD5hi" monoclonal islet-specific TCR transgenic T cells cannot be controlled by phosphatase over-expression. Thus, they implicate CD8 T cells with relatively higher levels of basal self-reactivity in autoimmunity. However, the interpretation of some of the presented data is questioned and compromises some of the conclusions at this stage. A clearer explanation of the data and experimental methods as well as increased rigor in presentation is suggested.
Specific comments
(1) Figures 1 through 4 contain data that largely recapitulate published findings (Fulton et al., Nat. Immunol, 2015; Lee et al, Nat. Comm., 2024; Swee et al, Open Biol, 2016; Dong et al, Immunology & Cell Biology, 2021); it is noted that there is value in confirming phenotypic differences between naive CD5lo and CD5hi CD8 T cells in the NOD background. It is important to contextualize the data while being wary of making parallels with results obtained from CD5lo and CD5hi CD4 T cells. There should also be additional attention paid to the wording in the text describing the data (e.g, the authors assert that, in Figure 4C, the "CD5hi group exhibited higher percentages of CD8+ T cells producing TNF-α, IFN-γ and IL-2" though there is no difference in IL-2 nor consistent differences in TNF-α between the CD5lo and CD5hi populations).
(2) The comparison of a marker of self-reactivity, CD5 in this case, on broad thymocyte populations (DN/DP/CD8SP) is cautioned (Figure 5). CD5 is upregulated with signals associated with b-selection and positive selection; CD5 levels will thus vary even among subsets within these broad developmental intermediates. This is a particularly important consideration when comparing CD5 across thymic intermediates in polyclonal versus TCR transgenic thymocytes due to the striking differences in thymic selection efficiency, resulting in different developmental population profiles. The higher levels of CD5 noted in the DN population of NOD8.3 mice, for example, is likely due to the shift towards more mature DN4 post-b-selection cells (Figure 5E, Supplementary Figure 3A). Similarly, in the DP population, the larger population of post-positive selection cells in the NOD8.3 transgenic thymus may also skew CD5 levels significantly (Figure 5F, Supplementary Figure 3A). Overall, the reported differences between NOD and NOD8.3 thymocyte subsets could be due largely to differences in differentiation/maturation stage rather than affinity for self-antigen during T cell development. The lack of differences in CD5 levels of CD8 SP thymocytes (Fig. 5B) and CD8 T cells in the pancreas draining lymph nodes (Fig. 6B) from NOD vs NOD8.3 mice also raises questions about the relevance of this model to address the question of basal self-reactivity and diabetogenicity; the phenotype of the CD8 T cells that were analyzed in the pancreas draining lymph nodes is not clear (i.e., are these gated on naive T cells?). Furthermore, the rationale for the comparison with NOD-BDC2.5 mice that carry an MHC II-restricted TCR is unclear.
(3) In reference to the conclusion that transgenic Pep phosphatase does not inhibit the diabetogenic potential of "CD5hi" CD8 T cells, there is some concern that comparing diabetes development in mice receiving polyclonal versus TCR transgenic T cells specific for an islet antigen is not appropriate. The increased frequency and number of antigen-specific T cells in the NOD8.3 mice may be responsible for some of the observed differences. Further justification for the comparison is suggested.
(4) There is an interesting observation that TCR sequences from the CD5hi CD8 T cells may share some characteristics with diabetogenic T cells found in patients (e.g., CDR3 length) and that IGFP-specific T cells may be preferentially found within the CD5hi naive CD8 T cell population. However, there are questions about the reproducibility of the TCR sequencing data given the low number of replicates and sampling size. In particular, the TRAV, TRAJ, TRBV, and TRBJ frequency is variable across sequencing runs. Is this data truly representative of the overall TCR repertoire of CD5hi vs CD5lo CD8 T cells?
(5) For clarity and transparency, please consider:<br /> ● Naïve T cell gating/sorting is not always clear.<br /> ● Additional controls should be considered for tetramer and cytokine stains/gating, in particular.<br /> ● The reporting of the percentage of cells expressing a certain marker (e.g., activation marker) and gMFI of this marker is often used interchangeably. Reporting gMFI is most appropriate for unimodal populations (normal distribution), but some of the populations for which gMFI is reported are bimodal (e.g., DN CD5 in Supplementary Figure 3D, etc.). The figure legends throughout the paper do not clearly explain the gating strategy when reporting gMFI. When reporting frequency, the reference population is often unclear (% of parent population, % of naive CD8 T cells, etc.).<br /> ● Several items are missing or incorrectly described in the methods section; for example:<br /> --EdU incorporation assay presented in Supplementary Figure 4.<br /> --Construction of the Overlapped Count Matrix in Figure 7G.<br /> --Clonality, Pielou's evenness, richness, and medium metrics, although reported in the methods, are not shown in any of the figures as far as noted.
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Reviewer #1 (Public Review):
Summary:
The authors aimed to elucidate the cytological mechanisms by which conjugated linoleic acids (CLAs) influence intramuscular fat deposition and muscle fiber transformation in pig models. Utilizing single-nucleus RNA sequencing (snRNA-seq), the study explores how CLA supplementation alters cell populations, muscle fiber types, and adipocyte differentiation pathways in pig skeletal muscles.
Strengths:
Innovative approach: The use of snRNA-seq provides a high-resolution insight into the cellular heterogeneity of pig skeletal muscle, enhancing our understanding of the intricate cellular dynamics influenced by nutritional regulation strategy.
Robust validation: The study utilizes multiple pig models, including Heigai and Laiwu pigs, to validate the differentiation trajectories of adipocytes and the effects of CLA on muscle fiber type transformation. The reproducibility of these findings across different (nutritional vs genetic) models enhances the reliability of the results.
Advanced data analysis: The integration of pseudotemporal trajectory analysis and cell-cell communication analysis allows for a comprehensive understanding of the functional implications of the cellular changes observed.
Practical relevance: The findings have significant implications for improving meat quality, which is valuable for both the agricultural and food industry.
Weaknesses:
Model generalizability: While pigs are excellent models for human physiology, the translation of these findings to human health, especially in diverse populations, needs careful consideration.
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Reviewer #1 (Public Review):
Summary:
The study investigates the impact of Clonal Hematopoiesis of Indeterminate Potential (CHIP) on Immune Checkpoint Inhibitor (ICI) therapy outcomes in NSCLC patients, analyzing blood samples from 100 patients pre- and post-ICI therapy for CHIP, and conducting single-cell RNA sequencing (scRNA-seq) of PBMCs in 63 samples, with validation in 180 more patients through whole exome sequencing. Findings show no significant CHIP influence on ICI response, but a higher CHIP prevalence in NSCLC compared to controls, and a notable CHIP burden in squamous cell carcinoma. Severely affected CHIP groups showed NF-kB pathway gene enrichment in myeloid clusters.
Strengths:
The study is commendable for analyzing a significant cohort of 100 patients for CHIP and utilizing scRNA-seq on 63 samples, showcasing the use of cutting-edge technology.
The study tackles the vital clinical question of predicting ICI therapy outcomes in NSCLC.
Weaknesses:
The manuscript's comparison of CHIP prevalence between NSCLC patients and healthy controls could be strengthened by providing more detailed information on the control group. Specifically, details such as sex, smoking status, and comorbidities are needed to ensure the differences in CHIP are attributable to lung cancer rather than other factors. Including these details, along with a comparative analysis of demographics and comorbidities between both groups and clarifying how the control group was selected, would enhance the study's credibility and conclusions.
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Reviewer #1 (Public Review):
Summary:
This research article by Nath et al. from the Lee Lab addresses how lipolysis under starvation is achieved by a transient receptor potential channel, TRPγ, in the neuroendocrine neurons to help animals survive prolonged starvation. Through a series of genetic analyses, the authors identify that TRPγ mutations specifically lead to a failure in lipolytic processes under starvation, thereby reducing animals' starvation resistance. The conclusion was confirmed through total triacylglycerol levels in the animals and lipid droplet staining in the fat bodies. This study highlights the importance of transient receptor potential (TRP) channels in the fly brain to modulate energy homeostasis and combat metabolic stress. While the data is compelling and the message is easy to follow, several aspects require further clarification to improve the interpretation of the research and its visibility in the field.
Strengths:
This study identifies the biological meaning of TRPγ in promoting lipolysis during starvation, advancing our knowledge about TRP channels and the neural mechanisms to combat metabolic stress. Furthermore, this study demonstrates the potential of the TRP channel as a target to develop new therapeutic strategies for human metabolic disorders by showing that metformin and AMPK pathways are involved in its function in lipid metabolisms during starvation in Drosophila.
Weaknesses:
Some key results that might strengthen their conclusions were left out for discussion or careful explanation (see below). If the authors could improve the writing to address their findings and connect their findings with conclusions, the research would be much more appreciated and have a higher impact in the field.
Here, I listed the major issues and suggestions for the authors to improve their manuscript:
(1) Are the increased lipid droplet size and the upregulated total TAG level measured in the starved or sated mutant in Figure 1? This information might be crucial for readers to understand the physiological function of TRP in lipid metabolism. In other words, clarifying whether the upregulated lipid storage is observed only in the starved trp mutant will advance our knowledge of TRPγ. If the increase of total TAG level is only observed in the starved animals, TRP in the Dh44 neurons might serve as a sensor for the starvation state required to promote lipolysis in starvation conditions. On the other hand, if the total TAG level increases in both starved and sated animals, activation of Dh44 through TRPγ might be involved in the lipid metabolism process after food ingestion.
(2) It is unclear how AMPK activation in Dh44 neurons reduces the total triacylglycerol (TAG) levels in the animals (Figure 3G). As AMPK is activated in response to metabolic stress, the result in Figure 3G might suggest that Dh44 neurons sense metabolic stress through AMPK activation to promote lipolysis in other tissues. Do Dh44 neurons become more active during starvation? Is activation of Dh44 neurons sufficient to activate AMPK in the Dh44 neurons without starvation? Is activation of AMPK in the Dh44 neurons required for Dh44 release and lipolysis during starvation? These answers would provide more insights into the conclusion in Lines 192-193.
(3) It is unclear how the lipolytic gene brummer is further downregulated in the trpγ mutant during starvation while brummer is upregulated in the control group (Figure 6A). This result implies that the trpγ mutant was able to sense the starvation state but responded abnormally by inhibiting the lipolytic process rather than promoting lipolysis, which makes it more susceptible to starvation (Figure 3B).
(4) There is an inconsistency of total TAG levels and the lipid droplet size observed in the Dh44 mutant but not in the Dh44-R2 mutant (Figures 7A and 7F). This inconsistency raises a possibility that the signaling pathway from Dh44 release to its receptor Dh44-R2 only accounts for part of the lipid metabolic process under starvation. Adding discussion to address this inconsistency may be helpful for readers to appreciate the finding.
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Reviewer #1 (Public Review):
This work from Cui, Pan, Fan, et al explores memory impairment in chronic pain mouse models, a topic of great interest in the neurobiology field. In particular, the work starts from a very interesting observation, that WT mice can be divided into susceptible and unsusceptible to memory impairment upon modelling chronic pain with CCI. This observation represents the basis of the work where the authors identify the sphingosine receptor S1PR1 as down-regulated in the dentate gyrus of susceptible animals and demonstrate through an elegant range of experiments involving AAV-mediated knockdown or overexpression of S1PR1 that this receptor is involved in the memory impairment observed with chronic pain. Importantly for translational purposes, they also show that activation of S1PR1 through a pharmacological paradigm is able to rescue the memory impairment phenotype.
The authors also link these defects to reduced dendritic branching and a reduced number of mature excitatory synapses in the DG to the memory phenotype.
They then proceed to explore possible mechanisms downstream of S1PR1 that could explain this reduction in dendritic spines. They identify integrin α2 as an interactor of S1PR1 and show a reduction in several proteins involved in actin dynamic, which is crucial for dendritic spine formation and plasticity.
They thus hypothesize that the interaction between S1PR1 and Integrin α2 is fundamental for the activation of Rac1 and Cdc42 and consequently for the polymerisation of actin; a reduction in this pathway upon chronic pain would thus lead to impaired actin polymerisation, synapse formation, and thus impaired memory.
The work is of great interest and the experiments are of very good quality with results of great importance. I have however some concerns. The main concern I have relates to the last part of the work, namely Figures 8 and 9, which I feel are not at the same level as the results presented in the previous 7 Figures, which are instead outstanding.
In particular:
- In Figure 8, given the reduction in all the proteins tested, the authors need to check some additional proteins as controls. One good candidate could be RhoA, considering the authors say it is activated by S1PR2 and not by S1PR1;
- In addition to the previous point, could the authors also show that the number of neurons is not grossly different between susceptible and unsusceptible mice? This could be done by simply staining for NeuN or performing a western blot for a neuronal-specific protein (e.g. Map2 or beta3-tubulin);
- In Figure 8, the authors should also evaluate the levels of activated RAC1 and activated Cdc42, which are much more important than just basal levels of the proteins to infer an effect on actin dynamics. This is possible through kits that use specific adaptors to pulldown GTP-Rac1 and GTP-Cdc42;
- In Figure 9C, the experiment is performed in an immortalised cell line. I feel this needs to be performed at least in primary hippocampal neurons;
- In Figure 9D, the authors use a Yeast two-hybrid system to demonstrate the interaction between S1PR1 and Integrin α2. However, as the yeast two-hybrid system is based on the proximity of the GAL4 activating domain and the GAL4 binding domain, which are used to activate the transcription of reporter genes, the system is not often used when probing the interaction between transmembrane proteins. Could the authors use other transmembrane proteins as negative controls?;
- In Figure 9E, the immunoblot is very unconvincing. The bands in the inputs are very weak for both ITGA2 and S1PR1, the authors do not show the enrichment of S1PR1 upon its immunoprecipitation and the band for ITGA2 in the IP fraction has a weird appearance. Were these experiments performed on DG lysates only? If so, I suggest the authors repeat the experiment using the whole brain (or at least the whole hippocampus) so as to have more starting material. Alternatively, if this doesn't work, or in addition, they could also perform the immunoprecipitation in heterologous cells overexpressing the two proteins;
- About the point above, even if the results were convincing, the authors can't say that they demonstrate an interaction in vivo. In co-IP experiments, the interaction is much more likely to occur in the lysate during the incubation period rather than being conserved from the in vivo state. These co-IPs demonstrate the ability of proteins to interact, not necessarily that they do it in vivo. If the authors wanted to demonstrate this, they could perform a Proximity ligation assay in primary hippocampal neurons, using antibodies against S1PR1 and ITGA2.
- In Figure 9H, could the authors increase the N to see if shItga2 causes further KD in the CCI?
- To conclusively demonstrate that S1PR1 and ITGA2 participate in the same pathway, they could show that knocking down the two proteins at the same time does not have additive effects on behavioral tests compared to the knockdown of each one of them in isolation.
Other major concerns:
- Supplementary Figure 5: the image showing colocalisation between S1PR1 and CamKII is not very convincing. Is the S1PR1 antibody validated on Knockout or knockdown in immunostaining?;
- It would be interesting to check S1PR2 levels as a control in CCI-chronic animals;
- Figure 1: I am a bit concerned about the Ns in these experiments. In the chronic pain experiments, the N for Sham is around 8 whereas is around 20 for CCI animals. Although I understand higher numbers are necessary to see the susceptible and unsusceptible populations, I feel that then the same number of Sham animals should be used;
- Figures 1E and 1G have much higher Ns than the other panels. Why is that? If they have performed this high number of animals why not show them in all panels?;
- In the experiments where viral injection is performed, the authors should show a zoomed-out image of the brain to show the precision of the injection and how spread the expression of the different viruses was;
- The authors should check if there is brain inflammation in CCI chronic animals. This would be interesting to explain if this could be the trigger for the effects seen in neurons. In particular, the authors should check astrocytes and microglia. This is of interest also because the pathways altered in Figure 8A are related to viral infection;
- If the previous point shows increased brain inflammation, it would be interesting for the authors to check whether a prolonged anti-inflammatory treatment in CCI animals administered before the insurgence of memory impairment could stop it from happening;
- In addition, the authors should speculate on what could be the signal that can induce these molecular changes starting from the site of injury;
- Also, as the animals are all WT, the authors should speculate on what could render some animals prone to have memory impairments and others resistant.
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Reviewer #1 (Public Review):
The paper proposes an interesting perspective on the spatio-temporal relationship between FC in fMRI and electrophysiology. The study found that while similar network configurations are found in both modalities, there is a tendency for the networks to spatially converge more commonly at synchronous than asynchronous time points. However, my confidence in the findings and their interpretation is undermined by an apparent lack of justification for the expected outcomes for each of the proposed scenarios, and in the analysis pipeline itself.
Main Concerns
(1) Figure 1 makes sense to me conceptually, including the schematics of the trajectories, i.e.<br /> Scenario 1: Temporally convergent, same trajectories through connectome state space<br /> Scenario 2: Temporally divergent, different trajectories through connectome state space
However, based on my understanding I am concerned that these scenarios do not necessarily translate into the schematic CRP plots shown in Figure 2C, or the statements in the main text:
For Scenario 1: "epochs of cross-modal spatial similarity should occur more frequently at on-diagonal (synchronous) than off-diagonal (asynchronous) entries, resulting in an on-/off-diagonal ratio larger than unity"<br /> For Scenario 2: "epochs of spatial similarity could occur equally likely at on-diagonal and off-diagonal entries (ratio≈1)"
Where do the authors get these statements and the schematics in Figure 2C from? Are they based on previous literature, theory, or simulations?<br /> I am not convinced based on the evidence currently in the paper, that the ratio of off- to on-diagonal entries (and under what assumptions) is a definitive way to discriminate between scenarios 1 and 2.
For example, what about the case where the same network configuration reoccurs in both modalities at multiple time points? It seems to me that one would get a CRP with entries occurring equally on the on-diagonal as on the off-diagonal, regardless of whether the dynamics are matched between the two modalities or not (i.e. regardless of scenario 1 or 2 being true).
This thought experiment example might have a flaw in it, and the authors might ultimately be correct, but nonetheless, a systematic justification needs to be provided for using the ratio of off- to on-diagonal entries to discriminate between scenarios 1 and 2 (and under what assumptions it is valid).
In the absence of theory, a couple of ways I can think of to gain insight into this key aspect are:
(1) Use surrogate data for scenarios 1 and 2:<br /> a. For scenario 1: Run the CRP using a single modality. E.g. feed in the EEG into the analysis as both modality 1 AND modality 2. This should provide at least one example of CRP under scenario 1 (although it does not ensure that all CRPs under this scenario will look like this, it is at least a useful sanity check)<br /> b. For scenario 2: Run the CRP using a single modality plus a shuffled version. E.g. feed in the EEG into the analysis as both modality 1 AND a temporally shuffled version of the EEG as modality 2. The temporal shuffling of the EEG could be done by simply splitting the data into blocks of say ~10s and then shuffling them into a new order. This should provide a version of the CRP under scenario 2 (although it does not ensure that all CRPs under this scenario will look like this, it is at least a useful sanity check).
(2) Do simulations, with clearly specified assumptions, for scenarios 1 and 2. One way of doing this is to use a simplified (state-space) setup and randomly simulate N spatially fixed networks that are independently switching on and off over time (i.e. "activation" is 0 or 1). Note that this would result in a N-dimensional connectome state space.
The authors would only need to worry about simulating the network activation time courses, i.e. they would not need to bother with specifying the spatial configuration of each network, instead, they would make the implied assumption that each of these networks has the same spatial configuration in modality 1 and modality 2.
With that assumption, the CRP calculation should simply correspond to calculating, at each time i in modality 1 and time j in modality 2, the number of networks that are activating in both modality 1 and modality 2, by using their activation time courses. Using this, one can simulate and compute the CRPs for the two scenarios:<br /> a. Scenario 1: where the simulated activation timecourses are set to be the same between both modalities<br /> b. Scenario 2: where the simulated activation timecourses are simulated separately for each of the modalities
(2) Choices in the analysis pipeline leading up to the computation of FC in fMRI or EEG will affect the quality of information available in the FC. For example, but not only, the choice of parcellation (in the study, the number of parcels is very high given the number of EEG sensors). I think it is important that we see the impact of the chosen pipeline on the time-averaged connectomes, an output that the field has some idea about what is sensible. This would give confidence that the information being used in the main analyses in the paper is based on a sensible footing and relates to what the field is used to thinking about in terms of FC. This should be trivial to compute, as it is just a case of averaging the time-varying FCs being used for the CRP over all time points. Admittedly, this approach is less useful for the intracranial EEG.
(3) Leakage correction. The paper states: "To mitigate this issue, we provide results from source-localized data both with and without leakage correction (supplementary and main text, respectively)." Given that FC in EEG is dominated by spatial leakage (see Hipp paper), then I cannot see how it can be justified to look at non-spatial leakage correction results at all, let alone put them up front as the main results. All main results/figures for the scalp EEG should be done using spatial leakage-corrected EEG data.
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Reviewer #1 (Public Review):
Summary:
Shen et al. conducted three experiments to study the cortical tracking of the natural rhythms involved in biological motion (BM), and whether these involve audiovisual integration (AVI). They presented participants with visual (dot) motion and/or the sound of a walking person. They found that EEG activity tracks the step rhythm, as well as the gait (2-step cycle) rhythm. The gait rhythm specifically is tracked superadditively (power for A+V condition is higher than the sum of the A-only and V-only condition, Experiments 1a/b), which is independent of the specific step frequency (Experiment 1b). Furthermore, audiovisual integration during tracking of gait was specific to BM, as it was absent (that is, the audiovisual congruency effect) when the walking dot motion was vertically inverted (Experiment 2). Finally, the study shows that an individual's autistic traits are negatively correlated with the BM-AVI congruency effect.
Strengths:
The three experiments are well designed and the various conditions are well controlled. The rationale of the study is clear, and the manuscript is pleasant to read. The analysis choices are easy to follow, and mostly appropriate.
Weaknesses:
I only have one potential worry. The analysis for gait tracking (1 Hz) in Experiment 2 (Figures 3a/b) starts by computing a congruency effect (A/V stimulation congruent (same frequency) versus A/V incongruent (V at 1 Hz, A at either 0.6 or 1.4 Hz), separately for the Upright and Inverted conditions. Then, this congruency effect is contrasted between Upright and Inverted, in essence computing an interaction score (Congruent/Incongruent X Upright/Inverted). Then, the channels in which this interaction score is significant (by cluster-based permutation test; Figure 3a) are subselected for further analysis. This further analysis is shown in Figure 3b and described in lines 195-202. Critically, the further analysis exactly mirrors the selection criteria, i.e. it is aimed at testing the effect of Congruent/Incongruent and Upright/Inverted. This is colloquially known as "double dipping", the same contrast is used for selection (of channels, in this case) as for later statistical testing. This should be avoided, since in this case even random noise might result in a significant effect. To strengthen the evidence, either the authors could use a selection contrast that is orthogonal to the subsequent statistical test, or they could skip either the preselection step or the subsequent test. (It could be argued that the test in Figure 3b and related text is not needed to make the point - that same point is already made by the cluster-based permutation test.)
Related to the above: the test for the three-way interaction (lines 211-216) is reported as "marginally significant", with a p-value of 0.087. This is not very strong evidence.
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Reviewer #1 (Public Review):
Summary:
In the paper, the authors study whether the number of deaths in cancer patients in the USA went up or down during the first year (2020) of the COVID-19 pandemic. They found that the number of deaths with cancer mentioned on the death certificate went up, but only moderately. In fact, the excess with-cancer mortality was smaller than expected if cancer had no influence on the COVID mortality rate and all cancer patients got COVID with the same frequency as in the general population. The authors conclude that the data are consistent with cancer not being a risk factor for COVID and that cancer patients were likely actively shielding themselves from COVID infections.
Strengths:
The paper studies an important topic and uses sound statistical and modeling methodology. It analyzes both, deaths with cancer listed as the primary cause of death, as well as deaths with cancer listed as one of the contributing causes. The authors argue, correctly, that the latter is a more important and reliable indicator to study relationships between cancer and COVID. The authors supplement their US-wide analysis with analysing three states separately.
For comparison, the authors study excess mortality from diabetes and from Alzheimer's disease. They show that Covid-related excess mortality in these two groups of patients was expected to be much higher (than in cancer patients), and indeed that is what the data showed.
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Reviewer #1 (Public Review):
Summary:
Codol et al. present a toolbox that allows simulating biomechanically realistic effectors and training Artificial Neural Networks (ANNs) to control them. The paper provides a detailed explanation of how the toolbox is structured and several examples demonstrating its utility.
Main comments:
(1) The paper is well-written and easy to follow. The schematics facilitate understanding of the toolbox's functionality, and the examples give insight into the potential results users can achieve.
(2) The toolbox's latest version, developed in PyTorch, is expected to offer greater benefits to the community.
(3) The new API, being compatible with Gymnasium, broadens the toolbox's application scope, enabling the use of Reinforcement Learning for training the ANNs.
Impact:
MotorNet is designed to simplify the process of simulating complex experimental setups, enabling the rapid testing of hypotheses on how the brain generates specific movements. Implemented in PyTorch and compatible with widely-used machine learning toolboxes, including Gymnasium, it offers an end-to-end pipeline for training ANNs on simulated setups. This can greatly assist experimenters in determining the focus of their subsequent efforts.
Additional context:
The main outcome of the work, a toolbox, is supplemented by a GitHub repository and a documentation webpage. Both the repository and the webpage are well-organized and user-friendly. The webpage guides users through the toolbox installation process, as well as the construction of effectors and Artificial Neural Networks (ANNs).
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Reviewer #1 (Public Review):
Summary:
The global decline of amphibians is primarily attributed to deadly disease outbreaks caused by the chytrid fungus, Batrachochytrium dendrobatidis (Bd). It is unclear whether and how skin-resident immune cells defend against Bd. Although it is well known that mammalian mast cells are crucial immune sentinels in the skin and play a pivotal role in immune recognition of pathogens and orchestrating subsequent immune responses, the roles of amphibian mast cells during Bd infections is largely unknown. The current study developed a novel way to enrich X. laevis skin mast cells by injecting the skin with recombinant stem cell factor (SCF), a KIT ligand required for mast cell differentiation and survival. The investigators found an enrichment of skin mast cells provides X. laevis substantial protection against Bd and mitigates the inflammation-related skin damage resulting from Bd infection. Additionally, the augmentation of mast cells leads to increased mucin content within cutaneous mucus glands and shields frogs from the alterations to their skin microbiomes caused by Bd.
Strengths:
This study underscores the significance of amphibian skin-resident immune cells in defenses against Bd and introduces a novel approach to examining interactions between amphibian hosts and fungal pathogens.
Weaknesses:
The main weakness of the study is lack of functional analysis of X. laevis mast cells. Upon activation, mast cells have the characteristic feature of degranulation to release histamine, serotonin, proteases, cytokines, and chemokines, etc. The study should determine whether X. laevis mast cells can be degranulated by two commonly used mast cell activators IgE and compound 48/80 for IgE-dependent and independent pathway. This can be easily done in vitro. It is also important to assess whether in vivo these mast cells are degranulated upon Bd infection using avidin staining to visualize vesicle releases from mast cells. Figure 3 only showed rSCF injection caused an increase in mast cells in naïve skin. They need to present whether Bd infection can induce mast cell increase and rSCF injection under Bd infection causes a mast cell increase in the skin. In addition, it is unclear how the enrichment of mast cells provides the protection against Bd infection and alternations to skin microbiomes after infection. It is important to determine whether skin mast cell release any contents mentioned above.
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Reviewer #1 (Public Review):
The authors tested whether anterior insular cortex neurons that increase or decrease firing during fear behavior, freezing, bidirectionally control fear via separate, anatomically defined outputs. Using a fairly simple behavior where mice were exposed to tone-shock pairings, they found roughly equal populations that increased or decreased firing during freezing. They next tested whether these distinct populations also had distinct outputs. Using retrograde tracers they found that the anterior insular cortex contains non-overlapping neurons which project to the mediodorsal thalamus or amygdala. Mediodorsal thalamus-projecting neurons tended to cluster in deep cortical layers, while amygdala-projecting neurons were primarily in more superficial layers. Stimulation of insula-thalamus projection decreased freezing behavior, and stimulation of insula-amygdala projections increased fear behavior. Given that the neurons which increased firing were located in deep layers, that thalamus projections occurred in deep layers, and that stimulation of insula-thalamus neurons decreased freezing, the authors concluded that the increased-firing neurons were likely thalamic projections. Similarly, given that decreased-firing neurons tended to occur in more superficial layers, that insula-amygdala projections were primarily superficial, and that insula-amygdala stimulation increased freezing behavior, authors concluded that the decreased firing cells were likely amygdala projections. The study has several strengths though also some caveats. Overall, the authors provide a valuable contribution to the field by demonstrating bidirectional control of behavior, linking the underlying anatomy and physiology.
Strengths:
The potential link between physiological activity, anatomy, and behavior is well laid out and is an interesting question. The activity contrast between the units that increase/decrease firing during freezing is clear.
It is nice to see the recording of extracellular spiking activity, which provides a clear measure of neural output, whereas similar studies often use bulk calcium imaging, a signal which rarely matches real neural activity even when anatomy suggests it might.
Weaknesses:
The link between spiking, anatomy, and behavior requires assumptions/inferences: the anatomically/genetically defined neurons which had distinct outputs and opposite behavioral effects can only be assumed the increased/decreased spiking neurons, based on the rough area of cortical layer they were recorded. This is, of course, discussed as a future experiment.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The main goal of the authors was to study the testis-specific role of the protein FBXO24 in the formation and function of the ribonucleoprotein granules (membrane-less electron-dense structures rich in RNAs and proteins).
Strengths:
The wide variety of methods used to support their conclusions (including transgenic models)
Weaknesses:
The complex phenotype observed, in some situations, cannot be fully explained by the experiments presented by the authors (i.e., AR or the tail structure).
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors have initiated studies to understand the molecular mechanisms underlying the devolvement of multi drug resistance in clinical Mtb strains. They demonstrate the association of isoniazid resistant isolates by rifampicin treatment supporting the idea that selection of MDR is a microenvironment phenomenon and involves a group of isolates.
Strengths:
The methods used in this study are robust and the results support the authors claims to a major extent.<br /> The language has now been corrected and is better to comprehend.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Dipasree Hajra et al demonstrated that Salmonella was able to modulate the expression of Sirtuins (Sirt1 and Sirt3) and regulate the metabolic switch in both host and Salmonella, promoting its pathogenesis. The authors found Salmonella infection induced high levels of Sirt1 and Sirt3 in macrophages, which were skewed toward the M2 phenotype allowing Salmonella to hyper-proliferate. Mechanistically, Sirt1 and Sirt3 regulated the acetylation of HIF-1alpha and PDHA1, therefore mediating Salmonella-induced host metabolic shift in the infected macrophages. Interestingly, Sirt1 and Sirt3-driven host metabolic switch also had an effect on the metabolic profile of Salmonella. Counterintuitively, inhibition of Sirt1/3 led to increased pathogen burdens in an in vivo mouse model. Overall, this is a well-designed study.
Comments on revised version:
The authors have performed additional experiments to address the discrepancy between in vitro and in vivo data. While this offers some potential insights into the in vivo role of Sirt1/3 in different cell types and how this affects bacterial growth/dissemination, I still believe that Sirt1/3 inhibitors could have some effect on the gut microbiota contributing to increased pathogen counts. This possibility can be discussed briefly to give a better scenario of how Sirt1/3 inhibitors work in vivo. Additionally, the manuscript would improve significantly if some of the flow cytometry analysis and WB data could be better analyzed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
The authors indicated that the adherence of ETEC is to intestinal epithelial cells. However, it is also possible that the majority of ETEC may reside in the intestinal mucus, particularly under in vivo infection condition. The colonization of ETEC in the jejunum and colon of piglets (Fig 2C) and in the intestines of mice (Fig S2A) does not necessarily reflect the adherence of ETEC to epithelial cells. Please verify these observations with other methods, such as immunostaining. Also, while Salmonella enterica serovar Typhimurium or Listeria monocytogenes can invade organoids within 1 hour, it is unknown if ETEC invade into organoids in this study. Clarifying this will help resolve if A. muciniphila block the adherence and/or invasion of ETEC. Please also address if A. muciniphila metabolites could prevent ETEC infection in the organoid models.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Using the UK Biobank, this study assessed the value of nuclear magnetic resonance measured metabolites as predictors of progression to diabetes. The authors identified a panel of 9 circulating metabolites that improved the ability in risk prediction of progression from prediabetes to diabetes. In general, this is a well-performed study, and the findings may provide a new approach to identifying those at high risk of developing diabetes.
I have some comments that may improve the importance of this study.
(1) It is unclear why the authors only considered the top 20 variables in the metabolite selection and why they did not set a wider threshold.
(2) The methods section would benefit from a more detailed exposition of how parameter tuning was conducted and the range of parameters explored during the training of the RSF model.
(3) It is hard to understand the meaning of the decision curve analysis and the clinical implications behind the net benefit, which are required to clarify the application values of models.
(4) Notably, the NMR platform utilized within the UK Biobank primarily focused on lipid species. This limitation should be discussed in the manuscript to provide context for interpreting the results and acknowledge the potential bias from the measuring platform.
(5) The manuscript should explain the potential influence of non-fasting status on the findings, particularly concerning lipoprotein particles and composition. There should be a detailed discussion of how non-fasting status may impact the measurement and the findings.
(6) Cross-platform standardization is an issue in metabolism, and further descriptions of quality control are recommended.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Recent studies have used optical or electrophysiological techniques to chronically measure receptive field properties of sensory cortical neurons over long time periods, i.e. days to weeks, to ask whether sensory receptive fields are stable properties. Akritas et al expand on prior studies by investigating whether nonlinear contextual sensitivity, a property not previously investigated in the context of so-called 'representational drift,' remains stable over days or weeks of recording. They performed chronic tetrode recordings of auditory cortical neurons over at least five recording days while also performing daily measurements of both the linear spectro-temporal receptive field (principal receptive field, PRF) and non-linear 'contextual gain field' (CGF), which captures the neuron's sensitivity to acoustic context. They found that spike waveforms could be reliably matched even when recorded weeks apart. In well-matched units, by comparing the correlation between tuning within one day's session to sessions across days, both PRFs and CGFs showed remarkable stability over time. This was the case even when recordings were performed over weeks. Meanwhile, behavioral and brain state, measured with locomotion and pupil diameter, respectively, resulted in small but significant shifts in the ability of the PRF/CGF model to predict fluctuations in the neuronal response over time.
Strengths:
The study addresses a fundamental question, which is whether the neural underpinnings of sensory perception, which encompasses both sensory events and their context, are stable across relevant timescales over which our experiences must be stable, despite biological turnover. Although two-photon calcium imaging is ideal for identifying neurons stably regardless of their activity levels and tuning, it lacks temporal precision and is therefore limited in its ability to capture the complexity of sensory responses. Akritas et al performed painstaking chronic extracellular recordings in the auditory cortex with the temporal resolution to investigate complex receptive field properties, such as neural sensitivities to acoustic context. Prior studies, particularly in the auditory cortex, focused on basic tuning properties or sensory responsivity, but Akritas et al expand on this work by showing that even the nonlinear, contextual elements of sensory neurons' responses can remain stable, providing a mechanism for the stability of our complex perception. This work is both novel and broadly applicable to those investigating cortical stability across sensory modalities.
Weaknesses:
Apart from some aspects such as single-unit versus multi-unit, the study largely treats their dataset as a monolith rather than showing how factors such as firing rate, depth, and cell type could define more or less stable subpopulations. It is likely that their methodology did not enable an even sampling over these qualities, and the authors should discuss these biases to put their findings more in context with related studies.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, the authors explored how galanin affects whole-brain activity in larval zebrafish using wide-field Ca2+ imaging, genetic modifications, and drugs that increase brain activity. The authors conclude that galanin has a sedative effect on the brain under normal conditions and during seizures, mainly through the galanin receptor 1a (galr1a). However, acute "stressors(?)" like pentylenetetrazole (PTZ) reduce galanin's effects, leading to increased brain activity and more seizures. The authors claim that galanin can reduce seizure severity while increasing seizure occurrence, speculated to occur through different receptor subtypes. This study confirms galanin's complex role in brain activity, supporting its potential impact on epilepsy.
Strengths:
The overall strength of the study lies primarily in its methodological approach using whole-brain Calcium imaging facilitated by the transparency of zebrafish larvae. Additionally, the use of transgenic zebrafish models is an advantage, as it enables genetic manipulations to investigate specific aspects of galanin signaling. This combination of advanced imaging and genetic tools allows for addressing galanin's role in regulating brain activity.
Weaknesses:
The weaknesses of the study also stem from the methodological approach, particularly the use of whole-brain Calcium imaging as a measure of brain activity. While epilepsy and seizures involve network interactions, they typically do not originate across the entire brain simultaneously. Seizures often begin in specific regions or even within specific populations of neurons within those regions. Therefore, a whole-brain approach, especially with Calcium imaging with inherited limitations, may not fully capture the localized nature of seizure initiation and propagation, potentially limiting the understanding of Galanin's role in epilepsy.
Furthermore, Galanin's effects may vary across different brain areas, likely influenced by the predominant receptor types expressed in those regions. Additionally, the use of PTZ as a "stressor" is questionable since PTZ induces seizures rather than conventional stress. Referring to seizures induced by PTZ as "stress" might be a misinterpretation intended to fit the proposed model of stress regulation by receptors other than Galanin receptor 1 (GalR1).
The description of the EAAT2 mutants is missing crucial details. EAAT2 plays a significant role in the uptake of glutamate from the synaptic cleft, thereby regulating excitatory neurotransmission and preventing excitotoxicity. Authors suggest that in EAAT2 knockout (KO) mice galanin expression is upregulated 15-fold compared to wild-type (WT) mice, which could be interpreted as galanin playing a role in the hypoactivity observed in these animals.
However, the study does not explore the misregulation of other genes that could be contributing to the observed phenotype. For instance, if AMPA receptors are significantly downregulated, or if there are alterations in other genes critical for brain activity, these changes could be more important than the upregulation of galanin. The lack of wider gene expression analysis leaves open the possibility that the observed hypoactivity could be due to factors other than, or in addition to, galanin upregulation.
Moreover, the observation that in double KO mice for both EAAT2 and galanin, there was little difference in seizure susceptibility compared to EAAT2 KO mice alone further supports the idea that galanin upregulation might not be the reason for the observed phenotype. This indicates that other regulatory mechanisms or gene expressions might be playing a more pivotal role in the manifestation of hypoactivity in EAAT2 mutants.
These methodological shortcomings and conceptual inconsistencies undermine the perceived strengths of the study, and hinders understanding of Galanin's role in epilepsy and stress regulation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Tateishi et al. report a Tn-seq-based analysis of genetic requirements for growth and fitness in 8 clinical strains of Mycobacterium intracellulare Mi), and compare the findings with a type strain ATCC13950. The study finds a core set of 131 genes that are essential in all nine strains, and therefore are reasonably argued as potential drug targets. Multiple other genes required for fitness in clinical isolates have been found to be important for hypoxic growth in the type strain.
Strengths:
The study has generated a large volume of Tn-seq datasets of multiple clinical strains of Mi from multiple growth conditions, including from mouse lungs. The dataset can serve as an important resource for future studies on Mi, which despite being clinically significant remains a relatively understudied species of mycobacteria.
Weaknesses:
The paper lacks clarity in data presentation and organization. For example, some of the key data on cfu counts of clinical Mi strains in a mouse model can be presented along with the Tn-seq dataset in Figure 6, the visualization of which can be improved with volcano plots. etc. Improvement in data visualization is perhaps necessary throughout the paper.
The primary claim of the study that the clinical strains are better adapted for hypoxic growth is not well-supported by the data presented in Figure 7.
The title of the paper is misleading as the study doesn't provide any mechanistic aspect of hypoxic adaptation in Mi.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This work sought to demonstrate that gut microbiota dysbiosis may promote the colonization of mycobacteria, and they tried to prove that Nos2 down-regulation was a key mediator of such gut-lung pathogenesis transition.
Strengths:
They did large-scale analysis of RNAs in lungs to analyze the gene expression of mice upon gut dysbiosis in MS-infected mice. This might help provide an overview of gene pathways and critical genes for lung pathology in gut dysbiosis. This data is somewhat useful and important for the TB field.
Weaknesses:
(1) They did not use wide-type Mtb strain (e.g. H37Rv) to develop mouse TB infection models, and this may lead to the failure of the establishment of TB granuloma and other TB pathology icons.
(2) The usage of in vitro assays based on A542 to examine the regulation function of Nos2 expression on NO and ROS may not be enough. A542 is not the primary Mtb infection target in the lungs.
(3) They did not examine the lung pathology upon gut dysbiosis to examine the true significance of increased colonization of Mtb.
(4) Most of the studies are based on MS-infected mouse models with a lack of clinical significance.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript nicely outlines a conceptual problem with the bFAC model in A-motility, namely, how is the energy produced by the inner membrane AglRQS motor transduced through the cell wall into mechanical force on the cell surface to drive motility? To address this, the authors make a significant contribution by identifying and characterizing a lytic transglycosylase (LTG) called AgmT. This work thus provides clues and a future framework work for addressing mechanical force transmission between the cytoplasm and the cell surface.
Strengths:
(1) Convincing evidence shows AgmT functions as an LTG and, surprisingly, that mltG from E. coli complements the swarming defect of an agmT mutant.
(2) Authors show agmT mutants develop morphological changes in response to treatment with a -lactam antibiotic, mecillinam.
(3) The use of single-molecule tracking to monitor the assembly and dynamics of bFACs in WT and mutant backgrounds.
(4) The authors understand the limitations of their work and do not overinterpret their data.
Weaknesses:
(1) A clear model of AgmT's role in gliding motility or interactions with other A-motility proteins is not provided. Instead, speculative roles for how AgmT enzymatic activity could facilitate bFAC function in A-motility are discussed.
(2) Although agmT mutants do not swarm, in-depth phenotypic analysis is lacking. In particular, do individual agmT mutant cells move, as found with other swarming defective mutants, or are agmT mutants completely nonmotile, as are motor mutants?
(3) The bioinformatic and comparative genomics analysis of agmT is incomplete. For example, the sequence relationships between AgmT, MltG, and the 13 other LTG proteins in M. xanthus are not clear. Is E. coli MltG the closest homology to AgmT? Their relationships could be addressed with a phylogenetic tree and/or sequence alignments. Furthermore, are there other A-motility genes in proximity to agmT? Similarly, does agmT show specific co-occurrences with the other A-motility genes across genera/species?
(4) Related to iii, what about the functional relationship of the endogenous 13 LTG genes? Although knockout mutants were shown to be motile, presumably because AgmT is present, can overexpression of them, similar to E. coli MltG, complement an agmT mutant? In other words, why does MltG complement and the endogenous LTG proteins appear not to be relevant?
(5) Based on Figure 2B, overexpression of MltG enhances A-motility compared to the parent strain and the agmT-PAmCh complemented strain, is this actually true? Showing expanded swarming colony phenotypes would help address this question.
(6) Cell flexibility is correlated with gliding motility function in M. xanthus. Since AgmT has LTG activity, are agmT mutants less flexible than WT cells and is this the cause of their motility defect?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Li et al investigated how adjuvants such as MPLA and CpG influence antigen presentation at the level of the Antigen-presenting cell and MHCII : peptide interaction. They found that the use of MPLA or CpG influences the exogenous peptide repertoire presented by MHC II molecules. Additionally, their observations included the finding that peptides with low-stability peptide:MHC interactions yielded more robust CD4+ T cell responses in mice. These phenomena were illustrated specifically for 2 pattern recognition receptor activating adjuvants. This work represents a step forward for how adjuvants program CD4+ Th responses and provides further evidence regarding the expected mechanisms of PRR adjuvants in enhancing CD4+ T cell responses in the setting of vaccination.
Strengths:
The authors use a variety of systems to analyze this question. Initial observations were collected in an H pylori model of vaccination with a demonstration of immunodominance differences simply by adjuvant type, followed by analysis of MHC:peptide as well as proteomic analysis with comparison by adjuvant group. Their analysis returns to peptide immunization and analysis of strength of relative CD4+ T cell responses, through calculation of IC:50 values and strength of binding. This is a comprehensive work. The logical sequence of experiments makes sense and follows an unexpected observation through to trying to understand that process further with peptide immunization and its impact on Th responses. This work will premise further studies into the mechanisms of adjuvants on T cells
Weaknesses:
While MDP has a different manner of interaction as an adjuvant compared to CpG and MPLA, it is unclear why MDP has a different impact on peptide presentation and it should be further investigated, or at minimum highlighted in the discussion as an area that requires further investigation.
It is alluded by the authors that TLR activating adjuvants mediate selective, low affinity, exogenous peptide binding onto MHC class II molecules. However, this was not demonstrated to be related specifically to TLR binding. I wonder if some work with TLR deficient mice (TLR 4KO for example) could evaluate this phenomenon more specifically.
It is unclear to me if this observation is H pylori model/antigen-specific. It may have been nice to characterize the phenomenon with a different set of antigens as supplemental. Lastly, it is unclear if the peptide immunization experiment reveals a clear pattern related to high and low-stability peptides among the peptides analyzed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
SARS-CoV-2 infection induces syncytia formation, which promotes viral transmission. In this paper, the authors aimed to understand how host-derived inflammatory cytokines IL-1α/β combat SARS-CoV-2 infection.
Strengths:
First, they used a cell-cell fusion assay developed previously to identify IL-1α/β as the cytokines that inhibit syncytia formation. They co-cultured cells expressing the spike protein and cells expressing ACE2 and found that IL-1β treatment decreased syncytia formation and S2' cleavage.
Second, they investigated the IL-1 signaling pathway in detail, using knockouts or pharmacological perturbation to understand the signaling proteins responsible for blocking cell fusion. They found that IL-1 prevents cell-cell fusion through MyD88/IRAK/TRAF6 but not TAK1/IKK/NF-κB, as only knocking out MyD88/IRAK/TRAF6 eliminates the inhibitory effect on cell-cell fusion in response to IL-1β. This revealed that the inhibition of cell fusion did not require a transcriptional response and was mediated by IL-1R proximal signaling effectors.
Third, the authors identified RhoA/ROCK activation by IL-1 as the basis for this inhibition of cell fusion. By visualizing a RhoA biosensor and actin, they found a redistribution of RhoA to the cell periphery and cell-cell junctions after IL-1 stimulation. This triggered the formation of actin bundles at cell-cell junctions, preventing fusion and syncytia formation. The authors confirmed this molecular mechanism by using constitutively active RhoA and an inhibitor of ROCK.
Diverse Cell types and in vivo models were used, and consistent results were shown across diverse models. These results were convincing and well-presented.
Weaknesses:
As the authors point out in the discussion, whether IL-1-mediated RhoA activation is specific to viral infection or regulates other RhoA-regulated processes is unclear. We would also require high-magnification images of the subcellular organization of the cytoskeleton to appreciate the effect of IL-1 stimulation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Chlamydia spp. has a biphasic developmental cycle consisting of an extracellular, infectious form called an elementary body (EB) and an intracellular, replicative form known as a reticular body (RB). The structural stability of EBs is maintained by extensive cross-linking of outer membrane proteins while the outer membrane proteins of RBs are in a reduced state. The overall redox state of EBs is more oxidized than RBs. The authors propose that the redox state may be a controlling factor in the developmental cycle. To test this, alkyl hydroperoxide reductase subunit C (ahpC) was overexpressed or knocked down to examine effects on developmental gene expression. KD of ahpC induced increased expression of EB-specific genes and accelerated EB production. Conversely, overexpression of phpC delayed differentiation to EBs. The results suggest that chlamydial redox state may play a role in differentiation.
Strengths:
Uses modern genetic tools to explore the difficult area of temporal gene expression throughout the chlamydial developmental cycle.
Weaknesses:
The environmental signals triggering ahpC expression/activity are not determined.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript by Kely C. Matteucc et al. titled "Reprogramming of host energy metabolism mediated by the TNF-iNOS-HIF-1α axis plays a key role in host resistance to Plasmodium infection" describes that TNF induces HIF-1α stabilization that increases GLUT1 expression as well as glycolytic metabolism in monocytic and splenic CD11b+ cells in P. chabaudi infected mice. Also, TNF signaling plays a crucial role in host energy metabolism, controlling parasitemia, and regulating the clinical symptoms in experimental malaria.
Weaknesses:
Even though iNOS deficiency reduced the expression of the glycolytic enzymes as well as reduced GLUT1 expression and lower ECAR in splenic monocytes, there is no data to support that RNI induces the expression and stabilization of HIF-1α.
This paper involves an incredible amount of work, and the authors have done an exciting study addressing the TNF-iNOS-HIF-1α axis as a critical role in host immune defense during Plasmodium infection.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors provide a study among healthy individuals, general medical patients and patients receiving haematopoietic cell transplants (HCT) to study the gut microbiome through shotgun metagenomic sequencing of stool samples. The first two groups were sampled once, while the patients receiving HCT were sampled longitudinally. A range of metadata (including current and previous (up to 1 year before sampling) antibiotic use) was recorded for all sampled individuals. The authors then performed shotgun metagenomic sequencing (using the Illumina platform) and performed bioinformatic analyses on these data to determine the composition and diversity of the gut microbiota and the antibiotic resistance genes therein. The authors conclude, on the basis of these analyses, that some antibiotics had a large impact on gut microbiota diversity, and could select opportunistic pathogens and/or antibiotic resistance genes in the gut microbiota.
Strengths:
The major strength of this study is the considerable achievement of performing this observational study in a large cohort of individuals. Studies into the impact of antibiotic therapy on the gut microbiota are difficult to organise, perform and interpret, and this work follows state-of-the-art methodologies to achieve its goals. The authors have achieved their objectives and the conclusion they draw on the impact of different antibiotics and their impact on the gut microbiota and its antibiotic resistance genes (the 'resistome', in short), are supported by the data presented in this work.
Weaknesses:
The weaknesses are the lack of information on the different resistance genes that have been identified and which could have been supplied as Supplementary Data. In addition, no attempt is made to assess whether the identified resistance genes are associated with mobile genetic elements and/or (opportunistic) pathogens in the gut. While this is challenging with short-read data, alternative approaches like long-read metagenomics, Hi-C and/or culture-based profiling of bacterial communities could have been employed to further strengthen this work. Unfortunately, the authors have not attempted to perform corrections for multiple testing because many antibiotic exposures were correlated.
Impact:
The work may impact policies on the use of antibiotics, as those drugs that have major impacts on the diversity of the gut microbiota and select for antibiotic resistance genes in the gut are better avoided. However, the primary rationale for antibiotic therapy will remain the clinical effectiveness of antimicrobial drugs, and the impact on the gut microbiota and resistome will be secondary to these considerations.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Despite the study being a collation of important results likely to have an overall positive effect on the field, methodological weaknesses and suboptimal use of statistics make it difficult to give confidence to the study's message.
Strengths:
Relevant human and mouse models approached with in vivo and in vitro techniques.
Weaknesses:
The methodology, statistics, reagents, analyses, and manuscripts' language all lack rigour.
(1) The authors used statistics to generate P-values and Rsquare values to evaluate the strength of their findings.
However, it is unclear how stats were used and/or whether stats were used correctly. For instance, the authors write: "Gaussian distribution of all numerical variables was evaluated by QQ plots". But why? For statistical tests that fall under the umbrella of General Linear Models (line ANOVA, t-tests, and correlations (Pearson's)), there are several assumptions that ought to be checked, including typically:
(a) Gaussian distribution of residuals.
(b) Homoskedasticity of the residuals.
(c) Independence of Y, but that's assumed to be valid due to experimental design.
So what is the point of evaluating the Gaussian distribution of the data themselves? It is not necessary. In this reviewer's opinion, it is irrelevant, not a good use of statistics, and we ought to be leading by example here.
Additionally, it is not clear whether the homoscedasticity of the residuals was checked. Many of the data appear to have particularly heteroskedastic residuals. In many respects, homoscedasticity matters more than the normal distribution of the residuals. In Graphpad analyses if ANOVA is used but equal variances are assumed (when variances among groups are unequal then standard deviations assigned in each group will be wrong and thus incorrect p values are being calculated.
Based on the incomplete and/or wrong statistical analyses it is difficult to evaluate the study in greater depth.
While on the subject of stats, it is worth mentioning this misuse of statistics in Figure 3D, where the authors added the Slc34a1 transcript levels from controls in the correlation analyses, thereby driving the intercept down. Without the Control data there does not appear to be a correlation between the Slc34a1 levels and tumor size.
There is more. The authors make statements (e.g. in the figure levels as: "Correlations indicated by R2.". What does that mean? In a simple correlation, the P value is used to evaluate the strength of the slope being different from zero. The authors also give R2 values for the correlations but they do not provide R2 values for the other stats (like ANOVAs). Why not?
(2) The authors used antibodies for immunos and WBs. I checked those antibodies online and it was concerning:
(a) Many are discontinued.
(b) Many are not validated.
(c) Many performed poorly in the Immunos, e.g. FGF23, FGFR1, and Kotho are not really convincing. PO5F1 (gene: OCT4) is the one that looks convincing as it is expressed at the correct cell types.
(d) Others like NPT2A (product of gene SLC34A1) are equally unconvincing. Shouldn't the immuno show them to be in the plasma membrane?
If there is some brown staining, this does not mean the antibodies are working. If your antibodies are not validated then you ought to omit the immunos from the manuscript.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Bloomington
DOI: 10.1038/s41588-020-0695-1
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @olekpark
SciCrunch record: RRID:SCR_006457
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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7405
DOI: 10.1038/s41556-020-00626-1
Resource: (BDSC Cat# 7405,RRID:BDSC_7405)
Curator: @olekpark
SciCrunch record: RRID:BDSC_7405
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Bloomington
DOI: 10.1038/s41598-021-81894-1
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @olekpark
SciCrunch record: RRID:SCR_006457
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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51324
DOI: 10.1038/s41467-021-22927-1
Resource: (BDSC Cat# 51324,RRID:BDSC_51324)
Curator: @olekpark
SciCrunch record: RRID:BDSC_51324
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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6627
DOI: 10.1038/s41467-022-30182-1
Resource: (BDSC Cat# 6627,RRID:BDSC_6627)
Curator: @olekpark
SciCrunch record: RRID:BDSC_6627
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Bloomington
DOI: 10.1038/s41467-022-33845-1
Resource: (BDSC Cat# 59843,RRID:BDSC_59843)
Curator: @olekpark
SciCrunch record: RRID:BDSC_59843
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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18281
DOI: 10.1038/s41467-022-33748-1
Resource: BDSC_18281
Curator: @olekpark
SciCrunch record: RRID:BDSC_18281
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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2376
DOI: 10.1007/978-1-0716-3259-8_8
Resource: (BDSC Cat# 2376,RRID:BDSC_2376)
Curator: @olekpark
SciCrunch record: RRID:BDSC_2376
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www.youtube.com www.youtube.com
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A habit of the top 1% people is to make simple decisions fast, and think more carefully about the important ones.
It optimizes energy.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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34646
DOI: 10.1038/s44319-023-00017-1
Resource: (BDSC Cat# 34646,RRID:BDSC_34646)
Curator: @olekpark
SciCrunch record: RRID:BDSC_34646
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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BDSC #51324
DOI: 10.1007/978-1-0716-0712-1_22
Resource: (BDSC Cat# 51324,RRID:BDSC_51324)
Curator: @bpowell22
SciCrunch record: RRID:BDSC_51324
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors have studied the effects of platelets in OPC biology and remyelination. For this, they used mutant mice with lower levels of platelets as a demyelinating/remyelinating scenario, as well as in a model with large numbers of circulating platelets.
Strengths:
-The work is very focused, with defined objectives.<br /> -The work is properly done.
Revision comments:
Having consulted the new version of the work by Amber et al., the modifications and the point-by-point cover letter explaining them give direct answers to my previous comments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This paper reported a protocol of using human-induced pluripotent stem cells to generate cells expressing microglia-enriched genes and responding to LPS by drastically upregulation of proinflammatory cytokines. Upon subretinal transplantation in mice, hiPSC-derived cells integrated into the host retina and maintained retinal homeostasis while they responded to RPE injury by migration, proliferation, and phagocytosis. The findings revealed the potential of using hiPSC-derived cell transplantation for microglia replacement as a therapeutic strategy for retinal diseases.
Strengths:
The paper demonstrates a method of consistently generating a significant quantity of hiPSC-derived microglia-like cells for in vitro study or for in vivo transplantation. RNAseq analysis offers an opportunity for comprehensive transcriptome profiling of the derived cells. It is impressive that following transplantation, these cells were well integrated into the retina, migrated to the corresponding layers, adopted microglia-like morphologies, and survived for a long term without generating apparent harm. The work has laid a foundation for future utilization of hiPSC-derived microglia in lab and clinical applications.
Weaknesses:
(1) The primary weakness of the paper concerns its conclusion of having generated "homogenous mature microglia", partly based on the RNAseq analysis. However, the comparison of gene profiles was carried out only between "hiPSC-derived mature microglia" and the proliferating myeloid progenitors. While the transcriptome profiles revealed a trend of enrichment of microglia-like gene expression in "hiPSC-derived mature microglia" compared to proliferating myeloid progenitors, this is not sufficient to claim they are "mature microglia". It is important that one carries out a comparative analysis of the RNAseq data with those of primary human microglia, which may be done by leveraging the public database. To convincingly claim these cells are mature microglia, questions to be addressed include how similar the molecular signatures of these cells are compared with the fully differentiated primary microglia cell or if they remain progenitor-like or take on mosaic properties, and how they distinguish from macrophages.
(2) While the authors attempted to demonstrate the functional property of "hiPSC-derived mature microglia" in culture, they used LPS challenge, which is an inappropriate assay. This is because human microglia respond poorly to LPS alone but need to be activated by a combination of LPS with other factors, such as IFNγ. Their data that "hiPSC-derived mature microglia" showed robust responses to LPS indeed implicates that these cells do not behave like mature human microglia.
(3) The resolution of Figs. 4 - 6 is so low that even some of the text and labels are hardly readable. Based on the morphology shown in Fig. 4 and the statement in line 147, these hiPSC-derived "cells altered their morphology to a rounded shape within an hour of incubation and rapidly internalized the fluorescent-labeled particles". This is a peculiar response. Usually, microglia do not respond to fluorescent-labeled zymosan by turning into a rounded-shaped morphology within an hour when they internalize them. Such a behavior usually implicates weak phagocytotic capacity.
(4) Data presented in Fig. 5 are not very convincing to support that transplanted cells were immunopositive for "human CD11b (Fig.5C), as well as microglia signature markers P2ry12 and TMEM119 (Fig.5D)" (line 167). The resolution and magnification of Fig. 5D are too low to tell the colocalization of tdT and human microglial marker immunolabeling. In the flat-mount images (C, I), hCD11b immunolabeling is not visible in the GCL or barely visible in the IPL. This should be discussed.
(5) Microglia respond to injury by becoming active and losing their expression of the resting state microglial marker, such as P2ry12, which is used in Fig. 6 for the detection of migrated microglia. To confirm that these cells indeed respond to injury like native microglia, one should check for activated microglial markers and induction of pro-inflammatory cytokines in the sodium iodate-injury model.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, Behruznia and colleagues use long-read sequencing data for 335 strains of the Mycobacterium tuberculosis complex to study genome evolution in this clonal bacterial pathogen. They use both a "classical" pangenome approach that looks at the presence and absence of genes, and a more general pangenome graph approach to investigate structural variants also in non-coding regions. The two main results of the study are that (1) the MTBC has a small pangenome with few accessory genes, and that (2) pangenome evolution is driven by deletions in sublineage-specific regions of difference. Combining the gene-based approach with a pangenome graph is innovative, and the former analysis is largely sound apart from a lack of information about the data set used. The graph part, however, requires more work and currently fails to support the second main result. Problems include the omission of important information and the confusing analysis of structural variants in terms of "regions of difference", which unnecessarily introduces reference bias. Overall, I very much like the direction taken in this article, but think that it needs more work: on the one hand by simply telling the reader what exactly was done, on the other by taking advantage of the information contained in the pangenome graph.
Strengths:
The authors put together a large data set of long-read assemblies representing most lineages of the Mycobacterium tuberculosis context, covering a large geographic area. State-of-the-art methods are used to analyze gene presence-absence polymorphisms (Panaroo) and to construct a pangenome graph (PanGraph). Additional analysis steps are performed to address known problems with misannotated or misassembled genes in pangenome analysis.
Weaknesses:
The study does not quite live up to the expectations raised in the introduction. Firstly, while the importance of using a curated data set is emphasized, little information is given about the data set apart from the geographic origin of the samples (Figure 1). A BUSCO analysis is conducted to filter for assembly quality, but no results are reported. It is also not clear whether the authors assembled genomes themselves in the cases where, according to Supplementary Table 1, only the reads were published but not the assemblies. In the end, we simply have to trust that single-contig assemblies based on long-reads are reliable.
One issue with long read assemblies could be that high rates of sequencing errors result in artificial indels when coverage is low, which in turn could affect gene annotation and pangenome inference (e.g. Watson & Warr 2019, https://doi.org/10.1038/s41587-018-0004-z). Some of the older long-read data used by the authors could well be problematic (PacBio RSII), but also their own Nanopore assemblies, six of which have a mean coverage below 50 (Wick et al. 2023 recommend 200x for ONT, https://doi.org/ 10.1371/journal.pcbi.1010905). Could the results be affected by such assembly errors? Are there lineages, for example, for which there is an increased proportion of RSII data? Given the large heterogeneity in data quality on the NCBI, I think more information about the reads and the assemblies should be provided.
The part of the paper I struggled most with is the pangenome graph analysis and the interpretation of structural variants in terms of "regions of difference". To start with, the method section states that "multiple whole genomes were aligned into a graph using PanGraph" (l.159/160), without stating which genomes were for what reason. From Figure 5 I understand that you included all genomes, and that Figure 6 summarizes the information at the sublineage level. This should be stated clearly, at present the reader has to figure out what was done. It was also not clear to me why the authors focus on the sublineage level: a minority of accessory genes (107 of 506) are "specific to certain lineages or sublineages" (l. 240), so why conclude that the pangenome is "driven by sublineage-specific regions of difference", as the title states? What does "driven by" mean? Instead of cutting the phylogeny arbitrarily at the sublineage level, polymorphisms could be described more generally by their frequencies.
I fully agree that pangenome graphs are the way to go and that the non-coding part of the genome deserves as much attention as the coding part, as stated in the introduction. Here, however, the analysis of the pangenome graph consists of extracting variants from the graph and blasting them against the reference genome H37Rv in order to identify genes and "regions of difference" (RDs) that are variable. It is not clear what the authors do with structural variants that yield no blast hit against H37Rv. Are they ignored? Are they included as new "regions of difference"? How many of them are there? etc. The key advantage of pangenome graphs is that they allow a reference-free, full representation of genetic variation in a sample. Here reference bias is reintroduced in the first analysis step.
Along similar lines, I find the interpretation of structural variants in terms of "regions of difference" confusing, and probably many people outside the TB field will do so. For one thing, it is not clear where these RDs and their names come from. Did the authors use an annotation of RDs in the reference genome H37Rv from previously published work (e.g. Bespiatykh et al. 2021)? This is important basic information, its lack makes it difficult to judge the validity of the results. The Bespiatykh et al. study uses a large short-read data (721 strains) set to characterize diversity in RDs and specifically focuses on the sublineage-specific variants. While the authors cite the paper, it would be relevant to compare the results of the two studies in more detail.
As far as I understand, "regions of difference" have been used in the tuberculosis field to describe structural variants relative to the reference genome H37Rv. Colloquially, regions present in H37Rv but absent in another strain have been called "deletions". Whether these polymorphisms have indeed originated through deletion or through insertion in H37Rv or its ancestors requires a comparison with additional strains. While the pangenome graph does contain this information, the authors do not attempt to categorize structural variants into insertions and deletions but simply seem to assume that "regions of difference" are deletions. This, as well as the neglect of paralogs in the "classical" pangenome analysis, puts a question mark behind their conclusion that deletion drives pangenome evolution in the MTBC.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Li Zhang et al. characterized two new Gram-negative endolysins identified through an AMP-targeted search in bacterial proteomes. These endolysins exhibit broad lytic activity against both Gram-negative and Gram-positive bacteria and retain significant antimicrobial activity even after prolonged exposure to high temperatures (100{degree sign}C for 1 hour). This stability is attributed to a temperature-reversible transition from a dimer to a monomer. The authors suggest several potential applications, such as complementing heat sterilization processes or being used in animal feed premixes that undergo high-temperature pelleting, which I agree with.
Strengths:
The claims are well-supported by relevant and complementary assays, as well as extensive bioinformatic analyses.
Weaknesses:
There are numerous statements in the introduction and discussion sections that I currently do not agree with and consider need to be addressed. Therefore, I recommend major revisions.
Major comments:
Introduction and Discussion:
The introduction and the discussion are currently too general and not focused. Furthermore, there are some key concepts that are missing and are important for the reader to have an overview of the current state-of-the-art regarding endolysins that target gram-negatives. Specifically, the concepts of 'Artilysins', 'Innolysins', and 'Lysocins' are not introduced. Besides this, the authors do not mention other high-throughput mining or engineering strategies for endolysins, such as e.g. the VersaTile platform, which was initially developed by Hans Gerstmans et al. for one of the targeted pathogens in this manuscript (i.e., Acinetobacter baumannii). Recent works by Niels Vander Elst et al. have demonstrated that this VersaTile platform can be used to high-throughput screen and hit-to-lead select endolysins in the magnitude tens of thousands. Lastly, Roberto Vázquez et al. have recently demonstrated with bio-informatic analyses that approximately 30% of Gram-negative endolysin entries have AMP-like regions (hydrophobic short sequences), and that these entries are interesting candidates for further wet lab testing due to their outer membrane penetrating capacities. Therefore, I fully disagree with the statement being made in the introduction that endolysin strategies to target Gram-negatives are 'in its infancy' and I urge the authors to provide a new introduction that properly gives an overview of the Gram-negative endolysin field.
Results:
It should be mentioned that the halo assay is a qualitative assay for activity testing. I personally do not like that the size of the halos is used to discriminate in endolysin activity. In this reviewer's opinion, the size of the halo is highly dependent on (i) the molecular size of the endolysin as smaller proteins can diffuse further in the agar, and (ii) the affinity of the CBD subdomain of the endolysin for the bacterial peptidoglycan. It should also be said that in the halo assay, there is a long contact time between the endolysin and the bacteria that are statically embedded in the agar, which can result in false positive results. How did the authors mitigate this?
Testing should have been done at equimolar concentrations. If the authors decided to e.g. test 50 µg/mL for each protein, how was this then compensated for differences in molecular weight? For example, if PHAb10 and PHAb11 have smaller molecular sizes than PHAb7, 8, and 9, there is more protein present in 50 µg/mL for the first two compared to the others, and this would explain the higher decrease in bacterial killing (and possibly the larger halos).
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Scr4
DOI: 10.1038/s41467-019-11416-1
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @maulamb
SciCrunch record: RRID:SCR_006457
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors show that upon treatment with Doxorubicin (Doxo), there is an increase in senescence and inflammatory markers in the muscles. They also show these genes get upregulated in C2C12 myoblasts when treated with conditioned media or 15d-PGJ2. 15dPGJ2 induces cell death in the myoblasts, decreases proliferation (measured by cell numbers), and decreases differentiation and fusion. 15d-PGJ2 modified Cys184 of HRas, which is required for its activation as indicated by the FRET analysis with RAF RBD. They also showed that 15d-PGJ2 activates ERK signaling, but not Akt signaling, through the electrophilic center. 15d-PGJ2 inhibits Golgi localization of HRAS (only WT, not C181 or C184 mutant). They also showed that expressing the WT HRas followed by 15d-PGJ2 treatment led to a decrease in the levels of MHC mRNA and protein, and this defect is dependent on C184. This is a well-written manuscript with interesting insights into the mechanism of action of 15d-PGJ2. However, some clarification and experiments will help the paper advance the field significantly.
Strengths:
The data clearly shows that 15d-PGJ2 has a negative role in the myoblast cells and that it leads to modification of HRas protein. Moreover, the induction of biosynthetic enzymes in the PGD2 pathway also supports the induction of 15d-PGJ2 in Doxorubicin-treated cells. Both conditioned media experiments and the 15d-PGJ2 experiments show that 15d-PGJ2 could be the active component secreted by the senescent myoblasts.
Weaknesses:
The genes that are upregulated in the muscles upon injection with Doxo are also markers for inflammation. Since Doxo is also known to induce systemic inflammation, it is important to delineate these two effects (Inflammatory cells vs senescent cells). The expression of beta Gal and other markers of senescence in the tissue sections will help to delineate these.
In Figure 2, where the defect in the differentiation of myoblasts upon treatment with 15d-PGJ2 is shown, most of the cells die within 48 hours at higher concentrations, making it difficult to perform the experiments. This also shows that 15d-PGJ2 was toxic to these cells. Lower concentrations show a decrease in the differentiation based on the lower number of nuclei in fibers and low expression of MyoD, MyoG, and MHC. However, it is unclear if this is due to increased cell death or defective differentiation. It would be a lot more informative if the cell count, cell division, and cell death could be plotted for these concentrations of the drug during the experiment. Also, in the myoblast experiments, are the effects of treatment with Dox reversible?
In Figure 3, most of the experiments are done at a high concentration, which induces almost complete cell death within 48 hours. Even at such a high concentration of 15dPGJ2, the increase in ERK phosphorylation is minimal.
The experiment Figure 4C shows that C181 and C84 mutants of the HRas show higher levels in Golgi compared with WT. However, this could very well be due to the defect in palmitoylation rather than the modification with 15d-PGJ2. Though the authors allude to the possibility that intracellular redistribution of HRas by 15d-PGJ2 requires C181 palmitoylation, the direct influence of C184 modification on C181 palmitoylation is not shown. To have a meaningful conclusion, the authors need to compare the palmitoylation and modification with 15d-PGJ2.
To test if the inhibition of myoblast differentiation depends on HRas, they overexpressed the HRas and mutants in the C2C12 lines. However, this experiment does not take the endogenous HRAs into consideration, especially when interpreting the C184 mutant. An appropriate experiment to test this would be to knock down or knock out HRas (or make knock-in mutations of C184) and show that the effect of 15d-PGJ2 disappears. Moreover, in this specific experiment, it is difficult to interpret without a control with no HRas construct and another without the 15d-PGJ2 treatment.
Moreover, the overall study does not delineate the toxic effects of 15d-PGJ2 from its effect on the differentiation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Zheng et al. study the 'glass' transitions that occurs in proteins at ca. 200K using neutron diffraction and differential isotopic labeling (hydrogen/deuterium) of the protein and solvent. To overcome limitations in previous studies, this work is conducted in parallel with 4 proteins (myoglobin, cytochrome P450, lysozyme and green fluorescent protein) and experiments were performed at a range of instrument time resolutions (1ns - 10ps). The author's data looks compelling, and suggests that transitions in the protein and solvent behavior are not coupled and contrary to some previous reports, the apparent water transition temperature is a 'resolution effect'; i.e. instrument response limited. This is likely to be important in the field, as a reassessment of solvent 'slaving' and the role of the hydration shell on protein dynamics should be reassessed in light of these findings.
Strengths:
The use of multiple proteins and instruments with a rate of energy resolution/ timescales.
Weaknesses:
The paper could be organised to better allow the comparison of the complete dataset collected.<br /> The extent of hydration clearly influences the protein transition temperature. The authors suggest that "water can be considered here as lubricant or plasticizer which facilitates the motion of the biomolecule." This may be the case, but the extent of hydration may also alter the protein structure.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The present paper introduces Oscillation Component Analysis (OCA), in analogy to ICA, where source separation is underpinned by a biophysically inspired generative model. It puts the emphasis on oscillations, which is a prominent characteristic of neurophysiological data.
Strengths:
Overall, I find the idea of disambiguating data-driven decompositions by adding biophysical constrains useful, interesting and worth pursuing. The model incorporates both a component modelling of oscillatory responses that is agnostic about the frequency content (e.g. doesn't need bandpass filtering or predefinition of bands) and a component to map between sensor and latent-space. I feel these elements can be useful in practice.
Weaknesses:
Lack of empirical support: I am missing empirical justification of the advantages that are theoretically claimed in the paper. I feel the method needs to be compared to existing alternatives.
Comments on the revised version: This concern has been addressed in the revised version.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study identifies new types of interactions between Drosophila gustatory receptor neurons (GRNs) and shows that these interactions influence sensory responses and behavior. The authors find that HCN, a hyperpolarization-activated cation channel, suppresses the activity of GRNs in which it is expressed, preventing those GRNs from depleting the sensillum potential, and thereby promotes the activity of neighboring GRNs in the same sensilla. HCN is expressed in sugar GRNs, so HCN dampens excitation of sugar GRNs and promotes excitation of bitter GRNs. Impairing HCN expression in sugar GRNs depletes the sensillum potential and decreases bitter responses, especially when flies are fed on a sugar-rich diet, and this leads to decreased bitter aversion in a feeding assay. The authors' conclusions are supported by genetic manipulations, electrophysiological recordings, and behavioral assays.
Strengths:
(1) Non-synaptic interactions between neurons that share an extracellular environment (sometimes called "ephaptic" interactions) have not been well-studied, and certainly not in the insect taste system. A major strength of this study is the new insight it provides into how these interactions can impact sensory coding and behavior.
(2) The authors use many different types of genetic manipulations to dissect the role of HCN in GRN function, including mutants, RNAi, overexpression, ectopic expression, and neuronal silencing. Their results convincingly show that HCN impacts the sensillum potential and has both cell-autonomous and nonautonomous effects that go in opposite directions. Temporally controlled RNAi experiments suggest that the effect is not due to developmental changes. There are a couple of conflicting or counterintuitive results, but the authors discuss potential explanations.
(3) Experiments comparing flies raised on different food sources suggest an explanation for why the system may have evolved the way that it did: when flies live in a sugar-rich environment, their bitter sensitivity decreases, and HCN expression in sugar GRNs helps to counteract this decrease. New experiments in the revised paper show the timecourse of how sugar diet affects GRN responses and sensillum potential.
Weaknesses/Limitations:
(1) The RNAi Gal80ts experiment only compares responses of experimental flies housed at different temperatures without showing control flies (e.g. Gal4/+ and UAS/+ controls) to confirm that observed differences are not due to nonspecific effects of temperature. Certainly temperature cannot account for sugar and bitter GRN firing rates changing in opposite directions, but it may have some kind of effect.
(2) The experiments where flies are put on sugar vs. sorbitol food show that the diet clearly affects GRN responses and sensillum potential, even for food exposures as short as 1-4 hours, but it is not clear to what extent the GRNs in the labellum are being stimulated during those incubation periods. The flies are most likely not feeding over a 1 hour period if they were not starved beforehand, in which case it is not clear how many times the labellar GRNs would contact the food substrate.
(3) The authors mention that HCN may impact the resting potential in addition to changing the excitability of the cell through various mechanisms. It would be informative to record the resting potential and other neuronal properties, but this is very difficult for GRNs, so the current study is not able to determine exactly how HCN affects GRN activity.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study reports on the thermophilization of bird communities in a network of islands with varying areas and isolation in China. Using data from 10 years of transect surveys, the authors show that warm-adapted species tend to gradually replace cold-adapted species, both in terms of abundance and occurrence. The observed trends in colonisations and extinctions are related to the respective area and isolation of islands, showing an effect of fragmentation on the process of thermophilization.
Strengths:
Although thermophilization of bird communities has been already reported in different contexts, it is rare that this process can be related to habitat fragmentation, despite the fact that it has been hypothesized for a long time that it could play an important role. This is made possible thanks to a really nice study system in which the construction of a dam has created this incredible Thousand Islands lake. Here, authors do not simply take observed presence-absence as granted and instead develop an ambitious hierarchical dynamic multi-species occupancy model. Moreover, they carefully interpret their results in light of their knowledge of the ecology of the species involved.
Weaknesses:
Despite the clarity of this paper on many aspects, I see a strong weakness in the authors' hypotheses, which obscures the interpretation of their results. Looking at Figure 1, and in many sentences of the text, a strong baseline hypothesis is that thermophilization occurs because of an increasing colonisation rate of warm-adapted species and extinction rate of cold-adapted species. However, there does not need to be a temporal trend! Any warm-adapted species that colonizes a site has a positive net effect on CTI; similarly, any cold-adapted species that goes extinct contributes to thermophilization.
Another potential weakness is that fragmentation is not clearly defined. Generally, fragmentation sensu lato involves both loss of habitat area and changes in the spatial structure of habitats (i.e. fragmentation per se). Here, both area and isolation are considered, which may be slightly confusing for the readers if not properly defined.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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5073
DOI: 10.1038/s41467-023-41103-1
Resource: (BDSC Cat# 5073,RRID:BDSC_5073)
Curator: @anisehay
SciCrunch record: RRID:BDSC_5073
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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w1118
DOI: 10.1186/s40659-023-00462-1
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @anisehay
SciCrunch record: RRID:SCR_006457
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www.nature.com www.nature.com
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HEK 293
DOI: 10.1038/s42003-024-06458-1
Resource: (IZSLER Cat# BS CL 129, RRID:CVCL_0045)
Curator: @dhovakimyan1
SciCrunch record: RRID:CVCL_0045
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docdrop.org docdrop.org
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over a third of the world soils are heavily degraded
for - stats - agriculture - 1/3 of world's soils are degraded
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors isolated and cultured pulmonary artery smooth muscle cells (PASMC) and pulmonary artery adventitial fibroblasts (PAAF) of the lung samples derived from the patients with idiopathic pulmonary arterial hypertension (PAH) and the healthy volunteers. They performed RNA-seq and proteomics analyses to detail the cellular communication between PASMC and PAAF, which are the main target cells of pulmonary vascular remodeling during the pathogenesis of PAH. The authors revealed that PASMC and PAAF retained their original cellular identity and acquired different states associated with the pathogenesis of PAH, respectively.
Strengths:
Although previous studies have shown that PASMC and PAAF cells each have an important role in the pathogenesis of PAH, there have been scarce reports focusing on the interactions between PASMC and PAAF. These findings may provide valuable information for elucidating the pathogenesis of pulmonary arterial hypertension.
Weaknesses:
The results of proteome analysis using primary culture cells in this paper seem a bit insufficient to draw conclusions. In particular, the authors described "We elucidated the involvement of cellular crosstalk in regulating cell state dynamics and identified pentraxin-3 and hepatocyte growth factor as modulators of PASMC phenotypic transition orchestrated by PAAF." However, the presented data are considered limited and insufficient.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, the authors generated a novel transgenic mouse line OpalinP2A-Flpo-T2A-tTA2 to specifically label mature oligodendrocytes, and at the same time their embryonic origins by crossing with a progenitor cre mouse line. With this clever approach, they found that LGE/CGE-derived OLs make minimum contributions to the neocortex, whereas MGE/POA-derived OLs make a small but lasting contribution to the cortex. These findings are contradictory to the current belief that LGE/CGE-derived OPCs make a sustained contribution to cortical OLs, whereas MGE/POA-derived OPCs are completely eliminated. Thus, this study provides a revised and more comprehensive view on the embryonic origins of cortical oligodendrocytes. To specifically label mature oligodendrocytes, and at the same time their embryonic origins by crossing with a progenitor cre mouse line. With this clever approach, they found that LGE/CGE-derived OLs make minimum contributions to the neocortex, whereas MGE/POA-derived OLs make a small-but-lasting contribution to to cortex. These findings are contradictory to the current belief that LGE/CGE-derived OPCs make a sustained contribution to cortical OLs, whereas MGE/POA-derived OPCs are completely eliminated. Thus, this study has provided a revised and updated view on the embryonic origins of cortical oligodendrocytes.
Strengths:
The authors have generated a novel transgenic mouse line to specifically label mature differentiated oligodendrocytes, which is very useful for tracing the final destiny of mature myelinating oligodendrocytes. Also, the authors carefully compared the distribution of three progenitor cre mouse lines and suggested that Gsh-cre also labeled dorsal OLs, contrary to the previous suggestion that it only marks LGE-derived OPCs. In addition, the author also analyzed the relative contributions of OLs derived from three distinct progenitor domains in other forebrain regions (e.g. Pir, ac). Finally, the new transgenic mouse lines and established multiple combinatorial genetic models will facilitate future investigations of the developmental origins of distinct OL populations and their functional and molecular heterogeneity.
Comments on latest version: In this revised and improved manuscript, the authors have adequately addressed my concerns, and I have no further issues to raise.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Gout, a prevalent form of arthritis among the elderly, exhibits an intricate relationship with age and gut microbiota. The authors found that gut microbiota plays a crucial role in determining susceptibility to age-related gout. They observed that age-related gut microbiota regulated the activation of the NLRP3 inflammasome pathway and modulated uric acid metabolism. "Younger" microbiota has a positive impact on the gut microbiota structure of old or aged mice, enhancing butanoate metabolism and butyric acid content. Finally, they found butyric acid exerts a dual effect, inhibiting inflammation in acute gout and reducing serum uric acid levels. This work's insight emphasizes the potential of a "young" gut microbiome in mitigating senile gout. The whole study was interesting, but there were some minor errors in the overall writing of the paper. The author should carefully check the spelling of the words in the text and the case consistency of the group names.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The paper submitted by Yogesh and Keller explores the role of cholinergic input from the basal forebrain (BF) in the mouse primary visual cortex (V1). The study aims to understand the signals conveyed by BF cholinergic axons in the visual cortex, their impact on neurons in different cortical layers, and their computational significance in cortical visual processing. The authors employed two-photon calcium imaging to directly monitor cholinergic input from BF axons expressing GCaMP6 in mice running through a virtual corridor, revealing a strong correlation between BF axonal activity and locomotion. This persistent activation during locomotion suggests that BF input provides a binary locomotion state signal. To elucidate the impact of cholinergic input on cortical activity, the authors conducted optogenetic and chemogenetic manipulations, with a specific focus on L2/3 and L5 neurons. They found that cholinergic input modulates the responses of L5 neurons to visual stimuli and visuomotor mismatch, while not significantly affecting L2/3 neurons. Moreover, the study demonstrates that BF cholinergic input leads to decorrelation in the activity patterns of L2/3 and L5 neurons.
This topic has garnered significant attention in the field, drawing the interest of many researchers actively investigating the role of BF cholinergic input in cortical activity and sensory processing. The experiments and analyses were thoughtfully designed and conducted with rigorous standards, providing evidence of layer-specific differences in the impact of cholinergic input on neuronal responses to bottom-up (visual stimuli) and top-down inputs (visuomotor mismatch).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The circuit mechanism underlying the formation of grid cell activity and the organization of grid cells in the medial entorhinal cortex (MEC) is still unclear. To understand the mechanism, the current study investigated synaptic interactions between stellate cells (SC) and PV+ interneurons (IN) in layer 2 of the MEC by combing optogenetic activations and paired patch-clamp recordings. The results convincingly demonstrated highly structured interactions between these neurons: specific and direct excitatory-inhibitory interactions existed at the scale of grid cell phase clusters, and indirect interactions occurred at the scale of grid modules.
Strengths:
Overall, the manuscript is very well written, the approaches used are clever, and the data were thoroughly analyzed. The study conveyed important information for understanding the circuit mechanism that shapes grid cell activity. It is important not only for the field of MEC and grid cells, but also for broader fields of continuous attractor networks and neural circuits.
Weaknesses:
(1) The study largely relies on the fact that ramp-like wide-field optogenetic stimulation and focal optogenetic activation both drove asynchronous action potentials in SCs, and therefore, if a pair of PV+ INs exhibited correlated activity, they should receive common inputs. However, it is unclear what criteria/thresholds were used to determine the level of activity asynchronization, and under these criteria, what percentage of cells actually showed synchronized or less asynchronized activity. A notable percentage of synchronized or less asynchronized SCs could complicate the results, i.e., PV+ INs with correlated activity could receive inputs from different SCs (different inputs), which had synchronized activity. More detailed information/statistics about the asynchronization of SC activity is necessary for interpreting the results.
(2) The hypothesis about the "direct excitatory-inhibitory" synaptic interactions is made based on the GABAzine experiments in Figure 4. In the Figure 8 diagram, the direct interaction is illustrated between PV+ INs and SCs. However, the evidence supporting this "direct interaction" between these two cell types is missing. Is it possible that pyramidal cells are also involved in this interaction? Some pieces of evidence or discussions are necessary to further support the "direction interaction".
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this very interesting study, Agha and colleagues show that two types of Chx10-positive neurons (V2a neurons) have different anatomical and electrophysiological properties and receive distinct patterns of excitatory and inhibitory inputs as a function of speed during fictive swimming in the larval zebrafish. Using single cell fills they show that one cell type has a descending axon ("descending V2as"), while the other cell type has both a descending axon and an ascending axon ("bifurcating V2as"). In the Chx10:GFP line, descending V2as display strong GFP labeling, while bifurcating V2as display weak GFP labeling. The bifurcating V2as are located more laterally in the spinal cord. These two cell types have different electrophysiological properties as revealed by patch-clamp recordings. Positive current steps indicated that descending V2as comprise tonic spiking or bursting neurons. Bifurcating V2as comprise chattering or bursting neurons. The two types of V2a neurons display different recruitment patterns as a function of speed. Descending tonic and bifurcating chattering neurons are recruited at the beginning of the swimming bout, at fast speeds (swimming frequency above 30 Hz). Descending bursting neurons were preferentially recruited at the end of swimming bouts, at low speeds (swimming frequency below 30 Hz), while bifurcating bursting neurons were recruited for a broader swimming frequency range. The two types of V2a neurons receive distinct patterns of excitatory and inhibitory inputs during fictive locomotion. In descending V2as, when speed increases: i) excitatory conductances increase in fast neurons and decreases in slow neurons; ii) inhibitory conductances increase in fast neurons and increases in slow neurons. In bifurcating V2as, when speed increases: i) excitatory conductances increase in fast neurons but does not change in slow neurons; ii) inhibitory conductances increase in fast neurons and does not change in slow neurons. The timing of excitatory and inhibitory inputs was then studied. In descending V2as, fast neurons receive excitatory and inhibitory inputs that are in anti-phase with low contrast in amplitude and are both broadly distributed over the phase. The slow neurons receive two peaks of inhibition, one in anti-phase with the excitatory inputs and another just after the excitation. In bifurcating V2as, fast neurons receive two peaks of inhibition, while the slow ones receive anti-phase inhibition. They also show that silencing Dmrt3-labeled dI6 interneurons disrupted rhythm generation selectively at high speed.
Strengths:
This study focuses on the diversity of V2a neurons in zebrafish, an interesting cell population playing important roles in locomotor control and beyond, from fish to mammal. The authors provide compelling evidence that two subtypes of V2as show distinct anatomical, electrophysiological, speed-dependent spiking activity, and receive distinct synaptic inputs as a function of speed. This opens the door to future investigation of the inputs and outputs of these neurons. Finding ways to activate or inhibit specifically these cells would be very helpful in the years to come. The authors also provide an interesting speed-dependent circuit mechanism for rhythm generation.
Weaknesses:
No major weakness detected. The experiments were carefully done, and the data are of high quality.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
While there are many models for sequence retrieval, it has been difficult to find models that vary the speed of sequence retrieval dynamically via simple external inputs. While recent works have proposed some mechanisms, the authors here propose a different one based on heterogeneous plasticity rules. Temporally symmetric plasticity kernels (that do not distinguish between the order of pre and post spikes, but only their time difference) are expected to give rise to attractor states, asymmetric ones to sequence transitions. The authors incorporate a rate-based, discrete-time analog of these spike-based plasticity rules to learn the connections between neurons (leading to connections similar to Hopfield networks for attractors and sequences). They use either a parametric combination of symmetric and asymmetric learning rules for connections into each neuron, or separate subpopulations having only symmetric or asymmetric learning rules on incoming connections. They find that the latter is conducive to enabling external inputs to control the speed of sequence retrieval.
Comments on revised version:
The authors have addressed most of the points of the reviewers.
A major substantive point raised by both reviewers was on the biological plausibility of the learning.
The authors have added a section in the Discussion. This remains an open question, however the discussion suffices for the current paper.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
This study examined the role of a prefrontal cortex cell type in active avoidance behavior. The authors conduct a series of behavioral experiments incorporating fiber photometry and optogenetic silencing. The results indicate that prefrontal parvalbumin (PV) neurons play a permissive role in performing signaled active avoidance learning, for which details are sorely lacking. Notably, infralimbic parvalbumin activity resolves incompatible defensive responses to threat by suppressing conditional freezing in order to permit active instrumental controlling responses. The overall findings provide a significant contribution to our understanding of mechanisms that support aversively motivated instrumental learning and may provide insight into both stress vulnerability and resilience processes.
Strengths:
The writing and presentation of data is clear. The authors use a number of temporally-relevant methods and analyses that identify a novel prefrontal mechanism in resolving the conflict between competing actions (freezing vs escape avoidance). The authors conduct an extensive number of experiments to demonstrate that the uncovered prefrontal mechanism is selective for the initiation of avoidance under threat circumstances, not reward settings or general features of movement.
Weaknesses:
The study exclusively focuses on parvalbumin cells, thus questions remain whether the present findings are specific to parvalbumin or applicable to other prefrontal interneuron subtypes. The exact mechanisms that coordinate infralimbic parvalbumin cell activity and threat avoidance behavior are not explored.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Peterson et al., present a series of experiments in which the Pavlovian performance (i.e. time spent at a food cup/port) of male and female rats is assessed in various tasks in which context/cue/outcome relationships are altered. The authors find no sex differences in context-irrelevant tasks, and no such differences in tasks in which the context signals that different cues will earn different outcomes. They do find sex differences, however, when a single outcome is given and context cues must be used to ascertain which cue will be rewarded with that outcome (Ctx-dep O1 task). Specifically, they find that males acquired the task faster, but that once acquired, performance of the task was more resilient in female rats against exposures to a stressor. Finally, they show that these sex differences are reflected in differential rates of c-fos expression in all three subregions of rat OFC, medial, lateral and ventral, in the sense that it is higher in females than males, and only in the animals subject to the Ctx-dep O1 task in which sex differences were observed.
Strengths:
• Well written<br /> • Experiments elegantly designed<br /> • Robust statistics<br /> • Behaviour is the main feature of this manuscript, rather than any flashy techniques or fashionable lab methodologies, and luckily the behaviour is done really well.<br /> • For the most part I think the conclusions were well supported, although I do have some slightly different interpretations to the authors in places.
Weaknesses:
The authors have done an excellent job of addressing all previous weaknesses. I have no further comments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This interesting study investigates the neurobiological mechanisms underlying the stable operation and maintenance of functionally appropriate rhythmic motor patterns during changing environmental conditions - temperature in this study in the crab Cancer borealis stomatogastric neural pattern generating network producing the pyloric motor rhythm, which is naturally subjected to temperature perturbations over a substantial range. This study is relevant to the general problem that some rhythmic motor systems adjust to changing environmental conditions and state changes by increasing the cycle frequency in a smooth monotonic fashion while maintaining the relative timing of different network activity pattern phases that determine proper motor coordination. How this is achieved mechanistically in complex dynamic motor networks is not understood, particularly how the frequency and phase adjustments are achieved as conditions change while avoiding operational instabilities on different time scales. The authors specifically studied the contributions of the hyperpolarization-activated inward current (Ih), which is involved in rhythm control, to the adjustments of frequency and phases in the pyloric rhythmic pattern as the temperature was altered from 11 degrees C to 21 degrees C. They present strong evidence that this current is a critical biophysical feature in the ability of this system to adjust transiently and persistently to temperature perturbations appropriately. After blocking Ih in the pyloric network with cesium, the network was unable to reliably produce its characteristic rapid and smooth increase in the frequency of the triphasic rhythmic motor pattern in response to increasing temperature or its typical steady-state increase in frequency over this Q10 temperature range.
Strengths:
(1) The authors addressed this problem by technically rigorous experiments in the crab Cancer borealis stomatogastric ganglion (STG) in vitro, which readily allows for neuronal activity recording in a behaviorally and architecturally defined rhythmic neural circuit in conjunction with the application of blockers of Ih and synaptic receptors to disrupt circuit interactions. This approach is an effective way to experimentally investigate how complex rhythmic networks, at least in poikilotherms, mechanistically adjust to environmental perturbations such as temperature.
(2) While previous work demonstrated that Ih increases in pyloric neurons as temperature increases, the authors here establish that this increase is necessary for normal responses of STG neural activity to temperature, which consist of a smooth monotonic increase in the frequency of rhythmic activity with increasing temperature.
(3) The data shows that blocking Ih with cesium causes the frequency to transiently decrease ("jags") when the temperature increases and then increases after the temperature stabilizes at a steady state, revealing a non-monotonic frequency response to temperature perturbations.
(4) The authors dissect some of the underlying neuronal and circuit dynamics, presenting evidence that after blocking Ih, the non-monotonic jags in the frequency response are mediated by intrinsic properties of pacemaker neurons, while in the steady state, Ih determined the overall frequency change (i.e., temperature sensitivity) through network interactions.
(5) The authors' results highlight the existence of more complex dynamic responses to increasing temperature for the first time, suggesting a longer timescale process than previously recognized that may result from interactions between multiple channels and/or ion channel kinetics.
Weaknesses:
The involvement of Ih in achieving the frequency and phase adjustments as conditions change and allowing smooth transitions to avoid operational instabilities in other complex rhythmic motor netReviewer #2 (Public Review):
Summary:
Using the crustacean stomatogastric nervous system (STNS), the authors present an interesting study wherein the contribution of the Ih current to temperature-induced changes in the frequency of a rhythmically active neural circuit is evaluated. Ih is a hyperpolarization-activated cation current that depolarizes neurons. Under normal conditions, increasing the temperature of the STNS increases the frequency of the spontaneously active pyloric rhythm. Notably, under normal conditions, as temperature systematically increases, the concomitant increase in pyloric frequency is smooth (i.e., monotonic). By contrast, blocking Ih with extracellular cesium produces temperature-induced pyloric frequency changes that follow a characteristic sawtooth response (i.e., non-monotonic). That is, in cesium, increasing temperature initially results in a transient drop in pyloric frequency that then stabilizes at a higher frequency. Thus, the authors conclude that Ih establishes a mechanism that ensures smooth changes in neural network frequency during environmental disturbances, a feature that likely bestows advantages to the animal's function.
The study describes several surprising and interesting findings. In general, the study's primary observation of the cesium-induced sawtooth response is remarkable. To my knowledge, this type of response has not yet been described in neurobiological systems, and I suspect that the unexpected response will be of interest to many readers.
At first glance, I had some concerns regarding the use of extracellular cesium to understand network phenomena. Yes, extracellular cesium blocks Ih. But extracellular cesium has also been shown to block astrocytic potassium channels, at least in mammalian systems (i.e., K-IR, PMID: 10601465), and such a blockade can elevate extracellular potassium. I was heartened to see that the authors acknowledge the non-specificity of cesium (lines 320-325) and I agree with the authors' contention that "a first approximation most of the effects seen here can likely be attributed to Cs+ block of Ih". Upon reflecting on the potential confound, I was also reassured to see that extracellular cesium alone does not increase pyloric frequency, an effect that might be expected if cesium indirectly raises [K+]outside. I suggest including that point in the discussion.
In summary, the authors present a solid investigation of a surprising biological phenomenon. In general, my comments are fairly minor. This is an interesting study.
Strengths:
A major strength of the study is the identification of an ionic conductance that mediates stable, monotonic changes in oscillatory frequency that accompany changes in the environment (i.e., temperature).
Weaknesses:
A potential experimental concern stems from the use of extracellular cesium to attribute network effects specifically to Ih. Previous work has shown that extracellular cesium also blocks inward-rectifier potassium channels expressed by astrocytes, and that such blockade may also elevate extracellular potassium, an action that generally depolarizes neurons. Notably, the authors address this potential concern in the discussion.works, for example, in homeotherms, is not established, so the present results may have limited general extrapolations.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This work successfully identified and validated TRLs in hepatic metastatic uveal melanoma, providing new horizons for enhanced immunotherapy. Uveal melanoma is a highly metastatic cancer that, unlike cutaneous melanoma, has a limited effect on immune checkpoint responses, and thus there is a lack of formal clinical treatment for metastatic UM. In this manuscript, the authors described the immune microenvironmental profile of hepatic metastatic uveal melanoma by sc-RNAseq, TCR-seq, and PDX models. Firstly, they identified and defined the phenotypes of tumor-reactive T lymphocytes (TRLs). Moreover, they validated the activity of TILs by in vivo PDX modeling as well as in vitro co-culture of 3D tumorsphere cultures and autologous TILs. Additionally, the authors found that TRLs are mainly derived from depleted and late-activated T cells, which recognize melanoma antigens and tumor-specific antigens. Most importantly, they identified TRLs-associated phenotypes, which provide new avenues for targeting expanded T cells to improve cellular and immune checkpoint immunotherapy.
Comments on revised manuscript
The revised manuscript has addressed all my concerns.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This is large-scale genomics and transcriptomics study of the epidemic community-acquired methicillin-resistant S. aureus clone USA300, designed to identify core genome mutations that drove the emergence of the clone. It used publicly available datasets and a combination of genome-wide association studies (GWAS) and independent principal-component analysis (ICA) of RNA-seq profiles to compare USA300 versus non-USA300 within clonal complex 8. By overlapping the analyses the authors identified a 38bp deletion upstream of the iron-scavenging surface-protein gene isdH that was both significantly associated with the USA300 lineage and with a decreased transcription of the gene.
Strengths:
Several genomic studies have investigated genomic factors driving the emergence of successful S. aureus clones, in particular USA300. These studies have often focussed on acquisition of key accessory genes or have focussed on a small number of strains. This study makes a smart use of publicly available repositories to leverage the sample size of the analysis and identify new genomics markers of USA300 success.
The approach of combining large-scale genomics and transcriptomics analysis is powerful, as it allows to make some inferences on the impact of the mutations. This is particular important for mutations in intergenic regions, whose functional impact is often uncertain.
The statistical genomics approaches are elegant and state-of-the-art and can be easily applied to other contexts or pathogens.
Weaknesses:
The main weakness of this work is that these data don't allow a casual inference on the role of isdH in driving the emergence of USA300. It is of course impossible to prove which mutation or gene drove the success of the clone, however, experimental data would have strengthen the conclusions of the authors in my opinion.
Another limitation of this approach is that the approach taken here doesn't allow to make any conclusions on the adaptive role of the isdH mutation. In other words, it is still possible that the mutation is just a marker of USA300 success, due to other factors such as PVL, ACMI or the SCCmecIVa. This is because by its nature this analysis is heavy influenced by population structure. Usually, GWAS is applied to find genetic loci that are associated with a phenotype and are independent of the underlying population structure. Here, authors are using GWAS to find loci that are associated with a lineage. In other words, they are simply running a univariate analysis (likely a logistic regression) between genetic loci and the lineage without any correction for population structure, since population structure is the outcome. Therefore, this approach can't be applied to most phenotype-genotype studies where correction for population structure is critical.
Finally, the approach used is complex and not easily reproduced to another dataset. Although I like DBGWAS and find the network analysis elegant, I would be interested in seeing how a simpler GWAS tool like Pyseer would perform.
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www.biorxiv.org www.biorxiv.org
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Joint Public Review:
The present study explored the principles that allow cells to maintain complex subcellular proteinaceous structures despite the limited lifetimes of the individual protein components. This is particularly critical in the case of neurons, where the size and protein composition of synapses define synaptic strength and encode memory.
PSD95 is an abundant synapse protein that acts as a scaffold in the recruitment of transmitter receptors and other signaling proteins and is required for proper memory formation. The authors used super-resolution microscopy to study PSD95 super-complexes isolated from the brains of mice expressing tagged PSD variants (Halo-Tag, mEos, GFP). Their results show compellingly that a large fraction (~25%) of super-complexes contains two PSD95 copies about 13 nm apart, that there is substantial turnover of PSD95 proteins in super-complexes over a period of seven days, and that ~5-20% of the super-complexes contain new and old PSD95 molecules. This percentage is higher in synaptic fractions as compared to total brain lysates, and highest in isocortex samples (~20%). These important findings support the notion put forward by Crick that sequential subunit replacement gives synaptic super-complexes long lifetimes and thus aids in memory maintenance. Overall, this is very interesting, providing key insights into how synaptic protein complexes are formed and maintained. On the other hand, the actual role of these PSD95 super-complexes in long-term memory storage remains unknown.
Strengths
(1) The study employed an appropriate and validated methodology.
(2) Large numbers of PSD95 super-complexes from three different mouse models were imaged and analyzed, providing adequately powered sample sizes.
(3) State-of-the-art super-resolution imaging techniques (PALM and MINFLUX) were used, providing a robust, high-quality, cross-validated analysis of PSD95 protein complexes that is useful for the community.
(4) The result that PSD95 proteins in dimeric complexes are on average 12.7 nm apart is useful and has implications for studies on the nanoscale organization of PSD95 at synapses.
(5) The finding that postsynaptic protein complexes can continue to exist while individual components are being renewed is important for our understanding of synapse maintenance and stability.
(6) The data on the turnover rate of PSD95 in super-complexes from different brain regions provide a first indication of potentially meaningful differences in the lifetime of super-complexes between brain regions.
Weaknesses
(1) The manuscript emphasizes the hypothesis that stable super-complexes, maintained through sequential replacement of subunits, might underlie the long-term storage of memory. While an interesting idea, this notion requires considerably more research. The presented experimental data are indeed consistent with this notion, but there is no evidence that these complexes are causally related to memory storage.
(2) Much of the presented work is performed on biochemically isolated protein complexes. The biochemical isolation procedures rely on physical disruption and detergents that are known to alter the composition and structure of complexes in certain cases. Thus, it remains unclear how the protein complexes described in this study relate to PSD95 complexes in intact synapses.
(3) Because not all GFP molecules mature and fold correctly in vitro and the PSD95-mEos mice used were heterozygous, the interpretation of the corresponding quantifications is not straightforward.
(4) It was not tested whether different numbers of PSD95 molecules per super-complex might contribute to different retention times of PSD95, e.g. in synaptic vs. total-forebrain super-complexes.
(5) The conclusion that the population of 'mixed' synapses is higher in the isocortex than in other brain regions is not supported by statistical analysis.
(6) The validity of conclusions regarding PSD95 degradation based on relative changes in the occurrence of SiR-Halo-positive puncta is limited.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Bowler et al. present a thoroughly tested system for modularized behavioral control of navigation-based experiments, particularly suited for pairing with 2-photon imaging but applicable to a variety of techniques. This system, which they name behaviorMate, represents a valuable contribution to the field. As the authors note, behavioral control paradigms vary widely across laboratories in terms of hardware and software utilized and often require specialized technical knowledge to make changes to these systems. Having a standardized, easy-to-implement, and flexible system that can be used by many groups is therefore highly desirable. This work will be of interest to systems neuroscientists looking to integrate flexible head-fixed behavioral control with neural data acquisition.
Strengths:
The present manuscript provides compelling evidence of the functionality and applicability of behaviorMate. The authors report benchmark tests for real-time update speed between the animal's movement and the behavioral control, on both the treadmill-based and virtual reality (VR) setups. Further, they nicely demonstrate and quantify reliable hippocampal place cell coding in both setups, using synchronized 2-photon imaging. This place cell characterization also provides a concrete comparison between the place cell properties observed in treadmill-based navigation vs. visual VR in a single study, which itself is a helpful contribution to the field.
Documentation for installing and operating behaviorMate is available via the authors' lab website and linked in the manuscript.
Weaknesses:
The following comments are mostly minor suggestions intended to add clarity to the paper and provide context for its significance.
(1) As VRMate (a component of behaviorMate) is written using Unity, what is the main advantage of using behaviorMate/VRMate compared to using Unity alone paired with Arduinos (e.g. Campbell et al. 2018), or compared to using an existing toolbox to interface with Unity (e.g. Alsbury-Nealy et al. 2022, DOI: 10.3758/s13428-021-01664-9)? For instance, one disadvantage of using Unity alone is that it requires programming in C# to code the task logic. It was not entirely clear whether VRMate circumvents this disadvantage somehow -- does it allow customization of task logic and scenery in the GUI? Does VRMate add other features and/or usability compared to Unity alone? It would be helpful if the authors could expand on this topic briefly.
(2) The section on "context lists", lines 163-186, seemed to describe an important component of the system, but this section was challenging to follow and readers may find the terminology confusing. Perhaps this section could benefit from an accompanying figure or flow chart, if these terms are important to understand.
(2a) Relatedly, "context" is used to refer to both when the animal enters a particular state in the task like a reward zone ("reward context", line 447) and also to describe a set of characteristics of an environment (Figure 3G), akin to how "context" is often used in the navigation literature. To avoid confusion, one possibility would be to use "environment" instead of "context" in Figure 3G, and/or consider using a word like "state" instead of "context" when referring to the activation of different stimuli.
(3) Given the authors' goal of providing a system that is easily synchronizable with neural data acquisition, especially with 2-photon imaging, I wonder if they could expand on the following features:
(3a) The authors mention that behaviorMate can send a TTL to trigger scanning on the 2P scope (line 202), which is a very useful feature. Can it also easily generate a TTL for each frame of the VR display and/or each sample of the animal's movement? Such TTLs can be critical for synchronizing the imaging with behavior and accounting for variability in the VR frame rate or sampling rate.
(3b) Is there a limit to the number of I/O ports on the system? This might be worth explicitly mentioning.
(3c) In the VR version, if each display is run by a separate Android computer, is there any risk of clock drift between displays? Or is this circumvented by centralized control of the rendering onset via the "real-time computer"?
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public Review):
Summary:
Qin and colleagues analysed data from the Human Connectome Project on four right-handed subgroups with different gyrification patterns in Heschl's gyrus. Based on these groups, the authors highlight the structure-function relationship of planum temporale asymmetry in lateralised language processing at the group level and next at the individual level. In particular, the authors propose that especially microstructural asymmetries are related to functional auditory language asymmetries in the planum temporale.
Strengths:
The study is interesting because of an ongoing and long-standing debate about the relationship between structural and functional brain asymmetries, and in particular whether structural brain asymmetries can be seen as markers of functional language brain lateralisation.
In this debate, the relationship between Heschl's gyrus asymmetry and planum temporale asymmetry is rare and therefore valuable here. A large sample size and inter-rater reliability support the findings.
Weaknesses:
In this case of multiple brain measures, it would be important to provide the reader with some sort of effect size (e.g. Cohen's d) to help interpret the results. In addition, the authors highlight the microstructural results in spite of the macrostructural results. However, the macrostructural surface results are also strong. I would suggest either reducing the emphasis on micro vs macrostructural results or adding information to justify the microstructural importance.
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Reviewer #1 (Public Review):
Summary:
In this study, the authors trained a variational autoencoder (VAE) to create a high-dimensional "voice latent space" (VLS) using extensive voice samples, and analyzed how this space corresponds to brain activity through fMRI studies focusing on the temporal voice areas (TVAs). Their analyses included encoding and decoding techniques, as well as representational similarity analysis (RSA), which showed that the VLS could effectively map onto and predict brain activity patterns, allowing for the reconstruction of voice stimuli that preserve key aspects of speaker identity.
Strengths:
This paper is well-written and easy to follow. Most of the methods and results were clearly described. The authors combined a variety of analytical methods in neuroimaging studies, including encoding, decoding, and RSA. In addition to commonly used DNN encoding analysis, the authors performed DNN decoding and resynthesized the stimuli using VAE decoders. Furthermore, in addition to machine learning classifiers, the authors also included human behavioral tests to evaluate the reconstruction performance.
Weaknesses:
This manuscript presents a variational autoencoder (VAE) to evaluate voice identity representations from brain recordings. However, the study's scope is limited by testing only one model, leaving unclear how generalizable or impactful the findings are. The preservation of identity-related information in the voice latent space (VLS) is expected, given the VAE model's design to reconstruct original vocal stimuli. Nonetheless, the study lacks a deeper investigation into what specific aspects of auditory coding these latent dimensions represent. The results in Figure 1c-e merely tested a very limited set of speech features. Moreover, there is no analysis of how these features and the whole VAE model perform in standard speech tasks like speech recognition or phoneme recognition. It is not clear what kind of computations the VAE model presented in this work is capable of. Inclusion of comparisons with state-of-the-art unsupervised or self-supervised speech models known for their alignment with auditory cortical responses, such as Wav2Vec2, HuBERT, and Whisper, would strengthen the validation of the VAE model and provide insights into its relative capabilities and limitations.
The claim that the VLS outperforms a linear model (LIN) in decoding tasks does not significantly advance our understanding of the underlying brain representations. Given the complexity of auditory processing, it is unsurprising that a nonlinear model would outperform a simpler linear counterpart. The study could be improved by incorporating a comparative analysis with alternative models that differ in architecture, computational strategies, or training methods. Such comparisons could elucidate specific features or capabilities of the VLS, offering a more nuanced understanding of its effectiveness and the computational principles it embodies. This approach would allow the authors to test specific hypotheses about how different aspects of the model contribute to its performance, providing a clearer picture of the shared coding in VLS and the brain.
The manuscript overlooks some crucial alternative explanations for the discriminant representation of vocal identity. For instance, the discriminant representation of vocal identity can be either a higher-level abstract representation or a lower-level coding of pitch height. Prior studies using fMRI and ECoG have identified both types of representation within the superior temporal gyrus (STG) (e.g., Tang et al., Science 2017; Feng et al., NeuroImage 2021). Additionally, the methodology does not clarify whether the stimuli from different speakers contained identical speech content. If the speech content varied across speakers, the approach of averaging trials to obtain a mean vector for each speaker-the "identity-based analysis"-may not adequately control for confounding acoustic-phonetic features. Notably, the principal component 2 (PC2) in Figure 1b appears to correlate with absolute pitch height, suggesting that some aspects of the model's effectiveness might be attributed to simpler acoustic properties rather than complex identity-specific information.
Methodologically, there are issues that warrant attention. In characterizing the autoencoder latent space, the authors initialized logistic regression classifiers 100 times and calculated the t-statistics using degrees of freedom (df) of 99. Given that logistic regression is a convex optimization problem typically converging to a global optimum, these multiple initializations of the classifier were likely not entirely independent. Consequently, the reported degrees of freedom and the effect size estimates might not accurately reflect the true variability and independence of the classifier outcomes. A more careful evaluation of these aspects is necessary to ensure the statistical robustness of the results.
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Reviewer #1 (Public Review):
Lu & Golomb combined EEG, artificial neural networks, and multivariate pattern analyses to examine how different visual variables are processed in the brain. The conclusions of the paper are mostly well supported, but some aspects of methods and data analysis would benefit from clarification and potential extensions.
The authors find that not only real-world size is represented in the brain (which was known), but both retinal size and real-world depth are represented, at different time points or latencies, which may reflect different stages of processing. Prior work has not been able to answer the question of real-world depth due to the stimuli used. The authors made this possible by assessing real-world depth and testing it with appropriate methodology, accounting for retinal and real-world size. The methodological approach combining behavior, RSA, and ANNs is creative and well thought out to appropriately assess the research questions, and the findings may be very compelling if backed up with some clarifications and further analyses.
The work will be of interest to experimental and computational vision scientists, as well as the broader computational cognitive neuroscience community as the methodology is of interest and the code is or will be made available. The work is important as it is currently not clear what the correspondence between many deep neural network models and the brain is, and this work pushes our knowledge forward on this front. Furthermore, the availability of methods and data will be useful for the scientific community.
Some analyses are incomplete, which would be improved if the authors showed analyses with other layers of the networks and various additional partial correlation analyses.
Clarity
(1) Partial correlations methods incomplete - it is not clear what is being partialled out in each analysis. It is possible to guess sometimes, but it is not entirely clear for each analysis. This is important as it is difficult to assess if the partial correlations are sensible/correct in each case. Also, the Figure 1 caption is short and unclear.
For example, ANN-EEG partial correlations - "Finally, we directly compared the timepoint-by-timepoint EEG neural RDMs and the ANN RDMs (Figure 3F). The early layer representations of both ResNet and CLIP were significantly correlated with early representations in the human brain" What is being partialled out? Figure 3F says partial correlation
Issues / open questions
(2) Semantic representations vs hypothesized (hyp) RDMs (real-world size, etc) - are the representations explained by variables in hyp RDMs or are there semantic representations over and above these? E.g., For ANN correlation with the brain, you could partial out hyp RDMs - and assess whether there is still semantic information left over, or is the variance explained by the hyp RDMs?
(3) Why only early and late layers? I can see how it's clearer to present the EEG results. However, the many layers in these networks are an opportunity - we can see how simple/complex linear/non-linear the transformation is over layers in these models. It would be very interesting and informative to see if the correlations do in fact linearly increase from early to later layers, or if the story is a bit more complex. If not in the main text, then at least in the supplement.
(4) Peak latency analysis - Estimating peaks per ppt is presumably noisy, so it seems important to show how reliable this is. One option is to find the bootstrapped mean latencies per subject.
(5) "Due to our calculations being at the object level, if there were more than one of the same objects in an image, we cropped the most complete one to get a more accurate retinal size. " Did EEG experimenters make sure everyone sat the same distance from the screen? and remain the same distance? This would also affect real-world depth measures.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Kv2 subfamily potassium channels contribute to delayed rectifier currents in virtually all mammalian neurons and are encoded by two distinct types of subunits: Kv2 alpha subunits that have the capacity to form homomeric channels (Kv2.1 and Kv2.2), and KvS or silent subunits (Kv5,6,8.9) that can assemble with Kv2.1 or Kv2.2 to form heteromeric channels with novel biophysical properties. Many neurons express both types of subunits and therefore have the capacity to make both homomeric Kv2 channels and heteromeric Kv2/KvS channels. Determining the contributions of each of these channel types to native potassium currents has been very difficult because the differences in biophysical properties are modest and there are no Kv2/KvS-specific pharmacological tools. The authors set out to design a strategy to separate Kv2 and Kv2/KvS currents in native neurons based on their observation that Kv2/KvS channels have little sensitivity to the Kv2 pore blocker RY785 but are blocked by the Kv2 VSD blocker GxTx. They clearly demonstrate that Kv2/KvS currents can be differentiated from Kv2 currents in native neurons using a two-step strategy to first selectively block Kv2 with RY785, and then block both with GxTx. The manuscript is beautifully written; takes a very complex problem and strategy and breaks it down so both channel experts and the broad neuroscience community can understand it.
Strengths:
The compounds the authors use are highly selective and unlikely to have significant confounding cross-reactivity to other channel types. The authors provide strong evidence that all Kv2/KvS channels are resistant to RY785. This is a strength of the strategy - it can likely identify Kv2/KvS channels containing any of the 10 mammalian KvS subunits and thus be used as a general reagent on all types of neurons. The limitation then of course is that it can't differentiate the subtypes, but at this stage, the field really just needs to know how much Kv2/KvS channels contribute to native currents and this strategy provides a sound way to do so.
Weaknesses:
The authors are very clear about the limitations of their strategy, the most important of which is that they can't differentiate different subunit combinations of Kv2/KvS heteromers. This study is meant to be a start to understanding the roles of Kv2/KvS channels in vivo. As such, this is a minor weakness, far outweighed by the potential of the strategy to move the field through a roadblock that has existed since its inception.
The study accomplishes exactly what it set out to do: provide a means to determine the relative contributions of homomeric Kv2 and heteromeric Kv2/KvS channels to native delayed rectifier K+ currents in neurons. It also does a fabulous job laying out the case for why this is important to do.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In their current study, Cummings et al have approached this fundamental biochemical problem using a combination of purified enzyme-substrate reactions, MS/MS, and microscopy in vitro to provide key insights into the hierarchy of generating polyglycylation in cilia and flagella. They first establish that TTLL8 is a monoglycylase, with the potential to add multiple mono glycine residues on both α- and β-tubulin. They then go on to establish that monoglycylation is essential for TTLL10 binding and catalytic activity, which progressively reduces as the level of polyglycylation increases. This provides an interesting mechanism of how the level of polyglycylation is regulated in the absence of a deglycylase. Finally, the authors also establish that for efficient TTLL10 activity, it is not just monoglycylation, but also polyglutamylation that is necessary, giving a key insight into how both these modifications interact with each other to ensure there is a balanced level of PTMs on the axonemes for efficient cilia function.
Strengths:
The manuscript is well-written, and experiments are succinctly planned and outlined. The experiments were used to provide the conclusions to what the authors were hypothesising and provide some new novel possible mechanistic insights into the whole process of regulation of tubulin glycylation in motile cilia.
Weaknesses:
The initial part of the manuscript where the authors discuss about the requirement of monoglycylation by TTLL8 is not new. This was established back in 2009 when Rogowski et al (2009) showed that polyglycylation of tubulin by TTLL10 occurs only when co-expressed in cells with TTLL3 or TTLL8. So, this part of the study adds very little new information to what was known.
The study also fails to discuss the involvement of the other monoglycylase, TTLL3 in the entire study, which is a weakness as in vivo, in cells, both the monoglycylases act in concert and so, may play a role in regulating the activity of TTLL10.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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33079
DOI: 10.1038/s42003-020-0889-1
Resource: (BDSC Cat# 33079,RRID:BDSC_33079)
Curator: @PeterEckmann
SciCrunch record: RRID:BDSC_33079
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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51483
DOI: 10.1038/s41593-023-01568-1
Resource: (BDSC Cat# 51483,RRID:BDSC_51483)
Curator: @mpairish
SciCrunch record: RRID:BDSC_51483
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Local file Local file
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52303
DOI: 10.1038/s41467-024-47236-1
Resource: BDSC_52303
Curator: @bandrow
SciCrunch record: RRID:BDSC_52303
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codes.ohio.gov codes.ohio.gov
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(1) The filing by a registered elector of a written request with a board of elections or the secretary of state, on a form prescribed by the secretary of state and signed by the elector, that the registration be canceled. The filing of such a request does not prohibit an otherwise qualified elector from reregistering to vote at any time.
The only true protest vote.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
DMS-MaP is a sequencing-based method for assessing RNA folding by detecting methyl adducts on unpaired A and C residues created by treatment with dimethylsulfate (DMS). DMS also creates methyl adducts on the N7 position of G, which could be sensitive to tertiary interactions with that atom, but N7-methyl adducts cannot be detected directly by sequencing. In this work, the authors adopt a previously developed method for converting N7-methyl-G to an abasic site to make it detectable by sequencing and then show that the ability of DMS to form an N7-methyl-G adduct is sensitive to RNA structural context. In particular, they look at the G-quadruplex structure motif, which is dense with N7-G interactions, is biologically important, and lacks conclusive methods for in-cell structural analysis.
Strengths:
- The authors clearly show that established methods for detecting N7-methyl-G adducts can be used to detect those adducts from DMS and that the formation of those adducts is sensitive to structural context, particularly G-quadruplexes.
- The authors assess the N7-methyl-G signal through a wide range of useful probing analyses, including standard folding, adduct correlations, mutate-and-map, and single-read clustering.
- The authors show encouraging preliminary results toward the detection of G-quadruplexes in cells using their method. Reliable detection of RNA G-quadruplexes in cells is a major limitation for the field and this result could lead to a significant advance.
- Overall, the work shows convincingly that N7-methyl-G adducts from DMS provide valuable structural information and that established data analyses can be adapted to incorporate the information.
Weaknesses:
- Most of the validation work is done on the spinach aptamer and it is the only RNA tested that has a known 3D structure. Although it is a useful model for validating this method, it does not provide a comprehensive view of what results to expect across varied RNA structures.
- It's not clear from this work what the predictive power of BASH-MaP would be when trying to identify G-quadruplexes in RNA sequences of unknown structure. Although clusters of G's with low reactivity and correlated mutations seem to be a strong signal for G-quadruplexes, no effort was made to test a range of G-rich sequences that are known to form G-quadruplexes or not. Having this information would be critical for assessing the ability of BASH-MaP to identify G-quadruplexes in cells.
- Although the authors present interesting results from various types of analysis, they do not appear to have developed a mature analysis pipeline for the community to use. I would be inclined to develop my own pipeline if I were to use this method.
- There are various aspects of the DAGGER analysis that don't make sense to me:<br /> (1) Folding of the RNA based on individual reads does not represent single-molecule folding since each read contains only a small fraction of the possible adducts that could have formed on that molecule. As a result, each fold will largely be driven by the naive folding algorithm. I recommend a method like DREEM that clusters reads into profiles representing different conformations.<br /> (2) How reliable is it to force open clusters of low-reactivity G's across RNA's that don't already have known G-quadruplexes?<br /> (3) By forcing a G-quadruplex open it will be treated as a loop by the folding algorithm, so the energetics won't be accurate.<br /> (4) It's not clear how signals on "normal" G's are treated. In Figure 5C some are wiped to 0 but others are kept as 1.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors performed experimental evolution of MreB mutants that have a slow-growing round phenotype and studied the subsequent evolutionary trajectory using analysis tools from molecular biology. It was remarkable and interesting that they found that the original phenotype was not restored (most common in these studies) but that the round phenotype was maintained.
Strengths:
The finding that the round phenotype was maintained during evolution rather than that the original phenotype, rod-shaped cells, was recovered is interesting. The paper extensively investigates what happens during adaptation with various different techniques. Also, the extensive discussion of the findings at the end of the paper is well thought through and insightful.
Weaknesses:<br /> I find there are three general weaknesses:
(1) Although the paper states in the abstract that it emphasizes "new knowledge to be gained" it remains unclear what this concretely is. On page 4 they state 3 three research questions, these could be more extensively discussed in the abstract. Also, these questions read more like genetics questions while the paper is a lot about cell biological findings.
(2) it is not clear to me from the text what we already know about the restoration of MreB loss from suppressors studies (in the literature). Are there suppressor screens in the literature and which part of the findings is consistent with suppressor screens and which parts are new knowledge?
(3) The clarity of the figures, captions, and data quantification need to be improved.
Tags
Annotators
URL
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www.biorxiv.org www.biorxiv.org
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Joint Public Review:
An outside expert evaluated your responses to the original reviewers and offered the following comments:
The main criticism was whether deleterious variants were appropriately classified in the work. The authors use two different methods to characterize the effect of alleles to satisfy these comments. The result is somewhat complex. The authors do replicate the effect of dominance on fixation and segregation of deleterious alleles by classifying polymorphisms as synonymous or synonymous with SNPeff. This is not entirely surprising as it is approximately equivalent to classifying based on fold degeneracy (but it includes sites that have other than 0 or 4 fold degeneracy). However, the authors do not mention in the text that their observation of increased segregating deleterious mutations in recessive alleles was only statistically significant in A. halleri (for both analyses). Using SIFT, the authors only find an effect of dominance in A. lyrata. So in reality, while the trends are the same across the analyses, the statistical significance of the effects of dominance was not consistent.
Reviewer 2 had several more detailed criticisms of the manuscript. The first was that the authors should explore the dominance of linked deleterious mutations themselves. I agree that this would be interesting, but it is very difficult to accomplish, and I agree with the author's reluctance to do much more here. The reviewer also criticized the authors simulation approach. The authors provided their simulation script as requested, but declined to do additional simulations under varied selection coefficients. I felt this was a minimally adequate response to the reviewers concerns, but the authors could have reasonably conducted a few additional simulations under varied selection coefficients.
I think that the scope of the findings described in the assessment was reasonable. This is interesting work, but despite the author's arguments, the system is somewhat unique if for no other reason than that balancing selection at S-loci is uniquely strong
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors provided a detailed analysis of the real-time structural changes in actin filaments resulting from cofilin binding, using High-Speed Atomic Force Microscopy (HSAFM). The cofilin family controls the lifespan of actin filaments in cells by severing the filament and promoting depolymerization. Understanding the effects of cofilin on actin filament structure is critical. It is widely acknowledged that cofilin binding significantly shortens the pitch of the actin helix. The authors previously reported (1) that this shortening extends to the unbound region of the actin filament on the pointed end side of the cofilin binding cluster. In this study, the authors presented substantially improved AFM images and provide detailed accounts of the dynamics observed. It was found that a minimal cofilin-binding cluster, consisting of 2-4 molecules, could induce changes in the helical parameters over one or more actin crossover repeats. Adjacent to the cofilin-binding clusters, the actin crossovers were observed to shorten within seconds, and this shortening was limited to one side of the cluster. Additionally, the phosphate binding to the actin filament was observed to stabilize the helical twist, suggesting a mechanism in which cofilin preferentially binds to ADP-bound actin filaments. These findings significantly advance our understanding of actin filament dynamics which is essential for a wide of cellular processes.
However, two insufficient parts exist. Readers should be aware of possible errors in the Mean Axial Distance (MAD) analysis and the limitations of discussions about the actin subunit structure.
The authors have presented findings that the MAD within actin filaments exhibits a significant dependency on the helical twist. However, difficulty in determining each subunit interval from the AFM image might affect the analysis. For example, the observation of three peaks in HHP6 of Figure Supplement 6C, corresponding to 4.5 pairs, showed peak intervals of 5, 11.8, 8.7, and 5.7 nm (measured from the figure). The second region (11.8 nm) appears excessively long. If one peak is hidden in the second region, the MAD becomes 5.5 nm.
The authors also suggest a strong link between the C-form (cofilin binding form of actin found in cofilactin) and the formation of regions of the short pitch helix outside the cofilin binding cluster. However, the AFM observation did not provide any evidence about the actin form in these regions because of measurement limitations. Additionally, Oda et al. (2) have demonstrated that the C-form is highly unstable in the absence of cofilin binding, casting doubt on the possibility of the C-form propagating without cofilin binding. The "C-actin-like structure" in the paper is not necessarily related to the C-form actin. It might be one of the G-forms (monomeric actin forms) or another unknown form.
(1) K. X. Ngo et al., a, Cofilin-induced unidirectional cooperative conformational changes in actin filaments revealed by high-speed atomic force microscopy. eLife 4, (2015).<br /> (2) T. Oda et al., Structural Polymorphism of Actin. Journal of molecular biology 431, 3217-3228 (2019).
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This work probes the control of the hox operon in the cyanobacterium Synechocystis, where this operon directs the synthesis of a bidirectional hydrogenase that functions to produce hydrogen. In assessing the control of the hox system, the authors focused on the relative contributions of cyAbrB2, alongside SigE (and to a lesser extent, SigA and cyAbrB1) under both aerobic and microoxic conditions. In mapping the binding sites of these different proteins, they discovered that cyAbrB2 bound many sites throughout the chromosome, repressed many of its target genes, and preferentially bound regions that were (relatively) rich in AT-residues. These characteristics led the authors to consider that cyAbrB2 may function as a nucleoid-associated protein (NAP) in Synechocystis, given the functional similarities with other NAPs like H-NS. They assessed the local chromosome conformation in both wild type and cyabrB2 mutant strains at multiple sites within a 40 kb window on either side of the hox locus, using a region within the hox operon as bait. They concluded that cyAbrB2 functions as a nucleoid associated protein that influences the activity of SigE through its modulation of chromosome architecture.
The authors approached their experiments carefully, and the data were generally very clearly presented. At the same time, the overall work contains many lines of inquiry and different protein investigations that in some ways made it more challenging to identify the overall take-away message(s).
Based on the data presented, the authors make a strong case for cyAbrB2 as a nucleoid-associated protein, given the multiple ways in which is seems to function similarly to the well-studied Escherichia coli H-NS protein. They now provide additional commentary that relates cyAbrB2 with other nucleoid-associated proteins.
Previous work had revealed a role for SigE in the control of hox cluster expression, which nicely justified its inclusion (and focus) in this study. The focus on cyAbrB2 is also well-justified, given previous reports of its control of hox expression; however, it shares binding sites with an essential homologue cyAbrB1. Interestingly, while the B1 protein appears to bind similar sites, instead of repressing hox expression, it is known as an activator of this operon. If the information on cyAbrB1 is retained in the manuscript, it would be important to consider how cyAbrB1 activity might influence the results described here (although the authors could also consider removing the cyAbrB1 information to help improve the focus of the manuscript).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This manuscript presents a model in which combined action of the transporter-like protein DISP and the sheddases ADAM10/17 promote shedding of a mono-cholesteroylated Sonic Hedgehog (SHH) species following cleavage of palmitate from the dually lipidated precursor ligand. The authors propose that this leads to transfer of the cholesterol-modified SHH to HDL for solubilization. The minimal requirement for SHH release by this mechanism is proposed to be the covalently linked cholesterol modification because DISP could promote transfer of a cholesteroylated mCherry reporter protein to serum HDL. The authors used an in vitro system to demonstrate dependency on DISP/SCUBE2 for release of the cholesterol modified ligand. These results confirm previously published results from other groups (PMC3387659 and PMC3682496).
A strength of the work is the use of a bicistronic SHH-Hhat system to consistently generate dually-lipidated ligand to determine the quantity and lipidation status of SHH released into cell culture media.
Key shortcomings include the unusual normalization strategies used for many experiments and the lack of quantification/statistical analyses for several experiments. Due to these omissions, it is difficult to conclude that the data justify the conclusions. The significance of the data provided is overstated because many of the presented experiments confirm/support previously published work. The study provides a modest advance in understanding of the complex issue of SHH membrane extraction.
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docdrop.org docdrop.org
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in the case of the new world the the the maize plant the wild maize plant had a little cob on it that was only about one centimeter long
for - corn - thousands of years to breed from 1 cm cob to present size - transition - stone age to agriculture - importance of women
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arxiv.org arxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> This paper presents a cognitive model of out-of-distribution generalisation, where the representational basis is grid-cell codes. In particular, the authors consider the tasks of analogies, addition, and multiplication, and the out-of-distribution tests are shifting or scaling the input domain. The authors utilise grid cell codes, which are multi-scale as well as translationally invariant due to their periodicity. To allow for domain adaptation, the authors use DPP-A which is, in this context, a mechanism of adapting to input scale changes. The authors present simulation results demonstrating that this model can perform out-of-distribution generalisation to input translations and re-scaling, whereas other models fail.
Strengths:<br /> This paper makes the point it sets out to - that there are some underlying representational bases, like grid cells, that when combined with a domain adaptation mechanism, like DPP-A, can facilitate out-of-generalisation. I don't have any issues with the technical details.
Weaknesses:<br /> The paper does leave open the bigger questions of 1) how one learns a suitable representation basis in the first place, 2) how to have a domain adaptation mechanism that works in more general settings other than adapting to scale. Overall, I'm left wondering whether this model is really quite bespoke or whether there is something really general here. My comments below are trying to understand how general this approach is.
COMMENTS<br /> This work relies on being able to map inputs into an appropriate representational space. The inputs were integers so it's easy enough to map them to grid locations. But how does this transfer to making analogies in other spaces? Do the inputs need to be mapped (potentially non-linearly) into a space where everything is linear? In general, what are the properties of the embedding space that allows the grid code to be suitable? It would be helpful to know just how much leg work an embedding model would have to do.
It's natural that grid cells are great for domain shifts of translation, rescaling, and rotation, because they themselves are multi-scaled and are invariant to translations and rotations. But grid codes aren't going to be great for other types of domain shifts. Are the authors saying that to make analogies grid cells are all you need? If not then what else? And how does this representation get learned? Are there lots of these invariant codes hanging around? And if so how does the appropriate one get chosen for each situation? Some discussion of the points is necessary as otherwise, the model seems somewhat narrow in scope.
For effective adaptation of scale, the authors needed to use DPP-A. Being that they are relating to brains using grid codes, what processes are implementing DPP-A? Presumably, a computational module that serves the role of DPP-A could be meta-learned? I.e. if they change their task set-up so it gets to see domain shifts in its training data an LSTM or transformer could learn to do this. The presented model comparisons feel a bit of a straw man.
I couldn't see it explained exactly how R works.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors use an interesting expression system called a retron to express single-stranded DNA aptamers. Expressing DNA as a single-stranded sequence is very hard - DNA is naturally double-stranded. However, the successful demonstration by the authors of expressing Lettuce, which is a fluorogenic DNA aptamer, allowed visual demonstration of both expression and folding. This method will likely be the main method for expressing and testing DNA aptamers of all kinds, including fluorogenic aptamers like Lettuce and future variants/alternatives.
Strengths:
This has an overall simplicity which will lead to ready adoption. I am very excited about this work. People will be able to express other fluorogenic aptamers or DNA aptamers tagged with Lettuce with this system.
Weaknesses:
Several things are not addressed/shown:
(1) How stable are these DNA in cells? Half-life?
(2) What concentration do they achieve in cells/copy numbers? This is important since it relates to the total fluorescence output and, if the aptamer is meant to bind a protein, it will reveal if the copy number is sufficient to stoichiometrically bind target proteins. Perhaps the gels could have standards with known amounts in order to get exact amounts of aptamer expression per cell?
(3) Microscopic images of the fluorescent E. coli - why are these not shown (unless I missed them)? It would be good to see that cells are fluorescent rather than just showing flow sorting data.
(4) I would appreciate a better Figure 1 to show all the intermediate steps in the RNA processing, the subsequent beginning of the RT step, and then the final production of the ssDNA. I did not understand all the processing steps that lead to the final product, and the role of the 2'OH.
(5) I would like a better understanding or a protocol for choosing insertion sites into MSD for other aptamers - people will need simple instructions.
(6) Can the gels be stained with DFHBI/other dyes to see the Lettuce as has been done for fluorogenic RNAs?
(7) Sometimes FLAPs are called fluorogenic RNA aptamers - it might be good to mention both terms initially since some people use fluorogenic aptamer as their search term.
(8) What E coli strains are compatible with this retron system?
(9) What steps would be needed to use in mammalian cells?
(10) Is the conjugated RNA stable and does it degrade to leave just the DNA aptamer?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors have developed a valuable method based on a fully cell-free system to express a channel protein and integrate it into a membrane vesicle in order to characterize it biophysically. The study presents a useful alternative to study channels that are not amenable to being studied by more traditional methods.
Strengths:
The evidence supporting the claims of the authors is solid and convincing. The method will be of interest to researchers working on ionic channels, allowing them to study a wide range of ion channel functions such as those involved in transport, interaction with lipids, or pharmacology.
Weaknesses:
The inclusion of a mechanistic interpretation of how the channel protein folds into a protomer or a tetramer to become functional in the membrane would strengthen the study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this important study, Huffer et al posit that non-cold sensing members of the TRPM subfamily of ion channels (e.g., TRPM2, TRPM4, TRPM5) contain a binding pocket for icilin which overlaps with the one found in the cold-activated TRPM8 channel.
The authors identify the residues involved in icilin binding by analyzing the existing TRPM8-icilin complex structures and then use their previously published approach of structure-based sequence comparison to compare the icilin binding residues in TRPM8 to other TRPM channels. This approach uncovered that the residues are conserved in a number of TRPM members: TRPM2, TRPM4, and TRPM5. The authors focus on TRPM4, with the rationale that it has the simplest activation properties (a single Ca2+-binding site). Electrophysiological studies show that icilin by itself does not activate TRPM4, but it strongly potentiates the Ca2+ activation of TRPM4, and introducing the A867G mutation (the mutation that renders avian TRPM8 sensitive to icilin) further increases the potentiating effects of the compound. Conversely, the mutation of a residue that likely directly interacts with icilin in the binding pocket, R901H, results in channels whose Ca2+ sensitivity is not potentiated by icilin.
The data indicate that, just like in TRPV channels, the binding pockets and allosteric networks might be conserved in the TRPM subfamily.
The data are convincing, and the authors employ good experimental controls.
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Reviewer #1 (Public Review):
Summary:
This work combines molecular dynamics (MD) simulations along with experimental elucidation of the efficacy of ATP as a biological hydrotrope. While ATP is broadly known as the energy currency, it has also been suggested to modulate the stability of biomolecules and their aggregation propensity. In the computational part of the work, the authors demonstrate that ATP increases the population of the more expanded conformations (higher radius of gyration) in both a soluble folded mini-protein Trp-cage and an intrinsically disordered protein (IDP) Aβ40. Furthermore, ATP is shown to destabilise the pre-formed fibrillar structures using both simulation and experimental data (ThT assay and TEM images). They have also suggested that the biological hydrotrope ATP has significantly higher efficacy as compared to the commonly used chemical hydrotrope sodium xylene sulfonate (NaXS).
Strengths:
This work presents a comprehensive and compelling investigation of the effect of ATP on the conformational population of two types of proteins: globular/folded and IDP. The role of ATP as an "aggregate solubilizer" of pre-formed fibrils has been demonstrated using both simulation and experiments. They also elucidate the mechanism of action of ATP as a multi-purpose solubilizer in a protein-specific manner. Depending on the protein, it can interact through electrostatic interactions (for predominantly charged IDPs like Aβ40), or primarily van der Waals' interactions through (for Trp-Cage).
Weaknesses:
The data presented by the authors are sound and adequately support the conclusions drawn by the authors. However, there are a few points that could be discussed or elucidated further to broaden the scope of the conclusions drawn in this work as discussed below:
(i) The concentration of ATP used in the simulations is significantly higher (500 mM) as compared to those used in the experiments (6-20 mM) or cellular cytoplasm (~5 mM as mentioned by the authors). Since the authors mention already known concentration dependence of the effect of ATP, it is worth clarifying the possible limitations and implications of the high ATP concentrations in the simulations. It seems ATP can stabilise the proteins at low concentrations, but the current work does not address this possible effect. It would be interesting to see whether the effect of ATP on globular proteins and IDPs remains similar even at lower ATP concentrations.
(ii) The authors make a somewhat ambitious statement that the role of ATP as a solubilizer of pre-formed fibrils could be used as a therapeutic strategy in protein aggregation-related diseases. However, it is not clear how it would be so since ATP is a promiscuous substrate in several biochemical processes and any additional administration of ATP beyond normal cellular concentration (~5 mM) could be detrimental.
(iii) A natural question arises about what is so special about ATP as a solubilizer. The authors have also asked this question but in a limited scope of comparing to a commonly used chemical hydrotrope NaXS. However, a bigger question would be what kind of chemical/physical features make ATP special? For example, (i) if the amphiphilic property is important, what about some standard surfactants? (ii) how would ATP compare to other nucleotides like ADP or GTP? It might be useful to explore such questions in the future to further establish the special role of ATP in this regard.
(iv) In Figure 2F, it seems that in the presence of 0.5 M ATP, the Rg increases (as expected), but the number of native contacts remains almost similar. The reduction in the number of native contacts at higher ATP concentrations is not as dramatic as the increase in Rg. This is somewhat counterintuitive and should be looked into. Normally one would expect a monotonous reduction in the number of native contacts as the protein unfolds (increase in Rg).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In their manuscript "PDGFRRa signaling regulates Srsf3 transcript binding to affect PI3K signaling and endosomal trafficking" Forman and colleagues use iMEPM cells to characterize the effects of PDGF signaling on alternative splicing. They first perform RNA-seq using a one-hour stimulation with Pdgf-AA in control and Srsf3 knockdown cells. While Srsf3 manipulation results in a sizeable number of DE genes, PDGF does not. They then turn to examine alternative splicing, due to findings from this lab. They find that both PDGF and Srsf3 contribute much more to splicing than transcription. They find that the vast majority of PDGF-mediated alternative splicing depends upon Srsf3 activity and that skipped exons are the most common events with PDGF stimulation typically promoting exon skipping in the presence of Srsf3. They used eCLIP to identify RNA regions bound to Srsf3. Under both PDGF conditions, the majority of peaks were in exons with +PDGF having a substantially greater number of these peaks. Interestingly, they find differential enrichment of sequence motifs and GC content in stimulated versus unstimulated cells. They examine 2 transcripts encoding PI3K pathway (enriched in their GO analysis) members: Becn1 and Wdr81. They then go on to examine PDGFRRa and Rab5, an endosomal marker, colocalization. They propose a model in which Srsf3 functions downstream of PDGFRRa signaling to, in part, regulate PDGFRa trafficking to the endosome. The findings are novel and shed light on the mechanisms of PDGF signaling and will be broadly of interest. This lab previously identified the importance of PDGF naling on alternative splicing. The combination of RNA-seq and eCLIP is an exceptional way to comprehensively analyze this effect. The results will be of great utility to those studying PDGF signaling or neural crest biology. There are some concerns that should be considered, however.
(1) It took some time to make sense of the number of DE genes across the results section and Figure 1. The authors give the total number of DE genes across Srsf3 control and loss conditions as 1,629 with 1,042 of them overlapping across Pdgf treatment. If the authors would add verbiage to the point that this leaves 1,108 unique genes in the dataset, then the numbers in Figure 1D would instantly make sense. The same applies to PDGF in Figure 1F and the Venn diagrams in Figure 2.
(2) The percentage of skipped exons in the +PSI on the righthand side of Figure 2F is not readable.
(3) It would be useful to have more information regarding the motif enrichment in Figure 3. What is the extent of enrichment? The authors should also provide a more complete list of enriched motifs, perhaps as a supplement.
(4) It is unclear what subset of transcripts represent the "overlapping datasets" on lines 280-315. The authors state that there are 149 unique overlapping transcripts, but the Venn diagram shows 270. Also, it seems that the most interesting transcripts are the 233 that show alternative splicing and are bound by Srsf3. Would the results shown in Figure 5 change if the authors focused on these transcripts?
(5) In general, there is little validation of the sequencing results, performing qPCR on Arhgap12 and Cep55. The authors should additionally validate the PI3K pathway members that they analyze. Related, is Becn1 expression downregulated in the absence of Srsf3, as would be predicted if it is undergoing NMD?
(6) What is the alternative splicing event for Acap3?
(7) The insets in Figure 6 C"-H" are useful but difficult to see due to their small size. Perhaps these could be made as their own figure panels.
(8) In Figure 6A, it is not clear which groups have statistically significant differences. A clearer visualization system should be used.
(9) Similarly in Figure 6B, is 15 vs 60 minutes in the shSrsf3 group the only significant difference? Is there a difference between scramble and shSrsf3 at 15 minutes? Is there a difference between 0 and 15 minutes for either group?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> Sha K et al aimed at identifying the mechanism of response and resistance to castration in the Pten knockout GEM model. They found elevated levels of TNF overexpressed in castrated tumors associated with an expansion of basal-like stem cells during recurrence, which they show occurring in prostate cancer cells in culture upon enzalutamide treatment. Further, the authors carry on a timed dependent analysis of the role of TNF in regression and recurrence to show that TNF regulates both processes. Similarly, CCL2, which the authors had proposed as a chemokine secreted upon TNF induction following enzalutamide treatment, is also shown to be elevated during recurrence and associated with the remodeling of an immunosuppressive microenvironment through depletion of T cells and recruitment of TAMs.
Strengths:
The paper exploits a well-established GEM model to interrogate mechanisms of response to standard-of-care treatment. This is of utmost importance since prostate cancer recurrence after ADT or ARSi marks the onset of an incurable disease stage for which limited treatments exist. The work is relevant in the confirmation that recurrent prostate cancer is mostly an immunologically "cold" tumor with an immunosuppressive immune microenvironment
Weaknesses:
While the data is consistent and the conclusions are mostly supported and justified, the findings overall are incremental and of limited novelty. The role of TNF and NF-kB signaling in tumor progression and the role of the CCL2-CCR2 in shaping the immunosuppressive microenvironment are well established.
On the other hand, it is unclear why the authors decided to focus on the basal compartment when there is a wealth of literature suggesting that luminal cells are if not exclusively, surely one of the cells of origin of prostate cancer and responsible for recurrence upon antiandrogen treatment. As a result, most of the later shown data has to be taken with caution as it is not known if the same phenomena occur in the luminal compartment.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Liver cancer shows a higher incidence in males than females with incompletely understood causes. This study utilized a mouse model that lacks the bile acid feedback mechanisms (FXR/SHP DKO mice) to study how dysregulation of bile acid homeostasis and a high circulating bile acid may underlie the gender-dependent prevalence and prognosis of HCC. By transcriptomics analysis comparing male and female mice, unique sets of gene signatures were identified and correlated with HCC outcomes in human patients. The study showed that the ovariectomy procedure increased HCC incidence in female FXR/SHP DKO mice that were otherwise resistant to age-dependent HCC development and that removing bile acids by blocking intestine bile acid absorption reduced HCC progression in FXR/SHP DKO mice. Based on these findings, the authors suggest that gender-dependent bile acid metabolism may play a role in the male-dominant HCC incidence, and that reducing bile acid levels and signaling may be beneficial in HCC treatment.
Strengths:
(1) Chronic liver diseases often preceed the development of liver and bile duct cancer. Advanced chronic liver diseases are often associated with dysregulation of bile acid homeostasis and cholestasis. This study takes advantage of a unique FXR/SHP DKO model that develops high organ bile acid exposure and spontaneous age-dependent HCC development in males but not females to identify unique HCC-associated gene signatures. The study showed that the unique gene signature in female DKO mice that had lower HCC incidence also correlated with lower-grade HCC and better survival in human HCC patients.
(2) The study also suggests that differentially regulated bile acid signaling or gender-dependent response to altered bile acids may contribute to gender-dependent susceptibility to HCC development and/or progression.
Weaknesses:
(1) HCC shows heterogeneity, and it is unclear what tissues (tumor or normal) were used from the DKO mice and human HCC gene expression dataset to obtain the gene signature, and how the authors reconcile these gene signatures with HCC prognosis.
(2) The authors identified a unique set of gene expression signatures that are linked to HCC patient outcomes, but analysis of these gene sets to understand the causes of cancer promotion is still lacking. The studies of urea cycle metabolism and estrogen signaling were preliminary and inconclusive. These mechanistic aspects may be followed up in revision or future studies.
(3) While high levels of bile acids are convincingly shown to promote HCC progression, their role in HCC initiation is not established. The DKO model may be limited to conditions of extremely high levels of organ bile acid exposure. The DKO mice do not model the human population of HCC patients with various etiology and shared liver pathology (i.e. cirrhosis). Therefore, high circulating bile acids may not fully explain the male prevalence of HCC incidence.
(4) The authors showed lower circulating bile acids and increased fecal bile acid excretion in female mice and hypothesized that this may be a mechanism underlying the lower bile acid exposure that contributed to lower HCC incidence in female DKO mice. Additional analysis of organ bile acids within the enterohepatic circulation may be performed because a more accurate interpretation of the circulating bile acids and fecal bile acids can be made in reference to organ bile acids and total bile acid pool changes in these mice.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Wilson's Disease (WD) is an inherited rare pathological condition due to a mutation in ATP7B that alters mitochondrial structure and dysfunction. Additionally, WD results in dysregulated copper metabolism in patients. These metabolic abnormalities affect the functions of the liver and can result in cholecystitis. Understanding the immune component and its contribution to WD and cholecystitis has been challenging. In this work, the authors have performed single-cell RNA sequencing of mesenchymal tissue from three WD patients and three liver hemangioma patients.
Strengths:
The authors describe the transcriptomic alterations in myeloid and lymphoid compartments.
Weaknesses:
In brief, this manuscript lacks a clear focus, and the writing needs vast improvement. Figures lack details (or are misrepresented), the results section only catalogs observations, and the discussion needs to focus on their findings' mechanistic and functional relevance. The major weakness of this manuscript is that the authors do not provide a mechanistic link between the absence of ATP7B and NK cells' impaired/altered functions. While the work is of high clinical relevance, there are various areas that could be improved.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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4199
DOI: 10.1007/s00018-024-05142-1
Resource: (BDSC Cat# 4199,RRID:BDSC_4199)
Curator: @bandrow
SciCrunch record: RRID:BDSC_4199
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Bloomington Drosophila Stock Center
DOI: 10.1038/s42003-019-0674-1
Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)
Curator: @bpowell22
SciCrunch record: RRID:SCR_006457
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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BDSC#30924
DOI: 10.1186/s12915-024-01894-1
Resource: BDSC_30924
Curator: @bandrow
SciCrunch record: RRID:BDSC_30924
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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BL3605
DOI: 10.1007/s12031-024-02227-1
Resource: (BDSC Cat# 3605,RRID:BDSC_3605)
Curator: @bandrow
SciCrunch record: RRID:BDSC_3605
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> This manuscript aimed to investigate the emergence of emotional sensitivity and its relationship with gestational age. Using an oddball paradigm and event-related potentials, the authors conducted an experiment in 120 healthy neonates with a gestational age range of 35 to 40 weeks. A significant developmental milestone was identified at 37 weeks gestational age, marking a crucial juncture in neonatal emotional responsiveness.
Strengths:<br /> This study has several strengths, by providing profound insights into the early development of social-emotional functioning and unveiling the role of gestational age in shaping neonatal perceptual abilities. The methodology of this study demonstrates rigor and well-controlled experimental design, particularly involving matched control sounds, which enhances the reliability of the research. Their findings not only contribute to the field of neurodevelopment, but also showcase potential clinical applications, especially in the context of autism screening and early intervention for neurodevelopmental disorders.
Comments on the revised version:
After reviewing the authors' response letter and the revised manuscript, I believe they have done a commendable job in addressing my comments.<br /> Additionally, I concur with the concerns raised by Reviewer #2 regarding several potential confounding factors that require better control in their experimental design. These include the differences in physical properties between vocal and nonvocal stimuli, as well as the infant's exposure to the speech/auditory environment. These concerns should be thoroughly and explicitly discussed in the manuscript, ensuring a clearer understanding for the readers.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Tung and colleagues identify Calreticulin as a repressor of ATF6 signaling using a crispr screen and characterize the functional interaction between ATF6 and CALR.
Strengths:
The manuscript is well written and interesting with an innovative experimental design which provides some new mechanistic insight into ATF6 regulation as well as crosstalk with the IRE1 pathway. The methods used were fit for purpose and reasonable conclusions were drawn from the data presented.
Comments on latest version:
The authors did a good job at addressing my comments even though they found several aspects to exceed the scope of the work. The manuscript is clearer now and the model pushed by the authors is better supported by the data. One point I am curious about the authors' opinion would be about the status of ATF6alpha activation in pathological cells in which CALR is mutated (e.g., myeloproliferative neoplasms), although this neither challenges the conclusions of the manuscript and my positive opinion of the work.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In this study, Ruan et al. investigate the role of the IQCH gene in spermatogenesis, focusing on its interaction with calmodulin and its regulation of RNA-binding proteins. The authors examined sperm from a male infertility patient with an inherited IQCH mutation as well as Iqch CRISPR knockout mice. The authors found that both human and mouse sperm exhibited structural and morphogenetic defects in multiple structures, leading to reduced fertility in Ichq-knockout male mice. Molecular analyses such as mass spectrometry and immunoprecipitation indicated that RNA-binding proteins are likely targets of IQCH, with the authors focusing on the RNA-binding protein HNRPAB as a critical regulator of testicular mRNAs. The authors used in vitro cell culture models to demonstrate an interaction between IQCH and calmodulin, in addition to showing that this interaction via the IQ motif of IQCH is required for IQCH's function in promoting HNRPAB expression. In sum, the authors concluded that IQCH promotes male fertility by binding to calmodulin and controlling HNRPAB expression to regulate the expression of essential mRNAs for spermatogenesis. These findings provide new insight into molecular mechanisms underlying spermatogenesis and how important factors for sperm morphogenesis and function are regulated.
The strengths of the study include the use of mouse and human samples, which demonstrate a likely relevance of the mouse model to humans; the use of multiple biochemical techniques to address the molecular mechanisms involved; the development of a new CRISPR mouse model; ample controls; and clearly displayed results. Assays are done rigorously and in a quantitative manner. Overall, the claims made by the authors in this manuscript are well-supported by the data provided.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This study used prolonged stimulation of a limb to examine possible plasticity in somatosensory evoked potentials induced by the stimulation. They also studied the extent that the blood brain barrier (BBB) was opened by the prolonged stimulation and whether that played a role in the plasticity. They found that there was potentiation of the amplitude and area under the curve of the evoked potential after prolonged stimulation and this was long-lasting (>5 hrs). They also implicated extravasation of serum albumin, caveolae-mediated transcytosis, and TGFb signalling, as well as neuronal activity and upregulation of PSD95. Transcriptomics was done and implicated plasticity related genes in the changes after prolonged stimulation, but not proteins associated with the BBB or inflammation. Next, they address the application to humans using a squeeze ball task. They imaged the brain and suggested that the hand activity led to an increased permeability of the vessels, suggesting modulation of the BBB.
Strengths:
The strengths of the paper are the novelty of the idea that stimulation of the limb can induce cortical plasticity in a normal condition, and it involves the opening of the BBB with albumin entry. In addition, there are many datasets, both rat and human data.
Weaknesses:
The explanation of why prolonged stimulation in the rat was considered relevant to normal conditions is still somewhat weak. The authors argue that the stimulation frequency they used is similar to rhythmic whisker movement. That is a good argument. However, the intensity they used, 2 mA is in the range they say can elicit a seizure if stimulation is 50 Hz. So that weakens the argument.
The authors made a lot of the requested changes but some questions were not addressed or the explanations were so brief that the confusion remained. Please go over the revisions again and make sure sentences are complete, jargon is explained, and arguments/justifications are clear. It will help the reader greatly.
The authors responded to the previous comments of Reviewer 2 regarding experimental design and variability of washout periods. It would be useful to incorporate the response into the paper so the readers know why the authors think the variability was not an important factor in the results.
Comments on the revised version:
The manuscript is improved.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Wang, He et al have constructed a comprehensive single nucleus atlas for the gills of the deep sea Bathymodioline mussels, which possess intracellular symbionts that provide a key source of carbon and allow them to live in these extreme environments. They provide annotations of the different cell states within the gills, shedding light on how multiple cell types cooperate to give rise to the emergent functions of the composite tissues and the gills as a whole. They pay special attention to characterizing the bacteriocyte cell populations and identifying sets of genes that may play a role in their interaction with the symbiotes.
Wang, He et al sample mussels from 3 different environments: animals from their native methane rich environment, animals transplanted to a methane-poor environment to induce starvation and animals that have been starved in the methane-poor environment and then moved back to the methane-rich environment. They demonstrated that starvation had the biggest impact on bacteriocyte transcriptomes. They hypothesize that the up-regulation of genes associated with lysosomal digestion leads to the digestion of the intracellular symbiont during starvation, while the non-starved and reacclimated groups more readily harvest the nutrients from symbiotes without destroying them. Further work exploring the differences in symbiote populations between ecological conditions will further elucidate the dynamic relationship between host and symbiote. This will help disentangle specific changes in transcriptomic state that are due to their changing interactions with the symbiotes from changes associated with other environmental factors.
This paper makes available a high quality dataset that is of interest to many disciplines of biology. The unique qualities of this non-model organism and collection of conditions sampled make it of special interest to those studying deep sea adaptation, the impact of environmental perturbation on Bathymodioline mussels populations, and intracellular symbiotes. The authors also use a diverse array of tools to explore and validate their data.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript by Dubicka and co-workers on calcification in miliolid foraminifera presents an interesting piece of work. The study uses confocal and electron microscopy to show that the traditional picture of calcification in porcelaneous foraminifera is incorrect.
Strengths:<br /> The authors present high-quality images and an original approach to a relatively solid (so I thought) model of calcification.
Weaknesses:
There are several major shortcomings. Despite the interesting subject and the wonderful images, the conclusions of this manuscript are simply not supported at all by the results. The fluorescent images may not have any relation to the process of calcification and should therefore not be part of this manuscript. The SEM images, however, do point to an outdated idea of miliolid calcification. I think the manuscript would be much stronger with the focus on the SEM images and with the speculation of the physiological processes greatly reduced.
Comments on revised version:
I continue to disagree. As the authors acknowledge: 'may be a hint indicating ACC...', but it may also be something else. This is really something else than showing ACC is involved in foraminiferal calcification. I still think the reasoning is shaky and below, I will clarify why the fluorescence may well not be related to ACC and in fact, some or even most of the vesicles may not play the role that the authors suggest. Even if they do, the conclusions are not supported by the data presented here. Unfortunately, I found some of the other answers to my question not satisfactory either.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors utilize fluid-structure interaction analyses to simulate fluid flow within and around the Cambrian cnidarian Quadrapyrgites to reconstruct feeding/respiration dynamics. Based on vorticity and velocity flow patterns, the authors suggest that the polyp expansion and contraction ultimately develop vortices around the organism that are like what modern jellyfish employ for movement and feeding. Lastly, the authors suggest that this behavior is likely a prerequisite transitional form to swimming medusae.
Strengths:
While fluid-structure-interaction analyses are common in engineering, physics, and biomedical fields, they are underutilized in the biological and paleobiological sciences. Zhang et al. provide a strong approach to integrating active feeding dynamics into fluid flow simulations of ancient life. Based on their data, it is entirely likely the described vortices would have been produced by benthic cnidarians feeding/respiring under similar mechanisms. However, some of the broader conclusions require additional justification.
Weaknesses:
(1) The claim that olivooid-type feeding was most likely a prerequisite transitional form to jet-propelled swimming needs much more support or needs to be tailored to olivooids. This suggests that such behavior is absent (or must be convergent) before olivooids, which is at odds with the increasing quantities of pelagic life (whose modes of swimming are admittedly unconstrained) documented from Cambrian and Neoproterozoic deposits. Even among just medusozoans, ancestral state reconstruction suggests that they would have been swimming during the Neoproterozoic (Kayal et al., 2018; BMC Evolutionary Biology) with no knowledge of the mechanics due to absent preservation.<br /> (2) While the lack of ambient flow made these simulations computationally easier, these organisms likely did not live in stagnant waters even within the benthic boundary layer. The absence of ambient unidirectional laminar current or oscillating current (such as would be found naturally) biases the results.<br /> (3) There is no explanation for how this work could be a breakthrough in simulation gregarious feeding as is stated in the manuscript.
Despite these weaknesses the authors dynamic fluid simulations convincingly reconstruct the feeding/respiration dynamics of the Cambrian Quadrapyrgites, though the large claims of transitionary stages for this behavior are not adequately justified. Regardless, the approach the authors use will be informative for future studies attempting to simulate similar feeding and respiration dynamics.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Extracellular ATP represents a danger-associated molecular pattern associated to tissue damage and can act also in an autocrine fashion in macrophages to promote proinflammatory responses, as observed in a previous paper by the authors in abdominal sepsis. The present study addresses an important aspect possibly conditioning the outcome of sepsis that is the release of ATP by bacteria. The authors show that sepsis-associated bacteria do in fact release ATP in a growth dependent and strain-specific manner. However, whether this bacterial derived ATP play a role in the pathogenesis of abdominal sepsis has not been determined. To address this question, a number of mutant strains of E. coli has been used first to correlate bacterial ATP release with growth and then, with outer membrane integrity and bacterial death. By using E. coli transformants expressing the ATP-degrading enzyme apyrase in the periplasmic space, the paper nicely shows that abdominal sepsis by these transformants results in significantly improved survival. This effect was associated to the reduction of small peritoneal macrophages and CX3CR1+ monocytes, and increase in neutrophils. To extrapolate the function of bacterial ATP from the systemic response to microorganisms, the authors exploited bacterial OMVs either loaded or not with ATP to investigate the systemic effects devoid of living microorganisms. This approach showed that ATP-loaded OMVs induced degranulation of neutrophils after lysosomal uptake, suggesting this mechanism could contribute to sepsis severity.
Strengths:
The most compelling part of the study is the analysis of E. coli mutants to address different aspects of bacterial release of ATP that could be pathogenically relevant during systemic dissemination of bacteria in the host.
Weaknesses:
As pointed out in the limitations of the study whether ATP-loaded OMVs could provide a mechanistic proof of the pathogenetic role of bacteria-derived ATP independently of live microorganisms in sepsis is interesting but not definitively convincing. It could be useful to see whether degranulation of neutrophils is differently induced also by apyrase-expressing vs control E. coli transformants. Also, the increase of neutrophils in bacterial ATP-depleted abdominal sepsis, which has better outcome than "ATP-proficient" sepsis, seems difficult to correlate to the hypothesized tissue damage induced by ATP delivered via non-infectious OMVs. Is neutrophils count affected by ATP delivered via OMVs? Probably a comparison of cytokine profiles in the abdominal fluids of E. coli and OMV treated animals could be helpful in defining the different responses induced by OMV-delivered vs bacterial-released ATP.
The analyses performed on OMV treated versus E. coli infected mice are not immediately related and difficult to combine when trying to draw a pathogenetic hypothesis for bacterial ATP in sepsis.
It's not clear why lung neutrophils were used for RNAseq.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Gating of Kv10 channels is unique because it involves coupling between non-domain swapped voltage sensing domains, a domain-swapped cytoplasmic ring assembly formed by the N- and C-termini, and the pore domain. Recent structural data suggests that activation of the voltage sensing domain relieves a steric hindrance to pore opening, but the contribution of the cytoplasmic domain to gating is still not well understood. This aspect is of particular importance because proteins like calmodulin interact with the cytoplasmic domain to regulate channel activity. The effects of calmodulin (CaM) in WT and mutant channels with disrupted cytoplasmic gating ring assemblies are contradictory, resulting in inhibition or activation, respectively. The underlying mechanism for these discrepancies is not understood. In the present manuscript, Reham Abdelaziz and collaborators use electrophysiology, biochemistry and mathematical modeling to describe how mutations and deletions that disrupt inter-subunit interactions at the cytoplasmic gating ring assembly affect Kv10.1 channel gating and modulation by CaM. In the revised manuscript, additional information is provided to allow readers to identify within the Kv10.1 channel structure the location of E600R, one of the key channel mutants analyzed in this study. However, the mechanistic role of the cytoplasmic domains that this study focuses on, as well as the location of the ΔPASCap deletion and other perturbations investigated in the study remain difficult to visualize without additional graphical information. This can make it challenging for readers to connect the findings presented in the study with a structural mechanism of channel function.
The authors focused mainly on two structural perturbations that disrupt interactions within the cytoplasmic domain, the E600R mutant and the ΔPASCap deletion. By expressing mutants in oocytes and recording currents using Two Electrode Voltage-Clamp (TEV), it is found that both ΔPASCap and E600R mutants have biphasic conductance-voltage (G-V) relations and exhibit activation and deactivation kinetics with multiple voltage-dependent components. Importantly, the mutant-specific component in the G-V relations is observed at negative voltages where WT channels remain closed. The authors argue that the biphasic behavior in the G-V relations is unlikely to result from two different populations of channels in the oocytes, because they found that the relative amplitude between the two components in the G-V relations was highly reproducible across individual oocytes that otherwise tend to show high variability in expression levels. Instead, the G-V relations for all mutant channels could be well described by an equation that considers two open states O1 and O2, and a transition between them; O1 appeared to be unaffected by any of the structural manipulations tested (i.e. E600R, ΔPASCap, and other deletions) whereas the parameters for O2 and the transition between the two open states were different between constructs. The O1 state is not observed in WT channels and is hypothesized to be associated with voltage sensor activation. O2 represents the open state that is normally observed in WT channels and is speculated to be associated with conformational changes within the cytoplasmic gating ring that follow voltage sensor activation, which could explain why the mutations and deletions disrupting cytoplasmic interactions affect primarily O2.
Severing the covalent link between the voltage sensor and pore reduced O1 occupancy in one of the deletion constructs. Although this observation is consistent with the hypothesis that voltage-sensor activation drives entry into O1, this result is not conclusive. Structural as well as functional data has established that the coupling of the voltage sensor and pore does not entirely rely on the S4-S5 covalent linker between the sensor and the pore, and thus the severed construct could still retain coupling through other mechanisms, which is consistent with the prominent voltage dependence that is observed. If both states O1 and O2 require voltage sensor activation, it is unclear why the severed construct would affect state O1 primarily, as suggested in the manuscript, as opposed to decreasing occupancy of both open states. In line with this argument, the presence of Mg2+ in the extracellular solution affected both O1 and O2. This finding suggests that entry into both O1 and O2 requires voltage-sensor activation because Mg2+ ions are known to stabilize the voltage sensor in its most deactivated conformations.
Activation towards and closure from O1 is slow, whereas channels close rapidly from O2. A rapid alternating pulse protocol was used to take advantage of the difference in activation and deactivation kinetics between the two open components in the mutants and thus drive an increasing number of channels towards state O1. Currents activated by the alternating protocol reached larger amplitudes than those elicited by a long depolarization to the same voltage. This finding is interpreted as an indication that O1 has a larger macroscopic conductance than O2. In the revised manuscript, the authors performed single-channel recordings to determine why O1 and O2 have different macroscopic conductance. The results show that at voltages where the state O1 predominates, channels exhibited longer open times and overall higher open probability, whereas at more depolarized voltages where occupancy of O2 increases, channels exhibited more flickery gating behavior and decreased open probability. These results are informative but not conclusive because additional details about how experiments were conducted, and group data analysis are missing. Importantly, results showing inhibition of single ΔPASCap channels by a Kv10-specific inhibitor are mentioned but not shown or quantitated - these data are essential to establish that the new O1 conductance indeed represents Kv10 channel activity.
It is shown that conditioning pulses to very negative voltages result in mutant channel currents that are larger and activate more slowly than those elicited at the same voltage but starting from less negative conditioning pulses. In voltage-activated curves, O1 occupancy is shown to be favored by increasingly negative conditioning voltages. This is interpreted as indicating that O1 is primarily accessed from deeply closed states in which voltage sensors are in their most deactivated position. Consistently, a mutation that destabilizes these deactivated states is shown to largely suppress the first component in voltage-activation curves for both ΔPASCap and E600R channels.
The authors then address the role of the hidden O1 state in channel regulation by calmodulation. Stimulating calcium entry into oocytes with ionomycin and thapsigarging, assumed to enhance CaM-dependent modulation, resulted in preferential potentiation of the first component in ΔPASCap and E600R channels. This potentiation was attenuated by including an additional mutation that disfavors deeply closed states. Together, these results are interpreted as an indication that calcium-CaM preferentially stabilizes deeply closed states from which O1 can be readily accessed in mutant channels, thus favoring current activation. In WT channels lacking a conducting O1 state, CaM stabilizes deeply closed states and is therefore inhibitory. It is found that the potentiation of ΔPASCap and E600R by CaM is more strongly attenuated by mutations in the channel that are assumed to disrupt interaction with the C-terminal lobe of CaM than mutations assumed to affect interaction with the N-terminal lobe. These results are intriguing but difficult to interpret in mechanistic terms. The strong effect that calcium-CaM had on the occupancy of the O1 state in the mutants raises the possibility that O1 can be only observed in channels that are constitutively associated with CaM. To address this, a biochemical pull-down assay was carried out to establish that only a small fraction of channels are associated with CaM under baseline conditions. These CaM experiments are potentially very interesting and could have wide physiological relevance. However, the approach utilized to activate CaM is indirect and could result in additional non-specific effects on the oocytes that could affect the results.
Finally, a mathematical model is proposed consisting of two layers involving two activation steps for the voltage sensor, and one conformational change in the cytoplasmic gating ring - completion of both sets of conformational changes is required to access state O2, but accessing state O1 only requires completion of the first voltage-sensor activation step in the four subunits. The model qualitatively reproduces most major findings on the mutants. Although the model used is highly symmetric and appears simple, the mathematical form used for the rate constants in the model adds a layer of complexity to the model that makes mechanistic interpretations difficult. In addition, many transitions that from a mechanistic standpoint should not depend on voltage were assigned a voltage dependence in the model. These limitations diminish the overall usefulness of the model which is prominently presented in the manuscript. The most important mechanistic assumptions in the model are not addressed experimentally, such as the proposition that entry into O1 depends on the opening of the transmembrane pore gate, whereas entry into O2 involves gating ring transitions - it is unclear why O2 would require further gating ring transitions to conduct ions given that the gating ring can already support permeation by O1 without any additional conformational changes.
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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BDSC#27,247
DOI: 10.1007/s00018-023-04918-1
Resource: (BDSC Cat# 27247,RRID:BDSC_27247)
Curator: @mpairish
SciCrunch record: RRID:BDSC_27247
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www.youtube.com www.youtube.com
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1:09 (Norris, offscreen) All the time you're collecting information you're asking new questions. That's the key 1:14 part of science. It's not just one question and the answer, it's one question leading 1:19 to a bunch of other questions, leading to a bunch of other answers, which in turn eventually 1:24 lead you to a much more full understanding of the process.
Norris describes the "key part of science"
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0:02 (Narrator) Science, the art of learning about the natural world around us. It seems straight-foward, 0:08 you ask a question, you make a hypothesis about what you expect to find, then you perform 0:14 an experiment to see if the hypothesis is correct, you analyze the data, and determine 0:20 if you were right. Simple, right? Well, not really. There is much more to it than that, 0:27 which is what makes science so exciting. And fun! In fact, scientists often describe it 0:34 as a process that is all about exploring, asking questions, testing hypotheses, and 0:41 changing directions if their original ideas were wrong; all the while working and sharing 0:47 with other scientists, advancing what 0:50 we know 0:51 about the world 0:52 around us.
"Science [is] the art of learning about the natural world around us" (0:02). Unlike the linear process that often comes to mind, the scientific process constantly loops back onto itself and even entirely changes directions as more and more data is accumulated. This is what makes science so exciting, the discovery of information, the new questions prompted by such discoveries, and the interconnectedness of the science community which expands upon this process one hundred fold.
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Reviewer #1 (Public Review):
This manuscript by Negi et al. investigates the effects of different ubiquitin and ubiquitin-like modifications on the stability of substrate proteins, seeking to provide mechanistic insights into known effects of these modifications on cellular protein abundance. The authors focus on comparative studies of two modifications, ubiquitin and FAT10 (a protein with two ubiquitin-like domains), on a panel of substrate proteins; prior work had established that FAT10-conjugated proteins had lower stability to proteosomal degradation than Ub-modified counterparts.
Strengths of the work include its integration of data across diverse approaches, including molecular dynamics simulations, solution NMR spectroscopy, and in vitro and cellular stability assays. From these, the authors provide provocative mechanistic insight into the lower stability of FAT10 on its own, and in FAT10-mediated destabilization of substrate proteins in computational and experimental findings. Notably, such destabilization impacts both the tag and tagged proteins, raising some provocative questions about mechanism. The data here are generally compelling, albeit with minor concerns on presentation in parts. Conclusions from this work will be interesting to scientists in several fields, particularly those interested in cellular proteostasis and in vitro protein design / long-range communication.
The most substantial weakness of this work from my perspective is the specificity of these destabilization effects. In particular, technical challenges of producing bona fide Ub- or FAT10-conjugated substrates with native linkages limits the ability to conduct in vitro studies on exactly the same molecules as being studied in cellular environments. Given some discussion in the manuscript about the importance of linkage location on the specificity of certain tag/substrate interactions, this raises an understandable but unfortunate caveat that needs to be considered more fully both in general and in light of data from other fields (e.g. single molecule pulling) showing site-dependence of comparable effects. I note that these concerns do not impact the caliber of the conclusions themselves, but perhaps suggest area for caution as to their potential impact at this time.
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Reviewer #1 (Public Review):
This work focuses on the trade-off between precision and robustness in morphogen gradients of Hedgehog signaling. It presents a framework for how hedgehog signaling rises to precise responses and robust responses. This Framework is based on the characteristics of the hedgehog signaling pathway and specifically on the characteristics of the dynamical and stationary gradients that it forms in the Drosophila wing disc. On the one hand, the manuscript takes into account known results showing that the Hedgehog stationary gradient is robust due to a self-enhanced degradation (via activation of the Patched receptor). On the other hand, it uses the concept of dynamic interpretation of the gradient introduced by the leading author of this manuscript. According to this interpretation, different targets may be responding to a single signaling threshold and what differentiates the targets is whether they respond to the transient gradient, which extends over more cells, or if they respond to the stationary gradient. The Framework presented in this manuscript takes this prior knowledge and builds on it. The Framework proposes that the response from different targets will not be equally robust. Specifically, if the target responds to the stationary gradient, it will be a target with a robust response. Conversely, if the target responds to the gradient while it is being built, then it will be less robust but more precise. This framework is analyzed using mathematical models. Finally, experimental data that partially corroborate this framework are presented, focusing on the col and Dpp targets, which, according to previous results, read the stationary and transient gradients, respectively. To changes in Hh levels, the col pattern is more robust than the Dpp pattern. Furthermore, it is shown that this robustness decreases if the Patched receptor is not regulated. Hence, these experimental results confirm that the robustness is target-specific, as predicted by the models. The precision of the Dpp pattern is not tested experimentally.
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Reviewer #1 (Public Review):
Kerkoerle and colleagues present a very interesting comparative fMRI study in humans and monkeys, assessing neural responses to surprise reactions at the reversal of a previously learned association. The implicit nature of this task, assessing how this information is represented without requiring explicit decision making, is an elegant design. The paper reports that both humans and monkeys show neural responses across a range of areas when presented with incongruous stimulus pairs. Monkeys also show a surprise response when the stimuli are presented in the reversed direction. However, humans show no such surprise response based on this reversal, suggesting that they encode the relationship reversibly and bidirectionally, unlike the monkeys. This has been suggested as a hallmark of symbolic representation, that might be absent in nonhuman animals.
I find this experiment and the results quite compelling, and the data do support the hypothesis that humans are somewhat unique in their tendency to form reversible, symbolic associations. I think that an important strength of the results is that the critical finding is the presence of an interaction between congruity and canonicity in macaques, which does not appear in humans. These results go a long way to allay concerns I have about the comparison of many human participants to a very small number of macaques.
The results do appear to show that macaques show the predicted interaction effect (even despite the sample size), while humans do not. I think this is quite convincing. (Although had the results turned out differently (for example an effect in humans that was absent in macaques), I think this difference in sample size would be considerably more concerning.)
I would also note that while I agree with the authors conclusions, it is also notable to me that the congruity effect observed in humans (red vs blue lines in Fig. 2B) appears to be far more pronounced than any effect observed in the macaques (Fig. 3C-3). Again, this does not challenge the core finding of this paper but does suggest methodological or possibly motivational/attentional differences between the humans and the monkeys (or, for example, that the monkeys had learned the associations less strongly and clearly than the humans). The authors now discuss this more fully.
This is a strong paper with elegant methods and makes a worthwhile contribution to our understanding of the neural systems supporting symbolic representations in humans, as opposed to other animals.
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Reviewer #1 (Public Review):
More than ten years ago, it was shown that activity in the primary visual cortex of mice substantially increases when mice are running compared to when they are sitting still. This finding 'revolutionised' our thinking about visual cortex, turning away from it being a passive image processor and highlighting the influence of non-visual factors. The current study now for the first time repeats this experiment in marmosets. The authors find that in contrast to mice, marmoset V1 activity is slightly suppressed during running, and they relate this to differences in gain modulations of V1 activity between the two species.
Strengths
- Replication in primates of the original finding in mice partly took so long, because of the inherent difficulties with recording from the brain of a running primate. In fact one recent, highly related study on macaques looked at spontaneous limb movements as the macaque was sitting. The treadmill for the marmosets in the current study is a very elegant solution to the problem of running in primates. It allows for true replication of the 'running vs stationary' experiment and undoubtedly opens up many possibilities for other experiments recording from a head-fixed but active marmoset.<br /> - In addition to their own data in marmoset, the authors run their analyses on a publicly available data set in mouse. This allows them to directly compare mouse and marmoset findings, which significantly strengthens their conclusions.<br /> - Marmoset vision is fundamentally different from mouse vision as they have a fovea and make goal-directed eye movements. In this revised version of their paper, the authors acknowledge this and investigate the possible effect of eye movements and pupil size on the differences they find between running and stationary. They conclude that eye input does not explain all these differences.
Significance
The paper provides interesting new evidence to the ongoing discussion about the influence of non-visual factors in general, and running in particular, on visual cortex activity. As such, it helps to pull this discussion out of the rodent field mainly and into the field of primate research. The bigger question of *why* there are differences between rodents and primates remains still unanswered, but the authors do their best to provide possible explanations. The elegant experimental set-up of the marmoset on a treadmill will certainly add new findings to this issue also in the years to come.
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Reviewer #1 (Public Review):
Summary:
The current study provided a follow-up analysis using published datasets focused on the individual variability of both the distraction effect (size and direction) and the attribute integration style, as well as the association between the two. The authors tried to answer the question of whether the multiplicative attribute integration style concurs with a more pronounced and positively oriented distraction effect.
Strengths:
The analysis extensively examined the impacts of various factors on decision accuracy, with particular focus on using two-option trials as control trials, following the approach established by Cao & Tsetsos (2022). The statistical significance results were clearly reported.
The authors meticulously conducted supplementary examinations, incorporating the additional term HV+LV into GLM3. Furthermore, they replaced the utility function from the expected value model with values from the composite model.
Weaknesses:
The authors did a great job addressing the weaknesses I raised in the previous round of review, except on the generalizability of the current result in the larger context of multi-attribute decision-making. It is not really a weakness of the manuscript but more of a limitation of the studied topic, so I want to keep this comment for public readers.
The reward magnitude and probability information are displayed using rectangular bars of different colors and orientations. Would that bias subjects to choose an additive rule instead of the multiplicative rule? Also, could the conclusion be extended to other decision contexts such as quality and price, where a multiplicative rule is hard to formulate?
Overall, the authors have achieved their aims after clarifying that the study was trying to establish a correlation between the integration style and attraction effect. This result may be useful to inspire neuroimaging or neuromodulation studies that investigate multi-attribute decision making.
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Reviewer #1 (Public Review):
Summary:
Rook et al examined the role of BMP signaling in cerebellum development, using chick as a model alongside human tissue samples. They first examined p-SMADs and found differences between the species, with human samples retaining high p-SMAD after foliation, while in chick, BMP signaling appears to decrease following foliation. To understand the role of BMP during early development, they then used early chick embryos to modulate BMP, using either a constitutively active BMP regulator to increase BMP signaling or overexpressing the negative intracellular BMP regulator to decrease BMP signaling. After validating the constructs in ovo, the authors then examined GNP morphology and migration. They then determined whether the effects were cell autonomous.
Strengths:
The experiments were well-designed and well-controlled. The figures were extremely clear and convincing, and the accompanying drawings help orient the reader to easily understand the experimental set up. These studies also help clarify the role of BMP at different stages of cerebellum development, suggesting early BMP signaling is required for dorsalization, not rhombic lip induction, and that later BMP signaling is needed to regulate the timing of migration and maturation of granule neurons.
Weaknesses:
While these studies certainly hint that BMP modulation may affect tumor growth, this was not explicitly tested here. Future studies are required to generalize the functional role of BMP signaling in normal cerebellum development to malignant growth.
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Reviewer #1 (Public Review):
Summary:
Zhu et al. set out to better understand the neural mechanisms underlying Drosophila larval escape behavior. The escape behavior comprises several sequenced movements, including a lateral roll motion followed by fast crawling. The authors specifically were looking to identify neurons important for the roll-to-crawl transition.
Strengths:
This paper is clearly written, and the experiments are logical and complementary. They support the author's main claim that SeIN128 is a type of descending neuron that is both necessary and sufficient to modulate the termination of rolling. In general, the rigor is high.
Weaknesses:
-This manuscript is narrowly focused on Drosophila larval escape behavior. It would be more accessible to a broader audience if this work were put into a larger context of descending control.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Campbell et al investigated the effects of light on the human brain, in particular the subcortical part hypothalamus during auditory cognitive tasks. The mechanisms and neuronal circuits underlying light effects in non-image forming responses are so far mostly studied in rodents but are not easily translated in humans. Therefore, this is a fundamental study aiming to establish the impact light illuminance has on the subcortical structures using the high-resolution 7T fMRI. The authors found that parts of the hypothalamus are differently responding to illuminance. In particular, they found that the activity of the posterior hypothalamus increases while the activity of the anterior and ventral parts of the hypothalamus decreases under high illuminance. The authors also report that the performance of the 2-back executive task was significantly better in higher illuminance conditions. However, it seems that the activity of the posterior hypothalamus subpart is negatively related to the performance of the executive task, implying that it is unlikely that this part of the hypothalamus is directly involved in the positive impact of light on performance observed. Interestingly, the activity of the posterior hypothalamus was, however, associated with an increased behavioural response to emotional stimuli. This suggests that the role of this posterior part of the hypothalamus is not as simple regarding light effects on cognitive and emotional responses. This study is a fundamental step towards our better understanding of the mechanisms underlying light effects on cognition and consequently optimising lighting standards.
Strengths:
While it is still impossible to distinguish individual hypothalamic nuclei, even with the high-resolution fMRI, the authors split the hypothalamus into five areas encompassing five groups of hypothalamic nuclei. This allowed them to reveal that different parts of the hypothalamus respond differently to an increase in illuminance. They found that higher illuminance increased the activity of the posterior part of the hypothalamus encompassing the MB and parts of the LH and TMN, while decreasing the activity of the anterior parts encompassing the SCN and another part of TMN. These findings are somewhat in line with studies in animals. It was shown that parts of the hypothalamus such as SCN, LH, and PVN receive direct retinal input in particular from ipRGCs. Also, acute chemogenetic activation of ipRGCs was shown to induce activation of LH and also increased arousal in mice.
Weaknesses:
While the light characteristics are well documented and EDI calculated for all of the photoreceptors, it is not very clear why these irradiances and spectra were chosen. It would be helpful if the authors explained the logic behind the four chosen light conditions tested. Also, the lights chosen have cone-opic EDI values in a high correlation with the melanopic EDI, therefore we can't distinguish if the effects seen here are driven by melanopsin and/or other photoreceptors. In order to provide a more mechanistic insight into the light-driven effects on cognition ideally one would use silent substitution approach to distinguish between different photoreceptors. This may be something to consider when designing the follow-up studies.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
The current study aims to quantify associations between regular use of proton-pump inhibitors (PPI) - defined as using PPI most days of the week during the last 4 weeks at one cross-section in time - with several respiratory outcomes (6 in total: risk of influenza, pneumonia, COVID-19, other respiratory tract infections, as well as COVID-19 severity and mortality) up to several years later in time.
Strengths:
Several sensitivity analyses were performed, including i) estimation of the e-value to assess how strong unmeasured confounders should be to explain observed effects, ii) comparison with another drug with a similar indication to potentially reduce (but not eliminate) confounding by indication, iii)
Weaknesses:
While the original submission had several weaknesses, the authors have appropriately addressed all issues raised. There are inevitable weaknesses remaining, but these are appropriately highlighted in the discussion. Remaining weaknesses that remain - but are highlighted in the discussion - include the fact that the main exposure of interest is only measured at one time-point whereas outcomes are assessed over a long time period, the inclusion of prevalent users leading to potential bias (e.g. those experiencing bad outcomes already stopping because of side-effects before inclusion in the study), and the possibility of unmeasured confounding explaining observations (e.g. severity of underlying comorbidities leading to PPI prescriptions combined with the absence of information about comorbidity severity), and potential selection bias.
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Reviewer #1 (Public Review):
Summary:
Horn and colleagues present data suggesting that the targeting of GREM1 has little impact on a mouse model of metabolic dysfunction-associated steatohepatitis. Importantly, they also challenge existing data on the detection of GREM1 by ELISA in serum or plasma by demonstrating that high-affinity binding of GREM1 to heparin would lead to localisation of GREM1 in the ECM or at the plasma membrane of cells.
Strengths:
This is an impressive tour-de-force study around the potential of targeting GREM1 in MASH.
This paper will challenge many existing papers in the field around our ability to detect GREM1 in circulation, at least using antibody-mediated detection.
Well-controlled, detailed studies like this are critically important in order to challenge less vigorous studies in the literature.
The impressive volume of high-level, well-controlled data using an impressive range of in vitro biochemical techniques, rodent models, and human liver slices.
Weaknesses: only minor.
(1) The authors clearly show that heparin can limit the diffusion of GREM1 into the circulation-however, in a setting where GREM1 is produced in excess (e.g. cancer), could this "saturate" the available heparin and allow GREM1 to "escape" into the circulation?
(2) Secondly, has the author considered that GREM1 be circulating bound to a chaperone protein like albumin which would reduce its reactivity with GREM1 detection antibodies?
(3) Statistics-there is no mention of blinding of samples-I assume this was done prior to analysis?
(4) Line 211-I suggest adding the Figure reference at the end of this sentence to direct the reader to the relevant data.
(5) Figure 1E Y-axis units are a little hard to interpret-can integers be used?
(6) Did the authors attempt to detect GREM1 protein by IHC? There are published methods for this using the R&D Systems mouse antibody (PMID 31384391).
(7) Did the authors ever observe GREM1 internalisation using their Atto-532 labelled GREM1?
(8) Did the authors complete GREM1 ISH in the rat CDAA-HFD model? Was GREM1 upregulated, and if so, where?
(9) Supplementary Figure 4C - why does the GFP level decrease in the GREM1 transgenic compared to control the GFP mouse? No such change is observed in Supplementary Figure 4E.
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Reviewer #1 (Public Review):
Summary:
The authors used a novel multi-dimensional experience sampling (mDES) approach to identify data-driven patterns of experience samples that they use to interrogate fMRI data collected during naturalistic movie-watching data. They identify a set of multi-sensory features of a set of movies that delineate low-dimensional gradients of BOLD fMRI signal patterns that have previously been linked to fundamental axes of cortical organization.
Strengths:
The novel solution to challenges associated with experience sampling offers potential access to aspects of experience that have been challenging to assess. While inventive, I worry that the reliability of the mDES approach is currently under-investigated, making it challenging to interpret the import of the later analyses, which are themselves strong and compelling.
Weaknesses:
The lack of direct interrogation of individual differences/reliability of the mDES scores warrants some pause.
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Reviewer #1 (Public Review):
Summary:
In this work, Noorman and colleagues test the predictions of the "four-stage model" of consciousness by combining psychophysics and scalp EEG in humans. The study relies on an elegant experimental design to investigate the respective impact of attentional and perceptual blindness on visual processing.
The study is very well summarised, the text is clear and the methods seem sound. Overall, a very solid piece of work. I haven't identified any major weaknesses. Below I raise a few questions of interpretation that may possibly be the subject of a revision of the text.
(1) The perceptual performance on Fig1D appears to show huge variation across participants, with some participants at chance levels and others with performance > 90% in the attentional blink and/or masked conditions. This seems to reveal that the procedure to match performance across participants was not very successful. Could this impact the results? The authors highlight the fact that they did not resort to post-selection or exclusion of participants, but at the same time do not discuss this equally important point.
(2) In the analysis on collinearity and illusion-specific processing, the authors conclude that the absence of a significant effect of training set demonstrates collinearity-only processing. I don't think that this conclusion is warranted: as the illusory and non-illusory share the same shape, so more elaborate object processing could also be occuring. Please discuss.
(3) Discussion, lines 426-429: It is stated that the results align with the notion that processes of perceptual segmentation and organization represent the mechanism of conscious experience. My interpretation of the results is that they show the contrary: for the same visibility level in the attentional blind or masking conditions, these processes can be implicated or not, which suggests a role during unconscious processing instead.
(4). The two paradigms developed here could be used jointly to highlight non-idiosyncratic NCCs, i.e. EEG markers of visibility or confidence that generalise regardless of the method used. Have the authors attempted to train the classifier on one method and apply it to another (e.g. AB to masking and vice versa)? What perceptual level is assumed to transfer?
(5). How can the results be integrated with the attentional literature showing that attentional filters can be applied early in the processing hierarchy?
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Reviewer #1 (Public Review):
Summary:
It is suggested that for each limb the RG (rhythm generator) can operate in three different regimes: a non-oscillating state-machine regime, and in a flexordriven and a classical half-center oscillatory regime. This means that the field can move away from the old concept that there is only room for the classic half-center organization
Strengths:
A major benefit of the present paper is that a bridge was made between various CPG concepts ( "a potential contradiction between the classical half-center and flexor-driven concepts of spinal RG operation"). Another important step forward is the proposal about the neural control of slow gait ("at slow speeds ({less than or equal to} 0.35 m/s), the spinal network operates in a state regime and requires external inputs for phase transitions, which can come from limb sensory feedback and/or volitional inputs (e.g. from the motor cortex").
Weaknesses:
Some references are missing.
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Reviewer #1 (Public Review):
Summary:
This paper provides a resource for researchers studying the marine annelid Platynereis dumerilii. It is only the third whole-body connectome to be assembled and thus provides a comparison with those less complex animals: the nematode Caenorhabditis elegans and the tunicate Ciona intestinialis. The paper catalogs all cells in the body, not just neurons, and details how sensory neurons, interneurons, motor neurons, and effector organs are connected. From this, the authors are able to extract information about the organization of different aspects of the nervous system. These include the extent of recurrent connectivity, unimodal and multimodal sensory processing, and long-range and short-range connectivity.
Several interesting conclusions are drawn, including the concept that circuit evolution might have proceeded by duplication and diversion of cell types, much as it has been posited that gene evolution has occurred. It also informs the understanding of the evolution of segmental body plans in annelids by mapping and comparing cells in each segment.
Strengths:
This paper contains a wealth of data. The raw dataset is available. The codes and scripts are provided to allow interested readers to utilize this dataset.
The analysis is painstakingly meticulous. The diagrams are organized to orient the reader to the complexities of this overwhelming analysis
Weaknesses:
The strength of the paper is also its weakness. It contains so much data and analysis that it is burdensome to read and understand. There are 16 multi-panel data figures in the main text, and \another 38 supplemental figures, and 5 videos.
The impact of the paper is diminished by its size and depth. The paper could be broken up into smaller thematic papers that would be more accessible to researchers interested in particular topics. For example, there could be a single paper on the mushroom body and another paper on the segmental organization.
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Reviewer #1 (Public Review):
The authors in this paper investigate the nature of the activity in the rodent EPN during a simple freely moving cue-reward association task. Given that primate literature suggests movement coding whereas other primate and rodent studies suggest mainly reward outcome coding in the EPNs, it is important to try to tease apart the two views. Through careful analysis of behavior kinematics, position, and neural activity in the EPNs, the authors reveal an interesting and complex relationship between the EPN and mouse behavior.
Strengths:
(1) The authors use a novel freely moving task to study EPN activity, which displays rich movement trajectories and kinematics. Given that previous studies have mostly looked at reward coding during head-fixed behavior, this study adds a valuable dataset to the literature.
(2) The neural analysis is rich and thorough. Both single neuron level and population level (i.e. PCA) analysis are employed to reveal what EPN encodes.
Weaknesses:
(1) One major weakness in this paper is the way the authors define the EPN neurons. Without a clear method of delineating EPN vs other surrounding regions, it is not convincing enough to call these neurons EPNs solely from looking at the electrode cannula track from Figure 2B. Indeed, EPN is a very small nucleus and previous studies like Stephenson-Jones et al (2016) have used opto-tagging of Vglut2 neurons to precisely label EPN single neurons. Wallace et al (2017) have also shown the existence of SOM and PV-positive neurons in the EPN. By not using transgenic lines and cell-type specific approaches to label these EPN neurons, the authors miss the opportunity to claim that the neurons recorded in this study do indeed come from EPN. The authors should at least consider showing an analysis of neurons slightly above or below EPN and show that these neurons display different waveforms or firing patterns.
(2) The authors fail to replicate the main finding about EPN neurons which is that they encode outcome in a negative manner. Both Stephenson-Jones et al (2016) and Hong and Hikosaka (2008) show a reward response during the outcome period where firing goes down during reward and up during neutral or aversive outcome. However, Figure 2 G top panel shows that the mean population is higher during correct trials and lower during incorrect trials. This could be interesting given that the authors might try recording from another part of EPN that has not been studied before. However, without convincing evidence that the neurons recorded are from EPN in the first place (point 1), it is hard to interpret these results and reconcile them with previous studies.
3) The authors say that: 'reward and kinematic doing are not mutually exclusive, challenging the notion of distinct pathways and movement processing'. However, it is not clear whether the data presented in this work supports this statement. First, the authors have not attempted to record from the entire EPN. Thus it is possible that the coding might be more segregated in other parts of EPN. Second, EPNs have previously been shown to display positive firing for negative outcomes and vice versa, something which the authors do not find here. It is possible that those neurons might not encode kinematic and movement variables. Thus, the authors should point out in the main text the possibility that the EPN activity recorded might be missing some parts of the whole EPN.
4). The authors use an IR beam system to record licks and make a strong claim about the nature of lick encoding in the EPN. However, the authors should note that IR beam system is not the most accurate way of detecting licks given that any object blocking the path (paw or jaw-dropping) will be detected as lick events. Capacitance based, closed-loop detection, or video capturing is better suited to detect individual licks. Given that the authors are interested in kinematics of licking, this is important. The authors should either point this out in the main text or verify in the system if the IR beam is correctly detecting licks using a combination of those methods.
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Reviewer #1 (Public Review):
Summary:
The authors state the study's goal clearly: "The goal of our study was to understand to what extent animal individuality is influenced by situational changes in the environment, i.e., how much of an animal's individuality remains after one or more environmental features change." They use visually guided behavioral features to examine the extent of correlation over time and in a variety of contexts. They develop new behavioral instrumentation and software to measure behavior in Buridan's paradigm (and variations thereof), the Y-maze, and a flight simulator. Using these assays, they examine the correlations between conditions for a panel of locomotion parameters. They propose that inter-assay correlations will determine the persistence of locomotion individuality.
Strengths:
The OED defines individuality as "the sum of the attributes which distinguish a person or thing from others of the same kind," a definition mirrored by other dictionaries and the scientific literature on the topic. The concept of behavioral individuality can be characterized as:<br /> (1) a large set of behavioral attributes,<br /> (2) with inter-individual variability, that are<br /> (3) stable over time.
A previous study examined walking parameters in Buridan's paradigm, finding that several parameters were variable between individuals, and that these showed stability over separate days and up to 4 weeks (DOI: 10.1126/science.aaw718). The present study replicates some of those findings and extends the experiments from temporal stability to examining the correlation of locomotion features between different contexts.
The major strength of the study is using a range of different behavioral assays to examine the correlations of several different behavior parameters. It shows clearly that the inter-individual variability of some parameters is at least partially preserved between some contexts, and not preserved between others. The development of high-throughput behavior assays and sharing the information on how to make the assays is a commendable contribution.
Weaknesses:
The definition of individuality considers a comprehensive or large set of attributes, but the authors consider only a handful. In Supplemental Fig. S8, the authors show a large correlation matrix of many behavioral parameters, but these are illegible and are only mentioned briefly in Results. Why were five or so parameters selected from the full set? How were these selected? Do the correlation trends hold true across all parameters? For assays in which only a subset of parameters can be directly compared, were all of these included in the analysis, or only a subset?
The correlation analysis is used to establish stability between assays. For temporal re-testing, "stability" is certainly the appropriate word, but between contexts, it implies that there could be 'instability'. Rather, instead of the 'instability' of a single brain process, a different behavior in a different context could arise from engaging largely (or entirely?) distinct context-dependent internal processes, and have nothing to do with process stability per se. For inter-context similarities, perhaps a better word would be "consistency".
The parameters are considered one by one, not in aggregate. This focuses on the stability/consistency of the variability of a single parameter at a time, rather than holistic individuality. It would appear that an appropriate measure of individuality stability (or individuality consistency) that accounts for the high-dimensional nature of individuality would somehow summarize correlations across all parameters. Why was a multivariate approach (e.g. multiple regression/correlation) not used? Treating the data with a multivariate or averaged approach would allow the authors to directly address 'individuality stability', along with the analyses of single-parameter variability stability.
The correlation coefficients are sometimes quite low, though highly significant, and are deemed to indicate stability. For example, in Figure 4C top left, the % of time walked at 23{degree sign}C and 32{degree sign}C are correlated by 0.263, which corresponds to an R2 of 0.069 i.e. just 7% of the 32{degree sign}C variance is predictable by the 23{degree sign}C variance. Is it fair to say that a 7% determination indicates parameter stability? Another example: "Vector strength was the most correlated attention parameter... correlations ranged... to -0.197," which implies that 96% (1 - R2) of Y-maze variance is not predicted by Buridan variance. At what level does an r value not represent stability?
The authors describe a dissociation between inter-group differences and inter-individual variation stability, i.e. sometimes large mean differences between contexts, but significant correlation between individual test and retest data. Given that correlation is sensitive to slope, this might be expected to underestimate the variability stability (or consistency). Is there a way to adjust for the group differences before examining the correlation? For example, would it be possible to transform the values to in-group ranks prior to correlation analysis?
What is gained by classifying the five parameters into exploration, attention, and anxiety? To what extent have these classifications been validated, both in general and with regard to these specific parameters? Is the increased walking speed at higher temperatures necessarily due to an increased 'explorative' nature, or could it be attributed to increased metabolism, dehydration stress, or a heat-pain response? To what extent are these categories subjective?
The legends are quite brief and do not link to descriptions of specific experiments. For example, Figure 4a depicts a graphical overview of the procedure, but I could not find a detailed description of this experiment's protocol.
Using the current single-correlation analysis approach, the aims would benefit from re-wording to appropriately address single-parameter variability stability/consistency (as distinct from holistic individuality). Alternatively, the analysis could be adjusted to address the multivariate nature of individuality, so that the claims and the analysis are in concordance with each other.
The study presents a bounty of new technology to study visually guided behaviors. The GitHub link to the software was not available. To verify the successful transfer of open hardware and open-software, a report would demonstrate transfer by collaboration with one or more other laboratories, which the present manuscript does not appear to do. Nevertheless, making the technology available to readers is commendable.
The study discusses a number of interesting, stimulating ideas about inter-individual variability, and presents intriguing data that speaks to those ideas, albeit with the issues outlined above.
While the current work does not present any mechanistic analysis of inter-individual variability, the implementation of high-throughput assays sets up the field to more systematically investigate fly visual behaviors, their variability, and their underlying mechanisms.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This work aims to understand the role of thalamus POm in dorsal lateral striatum (DLS) projection in learning a sensorimotor associative task. The authors first confirm that POm forms "en passant" synapses with some of the DLS neuronal subtypes. They then perform a go/no-go associative task that consists of the mouse learning to discriminate between two different textures and to associate one of them with an action. During this task, they either record the activity of the POm to DLS axons using endoscopy or silence their activity. They report that POm axons in the DLS are activated around the sensory stimulus but that the activity is not modulated by the reward. Last, they showed that silencing the POm axons at the level of DLS slows down learning the task.
The authors show convincing evidence of projections from POm to DLS and that POm inputs to DLS code for whisking whatever the outcome of the task is. However, their results do not allow us to conclude if more neurons are recruited during the learning process or if the already activated fibres get activated more strongly. Last, because POm fibres in the DLS are also projecting to S1, silencing the POm fibres in the DLS could have affected inputs in S1 as well and therefore, the slowdown in acquiring the task is not necessarily specific to the POm to DLS pathway.
Strengths:
One of the main strengths of the paper is to go from slice electrophysiology to behaviour to get an in-depth characterization of one pathway. The authors did a comprehensive description of the POm projections to the DLS using transgenic mice to unambiguously identify the DLS neuronal population. They also used a carefully designed sensorimotor association task, and they exploited the results in depth.
It is a very nice effort to have measured the activity of the axons in the DLS not only after the mice have learned the task but throughout the learning process. It shows the progressive increase of activity of POm axons in the DLS, which could imply that there is a progressive strengthening of the pathway. The results show convincingly that POm axons in the DLS are not activated by the outcome of the task but by the whisker activity, and that this activity on average increases with learning.
Weaknesses:
One of the main targets of the striatum from thalamic input are the cholinergic neurons that weren't investigated here, is there information that could be provided?
It is interesting to know that the POm projects to all neuronal types in the DLS, but this information is not used further down the manuscript so the only take-home message of Figure 1 is that the axons that they image or silence in the DLS are indeed connected to DLS neurons and not just passing fibres. In this line, are these axons the same as the ones projecting to S1? If this is the case, why would we expect a different behaviour of the axon activity at the DLS level compared to S1?
The authors used endoscopy to measure the POm axons in the DLS activity, which makes it impossible to know if the progressive increase of POm response is due to an increase of activity from each individual neuron or if new neurons are progressively recruited in the process.
The picture presented in Figure 4 of the stimulation site is slightly concerning as there are hardly any fibres in neocortical layer 1 while there seems to be quite a lot of them in layer 4, suggesting that the animal here was injected in the VB. This is especially striking as the implantation and projection sites presented in Figures 1 and 2 are very clean and consistent with POm injection.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The novel advance by Wang et al is in the demonstration that, relative to a standard extinction procedure, the retrieval-extinction procedure more effectively suppresses responses to a conditioned threat stimulus when testing occurs just minutes after extinction. The authors provide some solid evidence to show that this "short-term" suppression of responding involves engagement of the dorsolateral prefrontal cortex.
Strengths:
Overall, the study is well-designed and the results are potentially interesting. There are, however, a few issues in the way that it is introduced and discussed. Some of the issues concern clarity of expression/communication. However, others relate to a theory that could be used to help the reader understand why the results should have come out the way that they did. More specific comments and questions are presented below.
Weaknesses:
INTRODUCTION & THEORY
(1) Can the authors please clarify why the first trial of extinction in a standard protocol does NOT produce the retrieval-extinction effect? Particularly as the results section states: "Importantly, such a short-term effect is also retrieval dependent, suggesting the labile state of memory is necessary for the short-term memory update to take effect (Fig. 1e)." The importance of this point comes through at several places in the paper:
1A. "In the current study, fear recovery was tested 30 minutes after extinction training, whereas the effect of memory reconsolidation was generally evident only several hours later and possibly with the help of sleep, leaving open the possibility of a different cognitive mechanism for the short-term fear dementia related to the retrieval-extinction procedure." ***What does this mean? The two groups in study 1 experienced a different interval between the first and second CS extinction trials; and the results varied with this interval: a longer interval (10 min) ultimately resulted in less reinstatement of fear than a shorter interval. Even if the different pattern of results in these two groups was shown/known to imply two different processes, there is absolutely no reason to reference any sort of cognitive mechanism or dementia - that is quite far removed from the details of the present study.
1B. "Importantly, such a short-term effect is also retrieval dependent, suggesting the labile state of memory is necessary for the short-term memory update to take effect (Fig. 1e)." ***As above, what is "the short-term memory update"? At this point in the text, it would be appropriate for the authors to discuss why the retrieval-extinction procedure produces less recovery than a standard extinction procedure as the two protocols only differ in the interval between the first and second extinction trials. References to a "short-term memory update" process do not help the reader to understand what is happening in the protocol.
(2) "Indeed, through a series of experiments, we identified a short-term fear amnesia effect following memory retrieval, in addition to the fear reconsolidation effect that appeared much later."<br /> ***The only reason for supposing two effects is because of the differences in responding to the CS2, which was subjected to STANDARD extinction, in the short- and long-term tests. More needs to be said about how and why the performance of CS2 is affected in the short-term test and recovers in the long-term test. That is, if the loss of performance to CS1 and CS2 is going to be attributed to some type of memory updating process across the retrieval-extinction procedure, one needs to explain the selective recovery of performance to CS2 when the extinction-to-testing interval extends to 24 hours. Instead of explaining this recovery, the authors note that performance to CS1 remains low when the extinction-to-testing interval is 24 hours and invoke something to do with memory reconsolidation as an explanation for their results: that is, they imply (I think) that reconsolidation of the CS1-US memory is disrupted across the 24-hour interval between extinction and testing even though CS1 evokes negligible responding just minutes after extinction.
(3) The discussion of memory suppression is potentially interesting but, in its present form, raises more questions than it answers. That is, memory suppression is invoked to explain a particular pattern of results but I, as the reader, have no sense of why a fear memory would be better suppressed shortly after the retrieval-extinction protocol compared to the standard extinction protocol; and why this suppression is NOT specific to the cue that had been subjected to the retrieval-extinction protocol.
3A. Relatedly, how does the retrieval-induced forgetting (which is referred to at various points throughout the paper) relate to the retrieval-extinction effect? The appeal to retrieval-induced forgetting as an apparent justification for aspects of the present study reinforces points 2 and 3 above. It is not uninteresting but needs some clarification/elaboration.
(4) Given the reports by Chalkia, van Oudenhove & Beckers (2020) and Chalkia et al (2020), some qualification needs to be inserted in relation to reference 6. That is, reference 6 is used to support the statement that "during the reconsolidation window, old fear memory can be updated via extinction training following fear memory retrieval". This needs a qualifying statement like "[but see Chalkia et al (2020a and 2020b) for failures to reproduce the results of 6]."
https://pubmed.ncbi.nlm.nih.gov/32580869/<br /> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115860/
CLARIFICATIONS, ELABORATIONS, EDITS
(5) The Abstract was not easy to follow:
5A. What does it mean to ask: "whether memory retrieval facilitates update mechanisms other than memory reconsolidation"? That is, in what sense could or would memory retrieval be thought to facilitate a memory update mechanism?
5B. "First, we demonstrate that memory reactivation prevents the return of fear shortly after extinction training in contrast to the memory reconsolidation effect which takes several hours to emerge and such a short-term amnesia effect is cue independent (Study 1, N = 57 adults)."<br /> ***The phrasing here could be improved for clarity: "First, we demonstrate that the retrieval-extinction protocol prevents the return of fear shortly after extinction training (i.e., when testing occurs just min after the end of extinction)." Also, cue-dependence of the retrieval-extinction effect was assessed in study 2.
5C. "Furthermore, memory reactivation also triggers fear memory reconsolidation and produces cue-specific amnesia at a longer and separable timescale (Study 2, N = 79 adults)." ***In study 2, the retrieval-extinction protocol produced a cue-specific disruption in responding when testing occurred 24 hours after the end of extinction. This result is interesting but cannot be easily inferred from the statement that begins "Furthermore..." That is, the results should be described in terms of the combined effects of retrieval and extinction, not in terms of memory reactivation alone; and the statement about memory reconsolidation is unnecessary. One can simply state that the retrieval-extinction protocol produced a cue-specific disruption in responding when testing occurred 24 hours after the end of extinction.
5D. "...we directly manipulated brain activities in the dorsolateral prefrontal cortex and found that both memory retrieval and intact prefrontal cortex functions were necessary for the short-term fear amnesia."<br /> ***This could be edited to better describe what was shown: E.g., "...we directly manipulated brain activities in the dorsolateral prefrontal cortex and found that intact prefrontal cortex functions were necessary for the short-term fear amnesia after the retrieval-extinction protocol."
5E. "The temporal scale and cue-specificity results of the short-term fear amnesia are clearly dissociable from the amnesia related to memory reconsolidation, and suggest that memory retrieval and extinction training trigger distinct underlying memory update mechanisms."<br /> ***The pattern of results when testing occurred just minutes after the retrieval-extinction protocol was different from that obtained when testing occurred 24 hours after the protocol. Describing this in terms of temporal scale is unnecessary, and suggesting that memory retrieval and extinction trigger different memory update mechanisms is not obviously warranted. The results of interest are due to the combined effects of retrieval+extinction and there is no sense in which different memory update mechanisms should be identified with retrieval (mechanism 1) and extinction (mechanism 2).
5F. "These findings raise the possibility of concerted memory modulation processes related to memory retrieval..."<br /> ***What does this mean?
(6) "...suggesting that the fear memory might be amenable to a more immediate effect, in addition to what the memory reconsolidation theory prescribes..."<br /> ***What does it mean to say that the fear memory might be amenable to a more immediate effect?
(7) "Parallel to the behavioral manifestation of long- and short-term memory deficits, concurrent neural evidence supporting memory reconsolidation theory emphasizes the long-term effect of memory retrieval by hypothesizing that synapse degradation and de novo protein synthesis are required for reconsolidation."<br /> ***This sentence needs to be edited for clarity.
(8) "previous behavioral manipulations engendering the short-term declarative memory effect..."<br /> ***What is the declarative memory effect? It should be defined.
(9) "The declarative amnesia effect emerges much earlier due to the online functional activity modulation..."<br /> ***Even if the declarative memory amnesia effect had been defined, the reference to online functional activity modulation is not clear.
(10) "However, it remains unclear whether memory retrieval might also precipitate a short-term amnesia effect for the fear memory, in addition to the long-term prevention orchestrated by memory consolidation."<br /> ***I found this sentence difficult to understand on my first pass through the paper. I think it is because of the phrasing of memory retrieval. That is, memory retrieval does NOT precipitate any type of short-term amnesia for the fear memory: it is the retrieval-extinction protocol that produces something like short-term amnesia. Perhaps this sentence should also be edited for clarity.
I will also note that the usage of "short-term" at this point in the paper is quite confusing: Does the retrieval-extinction protocol produce a short-term amnesia effect, which would be evidenced by some recovery of responding to the CS when tested after a sufficiently long delay? I don't believe that this is the intended meaning of "short-term" as used throughout the majority of the paper, right?
(11) "To fully comprehend the temporal dynamics of the memory retrieval effect..."<br /> ***What memory retrieval effect? This needs some elaboration.
(12) "We hypothesize that the labile state triggered by the memory retrieval may facilitate different memory update mechanisms following extinction training, and these mechanisms can be further disentangled through the lens of temporal dynamics and cue-specificities."<br /> ***What does this mean? The first part of the sentence is confusing around the usage of the term "facilitate"; and the second part of the sentence that references a "lens of temporal dynamics and cue-specificities" is mysterious. Indeed, as all rats received the same retrieval-extinction exposures in Study 2, it is not clear how or why any differences between the groups are attributed to "different memory update mechanisms following extinction".
(13) "In the first study, we aimed to test whether there is a short-term amnesia effect of fear memory retrieval following the fear retrieval-extinction paradigm."<br /> ***Again, the language is confusing. The phrase, "a short-term amnesia effect" implies that the amnesia itself is temporary; but I don't think that this implication is intended. The problem is specifically in the use of the phrase "a short-term amnesia effect of fear memory retrieval." To the extent that short-term amnesia is evident in the data, it is not due to retrieval per se but, rather, the retrieval-extinction protocol.
(14) The authors repeatedly describe the case where there was a 24-hour interval between extinction and testing as consistent with previous research on fear memory reconsolidation. Which research exactly? That is, in studies where a CS re-exposure was combined with a drug injection, responding to the CS was disrupted in a final test of retrieval from long-term memory which typically occurred 24 hours after the treatment. Is that what the authors are referring to as consistent? If so, which aspect of the results are consistent with those previous findings? Perhaps the authors mean to say that, in the case where there was a 24-hour interval between extinction and testing, the results obtained here are consistent with previous research that has used the retrieval-extinction protocol. This would clarify the intended meaning greatly.
DATA
(15) Points about data:
15A. The eight participants who were discontinued after Day 1 in study 1 were all from the no-reminder group. Can the authors please comment on how participants were allocated to the two groups in this experiment so that the reader can better understand why the distribution of non-responders was non-random (as it appears to be)?
15B. Similarly, in study 2, of the 37 participants that were discontinued after Day 2, 19 were from Group 30 min, and 5 were from Group 6 hours. Can the authors comment on how likely these numbers are to have been by chance alone? I presume that they reflect something about the way that participants were allocated to groups, but I could be wrong.
15C. "Post hoc t-tests showed that fear memories were resilient after regular extinction training, as demonstrated by the significant difference between fear recovery indexes of the CS+ and CS- for the no-reminder group (t26 = 7.441, P < 0.001; Fig. 1e), while subjects in the reminder group showed no difference of fear recovery between CS+ and CS- (t29 = 0.797, P = 0.432, Fig. 1e)."<br /> ***Is the fear recovery index shown in Figure 1E based on the results of the 1st test trial only? How can there have been a "significant difference between fear recovery indexes of the CS+ and CS- for the no-reminder group" when the difference in responding to the CS+ and CS- is used to calculate the fear recovery index shown in 1E? What are the t-tests comparing exactly, and what correction is used to account for the fact that they are applied post-hoc?
15D. "Finally, there is no statistical difference between the differential fear recovery indexes between CS+ in the reminder and no reminder groups (t55 = -2.022, P = 0.048; Fig. 1c, also see Supplemental Material for direct test for the test phase)."<br /> ***Is this statement correct - i.e., that there is no statistically significant difference in fear recovery to the CS+ in the reminder and no reminder groups? I'm sure that the authors would like to claim that there IS such a difference; but if such a difference is claimed, one would be concerned by the fact that it is coming through in an uncorrected t-test, which is the third one of its kind in this paragraph. What correction (for the Type 1 error rate) is used to account for the fact that the t-tests are applied post-hoc? And if no correction, why not?
15E. In study 2, why is responding to the CS- so high on the first test trial in Group 30 min? Is the change in responding to the CS- from the last extinction trial to the first test trial different across the three groups in this study? Inspection of the figure suggests that it is higher in Group 30 min relative to Groups 6 hours and 24 hours. If this is confirmed by the analysis, it has implications for the fear recovery index which is partly based on responses to the CS-. If not for differences in the CS- responses, Groups 30 minutes and 6 hours are otherwise identical.
15F. Was the 6-hour group tested at a different time of day compared to the 30-minute and 24-hour groups; and could this have influenced the SCRs in this group?
15G. Why is the range of scores in "thought control ability" different in the 30-minute group compared to the 6-hour and 24-hour groups? I am not just asking about the scale on the x-axis: I am asking why the actual distribution of the scores in thought control ability is wider for the 30-minute group?
(16) During testing in each experiment, how were the various stimuli presented? That is, was the presentation order for the CS+ and CS- pseudorandom according to some constraint, as it had been in extinction? This information should be added to the method section.
(17) "These results are consistent with previous research which suggested that people with better capability to resist intrusive thoughts also performed better in motivated dementia in both declarative and associative memories."<br /> ***Which parts of the present results are consistent with such prior results? It is not clear from the descriptions provided here why thought control ability should be related to the present findings or, indeed, past ones in other domains. This should be elaborated to make the connections clear.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
This is a large cohort of ischemic stroke patients from a single centre. The author successfully set up predictive models for PTS.
Strengths:
The design and implementation of the trial are acceptable, and the results are credible. It may provide evidence of seizure prevention in the field of stroke treatment.
Weaknesses:
The methodology needs further consideration. The Discussion needs extensive rewriting.
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Reviewer #1 (Public Review):
This study uses MEG to test for a neural signature of the trial history effect known as 'serial dependence.' This is a behavioral phenomenon whereby stimuli are judged to be more similar than they really are, in feature space, to stimuli that were relevant in the recent past (i.e., the preceding trials). This attractive bias is prevalent across stimulus classes and modalities, but a neural source has been elusive. This topic has generated great interest in recent years, and I believe this study makes a unique contribution to the field. The paper is overall clear and compelling, and makes effective use of data visualizations to illustrate the findings. Below, I list several points where I believe further detail would be important to interpreting the results. I also make suggestions for additional analyses that I believe would enrich understanding but are inessential to the main conclusions.
(1) In the introduction, I think the study motivation could be strengthened, to clarify the importance of identifying a neural signature here. It is clear that previous studies have focused mainly on behavior, and that the handful of neuroscience investigations have found only indirect signatures. But what would the type of signature being sought here tell us? How would it advance understanding of the underlying processes, the function of serial dependence, or the theoretical debates around the phenomenon?
(1a) As one specific point of clarification, on p. 5, lines 91-92, a previous study (St. John-Saaltink et al.) is described as part of the current study motivation, stating that "as the current and previous orientations were either identical or orthogonal to each other, it remained unclear whether this neural bias reflected an attraction or repulsion in relation to the past." I think this statement could be more explicit as to why/how these previous findings are ambiguous. The St. John-Saaltink study stands as one of very few that may be considered to show evidence of an early attractive effect in neural activity, so it would help to clarify what sort of advance the current study represents beyond that.
(1b) The study motivation might also consider the findings of Ranieri et al (2022, J. Neurosci) Fornaciai, Togoli, & Bueti (2023, J. Neurosci), and Luo & Collins (2023, J. Neurosci) who all test various neural signatures of serial dependence.
(2) Regarding the methods and results, it would help if the initial description of the reconstruction approach, in the main text, gave more context about what data is going into reconstruction (e.g., which sensors), a more conceptual overview of what the 'reconstruction' entails, and what the fidelity metric indexes. To me, all of that is important to interpreting the figures and results. For instance, when I first read, it was unclear to me what it meant to "reconstruct the direction of S1 during the S2 epoch" (p. 10, line 199)? As in, I couldn't tell how the data/model knows which item it is reconstructing, as opposed to just reporting whatever directional information is present in the signal.
(2a) Relatedly, what does "reconstruction strength" reflect in Figure 2a? Is this different than the fidelity metric? Does fidelity reflect the strength of the particular relevant direction, or does it just mean that there is a high level of any direction information in the signal?
(3) Then in the Methods, it would help to provide further detail still about the IEM training/testing procedure. For instance, it's not entirely clear to me whether all the analyses use the same model (i.e., all trained on stimulus encoding) or whether each epoch and timepoint is trained on the corresponding epoch and timepoint from the other session. This speaks to whether the reconstructions reflect a shared stimulus code across different conditions vs. that stimulus information about various previous and current trial items can be extracted if the model is tailored accordingly. Specifically, when you say "aim of the reconstruction" (p. 31, line 699), does that simply mean the reconstruction was centered in that direction (that the same data would go into reconstructing S1 or S2 in a given epoch, and what would differentiate between them is whether the reconstruction was centered to the S1 or S2 direction value)? Or were S1 and S2 trained and tested separately for the same epoch? And was training and testing all within the same time point (i.e., train on delay, test on delay), or train on the encoding of a given item, then test the fidelity of that stimulus code under various conditions?
(3a) I think training and testing were done separately for each epoch and timepoint, but this could have important implications for interpreting the results. Namely if the models are trained and tested on different time points, and reference directions, then some will be inherently noisier than others (e.g., delay period more so than encoding), and potentially more (or differently) susceptible to bias. For instance, the S1 and S2 epochs show no attractive bias, but they may also be based on more high-fidelity training sets (i.e., encoding), and therefore less susceptible to the bias that is evident in the retrocue epoch.
(4) I believe the work would benefit from a further effort to reconcile these results with previous findings (i.e., those that showed repulsion, like Sheehan & Serences), potentially through additional analyses. The discussion attributes the difference in findings to the "combination of a retro-cue paradigm with the high temporal resolution of MEG," but it's unclear how that explains why various others observed repulsion (thought to happen quite early) that is not seen at any stage here. In my view, the temporal (as well as spatial) resolution of MEG could be further exploited here to better capture the early vs. late stages of processing. For instance, by separately examining earlier vs. later time points (instead of averaging across all of them), or by identifying and analyzing data in the sensors that might capture early vs. late stages of processing. Indeed, the S1 and S2 reconstructions show subtle repulsion, which might be magnified at earlier time points but then shift (toward attraction) at later time points, thereby counteracting any effect. Likewise, the S1 reconstruction becomes biased during the S2 epoch, consistent with previous observations that the SD effects grow across a WM delay. Maybe both S1 and S2 would show an attractive bias emerging during the later (delay) portion of their corresponding epoch? As is, the data nicely show that an attractive bias can be detected in the retrocue period activity, but they could still yield further specificity about when and where that bias emerges.
(5) A few other potentially interesting (but inessential considerations): A benchmark property of serial dependence is its feature-specificity, in that the attractive bias occurs only between current and previous stimuli that are within a certain range of similarity to each other in feature space. I would be very curious to see if the neural reconstructions manifest this principle - for instance, if one were to plot the trialwise reconstruction deviation from 0, across the full space of current-previous trial distances, as in the behavioral data. Likewise, something that is not captured by the DoG fitting approach, but which this dataset may be in a position to inform, is the commonly observed (but little understood) repulsive effect that appears when current and previous stimuli are quite distinct from each other. As in, Figure 1b shows an attractive bias for direction differences around 30 degrees, but a repulsive one for differences around 170 degrees - is there a corresponding neural signature for this component of the behavior?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, the authors developed an organoid system that contains smooth muscle cells (SMCs) and interstitial cells of Cajal (ICCs; pacemaker) but few enteric neurons, and generates rhythmic contractions as seen in the developing gut. The stereotypical arrangements of SMCs and ICCs in the organoid allowed the authors to identify these cell types in the organoid without antibody staining. The authors took advantage of this and used calcium imaging and pharmacology to study how calcium transients develop in this system through the interaction between the two types of cells. The authors first show that calcium transients are synchronized between ICC-ICC, SMC-SMC, and SMC-ICC. They then used gap junction inhibitors to suggest that gap junctions are specifically involved in ICC-to-SMC signaling. Finally, the authors used an inhibitor of myosin II to suggest that feedback from SMC contraction is crucial for the generation of rhythmic activities in ICCs. The authors also show that two organoids become synchronized as they fuse and SMCs mediate this synchronization.
Strengths:
The organoid system offers a useful model in which one can study the specific roles of SMCs and ICCs in live samples.
Weaknesses:
Since only one blocker each for gap junction and myosin II was used, the specificities of the effects were unclear.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In the article by Dearlove et al., the authors present evidence in strong support of nucleotide ubiquitylation by DTX3L, suggesting it is a promiscuous E3 ligase with capacity to ubiquitylate ADP ribose and nucleotides. The authors include data to identify the likely site of attachment and the requirements for nucleotide modification.
While this discovery potentially reveals a whole new mechanism by which nucleotide function can be regulated in cells, there are some weaknesses that should be considered. Is there any evidence of nucleotide ubiquitylation occurring cells? It seems possible, but evidence in support of this would strengthen the manuscript. The NMR data could also be strengthened as the binding interface is not reported or mapped onto the structure/model, this seems of considerable interest given that highly related proteins do have the same activity.
The paper is for the most part well well-written and is potentially highly significant, but it could be strengthened as follows:
(1) The authors start out by showing DTX3L binding to nucleotides and ubiquitylation of ssRNA/DNA. While ubiquitylation is subsequently dissected and ascribed to the RD domains, the binding data is not followed up. Does the RD protein alone bind to the nucleotides? Further analysis of nucleotide binding is also relevant to the Discussion where the role of the KH domains is considered, but the binding properties of these alone have not been analysed.<br /> (2) With regard to the E3 ligase activity, can the authors account for the apparent decreased ubiquitylation activity of the 232-C protein in Figure 1/S1 compared to FL and RD?<br /> (3) Was it possible to positively identify the link between Ub and ssDNA/RNA using mass spectrometry? This would overcome issues associated with labels blocking binding rather than modification.<br /> (4) Furthermore, can a targeted MS approach be used to show that nucleotides are ubiquitylated in cells?<br /> (5) Do the authors have the assignments (even partial?) for DTX3L RD? In Figure 4 it would be helpful to identify the peaks that correspond to the residues at the proposed binding site. Also do the shifts map to a defined surface or do they suggest an extended site, particularly for the ssDNA.<br /> (6) Does sequence analysis help explain the specificity of activity for the family of proteins?<br /> (7) While including a summary mechanism (Figure 5I) is helpful, the schematic included does not necessarily make it easier for the reader to appreciate the key findings of the manuscript or to account for the specificity of activity observed. While this figure could be modified, it might also be helpful to highlight the range of substrates that DTX3L can modify - nucleotide, ADPr, ADPr on nucleotides etc.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors characterized a new non-coding RNA, which they named as PITAR. They first showed that the PITAR expression levels are higher in glioblastoma, and then demonstrated that knockdown of PITAR in glioblastoma cells decreased cell growth, induced G0/G1 arrest and apoptosis. They further identified the E3 ubiquitin ligase TRIM28 is the target of PITAR, and showed that PITAR bound to the TRIM28 mRNA and regulated the stability and expression of the latter. Since TRIM28 has been reported to be an E3 ubiquitin ligase for the tumor suppressor p53, the authors tried to link the PITAR function to p53 regulation. They showed that one PITAR siRNA increased the levels of p53 and p21, and the stability of p53, and these effects could be diminished by overexpression of TRIM28. They also showed that PITAR overexpression decreased the levels of adriamycin-induced p53/p21 expression and reversed DNA damage-induced G2/M arrest. Lastly, the authors showed that PITAR siRNA decreased the growth of glioblastoma, while PITAR overexpression increased glioblastoma growth and counteracted temozolomide for its anti-glioblastoma activity.
Overall, the manuscript has provided evidence supporting the important role of PITAR in the regulation of the growth of glioblastoma. The results supporting the regulation of PITAR on TRIM28 appear to be convincing. However, some weaknesses are also noted.
(1) More than one siRNA/shRNA should be used in critical experiments. For example, Fig 7A-E are important experiments demonstrating PITAR suppresses tumor growth. It is compelling that the siPITAR tumors disappeared at the end of the experiment. While this might be due to apoptosis, using another siRNA to confirm the results would be necessary. The authors may also need to use this model to test their hypothesis that PITAR regulates tumor growth through p53. They can check p53, p21, apoptosis levels in tumor sections.
(2) The data supporting that PITAR downregulates p53 stability and activity can be strengthened. The half-life of endogenous p53 protein is generally 20-30 min, and thus the cycloheximide chase experiments (Fig 5E) need to use shorter treatment time. The ubiquitinated p53 bands are not clear (Fig 5F), and the data suggesting that PITAR regulates p53 ubiquitination are not convincing. While the p53 protein level was largely altered by PITAR/TRIM28, the mRNA levels of its target genes, including p21 and MDM2 only marginally changed (Fig S6D). Other p53 targets, particularly proapoptotic genes, may need to be examined.
(3) The model depicting the role of PITAR in the cellular response to DNA-damaging agents is confusing. If DNA damaging agents like TMZ induce PITAR to inactivate p53, PITAR overexpression would confer TMZ resistance. However, Fig 7G did not support this. While the experimental design is quite problematic given that U87 cells already express a high level of PITAR, PITAR-overexpressing cells were still sensitive to TMZ treatment (this is apparent when checking the images in Fig 7F, although the large error bars shown in Fig 7G may lead to a "not significant" conclusion). The authors may need to test whether PITAR downregulation, which would increase p53 activity, has any effects on TMZ-insensitive tumors. Such results are more therapeutically relevant. It would also be helpful if the authors test whether PITAR is overexpressed in TMZ-resistant clinical samples.
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Reviewer #1 (Public Review):
The authors characterized a new non-coding RNA, which they named as PITAR. They first showed that the PITAR expression levels are higher in glioblastoma, and then demonstrated that knockdown of PITAR in glioblastoma cells decreased cell growth, induced G0/G1 arrest and apoptosis. They further identified the E3 ubiquitin ligase TRIM28 is the target of PITAR, and showed that PITAR bound to the TRIM28 mRNA and regulated the stability and expression of the latter. Since TRIM28 has been reported to be an E3 ubiquitin ligase for the tumor suppressor p53, the authors tried to link the PITAR function to p53 regulation. They showed that one PITAR siRNA increased the levels of p53 and p21, and the stability of p53, and these effects could be diminished by overexpression of TRIM28. They also showed that PITAR overexpression decreased the levels of adriamycin-induced p53/p21 expression and reversed DNA damage-induced G2/M arrest. Lastly, the authors showed that PITAR siRNA decreased the growth of glioblastoma, while PITAR overexpression increased glioblastoma growth and counteracted temozolomide for its anti-glioblastoma activity.
Overall, the manuscript has provided preliminary evidence supporting the important role of PITAR in the regulation of the growth and drug resistance of glioblastoma. The results supporting the regulation of PITAR on TRIM28 appear to be convincing. However, the study suffers significant weaknesses summarized as below.
(1) Only one PITAR siRNA was tested in majority of the experiments, which compromises the validity of the results. Some results are inconsistent. For example, Fig 2G indicates that PITAR siRNA caused G1 arrest. However, PITAR overexpression in the same cell line did not show any effect on cell cycle progression in Fig 5I.
(2) The conclusion that PITAR inactivates p53 through regulating TRIM28, which is highlighted in the title of the manuscript, is not supported by convincing results. Although the authors showed that a PITAR siRNA increased while PITAR overexpression decreased p53 level, the siRNA only marginally increased the stability of p53 (Fig 5E). The p53 ubiquitination level was barely affected by PITAR overexpression in Fig 5F. To convincingly demonstrate that PITAR regulates p53 through TRIM28, the authors need to show that this regulation is impaired/compromised in TRIM28-knockout conditions. The authors only showed that TRIM28 overexpression suppressed PITAR siRNA-induced increase of p53, which is not sufficient. Note that only one cell line was investigated in Fig 5.
(3) Another major weakness of this manuscript is that the authors did not provide any evidence indicating that the glioblastoma-promoting activities of PITAR were mediated by its regulation of p53 or TRIM28 (Fig 6 and Fig 7). Thus, the regulation of glioblastoma growth and the regulation of TRIM28/p53 appear to be disconnected.
(4) It is not clear what kind of message the authors tried to deliver in Fig 7F/G. Based on the authors' hypothesis, DNA damaging agents like TMZ would induce PITAR to inactivate p53, which would compromise TMZ's anti-cancer activity. However, the data show that TMZ was very effective in the inhibition of U87 growth. The authors may need to test whether PITAR downregulation, which would increase p53 activity, have any effects on TMZ-insensitive tumors. Such results are more therapeutically relevant.
(5) Lastly, the model presented in Fig 7H is confusing. It is not clear what the exact role of PITAR in the DNA damage response based on this model. If DNA damage would induce PITAR expression, this would lead to inactivation of p53 as revealed by this manuscript. However, DNA damage is known to activate p53. Do the authors want to imply that PITAR induction by DNA damage would help to bring down the p53 level at the end of DNA damage response? The presented data do not support this role unfortunately.
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Reviewer #1 (Public Review):
SUMMARY:
The goal of Knudsen-Palmer et al. was to define a biological set of rules that dictate the differential RNAi-mediated silencing of distinct target genes, motivated by facilitating the long-term development of effective RNAi-based drugs/therapeutics. This work provides insights into how 1) cis-regulatory elements influence the RNAi-mediated regulation of genes; 2) determines that genes can "recover" from RNAi-silencing signals in an animal; and 3) pUGylation occurs exclusively downstream of the dsRNA trigger sequence, suggesting 3º siRNAs are not produced. In addition, the authors show that the speed at which RNAi-silencing is triggered does not correlate with the longevity of the silencing. Overall, the work presented supports the conclusions of the authors. The insights are significant because they suggest that if we understand the rules by which RNAi pathways effectively silence genes with different transcription/processing levels then we can design more effective synthetic RNAi-based therapeutics targeting endogenous genes.
MAJOR STRENGTH:
The authors use a combination of computational modeling, genetics, and RNAi function assays to reveal several criteria for effective RNAi-mediated silencing of two distinct targets.
WEAKNESS:
It may be beyond the scope of this study, but it would be interesting to know the typical expression levels and turnover rates of unc-22 and bli-1. Based on the results from the altered cis-regulatory regions of bli-1 and unc-22 in Fig 5, it seems like the transcription/turnover rates of each of these genes could also be used as a proof of principle for testing the model proposed in Figure 4. The strength of the model would be further increased if the RNAi sensitivity of unc-22 reflects differences in its transcription/turnover rates compared to bli-1.
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Reviewer #1 (Public Review):
Summary:
TMC7 knockout mice were generated by the authors and the phenotype was analyzed. They found that Tmc7 is localized to Golgi and is needed for acrosome biogenesis.
Strengths:
The phenotype of infertility is clear, and the results of TMC7 localization and the failed acrosome formation are highly reliable. In this respect, they made a significant discovery regarding spermatogenesis.
In the original version, I pointed out the gap between their pH/calcium imaging data and the hypothesis of ion channel function of TMC7 in the Golgi. Now the author agrees and has changed the description to be reasonable. Additional experiments were also performed, and I can say that they have answered my concern adequately.
I would say it is good to add any presumed mechanism for the observed changes in pH and calcium concentration in the cytoplasm this time.
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Reviewer #1 (Public Review):
Summary:
In this paper, the authors performed molecular dynamics (MD) simulations to investigate the molecular basis of association of alpha-synuclein chains under molecular crowding and salt conditions. Aggregation of alpha-synuclein is linked to the pathogenesis of Parkinson's disease, and the liquid-liquid phase separation (LLPS) is considered to play an important role in the nucleation step of the alpha-synuclein aggregation. This paper re-tuned the Martini3 coarse-grained force field parameters, which allows long-timescale MD simulations of intrinsically disordered proteins with explicit solvent under diverse environmental perturbation. Their MD simulations showed that alpha-synuclein does not have a high LLPS-forming propensity, but the molecular crowding and salt addition tend to enhance the tendency of droplet formation and therefore modulate the alpha-synuclein aggregation. The MD simulation results also revealed important intra and inter-molecule conformational features of the alpha-synuclein chains in the formed droplets and the key interactions responsible for the stability of the droplets. These MD simulation data add biophysical insights into the molecular mechanism underlying the association of alpha-synuclein chains, which may be useful for understanding the pathogenesis of Parkinson's disease.
Strengths:
(1) The re-parameterized Martini 3 coarse-grained force field enables the large-scale MD simulations of the intrinsically disordered proteins with explicit solvent, which will be useful for a more realistic description of the molecular basis of LLPS.
(2) This paper showed that the molecular crowding and salt contribute to the modulation of the LLPS through different means. The molecular crowding minimally affects surface tension, but adding salt increases surface tension. It is also interesting to show that the aggregation pathway involves the disruption of the intra-chain interactions arising from C-terminal regions, which potentially facilitates the formation of inter-chain interactions.
Weaknesses:
(1) Although the authors emphasized the advantage of the Martini3 force field for its explicit description of solvent, this paper did not analyze the water behavior contained in the simulation trajectories and discuss the water's role in the aggregation and LLPS.
(2) This paper discussed the effects of crowders and salt on the surface tension of the droplets. The calculation of the surface tension relies on the droplet shape. However, for the formed clusters in the MD simulations, the typical size is <10, which may be too small to rigorously define the droplet shape. As shown in previous work cited by this paper [Benayad et al., J. Chem. Theory Comput. 2021, 17, 525−537], the calculated surface tension becomes stable when the chain number is larger than 100.
(3) Both the sizes and volume fractions of the crowders can affect the protein association. It will be interesting to perform MD simulations by adding crowders with various sizes and volume fractions. In addition, in this work the crowders were modelled by fullerenes, which contribute to protein aggregation mainly by entropic means as discussed in the manuscript. It is not very clear how the crowder effect is sensitive to the chemical nature of the crowders (e.g., inert crowers with excluded volume effect or crowders with non-specific attractive interactions with proteins, etc).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Fister et. al. investigate how amputational and burn wounds affect sensory axonal damage and regeneration in a zebrafish model system. The authors discovered that burn injury results in increased peripheral axon damage and impaired regeneration. Convincing experiments show altered axonal morphology and increased Ca2+ fluxes as a result of burn damage. Further experimental proof supports that early removal of the burnt tissue by amputation rescues axonal damage. Burn damage was also shown to markedly increase keratinocyte migration and increase localized ROS production as measured by the dye Pfbsf. These responses could be inhibited by Arp 2/3 inhibition and isotonic treatment.
Strengths:
The authors use state-of-the-art methods to study and compare transection and burn-induced tissue damage. Multiple experimental approaches (morphology, Ca2+ fluxing, cell membrane labeling) confirm axonal damage and the impaired regeneration time. Furthermore, the results are also accompanied by functional response tests of touch sensitivity. This is the first study to extend the role of tissue-damage related osmotic exposure beyond wound closure and leukocyte migration to a novel layer of pathology: axonal damage and regeneration.
The authors provide elegant experiments showing that early removal of the burnt tissue can rescue damage-induced axonal damage, which could also be interpreted in an osmotic manner. In the revised version of the paper the authors indeed show that tail fin transections close faster than burn wounds, allowing for lower hypotonic exposure time. However, their new experiments suggest that axonal damage and slow regeneration in tail fin burn wounds are not a direct consequence of the extended exposure time to hypotonic water.
Weaknesses:
The conclusions of the paper claiming a link between burn-induced epithelial cell migration, spatial redox signaling, and sensory axon regeneration are mainly based on correlative observations. Arp 2/3 inhibition impairs cell migration but has no significant effect on axon regeneration and restoration of touch sensitivity.
Genetic approaches have been tested during the revision process to directly prove the role of ROS production by targeting DUOX, however, the combination of DUOX morpholino and burn injury was lethal to the larvae and long-term pharmacological inhibition over 1 hour was also detrimental.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In the manuscript Chugh and co-workers utilize a suite of NMR relaxation methods to probe the dynamic landscape of the TAR RNA binding protein (TRBP) double-stranded RNA-binding domain 2 (dsRBD2) and compare these to their previously published results on TRBP dsRBD1. The authors show that, unlike dsRBD1, dsRBD2 is a rigid protein with minimal ps-ns or us-ms time scale dynamics in the absence of RNA. They then show that dsRBD2 binds to canonical A-form dsRNA with a higher affinity and with less changes in dynamics compared to dsRBD1.
Strengths:
The authors expertly use a variety of NMR techniques to probe protein motions over six-orders of magnitude in time. Other NMR titration experiments and ITC data support the RNA-binding model.
Weaknesses:
Generally, the data collection and analysis are sound. However, microsecond timescale dynamics for the RNA-bound form of dsRBD2 are inferred from a sample that is only 5% bound. Additionally, the manuscript lacks context with the much broader field of RNA-binding proteins. For example, many studies have shown that RNA recognition motif (RRM) domains have similar dynamic characteristics when binding diverse RNA substrates.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The study identifies the epigenetic reader SntB as a crucial transcriptional regulator of growth, development, and secondary metabolite synthesis in Aspergillus flavus, although the precise molecular mechanisms remain elusive. Using homologous recombination, researchers constructed sntB gene deletion (ΔsntB), complementary (Com-sntB), and HA tag-fused sntB (sntB-HA) strains. Results indicated that deletion of the sntB gene impaired mycelial growth, conidial production, sclerotia formation, aflatoxin synthesis, and host colonization compared to the wild type (WT). The defects in the ΔsntB strain were reversible in the Com-sntB strain.
Further experiments involving ChIP-seq and RNA-seq analyses of sntB-HA and WT, as well as ΔsntB and WT strains, highlighted SntB's significant role in the oxidative stress response. Analysis of the catalase-encoding catC gene, which was upregulated in the ΔsntB strain, and a secretory lipase gene, which was downregulated, underpinned the functional disruptions observed. Under oxidative stress induced by menadione sodium bisulfite (MSB), the deletion of sntB reduced catC expression significantly. Additionally, deleting the catC gene curtailed mycelial growth, conidial production, and sclerotia formation, but elevated reactive oxygen species (ROS) levels and aflatoxin production. The ΔcatC strain also showed reduced susceptibility to MSB and decreased aflatoxin production compared to the WT.
This study outlines a pathway by which SntB regulates fungal morphogenesis, mycotoxin synthesis, and virulence through a sequence of H3K36me3 modification to peroxisomes and lipid hydrolysis, impacting fungal virulence and mycotoxin biosynthesis.
The authors have achieved the majority of their aims at the beginning of the study, finding target genes, which led to catC mediated regulation of development, growth and aflatoxin metabolism. Overall most parts of the study are solid and clear.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
V.Mischley et al have applied several simple machine learning (ML)frameworks (which were widely used before the advent of deep learning methods) to distinguish (as the authors claimed) between interacting and non-interacting pairs. For this purpose, the authors have generated two sets of protein pairs, equal in their size (which is preferable for classification problems in ML). The first set comprises a non-redundant set of interacting proteins from the DOCKGROUND database, and the second set consists of presumably non-interacting protein pairs. Then, the authors trained and evaluated compared performance of the utilized ML frameworks using a set of well-described parameters. The authors also demonstrated the superior performance of their method in comparison to other metrics, such as ipTM and pdockQ. Finally, the authors applied their method to identify interacting pairs within the tumor necrosis factor superfamily. In general, the paper is well written, and the methodology applied is sound, however, I have a fundamental concern regarding the non-interacting set. As follows from the author's description, this set does not ensure that generated protein pairs do not interact as follows from the main paradigm of template-based docking (structurally similar proteins have similar binding modes). In my opinion, this set rather presents a set of non-cognate or weekly interacting protein pairs. That also explains the drop in performance for the pDockQ metric on the authors' set (AUC 0.71 in this paper opposite t0 0.87 in the original paper), as pDockQ was trained on the set of truly non-interacting proteins. In that respect, it would be interesting to see the performance of the authors' approach, but trained on the set described in the pDockQ paper (more or less the same set of interacting pairs but a different set of non-interacting proteins).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors' claims that CD9 and CD81 are key regulators of TNT formation and function are well-supported by the data. The use of KO and OE models provides strong evidence. The differential proteomic analysis between TNTs and EVPs and the functional assays justify the conclusion that these tetraspanins are critical for TNT biogenesis and functionality. Overall, the manuscript presents a nice study that advances our understanding of TNTs and their regulation by CD9 and CD81. Despite some limitations, the strengths of the experimental design and the robustness of the data justify the authors' conclusions. Future studies addressing the identified weaknesses would further solidify these findings and their implications in pathological contexts.
Strengths:
Novelty and Significance - this study addresses the composition and regulation of tunneling nanotubes (TNTs). By identifying the roles of CD9 and CD81 tetraspanins, the researchers offer insights into the molecular mechanisms underlying TNT formation. This could have implications for understanding cellular communication in pathological conditions such as cancer.
Methodological Accuracy - the authors employed a well-designed biochemical approach to isolate TNTs from U2OS cells, distinguishing them from extracellular vesicles and particles (EVPs). The use of multiple independent preparations and the application of LC-MS/MS for proteomic analysis ensure robustness and reproducibility of the data.
Complete Analysis - the study provides a detailed proteomic profile of TNTs, identifying 1177 proteins and highlighting key components. The comparative analysis between TNTs and EVPs further strengthens the findings by demonstrating distinct proteomic landscapes.
Functional Insights - using knockout (KO) and overexpression (OE) models, the authors convincingly demonstrate the distinct roles of CD9 and CD81 in TNT formation and function. CD9 is shown to stabilize TNTs, while CD81 facilitates vesicle transfer, likely by aiding membrane docking or fusion.
Experimental Design - the use of actin chromobody-GFP and various fluorescent markers enabled the authors to visualize TNTs and validate their isolation protocol. Additionally, the combination of electron microscopy, flow cytometry, and live-cell imaging provided convincing evidence for their claims.
Weaknesses:
Potential Contaminations - while the authors took steps to minimize contamination with other cellular structures, the presence of some nuclear proteins and the possible inclusion of small portions of cell bodies or ER in the TNT preparations cannot be entirely ruled out. This may affect the interpretation of some proteomic data.
Limited Cell Models - the experiments were conducted in U2OS and SH-SY5Y cells. While these are relevant models, in vivo validation of the findings would significantly enhance the impact and translational potential of the research.
Functional Mechanisms - although the study provides strong evidence for the roles of CD9 and CD81, the exact molecular mechanisms by which these tetraspanins regulate TNT formation and vesicle transfer remain partially speculative. Further biochemical and biophysical analyses would be necessary to elucidate these mechanisms in detail.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this study, the authors used a stopped-flow method to investigate the kinetics of substrate translocation through the channel in hexameric ClpB, an ATP-dependent bacterial protein disaggregase. They engineered a series of polypeptides with the N-terminal RepA ClpB-targeting sequence followed by a variable number of folded titin domains. The authors detected translocation of the substrate polypeptides by observing the enhancement of fluorescence from a probe located at the substrate's C-terminus. The total time of the substrates' translocation correlated with their lengths, which allowed the authors to determine the number of residues translocated by ClpB per unit time.
Strengths:
This study confirms a previously proposed model of processive translocation of polypeptides through the channel in ClpB. The novelty of this work is in the clever design of a series of kinetic experiments with an engineered substrate that includes stably folded domains. This approach produced a quantitative description of the reaction rates and kinetic step sizes. Another valuable aspect is that the method can be used for other translocases from the AAA+ family to characterize their mechanism of substrate processing.
Weaknesses:
The main limitation of the study is in using a single non-physiological substrate of ClpB, which does not replicate the physical properties of the aggregated cellular proteins and includes a non-physiological ClpB-targeting sequence. Another limitation is in the use of ATPgammaS to stimulate the substrate processing. It is not clear how relevant the results are to the ClpB function in living cells with ATP as the source of energy, a multitude of various aggregated substrates without targeting sequences that need ClpB's assistance, and in the presence of the co-chaperones.
The authors do not attempt to correlate the kinetic step sizes detected during substrate translocation and unfolding with the substrate's structure, which should be possible, given how extensively the stability and unfolding of the titin I27 domain were studied before. Also, since the substrate contains up to three I27 domains separated with unstructured linkers, it is not clear why all the translocation steps are assumed to occur with the same rate constant.
Some conclusions presented in the manuscript are speculative:
The notion that the emission from Alexa Fluor 555 is enhanced when ClpB approaches the substrate's C-terminus needs to be supported experimentally. Also, evidence that ATPgammaS without ATP can provide sufficient energy for substrate translocation and unfolding is missing in the paper.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, Abidi and colleagues used Notch pathway-neutralizing antibodies to inhibit sebaceous glands in the skin. The authors find that blocking either the Notch1 receptor or the Jag2 ligand caused loss of the glands and increased retention of sebaceous progenitor cells. Moreover, these glands began to reappear 14 days after treatment.
Strengths:
Overall, this study definitively identifies the Notch receptor/ligand combination that maintains these glands in the adult. The manuscript is clearly written and the figures are beautifully made.
Weaknesses:
Minor text edits should be made.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, the authors present an interesting strategy to interfere with the HBV life cycle: the preparation of geranyl and peptides' dimers that could impede the correct assembly of hepatitis B core protein HBc into viable capsids. These dimers are of different nature, depending on the HBc site the authors plan to target. A preliminary study with geranyl dimers (targeting a hydrophobic site of HBc) was first investigated. The second series deals with peptide-PEG linker-peptide dimers, targeting the tips of HBc dimer spikes.
Strengths:
This work is very well conducted, combining ITC experiments (for determination of dimers' KD), cellular effects (thanks to the grafting of previously developed dimers with polyarginine-based cell penetrating peptide) HBV infected HEK293 cells and Cryo-EM studies.
The findings of these research teams unambiguously demonstrated the interest of such dimeric structures in impeding the correct HBV life cycle and thus, could bring solutions in the control of its development. Ultimately, a new class of HBV Capside Assembly Modulators could arise from this study.
There is no doubt that this work could bring very interesting information for people working on VHB.
Weaknesses:
Some minor corrections must be made, especially for a more precise description of the strategy and the chemical structure of the designed new VHB capsid assembly modulators.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this article, Almeida and colleagues use a combination of NMR and ITC to study the interaction of the EBH domain of microtubule end-binding protein 1 (EB1) with SxIP peptides derived from the MACF plus-end tracking protein. EBH forms a dimer and in isolation has previously been shown to have a disordered C-terminal tail. Here, the authors use NMR to determine a solution structure of the EBH dimer bound to 11-mer SxIP peptides derived from MACF, and observe that the disordered C-terminal of EBH is recruited by residues C-terminal to the SxIP motif to fold into the final complex. By comparison of binding in different length peptides, and of EBH lacking the C-terminal tail, they show that these additional contacts increase binding affinity by an order of magnitude, greatly stabilising the interaction, in a binding mode they term 'dock-and-lock'.
The authors also use their new structural knowledge to design peptides with higher affinities and show in a cell model that these can be weakly recruited to microtubule ends - although a dimeric construct is necessary for efficient recruitment. Ultimately, by demonstrating the feasibility of targeting these proteins, this work points towards the possibility of designing small-molecules to block the interactions.
Strengths:
The authors determine an NMR structure of the dimeric complex, and additional report nuclear spin relaxation measurements to explore conformational dynamics within the complex via S2 order parameters and exchange contributions to relaxation (Rex terms).
A variety of appropriate experimental techniques are applied to probe the thermodynamics and kinetics of peptide binding: ITC, 2D NMR lineshape analysis, and chemical exchange saturation transfer (CEST) NMR. These yield consistent results, and a thoughtful analysis is described, based on the non-observation of exchange broadening in 2D titration and CEST measurements, in order to conclude that the proposed locking step, in which the C-terminal tail of EBH folds against the bound peptide, must occur on a rapid (sub-ms) timescale.
The use of 2D NMR lineshape analysis enables authors to extract the fullest information from their titration data, permitting an analysis of binding kinetics in addition to affinities. They also mention briefly that this enables them to account for the fact that binding occurs to two symmetric sites on the EBH dimer.
The authors use a range of peptide lengths, and mutations of EBH, to explore the contribution of different parts of the sequence to the overall binding affinity. They also use their structural observations to design a new peptide that binds with sub-micromolar affinity. They develop a simple but effective fluorescence assay to test the interaction of these peptides with microtubule ends within cells and show that their designed peptide can compete with native ligands for EBH.
Weaknesses:
There is no direct experimental evidence for independent dock and lock steps. The model is certainly plausible given their structural data, but all titration and CEST measurements are fully consistent with a simple one-step binding mechanism. Indeed, it is acknowledged that the results for the VLL peptide are not consistent with the predictions of this model, as affinity and dissociation rates do not co-vary. The model may still be a helpful way to interpret and discuss their results, and may indeed be the correct mechanism, but this has not yet been proven.
There is little discussion of the fact that binding occurs to EBH dimers - either in terms of the functional significance of this or in the acquisition and analysis of their data. There is no discussion of cooperation in binding (or its absence), either in the analysis of NMR titrations or in ITC measurements. Complete ITC fit results have not been reported so it is not possible to evaluate this for oneself.
Three peptides are used to examine the role of C-terminal residues in SxIP motifs: 4-MACF (SKIP), 6-MACF (SKIPTP), and 11-MACF (KPSKIPTPQRK). The 11-mer demonstrates the strongest binding, but this has added residues to the N-terminal as well. It has also introduced charges at both termini, further complicating the interpretation of changes in binding affinities. Given this, I do not believe the authors can reasonably attribute increased affinities solely to post-SxIP residues.
Experimental uncertainties are, with exceptions, not reported.
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Reviewer #1 (Public Review):
Summary:
The manuscript by Velichko et al. argues that the ability of nucleolar protein Treacles to form phase-separated condensates is necessary for its function in nucleolar organization, rRNA transcription, and rDNA repair. These findings may be of interest to the communities studying biomolecular condensates, nucleolar organization, and ribosome biogenesis. The authors propose that Treacle's ability to undergo liquid-liquid phase separation is the key to its role as a scaffold for the FC of the nucleolus. The experiments in this study were designed and performed well, particularly the overexpression studies, done in the absence of endogenous protein and accounted for the protein expression levels. However, in my view, the interpretation of these data should consider the possibility that specific protein-protein interactions of Treacle may also play a role in the organization of the FC compartment in vivo. The in vivo results do not exclude, and sometimes imply the presence of specific protein-protein interactions that may drive the organization of FC instead of, or in addition to LLPS.
Main points:
In the first part of the manuscript, the depletion of Treacle disrupted the FC and its (somewhat arbitrary) boundary with the dense fibrillar component, as well as rRNA biogenesis. The phenotypic effects of Treacle depletion by gene knockout or siRNA knockdown were evaluated thoroughly, and I see no issues here except that all experiments were conducted in HeLa cells, and it may not hurt to validate some key findings in a more normal cell line.
Next, the authors tested the hypothesis that the function of Treacle is due to its ability to form biomolecular condensates. In vitro, recombinant Treacle displayed classical phase separation behavior, forming liquid droplets at low salt concentrations and in the presence of dextran. Similarly, overexpression of fluorescently tagged Treacle at high concentrations showed classical liquid droplet behavior, characterized by round shapes and rapid fusion, which is illustrated by beautiful live cell video microscopy. The issue I see here is with the interpretation: the formation of classical phase-separated droplets at high concentrations suggests that Treacle may require reaching a certain saturating concentration to undergo phase separation. In other words, high levels of overexpressed protein might lead to abnormal phase separation that may not happen under normal expression levels. Based on these results, it is not necessarily correct to assume that its normal conformation is solely due to phase separation, as the formation of condensates at saturating concentrations does not automatically imply that the same components undergo phase separation under physiological conditions.
Treacle had been previously reported to interact with other proteins, specifically RPA194 and UBF, and these interactions were mapped to specific domains: the central repeated domain reportedly binds to RNA Pol I, while the C-terminus is involved in rDNA promoter recognition and UBF recruitment. Both of these proteins are necessary for rRNA transcription and nucleolar formation. Authors showed that overexpressing mutants impaired in phase separation resulted in defects in ribosomal RNA transcription and processing, as well as reduced DNA damage response efficiency. Specific protein-protein interactions as potential drivers of compartmentalization should be factored into the interpretation of these results. For instance, the deletion of the C-terminal (Δ1121-1488) results may indicate that the interaction with UBF is important. A charge-scrambled central domain mutant may have lost its interaction with Pol I. These specific interactions may establish the architecture of the compartment and increase the local concentration of Treacle, which in turn could facilitate phase separation locally. LLPS and specific protein-protein interactions are not mutually exclusive.
Overall, the data supports the idea that the overexpressed Treacle behaves like a classic phase-separated protein, but it is still possible that at physiological levels its specific interactions with other proteins are also important for the organization of FC. I am not suggesting that authors performed a conceptually different work, but this aspect should be discussed in the manuscript.
Other points:
FACS - sorting used throughout the study to separate treatment from the control essentially distinguishes transfected vs untransfected cells. Since the transfection itself can have odd effects, it might be beneficial to include an additional control involving Cas9 transfection with a non-targeting guide RNA.
The authors convincingly demonstrated in Figure 1 that the depletion of Treacle reduces RPA194 occupancy on the rDNA. This raises a question: which Treacle mutants can restore RPA194 occupancy, and which cannot?
Figure 2 - measuring FRAP recovery rates as indicative of LLPS, at least for the full-length Treacle, would be more informative if authors assessed the protein turnover within the compartment (half or partial FRAP) versus exchange in and out of the compartment (full compartment FRAP).
Statement related to Figure 2: "Fluorescence recovery in FCs, nucleolar caps, and extranucleolar condensates never reached the initial values over the analyzed time periods. This suggests that the high molecular exchange rate occurs through the mixing of Treacle molecules within the condensate boundaries and does not involve external diffusion". Assuming the post-bleach data were normalized to the cell's total fluorescent intensity, the presence of a substantial immobile fraction could also suggest high-affinity binding of that fraction to something within the compartment.
Data related to DDR activation in ribosomal genes under genotoxic stress (Figure 5) is convincing, but it would not hurt to confirm the key findings in a more normal cell line, since HeLa cells may not accurately represent all aspects of healthy DDR.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this paper, Schalcher et al. examined how barn owls' landing force affects their hunting success during two hunting strategies: strike hunting and sit-and-wait hunting. They tracked tens of barn owls that raised their nestlings in nest boxes and utilized high-resolution GPS and acceleration loggers to monitor their movement. In addition, camcorders were placed near their nest boxes and used to record the prey they brought to the nest, thus measuring their foraging success.
This study generated a unique dataset and provided new insights into the foraging behavior of barn owls. The researchers discovered that the landing force during hunting strikes was significantly higher compared to the sit-and-wait strategy. Additionally, they found a positive relationship between landing force and foraging success during hunting strikes, whereas, during the sit-and-wait strategy, there was a negative relationship between the two. This suggests that barn owls avoid detection by generating a lower landing force and producing less noise. Furthermore, the researchers observed that environmental characteristics affect barn owls' landing force during sit-and-wait hunting. They found a greater landing force when landing on buildings, a lower landing force when landing on trees, and the lowest landing force when landing on poles. The landing force also decreased as the time to the next hunting attempt decreased. These findings collectively suggest that barn owls reduce their landing force as an acoustic camouflage to avoid detection by their prey.
The main strength of this work is the researchers' comprehensive approach, examining different aspects of foraging behavior, including high-resolution movement, foraging success, and the influence of the environment on this behavior, supported by impressive data collection.
The results presented support the authors' conclusion that lower landing force during sit-and-wait hunting increases hunting success, likely due to a decreased probability of detection by their prey, resulting in acoustic camouflage. The authors also hypothesized that hunting success is crucial for survival, and thus, acoustic camouflage has a direct link to fitness. This paper provides an unprecedented dataset and the first measurement of landing force during hunting in the wild. It is likely to inspire many other researchers currently studying animal foraging behavior to explore how animals' movement affects foraging success.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors have shown the following:
(1) SY1 aggregation enhances (in terms of number of aggregates) when Sphingolipid biosynthesis is blocked.<br /> (2) In a normal cell (where sphingolipid biosynthesis is not hampered), the aggregate of SY1 (primarily the Class I aggregate) is localized only on the mitochondrial endomembrane system.<br /> (3) The localization is due to the association of SY1 (aggregates) with mitochondrial proteins like Tom70, Tim44, etc. (Is the localization completely lost? What happens to the toxicity when the aggregates are not localized on mitochondria?)<br /> (4) This fuels the loss of mitochondrial function.<br /> (5) Mitochondrial function is further abrogated when there is a block in sphingolipid biosynthesis.<br /> (6) A similar phenomenon is conserved in mammalian cell lines.
Comments on the revised version
The authors have addressed all the issues raised and I am satisfied with the answers but with the following reservations.
(1) I still think that the authors need to set the importance of the differences in aggregation in the context of toxicity arising from protein misfolding/aggregation. While the authors state the limitation in the response, and I agree that a single manuscript cannot complete a field of investigation I still think that this is an important point missing from this manuscript.
(2) I retain my reservations about the fluorescence intensity data shown for Rho123, DCF, Jc1, and MitoSox. The errors are much lower than what we typically achieve in biological experiments in our as well as our collaborator's lab. A glimpse at published literature would also support our statement. Specifically, RHO123 shows a large difference in errors between Figure 5 and Figure 5 Supplement 2. The point to note is that the absolute intensities do not vary between these figures, but the errors are the order of magnitude lower in the main figures. I, therefore, accept these figures in good faith without further interrogation.<br /> I think the message from the manuscript is important and worth following up on.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
This study by Algranati et al. is a important contribution to our understanding of H3-K27M pediatric gliomas. It convincingly demonstrates that the concomitant targeting of histone deacetylases (HDACs) and MYC, through a combination therapy of Sulfopin and Vorinostat, results in a notable reduction in cell viability and tumor growth. This reduction is linked to the suppression of critical oncogenic pathways, particularly mTOR signaling, emphasizing the role of these pathways in the disease's pathogenesis. The manuscript is a step forward in the field, as it unveils a vulnerability from dual targeting HDACs and MYC in the context of pediatric gliomas.
Comments on revised version
The authors have nicely explained their rationale for dose selection, treatment timing, and the relationship between MYC expression and sensitivity to the combined treatment. They have also clarified the experimental conditions for the in vitro and in vivo studies, ensuring consistency across the various analyses.
Overall, the authors have been responsive to the reviewers' comments and have made appropriate revisions to improve the clarity and robustness of their study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript examines the contribution of dorsal and intermediate hippocampus to goal-directed navigation in a wide virtual environment where visual cues are provided by the scenery on the periphery of a wide arena. Among a choice of 2 reward zones located near the arena periphery, rats learn to navigate from the center of the arena to the reward zone associated with the highest reward. Navigation performance is largely assessed from the rats' body orientation when they leave the arena center and when they reach the periphery, as well as the angular mismatch between reward zone and the site rats reach the periphery. Muscimol inactivation of dorsal and intermediate hippocampus alters rat navigation to the reward zone, but the effect was more pronounced for the inactivation of intermediate hippocampus, with some rat trajectories ending in the zone associated with the lowest reward. Based on these results, the authors suggest that the intermediate hippocampus is critical especially for navigating to the highest reward zone.
Strengths:
- The authors developed an effective approach to study goal-directed navigation in a virtual environment where visual cues are provided by the peripheral scenery.
- In general, text is clearly written and the figures are well designed and relatively straightforward to interpret, even without reading the legends.
- An intriguing result, which would deserve to be better investigated and/or discussed, was that rats tended to rotate always in the counterclockwise direction. Could this be because of a hardware bias making it easier to turn left, some aspect of the peripheral landscape, or a natural preference of rats to turn left that is observable (or reported) in real environment?
- Another interesting observation, which would also deserved to be addressed in the discussion, is the fact that dHP/iHP inactivations produced to some extent consistent shifts in departing and peripheral crossing directions. This is visible from the distributions in Figures 6 and 7, which still show a peak under muscimol inactivation, but this peak is shifted to earlier angles than the correct ones. Such change is not straightforward to interpret, unlike the shortening of the mean vector length.<br /> Maybe rats under muscimol could navigate simply using association of reward zone with some visual cues in the peripheral scene, in brain areas other than the hippocampus, and therefore stopped their rotation as soon as they saw the cues, a bit before the correct angle. While with their hippocampus intact, rats could estimate precisely the spatial relationship between the reward zone and visual cues.
Weaknesses:
- I am not sure that the differential role of dHP and iHP for navigation to high/low reward locations is supported by the data. The current results could be compatible with iHP inactivation producing a stronger impairment on spatial orientation than dHP inactivation, generating more erratic trajectories that crossed by chance the second reward zone.
To make the point that iHP inactivation affects disambiguation of high and low reward locations, the authors should show that the fraction of trajectories aiming at the low reward zone is higher than expected by chance. Somehow we would expect to see a significant peak pointing toward the low reward zone in the distribution of Figures 6-7.
Review of revised manuscript
The experimental paradigm and analyses are interesting/novel and generate some intriguing phenomena such as the animals' preference for counterclockwise rotation and the stereotypical trajectory shifts induced by muscimol inactivation. Understanding better the underlying mechanisms of these phenomena and the navigational strategies involved in this apparatus will be important in the future for correctly interpreting inactivation experiments.
The idea of a differential effect of dMUS and iMUS was toned down in the abstract and other parts of the manuscript, such that the claims now better match the data.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript aims at a quantitative model of how visual stimuli, given as time-dependent light intensity signals, are transduced into electrical currents in photoreceptors of macaque and mouse retina. Based on prior knowledge on the fundamental biophysical steps of the transduction cascade and a relatively small number of free parameters, the resulting model is found to fairly accurately capture measured photoreceptor currents under a range of diverse visual stimuli and with parameters that are (mostly) identical for photoreceptors of the same type.
Furthermore, as the model is invertible, the authors show that it can be used to derive visual stimuli that result in a desired, predetermined photoreceptor response. As demonstrated with several examples, this can be used to probe how the dynamics of phototransduction affect downstream signals in retinal ganglion cells, for example, by manipulating the visual stimuli in such a way that photoreceptor signals are linear or have reduced or altered adaptation. This innovative approach had already previously been used by the same lab to probe the contribution of photoreceptor adaptation to differences between On and Off parasol cells (Yu et al, eLife 2022), but the present paper extends this by describing and testing the photoreceptor model more generally and in both macaque and mouse as well as for both rods and cones.
Strengths:
The presentation of the model is thorough and convincing, and the ability to capture responses to stimuli as different as white noise with varying mean intensity and flashes with a common set of model parameters across cells is impressive. Also, the suggested approach of applying the model to modify visual stimuli that effectively alter photoreceptor signal processing is thought-provoking and should be a powerful tool for future investigations of retinal circuit function. The examples of how this approach can be applied are convincing and corroborate, for example, previous findings that adaptation to ambient light in the primate retina, as measured by responses to light flashes, mostly originates in photoreceptors. Application of the approach by other labs is facilitated by the clear exposition and the listing of obtained optimal parameter values.
Weaknesses:
The model is impressive, but not perfect, including some small systematic differences between model predictions and measurements from held-out cells. The deviations likely (partly) reflect differences between cells used for parameter optimization and test cells, as stated in the text (though this is not fully proven), which has to be kept in mind when applying the model, in particular with the listed parameters.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Microfossils from the Paleoarchean Eon represent the oldest evidence of life, but their nature has been strongly debated among scientists. To resolve this, the authors reconstructed the lifecycles of Archaean organisms by transforming a Gram-positive bacterium into a primitive lipid vesicle-like state and simulating early Earth conditions. They successfully replicated all morphologies and life cycles of Archaean microfossils and studied cell degradation processes over several years, finding that encrustation with minerals like salt preserved these cells as fossilized organic carbon. Their findings suggest that microfossils from 3.8 to 2.5 billion years ago were likely liposome-like protocells with energy conservation pathways but without regulated morphology.
Strengths:
The authors have crafted a compelling narrative about the morphological similarities between microfossils from various sites and proliferating wall-deficient bacterial cells, providing detailed comparisons that have never been demonstrated in this detail before. The extensive number of supporting figures is impressive, highlighting numerous similarities. While conclusively proving that these microfossils are proliferating protocells morphologically akin to those studied here is challenging, we applaud this effort as the first detailed comparison between microfossils and morphologically primitive cells.
Weaknesses:
Although the species used in this study closely resembles the fossils morphologically, it would be beneficial to provide a clearer explanation for its selection. The literature indicates that many bacteria, if not all, can be rendered cell wall-deficient, making the rationale for choosing this specific species somewhat unclear.
While this manuscript includes clear morphological comparisons, we believe the authors do not adequately address the limitations of using modern bacterial species in their study. All contemporary bacteria have undergone extensive evolutionary changes, developing complex and intertwined genetic pathways unlike those of early life forms. Consequently, comparing existing bacteria with fossilized life forms is largely hypothetical, a point that should be more thoroughly emphasized in the discussion.
Another weak aspect of the study is the absence of any quantitative data. While we understand that obtaining such data for microfossils may be challenging, it would be helpful to present the frequencies of different proliferative events observed in the bacterium used. Additionally, reflecting on the chemical factors in early life that might cause these distinct proliferation modes would provide valuable context.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study provides compelling evidence suggesting that ghrelin, a molecule released in the surroundings of the major adult brain neurogenic niche (V-SVZ) by blood vessels with high blood flow, controls the migration of newborn interneurons towards the olfactory bulbs.
Strengths:
This study is a tour de force as it provides a solid set of data obtained by time-lapse recordings in vivo. The data demonstrate that the migration and guidance of newborn neurons rely on factors released by selective types of blood vessels.
Weaknesses:
Some intermediate conclusions are weak and may be reinforced by additional experiments.
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doi.org doi.org
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Reviewer #2 (Public Review):
Summary:
The authors investigated systemic inflammation induced by LPS in various tissues and also examined immune cells of the mice using tight junction protein-based PDZ peptide. They explored the mechanism of anti-systemic inflammatory action of PDZ peptides, which enhanced M1/M2 polarization and induced the proliferation of M2 macrophages. Additionally, they insisted the physiological mechanism that inhibited the production of ROS in mitochondria, thereby preventing systemic inflammation.
Strength
In the absence of specific treatments for septic shock or sepsis, the study demonstrating that tight junction-based PDZ peptides inhibit systemic inflammation caused by LPS is highly commendable. Whereas previous research focused on antibiotics, this study proves that modifying parts of intracellular proteins can significantly suppress symptoms caused by septic shock. The authors expanded the study of localized inflammation caused by LPS or PM2.5 in the respiratory track to systemic inflammation, presenting promising results. They not only elucidated the physiological mechanism by identifying the transcriptome through RNA sequencing but also demonstrated that PDZ peptides inhibit the production of ROS in mitochondria and prevent mitochondrial fission. This research is highly regarded as an excellent study with potential as a treatment for septic shock or sepsis.
Weakness
(1) They Focused intensively on acute inflammation for a short duration instead of chronic inflammation.<br /> (2) LPS was used to induce septic shock, but administrating actual microbes such as E.coli would yield more accurate results.<br /> (3) The authors used pegylated peptides, but future research should utilize the optimized peptides to derive the optimal peptide, and further, PK/PD studies are also necessary.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, the authors studied the roles of SPNS1 which is a lysolipid transporter from the lysosomes in the nervous system using cell and mouse models. The authors tried to show that reduced sphingosine release from the lysosomes via SPNS1 affects myelination.
Strengths:
The authors used knockout models for cells and animals so the results are solid. They also used electron microscopic analysis of the phenotypes of the cells and mouse tissues.
Weaknesses:
The biochemical methods are not fully described at the moment. There is a lack of solid evidence to support the major claim.
If the authors could provide solid evidence that lipids that are released from the lysosomes via SPNS1 are used for myelination, this would be a major finding for the sources of lipids for the formation of axons.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This very short paper shows a greater likelihood of C->U substitutions at sites predicted to be unpaired in the SARS-CoV-2 RNA genome, using previously published observational data on mutation frequencies in SARS-CoV-2 (Bloom and Neher, 2023).
General comments:
A preference for unpaired bases as a target for APOBEC-induced mutations has been demonstrated previously in functional studies so the finding is not entirely surprising. This of course assumes that A3A or other APOBEC is actually the cause of the majority of C->U changes observed in SARS-CoV-2 sequences.
I'm not sure why the authors did not use the published mutation frequency data to investigate other potential influences on editing frequencies, such as 5' and 3' base contexts. The analysis did not contribute any insights into the potential mechanisms underlying the greater frequency of C->U (or G->U) substitutions in the SARS-CoV-2 genome.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, Floedder et al report that dopamine ramps in both Pavlovian and Instrumental conditions are shaped by reward interval statistics. Dopamine ramps are an interesting phenomenon because at first glance they do not represent the classical reward prediction errors associated with dopamine signaling. Instead, they seem somewhat to bridge the gap between tonic and phasic dopamine, with an intense discussion still being held in the field about what is their actual behavioral role. Here, in tests with head-fixed mice, and dopamine being recorded with a genetically encoded fluorescent sensor in the nucleus accumbens, the authors find that dopamine ramps were only present when intertrial intervals were relatively short and the structure of the task (Pavlovian cue or progression in a VR corridor) contained elements that indicated progression towards the reward (e.g., a dynamic cue). The authors show that these findings are well explained by their previously published model of Adjusted Net Contingency of Causal Relation (ANCCR).
Strengths:
This descriptive study delineates some fundamental parameters that define dopamine ramps in the studied conditions. The short, objective, and to-the-point format of the manuscript is great and really does a service to potential readers. The authors are very careful with the scope of their conclusions, which is appreciated by this reviewer.
Weaknesses:
The discussion of the results is very limited to the conceptual framework of the authors' preferred model (which the authors do recognize, but it still is a limitation). The correlation analysis presented in panel I of Figure 3 seems unnecessary at best and could be misleading, as it is really driven by the categorical differences between the two conditions that were grouped for this analysis. There are some key aspects of the data and their relationship with each other, the previous literature, and the methods used to collect them, that could have been better discussed and explored.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Horan et al. present a system for the chronic implantation of Neuropixels probes in mice and rats that allows the repeated cycles of implantation, explant, and reuse. A detailed protocol of the procedure, along with technical drawings for the parts of the system are provided, for potential users to undertake the technique in their own laboratory. The authors documented the adoption of this system in ten laboratories, demonstrating that the technique can be widely deployed. Yields in the number of neurons recorded over time are reported to indicate that the technique can achieve stable yields over time.
Strengths:
The authors provide compelling evidence that their technique can be widely deployed and acquired by different laboratories by documenting in detail the success rates at each step of the procedure and the common failure modes across ten laboratories. This is important because an impediment for a laboratory to try out a new technique is a lack of assurance about whether that technique would be successful outside the environment where the technique was originally developed. It is helpful that the authors show that even users who were not directly trained by the original developer of the technique can acquire the technique by receiving only the protocol and the technical drawings.
Weaknesses:
I would have liked to see more evidence demonstrating the purported advantages of the Repix design ("We found that the key advantage of Repix is robustness and simplicity.") relative to other techniques already available for chronic implantation allowing for reuse (Juavinett 2019, Luo 2020, van Daal 2021, Bimbard 2023, Melin 2023). While it is commendable that the authors demonstrate the durability of their design during social interactions, I would have liked to see evidence demonstrating that aluminum construction (compared to plastic) is necessary for "rough-and-tumble fights of male mice."
Aluminum parts are typically more expensive than plastic parts, and because machining aluminum parts is typically slower than 3D printing in plastic, the commitment to aluminum can greatly slow down the adaptation of the Repix design for specific experimental needs or for newer versions of Neuropixels probes to be released in the future. Also, as the authors stated, aluminum parts are a bit heavier than plastic parts. In addition, I remain not fully convinced that the Repix design is significantly simpler than the existing designs, and I would be more convinced if the authors could quantify the number of modular components of the Repix system relative to existing designs, or perhaps provide a time estimate of assembling a Repix system compared to assembling an existing design.
The possibility of achieving greater yield using dexamethasone is intriguing, but the authors only show this for rats and one brain region. Were the surgeries done using dexamethasone performed after the surgeries not using dexamethasone? If so, could the improved yield simply be due to improvement in surgical technique? As such, it remains unclear whether dexamethasone actually helps to achieve greater yields.
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www.youtube.com www.youtube.com
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According to Nishant, what I agree with, the truly successful people are MASTERS in their craft. They have committed to lifelong learning.
"Your learning capability decides your earning capacity."
See also: Ultralearning, Scott H. Young, and Deep Work, Cal Newport... The argument is the same: your ability to adapt in a complex rapidly changing information economy, and to master material determines how much you can earn.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The study shows a new mechanism of NFkB-p65 regulation mediated by Vangl2-dependent autophagic targeting. Autophagic regulation of p65 has been reported earlier; this study brings an additional set of molecular players involved in this important regulatory event, which may have implications for chronic and acute inflammatory conditions.
Comments on the revised version:
The authors have addressed the earlier concerns and I am satisfied with the revised version. I have no additional comments to make.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this study, Hunt et al investigated the role of the ubiquitin-conjugating enzyme UBE2D/effete (eff) in maintaining proteostasis during aging. Utilizing Drosophila as a model, the researchers observed diverse roles of E2 ubiquitin-conjugating enzymes in handling the aggregation-prone protein huntingtin-polyQ in the retina. While some E2s facilitated aggregate assembly, UBE2D/eff and other E2s were crucial for degradation of htt-polyQ. The study also highlights the significance of UBE2D/eff in skeletal muscle, showing that declining levels of eff during aging correlate with proteostasis disruptions. Knockdown of eff in muscle led to accelerated accumulation of poly-ubiquitinated proteins, shortened lifespan, and mirrored proteomic changes observed in aged muscles. The introduction of human UBE2D2, analogous to eff, partially rescued the deficits in lifespan and proteostasis caused by eff-RNAi expression in muscles.
Comments on revised version:
In this revised manuscript, the authors have addressed some of my concerns, yet several significant caveats remain unaddressed.
One major concern stems from the unexpected outcome observed in the UBE2D/eff loss-of-function experiment. Despite its known role as a ubiquitin-conjugating enzyme (E2), reducing UBE2D/eff levels led to an increase in poly-ubiquitinated proteins and p62 accumulation, suggesting a more complex and multifaceted phenotype seemingly unrelated to the expected role of UBE2D/eff. The authors proposed that an overall disruption of protein quality control, indirectly caused by effRNAi, could explain these phenotypes. However, while the authors noted that effRNAi does not affect proteasome activity, they have not explored other possibilities, leaving a mechanistic explanation still missing.
Furthermore, the comparative analysis of the old versus young proteome identified 10 out of 21 E2 enzymes, suggesting that other E2s may also contribute to age-related changes in proteostasis and lifespan. In this context, the authors mentioned that overexpression of human UBE2D2 in skeletal muscle does not influence lifespan, indicating that the reduced Eff levels observed during aging may not necessarily contribute to the aging phenotype.<br /> At this point, I believe the manuscript remains largely descriptive.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In the present study, the authors examined the possibility of using phosphatidyl-inositol kinase 3-kinase alpha (PI3Ka) inhibitors for heterotopic ossification (HO) in fibrodysplasia ossificans progressiva (FOP). Administration of BYL719, a chemical inhibitor of PI3Ka, prevented HO in a mouse model of FOP that expressed a mutated ACVR1 receptor. Genetic ablation of PI3Ka (p110a) also suppressed HO in mice. BYL719 blocked osteochondroprogenitor specification and reduced inflammatory responses, such as pro-inflammatory cytokine expression and migration/proliferation of immune cells. The authors claimed that inhibition of PI3Ka is a safe and effective therapeutic strategy for HO.
This is a revision of the original manuscript by Valer et al. The authors performed new experiments and added those data to the manuscript to respond to this reviewer's comments and questions.
Strengths:
Now it became clear that BYL719 inhibited the multiple signaling pathways in multiple types of cells.
Weaknesses:
However, it was not clear the critical role of PI3K in the inhibition of HO by this compound.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript by Zhou et al offers new high-resolution Cryo-EM structures of two human biotin-dependent enzymes: propionyl-CoA carboxylase (PCC) and methycrotonyl-CoA carboxylase (MCC). While X-ray crystal structures and Cryo-EM structures have previously been reported for bacterial and trypanosomal versions of MCC and for bacterial versions of PCC, this marks one of the first high resolution Cryo-EM structures of the human version of these enzymes. Using the biotin cofactor as an affinity tag, this team purified a group of four different human biotin-dependent carboxylases from cultured human Expi 293F (kidney) cells (PCC, MCC, acetyl-CoA carboxylase (ACC), and pyruvate carboxylase). Following further enrichment by size-exclusion chromatography, they were able to vitrify the sample and pick enough particles of MCC and PCC to separately refine the structures of both enzymes to relatively high average resolutions (the Cryo-EM structure of ACC also appears to have been determined from these same micrographs, though this is the subject of a separate publication). To determine the impact of substrate binding on the structure of these enzymes and to gain insights into substrate selectivity, they also separately incubated with propionyl-CoA and acetyl-CoA and vitrified the samples under active turnover conditions, yielding a set of cryo-EM structures for both MCC and PCC in the presence and absence of substrates and substrate analogues.
Strengths:
The manuscript has several strengths. It is clearly written, the figures are clear and the sample preparation methods appear to be well described. This study demonstrates that Cryo-EM is an ideal structural method to investigate the structure of these heterogeneous samples of large biotin-dependent enzymes. As a consequence, many new Cryo-EM structures of biotin-dependent enzymes are emerging, thanks to the natural inclusion of a built-in biotin affinity tag. While the authors report no major differences between the human and bacterial forms of these enzymes, it remains an important finding that they demonstrate how/if the structure of the human enzymes are or are not distinct from the bacterial enzymes. The MCC structures also provide evidence for a transition for BCCP-biotin from an exo-binding site to an endo-binding site in response to acetyl-CoA binding. This contributes to a growing number of biotin-dependent carboxylase structures that reveal BCCP-biotin binding at locations both inside (endo-) and outside (exo-) of the active site.
Weaknesses:
There are some minor weaknesses. Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues. There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors state that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. This is not a particularly deep analysis and doesn't really require a cryo-EM structure to invoke. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. This suggests, perhaps, that these structures do not yet fully capture the proper conformational states. The authors also need to be careful with their over-interpretation of structure to invoke mechanisms of conformational change. A snapshot of the starting state (apo) and final state (ligand-bound) is insufficient to conclude *how* the enzyme transitioned between conformational states. I am constantly frustrated by structural reports in the biotin-dependent enzymes that invoke "induced conformational changes" with absolutely no experimental evidence to support such statements. Conformational changes that accompany ligand binding may occur through an induced conformational change or through conformational selection and structural snapshots of the starting point and the end point cannot offer any valid insight into which of these mechanisms is at play.
Some of these minor deficiencies aside, the overall aim of contributing new cryo-EM structures of the human MCC and PCC has been achieved. While I am not a cryo-EM expert, I see no flaws in the methodology or approach. While the contributions from these structures are somewhat incremental, it is nevertheless important to have these representative examples of the human enzymes and it is noteworthy to see a new example of the exo-binding site in a biotin-dependent enzyme.
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public Review):
Summary:
In this study, the authors show that a long-non coding RNA lncDACH1 inhibits sodium currents in cardiomyocytes by binding to and altering the localization of dystrophin. The authors use a number of methodologies to demonstrate that lncDACH1 binds to dystrophin and disrupts its localization to the membrane, which in turn downregulates NaV1.5 currents. Knockdown of lncDACH1 upregulates NaV1.5 currents. Furthermore, in heart failure, lncDACH1 is shown to be upregulated which suggests that this mechanism may have pathophysiological relevance.
Strengths:
(1) This study presents a novel mechanism of Na channel regulation which may be pathophysiologically important.
(2) The experiments are comprehensive and systematically evaluate the physiological importance of lncDACH1.
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Reviewer #1 (Public Review):
In this work, the authors study the dynamics of fast-adapting pathogens under immune pressure in a host population with prior immunity. In an immunologically diverse population, an antigenically escaping variant can perform a partial sweep, as opposed to a sweep in a homogeneous population. In a certain parameter regime, the frequency dynamics can be mapped onto a random walk with zero mean, which is reminiscent of neutral dynamics, albeit with differences in higher order moments. Next, they develop a simplified effective model of time dependent selection with expiring fitness advantage, and posit that the resulting partial sweep dynamics could explain the behaviour of influenza trajectories empirically found in earlier work (Barrat-Charlaix et al. Molecular Biology and Evolution, 2021). Finally, the authors put forward an interesting hypothesis: the mode of evolution is connected to the age of a lineage since ingression into the human population. A mode of meandering frequency trajectories and delayed fixation has indeed been observed in one of the long-established subtypes of human influenza, albeit so far only over a limited period from 2013 to 2020. The paper is overall interesting and well-written. Some aspects, detailed below, are not yet fully convincing and should be treated in a substantial revision.
Major points
(1) The quasi-neutral behaviour of amino acid changes above a certain frequency (reported in Fig, 3), which is the main overlap between influenza data and the authors' model, is not a specific property of that model. Rather, it is a generic property of travelling wave models and more broadly, of evolution under clonal interference (Rice et al. Genetics 2015, Schiffels et al. Genetics 2011). The authors should discuss in more detail the relation to this broader class of models with emergent neutrality. Moreover, the authors' simulations of the model dynamics are performed up to the onset of clonal interference \rho/s_0 = 1 (see Fig. 4). Additional simulations more deeply in the regime of clonal interference (e.g. \rho / s_0 = 5) show more clearly the behaviour in this regime.
In this context, I also note that the modelling results of this paper, in particular the stalling of frequency increase and the decrease in the number of fixations, are very similar to established results obtained from similar dynamical assumptions in the broader context of consumer resource models; see, e.g., Good et al. PNAS 2018. The authors should place their model in this broader context.
(2) The main conceptual problem of this paper is the inference of generic non-predictability from the quasi-neutral behaviour of influenza changes. There is no question that new mutations limit the range of predictions, this problem being most important in lineages with diverse immune groups such as influenza A(H3N2). However, inferring generic non-predictability from quasi-neutrality is logically problematic because predictability refers to individual trajectories, while quasi-neutrality is a property obtained by averaging over many trajectories (Fig. 3). Given an SIR dynamical model for trajectories, as employed here and elsewhere in the literature, the up and down of individual trajectories may be predictable for a while even though allele frequencies do not increase on average. The authors should discuss this point more carefully.
(3) To analyze predictability and population dynamics (section 5), the authors use a Wright-Fisher model with expiring fitness dynamics. While here the two sources of the emerging neutrality are easily tuneable (expiring fitness and clonal interference), the connection of this model to the SIR model needs to be substantiated: what is the starting selection s_0 as a function of the SIR parameters (f, b, M, \epsilon), the selection decay \nu = \nu(f, b, M, \epsilon, \gamma)? This would enable the comparison of the partial sweep timing in both models and corroborate the mapping of the SIR onto the simplified W-F model. In addition, the authors' point would be strengthened if the SIR partial sweeps in Fig.1 and Fig.2 were obtained for a combination of parameters that results in a realistic timescale of partial sweeps.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study presents useful insights into the in vivo dynamics of insulin-producing cells (IPCs), key cells regulating energy homeostasis across the animal kingdom. The authors provide compelling evidence using adult Drosophila melanogaster that IPCs, unlike neighboring DH44 cells, do not respond to glucose directly, but that glucose can indirectly regulate IPC activity after ingestion supporting an incretin-like mechanism in flies, similar to mammals. The authors link the decreased activity of IPCs to hyperactivity observed in starved flies, a locomotive behavior aimed at increasing food search.
Furthermore, there is supporting evidence in the paper that IPCs receive inhibitory inputs from Dh44 neurons, which are linked to increased locomotor activity. However, although the electrophysiological data underlying the dynamics of IPCs in vivo is compelling, the link between IPCs and other potential elements of the circuitry (e.g. octopaminergic neurons) regulating locomotive behaviors is not clear and would benefit from more rigorous approaches.
This paper is of interest to cell biologists and electrophysiologists, and in particular to scientists aiming to understand circuit dynamics pertaining to internal state-linked behaviors competing with the feeding state, shown here to be primarily controlled by the IPCs.
Strengths:
(1) By using whole-cell patch clamp recording, the authors convincingly showed the activity pattern of IPCs and neighboring DH44 neurons under different feeding states.
(2) The paper provides compelling evidence that IPCs are not directly and acutely activated by glucose, but rather through a post-ingestive incretin-like mechanism. In addition, the authors show that Dh44 neurons located adjacent to the IPCs respond to bath application of glucose contrary to the IPCs.
(3) The paper provides useful data on the firing pattern of 2 key cell populations regulating food-related brain function and behavior, IPCs and Dh44 neurons, results which are useful to understand their in vivo function.
Weaknesses:
(1) The term nutritional state generally refers to the nutrients which are beneficial to the animal. In Figure 1, the authors showed that IPCs respond to glucose but not proteins. To validate the term nutritional state the authors could test the effect of a non-nutritive sugar (e.g. D-arabinose or L-Glucose) on the post-ingestive physiological responses of the IPCs.
(2) It is difficult to grasp the main message from the figures in the result section as some figures have several results subsections referring to different points the authors want to make. The key results of a figure will be easier to understand if they are summarized in one section of the results. Alternatively, a figure can be split into 2 figures if there are several key messages in those figures, e.g. Figures 2 and 3.
(3) The prime investigation of the paper is about the physiological response and locomotive behavioral readout linked to IPCs. The authors do not show a link between OANs and IPCs in terms of functional or behavioral readouts. In Figure 2 the authors first start with stating a link between OAN neurons and locomotion changes resulting from internal feeding states. The flow of the paper would be better if the authors focused on the effect of optogenetic activation of IPCs under different feeding states and their impact on fly locomotion. If the experiments done on optogenetic activation of OANs were to validate the experimental approach the data on OAN neurons is better suited for the supplement without the need of a subsection in the result section on the OANs.
(4) Figure 2F shows that optogenetic activation of IPCs in fed flies does not influence their locomotor output. In the text, the conclusion linked to Figure 2F-H states that IPC activation reduces starvation-induced hyperactivity which is a statement more suited to Figure 2I-K.
(5) The authors show activation of Dh44 neurons leads to hyperpolarisation of the IPCs. What is the functional link between non-PI Dh44 neurons and the IPCs? Do IPCs express DH44R or is DH44 required for this effect on IPCs? Investigating a potential synaptic or peptidergic link between DH44 neurons and IPCs and its effect on behavior would benefit the paper, as it is so far not well connected.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Here the authors convincingly identify and characterize the SERBP1 interactome and further define its role in the nucleus, where it is associated with complexes involved in splicing, cell division, chromosome structure, and ribosome biogenesis. Many of the SERBP1-associated proteins are RNA-binding proteins and SERBP1 exerts its impact, at least in part, through these players. SERBP1 is mostly disordered but along with its associated proteins displays a preference for G4 binding and can can bind to PAR and be PARylated. They present data that strongly suggest that complexes in which SERBP1 participates are assembled through G4 or PAR binding. The authors suggest that because SERBP1 lacks traditional functional domains yet is clearly involved in distinct regulatory complexes, SERBP1 likely acts in the early steps of assembly through the recognition of interacting sites present in RNA, DNA, and proteins.
Strengths:
The data is very convincing and demonstrated through multiple approaches.
Weaknesses:
No weaknesses were identified by this reviewer.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript studies nutrient intake rates for stationary and motile microorganisms to assess the effectiveness of swim vs. stay strategies. This work provides valuable insights on how the different strategies perform in the context of a simplified mathematical model that couples hydrodynamics to nutrient advection and diffusion. The swim and stay strategies are shown to yield similar nutrient flux under a range of conditions.
Strengths:
Strengths of the work include (i) the model prediction in Fig. 3 of nutrient flux applied to a range of microorganisms including an entire clade that are known to use different feeding strategies and (ii) a study of the interaction between cilia and absorption coverage showing the robustness of their predictions provided these regions have sufficient overlap.
Weaknesses: To improve the work, the authors should further expand their discussion of the following points:
(1) The authors comment that a number of species alternate between sessile and motile behavior. It would be helpful to discuss what is known about what causes switching between these modes and whether this provides insights regarding the advantages of the different behaviors.
(2) An encounter zone of R=1.1a appears be used throughout the manuscript, but I could not find a biological justification for this particular value. This results appear to be quite sensitive to this choice, as shown in Supplement Fig. 3(B). In the Discussion, it is mentioned that using a much larger exclusion zone leads to significantly different nutrient flux, and it is implied that such a large exclusion zone is not biologically plausible, but this was not explained sufficiently.
(3) In schematic of the in Fig. 2(B) it was unclear if the encounter zone in the envelope model is defined analogously to the Stokeslet model or if a different formulation is used.
(4) The force balance argument should be clarified. Equation (3) of the supplement gives the force-velocity relation in the motile case. Since equation (4), which the authors state is the net force in the sessile case, seems to involve the same expression, would it not follow from U=0 in the sessile case that one would simply obtain quiescent flow with Fcilia=0?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Tutak et al use a combination of pulldowns, analyzed by mass spectrometry, reporter assays, and fluorescence experiments to decipher the mechanism of protein translation in fragile X-related diseases. The topic is interesting and important.
Although a role for Rps26-deficient ribosomes in toxic protein translation is plausible based on already available data, the authors' data are not carefully controlled and thus do not support the conclusions of the paper.
Strengths:
The topic is interesting and important.
Weaknesses:
In particular, there is very little data to support the notion that Rps26-deficient ribosomes are even produced under the circumstances. And no data that indicate that they are involved in the RAN translation. Essential controls (for ribosome numbers) are lacking, no information is presented on the viability of the cells (Rps26 is an essential protein), and the differences in protein levels could well arise from block in protein synthesis, and cell division coupled to differential stability of the proteins.
Specific points:
(1) Analysis of the mass spec data in Supplemental Table S3 indicates that for many of the proteins that are differentially enriched in one sample, a single peptide is identified. So the difference is between 1 peptide and 0. I don't understand how one can do a statistical analysis on that, or how it would give out anything of significance. I certainly do not think it is significant. This is exacerbated by the fact that the contaminants in the assay (keratins) are many, many-fold more abundant, and so are proteins that are known to be mitochondrial or nuclear, and therefore likely not actual targets (e.g. MCCC1, PC, NPM1; this includes many proteins "of significance" in Table S1, including Rrp1B, NAF1, Top1, TCEPB, DHX16, etc...).
The data in Table S6/Figure 3A suffer from the same problem.
I am not convinced that the mass spec data is reliable.
(2) The mass-spec data however claims to identify Rps26 as a factor binding the toxic RNA specifically. The rest of the paper seeks to develop a story of how Rps26-deficient ribosomes play a role in the translation of this RNA. I do not consider that this makes sense.
(3) Rps26 is an essential gene, I am sure the same is true for DHX15. What happens to cell viability? Protein synthesis? The yeast experiments were carefully carried out under experiments where Rps26 was reduced, not fully depleted to give small growth defects.
(4) Knockdown efficiency for all tested genes must be shown to evaluate knockdown efficiency.
(5) The data in Figure 1E have just one mock control, but two cell types (control si and Rps26 depletion).
(6) The authors' data indicate that the effects are not specific to Rps26 but indeed also observed upon Rps25 knockdown. This suggests strongly that the effects are from reduced ribosome content or blocked protein synthesis. Additional controls should deplete a core RP to ascertain this conclusion.
(7) Supplemental Figure S3 demonstrates that the depletion of S26 does not affect the selection of the start codon context. Any other claim must be deleted. All the 5'-UTR logos are essentially identical, indicating that "picking" happens by abundance (background).
(8) Mechanism is lacking entirely. There are many ways in which ribosomes could have mRNA-specific effects. The authors tried to find an effect from the Kozak sequence, unsuccessfully (however, they also did not do the experiment correctly, as they failed to recognize that the Kozak sequence differs between yeast, where it is A-rich, and mammalian cells, where it is GGCGCC). Collisions could be another mechanism.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript focuses on an unexpected finding that a tiny change in a protein's aminoacid sequence can redefine its biological function. The authors' data and analyses explain how a chromodomain, typically implicated in interactions with histones, can also mediate binding of HP1 homolog Rhino to the non-histone partner protein Kipferl. They elegantly pinpoint the capacity for such interaction to a single aminoacid substitution (in fact, a single-nucleotide! substitution).
Strengths:
Both genetic and biochemical approaches are applied to rigorously probe the proposed explanation. The authors find their predictions to be borne out both in vivo, in mutant animals, and in biochemical experiments. The manuscript also features phylogenetic comparisons that put the finding into a broader evolutionary perspective.
Weaknesses pointed out in the original submission were addressed in the revised manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, Jellinger et al. performed engram-specific sequencing and identified genes that were selectively regulated in positive/negative engram populations. In addition, they performed chronic activation of the negative engram population over 3 months and observed several effects on fear/anxiety behavior and cellular events such as upregulation of glial cells and decreased GABA levels.
Strengths:
They provide useful engram-specific GSEA data and the main concept of the study, linking negative valence/memory encoding to cellular level outcomes including upregulation of glial cells, is interesting and valuable.
Comments on the revised manuscript:
The revised manuscript still does not adequately address the primary technical concern regarding long-term DREADD manipulation. The authors reference their previous work (Suthard et al., 2023) as evidence; however, this earlier paper only presents fluorescence intensity in a non-quantitative manner with merely three samples (Supplementary Figure 7). This limited evidence does not sufficiently support the claim of potent long-term activation. The discussion in the revision stating "...even if our manipulation is only working for 1 month, rather than 3 months..." is unconvincing, particularly given that the title and abstract still claims "chronic activation of...". To substantiate the technical validity of the study, at least cFos staining at various time points is necessary, which is less burdensome compared to more direct demonstrations such as slice physiology. Thus, although I believe it could be an interesting study for some audiences, I cannot support the strength of the evidence presented in the study.
Furthermore, in response to all reviewers' concerns regarding the quantification of GABA, the authors have removed the data from the study rather than providing properly acquired images or quantified data. This action diminishes the significance of the study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
In the manuscript the authors suggest a computational mechanism called recall-gated consolidation, which prioritizes the storage of previously experienced synaptic updates in memory. The authors investigate the mechanism with different types of learning problems including supervised learning, reinforcement learning, and unsupervised auto-associative memory. They rigorously analyse the general mechanism and provide valuable insights into its benefits.
Strengths:
The authors establish a general theoretical framework, which they translate into three concrete learning problems. For each, they define an individual mathematical formulation. Finally, they extensively analyse the suggested mechanism in terms of memory recall, consolidation dynamics, and learnable timescales.
The presented model of recall-gated consolidation covers various aspects of synaptic plasticity, memory recall, and the influence of gating functions on memory storage and retrieval. The model's predictions align with observed spaced learning effects.
The authors conduct simulations to validate the recall-gated consolidation model's predictions, and their simulated results align with theoretical predictions. These simulations demonstrate the model's advantages over consolidating any memory and showcase its potential application to various learning tasks.
The suggestion of a novel consolidation mechanism provides a good starting point to investigate memory consolidation in diverse neural systems and may inspire artificial learning algorithms.
Weaknesses:
I appreciate that the authors devoted a specific section to the model's predictions, and point out how the model connects to experimental findings in various model organisms. However, the connection is rather weak and the model needs to make more specific predictions to be distinguishable from other theories of memory consolidation (e.g. those that the authors discuss) and verifiable by experimental data.
The model is not compared to other consolidation models in terms of performance and how much it increases the signal-to-noise ratio. It is only compared to a simple STM or a parallel LTM, which I understand to be essentially the same as the STM but with a different timescale (so not really an alternative consolidation model). It would be nice to compare the model to an actual or more sophisticated existing consolidation model to allow for a fairer comparison.
The article is lengthy and dense and it could be clearer. Some sections are highly technical and may be challenging to follow. It could benefit from more concise summaries and visual aids to help convey key points.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The mechanisms of how axonal projections find their correct target requires the interplay of signalling pathways, and cell adhesion that act over short and long distances. The current study aims to use the small ventral lateral clock neurons (s-LNvs) of the Drosophila clock circuit as a model to study axon projections. These neurons are born during embryonic stages and are part of the core of the clock circuit in the larval brain. Moreover, these neurons are maintained through metamorphosis and become part of the adult clock circuit. The authors use the axon length by means of anti-Pdf antibody or Pdf>GFP as a read-out for the axonal length. Using ablation of the MB- the overall target region of the s-LNvs, the authors find defects in the projections. Next, by using Dscam mutants or knock-down they observe defects in the projections. Manipulations by the DNs - another group of clock neurons - can induce defects in the s-LNvs axonal form, suggesting an active role of these neurons in the morphology of the s-LNvs.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This manuscript puts forward the concept that there is a specific time window during which YAP/TAZ driven transcription provides feedback for optimal endothelial cell adhesion, cytoskeletal organization and migration. The study follows up on previous elegant findings from this group and others which established the importance of YAP/TAZ-mediated transcription for persistent endothelial cell migration. The data presented here extends the concept at two levels: first, the data may explain why there are differences between experimental setups where YAP/TAZ activity are inhibited for prolonged times (e.g. cultures of YAP knockdown cells), versus experiments in which the transient inhibition of YAP/TAZ and (global) transcription affects endothelial cell dynamics prior to their equilibrium.
All experiments are convincing, clearly visualized and quantified.
The strength of the paper is that it clearly indicates that there are temporal controlled feedback systems which which is important for endothelial collective cell behavior.
A limitation of the study is that the inhibitory studies in vivo may include off-target effects as well. Future endeavors, including specific knockout models, optogenetics and/or transgenic zebrafish lines that visualize endothelial cell properties (proliferation and migration) will be informative to track individual endothelial cell responses upon feedback signals.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this work the authors propose a new regulatory role for one of the most abundant circRNAs, circHIPK3. They demonstrate that circHIPK3 interacts with an RNA binding protein (IGF2BP2), sequestering it away from its target mRNAs. This interaction is shown to regulate the expression of hundreds of genes that share a specific sequence motif (11-mer motif) in their untranslated regions (3'-UTR), identical to one present in circHIPK3 where IGF2BP2 binds. The study further focuses on the specific case of STAT3 gene, whose mRNA product is found to be downregulated upon circHIPK3 depletion. This suggests that circHIPK3 sequesters IGF2BP2, preventing it from binding to and destabilizing STAT3 mRNA. The study presents evidence supporting this mechanism and discusses its potential role in tumor cell progression. These findings contribute to the growing complexity of understanding cancer regulation and highlight the intricate interplay between circRNAs and protein-coding genes in tumorigenesis.
Strengths:
The authors show mechanistic insight into a proposed novel "sponging" function of circHIPK3 which is not mediated by sequestering miRNAs but rather a specific RNA binding protein (IGF2BP2). They address the stoichiometry of the molecules involved in the interaction, which is a critical aspect that is frequently overlooked in this type of study. They provide both genome-wide analysis and a specific case (STAT3) which is relevant for cancer progression. Overall, the authors have significantly improved their manuscript in their revised version.
Weaknesses:
There are seemingly contradictory effects of circHIPK3 and STAT3 depletion in cancer progression. However, the authors have addressed these issues in their revised manuscript, incorporating potential reasons that might explain such complexity.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Plasticity in the basolateral amygdala (BLA) is thought to underlie the formation of associative memories between neutral and aversive stimuli, i.e. fear memory. Concomitantly, fear learning modifies the expression of BLA theta rhythms, which may be supported by local interneurons. Several of these interneuron subtypes, PV+, SOM+, and VIP+, have been implicated in the acquisition of fear memory. However, it was unclear how they might act synergistically to produce BLA rhythms that structure the spiking of principal neurons so as to promote plasticity. Cattani et al. explored this question using small network models of biophysically detailed interneurons and principal neurons.
Using this approach, the authors had four principal findings:<br /> (1) Intrinsic conductances in VIP+ interneurons generate a slow theta rhythm that periodically inhibits PV+ and SOM+ interneurons, while disinhibiting principal neurons.<br /> (2) A gamma rhythm arising from the interaction between PV+ and principal neurons establishes the precise timing needed for spike-timing-dependent plasticity.<br /> (3) Removal of any of the interneuron subtypes abolishes conditioning-related plasticity.<br /> (4) Learning-related changes in principal cell connectivity enhance the expression of slow theta in the local field potential.
The strength of this work is that it explores the role of multiple interneuron subtypes in the formation of associative plasticity in the basolateral amygdala. The authors use biophysically detailed cell models that capture many of their core electrophysiological features, which helps translate their results into concrete hypotheses that can be tested in vivo. Moreover, they try to align the connectivity and afferent drive of their model with those found experimentally. However, the weakness is that their attempt to align with the experimental literature (specifically Krabbe et al. 2019) is performed inconsistently. Some connections between cell types were excluded without adequate justification (e.g. SOM+ to PV+). In addition, the construction of the afferent drive to the network does not reflect the stimulus presentations that are given in fear conditioning tasks. For instance, the authors only used a single training trial, the conditioning stimulus was tonic instead of pulsed, the unconditioned stimulus duration was artificially extended in time, and its delivery overlapped with the neutral stimulus, instead of following its offset. These deviations undercut the applicability of their findings.
This study partly achieves its aim of understanding how networks of biophysically distinctive interneurons interact to generate nested rhythms that coordinate the spiking of principal neurons. What still remains to demonstrate is that this promotes plasticity for training protocols that emulate what is used in studies of fear conditioning.
Setting aside the issues with the conditioning protocol, the study offers a model for the generation of multiple rhythms in the BLA that is ripe for experimental testing. The most promising avenue would be in vivo experiments testing the role of local VIP+ neurons in the generation of slow theta. That would go a long way to resolving whether BLA theta is locally generated or inherited from medial prefrontal cortex or ventral hippocampus afferents.
The broader importance of this work is that it illustrates that we must examine the function of neurons not just in terms of their behavioral correlates, but by their effects on the microcircuit they are embedded within. No one cell type is instrumental in producing fear learning in the BLA. Each contributes to the orchestration of network activity to produce plasticity. Moreover, this study reinforces a growing literature highlighting the crucial role of theta and gamma rhythms in BLA function.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Plasticity in the basolateral amygdala (BLA) is thought to underlie the formation of associative memories between neutral and aversive stimuli, i.e. fear memory. Concomitantly, fear learning modifies the expression of BLA theta rhythms, which may be supported by local interneurons. Several of these interneuron subtypes, PV+, SOM+, and VIP+, have been implicated in the acquisition of fear memory. However, it was unclear how they might act synergistically to produce BLA rhythms that structure the spiking of principal neurons so as to promote plasticity. Cattani et al. explored this question using small network models of biophysically detailed interneurons and principal neurons.
Using this approach, the authors had four principal findings:
(1) Intrinsic conductances in VIP+ interneurons generate a slow theta rhythm that periodically inhibits PV+ and SOM+ interneurons, while disinhibiting principal neurons.<br /> (2) A gamma rhythm arising from the interaction between PV+ and principal neurons establishes the precise timing needed for spike-timing-dependent plasticity.<br /> (3) Removal of any of the interneuron subtypes abolishes conditioning-related plasticity.<br /> (4) Learning-related changes in principal cell connectivity enhance expression of slow theta in the local field potential.
The strength of this work is that it explores the role of multiple interneuron subtypes in the formation of associative plasticity in the basolateral amygdala. The authors use biophysically detailed cell models that capture many of their core electrophysiological features, which helps translate their results into concrete hypotheses that can be tested in vivo. Moreover, they try to align the connectivity and afferent drive of their model with those found experimentally.
Deficient in this study is the construction of the afferent drive to the network, which does elicit activities that are consistent with those observed to similar stimuli. It still remains to be demonstrated that their mechanism promotes plasticity for training protocols that emulate the kinds of activities observed in the BLA during fear conditioning.
Setting aside the issues with the conditioning protocol, the study offers a model for the generation of multiple rhythms in the BLA that is ripe for experimental testing. The most promising avenue would be in vivo experiments testing the role of local VIP+ neurons in the generation of slow theta. That would go a long way to resolving whether BLA theta is locally generated or inherited from medial prefrontal cortex or ventral hippocampus afferents.
The broader importance of this work is that it illustrates that we must examine the function of neurons not just in terms of their behavioral correlates, but by their effects on the microcircuit they are embedded within. No one cell type is instrumental in producing fear learning in the BLA. Each contributes to the orchestration of network activity to produce plasticity. Moreover, this study reinforces a growing literature highlighting the crucial role of theta and gamma rhythms in BLA function.
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- Jun 2024
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link.springer.com link.springer.com
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BRAIN Initiative Cell Census Network
DOI: 10.1007/s00418-023-02209-1
Resource: BICCN (RRID:SCR_015820)
Curator: @evieth
SciCrunch record: RRID:SCR_015820
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Tiemann et al. have undertaken an original study on the availability of molecular dynamics (MD) simulation datasets across the Internet. There is a widespread belief that extensive, well-curated MD datasets would enable the development of novel classes of AI models for structural biology. However, currently, there is no standard for sharing MD datasets. As generating MD datasets is energy-intensive, it is also important to facilitate the reuse of MD datasets to minimize energy consumption. Developing a universally accepted standard for depositing and curating MD datasets is a huge undertaking. The study by Tiemann et al. will be very valuable in informing policy developments toward this goal.
Strengths:
The study presents an original approach to addressing a growing concern in the field. It is clear that adopting a more collaborative approach could significantly enhance the impact of MD simulations in modern molecular sciences.
The timing of the work is appropriate, given the current interest in developing AI models for describing biomolecular dynamics.
Weaknesses:
The study primarily focuses on one major MD engine (GROMACS), although this limitation is not significant considering the proof-of-concept nature of the study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript proposes an alternative method by SDS-PAGE calibration of Halo-Myo10 signals to quantify myosin molecules at specific subcellular locations, in this specific case filopodia, in epifluorescence datasets compared to the more laborious and troublesome single molecule approaches. Based on these preliminary estimates, the authors developed further their analysis and discussed different scenarios regarding myosin 10 working models to explain intracellular diffusion and targeting to filopodia.
Strengths:
I confirm my previous assessment. Overall, the paper is elegantly written and the data analysis is appropriately presented. Moreover, the novel experimental approach offers advantages to labs with limited access to high-end microscopy setups (super-resolution and/or EM in particular), and the authors proved its applicability to both fixed and live samples.
Weaknesses:
Myself and the other two reviewers pointed to the same weakness, the use of protein overexpression in U2OS. The authors claim that Myosin10 is not expressed by U2OS, based on Western blot analysis. Does this completely rule out the possibility that what they observed (the polarity of filopodia and the bulge accumulation of Myo10) could be an artefact of overexpression? I am afraid this still remains the main weakness of the paper, despite being properly acknowledged in the Limitations.
I consider all the remaining issues I expressed during the first revision solved.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This study is convincing because they performed time-resolved X-ray crystallography under different pH conditions using active/inactive metal ions and PpoI mutants, as with the activity measurements in solution in conventional enzymatic studies. Although the reaction mechanism is simple and may be a little predictable, the strength of this study is that they were able to validate that PpoI catalyzes DNA hydrolysis through "a single divalent cation" because time-resolved X-ray study often observes transient metal ions which are important for catalysis but are not predictable in previous studies with static structures such as enzyme-substrate analog-metal ion complexes. The discussion of this study is well supported by their data. This study visualized the catalytic process and mutational effects on catalysis, providing new insight into the catalytic mechanism of I-PpoI through a single divalent cation. The authors found that His98, a candidate of proton acceptor in the previous experiments, also affects the Mg2+ binding for catalysis without the direct interaction between His98 and the Mg2+ ion, suggesting that "Without a proper proton acceptor, the metal ion may be prone for dissociation without the reaction proceeding, and thus stable Mg2+ binding was not observed in crystallo without His98". In future, this interesting feature observed in I-PpoI should be investigated by biochemical, structural, and computational analyses using other metal-ion dependent nucleases.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors follow up on their published observation that providing a lower glucose parental nutrition (PN) reduces sepsis from a common pathogen [Staphylococcus epidermitis (SE)] in preterm piglets. Here they found that a higher dose of glucose could thread the needle and get the protective effects of low glucose without incurring significant hypoglycemia. They then investigate whether the change in low glucose PN impacts metabolism to confer this benefit. The finding that lower glucose reduces sepsis is important as sepsis is a major cause of morbidity and mortality in preterm infants, and adjusting PN composition is a feasible intervention.
Strengths:
(1) They address a highly significant problem of neonatal sepsis in preterm infants using a preterm piglet model.
(2) They have compelling data in this paper (and in a previous publication, ref 27) that low glucose PN confers a survival advantage. A downside of the low glucose PN is hypoglycemia which they mitigate in this paper by using a slightly high amount of glucose in the PN.
(3) The experiment where they change PN from high to low glucose after infection is very important to determine if this approach might be used clinically. Unfortunately, this did not show an ability to reduce sepsis risk with this approach. Perhaps this is due to the much lower mortality in the high glucose group (~20% vs 87% in the first figure).
(4) They produce an impressive multiomics data set from this model of preterm piglet sepsis which is likely to provide additional insights into the pathogenesis of preterm neonatal sepsis.
Weaknesses:
(1) The high glucose control gives very high blood glucose levels (Figure 1C). Is this the best control for typical PN and glucose control in preterm neonates? Is the finding that low glucose is protective or high glucose is a risk factor for sepsis?
(2) In Figure 1B, preterm piglets provided the high glucose PN have 13% survival while preterm piglets on the same nutrition in Figure 6B have ~80% survival. Were the conditions indeed the same? If so, this indicates a large amount of variation in the outcome of this model from experiment to experiment.
(3) Piglets on the low glucose PN had consistently lower density of SE (~1 log) across all time points. This may be due to changes in immune response leading to better clearance or it could be due to slower growth in a lower glucose environment.
(4) Many differences in the different omics (transcriptomics, metabolomics, proteomics) were identified in the SE-LOW vs SE-HIGH comparison. Since the bacterial load is very different between these conditions, could the changes be due to bacterial load rather than metabolic reprogramming from the low glucose PN?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The current manuscript uses electron spin resonance spectroscopy to understand how the dynamic behavior and conformational heterogeneity of the LPS transport system change during substrate transport and in response to the membrane, bound nucleotide (or transition state analog), and accessory subunits. The study builds on prior structural studies to expand our molecular understanding of this highly significant bacterial transport system.
Strengths
This series of well-designed and well-executed experiments provides new mechanistic insights into the dynamic behavior of the LPS transport system. Notable new insights provided by this study include its indication of the spatial organization of the LptC domain, which was poorly resolved in structures, and how the LptC domain modulates the dynamic behavior of the gate through which lipids access the binding site. In addition, a mass spectrometry approach designed to examine LPS binding at different stages in the nucleotide-dependent conformational cycle provides insight into the order of operations of LPS binding and transport.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Schafer et al. tested whether the hippocampus tracks social interactions as sequences of neural states within an abstract social space defined by dimensions of affiliation and power, using a task in which participants engaged in narrative-based social interactions. The findings of this study revealed that individual social relationships are represented by unique sequences of hippocampal activity patterns. These neural trajectories corresponded to the history of trial-to-trial affiliation and power dynamics between participants and each character, suggesting an extended role of the hippocampus in encoding sequences of events beyond spatial relationships.
The current version has limited information on details in decoding and clustering analyses which can be improved in the future revision.
Strengths:
(1) Robust Analysis: The research combined representational similarity analysis with manifold analyses, enhancing the robustness of the findings and the interpretation of the hippocampus's role in social cognition.
(2) Replicability: The study included two independent samples, which strengthens the generalizability and reliability of the results.
Weaknesses:
I appreciate the authors for utilizing contemporary machine-learning techniques to analyze neuroimaging data and examine the intricacies of human cognition. However, the manuscript would benefit from a more detailed explanation of the rationale behind the selection of each method and a thorough description of the validation procedures. Such clarifications are essential to understand the true impact of the research. Moreover, refining these areas will broaden the manuscript's accessibility to a diverse audience.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
An online database called MRAD has been developed to identify the risk or protective factors for AD.
Strengths:
This study is a very intriguing study of great clinical and scientific significance that provided a thorough and comprehensive evaluation with regard to risk or protective factors for AD. It also provided physicians and scientists with a very convenient, free as well as user-friendly tool for further scientific investigation.
Weaknesses:
(1) The paper mentions that the MRAD database currently contains data only from European populations, with no mention of data from other populations or ethnicities. Given potential differences in Alzheimer's Disease (AD) across different populations, the limitations of the data should be emphasized in the discussion, along with plans to expand the database to include data from more racial and geographic regions.
(2) Sufficient information should be provided to clarify the data sources, sample selection, and quality control methods used in the MRAD database. Readers may expect more detailed information about the data to ensure data reliability, representativeness, and research applicability.
(3) While the authors mention that the MRAD database offers interactive visualization interfaces, the paper lacks detailed information on how to interpret and understand these visual results. Guidelines on effectively using these visualization tools to help researchers better comprehend the data are essential.
(4) In the conclusion section of the paper, it is advisable to explicitly emphasize the practical applications and potential clinical significance of the MRAD database. The paper should articulate how MRAD can contribute to the early identification, diagnosis, prevention, and treatment of AD and its potential societal and clinical value more clearly.
(5) Grammar and Spelling Errors: There are several spelling and grammar errors in the paper. Referring to a scientific editing service is recommended.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This study by Hallada et al. reported the detailed characterization of cis and trans-binding of JAM-C in mediating the developmental migration of CGNs, combining ex vivo cultures, time-lapse imaging, and mathematical analyses. Overall, the study was comprehensively carried out, and the conclusion is important in our understanding of the signaling mechanism of cerebellar development.
Weaknesses:
Several technical concerns need to be clarified.
(1) The efficiency of shRNA knockdown of endogenous JAM-C. The entire study was based on the assumption that the endogenous wild-type JAM-C was depleted to the extent that it would not influence the observed phenotypes. However, this point requires verification, particularly in the ex vivo cultures.
(2) The expression levels of mutant JAM-C proteins. It is unclear whether the exogenous expression of mutant JAM-C proteins would be comparable to that of the endogenous JAM-C. In addition, the levels of exogenously expressed JAM-C may likely alter over the time course of experiments, e.g., in some experiments over 48 hours.
(3) The resolution of imaging methods. Different imaging methods were utilized in the study, and it is essential to clearly state the resolution of each imaging dataset (e.g., 0.2 x 0.2 um per pixel). This information is crucial to assess the reliability of observed phenotypes, which in some cases were relatively unimpressive.
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