- Apr 2024
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
REV7 facilitates the recruitment of Shieldin complex and thereby inhibits end resection and controls DSB repair choice in metazoan cells. Puzzlingly, Shieldin is absent in many organisms and it is unknown if and how Rev7 regulates DSB repair in these cells. The authors surmised that yeast Rev7 physically interacts with Mre11/Rad50/Xrs2 (MRX), the short-range resection nuclease complex, and tested this premise using yeast two-hybrid (Y2H) and microscale thermophoresis (MST). The results convincingly showed that the individual subunits of MRX interact robustly with Rev7. AlphaFold Multimer modelling followed by Y2H confirmed that the carboxy-terminal 42 amino acid is essential for interaction with MR and G4 DNA binding by REV7. The mutant rev7 lacking the binding interface (Rev7-C1) to MR shows moderate inhibition to the nuclease and the ATPase activity of Mre11/Rad50 in biochemical assays. Deletion of REV7 also causes a mild reduction in NHEJ using both plasmid and chromosome-based assays and increases mitotic recombination between chromosomal ura3-01 and the plasmid ura3 allele interrupted by G4. The authors concluded that Rev7 facilitates NHEJ and antagonizes HR even in budding yeast, but it achieves this by blocking Mre11 nuclease and Rad50 ATPase.
Weaknesses:
There are many strengths to the studies and the broad types of well-established assays were used to deduce the conclusion. Nevertheless, I have several concerns about the validity of experimental settings due to the lack of several key controls essential to interpret the experimental results. The manuscript also needs a few additional functional assays to reach the accurate conclusions as proposed.
(1) AlphaFold model predicts that Mre11-Rev7 and Rad50-Rev7 binding interfaces overlap and Rev7 might bind only to Mre11 or Rad50 at a time. Interestingly, however, Rev7 appears dimerized (Figure 1). Since the MR complex also forms with 2M and 2R in the complex, it should still be possible if REV7 can interact with +-*both M and R in the MR complex. The author should perform MST using MR complex instead of individual MR components. The authors should also analyze if Rev7-C1 is indeed deficient in interaction with MR individually and with complex using MST assay.
(2) The nuclease and the ATPase assays require additional controls. Does Rev7 inhibit the other nuclease or ATPase non-specifically? Are these outcomes due to the non-specific or promiscuous activity of Rev7? In Figure 6, the effect of REV7 on the ATP binding of Rad50 could be hard to assess because the maximum Rad50 level (1 uM) was used in the experiments. The author should use the suboptimal level of Rad50 to check if REV7 still does not influence ATP binding by Rad50.
(3) The moderate deficiency in NHEJ using plasmid-based assay in REV7 deleted cells can be attributed to aberrant cell cycle or mating type in rev7 deleted cells. The authors should demonstrate that rev7 deleted cells retain largely normal cell cycle patterns and the mating type phenotypes. The author should also analyze the breakpoints in plasmid-based NHEJ assays in all mutants, especially from rev7 and rev7-C1 cells.
(4) It is puzzling why the authors did not analyze end resection defects in rev7 deleted cells after a DSB. The author should employ the widely used resection assay after a HO break in rev3, rev7, and mre11 rev7 cells as described previously.
(5) Is it possible that Rev7 also contributes to NHEJ as the part of TLS polymerase complex? Although NHEJ largely depends on Pol4, the authors should not rule out that the observed NHEJ defect in rev7 cells is due at least partially to its TLS defect. In fact, both rev3 or rev1 cells are partially defective in NHEJ (Figure 7). Rev7-C1 is less deficient in NHEJ than REV7 deletion. These results predict that rev7-C1 rev3 should be as defective as the rev7 deletion. Additionally, the authors should examine if Rev7-C1 might be deficient in TLS. In this regard, does rev7-C1 reduce TLS and TLS-dependent mutagenesis? Is it dominant? The authors should also check if Rev3 or Rev1 are stable in Rev7 deleted or rev7-C1 cells by immunoblot assays.
(6) Due to the G4 DNA and G4 binding activity of REV7, it is not clear which class of events the authors are measuring in plasmid-chromosome recombination assay in Figure 9. Do they measure G4 instability or the integrity of recombination or both in rev7 deleted cells? Instead, the effect of rev7 deletion or rev7-C1 on recombination should be measured directly by more standard mitotic recombination assays like mating type switch or his3 repeat recombination.
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www.medrxiv.org www.medrxiv.org
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Reviewer #3 (Public Review):
Summary:
The paper attempts to model the functional significance of variants of PLCG2 in a set of patients with variable clinical manifestations.
Strengths:
A study attempting to use the Drosophila system to test the function of variants reported from human patients.
Weaknesses:
Additional experiments are needed to shore up the claims in the paper. These are listed below.
Major Comments:
(1) Does the pLI/ missense constraint Z score prediction algorithm take into consideration whether the gene exhibits monoallelic or biallelic expression?
(2) Figure 1B: Include human PLCG2 in the alignment that displays the species-wide conserved variant residues.
(3) Figure 4A:<br /> Given that<br /> (i) sl is predicted to be the fly ortholog for both mammalian PLCγ isozymes: PLCG1 and PLCG2 [Line 62]<br /> (ii) they are shown to have non-redundant roles in mammals [Line 71] and<br /> (iii) reconstituting PLCG1 is highly toxic in flies, leading to increased lethality.<br /> This raises questions about whether sl mutant phenotypes are specifically caused by the absence of PLG1 or PLCG2 functions in flies. Can hPLCG2 reconstitution in sl mutants be used as a negative control to rule out the possibility of the same?
(4) Do slT2A/Y; UAS-PLCG1Reference flies survive when grown at 22{degree sign}C? Since transgenic fly expressing PLCG1 cDNA when driven under ubiquitous gal4s, Tubulin and Da, can result in viable progeny at 22{degree sign}C, the survival of slT2A/Y; UAS-PLCG1Reference should be possible.<br /> and similarly<br /> Does slT2A flies exhibit the phenotypes of (i) reduced eclosion rate (ii) reduced wing size and ectopic wing veins and (iii) extra R7 photoreceptor in the fly eye at 22{degree sign}C?<br /> If so, will it be possible to get a complete rescue of the slT2A mutant phenotypes with the hPLCG1 cDNA at 22{degree sign}C? This dataset is essential to establish Drosophila as an ideal model to study the PLCG1 de novo variants.
(5) Localisation and western blot assays to check if the introduction of the de novo mutations can have an impact on the sub-cellular targeting of the protein or protein stability respectively.
(6) Analysing the nature of the reported gain of function (experimental proof for the same is missing in the manuscript) variants:<br /> Instead of directly showing the effect of introducing the de novo variant transgenes in the Drosophila model especially when the full-length PLCG1 is not able to completely rescue the slT2A phenotype;<br /> (i) Show that the gain-of-function variants can have an impact on the protein function or signalling via one of the three signalling outputs in the mammalian cell culture system: (i) inositol-1,4,5-trisphosphate production, (ii) intracellular Ca2+ release or (iii) increased phosphorylation of extracellular signal-related kinase, p65, and p38.<br /> OR<br /> (ii) Run a molecular simulation to demonstrate how the protein's auto-inhibited state can be disrupted and basal lipase activity increased by introducing D1019G and D1165G, which destabilise the association between the C2 and cSH2 domains. The H380R variant may also exhibit characteristics similar to the previously documented H335A mutation which leaves the protein catalytically inactive as the residue is important to coordinate the incoming water molecule required for PIP2 hydrolysis.
(7) Clarify the reason for carrying out the wing-specific and eye-specific experiments using nub-gal4 and eyless-gal4 at 29˚C despite the high gal4 toxicity at this temperature.
(8) For the sake of completeness the authors should also report other variants identified in the genomes of these patients that could also contribute to the clinical features.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In this manuscript, Casas-Tintó et al. explore the role of glial cells in the response to a neurodegenerative injury in the adult brain. They used Drosophila melanogaster as a model organism and found that glial cells are able to generate new neurons through the mechanism of transdifferentiation in response to injury.
This paper provides a new mechanism in regeneration and gives an understanding of the role of glial cells in the process.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Based on their observation that tumor has an iron-deficient microenvironment, and the assumption that nutritional immunity is important in bacteria-mediated tumor modulation, the authors postulate that manipulation of iron homeostasis can affect tumor growth. This paper uses straightforward in vitro and in vivo techniques to examine a specific and important question of nutritional immunity in bacteria-mediated tumor therapy. They are successful in showing that manipulation of iron regulation during nutritional immunity does affect the virulence of the bacteria, and in turn the tumor. These findings open future avenues of investigation, including the use of different bacteria, different delivery systems for therapeutics, and different tumor types. The authors were also successful in addressing the reviewer's concerns adequately.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In the 'bCFS' paradigm, a monocular target gradually increases in contrast until it breaks interocular suppression by a rich monocular suppressor in the other eye. The present authors extend the bCFS paradigm by allowing the target to reduce back down in contrast until it becomes suppressed again. The main variable of interest is the contrast difference between breaking suppression and (re) entering suppression. The authors find this difference to be constant across a range of target types, even ones that differ substantially in the contrast at which they break interocular suppression (the variable conventionally measured in bCFS). They also measure how the difference changes as a function of other manipulations. Interpretation is in terms of the processing of unconscious visual content, as well as in terms of the mechanism of interocular suppression.
Strengths:
Interpretation of bCFS findings is mired in controversy, and this is an ingenuous effort to move beyond the paradigm's exclusive focus on breaking suppression. The notion of using the contrast difference between breaking and entering suppression as an index of suppression depth is interesting. The finding that this difference is similar for a range of target types that do differ in the contrast at which they break suppression, suggests a common mechanism of suppression across those target types.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors image dopamine axons in medial prefrontal cortex (mPFC) using microprism-mediated two-photon calcium imaging. They image these axons as mice learn that two auditory cues predict two distinct outcomes, tailshock, or water delivery. They find that some axons show a preference for encoding of the shock and some show a preference for encoding of water. The authors report a greater number of dopamine axons in mPFC that respond to shock. Across time, the shock-preferring axons begin to respond preferentially to the cue predicting shock, while there is a less pronounced increase in the water-responsive axons that acquire a response to the water-predictive cue (these axons also increase non-significantly to the shock-predictive cue). These data lead the authors to argue that dopamine axons in mPFC preferentially encode aversive stimuli.
Strengths:
The experiments are beautifully executed and the authors have mastered an impressively complex technique. Specifically, they are able to image and track individual dopamine axons in mPFC across days of learning. And this technique is used the way it should be: the authors isolate distinct dopamine axons in mPFC and characterize their encoding preferences and how this evolves across learning of cue-shock and cue-water contingencies. Thus, these experiments are revealing novel information about how aversive and rewarding stimuli is encoded at the level of individual axons, in a way that has not been done before. This is timely and important.
Weaknesses:
The overarching conclusion of the paper is that dopamine axons preferentially encode aversive stimuli. However, this is confounded by differences in the strength of the aversive and appetitive outcomes. As the authors point out, the axonal response to stimuli is sensitive to outcome magnitude (Supp Fig 3). That is, if you increase the magnitude of water or shock that is delivered, you increase the change in fluorescence that is seen in the axons. Unsurprisingly, the change in fluorescence that is seen to shock is considerably higher than water reward. Further, over 40% of the axons respond to water early in training [yet just a few lines below the authors write: "Previous studies have demonstrated that the overall dopamine release at the mPFC or the summed activity of mPFC dopamine axons exhibits a strong response to aversive stimuli (e.g., tail shock), but little to rewards", which seems inconsistent with their own data]. Given these aspects of the data, it could be the case that the dopamine axons in mPFC encodes different types of information and delegates preferential processing to the most salient outcome across time. The use of two similar sounding tones (9Khz and 12KHz) for the reward and aversive predicting cues are likely to enhance this as it requires a fine-grained distinction between the two cues in order to learn effectively. That is not to say that the mice cannot distinguish between these cues, rather that they may require additional processes to resolve the similarity, which are known to be dependent on the mPFC.
There is considerable literature on mPFC function across species that would support such a view. Specifically, theories of mPFC function (in particular prelimbic cortex, which is where the axon images are mostly taken) generally center around resolution of conflict in what to respond, learn about, and attend to. That is, mPFC is important for devoting the most resources (learning, behavior) to the most relevant outcomes in the environment. This data then, provides a mechanism for this to occur in mPFC. That is, dopamine axons signal to the mPFC the most salient aspects of the environment, which should be preferentially learnt about and responded towards. This is also consistent with the absence of a negative prediction error during omission: the dopamine axons show increases in responses during receipt of unexpected outcomes but do not encode negative errors. This supports a role for this projection in helping to allocate resources to the most salient outcomes and their predictors, and not learning per se. Below are a just few references from the rich literature on mPFC function (some consider rodent mPFC analogous to DLPFC, some mPFC), which advocate for a role in this region in allocating attention and cognitive resources to most relevant stimuli, and do not indicate preferential processing of aversive stimuli.
References:<br /> 1. Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual review of neuroscience, 24(1), 167-202.<br /> 2. Bissonette, G. B., Powell, E. M., & Roesch, M. R. (2013). Neural structures underlying set-shifting: roles of medial prefrontal cortex and anterior cingulate cortex. Behavioural brain research, 250, 91-101.<br /> 3. Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual review of neuroscience, 18(1), 193-222.<br /> 4. Sharpe, M. J., Stalnaker, T., Schuck, N. W., Killcross, S., Schoenbaum, G., & Niv, Y. (2019). An integrated model of action selection: distinct modes of cortical control of striatal decision making. Annual review of psychology, 70, 53-76.<br /> 5. Ridderinkhof, K. R., Ullsperger, M., Crone, E. A., & Nieuwenhuis, S. (2004). The role of the medial frontal cortex in cognitive control. science, 306(5695), 443-447.<br /> 6. Nee, D. E., Kastner, S., & Brown, J. W. (2011). Functional heterogeneity of conflict, error, task-switching, and unexpectedness effects within medial prefrontal cortex. Neuroimage, 54(1), 528-540.<br /> 7. Isoda, M., & Hikosaka, O. (2007). Switching from automatic to controlled action by monkey medial frontal cortex. Nature neuroscience, 10(2), 240-248.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors note that negative ruminations can lead to pathological brain states and mood/anxiety dysregulation. They test this idea by using mouse engram-tagging technology to label dentate gyrus ensembles activated during a negative experience (fear conditioning). They show that chronic chemogenetic activation of these ensembles leads to behavioral (increased anxiety, increased fear generalization, reduced fear extinction) and neural (increases in neuroinflammation, microglia, and astrocytes).
Strengths:
The question the authors ask here is an intriguing one, and the engram activation approach is a powerful way to address the question. Examination of a wide range of neural and behavioral dependent measures is also a strength.
Weaknesses:
The major weakness is that the authors have found a range of changes that are correlates of chronic negative engram reactivation. However, they do not manipulate these outcomes to test whether microglia, astrocytes, or neuroinflammation are causally linked to the dysregulated behaviors.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Here Li et al. examine pup-directed behavior in virgin Mandarin voles. Some males and females tend towards infanticide, others tend towards pup care. c-Fos staining showed more oxytocin cells activated in the paraventricular nucleus (PVN) of the hypothalamus in animals expressing pup care behaviors than in infanticidal animals. Optogenetic stimulation of PVN oxytocin neurons (with an oxytocin-specific virus to express the opsin transgene) increased pup-care, or in infanticidal voles increased latency towards approach and attack.
Suppressing the activity of PVN oxytocin neurons promoted infanticide. The use of a recent oxytocin GRAB sensor (OT1.0) showed changes in medial prefrontal cortex (mPFC) signals as measured with photometry in both sexes. Activating mPFC oxytocin projections increased latency to approach and attack in infanticidal females and males (similar to the effects of peripheral oxytocin injections), whereas in pup-caring animals only males showed a decrease in approach. Inhibiting these projections increased infanticidal behaviors in both females and males and had no effect on pup caretaking.
Strengths:
Adopting these methods for Mandarin voles is an impressive accomplishment, especially the valuable data provided by the oxytocin GRAB sensor. This is a major achievement and helps promote systems neuroscience in voles.
Weaknesses:
The study would be strengthened by an initial figure summarizing the behavioral phenotypes of voles expressing pup care vs infanticide: the percentages and behavioral scores of individual male and female nulliparous animals for the behaviors examined here. Do the authors have data about the housing or life history/experiences of these animals? How bimodal and robust are these behavioral tendencies in the population?
Optogenetics with the oxytocin promoter virus is a nice advance here. More details about their preparation and methods should be in the main text, and not simply relegated to the methods section. For optogenetic stimulation in Figure 2, how were the stimulation parameters chosen? There is a worry that oxytocin neurons can co-release other factors- are the authors sure that oxytocin is being released by optogenetic stimulation as opposed to other transmitters or peptides, and acting through the oxytocin receptor (as opposed to a vasopressin receptor)?
Given that they are studying changes in latency to approach/attack, having some controls for motion when oxytocin neurons are activated or suppressed might be nice. Oxytocin is reported to be an anxiolytic and a sedative at high levels.
The OT1.0 sensor is also amazing, these data are quite remarkable. However, photometry is known to be susceptive to motion artifacts and I didn't see much in the methods about controls or correction for this. It's also surprising to see such dramatic, sudden, and large-scale suppression of oxytocin signaling in the mPFC in the infanticidal animals - does this mean there is a substantial tonic level of oxytocin release in the cortex under baseline conditions?
Figure 5 is difficult to parse as-is, and relates to an important consideration for this study: how extensive is the oxytocin neuron projection from PVN to mPFC?
In Figures 6 and 7, the authors use the phrase 'projection terminals'; however, to my knowledge, there have not been terminals (i.e., presynaptic formations opposed to a target postsynaptic site) observed in oxytocin neuron projections into target central regions.
Projection-based inhibition as in Figure 7 remains a controversial issue, as it is unclear if the opsin activation can be fast enough to reduce the fast axonal/terminal action potential. Do the authors have confirmation that this works, perhaps with the oxytocin GRAB OT sensor?
As females and males had similar GRAB OT1.0 responses in mPFC, why would the behavioral effects of increasing activity be different between the sexes?
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Reviewer #3 (Public Review):
The authors delved into an important aspect of abortifacient diseases of livestock in Tanzania. The thoughts of the authors on the topic and its significance are implied, and the methodological approach needs further clarity. The number of wards in the study area, statistical selection of wards, type of questionnaire ie open or close-ended. Statistical analyses of outcomes were not clearly elucidated in the manuscript. Fifteen wards were mentioned in the text but 13 used what were the exclusion criteria. Observations were from pastoral, agropastoral, and smallholder agroecological farmers. No sample numbers or questionnaires were attributed to the above farming systems to correlate findings with management systems. The impacts of the research investigation output are not clearly visible as to warrant intervention methods. What were the identified pathogens from laboratory investigation, particularly with the use of culture and PCR not even mentioning the zoonotic pathogens encountered if any? The public health importance of any of the abortifacient agents was not highlighted.
In conclusion, based on the intent of the authors and the content of this research, and the weight of the research topic, there are obvious weaknesses in the critical data analysis to demonstrate cause, effect, and impact.
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Reviewer #3 (Public Review):
A classic method to detect recessive disease variants is homozygosity mapping, where affected individuals in a pedigree are scanned for the presence of runs of homozygosity (ROH) intersecting in a given region. The method could in theory be extended to biobanks with large samples of unrelated individuals; however, no efficient method was available (to the best of my knowledge) for detecting overlapping clusters of ROH in such large samples. In this paper, the authors developed such a method based on the PBWT data structure. They applied the method to the UK biobank, finding a number of associations, some of them not discovered in single SNP associations.
Major strengths:<br /> • The method is innovative and algorithmically elegant and interesting. It achieves its purpose of efficiently and accurately detecting ROH clusters overlapping in a given region. It is therefore a major methodological advance.<br /> • The method could be very useful for many other researchers interested in detecting recessive variants associated with any phenotype.<br /> • The statistical analysis of the UK biobank data is solid and the results that were highlighted are interesting and supported by the data.
Major weaknesses:<br /> • The positions and IDs of the ROH clusters in the UK biobank are not available for other researchers. This means that other researchers will not be able to follow up on the results of the present paper.<br /> • The vast majority of the discoveries were in regions already known to be associated with their respective phenotypes based on standard GWAS.<br /> • The running time seems rather long (at least for the UK biobank), and therefore it will be difficult for other researchers to extensively experiment with the method in very large datasets. That being said, the method has a linear running time, so it is already faster than a naïve algorithm.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this article, the authors provide an inventory of the 5' spliced leader sequences, cap structures, and eIF4E isoforms present in the model dinoflagellate species A. carterae. They provide evidence that the 5' cap structure is m7G, as it is in most characterized eukaryotes that do not employ trans-splicing for mRNA maturation, and that there are additional methylated nucleotides throughout the spliced leader RNAs. They then show that of the 8 different eIF4E species in A. carterae, only a subset of eIF4E1 and eIF4E2 proteins are detected and that the levels change according to time of day. Interestingly, while the eIF4E1 proteins bind a canonical cap nucleotide and are able to complement eIF4E-deficiency in yeast, an eIF4E2 paralog does not bind the traditional cap.
Strengths:
A strength of the article is that the authors have clearly presented the findings and by straying away from traditional model organisms, they have highlighted unique and interesting features of an understudied system for translational control. They provide complementary evidence for most findings using multiple techniques. E.g. the evidence that eIF4E1A binds m7GTP is supported by both pulldowns using m7GTP sepharose as well as SPR experiments to directly monitor binding of recombinant protein with affinity measurements. The methods are extremely detailed noting cell numbers, volumes, concentrations, etc. used in the experiments to be easily replicated.
Weaknesses:
While not necessary to support the author's conclusions, the significance of the work would be further enhanced by additional experiments to gain insights into mechanisms for translational control and to link specific SLs to organismal functions or mechanisms of mRNA recruitment.
-Monitoring diel expression of SLs and direct sequencing of mature mRNA would yield insights into whether there is regulated expression of RNAs with different SLs or the SLs themselves. This would also allow the authors to perform gene ontology to link SL expression at different points in the diel cycle to related functions, e.g. photosynthesis.
-In addition, the work would be strengthened by polysome sequencing or ribosome profiling as a function of the diel cycle, with analyses of when various spliced leader sequences are recruited to ribosomes in parallel with western blotting of polysome fractions to determine when various eIF4E isoforms are present on polysomes. This is a substantial expansion though from what the authors focused on in this manuscript, and not having these experiments does not undermine the findings presented. Alternatively, they could attempt to make bioinformatic comparisons with existing ribosome profiling datasets from a related dinoflagellate, Lingulodinium polyedrum, discussed briefly, if there were sufficient overlap between SL RNAs in these organisms.
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Reviewer #3 (Public Review):
Summary:
Lichtinger et al. have used an extensive set of molecular dynamics (MD) simulations to study the conformational dynamics and transport cycle of an important member of the proton-coupled oligopeptide transporters (POTs), namely SLC15A2 or PepT2. This protein is one of the most well-studied mammalian POT transporters that provides a good model with enough insight and structural information to be studied computationally using advanced enhanced sampling methods employed in this work. The authors have used microsecond-level MD simulations, constant-PH MD, and alchemical binding free energy calculations along with cell-based transport assay measurements; however, the most important part of this work is the use of enhanced sampling techniques to study the conformational dynamics of PepT2 under different conditions.
The study attempts to identify links between conformational dynamics and chemical events such as proton binding, ligand-protein interactions, and intramolecular interactions. The ultimate goal is of course to understand the proton-coupled peptide and drug transport by PepT2 and homologous transporters in the solute carrier family.
Some of the key results include<br /> (1) Protonation of H87 and D342 initiate the occluded (Occ) to the outward-facing (OF) state transition.
(2) In the OF state, through engaging R57, substrate entry increases the pKa value of E56 and thermodynamically facilitates the movement of protons further down.
(3) E622 is not only essential for peptide recognition but also its protonation facilitates substrate release and contributes to the intracellular gate opening. In addition, cell-based transport assays show that mutation of residues such as H87 and D342 significantly decreases transport activity as expected from simulations.
Strengths:
(1) This is an extensive MD-based study of PepT2, which is beyond the typical MD studies both in terms of the sheer volume of simulations as well as the advanced methodology used. The authors have not limited themselves to one approach and have appropriately combined equilibrium MD with alchemical free energy calculations, constant-pH MD, and geometry-based free energy calculations. Each of these 4 methods provides a unique insight regarding the transport mechanism of PepT2.
(2) The authors have not limited themselves to computational work and have performed experiments as well. The cell-based transport assays clearly establish the importance of the residues that have been identified as significant contributors to the transport mechanism using simulations.
(3) The conclusions made based on the simulations are mostly convincing and provide useful information regarding the proton pathway and the role of important residues in proton binding, protein-ligand interaction, and conformational changes.
Weaknesses:
(1) Some of the statements made in the manuscript are not convincing and do not abide by the standards that are mostly followed in the manuscript. For instance, on page 4, it is stated that "the K64-D317 interaction is formed in only ≈ 70% of MD frames and therefore is unlikely to contribute much to extracellular gate stability." I do not agree that 70% is negligible. Particularly, Figure S3 does not include the time series so it is not clear whether the 30% of the time where the salt bridge is broken is in the beginning or the end of simulations. For instance, it is likely that the salt bridge is not initially present and then it forms very strongly. Of course, this is just one possible scenario but the point is that Figure S3 does not rule out the possibility of a significant role for the K64-D317 salt bridge.
(2) Similarly, on page 4, it is stated that "whether by protonation or mutation - the extracellular gate only opens spontaneously when both the H87 interaction network and D342-R206 are perturbed (Figure S5)." I do not agree with this assessment. The authors need to be aware of the limitations of this approach. Consider "WT H87-prot" and "D342A H87-prot": when D342 residue is mutated, in one out of 3 simulations, we see the opening of the gate within 1 us. When D342 residue is not mutated we do not see the opening in any of the 3 simulations within 1 us. It is quite likely that if rather than 3 we have 10 simulations or rather than 1 us we have 10 us simulations, the 0/3 to 1/3 changes significantly. I do not find this argument and conclusion compelling at all.
(3) While the MEMENTO methodology is novel and interesting, the method is presented as flawless in the manuscript, which is not true at all. It is stated on Page 5 with regards to the path generated by MEMENTO that "These paths are then by definition non-hysteretic." I think this is too big of a claim to say the paths generated by MEMENTO are non-hysteretic by definition. This claim is not even mentioned in the original MEMENTO paper. What is mentioned is that linear interpolation generates a hysteresis-free path by definition. There are two important problems here: (a) MEMENTO uses the linear interpolation as an initial step but modifies the intermediates significantly later so they are no longer linearly interpolated structures and thus the path is no longer hysteresis-free; (b) a more serious problem is the attribution of by-definition hysteresis-free features to the linearly interpolated states. This is based on conflating the hysteresis-free and unique concepts. The hysteresis in MD-based enhanced sampling is related to the presence of barriers in orthogonal space. For instance, one may use a non-linear interpolation of any type and get a unique pathway, which could be substantially different from the one coming from the linear interpolation. None of these paths will be hysteresis-free necessarily once subjected to MD-based enhanced sampling techniques.
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Reviewer #3 (Public Review):
Summary:
The authors were trying to elucidate the role of USP8 in the endocytic pathway. Using C. elegans epithelial cells as a model, they observed that when USP8 function is lost, the cells have a decreased number and size in lysosomes. Since USP8 was already known to be a protein linked to ESCRT components, they looked into what role USP8 might play in connecting lysosomes and multivesicular bodies (MVB). They observed fewer ESCRT-associated vesicles but an increased number of "abnormal" enlarged vesicles when USP8 function was lost. At this specific point, it's not clear what the objective of the authors was. What would have been their hypothesis addressing whether the reduced lysosomal structures in USP8 (-) animals were linked to MVB formation? Then they observed that the abnormally enlarged vesicles, marked by the PI3P biosensor YFP-2xFYVE, are bigger but in the same number in USP8 (-) compared to wild-type animals, suggesting homotypic fusion. They confirmed this result by knocking down USP8 in a human cell line, and they observed enlarged vesicles marked by YFP-2xFYVE as well. At this point, there is quite an important issue. The use of YFP-2xFYVE to detect early endosomes requires the transfection of the cells, which has already been demonstrated to produce differences in the distribution, number, and size of PI3P-positive vesicles (doi.org/10.1080/15548627.2017.1341465). The enlarged vesicles marked by YFP-2xFYVE would not necessarily be due to the loss of UPS8. In any case, it appears relatively clear that USP8 localizes to early endosomes, and the authors claim that this localization is mediated by Rabex-5 (or Rabx-5). They finally propose that USP8 dissociates Rabx-5 from early endosomes facilitating endosome maturation.
Weaknesses:
The weaknesses of this study are, on one side, that the results are almost exclusively dependent on the overexpression of fusion proteins. While useful in the field, this strategy does not represent the optimal way to dissect a cell biology issue. On the other side, the way the authors construct the rationale for each approximation is somehow difficult to follow. Finally, the use of two models, C. elegans and a mammalian cell line, which would strengthen the observations, contributes to the difficulty in reading the manuscript.
The findings are useful but do not clearly support the idea that USP8 mediates Rab5-Rab7 exchange and endosome maturation, In contrast, they appear to be incomplete and open new questions regarding the complexity of this process and the precise role of USP8 within it.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Loss of cell attachment to extracellular matrix (ECM) triggers aniokis (a type of programmed cell death), and resistance to aniokis plays a role in cancer development. However, mechanisms underlying anoikis resistance, and the precise role of F-actin, are not fully known.
Here the authors describe the formation of a new organelle, giant unilocular vacuole (GUVac), in cells whose F-actin is disrupted during loss of matrix attachment. GUVac formation (diameter >500 nm) resulted from a previously unrecognised macropinocytosis-like process, characterized by inwardly curved micron-sized plasma membrane invaginations, dependent on F-actin depolymerization, septin recruitment, and PI(3)P. Finally, the authors show GUVac formation after loss of matrix attachment promotes resistance to anoikis.
From these results, the authors conclude that GUVac formation promotes cell survival in environments where F-actin is disrupted and conditions of cell stress.
Strengths:
The manuscript is clear and well-written, figures are all presented at a very high level.
A variety of cutting-edge cell biology techniques (eg time-lapse imaging, EM, super-resolution microscopy) are used to study the role of the cytoskeleton in GUVac formation. It is discovered that: (i) a macropinocytosis-like process dependent on F-actin depolymerisation, SEPT6 recruitment, and PI(3)P contributes to GUVac formation, and (ii) GUVac formation is associated with resistance to cell death.
Weaknesses:
The manuscript is highly reliant on the use of drugs, or combinations of drugs, for long periods of time (6hr, 18hr..). Wherever possible the authors should test conclusions drawn from experiments involving drugs also using other canonical cell biology approaches (eg siRNA, Crispr). Although suggestive as a first approach, it is not reliable to draw conclusions from experiments where only drug combinations are being advanced (eg LatB + FCF).
F-actin is well known to play a wide variety of roles in cell death and other canonical cell death pathways (PMID: 26292640). The authors show using pharmacological inhibition that F-actin is key for GUVac formation. However, especially when testing for physiological relevance, how can these other roles for F-actin be ruled out?
To test the role of septins in GUVac formation only recruitment studies and no direct functional work is performed. A drug forchlofeneuron (FCF) is used, but this is well known to have off-target effects (PMID: 27473917).
Cells that possess GUVac are resistant to aniokis, but how are these cells resistant? This report is focused on mechanisms underlying GUVac formation and does not directly test for mechanisms underlying aniokis resistance.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The mechanism underlying the well-documented CO2-regulated activity of connexin 26 (Cx26) remains poorly understood. This is largely due to the labile nature of CO2-mediated carbamylation, making it challenging to visualize the effects of this reversible posttranslational modification. This paper by Brotherton et al. aims to address this gap by providing structural insights through cryo-EM structures of a carbamylation-mimetic mutant of the gap junction protein.
Strength:
The combination of the mutation, elevated PCO2, and the use of LMNG detergent resulted in high-resolution maps that revealed, for the first time, the structure of the cytoplasmic loop between transmembrane helix (TM) 2 and 3.
Weaknesses:
While the structure of the TM2-TM3 loop may suggest a mechanism for stabilizing the closed conformation, the EM density is not strong enough to support direct interaction with carbamylated or mutated K125.
Overall, the cryo-EM structures presented in this study support their proposing mechanism in which carbamylation at K125 promotes Cx26 gap junction closure. Through careful control of the pH and PCO2 for each cryo-EM sample, the current study substantiated that the more closed conformation observed in high PCO2 is independent of pH but likely triggered by carbamylation. This was unclear from their prior cryo-EM map of wildtype Cx26 at high PCO2.
While the new structures successfully visualize the TM2-TM3 loop, which likely plays significant roles in CO2-regulated Cx26 activity, further studies are necessary to understand the underlying mechanism. For instance, the current study lacks explanation regarding what propels the movement of the N-terminal helix, how carbamylated K125 interacts with the TM2-TM3 loop, the importance of the lipids visualized in the map, or the reason why gap junctions are constitutively open while hemichannels are closed under normal PCO2 levels
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Granule cells' axons bifurcate to form parallel fibers (PFs) and ascending axons (AAs). While the significance of PFs on cerebellar plasticity is widely acknowledged, the importance of AAs remains unclear. In the current paper, Conti and Auger conducted electrophysiological experiments in rat cerebellar slices and identified a new form of synaptic plasticity in the AA-Purkinje cell (PC) synapses. Upon simultaneous stimulation of AAs and PFs, AA-PC EPSCs increased, while PFs-EPSCs decreased. This suggests that synaptic responses to AAs and PFs in PCs are jointly regulated, working as an additional mechanism to integrate motor/sensory input. This finding may offer new perspectives in studying and modeling cerebellum-dependent behavior. Overall, the experiments are performed well. However, there are two weaknesses. First, the baseline of electrophysiological recordings is influenced significantly by run-down, making it difficult to interpret the data quantitatively. The amplitude of AA-EPSCs is relatively small and the run-down may mask the change. The authors should carefully reexamine the data with appropriate controls and statistics. Second, while the authors show AA-LTP depends on mGluR, NMDA receptors, and GABA-A receptors, which cell types express these receptors and how they contribute to plasticity is not clarified. The recommended experiments may help to improve the quality of the manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary
The L114P gain of function mutation in the K2P channel TALK-1 encoded by KCNJ16 has been associated with maturity-onset diabetes of the young (MODY). In this study, Nakhe et al. generated mice carrying L114P TALK-1 and evaluated the impact of the mutation on pancreatic islet functions and glucose homeostasis. The authors report that the mutation increases neonatal lethality, owing to hyperglycemia caused by a lack of glucose-stimulated Ca2+ influx and insulin secretion. Adult mutant mice showed glucose intolerance and fasting hyperglycemia, which is attributed to blunted glucose-stimulated insulin secretion as well as increased glucagon secretion. Interestingly, male mice were more affected than female mice. Islets from adult mutant mice were found to have reduced Ca2+ entry upon glucose stimulation but also enhanced IP3-induced ER Ca2+ release, consistent with previous studies from the group showing a role of TALK-1 in ER Ca2+ homeostasis. Finally, comparison of bulk RNA sequencing results from WT and mutant islets revealed altered expression of genes involved in β-cell identify, function and signaling, which also contributes to the observed islet dysfunction.
Strengths
This is a well-executed and rigorous study that will be of great interest to the diabetes and islet biology communities. The findings provide convincing evidence supporting a causal role of the L114P gain of function TALK-1 mutation in glucose-stimulated insulin secretion defects and diabetes. The neonatal diabetes phenotype and the gender difference uncovered by the study have important clinical implications. The complexity of TALK-1 expression and hormone secretion in different endocrine cell types and how it impacts glucose homeostasis is elegantly illustrated in the L114P TALK-1 mouse model. The authors carefully and thoroughly addressed limitations of their study and discussed future directions. The importance of TALK-1 in β-cell and islet function demonstrated by this study will prompt future efforts targeting this important channel for diabetes treatment.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript reports the discovery of new compounds that selectively inhibit SMARCA4/SMARCA2 ATPase activity that work through a different mode as previously developed SMARCA4/SMARCA2 inhibitors. They also demonstrate the anti-tumor effects of the compounds on uveal melanoma cell proliferation and tumor growth. The findings indicate that the drugs exert their effects by altering chromatin accessibility at binding sites for lineage-specific transcription factors within gene enhancer regions. In uveal melanoma, altered expression of the transcription factor, SOX10, and SOX10 target gene underlies the anti-proliferative effects of the compounds. This study is significant because the discovery of new SMARCA4/SMARCA2 inhibitory compounds that can abrogate uveal melanoma tumorigenicity has therapeutic value. In addition, the findings provide evidence for the therapeutic use of these compounds in other transcription factor-dependent cancers.
Strengths:
The strengths of this manuscript include biochemical evidence that the new compounds are selective for SMARCA4/SMARCA2 over other ATPases and that the mode of action is distinct from a previously developed compound, BRM014, which binds the RecA lobe of SMARCA2. There is also strong evidence that FHT1015 suppresses uveal melanoma proliferation by inducing apoptosis. The in vivo suppression of tumor growth without toxicity validates the potential therapeutic utility of one of the new drugs. The conclusion that FHT1015 primarily inhibits SMARCA4 activity and thereby suppresses chromatin accessibility at lineage-specific enhancers is substantiated by ATAC-seq and ChIP-seq studies.
Weaknesses:
The weaknesses include a lack of more precise information on which SMARCA4/SMARCA2 residues the drugs bind. Although the I1173M/I1143M mutations are evidence that the critical residues for binding reside outside the RecA lobe, this site is conserved in CHD4, which is not affected by the compounds. Hence, this site may be necessary but not sufficient for drug binding or specifying selectivity. A more precise evaluation of the region specifying the effect of the new compounds would strengthen the evidence that they work through a novel mode and that they are selective. Another concern is that the mechanisms by which FHT1015 promotes apoptosis rather than simply cell cycle arrest are not clear. Does SOX10 or another lineage-specific transcription factor underlie the apoptotic effects of the compounds?
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This study presents a new approach of combining two measurements (pHLA binding and pHLA-TCR binding) in order to refine predictions of which patient mutations are likely presented to and recognized by the immune system. Improving such predictions would play an important role in making personalized anti-cancer vaccinations more effective.
Strengths:
The study combines data from pre-existing tools pVACseq and pMTNet and applies them to a CRC patient population, which the authors show may improve the chance of identifying immunogenic, cancer-derived neoepitopes. Making the datasets collected publicly available would expand beyond the current datasets that typically describe caucasian patients.
Weaknesses:
It is unclear whether the pNetMHCpan and pMTNet tools used by the authors are entirely independent, as they appear to have been trained on overlapping datasets, which may explain their similar scores. The pHLA-TCR score seems to be driving the effects, but this not discussed in detail.
Due to sample constraints, the authors were only able to do a limited amount of experimental validation to support their model; this raises questions as to how generalisable the presented results are. It would be desirable to use statistical thresholds to justify cutoffs in ELISPOT data.
Some of the TCR repertoire metrics presented in Figure 2 are incorrectly described as independent variables and do not meaningfully contribute to the paper. The TCR repertoires may have benefitted from deeper sequencing coverage, as many TCRs appear to be supported only by a single read.
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Reviewer #3 (Public Review):
The mechanical properties of DNA wrapped in nucleosomes affect the stability of nucleosomes and may play a role in the regulation of DNA accessibility in eukaryotes. In this manuscript, Ngo and coworkers study how the stability of a nucleosome is affected by the introduction of a CC mismatched base pair, which has been reported to increase the flexibility of DNA. Previously, the group has used a sophisticated combination of single-molecule FRET and force spectroscopy with an optical trap to show that the more flexible half of a 601 DNA segment provides for more stable wrapping as compared to the other half. Here, it is confirmed with a single-molecule cyclization essay that the introduction of a CC mismatch increases the flexibility of a DNA fragment. Consistent with the previous interpretation, it also increased the unwrapping force for the half of the 601 segment in which the CC mismatch was introduced, as measured with single-molecule FRET and force spectroscopy. Enhanced stability was found up to 56 bp into the nucleosome. The intricate role of mechanical stability of nucleosomes was further investigated by comparing force-induced unwrapping profiles of yeast and Xenopus histones. Intriguingly, asymmetric unwrapping was more pronounced for yeast histones.
Note from Reviewing Editor:
The authors addressed the points in the reviews by making appropriate text additions and clarifications.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Asabuki and Clopath study stochastic sequence learning in recurrent networks of Poisson spiking neurons that obey Dale's law. Inspired by previous modeling studies, they introduce two distinct learning rules, to adapt excitatory-to-excitatory and inhibitory-to-excitatory synaptic connections. Through a series of computer experiments, the authors demonstrate that their networks can learn to generate stochastic sequential patterns, where states correspond to non-overlapping sets of neurons (cell assemblies) and the state-transition conditional probabilities are first-order Markov, i.e., the transition to a given next state only depends on the current state. Finally, the authors use their model to reproduce certain experimental songbird data involving highly-predictable and highly-uncertain transitions between song syllables.
Strengths:
This is an easy-to-follow, well-written paper, whose results are likely easy to reproduce. The experiments are clear and well-explained. The study of songbird experimental data is a good feature of this paper; finches are classical model animals for understanding sequence learning in the brain. I also liked the study of rapid task-switching, it's a good-to-know type of result that is not very common in sequence learning papers.
Weaknesses:
While the general subject of this paper is very interesting, I missed a clear main result. The paper focuses on a simple family of sequence learning problems that are well-understood, namely first-order Markov sequences and fully visible (no-hidden-neuron) networks, studied extensively in prior work, including with spiking neurons. Thus, because the main results can be roughly summarized as examples of success, it is not entirely clear what the main point of the authors is.
Going into more detail, the first major weakness I see in this paper is the heuristic choice of learning rules. The paper studies Poisson spiking neurons (I return to this point below), for which learning rules can be derived from a statistical objective, typically maximum likelihood. For fully-visible networks, these rules take a simple form, similar in many ways to the E-to-E rule introduced by the authors. This more principled route provides quite a lot of additional understanding on what is to be expected from the learning process. For instance, should maximum likelihood learning succeed, it is not surprising that the statistics of the training sequence distribution are reproduced. Moreover, given that the networks are fully visible, I think that the maximum likelihood objective is a convex function of the weights, which then gives hope that the learning rule does succeed. And so on. This sort of learning rule has been studied in a series of papers by David Barber and colleagues [refs. 1, 2 below], who applied them to essentially the same problem of reproducing sequence statistics in recurrent fully-visible nets. It seems to me that one key difference is that the authors consider separate E and I populations, and find the need to introduce a balancing I-to-E learning rule.
Because the rules here are heuristic, a number of questions come to mind. Why these rules and not others - especially, as the authors do not discuss in detail how they could be implemented through biophysical mechanisms? When does learning succeed or fail? What is the main point being conveyed, and what is the contribution on top of the work of e.g. Barber, Brea, et al. (2013), or Pfister et al. (2004)?
The use of a Poisson spiking neuron model is the second major weakness of the study. A chief challenge in much of the cited work is to generate stochastic transitions from recurrent networks of deterministic neurons. The task the authors set out to do is much easier with stochastic neurons; it is reasonable that the network succeeds in reproducing Markovian sequences, given an appropriate learning rule. I believe that the main point comes from mapping abstract Markov states to assemblies of neurons. If I am right, I missed more analyses on this point, for instance on the impact that varying cell assembly size would have on the findings reported by the authors.
Finally, it was not entirely clear to me what the main fundamental point in the HVC data section was. Can the findings be roughly explained as follows: if we map syllables to cell assemblies, for high-uncertainty syllable-to-syllable transitions, it becomes harder to predict future neural activity? In other words, is the main point that the HVC encodes syllables by cell assemblies?
(1) Learning in Spiking Neural Assemblies, David Barber, 2002. URL: https://proceedings.neurips.cc/paper/2002/file/619205da514e83f869515c782a328d3c-Paper.pdf
(2) Correlated sequence learning in a network of spiking neurons usingmaximum likelihood, David Barber, Felix Agakov, 2002. URL: http://web4.cs.ucl.ac.uk/staff/D.Barber/publications/barber-agakov-TR0149.pdf
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this paper, the authors sought to evaluate whether the novel TB drug candidate, spectinamide 1599 (S), given via inhalation to mouse TB models, and combined with the drugs B (bedaquiline) and Pa (pretomanid), would demonstrate similar efficacy to that of BPaL regimen (where L is linezolid). Because L is associated with adverse events when given to patients long-term, and one of those is associated with myelosuppression (bone marrow toxicity) the authors also sought to assess blood parameters, effects on bone marrow, immune parameters/cell effects following treatment of mice with BPaS and BPaL. They conclude that BPaL and BPaS have equivalent efficacy in both TB models used and that BPaL resulted in weight loss and anemia (whereas BPaL did not) under the conditions tested, as well as effects on bone marrow.
Strengths:
The authors used two mouse models of TB that are representative of different aspects of TB in patients (which they describe well), intending to present a fuller picture of the activity of the tested drug combinations. They conducted a large body of work in these infected mice to evaluate efficacy and also to survey a wide range of parameters that could inform the effect of the treatments on bone marrow and on the immune system. The inclusion of BPa controls (in most studies) and also untreated groups led to a large amount of useful data that has been collected for the mouse models per se (untreated) as well as for BPa - in addition to the BPaS and BPaL combinations which are of particular interest to the authors. Many of these findings related to BPa, BPaL, untreated groups, etc corroborate earlier findings and the authors point this out effectively and clearly in their manuscript. To go further, in general, it is a well-written and cited article with an informative introduction.
Weaknesses:
The authors performed a large amount of work with the drugs given at the doses and dosing intervals started, but at present, there is no exposure data available in the paper. It would be of great value to understand the exposures achieved in plasma at least (and in the lung if more relevant for S) in order to better understand how these relate to clinical exposures that are observed at marketed doses for B, Pa, and L as well as to understand the exposure achieved at the doses being evaluated for S. If available as historical data this could be included/cited. Considering the great attempts made to evaluate parameters that are relevant to clinical adverse events, it would add value to understand what exposures of drug effects such as anemia, weight loss, and bone marrow effects, are being observed.
It would also be of value to add an assessment of whether the weight loss, anemia, or bone marrow effects observed for BPaL are considered adverse, and the extent to which we can translate these effects from mouse to patient (i.e. what are the limitations of these assessments made in a mouse study?). For example, is the small weight loss seen as significant, or is it reversible? Is the magnitude of the changes in blood parameters similar to the parameters seen in patients given L?
In addition, it is always challenging to interpret findings for combinations of drugs, so the addition of language to explain this would add value: for example, how confident can we be that the weight loss seen for only the BPaL group is due to L as opposed to a PK interaction leading to an elevated exposure and weight loss due to B or Pa?
Turning to the evaluations of activity in mouse TB models, unfortunately, the evaluations of activity in the BALB/c mouse model as well as the spleens of the Kramnik model resulted in CFU below/at the limit of detection and so, to this reviewer's understanding of the data, comparisons between BPaL and BPaS cannot be made and so the conclusion of equivalent efficacy in BALB/c is not supported with the data shown. There is no BPa control in the BALB/c study, therefore it is not possible to discern whether L or S contributed to the activity of BPaL or BPaS; it is possible that BPa would have shown the same efficacy as the 3 drug combinations. It would be valuable to conduct a study including a BPa control and with a shorter treatment time to allow comparison of BPa, BPaS, and BPaL. In the Kramnik lungs, as the authors rightly note, the studies do not support any contribution of S or L to BPa - i.e. the activity observed for BPa, BPaL, and BPaS did not significantly differ. Although the conclusions note equivalency of BPaL and BPaS, which is correct, it would be helpful to also include BPa in this statement; it would be useful to conduct a study dosing for a longer period of time or assessing a relapse endpoint, where it is possible that a contribution of L and/or S may be seen - thus making a stronger argument for S contributing an equivalent efficacy to L. The same is true for the assessment of lesions - unfortunately, there was no BPa control meaning that even where equivalency is seen for BPaL and BPaS, the reader is unable to deduce whether L or S made a contribution to this activity.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The article by Huang et.al. presents an in-depth study on the role of DNA methylation in regulating virulence and metabolism in Pseudomonas syringae, a model phytopathogenic bacterium. This comprehensive research utilized single-molecule real-time (SMRT) sequencing to profile the DNA methylation landscape across three model pathovars of P. syringae, identifying significant epigenetic mechanisms through the Type-I restriction-modification system (HsdMSR), which includes a conserved sequence motif associated with N6-methyladenine (6mA). The study provides novel insights into the epigenetic mechanisms of P. syringae, expanding the understanding of bacterial pathogenicity and adaptation. The use of SMRT sequencing for methylome profiling, coupled with transcriptomic analysis and in vivo validation, establishes a robust evidence base for the findings
Strengths:
The results are presented clearly, with well-organized figures and tables that effectively illustrate the study's findings.
Weaknesses:
It would be helpful to add more details, especially in the methods, which make it easy to evaluate and enhance the manuscript's reproducibility.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Pal et al. provide valuable evidence supporting distinct vascular bed-specific VEGF-A mediated vascular permeability function of Neuropilin-1 (NRP1) in adult mice. Using a suite of genetic mice models and state-of-the-art vascular permeability assays the authors demonstrate that ear skin vasculature of EC-specific NRP1 adult knockout mice is hypersensitive to VEGF-A mediated high-molecular weight dye leakage from venules, as opposed to back skin and tracheal vasculature where EC-specific NRP1 loss had a more classical negative effect on permeability. Interestingly, both whole organism KO of NRP1 and a blocking antibody treatment, attenuated VEGF-A mediated permeability in ear skin and had the usual attenuation of permeability phenotype in back skin and tracheal vasculature. Using a pericyte promoter specific reporter mice line, the authors characterize NRP1 expression in the vascular beds of the ear dermis and back skin and conclude that NRP1 expression is higher in perivascular cells in the ear dermis as opposed to back skin vasculature, thus indicating a juxtracrine NRP1-VEGFR2 signaling model in adult mice. Further, they use a Vegfr2 phosphosite mutant homozygous mice model in the background of NRP1 iECKO to find the hypersensitivity to VEGF-A stimulation in ear skin is abrogated and therefore, prove the juxtracrine NRP1 control of VEGFR2 mediated downstream signaling leading to vascular permeability. Further, they successfully show distinctive vascular bed-specific results as above using a well-characterized VE-Cadherin Y685 antibody staining which corresponds to vascular leakage downstream of VEGF-A/VEGFR2 signaling in ear dermis and back skin vascular beds.
Strengths:
The question of the in vivo role of NRP1 in VEGF-A-induced hyper-permeability is an unresolved one and the elegant use of genetic mice models to demonstrate the phenotypes is valuable to the field. The organotypic differences observed in vascular permeability upon VEGF-A treatment in ear skin versus back skin and tracheal vasculature are solid. The subsequent investigation to validate heightened VEGFR2 signaling in ear dermis downstream of VEGF-A stimulation using Vegfr2 Y949F mice, VEC Y685 antibody, and pPLCγ antibody is also very convincing.
Weaknesses:
The mechanism proposed by the authors by which EC-specific loss of NRP1 caused hypersensitivity to VEGF-A in ear dermis is through elevated juxtracrine signaling of NRP1 expressed in pericytes in trans binding and retaining VEGFR2 on the cell surface of ECs to sustain downstream signaling for longer time, in corroboration to earlier findings in Koch et al., 2014, where NRP1 was studied in the context of tumor angiogenesis. To support their claim, the authors stain the ear dermis and back skin vasculature of Pdgfrb-GFP reporter mice, with NRP1 and CD31 antibodies and find out that ear skin vasculature has higher perivascular cells as opposed to back skin vasculature. While this is a good experiment to prove the above point, there are no functional experiments to support this model.
Overall, although the paper presents very useful findings in the field of NRP1-VEGFR2 biology, and most of the conclusions are well supported by the data, there are a few points if addressed can significantly substantiate the model of juxtracrine signaling proposed by the authors. They are:
(1) It will be important to know if the perivascular to vascular NRP1 expression (such as in Figure 3B) increases further in ear skin vasculatures of NRP1 iECKO mice compared to otherwise WT mice.
(2) Does knocking out NRP1 in pericytes attenuate the VEGF-A mediated hyperpermeability observed in ear skin of NRP1 iECKO mice (similar to experiments in 1C, 2C)?
(3) What is the status of VEGFR2 expression in ECs of ear skin and back skin of NRP1 iECKO and NRP1 iKO mice? This experiment is a proof-of-concept and is not essential to prove the point of juxtracrine NRP1 signaling since downstream readouts - pPLCγ and VEC Y685 staining have already been shown to correlate in the ear dermis.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This paper by Portela Catani et al examines the antigenic relationships (measured using monotypic ferret and mouse sera) across a panel of N2 genes from the past 14 years, along with the underlying sequence differences and phylogenetic relationships. This is a highly significant topic given the recent increased appreciation of the importance of NA as a vaccine target, and the relative lack of information about NA antigenic evolution compared with what is known about HA. Thus, these data will be of interest to those studying the antigenic evolution of influenza viruses. The methods used are generally quite sound, though there are a few addressable concerns that limit the confidence with which conclusions can be drawn from the data/analyses.
Strengths:
-The significance of the work, and the (general) soundness of the methods.<br /> -Explicit comparison of results obtained with mouse and ferret sera
Weaknesses:
- Machine learning analyses neither experimentally validated nor shown to be better than simple, phylogenetic-based inference.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Single unit neural activity tuned to environmental or behavioral variables gradually changes over time. This phenomenon, called representational drift, occurs even when all external variables remain constant, and challenges the idea that stable neural activity supports the performance of well-learned behaviors. While a number of studies have described representational drift across multiple brain regions, our understanding of the underlying mechanism driving drift is limited. Ratzon et al. propose that implicit regularization - which occurs when machine learning networks continue to reconfigure after reaching an optimal solution - could provide insights into why and how drift occurs in neurons. To test this theory, Ratzon et al. trained a recurrent neural network (RNN) trained to perform the oft-utilized linear track behavioral paradigm and compare the changes in hidden layer units to those observed in hippocampal place cells recorded in awake, behaving animals.
Ratzon et al. clearly demonstrate that hidden layer units in their model undergo consistent changes even after the task is well-learned, mirroring representational drift observed in real hippocampal neurons. They show that the drift occurs across three separate measures: the active proportion of units (referred to as sparsification), spatial information of units, and correlation of spatial activity. They continue to address the conditions and parameters under which drift occurs in their model to assess the generalizability of their findings to non-spatial tasks. Last, they investigate the mechanism through which sparsification occurs, showing that flatness of the manifold near the solution can influence how the network reconfigures. The authors suggest that their findings indicate a three stage learning process: 1) fast initial learning followed by 2) directed motion along a manifold which transitions to 3) undirected motion along a manifold.
Overall, the authors' results support the main conclusion that implicit regularization in machine learning networks mirrors representational drift observed in hippocampal place cells. Their findings promise to open new fields of inquiry into the connection between machine learning and representational drift in other, non-spatial learning paradigms, and to generate testable predictions for neural data.
Strengths:
(1) Ratzon et al. make an insightful connection between well-known phenomena in two separate fields: implicit regularization in machine learning and representational drift in the brain. They demonstrate that changes in a recurrent neural network mirror those observed in the brain, which opens a number of interesting questions for future investigation.
(2) The authors do an admirable job of writing to a large audience and make efforts to provide examples to make machine learning ideas accessible to a neuroscience audience and vice versa. This is no small feat and aids in broadening the impact of their work.
(3) This paper promises to generate testable hypotheses to examine in real neural data, e.g., that drift rate should plateau over long timescales (now testable with the ability to track single-unit neural activity across long time scales with calcium imaging and flexible silicon probes). Additionally, it provides another set of tools for the neuroscience community at large to use when analyzing the increasingly high-dimensional data sets collected today.
Weaknesses:
The revised manuscript addresses all the weaknesses outlined in my initial review. However, there is one remaining (minor) weakness regarding how "sparseness" is used and defined.
Sparseness can mean different things to different fields. For example, for engram studies, sparseness could be measured at the population level by the proportion of active cells, whereas for a physiology study, sparseness might be measured at the neuron level by the change in peak firing rate of each cell as an animal enters that cell's place field. In this manuscript, the idea of "sparseness" is introduced indirectly in the last paragraph of the introduction as "...changes in activity statistics (sparseness)...", but it is unclear from the preceding text if the referenced "activity statistics" used to define sparseness are the "fraction of active units," or their "tuning specificity," or both. While sparseness is clearly defined in the Methods section for the RNN, there is no mention of how it is defined for neural data, and spatial information is not mentioned at all. For clarity, I suggest explicitly defining sparseness for both the RNN and real neural data early in the main text, e.g. "Here, we measure sparseness in neural data by A and B, and by the analogous metric(s) of X and Y in our RNN..." This is a small but important nuance that will enhance the ease of reading for a broad neuroscience audience.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The manuscript by Nagel, et al. describes studies of mouse vomeronasal sensory neuron (VSN) tuning to mouse urine samples across different sexes and strains, including wild mice, alongside mass spectrometry analysis of the same samples. The authors performed live Ca2+ imaging (CAL520 dye) of VSNs in acute vomeronasal organ (VNO) slices to determine how VSNs are tuned to pairs of stimuli that differ in their origin (e.g. male C57BL/6 versus male BALB/c urine, male C57BL/6 versus female C57BL/6, etc.). For each pair of tested odorants, the results measure the proportion of VSNs that respond to both stimuli ("generalists") or just one of the two ("specialists"), as well as metrics of tuning preference and response reliability. The authors find in most cases that generalists make up a larger proportion of responsive VSNs than specialists, but several pairwise comparisons showed a high degree of strain selectivity. Notably, the authors evaluated VSN tuning in both male C57BL/6 and male BALB/c VNOs, finding strain-dependent differences in the representation of mouse urine. Alongside these measurements of VSN tuning, the authors report results of mass spectrometry analyses of volatiles and proteins in the same urine samples. These analyses indicated a number of molecules in each category that vary across sex and strain, and therefore represent candidate vomeronasal ligands. However, this study did not directly test whether any of these candidate molecules drives VSN activity. Overall, this work provides solid information related to mouse vomeronasal chemosensation.
Strengths:
A strength of the current study is its focus on characterizing the neural responses of the VNO to urine derived from wild mice. The majority of existing vomeronasal system research has relied on the use of inbred strains for both neural response recordings and investigations of candidate vomeronasal system ligands. Inbreeding in laboratory environments may alter the chemical composition of bodily secretions, thereby potentially changing the information they contain. Moreover, the more homogeneous nature of inbred strains could be critical when studying the AOS mediated social aspects. If there exist noticeable differences in the chemical composition of secretions from wild animals compared to inbred strains, this would suggest that future research must consider natural sources of candidate ligands outside of inbred strains. This work identifies some intriguing differences, worthy of further exploration, between the urine composition of wild mice versus inbred mice, as well as disparities in how the VNO responds to urine from these different sources. However, the molecular composition and VNO responsiveness to wild mouse urine was found to be highly overlapping with inbred mouse urine, supporting the continued investigation of candidate ligands found in inbred mouse urine.
Another positive aspect of this work is its use of the same set of stimuli as a previous study by the same authors (Bansal et al., 2021) in the downstream accessory olfactory bulb. The consistency in stimulus selection facilitates a comparison of information processing of sex and strain information from the sensory periphery to the brain. Although comparisons between the two connected regions are not a focus of this work, and methodological differences (e.g., Ca2+ imaging versus electrophysiology) may introduce caveats into comparisons, the support of "apples to apples" comparisons across connected circuits is critical to progress in the field.
Finally, this study directly measured VSN tuning in both male C57BL/6 and male BALB/c VNOs, finding subtle but important differences in the representation of mouse urine in these two recipient strains. Given that there is a long history of behavioral research into strain-specific differences in social behavior, this research paves the way for future studies into how different mouse strains detect and process social chemosignals.
Weaknesses:
One of the primary objectives in this study is to ascertain the extent to which the response profiles of VSNs are specific to sex and strain. The design of these Ca2+ imaging experiments uses a simple stimulus design, using two interleaved bouts of stimulation with pairs of urine (e.g., male versus female C57BL/6, male C57BL/6 versus male BALB/c) at a single dilution factor (1:100). This introduces two significant limitations: (1) the "generalist" versus "specialist" descriptors pertain only to the specific pairwise comparisons made and (2) there is no information about the sensitivity/concentration-dependence of the responses.
The functional measurements of VSN tuning to various pairs of urine stimuli are presented alongside mass spectrometry-based comparisons. However, the mass spectrometry-based analysis was performed separately from VSN tuning experiments/analysis. The juxtaposition of these measurements may give some readers the impression that VSN tuning measurements were integrated with molecular profiling (i.e., that the molecular diversity was causally related physiological responses). This is a hypothesis raised by the parallel studies, but not a supported conclusion of the current work.
The impact of mass spectrometry findings is acknowledged to be limited to nonvolatile organic compounds and proteins/peptides, and that it is possible that few of these candidate molecules are active in the VNO. Moreover, it remains possible that the VSN responses are driven mostly by small nonvolatiles (e.g., polar steroids), a class of strong VSN ligands that were excluded from molecular analysis.
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Reviewer #3 (Public Review):
A brain region called the retrotrapezoid nucleus (RTN) regulates breathing in response to changes in CO2/H+, a process termed central chemoreception. A transcription factor called PHOX2B is important for RTN development and mutations in the PHOX2B gene result in a severe type of sleep apnea called Congenital Central Hypoventilation Syndrome. PHOX2B is also expressed throughout life, but its postmitotic functions remain unknown. This study shows that knockdown of PHOX2B in the RTN region in adult rats decreased expression of Task2 and Gpr4 in Nmb-expressing RTN chemoreceptors and this corresponded with a diminished ventilatory response to CO2 but did not impact baseline breathing or the hypoxic ventilatory response. These results provide novel insight regarding postmitotic functions of PHOX2B in RTN neurons.
I have two main concerns and several points of clarification.
Main issues:<br /> (1) The experimental approach was not targeted to Nmb+ neurons and since other cells in the area also express Phox2b, conclusions should be tempered to focus on Phox2b expressing parafacial neurons NOT specifically RTN neurons
(2) It's not clear whether PHOX2B is important for transcription of pH sensing machinery, cell health or both. If knockdown of PHOX2B knockdown results in loss of RTN neurons this is also expected to decrease Task2 and Gpr4 levels, albeit by a transcription-independent mechanism.
Other points:
(3) All individual data points should be visible in floating bar graphs in Figs 1 and 4. For example, I don't see any dots for naïve animals in any of the panels in Fig. 1.
(4) the C1 and facial partly overlap with the RTN at this level of the medulla and these cells should appear as Phox2b+/Nmb- cells so it is not clear to me why these cells are not evident in the control tissue in figs 2B and 3B. Also, some of the bregma levels shown in Fig. 5A overlap with Figs 2-3 so again it's not clear to me how this non-cell type specific viral approach was targeted to Nmb cells but not near by TH+ cells. Please clarify.
(5) How do you get a loss of Nmb+ neurons (Figs 2-3) with no change in Nmb fluorescence (Fig. 5B)? In the absence of representative images these results are not compelling and should be substantiated by more readily quantifiable approaches like qPCR.
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Reviewer #3 (Public Review):
Summary:
The manuscript addresses a question inspired by the Baroceptor Hypothesis and its links to visual awareness and interoception. Specifically, the reported study aimed to determine if the effects of cardiac contraction (systole) on binocular rivalry (BR) are facilitatory or suppressive. The main experiment - relying on a technically challenging procedure of presenting stimuli synchronised with the heartbeats of participants - has been conducted with great care, and numerous manipulation checks the authors report convincingly show that the methods they used work as intended. Moreover, the control experiment allows for excluding alternative explanations related to participants being aware of their heartbeats. Therefore, the study convincingly shows the effect of cardiac activity on BR - and this is an important finding. The results, however, do not allow for unambiguously determining if this effect is facilitatory or suppressive (see details below), which renders the study not as informative as it could be.
While the authors strongly focus on interoception and awareness, this study will be of interest to researchers studying BR as such. Moreover, the code and the data the authors share can facilitate the adoption of their methods in other labs.
Strengths:
(1) The study required a complex technical setup and the manuscript both describes it well and demonstrates that it was free from potential technical issues (e.g. in section 3.3. Manipulation check).
(2) The sophisticated statistical methods the authors used, at least for a non-statistician like me, appear to be well-suited for their purpose. For example, they take into account the characteristics of BR (gamma distributions of dominance durations). Moreover, the authors demonstrate that at least in one case their approach is more conservative than a more basic one (Binomial test) would be.
(3) Finally, the control experiment, and the analysis it enabled, allow for excluding a multitude of alternative explanations of the main results.
(4) The authors share all their data and materials, even the code for the experiment.
(5) The manuscript is well-written. In particular, it introduces the problem and methods in a way that should be easy to understand for readers coming from different research fields.
Weaknesses:
(1) The interpretation of the main result in the context of the Baroceptor hypothesis is not clear. The manuscript states: The Baroreceptor Hypothesis would predict that the stimulus entrained to systole would spend more time suppressed and, conversely, less time dominant, as cortical activity would be suppressed each time that stimulus pulses. The manuscript does not specify why this should be the case, and the term 'entrained' is not too helpful here (does it refer to neural entrainment? or to 'being in phase with'?). The answer to this question is provided by the manuscript only implicitly, and, to explain my concern, I try to spell it out here in a slightly simplified form.
During systole (cardiac contraction), the visual system is less sensitive to external information, so it 'ignores' periods when the systole-synchronised stimulus is at the peak of its pulse. Conversely, the system is more sensitive during diastole, so the stimulus that is at the peak of its pulse then should dominate for longer, because its peaks are synchronised with the periods of the highest sensitivity of the visual system when the information used to resolve the rivalry is sampled from the environment. This idea, while indeed being a clever test of the hypothesis in question, rests on one critical assumption: that the peak of the stimulus pulse (as defined in the manuscript) is the time when the stimulus is the strongest for the visual system. The notion of 'stimulus strength' is widely used in the BR literature (see Brascamp et al., 2015 for a review). It refers to the stimulus property that, simply speaking, determines its tendency to dominate in the BR. The strength of a stimulus is underpinned by its low-level visual properties, such as contrast and spatial frequency content. Coming back to the manuscript, the pulsing of the stimuli affected at least spatial frequency (and likely other low-level properties), and it is unknown if it was in phase with the pulsing of the stimulus strength, or not. If my understanding of the premise of the study is correct, the conclusions drawn by the authors stand only if it was.
In other words, most likely the strength of one of the stimuli was pulsating in sync with the systole, but is it not clear which stimulus it was. It is possible that, for the visual system, the stimulus meant to pulse in sync with the systole was pulsing strength-wise in phase with the diastole (and the one intended to pulse with in sync with the diastole strength-wise pulsed with the systole). If this is the case, the predictions of the Baroceptor Hypothesis hold, which would change the conclusion of the manuscript.
(2) Using anaglyph goggles necessitates presenting stimuli of a different colour to each eye. The way in which different colours are presented can impact stimulus strength (e.g. consider that different anaglyph foils can attenuate the light they let through to different degrees). To deal with such effects, at least some studies on BR employed procedures of adjusting the colours for each participant individually (see Papathomas et al., 2004; Patel et al., 2015 and works cited there). While I think that counterbalancing applied in the study excludes the possibility that colour-related effects influenced the results, the effects of interest still could be stronger for one of the coloured foils.
(3) Several aspects of the methods (e.g. the stimuli), are not described at the level of detail some readers might be accustomed to. The most important issue here is the task the participants performed. The manuscript says that they pressed a button whenever they experienced a switch in perception, but it is only implied that there were different buttons for each stimulus.
Brascamp, J. W., Klink, P. C., & Levelt, W. J. M. (2015). The 'laws' of binocular rivalry: 50 years of Levelt's propositions. Vision Research, 109, 20-37. https://doi.org/10.1016/j.visres.2015.02.019<br /> Papathomas, T. V., Kovács, I., & Conway, T. (2004). Interocular grouping in binocular rivalry: Basic attributes and combinations. In D. Alais & R. Blake (Eds.), Binocular Rivalry (pp. 155-168). MIT Press<br /> Patel, V., Stuit, S., & Blake, R. (2015). Individual differences in the temporal dynamics of binocular rivalry and stimulus rivalry. Psychonomic Bulletin and Review, 22(2), 476-482. https://doi.org/10.3758/s13423-014-0695-1
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Reviewer #3 (Public Review):
Summary:
In this manuscript, the authors propose that astrocytic water channel AQP4 represents the dominant pathway for tonic water efflux without which astrocytes undergo cell swelling. The authors measure changes in astrocytic sulforhodamine fluorescence as the proxy for cell volume dynamics. Using this approach, they perform a technically elegant series of ex vivo and in vivo experiments exploring changes in astrocytic volume in response to AQP4 inhibitor TGN-020 and/or neuronal stimulation. The key finding is that TGN-020 produces an apparent swelling of astrocytes and modifies astrocytic cell volume regulation after spreading depolarizations. Additionally, systemic application of TGN-020 produced changes in diffusion-weighted MRI signal, which the authors interpret as cellular swelling. This study is perceived as potentially significant. However, several technical caveats should be strongly considered and perhaps addressed through additional experiments.
Strengths:
(1) This is a technically elegant study, in which the authors employed a number of complementary ex vivo and in vivo techniques to explore functional outcomes of aquaporin inhibition. The presented data are potentially highly significant (but see below for caveats and questions related to data interpretation).
(2) The authors go beyond measuring cell volume homeostasis and probe for the functional significance of AQP4 inhibition by monitoring Ca2+ signaling in neurons and astrocytes (GCaMP6 assay).
(3) Spreading depolarizations represent a physiologically relevant model of cellular swelling. The authors use ChR2 optogenetics to trigger spreading depolarizations. This is a highly appropriate and much-appreciated approach.
Weaknesses:
(1) The main weakness of this study is that all major conclusions are based on the use of one pharmacological compound. In the opinion of this reviewer, the effects of TGN-020 are not consistent with the current knowledge on water permeability in astrocytes and the relative contribution of AQP4 to this process.
Specifically: Genetic deletion of AQP4 in astrocytes reduces plasmalemmal water permeability by ~two-three-fold (when measured a 37oC, Solenov et al., AJP-Cell, 2004). This is a significant difference, but it is thought to have limited/no impact on water distribution. Astrocytic volume and the degree of anisosmotic swelling/shrinkage are unchanged because the water permeability of the AQP4-null astrocytes remains high. This has been discussed at length in many publications (e.g., MacAulay et al., Neuroscience, 2004; MacAulay, Nat Rev Neurosci, 2021) and is acknowledged by Solenov and Verkman (2004).
Keeping this limitation in mind, it is important to validate astrocytic cell volume changes using an independent method of cell volume reconstruction (diameter of sulforhodamine-labeled cell bodies? 3D reconstruction of EGFP-tagged cells? Else?)
(2) TGN-020 produces many effects on the brain, with some but not all of the observed phenomena sensitive to the genetic deletion of AQP4. In the context of this work, it is important to note that TGN-020 does not completely inhibit AQP4 (70% maximal inhibition in the original oocyte study by Huber et al., Bioorg Med Chem, 2009). Thus, besides not knowing TGN-020 levels inside the brain, even "maximal" AQP4 inhibition would not be expected to dramatically affect water permeability in astrocytes.
This caveat may be addressed through experiments using local delivery of structurally unrelated AQP4 blockers, or, preferably, AQP4 KO mice.
(3) This reviewer thinks that the ADC signal changes in Figure 5 may be unrelated to cellular swelling. Instead, they may be a result of the previously reported TGN-020-induced hyphemia (e.g., H. Igarashi et al., NeuroReport, 2013) and/or changes in water fluxes across pia matter which is highly enriched in AQP4. To amplify this concern, AQP4 KO brains have increased water mobility due to enlarged interstitial spaces, rather than swollen astrocytes (RS Gomolka, eLife, 2023). Overall, the caveats of interpreting DW-MRI signal deserve strong consideration.
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Reviewer #3 (Public Review):
Summary:
Neurogenesis in the mammalian olfactory epithelium persists throughout the life of the animal. The process replaces damaged or dying olfactory sensory neurons. It has been tacitly that replacement of the OR subtypes is stochastic, although anecdotal evidence has suggested that this may not be the case. In this study, Santoro and colleagues systematically test this hypothesis by answering three questions: is there enrichment of specific OR subtypes associated with neurogenesis? Is the enrichment dependent on sensory stimulus? Is the enrichment the result of differential generation of the OR type or from differential cell death regulated by neural activity? The authors provide some solid evidence indicating that musk odor stimulus selectively promotes the OR types expressing the musk receptors. The evidence argues against a random selection of ORs in the regenerating neurons.
Strengths:
The strength of the study is a thorough and systematic investigation of the expression of multiple musk receptors with unilateral naris occlusion or under different stimulus conditions. The controls are properly performed. This study is the first to formulate the selective promotion hypothesis and the first systematic investigation to test it. The bulk of the study uses in situ hybridization and immunofluorescent staining to estimate the number of OR types. These results convincingly demonstrate the increased expression of musk receptors in response to male odor or muscone stimulation.
Weaknesses:
A major weakness of the current study is the single-cell RNASeq result. The authors use this piece of data as a broad survey of receptor expression in response to unilateral nasal occlusion. However, several issues with this data raise serious concerns about the quality of the experiment and the conclusions. First, the proportion of OSNs, including both the immature and mature types, constitutes only a small fraction of the total cells. In previous studies of the OSNs using the scRNASeq approach, OSNs constitute the largest cell population. It is curious why this is the case. Second, the authors did not annotate the cell types, making it difficult to assess the potential cause of this discrepancy. Third, given the small number of OSNs, it is surprising to have multiple musk receptors detected in the open side of the olfactory epithelium whereas almost none in the closed side. Since each OR type only constitutes ~0.1% of OSNs on average, the number of detected musk receptors is too high to be consistent with our current understanding and the rest of the data in the manuscript. Finally, unlike the other experiments, the authors did not describe any method details, nor was there any description of quality controls associated with the experiment. The concerns over the scRNASeq data do not diminish the value of the data presented in the bulk of the study but could be used for further analysis.
A weakness of the experiment assessing musk receptor expression is that the authors do not distinguish immature from mature OSNs. Immature OSNs express multiple receptor types before they commit to the expression of a single type. The experiments do not reveal whether mature OSNs maintain an elevated expression level of musk receptors.
There are also two conceptual issues that are of concern. The first is the concept of selective neurogenesis. The data show an increased expression of musk receptors in response to male odor stimulation. The authors argue that this indicates selective neurogenesis of the musk receptor types. However, it is not clear what the distinction is between elevated receptor expression and a commitment to a specific fate at an early stage of development. As immature OSNs express multiple receptors, a likely scenario is that some newly differentiated immature OSNs have elevated expression of not only the musk receptors but also other receptors. The current experiments do not distinguish the two alternatives. Moreover, as pointed out above, it is not clear whether mature OSNs maintain the increased expression. Although a scRNASeq experiment can clarify it, the authors, unfortunately, did not perform an in-depth analysis to determine at which point of neurogenesis the cells commit to a specific musk receptor type. The quality of the scRNASeq data unfortunately also does not lend confidence for this type of analysis.
A second conceptual issue, the idea of homeostasis in regeneration, which the authors presented in the Introduction, needs clarification. In its current form, it is confusing. It could mean that a maintenance of the distribution of receptor types, or it could mean the proper replacement of a specific OR type upon the loss of this type. The authors seem to refer to the latter and should define it properly.
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Reviewer #3 (Public Review):
In this manuscript, Magnuson and colleagues investigate the meiotic functions of ARID1A, a putative DNA binding subunit of the SWI/SNF chromatin remodeler BAF. The authors develop a germ cell specific conditional knockout (cKO) mouse model using Stra8-cre and observe that ARID1A-deficient cells fail to progress beyond pachytene, although due to inefficiency of the Stra8-cre system the mice retain ARID1A-expressing cells that yield sperm and allow fertility. Because ARID1A was found to accumulate at the XY body late in Prophase I, the authors suspected a potential role in meiotic silencing and by RNAseq observe significant misexpression of sex-linked genes that typically are silenced at pachytene. They go on to show that ARID1A is required for exclusion of RNA PolII from the sex body and for limiting promoter accessibility at sex-linked genes, consistent with a meiotic sex chromosome inactivation (MSCI) defect in cKO mice. The authors proceed to investigate the impacts of ARID1A on H3.3 deposition genome-wide. H3.3 is known be regulated by ARID1A and is linked to silencing, and here the authors find that upon loss of ARID1A, overall H3.3 enrichment at the sex body as measured by IF failed to occur, but H3.3 was enriched specifically at transcriptional start sites of sex-linked genes that are normally regulated by ARID1A. The results suggest that ARID1A normally prevents H3.3 accumulation at target promoters on sex chromosomes and based on additional data, restricts H3.3 to intergenic sites. Finally, the authors present data implicating ARID1A and H3.3 occupancy in DSB repair, finding that ARID1A cKO leads to a reduction in focus formation by DMC1, a key repair protein. Overall the paper provides new insights into the process of MSCI from the perspective of chromatin composition and structure, and raises interesting new questions about the interplay between chromatin structure, meiotic silencing and DNA repair.
In general the data are convincing. The conditional KO mouse model has some inherent limitations due to incomplete recombination and the existence of 'escaper' cells that express ARID1A and progress through meiosis normally. This reviewer feels that the authors have addressed this point thoroughly and have demonstrated clear and specific phenotypes using the best available animal model. The data demonstrate that the mutant cells fail to progress past pachytene, although it is unclear whether this specifically reflects pachytene arrest, as accumulation in other stages of Prophase also is suggested by the data in Table 1.
The revised manuscript more appropriately describes the relationship between ARID1A and DNA damage response (DDR) signaling. The authors don't see defects in a few DDR markers in ARID1A CKO cells (including a low resolution assessment of ATR), suggesting that ARID1A may not be required for meiotic DDR signaling. However, as previously noted the data do not rule out the possibility that ARID1A is downstream of DDR signaling, and the authors note the possibility of a role for DDR signaling upstream of ARID1A.
A final comment relates to the impacts of ARID1A loss on DMC1 focus formation and the interesting observation of reduced sex chromosome association by DMC1. The authors additionally assess the related recombinase RAD51 and suggest that it is unaffected by ARID1A loss. However, only a single image of RAD51 staining in the cKO is provided (Fig. S11) and there are no associated quantitative data provided. The data are suggestive and conclusions about the impacts of ARID1A loss on RAD51 must be considered as preliminary until more rigorously assessed.
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Reviewer #3 (Public Review):
Summary:
This work describes a new pathway by which malaria parasites, P. falciparum, may regulate their growth and virulence (i.e. their expression of virulence-linked cytoadhesins). This is a topic of considerable interest in the field - does this important parasite sense factor(s) in its host bloodstream and regulate itself accordingly? Several fragments of evidence have come out on this topic in the past decade, showing, for example, reduced parasite growth under calorie restriction (in mice); parasite dormancy in response to amino acid starvation (in culture and in mice), and also reduced virulence in dry-season, low-parasitaemia infections in humans. The molecular mechanisms that may underlie this interesting biology remain only poorly understood.
Here, the authors show that dry-season P. falciparum parasites have reduced expression of Pol3-transcribed tRNAs and ncRNAs that positively regulate virulence gene expression. They link the level of Pol3 activity to PfMaf1, a remnant of the largely-absent nutrient-sensing TOR pathway in this parasite. They propose that in the dry season, human hosts may be calorie-restricted, leading to Maf1 moving to the nucleus and suppressing Pol3, thus downregulated growth and virulence of parasites. The evidence is intriguing and the idea is conceptually elegant.
Strengths:
The use of dry/wet-season field samples from The Gambia is a strength, showing potential real-world relevance. The generation of an inducible knockdown of Maf1 in lab-cultured parasites is also a strength, allowing this pathway to be studied somewhat in isolation.
Weaknesses:
(1) The signals upstream of Maf1 remain rather a black box. 4 are tested - heatshock and low-glucose, which seem to suppress ALL transcription; low-Isoleucine and high magnesium, which suppress Pol3. Therefore the authors use Mg supplementation throughout as a 'starvation type' stimulus. They do not discuss why they didn't use amino acid limitation, which could be more easily rationalised physiologically. It may for experimental simplicity (no need for dropout media) but this should be discussed, and ideally sample experiments with low-IsoLeu should be done too, to see if the responses (e.g. cytoadhesion) are all the same.
(2) The proteomics, conducted to seek partners of Maf1, is probably the weakest part. From Fig S4 it is clear that the proteins highlighted in the text are highly selected (as ones that might be relevant, e.g. phosphatases), but many others are more enriched. It would be good to see a) the top hits from the whole list provided as a short table within the main proteomics figure, along with the GO terms that actually came top in enrichment; b) the whole list provided as a supp. spreadsheet for easy re-analysis, rather than a PDF which cannot be easily re-used.
(3) Fig 3 shows the Maf1-low line has very poor growth after only 5 days but it is stated that no dead parasites are seen even after 8 cycles and the merozoites number is down only ~18 to 15... is this too small to account for such poor growth (~5-fold reduced in a single cycle, day 3-5)? It would additionally be interesting to see a cell-cycle length assessment and invasion assay, to see of Maf1-low parasite have further defects in growth.
Other weaknesses, which are more restricted but were not addressed in revision, are highlighted below:
Fig S1B - The downregulation of RNAPol3 transcripts caused by a commercial Pol3 inhibitor is pretty weak - mostly non-significant. The authors might comment on why they think this is, when interfering with PfMaf1 evidently has a greater effect.
Fig 2D: the legend states ' Expressed transcripts from three replicates between control and addition of MgCl2 that are significantly up-regulated are highlighted in red while significantly down-regulated RNA Pol III genes are highlighted in blue (FDR corrected p-value of <0.05) and a FC {greater than or equal to}{plus minus} 1.95) with examples listed as text'. This isn't very clear. The authors could clarify whether they took ALL (Pol3 or not) upregulated genes to show in red, but only putative Pol3-regulated genes to show in blue? If so, why? Or did they take all significantly downregulated genes, and found they were all annotated as pol3 transcribed? (I cannot see any dots that are not blue. If there are some, a clearer figure is needed?)
Line 227: 'PfMaf1 levels were shown to decrease by approximately 57% in total extracts after one cycle' - the provenance of this very precise percentage isn't clear (it does not appear on the figure). Is it densitometry of a western blot? And if so, is it an average of the 3 replicates that are stated in the legend (but not shown), or from the single example blot shown in Figure 3?
Fig 4A: the western blot, as shown, lacks controls, both for loading and for completeness of cyto/nuclear fractionation. To avoid confusion, these should be shown in the main figure, as is standard in the field, rather than separately in a supp figure. Ideally, 3 repeats should be done, with densitiometry quantification.
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Reviewer #3 (Public Review):
Unfortunately, this study fails to incorporate the most important variable impacting the ability to predict mosaicism, the accuracy of the test. The fact is that most embryos diagnosed as mosaic are not mosaic. There may be 4 cases out of thousands and thousands of transfers where a confirmation was made. Mosaicism has become a category of diagnosis in which embryos with noisy NGS profiles are placed. With VeriSeq NGS it is not possible to routinely distinguish true mosaicism from noise. An analysis of NGS noise levels (MAPD) versus the rate of mosaics by clinic using the registry will likely demonstrate this is the case. Without accounting for the considerable inaccuracy of the method of testing the proposed modeling is meaningless.
Recent data using more accurate methods of identifying mosaicism indicate that the prevalence of true preimplantation embryonic mosaicism is only 2%, which is also consistent with findings made post-implantation. This model fails to account for the possibility that, because so few embryos are actually mosaic, there is actually no relevance to clinical care whatsoever. In fact, differences in clinical outcomes of embryos designated as mosaic could be entirely attributed to poor embryo quality resulting in noise levels that make NGS results fall into the "mosaic" category.
Additional comments:
Indeed, as more data emerges, it appears that the majority of embryos from both healthy and infertile couples are mosaic to some degree (Coticchio et al., 2021; Griffin et al., 2022).
This statement should be softened as all embryos will be considered mosaic when a method with a 10% false positive rate is applied to 10 more parts of the same embryo. The distinction between artifact and true mosaicism cannot be made with nearly all current methods of testing. When virtually no embryos display uniform aneuploidy in a rebiopsy study, there should be great concern over the accuracy of the testing used. The vast majority of aneuploidy is meiotic in origin.
Experimental data provides strong evidence that, for the most part, the biopsy result obtained accurately represents the chromosome constitution of the rest of the embryo (Kim 96 et al., 2022; Navratil et al., 2020; Victor et al., 2019).
This statement is incorrect given published systematic review of the literature indicates a 10% false positive rate based on rebiopsy results.
This shows that accurately classifying a mosaic embryo based on a single biopsy is not robust.
This is exactly why the practice of designating embryo mosaics with intermediate copy numbers should not exist.
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Reviewer #3 (Public Review):
The article presents a comprehensive study on the stratification of viral shedding patterns in saliva among COVID-19 patients. The authors analyze longitudinal viral load data from 144 mildly symptomatic patients using a mathematical model, identifying three distinct groups based on the duration of viral shedding. Despite analyzing a wide range of clinical data and micro-RNA expression levels, the study could not find significant predictors for the stratified shedding patterns, highlighting the complexity of SARS-CoV-2 dynamics in saliva. The research underscores the need for identifying biomarkers to improve public health interventions and acknowledges several limitations, including the lack of consideration of recent variants, the sparsity of information before symptom onset, and the focus on symptomatic infections.
The manuscript is well-written, with the potential for enhanced clarity in explaining statistical methodologies. This work could inform public health strategies and diagnostic testing approaches. However, there is a thorough development of new statistical analysis needed, with major revisions to address the following points:
(1) Patient characterization & selection: Patient immunological status at inclusion (and if it was accessible at the time of infection) may be the strongest predictor for viral shedding in saliva. The authors state that the patients were not previously infected by SARS-COV-2. Was Anti-N antibody testing performed? Were other humoral measurements performed or did everything rely on declaration? From Figure 1A, I do not understand the rationale for excluding asymptomatic patients. Moreover, the mechanistic model can handle patients with only three observations, why are they not included? Finally, the 54 patients without clinical data can be used for the viral dynamics fitting and then discarded for the descriptive analysis. Excluding them can create a bias. All the discarded patients can help the virus dynamics analysis as it is a population approach. Please clarify. In Table 1 the absence of sex covariate is surprising.
(2) Exact study timReviewer #3 (Public Review):eline for explanatory covariates: I understand the idea of finding « early predictors » of long-lasting viral shedding. I believe it is key and a great question. However, some samples (Figure 4A) seem to be taken at the end of the viral shedding. I am not sure it is really easier to micro-RNA saliva samples than a PCR. So I need to be better convinced of the impact of the possible findings. Generally, the timeline of explanatory covariate is not described in a satisfactory manner in the actual manuscript. Also, the evaluation and inclusion of the daily symptoms in the analysis are unclear to me.
(3) Early Trajectory Differentiation: The model struggles to differentiate between patients' viral load trajectories in the early phase, with overlapping slopes and indistinguishable viral load peaks observed in Figures 2B, 2C, and 2D. The question arises whether this issue stems from the data, the nature of Covid-19, or the model itself. The authors discuss the scarcity of pre-symptom data, primarily relying on Illinois patients who underwent testing before symptom onset. This contrasts earlier statements on pages 5-6 & 23, where they claim the data captures the full infection dynamics, suggesting sufficient early data for pre-symptom kinetics estimation. The authors need to provide detailed information on the number or timing of patient sample collections during each period.
(4) Conditioning on the future: Conditioning on the future in statistics refers to the problematic situation where an analysis inadvertently relies on information that would not have been available at the time decisions were made or data were collected. This seems to be the case when the authors create micro-RNA data (Figure 4A). First, when the sampling times are is something that needs to be clarified by the authors (for clinical outcomes as well). Second, proper causal inference relies on the assumption that the cause precedes the effect. This conditioning on the future may result in overestimating the model's accuracy. This happens because the model has been exposed to the outcome it's supposed to predict. This could question the - already weak - relation with mir-1846 level.
(5) Mathematical Model Choice Justification and Performance: The paper lacks mention of the practical identifiability of the model (especially for tau regarding the lack of early data information). Moreover, it is expected that the immune effector model will be more useful at the beginning of the infection (for which data are the more parsimonious). Please provide AIC for comparison, saying that they have "equal performance" is not enough. Can you provide at least in a point-by-point response the VPC & convergence assessments?
(6) Selected features of viral shedding: I wonder to what extent the viral shedding area under the curve (AUC) and normalized AUC should be added as selected features.
(7) Two-step nature of the analysis: First you fit a mechanistic model, then you use the predictions of this model to perform clustering and prediction of groups (unsupervised then supervised). Thus you do not propagate the uncertainty intrinsic to your first estimation through the second step, ie. all the viral load selected features actually have a confidence bound which is ignored. Did you consider a one-step analysis in which your covariates of interest play a direct role in the parameters of the mechanistic model as covariates? To pursue this type of analysis SCM (Johnson et al. Pharm. Res. 1998), COSSAC (Ayral et al. 2021 CPT PsP), or SAMBA ( Prague et al. CPT PsP 2021) methods can be used. Did you consider sampling on the posterior distribution rather than using EBE to avoid shrinkage?
(8) Need for advanced statistical methods: The analysis is characterized by a lack of power. This can indeed come from the sample size that is characterized by the number of data available in the study. However, I believe the power could be increased using more advanced statistical methods. At least it is worth a try. First considering the unsupervised clustering, summarizing the viral shedding trajectories with features collapses longitudinal information. I wonder if the R package « LongituRF » (and associated method) could help, see Capitaine et al. 2020 SMMR. Another interesting tool to investigate could be latent class models R package « lcmm » (and associated method), see Proust-Lima et al. 2017 J. Stat. Softwares. But the latter may be more far-reached.
(9) Study intrinsic limitation: All the results cannot be extended to asymptomatic patients and patients infected with recent VOCs. It definitively limits the impact of results and their applicability to public health. However, for me, the novelty of the data analysis techniques used should also be taken into consideration.
Strengths are:<br /> - Unique data and comprehensive analysis.<br /> - Novel results on viral shedding.
Weaknesses are:<br /> - Limitation of study design.<br /> - The need for advanced statistical methodology.
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www.medrxiv.org www.medrxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript by Liu et al. presents a case that CAPSL mutations are a cause of familial exudative vitreoretinopathy (FEVR). Attention was initially focused on the CAPSL gene from whole exome sequence analysis of two small families. The follow-up analyses included studies in which CAPSL was manipulated in endothelial cells of mice and multiple iterations of molecular and cellular analyses. Together, the data show that CAPSL influences endothelial cell proliferation and migration. Molecularly, transcriptomic and proteomic analyses suggest that CAPSL influences many genes/proteins that are also downstream targets of MYC and may be important to the mechanisms.
Strengths:
This multi-pronged approach found a previously unknown function for CAPSLs in endothelial cells and pointed at MYC pathways as high-quality candidates in the mechanism.
Weaknesses:
Two issues shape the overall impact for me. First, the unreported population frequency of the variants in the manuscript makes it unclear if CAPSL should be considered an interesting candidate possibly contributing to FEVR, or possibly a cause. Second, it is unclear if the identified variants act dominantly, as indicated in the pedigrees. The studies in mice utilized homozygotes for an endothelial cell-specific knockout, leaving uncertainty about what phenotypes might be observed if mice heterozygous for a ubiquitous knockout had instead been studied.
In my opinion, the following scientific issues are specific weaknesses that should be addressed:
(1) Please state in the manuscript the number of FEVR families that were studied by WES. Please also describe if the families had been selected for the absence of known mutations, and/or what percentage lack known pathogenic variants.
(2) A better clinical description of family 3104 would enhance the manuscript, especially the father. It is unclear what "manifested with FEVR symptoms, according to the medical records" means. Was the father diagnosed with FEVR? If the father has some iteration of a mild case, please describe it in more detail. If the lack of clinical images in the figure is indicative of a lack of medical documentation, please note this in the manuscript.
(3) The TGA stop codon can in some instances also influence splicing (PMID: 38012313). Please add a bioinformatic assessment of splicing prediction to the assays and report its output in the manuscript.
(4) More details regarding utilizing a "loxp-flanked allele of CAPSL" are needed. Is this an existing allele, if so, what is the allele and citation? If new (as suggested by S1), the newly generated CAPSL mutant mouse strain needs to be entered into the MGI database and assigned an official allele name - which should then be utilized in the manuscript and who generated the strain (presumably a core or company?) must be described.
(5) The statement in the methods "All mice used in the study were on a C57BL/6J genetic background," should be better defined. Was the new allele generated on a pure C57BL/6J genetic background, or bred to be some level of congenic? If congenic, to what generation? If unknown, please either test and report the homogeneity of the background, or consult with nomenclature experts (such as available through MGI) to adopt the appropriate F?+NX type designation. This also pertains to the Pdgfb-iCreER mice, which reference 43 describes as having been generated in an F2 population of C57BL/6 X CBA and did not designate the sub-strain of C57BL/6 mice. It is important because one of the explanations for missing heritability in FEVR may be a high level of dependence on genetic background. From the information in the current description, it is also not inherently obvious that the mice studied did not harbor confounding mutations such as rd1 or rd8.
(6) In my opinion, more experimental detail is needed regarding Figures 2 and 3. How many fields, of how many retinas and mice were analyzed in Figure 2? How many mice were assessed in Figure 3?
(7) I suggest adding into the methods whether P-values were corrected for multiple tests.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Using patch clamp electrophysiology and Förster resonance energy transfer (FRET), Peters and co-workers showed that the disordered N-terminus of both LRMP and HCN4 are necessary for LRMP to interact with HCN4 and inhibit the cAMP-dependent potentiation of channel opening. Strikingly, they identified two HCN4-specific residues, P545 and T547 in the C-linker of HCN4, that are close in proximity to the cAMP transduction centre (elbow Clinker, S4/S5-linker, HCND) and account for the LRMP effect.
Strengths:
Based on these data, the Authors propose a mechanism in which LRMP specifically binds to HCN4 via its isotype-specific Nterminal sequence and thus prevents the cAMP transduction mechanism by acting at the interface between the elbow Clinker, the S4S5-linker, the HCND.
Weaknesses:
Although the work is interesting, there are some discrepancies between data that need to be addressed.
- I suggest inserting in Table 1 and in the text, the Δ shift values (+cAMP; + LRMP; +cAMP/LRMP). This will help readers.
- Figure 1 is not clear, the distribution of values is anomalously high. For instance, in 1B the distribution of values of V1/2 in the presence of cAMP goes from - 85 to -115. I agree that in the absence of cAMP, HCN4 in HEK293 cells shows some variability in V1/2 values, that nonetheless cannot be so wide (here the variability spans sometimes even 30 mV) and usually disappears with cAMP (here not).<br /> This problem is spread throughout the ms, and the measured mean effects indeed always at the limit of statistical significance. Why so? Is this a problem with the analysis, or with the recordings?<br /> There are several other problems with Figure 1 and in all figures of the ms: the Y scale is very narrow while the mean values are marked with large square boxes. Moreover, the exemplary activation curve of Fig 1A is not representative of the mean values reported in Figure 1B, and the values of 1B are different from those reported in Table 1.<br /> On this ground it is difficult to judge the conclusions and it would also greatly help if exemplary current traces would also be shown.
- "....HCN4-P545A/T547F was insensitive to LRMP (Figs. 6B and 6C; Table 1), indicating that the unique HCN4 C-linker is necessary for regulation by LRMP. Thus, LRMP appears to regulate HCN4 by altering the interactions between the C-linker, S4-S5 linker, and N-terminus at the cAMP transduction centre."
Although this is an interesting theory, there are no data supporting it. Indeed, P545 and T547 at the tip of the C-linker elbow (fig 6A) are crucial for LRMP effect, but these two residues are not involved in the cAMP transduction centre (interface between HCND, S4S5 linker and Clinker elbow), at least for the data accumulated till now in the literature. Indeed, the hypothesis that LRMP somehow inhibits the cAMP transduction mechanism of HCN4 given the fact that the two necessary residues P545 and T547 are close to the cAMP transduction centre, awaits to be proven.
Moreover, I suggest analysing the putative role of P545 and T547 in the light of the available HCN4 structures. In particular, T547 (elbow) point towards the underlying shoulder of the adjacent subunit and, therefore, it is in a key position for the cAMP transduction mechanism. The presence of bulky hydrophobic residues (very different nature compared to T) in the equivalent position of HCN1 and HCN2 is also favouring this hypothesis. In this light, it will also be interesting to see whether single T547F mutation is sufficient to prevent LRMP effect.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This research article reports that a greater number of senescent osteoclasts (SnOCs), which produce Netrin-1 and NGF, are responsible for innervation in the LSI and aging animal models.
Strengths:
The research is based on previous findings in the authors' lab and the fact that the IVD structure was restored by treatment with ABT263. The logic is clear and clarifies the pathological role of SnOCs, suggesting the potential utilization of senolytic drugs for the treatment of LBP. Generally, the study is of good quality and the data is convincing.
Weaknesses:
All my concerns have been well addressed, no further comments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In the manuscript entitled "Embryonic Origins of Forebrain Oligodendrocytes Revisited by Combinatorial Genetic Fate Mapping," Cai et al. used an intersectional/subtractional strategy to genetically fate-map the oligodendrocyte populations (OLs) generated from medial ganglionic eminence (NKX2.1+), lateral ganglionic eminences, and dorsal progenitor cells (EMX1+). Specifically, they generated an OL-expressing reporter mouse line OpalinP2A-Flpo-T2A-tTA2 and bred with region-specific neural progenitor-expressing Cre lines EMX1-Cre for dOL and NKX2.1-Cre for MPOL. They used a subtractional strategy in the OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mouse line to predict the origins of OLs from lateral/caudal ganglionic eminences (LC). With their genetic tools, the authors concluded that neocortical OLs primarily consist of dOLs. Although the populations of OLs (dOLs or MP-OLs) from Emx1+ or Nkx2.1+ progenitors are largely consistent with previous findings, they observed that MP-OLs contribute minimally but persist into adulthood without elimination as in the previous report (PMID: 16388308).
Intriguingly, by using an indirect subtraction approach, they hypothesize that both Emx1-negative and Nkx2.1-negative cells represent the progenitors from lateral/caudal ganglionic eminences (LC), and conclude that neocortical OLs are not derived from the LC region. This is in contrast to the previous observation for the contribution of LC-expressing progenitors (marked by Gsx2-Cre) to neocortical OLs (PMID: 16388308). The authors claim that Gsh2 is not exclusive to progenitor cells in the LC region (PMID: 32234482). However, Gsh2 exhibits high enrichment in the LC during early embryonic development. The presence of a small population of Gsh2-positive cells in the late embryonic cortex could originate/migrate from Gsh2-positive cells in the LC at earlier stages (PMID: 32234482). Consequently, the possibility that cortical OLs derived from Gsh2+ progenitors in LC could not be conclusively ruled out. Notably, a population of OLs migrating from the ventral to the dorsal cortical region was detected after eliminating dorsal progenitor-derived OLs (PMID: 16436615).
The indirect subtraction data for LC progenitors drawn from the OpalinFlp-tdTOM reporter in Emx1-negative and Nkx2.1-negative cells in the OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mouse line present some caveats that could influence their conclusion. The extent of activity from the two Cre lines in the OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mice remains uncertain. The OpalinFlp-tdTOM expression could occur in the presence of either Emx1Cre or Nkx2.1Cre, raising questions about the contribution of the individual Cre lines. To clarify, the authors should compare the tdTOM expression from each individual Cre line, OpalinFlp::Emx1Cre::RC::FLTG or OpalinFlp::Nkx2.1Cre::RC::FLTG, with the combined OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mouse line. This comparison is crucial as the results from the combined Cre lines could appear similar to only one Cre line active.
Overall, the authors provided intriguing findings regarding the origin and fate of oligodendrocytes from different progenitor cells in embryonic brain regions. However, further analysis is necessary to substantiate their conclusion about the fate of LC-derived OLs convincingly.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The main objective of this work has been to delve into the mechanisms underlying the increment of D-serine in serum, as a marker of renal injury.
Strengths:
With a multi-hierarchical approach, the work shows that Ischemia reperfusion injury in kidney causes a specific increment in renal reabsorption of D-serine that, at least in part, is due to the increased expression of the apical transporter ASCT2. In the way, the authors revealed that SMCT1 also transports D-serine.
The manuscript also supports that increased expression of ASCT2, even together with the parallel decreased expression of SMCT1, in renal proximal tubules underlies the increased reabsorption of D-serine responsible of the increment of this enantiomer in serum in a murine model of ischemia reperfusion injury.
Weaknesses:
Remains to be clarified whether ASCT2 has substantial stereospecificity in favor of D- versus L-serine to sustain a ~10-fold decreased in the ratio D-serine/L-serine in the urine of mouse under ischemia reperfusion injury (IRI).<br /> It is not clear how the increment in the expression of ASCT2, in parallel with the decreased expression of SMCT1, results in increased renal reabsorption of D-serine in IRI.
I am satisfied with the changes the authors have introduced in the text of the revised version of their manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Zhao et al. address the question of whether intermediate states of the epithelial-to-mesenchymal transition (EMT) exist in a natural developmental context as well as in cancer cells. This is important not only for our understanding of these developmental systems but also for their development as resources for new anti-cancer approaches. Guided by single-cell RNA sequencing analysis of delaminating mouse cranial neural crest cells, they identify two distinct populations with transcriptional signatures intermediate between neuroepithelial progenitors and migrating crest. Both clusters are also spatially intermediate and are actively cycling, with one in S-phase and one in G2/M. They show that blocking progression through S phase prior to the onset of delamination and knockdown of intermediate state marker Dlc1 both reduce the number of migratory cells that have completed EMT. Overall, the work provides a modern take and new insights into the classical developmental process of neural crest delamination.
Strengths:
• Deep analysis of the scRNAseq dataset revealed previously unappreciated cell populations intermediate between premigratory and migratory crest.<br /> • The observation that delaminating/intermediate neural crest cells appear to be in S or G2/M phase is interesting and worth reporting, though the ultimate significance remains unclear, given that they do not make distinct derivatives depending on their cycle state.<br /> • The authors employ new methods for multiplex spatial imaging to more accurately define their populations of interest and their relative positions.<br /> • The authors present evidence that intermediate state gene Dlc1 (a Rho GAP) is not just a marker but functionally required for neural crest delamination in mouse, as previously shown in chicken.
Weaknesses:
• Similar experiments involving blockade of cell cycle progression and Dlc1 dose manipulation were previously performed in chick models, as noted in the discussion. The newly-defined intermediate states give added context to the results, but they are not entirely novel.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this study, the authors set out to address the question of how the SNARE protein Syntaxin 17 senses autophagosome maturation by being recruited to autophagosomal membranes only once autophagosome formation and sealing is complete. The authors discover that the C-terminal region of Syntaxin 17 is essential for its sensing mechanism that involves two transmembrane domains and a positively charged region. The authors discover that the lipid PI4P is highly enriched in mature autophagosomes and that electrostatic interaction with Syntaxin 17's positively charged region with PI4P drives recruitment specifically to mature autophagosomes. The temporal basis for PI4P enrichment and Syntaxin 17 recruitment to ensure that unsealed autophagosomes do not fuse with lysosomes is a very interesting and important discovery. Overall, the data are clear and convincing, with the study providing important mechanistic insights that will be of broad interest to the autophagy field, and also to cell biologists interested in phosphoinositide lipid biology. The author's discovery also provides an opportunity for future research in which Syntaxin 17's c-terminal region could be used to target factors of interest to mature autophagosomes.
Strengths:
The study combines clear and convincing cell biology data with in vitro approaches to show how Syntaxin 17 is recruited to mature autophagosomes. The authors take a methodical approach to narrow down the critical regions within Syntaxin 17 required for recruitment and use a variety of biosensors to show that PI4P is enriched on mature autophagosomes.
Weaknesses:
There are no major weaknesses, overall the work is highly convincing. It would have been beneficial if the authors could have shown whether altering PI4P levels would affect Syntaxin 17 recruitment. However, this is understandably a challenging experiment to undertake and the authors outlined their various attempts to tackle this question.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
The data reported here demonstrate that Sema7a defines the local behavior of growing axons in the developing zebrafish lateral line. The analysis is sophisticated and convincingly demonstrates effects on axon growth and synapse architecture. Collectively, the findings point to the idea that the diffusible form of sema7a may influence how axons grow within the neuromast and that the GPI-linked form of sema7a may subsequently impact how synapses form, though additional work is needed to strongly link each form to its' proposed effect on circuit assembly.
Comments on revised submission:
The revised manuscript is significantly improved. The authors comprehensively and appropriately addressed most of the reviewers' concerns. In particular, they added evidence that hair cells express both Sema7A isoforms, showed that membrane bound Sema7A does not have long range effects on guidance, demonstrated how axons behave close to ectopic Sema7A, and analyzed other features of the hair cells that revealed no strong phenotypes. The authors also softened the language in many, but not all places. Overall, I am satisfied with the study as a whole.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Authors mapped monosynaptic inputs to dopamine, GABA, and glutamate neurons in VTA under different anesthesia methods, and under drugs (cocaine, morphine, methamphetamine, amphetamine, nicotine, fluoxetine). They found that input patterns under different conditions are separated, and identified some key brain areas to contribute to such separation. They also searched a database for gene expression patterns that are common across input brain areas with some changes by anesthesia or drug administration.
Strengths:
The whole-brain approach to address drug effects is appealing and their conclusion is clear. The methodology and motivation are clearly explained.
Weaknesses:
While gene expression analyses may not be related to their findings on the anatomical effects of drugs, this will be a nice starting point for follow-up studies.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors aimed to develop an automated tool to easily collect, process, and annotate the biomedical literature for higher efficiency and better reproducibility.
Strengths:
Two charms coming with the efforts made by the team are Pubget (for efficient and reliable grabbing articles from PubMed) and labelbuddy (for annotating text). They make text-mining of the biomedical literature more accessible, effective, and reproducible for streamlined text-mining and meta-science projects. The data were collected and analyzed using solid and validated methodology and demonstrated a very promising direction for meta-science studies.
Weaknesses:
More developments are needed for different resources of literature and strengths of AI-powered functions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The neural retina is one of the most energetically active tissues in the body and research into retinal metabolism has a rich history. Prevailing dogma in the field is that the photoreceptors of the neural retina (rods and cones) are heavily reliant on glycolysis, and as oxygen tension at the level of photoreceptors is very low, these specialized sensory neurons carry out aerobic glycolysis, akin to the Warburg effect in cancer cells. It has been found that this unique metabolism changes in many retinal diseases, and targeting disease-altered retinal metabolism may be a viable treatment strategy. The neural retina is composed of 11 different cell types, and many research groups over the past century have contributed to our current understanding of cell-specific metabolism of retinal cells. More recently, it has been shown in mouse models and co-culture of the mouse neural retina with human RPE cultures that photoreceptors are reliant on the underlying retinal pigment epithelium for supplying nutrients. Chen and colleagues add to this body of work by studying an ex vivo culture of the developing mouse retina that maintained contact with the retinal pigment epithelium. They exposed such ex vivo cultures to small molecule inhibitors of specific metabolic pathways, performing targeted metabolomics on the tissue and staining tissue with key metabolic enzymes to lay the groundwork for what metabolic pathways may be active in particular cell types of the retina. The authors conclude that rod and cone photoreceptors are reliant on different metabolic pathways to maintain their cell viability - in particular, that rods rely on oxidative phosphorylation and cones rely on glycolysis. Further, their data suggest multiple mechanisms whereby glycolysis may occur simultaneously with anapleurosis to provide abundant energy to photoreceptors. The data from metabolomics revealed several novel findings in retinal metabolism, including the use of glutamine to fuel the mini-Krebs cycle, the utilization of the Cahill cycle in photoreceptors, and a taurine/hypotaurine shuttle between the underlying retinal pigment epithelium and photoreceptors to transfer reducing equivalents from the RPE to photoreceptors. In addition, this study provides quantitative metabolomics datasets that can be compared across experiments and groups. The use of this platform will allow for rapid testing of novel hypotheses regarding the metabolic ecosystem in the neural retina.
Strengths:
The data on differences in susceptibility of rods and cones to mitochondrial dysfunction versus glycolysis provides novel hypothesis-generating conjectures that can be tested in animal models. The multiple mechanisms that allow anapleurosis and glycolysis to run side-by-side add significant novelty to the field of retinal metabolism, setting the stage for further testing of these hypotheses as well.
Weaknesses:
Almost all of the conclusions from the paper are preliminary, based on data showing enzymes necessary for a metabolic process are present and the metabolites for that process are also present. However, to truly prove whether these processes are happening (rather than speculation of the possibility they are happening), further experiments are necessary. As it currently stands, results from this study contradict results from other studies - in particular that cones, not rods, are most reliant of glycolysis. The authors attempt to address these contradictions, but without further experimentation, logical arguments carry only so much weight. At a minimum, the authors have argued that the small molecules they use are exquisitely specific for their intended targets, but validating results with a second small molecule that hits the same target but is structurally different would bolster their claims. Genetically knocking down the intended targets with interfering RNA technology would also be possible, as would explant cultures from knock-out animals. Without these studies to confirm target specificity, combined with the fact that conclusions from this study contradict existing studies in the literature, the results have to be categorized as speculative and hypothesis-generating rather than conclusive.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This is a conceptually appealing study by Giunti et al in which the authors identify a role for PTEN/daf-18 and daf-16/FOXO in the development of inhibitory GABA neurons, and then demonstrate that a diet rich in ketone body β-hydroxybutyrate partially suppresses the PTEN mutant phenotypes. The authors use three assays to assess their phenotypes: (1) pharmacological assays (with levamisole and aldicarb); (2) locomotory assays and (3) cell morphological assays. These assays are carefully performed and the article is clearly written. While neurodevelopmental phenotypes had been previously demonstrated for PTEN/daf-18 and daf-16/FOXO (in other neurons), and while KB β-hydroxybutyrate had been previously shown to increase daf-16/FOXO activity (in the context of aging), this study is significant because it demonstrates the importance of KB β-hydroxybutyrate and DAF-16 in the context of neurodevelopment. Conceptually, and to my knowledge, this is the first evidence I have seen of a rescue of a developmental defect with dietary metabolic intervention, linking, in an elegant way, the underpinning genetic mechanisms with novel metabolic pathways that could be used to circumvent the defects.
Strengths:
What their data clearly demonstrate, is conceptually appealing, and in my opinion, the biggest contribution of the study is the ability of reverting a neurodevelopmental defect with a dietary intervention that acts upstream or in parallel to DAF-16/FOXO.
Weaknesses:
The model shows AKT-1 as an inhibitor of DAF-16, yet their studies show no differences from wildtype in akt-1 and akt-2 mutants. AKT is not a major protein studied in this paper, and it can be removed from the model to avoid confusion, or the result can be discussed in the context of the model to clarify interpretation.
When testing additional genes in the DAF-18/FOXO pathway, there were no significant differences from wild type in most cases. This should be discussed. Could there be an alternate pathway via DAF-18/DAF-16, excluding the PI3K pathway or are there variations in activity of PI3K genes during a ketogenic diet that are hard to detect with current assays?
The consequence of SOD-3 expression in the broader context of GABA neurons was not discussed. SOD-3 was also measured in the pharynx but measuring it in neurons would bolster the claims.
If they want to include AKT-1, seeing its effect on SOD-3 expression could be meaningful to the model.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Mao and colleagues generated powerful reagents to genetically analyse chemical communication (CCT) in the brain, and in the process uncovered a function for the CNMa neuropeptide expressed in a subset of DN1p neurons that contributes to the temporal organization of locomotor activity, i.e., the timing of morning anticipation.
Strengths:
The strength of the manuscript relies in the generation/characterization of new tools for conditional targeting a well-defined set of CCT genes along with the design and testing of improved versions of Cas9 for efficient knock out. Such invaluable resources will be of interest to the whole community. The authors employed these tools and intersectional genetics to provide an alternative profiling of clock neurons, which is complementary to the ones already published. Furthermore, they uncovered a role for CNMamide, expressed in two DN1ps, in the timing of morning anticipation.
Weaknesses:
All prior concerns have been addressed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this study the authors used patch-clamp to characterize the implication of various voltage-gated Na+ channels in the firing properties of mouse nociceptive sensory neurons. They claim that depending on the culture conditions NaV1.3, NaV1.7, and NaV1.8 have distinct contributions to action potential firing and that similar firing patterns can result from distinct relative roles of these channels.
Strengths:
The paper addresses the important issue of understanding the lack of success of therapeutic strategies targeting NaV channels in the context of pain. Specifically, the authors test the hypothesis that different NaV channels contribute in a plastic manner to action potential firing, which may be the reason why it is difficult to target pain by inhibiting these channels.
Weaknesses:
(1) - The main claim of this paper is that "nociceptors can achieve equivalent excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8". From this, they allude to the manifestation of "degeneracy", a concept implying that a biological process can occur via distinct sets of underlying components.<br /> In my opinion, the analyses of the data is biased towards the author's interpretation.<br /> - First, when comparing the excitability across neurons one should relate the response (in this case mean firing frequency) to the absolute size of the stimulus, not to the size of the stimulus normalized to the rheobase (see e.g., Figs. 1A). From this particular figure the authors conclude that the excitability is similar in the culture stages DIV0 and DIV4-7, but these data were not directly compared.<br /> - Second, the authors reach their conclusion from the comparison of the (average) firing rate determined over 1 s current stimulation in distinct conditions. However, this is not the only parameter that determines how sensory neurons might convey information. For instance, the time dependence of the instantaneous frequency, the actual firing pattern, maybe also important.<br /> - Third, the use of 1 s of current stimulation might not be sufficient to characterize the firing pattern if one wants to obtain conclusions that could translate to clinical settings (i.e., sustained pain).<br /> - Fourth, out of principle, the gating properties of NaV1.7 and NaV1.8 channels are not identical, and therefore their contributions to excitability should not be the same. A neuron in which NaV1.7 is the main contributor is expected to have a damping firing pattern due to cumulative channel inactivation, whereas another depending mainly on NaV1.8 is expected to display more sustained firing. This is actually seen in the results of the modelling.
(2) - The quality of some recordings is dubious. The currents shown as TTX-sensitive in Fig. 1D look very strange (not like the ones at Baseline DIV4-7). These traces show abnormally fast inactivation and even transient deflections above zero current line. These are obvious artifacts of the subtraction procedure, probably due to unstable current amplitudes along the recording time. Similar odd-looking traces are shown in Fig. 3A.
(3) - I would like to point out that the main Significance Statement of the manuscript reads "The analgesic efficacy of subtype-selective drugs hinges on which subtype controls excitability". I would like to point out that, in addition of being extremely obvious for anyone knowing a bit about pain signaling, the authors did not test the analgesic efficacy of any drug in this study.
(4) - A critical issue in the manuscript is the unnecessary use of phrases that imply that biological entities have some sort of willpower, flirting with anthropomorphism and teleological language.<br /> Sentences such as "Nociceptive sensory neurons convey pain signals to the CNS using action potentials" (see the Abstract) should be avoided. Neurons do not really "use" action potentials, they have no will to do so. Action potentials are not tools or means to be "used" by neurons. There are many other examples of misuse of the verb "use" in many other sentences. These were pointed out during the revision phase, but unfortunately the authors refused to correct them.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
The original research article, titled "mitoBKCa is functionally expressed in murine and human breast cancer cells and promotes metabolic reprogramming" by Bischof et al, has demonstrated the underlying molecular mechanisms of alterations in the function of Ca2+ activated K+ channel of large conductance (BKCa) in the development and progression of breast cancer. The authors also proposed that targeting mitoBKCa in combination with established anti-cancer approaches, could be considered as a novel treatment strategy in breast cancer treatment.
The paper is modified according to the reviewer's comments. Most of the queries raised by this reviewer were answered. However, the preclinical implication of this study can also be manifested in combinatorial treatment with known chemotherapeutic drugs which is lacking in this manuscript. Hopefully, the authors will consider this in their future study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Astrocyte biology is an active area of research and this study is timely and adds to a growing body of literature in the field. The RNA-seq, Herp expression, and Ca2+ release data across wild-type, Bmal1 knockout, and Herp knockdown cellular models are robust and lend considerable support to the study's conclusions, highlighting their importance. Despite these strengths, the manuscript presents a gap in elucidating the dynamics of HERP and the involvement of ITPR1/2 in modulating Ca2+ release patterns and their circadian variations, which remains insufficiently supported and characterized. While the Connexin data underscore the importance of rhythmic Ca2+ release triggered by ATP, the relationship here appears correlational and the role of HERP and ITPR in Cx function remains to be characterized. Moreover, enhancing the manuscript's clarity and readability could significantly benefit the presentation and comprehension of the findings.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Mullen et al present an important study describing how DHODH inhibition enhances efficacy of immune checkpoint blockade by increasing cell surface expression of MHC I in cancer cells. DHODH inhibitors have been used in the clinic for many years to treat patients with rheumatoid arthritis and there has been a growing interest in repurposing these inhibitors as anti-cancer drugs. In this manuscript, the Singh group builds on their previous work defining combinatorial strategies with DHODH inhibitors to improve efficacy. The authors identify an increased expression of genes in the antigen presentation pathway and MHC I after BQ treatment which is mediated strictly by pyrimidine depletion and CDK9/P-TEFb. The authors rationalize that increased MHC I expression induced by DHODH inhibition might favor efficacy of dual immune checkpoint blockade. In fact, this combinatorial treatment prolonged survival in an immunocompetent B16F10 melanoma model.
Previous studies have shown that DHODH inhibitors can increase expression of innate immunity-related genes but the role of DHODH and pyrimidine nucleotides in antigen presentation has not been previously reported. A strength of the manuscript is the solid in vitro mechanistic data supported by analysis in multiple cell lines. The in vivo data show compelling additive effects of DHODH inhibitors and ICB. However, more controls and experiments would be required to define the nature of these effects and to confirm that the mechanistic in vitro data is conserved in vivo.
This is a relevant manuscript proposing a mechanistic link between pyrimidine depletion and MHC I expression and a novel therapeutic approach combining DHODH inhibitors with dual checkpoint blockade. These results might be relevant for the clinical development of DHODH inhibitors in the treatment of solid tumors, a setting where these have not shown optimal efficacy yet.
Comments on revised version:
The authors have addressed my questions regarding validation of gene expression in other cell lines. They have also provided an explanation about why in vivo evaluations could not be performed for the experiment in Figure 5E.
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www.medrxiv.org www.medrxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript by Liu et al. presents a case that CAPSL mutations are a cause of familial exudative vitreoretinopathy (FEVR). Attention was initially focused on the CAPSL gene from whole exome sequence analysis of two small families. The follow-up analyses included studies in which CAPSL was manipulated in endothelial cells of mice and multiple iterations of molecular and cellular analyses. Together, the data show that CAPSL influences endothelial cell proliferation and migration. Molecularly, transcriptomic and proteomic analyses suggest that CAPSL influences many genes/proteins that are also downstream targets of MYC and may be important to the mechanisms.
Strengths:
This multi-pronged approach found a previously unknown function for CAPSLs in endothelial cells and pointed at MYC pathways as high-quality candidates in the mechanism.
Weaknesses:
Two issues shape the overall impact for me. First, the unreported population frequency of the variants in the manuscript makes it unclear if CAPSL should be considered an interesting candidate possibly contributing to FEVR, or possibly a cause. Second, it is unclear if the identified variants act dominantly, as indicated in the pedigrees. The studies in mice utilized homozygotes for an endothelial cell-specific knockout, leaving uncertainty about what phenotypes might be observed if mice heterozygous for a ubiquitous knockout had instead been studied.
In my opinion, the following scientific issues are specific weaknesses that should be addressed:
(1) Please state in the manuscript the number of FEVR families that were studied by WES. Please also describe if the families had been selected for the absence of known mutations, and/or what percentage lack known pathogenic variants.
(2) A better clinical description of family 3104 would enhance the manuscript, especially the father. It is unclear what "manifested with FEVR symptoms, according to the medical records" means. Was the father diagnosed with FEVR? If the father has some iteration of a mild case, please describe it in more detail. If the lack of clinical images in the figure is indicative of a lack of medical documentation, please note this in the manuscript.
(3) The TGA stop codon can in some instances also influence splicing (PMID: 38012313). Please add a bioinformatic assessment of splicing prediction to the assays and report its output in the manuscript.
(4) More details regarding utilizing a "loxp-flanked allele of CAPSL" are needed. Is this an existing allele, if so, what is the allele and citation? If new (as suggested by S1), the newly generated CAPSL mutant mouse strain needs to be entered into the MGI database and assigned an official allele name - which should then be utilized in the manuscript and who generated the strain (presumably a core or company?) must be described.
(5) The statement in the methods "All mice used in the study were on a C57BL/6J genetic background," should be better defined. Was the new allele generated on a pure C57BL/6J genetic background, or bred to be some level of congenic? If congenic, to what generation? If unknown, please either test and report the homogeneity of the background, or consult with nomenclature experts (such as available through MGI) to adopt the appropriate F?+NX type designation. This also pertains to the Pdgfb-iCreER mice, which reference 43 describes as having been generated in an F2 population of C57BL/6 X CBA and did not designate the sub-strain of C57BL/6 mice. It is important because one of the explanations for missing heritability in FEVR may be a high level of dependence on genetic background. From the information in the current description, it is also not inherently obvious that the mice studied did not harbor confounding mutations such as rd1 or rd8.
(6) In my opinion, more experimental detail is needed regarding Figures 2 and 3. How many fields, of how many retinas and mice were analyzed in Figure 2? How many mice were assessed in Figure 3?
(7) I suggest adding into the methods whether P-values were corrected for multiple tests.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
ImmCellTyper is a new toolkit for Cytometry by time-of-flight data analysis. It includes BinaryClust, a semi-supervised clustering tool (which takes into account prior biological knowledge), designed for automated classification and annotation of specific cell types and subpopulations. ImmCellTyper also integrates a variety of tools to perform data quality analysis, batch effect correction, dimension reduction, unsupervised clustering, and differential analysis.
Strengths:
The proposed algorithm takes into account the prior knowledge.<br /> The results on different benchmarks indicate competitive or better performance (in terms of accuracy and speed) depending on the method.
Weaknesses:
The proposed algorithm considers only CyTOF markers with binary distribution.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Ephaptic inhibition between neurons housed in the same sensilla has been long discovered in flies, but the molecular basis underlying this inhibition is underexplored. Specifically, it remains poorly understood which receptors or channels are important for maintaining the transepithelial potential between the sensillum lymph and the hemolymph (known as the sensillum potential), and how this affects the excitability of neurons housed in the same sensilla.
Lee et al. used single-sensillum recordings (SSR) of the labellar taste sensilla to demonstrate that the HCN channel, Ih, is critical for maintaining sensillum potential in flies. Ih is expressed in sugar-sensing GRNs (sGRNs) but affects the excitability of both the sGRNs and the bitter-sensing GRNs (bGRNs) in the same sensilla. Ih mutant flies have decreased sensillum potential, and bGRNs of Ih mutant flies have a decreased response to the bitter compound caffeine. Interestingly, ectopic expression of Ih in bGRNs also increases sGRN response to sucrose, suggesting that Ih-dependent increase in sensillum potential is not specific to Ih expressed in sGRNs. The authors further demonstrated, using both SSR and behavior assays, that exposure to sugars in the food substrate is important for the Ih-dependent sensitization of bGRNs. The experiments conducted in this paper are of interest to the chemosensory field. The observation that Ih is important for the activity in bGRNs albeit expressed in sGRNs is especially fascinating and highlights the importance of non-synaptic interactions in the taste system.
Despite the interesting results, this paper is not written in a clear and easily understandable manner. It uses poorly defined terms without much elaboration, contains sentences that are borderline unreadable even for those in the narrower chemosensory field, and many figures can clearly benefit from more labeling and explanation. It certainly needs a bit of work.
Below are the major points:
(1) Throughout the paper, it is assumed that Ih channels are expressed in sugar-sensing GRNs but not bitter-sensing GRNs. However, both this paper and citation #17, another paper from the same lab, contain only circumstantial evidence for the expression of Ih channels in sGRNs. A simple co-expression analysis, using the Ih-T2A-GAL4 line and Gr5a-LexA/Gr66a-LexA line, all of which are available, could easily demonstrate the co-expression. Including such a figure would significantly strengthen the conclusion of this paper.
(2) Throughout this paper, it is often unclear which class of labellar taste sensilla is being recorded. S-a, S-b, I-a, and I-b sensilla all have different sensitivities to bitters and sugars. Each figure should clearly indicate which sensilla is being recorded. Justification should be provided if recordings from different classes of sensilla are being pooled together for statistics.
(3) In many figures, there is a lack of critical control experiments. Examples include Figures 1C-F (lacking UAS control), Figure 2I-J (lacking UAS control), Figure 4E (lacking the UAS and GAL4 control, and it is also strange to compare Gr64f > RNAi with Gr66a > RNAi, instead of with parental GAL4 and UAS controls.), and Figure 5D (lacking UAS control). Without these critical control experiments, it is difficult to evaluate the quality of the work.
(4) Figure 2A could benefit from more clarification about what exactly is being recorded here. The text is confusing: a considerable amount of text is spent on explaining the technical details of how SP is recorded, but very little text about what SP represents, which is critical for the readers. The authors should clarify in the text that SP is measuring the potential between the sensillar lymph, where the dendrites of GRNs are immersed, and the hemolymph. Adding a schematic figure to show that SP represents the potential between the sensillar lymph and hemolymph would be beneficial.
(5) The sGRN spiking rate in Figure 4B deviates significantly from previous literature (Wang, Carlson, eLife 2022; Jiao, Montell PNAS 2007, as examples), and the response to sucrose in the control flies is not dosage-dependent, which raises questions about the quality of the data. Why are the responses to sucrose not dosage-dependent? The responses are clearly not saturated at these (10 mM to 100 mM) concentrations.
(6) In Figure 4C, instead of showing the average spike rate of the first five seconds and the next 5 seconds, why not show a peristimulus time histogram? It would help the readers tremendously, and it would also show how quickly the spike rate adapts to overexpression and control flies. Also, since taste responses adapt rather quickly, a 500 ms or 1 s bin would be more appropriate than a 5-second bin.
(7) Lines 215 - 220. The authors state that the presence of sugars in the culture media would expose the GRNs to sugar constantly, without providing much evidence. What is the evidence that the GRNs are being activated constantly in flies raised with culture media containing sugars? The sensilla are not always in contact with the food.
(8) Line 223. To show that bGRN spike rates in Ih mutant flies "decreased even more than WT", you need to compare the difference in spike rates between the sorbitol group and the sorbitol + sucrose group, which is not what is currently shown.
(9) To help readers better understand the proposed mechanisms here, including a schematic figure would be helpful. This should show where Ih is expressed, how Ih in sGRNs impacts the sensillum potential, how elevated sensillum potential increases the electrical driving force for the receptor current, and affects the excitability of the bGRNs in the same sensilla, and how exposure to sugar is proposed to affect ion homeostasis in the sensillum lymph.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The present study proposes a neural circuit model consisting of coupled sensory and memory networks to explain the circuit mechanism of the cardinal effect in orientation perception which is characterized by the bias towards the oblique orientation and the largest variance at the oblique orientation.
Strengths:
The authors have done numerical simulations and preliminary analysis of the neural circuit model to show the model successfully reproduces the cardinal effect. And the paper is well-written overall. As far as I know, most of the studies on the cardinal effect are at the level of statistical models, and the current study provides one possibility of how neural circuit models reproduce such an effect.
Weaknesses:
There are no major weaknesses and flaws in the present study, although I suggest the author conduct further analysis to deepen our understanding of the circuit mechanism of the cardinal effects. Please find my recommendations for concrete comments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This important study relies on a rare dataset: intracranial recordings within the thalamus and the subthalamic nucleus in awake humans, while they were performing a tactile detection task. This procedure allowed the authors to identify a small but significant proportion of individual neurons, in both structures, whose activity correlated with the task (e.g. their firing rate changed following the audio cue signalling the start of a trial) and/or with the stimulus presentation (change in firing rate around 200 ms following tactile stimulation) and/or with participant's reported subjective perception of the stimulus (difference between hits and misses around 200 ms following tactile stimulation). Whereas most studies interested in the neural underpinnings of conscious perception focus on cortical areas, these results suggest that subcortical structures might also play a role in conscious perception, notably tactile detection.
Strengths:
There are two strongly valuable aspects in this study that make the evidence convincing and even compelling. First, these types of data are exceptional, the authors could have access to subcortical recordings in awake and behaving humans during surgery. Additionally, the methods are solid. The behavioral study meets the best standards of the domain, with a careful calibration of the stimulation levels (staircase) to maintain them around the detection threshold, and an additional selection of time intervals where the behavior was stable. The authors also checked that stimulus intensity was the same on average for hits and misses within these selected periods, which warrants that the effects of detection that are observed here are not confounded by stimulus intensity. The neural data analysis is also very sound and well-conducted. The statistical approach complies with current best practices, although I found that, in some instances, it was not entirely clear which type of permutations had been performed, and I would advocate for more clarity in these instances. Globally the figures are nice, clear, and well presented. I appreciated the fact that the precise anatomical location of the neurons was directly shown in each figure.
Weaknesses:
Some clarification is needed for interpreting Figure 3, top rows: in my understanding the black curve is already the result of a subtraction between stimulus present trials and catch trials, to remove potential drifts; if so, it does not make sense to compare it with the firing rate recorded for catch trials.
I also think that the article could benefit from a more thorough presentation of the data and that this could help refine the interpretation which seems to be a bit incomplete in the current version. There are 8 stimulus-responsive neurons and 8 perception-selective neurons, with only one showing both effects, resulting in a total of 15 individual neurons being in either category or 13 neurons if we exclude those in which the behavior is not good enough for the hit versus miss analysis (Figure S4A). In my opinion, it should be feasible to show the data for all of them (either in a main figure, or at least in supplementary), but in the present version, we get to see the data for only 3 neurons for each analysis. This very small selection includes the only neuron that shows both effects (neuron #001; which is also cue selective), but this is not highlighted in the text. It would be interesting to see both the stimulus-response data and the hit versus miss data for all 13 neurons as it could help develop the interpretation of exactly how these neurons might be involved in stimulus processing and conscious perception. This should give rise to distinct interpretations for the three possible categories. Neurons that are stimulus-responsive but not perception-selective should show the same response for both hits and misses and hence carry out indifferently conscious and unconscious responses. The fact that some neurons show the opposite pattern is particularly intriguing and might give rise to a very specific interpretation: if the neuron really doesn't tend to respond to the stimulus when hits and misses are put together, it might be a neuron that does not directly respond to the stimulus, but whose spontaneous fluctuations across trials affect how the stimulus is perceived when they occur in a specific time window after the stimulus. Finally, neuron #001 responds with what looks like a real burst of evoked activity to stimulation and also shows a difference between hits and misses, but intriguingly, the response is strongest for misses. In the discussion, the interesting interpretation in terms of a specific gating of information by subcortical structures seems to apply well to this last example, but not necessarily to the other categories.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Using ex vivo electrophysiology and morphological analysis, Boi et al. investigate the electrophysiological and morphological properties of serotonergic and dopaminergic subpopulations in the dorsal raphe nucleus (DRN). They performed labor-intensive and rigorous electrophysiology with posthoc immunohistochemistry and neuronal reconstruction to delineate the two major cell classes in the DRN: DRN-DA and DRN-5HT, named according to their primary neurotransmitter machinery. They find that the dopaminergic (DRN-DA) and serotonergic (DRN-5HT) neurons are electrophysiologically and morphologically distinct, and are altered following striatal injection of the toxin 6-OHDA. However, these alterations were largely prevented in DRN-5HT neurons by pre-treatment with desipramine. These findings suggest an important interplay between catecholaminergic systems in healthy and parkinsonian conditions, as well as a relationship between neuronal structure and function.
Strengths:
Large, well-validated dataset that will be a resource for others.<br /> Complementary electrophysiological and anatomical characterizations.<br /> Conclusions are justified by the data.<br /> Relevant for basic scientists interested in DRN cell types and physiology<br /> Relevant for those interested in serotonin and/or DRN neurons in Parkinson's Disease
Weaknesses:
Given the scope of the author's questions and hypotheses, I did not identify any major weaknesses.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors have examined the 5-HT3 receptor using voltage clamp fluorometry, which enables them to detect structural changes at the same time as the state of receptor activation. These are ensemble measurements, but they enable an impressive scheme of the action of different agonists and antagonists to be built up. The growing array of structural snapshots of 5-HT3 receptors is used to good effect to understand the results.
Strengths:
The combination of rigorously tested fluorescence reporters with oocyte electrophysiology across a large panel of ligands is a solid development for this receptor type.
Weaknesses:
In their revision, the authors corrected all the weaknesses of the original submission.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Chang et al. investigated the mechanisms governing collagen fibrillogenesis, firstly demonstrating that cells within tail tendons are able to uptake exogenous collagen and use this to synthesize new collagen-1 fibrils. Using an endocytic inhibitor, the authors next showed that endocytosis was required for collagen fibrillogenesis and that this process occurs in a circadian rhythmic manner. Using knockdown and overexpression assays, it was then demonstrated that collagen fibril formation is controlled by vacuolar protein sorting 33b (VPS33b), and this VPS33b-dependent fibrillogenesis is mediated via Integrin alpha-11 (ITGA11). Finally, the authors demonstrated increased expression of VPS33b and ITGA11 at the gene level in fibroblasts from patients with idiopathic pulmonary fibrosis (IPF), and greater expression of these proteins in both lung samples from IPF patients and in chronic skin wounds, indicating that endocytic recycling is disrupted in fibrotic diseases.
Strengths:
The authors have performed a comprehensive functional analysis of the regulators of endocytic recycling of collagen, providing compelling evidence that VPS33b and ITGA11 are crucial regulators of this process.
Weaknesses:
Throughout the study, several different cell types have been used (immortalised tail tendon fibroblasts, NIHT3T cells, and HEK293T cells). In general, it is not clear which cells have been used for a particular experiment, and the rationale for using these different cell types is not explained. In addition, some experimental details are missing from the methods.
There is also a lack of functional studies in patient-derived IPF fibroblasts which means the link between endocytic recycling of collagen and the role of VPS33b and ITGA11 cannot be fully established.
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www.biorxiv.org www.biorxiv.org
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Reviewer #4 (Public Review):
Summary:
Masala N et al showed interesting aberrant calcium microwaves in the hippocampus when synapsin promoter driven GCaMPs were expressed for a long period of time. These aberrant hippocampal Ca2+ micro-waves depend on the viral titre of the GECI. The microwave of Ca2+ was not observed when GECI was expressed only a sparse set of neurons.
Strengths:
These findings are important to wide neuroscience community especially when considering a great number of investigators are using similar approaches. Results look convincing and are consistent across several laboratories.
Weaknesses:
Synapsin promoter labels both excitatory pyramidal neurons and inhibitory neurons. To avoid aberrant Ca2+ microwave, a combination of Flex virus and CaMKII-Cre or Thy-1-GCaMP6s and 6f mice were tested. However, all these approaches limit the number of infected pyramidal neurons. While the comprehensive display of these results is appreciated, one additional important test would be more informative. To distinguish whether the microwave of Ca2+ is sufficiently caused via the expression of GCaMP in interneurons, or just a matter of pyramidal neuron density, testing Flex-GCaMP6 in interneuron specific mouse lines such as PV-Cre and SOM-Cre will provide further clarifications.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This paper aims to demonstrate the role of G-quadruplex DNA structures in the establishment of chromosome loops. The authors introduced an array of G4s spanning 275 bp, naturally found within a very well-characterized promoter region of the hTERT promoter, in an ectopic region devoid of G-quadruplex and annotated gene. As a negative control, they used a mutant version of the same sequence in which G4 folding is impaired. Due to the complexity of the region, 3 G4s on the same strand and one on the opposite strand, 12 point mutations were made simultaneously (G to T and C to A). Analysis of the 3D genome organization shows that the WT array establishes more contact within the TAD and throughout the genome than the control array. Additionally, a slight enrichment of H3K4me1 and p300, both enhancer markers, was observed locally near the insertion site. The authors tested whether the expression of genes located either nearby or up to 5 Mb away was up-regulated based on this observation. They found that four genes were up-regulated from 1.5 to 3-fold. An increased interaction between the G4 array compared to the mutant was confirmed by the 3C assay. For in-depth analysis of the long-range changes, they also performed Hi-C experiments and showed a genome-wide increase in interactions of the WT array versus the mutated form.
Strengths:
The experiments were well-executed and the results indicate a statistical difference between the G4 array inserted cell line and the mutated modified cell line.
Weaknesses:
The control non-G4 sequence contains 12 point mutations, making it difficult to draw clear conclusions. These mutations not only alter the formation of G4, but also affect at least three Sp1 binding sites that have been shown to be essential for the function of the hTERT promoter, from which the sequence is derived. The strong intermingling of G4 and Sp1 binding sites makes it impossible to determine whether all the observations made are dependent on G4 or Sp1 binding. As a control, the authors used Locked Nucleic Acid probes to prevent the formation of G4. As for mutations, these probes also interfere with two Sp1 binding sites. Therefore, using this alternative method has the same drawback as point mutations. This major issue should be discussed in the paper. It is also possible that other unidentified transcription factor binding sites are affected in the presented point mutants.
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Reviewer #3 (Public Review):
Summary:
The authors study the function of HCN channels in L2/3 pyramidal neurons, employing somatic whole-cell recordings in acute slices of visual cortex in adult mice and a bevy of technically challenging techniques. Their primary claim is a non-uniform HCN distribution across the dendritic arbor with a greater density closer to the soma (roughly opposite of the gradient found in L5 PT-type neurons). The second major claim is that multiple sources of long-range excitatory input (cortical and thalamic) are differentially affected by the HCN distribution. They further describe an interesting interplay of NMDAR and HCN, serotonergic modulation of HCN, and compare HCN-related properties at 1, 2 and 6 weeks of age. Several results are supported by biophysical simulations.
Strengths:
The authors collected data from both male and female mice, at an age (6-10 weeks) that permits comparison with in vivo studies, in sufficient numbers for each condition, and they collected a good number of data points for almost all figure panels. This is all the more positive, considering the demanding nature of multi-electrode recording configurations and pipette-perfusion. The main strength of the study is the question and focus.
Weaknesses:
Unfortunately, in its present form, the main claims are not adequately supported by the experimental evidence: primarily because the evidence is indirect and circumstantial, but also because multiple unusual experimental choices (along with poor presentation of results) undermine the reader's confidence. Additionally, the authors overstate the novelty of certain results and fail to cite important related publications. Some of these weaknesses can be addressed by improved analysis and statistics, resolving inconsistent data across figures, reorganizing/improving figure panels, more complete methods, improved citations, and proofreading. In particular, given the emphasis on EPSPs, the primary data (for example EPSPs, overlaid conditions) should be shown much more.
However, on the experimental side, addressing the reviewer's concerns would require a very substantial additional effort: direct measurement of HCN density at different points in the dendritic arbor and soma; the internal solution chosen here (K-gluconate) is reported to inhibit HCN; bath-applied cesium at the concentrations used blocks multiple potassium channels, i.e. is not selective for HCN (the fact that the more selective blocker ZD7288 was used in a subset of experiments makes the choice of Cs+ as the primary blocker all the more curious); pathway-specific synaptic stimulation, for example via optogenetic activation of specific long-range inputs, to complement / support / verify the layer-specific electrical stimulation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Authors suggest a new biomarker of chronic back pain with the option to predict the result of treatment. The authors found a significant difference in a fractional anisotropy measure in superior longitudinal fasciculus for recovered patients with chronic back pain.
Strengths:<br /> The results were reproduced in three different groups at different studies/sites.
Weaknesses:<br /> - The number of participants is still low.<br /> - An explanation of microstructure changes was not given.<br /> - Some technical drawbacks are presented.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors aimed to investigate the effectiveness of streptavidin imaging as an alternative to traditional antibody labeling for visualizing proteins within cellular contexts. They sought to address challenges associated with antibody accessibility and inconsistent localization by comparing the performance of streptavidin imaging with a TurboID-HA tandem tag across various protein localization scenarios, including phase-separated regions. They aimed to assess the reliability, signal enhancement, and potential advantages of streptavidin imaging over antibody labeling techniques.
Overall, the study provides a convincing argument for the utility of streptavidin imaging in cellular protein visualization. By demonstrating the effectiveness of streptavidin imaging as an alternative to antibody labeling, the study offers a promising solution to issues of accessibility and localization variability. Furthermore, while streptavidin imaging shows significant advantages in signal enhancement and preservation of protein interactions, the authors must consider potential limitations and variations in its application. Factors such as the fact that tagging may sometimes impact protein function, background noise, non-specific binding, and the potential for off-target effects may impact the reliability and interpretation of results. Thus, careful validation and optimization of streptavidin imaging protocols are crucial to ensure reproducibility and accuracy across different experimental setups.
Strengths:
- Streptavidin imaging utilizes multiple biotinylation sites on both the target protein and adjacent proteins, resulting in a substantial signal boost. This enhancement is particularly beneficial for several applications with diluted antigens, such as expansion microscopy or correlative light and electron microscopy.
- This biotinylation process enables the identification and characterization of interacting proteins, allowing for a comprehensive understanding of protein-protein interactions within cellular contexts.
Weaknesses:
- One of the key advantages of antibodies is that they label native, endogenous proteins, i.e. without introducing any genetic modifications or exogenously expressed proteins. This is a major difference from the approach in this manuscript, and it is surprising that this limitation is not really mentioned, let alone expanded upon, anywhere in the manuscript. Tagging proteins often impacts their function (if not their localization), and this is also not discussed.
- Given that BioID proximity labeling encompasses not only the protein of interest but also its entire interacting partner history, ensuring accurate localization of the protein of interest poses a challenge.
- The title of the publication suggests that this imaging technique is widely applicable. However, the authors did not show the ability to track the localization of several distinct proteins on the same sample, which could be an additional factor demonstrating the outperformance of streptavidin imaging compared with antibody labeling. Similarly, the work focuses only on small 2D samples. It would have been interesting to be able to compare this with 3D samples (e.g. cells encapsulated in an extracellular matrix) or to tissues.
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Reviewer #3 (Public Review):
Summary:
Cellulose is a major component of the primary cell wall of growing cells and it is made by cellulose synthases (CESAs) organized into multi-subunit complexes in the plasma membrane. Previous results have resolved the structure of secondary cell wall CESAs, which are only active in a subset of cells. Here, the authors evaluate the structure of CESAs from soybeans (Glycine max, Gm) via cryo-EM and compare these structures to secondary cell wall CESAs. First, they expressed GmCESA1, GmCESA3, or GmCESA6 in insect cells, purified these proteins as both monomers and homotrimers and demonstrated their capacity to incorporate 3H-labelled glucose into the cellulase-sensitive product in a pH and divalent cation (e.g., Mg2+) -dependant fashion (Figure 1). Although CESA1, CESA3, and a CESA6-like isoform are essential for cellulose synthesis in Arabidopsis, in this study, monomers and homotrimers both showed catalytic activity, and there was more variation between individual isoforms than between their oligomerization states (i.e., CESA3 monomers and trimers showed similar activities, which were substantially different from CESA1 monomers or trimers).
They next use cryo-EM to solve the structure of each homotrimer to ~3.0 to 3.3 A (Figure 2). They compare this with PttCESA8 and find important similarities, such as the unidentified density at a positively-charged region near Arg449, Lys452, and Arg453, and differences, such as the position and relatively low resolution (suggesting higher flexibility) of TM7, which presumably creates a large lateral lipid-exposed channel opening, rather than the transmembrane pore in PttCESA8. Like PttCESA8, an oligosaccharide in the translocation channel was co-resolved with the protein structure. Neither the N-terminal domains nor the CSRs (a plant-specific insert into the cytosolic loop between TM2 and TM3) are resolved well.
Several previous models have proposed that the cellulose synthase complexes may be composed of multiple heterotrimers, but since the authors were able to isolate beta-glucan-synthesizing homotrimers, their results challenge this model. Using the purified trimers, the authors investigated how the CESA homotrimers might assemble into higher-order complexes. They detected interactions between each pair of CESA homotrimers via pull-down assays (Figure 3), although these same interactions were also detected among monomers (Supplemental Figure 4). Neither catalytic activity nor these inter-homotrimer interactions required the N-terminal domain (Figure 4). When populations of homotrimers were mixed, they formed larger aggregations in vitro (Figure 4) and displayed increased activity, compared to the predicted additive activity of each enzyme alone (Figure 5). Intriguingly, this synergistic behavior is observed even when one trimer is chemically inactivated before mixing (Supplemental Figure 6), suggesting that the synergistic effects are due to structural interactions.
Strengths:
The main strength of this manuscript is its detailed characterization of the structure of multiple CESAs, which complements previous studies of secondary cell wall CESAs. They provide a comprehensive comparison of these new structures with previously resolved CESA structures and discuss several intriguing similarities and differences. The synergistic activity observed when different homotrimers are mixed is a particularly interesting result. These results provide fundamental in vitro support for a cellulose synthase complex comprised of a hexamer of CESA homotrimers.
Weaknesses:
There are several weaknesses in the manuscript. The authors do not present any data to indicate that GmCESA1, GmCESA3, and GmCESA6 are primary cell wall CESAs (e.g. expression patterns, phylogenetic evidence). Furthermore, their evidence that these proteins make cellulose in vitro is limited to the beta-glucanase-sensitive digestion of the product. Previous reports characterizing CESA structures have used multiple independent methods: sensitivity and resistance of the product to various enzymes, linkage analysis, and importantly, TEM of the product to ensure that it makes genuine cellulose microfibrils, rather than amorphous beta-glucan. Without demonstrating that GmCESA1, GmCESA3, and GmCESA6 are genuinely synthesizing cellulose microfibrils (via TEM) and that they are primary cell wall CESAs (via expression patterns & phylogenetic evidence), it is difficult to place the results into context. Finally, the authors indicate that they were unable to isolate heterotrimers in vitro, but they do not present any evidence of these experiments, which is essential to evaluate their conclusion that these CESAs operate as homotrimers in vitro.
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Reviewer #3 (Public Review):
The authors have investigated the effect of noncaloric monosaccharides on angiogenesis in the zebrafish embryo. These compounds are used as substitutes of sugars to sweeten beverages and they are commonly used by diabetic patients. The authors show that noncaloric monosaccharides and glucose similarly induce excessive blood vessel formation due to the increased formation of tip cells by endothelial cells. The authors show that this excessive angiogenesis involved the foxo1a-marcksl1a pathway.
A limitation of the study is that the mechanism of angiogenesis in the retinal circulation and in peripheral vasculature is certainly different.
This result suggests that these noncaloric monosaccharides share common side effects with glucose. Consequently, more caution should be taken with regard to the use of these artificial sweeteners. This work is of interest for better management of diabetes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This article is the first report to study the effects of T. pallidum on the neural development of an iSPC-derived brain organoid model. The study indicates that T. pallidum inhibits the differentiation of subNPC1B neurons into hindbrain neurons, hence affecting brain organoid neurodevelopment. Additionally, the TCF3 and notch signaling pathways may be involved in the inhibition of the subNPC1B-hindbrain neuron differentiation axis. While the majority of the data in this study support the conclusions, there are still some questions that need to be addressed and data quality needs to be improved. The study provides valuable insights for future investigations into the mechanisms underlying congenital neurodevelopment disability.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This study presents a solid framework for the metabolic modeling of microbial species and resources in the rhizosphere environment. It is an ambitious effort to tackle the huge complexity of the rhizosphere and reveal the plant-microbiota interactions therein. Considering previously published data by Berihu et al., going through a series of steps, the framework then finds associations between an apple tree disease state and both microbes and metabolites. The framework is well explained and motivated. I think that further work should be done to validate the method, both using synthetic data, with a known ground truth and following up on key findings experimentally.
Strengths:
- The manuscript is well written with a good balance between detail and readability. The framework steps are well-motivated and explained.
- The authors faithfully acknowledge the limitations of their approach and do not try to "over-sell" their conclusions.
- The presented framework has the potential for significant discovery if the hypotheses generated are followed up with experimental validation.
Weaknesses:
- When presenting a computational framework, best practices include running it on artificial (synthetic) data where the ground truth is known and therefore the precision and accuracy of the method may be assessed. This is not an optional step, the same way that positive/negative controls in lab experiments are not optional. Without this validation step, the manuscript is severely limited. The authors should ask themselves: what have we done to convince the reader that the framework actually works, at least on our minimal synthetic data?
Justification of claims and conclusions:
The claims and conclusions are sufficiently well justified since the limitations of this approach are acknowledged by the authors.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Authors performed a genome-wide CRISPR-based screen for synthetic lethal interactions in leukemic cells expressing a mutant form of PPM1D and identified SOD1. Loss of SOD1 or its inhibition with small molecule compounds reduced survival of the cells containing truncated PPM1D. Further analysis revealed that mitochondria are functionally deficient in PPM1D mutant cells resulting in increased levels of ROS. Surprisingly, expression profiling and reverse phase protein arrays revealed that PPM1D mutant cells did not respond appropriately to the increased levels of ROS. The precise molecular mechanism underlying this phenotype remains currently unclear, nevertheless the study convincingly shows that PPM1D mutant cells are vulnerable to oxidative stress.
Strengths:
Experimental procedures used in the study are appropriate and overall the presented data are very convincing. The study identified an important vulnerability of leukemic cells that carry PPM1D mutation and provides a fundamental background for testing SOD1 inhibitors in preclinical research. In the revised version of the manuscript, authors provide several new experiments that support their former conclusions. In particular, they showed that deletion of SOD1 in AML cells improved survival of the transplanted mice and this effect was more prominent when using cells carrying the mutant PPM1D. Further, they included an important control experiment that showed decreased SOD1 activity after treatment with ATN-224 inhibitor.
Weaknesses:
In the opinion of reviewer, there are no obvious weaknesses in this study. In broader view, the findings presented here using in vitro cultures will need to be validated in vivo by future research. Cell lines used in the study were generated by CRSIPR approaches in AML cells that have already been transformed. In addition, genome editing is inheritably connected with a risk of off target effects. It would therefore be great to identify AML samples carrying the PPM1D mutation that has been naturally selected during the transformation process.
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- Mar 2024
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
The authors comprehensively demonstrated the Cbfβ gene, which is involved in articular cartilage homeostasis, can promote articular cartilage regeneration and repair in osteoarthritis (OA) through regulating Hippo/YAP signaling TGF-β signaling, and canonical Wnt signaling. First, the authors demonstrated the deletion of Cbfβ can induce the OA phenotypes including decreased articular cartilage and osteoblasts, and increased osteoclasts and subchondral bone hyperplasia, and induce the early onset of OA. Additionally, the authors showed that the deficiency of Cbfβ in cartilage can increase canonical Wnt signaling and decrease TGF-β and Hippo signaling. Finally, the authors demonstrated that the overexpression of Cbfβ can inhibit Wnt signaling and enhance Hippo/YAP signaling in knee joints articular cartilage of ACLT-induced OA mice and protect against ACLT-induced OA. The manuscript is overall well-constructed, and the authors provided evidence to support their findings.
In Fig. 7I, it could be better to show the statistical analysis between normal and AAV-mediated Cbfβ ACLT mice groups.
In Fig. 9H-K, in the quantification analysis, the OARSI score in the DMM+AAV-YFP group is higher than in the sham group significantly. However, the SO staining results appear to show no significant difference between the DMM+AAV-luc-YFP group (Fig. 9I) and the sham group (Fig. 9H).
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Reviewer #3 (Public Review):
The authors first characterize their mouse model of pancreatic cancer and show that CYRI-B mRNA is detectable in pancreatic lesions and that its amount increases over time. They also show that genetic deletion of CYRI-B accelerates pancreatic ductal adenocarcinoma (PDAC), leading to lower survival of mice. This is accompanied by higher levels of phospho-(i.e. activated)-JNK and -ERK, which are likely two of the factors driving cancer cell proliferation. Using in vivo transplantation, the authors further demonstrate that cancer cells depleted for CYRI-B exhibit decreased numbers of metastases in the mesentery, despite showing similar proliferation as control cells.<br /> Cancer cell migration can be driven by LPA, which binds LPAR1 at the surface of PDAC cells. Investigation of chemotactic migration of cancer cells towards fetal bovine serum as a source of LPA further shows that cancer cells depleted for CYRI-B and expressing GFP as control exhibit strongly reduced chemotactic migration, while cells re-expressing CYRI-B-GFP show normal chemotactic migration. Furthermore, this restored migration is blocked by using the LPAR1/3 inhibitor K116425, showing that CYRI-B is required for the chemotactic migration of PDAC cells in a gradient of serum LPA.
Using live cell imaging, the authors show that CYRI-B-GFP and LPAR1-mCherry localize to macropinocytic cups and to macropinosomes, indicating that LPAR1 can be internalized by PDAC cells through macropinocytosis. This notion is supported by immunofluorescence analyses showing that PDAC cells depleted for CYRI-B have reduced LPAR1-mCherry internalization upon stimulation with LPA, compared to cells rescued by CYRI-B-GFP expression. Collectively, the authors suggest that CYRI-B regulates macropinocytic uptake of LPAR1, thus regulating the chemotactic migration of PDAC cells towards LPA, which supports the metastasis of pancreatic cancer.
This is an interesting manuscript that makes a convincing case for the involvement of CYRI-B as a driver of PDAC. A particular strength is the expert use of different mouse models and derived cancer cell lines. The major conclusions are supported by the data presented. The results could be further strengthened by detecting CYRI-B protein (in addition to mRNA) in cancer lesions and also by staining endogenous CYRI-B and LPAR1 in the macropinocytosis experiments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
The submitted paper by Hoving et al addresses the role of N-cadherin in Schwann cell collective cell migration and its previously unknown relationship with the slit/robo signaling pathway. The main conclusion is that N-cadherin has two distinct functions. One that is dependent on its classical role as a cell-cell junction protein promoting cell clustering and one that promotes cell repulsion and polarity independently of the formation of cell adhesion complexes. The second function is mediated by the Slit/Robo pathway. It is proposed that N-cadherin and Glypican-4 act together to present Slit2/3 at the surface of Schwann cells in order to trigger Robo signaling on neighboring cells.
The data about N-cadherin loss of function and the associated rescue experiments with the various truncated forms of N-cadherin are well substantiated by proper controls for efficiency and specificity. They show that the extracellular domain of Ncadherin is the one required for the repulsive effect. The experiments performed to distinguish the roles in adhesion and repulsion seem clear and conclusive. In addition, the fact the slit signal needs to be provided in a polarized manner for directional migration to occur is also clearly demonstrated in vitro and on slice assays. Overall the model that Ncadherin plays two different roles, a repulsive one via presentation of slit at the cell surface and a cell adhesion one via formation of adherens junctions, is well supported by the data and will be of interest beyond the subfield of the authors.
However, other parts of the manuscript seem weaker. If N-cadherin presentation of the Slit signal is so critical why are repulsion rates still very high in cells without N-cadherin? Same is observed with Glypican4 knockdowns. In both loss of function 50% of cell collisions lead to repulsion (compared to 70% amongst control cells). While significant such drop remains modest. The authors propose a cooperative role of Glypican-4 and N-cadherin at the cell surface as co-binding factors for Slit2/3 but they have not checked whether double knockdown of N-cad and Glypican4 might have a stronger effect. Could Glypican and N-cadherin present Slit at the cell surface independently in a somewhat redundant manner? Can Glypican and Slit interact physically in absence of N-cadherin? They also have not further analyzed the putative colocalization fo Ncad and Glypican at the cell surface.
The data supporting a role for N-cadherin in Slit's trafficking to the cell surface seem also circumstantial. While western blot data seem to indicate no change in Slit protein level after N-cad knockdown, immunostaining for Slit in such condition show a dramatic loss of Slit signal. These two independent data sets are difficult to reconcile and are not designed to address whether Slit reaches the cell surface in control or N-cadherin knockdown conditions.
If Slit signaling is so critical for repulsion why in double sit2/3 knockdown 40% of collisions still lead to repulsion. Also, no analysis of cell collision are provided upon Robo1/2 knockdown for comparison with Slit knockdowns. Altogether, these relatively mild effects of n-cad, slit or glypican knockdown on repulsion seem to indicate that other signals might contribute to contact-inhibition and polarization/repulsion of cells upon physical contact but this is unfortunately not discussed. All statements related to cell polarity stem from the overall cell morphology without being substantiated by actual polarity analysis (using markers such as detection of Rac-GTP or using a proxy such as the golgi-nucleus axis). The authors present the cell cluster generated after Sox2 expression and Sox2 + exposure to recombinant Slit2 as lacking polarity, however in one case cells do not present any flat membrane at their free edge whereas in the other case they do. This suggests a minimal cell polarity with a protrusive-like organization away from the contact. Finally, Robo1/2 siRNA knockdown are used but contrary to the other loss of functions it seems that controls for knockdown efficiency/specificity were not provided.
Therefore, while the study is overall well documented and based on solid data, some weaknesses exist.
The overall topic is clearly of broad interest as N-cadherin is protein essential in various biological settings from development to disease but the range of its biological functions remains to be fully explored. This study clearly adds to the current knowledge and how N-cadherin might act in vivo and in particular how it could mediate crosstalks between various signaling pathways.
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Reviewer #3 (Public Review):
B cell receptors are produced through a combination of random V(D)J recombination and somatic hypermutation. Identifying clonal lineages - cells that descend from a common V(D)J rearrangement - is an important part of B cell repertoire analysis. Here, the authors developed a new method to identify clonal lineages from BCR data. This method builds off of prior advances in the field and uses both an adaptive clonal distance threshold and shared somatic hypermutation information to group B cells into clonal lineages.
The major strength of this paper is its thorough quantitative treatment of the subject and integration of multiple improvements into the clonal clustering process. By their simulation results, the method is both highly efficient and accurate.
The only notable weakness we identified is that much of the impact of the method will depend on its superiority to existing approaches, and this is not convincingly demonstrated by Fig. 4. In particular, little detail is given on how the other clonal clustering programs were run, and this can significantly impact their performance. More specifically:
(1) Scoper supports multiple methods for clonal clustering, including both adaptive CDR3 distance thresholds (Nouri and Kleinstein, 2018) and shared V-gene mutations (Nouri and Kleinstein, 2020). It is not clear which method was used for benchmarking. The specific functions and settings used should have been detailed and justified. Spectral clustering with shared V gene mutations would be the most comparable to the authors' method. Similar detail is needed for partis.<br /> (2) It is not clear how the adaptive thresholds and shared mutation analysis in the authors' method differ from prior approaches such as scoper and partis.<br /> (3) The scripts for performing benchmarking analyses, as well as the version numbers of programs tested, are not available.<br /> (4) Similar to above, P. 10 describes single linkage hierarchical clustering with a fixed threshold as a "crude method" that "suffers from inaccuracy as it loses precision in the case of highly-mutated sequences and junctions of short length." As far as we could tell, this statement is not backed up by either citations or analyses in the paper. It should not be difficult for the authors to test this though using their simulations, as this method is also implemented in scoper.
References<br /> Nouri N, Kleinstein SH. 2020. Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data. PLOS Comput Biol 16:e1007977. doi:10.1371/journal.pcbi.1007977<br /> Nouri N, Kleinstein SH. 2018. A spectral clustering-based method for identifying clones from high-throughput B cell repertoire sequencing data. Bioinformatics 34:i341-i349. doi:10.1093/bioinformatics/bty235
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Reviewer #3 (Public Review):
Mohseni and Elhaik challenge the widespread use of PCA as an analytical and interpretive tool in the study of geometric morphometrics. The standard approach in geometric morphometrics analysis involves Generalised Procrustes Analysis (GPA) followed by Principal Component Analysis (PCA). Recent research challenges PCA outcomes' accuracy, robustness, and reproducibility in morphometrics analysis. In this paper, the authors demonstrate that PCA is unreliable for such studies. Additionally, they test and compare several Machine-Learning methods and present MORPHIX, a Python package of their making that incorporates the tools necessary to perform morphometrics analysis using ML methods.
Mohseni and Elhaik conducted a set of thorough investigations to test PCA's accuracy, robustness, and reproducibility following renewed recent criticism and publications where this method was abused. Using a set of 2 and 3D morphometric benchmark data, the authors performed a traditional analysis using GPA and PCA, followed by a reanalysis of the data using alternative classifiers and rigorous testing of the different outcomes.
In the current paper, the authors evaluated eight ML methods and compared their classification accuracy to traditional PCA. Additionally, common occurrences in the attempted morphological classification of specimens, such as non-representative partial sampling, missing specimens, and missing landmarks, were simulated, and the performance of PCA vs ML methods was evaluated.
The main problem with this manuscript is that it is three papers rolled into one, and the link doesn't work. The title promises a new Python package, but the actual text of the manuscript spends relatively little time on the Python package itself and barely gives any information about the package and what it includes or its usefulness. It is definitely not the focus of the manuscript. The main thrust of the manuscript, which takes up most of the text, is the analysis of the papionin dataset, which shows very convincingly that PCA underperforms in virtually all conditions tested. In addition, the manuscript includes a rather vicious attack against two specific cases of misuse of PCA in paleoanthropological studies, which does not connect with the rest of the manuscript at all.
If the manuscript is a criticism of PCA techniques, this should be reflected in the title. If it is a report of a new Python package, it should focus on the package. Otherwise, there should be two separate manuscripts here.
The criticism of PCA is valid and important. However, pointing out that it is problematic in specific cases and is sometimes misused does not justify labeling tens of thousands of papers as questionable and does not justify vilifying an entire discipline. The authors do not make a convincing enough case that their criticism of the use of PCA in analyzing primate or hominin skulls is relevant to all its myriad uses in morphometrics. The criticism is largely based on statistical power, but it is framed as though it is a criticism of geometric morphometrics in general.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Drug resistance is a perennial problem for malaria control and strategies to prevent the acquisition and spread of drug resistance mutations are desperately needed. One strategy is to identify drug resistance mutations that arise in blood-stage parasites, but cannot be readily spread to a new human host. Since malaria parasites must survive and replicate in mosquitoes in order to be transmitted, mutations with elevated mosquito-stage fitness defects will not spread efficiently. Buchanan and coworkers focus on the drug azithromycin and its known role of inhibiting the ribosomes found in parasite apicoplast organelles. Apicoplast organelles are known to have elevated metabolic activity in mosquito stage parasites and azithromycin resistance mutations could interfere with mosquito stage parasite development and parasite transmission.
To address this hypothesis, azithromycin-resistant P. berghei and P. falciparum parasites were generated and analyzed for transmission defects. All lines had mutations in the apicoplast ribosomal protein Rpl4 consistent with the known role of azithromycin inhibiting the 50S ribosomal subunit. Overall, the three lines (3 berghei and one falciparum) had phenotypes that should limit parasite transmission, however, detailed characterization showed that there were surprising differences between the two parasite species and even between the P. berghei lines. The P. berghei lines produced fewer oocysts and sporozoites with aberrant apicoplast morphology compared to wild-type controls. Sporozoites from azithromycin-resistant lines appeared to have motility defects and typically were not able to infect mice (one strain produced infections when 10,000 sporozoites were injected, but not when 1,000 were).
By contrast, the azithromycin-resistant P. falciparum strain did not display any mosquito-stage phenotypes and produced motile sporozoites with intact apicoplast organelles. These sporozoites, however, developed abnormally in a humanized mouse model with reduced liver-stage nuclear division and abnormal apicoplast morphology. These defects combined with a five-fold lower prevalence suggest that azithromycin-resistant P. falciparum parasites experience significant fitness costs during liver stage development (at least those harboring the G76V mutation).
Strengths:
This work was carefully conducted and transparently presented. It provides a comprehensive view of how parasite development is impacted by azithromycin resistance mutations during the mosquito and liver stages in P. berghei and P. falciparum. It adds a new dimension to the growing literature on the transmissibility of drug-resistant parasites, by showing that mutations in the apicoplast genome can impact transmission.
Weaknesses:
Whether these liver-stage defects in P. falciparum are severe enough to completely block subsequent blood-stage infection remains to be seen and would require experiments with humanized mice continuously grafted with human red blood cells - a difficult and expensive model system.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this manuscript, the authors describe a novel mode of release of small extracellular vesicles. These small EVs are released via the rupture of the membrane of so-called amphiectosomes that resemble "morphologically" Multivesicular Bodies.
These structures have been initially described by the authors as released by colorectal cancer cells (https://doi.org/10.1080/20013078.2019.1596668). In this manuscript, they provide experiments that allow us to generalize this process to other cells. In brief, amphiectosomes are likely released by ectocytosis of amphisomes that are formed by the fusion of multivesicular endosomes with autophagosomes. The authors propose that their model puts forward the hypothesis that LC3 positive vesicles are formed by "curling" of the autophagosomal membrane which then gives rise to an organelle where both CD63 and LC3 positive small EVs co-exist and would be released then by a budding mechanism at the cell surface that appears similar to the budding of microvesicles /ectosomes. Very correctly the authors make the distinction from migrasomes because these structures appear very similar in morphology.
Strengths:
The findings are interesting despite that it is unclear what would be the functional relevance of such a process and even how it could be induced. It points to a novel mode of release of extracellular vesicles.
Weaknesses:
This reviewer has comments and concerns concerning the interpretation of the data and the proposed model. In addition, in my opinion, some of the results in particular micrographs and immunoblots (even shown as supplementary data) are not of quality to support the conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
White et al. described laser-induced wound healing of the Drosophila pupal notum. They found that the epithelial monolayer is dynamically induced to form syncytia by cell-cell fusion as an important part of repair. They reveal two processes: cell shrinking and border breakage that occur as part of syncytia formation. Expression of GFP in the cytoplasms of some epithelial cells reveals that cytoplasmic contents mix following injury and the GFP rapidly diffuses between cells. Using live imaging they observe that syncytia expand towards the wound, maintain their positions close to the leading edge, and apparently displace smaller cells. They propose that syncytia redistribute cellular components towards the wound facilitating repair and show that labelled actin becomes concentrated at the leading edge.
Strengths:
The manuscript is interesting and on an important and emerging topic of wound healing in a genetically tractable organism. The manuscript is very well written.
Weaknesses:
There are three major issues that the authors must address:
(1) Is cell-cell fusion sufficient to enhance/facilitate wound healing?
(2) Characterization of "border breakdown"; Is this phenomenon disassembly of apical junctions following membrane fusion?
(3) Are cells really shrinking or is it only the apical domains that "shrink" as the cells join the syncytium?
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Reviewer #3 (Public Review):
Summary:
In this manuscript, Weng et al. detect a neuron-specific transcriptome that regulates aging. The authors first profile neuron-specific responses during aging at a time point where a loss in memory function is present. They discover signatures unique to neurons which validate their pipeline and reveal the loss of neuron identity with age. For example, old neurons reduce the expression of genes related to synaptic function and neuropeptide signaling and increase the expression of chromatin regulators, insulin peptides, and glycoproteins. The authors discover the detrimental effect of selected upregulated genes (utx-1, ins-19, and nmgp-1) by knocking them down in the whole body and detecting improvement of short memory functions. They then use their pipeline to test neuronal profiles of long-lived insulin/IGF mutants. They discover that genes related to stress response pathways are upregulated upon longevity (e.g. dod-24, F08H9.4) and that they are required for improved neuron function in long-lived individuals.
Strengths:
Overall, the manuscript is well-written, and the experiments are well-described. The authors take great care to explain their reasoning for performing experiments in a specific way and guide the reader through the interpretation of the results, which makes this manuscript an enjoyable and interesting read. Using neuron-specific transcriptomic analysis in aged animals the authors discover novel regulators of learning and memory, which underlines the importance of cell-specific deep sequencing. The time points of the transcriptomic profiling are elegantly chosen, as they coincide with the loss of memory and can be used to specifically reveal gene expression profiles related to neuron function. The authors showcase on the dod-24 example how powerful this approach is. In long-lived insulin/IGF-1 receptor mutants body-wide dod-24 expression differs from neuron-specific profiles. Importantly, the depletion of dod-24 has an opposing effect on lifespan and learning memory. The dataset will provide a useful resource for the C. elegans and aging community.
Weaknesses:
While this study nicely describes the neuron-specific profiles, the authors do not test the relevance in a tissue-specific way. It remains unclear if modifying the responses only in neurons has implications for either memory or potentially for lifespan. The authors point to this in the text and refer to tissue-specific datasets. However, it is possible that the tissue-specific profile changes with age. The authors should consider mining publicly available cell-specific aging datasets and performing neuron-specific RNAi to test the functional relevance of the neuron-specific response. This would strengthen the importance of cell-specific profiling.
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Reviewer #3 (Public Review):
Summary:
The authors have created DHCR24 knockin mice and noted changes in the sperm sterol composition. Concurrently, alterations in the quantity, motility, and function of the sperm in DHCR24 knockin mice were identified.
Strengths:
The manuscript offers an intriguing perspective on how disruptions in sperm sterol composition can lead to sperm abnormalities.
Weaknesses:
From the current data, several issues remain to be clarified, including the fertility test results, which merit a more detailed presentation to ascertain whether differences stem from individual variability or overall changes. The authors suggest an increase in ROS in the sperm of DHCR24 knockin mice, leading to sperm damage, which also requires further confirmation. Moreover, the quality of some data requires verification or improvement, such as the morphological analysis of testicular sections and the OCR experiments.
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Reviewer #3 (Public Review):
The author presents a novel theory and computational model suggesting that grid cells do not encode space, but rather encode non-spatial attributes. Place cells in turn encode memories of where those specific attributes occurred. The theory accounts for many experimental results and generates useful predictions for future studies. The model's simplicity and potential explanatory power will interest others in the field, though there are a number of concerns that should first be addressed.
A crucial assumption of the model is that the content of experience must be constant in space. It's difficult to imagine a real-world example that satisfies this assumption. Odors and sounds are used as examples. While they are often more spatially diffuse than an objects on the ground, odors and sounds have sources that are readily detectable. Animals can easily navigate to a food source or to a vocalizing conspecific. This assumption is especially problematic because it predicts that all grid cells should become silent when their preferred non-spatial attribute (e.g. a specific odor) is missing. I'm not aware of any experimental data showing that grid cells become silent. On the contrary, grid cells are known to remain active across all contexts that have been tested, including across sleep/wake states. Unlike place cells, grid cells do not seem to turn off. Since grid cells are active in all contexts, their preferred attribute must also be present in all contexts, and therefore they would not convey any information about the specific content of an experience.
The proposed novelty of this theory is that other models all assume that grid cells encode space. This isn't quite true of models based on continuous attractor networks, the discussion of which is notably absent. More specifically, these models focus on the importance of intrinsic dynamics within the entorhinal cortex in generating the grid pattern. While this firing pattern is aligned to space during navigation and therefore can be used as a representation of that space, the neural dynamics are preserved even during sleep. Similarly, it is because the grid pattern does not strictly encode physical space that grid-like signals are also observed in relation to other two-dimensional continuous variables.
The use of border cells or boundary vector cells as the main (or only) source of spatial information in the hippocampus is not well supported by experimental data. Border cells in the entorhinal cortex are not active in the center of an environment. Boundary-vector cells can fire farther away from the walls but are not found in the entorhinal cortex. They are located in the subiculum, a major output of the hippocampus. While the entorhinal-hippocampal circuit is a loop, the route from boundary-vector cells to place cells is much less clear than from grid cells. Moreover, both border cells and boundary-vector cells (which are conflated in this paper) comprise a small population of neurons compared to grid cells.
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Reviewer #3 (Public Review):
In this manuscript, Berger et al. study how internal energy storage influence learning and memory. Since in Drosophila melanogaster, octopamine (OA) is involved in the regulation of energy homeostasis they focus on the roles of OA. To do so they use the tyramine-β-hydroxylase (Tbh) mutant that is lacking the neurotransmitter OA and study short term memory (STM), long-term memory (LTM) and anesthesia-resistant memory (ARM). They show that the duration of starvation affects the magnitude of both short- and long-term memory. In addition, they show that OA has a suppressive effect on learning and memory. In terms of energy storage, they show that internal glycogen storage influences how long sucrose is remembered, and high glycogen suppresses memory. Finally, they show that insulin-like signaling in octopaminergic neurons, which is also related to internal energy storage, suppresses learning and memory.
The revised version of the manuscript is greatly improved, and I thank the authors for taking the comment seriously. This is an important study that extends our knowledge on OA activity in learning and memory and the effects the metabolic state has on learning and memory. The authors nicely use the genetic tools available in flies to try and unravel the complex circuitry of metabolic state level, OA activity and learning and memory. The overall take-home message of the manuscript is clear and supported by the data presented.
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Reviewer #3 (Public Review):
The manuscript by Mahapatra and Takahashi addresses the role of presynaptic release site clearance during sustained synaptic activity. The authors characterize the effects of pharmacologically interfering with SV endocytosis (pre-incubation with Dynasore or Pitstop-2) on synaptic short-term plasticity (STP) at two different CNS synapses (calyx of Held synapses and hippocampal SC to CA1 synapses) using patch-clamp recordings in acute slices under experimental conditions designed to closely mimic a physiological situation (37{degree sign}C and 1.3 mM external [Ca2+]). Endocytosis blocker-induced changes in STP and in the recovery from short-term depression (STD) are compared to those seen after pharmacologically inhibiting actin filament assembly (pre-incubation with Latrunculin-B or the selective Cdc42 GTPase inhibitor ML-141). Presynaptic capacitance (Cm) recordings in calyx terminals were used to establish the effects of the pharmacological maneuvers on SV endocytosis.<br /> Latrunculin-B and ML-141 neither affect SV endocytosis (assayed by Cm recordings) nor EPSC recovery following conditioning trains, but strongly enhances STD at calyx synapses. No changes in STP were observed at Latrunculin-B- or ML-141-treated SC to CA1 synapses.
Dynasore and Pitstop-2 slow down endocytosis, limit the total amount of exocytosis in response to long stimuli, enhance STD in response to 100 Hz stimulation, but profoundly accelerate EPSC recovery following conditioning 100 Hz trains at calyx synapses. At SC to CA1 synapses, Dynasore and Pitstop-2 reduce the extend of facilitation and lower relative steady-state EPSCs suggesting a change in the facilitation-depression balance in favor of the latter.
The authors use state-of-the art techniques and their data, which is clearly presented, leads to authors to conclude that endocytosis is universally important for clearance of release sites while the importance of scaffold protein-mediated site clearance is limited to 'fast synapses'.
Unfortunately, and perhaps not completely unexpected in view of the pharmacological tools chosen, there are several observations which remain difficult to understand:
(1) Blocking site clearance affects release sites that have previously been used, i.e. sites at which SV fusion has occurred and which therefore need to be cleared. Calyces use at most 20% of all release sites during a single AP, likely fewer at 1.3 mM external [Ca2+]. Even if all those 20% of release sites become completely unavailable due to a block of release site clearance, the 2nd EPSC in a train should not be reduced by >20% because ~80% of the sites cannot be affected. However, ~50% EPSC reduction was observed (Fig. 2B1, lower right panel) raising the possibility that Dynasore does more than specifically interfering with SVs endocytosis (and possibly Pitstop as well). Non-specific effects are also suggested by the observed two-fold increase in initial EPSC size in SC to CA1 synapses after Dynasore pre-incubation.
(2) More severe depression was observed at calyx synapses after blocking endocytosis which the authors attribute to a presynaptic mechanism affecting pool replenishment. When probing EPSC recovery after conditioning 100 Hz trains, a speed up was observed mediated by an "unknown mechanism" which is "masked in 2 mM [Ca2+]". These two observations, deeper synaptic depression during 100 Hz but faster recovery from depression following 100 Hz, are difficult to align and no attempt was made to find an explanation.
(3) To reconcile previous data reporting a block of Ca2+-dependent recovery (CDR) by Dynasore or Latrunculin (measured at 2 mM external [Ca2+]) with the data presented here (using 1.3 mM external [Ca2+]) reporting no effect or a speed up of recovery from depression, the authors postulate that "CDR may operate only when excessive Ca2+ enters during massive presynaptic activation" (page 10 line 244). While that is possible, such explanation ignores plenty of calyx studies demonstrating fiber stimulation-induced CDR and elucidating molecular pathways mediating fiber stimulation-induced CDR, and it also completely dismisses the strong change in recovery time course after 10 Hz conditioning (single exponential) as compared to 100 Hz conditioning (double exponential with a pronounced fast component).
Strong presynaptic stimuli such as those illustrated in Figs. 1B,C induce massive exocytosis. The illustrated Cm increase of 2 to 2.5 pF represents fusion of 25,000 to 30,000 SVs (assuming a single SV capacitance of 80 aF) corresponding to a 12 to 15% increase in whole terminal membrane surface (assuming a mean terminal capacitance of ~16 pF). Capacitance measurements can only be considered reliable in the absence of marked changes in series and membrane conductance. Documentation of the corresponding conductance traces is therefore advisable for such massive Cm jumps and merely mentioning that the first 450 ms after stimulation were skipped during analysis or referring to previous publications showing conductance traces is insufficient.<br /> All bar graphs in Figures 1 through 6 and Figures S3 through S6 compare three or even four (Fig. 5C) conditions, i.e. one control and at least two treatment data sets. It appears as if repeated t-tests were used to run multiple two-group comparisons (i.e. using the same control data twice for two different comparisons). Either a proper multiple comparison test should be used or a Bonferroni correction or similar multiple-comparison correction needs to be applied.
Finally, the terminology of contrasting "fast-signaling" (calyx synapses) and "slow-plastic" (SC synapses) synapses seems to imply that calyx synapses lack plasticity, as does the wording "conventional bouton-type synapses involved in synaptic plasticity" (page 11, line 251). I assume, the authors primarily refer to the maximum frequencies these two synapse types typically transmit (fast-signaling vs slow-signaling)?
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Reviewer #3 (Public Review):
Summary:
This study concerns how macaque visual cortical area MT represents stimuli composed of more than one speed of motion.
Strengths:
The study is valuable because little is known about how the visual pathway segments and preserves information about multiple stimuli. The study presents compelling evidence that (on average) MT neurons represent the average of the two speeds, with a bias that accentuates the faster of the two speeds. An additional strength of the study is the inclusion of perceptual reports from both humans and one monkey participant performing a task in which they judged whether the stimuli involved one vs two different speeds. Ultimately, this study raises intriguing questions about how exactly the response patterns in visual cortical area MT might preserve information about each speed, since such information could potentially be lost in an average response as described here, depending on assumptions about how MT activity is evaluated by other visual areas.
Weaknesses:
My main concern is that the authors are missing an opportunity to make clear that the divisive normalization, while commonly used to describe neural response patterns in visual areas (and which fits the data here), fails on the theoretical front as an explanation for how information about multiple stimuli can be preserved. Thus, there is a bit of a disconnect between the goal of the paper - how does MT represent multiple stimuli? - and the results: mostly averaging responses which, while consistent with divisive normalization, would seem to correspond to the perception of a single intermediate speed. This is in contrast to the psychophysical results which show that subjects can at least distinguish one from two speeds. The paper would be strengthened by grappling with this conundrum in a head-on manner.
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Reviewer #3 (Public Review):
Summary:
In order to study the factors and neural dynamics that lead to the suppression of irrelevant information in the brain, the authors trained artificial neural networks in the execution of a task that involved the discrimination of complex stimuli with three main features: color, shape, and width. Specific combinations of color and shape led to a reward, but the temporal structure made color dynamically irrelevant at the beginning of the trial, and then it became relevant once the shape was presented. On the other hand, the width of the stimulus was always irrelevant. Importantly, non-human primates were also trained to execute this task (in a previous study by the authors) and the activity from neural populations from the dorsolateral Prefrontal Cortex (dlPFC) was recorded, allowing to compare the coding of information by the artificial neural network model with what happens in biological neural populations.
The authors changed systematically the amount of noise present in the neural network model, as well as limiting the firing rate of the artificial neurons to simulate the limitations imposed by high metabolic costs in biological neurons. They found that models with medium and low noise, as well as medium and low metabolic cost, developed information encoding patterns that resembled the patterns observed throughout learning in the dlPFC, as follows: early in the learning process, color information was strongly represented during the whole trial, as well as shape and width, whereas the color/shape combination significance (XOR operation) was weakly encoded. Late in learning, color information was initially suppressed (while it was deemed irrelevant) and became more prominent during the shape presentation. Width information coding decreased, and the XOR operation result became more strongly encoded.
Subthreshold activity dynamics were studied by training artificial networks consisting of 2 neurons, with the aim of understanding how dynamically irrelevant information is suppressed and then encoded more strongly at a different time during the trial. Under medium noise and medium metabolic cost, color information is suppressed by the divergence of the activity away from the level that triggers spikes. The authors claim that this subthreshold dynamic explains the suppression of irrelevant information in biological neural networks.
Strengths:
The study leverages the power of computational models to simulate biological networks and do manipulations that are difficult (if not impossible) to perform in vivo. The analyses of the activity of the network model are neat and thorough and provide a clear demonstration of how noise and metabolic costs may affect the information coding in the brain. The mathematical analyses are rigorous and nicely documented.
Weaknesses:
The study does not leverage the fact that they have access to the activity of individual neurons both on a neural network model and in neural recordings. The model/brain comparison results are limited to the decodability of different pieces of information during the execution of the task at different stages of learning. It would have been useful if the authors had shown response profiles of individual neurons, both biological and artificial, to strengthen the claim that the activity patterns are similar. Perhaps showing that the firing rates vary in a similar way in the large models (like they do for the 2-neuron model) would have been informative. For instance, it is possible that suppression is not occurring in the dlPFC, but that the PFC receives input with this information already suppressed. If suppression indeed happens in the PFC, response profiles associated with this process may be observed.
There is no way to say that the 2-neuron models are in any way informative of what happens in brain neurons, or even larger artificial networks since the sources of sensory input, noise, and inhibition will differ between biological and artificial networks. And because the firing patterns are not shown for large networks, it is not clear if some non-coding artificial neurons will become broadly inhibitory but maintain a relatively high firing rate (to mention only one possibility).
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Reviewer #3 (Public Review):
Summary
In their manuscript, Vickers and McCormick have demonstrated the potential of leveraging mesoscale two-photon calcium imaging data to unravel complex behavioural motifs in mice. Particularly commendable is their dedication in providing detailed surgical preparations and corresponding design files, a contribution that will greatly benefit the broader neuroscience community as a whole. The quality of the data is high and examples are available to the community. More importantly, the authors have acquired activity-clustered neural ensembles at an unprecedented spatial scale to further correlate with high level behaviour motifs identified by B-SOiD. Such an advancement marks a significant contribution to the field. While the manuscript is comprehensive and the analytical strategy proposed is promising, some technical aspects warrant further clarification. Overall, the authors have presented an invaluable and innovative approach, effectively laying a solid foundation for future research in correlating large scale neural ensembles with behavioural. The implementation of a custom sound insulator for the scanner is a great idea and should be something implemented by others.
This is a methods paper, but there is no large diagram (in the main figures) that shows how all the parts are connected, communicating and triggering between each other. This is described in the methods and now supplemental figure, but a visual representation would greatly benefit the readers looking to implement something similar as a main figure but I guess they can find it in the methods. No stats for the results shown in Figure 6e, it would be useful to know which of these neural densities for all areas show a clear statistical significance across all the behaviors. While I understand that this is a methods paper, it seems like the authors are aware of the literature surrounding large neuronal recordings during mouse behavior. Indeed, in line 178-179 the authors mention how a significant portion of the variance in neural activity can be attributed to changes in "arousal or self-directed movement even during spontaneous behavior." Why then did the authors not make an attempt at a simple linear model that tries to predict the activity of their many thousands of neurons by employing the multitude of regressors at their disposal (pupil, saccades, stimuli, movements, facial changes, etc). These models are straightforward to implement, and indeed it would benefit this work if the model extracts information on par with what it's known from the literature. We also realize such a model could be done in the future.
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Reviewer #3 (Public Review):
Summary:
The authors established a new virtual reality place preference task. On the task, rats, which were body-restrained on top of a moveable Styrofoam ball and could move through a circular virtual environment by moving the Styrofoam ball, learned to navigate reliably to a high-reward location over a low-reward location, using allocentric visual cues arranged around the virtual environment.
The authors also showed that functional inhibition by bilateral microinfusion of the GABA-A receptor agonist muscimol, which targeted the dorsal or intermediate hippocampus, disrupted task performance. The impact of functional inhibition targeting the intermediate hippocampus was more pronounced than that of functional inhibition targeting the dorsal hippocampus.
Moreover, the authors demonstrated that the same manipulations did not significantly disrupt rats' performance on a virtual reality task that required them to navigate to a spherical landmark to obtain reward, although there were numerical impairments in the main performance measure and the absence of statistically significant impairments may partly reflect a small sample size (see comments below).
Overall, the study established a new virtual-reality place preference task for rats and established that performance on this task requires the dorsal to intermediate hippocampus. They also established that task performance is more sensitive to the same muscimol infusion (presumably - doses and volumes used were not clearly defined in the manuscript, see comments below) when the infusion was applied to the intermediate hippocampus, compared to the dorsal hippocampus, although this does not offer strong support for the authors claim that dorsal hippocampus is responsible for accurate spatial navigation and intermediate hippocampus for place-value associations (see comments below).
Strengths:
(1) The authors established a new place preference task for body-restrained rats in a virtual environment and, using temporary pharmacological inhibition by intra-cerebral microinfusion of the GABA-A receptor agonist muscimol, showed that task performance requires dorsal to intermediate hippocampus.
(2) These findings extend our knowledge about place learning tasks that require dorsal to intermediate hippocampus and add to previous evidence that, for some place memory tasks, the intermediate hippocampus may be more important than other parts of the hippocampus, including the dorsal hippocampus, for goal-directed navigation based on allocentric place memory.
(3) The hippocampus-dependent task may be useful for future recording studies examining how hippocampal neurons support behavioral performance based on place information.
Weaknesses:<br /> (1) The new findings do not strongly support the authors' suggestion that the dorsal hippocampus is responsible for accurate spatial navigation and the intermediate hippocampus for place-value associations.
The authors base this claim on the differential effects of the dorsal and intermediate hippocampal muscimol infusions on different performance measures. More specifically, dorsal hippocampal muscimol infusion significantly increased perimeter crossings and perimeter crossing deviations, whereas dorsal infusion did not significantly change other measures of task performance, including departure direction and visits to the high-value location. However, these statistical outcomes offer only limited evidence that dorsal hippocampal infusion specifically affected the perimeter crossing, without affecting the other measures. Numerically the pattern of infusion effects is quite similar across these various measures: intermediate hippocampal infusions markedly impaired these performance measures compared to vehicle infusions, and the values of these measures after dorsal hippocampal muscimol infusion were between the values in the intermediate hippocampal muscimol and the vehicle condition (Figures 5-7). Moreover, I am not so sure that the perimeter crossing measures really reflect distinct aspects of navigational performance compared to departure direction and hit rate, and, even if they did, which aspects this would be. For example, in line 316, the authors suggest that 'departure direction and PCD [perimeter crossing deviation] [are] indices of the effectiveness and accuracy of navigation, respectively'. However, what do the authors mean by 'effectiveness' and 'accuracy'? Accuracy typically refers to whether or not the navigation is 'correct', i.e. how much it deviates from the goal location, which would be indexed by all performance measures.
So, overall, I would recommend toning down the claim that the findings suggest that the dorsal hippocampus is responsible for accurate spatial navigation and the intermediate hippocampus for place-value associations.
(2) The claim that the different effects of intermediate and dorsal hippocampal muscimol infusions reflect different functions of intermediate and dorsal hippocampus rests on the assumption that both manipulations inhibit similar volumes of hippocampal tissue to a similar extent, but at different levels along the dorso-ventral axis of the hippocampus. However, this is not a foregone conclusion (e.g., drug spread may differ depending on the infusion site or drug effects may differ due to differential expression of GABA-A receptors in the dorsal and intermediate hippocampus), and the authors do not provide direct evidence for this assumption. Therefore, a possible alternative account of the weaker effects of dorsal compared to intermediate hippocampal muscimol infusions on place-preference performance is that the dorsal infusions affect less hippocampal volume or less markedly inhibit neurons within the affected volume than the intermediate infusions. I would recommend that the authors briefly consider this issue in the discussion. Moreover, from the Methods, it is not clear which infusion volume and muscimol concentration were used for the different infusions (see below, 4.a.), and this must be clarified.
(3) It is good that the authors included a comparison/control study using a spherical beacon-guided navigation task, to examine the specific psychological mechanisms disrupted by the hippocampal manipulations. However, as outlined below (4.b.), the sample size for the comparison study was lower than for the main study, and the data in Figure 8 suggest that the comparison task may be affected by the hippocampal manipulations similarly to the place-preference task, albeit less markedly. This would raise the question as to which mechanisms that are common to the two tasks may be affected by hippocampal functional inhibition, which should be considered in the discussion.
(4) Several important methodological details require clarification:<br /> a. Drug infusions (from line 673):<br /> - '0.3 to 0.5 μl of either phosphate-buffered saline (PBS) or muscimol (MUS) was infused into each hemisphere'; the authors need to clarify when which infusion volume was used and why different infusion volumes were used.<br /> - I could not find the concentration of the muscimol solution that was used. The authors must clarify this and also should include a justification of the doses used, e.g. based on previous studies.<br /> - Please also clarify if the injectors and dummies were flush with the guides or by which distance they protruded from the guides.<br /> b. Sample sizes: The authors should include sample size justifications, e.g. based on considerations of statistical power, previous studies, practical considerations, or a combination of these factors. Importantly, the smaller sample size in the control study using the spherical beacon-guided navigation task (n=5 rats) limits comparability with the main study using the place-preference task (n=8). Numerically, the findings on the control task (Figure 8) look quite similar to the findings on the place-preference task, with intermediate hippocampal muscimol infusions causing the most pronounced impairment and dorsal hippocampal muscimol infusions causing a weaker impairment. These effects may have reached statistical significance if the same sample size had been used in the place-preference study.<br /> c. Statistical analyses: Why were the data of the intermediate and dorsal hippocampal PBS infusion conditions averaged for some of the analyses (Figure 5; Figure 6B and C; Figure 7B and C; Figure 8B) but not for others (Figure 6A and Figure 7A)?
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Reviewer #3 (Public Review):
A mechanical model of C. elegans, embedded in a resistive force environment, is used to calculate input torque patterns required to generate output curvature patterns and coordinates, corresponding to a number of different locomotion behaviors in C. elegans.
Strengths:
The use of a mechanical model to study a variety of locomotor sequences and the grounding in empirical data are strengths. The matching of speeds (though requiring adjusted drag coefficients) is a strength.
Weaknesses:
The paper lacks evidence of numerical validation or comparison with the results and tools in the literature. E.g. is it surprising that the uniform torque distribution yields maximal speed? What is the relation between input and output data? How does the input-output relation depend on the parameters of the model? What novel model predictions are made?
In particular, if validated, the breakdown of drag forces and torque distributions during forward locomotion and turning behaviors may be interesting to compare to predictions by other tools, and to empirical measurement. One caveat is that the worm touches itself during such turns, and even crosses over itself in delta turns, and so the estimated drag coefficients and the resultant mechanical forces are likely incorrect.
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Reviewer #3 (Public Review):
In Okholm et al., the authors evaluate the functional impact of circHIPK3 in bladder cancer cells. By knocking down circHIPK3 and performing an RNA-seq analysis, the authors found thousands of deregulated genes which look unaffected by miRNAs sponging function and that are, instead, enriched for a 11-mer motif. Further investigations showed that the 11-mer motif is shared with the circHIPK3 and able to bind the IGF2BP2 protein. The authors validated the binding of IGF2BP2 and demonstrated that IGF2BP2 KD antagonizes the effect of circHIPK3 KD and leads to the upregulation of genes containing the 11-mer. Among the genes affected by circHIPK3 KD and IGF2BP2 KD, resulting in downregulation and upregulation respectively, the authors found the STAT3 gene, which also consistently has concomitant upregulation of one of its targets TP53. The authors propose a mechanism of competition between circHIPK3 and IGF2BP2 triggered by IGF2BP2 nucleation, potentially via phase separation.
Strengths:
Although the number of circRNAs continues to grow, this field lacks many instances of detailed molecular investigations. The presented work critically addresses some of the major pitfalls in the field of circRNAs, and there has been a careful analysis of aspects frequently poorly investigated. Experiments involving use of time-point knockdown followed by RNA-seq, investigation of miRNA-sponge function of circHIPK3, identification of 11-mer motif, identification and validation of IGF2BP2, and the analysis of copy number ratio between circHIPK3 and IGF2BP2 in assessing the potential ceRNA mode of action are thorough and convincing.
Weaknesses:
It is unclear why the authors used certain bladder cancer cells versus non-bladder cells in some experiments. The efficacy of certain experiments (specifically rescue experiments) and some control conditions is still questionable. Overall, the presented study adds some further knowledge in describing circHIPK3 function, its capability to regulate some downstream genes, and its interaction and competition for IGF2BP2.
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Reviewer #3 (Public Review):
Summary:
The cognitive striatum, also known as the dorsomedial striatum, receives input from brain regions involved in high-level cognition and plays a crucial role in processing cognitive information. However, despite its importance, the extent to which different projection pathways of the striatum contribute to this information processing remains unclear. In this paper, Bruce et al. conducted a study using a range of causal and correlational techniques to investigate how these pathways collectively contribute to interval timing in mice. Their results were consistent with previous research, showing that the direct and indirect striatal pathways perform opposing roles in processing elapsed time. Based on their findings, the authors proposed a revised computational model in which two separate accumulators track evidence for elapsed time in opposing directions. These results have significant implications for understanding the neural mechanisms underlying cognitive impairment in neurological and psychiatric disorders, as disruptions in the balance between direct and indirect pathway activity are commonly observed in such conditions.
Strengths:
The authors employed a well-established approach to study interval timing and employed optogenetic tagging to observe the behavior of specific cell types in the striatum. Additionally, the authors utilized two complementary techniques to assess the impact of manipulating the activity of these pathways on behavior. Finally, the authors utilized their experimental findings to enhance the theoretical comprehension of interval timing using a computational model.
Weaknesses:
The behavioral task used in this study is best suited for investigating elapsed time perception, rather than interval timing. Timing bisection tasks are often employed to study interval timing in humans and animals. The main results from unit recording (opposing slopes of D1/D2 cell firing rate, as shown in Figure 3D) appear to be very sensitive to a couple of outlier cells, and the predictive power of ensemble recording seems to be only slightly above chance levels. In the optogenetic experiment, the laser was kept on for too long (18 seconds) at high power (12 mW). This has been shown to cause adverse effects on population activity (for example, through heating the tissue) that are not necessarily related to their function during the task epochs. Given the systemic delivery of pharmacological interventions, it is difficult to conclude that the effects are specific to the dorsomedial striatum. Future studies should use the local infusion of drugs into the dorsomedial striatum.
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Reviewer #3 (Public Review):
Summary:
In this manuscript, the authors discover that nuclear volume decreases after mitotic exit following cell confinement in a manner that scales with the extent of confinement. This adaptation appears to protect the cells from adverse outcomes of critical confinement such as nuclear blebs and DNA damage. The evidence to support these claims is strong.
The authors also provide a model in which argue that what they call the "apparent nuclear surface area" is modulated by confinement through a mechanism regulated by cPLA2 and myosin II activities. Here there are weaknesses in that the manuscript relies on a single approach, measurements are indirect, and alternative models are not explored. Similarly, additional considerations need to be addressed so that the reader can interpret the data presented - for example whether cell volume is also changing coincident with nuclear volume changes, and whether other aspects of cell physiology such as cytokinesis are altered.
Considerations that could support the manuscript further:
One essential consideration that goes unaddressed is whether the nuclear volume alone is changing under compression (resulting in a higher nuclear to cytoplasmic ratio) or if the cell volume is changing and the nuclear volume is following suit (no change in the N:C ratio). Depending on which of these is the case, the overall model would likely shift. In particular, interpreting the effect of disrupting myosin II activity given its different distribution at the cortex in response to the higher confinement would be influenced by which of these conditions are at play.
A key approach used and interpreted by the investigators is an assessment of the folding of the "inner lamin envelope", which they derive from an image analysis routine of lamin staining that they developed and argue reflects "nuclear envelope tension". I am not convinced of the robustness of this approach or what it mechanistically reveals. It may or may not reflect the contour of the inner nuclear membrane, which (perhaps) is the most relevant to the authors' interpretation of nuclear envelope tension. Given the major contribution of this data to the model, which is based on the "unfolding" of the nuclear envelope, an orthogonal approach (e.g. electron microscopy - which one needs to truly address the high-frequency undulations of the nuclear envelope) is needed to support the larger conclusions.
The authors argue that nuclear tension is lost after mitosis in the confined devices because nuclear volume has decreased. While a smaller nuclear volume might indeed translate to less compressive force from the device on the nucleus, one would imagine that the chromosomes still have to be accommodated and that confining them in a smaller volume could increase the tension. Although arguable, the potential alternative possibilities suggest that actual measurements of nuclear envelope tension are needed to robustly test the model. The authors cite the observation that blebs are less prevalent after mitosis as additional support for this model, but this is expected as nuclear envelope breakdown and reformation will "reset" the nuclear contour while the appearance of blebs at mitotic entry is essential a "memory" of all blebs and ruptures over the entire preceding cell cycle.
Representative images for the pharmacological perturbations other than blebbistatin are notably absent - only the analyzed data are presented in the manuscript or the supplemental material. How these perturbations (e.g. to cPLA2) also affect the cortex is important to interpret the data given the point raised above. Orthogonal approaches would also strengthen the conclusions (for example, the statement that "nuclear adaptation observed during mitosis requires nuclear tension sensing through cPLA2" requires more evidence to be convincing - it is not sufficiently supported by the data presented). Even if this is the case, the authors acknowledge that cPLA2 is likely not the answer to the adaption observed under the lower degrees of confinement. Thus, the mechanisms underlying the adaptive changes to nuclear volume remain enigmatic.
One more consideration that seems to go without comment is that the cells under confinement do not appear to successfully complete cytokinesis (Fig. 5b). At a minimum this seems like a major perturbation to cell physiology and needs to be more fully discussed by the authors as playing a role in the observed changes in nuclear volume.
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Reviewer #3 (Public Review):
The authors report on the engineering of an induced Pluripotent Stem Cell (iPSC) line that harbours a single copy of a split mNeonGreen, mNG2(1-10). This cell line is subsequently used to take endogenous protein with a smaller part of mNeonGreen, mNG2(11), enabling complementation of mNG into a fluorescent protein that is then used to visualize the protein. The parental cell is validated and used to construct several iPSC line with endogenously tagged proteins. These are used to visualize and quantify endogenous protein localisation during mitosis.
I see the advantage of tagging endogenous loci with small fragments, but the complementation strategy has disadvantages that deserve some attention. One potential issue is the level of the mNG2(1-10). In addition, this may probably not work for organelle-resident proteins, where the mNG2(11) tag is localised in a membrane enclosed compartment.
Overall the tools and resources reported in this paper will be valuable for the community that aims to study proteins at endogenous levels.
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Reviewer #3 (Public Review):
Summary:
Kokinovic et al. presents an interesting paper that addresses an important gap in knowledge about the differences in the development of direct and indirect pathway striatal neurons in the striosome and matrix compartments. The division of the striatum into 4 distinct populations, striosome-dSPNs, striosome-iSPNs, matrix-dSPNs, and matrix-iSPNs is important, but rarely done. This study records all four populations across early development and shows differences in action potential characteristics and intrinsic properties. They also suppress striosome activity during postnatal development and evaluate the characteristics of adult dopaminergic neurons in control and previously striosome-quieted conditions.
Strengths:
The striatal electrophysiology is beautifully and carefully done and shows important developmental differences between neural subtypes.
The idea to test the striatonigral connection is a good idea.
Weaknesses:
The authors didn't actually test the striatonigral connection. The experiments they do instead don't convincingly show that the striosomal or even striatal connection to the dopaminergic neurons is altered after postnatal striosome suppression.
Major concerns:
(1) mIPSCs are measured and are reduced after chemogenetic suppression of striosomal neurons during development. This is an interesting finding, but these mIPSCs could be coming from any inhibitory input onto the SNc neurons. It is unlikely that most of the mIPSCs are coming from the striosomal inputs. The GPe is much more likely to be the source of these mIPSCs than the striatum because the GPe inputs form synapses nearer the soma and have a higher probability of release (Evans et al., 2020). dSPNs inhibit GPe neurons through a non-canonical pathway (Cui et al., 2021; Spix et al., 2021) and striosomes also inhibit the SNr (McGregor et al., 2019). The striatum has the potential to disinhibit SNc neurons through both the SNr or the GPe (Evans, 2022), and modification of the striosome-SNr or striosome-GPe connections during development could be what is causing the mIPSC changes. To claim that the striosome-SNc connection is altered, a direct test of this connection is necessary.
(2) The dopaminergic neurons recorded seem to be randomly selected, but the striosomes do not inhibit all SNc dopamine neurons. They selectively inhibit the ventral tier SNc neurons (Evans et al., 2020). In the present manuscript, it is impossible to know which subpopulation of SNc neurons was recorded, so it is impossible to tell whether the dopaminergic neurons recorded are the ones expected to receive striosomal input.
(3) Very similarly, the striosomes selectively wrap around the "SNr dendrite" of SNc neurons that participate in striosome-dendron bouquets (Crittenden et al., 2016). However, not all SNc neurons have prominent SNr dendrites (Henny et al., 2012). In the morphological images of Supplemental Figure 3, it looks like the recorded cells sometimes have an SNr dendrite and sometimes don't (but it is hard to tell because the medial-lateral rostral-caudal axis is not labeled in the images). The presence or absence of the "SNr dendrite" is a strong determinant of whether an individual dopaminergic neuron receives striosomal inhibition or not (Evans et al., 2020). As above, not knowing whether the neurons recorded have SNr dendrites makes it impossible to know whether they should be receiving striosomal input at all.
(4) It's quite interesting that the dendron-bouquet structure is intact even after striosomal activity suppression, as cannabinoid receptor knockout greatly disrupts the structural integrity of bouquets (Crittenden et al., 2022). However, going along with point 3, the gephyrin puncta analysis only at the somas is very limiting. The striosome-SNc relevant puncta would be primarily on the SNr dendrite. Gephyrin density on the SNr dendrites or in bouquets would be much more informative than density on the soma.
(5) The authors claim that "CNO didn't affect the shape of the DA neuron dendritic tree", but more information about the morphological analysis should be added. It is not clear how the sholl analysis was conducted or whether a full 3D reconstruction was made. This claim seems to be based on only one dendritic measurement (sholl analysis), but many other dendritic or morphological features could be altered.
Crittenden, J.R., Tillberg, P.W., Riad, M.H., Shima, Y., Gerfen, C.R., Curry, J., Housman, D.E., Nelson, S.B., Boyden, E.S., & Graybiel, A.M. (2016) Striosome-dendron bouquets highlight a unique striatonigral circuit targeting dopamine-containing neurons. Proc. Natl. Acad. Sci. U.S.A., 113, 11318-11323.<br /> Crittenden, J.R., Yoshida, T., Venu, S., Mahar, A., & Graybiel, A.M. (2022) Cannabinoid Receptor 1 Is Required for Neurodevelopment of Striosome-Dendron Bouquets. eNeuro, 9, ENEURO.0318-21.2022.<br /> Cui, Q., Du, X., Chang, I.Y.M., Pamukcu, A., Lilascharoen, V., Berceau, B.L., García, D., Hong, D., Chon, U., Narayanan, A., Kim, Y., Lim, B.K., & Chan, C.S. (2021) Striatal Direct Pathway Targets Npas1+ Pallidal Neurons. J Neurosci, 41, 3966-3987.<br /> Evans, R.C. (2022) Dendritic involvement in inhibition and disinhibition of vulnerable dopaminergic neurons in healthy and pathological conditions. Neurobiol Dis, 172, 105815.<br /> Evans, R.C., Twedell, E.L., Zhu, M., Ascencio, J., Zhang, R., & Khaliq, Z.M. (2020) Functional Dissection of Basal Ganglia Inhibitory Inputs onto Substantia Nigra Dopaminergic Neurons. Cell Rep, 32, 108156.<br /> Henny, P., Brown, M.T.C., Northrop, A., Faunes, M., Ungless, M.A., Magill, P.J., & Bolam, J.P. (2012) Structural correlates of heterogeneous in vivo activity of midbrain dopaminergic neurons. Nat. Neurosci., 15, 613-619.<br /> McGregor, M.M., McKinsey, G.L., Girasole, A.E., Bair-Marshall, C.J., Rubenstein, J.L.R., & Nelson, A.B. (2019) Functionally Distinct Connectivity of Developmentally Targeted Striosome Neurons. Cell Rep, 29, 1419-1428.e5.<br /> Spix, T.A., Nanivadekar, S., Toong, N., Kaplow, I.M., Isett, B.R., Goksen, Y., Pfenning, A.R., & Gittis, A.H. (2021) Population-specific neuromodulation prolongs therapeutic benefits of deep brain stimulation. Science, 374, 201-206.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The receptor binding domain of SARS-Cov-2 spike protein contains two N-glycans which have been conserved by the variants observed in these last 4 years. Through the use of extensive molecular dynamics, the authors demonstrate that even if glycosylation is conserved, the stabilization role of glycans at N343 differs among the strains. They also investigate the effect of this glycosylation on the binding of RBD towards sialylated gangliosides, as a function of evolution.
Strengths:
The molecular dynamics characterization is well performed and demonstrates differences in the effect of glycosylation as a factor of evolution. The binding of different strains to human gangliosides shows variations of strong interest. Analyzing the structure function of glycans on SARS-Cov-2 surface as a function of evolution is important for the surveillance of novel variants since it can influence their virulence.
Weaknesses:
The article is difficult to read, with no sufficient efforts of clarification for non-glycobiology audiences. The presentation of previous knowledge about RBD glycosylation and its effect on structure is very difficult to follow and should be reorganized. The choice of the nature of the biantennary glycan at N343 is not rationalized. A major weakness is the absence of data supporting the proposed binding site for ganglioside.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This work aims to demonstrate how recent advances in thermal stability assays can be utilised to screen chemical libraries and determine the compound mechanism of action. Focusing on 96 compounds with known mechanisms of action, they use the PISA assay to measure changes in protein stability upon treatment with a high dose (10uM) in live K562 cells and whole cell lysates from K562 or HCT116. They intend this work to showcase a robust workflow that can serve as a roadmap for future studies.
Strengths:
The major strength of this study is the combination of live and whole cell lysates experiments. This allows the authors to compare the results from these two approaches to identify novel ligand-induced changes in thermal stability with greater confidence. More usefully, this also enables the authors to separate the primary and secondary effects of the compounds within the live cell assay.
The study also benefits from the number of compounds tested within the same framework, which allows the authors to make direct comparisons between compounds.
These two strengths are combined when they compare CHEK1 inhibitors and suggest that AZD-7762 likely induces secondary destabilisation of CRKL through off-target engagement with tyrosine kinases.
Weaknesses:
One of the stated benefits of PISA compared to the TPP in the original publication (Gaetani et al 2019) was that the reduced number of samples required allows more replicate experiments to be performed. Despite this, the authors of this study performed only duplicate experiments. They acknowledge this precludes the use of frequentist statistical tests to identify significant changes in protein stability. Instead, they apply an 'empirically derived framework' in which they apply two thresholds to the fold change vs DMSO: absolute z-score (calculated from all compounds for a protein) > 3.5 and absolute log2 fold-change > 0.2. They state that the fold-change threshold was necessary to exclude non-specific interactors. While the thresholds appear relatively stringent, this approach will likely reduce the robustness of their findings in comparison to an experimental design incorporating more replicates. Firstly, the magnitude of the effect size should not be taken as a proxy for the importance of the effect. They acknowledge this and demonstrate it using their data for PIK3CB and p38α inhibitors (Figures 2B-C). They have thus likely missed many small, but biologically relevant changes in thermal stability due to the fold-change threshold. Secondly, this approach relies upon the fold-changes between DMSO and compound for each protein being comparable, despite them being drawn from samples spread across 16 TMT multiplexes. Each multiplex necessitates a separate MS run and the quantification of a distinct set of peptides, from which the protein-level abundances are estimated. Thus, it is unlikely the fold changes for unaffected proteins are drawn from the same distribution, which is an unstated assumption of their thresholding approach. The authors could alleviate the second concern by demonstrating that there is very little or no batch effect across the TMT multiplexes. However, the first concern would remain. The limitations of their approach could have been avoided with more replicates and the use of an appropriate statistical test. It would be helpful if the authors could clarify if any of the missed targets passed the z-score threshold but fell below the fold-change threshold.
The authors use a single, high, concentration of 10uM for all compounds. Given that many of the compounds likely have low nM IC50s, this concentration will often be multiple orders of magnitude above the one at which they inhibit their target. This makes it difficult to assess the relevance of the off-target effects identified to clinical applications of the compounds or biological experiments. The authors acknowledge this and use ranges of concentrations for follow-up studies (e.g. Figure 2E-F). Nonetheless, this weakness is present for the vast bulk of the data presented.
The authors claim that combining cell-based and lysate-based assays increases coverage (Figure 3F) is not supported by their data. The '% targets' presented in Figure 3F have a different denominator for each bar. As it stands, all 49 targets quantified in both assays which have a significant change in thermal stability may be significant in the cell-based assay. If so, the apparent increase in % targets when combining reflects only the subsetting of the data. To alleviate this lack of clarity, the authors could update Figure 3F so that all three bars present the % targets figure for just the 60 compounds present in both assays.
Aims achieved, impact and utility:
The authors have achieved their main aim of presenting a workflow that serves to demonstrate the potential value of this approach. However, by using a single high dose of each compound and failing to adequately replicate their experiments and instead applying heuristic thresholds, they have limited the impact of their findings. Their results will be a useful resource for researchers wishing to explore potential off-target interactions and/or mechanisms of action for these 96 compounds, but are expected to be superseded by more robust datasets in the near future. The most valuable aspect of the study is the demonstration that combining live cell and whole cell lysate PISA assays across multiple related compounds can help to elucidate the mechanisms of action.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this manuscript, Long et al. demonstrated that the deletion of SUL1, which encodes a sulfate transporter localized on the plasma membrane, extends the replicative lifespan in S. cerevisiae. The authors further investigated the mechanism underlying this lifespan extension. They found that, unlike sul1∆ mutants, other mutants that have been shown to have a deficiency in sulfate transport cannot extend lifespan, from which they concluded that it is unlikely that SUL1 deletion extends lifespan by impairing sulfate intake. The authors then performed a series of characterizations on sul1∆ mutants and found that consistent with previous studies, PKA activity is downregulated when SUL1 is deleted. The authors demonstrated that SUL1 deletion promotes the nuclear localization of Msn2, as well as autophagy, which are known downstream signals of the PKA pathway. In addition, the authors show that MSN2 and ATG8 are indispensable for the lifespan extension in sul1∆ cells. Altogether, this manuscript suggests that SUL1 deletion extends lifespan by affecting PKA activity.
Strengths:
This study reported an interesting phenotype that the deletion of SUL1, but not SUL2, promotes lifespan extension in budding yeast. The authors performed some characterizations on sul1∆ mutants and epistatic studies to demonstrate that this lifespan extension requires MSN2 and ATG8, which further support the importance of the PKA pathway in regulating lifespan.
Weaknesses:
However, one of the major findings in this paper that SUL1 deletion extends lifespan independently of its role in sulfate uptake was merely based on lifespan measurements on sul2∆, SUL1E427Q, and met3∆ mutants, which cannot exclude the possibility that yeast lifespan is affected by sulfate intake. In addition, the strength of evidence for whether SUL1 deletion extends lifespan through affecting PKA activity is incomplete. It has been shown that Sul1 and Sul2 have redundant functions in both sulfate transport and PKA activation (Kankipati et al. 2015). However, in this manuscript, as shown by the authors, the deletion of SUL2 does not extend the lifespan compared with sul1∆ mutants. Without a further characterization on why deletion of SUL1, but not SUL2, extends lifespan, it is likely that SUL1 deletion extends lifespan independently of either sulfate transport or PKA activation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary
The authors of this work aim to address the challenge of accurately and efficiently identifying protein binding sites from sequences. They recognize that the limitations of current methods, including reliance on multiple sequence alignments or experimental protein structure, and the under-explored geometry of the structure, which limit the performance and genome-scale applications. The authors have developed a multi-task network, GPSite, that predicts binding residues for a range of biologically relevant molecules, including DNA, RNA, peptides, proteins, ATP, HEM, and metal ions, using sequence embeddings from protein language models and ESMFold-predicted structures. The reported results showed to be superior to current sequence-based and structure-based methods in terms of accuracy and efficiency.
Strengths<br /> (1) The GPSite model's ability to predict binding sites for a wide variety of molecules, including DNA, RNA, peptides, and various metal ions.<br /> (2) Based on the presented results, GPSite outperforms state-of-the-art methods in several benchmark datasets in terms of accuracy and efficiency.<br /> (3) GPSite adopts predicted structure instead of native structures as input, enabling the model to be applied to a wider range of scenarios where native structures are rare.<br /> (4) The low computational cost of GPSite is beneficial, which enables rapid genome-scale binding residue annotations, indicating the model's potential for large-scale downstream applications and discoveries.
Weaknesses
There are no major weaknesses after the revision.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
How the microbial composition of the human body is influenced by and influences disease progression is an important topic. For people with COVID-19, symptomatic progression and deterioration can be difficult to predict. This manuscript attempts to associate the nasal and fecal microbiomes of COVID-19 patients with the severity of disease symptoms, with the goal of identifying microbial markers that can predict disease outcomes. However, the value of this work is held back by unclear methods and data presentation.
Strengths:
Analysis of microbiomes from two distinct anatomical locations and across three distinct patient groups is a substantial undertaking. How these microbiomes influence and are influenced by COVID-19 disease progression is an important question. In particular, the putative biomarker identified here could be of clinical value with additional research.
Weaknesses:
The methods and statistics used for several figures and comparisons are unclear or used in non-standard ways. For instance: the description of the Bray-Curtis test for Figure 1 is inaccurate and conflicts between the text and figure legend; the method used to compare the relative abundance of genera in Figure 2 is not clear; and it is not stated how the "total amount" of detected bacteria is inferred from the data presented in Figures 2C and 2D.
The description of results for Figure 1 is overstated or unclear for both the alpha diversity among disease groups and the overlap for nasal samples.
The most abundant phyla from nasal samples cumulatively account for less than 1% of abundance and it is unclear why this would be expected or how it compares to other work. Relatedly, the potential biological relevance of the very small proportional changes among phyla in the nasal samples is also not clear.
There is no real discussion of how the identified biomarkers might work in practice. While some microbes are detected in one condition but not others, it is unclear whether these organisms are expected to already exist below the detection threshold and then increase in abundance along with disease severity, or if they are picked up from the environment. For instance, would the presence of these 'severe' - associated microbes in patients with mild or moderate disease justify additional treatment to prevent disease progression?
The authors use the term "nasopharyngeal-faecal axis", but there is no substantial discussion of how these two microbiomes interact to influence disease progression, or how they are jointly affected to yield useful biomarkers. With one exception, correlation values between nasal and fecal microbes range from negligible to modest. It is unclear, then, how much parallel influence disease has on these microbiomes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This study explores sensory prediction errors in the sensory cortex. It focuses on the question of how these signals are shaped by non-hierarchical interactions, specifically multimodal signals arising from same-level cortical areas. The authors used 2-photon imaging of mouse auditory cortex in head-fixed mice that were presented with sounds and/or visual stimuli while moving on a ball. First, responses to pure tones, visual stimuli, and movement onset were characterized. Then, the authors made the running speed of the mouse predictive of sound intensity and/or visual flow. Mismatches were created through the interruption of sound and/or visual flow for 1 second while the animal moved, disrupting the expected sensory signal given the speed of movement. As a control, the same sensory stimuli triggered by the animal's movement were presented to the animal decoupled from its movement. The authors suggest that auditory responses to the unpredicted silence reflect mismatch responses. That these mismatch responses were enhanced when the visual flow was congruently interrupted, indicates the cross-modal influence of prediction error signals.
This study's strengths are the relevance of the question and the design of the experiment. The authors are experts in the techniques used. The analysis explores neither the full power of the experimental design nor the population activity recorded with 2-photon, leaving open the question of to what extent what the authors call mismatch responses are not sensory responses to sound interruption. The auditory system is sensitive to transitions and indeed responses to the interruption of the sound are similar in quality, if not quantity, in the predictive and the control situation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this article, Hermannova et al catalog the changes in ribosome association with mRNAs when the eukaryotic translation initiation factor 3 is disrupted by knocking down subunits of the multisubunit protein. They find that RNAs relying on TOP motifs for translation, such as ribosomal protein RNAs, and RNAs encoding proteins that modify other proteins in the ER or components of the lysosome are upregulated. In contrast, proteins encoding components of MAP kinase cascades are downregulated when subunits of eIF3 are knocked down.
Strengths:
The authors use ribosome profiling of well-characterized mutants lacking subunits of eIF3 and assess the changes in translation that take place. They supplement the ribosome association studies with western blotting to determine protein level changes of affected transcripts. They analyze what is being encoded by the transcripts undergoing translation changes, which is important for understanding more broadly how translation initiation factor levels affect cancer cell translatomes.
Weaknesses:
(1) The data are presented as a catalog of effects, and the paper would be strengthened if there were a clear model tying the various effects together or linking individual subunit knockdown to cancerous phenotypes. It is unclear what the hypothesis is for cells having more MAPK activity with less of the MAPK proteins being translated, so the main findings of the paper become observational without context.
(2) The conclusions drawn are presented as very generalized other than in the last paragraph, but the experiments were only done in Hela cells. Since conclusions are being made about how translation changes affect MAP kinase signaling and there is mention in the abstract that dysregulation of these subunits is observed in cancer, at least one other cell line would need to be analyzed to provide evidence that the effects of subunit knockdown aren't cell-line specific.
(3) It is also unclear how replicates were performed and how many replicates were performed for several experiments. Biological replicates are mentioned, but what the authors did for biological replicates isn't defined and the description of the collection of cells for polysome/ribosome footprint/RNA seq samples makes it unclear whether the "biological replicates" are samples from separate transfections (true biological replicates) or different aliquots or wells from a single transfection (technical replicates) being run over a separate gradient. If using technical replicates, the data comparing the effects of knocking down D vs E vs H subunits are substantially weakened because subunit-specific differences could be the result of non-specific events that occurred in a transfection. It's also notable that while the pooled siRNAs will increase the potency of knockdown, it is possible that one or more of the siRNAs could have off-target effects, and analyzing individual siRNAs would be better for ensuring effects are specific.
(4) Many of the changes in protein levels reported by Western are subtle. Data from all western blots making claims of quantitative differences should really be quantified relative to nontreated over-loading control or total protein quantified from the gel, and presented with a degree of error from biological replicates to make conclusions about differences in protein levels between samples.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This study investigates subtelomeric repetitive sequences in the budding yeast Saccharomyces cerevisiae, known as Y' and X-elements. Taking advantage of yeast strain SY12 that contains only 3 chromosomes and six telomeres (normal yeast strains contain 32 telomeres) the authors are able to generate a strain completely devoid of Y'- and X-elements.
Strengths:
They demonstrate that the SY12 delta XY strain displays normal growth, with stable telomeres of normal length that were transcriptionally silenced, a key finding with wide implications for telomere biology. Inactivation of telomerase in the SY12 and SY12 delta XY strains frequently resulted in survivors that had circularized all three chromosomes, hence bypassing the need for telomeres altogether. They show that survivors with fused chromosomes and so-called atypical survivors arise independently of the central recombination protein Rad52. The SY12 and SY12 delta XY yeast strains can become a useful tool for future studies of telomere biology. The conclusions of this manuscript are well supported by the data and are valuable for researchers studying telomeres.
Weaknesses:
A weakness of the manuscript is the analysis of telomere transcriptional silencing. They state: "The results demonstrated a significant increase in the expression of the MPH3 and HSP32 upon Sir2 deletion, indicating that telomere silencing remains effective in the absence of X and Y'-elements". However, for the SY12 strain, their analyses indicate that the difference between the WT and sir2 strains is nonsignificant. In addition, a striking observation is that the SY12 strain (with only three chromosomes) express much less of both MPH3 and HSP32 than the parental strain BY4742 (16 chromosomes), both in the presence and absence of Sir2.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This valuable study by Semenova and colleagues describes a large cross-sectional cohort of 115 individuals on ART. Participants contributed a single blood sample which underwent IPDA, and 25-color flow with various markers (pre and post-stimulation). The authors then used clustering, decision tree analyses, and machine learning to look for correlations between these immunophenotypic markers and several measures of HIV reservoir volume. They identified two distinct clusters that can be somewhat differentiated based on total HIV DNA level, intact HIV DNA level, and multiple T cell cellular markers of activation and exhaustion.
The conclusions of the paper are supported by the data but the relationships between independent and dependent variables in the models are correlative with no mechanistic work to determine causality. It is unclear in most cases whether confounding variables could explain these correlations. If there is causality, then the data is not sufficient to infer directionality (ie does the immune environment impact the HIV reservoir or vice versa or both?). In addition, even with sophisticated and appropriate machine learning approaches, the models are not terribly predictive or highly correlated. For these reasons, the study is very much hypothesis-generating and will not impact cure strategies or HIV reservoir measurement strategies in the short term.
Strengths:
The study cohort is large and diverse in terms of key input variables such as age, gender, and duration of ART. Selection of immune assays is appropriate. The authors used a wide array of bioinformatic approaches to examine correlations in the data. The paper was generally well-written and appropriately referenced.
Weaknesses:
(1) The major limitation of this work is that it is highly exploratory and not hypothesis-driven. While some interesting correlations are identified, these are clearly hypothesis-generating based on the observational study design.
(2) The study's cross-sectional nature limits the ability to make mechanistic inferences about reservoir persistence. For instance, it would be very interesting to know whether the reservoir cluster is a feature of an individual throughout ART, or whether this outcome is dynamic over time.
(3) A fundamental issue is that I am concerned that binarizing the 3 reservoir metrics in a 50/50 fashion is for statistical convenience. First, by converting a continuous outcome into a simple binary outcome, the authors lose significant amounts of quantitative information. Second, the low and high reservoir outcomes are not actually demonstrated to be clinically meaningful: I presume that both contain many (?all) data points above levels where rebound would be expected soon after interruption of ART. Reservoir levels would also have no apparent outcome on the selection of cure approaches. Overall, dividing at the median seems biologically arbitrary to me.
(4) The two reservoir clusters are of potential interest as high total and intact with low % intact are discriminated somewhat by immune activation and exhaustion. This was the most interesting finding to me, but it is difficult to know whether this clustering is due to age, time on ART, other co-morbidity, ART adherence, or other possible unmeasured confounding variables.
(5) At the individual level, there is substantial overlap between clusters according to total, intact, and % intact between the clusters. Therefore, the claim in the discussion that these 2 cluster phenotypes may require different therapeutic approaches seems rather speculative. That said, the discussion is very thoughtful about how these 2 clusters may develop with consideration of the initial insult of untreated infection and / or differences in immune recovery.
(6) The authors state that the machine learning algorithms allow for reasonable prediction of reservoir volume. It is subjective, but to me, 70% accuracy is very low. This is not a disappointing finding per se. The authors did their best with the available data. It is informative that the machine learning algorithms cannot reliably discriminate reservoir volume despite substantial amounts of input data. This implies that either key explanatory variables were not included in the models (such as viral genotype, host immune phenotype, and comorbidities) or that the outcome for testing the models is not meaningful (which may be possible with an arbitrary 50/50 split in the data relative to median HIV DNA volumes: see above).
(7) The decision tree is innovative and a useful addition, but does not provide enough discriminatory information to imply causality, mechanism, or directionality in terms of whether the immune phenotype is impacting the reservoir or vice versa or both. Tree accuracy of 80% is marginal for a decision tool.
(8) Figure 2: this is not a weakness of the analysis but I have a question about interpretation. If total HIV DNA is more predictive of immune phenotype than intact HIV DNA, does this potentially implicate a prior high burden of viral replication (high viral load &/or more prolonged time off ART) rather than ongoing reservoir stimulation as a contributor to immune phenotype? A similar thought could be applied to the fact that clustering could only be detected when applied to total HIV DNA-associated features. Many investigators do not consider defective HIV DNA to be "part of the reservoir" so it is interesting to speculate why these defective viruses appear to have more correlation with immunophenotype than intact viruses.
(9) Overall, the authors need to do an even more careful job of emphasizing that these are all just correlations. For instance, HIV DNA cannot be proven to have a causal effect on the immunophenotype of the host with this study design. Similarly, immunophenotype may be affecting HIV DNA or the correlations between the two variables could be entirely due to a separate confounding variable.
(10) In general, in the intro, when the authors refer to the immune system, they do not consistently differentiate whether they are referring to the anti-HIV immune response, the reservoir itself, or both. More specifically, the sentence in the introduction listing various causes of immune activation should have citations. (To my knowledge, there is no study to date that definitively links proviral expression from reservoir cells in vivo to immune activation as it is next to impossible to remove the confounding possible imprint of previous HIV replication.) Similarly, it is worth mentioning that the depletion of intact proviruses is quite slow such that provial expression can only be stimulating the immune system at a low level. Similarly, the statement "Viral protein expression during therapy likely maintains antigen-specific cells of the adaptive immune system" seems hard to dissociate from the persistence of immune cells that were reactive to viremia.
(11) Given the many limitations of the study design and the inability of the models to discriminate reservoir volume and phenotype, the limitations section of the discussion seems rather brief.
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arxiv.org arxiv.org
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Reviewer #3 (Public Review):
The manuscript "Theory of active self-organization of dense nematic structures in the actin cytoskeleton" analysis self-organized pattern formation within a two-dimensional nematic liquid crystal theory and uses microscopic simulations to test the plausibility of some of the conclusions drawn from that analysis. After performing an analytic linear stability analysis that indicates the possibility of patterning instabilities, the authors perform fully non-linear numerical simulations and identify the emergence of stripe-like patterning when anisotropic active stresses are present. Following a range of qualitative numerical observations on how parameter changes affect these patterns, the authors identify, besides isotropic and nematic stress, also active self-alignment as an important ingredient to form the observed patterns. Finally, microscopic simulations are used to test the plausibility of some of the conclusions drawn from continuum simulations.
The paper is well written, figures are mostly clear and the theoretical analysis presented in both, main text and supplement, is rigorous. Mechano-chemical coupling has emerged in recent years as a crucial element of cell cortex and tissue organization and it is plausible to think that both, isotropic and anisotropic active stresses, are present within such effectively compressible structures. Even though not yet stated this way by the authors, I would argue that combining these two is of the key ingredients that distinguishes this theoretical paper from similar ones. The diversity of patterning processes experimentally observed is nicely elaborated on in the introduction of the paper, though other closely related previous work could also have been included in these references (see below for examples).
To introduce the continuum model, the authors exclusively cite their own, unpublished pre-print, even though the final equations take the same form as previously derived and used by other groups working in the field of active hydrodynamics (a certainly incomplete list: Marenduzzo et al (PRL, 2007), Salbreux et al (PRL, 2009, cited elsewhere in the paper), Jülicher et al (Rep Prog Phys, 2018), Giomi (PRX, 2015),...). To make better contact with the broad active liquid crystal community and to delineate the present work more compellingly from existing results, it would be helpful to include a more comprehensive discussion of the background of the existing theoretical understanding on active nematics. In fact, I found it often agrees nicely with the observations made in the present work, an opportunity to consolidate the results that is sometimes currently missed out on. For example, it is known that self-organised active isotropic fluids form in 2D hexagonal and pulsatory patterns (Kumar et al, PRL, 2014), as well as contractile patches (Mietke et al, PRL 2019), just as shown and discussed in Fig. 2. It is also known that extensile nematics, \kappa<0 here, draw in material laterally of the nematic axis and expel it along the nematic axis (the other way around for \kappa>0, see e.g. Doostmohammadi et al, Nat Comm, 2018 "Active Nematics" for a review that makes this point), consistent with all relative nematic director/flow orientations shown in Figs. 2 and 3 of the present work.
The results of numerical simulations are well-presented. Large parts of the discussion of numerical observations - specifically around Fig. 3 - are qualitative and it is not clear why the analysis is restricted to \kappa<0. Some of the observations resonate with recent discussions in the field, for example the observation of effectively extensile dynamics in a contractile system is interesting and reminiscent of ambiguities about extensile/contractile properties discussed in recent preprints (https://arxiv.org/abs/2309.04224). It is convincingly concluded that, besides nematic stress on top of isotropic one, active self-alignment is a key ingredient to produce the observed patterns.
I compliment the authors for trying to gain further mechanistic insights into this conclusion with microscopic filament simulations that are diligently performed. It is rightfully stated that these simulations only provide plausibility tests and, within this scope, I would say the authors are successful. At the same time, it leaves open questions that could have been discussed more carefully. For example, I wonder what can be said about the regime \kappa>0 (which is dropped ad-hoc from Fig. 3 onward) microscopically, in which the continuum theory does also predict the formation of stripe patterns - besides the short comment at the very end? How does the spatial inhomogeneous organization the continuum theory predicts fit in the presented, microscopic picture and vice versa?
Overall, the paper represents a valuable contribution to the field of active matter and, if strengthened further, might provide a fruitful basis to develop new hypothesis about the dynamic self-organisation of dense filamentous bundles in biological systems.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
The work by Dar et al. examines RNA metabolism under cellular stress, focusing on stress-granule-dependent RNA decay. It employs direct RNA sequencing with a Nanopore-based method, revealing that cellular stress induces prevalent 5' end RNA decay that is coupled to translation and ribosome occupancy but is independent of the shortening of the poly(A) tail. This decay, however, is dependent on XRN1 and enriched in the stress granule transcriptome. Notably, inhibiting stress granule formation in G3BP1/2-null cells restores the RNA length to the same level as wild-type. It suppresses stress-induced decay, identifying RNA decay as a critical determinant of RNA metabolism during cellular stress and highlighting its dependence on stress-granule formation.
This is an exciting and novel discovery. I am not an expert in sequencing technologies or sequencing data analysis, so I will limit my comments purely to biology and not technical points. The PI is a leader in applying innovative sequencing methods to studying mRNA decay.
One aspect that appeared overlooked is that poly(A) tail shortening per se does lead to decapping. It is shortening below a certain threshold of 8-10 As that triggers decapping. Therefore, I found the conclusion that poly(A) tail shortening is not required for stress-induced decay to be somewhat premature. For a robust test of this hypothesis, the authors should consider performing their analysis in conditions where CNOT7/8 is knocked down with siRNA.
Similarly, as XRN1 requires decapping to take place, it necessitates the experiment where a dominant-negative DCP2 mutant is over-expressed.
Are G3BP1/2 stress granules required for stress-induced decay or simply sites for storage? This part seems unclear. A very worthwhile test here would be to assess in XRN1-null background.
Finally, the authors speculate that the mechanism of stress-induced decay may have evolved to relieve translational load during stress. But why degrade the 5' end when removing the cap may be sufficient? This returns to the question of assessing the role of decapping in this mechanism.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this study, the authors set out to understand the mechanisms behind chlorophyll biosynthesis in rice, focusing in particular on the role of OsNF-YB7, an ortholog of Arabidopsis LEC1, which is a positive regulator of chlorophyll (Chl) biosynthesis in Arabidopsis. They showed that OsNF-YB7 loss-of-function mutants in rice have chlorophyll-rich embryos, in contrast to Arabidopsis LEC1 loss-of-function mutants. This contrasting phenotype led the authors to carry out extensive molecular studies on OsNF-YB7, including in vitro and in vivo protein interaction studies, gene expression profiling, and protein-DNA interaction assays. The evidence provided well supported the core arguments of the authors, emphasising that OsNF-YB7 is a negative regulator of Chl biosynthesis in rice embryos by mediating the expression of OsGLK1, a transcription factor that regulates downstream Chl biosynthesis genes. In addition, they showed that OsNF-YB7 interacts with OsGLK1 to negatively regulate the expression of OsGLK1, demonstrating the broad involvement of OsNF-YB7 in rice Chl biosynthetic pathways.
Strengths:
This study clearly demonstrated how OsNF-YB7 regulates its downstream pathways using several in vitro and in vivo approaches. For example, gene expression analysis of OsNF-YB7 loss-of-function and gain-of-function mutants revealed the expression of selected downstream chl biosynthetic genes. This was further validated by EMSA on the gel. The authors also confirmed this using luciferase assays in rice protoplasts. These approaches were used again to show how the interaction of OsNF-YB7 and OsGLK1 regulates downstream genes. The main idea of this study is very well supported by the results and data.
Weaknesses:
From an evolutionary perspective, it is interesting to see how two similar genes have come to play opposite roles in Arabidopsis and rice. It would have been more interesting if the authors had carried out a cross-species analysis of AtLEC1 and OsNF-YB7. For example, overexpressing AtLEC1 in an osnf-yb7 mutant to see if the phenotype is restored or enhanced. Such an approach would help us understand how two similar proteins can play opposite roles in the same mechanism within their respective plant species.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This study from the Flores group aims at understanding neuronal circuit changes during adolescence which is an ill-defined, transitional period involving dramatic changes in behavior and anatomy. They focus on DA innervation of the prefrontal cortex, and their interaction with the guidance cue Netrin-1. They propose DA axons in the PFC increase in the postnatal period, and their density is reduced in a Netrin 1 knockdown, suggesting that Netrin abets the development of this mesocortical pathway. In such mice impulsivity gauged by a go-no go task is reduced. They then provide some evidence that Unc5c is developmentally regulated in DA axons. Finally they use an interesting hamster model, to study the effect of light hours on mesocortical innervation, and make some interesting observations about the timing of innervation and Unc5c expression, and the fact that females housed in winter day length conditions display an accelerated innervation of the prefrontal cortex.
Comments on the revision. Several points were addressed; some remain to be addressed.
4. It's not clear to me that TH doesnt stain noradrenergic axons in the PFC. See Islam and Blaess, 2021, and references therein.
6. The Netrin knockdown data provided is from a previous study/samples.
8. While the authors make the argument that the behavior is linked to DA, they still haven't formally tested it, in my opinion.
13. Fig 3, UNc 5c levels are not yet quantified. Furthermore, I agree with the previous reviewer that Unc5C knockdown would corroborate key aspects of the model.
New - Developmental trajectory of prefrontal TH-positive axons from early adolescence to adulthood is similar in male and female rats, (Willing Juraska et al., 2017). This needs discussion.
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Reviewer #3 (Public Review):
Summary:
This interesting manuscript presents a comparison of biophysical properties, TEM appearances, and phosphorylation patterns of brain-derived synuclein fibrils from 3 subjects each with Parkinson Disease (PD), Parkinson Disease with Dementia (PDD), Dementia with Lewy bodies (DLB) and Multiple System Atrophy (MSA), the effects of studying these brain-derived fibrils in a Seeding Aggregation Assay (SAA), and a comparison of the seeded and resultant fibers. The results are not unexpected.
Strengths:
The work explores an important question. Namely, what is the fidelity of synuclein fibrils produced during an SAA reaction to the starting material if that material has been extracted from the brains of deceased patients with synucleinopathies.
Weaknesses:
The work suffers from several methodological flaws
The experiments are missing two important controls. 1) what to fibrils generated by different in vitro fibril preparations made from recombinant synclein protein look like; and 2) the use of CSF from the same patients whose brain tissue was used to assess whether CSF and brain seeds look and behave identically. The latter is perhaps the most important question of all - namely how representative are CSF seeds of what is going on in patients' brains?
In their discussion the authors do not comment on the obvious differences in the conditions leading to the formation of seeds in the brain and in the artificial conditions of the seeding assay. Why should the two sets of conditions be expected to yield similar morphologies, especially since the extracted fibrils are subjected to harsh conditions for solubilization and re-suspension.
Finally, the key experiment was not performed - would the resultant seeds from SAA preparations from the different nosological entities produce different pathologies when injected into animal brains? But perhaps this is the subject of a future manuscript.
Furthermore, the authors comment on phosphorylation patterns, stating that the resultant seeds are less heavy phosphorylated than the original material. Again, this should not be surprising, since the SAA assay conditions are not known to contain the enzymes necessary to phosphorylate synuclein. The discussion of PTMs is limited to pS-129 phosphorylation. What about other PTMs? How does the pattern of PTMs affect the seeding pattern.
Lastly, the manuscript contains no data on how the diagnostic categories were assigned at autopsy. This information should be included in the supplementary material.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this manuscript, Wang et al. performed a study looking at vascular changes in response to anesthesia in awake mice using ultrasound localization microscopy (ULM). The authors report a reduction of vascularity and blood flow velocity in the awake state. In addition, they demonstrate the reproducibility of ULM measurements in time.
Strengths:
Demonstration that high-quality, state-of-the-art ULM images can be performed using cranial windows in awake animals.<br /> Demonstration that repeated imaging in time produces comparable images.
Weaknesses:
It is unclear whether multiple animals were used in the statistical analysis.<br /> Generalizations are sometimes drawn from what seems to be the analysis of a single vessel.<br /> The description of the statistical analysis is mostly qualitative.<br /> Some terms used are insufficiently defined.<br /> Additional limitations should be included in the discussion.<br /> Some technical details are lacking.
Without information about whether the results obtained come from multiple animals, it is difficult to conclude that the authors generally achieved their aim. They do achieve it in a single animal.
The results that are shown are interesting and could have an impact on the ULM community and beyond. In particular, the experimental setup they used along with the high reproducibility they report could become very important for the use of ULM in larger animal cohorts.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The protein kinase, Aurora B, is a critical regulator of mitosis and cytokinesis in eukaryotes, exhibiting a dynamic localisation. As part of the Chromosomal Passenger Complex (CPC), along with the Aurora B activator, INCENP, and the CPC localisation module comprised of Borealin and Survivin, Aurora B travels from the kinetochores at metaphase to the spindle midzone at anaphase, which ensures its substrates are phosphorylated in a time- and space-dependent manner. In the kinetoplastid parasite, T. brucei, the Aurora B orthologue (AUK1), along with an INCENP orthologue known as CPC1, and a kinetoplastid-specific protein CPC2, also displays a dynamic localisation, moving from the kinetochores at metaphase, to the spindle midzone at anaphase, to the anterior end of the newly synthesised flagellum attachment zone (FAZ) at cytokinesis. However, the trypanosome CPC lacks orthologues of Borealin and Survivin, and T. brucei kinetochores also have a unique composition, being comprised of dozens of kinetoplastid-specific proteins (KKTs). Of particular importance for this study are KKT7 and the KKT8 complex (comprising KKT8, KKT9, KKT11, and KKT12). Here, Ballmer and Akiyoshi seek to understand how the CPC assembles and is targeted to its different locations during the cell cycle in T. brucei.
Strengths & Weaknesses:
Using immunoprecipitation and mass-spectrometry approaches, Ballmer and Akiyoshi show that AUK1, CPC1, and CPC2 associate with two orphan kinesins, KIN-A and KIN-B, and with the use of endogenously expressed fluorescent fusion proteins, demonstrate for the first time that KIN-A and KIN-B display a dynamic localisation pattern similar to other components of the CPC, providing compelling evidence for KIN-A and KIN-B being bona fide CPC proteins.
They then demonstrate, by using RNAi to deplete individual components, that the CPC proteins have hierarchical interdependencies for their localisation to the kinetochores at metaphase. These experiments appear to have been well performed.
Ballmer and Akiyoshi then go on to determine the kinetochore localisation domains of KIN-A and KIN-B. Using ectopically expressed GFP-tagged truncations, they show that coiled coil domains within KIN-A and KIN-B, as well as a disordered C-terminal tail present only in KIN-A, but not the N-terminal motor domains of KIN-A or KIN-B, are required for kinetochore localisation. These data are strengthened by immunoprecipitating CPC complexes and crosslinking them prior to mass spectrometry analysis (IP-CLMS), a state-of-the-art approach, to determine the contacts between the CPC components. Structural predictions of the CPC structure are also made using AlphaFold2, suggesting that coiled coils form between KIN-A and KIN-B, and that KIN-A/B interact with the N termini of CPC1 and CPC2. Experimental results showing that CPC1 and CPC2 are unable to localise to kinetochores if they lack their N-terminal domains are consistent with these predictions. Altogether these data provide compelling evidence of the protein domains required for CPC kinetochore localisation and CPC protein interactions and indicate that both KIN-A and KIN-B have a role to play.
Next, using a mixture of RNAi depletion and LacI-LacO recruitment experiments, the authors show that kinetochore proteins KKT7 and KKT9 are required for AUK1 to localise to kinetochores (other KKT8 complex components were not tested here) and that all components of the KKT8 complex are required for KIN-A kinetochore localisation. Further, both KKT7 and KKT8 were able to recruit AUK1 to an ectopic locus in S phase, and KKT7 recruited KKT8 complex proteins, indicating it is upstream of KKT8, in line with previous work showing kinetochore localization of KKT7 is unaffected by disruption of the KKT8 complex. This leads to the conclusion that the KKT8 complex is likely the main kinetochore receptor of the CPC.
Further IP-CLMS experiments, in combination with recombinant protein pull down assays and structural predictions, suggested that within the KKT8 complex, there are two subcomplexes of KKT8:KKT12 and KKT9:KKT11, and that KKT7 interacts with KKT9:KKT11 to recruit the remainder of the KKT8 complex. The authors also assess the interdependencies between KKT8 complex components for localisation and expression, showing that all four subunits are required for the assembly of a stable KKT8 complex and present AlphaFold2 structural modelling data to support the two subcomplex model. In general, these data are of high quality and convincing, although it is a shame that data showing the effects of KKT8, KKT9 and KKT12 depletion on KKT11 localisation and abundance could not be presented alongside the reciprocal experiments in Fig S4I-L.
The authors also convincingly show that AlphaFold2 predictions of interactions between KKT9:KKT11 and a conserved domain (CD1) in the C-terminal tail of KIN-A are correct, with CD1 and a second conserved domain, CD2, identified through sequence analysis, acting synergistically to promote KIN-A kinetochore localisation at metaphase, but not being required for KIN-A to move to the central spindle at anaphase. They then hypothesise that the kinesin motor domain of KIN-A (but not KIN-B which is predicted to be inactive based on non-conservation of residues key for activity) determines its central spindle localisation at anaphase through binding to microtubules. In support of this hypothesis, the authors show that KIN-A, but not KIN-B can bind microtubules in vitro and in vivo. However, ectopically expressed GFP-NLS fusions of full length KIN-A or KIN-A motor domain did not localise to the central spindle at anaphase. The authors suggest this is due to the GFP fusion disrupting the ATPase activity of the motor domain, although they provide no evidence that this is the case. Instead, they replace endogenous KIN-A with a predicted ATPase-defective mutant (G210A), showing that while this still localises to kinetochores, the kinetochores were frequently misaligned at metaphase, and that it no longer concentrates at the central spindle (with concomitant mis-localisation of AUK1), causing cells to accumulate at anaphase. From these data, the authors conclude that KIN-A ATPase activity is required for chromosome congression to the metaphase plate and its central spindle localisation at anaphase. While these data are highly suggestive that KIN-A possesses ATPase activity, and that this activity is essential for its function, definitive biochemical evidence of KIN-A's ATPase activity is still lacking.
Impact:
Overall, this work uses a wide range of cutting edge molecular and structural predictive tools to provide a significant amount of new and detailed molecular data that shed light on the composition of the unusual trypanosome CPC and how it is assembled and targeted to different cellular locations during cell division. Given the fundamental nature of this research, it will be of interest to many parasitology researchers as well as cell biologists more generally, especially those working on aspects of mitosis and cell division, and those interested in the evolution of the CPC.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Sang et al. successfully demonstrate that a set of single sensory neurons in the pharynx of Drosophila promotes avoidance of food with high salt concentrations, complementing previous findings on Ir7c neurons with an additional internal sensing mechanism. The experiments are well-conducted and presented, convincingly supporting their important findings and extending the understanding of internal sensing mechanisms.
The authors convincingly demonstrate the avoidance phenotype using different behavioral assays, thus comprehensively analyzing different aspects of the behavior. The experiments are straightforward and well-contextualized within existing literature.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors found two endosomal fusion modes by live cell imaging of endosomes in yolk sac lateral endoderm cells of 8.5-day-old embryonic mice and described the fusion modes by mathematical models and simulations. They also showed that actin polymerization is involved in the regulation of one of the fusion modes.
Strengths:
The strength of this study is that the authors' claims are well supported by beautiful live cell images and theoretical models. By using specialized cells, yolk sac visceral endoderm cells, the live images of endosomal fusion, localization of actin-related molecules, and validation data from multiple inhibitor experiments are clear.
Weaknesses:
This study does not include any assessment of whether the two types of endosome fusions claimed by the authors occur in general cells, so the article is limited to showing a phenomenon specific to yolk sac lateral endoderm cells. Also, the study does not show the physiological importance of the two types of fusion. There are some unclear points in the method of image analysis and some of the descriptions in the text are not logical.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors use docking and molecular dynamics (MD) simulations to investigate transient conformations that are otherwise difficult to resolve experimentally. The docking and simulations suggest an interesting series of events whereby agonists initially bind to the low affinity site and then flip 180 degrees as the site contracts to its high affinity conformation. This work will be of interest to the ion channel community and to biophysical studies of pentameric ligand-gated channels.
Strengths:
I find the premise for the simulations to be good, starting with an antagonist bound structure as an estimate of the low affinity binding site conformation, then docking agonists into the site and using MD to allow the site to relax to a higher affinity conformation that is similar to structures in complex with agonists. The predictions are interesting and provide a view into what a transient conformation that is difficult to observe experimentally might be like.
Weaknesses:
A weakness is that the relevance of the initial docked low affinity orientations depend solely on in silco results, for which simulated vs experimental binding energies deviate substantially for two of the four ligands tested. This raises some doubt as to the validity of the simulations. I acknowledge that the calculated binding energies for two of the ligands were closer to experiment, and simulated efficiencies were a good representation of experimental measures, which gives some support to the relevance of the in silico observations. Regardless, some of the reviewers comments regarding the simulation methodology were not seriously addressed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript details the characterization of ClpL from L. monocytogenes as a potent and autonomous AAA+ disaggregase. The authors demonstrate that ClpL has potent and DnaK-independent disaggregase activity towards a variety of aggregated model substrates, and that this disaggregase activity appears to be greater than that observed with the canonical DnaK/ClpB co-chaperone. Furthermore, LmClpL appears to have greater thermostability as compared to LmDnaK, suggesting that ClpL-expressing cells may be able to withstand more severe heat stress conditions. Interestingly, LmClpL can provide thermotolerance to E. coli that have been genetically depleted of either ClpB or in cells expressing a mutant DnaK103. The authors further characterized the mechanisms by which ClpL interacts with protein aggregates, identifying that the N-terminal domain of ClpL is essential for disaggregase function. Lastly, by EM and mutagenesis analysis the authors report that ClpL can exist in a variety of larger macromolecular complexes, including dimer or trimers of hexamers/heptamers, and they provide evidence that the N-terminal domains of ClpL prevent dimer ring formation, thus promoting an active and substrate-binding ClpL complex. Throughout this manuscript the authors compare LmClpL to ClpG, another potent and autonomous disaggregase found in gram-negative bacteria that has been reported on previously, demonstrating that these two enzymes share homologous activity and qualities. Taken together this report clearly establishes ClpL as a novel and autonomous disaggregase.
Analysis:
The work presented in this report amounts to a significant body of novel and significant work that will be of interest to protein chaperone community. Furthermore, by providing examples of how ClpL can provide in vivo thermotolerance to both E. coli and L. gasseri the authors have expanded the significance of this work and provides novel insight into potential mechanisms responsible for thermotolerance in food-borne pathogens. The figures are clearly depicted, well-labeled, and easy to understand, and the manuscript is well-written. Experimentally the work was performed to a high standard with excellent controls, aiding in the ability for the audience to understand the major findings and conclusions. Additionally, the authors have effectively and efficiently expanded on their work through the peer review process, further increasing the understandability and significance of their work. Overall, the data presented, and analysis thereof, support the authors' conclusions, and thus this study represents an important addition to our understanding of molecular chaperone biochemistry. Lastly, this study establishes new avenues for research into autonomous disaggregates, their role in in vivo thermotolerance, and the mechanisms by which AAA+ chaperones recognize and interact with substrate proteins.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this article, Gao et. al. uses single-molecule FRET (smFRET) and position-specific labelling of RNA (PLOR) to dissect the folding and behavioral ligand sensing of the Guanidine-IV riboswitch in the presence and absence of the ligand guanidine and the cation Mg2+. The results provided valuable information on the mechanistic aspects of the riboswitch, including the confirmation of the kissing loop present in the structure as essential for folding and riboswitch activity. Co-transcriptional investigations of the system provided key information on the ligand-sensing behavior and ligand-binding window of the riboswitch. A plausible folding model of the Guanidine-IV riboswitch was proposed as a final result. The evidence presented here sheds additional light on the mode of action of transcriptional riboswitches.
Strengths:
The investigations were very thorough, providing data that supports the conclusions. The use of smFRET and PLOR to investigate RNA folding has been shown to be a valuable tool for the understanding of folding and behavior properties of these structured RNA molecules. The co-transcriptional analysis brought important information on how the riboswitch works, including the ligand-sensing and the binding window that promotes the structural switch. The fact that investigations were done with the aptamer domain, aptamer domain + terminator/anti-terminator region, and the full-length riboswitch were essential to inform how each domain contributes to the final structural state if in the presence of the ligand and Mg2+.
Weaknesses:
The system has its own flaws when compared to physiological conditions. The RNA polymerase used (the study uses T7 RNA polymerase) is different from the bacterial RNA polymerase, not only in complexity, but also in transcriptional speed, which can directly interfere with folding and ligand-sensing. Additionally, rNTPs concentrations were much lower than physiological concentrations during transcription, likely causing a change in the polymerase transcriptional speed. These important aspects and how they could interfere with results are important to be addressed to the broad audience. Another point of consideration to be aware of is that the bulky fluorophores attached to the nucleotides can interfere with folding to some extent.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Zeng and Stanley show that in yeast, intron-lariat intermediates that accumulated due to defects in pre-mRNA splicing, are transported to the cytoplasm using the canonical mRNA export pathway. Moreover, they demonstrate that export requires the nuclear basket, a sub-structure of the nuclear pore complex previously implicated with the retention of immature mRNAs. These observations are important as they put into question a longstanding model that the main role of the nuclear basket is to ensure nuclear retention of immature or faulty mRNAs.
Strengths:
The authors elegantly combine genetic, biochemical, and single-molecule resolution microscopy approaches to identify the cellular pathway that mediates the cytoplasmic accumulation of lariat intermediates. Cytoplasmic accumulation of such splicing intermediates had been observed in various previous studies but how these RNAs reach the cytoplasm had not yet been investigated. By using smFISH, the authors present compelling, and, for the first time, direct evidence that these intermediates accumulate in the cytoplasm and that this requires the canonical mRNA export pathway, including the RNA export receptor Mex67 as well as various RNA-binding proteins including Yra1, Npl3 and Nab2. Moreover, they show that the export of lariat intermediates, but not mRNAs, requires the nuclear basket (Mlp1) and basket-associated proteins previously linked to the mRNP rearrangements at the nuclear pore. This is a surprising and important observation with respect to a possible function of the nuclear basket in mRNA export and quality control, as it challenges a longstanding model that the role of the basket in mRNA export is primarily to act as a gatekeeper to ensure that immature mRNAs are not exported. As discussed by the authors, their finding suggests a role for the basket in promoting the export of certain types of RNAs rather than retention, a model also supported by more recent studies in mammalian cells. Moreover, their findings also collaborate with a recent paper showing that in yeast, not all nuclear pores contain a basket (PMID: 36220102), an observation that also questioned the gatekeeper model of the basket, as it is difficult to imagine how the basket can serve as a gatekeeper if not all nuclear pore contain such a structure.
Weaknesses:
One weakness of this study is that all their experiments rely on using synthetic splicing reporter containing a lacZ gene that produces a relatively long transcript compared to the average yeast mRNA.
The rationale for using a reporter containing the brG (G branch point) resulting in more stable lariat intermediates due to them being inefficient substrates for the debranching enzyme Dbr1 could be described earlier in the manuscript, as this otherwise only becomes clear towards the end, what is confusing.
Discussion of their observation in the context that, in yeast, not all pores contain a basket would be useful.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors provide the first image analysis by cryoET of toroids assembled by FtsZ crosslinked by ZapD. Previously toroids of FtsZ alone have been imaged only in projection by negative stain EM. The authors attempt to distinguish ZapD crosslinks from the underlying FtsZ filaments. I did not find this distinction convincing, especially because it seems inconsistent with the 1:1 stoichiometry demonstrated by pelleting. I was intrigued by one image showing straight filament pairs, which may suggest a new model for how ZapD crosslinks FtsZ filaments.
Strengths:
(1) The first image analysis of FtsZ toroids by cryoET.<br /> (2) The images are accompanied by pelleting assays that convincingly establish a 1:1 stoichiometry of FtsZ:ZapD subunits.<br /> (3) Fig. 5 shows an image of a pair of FtsZ filaments crosslinked by ZapD. This seems to have higher resolution than the toroids. Importantly, it suggests a new model for the structure of FtsZ-ZapD that resolves previously unrecognized conflicts. (This is discussed below under weaknesses, because it is so far only supported by a single image.)
Weaknesses:
This paper reports a study by cryoEM of polymers and bundles assembled from FtsZ plus ZapD. Although previous studies by other labs have focused on straight bundles of filaments, the present study found toroids mixed with these straight bundles, and they focused most of their study on the toroids. In the toroids they attempt to delineate FtsZ filaments and ZapD crosslinks. A major problem here is with the stoichiometry. Their pelleting assays convincingly established a stoichiometry of 1:1, while the mass densities identified as ZapD are sparse and apparently well below the number of FtsZ (FtsZ subunits are not resolved in the reconstructions, but the continuous sheets or belts seem to have a lot more mass than the identified crosslinks.) Apart from the stoichiometry I don't find the identification of crosslinks to be convincing. It is missing an important control - cryoET of toroids assembled from pure FtsZ, without ZapD.
However, if I ignore these and jump to Fig. 5, I think there is an important discovery that resolves controversies in the present study as well as previous ones, controversies that were not even recognized. The controversy is illustrated by the Schumacher 2017 model (their Fig. 7), which is repeated in a simplified version in Fig. 1a of the present mss. That model has a two FtsZ filaments in a plane facing ZapD dimers which bridge them. In this planar model the C-terminal linker, and the ctd of FtsZ that binds ZapD facing each other and the ZapD in the middle, with. The contradiction arises because the C-terminus needs to face the membrane in order to attach and generate a bending force. The two FtsZ filaments in the planar model are facing 90{degree sign} away from the membrane. A related contradiction is that Houseman et al 2016 showed that curved FtsZ filaments have the C terminus on the outside of the curve. In a toroid the C termini should all be facing the outside. If the paired filaments had the C termini facing each other, they could not form a toroid because the two FtsZ filaments would be bending in opposite directions.
Fig. 5 of the present mss seems to resolve this by showing that the two FtsZ filaments and ZapD are not planar, but stacked. The two FtsZ filaments have their C termini facing the same direction, let's say up, toward the membrane, and ZapD binds on top, bridging the two. The spacing of the ctd binding sites on the Zap D dimer is 6.5 nm, which would fit the ~8 nm width of the paired filament complex observed in the present cryoEM (Fig S13). In the Schumacher model the width would be about 20 nm. Importantly, the stack model has the ctd of each filament facing the same direction, so the paired filaments could attach to the membrane and bend together (using ctd's not bound by ZapD). Finally, the new arrangement would also provide an easy way for the complex to extend from a pair of filaments to a sheet of three or four or more.
A problem with this new model from Fig. 5 is that it is supported by only a single example of the paired FtsZ-ZapD complex. If this is to be the basis of the interpretation, more examples should be shown. Maybe examples could be found with three or four FtsZ filaments in a sheet.
What then should be done with the toroids? I am not convinced by the identification of ZapD as "connectors." I think it is likely that the ZapD is part of the belts that I discuss below, although the relative location of ZapD in the belts is not resolved. It is likely that the resolution in the toroid reconstructions of Fig. 4, S8,9 is less than that of the isolated pf pair in Fig. 5c.
Importantly, If the authors want to pursue the location of ZapD in toroids, I suggest they need to compare their ZapD-containing toroids with toroids lacking ZapD. Popp et al 2009 have determined a variety of solution conditions that favor the assembly of toroids by FtsZ with no added protein crosslinker. It would be very interesting to investigate the structure of these toroids by the present cryoEM methods, and compare them to the FtsZ-ZapD toroids. I suspect that the belts seen in the ZapD toroids will not be found in the pure FtsZ toroids, confirming that their structure is generated by ZapD.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this paper, Wang et al. provide the most comprehensive description and comparison of the expression of the different genes required to synthesize, transport, and recycle the most common neurotransmitters (Glutamate, Acetylcholine, GABA, Serotonin, Dopamine, Octopamine, and Tyramine) used by hermaphrodite and male C. elegans. This paper will be a seminal reference in the field. Building and contrasting observations from previous studies using fosmid, multicopy reporters, and single-cell sequencing, they now describe CRISPR/Cas-9-engineered reporter strains that, in combination with the multicolor pan-neuronal labeling of all C. elegans neurons (NeuroPAL), allows rigorous elucidation of neurotransmitter expression patterns. These novel reporters also illuminate previously unappreciated aspects of neurotransmitter biology in C. elegans, including sexual dimorphism of expression patterns, co-transmission, and the elucidation of cell-specific pathways that might represent new forms of neurotransmission.
Strengths:
The authors set out to establish neurotransmitter identities in C. elegans males and hermaphrodites via varying techniques, including integration of previous studies, examination of expression patterns, and generation of endogenous CRISPR-labeled alleles. Their study is comprehensive, detailed, and rigorous, and achieves the aims. It is an excellent reference for the field, particularly those interested in biosynthetic pathways of neurotransmission and their distribution in vivo, in neuronal and non-neuronal cells.
Weaknesses:
No weaknesses were noted. The authors do a great job linking their characterizations with other studies and techniques, giving credence to their findings. As the authors note, there are sexually dimorphic differences across animals and varying expression patterns of enzymes. While it is unlikely there will be huge differences in the reported patterns across individual animals, it is possible that these expression patterns could vary developmentally, or based on physiological or environmental conditions. It is unclear from the study how many animals were imaged for each condition, and if the authors noted changes across individuals during development (could be further acknowledged in the discussion?)
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Reviewer #3 (Public Review):
In the submitted manuscript, Dong and colleagues set out to dissect the role of the Rab10 small GTPase on the intracellular trafficking and exocytosis of dense core vesicles (DCVs). While the authors have already shown that Rab3 plays a central role in the exocytosis of DVC in mammalian neurons, the roles of several other Rab-members have been identified genetically, but their precise mechanism of action in mammalian neurons remains unclear. In this study, the authors use a carefully designed and thoroughly executed series of experiments, including live-cell imaging, functional calcium-imaging, proteomics, and electron microscopy, to identify that DCV secretion upon Rab10 depletion in adult neurons is primarily a result of dysregulated protein synthesis and, to a lesser extent, disrupted intracellular calcium buffering. Given that the full deletion of Rab10 has a deleterious effect on neurons and that Rab10 has a major role in axonal development, the authors cautiously employed the knock-down strategy from 7 DIV, to focus on the functional impact of Rab10 in mature neurons. The experiments in this study were meticulously conducted, incorporating essential controls and thoughtful considerations, ensuring rigorous and comprehensive results.
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Reviewer #3 (Public Review):
Summary
The authors have made simultaneous recordings of the responses of large numbers of neurons from the primary visual cortex of macaque monkeys using optical two-photon imaging of calcium signals from the superficial layers of the cortex. Recordings were made to compare the responses of the cortical neurons under normal binocular viewing of a flat screen with both eyes open and monocular viewing of the same screen with one eye's view blocked by a translucent filter. The screen displayed visual stimuli comprising small contrast patches of Gabor function distributions of luminance, a stimulus that is known to excite cortical neurons.
Strengths
This is an important data set, given the large number of neurons recorded. The authors present a simple model to explain binocular combination of neuronal signals from the right and left eyes. The work advances the use of two-photon imaging in the cerebral neocortex. The research design adds valuable information to our understanding of the organization of binocular vision in macaque monkeys, which are the only realistic animal model of human vision for the study of binocular interactions.
Limitations and Weaknesses
(1) Given that these recordings are made optically, these results reflect primarily activations of neurons in the superficial layers of the cortex. This limitation arises from the usual constraints (depth of cortex, degree of myelination) on optical imaging in the macaque cortex. This means that the sample of neurons forming this data set is not fully representative of the population of binocular neurons within the visual cortex. This limitation is important in comparing the outcome of these experiments with the results from other studies of binocular combination, which have used single-electrode recording. Electrode recording will result in a sample of neurons that is drawn from many layers of the cortex, rather than just the superficial layers, noting that electrode recordings also carry different risks of sampling bias.
(2) Single neuron recording of binocular neurons in the primary visual cortex has shown that these neurons often have some spontaneous activity. Assessment of this spontaneous level of firing is important for accurate model fitting [1]. The present imaging approach works exclusively with differential measurements of neuronal signals, so assessment of the level of spontaneous activity is not feasible.
(3) The arrangements for visual stimulation and comparison of binocular and monocular responses mean that the stereoscopic disparity of the binocular stimuli is always at zero or close to zero. The consequence is that the experimental design does not test the cortical response over a range of different binocular depths.
The animal's fixation point is in the centre of a single display that is viewed binocularly. The fixation point is, by definition, at zero disparity.. Provided that the animals accurately converged their eyes on the binocular fixation point, then the disparity of the visual stimuli across the whole display will always be at or close to zero. However, we already know from earlier work that neurons in the visual cortex exhibit a range of selectivity for binocular disparity. Some neurons have their peak response at non-zero disparities, representing binocular depths nearer than the fixation depth or beyond it.
There are also other neurons whose response is maximally suppressed by disparities at the depth of the fixation point (so-called Tuned Inhibitory [TI] neurons). The simple model and analysis presented in the paper for the summation of monocular responses to predict binocular responses will perform adequately for neurons that are tuned to zero disparity, so-called tuned excitatory neurons [TE], but is necessarily compromised when applied to neurons that have other, different tuning profiles for binocular disparity. Specifically, when neurons are stimulated binocularly with a non-preferred disparity, the binocular response may be lower than the monocular response [2, 3]. The same limitation applies to another recent paper [4].
This more realistic view of binocular responses needs to be considered further to gain a full picture of the operation of the visual cortex in responding to binocular depth
Citations
1. Prince, S.J.D., Pointon, A.D., Cumming, B.G., and Parker, A.J., (2002). Quantitative analysis of the responses of V1 neurons to horizontal disparity in dynamic random-dot stereograms. Journal of Neurophysiology, 87: 191-208.
2. Prince, S.J.D., Cumming, B.G., and Parker, A.J., (2002). Range and mechanism of encoding of horizontal disparity in macaque V1. Journal of Neurophysiology, 87: 209-221.
3. Poggio, G.F. and Fischer, B., (1977). Binocular interaction and depth sensitivity in striate and prestriate cortex of behaving rhesus monkey. Journal of Neurophysiology, 40: 1392-1405 doi 10.1152/jn.1977.40.6.1392.
4. B. A. Mitchell, K. Dougherty, J. A. Westerberg, B. M. Carlson, L. Daumail, A. Maier, et al. (2022) Stimulating both eyes with matching stimuli enhances V1 responses.<br /> iScience 2022 Vol. 25 Issue 5 DOI: 10.1016/j.isci.2022.104182
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Reviewer #3 (Public Review):
Strengths:
The authors present differences between ADHD and TD children in biological motion processing, and this question has not received as much attention as equivalent processing capabilities in autism. They use a task that appears well controlled. They raise some interesting mechanistic possibilities for differences in local and global motion processing, which are distinctions worth exploring. The group differences will therefore be of interest to those studying ADHD, as well as other developmental conditions, and those examining biological motion processing mechanisms in general.
Weaknesses:
The data are not strong enough to support claims about differences between global and lobal processing wrt social communication skills and age. The mechanistic possibilities for why these abilities may dissociate in such a way are interesting, but the crucial tests of differences between correlations do not present a clear picture. Further empirical work would be needed to test the authors' claims. Specifics:
The authors state frequently that it was the local BM task that related to social communication skills (SRS) and not the global tasks. However, the results section shows a correlation between SRS and all three tasks. The only difference is that when looking specifically within the ADHD group, the correlation is only significant for the local task. The supplementary materials demonstrate that tests of differences between correlations present an incomplete picture. Currently they have small samples for correlations, so this is unsurprising.
Theoretical assumptions. The authors make some statements about local vs global biological motion processing that should still be made more tentatively. They assume that local processing is specifically genetically whereas global processing is a product of experience. These data in newborn chicks are controversial and confounded - I cannot remember the specifics but I think there an upper vs lower visual field complexity difference here.
Readability. The manuscript needs very careful proofreading and correction for grammar. There are grammatical errors throughout.
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Reviewer #3 (Public Review):
Summary:
This study aimed to investigate whether the development of functional connectivity (FC) is modulated by early physical growth and whether these might impact cognitive development in childhood. This question was investigated by studying a large group of infants (N=204) assessed in Gambia with fNIRS at 5 visits between 5 and 24 months of age. Given the complexity of data acquisition at these ages and following data processing, data could be analyzed for 53 to 97 infants per age group. FC was analyzed considering 6 ensembles of brain regions and thus 21 types of connections. Results suggested that: i) compared to previously studied groups, this group of Gambian infants have different FC trajectory, in particular with a change in frontal inter-hemispheric FC with age from positive to null values; ii) early physical growth, measured through weight-for-length z-scores from birth on, is associated with FC at 24 months. Some relationships were further observed between FC during the first two years and cognitive flexibility at 4-5 years of age, but results did not survive corrections for multiple comparisons.
Strengths:
The question investigated in this article is important for understanding the role of early growth and undernutrition on brain and behavioral development in infants and children. The longitudinal approach considered is highly relevant to investigate neurodevelopmental trajectories. Furthermore, this study targets a little-studied population from a low-/middle-income country, which was made possible by the use of fNIRS outside the lab environment. The collected dataset is thus impressive and it opens up a wide range of analytical possibilities.
Weaknesses:
- Analyzing such a huge amount of collected data at several ages is not an easy task to test developmental relationships between growth, FC, and behavioral capacities. In its present form, this study and the performed analyses lack clarity, unity and perhaps modeling, as it suggests that all possible associations were tested in an exploratory way without clear mechanistic hypotheses. Would it be possible to specify some hypotheses to reduce the number of tests performed? In particular, considering metrics at specific ages or changes in the metrics with age might allow us to test different hypotheses: the authors might clarify what they expect specifically for growth-FC-behaviour associations. Since some FC measures and changes might be related to one another, would it be reasonable to consider a dimensionality reduction approach (e.g., ICA) to select a few components for further correlation analyses?
- It seems that neurodevelopmental trajectories over the whole period (5-24 months) are little investigated, and considering more robust statistical analyses would be an important aspect to strengthen the results. The discussion mentions the potential use of structural equation modelling analyses, which would be a relevant way to better describe such complex data.
- Given the number of analyses performed, only describing results that survive correction for multiple comparisons is required. Unifying the correction approach (FDR / Bonferroni) is also recommended. For the association between cognitive flexibility and FC, results are not significant, and one might wonder why FC at specific ages was considered rather than the change in FC with age. One of the relevant questions of such a study would be whether early growth and later cognitive flexibility are related through FC development, but testing this would require a mediation analysis that was not performed.
- Growth is measured at different ages through different metrics. Justifying the use of weight-for-length z-scores would be welcome since weight-for-age z-scores might be a better marker of growth and possible undernutrition (this impacting potentially both weight and length). Showing the distributions of these z-scores at different ages would allow the reader to estimate the growth variability across infants.
- Regarding FC, clarifications about the long-range vs short-range connections would be welcome, as well as drawing a summary of what is expected in terms of FC "typical" trajectory, for the different brain regions and connections, as a marker of typical development. For instance, the authors suggest that an increase in long-range connectivity vs a decrease in short-range is expected based on previous fNIRS studies. However anatomical studies of white matter growth and maturation would suggest the reverse pattern (short-range connections developing mostly after birth, contrarily to long-range connections prenatally).
The authors test associations between FC and growth, but making sense of such modulation results is difficult without a clearer view of developmental changes per se (e.g., what does an early negative FC mean? Is it an increase in FC when the value gets close to 0? In particular, at 24m, it seems that most FC values are not significantly different from 0, Figure 2B). Observing positive vs negative association effects depending on age is quite puzzling. It is also questionable, for some correlation analyses with cognitive flexibility, to focus on FC that changes with age but to consider FC at a given age.
- The manuscript uses inappropriate terms "to predict", "prediction" whereas the conducted analyses are not prediction analyses but correlational.
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Reviewer #3 (Public Review):
Summary:
Garcia et al., investigated whether the human left superior frontal sulcus (SFS) is involved in integrating evidence for decisions across either perceptual and/or value-based decision-making. Specifically, they had 20 participants perform two decision-making tasks (with matched stimuli and motor responses) in an fMRI scanner both before and after they received continuous theta burst transcranial magnetic stimulation (TMS) of the left SFS. The stimulation thought to decrease neural activity in the targeted region, led to reduced accuracy on the perceptual decision task only. The pattern of results across both model-free and model-based (Drift diffusion model) behavioural and fMRI analyses suggests that the left SLS plays a critical role in perceptual decisions only, with no equivalent effects found for value-based decisions. The DDM-based analyses revealed that the role of the left SLS in perceptual evidence accumulation is likely to be one of decision boundary setting. Hence the authors conclude that the left SFS plays a domain-specific causal role in the accumulation of evidence for perceptual decisions. These results are likely to add importance to the literature regarding the neural correlates of decision-making.
Strengths:
The use of TMS strengthens the evidence for the left SFS playing a causal role in the evidence accumulation process. By combining TMS with fMRI and advanced computational modelling of behaviour, the authors go beyond previous correlational studies in the field and provide converging behavioural, computational, and neural evidence of the specific role that the left SFS may play.
Sophisticated and rigorous analysis approaches are used throughout.
Weaknesses:
Though the stimuli and motor responses were equalised between the perception and value-based decision tasks, reaction times (according to Figure 1) and potential difficulty (Figure 2) were not matched. Hence, differences in task difficulty might represent an alternative explanation for the effects being specific to the perception task rather than domain-specificity per se.
No within- or between-participants sham/control TMS condition was employed. This would have strengthened the inference that the apparent TMS effects on behavioural and neural measures can truly be attributed to the left SFS stimulation and not to non-specific peripheral stimulation and/or time-on-task effects.
No a priori power analysis is presented.
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Reviewer #3 (Public Review):
Summary:
In this very important study by Dantzer et al., 'Emerging role of oncogenic b-catenin in exosome biogenesis as a driver of immune escape in hepatocellular carcinoma' the authors define a role for oncogenic b-catenin on exosome biology and explore the link between reduce exosome secretion and tumor immune cell evasion. Using transcriptional and proteomic analysis of hepatocellular carcinoma cells with either oncogenic or wildtype b-catenin the authors find that oncogenic b-catenin negatively regulates exosome biogenesis.
The authors can provide compelling evidence that oncogenic b-catenin in different hepatocellular carcinoma cells negatively regulates exosome biogenesis and secretion, by downregulation of, amongst others, SDC4 and RAB27A, two proteins involved in exosome biogenesis. The authors corroborate these results by inducing b-catenin activation using CHIR99021 in a hepatocarcinoma cell line with non-oncogenic bCatenin (Huh7 cells). The authors can further demonstrate convincingly that a reduction in exosome release by hepatocarcinoma spheroids leads to a reduction in immune cell infiltration into the tumor spheroid.
Strengths:
This is a very important and well-conceived study, that appeals to a readership beyond the field of hepatocarcinoma. The authors demonstrate a compelling link between oncogenic bCatenin and exosome biogenesis. Their results are convincing and with well-designed control experiments. The authors included various complementary lines of investigation to verify their findings.
Weaknesses:
One limitation of this study is that the mechanistic relationship of exosome release and how they affect immune cells remains to be elucidated. In this context, the authors conclusions rest on the assumption that hepatocarcinoma immune evasion is based exclusively on the reduced number of exosomes. However, the authors do not analyze exosome composition between exosomes of wild type and oncogenic background, which could be different.
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Reviewer #3 (Public Review):
Summary:
This study aims to understand gene regulation of the plant bacterial pathogen Pseudomonas syringae. Although the function of some TFs has been characterized in this strain, a global picture of the gene regulatory network remains elusive. The authors conducted a large-scale ChIP-seq analysis, covering 170 out of 301 TFs of this strain, and revealed gene regulatory hierarchy with functional validation of some previously uncharacterized TFs.
Strengths:
- This study provides one of the largest ChIP-seq datasets for a single bacterial strain, covering more than half of its TFs. This impressive resource enabled comprehensive systems-level analysis of the TF hierarchy.
- This study identified novel gene regulation and function with validations through biochemical and genetic experiments.
- The authors attempted on broad analyses including comparisons between different bacterial strains, providing further insights into the diversity and conservation of gene regulatory mechanisms.
Weaknesses:
(1) Some conclusions are not backed by quantitative or statistical analyses, and they are sometimes overinterpreted.
(2) Some figures and analyses are not well explained, and I was not able to understand them.
(3) The Method section lacks depth, especially in data analyses. It is strongly recommended that the authors share their analysis codes so that others can reproduce the analyses.
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Reviewer #3 (Public Review):
When members of two related but diverged species mate, the resulting hybrids can produce offspring where parts of one species' genome replace those of the other. These "introgressions" often create regions with a much greater density of sequence differences than are normally found between members of the same species. Previous studies have shown that increased sequence differences, when heterozygous, can reduce recombination during meiosis specifically in the region of increased difference. However, most of these studies have focused on crossover recombination, and have not measured noncrossovers. The current study uses a pair of Saccharomyces uvarum crosses: one between two natural isolates that, while exhibiting some divergence, do not contain introgressions; the other is between two fermentation strains that, when combined, are heterozygous for 9 large regions of introgression that have much greater divergence than the rest of the genome. The authors wished to determine if introgressions differently affected crossovers and noncrossovers, and, if so, what impact that would have on the gene shuffling that occurs during meiosis.
While both crossovers and noncrossovers were measured, assessing the true impact of increased heterology (inherent in heterozygous introgressions) is complicated by the fact that the increased marker density in heterozygous introgressions also increases the ability to detect noncrossovers. The authors used a relatively simple correction aimed at compensating for this difference, and based on that correction, conclude that, while as expected crossovers are decreased by increased sequence heterology, counter to expectations noncrossovers are substantially increased. They then show that, despite this, genetic shuffling overall is substantially reduced in regions of heterozygous introgression. However, it is likely that the correction used to compensate for the effect of increased sequence density is defective, and has not fully compensated for the ascertainment bias due to greater marker density. The simplest indication of this potential artifact is that, when crossover frequencies and "corrected" noncrossover frequencies are taken together, regions of introgression often appear to have greater levels of total recombination than flanking regions with much lower levels of heterology. This concern seriously undercuts virtually all of the novel conclusions of the study.
Until this methodological concern is addressed, the work will not be a useful contribution to the field.
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Reviewer #3 (Public Review):
While I am not a specialist in this field, I do have some knowledge of the subject matter and the computational aspects involved.
The authors employ simple machine learning techniques (such as SVM) for the following purposes:
a. Prediction of aversive valence.<br /> b. Predicting anti-repellent chemicals.<br /> c. Predicting calcium mobilization.
The approach is commonplace in chemoinformatics literature.
Weaknesses:
- All the above models are presented discretely, making it difficult to discern experiment design principles and connectedness.<br /> - The ML work is rudimentary, lacking adequate details. Chemoinformatics has reached great heights, and SVM does not seem contemporary.<br /> - There is significant existing research on finding repellents.
Strengths:
- Authors attempt to make a case for calcium mobilization in the context of repellency. This aspect sounds interesting but is not surprising.<br /> - Behavioral profiling of repellents could be useful.
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Reviewer #3 (Public Review):
Summary:<br /> This work focuses on accessibility of scientific images for individuals with color vision deficiencies, particularly deuteranopia. The research involved an analysis of images from eLife published in 2012-2022. The authors manually reviewed nearly 5,000 images, comparing them with simulated versions representing the perspective of individuals with deuteranopia, and also evaluated several methods to automatically detect such images including training a machine-learning algorithm to do so, which performed the best. The authors found that nearly 13% of the images could be challenging for people with deuteranopia to interpret. There was a trend toward a decrease in problematic images over time, which is encouraging.
Strengths:<br /> The manuscript is well organized and written. It addresses inclusivity and accessibility in scientific communication, and reinforces that there is a problem and that in part technological solutions have potential to assist with this problem.
The number of manually assessed images for evaluation and training an algorithm is, to my knowledge, much larger than any existing survey. This is a valuable open source dataset beyond the work herein.
The sequential steps used to classify articles follow best practices for evaluation and training sets.
Weaknesses:<br /> I do not see any major issues with the methods. The authors were transparent with the limitations (the need to rely on simulations instead of what deuteranopes see), only capturing a subset of issues related to color vision deficiency, and the focus on one journal that may not be representative of images in other journals and disciplines.
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Reviewer #3 (Public Review):
Summary:
This paper uses indirect immunofluorescence, superresolution fluorescence microscopy, and X-ChIP to demonstrate radial distribution profiles of all histone H1 somatic variants with the exception of histone H1.1. The results support earlier work from chromatin immunoprecipitation experiments that revealed biases for active versus repressed states of chromatin. The previous studies provided some support for the subtle sequence variation found primarily within the C-terminus of histone H1 variants conferred preferences in the type of DNA (e.g. methylated DNA) or chromatin bound. The current study significantly strengthens that argument. Importantly, this was shown across multiple cell lines and reveals conserved properties of localization of histone H1 variants.
Strengths:
The strength of the manuscript is the combined use of quantitative analysis of indirect immunofluorescence and X-ChIP. The results generally support the polar organization of the genome and a corresponding distribution of histone H1 variants that reflect this polar organization. AT-rich chromatin is positioned near the lamina and is found to be enriched in H1.2, H1.3, and H1.5. H1.4 and H1.X were more biased towards the GC-rich intranuclear chromatin.
There is emerging functional evidence for variant-specific properties to histone H1 subtypes. This work provides an important building block in understanding how different histone H1 variants may have specific functional consequences. The histone H1 variant that is most abundant in most cell types, H1.2, was found to decrease the area of the immunofluorescent slice that was chromatin-free when depleted, suggesting a more important role in global chromatin organization.
Weaknesses:
While histone H1 variants may show biases in their distributions, it is unlikely that these are more than biases. That is, it is unlikely that specific H1 variants are unable to bind to nucleosomes in regions where they are depleted. Fluorescence recovery after photobleaching experiments have demonstrated differences in binding affinity but the capacity to bind a range of chromatin structures, including highly acetylated chromatin, for histone H1 variants. Thus, it is critical in assessing this data to have accurate quantitative information on the relative abundance of the different histone variants amongst the cell lines tested here. The paper relies upon quantification by immunoblotting.
Another uncertainty in both the ChIP and immunofluorescence datasets is the accessibility of the epitope. This weakness is highlighted by the apparent loss of H1.2 and H1.4 in mitotic chromosomes that is revealed to be false by the detection of the phosphorylated species. The distributions relative to the surface of chromosomes in mitosis and the depletion of H1.2, H1.3, and H1.5 from the central regions of interphase nuclei reveals an unusual dissipation of the staining that is suggestive of antibody accessibility problems. The overall image quality of the immunofluorescence images is poor, further complicating analysis.
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Reviewer #3 (Public Review):
In this study, Yang et al. address a fundamental question of the role of dorsal striatum in neural coding of gait. The authors study the respective role of D1 and D2 MSNs by linking their balanced activity to detailed gait parameters. In addition, they put in parallel the striatal activity related to whole-body measures such as initiation/cessation of movement or body speed. They are using an elegant combination of high-resolution single-limb motion tracking, identification of bouts of movements and electrophysiological recordings of striatal neurons to correlate those different parameters. Subpopulations of striatal output neurons (D1 and D2 expressing neurons) are identified in neural recordings with optogenetic tagging. Those complementary approaches show that a subset of striatal neurons have phase-locked activity to individual limbs. In addition, more than a third of MSNs appear to encode all three aspects of motor behavior addressed here, initiation/cessation of movement, body speed and gait. This activity is balanced between D1 and D2 neurons, with a higher activity of D1 neurons only for movement initiation. Finally, alterations of gait, and the associated striatal activity, is studied in a mouse model of Parkinson's Disease, using 6-OHDA lesions in the medial forebrain bundle (MFB). In the 6OHDA mice, there is an imbalance toward D2 activity.
Strengths:
The study combines elegant approaches to correlate cell-specific striatal activity with specific aspects of motion and how it is affected in a PD model. The results are convincing, and the methodology supports the conclusions presented here.
Weaknesses:
All the data were not fully exploited or explained in the first version of the manuscript and the present version has been significantly improved.
There is a long-standing debate on the respective role of D1 and D2 MSNs on the control of movement. This study goes beyond prior work by providing detailed quantification of individual limb kinematics, in parallel of whole-body motion, and showing high proportion of MSNs to be phase-locked to precise gait cycle and also encoding whole-body motion. The temporal resolution used here highlights preferential activity of D1 MSN at the movement starts, where previous studies described a more balanced involvement. Finally they reveal neural mechanisms of dopamine depletion induced gait alterations, with a preponderant phase-locked activity of D2 neurons.
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Reviewer #3 (Public Review):
Summary:
Male fertility depends on both sperm and seminal plasma, but the functional effect of seminal plasma on sperm has been relatively understudied. The authors investigate the testosterone-dependent synthesis of seminal plasma and identify oleic acid as a key factor in enhancing sperm fertility.
Strengths:
The evidence for changes in cell proliferation and metabolism of seminal vesicle epithelial cells and the identification of oleic acid as a key factor in seminal plasma is solid.
Weaknesses:
The evidence that oleic acids enhance sperm fertility in vivo needs more experimental support, as the main phenotypic effect in vitro provided by the authors remains simply as an increase in the linearity of sperm motility, which does not necessarily correlate with enhanced sperm fertility.
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Reviewer #3 (Public Review):
Summary:
The authors aimed to study the activation of gliogenesis and the role of newborn astrocytes in a post-ischemic scenario. Combining immunofluorescence, BrdU-tracing, and genetic cellular labelling, they tracked the migration of newborn astrocytes (expressing Thbs4) and found that Thbs4-positive astrocytes modulate the extracellular matrix at the lesion border by synthesis but also degradation of hyaluronan. Their results point to a relevant function of SVZ newborn astrocytes in the modulation of the glial scar after brain ischemia. This work's major strength is the fact that it is tackling the function of SVZ newborn astrocytes, whose role is undisclosed so far.
Strengths:
The article is innovative, of good quality, and clearly written, with properly described Materials and Methods, data analysis, and presentation. In general, the methods are designed properly to answer the main question of the authors, being a major strength. Interpretation of the data is also in general well done, with results supporting the main conclusions of this article.
Weaknesses:
However, there are some points of this article that still need clarification to further improve this work.
- As a first general comment, is it possible that the increase in Thbs4-positive astrocytes can also happen locally close to the glia scar, through the proliferation of local astrocytes or even from local astrocytes at the SVZ? As it was shown in published articles most of the newborn astrocytes in the adult brain actually derive from proliferating astrocytes, and a smaller percentage is derived from NSCs. How can the authors rule out a contribution of local astrocytes to the increase of Thbs4-positive astrocytes? The authors also observed that only about one-third of the astrocytes in the glial scar derived from the SVZ.
- It is known that the local, GFAP-reactive astrocytes at the scar can form the required ECM. The authors propose a role of Thbs4-positive astrocytes in the modulation, and perhaps maintenance, of the ECM at the scar, thus participating in scar formation likewise. So, this means that the function of newborn astrocytes is only to help the local astrocytes in the scar formation and thus contribute to tissue regeneration. Why do we need specifically the Thbs4-positive astrocytes migrating from the SVZ to help the local astrocytes? Can you discuss this further?
- The authors observed that the number of BrdU- and DCX-positive cells decreased 15 dpi in all OB layers (Fig. S5). They further suggest that ischemia-induced a change in the neuroblasts ectopic migratory pathway, depriving the OB layers of the SVZ newborn neurons. Are the authors suggesting that these BrdU/DCX-positive cells now migrate also to the ischemic scar, or do they die? In fact, they see an increase in caspase-3 positive cells in the SVZ after ischemia, but they do not analyse which type of cells are dying. Alternatively, is there a change in the fate of the cells, and astrogliogenesis is increased at the expense of neurogenesis? The authors should understand which cells are Cleaved-caspase-3 positive at the SVZ and clarify if there is a change in cell fate. Also please clarify what happens to the BrdU/DCX-positive cells that are born at the SVZ but do not migrate properly to the OB layers.
- The authors showed decreased Nestin protein levels at 15 dpi by western blot and immunostaining shows a decrease already at 7div (Figure 2). These results mean that there is at least a transient depletion of NSCs due to the promotion of astrogliogenesis. However, the authors show that at 30dpi there is an increase of slow proliferating NSCs (Figure 3). Does this mean, that there is a reestablishment of the SVZ cytogenic process? How does it happen, more specifically, how NSCs number is promoted at 30dpi? Please explain how are the NSCs modulated throughout time after ischemia induction and its impact on the cytogenic process.
- The authors performed a classification of Thbs4-positive cells in the SVZ according to their morphology. This should be confirmed with markers expressed by each of the cell subtypes.
- In Figure S6, the authors quantified HABP spots inside Thbs4-positive astrocytes. Please show a higher magnification picture to show how this quantification was done.
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Reviewer #3 (Public Review):
In this manuscript, the authors investigated the effects of deletion of the ER-plasma membrane/Golgi tethering proteins tricalbins (Tcb1-3) on vacuolar morphology to demonstrate the role of membrane contact sites (MCSs) in regulating vacuolar morphology in Saccharomyces cerevisiae. Their data show that tricalbin deletion causes vacuolar fragmentation possibly in parallel with TORC1 pathway. In addition, their data reveal that levels of various lipids including ceramides, long-chain base (LCB)-1P, and phytosphingosine (PHS) are increased in tricalbin-deleted cells. The authors find that exogenously added PHS can induce vacuole fragmentation and by performing analyses of genes involved in sphingolipid metabolism, they conclude that vacuolar fragmentation in tricalbin-deleted cells is due to the accumulated PHS in these cells. Importantly, exogenous PHS- or tricalbin deletion-induced vacuole fragmentation was suppressed by loss of the nucleus vacuole junction (NVJ), suggesting the possibility that PHS transported from the ER to vacuoles via the NVJ triggers vacuole fission. Of note, the authors find that hyperosmotic shock increases intracellular PHS levels, suggesting a general role of PHS in vacuole fission in response to physiological vacuolar division-inducing stimuli.
This work provides valuable insights into the relationship between MCS-mediated sphingolipid metabolism and vacuole morphology. The conclusions of this paper are mostly supported by their results, but inclusion of direct evidence indicating increased transport of PHS from the ER to vacuoles via NVJ in response to vacuolar division-inducing stimuli would have strengthened this study.
There is another weakness in their claim that the transmembrane domain of Tcb3 contributes to the formation of the tricalbin complex which is sufficient for tethering ER to the plasma membrane and the Golgi complex. Their claim is based only on the structural simulation, but not on by biochemical experiments such as co-immunoprecipitation and pull-down.
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Reviewer #3 (Public Review):
Summary: Irisin has previously been demonstrated to be a muscle-secreted factor that affects skeletal homeostasis. Through the use of different experimental approaches, such as genetic knockout models, recombinant Irisin treatment, or different cell lines, the role of Irisin on skeletal homeostasis has been revealed to be more complex than previously thought and this warrants further examination of its role. Therefore, the current study sought to rigorously examine the effects of global Irisin knockout (KO) in male and female mouse bone. Authors demonstrated that in calcium-demanding settings, such as lactation or low-calcium diet, female Irisin KO mice lose less bone compared to wildtype (WT) female mice. Interestingly male Irisin KO mice exhibited worse skeletal deterioration compared to WT male mice when fed low-calcium diet. When examined for transcriptomic profiles of osteocyte-enriched cortical bone, authors found that Irisin KO altered the expression of osteocytic osteolysis genes as well as steroid and fatty acid metabolism genes in males but not in females. These data support authors' conclusion that Irisin regulates skeletal homeostasis in a sex-dependent manner.
Strengths:
The major strength of the study is rigorous examination of the effects of Irisin deletion in the settings of skeletal maturity and increased calcium demands in female and male mice. Since many of the common musculoskeletal disorders are dependent on sex, examining both sexes in the preclinical setting is crucial. Had the investigators only examined females or males in this study, the conclusion from each sex would have contradicted each other regarding the role of Irisin on bone. Also, the approaches are thorough and comprehensive that assess the functional (mechanical testing), morphological (microCT, BSEM, and histology), and cellular (RNA-seq) properties of bone. Transcriptomic data deposited to NCBI GEO data repository will be a valuable resource to musculoskeletal researchers who aim to further assess the affects of Irisin on skeleton.
Weaknesses:
One of the weaknesses of this study is a lack of detailed mechanistic analysis of why Irisin has sex-dependent role on skeletal homeostasis. However, the osteocyte transcriptome comparisons between LC females vs. LC males lay a foundation for such future mechanistic studies.
Another weakness is authors did not present data that convincingly demonstrate that Irisin secretion is altered in the skeletal muscle between female vs. male WT mice in response to calcium restriction. The supplement skeletal muscle data only present functional and electrophysiological outcomes. Since Itgav or Itgb5 were not different in any of the experimental groups, it is assumed that the changes in the level of Irisin is responsible for the phenotypes observed in WT mice. Assessing Irisin expression will further strengthen the conclusion based on observing skeletal changes that occur in Irisin KO male and female mice.
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Reviewer #3 (Public Review):
Summary:
The authors show that a GAN can learn to reproduce the distribution of outputs of a neuron endowed with Oja's plasticity rule throughout its learning process by learning a plasticity rule. The GAN does not, however, learn Oja's rule. Indeed, the plasticity dynamics it infers can differ dramatically from the true dynamics. The authors propose this approach as a way to uncover families of putative plasticity rules consistent with observed activity patterns in biological systems.
Oja's rule was a great choice for the comparison because it makes explicit, I think, the limitations of this approach. As is well known, Oja's rule allows a (linear) neuron to learn the first principal component of its inputs; the synaptic weights converge to the first eigenvector of the input covariance. After this learning process, the response of a neuron to a particular input sample measures the weighted angle between that input and that principal component.
The other, meta-learned plasticity rules that the authors' GAN uncovers notably do not learn the same computation as Oja's rule (Figure 2). This is, to me, the central finding of the paper and fleshed out nicely. It seems to me that this may be because the objective of the GAN is only to reproduce the marginal output statistics of the neuron. It is, if I understand correctly, blind to the input samples, the inputs' marginal statistics, and to correlations between the input and output. I wonder if a GAN that also had some knowledge of the correlation between input and outputs might be more successful at learning the underlying true dynamics.
The focus on reproducing output statistics has some similarity to some types of experiments (e.g., in vivo recordings) but also seems willfully blind to other aspects of these experiments. In my experience, experimentalists are well aware that the circuits they record receive external inputs. Those inputs are often recorded (perhaps in separate experiments or studies). The point being that I'm not sure that this is an entirely fair comparison to the field.
Finally, the plasticity models studied by theoreticians are not only constructed by intuition and hand-tuning. They also draw, often heavily, on biological data and principles. Oja's rule, for example, is simply the combination of Hebbian learning with a homeostatic constraint on the total synaptic weight amplitude (under the choice of a Euclidean norm).
To me, this study very nicely exposes the caveats and risks associated with a blind machine-learning approach to model specification in biology and highlights the need for understanding underlying biological mechanisms and principles. I agree with the authors that heterogeneity and degeneracy in plasticity rules deserve much more attention in the field.
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Reviewer #3 (Public Review):
Summary:
This work provides insights into predictive coding models of visual cortex processing. These models predict that visual cortex neurons will show elevated responses when there are unexpected changes to learned sequential stimulus patterns. This model is currently controversial, with recent publications providing conflicting evidence. In this work, the authors test two types of unexpected pattern variations in layer 2/3 of the mouse visual cortex. They show that pattern omission evokes elevated responses, in favor of a predictive coding model, but find no evidence for prediction errors with substituted patterns, which conflicts with both prior results in L4, and with the expectations of a predictive coding model. They also report that with sequence training, responses sparsify and decorrelate, but surprisingly find no changes in the ability of an ideal observer to decode stimulus identity or timing.
These results are an important contribution to the understanding of how temporal sequences and expectations are encoded in the primary visual cortex. However, there are several methodological concerns with the study, and some of the authors' interpretations and conclusions are unsupported by data.
Major concerns:
(1) Experimental design using a block structure. The use of a block structure on test days (0 and 5) in which sequences were presented in 100 repetition blocks leads to several potential confounds. First, there is the potential for plasticity within blocks, which could alter the responses and induce learned expectations. The ability of the authors to clearly distinguish blocks 1 and 2 on Day 0 with a decoder suggests this change over time may be meaningful.
Repeating the experiments with fully interleaved sequences on test days would alleviate this concern. With the existing data, the authors should compare responses from the first trials in a block to the last trials in a block.
This block design likely also accounts for the ability of a decoder to readily distinguish stimulus A in ABCD from A in ABBD. As all ABCD sequences were run in a contiguous block separate from ABBD, the recent history of experience is different for A stimuli in ABCD versus ABBD. Running fully interleaved sequences would also address this point, and would also potentially mitigate the impact of drift over blocks (discussed below).
(2) The computation of prediction error differs significantly for omission as opposed to substitutions, in meaningful ways the authors do not address. For omission errors, PE compares the responses of B1 and B2 within ABBD blocks. These responses are measured from the same trial, within tens of milliseconds of each other. In contrast, substitution PE is computed by comparing C in ABCD to C in ACBD. As noted above, the block structure means that these C responses were recorded in different blocks, when the state of the brain could be different. This may account for the authors' detection of prediction error for omission but not substitution. To address this, the authors should calculate PE for omission using B responses from ABCD.
(3) The behavior of responses to B and C within the trained sequence ABCD differs considerably, yet is not addressed. Responses to B in ABCD potentiate from d0-> d5, yet responses to C in the same sequence go down. This suggests there may be some difference in either the representation of B vs C or position 2 vs 3 in the sequence that may also be contributing to the appearance of prediction errors in ABBD but not ACBD. The authors do not appear to consider this point, which could potentially impact their results. Presenting different stimuli for A,B,C,D across mice would help (in the current paper B is 75 deg and C is 165 deg in all cases). Additionally, other omissions or substitutions at different sequence positions should be tested (eg ABCC or ABDC).
(4) The authors' interpretation of their PCA results is flawed. The authors write "Experience simplifies activity in principal component space". This is untrue based on their data. The variance explained by the first set of PCs does not change with training, indicating that the data is not residing in a lower dimensional ("simpler") space. Instead, the authors show that the first 5 PCs better align with their a priori expectations of the stimulus structure, but that does not mean these PCs necessarily represent more information about the stimulus (and the fact that the authors fail to see an improvement in decoding performance argues against this case). Addressing such a question would be highly interesting, but is lacking in the current manuscript. Without such analysis, referring to the PCs after training as "highly discretized" and "untangled" are largely meaningless descriptions that lack analytical support.
(5) The authors report that activity sparsifies, yet provide only the fraction of stimulus-selective cells. Given that cell detection was automated in a manner that takes into account neural activity (using Suite2p), it is difficult to interpret these results as presented. If the authors wish to claim sparsification, they need to provide evidence that the total number of ROIs drawn on each day (the denominator for sparseness in their calculation) is unbiased. Including more (or less) ROIs can dramatically change the calculated sparseness.
The authors mention sparsification as contributing to coding efficiency but do not test this. Training a decoder on variously sized subsets of their data on days 0 and 5 would test whether redundant information is being eliminated in the network over training.
(6) The authors claim their results show representational drift, but this isn't supported in the data. Rather they show that there is some information in the structure of activity that allows a decoder to learn block ID. But this does not show whether the actual stimulus representations change, and could instead reflect an unrelated artifact that changes over time (responsivity, alertness, bleaching, etc). To actually assess representational drift, the authors should directly compare representations across blocks (one could train a decoder on block 1 and test on blocks 2-5). In the absence of this or other tests of representational drift over blocks, the authors should remove the statement that "These findings suggest that there is a measurable amount of representational drift".
(7) The authors allude to "temporal echoes" in a subheading. This term is never defined, or substantiated with analysis, and should be removed.
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Reviewer #3 (Public Review):
Summary:
The study by Yao, Dai and colleagues successfully describes the design of a viral gene drive against herpes simplex virus 1. Gene drives are genetic modifications designed to spread efficiently in a population. Most applications have been developed in insects to eradicate diseases such as malaria, and the design of gene drives in viruses is an exciting recent development. A viral gene drive system was first described with human cytomegalovirus, another virus of the herpesvirus family (PMID: 32985507), and the authors followed similar methods to design a gene drive against HSV-1. While some key experiments lack rigorous controls, overall the authors convincingly showed that an HSV-1 gene drive could spread efficiently in the target population in cell culture experiments. Cytomegalovirus and HSV-1 have very different infection dynamics, and these new findings suggest that viral gene drives could be developed in a wide variety of herpesviruses. This significantly expands the potential of the technology and will be of interest to readers interested in gene drives, viral engineering, or biotechnology in general.
The most novel and interesting part of the study is the comparison of gene drives relying on spCas9 and Un1Cas12f1 nuclease. Most gene drives developed to date have relied on Cas9 or similar nucleases. Cleavage and repair of the target site by non-homologous end-joining (NHEJ) can lead to the formation of drive-resistant sequences, and, depending on the selective pressure on the wild-type, gene drive and drive-resistant alleles, prevent successful gene drive propagation. By contrast to most RNA-guided nucleases, Un1Cas12f1 cleaves outside of the RNA-recognition site. The authors hypothesized that it could prevent the appearance of drive-resistant sequences, since the target sequence would be preserved after NHEJ repair. Indeed, the study convincingly showed that Un1Cas12f1 induced fewer drive-resistant mutations, which led to almost complete penetrance of the drive. However, the claim in the abstract that an "Un1Cas12f1 gene drive yielded a greater conversion" rate than Cas9 appears unsupported. Together with its smaller size, this positions Un1Cas12f1 as an interesting alternative to Cas9 for gene drives in any organism. This development will be of great interest to researchers interested in gene drives.
Strengths:
Overall, this study is well done and the main conclusions are supported by the data. The authors used flow cytometry to follow gene drive propagation, detecting either fluorescent or cell surface proteins expressed by the different viral populations. This represents an indirect but adequate way of measuring the proportion of the different viral populations, assuming that each of the target BHK cells is infected with only one virus.<br /> In particular, the results in Fig 3 showing that Un1Cas12f1 induces fewer drive-resistant mutations than Cas9 are convincing.
Weaknesses:
The manuscript presents several conceptual and methodological weaknesses that could be discussed or addressed experimentally, which would improve the overall rigor of the study.
(1) In the abstract and the text, the author claims that "HSV1 emerges as a dependable and swift platform for gene drive assessment". It is unclear if the author believes that the main interest of their work with HSV-1 is to provide a platform for testing gene drive for other organisms, or whether a gene drive for HSV-1 could be useful by itself. While their findings with Un1Cas12f1 certainly warrant investigation in other systems, the dynamics of DNA cleavage, recombination, and selection of drive-resistant alleles will be very different between a viral infection where hundreds or thousands of genome copies co-exist in a cell nucleus, and during sexual reproduction where only one gene drive and wild-type allele are present in a fertilized egg. As such, it is unsure whether gene drive dynamics in HSV-1 will be informative for other organisms besides other herpesviruses. On the other hand, the authors provide little perspectives on the potential usage of an HSV-1 gene drive, beyond concluding that "Our study opens new possibilities for using the HSV1 gene drive for the prevention and treatment of diseases". The authors designed a drive against the important viral protein gE in an attempt to limit infectivity, but it is unclear from the data presented whether this was successful. An extended discussion on the potential use case of an HSV-1 gene drive would be informative.
(2) Unfortunately, the experiments presented lack rigorous controls to unambiguously show that gene drive propagation is mediated by CRISPR-directed recombination into the target genome. Gene drive-mediated recombination converts wild-type viruses into new recombinant viruses and the population of recombinants is expected to increase in frequency, as observed with the yellow population in Fig 2G and 3G. However, a rigorous experimental design would show that this population of recombinant viruses does not appear with a non-functional CRISPR system (for example if Cas9 is deleted in the gene drive virus) or if the target site is absent in the recipient virus. The comparison of Fig 2B and 2D does show that gene drive viruses do not increase in frequency when the target site is absent in the V19 virus, but these experiments could not distinguish between original and recombinant gene drive viruses. Thus, it is unknown if the increase in gene drive frequency in Fig 2B is because wild-type viruses have been converted to gene drive viruses, or because the WT and v23 viruses replicate with different dynamics (one could imagine for example that CRISPR cleavage of the WT genomes impaired the replication of the WT virus without inducing recombination, thus giving an advantage to v23). In Fig 2G and 3B, the authors do follow the population of recombinant viruses, in yellow, which increase in frequency as expected. However, in these experiments, either the donor or recipient viruses are mutated for gE, and the different viral populations might replicate with different dynamics, which confounds the interpretation of the results (see point 4. below). Overall, while the data presented suggests that CRISPR-mediated gene drive propagation is happening, it does not conclusively rule out other explanations, especially if viruses have different fitness.
(3) In Fig 2F-G-H, the authors designed a gene drive knocking out an important viral gene, gE, in an attempt to build a drive that reduces infectivity. gE knockout viruses V10 and V15 had smaller plaques but replicated with similar titers (Fig 1B, 1C). The gene drive against gE spread efficiently in Fig 2G. However, gE-KO viruses did not appear to have a meaningful disadvantage in the experimental system used, since the high MOI used in the co-infection experiments allowed to bypass the cell-to-cell defect of gE mutants. It would have been interesting to characterize the final population composed primarily of original and recombinant viruses (at P3 in Fig 2G), and in particular measure the plaque size of these viruses. Recombinant viruses should have smaller plaque sizes, and showing that the gene drive was able to propagate an attenuating phenotype would be a meaningful result that hints at potential therapeutic applications.
(4) Experiments presented in Fig 3 compared the dynamics of Cas9 and Un1Cas12f1 gene drives, but the experimental system used is a bit puzzling and makes the interpretation of the results challenging. In particular, the authors chose to use gE-knockout virus v10 as the recipient for the gene drive, which allowed them to use gE in their flow cytometry assay. Unfortunately, this added a confounding factor to the experiments, since gE- viruses might replicate with different dynamics than gE+ viruses (for example v10 titers are one log higher than WT at 12h in Fig 1C). In Fig 3B, gD+ gE- viruses (in blue) disappear and are replaced by gD+ GFP+ gE- recombinants (in yellow), which is suggestive of efficient gene drive recombination, as pointed out by the authors. However, the population of gD+ GFP+ virus (in green) representing the original gene drive virus also disappeared over time. At the end of the experiments in Fig 3B, the population of gE+ viruses is gone. This is unexpected and suggests that the gD+ GFP+ gE- (yellow) has a replicative advantage over gD+ GFP+ (green), and that the gE- mutation is actually positively selected in these viral competition assays. So in these experiments, both gene drive-mediated recombination and competition between viral genotypes appear to be happening at the same time, which makes interpretation of the results challenging. However, despite these limitations, the results presented convincingly suggested that Un1Cas12f1 gene drives achieved higher penetrance than Cas9's, which is one of the most important findings of the study.
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Reviewer #3 (Public Review):
Summary:<br /> In this manuscript, the authors have used biochemical approaches to provide compelling evidence for the cleavage of TRMT1 by SARS-CoV-2 Nsp5 protease.<br /> This work is of wide interest to biochemists, cell biologists, and structural biologists in the coronavirus (CoV) field. Furthermore, it substantially advances the understanding of how CoV's interact with host factors during infection and modify cellular metabolism.
Strengths:<br /> The authors provide multiple lines of biochemical evidence to report a TRMT1-Nsp5 interaction during SARS-CoV-2 infection. They show that the host enzyme TRMT1 is cleaved at a specific site, and that it generates fragments that are incapable of functioning properly. This is an important result because TRMT1 is a critical player in host protein synthesis. This also advances our understanding of virus-host interactions during SARS-CoV-2 infections. Furthermore, this revised submission attempts to address the mechanistic role of TRMT1-Nsp5 interaction.
Weaknesses:<br /> The discussion on the enhanced viral infectivity upon expression of the non-cleavable TRMT1 is unclear. As presented, this is a bit contradictory to the suggested function of the TRMT1-Nsp5 interaction in diverting the host tRNA pools towards viral propagation. If the authors' model were correct, then one would expect a non-cleavable TRMT1 to inhibit viral infectivity because the virus would be unable to divert the host tRNA pools towards its propagation. I think this section needs to be written more clearly. But other than this, I have no further questions/suggestions for the authors.
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Reviewer #3 (Public Review):
Human complex traits including common diseases are highly polygenic (influenced by thousands of loci). This observation is in need of an explanation. The authors of this manuscript propose a model that a competition for a single global resource (such as RNA polymerase II) may lead to a highly polygenic architecture of traits. Following an analytical examination the authors reject their hypothesis. This work is of clear interest to the field. It remains to be seen if the model covers the variety of possible competition models.
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Reviewer #3 (Public Review):
The message conveyed by figure 1b is now clearer, but could still be improved. The authors explained the meaning of this figure well in their response to the reviewers: "For example, the results for CRISPR were obtained from 15 focus studies (original research) and 18 subsequent studies (papers citing focus articles). Those 15 studies identified 9,268 genes where loss-of-function changed phenotypes but, in their titles and abstracts, mentioned only 18 of those 9,268 genes. While the 9,268 hit genes have received similar research attention to the entirety of protein-coding genes, the 18 hit genes mentioned in the title or abstract are significantly more well studied. The articles citing the focus articles also only mentioned in their titles and abstracts 19 highly studied hit genes".<br /> The new Figure S8 is good.
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Reviewer #3 (Public Review):
Summary:
Li et al investigated the initial target of the herbicidal caprilic acid (CAP). Using a combination of proteomic and metabolomic approaches, they generated a list of candidate targets for CAP and identified a Serine hydroxymethyl transferase (SHMT) as the best candidate.
CAP application to Conyza canadensis induces an early and brief increase in SHMT1 protein and transcript. Studies with purified recombinant CcSHMT1 indicate that enzymatic activity is inhibited by CAP. The authors suggest a kinetic mechanism of CAP inhibition but more data should be collected to reach a firm conclusion on this point.
Transgenic Arabidopsis and rice plants expressing CcSHMT1 show increased tolerance to CAP, as measured by biomass reduction 7 days after treatment with CAP. Similar results were obtained with Arabidopsis and rice plants overexpressing AtSHMT2 and OsSHMT1, respectively. OsSHMT1 single and double mutant rice plants showed increased tolerance to CAP. These results strongly link CAP tolerance to the level of SHMT, which can be manipulated by transgenesis, and suggest that engineered SHMT can also lead to higher CAP tolerance.
Finally, structural analysis allowed the identification of three residues close to the active site involved in the binding of CAP. Arabidopsis plants containing AtSHMT2 modified in these three residues are more sensitive to CAP.
Strengths:
The work of Li et al. includes a large number of assays using different methodologies. The evidence suggests that SHMT inhibition by CAP is effective in inhibiting plant growth. In addition, new technologies that manipulate SHMT levels or activity may improve crop yield by controlling weeds. Structural analysis can be the starting point for the design of more complex molecules that exceed the herbicidal activity of CAP.
Weaknesses:
The methods are rather incomplete, lacking many details necessary to fully understand the author's reasoning. It is not possible to reproduce the experiments on the basis of the information provided.
Although the conclusions are generally well supported, the results are presented in an incorrect or confusing manner. In the comparison of wild-type and transgenic plants, the control condition is missing in some experiments (Figures 4A and 5A). In some plots, the scales are not logical, making them difficult to interpret and fit into an equation (Figures 4B, 4C, 4E, 5E, 6E, 6F).
A final concern is the finding that some point mutations in the SHMT1 gene lead to more tolerant plants (Figures 6D, 6E, 6F). The authors could then explain whether this means that resistance to CAP could be easily acquired by weeds.
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Reviewer #3 (Public Review):
Summary:<br /> The manuscript by Wang et al. investigates the effects of B. velezensis HBXN2020 in alleviating S. Typhimurium-induced mouse colitis. The results showed that B. velezensis HBXN2020 could alleviate bacterial colitis by enhancing intestinal homeostasis (decreasing harmful bacteria and enhancing the abundance of Lactobacillus and Akkermansia) and gut barrier integrity and reducing inflammation. Overall, the manuscript is of potential interest to readers.
Strengths:<br /> B. velezensis HBXN2020 is a novel species of Bacillus that can produce a great variety of secondary metabolites and exhibit high antibacterial activity against several pathogens. B. velezensis HBXN2020 is able to form endospores and has strong anti-stress capabilities. B. velezensis HBXN2020 has a synergistic effect with other beneficial microorganisms, which can improve intestinal homeostasis.
Weaknesses:<br /> There are few studies about the clinical application of Bacillus velezensis. Thus, more studies are still needed to explore the effectiveness of Bacillus velezensis before clinical application.
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Reviewer #3 (Public Review):
Summary:
Grattan and colleagues were trying to establish the neural mechanism underlying lactational infertility, in particular trying to establish the relative importance of the neurogenic effects of the suckling stimulus versus prolactin per se. They have shown that in the mouse it is rather prolactin and more specifically its action on the hypothalamic arcuate kisspeptin neuronal system, which is the key neural construct underlying gonadotrophin-releasing hormone (GnRH) pulse generation and central to the neuroendocrine control of reproduction, that mediates lactational infertility. The authors have taken a measured tone to emphasise the data pertaining to the mouse without extravagant extrapolation to humans. Nevertheless, the key findings provide a substantial foundation to facilitate interpretation of studies in other species.
Strengths:
The major strength of this study is the use of a combination of cutting-edge technologies, which of course underlie the majority of scientific advances rather than intellectual prowess favoured by the majority of scientists. Their approach avoided the major confounding effects of using pharmacological strategies to suppress prolactin action that has complicated the vast majority of previous studies. The study also provides an elegant and comprehensive contiguous description of GnRH pulse generator frequency across the ovarian cycle, through pregnancy and lactation, and into weaning in individual animals.
Weaknesses:<br /> There are no significant weaknesses.
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Reviewer #3 (Public Review):
In this manuscript, Nishi et al. propose a new model to explain the previously reported myeloid-biased hematopoiesis associated with aging. Traditionally, this phenotype has been explained by the expansion of myeloid-biased hematopoietic stem cell (HSC) clones during aging. Here, the authors question this idea and show how their Hoxb5 reporter model can discriminate long-term (LT) and short-term (ST) HSC and characterized their lineage output after transplant. From these analyses, the authors conclude that changes during aging in the LT/ST HSC proportion explain the myeloid bias observed.
Although the topic is appropriate and the new model provides a new way to think about lineage-biased output observed in multiple hematopoietic contexts, some of the experimental design choices, as well as some of the conclusions drawn from the results could be substantially improved. Also, they do not propose any potential mechanism to explain this process, which reduces the potential impact and novelty of the study. Specific concerns are outlined below.
Major
(1) As a general comment, there are experimental details that are either missing or not clear. The main one is related to transplantation assays. What is the irradiation dose? The Methods sections indicates "recipient mice were lethally irradiated with single doses of 8.7 or 9.1 Gy". The only experimental schematic indicating the irradiation dose is Figure 7A, which uses 8.7 Gy. Also, although there is not a "standard", 11 Gy split in two doses is typically considered lethal irradiation, while 9.5 Gy is considered sublethal. Is there any reason for these lower doses? Same question for giving a single dose and for performing irradiation a day before transplant.
(2) The manuscript would benefit from the inclusion of references to recent studies discussing hematopoietic biases and differentiation dynamics at a single-cell level (e.g., Yamamoto et. al 2018; Rodriguez-Fraticelli et al., 2020). Also, when discussing the discrepancy between studies claiming different biases within the HSC pool, the authors mentioned that Montecino-Rodriguez et al. 2019 showed preserved lymphoid potential with age. It would be good to acknowledge that this study used busulfan as the conditioning method instead of irradiation.
(3) When representing the contribution to PB from transplanted cells, the authors show the % of each lineage within the donor-derived cells (Figures 3B-C, 5B, 6B-D, 7C-E, and S3 B-C). To have a better picture of total donor contribution, total PB and BM chimerism should be included for each transplantation assay. Also, for Figures 2C-D and Figures S2A-B, do the graphs represent 100% of the PB cells? Are there any radioresistant cells?
(4) For BM progenitor frequencies, the authors present the data as the frequency of cKit+ cells. This normalization might be misleading as changes in the proportion of cKit+ between the different experimental conditions could mask differences in these BM subpopulations. Representing this data as the frequency of BM single cells or as absolute numbers (e.g., per femur) would be valuable.
(5) Regarding Figure 1B, the authors argue that if myeloid-biased HSC clones increase with age, they should see increased frequency of all components of the myeloid differentiation pathway (CMP, GMP, MEP). This would imply that their results (no changes or reduction in these myeloid subpopulations) suggest the absence of myeloid-biased HSC clones expansion with age. This reviewer believes that differentiation dynamics within the hematopoietic hierarchy can be more complex than a cascade of sequential and compartmentalized events (e.g., accelerated differentiation at the CMP level could cause exhaustion of this compartment and explain its reduction with age and why GMP and MEP are unchanged) and these conclusions should be considered more carefully.
(6) Within the few recipients showing good donor engraftment in Figure 2C, there is a big proportion of T cells that are "amplified" upon secondary transplantation (Figure 2D). Is this expected?
(7) Do the authors have any explanation for the high level of variability within the recipients of Hoxb5+ cells in Figure 2C?
(8) Can the results from Figure 2E be interpreted as Hoxb5+ cells having a myeloid bias? (differences are more obvious/significant in neutrophils and monocytes).
(9) Is Figure 2G considering all primary recipients or only the ones that were used for secondary transplants? The second option would be a fairer comparison.
(10) When discussing the transcriptional profile of young and aged HSCs, the authors claim that genes linked to myeloid differentiation remain unchanged in the LT-HSC fraction while there are significant changes in the ST-HSCs. However, 2 out of the 4 genes shown in Figure S4B show ratios higher than 1 in LT-HSCs.
(11) When determining the lymphoid bias in ST-HSCs, the authors focus on the T-cell subtype, not considering any other any other lymphoid population. Could the authors explain this?
(12) Based on the reduced frequency of donor cells in the spleen and thymus, the authors conclude "the process of lymphoid lineage differentiation was impaired in the spleens and thymi of aged mice compared to young mice". An alternative explanation could be that differentiated cells do not successfully migrate from the bone marrow to these secondary lymphoid organs. Please consider this possibility when discussing the data.
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Reviewer #3 (Public Review):
Fister and colleagues use regeneration of the larval zebrafish caudal fin to compare the effects of two modes of tissue damage-transection and burn-on cutaneous sensory axon regeneration. The authors found that restoration of sensory axon density and function is delayed following burn injury compared to transection.
The authors hypothesized that thermal injury triggers signals within the wound microenvironment that impair sensory neuron regeneration. The authors identify differences in the responses of epithelial keratinocytes to the two modes of injury: keratinocytes migrate in response to burn but not transection. Inhibiting keratinocyte migration with the small-molecule inhibitor of Arp2/3 (CK666) resulted in decreased production of reactive oxygen species (ROS) at early, but not late, time points. Preventing keratinocyte migration by wounding in isotonic media resulted in increased sensory function 24 hours after burn.
Strengths of the study include the beautiful imaging and rigorous statistical approaches used by the authors. The ability to assess both axon density and axon function during regeneration is quite powerful. The touch assay adds a unique component to the paper and strengthens the argument that burns are more damaging to sensory structures and that different treatments help to ameliorate this.
A weakness of the study is the lack of genetic and cell-autonomous manipulations. Additional comparisons between transection and burns, in particular with manipulations that specifically modulate ROS generation or cell migration without potentially confounding effects on other cell types or processes would help to strengthen the manuscript. In terms of framing their results, the authors refer to "sensory neurons" and "sensory axons" throughout the text - it should be made clear what type of neuron(s)/axon(s) are being visualized/assayed. Along these lines, a broader discussion of how burn injuries affect sensory function in other systems - and how the authors' results might inform our understanding of these injury responses - would be beneficial to the reader.
In summary, the authors have established a tractable vertebrate system to investigate different sensory axon wound healing outcomes in vivo that may ultimately allow for the identification of improved treatment strategies for human burn patients. Although the study implicates differences in keratinocyte migration and associated ROS production in sensory axon wound healing outcomes, the links between these processes could be more rigorously established.
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Reviewer #3 (Public Review):
Induced pluripotent stem cells, or iPSCs, are cells that scientists can push to become new, more mature cell types like neurons. iPSCs have a high potential to transform how scientists study disease by combining precision medicine gene editing with processes known as high-content imaging and drug screening. However, there are many challenges that must be overcome to realize this overall goal. The authors of this paper solve one of these challenges: predicting cell types that might result from potentially inefficient and unpredictable differentiation protocols. These predictions can then help optimize protocols.
The authors train advanced computational algorithms to predict single-cell types directly from microscopy images. The authors also test their approach in a variety of scenarios that one may encounter in the lab, including when cells divide quickly and crowd each other in a plate. Importantly, the authors suggest that providing their algorithms with just the right amount of information beyond the cells' nuclei is the best approach to overcome issues with cell crowding.
The work provides many well-controlled experiments to support the authors' conclusions. However, there are two primary concerns: (1) The model may be relying too heavily on the background and thus technical artifacts (instead of the cells) for making CNN-based predictions, and (2) the conclusion that their nucleocentric approach (including a small area beyond the nucleus) is not well supported, and may just be better by random chance. If the authors were to address these two concerns (through additional experimentation), then the work may influence how the field performs cell profiling in the future.
Additionally, the impact of this work will be limited, given the authors do not provide a specific link to the public source code that they used to process and analyze their data.
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Reviewer #3 (Public Review):
Summary:
The mechanical properties of DNA wrapped in nucleosomes affect the stability of nucleosomes and may play a role in the regulation of DNA accessibility in eukaryotes. In this manuscript, Ngo and coworkers study how the stability of a nucleosome is affected by the introduction of a CC mismatched base pair, which has been reported to increase the flexibility of DNA. Previously, the group has used a sophisticated combination of single-molecule FRET and force spectroscopy with an optical trap to show that the more flexible half of a 601 DNA segment provides for more stable wrapping as compared to the other half. Here, it is confirmed with a single-molecule cyclization essay that the introduction of a CC mismatch increases the flexibility of a DNA fragment. Consistent with the previous interpretation, it also increased the unwrapping force for the half of the 601 segment in which the CC mismatch was introduced, as measured with single-molecule FRET and force spectroscopy. Enhanced stability was found up to 56 bp into the nucleosome. The intricate role of mechanical stability of nucleosomes was further investigated by comparing force-induced unwrapping profiles of yeast and Xenopus histones. Intriguingly, asymmetric unwrapping was more pronounced for yeast histones.
Strengths:
(1) High-quality single-molecule data.
(2) Novel mechanism, potentially explaining the increased prominence of mutations near the dyads of nucleosomes.
(3) A clear mechanistic explanation of how mismatches affect nucleosome stability.
Weaknesses:
(1) Disconnect between mismatches in nucleosomes and measurements comparing Xenopus and yeast nucleosome stability.
(2) Convoluted data in cyclization experiments concerning the phasing of mismatches and biotin site.
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Reviewer #3 (Public Review):
Summary:
In this study, Wang et al. have demonstrated that TMC7, a testis-enriched multipass transmembrane protein, is essential for male reproduction in mice. Tmc7 KO male mice are sterile due to reduced sperm count and abnormal sperm morphology. TMC7 co-localizes with GM130, a cis-Golgi marker, in round spermatids. The absence of TMC7 results in reduced levels of Golgi proteins, elevated abundance of ER stress markers, as well as changes of Ca2+ and pH levels in the KO testis. However, further confirmation is required because the analyses were performed with whole testis samples in spite of the differences in the germ cell composition in WT and KO testis. In addition, the causal relationships between the reported anomalies await thorough interrogation.
Strengths:<br /> The microscopic images are of great quality, all figures are properly arranged, and the entire manuscript is very easy to follow.
Weaknesses:<br /> Tmc7 KO male mice show multiple anomalies in sperm production and morphogenesis, such as reduced sperm count, abnormal sperm head, and deformed midpiece. Thus, it is confusing that the authors focused solely on impaired acrosome biogenesis. Further investigations are warranted to determine whether the abnormalities reported in this manuscript (e.g., changes in protein, Ca2+, and pH levels) are directly associated with the molecular function of TMC7 or are the byproducts of partially arrested spermiogenesis. Please find additional comments in "Recommendations for the authors".
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Reviewer #3 (Public Review):
Summary:
A known feature of cilia in vertebrates and many, if not all, invertebrates is the striking heterogeneity of their lengths among different cell types. The underlying mechanisms, however, remain largely elusive. In the manuscript, the authors addressed this question from the angle of intraflagellar transport (IFT), a cilia-specific bidirectional transportation machinery essential to biogenesis, homeostasis, and functions of cilia, by using zebrafish as a model organism. They conducted a series of experiments and proposed an interesting mechanism. Furthermore, they achieved in situ live imaging of IFT in zebrafish larvae, which is a technical advance in the field.
Strengths:
The authors initially demonstrated that ectopically expressed Ift88-GFP through a certain heat-shock induction protocol fully sustained the normal development of mutant zebrafish that would otherwise be dead by 7 dpf due to the lack of this critical component of IFT-B complex. Accordingly, cilia formations were also fully restored in the tissues examined. By imaging the IFT using Ift88-GFP in the mutant fish as a marker, they unexpectedly found that both anterograde and retrograde velocities of IFT trains varied among cilia of different cell types and appeared to be positively correlated with the length of the cilia.
For insights into the possible cause(s) of the heterogeneity in IFT velocities, the authors assessed the effects of IFT kinesin Kif3b and Kif17, BBSome, and glycylation or glutamylation of axonemal tubulin on IFT and excluded their contributions. They also used a cilia-localized ATP reporter to exclude the possibility of different ciliary ATP concentrations. When they compared the size of Ift88-GFP puncta in crista cilia, which are long, and spinal cord cilia, which are relatively short, by imaging with a cutting-edge super-resolution microscope, they noticed a positive correlation between the puncta size, which presumably reflected the size of IFT trains, and the length of the cilia.
Finally, they investigated whether it is the size of IFT trains that dictates the ciliary length. They injected a low dose (0.5 ng/embryo) of ift88 MO and showed that, although such a dosage did not induce the body curvature of the zebrafish larvae, crista cilia were shorter and contained less Ift88-GFP puncta. The particle size was also reduced. These data collectively suggested mildly downregulated expression levels of Ift88-GFP. Surprisingly, they observed significant reductions in both retrograde and anterograde IFT velocities. Therefore, they proposed that longer IFT trains would facilitate faster IFT and result in longer cilia.
Weaknesses:
The current manuscript, however, contains serious flaws that markedly limit the credibility of major results and findings. Firstly, important experimental information is frequently missing, including (but not limited to) developmental stages of zebrafish larvae assayed (Figures 1, 3, and 5), how the embryos or larvae were treated to express Ift88-GFP (Figures 3-5), and descriptions on sample sizes and the number of independent experiments or larvae examined in statistical results (Figures 3-5, S3, S6). For instance, although Figure 1B appears to be the standard experimental scheme, the authors provided results from 30-hpf larvae (Figure 3) that, according to Figure 1B, are supposed to neither express Ift88-GFP nor be genotyped because both the first round of heat shock treatment and the genotyping were arranged at 48 hpf. Similarly, the results that ovl larvae containing Tg(hsp70l:ift88 GFP) (again, because the genotype is not disclosed in the manuscript, one can only deduce) display normal body curvature at 2 dpf after the injection of 0.5 ng of ift88 MO (Fig 5D) is quite confusing because the larvae should also have been negative for Ift88-GFP and thus displayed body curvature. Secondly, some inferences are more or less logically flawed. The authors tend to use negative results on specific assays to exclude all possibilities. For instance, the negative results in Figures 4A-B are not sufficient to "suggest that the variability in IFT speeds among different cilia cannot be attributed to the use of different motor proteins" because the authors have not checked dynein-2 and other IFT kinesins. In fact, in their previous publication (Zhao et al., 2012), the authors actually demonstrated that different IFT kinesins have different effects on ciliogenesis and ciliary length in different tissues. Furthermore, instead of also examining cilia affected by Kif3b or Kif17 mutation, they only examined crista cilia, which are not sensitive to the mutations. Similarly, their results in Figures 4C-G only excluded the importance of tubulin glycylation or glutamylation in IFT. Thirdly, the conclusive model is based on certain assumptions, e.g., constant IFT velocities in a given cell type. The authors, however, do not discuss other possibilities.
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Reviewer #3 (Public Review):
Summary:
The authors studied the function of Hsp110 co-chaperones (e.g. yeast Sse1) in Hsp70-dependent protein disaggregation reactions. The study builds on former work by the authors (Wyszkowski et al., 2021, PNAS), analyzing the binding of Hsp70 and J-domain protein (JDP) cochaperones to protein aggregates using bio-layer interferometry (BLI). It was shown before by other groups that Hsp110 enhances Hsp70 disaggregation activity. The mechanism of Hsp110-stimulated disaggregation activity, however, remained poorly defined. Here, the authors show that yeast Hsp110 increases Hsp70 recruitment to the surface of protein aggregates. The effect is largely dependent on J-domain protein (JDP) identity and is particularly pronounced for class B JDPs (e.g. yeast Sis1), which are also more effective in disaggregation reactions. The authors also confirm former results, showing inhibition by increased Hsp110 levels, and provide novel evidence that the inhibitory effect is caused by competition between Hsp110 and JDPs for Hsp70 binding.
Strengths:
The work represents a very thoroughly executed study, which provides novel insights into the mechanism of Hsp70-mediated protein disaggregation. Key findings established for yeast chaperones are also documented for human counterparts. The observation that Hsp110 might displace JDPs from Hsp70 during the disaggregation reaction is very appealing. It will now become important to validate this initial finding and dissect how it propels the disaggregation reaction.
Weaknesses:
How exactly the interplay between JDPs and Hsp110 orchestrates protein disaggregation remains largely speculative and further analysis is required for a deeper mechanistic understanding. Enhanced recruitment of Hsp70 in the presence of Hsp110 was shown for amyloid fibrils before (Beton et al., EMBO J 2022) and should be acknowledged. The assay reporting on the refolding activity of Hsp70 seems problematic due to the high spontaneous refolding of the substrate Luciferase and should be modified.
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Reviewer #3 (Public Review):
Overall:
ExoIII has been described and commercialized as a dsDNA-specific nuclease. Several lines of evidence, albeit incomplete, have indicated this may not be entirely true. Therefore, Wang et al comprehensively characterize the endonuclease and exonuclease enzymatic activities of ExoIII on ssDNA. A strength of the manuscript is the testing of popular kits that utilize ExoIII and coming up with and testing practical solutions (e.g. the addition of SSB proteins ExoIII variants such as K121A and varied assay conditions).
Comments:
(1) The footprint of ExoIII on DNA is expected to be quite a bit larger than 5-nt, see structure in manuscript reference #5. Therefore, the substrate design in Figure 1A seems inappropriate for studying the enzymatic activity and it seems likely that ExoIII would be interacting with the FAM and/or BHQ1 ends as well as the DNA. Could this cause quenching? Would this represent real ssDNA activity? Is this figure/data necessary for the manuscript?
(2) Based on the descriptions in the text, it seems there is activity with some of the other nucleases in 1C, 1F, and 1I other than ExoIII and Cas12a. Can this be plotted on a scale that allows the reader to see them relative to one other?
(3) The sequence alignment in Figure 2N and the corresponding text indicates a region of ExoIII lacking in APE1 that may be responsible for their differences in substrate specificity in regards to ssDNA. Does the mutational analysis support this hypothesis?
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Reviewer #3 (Public Review):
This study aimed to explore the computational mechanisms of view invariance, driven by the observation that in some regions of monkey visual cortex, neurons show comparable responses to (1) a given face and (2) to the same face but horizontally flipped. Here they study this known phenomenon using AlexNet and other shallow neural networks, using an index for mirror symmetric viewpoint tuning based on representational similarity analyses. They find that this tuning is enhanced at fully connected- or global pooling layers (layers which combine spatial information), and that the invariance is prominent for horizontal- but not vertical- or rotational transformations. The study shows that mirror tuning can be learned when a given set of images are flipped horizontally and given the same label, but *not* if they are flipped and given different labels. They also show that networks learn this tuning by focusing on local features, not global configurations.
I found the study to be a mixed read. Some analyses were fascinating: for example, it was satisfying to see the use of well-controlled datasets to increase or decrease the rate of mirror-symmetry tuning. The insertion- and deletion¬ experiments were elegant tests to probe the mechanisms of mirror symmetry, asking if symmetry could arise from (1) global feature configurations (in a holistic sense) vs. (2) local features, with stronger evidence for the latter. These two sets of results were successful and interpretable. They stand in contrast with the first analysis, which relies on observations that do not seem justified. Specifically, Figure 2D shows mirror-symmetry tuning across 11 stages of image processing, from pixels space to fully connected layers. It shows that images from different object categories evoke considerably different tuning index values. The explanation for this result is that some categories, such as "tools," have "bilaterally symmetric structure," but this is not explicitly measured anywhere. "Boats" are described as having "front-back symmetry," more so than flowers. One imagines flowers being extremely symmetric, but perhaps that depends on the metric. What is the metric? At first I thought it was the mirror-symmetric viewpoint tuning index in the image (pixel) space, but this cannot be, as the index for faces and flowers is negative, cars have no symmetry, and boats are positive. To support these descriptions, one must have an independent variable (for object class symmetry) that can be related to the dependent variable (the mirror-symmetric viewpoint tuning index). If it exists, it is not a part of the Results section. This omission undermines other parts of the Results section: "some car models have an approximate front-back symmetry...however, a flower typically does not..." "Some," "typically:" how many in the dataset exactly, and how often? The description of CIFAR-10 as having bilaterally symmetric categories - are all these categories equally symmetric? If not, would such variability matter in terms of these results? These assessments of object category symmetry values are made before experiments are presented, so they are not interpretations of the results, and it would be circular to write it otherwise.
Overall, my bigger concern is that the framing is misleading or at best incomplete. The manuscript successfully showed that if one introduces left-right symmetry to a dataset, the network will develop population-level representations that are also bilaterally symmetric. But the study does not explain that the model's architecture and random weight distribution are sufficient for symmetry tuning to emerge, without training, just to a much more limited degree. Baek et al. showed in 2021 that viewpoint-invariant face-selective units and mirror-symmetric units emerge in untrained networks ("Face detection in untrained deep neural networks"; this current manuscript cites this paper but does not mention that mirror symmetry is a feature of the 2021 study). This current study also used untrained networks as controls (Fig. 3), and while they were useful in showing that learning boosts symmetry tuning, the results also clearly show that horizontal-reflection invariance is far from zero. So, the simple learning-driven explanation for the mirror-symmetric viewpoint tuning for faces is wrong: while (1) network training and (2) pooling are mechanisms that charge the development of mirror-symmetric tuning, the lottery ticket hypothesis is enough for its emergence. Faces and numbers are simple patterns, so the overparameterization of networks is enough to randomly create units that are tuned to these shapes and to wire many of them together. How learning shapes this process is an interesting direction, especially now that this current study has outlined its importance.
Finally, it would help to cite other previous demonstrations of equivariance and mirror symmetry in neural networks. Chris Olah, Nick Cammarata, Chelsea Voss, Ludwig Schubert, and Gabriel Goh of OpenAI wrote of this phenomenon in 2020 (Distill journal).
Some other observations that might help:
- I am enthusiastic about the experiments using different datasets to increase or decrease the rate of mirror-symmetry tuning (sets including CIFAR10, SVHN, symSVHN, asymSVHN); it is worth noting, however, that the lack of a ground truth metric for category symmetry is a problem here too. In the asymSVHN dataset, images are flipped and given different labels. If some categories are naturally symmetric after horizontal flips, such as images containing "0" or "8", then changing the label is likely to disturb training. This would explain why the training loss is larger for this condition (Figure S4D).
- It is puzzling why greyscale 3D rendered images are used. By using greyscale 3D render (at least as shown in the figures) the study proceeds as if the units are invariant under color transformations. Unfortunately, this is not true and using greyscale images impact the activations of different layers of Alexnet in a way that is not fully defined. Moreover, many units in shallow networks focus on color and exactly these units could be invariant to other transformation like the mirror symmetry, but grey scaling the images makes them inactive.
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Reviewer #3 (Public Review):
It has recently been demonstrated that bacteria in biofilms show changes in membrane potential in response to changes in their environment, and that these can propagate signals through the biofilm to coordinate bacterial behavior. Akabuogu et al. contribute to this exciting research area with a study of blue light-induced membrane potential dynamics in E. coli biofilms. They demonstrate that Thioflavin-T (ThT) intensity (a proxy for membrane potential) displays multiphasic dynamics in response to blue light treatment. They additionally use genetic manipulations to implicate the potassium channel Kch in the latter part of these dynamics. Mechanosensitive ion channels may also be involved, although these channels seem to have blue light-independent effects on membrane potential as well. In addition, there are challenges to the quantitative interpretation of ThT microscopy data which require consideration. The authors then explore whether these dynamics are involved in signaling at the community level. The authors suggest that cell firing is both more coordinated when cells are clustered and happens in waves in larger, 3D biofilms; however, in both cases evidence for these claims is incomplete. The authors present two simulations to describe the ThT data. The first of these simulations, a Hodgkin-Huxley model, indicates that the data are consistent with the activity of two ion channels with different kinetics; the Kch channel mutant, which ablates a specific portion of the response curve, is consistent with this. The second model is a fire-diffuse-fire model to describe wavefront propagation of membrane potential changes in a 3D biofilm; because the wavefront data are not presented clearly, the results of this model are difficult to interpret. Finally, the authors discuss whether these membrane potential changes could be involved in generating a protective response to blue light exposure; increased death in a Kch ion channel mutant upon blue light exposure suggests that this may be the case, but a no-light control is needed to clarify this.
In a few instances, the paper is missing key control experiments that are important to the interpretation of the data. This makes it difficult to judge the meaning of some of the presented experiments.
(1) An additional control for the effects of autofluorescence is very important. The authors conduct an experiment where they treat cells with CCCP and see that Thioflavin-T (ThT) dynamics do not change over the course of the experiment. They suggest that this demonstrates that autofluorescence does not impact their measurements. However, cellular autofluorescence depends on the physiological state of the cell, which is impacted by CCCP treatment. A much simpler and more direct experiment would be to repeat the measurement in the absence of ThT or any other stain. This experiment should be performed both in the wild-type strain and in the ∆kch mutant.
(2) The effects of photobleaching should be considered. Of course, the intensity varies a lot over the course of the experiment in a way that photobleaching alone cannot explain. However, photobleaching can still contribute to the kinetics observed. Photobleaching can be assessed by changing the intensity, duration, or frequency of exposure to excitation light during the experiment. Considerations about photobleaching become particularly important when considering the effect of catalase on ThT intensity. The authors find that the decrease in ThT signal after the initial "spike" is attenuated by the addition of catalase; this is what would be predicted by catalase protecting ThT from photobleaching (indeed, catalase can be used to reduce photobleaching in time lapse imaging).
(3) It would be helpful to have a baseline of membrane potential fluctuations in the absence of the proposed stimulus (in this case, blue light). Including traces of membrane potential recorded without light present would help support the claim that these changes in membrane potential represent a blue light-specific stress response, as the authors suggest. Of course, ThT is blue, so if the excitation light for ThT is problematic for this experiment the alternative dye tetramethylrhodamine methyl ester perchlorate (TMRM) can be used instead.
(4) The effects of ThT in combination with blue light should be more carefully considered. In mitochondria, a combination of high concentrations of blue light and ThT leads to disruption of the PMF (Skates et al. 2021 BioRXiv), and similarly, ThT treatment enhances the photodynamic effects of blue light in E. coli (Bondia et al. 2021 Chemical Communications). If present in this experiment, this effect could confound the interpretation of the PMF dynamics reported in the paper.
(5) Figures 4D - E indicate that a ∆kch mutant has increased propidium iodide (PI) staining in the presence of blue light; this is interpreted to mean that Kch-mediated membrane potential dynamics help protect cells from blue light. However, Live/Dead staining results in these strains in the absence of blue light are not reported. This means that the possibility that the ∆kch mutant has a general decrease in survival (independent of any effects of blue light) cannot be ruled out.
(6) Additionally in Figures 4D - E, the interpretation of this experiment can be confounded by the fact that PI uptake can sometimes be seen in bacterial cells with high membrane potential (Kirchhoff & Cypionka 2017 J Microbial Methods); the interpretation is that high membrane potential can lead to increased PI permeability. Because the membrane potential is largely higher throughout blue light treatment in the ∆kch mutant (Fig. 3AB), this complicates the interpretation of this experiment.
Throughout the paper, many ThT intensity traces are compared, and described as "similar" or "dissimilar", without detailed discussion or a clear standard for comparison. For example, the two membrane potential curves in Fig. S1C are described as "similar" although they have very different shapes, whereas the curves in Fig. 1B and 1D are discussed in terms of their differences although they are evidently much more similar to one another. Without metrics or statistics to compare these curves, it is hard to interpret these claims. These comparative interpretations are additionally challenging because many of the figures in which average trace data are presented do not indicate standard deviation.
The differences between the TMRM and ThT curves that the authors show in Fig. S1C warrant further consideration. Some of the key features of the response in the ThT curve (on which much of the modeling work in the paper relies) are not very apparent in the TMRM data. It is not obvious to me which of these traces will be more representative of the actual underlying membrane potential dynamics.
A key claim in this paper (that dynamics of firing differ depending on whether cells are alone or in a colony) is underpinned by "time-to-first peak" analysis, but there are some challenges in interpreting these results. The authors report an average time-to-first peak of 7.34 min for the data in Figure 1B, but the average curve in Figure 1B peaks earlier than this. In Figure 1E, it appears that there are a handful of outliers in the "sparse cell" condition that likely explain this discrepancy. Either an outlier analysis should be done and the mean recomputed accordingly, or a more outlier-robust method like the median should be used instead. Then, a statistical comparison of these results will indicate whether there is a significant difference between them.
In two different 3D biofilm experiments, the authors report the propagation of wavefronts of membrane potential; I am unable to discern these wavefronts in the imaging data, and they are not clearly demonstrated by analysis.
The first data set is presented in Figures 2A, 2B, and Video S3. The images and video are very difficult to interpret because of how the images have been scaled: the center of the biofilm is highly saturated, and the zero value has also been set too high to consistently observe the single cells surrounding the biofilm. With the images scaled this way, it is very difficult to assess dynamics. The time stamps in Video S3 and on the panels in Figure 2A also do not correspond to one another although the same biofilm is shown (and the time course in 2B is also different from what is indicated in 2B). In either case, it appears that the center of the biofilm is consistently brighter than the edges, and the intensity of all cells in the biofilm increases in tandem; by eye, propagating wavefronts (either directed toward the edge or the center) are not evident to me. Increased brightness at the center of the biofilm could be explained by increased cell thickness there (as is typical in this type of biofilm). From the image legend, it is not clear whether the image presented is a single confocal slice or a projection. Even if this is a single confocal slice, in both Video S3 and Figure 2A there are regions of "haze" from out-of-focus light evident, suggesting that light from other focal planes is nonetheless present. This seems to me to be a simpler explanation for the fluorescence dynamics observed in this experiment: cells are all following the same trajectory that corresponds to that seen for single cells, and the center is brighter because of increased biofilm thickness.
The second data set is presented in Video S6B; I am similarly unable to see any wave propagation in this video. I observe only a consistent decrease in fluorescence intensity throughout the experiment that is spatially uniform (except for the bright, dynamic cells near the top; these presumably represent cells that are floating in the microfluidic and have newly arrived to the imaging region).
3D imaging data can be difficult to interpret by eye, so it would perhaps be more helpful to demonstrate these propagating wavefronts by analysis; however, such analysis is not presented in a clear way. The legend in Figure 2B mentions a "wavefront trace", but there is no position information included - this trace instead seems to represent the average intensity trace of all cells. To demonstrate the propagation of a wavefront, this analysis should be shown for different subpopulations of cells at different positions from the center of the biofilm. Data is shown in Figure 8 that reflects the velocity of the wavefront as a function of biofilm position; however, because the wavefronts themselves are not evident in the data, it is difficult to interpret this analysis. The methods section additionally does not contain sufficient information about what these velocities represent and how they are calculated. Because of this, it is difficult for me to evaluate the section of the paper pertaining to wave propagation and the predicted biofilm critical size.
There are some instances in the paper where claims are made that do not have data shown or are not evident in the cited data:
(1) In the first results section, "When CCCP was added, we observed a fast efflux of ions in all cells"- the data figure pertaining to this experiment is in Fig. S1E, which does not show any ion efflux. The methods section does not mention how ion efflux was measured during CCCP treatment.
(2) In the discussion of voltage-gated calcium channels, the authors refer to "spiking events", but these are not obvious in Figure S3E. Although the fluorescence intensity changes over time, it's hard to distinguish these fluctuations from measurement noise; a no-light control could help clarify this.
(3) The authors state that the membrane potential dynamics simulated in Figure 7B are similar to those observed in 3D biofilms in Fig. S4B; however, the second peak is not clearly evident in Fig. S4B and it looks very different for the mature biofilm data reported in Fig. 2. I have some additional confusion about this data specifically: in the intensity trace shown in Fig. S4B, the intensity in the second frame is much higher than the first; this is not evident in Video S6B, in which the highest intensity is in the first frame at time 0. Similarly, the graph indicates that the intensity at 60 minutes is higher than the intensity at 4 minutes, but this is not the case in Fig. S4A or Video S6B.
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Reviewer #3 (Public Review):
The authors present in this study the characterization of two mutant lines of the filasterean Capsaspora owczarzaki, a unicellular holozoan with a key phylogenetic position to understand multicellular development in animals. The present study is built on a previous work from the same research group, on the mutant of the orthologue of the Yorki gene in C. owczarzaki. By knocking out the two upstream kinases of the same pathway, coHpo-/- and coWts-/-, in single cell and aggregates of C. owkzarzaki, they now have mutated the entire pathway and in different cellular contexts.
The authors obtain results in the same direction as the previous work, demonstrating that the Hippo pathway of the unicellular holozoan C. owczarzaki, is not involved in the control of cell proliferation but is related with cytoskeletal dynamics through the actin-myosin mechanism.
In this revised version of the study, the authors have addressed my concerns by providing additional experiments, references and discussing further the points of controversy.
I think the authors have done a great job improving the robustness of the paper proving further some of the claims raised in the previous version of the manuscript.
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Reviewer #3 (Public Review):
Summary:
The manuscript examined the role of large versus small prediction errors (PEs) in creating a state-based memory distinction between acquisition and extinction. The premise of the paper is based on theoretical claims and empirical findings that gradual changes between acquisition and extinction would lead to the potential overwriting of the acquisition memory with extinction, resulting in a more durable reduction in conditioned responding (i.e. more durable extinction effect). The paper tests the hypotheses in a series of elegant experiments in which the shock intensity is decreased across extinction sessions before non-reinforced CS presentations are given. Additional manipulations include context change, shock devaluation, and controlling for lower shock intensity exposure. The critical comparison was standard non-reinforced extinction training. The critical tests were done in spontaneous recovery and reinstatement.
Strengths:<br /> The findings are of tremendous importance in understanding how memories can be updated and reveal a well-defined role of PE in this process. It is well-established that PE is critical for learning, so delineating how PE is critical for generating memory states and the role it serves in keeping memories dissociable (or not) is exciting and clever. As such the paper addresses a fundamental question in the field.
The studies test clear and defined predictions derived from simulations of the state-belief model of Cochran & Cisler (2019). The designs are excellent: well-controlled and address the question.
The authors have done an excellent job of explaining the value of the latent state models.
The authors have studied both sexes in the study presented, providing generality across the sexes in their findings. However, depicting the individual data points in the bar graphs and noting which data represent males and which represent females would be of great value.
Weaknesses:
(1) While it seems obvious that delivering a lower intensity shock will generate a smaller PE than say no shock, it would have been nice to see data from say a compound testing procedure that confirms this.
(2) The devaluation experiment is quite clever, but it also would be strengthened if there was evidence in the paper that this procedure does indeed lead to shock devaluation.
(3) It would have been very exciting to see even more parametric examinations of this idea, like maintaining shock intensity but gradually reducing shock duration, which would have increased the impact of the paper.
(4) Individual data points should be represented in the test figures (see above also).
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Reviewer #3 (Public Review):
Summary:<br /> This manuscript describes the symptoms of patients harboring KCNQ2 mutation G256W, functional changes of the mutant channel in exogenous expression, and phenotypes of G256W/+ mice. The patients presented seizures, the mutation reduced currents of the channel, and the G256W/+ mice showed seizures, increased firing frequency in neurons, reduced KCNQ2 expression,<br /> and altered subcellular distribution.
Strengths:
This is a large amount of work and all results corroborated the pathogenicity of the mutation in KCNQ2, providing an interesting example of KCNQ2-associated neurological disorder's impact on functions at all levels including molecular, cellular, tissue, animal model, and patients.
Weaknesses:
The manuscript described observations of changes in association with the mutation at molecular cellular functions and animal phenotype, but the results in some aspects are not as strong as in others. Nevertheless, the manuscript made overarching conclusions even when the evidence was not sufficiently strong.
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Reviewer #3 (Public Review):
Stout et al investigate the link between prefrontal-hippocampal (PFC-HPC) theta-band coherence and accurate decisions in spatial decision making tasks. Previous studies show that PFC-HPC theta coherence positively correlates with task learning and correct decisions but the nature of this relation relies on correlations that cannot show whether coherence leads, coincides or is a consequence of decision making. To investigate more precisely this link, the authors devise a novel paradigm. In this paradigm the rat is blocked during a delay period preceding its choice and they control on a trial-by-trial basis the level of PFC-HPC theta coherence prior to the decision by allowing the rat to access the choice point only at a time when coherence reaches above or below a threshold. The design of the paradigm is very well controlled in many ways. First, using the PFC-HPC theta coherence during the delay period to gate when the rat accesses the choice zone clearly separates this coherence from the behavioural decision itself. Moreover, the behaviour of the animal is similar during high and low coherence periods. Finally, control trials are matched trial-by-trial to the time spent waiting by the rat when gated on theta coherence, which is crucial given that working memory performance depends on delay duration. All these features bolster the specificity of the author's main finding which is that PFC-HPC theta coherence prior to choice making is strongly predictive of accuracy in two tasks : one that requires working memory and another in which behaviour is cue-guided. Although this paradigm does not provide direct causal evidence, it convincingly supports the idea that PFC-HPC theta coherence prior to the behavioural decision is related to correct decision making and is not simply temporally coincidental or a consequence of the decision output.
The authors also investigate the mechanisms behind the increase in PFC-HPC coherence during the task and show that it likely involves the recruitment of a small population of PFC neurons, via interactions with the Ventral Midline Thalamus that could mediate prefrontal/hippocampal dialogue.
A key point of interest is the unexpected result showing a link between theta coherence even in the cue-driven version of the task. As the authors point out, muscimol inhibition of neither PFC nor HPC, nor the ventral midline thalamus impacts performance in this task. This raises the question of why coherence between two areas is predictive of choice accuracy when neither area appears to be causally involved. The authors discuss various options and explanations for this discrepancy which clearly adds to the current debate. Moreover their novel paradigm provides new tools to interrogate when inter-area synchrony is associated with information transfer and when this information is then used to drive behavioural decisions.
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Reviewer #3 (Public Review):
Summary and strengths:
In the manuscript, Abd El Hay et al investigate the role of thermally sensitive ion channels TRPM2 and TRPV1 in warm preference and their dynamic response features to thermal stimulation. They develop a novel thermal preference task, where both the floor and air temperature are controlled, and conclude that mice likely integrate floor with air temperature to form a thermal preference. They go on to use knockout mice and show that TRPM2-/- mice play a role in the avoidance of warmer temperatures. Using a new approach for culturing DRG neurons they show the involvement of both channels in warm responsiveness and dynamics. This is an interesting study with novel methods that generate important new information on the different roles of TRPV1 and TRPM2 on thermal behavior.
Open questions and weaknesses:
(1) Differences in the response features of cells expressing TRPM2 and TRPV1 are central and interesting findings but need further validation (Figures 3 and 4). To show differences in the dynamics and the amplitude of responses across different lines and stimulus amplitudes more clearly, the authors should show the grand average population calcium response from all responsive neurons with error bars for all 3 groups for the different amplitudes of stimuli (as has been presented for the thermal stimuli traces). The authors should also provide a population analysis of the amplitude of the responses in all groups to all stimulus amplitudes. Prior work suggests that thermal detection is supported by an enhancement or suppression of the ongoing activity of sensory fibers innervating the skin. The authors should present any data on cells with ongoing activity.
(2) The authors should better place their findings in context with the literature and highlight the novelty of their findings. The introduction builds a story of a 'disconnect' or 'contradictory' findings about the role of TRPV1 and TRPM2 in warm detection. While there are some disparate findings in the literature, Tan and McNaughton (2016) show a role for TRPM2 in the avoidance of warmth in a similar task, Paricio et al. (2020) show a significant reduction in warm perception in TRPM2 and TRPV1 knock out lines and Yarmolinksy et al. (2016) show a reduction in warm perception with TRPV1 inactivation. All these papers are therefore in agreement with the authors finding of a role for these channels in warm behavior. The authors should change their introduction and discussion to more correctly discuss the findings of these studies and to better pinpoint the novelty of their own work.
(3) The responses of 60 randomly selected cells are shown in Figure 2B. But, looking at the TRPM2-/- data, warm responses appear more obvious than in WTs and the weaker responders of the WT group appear weaker than the equivalent group in the TRPV1-/- and TRPM2-/- data. This does not necessarily invalidate the results, but it may suggest a problem in the data selection. Because the correct classification of warm-sensitive neurons is central to this part of the study more validation of the classifier should be presented. For example, the authors could state if they trained the classifier using equal amounts of cells, show some randomly selected cells that are warm-insensitive for all genotypes, and show the population average responses of warm-insensitive neurons.
(4) The interpretation of the main behavioral results and justification of the last figure is presented as the result of changes in sensing but differences in this behavior could be due to many factors and this needs clarification and discussion. (i) The authors mention that 'crucially temperature perception is not static' and suggest that there are fluctuating changes in perception over time and conclude that their modelling approach helps show changes in temperature detection. They imply that temperature perceptual threshold changes over time, but the mouse could just as easily have had exactly the same threshold throughout the task but their motivation (or some other cognitive variable) might vary causing them to change chamber. The authors should correct this. (ii) Likewise, from their fascinating and high-profile prior work the authors suggest a model of internal temperature sensing whereby TRPM2 expression in the hypothalamus acts as an internal sensory of body temperature. Given this, and the slow time course of the behavior in chambers with different ambient temperatures, couldn't the reason for the behavioral differences be due to central changes in hypothalamic processing rather than detection by skin temperature? If TRPM2-/- were selectively ablated from the skin or the hypothalamus (these experiments are not necessary for this paper) it might be possible to conclude whether sensation or body temperature is more likely the root cause of these effects but, without further experiments it is tough to conclude either way. (iii) Because the ambient temperature is controlled in this behavior, another hypothesis is that warm avoidance could be due to negative valence associated with breathing warm air, i.e. a result of sensation within the body in internal pathways, rather than sensing from the external skin. Overall, the authors should tone down conclusions about sensation and present a more detailed discussion of these points.
(5) It is an excellent idea to present a more in-depth analysis of the behavioral data collected during the preference task, beyond 'the mouse is on one side or the other'. However, the drift-diffusion approach is complex to interpret from the text in the results and the figures. The results text is not completely clear on which behavioral parameters are analyzed and terms like drift, noise, estimate, and evidence are not clearly defined. Currently, this section of the paper slightly confuses and takes the paper away from the central findings about dynamics and behavioral differences. It seems like they could come to similar conclusions with simpler analysis and simpler figures.
(6) In Figure 2D the % of warm-sensitive neurons are shown for each genotype. Each data point is a field of view, however, reading the figure legend there appear to be more FOVs than data points (eg 10 data points for the TRPV1-/- but 17 FOVs). The authors should check this.
(7) Can the authors comment on why animals with over-expression of TRPV1 spend more time in the warmest chamber to start with at 38C and not at 34C?
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Reviewer #3 (Public Review):
Reviewing Editor's Summary:
The revised manuscript has clarified concerns raised by the reviewers concerning the analysis method in constructing the correlation matrix. These key results are now readily comprehensible. They have also added a final section to the Discussion, sketching some important questions for future research (e.g., number/resolution of channels and extension of the logic used here to look at number channels in other tasks).
Reviewer 1 was satisfied with these changes and has updated their review. Reviewer 2 did not think the revision tackled the theoretical issues raised in their initial review; as such, this reviewer has opted to leave their initial public review unchanged.
I also believe that the revision does not adequately address a major theoretical issue, namely whether the current data provide evidence of sensorimotor number channels, the central claim of the paper. The authors argue that since perception is noise free (stimuli were given symbolically), then the task variance comes from processes associated with sensorimotor transformation. Let's consider the task: A number is presented, the participant then attempts to produce that number of taps. To preclude counting, they are required to say the syllable "ba" as fast as possible while tapping. The sensorimotor channel idea would suppose that the symbolic stimulus activates a set of channels, each of which specifies the number of taps that should be produced. For example, a "6" channel likes to produce 6 outputs (with variability), a "10" channel 10 outputs (with variability), etc., with the actual production of the (weighted) integration of these outputs.
An alternative is that, since explicit counting is prevented by the secondary task, the participant makes an internal estimation of the number of produced taps. These judgments could be based on the output of amodal number channels. For example, the same process would be at play if the task were changed such that the participants watched a dot flash and had to estimate the number of flashes (while concurrently saying "ba"). The authors indicate in their response letter that they are conducting experiments along these lines and that the results are similar. They suggest that this provides support for the existence of both sensory and sensorimotor number channels. Extending this, if the experiment were tones instead of flashes, the argument would be that there are auditory, visual, and sensorimotor number channels. It seems more parsimonious to interpret such a pattern as reflective of amodal number channels.
I recognize there are other intriguing reasons to think there may be intimate links between our sense of number and movement, but I remain unconvinced that the current results provide evidence for sensorimotor number channels.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript reports two neuroimaging experiments assessing commonalities and differences in activation loci across mechanical problem-solving, technical reasoning, fluid cognition, and "mentalizing" tasks. Each task includes a control task. Conjunction analyses are performed to identify regions in common across tasks. As Area PF (a part of the supramarginal gyrus of the inferior parietal lobe) is involved across 3 of the 4 tasks, the investigators claim that it is the hub of technical cognition.
Strengths:
The aim of finding commonalities and differences across related problem-solving tasks is a useful and interesting one.
The experimental tasks themselves appear relatively well-thought-out, aside from the concern that they are differentially difficult.
The imaging pipeline appears appropriate.
Weaknesses:
(1) Methodological<br /> As indicated in the supplementary tables and figures, the experimental tasks employed differ markedly in 1) difficulty and 2) experimental trial time. Response latencies are not reported (but are of additional concern given the variance in difficulty). There is concern that at least some of the differences in activation patterns across tasks are the result of these fundamental differences in how hard various brain regions have to work to solve the tasks and/or how much of the trial epoch is actually consumed by "on-task" behavior. These difficulty issues should be controlled for by 1) separating correct and incorrect trials, and 2) for correct trials, entering response latency as a regressor in the Generalized Linear Models, 3) entering trial duration in the GLMs.
A related concern is that the control tasks also differ markedly in the degree to which they were easier and faster than their corresponding experimental task. Thus, some of the control tasks seem to control much better for difficulty and time on task than others. For example, the control task for the psychotechnical task simply requires the indication of which array contains a simple square shape (i.e., it is much easier than the psychotechnical task), whereas the control task for mechanical problem-solving requires mentally fitting a shape into a design, much like solving a jigsaw puzzle (i.e., it is only slightly easier than the experimental task).
(2) Theoretical<br /> The investigators seem to overlook prior research that does not support their perspective and their writing seems to lack scientific objectivity in places. At times they over-reach in the claims that can be made based on the present data. Some claims need to be revised/softened.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
Hoogstraaten et al investigated the involvement of rabphilin-3A RPH3A in DCV fusion in neurons during calcium-triggered exocytosis at the synapse and during neurite elongation. They suggest that RPH3A acts as an inhibitory factor for LDV fusion and this is mediated partially via its interaction with SNAP25 and not Rab3A/Rab27. It is a very elegant study although several questions remain to be clarified.
Strengths:
The authors use state-of-the-art techniques like tracking NPY-PHluorin exocytosis and FRAP experiments to quantify these processes providing novel insight into LDCs exocytosis and the involvement of RPH3A.
Weaknesses:
At the current state of the manuscript, further supportive experiments are necessary to fully support the authors' conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this work, the authors use a Hidden Markov Model (HMM) to describe dynamic connectivity and amplitude patterns in fMRI data, and propose to integrate these features with the Fisher Kernel to improve the prediction of individual traits. The approach is tested using a large sample of healthy young adults from the Human Connectome Project. The HMM-Fisher Kernel approach was shown to achieve higher prediction accuracy with lower variance on many individual traits compared to alternate kernels and measures of static connectivity. As an additional finding, the authors demonstrate that parameters of the HMM state matrix may be more informative in predicting behavioral/cognitive variables in this data compared to state-transition probabilities.
Strengths:
- Overall, this work helps to address the timely challenge of how to leverage high-dimensional dynamic features to describe brain activity in individuals.<br /> - The idea to use a Fisher Kernel seems novel and suitable in this context.<br /> - Detailed comparisons are carried out across the set of individual traits, as well as across models with alternate kernels and features.<br /> - The paper is well-written and clear, and the analysis is thorough.
Potential weaknesses:
- One conclusion of the paper is that the Fisher Kernel "predicts more accurately than other methods" (Section 2.1 heading). I was not certain this conclusion is fully justified by the data presented, as it appears that certain individual traits may be better predicted by other approaches (e.g., as shown in Figure 3) and I found it hard to tell if certain pairwise comparisons were performed -- was the linear Fisher Kernel significantly better than the linear Naive normalized kernel, for example?
- While 10-fold cross-validation is used for behavioral prediction, it appears that data from the entire set of subjects is concatenated to produce the initial group-level HMM estimates (which are then customized to individuals). I wonder if this procedure could introduce some shared information between CV training and test sets. This may be a minor issue when comparing the HMM-based models to one another, but it may be more important when comparing with other models such as those based on time-averaged connectivity, which are calculated separately for train/test partitions (if I understood correctly).
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This paper seeks to understand the role of alveolar myofibroblasts in abnormal lung development after saccular stage injury.
Strengths:
Multiple models of neonatal injury are used, including hyperoxia and transgenic models that target alveolar myofibroblasts.
Weaknesses:
There are several weaknesses that leave the conclusions significantly undersupported by the data as presented:
(1) There is no validation of the decreased number of myofibroblasts suggested by flow cytometry/scRNAseq at the level of the tissue. Given that multiple groups have reported increased myofibroblasts (aSMA+ fibroblasts) in humans with BPD and in mouse models, demonstrating a departure from prior findings with tissue validation in the mouse models is essential. There are many reasons for decreased numbers of a subpopulation by flow cytometry, most notably that injured cells may be less likely to survive the cell sorting process.
(2) The hallmark genes used to define the subpopulations are not given in single-cell data. As the definition of fibroblast subtypes remains an area of unsettled discussion in the field, it is possible that the decreased number by classification and not a true difference. Tissue validation and more transparency in the methods used for single-cell sequencing would be critical here.
(3) There is an oversimplification of neonatal hyperoxia as a "BPD model" used here without a reference to detailed prior work demonstrating that the degree and duration of hyperoxia dramatically change the phenotype. For example, Morty et al have shown that hyperoxia of 85% or more x 14 days is required to demonstrate the septal thickening observed in severe human BPD. Other than one metric of lung morphometry (MLI), which is missing units on the y-axis and flexivent data, the authors have not fully characterized this model. Prior work comparing 75% O2 exposure for 5, 8, or 14 days shows that in the 8-day exposed group (similar to the model used here), much of the injury was reversible. What evidence do the authors have that hyperoxia alone is an accurate model of the permanent structural injury seen in human BPD?
(4) Thibeault et al published a single-cell analysis of neoantal hyperoxia in 2021, with seemingly contrasting findings. How does this dataset compare in context?
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This is a well-prepared manuscript that presented interesting research results. The only defect is that the authors should further revise the English language.
Strengths:
The omics method produced unbiased results.
Weaknesses:
LPS neutralization is not a new method for treating leptospiral infection.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> This study provides a comparison of TCR gene segment usage between foetal and adult thymus.
Strengths:<br /> Interesting computational analyses was performed to find interesting differences in TCR gene usage within unpaired TCRa and TCRb chains between foetal and adult thymus.
Weaknesses:<br /> This study was significantly lacking insight and interpretation into what the data analysed actually means for the biology. The dataset discussed in the paper is from only two experiments. One comparing foetal and adult thymi from 4 mice per group and another which involved hydrocortisone treatment. The paper uses TCR sequencing methodology that sequences each TCR alpha and beta chains in an unpaired way, meaning that the true identity of the TCR heterodimer is lost. This also has the added problem of overestimating clonality, and underestimating diversity.<br /> Limited detail in the methods sections also limits the ability for readers to properly interpret the dataset. What sex of mice were used? Are there any sex differences? What were the animal ethics approvals for the study?
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This manuscript reports a detailed genetic and epigenomic analysis of diagnostic and relapsed AML. The study is mostly correlative and some of the initial findings, such as the stability of mutations in epigenetic regulators at diagnosis and relapse and in signaling pathway modulators such as FLT3 and NRAS being lost - not novel.
The authors show that in a large fraction (approximately half) of the relapsed AMLs they study, there are no alterations in the AML driver mutations. The authors conclude that this indicates that these patients show non-genetic mechanisms of relapse, for which the authors embark on a series of epigenomic experiments to try and pin down the correlative or causative epigenetic mechanisms. In 9 (out of 25) patient samples with stable driver mutations ( i.e. no change in clonality or novel AML driver mutation accumulation) the study shows that there is high epigenetic variability as measured by chromatin accessibility changes and that these changes resemble less differentiated state in the relapsed compared to the diagnostic sample. The manuscript makes some key observations: 1) non-genetic mechanisms are likely to account for relapse in a substantial proportion of patients. 2) some of the clones that emerge following relapse are likely present in prior diagnosis samples indicating that chemotherapy selects for them, 3) Of note, the authors also look at the LSC and non-LSC compartments and show that the LSC compartment is more rigid in terms of epigenetic evolution towards relapse than the non-LSC cells. 4) Using a small number of patients (but justifiable since the assays used are rigorous and demanding) - the authors present the most interesting finding of the study - that epigenetic evolution of relapse in several different AML patients seems to be convergent.<br /> This is based on the epigenetic similarities in clones (as defined by mitochondrial Atac-seq) between different epigenetic relapsed clones, even though they were distinct at diagnosis. Thus, this study has several important observations. Some of these observations are incremental - it has been shown that epigenetic mechanisms drive relapse in AML but several are not. I think this study - although descriptive and not showing causal relationships - is an important study for advancing our understanding of AML relapse.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> In the manuscript by Valenzisi et al., the authors report on the role of WRNIP1 to prevent R-loop and TRC-associated DNA damage. The authors claim WRNIP1 localizes to TRCs in response to replication stress and prevents R-loop accumulation, TRC formation, replication fork stalling, and subsequent DNA damage. While the findings are of potential significance to the field, the strength of evidence in support of the conclusions is lacking.
In the revised submission by Velenzisi et al., the manuscript is still missing the controls that were requested in the original review. One cannot conclude the D37A mutant is unable to rescue DNA damage unless it is shown in the same experiment that the WT is able to rescue it. This is also true for the fork speed, stalled forks, and restarting forks experiments. Below is a list of Figures missing key controls.
Figure 1B -missing the shWRNIP1WT control<br /> Figure 1C - missing the MRC5SV control<br /> Figure 1D - missing the shWRNIP1WT control<br /> Figure 3C - missing the shWRNIP1WT control<br /> Figure 5A - missing the shWRNIP1WT control<br /> Figure 5B - missing the shWRNIP1WT control<br /> Figure 5C - missing the shWRNIP1WT control<br /> Figure 5D - missing the shWRNIP1WT control<br /> Figure 6C - missing the shWRNIP1WT control
Also, the authors did not explain the result showing shWRNIP1 decreases DNA damage compared to MRC5SV in Figure 1D (compare lanes 4 and 8). Again, this suggests WRNIP1 actually increases DNA damage in response to Aph and DRB. This concern was raised in the original peer review, and it remains unaddressed in the revised manuscript.
The use of RNaseHIII increases the specificity of the S9.6 antibody and improves confidence in the DNA-RNA hybrid data throughout the manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The vesicular monoamine transporter is a key component in neuronal signaling and is implicated in diseases such as Parkinson's. Understanding of monoamine processing and our ability to target that process therapeutically has been to date provided by structural modeling and extensive biochemical studies. However, structural data is required to establish these findings more firmly.
Strengths:
Dalton et al resolved a structure of VMAT2 in the presence of an important inhibitor, tetrabenazine, with the protein in detergent micelles, using cryo-EM and with the aid of protein domains fused to its N- and C-terminal ends, including one fluorescent protein that facilitated protein screening and purification. The resolution of the maps allows clear assignment of the amino acids in the core of the protein. The structure is in good agreement with a wealth of experimental and structural prediction data, and provides important insights into the binding site for tetrabenazine and selectivity relative to analogous compounds. The authors provide additional biochemical analyses that further support their findings. The comparison with AlphaFold models is enlightening.
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Reviewer #3 (Public Review):
Summary:
This manuscript describes a study of the olfactory tubercle in the context of reward representation in the brain. The authors do so by studying the responses of OT neurons to odors with various reward contingencies and compare systematically to the ventral pallidum. Through careful tracing, they present convincing anatomical evidence that the projection from the olfactory tubercle is restricted to the lateral portion of the ventral pallidum.
Using a clever behavioral paradigm, the authors then investigate how D1 receptor- vs. D2 receptor-expressing neurons of the OT respond to odors as mice learn different contingencies. The authors find that, while the D1-expressing OT neurons are modulated marginally more by the rewarded odor than the D2-expressing OT neurons as mice learn the contingencies, this modulation is significantly less than is observed for the ventral pallidum. In addition, neither of the OT neuron classes shows conspicuous amount of modulation by the reward itself. In contrast, the OT neurons contained information that could distinguish odor identities. These observations have led the authors to conclude that the primary feature represented in the OT may not be reward.
Strengths:
The highly localized projection pattern from olfactory tubercle to ventral pallidum is a valuable finding and suggests that studying this connection may give unique insights into the transformation of odor by reward association.
Comparison of olfactory tubervle vs. ventral pallidum is a good strategy to further clarify the olfactory tubercle's position in value representation in the brain.
Weaknesses:
The study comes to a different conclusion about the olfactory tubercle regarding reward representations from several other prior works. Whether this stems from a difference in the experimental configurations such as behavioral paradigms used or indeed points to a conceptually different role for the olfactory tubercle remains to be seen.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> This study indicates that connections across human cortical pyramidal cells have identical latencies despite a larger mean dendritic and axonal length between somas in the human cortex. A precise demonstration combining detailed electrophysiology and modeling indicates that this property is due to faster propagation of signals in proximal human dendrites. This faster propagation is itself due to a slightly thicker dendrite, a larger capacitive load, and stronger hyperpolarizing currents. Hence, the biophysical properties of human pyramidal cells are adapted such that they do not compromise information transfer speed.
Strengths:<br /> The manuscript is clear and very detailed. The authors have experimentally verified a large number of aspects that could affect propagation speed and have pinpointed the most important one. This paper provides an excellent comparison of biophysical properties between rat and human pyramidal cells. Thanks to this approach a comprehensive description of the mechanisms underlying the acceleration of propagation in human dendrite is provided.
Weaknesses:<br /> Several aspects having an impact on propagation speed are highlighted (dendritic diameter, ionic channels, capacitive load) and there is no clear ranking of their impact on signal propagation speed. It seems that the capacitive load plays a major role, much more than dendritic diameter for which only a 10% increase is observed across species. Both aspects actually indicate that there is an increase in passive signal propagation speed with bigger cells at least close to the soma. This suggests that bigger cells are mechanically more rapid. An intuitive reason why capacitive load increases speed would also help the reader follow the demonstration.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In this manuscript, Ma et al seek to identify stem cell niche factors. They perform an RNAi screen in glial cells and screen for candidates that support and maintain neuroblasts (NBs) in the developing fly brain. Through this, they identify two subunits of ferritin, which is a conserved protein that can store iron in cells in a non-toxic form and release it in a controlled manner when and where required. They present data to support the conclusion that ferritin produced in glia is released and taken up by NBs where it is utilised by enzymes in the Krebs cycle as well as in the electron transport chain. In its absence from glia, NBs are unable to generate sufficient energy for division and therefore prematurely differentiate via nuclear prospero resulting in small brains. The work will be of interest to those interested in neural stem cells and their non-cell autonomous control by niches.
The past decade has seen a growing appreciation of how glial cells support and maintain NBs during development. The authors' discovery of glial-derived ferritin providing essential iron atoms for energy production is interesting and important. They have employed a variety of genetic tools and assays to uncover how ferritin in glia might support NBs. This is particularly challenging because there are no direct ways of assaying for iron or energy consumption in a cell-specific manner.
There are however instances where conclusions are drawn to support the story being developed without considering the equally plausible alternative explanations that should ideally be addressed.
For example, the data supporting the transfer of ferritin from glia to NBs was weak given the misexpression system used; the Shi[ts] experiment was also not convincing (perhaps they have more representative images?).
The iron manipulation experiments are in the whole animal and it is likely that this affects general feeding behaviour, which is known to affect NB exit from quiescence and proliferative capacity. The loss of ferritin in the gut and iron chelators enhancing the NB phenotype are used as evidence that glia provide iron to NB to support their number and proliferation. Since the loss of NB is a phenotype that could result from many possible underlying causes (including low nutrition), this specific conclusion is one of many possibilities.
Similarly, knockdown of the FeS protein assembly components phenocopy glial ferritin knock down. Since iron is so important for the TCA and the ETC, this is not surprising, but the similarities in the two phenotypes seem insufficient to say that it's glial ferritin that's causing the lack of iron in the NB and therefore resulting in loss of NBs.
Pros RNAi will certainly result in an increase in NB numbers because the loss of pros results in an inability of NB progeny to differentiate. This (despite the slight increase in nuclear pros) is not sufficient to infer that glial ferritin knockdown results in premature differentiation of NBs via nuclear pros.
I recognise these are challenging to prove irrefutably, however, the frequency of such expansive interpretations of data is of concern.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> Loewinger et al., extend a previously described framework (Cui et al., 2021) to provide new methods for statistical analysis of fiber photometry data. The methodology combines functional regression with linear mixed models, allowing inference on complex study designs that are common in photometry studies. To demonstrate its utility, they reanalyze datasets from two recent fiber photometry studies into mesolimbic dopamine. Then, through simulation, they demonstrate the superiority of their approach compared to other common methods.
Strengths:<br /> The statistical framework described provides a powerful way to analyze photometry data and potentially other similar signals. The provided package makes this methodology easy to implement and the extensively worked examples of reanalysis provide a useful guide to others on how to correctly specify models.
Modeling the entire trial (function regression) removes the need to choose appropriate summary statistics, removing the opportunity to introduce bias, for example in searching for optimal windows in which to calculate the AUC. This is demonstrated in the re-analysis of Jeong et al., 2022, in which the AUC measures presented masked important details about how the photometry signal was changing.
Meanwhile, using linear mixed methods allows for the estimation of random effects, which are an important consideration given the repeated-measures design of most photometry studies.
Weaknesses:<br /> While the availability of the software package (fastFMM), the provided code, and worked examples used in the paper are undoubtedly helpful to those wanting to use these methods, some concepts could be explained more thoroughly for a general neuroscience audience.
While the methodology is sound and the discussion of its benefits is good, the interpretation and discussion of the re-analyzed results are poor:
In section 2.3, the authors use FLMM to identify an instance of Simpson's Paradox in the analysis of Jeong et al. (2022). While this phenomenon is evident in the original authors' metrics (replotted in Figure 5A), FLMM provides a convenient method to identify these effects while illustrating the deficiencies of the original authors' approach of concatenating a different number of sessions for each animal and ignoring potential within-session effects. The discussion of this result is muddled. Having identified the paradox, there is some appropriate speculation as to what is causing these opposing effects, particularly the decrease in sessions. In the discussion and appendices, the authors identify (1) changes in satiation/habitation/motivation, (2) the predictability of the rewards (presumably by the click of a solenoid valve) and (3) photobleaching as potential explanations of the decrease within days. Having identified these effects, but without strong evidence to rule all three out, the discussion of whether RPE or ANCCR matches these results is probably moot. In particular, the hypotheses developed by Jeong et al., were for a random (unpredictable) rewards experiment, whereas the evidence points to the rewards being sometimes predictable. The learning of that predictability (e.g. over sessions) and variation in predictability (e.g. by attention level to sounds of each mouse) significantly complicate the analysis. The FLMM analysis reveals the complexity of analyzing what is apparently a straightforward task design. If this paper is not trying to arbitrate between RPE and ANCCR, as stated in the text, the post hoc reasoning of the authors of Jeong et al 2022 provided in the discussion is not germane. Arbitrating between the models likely requires new experimental designs (removing the sound of the solenoid, satiety controls) or more complex models (e.g. with session effects, measures of predictability) that address the identified issues.
Of the three potential causes of within-session decreases, the photobleaching arguments advanced in the discussion and expanded greatly in the appendices are not convincing. The data being modeled is a processed signal (ΔF/F) with smoothing and baseline correction and this does not seem to have been considered in the argument. Furthermore, the photometry readout is also a convolution of the actual concentration changes over time, influenced by the on-off kinetics of the sensor, which makes the interpretation of timing effects of photobleaching less obvious than presented here and more complex than the dyes considered in the cited reference used as a foundation for this line of reasoning.
Within this discussion of photobleaching, the characterization of the background reward experiments used in part to consider photobleaching (appendix 7.3.2) is incorrect. In this experiment (Jeong et al., 2022), background rewards were only delivered in the inter-trial-interval (i.e. not between the CS+ and predicted reward as stated in the text). Both in the authors' description and in the data, there is a 6s before cue onset where rewards are not delivered and while not described in the text, the data suggests there is a period after a predicted reward when background rewards are not delivered. This complicates the comparison of this data to the random reward experiment.
The discussion of the lack of evidence for backpropagation, taken as evidence for ANCCR over RPE, is also weak. A more useful exercise than comparing FLMM to the methods and data of Jeong et al., 2022, would be to compare against the approach of Amo et al., 2022, which identifies backpropagation (data publicly available: DOI: 10.5061/dryad.hhmgqnkjw). The replication of a positive result would be more convincing of the sensitivity of the methodology than the replication of a negative result, which could be a result of many factors in the experimental design. Given that the Amo et al. analysis relies on identifying systematic changes in the timing of a signal over time, this would be particularly useful in understanding if the smoothing steps in FLMM obscure such changes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> The authors present a Python tool, Heron, that provides a framework for defining and running experiments in a lab setting (e.g. in behavioural neuroscience). It consists of a graphical editor for defining the pipeline (interconnected nodes with parameters that can pass data between them), an API for defining the nodes of these pipelines, and a framework based on ZeroMQ, responsible for the overall control and data exchange between nodes. Since nodes run independently and only communicate via network messages, an experiment can make use of nodes running on several machines and in separate environments, including on different operating systems.
Strengths:<br /> As the authors correctly identify, lab experiments often require a hodgepodge of separate hardware and software tools working together. A single, unified interface for defining these connections and running/supervising the experiment, together with flexibility in defining the individual subtasks (nodes) is therefore a very welcome approach. The GUI editor seems fairly intuitive, and Python as an accessible programming environment is a very sensible choice. By basing the communication on the widely used ZeroMQ framework, they have a solid base for the required non-trivial coordination and communication. Potential users reading the paper will have a good idea of how to use the software and whether it would be helpful for their own work. The presented experiments convincingly demonstrate the usefulness of the tool for realistic scientific applications.
Weaknesses:<br /> In my opinion, the authors somewhat oversell the reproducibility and "self-documentation" aspect of their solution. While it is certainly true that the graph representation gives a useful high-level overview of an experiment, it can also suffer from the same shortcomings as a "pure code" description of a model - if a user gives their nodes and parameters generic/unhelpful names, reading the graph will not help much. Making the link between the nodes and the actual code is also not straightforward, since the code for the nodes is spread out over several directories (or potentially even machines), and not directly accessible from within the GUI. The authors state that "[Heron's approach] confers obvious benefits to the exchange and reproducibility of experiments", but the paper does not discuss how one would actually exchange an experiment and its parameters, given that the graph (and its json representation) contains user-specific absolute filenames, machine IP addresses, etc, and the parameter values that were used are stored in general data frames, potentially separate from the results. Neither does it address how a user could keep track of which versions of files were used (including Heron itself).
Another limitation that in my opinion is not sufficiently addressed is the communication between the nodes, and the effect of passing all communications via the host machine and SSH. What does this mean for the resulting throughput and latency - in particular in comparison to software such as Bonsai or Autopilot? The paper also states that "Heron is designed to have no message buffering, thus automatically dropping any messages that come into a Node's inputs while the Node's worker function is still running."- it seems to be up to the user to debug and handle this manually?
As a final comment, I have to admit that I was a bit confused by the use of the term "Knowledge Graph" in the title and elsewhere. In my opinion, the Heron software describes "pipelines" or "data workflows", not knowledge graphs - I'd understand a knowledge graph to be about entities and their relationships. As the authors state, it is usually meant to make it possible to "test propositions against the knowledge and also create novel propositions" - how would this apply here?
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This paper reexamined large excitatory neurons in the stratum radiatum with optogenetics. The findings are valuable because prior studies of the circuitry were confounded by the use of stimulating electrodes placed in different layers where multiple inputs were stimulated at one time. The strength of the evidence for the conclusions is incomplete because of several concerns with the manuscript.
Strengths:
The strength of the study is the very nice presentation of data. Also, there is a nice combination of patching, LFPs, paired recordings, and microelectrode arrays.
Weaknesses:
The limitations are in the conclusions which don't seem fully justified.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Xiong et al. investigated the debated mechanism of PKA activation using hippocampal CA1 neurons under pharmacological and synaptic stimulations. Examining the two PKA major isoforms in these neurons, they found that a portion of PKA-C dissociates from PKA-R and translocates into dendritic spines following norepinephrine bath application. Additionally, their use of a non-dissociable form of PKC demonstrates its essential role in structural long-term potentiation (LTP) induced by two-photon glutamate uncaging, as well as in maintaining normal synaptic transmission, as verified by electrophysiology. This study presents a valuable finding on the activation-dependent re-distribution of PKA catalytic subunits in CA1 neurons, a process vital for synaptic functionality. The robust evidence provided by the authors makes this work particularly relevant for biologists seeking to understand PKA activation and its downstream effects essential for synaptic plasticity.
Strengths:
The study is methodologically robust, particularly in the application of two-photon imaging and electrophysiology. The experiments are well-designed with effective controls and a comprehensive analysis. The credibility of the data is further enhanced by the research team's previous works in related experiments. The conclusions of this paper are mostly well supported by data. The research fills a significant gap in our understanding of PKA activation mechanisms in synaptic functioning, presenting valuable insights backed by empirical evidence.
Weaknesses:
The physiological relevance of the findings regarding PKA dissociation is somewhat weakened by the use of norepinephrine (10 µM) in bath applications, which might not accurately reflect physiological conditions. Furthermore, the study does not address the impact of glutamate uncaging, a well-characterized physiologically relevant stimulation, on the redistribution of PKA catalytic subunits, leaving some questions unanswered.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Nguyen et al show data indicating that the vomeronasal organ (VNO) and ventromedial hypothalamus (VMH) are part of a circuit that elicits defensive responses induced by predator odors. They also show that using fresh or old predator saliva may be a method to change the perceived imminence of predation. The authors also identify a family of VNO receptors that are activated by cat saliva. Next, the authors show how different components of this defensive circuit are activated by saliva, as measured by fos expression. Though interesting, the findings are not all integrated into a single narrative, and some of the results are only replications of earlier findings using modern methods. Overall, these findings provide incremental advance.
Strengths:
(1) Predator saliva is a stimulus of high ethological relevance
(2) The authors performed a careful quantification of fos induction across the anterior-posterior axis in figure 6
Weaknesses:
(1) It is unclear if fresh and old saliva indeed alter the perceived imminence of predation, as claimed by the authors. Prior work indicates that lower imminence induces anxiety-related actions, such as re-organization of meal patterns and avoidance of open spaces, while slightly higher imminence produces freezing. Here, the authors show that fresh and old predator saliva only provoke different amounts of freezing, rather than changing the topography of defensive behaviors, as explained above. Another prediction of predatory imminence theory would be that lower imminence induced by old saliva should produce stronger cortical activation, while fresh saliva would activate amygdala, if these stimuli indeed correspond to significantly different levels of predation imminence.
(2) It is known that predator odors activate and require AOB, VNO and VMH, thus replications of these findings are not novel, decreasing the impact of this work.
(3) There is a lack of standard circuit dissection methods, such as characterizing the behavioral effects of increasing and decreasing neural activity of relevant cell bodies and axonal projections, significantly decreasing the mechanistic insights generated by this work
(4) The correlation shown in Figure 5c may be spurious. It appears that the correlation is primarily driven by a single point (the green square point near the bottom left corner). All correlations should be calculated using Spearman correlation, which is non-parametric and less likely to show a large correlation due to a small number of outliers. Regardless of the correlation method used, there are too few points in Figure 5c to establish a reliable correlation. Please add more points to 5c.
(5) Please cite recent relevant papers showing VMH activity induced by predators, such as https://pubmed.ncbi.nlm.nih.gov/33115925/ and https://pubmed.ncbi.nlm.nih.gov/36788059/
(6) Add complete statistical information in the figure legends of all figures, which should include n, name of test used and exact p values.
(7) Some of the findings are disconnected from the story. For example, the authors show V2R-A4-expressing cells are activated by predator odors. Are these cells more likely to be connected to the rest of the predatory defense circuit than other VNO cells?
(8) Please paste all figure legends directly below their corresponding figure to make the manuscript easier to read
(9) Were there other behavioral differences induced by fresh compared to old saliva? Do they provoke differences in stretch-attend risk evaluation postures, number of approaches, average distance to odor stimulus, velocity of movements towards and away the odor stimulus, etc?
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> This paper by Portela Catani et al examines the antigenic relationships (measured using monotypic ferret and mouse sera) across a panel of N2 genes from the past 14 years, along with the underlying sequence differences and phylogenetic relationships. This is a highly significant topic given the recent increased appreciation of the importance of NA as a vaccine target, and the relative lack of information about NA antigenic evolution compared with what is known about HA. Thus, these data will be of interest to those studying the antigenic evolution of influenza viruses. The methods used are generally quite sound, though there are a few addressable concerns that limit the confidence with which conclusions can be drawn from the data/analyses.
Strengths:<br /> -The significance of the work, and the (general) soundness of the methods.<br /> -Explicit comparison of results obtained with mouse and ferret sera
Weaknesses:<br /> - Approach for assessing influence of individual polymorphisms on antigenicity does not account for potential effects of epistasis (this point is acknowledged by the authors).<br /> - Machine learning analyses neither experimentally validated nor shown to be better than simple, phylogenetic-based inference.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This study studied the neural mechanisms underlying the shift of ocular dominance induced by "dichoptic-backward-movie" adaptation. The study is self-consistent.
Strengths:
The experimental design is solid and progressive (relationship among three studies), and all of the raised research questions were well answered.<br /> The logic behind the neural mechanisms is solid.<br /> The findings regarding the cTMS (especially the position/site can be useful for future medical implications).<br /> The updated Exp4 eliminates some concerns and thus makes the results even more solid.
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- Feb 2024
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
This manuscript reveals an important mechanism of KCNQ1/IKs channel gating such that the open state of the pore is unstable and undergoes intermittent closed and open conformations. PUFA enhances the maximum open probability of IKs by binding to a crevice adjacent to the pore and stabilizing the open conformation. This mechanism is supported by convincing single-channel recordings that show empty and open channel traces and the ratio of such traces is affected by PUFA. In addition, mutations of the pore residues alter PUFA effects, convincingly supporting that PUFA alters the interactions among these pore residues.
Strengths:<br /> The data are of high quality and the description is clear.
Weaknesses:<br /> Some comments about the presentation.
(1) The structural illustrations in this manuscript in general need to be more clarified.
(2) The manuscript heavily relies on the comparison between the S4-down and S4-up structures (Figures 3, 4, and 7) to illustrate the difference between the extracellular side of the pore and to lead to the hypothesis of open-state stability being affected by PUFA. This may mislead the readers to think that the closed conformation of the channel in the up-state is the same as that in the down-state.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> The authors demonstrate the activation of Polycystin-1 (PC1), a G-protein coupled receptor, using small peptides derived from its original agonist, the stalk TA protein. In the experimental part of the study, the authors performed cellular assays to check the peptide-induced reactivation of a mutant form of PC1 which does not contain the stalk agonist. The experimental data is supported by computational studies using state-of-the-art Gaussian accelerated Molecular Dynamics (GaMD) and bioinformatics analysis based on sequence covariance. The computer simulations revealed the mechanistic details of the binding of the said peptides with the mutant PC1 protein and discovered different bound, unbound, and intermediate conformations depending on the peptide size and sequence. The use of reliable and well-established molecular simulation algorithms and the physiological relevance of this protein autosomal dominant polycystic kidney disease (ADPKD) make this work particularly valuable.
Strengths:<br /> This work is exploratory and its goal is to establish that small peptides can be used to probe the PC1 signaling process. The authors have provided sufficient evidence to justify this claim. Their GaMD simulations have produced free-energy landscapes that differentiate the interaction of PC1 with three different synthetic peptides and demonstrate the associated conformational dynamics of the receptor protein. Their trajectory analysis and sequence covariance analysis could identify residue-specific interactions that facilitate this process.
Weaknesses:<br /> The following minor weaknesses should be taken into account by the reader when interpreting the results:
(1) No control has been used for the computational (GaMD) study as the authors only report the free energy surface for 3 highly agonistic peptides but for none of the other peptides that did not induce an agonistic effect. Therefore, in the current version, the reliability of the computational results is not foolproof.
(2) All discussions about the residue level interactions focused only on geometric aspects (distance, angle, etc) but not the thermodynamic aspect (e.g. residue-wise interaction energy). Considering they perform a biased simulation, the lack of interaction energy analysis only provides a qualitative picture of the mechanism.
(3) It is not mentioned clearly whether the reader should interpret the free energy landscapes quantitatively or qualitatively. Considering no error analysis or convergence plots are reported for the GaMD free energy surfaces, it may be assumed the results are qualitative. The readers should consider this caveat and not try to quantitatively reproduce these free energy landscapes with other comparable techniques.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
Jojoa-Cruz et al provide a new structure of At-OSCA3.1. The structure of OSCA 3.1 is similar to previous OSCA cryo-em structures of both OSCA3.1 and other homologues validating the new structure. Using the novel structure of OSCA3.1 as a guide they created several point mutations to investigate two different mechanosensitive modalities: poking and stretching. To investigate the ability of OSCA channels to gate in response to poking they created point mutations in OSCA1.2 to reduce sensitivity to poking based on the differences between the OSCA1.2 and 3.1 structures. Their results suggest that two separate regions are responsible for gating in response to poking and stretching.
Strengths:
Through a detailed structure based analysis, the authors identified structural differences between OSCA3.1 and OSCA1.2. The use of technically sound data supports the hypothesis that poking and stretching are sensed by two unique regions in the protein. These subtle structural changes between homologues identify regions in the amphipathic helix and near the pore that are essential for gating of OSCA1.2 in response to poking and stretching. Mutations in the AH of OSCA1.2 decrease the sensitivity to poking stimulus however these mutations have similar stretch activated currents to the WT. The point mutations described in the manuscript will set the foundation for investigations into how these two channels sense tension using different regions of structurally similar proteins.
Weaknesses:
Mutations in the amphipathic helix at W75 and L80 show reduced gating in response to poking stimuli. The gating observed occurs at poking depths similar to cellular rupture, the similarity in depths suggests that these mutations could be a complete loss of functions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In their manuscript, Schneider et al. aim to develop voyAGEr, a web-based tool that enables the exploration of gene expression changes over age in a tissue- and sex-specific manner. The authors achieved this goal by calculating the significance of gene expression alterations within a sliding window, using their unique algorithm, Shifting Age Range Pipeline for Linear Modelling (ShARP-LM), as well as tissue-level summaries that calculated the significance of the proportion of differentially expressed genes by the windows and calculated enrichments of pathways for showing biological relevance. Furthermore, the authors examined the enrichment of cell types, pathways, and diseases by defining the co-expressed gene modules in four selected tissues. Although their algorithm ShARP-LM has limited statistical power due to its calculation within a 16-year window, the voyAGEr was developed as a discovery tool, giving researchers easy access to the vast amount of transcriptome data from the GTEx project. Overall, the research design is unique and well-performed in simulating age-dependent changes in gene expression. The interesting results provide useful resources for the field of human genetics of aging.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> In this manuscript, entitled "Telomere length sensitive regulation of Interleukin Receptor 1 type 1 (IL1R1) by the shelterin protein TRF2 modulates immune signalling in the tumour microenvironment", Dr. Mukherjee and colleagues pointed out clarifying the extra-telomeric role of TRF2 in regulating IL1R1 expression with consequent impact on TAMs tumor-infiltration.
Strengths:<br /> Upon careful manuscript evaluation, I feel that the presented story is undoubtedly well conceived. At the technical level, experiments have been properly performed and the obtained results support the authors' conclusions.
Weaknesses:<br /> Unfortunately, the covered topic is not particularly novel. In detail, the TRF2 capability of binding extratelomeric foci in cells with short telomeres has been well demonstrated in a previous work published by the same research group. The capability of TRF2 to regulate gene expression is well-known, the capability of TRF2 to interact with p300 has been already demonstrated and, finally, the capability of TRF2 to regulate TAMs infiltration (that is the effective novelty of the manuscript) appears as an obvious consequence of IL1R1 modulation (this is probably due to the current manuscript organization).
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The work submitted by Dr. Jeong-Oh Shin and co-workers aims to investigate the therapeutic efficacy of rhPTH(1-34) and R25CPTH(1-34) on bone regeneration and osseointegration of titanium implants using a postmenopausal osteoporosis animal model.<br /> In my opinion the findings presented are not strongly supported by the provided data since the methods utilized do not allow to significantly support the primary claims.
Strengths:
Strengths include certain good technologies utilized to perform histological sections (i.e. the EXAKT system).
Weaknesses:
Certain weaknesses significantly lower the enthusiasm for this work. Most important: the limited number of samples/group. In fact, as presented, the work has an n=4 for each treatment group. This limited number of samples/group significantly impairs the statistical power of the study. In addition, the implants were surgically inserted following a "conventional implant surgery", implying that no precise/guided insertion was utilized. This weakness is, in my opinion, particularly significant since the amount of bone osteointegration may greatly depend on the bucco-lingual positioning of each implant at the time of the surgical insertion (which should, therefore, be precisely standardized across all animals and for all surgical procedures).<br /> On a minor note: not sure why the authors present a methodology to evaluate the dynamic bone formation (line 272) but do not present results (i.e. by means of histomorphometrical analyses) utilizing this methodology.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Chen et al. investigated how intermittent fasting causes metabolic benefits in obese mice and find that intestinal ILC3 and IL-22-IL-22R signaling contribute to the beiging of white adipose tissue (WAT) and consequent metabolic benefits including improved glucose and lipid metabolism in diet-induced obese mice. They demonstrate that intermittent fasting causes increased IL22+ILC3 in small intestines of mice. Adoptive transfer of purified intestinal ILC3 or administration of exogenous IL-22 can lead to increases in UCP1 gene expression and energy expenditure as well as improved glucose metabolism. Importantly, the above metabolic benefits caused by intermittent fasting are abolished in IL-22R-/- mice. Using an in vitro experiment, the authors show that ILC3-derived IL-22 may directly act on adipocytes to promote SVF beige differentiation. Finally, by performing sc-RNA-seq analysis of intestinal immune cells from mice with different treatments, the authors indicate a possible way of intestinal ILC3 being activated by intermittent fasting. Overall, this study provides a new mechanistic explanation for the metabolic benefits of intermittent fasting and reveals the role of intestinal ILC3 in the enhancement of the whole-body energy expenditure and glucose metabolism likely via IL-22-induced beige adipogenesis.
Although this study presents some interesting findings, particularly IL-22 derived from intestinal ILC3 could induce beiging of WAT by directly acting on adipocytes, the experimental data are not sufficient to support the key claims in the manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
In this manuscript, Lim and colleagues use an innovative CDRA chip platform to derive and mechanistically elucidate the molecular wiring of doxorubicin-resistant (DOXR) MDA-MB-231 cells. Given their enlarged morphology and polyploidy, they termed these cells as Large-DOXR (L-DORX). Through comparative functional omics, they deduce the NUPR1/HDAC11 axis to be essential in imparting doxorubicin resistance and, consequently, genetic or pharmacologic inhibition of the NUPR1 to restore sensitivity to the drug.
Strengths:
The study focuses on a major clinical problem of the eventual onset of resistance to chemotherapeutics in patients with triple-negative breast cancer (TNBC). They use an innovative chip-based platform to establish as well as molecularly characterize TNBC cells showing resistance to doxorubicin and uncover NUPR1 as a novel targetable driver of the resistant phenotype.
Weaknesses:
Critical weaknesses are the use of a single cell line model (i.e., MDA-MB-231) for all the phenotypic and functional experiments and absolutely no mechanistic insights into how NUPR1 functionally imparts resistance to doxorubicin. It is imperative that the authors demonstrate the broader relevance of NUPR1 in driving dox resistance using independent disease models.
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Reviewer #3 (Public Review):
Summary:<br /> The manuscript by Yujiro Umezaki and colleagues aims to describe how taste stimuli influence temperature preference in Drosophila. Under starvation flies display a strong preference for cooler temperatures than under fed conditions that can be reversed by refeeding, demonstrating the strong impact of metabolism on temperature preference. In their present study, Umezaki and colleagues observed that such changes in temperature preference are not solely triggered by the metabolic state of the animal but that gustatory circuits and peptidergic signalling play a pivotal role in gustation-evoked alteration in temperature preference.
The study of Umezaki is definitively interesting and the findings in this manuscript will be of interest to a broad readership.
Strengths:<br /> The authors demonstrate interesting new data on how taste input can influence temperature preference during starvation. They propose how gustatory pathways may work together with thermosensitive neurons, peptidergic neurons and finally try to bridge the gap between these neurons and clock genes. The study is very interesting and the data for each experiment alone are very convincing.
Weaknesses:<br /> In my opinion, the authors have opened many new questions but did not fully answer the initial question - how do taste-sensing neurons influence temperature preferences? What are the mechanisms underlying this observation? Instead of jumping from gustatory neurons to thermosensitive neurons to peptidergic neurons to clock genes, the authors should have stayed within the one question they were asking at the beginning. How does sugar sensing influence the physiology of thermos-sensation in order to change temperature preference? Before addressing all the following questions of the manuscript the authors should first directly decipher the neuronal interplay between these two types of neurons.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:<br /> The authors examined the effects of glutamate release from PMv LepR neurons in the regulation of puberty and reproduction in female mice.
Strengths:<br /> Multiple genetic mouse models were utilized to either manipulate PMv LepR neuron activities, or to delete glutamate vesicle transporters from LepR neurons. The authors have been quite rigorous in validating these models and exploring potential contaminations. Most of the data presented are solid and convincing and support the conclusion.
Weaknesses:<br /> Some results are hard to interpret.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
This work is carried out by the research group led by Shuiqiao Yuan, who has a long interest and significant contribution in the field of male germ cell development. The authors study a protein for which limited information existed prior to this work, a component of the E3 ubiquitin ligase complex, FBXO24. The authors generated the first FBXO24 KO mouse model reported in the literature using CRISPR, which they complement with HA-tagged FBXO24 transgenic model in the KO background. The authors begin their study with a very careful examination of the expression pattern of the FBXO24 gene at the level of mRNA and the HA-tagged transgene, and they provide conclusive evidence that the protein is expressed exclusively in the mouse testis and specifically in post-meiotic spermatids of stages VI to IX, which include early stages of spermatid elongation and nuclear condensation. The authors report a fully sterile phenotype for male mice, while female mice are normal. Interestingly, the testis size and the populations of spermatogenic cells in the KO mutant mice show small (but significant) reduction compared to the WT testis. Importantly, the mature sperm from KO animals show a series of defects that were very thoroughly documented in this work by scanning and transmission electron microscopy; this data constitutes a very strong point in this paper. FBXO24 KO sperm have severe defects in the mitochondrial sheath with missing mitochondria near the annulus, and missing outer dense fibers. Collectively these defects cause abnormal bending of the flagellum and severely reduced sperm motility. Moreover, defects in nuclear condensation are observed with faint nuclear staining of elongating and elongated spermatids, and reduction of protein levels of protamine 2 combined with increased levels of histones and transition protein 1. All the above are in line with the observed male sterility phenotype.
The authors also performed RNASeq in the KO animal, and found profound changes in the abundance of thousands of mRNAs; changes in mRNA splicing patterns were noted as well. This data reveals deeply affected gene expression patterns in the FBXO24 KO testis, which further supports the essential role that this factor serves in spermiogenesis. Unfortunately, a molecular explanation of what causes these changes is missing; it is still possible that they are an indirect consequence of the absence of FBXO24 and not directly caused by it.
The finding that Miwi protein levels are increased in the FBXO24 KO testis is an important point in this work, and it is in agreement with the observed increased size of the chromatoid body, where most of Miwi protein is accumulated in round spermatids. This finding is well supported with experiments performed in 293T cells showing that Miwi ubiquitination is FBXO24 dependent in this ectopic system. Moreover, the authors detect reduced ubiquitination of endogenous Miwi protein immunoprecipitated from FBXO24 KO testis. Consistent with an increase in Miwi protein levels, Miwi-sized piRNAs show increased abundance in total RNA from FBXO24 KO testis. It has been documented that Piwi proteins stabilize their piRNA cargo, so the increase in piRNA levels in 29-32 nt sizes is most likely not a result of altered biogenesis, but increased half-life of the piRNAs as a result of Miwi upregulation. piRNAs have been involved in the regulation of mRNAs in the post-meiotic spermatid, but it is unclear how increased Miwi protein and its piRNA cargo at the levels observed in this study contribute to the complete infertility phenotype of the FBXO24 KO male mice.
Therefore, a well-reasoned narrative on if and how the absence of FBXO24 as an E3 ubiquitin ligase is responsible for the observed mRNA and protein differential expression is largely absent. If FBXO24-mediated ubiquitination is required for normal protein degradation during spermiogenesis, protein level increase should be the direct consequence of genuine FBXO24 targets in the KO testis. Apart from Miwi, the possible involvement of ubiquitination was not shown for any other proteins that the authors found interact with FBXO24 such as splicing factors SRSF2, SRSF3, SRSF9, or any of the other proteins whose levels were found to be changed (reduced, thus the change in the KO is less likely due to absence of ubiquitination) such as ODF2, AKAP3, TSSK4, PHF7, TSSK6 and RNF8. Interestingly, the authors do observe increased amounts of histones and transition proteins, but reduced amounts of protamines, which directly shows that histone to protamine transition is indeed affected in the FBXO24 KO testis, consistent with the observed less condensed nuclei of spermatozoa. Could histones and transition proteins be targets of the proposed ubiquitin ligase activity of FBXO24, and in its absence, histone replacement is abrogated? Providing experimental evidence to address this possibility would greatly expand our understanding on why FBXO24 is essential during spermiogenesis.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
Summary:
The authors used a novel technique to treat male infertility. In a proof-of-concept study, the authors were able to rescue the phenotype of a knockout mouse model with immotile sperm using this technique. This could also be a promising treatment option for infertile men.
Strengths:
In their proof-of-concept study, the authors were able to show that the novel technique rescues the infertility phenotype in vivo.
Weaknesses:
Some minor weaknesses, especially in the discussion section, could be addressed to further improve the quality of the manuscript.
It is very convincing that the phenotype of Armc2 KO mice could (at least in part) be rescued by injection of Armc2 RNA. However, a central question remains about which testicular cell types have been targeted by the constructs. From the pictures presented in Figures 7 and 8, this issue is hard to assess. Given the more punctate staining of the DNA construct a targeting of Sertoli cells is more likely, whereas the more broader staining of seminiferous tubules using RNA constructs is talking toward germ cells.
Further, the staining for up to 119 days (Figure 5) would point toward an integration of the DNA construct into the genome of early germ cells such as spermatogonia and/or possibly to Sertoli cells. Given the expression after RNA transfection for up to 21 days (Figure 4) and the detection of motile sperm after 21 days (Figure 11), this would point to either round spermatids or spermatocytes.
These aspects need to be discussed more carefully (discussion section: lines 549-574).
It would also be very interesting to know in which testicular cell type Armc2 is endogenously expressed (lines 575-591).
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Reviewer #3 (Public Review):
Summary:<br /> This work uses tools and concepts from co-phylogenetic analyses to reconstruct the evolutionary and diversification history of coronaviruses in mammals. It concludes that cross-species transmissions from bats to humans are a relatively common event (compared to bats to other species). Across all mammals, the diversification history of coronaviruses suggests that there is potential for further evolutionary diversification.
Strengths:<br /> The article uses an interesting approach based on jointly looking at the extant network of coronaviruses-mammals interactions, and the phylogenetic history of both these organisms. The authors do an impressive job of explaining the challenges of reconstructing evolutionary dynamics for RNA viruses, and this helps readers appraise the relevance of their approach.
Weaknesses:<br /> I remain unconvinced by the argument that sampling does not introduce substantial biases in the analyses. As the authors highlight, incomplete knowledge of the extant interactions would lead to a biased reconstruction of the diversification history. In a recent paper (Poisot et al. 2023, Patterns), we look at sampling biases in the virome of mammals and suggest that is a fairly prominent issue, that is furthermore structured by taxonomy, space, and phylogenetic position. Case in point, even for betacoronaviruses, there have been many newly confirmed hosts in recent years. For organisms that have received less intense scrutiny, I think a thorough discussion of potential gaps in data would be required (see for example Cohen et al. 2022, Nat. Comms).
I was also surprised to see little discussion of the differences between alpha and beta coronaviruses - there is evidence that they may differ in their cross-species transmission (see Caraballo et al. 2022 Micr. Spectr.), which could call into question the relevance of treating all coronaviruses as a single, homogeneous group.
Some of the discussions in this paper also echo previous work by e.g. Geoghegan et al. (see 2017, PLOS Pathogens), which I was surprised to not see discussed, as it is a much earlier investigation of the relative frequencies of co-divergence and host switches for different viral families, with a deep discussion of how this may structure future evolutionary dynamics.
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Reviewer #3 (Public Review):
Summary:
This work describes a new pathway by which malaria parasites, P. falciparum, may regulate their growth and virulence (i.e. their expression of virulence-linked cytoadhesins). This is a topic of considerable interest in the field - does this important parasite sense factor(s) in its host bloodstream and regulate itself accordingly? Several fragments of evidence have come out on this topic in the past decade, showing, for example, reduced parasite growth under calorie restriction (in mice); parasite dormancy in response to amino acid starvation (in culture and in mice), and also reduced virulence in dry-season, low-parasitaemia infections in humans. The molecular mechanisms that may underlie this interesting biology remain only poorly understood.
Here, the authors show that dry-season P. falciparum parasites have reduced expression of Pol3-transcribed tRNAs and ncRNAs that positively regulate virulence gene expression. They link the level of Pol3 activity to PfMaf1, a remnant of the largely-absent nutrient-sensing TOR pathway in this parasite. They propose that in the dry season, human hosts may be calorie-restricted, leading to Maf1 moving to the nucleus and suppressing Pol3, thus downregulated growth and virulence of parasites. The evidence is intriguing and the idea is conceptually elegant.
Strengths:
The use of dry/wet-season field samples from The Gambia is a strength, showing potential real-world relevance. The generation of an inducible knockdown of Maf1 in lab-cultured parasites is also a strength, allowing this pathway to be studied somewhat in isolation.
Weaknesses:
(1) The signals upstream of Maf1 remain rather a black box. 4 are tested - heat shock and low-glucose, which seem to suppress ALL transcription; low-Isoleucine and high magnesium, which suppress Pol3. Therefore the authors use Mg supplementation throughout as a 'starvation type' stimulus. They do not discuss why they didn't use amino acid limitation, which could be more easily rationalised physiologically. It may be for experimental simplicity (no need for dropout media) but this should be discussed, and ideally, sample experiments with low-IsoLeu should be done too, to see if the responses (e.g. cytoadhesion) are all the same.
(2) The proteomics, conducted to seek partners of Maf1, is probably the weakest part. From Figure S3: the proteins highlighted in the text are clearly highly selected (as ones that might be relevant, e.g. phosphatases), but many others are more enriched. It would be good to see the whole list, and which GO terms actually came top in enrichment.
(3) Figure 3 shows the Maf1-low line has very poor growth after only 5 days but it is stated that no dead parasites are seen even after 8 cycles and the merozoites number is down only ~18 to 15... is this too small to account for such poor growth (~5-fold reduced in a single cycle, day 3-5)? It would additionally be interesting to see a cell-cycle length assessment and invasion assay, to see if Maf1-low parasites have further defects in growth.
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Reviewer #3 (Public Review):
Liang and colleagues set out to test whether the human brain uses distance and grid-like codes in social knowledge using a design where participants had to navigate in a two-dimensional social space based on competence and warmth during an fMRI scan. They showed that participants were able to navigate the social space and found distance-based codes as well as grid-like codes in various brain regions, and the grid-like code correlated with behavior (reaction times).
On the whole, the experiment is designed appropriately for testing for distant-based and grid-like codes, and is relatively well powered for this type of study, with a large amount of behavioral training per participant. They revealed that a number of brain regions correlated positively or negatively with distance in the social space, and found grid-like codes in the frontal polar cortex and posterior medial entorhinal cortex, the latter in line with prior findings on grid-like activity in entorhinal cortex. The current paper seems quite similar conceptually and in design to previous work, most notably Park et al., 2021, Nature Neuroscience.
(1) The authors claim that this study provides evidence that humans use a spatial / grid code for abstract knowledge like social knowledge.
This data does specifically not add anything new to this argument. As with almost all studies that test for a grid code in a similar "conceptual" space (not only the current study), the problem is that, when the space is not a uniform, square/circular space, and 2-dimensional then there is no reason the code will be perfectly grid like, i.e., show six-fold symmetry. In real world scenarios of social space (as well as navigation, semantic concepts), it must be higher dimensional - or at least more than two dimensional. It is unclear if this generalizes to larger spaces where not all part of the space is relevant. Modelling work from Tim Behrens' lab (e.g., Whittington et al., 2020) and Bradley Love's lab (e.g., Mok & Love, 2019) have shown/argued this to be the case. In experimental work, like in mazes from the Mosers' labs (e.g., Derdikman et al., 2009), or trapezoid environments from the O'Keefe lab (Krupic et al., 2015), there are distortions in mEC cells, and would not pass as grid cells in terms of the six-fold symmetry criterion.
The authors briefly discuss the limitations of this at the very end but do not really say how this speaks to the goal of their study and the claim that social space or knowledge is organized as a grid code and if it is in fact used in the brain in their study and beyond. This issue deserves to be discussed in more depth, possibly referring to prior work that addressed this, and raise the issue for future work to address the problem - or if the authors think it is a problem at all.
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Reviewer #3 (Public Review):
Summary:<br /> In this manuscript, Salazar-Lázaro et al. presented interesting data that C-terminal half of the Syx1 SNARE domain is responsible for clamping of spontaneous release, stabilizing RRP, and also Ca2+-evoked release. The authors routinely utilized the chimeric approach to replace the SNARE domain of Syx1 with its paralogue Syx2 and analyzed the neuronal activity through electrophysiology. The data are straightforward and fruitful. The conclusions are reasonable.
Strengths:<br /> The electrophysiology data that illustrate the important functions of Syx1 in clamping of spontaneous release, stabilizing RRP, and also Ca2+-evoked release were clear and convincing.
Weaknesses:<br /> One weakness is that the authors did not go deep into the underlying molecular mechanisms experimentally, either because of a variety of complicated possibilities or limited space of the manuscript.
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Reviewer #3 (Public Review):
Summary: The authors aim to solve how landscape context impacts the community BEF relationship. They found habitat loss and fragmentation per se have inconsistent effects on biodiversity and ecosystem function. And habitat loss rather than fragmentation per se can weaken the positive BEF relationship by decreasing the degree of habitat specialization of the community.
Strengths: The authors provide a good background, and they have a good grasp of habitat fragmentation and BEF literature.<br /> A major strength of this study is separating the impacts of habitat loss and fragmentation per se using the convincing design selection of landscapes with different combinations of habitat amount and fragmentation per se.<br /> Another strength is considering the role of specialists and generalists in shaping the BEF relationship.
Weaknesses:<br /> No<br /> In the revised manuscript, the authors have provided more detailed information about the ecological significance of these fragmentation indices. and also integrated two environmental factors related to water and temperature (soil water content and land surface temperature) into the data analysis to control their potential impact.
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Reviewer #3 (Public Review):
Summary:
Using a combination of approaches, including automated feature selection and hierarchical clustering, the author identified a set of genes persistently associated with extrachromosomal DNA (ecDNA) presence across cancer types. The authors further validated the gene set identified using gene ontology enrichment analysis and identified that upregulated genes in extrachromosomal DNA-containing tumors are enriched in biological processes like DNA damage and cell proliferation, whereas downregulated genes are enriched in immune response processes.
Comments for the previous version:
Major comments:
(1) The authors presented a solid comparative analysis of ecDNA-containing and ecDNA-free tumors. An established automated feature selection approach, Boruta, was used to select differentially expressed genes (DEG) in ecDNA(+) and ecDNA(-) TCGA tumor samples, and the iterative selection process and two-tier multiple hypothesis testing ensured the selection of reliable DEGs. The author showed that the DEG selected using Boruta has stronger predictive power than genes with top log-fold changes.
(2) The author performed a thorough interpretation of the findings with GO enrichment analysis of biological processes enriched in the identified DEG set and presented interesting findings, including the enrichment in DNA damage process among the genes upregulated in ecDNA(+) tumors.
(3) Overall, the authors achieved their aims with solid data mining and analysis approaches applied to public data tumor data sets.
(4) While it may not be the scope of this study, it will be interesting to at least have some justification for choosing Boruta over other feature selection methods, such as Recursive Feature Elimination (RFE) and backward stepwise selection.
(5) The authors showed that DESEQ-selected DEGs with top log-fold changes have less strong predictive power and speculated that this may be due to the fact that genes with top log-fold changes (LFC) are confined only to a small subset of samples. It will be interesting to select DEGs with top log-fold changes after first partitioning the tumor samples. For example, randomly partition the tumor samples, identify the DEGs with top LFC, combine the DEGs identified from each partition, then evaluate the predictive power of these DEGs against the Boruta-selected DEGs.
(6) While the authors showed that the presence of mutations was not able to classify ecDNA(+) and (-) tumor samples, it will be interesting to see if variant allele frequencies of the genes containing these mutations have predictive power.
Comments for the revised version:
The authors addressed the comments and recommendations with solid analysis and explanations in the revision. The added analysis using GLM is especially appreciated and provides convincing evidence for the predicting power of the Boruta-selected genes. The only comment is at this point is that it is recommended that the author provide some justification for choosing Boruta over other feature selection methods. It is not necessary to provide benchmarking results - justification based on the review of previous literature is sufficient, as it is not well explained in the paper why Boruta was chosen in the first place. Is it state-of-the-art? Has it demonstrated better performance in other settings? A few sentences answering these questions should suffice.
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Reviewer #3 (Public Review):
In this manuscript, the authors define the developmental trajectory resulting in a diverse mTEC compartment. Using a variety of approaches, including a novel CCL21-fate mapping model, data is presented to argue that embryonic CCL21-expressing thymocyte attracting mTECs naturally convert to into self-antigen displaying mTEC subsets, including Aire+ mTECs and thymic tuft cells. Perhaps somewhat surprisingly, a large fraction of cTECs were also marked for having expressed CCL21, suggesting that there exists some conversion of mTEC (progenitors) into cTEC, a developmentally interesting observation that could be followed up later. Overall, the experimental setup, writing, and conclusions, are all outstanding. The one question I have, which may be more of a curiosity of this reviewer than a requirement for the manuscript, is whether thymocytes themselves are required for the conversion/maturation of attracting TECs to mTECs? For example, in CD3e-/- (or Rag-/-) mice, are mTECs arrested at the thymocyte attracting stage, or is the conversion process 'pre-programed'? In the same vein, do cTECs (or the immature cTECs) maintain CCL21 expression in the absence of mature thymocytes? These are not critical studies but are fairly straightforward (effort- and time-wise) that would aid in placing this process in the overall scope of thymus development.
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Reviewer #3 (Public Review):
I very much like this approach and the idea of incorporating hypervariable markers. The method is intriguing, and the ability to e.g. estimate recombination rates, the size of DMRs, etc. is a really nice plus. I am not able to comment on the details of the statistical inference, but from what I can evaluate it seems reasonable and in principle the inclusion of highly mutable sties is a nice advance. This is an exciting new avenue for thinking about inference from genomic data. I remain a bit concerned about how well this will work in systems where much less is understood about methylation,
The authors include some good caveats about applying this approach to other systems, but I think it would be helpful to empiricists outside of thaliana or perhaps mammalian systems to be given some indication of what to watch out for. In maize, for example, there is a non-bimodal distribution of CG methlyation (35% of sites are greater than 10% and less than 90%) but this may well be due to mapping issues. The authors solve many of the issues I had concerns with by using gene body methylation, but this is only briefly mentioned on line 659. I'm assuming the authors' hope is that this method will be widely used, and I think it worth providing some guidance to workers who might do so but who are not as familiar with these kind of data.
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Reviewer #3 (Public Review):
Summary: The paper "Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction" reports the combination of prior knowledge signaling networks, multiparametric cell-based data on the activation status of 14 crucial proteins emblematic of the cell state downstream of FLT3 obtained under a variety of perturbation conditions and Boolean logic modeling, to gain mechanistic insight into drug resistance in acute myeloid leukemia patients carrying the internal tandem duplication in the FLT3 receptor tyrosine kinase and predict drug combinations that may reverse pharmacoresistant phenotypes. Interestingly, the utility of the approach was validated in vitro and using real-world data.
Strengths:
The model predictions have been validated in vitro and using external data.
This is a complex study, but readability is enhanced by the inclusion of a section that summarizes the study design, plus relevant figures. The availability of data as supplementary material and the availability of code in GitHub are also high points.
Weaknesses:
There are some apparent discrepancies between predicted and observed data that have been seemingly overlooked.
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Reviewer #3 (Public Review):
Summary:<br /> In this study, the authors collected a large set of data on root traits and root-associated microbes in the root endosphere and rhizosphere in order to integrate these important organisms in the root economics spectrum. By sampling a relatively large set of species from the subtropics along an elevation gradient, they tested whether microbial functions covary with root traits and root trait axes and if so, aimed to discuss what this could tell us about the (belowground) functioning of trees and forests.
Strengths:<br /> The strengths of this study lie mostly in the impressive dataset set the authors compiled: they sampled belowground properties of a relatively large number of tree species from an understudied region: i.e., the subtropics, where species-level root data are notoriously scarce. Secondly, their extensive sampling of associated microbes to integrate them in the root economics space is an important quality, because of the strong associations between roots and fungi and bacteria: soil microbes are directly related to root form (e.g., mycorrhizal fungi and root diameter and SRL), and function (e.g., taking up soil nutrients from various sources). Thirdly, the PCA figures (Figures 2 and 3) look very nice and intuitive and the paper is very well written.
Weaknesses:<br /> That said, this study also has several methodological weaknesses that make the results, and therefore the impact of this study difficult to evaluate and interpret.
(1) Design: The design of this study needs further explanation and justification in the Introduction and Methods sections in order to understand the ecological meaning of the results. Root traits and microbial community composition differ with their environment, and therefore (likely) also with elevation. Elevation is included in the redundancy analysis as a main effect, but without further environmental information, its impact is not ecologically meaningful. What is the rationale for including an elevation gradient in the design and as a main effect in the analyses? Do environmental conditions vary across altitudes and how, and if so, how would this impact the data?
What is the rationale behind sampling endosphere and rhizosphere microbial communities - why do both? And why also include pathogens - what are their expected roles in the RES? What do we know about this already? The introduction needs a more extensive literature review of these additional variables that are included in the analyses.
(2) Units of replication and analysis in the model: What are the units of replication and analyses, e.g., how many trees were sampled per species, how many species or trees per elevation, and how many plots per elevation? Were all 11 plots at different elevations and if so, which ones? The level of analysis for the redundancy analyses is not entirely clear: L. 404 mentions that the analyses were done 'across the rhizosphere and root tissue samples', but is that then at the individual-tree level? If so, it seems that these analyses should then also account for dependencies between trees from the same species and phylogeny (as (nested) covariates or random factors). With the information provided, I cannot tell whether there was sufficient replication for statistical interpretations.
(3) PCA: The results of the parallel analyses are not described: which components were retained? Because the authors aim to integrate microbial functions in a root economics space, I recommend first demonstrating the existence of a root economics space across the 52 subtropical species before running a PCA that includes the microbial traits. The PCA shown in this study does not exactly match the RES and this could be because traits of these species covary differently, but may also simply result from including additional traits to the PCA.
Also, the PCA's shown are carried out at the individual-tree level. I would recommend, however, including the species-level PCA's in the main text, because the individual-level PCA may not only reflect species-inherent ecological strategies (that e.g., the RES by Bergmann et al. 2020 describe) but also plasticity (Figures 2 and 3 both show an elevation effect that may be partly due to plasticity). While the results here are rather similar, intraspecific differences in root traits may follow different ecological principles and therefore not always be appropriate to compare with an interspecific RES (see for example Weemstra & Valverde-Barrantes, 2022, Annals of Botany).
I could not deduce whether tree species in the "fungal PCA" (Figure 2) were assigned as AM or EcM based on Table 1, or based on their observed fungal community composition. In the former case, the fungal functional guild gradient (from EcM to saprotrophs and AM) is partially an artificial one, because EcM tree species are not AM species (according to Table 1) and therefore, by definition, constitute a tradeoff or autocorrelation. And, as the authors also discuss, AM tree species may host EcM fungal species. Before I can evaluate the ecological meaning of PC1, and whether or not it really represents a mineral/organic nutrient gradient, information is needed on which data are used here.
I do not agree with the term 'gradient of bacterial guilds' (i.e., PC1 in Figure 3). All but 1 bacterial 'function' positively loaded on PC1 and 'fermentation' was only weakly negatively correlated with PC1. I do not think this constitutes a 'bacterial gradient'.
(4) Soil samples: Were they collected from the surrounding soil of each tree (L. 341), or from the root zone (L. 110). The former seems to refer to bulk soil samples, but the latter could be interpreted as rhizosphere soils. It is therefore not entirely clear whether these are the same soil samples, and if so, where they were sampled exactly.
Aims:<br /> The authors aimed to integrate endospheric and rhizospheric microbial and fungal community composition in the root economics space. Owing to statistical concerns (i.e., lacking parallel analysis results and the makeup of the PCs (AM versus EcM classification), I am not sure the authors succeeded in this. Besides that, the interpretation of the axes seems rather oversimplified and needs some consideration.
Root N is discussed as an important driver of fungal functional composition. Indeed, it was one of the significant variables in the redundancy models predicting microbial community composition, but its contribution to community composition was small (2 - 3 %), and the mechanistic interpretation was rather speculative. Specifically, the role of root N in root (and tree) functioning remains highly uncertain: the link with respiration and exudation is increasingly demonstrated but its actual meaning for nutrient uptake is not well understood (Freschet et al. 2021. New Phytologist). If and how root economics (represented by root N) and the fungal-driven nutrient economy (EcM versus AM, saprotrophs) can indeed be integrated into a unified framework (L. 223 - 224) seems a relevant question that is worth pursuing based on this paper, but in my opinion, this study does not clearly answer it, because the statistical analyses might need further work (or explanation) and underlying mechanisms are not well explained and supported by evidence.
In addition, the root morphology axis was indeed independent of the "fungal gradient", but this is in itself not an interesting finding. What is interesting, but not discussed is that, generally, AM species are expected to have thicker roots than EcM tree species (Gu et al. 2014 Tree Physiology; Kong et al. 2014 New Phytologist). I am therefore curious to see why this is not the case here? Did the few EcM species sampled just happen to have very thick roots? Or is there a phylogenetic effect that influences both mycorrhizal type and root thickness that is not accounted for here (Baylis, 1975; Guo et al., 2008 New Phytologist; Kubisch et al., 2015 Frontiers in Plant Science; Valverde-Barrantes et al., 2015 Functional Ecology; 2016 Plant and Soil)?
I also do not agree with the conclusion that this integrated framework 'explained' tree distributions along the elevation gradient. First of all, it is difficult to interpret because the elevation gradient is not well explained (e.g., in terms of environmental variation). Secondly, the framework might coincide with the framework, but the framework does not explain it: an environmental gradient probably underlies the elevation gradient that may be selected for species with certain root traits or mycorrhizal types, but this is not tested nor clearly demonstrated by the data. It thus remains rather speculative, and it should be more thoroughly explained based on the data observed. Similarly, I do not understand from this study how root traits like root N can influence the abundance of EcM and pathogenic fungi (L. 242 - 243). Which data show this causality? It seems a strong statement, but not well supported (or explained).
Impact:<br /> The data collected for this study are timely, valuable, and relevant. Soilborne microbes (fungi and bacteria; symbionts and pathogens) play important roles in root trait expressions (e.g., root diameter) and below-ground functioning (e.g., resource acquisition). They should therefore not be excluded from studies into the belowground functioning of forests, but they mostly are. This dataset therefore has the potential to improve our understanding of this subject. Making these data publicly available in large-scale datasets that have recently been initiated (e.g., FRED) will also allow further study in comparative (with other biomes) or global (across biomes) studies.
Technically, the methodology seems sound, although I lack the expertise to judge the Molecular Methods (L. 349 - 397). However, owing to some statistical uncertainties mentioned above (that the authors might well clarify or improve) and the oversimplified discussion, I am hesitant to determine the impact of the contents of this work. Statistical improvements and/or clearer explanation/justification of statistical choices made can make this manuscript highly interesting and impact, however.
Context:<br /> As motivated above, I am not sure to what extent the EcM - AM/saprotroph presents a true ecological tradeoff. However, if it does, this work would fit very well in the context of the mycorrhizal-associated nutrient economy (Phillips et al. 2013 New Phytology). This theory postulates that EcM trees generally produce low-quality litter (associated with 'slow traits') that can be more readily accessed by EcM but not AM fungi, thereby slowing down nutrient cycling rates at their competitive advantage, and vice versa for AM tree species. This study did not aim to test the MANE, so it was beyond its scope to study litter quality, and the number of EcM and AM species was unbalanced (8 EcM versus 44 AM species): nonetheless, the denser roots of EcM species and higher root N of AM species indicates that the MANE may also apply to this subtropical forest and may be an interesting impetus for future work on this topic. It might also offer one way to bridge the root economics space and the MANE.
What I also found interesting is the sparse observations of EcM fungal taxa in the root endosphere of species typically identified as AM hosts (L. 212 - 214). While their functionality remains to be tested (fungal structures in the endosphere were not studied here), this observation might call for renewed attention to classifying species as AM, EcM, or both.
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Reviewer #3 (Public Review):
This paper uses behavior and functional brain imaging to understand how neural and cognitive representations of visual and auditory stimuli change as participants learn associations among them. Prior work suggests that areas in the anterior temporal (ATL) and perirhinal cortex play an important role in learning/representing cross-modal associations, but the hypothesis has not been directly tested by evaluating behavior and functional imaging before and after learning cross-modal associations. The results show that such learning changes both the perceived similarities amongst stimuli and the neural responses generated within ATL and perirhinal regions, providing novel support for the view that cross-modal learning leads to a representational change in these regions.
This work has several strengths. It tackles an important question for current theories of object representation in the mind and brain in a novel and quite direct fashion, by studying how these representations change with cross-modal learning. As the authors note, little work has directly assessed representational change in ATL following such learning, despite the widespread view that ATL is critical for such representation. Indeed, such direct assessment poses several methodological challenges, which the authors have met with an ingenious experimental design. The experiment allows the authors to maintain tight control over both the familiarity and the perceived similarities amongst the shapes and sounds that comprise their stimuli so that the observed changes across sessions must reflect learned cross-modal associations among these. I especially appreciated the creation of physical objects that participants can explore and the approach to learning in which shapes and sounds are initially experienced independently and later in an associated fashion. In using multi-echo MRI to resolve signals in ventral ATL, the authors have minimized a key challenge facing much work in this area (namely the poor SNR yielded by standard acquisition sequences in ventral ATL). The use of both univariate and multivariate techniques was well-motivated and helpful in testing the central questions. The manuscript is, for the most part, clearly written, and nicely connects the current work to important questions in two literatures, specifically (1) the hypothesized role of the perirhinal cortex in representing/learning complex conjunctions of features and (2) the tension between purely embodied approaches to semantic representation vs the view that ATL regions encode important amodal/crossmodal structure.
There are some places in the manuscript that would benefit from further explanation and methodological detail. I also had some questions about the results themselves and what they signify about the roles of ATL and the perirhinal cortex in object representation.
A) I found the terms "features" and "objects" to be confusing as used throughout the manuscript, and sometimes inconsistent. I think by "features" the authors mean the shape and sound stimuli in their experiment. I think by "object" the authors usually mean the conjunction of a shape with a sound---for instance, when a shape and sound are simultaneously experienced in the scanner, or when the participant presses a button on the shape and hears the sound. The confusion comes partly because shapes are often described as being composed of features, not features in and of themselves. (The same is sometimes true of sounds). So when reading "features" I kept thinking the paper referred to the elements that went together to comprise a shape. It also comes from ambiguous use of the word object, which might refer to (a) the 3D-printed item that people play with, which is an object, or (b) a visually-presented shape (for instance, the localizer involved comparing an "object" to a "phase-scrambled" stimulus---here I assume "object" refers to an intact visual stimulus and not the joint presentation of visual and auditory items). I think the design, stimuli, and results would be easier for a naive reader to follow if the authors used the terms "unimodal representation" to refer to cases where only visual or auditory input is presented, and "cross-modal" or "conjoint" representation when both are present.
B) There are a few places where I wasn't sure what exactly was done, and where the methods lacked sufficient detail for another scientist to replicate what was done. Specifically:
(1) The behavioral study assessing perceptual similarity between visual and auditory stimuli was unclear. The procedure, stimuli, number of trials, etc, should be explained in sufficient detail in methods to allow replication. The results of the study should also minimally be reported in the supplementary information. Without an understanding of how these studies were carried out, it was very difficult to understand the observed pattern of behavioral change. For instance, I initially thought separate behavioral blocks were carried out for visual versus auditory stimuli, each presented in isolation; however, the effects contrast congruent and incongruent stimuli, which suggests these decisions must have been made for the conjoint presentation of both modalities. I'm still not sure how this worked. Additionally, the manuscript makes a brief mention that similarity judgments were made in the context of "all stimuli," but I didn't understand what that meant. Similarity ratings are hugely sensitive to the contrast set with which items appear, so clarity on these points is pretty important. A strength of the design is the contention that shape and sound stimuli were psychophysically matched, so it is important to show the reader how this was done and what the results were.
(2) The experiences through which participants learned/experienced the shapes and sounds were unclear. The methods mention that they had one minute to explore/palpate each shape and that these experiences were interleaved with other tasks, but it is not clear what the other tasks were, how many such exploration experiences occurred, or how long the total learning time was. The manuscript also mentions that participants learn the shape-sound associations with 100% accuracy but it isn't clear how that was assessed. These details are important partly b/c it seems like very minimal experience to change neural representations in the cortex.
(3) I didn't understand the similarity metric used in the multivariate imaging analyses. The manuscript mentions Z-scored Pearson's r, but I didn't know if this meant (a) many Pearson coefficients were computed and these were then Z-scored, so that 0 indicates a value equal to the mean Pearson correlation and 1 is equal to the standard deviation of the correlations, or (b) whether a Fisher Z transform was applied to each r (so that 0 means r was also around 0). From the interpretation of some results, I think the latter is the approach taken, but in general, it would be helpful to see, in Methods or Supplementary information, exactly how similarity scores were computed, and why that approach was adopted. This is particularly important since it is hard to understand the direction of some key effects.
C) From Figure 3D, the temporal pole mask appears to exclude the anterior fusiform cortex (or the ventral surface of the ATL generally). If so, this is a shame, since that appears to be the locus most important to cross-modal integration in the "hub and spokes" model of semantic representation in the brain. The observation in the paper that the perirhinal cortex seems initially biased toward visual structure while more superior ATL is biased toward auditory structure appears generally consistent with the "graded hub" view expressed, for instance, in our group's 2017 review paper (Lambon Ralph et al., Nature Reviews Neuroscience). The balance of visual- versus auditory-sensitivity in that work appears balanced in the anterior fusiform, just a little lateral to the anterior perirhinal cortex. It would be helpful to know if the same pattern is observed for this area specifically in the current dataset.
D) While most effects seem robust from the information presented, I'm not so sure about the analysis of the perirhinal cortex shown in Figure 5. This compares (I think) the neural similarity evoked by a unimodal stimulus ("feature") to that evoked by the same stimulus when paired with its congruent stimulus in the other modality ("object"). These similarities show an interaction with modality prior to cross-modal association, but no interaction afterward, leading the authors to suggest that the perirhinal cortex has become less biased toward visual structure following learning. But the plots in Figures 4a and b are shown against different scales on the y-axes, obscuring the fact that all of the similarities are smaller in the after-learning comparison. Since the perirhinal interaction was already the smallest effect in the pre-learning analysis, it isn't really surprising that it drops below significance when all the effects diminish in the second comparison. A more rigorous test would assess the reliability of the interaction of comparison (pre- or post-learning) with modality. The possibility that perirhinal representations become less "visual" following cross-modal learning is potentially important so a post hoc contrast of that kind would be helpful.
E) Is there a reason the authors did not look at representation and change in the hippocampus? As a rapid-learning, widely-connected feature-binding mechanism, and given the fairly minimal amount of learning experience, it seems like the hippocampus would be a key area of potential import for the cross-modal association. It also looks as though the hippocampus is implicated in the localizer scan (Figure 3c).
F) The direction of the neural effects was difficult to track and understand. I think the key observation is that TP and PRh both show changes related to cross-modal congruency - but still it would be helpful if the authors could articulate, perhaps via a schematic illustration, how they think representations in each key area are changing with the cross-modal association. Why does the temporal pole come to activate *less* for congruent than incongruent stimuli (Figure 3)? And why do TP responses grow less similar to one another for congruent relative to incongruent stimuli after learning (Figure 4)? Why are incongruent stimulus similarities *anticorrelated* in their perirhinal responses following cross-modal learning (Figure 6)?
This work represents a key step in our advancing understanding of object representations in the brain. The experimental design provides a useful template for studying neural change related to the cross-modal association that may prove useful to others in the field. Given the broad variety of open questions and potential alternative analyses, an open dataset from this study would also likely be a considerable contribution to the field.
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