- Apr 2024
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Reviewer #1 (Public Review):
Summary:
In this study, the authors generated a novel transgenic mouse line OpalinP2A-Flpo-T2A-tTA2 to specifically label mature oligodendrocytes, and at the same time their embryonic origins by crossing with a progenitor cre mouse line. With this clever approach, they found that LGE/CGE-derived OLs make minimum contributions to the neocortex, whereas MGE/POA-derived OLs make a small but lasting contribution to the cortex. These findings are contradictory to the current belief that LGE/CGE-derived OPCs make a sustained contribution to cortical OLs, whereas MGE/POA-derived OPCs are completely eliminated. Thus, this study provides a revised and more comprehensive view on the embryonic origins of cortical oligodendrocytes. To specifically label mature oligodendrocytes, and at the same time their embryonic origins by crossing with a progenitor cre mouse line. With this clever approach, they found that LGE/CGE-derived OLs make minimum contributions to the neocortex, whereas MGE/POA-derived OLs make a small-but-lasting contribution to to cortex. These findings are contradictory to the current belief that LGE/CGE-derived OPCs make a sustained contribution to cortical OLs, whereas MGE/POA-derived OPCs are completely eliminated. Thus, this study has provided a revised and updated view on the embryonic origins of cortical oligodendrocytes.
Strengths:
The authors have generated a novel transgenic mouse line to specifically label mature differentiated oligodendrocytes, which is very useful for tracing the final destiny of mature myelinating oligodendrocytes. Also, the authors carefully compared the distribution of three progenitor cre mouse lines and suggested that Gsh-cre also labeled dorsal OLs, contrary to the previous suggestion that it only marks LGE-derived OPCs. In addition, the author also analyzed the relative contributions of OLs derived from three distinct progenitor domains in other forebrain regions (e.g. Pir, ac). Finally, the new transgenic mouse lines and established multiple combinatorial genetic models will facilitate future investigations of the developmental origins of distinct OL populations and their functional and molecular heterogeneity.
Weaknesses:
Since OpalinP2A-Flpo-T2A-tTA2 only labels mature oligodendrocytes but not OPCs, the authors can not suggest that the lack of LGE/CGE-derived-OLs in the neocortex is less likely caused by competitive postnatal elimination, but more likely due to limited production and/or allocation (line 118-9). It remains possible that LGE/CGE-derived OPCs migrate into the cortex but are later eliminated.
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Reviewer #1 (Public Review):
This is an interesting, informative, and well-designed study that combines theoretical and experimental methodologies to tackle the phenomenon of higher-resolution structures/substructures in model biomolecular condensates. However, there is significant room for improvement in the presentation and interpretation of the results. As it stands, the precise definition of "frustration," which is a main theme of this manuscript (as emphasized in the title), is not sufficiently well articulated. This situation should be rectified to avoid "frustration" becoming a "catch-all" term without a clear perimeter of applicability rather than a precise, informative description of the physical state of affairs. There are also a few other concerns, e.g., regarding interpretation of correlation of phase-separation critical temperature and transfer free energy of amino acid residues as well as the difference between critical temperature and onset temperature, and the way the simulated configurations are similar to that of gyroids. Accordingly, the manuscript should be revised to address the following:
(1) It is accurately pointed out on p.4 that elastin-like polypeptides (ELPs) undergo heat-induced phase separation and therefore exhibit lower critical solution temperatures (LCSTs). But it is not entirely clear how this feature is reproduced by the authors' simulation. A relationship between simulated surface tension and "transition temperature" is provided in Fig.1C; but is the "transition temperature" (authors cited ref.41 by Urry) the same as critical temperature? Apparently, Urry's Tt is "critical onset temperature", the temperature when phase separation happens at a given polymer concentration. This is different from the (global) critical temperature LCST - though the two may be correlated-or not-depending on the shape of the phase boundary. Moreover, is the MOFF coarse-grained forcefield (first step in the multi-scale simulation), by itself, capable of reproducing heat-induced phase separation in a way similar to the forcefield of Dignon et al., ACS Cent Sci 5, 821-230 (2019)? Or, is this temperature-dependent effect appearing only subsequently, after the implementation of the MARTINI and/or all-atom steps? Clarification is needed. To afford a more informative context for the authors' introductory discussion, the aforementioned Dignon et al. work and the review by Cinar et al. [Chem Eur J 25, 13049-13069 (2019)], both touching upon the physical underpinning of the LCST feature of elastin, should also be cited along with refs.41-43.
(2) "Frustration" and "frustrated" are used prominently in the manuscript to characterize certain observed molecular configurations (11 times total, in both the title and in the abstract). Apparently, it is the most significant conceptual pronouncement of this work, hence its precise meaning is of central importance to the authors' thesis. Whereas one should recognize that the theoretical and experimental observations are striking without invocation of the "frustration" terminology, usage of the term can be useful if it offers a unifying conceptual framework. However, as it stands, a clear definition of the term "frustration" is lacking, leaving readers to wonder what molecular configurations are considered "frustrated" and what are not (i.e.,is the claim of observation of frustration falsifiable?). For instance, "frustrated microphase separation" appears in both the title and abstract. A logical question one may ask is: "Are all microphase separations frustrated"? If the answer is in the affirmative, does invocation of the term "frustration" add anything to our physical insight? If the answer is not in the affirmative, then how does one distinguish between microphase separations that are frustrated from those that are not frustrated? Presumably all simulated and experimental molecular configurations in the present study are those of lowest free energy for the given temperature. In other words, they are what they are. In the discussion about frustrated phase separation on p.13, for example, the authors appear to refer to the fact that chain connectivity is preventing hydrophobic residues to come together in a way to achieve the most favorable interactions as if there were no chain connectivity (one may imagine in that case all the hydrophobic residues will form a large cluster without microphase separation). Is this what the authors mean by "frustration"? If that's true, isn't that merely stating the obvious, at least for the observed microphase separation? In general, does "frustration" always mean deviation of actual, physical molecular configurations from certain imagined/hypothetical/reference molecular configurations, and therefore dependent upon the choice of the imagined reference configuration? If this is how the authors apply the term "frustration" in the present work, what is the zero-frustration reference state/configuration for microphase separation? And, similarly, what is the zero-frustration reference state/configuration when frustrated EPS-water interactions are discussed (~p.14-p.15, Fig.5)? How do non-frustrated water-protein interactions look like? Is the classic clathrate-like organization of water hydrogen bonds around small nonpolar solute "frustrated"?
(3) In the discussion about the correlation of various transfer free energy scales for amino acids and Urry's critical onset temperature (ref.41) on p.11 and Fig.4, is there any theoretical relationship to be expected between the interactions among amino acids of ELPs and their critical onset temperatures? While a certain correlation may be intuitively expected if the free energy scale "is working", is there any theoretical insight into the mathematical form of this relationship? A clarifying discussion is needed because it bears logically on whether the observed correlation or lack thereof for different transfer energy scales is a good indication of the adequacy of the energy scales in describing the actual physical interactions at play. This question requires some prior knowledge of the expected mathematical relationship between interaction parameters and onset temperature.
(4) To provide a more comprehensive context for the present study, it is useful to compare the microphase separation seen in the authors' simulation with the micelle-like structures observed in recent simulated condensed/aggregated states of hydrophobic-polar (HP) model sequences in Statt et al., J Chem Phys 152, 075101 (2020) [see esp. Fig.6] and Wessén et al., J Phys Chem B 126, 9222-9245 (2022) [see, e.g., Fig.10].
(5) "Gyroid-like morphology" is mentioned several times in the manuscript (p.4, p.8, p.17, Fig.S3). This is apparently an interesting observation but a clear explanation is lacking. A more detailed and specific discussion, perhaps with additional graphical presentations, should be provided to demonstrate why the simulated condensed-phase ELP configurations are similar to the classical description of gyroid as in, e.g., Terrones & Mackay, Chem Phys Lett 207, 45-50 (1993) and Lambert et al., Phil Trans R Soc A 354, 2009-2023 (1996).
Comments on the revised manuscript:
The authors have adequately addressed my previous concerns.
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Reviewer #1 (Public Review):
Most amino acids are stereoisomers in the L-enantiomer, but natural D-serine has also been detected in mammals and its levels shown to be connected to a number of different pathologies. Here, the authors convincingly show that D-serine is transported in the kidney by the neutral amino acid transporter ASCT2 and as a non-canonical substrate for the sodium-coupled monocarboxylate transporter SMCTs. Although both transport D-serine, this important study further shows in a mouse model for acute kidney injury that ASCT2 has the dominant role.
Strengths:
The paper combines proteomics, animal models, ex vivo transport analyses and in vitro transport assays using purified components. The exhaustive methods employed provide compelling evidence that both transporters can translocate D-serine in the kidney.
Weakness:
In the model for acute kidney injury the SMCTs proteins were not showing a significant change in expression levels and were rather analysed based on other, circumstantial evidence. Although its clear SMCTs can transport D-serine its physiological role is less obvious compared to ASCT2.
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Reviewer #1 (Public Review):
Summary:
LRRK2 protein is familially linked to Parkinson's disease by the presence of several gene variants that all confer a gain-of-function effect on LRRK2 kinase activity.
The authors examine the effects of BDNF stimulation in immortalized neuron-like cells, cultured mouse primary neurons, hIPSC-derived neurons, and synaptosome preparations from the brain. They examine an LRRK2 regulatory phosphorylation residue, LRRK2 binding relationships, and measures of synaptic structure and function.
Strengths:
The study addresses an important research question: how does a PD-linked protein interact with other proteins, and contribute to responses to a well-characterized neuronal signalling pathway involved in the regulation of synaptic function and cell health?
They employ a range of good models and techniques to fairly convincingly demonstrate that BDNF stimulation alters LRRK2 phosphorylation and binding to many proteins. Some effects of BDNF stimulation appear impaired in (some of the) LRRK2 knock-out scenarios (but not all). A phosphoproteomic analysis of PD mutant Knock-in mouse brain synaptosomes is included.
Weaknesses:
The data sets are disjointed, conclusions are sweeping, and not always in line with what the data is showing. Validation of 'omics' data is very light. Some inconsistencies with the major conclusions are ignored. Several of the assays employed (western blotting especially) are likely underpowered, findings key to their interpretation are addressed in only one or other of the several models employed, and supporting observations are lacking.
As examples to aid reader interpretation:
(a) pS935 LRRK2 seems to go up at 5 minutes but goes down below pre-stimulation levels after (at times when BDNF-induced phosphorylation of other known targets remains very high). This is ignored in favour of discussion/investigation of initial increases, and the fact that BDNF does many things (which might indirectly contribute to initial but unsustained changes to pLRRK2) is not addressed.
(b) Drebrin coIP itself looks like a very strong result, as does the increase after BDNF, but this was only demonstrated with a GFP over-expression construct despite several mouse and neuron models being employed elsewhere and available for copIP of endogenous LRRK2. Also, the coIP is only demonstrated in one direction. Similarly, the decrease in drebrin levels in mice is not assessed in the other model systems, coIP wasn't done, and mRNA transcripts are not quantified (even though others were). Drebrin phosphorylation state is not examined.
(c) The large differences in the CRISPR KO cells in terms of BDNF responses are not seen in the primary neurons of KO mice, suggesting that other differences between the two might be responsible, rather than the lack of LRRK2 protein.
(d) No validation of hits in the G2019S mutant phosphoproteomics, and no other assays related to the rest of the paper/conclusions. Drebrin phosphorylation is different but unvalidated, or related to previous data sets beyond some discussion. The fact that LRRK2 binding occurs, and increases with BDNF stimulation, should be compared to its phosphorylation status and the effects of the G2019S mutation.
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Reviewer #1 (Public Review):
Amason et al. investigated the formation of granulomas in response to Chromobacterium violaceum infection, aiming to uncover the cellular mechanisms governing the granuloma response. They identify spatiotemporal gene expression of chemokines and receptors associated with the formation and clearance of granulomas, with a specific focus on those involved in immune trafficking. By analyzing the presence or absence of chemokine/receptor RNA expression, they infer the importance of immune cells in resolving infection. Despite observing increased expression of neutrophil-recruiting chemokines, treatment with reparixin (an inhibitor of CXCR1 and CXCR2) did not inhibit neutrophil recruitment during infection. Focusing on monocyte trafficking, they found that CCR2 knockout mice infected with C. violaceum were unable to form granulomas, ultimately succumbing to infection.
The spatial transcriptomics data presented in the figures could be considered a valuable resource if shared, with the potential for improved and clarified analyses. The primary conclusion of the paper, that C. violaceum infection in the liver cannot be contained without macrophages, would benefit from clarification.
While the spatial transcriptomic data generated in the figures are interesting and valuable, they could benefit from additional information. The manual selection of regions of granulomas for analysis could use additional context - was the rest of the liver not sequenced, or excluded for other reasons? Including a healthy liver in the analysis could serve as a control for any lasting effects at the final time point of 21 days. Providing more context for the scalebars throughout the spatial analyses, such as whether the data are raw counts or normalized based on the number of reads per spatial spot, would be helpful for interpretation, as changes in expression could signal changes in the numbers of cells or changes in the gene expression of cells.
In Figure 4, qualitative measurements are valuable, but having an idea of the raw data for a few of the pursued chemokines/receptors would aid interpretation. It would also be beneficial to clarify whether the reported values are across all clusters and consider focusing on clusters with the greatest change in expression. Figures 5E and F would benefit from clarification regarding the x-axis units and whether the expression levels are summed across all clusters for each time point. Additionally, information on the sequencing depth of the samples would be helpful, particularly as shallow sequencing of RNA can result in poor capture of low-expression transcripts.
Regarding the conclusion of the essentiality of macrophages in granuloma formation, it may be prudent to further investigate the role of macrophages versus CCR2. Analyzing total cell counts in the liver after infection could provide insight into whether the decrease in the fraction of macrophages is due to decreased numbers or infiltration of other cell types. Consideration of experiments deleting macrophages directly, instead of CCR2, could provide more definitive evidence of the necessity of macrophage migration in containing infections.
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Reviewer #1 (Public Review):
Pineda et al investigate the association of the hypothesis that Dux4, an embryonic transcription factor, expression in tumor cells is associated with immune evasion and resistance to immunotherapy. They analyze existing cohorts of bulk RNAseq sequenced tumors across cancer types to identify Dux4 expression and association with survival. They find that Dux4 expression is detected in a higher proportion of metastatic tumors compared to primary tumors, is associated with decreased immune infiltrate and a variety of immune metrics and previously nominated immune signatures, and do an in depth evaluation of a cohort of metastatic urothelial cell carcinoma, finding that Dux4 expression is associated with a more immunodeficient tumor microenvironment (desert or excluded microenvironment) and worse survival in this aPDL1 treated cohort. They then find that Dux4 expression is a major independent predictor of survival in this cohort using different types of survival analyses (KM, Cox PH, and random survival forests). With prior existing biological data supporting the hypothesis (in prior work, the senior author has demonstrated Dux4 expression causally suppresses MHC-I expression in interferon-gamma treated cell lines), the current work links Dux4 expression with less immune activity in clinical tumor samples and with survival in ICI treated urothelial carcinomas, and demonstrates that Dux4 expression provides independent information towards survival including other molecular and clinical characteristics (TMB, ECOG PS as the other strongest markers), and provides interesting resolution on landmark analyses with TMB and Dux4 expression providing greater informativeness at later survival landmarks (e.g. 1 year and later), while ECOG PS has strong informativeness already at earlier time points. This work provides impetus towards more mechanistic and functional dissection of the mechanism of Dux4-associated changes with the tumor microenvironment (e.g. in vivo mouse studies) as well as potential interventional studies (e.g. Dux4 as a target in combination therapies). What the work does not provide is additional resolution on the mechanism of how Dux4 may be associated with a more immunodeficient microenvironment.
The conclusions are generally well supported, but there are issues that would benefit from clarification and extension:
- The finding that Dux4 expression is detected in a higher proportion of metastatic tumors and at higher levels compared to TCGA samples (Fig 1BC) is striking. However, at least for one tumor type (melanoma), the TCGA cohort is comprised of mostly locoregional metastatic (n=81 primary and 367 metastatic tumors in the PanCan Atlas). Since there are annotations for primary and (locoregional) metastatic samples in TCGA, an analysis of the primary vs. locoregional metastasis vs distant metastatic samples seems reasonable and likely informative. The analysis of tumors with matched FFPE and flash frozen samples with hybrid probe capture and polyA sequencing, respectively is a nice validation to show that the difference in Dux4 expression is not due to differences in preservation of starting material/sequencing in the metastatic samples vs TCGA samples (S1BC).<br /> - The findings that Dux4 expression in the metastatic urothelial carcinoma setting is associated with a more immunodeficient microenvironment (Figure 2) is clear and unambiguous using multiple lines of data and analyses (bulk RNAseq, DUX4-positive vs DUX4-negative tumors, different immune cell and cytokine signatures; IHC showing an association with immune deserts and immune excluded phenotypes). However, this is an association and does not demonstrate causality.<br /> - The survival analyses (Fig 3,4,5) show fairly convincingly that Dux4 provide independent predictive information beyond clinical variables and TMB towards survival in the aPDL1 treated metastatic urothelial carcinoma cohort. However, the choice to split the cohort into Dux4 negative (defined as < 0.25 TPM) and Dux4 positive (> 1 TPM) while excluding a large number of patients (n=126 pts) that fall in between has significant impact on the rigor of conclusions. This would benefit from showing all the data (e.g. including the 3rd group of in-betweens in the survival analyses as a separate group).<br /> - The authors demonstrate that adding Dux4 to clinical markers and TMB results in an improved predictive model for survival, but there are a few questions regarding this model as a clinical biomarker<br /> o Is Dux4 expression better than other correlated immune signatures/markers (e.g. interferon gamma, T effector signature, overall immune infiltrate) in providing additional information?<br /> - The use of random survival forests to quantify the (predictive) marginal effect of Dux4+ vs Dux4- expression on survival in a non-parametric model as well as shed light on association with survival at different landmark times using Shapley values is quite interesting and well conducted.
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Reviewer #1 (Public Review):
The authors have made a novel and important effort to distinguish and include different sources of active deformations for fitting C elegans embryo development: cyclic muscle contractions and actomyosion circumferential stresses. The combination and synchronisation of both contributions are, according to the model, responsible for different elongation rates, and can induce bending and torsion deformations, which are a priori not expected from purely contractile forces. The model can be applied to other growth processes in initially cylindrical shapes.
The tilt of the fibers is an important assumption of the model. However, fiber direction in Figure 3B is not fully clear for explaining the tilting. The fiber in 3B has not very much in common with the fibers in the color part of the figure. Also, is vector m supposed to be tangent to the fiber? In the figure does not seem to be so. It should be expected that alpha is a consequence of the deformation, not as an input parameter, as it seems in the tests of Figure 6A. How is the value of alpha chosen? According to Figure 6, torsion is expected for alpha>0, but for beta=pi/2 and alpha>0 no torsion may be obtained. In fact, it seems that torsion should appear when cos(beta)*sin(alpha)>0. As a consequence, value of beta should be given in Figure 6. Can the amount of torsion be tested as a function of alpha and beta?
The transfer of energy and deformation is a very interesting aspect of the paper, and also crucial for the model and predicting elongation. However, the modelling of this transfer remains very obscure and only explained in the Appendix. Some more details on how the transfer is selected should be given in the main text. Can the transfer of energy interpreted as a change of the relaxed reference configuration? Once a ratio of the energy transferred is fixed, the assumption on elongation distribution should be stated. (Uniformly? ) The authors should also define in the main text the factor g_a1, and explain how this value is computed from condition W_c=W_r .
Given the convoluted shape of the embryo in the egg, contact may be a crucial mechanism for determining growth and torsion. The model does not include this contact, and this limitation should be reflected in the article.
Minor comment:<br /> -Line 300: "we determine the optimal values for the activation parameters". the optimal with respect to which objective? Norm of difference between experimental and computational displacements? How this is quantified needs to be specified.
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Reviewer #1 (Public Review):
Summary:
This study presents careful biochemical experiments to understand the relationship between LRRK2 GTP hydrolysis parameters and LRRK2 kinase activity. The authors report that incubation of LRRK2 with ATP increases the KM for GTP and decreases the kcat. From this they suppose an autophosphorylation process is responsible for enzyme inhibition. LRRK2 T1343A showed no change, consistent with it needing to be phosphorylated to explain the changes in G-domain properties. The authors propose that phosphorylation of T1343 inhibits kinase activity and influences monomer-dimer transitions.
Strengths:
Strengths of the work are the very careful biochemical analyses and interesting result for wild type LRRK2.
Weaknesses:
The conclusions related to involvement of a monomer-dimer transition are to this reviewer, premature and an independent method needs to be utilized to bolster this aspect of the story.
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Reviewer #1 (Public Review):
The author studies a family of models for heritable epigenetic information, with a focus on enumerating and classifying different possible architectures. The key aspects of the paper are:
- Enumerate all 'heritable' architectures for up-to 4 constituents.<br /> - A study of whether permanent ("genetic") or transient ("epigenetic") perturbations lead to heritable changes<br /> - Enumerated the connectivity of the "sequence space" formed by these heritable architectures<br /> - Incorporating stochasticity, the authors explore stability to noise (transient perturbations)<br /> - A connection is made with experimental results on C elegans.
The study is timely, as there is a renewed interest in the last decade in non-genetic, heritable heterogeneity (e.g., from single-cell transcriptomics). Consequently, there is a need for a theoretical understanding of the constraints on such systems. There are some excellent aspects of this study: for instance, the attention paid to how one architecture "mutates" into another. Unfortunately, the manuscript as a whole does not succeed in formalising nor addressing any particular open questions in the field. Aside from issues in presentation and modelling choices (detailed below), it would benefit greatly from a more systematic approach rather than the vignettes presented.
## Terminology
The author introduces a terminology for networks of interacting species in terms of "entities" and "sensors" -- the former being nodes of a graph, and the latter being those nodes that receive inputs from other nodes. In the language of directed graphs, "entities" would seem to correspond to vertices, and "sensors" those vertices with positive indegree and outdegree. Unfortunately, the added benefit of redefining accepted terminology from the study of graphs and networks is not clear.
## Model
The model seems to suddenly change from Figure 4 onwards. While the results presented here have at least some attempt at classification or statistical rigour (i.e. Fig 4 D), there are suddenly three values associated with each entity ("property step, active fraction, and number"). Furthermore, the system suddenly appears to be stochastic. The reader is left unsure what has happened, especially after having made the effort to deduce the model as it was in Figs 1 through 3. No respite is to be found in the SI, either, where this new stochastic model should have been described in sufficient detail to allow one to reproduce the simulation.
## Perturbations
Inspired especially by experimental manipulations such as RNAi or mutagenesis, the author studies whether such perturbations can lead to a heritable change in network output. While this is naturally the case for permanent changes (such as mutagenesis), the author gives convincing examples of cases in which transient perturbations lead to heritable changes. Presumably, this is due the the underlying multistability of many networks, in which a perturbation can pop the system from one attractor to another.
Unfortunately, there appears to be no attempt at a systematic study of outcomes, nor a classification of when a particular behaviour is to be expected. Instead, there is a long and difficult-to-read description of numerical results that appear to have been sampled at random (in terms of both the architecture and parameter regime chosen). The main result here appears to be that "genetic" (permanent) and "epigenetic" (transient) perturbations can differ from each other -- and that architectures that share a response to genetic perturbation need not behave the same under an epigenetic one. This is neither surprising (in which case even illustrative evidence would have sufficed) nor is it explored with statistical or combinatorial rigour (e.g. how easy is it to mistake one architecture for another? What fraction share a response to a particular perturbation?)
As an additional comment, many of the results here are presented as depending on the topology of the network. However, each network is specified by many kinetic constants, and there is no attempt to consider the robustness of results to changes in parameters.
## DNA analogy
At two points, the author makes a comparison between genetic information (i.e. DNA) and epigenetic information as determined by these heritable regulatory architectures. The two claims the author makes are that (i) heritable architectures are capable of transmitting "more heritable information" than genetic sequences, and (ii) that, unlike DNA, the connectivity (in the sense of mutations) between heritable architectures is sparse and uneven (i.e. some architectures are better connected than others).
In both cases, the claim is somewhat tenuous -- in essence, it seems an unfair comparison to consider the basic epigenetic unit to be an "entity" (e.g., an entire transcription factor gene product, or an organelle), while the basic genetic unit is taken to be a single base-pair. The situation is somewhat different if the relevant comparison was the typical size of a gene (e.g., 1 kb).
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Reviewer #1 (Public Review):
Summary:
This describes the molecular identity of the intermediate status of cranial neural crest cells (NCCs) during the initial delamination process. Taking advantage of single-cell RNA seq, the authors identify new populations of cells during EMT characterized by a specific set of gene expressions, including Dlc1. Promigratory cranial NCCs differentiate through different trajectories depending on their cell cycle phases but converge into a common progenitor, then differentiate into mesenchymal cells expressing region-specific genes.
Strengths:
Single-cell RNA seq data convincingly support what the authors claim. This is the first time to identify intermediate states between premigratory and migratory cranial NCCs. Silencing one of the marker genes, Dlc1, reduces the migratory activity of cranial NCCs. These findings deepen our understanding of the mechanism of EMT in general.
Comments on revised version:
Weaknesses:
None after substantial revision.
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Reviewer #1 (Public Review):
In this manuscript, the authors report a molecular mechanism for recruiting syntaxin 17 (Syn17) to the closed autophagosomes through the charge interaction between enriched PI4P and the C-terminal region of Syn17. How to precisely control the location and conformation of proteins is critical for maintaining autophagic flux. Particularly, the recruitment of Syn17 to autophagosomes remains unclear. In this paper, the author describes a simple lipid-protein interaction model beyond previous studies focusing on protein-protein interactions. This represents conceptual advances.
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Reviewer #1 (Public Review):
Li et al report that upon traumatic brain injury (TBI), Pvr signalling in astrocytes activates the JNK pathway and up-regulates the expression of the well-known JNK target MMP1. The FACS sort astrocytes, and carry out RNAseq analysis, which identifies pvr as well as genes of the JNK pathway as particularly up-regulated after TBI. They use conventional genetics loss of function, gain of function and epistasis analysis with and without TBI to verify the involvement of the JNK-MMP1 signalling pathway downstream of PVR. They also show that blocking endocytosis prolongs the involvement of this pathway in the TBI response.
The strengths are that multiple experiments are used to demonstrate that TBI in their hands damaged the BBB, induced apoptosis and increased MMP1 levels. The RNAseq analysis on FACS sorted astrocytes is nice and will be valuable to scientists beyond the confines of this paper. The functional genetic analysis is conventional, yet sound, and supports claims of JNK and MMP1 functioning downstream of Pvr in the TBI context.
For this revised version the authors have removed all the unsupported claims. This renders their remaining claims more solid. However, it has resulted in the loss of important cellular aspects of the response to TBI, limiting the scope and value of the work.
The main weakness is that novelty and insight are both rather limited. Others had previously published that both JNK signalling and MMP1 were activated upon injury, in multiple contexts (as well as the articles cited by the authors, they should also see Losada-Perez et al 2021). That Pvr can regulate JNK signalling was also known (Ishimaru et al 2004). The authors claim that the novelty was investigating injury responses in astrocytes in Drosophila. However, others had investigated injury responses by astrocytes in Drosophila before. It had been previously shown that astrocytes - defined as the Prospero+ neuropile glia, and also sharing evolutionary features with mammalian NG2 glia - respond to injury both in larval ventral nerve cords and in adult brains, where they proliferate regenerating glia and induce a neurogenic response (Kato et al 2011; Losada-Perez et al 2016; Harrison et al 2021; Simoes et al 2022). The authors argue that the novelty of the work is the investigation of the response of astrocytes to TBI. However, this is of somewhat limited scope. The authors mention that MMP1 regulates tissue remodelling, the inflammatory process and cancer. Exploring these functions further would have been an interesting addition, but the authors did not investigate what consequences the up-regulation of MMP1 after injury has in repair or regeneration processes.
The statistical analysis is incorrect in places, and this could affect the validity of some claims.
Altogether, this is an interesting and valuable addition to the repertoire of articles investigating neuron-glia communication and glial responses to injury in the Drosophila central nervous system (CNS). It is good and important to see this research area in Drosophila grow. This community together is building a compelling case for using Drosophila and its unparalleled powerful genetics to investigate nervous system injury, regeneration and repair, with important implications. Thus, this paper will be of interest to scientists investigating injury responses in the CNS using Drosophila, other model organisms (eg mice, fish) and humans.
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Reviewer #1 (Public Review):
Dasguta et al. have dissected the role of Sema7a in fine tuning of a sensory microcircuit in the posterior lateral line organ of zebrafish. They attempt to also outline the different roles of a secreted verses membrane-bound form of Sema7a in this process. Using genetic perturbations and axonal network analysis, the authors show that loss of both Sema7a isoforms causes abnormal axon terminal structure with more bare terminals and fewer loops in contact with presynaptic sensory hair cells. Further, they show that loss of Sema7a causes decreased number and size of both the pre- and post-synapse. Finally, they show that overexpression of the secreted form of Sema7a specifically can elicit axon terminal outgrowth to an ectopic Sema7a expressing cell. Together, the analysis of Sema7a loss of function and overexpression on axon arbor structure is fairly thorough and revealed a novel role for Sema7a in axon terminal structure. However, the connection between different isoforms of Sema7a and the axon arborization needs to be substantiated. Furthermore, the effect of loss of Sema7a on the presynaptic cell is not ruled out as a contributing factor to the synaptic and axon structure phenotypes. These issues weaken the claims made by the authors including the statement that they have identified dual roles for the GPI-anchored verses secreted forms of Sema7a on synapse formation and as a chemoattractant for axon arborization respectively.
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Reviewer #1 (Public Review):
Summary:
Through an unbiased genomewide KO screen, the authors identified loss of DBT to suppress MG132-mediated death of cultured RPE cells. Further analyses suggested that DBT reduces ubiquitinated proteins by promoting autophagy. Mechanistic studies indicated that DBT loss promotes autophagy via AMPK and its downstream ULK and mTOR signaling. Furthermore, loss of DBT suppresses polyglutamine- or TDP-43-mediated cytotoxicity and/or neurodegeneration in fly models. Finally, the authors showed that DBT proteins are increased in ALS patient tissues, compared to non-neurological controls.
Strengths:
The idea is novel, the evidence is convincing, and the data are clean. The findings have implications for human diseases.
Weaknesses:
None.
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Reviewer #1 (Public Review):
Summary:
In this study, the authors distinguished afferent inputs to different cell populations in the VTA using dimensionality reduction approaches and found significantly distinct patterns between normal and drug treatment conditions. They also demonstrated negative correlations of the inputs induced by drugs with gene expression of ion channels or proteins involved in synaptic transmission and demonstrated the knockdown of one of the voltage-gated calcium ion channels caused decreased inputs.
Weaknesses:
(1) For quantifications of brain regions in this study, boundaries were based on the Franklin-Paxinos (FP) atlas according to previous studies (Beier KT et al 2015, Beier KT et al 2019). It has been reported significant discrepancies exist between the anatomical labels on the FP atlas and the Allen Brain Atlas (ref: Chon U et al., Nat Commun 2019). Although a summary of conversion is provided as a sheet, the authors need to describe how consistent or different the brain boundaries they defined in the manuscript with Allen Brain Atlas by adding histology images. Also, I wonder how reliable the annotations were for over a hundred of animals with manual quantification. The authors should briefly explain it rather than citing previous studies in the Material and Methods Section.
(2) Regarding the ellipsoids in the PC, although it's written in the manuscript that "Ellipsoids were centered at the average coordinate of a condition and stretched one standard deviation along the primary and secondary axes", it's intuitively hard to understand in some figures such as Figure 2O, P and Figure S1. The authors need to make their data analysis methods more accessible by providing source code to the public.
(3) In histology images (Figure 1B and 3K), the authors need to add dashed lines or arrows to guide the reader's attention.
(4) In Figure 2A and G, apparently there are significant differences in other brain regions such as NAcMed or PBN. If they are also statistically significant, the authors should note them as well and draw asterisks(*).
(5) In Figure 2N about the spatial distribution of starter cells, the authors need to add histology images for each experimental condition (i.e. saline, fluoxetine, cocaine, methamphetamine, amphetamine, nicotine, and morphine) as supplement figures.
(6) In the manuscript, it is necessary to explain why Cacna1e was selected among other calcium ion channels.
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Reviewer #2 (Public Review):
The authors analysed functional MRI recordings of brain activity at rest, using state-of-the-art methods that reveal the diverse ways in which the information can be integrated in the brain. In this way, they found brain areas that act as (synergistic) gateways for the 'global workspace', where conscious access to information or cognition would occur, and brain areas that serve as (redundant) broadcasters from the global workspace to the rest of the brain. The results are compelling and consisting with the already assumed role of several networks and areas within the Global Neuronal Workspace framework. Thus, in a way, this work comes to stress the role of synergy and redundancy as complementary information processing modes, which fulfill different roles in the big context of information integration.<br /> In addition, to prove that the identified high-order interactions are relevant to the phenomenon of consciousness, the same analysis was performed in subjects under anesthesia or with disorders of consciousness (DOC), showing that indeed the loss of consciousness is associated with a deficient integration of information within the gateway regions.
However, there is still a standing issue that could be the basis for an improved analysis: the concepts of gateways and broadcasters allude to a directionality in the information flow. In fact, Figure 1 depicts Stage (i) and Stage (iii) as one-way processes. However, the identification of gateway and broadcaster regions relies on matrices that are symmetrical, i.e. they are not directed. Would it be possible to assess the gateway or broadcaster nature of a region taking into account the directionality of the information flow? In other words, if region X is a gateway, I would expect a synergistic relationship between the past of X,Y and present of Y (Y not being a gateway) towards the present of X; but not necessarily the other way around (i.e. the present of Y being less dependent on the past/present of X). A similar reasoning can be made for broadcasters.
Although regional differences in haemodynamics complicate attempts to map directed information flow from fMRI recordings, perhaps the IID framework could be leveraged to extract directed data (i.e., there are many atoms that are explicitly directed). As an avenue for future research, it would be interesting to discuss the feasibility or limitations of such analysis.
Also, there is something confusing in Figure 4B-C and its description. Awake should be similar to recovery (they are both awake, aren't they? Not much info is given, anyway); thus it seems counterintuitive that anesthesia minus awake looks so different than anesthesia minus recovery. The first is mostly blue-ish and the second is mostly red. Is it possible that Figure 4C is actually recovery minus anesthesia? That would make much more sense, also for Figure 4D. Please correct me if I am wrong.
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Reviewer #1 (Public Review):
Qin et al. set out to investigate the role of mechanosensory feedback during swallowing and identify neural circuits that generate ingestion rhythms. They use Drosophila melanogaster swallowing as a model system, focusing their study on the neural mechanisms that control cibarium filling and emptying in vivo. They find that pump frequency is decreased in mutants of three mechanotransduction genes (nompC, piezo, and Tmc), and conclude that mechanosensation mainly contributes to the emptying phase of swallowing. Furthermore, they find that double mutants of nompC and Tmc have more pronounced cibarium pumping defects than either single mutants or Tmc/piezo double mutants. They discovered that the expression patterns of nompC and Tmc overlap in two classes of neurons, md-C and md-L neurons. The dendrites of md-C neurons warp the cibarium and project their axons to the subesophageal zone of the brain. Silencing neurons that express both nompC and Tmc leads to severe ingestion defects, with decreased cibarium emptying. Optogenetic activation of the same population of neurons inhibited filling of the cibarium and accelerated cibarium emptying. In the brain, the axons of nompC∩Tmc cell types respond during ingestion of sugar but do not respond when the entire fly head is passively exposed to sucrose. Finally, the authors show that nompC∩Tmc cell types arborize close to the dendrites of motor neurons that are required for swallowing and that swallowing motor neurons respond to the activation of the entire Tmc-GAL4 pattern.
Strengths:<br /> -The authors rigorously quantify ingestion behavior to convincingly demonstrate the importance of mechanosensory genes in the control of swallowing rhythms and cibarium filling and emptying<br /> -The authors demonstrate that a small population of neurons that express both nompC and Tmc oppositely regulate cibarium emptying and filling when inhibited or activated, respectively<br /> -They provide evidence that the action of multiple mechanotransduction genes may converge in common cell types
Weaknesses:<br /> -A major weakness of the paper is that the authors use reagents that are expressed in both md-C and md-L but describe the results as though only md-C is manipulated<br /> -Evidence that the defects they see in pumping can be specifically attributed to md-C is based on severing the labellum and allowing md-L neurons to degrade.<br /> -GRASP is known to be non-specific and prone to false positives when neurons are in close proximity but not synaptically connected. A positive GRASP signal supports but does not confirm direct synaptic connectivity between md-C/md-L axons and MN11/MN12.<br /> -MN11/MN12 LexA lines are not included in the manuscript and their expression patterns (shared with the reviewers in the author response) do not appear to contain any motor neurons. Double labeling with previously described MN11 and MN12 motor neuron Gal4 lines is needed to support the claim that these LexA lines in fact label MN11 and MN12.<br /> -As seen in Figure Supplement 2, the expression pattern of Tmc-GAL4 is broader than md-C alone. Therefore, the functional connectivity the authors observe between Tmc expressing neurons and MN11 and 12 cannot be traced to md-C alone<br /> -Example traces of md-C calcium imaging during ingestion in vivo are not included, and evidence that md-C neurons respond to mechanical force is lacking<br /> -A positive control (perhaps demonstrating that sugar sensory neurons respond to sucrose in this preparation) is needed to assess whether the lack of response to sucrose ex vivo in Figure 4K is informative<br /> -Proximity between md-C neurons and muscles is not evidence that they sense stretch<br /> -Reporting of posthoc tests needs to be improved throughout the manuscript, as it is not clear which comparisons are noted with asterisks in the figures.
Overall, this work convincingly shows that swallowing and swallowing rhythms are dependent on several mechanosensory genes. Qin et al. also characterize a candidate neuron, md-C, that is likely to provide mechanosensory feedback to pumping motor neurons, but the results they present here are not sufficient to assign this function to md-C alone. This work will have a positive impact on the field by demonstrating the importance of mechanosensory feedback to swallowing rhythms and providing a potential entry point for future investigation of the identity and mechanisms of swallowing central pattern generators.
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Reviewer #1 (Public Review):
Original Review:
Bischoff et al present a carefully prepared study on a very interesting and relevant topic: the role of ion channels (here a Ca2+-activated K+ channel BK) in regulating mitochondrial metabolism in breast cancer cells. The potential impact of these and similar observations made in other tumor entities has only begun to be appreciated. That being said, the authors pursue in my view an innovative approach to understanding breast cancer cell metabolism.
Considering the following points would further strengthen the manuscript:
Methods:
(1) The authors use an extracellular Ca2+ concentration (2 mM) in their Ringer's solutions that is almost twice as high as the physiologically free Ca2+ concentration (ln 473). Moreover, the free Ca2+ concentration of their pipette solution is not indicated (ln 487).
(2) Ca2+I measurements: The authors use ATP to elicit intracellular Ca2+ signals. Is this then physiological stimulus for Ca2+ signaling in breast cancer? What is the rationale for using ATP? Moreover, it would be nice to see calibrated baseline values of Ca2+i
(3) Membrane potential measurements: It would be nice to see a calibration of the potential measurements; this would allow to correlate IV relationship with membrane potential. Without calibration it is hard to compare unless the identical uptake of the dye is shown.<br /> Do paxilline or IbTx also induce a depolarization?
(4) mito-potential measurements: Why did the authors use such a long time course and preincubated cells mit channel blockers overnight? Why did they not perform paired experiments and record the immediate effect of the BK channel blockers in the mito potential?
(5) MTT assay are also based on mitochondrial function - since modulation of mito function is at the core of this manuscript, an alternative method should be used.
Results:
(1) Fig. 5G: The number of BK "positive" mitoplasts is surprisingly low - how does this affect the interpretation? Did the authors attempt to record mitoBK current in the "whole-mitoplast" mode? How does the mitoBK current density compare with that of the plasma membrane? Is it possible to theoretically predict the number of mitoBK channels per mitochondrium to elicit the observed effects? Can these results be correlated with immuno-localization of mitoBK channels?
(2) There are also reports about other mitoK channels (e.g. Kv1.3, KCa3.1, KATP) playing an important role in mitochondrial function. Did the authors observe them, too? Can the authors speculate on the relative importance of the different channels? Is it known whether they are expressed organ-/tumor-specifically?
Comments on revised version:
The authors responded to all of my comments - except for one - in a satisfactory way so that I have no further concerns. The authors have prepared a very interesting piece of work that advances the field.
However, I disagree with respect to their interpretation of statistics. Individually analyzed cells are not the best biological replicate per se. In my view a true replicate requires the use of an independent batch of cells derived from a new passage. The statistical analysis can only based on the total number of n cells, if each replicate contributes the same number of cells. If this is not the case, the authors will have to calculate the average of each replicate first so that they are equally weighted.
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Joint Public Review:
Neuropeptide signaling is an important component of nervous systems, where neuropeptides typically act via G-protein coupled receptors (GPCRs) to regulate many physiological and behavioral processes. Neuropeptides and their cognate GPCRs have been extensively characterized in bilaterian animals, revealing that a core set of neuropeptide signaling systems originated in common ancestors of extant Bilateria. Neuropeptides have also been identified in cnidarians, which are a sister group to the Bilateria. However, the GPCRs that mediate the effects of neuropeptides in cnidarians have not been identified.
In this paper the authors perform a phylogenetic analysis of GPCRs in metazoans and report that the orthologs of bilaterian neuropeptide receptors are not found in cnidarians. This indicates that neuropeptide signaling systems have largely evolved independently in cnidarians and bilaterians. To accomplish this, they generated a library of putative and known neuropeptides computationally identified in the genome of the cnidarian sea anemone Nematostella vectensis. These peptides were systematically screened for their ability to activate any of the 161 putative Nematostella GPCRs.
This work identified 31 validated GPCRs. These, together with GPCRs that cluster with them, were then used to demonstrate the independent expansion of GPCRs in cnidarian and bilaterian lineages. The authors then mapped validated receptors and ligands to the Nematostella single cell data to provide an overview of the cell types expressing these signaling genes. In addition, the authors have begun to analyze neuropeptide signaling networks in N. vectensis by showing potential signaling connections between cell types expressing neuropeptides and cell types expressing cognate receptors.
This work is the most extensive pharmacological characterization of neuropeptide GPCRs in a cnidarian to date and thus represents an important accomplishment, and is one that will improve our understanding of how peptidergic signaling evolved in animals and its impact on evolution of nervous systems. In addition, this impressive work transforms our knowledge of neuropeptide signaling systems in cnidarians and provides the foundations for extensive functional characterization neuropeptide systems in the context of nervous systems that exhibit radial symmetry, contrasting with the bilaterally symmetrical architecture of the majority of bilaterian nervous systems.
The reviewers did not detect any weaknesses in the work but asked that the authors comment on the following points, which they have done in the revised version.
(1) Clearly, other neuropeptide signaling systems in cnidarians remain to be discovered but this paper represents a huge step forward.
(2) There are limitations in what can be interpreted from single cell transcriptomic data but the data nevertheless provide the foundations for future studies involving i). detailed anatomical analysis of neuropeptide and neuropeptide receptor expression in N. vectensis using mRNA in situ hybridization and/or immunohistochemical methods and ii). functional analysis of the physiological/behavioral roles of neuropeptide signaling systems in N. vectensis.
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Reviewer #1 (Public Review):
Summary:
In the resubmitted manuscript by Chen et al. entitled, "Retinal metabolism: Evidence for uncoupling of glycolysis and oxidative phosphorylation via Cori-, Cahill-, and mini-Krebs-cycle", the authors look to provide insight on retinal metabolism and substrate utilization but using a murine explant model with various pharmacological treatments in conjunction with metabolomics. The authors conclude that photoreceptors, a specific cell within the explant, which also includes retinal pigment epithelium (RPE) and many other types of cells, are able to uncouple glycolytic and Krebs-cycle metabolism via three different pathways: 1) the mini-Krebs-cycle, fueled by glutamine and branched-chain amino acids; 2) the alanine-generating Cahill-cycle; and 3) the lactate-releasing Cori-cycle. While the authors have toned down some of their bold conclusions made in the original manuscript, they did very little in the way of providing additional well-controlled experiments, including cell-specific treatments, genetic knockouts, or stable isotope tracing to support their conclusions. Rather, the authors proceed to speculate more without additional data. The major issues raised by this reviewer were not adequately addressed. As such, the conclusions continue to be highly speculative and not well supported with evidence.
Strengths of resubmission:
The resubmission toned down some of its bold statements.
Weaknesses of resubmission:
Major weaknesses of this study persist including lack of in vivo supporting data. Also, retinal explant culture metabolomics are done in neuroretina with RPE attached, which are metabolically active and can be altered by the treatments investigated herein, further confounding the claims made regarding the neuroretina. While including the RPE in the explant model is commended, it needs to be separated from the retina prior to metabolomics to get a better sense of each tissues' metabolism. Also, melanin within RPE will hinder immunofluorescence signal, so one cannot state that RPE do not express certain enzymes based solely on immunofluorescence. Pharmacologic treatments are not cell-specific as the enzymes are expressed in numerous cells within the retina and RPE, and/or the treatments have significant off-target effects (such as shikonin). So, it is difficult to ascertain that the metabolic changes are secondary to the effects on photoreceptors alone, which the authors claim. Additionally, the explants are taken at a very early age when photoreceptors are known to still be maturing. No mention or data is presented on how these metabolic changes are altered in retinal explants after photoreceptors have fully matured. Likewise, significant assumptions are made based on a single metabolomics experiment with no stable isotope tracing to support the pathways suggested. In vivo, stable-isotope retinal metabolomics are being done and have been done, so stating this technology is beyond our field is false. Therefore, the conclusions reached in this manuscript are still not supported.
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Joint Public Review:
Bolivar et al. set out to explore whether four distinct neuronal subtypes within the peripheral nervous system exhibit varying potentials for axon regeneration following nerve injury. To investigate this question, they harnessed the power of four distinct reporter mouse models featuring fluorescent labeling of these neuronal subtypes. Their findings reveal that axons of nociceptor neurons exhibit faster regeneration than those of motor neurons, with mechanoreceptors, and proprioceptors displaying the slowest regeneration rate.
To delve into the molecular mechanisms underlying this divergence in regeneration potential, the authors employed the Ribotag technique in mice. This approach enabled them to dissect the differential translatomes of these four neuronal populations after nerve injury, comparing them to uninjured neurons. Their comprehensive expression profiling data uncovers a remarkably heterogeneous response among these neuron subtypes to axon injury.
To focus on one identified target with a mechanistic experiment as a proof of concept, their analysis highlights a striking upregulation of MED12 in proprioceptors, leading to the hypothesis that this molecule may play an inhibitory role, contributing to the comparatively slower regeneration of proprioceptor axons when compared to other neuronal subtypes. This hypothesis gains support from their in vitro model, where siRNA-mediated downregulation of MED12 results in a significant increase in neurite outgrowth in proprioceptive neurons after plating in cell culture dishes.
Overall, this is an interesting study, and in conjunction with similar work from others will be highly valuable for neurobiologists studying how to modulate the regeneration of axons from distinct neuronal subtypes. The quality of data presentation appears to be very good in general, and the manuscript is appropriately written.
Comments on revised version:
Because there are multiple explanations for the differential regeneration responses, the authors have provided further discussion about how regeneration may be regulated in vitro and in vivo. The detection of a gene, Med12, which is unregulated in proprioceptive neurons, but not nociceptive and mechanoceptors, gives support to the existence of specific programs of responses in the peripheral nervous system after injury. Further investigation is needed to define this responsiveness in detail.
Another response is the role of neurotrophins and their receptors. The authors have considered outcomes as a result of different Trk receptor signaling and also the effect of TGFbeta and IL6 as cytokine modulators. Add to this list is the possibility that axon guidance molecules and downstream substates may also play a role.
The original title was considered to be too broad and did not explain all the mechanistic aspects of this study. Therefore a revised title "Neuron-specific RNA-sequencing reveals different response in peripheral neurons after nerve injury" was used. It is appropriately suitable for the results reported in this manuscript.
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Reviewer #1 (Public Review):
Summary:
The authors are interested in the developmental origin of the neurons of the cerebellar nuclei. They identify a population of neurons with a specific complement of markers that originate in a distinct location from where cerebellar nuclear precursor cells have been thought to originate that show distinct developmental properties. The cerebellar nuclei have been well studied in recent years both to understand their development and through an evolutionary lens, which supports the importance of this study. The discovery of a new germinal zone giving rise to a new population of CN neurons is an exciting finding, and it enriches our understanding of cerebellar development, which has previously been quite straightforward, where cerebellar inhibitory cells arise from the ventricular zone and the excitatory cells arise from the rhombic lip.
Strengths:
One of the strengths of the manuscript is that the authors use a wide range of technical approaches, including transgenic mice that allow them to disentangle the influence of distinct developmental organizers such as ATOH.<br /> Their finding of a novel germinal zone and a novel population of CN neurons is important for developmental neuroscientists, and cerebellar neuroscientists.
Weaknesses:
One important question raised by this work is what these newly identified cells eventually become in the adult cerebellum. Are they excitatory or inhibitory? Do they correspond to a novel cell type or perhaps one of the cell classes that have been recently identified in the cerebellum (e.g. Fujita et al., eLife, 2020)? Understanding this would significantly bolster the impact of this manuscript.
The major weakness of the manuscript is that it is written for a very specialized reader who has a strong background in cerebellar development, making it hard to read for a general audience. It's challenging to follow the logic of some of the experiments as well as to contextualize these findings in the field of cerebellar development.
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Reviewer #1 (Public Review):
Summary:
This interesting study explores the mechanism behind an increased susceptibility of daf-18/PTEN mutant nematodes to paralyzing drugs that exacerbate cholinergic transmission. The authors use state-of-the-art genetics and neurogenetics coupled with locomotor behavior monitoring and neuroanatomical observations using gene expression reporters to show that the susceptibility occurs due to low levels of DAF-18/PTEN in developing inhibitory GABAergic neurons early during larval development (specifically, during the larval L1 stage). DAF-18/PTEN is convincingly shown to act cell-autonomously in these cells upstream of the PI3K-PDK-1-AKT-DAF-16/FOXO pathway, consistent with its well-known role as an antagonist of this conserved signaling pathway. The authors exclude a role for the TOR pathway in this process and present evidence implicating selectivity towards developing GABAergic neurons. Finally, the authors show that a diet supplemented with a ketogenic body, β-hydroxybutyrate, which also counteracts the PI3K-PDK-1-AKT pathway, promoting DAF-16/FOXO activity, partially rescues the proper development (morphology and function) of GABAergic neurons in daf-18/PTEN mutants, but only if the diet is provided early during larval development. This strongly suggests that the critical function of DAF-18/PTEN in developing inhibitory GABAergic neurons is to prevent excessive PI3K-PDK-1-AKT activity during this critical and particularly sensitive period of their development in juvenile L1 stage worms. Whether or not the sensitivity of GABAergic neurons to DAF-18/PTEN function is a defining and widespread characteristic of this class of neurons in C. elegans and other animals, or rather a particularity of the unique early-stage GABAergic neurons investigated remains to be determined.
Strengths:
The study reports interesting and important findings, advancing the knowledge of how daf-18/PTEN and the PI3K-PDK-1-AKT pathway can influence neurodevelopment, and providing a valuable paradigm to study the selectivity of gene activities towards certain neurons. It also defines a solid paradigm to study the potential of dietary interventions (such as ketogenic diets) or other drug treatments to counteract (prevent or revert?) neurodevelopment defects and stimulate DAF-16/FOXO activity.
Weaknesses:
(1 )Insufficiently detailed methods and some inconsistencies between Figure 4 and the text undermine the full understanding of the work and its implications.
The incomplete methods presented, the imprecise display of Figure 4, and the inconsistency between this figure and the text, make it presently unclear what are the precise timings of observations and treatments around the L1 stage. What exactly do E-L1 and L1-L2 mean in the figure? The timing information is critical for the understanding of the implications of the findings because important changes take place with the whole inhibitory GABAergic neuronal system during the L1 stage into the L2 stage. The precise timing of the events such as neuronal births and remodelling events are well-described (e.g., Figure 2 in Hallam and Jin, Nature 1998; Fig 7 in Mulcahy et al., Curr Biol, 2022). Likewise, for proper interpretation of the implication of the findings, it is important to describe the nature of the defects observed in L1 larvae reported in Figure 1E - at present, a representative figure is shown of a branched commissure. What other types of defects, if any, are observed in early L1 larvae? The nature of the defects will be informative. Are they similar or not to the defects observed in older larvae?
(2) The claim of proof of concept for a reversal of neurodevelopment defects is not fully substantiated by data.
The authors state that the work "constitutes a proof of concept of the ability to revert a neurodevelopmental defect with a dietary intervention" (Abstract, Line 56), however, the authors do not present sufficient evidence to distinguish between a "reversal" or prevention of the neurodevelopment defect by the dietary intervention. This clarification is critical for therapeutic purposes and claims of proof-of-concept. From the best of my understanding, reversal formally means the defect was present at the time of therapy, which is then reverted to a "normal" state with the therapy. On the other hand, prevention would imply an intervention that does not allow the defect to develop to begin with, i.e., the altered or defective state never arises. In the context of this study, the authors do not convincingly show reversal. This would require showing "embryonic" GABAergic neuron defects or showing convincing data in newly hatched L1 (0-1h), which is unclear if they do so or not, as I have failed to find this information in the manuscript. Again, the method description needs to be improved and the implications can be very different if the data presented in Figure 2D-E regard newly born L1 animals (0-1h) or L1 animals at say 5-7h after hatching. This is critical because the development of the embryonically-born GABAergic DD neurons, for instance, is not finalized embryonically. Their neurites still undergo outgrowth (albeit limited) upon L1 birth (see DataS2 in Mulcahy et al., Curr Biol 2022), hence they are susceptible to both committing developmental errors and to responding to nutritional interventions to prevent them. In contrast to embryonic GABAergic neurons, embryonic cholinergic neurons (DA/DB) do not undergo neurite outgrowth post-embryonically (Mulcahy et al., Curr Biol 2022), a fact which could provide some mechanistic insight considering the data presented. However, neurites from other post-embryonically-born neurons also undergo outgrowth post-embryonically, but mostly during the second half of the L1 stage following their birth up to mid-L2, with significant growth occurring during the L1-L2 transition. These are the cholinergic (VA/VB and AS neurons) and GABAergic (VD) neurons. The fact that AS neurons undergo a similar amount of outgrowth as VD neurons is informative if VD neurons are or are not susceptible to daf-18/PTEN activity. Independently, DD neurons are still quite unique on other aspects (see below), which could also bring insight into their selective response.
Finally, even adjusting the claim to "constitutes a proof-of-concept of the ability of preventing a neurodevelpmental defect with a dietary intervention" would not be completely precise, because it is unclear how much this work "constitutes a proof of concept". This is because, unless I misunderstood something, dietary interventions are already applied to prevent neurodevelopment defects, such as when folic acid supplementation is recommended to pregnant women to prevent neural tube defects in newborns.
(3) The data presented do not warrant the dismissal of DD remodeling as a contributing factor to the daf-18/PTEN defects.
Inhibitory GABAergic DD neurons are quite unique cells. They are well-known for their very particular property of remodeling their synaptic polarity (DD neurons switch the nature of their pre- and post-synaptic targets without changing their wiring). This process is called DD remodeling. It starts in the second half of the L1 stage and finishes during the L2 stage. Unfortunately, the fact that the authors find a specific defect in early GABAergic neurons (which are very likely these unique DD neurons) is not explored in sufficient detail and depth. The facts that these neurons are not fully developed at L1, that they still undergo limited neurite growth, and that they are poised for striking synaptic plasticity in a few hours set them apart from the other explored neurons, such as early cholinergic neurons, which show a more stable dynamics and connectivity at L1 (see Mulcahy et al., Curr Biol 2022).
The authors use their observation that daf-18/PTEN mutants present morphological defects in GABAergic neurons prior to DD remodeling to dismiss the possibility that the DAF-18/PTEN-dependent effects are "not a consequence of deficient rearrangement during the early larval stages". However, DD remodeling is just another cell-fate-determined process and as such, its timing, for instance, can be affected by mutations in genes that affect cell fates and developmental decisions, such as daf-18 and daf-16, which affect developmental fates such as those related with the dauer fate. Specifically, the authors do not exclude the possibility that the defects observed in the absence of either gene could be explained by precocious DD remodeling. Precocious DD remodeling can occur when certain pathways, such as the lin-14 heterochronic pathway, are affected. Interestingly, lin-14 has been linked with daf-16/FOXO in at least two ways: during lifespan determination (Boehm and Slack, Science 2005) and in the L1/L2 stages via the direct negative regulation of an insulin-like peptide gene ins-33 (Hristova et al., Mol Cell Bio 2005). It is likely that the prevention of DD dysfunction requires keeping insulin signaling in check (downregulated) in DD neurons in early larval stages, which seems to coincide with the critical timing and function of daf-18/PTEN. Hence, it will be interesting to test the involvement of these genes in the daf-18/daf-16 effects observed by the authors.
Discussion on the impact of the work on the field and beyond:
The authors significantly advance the field by bringing insight into how DAF-18/PTEN affects neurodevelopment, but fall short of understanding the mechanism of selectivity towards GABAergic neurons, and most importantly, of properly contextualizing their findings within the state-of-the-art C. elegans biology.
For instance, the authors do not pinpoint which type of GABAergic neuron is affected, despite the fact that there are two very well-described populations of ventral nerve cord inhibitory GABAergic neurons with clear temporal and cell fate differences: the embryonically-born DD neurons and the post-embryonically-born VD neurons. The time point of the critical period apparently defined by the authors (pending clarifications of methods, presentation of all data, and confirmation of inconsistencies between the text and figures in the submitted manuscript) could suggest that DAF-18/PTEN is required in either or both populations, which would have important and different implications. An effect on DD neurons seems more likely because an image is presented (Figure 2D) of a defect in an L1 daf-18/PTEN mutant larva with 6 neurons (which means the larva was processed at a time when VD neurons were not yet born or expressing pUnc-47, so supposedly it is an image of a larva in the first half of the L1 stage (0-~7h?)). DD neurons are also likely the critical cells here because the neurodevelopment errors are partially suppressed when the ketogenic diet is provided at an "early" L1 stage, but not later (e.g., from L2-L3, according to the text, L2-L4 according to the figure? ).
This study brings important contributions to the understanding of GABAergic neuron development in C. elegans, but unfortunately, it is justified and contextualized mostly in distantly-related fields - where the study has a dubious impact at this stage rather than in the central field of the work (post-embryonic development of C. elegans inhibitory circuits) where the study has stronger impact. This study is fundamentally about a cell fate determination event that occurs in a nutritionally-sensitive developmental stage (post-embryonic L1 larval stage) yet the introduction and discussion are focused on more distantly related problems such as excitatory/inhibitory (E/I) balance, pathophysiology of human diseases, and treatments for them. Whereas speculation is warranted in the discussion, the reduced in-depth consideration of the known biology of these neurons and organisms weakens the impact of the study as redacted. For instance, the critical role of DAF-18/PTEN seems to occur at the early L1 larval stage, a stage that is particularly sensitive to nutritional conditions. The developmental progression of L1 larvae is well-known to be sensitive to nutrition - eg, L1 larvae arrest development in the absence of food, something that is explored in nematode labs to synchronize animals at the L1 stage by allowing embryos to hatch into starvation conditions (water). Development resumes when they are exposed to food. Hence, the extensive postembryonic developmental trajectory that GABAergic neurons need to complete is expected to be highly susceptible to nutrition. Is it? The sensitivity towards the ketogenic diet intervention seems to favor this. In this sense, the attribution of the findings to issues with the nutrition-sensitive insulin-like signaling pathway seems quite plausible, yet this possibility seems insufficiently considered and discussed.
Finally, the fact that imbalances in excitatory/inhibitory (E/I) inputs are linked to Autism Spectrum Disorders (ASD) is used to justify the relevance of the study and its findings. Maybe at this stage, the speculation would be more appropriate if restricted to the discussion. In order to be relevant to ASD, for instance, the selectivity of PTEN towards inhibitory neurons should occur in humans too. However, at present, the E/I balance alteration caused by the absence of daf-18/PTEN in C. elegans could simply be a coincidence due to the uniqueness of the post-embryonic developmental program of GABAergic neurons in C. elegans. To be relevant, human GABAergic neurons should also pass through a unique developmental stage that is critically susceptible to the PI3K-PDK1-AKT pathway in order for DAF-18/PTEN to have any role in determining their function. Is this the case? Hence, even in the discussion, where the authors state that "this study provides universally relevant information on.... the mechanisms underlying the positive effects of ketogenic diets on neuronal disorders characterized by GABA dysfunction and altered E/I ratios", this claim seems unsubstantiated as written particularly without acknowledging/mentioning the criteria that would have to be fulfilled and demonstrated for this claim to be true.
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Reviewer #1 (Public Review):
This study presents valuable observations of white matter organisation from diffusion MRI and two types of synchrotron imaging in both monkeys and mice. Cross-modality comparisons are interesting as the different methods are able to probe anatomical structures at different length scales, from single axons in high-resolution synchrotron (ESRF) imaging, to clusters of axons in lower-resolution synchrotron (DEXY) data, to axon populations at the mm-scale in diffusion MRI. By acquiring all modalities in monkey and mouse ex vivo samples, the authors can observe principles of fibre organisation, and characterise how fibre characteristics, such as tortuosity and micro-dispersion, vary across select brain regions and in healthy tissue versus a demyelination model. The results are solid, though some statements (in the abstract/discussion) do not appear to be fully supported, and statistical tests would help confirm whether tissue characteristics are similar/different between different conditions.
One very interesting result is the observation of apparent laminar organisation of fibres in ex vivo monkey white matter samples. DESY data from the corpus callosum shows fibres with two dominant orientations (one L-R, one slightly inclined), clustered in laminar structures within this major fibre bundle. Thanks to the authors providing open data, I was able to look through the raw DESY volume and observe regions with different "textures" (different orientations) in the described laminar arrangement. That this organisation can be observed by eye, as well as by structure tensor, is fairly convincing. As not all readers will download the data themselves, the manuscript could benefit from additional figures/videos to demonstrate (1) the quality of the DESY data and (2) a more 3D visualisation of the laminar structures (where the coronal plane shows convincing columnar structure or stripes). Similarly in Figure 5A, though this nicely depicts two populations with different orientations, it is somewhat difficult to see the laminar structure in the current image.
ESRF data of the centrum semiovale (CS) contributes evidence for similar laminar structures in a crossing fibre region, where primarily AP fibres are shown to cluster in 3 laminar structures. As above, further visualisations of the ESRF volume in the CS (as shown in Figure 4E) would be of value (e.g. showing consistency across the 4 volumes, 2D images showing stripey/columnar patterns along different axes, etc).
A key limitation of this result is that, though the DESY data from the CC seems convincing, the same structures were not observed in high-resolution synchrotron (ESRF) data of the same tissue sample in the corpus callosum. This seems surprising and the manuscript does not provide a convincing explanation for this inconsistency. The authors argue that this is due to the limited FOV of the ESRF data (~200x200x800 microns). However, the observed laminar structures in DESY are ~40 microns thick, and ERSF data from the CST suggests laminar thicknesses in the range of 5-40 microns with a similar FOV. This suggests the ERSF FOV would be sufficient to capture at least a partial description of the laminar organisation. Further, the DESY data from the CC shows columnar variations along the LR axis, which we might expect to be observed along the long axis of the ESFR volume of the same sample. Additional analyses or explanations to reconcile these apparently conflicting observations would be of value. For example, the authors could consider down-sampling the ESRF data in an appropriate manner to make it more similar to the DESY data, and running the same analysis, to see if the observed differences are related to resolution (i.e. the thinner laminar structures cluster in ways that they look like a thicker laminar structure at lower resolution), or crop the DESY data to the size of the ESRF volume, to test whether the observed differences can be explained by differences in FOV.
Laminar structures were not observed in mouse data, though it is unclear if this is due to anatomical differences or somewhat related to differences in data quality across species.
The authors further quantify various other characteristics of the white matter, such as micro-dispersion, tortuosity, and maximum displacement. Notably, the microscopic FA calculated via structure tensor is fairly consistent across regions, though not modalities. When fibre orientations are combined across the sample, they are shown to produce similar FODs to dMRI acquired in the same tissue, which is reassuring. As noted in the text, the estimates of tortuosity and max displacement are dependent on the FOV over which they are calculated. Calculating these metrics over the same FOV, or making them otherwise invariant to FOV, could facilitate more meaningful comparisons across samples and/or modalities.
Though the results seem solid, some statements, particularly in the abstract and discussion, do not seem to be fully supported by the data. For example, the abstract states "Our findings revealed common principles of fibre organisation in the two species; small axonal fasciculi and major bundles formed laminar structures with varying angles, according to the characteristics of major pathways.", though the results show "no strong indication within the mouse CC of the axonal laminar organisation observed in the monkey". Similarly, the introduction states: "By these means, we demonstrated a new organisational principle of white matter that persists across anatomical length scales and species, which governs the arrangement of axons and axonal fasciculi into sheet-like laminar structures." Further comments on the text are provided below.
One observation not notably discussed in the paper is that the spherical histograms of Figure 3E/H appear to have an anisotropic spread of the white points about 0,0. It would be interesting if the authors could comment on whether this could be interpreted as the FOD having asymmetric dispersion and if so, whether the axis of dispersion relates to the fibre orientations of the laminar structures.
A limitation of the study is that it considers only small ex vivo tissue samples from two locations in a single postmortem monkey brain and slightly larger regions of mouse brain tissue. Consequently, further evidence from additional brain regions and subjects would be required to support more generalised statements about white matter organisation across the brain.
Given the monkey results, the mouse study (section 2.5 onwards) lacks some motivation. In particular, it is unclear why a demyelination model was studied and if/how this would link to the laminar structure observed in the monkey data. Further, it is unclear how comparable tortuosity/max deviation values are across species, considering the differences in data quality and relative resolution, given that the presented results show these values are very modality-dependent.
The paper introduces a new method of "scale-space" parameters for structure tensors. Since, to my understanding, this is the first description of the method, some simple validation of the method would be welcomed. Further, the same scale parameters are not used across monkeys and mice, with a larger kernel used in mice (Table 2) which is surprising given their smaller brain size. Some explanation would be helpful.
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Reviewer #1 (Public Review):
Summary:
The work in the manuscript titled " Altered firing output of VIP interneurons and early dysfunctions in CA1 hippocampal circuits in the 3xTg mouse model of Alzheimer's disease" utilized patch-clamp techniques to explore the electrophysiological characteristics of VIP interneurons in the early stages of AD using the 3xTg mouse model. The study revealed that VIP interneurons exhibited prolonged action potentials and reduced firing rates. These changes could not be attributed to modifications in input signals or morphological transformations. The authors attributed aberrant VIP activity to the accumulation of beta-amyloid in those interneurons.
The decreased frequency of VIP inhibitory events was associated with no observed changes in excitatory drive to these interneurons. Consequently, heightened activity in the general population of CA1 interneurons was observed during a decision-making task and an object recognition test. In light of these findings, the authors concluded that the altered firing patterns of VIP interneurons may initiate early-stage dysfunction in hippocampal CA1 circuits, potentially influencing the progression of AD pathology.
Strengths:
Overall the work is novel and moves the field of Alzheimer's disease forward in a significant way. The manuscript reports a novel concept of aberrant activity in VIP interneurons during the early stages of AD thus contributing to dysfunctions of the CA1 microcircuit. This results in the enhancement of the inhibitory tone on the primary cells of CA1. Thus, the disinhibition by VIP interneurons of Principal Cells is dampened. The manuscript was skillfully composed, and the study was of strong scientific rigor featuring well-designed experiments. Necessary controls were present. Both sexes were included.
Limitations:
(1) The authors attributed aberrant circuit activity to the accumulation of "Abeta intracellularly" inside IS-3 cells. That is problematic. 6E10 antibody recognizes amyloid plaques in addition to Amyloid Precursor Protein (APP) as well as the C99 fragment. There are no plaques at the ages 3xTg mice were examined. Thus, the staining shown in Figure 1a is of APP/C99 inside neurons, not abeta accumulations in neurons. At the ages of 3-6 months, 3xTg starts producing abeta oligomers and potentially tau oligomers as well (Takeda et al., 2013 PMID: 23640054; Takeda et al., 2015 PMID: 26458742 and others). Emerging literature suggests that abeta and tau oligomers disrupt circuit function. Thus, a more likely explanation of abeta and tau oligomers disrupting the activity of VIP neurons is plausible.
(2) Authors suggest that their animals do not exhibit loss of synaptic connections and show Figure 3d in support of that suggestion. However, imaging with confocal microscopy of 70-micron thick sections would not allow the resolution of pre- and post-synaptic terminals. More sensitive measures such as electron microscopy or array tomography are the appropriate techniques to pursue. It is important for the authors to either remove that data from the manuscript or address the limitations of their technique in the discussion section. There is a possibility of loss of synaptic connections in their mouse model at the ages examined.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The paper of Mao et al. expands the genetic toolset that was previously developed by the Rao lab (Denfg et al 2019) to introduce the conditional KO or downregulation of neurotransmission components in Drosophila. The authors then use these tools to investigate neurotransmission in the the clock neurons of the Drosophila brain. They first test some known components and then analyze the contribution of the CNMa neuropeptide and its receptor to the circadian behavior. The results indicate that CNMA acts from a subset of DN1ps (dorsal clock neurons) to set the phase of the morning peak of locomotor activity in light:dark cycles, with an advanced morning activity in the absence of the neuropeptide. Interestingly, the receptor for the PDF neuropeptide appears to be acting in some of the CNMa neurons to control morning activity.
Strengths/weaknesses:
This is clearly a very useful new set of tools to restrict the manipulation of these components to specific neuronal populations, and overall (see specific points below), the paper is convincing to show that the tools indeed allow to efficiently and specifically eliminate neuropeptides/receptors from subsets of neurons. The analysis of the CNMa function in the clock network reveals a new and interesting function for CNMa in the control of morning anticipation in LD conditions. This function appears to depend on CNMA_expressing DN1ps.
Comment on revised version:
I believe that the authors properly addressed the main points that were raised in my comment on version 1.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, the authors present new tools to collect and process information from the biomedical literature that could be typically used in a meta-analytic framework. The tools have been specifically developed for the neuroimaging literature. However, many of their functions could be used in other fields. The tools mainly enable to downloading of batches of paper from the literature, extracting relevant information along with meta-data, and annotating the data. The tools are implemented in an open ecosystem that can be used from the command line or Python.
Strengths:
The tools developed here are really valuable for the future of large-scale analyses of the biomedical literature. This is a very well-written paper. The presentation of the use of the tools through several examples corresponding to different scientific questions really helps the readers to foresee the potential application of these tools.
Weaknesses:
The tools are command-based and store outcomes locally. So users who prefer to work only with GUI and web-based apps may have some difficulties. Furthermore, the outcomes of the tools are constrained by inherent limitations in the scientific literature, in particular, here the fact that only a small portion of the publications have full text openly available.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this work, Xie, Prescott and colleagues have reevaluated the role of Nav1.7 in nociceptive sensory neurons excitability. They find that nociceptors can make use of different sodium channel subtypes to reach equivalent excitability. The existence of this degeneracy is critical to understanding the neuronal physiology under normal and pathological conditions and could explain why Nav subtype-selective drugs have failed in clinical trials. More concretely, nociceptor repetitive spiking relies on Nav1.8 at DIV0 (and probably under normal conditions in vivo), but on Nav1.7 and Nav1.3 at DIV4-7 (and after inflammation in vivo).
The conclusions of this paper are mostly well supported by data, and these findings should be of broad interest to scientists working on pain, drug development, neuronal excitability and ion channels.
Strengths:
The authors have employed elegant electrophysiology experiments (including specific pharmacology and dynamic clamp) and computational simulations to study the excitability of a subpopulation of DRGs that would very likely match with nociceptors (they take advantage of using transgenic mice to detect Nav1.8-expressing neurons). They make a strong point showing the degeneracy that occurs at the ion channel expression level in nociceptors, adding this new data to previous observations in other neuronal types. They also demonstrate that the different Nav subtypes functionally overlap and are able to interchange their "typical" roles in action potential generation. As Xie, Prescott and colleagues argue, the functional implications of the degenerate character of nociceptive sensory neurons excitability need to be seriously taken into account regarding drug development and clinical trials with Nav subtype-selective inhibitors.
In this revised version, the quality of the manuscript has been visibly improved. In my opinion, the questions and concerns raised by reviewers have been addressed clearly. After a detailed reading of this version and the comments to the reviewers, I have no additional comments or criticisms.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In Ryu et al., the authors use a cortical mouse astrocyte culture system to address the functional contribution of astrocytes to circadian rhythms in the brain. The authors' starting point is transcriptional output from serum-shocked culture, comparative informatics with existing tools and existing datasets. After fairly routine pathway analyses, they focus on the calcium homeostasis machinery and one gene, Herp, in particular. They argue that Herp is rhythmic at both mRNA and protein levels in astrocytes. They then use a calcium reporter targeted to the ER, mitochondria, or cytosol and show that Herp modulates calcium signaling as a function of circadian time. They argue that this occurs through the regulation of inositol receptors. They claim that the signaling pathway is clock-controlled by a limited examination of Bmal1 knockout astrocytes. Finally, they switch to calcium-mediated phosphorylation of the gap junction protein Connexin 43 but do not directly connect HERP-mediated circadian signaling to these observations. While these experiments address very important questions related to the critical role of astrocytes in regulating circadian signaling, the mechanistic arguments for HERP function, its role in circadian signaling through inositol receptors, the connection to gap junctions, and ultimately, the functional relevance of these findings is only partially substantiated by experimental evidence.
Strengths:
- The paper provides useful datasets of astrocyte gene expression in circadian time.
- Identifies HERP as a rhythmic output of the circadian clock.
- Demonstrates the circadian-specific sensitivity of ATP -> calcium signaling.
- Identifies possible rhythms in both Connexin 43 phosphorylation and rhythmic movement of calcium between cells.
Weaknesses:
- It is not immediately clear why the authors chose to focus on Ca2+ homeostasis or Herp from their initial screens as neither were the "most rhythmic" pathways in their primary analyses.
- It would have been interesting (and potentially important) to know whether various methods of cellular synchronization would also render HERP rhythmic (e.g., temperature, forskolin, etc). If Herp is indeed relatively astrocyte-specific and rhythmic, it should be easy to assess its rhythmicity in vivo.
- The authors show that Herp suppression reduces ATP-mediated suppression of calcium whereas it initially increases Ca2+ in the cytosol and mitochondria and then suppresses it. The dynamics of the mitochondrial and cytosolic responses are not discussed in any detail and it is unclear what their direct relationship is to Herp-mediated ER signaling. What is the explanation for Herp (which is thought to be ER-specific) to calcium signaling in other organelles?
- What is the functional significance of promoting ATP-mediated suppression of calcium in ER?
- The authors then nicely show that the effect of ATP is dependent on intrinsic circadian timing but do not explain why these effects are antiphase in cytosol or mitochondria. Moreover, the ∆F/F for calcium in mitochondria and cytosol both rise, cross the abscissa, and then diminish - strongly suggesting a biphasic signaling event. Therefore, one wonders whether measuring the area under the curve is the most functionally relevant measurement of the change.
- Why are mitochondrial and cytosolic calcium not also demonstrated for Bmal1 KO astrocytes?
- The authors claim that Herp acts by regulating the degradation of ITPRs but this hypothesis - rather central to the mechanisms proposed in this study - is not experimentally substantiated.
- There is no clear demonstration of the functional relevance of the circadian rhythms of ATP-mediated calcium signaling.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This is an interesting and well-written paper reporting on a novel approach to studying cerebellar function based on the idea of selective recruitment using fMRI. The study is well-designed and executed. Analyses are sound and results are properly discussed. The paper makes a significant contribution to broadening our understanding of the role of the cerebellum in human behavior.
- While the authors provide a compelling case for the link between BOLD and the cerebellar cortical input layer, there remains considerable unexplained variance. Perhaps the authors could elaborate a bit more on the assumption that BOLD signals mainly reflect the input side of the cerebellum (see for example King et al., elife. 2023 Apr 21;12:e81511).
- The current approach does not appear to take the non-linear relationships between BOLD and neural activity into account.
- The authors may want to address a bit more the issue of closed loops as well as the underlying neuroanatomy including the deep cerebellar nuclei and pontine nuclei in the context of their current cerebello-cortical correlational approach. But also the contribution of other brain areas such as the basal ganglia and hippocampus.
- What about the direct projections of mossy fibers to the DCN that actually bypasses the cerebellar cortex?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this work, the authors set out to ask whether the MYRF family of transcription factors, represented by myrf-1 and myrf-2 in C. elegans, have a role in the temporally controlled expression of the miRNA lin-4. The precisely timed onset of lin-4 expression in the late L1 stage is known to be a critical step in the developmental timing ("heterochronic") pathway, allowing worms to move from the L1 to the L2 stage of development. Despite the importance of this step of the pathway, the mechanisms that control the onset of lin-4 expression are not well understood.
Overall, the paper provides convincing evidence that MYRF factors have a key role in promoting lin-4 expression in young larvae. Using state-of-the-art techniques (knock-in reporters and conditional alleles), the authors show that MYRF factors are essential for lin-4 activation and act cell-autonomously. Results using some unusual gain-of-function alleles are supported by consistent results using other approaches. The authors also provide evidence supporting the idea that MYRF factors activate lin-4 by directly activating its promoter. Because these results are indirect test of this, further experiments will be necessary to conclusively determine whether lin-4 is indeed a direct target of MYRF factors. myrf-1 and myrf-2 likely function redundantly to activate lin-4; potential complex interactions between these two genes will be an interesting area for future work.
Overall, the paper's results are convincing. The important findings on miRNA regulation and the control of developmental timing will make this work of interest to a broad range of developmental biologists.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
Shotgun data have been analysed to obtain fungal and bacterial organisms abundance. Through their metabolic functions and through co-occurrence networks, a functional relationship between the two types of organisms can be inferred. By means of metabolomics, function-related metabolites are studied in order to deepen the fungus-bacteria synergy.
Strengths:
Data obtained in bacteria correlate with data from other authors.<br /> The study of metabolic "interactions" between fungi and bacteria is quite new.<br /> The inclusion of metabolomics data to support the results is a great contribution.
Weaknesses:
All my concerns have been clarified
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Reviewer #1 (Public Review):
The manuscript by Mullen et al. investigated the gene expression changes in cancer cells treated with the DHODH inhibitor brequinar (BQ), to explore the therapeutic vulnerabilities induced by DHODH inhibition. The study found that BQ treatment causes upregulation of antigen presentation pathway (APP) genes and cell surface MHC class I expression, mechanistically which is mediated by the CDK9/PTEFb pathway triggered by pyrimidine nucleotide depletion. The combination of BQ and immune checkpoint therapy demonstrated a synergistic (or additive) anti-cancer effect against xenografted melanoma, suggesting the potential use of BQ and immune checkpoint blockade as a combination therapy in clinical therapeutics.
The interesting findings in the present study include demonstrating a novel cellular response in cancer cells induced by DHODH inhibition. However, whether the increased antigen presentation by DHODH inhibition actually contributed to the potentiation of the efficacy of immune-check blockade (ICB) is not directly examined is the limitation of the study. Moreover, the mechanism of the increased antigen presentation pathway by pyrimidine depletion mediated by CDK9/PTEFb was not validated by genetic KD or KO targeting by CDK9/PTEFb pathways. Finally, high concentrations of BQ have been reported to show off-target effects, sensitizing cancer cells to ferroptosis, and the authors should discuss whether the dose used in the in vivo study reached the ferroptotic sensitizing dose or not.
Comment on the revised version:
In their response letter, the authors appropriately addressed the reviewer's comments.
However, it is unfortunate that these comments are not reflected in the main text. Consequently, readers may encounter the same questions. Therefore, the reviewer recommends mentioning them in the discussion or limitations of the study, even if briefly, to address readers' concerns. Especially, addressing the comments such as the dosage of BQ being lower than the reported pro-ferroptotic dose (PMID 37407687), and the lack of examining potential impact of immune cell depletion on the efficacy of BQ treatment would be necessary for considering the proposed mechanism. The latter limitation is also raised by the other reviewer.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript by Warfvinge et al. reports the results of CITE-seq to generate single-cell multi-omics maps from BM CD34+ and CD34+CD38- cells from nine CML patients at diagnosis. Patients were retrospectively stratified by molecular response after 12 months of TKI therapy using European Leukemia Net (ELN) recommendations. They demonstrate heterogeneity of stem and progenitor cell composition at diagnosis, and show that compared to optimal responders, patients with treatment failure after 12 months of therapy demonstrate increased frequency of molecularly defined primitive cells at diagnosis. These results were validated by deconvolution of an independent previously published dataset of bulk transcriptomes from 59 CML patients. They further applied a BCR-ABL-associated gene signature to classify primitive Lin-CD34+CD38- stem cells as BCR:ABL+ and BCR:ABL-. They identified variability in the ratio of leukemic to non-leukemic primitive cells between patients, showed differences in expression of cell surface markers and determined that a combination of CD26 and CD35 cell surface markers could be used to prospectively isolate the two populations. The relative proportion of CD26-CD35+ (BCR:ABL-) primitive stem cells was higher in optimal responders compared to treatment failures, both at diagnosis and following 3 months of TKI therapy.
Strengths:
The studies are carefully conducted and the results are very clearly presented. The data generated will be a valuable resource for further studies. The strengths of this study are the application of single-cell multi-omics using CITE-Seq to study individual variations in stem and progenitor clusters at diagnosis that are associated with good versus poor outcomes in response to TKI treatment. These results were confirmed by deconvolution of a historical bulk RNAseq data set. Moreover, they are also consistent with a recent report from Krishnan et al. and are a useful confirmation of those results. The major new contribution of this study is the use of gene expression profiles to distinguish BCR-ABL+ and BCR-ABL- populations within CML primitive stem cell clusters and then applying antibody-derived tag (ADT) data to define molecularly identified BCR:ABL+ and BCR-ABL- primitive cells by expression of surface markers. This approach allowed them to show an association between the ratio of BCR-ABL+ vs BCR-ABL- primitive cells and TKI response and study dynamic changes in these populations following short-term TKI treatment.
Weaknesses:
The number of samples studied by CITE-Seq is limited. However, the authors have confirmed their key observations in additional samples. The BCR-ABL+ versus BCR-ABL- status of cells was not confirmed by direct sequencing for BCR-ABL. However, we recognize that the methodologies to perform these analyses on single cells is still evolving and the authors have shown that CD26 and CD35 expression can consistently identify BCR-ABL+ versus BCR-ABL- cells. It will be of interest to learn whether the GEP and surface markers identified here can distinguish BCR-ABL+ primitive stem cells later in the course of TKI treatment.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
This is an important manuscript that links gene expression to genetic variants and regions of open chromatin. The mechanisms of genetic gene regulation are essential to understanding how standing genetic variation translates to function and phenotype. This data set has the ability to add substantial insight into the field. In particular, the authors show how the relationships between variants, chromatin, and genes are spatially constrained by topologically associated domains.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Cell type deconvolution is one of the early and critical steps in the analysis and integration of spatial omic and single cell gene expression datasets, and there are already many approaches proposed for the analysis. Sang-aram et al. provide an up-to-date benchmark of computational methods for cell type deconvolution.
In doing so, they provide some (perhaps subtle) additional elements that I would say are above the average for a benchmarking study: i) a full Nextflow pipeline to reproduce their analyses; ii) methods implemented in Docker containers (which can be used by others to run their datasets); iii) a fairly decent assessment of their simulator compared to other spatial omics simulators. A key aspect of their results is that they are generally very concordant between real and synthetic datasets. And, it is important that they authors include an appropriate "simpler" baseline method to compare against and surprisingly, several methods performed below this baseline. Overall, this study also has the potential to also set the standard of benchmarks higher, because of these mentioned elements.
The only weakness of this study that I can readily see is that this is a very active area of research and we may see other types of data start to dominate (CosMx, Xenium) and new computational approaches will surely arrive. The Nextflow pipeline will make the the prospect of including new reference datasets and new computational methods easier.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
The authors primary objective in this study was to identify differences between patients with preeclampsia and normal patients with respect to the placental syncytiotrophoblast extracellular vesicle proteome.
A strength of this study is that the authors identified novel STB-EV protein markers that are more abundant in the placenta of patients with preeclampsia compared with normal controls. This contributes a little more to what is already known about STB-EV markers and preeclampsia. If these markers can be shown to be more abundant in maternal plasma of preeclampsia patients, it would be very useful for identifying patients who are at high risk for developing early-onset preeclampsia.
Weaknesses include:<br /> (1) The small sample size. There were only 6 patients in the study group and 6 normal controls. However, this can be considered as a pilot study.<br /> (2) The normal controls were not matched with the study patients and the authors did not state how the controls were selected.<br /> (3) The authors state that the placenta samples were obtained at the time of elective cesarean section. However, it is likely that all the preeclampsia patients were delivered for clinical indications rather than electively. This should be clarified.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors set out to use structural biology (cryo-em), SPR and complement convertase assays to understand the mechanism(s) by which ISG65 dampens the cytotoxicity/cellular clearance to/of trypanosmes opsonised with C3b by the innate immune system.
The cryo-EM structure adds significantly the the author's previous crystallographic data because the latter was limited to the C3d sub-domain of C3b. Further, the in vitro convertase assay adds an additional functional dimension to this study.
The authors have achieved their aims and the results support their conclusions.
The role of complement in immunity to T. brucei (or lack thereof) has been a significant question in molecular parasitology for over 30 years. The identification of ISG65 as the C3 receptor and now this study providing mechanistic insights represents a major advance in the field.
The authors have appropriately put their results into perspective with other recent reports on the role of ISG65.
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Reviewer #1 (Public Review):
The goal of this study is to understand the allosteric mechanism of overall activity regulation in an anaerobic ribonucleotide reductase (RNR) that contains an ATP-cone domain. Through cryo-EM structural analysis of various nucleotide-bound states of the RNR, the mechanism of dATP inhibition is found to involve order-disorder transitions in the active site. These effects appear to prevent binding of substrate and a radical transfer needed to initiate the reaction.
Strengths of the manuscript include the comprehensive nature of the work - including both numerous structures of different forms of the RNR and detailed characterization of enzyme activity to establish the parameters of dATP inhibition. The manuscript has been improved in a revision by performing additional experiments to help corroborate certain aspects of the study. But these new experiments do not address all of the open questions about the structural basis for mechanism. Additionally, some questions about the strength of biochemical data and fit of binding or kinetic curves to data that were raised by other referees still remain. Some experimental observations are not consistent with the proposed model. For example, why does dATP enhance Gly radical formation when the proposed mechanism of dATP inhibition involves disorder in the Gly radical domain?
The work is impactful because it reports initial observations about a potentially new mode of allosteric inhibition in this enzyme class. It also sets the stage for future work to understand the molecular basis for this phenomenon in more detail.
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www.biorxiv.org www.biorxiv.org
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Reviewer #3 (Public Review):
In the revised manuscript by Maio et al, the authors examined the bioenergetic mechanisms involved in the delayed migration of DC's during Mtb infection. The authors performed a series of in vitro infection experiments including bioenergetic experiments using the Agilent Seahorse XF, and glucose uptake and lactate production experiments. Also, data from SCENITH is included in the revised manuscript as well as some clinical data. This is a well written manuscript and addresses an important question in the TB field. A remaining weakness is the use of dead (irradiated) Mtb in several of the new experiments and claims where iMtb data were used to support live Mtb data. Another notable weakness lies in the author's insistence on asserting that lactate is the ultimate product of glycolysis, rather than acknowledging a large body of historical data in support of pyruvate's role in the process. This raises a perplexing issue highlighted by the authors: if Mtb indeed upregulates glycolysis, one would expect that inhibiting glycolysis would effectively control TB. However, the reality contradicts this expectation. Lastly, the examination of the bioenergetics of cells isolated from TB patients undergoing drug therapy, rather than studying them at their baseline state is a weakness.
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Reviewer #1 (Public Review):
Summary:
Transposable Elements (TEs) are exogenously acquired DNA regions that have played important roles in the evolutional acquisition of various biological functions. TEs may have been important in the evolution of the immune system, but their role in thymocytes has not been fully clarified.
Using the human thymus scRNA dataset, the authors suggest the existence of cell type-specific TE functions in the thymus. In particular, it is interesting to show that there is a unique pattern in the type and expression level of TEs in thymic antigen-presenting cells, such as mTECs and pDCs, and that they are associated with transcription factor activities. Furthermore, the authors suggested that TEs may be non-redundantly regulated in expression by Aire, Fezf2, and Chd4, and that some TE-derived products are translated and present as proteins in thymic antigen-presenting cells. These findings provide important insights into the evolution of the acquired immune system and the process by which the thymus acquires its function as a primary lymphoid tissue.
Strengths:
(1) By performing single-cell level analysis using scRNA-seq datasets, the authors extracted essential information on heterogeneity within the cell population. It is noteworthy that this revealed the diversity of expression not only of known autoantigens but also of TEs in thymic antigen-presenting cells.
(2) The attempt to use mass spectrometry to confirm the existence of TE-derived peptides is worthwhile, even if the authors did not obtain data on as many transcripts as expected.
(3) The use of public data sets and the clearly stated methods of analysis improved the transparency of the results.
Weaknesses:
(1) The authors sometimes made overstatements largely due to the lack or shortage of experimental evidence.
For example in Figure 4, the authors concluded that thymic pDCs produced higher copies of TE-derived RNAs to support the constitutive expression of type-I interferons in thymic pDCs, unlike peripheral pDCs. However, the data was showing only the correlation between the distinct TE expression pattern in pDCs and the abundance of dsRNAs. We are compelled to say that the evidence is totally too weak to mention the function of TEs in the production of interferon. Even if pDCs express a distinct type and amount of TE-derived transcripts, it may be a negligible amount compared to the total cellular RNAs. How many TE-derived RNAs potentially form the dsRNAs? Are they over-expressed in pDCs?<br /> The data interpretation requires more caution to connect the distinct results of transcriptome data to the biological significance.
We contend that our manuscript combines the attributes of a research article (novel concepts) and a resource article (datasets of TEs implicated in various aspects of thymus function). The critical strength of our work is that it opens entirely novel research perspectives. We are unaware of previous studies on the role of TEs in the human thymus. The drawback is that, as with all novel multi-omic systems biology studies, our work provides a roadmap for a multitude of future mechanistic studies that could not be realized at this stage. Indeed, we performed wet lab experiments to validate some but not all conclusions: i) presentation of TE-derived MAPs by TECs and ii) formation of dsRNAs in thymic pDCs. In response to Reviewer #1, we performed supplementary analyses to increase the robustness of our conclusions. Also, we indicated when conclusions relied strictly on correlative evidence and clarified the hypotheses drawn from our observations. Regarding the Reviewer's questions about TE-derived dsRNAs, LINE, LTR, and SINE elements all have the potential to generate dsRNAs, given their highly repetitive nature and bi-directional transcription (1). As ~32% of TE subfamilies are overexpressed in pDCs, we hypothesized that these TE sequences might form dsRNA structures in these cells. To address the Reviewer's concerns regarding the amount of TE-derived RNAs among total cellular RNAs, we also computed the percentage of reads assigned to TEs in the different subsets of thymic APCs (see Reviewer 1 comment #4).<br /> ------
I appreciate the authors' efforts to improve the quality of this valuable paper. The additional data proposed by the authors enhanced the possibility that the non-negligible amount of RNAs in pDCs is derived from TE elements. Their biological roles and significance will be demonstrated in future research.
(2) Lack of generality of specific examples. This manuscript discusses the whole genomic picture of TE expression. In addition, one good way is to focus on the specific example to clearly discuss the biological significance of the acquisition of TEs for the thymic APC functions and the thymic selection.
In Figure 2, the authors focused on ETS-1 and its potential target genes ZNF26 and MTMR3, however, the significance of these genes in NK cell function or development is unclear. The authors should examine and discuss whether the distinct features of TEs can be found among the genomic loci that link to the fundamental function of the thymus, e.g., antigen processing/presentation.
We thank the Reviewer for this highly relevant comment. We investigated the genomic loci associated with NK cell biology to determine if ETS1 peaks would overlap with TE sequences in protein-coding genes' promoter region. Figure 2h illustrates two examples of ETS1 significant peaks overlapping TE sequences upstream of PRF1 and KLRD1. PRF1 is a protein implicated in NK cell cytotoxicity, whereas KLRD1 (CD94) dimerizes with NKG2 and regulates NK cell activation via interaction with the nonclassical MHC-I molecule HLA-E (2, 3). Thus, we modified the section of the manuscript addressing these results to include these new analyses: "Finally, we analyzed publicly available ChIP-seq data of ETS1, an important TF for NK cell development (4), to confirm its ability to bind TE sequences. Indeed, 19% of ETS1 peaks overlap with TE sequences (Figure 2g). Notably, ETS1 peaks overlapped with TE sequences (Figure 2h, in red) in the promoter regions of PRF1 and KLRD1, two genes important for NK cells' effector functions (2, 3)."<br /> ------
I am convinced by the authors' explanation that TE elements may contribute to the functions of NK cells.<br /> However, since I have understood that the main topic of this paper is about the thymus and thymic antigen-presenting cells, the mention of NK cells seems abrupt and unconnected to me. NK cells are a type of innate lymphocyte that arise in the bone marrow, and thymus is dispensable for their development and function. The readers might expect to find something more fundamental regarding the function of the thymus and immunological tolerance.
(3) Since the deep analysis of the dataset yielded many intriguing suggestions, why not add a discussion of the biological reasons and significance? For example, in Figure 1, why is TE expression negatively correlated with proliferation? cTEC-TE is mostly postnatal, while mTEC-TE is more embryonic. What does this mean?
We thank the Reviewer for this comment. To our knowledge, the relationship between cell division and transcriptional activity of TEs has not been extensively studied in the literature. However, a recent study has shown that L1 expression is induced in senescent cells. We therefore added the following sentences to our Discussion: "The negative correlation between TE expression and cell cycle scores in the thymus is coherent with recent data showing that transcriptional activity of L1s is increased in senescent cells (5). A potential rationale for this could be to prevent deleterious transposition events during DNA replication and cell division." We also added several discussion points regarding the regulation of TEs by KZFPs to answer concerns raised by Reviewer 2 (see Reviewer 2 comment #1).<br /> ------
I agree on the possibility suggested by the authors.
(4) To consolidate the experimental evidence about pDCs and TE-derived dsRNAs, one option is to show the amount of TE-derived RNA copies among total RNAs. The immunohistochemistry analysis in Figure 4 requires additional data to demonstrate that overlapped staining was not caused by technical biases (e.g. uneven fixation may cause the non-specifically stained regions/cells). To show this, authors should have confirmed not only the positive stainings but also the negative staining (e.g. CD3, etc.). Another possible staining control was showing that non-pDC (CD303- cell fractions in this case) cells were less stained by the ds-RNA probe.
We thank the Reviewer for this suggestion. We computed the proportion of reads in each cell assigned to two groups of sequences known to generate dsRNAs: TEs and mitochondrial genes (1). These analyses showed that the proportion of reads assigned to TEs is higher in pDCs than other thymic APCs by several orders of magnitude (~20% of all reads). In contrast, reads derived from mitochondrial genes had a lower abundance in pDCs. We included these results in Figure 4 - figure supplement 2 and included the following text in the Results section "To evaluate if these dsRNAs arise from TE sequences, we analyzed in thymic APC subsets the proportion of the transcriptome assigned to two groups of genomic sequences known as important sources of dsRNAs, TEs and mitochondrial genes (1). Strikingly, whereas the percentage of reads from mitochondrial genes was typically lower in pDCs than in other thymic APCs, the proportion of the transcriptome originating from TEs was higher in pDCs (~22%) by several orders of magnitude (Figure 4 - figure supplement 2)." As a negative control for the immunofluorescence experiments, we used CD123- cells. Indeed, flow cytometry analysis of the magnetically enriched CD303+ fraction was around 90% pure, as revealed by double staining with CD123 and CD304 (two additional markers of pDCs): CD123- cells were also CD304-/lo, showing that these cells are non- pDCs. Thus, we decided to compare the dsRNA signal between CD123+ cells (pDCs) and CD123- cells (non-pDCs). The difference between CD123+ and CD123- cells was striking (Figure 4d).<br /> ------
Although the technical concerns about immunostaining were not resolved, it is understandable that it would be difficult to rerun the experiment since the authors used the precious human thymi as the experimental material. Immunostaining co-staining requires careful interpretation so that careful experimental setup is needed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors use insights into the dynamics of the PKA kinase domain, obtained by NMR experiments, to inform MD simulations that generate an energy landscape of PKA kinase domain conformational dynamics.
Strengths:
The authors integrate strong experimental data through the use of state-of-the-art MD studies and derive detailed insights into allosteric communication in PKA kinase. Comparison of wt kinase with a mutant (F100A) shows clear differences in the allosteric regulation of the two proteins. These differences can be rationalized by NMR and MD results. During the revision process, the authors have addressed the reviewers' comments adequately and have improved the accessibility of the manuscript to a wider audience.
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Reviewer #1 (Public Review):
Summary:
The authors have implemented Optimal Transport algorithm in GromovMatcher for comparing LC/MS features from different datasets. This paper gains significance in the proteomics field for performing meta-analysis of LC/MS data.
Strengths:
The main strength is that GromovMatcher acheives significant performance metrics compared to other existing methods. The authors have done extensive comparisons to claim that GromovMatcher performs well.
Weaknesses:
The authors might need to add the limitation of datasets and thus have tested/validated their tool using simulated data in the abstract as well.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Theoretical principles of viscous fluid mechanics are used here to assess likely mechanisms of transport in the ER. A set of candidate mechanisms is evaluated, making good use of imaging to represent ER network geometries. Evidence is provided that the contraction of peripheral sheets provides a much more credible mechanism than the contraction of individual tubules, junctions, or perinuclear sheets.
The work has been conducted carefully and comprehensively, making good use of underlying physical principles. There is a good discussion of the role of slip; sensible approximations (low volume fraction, small particle size, slender geometries, pragmatic treatment of boundary conditions) allow tractable and transparent calculations; clear physical arguments provide useful bounds; stochastic and deterministic features of the problem are well integrated.
There are just a couple of areas where more discussion might be warranted, in my view.
(1) The energetic cost of tubule contraction is estimated, but I did not see an equivalent estimate for the contraction of peripheral sheets. It might be helpful to estimate the energetic cost of viscous dissipation in generated flows at higher frequencies. The mechanism of peripheral sheet contraction is unclear: do ATP-driven mechanisms somehow interact with thermal fluctuations of membranes?
(2) Mutations are mentioned in the abstract but not (as far as I could see) later in the manuscript. It would be helpful if any consequences for pathologies could be developed in the text.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, proteomics analysis of the plasma of human subjects that underwent an exercise training regime consisting of a combination of endurance and resistance exercise led to the identification of several proteins that were responsive to exercise training. Confirming previous studies, many exercise-responsive secreted proteins were found to be involved in the extra-cellular matrix. The protein CD300LG was singled out as a potential novel exercise biomarker and the subject of numerous follow-up analyses. The levels of CD300LG were correlated with insulin sensitivity. The analysis of various open-source datasets led to the tentative suggestion that CD300LG might be connected with angiogenesis, liver fat, and insulin sensitivity. CD300LG was found to be most highly expressed in subcutaneous adipose tissue and specifically in venular endothelial cells. In a subset of subjects from the UK Biobank, serum CD300LG levels were positively associated with several measures of physical activity - particularly vigorous activity. In addition, serum CD300LG levels were negatively associated with glucose levels and type 2 diabetes. Genetic studies hinted at these associations possibly being causal. Mice carrying alterations in the CD300LG gene displayed impaired glucose tolerance, but no change in fasting glucose and insulin. Whether the production of CD300LG is changed in the mutant mice is unclear.
Strengths:
The specific proteomics approach conducted to identify novel proteins impacted by exercise training is new. The authors are resourceful in the exploitation of existing datasets to gain additional information on CD300LG.
Weaknesses:
While the analyses of multiple open-source datasets are necessary and useful, they lead to relatively unspecific correlative data that collectively insufficiently advance our knowledge of CD300LG and merely represent the starting point for more detailed investigations. Additional more targeted experiments of CD300LG are necessary to gain a better understanding of the role of CD300LG and the mechanism by which exercise training may influence CD300LG levels. One should also be careful to rely on external data for such delicate experiments as mouse phenotyping. Can the authors vouch for the quality of the data collected?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript presented a useful toolkit designed for CyTOF data analysis, which integrates 5 key steps as an analytical framework. A semi-supervised clustering tool was developed, and its performance was tested in multiple independent datasets. The tool was compared to human experts as well as supervised and unsupervised methods.
Strengths:
The study employed multiple independent datasets to test the pipeline. A new semi-supervised clustering method was developed.
Weaknesses:
The examination of the whole pipeline is incomplete. Lack of descriptions or justifications for some analyses.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study identifies new types of interactions between Drosophila gustatory receptor neurons (GRNs) and shows that these interactions influence sensory responses and behavior. The authors find that HCN, a hyperpolarization-activated cation channel, suppresses the activity of GRNs in which it is expressed, preventing those GRNs from depleting the sensillum potential, and thereby promoting the activity of neighboring GRNs in the same sensilla. HCN is expressed in sugar GRNs, so HCN dampens the excitation of sugar GRNs and promotes the excitation of bitter GRNs. Impairing HCN expression in sugar GRNs depletes the sensillum potential and decreases bitter responses, especially when flies are fed on a sugar-rich diet, and this leads to decreased bitter aversion in a feeding assay. The authors' conclusions are supported by genetic manipulations, electrophysiological recordings, and behavioral assays.
Strengths:
(1) Non-synaptic interactions between neurons that share an extracellular environment (sometimes called "ephaptic" interactions) have not been well-studied, and certainly not in the insect taste system. A major strength of this study is the new insight it provides into how these interactions can impact sensory coding and behavior.
(2) The authors use many different types of genetic manipulations to dissect the role of HCN in GRN function, including mutants, RNAi, overexpression, ectopic expression, and neuronal silencing. Their results convincingly show that HCN impacts the sensillum potential and has both cell-autonomous and nonautonomous effects that go in opposite directions. There are a couple of conflicting or counterintuitive results, but the authors discuss potential explanations.
(3) Experiments comparing flies raised on different food sources suggest an explanation for why the system may have evolved the way that it did: when flies live in a sugar-rich environment, their bitter sensitivity decreases, and HCN expression in sugar GRNs helps to counteract this decrease.
Weaknesses/Limitations:
(1) The genetic manipulations were constitutive (e.g. Ih mutations, RNAi, or misexpression), and depleting Ih from birth could lead to compensatory effects that change the function of the neurons or sensillum. Using tools to temporally control Ih expression could help to confirm the results of this study.
(2) The behavioral experiment shows a striking loss of bitter sensitivity, but it was only conducted for one bitter compound at one concentration. It is not clear how general this effect is. The same is true for some of the bitter GRN electrophysiological experiments that only tested one compound and concentration.
(3) Several experiments using the Gal4/UAS system only show the Gal4/+ control and not the UAS/+ control (or occasionally neither control). Since some of the measurements in control flies seem to vary (e.g., spiking rate), it is important to compare the experimental flies to both controls to ensure that any observed effects are in fact due to the transgene expression.
(4) I was surprised that manipulations of sugar GRNs (e.g. Ih knockdown, Gr64a-f deletion, or Kir silencing) can impact the sensillum potential and bitter GRN responses even in experiments where no sugar was presented. I believe the authors are suggesting that the effects of sugar GRN activity (e.g., from consuming sugar in the fly food prior to the experiment) can have long-lasting effects, but it wasn't entirely clear if this is their primary explanation or on what timescale those long-lasting effects would occur. How much / how long of a sugar exposure do the flies need for these effects to be triggered, and how long do those effects last once sugar is removed?
(5) The authors mention that HCN may impact the resting potential in addition to changing the excitability of the cell through various mechanisms. It would be informative to record the resting potential and other neuronal properties, but this is very difficult for GRNs, so the current study is not able to determine exactly how HCN affects GRN activity.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors demonstrate that it is possible to carry out eQTL experiments for the model eukaryote S. cerevisiae, in "one pot" preparations, by using single-cell sequencing technologies to simultaneously genotype and measure expression. This is a very appealing approach for investigators studying genetic variation in single-celled and other microbial systems, and will likely inspire similar approaches in non-microbial systems where comparable cell mixtures of genetically heterogeneous individuals could be achieved.
Strengths:
While eQTL experiments have been done for nearly two decades (the corresponding author's lab are pioneers in this field), this single-cell approach creates the possibility for new insights about cell biology that would be extremely challenging to infer using bulk sequencing approaches. The major motivating application shown here is to discover cell occupancy QTL, i.e. loci where genetic variation contributes to differences in the relative occupancy of different cell cycle stages. The authors dissect and validate one such cell cycle occupancy QTL, involving the gene GPA1, a G-protein subunit that plays a role in regulating the mating response MAPK pathway. They show that variation at GPA1 is associated with proportional differences in the fraction of cells in the G1 stage of the cell cycle. Furthermore, they show that this bias is associated with differences in mating efficiency.
Weaknesses:
While the experimental validation of the role of GPA1 variation is well done, the novel cell cycle occupancy QTL aspect of the study is somewhat underexploited. The cell occupancy QTLs that are mentioned all involve loci that the authors have identified in prior studies that involved the same yeast crosses used here. It would be interesting to know what new insights, besides the "usual suspects", the analysis reveals. For example, in Cross B there is another large effect cell occupancy QTL on Chr XI that affects the G1/S stage. What candidate genes and alleles are at this locus? And since cell cycle stages are not biologically independent (a delay in G1, could have a knock-on effect on the frequency of cells with that genotype in G1/S), it would seem important to consider the set of QTLs in concert.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
The manuscript investigates the role of the membrane-deforming cytoskeletal regulator protein Abba in cortical development and its potential implications for microcephaly. It is a valuable contribution to the understanding of Abba's role in cortical development. The strengths and weaknesses identified in the manuscript are outlined below:
Clinical Relevance:
The authors identified a patient with microcephaly and a patient with an intellectual disability harboring a mutation in the Abba variant (R671W) adding a clinically relevant dimension to the study.
Mechanistic Insights:
The study offers valuable mechanistic insights into the development of microcephaly by elucidating the role of Abba in radial glial cell proliferation, radial fiber organization, and the migration of neuronal progenitors. The identification of Abba's involvement in the cleavage furrow during cell division, along with its interaction with Nedd9 and positive influence on RhoA activity, adds depth to our understanding of the molecular processes governing cortical development. Though the reported results establish the novel interaction between Abba and Nedd9, the authors have not addressed whether the mutant protein loses this interaction and whether that results in the observed effects.
In Vivo Validation:
The overexpression of mutant Abba protein (R671W) resulting in phenotypic similarities to Abba knockdown effects supports the significance of Abba in cortical development.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This work proposes a new method, DyNetCP, for inferring dynamic functional connectivity between neurons from spike data. DyNetCP is based on a neural network model with a two-stage model architecture of static and dynamic functional connectivity.
This work evaluates the accuracy of the synaptic connectivity inference and shows that DyNetCP can infer the excitatory synaptic connectivity more accurately than a state-of-the-art model (GLMCC) by analyzing the simulated spike trains. Furthermore, it is shown that the inference results obtained by DyNetCP from large-scale in-vivo recordings are similar to the results obtained by the existing methods (jitter-corrected CCG and JPSTH). Finally, this work investigates the dynamic connectivity in the primary visual area VISp and in the visual areas using DyNetCP.
Strengths:
The strength of the paper is that it proposes a method to extract the dynamics of functional connectivity from spike trains of multiple neurons. The method is potentially useful for analyzing parallel spike trains in general, as there are only a few methods (e.g. Aertsen et al., J. Neurophysiol., 1989, Shimazaki et al., PLoS Comput Biol 2012) that infer the dynamic connectivity from spikes. Furthermore, the approach of DyNetCP is different from the existing methods: while the proposed method is based on the neural network, the previous methods are based on either the descriptive statistics (JSPH) or the Ising model.
Weaknesses:
Although the paper proposes a new method, DyNetCP, for inferring the dynamic functional connectivity, its strengths are neither clear nor directly demonstrated in this paper. That is, insufficient analyses are performed to support the usefulness of DyNetCP.
First, this paper attempts to show the superiority of DyNetCP by comparing the performance of synaptic connectivity inference with GLMCC (Figure 2). However, the improvement in the synaptic connectivity inference does not seem to be convincing. While this paper compares the performance of DyNetCP with a state-of-the-art method (GLMCC), there are several problems with the comparison. For example:
(1) This paper focused only on excitatory connections (i.e., ignoring inhibitory neurons).
(2) This paper does not compare with existing neural network-based methods (e.g., CoNNECT: Endo et al. Sci. Rep. 2021; Deep learning: Donner et al. bioRxiv, 2024).
(3) Only a population of neurons generated from the Hodgkin-Huxley model was evaluated.
Thus, the results in this paper are not sufficient to conclude the superiority of DyNetCP in the estimation of synaptic connections. In addition, this paper compares the proposed method with the standard statistical methods Jitter-corrected CCG (Figure 3) and JPSTH (Figure 4). Unfortunately, these results do not show the superiority of the proposed method. It only shows that the results obtained by the proposed method are consistent with those obtained by the existing methods (CCG or JPSTH). This paper also compares the proposed method with standard statistical methods, such as jitter-corrected CCG (Figure 3) and JPSTH (Figure 4). It only shows that the results obtained by the proposed method are consistent with those obtained by the existing methods (CCG or JPSTH), which does not show the superiority of the proposed method.
In summary, although DyNetCP has the potential to infer synaptic connections more accurately than existing methods, the paper does not provide sufficient analysis to make this claim. It is also unclear whether the proposed method is superior to the existing methods for estimating functional connectivity, such as jitter-corrected CCG and JPSTH. Thus, the strength of DyNetCP is unclear.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
A subclass of inhibitory heterotrimeric guanine nucleotide-binding protein subunits, GNAI, has been implicated in sensory hair cell formation, namely the establishment of hair bundle (stereocilia) orientation and staircase formation. However, the former role of hair bundle orientation has only been demonstrated in mutants expressing pertussis toxin, which blocks all GNAI subunits, but not in mutants with a single knockout of any of the Gnai genes, suggesting that there is a redundancy among various GNAI proteins in this role. Using various conditional mutants, the authors concluded that GNAI3 is the primary GNAI proteins required for hair bundle morphogenesis, whereas hair bundle orientation requires both GNAI2 and GNAI3.
Strength
Various compound mutants were generated to decipher the contribution of individual GNAI1, GNAI2, GNAI3 and GNAIO in the establishment of hair bundle orientation and morphogenesis. The study is thorough with detailed quantification of hair bundle orientation and morphogenesis, as well as auditory functions.
The revised manuscript has clarified the phenotypic differences raised between the Gnai2/3 double mutants and Ptx mutant phenotypes and resolved the weakness pointed out in the previous submission. These results further illustrate the dynamic requirement of Gnai/O in hair bundle establishment and is an important contribution to the field.
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arxiv.org arxiv.org
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Reviewer #2 (Public Review):
In this manuscript, the authors analyze the shapes of cerebral cortices from several primate species, including subgroups of young and old humans, to characterize commonalities in patterns of gyrification, cortical thickness, and cortical surface area. The authors state that the observed scaling law shares properties with fractals, where shape properties are similar across several spatial scales. One way the authors assess this is to perform a "cortical melting" operation that they have devised on surface models obtained from several primate species. The authors also explore differences in shape properties between brains of young (~20 year old) and old (~80) humans. A challenge the authors acknowledge struggling with in reviewing the manuscript is merging "complex mathematical concepts and a perplexing biological phenomenon." This reviewer remains a bit skeptical about whether the complexity of the mathematical concepts being drawn from are justified by the advances made in our ability to infer new things about the shape of the cerebral cortex.
(1) The series of operations to coarse-grain the cortex illustrated in Figure 1 produces image segmentations that do not resemble real brains. The process to assign voxels in downsampled images to cortex and white matter is biased towards the former, as only 4 corners of a given voxel are needed to intersect the original pial surface, but all 8 corners are needed to be assigned a white matter voxel. The reason for introducing this bias (and to the extent that it is present in the authors' implementation) is not provided. The authors provide an intuitive explanation of why thickness relates to folding characteristics, but ultimately an issue for this reviewer is, e.g., for the right-most panel in Figure 2b, the cortex consists of several 4.9-sided voxels and thus a >2 cm thick cortex. A structure with these morphological properties is not consistent with the anatomical organization of typical mammalian neocortex.
(2) For the comparison between 20-year-old and 80-year-old brains, a well-documented difference is that the older age group possesses more cerebral spinal fluid due to tissue atrophy, and the distances between the walls of gyri becomes greater. This difference is born out in the left column of Figure 4b. It seems this additional spacing between gyri in 80 year olds requires more extensive down-sampling (larger scale values in Figure 4a) to achieve a similar shape parameter K as for the 20 year olds. The authors assert that K provides a more sensitive measure (associated with a large effect size) than currently used ones for distinguishing brains of young vs. old people. A more explicit, or elaborate, interpretation of the numbers produced in this manuscript, in terms of brain shape, might make this analysis more appealing to researchers in the aging field.
(3) In the Discussion, it is stated that self-similarity, operating on all length scales, should be used as a test for existing and future models of gyrification mechanisms. Given the lack of association between the abstract mathematical parameters described in this study and explicit properties of brain tissue and its constituents, it is difficult to envision how the coarse-graining operation can be used to guide development of "models of cortical gyrification."
(4) There are several who advocate for analyzing cortical mid-thickness surfaces, as the pial surface over-represents gyral tips compared to the bottoms of sulci in the surface area. The authors indicate that analyses of mid-thickness representations will be taken on in future work, but this seems to be a relevant control for accepting the conclusions of this manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this study, Lin et al developed a protocol termed HIF-Clear, to perform tissue clearing and labelling on large-scale FFPE mouse brain specimens. They have optimized protocols for dewaxing and adequate delipidation of FFPE tissues to enable deep immunolabelling, even for whole mouse brains. This was useful for the study of disease models such as in an astrocytoma model to evaluate spatial architecture of the tumour and its surrounding microenvironment. It was also used in a traumatic brain injury model to quantify changes in vasculature density and differences in monoaminergic innervation. They have also demonstrated the potential of multi-round immunolabelling using photobleaching, as well as expansion microscopy with FFPE samples using Hif Clear.
Comments on revised version:
The revised manuscript by Lin et al is much improved with a more detailed methods description. There are only a few minor comments for the authors that are still valid:
- Some procedures, including the basic HIF-Clear protocol, seem to produce marked tissue expansion that is not mentioned in the manuscript. Users should take this fact into consideration when making measurements.<br /> - The authors have provided a comparison between mouse and human brain samples in Figure S12. However, it is misleading to mention that the "fluorescent signals are comparable at varying depth" as the figure clearly showed a lack of continuous staining especially for SMI312 at 900um depth, and human brain tissue showed considerably increased background signal (likely due to endogenous lipofuscin which has autofluorescent properties). Also, This is difficult to assess in the present design of the experiment because, at different depths, the tissue and the antigen may change themselves... making it difficult to make a direct staining comparison with other depths.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Working memory is imperfect - memories accrue errors over time and are biased towards certain identities. For example, previous work has shown memory for orientation is more accurate near the cardinal directions (i.e., variance in responses is smaller for horizontal and vertical stimuli) while being biased towards diagonal orientations (i.e., there is a repulsive bias away from horizontal and vertical stimuli). The magnitude of errors and biases increase the longer an item is held in working memory and when more items are held in working memory (i.e., working memory load is higher). Previous work has argued that biases and errors could be explained by increased perceptual acuity at cardinal directions. However, these models are constrained to sensory perception and do not explain how biases and errors increase over time in memory. The current manuscript builds on this work to show how a two-layer neural network could integrate errors and biases over a memory delay. In brief, the model includes a 'sensory' layer with heterogenous connections that lead to the repulsive bias and decreased error in the cardinal directions. This layer is then reciprocally connected with a classic ring attractor layer. Through their reciprocal interactions, the biases in the sensory layer are constantly integrated into the representation in memory. In this way, the model captures the distribution of biases and errors for different orientations that have been seen in behavior and their increasing magnitude with time. The authors compare the two-layer network to a simpler one-network model, showing that the one-model network is harder to tune and shows an attractive bias for memories that have lower error (which is incompatible with empirical results).
Strengths:
The manuscript provides a nice review of the dynamics of items in working memory, showing how errors and biases differ across stimulus space. The two-layer neural network model is able to capture the behavioral effects as well as relate to neurophysiological observations that memory representations are distributed across the sensory cortex and prefrontal cortex.
The authors use multiple approaches to understand how the network produces the observed results. For example, analyzing the dynamics of memories in the low-dimensional representational space of the networks provides the reader with an intuition for the observed effects.
As a point of comparison with the two-layer network, the authors construct a heterogenous one-layer network (analogous to a single memory network with embedded biases). They argue that such a network is incapable of capturing the observed behavioral effects but could potentially explain biases and noise levels in other sensory domains where attractive biases have lower errors (e.g., color).
The authors show how changes in the strength of Hebbian learning of excitatory and inhibitory synapses can change network behavior. This argues for relatively stronger learning in inhibitory synapses, an interesting prediction.
The manuscript is well-written. In particular, the figures are well done and nicely schematize the model and the results.
Weaknesses:
Despite its strengths, the manuscript does have some weaknesses.
First, as far as we can tell, behavioral data is only presented in schematic form. This means some of the nuances of the effects are lost. It also means that the model is not directly capturing behavioral effects. Therefore, while providing insight into the general phenomenon, the current manuscript may be missing some important aspects of the data.
Relatedly, the models are not directly fit to behavioral data. This makes it hard for the authors to exclude the possibility that there is a single network model that could capture the behavioral effects. In other words, it is hard to support the authors' conclusion that "....these evolving errors...require network interaction between two distinct modules." (from the abstract, but similar comments are made throughout the manuscript). Such a strong claim needs stronger evidence than what is presented. Fitting to behavioral data could allow the authors to explore the full parameter space for both the one-layer and two-layer network architectures.
In addition, directly comparing the ability of different model architectures to fit behavioral data would allow for quantitative comparison between models. Such quantitative comparisons are currently missing from the manuscript.
To help broaden the impact of the paper, it would be helpful if the authors provided insight into how the observed behavioral biases and/or network structures influence cognition. For example, previous work has argued that biases may counteract noise, leading to decreased variance at certain locations. Is there a similar normative explanation for why the brain would have repulsive biases away from commonly occurring stimuli? Are they simply a consequence of improved memory accuracy? Why isn't this seen for all stimulus domains?
Previous work has found both diffusive noise and biases increase with the number of items in working memory. It isn't clear how the current model would capture these effects. The authors do note this limitation in the Discussion, but it remains unclear how the current model can be generalized to a multi-item case.
The role of the ring attractor memory network isn't completely clear. There is noise added in this stage, but how is this different from the noise added at the sensory stage? Shouldn't these be additive? Is the noise necessary? Similarly, it isn't clear whether the memory network is necessary - can it be replaced by autapses (self-connections) in the sensory network to stabilize its representation? In short, it would be helpful for the authors to provide an intuition for why the addition of the memory network facilitates the repulsive bias.
Overall:
Overall, the manuscript was successful in building a model that captured the biases and noise observed in working memory. This work complements previous studies that have viewed these effects through the lens of optimal coding, extending these models to explain the effects of time in memory. In addition, the two-layer network architecture extends previous work with similar architectures, adding further support to the distributed nature of working memory representations.
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Reviewer #1 (Public Review):
Summary:
A cortico-centric view is dominant in the study of the neural mechanisms of consciousness. This investigation represents the growing interest in understanding how subcortical regions are involved in conscious perception. To achieve this, the authors engaged in an ambitious and rare procedure in humans of directly recording from neurons in the subthalamic nucleus and thalamus. While participants were in surgery for the placement of deep brain stimulation devices for the treatment of essential tremor and Parkinson's disease, they were awakened and completed a perceptual-threshold tactile detection task. The authors identified individual neurons and analyzed single-unit activity corresponding with the task phases and tactile detection/perception. Among the neurons that were perception-responsive, the authors report changes in firing rate beginning ~150 milliseconds from the onset of the tactile stimulation. Curiously, the majority of the perception-responsive neurons had a higher firing rate for missed/not perceived trials. In summary, this investigation is a valuable addition to the growing literature on the role of subcortical regions in conscious perception.
Strengths:
The authors achieved the challenging task of recording human single-unit activity while participants performed a tactile perception task. The methods and statistics are clearly explained and rigorous, particularly for managing false positives and non-normal distributions. The results offer new detail at the level of individual neurons in the emerging recognition of the role of subcortical regions in conscious perception.
Weaknesses:
"Nonetheless, it remains unknown how the firing rate of subcortical neurons changes when a stimulus is consciously perceived." (lines 76-77) The authors could be more specific about what exactly single-unit recordings offer for interrogating the role of subcortical regions in conscious perception that is unique from alternative neural activity recordings (e.g., local field potential) or recordings that are used as proxies of neural activity (e.g., fMRI).
Related comment for the following excerpts:
"After a random delay ranging from 0.5 to 1 s, a "respond" cue was played, prompting participants to verbally report whether they felt a vibration or not. Therefore, none of the reported analyses are confounded by motor responses." (lines 97-99).
"These results show that subthalamic and thalamic neurons are modulated by stimulus onset, irrespective of whether it was reported or not, even though no immediate motor response was required." (lines 188-190).
"By imposing a delay between the end of the tactile stimulation window and the subjective report, we ensured that neuronal responses reflected stimulus detection and not mere motor responses." (lines 245-247).
It is a valuable feature of the paradigm that the reporting period was initiated hundreds of milliseconds after the stimulus presentation so that the neural responses should not represent "mere motor responses". However, verbal report of having perceived or not perceived a stimulus is a motor response and because the participants anticipate having to make these reports before the onset of the response period, there may be motor preparatory activity from the time of the perceived stimulus that is absent for the not perceived stimulus. The authors show sensitivity to this issue by identifying task-selective neurons and their discussion of the results that refer to the confound of post-perceptual processing. Still, direct treatment of this possible confound would help the rigor of the interpretation of the results.
"When analyzing tactile perception, we ensured that our results were not contaminated with spurious behavior (e.g. fluctuation of attention and arousal due to the surgical procedure)." (lines 118-117).
Confidence in the results would be improved if the authors clarified exactly what behaviors were considered as contaminating the results (e.g., eye closure, saccades, and bodily movements) and how they were determined.
The authors' discussion of the thalamic neurons could be more precise. The authors show that only certain areas of the thalamus were recorded (in or near the ventral lateral nucleus, according to Figure S3C). The ventral lateral nucleus has a unique relationship to tactile and motor systems, so do the authors hypothesize these same perception-selective neurons would be active in the same way for visual, auditory, olfactory, and taste perception? Moreover, the authors minimally interpret the location of the task, sensory, and perception-responsive neurons. Figure S3 suggests these neurons are overlapping. Did the authors expect this overlap and what does it mean for the functional organization of the ventral lateral nucleus and subthalamic nucleus in conscious perception?
"We note that, 6 out of 8 neurons had higher firing rates for missed trials than hit trials, although this proportion was not significant (binomial test: p = 0.145)." (lines 215-216).
It appears that in the three example neurons shown in Figure 4, 2 out of 3 (#001 and #068) show a change in firing rate predominantly for the missed stimulations. Meanwhile, #034 shows a clear hit response (although there is an early missed response - decreased firing rate - around 150 ms that is not statistically significant). This is a counterintuitive finding when compared to previous results from the thalamus (e.g., local field potentials and fMRI) that show the opposite response profile (i.e., missed/not perceived trials display no change or reduced response relative to hit/perceived trials). The discussion of the results should address this, including if these seemingly competing findings can be rectified.
The authors report 8 perception-responsive neurons, but there are only 5 recording sites highlighted (i.e., filled-in squares and circles) in Figures S3C and 4D. Was this an omission or were three neurons removed from the perception-responsive analysis?
Could the authors speak to the timing of the responses reported in Figure 4? The statistically significant intervals suggested both early (~160-200ms) to late responses (~300ms). Some have hypothesized that subcortical regions are early - ahead of cortical activation that may be linked with conscious perception. Do these results say anything about this temporal model for when subcortical regions are active in conscious perception?
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Reviewer #1 (Public Review):
Summary:
People with Parkinson's disease often experience a variety of nonmotor symptoms, the biological bases of which remain poorly understood. Johansson et al began to study potential roles of the dorsal raphe nucleus (DRN) degeneration in the pathophysiology of neuropsychiatric symptoms in PD.
Strengths:
Boi et al validated a transgenic reporter mouse line that can reliably label dopaminergic neurons in the DRN. This brain region shows severe neurodegeneration and has been proposed to contribute to the manifestation of neuropsychiatric symptoms in PD. Using this mouse line (and others), Boi and colleagues characterized electrophysiological and morphological phenotypes of dopaminergic and serotoninergic neurons in the raphe nucleus. This study involved very careful topographical registration of recorded neurons to brain slices for post hoc immunohistochemical validation of cell identity, making it an elegant and thorough piece of work.
In relevance to PD pathophysiology, the authors evaluated the physiological and morphological changes of DRN serotoninergic and dopaminergic neurons after a partial loss of nigrostriatal dopamine neurons, which serves as a mouse model of early parkinsonian pathology. Moreover, the authors identified a series of physiological and morphological changes of subtypes of DRN neurons that depend on nigral dopaminergic neurodegeneration, LC noradrenergic neurodegeneration, or both. Indeed this works highlights the importance of LC noradrenergic degeneration in PD pathophysiology.
Overall, this is a well-designed study with high significance to the Parkinson's research field.
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Reviewer #1 (Public Review):
Summary:
This is a study on the role of the retrosplenial cortex (RSC) and the hippocampus in working memory. Working memory is a critical cognitive function that allows temporary retention of information for task execution. The RSC, which is functionally and anatomically connected to both primary sensory (especially visual) and higher cognitive areas, plays a key role in integrating spatial-temporal context and in goal-directed behaviors. However, the specific contributions of the RSC and the hippocampus in working memory-guided behaviors are not fully understood due to a lack of studies that experimentally disrupt the connection between these two regions during such behaviors.
In this study, researchers employed eArch3.0 to silence hippocampal axon terminals in the RSC, aiming to explore the roles of these brain regions in working memory. Experiments were conducted where animals with silenced hippocampal axon terminals in the RSC performed a delayed non-match to place (DNMP) task. The results indicated that this manipulation impaired memory retrieval, leading to decreased performance and quicker decision-making in the animals. Notably, the authors observed that the effects of this impairment persisted beyond the light-activation period of the opsin, affecting up to three subsequent trials. They suggest that disrupting the hippocampal-RSC connection has a significant and lasting impact on working memory performance.
Strengths:
They conducted a study exploring the impact of direct hippocampal inputs into the RSC, a region involved in encoding spatial-temporal context and transferring contextual information, on spatial working memory tasks. Utilizing eArch3.0 expressed in hippocampal neurons via the viral vector AAV5-hSyn1-eArch3.0, they aimed to bilaterally silence hippocampal terminals located at the RSC in rats pre-trained in a DNMP task. They discovered that silencing hippocampal terminals in the RSC significantly decreased working memory performance in eArch+ animals, especially during task interleaving sessions (TI) that alternated between trials with and without light delivery. This effect persisted even in non-illuminated trials, indicating a lasting impact beyond the periods of direct manipulation. Additionally, they observed a decreased likelihood of correct responses following TI trials and an increased error rate in eArch+ animals, even after incorrect responses, suggesting an impairment in error-corrective behavior. This contrasted with baseline sessions where no light was delivered, and both eArch+ and control animals showed low error rates.
Weaknesses:
While I agree with the authors that the role of hippocampal inputs to the RSC in spatial working memory is understudied and merits further investigation, I find that the optogenetic experiment, a core part of this manuscript that includes viral injections, could be improved. The effects were rather subtle, rendering some of the results barely significant and possibly too weak to support major conclusions. Additionally, no mechanistic investigation was conducted beyond referencing previous reports to interpret the core behavioral phenotypes.
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Reviewer #1 (Public Review):
Summary:
The manuscript entitled "Staphylococcus aureus counters organic acid anion-mediated inhibition of peptidoglycan cross-linking through robust alanine racemase activity" by Panda, S et al. reports an extensive biochemical analysis of the result from a Tn screen that identified alr1 as being required for acetic acid tolerance. In the end, they demonstrate that reduced D-Ala pools in the ∆alr1 mutant lead to a drastic reduction in D-Ala-D-Ala dipeptide. They show that this is due to the ability of organic acid anions to limit the D-Ala-D-Ala ligase enzyme Ddl. They demonstrate that:
(1) Acetate exposure in the ∆alr1 results in reduced D-Ala-D-Ala dipeptide, but not the monomers.
(2) Acetate can bind to purified Ddl in vitro.
(3) This binding results in reduced enzyme activity.
(4) Other organic acid anions such as lactate, proprionate, and itaconitate can also inhibit Ddl.
The experiments are clearly described and logically laid out. I have only a few minor comments to add.
Strengths:
The most significant strength is the exceptional experimental data that supports the authors' hypotheses.
Weaknesses:
Only minor weaknesses were identified by this reviewer.
(1) Which allele is alr1, the one upstream of MazEF or the one in the Lysine biosynthetic operon?
(2) Figure 3B. Where does the C3N2 species come from in the WT and why is it absent in the mutants? It is about 25% of the total dipeptide pool.
(3) Figure 3D could perhaps be omitted. I understand that the authors attained statistical significance in the fitness defect, but biologically this difference is very minor. One would have to look at the isotopomer distribution in the Dat overexpressing strain to make sure that increased flux actually occurred since there are other means of affecting activity (e.g. allosteric modulators).
(4) In Figure 4A, why is the complete subunit UDP-NAM-AEKAA increasing in each strain upon acetate challenge if there was such a stark reduction in D-Ala-D-Ala, particularly in the ∆alr1 mutant? For that matter, why are the levels of UDP-NAM-AEKAA in the ∆alr1 mutant identical to that of WT with/out acetate?
(5) Figure 4B. Is there no significant difference between ddl and murF transcripts between WT and ∆alr1 under acetate stress? This comparison was not labeled if the tests were done.
(6) Although tricky, it is possible to measure intracellular acetate. It might be of interest to know where in the Ddl inhibition curve the cells actually are.
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Reviewer #2 (Public Review):
The authors aimed at elucidating the development of high altitude polycythemia which affects mice and men staying in a hypoxic atmosphere at high altitude (hypobaric hypoxia; HH). HH causes increased erythropoietin production which stimulates the production of red blood cells. The authors hypothesize that increased production is only partially responsible for exaggerated red blood cell production, i.e. polycythemia, but that decreased erythrophagocytosis in the spleen contributes to high red blood cells counts.
The main strength of the study is the use of a mouse model exposed to HH in a hypobaric chamber. However, not all of the reported results are convincing due to some smaller effects which one may doubt to result in the overall increase in red blood cells as claimed by the authors. Moreover, direct proof for reduced erythrophagocytosis is compromised due to a strong spontaneous loss of labelled red blood cells, although effects of labelled E. coli phagocytosis are shown.
Comments on latest version:
The authors have partly addressed my comments.
(1) The response to my question regarding unchanged MCH is a kind of "hand waiving" - maybe it would require substantially more extensive work to clarify this issue
(2) The moderate if not marginal difference in normal vs splenectomy argues against a significant role of the spleen - even if the difference was slightly larger in HH
(3) There is still overinterpretation of data. My Q was: Is the reduced phagocytic capacity in Fig 4B significant? Response: "This is indicative of a diminished phagocytic capacity, particularly when contrasted<br /> with NN conditions." I guess that is a "no"
(4) I assume my question with respect to bi- or trivalent iron chelators was misunderstood.
In general, as indicated above, it is an interesting hypothesis which is corroborated by data in several instances. Maybe the scientific community should decide whether it is all in all conclusive.
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Reviewer #1 (Public Review):
A descriptive manuscript investigating the ability of a peptide, implicated in development, to induce signalling responses indicative of immunity. The work clearly documents the ability of the synthetic peptide to induce these responses, and open future work to link this back to physiology.
Comments on revised version:
Congratulations to the authors for the improvements to the manuscript.
I still have reservations, as raised by other reviewers, about whether the outputs observed can definitively be classified as immune/defence outputs without assaying an impact upon microbial growth. Indeed, this is challenging to address as many of the outputs are shared by multiple pathways. This is especially the case here as the peptide could have different effects in different tissues or cells with different expression levels of the receptors (e.g. hypothetically - no expression = no effect; weak expression - cell wall loosening and susceptibility; high expression - strong response and 'defence' response). I do however appreciate that the authors have toned down some of the conclusions regarding the defence response and also they included further reference to outputs also being from developmental pathways.
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Reviewer #1 (Public Review):
This study presents valuable data on effector proteins (=virulence factors) used by the bacterial pathogen Legionella pneumophila that target host vesicle trafficking GTPases during infection. The evidence supporting the claims of the authors is robust, and the data suggest a sophisticated interplay between multiple effectors with the goal of temporarily exploiting host cell Rab10 during infection.
The authors have done a nice job addressing my earlier concerns. I have no further criticism about the revised paper.
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Reviewer #1 (Public Review):
Summary:
This study brings new information about the function of serotonin-gated ion channels 5-HT3AR, by describing the conformational changes undergoing during ligands binding. These results can be potentially extrapolated to other members of the Cys-loop ligand-gated ion channels. By combining fluorescence microscopy with electrophysiological recordings, the authors investigate structural changes inside and outside the orthosteric site elicited by agonists, partial agonists, and antagonists. The results are convincing and correlate well with the observations from cryo-EM structures. The work will be of important significance and broad interest to scientists working on channel biophysics but also drug development targeting ligand-gated ion channels.
Strengths:
The authors present an elegant and well-designed study to investigate the conformational changes on 5-HT3AR where they combine electrophysiological and fluorometry recordings. They determined four positions suitable to act as sensors for the conformational changes of the receptor: two inside and two outside the agonist binding site. They make a strong point showing how antagonists produce conformational changes inside the orthosteric site similarly as agonists do but they failed to spread to the lower part of the ECD, in agreement with previous studies and Cryo-EM structures. They also show how some loss-of-function mutant receptors elicit conformational changes (changes in fluorescence) after partial agonist binding but failed to produce measurable ionic currents, pointing to intermediate states that are stabilized in these conditions. The four fluorescence sensors developed in this study may be good tools for further studies on characterizing drugs targeting the 5-HT3R. The major conclusions of the manuscript seem well justified.
Weaknesses:
Weaknesses have been very well addressed during the review process.
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Joint Public Review:
Summary:
This important manuscript investigates a subpopulation of glutamatergic neurons in the suprammamillary nucleus that projects to the pre-optic hypothalamus area (SuM-VGLUT2+::POA). First, they define the neural circuitry of these neurons, which contact many stress/threat-associated brain regions. Then they employ fibre photometry to measure the activity of these neurons during various threatening tasks and find the responses correlate well with threat stimuli. Finally, they stimulate these neurons and find multiple lines of evidence that mice find this aversive and will act to avoid receiving this stimulation. In sum, they provide solid evidence that this neuronal population represents a new node in stress response circuitry that allows the animal to produce flexible behaviours in response to stress, which will be of interest to neuroscientists across several sub-fields.
Strengths:
Overall this is a solid manuscript tackling an important question. Coping with stress by an animal in danger is essential for survival. This manuscript identifies a novel population of neurons in the murine supramamillary nucleus (SuM) projecting to the pre-optic hypothalamus area among other regions that is involved in this important process. The evidence to support the conclusions is solid.
Specific strengths:
• The topic is novel.
• The manuscript follows a logical structure and neatly moves through the central story. Several potential alternate interpretations are well-controlled for.
• The manuscript employs an array of different tasks to provide converging evidence for their conclusions.
• The authors provide excellent evidence of the specificity of the function of this neuronal population, both from anatomical studies and from behavioural studies (e.g. demonstrating that activity of gabaergic neurons in the same region does not correlate with behaviours in the same way).
• The study is well-powered (sample sizes are good) and the effects are convincing.
Weaknesses:
* Not all of the reviewer comments were addressed in the manuscript itself, although this was acknowledged in the author's responses to reviewers. One key example is as follows:
* The authors did not entirely address comments related to rigor but they at least acknowledged it. For example, in multiple places they argue that WT, purchased mice are probably not different in baseline behavior compared to Vgltu2-IRES-Cre because it is unlikely that adding the IRES-Cre will change behavior. However, they do not acknowledge that transgenic lines are not from the exact same genetic background and generation number, and there is ample evidence in the literature that transgenic mice on a B6J background can differ in basal phenotypes from one another and B6J. In one place they show some basal behavior, at least in heat map form though not quantified. Had the authors decided to apply this more pervasively, it would have made the story even more compelling in terms of a stress/threat-induced phenotype.
Comments on revised version from the Reviewing Editor:
The authors have done a thorough job of answering the reviewer queries, and a good job of explaining why they have not answered a particular point. Indeed, there is so much additional information in response to the reviewers that I hope readers of the manuscript will read the reviews and responses as well! I think they add a lot.
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Reviewer #1 (Public Review):
Summary:
The authors describe that the endocytic pathway is crucial for ColI fibrillogenesis. ColI is endocytosed by fibroblasts, prior to exocytosis and formation of fibrils, which can include a mixture of endogenous/nascent ColI chains and exogenous ColI. ColI uptake and fibrillogenesis are regulated by circadian rhythm as described by the authors in 2020, thanks to the dependence of this pathway on circadian-clock-regulated protein VPS33B. Cells are capable of forming fibrils with recently endocytosed ColI when nascent chains are not available. Previously identified VPS33B is demonstrated not to have a role in endocytosis of ColI, but to play a role in fibril formation, which the authors demonstrate by showing the loss of fibril formation in VPS33B KO, and an excess of insoluble fibrils - along-side a decrease in soluble ColI secretion - in VPS33B overexpression conditions. A VPS33B binding protein VIPAS39 is also shown to be required for fibrillogenesis and to colocalise with ColI. The authors thus conclude that ColI is internalised into endosomal structures within the cell, and that ColI, VPS33B, and VIPA39 are co-trafficked to the site of fibrillogenesis, where along with ITGA11, which by mass spectrometric analysis is shown to be regulated by VPS33B levels, ColI fibrils are formed. Interestingly, in involved human skin sections from idiopathic pulmonary fibrosis (IPF) patients, ITGA11 and VPS33B expression is increased compared to healthy tissue, while in patient-derived fibroblasts, uptake of fluorescently-labelled ColI is also increased. This suggests that there may be a significant contribution of endocytosis-dependent fibrillogenesis in the formation of fibrotic and chronic wound-healing diseases in humans.
Strengths:
This is an interesting paper that contributes an exciting novel understanding of the formation of fibrotic disease, which despite its high occurrence, still has no robust therapeutic options. The precise mechanisms of fibrillogenesis are also not well understood, so a study devoted to this complex and key mechanism is well appreciated. The dependence of fibrillogenesis on VPS33B and VIPA39 is convincing and robust, while the distinction between soluble ColI secretion and insoluble fibrillar ColI is interesting and informative.
Weaknesses:
There are a number of limitations to this study in its current state. Inhibition of ColI uptake is performed using Dyngo4a, which although proposed as an inhibitor of Clathrin-dependent endocytosis is known to be quite un-specific. This may not be a problem however, as the endocytic mechanism for ColI also does not seem to be well defined in the literature, in fact, the principle mechanism described in the papers referred to by the authors is that of phagocytosis. It would be interesting to explore this important part of the mechanism further, especially in relation to the intracellular destination of ColI. The circadian regulation does not appear as robust as the authors' last paper, however, there could be a larger lag between endocytosis of ColI and realisation of fibrils. The authors state that the endocytic pathway is the mechanism of trafficking and that they show ColI, VPS33B, and VIPA39 are co-trafficked. However, the only link that is put forward to the endosomes is rather tenuously through VPS33B/VIPA39. There is no direct demonstration of ColI localisation to endosomes (ie. immunofluorescence), and this is overstated throughout the text. Demonstrating the intracellular trafficking and localisation of ColI, and its actual relationship to VPS33B and VIPA39, followed by ITGA11, would broaden the relevance of this paper significantly to incorporate the field of protein trafficking. Finally, the "self-formation" of ColI fibrils is discussed in relation to the literature and the concentration of fluorescently-tagged ColI, however as the key message of the paper is the fibrillogenesis from exocytosed colI, I do not feel like it is demonstrated to leave no doubt. Specific inhibition of intracellular trafficking steps, or following the progressive formation of ColI fibrils over time by immunofluorescence would demonstrate without any further doubt that ColI must be endocytosed first, to form fibrils as a secondary step, rather than externally-added ColI being incorporated directly to fibrils, independent of cellular uptake.
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Reviewer #1 (Public Review):
Summary:
The authors quantitatively describe the complex binding equilibria of BRAF and its inhibitors resulting in some cases in the paradoxical activation of BRAF dimer when bound to ATP competitive inhibitors. The authors use a biophysical tour de force involving FRET binding assays, NMR, kinase activity assays, and DEER spectroscopy.
Strengths:
The strengths of the study are the beautifully conducted assays that allow for a thorough characterization of the allostery in this complex system. Additionally, the use of F-NMR and DEER spectroscopy provides important insights into the details of the process.
The resulting model for binding of inhibitors and dimerization (Figure 4) is very helpful.
Weaknesses:
This is a complex system and its communication is inherently challenging. It might be of interest to the broader readership to understand the implications of the model for drug development and therapy.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Szathmary and colleagues explore the parabolic growth regime of replicator evolution. Parabolic growth occurs when nucleic acid strain separation is the rate limiting step of the replication process which would have been the case for non-enzymatic replication of short oligonucleotide that could precede the emergence of ribozyme polymerases and helicases. The key result is that parabolic replication is conducive to the maintenance of genetic diversity, that is, coexistence of numerous master sequences (the Gause principle does not apply). Another important finding is that there is no error threshold for parabolic replication except for the extreme case of zero fidelity.
Strengths:
I find both the analytic and the numerical results to be quite convincing and well described. The results of this work are potentially important because they reveal aspects of a realistic evolutionary scenario for the origin of replicators.
Weaknesses:
There are no obvious technical weaknesses. It can be argued that the results represent an incremental advance because many aspects of parabolic replication have been explored previously (the relevant publications are properly cited). Obviously, the work is purely theoretical, experimental study of parabolic replication is due. In the opinion of this reviewer, though, these are understandable limitations that do not actually detract from the value of this work.
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Reviewer #1 (Public Review):
This paper identifies GABA cells in the preoptic hypothalamus and others in the posterior hypothalamus which are involved in REM sleep rebound (the increase in REM sleep) after selective REM sleep deprivation. By calcium photometry, these preoptic cells are most active during REM, and show more calcium signals during REM deprivation, suggesting they respond to "REM pressure". Inhibiting these cells ontogenetically diminishes REM sleep. The optogenetic and photometry work is carried out to a high standard, the paper is well written, and the findings are interesting and enhance our understanding of REM sleep regulation. The new findings make it clear that as for the circuitry that regulates NREM sleep, REM sleep circuitry is also quite distributed in the brain. It is unclear if there is a true "REM center". The study of mechanisms of catching up on lost sleep (sleep homeostasis), has previously focused on NREM sleep, where various circuits have been identified. That there is a special mechanism that also tracks time awake and compensates with REM sleep is intriguing.
In a broader context, the existence of REM rebound suggests that REM sleep must have a function, otherwise why catch up on it. There is a lot of literature that suggests REM contributes to emotional processing, for example. The new findings deepen our appreciation of REM regulation. As REM sleep is often disturbed in stress (e.g. post-traumatic stress disorder) and in depression, understanding more about REM regulation could ultimately aid treatments for people living with these conditions.
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Reviewer #2 (Public Review):
Summary:
The authors describe and quantify a phenomenon in the CA1 and CA3 of the hippocampus that they call aberrant Ca2+ micro-waves. Micro-waves are sometimes seen during 2-photon calcium imaging of populations of neurons under certain conditions. They are spatially confined slow calcium events that start in a few cells and slowly spread to neighboring groups of cells. This phenomenon has been uttered between researchers in the field at conferences, but no one has taken the time to carefully capture and quantify micro-waves and pin down the causes. The authors show that micro-waves are dependent on the viral titre of the genetically encoded calcium indicators (GECIs), the genetic promoter (synapsin), the neuronal subtype (granule cells in the dentate gyrus do not produce micro-waves and they are not seen in the neocortex), and the density of GECI expression. The authors should be commended for their work and for raising awareness to all labs doing any form of calcium imaging in populations of neurons. The authors also come up with alternative approaches to avoid artifactual micro-waves such as reducing the transduction titre (1:2 dilution of virus) and a transduction method employing sparser and cre-dependent GECI expression in principal cells using a CaMKII promoter.
Strengths:
The micro-waves reported in the paper were robustly observed across 4 laboratories and 3 different countries with various experimenters and calcium imaging set-ups. This adds significant strength to the work.
The age of mice used covered a broad range (from 6 to 43 weeks). This is a strength because it covers most ages that are used in labs that regularly do calcium imaging.
Another strength is they used different GCaMP variants (GCaMP6m, GCaMP6s, GCaMP7f), as well as a red indicator: RCaMP. This shows the micro-waves are not an issue with any particular GECI, as the authors suggest.
The authors include many movies of micro-waves. This is extremely useful for researchers in the field to view them in real-time so they can identify them in their own data.
They provide a useful table with specific details of the virus injected, titre, dilution, and other information along with the incidence of micro-waves. A nice look-up table for researchers to see if their viral strategy is associated with a high or low incidence of micro-waves.
Weaknesses:
The effect of mico-waves on single cell function was not analyzed. It would be useful, for example, if we knew the influence of micro-waves on place fields. Can a place cell still express a place field in a hippocampus that produces micro-waves? What effect might a microwave passing over a cell have on its place field? Mice were not trained in these experiments, so the authors do not have the data. However, they do briefly discuss these ideas.
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Reviewer #1 (Public Review):
The manuscript by Oleh et al. uses in vitro electrophysiology and compartmental modeling (via NEURON) to investigate the expression and function of HCN channels in mouse L2/3 pyramidal neurons. The authors conclude that L2/3 neurons have developmentally regulated HCN channels, the activation of which can be observed when subjected to large hyperpolarizations. They further conclude via blockade experiments that HCN channels in L2/3 neurons influence cellular excitability and pathway-specific EPSP kinetics, which can be neuromodulated. While the authors perform a wide range of slice physiology experiments, concrete evidence that L2/3 cells express functionally relevant HCN channels is limited. There are serious experimental design caveats and confounds that make drawing strong conclusions from the data difficult. Furthermore, the significance of the findings is generally unclear, given modest effect sizes and a lack of any functional relevance, either directly via in vivo experiments or indirectly via strong HCN-mediated changes in known operations/computations/functions of L2/3 neurons.
Specific points:
(1) The interpretability and impact of this manuscript are limited due to numerous methodological issues in experimental design, data collection, and analysis. The authors have not followed best practices in the field, and as such, much of the data is ambiguous and/or weak and does not support their interpretations (detailed below). Additionally, the authors fail to appropriately explain their rationale for many of their choices, making it difficult to understand why they did what they did. Furthermore, many important references appear to be missing, both in terms of contextualizing the work and in terms of approach/method. For example, the authors do not cite Kalmbach et al 2018, which performed a directly comparable set of experiments on HCN channels in L2/3 neurons of both humans and mice. This is an unacceptable omission. Additionally, the authors fail to cite prior literature regarding the specificity or lack thereof of Cs+ in blocking HCN. In describing a result, the authors state "In line with previous reports, we found that L2/3 PCs exhibited an unremarkable amount of sag at 'typical' current commands" but they then fail to cite the previous reports.
(2) A critical experimental concern in the manuscript is the reliance on cesium, a nonspecific blocker, to evaluate HCN channel function. Cesium blocks HCN channels but also acts at potassium channels (and possibly other channels as well). The authors do not acknowledge this or attempt to justify their use of Cs+ and do not cite prior work on this subject. They do not show control experiments demonstrating that the application of Cs+ in their preparation only affects Ih. Additionally, the authors write 1 mM cesium in the text but appear to use 2 mM in the figures. In later experiments, the authors switch to ZD7288, a more commonly used and generally accepted more specific blocker of HCN channels. However, they use a very high concentration, which is also known to produce off-target effects (see Chevaleyre and Castillo, 2002). To make robust conclusions, the authors should have used both blockers (at accepted/conservative concentrations) for all (or at least most) experiments. Using one blocker for some experiments and then another for different experiments is fraught with potential confounds.
(3) A stronger case could be made that HCN is expressed in the somatic compartment of L2/3 cells if the authors had directly measured HCN-isolated currents with outside-out or nucleated patch recording (with appropriate leak subtraction and pharmacology). Whole-cell voltage-clamp in neurons with axons and/or dendrites does not work. It has been shown to produce erroneous results over and over again in the field due to well-known space clamp problems (see Rall, Spruston, Williams, etc.). The authors could have also included negative controls, such as recordings in neurons that do not express HCN or in HCN-knockout animals. Without these experiments, the authors draw a false equivalency between the effects of cesium and HCN channels, when the outcomes they describe could be driven simply by multiple other cesium-sensitive currents. Distortions are common in these preparations when attempting to study channels (see Williams and Womzy, J Neuro, 2011). In Fig 2h, cesium-sensitive currents look too large and fast to be from HCN currents alone given what the authors have shown in their earlier current clamp data. Furthermore, serious errors in leak subtraction appear to be visible in Supplementary Figure 1c. To claim that these conductances are solely from HCN may be misleading.
(4) The authors present current-clamp traces with some sag, a primary indicator of HCN conductance, in Figure 2. However, they do not show example traces with cesium or ZD7288 blockade. Additionally, the normalization of current injected by cellular capacitance and the lack of reporting of input resistance or estimated cellular size makes it difficult to determine how much current is actually needed to observe the sag, which is important for assessing the functional relevance of these channels. The sag ratio in controls also varies significantly without explanation (Figure 6 vs Figure 7). Could this variability be a result of genetically defined subgroups within L2/3? For example, in humans, HCN expression in L2/3 varies from superficial and deep neurons. The authors do not make an effort to investigate this. Regardless of inconsistencies in either current injection or cell type, the sag ratio appears to be rather modest and similar to what has already been reported previously in other papers.
(5) In the later experiments with ZD7288, the authors measured EPSP half-width at greater distances from the soma. However, they use minimal stimulation to evoke EPSPs at increasingly far distances from the soma. Without controlling for amplitude, the authors cannot easily distinguish between attenuation and spread from dendritic filtering and additional activation and spread from HCN blockade. At a minimum, the authors should share the variability of EPSP amplitude versus the change in EPSP half-width and/or stimulation amplitudes by distance. In general, this kind of experiment yields much clearer results if a more precise local activation of synapses is used, such as dendritic current injection, glutamate uncaging, sucrose puff, or glutamate iontophoresis. There are recording quality concerns here as well: the cell pictured in Figure 3a does not have visible dendritic spines, and a substantial amount of membrane is visible in the recording pipette. These concerns also apply to the similar developmental experiment in 6f-h, where EPSP amplitude is not controlled, and therefore, attenuation and spread by distance cannot be effectively measured. The outcome, that L2/3 cells have dendritic properties that violate cable theory, seems implausible and is more likely a result of variable amplitude by proximity.
(6) Minimal stimulation used for experiments in Figures 3d-i and Figures 4g-h does not resolve the half-width measurement's sensitivity to dendritic filtering, nor does cesium blockade preclude only HCN channel involvement. Example traces should be shown for all conditions in 3h; the example traces shown here do not appear to even be from the same cell. These experiments should be paired (with and without cesium/ZD). The same problem appears in Figure 4, where it is not clear that the authors performed controls and drug conditions on the same cells. 4g also lacks a scale bar, so readers cannot determine how much these measurements are affected by filtering and evoked amplitude variability. Finally, if we are to believe that minimal stimulation is used to evoke responses of single axons with 50% fail rates, NMDA receptor activation should be minimal to begin with. If the authors wish to make this claim, they need to do more precise activation of NMDA-mediated EPSPs and examine the effects of ZD7288 on these responses in the same cell. As the data is presented, it is not possible to draw the conclusion that HCN boosts NMDA-mediated responses in L2/3 neurons.
(7) The quality of recordings included in the dataset has concerning variability: for example, resting membrane potentials vary by >15-20 mV and the AP threshold varies by 20 mV in controls. This is indicative of either a very wide range of genetically distinct cell types that the authors are ignoring or the inclusion of cells that are either unhealthy or have bad seals.
(8) The authors make no mention of blocking GABAergic signaling, so it must be assumed that it is intact for all experiments. Electrical stimulation can therefore evoke a mixture of excitatory and inhibitory responses, which may well synapse at very different locations, adding to interpretability and variability concerns.
(9) The investigation of serotonergic interaction with HCN channels produces modest effect sizes and suffers the same problems as described above.
(10) The computational modeling is not well described and is not biologically plausible. Persistent and transient K channels are missing. Values for other parameters are not listed. The model does not seem to follow cable theory, which, as described above, is not only implausible but is also not supported by the experimental findings.
Taken together, there are serious methodological and analytical concerns that need to be addressed before the authors' claims can be supported. Combined with the small effect sizes and high data variability throughout the paper, this makes it hard to see how the manuscript could make a strong contribution to advancing our understanding of L2/3 cortical pyramidal neuron function.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Organization of cell surface receptors in membrane nanodomains is important for signaling, but how this is regulated is poorly understood. In this study the authors employ TIRFM single-molecule tracking combined with multiple analyses to show that ligand exposure increases diffusion of the immune receptor FLS2 in the plasma membrane and its co-localization with remorin REM1.3 in a manner dependent on the phosphosite S938. They additionally show that ligand increases dwell time of FLS2, and this is linked to FLS2 endocytosis, also in a manner dependent on S938 phosphorylation. The study uncovers a regulatory mechanism of FLS2 localization in the nanodomain crucial for signaling.
Strengths:
TIRFM single-molecule tracking, FRAP, FRET and endocytosis experiments were nicely done. A role of S938 phosphorylation is convincing.
Weaknesses:
In the previous submission, reviewers pointed out multiple issues, which the reviewers believed the authors can address in the revision. The revised version does improve to some extent but still contains many issues in terms of data analysis and writing.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, Misic et al showed that white matter properties can be used to classify subacute back pain patients that will develop persisting pain.
Strengths:
Compared to most previous papers studying associations between white matter properties and chronic pain, the strength of the method is to perform a prediction in unseen data. Another strength of the paper is the use of three different cohorts. This is an interesting paper that provides a valuable contribution to the field.
Weaknesses:
The authors imply that their biomarker could outperform traditional questionnaires to predict pain: "While these models are of great value showing that few of these variables (e.g. work factors) might have significant prognostic power on the long-term outcome of back pain and provide easy-to-use brief questionnaires-based tools, (21, 25) parameters often explain no more than 30% of the variance (28-30) and their prognostic accuracy is limited.(31)". I don't think this is correct; questionnaire-based tools can actually achieve far greater prediction than their model in about half a million individuals from the UK Biobank (Tanguay-Sabourin et al., A prognostic risk score for the development and spread of chronic pain, Nature Medicine 2023).
Moreover, the main weakness of this study is the sample size. It remains small despite having 3 cohorts. This is problematic because results are often overfitted in such a small sample size brain imaging study, especially when all the data are available to the authors at the time of training the model (Poldrack et al., Scanning the horizon: towards transparent and reproducible neuroimaging research, Nature Reviews in Neuroscience 2017). Thus, having access to all the data, the authors have a high degree of flexibility in data analysis, as they can retrain their model any number of times until it generalizes across all three cohorts. In this case, the testing set could easily become part of the training making it difficult to assess the real performance, especially for small sample size studies.
Even if the performance was properly assessed, their models show AUCs between 0.65-0.70, which is usually considered as poor, and most likely without potential clinical use. Despite this, their conclusion was: "This biomarker is easy to obtain (~10 min 18 of scanning time) and opens the door for translation into clinical practice." One may ask who is really willing to use an MRI signature with a relatively poor performance that can be outperformed by self-report questionnaires?
Overall, these criticisms are more about the wording sometimes used and the inference they made. I think the strength of the evidence is incomplete to support the main claims of the paper.
Despite these limitations, I still think this is a very relevant contribution to the field. Showing predictive performance through cross-validation and testing in multiple cohorts is not an easy task and this is a strong effort by the team. I strongly believe this approach is the right one and I believe the authors did a good job.
Minor points:
Methods:
I get the voxel-wise analysis, but I don't understand the methods for the structural connectivity analysis between the 88 ROIs. Have the authors run tractography or have they used a predetermined streamlined form of 'population-based connectome'? They report that models of AUC above 0.75 were considered and tested in the Chicago dataset, but we have no information about what the model actually learned (although this can be tricky for decision tree algorithms).
Minor:<br /> What results are shown in Figure 7? It looks more descriptive than the actual results.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Chowdhury and co-workers provide interesting data to support the role of G4-structures in promoting chromatin looping and long-range DNA interactions. The authors achieve this by artificially inserting a G4-containing sequence in an isolated region of the genome using CRISPR-Cas9 and comparing it to a control sequence that does not contain G4 structures. Based on the data provided, the authors can conclude that G4-insertion promotes long-range interactions (measured by Hi-C) and affects gene expression (measured by qPCR) as well as chromatin remodelling (measured by ChIP of specific histone markers).
Whilst the data presented is promising and partially supports the authors' conclusion, this reviewer feels that some key controls are missing to fully support the narrative. Specifically, validation of actual G4-formation in chromatin by ChIP-qPCR (at least) is essential to support the association between G4-formation and looping. Moreover, this study is limited to a genomic location and an individual G4-sequence used, so the findings reported cannot yet be considered to reflect a general mechanism/effect of G4-formation in chromatin looping.
Strengths:
This is the first attempt to connect genomics datasets of G4s and HiC with gene expression. The use of Cas9 to artificially insert a G4 is also very elegant.
Weaknesses:
Lack of controls, especially to validate G4-formation after insertion with Cas9. The work is limited to a single G4-sequence and a single G4-site, which limits the generalisation of the findings.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Galanti et al. present an innovative new method to determine the susceptibility of large collections of plant accessions towards infestations by herbivores and pathogens. This work resulted from an unplanned infestation of plants in a greenhouse that was later harvested for sequencing. When these plants were extracted for DNA, associated pest DNA was extracted and sequenced as well. In a standard analysis, all sequencing reads would be mapped to the plant reference genome and unmapped reads, most likely originating from 'exogenous' pest DNA, would be discarded. Here, the authors argue that these unmapped reads contain valuable information and can be used to quantify plant infestation loads.
For the present manuscript, the authors re-analysed a published dataset of 207 sequenced accessions of Thlaspi arvense. In this data, 0.5% of all reads had been classified as exogenous reads, while 99.5% mapped to the T. arvense reference genome. In a first step, however, the authors repeated read mapping against other reference genomes of potential pest species and found that a substantial fraction of 'ambiguous' reads mapped to at least one such species. Removing these reads improved the results of downstream GWAs, and is in itself an interesting tool that should be adopted more widely.
The exogenous reads were primarily mapped to the genomes of the aphid Myzus persicae and the powdery mildew Erysiphe cruciferarum, from which the authors concluded that these were the likely pests present in their greenhouse. The authors then used these mapped pest read counts as an approximate measure of infestation load and performed GWA studies to identify plant gene regions across the T. arvense accessions that were associated with higher or lower pest read counts. In principle, this is an exciting approach that extracts useful information from 'junk' reads that are usually discarded. The results seem to support the authors' arguments, with relatively high heritabilities of pest read counts among T. arvense accessions, and GWA peaks close to known defence genes. Nonetheless, I do feel that more validation would be needed to support these conclusions, and given the radical novelty of this approach, additional experiments should be performed.
A weakness of this study is that no actual aphid or mildew infestations of plants were recorded by the authors. They only mention that they anecdotally observed differences in infestations among accessions. As systematic quantification is no longer possible in retrospect, a smaller experiment could be performed in which a few accessions are infested with different quantities of aphids and/or mildew, followed by sequencing and pest read mapping. Such an approach would have the added benefit of allowing causally linking pest read count and pest load, thereby going beyond correlational associations.
On a technical note, it seems feasible that mildew-infested leaves would have been selected for extraction, but it is harder to explain how aphid DNA would have been extracted alongside plant DNA. Presumably, all leaves would have been cleaned of live aphids before they were placed in extraction tubes. What then is the origin of aphid DNA in these samples? Are these trace amounts from aphid saliva and faeces/honeydew that were left on the leaves? If this is the case, I would expect there to be substantially more mildew DNA than aphid DNA, yet the absolute read counts for aphids are actually higher. Presumably read counts should only be used as a relative metric within a pest organism, but this unexpected result nonetheless raises questions about what these read counts reflect. Again, having experimental data from different aphid densities would make these results more convincing.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors establish a recombinant insect cell expression and purification scheme for the antiviral Dicer complex of C. elegans. In addition to Dicer-1, the complex harbors two additional proteins, the RIG-I-like helicase DRH-1 and the dsRNA-binding protein RDE-4. The authors show that the complex prefers blunt-end dsRNA over dsRNAs that contain overhangs. Furthermore, whereas ATP-dependent dsRNA cleavage only exacerbates regular dsRNA cleavage activity, the presence of RDE-4 is essential to ATP-dependent and ATP-independent dsRNA cleavage. Single-particle cryo-EM studies of the ternary C. elegans Dicer complex reveal that the N-terminal domain of DRH-1 interacts with the helicase domain of DCR-1, thereby relieving its autoinhibitory state. Last, the authors show that the ternary complex is able to processively cleave long dsRNA, an activity primarily relying on the helicase activity of DRH-1.
Strengths:
• First thorough biochemical characterization of the antiviral activity of C. elegans Dicer in complex with the RIG-I like helicase DRH-1 and the dsRNA-binding protein RDE-4<br /> • Discovery that RDE-4 is essential to dsRNA processing, whereas ATP hydrolysis is not<br /> • Discovery of an autoinhibitory role of DRH-1's N-terminal domain (in analogy to the CARD domains of RIG-I)<br /> • First structural insights into the ternary complex DCR-1:DRH-1:RDE-4 by cryo-EM to medium resolution<br /> • Trap experiments reveal that the ternary DCR-1 complex cleaves blunt-ended dsRNA processively. Likely, the helicase domain of DRH-1 is responsible for this processive cleavage.
Weaknesses:
• Cryo-EM Structure of the ternary Dicer-1:DRH-1:RED-4 complex to only medium resolution<br /> • High-resolution structure of the C-terminal domain of DRH-1 bound to dsRNA does not reveal the mechanism of how blunt-end dsRNA and overhang-containing one are being discriminated<br /> • The cryo-EM structure of DCR1:DRH-1:RDE-4 in the presence of ATP only reveals the helicase and CTD domains of DRH-1 bound to dsRNA. No information on dsRNA termini recognition is presented. The paragraph seems detached from the general flow of the manuscript.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this work, Odenwald and colleagues show that mutant biotin ligases used to perform proximity-dependent biotin identification (TurboID) can be used to amplify signal in fluorescence microscopy and to label phase-separated compartments that are refractory to many immunofluorescence approaches. Using the parasite Trypanosoma brucei, they show that fluorescent methods such as expansion microscopy and CLEM, which require bright signals for optimal detection, benefit from the elevated signal provided by TurboID fusion proteins when coupled with labeled streptavidin. Moreover, they show that phase-separated compartments, where many antibody epitopes are occluded due to limited diffusion and potential sequestration, are labeled reliably with biotin deposited by a TurboID fusion protein that localizes within the compartment. They show successful labeling of the nucleolus, likely phase-separated portions of the nuclear pore, and stress granules. Lastly, they use a panel of nuclear pore-TurboID fusion proteins to map the regions of the T. brucei nuclear pore that appear to be phase-separated by comparing antibody labeling of the protein, which is susceptible to blocking, to the degree of biotin deposition detected by streptavidin, which is not.
Strengths:
Overall, this study shows that TurboID labelling and fluorescent streptavidin can be used to boost signal compared to conventional immunofluorescence in a manner similar to tyramide amplification, but without having to use antibodies. TurboID could prove to be a viable general strategy for labeling phase-separated structures in cells, and perhaps as a means of identifying these structures, which could also be useful.
Weaknesses:
However, I think that this work would benefit from additional controls to address if the improved detection that is being observed is due to the increased affinity and smaller size of streptavidin/biotin compared to IgGs, or if it has to do with the increased amount of binding epitope (biotin) being deposited compared to the number of available antibody epitopes. I also think that using the biotinylation signal produced by the TurboID fusion to track the location of the fusion protein and/or binding partners in cells comes with significant caveats that are not well addressed here, mostly due to the inability to discern which proteins are contributing to the observed biotin signal.
To dissect the contributions of the TurboID fusion to elevating signal, anti-biotin antibodies could be used to determine if the abundance of the biotin being deposited by the TurboID is what is increasing detection, or if streptavidin is essential for this. Alternatively, HaloTag or CLIP tagging could be used to see if diffusion of a small molecule tag other than biotin can overcome the labeling issue in phase-separated compartments. There are Halo-biotin substrates available that would allow the conjugation of 1 biotin per fusion protein, which would allow the authors to dissect the relative contributions of the high affinity of streptavidin from the increased amount of biotin that the TurboID introduces.
The idea of using the biotin signal from the TurboID fusion as a means to track the changing localization of the fusion protein or the location of interacting partners is an attractive idea, but the lack of certainty about what proteins are carrying the biotin signal makes it very difficult to make clear statements. For example, in the case of TurboID-PABP2, the appearance of a biotin signal at the cell posterior is proposed to be ALPH1, part of the mRNA decapping complex. However, because we are tracking biotin localization and biotin is being deposited on a variety of proteins, it is not formally possible to say that the posterior signal is ALPH1 or any other part of the decapping complex. For example, the posterior labeling could represent a localization of PABP2 that is not seen without the additional signal intensity provided by the TurboID fusion. There are also many cytoskeletal components present at the cell posterior that could be being biotinylated, not just the decapping complex. Similar arguments can be made for the localization data pertaining to MLP2 and NUP65/75. I would argue that the TurboID labeling allows you to enhance signal on structures, such as the NUPs, and effectively label compartments, but you lack the capacity to know precisely which proteins are being labeled.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The manuscript by Wang et al. investigates the role of Rnf220 in hindbrain development and Hox expression. The authors suggest that Rnf220 controls Hox expression in the hindbrain by regulating WDR5 levels. The authors combine in vivo experiments with experiments in P19 cells to demonstrate this mechanism. However, the in vivo data does not provide strong support for the claims the authors make and the role of Rnf in Hox maintenance and pons development is unclear.
Specific concerns with in vivo data:
A major issue throughout the paper is that Hox expression analysis is done exclusively through quantitative PCR, with values ranging from 2-fold to several thousand-fold upregulation, with no antibody validation for any Hox protein (presumably they are all upregulated).
In Figure 1, massive upregulation of most Hox genes in the brainstem is shown after e16.5 but the paper quickly focuses on analysis of PN nuclei. What are the other consequences of this broad upregulation of Hox genes in the brainstem? There is no discussion of the overall phenotype of the mice, the structure of the brainstem, the migration of neurons, etc. The very narrow focus on motor cortex projections to PN nuclei seems bizarre without broad characterization of the mice, and the brainstem in particular. There is only a mention of "severe motor deficits" from previous studies, but given the broad expression of Rnf220, the fact that is a global knockout, and the effects on spinal cord populations shown previously the justification for focusing on PN nuclei does not seem strong.
It is stated that cluster 7 in scRNA-seq corresponds to the PN nuclei. The modest effect shown on Hox3-5 expression in that data in Figure 1 is inconsistent with the larger effect shown in Figure 2.
Presumably, Hox genes are not the only targets of Rnf220 as shown in the microarray/RNA-sequencing data. There is no definitive evidence that any phenotypes observed (which are also not clear) are specifically due to Hox upregulation. The only assay the authors use to look at a Hox-dependent phenotype in the brainstem is the targeting of PN nuclei by motor cortex axons. This is only done in 2 animals and there are no details as to how the data was analyzed and quantified. The only 2 images shown are not convincing of a strong phenotype, they could be taken at slightly different levels or angles. At the very least, serial sections should be shown and the experiment repeated in more animals. There is also no discussion of how these phenotypes, if real, would relate to previous work by the Rijli group which showed very precise mechanisms of synaptic specificity in this system.
The temporal aspect of this regulation in vivo is not clear. The authors show some expression changes begin at e16.5 but are also present at 2 months. Is the presumed effect on neural circuits a result of developmental upregulation at late embryonic stages or does the continuous overexpression in adult mice have additional influence? Are any of the Hox genes upregulated normally expressed in the brainstem, or PN specifically, at 2 months? Why perform single-cell sequencing experiments at 2 months if this is thought to be mostly a developmental effect? Similarly, the significance of the upregulated WRD5 in the pons and pontine nuclei at 2 months in Figure 3 is not clear.
In Figure 3C the levels of RNF220 in wt and het don't seem to be that different.
Based on the single-cell experiments, and the PN nuclei focus, the rescue experiments are confusing. If the Rnf220 deletion has a sustained effect for up to 2 months, why do the injections in utero? If the focus is the PN nuclei why look at Hox9 expression and not Hox3-5 which are the only Hox genes upregulated in PN based on sc-sequencing? No rescue of behavior or any phenotype other than Hox expression by qPCR is shown and it is unclear whether upregulation of Hox9 paralogs leads to any defects in the first place. The switch to the Nes-cre driver is not explained. Also, it seems that wdr5 mRNA levels are not so relevant and protein levels should be shown instead (same for rescue experiments in P19 cells).
Other:<br /> What is the relationship between Retinoic acid and WRD5? In Figure 3E there is no change in WRD5 levels without RA treatment in Rnf KO but an increase in expression with RA treatment and Rnf KO. However, the levels of WRD5 do not seem to change with RA treatment alone. Does Rnf220 only mediate WDR5 degradation in the presence of RA? This does not seem to be the case in experiments in 293 cells in Figure 4.
Why are the levels of Hox upregulation after RA treatment so different in Figure 5 and Figure Supplement 5?
In Figures 4B+C which lanes are input and which are IP? There is no quantitation of Figure 4D, from the blot it does look that there is a reduction in the last 2 columns as well. The band in the WT flag lane seems to have a bubble. Need to quantitate band intensities. Same for E, the effect does not seem to be completely reversed with MG132.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors were trying to achieve that Tgif1 expression is regulated by EAK1/2 and PTH in a time-dependent manner, and its roles in suppressing Pak3 for facilitating osteoblast adhesion. The authors further tried to achieve that the Tgif1-Pak3 signaling plays a significant role in osteoblast migration to the site of bone repair and bone remodeling.
Strengths:
- In a previous study, they demonstrated that Tgif1 is a target gene of PTH, and the absence of Tgif1 failed to increase bone mass by PTH treatment (Saito et al., Nat Commun., 2019). In this study, they found that Tgif1-Pak3 signaling prompts osteoblast migration through osteoblast adhesion to prompt bone regeneration. This novel finding provides a better understanding of how Tgif1 expression in osteoblasts regulates adherence, spreading, and migration during bone healing and bone remodeling.<br /> - The authors demonstrated that ERK1/2 and PTH regulate Tgif1 expression in a time-dependent manner and its role in suppressing Pak3 through various experimental approaches such as luciferase assay, ChIP assay, and gene silencing. These results contribute to the overall strength of the article.
Weaknesses:
None after substantial revisions especially in vivo parts.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
in this paper authors show that the degree of pigmentation for RPE cells is not correlated with a level of maturation and function. They suggest that this status could be different in vitro than in vivo but do not provide proper experiments to validate this hypothesis. However, it is the first time that the absence of correlation between pigmentation and function is studied.
Strengths:
The methods are good and experiments very rigorous
Comments on current version:
The authors have modified their title and focus on QC for in vitro process
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
A novel serine protease and a inhibitor pair regulate cell migration in the neural crest.
Strengths:
The reproduction of classical cranial neural crest extirpations and their phenocopy by SerpinE2 morpholino are remarkable. Very scholarly written and data of the highest quality.
Weaknesses:
All were improved upon revision.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Building upon their famous tool for the deconvolution of human transcriptomics data (EPIC), Gabriel et al. implemented a new methodology for the quantification of the cellular composition of samples profiled with Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq). To build a signature for ATAC-seq deconvolution, they first created a compendium of ATAC-seq data and derived chromatin accessibility marker peaks and reference profiles for 21 cell types, encompassing immune cells, endothelial cells, and fibroblasts. They then coupled this novel signature with the EPIC deconvolution framework based on constrained least-square regression to derive a dedicated tool called EPIC-ATAC. The method was then assessed using real and pseudo-bulk RNA-seq data from human peripheral blood mononuclear cells (PBMC) and, finally, applied to ATAC-seq data from breast cancer tumors to show it accurately quantifies their immune contexture.
Strengths:
Overall, the work is of very high quality. The proposed tool is timely; its implementation, characterization, and validation are based on rigorous methodologies and resulted in robust results. The newly-generated, validation data and the code are publicly available and well-documented. Therefore, I believe this work and the associated resources will greatly benefit the scientific community.
Weaknesses:
A few aspects can be improved to clarify the value and applicability of the EPIC-ATAC and the transparency of the benchmarking analysis.
Most of the validation results in the main text assess the methods on all cell types together, by showing the correlation, RMSE, and scatterplots of the estimated vs. true cell fractions. This approach is valuable for showing the overall method performance and for detecting systematic biases and noisy estimates. However, it provides very limited insights regarding the capability of the methods to estimate the individual cell types, which is the ultimate aim of deconvolution analysis. This limitation is exacerbated for rare cell types, which could even have a negative correlation with the ground truth fractions, but not weigh much on the overall RMSE and correlation. I would suggest integrating into the main text and figures an in-depth assessment of the individual cell types. In particular, it should be shown and discussed which cell types can be accurately quantified and which ones are less reliable.
In the benchmarking analysis, EPIC-ATAC is compared to several deconvolution methods, most of which were originally developed for transcriptomics data. This comparison is not completely fair unless their peculiarities and the limitations of tweaking them to work with ATAC-seq data are discussed. For instance, some methods (including the original EPIC) correct for cell-type-specific mRNA bias, which is not present in ATAC-seq data and might, thus, result in systematic errors.
On a similar note, it could be made more explicit which adaptations were introduced in EPIC, besides the ad-hoc ATAC-seq signature, to make it applicable to this type of data.
Given that the final applicability of EPIC-ATAC is on real bulk RNA-seq data, whose characteristics might not be completely recapitulated by pseudo-bulk samples, it would be interesting to see EPIC and EPIC-ATAC compared on a dataset with matched, real bulk RNA-seq and ATAC-seq, respectively. It would nicely complement the analysis of Figure 7 and could be used to dissect the commonalities and peculiarities of these two approaches.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Cellulose is the major component of the plant cell wall and as such is a major component of all plant biomass on the planet. It is made at the cell surface by a large membrane-bound complex known as the cellular synthase complex. It is the structure of the cellulose synthase complex that determines the structure of the cellulose microfibril, the unit of cellulose found in nature. Consequently, while understanding the molecular structure of individual catalytic subunits that synthesise individual beta 1-4 glucose chains is important, to really understand cellulose synthesis it is necessary to understand the structure of the entire complex.
In higher plants, cellulose is synthesised by a large membrane-bound complex composed of three different CESA proteins. During cellulose synthesis in the primary cell wall, this is composed of members of groups CESA1, CESA3, and CESA6. While the authors have previously presented structural data on CESA8, required for cellulose synthesis in the secondary cell wall, here they provide structural and enzymatic analysis of CESA1, CESA3, and CESA6 from soya beans.
The authors have utilised their established protocol to purify trimers for all three classes of CESA proteins and obtain structural information using electron microscopy. The structures reveal some subtle, but interesting differences between the structures obtained in this study and that previously obtained for CESA8. In particular, they identify a change in the position of transmembrane helices 7 that in previous structures formed part of the transmembrane channel. In the structure of CESA1 TM7 is shifted laterally to a position more towards the periphery of the protomer, where it is stabilised by inter-protomer interactions. This creates a large lipid-exposed channel opening that is likely encountered by the growing cellulose chain. In the discussion, the authors speculate this channel might facilitate lateral movement of cellulose chains in the membrane which would allow them to associate to form the microfibril. There is, however, no explanation for why this might be different for CESA proteins involved in primary and secondary cell wall CESA proteins.
Interactions within the trimer as stabilised by the plant conserved regions (PCR), while in common with previous studies that class-specific regions (CSR) are not resolved, are likely highly disordered as has been suggested in previous studies. As the name suggests these regions are likely to be important for determining how different CESA proteins interact, but it remains to be seen how they achieve this. Similarly, the N-terminal domain (NTD) remains rather intriguing. In the CESA3 structure, the NTD forms a stalk that protrudes into the cytoplasm that was previously observed for CESA8, while it remains unresolved in CESA1 and CESA6. The authors suggest the inability to resolve this region is likely the result of the NTD being able to form multiple conformations. Loss of the NTD does not prevent the formation of trimers and CESA1 and CESA3 are still able to interact. Previous bioinformatic studies suggest that the CSR part of the NTD is also highly class-specific (Carrol et al. 2011 Frontiers in Plant Science 2, 5-5) suggesting it is also likely to participate in interactions between different CESA proteins. This analysis provides little new information on the structure of the NTD or how it functions as part of the cellulose synthase complex.
The other important point regarding cellulose synthesis is how the different CESA trimers function during cellulose synthesis and complex assembly. The authors provide biochemical evidence that mixed complexes of two different CESA proteins are able to synergistically increase the rate of cellulose synthesis. This increase is not dramatic, around 2-fold as it is unclear what brings about this increase and whether it results from the ability to form larger complexes favouring greater rates of cellulose synthesis.
It is clear however from electron microscopy that mixing of CESA proteins can lead to the formation of large aggregates not seen with single CESA proteins. The aggregates observed do not form rosette-type shapes but appear to be much more random aggregates of different CESA trimers. The authors suggest that this is likely a result of the fact that the complexes are not constrained in two dimensions by the membrane, however, if these are biologically relevant interactions that form aggregates it is somewhat surprising that they do not form hexameric structures, particularly since they are essentially forming as a single layer.
Overall the study provides some important data and raises a number of important questions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript successfully established a new short-term model of diabetic retinopathy by treating zebrafish embryos with high concentrations of monosaccharides, resembling the hyperangiogenic characteristics observed in proliferative diabetic retinopathy in patients. They found that excessive angiogenesis induced by glucose and noncaloric monosaccharides was achieved by activating the quiescent endothelial cells into proliferating tip cells. Importantly, the authors further confirmed the effects of monosaccharides on inducing excessive angiogenesis were mediated by the foxo1a-marcksl1a pathway.
Strengths:
These results showed the potentially detrimental effects of the noncaloric monosaccharides on blood vessel function and provided novel insights into the underlying mechanisms.
Weaknesses:
The mechanism of noncaloric monosaccharides inducing excessive sprouting angiogenesis is not solid enough.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This impressive study by Bandet and Winship uses 2-photon imaging in awake behaving mice to examine long-term changes in neural activity and functional connectivity after focal ischemic stroke. The authors discover that there are long-lasting perturbations in neural activity and functional connectivity, specifically within peri-infarct cortex but not more distant cortical regions. Overall I thought the study provided important new findings that were supported by compelling data.
Strengths:
This is a technically challenging study and the experiments appear to be well done. The manuscript was written in a concise manner, and the figures were clearly presented. The analytic tools were rigorous and appropriate, leading to novel insights regarding neural activity patterns during movement or rest. The discovery of long-lasting impairments in neural activity/functional connectivity is important (and often overlooked) given that future stroke studies need to recognize what problems exist in order to properly rectify them. The authors also question the spatial extent to which functional changes occur after stroke, at least at the single cell level. Overall, I think this was a well-executed study whose primary conclusions were justified by the data presented.
Weaknesses:
I found very little in the way of weaknesses. The authors addressed my comments about the methodology, statistical analysis, normalization of data and discussion points about cortical plasticity during stroke recovery.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This is an interesting study by Xu et al showing the effects of infection with the Treponema pallidum virus (which causes syphilis disease) on neuronal development using iPSC-derived human brain organoids as a model and single-cell RNA sequencing. This work provides an important insight into the impact of the virus on human development, bridging the gap between the phenomena observed in studies using animal models as well as non-invasive human studies showing developmental abnormalities in fetuses infected with the virus in utero through maternal vertical transmission.
Using single-cell RNAseq in combination with qPCR and immunofluorescence techniques, the authors show that T. pallidum infected organoids are smaller in size, in particular during later growth stages, contain a larger number of undifferentiated neuronal lineage cells, and exhibit decreased numbers of specific neuronal subcluster, which the authors have identified as undifferentiated hindbrain neurons.
The study is an important first step in understanding how T. pallidum affects human neuronal development and provides important insight into the potential mechanisms that underlie the neurodevelopmental abnormalities observed in infected human fetuses. Several important weaknesses have also been noted, which need to be addressed to strengthen the study's conclusions.
Strengths:
(1) The study is well written, and the data quality is good for the most part.
(2) The study provides an important first step in utilizing human brain organoids to study the impact of T. pallidum infection on neuronal development.
(3) The study's conclusions may provide important insight to other researchers focused on studying how viral infections impact neuronal development.
Weaknesses:
(1) It is unclear how T. pallidum infection was validated in the organoids. If not all cells are infected, this could have important implications for the study's conclusions, in particular the single-cell RNAseq experiments. Were only cells showing the presence of the virus selected for sequencing? A detailed description of how infection was validated and the process of selection of cells for RNAseq would strongly support the study's conclusions.
(2) The authors show that T. pallidum infection results in impaired development of hindbrain neurons. How does this finding compare to what has already been shown in animal studies? Is a similar deficit in this brain region observed with this specific virus? It would be useful to strengthen the study's conclusions if the authors added a discussion about the observed deficits in hindbrain neuronal development, and prior literature on similar studies conducted in animal models or human patients. Does T. pallidum preferentially target these neurons, or is this a limitation of the current organoid model system?
(3) The authors show that T. pallidum-infected organoids are smaller in size by measuring organoid diameter during later stages of organoid growth, with no change during early stages. Does that represent insufficient infection at the early stages? Is this due to increased cell death or lack of cell division in the infected organoids? Experiments using IHC to quantify levels of cleaved caspase and/or protein markers for cell proliferation would be able to address these questions.
4) In Figure 1D authors show differences in rosette-like structure in the infected organoids. The representative images do not appear to be different in any of the discussed components (e.g., the sox2 signal looks fairly similar between the two conditions). No quantification of these structures was presented. Authors should provide quantification or a more representative image to support their statement.
5) The IHC images shown in Figures 3E, G, and Figure 4E look very similar between the two conditions despite the discussed decrease in the text. A more suitable representative image should be presented, or the analysis should be amended to reflect the observed results.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript aimed to investigate the emergence of emotional sensitivity and its relationship with gestational age. Using an oddball paradigm and event-related potentials, the authors conducted an experiment in 120 healthy neonates with a gestational age range of 35 to 40 weeks. A significant developmental milestone was identified at 37 weeks gestational age, marking a crucial juncture in neonatal emotional responsiveness.
Strengths:
This study has several strengths, by providing profound insights into the early development of social-emotional functioning and unveiling the role of gestational age in shaping neonatal perceptual abilities. The methodology of this study demonstrates rigor and well-controlled experimental design, particularly involving matched control sounds, which enhances the reliability of the research. Their findings not only contribute to the field of neurodevelopment, but also showcase potential clinical applications, especially in the context of autism screening and early intervention for neurodevelopmental disorders.
Weaknesses:
More details should be provided in terms of inclusion and exclusion criteria for the participants, as well as missing data due to the non-cooperation of newborns during the experimental process. Potential differences between preterm and full-term infants are worth exploring. Several aspects of EEG data analyses and data interpretation should be better clarified.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors describe a new pipeline to measure changes in vasculature diameter upon opt-genetic stimulation of neurons.
The work is interesting and the topic is quite relevant to better understand the hemodynamic response on the graph/network level.
Strengths:
The manuscript provides a pipeline that allows for the detection of changes in the vessel diameter as well as simultaneously allowing for the location of the neurons driven by stimulation.
The resulting data could provide interesting insights into the graph-level mechanisms of regulating activity-dependent blood flow.
The interesting findings include that vessel radius changes depend on depth from the cortical surface and that dilations on average happen closer to the activated neurons.
Weaknesses:
The utility of a pipeline depends on the generalization properties.
While the proposed pipeline seems to work for the data the authors acquired, it is unclear if this pipeline will actually generalize to novel data sets possibly recorded by a different microscope (e.g. different brand), or different imagining conditions (e.g. illumination or different imagining artifacts) or even to different brain regions or animal species, etc.
The authors provide a 'black-box' approach that might work well for their particular data sets and image acquisition settings but it is left unclear how this pipeline is actually widely applicable to other conditions as such data is not provided.
In my experience, without well-defined image pre-processing steps and without training on a wide range of image conditions pipelines typically require significant retraining, which in turn requires generating sufficient amounts of training data, partly defying the purpose of the pipeline.
It is unclear from the manuscript, how well this pipeline will perform on novel data possibly recorded by a different lab or with a different microscope.
Analysis
Some of the chosen analysis results seem to not fully match the shown data, or the visualization of the data is hard to interpret in the current form. Additionally, some measures seem not fully adapted to the current situation (e.g. the efficiency measure does not consider possible sources or sinks). Thus, some additional analysis work might be required to account for this.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
The authors set out to identify CAPs (Candidate Adaptive Polymorphyisms), i.e., simply put mutations that carry a potential functional advantage, and utilize computational methods based on the perturbation of C-alpha positions with an Elastic Network Model to determine if dynamics of CAP residues are different in any way.
The authors have addressed the main methodological concerns.
However, one point remains. The specific comparison of which CAPs have been previously identified by other means, particularly with other computational methods that look into dynamics is still lacking. It is unfortunate that the authors do not present such analysis, particularly with respect to single point mutational analysis of Teruel et al. in Plos Comp. Bio. If CAP positions were previously identified by other means it adds strength to the methodology used by the authors. The authors also do not discuss their results in light of the work of Lam et al. (Sci. Comm, 2020) where an evolutionary analysis of Spike/ACE2 binding across homologues is performed. I believe that such deeper discussion of the current results in light of previous work, adds strength to the analysis presented in this manuscript as the methodology is different. Even if all results were not new, with the method being different from the other means by which such results were obtained, it would be still a worthy contribution to the field. Furthermore, for the community at large trying to understand the importance of particular positions in Spike, knowing that a particular position identified here was also identified by works X, Y, Z adds a lot of to the field. I can only think that the authors may imagine that if one of their CAPs was identified by other means previously, it takes away from the merit of their work, but it is actually the opposite. I urge the authors to not brush away this. In fact, more important than any methodological aspect of the present work, this strengthening of evidence for particular positions by several independent methods is the most important evidence that the authors can contribute to the field.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The work by Ginatt et al. uses genome-scale metabolic modeling to identify and characterize trophic interactions between rhizosphere-associated bacteria. Beyond identifying microbial species associated with specific host and soil traits (e.g., disease tolerance), a detailed understanding of the interactions underlying these associations is necessary for developing targeted microbiome-centered interventions for plant health. It has nonetheless remained challenging to define the roles of specific organisms and metabolic species in natural rhizobiomes. Here, the authors combine microbial compositional data obtained through metagenomic sequencing with a new collection of genome-scale models to predict interactions in the native rhizosphere communities of apple rootstocks. To do this, they have established processes to integrate these sources of data and model specific trophic exchanges, which they use to obtain testable hypotheses for targeted modulation of microbiota members in situ.
The authors carry out a careful model curation process based on metagenomic sequencing data and existing model generation tools, which, together with basing the in silico medium composition on known root exudates, strengthens their predictions of interaction network features. Moreover, its reliance on genome-scale models provides a broader basis for linking sequence-based information to predictions of function on a multispecies level beyond rhizosphere microbiomes.
Having generated a set of predicted trophic interactions, the authors carried out a detailed analysis linking features of these interactions to organism taxonomy and broader ecosystem properties. Intriguingly, the organisms predicted to grow in the first iteration of their framework (i.e., on only root exudates) broadly correspond to taxonomic groups experimentally shown to benefit from these compounds. Additionally, the simulations predicted some patterns of vitamin and amino acid secretion that are known to form the basis for interactions in the rhizosphere. Together, these outcomes underscore the applicability of this method to help disentangle trophic interaction networks in complex microbiomes.
The methodology described in this paper represents a useful and promising framework to better understand the complexity of microbial interaction networks in situ. However, the degree to which the predictions can vary according to environmental composition remains difficult to quantify, and the work does not address the sensitivity of the modeling predictions beyond a simulated medium containing 33 root exudates. I find this especially important given that relatively few (84 of 243) species were predicted to grow even after cross-feeding, suggesting that a richer medium could lead to different interaction network structures. While the authors do state the importance of environmental composition and have carefully designed an in silico medium, I believe that simulating a broader set of resource pools would add necessary insight into both the predictive power of the models themselves and trophic interactions in the rhizosphere more generally.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Gain-of-function mutations and amplifications of PPM1D are fond across several human cancers and are associated with advanced tumor stage, worse prognosis, and increased lymph node metastasis. This manuscript presents important findings that SOD1 inhibition is a potential strategy to achieve therapeutic synergism for PPM1D-mutant leukemia; and demonstrates the redox landscape of PPM1D-mutant cells.
Strengths:
In this manuscript, Zhang and colleagues investigate the synthetic-lethal dependencies of PPM1D (protein phosphatase, Mg2+/Mn2+ dependent 1D) in leukemia cells using CRISPR/Cas9 screening. They identified that SOD1 (superoxide dismutase-1) as the top hit, whose loss reduces cellular growth in PPM1D-mutant cells, but not wildtype (WT) cells. Consistently, the authors demonstrate that PPM1D-mutant cells are more sensitive to SOD1 inhibitor treatment. By performing different in vitro studies, they show that PPM1D-mutant leukemia cells have elevated level of reactive oxygen species (ROS), decreased basal respiration, increased genomic instability, and impaired non-homologous end-joining repair. These data highlight the potential of SOD1 inhibition as a strategy to achieve therapeutic synergism for PPM1D-mutant leukemia; and demonstrates the redox landscape of PPM1D-mutant cells.
Weaknesses:
While the current study has identified synthetic lethality of PPM1D-mutant leukemia cells upon SOD1 inhibition, the underlying mechanism remains elusive. Although ROS levels have been assessed between wild-type (WT) and PPM1D-mutant leukemia cells, the specific redox alterations induced by SOD1 inhibition in PPM1D mutant versus WT cells have not been elucidated. To address this gap, direct comparisons of ROS levels using various probes should be conducted between PPM1D mutant and WT cells under conditions of SOD1 inhibition.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Warming and precipitation regime change significantly influences both above-ground and below-ground processes across Earth's ecosystems. Soil microbial communities, which underpin the biogeochemical processes that often shape ecosystem function, are no exception to this, and although research shows they can adapt to this warming, population dynamics and ecophysiological responses to these disturbances are not currently known. The Qinghai-Tibet Plateau, the Third Pole of the Earth, is considered among the most sensitive ecosystems to climate change. The manuscript described an integrated, trait-based understanding of these dynamics with the qSIP data. The experimental design and methods appear to be of sufficient quality. The data and analyses are of great value to the larger microbial ecological community and may help advance our understanding of how microbial systems will respond to global change. There are very few studies in which the growth rates of bacterial populations from multifactorial manipulation experiments on the Qinghai-Tibet Plateau have been investigated via qSIP, and the large quantity of data that comprises the study described in this manuscript, will substantially advance our knowledge of bacterial responses to warming and precipitation manipulations.
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- Mar 2024
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www.defenseurdesdroits.fr www.defenseurdesdroits.fr
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La Défenseure des droits a été saisie de plusieurs réclamations concernant lesdifficultés d’accès au lycée rencontrées par de jeunes filles musulmanes portantdes vêtements correspondant ou assimilés à des abayas
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www.legifrance.gouv.fr www.legifrance.gouv.fr
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L'enseignant référent qui coordonne les équipes de suivi de la scolarisation est l'interlocuteur des familles pour la mise en place du projet personnalisé de scolarisation.
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Les conditions permettant cette inscription et cette fréquentation sont fixées par convention entre les autorités académiques et l'établissement de santé ou médico-social.
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l'Etat met en place les moyens financiers et humains nécessaires à la scolarisation en milieu ordinaire des enfants, adolescents ou adultes en situation de handicap.
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le plus proche de son domicile
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L'acquisition d'une culture générale et d'une qualification reconnue est assurée à tous les jeunes, quelle que soit leur origine sociale, culturelle ou géographique.
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permettre de façon générale aux élèves en difficulté, quelle qu'en soit l'origine, en particulier de santé, de bénéficier d'actions de soutien individualisé.
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Il veille également à la mixité sociale des publics scolarisés au sein des établissements d'enseignement
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Il veille à la scolarisation inclusive de tous les enfants, sans aucune distinction
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Article L111-1Modifié par LOI n°2021-1109 du 24 août 2021 - art. 58L'éducation est la première priorité nationale. Le service public de l'éducation est conçu et organisé en fonction des élèves et des étudiants. Il contribue à l'égalité des chances et à lutter contre les inégalités sociales et territoriales en matière de réussite scolaire et éducative. Il reconnaît que tous les enfants partagent la capacité d'apprendre et de progresser. Il veille à la scolarisation inclusive de tous les enfants, sans aucune distinction. Il veille également à la mixité sociale des publics scolarisés au sein des établissements d'enseignement. Pour garantir la réussite de tous, l'école se construit avec la participation des parents, quelle que soit leur origine sociale. Elle s'enrichit et se conforte par le dialogue et la coopération entre tous les acteurs de la communauté éducative.
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Elle s'enrichit et se conforte par le dialogue et la coopération entre tous les acteurs de la communauté éducative.
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pressbooks.online.ucf.edu pressbooks.online.ucf.edu
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As soon as he was born, he cried not as other babes use to do, Miez, miez, miez, miez, but with a high, sturdy, and big voice
Showing the parallel between him and other babies of his age, he describes that he did not shout "Miez, Miez, Miez, Miez", which translates to "no, no, no, no" in old germanic dialects like the other children. But instead, in a polar opposite manor, yelled "high, sturdy and big voice" shouted drink, drink, drink. Showing from an early age leadership, confidence, and "greatness".
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www.legifrance.gouv.fr www.legifrance.gouv.fr
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Article L111-1Version en vigueur depuis le 26 août 2021Modifié par LOI n°2021-1109 du 24 août 2021 - art. 58L'éducation est la première priorité nationale. Le service public de l'éducation est conçu et organisé en fonction des élèves et des étudiants. Il contribue à l'égalité des chances et à lutter contre les inégalités sociales et territoriales en matière de réussite scolaire et éducative.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Osteoarthritis (OA) is associated with painful, chronic inflammation that often leads to severe joint pain and joint stiffness for people over the age of 55. There is no effective therapeutic drug in the treatment of osteoarthritis. The authors found that mice without Cbfβ in their chondrocytes develop spontaneous OA. Authors uncovered that the deficiency of Cbfβ caused increased canonical Wnt signaling and inflammatory response, and decreased Hippo/YAP signaling and TGF-β signaling in articular cartilage. Authors showed that ACLT surgery-induced OA decreased Cbfβ and Yap expression and increased active β-catenin expression in articular cartilage, while local AAV-mediated Cbfβ overexpression promoted Yap expression, diminished active β-catenin expression in OA lesions. The authors demonstrated that AAV-mediated Cbfβ overexpression in knee joints of mice with OA showed the significant protective effect of Cbfβ on articular cartilage in the ACLT OA mouse model. The results from the study demonstrated Cbfβ maintains articular cartilage homeostasis through inhibiting Wnt/β-catenin signaling and increasing Hippo/Yap, and TGFβ signaling. Importantly, the authors proved that local Cbfβ overexpression could be an effective strategy for treatment of OA. The data shown in the study demonstrated that the findings are novel and very significant, and the authors' claims and conclusions are justified by their data. The paper is generally excellent with an interesting scientific premise and strong scientific rigor. The findings in this manuscript are novel, the manuscript is clearly written, and the findings will make a significant impact in the field.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this paper, Nikolaou et al. demonstrated that CYRI-B expression is upregulated in a mouse model of pancreatic ductal adenocarcinoma (PDAC). Interestingly, they found that, while CYRI-B KO promotes the early stages of tumour progression, it prevents the formation of metastasis at later stages. Focusing on the latter, the authors highlight a role for CYRI-B in controlling the membrane availability of the LPA receptor LPAR1, which is required to support PDAC cell chemotaxis towards serum or LPA.
Strengths: the in vivo and imaging data are very solid, and convincingly support the authors' conclusions. The KPC model is well-established in PDAC research and is a very powerful tool to investigate disease onset and progression. The imaging approaches used are of a very high standard. Good data presentation with the use of super-plots.
Weaknesses: the authors focused on chemotaxis, but did not present any evidence with regard to the role of CYRI-B in 3D cell invasion, which is a key process associated with cell invasion. The data presented clearly show a specific effect towards liver metastasis, while diaphragm and bowel metastasis were not affected by CYRI-B deletion. It would be beneficial to include a discussion about this, providing some potential explanation behind this observation.
This work is of interest to cell biologists not only working in pancreatic cancer but also more broadly to researchers interested in vesicular trafficking, plasma membrane receptor dynamics and cell migration.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Hoving and colleagues investigated the mechanisms of contact inhibition of locomotion (CIL) in Schwann cells using cell migration assays, in combination with siRNA as well as an ex-vivo model for collective cell migration of the peripheral nervous system. They found that N-cadherin is needed for proper cell repulsion during CIL. Schwann Cells depleted of N-cadherin failed CIL when encountering other Schwann cells depleted of N-cadherin, however they maintained CIL when encountering Schwann cells expressing N-cadherin. Depletion of alpha-catenin and to some degree p120 did not have the same effect as N-cadherin depletion. Further, they determined that the extracellular domain is needed for CIL as well as an interaction with Glypican-4. Glypicans often act as co-receptors for other signaling molecules, and so the authors further narrowed CIL's dependence to Slit signaling. N-cadherin was needed for proper Slit surface expression, again, dependent on the extracellular domain, and depletion of both Slit2 and 3 lead to a cell clumping and rounding phenotype. Finally, using an ex-vivo model of Schawnn cell migration they showed that rSlit lead to a similar cell rounding and clumping phenotype, ultimately leading to an inhibition of cell migration.
Strengths
This was a very methodical examination of what is needed for CIL in cultured Schwann cells. The data presented largely supports the findings and the linking of N-cad to glypican-4 to Slit signaling further illuminates this process helping to define the molecular players. The mechanistic insight goes further in that they demonstrate the Slit does not get to the cell surface without the expression of the extracellular domain of N-cad.
Weaknesses
The conclusions that can be drawn from this study remain a little narrow since only Schwann cells were used. This is not so much a weakness in that authors were indeed investigating the periphery nervous system regeneration but it does limit their findings. The experiments carried out in the ex-vivo system only touch on one aspect of their cell culture work, the mechanism of Slit. No other aspects of their cell culture system was tested ex-vivo which
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www.biorxiv.org www.biorxiv.org
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Reviewer #1(Public Review):
In this manuscript the authors report an experiment to assess how training on a perceptual task may not only increase performance on that task but impact on the appearance of the trained stimuli. They compare discrimination performance, coherence thresholds, and estimation biases for random dot motion direction relative to horizontal rightward in three groups of observers before and after 3 days in which they either trained on a discrimination task, an estimation task, or did not train. The authors report significant increases in discrimination performance post training compared to not training. They also report increases in estimation biases when assessed as the average estimate (over a bimodal distribution that crosses 0) but not when assessed as the mode of the bimodal distribution. They conclude that training resulted in "increases in already-large estimation biases away from horizontal".
The methods and results are strengthened by the combination of classical psychophysical techniques and sophisticated computational modelling. One weakness is the possibility is misleading summary statistics when dealing with bimodal distributions. Convincing evidence that observers perceived stimulus directions as further from horizontal (in the absolute sense) following training is not presented in the current manuscript. Irrespective, this work is likely to impact the field.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Identifying individual BCR/Ab chain sequences that are members of the same clone is a long-standing problem in the analysis of BCR/Ab repertoire sequencing data. The authors propose a new method designed to be scalable for application to huge repertoire data sets without sacrificing accuracy. Their approach utilizes Hamming Distance between CDR3 sequences followed by clustering for a fast, high-precision approach to classifying pairs of sequences as related or not, and then refines the classification using mutation information from germline-encoded regions. They compare their method with other state-of-the-art methods using synthetic data.
The authors address an important problem in an interesting, innovative, and rigorous way, using probabilistic representations of CDR3 differences, frequencies of shared and not-shared mutations, and the relationships between the two under hypotheses of related pairs and unrelated pairs, and from these develop an approach for determining thresholds for classification and lineage assignment. Benchmarking shows that the proposed method, the complete method including both steps, outperforms other methods.
Strengths of the method include its theoretical underpinnings which are consistent with an immunologist's intuition about how related and unrelated sequences would compare with each other in terms of the metrics to use and how those metrics are related to each other.
I have two high-level concerns:<br /> (1) It isn't clear how the real and synthetic data are being used to estimate parameters for the classifier and evaluate the classifier to avoid circularity. It seems like the approach is used to assign lineages in the data from [1], and then properties of this set of lineages are used to estimate parameters that are then used to refine the approach and generate synthetic data that is used to evaluate the approach. This may not be a problem with the approach but rather with its presentation, but it isn't entirely clear what data is being used and where for what purpose. An understanding of this is necessary in order to truly evaluate the method and results.<br /> (2) Regarding the data used for benchmarking - given the intertwined fashion by which the classification approach and synthetic data generation approach appear to have been developed, it is not surprising that the proposed approach outperforms the other methods when evaluated on the synthetic data presented here. It would be better to include in the benchmark the data used by the other methods to benchmark themselves or also generate synthetic data using their data generation procedures.
An improved method for BCR/Ab sequence lineage assignment would be a methodologic advancement that would enable more rigorous analyses of BCR/Ab repertoires across many fields, including infectious disease, cancer, autoimmune disease, etc., and in turn, enable advancement in our understanding of humoral immune responses. The methods would have utility to a broad community of researchers.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Doxorubincin has long been known to cause bone loss by increasing osteoclast and suppressing osteoblast activities. The study by Wang et al. reports a comprehensive investigation into the off-target effects of doxorubicin on bone tissues and potential mechanisms.. They used a tumor-free model with wild type mice and found that even a single dose of doxorubicin has a major influence by increasing leukopenia and DAMPs and inflammasomes in macrophages and neutrophils, and inflammation-related cell death (pyroptosis and NETosis). The gene knockout study shows that AIM2 and NLRP3 are the major contributors to bone loss. Overall, the study confirmed previous findings regarding the impact of doxorubicin on tissue inflammation and expands the research further into bone tissue. The presented data presented are consistent; however, a major question remains regarding whether doxorubicin drives inflammation and its related events. Most in vitro study showed that the effect of doxorubincin cannot be demonstrated without LPS priming. This observation raises the question of whether doxorubincin itself could activate the inflammasome and the related events. In vivo study, on the other hand, suggested that it doesn't require LPS. The inconsistency here was not explained further. Moreover, a tumor-free mouse model was used for the study; however, immune responses in tumor bearing models would likely be distinct from tumor-free ones. The justification for using tumor-free models is not well-established.
Strengths:
The paper includes a comprehensive study that shows the effects of doxorubincin on cytokine levels in serum, release of DAMPs and NETosis, and leukopenia using both in vivo and in vitro models. Bone marrow cells, macrophages and neutrophils were isolated from the bone marrow, and the levels of cytokines in serum were also determined.
They employed multiple knockout models with deficiency in Aim 2, Nlirp3, and double deficiencies to dissect the functional involvement of these two inflammasomes.
The experiments in general are well designed. The paper is also logically written, and figures were clearly labeled.
Weaknesses:
Most of the data presented are correlative, and there is not much effort to dissect the underlying molecular mechanism.
It is not entirely clear why a tumor free model is chosen to study immune responses, as immune responses can differ significantly with or without tumor-bearing.
Immune responses in isolated macrophages, neutrophils and bone marrow cells require priming with LPS, while such responses are not observed in vivo. There is no explanation for these differences.
The band intensities on Western blots in Fig. 4 and Fig. 5 are not quantified, and the numbers of repeats are also not provided.
Many abbreviations are used throughout the text, and some of the full names are not provided.
Fig. 5B needs a label on X axis.
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Reviewer #1 (Public Review):
In this manuscript by Buchanan and colleagues, the authors set out to determine if mutations associated with resistance to the Plasmodium apicoplast inhibitor azithromycin (AZ) had a measurable impact on the fitness of Plasmodium berghei and P. falciparum parasites as they traverse both the mosquito host and vertebrate liver.
The Plasmodium endosymbiotic organelles - the mitochondrion and apicoplast - are attractive drug targets as they (1) possess essential functions across the multi-host multi-compartment life cycle of these parasites, and (2) are of bacterial origin and thus are vulnerable to inhibition both to extant antibiotics, and novel drugs with high parasite specificity.
Historically however the high resistance propensity of drug targets encoded in the organellar genomes (most notably atovaquone and doxycycline) has precluded the use of these drugs in an endemic setting, limiting these potent compounds to use in prophylaxis for travelers from non-endemic countries. Several studies in the last decade now fairly definitively show that mutations conferring resistance to atovaquone in the mitochondrial gene cytochrome b are, in a mutation-dependent manner, totally or near-totally compromised in their ability to infect, grow, and escape the mosquito host, leading to a reexamination of the potential utility of this extraordinarily potent drug in endemic settings. Symmetries exist between the Plasmodium mitochondrion and apicoplast, which both appear to have highly fexpanded roles in the mosquito and liver relative to the blood stages. Thus, the authors set out to explore whether mutations in essential apicoplast genes were, in a similar manner to mutations in cytochrome B, associated with fitness effects in the mosquito and/or liver.
Towards this, the authors selected for several AZ-resistant parasite populations, all of which acquired mutations in the apicoplast genome-encoded ribosomal protein Rpl4. Interestingly, the authors observed contrasting fitness effects caused by these mutations, both between mutants within Plasmodium species, and between species. In P. berghei, AZ mutants were compromised in their ability to form oocysts and sporozoites, and a large proportion of sporozoites lacked an intact apicoplast and displayed aberrant gliding behaviour. Similarly, in the liver, Rpl4 mutant P. berghei liver schizonts were smaller, had fewer nuclei, and appeared extremely limited in their ability to cause a patent infection - crucially in particular via mosquito bites. Surprisingly, a P. falciparum Rpl4 mutant (notably in a different position of the protein) had no impact on sporogony but appeared to have a strong impact on liver schizont development in a liver-humanized mouse model, suggesting that establishment of blood stage infection in a subsequent human host would be less likely for mutant parasites.
This is a well-executed study, that presents novel and noteworthy findings. The impact of drug-resistance-conferring mutations in Plasmodium outside of the blood stage is woefully understudied, primarily due to significant challenges associated with studying Plasmodium, especially P. falciparum, in both the mosquito and liver which the authors navigate commendably. The results presented in this manuscript leverage state-of-the-art techniques and clearly support the authors' conclusion that AZ-conferring resistance mutations have a strong negative effect on the ability of Plasmodium parasites to both reinfect and cause symptomatic infection in a subsequent vertebrate host. This could indicate that apicoplast-targeted inhibitors are more attractive as co-drugs for malaria treatment than previously thought, due to the reduced probability of the spread of resistance, which has been a perennial issue in malaria therapeutic care.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Mohseni and Elhaik's article offers a critical evaluation of Geometric Morphometrics (GM), a common tool in physical anthropology for studying morphological differences and making phylogenetic inferences. I read their article with great interest, although I am not a geneticist or an expert on PCA theory since the problem of morphology-based classification is at the core of paleoanthropology.
The authors developed a Python package for processing superimposed landmark data with classifier and outlier detection methods, to evaluate the adequacy of the standard approach to shape analysis via modern GM. They call into question the accuracy, robustness, and reproducibility of GM, and demonstrate how PCA introduces statistical artefacts specific to the data, thus challenging its scientific rigor. The authors demonstrate the superiority of machine learning methods in classification and outlier detection tasks. The paper is well-written and provides strong evidence in support of the authors' argument. Thus, in my opinion, it constitutes a major contribution to the field of physical anthropology, as it provides a critical and necessary evaluation of what has become a basic tool for studying morphology, and of the assumptions allowing its application for phylogenetic inferences. Again, I am not an expert in these statistical methods, nor a geneticist, but the authors' contribution is of substantial relevance to our field (physical anthropology). The examples of NR fossils and HLD 6 are cases in point, in line with other notable examples of critical assessment of phylogenetic inferences made on the basis of PCA results of GM analysis. For example, see Lordkipanidze et al.'s (2014) GM analyses of the Dmanisi fossils, suggesting that the five crania represent a single regional variant of Homo erectus; and see Schwartz et al.'s (2014) comment on their findings, claiming that the dental, mandibular, and cranial morphology of these fossils suggest taxic diversity. Schwartz et al. (2014) ask, "Why did the GMA of 78 landmarks not capture the visually obvious differences between the Dmanisi crania and specimens commonly subsumed H. erectus? ... one wonders how phylogenetically reliable a method can be that does not reflect even easily visible gross morphological differences" (p. 360).
As an alternative to the PCA step in GM, the authors tested eight leading supervised learning classifiers and outlier detection methods on three-dimensional datasets. The authors demonstrated inconsistency of PCA clustering with the taxonomy of the species investigated for the reconstruction of their phylogeny, by analyzing a database comprising landmarks of 6 known species that belong to the Old World monkeys tribe Papionini, using PCA for classification. The authors also demonstrated that high explained variance should not be used as an estimate of high accuracy (reliability). Then, the authors altered the dataset in several ways to simulate the characteristic nature of paleontological data.
The authors excluded taxa from the database to study how PCA and alternative classifiers are affected by partial sampling, and the results presented in Figures 4 and 5, among others, are quite remarkable in showing the deviations from the benchmark data. These results expose the perils of applying PCA and GM for interpreting morphological data. Furthermore, they provide evidence showing that the alternative classifiers are superior to PCA, and that they are less susceptible to experimenter intervention. Similar results, i.e., inconsistencies in the PC plots, were obtained in examinations of the effect of removing specimens from the dataset and in the interesting test of removing landmarks to simulate partial morphological data, as is often the case with fossils. To test the combined effect of these data alterations, the authors combined removal of taxa, specific samples, and landmarks from the dataset. In this case, as well, the PCA results indicate deviation from the benchmark data. However, the ML classifiers could not remedy the situation. The authors discuss how these inconsistencies may lead to different interpretations of the data, and in turn, different phylogenetic conclusions. Lastly, the authors simulated the situation of a specimen of unknown taxonomy using outlier detection methods, demonstrating LOF's ability to identify a novelty in the morphospace.
References<br /> Bookstein FL. 1991. Morphometric tools for landmark data: geometry and biology [Orange book]. Cambridge New York: Cambridge University Press.<br /> Cooke SB, and Terhune CE. 2015. Form, function, and geometric morphometrics. The Anatomical Records 298:5-28.<br /> Lordkipanidze D, et al. 2013. A complete skull from Dmanisi, Georgia, and the evolutionary biology of early Homo. Science 342: 326-331.<br /> Schwartz JH, Tattersall I, and Chi Z. 2014. Comment on "A complete skull from Dmanisi, Georgia, and the evolutionary biology of Early Homo". Science 344(6182): 360-a.
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Joint Public Review:
Roget et al. build on their previous work developing a simple theoretical model to examine whether ageing can be under natural selection, challenging the mainstream view that ageing is merely a byproduct of other biological and evolutionary processes. The authors propose an agent-based model to evaluate the adaptive dynamics of a haploid asexual population with two independent traits: fertility timespan and mortality onset. Through computational simulations, their model demonstrates that ageing can give populations an evolutionary advantage. Notably, this observation arises from the model without invoking any explicit energy tradeoffs, commonly used to explain this relationship.
Additionally, the theoretical model developed here indicates that mortality onset is generally selected to start before the loss of fertility, irrespective of the initial values in the population. The selected relationship between the fertility timespan and mortality onset depends on the strength of fertility and mortality effects, with larger effects resulting in the loss of fertility and mortality onset being closer together. By allowing for a trans-generational effect on ageing in the model, the authors show that this can be advantageous as well, lowering the risk of collapse in the population despite an apparent fitness disadvantage in individuals. Upon closer examination, the authors reveal that this unexpected outcome is a consequence of the trans-generational effect on ageing increasing the evolvability of the population (i.e., allowing a more effective exploration of the parameter landscape), reaching the optimum state faster.
The simplicity of the proposed theoretical model represents both the major strength and weakness of this work. On one hand, with an original and rigorous methodology, the logic of their conclusions can be easily grasped and generalised, yielding surprising results. Using just a handful of parameters and relying on direct competition simulations, the model qualitatively recapitulates the negative correlation between lifespan and fertility without requiring energy tradeoffs. This alone makes this work an important milestone for the rapidly growing field of adaptive dynamics, opening many new avenues of research, both theoretically and empirically.
On the other hand, the simplicity of the model also makes its relationship with living organisms difficult to gauge, leaving open questions about how much the model represents the reality of actual evolution in a natural context. In particular, a more explicit discussion on how the specifics of the model can impact the results and their interpretation is needed. For example, the lack of mechanistic details on the trans-generational effect on ageing makes the results difficult to interpret. Even if analytical results are obtained, most of the observations appear derived from simulations as they are currently presented. Also, the choice of parameters for the simulations shown in the paper and how it relates to our biological knowledge is not fully addressed by the authors. Finally, the conclusions of evolvability are insufficiently supported, as the authors do not show if the wider genotypic variability in populations with the ageing trans-generational effect is, in fact, selected.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, Faniyan and colleagues build on their recent finding that renal Glut2 knockout mice display normal fasting blood glucose levels despite massive glucosuria. Renal Glut2 knockout mice were found to exhibit increased endogenous glucose production along with decreased hepatic metabolites associated with glucose metabolism. Crh mRNA levels were higher in the hypothalamus while circulating ACTH and corticosterone was elevated in this model. While these mice were able to maintain normal fasting glucose levels, ablating afferent renal signals to the brain resulted in substantially lower blood glucose levels compared to wildtype mice. In addition, the higher CRH and higher corticosterone levels of the knockout mice were lost following this denervation. Finally, acute phase proteins were altered, plasma Gpx3 was lower, and major urinary protein MUP18 and its gene expression were higher in renal Glut2 knockout mice. Overall, the main conclusion that afferent signaling from the kidney is required for renal glut2 dependent increases in endogenous glucose production is well supported by these findings.
Strengths:
An important strength of the paper is the novelty of the identification of kidney to brain communication as being important for glucose homeostasis. Previous studies had focused on other functions of the kidney modulated by or modulating brain function. This work is likely to promote interest in CNS pathways that respond to afferent renal signals and the response of the HPA axis to glucosuria. Additional strengths of this paper stem from the use of incisive techniques. Specifically, the authors use isotope enabled measurement of endogenous glucose production by GC-MS/MS, capsaicin ablation of afferent renal nerves, and multifiber recording from the renal nerve. The authors also paid excellent attention to rigor in the design and performance of these studies. For example, they used appropriate surgical controls, confirmed denervation through renal pelvic CGRP measurement, and avoided the confounding effects of nerve regrowth over time. These factors strengthen confidence in their results. Finally, humans with glucose transporter mutations and those being treated with SGLT2 inhibitors show a compensatory increase in endogenous glucose production. Therefore, this study strengthens the case for using renal Glut2 knockout mice as a model for understanding the physiology of these patients.
Weaknesses:
A few weaknesses exist. Most concerns relate to the interpretation of this study's findings. The authors state that loss of glucose in urine is sensed as a biological threat based on the HPA axis activation seen in this mouse model. This interpretation is understandable but speculative. Importantly, whether stress hormones mediate the increase in endogenous glucose production in this model and in humans with altered glucose transporter function remains to be demonstrated conclusively. For example, the paper found several other circulating and local factors that could be causal. This model is also unable to shed light on how elevated stress hormones might interact with insulin resistance, which is known to increase endogenous glucose production. That issue is of substantial clinical relevance for patients with T2D and metabolic disease. Finally, while findings from the Glut2 knockout mice are of scientific interest, it should be noted that the Glut2 receptor is critical to the function of pancreatic islets and as such is not a good candidate for pharmacological targeting
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The study investigated how root cap cell corpse removal affects the ability of microbes to colonize Arabidopsis thaliana plants. The findings demonstrate how programmed cell death and its control in root cap cells affect the establishment of symbiotic relationships between plants and fungi. Key details on molecular mechanisms and transcription factors involved are also given. The study suggests reevaluating microbiome assembly from the root tip, thus challenging traditional ideas about this process. While the work presents a key foundation, more research along the root axis is recommended to gain a better understanding of the spatial and temporal aspects of microbiome recruitment.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, the authors performed molecular dynamics (MD) simulations to investigate the molecular basis of the association of alpha-synuclein chains under molecular crowding and salt conditions. Aggregation of alpha-synuclein is linked to the pathogenesis of Parkinson's disease, and the liquid-liquid phase separation (LLPS) is considered to play an important role in the nucleation step of the alpha-synuclein aggregation. This paper re-tuned the Martini3 coarse-grained force field parameters, which allows long-timescale MD simulations of intrinsically disordered proteins with explicit solvent under diverse environmental perturbation. Their MD simulations showed that alpha-synuclein does not have a high LLPS-forming propensity, but the molecular crowding and salt addition tend to enhance the tendency of droplet formation and therefore modulate the alpha-synuclein aggregation. The MD simulation results also revealed important intra and inter-molecule conformational features of the alpha-synuclein chains in the formed droplets and the key interactions responsible for the stability of the droplets. These MD simulation data add biophysical insights into the molecular mechanism underlying the association of alpha-synuclein chains, which is important for understanding the pathogenesis of Parkinson's disease.
Strengths:
(1) The re-parameterized Martini 3 coarse-grained force field enables the large-scale MD simulations of the intrinsically disordered proteins with explicit solvent, which will be useful for a more realistic description of the molecular basis of LLPS.
(2) This paper showed that molecular crowding and salt contribute to the modulation of the LLPS through different means. The molecular crowding minimally affects surface tension, but adding salt increases surface tension. It is also interesting to show that the aggregation pathway involves the disruption of the intra-chain interactions arising from C-terminal regions, which potentially facilitates the formation of inter-chain interactions.
Weaknesses:
(1) Although the authors emphasized the advantage of the Martini3 force field for its explicit description of solvent, the whole paper did not discuss the water's role in the aggregation and LLPS.
(2) This paper discussed the effects of crowders and salt on the surface tension of the droplets. The calculation of the surface tension relies on the droplet shape. However, for the formed clusters in the MD simulations, the typical size is <10, which may be too small to rigorously define the droplet shape. As shown in previous work cited by this paper [Benayad et al., J. Chem. Theory Comput. 2021, 17, 525−537], the calculated surface tension becomes stable when the chain number is larger than 100.
(3) In this work, the Martini 3 force field was modified by rescaling the LJ parameters \epsilon and \sigma with a common factor \lambda. It has not been very clearly described in the manuscript why these two different parameters can be rescaled by a common factor and why it is necessary to separately tune these two parameters, instead of just tuning the coefficient \epsilon as did in a previous work [Larsen et al., PLoS Comput Biol 16: e1007870].
(4) Both the sizes and volume fractions of the crowders can affect the protein association. It will be interesting to perform MD simulations by adding crowders with various sizes and volume fractions. In addition, in this work, the crowders were modelled by fullerenes, which contribute to protein aggregation mainly by entropic means as discussed in the manuscript. It is not very clear how the crowder effect is sensitive to the chemical nature of the crowders (e.g., inert crowders with excluded volume effect or crowders with non-specific attractive interactions with proteins, etc) and therefore the force field parameters.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors' research group had previously demonstrated the release of large multivesicular body-like structures by human colorectal cancer cells. This manuscript expands on their findings, revealing that this phenomenon is not exclusive to colorectal cancer cells but is also observed in various other cell types, including different cultured cell lines, as well as cells in the mouse kidney and liver. Furthermore, the authors argue that these large multivesicular body-like structures originate from intracellular amphisomes, which they term "amphiectosomes." These amphiectosomes release their intraluminal vesicles (ILVs) through a "torn-bag mechanism." Finally, the authors demonstrate that the ILVs of amphiectosomes are either LC3B positive or CD63 positive. This distinction implies that the ILVs either originate from amphisomes or multivesicular bodies, respectively.
Strengths:
The manuscript reports a potential origin of extracellular vesicle (EV) biogenesis. The reported observations are intriguing.
Weaknesses:
It is essential to note that the manuscript has issues with experimental designs and lacks consistency in the presented data. Here is a list of the major concerns:
(1) The authors culture the cells in the presence of fetal bovine serum (FBS) in the culture medium. Given that FBS contains a substantial amount of EVs, this raises a significant issue, as it becomes challenging to differentiate between EVs derived from FBS and those released by the cells. This concern extends to all transmission electron microscopy (TEM) images (Figure 1, 2P-S, S5, Figure 4 P-U) and the quantification of EV numbers in Figure 3. The authors need to use an FBS-free cell culture medium.
(2) The data presented in Figure 2 is not convincingly supportive of the authors' conclusion. The authors argue that "...CD81 was present in the plasma membrane-derived limiting membrane (Figures 2B, D, F), while CD63 was only found inside the MV-lEVs (Fig. 2A, C, E)." However, in Figure 2G, there is an observable CD63 signal in the limiting membrane (overlapping with the green signals), and in Figure 2J, CD81 also exhibits overlap with MV-IEVs.
(3) Following up on the previous concern, the authors argue that CD81 and CD63 are exclusively located on the limiting membrane and MV-IEVs, respectively (Figure 2-A-M). However, in lines 104-106, the authors conclude that "The simultaneous presence of CD63, CD81, TSG101, ALIX, and the autophagosome marker LC3B within the MV-lEVs..." This statement indicates that CD63 and CD81 co-localize to the MV-IEVs. The authors need to address this apparent discrepancy and provide an explanation.
(4) The specificity of the antibodies used in Figure 2 should be validated through knockout or knockdown experiments. Several of the antibodies used in this figure detect multiple bands on western blots, raising doubts about their specificity. Verification through additional experimental approaches is essential to ensure the reliability and accuracy of all the immunostaining data in this manuscript.
(5) In Figures 2P-R, the morphology of the MV-IEVs does not resemble those shown in Figures 1-A, H, and D, indicating a notable inconsistency in the data.
(6) There are no loading controls provided for any of the western blot data. Additionally, for Figures 2-S4B, the authors should run the samples from lanes i-iii in a single gel.
(7) In Figure 2-S4, is there co-localization observed between LC3RFP (LC3A?) with other MV-IFV markers? How about LC3B? Does LC3B co-localize with other MV-IFV markers?
(8) The TEM images presented in Figure 2-S5, specifically F, G, H, and I, do not closely resemble the images in Figure 2-S5 K, L, M, N, and O. Despite this dissimilarity, the authors argue that these images depict the same structures. The authors should provide an explanation for this observed discrepancy to ensure clarity and consistency in the interpretation of the presented data.
(9) For Figures 3C and 3-S1, the authors should include the images used for EV quantification. Considering the concern regarding potential contamination introduced by FBS (concern 1), it is advisable for the authors to employ an independent method to identify EVs, thereby confirming the reliability of the data presented in these figures.
(10) Do the amphiectosomes released from other cell types as well as cells in mouse kidneys or liver contain LC3B positive and CD63 positive ILVs?
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Reviewer #1 (Public Review):
Summary:
This study aims to understand how cell fusion contributes to wound healing using a laser-induced injury in the notum epithelium of a developing fruit fly. The authors meticulously characterize the epithelial fusion events using a live imaging approach and report that syncytia arise by 'border breakdown' and 'cell shrinking'. The syncytial epithelial cells also appear to outcompete mononucleated cells and preferentially dissolve their tangential borders, which correlates with the accumulation of actin at the leading edge.
Strengths:
The strength of this study is the authors' live imaging approach to capture these dynamic fusion events that are a fundamental, yet poorly understood biological process.
Weaknesses:
A major weakness is that all the authors' conclusions are based on descriptive studies, in which the role of cell fusion is not directly tested. This is particularly important because other models of wound-induced polyploidization have demonstrated that another cytoskeletal protein, myosin, was upregulated and dependent on endoreplication, and not cell fusion. Therefore it remains unclear to what extent cell fusion, endoreplication, or both are required to outcompete mononucleated cells as well as pool actin as described in this study.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This is an original manuscript submission by Tatekoshi et al entitled, "Human induced pluripotent stem cell-derived cardiomyocytes to study inflammation-induced diastolic dysfunction." Based on the premise that treated HIV individuals commonly have heart failure with preserved ejection fraction, yet robust animal models have not been established, the team developed iPS-CM models to study HFpEF with this angle in mind. The group established iPS-CMs using standard methods and studied TNFa and IFNy effects on calcium transients. They observed that both cytokines increased calcium transient decay and downstroke times, which could be reversed by mitoTempo treatment in the case of TNFa. To determine how mitochondrial dysfunction may impact the cytokine-induced calcium transient changes, the team measured OCR treatment changes. They observed that NAC and TNFa co-treated cells demonstrated reduced OCR. The team went on to test the effects of antiretroviral therapies including tenofovir, relategravir, elvitegravir, and darunavir at 3-10 uM levels in iPS-CMs. The team noted that ART treatments reversed the diastolic dysfunction associated with TNFa treatment suggesting that ART therapies may improve diastolic dysfunction that is associated with TNFa signaling directly in cardiomyocytes. Following up on this treatment effect, the team screened several other candidates across drug classes and identified that dapagliflozin (SGLT2i) reversed diastolic dysfunction induced by TNFa. Finally, the team collected human serum from patients with HIV+ patients from two hospitals - Northwestern with diastolic dysfunction by cMRI, and UCSF with normal diastolic function by echo. Both cohort serum samples did not change calcium transients in iPS-CMs. However, due to numerous and significant major methodological concerns, and the potential low impact of the study results, this manuscript is expected to be of very low impact to the field in its current form.
Strengths:
1) From a significance standpoint, understanding the mechanisms of HFpEF, particularly in conditions such as HIV would be very impactful.
2) Collecting HIV patient serum and identifying a plasma factor that impacts cardiac function could be very significant if successful.
Weaknesses:
(1) I am not convinced how this study relates to HIV individual HFpEF, and the study design does not seem to be well thought out.
(2) The connectivity of the study experiments is loose, and data analysis and conclusions are broadly overstated and misinterpreted.
(3) For example the study lacks any measure of diastolic contractile function, and even if performed, the relevance of TNFa treatments to cells in vitro in these immature cell contexts would remain unclear. There is surprisingly no reported molecular analyses of potential mechanisms of the calcium transient changes. The study falls short in molecular detail and instead relies on drug treatments and responses that are hard to interpret with dosages that are not well justified and treatments that are numerous. Unclear what changes in calcium transients mean functionally without a comprehensive assessment of CM biomechanical contraction and relaxation measurements, and this would also require parallel molecular investigations of potential targets of any phenotypes observed.
(4) Calcium transient data need to be better illustrated such as with representative peak tracings. The data overall is with too few samples, particularly given the inherent heterogeneity of iPS-CM studies. The iPS-CM system as a model for diastolic dysfunction remains unestablished.
(5) There are unclear dose choices for the various ART drugs tested, as well as the other drugs tested such as SGLT2i. Besides the observation that SLC5A2 (SGLT2 target) is not established to be expressed in adult mammalian cardiomyocytes.
(6) HIV plasma samples were not tested for cytokine levels, but this could be done to assess the validity of the final experiments. It is unclear what is being tested with these experiments.
(7) The choice of serum controls from a second institution (UCSF) opens up concerns over batch effects unrelated to differences in diastolic dysfunction. However, there were no differences with the Northwestern samples. It is unclear why this data is included as it does not add to the impact of the study.
(8) There are concerns about the quality of the iPS-CMs since there is no cell imaging or molecular analyses. Figure 5 Supplement 1 images are of low quality and low resolution to assess cell quality. Overall the iPS-CM QC data is extremely sparse
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Reviewer #1 (Public Review):
Summary:
The manuscript by Relovska and colleagues aims to decipher the importance of sterol homeostasis on male reproduction and, in particular, the impact of altered sterol homeostasis in sperm cells. To this end, they are generating a global line of Dhcr24 transgenic mice by mating Dhcr24fl/fl mice (overexpressing the construct in the Rosa269c gene locus) with EIla 100 CRE mice (expressing Cre recombinase in the early mouse embryo).
The data provided are robust, using a range of approaches from sperm analysis (structure, function) to lipid analysis. Results show that overexpression of DHCR24 (TG) leads to altered sterol homeostasis in spermatozoa. Sperm from TG mice have abnormal mitochondria and sperm tails. TG spermatozoa have reduced efficiency in undergoing the acrosomal reaction. Furthermore, the data suggest that TG spermatozoa have an altered metabolism with increased oxygen consumption. These data highlight that desmosterol depletion and/or altered sterol homeostasis impact sperm morphology, number, motility, and metabolism, resulting in reduced male fertility.
Strengths:
The manuscript is clear and well-written, and the results are presented in high-quality figures.
Weaknesses:
The main concern is the clear analysis of the rodent model. Indeed, the use of this particular Cre leads to whole-body overexpression, the remaining question is whether the observed effects are directly mediated by the testicular impacts of Dhcr24 overexpression. Even if it is a testicular effect, we can't conclude where it comes from. Is it at the level of spermatogenesis, as the authors speculate? Furthermore, the authors mention that normally, Dhcr24c is mainly expressed in spermatogonia, so it's not clear why they focus only on spermatozoa, which in WT males do not normally express dhcr24 according to the authors. It is worth clarifying the testicular phenotype in more detail.
The lower level of TG in aged mice could suggest an extinction of the transgene at least in sperm during aging, which could be difficult to reconcile with the observed phenotype. With this in mind, it would be interesting to define the penetrance of the phenotype during aging, to define variability between mice, and to clearly define potential correlations between sterol levels and fertility disorders, or altered sperm parameters.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The goal of this study was to use in vitro cell populations to determine mechanisms that may be important for the propagation of epimutations induced by EDCs in vivo. To do this, authors exposed induced pluripotent stem cells (iPS), somatic cells (Sertoli, granulosa), and primordial germ cell like cells (PGCLCs) to BPS, and conducted epigenomic and transcriptomic analyses on outcomes. The importance of estrogen receptors, and the relationship of epigenomic results to genomic sites expressing EREs, were also determined in the different cell types. Results revealed differential effects of BPS in each cell population on each of these endpoints, and that epimutations were prevalent in enhancer regions with EREs with the exception of PGCLCs (which do not express ERs). The authors speculate that because epimutations also occurred in regions without EREs, especially in PGCLCs, other mechanisms may be in place. Finally, epimutations induced in iPSCs exposed to BPS that were subsequently differentiated into PGCLCs demonstrated that most epimutations were corrected.
Strengths:
A strength of this work is the use of different cell types representing somatic cells that would be the major recipient of EDC exposure; pluripotent cells representing preimplantation embryos; and PGCLCs that model the early germline in which epigenetic reprogramming takes place. Work differentiating the iPSCs from PGCLCs with or without BPS exposure at the iPSC level is also very informative as it suggests that most epimutations are corrected, at least in vitro. The paper is well-written and studies were technically well-executed and validated. Results are novel and likely to be of interest to those interested in transgenerational inheritance of environmentally-induced traits, as well as others more broadly interested in epigenetic mechanisms.
Critique/Weaknesses:
(1) A problem with in vitro work is that homogeneous cell lines/cultures are, by nature, absent from the rest of the microenvironment. The authors need to discuss this.
(2) What are n's/replicates for each study? Were the same or different samples used to generate the data for RNA sequencing, methylation beadchip analysis, and EM-seq? This clarification is important because if the same cultures were used, this would allow comparisons and correlations within samples.
(3) In Figure 1, it is interesting that the 50 uM BPS dose mainly resulted in hypermethylation whereas 100 uM appears to be mainly hypomethylation. (This is based on the subjective appearance of graphs). The authors should discuss and/or present these data more quantitatively. For example, what percentage of changes were hypo/hypermethylation for each treatment? How many DMRs did each dose induce? For the RNA-seq results, again, what were the number of up/down-regulated genes for each dose?
(4) Also in Figure 1, were there DMRs or genes in common across the doses? How did DMRs relate to gene expression results? This would be informative in verifying or refuting expectations that greater methylation is often associated with decreased gene expression.
(5) In Figure 2, was there an overlap in the hypo- and/or hyper-methylated DMCs? Please also add more description of the data in 2b to the legend including what the dot sizes/colors mean, etc. Some readers (including me) may not be familiar with this type of data presentation. Some of this comes up in Figure 4, so perhaps allude to this earlier on, or show these data earlier.
(6) iPSCs were derived from male mice MEFs, and subsequently used to differentiate into PGCLCs. The only cell type from an XX female is the granulosa cells. This might be important, and should be mentioned and its potential significance discussed (briefly).
(7) EREs are only one type of hormone response element. The authors make the point that other mechanisms of BPS action are independent of canonical endocrine signaling. Would authors please briefly speculate on the possibility that other endocrine pathways including those utilizing AREs or other HREs may play a role? In other words, it may not be endocrine signaling independent. The statement that the differences between PGCLCs and other cells are largely due to the absence of ERs is overly simplistic.
(8) Interpretation of data from the GO analysis is similarly overly simplistic. The pathways identified and discussed (e.g. PI3K/AKT and ubiquitin-like protease pathways are involved in numerous functions, both endocrine and non-endocrine. Also, are the data shown in Figure 6a from all 4 cell types? I am confused by the heatmap in 6c, which genes were significantly affected by treatment in which cell types?
(9) In Figure 7, what were the 138 genes? Any commonalities among them?
(10) The Introduction is very long. The last paragraph, beginning line 105, is a long summary of results and interpretations that better fit in a Discussion section.
(11) Provide some details on husbandry: e.g. were they bred on-site? What food was given, and how was water treated? These questions are to get at efforts to minimize exposure to other chemicals.
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Reviewer #1 (Public Review):
Wang et al investigated the evolution, expression, and function of the X-linked miR-506 miRNA family. They showed that the miR-506 family underwent rapid evolution. They provided evidence that miR-506 appeared to have originated from the MER91C DNA transposons. Human MER91C transposon produced mature miRNAs when expressed in cultured cells. A series of mouse mutants lacking individual clusters, a combination of clusters, and the entire X-linked cluster (all 22 miRNAs) were generated and characterized. The mutant mice lacking four or more miRNA clusters showed reduced reproductive fitness (litter size reduction). They further showed that the sperm from these mutants were less competitive in polyandrous mating tests. RNA-seq revealed the impact of deletion of miR-506 on the testicular transcriptome. Bioinformatic analysis analyzed the relationship among miR-506 binding, transcriptomic changes, and target sequence conservation. The miR-506-deficient mice did not have apparent effect on sperm production, motility, and morphology. Lack of severe phenotypes is typical for miRNA mutants in other species as well. However, the miR-506-deficient males did exhibit reduced litter size, such an effect would have been quite significant in an evolutionary time scale. The number of mouse mutants and sequencing analysis represent a tour de force.
Strengths:
This study is a comprehensive investigation of the X-linked miR-506 miRNA family. It provides important insights into the evolution and function of the miR-506 family.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The present study conducted by Berger et al. delves into the extent to which memory formation relies on available energy reserves. While aversive memory formation has been extensively studied in this context, the investigation into appetitive memory formation has been comparatively sparse. It has long been recognized that flies can only form appetitive memory under conditions of starvation. However, the authors of this study go beyond this understanding by revealing that not only the duration of starvation matters, but it also dictates the type of memory formed, whether short- or long-term memory. The authors illustrate that internal glycogen stores play a crucial role in this process, facilitated by insulin-like signaling in octopaminergic reward neurons, which integrates internal energy reserves into memory formation. Consequently, the authors propose that octopamine serves as a negative regulator of various forms of memory, shedding light on the enduring question of the octopaminergic neuronal system's involvement in appetitive memory formation, which has been overshadowed by the focus on the dopaminergic system in recent years. Additionally, the findings contribute to the ongoing debate concerning the role of insulin receptors, whether they function within neurons themselves or in glial cells. Moreover, the authors not only convincingly demonstrate that octopamine negatively regulates appetitive memory formation, but they also propose a mechanism whereby the insulin receptor in octopaminergic neurons senses the internal energy status and subsequently modulates the activity of these neurons. The experiments are meticulously designed, employing a variety of behavioral assays, genetic tools for manipulating neuronal activity, and state-of-the-art imaging techniques. The conclusions are well supported by the data and carefully performed controlled experiments, yielding high-quality data.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
This paper acknowledges that most development occurs in social contexts, with other social partners. The authors put forth two main frameworks of how development occurs within a social interaction with a caregiver. The first, is that although social interaction with mature partners is somewhat bi-directional, mature social partners exogenously influence infant behaviors and attention through "attentional scaffolding", and that in this case infant attention is reactive to caregiver behavior. The second framework posits that caregivers support and guide infant attention by contingently responding to reorientations in infant behavior, thus caregiver behaviors are reactive to infant behavior. The aim of this paper is to use moment-to-moment analysis techniques to understand the directionality of dyadic interaction.
Strengths:
The question driving this study is interesting and a genuine gap in the literature. Almost all development occurs in the presence of a mature social partner. While it is known that these interactions are critical for development, the directionality of how these interactions unfold in real-time is less known.
The analyses are appropriate for the question at hand, capturing small moment-to-moment dynamics in both infant and child behavior, and their relationships with themselves and each other. Autocorrelations and cross-correlations are powerful tools that can uncover small but meaningful patterns in data that may not be uncovered with other more discretized analyses (i.e. regression).
Weaknesses:
While the authors improved their explanation of why they are using cross-correlations and the resting EEG patterns and what they mean, they did not address this specific piece of feedback: to explain their rationale for only focussing on fronto-temporal channels, rather than averaging channels across the whole brain.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
Through a set of experiments and model simulations, the authors tested whether the commonly assumed world model of gravity was a faithful replica of the physical world. They found that participants did not model gravity as single, fixed vector for gravity but instead as a distribution of possible vectors. Surprisingly, the width of this distribution was quite large (~20 degrees). While previous accounts had suggested that this uncertainty was due to perceptual noise or an inferred external perturbation, the authors suggest that this uncertainty simply arises from a noisy distribution of the representation of gravity's direction. A reinforcement learning model with an initial uniform distribution for gravity's direction ultimately converged to a precision on the same order as the human participants, which lends support to the authors' conclusion and suggests that this distribution is learned through experience. What's more, further simulations suggest that representing gravity with such a wide distribution may balance speed and accuracy, providing a potentially normative explanation for the world model with gravity as a distribution.
Strengths:
The authors present surprising findings in a relatively straight-forward in a now classic experimental task. They provide a normative explanation based on a resource-rational framework for why people may have a stochastic world model instead of a deterministic world model. While the stochastic world model could be the result of people mentally simulating an external perturbation, the authors include several control experiments to test this possibility.
Weaknesses:
The possibility of inferred external perturbations, as opposed to a stochastic world model, is difficult to rule out. This could stem from how people interpret task instructions and it will likely take many, clever studies, to fully reconcile these two alternative accounts.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The study examines the role of release site clearance in synaptic transmission during repetitive activity under physiological conditions in two types of central synapses, calyx of Held and hippocampal CA1 synapses. After acute block of endocytosis by pharmacology, deeper synaptic depression or less facilitation was observed in two types of synapses. Acute block of CDC42 and actin polymerization, which possibly inhibits the activity of Intersectin, affected synaptic depression at the calyx synapse, but not at CA1 synapses. The data suggest an unexpected, fast role of the site clearance in counteracting synaptic depression.
Strengths:
The study uses acute block of the molecular targets with pharmacology together with precise electrophysiology. The experimental results are clear cut and convincing. The study also examines the physiological roles of the site clearance using action potential-evoked transmission at physiological Ca and physiological temperature at mature animals. This condition has not been examined.
Weaknesses:
Pharmacology may have some off-target effects, though acute manipulation should be appreciated and the authors have tried several reagents to verify the overall conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Gillespie et al. introduced a novel neurofeedback (NF) procedure to train rats in enhancing their sharp-wave ripple (SWR) rate within a short duration, a key neural mechanism associated with memory consolidation. The training, embedded within a spatial memory task, spanned 20-30 days and utilized food rewards as positive reinforcement upon SWR detection. Rats were categorized into NF and control groups, with the NF group further divided into NF and delay trials for within-subject control. While single trial differences were elusive due to the variability of SWR occurrence, the study revealed that statistically rats in NF trials exhibited a notably higher SWR rate before receiving rewards compared to delay trials. This difference was even more pronounced when juxtaposed with rats not exposed to NF training (control group). The unique design of blending the NF phase with the memory dependent spatial task enabled the authors to analyze whether the NF training influence the task performance and replay content during SWRs across three different conditions (NF trials, delay trials and control group). Interestingly, despite the NF training, there was no significant improvement or decline in the performance of the spatial memory task, and the replay content remained consistent across all three conditions. Hence, the operant conditioning only amplified the SWR rate before reward in NF trials without altering the task performance and the replay content during SWR. Moreover, considering the post-reward period, the total SWR count was consistent across all conditions as well, meaning the NF training also do not affect the total SWR count. The study concludes with the hypothesis of a potential homeostatic mechanism governing the total SWR production in rats. This research significantly extends previous work by Ishikawa et al. (2014), offering insights into the NF training with external reward on the SWR rate/counts, replay content and task performance.
Strengths:
- Integration of NF task and spatial memory task in a single trial<br /> The integration of NF training within a spatial memory task poses significant challenges. Gillespie and colleagues overcame this by seamlessly blending the NF task and the spatial memory task into a single trial. Each trial involved a rat undergoing three steps: First, initiating a trial. Second, moving to either the NF port or the delay trial port, as indicated by an LED, and then maintaining a nosepoke at one of the center ports. During this step, the rat had to keep its nose (in the NF port) until a sharp-wave ripple (SWR) exceeding a set threshold was detected, which then triggered a reward, or until a variable time elapsed (in the delay port). Third, the rat would choose one of eight arms to explore before starting the next trial. This integration of the two tasks (step two as the NF task and step three as the spatial memory task) facilitated a direct analysis of the impact of NF training on behaviorally relevant replay content during SWRs and the performance in the spatial memory task.
- Clear Group Separation<br /> A robust study design necessitates clear distinctions between experimental conditions to ensure that observed differences can be attributed to the variable under investigation. This study meticulously categorized rats into three distinct conditions: NF trials, delay trials (for within-subject control), and a control group (for across-subject control). Furthermore, for each trial, the times of interest (TOI) were separated into pre-reward and post-reward periods. This clear separation ensures that any observed differences in SWR rates and other outcomes can be confidently attributed to the effects of neurofeedback training during specific time periods, minimizing potential confounding factors.
- Evidence of SWR rate modulation<br /> The study's results offer compelling evidence that rats can be trained to modulate their SWR rates during the pre-reward period. This is evident from the observation that rats in the NF trials consistently displayed a higher SWR rate before receiving rewards compared to those in delay trials or the control group (Fig. 2). Such findings not only validate the efficacy of the NF paradigm but also underscore the potential of operant conditioning in influencing neural mechanisms. The observation that rats were able to produce larger SWR events by modulating their occurrence rate, rather than merely waiting for these events, suggests a learned strategy to generate them more efficiently.
- Evidence of SWR count homeostasis<br /> A notable finding from the study was the observation of a consistent total SWR count during both pre-reward and post-reward periods across all conditions, despite the evident increase in SWR rates during the pre-reward period in NF trials. This points to a potential homeostatic mechanism governing SWR production in rats. This balance suggests that while NF training can modulate the timing and rate of SWRs over a short duration, it doesn't influence the overall count of SWRs over a longer period. Such a mechanism might be essential in ensuring that the brain neither overcompensates nor depletes its capacity for SWRs, maintaining the overall neural balance and functionality. This discovery deepens our understanding of neural mechanisms and highlights potential avenues for future research into the regulatory processes governing neural activity.
In this revision, the paper explores a neurofeedback technique in rats that modulates hippocampal sharp-wave ripple (SWR) rates, crucial for memory replay, without altering the content of those replays. The study demonstrates that neurofeedback can specifically increase SWR rates during a task's pre-reward phase. Revisions address concerns about movement's impact on SWR rates, clarify the statistical approach used, and modify the title for accuracy, now emphasizing the modulation of memory replay rates rather than suggesting alterations to memory content itself. I think all the concerns in the previous version have been addressed.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The study investigates parafoveal processing during natural reading, combining eye-tracking and MEG techniques, building upon the RIFT paradigm previously introduced by Pan et al. (2021). Overall, the manuscript is well-written with a clear structure, and the data analysis and experimental results are presented in a lucid manner.
The authors have addressed the issues I raised in the previous round of review to my satisfaction. However, I still have two concerns that require the authors' consideration.
Firstly, the similarity between the RIFT analysis process in this study and traditional ERP analysis could lead readers to equate RIFT with components like N400, potentially influencing their interpretation of the results. Although the author's response has somewhat clarified my queries, I seek confirmation: does RIFT itself signify "visual attention" or the "allocation of attentional resources to the flickering target words" (line 208) in this study? While this may not be pivotal, as it primarily serves as an indicator to evaluate whether contextual congruity can indeed modulate the RIFT response rather than indicating early parafoveal semantic integration, I recommend that the authors explicitly address this point in the manuscript, maybe in the discussion section, to enhance reader comprehension of the article's rationale.
Secondly, regarding the study's conclusions, there appears to be an overemphasis in stating that "semantic information ... can also be integrated with the sentence context ..." (line 21-22). As raised by Reviewer 2 (Major Point 1) and acknowledged by the authors in the limitations of the revised manuscript (lines 403-412), the RIFT effect observed likely stems from local congruency. Therefore, adjusting the conclusion to "integrated with previous context" may offer a more precise reflection of the findings.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Zhu, et al present a genome-wide histone modification analysis comparing patients with schizophrenia (on or off antipsychotics) to non-psychiatric controls. The authors performed analyses across the dorsolateral prefrontal cortex and tested for enrichment of nearby genes and pathways. The authors performed analysis measuring the effect of age on the epigenomic landscape as well. This paper provides a unique resource around SCZ and its epigenetic correlates, and some potentially intriguing findings in the antipsychotic response dataset.
Comments on revised version:
The authors have adequately responded to my review comments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Sasaki et al. investigated methods to entrain vasomotion in awake wild-type mice across multiple regions of the brain using a horizontally oscillating visual pattern which induces an optokinetic response (HOKR) eye movement. They found that spontaneous vasomotion could be detected in individual vessels of their wild-type mice through either a thinned cranial window or intact skull preparation using a widefield macro-zoom microscope. They showed that low-resolution autofluorescence signals coming from the brain parenchyma could be used to capture vasomotion activity using a macro-zoom microscope or optical fibre, as this signal correlates well with the intensity profile of fluorescently-labelled single vessels. They show that vasomotion can also be entrained across the cortical surface using an oscillating visual stimulus with a range of parameters (with varying temporal frequencies, amplitudes, or spatial cycles), and that the amplitude spectrum of the detected vasomotion frequency increases with repeated training sessions. The authors include some control experiments to rule out fluorescence fluctuations being due to artifacts of eye movement or screen luminance and attempt to demonstrate some functional benefit of vasomotion entraining as HOKR performance improves after repeat training. These data add in an interesting way to the current knowledge base on vasomotion, as the authors demonstrate the ability to entrain vasomotion across multiple brain areas and show some functional significance to vasomotion with regards to information processing as HOKR task performance correlates well with vascular oscillation amplitudes.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Most studies in sensory neuroscience investigate how individual sensory stimuli are represented in the brain (e.g., the motion or color of a single object). This study starts tackling the more difficult question of how the brain represents multiple stimuli simultaneously and how these representations help to segregate objects from cluttered scenes with overlapping objects.
Strengths
The authors first document the ability of humans to segregate two motion patterns based on differences in speed. Then they show that a monkey's performance is largely similar; thus establishing the monkey as a good model to study the underlying neural representations.
Careful quantification of the neural responses in the middle temporal area during the simultaneous presentation of fast and slow speeds leads to the surprising finding that, at low average speeds, many neurons respond as if the slowest speed is not present, while they show averaged responses at high speeds. This unexpected complexity of the integration of multiple stimuli is key to the model developed in this paper.
One experiment in which attention is drawn away from the receptive field supports the claim that this is not due to the involuntary capture of attention by fast speeds.
A classifier using the neuronal response and trained to distinguish single-speed from bi-speed stimuli shows a similar overall performance and dependence on the mean speed as the monkey. This supports the claim that these neurons may indeed underlie the animal's decision process.
The authors expand the well-established divisive normalization model to capture the responses to bi-speed stimuli. The incremental modeling (eq 9 and 10) clarifies which aspects of the tuning curves are captured by the parameters.
Weaknesses
While the comparison of the overall pattern of behavioral performance between monkeys and humans is important, some of the detailed comparisons are not well supported by the data. For instance, whether the monkey used the apparent coherence simply wasn't tested and a difference between 4 human subjects and a single monkey subject cannot be tested statistically in a meaningful manner. I recommend removing these observations from the manuscript and leaving it at "The difference between the monkey and human results may be due to species differences or individual variability" (and potentially add that there are differences in the task as well; the monkey received feedback on the correctness of their choice, while the humans did not.)
A control experiment aims to show that the "fastest speed takes all" behavior is general by presenting two stimuli that move at fast/slow speeds in orthogonal directions. The claim that these responses also show the "fastest speed takes all" is not well supported by the data. In fact, for directions in which the slow speed leads to the largest response on its own, the population response to the bi-speed stimulus is the average of the response to the components. Only for the directions where the fast speed stimulus is the preferred direction is there a bias towards the faster speed (Figure 7A). The quantification of this effect in Figure 7B seems to suggest otherwise, but I suspect that this is driven by the larger amplitude of Rf in Figure 8, and the constraint that ws and wf are constant across directions. The interpretation of this experiment needs to be reconsidered.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This study compares experimental data recorded from the PFC of monkeys to the activity of recurrent neural networks trained to perform the same `task' as the monkeys, namely, to predict the delivery of reward following the presentation of visual stimuli. The visual information varied along 3 dimensions, color, shape, and width. Shape was always relevant for reward prediction, width was always irrelevant, and color was irrelevant at the beginning of the trial but became relevant later on, once it could be assessed together with shape. The neural data showed systematic changes in the representations of these features and of the expected reward as the learning progressed, and the objective of this study was to try to understand what principles could underlie these changes. The simulations and theoretical calculations indicated that the changes in PFC activity (throughout learning and throughout a trial) can be understood as an attempt by the circuitry to use an efficient representational strategy, i.e., one that uses as few spikes as possible, given that the resulting representation should be accurate enough for task performance.
Strengths:
- The paper is concise and clearly written.
- The paper shows that, in a neural circuit, the information that is decodable and the information that is task-relevant may relate in very different ways. Decodable information may be very relevant or very irrelevant. This fact is critical for interpreting the results of pure decoding studies, which often assume an equivalence. This take-home message is not emphasized by the authors, but I think is quite important.
- The results provide insight as to how neural representations may be transformed as a task is learned, which often results in subtle changes in selectivity and overall activity levels whose impact or reason is not entirely clear just by looking at the data.
Weaknesses:
The match between the real PFC and the model networks is highly qualitative, and as noted by the authors, comparisons only make sense in terms of *changes* between early and late learning. The time scales, activity levels, and decoding accuracies involved are all different between the model and recording data. This is not to disregard what the authors have done, but simply to point out an important limitation.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors bring together implanted radiofrequency coils, high-field MRI imaging, awake animal imaging, and sensory stimulation methods in a technological demonstration. The results are very detailed descriptions of the sensory systems under investigation.
Strengths:
- The maps are qualitatively excellent for rodent whole-brain imaging.<br /> - The design of the holder and the coil is pretty clever.
Weaknesses:
- Some unexpected regions appear on the whole brain maps, and the discussion of these regions is succinct.<br /> - The authors do not make the work and effort to train the animals and average the data from several hundred trials apparent enough. This is important for any reader who would like to consider implementing this technology.<br /> - The data is not available. This does not let the readers make their own assessment of the results.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors perform RNA-seq on FACS-isolated neurons from adult worms at days 1 and 8 of adulthood to profile the gene expression changes that occur with cognitive decline. Supporting data are included indicating that by day 7 of adulthood, learning and memory are reduced, indicating that this time point or after represents cognitively aged worms. Neuronal identity genes are reduced in expression within cognitively aged worms, whereas genes involved in proteostasis, transcription/chromatin, and stress response are elevated. A number of specific examples are provided, representing markers of specific neuronal subtypes, and correlating expression changes to the erosion of particular functions (e.g. motor neurons, chemosensory neurons, aversive learning neurons, etc).
To investigate whether the upregulation of genes in neurons with age is compensatory or deleterious, the authors reduced the expression of a set of three significantly upregulated genes and performed behavioral assays in young adults. In each case, reduction of expression improved memory, consistent with a model in which age-associated increases impair neuronal function. This claim would be bolstered by an experiment elevating the expression of these genes in young neurons, which should reduce the learning index if the hypothesis is correct.
The authors then characterize learning and memory in wild-type, daf-2, and daf-2/daf-16 worms with age and find that daf-2 worms have an extended ability to learn for approximately 10 days longer than wild types. This was daf-16 dependent. Memory was extended in daf-2 as well, and strikingly, daf-2;daf-16 had no short-term memory even at day 1. Transcriptomic analysis of FACS-sorted neurons was performed on the three groups at day 8. The authors focus their analysis on daf-2 vs. daf-2;daf-16 and present evidence that daf-2 neurons express a stress-resistance gene program. One question that remains unanswered is how well the N2 and daf-2;daf-16 correlate overall, and are there differences? This may be informative as wild type and daf-2;daf-16 mutants are not phenotypically identical when it comes to memory, and there may be differences that can be detected despite the overlap in the PCA. This analysis could reveal the daf-16 targets involved in memory.
The authors tested eight candidate genes that were more highly expressed in daf-2 neurons vs. daf-2;daf-16 and showed that reduction of 2 and 5 of these genes impaired learning and memory, respectively, in daf-2 worms. This finding implicates specific neuronal transcriptional targets of IIS in maintaining cognitive ability in daf-2 with age, which, importantly, are distinct from those in young wild type worms.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Huber proposes a theory where the role of the medial temporal lobe (MTL) is memory, where properties of spatial cells in the MTL can be explained through memory function rather than spatial processing or navigation. Instantiating the theory through a computational model, the author shows that many empirical phenomena of spatial cells can be captured, and may be better accounted through a memory theory. It is an impressive computational account of MTL cells with a lot of theoretical reasoning and aims to tightly relate to various spatial cell data.
In general, the paper is well written, but likely due to the complexity, there are various aspects of the paper that are difficult to understand. One point is that it is not entirely clear to me that it is a convincing demonstration of purely memory rather than navigation, but rather an account of the findings through the lens of memory. Below, I raise several big-picture theoretical questions. I also have some clarification questions about the model (where I also have some theoretical question marks - due to not achieving a full understanding).
(1) Although the theory is based on memory, it also is based on spatially-selective cells. Not all cells in the hippocampus fulfill the criteria of place/HD/border/grid cells, and place a role in memory. E.g., Tonegawa, Buszaki labs' work does not focus on only those cells, and there are certainly a lot of non-pure spatial cells in monkeys (Martinez-Trujillo) and humans (iEEG). Does the author mainly focus on saying that "spatial cells" are memory, but do not account for non-spatial memory cells? This seems to be an incomplete account of memory - which is fine, but the way the model is set up suggests that *all* memory is, place (what/where), and non-spatial attributes ("grid") - but cells that don't fulfil these criteria in MTL (Diehl et al., 2017, Neuron; non-grid cells; Schaeffer et al., 2022, ICML; Luo et al., 2024, bioRxiv) certainly contribute to memory, and even navigation. This is also related to the question of whether these cell definitions matter at all (Luo et al., 2024).
The authors note "However, this memory conjunction view of the MTL must be reconciled with the rodent electrophysiology finding that most cells in MTL appear to have receptive fields related to some aspect of spatial navigation (Boccara et al., 2010; Grieves & Jeffery, 2017). The paucity of non-spatial cells in MTL could be explained if grid cells have been mischaracterized as spatial." Is the author mainly talking about rodent work?
(2) Related to the last point, how about non-grid multi-field mEC cells? In theory, these also should be the same; but the author only presents perfect-look grid cells. In empirical work, clearly, this is not the case, and many mEC cells are multi-field non-grid cells (Diehl et al., 2017). Does the model find these cells? Do they play a different role?
As noted by the author "Because the non-spatial attributes are constant throughout the two-dimensional surface, this results in an array of discrete memory locations that are approximately hexagonal (as explained in the Model Methods, an "online" memory consolidation process employing pattern separation rapidly turns an approximately hexagonal array into one that is precisely hexagonal). "
If they are indeed all precisely hexagonal, does that mean the model doesn't have non-grid spatial cells?
(3) Theoretical reasons for why the model is put together this way, and why grid cells must be coding a non-spatial attribute: Is this account more data-driven (fits the data so formulated this way), or is it theoretical - there is a reason why place, border, grid cells are formulated to be like this. For example, is it an efficient way to code these variables? It can be both, like how the BVC model makes theoretical sense that you can use boundaries to determine a specific location (and so place cell), but also works (creates realistic place cells).
But in this case, the purpose of grid cell coding a non-spatial attribute, and having some kind of system where it doesn't fire at all locations seems a little arbitrary. If it's not encoding a spatial attribute, it doesn't have to have a spatial field. For example, it could fire in the whole arena - which some cells do (and don't pass the criteria of spatial cells as they are not spatially "selective" to another location, related to above).
(4) Why are grid cells given such a large role for encoding non-spatial attributes? If anything, shouldn't it be lateral EC or perirhinal cortex? Of course, they both could, but there is less reason to think this, at least for rodent mEC.
(5) Clarification: why do place cells and grid cells differ in terms of stability in the model? Place cells are not stable initially but grid cells come out immediately. They seem directly connected so a bit unclear why; especially if place cell feedback leads to grid cell fields. There is an explanation in the text - based on grid cells coding the on-average memories, but these should be based on place cell inputs as well. So how is it that place fields are unstable then grid fields do not move at all? I wonder if a set of images or videos (gifs) showing the differences in spatial learning would be nice and clarify this point.
(6) Other predictions. Clearly, the model makes many interesting (and quite specific!) predictions. But does it make some known simple predictions?<br /> • More place cells at rewarded (or more visited) locations. Some empirical researchers seem to think this is not as obvious as it seems (e.g., Duvellle et al., 2019; JoN; Nyberg et al., 2021, Neuron Review).<br /> • Grid cell field moves toward reward (Butler et al., 2019; Boccera et al., 2019).<br /> • Grid cells deform in trapezoid (Krupic et al., 2015) and change in environments like mazes (Derikman et al., 2014).
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osf.io osf.io
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Reviewer #1 (Public Review):
Summary:
This paper presents two experiments, both of which use a target detection paradigm to investigate the speed of statistical learning. The first experiment is a replication of Batterink, 2017, in which participants are presented with streams of uniform-length, trisyllabic nonsense words and asked to detect a target syllable. The results replicate previous findings, showing that learning (in the form of response time facilitation to later-occurring syllables within a nonsense word) occurs after a single exposure to a word. In the second experiment, participants are presented with streams of variable-length nonsense words (two trisyllabic words and two disyllabic words) and perform the same task. A similar facilitation effect was observed as in Experiment 1. The authors interpret these findings as evidence that target detection requires mechanisms different from segmentation. They present results of a computational model to simulate results from the target detection task and find that an "anticipation mechanism" can produce facilitation effects, without performing segmentation. The authors conclude that the mechanisms involved in the target detection task are different from those involved in the word segmentation task.
Strengths:
The paper presents multiple experiments that provide internal replication of a key experimental finding, in which response times are facilitated after a single exposure to an embedded pseudoword. Both experimental data and results from a computational model are presented, providing converging approaches for understanding and interpreting the main results. The data are analyzed very thoroughly using mixed effects models with multiple explanatory factors.
Weaknesses:
In my view, the main weaknesses of this study relate to the theoretical interpretation of the results.
(1) The key conclusion from these findings is that the facilitation effect observed in the target detection paradigm is driven by a different mechanism (or mechanisms) than those involved in word segmentation. The argument here I think is somewhat unclear and weak, for several reasons:
First, there appears to be some blurring in what exactly is meant by the term "segmentation" with some confusion between segmentation as a concept and segmentation as a paradigm.<br /> Conceptually, segmentation refers to the segmenting of continuous speech into words. However, this conceptual understanding of segmentation (as a theoretical mechanism) is not necessarily what is directly measured by "traditional" studies of statistical learning, which typically (at least in adults) involve exposure to a continuous speech stream followed by a forced-choice recognition task of words versus recombined foil items (part-words or nonwords). To take the example provided by the authors, a participant presented with the sequence GHIABCDEFABCGHI may endorse ABC as being more familiar than BCG, because ABC is presented more frequently together and the learned association between A and B is stronger than between C and G. However, endorsement of ABC over BCG does not necessarily mean that the participant has "segmented" ABC from the speech stream, just as faster reaction times in responding to syllable C versus A do not necessarily indicate successful segmentation. As the authors argue on page 7, "an encounter to a sequence in which two elements co-occur (say, AB) would theoretically allow the learner to use the predictive relationship during a subsequent encounter (that A predicts B)." By the same logic, encoding the relationship between A and B could also allow for the above-chance endorsement of items that contain AB over items containing a weaker relationship.
Both recognition performance and facilitation through target detection reflect different outcomes of statistical learning. While they may reflect different aspects of the learning process and/or dissociable forms of memory, they may best be viewed as measures of statistical learning, rather than mechanisms in and of themselves.
(2) The key manipulation between experiments 1 and 2 is the length of the words in the syllable sequences, with words either constant in length (experiment 1) or mixed in length (experiment 2). The authors show that similar facilitation levels are observed across this manipulation in the current experiments. By contrast, they argue that previous findings have found that performance is impaired for mixed-length conditions compared to fixed-length conditions. Thus, a central aspect of the theoretical interpretation of the results rests on prior evidence suggesting that statistical learning is impaired in mixed-length conditions. However, it is not clear how strong this prior evidence is. There is only one published paper cited by the authors - the paper by Hoch and colleagues - that supports this conclusion in adults (other mentioned studies are all in infants, which use very different measures of learning). Other papers not cited by the authors do suggest that statistical learning can occur to stimuli of mixed lengths (Thiessen et al., 2005, using infant-directed speech; Frank et al., 2010 in adults). I think this theoretical argument would be much stronger if the dissociation between recognition and facilitation through RTs as a function of word length variability was demonstrated within the same experiment and ideally within the same group of participants.
(3) The authors argue for an "anticipation" mechanism in explaining the facilitation effect observed in the experiments. The term anticipation would generally be understood to imply some kind of active prediction process, related to generating the representation of an upcoming stimulus prior to its occurrence. However, the computational model proposed by the authors (page 24) does not encode anything related to anticipation per se. While it demonstrates facilitation based on prior occurrences of a stimulus, that facilitation does not necessarily depend on active anticipation of the stimulus. It is not clear that it is necessary to invoke the concept of anticipation to explain the results, or indeed that there is any evidence in the current study for anticipation, as opposed to just general facilitation due to associative learning.
In addition, related to the model, given that only bigrams are stored in the model, could the authors clarify how the model is able to account for the additional facilitation at the 3rd position of a trigram compared to the 2nd position?
(4) In the discussion of transitional probabilities (page 31), the authors suggest that "a single exposure does provide information about the transitions within the single exposure, and the probability of B given A can indeed be calculated from a single occurrence of AB." Although this may be technically true in that a calculation for a single exposure is possible from this formula, it is not consistent with the conceptual framework for calculating transitional probabilities, as first introduced by Saffran and colleagues. For example, Saffran et al. (1996, Science) describe that "over a corpus of speech there are measurable statistical regularities that distinguish recurring sound sequences that comprise words from the more accidental sound sequences that occur across word boundaries. Within a language, the transitional probability from one sound to the next will generally be highest when the two sounds follow one another within a word, whereas transitional probabilities spanning a word boundary will be relatively low." This makes it clear that the computation of transitional probabilities (i.e., Y | X) is conceptualized to reflect the frequency of XY / frequency of X, over a given language inventory, not just a single pair. Phrased another way, a single exposure to pair AB would not provide a reliable estimate of the raw frequencies with which A and AB occur across a given sample of language.
(5) In experiment 2, the authors argue that there is robust facilitation for trisyllabic and disyllabic words alike. I am not sure about the strength of the evidence for this claim, as it appears that there are some conflicting results relevant to this conclusion. Notably, in the regression model for disyllabic words, the omnibus interaction between word presentation and syllable position did not reach significance (p= 0.089). At face value, this result indicates that there was no significant facilitation for disyllabic words. The additional pairwise comparisons are thus not justified given the lack of omnibus interaction. The finding that there is no significant interaction between word presentation, word position, and word length is taken to support the idea that there is no difference between the two types of words, but could also be due to a lack of power, especially given the p-value (p = 0.010).
(6) The results plotted in Figure 2 seem to suggest that RTs to the first syllable of a trisyllabic item slow down with additional word presentations, while RTs to the final position speed up. If anything, in this figure, the magnitude of the effect seems to be greater for 1st syllable positions (e.g., the RT difference between presentation 1 and 4 for syllable position 1 seems to be numerically larger than for syllable position 3, Figure 2D). Thus, it was quite surprising to see in the results (p. 16) that RTs for syllable position 1 were not significantly different for presentation 1 vs. the later presentations (but that they were significant for positions 2 and 3 given the same comparison). Is this possibly a power issue? Would there be a significant slowdown to 1st syllables if results from both the exact replication and conceptual replication conditions were combined in the same analysis?
(7) It is difficult to evaluate the description of the PARSER simulation on page 36. Perhaps this simulation should be introduced earlier in the methods and results rather than in the discussion only.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors introduce two preparations for observing large-scale cortical activity in mice during behavior. Alongside, they present intriguing preliminary findings utilizing these methods. This paper is poised to be an invaluable resource for researchers engaged in extensive cortical recording in behaving mice.
Strengths:
Comprehensive methodological detailing:<br /> The paper excels in providing an exceptionally detailed description of the methods used. This meticulous documentation includes a step-by-step workflow, complemented by thorough workflow, protocols and list of materials in the supplementary materials.
Minimal of movement artifacts:<br /> A notable strength of this study is the remarkably low movement artifacts, with specific strategies outlined to attain this outcome.
Insightful preliminary data and analysis:<br /> The preliminary data unveiled in the study reveal interesting heterogeneity in the relationships between neural activity and detailed behavioral features, particularly notable in the lateral cortex. This aspect of the findings is intriguing and suggests avenues for further exploration.
Weaknesses:
Clarification about the extent of the method in title:<br /> The title of the paper, using the term "pan-cortical", may inadvertently suggest that both the top and lateral view preparations are utilized in the same set of mice, while the authors employ either the dorsal view (which offers limited access to the lateral ventral regions) or the lateral view (which restricts access to the opposite side of the cortex).
Despite the authors not identifying qualitative effects, tilting the mouse's head could potentially influence behavioral outcomes in certain paradigms.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript examines the contribution of the dorsal and intermediate hippocampus to goal-directed navigation in a wide virtual environment where visual cues are provided by the scenery on the periphery of a wide arena. Among a choice of 2 reward zones located near the arena periphery, rats learn to navigate from the center of the arena to the reward zone associated with the highest reward. Navigation performance is largely assessed from the rats' body orientation when they leave the arena center and when they reach the periphery, as well as the angular mismatch between the reward zone and the site rats reach the periphery. Muscimol inactivation of the dorsal and intermediate hippocampus alters rat navigation to the reward zone, but the effect was more pronounced for the inactivation of the intermediate hippocampus, with some rat trajectories ending in the zone associated with the lowest reward. Based on these results, the authors suggest that the intermediate hippocampus is critical, especially for navigating to the highest reward zone.
Strengths:
_ The authors developed an effective approach to study goal-directed navigation in a virtual environment where visual cues are provided by the peripheral scenery.
_ In general, the text is clearly written and the figures are well-designed and relatively straightforward to interpret, even without reading the legends.
_ An intriguing result, which would deserve to be better investigated and/or discussed, was that rats tended to rotate always in the counterclockwise direction. Could this be because of a hardware bias making it easier to turn left, some aspect of the peripheral landscape, or a natural preference of rats to turn left that is observable (or reported) in a real environment?
_ Another interesting observation, which would also deserve to be addressed in the discussion, is the fact that dHP/iHP inactivations produced to some extent consistent shifts in departing and peripheral crossing directions. This is visible from the distributions in Figures 6 and 7, which still show a peak under muscimol inactivation, but this peak is shifted to earlier angles than the correct ones. Such change is not straightforward to interpret, unlike the shortening of the mean vector length.
Maybe rats under muscimol could navigate simply by using the association of reward zone with some visual cues in the peripheral scene, in brain areas other than the hippocampus, and therefore stopped their rotation as soon as they saw the cues, a bit before the correct angle. While with their hippocampus is intact, rats could estimate precisely the spatial relationship between the reward zone and visual cues.
Weaknesses:
_ I am not sure that the differential role of dHP and iHP for navigation to high/low reward locations is supported by the data. The current results could be compatible with iHP inactivation producing a stronger impairment on spatial orientation than dHP inactivation, generating more erratic trajectories that crossed by chance the second reward zone.
To make the point that iHP inactivation affects the disambiguation of high and low reward locations, the authors should show that the fraction of trajectories aiming at the low reward zone is higher than expected by chance. Somehow we would expect to see a significant peak pointing toward the low reward zone in the distribution of Figures 6-7.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This work describes a simple mechanical model of worm locomotion, using a series of rigid segments connected by damped torsional springs and immersed in a viscous fluid. It uses this model to simulate forward crawling movement, as well as omega turns.
Strengths:
The primary strength is in applying a biomechanical model to omega-turn behaviors. The biomechanics of nematode turning behaviors are relatively less well described and understood than forward crawling, and the increase in power during omega turns is one of the more novel results. The model itself may be a useful implementation to other researchers, particularly owing to its simplicity.
Weaknesses:
The strength of the model presented in this work relative to prior approaches is not well supported, and in general the paper would be improved with a better description of the broader context of existing modeling literature related to undulatory locomotion. This paper claims to improve on previous approaches to taking body shapes as inputs. However, the sole nematode model cited aims to do something different, and arguably more significant, which is to use experimentally derived parameters to model both the neural circuits that induce locomotion as well as the biomechanics and to subsequently compare the model to experimental data. Other modeling approaches do take experimental body kinematics as inputs and use them to produce force fields, however, they are not cited or discussed. Finally, the overall novelty of the approach is questionable. A functionally similar approach was developed in 2012 to describe worm locomotion in lattices (Majmudar, 2012, Roy. Soc. Int.), which is not discussed and would provide an interesting comparison and needed context.
In some sense, because the model takes kinematics as an input and uses previously established techniques to model mechanics, it is unsurprising that it can reproduce experimentally observed kinematics, however, the forces calculated and the variation of parameters could be of interest, but other methods derived from kinematics could provide similar results. It is unclear what the predictive power of the model is.
Relatedly, a justification of why the drag coefficients had to be changed by a factor of 100 should be explored. Plate conditions are difficult to replicate and the rheology of plates likely depends on several factors, but is for example, changes in hydration level likely to produce a 100-fold change in drag? or something more interesting/subtle within the model producing the discrepancy?
Finally, the language used to distinguish different modeling approaches was often unclear. For example, it was unclear in what sense the model presented in Boyle, 2012 was a "kinetic model" and in many situations, it appeared that the term kinematic might have been more appropriate. Other phrases like "frictional forces caused by the tension of its muscles" were unclear at first glance, and might benefit from revision and more canonical usage of terms.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
Laham et al. investigate how the projection from adult born granule cells into CA2 affects the retrieval of social memories at various developmental points. They use chemogenetic manipulations and electrophysiological recordings to test how this projection affects hippocampal network properties during behavior. The study is of relevant interest for the neuroscience community and the results are important for our understanding of how social memories of different nature (remote or immediate) are encoded and supported by the hippocampal circuitry. The behavioral experiments after abGC projections to CA2 are compelling as they show clearly distinct behavioral readout. While the electrophysiological experiments are difficult to interpret without more single cell responses quantifications, they clearly show that more than one region in the hippocampus is involved in the formation of social memories.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this study, Diana et al. present a Monte Carlo-based method to perform spike inference from calcium imaging data. A particular strength of their approach is that they can estimate not only averages but also uncertainties of the modeled process. The authors then focus on the quantification of spike time uncertainties in simulated data and in data recorded with a high sampling rate in cerebellar slices with GCaMP8f.
Strengths:
- The authors provide a solid groundwork for sequential Monte Carlo-based spike inference, which extends previous work of Pnevmatikakis et al., Greenberg et al., and others.
- The integration of two states (silence vs. burst firing) seems to improve the performance of the model.
- The acquisition of a GCaMP8f dataset in the cerebellum is useful and helps make the point that high spike time inference precision is possible under certain conditions.
Weaknesses:
- The algorithm is designed to predict single spike times. Currently, it is not benchmarked against other algorithms in terms of single spike precision and spike time errors. A benchmarking with the most recent other SMC model and another good model focused on single spike outputs (e.g., MLSpike) would be useful to have.
- Some of the analyses and benchmarks seem too cursory, and the reporting simply consists of a visual impression of results instead of proper analysis and quantification. For example, the authors write "The spike patterns obtained using our method are very similar across trials, showing that PGBAR can reliably detect single-trial action potential-evoked GCaMP8f fluorescence transients." This is a highly qualitative statement, just based on the (subjective) visual impression of a plot. Similarly, the authors write "we could reliably identify the two spikes in each trial", but this claim is not supported by quantification or a figure, as far as I can see. The authors write "but the trade-off between temporal accuracy, SNR and sampling frequency must be considered", but they don't discuss these trade-offs systematically.
- It has been shown several times from experimental data that spike inference with single spike resolution does not work well (Huang et al. eLife, 2021; Rupprecht et al., Nature Neuroscience, 2021) in general. This limitation should be discussed with respect to the applicability of the proposed algorithm for standard population calcium imaging data.
- Several analyses are based on artificial, simulated data with simplifying assumptions. Ever since Theis et al., Neuron, 2016, it has been known that artificially generated ground truth data should not be used as the primary means to evaluate spike inference algorithms. It would have been informative if the authors had used either the CASCADE dataset or their cerebellum dataset for more detailed analyses, in particular of single spike time precision.
- In its current state, the sum of the current weaknesses makes the suggested method, while interesting for experts, rather unattractive for experimentalists who want to perform spike inference on their recorded calcium imaging data.
Other comments:
- One of the key features of the SMC model is the assumption of two states (bursting vs. non-bursting). However, while it seems clear that this approach is helpful, it is not clear where this idea comes from, from an observation of the data or another concept.
- Another SMC algorithm (Greenberg et al., 2018) stated that the fitted parameters showed some degeneracy, resulting in ambiguous fitting parameters. It would be good to know if this problem was avoided by the authors.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Short Assessment
In this work the authors propose a new regulatory role for one the most abundant circRNAs, circHIPK3. They demonstrate that circHIPK3 interacts with an RNA binding protein (IGF2BP2), sequestering it away from its target mRNAs. This interaction is shown to regulates the expression of hundreds of genes that share a specific sequence motif (11-mer motif) in their untranslated regions (3'-UTR), identical to one present in circHIPK3 where IGF2BP2 binds. The study further focuses on the specific case of STAT3 gene, whose mRNA product is found to be downregulated upon circHIPK3 depletion. This suggests that circHIPK3 sequesters IGF2BP2, preventing it from binding to and destabilizing STAT3 mRNA. The study presents evidence supporting this mechanism and discusses its potential role in tumor cell progression. These findings contribute to the growing complexity of understanding cancer regulation and highlight the intricate interplay between circRNAs and protein-coding genes in tumorigenesis.
Strengths:<br /> The authors show mechanistic insight into a proposed novel "sponging" function of circHIPK3 which is not mediated by sequestering miRNAs but rather a specific RNA binding protein (IGF2BP2). They address the stoichiometry of the molecules involved in the interaction, which is a critical aspect that is frequently overlooked in this type of studies. They provide both genome-wide analysis and a specific case (STAT3) which is relevant for cancer progression. Overall, the authors have significantly improved their manuscript in their revised version.
Weaknesses:<br /> While the authors have performed northern blots to measure circRNA levels, an estimation of the circRNA overexpression efficiency, namely the circular-to-linear expression ratio, would be desired. The seemingly contradictory effects of circHIPK3 and STAT3 depletion in cancer progression, are now addressed by the authors in their revised manuscript, incorporating potential reasons that might explain such complexity.
Major points about revised manuscript
(1) In Supplementary Figure S5H, the membrane may have been trimmed too closely to the circRNA band, potentially resulting in the absence of the linear RNA band. Could the authors provide a full image of the membrane that includes the loading points? Having access to the complete image would allow for a more comprehensive evaluation of the results, including the presence or absence of expected linear and circular RNA bands.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Authors were attempting to determine the extent that CIH altered swallowing motor function; specifically, the timing and probability of the activation of the larygneal and submental motor pools. The paper describes a variety of different motor patterns elicited by optogenetic activation of individual neuronal phenotypes within PiCo in a group of mice exposed to CIH. They show that there are a variety of motor patterns that emerge in CIH mice; this is apparently different than the more consistent motor patterns elicited by PiCo activation in normoxic mice (previously published)
Strengths:
The preparation is technically challenging and gives valuable information related to the role of PiCo in the pattern of motor activation involved in swallowing and its timing with phrenic activity. Genetic manipulations allow for the independent activation of the individual neuronal phenotypes of PiCo (glutamatergic, cholinergic) which is a strength.
Weaknesses:
(1) Comparisons made between experimental data acquired currently with those previously published are extremely problematic, with the potential confounding influence of changing environments, genetics and litter effects. For example, were the current mice tested at the same time as those exposed to normoxia? Are they littermates (or at least from the same colony) as those previously examined? If they were tested at the same time and age, then the authors should explicitly state this in the methods. The authors have provided no statistical analyses to determine whether there is an effect of CIH on the motor patterns. In short, how can they be sure that the phenomena they observe with respect to motor patterns is due to CIH?
(2) The data are descriptive in nature, reporting only differences (diversity) of motor patterns in this cohort of animals exposed to CIH. There is limited mechanistic insight into how PiCo manipulation alters the pattern and probability of motor activation. Can they utilize Fos or marker of activation within the nTS or other regions to provide initial insight? Or in another nucleus that contributes as part of the circuit.
(3) The differences between the genotypes (ChaTcre; Vglut2Cre; ChatCre:Vglut2FlpO) with regard to the probability of generating a swallow are not sufficiently discussed, in my view. If, as the authors state, it is "reasonable to suggest that CIH differentially affects" these populations, then what are some viable reasons? What are the known differences in these populations of neurons that could lead to variable responses? Do they project to different places?
(4) The Results section is difficult to follow and interpret. It would be beneficial to have a couple of sentences after each sub-section stating what the data actually mean. As of now it reads like a statistical report of the data with little "basic" interpretation of the data.
(5) I have a hard time understanding the functional significance of calculating and plotting the degree of correlation between shifting/delaying the following inspiratory burst and triggering a swallow.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this work, the authors examine the activity and function of D1 and D2 MSNs in dorsomedial striatum (DMS) during an interval timing task. In this task, animals must first nose poke into a cued port on the left or right; if not rewarded after 6 seconds, they must switch to the other port. Critically, this task thus requires animals to estimate if at least 6 seconds have passed after the first nose poke - this is the key aspect of the task focused on here. After verifying that animals reliably estimate the passage of 6 seconds by leaving on average after 9 seconds, the authors examine striatal activity during this interval. They report that D1-MSNs tend to decrease activity, while D2-MSNs increase activity, throughout this interval. They suggest that this activity follows a drift-diffusion model, in which activity increases (or decreases) to a threshold after which a decision (to leave) is made. The authors next report that optogenetically inhibiting D1 or D2 MSNs, or pharmacologically blocking D1 and D2 receptors, increased the average wait time of the animals to 10 seconds on average. This suggests that both D1 and D2 neurons contribute to the estimate of time, with a decrease in their activity corresponding to a decrease in the rate of 'drift' in their drift-diffusion model. Lastly, the authors examine MSN activity while pharmacologically inhibiting D1 or D2 receptors. The authors observe most recorded MSNs neurons decrease their activity over the interval, with the rate decreasing with D1/D2 receptor inhibition.
Major strengths:
The study employs a wide range of techniques - including animal behavioral training, electrophysiology, optogenetic manipulation, pharmacological manipulations, and computational modeling. The behavioral task used by the authors is quite interesting and a nice way to probe interval timing in rodents. The question posed by the authors - how striatal activity contributes to interval timing - is of importance to the field and has been the focus of many studies and labs; thus, this paper can meaningfully contribute to that conversation. The data within the paper is presented very clearly, and the authors have done a nice job presenting the data in a transparent manner (e.g., showing individual cells and animals). Overall, the manuscript is relatively easy to read and clear, with sufficient detail given in most places regarding the experimental paradigm or analyses used.
Major weaknesses:
I perceive two major weaknesses. The first is the impact or contextualization of their results in terms of the results of the field more broadly. More specifically, it was not clear to me how the authors are interpreting the striatal activity in the context of what others have observed during interval timing tasks. In other words - what was the hypothesis going into this experiment? Does observing increasing/decreasing activity in D2 versus D1 support one model of interval timing over another, or does it further support a more specific idea of how DMS contributes to interval timing? Or was the main question that we didn't know if D2 or D1 neurons had differential activity during interval timing?
In the second, I felt that some of the conclusions suggested by the authors don't seem entirely supported by the data they present, or the data presented suggests a slightly more complicated story. Below I provide additional detail on some of these instances.
Regarding the results presented in Figures 2 and 3:
I am not sure the PC analysis adds much to the interpretation, and potentially unnecessarily complicates things. In particular, running PCA on a matrix of noisy data that is smoothed with a Gaussian will often return PCs similar to what is observed by the authors, with the first PC being a line up/down, the 2nd PC being a parabola that is up/down, etc. Thus, I'm not sure that there is much to be interpreted by the specific shape of the PCs here. I think an alternative analysis that might be both easier and more informative is to compute the slope of the activity of each neuron across the 6 seconds. This would allow the authors to quantify how many neurons increase or decrease their activity much like what is shown in Figure 2.
Relatedly, it seems that the data shown in Figure 2D *doesn't* support the authors' main claim regarding D2/D1 MSNs increasing/decreasing their activity, as the trial-by-trial slope is near 0 for both cell types.
Regarding the results in Figure 4:
The authors suggest that their data is consistent with a drift-diffusion model. However, it is unclear how well the output from the model fits the activity from neurons the authors recorded. Relatedly, it is unclear how the parameters were chosen for the D1/D2 versions of this model. I think that an alternate approach that would answer these questions is to fit the model to each cell, and then examine the best-fit parameters, as well as the ability of the model to predict activity on trials held out from the fitting process. This would provide a more rigorous method to identify the best parameters and would directly quantify how well the model captures the data.
Relatedly, looking at the raw data in Figure 2, it seems that many neurons either fire at the beginning or end of the interval, with more neurons firing at the end, and more firing at the beginning, for D2/D1 neurons respectively. Thus, it's not clear to me whether the drift-diffusion model is a good model of activity. Or, perhaps the model is supposed to be related to the aggregate activity of all D1/D2 neurons? (If so, this should be made more explicit. The comment about fitting the model directly to the data also still stands).
Further, it's unclear to me how, or why, the authors changed the specific parameters they used to model the optogenetic manipulation. Were these parameters chosen because they fit the manipulation data? This I don't think is in itself an issue, but perhaps should be clearly stated, because otherwise it sounds a bit odd given the parameter changes are so specific. It is also not clear to me why the noise in the diffusion process would be expected to change with increased inhibition.
Regarding the results in Figure 6:
My comments regarding the interpretation of PCs in Figure 2 apply here as well. In addition, I am not sure that examining PC2 adds much here, given that the authors didn't examine such nonlinear changes earlier in the paper.
A larger concern though that seems potentially at odds with the authors' interpretation is that there seems to be very little change in the firing pattern after D1 or D2 blockade. I see that in Figure 6F the authors suggest that many cells slope down (and thus, presumably, they are recoding more D1 cells), and that this change in slope is decreased, but this effect is not apparent in Figure 6C, and Figure 6B shows an example of a cell that seems to fire in the opposite direction (increase activity). I think it would help to show some (more) individual examples that demonstrate the summary effect shown by the authors, and perhaps the authors can comment on the robustness (or the variability) of this result.
Also, it seems that if the authors want to claim that this manipulation lowers the drift rate. I think to make this claim, they could fit the DDM model and examine whether D is significantly lower.
Regarding the results in Figure 7:
I am overall a bit confused about what the authors are trying to claim here. In Figure 7, they present data suggesting that D1 or D2 blockade disrupts their ability to decode time in the interval of interest (0-6 seconds). However, in the final paragraph of the results, the authors seem to say that by using another technique, they didn't see any significant change in decoding accuracy after D1 or D2 blockade. What do the authors make of this?
Impact:
The task and data presented by the authors are very intriguing, and there are many groups interested in how striatal activity contributes to the neural perception of time. The authors perform a wide variety of experiments and analysis to examine how DMS activity influences time perception during an interval-timing task, allowing for insight into this process. However, the significance of the key finding - that D2/D1 activity increases/ decreases with time - remains somewhat ambiguous to me. This arises from a lack of clarity regarding the initial hypothesis and the implications of this finding for advancing our understanding of striatal functions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This is well-performed research with solid results and thorough control. The authors did a good job of finding the relationship between the 5-HT1A receptor and megakaryocytopoiesis, which demonstrated the potential of vilazodone in the management of thrombocytopenia. It emphasizes the regulatory mechanism of 5-HT1A receptor signaling on hematopoietic lineages, which could further advance the field of thrombocytopenia for therapeutic purposes.
Strengths:
This is a comprehensive and detailed research using multiple methods and model systems to determine the pharmacological effects and molecular mechanisms of vilazodone. The authors conducted in vitro experiments using HEL and Meg-01 cells and in vivo experiments using Zebrafish and Kunming-irradiated mice. The experiments and bioinformatics analysis have been performed with a high degree of technical proficiency. The authors demonstrated how vilazodone binds to 5-HTR1A and regulates the SRC/MAPK pathway, which is inhibited by particular 5-HTR1A inhibitors. The authors determined this to be the mechanistic underpinning for the effects of vilazodone in promoting megakaryocyte differentiation and thrombopoiesis.
Weaknesses:
(1) Which database are the drug test sets and training sets for the creation of drug screening models obtained from? What criteria are used to grade the results?<br /> (2) What is the base of each group in Figure 3b for the survival screening of zebrafish? The positivity rate of GFP-labeled platelets is too low, as indicated by the quantity of eGFP+ cells. What gating technique was used in Figure 3e?<br /> (3) In Figure 4C, the MPV values of each group of mice did not show significant downregulation or upregulation. Please explain the possible reasons.<br /> (4) The PPI diagram and the KEGG diagram in Figure 6 both provide a possible mechanism pathway for the anti-thrombocytopenia effect of vilazodone. How can the author analyze the differences in their results?<br /> (5) 5-HTR1A protein expression is measured only in the Meg-01 cells assay. Similar quantitation through western blot is not shown in other cell models.
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Reviewer #1 (Public Review):
Summary:
In this manuscript the authors have applied an asymmetric split mNeonGreen2 (mNG2) system to human iPSCs. By integrating a constitutively expressed long fragment of mNG2 at the AAVS1 locus, this allows other proteins to be tagged through the use of available ssODN donors. This removes the need to generate long AAV donors for tagging, thus greatly facilitating high-throughput tagging efforts. The authors then demonstrate the feasibility of the method by successfully tagging 9 markers expressed in iPSC at various, and one expressed upon endoderm differentiation. Several additional differentiation markers were also successfully tagged but not subsequently tested for expression/visibility. As one might expect for high-throughput tagging, a few proteins, while successfully tagged at the genomic level, failed to be visible. Finally, to demonstrate the utility of the tagged cells, the authors isolated clones with genes relevant to cytokinesis tagged, and together with an AI to enhance signal to noise ratios, monitored their localization over cell division.
Strengths
Reviewer Comment: Characterization of the mNG2 tagged parental iPSC line was well and carefully done including validation of a single integration, the presence of markers for continued pluripotency, selected off-target analysis and G-banding-based structural rearrangement detection.<br /> The ability to tag proteins with simple ssODNs in iPSC capable of multi-lineage differentiation will undoubtedly be useful for localization tracking and reporter line generation.<br /> Validation of clone genotypes was carefully performed and highlights the continued need for caution with regards to editing outcomes.
Weaknesses
Reviewer Comment: IF and flow cytometry figures lack quantification and information on replication. How consistent is the brightness and localization of the markers? How representative are the specific images? Stability is mentioned in the text but data on the stability of expression/brightness is not shown.
Author Response: To address this comment, we have quantified the mean fluorescence intensity of the tagged cell populations in Fig. S3B-T. This data correlates well with the expected expression levels of each gene relative to the others (Fig. S3A), apart from CDH1 and RACGAP1, which are described in the discussion.
Reviewer Reply: Great, thanks.
Reviewer Comment: The localization of markers, while consistent with expectations, is not validated by a second technique such as antibody staining, and in many cases not even with Hoechst to show nuclear vs cytoplasmic.
Author Response: We find that the localization of each protein is distinct and consistent with previous studies. To address this comment, we have added an overlay of the green fluorescence images with brightfield images to better show the location of the tagged protein relative to the nuclei and cytoplasm. We have also added references to other studies that showed the same localization patterns for these proteins in iPSCs and other relevant cell lines.
Reviewer Reply: There was no question that the localization fit with expectations, however, this still doesn't show that in the same cell the tag is in the same spot. It would have been fairly simple to do for at least a handful of markers, image, fix and stain to demonstrate unequivocally the tag and protein are co-localized. Of course, this isn't damning by any means, it just would have been nice.
Reviewer Comment: For the multi-germ layer differentiation validation, NCAM is also expressed by ectoderm, so isn't a good solo marker for mesoderm as it was used. Indeed, the kit used for the differentiation suggests Brachyury combined with either NCAM or CXCR4, not NCAM alone.
Author Response: Since Brachyury is the most common mesodermal marker, we first tested differentiation using anti-Brachyury antibodies, but they did not work well for flow cytometry. We then switched to anti-NCAM antibodies. Since we used a kit for directed differentiation of iPSCs into the mesodermal lineage, NCAM staining should still report for successful differentiation. In the context of mixed differentiation experiments (embryoid body formation or teratoma assay), NCAM would not differentiate between ectoderm and mesoderm. The parental cells (201B7) have also been edited at the AAVS1 locus in multiple other studies, with no effect on their differentiation potential.
Reviewer Reply: This is placing a lot of trust in the kit that it only makes what it says it makes. It could have been measured by options other than flow such as qPCR, Western blot, or imaging, but fine.
Reviewer Comment: Only a single female parental line has been generated and characterized. It would have been useful to have several lines and both male and female to allow sex differences to be explored.
Author Response: We agree that it would be interesting (and important) to study differences in protein localization between female and male cell types, and from different individuals with different genetic backgrounds. We see our tool as opening a door for cell biology to move away from randomly collected, transformed, differentiated cell types to more directed comparative studies of distinct normal cell types. Since few studies of cell biological processes have been done in normal cells, a first step is to understand how processes compare in an isogenic background, then future studies can reveal how they compare with other individuals and sexes. We hope that either our group or others will continue to build similar lines so that these studies can be done.
Reviewer Reply: Fair enough.
Reviewer Comment: The AI-based signal to noise enhancement needs more details and testing. Such models can introduce strong assumptions and thus artefacts into the resolved data. Was the model trained on all markers or were multiple models trained on a single marker each? For example, if trained to enhance a single marker (or co-localized group of markers), it could introduce artefacts where it forces signal localization to those areas even for others. What happens if you feed in images with scrambled pixel locations, does it still say the structures are where the training data says they should be? What about markers with different localization from the training set. If you feed those in, does it force them to the location expected by the training data or does it retain their differential true localization and simply enhance the signal?
Author Response: The image restoration neural network was used as in Weigert et al., 2018. The model was trained independently for each marker. Each trained model was used only on the corresponding marker and with the same imaging conditions as the training images. From visual inspection, the fluorescent signal in the restored images was consistent with the signal in the raw images, both for interphase and mitotic cells. We found very few artefacts of the restoration (small bright or dark areas) that were discarded. We did not try to restore scrambled images or images of mismatched markers.
Reviewer Reply: I understand. What I'm saying is that for the restoration technique to be useful you need to know that it won't introduce artefacts if you have an unexpected localization. Think of it this way, if you already know the localization, then there's no point measuring it. If you don't, or there's a possibility that it is somewhere unexpected, then you need to know with confidence that your algorithm will be able to accurately detect that unexpected localization. As such, it would be extremely important to validate that your restoration algorithm will not bias the results to the expected localization if the true localization is unexpected/not seen in the training dataset. It would have been extremely trivial to run this analysis and I do not feel this comment has been in any way adequately addressed.
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Reviewer #1 (Public Review):
Summary:
This study offers a comprehensive examination of the early postnatal development of the patch and matrix compartments within the striatum. These are segregated circuits within the striatum circuits with distinct embryonic origins and functional roles in mature brain physiology. Despite the recognized significance of these circuits, a comprehensive understanding of their postnatal maturation remains elusive.
Strengths:
The authors undertake a thorough investigation, characterizing the intrinsic properties of direct pathway spiny projection neurons (dSPNs) and indirect pathway spiny projection neurons (iSPNs) across both matrix and striosome compartments throughout development. The authors identify the regulatory role of M1 receptors in modulating spontaneous activity in SPNs, and demonstrate the impact of chemogenetic inhibition of MOR-positive neurons during development on GABAergic synapses in substantia nigra pars compacta (SNc) dopamine (DA) neurons. These findings significantly advance our understanding of striatal development and function.
Weaknesses:
Certain methodological considerations warrant attention. Notably, the reliance on TdTomato expression for the identification of striosomes raises concerns, particularly regarding the substantial difference in slice thickness between the immunohistochemistry (IHC) images (50um) shown in Figure 2 and those utilized for whole-cell recordings (300um).
Enhanced clarification regarding the identification of cell patches is possible in the electrophysiology rig conditions. Using a widefield microscope rather than a confocal would strengthen the reliability of this methodology.
In the Ca2+ imaging experiments of Figure 2, striosomes were defined as the regions of brighter GCaMP fluorescence. This presents a potential limitation because it presupposes higher activity levels within patch cells, which is what the experiment is designed to test. Based on this criteria, neurons of this region will necessarily have more activity than in others.
There is also no information on how Ca2+ imaging traces were analyzed. In the examples provided, putative matrix neurons seem to exhibit different Ca2+ dynamics compared to striosome neurons. The plateau responses might reflect even higher activity than the transient signals observed in striosome neurons. It'll be important to know how the data was quantified. For example, calculations of F0 based on rolling functions tend to underestimate dF/F in traces like this. Calculations of the area under the curve can also provide valuable information in these cases.
There is no description of the 8mM KCl treatment in the methods. Was this only used for the Ca2+ imaging experiments? The percentage of active cells in Figures 2C-D is similar to or lower than that described in Figure 2B, which is confusing. Were recordings always performed in 8mM KCl?
Lastly, while the findings of Figure 6 suggest a deficit in striosomal inputs to SNc DA neurons, they do not conclusively demonstrate this point (DA neurons receive many sources of inhibition, and local interneurons in SNc are highly plastic). Given the availability of Opmr1-Cre mice and the utilization of multiple viruses in Figure 6 experiments, the inclusion of experiments employing ChR2 to directly assess striatal/striosome inputs would substantially strengthen this claim. This is the main claim stated in the manuscript title, so it is important to provide evidence of specific striatonigral deficits.
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Reviewer #1 (Public Review):
Summary:
The authors seek to elucidate the structural role of N-glycosylation at the N343 position of the SARS-CoV-2 Spike protein's Receptor Binding Domain (RBD) and its evolution across different variants of concern (VoCs). Specifically, they aim to understand the impact of this glycosylation on the RBD's stability and function, which could have implications for the virus's infectivity and, eventually, the effectiveness of vaccines.
Strengths:
The major strength of the study stems from the molecular-level picture emerging from the use of over 45 μs of cumulative molecular dynamics (MD) simulations, including both conventional and enhanced sampling schemes, which provide detailed insights into the structural role of N343 glycosylation. The combination of these simulations with experimental assays, such as electron-spray ionization mass spectrometry (ESI-MS) for affinity measurements, bolsters the reliability of the findings. At the same time, one potential weakness is the inherent limitation of the current computational models to fully capture the complexities of in vivo systems. While the authors acknowledge the difficulty in completely gauging the N343 glycosylation's impact on RBD folding due to the dynamic nature of glycan structures, their computational/experimental approach lends support to their claims.
Weaknesses:
One potential weakness is the inherent limitation of computational models to fully capture the complexities of in vivo systems. While the authors acknowledge the difficulty in completely gauging the N343 glycosylation's impact on RBD folding due to the dynamic nature of glycan structures, their multi-faceted approach lends solid support to their claims.
Other Comments:
The study shows that N343 glycosylation plays a structural role in stabilizing the RBD across various SARS-CoV-2 strains. The removal of this glycan led to conformational changes that could affect the virus's infectivity. The results correlate with a reported reduction in viral infectivity upon deletion of glycosylation sites, supporting the authors' conclusion that N343 glycosylation is functionally essential for viral infection.
By providing molecular insights into the spike protein's architectural changes, the work could influence the design of more effective vaccines and therapeutic agents. The data and methods used could serve as a valuable resource for researchers looking into viral evolution, protein-glycan interactions, and the development of glycan-based interventions.
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Reviewer #1 (Public Review):
Summary:
This is an interesting and potentially important paper, which however has some deficiencies.
Strengths:
A significant amount of potentially useful data.
Weaknesses:
One issue is a confusion of thermal stability with solubility. While thermal stability of a protein is a thermodynamic parameter that can be described by the Gibbs-Helmholtz equation, which relates the free energy difference between the folded and unfolded states as a function of temperature, as well as the entropy of unfolding. What is actually measured in PISA is a change in protein solubility, which is an empirical parameter affected by a great many variables, including the presence and concentration of other ambient proteins and other molecules. One might possibly argue that in TPP, where one measures the melting temperature change ∆Tm, thermal stability plays a decisive or at least an important role, but no such assertion can be made in PISA analysis that measures the solubility shift.
Another important issue is that the authors claim to have discovered for the first time a number of effects well described in prior literature, sometimes a decade ago. For instance, they marvel at the differences between the solubility changes observed in lysate versus intact cells, while this difference has been investigated in a number of prior studies. No reference to these studies is given during the relevant discussion.
The validity of statistical analysis raises concern. In fact, no calculation of statistical power is provided. As only two replicates were used in most cases, the statistical power must have been pretty limited. Also, there seems to be an absence of the multiple-hypothesis correction.
Also, the authors forgot that whatever results PISA produces, even at high statistical significance, represent just a prediction that needs to be validated by orthogonal means. In the absolute majority of cases such validation is missing.
Finally, to be a community-useful resource the paper needs to provide the dataset with a user interface so that the users can data-mine on their own.
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Joint Public Review:
Summary:
Brauns et al. work to decipher the respective contribution of active versus passive contributions to cell shape changes during germ band elongation. Using a novel quantification tool of local tension, their results suggest that epithelial convergent extension results from internal forces.
Strengths:
The approach developed here, tension isogonal decomposition, is original and the authors made the demonstration that we can extract comprehensive data on tissue mechanics from this type of analysis.
They present an elegant diagram that quantifies how active and passive forces interact to drive cell intercalations.
The model qualitatively recapitulates the features of passive and active intercalation for a T1 event.
Regions of high isogonal strains are consistent with the proximity of known active regions.
They define a parameter (the LTC parameter) which encompasses the geometry of the tension triangles and allows the authors to define a criterium for T1s to occur.
The data are clearly presented, going from cellular scale to tissue scale, and integrating modeling approach to complement the thoughtful description of tension patterns.
Weaknesses:
The modeling is interesting, with the integration of tension through tension triangulation around vertices and thus integrating force inference directly in the vertex model. However, the authors are not using it to test their hypothesis and support their analysis at the tissue level. Thus, although interesting, the analysis at the tissue level stays mainly descriptive.
Major points:
(1) The authors mention that from their analysis, they can predict what is the tension threshold required for intercalations in different conditions and predict that in Snail and Twist mutants the T1 tension threshold would be around √2. Since movies of these mutants are most probably available, it would be nice to confirm these predictions.
(2) While the formalism is very elegant and convincing, and also convincingly allows making sense of the data presented in the paper, it is not all that clear whether the claims are compatible with previous experimental observations. In particular, it has been reported in different papers (including Collinet et al NCB 2015, Clement et al Curr Biol 2017) that affecting the initial Myosin polarity or the rate of T1s does not affect tissue-scale convergent extension. Analysis/discussion of the Tor phenotype (no extension with myosin anisotropy) and the Eve/Runt phenotype (extension without Myosin anisotropy), which seem in contradiction with an extension mostly driven by myosin anisotropy.
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Reviewer #1 (Public Review):
The manuscript by Long et al. focused on SUL1, a gene encoding a sulfate transporter with signaling roles in yeast. The authors claim that the deletion of SUL1, rather than SUL2 (encoding a similar transporter), extended yeast replicative lifespan independent of sulfate transport. They also show that SUL1 loss-of-function mutants display decreased PKA activity, indicated by stress-protective carbohydrate accumulation, relevant transcription factor relocalization (measured during aging in single cells), and changes in gene expression. Finally, they show that loss of SUL1 increases autophagy, which is consistent with the longer lifespan of these cells. Overall, this is an interesting paper, but additional work should strengthen several conclusions, especially for the role of sulfate transport. Specific points include the following:
- What prompted the authors to measure the RLS of sul1 mutants? Prior systematic surveys of RLS in the same strain background (which included the same sul1 deletion strain they used) did not report lifespan extension in sul1 cells (PMID: 26456335).
- Cells carrying a mutant Sul1 (E427Q), which was reported to be disrupted in sulfate transport, did not have a longer lifespan (Figure 1), leading them to conclude that "lifespan extension by SUL1 deletion is not caused by decreased sulfate uptake". They would need to measure sulfate uptake in the mutants they test to draw that conclusion firmly.
- Related to my previous point, another simple experiment would be to repeat the assays in Figure 1 with exogenous sulfur added to see if the lifespan extension is suppressed.
- There needs to be more information in the text or the methods about how they did the enrichment analysis in Figure 2B. P-values are typically insufficient, and adjusted FDR values are reported from standard gene ontology platforms (e.g., PANTHER).
- It is somewhat puzzling that relocalization of Msn2 was not seen in very old cells (past the 17th generation), but it was evident in younger cells. The authors could consider another possibility, that it was early and midlife experiences that made those cells live longer. Past that window, loss of Sul1 may have no impact on longevity. A conditional shutoff system to regulate SUL1 expression would be needed to test the above, albeit this is probably beyond the scope of this report.
- The connections between glucose restriction, autophagy, and sul1 (Figure 4) could be further tested by measuring the RLS of sul1 cells in glucose-restricted cells. If RLS is further extended by glucose restriction, then whatever effects they see should be independent of glucose restriction.
- They made and tested the double (sul1, msn2) mutants, but they should also test the sul1, msn4 combination since Msn4 functions similarly to Msn2.
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Reviewer #1 (Public Review):
This is an interesting study investigating the mechanisms underlying membrane targeting of the NLRP3 inflammasome and reporting a key role for the palmitoylation-depalmitoylation cycle of cys130 in NRLP3. The authors identify ZDHHC3 and APT2 as the specific ZDHHC and APT/ABHD enzymes that are responsible for the s-acylation and de-acylation of NLRP3, respectively. They show that the levels of ZDHHC3 and APT2, both localized at the Golgi, control the level of palmitoylation of NLRP3. The S-acylation-mediated membrane targeting of NLRP3 cooperates with polybasic domain (PBD)-mediated PI4P-binding to target NLRP3 to the TGN under steady-state conditions and to the disassembled TGN induced by the NLRP3 activator nigericin.
However, the study has several weaknesses in its current form as outlined below.
(1) The novelty of the findings concerning cys130 palmitoylation in NLRP3 is unfortunately compromised by recent reports on the acylation of different cysteines in NLRP3 (PMID: 38092000), including palmitoylation of the very same cys130 in NLRP3 (Yu et al https://doi.org/10.1101/2023.11.07.566005), which was shown to be relevant for NLRP3 activation in cell and animal models. What remains novel and intriguing is the finding that NLRP3 activators induce an imbalance in the acylation-deacylation cycle by segregating NLRP3 in late Golgi/endosomes from de-acylating enzymes confined in the Golgi. The interesting hypothesis put forward by the authors is that the increased palmitoylation of cys130 would finally contribute to the activation of NLRP3. However, the authors should clarify the trafficking pathway of acylated-NLRP3. This pathway should, in principle, coincide with that of TGN46 which constitutively recycles from the TGN to the plasma membrane and is trapped in endosomes upon treatment with nigericin.
(2) To affect the S-acylation, the authors used 16 hrs treatment with 2-bromopalmitate (2-BP). In Figure 1f, it is quite clear that NLRP3 in 2-BP treated cells completely redistributed in spots dispersed throughout the cells upon nigericin treatment. What is the Golgi like in those cells? In other words, does 2-BP alter/affect Golgi morphology? What about PI4P levels after 2-BP treatment? These are important missing pieces of data since both the localization of many proteins and the activity of one key PI4K in the Golgi (i.e. PI4KIIalpha) are regulated by palmitoylation.
(3) The authors argue that the spots observed with NLRP-GFP result from non-specific effects mediated by the addition of the GFP tag to the NLRP3 protein. However, puncta are visible upon nigericin treatment, as a hallmark of endosomal activation. How do the authors reconcile these data? Along the same lines, the NLRP3-C130S mutant behaves similarly to wt NLRP3 upon 2-BP treatment (Figure 1h). Are those NLRP3-C130S puncta positive for endosomal markers? Are they still positive for TGN46? Are they positive for PI4P?
(4) The authors expressed the minimal NLRP3 region to identify the domain required for NLRP3 Golgi localization. These experiments were performed in control cells. It might be informative to perform the same experiments upon nigericin treatment to investigate the ability of NLRP3 to recognize activating signals. It has been reported that PI4P increases on Golgi and endosomes upon NG treatment. Hence, all the differences between the domains may be lost or preserved. In parallel, also the timing of such recruitment upon nigericin treatment (early or late event) may be informative for the dynamics of the process and of the contribution of the single protein domains.
(5) As noted above for the chemical inhibitors (1) the authors should check the impact of altering the balance between acyl transferase and de-acylases on the Golgi organization and PI4P levels. What is the effect of overexpressing PATs on Golgi functions?
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Reviewer #1 (Public Review):
Summary<br /> In this work, Mouelhi et al investigated how the nucleus responds to long term confinement. They find that short-term confinement does not affect nuclear volume, whereas long-term confinement leads to a decrease in volume. The authors propose this decrease occurs after mitosis and relies on cPLA2 and myosin contractility.
Strengths
The ability to accurately control cell confinement allows authors to determine its effects on cellular function with high resolution. This provides a good addition to the existing collection of tools used for cellular micromanipulation. The results provided are relevant and timely and could help understand how cancer cells adapt to conditions of confinement.
Weaknesses
I have a few concerns which I believe should be addressed:
(1) It is unclear whether the authors took into consideration the contribution of nuclear blebs for nuclear volume measurements. This would be particularly relevant in situations of very strong confinement. Blebs were previously shown to affect volume (Mistriotis et al., JCB 2019). One could argue that the decreased nuclear volume was due to the increased blebbing observed in very strong confinements.
(2) From their experimental setup, it is unclear whether the reduced nuclear volume observed after confined cell division arises from a geometrical constraint or is due to an intrinsic nuclear feature. One could argue that cells exiting mitosis under confinement have clustered chromosomes and, therefore, will have decreased volume. This would imply that the nucleus is not "reset" but rather that a geometrical constraint is forcing nuclei to be smaller. One way to test this would be to follow individual cells under confinement, let them enter mitosis, and then release the confinement. If, under these conditions, the daughter nuclei are smaller, then it supports their model. If daughter nuclei recover to their initial value, then it´s simply due to a geometrical constraint that forces the clustering of chromosomes and the reassembly of the NE in a confined space.
(3) The authors claim that the nucleus adapts to confinement based on evidence that the nucleus no longer shrinks in the second division following the first division. I would argue no further decrease is possible because the DNA is already compacted in the smallest possible volume. If indeed nuclei are in a new homeostatic state as the authors claim, then one would expect nuclei to remain smaller even after confinement is removed. This analysis is missing.
(4) Also, if the authors want to claim that this is a mechanism used for cancer cells to adapt to confined situations as the title says, they need to show that normal, near-diploid cells do not behave in the same way. This analysis is missing.
(5) Authors state that "Loss of nuclear blebs is clearly linked to mitosis, suggesting that nuclear volume and nuclear envelope tension are tightly coupled, and supports the hypothesis that mitosis is a key regulator of nuclear envelope tension". I have a few issues with the way this sentence is written. Firstly, one could say that all nuclear structures (and not only blebs) are lost during mitosis because the nucleus disassembles. Hence, the new homeostatic state could be determined by envelope reassembly after mitosis and not mitosis itself. Secondly, I don´t understand why the loss of nuclear blebs suggests that volume and tension are tightly coupled. Thirdly, how can mitosis be a key regulator of nuclear envelope tension when the nucleus is disassembled during the process? These require clarification.
(6) The authors claim that, unlike previous studies (Lomakin et al), this work shows a "gradual nuclear adaptation". From their results, this is difficult to conclude simply because they do not analyse cPLA2 levels. This is solely based on indirect evidence obtained from cPLA2 inhibition. A gradual adaptation would mean that based on the level of confinement we would expect to have increasingly higher levels of cPLA2 (and therefore nuclear tension).
(7) The authors should refrain from saying that the mechanism behind DNA repair is coupled to the nuclear adaptation they show. There are several points regarding this statement. Firstly, increased DNA damage could be due to nuclear ruptures imposed by confinement at 2h. In fact, the authors show leakage of NLS from the nucleus after confinement (Figure S3A). Secondly, the decrease in DNA damage at 24h could be because these nuclei did not rupture. How can they ensure that cells with low DNA damage at 24h had increased DNA damage at 2h? Finally, one needs to confirm if the nuclei they are analysing at 24h did undergo a round of cell division previously. From the evidence provided, the authors cannot conclude that DNA damage regulation is occurring in confined cells. Moreover, cell cycle arrest is a known effect of DNA damage. Cells with high damage at 2h most likely are arrested or will present with increased mitotic errors (which the authors exclude from their analyses).
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Reviewer #1 (Public Review):
Summary:
The authors aim to address a critical challenge in the field of bioinformatics: the accurate and efficient identification of protein binding sites from sequences. Their work seeks to overcome the limitations of current methods, which largely depend on multiple sequence alignments or experimental protein structures, by introducing GPSite, a multi-task network designed to predict binding residues of various molecules on proteins using ESMFold.
Strengths:
(1) Benchmarking. The authors provide a comprehensive benchmark against multiple methods, showcasing the performances of a large number of methods in various scenarios.
(2) Accessibility and Ease of Use. GPSite is highlighted as a freely accessible tool with user-friendly features on their website, enhancing its potential for widespread adoption in the research community.
Weaknesses:
(1) Lack of significant insights. The paper reproduces results and analyses already presented in previous literature, without providing significant novel analysis or interpretation. However, they show a novel method with an original approach.
The work is useful for the field, especially in disease mechanism elucidation and novel drug design. The availability of genome-scale binding residue annotations GPSite offers is a significant advancement.
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Reviewer #1 (Public Review):
Summary:
This manuscript examined the impact of prenatal alcohol exposure on genome-wide DNA methylation in the brain and liver, comparing ethanol-exposed mice to unexposed controls. They also investigated whether a high-methyl diet (HMD) could prevent the DNA methylation alterations caused by alcohol. Using bisulfite sequencing (n=4 per group), they identified 78 alcohol-associated differentially methylated regions (DMRs) in the brain and 759 DMRs in the liver, of which 85% and 84% were mitigated by the HMD group, respectively. The authors further validated 7 DMRs in humans using previously published data from a Canadian cohort of children with FASD.
Overall, the findings from this study provide new insight into the impact of prenatal alcohol exposure, while also showing evidence for methyl-rich diets as an intervention to prevent the effects of alcohol on the epigenome. Some methodological concerns and confounders limit the robustness of these results, and should be addressed in future studies to further strengthen the conclusions of this study and its applicability to broader settings.
Strengths:
- The use of whole genome bisulfite sequencing allowed for the interrogation of the entire DNA methylome and DMR analysis, rather than a subset of CpGs.<br /> - The combination of data from animal models and humans allowed the authors to make stronger inferences regarding their findings<br /> - The authors investigated a potential mechanism (high methyl diet) to buffer against the effects of prenatal alcohol exposure, which increases the relevance and applicability of this research.
Weaknesses:
- The sample size was small for the epigenetic analyses, which limits the robustness of the findings.<br /> - The authors could not account for potential confounders in their analyses, including birthweight, alcohol levels, and sex. This is a particular problem for the high-methyl diet analyses, in which the alcohol-exposed mice consumed less alcohol than their non-diet counterparts.
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Joint Public Review:
In this manuscript, Xue and colleagues investigate the fundamental aspects of cellular fate decisions and differentiation, focusing on the dynamic behaviour of gene regulatory networks. It explores the debate between static (noise-driven) and dynamic (signal-driven) perspectives within Waddington's epigenetic landscape, highlighting the essential role of gene regulatory networks in this process. The authors propose an integrated analysis of fate-decision modes and gene regulatory networks, using the Cross-Inhibition with Self-activation (CIS) network as a model. Through mathematical modelling, they differentiate two logic modes and their effect on cell fate decisions: requires both the presence of an activator and absence of a repressor (AA configuration) with one where transcription occurs as long the repressor is not the only species on the promoter (OO configuration).
The authors establish a relationship between noise profiles, logic-motifs, and fate-decision modes, showing that defining any two of these properties allows the inference of the third. They also identify, under the signal-driven mode, two fundamental patterns of cell fate decisions: either prioritising progression or accuracy in the differentiation process. The authors apply this analysis to available high-throughput datasets of cell fate decisions in hematopoiesis and embryogenesis, proposing the underlying driving force in each case and utilising the observed noise patterns to nominate key regulators.
The paper significantly advances our understanding of gene regulatory networks through a well-described computational study, where the authors rigorously evaluate assumptions in modelling. Particularly commendable is their introduction of the concept of combinatorial logic, exemplified by the double 'and' and double 'or' (AA/OO) logic motifs, which they successfully map to previously described cell fate decision processes. This theoretical and computational exploration sheds light on the dynamic landscape of epigenetic cell fate decisions, emphasising the role of combinatorial logic in coordinating noise and signal-driven processes. The thorough comparison of two model configurations underscores the importance of integration logic, contributing to a clearer understanding of gene regulatory network dynamics. Importantly, the results of the simulations are presented clearly, enhancing accessibility and intuitive understanding. The paper's strength also lies in its predictive power, as the authors use simulations to make insightful predictions about the regulatory organisation of stem cell differentiation systems. While the exploration is restricted to specific scenarios, these limitations serve to highlight areas for future research rather than detract from the paper's strengths.
While the paper presents an intriguing framework for understanding gene regulatory networks and cell fate decisions, there are some weaknesses that warrant attention. Firstly, the framework would benefit from validation with more experimental data and application to diverse systems beyond those explored in the study, such as de-differentiation in adult tissues and regeneration processes. Additionally, while the authors successfully make predictions about the regulatory organisation of stem cell differentiation systems, there is a lack of discussion regarding how perturbations in the regulatory network could affect cell fate decisions. Furthermore, the paper could be strengthened by addressing the effects of mutations and other perturbations that may significantly influence cell fate decision-making processes, thus enhancing the robustness of the findings. Finally, there are instances where the clarity of the writing could be improved to enhance understanding and accessibility for readers.
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Reviewer #1 (Public Review):
Induction of beta cell regeneration is a promising approach for the treatment of diabetes. In this study, Massoz et.al., identified calcineurin (CaN) as a new potential modulator of beta cell regeneration by using zebrafish as model. They also showed that calcineurin (CaN) works together with Notch signaling to promote the beta cell regeneration. Overall, the paper is well organized, and technically sound. However, some evidences seem weak to get the conclusion.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The research study under review investigated the relationship between the gut and identified potential biomarkers derived from the nasopharyngeal and gut microbiota-based that could aid in predicting COVID-19 severity. The study reported significant changes in the richness and Shannon diversity index in nasopharyngeal microbiome associated with severe symptoms. The study showed a high abundance of Bacillota and Pesudomonadota in patients exhibiting severe symptomatology. Positive correlations were also found between Corynebacterium, Acinetobacter, Staphylococcus, and Veillonella, with the severity of SARS-CoV-2 infection.
Strengths:
The study successfully identified differences in the microbiome diversity that could indicate or predict disease severity. Furthermore, the authors demonstrated a link between individual nasopharyngeal organisms and the severity of SARS-CoV-2 infection. The density of the nasopharyngeal organism was shown to be a potential predictor of the severity of COVID-19.
Weaknesses:
The authors claimed an association between nasopharyngeal organisms and severity of SARS-CoV-2 infection but omitted essential data on the statistical significance of these associations between groups. The authors frequently referred to a p-value < 0.05 without presenting the actual p-values and percentages to show the significance of their results. The discussion is hard to understand (lacked clarity), as it contained an extensive literature review without discussing the study findings. A more focused discussion and results section on the main findings could have improved the overall readability of the paper. The role of potential confounders, such as HIV infection, and ethnicity which impacts the nasopharyngeal microbiome composition, was not included in the paper. Addressing the potential confounders would contribute to a more comprehensive understanding of the study's implications, specifically the role of the nasopharyngeal microbiome as a predictor of COVID-19 severity.
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www.biorxiv.org www.biorxiv.org
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Joint Public Review:
This study investigates the role of Ikaros, a zinc finger family transcription factor related to Helios and Eos, in T-regulatory (Treg) cell functionality in mice. Through genome-wide association studies and chromatin accessibility studies, the authors find that Ikaros shares similar binding sites to Foxp3. Ikaros cooperates with Foxp3 to establish a major portion of the Treg epigenome and transcriptome. Ikaros-deficient Treg exhibits Th1-like gene expression with abnormal expression of IL-2, IFNg, TNFa, and factors involved in Wnt and Notch signalling. Further, two models of inflammatory/ autoimmune diseases - Inflammatory Bowel Disease (IBD) and organ transplantation - are employed to examine the functional role of Ikaros in Treg-mediated immune suppression. The authors provide a detailed analysis of the epigenome and transcriptome of Ikaros-deficient Treg cells.
These studies establish Ikaros as a factor required in Treg for tolerance and the control of inflammatory immune responses. The data are of high quality. Overall, the study is well organized, and reports new data consolidating mechanistic aspects of Foxp3 mediated gene expression program in Treg cells.
Strengths:
The authors have performed biochemical studies focusing on mechanistic aspects of molecular functions of the Foxp3-mediated gene expression program and complemented these with functional experiments using two models of autoimmune diseases, thereby strengthening the study. The studies are comprehensive at both the cellular and molecular levels. The manuscript is well organized and presents a plethora of data regarding the transcriptomic landscape of these cells.
Weakness:
The findings of markedly increased percentages of activated conventional T cells (CD44hi), major increases in TFH cells, and elevated serum Ig levels indicate disrupted immune homeostasis even in the absence of overt autoimmune manifestations seen in histopathology. Thus, some of the observed genetic changes observed by the authors are likely Treg cell extrinsic. Further, clear conclusions from the genome-wide studies are lacking.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The manuscript describes the development of a mouse model that co-expresses a fluorescent protein ZsGreen) marker in gene fusion with the FSHR gene.
The authors are correct in that there is a lack of reliable antibodies against many of the GPCR family members. The approach is novel and interesting, with the potential to help understand the expression pattern of gonadotropin receptors. There has been a very long debate about the expression of gonadotropin receptors in other tissues other than gonads. While their expression of the FSHR in some of those tissues has been detected by a variety of methods, their physiological, or pathophysiological, function(s) remain elusive.
The authors in this manuscript assume that the expression of ZsGren and the FSHR are equal. While this is correct genetically (transcription->translation) it does not go hand in hand with other posttranslational processes.
(1) One of the shocking observations in this manuscript is the expression of FSHR in Leydig cells. Other observations are in the osteoblasts and endothelial cells as well as epithelial cells in different organs. The expression of ZsGreen in these tissues seems high and one shall start questioning if there are other mechanisms at play here.
First, the turnover of fluorescent proteins is long, longer than 48h, which means that they accumulate at a different speed than the endogenous FSHR This means that ZsGreen will accumulate in time while the FSHR receptor might be degraded almost immediately. This correlated with mRNA expression (by the authors) but does not with the results of other studies in single-cell sequencing (see below).
The expression of ZsGreen in Leydig cells seems much higher than in Sertoli cells, this is "disturbing" to put it mildly. This is visible in both the ZsGreen expression and the FISH assay (Figure 2 B-D).
(2) The expression in WAT and BAT is also questionable as the expression of ZsGreen is high everywhere. That makes it difficult to believe that the images are truly informative. For example, the stainings of aorta show the ZsGreen expression where elastin and collagen fibres are - these are not "cells" and therefore are not expressing ZsGreen.
(3) FISH expression (for FSHR) in WT mice is missing.
Also, the tissue sections were stained with the IgG only (neg control) but in practice both the KI and the WT tissues should be stained with the primary and secondary antibodies. The only control that I could think of to truly get a sense of this would be a tagged receptor (N-terminal) that could then be analysed by immunohistochemistry.
(4) The authors also claim:<br /> To functionally prove the presence of FSHR in osteoblasts/osteocytes, we also deleted FSHR in osteocytes using an inducible model. The conditional knockout of FSHR triggered a much more profound increase in bone mass and decrease in fat mass than blockade by FSHR antibodies (unpublished data).
This would be a good control for all their images. I think it is necessary to make the large claim of extragonadal expression, as well as intragonadal such as Leydig cells.
(5) Claiming that the under-developed Leydig cells in FSHR KO animals are due to a direct effect of the FSHR, and not via a cross-talk between Sertoli and Leydig cells, is too much of a claim. It might be speculated to some degree but as written at the moment it suggests this is "proven".
(6) We also do not know if this FSHR expressed is a spliced form that would also result in the expression of ZsGreen but in a non-functional FSHR, or whether the FSHR is immediately degraded after expression. The insertion of the ZsGreen might have disturbed the epigenetics, transcription, or biosynthesis of the mRNA regulation.
(7) The authors should go through single-cell data of WT mice to show the existence of the FSHR transcript(s).<br /> For example here:<br /> https://www.nature.com/articles/sdata2018192
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
As a pathogen, S. aureus has evolved strategies to evade the host's immune system. It effectively remains 'under the radar' in the host until it reaches high population densities, at which point it triggers virulence mechanisms, enabling it to spread within the host. The agr quorum sensing system is central to this process, as it coordinates the pathogen's virulence in response to its cell density.
In this study, Podkowik and colleagues suggest that cells activating agr signaling also benefit from protection against H2O2 stress, whereas inactivation of agr increases cell death. The underlying cause of this lack of protection is tied to an ATP deficit in the agr mutant, leading to increased glucose consumption and NADH production, ultimately resulting in a redox imbalance. In response to this imbalance, the agr mutant increases respiration, resulting in the endogenous production of ROS which synergizes with H2O2 to mediate killing of the agr mutant. Suppressing respiration in the agr mutant restored protection against H2O2 stress.
Additionally, the authors establish that agr-dependent protection against oxidative stress is also linked to RNAIII activation, and the subsequent block of Rot translation. However, the specific protective genes regulated by Rot remain unidentified. Thus, according to the evidence provided, agr triggers intrinsic mechanisms that not only decrease harmful ROS production within the cell but also alleviate its detrimental effects.
Interestingly, these protective mechanisms are long-lived, and guard the cells against external oxidative stressors such as H2O2, even after the agr system has been 'turned off' in the population.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Del Rosario et al characterized the extent and cell types of sibling chimerism in marmosets. To do so, they took advantage of the thousands of SNPs that are transcribed in single-nucleus RNA-seq (snRNA-seq) data to identify the sibling genotype of origin for all sequenced cells across 4 tissues (blood, liver, kidney, and brain) from many marmosets. They found that chimerism is prevalent and widespread across tissues in marmosets, which has previously been shown. However, their snRNA-seq approach allowed them to identify precisely which cells were of sibling origin, and which were not. In doing so they definitively show that sibling chimerism across tissues is limited to cells of myeloid and lymphoid lineages. The authors then focus on a large sample of microglia sequenced across many brain regions to quantify: (1) variation in chimerism across brain regions in the same individual, and (2) the relative importance of genetic vs. environmental context on microglia function/identity.
(1) Much like across different tissues in the same individual, they found that the proportion of chimeric microglia varies across brain regions collected from the same individuals (as well as differing from the proportion of sibling cells found in the blood of the same animals), suggesting that cells from different genetic backgrounds may differ in their recruitment and/or proliferation across regions and local tissue contexts, or that this may be linked to stochastic bottleneck effects during brain development.
(2) Their (admittedly smaller sample size) analyses of host-sibling gene expression showed that the local environment dominates genotype.
All told, this thoughtful and thorough manuscript accomplishes two important goals. First, it all but closes a previously open question on the extent and cell origins of sibling chimerism. Second, it sets the stage for using this unique model system to examine, in a natural context, how genetic variation in microglia may impact brain development, function, and disease.
The conclusions of this paper are well supported by the data, and the authors exert appropriate care when extrapolating their results that come from smaller samples. However, there are a few concerns that should be addressed.
The "modest correlation" mentioned in lines 170-172 does not take into account the uncertainty in estimates of each chimeric cell proportion (although the plot shows those estimates nicely). This is particularly important for the macrophages, which are far less abundant. Perhaps a more appropriate way to model this would be in a binomial framework (with a random effect for individuals of origin). Here, you could model the sibling identity of each macrophage as a function of the proportion of sibling-origin microglia and then directly estimate the percent variance explained.
A similar (albeit more complicated because of the number of regions being compared) approach could be applied to more rigorously quantify the variation in chimerism across brain regions (L198-215; Figure 4). This would also help to answer the question of whether specific brain regions are more "amenable" to microglia chimerism than others.
While the sample size is small, it would be exciting to see if any microglia eQTL are driven by sibling chimerism across the marmosets.
L290-292: The authors should propose ways in which they could test the two different explanations proposed in this paragraph. For instance, a simulation-based modeling approach could potentially differentiate more stochastic bottleneck effects from recruitment-like effects.
While intriguing, the gene expression comparison (Figure 5) is extremely underpowered. It would be helpful to clarify this and note the statistical thresholds used for identifying DEGs (the black points in the figure).
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:<br /> The study presented by Atsumi et al. is about using smartphone-driven, community-sourced data to enhance biodiversity monitoring. The idea is to leverage the widespread use of smartphones to gather data from the community quickly, contributing to a more comprehensive understanding of biodiversity. The authors discuss the importance of ecosystem services linked to biodiversity and the threats posed by human activities. It emphasizes the need for comprehensive biodiversity data to implement the Kunming-Montreal Global Biodiversity Framework. The 'Biome' mobile app, launched in Japan, uses species identification algorithms and gamification to gather over 6 million observations since 2019. While community-sourced data may have biases, incorporating it into Species Distribution Models (SDMs) improves accuracy, especially for endangered species. The app covers urban-natural gradients uniformly, enhancing traditional survey data biased towards natural areas. Combining these sources provides valuable insights into species distributions for conservation, protected area designation, and ecosystem service assessment.
Strengths:
The use of a smartphone app ('Biome') for community-driven species occurrence data collection represents an innovative and inclusive approach to biodiversity monitoring, leveraging the widespread use of smartphones. The app has successfully accumulated a large volume of species occurrence data since its launch in 2019, showcasing its effectiveness in rapidly gathering information from diverse locations. Despite challenges with certain taxa, the study highlights high species identification accuracy, especially for birds, reptiles, mammals, and amphibians, making the 'Biome' app a reliable tool for species observation. The integration of community-sourced data into Species Distribution Models (SDMs) improves the accuracy of predicting species distributions. This has implications for conservation planning, including the designation of protected areas and assessment of ecosystem services. The rapid accumulation of data and advancements in machine learning methods open up opportunities for conducting time-series analyses, contributing to the understanding of ecosystem stability and interaction strength over time. The study emphasizes the collaborative nature of the platform, fostering collaboration among diverse stakeholders, including local communities, private companies, and government agencies. This inclusive approach is essential for effective biodiversity assessment and decision-making. The platform's engagement with various stakeholders, including local communities, supports biodiversity assessment, management planning, and informed decision-making. Additionally, the app's role in fostering nature-positive awareness in society is highlighted as a significant contribution to creating a sustainable society.
Weaknesses:
While the studies make significant contributions to biodiversity monitoring, they also have some weaknesses. Firstly, relying on smartphone-driven, community-sourced data may introduce spatial and taxonomic biases. The 'Biome' app, for example, showed lower accuracy for certain taxa like seed plants, molluscs, and fishes, potentially impacting the reliability of the gathered data. Furthermore, the effectiveness of Species Distribution Models (SDMs) relies on the assumption that biases in community-sourced data can be adequately accounted for. The unique distribution patterns of the 'Biome' data, covering urban-natural gradients uniformly, might not fully represent the diversity of certain ecosystems, potentially leading to inaccuracies in the models. Moreover, the divergence in data distribution patterns along environmental gradients between 'Biome' data and traditional survey data raises concerns. The app data shows a more uniform distribution across natural-urban gradients, while traditional data is biased towards natural areas. This discrepancy may impact the representation of certain ecosystems and influence the accuracy of Species Distribution Models (SDMs). While the integration of 'Biome' data into SDMs improves accuracy, the study notes that controlling the sampling efforts is crucial. Spatially-biased sampling efforts in community-sourced data need careful consideration, and efforts to control biases are essential for reliable predictions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript presents a short report investigating mismatch responses in the auditory cortex, following previous studies focused on the visual cortex. By correlating the mouse locomotion speed with acoustic feedback levels, the authors demonstrate excitatory responses in a subset of neurons to halts in expected acoustic feedback. They show a lack of responses to mismatch in the visual modality. A subset of neurons show enhanced mismatch responses when both auditory and visual modalities are coupled to the animal's locomotion.
While the study is well-designed and addresses a timely question, several concerns exist regarding the quantification of animal behavior, potential alternative explanations for recorded signals, correlation between excitatory responses and animal velocity, discrepancies in reported values, and clarity regarding the identity of certain neurons.
Strengths:
(1) Well-designed study addressing a timely question in the field.
(2) Successful transition from previous work focused on the visual cortex to the auditory cortex, demonstrating generic principles in mismatch responses.
(3) The correlation between mouse locomotion speed and acoustic feedback levels provides evidence for a prediction signal in the auditory cortex.
(4) Coupling of visual and auditory feedback shows putative multimodal integration in the auditory cortex.
Weaknesses:
(1) Lack of quantification of animal behavior upon mismatches, potentially leading to alternative interpretations of recorded signals.
(2) Unclear correlation between excitatory responses and animal velocity during halts, particularly in closed-loop versus playback conditions.
(3) Discrepancies in reported values in a few figure panels raise questions about data consistency and interpretation.
(4) Ambiguity regarding the identity of the [AM+VM] MM neurons.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors were trying to understand the relation between the development of large trunks and longirrostrine mandibles in bunodont proboscideans of Miocene, and how it reflects the variation in diet patterns.
Strengths:
The study is very well supported, written, and illustrated, with plenty Supplementary materials. The authors included all Asian bunodont proboscideans with long mandibles and I suggest that they should use the expression "bunodont proboscideans" instead of gomphotheres.
Weaknesses:
I believe that the only weakness is the lack of discussion comparing their results with the development of gigantism and long limbs in proboscideans from the same epoch.
The authors reviewed the manuscript according to my suggestions and responded well to all my comments.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
This manuscript investigates the regulation of chlorophyll biosynthesis in rice embryos, focusing on the role of OsNF-YB7. The rigorous experimental approach, combining genetic, biochemical, and molecular analyses, provides a robust foundation for these findings. The research achieves its objectives, offering new insights into chlorophyll biosynthesis regulation, with the results convincingly supporting the authors' conclusions.
Strengths:
The major strengths include the detailed experimental design and the findings regarding OsNF-YB7's inhibitory role.
Weaknesses:
However, the manuscript's discussion on the practical implications for agriculture and the evolutionary analysis of regulatory mechanisms could be expanded.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Herrmannova et al explore changes in translation upon individual depletion of three subunits of the eIF3 complex (d, e, and f) in mammalian cells. The authors provide a detailed analysis of regulated transcripts, followed by validation by RT-qPCR and/or Western blot of targets of interest, as well as GO and KKEG pathway analysis. The authors confirm prior observations that eIF3, despite being a general translation initiation factor, functions in mRNA-specific regulation, and that eIF3 is important for translation re-initiation. They show that the global effects of eIF3e and eIF3d depletion on translation and cell growth are concordant. Their results support and extend previous reports suggesting that both factors control the translation of 5'TOP mRNAs. Interestingly, they identify MAPK pathway components as a group of targets coordinately regulated by eIF3 d/e. The authors also discuss discrepancies with other reports analyzing eIF3e function.
Strengths:
Altogether, a solid analysis of eIF3 d/e/h-mediated translation regulation of specific transcripts. The data will be useful for scientists working in the Translation field.
Weaknesses:
The authors could have explored in more detail some of their novel observations, as well as their impact on cell behavior.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors observed a decline in autophagy and proteasome activity in the context of Milton knockdown. Through proteomic analysis, they identified an increase in the protein levels of eIF2β, subsequently pinpointing a novel interaction within eIF subunits where eIF2β contributes to the reduction of eIF2α phosphorylation levels. Furthermore, they demonstrated that overexpression of eIF2β suppresses autophagy and leads to diminished motor function. It was also shown that in a heterozygous mutant background of eIF2β, Milton knockdown could be rescued. This work represents a novel and significant contribution to the field, revealing for the first time that the loss of mitochondria from axons can lead to impaired autophagy function via eIF2β, potentially influencing the acceleration of aging. To further support the authors' claims, several improvements are necessary, particularly in the methods of quantification and the points that should be demonstrated quantitatively. It is crucial to investigate the correlation between aging and the proteins eIF2β and eIF2α.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Here the authors discuss mechanisms of ligand binding and conformational changes in GlnBP (a small E Coli periplasmic binding protein, which binds and carries L-glutamine to the inner membrane ATP-binding cassette (ABC) transporter). The authors have distinguished records in this area and have published seminal works. They include experimentalists and computational scientists. Accordingly, they provide comprehensive, high-quality, experimental and computational work.
They observe that apo- and holo- GlnBP does not generate detectable exchange between open and (semi-) closed conformations on timescales between 100 ns and 10 ms. Especially, the ligand binding and conformational changes in GlnBP that they observe are highly correlated. Their analysis of the results indicates a dominant induced-fit mechanism, where the ligand binds GlnBP prior to conformational rearrangements. They then suggest that an approach resembling the one they undertook can be applied to other protein systems where the coupling mechanism of conformational changes and ligand binding.
They argue that the intuitive model where ligand binding triggers a functionally relevant conformational change was challenged by structural experiments and MD simulations revealing the existence of unliganded closed or semi-closed states and their dynamic exchange with open unbound conformations, discuss alternative mechanisms that were proposed, their merits and difficulties, concluding that the findings were controversial, which, they suggest is due to insufficient availability of experimental evidence to distinguish them. As to further specific conclusions they draw from their results, they determine that a conformational selection mechanism is incompatible with their results, but induced fit is. They thus propose induced fit as the dominant pathway for GlnBP, further supported by the notion that the open conformation is much more likely to bind substrate than the closed one based on steric arguments.
Considering the landscape of substrate-free states, in my view, the closed state is likely to be the most stable and, thus most highly populated. As the authors note and I agree that state can be sterically infeasible for a deep-pocketed substrate. As indeed they also underscore, there is likely to be a range of open states. If the populations of certain states are extremely low, they may not be detected by the experimental (or computational) methods. The free energy landscape of the protein can populate all possible states, with the populations determined by their relative energies. In principle, the protein can visit all states. Whether a particular state is observed depends on the time the protein spends in that state. The frequencies, or propensities, of the visits can determine the protein function. As to a specific order of events, in my view, there isn't any. It is a matter of probabilities which depend on the populations (energies) of the states. The open conformation that is likely to bind is the most favorable, permitting substrate access, followed by minor, induced fit conformational changes. However, a key factor is the ligand concentration. Ligand binding requires overcoming barriers to sustain the equilibrium of the unliganded ensemble, thus time. If the population of the state is low, and ligand concentration is high (often the case in in vitro experiments, and high drug dosage scenarios) binding is likely to take place across a range of available states.
This is however a personal interpretation of the data. The paper here, which clearly embodies massive careful, and high-quality work, is extensive, making use of a range of experimental approaches, including isothermal titration calorimetry, single-molecule Förster resonance energy transfer, and surface-plasmon resonance spectroscopy. The problem the authors undertake is of fundamental importance.
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www.biorxiv.org www.biorxiv.org
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Reviewer #2 (Public Review):
Summary:
In this manuscript Nie et al investigate the effect of PARG KO and PARG inhibition (PARGi) on pADPR, DNA damage, cell viability and synthetic lethal interactions in HEK293A and Hela cells. Surprisingly, the authors report that PARG KO cells are sensitive to PARGi and show higher pADPR levels than PARG KO cells, which is abrogated upon deletion or inhibition of PARP1/PARP2. The authors explain the sensitivity of PARG KO to PARGi through incomplete PARG depletion and demonstrate complete loss of PARG activity when incomplete PARG KO cells are transfected with additional gRNAs in the presence of PARPi. Furthermore, the authors show that the sensitivity of PARG KO cells to PARGi is not caused by NAD depletion but by S-phase accumulation of pADPR on chromatin coming from unligated Okazaki fragments, which are recognized and bound by PARP1. Consistently, PARG KO or PARG inhibition show synthetic lethality with Pol beta, which is required for Okazaki fragment maturation. PARG expression levels in ovarian cancer cell lines correlate negatively with their sensitivity to PARGi.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
The paper measures the prevalence and mortality of stroke and its comorbidities across geographic regions in order to find differences in risks that may lead to more effective guidance for these subpopulations. It also does a genetic analysis to look for variants that may drive these phenotypic variations.
Strengths:
The data provided here will provide a foundation for a lot of future research into the causes of the observed correlations as well as whether the observed differences in comorbidities across regions have clinically relevant effects on risk management.
Weaknesses:
As with any cross-national analysis of rates, the data is vulnerable to differences in classification and reporting across jurisdictions. Furthermore, given the increased death rate from COVID-19 associated with many of these comorbid conditions and the long-term effects of COVID-19 infection on vascular health, it is expected that many of the correlations observed in this dataset will shift along with the shifting health of the underlying populations.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
The manuscript by Duilio M. Potenza et al. explores the role of Arginase II in cardiac aging, majorly using whole-body arg-ii knock-out mice. In this work, the authors have found that Arg-II exerts non-cell-autonomous effects on aging cardiomyocytes, fibroblasts, and endothelial cells mediated by IL-1b from aging macrophages. The authors have used arg II KO mice and an in vitro culture system to study the role of Arg II. The authors have also reported the cell-autonomous effect of Arg-II through mitochondrial ROS in fibroblasts that contribute to cardiac aging. These findings are sufficiently novel in cardiac aging and provide interesting insights. While the phenotypic data seems strong, the mechanistic details are unclear. How Arg II regulates the IL-1b and modulates cardiac aging is still being determined. The authors still need to determine whether Arg II in fibroblasts and endothelial contributes to cardiac fibrosis and cell death. This study also lacks a comprehensive understanding of the pathways modulated by Arg II to regulate cardiac aging.
Strengths:
This study provides interesting information on the role of Arg II in cardiac aging.
The phenotypic data in the arg II KO mice is convincing, and the authors have assessed most of the aging-related changes.
The data is supported by an in vitro cell culture system.
Weaknesses:
The manuscript needs more mechanistic details on how Arg II regulates IL-1b and modulates cardiac aging.
The authors used whole-body KO mice, and the role of macrophages in cardiac aging is not studied in this model. A macrophage-specific arg II Ko would be a better model.
Experiments need to validate the deficiency of Arg II in cardiomyocytes.
The authors have never investigated the possibility of NO involvement in this mice model.
A co-culture system would be appropriate to understand the non-cell-autonomous functions of macrophages.
The Myocardial infarction data shown in the mice model may not be directly linked to cardiac aging.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
Semenova et al. have studied a large cross-sectional cohort of people living with HIV on suppressive ART, N=115, and performed high dimensional flow cytometry to then search for associations between immunological and clinical parameters and intact/total HIV DNA levels.
A number of interesting data science/ML approaches were explored on the data and the project seems a serious undertaking. However, like many other studies that have looked for these kinds of associations, there was not a very strong signal. Of course, the goal of unsupervised learning is to find new hypotheses that aren't obvious to human eyes, but I felt in that context, there were (1) results slightly oversold, (2) some questions about methodology in terms mostly of reservoir levels, and (3) results were not sufficiently translated back into meaning in terms of clinical outcomes.
Strengths:
The study is evidently a large and impressive undertaking and combines many cutting-edge statistical techniques with a comprehensive experimental cohort of people living with HIV, notably inclusive of populations underrepresented in HIV science. A number of intriguing hypotheses are put forward that could be explored further. Sharing the data could create a useful repository for more specific analyses.
Weaknesses:
Despite the detailed experiments and methods, there was not a very strong signal for the variable(s) predicting HIV reservoir size. The Spearman coefficients are ~0.3, (somewhat weak, and acknowledged as such) and predictive models reach 70-80% prediction levels, though sometimes categorical variables are challenging to interpret.
There are some questions about methodology, as well as some conclusions that are not completely supported by results, or at minimum not sufficiently contextualized in terms of clinical significance.
On associations: the false discovery rate correction was set at 5%, but data appear underdetermined with fewer observations than variables (144vars > 115ppts), and it isn't always clear if/when variables are related (e.g inverses of one another, for instance, %CD4 and %CD8).
The modeling of reservoir size was unusual, typically intact and defective HIV DNA are analyzed on a log10 scale (both for decays and predicting rebound). Also sometimes in this analysis levels are normalized (presumably to max/min?, e.g. S5), and given the large within-host variation of level we see in other works, it is not trivial to predict any downstream impact of normalization across population vs within-person.
Also, the qualitative characterization of low/high reservoir is not standard and naturally will split by early/later ART if done as above/below median. Given the continuous nature of these data, it seems throughout that predicting above/below median is a little hard to translate into clinical meaning.
Lastly, the work is comprehensive and appears solid, but the code was not shared to see how calculations were performed.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
The current study aims to quantify associations between the regular use of proton-pump inhibitors (PPI) - defined as using PPI most days of the week during the last 4 weeks at one cross-section in time - with several respiratory outcomes up to several years later in time. There are 6 respiratory outcomes included: risk of influenza, pneumonia, COVID-19, other respiratory tract infections, as well as COVID-19 severity and mortality).
Strengths:
Several sensitivity analyses were performed, including i) estimation of the e-value to assess how strong unmeasured confounders should be to explain observed effects, ii) comparison with another drug with a similar indication to potentially reduce (but not eliminate) confounding by indication.
Weaknesses:
(1) The main exposure of interest seems to be only measured at one time-point in time (at study enrollment) while patients are considered many years at risk afterwards without knowing their exposure status at the time of experiencing the outcome. As indicated by the authors, PPI are sometimes used for only short amounts of time. It seems biologically implausible that an infection was caused by using PPI for a few weeks many years ago.
(2) Previous studies have shown that by focusing on prevalent users of drugs, one often induces several biases such as collider stratification bias, selection bias through depletion of susceptible, etc.
(3) It seems Kaplan Meier curves are not adjusted for confounding through e.g. inverse probability weighting. As such the KM curves are currently not informative (or the authors need to make clearer that curves are actually adjusted for measured confounding).
(4) Throughout the manuscript the authors seem to misuse the term multivariate (using one model with e.g. correlated error terms to assess multiple outcomes at once) when they seem to mean multivariable.
(5) Given multiple outcomes are assessed there is a clear argument for accounting for multiple testing, which following the logic of the authors used in terms of claiming there is no association when results are not significant may change their conclusions. More high-level, the authors should avoid the pitfall of stating there is evidence of absence if there is only an absence of evidence in a better way (no statistically significant association doesn't mean no relationship exists).
(6) While the authors claim that the quantitative bias analysis does show results are robust to unmeasured confounding, I would disagree with this. The e-values are around 2 and it is clearly not implausible that there are one or more unmeasured risk factors that together or alone would have such an effect size. Furthermore, if one would use the same (significance) criteria as used by the authors for determining whether an association exists, the required effect size for an unmeasured confounder to render effects 'statistically non-significant' would be even smaller.
(7) Some patients are excluded due to the absence of follow-up, but it is unclear how that is determined. Is there potentially some selection bias underlying this where those who are less healthy stop participating in the UK biobank?
(8) Given that the exposure is based on self-report how certain can we be that patients e.g. do know that their branded over-the-counter drugs are PPI (e.g. guardium tablets)? Some discussion around this potential issue is lacking.
(9) Details about the deprivation index are needed in the main text as this is a UK-specific variable that will be unfamiliar to most readers.
(10) It is unclear how variables were coded/incorporated from the main text. More details are required, e.g. was age included as a continuous variable and if so was non-linearity considered and how?
(11) The authors state that Schoenfeld residuals were tested, but don't report the test statistics. Could they please provide these, e.g. it would already be informative if they report that all p-values are above a certain value.
(12) The authors would ideally extend their discussion around unmeasured confounding, e.g. using the DAGs provided in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832226/, in particular (but not limited to) around severity and not just presence/absence of comorbidities.
(13) The UK biobank is known to be highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. The potential problems this might create in terms of collider stratification bias - as highlighted here for example: https://www.nature.com/articles/s41467-020-19478-2 - should be discussed in greater detail and also appreciated more when providing conclusions.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The manuscript, "A versatile high-throughput assay based on 3D ring-shaped cardiac tissues generated from human induced pluripotent stem cell-derived cardiomyocytes," developed a unique culture platform with PEG hydrogel that facilitates the in-situ measurement of contractile dynamics of the engineered cardiac rings. The authors optimized the tissue seeding conditions, demonstrated tissue morphology with expressions of cardiac and fibroblast markers, mathematically modeled the equation to derive contractile forces and other parameters based on imaging analysis, and concluded by testing several compounds with known cardiac responses.
The authors answered my questions with appropriate experiments and explanation.
(1) This paper presents an intriguing platform that creates miniature cardiac rings with merely thousands of cardiomyocytes per tissue in a 96-well plate format. The shape of the ring and the squeezing motion can recapitulate the contraction of the cardiac chamber to a certain degree. However, Thavandiran et al. (PNAS 2013) created a larger version of the cardiac ring and found that electrical propagation revealed spontaneous infinite loop-like cycles of activation propagation traversing the ring. This model was used to mimic a reentrant wave during arrhythmia. Therefore, there are concerns about whether a large number of cardiac tissues experience arrhythmia due to geometry-induced re-entry current and cannot be used as a healthy tissue model.
In the new experiment, the authors demonstrated with voltage-sensitive dye that these miniaturized tissues do not experience any arrhythmia, potentially due to their small size.
(2) The platform can produce 21 cardiac rings per well in 96-well plates, with the throughput being the highest among competing platforms. The resulting tissues exhibit good sarcomere striation due to the strain from the pillars. However, emerging questions pertain to culture longevity and reproducibility among tissues. According to Figure 1E, uneven ring formation around the pillar leads to tissue thinning and breakage. Only 50% survival is observed after 20 days of culture in the optimized seeding group. Are there any strategies to improve this survival rate? Additionally, do the cardiac rings detach from the glass slides and roll up, given the two compartments with cardiac and fibroblast-rich regions where fibroblasts maintain attachment to the glass slides? Moreover, the standard deviation of force measurement is a quarter of the value, which is suboptimal given the high replicate number. As the platform utilizes imaging analysis to derive contractile dynamics, calibration based on the angle and distance of the camera lens to individual tissues should be conducted to reduce error. On the other hand, how reproducible are the pillars? It is highly recommended to mechanically evaluate the consistency of the hydrogel-based pillars across different wells and within wells to understand the variance.
The authors stated that the platform has been tested and improved with multiple cell lines to enhance tissue survival rates. The methodology of image capture and calculation of contractile dynamics were explained in detail to address concerns. Moreover, the reproducibility of the pillars was demonstrated by consistent results of Young's Modulus (AFM) from each pillar, showing low standard deviations.
(3) Does the platform allow the observation of non-synchronized beating when testing with compounds? This can be extremely important as the intended applications of this platform are drug testing and cardiac disease modeling. The author should elaborate on the method in the manuscript and explain the obtained results in detail.
Referring to Question #1, the platform does not present arrythmia potentially due to the small size of the tissue.
(4) The results of drug testing are interesting. Isoperenoral is typically causing positive chronotropic and positive inotropic responses, where inotropic responses are difficult to obtain due to low tissue maturity. It is inconsistent with other reported results that cardiac rings do not exhibit increased beating frequency, but slightly increased forces only.
The authors repeated the experiment with the same results and hypothesized that the results would be line-dependent, since the maturation of iPSC-CM is not consistent. The additional dose curves provided more information on the tissue behaviors against well-known compounds.
Overall, the manuscript is well-written, and the designed platform presents unique advantages for high-throughput cardiac tissue culture. The paper has adequate data to demonstrate the proof-of-concept study of the platform. The throughput, consistency of the tissue, and the potential integration of high-throughput automation would be the highlights of this platform.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Thermogenic adipocyte activity associate with cardiometabolic health in humans, but decline with age. Identifying the underlying mechanisms of this decline is therefore highly important.
To address this task, Holman and co-authors present compelling data from their investigations of the effects of two major determinants of thermogenic activity: cold, which induce thermogenic de novo differentiation as well as conversion of dormant thermogenic inguinal adipocytes: and aging, which strongly reduce thermogenic activity. The authors study young and middle-aged mice at thermoneutrality and following cold exposure.
Using linage tracing, the authors conclude that the older group produce less thermogenic adipocytes from progenitor differentiation. However, they found no differences between thermogenic differentiation capacity between the age groups when progenitors are isolated and differentiated in vitro. This finding is consistent with previous findings in humans, demonstrating that progenitor cells derived from dormant perirenal brown fat of humans differentiate into thermogenic adipocytes in vitro. Taken together, this underscores that age-related changes in the microenvironment rather than autonomous alterations in the ASPCs explain the age related decline in thermogenic capacity, This is an important finding in terms of identifying new approaches to switch dormant adipocytes into an active thermogenic phenotype.
To gain insight into the age-related changes, the authors use single cell and single nuclei RNA sequencing mapping of their two age groups, comparing thermoneutral and cold conditions between the two groups. Interestingly, where the literature previously demonstrated that de novo lipogenesis (DNL) occurs in relation to thermogenic activation, the authors show that DNL in fact is activated in a white adipocyte cell type, whereas the beige thermogenic adipocytes form a separate cluster.
Considering recent findings, that adipose tissue contains several subtypes of ASPCs and adipocytes, mapping the changes at single cell resolution following cold intervention provides an important contribution to the field, in particular as an older group with limited thermogenic adaptation is analyzed in parallel with a younger, more responsive group. This model also allowed for detection of microenvironment as a determining factor of thermogenic response.
The use of only two time points (young and middle-aged) along the aging continuum limits the conclusions that can be made on aging as the only driver of the observed differences between the groups. Furthermore, as the authors also discuss, aging is a complex phenotype, and in this case the older mice were heavier and had larger fat depots, which should be taken into consideration when interpreting the data.
In conclusion, this study provides an important resource for further studies, which should investigate how the findings can be translated into humans for reactivation of dormant thermogenic fat and a potential improvement of metabolic health.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Metzger et al develop a rigorous method filling an important unmet need in protein evolution - analysis of protein genetic architecture and evolution using data from combinatorially complete 20^N variant libraries. Addressing this need has become increasingly valuable, as experimental methods for generating these datasets expand in scope and scale. Their method integrates two key features - (1) it reports the effects of mutations relative to the average across all variants, rather than a particular genotype, making it useful for examining global genetic architecture, and (2) it does this for all possible 20 states at each site, in contrast to the binary analyses in prior work. These features are not individually novel but integrating them into a single analysis framework is novel and will be valuable to the protein evolution community. Using a previously published dataset generated by two of the authors, they conclude that (1) changes in function are largely attributable to pairwise but not higher-order interactions, and (2) epistasis potentiates, rather than constrains, evolutionary paths. These findings are well-supported by the data. Overall, this work has important implications for predicting the relationship between genotype and phenotype, which is of considerable interest to protein biochemistry, evolutionary biology, and numerous other fields.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors have generated a set of yeast S. cerevisiae strains containing different numbers of chromosomes.<br /> Elimination of telomerase activates homologous recombination (HR) to maintain telomeres in cells containing the original 16 chromosomes. However, elimination of telomerase leads to circularization of cells containing a single or two chromosomes. The authors examined whether the subtelomeric sequences X and Y' promote HR-mediated telomere maintenance using the strain SY12 carrying three chromosomes. They found that the subtelomeric sequences X and Y' are dispensable for cell proliferation and HR-mediated telomere maintenance in telomerase-minus SY12 cells. They conclude that subtelomeric X and Y' sequences do not play essential roles in both telomerase-proficient and telomerase-null cells and propose that these sequences represent remnants of genome evolution.
Interestingly, telomerase-minus SY12 generates survivors that are different from well-established Type I or Type II survivors. The authors uncover atypical telomere formation which does not depend on the Rad52 homologous recombination pathway.
Strengths:
The authors examined whether the subtelomeric sequences X and Y' promote HR-mediated telomere maintenance using the strain SY12 carrying three chromosomes. They show that subtelomeres do not have essential roles in telomere maintenance and cell proliferation.
Weaknesses:
It is not fully addressed how atypical survivors are generated independently of Rad52-mediated homologous recombination.<br /> It remains possible that X and Y elements influence homologous recombination, type 1 and type 2 (type X), at telomeres. In particular, the presence of X and Y elements appears to be important for promoting type 1 recombination, although the authors conclude "Elimination of subtelomeric repeat sequences exerts little effect on telomere functions".
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arxiv.org arxiv.org
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Reviewer #1 (Public Review):
Summary: In this article, Mirza et al developed a continuum active gel model of actomyosin cytoskeleton that account for nematic order and density variations in actomyosin. Using this model, they identify the requirements for the formation of dense nematic structures. In particular, they show that self-organization into nematic bundles requires both flow-induced alignment and active tension anisotropy in the system. By varying model parameters that control active tension and nematic alignment, the authors show that their model reproduces a rich variety of actomyosin structures, including tactoids, fibres, asters as well as crystalline networks. Additionally, discrete simulations are employed to calculate the activity parameters in the continuum model, providing a microscopic perspective on the conditions driving the formation of fibrillar patterns.
Strengths: The strength of the work lies in its delineation of the parameter ranges that generate distinct types of nematic organization within actomyosin networks. The authors pinpoint the physical mechanisms behind the formation of fibrillar patterns, which may offer valuable insights into stress fiber assembly. Another strength of the work is connecting activity parameters in the continuum theory with microscopic simulations.
Weaknesses: This paper is a very difficult read for nonspecialists, especially if you are not well-versed in continuum hydrodynamic theories. Efforts should be made to connect various elements of theory with biological mechanisms, which is mostly lacking in this paper. The comparison with experiments is predominantly qualitative. It is unclear if the theory is suited for in vitro or in vivo actomyosin systems. The justification for various model assumptions, especially concerning their applicability to actomyosin networks, requires a more thorough examination. The classification of different structures demands further justification. For example, the rationale behind categorizing structures as sarcomeric remains unclear when nematic order is perpendicular to the axis of the bands. Sarcomeres traditionally exhibit a specific ordering of actin filaments with alternating polarity patterns. Similarly, the criteria for distinguishing between contractile and extensile structures need clarification, as one would expect extensile structures to be under tension contrary to the authors' claim. Additionally, its unclear if the model's predictions for fiber dynamics align with observations in cells, as stress fibers exhibit a high degree of dynamism and tend to coalesce with neighboring fibers during their assembly phase. Finally, it seems that the microscopic model is unable to recapitulate the density patterns predicted by the continuum theory, raising questions about the suitability of the simulation model.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, Liu et al. used scRNA-seq to characterize cell type-specific responses during allergic contact dermatitis (ACD) in a mouse model, specifically the hapten-induced DNFB model. Using the scRNA-seq data, they deconvolved the cell types responsible for the expression of major inflammatory cytokines such as IFNG (from CD4 and CD8 T cells), IL4/13 (from basophils), IL17A (from gd T cells), and IL1B from neutrophils and macrophages. They found the highest upregulation of a type 1 inflammatory response, centering around IFNG produced by CD4 and CD8 T cells. They further identified a subpopulation of dermal fibroblasts that upregulate CXCL9/10 during ACD and provided functional genetic evidence in their mouse model that disrupting IFNG signaling to fibroblasts decreases CD8 T cell infiltration and overall inflammation. They identify an increase in IFNG-expressing CD8 T cells in human patient samples of ACD vs. healthy control skin and co-localization of CD8 T cells with PDGFRA+ fibroblasts, which suggests this mechanism is relevant to human ACD. This mechanism is reminiscent of recent work (Xu et al., Nature 2022) showing that IFNG signaling in dermal fibroblasts upregulates CXCL9/10 to recruit CD8 T cells in a mouse model of vitiligo. Overall, this is a very well-presented, clear, and comprehensive manuscript. The conclusions of the study are mostly well supported by data, but some aspects of the work could be improved by additional clarification of the identity of the cell types shown to be involved, including the exact subpopulation discovered by scRNA-seq and the subtype of CD8 T cell involved. The study was limited by its use of one ACD model (DNFB), which prevents an assessment of how broadly relevant this axis is. The human sample validation is slightly circumstantial and limited by the multiplexing capacity of immunofluorescence markers.
Strengths:
Through deep characterization of the in vivo ACD model, the authors were able to determine which cell types were expressing the major cytokines involved in ACD inflammation, such as IFNG, IL4/13, IL17A, and IL1B. These analyses are well-presented and thoughtful, showing first that the response is IFNG-dominant, then focusing on deeper characterization of lymphocytes, myeloid cells, and fibroblasts, which are also validated and complemented by FACS experiments using canonical markers of these cell types as well as IF staining. Crosstalk analyses from the scRNA-seq data led the authors to focus on IFNG signaling fibroblasts, and in vitro experiments demonstrate that CXCL9 and CXCL10 are expressed by fibroblasts stimulated by IFNG. In vivo functional genetic evidence demonstrates an important role for IFNG signaling in fibroblasts, as KO of Ifngr1 using Pdgfra-Cre Ifngr1 fl/fl mice, showed a reduction in inflammation and CD8 T cell recruitment.
Weaknesses:
The use of one model limits an understanding of how broad this fibroblast-T cell axis is during ACD. However, the authors chose the most commonly employed model and cited additional work in a vitiligo model (another type 1 immune response). The identity of the involved fibroblasts and T cells in the mouse model is difficult to assess as scRNA-seq identified subpopulations of these cell types, but most work in the Pdgfra-Cre Ifngr1 fl/fl mice used broad markers for these cell types as opposed to matched subpopulation markers from their scRNA-seq data. Human patient samples of ACD were co-stained with two markers at a time, demonstrating the presence of CD8+IFNG+ T cells, PDGFRA+CXCL10+ fibroblasts, and co-localization of PDGFRA+ fibroblasts and CD8+ T cells. However, no IF staining demonstrates co-expression of all 4 markers at once; thus, the human validation of co-localization of CD8+IFNG+ T cells and PDGFRA+CXCL10+ fibroblasts is ultimately indirect, although not a huge leap of faith. Although n=3 samples of healthy control and ACD samples are used, there is no quantification of any results to demonstrate the robustness of differences.
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www.medrxiv.org www.medrxiv.org
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Reviewer #1 (Public Review):
Summary:
The authors report compound heterozygous deleterious variants in the kinase domains of the non-receptor tyrosine kinases (NRTK) TNK2/ACK1 in familial SLE. They suggest that ACK1 and BRK deficiencies are associated with human SLE and impair efferocytosis.
Strengths:
The identification of similar mutations in non-receptor tyrosine kinases (NRTKs) in two different families with familial SLE is a significant finding in human disease. Furthermore, the paper provides a detailed analysis of the molecular mechanisms behind the impairment of efferocytosis caused by mutations in ACK1 and BRK.
Weaknesses:
A critical point in this paper is whether the loss of function of ACK1 or BRK contributes to the onset of familial SLE. The authors emphasize that inhibitors of ACK1/BRK worsened IgG deposition in the kidneys in a pristane-induced SLE model, which contributes not to the onset but to the exacerbation of SLE, thus only partially supporting their claim.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this manuscript, the authors employed direct RNA sequencing with nanopores, enhanced by 5' end adaptor ligation, to comprehensively interrogate the human transcriptome at single-molecule and nucleotide resolution. They conclude that cellular stress induces prevalent 5' end RNA decay that is coupled to translation and ribosome occupancy. Contrary to the literature, they found that, unlike typical RNA decay models in normal conditions, stress-induced RNA decay is dependent on XRN1 but does not depend on the removal of the poly(A) tail. The findings presented are interesting but a substantial amount of work is needed to fully establish these paradigm-shifting findings.
Strengths:
These are paradigm-shifting observations using cutting-edge technologies.
Weaknesses:
The conclusions do not appear to be fully supported by the data presented.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this study Cacho-Navas et al. describes the role of ICAM-1 expressed on the apical membrane of bile canaliculi and its function to control the homeostasis of the bile canaliculi (BCs). This is a previously unrecognized function of this protein in hepatocytes. The same authors have previously shown that basolateral ICAM-1 plays a role in controlling lymphocyte adhesion to hepatocytes during inflammation and that this interaction is responsible on the loss of polarity of hepatocytes during the disease.<br /> In this new study they show that ICAM-1, is mainly localized in the apical domain of the BC and in association with EBP-50, comunicates with the subapical acto-myosin ring to regulate the size and morphology of the BC.<br /> In this study they used the well-known immortal cell line of liver cells (HepG2) in which they knocked-out ICAM-1 using CRISPR-Cas9 editing and hepatic organoid derived from WT and ICAM-1-KO mice. alternating knocking-out as well as rescue experiments they show that in the absence of apical ICAM-1, the BC dimension and shape are altered.<br /> The conclusions of the study are sufficiently supported by the data.
Comments on revision:
The authors have addressed most of the reviewer's comments in the re-submission, however the use of the organoids as a model to study bile canaliculi is still not convincing.<br /> The HA-4 staining and the space wehere CFDA is secreted does not overlap considering the nuclei position in the middle z-stack section. Also, the interdigitations between cells identified by EM do not form an enclosed space as we should expect for a bile canaliculi.<br /> I understand that other studies have used these organoids to show some hepatocytic functions but at the same time none has characterized before the formation of bile canaliculi as suggested in this study. Therefore a characterization showing the expression of specific markers (i.e mrp2, bsep) should be provided to support this claim.<br /> I would suggest the authors to carefully read the helpful review by Marsee et al., Cell Stem Cell 2021 that clearly and carefully address the classification and validation of liver organoids from experts in the field.
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www.sciencedirect.com www.sciencedirect.com
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ZDB-ALT-110124-1
DOI: 10.1016/j.celrep.2024.113955
Resource: ZFIN_ZDB-ALT-110124-1
Curator: @abever99
SciCrunch record: RRID:ZFIN_ZDB-ALT-110124-1
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www.researchsquare.com www.researchsquare.com
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Reviewer #1 (Public Review):
Tu et al investigated how LFPs recorded simultaneously with rsfMRI explain the spatiotemporal patterns of functional connectivity in sedated and awake rats. They find that connectivity maps generated from gamma band LFPs (from either area) explain very well the spatial correlations observed in rsfMRI signals, but that the temporal variance in rsfMRI data is more poorly explained by the same LFP signals. The authors excluded the effects of sedation in this effect by investigating rats in the awake state (a remarkable feat in the MRI scanner), where the findings generally replicate. The authors also performed a series of tests to assess multiple factors (including noise, outliers, and nonlinearity of the data) in their analysis.
This apparent paradox is then explained by a hypothetical model in which LFPs and neurovascular coupling are generated in some sense "in parallel" by different neuron types, some of which drive LFPs and are measured by ePhys, while others (nNOS, etc.) have an important role in neurovascular coupling but are less visible in Ephys data. Hence the discrepancy is explained by the spatial similarity of neural activity but the more "selective" LFPs picked up by Ephys account for the different temporal aspects observed.
This is a deep, outstanding study that harnesses multidisciplinary approaches (fMRI and ephys) for observing brain activity. The results are strongly supported by the comprehensive analyses done by the authors, which ruled out many potential sources for the observed findings. The study's impact is expected to be very large.
There are very few weaknesses in the work, but I'd point out that the 1-second temporal resolution may have masked significant temporal correlations between LFPs and spontaneous activity, for instance, as shown by Cabral et al Nature Communications 2023, and even in earlier QPP work from the Keilholz Lab. The synchronization of the LFPs may correlate more with one of these modes than the total signal. Perhaps a kind of "dynamic connectivity" analysis on the authors' data could test whether LFPs correlate better with the activity at specific intervals. However, this could purely be discussed and left for future work, in my opinion.
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Annotators
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Summary:
In this paper, Song, Shi, and Lin use an existing deep learning-based sequence model to derive a score for each haplotype within a genomic region, and then perform association tests between these scores and phenotypes of interest. The authors then perform some downstream analyses (fine-mapping, various enrichment analyses, building polygenic scores) to ensure that these associations are meaningful. The authors find that their approach allows them to find additional associations, the associations have biologically interpretable enrichments in terms of tissues and pathways, and can slightly improve polygenic scores when combined with standard SNP-based PRS.
Strengths:
- I found the central idea of the paper to be conceptually straightforward and an appealing way to use the power of sequence models in an association testing framework.
- The findings are largely biologically interpretable, and it seems like this could be a promising approach to boost power for some downstream applications.
Weaknesses:
- While not a weakness of the manuscript, the proposed method is computationally intensive.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this study, Hoops et al. showed that Netrin-1 and UNC5c can guide dopaminergic innervation from nucleus accumbens to cortex during adolescence in rodent models. They found that these dopamine axons project to the prefrontal cortex in a Netrin-1 dependent manner and knocking down Netrin-1 disrupted motor and learning behaviors in mice. Furthermore, the authors used hamsters, a seasonal model that is affected by the length of daylight, to demonstrate that the guidance of dopamine axons is mediated by the environmental factor such as daytime length and in sex dependent manner.
Regarding the cell type specificity of Netrin-1 expression, the authors began by stating "this question is not the focus of the study and we consider it irrelevant to the main issue we are addressing, which is where in the forebrain regions we examined Netrin-1+ cells are present." This statement contradicts the exact issue regarding the specificity issue I raised. They then went on to show the RNAscope data for Netriin-1 in Figure 2, which showed Netrin-1 mRNA was actually expressed quite ubiquitously in anterior cingulate cortex, dorsopeduncular cortex, infralimbic cortex, prelimbic cortex, etc. In addition, contrary to the authors' statement that Netrin-1 is a "secreted protein", the confocal images in Figure 1 in the rebuttal letter actually show Netrin-1 present in "granule-like" organelles inside the cytoplasm of neurons. Finally, the authors presented Figure 7 to indicate the location where virus expressing Netrin-1 shRNA might be located. Again, the brain region targeted was quite focal and most likely did not cover all the Netrin-1+ brain regions in Figure 2. Collectively, these results raised more questions regarding the specificity of Netrin-1 expression in brain regions that are behaviorally relevant to this study.
With respect to the effectiveness of Netrin-1 knockdown in the animals in this study, the authors cited data in HEK293 cells (Figure 5), which did not include any statistics, and previously published in vivo data in a separate, independent study (Figure 6). They do not provide any data regarding the effectiveness of Netrin-1 knockdown in THIS study.
Similar concerns regarding UNC5C knockdown (points #6, #7, and #8) were not adequately addressed.
In brief, while this study provides a potential role of Netrin-1-UNC5C in target innervation of dopaminergic neurons and its behavioral output in risk-taking, the data lack sufficient evidence to firmly establish the cause-effect relationship.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this paper, the authors developed an image analysis pipeline to automatically identify individual neurons within a population of fluorescently tagged neurons. This application is optimized to deal with multi-cell analysis and builds on a previous software version, developed by the same team, to resolve individual neurons from whole-brain imaging stacks. Using advanced statistical approaches and several heuristics tailored for C. elegans anatomy, the method successfully identifies individual neurons with a fairly high accuracy. Thus, while specific to C. elegans, this method can become instrumental for a variety of research directions such as in-vivo single-cell gene expression analysis and calcium-based neural activity studies.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
In this manuscript, Yao et al. explored the transcriptomic characteristics of neural stem cells (NSCs) in the human hippocampus and their changes under different conditions using single-nucleus RNA sequencing (snRNA-seq). They generated single-nucleus transcriptomic profiles of human hippocampal cells from neonatal, adult, and aging individuals, as well as from stroke patients. They focused on the cell groups related to neurogenesis, such as neural stem cells and their progeny. They revealed genes enriched in different NSC states and performed trajectory analysis to trace the transitions among NSC states and towards astroglial and neuronal lineages in silico. They also examined how NSCs are affected by aging and injury using their datasets and found differences in NSC numbers and gene expression patterns across age groups and injury conditions. One major issue of the manuscript is questionable cell type identification. For example, more than 50% of the cells in the astroglial lineage clusters are NSCs, which is extremely high and inconsistent with classic histology studies.
While the authors have made efforts to address previous critics, major concerns have not been adequately addressed, including a very limited sample size and patient information. In addition, some analytical approaches are still questionable and the authors acknowledge some issues they cannot address. Therefore, while the topic is interesting, some results are preliminary and some conclusions are not fully supported by the data presented.
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
The authors show that concurrently presenting foreign words and their translations during sleep leads to the ability to semantically categorize the foreign words above chance. Specifically, this procedure was successful when stimuli were delivered during slow oscillation troughs as opposed to peaks, which has been the focus of many recent investigations into the learning & memory functions of sleep. Finally, further analyses showed that larger and more prototypical slow oscillation troughs led to better categorization performance, which offers hints to others on how to improve or predict the efficacy of this intervention.
Comments on the revised version:
I applaud the authors on a nice rebuttal. Many responses use solid arguments based on the existing literature, such as their response regarding the possibility that low-level acoustic characteristics explaining EEG differences between conditions. Their new analyses also clarify the paper. Additionally, I appreciate their labeling their more speculative claims as such. Below are my remaining thoughts:
Major point:
The largest remaining issue for me regards the term 'episodic'. Before I begin, I should say that I imagine the authors have thought considerably about this definition and may disagree with what I will say. That would be fine - it's their choice at this journal. My main point in writing this is to help them clarify their case further. R3 had a similar concern on the first round of review, and I imagine others holding the "traditional" view of episodic memory would be similarly skeptical. If the authors have a great rebuttal to these points, I imagine it will address others' concerns too.<br /> I believe I understand the authors' argument: I read the Henke (2010, Nature Reviews Neuroscience) piece years back with great interest and again now, and I've gone back to read their other papers cited in this manuscript. Again, I applaud the authors on producing a large collection of fascinating findings expanding knowledge of what can be accomplished via unconscious learning. That includes this paper! But I still disagree with the term 'episodic' for what is measured here. The authors state in the Methods section that they prompted participants to 'guess whether the presented pseudoword designates an animal, a tool, or a place'. IMHO, the main issue of using 'episodic' is the nature of the memory representation - 'guessing' does not ask participants anything about the source (the who-what-when-why-where) of the information (anything about an episode).<br /> Notably, it does seem to fit their own definition from Henke (2010). Rapid? I believe so - 4 trial-learning is fairly quick. Certainly, there are studies of supposed episodic memory that use a few rounds of learning the same stimuli (rather than single trial learning) and one can still get away with calling the nature of the memories 'episodic'. Flexible? I believe the authors mean that their task is flexible because participants learn a category exemplar during sleep (e.g., 'aryl'-'bird') but then only respond based on its category membership ('animal'?). If this is the case, I agree that the representations are flexible. Reliant on the 'episodic memory system' (lines 495-9)? Reasonably likely, given their prior findings (e.g., Züst et al., 2019). However, there is considerable data suggesting the hippocampus contributes to functions beyond episodic memory, including statistical learning (e.g., Schapiro et al., 2013, Current Biology), motor learning (e.g., Schendan et al., 2003, Neuron; Dohring et al., 2017, Cortex; Jacobacci et al., 2020, PNAS), attention (e.g., Aly & Turk-Browne, 2016, Cerebral Cortex), perception (e.g., Lee et al., 2012), and semantic memory (e.g., Cutler et al., 2019, Frontiers in Human Neuroscience). Therefore, given that the hippocampus contributes to other tasks too, saying the task is episodic in part because it likely relies on the hippocampus (the 'episodic memory system') is an incorrect reverse inference. But regardless of this concern, it seems true to me that the term fits 'episodic' according to Henke (2010).<br /> So, it seems I'm raising an issue with this entire way of defining memory. IMHO, the biggest issue is that there is no reason to assume the participant relies upon any source-related information in making their guess. There is room in the field for a new type of rapid, unconscious, flexible, hippocampal-dependent learning that does not need to align with the term, 'episodic', for it to be important and fascinating! The term, 'episodic', is convenient for a reason - namely, for labeling the behavioral output of what it measures, not the process that underlies it. The authors have continually made an excellent case for rapid, unconscious, flexible, hippocampal-dependent learning, and it would seem even more beneficial for the field for the authors to just call this its own thing.
A related point:<br /> - I see that the authors do not use 'episodic' in prior papers with similar tasks (e.g., Züst et al., 2019), and I am curious if anything changed in their thinking or why they use the term now. They can ignore this if they'd like, but it would perhaps give useful context.
Other points:<br /> IMHO, the issue of repeated tests is more legitimate than the authors suggest. They state in their response letter, "However, recent literature suggests that retrieval practice is only beneficial when corrective feedback is provided (Belardi et al., 2021; Metcalfe, 2017)." This is incorrect. While retrieval practice is often less effective without feedback, it can be effective without feedback if retrieval accuracy is high and if the experimenters later employ a long enough retention interval to witness long-term effects. This is clear in various papers (e.g., Roediger & Karpicke, 2006, Psychological Science; Karpicke & Roediger, 2008, Science) and there is a nice theoretical model explaining how these complex effects could arise (Halamish & Bjork, 2011, JEP:LMC; Kornell et al., 2011, JML). The authors do not heavily rely on this in their paper, but they could consider tempering their claims that it is 'unlikely' (line 509) that delayed retrieval was affected by the first retrieval.<br /> The authors claim that fast spindles are part of a speculative model underlying their learning effects (lines 605-6). However, they did not find any differential spindle effects in determining later performance, so they could consider keeping just points #1&2 or mentioning that spindles differ by condition but may not directly influence the learning effects here.
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Reviewer #1 (Public Review):
This manuscript from Clayton and co-authors, entitled "Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors", aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first-generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microsecond MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped in identifying a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.
The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidine protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors can stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.
One potential weakness in the manuscript is the lack of reported uncertainties related to the analyzed quantities. Providing this information would significantly enhance the clarity regarding the reliability of the analyses and the confidence in the claims presented.
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Reviewer #1 (Public Review):
Zhang et al. tackle the important topic of primate-specific structural features of the brain and the link with functional specialization. The authors explore and compare gyral peaks of the human and macaque cortex through non-invasive neuroimagery, using convincing techniques that have been previously validated elsewhere. They show that nearly 60% of the macaque peaks are shared with humans, and use a multi-modal parcellation scheme to describe the spatial distribution of shared and unique gyral peaks in both species.
The claim is made that shared peaks are mainly located in lower-order cortical areas whereas unique peaks are located in higher-order regions, however, no systematic comparison is made. The authors then show that shared peaks are more consistently found across individuals than unique peaks, and show a positive but small and non-significant correlation between cross-individual counts of the shared peaks of the human and the macaque i.e. the authors show a non-significant trend for shared peaks that are more consistently found across humans to be those that are also more found across macaques.
In order to identify if unique and shared peaks could be identified based on the structural features of the cortical regions containing them, the authors compared them with t-tests. A correction for multiple comparisons should be applied and t-values reported. Graph-theoretical measures were applied to functional connectivity datasets (resting-state fMRI) and compared between unique and shared peak regions for each species separately. Again the absence of multiple comparison correction and t-values make the results hard to interpret. The same comment applies to the analysis reporting that shared peaks are surrounded by a larger number of brain regions than unique peaks. Finally, the potentially extremely interesting results about differential human gene expression of shared and unique peaks regions are not systematically reported e.g. the 28 genes identified are not listed and the selection procedure of 7 genes is not fully reported.
The paper is well written and the methods used for data processing are very compelling i.e. the peak cluster extraction pipeline and cross-species registration.
Comments on revision:
The authors have convincingly addressed all my previous concerns such that, as the revised paper stands now, the presented results provide solid support for the conclusions of the authors. The revised paper is now of interest for a large part of the neuroscience community and specifically for those interested in primate-specific structural features of the brain and the link with functional specialization.
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Reviewer #1 (Public Review):
Summary:
The authors re-analysed the data of a previous study in order to investigate the relation between asymmetries of subcortical brain structures and the hemispheric lateralization of alpha oscillations during visual spatial attention. The visual spatial attention task crossed the factors of target load and distractor salience, which made it possible to also test the specificity of the relation of subcortical asymmetries to lateralized alpha oscillations for specific attentional load conditions. Asymmetry of globus pallidus, caudate nucleus, and thalamus explained inter-individual differences in attentional alpha modulation in the left versus right hemisphere. Multivariate regression analysis revealed that the explanatory potential of these regions' asymmetries varies as a function of target load and distractor salience.
In the revision of the article, the authors addressed my concerns.
However, my concern with regard to the statistical analysis of the specificity of certain subcortical regions predicting HLM seems to be not fully addressed. The authors added an additional statistical analysis for "testing the null hypothesis that a given regressor does not impact all dependent variables". To my understanding, this is a somewhat unusual definition of a null hypothesis. Typically, the null hypothesis is the hypothesis of no effect, meaning here it should state that the effect is the same across predictors.
In the new statistical analysis, the authors seem to take non-significant results (p>.05) as evidence for the specificity of subcortical regions in predicting HLM. The rationale of this statistical approach is difficult to follow and was somewhat unclear to me.
A much simpler and more straight-forward approach would be to contrast beta-estimates per subcortical region between experimental conditions. For instance, if the beta estimates in the thalamus for the "low-load target, non-salient distractor" condition would be significantly larger than the beta estimates for the other conditions, this would speak to specificity.
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Reviewer #1 (Public Review):
SUMMARY:
Parkinson's disease (PD) and other synucleinopathies, including Parkinson's Disease Dementia (PDD), Dementia with Lewy Bodies (DLB), and Multiple System Atrophy (MSA), pose significant challenges for early diagnosis, as their clinical manifestations often emerge after substantial neurodegeneration has occurred. In this context, the Alpha-Synuclein Seeding Amplification Assay (SAA) has garnered considerable attention for its potential as a diagnostic tool, capable of detecting pathological forms of alpha-synuclein (αSyn) even before the onset of classical clinical symptoms and signs. The assay exploits αSyn's intrinsic property to convert healthy forms into pathological ones, subsequently amplifying these pathological forms for visualization. This study aims to investigate the efficacy of SAA in accurately identifying subtypes of synucleinopathies, including PD, PDD, DLB, and MSA. To achieve this, the results from the patient brain-derived αSyn SAA are compared with those obtained through conformational stability assays, immunolabeling, and electron microscopy. Study shows that brain-derived αSyn fibrils exhibit significant differences across various synucleinopathies in their conformation, biochemical profile and phosphorylation patterns. Importantly, the SAA method appears to fall short in capturing these distinctions.
The study's findings are highly relevant given the rapidly advancing landscape of utilizing the SAA for the diagnosis and differentiation of various forms of PD and synucleinopathies using patient biofluids. It is somewhat surprising that the authors primarily characterize SAA as a research tool without delving into its potential as a biomarker detection assay, especially in the context of the field's excitement about its diagnostic applications. Additionally, a missed opportunity lies in not referencing a recent study that employed SAA successfully to diagnose PD and subtype the condition using a vast sample size. To further strengthen the results, the inclusion of healthy control brains in the biochemical and immunostaining/immunoblot experiments would provide more robust comparisons. Overall, the authors have conducted their experiments diligently, and their study offers valuable insights that align with the ongoing efforts to enhance early diagnosis and subtype differentiation in the domain of synucleinopathies.
STRENGTH:
The strengths of this research article are indeed notable and contribute to the credibility and significance of the study:
Important Research Question: The study addresses a crucial question in the field of neurodegenerative diseases by evaluating the effectiveness of the αSyn SAA in diagnosing and differentiating synucleinopathies. This question is of significant clinical and scientific interest.<br /> Comprehensive Introduction: The article provides a thorough and well-structured introduction to the topic with an illustration, setting the stage for the research. It ensures that readers, including those unfamiliar with the subject matter, can grasp the context and significance of the study.<br /> Use of Patient Brain Tissue: The use of patient-derived brain tissue samples from various synucleinopathies, including PD, PDD, DLB, and MSA, enhances the clinical relevance and applicability of the findings.<br /> Replication and Statistical Significance: Conducting the experiments six times for each sample demonstrates the rigor of the study and the robustness of the results, and increases the confidence in the conclusions drawn.<br /> Clarity in Experimental Results and Discussion: The authors have presented the experimental results in a clear and understandable manner. I was personally impressed by images showing twisted and straight conformations of αSyn, as well as immunogold labeling for phosphorylation of αSyn, which aids in conveying the findings effectively to the readers. The results clearly show distinct differences in the characteristics of αSyn fibrils across different synucleinopathies. It also highlights the more aggressive seeding capacities and higher biochemical stability of αSyn in PDD and DLB patients, offering valuable insights into the pathophysiology of these conditions. The authors also clearly show that SAA fails in differentiating the disease types within the synucleinopathies.<br /> Clinical relevance: The study underscores the importance of considering complementary diagnostic methods alongside SAA for a more comprehensive understanding of synucleinopathy subtypes. The study might also play an important role in potential FDA approval of SAA as a diagnostic tool for synucleinopathies, especially for PD.<br /> These strengths collectively make the study a valuable contribution to the field of neurodegenerative diseases, shedding light on the limitations and potential applications of SAA in the diagnosis and differentiation of various synucleinopathies.
WEAKNESS:
While this study is overall robust, there are several aspects that could further enhance the quality and interpretation of the findings.
Clinical Data on Patient Brain Samples: The inclusion of specific details such as post-mortem intervals and the age at disease onset for patient brain samples would be valuable. These factors could significantly affect the quality of the tissues and their relevance to the study. Moreover, given the large variation in disease duration between PD and PDD, it's important to consider disease duration as a potential confounding factor, especially when concluding that PDD patients have a more severe form of synucleinopathy compared to PD.<br /> Inclusion of Healthy Controls in Multiple Tests: Given the importance of healthy controls in scientific studies, especially those involving human brain samples, the authors could consider using healthy controls in more tests to strengthen the robustness of the findings. Expanding the use of healthy controls in biochemical profiling and phosphorylation profiles would provide a better basis for comparison and clarify the significance of results in a disease context.<br /> This will help the authors to elaborate on the interpretation of results, for example, in Figure 3, where the authors claim that PD brains show mostly monomeric αSyn forms (line 119 and 120, and also in 222 and 223). Whether it implies the absence of alpha-syn pathology in PD brains? If there are differences from healthy controls? What are these low molecular weight bands (<15kD) (line 125-126) and whether they are also present in healthy controls? Also, we do not have a perfect pS129-specific (anti-p𝛼Syn) antibody. They are known for non-specific labeling. Investigating the phosphorylation levels in healthy controls and comparing them to PD brains, especially considering the predominance of monomeric (healthy αSyn?) in PD brains, would help clarify the observed changes.<br /> Age of Healthy Controls: Providing information about the age at death for healthy controls is crucial, as age can impact the accumulation of αSyn. Also include if the brain samples were age-matched, or analyses were age-adjusted.<br /> Braak Staging Discrepancy: The study reports the same Braak staging for both PD and PDD, despite the significant difference in disease duration. Maybe other reviewers with clinical experience might have a better take on this. This observation merits discussion in the paper, allowing readers to better understand the implications of this finding.<br /> Citation of Relevant Studies: The paper should consider citing and discussing a recent celebrated study on PD biomarkers that used thousands of cerebrospinal fluid (CSF) samples from different PD patient cohorts to demonstrate the effectiveness of SAA as a biochemical assay for diagnosing PD and its subtypes (https://doi.org/10.1016/S1474-4422(23)00109-6).<br /> In summary, these suggestions aim to enhance the study's quality and the clarity of its findings, ultimately contributing to a more comprehensive understanding of synucleinopathies and the diagnostic potential of SAA.
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Reviewer #1 (Public Review):
Summary:
Songbirds provide a tractable system to examine neural mechanisms of sequence generation and variability. In past work, the projection from LMAN to RA (output of the anterior forebrain pathway) was shown to be critical for driving vocal variability during babbling, learning, and adulthood. LMAN is immediately adjacent to MMAN, which projects to HVC. MMAN is less well understood but, anatomically, appears to resemble LMAN in that it is the cortical output of a BG-thalamocortical loop. Because it projects to HVC, a major sequence generator for both syllable phonology and sequence, a strong prediction would be that MMAN drives sequence variability in the same way that LMAN drives phonological variability. This hypothesis predicts that MMAN lesions in a Bengalese finch would reduce sequence variability. Here, the authors test this hypothesis. They provide a surprising and important result that is well motivated and well analyzed: MMAN lesions increase sequence variability - this is exactly the opposite result from what would be predicted based on the functions of LMAN.
Strengths:
(1) A very important and surprising result shows that lesions of a frontal projection from MMAN to HVC, a sequence generator for birdsong, increase syntactical variability.
(2) The choice of Bengalese finches, which have complex transition structures, to examine the mechanisms of sequence generation, enabled this important discovery.
(3) The idea that frontal outputs of BG-cortical loops can generate vocal variability comes from lesions/inactivations of a parallel pathway from LMAN to RA. The difference between MMAN and LMAN functions is striking and important.
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Reviewer #1 (Public Review):
Summary:
This manuscript reports a series of experiments examining category learning and subsequent generalization of stimulus representations across spatial and nonspatial domains. In Experiment 1, participants were first trained to make category judgments about sequences of stimuli presented either in nonspatial auditory or visual modalities (with feature values drawn from a two-dimensional feature manifold, e.g., pitch vs timbre), or in a spatial modality (with feature values defined by positions in physical space, e.g., Cartesian x and y coordinates). A subsequent test phase assessed category judgments for 'rotated' exemplars of these stimuli: i.e., versions in which the transition vectors are rotated in the same feature space used during training (near transfer) or in a different feature space belonging to the same domain (far transfer). Findings demonstrate clearly that representations developed for the spatial domain allow for representational generalization, whereas this pattern is not observed for the nonspatial domains that are tested. Subsequent experiments demonstrate that if participants are first pre-trained to map nonspatial auditory/visual features to spatial locations, then rotational generalization is facilitated even for these nonspatial domains. It is argued that these findings are consistent with the idea that spatial representations form a generalized substrate for cognition: that space can act as a scaffold for learning abstract nonspatial concepts.
Strengths:
I enjoyed reading this manuscript, which is extremely well written and well presented. The writing is clear and concise throughout, and the figures do a great job of highlighting the key concepts. The issue of generalization is a core topic in neuroscience and psychology, relevant across a wide range of areas, and the findings will be of interest to researchers across areas in perception and cognitive science. It's also excellent to see that the hypotheses, methods and analyses were pre-registered.
The experiments that have been run are ingenious and thoughtful; I particularly liked the use of stimulus structures that allow for disentangling of one-dimensional and two-dimensional response patterns. The studies are also well powered for detecting effects of interest. The model-based statistical analyses are thorough and appropriate throughout (and it's good to see model recovery analysis too). The findings themselves are clear-cut: I have little doubt about the robustness and replicability of these data.
Weaknesses:
In my original review I raised a concern related to a potential alternative interpretation of the findings: the idea that participants have substantial experience of representing space in terms of multiple, independent, and separable dimensions, whereas this may not be the case for the visual and auditory stimuli used here. As I noted in that prior review, on this view "the impact of spatial pre-training and (particularly) mapping is simply to highlight to participants that the auditory / visual stimuli comprise two separable (and independent) dimensions."
In addressing this point, the authors note that performance in the visual/auditory "mapping" task in Experiments 2c and 3c suggests that most participants were paying attention to both dimensions of auditory and visual stimuli. I agree that seems to have been the case. But there is a difference between making use of information from both dimensions, and realizing that ***the two dimensions are separable and independent*** (which is what is required for rotational generalization in this task).
As an analogy, suppose I have a task where participants have to map a pillow and a shuttlecock to category A, and a surfboard and a bicycle to category B. A participant could learn to do this just by memorizing the correct response for each item considered as a "whole thing". Or they could realize that the items contain component information, learning that "things with feathers" belong in category A, and "things that can carry people" go in category B. Performance may be the same in both cases, but the underlying process is quite different.
The "attention to dimensions" account that I advanced in my previous review was referring to something more like the latter (feathers/vehicle) case: that spatial pre-training helps people to understand that items can be decomposed into separable pieces of information. Above-chance performance in the visual-auditory mapping task does not (necessarily) demonstrate this ability because it could reflect memorization of "whole" stimuli rather than reflecting decomposition into separable component parts. I agree that it does at least show that participants were paying attention to and making use of information from both dimensions when making their mapping decisions; it's just that they may not have *realized* that they were using information from two separable dimensions.
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Reviewer #1 (Public Review):
Summary:
This is an interesting report examining activity patterns in mouse ACC and in the OFC neurons projecting to ACC. In addition, the effects of inactivation are examined. In aggregate, the results provide new and interesting information about these two brain areas and they translate motivation into action - a function that it seems intuitively plausible that ACC might perform but, despite this intuition, there have been comparatively few direct tests of the idea and little is known of the specific mechanisms. The study is performed carefully and is written up clearly. There were just a few points where I wondered if a little more clarification might be helpful.
Strengths:
The combination of recording and inactivation/inhibition experiments and the combination of investigation of ACC neurons and of OFC regions projecting to ACC are very impressive.
Weaknesses:
These are all minor points of clarification.
(1) An important conclusion (Figure 4) is that when mice are trained to run through no reward (N) cues in order to reach reward (R) cues, the OFC neurons projecting to ACC each respond to different specific events in a manner that ensures that collectively they tile the extended behavioural sequence. What I was less sure of was whether the ACC neurons do the same or not. Figure 3 suggests that on average ACC neurons maintain activity across N cues in order to get to R cues but I was not sure whether this was because all individual neurons did this or whether some had activity patterns like the OFC neurons projecting to ACC.
(2) Figure 1 versus Figure 2: There does not seem to be a particular motivation for whether chemogenetic inactivation or optogenetic inhibition were used in different experiments. I think that this is not problematic but, if I am wrong and there were specific reasons for performing each experiment in a certain way, then further clarification as to why these decisions were made would be useful. If there is no particular reason, then simply explaining that this is the case might stop readers from seeking explanations.
(3) P5, paragraph 2. The authors argue that OFC and anteriomedial (AM) thalamic inputs into ACC are especially important for mediating motivation through N cues in order to reach R cues. Is this based on a statistical comparison between the activity in OFC or AM inputs as opposed to the other inputs?
(4) P3, paragraph 2. Some papers by Khalighinejad and colleagues (eg Neuron 2020, Current Biology, 2022) might be helpful here in as much as they assess ACC roles in determining action frequency, initiation, and speed and mediating the relationship between reward availability and action frequency and speed.
(5) Paragraph 1 "This learning is of a more deliberate, informed nature than habitual learning, as they are sensitive to the current value of outcomes and can lead to a novel sequence of actions for a desired outcome1-3." Should "they" be "it"?
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Reviewer #1 (Public Review):
Summary:
Wang and colleagues present a study aimed at demonstrating the feasibility of repeated ultrasound localization microscopy (ULM) recording sessions on mice chronically implanted with a cranial window transparent to ultrasound. They provided quantitative information on their protocol, such as the required number of contrast-enhancing microbubbles (MBs) to get a clear image of the vasculature of a brain coronal section. Also, they quantified the co-registration quality over time-distant sessions and the vasodilator effect of isoflurane.
Strengths:
The study showed a remarkable performance in recording precisely the same brain coronal section over repeated imaging sessions. In addition, it sheds light on the vasodilator effect of isoflurane (an anesthetic whose effects are not fully understood) on the different brain vasculature compartments, although, as the authors stated, some insights in this aspect have already been published with other imaging techniques. The experimental setting and protocol are very well described.
Weaknesses:
While the title is fair with respect to the data shown, in the summary and the rest of the paper, the comparison between anesthetized and awake conditions is systematically stated, while more caution should be used.
First, isoflurane is one of the (many) anesthetics commonly used in pre-clinical research, and its effect on the brain vasculature cannot be generalized to all the anesthetics. Indeed, other anesthesia approaches do not produce evident vasodilation; see ketamine + medetomidine mixtures. Second, the imaged awake state is head-fixed and body-constrained in mice. A condition that can generate substantial stress in the animals. In this study, there is no evaluation of the stress level of the mice. In addition, the awake imaging sessions were performed a few minutes after the mouse woke up from isoflurane induction, which is necessary to inject the MB bolus. It is known that the vasodilator effects of isoflurane last a long time after its withdrawal. This aspect would have influenced the results, eventually underestimating the difference with respect to the awake state.
These limitations should be clearly described in the Discussion.
Looking at Figure 2e, it takes more than 5' to reach the 5 Millions MB count useful for good imaging. However, the MB count per pixel drops to a few % at that time. This information tells me that (i) repeated measurements are feasible but with limited brain coverage since a single 'wake up' is needed to acquire a single brain section and (ii) this approach cannot fit the requirements of functional ULM that requires to merge the responses to multiple stimuli to get a complete functional image. Of course, a chronic i.v. catheter would fix the issue, but this configuration is not trivial to test in the experimental setup proposed by the authors, hindering the extension of the approach to fULM.
Statistics are often poor or not properly described. The legend and the text referring to Figure 2 do not report any indication of the number of animals analyzed. I assume it is only one, which makes the findings strongly dependent on the imaging quality of THAT mouse in THAT experiment. Three mice have been displayed in Figure 3, as reported in the text, but it is not clear whether it is a mouse for each shown brain section. Figure 5 reports quantitative data on blood vessels in awake VS isoflurane states but: no indication about the number of tested mice is provided, nor the number of measured blood vessels per type and if statistics have been done on mice or with a multivariate method. Also, a T-test is inappropriate when the goal is to compare different brain regions and blood vessel types. Similar issues partially apply to Figure 6, too.
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Reviewer #2 (Public Review):
The authors combine genetic tools, dye fills and connectome analysis techniques to generate a "first-of-its-kind", near complete, synaptic resolution map of the head bristle neurons of Drosophila. While some of the BMN anatomy was already known based on previous work by the authors and other researchers, this is the first time a near complete map has been created for the head BMNs at electron microscopy resolution.
Strengths:
(1) The authors cleverly use techniques that allow moving back and forth between periphery (head bristle location) and brain, as well as moving between light microscopy and electron microscopy data. This allows them to first characterize the pathways taken by different head BMNs to project to the brain and also characterize anatomical differences among individual neurons at the level of morphology and connectivity.<br /> (2) The work is very comprehensive and results in a near complete map of all head BMNs.<br /> (3) Authors also complement this anatomical characterization with a first-level functional analysis using optogenetic activation of BMNs that results in expected directed grooming behavior.
Weaknesses:<br /> (1) While not strictly needed here, it could help provide context if authors revealed some of the important downstream pathways that could explain optogenetics behavioral phenotypes: This point was addressed by authors in the revisions and I agree a detailed description of downstream circuits is not needed at this point.<br /> (2) In contrast to the rigorous quantitative analysis of the anatomical data, the behavioral data is analyzed using much more subjective methods. While I do not think it is necessary to perform a rigorous analysis of behaviors in this anatomy focused manuscript, the conclusions based on behavioral analysis should be treated as speculative in the current form e.g. calling "nodding + backward motions" as an avoidance response is not justified as it currently stands. Strong optogenetic activation could lead to sudden postural changes that due to purely biomechanical constraints could lead to a couple of backward steps as seen in the example videos. Moreover since the quantification is manual, it is not clear what the analyst interprets as backward walking or nodding. Interpretation is also concerning because controls show backward walking (although in fewer instances based on subjective quantification): This point was addressed by the authors during revisions and I'm mostly satisfied with their response, where authors agree that the behavioral results are currently used to speculate about the role of BMNs in aversive behaviors. Still, the fact that controls show some "backward motions" is a bit concerning when talking about "significant differences" between control and test groups based on manual annotations and I would recommend future studies focusing on these behaviors to use more unbiased quantitative analysis wherever possible.
Summary:
The authors end up generating a near-complete map of head BMNs that will serve as a long-standing resource to the Drosophila research community. This will directly shape future experiments aimed at modeling or functionally analyzing the head grooming circuit to understand how somatotopy guides behaviors. I appreciate the authors taking the time to revise the manuscript and address reviewer concerns.
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Reviewer #1 (Public Review):
Summary:
The motivating questions are an accurate reflection of the current state of knowledge surrounding striatal pathway function. The comparisons of pathway function across striatal subregion, activation & inhibition, and task context are laudable and extremely important for advancing the subfield. Had these manipulations, to the largest extent possible been performed in single animals (e.g. activate dSPNs of DMS or DLS in the same mouse across the 3 tasks), this would have significantly strengthened the impact and conclusions that could be drawn by making this set of studies even more so internally consistent and directly comparable. While this is no longer possible, a conceptually related and fantastic contribution to the subfield (and likely beyond in terms of Opto manipulations of brain areas) would be to directly demonstrate that within their studies their DMS pathway manipulations do not impact nearby DLS activity (and vice versa). This is a significant and non-essential request. More feasibly and reasonably, it would be fantastic and strengthen the conclusions here to more fully detail their opsin expression patterns in DMS vs DLS groups and perhaps attempt to relate individual opsin profiles and fiberoptic targeting with behavioral outcomes across tests.
Strengths:
A comprehensive and paired comparison of inhibition and activation of striatal pathways across subregions and tasks is a very important and meaningful step towards reconciling contradictory results on striatal pathway function that are observed across labs (who typically focus on one subregion, one task setting, and often do not directly report comparisons of activation and inhibition).
Weaknesses:
Figure 1A - the example DMS vs DLS opsin expression and fiber targeting are not terribly convincing that the manipulations will be specific to each subregion (the example in Figure 2A is a little better but I have a similar concern still). The specificity of these manipulations is key to interpretation and conclusions and I strongly feel they should be strengthened here. The best evidence would be direct neural recordings (light in DMS, no effect in DLS, and vice versa), but this is a tall ask and not expected. The next best option, which is readily feasible, is to show not only fiberoptic targeting summaries (as in Figure 1A, Figure 2A) but also a summary of opsin spread for all animals (especially given the two examples appear to have significant spread across DMS and DLS). It would be of great benefit to the field to have these in the Allen Common Coordinate Framework. It would also be fine and useful to utilize the authors' current classical histological atlas alignment methods (e.g. Paxinos pdf). These histological summary figures would also benefit from being larger and more visible (perhaps as separate supplemental figures associated with the main figures).
Related to the above, it is a concern that the classic view is supported or not because of individual variations in virus/fiber targeting to striatal subregions which likely have greater granularity than the traditional dorsal medial vs lateral (e.g. Hunnicutt et al 2016, Foster et al 2021, Hintiryan et al 2016). Although there may not be enough animals or variation in targeting in the present study to find meaningful relationships, it would strengthen the paper and be a great benefit to the field to know whether for key findings if the strength of behavioral effects correlated with anterior/posterior or medial/lateral or dorsal/ventral fiberoptic coordinates (or the volume of opsin expression profiles).
Conceptually, a clear new idea or integrative interpretation of prior work (nor even the large body of results within this work) comes to the fore, save for the already appreciated fact that the classic view of opposing pathways is sometimes supported and sometimes not. Two tangible suggestions that I believe would facilitate the influence of this study - (1) can the authors more thoughtfully bridge the logical steps in their results sections and the prior context around them (some topic sentences jump right into results, e.g. line 195: "The inhibition experiment showed), and (2) in discussion, rather than emphasizing when/where the classic view is supported and not, more content on precisely why would be helpful. Some questions more specifically, if DMS/DLS pathway activation/inhibition is *mostly* oppositely appetitive/aversive, what does that mean in the context of spontaneous or reward-guided locomotion? Self-initiated pathway activation/inhibition is in part learned (with very intriguing differences across pathways in the expression across learning) - how should we think about striatal pathway function with regards to learning, spontaneous/innate behaviors, vs over-trained behaviors? When the classic view fails in the dorsal striatum - why? And is a complimentary "model" an actual alternative concept, a distinct mode of circuit function, or just a negative result on the classic view?
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www.biorxiv.org www.biorxiv.org
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Reviewer #1 (Public Review):
Gazula and co-workers presented in this paper a software tool for 3D structural analysis of human brains, using slabs of fixed or fresh brains. This tool will be included in Freesurfer, a well-known neuroimaging processing software. It is possible to reconstruct a 3D surface from photographs of coronal sliced brains, optionally using a surface scan as model. A high-resolution segmentation of 11 brain regions is produced, independent of the thickness of the slices, interpolating information when needed. Using this method, the researcher can use the sliced brain to segment all regions, without the need of ex vivo MRI scanning.
The software suite is freely available and includes 3 modules. The first accomplishes preprocessing steps, for correction of pixel sizes and perspective. The second module is a registration algorithm that registers a 3D surface scan obtained prior to sectioning (reference) to the multiple 2D slices. It is not mandatory to scan the surface, -a probabilistic atlas can also be used as reference- however the accuracy is lower. The third module uses machine learning to perform the segmentation of 11 brain structures in the 3D reconstructed volume. This module is robust, dealing with different illumination conditions, cameras, lens and camera settings. This algorithm ("Photo-SynthSeg") produces isotropic smooth reconstructions, even in high anisotropic datasets (when the in-plane resolution of the photograph is much higher than the thickness), interpolating the information between slices.
To verify the accuracy and reliability of the toolbox, the authors reconstructed 3 datasets, using real and synthetic data. Real data of 21 postmortem confirmed Alzheimer's disease cases from the Massachusetts Alzheimer's Disease Research Center (MADRC)and 24 cases from the AD Research at the University of Washington(who were MRI scanned prior to processing)were employed for testing. These cases represent a challenging real-world scenario. Additionally, 500 subjects of the Human Connectome project were used for testing error as a continuous function of slice thickness. The segmentations were performed with the proposed deep-learning new algorithm ("Photo-SynthSeg") and compared against MRI segmentations performed to "SAMSEG" (an MRI segmentation algorithm, computing Dice scores for the segmentations. The methods are sound and statistically showed correlations above 0.8, which is good enough to allow volumetric analysis. The main strengths of the methods are the datasets used (real-world challenging and synthetic) and the statistical treatment, which showed that the pipeline is robust and can facilitate volumetric analysis derived from brain sections and conclude which factors can influence in the accuracy of the method (such as using or not 3D scan and using constant thickness).
Although very robust and capable of handling several situations, the researcher has to keep in mind that processing has to follow some basic rules in order for this pipeline to work properly. For instance, fiducials and scales need to be included in the photograph, and the slabs should be photographed against a contrasting background. Also, only coronal slices can be used, which can be limiting for certain situations.
The authors achieved their aims, and the statistical analysis confirms that the machine learning algorithm performs segmentations comparable to the state-of-the-art of automated MRI segmentations.<br /> Those methods will be particularly interesting to researchers who deal with post-mortem tissue analysis and do not have access to ex vivo MRI. Quantitative measurements of specific brain areas can be performed in different pathologies and even in the normal aging process. The method is highly reproducible, and cost-effective since allows the pipeline to be applied by any researcher with small pre-processing steps.
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