Reviewer #1 (Public Review):

In this work, authors seek to understand how the polycomb complex may coordinate gene expression changes that occur during sequential stages of neuronal maturation. The main strengths are 1) choice of cerebellar granule neurons which mature over a protracted period during normal cerebellar development and constitute a relatively homogeneous population of neurons, 2) use of a genetic in vivo mouse model where a histone demethylase is knocked out, combined with an in vitro culture model of maturing cerebellar granule neurons in which a histone methyltransferase is inhibited, 3) use of CUT & TAG in neuronal cultures to investigate how changes in the H3K27me3 repressor chromatin modification at promoters correlate with gene expression and chromatin accessibility changes. The authors propose a bidirectional effect of the same chromatin repressor modification that is responsible, at least in part, for the timely loss of expression of early genes and the appearance of genes expressed later in maturation. This is the major impact of the work for those interested in cerebellar development. A weakness in the work lies in its narrow focus, which is on promoter regions almost exclusively.

The work is primarily bioinformatics driven and lacks physiological significance of the gene expression changes, or how the culture timing correlates with temporal regulation and chromatin changes in vivo. However, the results do support the proposal that polycomb-associated enzymatic activities play sequential roles during successive stages of cerebellar maturation.

Reviewer #1 (Public Review):

The authors have studied the effect of temperature on the interspecific interaction strength of coastal marine fish communities, using eDNA samples. Their introduction describes the state of the art concerning the dynamics of interspecific interactions in ecological communities. This introduction is well written and highly information dense, summarizing all that the reader needs to know to further understand their study setup and execution.

The authors hypothesize that water temperature changes could have an effect on the interspecific interaction strength between marine fishes, and they studied this with a two year long, bi-weekly eDNA sampling campaign at 11 study sites in Japan with different temperature gradients. These 550 water samples were analysed for fish biodiversity through eDNA-metabarcoding using MiFish primers. By using the most abundant fish species as an internal spike in and quantifying the copy numbers from this species by qPCR, the authors were able estimate DNA copy numbers for the total dataset. From the 50 most frequently detected fish species in these samples they showed that temperature affected the interspecific interaction strength between some species. Their work provides a highly relevant approach to perform species-interaction strength analysis based on eDNA biodiversity assessments, and as such provides a research framework to study marine community dynamics by eDNA, which is highly relevant in the study of ecosystem dynamics. The models and analytical methods used are clearly described and made available, enabling application of these methods by anyone interested in applying it to their own site and species group of interest.

Strengths: The authors have a study setup that is suitable to measure the effects of temperature of the eDNA diversity, and have taken a large number of samples and all appropriate controls to be able to accurately measure and describe these dynamics. The applied internal spike in to enable relative eDNA copy number quantification is convincing.

Weaknesses: The authors aim to study the relationship between species interaction strength and ecosystem complexity, and how temperature will influence this. However, there is only limited ecological context discussed explaining their results, and a link with climate change scenario's is also limited. A further discussion of this would have strengthened the manuscript.

The authors were able to find a correlation between water temperature and interaction strengths observed. However, since water temperature is dependent on many environmental variables that are either directly or indirectly influencing ecosystem dynamics, it is hard to prove a direct correlation between the observed changes in community dynamics and the temperature alone.

Reviewer #1 (Public Review):

The authors use a combination of structural and MD simulation approaches to characterize phospholipid interactions with the pentameric ligand-gated ion channel, GLIC. By analyzing the MD simulation data using clusters of closed and open states derived previously, the authors also seek to compare lipid interactions between putative functional states. The ultimate goal of this work is to understand how lipids shape the structure and function of this channel.

The strengths of this article include the following:

1) The MD simulation data provide extensive sampling of lipid interactions in GLIC, and these interactions were characterized in putative closed and open states of the channel. The extensive sampling permits confident delineation of 5-6 phospholipid interaction sites per subunit. The agreement in phospholipid binding poses between structures and the all-atom MD simulations supports the utility of MD simulations to examine lipid interactions.

2) The study presents phospholipid binding sites/poses that agree with functionally-important lipid binding sites in other pLGICs, supporting the notion that these sites are conserved. For example, the authors identify interactions of POPC at an outer leaflet intersubunit site that is specific for the open state. This result is quite interesting as phospholipids or drugs that positively modulate other pLGICs are known to occupy this site. Also, the effect of mutating W217 in the inner leaflet intersubunit site suggests that this residue, which is highly conserved in pLGICs, is an important determinant of the strength of phospholipid interactions at this site. This residue has been shown to interact with phospholipids in other pLGICs and forms the binding site of potentiating neurosteroids in the GABA(A) receptor.

Weaknesses of this article include the following:

1) The authors describe in detail state-dependent lipid interactions from the MD simulations; however, the functional significance of these findings is unclear. GLIC function appears to be insensitive to lipids, although this understanding is based on experiments where GLIC proteoliposomes were fused to oocyte membranes, which may not be optimal to control the lipid environment. Without functional studies of GLIC in model membranes, the lipid dependence of GLIC function is not definitively known. Therefore, it is difficult to interpret the meaning of these state-dependent lipid interactions in GLIC.

2) It is unlikely that the bound phospholipids in the GLIC structures, which are co-purified from e. coli membranes, are POPC. Rather, these are most like PE or PG lipids. While it is difficult to accommodate mixed phospholipid membranes in all-atom MD simulations, the choice of POPC for this model, while practically convenient, seems suboptimal, especially since it is not known if PE or PG lipids modulate GLIC function. Nevertheless, it is striking that the overall binding poses of POPC from the simulations agree with those identified in the structures. It is possible that the identity of the phospholipid headgroup will have more of an impact on the strength of interactions with GLIC rather than the interaction poses (see next point).

3) The all-atom MD simulations provide limited insight into the strength of the POPC interactions at each site, which is important to interpret the significance of these interactions. It is unlikely that the system has equilibrated within the 1.7 microseconds of simulation for each replicate preventing a meaningful assessment of the lipid interaction times. Although the authors report exchange of up to 4 POPC interacting at certain residues in M4, this may not represent binding/unbinding events (depending on how binding/interaction is defined), since the 4 Å cutoff distance for lipid interactions is relatively small. This may instead be a result of small movements of POPC in and out of this cutoff. The ability to assess interaction times may have been strengthened if the authors performed a single extended replicate up to, for example, 10-20 microseconds instead of extending multiple replicates to 1.7 microseconds.

Reviewer #1 (Public Review):

In principle a very interesting story, in which the authors attempt to shed light on an intriguing and poorly understood phenomenon; the link between damage repair and cell cycle re-entry once a cell has suffered from DNA damage. The issue is highly relevant to our understanding of how genome stability is maintained or compromised when our genome is damaged. The authors present the intriguing conclusion that this is based on a timer, implying that the outcome of a damaging insult is somewhat of a lottery; if a cell can fix the damage within the allocated time provided by the "timer" it will maintain stability, if not then stability is compromised. If this conclusion can be supported by solid data, the paper would make a very important contribution to the field.

However, the story in its present form suffers from a number of major gaps that will need to be addressed before we can conclude that MASTL is the "timer" that is proposed here. The primary concern being that altered MASTL regulation seems to be doing much more than simply acting as a timer in control of recovery after DNA damage. There is data presented to suggest that MASTL directly controls checkpoint activation, which is very different from acting as a timer. The authors conclude on page 8 "E6AP promoted DNA damage checkpoint signaling by counteracting MASTL", but in the abstract the conclusion is "E6AP depletion promoted cell cycle recovery from the DNA damage checkpoint, in a MASTL-dependent manner". These 2 conclusions are definitely not in alignment. Do E6AP/MASTL control checkpoint signaling or do they control recovery, which is it?<br /> Also, there is data presented that suggest that MASTL does more than just controlling mitotic entry after DNA damage, while the conclusions of the paper are entirely based on the assumption that MASTL merely acts as a driver of mitotic entry, with E6AP in control of its levels. This issue will need to be resolved.

Finally, the authors have shown some very compelling data on the phosphorylation of E6AP by ATM/ATR, and its role in the DNA damage response. But the time resolution of these effects in relation to arrest and recovery have not been addressed.

Reviewer #1 (Public Review):

In this report, the authors use what they describe as a novel phenotypic survival screening method to uncover ATP-dependent kinases that may show synthetic lethality (when inhibited) with BRCA2 loss. Interestingly, they find that inhibiting ROCK kinases in BRCA2 deficient cells (but not BRCA1 deficient cells), triggers synthetic lethality. They further show that the synthetic lethality is independent of acute replication stress and is preceded by enhanced M-phase defects (anaphase bridges and abnormal mitotic figures). These data, therefore, suggest a new pathway (ROCK kinases) that may be targeted to induce synthetic lethality in BRCA2 deficient cells.

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

Minor concerns:<br /> 1. The E80A, K88N and R90W (previously reported by the same group) mutations are located very close to each other in the homeodomain (Figure 1A), but had distinct effects on the activity of CRX. Has the structure of the homeodomain (of CRX) been resolved? If so, could the authors discuss this phenomenon (mutations close to each other but have distinct effects) based on the HD-DNA structure? In addition, has this phenomenon been observed in other homeodomain TFs?<br /> 2. The authors should briefly summarize the effects/disease-causing-mechanisms of all the reported CRX mutations in the discussion part. The readers can then have a better overview of the topic.<br /> 3. CRX can also function as a pioneer factor (reported by the same group). Would these HD mutations distinctively affect chromatin accessibility (which then leads to ectopic binding on the genome)?<br /> 4. The discussion part can be shortened and simplified.

Reviewer #1 (Public Review):

Zhou et al. investigated the factors that regulate mitotic chromosome size scaling during the early embryo divisions in Xenopus laevis using imaging of intact whole embryos and of embryo extracts with different sources of nuclei. They find that chromosome volume decreases during embryogenesis, and scales with nuclear and spindle volume throughout a broad range of embryo stages (stages 3 to 9) and cell sizes. They show that extracts from stage 3 or stage 8 embryos demonstrate significant differences in chromosome length, mirroring changes to chromosome volume observed in vivo. Using extracts from eggs or stage 8 embryos, and nuclei from sperm or stage 8 embryos, the authors demonstrate that chromosome length is dictated by the chromosomes and not the maternal mitotic environment, and find that the major determining factor is the amount of condensin I loading on mitotic chromosomes, which they correlate to changes in DNA loop size and layering. Interestingly, they find that the prior state of nuclei prior to entry into mitosis dictates mitotic chromosome length. They attribute this phenomenon to the nuclear to-cytoplasmic ratio during the prior interphase and suggest that some factor is titrated on chromatin that sets condensin I loading in mitosis. Notably, they found that chromosome length does not scale with nuclear or spindle size in vitro. In another set of experiments, the authors found that artificially increasing the palmitoylation of importin resulted in decreased chromosome length. However, this scaling effect is not due to condensin I loading differences, but to some unidentified importin cargo that would get released as cell size decreases during development. Overall, the conclusions of this paper are well supported by data, but some aspects of data interpretation and analysis need to be clarified and extended. The approaches used here are quite impressive and creative and provide compelling evidence for factors that regulate chromosome scaling during development in a vertebrate organism.

Reviewer #1 (Public Review):

The impact of the COVID-19 pandemic on cancer screening, diagnosis, referrals, and management has been well documented in high-resourced countries; but such quantitative estimates are rarely available from low- and middle-income countries (LMIC). The authors chose two very high human development index (HDI) category LMICs (Argentina and Thailand), two high HDI category LMICs (Colombia and Sri Lanka), and two medium HDI category LMICs (Bangladesh and Morocco), and looked at available data for cervical, breast, and colorectal cancer screening. The authors demonstrate that the reduction in the test volumes during the pandemic (2020) versus the previous year (2019) was quite comparable to that observed in high-income countries. Additionally, some countries demonstrated resilient catch-up of programmatic performance within a short period of time after the disruptions.

Major strengths include the use of national-level data estimates from key focal points for the CancScreen-5 project, an international data repository of cancer screening programmatic data, the use of appropriately comparable monthly estimates in the pre-pandemic vs. pandemic year, and representation of illustrative case studies from six countries across the medium-to-very high HDI status among LMICs.

Weaknesses include inherent limitations of such real-world outcome/registry data, lack of data across the screening continuum, inability to explore granular-level country-specific factors affecting disruptions as well as catch-up of screening, and high variability of performance of screening tests (especially those with subjective interpretation such as VIA for cervical cancer or clinical breast exam) across the comparison periods such that screen positivity rates may have been affected in unpredictable ways.

The authors have achieved their aims since this descriptive epidemiology analysis provides key estimates from LMICs that have not been explored/evaluated in the literature.

This work will be useful for future studies conducted by health modellers on measuring the impact on late/advanced stage detection and excess case burden and mortality.

Reviewer #1 (Public Review):

This paper is based on the premise that ketamine exerts antidepressant effects that are rapid by increasing glutamatergic transmission. However, the authors note that how this effect occurs is unclear because ketamine antagonizes the NMDA receptor, a glutamatergic receptor.<br /> Others have suggested a compensatory change in the glutamatergic transmission and the authors suggest how this might occur. The authors should clarify if prior studies suggested a mechanism different from theirs and if so, which might be correct.

There are also other mechanisms, such as the block of NMDA receptors on interneurons and the disinhibition of principal cells. It is important to clarify if this has already been addressed in the literature. Also, if their cultures are primarily glutamatergic neurons or they include interneurons and glia.

The authors show calcineurin is reduced after ketamine exposure and this increases AMPA receptor GluA1 phosphorylation. They also show that Calcium permeable AMPA receptors )CP-AMPARs) increase.

They also use suggest that the CP-AMPARs and other changes lead to enhanced synaptic plasticity, which could lead to antidepressant effects.

Although a lot of work is done in cultured hippocampal neurons, 14 days in vitro, they show effects in vivo that are consistent with the data from cultures. For example, ketamine increases GluA1 phosphorylation. Also, blocking CPAMPARs in vivo reduces anxiety/depressive behaviors such as the open field and tail suspension tests.

Overall the study appears to be done well and the presentation, writing, and references are good. There are important concerns regarding statistics, behavior, and pharmacology and several minor concerns.

Major concerns<br /> 1. Statistics.<br /> What was the stat test if the control was always 1?<br /> Often the control group is 1.00 with no SD but in other tests, the control group is 1.000 with an SD.<br /> e.g., line 145: "(CTRL) (CTRL, 1.000 and ketamine, 1.598 {plus minus} 0.543, p = 145 0.0039), but not GluA2 (CTRL, 1.000 and ketamine, 1.121 {plus minus} 0.464, p = 0.6498"

Line 188:<br /> Here the control group has a SD:<br /> Line 188 CTRL, 1.000 {plus minus} 0.106 and ketamine, 0.942 {plus minus} 0.051, p = 0.0170

2. Behavior.<br /> It is not clear that the open field and tail suspension tests measure antidepressant actions. Why were more standard tests such as forced swim or sucrose preference, novelty-suppressed feeding, etc not used?

3. Pharmacology.<br /> The conclusions rest on the specificity of drugs.<br /> Is 5 uM FK506 specific?<br /> 20 μM 1-naphthyl acetyl spermine (NASPM)?<br /> 10 mg/kg IEM-1460?

Reviewer #1 (Public Review):

The essentiality of Rv1636 has previously been predicted in numerous genetic studies. Here, the authors provide evidence that Rv1636 is an essential protein in Mtb. The authors report that chromosomal deletion of the gene encoding Rv1636 is only possible when an additional copy of the wild type gene is provided at the L5 integration site in the chromosome. While this is a standard method of demonstrating gene/protein essentiality in this system, the manuscript only provides a PCR reaction with "no amplicon" as proof of a double crossover event in an engineered merodiploid strain (Fig 6C). The authors fail to provide definitive evidence for a double crossover mutation in the merodiploid using primers that amplify a double crossover-dependent amplicon or the authors should a provide a southern blot demonstrating evidence for a bona fide double crossover event. The authors suggest that silencing the gene encoding Rv1636 with a CRISPRi system decreases viability of Mtb when a silencing guide RNA is expressed following Atc addition and spot plated onto agar. These studies lack a "no Atc control" and it is unclear how Mtb colonies appear after 6-7 days in these studies given the slow growth of this bacterium.

A sub-point of the manuscript describes the genetic organization around the gene that encodes Rv1636 in various Mycobacterial spp. Figure 1 also highlights the putative transcriptional start sites for the gene encoding Rv1636. The putative transcriptional start site information is just a summary of work from other groups and this information adds little to the main goals of this manuscript.

Another sub-point of this manuscript is that Rv1636 may be secreted by Mtb in a SecA2 dependent manner. The authors demonstrate that Rv1636 is not present in the culture filtrate of Mtb lacking SecA2 (Fig 2). However, these data are difficult to interpret without a secreted protein "loading control" which is typical for these types of experiments. The authors also report the development of a luciferase-based detection method for quantifying protein secretion in Mtb and use this to support their conclusion. This is a new tool that could be useful in detecting secreted proteins in Mtb. However, this method is not rigorously validated in these studies and do not present controls for cell lysis for example. Additionally, the authors fuse a ~19 kDA luciferase subunit to the C-terminus of CFP10 as a reporter for Esx1-dependent secretion. It is known that this region of CFP10 is critical for interactions with secretory components of the Esx1 system fractionation and it unclear if the CFP10 fusion protein is actually secreted.

The authors explore the idea that Rv1636 may potentially function as a "sink" for cAMP and quantify the molar amounts cAMP, ATP, and Rv1636 in Mtb. These studies demonstrate that the molar amounts of Rv1636 exceeds the levels of cAMP (free or protein-bound) in the cytosol of the Mtb. The authors conclude that the excess of Rv1636 may potentially be a "sink" for unbound cAMP but do not test this idea experimentally in Mtb due to the very low levels of cAMP in this bacteria.

Instead, the authors continue exploring the idea that specific proteins can serve as a cAMP "sink" using M. smegmatis (Msm) since this bacterium produces more cAMP (~25x) in the cytosol compared to Mtb. The authors present data that over expression of Rv1636 in Msm increases the amount of protein-bound cAMP. It is presumed here that the protein-bound cAMP is bound to Rv1636. Alternatively, deleting the Rv1636 homolog in Msm (MSMEG_3811) results in an increase in the amount of "free cAMP". Again, it is presumed that deleting the cAMP binding protein MSMEG_3811 is responsible for the increase in the amount of "free cAMP" in the cell.

Lastly, the authors use two small molecule compounds that may bind Rv1636 and demonstrate some level of bacterial inhibition using a spot plating method. No evidence is provided to demonstrate that these compounds are specifically binding/inhibiting Rv1636. These studies are lacking rigorous demonstration of "on target" inhibition and add very little to the reliable conclusions in this paper.

Reviewer #1 (Public Review):

Villalobos-Cantor et al. describe a chemical/genetic strategy to enable cell-type-specific labeling of nascent proteins in living tissues (called POPPi). O-propargyl-puromycin (OPP) is a commonly used compound to label nascent proteins in cells and tissue, however, its application is limited in vivo because it can not be targeted to individual cell types, tissues, or organs. Using Drosophila as a genetically tractable in vivo model organism, Villalobos-Cantor et al. incubate live tissue with a puromycin analog called phenylacetyl-OPP (PhAc-OPP) in combination with cell-type expression of Penicillin G acylase (PGA), which converts PhAc-OPP to OPP. As PGA is under the control of the Gal4/UAS system, a vast library of tissue-specific Gal4 lines can in theory be used to conduct labeling experiments in vivo.

The major strength of the methods and results is the demonstration that labeling can occur in specific cell types of the dissected brain - neurons and glia. For example, protein synthesis in individual dopamine neurons in the brain can be visualized and distinguished from neighboring cells, a remarkable achievement and striking image. These results in dissected brains nicely demonstrate that PhAc-OPP can penetrate into brain tissue, diffuse to internal locations, pass through the cell membrane, and become converted to OPP and label nascent proteins. A major weakness of the methods and results is the lack of exploration of POPPi in tissues other than the brain, as well as in non-dissected living animals. For example, the authors do not test if PhAc-OPP delivery can occur by feeding animals, or if PhAc-OPP can penetrate into various dissected tissues. Results from these experiments would be of great importance to others interested in applying this technique in non-brain tissues, and would properly support the authors' claims in the title and abstract that this is a general method (not only for the brain).

Assuming that PhAc-OPP can penetrate various dissected tissues, this method would have a significant impact on tissue-specific measurements of protein synthesis and could be a valuable new molecular reporter for gene function analysis (e.g. tissue-specific gene knockout + POPPi). If PhAc-OPP could be ingested by flies, perfuse through the body, and label nascent proteins in a cell-type specific manner, then POPPi could be incredibly useful for tissue-specific proteome profiling (i.e. mass spectrometry) in an in vivo living animal (non-dissected), similar to the BioID system.

Reviewer #1 (Public Review):

This project aimed to understand if decision making impairments commonly observed in older adults arise from working memory (WM) or reinforcement learning (RL) deficits. Evidence in the paper suggests it is the former; they observe poorer task accuracy in older adults that is accompanied by a faster memory decay in older adults using a novel hierarchical instantiation of a previously validated computational model. There were no similar changes in RL in this model. These results are extended using Magnetic Resonance Spectroscopy (MRS) to measure glutamate and GABA levels in striatum, prefrontal and parietal regions. They found that impairments in working memory were linked to reductions of glutamate in PFC, particularly in the older adult group.

The task employed is elegant and has been studied extensively in different populations and is well-validated (though here a hierarchical Bayesian extension is developed and validated). The results however may not be definitive in some respects; the paper did not replicate previously observed RL deficits. It therefore, remains possible that this is due to the sensitivity of the task to this RL component in ageing and future work is needed to fully bridge the gap in the literature.

Although the study is well-executed, there is an obvious limitation in the use of a cross-sectional design to address this question. The authors acknowledge this limitation in the discussion but could go further to highlight the potential confound of cohort effects on gaming, RL and WM tasks more generally. Without within-person change data, the evidence can only be suggestive of potential age-related decline. For this reason, it may be more appropriate to use the terminology "age-related differences' rather than "age-related declines" given the study design.

Reviewer #1 (Public Review):

This study represents an important work in the field of (CAR)T-cell immunotherapy by analyzing the effect of different oxygen tension on the function and differentiation of T-cells (especially CD8+). Although it has been described that low oxygen levels can influence effector function/differentiation of T-cells, as nicely acknowledged by the authors in the introduction, a comprehensive analysis in the context of immunotherapy has been missing so far and this study adds significant findings that will be relevant for patient care in all fields applying (CAR)T-cell immunotherapy.

The strength of the evidence is generally solid although there are some discrepancies between the different ways to induce HIF-1α (i.e. low O2, pharmacological inhibition, shRNA knockdown) that need to be clearly stated and/or discussed.

1) The first section of the results determines the impact of low oxygen and pharmacological HIF-1α stabilization on CD8+ T-cell activation/differentiation. Low oxygen diminishes cell growth but induces T-cell activation and effector cytokines, while HIF-1a stabilization mimics the effects on activation without alterations in expansion. Unfortunately, it remains unclear why effects upon low O2 are more pronounced although pharmacological HIF-1a stabilization is more efficient.<br /> 2) As a next step, in vitro conditioned T-cells are transferred into a subcutaneous B16-OVA model. Although only the low O2 levels increase T-cell numbers in vivo after the transfer, the initial tumor burden was nicely decreased by both low O2 and HIF-1a stabilization. However, only the latter significantly improved survival and it remains unclear and uncommented why.<br /> 3) Next, the authors address whether pre-conditioning of human CART-cells to induce HIF-1α either by pharmacological stabilization or by silencing of VHL shows similar effects. Surprisingly, both ways of HIF-1a stabilization resulted in different effects concerning differential gene expression and cytotoxic capacity of CART-cells. Accordingly, pharmacologically pre-conditioned CART-cells did not have a significant impact on survival in an in vivo model, while the VHL-silenced ones did significantly improve animal survival. This discrepancy between the two modes of HIF-1a stabilization remains uncommented. Unfortunately, it also remains unclear why the pharmacological HIF-1a stabilization significantly improved the survival in animals of the B16-OVA model and not in the human CART-cell model.<br /> 4) After this, the researchers determine how the timing of hypoxic conditioning affects the (CAR)T-cells. Here it is convincingly shown that already a short period of hypoxic conditioning (1 day) with a subsequent expansion phase (additional 6 days) is sufficient to induce HIF-1a mediated alterations (e.g. metabolic changes, calcium flux, intracellular signaling). Although this section is coherent in itself, the switch between different times of hypoxic conditioning, expansion, and analysis is difficult to follow and might lead to confusion. The expression pattern of e.g. HIF-1a on day 1 and day 7 together with the nuclear amounts of NFAT and c-Myc might be misunderstood, like the other presented data as well.<br /> 5) Last, short-term hypoxic conditioning of CART cells is tested in a solid tumor mouse model. The previously identified conditioning protocol also increases CART-cell function against solid tumors (as shown by enhanced cytotoxicity, reduced tumor burden, and prolonged survival). Unfortunately, although both HER2-CART-cells and CD19-CART-cells are shown to have superior cytotoxicity in vitro after the pre-conditioning, only HER2-CART-cells are demonstrated to be superior upon low O2 conditioning in an in vivo adoptive transfer mouse model and CD19-CART-cells remain an open question.

Generally spoken, the limitations of the manuscript are:<br /> 1) The occurring discrepancies of determining effects caused by the different modes of Hif-1a stabilization which certainly are caused by the complex nature of Hif-1a regulatory network, and;<br /> 2) The limitation of detected effects primarily on CD8+ T cells while CART-cells products usually are a mixture of CD4+ and CD8+ ones.

Reviewer #1 (Public Review):

This manuscript described the role of ALKBH5, an evolutionarily conserved mRNA m6A demethylase as a key regulator of axon regeneration. The authors screened the function of m6A regulators during axon regeneration and found that ALKBH5 limits regenerative growth associated with DRG neurons, by enhancing the stability of Lpin2 mRNA via erasing a single m6A modification in the 3'UTR. The major strength of the manuscript is the convincing importance of ALKDH5 as an attenuator to initially suppress the axon regeneration in the CNS and in the PNS proven by in vivo model system. These findings further suggest the potential use of ALKDH5 inhibitors to enhance neural regeneration upon physical injury.

Reviewer #1 (Public Review):

Baggett C., Murphy K. R., and Sengun E. et al. investigated cell senescence as the basis of pro-arrhythmogenic changes associated with myocardial infarction in the aged heart using the rabbit as a model, with validation of senescence markers on human heart specimens. The study is interesting and addresses a relevant biological and health issue. The authors demonstrate that aged rabbits are prone to arrhythmogenesis associated with higher mortality within 72 h after induction of myocardial infarction. Analysis of scar morphology determined that fibrosis is not sufficient to explain age-associated arrhythmogenesis. Instead, the authors show that senescence, assessed by -galactosidase activity, expression of regulators of the senescence-associated secretory phenotype, and H2AX, is increased in myofibroblasts compared to endothelial cells in infarcted aged rabbit hearts. Accordingly, H2AX was detected in αSMA+ cells in human-aged hearts. The authors tested the influence of myofibroblasts on cardiomyocyte electrophysiology by exposing cardiomyocytes in vitro to conditioned media from fibroblasts in which senescence was induced by treatment with etoposide. Such treatment did not affect action potential duration, leading the authors to conclude that senescent fibroblasts are unlikely to influence cardiomyocytes through paracrine signaling. Instead, the authors propose a possible yuxtacrine effect. To test this, they performed immunofluorescence to infer potential myofibroblast-cardiomyocyte coupling by the presence of connexin 43 in the cell-cell interphase and tested the potential electrophysiological effects of coupling using a computational model.

The analysis of peri-procedure mortality, arrhythmogenesis, and senescence in young and aged rabbits subjected to myocardial infarction is valuable, represents a significant amount of work, and the results support the conclusions drawn. Stronger evidence that senescent myofibroblasts couple with cardiomyocytes in the aged heart is needed to support the proposed model.

The authors conclude a propensity of myofibroblast senescence based on the finding that 80% of αSMA+ cells are also positive for H2AX. Showing the immunofluorescence results on hearts 2 weeks after MI would help to more convincingly illustrate the result. From these immunofluorescence experiments, it is also concluded that most of the persistent senescent cells in the scar correspond to myofibroblasts. The results presented show a continued increase in the proportion of H2AX+ cells in aged hearts up to 12 weeks after myocardial infarction. According to results in Figures 4F and G, these cells do not correspond to either myofibroblasts or endothelial cells. Given that H2AX+ cells are significantly increased in the aged heart, could the results presented suggest that a different cell type might be more important for the aged heart's response to MI? Providing some insight into the identity of these cells would be helpful to better understand the results presented. For example, cardiomyocyte senescence could contribute to arrhythmic phenotypes.

The results presented show that treatment of cardiomyocytes with conditioned media from, and co-cultured with, senescent myofibroblasts did not change action potential duration in cardiomyocytes. This led to the conclusion that paracrine signalling is unlikely to contribute to a pro-arrhythmogenic phenotype. It is possible that cardiomyocytes do couple with myofibroblasts in the in vitro system used. In which case, the results presented would not favor the proposed model. Another important possibility to be considered is that myofibroblasts might not have produced senescence-associated secretory phenotype-mediators at concentrations high enough to alter action potential duration in the conditions tested. Experimental evidence of the levels of selected mediators of the senescence-associated secretory phenotype in conditioned media would help assess a potential paracrine effect.

The evidence of coupling, i.e., the presence of connexin-43 in the interphase between αSMA+ and cardiomyocytes needs to be strengthened. Perhaps analyzing Z-stack 3D reconstructions would help to better define adjacent cells and more precisely reveal the localization of connexin-43.

Reviewer #1 (Public Review):

This manuscript describes the differences in the plasma proteome and metabolome in healthy Tanzanian and healthy Dutch adults. The inflammatory plasma proteome was measured using the Olink 92 Inflammation panel, while the plasma metabolome was analyzed using a mass spectrometry-based untargeted approach. The plasma metabolome was measured only in the Tanzanian cohort. This study aimed to link the pro-inflammatory proteome of Tanzanian and Dutch healthy individuals with environmental factors and dietary lifestyles.

The correlation between the plasma proteome and food-derived metabolome profiles can shed light on the development of non-communicable diseases. This observation stresses the importance of dietary transition and lifestyle changes in expressing inflammation-related molecules. Moreover, this study describes the inflammatory proteome profile in healthy Tanzanian individuals covering a cohort with limited studies. The molecular differences in circulating biomolecules between healthy individuals living in East Africa and individuals living in Western Europe and the correlations with intrinsic and environmental features are novel.

This study lacks a robust and solid validation of some of the differentially regulated circulating proteins and correlations between food-derived metabolites and proteins in a selected cohort. The discovery-driven approach in this manuscript highlights potential findings that need to be supported by a validation phase. According to this reviewer, the lack of such validation impacts the robustness of the results and the hypotheses generated. Due to that, the manuscript should incorporate validation experiments.

Reviewer #1 (Public Review):

For PRLR, the question being asked is whether and how the intracellular domain (ICD) interacts with the cellular membrane or how the disordered ICD can relay and transmit information. The authors show that PI(4,5)P2 in the membrane localizes around the transmembrane domain (TMD) due to charge interactions and facilitates binding of the ICD to the membrane, even in the absence of the TMD. Furthermore, the ICD and PI(4,5)P2 form a co-structure with JAK2 which locks a disordered part of the ICD into an extended conformation, allowing for signal relay and, through multiple complex conformations, may enable switching signalling on and off.

Strengths:<br /> - NMR paired with MD is a powerful way to probe an interaction especially when peaks disappear and become difficult to probe by NMR.<br /> - Using NMR and MD to formulate hypotheses which are then tested by cell studies is quite informative. The combination of MD, NMR, and cell biology is a strength.<br /> - The authors are diligent in testing MD simulations on systems with and without PIP2.<br /> - The use of Pep1 and Pep2 to differentiate the KxK region that interacts with PIP2 is helpful.<br /> - The four utilized mutants help illustrate the co-dependence of the respective regions in the formation of the co-structure.

Weaknesses:

- In Figure 2G, there is a big change in CSP between 280 and 290, which the authors do not comment about.<br /> - The data in Figure 2 are summarized as indicating the formation of extended structure in the ICD upon binding. It is not clear to me what data show an extended structure.<br /> - No modelling or experiments were done with PIP3 despite conclusions and models which rely on the phosphorylation of PIP2 to PIP3. At the very least, these would be useful as negative controls.<br /> - Only R2 experiments were done when the authors mention investigating dynamics. R1 and -HetNOE dynamics would be useful for creating a complete picture.<br /> - Some of the exciting results are under-emphasized including Fig 3H and 3I.

Reviewer #1 (Public Review):

This study demonstrates that Chinmo promotes larval development as part of the metamorphic gene network (MGN), in part by regulating Br-C expression in some tissues (exemplified in the wing disc) and in a Br-C independent manner in other tissues such as the salivary gland. I have included below the following comments on the submitted version of this manuscript:

1. The authors have shown experimentally that Chinmo regulates Br-C expression in the wing disc but not the larval salivary gland. Based on this, they posit that Chinmo promotes larval development in a Br-C-dependent manner in imaginal tissues and a Br-C-independent manner in other larval tissues. This generalization of Chinmo's role in development would be more compelling if the relationship between Chinmo and Br-C were explored in other examples of imaginal/larval tissues.

2. Chinmo, Br-C, and E93 have all been shown to be EcR-regulated in larval tissues, including the brain and wing disc (as in Zhou et al. 2006, Dev Cell; Narbonne-Reveau and Maurange 2019, PLOS Biology; Uyeharu et al. 2017, ). It would be interesting (and I believe relevant to this study) to know whether the roles of these factors in their respective developmental stages are EcR-dependent and whether their regulation by EcR (or lack thereof) depends on whether the tissue is larval or imaginal.

3. In the chinmo qPCR analysis shown in Fig1A, whether animals were sex-matched or controlled was not indicated. Since Chinmo has a published role in regulating sexual identity (Ma et al. 2014, Dev Cell; Grmai et al. 2018, PLOS Genetics), and since growth/body size is known to be a sexually dimorphic trait (Rideout et al. 2015, PLOS Genetics), it seems important to establish whether the requirement of Chinmo for larval development and/or growth. I recommend either 1) controlling for sex by repeating qPCRs in Fig 1A in either males or females, or 2) reporting male/female chinmo levels at each stage side-by-side.

4. In Fig2E, the authors show that salivary gland secretion (sgs) genes are repressed in salivary glands lacking chinmo. Sgs genes are expressed during late larval stages as the animal prepares to pupate. Thus, based on the proposed model where Chinmo promotes larval development and represses the larval-to-pupal transition, one might expect that larval salivary glands lacking chinmo would express higher than normal levels of sgs genes. This expectation directly opposes the observed result - it would be helpful to speculate on this in the interpretation of results.

Reviewer #1 (Public Review):

The authors study single and pairs of MDCK cells adherent to an H-shaped geometry on a flat surface. In this pattern, the cells form strong peripheral stress fibers. To a lesser extent, these cells also exhibit stress fibers in the cell interior, which otherwise has a rather homogenous actin distribution. Using a combination of traction force microscopy, from which they infer the stress distribution by monolayer stress microscopy, and "contour analysis" the authors quantify the 'bulk' and the 'surface' stress in these cells. This analysis shows that single cells are mechanically polarized whereas pairs are not.

The authors then go on to optogenetically activate the actomyosin contractility of either one half of a single cell or one cell of a pair. Combining their stress measurements in these situations and using a finite element mechanical model, the authors convincingly show that the mechanical response in the non-activated part is active. By varying the aspect ratio of the adhesion patterns, they also find that the efficacy of active stress propagation depends on the mechanical and structural polarity of the cell. Furthermore, they provide evidence that their results on cell pairs generalize to tissues.

Strengths:

This study uses a nice combination of physical tools to address an important question in tissue mechanics. The data is compelling and fully supports the authors' conclusions.

Weaknesses:

There are no major weaknesses.

In summary, although the fact that mechanical stress propagation in tissues is an active process might not come as a surprise, the study makes substantial contributions to a quantitative contribution of this process. As such it is of fundamental significance in the field. It will be interesting to explore the consequences of this mechanism for mechanical stress propagation in the context of developmental processes. It will be also of great interest to study how this local process can be accounted for in large-scale theories.

Reviewer #1 (Public Review):

In this manuscript, the authors seek to define the transcriptional response to deafening in the songbird brain. They compare transcriptional changes in the song regions with changes in the non-singing-associated surrounds, compute a song degradation score against which they can compare gene expression, and they use single-cell sequencing data from these brain regions to map genes to cells. The study is impressively comprehensive for time points, replicates, brain regions, comparisons, and alternative strategies (e.g. the LMAN lesions). This dataset builds nicely upon studies that assessed gene expression changes upon singing and applies a broad and useful series of bioinformatics analyses to get the strongest evidence for function from the data.

I think this dataset will be of great interest to a broad range of researchers who study neuronal plasticity mechanisms.

Reviewer #1 (Public Review):

The network of neurons of the inferior olive has long been suggested as a timing machine that controls the precise timing of movements, correcting movement and participating in the prediction of movement time. These timing capabilities have been attributed to the unique feature of the neurons to generate subthreshold voltage oscillations that can be used as a timing machine. In this study, the effect of the inhibitory and excitatory synaptic inputs on the oscillatory behavior was examined, demonstrating their different effects as well as the effects of combing the two inputs.

Reviewer #1 (Public Review):

Overall, this manuscript by Liu et al. provides a largely convincing mechanism for both how Zfp467 regulates osteoblast differentiation and how PTH1R expression and function in osteoblast-lineage cells is regulated at the transcriptional level, finding that NF-kB (RelB/p50) regulates PTH1R expression downstream of Zfp467. PTH1R expression and activity in turn is enhanced in Zfp467-deficient osteoblasts. In turn, PTH signaling regulates Zfp467 expression through PKA activity. In particular, the new findings on mechanisms of regulating PTH1R expression and evidence that this in turn impacts osteoblast differentiation are felt to be of broad interest and importance. The approach used is felt to be largely sound. Areas of major concern are few and relate mostly to better fleshing out how the NF-kB pathway is impacted as a part of the molecular pathway implicated here and clarifying some confusion regarding uCT data that appears to be discussed but which this reviewer cannot locate in the figure.

Reviewer #1 (Public Review):

In this study, the authors sought to develop a measure of Staphylococcus aureus intracellular virulence levels in the lab (the InToxSa assay) that more closely mimics the activity seen in vivo. They then used untargeted approaches (GWAS, homoplasy) on a set of 387 Australasian clinical isolates to identify genes with mutants associated with reduced intracellular toxicity. The authors identified several mutated genes which reduced virulence in the strains chosen for the study, demonstrating that their approach can be used to uncover virulence-related genes in S. aureus.

The study is clearly written, with high-quality figures. The development of the InToxSa assay is carefully described and logical. InToxSa was shown to potentially be more sensitive than the tryptophan blue test in detecting reduced intracellular cytotoxicity phenotype. They also showed evidence for agrA mutants and other transposon mutants with reduced inToxSa cytotoxicity having increased bacterial cell numbers cells compared to wild-type (Fig 2, Fig5GH), which is critical to the argument that bacteremia selects for intracellular persistence as a way to escape the immune system. There was an interesting and thoughtful use of random forest to choose the most appropriate parameters of the kinetic model.

The GWAS studies used publicly deposited genome data and clearly showed lineage effects of reduced intracellular survival of CC239 and CC22, confirming previous results. GWAS also confirmed the well-known pervasive association of agr mutants with reduced toxicity. Using a well-described homoplasy test for convergent evolution to extract more power, several other potential genes associated with enhanced intracellular toxicity were discovered or rediscovered, perhaps most significantly, the ausA gene, with biosynthesizes aureusimines (pyrazinone secondary metabolites) posited to have a role in the phagosomal escape.

There are two main 'weaknesses'. The first is the limited power that comes from only using measuring the phenotype of 387 strains. Whether this is because of the expense/ difficulty of the inToxSa is not discussed, leaving open the question of how much this assay could be scaled up in the future. The second is that the main output of the assay is actually reduced intracellular toxicity (PI uptake AUC), which is inferred to be strongly linked to increased intracellular persistence. The linkage between the phenotypes comes primarily from microscopic studies on a limited number of strains. It may be true of all cases but the possibility exists that for some of the strains, reduced cytotoxicity may be associated with intracellular elimination, which would presumably be a negative outcome for systemic infection.

Overall, the authors achieved their aims in terms of assay development and showing the utility of the pipeline for mutation discovery. This is a waypoint in the larger aim of understanding mutational pathways that lead to increased persistence of systemic S. aureus. Obviously, a lot more data is needed. The InToxSa intracellular screening method is interesting and could be reused/adapted by the community. This research should also spark more interest in the role of ausA and aureusimines in virulence and some of the other genes discovered through the untargeted approach.

Reviewer #1 (Public Review):

In this paper, Krishnan et al. describe their findings on the genetic architecture of the heart mitochondrial proteome that influences cardiac hypertrophy. They analyzed common genetic variations contributing to mitochondrial and heart functions in a panel of inbred mouse strains called the Hybrid Mouse Diversity Panel (HMDP), by performing whole heart proteomics. The authors have published a number of papers on this panel, which appears to be a powerful system to study various genetic factors. They identified three trans-acting genetic loci, located on chromosome (chr) 7, chr13, and chr17, which control both mitochondrial proteins and heart hypertrophy. High-resolution regional mapping identified NDUFS4, LRPPRC, and COQ7 as the candidate genes for chr13, chr17, and chr7 loci, and variations of these genes were associated with heart mass in isoproterenol-induced heart failure and diet-induced obesity. Using co-expression protein networks using weighted gene co-expression network analysis (WGCNA), they show that the chr13 locus was highly enriched for complex-I proteins, the chr17 locus for mitochondrial ribonucleoprotein complex, and the chr7 locus for ubiquinone biosynthesis. They concluded that "common variations of certain mitochondrial proteins can act in trans to influence mitochondrial functions and contribute to heart hypertrophy, elucidating mechanisms that may underlie genetic susceptibility to heart failure in human populations."

Although these studies are interesting and provide novel findings in the genetics of cardiac hypertrophy, there are a number of technical and conceptual issues that need to be addressed.

Reviewer #1 (Public Review):

Mermithid nematodes are ecologically important parasitoids of arthropods, annelids and mollusks today. Their fossil record in amber reaches back into the Early Cretaceous, some 135 million years ago. Luo et al. more than triple this record by presenting, with ample illustrations, exceptionally well preserved new specimens from the beginning of the Late Cretaceous (99 Ma ago) of Myanmar. Their most important finding is that mermithids parasitized a number of insect clades in the Cretaceous that they are not known to infect today or in Cenozoic amber; further, the proportion of holometabolous insects among the hosts is found to be lower in the Cretaceous than in the Cenozoic. The strengths of the paper lie in the specimens, the illustrations of the specimens, and the documentation of when, where and how the specimens were acquired. Certain nomenclatural aspects of the paper require improvement. A potential weakness of the paper could be collection bias: it is not tested whether the collections used to show the shift toward holometabolous hosts from the mid-Cretaceous to the Cenozoic are representative of the fossil record as it is preserved and accessible today.

Reviewer #1 (Public Review):

This paper investigates the neural correlates of noise-induced hearing loss. The authors use an electrode array to capture neural responses across the inferior colliculus to speech and synthetic sounds in both normal-hearing gerbils, and gerbils with noise-induced hearing loss. They use dimensionality reduction to isolate a low-dimensional response subspace that captures most of the information about the speech signals, and find that this low-dimensional representation is altered considerably by hearing loss (evaluated with CCA). To probe the basis of these differences, the authors train an artificial neural network to predict the subspace responses to arbitrary stimuli, for instance to investigate the consequences of frequency-dependent amplification of sound with a hearing aid, or synthetic test stimuli. Using this approach, they find that the representation of sounds in quiet is largely restored by a hearing aid algorithm that amplifies high frequencies to render them audible. However, the representation of sounds in noise also differs between the IC of normal-hearing and hearing-impaired gerbils, and this difference is not eliminated by a hearing aid. Specifically, low-frequency maskers seem to distort the representation of high-frequency sounds (e.g. consonants in speech), even once the high-frequencies have been amplified to compensate for the hearing loss.

Overall, this is a strong paper. The topic is important, the methods are innovative, logical, and rigorous, and the whole thing is exceptionally clearly described. I greatly appreciate the care that clearly went into writing the paper. I have two major concerns. The first seems fairly critical to the paper's conclusions, but I hope can be addressed with some kind of control experiment. The second could potentially be thought of as more of a future direction, but it speaks to the specificity of the conclusions.

1. My main substantive concern is that the conclusions depend critically on believing the predictions of the DNN, and yet it is not clear we should expect it to generalize well to stimuli outside its training distribution. Current artificial neural networks typically work very well for stimuli like those they were trained on, but often do not generalize as well as one might like. The authors recorded responses to speech in quiet and in different noise levels, and show that the trained DNN (trained on these sounds and the associated responses) produces very accurate predictions on held-out sounds from this distribution. But the conclusions depend critically on the DNN predictions for sound processed by a hearing aid, and for synthetic sounds (pure tones, SAM noises) that are quite unlike the training data. The predictions look reasonable in places where we have some prior sense for what to expect (level-dependent frequency tuning to pure tones), which is reassuring, but I am not sure how to be confident that the predictions should be accurate for all of the conditions that are tested, in particular to the results with the simulated hearing aid. I am pretty sure that the predictions will be inaccurate for some types of stimuli (just based on the various pathologies that are known to occur with neural networks). I would hope that this would not be the case for the conditions tested by the authors, but it is hard to be sure, and this makes the conclusions seem a little more vulnerable than I would like.<br /> How do we know that the DNN generalizes beyond its training data well enough to render the conclusions airtight?

2. My second concern is the extent to which the results are specific to a) the IC, and b) noise. The authors assert that similar effects would not be present in the nerve, citing a Heinz paper, but I am not sure how clear this evidence is - it is not described in enough detail here to assess. It would be nice to show this, perhaps by repeating their analysis on a model of the nerve with and without simulated hearing loss. One can similarly wonder about the effects in the cortex, especially given the literature on noise invariance (Rabinowitz, Moore, Khalighinejad, Kell...), which would at least be worth discussing. It is similarly unclear whether the results are specific to additive noise. Would similar conclusions hold for any type of distortion? This could be easily addressed by an additional DNN analysis (e.g. with clipping, or segments of speech intermittently replaced by silence, or reverberation).

Reviewer #1 (Public Review):

This manuscript seeks a greater understanding of joint movements in recipients of total knee replacements who have symptoms of unstable prosthetic joints. The authors describe the results of a carefully conducted retrospective analysis of joint movements after total knee replacement (TKA) using a recently developed method based on videofluoroscopy. Kinematic data supplemented by electromyography measurements of muscle activation through normal gait. These measurements were conducted while walking on flat ground, down an incline, or down stairs. The kinematics and EMG data provide convincing evidence of altered knee kinematics when symptoms of joint instability occurred that were accompanied by subject-specific changes in patterns of muscle activation. The manuscript raises interesting questions about how patients adapt muscle activation patterns to limit discomfort prior to TKA and to what degree these same defensive strategies influence joint stability post-operatively.

Reviewer #1 (Public Review):

In this manuscript, Li et al characterize sex differences in the impact of macrophage RELMa in protection against diet-induced obesity [DIO]. This is a key area of interest as obesity studies in mice have generally focused exclusively on male animals, as they tend to gain more weight, faster than female mice. The authors use a combination of flow cytometry, adoptive transfer, and single-cell transcriptomics to characterize the mechanism of action for female-specific DIO protection. They identify a potential role for eosinophils in mediating female DIO protection downstream of RELMa production by macrophage. They also use the transcriptomic characterization of the stromal vascular fraction of the adipose tissue to evaluate molecular and cellular drivers of this sex-specific DIO protection.<br /> Although the authors provide solid evidence for many claims in the manuscript, there is generally not enough information about the studies' methods (especially on the computational/data analysis aspects) for a careful evaluation of the result's robustness at this stage.

Reviewer #1 (Public Review):

In vertebrates, ciliary motility is important for left-right body patterning, airway clearance, cerebrospinal fluid flow, and the locomotion of spermatozoa. The movement of cilia is powered by the action of dyneins tethered to axonemal doublet microtubules. The largest and most powerful axonemal dynein, OAD, is tethered by a pentameric docking complex (the OAD-DC). Here, Yamaguchi, Morikawa and Kikkawa show convincingly that the Calaxin and Armc4 subunits of the OAD-DC have discrete roles in docking OADs. Using zebrafish mutants, they show that loss of Armc4 causes complete loss of the OAD, whereas mutation of Calaxin causes only partial OAD loss. They demonstrate that Calaxin localization is dependent on Armc4 but independent of the OAD or calcium conditions. Using cryo-ET, they report a higher resolution structure of the wild-type zebrafish sperm axoneme than previously determined (Yamaguchi et al., 2018) and show that the OAD and OAD-DC structures resemble the cryo-EM structures of other organisms. Cryo-ET analysis of calaxin-/- axonemes reveals that without Calaxin, OADs have mostly normal conformations but make fewer connections with the OAD-DC and are less stably bound. The paper is well-written with appropriate methods and conclusions.

Reviewer #1 (Public Review):

This interesting manuscript by Nakajima-Takagi et al describes the roles of the PRC 1.1 member Pcgf1 in myeloid lineage commitment in hematopoiesis and in regulating myeloid differentiation and self-renewal during emergency myelopoiesis. The roles of Pcgf1 have been explored previously in the context of Runx1 depletion or in the context of myelofibrosis together with the JAK2V617F mutation, but this is the first report of the specific roles of Pcgf1 in HSCs and in myelopoiesis. The authors convincingly demonstrate that conditional deletion of Pcgf1 in hematopoietic cells causes a lineage switch in HSCs from lymphoid to myeloid fates and that a key mechanism for this lineage switch is regulation of the H2AK119ub1 chromatin mark, leading to de-repression of CEBPalpha, a key transcription factor that promotes myeloid cell fate. They also perform a single-cell RNAseq experiment and demonstrate an increase in the population of "self-renewing GMPs", and they attribute this increase to an upregulation in HoxA9 expression and beta-catenin activation. They also demonstrate that HoxA9 overexpression promotes beta-catenin activation, which has been observed in emergency myelopoiesis in other studies, though the mechanism for this is unclear. The authors also demonstrate that deletion of Pcgf1 in hematopoietic cells can also lead to deregulated myelopoiesis, leading to a lethal MPN in a subset of animals. They conclude that Pcgf1 plays a critical role to regulate emergency myelopoiesis, and to prevent the malignant transformation of myeloid progenitors.

Overall, the methods are highly rigorous and the results support the authors' conclusions. The only conclusion that would require further clarification is that Pcgf1 promotes emergency myelopoiesis. Emergency myelopoiesis typically starts with a proliferative burst of myeloid progenitors in response to a stress stimulus, followed by enhanced myeloid differentiation into mature functional myeloid cells. In this Pcgf1 KO mouse model, it is clear that there is an increase in the production of myeloid progenitors, and prolonged survival of myeloid progenitors in culture, but there is no demonstration that this results in the generation of mature functional myeloid cells. It appears that there may also be a differentiation block, likely due to the increase in "self-renewing progenitors", which is likely a consequence of HoxA9 upregulation, and possibly the beta-catenin activation in myeloid progenitors. Therefore, if there is also a differentiation block due to Pcgf1 deletion, the statement that emergency myelopoiesis is enhanced may be an oversimplification. What appears to occur is an expansion of a pool of self-renewing transformed or pre-transformed myeloid progenitors, and the relevance of this event to emergency myelopoiesis is not entirely clear. However, there is a clear significance of these findings and this new mouse model for studying the pathogenesis of myeloid malignancies, such as MPN, MDS, or AML, in which mutations in other components of PRC1.1 are frequently mutated, so this study is likely to have a significant impact in the field.

Reviewer #1 (Public Review):

This paper presents a thorough biochemical characterization of inferred ancestral versions of the Dicer helicase function. Probably the most significant finding is that the deepest ancestral protein reconstructed (AncD1D2) has significant double-stranded RNA-stimulated ATPase activity that was lost later, along the vertebrate lineage. These results strongly suggest that the previously known differences in ATPase activity between extant vertebrates and, for example, extant arthropods is due to loss of the ATPase activity over evolutionary time as opposed to gains in specific lineages. Based on their analysis, the authors also "restore" ATPase function in the vertebrate dicer, but they did so by making many (over 40) mutations in the vertebrate protein, and it is not clear which of these many mutations is required for the restoration of the activity. Thus, it is difficult to discern how the results of this experiment relate to the evolutionary history.

A criticism of the paper is the authors' tendency (probably unconscious) to ascribe a purposefulness to evolution. For example, in the introduction, "We speculate that the unique role of the RLR's in the interferon signaling pathway in vertebrates...created an incentive to jettison an active helicase in vertebrates." Although this sentence is clearly labelled as speculation and "incentive" is clearly a metaphor, the implication is that evolution somehow has forethought. (There are other instances of this notion in the paper, for example, in the last line of the abstract). The author's statement also implies that the developing interferon system somehow caused the loss of active helicase, but it seems equally plausible that the helicase function was lost before the interferon system co-opted it.

Reviewer #1 (Public Review):

VO2max is one of the most important gross criteria of peak performance ability and a plethora of studies focused on VO2max prediction. This manuscript provides huge and comprehensive data from male runners and male cyclists. The endurance-trained athletes performed cardiopulmonary exercise testing on a treadmill (n= 3330) or cycle ergometer (n=1094). In contrast to former studies, the authors used machine learning for algorithms and VO2max prediction. Models were derived and internally validated with multiple linear regression. The present study substantially expands current research.

Sadly, the manuscript has an important and relevant main shortcoming as the limitations of the study had not been addressed properly:<br /> - The authors paid no attention to the fact that their results are strongly influenced by the exercise protocol used. It is obvious e.g. that maximal performance attainable in protocols with 2-minute exercise steps will be higher compared to an identical protocol with 3- or 4-minute steps.<br /> - The exercise intensity was kept constant for only 2 minutes before the workload was increased (by 1km/h treadmill or by 20-30 W cycle ergometer). Due to the kinetics of lactate, VO2, etc., it is evident that the short 2-min intervals aggravate the correct determination of aerobic and anaerobic threshold. It is well-known that longer-lasting constant exercise steps (e.g. 4 minutes) are better when the focus is centered on threshold determinations.

The quality of this manuscript will be substantially improved when the authors could implement a comprehensive and blunt paragraph showing the limitations of their study.

Reviewer #1 (Public Review):

The authors provide evidence for chromatin, which in Drosophila muscle cells is peripherally localized in the nucleus, whereas the central region is depleted of chromatin, and is organised such that RNA polymerase II (RNAp) is surrounding dense regions of chromatin. The authors theoretically study the formation of these regions by describing chromatin as a multi-block copolymer, where the blocks correspond to active and inactive chromatin regions. These regions are assumed to phase separately and to have different solvability. The solvability of the active region is regulated by binding RNAp. The authors study the core-shell organization in a layered geometry by analyzing the various contributions to free energy. In this way, they in particular obtain the dependence of the shell-layer thickness, which is described as a polymer brush. From these results, they infer chromatin organization in spherical core-shell chromatin domains and compare these results to Brownian dynamics simulations.

The work is well done and even though it uses standard methods for studying block copolymers and polymer brushes obtains interesting information about local chromatin organization. These findings should be of great interest to researchers in the field of chromatin organization and in general to everybody interested in understanding the physical principles of biological organization.

The work has two main weaknesses: The experimental evidence for RNAp and chromatin micro-organization is weak as only one example is shown. It remains unclear whether the observed organization pattern is common or not. Also, no data is shown concerning the dependence of the extensions of the active and inactive phases on parameters, for example, solvent properties or transcriptional activity. Second, some parts could prove difficult for biologists to assess. For example, the expression for the brush-free energy should be explained in more detail and notions like that of 'mushrooms' need to be introduced. As a second example, biologists might benefit from a better explanation of the concept of a theta solvent and its relevance.

Reviewer #1 (Public Review):

Marchal-Duval et al studied the role of Prrx1 in lung fibroblasts. Prrx1 is a transcription factor expressed in lung fibroblasts but not in other cell types. The authors showed that Prrx1 gene expression was enhanced in IPF patients. Immunohistochemistry in IPF tissue suggested that Prrx1 was expressed in fibroblasts in fibroblastic foci. The authors then showed that Prrx1 expression was regulated by TGF-b1 stimulation or stiffness of substrate by in vitro experiments using primary human lung fibroblasts from either normal or IPF lungs. The authors also showed that Prrx1 regulated fibroblast proliferation and TGF-b signaling by regulating PPM1A and Tgfbr2 expression. Finally, the authors revealed that Prrx1 knockdown suppressed fibrosis in bleomycin-induced fibrosis or PCLS. This manuscript identified novel molecular roles of Prrx1 in fibroblast activation, which is expressed in not only lung fibroblasts but also in other injured or developing organs. To support the idea that Prrx1 plays a critical role in lung fibrosis, however, some discrepancies between in vitro and in vivo data need to be clarified.

1. Although the authors showed that Prrx1 knockdown in primary fibroblasts reduced Smad2/3 phosphorylation, the reduction of Acta2 or Col1a1 after Prrx1 knockdown and TGF-b1 stimulation was not impressive (Fig. S6), suggesting that the inhibition of TGF-b signaling by Prrx1 knockdown is only partial. In contrast, Prrx1 knockdown by ASO in bleomycin-induced fibrosis showed remarkable fibrosis suppression (Fig. 6, 7). Admittedly there are differences in models and nucleotides used, but this discrepancy needs to be addressed.

2. Fig.6 and 7 lack control groups, where mice are treated with PBS instead of bleomycin and treated with either control ASO or Prrx1 ASO.

3. In Fig. 6F, the hydroxyproline content is shown with ug collagen/ug protein. Total protein in the lung is influenced by infiltration of hematopoietic cells, which are the major population in injured lungs by cell count. Fibrosis should be ideally assessed as ug hydroxyproline/lung (or lobe).

4. Major proliferating populations in bleomycin-treated lungs are not mesenchymal cells but epithelial/endothelial/hematopoietic cells. Mki67+ cells (Fig. 7D) need to be identified by co-staining with mesenchymal markers if the authors claim that Prrx1 knockdown suppresses fibroblast proliferation in vivo.

5. Bleomycin-injured lungs or IPF tissue are patchy and mixed with normal and abnormal areas. Therefore, how areas of interest are chosen for histological quantifications (Fig. 6C, S14D) need to be described in the methods section.

Reviewer #1 (Public Review):

Here the authors investigate the mechanisms by which pulmonary endothelial cells (EC) contribute to alveolar repair post-H1N1-mediated acute lung injury and the molecular basis for the heterogeneity of this response among different EC subpopulations. Using single-cell transcriptomic analysis they identify the CREB family factor Atf3 differentially enriched in CAP1B cells, a subpopulation of EC previously known for its proliferative behavior in response to alveolar injury. They report a crucial role for Atf3 in injury repair but not during homeostasis. Using a combination of lineage tracing and loss function approach and an influenza mouse model in vivo, they show that Atf3 inactivation in ECs results in the inability of CAP1B ECs to initiate a proliferative response to repair the vascular compartment and ultimately regenerate the lung. Notably, the decreased number of Atf3 lineage-labeled EC capillaries was shown to correlate with the alveolar regions that failed to repair the post-H1N1 injury. They conclude that Atf3 is an essential factor for repair damaged capillaries in alveolar injury.

The study is carefully designed and the results provide novel important information about a previously undisclosed role of Atf3 in the regeneration of the lung vascular component. The work has many strengths and is supported by impressively coherent data from the analysis of mouse genetic models, single-cell transcriptomic, and phenotypic characterization.

Joint Public Review:

The manuscript "Monoallelically-expressed Noncoding RNAs form nucleolar territories on NOR-containing chromosomes and regulate rRNA expression" reports the discovery of a family of ncRNAs they call SNULs for Single NUcleolus Localized RNA and examine their localization with respect to nucleoli and reports that the RNAs they are examining are monoallelically expressed in a mitotically stable manner similar to what happens in X inactivation.

These RNAs come from a screen which is not well described and the descriptions of the sequence analyses are unclear, so it is difficult to know exactly what they are analyzing in the manuscript. If these are RNAs with reasonable abundance, then they should be findable without the extensive PCR amplification they appear to have done for the PacBio sequencing (the methods section is not clear on exactly how many rounds of PCR were performed). Moreover, given the acknowledged sequence similarities of the SNULs with other RNAs, the possibility of chimaera formation during PCR amplification is high. They are clearly detecting RNAs associated with nucleoli but exactly what they are examining is unclear. It is possible that a clear determination of the genomic origin of these RNAs will be complicated by the repetitive sequences in the regions of the genome where they reside.

Note also that the idea of monoallelic expression from rRNA encoding loci is interesting, but has been established in 2009. Title: Allelic inactivation of rDNA loci. Genes Dev. 2009 Oct 15;23(20):2437-47. doi: 10.1101/gad.544509.

Reviewer #1 (Public Review):

Jordan and Keller investigated the possibility that sensorimotor prediction error (mismatch between expected and actual inputs) triggers locus coeruleus (LC) activation, which in turn drives plasticity of cortical neurons that detect the mismatch (e.g. layer 2/3 neurons in V1), thus updating the internal presentation (expected) to match more the sensory input. Using genetic tools to selectively label LC neurons in mice and in vivo imaging of LC axonal calcium responses in the V1 and motor cortex in awake mice in virtual reality training, they showed that LC axons responded selectively to a mismatch between the visual input and locomotion. The greater the mismatch (the faster the locomotion in relation to the visual input), the larger the LC response. This seemed to be a global response as LC responses were indistinguishable between sensory and motor cortical areas. They further showed that LC drove learning (updating the internal model) despite that LC optical stimulation failed to alter acute cellular responses. Responses in the visual cortex increased with locomotion, and this was suppressed following LC phasic stimulation during visuomotor coupled training (closed loop). In the last section, they showed that artificial optogenetic stimulation of LC permitted plasticity over minutes, which would normally take days in non-stimulated mice trained in the visuomotor coupling mode. These data enhance our understanding of LC functionality in vivo and support the framework that LC acts as a prediction error detector and supervises cortical plasticity to update internal representations.

The experiments are well-designed and carefully conducted. The conclusions of this work are in general well supported by the data.

Reviewer #1 (Public Review):

The authors evaluate a number of stochastic algorithms for the generation of wiring diagrams between neurons by comparing their results to tentative connectivity measured in cell cultures derived from embryonic rodent cortices. They find the best match for algorithms that include a term of homophily, i.e. preference for connections between pairs that connect to an overlapping set of neurons. The trend becomes stronger, the older the culture is (more days in vitro).

From there, they branch off to a set of related results: First, that connectivity states reached by the optimal algorithm along the way are similar to connectivity in younger cultures (fewer days in vitro). Second, that connectivity in a more densely packed network (higher plating density) differs only in terms of shorter-range connectivity and even higher clustering, while other topological parameters are conserved. Third, blocking inhibition results in more unstructured functional connectivity. Fourth, results can be replicated to some degree in cultures of human neurons, but it depends on the type of cell.

The culturing and recording methods are strong and impressive. The connectivity derivation methods use established algorithms but come with one important caveat, in that they are purely based on correlation, which can lead to the addition of non-structurally present edges. While this focus on "functional connectivity" is an established method, it is important to consider how this affects the main results. One main way in which functional connectivity is likely to differ from the structural one is the presence of edges between neurons sharing common innervation, as this is likely to synchronize their spiking. As they share innervation from the same set of neurons, this type of edge is placed in accordance with a homophilic principle. In other words, this is not merely an algorithmic inaccuracy, but a potential bias directly related to the main point of the manuscript. This is not invalidating the main point, which the authors clearly state to be about the correlational, functional connectivity (and using that is established in the field). But it becomes relevant when in conclusion the functional connectivity is implicitly or explicitly equated with the structural one. Specifically, considering a long-range connection to be more costly implies an actual, structural connection to be present. Speculating that the algorithm reveals developmental principles of network formation implies that it is the actual axons and synapses forming and developing. The term "wiring" also implies structural rather than functional connectivity. One should carefully consider what the distinction means for conclusions and interpretation of results.

The main finding is that out of 13 tested algorithms to model the measured functional connectivity, one based on homophilic attachment works best, recreating with a simple principle the distributions of various topological parameters.<br /> First, I want to clear up a potential misunderstanding caused by the naming the authors chose for the four groups of generative algorithms: While the ones labelled "clustering" are based on the clustering coefficient, they do not necessarily lead to a large value of that measure nor are they really based on the idea that connectivity is clustered. Instead, the "homophilic" ones are a form of maximizing the measure (but balanced by the distance term). To be clear, their naming is not wrong, nor needs to be changed, but it can lead to misunderstandings that I wanted to clear up. Also, this means that the principle of "homophilic wiring" is a confirmation of previous findings that neuronal connectivity features increased values of the clustering coefficient. What is novel is the valuable finding that the principle also leads to matching other topological network parameters.

The main finding is based on essentially fitting a network generation algorithm by minimizing an energy function. As such, we must consider the possibility of overfitting. Here the authors provide additional validation by using measures that were not considered in the fitting (Fig 5, to a lesser degree Fig 3e), increasing the strength of the results. Also, for a given generative algorithm, only 2 wiring parameters were optimized. However, with respect to this, I was left with the impression that a different set of them was optimized for every single in-vitro network (e.g. n=6 sets for the sparse PC networks; though this was not precisely explained, I base this on the presence of distributions of wiring parameters in Fig 6c). The results would be stronger if a single set could be found for a given type of cell culture, especially if we are supposed to consider the main finding to be a universal wiring principle. At least report and discuss their variability.

Next, the strength of the finding depends on the strengths of the alternatives considered. Here, the authors selected a reasonably high number of twelve alternatives. The "degree" family places connections between nodes that are already highly connected, implementing a form of rich-club principle, which has been repeatedly found in brain networks. However, I do not understand the motivation for the "clustering" family. As mentioned above, they do not serve to increase the measure of the clustering coefficient, as the pair is likely not part of the same cluster. As inspiration, "Collective dynamics of 'small-world' networks" is cited, but I do not see the relation to the algorithm or results presented in that study. A clearly explained motivation for the alternatives (and maybe for the individual algorithms, not just the larger families) would strengthen the result. 

Related to the interpretation of results, as they are presented in Fig3a, bottom left: What data points exactly go into each colored box? Specifically, into the purple box? What exactly is meant by "top performing networks across the main categories" mean? Compared with Supp Fig S4, it seems as if the authors do not select the best model out of a family and instead pool the various models that are part of the same family, albeit each with their optimized gamma and eta. Otherwise, the purple box at DIV14 in Fig3 would be identical to "degree average" at DIV14 in S4. If true, I find this problematic, as visually, the performance of one family is made to look weaker by including weak-performing models in it. I am sure one could formulate a weak-performing homophily-based rule that drives the red box up. If such pooling is done for the statistical tests in Supp Tables 3-7, this is outright misleading! (for some cases "degree average" seems not significantly worse than the homophily rules).

The next finding is related to the development of connectivity over the days in vitro. Here, the authors compare the connectivity states the network model goes through as the algorithm builds it up, to connectivity in-vitro in younger cultures. They find comparable trajectories for two global topological parameters. <br /> Here, once again it is a strength that the authors considered additional parameters outside the ones used in fitting. However, it should be noted that the values for "global efficiency" at DIV14 (the very network that was optimized!) are clearly below the biological values plotted, weakening the generality of the previous result. This is never discussed in the text.

The conclusion of the authors in this part derives from values of modularity decreasing over time in both model and data, and global efficiency increasing. The main impact of "time" in this context is the addition of more connections, and increasing edge density. And there is a known dependency between edge density and the bounds of global efficiency. I am not convinced the result is meaningful for the conclusion in this state. If one were to work backwards from the DIV14 model, randomly removing connections (with uniform probabilities): Would the resulting trajectory match DIV12, DIV10, and DIV7 equally well? If so, the trajectory resulting from the "matching" algorithm is not meaningful.

Further, the conclusion of the authors implies that connections in the cultures are formed as in the algorithm: one after another over time without pruning. This could be simply tested: How stable are individual connections in vitro over time (between DIV)? 

The next finding is that at higher densities, the connections formed by the neurons still have very comparable structures, only differing in clustering and range; and that the same generative algorithm is optimal for modelling them. I think in its current state, the correlation analysis in Fig. 4a supports this conclusion only partially: Most of these correlations are not surprising. Shortest path lengths feature heavily in the calculation of small worldness and efficiency (in one case admittedly the inverse). Also for example network density has known relations with other measures. The analysis would be stronger if that was taken into account, for example showing how correlations deviate from the ones expected in an Erdos-Renyi-type network of equal sizes.

Yet, overall the results are supported by the depicted data and model fits in Supp. Fig S7. With the caveat that some of the numerical values depicted seem off: <br /> What are the units for efficiency? Why do they take values up to 2000? Should be < 1 as in 4b. Also, what is "strength"? I assume it's supposed to be the value of STTC, but that's not supposed to be >1. Is it the sum over the edges? But at a total degree of around 40, this would imply an average STTC almost three times higher than what's reported in Fig 1i. Also, why is the degree around 40, but between 1000 and 1500 in Fig S2? <br /> Finally, it should be mentioned that "degree average" seems (from the boxplot) to work equally well.

Further, the conclusion of the "matching" algorithm equally fitting both cases would be stronger if we were informed about the wiring parameters (η and γ) resulting in both cases. That way we could understand: Is it the same algorithm fitting both cases or very different variants of the same? It is especially crucial here, because the η and γ parameters determine the interplay between the distance- and topology-dependent terms, and this is the one case where a very different set of pairwise distances (due to higher density) are tested. Does it really generalize to these new conditions?

Conversely, the results relating to GABAa blocking show a case where the distances are comparable, but the topology of functional connectivity is very different. (Here again, the contrast between structural and functional connectivity could be made a bit clearer. How is correlational detection of connections affected by "bursty" activity?) The reduction in tentative inhibition following the application of the block is convincing.

The main finding is that despite of very different connectivities, the "matching" algorithm still holds best. This is adequately supported by applying the previous analyses to this case as well. <br /> The authors then interpret the differences between blocked and control by inspection of the η and γ parameters, finding that the relative impact of the distance-based term is likely reduced, as a lower (less negative) exponent would lead to more equal values for different distances. This is a good example of inspecting the internals of a generative algorithm to understand the modeled system and is confirmed by longer edge lengths in Supp Fig. S12C.

The authors further inspect the wiring probabilities used internally at each step of the algorithm and compare across conditions. They conclude from differences in the distribution of P_ij values that the GABAa-blocked network had a "more random" topology with "less specific" wiring. This is the opposite of the conclusion I would draw, given the depicted data. This may be partially because the authors do not clearly define their concept of "random" vs. "specific". I understand it to be the following: At each time step, one unconnected pair is randomly picked and connected, with probabilities proportional to P_ij, as in Akarca et al., 2021; "randomness" then refers to the entropy of that process. In that case, the "most random" or highest entropy case is given by uniform P_ij values, which would be depicted as a delta peak at 1 / n_pairs in the present plot. A flatter distribution would indicate more randomness if it was the distribution of P_ij over pairs of neurons (x-axis: pairs; y-axis P_ij). The conclusion should be clarified by the use of a mathematical definition and supported by data using that definition.

Next, the methods are repeated for various cultures of human neurons. I have no specific observations there.

In summary, while I think the most important methods are sound, and the main conclusions (reflected in the title of the paper) are supported, the analysis of more specific cases (everything from Fig 3e onwards, except for Fig 5) requires more work as in the current state their conclusions are not adequately supported.

Reviewer #1 (Public Review):

This work deals with courtship behaviour in mice. Authors try to identify the acoustic features that influence the attractivity level of male courtship songs to females. Courtship songs are made of sequences of short ultrasound syllables emitted at a rate of 7-10Hz. Authors manipulated these syllables by changing either the spectrotemporal content of each syllable or the intersyllable intervals. The authors found that it was only when sequences of syllables were irregular (with highly variable intersyllable intervals) that the female was less attracted to the song. The data, therefore, brings evidence that the acoustic features of syllables account less than the song's temporal regularity for the attractivity of courtship songs. The authors suggest that temporal regularity of syllable emission, building on breathing patterns, could reflect male fitness. They also suggest that temporal regularity could be an acoustic cue compressing the complex acoustic information carried by songs.

Strengths:

The study is well-written, very straightforward, and easy to follow. Behavioral tasks are well-designed and many tests, on a large enough set of animals have been done to support the conclusions. Results are clearly presented and provide enough details to see individual points. The discussion makes interesting connections between syllable rhythms and animals' fitness or brain rhythms.

Weaknesses:

Although the study is easy to understand and provides interesting results, the data analysis remains incomplete, and the interpretation of results is not cautious enough.

For instance, Fig. 2 shows a preference for song playback but we cannot determine if it is a general preference for a sound or a specific preference for male songs because only the difference between the presence of song or silence is tested. I acknowledge that the authors did not overstate their results, but the experimental design is incomplete and hard to interpret in that respect. For instance, the expression "preferential approach to song" is ambiguous.

There is no analysis of individual preference across tests and we might have the feeling that the effect shown mostly depends on the preference of only a few animals. Indeed, it seems that roughly one-third of animals showed a strong preference for the intact song while another third showed a strong preference for the modified song, whatever the modification. A few animals are therefore "swing voters". It would have been interesting, if not pertinent, to have a deeper analysis of the behavior of these later animals. Do they choose less (i.e. spend less time close to speakers) or do they swing from one corner to another? What about the animals which always chose the modified song? Are these animals that already showed a weak or strong preference for silence, therefore showing they were not comfortable with the songs played? There is no discussion of these aspects either.

Also, on page 11, it is written "female listeners perceptually compress the high sensory dimensionality of male songs by selectively monitoring a reduced subset of meaningful acoustic features in isolation." This statement or hypothesis is questionable. After all, if someone would change the inter-syllable intervals in human speech, that would become cryptic or at least annoying for the listener. Humans would definitely prefer normal speech. Is this because we compress acoustic features? Not really. It is likely that this modified speech just differs too much from the set of parameters typically encountered and therefore understood/interpreted while learning a language in childhood. Thus, the hypothesis here is rather to determine, for a given acoustic feature, if there is a range within which the perception of the message carried by the song (courtship) is maintained. Interpretation of "compressed acoustic features" with regards to animals' preference seems an overinterpretation. Same remark at the end of the conclusion.

Reviewer #1 (Public Review):

Tippett et al present whole cell and proteoliposome transport data showing unequivocally that purified recombinant SLC26A6 reconstituted in proteoliposomes mediates electroneutral chloride/bicarbonate exchange, as well as coupled chloride/oxalate exchange unassociated with detectable current. Both functions contrast with the uncoupled chloride conductance mediated by SLC26A9. The authors also present a novel cryo-EM structure of full-length human SLC26A6 chloride/anion exchanger. As part of the structure, they offer the first partial view of the STAS domain previously predicted to be unstructured. They further define a single Arg residue of the SLC26A6 transmembrane domain required for coupled exchange, mutation of which yields apparently uncoupled electrogenic chloride transport mechanistically resembling that of SLC26A9, although of lower magnitude. The authors further apply to proteoliposomes for the first time a still novel approach to the measurement of bicarbonate transport using a bicarbonate-selective Europium fluorophor. The evidence strongly supports the authors' claims and conclusions, with one exception.

The manuscript has numerous strengths.

As a structural biology contribution, the authors extend the range of SLC26 structures to SLC26A6, comparing it in considerable detail to the published SLC26A9 structure, and presenting for the first time the structure of a portion of the STAS IVS domain of SLC26A6 long considered unstructured.

The authors also apply a remarkably extensive range of creative technical approaches to assess the functional mechanisms of anion transport by SLC26A6, among them the first application of the novel, specific bicarbonate sensor Eu-L1+ to directly assess bicarbonate transport in reconstituted proteoliposomes. The authors also present the first (to this reviewer's knowledge) functional proteoliposome reconstitution of chloride-bicarbonate exchange mediated by an SLC26 protein. They define a residue in surrounding the anion binding pocket which explains part of the difference in anion exchange coupling between SLC26A6 and SLC26A9. In the setting of past conflicting results, the current work also contributes to the weight of previous evidence demonstrating that SLC26A6 mediates electroneutral rather than electrogenic Cl-/HCO3- exchange.

Each of these achievements constitutes a significant advance in our understanding.

The paper has only a few weaknesses. One is an incomplete explanation of the mechanistic determinants of anion exchange coupling in SLC26A6 vs. uncoupled anion transport by SLC26A9. A second minor weakness is the inconsistently repeated conclusion that SLC26A6 mediates strictly coupled chloride/oxalate exchange. The data presented do not measure the stoichiometry of Cl-/oxalate exchange. The AMCA proteoliposome assay documented extracellular oxalate-dependent proteoliposomal anion transport that was most simply interpreted as coupled exchange, whereas no stoichiometric coupled exchange was documented in the AMCA experiments as presented.

Overall, the manuscript represents an important advance in our understanding of the SLC26 protein family and of coupled vs uncoupled carrier-mediated anion transport.

Reviewer #1 (Public Review):

In this study the authors first perform global knockout of the gene coding for the polarity protein Crumbs 3 (CRB3) in the mouse and show that this leads to perinatal lethality and anopthalmia. Next, they create a conditional knockout mouse specifically lacking CRB3 in mammary gland epithelial cells and show that this leads to ductal epithelial hyperplasia, impaired branching morphogenesis and tumorigenesis. To study the mechanism by which CRB3 affects mammary epithelial development and morphogenesis, the authors turn to MCF10A cells and find that CRB3 shRNA-mediated knockdown in these cells impairs their ability to form properly polarized acini in 3D cultures. Furthermore, they find that MCF10A cells lacking CRB3 display reduced primary ciliation frequency compared to control cells, which is in agreement with previous studies implicating CRB3 in primary cilia biogenesis. Using a combination of biochemical, molecular- and imaging approaches the authors then provid evidence indicating that CRB3 promotes ciliogenesis by mediating Rab11-dependent recruitment of gamma tubulin ring complex component GCP6 to the centrosome/ciliary base, and they also show that CRB3 itself is localized to the base of primary cilia. Finally, to assess the functional consequences of CRB3 loss on ciliary signaling function, the authors analyze the effect of CRB3 loss on Hedgehog and Wnt signaling using cell-based assays or a mouse model.

Overall, the described findings are interesting and in agreement with previous studies showing an involvement of CRB3 in epithelial cell biology, tumorigenesis and ciliogenesis. The results showing a role for CRB3 in mammary epithelial development and morphogenesis in vivo seem convincing. However, a major weakness of this study is that quantitative analysis of several key results is either lacking, not done appropriately, or is incompletely described. In addition, some of the cell-based experiments are lacking appropriate controls, and the claim that CRB3 directly binds to Rab11 is not supported by the data provided.

Reviewer #1 (Public Review):

In "Striatal ensemble activity in an innate behavior", Minkowicz et al. strive to characterize how the striatum, the primary input nucleus of the basal ganglia, represents grooming. Here, grooming is used as a paradigmatic habitual behavior. The pose dynamics of grooming are stereotyped: mice perform it spontaneously and prior work has shown that it is both represented and controlled by the striatum.

The manuscript presents a valuable contribution to the field by shedding light on how ensembles of neurons encode this innate behavior. Additionally, the use of supervised machine learning allowed the authors to collect and precisely align a large number of grooming repetitions, which enabled most of their downstream analysis.

I found the paper to be well-written and the conclusions are mostly well-supported. However, some of the data analysis was a bit opaque, and some more detail and reanalysis could substantially strengthen the authors' claims.

1) The authors identified grooming bouts using empirically defined thresholds and manual tweaking. Next, the boundaries of grooming were used for trial alignment and linear time warping. This is a completely sensible approach; however, in using only the boundaries of grooming episodes, the dynamics of grooming bouts are ignored. I am particularly concerned that pose dynamics of grooming bouts are most stereotyped at the boundaries (e.g. they always begin and end with specific paw movements). To play devil's advocate, if the striatum encodes pose dynamics and not boundaries and pose dynamics are noisy between the beginning and end of these bouts (either due to the dynamics of the behavior or how it was identified), then a "boundary-like" representation may emerge in the average. I strongly recommend re-running a subset of the analysis after accounting for variability in grooming dynamics. A simple thing to try would be to further cluster grooming bouts using 3D keypoint trajectories. Another would be to warp grooming bouts in a manner that accounts for keypoint trajectories (e.g. DTW or other recent time-warping variants).

2) The authors should consider if the correlation to grooming is due to (at least in part) a correlation with another aspect of movement, e.g. overall velocity, acceleration, height, or angular velocity. This should be straightforward to analyze with the current dataset. To start, I would simply take the velocity and acceleration of the mouse's centroid (head and body could be considered separately). Next, look at the correlation with DLS spiking. If a clear relationship emerges, then check to see how velocity (or another variable) maps onto grooming. It may be that DLS neurons appear to encode the boundaries of grooming when they (at least partially) encode other variables.

3) The ensemble analysis is potentially critical to our understanding of SPNs. Figure 4A suggests that ensembles encode grooming with a probabilistic code - ensembles appear to be engaged for a small number of grooming bouts in the session. First, a basic question is what is the probability a given ensemble is activated during grooming? Second, the more complex question is whether there is an explanation for why one ensemble is engaged for some trials and not others? Related to point 2, I wonder if another aspect of behavior - e.g. vigor, duration, or speed - determines this. I suggest some analysis to at least rule out some simple explanations.

Reviewer #1 (Public Review):

In this manuscript by Douglas et al, the investigative team seeks to identify Staphylococcus aureus genes (and associated polymorphisms) that confer altered susceptibility to human serum, with the hypothesis that such genes might contribute to the propensity of a strain to cause bacteremia, invasive disease, and/or death. Using an innovative GWAS-like approach applied to a bank of over 300 well-characterized clinical S. aureus isolates, the authors discover SNPs in seven different staphylococcal genes that confer increased survival in the setting of serum exposure. The authors then mainly focus on one gene, tcaA, and illustrate a potential mechanism whereby modification of peptidoglycan structure and WTA display leads to altered susceptibility to serum, serum-derived antimicrobial compounds, and antibiotics. One particularly significant finding is that the identified tcaA SNP is significantly associated with patient mortality, in that patients infected with the SNP bearing isolate are less likely to die from infection. It is therefore hypothesized that this SNP represents an adaptive mutation that promotes serum survival while decreasing virulence and host mortality. In a murine model of infection, the strain bearing the WT allele of tcaA is significantly more virulent than the tcaA mutant, suggesting that the role of tcaA in bacteremia is infection-phase dependent.

This manuscript has many strengths. The triangulation of genomic analysis, patient outcomes data, and in vitro and in vivo mechanistic testing adds to the significance of the findings in terms of human disease. Testing the impact of mutating tcaA in multiple staphylococcal lineages and backgrounds also increases the rigor of the study. The identification of bacterial loci that impact susceptibility to both host antimicrobial compounds and commonly used antibiotics is also a strength of this work, given the evolutionary and treatment implications for such genes.

One moderate weakness is that the impact of the identified SNP in tcaA is only tested in some of the assays, whereas the majority of the testing is performed with a whole gene knockout. Additionally, for some experiments, rigor is lacking in that statistical measures are not deployed to support the conclusions of biologically meaningful changes based on data with very modest differences between groups. In some cases this results in more speculative conclusions that will require further testing to validate. Finally, there are instances of inter-experiment variability that require further explanation. All in all, this is an exciting manuscript that will be of interest to the broader research communities focused on staphylococcal pathogenesis, bacterial evolution, and host-pathogen interactions, as well as to clinicians who care for patients with invasive staphylococcal infection.

Reviewer #1 (Public Review):

The manuscript by Hussein et al. uses cryoEM structure, microscale thermophoresis (MST), and molecular dynamics simulations (conventional and CpHMD) to unravel the Zn2+ and proton role in the function of the Cation Diffusion Facilitator YiiP. First, they generate mutants that abolish each of the three Zn2+ models to study the role of each of them separately, both structurally and functionally. Next, they used a Monte Carlo approach refining the CpHMD data with the MST points to establish the Zn2+ or proton binding state depending on the pH. That predicted a stoichiometry of one Zn2+ to 2 or 3 protons (1:3 under lower pH values). Finally, they proposed a mechanism that involves first the binding of Zn2+ to one low-affinity site and then, after the Zn2+ migrates to the highest affinity site in the transmembrane portion of the protein. The lack of Zn2+ in the low-affinity site might induce occlusion of the transporter.

The manuscript is well-written it is of interest to the field of Cation Facilitator Transporters. It is also an excellent example of a combination of different techniques to obtain relevant information on the mechanism of action of a transporter.

I have only a few comments that might need clarification from the authors:

- If the unbinding of Zn2+ to site B triggers the occlusion (and maybe the OF state) and the external pH does not affect that binding, how is it prevented from being always bound to Zn2+ and thus occluded also while it should be transporting protons (B to C panels in Figure 5)? Are there some other factors that I am missing?<br /> - I am not an expert on experiments, but the results for mutants that abolish site C are difficult to understand. For D287A/H263A, the SEC columns data suggest a population of higher oligomers. Still, for the D70A/D287A/H263A and D51A/D287A/H263A, they showed a native dimer. I understand your suggestion that the Fab induces the domain swap, but how do you explain the double mutant SEC column result? Please elaborate.<br /> - Since in the D287A mutant, you are disrupting the preferred tetrahedral coordination of Zn2+, but it still binds, do you observe any waters that compensate for the missing aspartate? Maybe in the MD simulations?

Reviewer #1 (Public Review):

Tomasi et al. performed a combination of bioinformatic, next-generation tRNA sequencing experiments to predict the set of tRNA modifications and their corresponding genes in the tRNAs of the pathogenic bacteria Mycobacterium tuberculosis. Long known to be important for translation accuracy and efficiency, tRNA modifications are now emerging as having regulatory roles. However, the basic knowledge of the position and nature of the modifications present in a given organism is very sparse beyond a handful of model organisms. Studies that can generate the tRNA modification maps in different organisms along the tree of life are good starting points for further studies. The focus here on a major human pathogen that is studied by a large community raises the general interest of the study. Finally, deletion of the gene mnmA responsible for the insertion of s2U at position 34 revealed defects in in growth in macrophage but in test tubes suggesting regulatory roles that will warrant further studies. The conclusions of the paper are mostly supported by the data but the partial nature of the bioinformatic analysis and absence of Mass-Spectrometry data make it incomplete. The authors do not take advantage of the Mass spec data that is published for Mycobacterium bovis (PMID: 27834374) to discuss what they find.

Important points to be considered:

1) The authors say they took a list of proteins involved in tRNA modifications from Modomics and added manually a few but we do not know the exact set of proteins that were used to search the M. mycobacterium genome.

2) The absence of mnmGE genes in TB suggested that the xcm5U derivatives are absent. These are present in M. bovis (PMID: 27834374). Are the MnmEG gene found in M. bovis? If yes, then the authors should perform a phylogenetic distribution analysis in the Mycobacterial clade to see when they disappeared. If they are not present in M. bovis then maybe a non-orthologous set of enzymes do the same reaction and then the authors really do not know what modification is present or not at U34 without LC-MS. The exact same argument can be given for the xmo5U derivatives that are also found in M.bovis but not predicted by the authors in M. tuberculosis.

3) Why is the Psi32 predicted by the authors because of the presence of the Rv3300c/Psu9 gene not detected by CMC-treated tRNA seq while the other Psi residues are? Members of this family can modify both rRNA and tRNA. So the presence of the gene does not guarantee the presence of the modification in tRNAs

4) What are tsaBED not essential but tsaC (called sua5 by the authors) essential?

Reviewer #1 (Public Review):

Muller glia function as retinal stem cells in the adult zebrafish retina. Following retinal injury, Muller glia are reprogramned (reactive Muller glia), and then divide to produce a progenitor that amplifies and differentiates into retinal neurons. Previous scRNAseq analysis used total retinal RNA from uninjured and injured retinas isolated at time points when Muller glia are quiescent, being reprogrammed, and proliferating to reveal genes and gene regulatory networks underlying these events (Hoang et al., 2020). The manuscript by Celotto et al., used double transgenic zebrafish that allow them to purify by FACS quiescent and reactive Muller glia, Muller glia-derived progenitors, and their differentiating progeny at different times post retinal damage. RNA from these cell populations was used in scRNAseq studies to identify the transcriptomes associated with these cell populations. Importantly, they report two quiescent and two reactive Muller glia populations. These results raise the interesting possibility that Muller glia are a heterogenous population whose members may exhibit different regenerative responses to retinal injury. However, without further experimentation, the validity and significance of this result remain unclear. In addition to putative Muller cell heterogeneity, Celotto et al., identified multiple progenitor classes, some of which are specified to regenerate specific retinal neuron types. Because of its focus on Muller glia and Muller glia-derived progenitors at mid to late stages of retina regeneration, this new scRNAseq data will be a useful resource to the research community for further interrogation of gene expression changes underlying retina regeneration.

Major concerns:

1) The identification of multiple populations of Muller glia, reactive Muller glia, and progenitors is interesting, but beyond a few in situ hybridization studies to validate injury-dependent gene inductions, there are no experiments that confirm that multiple cell populations exist in vivo, and no experiments examining the significance of these different populations in the regenerative process. It would be helpful to discuss how the peripheral to the central gradient of Muller cell maturation influences the scRNAseq-based cell clustering results.

2) While the reliance on transient GFP and mCherry expression may be sufficient, the final population used for the scRNAseq analysis is only partial in nature. Permanently marking the MG through a Cre-Lox system is more ideal. The authors mention the possibility of missing highly proliferative populations of MG/RPC through the dilution of fluorescent proteins; a transgenic system that allows for true lineage tracing may then capture more appropriate MG/RPC populations. The lack of gating for a pure GFP population also confounds this problem which the authors do mention in the discussions; this oversight was not explained.

3) Much time was taken to identify each cell cluster and to list the differentially expressed genes, but no functional significance for these genes was probed. While a lot of work has gone into the analysis shown, altering some of the MG/RPC trajectories through differentially expressed genes would go a long way to making this study more impactful.

4) The data presented in this paper has significant overlap with scRNAseq data presented by Hoang et al., 2020 in Science where Muller glia, reactive Muller glia, and Muller glia-derived progenitors were carefully analyzed. How does their data fit with the data presented here? The authors could have used that paper as a jumping-off point and offered more time points for comparison, especially as progenitors differentiate.

5) A major conclusion of the paper is that neurogenic progenitors in the injured retina differentiate into neurons with a similar order as that taking place during development. This analysis is based on two time points, and while the trends stay true to the authors' model, two time points are too few to make such a conclusion. In addition, because of the time points chosen for this analysis, many mature neuronal markers are lacking. Including additional time points so mature neuronal markers are detected in the dataset would enhance the trajectory proposed.

Reviewer #1 (Public Review):

Ciampa et al. investigated the role of the hypoxia-inducible factor 1 (HIF-1) pathway in placental aging. They performed transcriptomic analysis of prior data of placental gene expression over serial timepoints throughout gestation in a mouse model and identified increased expression of senescence and HIF-1 pathways and decreased expression of cell cycle and mitochondrial transcripts with advancing gestational age. These findings were confirmed by RT-PCR, Western blot, and mitochondrial assessment from mouse placental tissues from late gestation time points. Studies of human placental samples at similar late gestational ages showed similar trends in increased HIF-1 targets and decreased mitochondrial abundance with increasing gestation, but were not significantly significant due to the limited availability of uncomplicated preterm placenta samples. The authors demonstrated that stabilization of HIF-1 in vitro using primary trophoblasts and choriocarcinoma cell lines recapitulated the gene and mitochondrial dysfunction seen in the placental tissues and were consistent with senescence. Interestingly, cell-conditioned media from HIF-1 stabilized placenta cell lines induced myometrial cell contractions in vitro and correspondingly, induction of HIF-1 in pregnant mice was associated with preterm labor in vivo. These data support the role of the HIF-1 pathway in the process of placental senescence with increasing gestational age and highlight this pathway as a potentially important contributor to gestational length and a potential target for therapeutics to reduce preterm birth.

Overall, the conclusions of this study are mostly well supported by the data. The concept of placental aging has been controversial, with several prior studies with conflicting viewpoints on whether placental aging occurs at all, is a normal process during gestation, or rather only a pathologic phenomenon in abnormal pregnancies. This has been rather difficult to study given the difficulty of obtaining serial placental samples in late gestation. The authors used both a mouse model of serial placental sampling and human placental samples obtained at preterm, but non-pathologic deliveries, which is an impressive accomplishment as it provides insight into a previously poorly understood timepoint of pregnancy. The data clearly demonstrate changes in the HIF-1 pathway and cellular senescence at increasing gestational ages in the third trimester, which is consistent with the process of aging in other tissues.

Weaknesses of this study are that although the authors attribute alterations in HIF-1 pathways in advanced gestation to hypoxia, there are no experiments directly assessing whether the changes in HIF-1 pathways are due to hypoxia in either in vitro or in vivo experiments. HIF-1 has both oxygen-dependent and oxygen-independent regulation, so it is unclear which pathways contribute to placental HIF-1 activity during late gestation, especially since the third-trimester placenta is exposed to significantly higher oxygen levels compared to the early pregnancy environment. Additionally, the placenta is in close proximity to the maternal decidua, which consists of immune and stromal cells, which are also significantly affected by HIF-1. Although the in vitro experimental data in this study demonstrate that HIF-1 induction leads to a placenta senescence phenotype, it is unclear whether the in vivo treatment with HIF-1 induction acts directly on the placenta or rather on uterine myometrium or decidua, which could also contribute to the initiation of preterm labor.

Reviewer #1 (Public Review):

Summary

Favate et al. measure the relative levels of metabolites in 12 Escherichia coli strains isolated from different replicate populations after 50,000 generations of the Lenski long-term laboratory evolution experiment. They use untargeted LC/MS methods that include standards and report both positive and negative ionization mode measurements. They initially use principal component analysis (PCA) to broadly compare how the metabolomes of these strains are similar and different. Then, they describe several instances where the changes in metabolite abundance they see in specific pathways correlate with mutations that lead to changes in the expression of genes that encode enzymes in those pathways.

Strengths

The statistical analyses and presentation of the high-throughput data are excellent. The most compelling results are communicated in wonderful figures that integrate their measurements of metabolite levels in this study with results from a prior study they conducted looking at changes in gene expression levels in the same bacterial strains. These sections include the ones describing large increases in NAD(P) pools due to mutations in nadR, changes in the levels of arginine and related compounds due to mutations in argR, and changes in metabolites from glycolysis and the TCA cycle related to iclR and arcB.

Weaknesses

Showing that A-2 and especially A-3 are outliers in the PCA analysis is useful, but it may be hiding other interesting signals in the data. The other strains are remarkably colinear on these plots, hinting that if the outliers were removed, one main component would emerge along which they are situated. It also seems possible that this additional analysis step would allow the second dimension to better differentiate them in a way that is interesting with respect to their mutator status or mutations in key metabolic or regulatory genes.

There is a missed opportunity to connect some key results to what is known about LTEE mutations that reduce the activity of pykF (pyruvate kinase I). This gene is mutated in all 12 LTEE populations, and often these mutations are frameshifts or transposon insertions that should completely knock out its activity. At first glance, inactivating an enzyme for a step in glycolysis does not make sense when the nutrient source in the growth medium is glucose, even though PykF is only one of two isozymes E. coli encodes for this reaction. There has been speculation that inactivating pykF increases the concentration of phosphoenolpyruvate (PEP) in cells and that this can lead to increased rates of glucose import because PEP is used by the phosphotransferase system of E. coli to import glucose (see https://doi.org/10.1002/bies.20629). The current study has confirmed the higher PEP levels, which is consistent with this model.

In the introduction, the papers cited to show the importance of changes in metabolism for adaptation do not seem to fit the focus of this study very well. They stress production of toxins and secondary metabolites, which do not seem to be mechanisms that are at work in the LTEE. I can think of two areas of background that would be more relevant: (1) studies of how bacterial metabolism evolves in adaptive laboratory evolution (ALE) experiments to optimize metabolic fluxes toward biomass production (for example, https://doi.org/10.1038/nature01149 ), and (2) discussions of how cross-feeding, metabolic niche specialization, and metabolic interdependence evolve in microbial communities, including in other evolution experiments (for example, https://doi.org/10.1073/pnas.0708504105 and https://doi.org/10.1128/mBio.00036-12).

Impact and Significance

While there has been past speculation about the effects of LTEE mutations on metabolism, this study measures changes in the levels of metabolites in related metabolic pathways for the first time. Therefore, it provides useful information about how metabolism evolves, in general, and will also be a useful resource for those studying other aspects of the LTEE related to metabolism, such as contingency in the evolution of citrate utilization.

Reviewer #1 (Public Review):

The study examines how hemocytes control whole-body responses to oxidative stress. Using single cell sequencing they identify several transcriptionally distinct populations of hemocytes, including one subset that show altered immune and stress gene expression. They also find that knockdown of DNA Damage Response (DDR) genes in hemocytes increases expression of the immune cytokine, upd3, and that both upd3 overexpression in hemocytes and hemocyte knockdown of DDR genes leads to increased lethality upon oxidative stress.

Strengths

1, The single cell analyses provide a clear description of how oxidative stress can cause distinct transcriptional changes in different populations of hemocytes. These results add to the emerging them in the field that there functionally different subpopulations of hemocytes that can control organismal responses to stress.<br /> 2, The discovery that DDR genes are required upon oxidative stress to limit cytokine production and lethality provides interesting new insight into the DDR may play non-canonical roles in controlling organismal responses to stress.

Weaknesses

1, In some ways the authors interpretation of the data - as indicated, for example, in the title, summary and model figure - don't quite match their data. From the title and model figure, it seems that the authors suggest that the DDR pathway induces JNK and Upd3 and that the upd3 leads to tissue wasting. However, the data suggest that the DDR actually limits upd3 production and susceptibility to death as suggested by several results:<br /> a) PQ normally doesn't induce upd3 but does lead to glycogen and TAG loss, suggesting that upd3 isn't connected to the PQ-induced wasting.<br /> b) knockdown of DDR upregulates upd3 and leads to increased PQ-induced death. This would suggest that activation of DDR is normally required to limit, rather than serve as the trigger for upd3 production and death.<br /> c) hemocyte knockdown of either JNK activity or upd3 doesn't affect PQ-induced death, suggesting that they don't contribute to oxidative stress-induced death. Its only when DDR is impaired (with DDR gene knockdown) that an increase in upd3 is seen (although no experiments addressed whether JNK was activated or involved in this induction of upd3), suggesting that DDR activation prevents upd3 induction upon oxidative stress.

2, The connections between DDR, JNK and upd3 aren't fully developed. The experiments show that susceptibility to oxidative stress-induced death can be caused by a) knockdown of DDR genes, b) genetic overexpression of upd3, c) genetic activation of JNK. But whether these effects are all related and reflect a linear pathway requires a little more work. For example, one prediction of the proposed model is that the increased susceptibility to oxidative stress-induced death in the hemocyte DDR gene knockdowns would be suppressed (perhaps partially) by simultaneous knockdown of upd3 and/or JNK. These types of epistasis experiments would strengthen the model and the paper.

3, The (potential) connections between DDR/JNK/UPD3 and the oxidative stress effects on depletion of nutrient (lipids and glycogen) stores was also not fully developed. However, it may be the case that, in this paper, the authors just want to speculate that the effects of hemocyte DDR/upd3 manipulation on viability upon oxidative stress involve changes in nutrient stores.

Reviewer #1 (Public Review):

In this study, Muronova et al., demonstrate the physiological importance of a centriole and microtubule-associated protein, CCDC146, in sperm flagellar formation and male reproduction. In a previous study, the authors identified two loss-of-function mutations in CCDC146 from the sterile males with multiple morphological abnormalities in flagellar (MMAF) phenotype. To further test physiological significance of the CCDC146, the authors generate its knockout mouse model. The knockout males share the MMAF phenotypes with severely impaired flagellar morphology due to the defective sperm generation in testes. Using CCDC146 knock-in mouse model and expansion microscopy techniques, the authors observed CCDC146 localizes at human and mouse sperm flagella, which is different from the somatic cells. The authors also observed impaired manchette and head-tail coupling apparatus in developing spermatid lacking CCDC146 and address CCDC146 loss-of-function induces molecular and structural defects at axoneme in developing male germ cells, which finally causes MMAF phenotype and male infertility.

This reviewer agrees that identifying and analyzing new pathogenic molecules and variants is hugely valuable to establish male infertility in genetic level. As the authors have done, this study also enlarges the genetic causality underlying MMAF and male infertility. In addition, this study applies new techniques, expansion microscopy, which is also an innovative approach. Although many approaches are used, unfortunately, this study misses the molecular mechanisms to explain pathogenicity to cause MMAF by the CCDC146. Only intracellular localization of the molecule is heavily examined. Although the authors show defective intracellular localization of the centriole and manchette, how CCDC146 loss-of-function and the developmental defects are linked is not examined. These limits provide the impression that this study could be simply another identification of the MMAF-causing gene, which were heavily performed by the authors. Also, in many parts, the results do not clearly support the authors claim. Therefore, this reviewer thinks the current manuscript requires additional results to clearly explain molecular mechanisms underlying the pathogenicity by CCDC146 loss-of-function.

Reviewer #1 (Public Review):

This research article by Watabe T and colleagues characterizes PKA waves triggered by prostaglandin E2 (PGE2). What the author discovered is that waves of PKA occur both in vitro, in MDCK epithelial monolayers, and in vivo, in the ear epidermis in mice. The PKA waves are the consequence PGE2 discharge, that in turn is triggered by Calcium bursts. Calcium level and ERK activity intensity control that mechanism by acting at different levels.

This article is a technological tour de force using different biosensors and optogenetic actuators. What makes this article interesting is the combination of these tools together to dissect a complex, highly dynamic signaling pathway at the single-cell level. For this reason, this paper represents the essence of modern cell biology and paves the way for the cell biology of the future. However, we think that the paper in this stage is still partly descriptive in its nature, and more measurements are needed to increase the strength of the mechanistic insights. Also, the work is not conclusive, some results are over-interpreted, and more work has to be done if the authors want to support all their claims.

Reviewer #1 (Public Review):

The manuscript by Huang et al. examines the potential "self-policing" of Bacillus cells within a biofilm. The authors first discover the co-regulation of lethal extracellular toxins (BAs) and the self-immunity mechanisms; the global regulator spoA controls both. The authors further show that a subpopulation of cells co-express these genes and speculate that these cells engage in preferential cooperation for biofilm formation (over cells that produce neither). Based on previous literature, the authors then evaluate the relative fitness of the wild-type strain compared to mutants locked into either constantly exporting the toxins or permanently immune to these poisons. The wild-type exhibited increased fitness (compared to the mutants) for the tested biofilm conditions. The manuscript raises interesting ideas and provides a potential model to probe questions of cooperatively in Bacillus biofilms.

Strengths:<br /> - The authors use fluorescence-producing reporter strains to discern the spatial expression patterns within biofilms. This real-time imaging provides striking confirmation of their conclusions about shared co-regulation.<br /> - The authors also nicely deploy genetic constructs in microbiological assays to show how toxin production and immunity can influence biofilm phenotypes, including resilience to stress.

Concerns:<br /> - My biggest concern is that the claim of policing on a single-cell level needs more quantitive microscopy, particularly of the xylose-induced strain. The data support a more tempered consideration of self-policing via BAs and self-resistance in this Bacillus species. It seems sufficient that this manuscript opens the door for a novel and readily examinable system for examining potential cooperation and its molecular controls (without making broader claims).<br /> - The discussion is more speculative than the presented data warrants. For example, the speculation in lines 289 - 310 is not anchored in the results. It is hard for this reviewer to imagine how one would use the genetic framework and tools developed in this manuscript to address the ideas proposed in lines 289 - 310.<br /> - Some conclusions (in the results section) are more decisive than the data supports. For example, the microscopy of the PI staining (as presented in Figure 2 and the supplemental movies) does not prove that only non-expressing cells die. Yet the conclusion in line 143 states that "ECM and BAs producers selectively punish the nonproducing siblings." Also, the presented data shows many non-labeled cells without PI; why do some nearby non-gfp-expressing cells remain alive?

Reviewer #1 (Public Review):

Zacharopoulos et al. present a multi-modal investigation into the developmental trajectories of cognitive processing, decision-making processing, and visuomotor processing in children and young adults, and attempt to relate them to neuroimaging measures of functional brain connectivity and neurotransmitter concentrations in two distinct brain regions.

Results suggest specific interactions between neurotransmitter concentrations and visuomotor task performance. Interestingly, GABA and Glu levels appear to have different relationships with task performance if the participant group is trichotomized into older, 'mean-age', and younger participants. These findings appear consistent across three different visuomotor processing tasks and replicate well between two time points at which task performance and MRS measures were established for each participant (1.5 years apart). Visuomotor connectivity (assessed with resting-state-fMRI) also showed age-group-specific relationships with neurotransmitter levels. Finally, the authors present evidence that visuomotor processing mediates the relationship between neurochemical levels and scores of fluid intelligence, but only for older participants.

STRENGTHS

The study has an astonishing sample size in the context of MRS research, a field that has historically struggled to aggregate large datasets because of a severe lack of methodological standardization. Longitudinal MRS data from close to 300 participants means that this is one of the largest MRS datasets to date, enabling the group to add another exciting piece of work to their six previously published manuscripts on relationships between cognitive performance and neurochemical measures from this powerful resource. MRS data quality appears excellent, owed to state-of-the-art acquisition and raw data processing. The authors are further to be commended for making the raw MRS data publicly available - they will serve as a fantastic resource for method developers and applied researchers in the field.

WEAKNESSES

There is generally little to no consideration or discussion concerning age trajectories of MRS-derived metabolite estimates during childhood and early adulthood, which are not clearly established at all. There is evidence for increasing GABA+macromolecules during childhood (Porges et al, eLife 2021, https://elifesciences.org/articles/62575), although it may be ascribed to macromolecules rather than GABA itself (Bell et al, Sci Rep 2021, https://pubmed.ncbi.nlm.nih.gov/33436899/). The findings should at least be discussed in the context of this literature, but I suggest going a step further. The authors have all the data to make a major contribution to the scarce body of evidence on metabolite changes between 6 and 18 years by examining whether GABA and Glu estimates actually appear to change systematically across the age range of their dataset (especially exciting since they have longitudinal data)! It would be immensely valuable to see an analysis like this.

With that said, a methodological weakness concerns the computation of neurochemical concentrations presented here. Firstly, the authors can provide more detail about the acquisition and data processing/modeling decisions. Secondly, and more importantly, MRS-derived estimates of concentration can never be absolute, and always require several assumptions about the relative contributions of tissue classes (GM, WM, CSF) to the measurement volume, tissue water content, water and metabolite MR relaxation times, MR visibility, etc. Quantitative MRS estimates therefore need to be interpreted with caution, especially when these confounding factors are likely to vary between observed groups, or with age, pathology, etc. - there is plenty of reason to assume that cortical maturation, iron accumulation, etc. contribute to changes in relative GM/WM/CSF fractions or relaxation time changes. The authors present two different correction methods to account for some of these aspects, but only present the results of one, stating that "The results showed the same general pattern across all quantification methods.", which is insufficient to assess what changed and what didn't. Interestingly, the authors have presented no less than *four* different quantification methods in a similar manuscript using the same dataset (Zacharopoulos et al, Human Brain Mapp 2021; https://onlinelibrary.wiley.com/doi/10.1002/hbm.25396), but they do not mention normalization to the internal creatine signal in this present work, or whether it yielded different results (which might indicate that their method of tissue correction introduces a confounder rather than correcting for it). There is no mention of whether any further analysis of the water T2 relaxation time estimates was performed, but it would be vital to understand whether they themselves change with age, since this would establish that they are likely to confound GABA and Glu estimation. Generally, the choice to perform additional subject-specific acquisitions to allow corrections for water T2 relaxation is understandable, but not clearly motivated or explained in the experimental section. The authors should further clarify whether the relative tissue volume fractions of GM, WM, and CSF are stable across the age range, or whether there is a systematic tissue composition change with age that may also confound the Glu and GABA estimation.

Finally, I am surprised to find no discussion of limitations at all. It is important to point out the methodological limitations of MRS, which are widely discussed in the MRS literature, but probably less obvious to those readers less intimately familiar with it. This concerns not only the confounding factors for quantification that I described above but also the challenges of the comparably low spectral resolution at 3 Tesla. Even with high-quality data as presented here, it remains unclear whether the small GABA signal can be reliably separated from glutamate, glutamine, and glutathione, all of which exhibit substantial spectral overlap with each other and other strong signals as well as the underlying macromolecular background. The limitations (and how they impact interpretation) ought to be mentioned and discussed in the context of the vast amount of literature. They should provide the reader with the appropriate context and the awareness that all MRS measures are extremely sensitive to many different experimental factors and modeling decisions.

Reviewer #1 (Public Review):

The authors show that TrafE, which is one of the five Dictyostelium discoideum TRAF proteins, is recruited to the Mycobacterium-containing vacuoles (MCVs) and is required for membrane damage repair and xenophagy. They propose that the TrafE-Ub-ALIX axis is important for the regulation of Vps4, and, thereby, for the normal function of ESCRT. They also suggest that TrafE is involved in phagophore sealing.

Overall, the parts of membrane damage repair and xenophagy induction are convincing. Although mammalian TRAF6 was already reported to be involved in the ubiquitination of Chlamydia and Toxoplasma-containing vacuoles (Haldar et al. PNAS, 2015, https://www.pnas.org/doi/epdf/10.1073/pnas.1515966112), how TRAF6 is recruited to pathogen-containing vacuoles remained unknown. This study reveals that the recruitment of TrafE to MCVs is dependent on membrane damage or reduced membrane tension. This is novel. However, the part of phagophore closure is too preliminary. The evidence that TrafE is involved in the phagophore closure is mostly indirect and weak.

Reviewer #1 (Public Review):

This manuscript presents evidence for Kv3 subunits being involved in shaping fast action potentials (APs) within the high-precision circuitry of the zebra finch song circuitry. The authors compare and contrast the morphology of Robustus Arcopallialis (RA) neurons with those in the adjacent intermediate arcopallium (AId) and compare their passive properties, action potential waveforms, and voltage-gated outward currents. Data using pharmacological agents known to interact with Kv3 channels reinforce their other observations.

Strengths:<br /> 1. Interesting avian model of cortical molecular mechanisms.<br /> 2. Comparative study at the level of cortical motoneurons showing those involved in fine motor control for vocalizations express high levels of Kv3.1.<br /> 3. Makes a case for convergent evolutionary utilization of Kv3.1 supporting fast spiking.<br /> 4. Clearly shows other Kv3 subunits are present in the nuclei under study.<br /> 5. Employs well-characterised pharmacological tools to support the physiology.

Weaknesses:<br /> 1. Comparison with Betz Cells comes across as of secondary importance and is perhaps a discussion point rather than the first introductory paragraph.<br /> 2. Fails to adequately quantify the absolute levels of Kv3 mRNA or protein in the zebra finch brain nuclei.<br /> 3. The comparison of % or fold differences between the two avian nuclei (RA and AId neuron) masks important quantitative evidence and the contribution of multiple subunits to functional channels is not well developed.<br /> 4. The voltage-clamp data suggests that the large TEA-sensitive current is too slow to dominantly contribute to the repolarization of a single AP (but would require sustained or cumulative depolarization to be activated), while the fast transient current which could contribute to single APs, is not sufficiently characterised.<br /> 5. It is not possible to conclude that the pharmacology is specific for Kv3.1, it is at best indicative, and the absence of more precise molecular tools (e.g. knockout or gene-edited animals) undermines the authors' justification of the zebra finch as an accessible model.<br /> 6. Although the authors acknowledge the presence of other Kv3 subunits, the report fails to explain whether they are functional, but focuses on Kv3.1 as being dominant, without sufficiently addressing how other subunits contribute (perhaps as heteromeric assemblies of subunits).

Reviewer #1 (Public Review):

This manuscript reports on a rapid and precise CRISPR/Cas9-mediated knock-in approach in the African turquoise killifish, an emerging vertebrate animal and gerontology model. More specifically, it describes an easily adoptable method to efficiently insert fluorescent reporters of different sizes at various genomic loci and to drive cell-type- and tissue-specific expression. This methodology will allow the development of humanized disease models and of cell-type specific molecular probes to study complex vertebrate biology, including aging biology, in the killifish. While this knock-in methodology is already widely used in common vertebrate animal models, the efficient generation of stable lines with germline transmission has been missing in killifish. As killifish have the shortest generation time of vertebrate animal models in laboratory conditions, show a rapid sexual maturity, and a short lifespan, the established method enables the generation of stable lines of homozygous transgenic vertebrate animals in 2-3 months. Overall, we believe this first report on efficient long (1.8kb) construct knock-in using CRISPR/Cas9 in the killifish establishes the killifish as a system for precise genetic engineering at scale, which has been challenging so far in vertebrates.

The establishment of this methodology will have a major impact in the field and be of extreme use within the scientific community. It will allow the development of scalable human disease models and integrate both genetics and age as risk factors, thus having the potential to identify future therapeutic targets for age-related diseases. It also has a generic character as the generated protocol can serve as a template for knock-in approaches in other emerging model organisms.

Although the reported data are of major interest and relevance to the scientific field, they are, as yet not sufficiently shown in convincing figures. The methodology is state-of-the-art and entails an extensive set of molecular, biochemical, and morphological/imaging technologies. While most of the data are nicely presented and accompanied by illustrative figures, the manuscript would benefit from the inclusion of a more detailed material and methods section, and a little more elaboration on morphometrical expression data in the results section, e.g, expression shown for all the studied genes in the larval fish, and a more critical discussion, that also highlights a few of the limitations, e.g., those related to the fast generation of homozygous F1 fish.

Reviewer #1 (Public Review):

The underlying principle of the experimental system described here is to test potential candidate genes that intersect with the proteotoxic-induced UPR by screening an siRNA pool that diminishes the UPR transcription reporter activated by sec-11 RNAi-mediated ER proteotoxic stress. The authors specifically focused on genes reported to play roles in LD biology, instead of general lipid synthesis genes. Systematic evaluation of the LD genes with respect to the induction of the UPR provides important insights into the overall functions and mechanisms of the UPR.

Using this set-up, the authors identified the hydroxysteroid dehydrogenase gene let-767/HSD17B12. Subsequent analyses revealed that let-767-mediated signaling is a key component that establishes the orchestration of both ER lipid and protein homeostasis and ER organismal functions, including ER lipid storage and ER structural changes. In addition, the authors found that acs-1i, knockdown of a gene involved in metabolism of lipids such as LCFA and mmBCFA, also diminished UPRE-GFP levels induced by sec-11i, albeit to a lesser extent than let-767i. Supplementation of lipid metabolites such as LCFA and mmBCFA recovered not only the sec-11-induced UPRE-GFP reporter phenotypes in acs-1i worms, but also the ER size and morphology and the LD and body sizes.

In contrast, the UPRE-GFP reporter phenotype in let-767i worms was not recovered by exogenously added LCFA or mmBCFA, although it was recovered by spb-1 RNAi, knockdown of a major lipogenic enzyme/pathway. The system established by the authors allowed them to quantitatively dissect the involvement of the Ire1-Xbp1 splicing UPR signaling branch. Finally, the authors demonstrated similar effects in mammalian tissue culture cells, suggesting conservation of the mechanisms.

The conclusions of this manuscript are generally in agreement with the data and the authors' interpretations are reasonable. However, at this point, the work remains descriptive and does not provide a mechanistic understanding. Overall contributions/advances towards providing new insights into how the UPR pathway is wired with respect to lipid-associated perturbations remain somewhat limited.

Reviewer #1 (Public Review):

The work in this study builds on previous studies by some of the same authors and aims to test whether the heartbeat evoked response was modulated by the local/global auditory regularities and whether this differed in post-comatose patients with different contagiousness diagnosis. The authors report that during the global effect there were differences between the MCS and UWS patients.

The study is well constructed and analysed and has data from 148 participants (although the maximum in anyone group was 59). The reporting of the results is excellent and the conclusions are supported by the results presented. This study and the results presented are discussed as evidence that EEG based techniques maybe a low cost diagnostic tool for consciousness in post-comatose patients, although it should be stressed that here no classification of diagnostics was performed on the EEG data.

One potential weakness was the relationship between the design of the experiment and the analysis pathway for the results. If I have understood correctly the experimental design the auditory regularity changed on whether the local/global regularity was standard/deviant. In the analysis the differences between all conditions in which the local or global regularity were compared between the standard and deviant trials. This difference was then compared between MCS and UWS patient groups. For these analyses the results for the health and emerging MCS were not included. If this is correct it would be interesting to understand the motivation for this. Relatedly, it would be good to clarify if the effects reported were corrected for the multiple planned contrasts and if not why they should not be corrected.

Reviewer #1 (Public Review):

Kazrin appears to be implicated in many diverse cellular functions, and accordingly, localizes to many subcellular sites. Exactly what it does is unclear. The authors perform a fairly detailed analysis of Kazrin in-cell function, and find that it is important for the perinuclear localization of TfN, and that it binds to members of the AP-1 complex (e.g., gamma-adaptin). The authors note that the C-terminus of Kazrin (which is predicted to be intrinsically disordered) forms punctate structures in the cytoplasm that colocalize with components of the endosomal machinery. Finally, the authors employ co-immunoprecipitation assays to show that both N and C-termini of Kazrin interacts with dynactin, and the dynein light-intermediate chain.

Much of the data presented in the manuscript are of fairly high quality and describe a potentially novel function for Kazrin C. However, I had a few issues with some of the language used throughout, the manner of data presentation, and some of their interpretations. Most notably, I think in its current form, the manuscript does not strongly support the authors' main conclusion: that Kazrin is a dynein-dynactin adaptor, as stated in their title. Without more direct support for this function, the authors need to soften their language. Specific points are listed below.

Major comments:<br /> 1) I agree with the authors that the data provided in the manuscript suggest that Kazrin may indeed be an endosomal adaptor for dynein-dynactin. However, without more direct evidence to support this notion, the authors need to soften their language stating as much. For example, the title as stated would need to be changed, as would much of the language in the first paragraph of the discussion. Alternatively, the manuscript could be significantly strengthened if the authors performed a more direct assay to test this idea. For example, the authors could use methods employed previously (e.g., McKenney et al., Science 2014) to this end. In brief, the authors can simply use their recombinant Kazrin C (with a GFP) to pull out dynein-dynactin from cell extracts and perform single molecule assays as previously described.<br /> 2) I'm not sure I agree with the use of the term 'condensates' used throughout the manuscript to describe the cytoplasmic Kazrin foci. 'Condensates' is a very specific term that is used to describe membraneless organelles. Given the presumed association of Kazrin with membrane-bound compartments, I think it's more reasonable to assume these foci are quite distinct from condensates.<br /> 3) The authors note the localization of Tfn as perinuclear. Although I agree the localization pattern in the kazKO cells is indeed distinct, it does not appear perinuclear to me. It might be useful to stain for a centrosomal marker (such as pericentrin, used in Figure 5B) to assess Tfn/EEA1 with respect to MT minus ends.<br /> 4) "Treatment with the microtubule depolymerizing drug nocodazole disrupted the perinuclear localization of GFP-kazrin C, as well as the concomitant perinuclear accumulation of EE (Fig. 5C & D), indicating that EEs and GFP-kazrin C localization at the pericentrosomal region required minus end-directed microtubule-dependent transport, mostly affected by the dynactin/dynein complex (Flores-Rodriguez et al., 2011)."<br /> - I don't agree that the nocodazole experiment indicates that minus end-directed motility is required for this perinuclear localization. In the absence of other experiments, it simply indicates that microtubules are required. It might, however, "suggest" the involvement of dynein. The same is true for the subsequent sentence ("Our observations indicated that kazrin C can be transported in and out of the pericentriolar region along microtubule tracks...").<br /> 5) Although I see a few examples of directed motion of Tfn foci in the supplemental movies, it would be more useful to see the kymographs used for quantitation (and noted by the authors on line 272). Also related to this analysis, by "centripetal trajectories", I assume the authors are referring to those moving in a retrograde manner. If so, it would be more consistent with common vernacular (and thus more clear to readers) to use 'retrograde' transport.<br /> 6) The error bars on most of the plots appear to be extremely small, especially in light of the accompanying data used for quantitation. The authors state that they used SEM instead of SD, but their reasoning is not stated. All the former does is lead to an artificial reduction in the real deviation (by dividing SD by the square root of whatever they define as 'n', which isn't clear to me) of the data which I find to be misleading and very non-representative of biological data. For example, the error bars for cell migration speed in Figure 2B suggest that the speeds for WT cells ranged from ~1.7-1.9 µm/sec, which I'm assuming is largely underrepresenting the range of values. Although I'm not a statistician, as someone that studies biochemical and biological processes, I strongly urge the authors to use plots and error bars that more accurately describe the data to your readers (e.g., scatter plots with standard deviation are the most transparent way to display data).

Reviewer #1 (Public Review):

Nicotine preference is highly variable between individuals. The paper by Mondoloni et al. provided some insight into the potential link between IPN nAchR heterogeneity with male nicotine preference behavior. They scored mice using the amount of nicotine consumption, as well as the rats' preference of the drug using a two-bottle choice experiment. An interesting heterogeneity in nicotine-drinking profiles was observed in adult male mice, with about half of the mice ceasing nicotine consumption at high concentrations. They observed a negative association of nicotine intake with nicotine-evoked currents in the antiparticle nucleus (IPN). They also identified beta4-containing nicotine acetylcholine receptors, which exhibit an association with nicotine aversion. The behavioral differentiation of av vs. n-avs and identification of IPN variability, both in behavioral and electrophysiological aspects, add an important candidate for analyzing individual behavior in addiction.

The native existence of beta4-nAchR heterogeneity is an important premise that supports the molecules to be the candidate substrate of variabilities. However, only knockout and re-expression models were used, which is insufficient to mimic the physiological state that leads to variability in nicotine preference.

Reviewer #1 (Public Review):

Cerebellar parallel fiber to Purkinje cell synapses display multiple forms of long-term plasticity, expressed in both presynaptic and postsynaptic compartments. At this synapse, a prominent form of presynaptic LTP was once thought to operate through cAMP-dependent activation of PKA, and subsequent phosphorylation of RIM1a. However, recent studies have questioned this hypothesis. LTP is not blocked by selective inhibitors of PKA, or by mutations in Rim1a designed to block PKA-dependent serine phosphorylation. In this study, Wang and colleagues use a wide array of pharmacology and genetics to elucidate a potential signaling cascade for presynaptic LTP in parallel fibers, where cAMP activates EPAC, leading to PKCε-dependent phosphorylation of RIM1α. Presynaptic ablation of either EPAC or PKCε leads to loss of presynaptic LTP and forskolin-induced potentiation. The experiments are generally well conceived and executed. The findings provide a new framework for understanding how presynaptic cAMP elevations can alter vesicle release machinery and drive synaptic plasticity, and open new avenues for exploration at synapses throughout the CNS. The manuscript could be improved by better a more transparent citation of previous studies and a more open discussion of the unknown steps in the newly-elucidated signaling cascade.

Reviewer #1 (Public Review):

This paper uses light field microscopy to measure calcium signals across the fly brain while it is walking and turning, and also while the fly is externally driven to walk and turn, using a treadmill. The authors drive calcium indicator expression using pan-neuronal drivers, as well as drivers specific to individual neurotransmitters and neuromodulators. From their experiments, the authors show that inhibitory and excitatory neurons in the brain are activated in similar patterns by walking and that neurons expressing machinery for different neuromodulatory amines tend to show differentially strong calcium signals during walking. By examining spontaneous and forced walking and turning, the authors identify brain regions that activate before spontaneous turning and that activate asymmetrically in concert with spontaneous or forced turning.

Strengths: Overall, the strength of this paper is in its careful descriptions and analyses of whole brain activation patterns that correlate with spontaneous and forced behaviors. Showing how the pattern of activity relates to broad classes of cells is also useful for understanding brain activation. Especially in brain regions identified as preceding spontaneous walking and in being asymmetrically involved in spontaneous and forced turning, it provides a wealth of potential hypotheses for new experiments. Overall, it contributes to a coarse-grained understanding of broad changes in brain activity during behavior.

Weaknesses: The primary weakness of this paper is that it presents some speculative interpretations and conclusions too strongly. Most importantly, average activity in a neuropil can represent the calcium activity of hundreds or thousands of neurons, and it is hard to know what fraction is active, for instance, or how expression pattern differences might play into calcium signals. Calcium signals also do not reliably indicate hyperpolarization, so a net increase in the average Ca++ indicator signal does not necessarily reflect that the average neuron is becoming more active, just that some labeled neurons are becoming more active, while others may be inactive or hyperpolarized. The conclusions about regions triggering walk (rather than just preceding it) are too strong for the manipulations in this paper, as are some of the links with individual neuron types. Thus, more presenting substantial caveats is required for the conclusions being drawn from the data presented here.

DOI: 10.1016/j.celrep.2023.112365

Resource: RRID:ZFIN_ZDB-ALT-071016-1

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-071016-1

What is this?

The space and the dual space is having the same dimension.

Linear functonal maps from a vector space to the real space.

If a vector is bounded, and we put this vector into the linear operator, then the output vector from the space would be bounded by the norm too.

Joint Public Review:

This paper presents two new tools for investigating GLP-1 signaling. The genetically encoded sensor GLPLight1 follows the plan for other GPCR-based fluorescent sensors, inserting a circularly permuted GFP into an intracellular loop of the GPCR. The light-uncaged agonist peptide, photo-GLP1, has no detectable agonist activity (as judged by the GLPLight1 sensor) until it is activated by light. However, based on the current characterization, it is unclear how useful either of these tools will be for investigating native GLP-1 signaling.

The GLPLight1 sensor has a strong fluorescent response to GLP-1 with an EC50 of ~10 nM, and its specificity is high, as shown by lack of response to ligands of related class B GPCRs. However, the native GLP1R enables biological responses to concentrations that are ~1000-fold lower than this (as shown, for instance, in a supplemental figure of this paper). This makes it difficult to see how the sensor will be useful for in vivo detection of GLP-1 release, as claimed; although there may be biological situations where the concentration is adequate to stimulate the sensor, this is not established. Data using a GLP-1 secreting cell line suggest that the sensor has bound some of the released GLP-1, but it is difficult to have confidence without seeing an actual fluorescence response to stimulated release.

Alternatively, the sensor might be used for drug screening, but it is unclear that this would be an improvement over existing high-throughput methods using the cAMP response to GLP1R activation (since those are much more sensitive and also allow detection of signaling through different downstream pathways).

The utility of the caged agonist PhotoGLP1 is similarly unclear. The data demonstrate a substantial antagonism of GLP-1 binding by the still-caged compound, and it is therefore unclear whether the kinetics of the response to PhotoGLP1 itself would mimic the normal activation by GLP-1 in the absence of the caged compound. A further concern is that the light-dependence of the agonist effect of PhotoGLP1 was evaluated only with the GLPLight1 sensor and not with GLP1R signaling itself, which is 1000x more sensitive and which would be the presumed target of the tool. In addition, PhotoGLP1 is based upon native GLP-1, which is rapidly truncated and inactivated by the peptidase DPPIV, expressed in most cell types, and expressed at very high levels in the plasma. The utility of PhotoGLP1 is therefore limited to acute (minutes) in vitro experiments.

Reviewer #1 (Public Review):

Using a combination of structural biology methods, this report aims at describing the auto-inhibited architecture of kinesin 1 either as homodimers or hetero-tetramers. Hence, the multiple contacts between the protein domains and their folding pattern is addressed using cross-linking mass spectrometry (XL-MS), negative stain electron microscopy and Alpha Fold based structure prediction. Based on the existing literature, the key domains and amino acids responsible for kinesin 1 inhibited state were not clearly deciphered. The synergetic use of different methods now seems to describe in detail the molecular cues which could induce kinesin-1 refolding and opening. Multiple interactions between the different domains seem to induce the folded conformation.

The combination of methodologies is an efficient way to unravel details that could not be addressed previously. The paper is well written. However, the methodology is sometimes not sufficiently detailed and the paper would benefit from additional explanations and demonstrations. The methods for generating the electron microscopy data and its relevance and quality, for instance, are barely described. In addition, the conclusions drawn would be more convincing if similar investigations would be carried out similarly for all isoforms (KIF5B and FIF5C) in parallel.

This article raises the potential strength and power of deep learning structure prediction methods combined simultaneously with other structural biology methods to answer specific questions. In the present context, this study will certainly be helpful to reveal and understand the activation mechanism of kinesin motor proteins.

Reviewer #1 (Public Review):

This work is a follow-up of the work from the same group where the authors showed that Lactiplantibacillus plantarum can enhance juvenile growth by activating the expression of an intestinal protease. They previously showed that this process was mediated by the dlt operon which is involved in the D-Alanylation of teichoic acid.

In the present study, the authors characterized the structure and enzymatic activity of the first protein encoded by this operon and show that the first gene of this operon encodes for an esterase releasing D-Ala from D-Ala lipoteichoic acids (LTA) and renamed it here DltE. The gene encoding this protein was previously uncharacterized and annotated as a peptidoglycan-binding protein putatively involved in peptidoglycan maturation. With the structure and enzymatic characterization of this protein, this study revealed that this protein does not act as peptidoglycan, but instead releases D-Ala from D-alanylated-LTA.

The authors use a Drosophila mutant impaired in response to mDAP-Peptidoglycan fragments (affected in the IMD pathway) to show that this mutant still responds to D-Ala-LTAs. This result is important to show that D-Ala-LTAs act as additional cues sensed by Drosophila independent of m-DAP-peptidoglycan by a still unknown sensory pathway. The study convincingly shows that D-Ala-LTA from the gut microbe L. plantarum leads to increase intestinal peptidase expression (intestinal activity) and enhance juvenile larva growth.

Reviewer #1 (Public Review):

This manuscript by Walker et. al. explores the interplay between the global regulators HapR (the QS master high cell density (HDC) regulator) and CRP. Using ChIP-Seq, the authors find that at several sites, the HapR and CRP binding sites overlap. A detailed exploration of the murPQ promoter finds that CRP binding promotes HapR binding, which leads to repression of murPQ. The authors have a comprehensive set of experiments that paints a nice story providing a mechanistic explanation for converging global regulation. I did feel there are some weak points though, in particular the lack of integration of previously identified transcription start sites, the lack of replication (at least replication presented in the manuscript) for many figures, some oddities in the growth curve, and not reexamining their HapR/CRP cooperative binding model in vivo using ChIP-Seq.

Reviewer #1 (Public Review):

Germe and colleagues have investigated the mode of action of bacterial DNA gyrase, a tetrameric GyrA2GyrB2 complex that catalyses ATP-dependent DNA supercoiling. The accepted mechanism is that the enzyme passes a DNA segment through a reversible double-stranded DNA break formed by two catalytic Tyr residues-one from each GyrA subunit. The present study sought to understand an intriguing earlier observation that gyrase with a single catalytic tyrosine that cleaves a single strand of DNA, nonetheless has DNA supercoiling activity, a finding that led to the suggestion that gyrase acts via a nicking closing mechanism. Germe et al used bacterial co-expression to make the wild-type and mutant heterodimeric BA(fused). A complexes with only one catalytic tyrosine. Whether the Tyr mutation was on the A side or BA fusion side, both complexes plus GyrB reconstituted fluoroquinolone-stabilised double-stranded DNA cleavage and DNA supercoiling. This indicates that the preparations of these complexes sustain double strand DNA passage. Of possible explanations, contamination of heterodimeric complexes or GyrB with GyrA dimers was ruled out by the meticulous prior analysis of the proteins on native Page gels, by analytical gel filtration and by mass photometry. Involvement of an alternative nucleophile on the Tyr-mutated protein was ruled unlikely by mutagenesis studies focused on the catalytic ArgTyrThr triad of residues. Instead, results of the present study favour a third explanation wherein double-strand DNA breakage arises as a consequence of subunit (or interface/domain) exchange. The authors showed that although subunits in the GyrA dimer were thought to be tightly associated, addition of GyrB to heterodimers with one catalytic tyrosine stimulates rapid DNA-dependent subunit or interface exchange to generate complexes with two catalytic tyrosines capable of double-stranded DNA breakage. Subunit exchange between complexes is facilitated by DNA bending and wrapping by gyrase, by the ability of both GyrA and GyrB to form higher order aggregates and by dense packing of gyrase complexes on DNA. By addressing a puzzling paradox, this study provides support for the accepted double strand break (strand passage) mechanism of gyrase and opens new insights on subunit exchange that may have biological significance in promoting DNA recombination and genome evolution.

The conclusions of the work are mostly well supported by the experimental data.

Strengths:

The study examines a fundamental biological question, namely the mechanism of DNA gyrase, an essential and ubiquitous enzyme in bacteria, and the target of fluoroquinolone antimicrobial agents.

The experiments have been carefully done and the analysis of their outcomes is comprehensive, thoughtful and considered.

The work uses an array of complementary techniques to characterize preparations of GyrA, GyrB and various gyrase complexes. In this regard, mass photometry seems particularly useful. Analysis reveals that purified GyrA and GyrB can each form multimeric complexes and highlights the complexities involved in investigating the gyrase system.

The various possible explanations for the double-strand DNA breakage by gyrase heterodimers with a single catalytic tyrosine are considered and addressed by appropriate experiments.

The study highlights the potential biological importance of interactions between gyrase complexes through domain-or subunit-exchange

Weaknesses:

The mutagenesis experiments described do not fully eliminate the perhaps unlikely participation of an alternative nucleophile.

Joint Public Review

The molecular composition of synaptic vesicles (SVs) has been defined in substantial detail, but the function of many SV-resident proteins are still unknown. The present study focused on one such protein, the 'orphan' SV-resident transporter SLC6A17. By utilizing sophisticated and extensive mouse genetics and behavioral experiments, the authors provide convincing support for the notion that certain SLC6A17 variants cause intellectual disability (ID) in humans carrying such genetic variations. This is an important and novel finding. Furthermore, the authors propose, based on LC-MS analyses of isolated SVs, that SLC6A17 is responsible for glutamine (Gln) transport into SVs, leading to the provocative idea that Gln functions as a neurotransmitter and that deficits in Gln transport into SVs by SLC6A17 represents a key pathogenetic mechanism in human ID patients carrying variants of the SLC6A17 gene.

This latter aspect of the present paper is not adequately supported by the experimental evidence so that the main conceptual claims of the study appear insufficiently justified at this juncture. Key weaknesses are as follows:

A. Detection of Gln, along with classical neurotransmitters such as glutamate, GABA, or ACh, in isolated SV fractions does not prove that Gln is transported into SVs by active transport. Gln is quite abundant in extracellular compartments. Its appearance in SV samples can therefore also be explained by trapping in SVs during endocytosis, presence in other - contaminating - organelles, binding to membrane surfaces, and other processes. Direct assays of Gln uptake into SVs, which have the potential to stringently test key postulates of the authors, are lacking.

B. The authors generated multiple potentially very useful genetic tools and models. However, the validation of these models is incomplete. Most importantly, it remains unclear whether the different mutations affect SLC6A17 expression levels, subcellular localization, or the expression and trafficking of other SV and synapse components.

C. Apart from the caveats mentioned above regarding Gln uptake into SVs, the data interpretation provided by the authors lacks stringency with respect to the biophysics of plasma membrane and SV transporters.

Reviewer #1 (Public Review):

Abdellahi et al. used targeted memory reactivation (TMR) and machine learning tools to look for evidence that waking neural activity is reinstated during subsequent REM sleep. Prior work has demonstrated that learning content is successfully decoded following TMR cues during NREM sleep, but a direct link between patterns of brain activity recorded during wakefulness and subsequent REM sleep in humans has never been reported. In this paper, the authors report that an LDA classifier detects wake-like neural activity (specifically, neural activity recorded while imaging performing a trained serial reaction time task) approximately one second after TMR cues are presented during REM sleep. Decoding performance is better when the classifier is trained on sleep trials with high theta compared to low theta power, and classifier performance was correlated with overnight improvement on the task.

Finding evidence of reinstated waking neural activity during REM sleep is an exciting result, and the authors present a promising method that holds implications for advancing our understanding of how memories are reprocessed during REM sleep. I think it is a particular strength of the paper that the authors trained on sleep data and tested in wake data, which is analogous to prior rodent studies that found evidence of replay during REM. I also thought playing sounds during the adaptation night, prior to SRTT training, provided a nice control.

The conclusions of this paper are mostly supported by the results presented, but it is not always clear how those results were obtained. Some aspects of the experimental and data analytic methods need to be clarified and expanded, both for a better understanding of how the results of this study were obtained, as well as for future reproducibility.

Reviewer #1 (Public Review):

Most previous studies investigating the phenomenon of crowding in depth use small stereoscopic differences in depth. Taken together their results suggest that a depth difference between target and flankers reduces crowding. A potential problem is that stereo displays can reduce depth perception. The studies that have used a real-depth display have provided some inconsistent findings. The present study investigated larger differences, representative of those among many objects in the real world. These larger differences increased crowding, even in the absence of diplopia (double vision).

This study is likely to be impactful in the field as it shows that crowding occurs in-depth and strengthens the importance of crowding in natural 3D environments. All existing models of crowding would need to be modified to explain this experimental finding.

The novel multi-depth plane display that the authors used enables measurements of depth differences that are more likely to correspond to differences in the real world, and could be used by others to further investigate crowding in-depth or other perceptual processes (e.g., visual search).

In general, there are some interactions that were reported and others that were not reported, but it would be important to know if they are significant. (pages 15-16) For example, when the target is at fixation and the target is at a variable flanker depth: In Experiment 1, was there a significant interaction between (a) target-fixation depth and flanker depth (in front versus behind) and (b) target-fixation depth and target-flanker spacing? In Experiment 3, it is reported that perceptual error was higher when the target was in from or behind the flanker ring and fixation and that the greatest perceptual error occurred when the target was behind, but it is not reported if this interaction was significant. Its presence is important to know whether the data should be independently analyzed for 'in front' and 'behind'. In Experiment 5, was the interaction between target-flanker spacing and depth significant?

The findings are clear but the explanation(s) for the findings is not. The authors state that large interocular disparity differences likely induce diplopia, which could increase perceptual error by increasing the number of features. The authors should explain what they mean by features and how an increased perceived number of features would increase crowding. Moreover, the authors acknowledge that only a few observers reported experiencing diplopia; however, they speculate that observers may have experienced diplopia but not noticed it consciously given the short stimulus presentation time.

Reviewer #1 (Public Review):

Pelentritou and colleagues investigated the brain's ability to infer temporal regularities in sleep. To do so, they measured the effect on brain and cardiac activity to the omission of an expected sound. Participants were presented with three different categories of sounds: fixed sound-to-sound intervals (isochronous), fixed heartbeat-to-sound intervals (synchronous), and a control condition without any regularity (asynchronous). When omitting a sound, they observed a difference in the isochronous and synchronous conditions compared to the control condition, in both wakefulness and sleep (NREM stage 2). Furthermore, in the synchronous condition, sounds were temporally associated with sleep slow waves suggesting that temporal predictions could influence ongoing brain dynamics in sleep. Finally, at the level of cardiac activity, the synchronous condition was associated with a deceleration of cardiac frequency across vigilance states. Overall, this work suggests that the sleeping brain can learn temporal expectations and responds to their violation.

Major strengths and weaknesses:<br /> The paradigm is elegant and robust. It represents a clever way to investigate an important question: whether the sleeping brain can form and maintain predictions during sleep. Previous studies have so far highlighted the lack of evidence for predictive processes during sleep (e.g. (Makov et al., 2017; Strauss et al., 2015; Wilf et al., 2016)). This work shows that at least a certain type of prediction still takes place during sleep.

However, there are some important aspects of the methodology and interpretations that appear problematic.<br /> (1) The methodology and how it compares to previous articles would need to be clarified. For example, the Methods section indicates that the authors used a right earlobe electrode as a reference. This is quite different from the nose reference used by SanMiguel et al. (2013) or in Dercksen et al. (2022). This could affect the polarity and topographies of the OEP or AEP and thus represents a very significant difference. Likewise, SOs are typically detected in a montage reference to the mastoids. Perhaps the left/right asymmetries present in many plots (e.g. Figure 3) could be due to the right earlobe reference used. Also, the authors did not use the same filters in wakefulness and sleep, which could introduce an important bias when comparing sleep and wake results or sleep results with previous wake papers.<br /> (2) The ERP to sound omission shows significant differences between the isochronous and asynchronous conditions in wakefulness (Figure 3A and Supp. Fig.) but this difference is very different from previous reports in wakefulness. Topographies are also markedly different, which questions whether the same phenomenon is observed. For example, SanMiguel and colleagues observed an N1 in response to omitted but expected sounds. The authors argue that they observe a similar phenomenon in the iso vs baseline contrast, but the timing and topography of their effect are very different from the typical N1. The authors also mention that, within their study, wake and N2 OEPs were "largely similar" but they differ in terms of latencies and topographies (Figure 3A-B). It would be better to have a more objective way to explore differences and similarities across the different analyses of the paper or with the literature.<br /> (3) The authors applied a cluster permutation to identify clusters of significant time points. However, some aspects of this analysis are puzzling. Indeed, the authors restricted the cluster permutation to a temporal window of 0 to 350ms in wake (vs. -100 to 500ms in sleep). This can be misleading since the graphs show a larger temporal window (-100 to 500ms). Consequently, portions of this time window could show no cluster because the analysis revealed an absence of significant clusters but because the cluster permutation was not applied there. Besides, some of the reported clusters are extremely brief (e.g. l. 195, cluster's duration: 62ms), which could question their physiological relevance or raise the possibility that some of these clusters could be false positives (there was no correction for multiple comparisons across the many cluster permutations performed). Finally, there seems to be a duplication of the bar graphs showing the number of significant electrodes in the positive and first negative cluster for Figure 2 Supp. Fig. 1.<br /> (4) More generally, regarding statistics, the absence of exact p-values can render the interpretation of statistical outputs difficult. For example, the authors report a significant modulation of the sound-to-SO latency across conditions (p<0.05) but no significant effect of heartbeat peak-to-SO latency (p>0.05). They interpret this pattern of results rather strongly as evidence that the "readjustment of SOs was specific to auditory regularities and not to cardiac input". Yet, examining the reported chi-square values show very close values between the two analyses (7.9 vs. 7.4). It seems thus difficult to argue for a real dissociation between the two effects. Providing exact p-values for all statistical tests could help avoid this pitfall.

Reviewer #1 (Public Review):

Kozol et al adapt an important tool, in the form of the atlas, to the Astyanax research community. While broadly the atlas appears to correctly identify large brain regions, it is unclear what is the significance of the finer divisions. The external confirmations are restricted to just a few large brain regions (by independent human observer: e.g., optic tectum, hypothalamus. By molecular marker: hypothalamus only.). As such, interpretations of results from as many as 180 small subregions should be interpreted sceptically.<br /> The authors also suggest that some brain regions have increased in size during cavefish evolution (e.g., hypothalamus, subpallium). The analysis of progeny from a genetic cross of cave and surface morphs suggest a complex genetic program has evolved to control this variant set of brain structures. With the development of genetic manipulation tools in this species, an exciting series of experiments may link causal variants with brain development differences.

MAJOR ISSUES<br /> Line 85+. Segmentation accuracy is not well established by the authors.<br /> For example, Figure S2 states that the pixel correlation is high between Astyanax populations. But the details of how this cross-correlation was done are sparse. Is the Y-axis here showing the fraction of pixels that are shared in the morphs? While the annotation appears to function similarly across morphs, the 80% machine:human correlation is difficult to put into context. On the one hand, this seems low. For what values should one strive? Are there common "mistakes" or differences in human & machine annotations that lead to certain regions being excluded? A discussion of these is warranted and will be useful to others who wish to use this approach.

Line 87. "such as" is misleading since these were the only two antibodies used to confirm molecular definitions of regions.<br /> But more to the point, additional markers should be used to confirm more than just the ISL+ hypothalamic divisions.<br /> This is particularly warranted, as Fig 1d is not convincing. I believe that the yellow label is ISL; this is difficult to see in the figures. ISL is not ideal since this is widespread in the hypothalamus. There are no ISL-negative regions depicted, which would be necessary to demonstrate that the resolution of this subregion labeling tool is high. A complementary approach would be to find molecular markers that are more restricted than ISL which label only subsets of hypothalamic regions.<br /> Finally, do the mid/hindbrain ISL labeled regions correspond to known ISL+ subregions?

The molecular and human-observed confirmations of brain regions suggests that the annotated borders of gross anatomical regions are correctly identified by the algorithm. However, data is not presented that indicates whether the smaller regions correspond to biologically meaningful compartments.

Parameters used in CobraZ to perform the segmentation are not defined. More transparency is required here for others to replicate.

Reviewer #1 (Public Review):

The authors of this manuscript aimed to systematically evaluate the pleiotropic effects of MCR-1-mediated colistin resistance. They evaluated the effect of MCR-1 and MCR-3 carried on different plasmids on antimicrobial peptides (AMPs) and assessed their ultimate effect on virulence. The authors find that MCR-1-mediated colistin resistance correlates with increased resistance against some host AMPs, but also increased sensitivity to others. The authors also find that MCR-1 alone is associated with resistance to human serum and to elements of the complement system. This highlights a potential selective advantage for MCR-1-mediated resistance to host immune factors and a potential for enhanced virulence.

The methods have been well established before and adequately support their main findings. While determining the role of MCR-1 in a single genetic background is important to better understand its potential pleiotropic effects against a diversity of AMPs and in a variety of scenarios, the impact and significance of the results are partially ameliorated because different genetic backgrounds, particularly those most relevant to a clinical (or agricultural) context were not considered. The results depicted here are still a necessary and important step towards a more comprehensive understanding of the pleiotropic effects of MCR-1. But, interactions between plasmids and host genomes and their co-evolution can have important effects more generally. The authors do mention this in the discussion and suggest it to be an important avenue for future work. However, given the objective of the study and the clinical and agricultural context in which the authors have framed their work, it seems more relevant to include those distinct genetic backgrounds already here.

The conclusions stemming from the results found in Figure 3, and Figures 4c and d seem too overreaching to me. The associated resistance to AMPs from pigs seems to be only strong enough against one of the five tested AMPs and hence concluding that these impose a strong selective pressure in the pig's gut seems unsubstantiated. Similarly, the difference in survival probability within their in vivo system, though statistically significant, seems to be very ild between their MCR-1 and empty vector control.

Reviewer #1 (Public Review):

The adhesion of Leishmania promastigotes to the stomodeal valve in the anterior region of the sandfly vector midgut is thought to be important to facilitate the transmission of the parasites by bite. The promastigote form found in attachment is termed a 'haptomonad', although its adhesion mechanism and role in facilitating transmission have not been well studied. Using 3D EM techniques, the paper provides detailed new information pertaining to the adhesion mechanism. Electron tomography was especially useful to reveal the ultrastructure of the attachment plaque and the extensive remodelling of the flagellum that occurs. A few of the attached haptomonads were found to be in division, which is a novel observation. The attachment of cultured promastigotes to plastic and glass surfaces in vitro was found to involve a similar remodeling of the flagellum and was exploited to image the sequential steps in attachment, flagellar remodeling, and haptomonad differentiation. The in vitro attachment was found to be calcium2+ dependent. Based mainly on the in vitro observations, a sound model of the haptomonad attachment plaque and differentiation process is provided.

Reviewer #1 (Public Review):

In this manuscript, Sampaio et al. tackle the role of fluid flow during left-right axis symmetry breaking. The left-right axis is broken in the left-right organiser (LRO) where cilia motility generates a directional flow that permit to dictate the left from the right embryonic side. By manipulating the fluid moved by cilia in zebrafish, the authors conclude that key symmetry breaking event occurs within 1 hour through a mechanosensory process.

Overall, while the study undeniably represents a huge amount of work, the conclusions are not sufficiently backed up by the experiments. Furthermore, the results provided present a limited advance to the field: the transient activity of the LRO is well established, and narrowing down this activity to 1 hour (even though unclear from the presented data that it is a valid conclusion) does not help to understand better the mechanism of symmetry breaking. Importantly, the authors do not provide any convincing experiments to back up the mechanosensory hypothesis because the fluid extraction experiments affect both the chemical and physical features of the LRO, so it is impossible to disentangle the two with this approach.

Reviewer #1 (Public Review):

In this manuscript, Lee and colleagues address the participation of NBR1 in chloroplast clearance after treatment with high light intensity. Authors use NBR1 fused to reporter proteins (GFP, mCherry), with the aid of nbr1, atg7, and nbr1-atg7 mutants, in combination with immunogold labelling to show localization of NBR1 to surface and interior of photodamaged chloroplasts, which follows with their engulfment in the vacuole, a process which is independent of ATG7. The combined use of ATG8 fused to GFP further shows that NBR1 and ATG8 are recruited independently to photodamaged chloroplasts. In addition, the use of mutant versions of NBR1 in combination with mutants lacking E3 ligases PUB4 and SP1 and mutant toc132-2 and tic40-4 lacking members of the TIC-TOC complex of protein translocation to the chloroplast, authors show that chloroplast localization of NBR1 requires the ubiquitin ligase domain (UBA2) of the protein, whereas, the PB1 domain exerts a negative effect on NBR1 chloroplast association, yet neither the PUB4 and SP1 E3 ligases nor the TOC-TIC are required for NBR1 association to photodamaged chloroplasts. All these approaches are well described and strongly support the authors' conclusions that the loss of chloroplast envelope integrity allows the entrance of cytosolic ubiquitin ligases and the participation of NBR1 in photodamaged chloroplast clearance by a process of microautophagy. All these findings add valuable information to our knowledge of chloroplast homeostasis in response to light stress.

To further support these conclusions, authors perform a chloroplast proteomic analysis of the WT, nbr1, atg7, and nbr1-atg7 mutants. However, in contrast with the above results, the description of the proteomic data is rather confusing. The paragraph on Page 17 (lines 393-406) is hard to follow. The term "over-representation of less abundant chloroplast protein" is also quite confusing, like the data in Fig. 6 and supplementary to this figure (what does show the PCA analysis in Fig. 6-suppl. 1?). I wonder whether it would be possible to show all these data as supplementary and try to present the data supporting the major conclusion of these analyses (if I understood correctly, that nbr1, atg7, and the double mutant have lower contents of chloroplast proteins), in a more simple and clear format.

Reviewer #1 (Public Review):

The manuscript entitled "Pooled genome-wide CRISPRa screening for rapamycin resistance gene in Drosophila cells" by Xia et al. is a well-structured piece of work with clear objectives and experiments. The authors successfully demonstrated genome-wide gene activation using CRISPRa using a novel sgRNA design, which overcame previous failed attempts to replicate gene activation that worked well in mammalian systems. The study is detailed and highly relevant for the application of CRISPRa in understanding the molecular mechanism of gene candidates.

Reviewer #1 (Public Review):

The model put forward by the authors in this manuscript is a simple and exciting one, explaining the function of AGS3 as a negative regulator of LGN, acting as a 'dominant-negative' version of LGN. Overall, the results support the model very well, and the results shown in Fig 6, which clearly reveal the functional relevance of AGS3, add strength to the paper.

In Figures 3A and B, the authors claim that AGS3 overexpression leads to depolarization of LGN in epidermal stem cells. However, in the example provided in Figure 3A, the LGN signal appears to be stronger than the control, with more LGN still on the apical side (many would categorize this as 'apically polarized'). In the scoring shown in Figure 3B, I am not sure if 'eyeballing' is the right way to decide whether it is polarized/depolarized/absent. The authors should come up with a bit more quantitative method to quantify the localization/amount of LGN and explain the method well in the manuscript. A similar concern regarding the determination of the LGN localization pattern applies to the rest of figure 3 as well.

Reviewer #1 (Public Review):

Previously the authors showed that ERK3 plays a critical role in the production of IL-8, immune cell chemotaxis, and metastasis (Bogucka et al, eLife 2020). This is a follow-up study on these observations in which they uncover a critical role for ERK3 in the activation of RhoGTPases, formation of actin-rich protrusions, and actin polymerization. Previous publications have reported a critical role of ERK3 in regulating cell morphology and migration. However, the molecular mechanisms responsible for these phenotypes remain elusive. The polarized phenotype of motile cells involves complex actin cytoskeleton re-arrangements, and in this study, the authors demonstrate a direct role for MAPK6 kinase in regulating actin dynamics.

First, the authors confirm that loss of ERK3 negatively affects MDA-MB231 cell motility and migration, both in vitro and in vivo. Interestingly loss of ERK3 reduced F-actin content in primary breast mammary epithelial cells. The authors used a multi-disciplinary approach to elucidate the underlying mechanisms. Using biochemical methods, they elegantly show the direct link between ERK3 and RhoGTPases as well as the ARP2/3 complex. Furthermore, direct binding of ERK3 to Rac1, Cdc42, and Arp2/3 complex is shown by biochemical assays, and these observations are validated by monitoring the interaction between ERK3 and the Cdc42/ARP2/3 complex in cells at endogenous levels. The finding that ERK3 acts as a GEF for Cdc42 and not Rac1 is interesting and further links this kinase to PAKs. PAK kinases have been shown to phosphorylate ERK3 at Ser 189 in the SEG motif to activate ERK3 (Deleris et al JBC,2011). Overall, this study generated a lot of interesting data and the work has been well-executed and properly interpreted. The main findings are novel and important, and they are of particular interest to readers in the fields of cell migration and actin dynamics. This manuscript is also likely to stimulate additional investigations using biophysical and structural methods to further decipher GEF activity controls ERK3.

Reviewer #1 (Public Review):

This paper by Zhuang and colleagues seeks to answer an important clinical question by trying to come up with novel predictive biomarkers to predict high-risk T1 colorectal cancers that are at risk for nodal involvement. The current clinical features may both miss patients who underwent local therapy and who should have gone on to have surgery and patients for whom surgery was done based on risk features but perhaps unnecessarily. Using a training and validation set, they developed a protein-based classifier with an AUC of 0.825 based on mass spec analyses and proteomic analyses of patients with and without LN importantly linking biological rationale to the proteomic discoveries.

In the training cohort, they took 105 candidate proteins reduced to 55, and did a validation in the training cohort first and then in two validation cohorts (one of which was prospective). They also looked at a 9 protein classifier which also performed well and furthermore looked at IHC for clinical ease.

Reviewer #1 (Public Review):

This paper presents a systematic and novel examination of how pupil size relates to BOLD fMRI signal in a set of subcortical nuclei. It provides some important novel findings that should help advance understanding of how pupil size relates to activity in subcortical nuclei as well as providing important advances in how to measure these relationships.

The authors first tried replicating prior findings of a relationship between pupil size and BOLD signal using the prior methods. They could not (despite replicating pupil-cortical region relationships), and so tested whether the delay in the hemodynamic response function might differ in subcortical and cortical regions. They found that BOLD signal in the subcortical nuclei showed associations with pupil size at short delays. This is a critical finding as typical fMRI analyses assume a longer delay and so likely obscure the ability to see effects in these subcortical regions. The authors provide a number of helpful 'control' analyses that help strengthen confidence in their findings. For instance, it buttresses their findings that the pons control region did not show any significant effect to time-to-peak on correlations with pupil size or derivative measures. It also is helpful to know that pupil size fluctuations were associated with cortical activity in the regions expected from prior studies. The rigor of the study is also supported by the fact that there was a preregistration and that data are publicly shared.

Reviewer #1 (Public Review):

The manuscript by Mansur et al examines the roles of KLHL40, mutations which lead to the development of skeletal muscle disease (nemaline myopathy, NM). The authors use CRISPR-based gene editing in a model organism (zebrafish) to disrupt the two fish isoforms of KLHL40 (a and b) and examine the resulting phenotypes. The authors find that disease-like phenotypes develop in adulthood selectively with the deletion of the KLHL40a isoform. Phenotypes include reduced body size, reduced endurance, and reduced life span with cellular effects that include perturbations to sarcomere organization, perturbed morphology of secretory organelles and mitochondria, and defects in collagen secretion and ECM deposition. The system provided the advantage of following both development and pre-disease state (onset) allowing the authors to look at changes in translation but mainly in the proteome with a focus on ubiquitylation (followed by mass spectrometry). Selective changes to the proteomthe e in KLHL40a deletion mutant are evident in the pre-symptomatic stage. Pathway analysis suggests that mutant cells show selective increases in glycolytic and biosynthetic enzymes/pathways, perhaps, akin to a Warburg effect. Monitoring the correlation between loss of KLHL40a-dependent ubiquitylation and increased protein levels defined the small GTPase Sar1a as a direct target for KLHL40a-directed degradation. Sar1a interacts with KLHL40a and is ubiquitylated by Cul3-KLHL40 in cell-free and over-expression assays in mammalian cells. Overexpression of Sar1a in muscle leads to endoplasmic reticulum (ER) membrane tubulation and thickening of the Z-lines similar to ones showing in KHLH40a deletion and NM patients. Markedly elevated levels of Sar1a and defects in collagen secretion are also recorded in patients with KLHL40 mutations. These observations suggest that selective control of COPII coat protein Sar1a levels (and thus the activity of the COPII coat, which mediates biosynthetic secretion from the ER), perturbs collagen secretion and ECM deposition. Overall this comprehensive work delineates the roles of Cul3-KLHL40a in the development of NM and specifically in regulating secretion by controlling the levels of one component of the COPII coat. The work is very interesting yet requires additional experimental clarifications and analysis.

Strength

This is a very interesting study showing global developmental and disease onset-related changes to the proteome focusing on changes derived from KLHL40a deletion. The work demonstrates a key role of ubiquitylation and selective protein degradation in the development and muscle disease onset. The global proteome view identified changes to energy production modes and defined direct regulation of Sar1a levels by Cul3-KHLH40a ubiquitylation which regulates ECM secretion, providing a mechanistic explanation for the development of NM in patients with KLHL40 mutations. Furthermore, the study highlights an interesting mechanism in which the levels of an individual component of the COPII coat are controlled by degradation to regulate biosynthetic secretion from the ER.

Weaknesses

There are weaknesses in the analysis that would markedly benefit from added clarifications. The differential outcome with the deletion of klhl40 a and b requires explanation. Morphological observations, which are key to understanding the overall phenotypes of KLHL40a deletion should be developed to provide a better definition of effects on organelle morphology and in particular ones involved in secretion. Some of the transcriptome-proteome data are left unexplored, in particular a view of the unfolded protein response (UPR) within the data, which will complement the documented defects in protein secretion and provide intrinsic controls to the work. The findings on Sar1a and the role of controlled degradation in regulating COPII activities are highly interesting yet a more complete analysis of COPII components is missing. Information on Sar1b, previously implicated in selective effects on secretion, Sec23-Sec24 and ratio (where levels are regulated by ubiquitylation and de ubiquitylation), and outer layer COPII proteins Sec13 and in particular Sec31, which is by itself a target for Cul3-KLHL12 regulation during development and modifies selective biosynthetic secretion, is lacking. Added analysis can provide new perspectives on the potential broader implications and significance of this study.

Reviewer #1 (Public Review):

The authors aimed to study the contribution of bacterial factors to poor treatment outcomes in drug-susceptible TB, an important issue that has not been well studied. The authors performed GWAS on a very large population-based (3 sites in China) dataset of 3416 Mtb WGS data of pre-treatment isolates linked with clinical data to predict treatment outcomes. Logistic regression was used to assess the association between predictors and outcomes and ROC curves were generated to assess the value of the genomic signatures to predict poor TB treatment outcomes. The authors were successful in identifying 14 Mtb variants in 13 genes and reactive oxygen species that were more likely to occur in patients with poor treatment outcomes.

The investigators were very thorough, in investigating both fixed and unfixed mutations, and analyzing the changes in gene expression under stress (exposure to first-line drugs and hypoxic conditions) for the 13 genes identified, which further strengthened the evidence generated by GWAS. The authors attempted to perform an external validation of their findings but could not identify a suitable existing dataset.

These data can be used by others to guide their analyses, and confirm if these 13 genes are also found in other settings. If confirmed, then the results could open the possibility for individualised tailoring of treatment of drug-susceptible TB, especially to prevent the risk of relapse.

Reviewer #1 (Public Review):

This study sought to establish a model of targeted lung endothelial ablation and subsequently study the regeneration process post-ablation using single-cell RNA-sequencing in order to identify key subpopulations and underlying mechanisms of regeneration.

Strengths of the study include:

1. The elegance of the DT endothelial ablation model which leverages local lung instillation of DT to locally ablate the endothelium and cause significant lung vascular leakiness while keeping the endothelium of other organs intact, as is convincingly demonstrated in Fig 1 and Fig 2.

2. The temporal analyses using scRNA-seq demonstrate key shifts in endothelial and non-endothelial cell populations following endothelial injury. These experiments identify a highly proliferative subpopulation of endothelial cells that expresses the transcription factor FoxM1 during the regeneration phase.

3. The authors discover that the traditionally designated "gCap" lung endothelial population contains additional subpopulations that have regenerative potential and that there is a transient expression of apelin in the regenerative population. Pharmacological inhibition of the apelin receptor increase mortality.

Potential weaknesses include:

1. The description of the "stem-like" nature of endothelial cells is not experimentally proven. "Stem-like" is a vague term and the usage of this term is primarily based on the expression of Procr. However, that itself does not justify the usage of "stem-like" unless there is more clear evidence of what "stem-like" properties these cells have, such as multipotency.

2. The intriguing finding of the proliferative EC population raises the question as to how these cells emerge. Do they have a specific subpopulation/cluster origin in the baseline lung endothelium, and was Apelin expression both necessary as well as sufficient to induce the switch to the proliferative state? Such mechanistic analyses would be very helpful in understanding the coordination of the lung endothelial regeneration program.

3. The authors mention that endothelial ablation also induces shifts in the numbers of other cell types such as epithelial cells, alveolar macrophages, and immune cells but there is no analysis beyond the quantification of the cells. Are these cells involved in the regeneration of the endothelium by providing ligands such as growth factors?

Reviewer #1 (Public Review):

Lammer et al. examined the effects of social loneliness, and longitudinal change in social loneliness, on cognitive and brain aging. In a large sample longitudinal dataset, the authors found that both baseline loneliness and an increase in loneliness at follow-up were significantly associated with smaller hippocampal volume, reduced cortical thickness, and worse cognition in healthy older adults. In addition, those older adults with high loneliness at baseline showed even smaller hippocampal volume at follow-up. These results are interesting in identifying the importance of social support to cognitive and brain health in old age. With a longitudinal design, they were able to show that increased loneliness was related to reduced brain structural measures. Such results could help guide clinicians and policymakers in designing social support systems that would benefit the growing aging population.

The strength of the current study lies in the large sample size and longitudinal follow-up design. The multilevel models used to separate within and between subject effects are well constructed. Combining neuroimaging data with behavioral changes provided further evidence that social loneliness may be related to accelerated brain aging. Stringent FDR correction, Bayes factor comparison, and the additional analyses for sensitivity showed the robustness and credibility of the results.

Weaknesses of the study were related to the interpretation and discussion of their findings.

Social loneliness is a relatively little-studied factor in cognitive ageing, and the authors should consider expanding the discussion, with some additional analyses, as to how their results could be used by clinicians and older adults to monitor social behaviors.

The authors examined the interaction between baseline and age change to see if higher baseline loneliness was associated with accelerated decline. The interaction was significant, but the authors did not further explore the interaction effect, which may have clinical significance. The authors should consider identifying a cut-off point in LSNS that suggests persons scoring less than this score on the LSNS may be at greater risk of accelerated brain decline than others. Such a cut-off point is important for clinicians, as well as for future researchers to compare their results.

Although it was not directly tested in the paper, LSNS scores did not seem to change with increasing age (Table 1). This general stability of LSNS scores in older adults should be discussed further. The authors should consider how their relatively healthy and high SES sample may be less vulnerable to loss of family or friends in old age, making this sample sub-optimal for the question they have. The significance of the subject effect suggests that some individuals still experience a loss of social connectedness. The authors may want to elaborate on this and give some explanations of such subject differences in the ageing effect on social loneliness. Although stress was not a significant mediating factor, is it related to baseline loneliness or changes in loneliness in the current sample?

The presentation of longitudinal data (Figure 1) lacks dimensionality. The scatter plots presented here are more suitable for cross-sectional studies and could cause confusion regarding the interpretation of the results. The authors should consider individual growth curves or spaghetti plots in visualizing change within subjects.

Reviewer #1 (Public Review):

Muscle is a major insulin-responsive tissue for the disposal of glucose, a process dependent on the translocation of GLUT4 glucose transporter from intracellular compartments to the plasma membrane. Knudsen and co-workers provide an analysis of the impact of microtubule-based movement on GLUT4 biology in muscle cell lines, and rodent and human muscle fibers ex vivo. A role for microtubules in the control of GLUT4 vesicle dynamics in both unstimulated and insulin-stimulated adipocytes (cultured and primary) has been previously reported by a number of groups. Less is known about the requirement for microtubules for GLUT4 translocation in muscle. A strength of this study is that key aspects of the work were performed in muscle fibers rather than muscle cell lines.

Conclusions that are strongly supported by the data presented include:

1. Demonstration of constitutive GLUT4 movement along microtubule tracks in both unstimulated and insulin-stimulated muscle fibers. GLUT4 dynamics in unstimulated fibers were captured by fluorescence recover after photobleaching (FRAP) and by quantifying vesicle movements by live cell microscopy, whereas in insulin-stimulated cells GLUT4 dynamics were captured by following the movements of GLUT4-containing vesicles. These data support a model in which intracellular GLUT4 is dynamic in both unstimulated and insulin-stimulated muscle fibers rather than being static in unstimulated conditions and only mobilized upon insulin-stimulation.

2. Similar microscopy analyses of GLUT4-containing vesicles demonstrate that depolymerization of microtubules reduced GLUT4 vesicle movement and impacted insulin-stimulated glucose uptake. Short term depolymerization of microtubules (5 min) did not affect insulin-stimulated glucose uptake, whereas insulin-stimulated glucose uptake was blocked after prolonged depolymerization (2 hrs). The use of a muscle on a chip method to monitor glucose uptake in real time was critical for these experiments.

The changes in glucose uptake were accompanied by changes in the morphologies of intracellular GLUT4-containing structures. The differences between short and long term depolymerization of microtubules support a model in which GLUT4 can be translocated to the plasma membrane by insulin stimulation in the absence of microtubules but an intact microtubule cytoskeleton is required to maintain GLUT4 in a "compartment" that can be recruited by insulin. Stated another way, the microtubule-dependent dynamics of GLUT4-containing vesicles in unstimulated cells is permissive for insulin-stimulated GLUT4 translocation.

3. Knockdown of the microtubule motor protein, Kif5b, blunts insulin-stimulated translocation of GLUT4 to the plasma membrane of cultured muscle cells. These findings agree with previously demonstrated role for Kif5b in adipocytes.

4. In an in vitro model of insulin resistance (incubation of muscle fibers with short chain C2 ceramide) unstimulated and insulin-stimulated GLUT4-containing vesicle movement was blunted and unstimulated and insulin-stimulated microtubule polymerization was reduced.

Weakness of the study include:

1. There are no data supporting a role for insulin regulation of microtubule-dependent GLUT4-containg vesicle movement. The data in Fig.2B do not support a differences in the number of "moving" GLUT4 vesicles between basal and insulin-stimulated fibers. The statement on line 103 that they "observed a ~16% but insignificant increase" to be confusing. These data do not support an effect of insulin on the number of moving GLUT4 vesicles that can be detected in an individual experiment. There is also effect of insulin on GLUT4 vesicles in the data reported in Fig.S2D, Fig.S5B, and Fig.S5F. However, the data in Fig. 2C suggest there was a consistent increase in "moving" vesicles in insulin-stimulated conditions in 4 independent experiments (how are these data normalized?). Because the basis of insulin-regulation of glucose uptake is the control of GLUT4 translocation to the plasma membrane, the authors need to clarify their thinking on why they do not detect insulin robust effects on GLUT4 dynamics in the individual experiments. Is it that they are not measuring the correct parameter? That the assay is not sensitive to the changes?

The small (or no effect) of insulin distracts a bit from the findings that there is microtubule-dependent GLUT4 movement in basal and stimulated muscle fibers, and that disruption of this movement by depolymerization of microtubules or Kif5b knockdown blunts GLUT4 translocation. As noted above, the data strongly support microtubule-dependent GLUT4 dynamics as permissive for insulin-stimulated GLUT4 translocation even if this dynamics might not be a target of insulin action.

2. The analyses of GLUT4-containing structures are not particularly informative. Co-localization with other markers (beyond syntaxin6) are needed to understand these structures. Defining structures as small, medium or large is incomplete. In particular, it is important to probe the microtubule nucleation site clusters for other membrane markers. Transferrin receptor? IRAP?

3. The Kinesore data do not support the authors hypothesis. The data show that Kinesore increases the amount of GLUT4 in the plasma membrane of basal cells and that insulin further increases plasma membrane GLUT4 to the same extent as it does in control cells. How does that provide insight into the role microtubules (or kif5b) in GLUT4 biology? Why does Kinesore increase plasma membrane GLUT4? Is it an effect of Kinesin 1 on GLUT4 vesicles? Kinesore is reported to remodel the microtubule cytoskeleton by a mechanism dependent on Kinesin 1. Is that the reason for the change in GLUT4?

4. The analysis of Kif5b is a bit cursory. Depolymerization of microtubules in muscle fibers essentially blocks all GLUT4 movement (only the insulin condition is shown in Fig.2B but I assume basal would be equally inhibited), and fully inhibits insulin-stimulated glucose uptake in muscle fibers. What are the effects of nocodazole in L6 cells (cell used for kif5b studies) and is it similar in magnitude to kif5b knockdown? Those data would identify there are non-Kif5b microtubule-dependent effects.

5. The authors need to show that the fibers isolated from the HFD mice remain insulin-resistant ex vivo by measuring glucose uptake. It is possible that once removed from the mice they "revert" to normal insulin-sensitivity, which might contribute to the differences reported in Fig5.

6. Although it is interesting that the authors have included the insulin-resistance models/experiments, they are not well developed and therefore the conclusions are not particularly strong.

7. The data do not support the title.

Reviewer #1 (Public Review):

The authors study the control of the timing of Q neuroblast migration, through the precisely timed expression of the Wnt receptor MIG-1/Frizzled, which halts migration of the QR.pa cell at its intended position. Understanding the underlying mechanism is important, as similar mechanisms might play a role in controlling the timing of biological processes in development much more broadly. The authors use precise measurements of mig-1 mRNA molecules, fitted to mathematical models of different mechanisms to control the timing of mig-1 expression, and couple this with experimental perturbations of mig-1 expression. In this way, the authors convincingly show that mig-1 dynamics is best explained by a model where mig-1 expression is controlled by the accumulation of an activator, rather than the degradation of a repressor, which is an important result. In addition, they show that the asymmetric division of QR.p into the larger QR.pa and smaller QR.pp cells is important for proper mig-1 expression in Qr.pa, likely by asymmetric inheritance of the activator. In the process, the authors identify novel conserved binding motifs that are responsible for different aspects of mig-1 dynamics, which will potentially allow identifying the putative activator in the future.

In its current form, I find the manuscript has two main weak points: First, the connection between the experiments and models is relatively weak. Now, the model is mostly used to aid the interpretation of experiments, by predicting rough trends. However, even though the model is in principle fitted to the experimental data in some cases, a detailed comparison between experimental results and the model is often lacking. For example, there are multiple occasions where the data appears to not fit the model in some aspects, but the potential origin of these mismatches is typically not discussed. Second, the authors present experimental evidence of an earlier model prediction, that positive feedback loops in mig-1 expression reduce variability in timing. Here, the authors speculate that this feedback loop might be due to the activation of mig-1 expression by mig-1-induced Wnt signaling, which in itself is an interesting idea. However, the genetic perturbation used here - manipulation of the Wnt pathway, rather than perturbing specifically the induction of mig-1 expression by Wnt signaling - likely changes the expression of many genes in the cell, making it difficult to establish whether the increased variability in Qr.pa position is indeed due breaking the proposed feedback loop.

Reviewer #1 (Public Review)

This paper utilizes two well-established mathematical models of colorectal cancer (CRC) screening to estimate the impact of disruptions in screening caused by the COVID-19 pandemic on long-term outcomes related to CRC. For screening, the authors use two recommendations from the US Preventive Services Task Force (USPSTF) (which were informed by the results of these models): screening colonoscopy every 10 years at ages 50, 60, and 70, and annual fecal immunochemical tests (FIT) from ages 50-75. Separate model runs were performed for 8 different cohorts at the time of the pandemic based on age, screening history, and adherence to screening. For each cohort, microsimulations were performed for 3 different scenarios--no disruption, delays in screening, or discontinuation from screening. The primary outcome was life-years gained (LYG) from screening.

In general, severe prolonged disruptions in any screening led to the largest loss of benefit from screening - for example, unscreened 50-year-olds forced to wait until age 65 (Medicare eligibility) had the largest absolute and relative loss in screening-associated LYG compared to shorter delays of 18 months or less. Losses were also higher in those who were semi-adherent to screening recommendations. The prolonged disruption had a consistently much greater impact than short-term reductions, changes in regimen, or assumptions about test sensitivity. The results are consistent between the two models. The authors point out that, since pandemic-induced disruptions in insurance coverage had a greater impact on minority populations already at risk for reduced access to screening and other preventive services, the pandemic may lead to further exacerbations in existing disparities in CRC incidence and mortality.

The strengths of this paper include the use of well-validated models, the consistent results between the models, the relatively intuitive nature of the findings, and the use of LYG, a commonly used metric for screening recommendations. As the authors point out, estimates of the population impact of the pandemic given the current age structure of the US would be helpful, these would be inherently speculative given the lack of empirical data on pandemic effects on screening. Although prioritizing screening individuals with long pandemic-induced delays is clearly the optimal policy approach, how this might be achieved is unclear.

Reviewer #1 (Public Review):

In this study, the authors use open-access datasets of Neuropixel recordings to explore the relationship between ripple strength and propagation in the septal/dorsal hippocampal pole. They found that the ripple strength correlates with the direction of propagation and that the duration of the events is dependent on the site of initiation. Medial pole ripples are longer and engage significantly more neurons than lateral ripples. These findings may have theoretical and practical implications for the study of sharp-wave ripples, a main oscillatory event underlying memory consolidation. While the approach is not entirely novel (e.g. Patel et al., JN 2013; Kumar and Deshmukh 2020), the study provides some additional insights. The strength of evidence of propagation dynamics is solid and claims are broadly supported. Some points however may require revision. In particular, issues regarding the definition of the longitudinal and transversal axes, as well as additional analysis on microcircuit interactions and neuronal dynamics per cell types and hippocampal sectors should be more thoroughly addressed in support of mechanisms.

Reviewer #1 (Public Review):

Nikolaos Koutras et al shed light on potential distinct functions of the Src family kinases (SFKs) Lck and Lyn in lymphoid signal transduction. The authors therefore overexpress Lyn and ectopic Lck in the B lymphoid cell line BJAB in an elegant Dox-inducible manner and compare the SFK's ability to trigger and shape B-lymphoid signal transduction. The findings indicate that ectopic expression of Lck is sufficient to phosphorylate the B cell receptor (BCR) ITAMs in BJAB cells. In these cells, constitutive ITAM and ITIM phosphorylation by both overexpressed Lck and Lyn induces BCR signaling, as demonstrated by phosphorylation of Syk and Akt, as well as CD22 inhibitory signaling, as shown by SHP-1 phosphorylation. In direct comparison, the influence of Lyn on said phosphorylation is stronger when it is (over-)expressed in the same amounts as Lck. This outcome was somewhat expected, since ITIM/ITAM phosphorylation is considered to be the principal function of Lyn in B cells.

The study finds Lyn to be degraded more efficiently via the proteasome and to be more tightly controlled by phosphatases when compared to Lck. However, rather than interpreting the findings as distinct kinase-intrinsic properties, one could attribute the slower degradation and stricter PTP control of Lyn to the fact that Lyn is the principal and predominant SFK in B cells and thus a "standard target" of the B-lymphoid molecular machinery, to which it is better adapted to.

Next, the authors present a RNAseq transcriptome analysis of Lck- and Lyn-expressing B cells and validate selected findings via qPCR. The data show Lyn and Lck to regulate pathways and biological functions of critical importance to B lymphocytes. Generally, most of the Lck/Lyn-regulated biological functions and pathways shown here (antigen presentation, cytokine production, migration, apoptosis, autophagy, etc.) are well known to be controlled by BCR signaling, which the overexpression of SFKs are constitutively activating, as shown earlier. While the authors draw a Venn diagram depicting differentially regulated transcripts between Lck- and Lyn-expressing cells, it does not seem like Lck is able to regulate pathways which are not "canonically" regulated by Lyn. There is also the persisting problem of Lck being expressed to a much higher extent and the effect of the endogenously expressed Lyn, since the model systems are not based on a Lyn-deficient cell line.

Lastly, the authors follow up their finding of deregulated transcripts belonging to the ER/UPR ontology cluster. Flow cytometric analysis indeed shows an influence of Lck and Lyn expression on ER homeostasis, which can be reverted with SFK inhibitors. Alas, additional follow-up experiments to functionally investigate the deregulated pathways suggested by the RNAseq analysis are not included in this study.

While there definitely are implications for the role of ectopic expression of Lck in CLL cells, this work however presents no direct comparison of expression strength or signaling outcomes between the study's BJAB (Burkitt lymphoma) cell line-based model and a model of CLL - be it a mouse model, human patient samples or a CLL cell line. Since the B-lymphoid cell line used, the Burkitt lymphoma line BJAB, is not CLL-derived, the conclusions that can be drawn for the pathophysiology of CLL is limited.

In principal, the authors show that the Src kinase Lck - when ectopically expressed - largely fills out the role of the predominant B-lymphoid Src kinase Lyn, namely phosphorylation of the CD79-ITAMs and induction of constitutive antigen receptor signaling. Given that the established role of Lck is the phosphorylation of ITAMs and activation of the T cell receptor in T cells, where it is predominantly expressed, these findings provide limited advancement of our current understanding of antigen receptor signal transduction. As a distinct functional difference between Lck and Lyn is not established in this work, said SFKs' largely exclusive expression in T and B cells remains enigmatic.

Reviewer #1 (Public Review):

Members of the SLC11/NRAMP family of transporters permit the movement of transition metals across cell membranes in all kingdoms of life. The current study builds off previous structural and mechanistic work on the SLC11/NRAMP family of transporters by Manatschal and colleagues reported in eLife; the current study presents a cryo-EM structure of a plant aluminum (Al3+) transporter that combats aluminum toxicity in soil. The structure was not determined in the presence of added metal ions, so the paper also employs a variety of established functional assays to test the effects of mutating suggested binding site residues. One notable result is the identification of a mutation (S68A) that maintains divalent transport but disrupts trivalent binding/transport. Strengths of the manuscript include the extensive legwork required to identify a combination of plant homologue, cameloid nanobody, and amphipol that is required to provide homogenous protein and interpretable cryo-EM data. The cryo-EM maps are reliable with low orientation bias and clear features. In addition, the authors perform a number of biochemical and transport assays with divalent metals to bolster their structural model.

Reviewer #1 (Public Review):

In this paper the authors are estimating the amount of transmission (via the force of infection) of EV-D^8 in England. The strengths of the study are the use of serological data for understanding underlying transmission, and the assessment of the sensitivity of the conclusions to the seropositivity cut off and the model form used. The weaknesses are the data not being annually and the lack of link to HFMD cases,, but these do not detract from the conclusions that can be drawn from the paper. The results do support the conclusions.

Reviewer #1 (Public Review):

In this paper, the authors developed a method that allows one to test a large number of drug combinations in a single cell culture sample. In principle, the experiments rely on the randomness of drug uptake in individual cells as a tool to create and encode drug treatments. They used a single sample containing thousands of cells treated with a combination of fluorescent barcoded drugs, and created transient drug gradients. They also developed segmentation- free image analysis capable of handling optical fields with a substantial number of cells. The major strength of this work is the demonstration of the feasibility of testing drug combinations in a relatively straightforward manner that could be used by many laboratories. As such this paper could have a significant impact on the early drug discovery of combinatorial therapy. One of the weaknesses in this manuscript is the absence of studies beyond just HeLa cells. In addition, the phenotype tested is cell death, which might limit the application to other drug interactions that might look at other phenotypes; e.g inhibition of cell proliferation or changes in differentiation phenotypes. Finally, there is a basic assumption that drug leakage does not occur or is minimal, but secondary uptake of the drug is likely and may not be homogeneous. Notwithstanding, the approach is feasible and likely will be applied in several laboratories.

Reviewer #1 (Public Review):

In this manuscript, Nocka and colleagues reveal a novel layer of regulation of the Btk tyrosine kinase, a key signaling protein in B lymphocyte signaling and an important drug target with 3 recently FDA-approved drugs, by the SH3-SH2 domain-containing adaptor protein Grb2. The authors nicely demonstrate a critical role of the interaction of the Grb2 SH3 domains with the Pro-rich linker C-terminal to the Btk PH-TH domains on membranes for full kinase activation of Btk. Hence this interaction recruits Btk to scaffold-mediated signaling clusters.

This is a technically sound paper with high-quality experiments. The manuscript is easy to follow and excellently written. The findings are novel and of high relevance towards a complete understanding of Btk regulation and signaling in cancer and normal cells.

Reviewer #1 (Public Review):

The study by Oikawa and colleagues demonstrates for the first time that a descending inhibitory pathway for nociception exists in non-mammalian organisms, such as Drosophila. This descending inhibitory pathway is mediated by a Drosophila neuropeptide called Drosulfakinin (DSK), which is homologous to mammalian cholecystokinin (CCK). The study creates and uses several Drosophila mutants to convincingly show that DSK negatively regulates nociception. They then use several sophisticated transgenic manipulations to demonstrate that a descending inhibitory pathway for nociception exists in Drosophila.

Strengths:

This study creates the possibility of using Drosophila to study descending nociceptive systems.

CRISPR/Cas9 is used to generate mutants of dsk, CCKLR-17D1, and CCKLR-17D3. The authors then use these mutants to clearly show that DSK negatively regulates nociception.

Several GAL4s are used to clearly show that these effects are likely mediated by two sets of neurons in the brain, MP1 and Sv.

RNAi and rescue experiments further show that CCKLR-17D1, a DSK receptor, functions in Goro neurons to negatively regulate nociception.

Thermogenetic experiments nicely show that activation of DSK neurons attenuates the nociceptive response.

Weaknesses:

A minor weakness in the study is that it is unclear how DSK negatively regulates nociception. An earlier study at the Drosophila nmj shows that loss of DSK signaling impairs neurotransmission and synaptic growth. In the current study, loss of CCKLR-17D1 in Goro neurons seems to increase intracellular calcium levels in the presence of noxious heat. An interesting future study would be the examination of the underlying mechanisms for this increase in intracellular calcium.

Reviewer #1 (Public Review):

Chan et al. tried identifying the binding sites or pockets for the KCNQ1-KCNE1 activator mefenamic acid. Because the KCNQ1-KCNE1 channel is responsible for cardiac repolarization, genetic impairment of either the KCNQ1 or KCNE1 gene can cause cardiac arrhythmia. Therefore, the development of activators without side effects is highly demanded. Because the binding of mefenamic acid requires both KCNQ1 and KCNE1 subunits, the authors performed drug docking simulation by using KCNQ1-KCNE3 structural model (because this is the only available KCNQ1-KCNE structure) with substitution of the extracellular five amino acids (R53-Y58) into D39-A44 of KCNE1. That could be a limitation of the work because the binding mode of KCNE1 might differ from that of KCNE3. Still, they successfully identified some critical amino acid residues, including W323 of KCNQ1 and K41 and A44 of KCNE1. They subsequently tested these identified amino acid residues by analyzing the point mutants and confirmed that they attenuated the effects of the activator. They also examined another activator, yet structurally different DIDS, and reported that DIDS and mefenamic acid share the binding pocket, and they concluded that the extracellular region composed of S1, S6, and KCNE1 is a generic binding pocket for the IKS activators.

The data are solid and well support their conclusions, although there are a few concerns regarding the choice of mutants for analysis and data presentation.

Other comments:

1. One of the limitations of this work is that they used psKCNE1 (mostly KCNE3), not real KCNE1, as written above. It is also noted that KCNQ1-KCNE3 is in the open state. Unbinding may be facilitated in the closed state, although evaluating that in the current work is difficult.<br /> 2. According to Figure 2-figure supplement 2, some amino acid residues (S298 and A300) of the turret might be involved in the binding of mefenamic acid. On the other hand, Q147 showing a comparable delta G value to S298 and A300 was picked for mutant analysis. What are the criteria for the following electrophysiological study?<br /> 3. It is an interesting speculation that K41C and W323A stabilize the extracellular region of KCNE1 and might increase the binding efficacy of mefenamic acid. Is it also the case for DIDS? K41 may not be critical for DIDS, however.<br /> 4. Same to #2, why was the pore turret (S298-A300) not examined in Figure 7?

Title: How Alive Is 1.5? Part One – A Small Budget, Shrinking Fast

Author: - Kevin Anderson - Dan Calverley

Key Messages - For a 50:50 chance of staying below 1.5°C, we’re using up the remaining carbon budget at around 1% every month. - Following current national emissions pledges (NDCs) to 2030 puts the temperature commitments within the Paris Agreement beyond reach. - Claims that 1.5°C is now inevitable also assign “well below 2°C” to the scrapheap. - An ‘outside chance’ of not exceeding 1.5°C remains viable, but ongoing fossil fuel use is rapidly undermining it. - The few credible pathways for an outside chance of 1.5°C are not being discussed. This is an active choice by policymakers and experts, who have largely dismissed equity-based social change.

Reviewer #1 (Public Review):

This is a valuable study demonstrating convincingly that PI3K signaling lies downstream of Pdgfra signaling in zebrafish cardiomyocyte progenitors as they undergo latero-medial migration and midline fusion, essential for heart tube formation, likely via chemotaxis. Whereas the authors used both multiple inhibitory drugs and dominant negative transgene expression to interrupt PI3K expression, with findings strongly aligning, the manuscript would have been stronger if genetic approaches were used to complement the above approaches. Nonetheless, the impact of dnPI3K inhibition allowed the authors to suggest that the effects were cell autonomous to migrating cardiomyocytes. The authors used contemporary live imaging techniques allowing quantification of key cell behaviors, and this is a strength of the paper. There are some issues about the inter-study alignment of trajectory data that need to be addressed. Perhaps the most conspicuous weakness is that the authors have not advanced the model for cardiomyocyte migration beyond adding the involvement of PI3K downstream of Pdgfra, which is to a significant degree expected. The recording of cardiomyocyte protrusions biased in their orientation towards the direction of migration, which is lost in the mutants, is an interesting advance, although it was not shown whether protrusions are causally related to migration.

Reviewer #1 (Public Review):

This manuscript addresses the important and understudied issue of circuit-level mechanisms supporting habituation, particularly in pursuit of the possible role of increases in the activity of inhibitory neurons in suppressing behavioral output during long-term habituation. The authors make use of many of the striking advantages of the larval zebrafish to perform whole brain, single neuronal calcium imaging during repeated sensory exposure, and high throughput screening of pharmacological agents in freely moving, habituating larvae. Notably, several blockers/antagonists of GABAA(C) receptors completely suppress habituation of the O-bend escape response to dark flashes, suggesting a key role for GABAergic transmission in this form of habituation. Other substances are identified that strikingly enhance habituation, including melatonin, although here the suggested mechanistic insight is less specific. To add to these findings, a number of functional clusters of neurons are identified in the larval brain that has divergent activity through habituation, with many clusters exhibiting suppression of different degrees, in line with adaptive filtration during habituation, and a single cluster that potentiates during habituation. Further assessment reveals that all of these clusters include GABAergic inhibitory neurons and excitatory neurons, so we cannot take away the simple interpretation that the potentiating cluster of neurons is inhibitory and therefore exerts an influence on the other adapting (depressing) clusters to produce habituation. Rather, a variety of interpretations remain in play.

Overall, there is great potential in the approach that has been used here to gain insight into circuit-level mechanisms of habituation. There are many experiments performed by the authors that cannot be achieved currently in other vertebrate systems, so the manuscript serves as a potential methodological platform that can be used to support a rich array of future work. While there are several key observations that one can take away from this manuscript, a clear interpretation of the role of GABAergic inhibitory neurons in habituation has not been established. This potential feature of habituation is emphasized throughout, particularly in the introduction and discussion sections, meaning that one is obliged as a reader to interrogate whether the results as they currently stand really do demonstrate a role for GABAergic inhibition in habituation. Currently, the key piece of evidence that may support this conclusion is that picrotoxin, which acts to block some classes of GABA receptors, prevents habituation. However, there are interpretations of this finding that do not specifically require a role for modified GABAergic inhibition. For instance, by lowering GABAergic inhibition, an overall increase in neural activity will occur within the brain, in this case below a level that could cause a seizure. That increase in activity may simply prevent learning by massively increasing neural noise and therefore either preventing synaptic plasticity or, more likely, causing indiscriminate synaptic strengthening and weakening that occludes information storage. Sensory processing itself could also be disrupted, for instance by altering the selectivity of receptive fields. Alternatively, it could be that the increase in neural activity produced by the blockade of inhibition simply drives more behavioral output, meaning that more excitatory synaptic adaptation is required to suppress that output. The authors propose two specific working models of the ways in which GABAergic inhibition could be implemented in habituation. An alternative model, in which GABAergic neurons are not themselves modified but act as a key intermediary between Hebbian assemblies of excitatory neurons that are modified to support memory and output neurons, is not explored. As yet, these or other models in which inhibition is not required for habituation, have not been fully tested.

This manuscript describes a really substantial body of work that provides evidence of functional clusters of neurons with divergent responses to repeated sensory input and an array of pharmacological agents that can influence the rate of a fundamentally important form of learning.

Reviewer #1 (Public Review):

Rosas et al studied the mechanism/s that enabled carbapenems resistance of a Klebsiella isolate, FK688, which was isolated from an infected patient. To identify and characterize this mechanism, they used a combination of multiple methods. They started by sequencing the genome of this strain by a combination of short and long read sequencing. They show that Klebsiella FK688 does not encode a carbapenemase, and thus looked for other mechanisms that can explain this resistance. They discover that both DHA-1 (located on the mega-plasmid) and an inactivation of the porin OmpK36, are required for carbapenem resistance in this strain. By using experimental evolution, it was shown that resistance is lost rapidly in the absence of antibiotics selection, by a deletion in pNAR1 that removed blaDHA-1. Moreover, their results suggested that it is likely that exposure to other antibiotics selected for the acquisition of the mega-plasmid that carries DHA-1, which then enabled this strain to gain resistance to carbapenemase by a single deletion.

The major strength of this study is the use of various approaches, to tackle an important and interesting problem.

The conclusions of this paper are mostly well supported by data, but one aspect is not clear enough. The description of the evolutionary experiment is not clear. I could not find a clear description of the names of the evolved populations. However, the authors describe strains B3 and A2, but their source is not clear. The legends of the relevant figure (Figure 5) are confusing. For example, the text describing panel B is not related to the image shown in this panel. Moreover, it is shown in panel C (and written in the main text) that the OmpK36+ evolved populations had only translucent colonies, so what is the source of B3(o)?

Reviewer #1 (Public Review):

The glideosome-associated connector is an essential piece of the machinery used by the apicomplexa parasites as they invade host cells. This GAC makes important interactions with the membrane and with actin during this process. Here, Kumar et al present the first structure of the GAC from T. gondii, showing a complex fold in a closed form. This structure was determined at pH 5, and they show that at more physiological pH values the structure is far more open. However, this is not in the context of actin, membrane, or other binding partners, and so the question remains about how open the structure is in its physiological context. The authors next use molecular dynamics, NMR, and mutagenesis to identify the residues involved in membrane binding and also assess actin binding through modelling which is not validated by experiment. This paper presents an important contribution to our understanding of the molecular machinery involved in host cell invasion but leaves many questions remaining about how this protein links to the cytoskeleton and functions during the invasion process.

• The structure of TgGAC provides the first such structure of this complex and is an important contribution to our understanding. The structure presented in Figure 1A is a composite, containing the crystal structure of the majority of the protein, determined at pH 5, to which has been docked the PH domain structure, determined by NMR. It would be good to see more clarity in the figure about what is experimentally determined and what is modelled.<br /> • SAXS data shows that, at pH 8, a substantial fraction of the protein is in a very extended conformation, which differs significantly from the compact structure seen in crystals at pH 5. I would prefer to see the models in Figure 2d represented as spheres or surfaces, to prevent over-interpretation associated with showing models with low-resolution data. However, the SAXS findings are robust and this is clearly a dynamic molecule in solution. It will be interesting to see what the situation is in the context of binding partners.<br /> • Molecular dynamic simulations next indicate the region which binds to a lipid bilayer, with contact residues forming a consistent interaction surface in three independent simulations. This identified the PH domain and neighbouring residues as the membrane interaction surface.<br /> • Switching to Plasmodium falciparum protein, the authors next use NMR to investigate the binding of the PH domain to membrane nanodiscs, and show that the same protein region identified in the MD simulations was found to bind in the NMR experiments.<br /> • These membrane binding assays were then followed up through liposome pelleting assays, using TgGAP, which showed that the protein only pellets in the presence of PA lipid and that mutation of residues identified through NMR abolished liposome binding. The mutations didn't have the same effect on full-length and PH domains (noting KER for example) suggesting that lipid binding is not entirely mediated by the PH domain in the full-length protein.<br /> • The authors next put the mutants into toxoplasma and assay the effect on apical localisation and on invasion percentage. Interestingly the mutants had little effect, perhaps due to the role of other regions of the GAC on lipid binding, suggesting that abolishing PH domain lipid binding is not sufficient. Unfortunately, as the mutations only partly reduced lipid binding in the context of full-length GAC, as shown in liposome experiments, it is hard to come to a firm conclusion about the importance of lipid binding from this data as the protein used in this experiment will still have partial lipid binding properties.<br /> • The authors next investigate actin binding by TgGAC and show that most of the N-terminal half of the protein is required for this function. The authors propose, using AlphaFold2 and similarities to catenins, how GAC might bind to actin. In the absence of any validation from experimental data, caution is needed here, and I would personally not rely on the accuracy of these models.

Reviewer #1 (Public Review):

During the height of the Covid19-pandemic, there was great and widely spread concern about the lowered protection the screening programs within the cancer area could offer. Not only were programs halted for some periods because of a lack of staff or concern about the spreading of SARS CoV2. When screening activities were upheld, participation decreased, and follow-up of positive test results was delayed. Mariam El-Zein and coworkers have addressed this concern in the context of cervical screening in Canada, one of the rather few countries in the world with well organized, population-based, although regionalized, cervical screening program.

Despite the existence of screening registries, they choose to do this in form of a survey on the internet, to different professional groups within the chain of care in cervical screening and colposcopy. The reason for taking this "soft data" approach is somewhat diffuse. The authors claim they want to "capture modifications". However, the suggestions that come from this study are limited and are submitted for publication 2 years after the survey when the height of the pandemic has passed long since, and its burden on the screening program has largely disappeared. The value of the study had been larger if either the conclusions had been communicated almost directly, or if the survey had been done later, to sum up the total effect of the pandemic on the Canadian cervical screening program.

Another major problem with this study is the coverage. The results of persistent activities to get a large uptake is somewhat depressing although this is not expressed by the authors. 510 professionals filled out the survey partially or in total. 10 professions were targeted. The authors make no attempt to assess the coverage or the validity of the sample. They state the method used does not make that possible. But the number of family practicians, colposcopists, cytotechnicians, etc. involved in the program should roughly be known and the proportion of those who answered the survey could have been calculated. My guess is that it is far below 10%. Also, the national distribution seems shewed despite the authors boosting its pan-Canadian character. I am just faintly familiar with the Canadian regions, but, as an example, only 2 replies from Quebec must question the national validity of this survey.

The result section is dominated by quantitative data from the responses to the 61 questions. All questions and their answers are tabulated. As there is no way to assess the selection bias of the answers these quantitative results have no real value from an epidemiological standpoint. The replies to the open-ended questions are summarized in a table and in the text. The main conclusion of the content analysis of the answers to the direct questions, and one of the main conclusions of the study, is that the majority favors HPV self-sampling in light of the pandemic. However, this not-surprising view is taken by only 80 responders while almost as many (n=60) had no knowledge about HPV self-sampling.

The authors conclude that their study identified the need for recommendations and strategies and building resilience in the screening system. No one would dispute the need, but the additional weight this study adds, unfortunately, is low, from a scientific standpoint.

The conclusion I draw from this study is that the authors have done a good job in identifying some possible areas within the Canadian screening programs where the SARS-Cov2 pandemic had negative effects and received some support for that in a survey. Furthermore, they listed a few actions that could be taken to alleviate the vulnerability of the program in a future similar situation, and received limited support for that. No more, no less.

Reviewer #1 (Public Review):

OTOP ion channels are proton-activated, proton-permeable proteins that participate in sour tasting but for which other physiological roles are just beginning to be elucidated. The authors of this manuscript noticed that the isoform OTOP3 shows activation by protons that are potentiated in the presence of Zn2+ and other divalent ions, while other isoforms are not weakly or not at all potentiated. This allowed them to apply a chimeric approach to define which regions of the protein are responsible for the Zn2+ effect. The authors found that a single extracellular loop and a single histidine residue located in it are sufficient to explain the potentiation and propose that this histidine is part of a binding site that allosterically couples to yet undefined proton binding sites(s) responsible for proton gating.

The authors have performed very high-quality experiments and carried out a careful analysis of the data. This characterization of gating behavior of OTOP channels should be a step in elucidating physiological roles and in understanding the dynamics of these proteins. For these reasons, it should be of interest to researchers working in molecular biophysics and the physiological roles of ion channels.

Reviewer #1 (Public Review):

In this study, the authors set out to determine the degree to which early language experience affects neural representations of concepts. To do so, they use fMRI to measure responses to 90 words in adults who are deaf. One group of deaf adults (n=16) were native signers (and thus had early language exposure); a second group (n=21) was exposed to sign language later on. The groups were relatively well-matched in other respects. The primary finding was that the high dimensional representations of concepts in the left lateral anterior temporal lobe (ATL) differed between native and delayed signers, suggesting a role for early language experience in concept representation.

The analyses are carefully conducted and reflect a number of thoughtful choices. These include the "inverted MDS" method for constructing semantic RDMs, a normal hearing comparison group for both behavioral and fMRI data, and care taken to avoid bias in defining functional ROIs. And, comparing early and delayed signing groups is a clever way to study the role of early language experience on adult language representations.

One interesting result that I struggled to put in a broader context relates to the disconnect between behavioral and neural results. Specifically, the behavioral semantic RDMs (Figure 1a) did not differ between any of the groups of participants. This suggests that the representations of the 90 concepts are represented similarly in all of the participants. However, the similarity of the neural RDMs in left lateral ATL differs between the native and delayed signing groups (but not in other regions). Given the similarity of the behavioral semantic RDMs, it is unclear how to interpret the difference in left lateral ATL representations. In other words, the neural differences in left ATL do not affect behavior (semantic representation). The importance of the differences in neural RDMs is therefore questionable.

An important point is that, if I understand correctly, the semantic space is defined by the 90 experimental items. That is, behavioral RDMs were created by having normal hearing participants arrange 90 items spatially, and neural RDMs were created by comparing patterns of responses to these 90 experimental items. This 90-dimensional space is thus both (a) lower dimensional than many semantic space models that include hundreds of directions and (b) constrained by the specific 90 experimental items chosen. On the one hand, this seems to limit the generalizability of the findings for semantic representations more broadly.

The logic behind using a categorical semantic RDM (e.g., Figure 2a) was not clear. The behavioral semantic RDMs (Figure 1a) clearly show gradations in dissimilarity, particularly for the abstract categories. It would seem that using the behavioral semantic RDM would capture a more accurate representation of the semantic space than the categorical one.

Reviewer #1 (Public Review):

In this paper, the authors present a method for discovering response properties of neurons, which often have complex relationships with other experimentally measured variables, like stimuli and animal behaviors. To find these relationships, the authors fit neural data with artificial neural networks, which are chosen to have an architecture that is tractable and interpretable. To interpret the results, they examine the first- and second-order approximations of the fitted artificial neural network models. They apply their method profitably to two datasets.

The strength of this paper is in the problem it is attempting to solve: it is important for the field to develop more useful ways to analyze and understand the massive neural datasets collected with modern imaging techniques.

The weaknesses of this paper lie in its claims (1) to be model free and (2) to distinguish the method from prior methods for systems identification, including spike triggered averaging and covariance (or rather their continuous response equivalents). On the first claim, the systems identification methods are arguably substantially more model free approach. On the second claim, this reviewer would require more evidence that the presented approach is substantially different from or an improvement on systems identification methods in common use applied directly to the data.

Reviewer #1 (Public Review):

Li et al investigated the behavioral response and fMRI activations associated with deep brain stimulation (DBS) of the lateral habenula (LHb) in 2 distinct rodent models of depression. They found that a) LHb DBS reduces depressive and anxiety behaviors using multiple behavioral tests: sucrose preference, forced swim, and open field. These results held across multiple models of depression and multiple tests, and generally restored results of these behavioral tests to parity with controls. Furthermore, fMRI activations of brain regions with known connectivity to LHb strongly correlated with behavioral responses to LHb DBS, particularly in limbic regions. These behavioral responses clearly depended on electrode location, with more medial placements within the LHb producing a more robust behavioral effect.

The conclusions of this paper are generally well supported by the data, with the primary weaknesses of the study being 1) limited novelty due to LHb already being a well-established target for DBS in depression, and 2) the questionable validity of rodent models of depression in general. The authors deal with the first point (novelty) by extending their study to electrode localization and fMRI correlates with the behavioral response, leading to insight into surgical targeting as well as mechanism of effect, respectively. They also partially mitigate fundamental problems with rodent models of depression by using 2 different models and showing consistent responses to LHb DBS across both. The methods used in this study were sound, with high-quality techniques used for electrode implantation, confirmation of electrode placement, fMRI acquisition, anesthesia and physiological monitoring, as well as an appropriate statistical analytic approach.

Reviewer #1 (Public Review):

Chromosomal aneuploidy in humans causes diseases such as Down syndrome associated with changes in cognitive and metabolic activities, but how extra copies of chromosomes cause the changes remains largely unknown. In this important paper, the authors characterized the metabolisms and physiology of the transgenic mouse with most of human chromosome 21 thoroughly and nicely showed the overexpression of sarcolipin which uncouples Ca2+ import with ATP hydrolysis of sarcoplasmic reticulum Ca2+ ATPase (SERCA), which results in heat production and hyperactive mitochondria activity.