Reviewer #3 (Public Review):

This manuscript investigates the impact of Growth arrest-specific 6 (Gas6) on Zika virus (ZIKV) infection and congenital disease. The authors use a cohort of patient samples isolated from the recent ZIKV outbreak and compliment these data with in vitro and in vivo mouse models to conclude that Gas6 association with ZIKV viral particles promotes neuronal complication and congenital ZIKV syndrome. A clear strength of the study is the incorporation of human data, which allows for some translatability from the in vitro and in vivo mouse studies included in the study. However, despite enthusiasm for the human dataset, there are significant weaknesses with both these data and many other studies in the manuscript that diminish this enthusiasm considerably. I have detailed my specific comments for the authors to consider below:

General comments:

1. For data transparency, it would be nice for the authors to include individual data points throughout the manuscript. This is also important for patient data, where the authors only now show box plots and not individual data points.

2. The font size in many figures is very small and resolution is very low. The authors should consider increasing these.

Specific comments:

1. The data provided in Figure 1 with a large cohort of patient data is a strength of the study, although the magnitude of the changes in Gas6 are not particularly compelling. Perhaps the authors can provide more discussion on variation in patient titers, timing of infection, or other information that might explain these differences. The authors should also include sex distribution of the patient data.

2. I do not find the data in Figure 2 particularly compelling. Moreover, these data do not support the conclusion that Gas6 directly correlates with these changes. I suggest removing these data from the manuscript.

3. Some aspects of Figure 4 are difficult to reconcile. Why does warfarin reduce viral titers so significantly without impacting levels of vRNA?

4. ELISA or Luminex data should be included to compliment transcript data in Figure 4.

5. There are Gas6 KO mice commercially available that the authors could use to support their findings. Data from these animals would be a rigorous way to determine the direct impact of Gas6 on ZIKV infections.

6. How stable is the association between Gas6 and ZIKV particles used? How was this complexing and purification performed? How did the authors measure the efficiency of the association? There are very few experimental details provided on these very important points.

7. Additional animal numbers are needed for the data shown in Figure 5D and 5E unless the authors can provide some justification of the analyses used to calculate the power needed for these studies.

8. There are no details provided for the data in pregnant women. At what stage of gestation were these women? When was the collection of blood relative to timing of infection? These are important details that should be included.

9. There are insufficient n's to show the data in Supplemental Figure 6B.

10. Figure 6 is difficult to interpret given the overall low number of animals and lack of analyses. Given that each pup has its own placenta, how do the authors know which of the fetuses in which the dam was infected with Gas6-ZIKV were actually infected/exposed to the virus? The data in Figure 6F would suggest that every fetus was infected, which is difficult to imagine at this stage of gestation. More details should be provided.

11. The inclusion of IHC and H&E analyses from placentas is needed.

12. Were only two animals used to generate the data in Figure 6D? What is the justification for such low numbers?

13. The impact of the Gas6-ZIKV complex virus on maternal viral loads are a critical point and should be included (with appropriate n's).

14. The author's conclude that monocytes are the primary producers of Gas6, but do not provide sufficient data to support these claims. As these data were performed in THP-1-derived monocytes, the authors should consider differentiating these monocytes to macrophages using PMA and determine the impact of this modulation on Gas6 production.

Reviewer #1 (Public Review): 

This is a very interesting manuscript showing the contribution of intrinsic excitability in the formation of cortical neuronal ensembles. Using paired recordings from layer 2/3 neurons from the visual cortex, the authors show that co-activation of neurons by optogenetic or electrical stimuli leads to persistent synaptic potentiation preceded by a transient synaptic depression. The stimulation of neurons induces, in addition, persistent plasticity of intrinsic neuronal excitability that is associated with an enhancement of membrane resistance and a hyperpolarization of the spike threshold. The authors conclude that intrinsic plasticity allows to persistently maintain activated circuits according to an iceberg-like effect, and thus to generate a new neuronal ensemble. 

This study is interesting as it integrates synaptic and intrinsic plasticity in the frame of the formation of cortical neuronal ensembles. However, it is unclear whether intrinsic plasticity occurs at pre- and post-synaptic neurons as illustrated in the final iceberg scheme. This has been shown by Ganguly et al., Nat Neurosci 2000 & Li et al., Neuron (2004). Nevertheless, this paper will have a strong impact in the field because of its conceptual clarity and the quality of the data.

Reviewer #2 (Public Review): 

This is a potentially very impactful manuscript. The reason is that plasticity of membrane excitability (intrinsic plasticity) is largely understood as a mechanism that merely aids synaptic plasticity (in cortex: LTP) in its role in the formation of memory engrams and in learning. For example, one prominent hypothesis (Josselyn/Silva) suggests that intrinsic plasticity might enhance the probability for subsequent LTP induction and form/stabilize engrams in this way. A somewhat different view has been presented by Brunel/Hansel, who argue that under some conditions, intrinsic plasticity can integrate neurons into engrams, even when synaptic weights remain frozen. Importantly, the current work might provide evidence for this latter intrinsic theory of learning. However, in this in vitro study, the application of optogenetic or electric protocols to drive correlated neuronal activity in a defined ensemble does not only lead to strong changes in membrane excitability but also causes a biphasic change in synaptic weights. Below, I will make suggestions on how these synaptic and intrinsic effects could be further separated (this should be done if the goal of this study is to show that excitability changes alone can promote ensemble integration). 

Major comments: 

Line 79 f: It is not clear from this paragraph, which of the cited papers provide experimental details and which one presents the 'alternative hypothesis' (Titley et al., 2017; see above). This should be described more accurately to share the precise status quo of this research field with the audience. 

Figure 2: This is the critical point, and my experimental comments will focus on this: the authors show in this figure that both the optical stimulation as well as the electrical stimulation trigger synaptic plasticity, consisting of an immediate depression, followed after a pause by a potentiation. This potentiation is - in the case of electrical stimulation - significantly different from the baseline values (not significant for the opto group, but the number of recordings is quite low). It thus is conceivable that this effect contributes to the enhanced correlation of activity in the network that is shown in Figure 1. 

This is a physiological observation, but attempts should be made to block/prevent the synaptic change and to assess whether enhanced correlation can persist with only excitability changes being available as a cellular mechanism. One way to do this is to perform recordings with physiological calcium and magnesium concentrations in the ACSF. As stated in the methods, the authors used 2mM Calcium and 1mM Magnesium. The physiological concentrations are about 1.2 mM Calcium and 1 mM Magnesium, thus creating an ionic milieu that is likely to be less permissive for LTP. The authors should try whether under these conditions the biphasic synaptic change is gone/reduced and the excitability change persists. If so, they can then test whether the enhanced activity correlation is still seen. Also, these recordings should be performed at physiological temperature. 

If this is not successful (or as an alternative to start with), the authors might try pharmacological or genetic LTP blockade (e.g. targeting NMDA receptors or CaMKII) or use weaker stimulation protocols (intrinsic plasticity has a lower induction threshold than LTP).

Reviewer #1 (Public Review):

This is essentially a simulation study of how IDPs interacts with a folded protein, or a folding-upon-binding event. This study speaks little to the the specific mechanism of Vav1, although it uses Vav1 autoinhibitory interaction as an example system. While the atomic details of the folding-upon-binding event is generally plausible, several aspects of this study requires clarification.

The first issue is a technical but potentially important one. The authors used three CVs in the metadynamics simulation-based study, which can be sound, except that the 1st and the 3rd CVs (native IDP binding contacts and the native binding contacts of a particular tyrosine of the IDP) seem highly correlated. This is generally less than ideal in sampling. What is the justification of introducing the 3rd CV other than the practical need to observe the binding/folding event in simulations? Was any analysis performed to preclude the possibility that the combination of these two correlated CVs distorts the binding process?

Secondly, the described binding event as an conformational selection process is inconsistent with a very similar process (IDP forming a helix and binding with a protein) as studied using unbiased MD simulation (https://doi.org/10.1021/jacs.0c03217), which showed that the helix formation was more of a consequence of the binding contacts, or in other word, an induced process. Likely the realty is not black and white, but because the cited study was based on unbiased situations and because the concerns with respect to the CVs used in the metadynamics simulations, further investigation and discussion may be needed.

Thirdly, the inconsistency with previous NMR study of the system in terms of binding free energy is concerning and further calculation/simulations seem necessarily. For example, can the simulations reproduce the energetic effect of certain mutations, which was also studied using NMR? Further work to ascertain the degree and depth of the issue would be extremely valuable.

Reviewer #2 (Public Review):

The manuscript describes a computational characterization of the binding and unbinding dynamics of a buried phosphorylated residue in the inhibitory module to the functional domain of Vav1, in an effort to shed lights on the autoinhibition mechanism. However, as the authors discussed at length in the "binding equilibrium" section (starting from line 269), the inconsistency between the computational findings and the NMR data, in terms of the free energy differences between the two states, is puzzling. While I appreciate very much the honest and insightful discussion about the potential convergence and force field issues that may have contributed to the inconsistency, the advancement that this work brings to our understanding of the mechanism is not obvious. Thus, it appears that this manuscript may fit better to a specialized journal in which the strength and weakness of using metadynamics to investigate IDR can be thoroughly presented and discussed.

Reviewer #3 (Public Review):

By using enhanced sampling simulations and force fields that ar able to describe both folded and unfolded states, the authors address the timely and important question of autoinhibition regulation in a prototypical system: the Dbl Homology domain in the protein Vav1. Their simulations and free energy landscapes are consistent with a complex and intriguing process, whereby partial folding<br /> the Ac-helix while unbound is followed by its docking to the binding site.<br /> The authors carefully compare their results to available experiments and openly discuss the discrepancies and their possible source.

The computational methods used here can be easily adapted to explore other auto inhibition mechanisms.

Reviewer #1 (Public Review):

Wolf et al. utilized transcriptional profiling of choroidal neovascularization (CNV ) membranes from four patients with neovascular age-related macular degeneration or nAMD (re-analyzed from their recent publication; Schlecht et al., 2020, Am J Pathol) and laser-induced murine model of CNV and identified fibroblast growth factor inducible-14 (FN14), as phylogenetically conserved mediator of CNV formation. Furthermore, the authors utilized intravitreal injection of FN14 decoy receptor that blocks interaction between FN14 and its ligand TWEAK to demonstrate reduced CNV size and decreased expression of a specific cytokine (IL6) in the laser induced murine model of CNV. Based on this data, the authors propose FN14 as a novel therapeutic target for nAMD. As highlighted by the authors, anti-VEGF therapy, the current therapeutic intervention for nAMD is not effective in about one third of nAMD patients. Therefore, the identification of novel therapeutics for nAMD has high clinical relevance. Importantly, the data presented in the current study is consistent with prior studies that have shown altered levels of FN14 as well as a role of TWEAK/FN14 pathway in pathological angiogenesis, including retinal neovascularization. Similarly, the claim that FN14 inhibition does not affect VEGF-A levels and displays VEGF-independent anti-angiogenic effect is supported by similar findings reported earlier in a model of ischemia induced retinopathy.

Overall, although the data show a contribution of FN14 in CNV pathology in laser induced murine model of CNV, the limited sample size of nAMD CNV membranes and lack of mechanistic insights in the rodent model, preclude the definitive link between TWEAK/FN14 pathway in nAMD.

1) Major challenge for the current study are technical limitations relevant to obtaining a larger sample size for human CNV membranes and lack of a suitable preclinical model to investigate nAMD pathobiology. Specifically to link/implicate FN14 in nAMD would require validating the FN14 expression changes in CNV membranes from a bigger nAMD sample size that is likely not feasible. Similarly, although laser-induced CNV is routinely utilized for nAMD studies, this is a VEGF-dependent process where anti-VEGF is remarkably efficient in targeting CNV and therefore not ideal for investigating mechanisms and drug-targets for patient population not responsive to anti-VEGF therapy.

2) The mechanistic basis of observed FN14 upregulation and consequence of FN14 upregulation need to be further clarified. FN14 is a highly inducible cytokine receptor that engages multiple signaling pathways, including nuclear factor-kB (NF-kB) and mitogen-activated protein kinase (MAPK). Given that the authors did not observe any significant upregulation of its ligand Tweak in human vitreous and plasma samples as well as in murine retina and RPE samples (Supplementary Fig. 4), makes it likely that FN14 mediated signaling pathway may be activated independent of its ligand TWEAK. Furthermore, it is well-established that FN14 is up-regulated after injury and apart from TWEAK expression of FN14 can be regulated by several cytokines and growth factors, and various other cytokines, including those that were upregulated in the current study (Figure 4). Therefore it would be important to interrogate if any of the upregulated cytokines (Figure 4) increases the expression and acts as a ligand for FN-14. Similarly, the human FN14 promoter region contains several potential transcription factor binding sites, including AP-1 sites and an NF-κB site. The activation of NF-κB involves two major signaling pathways, the canonical and non-canonical (or alternative) pathways. The canonical NF-κB pathway responds to diverse stimuli, including ligands of various cytokine receptors, pattern-recognition receptors (PRRs), TNF receptor (TNFR) superfamily members. Mechanistically, therefore it would be important to understand if FN-14 expression is upstream or downstream of these signaling pathways.

3) With regard to the data on FN14 decoy receptor, given that a decoy receptor binds to a receptor and does not signal or activate the intended receptor complex thus acting as inhibitor, it would be important to show the effect of the decoy receptor on the known downstream molecules of FN14 such as NF-κB or MAPK. This is particularly important as only Il-6 expression were significantly down regulated in experiments utilizing FN14 decoy receptor (Figure 4).

Reviewer #2 (Public Review):

Wolf and colleagues compare transcriptomic changes in human CNV membranes to-matched control RPE/choroid as well as in the mouse laser-induced CNV model. While it is conceptually a great study, this reviewer has concerns regarding the methodology. First, the comparison of isolated CNV membranes to normal RPE/choroid complex does not seem appropriate unless the CNV membrane contains RPE and choroid, which does not appear to be the case based on the histology shown. Since the RPE are believed to play a key role in CNV formation, analyzing the tissue without their contribution tells us little about this pathological process. Rather, analysis of the CNV membrane alone gives more information regarding CNV growth and scar formation.

A related second concern is the timepoint of analysis for the mice. At 7 days post laser, the CNV is still forming in the mouse model. Therefore, it is not surprising that comparing this to advanced human CNV generated different results. Perhaps a later timepoint would have been more informative and comparable to human CNV membranes. Still, this timepoint yields interesting information regarding changes during CNV formation. Another question regarding the mouse laser model is how many laser CNV spots were included in each section for sequencing analysis. Also, it is unclear if CNV was somehow isolated or if entire sections from laser-induced CNV mice were used for RNA isolation. If CNV areas were not isolated, the normal tissue in these sections could reduce the transcriptional changes detected.

Despite questions regarding the methodology, the conservation of the increased fibroblast growth factor inducible-14 between human and mouse is intriguing. Moreover, the inhibition of FN-14-TWEAK pathway further supports the role of FN-14 in CNV formation. The authors successfully demonstrate the potential role of FN-14 in CNV formation and, in doing so, present a potentially novel therapeutic target for neovascular AMD.

Reviewer #3 (Public Review):

The authors here present a transcriptome analysis of choroidal neovascular (CNV) membranes and compare these data to a mouse model of laser-induced CNV. Through this analysis they found several genes that were differentially expressed within these human CNV lesions and the mouse CNV lesions, and found common orthologous genes that were differentially expressed. Via these analyses the authors identified conserved mediators of CNV formation in human and mouse including FN14, LGALS3, AIF1, UNC5B, ADAM15, MCAM, CYBB, APLNR, KCNN4, UNC93B1. The authors focused on FN14 and its ligand TWEAK as it has been previously shown to be involved in angiogenesis, and suggests the FN14 / TWEAK pathway to be a potential target for the treatment of CNV.

They provide data that supports their conclusions, which have some strengths and weaknesses as follows.

1. The study was able to perform transcriptome analysis of difficult to obtain patient-derived CNV samples. They used 4 sections from CNV samples that were surgically removed. This material is difficult to obtain, and is directly relevant for human disease. However, I am concerned about the age of these samples and the fact that these samples were paraffin embedded, and how this could have affected the transcriptome data and analysis.

2. The authors used the commonly used mouse laser-induced CNV model, which is a surrogate model of human CNV. This model is more consistent with a wound healing model, and there is a combination of inflammatory, angiogenic, and fibrotic processes that occur throughout the model. Thus the rationale to compare these two different lesions may be limited, and makes it somewhat difficult to compare directly through a transcriptome analysis.

3. Their transcriptome analysis is consistent with genes that are known to be unregulated in CNV lesions. FN14 itself has previously been shown by Ameri et al. to mediate angiogenesis in retinal neovascularization. The authors do an admirable job of attempting to validate this result in the CNV lesions

4. The authors validated their study by immunofluorescence staining of FN14 within the the human and mouse CNV lesions. With respect to their suggestion that it may be used as a therapeutic, it is concerning that there is staining of the choroidal and retinal vessels in mice suggesting a normal physiologic role of FN14 within the retinal and choroidal vasculature as seen in Figure 3E, A. Though in humans there seems to be relatively low expression in the human retina.

5. They observed the presence of the FN14 ligand TWEAK in human vitreous samples, again providing relevance for human pathology. However, there was no difference in TWEAK levels within the vitreous and plasma of control and patients with wet AMD, suggesting its does not play a significant role in pathology.

6. Using an FN14 decoy they show decreased CNV lesion size and decreased IL-6 expression in the mouse CNV lesion, again providing supporting evidence of its role in treating CNV. However, these findings may only be relevant in the setting of laser-induced CNV, where there is known to be increased mediators of inflammation.

Reviewer #1 (Public Review):

In this paper, the authors investigate the tuning of visual neurons in primate area MT to motion parallax signals and to binocular disparity. Among this class of neurons, some are tuned incongruently to depth using these two cues - that is, neurons can be tuned to more distant objects through motion parallax but closer ones through binocular disparity. Using carefully designed visual stimuli, the authors investigate the tuning properties of these neurons and how they relate to a psychophysical task in which a monkey distinguishes world-frame-moving objects from world-frame-stationary objects during self-motion of the monkey.

The experiments and stimuli are expertly designed and the analyses are careful.

My primary question, in reading this paper, is how much of the psychophysical effect can be attributed to these incongruently tuned neurons, rather than simply having a population of neurons with a relatively wide range of tunings. The analyses and simulations as presented don't back up the central claim as strongly as they could that it's these incongruent neurons in particular that facilitate these psychophysical percepts.

Reviewer #2 (Public Review):

In this study, Kim et al. investigate an unsolved riddle in the neural mechanisms of motion perception: how does the visual system detect dynamic objects in the presence of self motion? They recorded from single neurons in macaque area MT while animals performed an object motion detection task while undergoing self motion. They find that MT neurons with incongruent depth tuning to binocular disparity and motion parallax cues respond selectively to dynamic objects during self motion. They further show that the response of these neurons are predictive of the animal's choice. They conclude that such incongruent neurons might play a novel role in solving the problem of scene relative object motion.

The study is elegantly conducted and the paper is very well written. The findings, although correlative, represent an important step forward in our understanding of the neural mechanisms of motion perception.

I have no major comments.

Reviewer #3 (Public Review):

The authors investigated how the visual system solves the important and challenging problem of detecting independently moving objects while the observer undergoes self-motion. The paper focuses on a certain population of neurons in brain area MT ('opposite cells') that exhibit tuning to combinations of motion parallax (i.e. speed and direction) and binocular disparity that would generally not be compatible with the retinal motion created by stationary objects in the environment during self-motion. One example is tuning to fast speeds and far away depth through disparity. Such combinations of signals that preferentially activate opposite cells are more likely to arise from an independently moving object than self-motion relative to a stationary environment, assuming both sources of information are available. The main hypothesis tested in this paper is whether opposite cells could be used as a neural mechanism to detect independently moving objects. Consistent with their tuning properties, the authors found that opposite cells demonstrate stronger activation to moving objects than stationary objects. More generally, there was an inverse correlation between congruence in motion parallax+disparity tuning and the preference for moving objects. In support of the main hypothesis, an ROC analysis revealed that opposite cells were more effective in detecting moving from stationary objects through a difference in firing rate when the object was labeled as moving either according to the ground truth or monkey judgments. The estimates of a linear classifier trained on model fits of the MT data reinforced the authors' findings.

The investigated topic is very interesting and the work is a valuable contribution to the field. The paper is well written. The experiments were well-designed and controlled. The analyses were appropriate and support the hypothesis.

The proposed local mechanism has a few limitations, mainly in its scope. First, the proposed local mechanism critically depends on the availability of binocular disparity. Humans are capable of detecting moving objects based on monocular optic flow, even when the moving object is aligned with the motion due to self-motion and varies based on speed alone (Royden & Moore, 2012). This scenario would not engage the proposed mechanism because disparity is not available and thus another mechanism like flow parsing would be needed. Second, while the proposed local mechanism may be more 'economical' (p. 3) than flow parsing, flow parsing addresses more phenomena than moving object detection. For example, flow parsing implicates the estimation of the world-relative direction (Warren & Rushton 2009; Fajen et al., 2013) and speed (Jörges & Harris, 2021) of independently moving objects. Layton & Fajen (2020) showed that a neural model of flow parsing can be used to detect moving objects in both monocular and binocular optic flow fields. The visual system may require a more 'complicated mechanism' (p. 28) to robustly perform the broader range of tasks, in situations where disparity may or may not be available and informative.

Reviewer #1 (Public Review):

This manuscript describes the capacity of primary human cholangiocytes to form ductal structures by self-organisation in progressively more complex culture conditions, including prefabricated channels. It reveals the importance of ECM components CollagenI and Fibrin and growth factor signalling by EGF and HGF for duct differentiation and branching. This analysis further shows an epistatic role of Notch signalling in this process. This work represents an important study of in vitro differentiation of commercial cholangiocytes into bilary ducts with a potential to contribute and advance tissue engineering approaches in the liver field. The presented work should be of interest to scientists in the stem cell differentiation and tissue engineering fields, as well as liver organogenesis.

Strength: Overall, the conclusions and interpretation are supported by the analysis. With the increasing complexity of the conditions, it provides a unique angle and valuable insights into culturing strategies to generate intricate ductal structures.

Weakness: My major concern is the statement that hierarchical intrahepatic bile ducts can be differentiated. The study shows exciting and promising data, however they require systematic characterisation of ductal differentiation in the various conditions. For instance, while 'hierarchical intrahepatic biliary ducts' are described for the chip configuration, neither cholangiocyte gene expression nor open lumens have been tested.

Reviewer #2 (Public Review):

The lack of suitable in vitro culture system recapitulating bile duct formation and branching slows the analysis of the mechanisms driving biliary morphogenesis. Here, the authors used adult human primary intrahepatic cholangiocytes and first confirmed the biliary phenotype of the cells by analysing the expression of cholangiocyte-specific markers and measuring enzyme activity. The cholangiocytes formed limited branched structures in Matrigel, but sprouting was significantly increased when Matrigel was mixed with collagen type I and when the medium was supplemented with EGF. Functional metabolite transport into the biliary lumen is demonstrated. The biological relevance of this culture system is supported by experiments showing that the effects of collagen plus EGF is abrogated by genetic or pharmacological inhibition of Notch signaling, a pathway which is essential in vivo for normal bile duct morphogenesis. Finally, the authors show that the culture conditions can be adapted into a microfluidic chip that should be amenable to the introduction of flow.

Strengths<br /> The paper is clearly written and illustrated, and the conclusions of the experiments are supported by the data. The biological relevance and biomedical interest of the new culture system combining Matrigel/collagen and EGF is well demonstrated by the experiments targeting Notch signaling and by the cultured ducts' capacity to transport a metabolite into the lumen.

Weaknesses<br /> The main weakness is in the limited morphological, functional and transcriptomic characterization of the cultured bile ducts, which is in part underlined by the authors in the discussion. To convince the reader of the wide applicability of the culture system and on the advantages of this system over existing ones mentioned in the paper, data on its stability over time should ideally be provided. Knowledge on regional specificities of cholangiocytes have accumulated recently, and providing a more detailed gene expression profile of the cultured cholangiocytes would also help in evaluating the potential usefulness of the system. Although the microfluidic chip with cholangiocytes is very appealing, prove of functionality, not only morphogenesis, would considerably improve the paper.

The materials and methods section does not describe the experimental procedures with sufficient detail.

Reviewer #3 (Public Review):

The manuscript from Smith et al. describes an in vitro platform to study bile duct cells morphogenesis and validate the role of Notch in this process. The authors use commercially available cholangiocytes, which they place in 3D culture and assess the capacity of the cells to form branching networks in the presence or absence of Notch signaling. Finally, they seed the cells on microfluidic chips. The resulting structures do not remain patent in chips incorporating Matrigel/collagen gels, but do so when fibrin-based gels are used.

Strengths<br /> Branching morphogenesis plays an important role both for biliary development and disease. Therefore, in principle, developing an in vitro platform to model this process could be beneficial both for groups working on developmental biology and for labs focusing on infantile cholangiopathies, such as Alagille syndrome.

Weaknesses<br /> Despite the usefulness of a modeling platform for tubulogenesis, the manuscript fails to illustrate the strengths of the system described and the analysis performed is insufficient to support the authors' claims. In particular:

The authors claim that their system differs from existing in vitro platforms for growing cholangiocytes in various aspects. However, these claims are not substantiated by a direct comparison between systems and, in some cases, they are contradicted by the references in the manuscript. For example, Sampaziotis et al. claim to grow mature and not adult-stem cell derived cholangiocytes. Although, the system by Huch et al. is based on adult stem cells, the characterization of cholangiocytes in the manuscript is very limited and does not provide evidence of marker expression or functional properties that are not demonstrated by adult stem cell-derived cholangiocytes. I agree about the difficulties in perfusing organoid systems and this is an important point; however, densified collagen tubes seeded with human cholangiocytes have also described and referenced in the paper (Ref 11).

Furthermore, the authors are using adult cholangiocytes for studying an embryological process (tubulogenesis) that happens at the level of the ductal plate and is initiated by the interaction between hepatoblasts and the ductal plate mesenchyma. Conceptually, adult frozen primary cholangiocytes expanded in monolayer and then cultured in Matrigel fail to recapitulate this setup; which renders the system not physiologically relevant. Therefore, it is difficult to assess how the mechanisms observed in this setting translate to human development or disease without further validation in vivo, or in patient tissue.

Importantly, the characterization of the cells and the platform lacks context and depth. Comparison to fresh primary cholangiocytes is required to assess the value of the system. A very limited number of markers is assessed, often with a single modality (e.g. only IF or only QPCR). Moreover, the data shown does not always support the claims of interpretation of the authors, but I have made specific recommendations on how to improve these aspects in the next section. The main concern here is the lack of convincing evidence for the presence of a lumen inside the branching structures, which recapitulates the lumen of bile ducts in vivo, ie surrounded by cells circumferentially with dimensions corresponding to the terminal branches of the intrahepatic ducts.

The use of microfluid chips could be an exciting aspect of the paper, as this has not been extensively described in the literature with human cells (although it has been achieved with mouse cells, PMID: 31465556) and the authors have a track record in this area. However, the matrix that was used for all the cells' characterization throughout the paper seems not to be working very well for maintaining a patent lumen and the authors switch to a fibrin-based ECM. There are 3 issues with this approach. First, although fibrin is present in the body, it is usually present in injury, which renders it an even less physiological matrix than Matrigel to study morphogenesis. Second, the human cells are not characterized in this new matrix, which could impact on marker expression or function. Third, and most importantly, the authors do not demonstrate how this chip could be used by the community, which functional assays could be performed, whether there is any benefit to the profile of the cells from perfusion or what additional insight it provides the system provides compared to Matrigel.

Reviewer #1 (Public Review):

The authors have improved the patterned chemical functionalization of surfaces using large-area polydimethylsiloxane (PDMS)-based elastomeric stamps.They then proceed with investigating the interaction of Grb2 with EGFR by expressing an artificial transmembrane receptor construct that has Grb2 as bait (bait-PAR-Grb2). They could show that these constructs are indeed organized according to the extracellular antibody surface pattern. They then pattern EGFR by a micro-structured surface of anti-EGFR antibodies (ED) and observe the interaction with what is now the freely diffusing prey bait-PAR-Grb2 construct. After stimulation with the growth factor EGF they observe an increase of recruitment of bait-PAR-Grb2 above already basal levels in these EGFR receptor patterns.

Here, several problems occur. For one, there is no quantification of this enhanced recruitment, just exemplary images in contrast to some other experiments. Second and more important, since the now prey (bait-PAR-Grb2) construct is part of the construct that is inserted in the membrane both EGFR as well as Grb2 react in an approximately two-dimensional surface. The tremendous increase in effective concentration of the Grb2-prey can therefore not only force the interaction with EGFR in this second order reaction (possibly irrespective of phosphorylation, see below) but also enhance the effective kinase activity of EGFR towards these highly concentrated substrates. These could now recruit pTyr dependent SH2 domain containing signaling adapters or activities like Shc. For example, already the basal kinase activity of EGFR could thereby generate substantial recruitment without EGF-stimulus and the stimulus-dependent response could result in hyper-phosphorylation of Grb2. It is also possible that due to the enhanced concentration at the plasma membrane of bait-PAR-Grb2 there is an interaction of the TMD of the Bait-PAR-Grb2 with EGFR that patterns the construct. The reason why I allude to this, is because there is no interaction of the bait-PAR-Grb2 construct without linker with the freely diffusing Shc (which should not be a problem in terms of super-enhanced concentration driven interaction with the prey (Shc) because it is freely diffusing in the cytoplasm). This could point at a problem in terms of Grb2 hyper-phosphorylation by EGFR kinase activity in the construct. Indeed, when the authors increase the linker length between Grb2 and the artificial receptor, they can actually observe a recruitment of Shc to the Bait-Parc-Grb2 pattern (again not quantified). Since in this case, the bait-PAR-Grb2 was patterned, it could well be that EGFR is recruited to bait-PAR-Grb2 via SH2-pTyr interaction, which then hyper phosphorylates Grb2 to recruit Shc or Shc is simply recruited to pTyr on EGFR or both mechanisms apply. In general, any second order protein interaction or reaction (for example kinase) is a function of the effective concentration of its components, which is highly distorted in a second order reaction system that has both Grb2 and EGFR associated and diffusing in the 2D surface of the membrane. In case that the prey is freely diffusible and the bait is on the membrane, this does not apply.

Another problem is that the presented models are not unambiguous nor provide any insight what they mean for EGFR signaling beyond what was already known for quite a while now. In that sense, none of the findings on constant SH3 mediated (Grb2-SOS or Grb2-Gab) interactions or pTyr conditional SH2 mediated interactions (Shc, Grb2, p85) are surprising or provide new information about EGFR signaling. What would have been interesting is if and how the pTyr-SH2 mediated complexes are distributed between the phosphorylated receptor and phosphorylated adapters in a EGFR density dependent manner and what impact this would have had on signaling. This would of course require constructs with mutations on pTyr sites and the monitoring of interactions with multiple Bait-PARs of wt and mutant proteins, all in the same cell. In this respect, the major point that could lift the methodology presented in the paper in relation to what was previously done, is the patterning of N different Bait-Parcs to simultaneously monitor multiple different interactions during receptor-induced signaling in the same cell. The modular design principle of bait-PARCs enables this simultaneous protein-interaction measurements and thereby allows for the direct analysis of relations between proteins in interconnected signaling networks. This is necessary to for example unravel mechanisms of signaling via distributed processes, signaling crosstalk and off-target effects of drugs, which are the rule more than the exception and otherwise blurred by cell-to-cell variance in protein expression levels and internal reaction states. This also applies to the presented studies on small molecule PPI disruptors that yielded nice results but no new significant insights.

Reviewer #2 (Public Review):

The approach is based on plating cells on a substrate containing micropatterned antibodies to the extracellular domain of a transmembrane bait protein, resulting in areas of high concentration of the intracellular portion of the bait, surrounded by areas of lower concentration. Fluorescently labeled prey proteins are co-expressed in the same cell, and association of bait and prey is assessed (via TIRF microscopy) by the colocalization of the prey with areas of high local bait concentration. As a test system, the authors chose the Grb2 adaptor as a bait, which can interact with other signaling proteins in the EGFR pathway via its SH2 domain or its two SH3 domains. In addition to being able to assess whether pairwise interactions are dependent on EGFR activation (and thus tyrosine phosphorylation) or are constitutive, further experiments tested the ability of cell-penetrating compounds to inhibit bait-prey interactions, and used FRAP to assess the kinetics of prey association.

Strengths: The beauty of this approach is that experiments can be performed in living cells in real time, using relatively simple and straightforward imaging approaches. Most other approaches to address similar questions either require cell lysis, or more sophisticated imaging modalities. In particular, the ability to examine both on-rates (via FRAP) or off-rates (using chemical inhibitors) provides valuable information that is often difficult to obtain in living cells. Thus in principle this has the potential be a real workhorse method for dissecting the dynamics of signaling events at the membrane.

Weaknesses: Despite the potential advantages of the approach, there are a number of serious weaknesses. Both bait and prey are extensively modified (by addition fusion to fluorescent proteins, and in the case of the bait by covalent tethering to the transmembrane fusion). High level expression of both bait and prey can potentially distort the kinetics of interactions and/or compete with endogenous interactions. Specifically in this case, membrane localization of Grb2 is expected to lead to constitutive activation of the Ras and possibly PI3K pathways, which is likely to induce feedback inhibition in cells expressing these constructs.

Another concern is that the signaling interactions studied are potentially much more complicated than the simple (and in some cases non-canonical) models presented here. Grb2 SH2 domain can interact directly with phosphorylated EGFR or with phosphorylated Shc (which is recruited to and phosphorylated by activated EGFR); PI3K can be activated by recruitment to phosphorylated Gab1 or EGFR, or by activated Ras; EGFR activation not only provides binding sites for SH2 domains on the receptor itself, but also phosphorylates Shc, Gab1, and many other proteins. So the recruitment of a prey protein to Grb2 bait upon EGF treatment can be due to any number of molecular interactions, greatly complicating interpretation of results.

Finally, the interpretation of the inhibitor experiments in Fig. 6 is complicated because of lack of information on the precise mechanisms involved-actinomycin D is not a well characterized signaling inhibitor, and the cyclic SH2 ligand seems to be acting to inhibit SH3-mediated interactions instead of SH2-mediated interactions as expected. These inhibitor data are quite surprising and difficult to rationalize, and thus in my mind do not provide solid evidence of the usefulness of the system for studying inhibitors.

Reviewer #1 (Public Review):

This asks how members of the kinesin-4 family stabilise the tips of microtubules so as to suppress both their growth and shrinkage. Using crystallography of soluble tubulin in complex with KLP-12, a kinesin-4 from C. elegans, electron microscopy, and biochemistry, together with characterisation of mutants in C. elegans, the authors build a case that kinesin-4 motors control microtubule length by stabilising tubulin in a bent conformation that is too straight to depolymerise readily and too bent to insert stably into the lattice.

The core of the work is a new crystal structure of KIF12 in complex with GMPCPP tubulin, with assembly of the tubulin blocked with a DARPIN that is fused to the kinesin. The structure is 2.9A resolution. Evidence is also presented that the KIF12 controls microtubule length in neurons and in vitro, that it is motile when artificially dimerised, and that its ATPase is activated both by microtubules and by free tubulin - especially by free tubulin.

The structure shows that KIF12 bends tubulin heterodimers to a level that lies between the extremes of bending defined by the KIF5B (lattice stabiliser) and KIF2C (lattice destabiliser) complexes. The detailed structure of the KIF12-tubulin interface is compared with these exemplars and KIF12 / kinesin-4 specific features identified.

The work will impact thinking about the detailed molecular basis of the mechanical interaction of kinesins with tubulins.

Reviewer #2 (Public Review):

Taguchi et al. carried out a functional and structural analysis of microtubule dynamics inhibition by the C. elegans kinesin-4 KLP-12. The authors found that both the motor domain and the tail of KLP-12 are necessary to precisely control axon length in C. elegans. The authors showed that a minimal dimer of KLP-12 is motile along the microtubule lattice and reduces microtubule growth rate in vitro; further biochemistry assay demonstrated that the KLP-12 motor domain can similarly bind the microtubule lattice and free tubulin. The authors then solved the crystal structure of KLP-12 motor domain in complex with tubulin and compared their structure data with that of Kif5B (a motile kinesin that does not depolymerize microtubules) and Kif2C (not actively motile but depolymerizes microtubules). They found that the structure of KLP-12 is more similar to that of Kif5B than that of Kif2C, whereas the curvature of tubulin in complex with KLP-12 is between the curvatures of tubulin in complex with Kif5B and Kif2C. The high-resolution structural data from this study suggest how kinesin-4 can be motile along the microtubule lattice and at the same time stop the microtubule dynamics at its plus end; the mild effect of KLP-12 on protofilament bending may be crucial in enabling the inhibition of both the polymerization and depolymerization of the microtubules.

Overall, this is a very nice study, although some aspects of data analysis or interpretation need to be extended or clarified.

1) Microtubule dynamics may be inhibited by reducing growth rate, inducing pausing, or altering catastrophe. To make their results more solid, the authors should examine whether KLP-12 impacts microtubule pausing and/or catastrophe. Such additional metrics may help strengthen the results and further the insight into the role of tubulin curvature in microtubule dynamics.

2) Structural comparison may be sensitive to the resolution of protein structures that are compared. The authors solved the crystal structure of KLP-12 at a resolution of 2.9 A, which is different from that of Kif4, Kif5B, or Kif2C from previous structure studies (1.7, 3.2, and 3.2 A). The values of root-mean-square distance between protein structures tend to increase if the two proteins that are being compared have been resolved at different resolutions. To strengthen their structural comparison results, the authors should account for the effect of different crystallographic resolutions on their root-mean-square distance evaluations.

3) Structural comparison may also be sensitive to what the proteins are in complex with. The authors solved the structure of KLP-12 that is in complex with GTP-tubulin, which may be different from the structure of KLP-12 that is free of tubulin, or in complex with GDP-tubulin. Previous studies had solved the structure of Kif4 which is free of tubulin (Chang et al 2013), and the structures of Kif5B (Gigant et al 2013) and Kif2C in the presence of GDP (Wang et al 2017). To strengthen their results, the authors should clarify how these differences between the previous and the current structural studies impact their structural comparison results.

Reviewer #3 (Public Review):

The authors study kinesin-4 KLP-12 using in vivo mutants and reconstitution of microtubule dynamics in vitro and show that KLP-12 prevents microtubule polymerisation. The authors then explain these observations with a crystal structure of KLP-12 motor domain in complex with a tubulin dimer. Using this structure and by comparing it to kinesin-1 KIF5B which binds straight tubulin dimers and kinesin-13 KIF2C which depolymerizes microtubules, they show how KLP-12 bends the tubulin dimer and explain how this bending mechanism can prevent polymerization.

Strengths:

The crystal structure of the motor domain in complex with a tubulin dimer adds a precious new structure of a motor bound to a tubulin dimer in a new conformation. The comparison with the structures of kinesin-1 KIF5B and kinesin-13 KIF2C also bound to a tubulin dimer is very thorough and convincing. The conserved residues mediating the interaction with tubulin are highlighted. This study adds a new type of curvature induced by a motor protein that influences microtubule dynamics. This work adds to the knowledge of the regulation of microtubule dynamics by microtubule motors.

Weaknesses:

Overall, the results support the conclusions. However, more analyses could be done to strengthen the authors' claims.<br /> The authors start the study using mutants of full-length KLP-12 that they study in vivo in C. elegans. It is however unclear which mutations were made and what their predicted effects on the structure/function of the protein are.<br /> In Figure 2, the dynamic microtubule assays show that a truncated construct of KLP-12 reduces the microtubule growth rate. However, the authors do not show whether KLP-12 has an effect on other parameters of microtubule dynamics thereby limiting the authors' claims.

Reviewer #1 (Public Review):

In this manuscript, the authors uncover a role for Hh in specifying identities of lamina neurons. They find that Hh, secreted by the photoreceptor neurons, forms a gradient along the developing lamina columns. This gradient is reflected in a gradient of Hh activity in the lamina precursors. The authors then use genetic manipulations to titrate the levels of Hh and find that L1-4 identities are specified at high Hh levels and L5 at low. Thus, like in the vertebrate spinal cord, the authors find that Hh acts like a morphogen to specify different neuronal identities at different concentrations.

Reviewer #2 (Public Review):

The authors' demonstration of a gradient of Hh is only partially convincing. Their data clearly show the presence of Hh in the distal but not proximal lamina, but it is not clear from Fig. 2C whether there is a significant difference in the levels experienced by the precursors of L1, L4 and L5. They have also found significant effects of complete loss or full activation of Hh signaling on the most distally and proximally located cell types. However, the effect of intermediate levels of Hh signaling on the medially located cell types is less clear. They obtain these intermediate levels by inactivating a temperature-sensitive allele of hh for different lengths of time, leaving open the possibility that distinct cell fates are determined at different developmental times, and they do not show any conditions that significantly increase the numbers of L1 or L4 neurons, cell types that are predicted to be specified by intermediate Hh levels. In addition, the authors define cell fates using combinations of only three transcription factor markers, leaving it uncertain whether Hh signaling indeed controls cell identities, or simply the expression of these transcription factors.

Reviewer #3 (Public Review):

Bostock and Fernandes present a novel role for the conserved Hedgehog (Hh) signaling pathway in specifying neuronal fate in the developing lamina of the Drosophila visual system. The authors apply straightforward, yet elegant genetics to demonstrate that high levels of Hh signaling (loss of the inhibitory ptc receptor) lead to distal lamina neuronal fate, with more L2/3 neurons and fewer L5 neurons. In contrast, lower levels of Hh signaling (either through reduced Hh itself or the downstream transcription factor Ci) lead to more proximal neuronal fates with reduced numbers of lamina neurons in total. By analyzing the expression pattern of an endogenously-expressed Hh:GFP fusion protein, the authors suggest that the Hh signal itself comes from the photoreceptors, and is faintly expressed in the axons as they reach the lamina in a distal to proximal gradient. A similar gradient signaling mechanism is a well-known role of the Hh ortholog, Sonic hedgehog (Shh), for controlling neuronal development in the vertebrate neural tube; however, this is the first time such a mechanism has been shown to play a role in Drosophila. Overall, this paper was well-written and the data generally support the authors' key claims, though there are a few minor places where the claims could be strengthened.

1) The authors use a combination of genetic approaches to show that the Hh signaling pathway is involved in patterning the lamina. These data appear to be strong and convincing, though it could be even stronger with a quantification of the effects of ptc and smo mutant clones shown. However, one of the points that lacks quite as much support is about the origin of Hh, and the gradient of distribution within the lamina. The Hh::GFP fusion protein does seem to indicate that Hh is expressed in the photoreceptors, but as the authors even pointed out, it is unclear whether the localized pattern is intracellular Hh, secreted Hh, or both. Secreted proteins are much harder to localize and can be more easily lost in staining processes compared to intracellular protein, so the actual distribution of Hh could be different in vivo. Furthermore, while ptc activity is low in L5 neurons based on ptc-LacZ expression, ptc activity seems to be strong just below the lamina near the L5 neurons, which could indicate a potential alternative source of Hh from below, or at least a higher Hh activity in this region. This could mean that it's the amount of ptc rather than the distribution of Hh itself that leads to differential specification.

2) Additionally, while the Hh titration experiment is intriguing and clever, It's not just that the levels of Hh have been changed in that case, but also the timing of when the Hh levels are reduced. Given that Hh is known to disrupt early lamina development, this could play a potentially confounding role.

Reviewer #1 (Public Review):

This is a nice biophysical study to show that the SWR1 complex can diffuse on DNA in one dimension and is blocked by nucleosomes. Diffusion is stimulated by ATP but does not require ATP hydrolysis distinguishing SWR1 movement from that of other chromatin remodelers.

The work is well done and convincing. It describes a relatively small aspect of SWR1 function, somewhat limiting the broader impact of the study.

Reviewer #2 (Public Review):

This manuscript provides exciting and timely new insight into the target search mechanism of SWR1, with fundamentally important implications for other remodelers. The authors use extremely elegant single-molecule approaches (TIRF-based fluorescence microscopy and optical trapping in combination with confocal microscopy) to study the interaction of SWR1 with DNA. This study provides the first conclusive demonstration that SWR1 undergoes 1D diffusion along DNA, which plays an important role in finding the correct nucleosomal substrate in vivo by guiding SWR1 molecules that bind to nucleosome-depleted regions towards flanking nucleosomes.

The authors demonstrate that the Swc2 DNA-binding domain of SWR1 alone can diffuse along DNA, indicating an important role in the target search mechanism. Interestingly, a significant effect of the nucleotide state on the diffusion of the complete SWR1 complex suggests a key role of the helicase subunit Swr1 in this process, which presents an exciting target for future research.

The authors have also analyzed the effects of Cas9 barriers and nucleosomes on the SWR1 diffusion along DNA. The fact that crossing the Cas9 barrier was observed very rarely argues in favor of the sliding mechanism for SWR1 diffusion. However, the diffusion coefficient of SWR1 significantly increases with increasing monovalent salt concentration, which is a hallmark of hopping-mediated diffusion. For that reason, SWR1 diffusion likely occurs through a combination of hopping and sliding.

SWR1 diffusion seems to be substantially restricted in the presence of nucleosomes, but the interpretation of the data is limited by the fact that (unlike the Cas9 case) the authors used unlabeled nucleosomes. Nevertheless, these data open up exciting new avenues for future research.

The manuscript is very well written, methodologically impressive, and the data are presented in a clear and efficient manner. The conclusions are strongly supported by the data and are of outstanding interest to the field of chromating biology. This manuscript will undoubtedly spark future research into the target search mechanisms of SWR1 and other remodelers and chromatin-associated proteins.

Reviewer #3 (Public Review):

In this manuscript the authors set out to determine how the SWR1 chromatin remodelling complex interacts with DNA. This was achieved by monitoring the diffusive motion of individual fluorescently labelled complexes along DNA.

It was first observed that the rate of association and dissociation of complexes from DNA was affected by the length of the DNA fragment.

It is concluded from measurements of on and off rates that SWR1 is primarily affected by the rate of association. The authors propose that this could underpin a mechanism that facilitates the enrichment of complexes at regions where large expanses of DNA are exposed.

Diffusive motion of SWR1 complexes is found to be modulated by nucleotide binding, but not to require ongoing ATP hydrolysis. This is an interesting observation that may affect the distribution of other chromatin remodelling enzymes.

The diffusive motion of SWR1 complexes is observed to be limited by the presence of bound DNA factors including Cas9 bound to DNA and nucleosomes. The authors propose that the relatively long region of DNA adjacent to nucleosomes at transcriptional start sites contributes to the targeting the activity of SWR1 complexes to +1 nucleosomes.

Reviewer #3 (Public Review):

The manuscript prepared by the teams of Sarah Buhrlage and Peter Sorger describes a systematic bioinformatics approach to report on the therapeutic potential of the family of deubiquitylating enzymes (DUBs).

DUBs have attracted recent attention, not only in terms of progress in understanding their biology, but also as drug targets for a variety of human disease conditions, such as cancer, neurodegeneration and immune disorders. Therefore, a comprehensive evaluation of their potential as key modulators in human diseases is timely.

The authors have collected available public data, in combination with some selected experiments, to create a 'DUB knowledge base' including function, CRISPR library screens for DUB essentiality (DepMap), co-dependent genes, DUB-protein interaction networks and substrates.

DUBs reflect a relevant family of enzymes, and one of their hallmarks is the relatively low level of critical mutations in humans. The fact that many DUB KO mice models show lethality in early development stages (e.g. 20 DUBs out of 82 with complete penetrance mentioned by the authors) is consistent with this observation.

Inherent to covering a broad range of information and touching on many aspects of DUB biology, each piece of information in the paper appears somewhat shallow. In aggregate, though, this study represents one of the largest assemblies of available information on DUBs compiled in one resource, reflecting a useful contribution to the field.

Reviewer #1 (Public Review):

Small, circular protein clamps bind to DNA either at a 3'-recessed ssDNA/dsDNA junction (PCNA clamp) or a 5'-recessed ssDNA/dsDNA junction (9:1:1 clamp). Replication Factor C (RFC) has been known for many years to play a role in DNA replication by loading PCNA onto 3'-recessed ssDNA/dsDNA junction DNAs. But RFC is also known to function in the repair of DNA with single-strand gaps or even single DNA nicks by loading PCNA, which then recruits other proteins to repair the gap or nick.<br /> The current paper reports the structures of a number of RFC-PCNA-DNA complexes using DNAs with either a 3'-recessed ssDNA/dsDNA junction or a 5'-recessed ssDNA/dsDNA junction. The data show clearly that RFC can bind both DNAs, loading PCNA onto the 3'-recessed ssDNA/dsDNA junction and binding at a second site the DNA with the 5'-recessed ssDNA/dsDNA junction. These data support previous studies that show that RFC can play a role in the repair of DNA lesions on gapped DNA. The studies, while substantially confirmatory of previous results, nevertheless show a definitive structure of the interaction of RFC/PCNA with gapped or nicked DNAs and as such add significantly to understanding mechanisms of DNA repair.

Reviewer #2 (Public Review):

This review is carried out with the caveat that I am not a structural biologist and therefore, cannot judge the correctness of the structures presented in this paper. The paper presents structures of yeast RFC-ATPgammaS with DNA and PCNA in both the open and closed forms. The RFC clamp loader aspects of the study, i.e. complexes with PCNA and 3'-junction DNA and with ATPgammaS, build on previous clamp-clamp loader studies, and it closely resembles a cryoEM study by the Kelch group.

The novelty of the paper lies in the analysis of the Rfc1 N-terminal BRCT domain, and its binding to 5'-junction DNA. And herein also lies the major concern that I have with the study. Biochemical studies from several labs have shown that the BRCT domain binds with a very high preference to 5'-junctions with a 5'-phosphate. Yet, this study was carried out with DNA substrates that lacked the 5'-phosphate. Two structures are obtained (RFC-3'DNA1-5'DNA2 and PCNA-RFC-3'DNA1-5'DNA2) that show binding of the 5'-junction DNA to the BRCT domain, yet the 5'-junction itself appears not to be engaged in the structure. Without an evaluation of this issue, the importance of this study remains undefined.

The authors provide additional experiments showing that RFC has a preference for gapped DNA structures. They propose hypothetical models for processes in which gap binding might regulate the execution of these processes, but they do not test these models in yeast. A repair function for the BRCT should be readily testable in yeast, and so should be the phenotype of BRCT point mutations that abrogate DNA interactions.

Reviewer #3 (Public Review):

Sliding clamps are closed protein rings (dimeric or trimeric) that encircle DNA and enable/mediate/stimulate DNA synthesis as well as a variety of other DNA modifying enzymatic reactions. Loading of sliding clamps onto DNA requires the activity of the sliding clamp loader, a heteropentameric AAA+ ensemble that uses the energy of ATP binding and hydrolysis to open the clamp, escort DNA into the opened clamp, and release the clamp for self-closure on DNA. The structure and function of sliding clamps and clamp loaders are conserved throughout evolution, albeit with significant differences in molecular mechanisms.

Five distinct subunits (RFC1, RFC2, RFC3, RFC4, and RFC5) assemble into the eukaryotic RFC clamp loader. The RFC subunits are structurally related; each feature at least three domains; two of these domains fold into the AAA module (termed AAA-ATP and AAA-lid). The third RFC domain is a helical bundle that combines with related domains from other RFC subunits to assemble into the so-termed RFC collar. The eukaryotic sliding clamp is a homotrimer of PCNA. The RFC clamp loader loads the PCNA ring onto 3' recessed primer-template junctions. Unique to eukaryotes is a series of RFC-like complexes (RLCs) that substitute RFC1 for another subunit to create a new entity with distinct properties. One RLC is the Rad24 clamp loader for RFC1 to create an entity that loses its ability to bind to 3' recessed DNA and PCNA but gains the property of binding to 5' recessed DNA and the 911 clamp.

Our understanding of the structure and function of clamp/clamp loaders, and especially the eukaryotic loaders, owes much to a series of thoughtful structural, biochemical, and genetic studies over the past three decades. Recently, Kelch and coworkers produced a series of structures of yeast RFC bound to PCNA and primer-template DNA (eLife, 2022). These structures show, inter alia, the details of the primer-template DNA within the loader and with the dsDNA portion of the DNA within the PCNA ring. In addition, Remus, Hite and co-workers and O'Donnell/Li have also submitted Bioarxiv preprints that describe analyses of the Rad24 clamp loader bound to the 911 clamp. Notably, the Rad24 loader appears to exhibit a novel binding mode. The 5' recessed DNA in the Rad24 loader is not found within the loader and the clamp, but 'above' (in a specific reference pose) the 911 ring.

The finding that the Rad24 loader acquires the capacity to bind DNA above the ring by swapping a single subunit (Rad24 for RFC1) prompted Zheng et al to ask whether this property is unique to the Rad24 loader or does the RFC loader also harbors this property. Astonishingly, the answer is likely: yes.

The authors note prior biochemical evidence suggesting that the picture provided by prior structural biology of RFC was incomplete. Susan Hardin and coworkers (1998) and Gregg Siegel and coworkers (2006/2010) had investigated the BRCT domain found at the N-terminus of the RFC1 subunit (Drosophila and Human) and had found that, in isolation, this domain bound to one DNA molecule with a preference for a recessed 5' DNA structure. The finding that RFC had binding sites for 3' and 5' recessed DNA was not accommodated in the extant crystal and EM structures.

This manuscript encompasses the following studies, experiments, and findings:

1) 5 cryo-EM derived models:

a. RFC with DNA in the loader (3'-DNA1) at 3.3 Å;

b. RFC with two DNA molecules (5'DNA2) at 3.3 Å;

c. RFC bound to the closed planar PCNA ring, 3' DNA (RFC−closed PCNA−DNA1) at 3.3 Å;

d. RFC bound to the open PCNA (with a 14 Å opening) ring, with 3' DNA (RFC−open PCNA−DNA1) at 3.4 Å;

e. RFC bound to the closed PCNA ring with the 3'DNA and the 5' DNA and the 5' DNA (3.1 Å) featuring a highly ordered model of the BRCT domain at the amino terminus of RFC1 RFC−3′-DNA1−5′-DNA2−PCNA (the BRCT domain had never been visualized in any RFC structure until now).

The cryo-EM analyses that included DNA were carried out with a DNA oligo with both 3' and 5' recessed ends. However, in none of the above cryo-EM analyses was the DNA visualized in its entirety.

The cryo-EM analyses in this work are of excellent quality as reflected in Supplementary Table 1 and the PDB validation reports.

The main novel finding of the above structures is the presence in the RFC loader of a second binding site for DNA. This second DNA site is located above the PCNA ring, with the dsDNA segment resting on the AAA+ ATPase domain and packed again against the AAA-lid domain. In one structure, the dsDNA is also packed against the ordered BRCT domain of RFC1 (RFC-3'DNA1-5'DNA2-PCNA). This work represents the first description of RFC structures bound to two DNA molecules. The finding of a second DNA binding site above the PCNA ring links this work to efforts to understand the structure and function of the Rad24 loader.

From the series of structures, the authors conclude that the 3' DNA binds first in the RFC clamp loader; this binding event leads to a structural change in RFC1 that enables the formation of the second DNA binding site (for the 5' DNA structure). This structural change is like that seen in the Kelch 2022 series of structures.

Left unexplained is why the BRCT domain becomes ordered in the presence of PCNA and the second DNA molecule (RFC−3′-DNA1−5′-DNA2−PCNA) but is not ordered in the structure without PCNA (5'DNA2). Perhaps, the authors could address this.

Zheng et al suggest that the 3' and 5' DNA molecule binds in a manner reminiscent of how a single DNA molecule with a gap might bind. Inspection of the structure suggests that a gap of 7 nucleotides (or larger with extrusion) might be the optimal size. This is to say that the two input DNA molecules bind with the chain directions arranged just so as to enable (virtual) linkage. Ample evidence exists in structural and biochemical studies to conclude how the 3' DNA is situated in the RFC loader chamber. However, no such evidence exists for the second DNA molecule. And, while the proposed virtual linkage scheme makes sense (and other schemes do not), could the authors comment on whether the chain direction for the second DNA molecule could be ascertained directly from the EM maps?

2) Biochemical analysis RFC-PCNA on DNA with nicks and varying length gaps.

a. The authors conclude that RFC binds tightly to all the substrates tested but binds with a two-fold (~15 nM vs ~30 nM) higher affinity for DNA molecules with gaps that have five or more bases.

b. The 5 nucleotide or large gaps compares well with the structural finding.

c. The presence of PCNA in the measurement reveals tighter binding than in its absence, but with the same trend as seen when PCNA was omitted.

d. Analysis of an RFC ensemble whose RFC1 lacks the BRCT domain revealed 2-fold tighter binding (16 nM vs. 32 nM) when BRCT was present than when not.

In view of the extensive set of contacts to DNA mediated by the BRCT domain, it is surprising that there is not a greater difference in Kd between primer-template and gapped DNA structures. Likewise, why does deletion of BRCT hardly change the affinity for DNA?

Supplementary Figure 7 provides the fits to the fluorescence binding data, which were fit to a simple one-site model corrected for non-specific binding. Could the authors provide the equation used? Also, are two copies of the primed-DNA template expected to bind to RFC as seen in the cryo-EM structure. If so, would it be appropriate for the binding data to be analyzed with a two-site model?

3) PCNA loading experiments on DNA structures harboring 10 or 50 nucleotide gaps (without and with RPA coating).

a. Measurements of loading efficiencies on the above DNA substrates showed a higher efficiency of loading when both primer #1 and primer #2 are included, in comparison to measurements with primer #1 alone.

Taken together, the structural and biochemical data point to the possibility that two DNA molecules, or gapped DNA structures, could be involved in the RFC loading reaction.

The authors then discuss their findings in the broader context of DNA repair and DNA replication.

Reviewer #1 (Public Review):

Here the authors studied the function of the linker domain of syntaxin 1 (the relatively short stretch connecting the SNARE domain with the transmembrane domain) as well as the possible role of palmitoylation by (i) elongating the linker at two different positions by inserting three additional amino acids (GSG), (ii) by substituting individual basic residues with glutamate residues in the basic cluster directly upstream of the TMD, and (iii) by substituting the two adjacent cysteine residues in the middle of the TMD with valines. The results are rather complex, with different effects on spontaneous and calcium-evoked release dependent on the position of the exchanges or insertions. A major part of the manuscript deals with the role of cysteine palmitoylation in the TMD, which intriguingly appears to be prevented by one of the K-E substitutions in the linker region (K260E). The authors also carry out some experiments with Syntaxin 1/Syntaxin 3B chimeras as well as some point mutations in Syx3. While wt Syx3B does not rescue release, converting a glutamate to a lysine residue in the polybasic stretch (i.e. rendering it more similar to Syx1) rescued both spontaneous and evoked release. Thus, one of the main findings is that palmitoylation is essential for spontaneous vesicle release: it is abolished when palmitoylation is blocked, either by direct replacement of the cysteines or indirectly by the K260E substitution.

Reviewer #2 (Public Review):

In this study, Vardar and colleagues demonstrate that juxtamembrane domain (JMD) and transmembrane domain (TMD) of syntaxin play critical roles in mediating neurotransmitter release by employing loss-of-function mutant forms of syntaxin 1A as well as gain-of-function mutant forms of syntaxin 3B/A. Only 3 residues (GSG) insertion in the JMD of syntaxin 1A altered neurotransmitter release in a location-dependent manner. In particular, K260 residue in the JMD of syntaxin 1A was important for the palmitoylation of C271/C272 residues in the TMD of syntaxin 1A. The neurotransmitter release that is mediated by palmitoylation-deficient syntaxin 1A significantly decreased Pvr (%) and mEPSC frequency. Therefore, the authors concluded that both JMD and TMD of syntaxin play important roles in mediating neurotransmitter release.

Reviewer #3 (Public Review):

Using a detailed mutational analysis of the SNARE protein syntaxin 1, Rosenmund and colleagues addressed the question of whether the juxtamembrane domain (JMD) and transmembrane domain (TMD) of the protein have an effect on neurotransmitter release from hippocampal neurons. The results show that insertions into the juxtamembrane domain of syntaxin strongly reduce synaptic strength, an observation that is consistent with previous studies on the mode of action of vesicular SNARE proteins, such as synaptobrevin. Furthermore, the authors show that some but not all charge reversal mutations in the JMD of syntaxin (e.g. K256, K260 and K263) reduce the pool of releasable vesicles while affecting palmitoylation of the protein. Palmitoylation mutants (C/V exchange), on the other hand, have little effect on evoked transmitter release but reduce spontaneous transmitter release, leading the authors to speculate that palmitoylation reduces the energy barrier of the actual fusion process.

Taken together, the findings suggest that the JMD and TMD of syntaxin 1 play an important yet unrecognized role in the fusion of small synaptic vesicles.

Reviewer #1 (Public Review):

Bisch-Knaden et al. investigated how the olfactory system of hawkmoths (Manduca sexta) could distinguish behaviorally relevant odor sources (nectar food sources and oviposition sites) from those which are irrelevant in a natural environment. This is of particular interest for the field of naturalistic insect-plant interactions. Technically and intellectually, the experiments are well-conducted and suited to understand how ecologically relevant naturally-occurring signals are processed in the brain of animals to produce adaptive behavior.

The authors collect volatiles from various (behaviorally relevant and irrelevant) plant sources in Southern Arizona (US), a natural habitat of M. sexta. They describe in detail the chemical composition and bioactivity of two floral sources which are important nectar resources for the moth, the jimsonweed Datura wrightii (which is also used by the moths for oviposition), and the agave species Agave palmieri, which is used only for feeding. Much of this has been described in a series of papers published between 2008-2014 (few of which are cited and/or discussed), which described the chemical composition and bioactivity of components in the floral odor of D. wrightii and A. palmieri, and how those two nectar sources differentially activate neurons in the primary olfactory centers of the brain. How the brain of moths could identify a behaviorally relevant odor bouquet (such as the floral scent of D. wrightii) in an environment of irrelevant odors (e.g. creosote bush) has also been previously examined.

The authors do an impressive work imaging activity in the primary olfactory centers, the ALs, in a model system for which neuronal markers that could facilitate this are not available, and understandable, they can only image accessible/identifiable glomeruli (ca. one third of all glomeruli). Hence, their conclusions necessarily apply only to those glomeruli imaged, and hence it cannot be concluded that vegetative host-plant volatiles are weak activators, because two-thirds of the glomeruli could not be imaged. Various previous reports used electrophysiological recordings in this brain region, which may be more sensitive to detect bioactivity, including inhibitory responses and correlations in the temporal domain. Also, previous work highly suggests that females rely on D. wrightii floral odors to find oviposition sites and therefore, the reported finding that vegetative odors are not strong activators may not be relevant in this case. Electrophysiological recordings from antennal lobe female-specific neurons with selectivity for certain D. wrightii floral odors further support this idea.

Reviewer #2 (Public Review):

Studying the olfactory encoding strategies of moths using ecologically relevant odors collected from the actual habitat is remarkably ambitious. The manuscript is well written and the design of the experiment is clear.

The authors collected the nocturnal emission of 16 plant species and systematically analyzed the constitution of the headspace of these plants. Then, they used GC-EAD to identify the active compounds and found 77 EAD-active ones in total. Subsequently, they used in vivo calcium imaging to study the representation of these active compounds in antennal lobes. A weakness is the absence of behavioral data.

Reviewer #3 (Public Review):

The authors' used state of the art approaches to analyse the volatiles emitted by plants in the natural environment of the hawkmoth Manduca sexta, which play different roles in their biology. They then investigated antennal detection of the identified compounds, as well as the representation of odour bouquets of flowering plants (used for feeding), larval host plants (used for oviposition), and surrounding non-host plants. They analysed their data with sophisticated methods and illustrate their results with highly comprehensive figures, which make the results easy to catch for the reader. The results show that flowering plants used for nectar feeding emit large amounts of volatiles and the identified compounds are equally well detected by the antennae and similarly represented within the antennal lobe in virgin and mated females. Larval host plants emit surprisingly small amounts of volatiles, but M. sexta antennae are still detecting characteristic compounds and more importantly, odour bouquets of these plants elicit specific activation patterns in the antennal lobe in very few glomeruli and this representation changes after mating. Interestingly, odour bouquets of host plants of sympatric hawkmoth species are highly represented within the antennal lobe and this representation takes even more weight in mated females. Lastly the representation of odour bouquets of non-host (background) plants, rather elaborated in virgin females, decreases after mating. All data are very well presented and illustrated. In the discussion, the results are very well put into the context of earlier studies, putting together knowledge on the ecology of hawkmoths, behavioural studies, as well as detection and central processing of plant volatiles and its plasticity. The conclusions drawn, insisting on the ecological adaptation of the female moth olfactory system in order to recognize and discriminate crucial information for feeding and host plant localization as a function of the physiological state, are sound and contribute an important piece of information to our knowledge on neural mechanisms underlying insect behaviour in a highly complex natural environment.

Reviewer #1 (Public Review):

The manuscript contrasts the role of non-specific PAG neurons to PAG CCK+ neurons in threat perception using a variety of low and high threat tasks including open field, elevated pus maze, a latency to enter a dark box assay, real-time place preference task, live predatory exposure, fear conditioning. CCK neuronal activity in the PAG was examined used gain and loss of function approaches using optogenetics, chemogenetics and fiber photometry. The data show that CCK PAG neurons have a dissociable function to the global PAG neuronal response in threatening situations with CCK neurons consistently enhancing flight to safety. Specifically, activation of CCK PAG neurons decreased time spend in the centre of an open field, increased speed and number of corner entries, reduced latency to enter a dark box, reduced time in a chamber paired with CCK-activation, reduced time spend in the open arms in the elevated plus maze, increasing pupil dilation, enhanc avoidance of a live predator, and CCK PAG inhibition having the opposite effect to that of activation. Fiber photometry data showed a ramping up upon initiation to escape a live predator, as well as a sustained activity post escape that increased with greater distance from the predator.

The experiments are well executed, the data are clear and convincing. The approach is thorough, and appropriate. The insight is significant and of value beyond the study of threat perception.

No major weaknesses were detected other than the lack of statistical reporting. The conclusion regarding a lack of role for PAG CCK neurons in fear learning should be dampened as this would require a more thorough investigation.

Reviewer #2 (Public Review):

This manuscript investigates the role of CCK-releasing neurons in ventral regions of the PAG in mediating defensive responses. While prior work in the field has identified columnar organization of mediating defensive responding (i.e., ventral versus dorsal PAG are implicated in freezing and flight, respectively), this work uses several approaches to parse the role of specific cell ensembles in defensive responding.

Through a series of expertly designed studies, the authors have provided compelling evidence that while there are many studies evidencing a role for l/vlPAG in freezing behavior, there may be a more nuanced role for l/vlPAG when considering cell-specific populations. Specifically, CCK neurons in l/vlPAG may drive organized escape/ avoidance of threat. Further, activation patterns and behaviors resulting from l/vlPAG manipulation seem to oppose those observed when interrogating l/vlPAG in a non cell type specific manner. These findings underscore the importance of not only neuroanatomical designation of function, but also molecular identification to fully understand the role of defensive response systems.

The identification of a sparse population of CCK cells that seem to oppose canonical role for ventral regions of PAG in defensive responding will be of importance to the field. However, there are some caveats that could be made more clear. For example, if l/vlPAG CCK neurons initiate escape to safety, it is not fully clear why these cells exhibit greater activity in safe versus threatening locations. One might expect greater activation upon initial escape if this population is the driving force behind the behavior. This raises the possibility that l/vlPAG CCK cells coordinate behavioral responses with another population of cells, such as one in the more dorsal regions described by many others to be important for escape and defensive flight. Addressing this would increase the value of the findings presented.

Reviewer #3 (Public Review):

A major role of the PAG in mediating defensive reactions is supported by early microinjection and lesion studies as well as more recent circuit neuroscience studies. By showing that CCK neuron activation promoted flight to a burrow, and a global preference for lower threat areas on one hand, and that their activity was correlated with distance to threat on the other, the present study adds to our knowledge of functionally specific circuit elements within the PAG that control different defensive behaviors. Importantly, some of the findings appear contradictory at first glance, and would need to be reconciled via further analyses and/or conceptualization.

The authors systematically performed similar experiments not only with a focus on the l/vlPAG CCK neurons, but also on the global neuronal population of the same area. This second aspect mainly recapitulates earlier findings, but most importantly, allows for a direct comparison between a molecularly defined population and the overall neuronal population. This critically highlights that although canonical delineations of the anatomical subregions were adopted based on some neurochemical markers, they do not present an absolute functional and molecular homogeneity, and therefore emphazises the importance of using specific subpopulations to draw finer conclusions.

The study employs several behavioural paradigms, which are, in the case of the rat exposure test, highly relevant from an ethological point of view, even though conceptual flaws might be present in some aspects of the others.

The experiments, incorporating state-of-the-are techniques are conducted rigorously, and the results are described thoroughly and without overreach. Some analytical approaches need to be described better. Some general points feel like they are not interpreted and conceptualized consequentially enough, including the seemingly contradictory findings. A global picture uniting the different results is missing, which leaves some parts disconnected, yet the data might offer enough elements to develop on that side. The results are well discussed on a higher level and integrated with fitting references for the different aspects of the study, however, the discussion of individual results should be enhanced.

The main weakness of the study is that the pertubational and observational approaches are not easily reconciled. While this is a common phenomenon in circuit research, it hampers a conclusive attribution of the functional role of PAG CCK cells and is in contrast to the study's major goal. This discrepancy needs to be resolved both, experimentally and conceptually.

Joint Public Review:

Lysosome-localized PI(3,5)P2, as well as lysosomal H+ and Cl-, are known to regulate lysosomal degradation, catabolite export, membrane trafficking (fusion/fission), and osmotic swelling/condensation, but the underlying mechanisms are not clear. CLC-7/Ostm1 is a lysosomal and osteoclast resorption lacuna localized chloride / proton antiporter. In osteoclasts it is essential for acid secretion and bone resorption. In lysosomes, the antiporter has been proposed to provide counter ions for efficient acidification and/or to raise luminal chloride concentration exploiting the proton gradient. Several previous lines of evidence have suggested a role of PI(3,5)P2 in CLC-7/Ostm1 regulation: i) plant vacuolar CLCs are potently inhibited by PI(3,5)P2 in the submicromolar range (plant vacuoles are somewhat similar to lsyosomes); ii) inhibition of the PI(3,5)P2 producing PIKFYVE kinase leads to lysosomal enlargement that is largely inhibited by CLC-7/Ostm1 knock-out; iii) PI3P like molecules have been found to be tightly bound to CLC-7/Ostm1 in 3D structures.

Leray et al. enhance the knowledge in these matters in three important aspects. i) In cells, they show that PIKFYVE inhibition leads to a hyperacidification of lysosomes (in addition to lysosome enlargement) in a manner that is largely dependent on the presence of CLC-7/Ostm1 (this finding is in contrast to earlier reports from another group); ii) In patch-clamp recordings of plasma-membrane targets CLC-7, they show that application of relatively high concentrations of PI(3,5)P2 (50 µM) via the measuring patch pipette leads to a ~40% reduction of currents; iii) In patch-clamp recordings, the PI(3,5)P2 inhibition is completely absent with the Y715C mutant, which was previously shown to cause hyperacidification of lysosomes; moreover, Y715 is in reasonable distance to the PIP3 binding site seen in 3D structures.

The manuscript is well written, and the results and statistical analyses are clearly shown. The results potentially provide significant and important steps forward in the understanding of the role of CLC-7/Ostm1 in lysosomal biology, with implications for basic cellular processes including autophagy, and for the role of lysosomes in neurodegenerative diseases. However, the conclusion that at baseline CLC-7 is not active because it is inhibited by PI(3,5)P2 could be an overstatement because there is no PI(3,5)P2 dose-response in the manuscript and the baseline concentration of PIP2 in lysosomes is not known. In addition, the possible role of chloride accumulation needs to be assessed.

Reviewer #1 (Public Review):

This work provides a different metric for cervical and colorectal cancers screening considering the screens each woman has received (self-reported). Using the traditional screen counts, it was reported that 50-64 years old women have lower screening rates for both cancers compared to all other age ranges. In this work, the authors use the Behavioural Risk Factor Surveillance System to evaluate the screening rates based on what woman has received more than was offered which allowed authors to enrich the understanding of possible predictors for being up-to-date for cervical and colorectal cancers screening. The findings of this work can help to understand better unscreened population and explore which predictors could be useful for promoting uptake of cervical and colorectal cancers screening. The analysis is done with a population sample which allows the results to be extrapolated to the United States.

The weakness of the paper is that the analysis is based on a self-report survey which may not be an accurate method of determining cancer screening rates due to recall. Claim data or medical records may provide a more reliable "gold standard" than self-reports. In general surveys are critical for providing rich information about the individuals and for observations regarding population health and it could help to better understand some measures. However, it is necessary to discuss better that this kind of information may be biased.

For future analysis, it could be useful to perform an analysis where self-report data and claim report information serve as a source of information together, it means to perform an analysis to compare self-reported information with objectively recorded participation in colorectal and cervical cancer screening in the national screening programme in the United States. It will allow to verify whether self-reported ever uptake corresponds with recorded ever uptake among survey respondents.

Reviewer #2 (Public Review):

This manuscript focuses on assessing the percentage of women who are within guidelines for screening for two common cancers - cervical and colorectal cancer (CRC). This area of inquiry has not been examined in many studies and is an area that could lead to interventions to increase adherence. In addition to the importance of the topic, other strengths include the large sample size, the robustness of the data - BRFSS, 2018, the number of covariates available in the dataset, and the implications of estimating prevalence within a national survey.

Weaknesses center around the use of jargon, e.g., women did not choose a screen - this is self-reported behavior; "screens"; inconsistencies - e.g., measures for cervical screening are not consistent (lines 138-141 vs 160-162); incomplete descriptions - e.g., was White Non-Hispanic White; and reporting of results - e.g., "cervical cancer screening was...: vs how it should read - 86% of women reported being UTD with cervical cancer screening...".

The results are presented in descriptive, unadjusted multinomial regressions and multivariate multinomial logistic regression. There are a few problems with this section: 1) the presentation of the data is confusing given all the comparisons - some seem redundant; 2) why are unadjusted results included; and 3) data needs to be included in the text. The issue of correct language when referring to screening persists in this section.

The conclusions in the Discussion are not all supported by the data. For example, if one looks at the data in the Figure, by test, women are 86% and 66% UTD for cervical and CRC screening compared to the HP 2030 goals of 84% and 74% respectively. One can't use the "dual" screening rate of 59% to compare to single screen that the HP 2030 goals were derived from. The first conclusion again is using different jargon - by-woman analysis. The second conclusion - age - is not well explained. The explanation about the physician level influencing decision also does not make sense given the data in this study. Patient level does not discuss options for CRC screening. The discussion of the COVID-19 pandemic is not relevant to the results of this analysis. There are several statements about the use of HPV self-test kits - these are not yet approved in the US, and other hypotheses stated are not supported based on data from this analysis. Lastly, the conclusions do not discuss what needs to be done to follow-up on this study.

In summary, the idea the investigators are trying to examine is important but attention to details, methods, wording, and conclusions would improve this paper and present a more complete message.

Reviewer #3 (Public Review):

Strengths:<br /> 1) The behavioral risk factor surveillance system has a broad generalizable population<br /> 2) Known sociodemographic risk factors factored into appropriate dual screening<br /> 3) Data reiterated the need for new strategies for reach and access for cancer prevention, particularly for those living in poverty or with low health literacy<br /> Weaknesses:<br /> 1) The CRC testing stated is not the 'routine' recommendations. Also, since it is self-reported, a patient might have under-reported obtaining a Pap or HPV test when she only received a speculum exam<br /> 2) Significant difference between those that were identified and those included in eligibility suggesting elements of selection bias and potential generalizability of respondents to the population<br /> 3) Data does not take into account the payer mix and potential for health insurance limitations of access

Reviewer #3 (Public Review):

This work investigates the effects of growing annual crops for two generations in the same or a different social environment (coexistence history being single plant, monoculture, mixture of species) on measures of competition and yield. This is a very interesting and timely topic; diversification in agriculture is a promising means to help reduce the global decline of biodiversity. The experimental setup appears to be sound and the experiment is carefully executed (though this is not my area of expertise). The authors conclude that growing plants in the same community as their parents did reduces competition.

However, I am not convinced by the interpretation of the results. Particularly the results for competition versus overall yield are in conflict. This discrepancy is not properly discussed and is largely ignored in the conclusions. Hence, I doubt whether the results support the conclusions.

My most important comment relates to the discrepancy between results for total yield (Figure 3b) versus those for competition (Figure 2a) and for net biodiversity effect (Figure 3a). Results for all those measures are based on yield records. Figure 2a and 3b (panel fertilizer) show clearly that plants that have the same coexistence history as the tested plants outperform those having a different co-existence history. Figure 3b, however, shows no effect of coexistence history on yield; total yield for Same and Different do not differ. How to reconcile these results? Remarkably, this discrepancy is not discussed at all; the discussion largely ignores the absence of an effect on total yield.

Related to the previous comment, the title includes the phrase "reduces competition". In the manuscript, competition is derived from effects on yield. Still, there is no benefit of the same coexistence history for total yield. This is somewhat misleading.

A second important comment relates to the absence of results from the second year. The Methods section explicitly states that the comparisons made in year 3 (as shown in Figure 2) were also made in the second year (2018; L350-358). However, no results are presented. Why are those results excluded?

A third comment relates to the distinction between competition and facilitation (Equations 3 and 4, and corresponding results), which is artificial and not very meaningful in my opinion. Since RII will never be precisely equal to zero (i.e., the RII=0 category is empty), an increase (decrease) in facilitation must go together with a decrease (increase) in competition, and vice versa. This must be the case since the total of both categories must add up to the number of comparisons made. In other words, if we have a total of N objects, being either apples or pears, then, if we have fewer apples, we must have more pears. (hence, L93-94 is a tautology). I suggest dropping this distinction from the manuscript.

The Discussion seems to ignore some of the results that don't seem to match the "desired" outcome. For example, L178 speaks about niche differentiation as if this was found, but it was not. Same for L200. Similarly, L181 speaks about "the yield benefit", which was not there.

While the manuscript is well written with respect to the language, it is not always easy to follow and absorb. This is partly because the number of traits is large. A table with the traits could help. Also, the writing could be improved to help the reader get the message. For example, when showing results in Figure 2, it could be mentioned from the start that these are relative to single plants, whereas those in Figure 3a are relative to monoculture. This can be found in the methods but should be clear from the Results as well.

Reviewer #1 (Public Review):

In this study, Stephan et al. use experimental data to test whether positive interactions between different crop species strengthen over time (generations) when these species are cultivated in association. Even if this has already been investigated in grassland species, we currently lack experimental data on such questions in crops, which makes the study original and with potentially important agronomic applications. To address the question, the authors designed two types of communities: monocultures and mixtures made from seeds collected on plants that evolved in the same community type in the previous two generations (i.e. mixtures from mixture seeds and monocultures from monoculture seeds), and monocultures and mixtures made from seeds collected on plants that evolved in a different community type in the previous two generations (i.e. mixtures from monoculture seeds and monocultures from mixture seeds). They then used multiple sets of indexes to characterize the magnitude and direction of plant-plant interactions in order to compare communities with different evolutionary histories. Interestingly, the experiment is also replicated across two fertilization treatments. At the individual plant level, the results suggest that facilitation increases and competition decreases for plants grown in the same community type as their progenitors compared to plants grown in a different community type as their progenitors. Community-level analysis, however, shows a different picture: both the total yield of the communities and the relative yield of the mixtures are not affected by the coexistence history of their parents, and the results do not provide evidence for increased complementarity between species that have evolved in mixtures in the previous generations. Finally, the authors show that several aboveground traits have lower variation in communities that evolved in the same community type in the previous generations compared to communities that evolved in a similar community type, which shows phenotypic convergence rather than the expected phenotypic divergence in mixtures. They also report differences in trait means, with for example lower mean leaf dry matter content in communities composed of offspring of plants that were grown in the same community type compared to communities composed of offspring of plants that were grown in a different community type.

The study is based on original and high-quality experimental data. The number of species, communities, and replicates is relevant regarding the research question. It is also very nice to have contrasted environments (fertilized vs unfertilized). All these combinations of factors have been replicated over three consecutive years, which also needs to be acknowledged as an impressive experimental effort.

The statistical analysis is rigorous and successfully accounts for design features when testing the effects of interest. My main criticisms concern, by order of importance, the disconnection between the results and the claims of the paper, some weaknesses in the experimental design, and the clarity of the Materials and Methods.

The main hypothesis of the study, which is that higher facilitation/complementarity should occur in mixtures made from plants that evolved in mixtures compared to mixtures made from plants that evolved in monoculture, is not supported by the results. However, the results are presented in such a way that it seems that this hypothesis is verified. For example, the first index which is used by the author (Relative Intensity Index, RII) shows a significant effect on the treatment of interest (coexistence history). However, this index is not the most relevant to capture facilitation or complementarity effects in multi-species communities, notably because it is computed at the single plant level, and only with three plants per species. The Loreau & Hector partitioning (Net Biodiversity Effect, NBE, partitioned into a Selection Effect, SE, and a Complementarity Effect, CE), which is used a second time, is the gold standard in the field. This is acknowledged by the authors given that they check the validity of RII by measuring its correlation with CE in Fig. S13). Unfortunately, RII and NBE give very different results: the coexistence history of the species has no effect on NBE, and most notably no effect on the CE component. Yet, the authors claim that the coexistence history has an effect on NBE in the fertilized treatment, but we do not have any information supporting the statistical significance of this result (the p-value used to support this claim l. 103 is > 0.05). More generally, several non-significant results are discussed (e.g. l. 100 to 105, l. 136 to 144). The Figures in the main text are also misleading. They show the means ({plus minus} standard error) in the different treatment but do not report statistical significance. Very often, the related boxplots in the Supplementary Information show much fewer differences between the treatments (e.g. Figure 2 vs Fig. S1, Figure 3 vs Figure S3), and the ANOVA tables confirm that these differences are not statistically significant. Overall, the fact that coexistence history has no effect on the total yield, on NBE, and most notably on the CE component, together with the fact that species' traits converge, notably towards taller plants, do not support reduce competition nor higher facilitation in mixtures with a mixture history compared to mixtures with a monoculture history.

The amount of phenotypic and genetic variation within each species at the beginning of the experiment has not been controlled and reported in the study. It seems that inbred lines were chosen for some species (e.g., wheat, oat, or lentil) which means that there was no genetic variation for these species, whereas landraces or open-pollinated varieties were chosen for others (e.g., coriander or camelina). It thus means that the evolutionary potential of the different species was not the same. It would have been more rigorous to choose either only fixed genotypes for all species (inbred lines or hybrids), which would then have evolved under the sole effect of epigenetic changes, or only mixtures of genotypes for all species (either varietal mixtures or open-pollinated varieties), which would then have evolved under natural selection and changes in gene frequency.

Several aspects of the Materials and Methods could be clarified. It is not clear how the different plots and community types were re-allocated each year. This is important to interpret the results, as soil legacy effects could also affect the outcomes of plant-plant interaction. For example, were mixture plots with a "pure" mixture history grown in the same plot from one year to the other, or were plots reshuffled each year? Also, the sowing pattern of the 4-species mixtures is not explained. Was it also alternate rows, as the 2 species mixtures? Was the pattern the same across the different replicates and treatments for a given 4-species mixture? We do not have information on the sowing densities in mixtures plots (was it simply their monoculture densities divided by the number of species?). An important aspect of index computation is also not explained. For example, monoculture yield is used as a reference to compute Relative Yield (RY), and single plant yield is used as a reference to compute RII. There are several ways to compute these reference values, given that there are multiple replicates of monocultures and single plants for a given species. It can be either the value of the closest replicate in the experiment in the same treatment, the average value of all replicates in the same treatment, or a model-derived prediction which accounts for design effects (BLUE or BLUP). In this experiment, monocultures and single plants are also replicated across different evolutionary histories. So, we need to know which type of monoculture plots or single plant plots were used to compute RII and NBE.

Reviewer #2 (Public Review):

The paper offers a very novel experimental framework for assessing how coexistence history could influence intercropping success in agricultural systems. The authors do a very nice job combining the science from multiple fields into a coherent and useful framework. Based on this framework we should conclude that growing crops in polyculture fields for multiple generations will increase the benefits of intercropping for growing food.

However, on the ecological side, there are some weaknesses that need to be addressed:<br /> 1. The introduction and discussion need more context for how co-occurrence can lead to more facilitation. I see how co-occurrence could lead to trait displacement and less niche overlap, so less competition. But what is the facilitation part of this? The introduction doesn't introduce any potential mechanisms for this despite many indications that facilitation could also change as a result of coexistence history.<br /> 2. The authors should think carefully about their use of net effects, RII_facilitation, and RII_competition. It appears to me as though all three are measuring net effects but in some cases facilitation > competition and in other cases competition > facilitation. Even though that's true, it doesn't mean that the indices aren't still measuring net effects. Given that, the authors should temper that language and consider reinterpreting some of their data.<br /> 3. The authors should also give careful consideration to the relative balance of inter vs. intraspecific competition. Many (if not all) of these trends could be indicative of stronger intraspecific competition than interspecific competition. This will need to be considered very carefully.<br /> 4. Have the authors considered separating their data into plots with and without legumes? The strong selection effects with co-occurrence history would also support this. Nitrogen enrichment is one of the most heavily studied facilitation mechanisms and thus this separation might help give insight into the mechanisms operating here.<br /> 5. Overall, a lack of clarity of underlying mechanisms is the greatest weakness of the paper.

Reviewer #4 (Public Review):

In this paper, the authors conducted a multi-year study in which they grew six crop species either in monoculture or mixture to find out whether species could adapt to growing in mixture. They found that there was a shift within species to different strategies for growing in mixture vs. monoculture, which increased the yield. Contrary to expectations, they found convergent trait selection and a reduction in overall trait variation. They discuss this surprising finding in depth and connect it well to previous and ongoing research. The authors conclude that crops that so far are mainly cultivated and bred in monocultures could instead be bred for higher yield in intercropping set-ups (thus mixtures of different crops at the same time in the same place).

This research is original and novel. Previous research had shown similar effects, but for non-crop plant species. Extending those previous findings to agriculture is highly relevant and timely. The experiment was conducted carefully. Not only was total yield measured, but also a series of traits were assessed to find out how the trait space changed over the three years the experiment was conducted. The manuscript is very well written. The abstract summarizes the results and implications of the study very well. The introduction set up the study very well and the discussion is appropriate in length and depth.

Reviewer #1 (Public Review):

Obesity and osteopenia are hallmarks of post-menopause culminating with osteoporosis if not treated with hormone replacement therapy. FSH is a sex hormone that regulates estrogen, however, the rising levels of FSH during pre- and post-menopause are implicated in obesity and osteoporosis The authors find that the FSH blocking antibody reduces body fat in mice on a high-fat diet and induces beige, UCP1-rich adipose tissue. The antibody also increases bone formation in mice to display an anabolic action evident in histomorphometry and an increase in bone mass. This dataset has been reproduced in a different lab in mice that had been ovariectomized and had lost bone. The authors also perform multipronged pharmacokinetic studies using mice with different genetic backgrounds and different technologies for detection of the injected antibody. These studies were coupled with biodistribution studies both in mice and monkeys showing that the antibody reaches the organs of interest. The monkeys were also used for a preliminary safety assessment, and the authors also assessed immunogenicity using human PBMCs. Finally, to facilitate future clinical development, the authors have used traditional biochemical measures combined with a thorough in silico analysis to establish that the antibody can be manufactured.

Reviewer #2 (Public Review):

During the late perimenopause, there is precipitous bone loss, onset of visceral obesity, dysregulated energy balance, and reduced physical activity. These aberrant physiologic changes across the menopausal transition are not fully explained by low estrogen, as estrogen levels are relatively unperturbed, while serum FSH levels rise to maintain estrogen secretion from an otherwise failing ovary. The question has been whether a rising FSH level is a driver for post-menopausal obesity and osteoporosis. The objective of the study is to test whether blocking FSH action will reduce obesity and bone loss in people. Towards this goal, the authors have developed our lead candidate, a first-in-class humanized FSH-blocking antibody, MS-Hu6. Obesity and osteoporosis are major public health problems. These two disorders track together in women across the menopausal transition. The study provided that MS-Hu6 is efficacious, durable and manufacturable, and is therefore poised for future human testing as a multipurpose therapeutic. It is a thorough characterization of MS-Hu6 in vivo efficacy, acute safety in monkeys, and a full evaluation of its pharmacokinetic, pharmacodynamic and biodistribution. This comprehensive analysis of the biology and physicochemistry is a first-in-class, humanized FSH- blocking antibody.

Reviewer #1 (Public Review):

Chamdima Bulumulla et al. report a synthetic 2D-composite nanofilm to visualize the dopamine transmission with sub-cellular resolution, favored temporal properties and quantal sensitivity. This work reveals that the somatodendritic dopamine release originates from the dendrites, including major dendrites, fine dendritic processes and dendritic arbors, but not soma. The dynamics of dendritic release are similar to those of axonal release but with a restricted spatial extent at the release site. By combining post hoc immunofluorescent super-resolution imaging, the authors find dendritic hotspots are enriched with presynaptic active zone protein Bassoon and co-localized with the SNARE complex protein, VAMP2. These data provide new insights into the spatiotemporal dynamics of somatodendritic dopamine release and also cast light on the potential molecular machinery.

Reviewer #2 (Public Review):

In this study, Bulumulla and colleagues explore the use of near-infrared dopamine nanosensors to visualize dopamine release from axons and dendrites. In the original description of this sensor published by the last author, the dopamine nanosensor was used to examine bulk dopamine release in tissue slices. Here, the authors take an innovative approach by applying a thin coat of the nanosensor to coverslips (named DopaFilm). This enables them to image dopamine release from cultured dopaminergic neurons with much higher spatiotemporal resolution.

This is a very exciting study that presents a novel approach to examining dopamine release with spatial precision that is so far unrivaled. The authors identify hotspots for DA release and also provide evidence for DA release in the presence of TTX, suggesting that they can image quantal release. In addition, the results here present the first clear visualization of somatodendritic dopamine release to date. Importantly, whether somatodendritic release genuinely occurs is still a matter of debate - some in the field believe that axonal fibers are the main source of DA released in midbrain VTA and SNc. Therefore, this manuscript presents an excellent study that contributes significantly to our understanding of dopamine release.

Comments:

The authors mention that they did not observe DA release at sites that did not also have bassoon puncta. However, the data in Figures S13A, and B suggests that this statement may be true only to a rough approximation. If possible, the authors should verify this statement by quantifying the DopaFilm signals at bassoon positive and bassoon negative areas.

In Fig 7C, the synaptobrevin2 staining does not seem to overlap well with the MAP2 or TH-GFP staining. Please comment on whether the synaptobrevin staining shown here represents staining in neighboring glutamatergic cells that are present in the co-cultures.<br /> Related to this, did the authors find any dependence of dopamine release here on glutamatergic transmission from cortical neurons? Please comment on this.

In Figure 4, optical stimulation results in DA release and fluorescence increases at multiple hotspots. Interestingly, the change in fluorescence reaches very similar amplitudes across hotspots for each stimulation (compare dF/F at first red symbol across hotspots for example). Does this indicate saturation of the nanosensor? Interestingly, this seems to be true for the third stimulus as well, after depression when the signals are much smaller. By contrast in the dendrites, this doesn't seem to be the case, as shown in Fig S12. Better clarification on this point will inform whether DopaFilm can be used to probe synaptic release properties such as variance, etc. Please comment on this.

Short-term plasticity. The authors suggest that dopamine neurons can sustain robust levels of release with no depletion but do not directly show this. Please provide time courses of DA release both from axons and dendrites during repeated stimulation. Relatedly, data shown in Fig 3I shows multiple stimulations without indicating the interstimulus interval. Please report the interstimulus interval for these experiments. The text mentions 1 stim per 2-3 min, but this is unclear. Lastly, optical stimulations in Figure 4C demonstrate multiple stimulations over time. It would be useful to see this quantified/normalized to the first stimulation.

Kinetics of release measured with DopaFilm. Figures 2B and 2D suggest that dendritic release is fast but the scaling of the traces shown makes it difficult to see onset timing. Please provide measurements of the averaged time-to-peak for both axonal DA release and somatodendritic release. Also, it would be helpful to the reader to discuss how these times compare to the time course of DA release as measured using dLight or GRABDA, carbon fibers and D2 IPSCs.

Reviewer #3 (Public Review):

This manuscript reports a new technology achievement of directly visualizing dopamine release from single synapses and with millisecond time resolution. Dopamine release is usually detected by electrochemical or microanalysis assays, which does not provide spatial or temporal information. Here, the authors utilized a recently developed dopamine nanosensor based on oligonucleotide-functionalized single-wall carbon nanotubes. DopaFilm is a thin layer of these nanosensors whose infrared fluorescence is highly sensitive to dopamine. When dopaminergic neurons were cultured on DopaFilms, local dopamine released from axons, dendrites, or varicosities can be reliably detected by fluorescence imaging of the DopaFilm. This manuscript includes extensive data to support the claim, which is further strengthened by post hoc immunostaining of proteins that are specific to dopaminergic neurons, dendrites, or synapses.

Overall, this is a high-quality work supported by extensive data. The engineering of the nanosensor has been previously reported and has been validated by different research groups. This work makes the nanosensors into two-dimensional DopaFilm to resolve signals from individual synapses. This manuscript shows that DopaFilm affords excellent sensitivity for detecting real-time dopamine release from individual varicosities or synapses. The spatiotemporal dynamics of dopamine release in the dendritic processes of dopaminergic neurons is a poorly understood phenomenon. Therefore, technologies reported in this work would be of interest to future studies of the underlying mechanisms of this process. The conclusions of this paper are well supported by data, but some questions would need to be clarified. For example, the authors showed some Bassoon spots with no dopamine release. Do these silent sites always remain silent? What is the percentage of these 'silent' sites compared to all observed dopamine release events?

Reviewer #1 (Public Review):

The work by Wenzel and colleagues exhaustively studies the network of interactions between MIT-containing proteins with the MIM containing proteins of the ESCRT-III complex. They discover 16 new interactions and at least one unknown factor interacting with ESCRT-III, CAPN7. Several findings are very interesting and provides essential stepping stones on which the community will continue progressing. In particular, the finding that IST1 clusters a very important network of MIT-containing proteins is reinforcing the view that IST1 is an essential factor of abscission, as proposed by the authors in previous papers. Also, that specific interactions between one ESCRT-III-MIM containing subunit and one MIT.containing partner can be disrupted through single point mutations, not affecting other MIT-MIM interactions is very striking and will provide excellent tools for the community to study the physiological role of these interactions in the future. Finally, the authors continue studying the role in cytokinetic abscission of several of these new interactions, in particular between IST1 and KATNA1, SPASTIN and CAPN7. They convincingly show that these co-factors are required for the completion of cytokinetic abscission, and that they are recruited by ESCRT-III subunits at the midbody. Overall, the study is very well conducted, interesting, providing a lot of essential information for the community working on ESCRT-III.

Reviewer #2 (Public Review):

Wenzel et al., present a focussed manuscript describing the many possible combinations of MIT-domain/MIM interactions between ESCRT-III subunits and their MIT-domain containing counterparts. Using elegant in-vitro studies, they describe and quantify binding affinities between many of these pairs (some of which have not been previously described), provide new highly detailed structural data describing how some of these interactions (SPASTIN MIT/IST1 MIM) occur. Building on the discovery of these new interactions, they describe MIT/MIM-dependent midbody localisation for new MIT-domain containing factors and their function in abscission, both in unperturbed cells and in cells in which abscission checkpoint signalling had been engaged. The strengths of this manuscript are the quality of the in-vitro data and the comprehensive nature of the interactome analysis. The collection of affinities for the various MIT-MIM interactions are valuable, believable and strong. The crystal structures describe well how the IST1 MIM binds SPASTIN's MIT domain and exposes differences between this and how SPASTIN's MIT binds the CHMP1B-MIM. The weaknesses are that besides documenting new players in abscission and/or abscission checkpoint operation, I'm not sure that we are learning much new about how the biological processes studied operate. I think that there is some interesting biology in the manuscript, but the cell biological side currently feels a little underdeveloped.

Reviewer #3 (Public Review):

In this manuscript, Wenzel et al. have sought to quantitatively understand the mechanism of AAA+ ATPase recruitment at the midbody during cytokinesis through ESCRT-III interactions. All known ESCRT-III proteins (12 in humans) possess MIM motifs, which bind to the MIT motifs of AAA+ ATPases such as VPS4. Additional MIT-domain containing proteins also exist, >20 in humans. An important feature of ESCRT-III proteins is their ability to form polymers - therefore at the midbody or other ESCRT-related locations, multiple MIM motifs (in multiple ESCRT-III) exist which can recruit MIT containing proteins.

While we can hypothesize that multiple MIM-motifs of ESCRT-III proteins may enable higher-avidity interactions to recruit the ATPases, the reason behind the existence of the MIM motifs in all ESCRT-III proteins is less intuitive. In this regard, the authors provide a useful resource to the community by quantitating all known MIM-MIT interactions in humans. As ESCRT-related events occur throughout biology, this work should be of broad interest beyond the cytokinesis field.

In addition to the analysis of the binding interactions, the authors also find previously unknown binding interactions between ESCRT-III and three ATPases SPASTIN, KATNA1 and CAPN7. The authors solve the structure of SPASTIN-MIT with IST1-MIM, and compare it to the previously solved structure of SPASTIN-MIT with CHMP1B-MIM. This analysis allowed the authors to create a specific mutation that disrupts SPASTIN's binding to CHMP1B but not to IST1. This mutant still localizes to the midbody compared to a mutant that disrupts binding to both CHMP1B and IST1, suggesting that CHMP1B binding of SPASTIN is dispensable for midbody localization in the presence of IST1 binding.

Furthermore, the authors find that a specific set of ESCRT-III proteins: IST1, CHMP3 and CHMP1B bind promiscuously to many MIT motifs, and provide a structural explanation behind it, owing to multiple binding modes between the MIM of CHMP3 with MIT of KATNA1.

The strength of the work lies in the comprehensive quantitative analysis of the different sets of interactions between MIM and MIT motifs, further structural and cellular correlation of these binding interactions, and the finding of new roles for previously undescribed interactions. The limitations of the work are a lack of acknowledgement/analysis of possible effects of labeled MIM peptides in the quantitation of binding affinities and an unsatisfying description of how the different number of interactions play a role in cytokinetic abscission, and generally in ESCRT-related events.

Reviewer #1 (Public Review):

This is an interesting study of how CSPG sulfation states are altered after MI and how this relates to sympathetic nerve regrowth in the infarct. The authors first demonstrate that 4,6-sulfation of CSPG is increased in the heart after ischemia/reperfusion injury. They then demonstrate that reducing 4-sulfation of CSPG with ARSB increases sympathetic neurite outgrowth from sympathetic ganglion explants in vitro. The authors then treated co-cultures of scar tissue from myocardial infarcts with superior cervical ganglion explants with ARSB and showed increased neurite outgrowth on the side of the scar after ARSB. Changes in CSPG sulfation enzymes were then shown to be altered after MI by Western blot, specifically an increase in CHST15. Finally, siRNA knockdown of CHST15 expression after MI in mice reduced CSPG sulfation and was associated with increased sympathetic reinnervation of the scar. This was also associated with fewer PVCs induced by isoproterenol and caffeine.

Strengths:<br /> • This is an impressive body of experiments with a logical progression to show CSPG sulfation changes after MI and the enzymes regulating this sulfation.<br /> • The authors have utilized in vitro and in vivo models to test their hypothesis that CSPG 4-sulfation suppresses innervation of the MI scar.<br /> • There is an important disease model and therapeutic aim to this work.

Weaknesses:<br /> • The causal relationship between ARSB treatment and neurite outgrowth phenomena the authors observe after MI are weak. Specifically, the co-culture assay does not seem to fully replicate the nerve/myocardial interface after MI. It is unclear why NGF needed to be added to the media to induce neurite outgrowth when it is established that multiple neurotrophic and neurotropic factors are already expressed in the myocardium after MI (Habecker et al., J Physiol 594.14 (2016) pp 3853-3875). By visual estimation, it also appears difficult to control for spatial distance between the sympathetic ganglion and myocardial explants in this culture system, a problem which may significantly affect the diffusion of axon guidance and other signaling molecules. Additionally, because ARSB is added to both the sympathetic ganglion and the myocardial explants, it is unclear where exactly it is disrupting CSPG sulfation. It has been shown that glia also secrete CSPGs (Yiu & He, Nature Reviews Neuroscience volume 7, pp617-627 (2006)) after CNS injury, preventing axon regeneration. Thus, inhibition of 4-sulfation by ARSB within the sympathetic ganglion explant should be taken into account as well when considering experimental specificity. This particular experiment is perhaps the least convincing in this work overall.<br /> • The underlying mechanism of the therapeutic potential of inhibiting 4-sulfation of CSPG is unclear. There is immunohistochemistry showing increased sympathetic nerve fibers by TH labeling, co-localized with fibronectin staining to delineate scar. However, how this phenomenon then leads to decreased arrhythmia is a bit of a black box, especially considering that scar tissue is electrophysiologically and mechanically discontinuous from working myocardium.

Overall, the authors demonstrated very interesting dynamics of CSPG sulfation after MI and its correlation with sympathetic innervation of the MI scar. They also demonstrated knockdown of CHST15 reduces PVCs in a mouse model of MI. The causal relationship between CSPG sulfation, reinnervation of scar, and arrhythmogenesis is less convincingly demonstrated as there is no clear functional pathway suggested by which reinnervating scar alters electrophysiology. The authors perhaps realize this issue and thus were careful to be measured in the title of their manuscript, which omits the pathophysiological consequences of sympathetic nerve regeneration.

This work will be important in highlighting the importance of neural/myocardial interactions in structural heart disease. It will also draw attention and effort to understanding neural remodeling after myocardial infarction and altering this remodeling for therapeutic benefit.

Reviewer #2 (Public Review):

The study by Blake et al. tested an interesting hypothesis that chondroitin sulfate proteoglycan (CSPG) 4, 6 sulfation plays a critical role in mediating sympathetic denervation and cardiac arrhythmia post-ischemia-reperfusion (I/R) in a mouse model. They provided solid molecular evidence showing CSPG 4, 6 sulfation in cardiac scar tissues post-I/R. They also suggest upregulated CHST15 and downregulated ARSB as a mechanism for the production and maintenance of sulfated CSPGs. Most importantly, in vivo siRNA knockdown of chst15 at the early time window of I/R prevented sulfated CSPGs and sympathetic denervation in cardiac scar tissue, which eventually improved cardiac arrhythmia. The strengths of this study come from the focus on a novel CSPG pathway as well as the solid molecular/animal data. It is clear from this study that CSPGs could be a promising therapeutic target to treat cardiac arrhythmia post-myocardial damage.

Reviewer #3 (Public Review):

The authors' prior work demonstrated that inhibiting CSPG signaling following myocardial infarction (MI) enabled sympathetic axon outgrowth into the post-MI scar and reduced ventricular arrhythmogenesis. In this study, the authors sought to determine if CSPG sulfation prevented sympathetic axon outgrowth into the post-MI scar.

The strengths of the study include its depth, multimodal tools, in vitro and ex vivo experimentation, and translatability of its findings to large animals and humans.

Minor weaknesses include limited rigor in experimental design supporting some of the conclusions.

The impact of this work is likely to be in the translation to large animals and humans, where scar modifying therapies may come to the forefront of post-MI treatments. The antiarrhythmic potential of this approach is potentially significant, as no current therapies improve the innervation of myocardial scar.

Reviewer #1 (Public Review):

In this manuscript, the Sorger lab examines RNA expression in cell lines lacking most of the DUBs, and uses this data set, along with published data, to generate hypotheses about these molecules. While most DUBs are unlikely to have direct roles in transcriptional regulation, these data can still be used to correlate inactivation of the DUB to the inactivation of other genes. Using other published RNA seq. experiments, they find similarities between the transcriptional effects of knocking down DUBS and other genes. They then discuss these in light of published literature and datasets, primarily confirming previously suggested activities.

The ways in which the authors carry out this study is reminiscent of the ways in which many scientists initially analyze their datasets (be they expression, protein abundance, PTM levels or CRISPR screening data) when they first have the data in hand: they look to DepMAP and BioGrid and other sites that consolidate data and try to come up with some hypothesis. However, for most investigators, this is the beginning of the investigation, whereas here it is the entire study. While they occasionally repeat the transcriptional analysis on members of the pathway in question to confirm that a particular DUB's knockout mirrors that of another gene, this is just confirming their original observation. For example, knockout of the DUB USP8 yielded similar expression changes as those associated with over activation of the NF-kB pathway. USP8 was previously shown to function in the ESCRT pathway, which is known to regulate the NF-kB pathway. The authors further confirm this by examining expression in other ESCRT mutants. As with many of the DUB interactions, they also show that this genetic interaction can be seen on DepMap. Finally, the investigators compare transcriptional output of mutants to that of cells treated with a few small molecule inhibitors. Not surprisingly, some correlate well with their presumed target, while others do not.

Almost all of the connections drawn here are confirmations. In some cases, the connections are well-established, whereas others are less understood. However, there is no follow-up on any potential biology. For this reason, most of the paper jumps from topic to topic with a few paragraphs on each area of biology. Given that the technique carried out (transcriptional profiling of mutants) has been carried out extensively for more than a decade, their starting dataset is not particularly novel, making this a rather modest resource for the community.

Reviewer #2 (Public Review):

Deubiquitinating enzymes (DUBs) are ~100 proteases that remove ubiquitin from proteins, thereby regulating protein turnover. DUB inhibition can potentially provide new avenues for regulating targets with small molecules. Towards this end, the study has assembled a knowledgebase of DUB activities, co-dependent genes and substrates by combining targeted experiments using CRISPR libraries and inhibitors with mining of functional genomic databases, including the Dependency Map, Connectivity Map, Cancer Cell Line Encyclopedia, and protein-protein interaction databases. Study data are browsable online via the DUB Portal.

Strengths

The study provides useful, new information on a number of DUBs, Better understanding the substrates and pathways regulated by DUBs could help future research efforts towards targeting these newly identified relationships or DUBs themselves through the design of new small molecules.

The study mines multiple already existing databases to better understand DUB activities, which is a great way of utilizing these already existing resources.

The DUB Portal enables easy, interactive exploration of study findings.

Weaknesses

The study somewhat over-reaches in its implications. For example, the abstract states that through DUBs, previously thought to be undruggable targets, such as c-Myc can be targeted. However, what new biology regarding Myc is uncovered is somewhat unclear.

It is somewhat unclear how some of the thresholds are selected in the study results section.

Reviewer #1 (Public Review):

Kwon, Huxlin and Mitchell compared motion perception and oculomotor responses in eight patients with post-stroke lesions in the primary visual cortex (V1). Motion perception was measured as peripheral motion discrimination thresholds (NDR) separately in the affected and the intact visual field. Due to restoration training, the NDR thresholds were below chance even in the affected visual field, indicating that some residual motion discrimination was possible. Oculomotor responses were measured as the gain of eye drifts (PFR) after saccades to dot patterns that are coherently drifting inside peripheral, stationary apertures. The authors distinguish between a predictive, open loop component up to 100 ms after the saccade that is entirely based on presaccadic motion processing in the peripheral visual field and a visually-driven component from 100 ms after the saccade that is based on postsaccadic motion processing in the fovea. While the PFR gain of patients in the intact field was comparable to the data of healthy control subjects from a previous study (Kwon et al., 2019), the predictive, open-loop PFR gain of patients in the affected field was close to zero. This was not the case for the visually-driven PFR. The authors interpret their findings in terms of a dissociation between residual motion perception and absent predictive oculomotor control in patients with V1 lesions.

Strengths:

The study contains a rare and valuable set of perceptual and oculomotor data from eight patients with lesions in V1, who underwent restoration training. The direct comparison between peripheral motion discrimination and predictive oculomotor responses is interesting and innovative. Also, the distinction between the predictive, open-loop and the closed-loop component of PFR is important. A potential dissociation between motion perception and oculomotor control would be very relevant for the understanding of different pathways of motion processing for perception and oculomotor control and also for the understanding of the effects of restoration trainings after lesions of V1.

Weaknesses:

The dissociation between perception and oculomotor control in the affected field is primarily based on two results: First, the combination of low PFR gain (Figure 4A) on the one hand and low to medium NDR thresholds (Table 1) on the other hand. Second, the absence of a correlation between NDR thresholds and PFR gain (Figure 4B). However, the data are not as clear-cut. The regression of PRF gain on NDR thresholds in the intact field predicts that there should be a substantial PRF gain only at NDR thresholds below about 0.3. For the affected field this applies only to three data points of which one shows a substantial PFR and is fully compatible with the data in the intact field. Hence, the evidence of a dissociation between motion perception and oculomotor control is based on a very small number of data points. This also allows for a different interpretation: instead of assuming separate pathways for motion perception and oculomotor control in patients, the results might also be explained by a different read-out of the same motion signal for perception and oculomotor control, where oculomotor control applies a more conservative threshold and requires a higher internal signal strength than the motion perception.

The comparison of the patients' data to the data in the previous study (Kwon et al., 2019) is not very informative. First, the patients were considerably older than the participants in the previous study, and an age-matched control group would be favourable. That being said, the fact that the PFR gain was comparable for the intact field of the patients and the previous study renders age-effects rather unlikely. Second, there is no control data for the motion discrimination task, so we don't know what the NDR thresholds and even more importantly what the relationship between NDR thresholds and PFR gain in healthy observers would be.

Reviewer #2 (Public Review):

This study addresses the oculomotor behaviour of cortically-blind patients (with lesions in V1) who are instructed to perform a saccade toward a cued target placed either in their intact or in the blind visual field. The saccadic target consists in an aperture containing random-dot motion at 75% direction discrimination threshold ("NDR"), and is presented with iso-eccentric similar distractor apertures: with this kind of stimulus, the gaze of normally-sighted participants drifts smoothly in the direction of the target random dot motion immediately after the end of the saccade. Importantly, for some patients, a perceptual training had led to a good recovery of perceptual performance in the blind field, as documented by the reduction of motion direction discrimination threshold to levels similar to the control healthy participants. Cortically-blind (CB) patients are shown to perform very similarly to control participants in terms of saccade accuracy, but they have longer latency. As for the postsaccadic ocular following response ("PFR"), the eye velocity component projected on the random-dot motion direction Is comparable to controls when the saccade was directed to the intact field, but the mean PFR is significantly lower for saccades directed toward the blind field. The authors conclude that V1 lesions result in a previously ignored selective impairment of the automatic transaccadic transmission of visual information that drive the ocular following response. In the supplementary information, it is also shown and the shift of saccadic landing position which is induced by the presaccadic target motion is strongly reduced (yet different from zero) for saccades to the blind field locations in CB patients.

The manuscript is very well written and illustrated, and the addressed question is novel and highly interesting. The inclusion in the experiment of locations of the patients' blind field for which some perceptual abilities had been recovered is particularly interesting. However some major weaknesses fragilize part of the results and undermine the interpretation of results (see below). I also list a series of other minor issues to be clarified or improved.

Main weaknesses:

1) Unfortunately, the present data do not allow to strongly support the conclusion that the reduced PFR gain in patients is decorrelated from the motion discrimination performance. As a matter of fact, in Figure 4B the function describing the relation between PFR gain and NDR is reasonably linear in a very limited interval of NDR values (say <0.3), and it should rather be described as a decreasing exponential, or similar, approaching 0 already for NDR~0.3. On the other hand, it is presumably hard to appropriately fit a similar exponential function to the blind-field datapoints, as the majority of the latter lay in the range of NDR threshold (say > 0.4) where the PFR gain would in any case be flat and close to 0. In other terms, in my view there aren't enough blind-field datapoints with low NDR threshold to assess a quantitative difference in the relation between PFR and NDR between CB patients and Control participants. Finally, and probably just a misunderstanding of mine, shouldn't the empty circles in Figure 4A and 4B have the same y-coordinate (the PFR gain value)? It does not seem so when looking at these figures.

2) A second weak point, in my opinion, concerns the interpretation of the results and in particular the exclusion of a role for presaccadic attentional mechanisms. The authors claim (lines 356-358): "That the FEF and its projections to area MT are intact in V1-stroke patients suggests preservation of pre-saccadic planning and attention selection for the saccade target even when visual input is weak or abnormal in a blind field" and this is definitely a valuable point. However a number of other physiological mechanisms involving V1 could play a role in the spatially-selective processing of motion and the argument that (lines 368 and ff) "other aspects of saccade pre-planning related to perceptual shifts in the position of motion targets, remain in the blind-field" is not very robust here, considering that the reduction in the angular deviation is very strong in the blind field (Supplementary Figure 2).

Here is a speculative alternative interpretation : V1-lesioned patients suffer among others of a specific impairment for spatially-selective motion processing. Unfortunately the training in peripheral motion discrimination does not test this particular possibility, if I understand correctly, as there was no other distractor aperture containing distracting motion information (see Fig 2A). In contrast, in the main experiment, a lack of spatial selectivity for motion integration may have strongly affected the presaccadic motion discrimination (being more global than local) as well as PFR and postsaccadic landing position shift (although the latter was partly spared). According to this possibility, a simple prediction is that depending on the (randomly determined) motion direction in the distracting apertures, the PFR (the true eye movement, not the projection according to the stimulus motion axis) should be deviated in different directions, coherent with a global integration of motion. Do the available data allow to verify this possibility? In general, I think that it would be interesting to analyse post-saccadic smooth eye velocity beyond the "projected" velocity.

Reviewer #3 (Public Review):

The human visual system comprises a tangle of neural pathways that subserve different perceptual, cognitive, and motor functions. Unfortunate cases of brain damage can reveal surprising dissociations between the functions of damaged and spared tissue. Perhaps the most famous example is blindsight, when damage to visual regions of occipital cortex leads to subjective blindness in parts of the visual field while sparing some visually-guided actions. Kwon, Huxlin and Mitchell had a rare opportunity to study eight individuals with that type of cortical blindness due to stroke, and put them through a carefully designed regimen of visual training and oculomotor testing.

The main focus was a particular oculomotor behavior that they term the "post-saccadic following response": when a neurotypical person makes a saccade to an object moving in the periphery, their eyes immediately begin smoothly following the stimulus motion, due to an oculomotor plan made before the saccade began. In this case, the stroke patients were able to regain their ability to discriminate stimulus motion in the "blind" parts of the visual field, but upon saccading to those stimuli they did not show the immediate post-saccadic following response. This surprising result shows yet another splintering dissociation between perception and action, demonstrating that the effects of stroke can be very specific to certain motor actions.

Strengths:

- The authors masterfully combined several techniques in a rare and carefully chosen sample of participants: neuropsychiatric evaluations, rehabilitation training, psychophysics and eye-movement analyses.<br /> - The analyses that link all those measures together, while complicated and precise, and elegantly and clearly presented.<br /> The study provides a twist on blindsight that is interesting philosophically, while also constraining our models of neural circuitry and informing approaches to rehabilitation after stroke.

Weakness:

- The unique nature of this study is a strength but also potentially limits its impact: the authors studied one particular type of eye movement with a complicated, unnatural stimulus arrangement. For example, the stimuli were groups of random moving dots windowed through static apertures. These stimuli, which move but also don't, are quite different from real moving objects that people track with their eyes (flying birds, for example). A related issue, which the authors briefly acknowledge, is that the training was specifically directed towards explicit perceptual reports. We therefore don't know if the oculomotor behavior (the PFR) could also be trained.<br /> - The authors rely on traditional null-hypothesis tests (t-tests and correlations) to make binary judgements of whether each effect or difference is "significant" (p<0.05). Some of the conclusions would be more convincing if supplemented with power analyses, bootstrapped confidence intervals, and Bayes factors to evaluate the strength of evidence.

Reviewer #1 (Public Review):

Roualt et al. use a task where people make decisions (and confidence judgments) with or without control over the information they sample. They show that when controlling the information sampling, people's choices are more 'sticky' due to a lower perceived hazard rate of the stimulus sequence. To account not just for choices but also confidence judgments, they extend a Bayesian model of hidden-state inference with a metacognitive module. They also link switches (and to some extend, model-derived changes-of-mind) to specific MEG and psychophysiological signatures.

The conclusions of this paper are mostly well supported by data, but some aspects of the effects reported, the model and psychological interpretation need to be clarified and extended.

Strengths:<br /> - the task is very well designed, with maximal similarity on perceptual and motor demands.<br /> - the data are beautifully presented, and the effects are very clear.<br /> - the topic of active sampling and exploration is of high interest, and it is timely to explore this with new experimental paradigms that improve on some aspects of previously used tasks.<br /> - using confidence judgments is a powerful way to disambiguate and extend computational models of behavior.

Weaknesses:<br /> - quite a few different effects are presented, and it's not always clear which ones are novel (going beyond replications of Weiss et al. 2021); which ones are the crucial effects to disambiguate 'information seeking' and 'changes of mind' from potentially confounding factors; and which effects are are, and are not, captured by the Bayesian model.<br /> - the control experiment on pro- vs. retro-active decision-making is crucial, but without comparing these data directly (and statistically) to the main experiments it's hard to know whether this potential confound really plays no role in behavior.

Reviewer #2 (Public Review):

Ps were presented with oriented bars from a blue or orange category, corresponding to CW or CCW tilt from the vertical but with variation around these orthogonal means. They are presented with 2-8 bars on each trial and asked to give the category from which they're drawn (cue-based trials, Cb), or to generate bars from one of the two categories (outcome-based trials, Ob). The category (blue vs orange) remained the same for several trials in a row and changed unpredictably. The change in Cb was simply that the presented category changed, but in Ob that the action-category mapping changed. Ps are slower to detect when the orientation changes in Ob trials and exhibit lower confidence in their decision, purportedly demonstrating that controllability increases the stability of beliefs. Changing your mind is also associated with stronger alpha suppression in the dorsal attention network, and followed by increased pupil dilation when presenting outcomes.

The manuscript is well-written and interesting, with beautiful figures. I also found interesting that the alpha effects preceded the dilation effects. If supported, I would find the core conclusion (controllability increases the stability of beliefs) especially fascinating. However I was sceptical, and think the authors need to justify this conclusion on the basis of my concerns. I would like to believe it but can't see past an apparent confound. I hope the authors can reassure.

Specifically, the Ob trials require selection of an action, monitoring the action-outcome relationship, and a judgement about the stimulus. The Cb trials, in contrast, I think simply require monitoring the stimulus (I could not figure out whether they perform an action to start each trial, but regardless, they will not need to keep track of action-outcome mappings). Therefore the fact that Ps are slower to notice the shift in Ob trials and that their judgements are associated with lower confidence would likely appear driven by the fact the Ps have three tasks (or at least two) rather than one. Relatedly, can the fact that alpha suppression and pupil dilation effects are increased with changes-of-mind in the Ob condition also be explained by the fact Ps have more tasks? If there are greater executive / working memory demands, this will reduce alpha and increase dilation (as already discussed in the manuscript). You detect stimulus changes less readily (etc) because there is a greater executive/working memory load in this condition, and this has nothing to do with controllability/action or stability of beliefs per se.

I was somewhat reassured to see that Ps were claimed to be "equally sensitive" to the available objective evidence across conditions, but I equally could not see how this conclusion could be reached. It would be good for the authors to clarify what they mean here - did they test for a significant slope/precision effect in the data shown in Fig 3A? Is it possible to say Ps are equally sensitive to the evidence other than on switch trials, when the insight into their sensitivity is given by a response that only requires them to process the evidence on switch trials? But more generally, I think the reader needs convincing that the Ob-Cb differences are generated by something other than number of tasks and generic WM/executive differences, however the authors can do it. E.g., would the effects be equivalent if giving people an additional task to the visual that isn't motor? E.g., implicitly counting backwards; monitoring an auditory stream.

My only other main point is that there is no discussion of alternative ways in which these data may have turned out. The discussion entirely reports claims and findings with which the present data are consistent. Are there no data or theories that could have led to alternative predictions? Currently the manuscript could give the flavour of such high consensus that there was little point running the studies - the empirical patterns to date all point in identical directions. I know this is not the case. One possibility that came to mind is that the stimulus ISIs are not very variable. 2Hz+-500ms. Given you can perceive better at certain oscillatory phases of visual processing (peaks), could Ps choose to start trials in Ob to align with peaks and thereby improve perceptual acuity? If this occurred, the influence must be weaker than those pulling in the opposite direction, but it could have led to an alternative outcome. If it's a quick analysis to perform/report and the authors agree with me, it may be interesting to see how the oscillations align with events differentially in Ob and Cb.

Reviewer #3 (Public Review):

In this study, Rouault et al measure changes-of-mind and confidence variations in a perceptual decision-making task where information sampling is done with or without control. When subjects have control over information sampling (i.e. are seeking information), the authors found that they need more contradictory evidence in order to switch their choices, that such switches are made with reduced confidence and yet are more likely to be confirmed later on (rather than reverting back to the original choices). MEG and pupillometry data additionally revealed that anticipatory suppression of alpha-band activity in occipital and frontal regions occurred prior to decision switches, while pupil dilation increased post-switch, and these two neurophysiological responses were stronger in the controllable condition.

This study comprises 4 experiments, one of which was previously published (Weiss et al, 2021, Nature Communications). The presence of multiple experiments and replicated findings help mitigate the concern of low sample sizes in each of the experiment. The main novelty of the study is that it includes measures of confidence and a sophisticated Bayesian model making robust predictions about both decisions and confidence ratings.

While this work is likely to be useful and significant for the field of decision-making research, there are also several weaknesses and concerns that the authors will hopefully be able to address.

1) One main concern is about the interpretation of the results - in particular, whether the observed differences between the cue-based and outcome-based conditions could be better explained by the presence of a target-induced confirmation bias in the outcome-based condition, which would induce a strong motivation to confirm that the chosen action does lead to the target. In other words, it is possible that having a target (e.g. "draw orange") may bias subjects towards believing they are drawing from that target even when they are not, and as a result needing less evidence to reach that conclusion (similar to the effect shown in Gesiarz, Cahill and Sharot, 2019, Plos Computational Biology). This could in turn lead to the observed patterns of results, i.e. needing more evidence against orange to switch, being less confident when switching etc... Additionally, the result that prior beliefs are stronger in the Ob condition (p.18-19) is consistent with this idea, since confirmation bias is usually associated with stronger prior beliefs.

2) There are a few other instances where I believe the conclusions are not fully supported by the results.<br /> 2a) One such instance is Experiment 3, which was run to test whether the temporal direction of the inference (prospective vs retrospective) could in fact explain the observed differences between condition. First, the effects on change of mind are not shown for this Experiment, only the effects on confidence - why is that? Second the confidence data presented in Figure S1 still shows some differences: lower overall confidence overall, higher confidence time-constant, and higher confidence-PSE in the prospective vs retrospective condition. Those differences are reported but then the authors still conclude that these results constitute evidence that the observed differences between Ob and Cb conditions in the main experiment are due to controllability and not to the temporal orientation. In my opinion, this conclusion is not supported by the data. One could conclude that temporality has no effect only if no difference in choice or confidence were observed.<br /> 2b) Another instance is the claim that there is a causal role for confidence in controlling changes-of-mind (p.11). Why this is an interesting idea, I am not sure it can be fully evidenced in this task without an experimentally controlled manipulation of confidence. The reason is that there could be a common cause to both high confidence and high propensity to confirm switch decisions without the two processes actually being causally related. One such common cause could be the strength of evidence.

3) The introduction is a little thin and would benefit from being expanded. Specifically, the mention that "information-seeking has been mostly studied under 'exploration-exploitation' dilemma is not true - while fairly recent there are many studies that have studied information-seeking in humans using other paradigms. Second and most importantly, the introduction is lacking the rationale for the proposed work - in addition to dissociating information-seeking from changes-of-mind, which is more of a methodological aim, what are the key questions that the authors trying to address, and what are the hypotheses given the current literature? Finally, the use of MEG and other physiological measures (pupillometric, cardiac patterns) is not motivated at all. The introduction should set the stage as to why collecting these data is needed given the question of interest. Similarly, the hypotheses should also set the stage for the specific analysis choices performed later, i.e. in what way does each presented analysis answer the question? This is not clear at the moment.

4) Behaviorally, one of the main novel aspects of the study is the inclusion and analysis of confidence in addition to changes of mind. Yet, the neurophysiological analyses do not touch on confidence at all, which also contributes to making the rationale for using these neurophysiological methods less clear, as described above.

Reviewer #1 (Public Review):

This study studies the cellular basis of the Yki ortholog using a unicellular organism Capsaspora owczarzaki. The authors made a genetic model for the loss-of-function of coYki and found distinct roles of this ortholog, which is unlike its roles in metazoans. These findings should enhance our understanding of the ancient roles of this factor. The tools they developed could also be useful for other people to use this unicellular organism as a model.

Reviewer #2 (Public Review):

This manuscript reports two important advances: (1) the establishment of genome editing in Capsaspora and (2) the characterization of a Yki mutant. Genome editing in Capsaspora is an important advance that will no doubt greatly increase the experimental tractability of this organism, which sits on a key position in the tree of life. It was a particularly suitable target for the study of Yki function, as it contains many components of the Hippo pathway that are conserved in animals but missing from choanoflagellates. Most of the data are convincing and well documented. Particularly striking is the result in Fig. 4E, in which treatment of Yki mutants with blebbistatin leads to the rescue of the normal round aggregate phenotype.

Reviewer #3 (Public Review):

Phillips and colleagues present results obtained by generating loss-of-function mutations in the YAP/TAZ ortholog of the unicellular holozoan Capsaspora owczarzaki. In previous work published collaboratively by the Pan and Ruiz-Trillo labs, the authors had shown that Capsaspora has orthologs of yorkie (yki) and hippo (hpo) and that when these genes were expressed in Drosophila they functioned in a way that was consistent with the well-characterized function of the Hippo pathway in regulating cell proliferation.

Characterizing the role of the pathway in Capsaspora required the ability to manipulate gene expression in that organism. In this manuscript, the authors describe remarkable progress in that area. They generate lines that stably express fluorescent proteins. Excitingly, they are able to use CRISPR/Cas9 and generate loss-of-function alleles using a donor-template strategy. These accomplishments pave the way for the study of Capsaspora using molecular tools.

The authors then use these technologies to generate biallelic loss of function mutations in Capsaspora. They find no evidence of defects in cell proliferation either when these cells are cultured by themselves or when they are mixed with wild-type cells. However, they do find evidence of abnormalities in the cytoskeleton. They find that the cells themselves, and the multicellular aggregates that they form are more irregular in shape. The cells appear to adhere to substrates better than wild-type cells. They show surface blebbing that changes in the cell cortex with evidence for altered actin dynamics.

From these experiments, the authors conclude that the ancestral function of the Hippo pathway is to regulate the cytoskeleton and that its ability to regulate cell proliferation was acquired more recently in evolution.

The technical achievements are impressive, the experiments are well designed and executed, and are presented clearly. I have no issues with them. However, I feel that two of the main conclusions that the authors make are not justified by the results.

1) The authors seem convinced that CoYki functions as a transcriptional regulator. They seem to suggest that it is primarily a regulator of cytoskeletal genes. There is a body of work from the Fehon laboratory that Yki has a function at the cell cortex in Drosophila that is independent of its function as a transcriptional regulator. See the work by Xu et al. 2018; PMID30032991 (not cited in this paper). In the absence of data that shows the localization of CoYki, I don't see how the authors can tell where it is working (in the nucleus or at the cell cortex) to regulate the cytoskeleton.

2) Capsaspora and animals such as ourselves are equally separated by time from our last common ancestor. There is no reason to think that the function of signaling pathways in the Capsaspora lineage has been frozen in time while ours have evolved. Indeed, the amazing diversity of protists is consistent with lots of evolution in every lineage. One could easily argue from the same data that the ancestral function of the Hippo pathway was to regulate cell proliferation and that this was lost in the lineage that led to Capsaspora. As we learn more about the function of the Hippo pathway in diverse organisms, we will be in a better position to guess what the ancestral function was.

In summary, this manuscript describes technological innovations that will have a big impact on those who want to study this organism. They also provide convincing data to show that the Capsaspora Yorkie ortholog regulates cytoskeletal dynamics and not cell proliferation. However, as described above, the authors would need to tone down some of their conclusions.

Reviewer #1 (Public Review):

This manuscript uncovers an apparently novel mechanism of TGF-β signaling. The authors identify Arl15 as an interacting partner of Smad4 using a two-hybrid screen. Arl15 binds directly to Smad4 through the MH2 domain on Smad4 when Arl15 is in the GTP-bound. Interestingly, their data suggest that when GTP bound, Arl15 displaces Smad4 from a closed to an open conformation. This leads to increased complex formation with R-Smads and appears to also facilitate Smad4 phosphorylation. In functional experiments the authors demonstrate that the GTPase activity of Arl15 promotes TGF-β-mediated activation of its transcriptional targets. Finally, the authors identify mutants of Arl15 in cancer patients that disrupted the interaction between Arl15 and Smad4. The authors put forth an intriguing model for how Arl15 through activation of its GTP-bound form opens up the closed Smad4 conformation to promote its activation and binding to R-Smads and subsequent stimulation of TGF-β target genes. Overall, this is a well-written manuscript and the data presented are of high quality and support the proposed model. The sub-cellular localization experiments, however, seem to be somewhat over-interpreted and the order in which these experiments are introduced into the paper is distracting. Nevertheless, the major aspects of this manuscript are strong and the results should provide new knowledge into the regulation of TGF-β signaling.

Reviewer #2 (Public Review):

The authors provide evidence that the small G protein Arl15 binds to the MH2 domain of Smad4, and propose, primarily on the basis of biochemical experiments that Arl15 controls the assembly of the heteromeric Smad (Smad4:R-Smad) complexes that form in response to TGF-b or BMP. They also propose that the Smad complex enhances the GAP activity of Smad4 toward Arl15. Finally, they propose that Arl15 acts as a global regulator of TGF-b family responses.

The initial observation that Arl15 interacts with the MH2 domain of Smad4 is intriguing and so are some of the biochemical interaction data. However, in the end, the proposed role of Arl15 in Smad complex formation in response to TGF-b or BMP and the proposed scenario are insufficiently supported by in vivo (in cells) data on the extent to which Arl15 controls the Smad complex formation and its activity. Indeed, experiments that I would intuitively see as the first and key questions to be addressed have not been done (or not been shown). More specifically: (1) Does Arl15 control/enhance the association of endogenous Smad4 with Smad2/3 or Smad1/5 in response to TGF-b or BMP, respectively? (2) Does Arl15 enhance the TGF-b- or BMP-induced nuclear localization of these endogenous complexes? (3) Since Arl15 enhances the direct target gene responses, does Arl15 enhance the TGF-b-induced binding of endogenous Smad complexes to regulatory sequences of target genes?

Reviewer #1 (Public Review):

By examining expression of GFP reporters containing different proportions of rare codons, all expressed from the same promoter and genomic locus, in different transgenic flies, these authors have uncovered a surprising sudden elimination of expression when rare codon proportions exceeded 50%, which is near the upper limit of rare codon usage among native mRNAs. Examining a reporter near the boundary of this limit, they observed high expression in testes and brain and little/no expression in other tissues; and within the testis, they found high expression in germ cells and somatic cells of the germline stem cell niche but no expression in the somatic cyst cells. Measuring both reporter protein and mRNA expression suggested that impaired translation dominates, and increased mRNA turnover contributes, to the failure to express reporters exceeding 50% rare codons. Developing a new metric for tissue-specific codon usage, taCAI, they found that endogenous genes in the testis of both Drosophila and humans show an abundance of rare codon-enriched mRNAs, suggesting that rare codon usage may play an important role in testis-specific gene expression. They went on to provide evidence that evolutionarily young genes in duplicated gene pairs generated by transposon insertions tend to have higher rare codon usage, particularly among testis mRNAs and provided evidence that for one such young gene, Rpl10a, decreasing its proportion of rare codons in a transgene led to aberrant increased expression in ovaries versus testis in a manner that severely reduced fertility specifically in females.

Reviewer #2 (Public Review):

Codon usage has been shown to be an important determinant of gene expression levels in diverse organisms but the impact of codon usage on tissue-specific gene expression is unclear. In this study, the authors examined tissue-specific expression of a series of codon usage-modified GFP/mCherry-GFP reporters in Drosophila. The results showed that testis and brain can specifically allow the expression of reporter GFP protein encoded by mRNA enriched with rare codons. The authors also developed a new tissue-specific codon usage metrics (taCAI) and revealed that genes specifically expressed in both Drosophila and human testis are enriched for those with low codon usage biases. Codon optimization of RpL10Aa, which is an evolutionarily young and testis-specific gene enriched with rare codons, results in its upregulation in the ovary. Together, these results demonstrate the tissue-specific impacts of codon usage on gene expression in Drosophila and suggest a role for codon usage bias in restricting gene expression to specific tissues.

The study addresses an important biological problem and the results suggest a role for codon usage in tissue-specific gene expression in Drosophila and possibly in mammals.

However, the cliff-like decrease of GFP reporter expression level in Figure 1 appeared to suggest that codon usage bias does not have much impact on gene expression level unless codon usage biases are very poor. This is not consistent with results of many other studies in different organisms including those in Drosophila (Carlini & Stephan Genetics 2003; Fu et al., 2016 Genes & Dev). It is important to note that the codon usage profile range of the reporters designed was not a good representation of the codon usage bias range of endogenous genes. As shown by Figure 1S, 14/16 reporter genes have extremely poor codon usage biases. The authors should clarify this point to avoid misinterpretation of the results. To understand the mechanism underlying the abolished GFP expression, I suggest that the gfp mRNA levels should be determined for at least some reporters. As suggested by previous studies in Neurospora and in Drosophila cells (Zhou et al., 2018 eLife, Yang et al., Nucleic Acids Research 2019), the dramatic decrease of protein expression by codon de-optimization could be due to premature termination of transcription or translation. Mechanisms that can cause such a cliff-like behavior should be discussed in the paper.

Reviewer #3 (Public Review):

61 codons encode 20 amino acids, and synonymous codons are used at different frequencies across different species. The inclusion of common or rare codons within a transcript has important functional consequences for the expression levels of a gene product. High frequencies of rare codons within messages are thought to cause ribosome stalling, ribosome collisions, and mRNA degradation. Recent work by others in the field suggests that the percentage of common and rare codons within a gene can also influence its transcription.

This current study seeks to explore how the inclusion of rare codons influences gene expression in a tissue specific manner. Using Drosophila as a model, the authors generate a series of GFP-based reporters that contain a range of rare codons. The positions of these rare codons were either randomly selected or clustered. Examining developing larvae, the authors observe that reporters containing greater than 50% dispersed rare codons exhibit a dramatic drop in GFP fluorescence compared to controls and other reporters that contain less then 50% rare codons. Reporters that contain clustered rare codons behave in a similar manner. The authors then use a Codon Adaptation Index (CAI) to provide evidence that endogenous Drosophila genes may also exhibit a drop off of protein expression when the rare codon percentage within a given transcript exceeds a certain threshold. Based on these data, they examine another clustered reporter (GFP54C3'), which falls near the limit of CAI for endogenously expressed Drosophila genes. Strikingly, expression of this reporter in developing larvae was only observed in the testes and brain. Further observations indicate that expression within the testis is enriched in the somatic hub and germ cells but was largely absent from somatic cyst cells.

Previous work in the field shows that the presence of rare codons can influence transcription and mRNA stability. Detailed analysis of public datasets showed that Drosophila testes accumulate high levels of endogenous mRNAs enriched for rare codons relative to other tissues, consistent with their reporter assays. Analysis of Human Protein Atlas (HPA) project data shows this trend appears to hold true for human testes as well.

Lastly, the authors show that Drosophila RpL10a, a newly evolved gene with a high percentage of rare codons, shows enriched expression in the testis. Codon optimizing RpL10a results in higher protein expression levels relative to a transgene with the endogenous compliment of rare codons. Moreover, the codon optimized transgene is expressed in the ovary, resulting in reduced female fertility. These results suggest that limiting expression of RpL10a protein to the testis is functionally significant.

Strengths<br /> The paper is well-written, and the data are clear. The significance of the study builds on previous work and now shows that the presence of rare codons within transcripts influences their tissue specific protein expression. This paper will have broad appeal to those interested in gene regulation, mRNA translation, codon usage, evolution of new genes, and fertility.

Weaknesses<br /> Although this study presents several very interesting observations, few mechanistic insights are provided. At the very least, comparison of the mRNA levels between the various reporters should be directly evaluated throughout the study.

Reviewer #1 (Public Review): 

In this paper, Pobegalov et al. use single-molecule C-trap technology to examine the dynamics of RecX interaction with distinct conformational states of RecA-ssDNA filaments. Using a multi-channel microfluidic flow cell, the authors demonstrate the biphasic disassembly of E. coli RecA-ssDNA nucleoprotein filaments by E. coli RecX. The authors trap ssDNA between two beads, assemble RecA onto this filament in a buffer containing ATP and RecA, and then while in a force clamp mode can move this filament into buffer containing RecX and observe change in bead distance as a read-out for nucleoprotein filament changes. With this method the authors demonstrate that RecX, in a concentration-dependent manner, leads to an initial steep decrease in filament length, and then a gradual reduction in bead distance (filament disassembly) over about 200s. This is in line with previous single-molecule studies done with RecA and RecX homologues in Mt and Bs. 

The authors then go on to show that the RecX-mediated disassembly is reversible to a degree. Incubation of RecA-ssDNA with RecX, followed by incubation with ATP leads to an increase in filament length, albeit not a full restoration of length, indicating that the alteration of the RecA filament is comprised of both reversible (compression) and irreversible (disassembly) mechanisms. They also show greater incubation times with RecX leads to a slower decompression rate of the filament, which indicated a prevention of RecA switching between active (ATP-bound) and inactive (ADP-bound or apo) forms. Through creation of a fluorescently tagged RecX they also demonstrate further evidence that RecX binds the apo form of RecA-ssDNA nucleoprotein filament and that upon association with ATP (or switch to the active form) RecX gradually dissociates from the filament. And finally, the authors demonstrate that RecA-dsDNA filaments are rapidly and irreversibly disassembled by RecX, with no restoration of filament length upon incubation in buffer lacking RecX. 

Strength:

Overall I believe that the data presented here accurately supports the authors interpretations and that they have presented novel findings regarding regulation of RecA-DNA nucleoprotein filaments via RecX. 

Weakness:

I do not believe that the data support the statement given in lines 396-400. The authors state that RecX interaction with the apo form of the RecA-ssDNA filament inhibits the transition to the ATP-bound state, which I believe is supported by their data that transition into the ATP-bound state is delayed following incubation with RecX. However, they go on to say that this is in line with previous reports which show that RecX blocks ATP hydrolysis by RecA. I think rather that their data suggests that RecX binds to inactive RecA and slows down binding of ATP by RecA. This would be in line with their hypothesis that RecX binding between monomers inhibits the cooperativity between the RecA monomers and slows down the apo-ATP transition (lines 440-442).

Reviewer #2 (Public Review): 

In this study, optical tweezers are used to isolate a single ssDNA molecule filamented by RecA-ATP. Shortening of the substrate is observed in the presence of RecX. This shortening occurs on two distinct timescales and is partially reversible, suggesting RecX both reversibly compacts the RecA filament upon binding and irreversibly promotes depolymerization of the RecA filament. In contrast, while RecX did not shorten the substrate in the absence of free ATP (apo state), the bound RecX inhibited subsequent elongation when RecA and ATP were reintroduced. Taken together, the different experimental combinations presented help test the validity and completeness of previously proposed models, resulting in a proposed model in which RecX regulates filamentation by binding to RecA in an inactive (ATP hydrolyzed) state. Overall, the presented experiments are of great value to further understand the system, though the final presented model makes one critical an assumption that could likely be tested and validated in an additional experiment using the same experimental apparatus and procedures described. 

In the last paragraph of the introduction, the authors describe their previous work, in which 3 mechanically distinct states of RecA-ssDNA filaments are identified. Yet in this paper the authors only refer to two mechanically distinct states: active (ATP-bound) and ap (ATP hydrolyzed). Is there a role for a third state in the model to describe these experiments? This should be addressed. 

The presented model shows RecX binding specifically to inactive (ATP hydrolyzed) RecA proteins, reasoning that even in the presence of free ATP, patches of inactive RecA will be available for RecX binding. Thus, the model should be sensitive to the fraction of RecA units in the inactive state at equilibrium, which is not altered systematically in the described experiments. This inactive fraction would be determined by the balance of the rate of ATP hydrolysis and ATP binding. The latter could be altered by adjusting the concentration of free ATP in buffer before the introduction of RecX, with the model predicting shortening should be faster at lower ATP concentrations (RecX binding enhanced). Alternatively, the use of ATP analog ATP-gamma-S, which resists hydrolysis and stabilizes RecA filaments, should inhibit RecX binding and compaction according to the model. At least one of these experiments would help to validate the proposed model.

Reviewer #3 (Public Review): 

This study by Alekseev et all focuses on the RecA nucleoprotein filament dynamics and its regulation by RecX protein. RecA and its eukaryotic homolog RAD51 is the key protein of recombination and DNA repair in all organisms including humans. Understanding the mechanism of RecA action and regulation is an important task. In spite of extended studies, the dynamics of the RecA nucleoprotein filament and its transition from active to inactive form is still poorly understood. The authors use a single-molecule approach to investigate the effect of RecX on the conformational status of the RecA nucleoprotein filament. This effect was measured by a change in the RecA filament length as a readout of a transition between the active and inactive filament conformation. The authors found that RecX exerts its regulatory effect through two modes of action: i) by promoting RecA dissociation from ssDNA and ii) causing a reversible conformational change of the filament. The later mode of RecX action is novel and is of particular interest. The authors suggest that RecX binds to and stabilizes the apo form of RecA causing RecA filament inactivation and delaying its reactivation in the presence of ATP. They used fluorescently labeled RecX to confirm their model. Overall, this is an interesting study.

Reviewer #1 (Public Review): 

A strength of the manuscript is the phospho-proteomic analysis related to homeostatic synaptic scaling and the direct examination of Shank3 phosphorylation using phosphomimietic and phosphodeficient mutations. Concerns include place these results into context with previous work from this group regarding synaptic scaling requiring neuronal gene expression or new protein expression; the possible protein kinase involved in Shank3 phosphorylation; and the possible link to the key cell autonomous role for MeCP2 in synaptic scaling and Shank3 phosphorylation based on previous work by this group.

Reviewer #2 (Public Review): 

Strengths: 

1. Comprehensive/rigorous phospho-proteomic analyses in both rat and mouse cultured cortical neurons are transparently reported. This large data set will made publicly available via a web browser and should a valuable resource to many other investigators studying synaptic regulation. 

2. Analyses of the role of Shank3 phosphorylation have been carefully done. Newly developed phosphosite-specific antibodies were used to confirm changes detected in the proteomics dataset, and phospho-mimetic and phospho-null Shank3 mutations at this site to demonstrate the functional impact of these changes. 

3. Taken together the combined data provide compelling new insights into the changes in protein phosphorylation that play a role in short-term homeostatic plasticity that will be of interest to a wide range of investigators. 

Weaknesses: 

1. The phospho-proteomic data reported are obtained using a conceptually similar approach to that recently reported by Desch et al., 2021, but only rat cortical neurons. They detected a total of ~45K phosphorylation events (vs. ~32K here), with ~3,300 sites (1285 proteins) regulated during homeostatic scaling up to 24 hrs, similar to what was detected here. Readers would benefit from additional discussion of the similarities and differences in the two data sets, and the reasons for the differences. 

2. The authors rely on a pharmacological approach to identify protein phosphatases 2A (PP2A) as a key mediator of the changes in Shank3 phosphorylation. These experiments appear to have been carefully done, but the interpretations would be more robust if additional molecular approaches were used to manipulate PP2A activity. 

3. No data are presented to identify the protein kinase responsible for Shank3 phosphorylation at these sites. The discussion mentions several kinases that phosphorylate various site in Shank3. Only one appears to target S1586/1511 - CaMKII. Indeed, the Desch 2021 study reported changes in CaMKII activation, earlier studies also implicated CaMKII (e.g., DOI: 10.1016/s0896-6273(02)01049-8), and multiple labs have shown that CaMKII can interact with Shank3. It is curious that more is not made of this. 

4. The data in Fig. 7 (sGluA2 and Shank3 clustering) are not very compelling.

Reviewer #3 (Public Review): 

Homeostatic synaptic scaling is critical for regulating synaptic strength when circuits are challenged - scaling up when activity is blocked and scaling down when activity is enhanced. Scaling has been associated with neurodevelopmental disorders such as autism spectrum disorder. In the current study the authors report that scaling protocols (24 hr treatment with TTX/upscaling or bicuculline/downscaling) carried out on cortical rodent cultures have only modest changes in the proteome, but that significant changes are observed in the phosphorylation state of many proteins. They focus on the phosphorylation state of a synaptic scaffolding protein Shank 3, that they had previously implicated in synaptic upscaling, and which was associated with autism. The study does a nice job of showing that upscaling protocols are associated with Shank3 dephosphorylation and Shank3 synaptic localization. The report goes on to show that the maintained dephosphorylation of Shank3 during upscaling is mediated by PP2A and is necessary for the synaptic localization and the physiological/anatomical expression of scaling. Similar results are presented for downscaling, but in the opposite direction - Shank 3 phosphorylation and removal of Shank 3 from the synapse. This study therefore uncovers a critical role of Shank 3 phosphorylation state in the biochemical pathway that allows for scaling, and therefore could be important in designing a therapeutic strategy for certain neurodevelopmental disorders. 

Strengths:

The observation that the phosphoproteome, more so than the proteome, is highly dynamic during scaling protocols, and they show this in both rat and mouse. 

Recognizing that phosphorylation of Shank 3 by itself does not drive scaling (not sufficient), but is permissive or necessary for scaling, suggesting a complexity of the biochemical pathways that mediate scaling. 

The compelling demonstration that Shank 3 phosphorylation is a bidirectional mediator of scaling and the further demonstration of PP2As role in upscaling establishes a significant part of the pathway that underlies homeostatic synaptic plasticity. The results therefore represent significant progress in a field that is trying to advance the mechanistic underpinnings of the pathways of homeostatic plasticity, which is thought to contribute to the establishment of neuronal excitability. This was possible by taking advantage of the accessibility of the culture system. 

Weaknesses:

While the study is carefully executed and results are clear, a few results appear to be contrary to what would be expected. However, these results do not diminish the main findings of the study.

Reviewer #3 (Public Review):

In this manuscript, the authors investigate the molecular mechanism of collective cell migration in the Drosophila egg chamber. They had previously identified planar cell polarity molecules (Fat2 and Lar) that coordinate the movement of leader and trailing cells, but how Fat2 regulates the protrusion and polarity of the trailing cell was not understood. Here they provide evidence that Fat acts in trans to restrict WAVE complex recruitment to a single surface of the trailing cell.

Strengths:

The Drosophila epithelial follicular cells are a powerful system for probing the mechanism of collective cell migration given the exquisite coordination of movement and the lack of true leaders and followers in this edgeless topology. The authors had previously demonstrated that Fat2 at the back of a given cell facilitates protrusion of the cell behind it, but the basis of this facilitation was not known. By probing the spatial dynamics of a likely regulator of protrusion (WAVE complex), the current work represents an important extension of their previous findings. The authors find that Fat2 foci show a strong colocalization with WAVE foci in adjacent cells, suggesting sub-micron-scale coordination between Fat2 foci and WAVE-based protrusion in adjacent cells. In the absence of Fat2, WAVE-based protrusions are still observed, but they are shorter lived and lack polarity, leading to a lack of coordinated collective movement. The paper is very clearly written, and they employ nice quantitative image analysis schemes to understand the microscopy data. The authors make powerful use of clonal analysis to understand molecular function and protein distribution in the complex context of collective cell migration. The findings are likely to be of general interest to the cell migration and development communities.

Weaknesses:

One of the most significant findings of this work is that Fat2 is not required for WAVE-based protrusions in the trailing cell, but it focuses protrusive activity to the Fat2-opposed membrane. The basis of this focusing is not known. The authors suggest this restriction is accomplished by Fat2-based sequestration of WAVE, but this seems unlikely given the amount of recruited versus free WAVE complex and the observation that significant WAVE depletion is needed to see a phenotype in other cells. This central point of how Fat2 restricts protrusions is not yet sufficiently bolstered.

It is unfortunate that the story is not as simple as loss of Lar blocks Fat2-WAVE communication. This would have been the most direct molecular link from Fat2 to the WAVE complex, but of course it can be difficult to identify redundant molecular mechanisms. In the absence of this, it would be valuable to have a little more insight into the Fat2/WAVE coupling. Fat2 foci are characterized as being at the tips of filopodia, though show that filopodia are dispensable for follicular migration. Given that WAVE complex is not typically observed at filopodial tips, I wonder whether these are really filopodia.

Reviewer #1 (Public Review):

Williams and colleagues explored the mechanisms that govern collective cell migration using Drosophila egg chambers as model system. The follicular epithelia of developing egg chambers undergoes a form of collective cell migration, migrating in a polarized manner on top of a basement resulting in the rotation of the entire egg chamber. As these cells rotate they also secrete more basement membrane protein that restricts the growth of the egg chamber into a single axis. This rotation is driven by lamellipodial protrusions of these epithelia cells which is planar polarized resulting in orchestrated collective cell migration. The atypical cadherin Fat2 was previously determined to be required for both planar polarity and cell migration. Through quantitative imaging techniques and the generation of mosaic mutants the authors of this study where able to demonstrate that Fat2 works in trans with WAVE complex, coupling planar with the actin protrusive machinery. More specifically, Fat2 establishes actin-bases protrusions at the leading-lagging axis of the migrating epithelia where the lagging edge with Fat2 enrichment stabilizes the WAVE complex in the leading edge of the proceeding cell. The use of fat2 null allele and mosaic clones of this allele helped to establish this cell-autonomous relationship. Loss of Fat2 led to a global destabilization of the WAVE complex which could now be found in protrusions on all sides of the cell instead of just the leading and lagging edges. The authors went on to demonstrate that the intracellular domain of Fat2 is dispensable and that the extracellular domain colocalizes with the WAVE complex. This finding does raise questions as to exactly how the extracellular domain is able to stabilize the WAVE complex which were not addressed in this study.

The claims of the manuscript were largely supported by the data, however, the strength of this manuscript is also somewhat of a weakness. The combination of Drosophila genetics and quantitative images techniques they developed helped to define the role of Fat2 in this system show that it links planar polarity to the cellular protrusion machinery. However this same rigor of quantification was not carried out throughout the manuscript and some of the findings are more qualitative in nature. This manuscript, while convincing and compelling, could benefit from the inclusion of more quantitative approaches to better support their claims.

This manuscript draws a clear connection between the planar polarity machinery and the actin protrusion machinery and how they both correlate with polarized collective cell migration. The impact of these findings will likely transcend this manuscript and will influence future studies seeking to further our understanding of collective cell migration. The quantitative methods used will also be of great use to the larger cell biology community.

Reviewer #2 (Public Review):

In this paper, Williams et al. seek to understand how Fat2 promotes formation and alignment of protrusions during Drosophila follicular epithelial cell migration in the egg chamber. The authors investigate how Fat2 regulates formation and localization of membrane protrusions by examining WAVE complex localization and activity in fat2 mutants. They find that the WAVE complex is is planar polarized to the leading edges of migrating follicle cells and is enriched at protrusions, which form at the leading edge. Furthermore, in fat2 mutant egg chambers, the WAVE complex is more uniformly distributed and protrusions are more transient and present around the cell perimeter. Using mosaic clones of fat2 mutant cells, the authors show Fat2 at the trailing edge acts non-autonomously to localize the WAVE complex to the leading edge of the cell behind. Fat2 puncta colocalize with the WAVE complex at positions of protrusion, suggesting that Fat2 acts very locally, at the level of punctate assemblies, to promote during protrusion formation. Furthermore, the authors show that the Fat2 intracellular domain is dispensable for WAVE-Fat2 puncta colocalization and protrusion formation. From these data, the authors propose the model that Fat2, at the trailing edge of a cell acts at the scale of puncta to localize the WAVE complex in puncta at the leading edge across the cell-cell interface.

The major conclusions from this study are generally well supported by the data and the authors test alternative hypotheses where appropriate. Additionally, the authors developed new computational tools to segment and quantify protrusion dynamics. However, there are some aspects data that could be further quantified to better show the trends shown in the representative images. Specifically, Fig. 4D-E, S4, and S7 rely solely on representative images and it would greatly strengthen conclusions drawn from the data shown in these figures to include some quantification of these data.

Reviewer #1 (Public Review):

This manuscript identifies a meiosis-specific protein that recruits and activates the motility of the dynein-1 transport machinery at the nuclear envelope. In prophase I of meiosis, dynein moves chromosomes tethered to the nuclear envelope to expedite the search and pairing between homologous chromosomes. Previous studies have shown that dynein tethers to chromosomes via the LINC complex, which consists of a SUN protein and transmembrane KASH protein. KASH5 comprises all the known features of bona fide cargo adaptors of dynein. A previous study reported an association between dynein and KASH5, but it remained to be demonstrated whether KASH5 directly binds dynein and activates its processive motility. Overall, the work is well done and will be broadly interesting to the cell biology and biophysics readership.

Reviewer #2 (Public Review):

The manuscript by Agrawal et al. describes a molecular analysis of the meiosis-specific nesprin-family protein KASH5. KASH5 is known to interact with dynein and dynactin, but the biological function of this interaction remained obscure. The authors utilize biochemistry and single-molecule analysis to demonstrate that KASH5 acts as an activating adapter molecule that links the dynein motor to dynactin and activates processive dynein motility along microtubules. They map the interaction between KASH5 and the dynein LIC subunit to show that KASH5 binds to the dynein LIC in a manner that is very similar to previously reported dynein adapter proteins. They test multiple point mutations that are predicted to disrupt this interaction and find a subset that both disrupt the KASH5-dynein interaction in vitro and in vivo. They finally test these mutations in meiotic mouse spermatocytes and show that some of the mutations predicted to disrupt the KASH5-dynein interaction also disrupt dynein recruitment to telomeres. This disruption is, however, more mild than the phenotypes caused by these mutations in non-meiotic cells. Overall, I found the manuscript to be highly accessible and the conclusions are well-supported by the data. The discovery of KASH5 as a dynein activating adapter is very interesting for the field and represents a novel class of transmembrane activating adapters. I do not have substantial reservations about the data, which I find is high quality and believable.

One of the more interesting aspects of the work that I think warrants more discussion from the authors is the stoichiometry of the KASH5-dynein complex. The SUN-Nesprin complexes are typically represented as trimers, a model based on the crystal structure of SUN2 (Sosa et al. Cell, 2012). In this work, the authors present evidence that KASH5 alone is a dimer and that the stoichiometry of the KASH5-LIC1 complex is 2:1. It is currently unclear to me how a KASH5 dimer might interact with a dynein dimer containing two LIC subunits. The authors mention a prior study that found a similar stoichiometry in the crystal structure for the well-studied adapter proteins BicD2 and LIC1 (Lee et al. Nat. Comm. 2020). However, that study presented evidence that the 2:1 stoichiometry observed in the crystal was likely a crystal packing artifact and that BicD2 bound to two LIC1 peptides in solution. This is something the authors of the current manuscript should mention and clarify in their discussion of these results. Further, it is interestingly unclear to me how a trimeric complex of SUN1-KASH5 might interact with the dimeric dynein complex. It is also unclear how a dimeric KASH5 would interact with a trimeric SUN1. The authors might consider expanding on their thoughts on the topic of the structural organization of the SUN-Nesprin-Dynein complexes in vivo, which would no doubt provide stimulating ideas for further experimentation.

A weakness of the paper is the somewhat mild phenotype observed in mouse spermatocytes expressing KASH5 mutants. While these same mutants had stronger phenotypes in non-meiotic cells, it is unclear why the phenotypes are more mild in the biologically relevant cell type. The authors' explanation of endogenous wild-type KASH5 blunting these effects seems plausible, but it would be nice to confirm. The authors do not try combining point mutations into a single construct, which may have stronger effects on dynein binding or titration of expression to higher levels to outcompete the endogenous KASH5 protein. Alternatively, it may be possible to knock down expression of the endogenous KASH5 protein using siRNA.

Reviewer #3 (Public Review):

This study contributes to understanding how a diverse and increasing number of activating adaptors allow dynein to move a wide range of intracellular cargoes. Here the authors identify a transmembrane protein called KASH5 as the activating adaptor required for dynein to move meiotic chromosomes, a process that facilitates homolog pairing.

It is an interesting study that combines in vitro reconstitutions with cellular measurements to validate KASH5 as the new dynein activating adaptor with some properties distinct from known adaptors. My main criticism, which should not require additional data collection but additional data analysis, is to quantify run-lengths and some measure of the number of processive events in the in vitro reconstitutions, as these are parameters that are as important as the velocity measurements that are shown.

Reviewer #1 (Public Review):

The authors have performed extensive and well-controlled HDX-MS experiments using recombinant PLCγ, phosphorylated receptor tyrosine kinase (FGFR1K) and PIP2-containing liposomes to investigate the mechanisms of PLCγ activation. The data supports a model in which PLCγ, which is basally inactive, is initially primed by the interaction of its nSH2 domain with tyrosine-phosphorylated FGFR1K and therefore recruited to the membrane, after which it gets phosphorylated, leading to a situation that favors a fully open PLCγ that can efficiently catalyze membrane-embedded PIP2, and thus trigger downstream signalling cascades. Interestingly, the authors also studied an oncogenic PLCγ mutation (D1165H), showing that this mutant, which seems to be conformationally more flexible, mimics RTK engagement.

The experiments are performed using catalytically inactive PLCγ mutant (H335A), so the phospholipase can interact with PIP2-containing liposomes but not catalytically hydrolyze PIP2 during the course of the HDX experiments.

Finally, the experiments with the liposomes were all performed for a given lipid composition (90% PE+10% PIP2).

Reviewer #2 (Public Review):

This manuscript provides HDX-MS analysis of PLCg1 bound to the soluble kinase domain of FGFR1 (FGFR1K) and/or liposomes containing PIP2. PLCg1 is autoinhibited as shown by the crystal structure of the full-length protein which includes multiple regulatory domains as well as the TIM barrel lipase domain. The FGFR1K binds to the N-terminal SH2 domain and this is verified by decreased exchange upon binding. The authors use a catalytically dead mutant in order to study the complexes at a constant concentration of PIP2 in the liposomes. The interesting story of the paper is that regions of the protein far from the FGFR1K binding site increase in exchange upon binding. While this is new information for this large protein that is arguably difficult to study, it is rather expected at this point having been observed in many other autoinhibited systems with similar SH2 and SH3 domains such as kinases.

The authors are able to study the ternary complex between liposomes containing PIP2 substrate, the FGF receptor kinase domain and the protein of interest, Phospholipase C gamma, which is a large multidomain protein. The crystal structure of the protein is in an autoinhibited form, and the authors are able to show using HDX-MS how opening might occur to an active state.

Reviewer #1 (Public Review):

This study uses a nice longitudinal dataset and performs relatively thorough methodological comparisons. I also appreciate the systematic literature review presented in the introduction. The discussion of confound control is interesting and it is great that a leave-one-site-out test was included. However, the prediction accuracy drops in these important leave-one-site-out analyses, which should be assessed and discussed further. Furthermore, I think there is a missed opportunity to test longitudinal prediction using only pre-onset individuals to gain clearer causal insights. Please find specific comments below, approximately in order of importance.

1. The leave-one-site-out results fail to achieve significant prediction accuracy for any of the phenotypes. This reveals a lack of cross-site generalizability of all results in this work. The authors discuss that this variance could be caused by distributed sample sizes across sites resulting in uneven folds or site-specific variance. It should be possible to test these hypotheses by looking at the relative performance across CV folds. The site-specific variance hypothesis may be likely because for the other results confounds are addressed using oversampling (i.e., sampling with replacement) which creates a large sample with lower variance than a random sample of the same size. This is an important null finding that may have important implications, so I do not think that it is cause for rejection. However, it is a key element of this paper and I think it should be assessed further and discussed more widely in the abstract and conclusion.

2. The authors state that "83.3% of subjects reported having no or just one binge drinking experience until age 14". To gain clearer insights into the causality, I recommend repeating the MRIage14 → AAMage22 prediction using only these 83% of subjects.

3. The feature importance results for brain regions are quite inconsistent across time points. As such, the study doesn't really address one of the main challenges with previous work discussed in the introduction: "brain regions reported were not consistent between these studies either and do not tell a coherent story". This would be worth looking into further, for example by looking at other indices of feature importance such as permutation-based measures and/or investigating the stability of feature importance across bootstrapped CV folds.

Reviewer #2 (Public Review):

The authors extensively compared different phenotypes of alcohol misuse and found that binge drinking is the most predictable phenotype of alcohol misuse, which can be predicted from their brain structure with a significant and high accuracy of 73% − 78%. More importantly, alcohol misuse at age 22 could be predicted from the brains at age 14 and age 19. Two non-linear models - SVM-rbf and GB perform better than the two linear models; and counter-balancing with oversampling is most effective confound-control technique. This work has made substantial experiments to verify the prediction results in long-term, large cohorts of data via a systematic prediction analysis.

Reviewer #1 (Public Review):

In this manuscript, Zalachoras and colleagues examined the role of glutathione (GSH) in the nucleus accumbens in effort-related behaviors. First, human participants were subjected to a behavioral task requiring physical efforts in which they are asked to squeeze a handgrip to obtain a monetary reward. The authors then quantified the level of 10 metabolites in the nucleus accumbens (NuAc) using 7T proton magnetic resonance spectroscopy (1H-MRS) and found that the level of GSH positively correlated with successful performance in the task. The authors then turned to rats and examined the causal relationship between GSH and effort-based task performance. First, the authors show that rats with high GSH in NuAc (as measured using ultra-high field 1H-MRS) spent more time moving in a forced swim test than those with low GSH. Furthermore, the authors used a progressive ratio (PR) task in rats, and showed that rats with high NuAc GSH levels exhibited a higher breakpoint, and bilateral injections of an inhibitor of gamma-glutamylcysteine synthetase (BSO), which inhibits the synthesis of GSH, into NAcc lowered a breakpoint than in control animals. Conversely, enhancing GSH synthesis by injecting N-acetyl-cysteine (NAC) into NuAc increased the NAcc GSH level and heightened a breakpoint in the PR task. Finally, the authors performed ex vivo patch-clamp recordings in the NuAc and showed that the amplitudes of miniature excitatory synaptic currents were increased and decreased in direct- and indirect-pathway medium spiny neurons in NuAc.

GSH consists of three amino acids (cysteine, glutamic acid and glycine), and is known as an important antioxidant. The finding that the level of GSH in NuAc correlates with effort-related behaviors is intriguing although the exact mechanism, while discussed in Discussion, remains unclear. The results are presented clearly and the authors make sound discussions.

Reviewer #2 (Public Review):

Overall, the rodent work gives convincing evidence for an important role of glutathione in nucleus accumbens in regulating the willingness to invest effort to obtain reward or escape an aversive situation. The convergent approach to assess the putative underlying biological mechanisms, is a particularly impressive combination of behaviour (forced swim test, progressive ratio test), MRS, BSO infusions, ex vivo electrophysiology, NAC dietary treatment, chromatography and identification of D1/D2 MSNs.

I would like to see made clearer the link between metabolism in the accumbens and effort-based decision-making. Beyond the basic logic that the nucleus accumbens is important in motivated performance, and that compromised metabolism in any brain region would reduce processing and thus affect any process that is dependent on this particular brain region. Is there a specific mechanism through which metabolism would affect particularly effort-based motivated performance? Would this not hold for other accumbens-dependent processes? How does this relate to for example resource limitation theories for cognitive control in the prefrontal cortex.

Furthermore, there are a number of specific concerns that I have about the paper:

- Lack of specificity of the effects: all manipulations and measurements are only in the nucleus accumbens, but not compared to a control region, so it is unclear whether the<br /> - Lack of generalizability because a male-only population (both human and rodent) is tested<br /> - In the human MRS study, the task cannot dissociate changes in willingness to exert effort from changes in the valuation / motivation, i.e. in the cost-benefit balance of effort and incentive, it is unclear which of these is changed to alter behaviour.<br /> - Statistical analyses consist of many independent tests not corrected for multiple comparisons, that should instead be combined into a single analysis. Furthermore, difference between groups are implied based on the presence/absence of an effect in each group, rather than a direct comparison between these.

Reviewer #3 (Public Review):

In this manuscript by Zalachoras and colleagues, the authors utilize proton magnetic resonance spectroscopy to investigate the levels of multiple metabolites in the nucleus accumbens of male human subjects during performance of a motivated behavioral task. They discover that glutathione levels are elevated in individuals with the highest motivational performance scores and that these levels directly correlated with effort. Using a similar approach in male rats, the authors confirm a similar relationship between accumbal glutathione levels and motivated behavior. The authors further demonstrate that decreasing or increasing glutathione levels in the nucleus accumbens decreases, or increases motivated behavior in male rats, respectively. Finally, the authors demonstrate that increasing glutathione levels in the brain through dietary supplementation with the cysteine donor N-acetyl-cysteine increases excitatory synaptic connectivity onto subpopulations of accumbal medium spiny neurons in subtly distinct ways with the core region of the structure. The strengths of the manuscript include the translational linkages between humans and the rat experimental system, the bidirectional modulation of glutathione levels, and analysis of synaptic changes in accumbal medium spiny neurons. Collectively these data support an important role for antioxidants in the function of the nucleus accumbens and the regulation of motivated behavior that has broad implications for the use of antioxident supplements in the treatment of disorders in which motivated behaviors are disrupted. However, the study is limited in its analysis of only male human and rodent subjects, leading to the question of whether these findings are sex-specific. Moreover, there is limited evidence to support whether the effects of treatment with antioxidants is temporary or irreversible, and the extent to which changes in synaptic connectivity in the nucleus accumbens also occur within the shell region of this structure, which is known to play an important role in the regulation of motivation.

Reviewer #2 (Public Review):

The manuscript by Morck et al examines five HCM-causing mutations in the lever arm of beta-cardiac myosin using biochemical and biophysical assays to assess their impact on myosin function. A range of effects were seen in the various assays with a common defect in the force sensitivity of the detachment rate constant.

The authors have selected six of the many mutations known to occur in β-cardiac myosin heavy chain in cases of hypertrophic cardiomyopathy. The common feature of these mutations is that all are located in the lever arm of the myosin. Three are in the pliant region and two are in the region that binds the ELC and the RLC. A strength of the manuscript is that multiple assays are used to access the effect of these mutations on myosin function. These include measurement of the extent of light chain binding, steady state actin-activated ATPase assays to determine the kcat and the dependence on actin concentration, in vitro motility assays, single turnover assays to access the amount of myosin in the SRX state in the absence of actin, comparison of a short tailed vs a longer tailed HMM fragments to access the fraction of myosin in the SRX state in the presence of actin and optical trapping to extract numerous mechanical and kinetic parameters. The investigation of HCM-causing mutations is a very active area of research and this manuscript adheres to a high standard in terms of examining a number of possibly related mutations using a number of assays. In doing so, it sets a high standard.<br /> A weakness of the study is that it is not always easy to interpret the in vitro assays in the context of how the mutation would lead to a hypertrophic heart disease and the authors acknowledge that future studies will likely have to done in a cellular or tissue model where an intact sarcomere along with other relevant proteins such as myosin binding protein-C are present in order to appreciate the full impact of the mutations.

Reviewer #1 (Public Review):

Morck et al. report the effect of five HCM causing lever arm mutations - two in the light chain binding region and three in the pliant region - on beta-cardiac myosin motor function and autoinhibition. Overall, this is a strong and very interesting work, especially since the functional consequences of mutations in the lever arm are understudied. The authors carefully compared light chain binding stoichiometries to the myosin heavy chain, steady-state ATPases, in vitro gliding velocities, and single ATP turnover kinetics of lever arm mutants in the context of short-tailed and long-tailed double-headed myosin constructs to investigate their effect on motor function and autoinhibition. They additionally used harmonic force spectroscopy to measure load-dependent detachment rates and step sizes of single-headed pliant region mutants and then calculate parameters including ensemble force, power output, and duty ratio. Finally, the authors discuss their findings with a structural model of the autoinhibited state of beta-cardiac myosin and conclude that mutations in the light chain binding region lead to changes in myosin motor activity and the formation of the autoinhibited state whereas mutations in the pliant region impact the ability of myosin to form the autoinhibited state. In summary, this work makes a significant contribution to the mechanisms of disease-causing mutations in beta-cardiac myosin and SRX myosin biology and will be of wide general interest.

The strengths of this work are the rigorous and well controlled experimental design and data analysis in addition to the use of human proteins to study human disease-causing mutations.

A weakness of this work is that the interpretation/discussion of the experimental results heavily relies on previous homology models of beta-cardiac myosin (e.g. Fig. S3) rather than the relevant parts of the recent high-resolution structures of smooth muscle myosin in the autoinhibited state (PMIDs: 34936462, 33268893, 33268888). For example, one of these studies showed a previously unknown conformation of the RLC bound to the lever arms of autoinhibited myosin. The same study also showed that the C-terminus of the RLC interacts with the hook to stabilize the autoinhibited state and that the RLC interacts with the ELC. It would be insightful to analyze or comment if the studied lever arm mutations may change these interactions and possibly alter an allosteric pathway that operates between the light chain bound lever arm and the motor domain.

Reviewer #3 (Public Review):

The paper by Morck et al. explores the functional consequences of a group of single mutations in the lever arm of myh7 that are associated with hypertrophic cardiomyopathy (HCM). The underlying hypothesis is that these mutations affect the population of the super-relaxed state of myosin. The investigators use range of biochemical and biophysical techniques to explore the activities of these myosins. They conclude that the mutations have a range of effects on the motors, and there is not a single mechanism that can account for hypercontractility that leads to HCM. Although there is not a straightforward connection between the mutations and HCM, the study is important in that it reveals the range of functional effects of the mutations.

A strength of the paper is the range of techniques used to examine the functional consequences of a range of myh7 mutations. Using single-molecule and ensemble techniques, they conclude the lever-arm mutations affect SRX to various extents, in addition to affecting force-dependent actin detachments, actin-activated ATPase activities, and power output. The effort required to express, purify, and characterize the six constructs (WT + 5 mutants) is considerable. A unified mechanism is not proposed as to how these mutants drive HCM, but the work remains significant in showing the range of functional effects that should be considered when modeling SRX, thin-filament activation, and interaction with other sarcomeric proteins.

A weakness in the paper is the variability in the reported ATPase activities as outlined below. This variability leads one to question the validity of the conclusions about actin-activation of the ATPase activity. Additionally, the paper does not show primary single-molecule data, and it does not adequately discuss limitations of the harmonic force spectroscopy method. To be clear, this method is appropriate for this study, but its model-dependent limitations need to be stated.

Specific Points:

The authors ability to conclude that there are differences in the ATPase activities among the isoforms is not convincing. The authors are to be commended for providing the detailed data summary in Table S1, but it is these data that raise concerns. For example, the ranges in the values of kcat's (3.8 - 6.1 s-1) and Km's (1.5 - 13.6 uM) in Table S1 obtained from the different WT-control experiments are very large. In a well-controlled ATPase assay, these numbers should be very similar. It makes one question the health of the proteins and the ability to know the active site concentrations. Normalizing each mutant to the paired WT protein provides a control for assay variability, but it does not control for variability in the health of the proteins. The reader is left to wonder if the percent differences reported for the mutants are meaningful.

Readers need to see primary optical trapping data. Only the results of analyses are shown. It would be helpful to see single interactions, and it would be useful to see displacement distributions. Given the mutations are in the myosin lever, one might expect changes in average displacements or changes in the width of the displacement. These data are not provided.

It is surprising that the authors do not show lifetimes of attachment durations from the optical trapping in the absence of force. Figure 3B is from the model-dependent fitting of the harmonic force spectroscopy experiment.

Reviewer #1 (Public Review):

Plant vacuole expansion is correlated with cell elongation, presumable to fill the space within the cell and to limit the volume of cytoplasm required in mature, elongated plant cells, such as root cells. Previous work from this lab has shown that vacuole reshaping via actin and myosin interactions plays a role in defining vacuole size and that auxin can regulate cell size via posttranslational regulation of SNAREs.

The authors conducted a screen of small bioactive molecules with known effects on plant cells (Drakakaki et al 2011) and isolated VAC1, a compound that causes aggregation of vacuolar SNARES (VAMP711, VTI11, SYP22) in an unknown compartment and changes to vacuolar morphology (Fig 2). The authors use HPLC-MS to analyze VAC1 metabolism in seedlings (Supplemental Figure 2) and test a few VAC1 analogues (Supplemental Figure 3).

Using a variety of fluorescent subcellular markers, the authors find that endocytic trafficking to the vacuole is disrupted by VAC1 treatment, resulting intracellular in signal aggregation, rather than localization to the tonoplast (Fig 3). Localization of clathrin-mediated endocytosis machinery and TGN/early endosome markers are qualitatively unaffected by VAC1. However, treatment with BFA and WM decrease VAC1 aggregate signal, implying that the affected compartments are upstream of (early endosome) or upstream/parallel to (late endosome) the site of VAC1 action. Since different vacuolar SNAREs act in heterotypic (endosome-derived) and homotypic (vacuole-derived) fusion, the authors test whether affecting either of these pathways using inducible amiRNA lines that target these different complexes. The vps3 amiRNA lines were slightly resistant to VAC1, implying that VAC1 primarily targets endosome-derived vesicle fusion with the vacuole. These results imply that endocytosis is unaffected by VAC1, but that a later step in endocytic trafficking is affected, before cargo reaches the vacuole.

The authors hypothesize that endocytic trafficking from the cell surface to the vacuole might be involved in vacuolar expansion during elongative growth. In agreement with this, they found a correlation between intensity of FM4-64 uptake (representing endocytosis) to VAC1 bodies, BFA bodies, or the tonoplast and cell elongation. This correlation could not be explained simply by the larger surface are of elongating cells (Figure 5). They also found that VAC1 temporarily disrupted this vacuole growth and elongative growth (although it recovers at later stages), further confirming that VAC1 targets endocytic trafficking to the vacuole (Fig 6). Although it is difficult to interpret FM4-64 tracking experiments quantitatively across different samples, these data imply that endocytic trafficking to the vacuole is correlated with cell expansion. Although the authors present these results as a paradox, it is unsurprising that increased endocytic trafficking is correlated with cell expansion from the perspective of cell wall secretion, since the volume of the cell wall must increase much more than the surface area of the plasma membrane during elongative growth.

Overall, this work carefully characterizes a small molecule that disrupts endocytic trafficking to the vacuole and places it within the molecular context of vacuolar trafficking, which will make this a useful tool to many researchers studying endocytic trafficking and vacuole biogenesis in plants.

Reviewer #2 (Public Review):

Dünser et al. investigate how membrane delivery to the vacuole affects cellular growth in the model plant Arabidopsis thaliana. The starting hypothesis of this paper is that interference with vacuolar N-ethylmaleimide-sensitive-factor attachment receptor (SNARE) protein function would specifically allow addressing the importance of membrane delivery to the vacuole for overall growth. A chemical screen was deployed to look for small compounds affecting SNARE accumulation and vacuolar morphology. Several vacuolar affecting compounds (VACs) were identified and the authors focused on one of these, VAC1, which induced an ectopic accumulation of the vacuolar SNARE complex adjacent to the main vacuole. Structure activity relationship analysis revealed that the compound itself, rather than its degradation or conversion products, was responsible for the observed cellular effect and that several chemical groups of VAC1 were essential for its function. Using cell biological, genetic and pharmacological tools, the authors conclude that VAC1 interferes with SNARE-dependent vesicle fusion events at the tonoplast. Application of VAC1 allowed the authors to identify a differential rate of membrane internalization between elongating and meristematic root cells. Quantification of plasma membrane and tonoplast surface area revealed to be closely balanced during rapid cellular expansion and VAC1 quickly disturbed this balance, while at the same time, this correlated with diminished root growth.

Strengths:<br /> -The authors report here on a very original and novel concept in plant endomembrane trafficking and the experiments performed support their hypotheses.<br /> -The authors performed a clever initial screen to identify vacuolar affecting compounds via accumulation of GFP-tagged SNARE proteins, followed by detailed confocal analysis of the effects of these compounds to in the end focus on a single compound for in depth analysis, which included a very detailed analysis of its degradation and conversion products as well as its derivatives to rule out that the observed effects were non-specific to the administered compound.<br /> -The subcellular imaging is of very high quality and overall the quantifications are rigorously performed and visualized with adequate statistical analysis.

Weaknesses:<br /> -Although the authors conclude that VAC1 likely affects SNARE-dependent membrane fusion at the tonoplast, its molecular target(s) remain unknown. Mechanistic insight into the observed effects therefore remains to be determined.<br /> -Support for the absence of any adverse effects of VAC1 on endocytic trafficking and actin dynamics could be more optimally be achieved using dynamic imaging.<br /> -The correlation between enhanced endocytic trafficking and cellular expansion, which is a key finding of this manuscript, could be further supported by the differential internalization of integral membrane proteins instead of membrane dyes.

Reviewer #3 (Public Review):

In this manuscript, authors are reporting identification of a compound, VAC1, which affects localization of vacuolar SNARE proteins in Arabidopsis root cells. Authors then examined the effect of VAC1 on other markers, and found that VAC1 affects localization/transport of plasma membrane proteins and FM4-64 but not early and late endosomal proteins, CLC, and actin microfilaments. Authors then examined the effects of VAC1 on expansion of the cell and vacuole and endocytic transport, based on which they concluded that endocytic transport from the PM to vacuole is enhanced during cell elongation, which could coordinate expansion of surface areas of the cell and vacuole.

It is firmly demonstrated in this work that VAC1 treatment resulted in abnormal localization of vacuolar SNARE proteins. In pictures presented in Figure 2C, vacuolar SNAREs seem to be accumulating in aster-like structures. Given that the SNARE proteins are membrane-anchored proteins, the SNARE-positive aster-like structures should be membranous structures. However, the lipophilic dye FM4-64 does not seem to reach the SNARE-positive spikes, accumulating inside the structure. It would be helpful to understand which step is affected by VAC1 more precisely if the detailed structure of the VAC1 body is investigated, e.g., by TEM. It would be also informative to test whether non-SNARE vacuolar proteins are also affected by VAC1 to see the effect of VAC1 is specific to SNARE proteins or not.

Related to the comment above, in some figures (e.g., Figure 3E), VAC1 bodies seem to be located inside the vacuole. It would be good to explain whether this consistent with the proposed mode of action of VAC1.

Reviewer #1 (Public Review):

LaRue, Linder and colleagues present an automation (GLO-Bot) and analysis pipeline building on the previously developed GLO-Roots, which makes use of a constitutively expressed luciferase gene to image plant roots in thin soil containers (rhizotrons). After validation of the system using a set of 6 accessions, the authors then take advantage of the increased throughput to phenotype root system architecture (RSA) of 93 natural Arabidopsis accessions and perform genome-wide association to identify polymorphic genomic regions that are associated with specific RSA traits. I appreciate that the authors made all data available via zenodo.

The authors succeeded in automating the GLO-Root system. Overall, the GLO-Bot appears to be a nice platform to collect time-lapse images of root growth in soil-substrate using rhizotrons. The automation of the GLO-Roots system using the GLO-Bot is well described, although not in sufficient detail to be rebuilt by interested researchers, e.g. the software controlling the robot is not described or made available, precluding wide adoption of the method. The image processing pipeline is clearly described in the methods and in Figure 2. The pipeline open source and available for use and appears to work well overall, although in some cases the vector representation of the root system appears to be incomplete.

The authors then present a quantitative analysis of RSA using a set of 93 accessions, with 6 replicates per accession, generating a large dataset on the diversity of RSA in Arabidopsis. Using average angle per day, the authors identify SNPs that significantly associated with angle at 28 days after sowing, and they describe a correlation between this trait and the mean diurnal temperature range at the site where the accession was originally collected. The main weakness of the manuscript in its current form are some details of the quantitative genetic analysis. In my opinion the quantitative genetic analysis would benefit from additional quality control as there are peculiarities in the dataset that was used as the basis for GWAS.

Reviewer #2 (Public Review):

Therese LaRue and colleagues have developed a second generation of the GLO-Roots system that had been developed in their lab and published in 2015. Importantly, the new system (GLO-Bot) and the analysis of the resulting images has now been largely automated and therefore provides a throughput allowing for genetic studies. In an impressive endeavor the authors have transformed more than 100 diverse accessions that had been selected using sensible criteria with the luciferase construct, which then allowed the RSA of these accessions to be measured using the GLO-Bot system. On a set of 6 diverse accessions, the authors carefully identify meaningful RSA traits that they then quantified in the accessions of a larger panel of almost 100 accessions. They also benchmarked the new imaging processing tools against gold-standard manual tools. Overall, they show that the data acquisition and analysis is reproducible and reasonably accurate. They then proceeded to conduct GWAS using the RSA traits and identified several significantly associated candidate SNPs. Finally, they correlated the RSA with environmental variables and found interesting correlations that are consistent with prior studies.

Strengths:

The manuscript presents interesting root phenotyping technology, a comprehensive atlas of RSA under rhizotron lab conditions in Arabidopsis, candidate genes potentially underlying RSA traits, and interesting associations of RSA and climate variables. This will be inspiring and useful to many other researchers and has the potential to be explored further in future studies.

Weaknesses:

Some aspects of the data analyses are not well described and should be described more. The trait data is heavily processed to "breeding values" and it is a bit unclear when unprocessed and processed trait data is used and why. Also, limitations and caveats are not discussed sufficiently. For instance, presenting and discussing the issues and caveats of measuring RSA that was generated in thin and not very wide soil sheets using the GLO-Bot system when natural growth in soil is usually largely unconstrained. Moreover, the analysis of potential candidate genes from the GWAS is not very well developed. Finally, the trait data was not available with the manuscript and a major impact of a resource like this will come from the data being fully available to the community.

Reviewer #3 (Public Review):

The authors provide a thorough description of a method to transform plants to be bioluminescent upon applications of the require substrate such that roots are visible on the windows of rhizoboxes. They have expanded on previous work by automatic the imaging process with a robot that moves rhizoboxes to an imager where images are captured. They have improved the image analysis pipeline to be mostly automated with a user presumably needed to run various scripts in batch mode on directories of images. One novel aspect of the image analysis pipeline is in using image subtraction to subtract the previous time root system from the current in order to identify new growth.

Overall, I think the authors provide a great amount of detail in parts needed and the methods, but some recommendations to increase reproducibility are more information about actual root traits measured. For example, one concern would be if root length is only summing pixels without considering diagonal pixels having a length of square-root of two, sqrt(2).

While the methodological aspects of the paper are compelling, the authors have furthered the significance through a biological application for genetic analysis among accessions of Arabidopsis and correlating root traits to climatic 'envirotypes' or data from the origin site of the respective accession. This genetic analysis would be furthered by greater consideration of time series analysis and multi-trait analysis, which is possible in GEMMA. The authors could consider genetic analysis of the PCA traits as well. Given the novelty of this type of time-series, multi-trait data - the authors can reach further here.

As far as the general structure of the manuscript, I struggled with the results mixing in the methods such that I was never sure if the lack of detail in methods there would be addressed later, along with the mixture of discussions. Perhaps these are personal choices, but the methods were also after supplemental. I simply ask the authors to consider the reader here by being honest with my own experience reading this manuscript.

Overall, I believe this manuscript advanced root phenotyping by providing relatively high-throughput (imaging is slow due to the long exposure times) data and doing the time-series, multi-trait genetic mapping. The authors mention imaging shoots but no data is presented - presumably, it would be interesting to tie that in but they may be reasons to not. The authors could also discuss more the advantages of this approach relative to color imaging that has also advanced significantly since the original GLO-Root paper was released. Last, I am not sure the description of the 6 accessions study adds much value to the paper, and probably many other preliminary studies were done to prototype. Overall, this is fantastic and substantial work presented in a compelling way.

Reviewer #1 (Public Review):

Dorkenwald & colleagues perform serial EM to fully reconstruct the neurites and synaptic connections between several hundred L2/3 pyramidal cells in the neocortex of a mouse. They find that automated methods struggle with the large volume of tissue they sample and devise methods for augmenting training data for human-assisted convolutional network-based segmentation. The data and code are available in various forms on a dedicated website. The scientific findings of the study are that the distribution of synapse spine volumes is best fit by a two-component log-normal mixture model, and that synapse sizes are coarsely correlated when multiple shared connections are considered, with the binary state accounting for much of the shared variation. This is interesting because multimodality in synaptic strength is an outcome that constrains models of synaptic learning and suggests additional structure in the connections that may form functional assemblies. The paper is well presented and well written and should be of interest to neurophysiologists, theoretical neuroscientists, cell biologists and neuroanatomists.

Reviewer #2 (Public Review):

The authors demonstrated the existence of binary and analogue forms of variabilities in dendritic spines using the double synaptic contacts between two neurons within the volume of 3D EM reconstructions (250*140*90um). The 160 double synaptic connections (EFig. 3) are stunning and exceptionally valuable, which provide a novel line of evidence for two modes of spine structural changes. The major weakness is the absence of behavioural manipulations to confirm the learning dependence of the results. However, the new ways of interpreting the EM data will be surprising to the neuroscience community and have a significant impact.

Reviewer #3 (Public Review):

The authors present a large scale study of connectomics in mouse primary visual cortex. Their study focuses on correlations among the spine head volumes of pairs of dual connections, and specifically those formed between Layer 2/3 pyramidal neurons. They define a "dual connection" as a pair of synapses connecting the same pre- and post-synaptic cells. They report on a novel and very interesting finding that the distribution of sizes among these pairs is bimodal can be fit by a mixture of a binary variable and a log-normal distribution. They draw the conclusion that the binary component could be due to synaptic plasticity rules and that the log-normal component is due to other factors. The authors also relate their novel findings to previous studies of correlations among dual connections.

1) The authors make the claim that the bimodality of the size distribution of "dual connections" is due to plasticity rules while the continuous gradation of the synapse size is dominated by "other influences" besides plasticity rules. But couldn't it be the case that precise synaptic plasticity rules are always at play and that the bimodality is due to the impact of "other influences" on these rules. These influences could be dendrite diameter, synapse density along the dendrite, distance from the soma, branch-point failure of propagation of the pre-synaptic AP or post-synaptic bAP, to name just a few. The continuous log-normal component of the gradation of synapse sizes is not at all inconsistent with the outcome of highly precise synaptic plasticity rules. Indeed, Bartol et al., 2015 showed that synaptic plasticity in rat CA1 stratum radiatum is as precise for small synapses as it is for large synapses over a broad, continuous, log-normal range of synapse sizes. Each individual synapse has its own unique activation history and a resulting, precise synaptic weight. And across the population of synapses there is a continuous distribution of activation histories.

2) The bimodality is a new and very interesting observation in this work and deserves much closer scrutiny to reveal the root cause behind it. The authors have shown that it exists in connections between layer 2/3 PyCs but is absent in other connections traced in their reconstruction of mouse neocortex. Perhaps this reveals something special about information processing in the neural subcircuit of layer 2/3 PyCs. With their highly detailed large-scale reconstruction, the authors have the opportunity to probe this question deeper.

Reviewer #1 (Public Review):

In this manuscript, Gao and colleagues use existing comprehensive RNA expression datasets and generate additional data from targeted gene deletion or pathway manipulation in secondary crest myofibroblasts (MFBs) during mouse lung alveolar septation. They integrate the results and use software tools to infer potential active signaling between MFBs and nearby alveolar epithelial type I (AT1) and AT2 cells. By examining which genes are increased and decreased upon deletion of IGF1 or IGF1R in MFBs at postnatal day 2, they generate a gene regulatory network (GNR) for the MFB during alveolar septation. They subsequently identify WNT5a as putatively signaling in an autocrine manner (via Ror2) and to AT2 cells (via Ror1), and FGF10 signaling to both AT1 and AT2 cells (via FGFR2) and in an autocrine manner (via FGFR1/3/4). They flesh out the GRN within the MFB by pharmacologic inhibition of FGFR2 and silencing of Wnt5a expression followed by qRT-PCR expression analysis of genes within the GRN, by which they build upon their initial GRN derived from modulation of IGF1 signaling. They also examine the expression of AT1 and AT2 marker genes in bulk cell RNA of all non-MFB cells by qRT-PCR, adding these connections onto their map. Overall this manuscript represents a cutting-edge and novel approach to extracting useful information from publicly available gene expression datasets. The work should be of high interest to lung developmental biologists and researchers interested in understanding BPD pathophysiology.

Reviewer #2 (Public Review):

In this manuscript, Gao et al claim that they have constructed a gene regulatory network underlying alveologenesis and its significance to bronchopulmonary dysplasia (BPD). Using RT-PCR and in situ hybridization, the authors claim that Igf1 and Igf1r are expressed in secondary crest myofibroblasts (SCMFs) and their loss of function using Gli1-creER results in alveolar simplification, a tissue level disorganization of alveoli that phenocopies BPD. Further, the authors investigate transcriptomic changes in mesenchymal and epithelial populations from control and Igf1r mutant lungs. For this, the authors developed a 47-gene panel that they claim to represent signaling modules within SCMFs and used this panel for RT-PCR analysis. These data are used to generate an interaction network to evaluate signaling partners, co-effectors mediated by IGF1 signaling in SCMFs, other fibroblasts and alveolar epithelial cells. Using this GRN, the authors concluded that Wnt5a is a key signaling molecule downstream of IGF1 signaling that regulates alveologenesis.

While the authors' claims are salient, some of the conclusions were previously shown by others. For example, a role for Wnt5a driven Ror/Vangl2 has already been shown to be a key mediator of alveologenesis, by virtue of the same signaling effectors identified in this study (Zhang 2020 eLife). Additionally, the genetic loss of function studies performed here are not specific to SCMFs and instead they target broader alveolar and airway fibroblasts. The construction of a gene regulatory network is a potentially exciting tool, but this requires additional perturbations to distinct nodes identified in this work. It would be of particular interest to determine whether there is any redundancy among these nodes and what are the downstream effectors that are specific to each node. While I recognize that this is outside the scope of this work, the authors need to demonstrate the significance of at least one such node.

Reviewer #3 (Public Review):

This paper uses a unique approach to untangle the molecular mechanisms driving the pathogenesis of BPD. Strengths of the study include using a new genetic mouse model and the approach of applying gene regulatory networks to this model. There are, however, significant weaknesses in the study which make the conclusions weakly supported by the data. It is not clear that the markers the authors use to define "secondary crest myofibroblasts" are truly labeling a distinct cell population. The authors identify Pdgfra+/Igf+ or Pdgfra+/Igfr+ cells as defining this population by RNA ISH, but the images presented are not convincing and not rigorously quantified. At least two large single-cell transcriptomes of the developing mouse lung have been published in the last 12 months (Zepp et al, Cell Stem Cell 2021 and Negretti et al, Development 2021) and the examination of the expression of Igf1 and Igfr in specific myofibroblast populations over time should be explored, a method perhaps more specific and sophisticated than the whole-lung RTqpCR used in this paper. The use of Dermo1-Cre will drive mutant allele expression in all mesenchymal cells, not just SCMF. While Gli1 is a previously published marker of SCMF, does this marker have specificity in the context of newer single-cell transcriptomic datasets? In addition, there exist significant concerns about the rigor of this study, including a lack of information about the number of technical and biological replicates used. Moreover, whole lung qPCR is used on human lung as an attempt to validate these methods, however, there is no significant clinical data given about the patients from who this RNA was obtained (e.g., at what age did they die? from what cause? what gestational age were they born?). Given these significant concerns about the strength of the data to support these conclusions, the impact of this work is difficult to assess and diminished in scope.

Reviewer #1 (Public Review):

This study investigates the use of two-photon fluorescence lifetime microscopy (FLIM) with single-cell resolution for endogenous FAD+/NAD(P)H+ signals in polarized human macrophages in vitro as an approach to classification through machine learning. They perform parallel conventional analysis of secreted proteins and metabolomics to complement the FLIM measurements. They find that fluorescence lifetime parameters can be used to distinguish M1 and M2 macrophages in a population and particularly the response of the different populations to the metabolic inhibitor FCCP. The results are put in context with earlier work on the role of fluorescent metabolite environment and protein binding in the context of the metabolic data on FLIM parameters.

Reviewer #2 (Public Review):

Neto et al. use advanced two-photon FLIM to investigate human macrophages based on their autofluorescence (mainly coming from NAD(P)H. The main hypothesis is that different metabolic activities coming from human macrophages will aid in their classification in primary cells.

It is nice that the authors explain why they use a double exponential approach. I wonder however if the limited signal to noise and therefore high background allows for such a model. One should perhaps consider a triple exponential that also accounts for the noise? How do the authors deal with this limitation? Other labs have used in the past non-fitting approaches (i.e. Phasor plot). Have you considered employing this approach? If not, why? It seems that in this case, it would be a good implementation provided that the background and scattered photons might have different lifetimes as compared to the ones coming from NAD(p)H bound/unbound.

It will be of interest to check all parameters provided (both lifetimes and the normalised pre-exponential factors) versus the number of photons. Also, plot these in a pixel by pixel basis and present the corresponding histograms. According to the few images presented it seems clear to me that measuring autofluorescence could be a big problem, especially using such low magnification (see Fig. 3A and 4A) - By the way - Fig 4 is named Fig. 3 in the text. In these figures, one cannot see any changes when inspecting the pixel by pixel data. The changes in ps are minimal (also check the resolution of your figures, it is very difficult to check the legends and values).

It is interesting that one can employ Maniche learning to analyse the FLIM data, but one should be able to see clear differences in the average lifetimes when comparing different macrophage populations and the authors should show these pictures with the corresponding histograms and the number of photons.

When measuring autofluorescence (and noise) one needs to be very accurate and I commend the authors to produce all 2D plots showing the number of photons versus their lifetimes to check if there is no correlation between these two parameters. If this is the case (positive correlation) then all data is not correct.

Reviewer #1 (Public Review):

Due to the considerable free energy of base-pair formation, the rapid reorganization of RNA structure frequently requires protein-assisted dissociation of RNA strands (chaperoning), as they otherwise remain in kinetically trapped conformations. RNA helicases of the DEAD-box and related families have long been described to act in this context as ATP-fuelled single-strand RNA binding proteins, but mechanistic insight into how DEAD-box helicases can cause local RNA strand separation has been limited.

The present work demonstrates that the DEAD-box helicase DbpA can locally 'unzip' double-stranded RNA in the 5'-to-3' direction (starting from a short 5' single-stranded overhang fixed by RecA_C, with unwinding on/ by RecA_N, after closure of the domains), and it elegantly provides detailed molecular insight into this process (crystal structure snapshots along the pathway, validation by NMR techniques and evidence for conformational sampling, biochemical activity assays).

These results are remarkable because DbpA had previously been described to act on RNA duplexes preferentially in the 3'-to-5' direction (Diges and Uhlenbeck (2005); Biochemistry 44, 7903; information currently not mentioned in the manuscript) and because only for this latter direction of DEAD-box helicase action a mechanistic model had previously been suggested (Mss116p, Mallam et al., 2012, unwinding on/ by RecA_C (during domain closure?), less detailed overall). Moreover, also the translocating and processive DEAH-box helicases act in the 3'-to-5' direction, with fairly well understood mechanistic details (reviewed in e.g. Bohnsack et al., 2021, Biol. Chem. 402, 561, currently not mentioned in the manuscript).

However, the unwinding activity of DbpA observed in the manuscript requires very specifically constructed RNA substrates. Furthermore, the author demonstrates that DbpA is NOT preferentially recruited to junctions of double-stranded RNAs with 5'-single-stranded overhangs if the 5'-overhangs are sufficiently long to be accommodated on the composite RNA binding surface of RecA_N and RecA_C. The presented model starts nevertheless with the assumption that 'the RNA duplex is recruited to the transiently-formed, closed-conformation' (p.23, l.456 and Fig. 8). These limitations of the approach and of the resulting model could be pointed out to the reader as such much more explicitly, possibly also invoking auxiliary protein-targeting factors rather than just a stochastic process of binding 5'-junctions (p.24, l.491).

Also, a pre-orientation of the RecA_N and RecA_C domains by auxiliary factors in the natural context (with examples from other helicases) may be considered in the discussion (rather than only a random tumbling of the RecA_N domain, p.23, l.454). In particular, it would be interesting here how the author now mechanistically interprets his previous observation (Wurm et al., 2021) that DbpA is strongly stimulated to act on substrates 'in trans', if the HP92 hairpin contains 6-12 nt of 5' single-stranded overhang 'in cis'. Could these nucleotides potentially pre-occupy the composite RNA binding surface? This data is currently not mentioned in the manuscript.

Finally, the proposed model is presented as 'the' general mode of action for DEAD-box helicases, whereas even for the very specialized DbpA, with its requirement to bind the HP92 hairpin, the precise natural RNA targets are unknown and unzipping in the 5'-to-3' direction may be a minor mode of action. A more balanced and extended discussion is warranted here, including the difference between translocating DEAH helicases and locally unwinding DEAD (DExD) helicases, the question of directionality and role auxiliary factors, and the explicit reference to data (see the specific points) which is not currently explained by the presented model and potentially in conflict. It may be useful to present some of these questions and references already in the introduction, such that also less specialized readers can better appreciate where and to which degree the present work provides previously unknown molecular details and conceptual novelty.

From a technical point-of-view, the work is very solid and represents an enormous tour-de-force, especially considering that this is presented as a single author work. The methods, although rather specialized, are sufficiently well described to be followed by a broader audience, and the illustrations and cartoons are very clear and consistent. The text is generally easy to follow, although occasionally some of the phrasing can be improved for clarity.

Reviewer #2 (Public Review):

The manuscript by Jan Philip Wurm structurally characterizes a long sought after catalytic intermediate of RNA double strand melting by an ATP-dependent RNA helicase of the DEAD-box family. These enzymes are the most abundant class of RNA remodelling enzymes and have essential functions during RNA metabolism throughout all organisms. In the past several structures of unwound single stranded (ss) RNA products bound to DEAD-box helicases together with intermediates of the coupled ATP hydrolysis reaction have been solved. However, it remained elusive how these enzymes bind and destabilize the double stranded (ds) RNA starting material. This knowledge gap is now closed with the current paper. The author exploits the fact that the enzmye DbpA from E.coli contains a specific RNA binding domain fused to the central helicase (RecA) domains, which facilitates stable RNA substrate binding. This set-up allows co-crystallization of several RNA substrates with ds or ss sections together with the helicase bound to the ATP-analog ADP-BeF3, and several well resolved crystal structures are obtained.

The substrate-bound structure shows that the helicase binds to the ss-dsRNA junction contacting the backbone of 3 ss and 3 ds nucleotides (nts), maintaining a continuously stacked conformation of the RNA bases that is compatible with a hybridized dsRNA. This structure provides a molecular explanation for the long-established preference and increased activity of many DEAD-box helicases on dsRNAs with short ssRNA overhangs. The author then shows that indeed also DbpA yields higher helicase activity on overhang-containing substrates, but that after an optimum, further increases in overhang length reduce unwinding rates again. Given that 3 ss nts were consistently found to be bound by DbpA, it would be interesting to see whether such substrates would actually give an even higher helicase activity than the tested 2 ss nt overhang substrate.

Another structure with a ssRNA product is elucidated for comparison. It shows the same unwound conformation of ssRNA with a contorted backbone that is incompatible with ds hybridization, which has in the past been observed in several other RNA-bound DEAD-box helicase structures. The main difference to the dsRNA substrate lies in the binding of nts #5 and #6 which are flipped out of the base stacking conformation. Interestingly, in three of the six protomers crystallized per assymmetric unit the ssRNA takes up the same stacked conformation as in the ds substrate bound state. This observation could indicate an intrinsic binding flexibility for both RNA conformations in DbpA. However, it would be important to show that the RNA in this region is not involved in crystal packing in any of the three structures, which could influence/distort its spatial arrangement.

Finally, EPR measurements are used to show that DbpA also samples the catalytically active, closed conformation in absence of bound ATP(-analoga) and substrate RNA, which could indicate that a preformed active state can even exists before ATP/RNA binding.

Where the paper is currently falling a bit short is in explaining why the double stranded portion of the RNA should melt. Where does the energy come from? This is one outstanding question, that was not possible to answer in the past without the current structural information. The suggested passive "fraying" is vague and not fully convincing. Just because ATP binding/hydrolysis can happen in the presence of already ssRNA ("futile cycle") this does not mean that the distorted/unstacked binding mode of ssRNA is not induced upon ATP binding/hydrolysis. Actually, one could argue to the contrary, that the high ATPase rates in the presence of ssRNA are suggesting that ssRNA poses less "resistance" to the coordinated motions that have to occur in the RNA and ATP binding sites to yield triphosphate binding/hydrolysis together with the distorted RNA conformation, thus making this state energetically more favorable and more populated (=higher kcat).

Here, a more extensive comparison of available DEAD-box helicase structures from different states of the catalytic cycle could potentially be instructive (with a focus on the coordination environment of the RNA backbone for nucleotide 5 and its connections/relay to the ATPase active site). Furthermore, a comparison of binding affinities for different RNA species (e.g. ssRNA, dsRNA with 0/1/2/3nt ssRNA overhangs) in the presence of different ATP hydrolysis intermediate analoga (ADP-BeF3, ADP+PO4, ADP+vanadate, ADP) would be useful.<br /> Importantly, throughout the paper is a joy to read, it shows carefully controlled experiments with high quality data that is concisely described and clearly illustrated. The subject matter is highly interesting for a wide range of biochemists, and structural biologists, and of fundamental importance for RNA biology.

Reviewer #3 (Public Review):

Using NMR a non-hydrolysable ATP analogue is identified that can stall substrate complexes. Then the author reports crystal structures with a hairpin substrate complexes and a single-stranded product complex all attached to the HP92 RNA that he has previously shown to be recognized by the RRM and one of the RecA domains. By comparing the crystallographic structures with previously reported structures very similar conformations are observed. However, two types of closed single-stranded substrate conformations are seen which suggests a mechanism of RNA substrate binding and unwinding coupled to ATP hydrolysis. The role of 5' single-stranded overhang regions is explored by biochemical activity assays as a function of 5' overhang. Finally, using RNA substrate spin labelled at two positions NMR PREs observed are consistent with transient samples of the substrate-bound closed structure already in the absence of nucleotide.

The work is technically sound and reports an interesting combination of crystallographic structures, supported by biochemical activity assays and NMR to identify transient interactions. The conclusions are well supported by the data shown. An interesting model is proposed for unwinding mechanisms by RNA helicases depending on 5' single-stranded overhangs, that may be of more general relevance.

Reviewer #1 (Public Review):

In this study, the authors used tracing/c-fos tagging/chemogenetic methods to perform a brain-wide screen of engram cells in the prelimbic cortex (PL) and identified specific activity patterns of these inputs across different phases of fear memory consolidation. The magnitude of the data set per se is remarkable. The data are well controlled and adequately analyzed. Projection-specific chemogenetic inhibition confirmed and extended previous studies by exposing the contribution of the claustrum and insula to PL inputs during encoding and recall of recent memory, respectively.

Reviewer #2 (Public Review):

While systems memory consolidation theory tends to categorize regions that are involved in memory acquisition and early recall vs regions involved at a later time point, recent evidence showed that regions known to be active at a remote time point, like the medial prefrontal cortex, may be involved also at an earlier stage. In this manuscript from Dixsaut and Gräff, they aim to dissect mPFC engrams connectivity and identify differences between early and later involvement. They found interesting and novel results that are essential to further unravel the role and time-dependent implication of different pathways linked to the mPFC in regulating memory consolidation. Interestingly here they focus specifically on engram cells instead of targeting all mPFC cells. This aspect is significant since these are cells that are believed to have a crucial role in memory acquisition and its following reactivation.

In particular, they analyzed several connecting regions that send projections to PL engram cells. Some (BLA, CLA and EC) active at encoding, some (RSP and INS) at recent memory recall. They further targeted these cells and inhibited them using chemogenetic manipulation during encoding (BLA,CLA and EC cells projecting to PL) or recent memory recall (RSP and INS cells projecting to PL). Via a well-designed and technically impressive analysis of this complex subnetwork linked to PL, the authors found a time-dependent implication of different projections bringing a new perspective on the role of PL engram cells in memory consolidation.

Overall, this manuscript represents a novel discovery that can bring to a constructive re-evaluation of the mPFC role in memory consolidation.

Reviewer #3 (Public Review):

Activity in the prelimbic cortex following an aversive event is necessary for subsequent remote retrieval of the consolidated fear memory weeks later, but the circuits supporting the gradual reorganization of memory into cortical circuits are not well understood. In this study, Dixsaut and Graff examined how certain subcortical and cortical inputs to the prelimbic cortex contribute to the establishment of memory-related neuronal ensembles at encoding and two retrieval timepoints. The results confirm recent reports that certain PL inputs, such as the basolateral amygdala and entorhinal cortex contribute to the consolidation of remote contextual fear memories, but also identify novel contributions for the claustrum and insula during encoding and retrieval respectively.

The strengths of this paper include the systematic, data-driven approach to identifying and testing relevant inputs. The use of TRAP2 mice offers advantages over previous cfos-based tagging approaches and is a powerful approach to map only those inputs that directly innervate experience-activated prelimbic cells. Through this approach, several expected and new inputs were revealed. The authors then followed up on two of these novel inputs to test their role in memory encoding and retrieval. The data reporting and presentation are transparent and thorough. While the technical and analytic aspects of this study are very strong, some core claims of this study are not fully supported by the data.

The core claims:<br /> 1) That neuronal ensembles after CFC training represent an associative engram. The comparison is a context exposure no-shock group, which doesn't control for an aversive experience independent of learning. Moreover, the PL is also implicated in the consolidation of a latent context memory, as shown with the context pre-exposure effect (e.g., work by Stanton and colleagues: Heroux et al., 2017; Robinson-Drummer et al., 2017). The cfos activation patterns in this study may thus represent contextual memory formation and/or contextual fear memory formation, but may also reflect aversive reactivity or attentional arousal. The observation of an ensemble reactivation-to-freezing correlation only in CNO groups (Figure 5) could reflect a contribution of these inputs to non-associative features, such that the removal of these inputs refines the relationship of the reactivated ensemble to behavior.<br /> 2) That the indicated inputs are "necessary" for consolidation. First, the reduction in freezing as a consequence of input inactivation is relatively modest, demonstrating a modulatory impact rather than necessity, and one consistent with a potential role in non-associative or aversive valence aspects of memory. Second, the lack of effect of input removal on the ensemble re-activation itself by the removal of CLA or INS inputs does not support a necessary role in ensemble formation or reactivation. Post-training inactivation of CLA-PL also did not affect engram formation, which is a timepoint where PL ensemble activation contributes to CFC consolidation and remote engram formation (DeNardo et al., 2019). These observations in the current study suggest that CLA input to PL modifies subsequent retrieval but does not support a necessity for this pathway in consolidation.<br /> 3) Related, the interpretation that INS-PL affects consolidation is not strongly supported since the manipulation and assessment of behavior occurred in the same retrieval session, suggesting an effect on retrieval, not consolidation. Because systems consolidation requires prefrontal activity within the first 1-2 weeks of training regardless of retrieval, determining which inputs to PL after training affected the development of remote ensembles would provide a stronger case for consolidation of relevant inputs.

Reviewer #1 (Public Review):

The enteric nervous system (ENS) mediates gut motility and secretion, and recent work has shown that molecular crosstalk between enteric neurons and macrophages regulates ENS homeostasis and function. This study finds a novel role for complement C1q in this crosstalk. Complement plays a key role in immune defenses against pathogens, and has also been shown to play a key role in synaptic pruning in the central nervous system (CNS) during development, where it is expressed by microglial cells. However, the role of myeloid-derived complement components in ENS function is unknown. In this study, Hooper and colleagues reveal a novel role for C1q in mediating enteric neuron-macrophage crosstalk. First using targeted analysis of different cell-types, they reveal that C1q components (C1qa, C1qb, C1qc) are mainly expressed by subepithelial immune cells, and in particular intestinal macrophages (CD11b+MHCII-F4/80hi). Elimination of macrophages using anti-CSFR1 led to decreased C1q. C1qafl/fl conditional mice were crossed with LysM-Cre to eliminate its expression in myeloid immune cells. This led to loss of C1q in the gut as well as other peripheral tissues but not the brain. Next, the authors find that loss of C1qa from macrophages led to no changes in microbiome composition, gut barrier permeability, susceptibility to DSS induced colitis, or Citrobacter rodentium infection. The immune populations in the gut were also not majorly affected. Imaging showed that C1q macrophages were mainly in submucosal plexus and located next to nerves. RNAseq showed changes in neuronal gene pathways related to synaptic organization in the associated tissues from C1q macrophage KO mice. Functionally, the authors then found that several measures of gut motility showed dysregulation, with faster transit time by carmine red, rhodamine B transit assay, a peristalsis assay, and colonic bead expulsion. Thus macrophage expressed C1q regulates peristalsis and neuronal function in the gut.

This is an exciting study that reveals a novel role for complement in regulating macrophage-neuron crosstalk and gut motility. Strengths include the use of interdisciplinary assays to first identify the cell-type that produces C1q, and then determine that this loss does not affect certain measures (microbiome composition, colitis, infection susceptibility), but does affect other measures (neuronal gene expression and gut motility measures). One remaining question is how C1q affects the nervous system, and a better characterization of neuronal composition or structure would be needed to rule in or rule out a mechanism.

Reviewer #2 (Public Review):

1. The manuscript is well-written, the data is of high quality and presented in a very logical manner.<br /> 2. The data demonstrating the motility defect in Lyz2-Cre:C1q-fl/fl mice is convincing.<br /> 3. The results supporting the conclusion that intestinal macrophages are the major source of C1q are strong.<br /> 4. The conclusion that C1q is mostly expressed by ENS-associated muscularis macrophages but not mucosal macrophages is not fully supported by the data.<br /> 5. Although comparison of the gene expression in Lyz2-Cre:C1q-fl/fl mice and control mice predicts changes in the ENS development and/or function, there is no data that would identify an ENS cell type(s) directly targeted by C1q and demonstrate their functional change (either in vivo or in vitro). This makes the conclusion of the direct link between macrophage-derived C1q and regulation of the ENS function questionable.

Reviewer #3 (Public Review):

This manuscript by Pendse et al aimed to identify the role of the complement component C1q in intestinal homeostasis, expecting to find a role in mucosal immunity. Instead, however, they discovered an unexpected role for C1qa in regulating gut motility. First, using RNA-Seq and qPCR of cell populations isolated either by mechanical separation or flow cytometry, the authors found that the genes encoding the subunits of C1q are expressed predominantly in a sub-epithelial population of cells in the gut that Cd11b+MHCII+F4/80high, presumably macrophages. They support this conclusion by analyzing mice in which intestinal macrophages are depleted with anti-CSF1R antibody treatment and show substantial loss of C1qa, b and c transcripts. Then, they generate Lyz2Cre-C1qaflx/flx mice to genetically deplete C1qa in macrophages and assess the consequences on the fecal microbiome, transcript levels of cytokines, macromolecular permeability of the epithelial barrier, and immune cell populations, finding no major effects. Furthermore, provoking intestinal injury with chemical colitis or infection (Citrobacter) did not reveal macrophage C1qa-dependent changes in body weight or pathogen burden.

Then, they analyzed C1q expression by IHC of cross-sections of small and large intestine and find that C1q immunoreactivity is detectable adjacent to, but not colocalizing with, TUBB3+ nerve fibers and CD169+ cells in the submucosa. Interestingly, they find little C1q immunoreactivity in the muscularis externa. Nevertheless, they perform RNA-sequencing of LMMP preparations (longitudinal muscle with adherent myenteric plexus) and find a number of changes in gene ontology pathways associates with neuronal function. Finally, they perform GI motility testing on the conditional knockout mice and find that they have accelerated GI transit times manifesting with subtle changes in small intestinal transit and more profound changes in measures of colonic motility.

Overall, the manuscript is very well-written and the observation that macrophages are the major source of C1q in the intestine is well supported by the data, derived from multiple approaches. The observations on C1q localization in tissue and the strength of the conclusions that can be drawn from their conditional genetic model of C1qa depletion, however, would benefit from more rigorous validation.

1 - Interpretation of the majority of the findings in the paper rest on the specificity of the Lyz2 Cre for macrophages. While the specificity of this Cre to macrophages and some dendritic cells has been characterized in the literature in circulating immune cells, it is not clear if this has been characterized at the tissue level in the gut. Evidence demonstrating the selectivity of Cre activity in the gut would strengthen the conclusions that can be drawn.

2 - Infectious and inflammatory colitis models were used to suggest that C1qa depletion in Lyz2+ lineage cells does not alter gut mucosal inflammation or immune response. However, the phenotyping of the mice in these models was somewhat cursory. For example, in DSS only body weight was shown without other typical and informative read-outs including colon length, histological changes, and disease activity scoring. Similarly, in Citrobacter only fecal cfu were measured. Especially if GI motility is accelerated in the KO mice, pathogen burden may not reflect efficiency of immune-mediated clearance alone.

3 - The evidence for C1q expression being restricted to nerve-associated macrophages in the submucosal plexus was insufficient. Localization was shown at low magnification on merged single-planar images taken from cross-sections. The data shown in Figure 4C is not of sufficient resolution to support the claims made - C1q immunoreactivity, for example, is very difficult to even see. Furthermore, nerve fibers closely approximate virtually type of macrophage in the gut, from those in the lamina propria to those in the muscularis. Is the 5um average on the proximity analysis any different for other macrophage populations to support the idea of a special relationship between C1q-expressing macrophages and neurons? There are many vessels in the submucosa and many associated perivascular nerve fibers - could the proximity simply reflect that both cell types are near vessels containing C1q in circulation? Finally, the resolution is too low to rule out C1q immunoreactivity in the muscularis externa.

4 - A major disconnect was between the observation that C1q expression is in the submucosa and the performance of RNA-seq studies on LMMP preparations. This makes it challenging to draw conclusions from the RNA-Seq data, and makes it particularly important to clarify the specificity of Lyz2-Cre activity. Finally, the pathways identified could reflect a loss of neurons or nerve fibers. No assessment of ENS health in terms of neuronal number or nerve fiber density is provided in either plexus.

5 - To my knowledge, there is limited evidence that the submucosal plexus has an effect on GI motility. A recent publication suggests that even when mice lack 90% of their submucosal neurons, they are well-appearing without overt deficits (PMID: 29666241). Submucosal neurons, however, are well known to be involved in the secretomotor reflex and fluid flux across the epithelium. Assessment of these ENS functions in the knockout mice would be important and valuable.

5 - Immune function and GI motility can be highly sex-dependent - in all experiments mice of both sexes were reportedly used but it is not clear if sex effects were assessed.

Reviewer #1 (Public Review):

Pinskey et al. examine the cilia from the closest unicellular relatives to metazoans, the choanoflagellates. Previous cilia structures come from more distantly-related organisms outside of the opisthokont clade or multicellular metazoans. As such it is not clear whether features that distinguish metazoan cilia, such as central pair shape or dynein motor number in the outer arm dyneins, are a natural consequence of the shift to multicellularity. The authors reveal the ultrastructure of Salpingoeca rosetta, using a combination of cryo-FIB milling and cryo-ET to great effect. Their doublet microtubule and central pair complex structures show that these unicellular organisms contain many of the hallmarks of metazoan cilia, in terms of attached protein densities. The authors identify unique MIPs and features, such as holes in the microtubule lattice. In addition they describe other unique features of these cilia, notably the striking ciliary vane and barb structures. Their data support their conclusions. The findings presented will interest multiple fields, namely the cilia field, evolutionary biologists working on the origin of multicellularity, and structural biology.

Strengths:

The authors use a series of excellent reconstructions to show convincingly that cilia from the choanoflagellate S. rosetta have many of the hallmarks of metazoan cilia. This is followed by a good description and analysis of the shape and distribution of the rail-MIP and microtubule lattice hole, which are both unique in this structure. In their discussion they hypothesise that the reduction of structural ciliary components seen in multicellular metazoans, compared with cilia of other unicellular organisms, reflects a transition from a requirement for a strong ciliary beat in a harsh open environment to beating in a more protected environment with fewer shear forces. They demonstrate that S. rosetta sit in the middle in terms of structural reduction, supporting this hypothesis. They also provide an excellent description of both the ciliary vane and barb structures found on S. rosetta.

Weaknesses:

The data presented here is, on the whole, descriptive. Whilst the descriptive elements are strong and important, more analysis and quantification is required to support the conclusions made in the paper. For example, in contrast to their analysis of the rail-MIP, their assertion that the ciliary vane orientation is linked to the CPC orientation is not backed up by quantification. In addition, this paper does not extensively discuss proteins within the MIP densities and central pair complex in detail, to the extent they can be discussed using the recent structures from Chlamydomonas.

Reviewer #2 (Public Review):

This is a lovely study that documents the structure of the flagellum of the choanoflagellate S. rosetta using cryo-electron tomography. The authors have generated an extensive dataset of 54 cryo-electron tomograms, collectively covering >7500 axonemal repeats that were used to generate an average structure. Doing so, they come at a number of novel insights, such as an interestingly animal-like structure for outer dynein arms and radial spokes, the presence of a flagellar vane (known in other choanoflagellates but seen for the first time in S. rosetta), and the discovery of two entirely new structures (barb structures and a "rail-MIP" (Microtubule Inner Protein)). This will be of broad interest to people interested in cilia/flagella and in eukaryotic/metazoan evolution.

Reviewer #3 (Public Review):

The ultrastructural details of eukaryotic cilium/flagellum architecture have been described in unprecedented resolution in a number of recent cryo-electron microscopy studies. These studies have however focused on a limited number of taxa, and there remain significant gaps in our knowledge to date. In particular, while there have been studies on the cilia of animals (which belong to the Opisthokonta clade) and those of unicellular eukaryotes such as algae and trypanosomes, there has to date been no examination of the cilia of unicellular opisthokonts. Pinskey et al. address this gap by examining the ciliary ultrastructure of choanoflagellates, single-celled organisms that are closely related to sponges.

In this paper, Pinskey et al. document the arrangement of structures in the 96-nm axonemal repeat, noting the similarities and differences with available structures from other taxa. The outer dynein arms, inner dynein arms, radial spokes, microtubule inner proteins and central pair complex are all described closely.

They additionally present a preliminary architecture of the ciliary vane, a brushlike arrangement of filaments outside the cilium that is thought to be involved in generating fluid flows to facilitate feeding. Pinskey et al. also discover the existence of "barbs", four-legged structures studded on the surface of the ciliary membrane, and which may be involved in the generation or maintenance of the ciliary vane.

The methods employed are cutting-edge, and the quality of the data is high, as is its presentation. The work undoubtedly fills a taxonomic gap in our knowledge of the ultrastructure of eukaryotic cilia, and given the choanoflagellates position on the boundary between unicellular/colonial and multicellular life, this will be a very valuable reference point for future studies.

Reviewer #1 (Public Review):

In this study the authors have investigated the modulation of auditory coding in the mouse auditory cortex related to the shift of attention between sounds and visual stimuli in a sensory discrimination task.

They employ a previously developed behavioral paradigm, which was used to investigate the same question in the mouse visual cortex. Mice most of the time receive both sounds and visual objects to guide their decision but the task alternates between blocks where sounds are informative and blocks where vision is actually informative. Multielectrode recordings are used to probe the activity of auditory cortex neurons during task performance. These recordings evidence that despite a large variety of effects in cortical neurons, overall the population is inhibited during the attentional shift towards sounds. This effect is similar to what is observed during task performance, if compared to non-engaged, passively listening animals. However this paper is the first one to demonstrate the effect during a real attentional shift independent of engagement. It is also interesting that despite lower firing rates the level of information stays the same, indicating that attention renders cortical activity more specific. Finally one important results is the fact that attention impacts activity outside the stimulus window, pointing at a network state change, rather than a focally targeted effect.

The results are solid and detailed. The analysis across layers and spike waveform types is appreciable. One may regret that no population analysis is done as maybe some results can be buried in the noise of single neurons. Yet, the present analysis is sufficient for the conclusions drawn.

One analysis seems to be missing however to connect these results with other studies. The authors have not really analysed modulation with respect to tuning. Are the neurons specifically tuned to one of the two expected stimuli modulated in a direction different from the rest of the neuronal population? If so this could reconcile the present findings with studies which found that attention boosts stimulus response.

Reviewer #2 (Public Review):

This paper will be of interest to neuroscientists studying mechanisms of selective attention, and those interested in how active listening shapes auditory processing. Animals are engaged in an across modality task switching paradigm with the key result being that actively attending to sounds causes widespread suppression in auditory cortex.

In this study mice are trained in a modality-switching task, learning a simple go-no go paradigm with sounds (high versus low frequency tone clouds) and visual stimuli (the direction of moving gratings). Both tasks are clearly suprathreshold (when unisensory) and performed to a high level in both unisensory blocks and in blocks where both modalities are presented, with the to-be-attended modality cued by the modality of the preceding unisenory block. Impressively, the mice can switch between modalities within a session, allowing the authors to examine single unit responses to both selective attention conditions.

Single unit activity is recorded across the cortical depth during task performance. The across-modality attention switching allows the same sensory stimuli to be presented in two contexts - one in which it is to be ignored, and the other in which it is to be attended. This raises this study above previous attempts to understand how active listening shapes cortical processing, where the comparison is animals doing a task to those not doing a task - here in both cases the animal is actively engaging with stimuli, motivated to perform a task and being rewarded for doing so.

A decoding approach is used to determine how well the two acoustic categories can be distinguished in both attend-a and attend-v conditions. Their key finding is that overall activity is suppressed in auditory cortex during attention to sounds. This confirms and builds on several previous studies that reached the same conclusion by comparing neural activity during passive listening and active task performance. The authors extend these findings taking an information theory approach to ask whether neural responses remain equally informative in both conditions, and using an 'information per spike' metric of efficiency demonstrate that a subpopulation of neurons in the deeper layers become more efficient in their representation of information (that is, they convey equivalent information with fewer spikes).

Overall the work included is technically demanding and performed to a high standard. I was surprised that the population of neurons in deep auditory cortex in which firing rates and information content increased were excluded from subsequent analysis with the authors choosing to focus on the 'efficiency' improvement in the suppressed population. I would like to see the analysis in figure 8, which seeks to link changes in firing rate to behaviour, repeated for this population. An alternative explanation (that is potentially supported by the observation in S1 that the firing rate changes are driven mostly by untuned neurons) is that during attention relevant neural populations are enhanced such that their activity is better read out and that homeostatic mechanisms act to suppress other, less informative, activity. It seems likely the authors have the data to rule this in or out.

I would like to see the behavioral data presented in a way that better demonstrates how well the mice were selectively attending to the relevant modality. Figure 2 presents the overall performance (d') on this task, which seem robust. However, in figure 8 a more careful analysis of the false alarm rates to the AuVr stimulus (which in the attend-a condition is really the most critical condition to confirm that the animals are performing a selective attention task and not dividing their attention across modalities) look really very high (near 100% in some sessions). I might have missed it, but I couldn't find any information about the distribution of trial types. If they are not equiprobable (i.e. there are fewer of the conflict trials) then overall d' is a poor measure of selective attention. Rather than an overall d' criterion for performance one that assesses the ability of the animal to selectively attend - such as the false alarm rate on the AuVr attend-a and ArVu on the attend-v - would be more appropriate. In figure 8 it would be helpful to know how the data are ordered - by mouse? I think the conclusion we're meant to take away from figure 8 is that increased firing rate predicts lapses of attention. However enhanced firing could indicate higher arousal and therefore intention to lick. A comparison of correct reject trials and hit trials as well as the hits/fa analysis included would be meaningful here to see whether this is a (pre) motor effect or an attentional effect.

The paper relies heavily on Wilcoxon rank sum tests without any multiple comparisons correction. Often the p values are very small and therefore the lack of correction is inconsequential however there are exceptions. Specifically, this is problematic, especially for the pupillometry section where the AVv_v comparison would not survive multiple comparisons (unlike the Ava_a comparison its range includes zero). This begs the question as to whether the significant effect on pupil size simply comes about from the presence of visual stimulus rather than the AV conditions. There is also no justification provided for why this is a one-tailed test.

Reviewer #3 (Public Review):

The authors measure modality-specific and modality unspecific attentional influences in the various layers and in putative inhibitory and excitatory neurons in the primary auditory cortex of mice.

The authors find that attention to the auditory stimuli specifically decreases responses in the deep layers and that this decrease predicts behavioural accuracy during modality-specific (auditory) attentional task.

The methodology used is rigorous and the authors document technically in a proper way their main findings. However, it is difficult to provide a mechanistic value to the main findings, in relation to how they are interpreted. Enhancement of sensory responses has been reported in association sensory areas (e.g. V4, Reynolds, Pasternak and Desimone, 2000), and normalization mechanisms possibly involving activation of inhibitory circuits are involved in attentional modulation of sensory responses in primary areas (work of Maunsell, 2017).

The authors should make an effort to put their findings in the biological context provided by the literature on attentional mechanisms affecting cortical sensory processing, and provide a more explicit interpretation of some of their critical findings in relation to the role of attentional mechanisms:

- How do they interpret the finding that deep layer suppression is modality specific? Why paying attention to the visual stimulus is not affecting auditory responsiveness in the same way? Indeed, the authors report that the spike reductions (occurring also during pre-stimulus) correlate with performance in acoustic but not in visual attentional tasks.

- What is the functional meaning and the interpretation that these findings extend also during the intertrial periods (upon presentation of task-irrelevant stimuli)? it would be important to clarify how these findings are consistent with modality and task-specific attentional mechanisms.

Reviewer #2 (Public Review):

The authors performed epidemiological investigations, whole-genome sequencing (WGS) SARS-CoV-2 isolates, and sophisticated modeling to identify the likely SARS-CoV-2 transmission routes in a large geriatrics hospital. They found that HCW-to-HCW transmission in Covid wards was not higher than expected but the risk of transmission between HCWs in non-Covid wards was two-fold higher than expected. They also identified excess patient-to-patient transmission events, most of which occurred within the same ward, but not necessarily in the same room. Finally, they found that most transmission events were related to HCWs, but at least one was related to a patient with community-acquired Covid-19. This study provides information that is helpful to infection prevention programs that are trying to prevent the spread of SARS-CoV-2 within hospitals, especially in geriatric hospitals. The strength of the study is that the authors combined standard epidemiological investigations with sophisticated WGS and mathematical modeling. They also stress that WGS is not necessary to control spread but was important for assessing how SARS-CoV-2 was spread. The primary limitation was that the study was done at one hospital early in the pandemic so the results may not be generalizable to other hospitals later in the pandemic.

Reviewer #1 (Public Review):

The authors combine genomic data, time of infection and ward sharing to identify nosocomial transmission events and reconstruct probable routes of transmission among patients and healthcare workers who work on either dedicated Covid-19 wards or on non-Covid-19 wards which nevertheless experienced an outbreak. Among their findings were that HCWs in Covid wards were less likely to transmit to their colleagues while those in outbreak wards were more likely to do, and patients with nosocomially acquired Covid-19 were more likely to be a source for other patients. They also find that inter-patient transmission was driven by ward-sharing but not necessarily room-sharing.

Strengths and weaknesses:

The work makes use of both epidemiological and genetic data, combining them using a robust Bayesian approach and using them to address meaningful questions. The basic methodology and dataset are identical to a previous study by the same authors ("Explosive nosocomial outbreak of SARS-CoV-2 in a rehabilitation clinic: the limits of genomics for outbreak reconstruction", Abbas et al. J Hosp Infect 2021). However, they address original relevant questions.

Given what we know about close proximity as a risk factor for transmission, it is unfortunate that the intriguing result that room-sharing does not contribute much more to transmission than ward-sharing could not be examined in greater detail, taking into account the closeness of beds and actual patient interactions, such as through contact tracing. Similarly, analysis or discussion on the impact of sampling policies evolution over time and possible uncertainty regarding individual information such as dates of symptoms are lacking.

The results are supported by the data and analysis performed, with appropriate levels of uncertainty.

This is a very clear article that presents important results. Indeed, despite the very high level of SARS-CoV-2 nosocomial circulation in long-term care facilities over the past two years, studies investigating transmission routes and quantifying transmission strength are still very limited. This paper quantifies the relative risks arising from different hospital relationships which are relevant, particularly for medical professionals and those making decisions about infection control. Principal results of interest include that cases appearing in wards not dedicated to Covid-19 are more risky, and they add emphasis to the risk of an index case to all patients on the ward, not just the room. Furthermore, they demonstrate that genomic data, even in a relatively slowly evolving pathogen, can be utilised in gaining insight into hospital transmission, which will motivate more extensive collection and analysis of genomic data. It is unfortunate that repeating such an analysis would not be possible in most hospitals where sequencing viral genomes have not been possible or prioritised.

Reviewer #3 (Public Review):

The paper by Abbas et al (2022) investigates the transmission chains of SARS-CoV-2 infections in four Swiss geriatric hospital wards that were affected by SARS-CoV-2 outbreaks. Using a Bayesian framework, the authors studied transmission patterns according to different types of cases (healthcare workers in COVID or non-COVID wards, patients with hospital-acquired infections) and the role of healthcare workers in the transmission process. The authors were able to reconstruct the transmission chains of the outbreak in the considered wards (with some uncertainty) and showed that HCWs experienced a higher risk of transmission in non-Covid wards in comparison with Covid wards.

The strength of the study is that the authors combined epidemiological and genetic sequencing data from patients and HCWs to study the transmission chains in the affected hospital wards. Using a Bayesian modelling framework, they were able to reconstruct the transmission chains and present their estimates in form of distribution (instead of only single values) and therefore quantify uncertainty in their results.

The coverage of their genetic sequencing was high, i.e., 82% of individuals who tested positive in the study were also sequenced. In addition, the authors had data on ward/room presence for patients and whether HCWs worked on COVID-wards or non-COVID wards. The authors used this information to substitute the missing contact data. The outbreaker2 package allowed for uncertainties in contact patterns by allowing non-infectious contacts to occur and incomplete reporting of contacts.

Since the authors used specific data from a Swiss university-affiliated geriatric acute-care hospital from the first COVID-19 wave without detailed data on contact patterns or adherence to IPC measures, it remains unclear how their results and conclusions may generalize to other settings and future COVID-19 waves. While their results on the higher risk of within-ward transmission in non-COVID wards are interesting, their proposition on differential HCW behavior remains hypothetical without respective data.

Abbas et al (2022) demonstrated how epidemiological and genetic sequence data can be combined and analyzed using the outbreaker2 package. Since they used the already existing open-source outbreaker2 package, their study is a good example for others to reconstruct outbreaks in other settings. In addition, it indicates where infection prevention strategies may need to focus and highlights the gaps in contact data information for healthcare settings.

Reviewer #1 (Public Review):

Pan et al. examined the role of oligodendroglial exocytosis, and specifically the role of L-type prostaglandin D synthase (LPGDS), in modulating oligodendrocyte differentiation and myelination. The topic of autocrine and paracrine signaling within the oligodendrocyte lineage is under-studied and the authors use a novel approach for oligodendrocyte precursor-specific inhibition of VAMP-mediated exocytosis using inducible expression of botulinum toxin with the PDGRFa-CreER transgenic mouse line (PD:ibot). Using a combination of in vitro culture systems and immunohistological analysis in vivo, the authors find ibot expression in OPCs leads to reduced oligodendrogenesis and myelination, leading to a behavioral deficit in rotarod performance. Additional transcriptomic analysis in PD:ibot mice revealed Ptgds, the gene encoding LPGDS, was significantly overexpressed in both mature oligodendrocytes and OPCs. Further pharmacological experiments with cultured OPCs showed direct LPGDS inhibition led to a similar inhibition of oligodendrogenesis as PD:ibot mice. Together, this study reveals VAMP-mediated exocytosis in OPCs is required for normal oligodendrogenesis and identifies LPGDS as a new chemical regulator of oligodendrocyte myelination. These findings are strengthened by careful characterization of the PD:ibot mouse line and effective use of culture systems and pharmacology to uncover a cellular mechanism. Quantification is performed at several levels of resolution using immunohistochemistry, electron micrography, and protein/transcriptomic analyses and control experiments were largely carefully considered.

Despite these strengths, there are some points that need to be further addressed. The interpretation of autocrine/paracrine signaling relies on a critical culture experiment in which PD:ibot OPCs were cultured in the presence of PD:ibot or control OPC well inserts. However, these results had a marginal effect size, raising questions as to the extent to which VAMP inhibition specifically had effects through the blockade of exocytosis (resulting in an autocrine/paracrine signaling deficit) or inhibited oligodendrogenesis in a cell-intrinsic mechanism (e.g. VAMP-dependent trafficking of critical myelination components, such as PLP (Feldmann et al., 2011)). Additionally, the authors claim the reduced number of oligodendrocytes in PD:ibot mice in vivo is not due to oligodendrocyte apoptosis and provide evidence by cleaved caspase-3 immunostaining of the cerebral cortex. While statistically not significant, the data is highly variable. If true, this would suggest oligodendrocyte differentiation is inhibited, which would coincide with a reduction of OPC proliferation. A complementary experiment comparing the rates of OPC proliferation between control and PD:ibot mice in vivo would provide further clarity on how oligodendrocyte density is being reduced. The relevance of these myelination deficits is assessed with a rotarod assay, however, the mice used for these experiments are several times older (2-5 months) than those used for all other histological quantification (P8-P30). The large variance in results could be due to age-related differences in myelination, and it is unclear whether the deficits at early timepoints show a linear progression with age.

Reviewer #2 (Public Review):

The report employs an oligodendrocyte botulinum B toxin transgenic mouse line by which they are able to perturb vesicular release in a cell-specific manner. Using this mouse line the authors contend that disrupting VAMP in this ibot mouse line is evidence for vesicular release from oligodendrocytes and extracellular release of signaling factors that contribute to the maturation of oligodendrocytes.

Using a transcriptomic approach the authors determined that expression of Prostaglandin-Endoperoxide Synthase 1 was elevated in OPCs and a pharmacological inhibitor results in a concentration-dependent reduction in OL maturation. Lastly, the authors determined that a global L-PGDS knockout mouse phenocopies the ibot mouse with respect to reduced developmental myelination.

These data build upon prior work identifying elevated expression of L-PGDS in OPCs. These data also provide preliminary evidence for the extracellular release of signals from OPCs which may then, in an autocrine or local paracrine manner, impact the potential for the maturation of this cell type.

Reviewer #3 (Public Review):

The authors pose an important question of whether oligodendrocyte lineage cells have an autocrine/paracrine signaling loop that contributes to their differentiation and myelination. While prior studies have demonstrated oligodendrocyte lineage cells have cell-intrinsic pathways that impact differentiation and myelination, there isn't a strong precedent for oligodendrocytes to promote their own differentiation via autocrine/paracrine mechanisms. The notion that oligodendrocyte lineage cells promote their own differentiation in an autocrine/paracrine manner is an intriguing one that adds a new layer to our understanding of how oligodendrocyte maturation is controlled. I anticipate this paper will prompt a new direction of future investigations to uncover the extent of oligodendrocyte autocrine/paracrine signaling.

To test the possible role of oligodendrocyte-secreted molecules on oligodendrocyte development, Pan et al. utilized a mouse model where the release of a subset of secretory vesicles (specifically VAMP1/2/3-dependent vesicles) is blocked. Blocking this vesicular release prevented or delayed the differentiation of oligodendrocytes in vivo and in vitro. Further, the authors identified changes to the mRNA and secreted protein levels of prostaglandin D2 synthase (L-PGDS). Prior RNA sequencing and snRNA sequencing datasets of the oligodendrocyte lineage have identified Ptgds as a highly abundant mRNA transcript in oligodendrocyte lineage cells, particularly mature oligodendrocytes. Ptgds encodes L-PGDS, which has an unknown role in oligodendrocyte function. L-PGDS has been shown to regulate Schwann cell myelin formation in the peripheral nervous system, prompting the question of whether this protein acts similarly in the central nervous system. The paper has a clear set of well-rounded experiments, with a few remaining points that would strengthen the conclusions:

One of the foundational conclusions of the study is that VAMP1/2/3-dependent exocytosis is critical to oligodendrocyte maturation, by using a PDGFRa-CreER mouse line combined with iBot mice that express botulinum toxin in Cre-expressing cells (abbreviated as PD:iBot). Prior work has demonstrated in vitro that oligodendrocyte morphological maturation, myelin gene expression and myelin protein transport can all be impacted by the loss of VAMPs, including VAMP3. This paper establishes the importance of these SNARE proteins in the oligodendrocyte lineage in vivo: the number of mature (CC1+) oligodendrocytes and myelin basic protein staining is substantially reduced in PD:iBot mice.

1) The data in Figure 3M suggests that PD:iBot oligodendrocytes (GFP+) are lacking MBP+ sheaths and that any myelin formed is by the smaller percent of oligodendrocytes that do not express botulinum (GFP- cells). Furthermore, the efficiency of iBot expression (as evaluated by GFP+ cells) shows that 80% of OPCs and just 60% of oligodendrocyte lineage cells express GFP at P8 and supplementary data shows just 30% of oligodendrocyte lineage cells express GFP at P30. This raises the question of whether PD:iBot cells are unable to differentiate and die. While the authors show no change in caspase-dependent apoptosis in PD:iBot cells in vivo and in vitro, the data still suggests that blocking VAMP-dependent exocytosis itself slows or prevents the progression to a fully myelinating oligodendrocyte in vivo rather than the putative autocrine/paracrine signals are required for OPC differentiation. Confirming whether botulinum-expressing cells also contribute to the population of surviving, differentiated oligodendrocytes in vivo to strengthen the conclusions that autocrine/paracrine secreted molecules contribute to the oligodendrocyte maturation in vivo.

2) The paper has complementary in vitro data to pinpoint a mechanism that results in hindered oligodendrocyte maturation. The authors conduct a well-designed set of in vitro co-culture experiments in Fig4 K-M that led them to conclude oligodendrocyte morphology is impacted by secreted molecules from other oligodendrocytes.

2a) The key experiment is the transwell co-culture experiment with control and iBot cells, which suggests that blocking secretion itself has the predominant impact on cell morphology: by eye, both group3 and 4 show the largest reduction in lamellar area and the difference between group 3 and 4 is slight. At day 3 of culture (Fig 4E), the authors show the clearest effect as a reduction in cells with lamellar morphology. The quantification of the lamellar cell area is less obvious than the % of cells with arborized vs lamellar shape, as seen in Figures E & F. I would recommend that the authors show representative images of these observations and quantification of morphologies for the transwell experiments. The impact of secreted factors may be clearer with this measure.

2b) On a related note, the cell morphology data is dependent on MBP staining. The authors show that MBP protein is reduced in cells from iBot mice. Since MBP+ cell area/arborized or lamellar structure is being quantified, there remains the possibility that the cells could display a more complex morphology (lamellar) that may be missed by only staining for MBP. The authors use a CellMask dye to show cellular morphology, which is a great idea. The authors state that it labels the plasma membrane; however, the methods (and images) indicate that a cytoplasmic CellMask was used (cat.no. H32720 labels nuclei and cytoplasm, not membranes). These conclusions about cell morphology vs simply MBP expression would be strengthened by an alternative membrane label (e.g., a CellMask plasma membrane dye).

3) The authors sought to identify what secreted factors may be affected by blocking VAMP1/2/3-dependent exocytosis. Pan et al. opted for a strategy of examining transcriptional changes, asserting that important genes may be upregulated in response to compensate for blocked secretion. While this is an indirect way to identify secreted candidates, the authors found a fortuitous result that Ptgds was substantially increased in the PD:iBot oligodendrocyte cells. To confirm that L-PGDS secretion is reduced from iBot cells, the authors show Western blots. By eye the change in L-PGDS is variable, however, the authors conduct several experiments with an inhibitor and product of L-PGDS that nonetheless indicate L-PGDS activity can contribute to the morphological maturation of oligodendrocytes. A caveat is that the AT-56 inhibitor reduces MBP+ cells, and the quantification of morphology is dependent on MBP staining (again, see my note in 2b about the CellMask dye). A report on differentiation (% MBP+ cells) may be a more accurate reflection of the result. The key, compelling experiment demonstrating the role of prostaglandin D2 is the authors' rescue experiment in Fig 4G.

4) Although it's not a direct demonstration that L-PDGS secretion from oligodendrocytes is the key factor, the global L-PDGS knockout mice phenocopy many of the observations of the PD:iBot mice. This is a nice set of observations consistent with the author's hypothesis that L-PDGS impacts oligodendrocyte maturation. Future work should pinpoint whether oligodendrocyte-derived L-PDGS is critical.

Minor points:<br /> 1) The authors demonstrate that PD:iBot expresses botulinum and loses VAMP2 protein levels in oligodendrocyte lineage cells, but there is no demonstration of whether VAMP3 is expressed or similarly affected. Prior work has demonstrated in vitro that oligodendrocytes express both VAMP2 and VAMP3 (VAMP1 not detected). This would more clearly demonstrate which VAMP-mediated vesicular transport is blocked for the effects observed.

2) It is satisfying to observe a behavioral effect in the PD:iBot mice. I would advise caution in interpreting any direct link between oligodendrocytes maturation and the rotarod behavioral difference at this time. Blocking secretion from PDGFRa-Cre expressing cells may have many indirect effects (beyond myelination) in both the CNS and other cell types that can express PDGFRa and VAMPs1/2/3. I was pleased that the authors did not conclude any direct links at this time.

Overall, the authors had a well-rounded manuscript with clearly described and thoughtful experiments. The data support the conclusion that VAMP-mediated exocytosis is critical for oligodendrocyte maturation. The evidence that reduced L-PDGS secretion from the oligodendrocytes can explain the effects of the iBot mice is not as clear cut, but their data does demonstrate that L-PDGS is an important molecule for the differentiation of oligodendrocytes. This work will lead a new direction for future studies to investigate autocrine/paracrine signaling in oligodendrocyte maturation.

Reviewer #1 (Public Review):

In this work, Hoye et al. analyzed a conditional mouse model for DDX3X syndrome, an important cause of neurodevelopmental disorders in humans, and provide critical insights into the pathomechanisms of this disorder. They show that homozygous loss of DDX3X in females in neural progenitors leads to microcephaly and massive apoptosis due to impaired neural progenitor cells. Furthermore, they show that conditional DDX3X KO mice are sexually dimorphic. In males, it seems that the paralog DDX3Y on the Y chromosome is also required for neurogenesis and may be partially able to compensate DDX3X function leading to comparable phenotypes of cKO males comparable to cHET females. The authors therefore mostly focus their analysis on cHET females and cKO males. The number of progenitors is increased in cHET females and cKO males. Additionally, they show that DDX3X dosage is important for proper neuron numbers. They could link the abrogated number of neuronal cell types to a globally prolonged cell cycle and identify altered cell cycle exit of radial glial cells (RGCs) as a possible explanation for fewer neurons. Finally, the authors shed light on the molecular mechanisms by which DDX3X impairs neurogenesis using ribosomal profiling (RIBO-Seq). Large-scale studies of translational profiling are rare and this dataset provides a novel and valuable resource of translational profiles in early mouse brain development to the community. In addition, their RIBO-Seq data on DDX3X deficient cells reveal an essential requirement of DDX3X for the translation of cortical progenitor-specific mRNAs. Several targets are critical for cortical development, as investigated in more detail for Setd3 in this manuscript. Overall, this study is of great importance and provides novel insights into the pathogenesis of DDX3X syndrome and the crucial role of DDX3X during cortical development.

The manuscript is well written and the data, in general, support the conclusions drawn, but some aspects need to be clarified or modified:

1. I have one concern regarding the mouse model, which the authors need to better explain. It is unclear to me why the expression levels in the male cKO are reduced to levels comparable to the cHET females at D11.5 (Figure 1D, E), and not comparable to cKO females as one might expect. This to me raises the question if this is indeed a good model for male cKO of DDX3X. Do the authors have an explanation for this? Could it be that the probes/primers used here are indeed specific for DDX3X or also detecting DDX3Y, or is there is another explanation?

2. While the increase in progenitor cells in cHET females and cKO males is convincing, the reduction in neurons is only supported by weak evidence and trends. Significance levels used to draw these conclusions are somewhat inconsistent (Figure 3 - figure supplement 2). For instance, in Figure 3 - figure supplement 2E results with a p-value of 0.2 are communicated as a trend, whereas in Figure 3 - figure supplement 2F a p-value of 0.15 is marked as no difference. Overall, the findings of reduced number of neurons during development are not well supported by the data in this manuscript, which should be improved or toned down.

3. Do the authors have an explanation for why the increased cell cycle duration and reduced neuron numbers may not lead to microcephaly?

4. For their ribosomal profiling experiments, the authors focused on cKO females and males, while in the rest of the paper they argue that cKO males are actually comparable to cHET females. And then for polysome fractionation, they go back to cHET females. Those inconsistencies are not well justified in the manuscript. I am worried that those data are then not really comparable, and differences in RNA abundance that they attribute to different developmental time points in RIBO seq vs. polysome fractionation (E11.5 vs. E14.5) may actually be due to different DDX3X levels.

Reviewer #2 (Public Review):

Hoye and colleagues use a mouse model of DDX3X syndrome, with Emx1-Cre-driven loss-of-function of Ddx3x, which encodes an RNA helicase. The authors first validate the conditional knockout of Ddx3x in neural progenitors and assess the impact on brain development via gross cortical anatomy and immunostaining for apoptosis. They also used in utero electroporation for CRISPR-based deletion to show that in males, DDX3Y can compensate for the loss of DDX3X during neurogenesis. These changes in neurogenesis were driven primarily by alterations in cell composition, with laminar distribution unaffected. The mechanism underlying increased progenitors and fewer mature neurons was a requirement for Ddx3x in progenitor cell cycle exit, primarily in radial glial cells, and semi-cumulative labeling demonstrated that loss of Ddx3x leads to longer cell cycles and fewer neurogenic divisions. Ribosome profiling, RNA-seq, and polysome fractionation were utilized to study DDX3X translation targets, resulting in the identification of several DDX3X-dependent targets. Overall, the study is rigorous, the manuscript is well-written, and the results are interesting and significant.

Reviewer #3 (Public Review):

De novo DDX3X mutations are associated with intellectual disability and variable degrees of brain malformation such as hypoplastic corpus callosum - the authors reported over 100 mutations and their disease presentations in 2020. In the present study, Hoye et al. analyzed a floxed Ddx3x mouse model and showed that Emx1-Cre mediated deletion in the dorsal brain leads to decreased brain size and widespread apoptosis in females but not males. Interestingly, the authors showed that Ddx3y was transcriptionally upregulated in cKO males, and suggested that Ddx3y compensated for the loss of Ddx3x. The authors analyzed heterozygous Ddx3x cKO females and cKO males together and concluded that Ddx3x deletion prolonged cell cycle, impaired cell cycle exit, leading to increased progenitor populations as well as fewer Tbr1 and Ctip2 neurons. To gain molecular insights, the authors performed Ribo-Seq in E11.5 cortical tissues and reported target genes that showed Ddx3x-dependent translation efficiency. This is beautiful work backed by mouse genetics and high-quality molecular, cellular, and developmental studies. The Ribo-Seq targets provide potential new insights into Ddx3x function and pathogenic mechanisms.

Reviewer #1 (Public Review):

Rizo et al. use all-atom molecular dynamics simulation to visualize the pre-fusion primed state during synaptic vesicle fusion. To this end, they incorporate some of the recent structural and functional data of SNARE and associated proteins, namely Synptotagmin-1 and Complexin to build their initial condition for the simulations. The data shed some new light on the potential organization of the fusion intermediate, but whether the observed protein organization is part of a true functional pathway or the product of the initial conditions chosen and the applied computational constraint is unclear, especially since none of the conditions tested result in membrane fusion.

Reviewer #2 (Public Review):

Rizo et al. present all-atom (AA) molecular dynamics simulations of molecular components of the neurotransmitter (NT) release machinery. Evoked NT release is triggered by machinery that senses calcium and responds by fusing the vesicular and plasma membranes to release NTs via a fusion pore. Synaptotagmin is the calcium sensor and the SNARE proteins are the core of the fusion machinery. Complexin is another molecular component, among others.

Simulations were performed with 4 trans-SNARE complexes bridging 2 membranes with realistic lipid compositions, either 2 planar, or 1 planar and 1 vesicular. Other simulations incorporate also the C2A and C2B domains of Synaptotagmin-1 (Syt), and the accessory and central helices of Complexin-1 (Cpx). The authors' aim is to study the vesicle-release machinery system in its "primed" state, in which fusion is blocked ("clamped") before the influx of calcium which triggers fusion of the membranes and release. The planar membrane is 26 nm x 26 nm (sometimes a little larger) and the vesicle diameter 26 nm. The duration of each of the simulations of 2-5 million atoms was typically about 0.5 µsec.

Some of the major conclusions the authors declare are as follows. (i) The juxtamembrane domains (linker domains, LDs) are unstructured in the trans-SNARE complexes. (ii) SNAREs on their own pull the membranes together and squash them into an extended contact zone (ECZ) (observed in simulations with SNAREs only) as seen in experiments (Hernandez et al, 2012). (iii) Their AA simulations are argued to support a model previously proposed by this group (voleti et al., 2020) of the primed state that clamps the fusion machinery, in which C2B binds the SNARE complex via the primary interface from the crystal structure (Zhou et al., 2015), with the C2B polybasic face binding the planar membrane, while a Cpx fragment binds the opposite side of the SNARE complex, based on an earlier crystal structure (Chen et al, 2002). In simulations, the structure was robust on the timescales probed. An orientation with the Cpx accessory helix impinging on the vesicle emerged, suggestive of a role in clamping fusion. The simulations implicate several residues as critical, consistent with earlier mutation studies. Two runs produced similar results.

This is a very nice study which offers important information and insights about possible structures in the primed NT release machinery. To my knowledge, this is the most extensive AA model of a plausible NT machinery to date. The conclusion that the LDs are unstructured is interesting, contradicting prior MARTINI studies assuming helices were continuous from the SNARE complex into the LDs, and equally interesting is the finding of an ECZ with SNAREs pushed aside, in accord with previous coarse-grained studies. The outcome of the simulations of the voleti et al. C2B-SNARE-Cpx model is informative, yielding the preferred orientation and supporting the primary interface and Cpx-SNARE interactions implied by crystal structures.

My main concerns are about the validity of the conclusions presented, given the AA results. AA simulations are extremely valuable, but have limited ability to probe the big questions about how the multi-component NT machinery cooperatively unclamps, fuses and releases on msec and greater timescales. I do believe a marriage of very short timescale methods (AA, MARTINI etc) and ultra coarse-grained methods is needed to understand these fascinating systems. This manuscript makes no reference to methods that probe these long timescales, and may sometimes overstate what can be concluded from their AA results. For example, their findings for the voleti C2B-SNARE-Cpx model do not, as far as I can see, obviously suggest that this structure clamps fusion. Similarly, simulations with Cpx removed and Ca2+ bound to the C2 domains were clearly worthwhile but inconclusive, as SNAREs were not released after ~ 400 ns of simulation. In both cases, uncertainties originate in the running time limitations of AA methods.

Reviewer #3 (Public Review):

Rizo and colleagues revisit several mechanistic questions centered on the roles of SNARE proteins, synaptotagmin 1 and complexin in catalyzing membrane fusion. This effort is purely simulation based with several impressive all-atom simulations of two closely apposed lipid bilayers harboring 4 mostly assembled SNARE complexes with and without Cpx1 and Syt1. The simulations explore only about half a microsecond of elapsed time and fail to capture the act of membrane fusion itself, perhaps due to this short time window imposed by computational limitations. The authors discuss various behaviors of the SNARE proteins and accessory proteins, comparing and contrasting their conformations with those derived from past crystallographic and NMR studies.

Strengths: There are several attractive features of this study. All-atom simulations of SNARE-mediated fusion will necessarily involve many millions of atoms and thus few if any studies of this ambitious scope have been published. Most past computational work in this arena has either been at the coarse-grained level (which has limitations as pointed out by the authors) or has focused purely on a single SNARE complex rather than trying to capture a more realistic fusion/pre-fusion state. And the questions posed in this study are extremely difficult if not impossible to answer via conventional structural, in vitro biochemical and in vivo functional experimental approaches.

Weaknesses: As is the case with all simulations, many realistic aspects of SNARE-mediated fusion and the various proteins involved were omitted from the simulations for practical reasons. And several of these omissions may have large impacts on the results and conclusions. These omissions include pieces of the SNARE proteins, Cpx1, and Syt1 that are known to impact synaptic transmission but were not included to minimize the number of atoms simulated. Divalent cation interactions with anionic phospholipids were omitted even though these interactions likely have a large influence on the energy barrier for membrane fusion. Also, each simulation was performed only once, so the reader has no sense of how representative or accurate the presented results are. And importantly, the simulations never captured a bone fide fusion event, which seems like a critical aspect of modeling the prefusion state. Given that even the fastest known synapses require 50-100 microseconds to convert a calcium influx into vesicle fusion, it is perhaps not surprising that no fusion events were observed in a 200-700 nanosecond simulation window across the handful of simulations performed in this study. Regardless of these omissions, the authors generated a large amount of simulated data and attempted to reconcile interesting observations with known protein structures and past functional data.

Review #1 (Public Review):

In this paper, Sun et al. established a new approach to generate vascularized brain organoids through side by side generation of brain organoids (BOrs) and vessel organoids (VOrs) that contains vessel-like structures and microglia. The fusion of brain and vessel organoids (fVBOrs) resulted in robust engraftment of vessel-like structures and microglia around ventricular zone (VZ)-like structures in the brain organoids suggesting cellular and functional integration of vessels and microglia with neurons. Importantly, the presence of vascular network and microglia increased the number of neuronal progenitors possibly due to a marked decrease in apoptotic cell number. By simultaneously inducing the inflammatory response by lipopolysaccharide (LPS) treatment and microglia ablation by PLX5622 treatment, authors also demonstrated the ability of microglia to respond immune stimuli in fVBOrs. Overall, the approach they took to generate vascularized brain organoids is a valuable addition to the previously published methods with a strength of simultaneous production of vessel-like structures and microglia in a single organoid. The conclusions in the paper are mostly well supported by the data, but a few points need to be clarified and some conclusions need further experimental supports.

Review #2 (Public Review):

The authors were attempting to introduce blood vessels with a competent blood brain barrier into cerebral brain organoids. The strength of the manuscript is that they were able to show that they are able to introduce all cellular components of a blood brain barrier (including microglia) into the cerebral organoid using their method. They were even able to show functional components of a competent blood brain barrier such as ZO-1 and CLDN5. The quality of the pictures is high. The weakness of the manuscript is that no in vivo perfusion is shown of the capillaries, so it is not clear whether blood vessels are truly competent. Dil staining in vitro is not enough to show competent perfusion.

Reviewer #1 (Public Review):

In this study, the authors formulate a model of within-host viral infection (similar to other standard published models) to analyze data of an experiment of a SARS-CoV-2 vaccine in macaques. For this experiment, they have frequent viral load measurements, as well as multiple (>40) other immune parameter measured at multiple time points. The objective of the paper, and the main novelty, is to understand the mechanistic correlates of protection afforded by the vaccine. To this end, the authors fit the mechanistic model to the viral load data in the vaccinated and control macaques (including previously infected) to find what parameters of the model are statistically different among the different experimental groups (this has been done before). But then go a step further and assess which of the more than 40 immune measurements better explains the statistical differences. That is, the inclusion of that information in model should explain the statistical differences in parameters. This is a clever and elegant approach and allows new insights into the mechanisms elicited by the vaccine that help control the virus.

The main strengths of the paper are the wealth of data and the good use of it, with sound statistical and modeling methodology. It is also important that the authors analyze more than one type of vaccine experiments, demonstrating some robustness of the approach. The results obtained, although not totally unexpected, shed some light into the mechanism of action of the vaccine and what experimental assay could serve as a correlate of protection also for other vaccines.

The main weakness of the paper is that currently, the paper is difficult to follow in some parts, and more/ clearer details would benefit the reader. For example, some modeling choices are not properly justified.

Reviewer #2 (Public Review):

The manuscript is a body of work focused on defining a "correlate of protection" for SARS-CoV-2 antibody-based vaccines. Their main conclusion, which was the antibody binding was most correlative, is in line with other studies indicating that the vaccines-induced antibodies are protective. The application of a mathematical model of viral infection helped quantify the data, and agreed that the antibodies inhibit the infection of cells. The authors claim that they established a "novel mathematical framework" to define correlates of protection, but the methods were not particularly new and lacked assessment of important vaccine-induced immune responses that would also be considered protective. In addition, it's unclear why one would desire a clinically-relevant correlate of protection without description of how to measure it in the clinic with a defining level of how to quantify risk.

Reviewer #3 (Public Review):

Alexandre et al. fit a mathematical model of viral-host dynamics to previously-published data from three SARS-CoV-2 challenge studies in non-human primates and identify immune markers that correlate with "protection" (as measured by viral loads) as well or better than knowing whether an animal was naive, vaccinated, or recovered from natural infection. Crucially, the use of this model allowed for summarizing the complex time-dependent outcome data (viral sgRNA and gRNA loads over time) as a small number of more interpretable parameters (e.g., within-host viral infectivity, infected cell death rates, virion production rates) while allowing for intra-individual variation in a statistically rigorous fashion. Vaccine correlates of protection are notoriously difficult to identify and could be extremely valuable when assessing risks and designing vaccine dosages and booster schedules. The methodological approach developed in this paper is broadly applicable and a worth-while contribution by itself. In the context of the particular data analyzed here, the statistically-predictive immune markers showed reassuring consistency between the two studies using protein-based vaccines, although the third study using a mRNA-based vaccine differed. The conclusions have two limitations, the first of which is directly acknowledged by the authors while the second is not:

1. The definition of "protection" is limited to the within-host cellular level. While within-host transmission is certainly related to between-host transmission and disease severity, many other factors play a role as well; this limitation is nicely acknowledged by the authors.

2. The models may be overfit to the data, although this concern is somewhat tempered by the finding that application to the two protein-based vaccine studies yielded broadly similar results. Predictive statistical models of the type used here would ideally be tested on a held-out set of test data from the same type of experiment. The repeated use of BIC in a stepwise model selection framework with many predictors and limited biological replicates is risky.

Reviewer #1 (Public Review):

The authors elegantly use the CRISPR/Cas9 screening approach to perform an unbiased analysis of which genes regulate the expression of the alarmins S100A8 and S100A9. As pointed out by the authors, these alarmins amplify inflammation and can thus contribute to tissue injury during excessive inflammation. Understanding the regulators of alarmin expression could lead to a better understanding of myeloid cell differentiation and hyperinflammatory activation.

The strengths of the study are:

1. Unbiased CRISPR/Cas9 screening which identifies C/EBP-delta as a regulator of alarmins

2. Rigorous analysis of the mechanistic link between C/EBP-delta and S100A8 and S100A9 using C/EBP-delta-knockout mouse cells as well as rescue of S100A8 and S100A9 expression with an inducible C/EBP-delta construct.

3. Showing translational relevance of the C/EBP-delta link by demonstrating a correlation between S100A8 and S100A9 levels with C/EBP-delta in patient samples of peripheral blood mononuclear cells

4. Promoter analysis and epigenetic assessment of how C/EBP-delta binds to the promoters of the alarmins and which epigenetic modulators contribute to their expression.

The weaknesses of the study are:

1. Unclear relevance of the C/EBP-delta regulation of alarmins in a disease model. The C/EBP-delta knockout cells are studied ex vivo but that does not address whether C/EBP-delta absence would dampen alarmin expression and inflammatory injury in vivo.

2. The phenotyping of the myeloid cells following C/EBP-delta deletion is very limited and does not provide a clear assessment of whether C/EBP-delta affects monocyte-to-macrophage differentiation and their polarization to specific monocyte and macrophage phenotypes.

Reviewer #2 (Public Review):

In this work, Jauch-Speer et al. examine the epigenetic mechanisms regulating the expression of S100A8 and S100A9, two prevalent DAMPs released by monocytes and neutrophils during acute inflammation and tissue injury. S100A8/9 are highly expressed by monocytes but downregulated in mature macrophages, and thus their transcription is temporally controlled. While helpful in anti-microbial responses, S100A8/9 have been associated with a variety of inflammatory diseases, including autoimmune and cardiovascular diseases, in which their expression may become dysregulated. However, the mechanisms regulating their expression are poorly understood. Using ER-Hoxb8 cells, a series of gene targeting and sequencing studies were employed to characterize the dynamics of s100a8 and s100a9 transcription and regulation. First, a genome-wide screening approach using the CRISPR/Cas9 system identified the transcription factor C/EBPδ as a direct regulator of s100a8/9, which were co-expressed by differentiating monocytes. Accordingly, S100A8 and S100A9 expression was decreased in C/EBPδ-deficient cells and increased with C/EBPδ overexpression. Next, ChIP- and ATAC-seq sequencing determined the C/EBPδ binding sites within the promoters for s100a8 and s100a9. Furthermore, the presence of H3K27me3 (silencing) markers on the s100a8/9 promoters were elevated in C/EBPδ KO cells relative to WT monocytes, as well as decreased expression of the demethylase-encoding gene jmjd3, which could mediate the removal of H3K27me3 markers. Thus, C/EBPδ-dependent JMJD3 was essential for the demethylation and expression of S1008/9 in monocytes. Finally, S100A8, S100A9, and C/EBPδ expression in classical monocytes was positively associated with stable coronary artery disease and MI in a cohort of cardiovascular disease patients, demonstrating clinical relevance.

Presented here are a logical series of studies that demonstrate a previously unknown epigenetic mechanism through which S100A8/9 expression is regulated in monocytes. Furthermore, the authors make use of a variety of current sequencing technologies to sufficiently support their conclusions. This work has important implications for diseases in which S100A8/9 expression is altered, and provides clinically relevant targets for future therapeutic studies. Overall, this study would be of great interest to macrophage biologists studying macrophages in a broad variety of disease models.

However, certain aspects of the paper require further clarification or were not sufficiently investigated.

1) The mechanism(s) through which S100A8/9 expression is subsequently downregulated in mature macrophages was a concept that was introduced, but not explored. Whether C/EBPδ and JMJD3 are also involved in the downregulation of S100A8/9 in monocytes during later stages of differentiation would be important to fully understand the temporal dynamics of this regulatory network.

2) The authors cite a differentiation protocol using estrogen-regulated Hoxb8 cells (Wang et al., 2006) to produce monocytes or neutrophils in culture over a span of 5 days, and utilizes differentiating monocytes as early as day 3. However, the original paper states that the precursor cells can differentiate into macrophages after 6 days - not monocytes. Macrophages and monocytes are functionally distinct, and will have different gene expression profiles as well as different epigenetic mechanisms regulating them. Hence it is unclear whether the cells at varying days of culture are monocytes or macrophages, or if transitioning from one to the other, what stage of differentiation they are in. Following this, the authors should characterize the exact cell composition of the culture at each day of differentiation using flow cytometry and more clearly validate that it was monocytes and not macrophages that were being analyzed. Additionally, cells grown in culture lack the complex cues and factors provided by the tissue environment, and thus additional studies ought to be performed on myeloid cells within tissues of interest to confirm these findings. The data in the cell line show a direct relationship between C/EBPδ and S100A8/A9, however the data in primary cells is only a correlation.

3) ATAC-Seq was not adequately utilized to characterize s100a8 and s100a9 chromatin (Figure 6). While the peaks for s100a8 and s100a9 were provided, the difference between day 0 and day 3 was not quantified, nor were peaks for any other genes shown despite over 20,000 gene regions with differential peaks between the two time points. What genes these differential peaks were annotated to aside from s100a8/9 would help paint a more comprehensive picture of the differences between day 0 and day 3. Furthermore, C/EBPδ KO cells were not analyzed by ATAC-seq despite being included in subsequent ChIP-seq experiments, creating a gap in the data analysis.

4) In the section that deals with human data, it states "RNA-seq in monocyte subpopulations of BioNRW participants (n=26,from 3 individuals in each of the sCAD, MI and Ctrl diagnostic groups)". N value is unclear. If its n=3 from 3 groups, is that not 9? What is 26 in reference to?

Reviewer #3 (Public Review):

Major strengths:<br /> 1) Unique design of genome-wide CRISPR screen by focusing on S100A9 expression. As presented, S100A9 expression, as detected by fluorescent antibody, is a robust reporter signal to unbiasedly screen for regulatory genes of S100A9.<br /> 2) The impact of C/EBPD knockout on S100A8/A9 expression is highly significant, as observed in multiple cell models. Importantly, the authors demonstrated that C/EBPD directly binds to the promoters of s100a8/a9 genes, and this gene activation is further regulated by chromatin accessibility, a process regulated by JMJD3-mediated demethylation.<br /> 3) The expression correlation between S100A8/A9 and C/EBPD has been observed in cardiovascular patients, implying clinical significance of this pathway in disease development.

Potential Weaknesses:<br /> 1) The genome-wide screen suggested that about 28% of all genes (estimated from the cell percentage) are involved in S100A9 regulation (Fig. 1B). This seems unlikely and probably reflects a high level of false positives in the screening results. The substantial level of noise could easily mask signals from other true regulators of S100A8/A9.<br /> 2) There were many hits from the CRISPR screen. The authors picked C/EBPD because three distinct gRNAs were identified from this gene. However, there are many other interesting candidates with highly significant p-values (better than C/EBPD) and with two distinct gRNAs. There is no description of these candidates, nor discussion of their potential relevance to S100A8/A9 regulation.

Reviewer #1 (Public Review):

The authors aimed to develop a new method for modulating interhemispheric inhibition (IHI) between the sensorimotor cortices. They present and validate a highly sophisticated neurofeedback approach that has a strong neuromodulatory effect on IHI. I'm not aware that such strong effects can be obtained with any other neuromodulatory tool that is currently available.

This study is well powered, very thoroughly executed and it reveals interesting new insights into how interhemispheric inhibition changes as a function of self-regulating unilateral sensorimotor activity. As such it provides an interesting new approach for neuromodulation which might provide new treatment opportunities, for example, in patients suffering from a unilateral stroke.

One weakness is that the authors did not yet test whether changes in interhemispheric inhibition and changes in corticomotor excitability are independent phenomena. This does not allow them to dissociate whether the participants learned to specifically modulate neural circuits regulating interhemispheric inhibition (as claimed by the authors) or rather unilateral excitability in general. Thus, while the authors achieved their aim at the phenomenological level, their interpretation regarding the specific neurobiological underpinnings is rather speculative. This is, however, important for designing evidence-based interventions for stroke recovery.

The manuscript would further benefit from editing the results section and modifying some of the figures to make it more accessible for the reader.

Reviewer #2 (Public Review):

The study by Ushiba et al. directly demonstrates that volitional control of motor cortical activation patterns using a brain-computer interface influences the strength of interhemispheric interaction in the motor system. Specifically, using non-invasive EEG, Ushiba et al. recorded electrical activity from neurons in the sensorimotor cortex in real-time, and provided information about the bilateral activation of the motor cortex to users on a computer screen, a process known as "neurofeedback". This allowed users to learn to modify the motor cortex activation patterns using their own volition, during states of high and low activation (relative to the contralateral hemisphere). By concurrently stimulating the motor cortex using magnetic pulses (TMS), Ushiba et al were able to show that states of higher relative ipsilateral cortical activation were associated with significantly lower levels of inhibition between the bilateral motor cortices.

The authors use common neuroscience techniques such as TMS and EEG, but they are deployed in combination and in real-time, making this study a technical masterwork. Moreover, statistically significant effects were achieved compared to rigorous control conditions, by analysing random trials when TMS stimuli were triggered without provision of neurofeedback and/or independent of successful neurofeedback control.

Nevertheless, even though the study clearly demonstrates that interhemispheric inhibition (IHI) may be influenced by neurofeedback, it does so only in the direction for decreasing IHI relative to baseline. Future studies will be needed to ascertain if a similar setup may also be used to successfully upregulate (i.e. increase) IHI.

Finally, although a number of previous studies indicate that IHI may be a relevant prognostic marker of motor recovery in clinical populations (e.g. patients with stroke), future work will need to explore more directly the links between IHI self-regulation and its impact, if any, on motor rehabilitation outcomes.

Reviewer #3 (Public Review):

In this study, healthy participants imagine moving their right index finger and receive neurofeedback of their oscillatory brain activity. They learn to up-and down-regulate the oscillations in the right motor cortex, and thereby its responsiveness to transcranial magnetic stimulation (TMS). Whenever the brain activity in the right motor cortex is desynchronized, i.e., more responsive, TMS to the right motor cortex induces a stronger effect on the left motor cortex, which is probed by TMS as well. In those participants who can better regulate the oscillations in the right motor cortex during the task, TMS of the right hemisphere induces a stronger effect on the left motor cortex already before the task at rest.

Strengths:<br /> This study successfully demonstrates that human subjects can volitionally control ipsilateral sensorimotor excitability (measured as sensorimotor rhythm event-related desynchronization or SMR-ERD) with the aid of brain computer interface (BCI)-based neurofeedback. The approach is innovative since it provides neurofeedback with regard to brain activity in both hemispheres independently. Furthermore, this study shows that the participants learn to both up-and down-regulate the ipsilateral brain activity; this modifies the ipsilateral hemisphere's responsiveness to a TMS pulse, which in turn changes also the responsiveness of the opposite brain hemisphere to a second TMS pulse (thereby applying a classical dual-coil paired-pulse protocol). It is important that another measure of interhemispheric interactions is applied as well, namely an oscillatory coherence measure. Interestingly, the paired-pulse TMS effects before the task at rest correspond to the interhemispheric coherence at rest, and to the paired-pulse TMS effects and the ipsilateral SMR-ERD during the task.

Weaknesses:<br /> Up- and down-regulating the oscillations in the right motor cortex has not led to a corresponding change in interhemispheric coherence (Figure 5D). Therefore, no conclusions with regard to interhemispheric "rebalancing" can be drawn. Moreover, "rebalancing" would indicate an "unbalanced" starting point, which is not the case in the examined healthy participants. The paired-pulse TMS effects can be explained by the modulated responsiveness of the right motor cortex: The more excitable the right motor cortex (i.e., the more SMR-ERD), the stronger its responsiveness to TMS, the stronger the impact of this first (conditioning) TMS pulse on the opposite hemisphere, the less responsive is the opposite hemisphere to the second (test) TMS pulse. This observation is in line with the well-established finding in the literature that this interhemispheric inhibition (IHI) is a stimulation intensity-dependent phenomenon of the first (conditioning) TMS pulse, which is also demonstrated in this study (Figure 2B); the neurofeedback task is achieving a similar effect (Figure 3 suppl 1; Figure 5B) without the necessity to modify the stimulation intensity of the conditioning pulse. This effect is however not achieved by changing the interhemispheric coherence (Figure 5D).

Moreover, the statistical analysis should only compare the latter three conditions (high, middle, low) that have been randomized, to avoid order effects due to cumulative TMS pulses.

It remains an open question, whether the more sophisticated neurofeedback approach (of modulating both hemispheres separately) was indeed necessary to achieve the findings of this work.

The supplementary findings (Figure 6 Suppl 1) underline the necessity to investigate other frequency bands as well with regard to the ERD findings/correlation (Figure 4, 5, 6) to confirm the frequency-specificity of the neurofeedback task.

Reviewer #1 (Public Review):

This is a very interesting paper describing membrane potential dynamics of hippocampal principal cells during UP/DOWN transitions and sharp-wave ripples. Using whole-cell in combination with linear LFP recordings in head-fixed awake mice, the authors show striking differences of membrane potential responses in principal cells from the dentage gyrus, CA3 and CA1 sectors. The authors propose that switches between a dominant inhibitory excitable state and a disinhibited non-excitable state control the intra-hippocampal dynamics during UP/DOWN transitions.

Obtaining intracellular recordings in vivo is commendable. The authors provide valuable data and analysis. While data show clear trends and some of the conclusions are well supported, the authors may need to clarify the following potential confounds, which can actually impact their conclusions and interpretation:

1- All the analysis is based in z-scored membrane potential responses but the mean resting membrane potential is never reported. For DG granule cells recorded in awake conditions, the membrane potential is usually hyperpolarized so that most of the effect may be due to reversed GABAa mediated currents. Similarly, for those cells exhibiting the non-expected polarization during UP/DOWN states there may be drifts around reversal potentials explaining their behavior. Moreover, regional trends on passive and active membrane parameters and connectivity can actually explain part of the variability. A longitudinal comparison of state Vm and spikes in fig.5 suggests that some of the largest depolarized responses are not correlated with firing. Authors should evaluate this angle, ideally showing the distribution of membrane potential values across cells and regions and confronting this with the different membrane potential responses.

2- While there are some trends for each hippocampal regions, there is also individual variability across cells during UP/DOWN transitions (fig.5) and near ripples (fig.6). What part of this variability can be explained by proximodistal and/or deep-superficial differences of cell location and identity? Can authors provide some morphological validation, even if in only a subset of cells? For CA3, proximodistal heterogeneity for intrinsic properties and entorhinal input responses are well documented in intracellular recordings both in vitro and in vivo. What is the location of CA3 cell contributing to this study? For CA1 cells, deep-superficial trends of GABAergic perisomatic inhibition and connectivity with input pathways dominate firing responses. Regarding DG cells, are all they from the upper blade?

3- AC-coupled LFP recordings cannot provide unambiguous identification of the sign of phasic CSD signals, because fluctuations accompanying UP/DOWN states alter the baseline reference. This is actually the case, given changes of membrane potential accompanying UP/DOWN transitions. I recommend reading Brankack et al. 1993 doi: 10.1016/0006-8993(93)90043-m. The authors should acknowledge this limitation and discuss how it could influence their results. One potential solution to get rid of this effect is using principal/independent component analysis for blind source separation.

Reviewer #2 (Public Review):

In this manuscript "Inhibition is the hallmark of CA3 intracellular dynamics around awake ripples" the authors obtained Vm recordings from CA1, CA3 and DG neurons while also obtaining local field potentials across the CA1 and DG layers. This enabled them to identify periods of up and down state transitions, and to detect sharp-wave ripples (SWRs). Using these data, they then came to the conclusion that compared to CA1 and DG, the Vm of more CA3 neurons is hyperpolarized at the approximate time of SWRs.

Unfortunately, for the following reasons, the current manuscript does not necessarily support this conclusion:

Recordings are obtained in mice who are recently (same day) recovering from craniotomy surgery/anesthesia and have no training on head fixation. This means that the behavioral state is abnormal, and the animal may have residual anesthesia effects.

Most of the paper is dedicated to dynamics around up-down state transitions, not focused on ripples.

Vm should be examined raw first, then split into fast and slow -the cell lives with the raw Vm.

While some (assumed) CA3 principal cells were hyperpolarized around the time of ripples, saying inhibition is the hallmark of CA3 dynamics around ripples is an exaggeration, especially because it does not seem mechanistically tied to anything else.

The use of ripple onset time is questionable, since the detected onset of the ripple depends on the detector settings, amplifier signal-to-noise ratio, etc. The best and most widely used (including by a subset of these authors) metric is the ripple peak time.

There is not enough raw data (or quality metrics) shown to judge the quality of the data, especially for the whole cell recordings. For instance what was the input resistance of the neurons? Was the access resistance constant?

There is not enough explanation regarding why the reported results on the spiking of CA1 and CA3 neurons in SWRs is so different than previously published. In general, whole cell recording is not the most reliable way to record spike timing, and the presented whole cell data differ from previously published juxtacellular and extracellular recording methods, which better preserve physiological spiking activity.

The number of neurons from each area is not reported.

There is no verification of cell type so it is inappropriate to assume that all neurons are the principal neurons.

Are the fluctuations in the CA3 Vm generally smaller than for CA1 and DG because of physiology or technical reasons?

Reviewer #3 (Public Review):

During slow wave sleep and quiet immobility, communication between the hippocampus and the neocortex is thought to be important for memory formation notably during periods of hippocampal synchronous activity called sharp-wave ripple events. The cellular mechanisms of sharp-wave ripple initiation in the hippocampus are still largely unknown, notably during awake immobility. In this paper, the authors addressed this question using patch-clamp recordings of principal cells in different hippocampal subfields (CA3, CA1 and the dentate gyrus) combined with extracellular recordings in awake head-fixed mice as well as computer modeling. Using the current source density (CSD) profile of local field potential (LFP) recordings in the molecular layer of the dentate gyrus as a proxy of UP/DOWN state activity in the entorhinal cortex they report the preferential occurrence of sharp-wave ripple (recorded in area CA1) during UP states with a higher probability toward the end of the UP state (unlike eye blinks which preferentially occur during DOWN states). Patch-clamp recordings reveal that a majority of dentate granule cells get depolarized during UP state while a majority of CA3 pyramidal cells get hyperpolarized and CA1 pyramidal cells show a more mixed behavior. Closer examination of Vm behavior around state transitions revealed that CA3 pyramidal cells are depolarized and spike at the DOWN/UP transition (with some cells depolarizing even earlier) and then progressively hyperpolarize during the course of the UP state while DGCs and CA1 pyramidal cells tend to depolarize and fire throughout the UP state. Interestingly, CA3 pyramidal cells also tend to be hyperpolarized during ripples (except for a minority of cells that get depolarized and could be instrumental in ripple generation), while DGCs and CA1 pyramidal cells tend to be depolarized and fire. The strong activation of dentate granule cells during ripples is particularly interesting and deserves further investigations. The observation that the probability of ripple occurrence increases toward the end of the UP state, when CA3 pyramidal cells are maximally hyperpolarized, suggests that the inhibitory state of the CA3 hippocampal network could be permissive for ripple generation possibly by de-inactivation of voltage-gated channels thus increasing their excitability (i.e. ability to get excited). Altogether, these results confirm previous work on the impact of slow oscillations on the membrane potential of hippocampal neurons in vivo under anesthesia but also point to specificities possibly linked to the awake state. They also invite to revisit previous models derived from in vitro recordings attributing synchronous activity in CA3 to a global build-up of excitatory activity in the network by suggesting a role for Vm hyperpolarization in preserving the excitability of the CA3 network.

1) In light of recent report of heterogeneity within hippocampal cell types (and notably description of a new CA3 pyramidal cell type instrumental for sharp-wave ripple generation) (Hunt et al., 2018), the small minority of CA3 pyramidal cells depolarized during ripples deserve more attention. These cells are indeed likely key in the generation of sharp wave ripple. Several analyses could be performed in order to decipher whether they have specific intrinsic properties (baseline Vm, firing threshold, burst propensity), whether they are located in specific sub-areas of CA3 (a versus b, deep versus superficial) and whether they are distinctively modulated during UP/DOWN states.

2) The authors use CSD analysis in the DG as a proxy of synaptic inputs coming from the EC to define alternating periods of UP and DOWN states. I have few questions concerning this procedure: 1- It is unclear if only periods when animals was still/immobile were analyzed. 2- How coherent were these periods with slow oscillations recorded in the cortex (which are also recorded with the linear probe?).<br /> 3- How long did these periods last? Did they occur during classically described hippocampal states (LIA/SIA) or do they correspond to a different state (Wolansky et al., J Neurosci 2006).

3) To better characterize hippocampal CSD profiles around ripples and UP/Down states transitions, could you plot ripple and UDS transition-triggered average CSD profiles across hippocampal subfields?

4) The duration of UP states appears longer than that reported in anesthetized animals. To ascertain this fact could the authors quantify and report mean UP and DOWN states durations? Shorter DOWN states would decrease the probability to detect ripple. Could the authors correct for this bias in their analysis of ripple occurrence during UP and DOWN states?

5) The authors report a high coherence between the Vm of an example CA3 pyramidal cells and UP/DOWN state in DG. Was it a general property of a majority of CA3 pyramidal cells? The coherence values should be reported for all CA3 pyramidal cells.

6) Was the high coherence between DG CSD magnitude and CA3 Vm specific to these slow oscillatory periods or a more general feature of the DG/CA3 functional coupling. For example, was it also observed during theta/movement periods?

7) Fig. 6 shows depolarization and increase firing in DGCs up to 150 ms prior to ripple onset. However, ripples sometime occur in bursts with one ripple following others. Could such phenomenon explain the firing prior to ripples? (which would in fact correspond to firing during a previous ripple). What is the behavior of firing rate and Vm of different cells types if analysis is restricted to isolated ripples? This analysis is notably important in CA3 where feedback inhibition following a first ripple could lead to hyperpolarization « during » the next ripple.

Reviewer #1 (Public Review):

Cluh is a protein involved in regulation of mitochondrial protein expression at the post-transcriptional level. The manuscript begins by the identification of a new Cluh partner, astrin. Astrin is a protein described earlier as involved in centrosome stability and mTOR signaling. Using a variety of techniques the authors demonstrate an extremely interesting and important link between metabolism, also governed by mTOR, mitochondrial function and cell cycle progression. Cluh binds to mRNA encoding astrin and its longer isoform, astrin-1, thereby protecting the encoded protein from degradation. This interaction takes place in the interphase, and in the absence of astrin the Cluh protein changes its subcellular location. The interaction of Cluh with astrin does not affect the regulation of mitochondria-related gene expression. Both proteins are functionally linked to the major driver of metabolism and cell fate, mTOR.

The manuscript is technically sound and convincing. Regulation described in this study sheds the light on how the cell integrates and fine-tunes various activities, which need to be coordinated with the cell fate decisions. However, further work is required to understand this process mechanistically and physiologically. The authors themselves discuss many open questions and research directions for the future. One of the most exciting questions is the spatial localization aspects of this regulation. Certainly, the results obtained here will initiate several additional studies. In summary, the paper provides very interesting insight into the relationship between important signaling proteins.

Reviewer #2 (Public Review):

In this manuscript the authors identified a novel interaction between the RNA binding protein CLUH and the known mTOR regulator astrin, proposing an additional regulatory mechanism by which CLUH impacts mTOR signalling and therefore cellular metabolism. They study how loss of one affects the levels or localization of the other interactor and the downstream consequences for cellular metabolites and mTOR signaling.

Strengths:<br /> The authors use detailed molecular biological and biochemical techniques to reveal that CLUH only interacts with the full length form of astrin (astrin-1), with the shorter isoform (astrin-2) being a product of several downstream translation start sites. This suggests an interesting coupling of the translational regulation of astrin with its ability to regulate CLUH localization. They show that loss of astrin leads to a striking redistribution of CLUH to focal adhesions, whereas overexpression of astrin-1 but not astrin-2 sequesters some of CLUH to the centrosome. Loss of astrin does not mimic the effect that loss of CLUH has on mitochondrial morphology and respiratory function, supporting the notion that CLUH remains functional in this aspect despite its relocalization. Using proteomics and metabolomics of starved cells, the authors show that both proteins are involved in metabolic rewiring of the cell.

Weaknesses:<br /> It remains unclear whether the mislocalization of CLUH upon loss of astrin has any consequences on metabolic rewiring, as astrin is a known interactor of the mTORC1 component Raptor and therefore loss of astrin may affect cellular metabolism only through this axis and not via CLUH mislocalization. This is supported by the finding that the metabolic profiles of CLUH and SPAG5 (=astrin) KO cells are almost polar opposites. The study is still lacking a mechanistic rescue experiment to test the claim that astrin is a negative regulator of CLUH.

Summary<br /> The authors have presented convincing evidence for the interaction between two mTOR regulators, CLUH and astrin. Astrin is important for the localization of CLUH and CLUH regulates the expression of astrin. However, this study still lacks the complete dissection of the individual vs. the combined effects of these proteins on cellular metabolism. To understand their impact, both individually and combined, will be very interesting to the field as the connections between regulation of the cell cycle and mitochondrial metabolism/biogenesis are still not well understood.

Reviewer #2 (Public Review):

The folding of chromosomes during interphase is controlled by two cohesin complexes, which share several common subunits but contain either STAG1 or STAG2. Mutations in the STAG proteins, as well as other cohesin subunits, are associated with developmental disease and cancer in humans.

This paper studies the function of STAG2 cohesin during neural development using a CRE/LOX approach to delete the gene in neural stem cells that give rise to a variety of functionally specialised cell types in the brain. This caused abnormal growth and neurological defects, and transcriptional analysis highlighted the cholesterol biosynthesis pathway, which is known to be important for myelination, as preferentially affected. Accordingly, histological analysis revealed that the brains of STAG2 mutant mice had fewer myelin fibres. Using a combination of single-cell and bulk RNA sequencing the authors found that oligodendrocytes, which are responsible for myelination, were present at roughly normal proportions among cells of the brain, but had altered gene expression patterns, including in cholesterol biosynthesis genes. Analysis of DNA looping by chromosome conformation capture revealed that STAG2 deletion affected the formation of short DNA loops emanating from promoters, but not longer-range units of genome organisation such as TADs and compartments.

Overall, this manuscript contains an impressive body of work that advances our understanding of how specialised cohesin complexes contribute to cell-type-specific transcription and genome organisation. To the best of my knowledge, the experiments have been performed to a high standard, and use diverse but appropriate methodologies.

Reviewer #1 (Public Review):

The authors generate a conditional mouse model of the STAG2 cohesin protein and use it to abolish STAG2 function in the brain. The authors show that while inactivation of STAG2 in the entire embryo is lethal, brain-specific STAG2 inactivation is compatible with development. However, such mice show neurological defects. The authors find that nerve fibre myelination is defective and focus on defective cohesin function in oligodendrocytes as the major cause of the myelination defects. They show misregulation of a subset of genes, which are enriched for those involved in cholesterol biosynthesis. Genome-wider chromosome capture experiments in oligodendrocytes found that coarse-range chromosome structure was not affected, however, the authors find effects on gene-looping. The results provide a framework for understanding the pathogenicity of cohesin mutations in humans.

Reviewer #3 (Public Review):

The authors investigated the role of STAG2, one of the cohesin complex subunits, in developing CNS, by using the Nex-Cre system. Conditional Stag2 KO in the CNS leads to neurological defects and premature death. RNAseq analysis from Stag2 ablated brain revealed changes in expression of myelin-related genes, correlating with defective myelin fiber formation. By single-cell RNAseq from Stag2 ablated brain, the authors revealed a maturation defect of Stag2 deleted oligodendrocytes (OLs), and RNAseq from purified OLs revealed changes in cholesterol biosynthesis-related genes, possibly underling the myelination defects. HiC studies revealed that Stag2 deficiency mainly leaves A and B compartments and TADs unaffected, while the number and strength of Promoter anchored loops were decreased genome-wide and at the level of downregulated genes. Altogether, this data extends our knowledge of the role of cohesin and 3D chromatin architecture in brain development.

Reviewer #1 (Public Review):

The authors sought to investigate the diet of the early fossil bird Jeholornis and its implications for bird-plant interactions in early bird evolution.

Major strengths were: 1) an exquisite near-complete cranial reconstruction of the early fossil bird Jeholornis from the Early Cretaceous of China, 2) a large sample of extant bird skulls (160) for the geometric morphometric analysis, and, 3) qualitative description of alimentary contents of extant birds.

Major weaknesses were: 1) restriction of diet consideration to only granivory and frugivory, 2) under-detailed comparisons between the extant and extinct alimentary contents, 3) unclear explanation of the connection between early fossil birds and seed dispersal.

The authors did not yet achieve their full aims because their methods limited the scope of their conclusions. Specifically, a third hypothesis that Jeholornis was neither granivorous nor frugivorous was not addressed in the study. This is especially poignant as the PCA data show overlap between the granivory and frugivory data points and the 'other diet' data points. If it is assumed that Jeholornis must be a granivore or a frugivore, then the results support frugivory over granivory for Jeholornis. However, as explained above, this assumption is not supported by the data provided so the third hypothesis needs to be tested.

The cranial reconstruction of Jeholornis and the alimentary content data for extant birds would be invaluable to the community. The geometric morphometric data are presented in a way that obscures how much overlap there is between dietary categories (non-frugivore and non-granivore diets are grouped as 'other diets'), so the utility of these data is unclear. This aspect has hampered the ability of the authors to reconstruct diet in Jeholornis and, thus, the bigger picture insights that can be drawn from these results, limiting the likely impact of the work.

Jeholornis is one of the earliest fossil birds, so understanding its diet and ecological role is important for understanding Mesozoic ecosystems and the emergence of modern ones.

Reviewer #2 (Public Review):

Hu et al. describe the skull morphology and gut contents of Jeholornis. They show the gut contains uncracked seeds and the beak shape is more like that of frugivorous or omnivorous birds than like seed-cracking or seed-grinding granivorous birds. Instead, available evidence suggests that Jeholornis consumed seeds while feeding on accessory tissues associated with the seeds, perhaps fruits. The comparisons with modern bird beaks and alimentary contents are detailed and demonstrate the utility of CT scans and digital reconstructions for studies of comparative biology using museum specimens.

Reviewer #3 (Public Review):

Hu et al. reported on a new specimen of the early bird Jeholornis, including a nearly complete skull. Using geometric morphometrics data collected from 3D and 2D retro-deformed reconstructions of its skull, the authors convincingly dismiss a seed-cracking feeding strategy for the taxon. They then use comparisons of 3D reconstructions of ingested seeds to extant birds with known feeding strategies to convincingly argue that Jeholornis was likely at least partially frugivorous. As such, this study provides the strongest evidence yet that early birds such as Jeholornis may have played a role in bird-mediated seed dispersal strategies in the Mesozoic.

Generally, the data presented in this paper support the authors' interpretations. The specimen at the core of this study is truly spectacular, and the authors' retro-deformation of its skull is skilled. The results of the authors' geometric morphometric analyses support their inference that Jeholornis was likely not a seed-cracker. Their comparisons of ingested seed shapes also convincingly supported a partially frugivorous diet. I especially applaud the authors' detailed description of their process of retro-deformation of the fossil skull (an example many should follow, including myself) as well as making both their raw data and their reconstructed surfaces available online.

However, there are a few major and several minor issues that I believe need to be addressed.

1. The implications for possible bird-mediated seed dispersal are clear in this study, but they are not conclusive. Rather, the authors (convincingly) demonstrate that Jeholornis was at least partially frugivorous -- a necessary component of such a mutualistic interaction. The authors do not demonstrate that such an interaction actually occurs. These results are nonetheless exciting and important, but I think certain statements in the paper are too strong. A notable example is the title - "Earliest evidence for frugivory and seed dispersal by birds." I would strongly urge the addition of a single word to better reflect the data presented: "Earliest evidence for frugivory and *possible* seed dispersal by birds." Similarly, in lines 328-329 -- "Strong indications for at least seasonal frugivory in Jeholornis provides direct evidence of [specialised seed-dispersal by animals during the Early Cretaceous] for the first time" -- is not true. This paper does not provide *direct* evidence for this, but *does* provide a mechanism consistent with this. There are a handful of other statements in the paper that I think should be toned down to account for this.

2. Much more information should be given about the new Jeholornis specimen. In the supplement, the authors state that "a few post cranial elements" (p. 17, line 352) are preserved along with the skull -- which elements? They should be figured and briefly described in the supplement. This is of relevance to the core assumption of the paper, namely that this individual belonged to Jeholornis -- the taxonomic assignment is based partially on the tail morphology -- which I assume means that, minimally, a complete tail is preserved. The authors also mention the pelvic morphology of the new specimen, so I assume at least some part of the pelvis is preserved. These should all be figured. Most anatomical discussion is limited to the skull (and especially the palate), which is understandable, given the focus of the paper. However, with that in mind, more attention should be paid to the retro-deformation of the skull. Figure 1 is quite attractive, but I'm confused by the differences in depicted preservation between the 3D (Fig. 1C, D) and 2D (Fig. 1E, F) reconstructions. For example, the braincase is not shown in panel C but is in panel E -- why? Is its shape inferred from other specimens for panel E? Again, I very much appreciate the inclusion of near step-by-step description of how the rostrum was retro-deformed. Minimally, a few comments on what isn't preserved would be useful.

3. The figures are visually attractive but I found some of them confusing or unclear. See my comments above regarding Figure 1. Despite the red arrows in Figure 4 and the supplemental figure, I was hard pressed to understand precisely what set the indicated seeds apart from the rest. In some cases I could see slight "dents" where one or two of the arrows indicated, but it was hard for me to see, even when I zoomed in on my screen. I think inset panels featuring zoom-ins on the indicated regions would be very useful in making the point the authors intend. Also, I don't know if the supplemental image naming/number scheme was imposed by the journal or is a choice by the authors, but I found it baffling. Something more traditional (like "Fig. S1" or "Supplemental Figure 1") would be much more efficient.

Reviewer #1 (Public Review):

This is an interesting paper that uses de novo protein design to probe the effects of oligomerization state on the activity of chimeric antigen receptors (CARS). The successful design of transmembrane domains with specific oligomeric states is an impressive result on its own. The proteins were designed using rotamer-based sequence optimization in Rosetta with an energy function specific for the membrane environment. During the design process it was important to explicitly reward sequence diversity as low diversity sequences (i.e. many leucines) produced the lowest energies when evaluated on the target backbone, but showed little specificity for a single conformation when docking simulations were performed with the designs. After experimentally evaluating a couple rounds of designs, the investigators settled on a design protocol that also included screening of the design candidates with docking simulations in alternative oligomerization states to check that the sequences preferred the desired oligomerization state. The designs were experimentally evaluated with gel electrophoresis and X-ray crystallography. In the end, designs that adopted well-defined dimers, trimers, or tetramers were created and carried forward in experiments as CARs.

In vitro experiments showed a clear correlation between oligomerization state of the CAR and cytokine secretion when CAR T cells were exposed to HER2+ cancer cells. The higher order oligomers also were more effective at slowing tumor growth in mice injected with HER2 tumor cells. These results confirm previous observations that dimeric CARs (via disulfide formation) are more effective than monomeric CARs. One exciting finding was that the designed CAR tetramer was as effective at suppressing tumor growth in mice as a standard CAR construct used in the field (transmembrane domain derived from CD28), but the tetramer CAR stimulated less cytokine release than the CD28TM CAR in vitro. The CAR T therapies currently used in the clinic frequently stimulate dangerous levels of cytokines, if a CAR T cell can be created that is as effective as current treatments but overall cytokine release is lowered, this could be an improvement over current treatment options. One caveat about the efficacy data presented in this paper is that CAR T cells were administered to the mice only a single day after injection of the cancer cells. More rigorous tests of efficacy will be needed to determine if the tetrameric CAR is on par with standard constructs used in therapy.

One thing that struck me is that the protein design process contained no consideration for how activation signals are transmitted from the extracellular domain (ECD) of the CAR to the intracellular activation domains. Does this suggest that specific conformational changes are not a part of the activation process? It would be great if the authors could comment on this. Do the results say anything about how binding to the ECD does or does not activate signaling?

Reviewer #2 (Public Review):

The authors designed and computationally refined a set of novel self-associating TM helices which were shown to form dimers and trimers by X-ray crystallography. The dimer (Car2) and trimer (Car3) as well as a modelled tetramer (Car4) were then fused to extracellular antigen-recognition and intracellular signalling domains. They were then compared to a monomer (Car1) and the original CD28 TMD in their ability to kill cancer cells in vitro and in vivo and to release various cytokines. Also, the authors show that a specific amino acid motif within the wild-type CD28 TMD of the CD28 CAR mediates interaction with the endogenous CD28 and that this is responsible for cytokine release, an undesired side reaction associated with cancer cell killing. Since their CARs with de novo designed TMDs show much reduced cytokine release, this confirms their notion that non-natural TMDs would isolate CARs from endogeneous CD28. The novel functional aspect about the designer CARs presented here is thus that cytokine secretion is less troubling when compared with the original CD28 CAR28. Most interestingly, they find that the antitumor activity of the constructs tested in an engineered mouse tumour model as well as induced cytokine release scales with the oligomeric state.<br /> In sum, the work is not only very elegant from a membrane protein engineering point of view. Rather, it represents a fine example of how protein design can be translated into medical applications.

Reviewer #3 (Public Review):

The paper by Elazar et al describes a highly significant and rigorously performed study that addresses the influence of TMD-mediated chimeric antigen receptor (CAR) oligomerization on the antitumor activity and cytokine release of CAR-T cells.

The transmembrane helices (TMHs) of most single-pass transmembrane receptors have long been considered as mere membrane anchors, and hence their function in receptor signaling has often been neglected. In recent years, however, several studies have found that TMH oligomerization can play an active and often essential role in the signaling mechanism of receptors including growth factor receptors, death receptors, and immune receptors. In this study, the authors have demonstrated that designed TMH oligomerization, which mediates CAR oligomerization, can have profound impact on the activity and cytokine release of CAR-T cells. Their findings have illuminated another dimension for CAR-T/NK engineering and optimization.

Specifically, the authors first performed de novo design of completely new TMHs that can form stable parallel dimer, trimer, or tetramers, as validated by SDS-PAGE and crystallography. Then, by replacing the TMH of the most used CARs, which is the TMH of CD28, with the designed TMHs, they found that the antitumor activity of the CAR-T cells in mice scaled linearly with CAR oligomeric state encoded by the designed TMH. More strikingly, their in vitro assays showed that the CARs with the designed TMHs all induced 2-10-fold less cytokine release than the CAR with CD28 TMH, raising the suspicion that the CD28 TMH may pair CAR with endogenous T cell CD28 leading to higher level of CD28 signaling independent of the CARs. Indeed, they have shown that a set of mutations in the CD28 TM of the regular CAR that is likely to disrupt TMH homodimerization led to 2-6-fold reduction in CAR-T cell cytokine release. Collectively, their results suggest that there is ample room for improving the CAR-T antitumor activity / cytokine release ratio by optimizing the CAR TM sequence, and it remains to be seen if this approach can be used to achieve better outcomes in higher animals.

Reviewer #1 (Public Review):

In the manuscript "Dnmt3a knockout impairs synapse maturation and is partly compensated by repressive modification H3K27me3," Li et al. investigate the role of Dnmt3a in the development of mouse cortical neurons by conditionally knocking it out during mid-late gestation and measuring the resulting molecular and phenotypic consequences. The study provides temporal context for Dnmt3a dependent DNA methylation in the development of a specific population of neurons and describes a potentially novel mode of compensatory histone trimethylation at H3K27 at particular genomic loci that lose DNA methylation. The authors first describe phenotypic aberrations induced by Dnmt3a-cko that include altered dendrite/spine morphology and deficits in particular social behaviors without overt morphological alterations in the brain. They then go on to describe the epigenomic landscape underlying their observations.

While the study includes high quality data that are novel, there are a few caveats that need to be addressed. For example, while the manuscript does provide evidence to suggest there may be regions of the genome that are compensated by H3K27me3, the biological basis for this remains unclear, as do the consequences of this compensation. The behavioral data while providing a phenotype for the regulatory role of Dnmt3a in neuronal structure and function are not related in any particular way to the sequencing data. Overall the paper presents chromatin information with a more limited biological context.

Reviewer #2 (Public Review):

In this study, Li, Pinto-Duarte and colleagues investigate functional and epigenomic effects of loss of DNMT3A in excitatory neurons using a conditional knockout mouse model. The authors characterize behavioral, cell-morphological, and electrophysiological deficits that suggest disruption of synapse function may be major driver of phenotypes in these mice. Through RNA-seq analysis of mutant neurons they identify 1720 dysregulated genes, some of which are implicated in dendritic and axonal development and synaptic formation. To understand the epigenetic factors underlying transcriptomic effects, the authors perform methylC-seq. They observe widespread reductions of mCG and mCH in mutant excitatory neurons and detect 141,633 differentially CG methylated regions (DMRs) which exhibit large reductions in mCG. To understand why sets of genes with widespread methylation depletion could be either up- or down-regulated, the authors profiled histone modifications. They observe changes in H3K27me3 signal over development and increases in this mark at DMRs upon loss of DNMT3A. They suggest that over-compensation by H3K27me3 repression at genes containing DMRs may drive some of the downregulation of gene expression observed in DNMT3A mutant mice. These results confirm findings from previous publications on loss DNA methylation in DNMT3A conditional mutant mice and identify novel alterations in H3K27me3 that may impact changes in gene expression in these mutants.

Understanding functional outcomes of DNMT3A loss and identifying mechanistic interplay between neuronal DNA methylation and other epigenetic mechanisms is of significant interest to the field. It has been clear that DNMT3A is critical to neuronal development, but cellular characterization such as spine morphology and synapse function has been limited. The analyses presented here provide robust evidence for synaptic alterations upon loss of DNMT3A. The authors' characterization of the differences in H3K27me3 across development and in the DNMT3A cKO underscores the potential importance of this mark when DNA methylation is altered. While changes in H3K27me3 are relevant and are likely to be functionally important, the study has some limitations in assessing the magnitude and impact of these changes:

1. Only two biological replicates per condition are included in most genomic analysis. This may lead to over-estimates of the changes observed due to sample-specific technical variation in the ChIP and sequencing procedures, particularly given the subtle alterations that are identified.

2. While the compensatory mechanism proposed is feasible in light of the findings presented, evidence definitively supporting H3K27me3 changes as truly compensatory for loss of mCG in DNMT3A conditional knockout neurons is limited. Additional genomic analyses or experimental evidence would be needed to authoritatively make this claim.

3. The study includes limited analyses assessing how changes in mCH and H3K27ac, two other epigenetic marks shown to be disrupted in DNMT3A models, are integrated with changes in H3K27me3, mCG and gene expression.

Overall, the study has generated valuable datasets that identify cellular phenotypes and suggest a novel disruption of H3K27me3 in DNMT3A conditional knockout mice. However, the conclusions regarding the importance of H3K27me3 in compensation in these mutant mice are quite speculative.

Reviewer #3 (Public Review):

In order to understand the regulatory mechanisms whereby DNMT3A controls neuronal maturation, the authors generate and analyze an extensive set of transcriptomic and epigenomic datasets generated in WT and DNMT3A KO neurons. However, in my opinion, these analyses provide largely correlative rather than causative observations, in which the direct and secondary effects of DNMT3A and DNA methylation on gene expression can not be distinguished from each other. This is well illustrated by the proposed mechanism whereby the accumulation of H3K27me3 in DNMT3A KO neurons can compensate the loss of DNA methylation in order to maintain the repression of certain genes and thus confer robustness to neuronal maturation. However, such compensatory mechanism is only supported by the increased levels of H3K27me3 around the promoter regions of some genes, but whether this increased levels of H3K27me3 have any functional impact on gene expression and/or in neuronal function has not been addressed by the authors. Similarly, the authors uncovered a large number of genomic regions that lose DNA methylation in DNMT3A KO neurons (differentially methylated regions (DMRs)) and that frequently overlap with putative enhancers. Based on these observations, the authors suggest that DNMT3A is essential for the methylation and subsequent repression of neuronal enhancers that are active during prenatal brain development. However, these suggestions are not fully supported by the data, as the authors do not provide direct evidences of whether the loss of DNA methylation in enhancers has any impact on their activity (e.g. H3K27ac or eRNA levels) or function (e.g. changes in expression of target genes).

More generally, recent work in the epigenetics field suggests that the function of certain epigenetic regulators might not be directly linked to their associated epigenetic marks (e.g. MLL3/4 and H3K4me1). To conclusively assess whether the functional relevance of DNMT3A or PRC2 could be attributed to their enzymatic activities and associated epigenetic marks, the generation of catalytic mutants would be ideal. Generating these catalytic mutants in a conditional manner can be technically challenging. Therefore, in the absence of such mutants, strong claims regarding the functional relevance of epigenetic marks should be avoided.

Reviewer #1 (Public Review):

In this impressive manuscript the authors sought to monitor the activity of the two principal cell types within the ventral striatum's olfactory tubercle -- those expressing either the dopamine D1 or D2 receptors. Work by several groups, including from this specific group, have provided evidence that olfactory tubercle neurons flexibly encode the learned meaning of odors. Reports using immediate early gene expression (Murata et al 2015) or fiber photometry (Gadziola et al 2020) have begun to uncover the possibly unique activities of tubercle D1 or D2 neurons during or following associative learning of odors. Here, Martiros and colleagues take the important step of real time monitoring of these neurons with 2-photon microscopy, as mice learned to associate odors [and tones] with wither positive or aversive outcomes.

There are many strengths of this study. These include a carefully designed behavioral task which manipulated assigned valence to the stimuli. Ideal cellular-level resolution monitoring of D1 or D2 (via adora2a) neural dynamics via GRIN lenses coupled with multiphoton imaging. And concise analyses of the dynamics in relationship to the behavior. An additional important strength is the forthcoming and fair discussion of their results in context of prior literature which allows the reader with an appropriate appreciation for the advances of the present work and what future directions it may foster.

There is not a single objective weakness in this study.

Conclusions are well supported by the results.

The authors results uncovering differing roles of tubercle D1 and D2 neurons are important and help steer the field by recognizing that these cell populations may both a)have differing inputs but also b)may differentially influence downstream circuits which may afford affective learning and responding.

Reviewer #2 (Public Review):

In this manuscript, Martiros and colleagues characterize the functional properties of neurons in the mouse olfactory tubercle. They record, using 2-photon microscopy, neuronal responses to odors associated with appetitive or aversive unconditioned stimuli and show that the activity of D1 and D2 type dopamine receptor expressing neurons is modulated by odor outcome associations. D1 neurons robustly encode learned odor valence, and D1 neurons maintain an odor valence representation even when appetitive (water drop) or aversive (air puff) unconditioned stimuli are removed. In contrast, D2 neurons are more selective to odor identity than D1 neurons, and odor valence coding in D2 neurons is dependent on odor outcome associations. Finally, the authors show that in D1 neurons, odor and tone outcome associations recruit largely non-overlapping neuronal ensembles.

Together, the experiments and analyses described in this manuscript address important yet poorly understood questions about the cellular and circuit mechanisms underlying odor valence coding. However, several concerns about experimental design and data analysis and interpretation need to be addressed.

Reviewer #3 (Public Review):

Martiros et al. investigated whether medium spiny neurons in the striatal component of the olfactory tubercle (OT) acquire conditioned responses to odors that have been paired with unconditioned stimuli (water and airpuff). The authors found that both cells containing D1-type receptors (D1R) and D2-type receptors (D2R) acquire conditioned responses to odors. D1R cells appear to have responded to the valence more readily than the identity of unconditioned stimuli, and vice versa for D2R cells. The authors also found that tones can be used to condition D1R and D2R cells; however, conditioned responses with tones were not as much correlated with the valence as those of odors. The conclusions of the paper should be written with a nuanced manner.

Strength:<br /> The authors used state-of-the-art techniques to monitor changes in cellular activity over multiple days in awake animals engaging in conditioning tasks.

Weaknesses:<br /> 1) The grin lens, used to detect cellular activities, was large relative to the mouse brain, causing an extensive brain damage. A 1.0-mm diameter lens was unilaterally placed from the top of the brain to the bottom where the olfactory tubercle is situated. The lateral width of one hemisphere at the level of the olfactory tubercle is approximately 3.5 mm, indicating a large portion of the brain was damaged by the placement of the grin lens. This may be estimated that approximately 20-25% of the brain hemisphere anterior to the thalamus was damaged. The implication of this issue needs to be discussed.

2) The recording of cells may have included non-striatal cells. The olfactory tubercle consists of three major components: striatal, pallidal, and islands of Calleja units. These units are interwoven within the OT. Although the stratal unit is filled with medium spiny GABAergic neurons that the authors was interested in, there are other cells. The pallidal region contains GABAergic, cholinergic, and glutamatergic neurons, and the island Calleja contains granule cells. The authors need to inform readers whether the cells of the pallidal and islands of Calleja units contain D1R or D2R. For example, granule cells of the islands of Calleja have been shown to express D1R (Ridray et al 1998). This fact affects the interpretation of the present study. The implication of this issue needs to be discussed.

Ridray S, Griffon N, Mignon V, Souil E, Carboni S, et al. 1998. Coexpression of dopamine D1 and D3 receptors in islands of Calleja and shell of nucleus accumbens of the rat: opposite and synergistic functional interactions. The European journal of neuroscience 10: 1676-86

Here are notable authors' claims and this reviewer's responses.

Claim 1:<br /> The authors state "the OT is likely to be involved in learning about both positive and negative odor associations, rather than the alternative possibilities that the OT is only involved in learning rewarded odor associations, or that it encodes odor salience rather than signed odor valence." I believe that this is a reasonable conclusion.

Claim 2A:<br /> The authors state "D1 OT neurons selectively and bidirectionally encode learned odor valence, unlike D2 neurons". This statement should be attenuated. Their data suggest that both D1R and D2R neurons are involved in both valence and identity and that D1R neurons are more likely involved in valence than identity, and vice versa.

Claim 2B:<br /> The authors state "stimulus valence representation by D1 OT neurons is limited to olfactory stimuli, and does not generalize to multimodal stimuli." This statement is premature, and the authors should provide a more nuanced statement. I note two issues: First, the mice had different experimental histories between odors and sounds; the mice were trained with odors first (4 sessions) and then with sounds (3 sessions). Therefore, differential responses between odors and tones can be attributed to their experimental histories rather than olfactory and auditory modalities. Indeed, the data showed that the mice had not fully learned to discriminate between two tones as the mice displayed anticipatory licks upon the tone paired with airpuff. In addition, it is not warranted to have a sweeping generalization because the authors examined only one reward (water) and one type of sounds (tones). Odors may be better conditioned with water while other rewards may work better with tones. Tones may have affective qualities that may have interfered with water conditioning and were needed additional pairing sessions. Remember that the absence of evidence does not provide a proof. It could simply that it was not done well. Moreover, OT neurons clearly responded to the auditory stimuli. Although the OT is strongly linked with the olfactory system compared to other sensory systems, the OT can receive sensory-related information from the limbic cortical structures that provide afferents, including the medial prefrontal cortex, basolateral nucleus of amygdala, and subiculum. Perhaps, the authors should discuss possible roles of these cortical structures in conditioned signals that were detected in the present study and how the large brain damage caused by the grin lens might have compromised afferent inputs to the OT.

Claim 3:<br /> The authors state "valence representation is not correlational in nature, but likely serves to inform downstream brain regions of the value of odor stimuli". The present study showed that OT responded to conditioned odors in the absence of behavior. Although this result makes it difficult to hypothesize the functional role of those signals, it is reasonable to infer that the acquired conditioned signals influence downstream systems for some unknown function. However, the method used to obtain the data was correlational. The authors should avoid misleading phrases. Additional experiments are needed to understand functional role of the acquires signals.

Reviewer #1 (Public Review):

Sučević and Schapiro investigated a neurobiologically inspired model of human hippocampal structure and computation in category learning. In three separate simulations, the model (C-HORSE) is presented with learning tasks defined by various category structures from prior work and evaluated for its ability to learn the category structure, generalize categorization to novel stimuli, and accurately recognize previously encountered stimuli. Although originally conceived of as a computational model of associative memory, C-HORSE is demonstrated to quite naturally account for human-like learning of the three category tasks. Notably, the authors characterize the mechanisms underlying the model's learning by way of additional simulations in which "lesions" to the model's monosynaptic pathway (MSP; direct connections between ERC and CA1) are contrasted with lesions to its trisynaptic pathway (TSP; pathway connecting ERC-DG-CA3-CA1). These in silico lesions offer key insight into the computational principles underlying theorized hippocampal functions in category learning: whereas MSP provides incremental learning of shared features diagnostic to category membership that are important for category generalization, TSP learns item-specific information that drives recognition behaviour. The authors propose that C-HORSE's successful account of a broad set of category learning datasets provides clear support for the role of complementary hippocampal functions mediated by MSP and TSP in category learning. This work adds compelling computational evidence to a growing literature linking hippocampus to a broader role in cognition that extends beyond declarative memory.

The model simulations are clear and properly conducted. The three datasets examined offer a relatively broad set of findings from the category learning literature; that the models provide reasonable accounts of human performance in all three speaks to the model's generalizability. Overall, I find this work exciting and an important step in linking longstanding well-established formal learning theories of psychology with neurobiological mechanism. Several weaknesses dampen this excitement, each of which are detailed below:

1. C-HORSE is presented as a new entry into a rich field of formal computational models of category learning. As noted above, the datasets examined span a broad range of learning contexts and structures and the model's ability to account for learning behaviour is compelling. However, no other models are leveraged to perform a direct evaluation. In other words, C-HORSE's predictions are compelling, but is it better than other competing models in the literature? To be clear, C-HORSE offers a novel alternative with its fundamental mechanisms originating from anatomical structure and connectivity. As such, a proof-of-concept showing that such a neurobiologically inspired framework can account for category learning behaviour is a worthwhile contribution in its own right and a clear strength of this paper. However, how to consider this model relative to existing theoretical frameworks is not well described in the manuscript.

2. Relatedly, C-HORSE is evaluated in terms of qualitative fit to behaviour measures from prior studies and in all three simulations restricted to measure of end of learning performance. Again, an appeal to the proof-of-concept nature of the current work may provide an appropriate context for this paper. But, a hallmark of well-established category learning models (e.g., SUSTAIN, DIVA, EBRW, SEA, etc.) is their ability to account for both end of learning generalization (and in some cases, recognition) and behaviour throughout the learning process. C-HORSE does provide predictions of how learning unfolds over time, but how well this compares to human measures is not considered in the current manuscript. Such comparisons would strengthen the support for C-HORSE as a viable model of category learning and help position it in the busy field of related formal models.

3. A consistent finding across all three simulations is that the TSP provides item-specific encoding. Evidence for this can be inferred by contrasting categorization and recognition performance across the TSP- and MSP-only model variants. In the discussion, the authors draw a parallel between exemplar theories of category learning and the TSP, which is a compelling theoretical position. However, as noted by the authors, unlike exemplar theories, the TSP-only model was notably impaired at categorization. The author's suggestions for extensions to C-HORSE that would enable better TSP-based categorization are interesting. But, I think it would be helpful to understand something about the nature of the representations being formed in the TSP-only model. For example, are they truly item-specific, are the shared category features simply lost to heightened encoding of item-unique features, are category members organized similarly to the intact model just with more variability, and so on. Characterizing the nature of these representations to understand the limitations of the TSP-only model seems important to understanding the representational dynamics of C-HORSE, but are not included in the current manuscript.

4. In general, a detailed description that links model mechanisms and analyses to the learning constructs of interest for the different simulations is lacking. For example, RSA results for simulation 1 are contrasted for initial and settled representations, but what is meaningful about these two timepoints is not directly stated (moreover, what initial and settled response mean in terms of the current model is not explained). The authors do briefly suggest that differences between initial and settled representations may reflect encoding dynamics before and after big-loop recurrence, but this is not established as a key metric for evaluating the nature of the model representations. In general, more motivation is needed to understand what the chosen analyses reveal about the nature of the model's learning process and representations.

5. I appreciate the comparison in the discussion to extant models of categorization. Certainly, the exemplar and prototype models are fixtures of the category learning literature and they somewhat align with the type of learning that TSP and MSP, respectively, provide. REMERGE and SUSTAIN are also briefly mentioned, but their discussion is limited which is unfortunate as they are actually more functionally equivalent to C-HORSE. I think, however, that the authors are missing an opportunity to discuss how C-HORSE offers a means for bridging levels of analysis to connect neurobiological mechanisms with these notably successful psychological models of category learning. Rather than framing C-HORSE as a competitor to existing models, it should be viewed as an account existing on a different level of analysis. In this sense, it complements existing approaches and potentially extends a theoretical olive branch between the psychology and neuroscience of category learning.

6. The discussion takes a broad perspective on covering evidence concerning hippocampal contributions to category learning. Although comprehensive, some sections are not well connected back to the main thrust of the paper. For example, a section on neuropsychological accounts of the hippocampus and category learning summarizes central aspects of this literature but is never reflected on through the lens of the current findings. I do think this prior work is relevant, especially since it a central theme of the hippocampus not being necessary for category/concept learning, but its connection back to the current study is not well argued. Similarly, the section on consolidation and sleep is relevant, but in its current form does not seem to fit with the rest of the paper.

Reviewer #2 (Public Review):

The authors present a model of the hippocampal region that incorporates both the (indirect) tri-synaptic and (direct) mono-synaptic pathways from entorhinal cortex (EC) to CA1 - the former incorporating projections from EC to dentate gyrus (DG), DG to CA3, and CA3 to CA1, and exhibiting a higher learning rate. They demonstrate that exposing this network to stimuli consistent with standard empirical tests of category learning (e.g. where within-category exemplars share a set of common features) allows the network to reliably assign both novel and previously encountered stimuli to the correct category (e.g. the network can learn to classify stimuli and generalise this knowledge to new examples). They show that the tri-synaptic pathway (TSP) preferentially supports the encoding of individual exemplars (e.g. analogous to episodic memory) while the mono-synaptic pathway (MSP) preferentially supports category learning.

The manuscript is well written, the simulation details appear sound, and the results are clearly and accurately presented. This model builds on a long tradition of computational modelling of hippocampal contributions to human memory function, strongly grounded in anatomical and electrophysiology data from both rodents and humans, and is therefore able to link phenomena at the level of individual cells and circuits to emergent behaviour - a major strength of this, and similar, work. However, I have two major concerns relating to the relationship between these findings and previously published work by the same and other authors.

First, it is not clear to me - from the manuscript - whether these results represent a significant novel advance on previous publications from the same senior author. Figures 1 and 3D are almost identical to figures published in Schapiro et al. (2017) Phil Trans B, and the take-home message (that the MSP might support statistical learning) is the same. In brief, it seems that the authors have subjected an identical network to some new (but related) tasks and reached the same set of conclusions. I see no distinction between learning to extract 'statistical regularities' (in previous work) and learning 'the structure of new categories' (described here). As an aside, demonstrating that an autoencoder network can learn stimulus categories and generalise to new exemplars is also well established.

Second, I have some concerns with the relationship between the properties of this hippocampal network model and well described properties of single cells in the rodent and human hippocampus. In particular, the CA1 units in this model (and to some extent, also the CA3 units) come to respond strongly to all exemplars from within each category (e.g. as shown in Figure 3D, bottom right panel). This appears to be at odds with the known properties of place and concept cells from the rodent and human hippocampus, respectively, which show little generalisation across related concepts (i.e. the Jennifer Aniston neuron does not fire in response to other actors from Friends, for example). If the emergent properties of this model are not consistent with existing data, then it is not a valid model.

More generally, the authors are clear that this model is "a microcosm of [the] hippocampus-neocortex relationship" and that the properties of the MSP "mirror those of neocortex". Why not assume that category learning is supported by an interaction between hippocampus and neocortex, then, as in the complementary learning systems (CLS) model? Aside from some correlational fMRI data and partial deficits in hippocampal amnesics - either of which could have a myriad of different explanations - what empirical data is better accounted for by this model than CLS? Put differently, what grounds are there for rejecting the CLS model? To some extent, this model appears to account for less empirical data than CLS, with the exception of a few recent neuroimaging studies (which are hard to interpret at the level of single cells)

Reviewer #3 (Public Review):

The current work aimed to determine how the hippocampus may be able to detect regularities across experiences and how such a mechanism may serve to support category learning and generalization. Rapid learning in the hippocampus is critical for episodic memory and encoding of individual episodes. However, the rapid binding of arbitrary associations and one-shot learning was long thought suboptimal for finding regularities across experiences to support generalization, which were instead ascribed to other, slower-learning memory systems. More recent work has started to highlight hippocampal role in generalization, renewing the question of how generalization can be accomplished alongside memory for episodic details within a single memory structure. The current paper offers a reconciliation, presenting a biologically-inspired model of the hippocampus that is able to learn categories alongside stimulus-specific information comparably to human performance. The results convincingly demonstrate how distinct pathways within the hippocampus may differentially serve these complementary memory functions, enabling the single structure to support both episodic memory and categorization.

Major strengths and contributions

The paper includes simulation of three distinct categorization tasks, with a clear explanation of the unique aspects of each task. The key results are consistent across tasks, lending further support to the main conclusions of the role of distinct hippocampal pathways in learning specific details vs. regularities. Together with prior work on how the same architecture can support statistical learning in other types of tasks, this work provides important evidence of the broad role of the hippocampus in rapid integration of related information to serve many forms of cognition.

Throughout the paper, the authors nicely explain in conceptual terms how the same underlying computations may serve all three categorization tasks as well as statistical learning and episodic inference tasks. Thus, the paper will be of broad interest, beyond researchers focused on modeling and/or categorization.

On a conceptual level, this work provides a fruitful framework for understanding hippocampal functions, representations and computations. It provides a highly plausible mechanistic explanation of how category learning and generalization can be accomplished in the hippocampus and how distinct types of representations may emerge in distinct hippocampal subfields. The framework can be used to derive new testable predictions, some of which the authors themselves introduced. It also provides new insights into how the outputs of different pathways influence each other, providing a more nuanced view of the division of labor and interactions between hippocampal subfields. For example, the big loop recurrence would eventually lead to category influences even on the initially sparse, pattern separated representations in the CA3, which is an idea consistent with empirical observations.

The presented computational model of the hippocampus is currently the most detailed and biologically plausible hippocampal model easily applicable in the area of cognitive neuroscience and behavioral simulations. The commonalities and differences with other related models (conceptual and computational) are well explained. Both the conceptual and technical descriptions of the model are exceptionally clear and detailed. The model is also publicly available for download for any researcher to use with their own task and data. All these aspects make it likely that other researchers may adopt the model in a wider range of tasks, stimulating new discoveries.

The autoencoder nature of the model and the use of categorization tasks meant that some measures of interest, like recognition of exemplar-specific information, could not be evaluated by direct reading of the output layer to compare with some label (like old/new). The authors however came up with clever ways how to evaluate recognition performance in each task that was sensible and highlighted the multiple ways how one may think about information contained in neural representations in each layer. This approach can also be utilized by others for evaluating item-specific and category information in activation patterns, for example in analyses of fMRI.

Finally, I thought the current paper and provided model may also serve as an excellent introduction to computational modeling for those new to this approach. The exceptional clarity of the conceptual and technical description of this model and the clear logic of how one may model a cognitive task and interpret results made this paper fairly accessible. Furthermore, the paper offered new insights and predictions based on analyzing the model's hidden layers, lesion performance, and/or noting some patterns of behavior unique to specific tasks. This was also instructive for highlighting the distinctive contributions that the computational modeling approach can have for furthering our understanding of cognition and the brain.

Weaknesses

The paper's strengths far outnumbered the weaknesses, that are minor. For one, the selected categorization tasks nicely complemented each other, but only covered stimuli with discrete-value dimensions (features like color, shape, symbol, etc). The degree to which the results generalize (or not) to continuous-value stimuli and different category structures (for instance information-integration or rule-based in COVIS framework) is not clear. How the model could be adjusted for continuous-value stimuli was not specified.

There is compelling evidence for the dissociation between different hippocampal pathways and subfields (CA1 vs. CA3) that the model is based on. As the authors noted, there is also compelling evidence for functional dissociations along the long hippocampal axis, with anterior portions more geared towards coarse, generalized representations while posterior towards more detailed, specific representations. The authors nicely pointed out that these proposals of within-hippocampus division of labor are less orthogonal than they may first appear, as there is greater proportion of CA1 in the anterior hippocampus. However, it is premature to imply that this resolves the CA1/CA3 vs. anterior/posterior question; the idea that existing anterior findings may be simply CA1 findings is currently only speculation. Furthermore, first studies indicating that anterior/posterior representational gradients may exist within each subfield are beginning to emerge.

Reviewer #1 (Public Review):

This is a very interesting paper trying to quantify excess deaths due to the COVID-19 pandemic in the USA. The paper is roughly divided into two main sections. In the first section, the authors estimate age and cause-specific excess mortality. In the second section, using their excess mortality estimates, the authors attempt to disentangle the impact of SARS-CoV-2 infection (direct impact) vs. the impact of NPIs on this excess mortality (indirect impact). I have some concerns, particularly with respect to the second section.

The model used to estimate excess mortality is quite clear. The authors adjust the baseline model to account for low influenza circulation (and deaths) during the COVID-19 pandemic, to avoid underestimating the number of deaths caused by COVID-19. While this makes sense if the authors are trying to estimate the total number of deaths caused by COVID-19, I'm not sure it needs to be accounted for if the authors want to estimate excess/added deaths. A counterfactual scenario would've included influenza. It also raises the question of whether (conceptually) they should be adjusting for other causes of deaths that may have also decreased during the pandemic. The authors briefly acknowledge this in the discussion ("we can't account for changes in baseline respiratory mortality due to depressed circulation of endemic pathogens other than influenza") but my comment goes beyond respiratory diseases. Analyses of excess mortality from other settings have suggested, for example, decreased deaths due to fewer traffic accidents (not in the US) or due to decreased air pollution, and not accounting for these would also lead to an underestimate of the total deaths caused by COVID-19. I understand that it is not feasible to account for all potential factors, so I wonder if they should focus on reporting excess deaths as compared to a counterfactual with influenza.

The second section, trying to estimate direct vs. indirect effects is also very interesting. However, more details are required about the regression model used and, importantly, what the assumptions and limitations of the approach are. Specifically:

- Please provide a bit more information on the regression used for direct vs. indirect effects. I'd like to see explicit discussion of the assumptions and limitations of the approach but also of the stringency index used. Does this model include an intercept? Was the association between stringency index and excess deaths assumed to be linear? Or were different functional forms considered? It is also not clear how well the model fits the data.<br /> - Related to the above, please provide more details on how the results of the regressions were translated into the results presented. The main text reports percentages, but the methods only briefly explain how numbers of direct deaths were calculated, and the supplementary tables report coefficients. It is not clear if these estimates of direct and indirect deaths were somehow constrained to add up to the total number of excess deaths, but it doesn't seem like it since point estimates cross 100% in some cases.<br /> - Please discuss the potential limitations of using the stringency index to quantify NPIs.<br /> - When estimating direct and indirect effects, the paper assumes that the estimated parameter is time-invariant? Indirect effects might have changed over the course of the epidemic by factors not necessarily captured by the stringency index used, particularly since the index doesn't take into account the implementation of the measures. Have the authors tested this assumption?<br /> - The authors state "In contrast, the indirect impact of the pandemic measured by the intervention term was highest in youngest age groups, decreased with age, and lost significance in individuals above 65 years" - I'm not entirely sure of where this statement comes from? For example Table S3 suggests that the indirect effect (multivariate or univariate) is higher in 25-64 yo than in <25s? The same table also suggests negative impacts (protective effects?) in >75s in the multivariate model. Please clarify.<br /> - How do the authors interpret "Percents of excess deaths" over 100%? Similarly, I don't fully understand how to interpret "The upper bound of the 95% confidence interval for heart diseases was above 100% (158%), suggesting that for every excess death from heart disease estimated by our model, up to 1.58 death from heart disease could be directly linked to SARS-CoV-2 infection.<br /> - Table 3: The signs of the point estimate vs CI for vehicle accidents are inconsistent.

Reviewer #2 (Public Review):

In this paper, the authors examine the impacts of the COVID-19 pandemic on excess mortality in the US up to April 30, 2021. The authors separate direct impacts (caused by COVID-19, coded as such or not) of the pandemic from indirect impacts (disruptions), finding that most excess deaths (90%) are due to direct impacts. Importantly, the authors find that the official COVID-19 death tally is an undercount of these deaths. Moreover, the authors also find that excess deaths due to other causes are the main driver of excess mortality among younger populations.

This study's strength includes the use of whole population surveillance data (vital registration) for a long period of time, the modeling of excess mortality that allows getting a more accurate estimate of the impacts of the pandemic, and the attempt to separate direct from indirect impacts. The key weaknesses are a lack of consideration of the challenges of using vital registration data and a lack of explicit outlining of causal assumptions for the part of the paper examining the effects of non-pharmaceutical interventions.

While I do believe that the authors have achieved their aims, especially in determining the number of excess deaths (all cause and by cause, and by age and state). The part about separating direct from indirect impacts may require some extra work in outlining assumptions or clarifying methods in order for it to be fully appraisable.

This is an important manuscript and study, given the complicated nature of coding causes of death (especially with a new disease), allowing for a more precise estimation of the impacts of the pandemic. If the authors address issues related to the direct vs indirect impacts, I believe that part can also be very important, as it would allow for better differentiation of the effects of COVID-19 vs the effects of human action.

Reviewer #3 (Public Review):

Authors examine mortality data in the US and use time-series approaches to estimate excess mortality during the COVID-19 pandemic.

Major comments:

I would encourage authors to discuss the two different concepts of excess mortality:<br /> (#1) what deaths were caused, directly or indirectly, by the pandemic. This is what the authors have aimed to assess, and I have no major concerns with the methodology<br /> (#2) how many additional deaths occurred during the pandemic, compared to what would have been expected in the absence of a pandemic. For such an analysis I think expected annual influenza deaths should be added back to the baseline (or subtracted from the excess)? Some of the discussion seems to relate more to an impression of #2 rather than #1 but I would be interested in the authors' thoughts.

2. Authors estimate fewer excess COVID deaths in the elderly than there were confirmed deaths (Table 3). Could this be an indication of some confirmed deaths being "deaths with COVID" rather than "deaths from COVID"? I'm not sure how to interpret the %s in the final column when they exceed 100%. The authors suggested a harvesting effect but I would suggest "deaths with COVID" might be a more likely explanation? This issue can be a limitation of confirmed-death data.

Reviewer #1 (Public Review):

The study by Monerisi et al. reports that loss-of-function mutations in metabolic pathways do not necessarily have a negative impact on cancer growth. The authors suggest that small solutes transferred via gap junction channels formed between wild-type cells and cells express mutants defective in metabolic pathways rescue the metabolic-deficient cancer cells. Through the examination of multiple human cell lines with several advanced means to determine gap junction coupling, Cx26 was identified as a major connexin molecule involved in medicating gap junction coupling between colorectal cancer (CRC) cells. The gene mutations of three metabolic gene mutations were investigated for major metabolic function of the cell, pH regulation, glycolysis and mitochondrial function.

Strengths:

The paper tests a new hypothesis that the mutations that inactivate key metabolic pathways do not incur functional deficits in cancer cells expressing the mutants due to their gap junction coupling to wild type cells.

From microarray data they identified multiple connexins expressed in various CRC cells. Several advanced analyses were used to assess gap junction coupling in CRC cells including fluorescence recovery after photobleaching (FRAP). The extent of permeability at steady state was evaluated using CellTracker dyes and coupling coefficients were determined. They also used flow-cytometry to study dye transfer, which will provide a quantitative, dynamic means for study cell coupling. The data showed that knocking down Cx26 could greatly reduce diffusive exchange in most of the CRC cells tested.

The study focused on three metabolic genes, Na+/H+ exchanger NHE1, a regulator of intracellular pH, a glycolytic gene, ALDOA and mitochondrial respiration gene, NDUFS1. These genes were knocked out in the selected CRC cells highly expressing these genes. The co-culture studies were well executed with fluorescence-markers distinguishing the WT and knockout cells and well-defined readouts such as intracellular pH, media pH, glucose/lactate levels and mitochondrial O2 consumption and glycolytic acid.

The experiments in general were well designed and conducted, and the data supported the conclusions. The paper is also logically written and figures were well presented providing clear graphic illustrations.

Weaknesses:

Although the hypothesis is innovative, no clear justification is provided that illustrates the scenario representing the clinical situation. The remaining questions include: What kind of somatic mutations in cancer cells has little impact on their growth and progression? What types of WT cells, within the tumor cells or with neighboring normal cells? Whether the current experimental design closely recapitulates the scenario in vivo?

The readouts for co-culturing for glycolytic ALDOA and NDUFS1 knockout are only cell mass, without determining the more relevant markers, glucose/lactate and mitochondrial O2 consumption and glycolytic acid production.<br /> The study needs to include cells without functional gap junctions like the characterized negative control RKO cells.

Reviewer #2 (Public Review):

This paper is a logical extension of the 50 year-old concept of the "bystander effect" in tumors, wherein the effects of anti-tumor chemotherapeutics extend beyond the cells that take them up due to spread through gap junctions to adjacent cells. In this case, however, the authors have creatively realized that the reverse might also occur, and that tumor cells with otherwise fatal mutations in essential metabolic pathways can be rescued by their neighbors through passage of the missing metabolites through gap junctions. This can explain why mutations in other critical pathways, such as protein synthesis and transporters, are selected against in rapidly growing tumors, but others in equally critical pathways of glycolysis, electron transport, etc. are not, despite these genes having been demonstrated to be essential in in vitro KO studies (where all cells in the plate have the critical gene knocked-out). A series of elegant experiments are used to test this proposal in several colorectal cancer (CRC) cell lines using three examples - pH regulation (defective Na+/H+ exchanger NHE1), glycolysis (defective Aldolase A (ALDOA)) and oxidative phosphorylation (defective Complex 1 - NDUFS1).

The authors first determine the levels of different Cx proteins expressed in each cell line, and determine that for most Cx26 and 31 are dominant, although come lines have a subset of cells with high Cx43 expression. They then use Cell Tracker Green to pre-label cells and use FRAP as a means to measure how well the cell population is coupled. This is a useful measurement but is significantly over-interpreted by the authors as a "permeability" in uM/min. This is not really a permeability, which requires knowledge of the concentration gradient of the permeant species, relative cell volumes, etc. Rather it is a rate of fluorescent recovery that is presumably correlated with, but not quantitatively related to, levels of coupling.

This fluorescent recovery is shown to be sensitive to siRNA KO of Cx expression, but strangely its reduction is only correlated with KD of Cx26 in the 5 cell lines examined. KD of Cx43 (in LOVO cells) and Cx31 in all 5 cell lines had no effect or in some cases seemed to increase the rate of recovery (DLD1 and SNU1235). This is a notable finding, yet the authors choose to completely ignore it and continue with Cx26 KDs in studies of specific metabolite transfers. Some discussion should be included as to why KD pf these Cxs has no effect or causes an apparent increase in coupling of the cells.

Rather than just focus on acute transfer of dye between cells, the authors develop a system using 50/50 mixes of cells labeled with two junctionally permeant dyes and measured the degree of mixing at equilibrium (48 hours). This is presented as a "coupling coefficient", but how it is calculated, and its significance is not well described, and does not correlate with the historical use of this term in the literature. Nonetheless, the studies do seem to demonstrate a good degree of equilibration, although it would have been informative to determine of the cells that do not exchange dyes express Connexins. To document that this equilibration requires gap junctions, the authors employ low density cultures, which significantly decrease dye exchange. However, in at least one cell line (SW1222) dye exchange is only reduced by <50%, indicating a very high background to this assay. This is not addressed.

The most compelling part of the study is the use of reporters to directly demonstrate a role of Cx26 coupling of cells to rescue cells with mutations of the three genes mentioned above when mixed with normal neighbors. This case was most convincing in the cases of ALDOA and NDUFS1, with the data for the pH regulation requiring more explanation for full understanding of the data shown (e.g. Figs 7 G and H).

Overall, the study does a credible job of demonstrating that Cx26 coupling of CRC cells serves to rescue cells with mutations in critically necessary metabolic pathways, presumably due to transfer of metabolites from surrounding wt cells. However, some of the results indicate this is not a simple process where all connexins behave similarly, and some effort should be made to investigate if Cx31 and 43, which do not seem to play the same roles in maintaining cell coupling as Cx26, also play any role in such metabolic rescue.

Reviewer #3 (Public Review):

Strengths of the study include that it appears to be a careful and well thought out set of experiments. The analysis and treatment of multiplexed data is also sophisticated. For the most part, the work is clearly and logically described, as well as well illustrated. In general, the authors achieved their experimental goals, and the methods while not entirely new, do provide new twists and augmentations that should be useful to the field. A general weakness is that this is not entirely a new story. Instead, it is a variant of one of the oldest concepts in the field of gap junction biology i.e. "Metabolic cooperation". The term "Metabolic cooperation" (i.e., as mediated by gap junctions) was not mentioned by the authors, but it is a long-established and foundational concept in the field. Indeed, in a classic paper by Gilula and colleagues published in 1972, the experimental approach used was similar to that of the study in hand. These earlier authors showed how transformed cell lines with deficiencies in hypoxanthine metabolism can be "rescued" by "metabolic cooperation" in co-culture with metabolically competent cells via passing a gap junctional permeant molecule. This and other relevant papers were not cited. More importantly, the extant literature places the onus on the authors to explain and convince reviewers why this study is more than an incremental step.

Reviewer #1 (Public Review):

Wahle and colleagues surveyed the occurrence of the non-canonical of "axon carrying dendrites" of neocortical pyramidal cells across different mammalian species. Their results indicate that there are differences between rodents, pigs, cats and ferrets on the one hand and primates on the other. Pyramidal cells of primates (humans and monkeys) have overall a lower proportion of axon carrying dendrites in the gray matter, which seem to be more concentrated in infragranular layers and in white matter.

The major strength of the manuscript lie in the large scope of the systematic survey of pyramidal cells with axon carrying dendrites across a range of different mammalian species. The authors also include developmental data and results comparing different cortical layers as well as the results from white matter and gray matter. With the necessary diversity of histological source material necessary for this study, the authors should assess and discuss potential other sources of differences between the species and their strategy to overcome these more explicitly.

The presented data and scope of the study are impressive and shed light on the potential evolutionary differences in the cortical circuitry of primates in contrast to other mammals.

Reviewer #2 (Public Review):

This is an interesting and scientifically rigorous report documenting atypical, dendritic locations for the emerging axon of pyramidal neurons. This is not an entirely new observation (the authors cite relevant publications, including Kole and Brette, 2018 and Mendizabal-Zubiaga et al., 2007), but still important, as a relatively overlooked fact with functional implications. A main feature of the present report is an exceptionally thorough cross-species survey, from which the authors conclude that, as compared with non-primates, the macaque and human brains have a lower proportion of neocortical pyramidal neurons with axon carrying dendrites. The results might be further supported by additional experiments, especially ultrastructural data, or by including more extensive developmental data. There is a section on Development, but there is hardly any Discussion. However, these matters are raised and adequately treated by reference to the existing literature.

Reviewer #3 (Public Review):

The authors used neuroanatomical techniques to study neocortical pyramidal neurons from several different mammalian species. Their message is that primate neocortex differs from that of other mammals in having substantially fewer cells with axons emanating from dendrites, rather than the canonical route from the soma. The authors employed a range of standard methods, ranging from tracer injection to Golgi impregnation to immunocytochemistry. The feature the authors report is undeniable; there clearly are axons that emanate from dendrites of neocortical pyramidal neurons. Prior studies have reported that these axons are more excitable, thus leading to the intriguing possibility of a fundamental architectural (and thus presumably functional) feature in how primate neocortex operates.

This is a provocative narrative, that leads to a number of interesting questions. However, I have reservations that the authors must address before I believe the claim that primates are really fundamentally different from other mammals in this respect. A strength but also a central limitation of this study is that different species were compared using different methods, and different areas were studied in different species. The authors make the implicit assumption that the prominence of this feature does not differ among cortical areas. However, it is entirely plausible that the proportion of neurons with axon-carrying dendrites does differ among cortical areas. The authors also group neurons into 2 large populations: infra- and supragranular. But again, layers 2 and 3 differ from one another (as do layers 5 and 6) in the specific populations of pyramidal cells they contain (morphological and neurochemical types, inputs and outputs, etc.). Certainly many studies do group neurons into these broad populations, but for this kind of comparison relevant differences or similarities could have been lost. Comparisons among species ideally would have all been in the same layer and area.

Another limitation is that the same method was not employed in different species. The reader needs to know that different methods reveal the same proportion of axon-carrying dendrites in a given area of a certain species. This should have been stated more clearly and earlier in the text; it took examination of the data tables to see this. The tables show that measurements were made in several different cortical areas. Can the authors provide any evidence that the proportion of neurons with axon-carrying dendrites does not differ in any one species among cortical areas? Figure 3 description and/or legend needs to state clearly that different species' neocortex was studied in different areas (and if all Fig3 samples shown are from same layers). Supplementary Excel file suggests that for humans Golgi-Kopsch reveals fewer infragranular AcD-cells than Golgi-Cox (4.43 vs 1.39), while for adult macaques Golgi-Kopsch revealed fewer than biocytin injection or SMI-32/BetaIV-spectrin immunofluorescence (13.34 vs 7.98 vs 6.29). Since the human data relies on Golgi methods, the authors must reassure the readers that the comparison of species is validated by direct comparison of different methods.

The message that primates have fewer cells with axon-carrying dendrites than other mammals might therefore certainly be interesting but far less compelling. The message might be that primate neocortex is not qualitatively different from that of other species; instead they simply have somewhat fewer AcD-bearing neurons than other mammalian species. But even that more modest conclusion is suggested but not fully proven by the data here.

I was puzzled by Fig 4 not including primate tissue. If the message is that spine density does not differ in dendrites with and without axons, surely it would be important to include primate tissue in this comparison; the comparison between primates and on-primates is after all the core message of this study. I also do not think the values for each species for non-AcD and shared root should be connected by a line; I suggest instead there should simply be a scatter of values for each group with a large symbol indicating mean or median value of each group. This would facilitate comparison.

Reviewer #2 (Public Review):

In this manuscript, Kim et al. scrutinize the role of the Seipin transmembrane domains during lipid droplet biogenesis mainly by molecular dynamics simulations. The study primarily exploits a a new structural model of human Seipin that includes the transmembrane regions. The authors do an excellent job in introducing/explaining the parameters analysed from the MD simulations, and confirm previously observed roles for the transmembrane segments in LD biogenesis. The authors identify key charged residues flanking Seipin transmembrane regions and propose a model for how the they facilitate the budding of lipid droplets from the ER membrane.

The role of the Seipin TMs in the formation of LDs is of great interest to the field. However, much of the data in this manuscript confirms previous observations, and as such the conceptual leap achieved is minor. On the other hand, the identification of conformational changes in the transmembrane region and flanking charged residues is novel and interesting. A drawback of the study is its complete dependence of incompletely described structural model of human Seipin. Given the importance of this model for the conclusions of the study, it is essential to describe the model in detail. The role of the charged residues flanking Seipin transmembrane segments should also be further characterized, in particular their potential impact in protein expression, membrane insertion and topology.

Joint Public Review:

The authors sought to demonstrate that for studies of aging, the 20-day life span of the nematode C. elegans gives it an advantage as a model, over mice (2 years) or humans (80 years). They were studying muscle aging and they showed that UNC-68, a single protein which is a homolog of three mammalian calcium release channel proteins RyR1, 2 and 3 is complexed with homolog proteins as part of a large multi-protein complex. The methods used were largely biochemical, using antibodies to identify the proteins they were interested in and a compound DNP to determine the degree of oxidation of UNC-68. There could be stronger support for the conclusion that antioxidant capacity contributes to life span.

They do show that a compound which was invented by one of the authors appeared to stabilize the association of FKB2 (the C. elegans homolog of the mammalian FKBP12 and 12.6 expressed in muscle and heart respectively) with UNC-68 but they did not show that if the association is strengthened, it reduces oxidation of UNC-68. Overall the data shown is consistent with what the same authors have shown in mammals.

Some weaknesses: It is unclear if there is sufficient evidence that antioxidant capacity contributes to life span, and because UNC-68 is not solely expressed in muscles they cannot be sure that the effect that they see is related to muscle function as opposed to nerve function.

They do show that a compound which was invented and marketed by one of the authors appeared to stabilize the association of FKB2 (the C. elegans homolog of the mammalian FKBP12 and 12.6 expressed in muscle and heart respectively) with UNC-68.

The authors should discuss differences in EC coupling in C. elegans relative to that of mammals and comment on the validity of C. elegans as a model for aging human muscle.

The authors do provide evidence for a remarkable degree of evolutionary conservation of excitation-contraction and in particular with respect to the calcium release channel. They provide a model system that might be important for the field including with respect to aging.

Reviewer #1 (Public Review):

The authors estimated the effectiveness of border restriction, testing and contact tracing in managing transmission of Covid19, and in detecting "missed" Covid19 cases. They developed a standard branching process model to disentangle the effects of each control measure on the incidence of missed infections, by fitting their model to data on cases both at the border and in the community of Singapore, from the beginning of the Covid19 outbreak until December 2021.

The Authors modelled detected and undetected community infections as two separate branches of the transmission tree. They then fitted their model to the observed incidence data to obtain an estimate of the number of missed infections. Through this method, they explained the importance and contribution of case ascertainment (through testing and contact tracing), as well as border and community restrictions, towards transmission reduction.

This modelling and inference framework could be applied to data from anywhere in the world to estimate the number of undetected infections when in lack of infection prevalence data.

Strengths:<br /> For each of the five phases of border and public health measures put in place in Singapore in 2021, the authors successfully provided estimates on the number of undetected community cases, effectiveness of contact tracing and testing in finding unlinked cases, and effective reproduction numbers of both detected and undetected cases. All these estimates can be valuable to Covid modellers worldwide to either benchmark or parametrise their own model parameters, and to Singapore's public health officials to decide on future strategies of transmission prevention.<br /> Estimating infection prevalence and case ascertainment rates is one of the main challenges of Covid modellers everywhere. The authors' method to reconstruct the transmission tree of both known infections and undetected ones, and the subsequent fitting to observed data, could be used to estimate case ascertainment rate in the absence of prevalence surveys.<br /> The authors also found that contact tracing is only useful for transmission reduction when coupled with a high rate of case ascertainment. This is a well-known but important result, highlighting the need for more timely and accessible community testing.

Weaknesses:<br /> The authors' models and estimates are mostly well supported by data, but the Methods need to be clarified and extended, and the results could be presented in a clearer way.<br /> The transmission model in particular needs to be presented in a more detailed way to avoid confusion around the modelling assumptions and to allow easy reproduction of the model by the reader.<br /> It would also be very useful to readers to visualize the different restriction measures in place together with the result graphs, to strengthen the link between the two and to highlight the effect that different border and public health regimes have on transmission and on the proportion of undetected infections, which the authors mention in the main text.<br /> While these results can definitely help the Singapore decision-makers design an efficient transmission control strategy, this paper could also be useful to researchers abroad. It is therefore important that the model is explained more clearly and that results and assumptions be benchmarked against those from some other country.

Reviewer #2 (Public Review):

This work combines multiple data sources and a branching-process mathematical model to assess the effectiveness of specific types of COVID-19 interventions including contact tracing, border screening, and case finding. The focus is on the original SARS-CoV-2 (2020) and the Delta (2021) variant outbreaks in Singapore. Utilizing data on both linked and unlinked cases, the model is also used to predict the total number of missed infections.

Strengths:<br /> The study provides a way to utilize data to understand the importance of various simultaneously employed intervention strategies throughout the pandemic. Given the constantly evolving state of the epidemic, this retrospective study provides insight into what interventions worked under which conditions. This will be valuable for policymakers to understand what types of strategies to prioritize.

The underlying model formulation has been used previously to understand components of transmission during the COVID-19 pandemic. Case data from Singapore is used to fit the model. Model conclusions on the number of true infections are consistent with a published seroprevalence study.

Weaknesses:<br /> The paper currently provides an incomplete description of the model. Multiple terms (e.g. cases vs infections) are used throughout the manuscript to have a precise meaning, but that is not apparent until reaching the Methods section at the end. As these terms could be misinterpreted, a precise definition should come earlier. More information is needed regarding the parameters. It is unclear which parameters were fit, and no parameter values were given. For the lognormal, a mean is given, but no standard deviation.

The identifiability of the model should be discussed. Given the wide range of some confidence intervals, it does seem that parameter identifiability could be a problem. The extent of this is hard to assess given the level of information on the parameters currently given.

Reviewer #3 (Public Review):

This paper presents a new mathematical method to estimate case ascertainment (the fraction of infections identified as cases) and applies it to COVID-19 data from Singapore over the period early 2020 to late (pre-Omicron) 2021.

The method relies upon access to line-listed case data that includes whether or not a case was an importation or was (epidemiologically) linked or unlinked.

Through the application of this method, new results on the contribution of case identification and contact tracing to reducing transmission are derived. Reproduction numbers for different classes of infections (importations, linked, unlinked) are computed.

A sensitivity analysis establishes that inclusion of the richer case line-list information results in tighter credible intervals for key parameters of interest, although there is no 'gold standard' on which to evaluate if those estimates are more accurate.

Of some interest, the results suggest that both the case- and infection-fatality-ratios were lower during the Delta wave in 2021 than the ancestral wave in 2020. The underlying reasons (particularly for the IFR) are unclear and not investigated, but are perhaps due to vaccination (although the paper reports approximately just 35% vaccination coverage in early 2021), age-specific effects or other socio-demographic effects.

The method is based on a branching process model, for which the key elements are well described (noting some (likely) typographical errors in the typesetting of the equations), although the exact details of the computational implementation are not described, leading to some ambiguity in how the method is implemented.

Reviewer #1 (Public Review):

They established a "behavioral transcriptomics" platform as they cultured mouse primary cell explant on an apparatus, imaged the cells over time, and analyzed cells with differential physiological status by scRNA-seq. They showed evidence that the system recapitulated physiological features of airway cells, including chemical-induced damage response. They further utilized the system to isolate cells of different cellular features and analyzed gene expression through scRNA-seq. The study demonstrates an interesting establishment and application of an in vitro system mimicking in vivo.

However, several major concerns need to be resolved. First, whereas the overall study seems to focus on the establishment of airway epithelial cell explant apparatus and its application, take home messages that are delivered by the authors seem to emphasize the transcriptome analysis part. The authors introduced "spatial transcriptomics" and "behavioral transcriptomics" in the abstract but it is hard to appreciate that the study resolves spatial transcriptomics. This causes unnecessary confusion. Second, probably related to the first question, it is hard to find the novelty of the study. Third, probably the last and most important part of the manuscript is to analyze the cells by Smart-seq. But the analysis was performed on the SO2 injured animal only and lacked experiment on wild type mice. If the authors tried to prove the feasibility of the technique rather than resolving physiological mechanism here, then I would recommend explaining why wild type experiment was not performed.

Reviewer #2 (Public Review):

Kwok et al. devise a method that uses a transgenic mouse line to make the link between cell behaviour in intact living tissue and subsequent dissociation into distinct groups for single cell sequencing. Specifically, they set up a mouse airway culture system in which it is possible to maintain live cells for multiple days and then preserve the same tissue. The analysed tissue section can be fixed and known cell types identified via classical staining protocols. In this system they imaged a number of tissue phenotypes such as ciliary beating, mucociliary clearing and airway regeneration. With respect to airway regeneration they observe that there was cellular heterogeneity between cells with the capacity to move and so-called non-movers, which the authors were able to quantitively track.

To make the link with single cell sequencing, they use the Kaede transgenic mouse lines, which contains a green fluorescent reporter gene, that can be converted into a red fluorescent reported gene by illuminating a defined tissue section, in this case regions enriched for movers or non-movers. After dissociation of the tissue, cells were FACS sorted using the reporter protein. Subsequent single cell RNAseq revealed distinct gene signatures that were associated with the mover versus the non-mover phenotype. These phenotypes could also be detected in previously published data sets.

The conclusions of the paper are supported by the data that is presented, but the comparison to existing mouse injury data could be improved.

A weakness of the paper is the implication that the technique can be used for any of the phenotypes that they have examined. However, in order to be assessed by this method, there need to be a reasonably large number of cells that show similar behaviour in a region that can be photoconverted. If it is indeed possible to do the photoconversion at the single cell level, the authors should demonstrate that such resolution is possible, or otherwise clearly state this limitation of the technique they have developed.

Reviewer #3 (Public Review):

In this manuscript, the authors identify a pressing need to couple visualized in situ cell behaviour with deep molecular profiling of visualized cells, aiming to move beyond inferences made from time-lapse tissue sampling approaches or the analysis of transcriptional kinetics to identify the molecular pathways that drive cellular behaviour in situ. The authors identify live cell imaging combined with deep molecular profiling of the imaged cells as one possible solution. To this end, the authors establish a novel platform for live cell imaging of tracheal epithelial cells using explants of mouse trachea that allows long-term visualization of cell behaviour, and try to couple live-cell imaging to the transcriptional cell states.

Combining single-cell RNA-seq analyses with live cell imaging offers the unique opportunity to link transcriptional and anatomic, morphological or movement phenotypes of individual cells. To be able to do this in intact tissues at baseline and in response to injury would allow a far more detailed and integral analysis of cellular behaviour in their physiological context. As such, the approach of the authors is interesting and clearly focused on achieving this goal. The only data that can support a claim of successfully achieving this ambitious goal are presented in figure 3, where an advanced mouse model (the Kaede-Green mouse) is used that allows labelling individual cells by photo-conversion, followed by isolation of individual cells by flow cytometry and plate-based scRNA-seq analysis of sorted cells. By taking this approach, the authors are able to identify transcriptional differences at the group level between tracheal epithelial cell subsets that differ in their movement after injury.

While this in itself is a remarkable accomplishment, and an interesting observation, the relationship between the 'behaviour' of the cells observed with live cell imaging (the movement after injury) versus the transcriptional phenotype remains rather elusive. One explanation could be that active movement of cells depends on a specific transcriptional program, that is lacking from the non-moving cells. Another explanation could be that the tracheal epithelial cells are inherently heterogeneous, and one subset has the capacity to move whereas others do not, and the transcriptional profile merely identifies these heterogeneous populations. The observation that non-mover cell populations contain both basal and club cells, whereas mover regions only have basal cells seems to support this notion to some extent. However, the authors then claim to use basal-cell derived signatures (excluding the club cells) from mover and non-mover regions and compare this to literature data from another injury model to show that these signatures also identify distinct subsets in a mouse model of polidocanol-induced injury. How the distinction basal vs club cells in the non-mover regions is made remains unclear, and would seem challenging from the number of cells analyzed (as presented in figure 3).

The identification of two behavioural phenotypes of basal cells (mover vs non-mover) in this manuscript is based on group-level phenotypes: the cells belong to a region of movers or a region of non-movers. This is relevant for figures 2 (including supplemental) and 3. In figure 2 supplemental 2C, it seems evident that within one region (or focussing only on all moving regions?), the behaviour of all cells within that region/selection is quite uniform: the variation is really very limited, and all cells seem to speed up and slow down in a highly coordinated fashion within the selected regions shown. At the same time, in figure 2D, the distribution of regions across speed categories at 26-36 hours pi (the peak of the movement in suppl 2C) seems almost bimodal, with regions belonging either to non-mover (range 0.5 - 2.5 uM/hr) or mover (range 3.0-7.0 uM/hr) phenotypes. However, all regions display an increased movement at 16h pi compared to the pre-injury movements (Figure 2C), indicating that all cells will be induced to induce movement to some extent. My main concern with this analysis is that the behavioural phenotype of the epithelial cells is assumed to be homogeneous within each region, allowing a contrast to be made in figure 3 for the transcriptional phenotypes on the basis of moving phenotypes rather than on the basis of the main variation within the dataset. For instance, from the t-SNE plot (3B) - for what it's worth of course - and the heatmap (3C) there seems to be at least one non-mover cell that transcriptionally has a higher resemblance to the mover cells than to the other non-mover cells. Of course that can just be the variability present in the dataset, but it could also indicate that non-mover regions are not completely homogeneous, and even more so, that the moving vs non-moving associated transcriptional phenotype is a gradual transition rather than 2 clearly separate sub-phenotypes.

All-in-all, this manuscript describes an interesting technical advance and shows some of the applications thereof. However, the approach also has its limitations: The requirement to mark cells with specific behavioural features for follow-up transcriptomic analysis (such as by photoconversion) necessitates the division of the epithelial cells into major categories on the basis of certain cellular phenotypes (such as movement) that can be visualized by live cell imaging. This limits the analysis opportunities to group-based contrasts in cellular behaviour as also used here by the authors. Also, the use of explanted tissue is of course less ideal than in vivo imaging, but most likely the only technically feasible approach at this moment. At the same time, the capacity to combine image-based features with single-cell transcriptomic data is an important advance, even when initially only possible in explanted tissue from mouse models carrying all kinds of fluorescent reporters. To strengthen the manuscript, it would therefore be important to discuss the limitations of the approach, as well as to provide a more comprehensive overview of the possible applications that the authors foresee.

Reviewer #3 (Public Review):

Age-related changes that occur in human blood have also been characterized in mouse models. However, one limitation to the mouse model is that mice are not a compelling model of the aging human blood and immune systems. Also, they do not develop spontaneous blood cancers that commonly occur in older people. By contrast, rats and humans share many genes involved in immunity and hematopoiesis that are absent in mice and older rats can develop age-related leukemias as in humans. Here the authors use flow cytometry to investigate changes in peripheral blood composition across the life course in aging male rats. They show that the composition of blood changes during aging and that many of these changes are like those observed in people. Further, they show that these changes are not linear but exhibit clear inflection points, most prominently at 15 and 24 months of age. DNA methylation changes also exhibit clear inflection points. These findings suggest that rat blood aging is not continuous but occurs in phases. This raises the possibility that interventions to modify blood aging may be the most beneficial if administered before these inflection points.

Strengths:

Some previous studies have examined blood aging in the mouse model, but the mouse is not a compelling model of human blood aging. An advance made here is that the authors show that the peripheral blood from aging male rats shows similar changes to those seen in older humans. This supports the idea that rats are an important model to use in studies of the aging blood and immune systems. Other strengths of this work include: 1) the use of a very large sample size to explore this question; 2) replication of their findings in both fixed cells and fresh blood; and 3) the demonstration of "inflection points" in blood aging with several different experimental approaches. These studies provide strong preclinical data that blood aging is non-linear and suggest there may be optimal windows throughout the aging process where interventions may be most effective.

Weaknesses:

The authors have been reasonably cautious in their conclusions, and most are supported by their data. Still there are some weaknesses in the study.

1) This study has used only male mice. This is an important limitation that has not been acknowledged in this work. This is a key limitation as the generalizability of their findings to females is uncertain. The work should be extended to include female animals.

2) The abstract is not well written and is quite vague. It does not give the reader a clear idea of the rationale for the work. The key findings are not clearly presented, and the claims made go quite far beyond the data presented in the study.

3) The authors use the term fragility in the abstract but never again. Potentially they mean frailty, which is a more common term in the geroscience literature. A role for frailty, as a validated measure of overall health in aging humans and preclinical models, has not been considered in this study. It would have been interesting to have measured frailty in the aging rats they investigate.

4) The authors note that they consider the "health status" of all rats used in the study and indeed they have included a table with some health outcomes. As noted above, a measure of frailty would have been very useful to quantify health in these rats. However, one issue that arises in this study is that the authors have excluded rats with overt sickness from the analysis. This would seem to bias their sample quite considerably. If the authors removed all the animals with overt sickness, then they are looking at blood aging from only the least frail rats in their sample. There is ample evidence that pathology does not equal disease expression. For example, pathology alone does not predict dementia risk in the absence of frailty (PMID: 30663607). Known cardiovascular disease risk factors are more potent in the face of frailty (PMID: 31986990; PMID: 32353205; PMID: 33951158). Similarly, biomarkers and genes do not equal disease expression (PMID: 34933996; PMID: 33210215). The work would be more impactful if the authors also included analysis of blood aging in samples from the rats with overt illness.

Despite these shortcomings, in general the authors' claims and conclusions are justified by their data.

Reviewer #1 (Public Review):

In this manuscript, Yanai et al. characterized the age-associated changes in population dynamics of immune cells in the peripheral blood of male rats. Using flow cytometry, authors described distinct characteristics in terms of leukocyte composition associated with young, middle-aged and old peripheral blood, such as increased myeloid bias in the older groups. Also, authors identified a novel aging prediction marker, CD25+ T cell frequency, for age prediction in rats. Additionally, authors performed and analyzed methylation profiles of whole peripheral blood and observed age-associated shifts in the methylome of peripheral blood.

The manuscript presents interesting findings and provides important resources for the aging research community to utilize rats as a relevant model to study blood aging. Only minor edits would be needed to improve rigor and clarity of the manuscript.

Reviewer #2 (Public Review):

The paper presents an assessment of blood aging in rats using two approaches: evaluating the peripheral blood cell composition and performing whole blood DNA methylation analysis. 

Although the overall changes in cell composition have been studied previously, here H Yanai, C Dunn, et al. look at it from a different perspective, focusing on the timing of drastic shifts identifying several key points along with the lifespan. They also train an age predictor based purely on the blood cell composition, determine which cell types contribute to it the most and show that this measure, as well as a simple myeloid/lymphoid ratio, reflect the disease state. Using a dataset previously used to construct rat DNA methylation-based age predictor, H Yanai, C Dunn, et al. focused on previously overlooked aspects of aging in rat blood epigenome such as identification of regions differentially methylated in aging and detection of the most affected genes. Similarly, to the cell count approach, authors estimate DNA methylation-based gene breakpoints, detecting two distinct waves of changes and identifying genes, promoter regions of whose were the most affected by this.<br /> H Yanai, C Dunn, et al. estimate the main change in cell composition happening at 15 months, while the young age DNA methylation breakpoint - at 12 months. The fact that the epigenetic effect is observed first is impressive considering the huge effect of cell composition on bulk methylation. 

Although the paper provides new insights into the trajectory of rat blood aging and the claims are mostly supported by the data, some of the points remain unclear or questionable. <br /> 1.    Using a panel of just 8 monoclonal antibodies authors managed to fit a model performing well on the training data (with r2=0.89), although it is unclear how well it works on a test set.<br /> 2.    Authors bring an important point of the effect of the difference in sample preparation (fresh vs fixed samples) and show (Supplementary Fig. 4) that there is indeed a shift. But it is unclear from the description whether the model was refitted including the new data (which presumably has paired fresh and fixed samples) or if it was the original model applied to these samples.<br /> 3.    The actual model for calculating age from the cell counts is not in the paper preventing it from being applied by the other groups. In addition, these animals are encoded differently for the data on health and cell counts. Taken together, it is impossible to verify the results provided in this part of the paper.

Reviewer #1 (Public Review):

In the manuscript "H3K9me1/2 methylation limits the lifespan of C. elegans" Huang M, Hong M et al performed a genetic analysis of putative H3K9 methyltransferases and their involvement in the lifespan regulation of daf-2 mutant worms. They build on an initial finding that set-21 mutation leads to a further extension of daf-2 lifespan and stress resistance and expand this to analyze all other putative H3K9 methyltransferases in the context of daf-2. They identify several putative methyltransferases which all extend daf-2 lifespan and stress resistance and show that a H3K9me inhibitor also has the same effect. They also perform some transcriptional analyses to examine how gene expression changes in these double mutant strains and take some daf-16 target genes and examine their effects on lifespan in the daf-2;set-21 double mutant. They show that deletion of some of those daf-16 target genes decreases the lifespan of daf-2;set-21 double mutants.

All in all I thought this was an interesting paper and the data appears to be strong but there are several critical missing pieces that I think need to be added to bolster the manuscript and shore up the findings. Most importantly I think that the authors need to examine how daf-2 mutation affects H3K9me1/2? Why are these putative methyltransferases actually important here? Also since the paper is so focused on H3K9me1/2 it seems important to show that the enzymes that are being studied do actually directly regulate H3K9 methylation. Finally some experiments should attempt to address why there are 6 enzymes which the authors believe are modifying the same mark all have the exact same effect on lifespan in daf-2 mutant worms. Usually it is believed that these chromatin modifying enzymes have some specificity (either by being expressed in different tissues or modifying different chromatin regions) but here they all have the exact same consequence! That is quite surprising and an attempt should be made to explain this finding (and best if backed up by some experiments!).

Reviewer #2 (Public Review):

In this paper, Huang and colleagues investigate whether putative C. elegans H3K9me methyltransferases are involved in aging by investigating their effects on long-lived daf-2 mutants. They find that modifiers of H3K9me1/2, but not H3K9me3, can synergistically extend the lifespan of daf-2 (in some cases, to three times as long as wild-type). They demonstrate that this synergistic effect on lifespan requires the DAF-16 transcription factor and some of its downstream regulatory targets. Like other mutations that extend lifespan, mutations in these HMTs also protect against heat and oxidative stress. Compellingly, they show that the effects on lifespan are phenocopied by a small molecular inhibitor known to target a conserved H3K9me1/2 HMT - this experiment strengthens their claim that the effects on lifespan are due to changes in H3K9me1/2 specifically, and are unlikely to be caused by non-enzymatic effects of mutating the SET-domain proteins.

This work contributes a new regulatory layer to the well-studied DAF-2/DAF-16 pathway for stress resistance and aging - it implicates a functional role for H3K9me1/2 at several DAF-16 target genes, and identifies possible HMTs. The conclusions of this paper are generally supported by the data presented. However, I have concerns regarding technical aspects of the experiments & analysis, and find some interpretations to be overstated.

1. The effects on lifespan reported in this manuscript are highly dependent on experimental technique. However, data are presented in this manuscript in a way that makes it difficult to evaluate the reproducibility of their results, which is important for effects on lifespan that may be statistically significant, but small. The following changes will improve the rigor of their findings. First, each lifespan assay should be replicated at least twice, if not three times, and results reported in the summary data table suggested below. Second, major results, like those of the daf-2; set-21 double mutants or the G9a inhibitor, should be performed blinded to further validate their findings. Finally, summary data for each experiment should be included in supplementary table(s), with conditions examined per assay, N, animals censored, median lifespan (along with average lifespan), and comparison used for determination of significance, which is most commonly calculated using a log rank test (which captures distinctions in survival for the entirety of the survival assay).

2. The transcriptomic analysis is important to link the synergistic extension of lifespan to the known DAF-16 pathway. However, the analysis was superficial -the authors used the mRNA-seq data to primarily validate their hypothesis that DAF-16 targets are most affected in HMT; daf-2 double mutants. Transcriptomic data are never used in an unbiased manner to identify other potential pathways, or even to demonstrate that DAF-16 Class I/II genes are the most affected in these genetic backgrounds. For example, it is important to show that there is more misregulation observed among Class I and Class II genes when compared to all transcriptomic changes caused by the mutations. The cursory approach to genomic analysis is also seen by how methods are explain, making it difficult to tell what comparisons are being drawn to identify misregulation. More analysis is required before the authors can fully support their claim that the effects of removing an HMT in a daf-2 background occur primarily through DAF-16 Class I gene regulation.

3. The findings presented here are interesting and uncover a new avenue of research for understanding longevity and stress resistance. However, for the most part, the effects on lifespan and stress resistance are seen in a daf-2 mutant background. This genetic background already experiences a significant lifespan increase, and therefore has many molecular & physiological differences from wild-type animals (which are well-characterized). Therefore, many of the broad statements in the abstract and discussion overstate the generality of their findings. This work clearly demonstrates that HMTs act to limit the lifespan of daf-2 mutants. Little effect, if any, was seen in HMT mutants in an otherwise wild-type background. In fact, some HMT mutants, like met-2, have a decreased lifespan, indicating that H3K9me1/2 may be protective for lifespan in some circumstances. Furthermore, the authors claim that these HMTs regulate Class I DAF-16 target genes, but no effort was made to demonstrate that this class of genes was more affected than any other class. Care should be taken to ensure that the claims made are fully supported by the data presented here.

Reviewer #3 (Public Review):

Previous work in C. elegans and other systems had suggested that H3K9 methylation is required for enhanced longevity. However, the authors discovered an interesting phenomenon in which decreased H3K9me2 methylation, but not H3K9me3 in a daf-2 mutant background is associated with increased longevity. This suggests that in the context of reduced insulin signaling, reduced H3K9me2 methylation has the opposite effect on longevity. By performing RNAseq, the authors show that daf-16 targets are increased in expression. This suggests that in a daf-2 mutant where daf-16 translocates into the nucleus, H3K9me2, but not H3K9me3 normally prevents daf-16 from fully activating it's transcriptional targets.

Overall, this is a well written, comprehensive paper examining an interesting phenomenon, wherein the manipulation of H3K9 levels has a context dependent effect on longevity. The authors do a very nice job in convincingly showing that this effect is likely through H3K9me2 preventing the full activation of daf-16 targets. This work adds significantly to our understanding of the relationship between repressive chromatin and longevity.

Reviewer #2 (Public Review):

In this manuscript, Bibel et al. used an in vitro system containing purified Argonaute, CK1, miRNA, and target RNA to investigate the molecular mechanisms underlying the phosphorylation of Argonaute proteins by CK1 and its consequences on the interaction between the RISC and its target RNAs.

The authors build upon observations by Golden et al, who previously described a phosphorylation/dephosphorylation affecting a cluster of 5 conserved residues (4 serines and 1 threonine) on the EI region of Argonaute.

Bibel and colleagues show that phosphorylation of these 5 residues by CK1 requires the formation of a Ago-miRNA-targetRNA complex and occurs in a partially hierarchical fashion, with S828 being the first site to be phosphorylated, followed by S831, and then by the three other sites.

Interestingly, the type of interaction between the Ago-mIR and the target is important. Pairing with the seed and some additional 3' pairing is essential, but perfect or near-perfect complementarity between the miRNA and the target sequence impairs, rather than promoting, phosphorylation by CK1.

Furthermore, confirming previous cell-based studies by the Mendel group, Bibel and colleagues show that phosphorylation of Ago promotes target dissociation.

Based on these results the authors propose a model in which binding of the core RISC complex to miRNA target sequence serves as a primer to induce sequential phosphorylation of the 5 residues in the Ago EI region. The consequent increase in negative charge of this region then facilitates the dissociation of the RISC from the negatively charged target mRNA.

The manuscript is beautifully written, the experiments are clearly described and their results support the model proposed by the authors. The relevant scientific literature is presented and the statistical analysis used is appropriate. These findings are of substantial interest to the scientific community, as they shed light on the emerging importance of the dynamic regulation of the RISC complex.

Reviewer #3 (Public Review):

In this article authors have developed a robotic system coupled with Artificial Intelligence (AI) to autonomously differentiate hiPSC into RPE. The goal is to reduce human errors and optimise culture conditions for clinical applications.

The paper is well written and experiments are rigorously conducted. The development of such approaches and protocols would clearly have a great impact on the quality of future cell therapy clinical applications and are developed by many groups demonstrating the need.

Reviewer #3 (Public Review):

In this paper, the authors' aim was to test how IRE1's oligomerization state relates to its activation status without relying on ectopic overexpression. The principle underlying the work is a rather simple one, which is that, if the population of IRE1 can be labeled stochastically with either of two different fluorescent probes, then if the protein dimerizes, presuming single molecules can be visualized, correlated migration of a spot of each fluorophore should be observed for some of those dimers. Any correlated migration, maintained for long enough, will by necessity by some sort of dimer or multimer. In principle, if my math is right, the correlation should be 50% of spots of each color, assuming all the molecules are in a dimer, all molecules are labeled with one fluorophore or the other, and the koff of the fluorophores is very low. In practice, the correlation appears closer to 10%, which the authors establish using a control molecule that should not dimerize except by chance, and another for which pseudo-dimerization is enforced due to the two HALO domains used to bind the fluorophores being conjugated to the same molecule in cis. Much of the paper is devoted to establishing the fundamentals of the system. For these experiments, the authors replaced endogenous IRE1 with the HALO-tagged version to generate near-normal expression and show that the IRE1-HALO behaves similarly to endogenous. They also show that correlated migration is observed in the dimer control to a much greater extent than in the monomer. 

Using these findings, they demonstrate, in my mind quite conclusively, that IRE1 exists as a dimer even in the unstimulated state. During ER stress, the authors observe a state that is more highly ordered. Mathematical modeling suggests a transition from predominantly dimers to a mix of dimers and something more highly ordered, with tetramers being the simplest explanation. Satisfyingly, a mutation that breaks the known dimer interface causes the protein to exist solely in monomers, as does deletion of the IRE1 lumenal domain, while disrupting the oligomerization interface keeps the protein as dimers. Mutation or deletion of the kinase and RNase domains does not affect higher order status, suggesting that activation of these domains is not a prerequisite for assembly. It is clear from this that the central claims of the paper, which is that IRE1 exists in a dimer in the basal state and transitions to a higher ordered structure in the activated state, are supported. Moreover, the general approach is likely to be appealing to the study of other molecules activated by multimerization. 

The principal advance of the paper is the technological approach for tracking IRE1 (and, presumably, other molecules whose activity is regulated by dimerization). The approach is quite elegant for that purpose. Its impact in terms of conclusions about IRE1 is perhaps less clear. The authors rationalize their endogenous-replacement approach by describing how their previous efforts and those of others relied on ectopic overexpression of GFP-tagged IRE1. The authors take great pains to claim that the observed multimerization status of the IRE1-HALO constructs is not a function of expression level, which would imply then that expression level alone is not responsible for the previously observed IRE1 oligomeric puncta. It is not clear why exactly the authors' results differ from this group's previous studies on the topic nor where the truth lies, including whether something inherent to the GFP-tagged overexpression approach favors non-physiologic structures, whether the difference is fundamentally one of cell type, or whether multimerization and activation are correlated but not causally related, with multimer-breaking mutations killing IRE1 by some other mechanism. Interpreting the data is also complicated by the fact that, while the authors point out that the percent of correlated trajectories (i.e., the measurement of multimerization state) does not itself correlate with expression level (using trajectories-per-movie as a proxy), the proper conclusion from that lack of correlation is not that variance in expression level does not account for the changes in apparent multimerization status, but instead that it cannot be the only factor. In some sense, the authors are attempting to play the argument both ways, by arguing that expression level matters for IRE1 activation (from previous studies) and that it doesn't (from this study). I think to address this the authors will need to better account, one way or another, for why the findings presented here differ from their previous findings and why these are the more salient (if in fact they are). 

The other somewhat substantial issue is that there is no control for what higher order structures look like. The authors give no sense for the dynamic range of the multimerization assay. I would presume that tetramers would show a higher percentage of correlated trajectories than dimers, and octamers higher still, and that the mathematical model accounts for this theoretical possibility in calculating an average protomer number of 2.7 in the stress condition, but it would be better to see that in practice; at first glance it would seem that engineering a tetrameric and/or higher order control and validating it would be straightforward. 

Lastly, the data analysis lacks statistical justification for its conclusions. I presume given the high number of readings that the observed changes are all statistically significant, but that should be indicated, as in most cases the 95% confidence intervals shown are overlapping.

Reviewer #1 (Public Review): 

In this manuscript, the authors sought to define the early events associated with activation of the ER stress-responsive membrane protein IRE1. Towards that aim, they used CRISPR to integrate a HALO tag into the genomic locus of IRE1 at the C-terminus of the protein. The authors then adapted a single molecule fluorescence microscopy approach where the HALO tag is liganded with two different fluorophores to define the oligomeric state of membrane proteins in cellular models. They validated this approach using ER membrane proteins containing defined number of HALO tags (single or double) and imaged with oblique angle illumination microscopy to confirm their ability to detect effect monomer and dimers of these tags. Using this approach with IRE1, they showed that in the absence of stress, there is a high fraction of apparent IRE1 dimers in the membrane. In response to ER stress, this oligomer size (calculated by correlated trajectories) increased, suggesting that ER stress promotes IRE1 oligomerization, eventually returning to dimers at longer treatment times. Intriguingly, using the ER stressor thapsigargin, the authors indicate that oligomerization precedes auto-phosphorylation of IRE1, suggesting that oligomerization is a key step in the activation of this enzyme. Extending this, the authors then transition to an overexpression model where they incorporate IRE1 constructs containing mutant that disrupt specific parts of the protein or prevent dimeric or oligomeric interactions to probe their importance in this early oligomerization observed in response to ER stress. This demonstrated that the oligomerization was primarily dictated by the ER luminal domain and involved two distinct interfaces specifically required for IRE1 dimer formation (in the absence of stress) and oligomer formation (following ER stress). Ultimately, with these results, the authors propose a model whereby IRE1 exists primarily as a autophosphorylation-deficient, back-to-back dimer that upon ER stress oligomerizes to a phosphorylation competent oligomer that allow autophosphorylations and IRE1 activation. 

Overall this is an interesting approach and study to define early stages of IRE1 activation. Notably, it reveals a different model of these early stages of IRE1 activation than those previously reported by this group and others using GFP-tagged IRE1 overexpression constructs (something that was enabled by the integration of HALO tags into the genomic locus). The experiments are well performed and the data appear to all be interpreted correctly, although there are a few remaining questions that should still be addressed.

Reviewer #2 (Public Review): 

The authors investigated changes in the unstressed and stressed oligomeric states of the mammalian endoplasmic reticulum (ER) stress sensor, IRE1a. Previous biochemical and microscopy studies in mammalian cells and studies of the related protein Ire1 in yeast, describe an increase in oligomerization of the stress sensor upon treatment of cells with chemical agents that impair the ER protein folding environment. The general view has been that IRE1 in unstressed cells is a monomer and varying degrees of misfolded protein stress stimulate dimerization, activation, and higher order oligomerization. Distinguishing between monomers and dimers, as well as tetramers or other small oligomers is technically challenging, especially for integral membrane proteins. To address this challenge, the authors turned to single particle tracking fluorescence microscopy of Halo-tagged endogenous IRE1. Using a clever combination of random labeling with two fluorescent dyes and oblique angle illumination to visualize single molecules, as well as dimers, the authors surprisingly find that their endogenous IRE1 reporter appears to be dimeric in homeostatic cells. This observation challenges the predominant model in which IRE1 is monomeric in unstressed cells and that even dimerization represents a switch into an active state. The authors claim to detect evidence for higher order oligomers following treatment with stressors. The authors then use a series of IRE1 mutants to identify how oligomerization is regulated and present a new model to reconcile the different models of IRE1 activation in the literature. 

The authors have extensively characterized their novel experimental system in terms of protein expression levels, functionality, and ability to distinguish monomers and dimers. The data are well presented and the authors are clearly familiar with the arguments that have surrounded the IRE1 oligomer question. That the authors observe the characteristic XBP1 mRNA splicing activity in the absence of visible large IRE1 clusters may suggest that the large clusters reported by others may have distinct roles, perhaps in more permissive mRNA cleavage. 

The present study is undermined by two major weaknesses. First, while the authors persuasively demonstrate that they can detect IRE1a dimers, a major claim of the manuscript rests upon detection of tetramers and possibly higher order oligomers. Unfortunately, the authors provide no independent controls to show what tetramer or higher order oligomer data would look like. Thus, the authors can only infer that higher order oligomers are detected, based on modest shifts in the percent of correlated particle trajectories observed in some cells. More robust evidence is needed to make claims of oligomerization. Tools have been developed by others that can induce reversible oligomerization of proteins. Application of these tools would provide powerful controls for tetramers or even higher order oligomers in this study. 

The second, deeper concern, is the discrepancy between the Halo Tag clustering results in this study and studies by this lab and several other labs that report a distinct stress phenotype. In mammalian cells and yeast, IRE1 and Ire1, tagged with different fluorescent proteins or even a small HA peptide epitope tag, undergo quantitative visible formation of puncta or clusters upon treatment with stressors. The small number of bright clusters that form effectively deplete the rest of the ER of IRE1 signal. In the present study, the authors observe no visible change in IRE1-Halo localization in stress cells. The authors do not investigate the cause of this difference. While one might argue that the presence of stress-inducible IRE1 activity is sufficient to argue that the reporter in this study is functional, IRE1 reporters (that do cluster) described in previous studies by the Walter lab and other groups are also demonstrably functional. Does IRE1 normally cluster? Is it cell-type dependent? Tag-dependent? Notably, the Pincus et al. PLoS Biology paper from the Walter lab used two different fluorescent protein tags that do not heterozygously dimerize. Robust colocalization and FRET signals were detected upon treatment of cells with stressors and clustering was subsequently observed. A 2007 Journal of Cell Biology study from Kimata et al. reported clustering in yeast with an Ire1 tagged with an HA epitope peptide. The HA peptide seems unlikely to be prone to any oligomerization propensities that GFP tagged reporters might experience. Importantly, a 2020 PNAS paper from the Walter lab (Belyy et al.) studied clustering of a robustly monomeric mNeonGreen-tagged IRE1 in U2-OS cells and mouse embryonic fibroblasts and this construct readily clustered following stress induction. 

When evaluated against the backdrop of the extensive literature describing the visual behavior of IRE1a in live cells, the absence of stress-induced clustering is both puzzling and disconcerting. Given the focus of this study is to use visual techniques to study IRE1a interactions, the burden of proof is on the authors to resolve this significant discrepancy with the rest of the IRE1a literature. One can easily imagine that incorporation of the majority of the pool of IRE1a into 10-100 clusters could produce very different correlated trajectory behavior. Until the authors can determine why their reporters behave differently from other IRE1a reporters and establish which version accurately reflects physiologic IRE1a behavior, the potential impact of the findings of this manuscript are of unknown value.