Reviewer #1 (Public Review):

This work describes a new method, Proteinfer, which uses dilated neural networks to predict protein function, using EC terms and GO terms. The software is fast and the server-side performance is fast and reliable. The method is very clearly described. However, it is hard to judge the accuracy of this method based on the current manuscript, and some more work is needed to do so.

I would like to address the following statement by the authors: (p3, left column): "We focus on Swiss Prot to ensure that our models learn from human-curated labels, rather than labels generated by electronic annotation".

There is a subtle but important point to be made here: while SwissProt (SP) entries are human-curated, they might still have their function annotated ("labeled") electronically only. The SP entry comprises the sequence, source organism, paper(s) (if any), annotations, cross-references, etc. A validated entry does not mean that the annotation was necessarily validated manually: but rather that there is a paper backing the veracity of the sequence itself, and that it is not an automatic generation from a genome project.<br /> Example: 009L_FRG3G is a reviewed entry, and has four function annotations, all generated by BLAST, with an IEA (inferred by electronic annotation) evidence code. Most GO annotations in SwissProt are generated that way: a reviewed Swissprot entry, unlike what the authors imply, does not guarantee that the function annotation was made by non-electronic means. If the authors would like to use non-electronic annotations for functional labels, they should use those that are annotated with the GO experimental evidence codes (or, at the very least, not exclusively annotated with IEA). Therefore, most of the annotations in the authors' gold standard protein annotations are simply generated by BLAST and not reviewed by a person. Essentially the authors are comparing predictions with predictions, or at least not taking care not to do so. This is an important point that the authors need to address since there is no apparent gold standard they are using.

The above statement is relevant to GO. But since EC is mapped 1:1 to GO molecular function ontology (as a subset, there are many terms in GO MFO that are not enzymes of course), the authors can easily apply this to EC-based entries as well.

This may explain why, in Figure S8(b), BLAST retains such a high and even plateau of the precision-recall curve: BLAST hits are used throughout as gold-standard, and therefore BLAST performs so well. This is in contrast, say to CAFA assessments which use as a gold standard only those proteins which have experimental GO evidence codes, and therefore BLAST performs much poorer upon assessment.

Pooling GO DAGs together: It is unclear how the authors generate performance data over GO as a whole. GO is really 3 disjoint DAGs (molecular function ontology or MFO, Biological Process or BPO, Cellular component or CCO). Any assessment of performance should be over each DAG separately, to make biological sense. Pooling together the three GO DAGs which describe completely different aspects of the function is not informative. Interestingly enough, in the browser applications, the GO DAG results are distinctly separated into the respective DAGs.

Figure 3 and lack of baseline methods: the text refers to Figures 3A and 3B, but I could only see one figure with no panels. Is there an error here? It is not possible at this point to talk about the results in this figure as described. It looks like Figure 3A is missing, with Fmax scores. In any case, Figure 3(b?) has precision-recall curves showing the performance of predictions is the highest on Isomerases and lowest in hydrolases. It is hard to tell the Fmax values, but they seem reasonably high. However, there is no comparison with a baseline method such as BLAST or Naive, and those should be inserted. It is important to compare Proteinfer with these baseline methods to answer the following questions: (1) Does Proteinfer perform better than the go-to method of choice for most biologists? (2) does it perform better than what is expected given the frequency of these terms in the dataset? For an explanation of the Naive method which answers the latter question, see: (https://www.nature.com/articles/nmeth.2340)

Reviewer #1 (Public Review):

In the present study, Ibáñez-Solé1 et al evaluate transcriptional noise across aging and tissues in several publicly available mouse and human datasets.  Initially, the authors compare 4 generalized approaches to quantify transcriptional noise across cell types and later implement a new approach which uses iterative clustering to assess cellular noise.  Based on implementation of this approach (scallop), the authors survey noise across seven sc-seq datasets relevant for aging.  Here, the authors conclude that enhanced transcriptional noise is not a hallmark of aging, rather changes in cell identity and abundances, namely immune and endothelial cells.  The development of new tools to quantify transcriptional noise from sc-seq data presents appeal, as these datasets are increasing exponentially.  Further, the conclusion that increased transcriptional noise is not a defined aspect of aging is clearly an important contribution; however, given the provocative nature of this claim, more comprehensive and systematic analyses should be performed.  In particular, the robustness and appeal of scallop is still not sufficiently demonstrated and given the complexity  (multiple tissues, species and diverse relative age ranges) of datasets analyzed, a more thorough comparison should be performed.  I list a few thoughts below:

Initially, the authors develop Decibel, which centralizes noise quantification methods. The authors provide schematics shown in Fig 1, and compare noise estimates with aging in Fig 2 - Supplement 2.   Since the authors emphasize the necessary use of scallop as a "better" pipeline, more systematic comparisons to the other methods should be made side-by-side.  For example, scallop noise estimates (Fig 2) compared to other euclidean distance-based measures (Fig 2 supplement 2) looks fairly similar.  Are downstream observations (ex lung immune composition changes more than noise) supported from these methods as well?  If so, this would strengthen the overall conclusion on noise with age, but if not, it would be relevant to understand why.

Similarly, the 'validation of scallop seems mostly based on the ability to localize noisy vs stable cells in Fig 1 supplement 1 and relative robustness within dataset to input parameters (Fig 1 supplement 2).  A more systematic analysis should be performed to robustly establish this method.  For example, noise cell clustering comparisons across the 7 datasets used.  In addition, the Levy et all 2020 implemented a pathway-based approach to validate.  Specifically, surrogate genes were derived from GCL value where KEGG preservation was used as an output.  Similar additional types of analyses should be performed in scallop 

The conclusion that immune and endothelial cell transcriptional shifts associate more with age than noise are quite compelling, but seem entirely restricted to the mouse and human lung datasets.  It would be interesting to know if pan-tissues these same cell types enrich age-related effects or whether this phenomenon is localized

Related to these, there does not seem to be a specific rationale for why these datasets (the seven used in total or the lung for deep-dive), were selected.  Clearly, many mouse and human sc-RNA-seq datasets exist with large variations in age so expanding the datasets analyzed and/or providing sufficient rationale as to why these ones are appearing for noise analyses would be helpful. For example, querying "aging" across sc-seq datasets in Single cell portal yields 79 available datasets: https://singlecell.broadinstitute.org/single_cell?type=study&page=1&terms=aging&facets=organism_age%3A0%7C103%7Cyears

The analysis that noise is indistinguishable from cell fate shifts is compelling, but again relies on one specific example where alternative surfactant genes are used as markers.  The same question arises if this observation holds up to other cell types within other organs.  For example the human cell atlas contains over dozens of tissue with large variations in age (https://www.science.org/doi/10.1126/science.abl4290).

Reviewer #1 (Public Review):

Xian et al. systematically evaluated age and sex-dependent differences in paw skin and sciatic nerves (SCN) tissues of naïve mice, utilizing DIA-PASEF, a highly sensitive and reproducible proteomics approach. The authors demonstrated that the deep proteome profiling enabled a discovery of significant differences between male and female mice and adolescent and adult mice such as homeostasis and epidermal signaling in skin and, myelination and neuronal development in SCN that are known to be relevant to the pathophysiology. The authors claim the need for the appropriate age and sex matching in the experiment design and suggest the work as a unique systems biology proteome resource in mouse disease model. As I understand this is the first attempt to molecularly characterize the impact of mouse age and sex that would help warrant the reproducibility of the preclinical research.

Reviewer #1 (Public Review):

This manuscript reports the results of studies on the effects of an ActRIIB-Fc ligand trap inhibitor of myostatin on muscle contractures that develop when brachial plexus nerve roots are severed at 6 after birth. One component of this pathological response seems to be a failure to add sarcomeres as the skeleton grows resulting in short muscles. The authors use a carefully performed set of animal studies to test the effects of the ligand trap on denervation-induced limitations in range of motion in young mice. They also investigate several biochemical mechanisms that might contribute to contractures and be modified by the ligand trap. Finally, the test for gender discordance in the protective effect of a proteasome inhibitor against contractures. The major finding of these studies is that the ligand trap improved the range of motion at the elbow and shoulder in female mice but not in males. The major caveat to interpreting the data is that group sizes are relatively small such that the study may have been underpowered to detect smaller effects on a range of motion and biochemical endpoints.

Joint Public Review:

Tiedemann et al. evaluated the neural response to insulin before and after a 3-month caloric restriction diet compared to an active waiting group in 50 elderly persons overweight and with obesity. Peripheral insulin sensitivity and central insulin sensitivity of the mesolimbic reward circuitry predicted weight loss success and improvement after caloric restriction. This is the first longitudinal study showing an improvement in central insulin sensitivity in humans.

Strengths<br /> The major strength of the paper is the longitudinal study design in persons at high risk to develop type 2 diabetes with multiple fMRI visits, with a state-of-the-art fMRI design. Moreover, the study uses a placebo-controlled approach to evaluate insulin sensitivity in the brain. Another strength is the fact the control group is an active waiting group, which means that they received dietary counselling after the study and additionally benefited from the study by receiving training courses on stress management.

Weakness<br /> A weakness of the study is the lack of metabolic assessments of the participants. Only fasting blood samples were available. No oral glucose tolerance test or hyperinsulinemic-euglycemic clamps were acquired to quantify peripheral or whole-body insulin resistance. Whether peripheral insulin sensitivity and central insulin sensitivity are, in fact, independently involved in the success or treatment outcome of intervention still needs to be validated in future studies.<br /> Another weakness is the food cue picture set implemented in the study. The different categories of pictures were not carefully matched for psychological and physical variables (such as the complexity of a picture). This could potentially influence neural food cue reactivity.<br /> The study evaluated the regional BOLD response of the reward circuitry showing that insulin signaling in the VTA and nucleus accumbens play an important role in successful weight loss. The role of insulin signaling on projections (or connectivity) of the mesolimbic reward circuitry was not evaluated in the current study.

Reviewer #1 (Public Review):

This manuscript discusses evolutionary patterns of manipulation of others' allocation of investment in individual reproduction relative to group productivity. Three traits are considered: this investment, manipulation of others' investment, and resistance to this investment. The main result of the manuscript is that the joint evolution of these traits can lead to the maintenance of diversity through, as documented here, cyclic (or noisier) dynamics. Although there are some analytical results, this main conclusion is instead supported by individual-based simulations, which seem correctly performed (but for clonal populations, as emphasized below).

There could be material for a good paper here but the organization of the manuscript makes it difficult to fully evaluate. The narrative is highly condensed, with the drawbacks that this often entails in terms of accurately conveying the results of a study, as illustrated here by the following issue.

The population is apparently assumed to be clonal (more than just "haploid"), meaning that there is no recombination between the loci controlling the three traits. In the one case where this assumption is relaxed (quite artificially), the cyclic dynamics disappear (section 4.4 of the appendix). This is crucial information that cannot be appreciated in the main text.

The paragraph at line 368 offers a simple explanation for the joint dynamics of traits. However, this explanation would hold identically for a sexual population and a clonal population, whereas these two cases seem to have completely different dynamics. Thus, there is something essential to explain these differences, that is missing from the given explanation.

This is especially important because the finding that the joint evolution of several traits can lead to some form of diversity maintenance is not surprising. As the discussion acknowledges (but the introduction seems to downplay), it is also well understood that manipulation and counter-adaptations to it can occur in many contexts and lead to the maintenance of diversity. For this reason, similar results in the present case are not surprising, and the main outcome of the study should be to provide a deeper understanding of the forces leading to the different outcomes in the current models.

I do not see clearly what distinguishes "manipulative cheating" from other forms of manipulations that have been previously discussed in the literature (e.g, as cited lines 461). Couldn't this be clarified by some kind of mathematical criterion?

Reviewer #1 (Public Review):

The study uses public behavioral and fMRI data to study the range adaptation properties of the orbitofrontal cortex (OFC) during risky choice that requires integrating potential gains and losses. The authors demonstrate how spill-over effects from the range of gains to the sensitivity to losses, cannot be explained by simple efficient coding accounts. The authors construct an artificial neural network (ANN) and show that Hebbian plasticity between attribute-specific and integration units can account for the context-dependent effect in behavior and fMRI data.

This is an interesting study that discusses a potential mechanism for context effects often seen in decision-making. A major concern is that the manuscript focuses on Hebbian plasticity as the key mechanism, whereas the results show that the choice of activation functions (sigmoidal vs. gaussian) has a comparable contribution to explaining behavior but is not discussed. In addition, the performance of even the best model is not very convincing for extreme ranges of expected value. There are additional moderate and minor concerns with result presentation and interpretation.

Reviewer #1 (Public Review):

Lymphatic drainage of CNS antigens has received lots of attention recently due to the (re)discovery of dural meningeal lymphatics. The role of dural lymphatics in CNS antigen drainage has been shown to be important in several contexts (AD, glioma, etc.). Few studies have focused on their role in CNS infections so far. In their study, Kovacs et al. dissected the role of meningeal lymphatic drainage in T cell responses during chronic Toxoplasma gondii infection in mice. They first show that T.g. infection drives DC accumulation in the dura and CSF at 6 weeks post-infection, which matches with the replication peak of T.g. in the brain, and with T cell expansion/activation in the dCLN. This effect on T cells in the dCLN was abrogated upon surgical blockade of dural drainage. However, dural lymphatic blockade did not affect T.g. burden, nor CD4+ and CD8+ T cell number and IFNg production in the brain in the chronic phase. They finally show that during chronic infection, antigen-specific T cells are generated not only in the dCLN but also in the periphery (ILN), which could account for the presence of T cells in the brain after surgical blockade of the lymphatics.

This study is interesting and some aspects are clearly convincing, but some precisions have to be made. More importantly, with similar tools, key experiments (as explained in the last paragraph: icv infection or chronic peripheral parasite clearance, etc.) have to be generated to bring more impact to this study and could reveal a new role for dCLN T cells.

Reviewer #1 (Public Review):

In this manuscript, Soto-Feliciano et al. investigate the tumor suppressive role of MLL3 in hepatocellular carcinoma (HCC). The authors used a variety of techniques including hydrodynamic tail vain injection (HTVI), CRISPR deletion, and shRNA to disrupt MLL3 expression in mouse models. They clearly show that MLL3 acts as a tumor suppressor in the context of MYC-induced HCC. They show that MLL3 acts by activating the Cdkn2a locus. Genomic analysis showed that MLL3 binds to enhancers and promoters, and specifically interacts with the Cdkn2a promoter. When MLL3 was downregulated, Cdkn2a levels fell and this corresponded to changes in relevant histone marks targeted by MLL3. The authors were also able to show that reintroduced MLL3 expression in a dox inducible system could rescue CDKN2A locus expression, which in turn reduced colony formation and induced apoptosis. Human genomic correlation showed that MLL3 and Cdkn2a mutations are generally mutually exclusive. Overall, the conclusions of the manuscript are well supported by a logical series of experiments with good controls and orthogonal approaches. While it would be useful to examine another HCC model such a CTNNB1-driven model, the current paper is convincing in its conclusions.

Reviewer #1 (Public Review):

Mikelov et al. investigated IgH repertoires of memory B cells, plasmablasts, and plasma cells from peripheral blood collected at three time-points over the course of a year. In order to obtain deep and unbiased repertoire sequences, authors adopted uniquely developed IgH repertoire profiling technology. Based on collected peripheral blood data, authors claim that; 1) A high degree of clonal persistence in individual memory B cell subsets with inter-individual convergence in memory and ASCs. 2) ASC clonotypes are transient over time and related to memory B cells. 3) Reactivation of persisting memory B cells with new rounds of affinity maturation during proliferation and differentiation into ASCs. 4) Both positive and negative selection contribute to persisting and reactivated lineages preserving the functionality and specificity of BCRs.

The present study provides useful technical application for the analysis of longitudinal B cell repertoires, and bioinformatics and statistical data analysis are impressive. Regarding point 1), clonal persistence of memory B cells is already well known. On the other hand, inter-individual convergence between memory B cells and plasma cells might not be shown in healthy individuals even though the biological significance of circulating plasma cells is questionable.

Regarding 2), temporal stability of plasma cell clonotypes has been demonstrated already in the bone marrow with serial biopsies over time (Wu et al. DOI: 10.1038/ncomms13838). The Association of clonotypes between memory and plasma cells in the blood of healthy donors might be new, however, again its biological significance is questionable.

Regarding 3) and 4), it is hard to generalize observations from the presented data because the analysis was based on just four donor cases with different health conditions, i.e. a combination of healthy and allergic. The cell number of plasmablasts and plasma cells isolated from peripheral blood is extremely low compared to memory B cells, and in fact, the vast majority of ASCs reside in the tissues such as lymphoid organs, bone marrow, and mucosal tissues rather than in circulating blood (Mandric et al. DOI: 10.1038/s41467-020-16857-7). As the most critical problem, direct pieces of evidence to claim points, 3) and 4) are missing.

Reviewer #1 (Public Review):

This study uses the mouse calyx of Held synapse as a model to explore the presynaptic role of rac1, a regulator of actin signaling in the brain. Many of the now-classical methods and theory pioneered by Neher and colleagues are brought to bear on this problem. Additionally, the authors were able to make a cell-specific knockout of rac1 by developing a novel viral construct to express cre in the globular bushy cells of the cochlear nucleus; by doing this in a rac1 floxed mouse, they were able to KO rac1 in these neurons starting at around P14. The authors found that KO of rac1 enhanced EPSC amplitude, vesicle release probability, quantal release rates, EPSC onset time and jitter during high-frequency activity, and fast recovery rates from depression. Because the calyx synapses are the largest and most reliable of central nerve terminals, all these various effects had no effect on suprathreshold transmission during 'in vivo-like' stimulus protocols. Moreover, there was no effect morphologically on the synapse. Through some unavoidably serpentine reasoning, the authors suggest that loss of rac1 affects the so-called molecular priming of vesicles, possibly due to a restructuring of actin barriers at the active zone. The experimental analysis is at a very high level, and the work is definitely an important contribution to the field of presynaptic physiology and biophysics. It will be important to test the effects of the KO on other synapses that are not such high-performers as the calyx, and this direction might reveal significant effects on information processing by altered rac1 expression.

Major points:<br /> 1. The measurement of onset delay was used to test whether rac1-/- affects positional priming. While there is a clear effect of the KO on the latency to EPSC onset, there is no singular interpretation one can take, due to the ambiguity of the 'onset delay'. Note that in the Results authors state Lines 201-203: "The time between presynaptic AP and EPSC onset (EPSC onset delay) is determined by the distance between SVs and VGCC which defines the time it takes for Ca2+ to bind to the Ca2+ sensor and trigger SV release (Fedchyshyn and Wang, 2007)." However, in Methods "The duration between stimulus and EPSC onset was defined as EPSC onset delay." Thus the 'onset' measured is not between presynaptic spike and EPSC but from axonal stimulus and EPSC. KO of rac might also affect spike generation, spike conduction, calcium channel function, etc. Indeed some additional options are offered in the Discussion. Since the change in onset is ~100usec at most, a number of small factors all could contribute here. Moreover, the authors conclude that the KO does NOT affect positional priming since they would have expected the onset to shorten, given the other enhancements observed in earlier sections.<br /> It seems to me that all the authors can really conclude is that the onset shifted and they do not know why. If onset is driven by multiple factors, and differentially affected in the KO, then all bets are off. Thus, data in this section might be removed, or at least the authors could further qualify their interpretations given this ambiguity.

2. If the idea is that the loss of Rac1 leads to a reduced actin barrier at the active zone, is there an ultrastructural way to visualize this, labeling for actin for example? Authors conclude that new techniques are needed, but perhaps this is 'just' an EM question.

3. Authors use 1 mM kynurenic acid in the bath to avoid postsynaptic receptor saturation. But since this is a competitive antagonist and since the KO shows a large increase in release, could saturation or desensitization have been enhanced in the KO? This would affect the interpretation of recovery rates in the KO, which are quite fast.

Reviewer #1 (Public Review):

Baldazzi and coworkers propose a resource allocation model for E. coli steady-state cell growth that allows a joint description of growth rate and yield (fraction of substrate converted into biomass) and compare it with a compiled dataset based on batch growth data from different strains and two growth conditions (as well as some chemostat growth data). The model includes a description of alternative respiration and fermentation pathways with different energy efficiency. The model predicts bounds on the achievable state growth rate vs yield space that are compared with data, as well as glucose uptake and acetate secretion rates, which are compared with data.

In my view, the main merits of the model are (i) the compiled dataset of growth-yield-uptake-secretion parameters and (ii) the proposition of a resource-allocation model that includes the energy budget. Contrary to most current models in this area, the biomass includes other cellular components (DNA, RNA, metabolites, ...) in addition to proteins.

The main limitations are that the trends in the data do not emerge well and the predictions of the model are not presented in a transparent way. I believe that considerable extra work is needed in order to valorize the effort and highlight the trends in both data and model. For the data, it suffices to present more "sections" of the dataset (preferably as 2D XY plots) and more reflection on their meaning. Regarding the model, I think more effort is needed towards "breaking it open" and providing insight into why the model makes certain predictions and which ones are not trivial.

Reviewer #1 (Public Review):

The study investigated the role of oxytocin (OT) in the paraventricular hypothalamic nucleus (PVH) and oxytocin receptor (OTR) in the hypothalamus in the regulation of food intake using conditional knockout of oxytocin in adults by adreno-associated virus (AAV) approaches. Although pharmacological studies have demonstrated that oxytocin/oxytocin receptors regulate food intake behavior, constitutive knockout (KO) models are not aligned with pharmacological studies. To overcome this discrepancy between pharmacological and developmental genetic approaches, the authors used AAV to knockout oxytocin/oxytocin receptors in adults of mice, circumventing developmental compensations. They found that adult KO of OT in the PVH, but not supraoptic nucleus (SO), led to obesity due to hyperphagia. They also investigated whether OTR in the anterior or posterior side of the hypothalamus contributes to OT-mediated food intake behavior, and found that the posterior hypothalamic areas are key for that. Overall, the experiments are thoughtfully designed, and the manuscript is well written. However, there are questions that authors need to address, in particular their OT KO model.

Reviewer #1 (Public Review):

Activation of TEAD-dependent transcription by YAP/TAZ has been implicated in the development and progression of a significant number of malignancies. For example, loss of function mutations in NF2 or LATS1/2 (known upstream regulators that promote YAP phosphorylation and its retention and degradation in the cytoplasm) promote YAP nuclear entry and association with TEAD to drive oncogenic gene transcription and occurs in a significant majority of mesothelioma patients. High levels of nuclear YAP have also been reported for a number of other cancer cell types. As such, the YAP-TEAD complex represents a promising target for drug discovery and therapeutic intervention. Based on the essential functional role for TEAD palmitoylation at a conserved cysteine site, discovered by the authors of this manuscript, several groups have successfully targeted this site using both reversible binding non-covalent TEAD inhibitors (i.e., flufenamic acid (FA), MGH-CP1, compound 2 and VT101~107), as well as covalent TEAD inhibitors (i.e., TED-347, DC-TEADin02, and K-975), which have been demonstrated to inhibit YAP-TEAD function and display anti-tumor activity in cells and in vivo.

Here, Hu et al. disclose the discovery of a new class of reversible TEAD inhibitors that putatively binds across a new site within the auto-PLM pocket across the TEAD family of proteins. To date, reported inhibitors that target this site (flufenamic acid (FA), TED-347, MYF-01-037, K975, VT103, MGH-CP1) function by binding to the same hydrophobic palmitate binding pocket (PBP) which is highly conserved. The novel TEAD inhibitor is identified from a screen of 30,000 compounds using recombinant TEAD2 and TEAD4 proteins and TEAD2 and TEAD4 click-ELISA assays. A molecule termed TM2 was found to show the strongest inhibition on TEAD auto-palmitoylation (IC50= 156nM for TEAD2 and 38nM for TEAD4) and is chosen for further characterization. A co-crystal structure of TEAD2 YAP binding domain in complex with TM2 was solved and revealed that TM2 not only occupied the familiar hydrophobic PLM site but also binds within a new pocket. Notably, the charge properties of this site might be compatible with the development of more drug-like analogs with enhanced hydrophilic properties. TM2 is profiled against several malignant pleural mesothelioma (MPM) cell lines (IC50 = 26-157nM) and activity correlates well with in vitro TEAD palmitoylation inhibition. Notably, consistent with results for related inhibitor classes, TM2 is not active as a monotherapy in cells beyond NF2 deficient cell lines, although cell type selective cytotoxicity is clearly shown.

Strengths:

This newly reported chemical series is highly tractable and could provide an excellent starting point for the development of effective TEAD inhibitors. The reported ability of TM2 to bind to a new site within the conserved TEAD auto-PBP site could enable this area of drug discovery.

Weaknesses:

The authors claim that TM2 is "more specific" than existing inhibitors, with respect to its ability to regulate YAP/TAZ-TEAD target gene expression. However, this statement is based on a comparison of unrelatable RNA-Seq datasets. TM2-regulated expression is evaluated in the context of cell (mono)culture following a continuous duration of target engagement. Comparison is made to the covalent inhibitor K975 based on a published dataset involving analysis of a drug-treated NCI-H226 tumor xenograft (i.e, in vivo drug treatment). Heterogeneity in cells, time point of analysis and duration and target engagement preclude the possibility of any reasonable comparison of these datasets. The ability of TM2 to bind within a new site is a significant finding. The comparison of TM2 binding mode to other inhibitors is based on structures of non-TEAD2 co-crystal structures. It will help significantly to clarify the differences in the side chains within this site across TEAD family members (i.e., TEAD1-4). The robustness of the proposed synergistic activity of TM2 in non-responsive cell lines is unclear.

Reviewer #1 (Public Review):

This is timely and foundational work that links cellular neurophysiology with extracellular single-unit recordings used to study LC function during behavior.

The strengths of this paper include:<br /> 1. Providing an updated assessment of LC cell morphology and cell types since much of the prior work was completed in the late 1970s and early to mid-1980s.<br /> 2. Connecting LC cell morphology with membrane properties and action potential shape.<br /> 3. Showing that neurons of the same type have electrical coupling

Collectively, these findings help to link LC neuron morphology and firing properties with recent work using extracellular recordings that identify different types of LC single units by waveform shape.

Another strength of this work is that it addresses recent findings suggesting the LC neurons may release glutamate by showing that, at least within the LC, there is no local glutamatergic excitatory transmission.

Weaknesses:<br /> The authors also propose to test the role of single LC neuron activity in evoking lateral inhibition, as well as proposing that electrical coupling between LC cell pairs is organized into a train pattern. The former point is based on a weak premise and the latter point has weak support in their data given the analyses performed.

Point 1: lateral inhibition in the LC<br /> The authors write in the abstract that "chemical transmission among LC noradrenergic neurons was not detected" and this was a surprising claim given the wealth of prior evidence supporting this in vitro and in vivo (Ennis & Aston-Jones 1986. Brain Res 374, 299-305; Aghajanian, Cedarbaum & Wang 1977. Brain Res 136, 570-577; Cedarbaum & Aghajanian. 1978 Life Sci 23, 1383-1392).

Huang et al. 2007 (Huang et al. 2007. Proc National Acad Sci 104, 1401-1406) showed that local inhibition in the LC is highly dependent on the frequency of action potentials, such that local release requires multiple APs in short succession and then requires some time for the hyperpolarization to appear (even over 1 sec). This work suggests that it is not a "concentration issue" per se, rather it is just that a single AP will not cause local NE release in the LC. Although the authors did try 5APs at 50Hz this may not be enough to generate local NE release according to this prior work. A longer duration may be needed. Additionally, although the authors incubated the slices with a NET inhibitor, that will not increase volume transmission unless there is actually NE release, which may have not happened under the conditions tested. In sum, there is no reason to expect that a single AP from one neuron would cause an immediate (within the 100 msec shown in Fig 3B) hyperpolarization of a nearby neuron. Therefore, the premise of the experiment that driving one neuron to fire one AP (or even 5AP's at 50Hz in some) is not an actual test of lateral inhibition mediated by NE volume neurotransmission in the LC. Strong claims that "chemical transmission...was not detected" require substantial support and testing of a range of AP frequencies and durations. Given the wealth of evidence supporting lateral inhibition of the LC, this claim seems unwarranted.

Point 2: Train-like connection pattern<br /> Demonstrating that connected cell pairs often share a common member is an important demonstration of a connection motif in the LC. However, a "train" connection implies that you can pass from A to B to C to D (and in reverse). However, the authors do not do an analysis to test whether this occurs. Therefore, "train" is not an appropriate term to describe the interesting connection motif that they observed.

In fact, writing A↔B↔C in the paper implies a train without direct support for that form of electrical transmission. For example, in Fig. 6C, it is clear that cell 6 is coupled to cell 1 and that cell 6 is also coupled to cell 8. In both cases, the connection is bilateral. Using the author's formatting of A↔B↔C , would correspond with Cell 6 being B and cells 1 and 8 being A and C (or vice versa). However, writing A↔B↔C implies a train, whereas one can instead draw this connection pattern where B is a common source:<br /> A C<br /> . .<br /> . .<br /> B

An analysis showing that spikes in A can pass through B and later appear in C is necessary to support the use of "train". The example in Fig. 6C argues against train at least for this one example.

Although the analysis is possible to do with the authors' substantial and unique data set, it should be also noted that prior work on putative electrical coupling in extracellular recordings from rat LC showed that trains among 3 single units occurred at an almost negligible rate because out of 12 rats "Only 1 triplet out of 22,100 possible triplet patterns (0.005%) was found in one rat and 4 triplets out of 1,330 possible triplet patterns (0.301%) were found in the other rat." and moreover patterns beyond 3 units were never observed (Totah et al 2018. Neuron 99, 1055-1068.e6).

Reviewer #1 (Public Review):

The authors generated a mouse model for GEN1 and a B-cell conditional MUS81 flox allele to create B-cells devoid of both proteins using two Cre drivers. Mb1-Cre driven by the Cd79a promoter depletes MUS81 in pre-pro B cells, whereas Cd23-Cre is driven by the Fcer2a promotor to deplete MUS81 in immature, transitional and late B cells. The results show that GEN1 and MUS81 are necessary for differentiation into pro-B cells, the expansion and maintenance of pro-B cells, or both. The CD23-Cre line showed that naïve B cells can persist without MUS81 and GEN1, but they are impaired for germinal center formation. Ex vivo analysis identified a proliferation defect upon stimulation and increased cell death due to apoptosis. RNA seq analysis of such cells revealed activation of the p53 pathway and the type I interferon response. Metaphase chromosomal analysis revealed hallmarks of genomic instability including chromosomal abnormalities, including breaks, fragments, fusions, and radials. The symmetry of the breakages suggests that they arose from unresolved HR intermediates.

Strengths:<br /> This is a well-executed study, and the results support the conclusions. While the role of both nucleases has been extensively studied in cellular systems, this is the first analysis at the organismic level with a focus on B-cell development.

Weaknesses:<br /> The nature of the actual substrate(s) for MUS81 and GEN1 remains unclear and the significance of unresolved HR intermediates for the observed phenotype remains an inference from the type of chromosome aberrations observed. The DNA damage analyses presented would benefit from being clarified and extended.

Reviewer #1 (Public Review):

This paper provides a progress report on methods development that was initiated previously by the same authors to identify macromolecular complexes in cryo-EM images of cells. Whereas others have proposed to perform this task in 3D reconstructions from tomographic tilt series, the method discussed here (2DTM) uses template matching with known reference structures against individual 2D projection images. This concept was introduced in previous work. In the current paper, the authors show that 2DTM can be used to classify distinct molecular populations. They demonstrate this by distinguishing cytoplasmic mature 60S ribosome particles from a nuclear pre-60S population. They also define a maximum likelihood metric that assigns a probability for each particle belonging to each class. The paper reads a bit dense, and one could discuss how big the advance is over the previous work by the same authors. But the general topic (of being able to identify distinct particle populations in cells) is an important one.

However, I think one major concern needs to be addressed much more openly in a revised version of the paper: that of potential model bias of incorrect references. The single-particle field previously suffered the problems of Einstein from noise can cause with the debacle around an incorrect HIV trimer reconstruction that was the result of picking particles with a high-resolution reference. I realise that the problem here is a different one, but similar problems of model bias may exist. In fact, the observation on page 18 that the reconstruction from the picked particles was estimated by FSC to be 3.5A, yet the resulting map had to be filtered at 10A to limit the noise, is a strong indication that model bias does play a large role in the identification of particles. This bias must affect the measured SNR scores, and thus the metrics presented. It also suggests that part of the identified picks may in fact not be true 60S ribosomes, but false positives. This would then affect the conclusions drawn. If the authors disagree (and I suspect they do), they should set out clear arguments for their case. Also, they should discuss how potential overfitting or model bias would affect their new metrics for particle classification in the discussion. Currently, the only reference to the dangers of overfitting is on page 16, merely referring to their previous paper.

Perhaps points for additional discussion could include:<br /> 1) In the light of overfitting, I was wondering whether one could detect the 80S ribosomes also through 2DTM using the 40S subunit as a reference.<br /> 2) The authors have been wise in selecting the 60S ribosome as a test case. Probably, because of its size and RNA content, for many instances of this complex the SNR is sufficiently high for detection. However, if less careful authors would choose a smaller target, what would happen? What would be the pitfalls and how could they be avoided?

Reviewer #1 (Public Review):

In this manuscript by Chen et al., the authors use live-cell single-molecule imaging to dissect the role of DNA binding domains (DBD) and activation domains (AD) in transcription factor mobility in the nucleus. They focus on the family of Hypoxia-Inducible factors isoforms, which dimerize and bind chromatin to induce a transcriptional response. The main finding is that activation domains can be involved in DNA binding as indicated by careful observations of the diffusion/reaction kinetics of transcription factors in the nucleus. For example, different bound fractions of HIF-1beta and HIF-2alpha are observed in the presence of different binding partners and chimeras. The paradigm of interchangeable parts of transcription factors has been eroded over the years (the recent work of Naama Barkai comes to mind, cited herein), so the present observations are not unexpected per se. Yet, the measurements are rigorous and well-performed and have the important benefit of being in living cells. Enthusiasm is also dampened by the exclusive use of one technique and one analysis to reach conclusions.

Reviewer #1 (Public Review):

The authors report a public browser in which users can easily investigate associations between PRSs for a wide range of traits, and a large set of metabolites measured by the Nightingale platform in UKBB. This browser can potentially be used for identifying novel biomarkers for disease traits or, alternatively, for identifying novel causal pathways for traits of interest.

Overall I have no major technical concerns about the study, but I would encourage the authors to revisit whether they can find a more compelling example that can better showcase the work that they have done. I understand that this is partly a resource paper but I think the resource itself can have more impact if the paper provides a clearer use-case for how it can drive novel biological insight.

PRS construction: It's unclear how well the PRS work. Should the reader prefer the stringent or lenient PRS? Perhaps there could be some validation with traits that have decent sample sizes in UKBB. Was there any filtering to remove traits with few GWS hits, low sample sizes, or low SNP heritability as these are unlikely to produce useful PRSs?

Reviewer #1 (Public Review):

This manuscript sets up a well-reasoned study and capitalizes on a very impressive long-term dataset. Their methods are generally sound and well explained. The argument for paternal kin recognition here could be compelling, but at this stage, it does not seem possible to rule out a simpler cognitive mechanism, i.e. gorillas direct their aggression toward unfamiliar and/or outgroup individuals. The authors note the difficulty of indexing familiarity versus kinship because there were very few out-group dyads (two individuals from different natal groups) that were related. But were there any in-group dyads that were not related? If so, then it might be plausible to add the natal group as a co-variate to parse these mechanisms. A result in either direction could be very compelling. Another concern is dealing with age- which is incredibly difficult with data like this and the authors have offered a reasonable compromise here by settling on a single term (age difference). It makes good sense that the difference in age between two partners should contribute to shaping the interactions between a dyad, however, each of the social behaviors here is more or less common depending on age in most species (including gorillas to the best of my knowledge) with social play generally decreasing with age while social grooming and aggression increase. I understand that it is not the intent of this manuscript to describe the ontogeny of social bonds, however, as the dataset includes individuals ranging from infants through adults, is it possible that such age-related changes in social behavior are affecting the results? Whether or not the authors find strong indications that gorillas can recognize paternal kin, specifically, beyond in-group/out-group familiarity, this manuscript represents an important contribution to the field.

Reviewer #1 (Public Review):

This is a randomized controlled trial to assess the impact on the COVID-19 progression (hospitalization, oxygen supplementation need, and/or death within 14 days) of 3 different mAbs. As only one of the assessed mAbs was shown to be active in vitro against the Omicron variant, which emerged after the study onset, the trial was interrupted for potential futility. The authors compared the activity of three mAbs in patients infected with Delta and in those with Omicron variant. Symptoms duration was shorter in patients treated with sotrovimab than in those treated with the other mAbs, mainly among Omicron infected patients. No disease progression was observed in the Delta group, while two patients infected with omicron and treated with bamlanivimab/etesevimab presented progression.

The strength of this study is that it provides clinical data about the efficacy of different mAbs on COVID-19 progression against the Omicron variant assessed by a pragmatic RCT.

The limitation is the reduced sample size.

The results are useful in confirming the usefulness of Sotrovimab in the management of patients with Omicron BA 1 and BA 1.1. They cannot be applied to other Omicron sub-lineages.

Considering the availability of antiviral agents for early use in patients with asymptomatic or mild infection but with risk factors for COVID-19 progression and the longer duration of symptoms observed for casirivimab/imdevimab compared with sotrovimab, the conclusion about the potential role of this mAb against Omicron seems inappropriate.

Reviewer #1 (Public Review):

While some microbes have evolved to need an animal host for completion of the life cycle or survival, termed "obligate pathogens" (i.e. Plasmodium falciparum, viruses, Neisseria gonorrhoeae), there are many bacteria and fungi that can cause disease in insect or mammalian hosts, but can survive okay in the environment and do not need a host in order to survive, persist, and replicate. These microbes are often described as "accidental pathogens," where they evolved in the absence of a host to survive durable conditions in the environment, and only caused disease when they are accidentally exposed to a host (i.e. breathing in spores or traumatic inoculation). In this work, the authors set out to determine whether selection for Saccharomyces cerevisiae's ability to bind plastic in the absence of a host resulted in enhanced virulence when the yeast was exposed to a host. In doing so, they would be experimentally showing that adaptation to environmental conditions without a host, can "accidentally" produce pathogens. In this work, the authors indeed demonstrated that S. cerevisiae which had been selected for its ability to adhere to plastics evolved multicellular phenotypes and enhanced virulence in the Galleria mellonella wax moth host. In doing so, they effectively show experimental proof of the accidental virulence hypothesis, which can serve as the basis for future studies to better understand existing non-obligate microbes, and how new changes/exposures in the environment can cause the adaptation of microbes, which may result in the emergence of new "accidental" human pathogens. The work also investigated the evolutionary relationship between the different forms of multicellularity and uncovered that there was a strong correlation between the emergence of multiple multicellular phenotypes over cycles of plastic adhesion selection, which is a new finding compared to previous reports that these phenotypes in the environment or in laboratory/mutant strains are independent.

The conclusions drawn in this paper are well supported by the data, and the experiments are well-designed and straightforward and presented in a way that is generally able to be understood. This study is of great interest to both microbiologists who study how microbes adapt to the environment and those who study microbes in the context of infectious disease. This study experimentally proves the tenet of the accidental virulence hypothesis that adaptation/evolutionary selection to environmental factors may incidentally enhance the ability to survive within hosts.

Additionally, the authors conducted the experiments in a robust, well-controlled manner, and systematically analyzed the multicellular phenotypes. They assayed the multicellular phenotypes in a clearly defined manner and were able to characterize the traits of a large number of individual clones grown encompassing different timepoints, sexual and asexual reproduction, strains, and selection. Additionally, their virulence studies in G. mellonella show an extraordinary amount of work, which allowed them to see the increase in virulence (~30%) in the hyper-multicellular phenotype after performing infections using 40 different isolates from the experiment.

The authors also sought to find a genetic basis for the increase of multicellular phenotypes and virulence following plastic adherence selection. To do so, they studied the length of the FLO11 gene in their S. cerevisiae isolates. FLO11 length had been previously implicated in fungal adhesion and fungal virulence, which could offer a reason for the enhanced virulence phenotype following selection for plastic adherence. While their findings show the ancestral and control isolates did not have increased FLO11 length while many of the plastic-selected isolates did, there was not a definitive correlation between the multicellular phenotypes and FLO11 length. The authors did not pursue an additional investigation into the genetic basis of these adaptations.

Two aspects the reader must consider are the host and the microbe used in these virulence experiments. S. cerevisiae is an interesting choice to use because it is not considered to be a "pathogenic" microbe, although there are rare cases in which it can cause disease in humans. However, previous studies have shown S. cerevisiae has been shown to cause disease in G. mellonella, which can also be seen in the survival curves presented in this paper. Therefore, using G. mellonella in this study shows that the selection process resulted in increased virulence in the host. To strongly show the accidental virulence/pathogen hypothesis, a host-microbe pair where disease does not normally/typically occur could be used. In the context of this study, it could be done using a mouse model infected with S.cerevisiae. In doing so, it could show that environmental selection in the absence of a host has the ability to turn a "non-disease-causing microbe" into a disease-causing one, rather than a disease-causing microbe into a more disease-causing microbe. This could also make a more applicable leap to human infectious diseases.

Reviewer #1 (Public Review):

This is a very thorough biochemical work that investigated the ParABS system in pSM19035 by Volante et al. Volante et al showed convincingly that a specific architecture of the centromere (parS) of pSM19035 is required to assemble a stable/functional partition complex. Minimally, four consecutive parS are required for the formation of partition complex, and to efficiently activate the ATPase activity of ParA. The work is very interesting, and the discovery will allow the community to compare and contrast to the more widespread/more investigated canonical chromosomal ParABS system (where ParB is a sliding CTPase protein clamp, and a single parS site is often sufficient to assemble a working partition complex). All the main conclusions in the abstract are justified and supported by biochemical data with appropriate controls. A proposed multistep mechanism of partition complex assembly and disassembly (summarized in Fig 6) is reasonable. Perhaps the only shortcoming of this work is that the team does not yet get to the bottom of why four consecutive parS are needed.

Reviewer #1 (Public Review):

Dhawan et al examine the involvement of the perirhinal cortex (PRC) and ventral hippocampus (vHPC) in different forms of approach-avoidance conflict. The paper is well written, the methods used are appropriate for the question asked and, in general, the authors have succeeded in identifying the PRC and vHPC involvement. As such, the paper will eventually have an impact on thinking about the roles of the PRC and vHPC in different forms of learning and memory. However, this impact is conditional on the authors' responses to queries regarding experimental design, group allocations and statistical analyses.

Reviewer #1 (Public Review):

Ahmed et al. examine the changes in the enhancer landscape that may contribute to the transition from Barrett's oesophagus (BO) to oesophageal adenocarcinoma (OAC), building upon their past works looking at the chromatin changes within this transition. They identified a repertoire of eRNA regions that display differential expression between OAC and BO, validating their association to enhancers using H3K27ac levels, CUT&TAG, and KAS-seq. The authors look further into the target genes and regulatory TFs that may define eRNA levels, finding several TFs - AP1, KLF5, CTCF, and HNF1 - that have previously been implicated in OAC and confirming that sets of eRNA target genes were downregulated upon depletion of these TFs. Ahmed et al. also showed that eRNA target genes were relevant to OAC phenotypes, akin to that of DEGs in whole RNA-seq datasets. The authors lastly validate the activity of certain eRNAs targeting JUP, MYBL2, and CCNE1 using functional methods to confirm enhancer activity and effects on cell viability, as well as clinical features such as the age of diagnosis and survival time.

The landscape of eRNA activity seems to be well validated. However, deeper analyses to support the relevance of the function of key eRNAs, their specificity in regulating target genes, and the interaction with other OAC features would further support these findings.

Reviewer #1 (Public Review):

In this paper, Blair et al., analyze hippocampal place cell remapping in rats performing a shock avoidance task using miniscopes to image large-field-of-views. They use behavioral (barriers) and pharmacological (scopolamine) manipulations to interfere with place cell representations during the formation and extinction of aversive memories. By exploiting multi-cellular imaging they examine cell remapping dynamics during learning and extinction induced by the different manipulations and evaluate how they relate to behavioral readouts. The work is carefully planned and analyses successfully control for many potential confounds (but see below).

Major strengths of the paper include a) using large-field-of-view miniscope imaging to provide place cell data from rats thus favoring inter-species comparisons (most miniscope data is emerging from mouse and rats, especially better in memory tasks); b) an appropriate set of control analysis and experiments to exclude for potential confounds especially when it comes to comparison between groups (speed, number of trials, performance, within- and between-trials differences). Major weaknesses are a) the systemic effect of pharmacological manipulations and specificity regarding memory function; b) the lack of appropriate shuffled contrasted effects. Other inevitable methodological aspects (such as the effect of large GRIN lenses on the integrity of the dorsal, and ubiquitous expression of GCaMP) also require further consideration.

The paper may be of interest to the neuroscience community by setting new methodological standards and providing new data for across-species comparisons.

Reviewer #1 (Public Review):

ARL3 is a small GTPase that localizes to the primary cilium and plays a role in regulating the localization of some specific ciliary membrane proteins, including PDEδ and NPHP3. Mutations in this gene cause Joubert syndrome, a type of ciliopathy characterized by cerebellar malformation, and retinal degeneration. While the majority of the diseases occur in an autosomal recessive manner, two mutations in ARL3 (D67V and Y90C) have been reported to cause autosomal dominant retinal diseases. In the current paper, Travis et al. sought to understand the pathogenesis of the diseases caused by the two autosomal dominant mutations. They found that D67V acts as a constitutive active mutation, whereas Y90C is a fast-cycling mutant, which can be activated in a guanine nucleotide exchange factor (GEF) independent manner. Since the fast-cycle mutant did not bind to the effector proteins in vitro (likely because the guanine nucleotide falls off from the mutant ARL3, which has a lower affinity to GDP/GTP), they developed a method to snapshot the interaction between ARL3 and its effector. Using this method, they showed that the Y90C mutant indeed has increased interaction with the effectors, suggesting that Y90C is an overactive form of ARL3. They then addressed how photoreceptor cells are affected by these two mutations using a mouse model and found that the mutations disrupt the proper migration of the photoreceptor cells.

Strengths:<br /> • The paper is well written, and it was easy to understand what the authors did from the figure legends and the methods section.<br /> • It was easy to find out what is known or unknown, as the paper has accurate references.<br /> • The authors developed a method to analyze a snapshot of the interaction between ARL3 and its interactors.<br /> • The paper has an in vivo model and connects the biochemical characteristics of ARL3 to in vivo cellular phenotypes.

Weaknesses:<br /> (1) I understand that authors focused on nuclear migration defect as the phenotype was first described in ARL3-Q71L transgenic mice. The similar phenotype observed in RP2 knockout mice further supports the idea that the defect is caused by the hyperactivation of ARL3. Indeed, the defect is not reported in the ARL3 knockout mice, however, I feel that it does not necessarily mean that the defect is not caused by loss of function. Although it has not been assessed, ARL3 knockout mice might have the same defect. Therefore, I think analyzing both the migration defect and trafficking defect would be more informative, rather than focusing on the migration defect. The fact that the relationship between nuclear migration defect and the retinal degeneration phenotype is not entirely clear further enhances the importance of analyzing the trafficking defect.<br /> Does the expression of ARL3-Y90C also cause the trafficking defect? If it is the case, you can separate the nuclear migration phenotype from the one caused by the trafficking defect. Would the expression of lipidated cargo(s) rescue the trafficking defect as well?<br /> I think many questions can be addressed by analyzing the localization of the lipidated cargos, such as PDE and GRK1.

(2) I am not quite sure if the nuclear migration was assessed properly. Based on the pictures in Fig.1, some of the FLAG-negative cells also seem to be migrating to INL (please see Fig.1C and Fig.1D). Is this biologically normal during development? Could this analysis be affected by the thickness of OPL, the layer between ONL and INL? Also, the picture is cut out in the middle of INL. Could authors include more layers, such as IPL, of the retina in the picture, so that we can evaluate INL and OPL better? Taking this into account, I think it is worth measuring the nuclear position of FLAG-negative cells as a negative control in all the experiments.

(3) The way that the authors showed the Y90C mutant of ARL3 is a fast-cycling mutant is not very compelling. In Figure 2C, the authors showed that ARL3 Y90C can bind to PDEδ, its effector, once it is pre-loaded with GTP. The authors also showed that the mutant can bind to its effector even without EDTA as long as an excess amount of GTP is added. The authors used endogenous ARL3 as a control to compare the effects between wild-type and mutants. I see that this experiment has multiple pitfalls. First, ideally, this type of experiment needs to be done with a purified protein using fluorescent guanine nucleotide/radioactive guanine nucleotide (e.g. nucleotide loading assay or nucleotide exchange assay) to directly access the kinetics of nucleotide exchange. However, I do understand that this is out of the authors' expertise. In the authors' experimental setting, I am not sure loading the protein with GTP in the presence of the EDTA means anything more than confirming that the protein is intact. Theoretically, wild-type and a fast-cycling mutant can load GTP with similar efficiency in the presence of EDTA. Then during immuno-precipitation, GTP falls off from the Y90C mutant faster than wild-type (because a fast-cycling mutant theoretically has a lower affinity to guanine nucleotides), assuming that GTP was not added during immuno-precipitation (GTP addition was not mentioned in the method, but could authors confirm this?). But in this case, the kinetic of GTP dissociation can be affected by many factors, including the presence of GAP in the reaction, the dissociation constant of Y90C, the volume of the buffer used, and the number of washing steps. Thus, it is not very easy to estimate the difference between wild-type and Y90C. Besides, using endogenous ARL3 rather than ARL3-wild type FLAG as a control can be dangerous. I have experienced that a tagged protein is cleaved to a protein that has a similar size to endogenous protein. (I expressed GFP-protein X in knockout cells lacking protein X, and saw the band at the position where the endogenous protein is observed in wild-type cells). So, the endogenous band that the authors showed could come from the cleaved FLAG-Arl3. (Authors can easily confirm this by having wild-type not expressing FLAG-tagged ARL3, though).

An alternative experiment that I would suggest is doing immuno-precipitation in the buffer containing: 1) no guanine nucleotide, 2) 10mM GDP, or 3) 10mM GTP in the cells expressing the following protein: 1) ARL3 wild-type FLAG, 2) ARL3 Y90C FLAG, or 3) ARL3 D129N FLAG. 10mM guanine nucleotide should be added throughout the process including washing. This experiment might also be affected by many factors, but variability should be lower than the experiment presented in Fig 2C. ARL3-wild type FLAG is also a better control here than endogenous protein.

(4) In Fig.3, the authors attempted to take a snapshot of the interaction between ARL3 and multiple effector proteins. The three bands that were enriched in the Q71L cells were found as RP2, UNC119, and BART by mass spec (Fig.3B). These bands were used as a readout for the subsequent experiments. I am not quite sure why the authors used this approach rather than using the cell line that expresses both FLAG-ARL3 and GFP tagged protein of interest, just like what the authors did in Fig3G. The reasons why I prefer the latter approach are the following: FLAG bands that correspond to the three proteins (RP2, UNC119, and BART) in wild-type cells are very close to the detection limit, 2) authors failed to confirm that the lowest band actually comes from BART, 3) authors cannot access some important effector proteins, such as PDE because 293 cells might not express them. All of the problems can be solved by using the approach that was taken in Figur 3G.<br /> If the authors chose the former approach because of some specific reason, I would appreciate it if the authors could explain that in the main text of the paper.

(5) ALR3 Y90C causes nuclear migration defect. Given that Y90C is a fast-cycling mutant (hyperactive) and has a high affinity to ARL13B, the nuclear migration defect might come from either the increased activity of ARL3 or sequestration of ARL13B, which can act as a GEF for ARL3 but potentially have other functions. If my understanding is correct, the authors concluded that the defect caused by ARL3-Y90C is likely due to hyper-activation of the protein, as Y90C/T31N mutant, which cannot bind to effectors but still retains the ability to capture ARL13B, did not cause migration defect. But I am a little confused by the fact that Y90C/R149H, which is unable to bind to ARL13B (Fig.2C) but still retains the ability to interact with the effectors (Fig.3F), did not have migration defect (Fig.7B). Wouldn't this mean that the sequestration of ARL13B could contribute to the phenotype?<br /> If my understanding is correct, the authors are trying to say that both hyper-activation of cytosolic ARL3 and the defect in endogenous ARL3 activation in cilium is necessary to cause migration defect. I am not very convinced by this hypothesis, and still think that the defect could be caused by sequestration of ARL13B to the cytoplasm.<br /> Then why Y90C/T31N did not cause the defect even though they can sequester ARL13B? This might be explained by the localization of the ARL13B mutants. If Y90C can localize to the cilium while the double mutant, Y90C/T31N, does not, then only Y90C might be able to inhibit the ARL13B function in the cilium. This could explain the lack of the defect in the cells expressing Y90C/T31N.<br /> It would be helpful to understand how exactly the fast-cycling mutant causes the defect if the authors can provide more information, including localization of ARL3 (wild-type and mutants) as well as key proteins, such as ARL13B and the effector proteins. Assessing ARL13B defect seems to be particularly important to me because ARL13B deficiency has been connected to neuronal migration defect (Higginbotham et al., 2012)<br /> What I am trying to say here is that how the defect is caused is likely very complex. So, providing more information without sticking to one specific hypothesis might be important for readers/authors to accurately interpret the data.

(6) The rescue experiments that the authors presented in Fig.5-6 are striking and would build a base for future therapy of the diseases caused by ARL3 defects. However, I believe more examinations are needed to accurately interpret the data. The authors did this rescue experiment by co-injecting ARL3-FLAG and chaperons/cargos if I understand the method section correctly. But I feel we can interpret this data correctly only when ARL3-FLAG and chaperons/cargos are co-expressed in the same cells. I think a better way to analyze the data might be by comparing the nuclear migration phenotype between ARL3-FLAG only and ARL3-FLAG;chaperons/cargos double-positive cells.

Reviewer #1 (Public Review):

Weiss et al have developed a novel model of Huntington's disease (HD) by injecting a mixture of recombinant adeno-associated viral vectors (AAVs) into the caudate and putamen of rhesus macaque monkeys. There is a significant need for relevant models of HD. While many mouse models exist, current models lack genetic relevance (with repeat lengths much longer than those found in humans being used) and mice lack the anatomical relevance to humans since they have small brains with important brain regions (in particular the neostriatum) being dissimilar to those seen in humans. The authors used non-human primates because they have large brains with anatomy similar to humans. They used a mixture of recombinant adeno-associated viral vectors (AAVs) in an attempt to overcome the shortcomings of previous models using AAVs. They studied their animals over 20 months using both behavioural tasks and MRI assessment. The animal served as their own controls for the imaging, which improves the power of the study. The methods of analysis, particularly the imaging, are modern and directly relevant to assessments that can be conducted on human patients.

Strengths<br /> The major strength of the paper is that the authors used Rhesus macaque, a species that is highly relevant to studies aimed at assessing therapies and drug delivery. As a stepping-stone to humans, the macaque has many advantages, including brain size, relevant anatomy and in particular, longevity compared to mice. The approach of mixing a number of recombinant AAVs is also interesting since it overcomes some of the limitations of individual AAVs as detailed in the Introduction. The tasks used for behavioural assessment to investigate the effect of the AAV on brain and behaviour also highlight the advantages of a monkey model, since human-relevant assessments were used. The study was very well controlled, with both vehicle and AAV containing non-pathogenic length CAG repeat (10Q) used.

The behavioural assessment was comprehensive, and the motor control measures are relevant to HD. MR imaging is also very relevant to what can be measured in humans. The imaging was comprehensive and of excellent quality. Overall, the study presents some important and interesting data, because an acute monkey model has not been studied in such depth previously. The range of approaches taken to assessing the animals is comprehensive and impressive.

This is a study that will be of interest to researchers who are developing methods for studying the role of the caudate/putamen in behaviour. I agree with the statement that the model will be useful for studying the effects/causes of disruption to the cortico-basal ganglia. The effect of the lesions on cortical regions of the brain are interesting, and well presented.

Weaknesses<br /> The major weakness of the study is that with the interpretation of the results. The changes in tractography, behavior and TBM are what would be expected following lesions of the neostriatum. Indeed, all the data point to this being an acute lesion model, and in my opinion, the authors have made an interesting novel neurotoxic model (using a very relevant neurotoxin). Unfortunately, there is no detailed pathology showing what is happening at the level of the striatum or associated cortical regions (see also below). The results have been interpreted as showing a progressive model, although evidence that there is progression is limited. The whole manuscript is written as though this is a genetically-relevant progressive model of HD. But the animals are normal, and so there is no genetic context relevant to HD. While the authors present this as a new model of HD with progressive motor and cognitive changes (as seen in the title of the paper) there is little evidence presented that there are major 'progressive' changes seen. Furthermore, the idea that the changes mirror those seen in HD patients (as stated in the discussion) is somewhat misleading. While their data may be similar to some findings in patients who have early degenerative changes, there are many differences that are either not seen or not explored in the new model. In particular, evidence that the changes seen in the monkeys are relevant to progression of disease in HD patients is missing. While this appears to be a sophisticated acute lesion model that has been assessed more thoroughly than previous models, nevertheless all evidence points to it being an acute rather than a progressive model. While I agree that the data show clearly that there are changes in motor function and to a lesser extent in cognitive function caused by the injection of the AAVs, it does not follow that the changes seen are 'progressive'. Even in rats following striatal lesions, changes in behaviour have been measured for months afterwards. For example, in acute lesions of monkeys, Deglon et al showed years ago that in NHPs the behavioral sequelae of acute neurotoxic lesions change with time. This model also does not show 'progression' in the sense of a progressive disorder in HD.

The authors state in the Abstract that the injection resulted in "robust expression of mutant huntingtin in the caudate and putamen". These data are not in the manuscript. This seems to be deduced, rather than measured experimentally.

A disadvantage of the method used, that has been a bugbear of the field, is that the authors chose to use a fragment of the HD gene, with a very long repeat that is seen only in juvenile patients. While using the fragment rather than the whole gene is a sensible approach, since it is known to be toxic, I am not clear why they chose to use a juvenile length repeat rather than a repeat in the adult-onset pathological range. There are mouse models with a CAG repeat of 40-50, but short lifespan of mice has limited their usefulness. Longevity is one of the major advantages of using a monkey. Had they used a repeat of 45 or 50, this would have been a much more interesting paper, because there is little known about the toxicity of proteins with that length repeat in vivo. As it stands, the model is a non-human primate acute fragment model using a long repeat. The disadvantages of fragment models and long CAG repeats has been well discussed in the literature and is a major criticism of many of the mouse models. Consistent with the disadvantages of fragment models with long repeats, the onset of the symptoms of the monkeys is much more rapid that would be expected in either juvenile or adult-onset HD and is likely to be due to both the fragment nature of the vector and long CAG repeat. The rapid onset of phenotype is not discussed in the context of other models.

The use of a DA receptor agonist was an interesting idea, because DA agonists have been shown to exacerbate abnormal involuntary movements in HD patients. The mechanism for this is complicated, however, given that the balance of D1 and D2 receptors changes as HD pathology progresses. The authors chose to use a non-selective agonist, which caused transient changes in behaviour. However, the usefulness/relevance of the apomorphine data is unclear, particularly since the effect was only seen at the early timepoints and not at the later timepoints. If the AAV causes acute toxicity, then such changes in response to apomorphine would be expected, and this would be expected to resolve with time - as was seen.

For their cognitive testing, the authors used a task (delayed non-match to sample) that measures object recognition and familiarity. Before surgery, only 11/17 of the animals were successfully trained to complete this task. It is not clear how useful the data are when only 64% of the animals can be included. It would have been better to have choosen a task that all monkeys could perform at baseline.

The results of the motor task showed a clear deficit. This would be expected with an acute lesion of the striatum. It was interesting that there was a significant improvement from the 9-month point to the 20-month point in the 85Q lesioned monkeys, whereas the performance of the vehicle-treated monkeys plateaued. There appeared to be a deleterious effect on the 10Q monkey performance that was maintained. (This was not discussed in any detail but should be.) This begs the question as to whether or not the 85Q-lesioned monkeys would recover to a level similar to the 10Q animals if left for another 12 months.

The tractography and tensor-based morphology data are clear, and consistent with the idea that a Q85 fragment would be neurotoxic. The authors consistently suggest that this is relevant to early stages of HD, but there is little evidence presented to support this statement. The sensitivity of the MRI used shows that multiple regions were affected beyond the lesion sites. This would be expected and is new and interesting data in the non-human primate field, although it does not bring anything particularly new to the table with respect to HD (since similar findings have been shown in lesion studies using mice, rats and sheep).

For HD researchers investigating aspects of the disease, such as transition from prodromal to early symptomatic stages, or for developing treatments, the usefulness of this model will be limited. It is not clear how this monkey model will be useful for developing either disease biomarkers or therapeutic strategies for HD (as stated in the abstract). For studying biomarkers of the disease, this model lacks a number of critical parameters. First, the genetic context of the disease is missing. Second, it is known that HD has multiple sites of pathology, and that symptoms are not simply due to degeneration of the caudate/putamen and that multiple regions of the brain where mutant Htt is expressed become dysfunctional and eventually degenerate. Understanding how the caudate/putamen degenerate is important, but since last century HD researchers have been very aware that dysfunction in the HD brain occurs at many sites other than the caudate/putamen. Indeed, it is probably not only a brain disease since there is evidence of peripheral pathology in humans and other models.

The authors state that they hope the model will become a widely used resource. This seems an unlikely scenario, given the limitations of the current study and the challenges associated with using monkeys. They say that a major advantage of their technique is being able to generate large numbers of monkeys. But this is not a relevant argument if the usefulness of the model to investigate HD is not proven. Studying the role of the caudate/putamen in motor behaviour is interesting for a small field but limited in scope.

The authors suggested a number of experiments that could be done, for example, using a shorter HD-relevant CAG repeat length. But as stated above, this is a weakness of the current study, and it would be much more useful had the authors done this experiment themselves. It seems unlikely that until the authors prove its usefulness, this model will not become a widely used resource, since the disadvantages of the model outweigh the advantages. Using monkeys requires a specialist laboratory and facilities and a careful consideration of the ethics involved in animal experimentation. Unless the model offers clear advantages over other models, it is unlikely to become mainstream. It is also not clear what therapies could be tested in this model that could not be tested in other existing models. For example, given that there is no control over which cells are infected by the AAVs, or if any of the cortical pathology is due to spread of AAV from the initial sites of injections, it is not clear how antisense oligonucleotides efficacy could be tested.

Reviewer #1 (Public Review):

Zhang et al. use a mosaic vaccine design, where three SARS-CoV-2 spike receptor domains (RBD) are linked together, to make a multivalent vaccine: one of the RBDs has the Omicron sub-lineage BA.1 sequence, while another has a combination of 8 mutations from different variants. They show that rats immunized with this construct have improved neutralization of Omicron and other variants relative to a mosaic vaccine where all RBDs are ancestral, as well as relative to the Sinopharm BBIBPCorV inactivated virus vaccine either as the primary vaccination or as a booster of BBIBPCorV.

Reviewer #1 (Public Review):

This is an interesting study supporting the notion mPFC is involved in early learning stages while the striatum becomes more engaged as animals become proficient in a temporal task. However, I have several concerns about whether the results support the main conclusions of the paper. First and foremost, it is difficult to dissociate the role of mPFC and the striatum linked with a better representation of elapsed time with learning from the operational learning aspects of the task. The latter include the increase in attention of sensory inputs associated with the nose poke, an increase in precision of movement kinematics (less body and face movements during the nose poke), and a more developed reward expectation from learning to time the 1.5 s. The authors should perform careful analysis to try to dissociate the learning of temporal and non-temporal factors and the involvement of the two areas. Second, I have comments of the decoding analysis. It is now well known that the neural activity associated with timed behaviors scales with time. Since the decoding was performed on truncated trials at 1.5s, the analysis will not capture the neural pattern of activation in longer trials. Thus, this is decoding of absolute elapsed time using activity of neurons that probably are encoding relative trial length. In addition, it seems that both areas encode the beginning and end of the trials, with high densities in the diagonal only on the initial and final bins, rather than the elapsed time across all the trials. These results could be related with learning of non-temporal factors discussed previously. Furthermore, the decoding of elapsed time both areas went down from early to late trials in the experiment of one session, supporting the notion that the striatum does not take over, although the rats learned to time the interval. This is contrary to the conclusions of the paper. Finally, animals with mPFC inactivations did not change behavior of the first session, but they partially learned on sessions two, three and five (with an increase mu2). How are these findings matching with the observation that mPFC decoding performance dramatically lowers on the second day?

Public Review:

Using a Discrete Choice Experiment (DCE) the study asks respondents in six EU countries to choose between two persons A and B and select the one that they believe s/he should receive the COVID-19 vaccine first. Across eight different scenarios, each person is given different attributes in terms of age, COVID-19 mortality risk, employment status, and country of residence (own vs. other with low healthcare system capacity). The study found the risk of mortality and also working for essential services to be perceived as particularly important across all the countries. Moreover, living in a low-income country with poor healthcare system capacity was found to be favored when it came to allocating the vaccine first. This is particularly interesting given that the respondents were selected from those who were not vaccinated at the time of the survey but were willing to receive one.

Strengths:

• The study evidence is based on large samples from 6 EU countries.<br /> • It captures the opinion of those who had not been vaccinated at the time of the survey, hence, allocation to those in low-income countries indicated further altruism.<br /> • The method, a conditional logit estimate, and also the robustness checks are appropriate and suitable.<br /> • The study distinguishes between two key attributes of mortality risk and country of residence allowing for evaluating the importance of each factor separately. The implication of these factors can be helpful in making decisions in the future. This is in particular critical given that the initial aim of COVAX was to prioritize those who are vulnerable and the healthcare workforce across the world before launching national programs did not materialize and we are still facing large global disparities between the global north and south.

Weaknesses:

• The sample from Germany is noticeably different from the rest of the countries (particularly in terms of having a higher ratio of those who are in the high-risk category). This might have impacted the results and needs to be reflected in the study discussion. Also, there is heterogeneity between studies in terms of the time of the fieldwork and each country's conditions in regards to the vaccination roll-out and the number of infections at that time.<br /> • The manuscript narrative needs to be updated to reflect the present conditions in terms of inoculation campaigns, their success rate, and their disparities across the world.<br /> • There is space for more discussions on an interesting finding of the study that is prioritizing the vaccines according to employment status and in particular income loss.<br /> • The temporal nature of the public views at various stages of the pandemic and vaccination campaigns should also be noted.

Reviewer #1 (Public Review):

This article creates a formal definition of the 'informativeness' of a randomized clinical trial. This definition rests upon four characteristics: feasibility, reporting, importance, and risk of bias. The authors have conducted a retrospective review of trials from three disease areas and reported the application of their definition to these trials. Their primary finding is that about one quarter of the trials deemed to be eligible for assessment satisfied all four criteria, or, equivalently, about three quarters failed one or more of their criteria. Notably, industry-sponsored studies were much more likely to be informative than non-industry-sponsored studies. It would be interesting to see a version of Figure 3 that categorizes by industry/non-industry to see the differences in fall-off between the four criterion.

As the authors point out, the key limitations to this work are its inherent retrospective nature and subjectiveness of application, making any sort of prospective application of this idea all but impossible. Rather, this approach is useful as a 'thermometer' for the overall health of the type of trials satisfying the eligibility criteria of this metric. A secondary and inherent limitation of this measure is the sequential nature of the four criteria: only among the trials that have been determined to be feasible (the first criterion measured) can one measure reporting, importance, and lack of bias. And only among those trials that are both feasible and reported properly can one measure their importance and lack of bias, and so forth. Thus, except for feasibility, one cannot determine the proportion of all trials that were properly reported, were importance, or evinced lack of bias.

Reviewer #1 (Public Review):

In this study, Trolle et al set out to investigate the impact of reintroduction of essential amino acid biosynthetic pathways into mammalian cells. To this end, they employed an elegant synthetic genomic approach to enable Chinese Hamster Ovary cells to endogenously produce methionine, threonine, isoleucine, and valine. Notwithstanding that attempts to functionalize biosynthesis of methionine, threonine and isoleucine were not successful, reintroduction of valine biosynthetic pathway rescued survival of Chinese Hamster Ovary cells deprived of valine. Moreover, the authors provide evidence that global mRNA abundance profiles in valine biosynthesis-proficient Chinese Hamster Ovary cells mirror those observed upon recovery from valine starvation. Collectively, these pioneering studies suggest potential for the functionalization of biosynthesis of essential amino acid in mammalian cells. Based on this, it was found that this study is of broad interest to a variety of research fields including synthetic biology, biotechnology, and biochemistry.

Strengths: This study incorporates a very elegant synthetic genomic approach to address a long-standing gap in knowledge related to exploring the ability of mammalian cells to tolerate restoration of essential amino acid biosynthesis. It was highly appreciated that this is one of the pioneering attempts to address this question. For the most part, the data were robust and supportive of the author's tenets. Finally, demonstration that Chinese Hamster Ovary cells can be rendered prototrophic for valine may open many interesting avenues in the domains of synthetic biology and biotechnology, with potential long-term applications in medicine.

Weaknesses: Relatively modest rescue of proliferation of valine-producing Chinese Hamster Ovary cells in valine-free media, apparent reduction in de novo valine synthesis during propagation of the cells and some technical issues pertinent to potential utilization of valine from breakdown of serum proteins were considered as the weaknesses of the study. Furthermore, it was thought that further molecular characterization of valine-prototrophic Chinese Hamster Ovary cells may be warranted.

Reviewer #1 (Public Review):

This manuscript uses a wide range of experimental and computational techniques to address how mice use active vision to gauge distance in a gap-jumping task. It is found that for this task, the animals can compensate for the lack of binocular vision via an increase in active head movements, to perform the overall task with similar effectiveness. When the primary visual cortex (V1) is temporarily inactivated using optogenetic techniques, the animals perform much worse, suggesting a critical role for V1 in distance estimation.

The paper makes substantial technical advances in the understanding of gap jumping in mice. The data are convincing that the animals can rely on monocular information to nearly equal effect as binocular vision. However, the reasons for this were somewhat murky: the authors concluded that the animals performed more active sensing movement, but the use of HMMs as the only means to assess this was a weakness of the manuscript. Roughly, they showed that the "recurrent" connections in an HMM were stronger with monocular vision than binocular, i.e. the mice tended to repeat certain motifs that the authors suggest were related to sensing the distance. There are several major weaknesses with this as the only approach. First, it is unclear in plain statistical terms what differs in pre-jump behavior. Second, it is unclear how these dynamical systems motifs are related to any kind of active sensing behavior. Third, and as a consequence, it is unclear any potential mechanistic benefit of the change in pre-jump behavior.

There are also a few weaknesses to the V1 analysis. First the only analysis of the effect of inhibiting V1 was basically that more of the animals chose not to jump. But, was their accuracy worse when they did jump? If not it is entirely unclear that V1 is involved in the distance estimation and in fact one could argue that they can judge the distance fine without V1 (which of course would not mean V1 were not used).

Reviewer #1 (Public Review):

The congenital condition posterior urethral valves (PUV) is a major cause of end stage renal disease in young males. While prior work has partially characterized the genetic landscape of this condition, Its pathogenesis remains poorly understood so any new insights will be of broad interest to pediatric nephrologists, urologists, geneticists and developmental biologists. The study by Chan et al makes a significant contribution to this story. Here, the authors have used for the first time a diverse ancestry whole-genome sequencing approach to tackle the problem and have identified variants within/near two genes, TBX5 and PTK7, as being significantly associated with this condition in both their original cohort as well in a replication study. The data are compelling and are a good example of the power of applying a diverse ancestry approach to disease locus discovery in rare disease. They also were able to use this approach to fine map variants inferred to be causal. This study's use of WGS provided other advantages: they could identify rare exonic variants and small structural variants missed by conventional microarrays. This strategy resulted in two additional observations: 1) none of the genes previously associated with congenital bladder outflow obstruction were associated with PUVs, showing that monogenic causes of PUVs are rare; 2) an enrichment in PUV cases of rare inversions affecting candidate cis-regulatory elements, with the strongest signal for inversions affecting CTCF-only regions.

While the genetic associations appear robust, there are a number of weaknesses to this study. The most obvious and important one is that all of the findings are associative, and none are experimentally validated. The authors nicely use bioinformatic methods to show that the variant near TBX5 may map into the same topologically associated domain, but they provide no direct evidence that this variant directly affects TBX5 expression. The closest they come to providing any link is by showing possibly permissive expression of TBX5 in relevant tissues. Likewise, they suggest that the intronic variant in PTK7 may disrupt the binding domain for at least two transcription factors, though neither is experimentally evaluated, and they provide no direct evidence showing that this variant affects the expression of PTK7. It should also be noted that their immunohistochemical studies of human fetal tissue for TBX5 and PTK7 are not convincing. There appears to be widespread staining of multiple cell types, suggesting either very broad expression of both genes or poor specificity of the primary antibodies. There is, of course, no reason that a broadly expressed gene cannot have organ or tissue-specific effects when its activity is altered, but these data do not provide compelling evidence that either TBX5 or PTK7 is functionally important in this condition. Further highlighting the importance of this issue, PUVs have not been described as a clinical manifestation of disease associated with mutations of either gene in humans. Finally, it would be useful for the authors to discuss how variants in either gene or in the patterns of structural variants that they found associated with PUV intersect with sex to result in this exclusively male condition.

Reviewer #1 (Public Review):

In this paper Bonnard et al. describe the development of a new method to quantify C. elegans feeding behaviour. The circuit mechanisms underlying feeding behaviour of worms are not fully understood and studying them potentially can lead to fundamental new insights into the control of rhythmic behaviours in general. In classical work, the up to 5Hz peristaltic movements of the worms' pharynx were assessed manually, a painful procedure which is challenging and error prone. Alternative methods have been developed, either by video recording and subsequent slo-mo manual analysis, or recording of electropharyngeogram in microfluidic devices, however, these prevent observations in unrestrained behaving animals. The approach reported here is based on a sophisticated image processing pipeline analysing freely moving worm populations of animals with fluorescently labelled pharynges. The authors convincingly show that peristaltic pumping rates can reliably be measured across development, under various feeding conditions and capturing known and previously undescribed phenotypes of feeding mutants. The method represents a significant improvement and possibly seems applicable to researchers in the community; however, it cannot measure detailed aspects of pharyngeal dynamics like it is possible with electropharyngeogram recordings. I see great potential also to perform long-term recordings, this unfortunately is not addressed in the current manuscript.

Reviewer #1 (Public Review):

This manuscript investigates the cellular and developmental defects underlying Wolbachia-induced cytoplasmic incompatibility (CI), which occurs when male insects harboring the endosymbiont bacteria Wolbachia fertilize eggs of uninfected females, triggering embryonic lethality at the first nuclear division. Characterization of the mechanisms of CI has implications for pest control in insects beyond Drosophila, and thus this topic will have broad interest.

Previous work, including by the Sullivan lab, has shown that CI is caused by a paternal effect in which the sperm from a Wolbachia+ male triggers a dramatic early failure in the first nuclear division within the newly fertilized Drosophila egg. In this work, the authors provide compelling evidence that there is an additional, later defect that is present in ~30% of the affected embryos. These defects occur at the mid-blastula transition and beyond. They go on to show that these later embryonic defects can be due to loss of the paternal genomic DNA (creating haploids) which could be due to the early fertilization defect, but also a chromosome segregation defect independent of haploidy or the initial fertilization defect. They use elegant single embryo PCR, pooled blastoderm genomic sequencing, and FISH methods to track the origins of the blastula defects; this is a compelling set of experiments! Taking all their results together, they conclude that the latter phenotype is due to a distinct molecular mechanism than that inducing first division defects. The paper is well written and easy to follow.

Reviewer #1 (Public Review):

This is a very interesting paper showing that postsynaptic bursts in the presence of dopamine produce input-specific LTP in hippocampal synapses 10 minutes after they were primed with negatively coincident pre- and postsynaptic activity. LTP requires NMDAR activation during priming and involves a cAMP-PKA cascade and protein synthesis. When this synaptic rule is incorporated into a computational model, reinforced learning is possible through selective reactivation of neurons. Experiments in behaving mice confirmed that neurons reactivated after an exploratory period display more activity than non-reactivated neurons.

Reviewer #1 (Public Review):

This manuscript describes a novel role of the centrosomal protein CEP83 in mesoderm patterning, specifically the balancing between the intermediate mesoderm (IM) and the lateral plate mesoderm (LPM). The authors nicely demonstrate that CEP83 is required for the accurate formation of the IM and differentiation into the kidney lineage. This is achieved by generating CEP83 knockout iPSC lines and differentiating these into mesoderm cultures and kidney organoids. The most obvious defects in the knockout situation are ciliary abnormalities (in the mesoderm monolayer as well as 3D organoid cultures), indicative of the critical role of the cilia in normal kidney formation. Strikingly, the CEP83-deficient cultures completely fail to undergo further differentiation into kidney epithelia as shown by immunohistochemistry for nephron and podocyte markers. Thorough transcriptomic and bioinformatic analyses provide insights into these defects on a molecular basis, i.e. the CEP83 knockout appears to favor the formation of the LPM at the expense of the IM, with LPM-specific marker genes strongly upregulated in the knockout. A possible key role for the transcription factor HAND2 is discussed.

Strengths and appraisal<br /> A major strength of this work is the use of cutting-edge technologies, including the CEP83 knockout in iPSCs, mesoderm and kidney organoid cultures, and bulk and single cell transcriptomics. These techniques provide strong data, which support the conclusions of this study.

Weaknesses<br /> There are no major weaknesses.

The impact of this work is strengthened by its relevance to human kidney disease, i.e. CEP83 mutations that manifest, amongst others, in the kidney. It is also interesting for the field of researchers that use kidney organoids from human pluripotent stem cells and their ongoing attempts of improving the organoid model to more accurately recapitulate human kidney pathologies.

Reviewer #1 (Public Review):

In this study, Ravindran et al. describe heterozygous de novo variants in the CRMP1 gene in three unrelated kindreds with muscular hypotonia, autism spectrum disorder, and/or intellectual disability. Based on in silico analysis these variants are predicted to affect the CRMP1 structure. The effect of these variants on the protein structure/levels and cellular processes was analyzed. The authors show that the identified CRMP1 variants are dominant-negative and impact the oligomerization of CRMP1 proteins. Moreover, overexpression of mutant-CRMP1 variants affects neurite outgrowth of murine cortical neurons. It has been known that maternal autoantibody reactivity to CRMP1 significantly increases the odds of a child having a higher Autism Diagnostic Observation Schedule (ADOS) severity score (PMID: 33483694), and increased CRMP1 mRNA levels were identified in individuals with schizophrenia and autism spectrum disorder (PMID: 22798627). Mice lacking Crmp1 expression manifest hyperactivity, impaired learning, memory, and prepulse inhibition (PMID: 24409129). Previous findings strongly support the involvement of CRMPs in neurodevelopmental disorders. It is known that the mammalian CRMP family consists of five cytosolic family members (CRMP1-5) and are highly expressed in the developing and adult nervous system. Monoallelic CRMP5 variants can cause Ritscher-Schinzel syndrome 4 (MIM#619435).

Regarding studies:<br /> In family 1, whole-exome sequencing (WES) was performed on a HiSeq XTen Deep Sequencer (Illumina, CA, USA), with an average coverage of ~36X, which is lower than expected. CRMP1 variant segregation was confirmed by Sanger sequencing.<br /> In family 2, the variant was detected by routine trio-based WES diagnostics. Sanger confirmation was not performed. IGV images can be added as supplementary material. Furthermore, median coverage was 75× which might not be sufficient for the identification of all heterozygous variants.<br /> In family 3, trio-based whole-genome sequencing was performed. Variants >4kb were called using CNVnator (v0.4.1) and annotated with AnnotSV (v2.5.1). An average depth-of-coverage of >50x was obtained. Sanger sequencing was performed to confirm the identified mutation in the CRMP1 gene.

Regarding Results:<br /> Proband 1 (P1) was born as the second child of non-consanguineous healthy parents of Caucasian descent after an uneventful pregnancy. At delivery, a singular umbilical artery was noted. P1 has a moderate intellectual disability and behavioral abnormalities. Chromosome analysis and array-CGH were normal in the index patient (P1). The identified NM_001014809.2(CRMP1_v001):c.1766C>T variant has not been reported in publicly available databases.<br /> Proband 2 (P2) was born as the second child of non-consanguineous parents of Caucasian descent after an uneventful pregnancy and delivery. The boy was macrosomic at birth. Since there was macrosomia, how would the pregnancy be uneventful? At the last assessment at 10 years of age, obesity associated with hyperphagia was of concern; the weight of the patient should be clarified. P2 was diagnosed with autism spectrum disorder but a normal cognitive profile. The identified NM_001014809.2(CRMP1_v001):c.1280C>T variant is very rare and reported in GnomAD exomes with allele frequency 0.0000041.<br /> Proband 3 (P3) is the first of three children of a non-consanguineous family of European descent. There is a familial history of obesity on both parental sides, and the father is macrocephalic (head circumference: 60.5 cm). Macrocephaly can be isolated and benign, such as in benign familial macrocephaly. However, P3 presented with moderate intellectual disability and an autism spectrum disorder. Since P3 has a macrocephaly also, the PTEN gene should be further interrogated by detailed WGS data analysis as well as an additional orthogonal method(s) since it has pseudogenes.<br /> Array analysis revealed two maternally inherited deletions: a 668 kb deletion at 3q26.31 and a 371kb at 5q23.1, confirmed by genome sequencing and considered a variant of unknown significance. The identified NM_001014809.2(CRMP1_v001):c.1052T>C variant has never been reported in the publicly available databases.<br /> Regarding the protein purification, the transient expression, the Western analysis (denaturing and native), and neurite length (4 independent experiments) all seem clean experimental data. The Western blots are clean, and band strength supports the authors' claims. Fluorescence images of the neurons (Fig 3) were not provided but the plots of the four experiments support again the authors' conclusions.<br /> To analyze the effect of CRMP1 variants on its protein levels and cellular function, two isoform variants (CRMP1B-P475L (P1) or -T313M (P2)) were chosen for further functional analysis. CRMP1B T313M and/or -P475L expression might perturb the oligomerization of CRMP1B-wildtype in a dominant-negative manner. Based on the data P475L may exhibit a stronger dominant-negative effect than T313M.

Reviewer #1 (Public Review):

Codjoe and colleagues report a combined proteomic and genetic analysis of MSL protein function in the context of mechanosensing in Arabidopsis leaf epidermis. The study identifies MSL10 as being associated with proteins residing in ER-PM contact sites (EPCSs). This is a novel and interesting observation and offers a new context in which to evaluate MSL activity in mechanosensing. It is striking that genetic suppressor analysis of a gain of function msl10 allele also identifies two components of EPCSs as suppressors.

This firmly associates MSL10 with EPCS. However, beyond this association, the study does not identify a clear mechanism of action or even relevance of EPCS localization or relevance of the MSL10/VAP27/SYT1 interaction. There is some indication based on synthetic lethality between msl10 loss of function and VAP27 or SYT1 overexpression that the interaction is relevant, but most direct assays for localization are negative. As a consequence, there is much interesting speculation in the discussion, but I find this somewhat unsatisfying.

Reviewer #1 (Public Review):

In this manuscript, the authors build off prior work identifying LamA as a mycobacterial protein required for asymmetrical cell division. The authors identify PgfA as a LamA protein interaction partner. A PgfA homolog has been studied in corynebacteria where it has channel activity and is involved in lipoglycan synthesis but had not been assigned a function in mycobacteria. The authors show that PgfA is essential in mycobacteria, and interacts with MmpL3, as well as a TMM analog. The data presented are interesting, important for the field, and convincing. However, the authors also make a number of conclusions in the text for which there is no data shown.

Reviewer #1 (Public Review):

The authors provide compelling evidence that the protein kinase GCN2, which is an arm of the integrated stress response (ISR) in cells deprived of amino acids and nutrients, displays a pro-tumorigenic role in prostate cancers.

The strength of the manuscript is its novelty, the well-performed experiments, and the very good quality of data and their analysis. The weak points are focused on a better explanation of the mechanisms of GCN2 function based on the presented data. Minor issues relate to the inclusion of a few control experiments to further improve the quality of the data.

Reviewer #1 (Public Review):

The authors report experiments and a mathematical model to understand how a flow network of Physarum polycephalum rearranges the channel radii in time. The topic is interesting since fluid flows in networks are ubiquitous and in many living systems the networks are not static but instead can rearrange over time. The variables that control the rearrangements, including growing and shrinking different flow channels, are still not understood though apparently often it is assumed that the local shear rate dictates time-dependent network dynamics. In this paper, the authors demonstrate using experiments that there is a time delay between the change in the flow and the change in the network geometry, and that network architecture-dependent parameters, such as the local shear rate in a channel, and the resistance of flow in a part of the network, relative to the resistance in the rest of the network, can be used to predict vein dynamics. For example, the authors observe vein dynamics by tracking vein radius and shear rate over time and identify regular behavior, e.g., usually stable veins perform looping trajectories in the shear rate-radius space shown in Figure 1, which appears to correlate with an in/decrease in shear followed by an in/decrease in vein radius yielding shear feedback on local vein adaptation. In contrast, usually in shrinking veins, the relation between shear and vein adaption is ambiguous, to use the authors' words. Their data makes clear these main features and the authors construct a mathematical model that helps understand the observed instabilities (channels shrink and disappear) or stability (channels can periodically grow and shrink). It is the features of the time dependence of the network, and identifying variables and a macroscopic model for the dynamics, that I think are the novelties of the paper and so most likely to be impactful in the field, e.g., vein fate being determined by network architecture dependent parameters, such as relative pressure and relative resistance. That said, I find some of the writing unclear and some of the figures challenging to read and understand. Also, it was unclear what might have been reported in several of the referenced papers that highlight dynamical features relevant to this paper.

Reviewer #1 (Public Review):

The manuscript by Rial et al. describes an interesting interaction between the dFOXO transcription factor and the transposable element (TE) activity in aging using Drosophila. The authors find that dFOXO deletion mutants lead to elevated TE expression. They go on to use Drosophila molecular genetics to over-express the gypsy retrotransposon coding sequences and show deleterious effects on lifespan. They show that a wild-type reverse transcriptase (RT) enzyme is required for the reduced lifespan. Interestingly, the effects are only observed in "middle-age" flies. The authors also go on to show that there are defects in circadian rhythms in the flies over-expressing gypsy.

Reviewer #1 (Public Review):

Yang et al. provide a scientifically sound and compelling manuscript.

Strengths:<br /> -Very thorough study characterizing transcriptional and secretory responses of organoids derived from mid-to-late gestation at baseline and after viral infection.<br /> -Establishes organoids as an important model to study vertically transmitted microbial infections.

Weaknesses:<br /> -Discussion and characterization of what each organoid type is specifically modeling (orientation/cell types) is important for context to fully grasp inherent strengths and weakness of model.<br /> -Despite commonly indicating TO and DO are matched, the use of this matched specificity is not utilized either experimentally or in the interpretation of data.<br /> -Given gestational age can putatively impact outcome, a better understanding of the result of each organoid line in terms of specific gestational age derived is warranted.<br /> -There is only a single readout for viral infection with quantification being % infected organoid (which could include organoids with only a single cell or hundreds of cells infected). A more fine-tuned quantification seems necessary given the conclusions of the manuscript.

Reviewer #1 (Public Review):

The authors asked to what extent early visual and visuomotor experience is essential for developing the ability to recalibrate the visuo-motor system flexibly. This kind of recalibration crucially underpins everyday actions, allowing the brain to issue effective feed-forward motor control commands that correctly account for temporary changes in sensory-motor mappings (e.g. when using tools, carrying objects, wearing new glasses). To address the role of experience in developing these recalibration abilities, they used the unusual clinical population of late-operated cataract patients: children and adolescents who initially had many years of sensory experience that is atypical in that it lacked effective pattern vision. They used a standard sensory-motor task in which participants point to targets with and without displacement of the visual image via a prism lens: after the prism displacement, the visuo-motor mapping needs to be recalibrated to enable effective pointing. They compared late-operated cataract patients with controls matched in age, controls matched in both age and visual acuity (via added visual blur), as well as an extensive broader comparison group of typically developing 6- to 17-year-olds. Their key findings were that recalibration was less effective - both in the initial effect and in the subsequent after-effect - in the patient group than in control groups; this was not related to chronological age but was related to time post-operation, such that performance came to match controls after around 2 years of improved visual experience. The authors conclude that flexible sensory recalibration abilities normally rely on extensive sensory-motor experience in childhood, and suggest that the underlying computational problem is establishing the correct correspondences between sensory and motor coordinate frames. This may be achieved through extended exposure to the sensory consequences of self-generated movements.

Strengths of the approach include use of the established (although rare and difficult to access) model population of late-operated cataract patients and a well-established experimental task (pointing after displacement of the visual image by viewing through prism lenses). The task has a known typical time-course of behaviour - supplemented here by an extensive additional study on typical development using the exact same main task, which even alone would be a meaningful contribution to literature on sensory-motor development. The procedure, measures, analysis, and the approach to control groups are careful and rigorous. The findings are rich in showing not only an initial deficit in patient vs control groups but also an approximate time course for further learning and development after which point (by ~2 years) the patients come to match controls. A challenge is the heterogenous group, in terms of age at operation and ages at testing and follow-up. However, this is very usual and almost inevitable in the literature with this kind of population, and is dealt with well in the analyses. The approach is also well supplemented by repeated follow-up of a portion (actually more than half) of the group.

One potential issue is the role of baseline pointing precision differences across the groups. It would be useful to better understand the potential role of the reduced pointing precision that was found in the cataract group (Supplemental Figure 1B). It is not surprising that, following visual deprivation, this group's predictive feedforward visuo-motor control was less precise than that of controls, even in the baseline measures before any prism manipulation, and even when the controls' vision is comparably blurred. It seems likely (although is not shown) that during the adaptation phase and the post-adaptation phase, the variability of individuals around their (gradually shifting) mean pointing location would also be higher than in controls. I wonder how large an explanatory role there could be simply for this noisier initial visuo-motor mapping in the patient group. It might be said that, on each trial, they intend to carry out a feedforward plan with a certain endpoint, but because of noise, they are on average substantially further from that endpoint than comparable controls are. So, during recalibration, while controls are dealing mainly with cancelling out one kind of error - the constant error due to the prism adaptation - the cataract patients are also dealing with more variable errors due to their own noisier visuo-motor system. In theory, could this alone - higher initial noise in the system - explain the difference? This seems like a simpler explanation than that the system has developed differently in substantial ways to do with its abilities to learn and adapt. One starting point for checking in to this would be asking if initial pointing variability predicts recalibration (perhaps controlling for visual acuity), both at first test and in the repeated participants. Another would be looking into ways to perturb controls' baseline pointing performance further (perhaps with something like an unexpected added weight rather than more visual blurring) so that their variable pointing errors were matched to the cataract group.

Another question is how well the contrast sensitivity function (CSF) as a whole (not just the maximum acuity point) was matched - this is dealt with only briefly. I am not sure to what extent the blurring manipulation would be expected to change the shape of the CSF as a whole to be in line with that of patients, and to what extent other aspects of the CSF besides the maximum acuity point determine the precision and accuracy of ballistic pointing movements under the experimental and lighting conditions used in the study. Depending on the answers to these questions, the concern could be that visual differences relevant to control of pointing remained across the patient and blurred control groups.

Another more minor or technical issue is some lack of detail in how the calibration index, which feeds into most of the key analyses, is calculated. It is likely that many different ways of doing this would lead to similar conclusions, but it should be clear, including for the sake of replicability.

Reviewer #1 (Public Review):

Ribonucleotide reductases (RNR) share low sequence similarity, which makes it challenging to infer their phylogeny with traditional methods. To accurately decipher their evolutionary history and evolutionary relationships between different clades the authors combined a structure-based workflow developed by Spence et al. (Reference 1) and a state-of-the-art evo-velocity analysis. Thus, they present a convincing phylogenetic map of RNR, among which they found a clade Ø unknown before and determined its cryo-EM model. One strength of this study is that the analysis pattern utilized in this paper can give a good example of the analysis of protein families which are highly diverse in sequence but share an overall conserved structure core, and thus this analysis pipeline may be implemented in other protein families. The weakness of this study is that the catalytic function of RNRs from the novel clade Ø is not well characterized, such as the ferritin-like domain. It would be interesting to design comprehensive biochemical experiments on this novel clade RNR and maybe the authors will do that in the near future. On the basis of the large-scale phylogeny of RNR, the authors studied three extension/insertion regions of RNR, including N-terminal ATP-cone, C-termini of class II RNR and finger-loop-motif of Class III RNR. These discoveries systematically reveal the plasticity and evolvability of RNRs, which may lead to a model to depict the complete evolutionary history of RNRs. Another weakness is that the descriptions on these extensions/insertions are somewhat scattered and lack a summary model/illustration/table to unify all discoveries. Overall, this manuscript can promote the understanding of RNRs and protein evolution, and the methodology utilized in this study may offer a reference of other diverse protein families.

Reviewer #1 (Public Review):

The authors use a novel Satellite Glial Cell (SGC)-enriched promoter Blbp to target diphtheria toxin (DTX) killing, then analyze changes in sympathetic ganglia and autonomic function. These changes are compared to those resulting from similarly targeted deletion of Kir4.1 channels. To summarize, tamoxifen induction of DTX in adult mice led to >50% reduction in cervical sympathetic SGCs, a substantial decrease in adrenergic enzymes (~90-99% loss of TH and DBH), smaller neurons, and decreased pS6 (from which impaired mTOR is inferred), loss of ~25% neurons but 8-fold cFOS activation, and maintained axons and 60% increased circulating NE. Expression of certain adrenergic receptor subtypes was also found to be decreased. Conditional knockdown of Kir4.1 (by ~75% in RT-PCR) led to no apparent decrease in SGC numbers (judged by Sox2 and Blbp staining), ~60% decrease in TH and DHB, increased numbers of smaller neurons and impaired mTOR signaling, loss of about 20% neurons and increased cFOS.

Although cellular effects of DTX ablation and Kir4.1 deletion in SGCs overlap considerably, the overlap does not include changes in autonomic function, where the DTX and Kir4.1-targeted deletion mice were quite different. DTX led to increased sympathetic activity (increased pupil size without apparent parasympathetic change in constriction and increased rate but reduced variability in heart rate). However, none of these changes were observed in the Kir4.1-targeted mice. The authors conclude that satellite glia is important for sympathetic neurons, partly through the provision of Kir4.1 channels and spatial buffering of potassium.

Strengths of the paper include the use of the novel promoter (which is stated to have ~50-fold higher abundance in SGCs than astrocytes) and the dataset itself, which is for the most part thorough and convincing Issues include specificity of the targeting, opposite effects on sympathetic function reported from studies using DREADD activation of SGCs, and conclusions regarding Kir4.1 effects and mechanism.

Concerning specificity, CNS involvement through effects on other cell types is not totally ruled out in these studies, and effects on the same cell type but in other ganglia (parasympathetic and sensory) might be expected to impact sympathetic function. For example, as Vit (2008) reported that following shRNA knockdown of Kir4.1 in trigeminal ganglia hypersensitivity to mechanical stimulation could affect autonomic activity. The authors tested for the influence of parasympathetic using pupillary constriction, and it is somewhat surprising that there is no deficit if neuronal death and dysfunction are as profound in parasympathetic ganglia as shown here for the superior cervical ganglia.

Physiological effects of DTX but not Kir4.1 deletion increased sympathetic activity, whereas increased heart rate was also observed following chemical activation of SGCs using DREADD ligands (Xie et al., 2017). This opposite action is not discussed at length but is attributed to "context-dependence." Inconsistent results with stimuli believed to target the same substrate are worthy of additional consideration by the authors. An alternative conclusion from the finding that the similar cellular level changes in sympathetic neurons induced by DTX and Kir4.1 cKO led to distinct changes in autonomic tone is that the neuronal phenotype does not dictate whole animal physiology.

Spatial buffering is given as the proposed benefit of Kir4.1 channels to the sympathetic neurons. However, this concept arose from studies in which clearance of local extracellular space was limited, and astrocytes were appreciated to be connected to a vast syncytium allowing siphoning away from the high levels near active neurons. The organization in peripheral ganglia differs in three major respects: Despite narrow extracellular space, there is no true barrier to diffusion of K ions from the neurons (one factor that makes drug targeting peripheral neurons appealing), SGCs are very thin (and thus without spatial consequence to uptake), and the coupling among the SGCs is local to those surrounding individual neurons, with very little coupling under normal conditions to other distal SGC-neuron units.

Reviewer #1 (Public Review):

The authors ask an interesting question as to whether working memory contains more than one conjunctive representation of multiple task features required for a future response with one of these representations being more likely to become relevant at the time of the response. With RSA the authors use a multivariate approach that seems to become the standard in modern EEG research.

I have three major concerns that are currently limiting the meaningfulness of the manuscript: For one, the paradigm uses stimuli with properties that could potentially influence involuntary attention and interfere in a Stroop-like manner with the required responses (i.e., 2 out of 3 cues involve the terms "horizontal" or "vertical" while the stimuli contain horizontal and vertical bars). It is not clear to me whether these potential interactions might bring about what is identified as conjunctive representations or whether they cause these representations to be quite weak. Second, the relatively weak conjunctive representations are making it difficult to interpret null effects such as the absence of certain correlations. Third, if the conjunctive representations truly are reflections of working memory activity, then it would help to include a control condition where memory load is reduced so as to demonstrate that representational strength varies as a function of load.

Depending on whether these concerns or some of them can be addressed or ruled out this manuscript has the potential of becoming influential in the field.

Reviewer #1 (Public Review):

The manuscript is well written, clearly describes the scientific background and hypotheses, and provides a sound illustration of the results, which can advance our current understanding of the neural basis of decision-making processes. The main conclusion is that pallidal stimulation in patients with dystonia leads to an increased number of exploratory choices, i.e. choosing the option with a lower expected value instead of exploiting the option with the highest expected value. There are, however, some shortcomings that limit the interpretability of the data in its current form regarding the lack of a healthy control group, inconsistency between frequentist and Bayesian statistics applied, and the limited specificity of the connectome correlation analysis. These shortcomings should be addressed by the authors in order to improve the paper.

Detailed description of comments:

(1) Generalizability:<br /> Studying dystonia patients gives the unique opportunity to study the effects of electrical pallidal stimulation on decision-making in humans and given that dystonia primarily affects movements rather than cognition/decision-making this might also well be representative of healthy people. This (i.e. the similarity between task performance of patients and healthy people) is, however, not demonstrated in this study. In the introduction, the authors state that reward prediction error is intact in dystonic patients, but the paper that they cite for this (ref 34) is titled '... abnormal reward learning in cervical dystonia'. Furthermore, albeit clearly less pronounced than movement symptoms cognitive problems are present in dystonia patients (see Jahanshahi 2017 Movement Disorders). I would therefore recommend enrolling a healthy control group allowing to compare DBS ON and DBS OFF to healthy people.

(2) Statistics:<br /> I understand that Bayesian statistics cannot always directly be compared to non-Bayesian frequentist statistics. However, to me, the frequentist and Bayesian statistics are not consistent in this study. ANOVAs, etc are applied on subject-averages data using a p-value of 0.05 to distinguish between significant vs. non-significant results. In the Bayesian modelling analysis, the 95% HDI is computed. While this number is arbitrary (just as a p-value of 0.05) it still has a rationale to it given that in the scientific community 95% is also used for frequentist confidence intervals. Therefore, I think that 95% would be the most consistent choice here. However, none of the model parameters differ between ON vs. OFF regarding the 95% HDIs, since they overlap with 0 (see 'Contrast' in table 1). Especially the decision threshold and drift rate scaling parameter HDIs have a large overlap with 0, but they are still interpreted as significant based on the Bayes factor. The Bayes factor, however, is not used for the behavioral analyses. For example, there are no effects of DBS on decision times, but at the computational level, several parameters (which predict the decision time) are affected. I think for the sake of consistency of analyses within the paper the statistics of the Bayesian analyses should rely on the 95% HDI.

(3) Connectome correlation analysis:<br /> If I understand it correctly, the connectome analysis relates behavioral effects of stimulation to whole-brain networks rather than just local effects in the pallidum by testing whether patients who showed stronger effects of stimulation have electrodes that are closer to connections with different brain areas. In the abstract, the results of this analysis are reported as "... was predicted by the degree of functional connectivity between the stimulating electrode and prefrontal and sensorimotor cortices". In the discussion, it is stated that "...DBS-induced enhanced exploration correlated with the functional connectivity of the stimulation volume in the GPI to frontal cortical regions identified previously in functional imaging studies of explore-exploit decision making ... The exploration-enhancing effects of GPI-DBS in our study were predicted by functional connectivity to brain regions whose neurons encode uncertainty [27] and predict behavioural switching[430 29, 30]". However, figure 4 essentially shows that almost the whole brain correlates with inter-individual differences in behavior reaching correlation coefficients as strong as -0.7 e.g. lower brain stem, cerebellum, and occipital cortex, none of which are mentioned in the paper. To me, it seems that there are correlations with very large and very distributed cortical areas rather than with specific areas in the prefrontal and sensorimotor cortex as stated in the paper.<br /> Related to this point: The variable used for the connectomic correlation analysis is not the same variable that was affected by DBS in the statistical analysis. The statistical analysis found that P(explore) differed between DBS ON vs OFF irrespective of the session. Instead the "maximum within-session increase in P(Explore) DBS-ON - P(Explore ) DBS-OFF" was used.

In general, could you please explain this analysis in more detail? If I understand it correctly each voxel had a value for 'connectivity' to the stimulation field and a value for 'behavioral effect' and across patients, this then gave an R-map. How was figure 4 thresholded (only the maximum positive and negative Rs are given in the color bar)? Then p-values are listed. One is 0.04 and another one is 0.009. What is the difference between the two? These values seem to reflect the correlation of similarity between the individual map with the group map and the behavioral variable, but was the correlation with the behavioral variable not already used for creating the R-map? Describing the analysis in more detail might help make it more understandable to the audience not familiar with the analysis (including me).

4) It is my understanding that high exploration (e.g. P(Explore) of 0.2) should be related to poorer task performance since the optimal strategy would always use the high-value option and only switch rarely to identify the reversal(s). Why is it then that DBS can affect exploration but not the sum of rewards if the two are related? Should DBS not affect the sum of rewards if it for example was more pronounced in its effect on P(explore)?

5) Would the authors have predicted different effects for subthalamic deep brain stimulation? The DBS effects on the GPi are mainly interpreted in terms of reduced firing rate/activity. Since the STN exerts glutamatergic innervation of the GPi, should STN suppression lead to similar results? Conversely, GPe exerts GABAergic innervation of the STN. Should GPe suppression lead to the opposite behavioral effect? Were some of the electrodes localized within or close to the GPe rather than GPi and if so, did these patients show different behavioral effects?

6) Was the OFF vs ON DBS order counterbalanced? 3 patients did not complete the task OFF, and the ON dataset was not available in another patient. Did the authors check if the DBS order was relevant for the DBS effect on P(explore)?

Reviewer #1 (Public Review):

The development and patterning of the pharyngeal arches of the vertebrate embryo have not been as well studied as many other more classical areas of embryonic development, such as the developing limb. However congenital malformations of pharyngeal arch derivatives are common, and elucidation of the mechanisms of pharyngeal arch development would be informative for human and animal health, as well as adding to our knowledge of biological mechanisms of patterning during organogenesis.

Using an unusual model - the development of the skate gill arch, and underpinned by a complementary analysis of pharyngeal arch patterning in the chicken embryo, this paper builds on previous work by the authors as well as more established paradigms of embryonic development and patterning, to understand the organisers and molecular pathways they express which contribute to gill arch/pharyngeal arch patterning.

Based on previous work that showed that the primary organiser of skate gill arch patterning - the GAER, expressed SHH, the authors used fate mapping techniques to establish the origin and subsequent morphogenesis of the GAER. They found that it has an endodermal origin. They repeated this experiment on chicken and found it to be the same.

They subsequently followed the expression of SHH and FGF8 through gill arch development, to show both the morphogenesis of the gill arch and that these genes go from a complementary gene expression to having an overlapping gene expression which is most highly in the posterior arch environment. The posterior expression and activation of the SHH and FGF pathways are also shown to be highest in the posterior gill arch- thus this is proposed as the primary mechanism by which the gill arch is 'polarised'.

Further work identified that the anterior gill arch expresses components of the Wnt signalling pathway, in a complementary way to FGF/SHH. Pharmalogical inhibition of Wnt signalling produces extra, non-polarised gill arches, suggestive of not only a loss of polarity but also a change in the distribution of gill arches- perhaps due to a modification of a Turing-type mechanism that would space the cartilages appropriately. At a molecular level, SHH expression did not change, but the activation of the SHH signalling pathway expanded. This perhaps suggests that Wnt signalling acts to restrain/inhibit SHH pathway activation, increasing and underpinning the mechanism of polarisation of the gill arch.

Fundamentally I think the work is strong overall. Each section of the paper is based on a clear platform of data and a hypothesis, which link together to really tell us about how this tissue is patterned - the organisers and the signalling pathways and the interactions between them. The fate mapping, sequencing, pharmacological inhibition, and HCR ISH are conclusive, although I presume due to using the usual skate a model the replicate numbers are quite low.

I do find the paper overly complex in interpretation and the figure quality of summary figures lacking in detail so that a non-gill arch expert can struggle to understand the findings. While the additional work in chicken pharyngeal arch is also strong, it is not overtly covered in the main body of the paper - and I think this is a mistake. I think interest here is uncovering mechanisms of vertebrate development - in which case a stronger comparison between chicks would demonstrate the similarities. I would suggest including make figures in which these species are shown together.

I also feel that there is much that could be discussed - not only about the formation of a polarised tissue but about how the gill arches are spaced - is this a Turing-type mechanism? Are there similarities that can be drawn with the limb or other systems which generate repeating structures? An interpretation of this could interest a wider group than only those that work on pharyngeal arch development.

In summary, I think this is an exciting paper using an unusual model and an understudied but important area of embryonic development which gives us an insight into how some of our commonly held dogmas may apply across different systems.

Reviewer #1 (Public Review):

Bakoyiannis et al. investigated the distinct contribution of ventral hippocampal outputs to the nucleus accumbens and medial prefrontal cortex on memory in mice exposed to a high-fat diet (HFD) beginning in adolescence. The authors first characterize the hippocampal to accumbens or mPFC circuits using intersectional viral approaches. They then replicate their previous finding that adolescent HFD contributes to the overactivation of the ventral hippocampus during contextual learning via quantification of c-fos+ cells. In this manuscript, the authors further explore the distinct contribution of these two outputs from the ventral hippocampus using chemogenetics to specifically inhibit one circuit or the other. Interestingly, the authors find that inhibition of either circuit returns c-fos+ cell number to control levels, but the effects on memory are dissociable. They demonstrate that inhibition of output to the NAc rescues HFD-induced deficits on object recognition, while inhibition of mPFC outputs rescues HFD-induced deficits on object location recall. The authors further confirmed that chemogenetic manipulations resulted in alterations in c-fos+ cells that were specific to CA1, and not CA3 or DG. Behaviorally, they excluded any contribution of anxiety on recall, finding no effect on the elevated plus maze.

The strengths of this manuscript include robust behavioral findings that can be attributed to specific circuits. The conclusions of this paper are largely well supported by the data, although some of the methods could provide more detail and the statistical approaches used for analysis need improvement.

Reliance on only one measure of anxiety to exclude this as a confound on recall performance is a weakness of the manuscript. To be more convincing that anxiety is not a confound, more than one behavioral assay should be performed.

Reviewer #1 (Public Review):

My impression is of a careful and thorough study, that potentially could provide a paradigm for future studies in this direction. A potential causative pathway for hepatic-related sarcopenia is identified. Parallel studies are made in both experimental and human clinical systems.

Reviewer #1 (Public Review):

Many animal studies have shown that the first and second heart fields give rise to the heart in normal embryonic development. For obvious reasons, this has not been well-studied in humans. Thus these investigators applied hiPSC technology to recapitulate human heart development using small molecules to modulate WNT signaling and thus induce mesodermal lineage differentiation. They set up a triple reporter genetic system (TBX5-Cre/MYL2-tdTomato/CCR5-CM-Lox-STOP-Lox-TurboGFP reporter) in two hiPSC lines and demonstrated that > 90% of ventricular cardiomyocytes were derived from the TBX5/MYL2 lineage. They used RT-qPCR to verify over 12 different time points during the course of the differentiation protocol that cells begin to express markers of the FHF lineage and eventually markers of ventricular cardiomyocytes.

Reviewer #1 (Public Review):

Detecting and quantifying balancing selection is a notoriously difficult challenge. Because the distribution of times to fixation or removal of strictly neutral variants has a long tail, it can be hard to exclude the null hypothesis of neutrality when testing for balancing selection that was not established so long ago that trans-specific variants can be observed. As Aqil et al. point out, most efforts to detect balancing selection in the human genome have been focused on single nucleotide variants. The authors seek to characterize the amount of balancing selection specific for polymorphic deletions. The authors justify their focus based on the fact that deletions are more likely to have functional consequences than single nucleotide variants, making it more likely that if they have remained for many generations, this could be a signature of balancing selection. That said multiple aspects of the analysis deserve more attention.

I have two broad concerns about the manuscript that the authors need to address. First, the authors use neutral simulations to exclude that neutrality alone can explain the amount of allele sharing observed between African modern humans and the archaic genomes. My concern is that human demography models, including the one from Gravel et al. (2011) used by the author are always simplifications of the complex demographic events that shaped human populations during evolution. In the case of the specific model used by the authors, African populations were inferred by the Gravel et al. model to have a constant population size for the past ~150,000 years (parameters Taf and Naf in the original model). This is an unrealistic assumption of this model. In brief, I am wondering how much the claim of the authors that neutrality alone cannot explain patterns of allele sharing is potentially based on mis-specifications of the neutral demography model. For example, the more fine scale fluctuations of effective population sizes in Africa inferred by author L. Speidel in 2019 Nature (Figure 3) paint a different picture than the Gravel et al. model. The authors need to run extensive testing of the robustness of their conclusions to changes in the neutral demographic model used. What if the average ancestral population size was closer to 20,000? What if it was closer to 50,000 and frequency fluctuations every generation were smaller? Given how uncertain past population sizes really were and the current uncertainties about demographic reconstruction in particular relative to linked selection, the authors need to explore a range of past populations size beyond the idiosyncrasies of a specific model.

My second broad concern is that it is difficult to evaluate how novel the findings really are. It is true that the authors focus on deletions while pasts scans for balancing selection in the human genome focused on SNVs. But it could be the case that a substantial number of the deletions identified here as under balancing selection could have previously identified as such loci through linked SNVs by the scans cited by the authors. The authors need to provide quantification of how many of their deletions are truly novel balancing selection loci as opposed to balancing selection loci already identified through linked SNVs.<br /> The novelty of the balanced deletions will also be better established by providing a more quantitative and less anecdotal functional analysis. It is true that the deletions include immune loci, but are they statistically enriched for immune loci as annotated for example by Gene Ontology, in a way that shows that their distribution across the genome is not random but indeed driven by selection enriching them at loci with specific functions? In addition, do the pie charts in Figure 5E, represent a statistically significant deviation from left to right or not?

Reviewer #1 (Public Review):

The authors generated valuable snRNAseq data sets from the hippocampus region in APO E4 and E3 mouse models. Through bioinformatics analysis, they identified a list of differentially expressed genes between E4 and E3at 5, 10, 15, and 20 months. In addition, changes in cell type distribution were observed across different time points, and the number of differentially gene expressions varied across multiple cell types. Through pathway enrichment analysis, the authors identified shared pathways such as calcium signaling and MAPK/Raps1/Pld pathways. To determine the relevance of these observations with respect to human Alzheimer's disease, they verified that genes/pathways identified in their mouse models are largely conserved in APOE4-Knockin and human APE4 iPSC-derived Neurons.

A major strength of this study comes from the combination of mouse and human models using snRNAseq analysis. In addition, the authors also used comprehensive bioinformatics tools to dissect the shared genes/pathways during disease progression. While a major weakness of the study is the lack of experimental validation of the specific pathways and their impact on disease. The observational gene expression analysis cannot provide any casual information. It is unclear whether the genes and pathways identified are primary events of disease etiology or secondary events due to disease progression.

Finally, I want to congratulate the authors on creating and sharing such a comprehensive set of snRNAseq data of the APO e4 allele. This set of omics data will become a reference point for the Alzheimer's research community. Their initial analysis of this rich dataset has yielded many interesting findings that may be validated by other groups.

Reviewer #1 (Public Review):

The authors have performed a deep mathematical analysis of unitary data recorded from the stellate ganglion to understand how the neural code is altered in heart failure.

The study is advantaged by being performed in vivo with afferent and efferent pathways intact. The use of modern microelectrode arrays has allowed mass activity to be recorded from multiple sites simultaneously within the ganglion. The authors have a number of powerful analytical tools that have revealed quantitative changes of interest.

The data are from animals under anesthesia with an open chest and open pericardial sac and one wonders what effect this has on the neural activity given the changes in pulmonary physiology this will cause.

Some of the data are from pigs where resiniferatoxin (a chemical agent to kill sensory afferents) was applied to the epicardial surface. Given the elevation in sensitivity of cardiac afferent reflexes in heart failure (Schultz, Zucker, and others), it is surprising that this had no effect on the neural activity recorded in the heart failure animals. Either the afferents were not destroyed (no data given to demonstrate this) or these sensory fibres play no role in the changes in neural activity reported from heart failure pigs. This would go against current data and remains unclear.

Most of the stellate neurons project to non-cardiac tissues. One does not get a sense of the proportion of activity that was related to the heart (left ventricular pressure) and whether in heart failure there is an elevated activity within a confined network or recruitment of additional networks. In this regard, the manuscript is jargon-heavy and for those that are physiologists, the subtleties of the study may be lost.

Finally, the authors could provide a clearer take-home message and break out of the shackles of math talk and interpret the possible physiological relevance of the work as well as why it is important to understand the changes in stellate neural network dynamics in heart failure.

Reviewer #1 (Public Review):

The authors analyze the roles of BRC-1 and SMC-5 in C. elegans meiosis taking advantage of specific assays to distinguish DSB repair pathways: an inter-sister assay (ICR) (Mos1 induced DSB), an inter-homolog assay (IH)(Mos1 induced DSB), a SCE assay based on Edu labelling of sister chromatids, and other assays such as radiation sensitivity. In addition, due to the controlled timing of DSB induction, by recovering progeny at specific time points, the authors evaluate the properties of cells at leptotene-mid pachytene or at late pachytene-diplotene. The authors also take advantage of SNP in the ICR assay to measure conversion tract length.

The main findings are:<br /> - Intersister crossovers are increased in brc-1 and smc-5.<br /> - Intersister non-crossovers are increased in smc-5.<br /> - Interhomolog recombination is increased in both brc-1 and smc-5 for late prophase cells.<br /> - Increased mutation rate in brc-1.<br /> - Shorter non crossover conversion tracts (ICR assay) in brc-1.<br /> - TMEJ involved in DSB repair in brc-1 smc-5 double mutant.<br /> - Independent localization of Brc-1 and smc-5.

Having assays for specific events allows gaining more direct information on the DSB repair phenotypes of such mutants. The conversion tract assay is the most convincing and clear data which fits well with the role of Brc-1 in end resection. However the results of the ICR and IH assays are interesting but do not fit with previous observations on the role of Brc-1 and Smc-5 based on analysis of meiotic phenotypes, Rad-51 foci and diakinesis, these discrepancies should be addressed.

The experimental approach has some issues that should be addressed: i) the two main windows (inter-homolog and non-inter homolog) are defined based on meiotic progression in wild type. The timing in the mutants and upon Mos1 induction (which could also affect the timing of meiotic progression) should be determined. In particular, the increase of interhomolog events in brc-1 is left without a validated interpretation. ii) Potentially the phenotypes observed in the ICR and IH assays (but not EdU) may be specific to Mos1-induced DSB and may not apply to Spo11-induced breaks. iii) The use of the Edu assay could be clarified, it seems that the interpretation of configurations is challenging, thus potentially leading to selection bias among diakinesis.

Reviewer #1 (Public Review):

In this manuscript, the authors relied on their well-established directed differentiation approach to differentiate pluripotent stem cells (hESCs) towards growth plate (BMP4-treated) or articular (TGFb3-treated) chondrocytes. Integrating RNA-seq data from hESCs-derived growth plate or articular chondrocytes with data from in vivo (fetal) counterparts, the authors showed similarities (and some divergences) in the transcriptional networks of in the in vitro-differentiated cells, uncovering genes with potential novel roles in cartilage biology. Integrating ATAC-seq (to assess chromatin accessibility) and transcriptomics data, the authors both characterized the regulatory landscapes in these cells, and also uncovered lineage-specific gene-regulatory networks. Using targeted ChIP-qPCR, and leveraging available ChIP-seq datasets, the authors validated the functional interactions of two well-described DNA-binding trans-acting factors (RUNX2 and RELA) with putative genomic targets (both previously involved and with non-explored/novel roles in cartilage biology). Taken together, these analyses provide novel insight into the molecular mechanisms contributing to growth plate and articular cartilage specification.

Strengths:

This is a very well-written manuscript. The findings are of relevance to understanding cartilage development and maintenance and are of potential impact to understand (and correct) cartilage damage and pathology. The experiments are well conducted, and the conclusions and claims are supported by the data. The authors performed a superb job characterizing and defining gene regulatory networks, elegantly integrating in vitro systems with in vivo datasets, and combining transcriptomics and epigenomics tools. These approaches uncovered regulatory networks and novel genes with unexplored roles and contributions to growth plate and articular cartilage development.

Weaknesses:

The functional implication of the findings is somewhat limited: while the authors did evaluate and confirm interactions of selected transcription factors with putative target genes, the mechanistic contribution of these findings to chondrocyte specification is not fully explored.

Reviewer #1 (Public Review):

This study presents novel experimental data from a mutant mouse model lacking microglia (Pu.1-/- mouse line) which indicates that these cells have an important role in the embryonic establishment of critical neural circuits in the brainstem generating breathing motor behavior in mice. Microglia are known to have important roles in shaping neural circuit assembly during development by controlling cell death, synapse refining, neurogenesis, and axon tract formation, but such roles have not been examined in the development of functional respiratory circuits. The authors examined the anatomical and functional characteristics of two main respiratory neuronal groups-in the embryonic parafacial (epF) and the preBötzinger complex (preBötC) regions that operate together in the developing brainstem to generate the rhythmic neural signals that are necessary to establish normal breathing behavior and ensure survival at birth. They present evidence that these respiratory networks become functional at typical developmental stages in the absence of microglia, but exhibit anomalies in rhythm generation (slower respiratory rhythm) and the mutants are unable to sustain breathing behavior at birth, consistent the observed neonatal death. Their data suggest that these deficits are associated with reduced cell numbers and abnormal rhythmogenesis in epF, and reduced commissural axonal projections of the preBötC circuits responsible for generating inspiratory rhythm.

Strengths of this study include the authors' use of the Pu.1-/- mutant in combination with technically well-executed, novel anatomical reconstruction of distributions of microglia in the developing hindbrain, neuronal activity imaging in the epF of the embryonic brainstem in vitro, and electrophysiological recording approaches in slices to assess aspects of the anatomical and functional status of the epF and preBötC relative to the control wild type mice. They also examine inspiratory drive transmission to phrenic motoneurons in vitro to assess the functional status of spinal respiratory motor output critical for breathing behavior at birth. Furthermore, their behavioral measurements by plethysmography document show that late-term (E18.5) Pu.1-/- embryos are unable to sustain breathing activity ex utero, which is consistent with the observed neonatal death of the mutants.

A limitation of the study is that the microglia-related mechanisms involved in regulating cell numbers in epF and the proper bilateral connectivity of preBötC circuits have not been investigated. Therefore it remains unknown if the reduced cell numbers in epF in the Pu.1-/- mutant is a defect, for example, of neurogenesis/neuronal migration or abnormal control of cell death, and if the defect of preBötC connectivity is actually related to the aggregation of microglia along the midline (possibly affecting commissural axonal tract formation), as the authors suggest.

Reviewer #1 (Public Review):

Blake and colleagues examine programs of alternative splicing controlled during T cell activation. Using CD4+ T cells from human donors, cells were stimulated with anti-CD28, anti-CD3, and combined anti-CD3/28 antibodies. RNA was then isolated at 2 time points, sequenced, and analyzed for changes in spliced isoform ratios. T Cell Receptor stimulation alone via anti-CD3 is known to induce the anergic state resulting from suboptimal stimulation, while CD28 costimulation with CD3 induces many genes to a higher level of expression similar to stimulation by antigen-presenting cells. Analyzing the splicing responses to these stimuli, the authors find that CD28 costimulation also enhances the splicing changes that accompany T cell activation. A subset of these splicing targets encode apoptotic regulators including Caspase-9, Bax, and Bim. They show that forced expression of the isoforms that are increased by costimulation results in reduced apoptosis in Jurkat cells treated with apoptotic inducers. Using kinase inhibitor treatments they show that Jnk kinase activity is required for the splicing changes in the three apoptotic regulators.

Reviewer #1 (Public Review):

This paper examines wtf genes in relatives of S. pombe to investigate the evolutionary history of the gene family. Classic theory suggests that distorters like wtf should be fairly transient - the fitness cost due to spore killing should select for suppressors and even if a selfish allele manages to fix, its advantage disappears (under either scenario, the drive function stops, and the allele degrades over time through random mutation). Despite these predictions, the authors provide convincing synteny data to argue that wtf genes were likely present more than 100 million years ago in the common ancestor of S. pombe and its relatives. Using phylogenetic approaches, the authors also show that since this ancient origin, wtf genes have evolved dynamically by gene duplication and gene conversion within descendant lineages. Additionally, by studying the genomic regions surrounding these genes, they discover an association in S. octosporus and S. osmophilus with 5S rDNA, which, like associated LTRs in S. pombe, might facilitate this duplication history. Finally, using transformation experiments, the authors demonstrate that these newly identified wtf genes have the very same poison and antidote functions originally described in S. pombe.

This work is a significant advance in our understanding of the evolution of wtf genes, moving beyond S. pombe to several other distantly related fission yeast species. More generally, it suggests a plausible mechanism for the continued existence of wtf genes across long evolutionary time scales.

Joint Public Review:

Here the authors develop and evaluate a new hybrid-capture sequencing approach for coronavirus (CoV) surveillance in bats. The intended goal is to overcome limitations in amplicon sequencing, which is the current standard method for viral surveillance in animal species. Whereas amplicon sequencing is only suitable for targeted analysis of the highly conserved RdRp gene in bat CoVs, the new hybrid-capture approach affords a great breadth of coverage across the full genome in diverse CoV species. This promises to improve the identification and phylogenetic analysis of bat CoVs. The authors conclude by making practical recommendations about how their new method can be applied to usefully complement existing technologies in the field.

The new method appears to suffer from a lower sensitivity for CoV detection than amplicon sequencing, and also struggles to yield complete sequences across the bat CoV spike protein, which is a highly divergent region. The authors have appropriately acknowledged these weaknesses, and show how other complementary tools can alleviate them - for example by using deep metagenome sequencing to resolve the spike protein in new CoV strains discovered through hybrid capture sequencing.

This is an excellent paper in my opinion. The study addresses an important problem - improved methodologies for CoV viral surveillance in bats, a common source of zoonotic viral transmission events. The authors developed a new method that has obvious utility. They have fairly evaluated this method against existing approaches (targeted amplicon sequencing and deep metagenomic sequencing) using appropriate data. In addition to describing a useful new method, the study also produced some novel results that are likely valuable - that of complete (or near-complete) genome sequences for several novel bat coronaviruses. The authors discuss the outcomes in a fair and balanced fashion and make some simple, practical recommendations about how their new tool might best be used. Finally, the article was very well written; clear, concise, and fluent.

Reviewer #1 (Public Review):

The manuscript is clear and well-written and provides a novel and interesting explanation of different illusions in visual numerosity perception. However, the model used in the manuscript is very similar to Dehaene and Changeux (1993) and the manuscript does not clearly identify novel computational principles underlying the number sense, as the title would suggest. Thus, while we were all enthusiastic about the topic and the overall findings, the paper currently reads as a bit of a replication of the influential Dehaene & Changeux (1993)-model, and the authors need to do more to compare/contrast to bring out the main results that they think are novel.

Major concerns:<br /> 1. The model presented in the current manuscript is very similar to the Dehaene and Changeux 1993 model. The main difference is in the implementation of lateral inhibition in the DoG layer where the 1993 model used a recurrent implementation, and the current model uses divisive normalization (see minor concern #1). The lateral inhibition was also identified as a critical component of numerosity estimation in the 1993 model, so the novelty in elucidating the computational principles underlying the number sense in the current manuscript is not evident.

If the authors hypothesize that the particular implementation of lateral inhibition used here is more relevant and critical for the number sense than the forms used in previous work (e.g., the recurrent implementation of the 1993 model or the local response normalization of the more recent models), then a direct comparison of the effects of the different forms is necessary to show this. If not, then the focus of the manuscript should be shifted (e.g., changing the title) to the novel aspects of the manuscript such as the use of the model to explain various visual illusions and adaptation and context effects.

Reviewer #1 (Public Review):

In this manuscript by Woods et al, the authors study the small heat shock protein HSPB5, specifically focusing on two cataract-associated mutations. They show that the mutations, which are located in the ACD core of the protein, disrupt the interaction of the core with the unfolded N-termini and generate a much more dynamic version of the protein. A surprising feature of the mutants is that they enhance in vitro chaperone activity directed against damaged GammaD-crystallin.

Reviewer #1 (Public Review):

This is an interesting new bladder function monitoring approach in rodents that can accurately monitor bladder filling and emptying in freely moving non-anaesthetized animals that does not require implantation of a suprapubic catheter. This was accomplished by using machine learning to define the bladder wall from fluoroscopic images of mice injected with iodinated radiocontrast media taken at 30 images/second over 2-3 hours. While this approach cannot provide any information on intravesical pressures, it can provide much more accurate and detailed information on bladder filling, urethral flow rate, intra contraction intervals and residual bladder volume than assays of voiding spots on paper or metabolic cages monitoring of urine production with microbalances.

Reviewer #1 (Public Review):

Jara et al studied the interaction between the dynein intermediate chain (IC) and the three dimeric light chains (Tctex, LC7, LC8), dynactin p150, and the nuclear distribution protein (NudE). The authors are able to produce the entire intrinsically disordered N-terminal domain of IC from Chaetomium thermophilum (CT) allowing them to study the assembly and regulatory mechanism of IC with five different partners.

The authors convincingly demonstrate that IC is maintained in an auto-inhibitory conformation through NMR titrations of separate constructs of IC. Using a combination of NMR, ITC, SV-AUC, SEC, and SEC-MALS, they demonstrate that release of this auto-inhibitory conformation, through binding of LC7, is required for binding to NudE and to some extent p150. Importantly, the presence of this auto-inhibited state is validated in the context of the full-length IC protein expressed and purified from insect cells.<br /> The work provides novel insight into how dynein assembly is regulated (Fig. 10) and illustrates the unique interaction mechanisms that can be exploited by intrinsically disordered proteins.

The conclusions of the manuscript are supported, for most parts, by experimental data, however, some aspects require some clarification or should be further supported by experimental data:

1) The authors propose that the two-step binding isotherm observed for p150 is due to binding to both the SAH and H2 regions of IC(1-88), while NudE shows a single binding event by ITC due to interaction with the SAH region only. The NMR experiments of IC(1-88) do not provide sufficient support for this hypothesis (Fig. 6B, bottom panel). Additional experimental data would be needed to fully support this conclusion.

2) ITC, NMR, and AUC data are presented for the binding of NudE to IC(1-260). Some more clarification is needed in terms of the interpretation of these data, also in the context of the observations on IC(FL). The experimental observations do not seem to be explainable simply by a weak complex or a concentration-dependent effect as suggested by the authors.

3) The difference in sedimentation coefficient of the dynein subcomplex + NudE and of the dynein subcomplex + p150 is surprisingly large suggesting significantly different shapes of the two bound complexes. Some discussion of this issue is present in the manuscript, but no clear explanation is provided. It would seem necessary to confirm these observations with other complementary techniques.

4) The authors suggest that the binding of LC7 releases the auto-inhibitory interaction of IC, however, NMR does not directly support this conclusion (Fig. 7B). Some discussion of why this long-range interaction inhibits the binding of NudE, but not LC7 itself, should be included.

Reviewer #1 (Public Review):

In this paper, Jan Kubanek attempts to derive an 'effective decision strategy' that is optimal (and therefore normative) given certain constraints resulting from computational capacity limitations. The author first points out that neoclassical economics (i.e., expected utility theory, EUT) provides normative predictions for decisions to maximize utility. Next, he (correctly) points out that finding the optimal solutions to decision problems requires computational resources that are unlikely to exist in actually existing decision-makers (animals and humans). He claims that this fact is the most severe problem for concluding that EUT is an accurate description of actual human or animal decision processes. I disagree with him on this point as I will lay out in more detail below. Next, the author attempts to find an 'efficient' (i.e., computationally reasonable) decision strategy that comes close to the original normative framework. He claims that such a strategy is EDM, whereby decisions are made by allocating relative effort in proportion to the relative reward of each option.

Overall, I find this paper hard to judge. The considerations described in this paper are certainly interesting and I have no reason to presume that the mathematical derivations described are wrong (without having made an effort to follow and check it in detail). Still, I find the paper, in the end, sterile and I fear it will have only limited impact. I think the manuscript should be expanded in three different directions to make it more relevant for the neuroscientific understanding of decision making. First, the author needs to show that EDM can also explain other known violations of EUT related to the axiom of regularity (i.e., preferences between two options should not be affected by the presence of inferior options). This seems relevant because these behavioral effects robustly violate the choice allocation strategy of EDM. Second, EDM is so abstract that the actual structure and capacity of the nervous system are nearly irrelevant. The author should consider more deeply the computational requirements and capacities of different types of brains; fruit flies, frogs, and primates, and the consequences of these differences for what is (or should be) achievable in terms of optimal behavior. Third, the paper contains no test for EDM. This is in part because EDM is at no point compared to the predictions of alternative theories.

My specific concerns are as follows:

(1) The author claims that the most severe problem of EUT is that it is computationally implausible. However, I disagree. It could be claimed that EUT describes an (unattainable) optimal state that actual brains try to accomplish with limited resources. (In essence, the current paper follows this strategy). I think the situation is much direr. During the last 70 years, a small army of psychologists and behavioral economists have described a large number of violations of EUT's normative predictions: the Allais paradox, framing effects, the behavioral tendencies summarized in Prospect theory, and others. These differences between behavior and normative predictions are important because they violate basic assumptions of the normative theory.

(2) The most interesting case of such violations is a set of well-known behavioral effects that occur in the context of multi alternative-multi attribute decision making. They are known as the attraction, similarity, and compromise effects (there is a large literature; more recently: Dumbalska T, Li V, Tsetsos K, Summerfield C. A map of decoy influence in human multi alternative choice. Proc Natl Acad Sci U S A. 2020 Oct 6;117(40):25169-25178. doi: 10.1073/pnas.2005058117. Epub 2020 Sep 21.) These biases have received so much attention because they violate a very basic axiom of EUT. Choices between two options should not be affected by the presence of a third option that is inferior to both of them. However, that is exactly what happens in these choice biases. The effects have been shown in many species ranging from humans to amphibians to invertebrates. As far as I can see, EDM cannot explain how choice allocation between two options A and B that have equal value would be changed by the inclusion of a new option D so that is of lower value than A or B in such a way that D is not chosen at all, but A is chosen more often than B if D is similar in attributes to A (the 'attraction' effect). If I am mistaken, the inclusion of an explanation of how this would work would be of major importance.

(3) EDM as described in this manuscript is completely static, that is it ignores actual computational processes that underlie decision making. This is in opposition to an important modern branch of decision research that has stressed the importance of understanding processes (and their limitations) to understand how choices are made. Examples are: (1) Roe RM, Busemeyer JR, Townsend JT. Multialternative decision field theory: a dynamic connectionist model of decision making. Psychol Rev. 2001 Apr;108(2):370-92. doi: 10.1037/0033-295x.108.2.370. PMID: 11381834.; (2) Tsetsos K, Usher M, Chater N. Preference reversal in multiattribute choice. Psychol Rev. 2010 Oct;117(4):1275-93. doi: 10.1037/a0020580. PMID: 21038979. The relationship between EDM and algorithmic implementations should be explored.

(4) Most importantly, what is missing is a clear prediction for a finding (behavioral or neuronal) that would only be predicted, but not by any other theory of decision making. Without such a proposed test, the idea has no scientific merit.

Reviewer #1 (Public Review):

Aberra et al.'s work is focused on identifying genes that exhibit opposing effects on type 2 diabetes and abdominal obesity. Identification of such genes would provide stepping stones for a better understanding of why some individuals with obesity are not developing type 2 diabetes, knowledge that ultimately could shed light on the complex interplay between fat distribution and type 2 diabetes.

Aberra et al. use a number of computational tools to identify genetic variants associated with both type 2 diabetes and waist-hip ratio (both adjusted for body mass index). They identify six genetic loci that associate with both phenotypes, but exhibit discordant effects.

To better understand which tissues and genes are potentially mediating the discordant effects, the authors use GTEx data to co-localize eQTLs with genetic variants at the six discordant loci. They identified four genes, at two of the discordant loci, that are regulated by an eQTL co-localizing with one of the discordant variants. Using the Finnish METSIM cohort and correlation analysis, the authors show that expression of these genes is associated with both glycemic and obesity risk-phenotypes.

The manuscript is very concise and well-written. All computational analyses seem well thought through and executed. I have two suggestions that potentially could help the authors to improve their work.

The authors write that they "[...] predict the mechanisms of action at discordant loci" (L. 286), which seems too strong a claim given their data. Potentially the following points could help to provide more evidence on the functional context to the four prioritized genes and more guidance on how mechanistic insights could be advanced further:

1) Aberra et al. indicate that the 2p21 locus harboring the THADA gene and its antisense RNA are differentially open during preadipocyte development. Are these RNAs differentially expressed during specific stages of adipocyte development and are they differentially expressed in certain human adipocyte clusters? Relevant datasets to address these questions could be (https://www.nature.com/articles/s41467-020-16019-9, https://pubmed.ncbi.nlm.nih.gov/32066997/, https://pubmed.ncbi.nlm.nih.gov/35296864/, and https://pubmed.ncbi.nlm.nih.gov/33116305/.

2) The authors' work may serve as an example on how to shortlist relevant genetic variants for variant-to-function approaches. It could be instructive to the metabolism community if the authors' in the Discussion could dedicate a paragraph to carefully discuss how one best could further explore the function of the discordant variants they identify and the genes they implicate. For instance, how could one (i) experimentally prove that the given variants regulate the predicted effector genes, (ii) further understand the mechanisms with which they impact adipocyte biology, and (iii) further establish evidence that they have a discordant effect on glycemic and lipid traits.

Reviewer #1 (Public Review):

The manuscript titled "Notch signaling functions in non-canonical juxtacrine manner in platelets to amplify thrombogenicity" by Chaurasia et al describes that human platelets have notable expression of Notch1 and its ligand DLL-4, which function in a non-canonical manner to synergize with physiological platelet agonists, leading to prothrombotic phenotype. Targeting Notch signaling specifically DLL-4-Notch1-NICD axis can be a potential approach to develop anti-platelet/anti-thrombotic therapeutic.

Start with an essential question that matters to you.

Reviewer #1 (Public Review):

This work addresses the problem of accurately estimating dynamics parameters in single particle tracking applications. The authors give a very extensive overview of the current problems and solutions while dealing with imaging of diffusive motion of subcellular particles and challenges that one faces while trying to estimate the main parameters of interest, such as diffusion constants. The authors properly address the issues with short trajectories, which are typical in practice and propose two advanced approached, which successfully deal with the mentioned shortcomings (short trajectories from which it is difficult to estimate parameters reliably, and the measurement errors that contaminate the input data). The proposed techniques are very interesting, and the way how those pure mathematical (and long existing) concepts are applied for this specific application of single particle tracking is rather novel. The proposed methodology is supported by a thorough validation, which includes simulations of all possible conditions (numbers of trajectories, distributions of the diffusion constants within the population of particles, the levels of inaccuracies in the measurements, etc.). Additionally, the experiments with the real data are also very convincing. The authors do focus on a regular Brownian diffusion and hopefully will show the applicability of these approaches to more typical applications containing anomalous diffusion. The availability of the code, which the authors provide on github, is very important, especially to less (technically) skilled audience from the field of experimental biology, who would like to apply those techniques to their data.

Reviewer #1 (Public Review):

The present study aims to define the main immune cell subsets found in the hemolymph of the white shrimp, P. vannamei. This is significant because this species is heavily farmed around the world to meet the demand of the human consumption market. Yet, farmed shrimp suffer from infectious diseases and therefore we need to understand how their immune system works to design strategies that decrease infection losses.

Classification of crustacean (and other invertebrates) hemocytes is difficult due to the lack of antibodies to use traditional flow cytometry approaches. Furthermore, hemocyte purification is not easy, cells die and clump, again precluding flow cytometry studies. Thus, the majority of what we know about shrimp hemocytes is based on morphological classification. This study contributes significantly to advancing our knowledge of shrimp Immunobiology by defining hemocyte subsets based on their transcriptional profiles.

Another strength of the paper is that some function in vivo assays (phagocytosis) are presented in an attempt to validate the single-cell data. The authors frame their question or try to frame their question with a more evolutionary angle, such as whether the macrophage-like cell is the evolutionary precursor of human macrophages. I think that this question is not really achievable because the evolution of innate immune systems may have diverged in many branches of the metazoan tree of life. The authors, however, identify gene markers that are conserved in macrophages from shrimp and humans and that is a fair conclusion. There are some methodological caveats to the study and the manuscript needs to be heavily edited to improve language as well as to increase the depth of the interpretation.

In summary, there are interesting findings in this manuscript but the manuscript needs to be significantly improved so that its quality and impact are elevated.

Reviewer #1 (Public Review):

The manuscript by LoMastro et al. investigates whether Plk4, the master regulator of centriole biogenesis in cycling cells, has a similar role during the differentiation of multi-ciliated cells, which produce tens to hundreds of centrioles during multi-ciliogenesis. Contrasting previous work that did not find an important role for Plk4 in this process based on chemical inhibition, the authors in the current study use genetic approaches and mouse models to show that Plk4 and its kinase activity are essential for centriole amplification and multi-ciliogenesis in two different multi-ciliated cell types in vitro and in vivo. In addition, they show that centriole amplification drives cell surface area expansion.

The study addresses an important question regarding the role of Plk4 in centriole amplification during multi-ciliogenesis. It convincingly establishes that contrary to previous findings, the Plk4-dependent control of centriole biogenesis that is well-established in cycling cells is conserved also during differentiation of multi-ciliated cells. The presented data is of very high quality, phenotypes are well described and quantified, the conclusions are clear, and obtained in both in vitro and in vivo models. The authors also test chemical inhibition of Plk4 as used in previous work and show that the lack of a strong phenotypes under these conditions is likely due to incomplete Plk4 inhibition.

Reviewer #1 (Public Review):

The authors of this study adopted Cas9-mediated enrichment of target locus and Nanopore long-read sequencing to accurately count repeat numbers in the CNBP gene, which is notorious for precise calling before. They also compared their result with that of the conventional approach, validating their approach. It is an interesting read and shows a pathway that a clinic can take in the near future.

However, this paper's novel contributions need to be emphasised as there are some papers that utilized Nanopore sequencing to elucidate short repeats (https://pubmed.ncbi.nlm.nih.gov/35245110/; https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00853-3). Another issue is the clinical utility of the approach. Although it is precise, it is not totally clear whether this accuracy is required in clinical practice, as the repeat status does not completely correlate with phenotypic severity.

Lastly, it is not clear about the familial cases (A1-A4). What are their relationships and why their copy numbers are not exactly the same? Is it because of extreme recombination and variation even in a family or just represent limited accuracy?

They lack a validation cohort, with prospective patients.

Reviewer #1 (Public Review):

The manuscript by Dr Riley and colleagues reports a novel link between molecular clock operative in skeletal muscle and titin mRNA, encoding for essential regulator of sarcomere length and muscular strength. Surprisingly, this clock-mediated regulation of titin occurs at the level of splicing, as demonstrated by SDS-VAGE analyses of skeletal muscle from muscle-specific Bmal1KO mice compared to Bmal1wt counterpart. Concomitant with switch of predominant isoform of titin, skeletal muscle of muscle specific Bmal1KO mice exhibited irregular sarcomere length. Moreover, the authors show that this shift of titin splice is causal for such sarcomere length irregularity and for altered sarcomere length in muscle from the mice with compromised clock function. Importantly, the authors provide compelling evidence that Rbm20, encoding for RNA-binding protein that mediates splicing of titin, is cooperatively regulated by Bmal1-Clock heterodimer and MyoD, via enhancer element in intron 1 of Rbm20, thus identifying Rbm20 as a novel direct clock-regulated gene in the skeletal muscle. Strikingly, rescue of Rbm20 in muscle specific Bmal1KO animals' results in rescue of titin splicing pattern and protein size, suggesting that Rbm20 mediates the regulatory effect of Bmal1 on titin splicing and represents a mechanistic link between the clock and regulator of sarcomere length and regularity.

Reviewer #1 (Public Review):

Detomasi et al. investigated the role of a protein encoded by the cwr-1 gene that belongs to the cell wall remodeling locus that controls cell fusion checkpoints in Neurospora crassa. This protein corresponds to a putative polysaccharide monooxygenase (called PMO or LPMO) from family AA11 (according to the CAZy family). This class of enzymes is known for oxidative cleavage of recalcitrant polysaccharides but recently diverging functions have emerged. In this work, the authors clearly demonstrated LPMO activity towards chitin for several CWR-1 from different haplogroups. Mutagenesis and construction of chimeras allowed the authors to reveal that enzymatic activity was not required for cell fusion blockage. Beyond this very interesting observation, they identified a polymorphic region in the main catalytic domain (corresponding to several loops) that was essential to trigger allorecognition. The authors suspect that this region is involved in the recognition of CWR-2, a transmembrane protein with two domains of unknown function. The authors propose a model highlighting the role of CWR-1 in allorecognition at the cell fusion checkpoint. These results open new prospects for the biological function of fungal PMOs/LPMOs not directly related to their enzymatic activity.

Reviewer #1 (Public Review):

The manuscript by Liu et al. outlines the role of exchange protein directly activated by cAMP (Epac2) in dopamine neurons and how this relates to cocaine effects on dopamine release and associated behaviors. Through a series of manipulations, they show that Epac2 expression increases cocaine reinforcement and dopamine release while decreases in Epac2 have the opposite effect. The manuscript is interesting and important, the design is rigorous, and it of broad impact on the field. There are only minor issues with the wording of the operant schedule (I am not sure that it is actually FR1) and some other wording issues (in some places it just states Epac2, rather than denoting these are its effects in dopamine neurons), but overall this is an excellent manuscript.

Reviewer #1 (Public Review):

Khan et al describe how two important transcription factors functionally cooperate to activate a few of the CRP-dependent genes in Mycobacterium tuberculosis. CRP is a global regulator in eubacteria needed to activate a number of genes while PhoP is an acid stress response regulator required for expression specific set of genes. The authors delineate the interaction between these two key regulators of the bacterial pathogen and show that in a subset of CRP-dependent promoters, PhoP binding recruits CRP to activate transcription.

The experiments are well designed and executed with a coalescent presentation of the manuscript. While the data is well organized and presented with clean images of phophorimages and blots to facilitate their easy understanding, interpretation could have been more robust (see comments below).

Obviously, the strength of the paper is the description of hitherto unknown stress-specific cooperation between two well-studied transcription factors with most evidence supporting the claims. In E.coli (and in other bacteria) studies CRP mediated control of genes have lead to the identification of different classes of CRP-dependent promoters with their own specific regulators. Such a description was lacking in M.tuberculosis and the PhoP - CRP collaboration described is likely to have implications on pathogenesis. The weakness (or possibly what remains to be explored) is that the precise mechanism of the cooperative transcription regulation is yet to be understood.

From the data presented it is apparent that PhoP binds to whiB up promoter own efficiently. It is also evident that CRP is recruited to its site as a result of PhoP binding. This is reminiscent of the bacteriophage Lamba paradigm of positive cooperativity. Thus, it is not reciprocal synergy (as stated in the paper in one place). It is Phop mediated recruitment as claimed elsewhere. Indeed, PhoP null mutants nicely support the latter interpretation

A discussion on why and how CRP binds on its own in other CRP-dependent promoters would help better appreciate the need for PhoP sites next to CRP sites for their cooperative interaction in these promoter subsets. CRP sites could be at a varied distance with respect to the promoter as seen in E.coli.

Reviewer #1 (Public Review):

In this paper the authors explore how trunk neural crest cells (NCCs) acquire regional identity in human ESC differentiation. Following from earlier findings that NMPs in vivo and NMP-like cells in vitro give to trunk neural crest, they now show that the transcription factor TBXT is required for the acquisition of posterior identity of NMPs and their derivative NCCs. When TBXT is reduced in hESCs they do not activate Hox gene expression or the expression of Wnt targets. Using a combination of TBXT ChIPseq in NMPs and ATACseq in control and TBXT depleted NMPs, they show that TBXT binds close to the TSS of genes whose expression is downregulated in the absence of TBXT and that in the absence of TBXT such regions lose their accessibility. These data suggest that TBXT mediates chromatin opening and subsequent activation of these transcripts. Finally, the authors also suggest that acquisition of posterior character in NCCs is largely dependent on Wnt signalling, while posterior spinal cord cells largely depend on FGF signalling.

The role of FGF and Wnt signalling in establishing anterior-posterior identity is well documented and the authors explore these pathways and the role of TBXT in this process using differentiation of human ESCs. The finding that TBXT is required for NMPs and NMP-derived NCCs to acquire posterior identity is interesting, and the authors show that this is likely to involve chromatin accessibility mediated by TBXT and activation of target genes. The involvement of TBXT/Wnt loop in the acquisition of posterior NCC identity is a new finding, and the authors provide an underlying molecular mechanism.

The authors suggest that they uncovered two distinct phases of how the posterior axial identity is controlled; the first involving TBXT/Wnt to generate posterior 'uncommitted progenitors', which then go on to generate NCCs, and the second involving FGF to impart posterior axial identity onto CNS/spinal cord cells. I am not convinced that their data show this; it is equally possible that NMPs are heterogeneous and the effects observed simply reflect a differential response of cells or selection. Since the authors largely analyse their data by qPCR it is difficult to disentangle this.

Some conclusions rely on the changes in expression of just a handful of markers; since gene expression changes dynamically during development it is important to acknowledge that the interpretation is very dependent on the stage examined.

The authors include some expression data in mouse to support their in vitro findings. However, these need to be explained and integrated better.

Reviewer #1 (Public Review):

The authors test a hypothesis that IL-33 plays a role in human parturition. It does so by (1) investigating changes in myometrial cell nuclear IL-33 expression during the third trimester of pregnancy. Their approach studies human myometrial cells, enhancing the clinical translatability of the present work. They demonstrate a reduced nuclear IL-33 staining with the onset of labour, further reduced by LPS. They implicate altered Ca2+ homeostasis in the actions of IL-33, and emerge with a model suggesting that IL-33 directly prevents excessive COX-2 expression in myometrial cells after LPS stimulation and it influences COX-2 expression by maintaining the severity of ER stress response.

Reviewer #1 (Public Review):

This is an exciting study using human electrophysiology to provide novel insights into the functional architecture of the posterior cingulate cortex (PCC). As the authors note, the PCC is an enigmatic brain region that is implicated across numerous cognitive functions and appears to play a crucial role in many neurological and neuropsychiatric conditions. Articulating the potential functional specialisations of subdivisions of the PCC to distinct aspects of cognition thus provides an innovative and powerful means of reconciling discrepancies in the extant literature, as well as stimulating new directions in the field.

Strengths of the study include the use of intracranial electrophysiology via local field potential and single-neuron recordings targeting the dorsal PCC. This approach enabled the authors to capture neural activity in the dorsal PCC during alternating episodic and executive cognitive tasks and to localise the functional clustering of single unit activity to uncover functional cell types within PCC.

The experimental tasks seem well-designed, drawing on the current understanding of the role of the DMN in memory-based constructive simulation processes (past and future), and the executive attention tasks to index the CCN. I was also pleased to see the inclusion of a "rest" condition in which endogenously driven forms of spontaneous cognition would be predicted to occur. Overall, the manuscript is very well-written, and the major conclusions appear well supported by the data.

Reviewer #1 (Public Review):

Jones et al. investigated the relationship between scale free neural dynamics and scale free behavioral dynamics in mice. An extensive prior literature has documented scale free events in both cortical activity and animal behavior, but the possibility of a direct correspondence between the two has not been established. To test this link, the authors took advantage of previously published recordings of calcium events in thousands of neurons in mouse visual cortex and simultaneous behavioral data. They find that scale free-ness in spontaneous behavior co occurs with scale free neuronal dynamics. The authors show that scale free neural activity emerges from subsets of the larger population - the larger population contains anticorrelated subsets that cancel out one another's contribution to population-level events. The authors propose an updated model of the critical brain hypothesis that accounts for the obscuring impact of large populations on nested subsets that generate scale free activity. The possibility that scale free activity, and specifically criticality, may serve as a unifying theory of brain organization has suffered from a lack of high-resolution connection between observations of neuronal statistics and brain function. By bridging theory, neural data, and behavioral dynamics, these data add a valuable contribution to fields interested in cortical dynamics and spontaneous behavior, and specifically to the intersection of statistical physics and neuroscience.

Strengths:<br /> This paper is notably well written and thorough.

The authors have taken a cutting-edge, high-density dataset and propose a data-driven revision to the status-quo theory of criticality. More specifically, due to the observed anticorrelated dynamics of large populations of neurons (which doesn't fit with traditional theories of criticality), the authors present a clever new model that reveals critical dynamics nested within the summary population behavior.

The conclusions are supported by the data.

Avalanching in subsets of neurons makes a lot of sense - this observation supports the idea that multiple, independent, ongoing processes coexist in intertwined subsets of larger networks. Even if this is wrong, it's supported well by the current data and offers a plausible framework on which scale free dynamics might emerge when considered at the levels of millions or billions of neurons.

The authors present a new algorithm for power law fitting that circumvents issues in the KS test that is the basis of most work in the field.

Weaknesses:<br /> This paper is technically sound and does not have major flaws, in my opinion. However, I would like to see a detailed and thoughtful reflection on the role that 3 Hz Ca imaging might play in the conclusions that the authors derive. While the dataset in question offers many neurons, this approach is, from other perspectives, impoverished - calcium intrinsically misses spikes, a 3 Hz sampling rate is two orders of magnitude slower than an action potential, and the recordings are relatively short for amassing substantial observations of low probability (large) avalanches. The authors carefully point out that other studies fail to account for some of the novel observations that are central to their conclusions. My speculative concern is that some of this disconnect may reflect optophysiological constraints. One argument against this is that a truly scale free system should be observable at any temporal or spatial scale and still give rise to the same sets of power laws. This quickly falls apart when applied to biological systems which are neither infinite in time nor space. As a result, the severe mismatch between the spatial resolution (single cell) and the temporal resolution (3 Hz) of the dataset, combined with filtering intrinsic to calcium imaging, raises the possibility that the conclusions are influenced by the methods. Ultimately, I'm pointing to an observer effect, and I do not think this disqualifies or undermines the novelty or potential value of this work. I would simply encourage the authors to consider this carefully in the discussion.

Reviewer #1 (Public Review):

In this article, the authors are trying to ascertain how emigrated SVZ cells can be beneficial - via neuroreplacement or neuroprotection. They provide evidence for the latter and also show that it is primarily precursors and not differentiated cells that migrate to photo-thrombotic cortical models of stroke.

The writing is lucid and the flow of the experiments logical. The images and quality of data are high and the depth of investigation appropriate (eg 100 cells examined per marker in Figure 1). The methods are clearly described. They appropriately control for changes in cortical lesion size. The photo-thrombotic lesion is a good choice in terms of controlling lesion placement and size.

A distinctive advantage of this paper is they show that reducing SVZ cytogenesis in the stroke model diminishes recovery, especially behavioural (single seed reaching behavior). This essential experiment has been remarkably under-utilized in the field.

The 2-photon imaging of dendric spines after stroke combined with multi-exposure speckle imaging is a technical tour-de-force especially since they combine it with ganciclovir-induced loss of cytogenesis and behavioural assays. Importantly, they show that SVZ cells are needed for full spine plasticity.

They are correct to examine the SVZ response in aging as it diminishes dramatically in animal models but in humans is associated with more strokes. As expected, they show reduced SVZ proliferation after stroke. This was associated with significantly worse performance in the seed-reaching task and depleting SVZ precursors with ganciclovir did not make it worse.

The viral VEGF delivery rescue experiment is fantastic. Behavior, blood vessel growth, and spine density are all rescued.

The idea that SVZ cells are beneficial via mechanisms other than cell replacement is not really that new. For example, neural stem cells from the SVZ have been shown to reduce inflammation and thereby be neuroprotective as the authors themselves acknowledge and cite (Pluchino et al., 2005).

The fact that it is primarily precursor cells that migrate towards the stroke does not mean that cell replacement does not occur. The precursors could gradually differentiate (even after 6 weeks post-injury) into more mature cells that do replace cells lost to injury. Also, the two events are not mutually exclusive.

Overall this is an interesting addition to the literature and methodologically it is quite strong. It is sure to generate follow on studies showing how different growth factors may be secreted by SVZ cells in various models of neurological disease.

Reviewer #1 (Public Review):

In this study, Scalabrino et al. show persistent cone-mediated RGC signaling despite changes in cone morphology and density with rod degeneration in CNGB1 mouse model of retinitis pigmentosa. The authors use a linear-nonlinear receptive field model to measure functional changes (spatial and temporal filters and gain) across the RGC populations with space-time separable receptive fields. At mesopic and photopic conditions, receptive field changes were minor until rod death exceeded 50%; while response gain decreased with photoreceptor degeneration. Using information theory, the authors evaluated the fidelity of RGC signaling demonstrated that mutual information decreased with rod loss, but cone-mediated RGC signaling was relatively stable and was more robust for natural movies than artificial stimulus. This work reveals the preservation of cone function and a robustness in encoding natural movies across degeneration. This manuscript is the first demonstration of using information theory to evaluate the effects of neural degeneration on sensory coding. The study uses a systematic evaluation of rod and cone function in this model of rod degeneration to make the following findings: (1) cone function persists for 5-7 months, (2) spatial and temporal changes to the ganglion cell receptive fields were not monotonic with time, (3) mutual information between spikes and photopic stimuli remained relatively constant up to 3-5 months, and (4) information rates were higher for natural movies than for checkerboard noise stimuli.

The strengths of this paper include the following:

A systemic evaluation of potentially confusing data. The authors do an excellent job of organizing the results in terms of light levels and time points. The results themselves are confusing and difficult to draw across metrics, but the data are presented as clearly as possible. The work is especially well executed and presented.

The insight that cone responses remain relatively stable despite rod loss. The study clearly demonstrates that despite cone loss and morphological changes, cone-mediated responses remain robust and functional.

The application of information theory to degeneration is the first of its kind and the study clearly shows the utility of the metric.

The results are thoughtfully interpreted.

The weaknesses of this study include the following:

The inability to follow the same ganglion cell types over time is a major weakness that could confound the interpretation in terms of whether the changes are happening from artifacts of the recording method or from dynamic changes in the pooled population of ganglion cells. Is there even a single cell class, for example the ON-OFF direction-selective ganglion cells, that this group has so well quantified on the MEA, that the study could track over time, in addition to examining the pooled population changes over time? Tracking a single cell type for each of the metrics would make the population data more convincing or could clearly show that not all ganglion cells follow the population trend.

While the non-monotonic changes are interesting, they are also difficult to make sense of. Can the authors speculate in the Discussion what could be underlying mechanisms that give rise to non-monotonic changes. In the absence of potential mechanisms, the concern of recording artifacts arises.

The mutual information calculation seems to be correlated with the spike rate despite the argument made in Fig 10E-F. Can the authors show this directly by calculating the bits per spike in Figures 8 and 9? Of all the metrics, the gain function and the mutual information seem to be more consistent with each other. Can the authors demonstrate or refute a connection between the spike rate and information rates?

Can the authors provide an explanation for why the mutual information calculation remains stable despite lower SNR and lower gain, especially after the contributions of oscillations have been ruled out?

Lack of age-matched WT controls to accompany the different time points. It is known that photoreceptor degeneration can occur naturally in WT mice. Though the authors have used controls pooled from across the ages used in the CNGB1 mutants, it would be informative to know if there are age-dependent changes in any of the metrics for WT mice.

Can the authors elaborate on why cone function persists despite the rod loss and morphological changes? This is unique for other models of rod loss and is worth extra discussion.

Reviewer #1 (Public Review):

The authors of this paper are offering the electron microscopy community an affordable tool to semi-automatize some of the most challenging and time-consuming steps to target a region of interest in a sample prepared for electron microscopy. This article is sharing in total transparency all their work and the immense development efforts put in by the authors in terms of finance, manpower, software, and hardware development. A huge effort has been done to make all the parts of the workflow accessible. The way to add the hardware to the existing ultramicrotomes is clearly explained and documented. The hardware to be purchased and adapted is also clearly documented. All the software needed is open-source, the code fully documented and the implementation documented. A critical assessment of the performances is shown for the two main and only suppliers of ultramicrotomes. The reproducibility of the approach has been quantified on numerous samples in a fair and systematic way. The limits and ways for improvements are openly and clearly discussed at the end of the article. All the process is documented by clear and didactic figures helping the readers to put the equations in context.

The implementation of this solution by laboratories will still be a substantial investment but the impact on the research can be so crucial that it can motivate groups to make the effort. The generosity of the authors to share all the data and the fact that nothing is hidden or prevents anybody to adapt this solution is exceptional and should be encouraged.

Reviewer #1 (Public Review):

Authors propose a mechanism where actin polymerization in the dendritic shaft plays a key role in trapping AMPAR vesicles around the stimulated site, promoting the preferential insertion of AMPAR into the potentiated synapse. This dendritic mechanism is novel and may be important for phenomena. Authors also developed a sophisticated method to observe the endogenous behavior of AMPAR using the HITI system.

However, there are some major issues that need to be addressed to support the authors' claims. Also, overall, it is hard to follow. It could be better written.

Reviewer #1 (Public Review):

This is an interesting study with observations that provide intriguing data to further think about how neurons in the medial temporal lobe correlate with recognition memory.

Figures 2 through 6. There is no description of the relationship between the findings and the anatomical location of the electrodes (other than distal versus local). Perhaps the non-uniform distribution of electrodes makes these analyses more complicated and such questions might have minimal if any statistical power. But how should we think about the claims in Figures 2-6 in relationship to the hippocampus, amygdala, entorhinal cortex, and parahippocampal gyrus? As one example question out of many, is Figure 2C revealing results for local pairs in all medial temporal lobe areas or any one area in particular? I won't spell out every single anatomical question. But essentially every figure is associated with an anatomical question that is not described in the results.

Figure 1<br /> 1A. I assume that image positions are randomized during a cued recall?<br /> What was the correlation between subjects' indication of how many images they thought they remembered and their actual performance?<br /> 1B. Chance is shown for hits but not misses. I assume that hits are defined as both images correct and misses as either 0 or 1 image correct. Then a chance for misses is 1-chance for hits = 5/6. It would be nice to mark this in the figure.<br /> The authors report that both incorrect was 11.9%. By chance, both incorrect should be the same as both correct, hence also 1/6 probability, hence the probability of both incorrect seems quite close to chance levels, right?<br /> 1C. How does the number of electrodes relate to the number of units recorded in each area?

Line 152. The authors state that neural firing during encoding was not modulated by memory for the time window of interest. This is slightly surprising given that other studies have shown a correlation between firing rates and memory performance (see Zheng et al Nature Neuroscience 2022 for a recent example). The task here is different from those in other studies, but is there any speculation as to potential differences? What makes firing rates during encoding correlate with subsequent memory in one task and not in another? And why is the interval from 2-3 seconds more interesting than the intervals after 3 seconds where the authors do report changes in firing rates associated with subsequent performance? Is there any reason to think that the interval from 2-3 seconds is where memories are encoded as opposed to the interval after 3 seconds?

Lines 154-157 and relationship to the subsequent analyses. These lines mention in passing differences in power in low-frequency bands and high-frequency bands. To what extent are subsequent results (especially Figures 3 and 4) related to this observation? That is, are the changes in spike-field coherence, correlated with, or perhaps even dictated by, the changes in power in the corresponding frequency bands?

Do local interactions include spike-field coherence measurements from the same microwire (i.e., spikes and LFPs from the same microwire)?

Figure 6. I was very excited about Figure 6, which is one of the most novel aspects of this study. In addition to the anatomical questions about this figure noted above, I would like to know more. What is the width of the Gaussian envelope? Are these units on the same or different microwires? How do the spike latencies reported here depend on the firing rates of the two units? What do these results look like for other pairs that are not putative upstream/downstream pairs?

Reviewer #1 (Public Review):

The work suggests an evolutionary "arms race" between Ophiocordyceps BRM1 and Aglaia and that acquisition of eIF4A-H153G was a key step permitting the fungus to colonize the plant during its life cycle. Functional experiments are convincing in terms of differential sensitivity of translation to repression by rocaglates when H153G (or equivalent) is introduced to various eIF4A isoforms from multiple species in cell-free reporter systems and in engineered fungal strains. Although BRM1 could not be genetically engineered, the authors introduced H153G or wild-type eIF4A into related C. orbiculare species and found the substitution reversed translational repression phenotypes of rocaglates. H153G also permitted growth on rocaglate-treated cucumber leaves in contrast to wild-type. Overall the work demonstrates a specific AA substitution analogous to change in the Aglaia plant itself that may permit Ophiocordyceps BRM1 to grow on the plant, bypassing a key defense mechanism. The H153 polymorphism in Ophiocordyceps BRM1 suggests growth of Aglaia species is an obligate part of the fungus' life cycle, and that it evolved to fill this niche in a way that no other described species has done. However, since the organism is also known to parasitize ant species, it is not entirely clear from the data presented that growth on Aglaia is an obligate step. Regardless, the report is highly suggestive of a specific AA substitution having evolved in a fugal species to bypass a specific plant defense strategy.

Reviewer #1 (Public Review):

This article clearly illustrates the limitations of previous predator escape models that (1) fail to incorporate the initial orientation of prey relative to predators, and (2) do not properly describe the endpoint of predator attacks, instead assuming infinite trajectories. The approach is novel and the implications for stochastic strategies are important. Some subtle rearrangements would improve the presentation of the data.

The correspondence between the presented behavioral data and model instantly validates the incorporation of predator attack distance and initial orientation of the prey into escape models. I am completely convinced that the lack of the two incorporated variables prevented the accurate reconstruction of ETs. These two variables create distributions over escape choices that are eventually claimed to balance behavioral perfection (i.e., minimization of Tdiff) with unpredictability (i.e., the choice of slightly suboptimal ETs when the effect on Tdiff is negligible relative to predator capture times). This is a case where precision is sometimes favored over variability and other times variability over precision.

It's here where my very mild (I truly liked this article - it is well done, well written, and creative) comments arise. The implications for stochastic strategies immediately emerge in the early results - bimodal strategies come about from the introduction of two variables. There is not enough credence given to the field of stochastic behavior in the introduction - the introduction focuses too much on previous models of predator-prey interaction, and in fact, Figure 1, which should set up the main arguments of the article, shows a model that is only slightly different (slight predator adjustment) that is eventually only addressed in the Appendix (see below). The question of "how and when do stochastic strategies emerge?" is a big deal. Figure 1 should set up a dichotomy: optimal strategies are available (i.e., those that minimize Tdiff) which would predict a single unimodal strategy. Many studies often advocate for Bayesian optimal behavior, but multimodal strategies are the reality in this study - why? Because if you consider the finite attack distance and inability of fish to evoke maximum velocity escapes while turning, it actually IS optimal. That's the main point I think of the article and why it's a broadly important piece of work. Further framing within the field of stochastic strategies (i.e., stochastic resonance) could be done in the introduction.

All experiments are well controlled (I especially liked the control where you varied the cutoff distance given that it is so critical to the model). Some of the figures require more labeling and the main marquee Figure 1 needs an overhaul because (1) the predator adjustment model that is only addressed in the Appendix shouldn't be central to the main introductory figure - it's the equivalent of the models/situations in Figure 6, and probably shouldn't take up too much space in the introductory text either (2) the drawing containing the model variables could be more clear and illustrative.

Finally, I think a major question could be posed in the article's future recommendations: Is there some threshold for predator learning that the fish's specific distribution of optimal vs. suboptimal choice prevents from happening? That is, the suboptimal choice is performed in proportion to its ability to differentiate Tdiff. This is "bimodal" in a sense, but a probabilistic description of the distribution (e.g., a bernoulli with p proportional to beta) would be really beneficial. Because prey capture is a zero-sum game, the predator will develop new strategies that sometimes allow it to win. It would be interesting if eventually the bernoulli description could be run via a sampler to an actual predator using a prey dummy; one could show that the predator eventually learns the pattern if the bernoulli for choosing optimal escape is set too high, and the prey has balanced its choice of optimal vs. suboptimal to circumvent predator learning.

Overall, a very good article.

Reviewer #1 (Public Review):

The authors combined light-sheet-based imaging with computational tools to track C. elegans motor behavior throughout the last ~5hrs of embryonic development. Using PCA and quantitative methods, the authors identified postures and movements along developmental time. Early on, embryonic movements are continuous and dominated by dorsoventral "flips". The embryos then enter a period of low activity followed by a phase where episodic sinusoidal waves are predominant. The authors later defined this episodic behavior as "slow wave twitch" (SWT). These phases are stereotyped across embryos, and the early flipping phase depends on neuronal synaptic transmission. Using a brightfield high-throughput method the authors implicated neuropeptides in SWT. Finally, they demonstrated that a somnogenic neuropeptide secreted from RIS neurons mediates the quiescent periods observed during SWT.

At a high level, the authors developed a pipeline to capture behavior during late embryonic development to make the following conclusions: 1) Embryonic behaviors followed a stereotyped trajectory, with early flipping and a late-stage dominated by episodic sinusoidal crawling-like waves. 2) Synaptic transmission is necessary for late-stage episodic movements. 3) A peptidergic neuron known to promote a sleep-like state in the hatched animals promotes quiescent periods observed during SWT. Overall these conclusions are well supported by the presented data. This work focuses on the late stages of development when behaviors emerge, a heavily understudied period. The study provides some of the first insights into embryonic behaviors in C.elegans and lays the groundwork for further studies using this system. Therefore, this work should have a significant impact on the fields of neurodevelopment and neuroscience.

Reviewer #1 (Public Review):

The authors tested, in 30 subjects, a model of traveling signals along the thalamo-cortico-thalamic projections to explain individual differences in spindle frequency. As predicted, they showed the presence of a relationship between the length of the thalamocortical white matter bundles and sleep spindle frequency (a specific characteristic of this functional network), and further showed that this neuroanatomical marker mediated the sex-related differences in sleep spindle frequency.

This paper has several strengths, both methodologically and conceptually. The authors leverage the use of polysomnographic/EEG overnight recordings and diffusion MRI data for their analysis, providing a unique dataset in a group of men and women. The focus on understanding the well-established sex difference in sleep spindles is a significant strength and advances knowledge and understanding of neuroanatomical underpinnings for this sex difference. Interestingly, the authors did not find a relationship between this neuroanatomical measure and sleep spindle amplitude, which deserves further comment. The current work can be used as a foundation for future work, for example, examining the relationship between neuroanatomical white matter fiber bundle length between thalamus and frontal cortex and functional sleep spindle outcomes, such as memory consolidation, as well as exploring age-related changes/differences in these measures.

Reviewer #1 (Public Review):

The authors initially demonstrated that the deletion of LIS1 using an inducible Cre mouse model hindered the maturation of T cells, as evidenced by a reduction in the number of DPs. Furthermore, it reduced early T cell and B cell development, specifically during β selection and prepro to pro B cells in the case of T and B cells, respectively. This correlated with an increase in cells at the G2/M stage. The authors then sorted for DN3 cells and seeded them onto OP9-DL1 stromal cells. In this model, the deletion of Lis1 reduced proliferation and lead to an accumulation of the cells at G2/M, similar to the results in vivo.

The authors then switch to examining the role of Lis1 at later stages of T cell development by deleting Lis1 at the DP stage. The deletion of Lis1 at this stage resulted in a reduction in CD4+ and CD8+ cells, which correlated with a drop in proliferation in CD4+, after the first division and a slight reduction in CD8+ cells. The drop in proliferation and increase in cells at the G2/M stage was shown to be due to an inability to correct condense the DNA at metaphase, resulting in aberrant numbers of centromeres and upregulation of apoptosis, which was also confirmed in DN3 cells. Finally, they demonstrate that this is due to an ineffective interaction between dynein and dynactin. Overall, this was an interesting study into the role of Lis1 in T cell division.

Reviewer #1 (Public Review):

In this manuscript, Blanc et al. developed a tool to align different larval zebrafish brains with pan-neural markers and additional birthdate labeling into a common atlas. By aligning transgenic lines into this reference atlas, the authors tried to infer the birth date and growth patterns of different neuron populations. The intention of providing an open-access tool and developmental atlas is good, especially considering most of the current zebrafish brain atlases were made for adult or larval zebrafish more than 5 days old. However, the key features claimed by the authors i.e., the "temporal dynamic" is essentially missing from the atlas. The tool was still built for a single development stage and reflected no information on growth patterns except the neuronal birthdate. Moreover, the accuracy of the registration method, the rationality of the birthdate labeling, and the validity of the proof-of-concept inference were also not sufficiently demonstrated in the experimental design.

Overall, I believe the manuscript has the potential to be a useful tool and an impactful developmental atlas for the community, but it would need substantial improvement in method design, experimental validation, and data/software availability.

Major points:

1. The authors claimed to have made a "3D-temporal" atlas for developing zebrafish hindbrain. However, the "temporal" component was solely birthdate inferred from temporal labeling. Images were still acquired at the same developmental stage, which makes the atlas and registration method not substantially different from the other existing atlases (e.g. ViBE-Z (Ronneberger 2012), Z-Brain (Randlett 2015), ZBB (Tabor 2019), Mapzebrain (Kunst 2019) - note not all of these tools were cited in introduction). The authors would have to either add temporal tracing of the population and provide registration between different developmental stages, or tune down the "temporal" term only to "birthdating".

2. Rigid registration was used to align the images from different individuals, as opposed to the more complicated non-linear registration used by all the tools above. The accuracy of such registration needs to be measured to justify the choice of method, by measuring the inter-individual variability using different registration methods. Variability should be quantified in 3D rather than along specific anatomical axes.

3. Birthdate labeling was achieved by photoconverting Kaede at different stages (24, 36, 48 hpf) and imaging at 72hpf. This method suffers from an intrinsic bias: the Kaede-red was subject to different time windows for diluting and metabolizing over development, making the age labeling incomparable between different labeling lengths. To verify the experimental design, the authors should 1) demonstrate that the red cells labeled in an early conversion are strictly included in the red cells labeled in a late conversion, and 2) provide an additional age-labeling method like BrdU treatment, to show the new cells incorporated between the two time points are reflected in the growing photoconverted population.

4. Proof-of-concept inference of GABAergic neuron birth date in Figure 5 is very vague. No link was shown between the red cells in Fig 5B and the gad1b in situ-positive cells in Fig 5D. If tracing the fate of these cells from 24-72hpf is not possible, the authors should at least demonstrate that they are 1) post-mitotic at 24hpf, i.e. HuC-positive; and 2) appear in similar numbers and similar neighborhood context as the red cells in Fig 5B. I also want to point out that while it is true that mRNAs are expressed earlier than fluorescent proteins in the transgenic line, an early-born cell expressing a specific gene late development does not mean it would express the gene early on. A gene can be ON early on and turned OFF later; Conversely, a gene can express late in the differentiation process while the cell is committed and went through terminal division early in the lineage.

5. It is mentioned many times that the platform is "open-access" and "expandable", but no source or browsable atlas was provided (maybe I was wrong, but I did not find the Fiji macro and R code on the provided website). The software and data availability should be improved, and more demonstration is needed to show its "expendability" -guidelines should be provided on how to upload users' own data to use this platform, and what kind of additional data is supported.

Reviewer #1 (Public Review):

Liau and colleagues have previously reported an approach that uses PAM-saturating CRISPR screens to identify mechanisms of resistance to active site enzyme inhibitors, allosteric inhibitors, and molecular glue degraders. Here, Ngan et al report a PAM-saturating CRISPR screen for resistance to the hypomethylating agent, decitabine, and focus on putatively allosteric regulatory sites. Integrating multiple computational approaches, they validate known - and discover new - mechanisms that increase DNMT1 activity. The work described is of the typical high quality expected from this outstanding group of scientists, but I find several claims to be slightly overreaching.

Major points:

The paper is presented as a new method - activity-based CRISPR scanning - to identify allosteric regulatory sites using DNMT1 as a proof-of-concept. Methodologically, the key differentiating feature from past work is that the inhibitor being used is an activity-based substrate analog inhibitor that forms a covalent adduct with the enzyme. I find the argument that this represents a new method for identifying allosteric sites to be relatively unconvincing and I would have preferred more follow-up of the compelling screening hits instead. The basic biology of DNMT1 and the translational relevance of decitabine resistance are undoubtedly of interest to researchers in diverse fields.

In contrast, I am unconvinced that there is any qualitative or quantitative difference in the insights that can be derived from "activity-based CRISPR scanning" (using an activity-based inhibitor) compared to their standard "CRISPR suppressor scanning" (not using an activity-based inhibitor). Key to their argument, which is expanded upon at length in the manuscript, is that decitabine - being an activity-based inhibitor that only differs from the substrate by 2 atoms - will enrich for mutations in allosteric sites versus orthosteric sites because it will be more difficult to find mutations that selectively impact analog binding than it is for other active-site inhibitors. However, other work from this group clearly shows that non-activity-based allosteric and orthosteric inhibitors can just as easily identify resistance mutations in allosteric sites distal from the active site of an enzyme (https://www.biorxiv.org/content/10.1101/2022.04.04.486977v1). If the authors had compared their decitabine screen to a reversible DNMT1 inhibitor, such as GSK3685032, and found that decitabine was uniquely able to identify resistance mutations in allosteric sites, then I would be convinced. But with the data currently available, I see no reason to conclude that "activity-based CRISPR scanning" biases for different functional outcomes compared to the "CRISPR suppressor scanning" approach.

How can LOF mutations from cluster 2 be leading to drug resistance? It is speculated in the paper that a change in gene dosage decreases the DNA crosslinks that cause toxicity. However, the immediate question then would be why do the resistance mutations cluster around the catalytic site? If it's just gene dosage from LOF editing outcomes, would you not expect the effect to occur more or less equally across the entire CDS?

In general, I found the screens, and integrative analyses, highly compelling. But the follow-up was rather narrow. For example, how much do these mutations shift the IC50 curves for DAC? What kinetic parameters have changed to increase catalytic activity? Do the mutants with increased catalytic activity alter the abundance of methylated DNA (naively or in response to the drug)? It is speculated that several UHRF1 sgRNAs disrupt PPIs and not DNA binding, but this is never tested.

Reviewer #1 (Public Review):

In general, I consider that the manuscript reflects a huge effort in terms work done and data collection, the manuscript is very well written, and it brings new knowledge in terms of cooperative breeding and its connection with groups size in ostrich. My major concerns are about the title and introduction that are in my opinion too broad and not enough detailed.

In the introduction the scientific background that led to this research is lacking, and the manuscript would benefit from a more supported introduction, which makes it difficult to understand how far this study went comparatively to previous studies.<br /> The research work was well conducted, and adjusted to the study aims. However, it would benefit from including more details on the observational data collected by the authors.

I think the research topic is interesting, and the study was well performed, but the manuscript would benefit from a more clear approach to the working hypothesis, expected results and background theories/hypotheses.

Reviewer #1 (Public Review):

The transition from flagellar motility to ameboid movement enables Trichomonas vaginalis to interact more intimately with the cells of the urogenital tract to colonize a host. This transition is characterized by a profound morphological shift that allows the parasite to adopt a more ameboid type of movement on the colonized epithelium. Over the past several years some of the molecules on the surface of Trichomonas have been characterized, but little is known about the mechanisms of cytoskeletal rearrangement that mediate the transition to cytoadherence and ameboid movement. The present study capitalizes on T. vaginalis isolates that retain a non-adherent (T1) or adherent (TH1) phenotype to identify differences in the actin cytoskeleton that are correlated with cytoadherence, uncovering a new protein (TvFACPα) that appears to regulate the process.

The authors first establish that the amounts of actin and actinin are correlated with greater cytoadherence. This result is somewhat expected for ameboid movement; nevertheless, the conclusion is supported by treatment with Latrunculin B. Immunoprecipitating T. vaginalis actin, the authors find a non-canonical homolog of the cap-binding protein alpha subunit (TvFACPα). The effects of TvFACPα on cytoadherence, morphogenesis, and wound-closing assays are compelling. In particular, the use of several mutants affecting actin binding (Δ237) and phosphorylation (S2A/D) provides some information about the structure-function relationship of the protein. Based on the known phosphorylation of human CPα by casein kinase 2 (CKII), the authors use an antibody against the known phosphorylation motif of CKII (pS/pTDXE) which partially matches the suspected phosphorylation motif on TvFACPα: pSESE. The S2A mutant is not recognized by the antibody (suggesting that it indeed recognizes the intended PTM) and the signal is diminished by treatment with the CKII inhibitor TBB. Perhaps the most compelling evidence for the effect of TvFACPα phosphorylation is the impact of TBB on ameboid morphogenesis, which is overcome by the expression of the S2D mutant of TvFACPα.

Several experiments also focus on the biochemical activity of TvFACPα to claim that it functions as a typical capping protein. The evidence presented relies on steady-state experiments and co-immunoprecipitation, which are ill-suited to determine the function of actin-binding proteins. Calling into further question the validity of their biochemical assays, binding assays showed relatively modest differences between G and F actin binding by WT TvFACPα (less than 2-fold), and a similarly modest decrease in binding when the putative actin-binding domain of TvFACPα was removed. The micromolar affinities calculated are also much higher than the typical nanomolar affinities of cap-binding proteins. Other cap-binding proteins occur as heterodimers, so the lack of a β subunit in the IPs calls into question the true identity of the novel factor. While the studies with live parasites do support the importance of TvFACPα in Trichomonas morphogenesis and cytoadherence, more detailed studies will be necessary to define its biochemical function.

Reviewer #1 (Public Review):

This is a simulation study comparing the performance of two major approaches for dealing with "population structure" when carrying out Genome-wide Association Studies - Principal Component Analysis and Linear Mixed-effects Models - a subject of considerable practical importance. The author correctly notes that previous comparisons have been quite limited. In particular, any study not concluding that LMM was superior has relied on very simple models of structure.

The paper is clearly written and beautifully reviews the theoretical underpinnings (albeit in a manner that will be difficult to penetrate without deep knowledge of several fields). The simulations are well-designed and far better than previous studies. From a theoretical point of view, the work is somewhat limited by being strongly anchored in a very classical quantitative genetics framework that is focused on allele frequencies and inbreeding coefficients, and totally ignores coalescent theory, but this is a minor quibble. The simulations are limited by utilizing ridiculously small sample sizes by the standards of modern human GWAS. And of course, they do not include all the complexities of real data.

The main conclusion of the study is that LMM really are generally superior - as expected on theoretical grounds. However, the authors do address whether switching to LMM really is practicable given the sample size and lack of data sharing that characterize human genetics. Nor is it clear whether the difference in performance matters in real life given that the entire framework used is an idealized one - the fact that real human data suffers from environmental confounders that are correlated with "ancestry" is not addressed, to take the most obvious example. That said, it is surely important to note that the approach routinely used by the majority of users (PCA with 10 PCs) is most used for historical reasons and has little theoretical or empirical justification.

Reviewer #1 (Public Review):

The authors sought to understand the mechanistic basis for differential effects of Ism1 (a protein released by adipocytes, immune cells, and others) and insulin at the level of protein phosphorylation. The critical experiments included analysis of phosphoproteome of cultured cells treated with insulin, recombinant Ism1, or albumin and tests of effects of global Ism1 knockouts on metabolism, in cage activity and skeletal muscle function. The phosphoproteome experiments demonstrated the expected overlap in peptides that were phosphorylated or dephosphorylated by Ism1 and insulin. Shared signaling pathways included increased Akt and mTOR activity. There were also phosphopeptides unique to Ism1 for which gene ontology analysis revealed enrichment for pathways linked to skeletal muscle. Ism1 stimulated protein synthesis in cultured C2C12 and in skeletal muscle in-vivo. Differential phosphorylation of Irs2 was observed when comparing the phosphoproteome for Ism1 and insulin suggesting a mechanistic basis for divergent activation of intracellular pathways. Studies of mice with global knockouts of Ism1 showed reduced muscle fiber cross-sectional area for some muscles and reduced grip strength. There was no change in whole-body metabolism or in-cage activity. The study adds interesting new information about signaling by Ism1 and suggests that Ism1 might be one determinant of homeostasis of muscle protein anabolism, catabolism, and strength.

There are a few caveats to consider when interpreting the data that include:

1. Gender effects were not considered;<br /> 2. Effects of the Ism1 knockout on muscle fiber area seemed to vary from muscle to muscle for unclear reasons;<br /> 3. The re-analysis of single-cell seq data may not have sampled many Myonuclei.

Reviewer #1 (Public Review):

Cyclic GMP (cGMP) and Ca2+ signaling have been strongly linked to parasite motility and invasion in apicomplexan parasites. Over the last decade, researchers have pieced together an understanding of key molecules (in particular kinases) involved in regulating motility. Whilst there has been some attempt at identifying Ca2+ responsive kinases, using phosphoproteomics, this has lacked temporal analysis. Herneisen et al performed a time-resolve analysis of phosphorylation upon stimulation with the PDE inhibitor zaprinast (which stimulates cGMP signaling upstream of Ca2+ responses). They identify well over 4000 proteins per run, which is the highest coverage yet seen in Toxoplasma and must be close to the full proteome at this lifecycle stage. Their careful analysis (which I find the most compelling aspect of this work) clusters groups of phosphorylated proteins based on their temporal pattern and confirms and extends what is understood about the order of events that occurs during signaling that activates motility and invasion across the apicomplexan parasites.

Hernesisen et al then combine thermal proteome profiling, to understand how proteins respond to changes in Ca2+ concentration. The aim of this is to identify effectors of phosphorylation patterns over time and is an ingenious way of getting an answer to the problem. It will not only identify proteins that directly bind Ca2+ ( a change in thermal stability in the presence of this ion) but potentially other proteins/complexes that change in structure also. They are careful in their analysis of the resulting dataset to not overinterpret their findings. Furthermore, they validate their findings on several proteins that likely do not directly bind Ca2+ (but likely change in other ways upon a Ca2+ signal). Pleasingly, these 5 candidates validate the approach. Across all datasets, the analysis of this data is robust, insightful, and concise and will be of great value to the apicomplexan research community.

What is nice to see, and something that has not been explored much in Apicomplexa is a focus on proteins that become dephosphorylated upon signaling. They then go on to functionally characterize a PP1 orthologue, which also changes thermal stability upon increasing Ca2+ concentration and likely mediates downstream dephosphorylation. The phenotype is a little messy, likely because, as pointed out by the authors, that PP1s localisation and activity is mediated by partner proteins. They, however, clearly show a change in localisation upon stimulation of motility with zaprinast, but not the Ca2+ ionophore A23187 and that PP1 depleted parasites likely have a defect in the invasion. The level of cytosolic PP1-depleted parasites (as measured by GCaMP) only differs when stimulation with zaprinast not with A23187.

The authors then finish by applying their phosphoproteomic approach to PP1-depleted parasites and reveal changes. The results are in line with a recent Plasmodium publication (Paul et al, Nat Comms, 2021)(which they appropriately cite).

Overall, this paper was a pleasure to read, its conclusions were valid and not over-interpreted (which can be the case when performing these types of experiments). They have managed to extract meaningful data from these large data sets into easily interpretable graphical representations and carefully validate their results. The work is of the highest quality and sets a benchmark for the field.

Reviewer #1 (Public Review):

In this study, Romero, Prosper, and colleagues have investigated the differential gene expression and regulation in hematopoietic stem and progenitor cells (HSPCs) in young or elderly healthy individuals. With the use of single-cell RNA sequencing (scRNA seq), the authors identified that the stem/progenitor repertoire is changed in elderly individuals, which is accompanied by changes in cell differentiation. The authors additionally compare HSPCs from patients with myelodysplastic syndrome (MDS) and found that MDS patients exhibit specific alterations in erythroid differentiation gene regulatory networks in MDS HSPCs. Overall, this study deals with a valuable resource of HSPC profiles in healthy individuals and proves the biased hematopoietic landscape over aging at a transcriptome level. It will serve as a valuable resource for understanding the molecular basis for hematopoietic aging, which will be useful for future therapeutics and applications.

Reviewer #1 (Public Review):

The authors of this manuscript aimed at demonstrating the hypothesis that hyperacusis is triggered by increased sensitivity in mid-range frequency following high-frequency cochlear trauma. The study combines a large variety of careful physiological and behavioral measurements that converge toward the above-mentioned interpretation, which was proposed in an earlier report. This will likely boost the development of hyperacusis mouse models which is beneficial for future treatments.

Reviewer #1 (Public Review):

This is a carefully-conducted fMRI study looking at how neural representations in the hippocampus, entorhinal cortex, and ventromedial prefrontal cortex change as a function of local and global spatial learning. Collectively, the results from the study provide valuable additional constraints on our understanding of representational change in the medial temporal lobes and spatial learning. The most notable finding is that representational similarity in the hippocampus post-local-learning (but prior to any global navigation trials) predicts the efficiency of subsequent global navigation.

Strengths:

The paper has several strengths. It uses a clever two-phase paradigm that makes it possible to track how participants learn local structure as well as how they piece together global structure based on exposure to local environments. Using this paradigm, the authors show that - after local learning - hippocampal representations of landmarks that appeared within the same local environment show differentiation (i.e., neural similarity is higher for more distant landmarks) but landmarks that appeared in different local environments show the opposite pattern of results (i.e., neural similarity is lower for more distant landmarks); after participants have the opportunity to navigate globally, the latter finding goes away (i.e., neural similarity for landmarks that occurred in different local environments is no longer influenced by the distance between landmarks). Lastly, the authors show that the degree of hippocampal sensitivity to global distance after local-only learning (but before participants have the opportunity to navigate globally) negatively predicts subsequent global navigation efficiency. Taken together, these results meaningfully extend the space of data that can be used to constrain theories of MTL contributions to spatial learning.

Weaknesses:

1. The study has an exploratory feel, in the sense that - for the most part - the authors do not set forth specific predictions or hypotheses regarding the results they expected to obtain. When hypotheses are listed, they are phrased in a general way (e.g., "We hypothesized that we would find evidence for both integration and differentiation emerging at the same time points across learning, as participants build local and global representations of the virtual environment", and "We hypothesized that there would be a change in EC and hippocampal pattern similarity for items located on the same track vs. items located on different tracks" - this does not specify what the change will be and whether the change is expected to be different for EC vs. hippocampus). I should emphasize that this is not, unto itself, a weakness of the study, and it appears that the authors have corrected for multiple comparisons (encompassing the range of outcomes explored) throughout the paper. However, at times it was unclear what "denominator" was being used for the multiple comparisons corrections (i.e., what was the full space of analysis options that was being corrected for) - it would be helpful if the authors could specify this more concretely, throughout the paper.

2. Some of the analyses featured prominently in the paper (e.g., interactions between context and scan in EC) did not pass multiple comparisons correction. I think it's fine to include these results in the paper, but it should be made clear whenever they are mentioned that the results were not significant after multiple comparisons correction (e.g., in the discussion, the authors say "learning restructures representations in the hippocampus and in the EC", but in that sentence, they don't mention that the EC results fail to pass multiple comparisons correction).

3. The authors describe the "flat" pattern across the distance 2, 3, and 4 conditions in Figure 4c (post-global navigation) and in Figure 5b (in the "more efficient" group) as indicating integration. However, this flat pattern across 2, 3, and 4 (unto itself) could simply indicate that the region is insensitive to location - is there some other evidence that the authors could bring to bear on the claim that this truly reflects integration? Relatedly, in the discussion, the authors say "the data suggest that, prior to Global Navigation, LEs had integrated only the nearest landmarks located on different tracks (link distance 2)" - what is the basis for this claim? Considered on its own, the fact that similarity was high for link distance 2 does not indicate that integration took place. If the authors cannot get more direct evidence for integration, it might be useful for them to hedge a bit more in how they interpret the results (the finding is still very interesting, regardless of its cause).

Reviewer #1 (Public Review):

The manuscript is likely of interest to cryo-electron microscopists working on cellular samples. It details a data-acquisition scheme for mapping large areas at a fine pixel size by cryo-electron microscopy for the purpose of macromolecular identification by high-resolution 2D template matching (2DTM). The authors succinctly describe the methodology, as well as detail the apparent effects of microscope aberrations on 2DTM results.

While other montaging approaches have been described recently, the one presented here differs in its approach to controlling defocus and avoids the need to sacrifice a biologically meaningful region of a sample. The authors investigate the compatibility of the data acquisition with their 2DTM method using cryoFIB-milled mouse neutrophil-like cells and the 60S ribosome as an example case. In order to minimize unnecessary exposures, the authors restrict illumination to a circle inscribed on the detector and use beam image-shift in lieu of stage shift. This approach introduces several optical aberrations for which the authors investigate the effects on the 2DTM results. The results of the investigated aberration effects may be of general interest to the cryoEM community, not just those using montaging methods.

Reviewer #1 (Public Review)

The aim of the authors was to clarify the function of pinnae, forming part of katydid ears in the forelegs. Previous work suggested a protective function for the thin tympana or a device for directional hearing. A major strength of the paper is the combination of methods, such as experimental biophysical measurements with Laser-Doppler-Vibrometry and numerical modelling. In addition, detailed morphological data were obtained by scanning ears with a µCT-scanner, which formed the basis for producing 3D-printed models of the ear. These methods were combined with audiograms of sensory units in the ear, and measurements of behavioral sensitivity.

Using experimental ablation of the pinnae, the authors can convincingly show that the cavities formed by the pinnae produce resonances at very high ultrasonic frequencies and that these resonances boost the perception of sound by about 20 - 30 decibels, i.e. make the ear more sensitive for these frequencies. By contrast, the data do not support the hypothesis that pinnae serve in directional hearing.

To my knowledge, the method of performing acoustic measurements using synthetic 3D-printed scaled ear models is completely new in the field. It offers great advantages for studying the often-minute structures in insects.

Reviewer #1 (Public Review):

Using single cell analysis, Paxman et al observe protein aggregation in aging yeast that is specific to cells with deregulated rDNA silencing. This is confirmed in sir2 mutant cells. The authors then investigate the mechanism by which silencing defects of the rDNA locus might be linked to a decline in protein homeostasis. Through a screen for aggregation of RNA binding proteins, they find that disruption of rDNA silencing leads to aggregation of those RNA binding proteins that are involved in rRNA processing. Overexpression of a subset of these rRNA binding genes consistently shorten the lifespan of mode 1 cells, presumably by contributing to their defects in protein homeostasis. This suggests that age dependent changes in rDNA silencing lead to the aberrant expression of rRNAs and the formation of rDNA circles. Deletion of fob1 (resulting in a loss of rDNA recombination) indeed suppresses aggregation of Nop15 that is used for in-depth analysis. Of note, enhancing rRNA transcription or Nop15 expression leads to enhanced protein aggregation even in the absence of rDNA circles.

In all this study addresses an interesting and exciting question and is well executed. Importantly, it contributes to the understanding of distinct aging trajectories and raises important questions how these processes might be relevant in multicellular organisms. Given the fact that the paper focuses on rDNA silencing, I think that using the term "chromatin stability" is too broad and should be replaced with "rDNA silencing".

Reviewer #1 (Public Review):

In this manuscript the authors set out to characterise the process of differentiation of inner cell mass cells within the mouse blastocyst into either epiblast or primitive endoderm, which is a binary fate choice, using various models. To this end, they made use of well-established reporter cell lines previously generated in their lab as well as a widely used fluorescent system (FUCCI) that allows stages in the cell cycle to be visualised and sorted. The experimental output was compared with computational models and published data generated from mouse embryos during the process of primitive endoderm and epiblast segregation. Their data uncovered interesting mechanistic insight into the dynamics of the cell cycle and how these correlate with lineage choice and amplification. The methods have been carefully considered and validated in previous work by the group and the analysis is thorough. The single cell profiling is particularly well presented, and backed up by immunofluorescence data using well-characterised lineage reporters with appropriate statistical analysis. Probably the most interesting finding, which the authors identify as unexpected, is the considerable lengthening of the G1 part of the cell cycle in cells differentiating into PrE, but coinciding with a reduction in overall cell cycle length. Also, cell cycle length from mother to daughter cells in all conditions appears not to be inherited, yet sister cells, and to a lesser extent, cousins, appear to retain similar cell cycle dynamics. This feature is attributed to differential levels of FGF, suggested by the use of PD03 or PD17 as downstream inhibitors. Not surprisingly, levels of the PrE-associated factor Hex could predict the likelihood of differentiation to PrE, but also higher levels of Hex correlated with a shorter cell cycle. Also, blocking MEK/ERK signalling increased cell cycle duration as well as reducing differentiation to PrE in the culture conditions designed to promote differentiation to epiblast. The aims of the paper appear to be achieved and the results adequately support the authors' conclusions. A similar system to the one established here could be envisaged for downstream developmental processes, such as those involving binary decisions for specific tissue formation in organogenesis, but would require the generation and validation of different reporter cell lines.

Reviewer #1 (Public Review):

Selecting appropriate Bioinformatics approaches to arrive at a consensus classification of SNVs can be labor intensive and misleading due to discordance in results from different programs. The authors evaluated 31 Bioinformatic or computational tools used for in silico prediction of single nucleotide variants (SNVs). They selected a filtered list of SNVs at the HBA1, HBA2, and HBB genes, and compared in silico prediction results with annotations based on evidence in literature and databases curated by an expert panel comprising co-authors of this study. They found both specificity and concordance among different tools lacking in certain aspects when thresholds are chosen to maximize the Matthews correlation (MCC) and thus proposed an improved strategy. For this, the authors focused on the top prediction algorithms and varied their decision thresholds separately for pathogenic and benign variant classification and optimized the predictive power of these tools by choosing thresholds that generated at least supporting strength likelihood ratios (LRs) to achieve balanced classification.

The authors have likely spent significant effort annotating the list of pathogenic or benign SNVs in adult globin genes by iteratively evaluating independent annotations submitted by experts and arriving at a consensus. These annotations when added to the database of SNVs might improve the breadth of knowledge on the pathogenicity of adult globin SNVs and likely lead to an improved prediction by the existing tools. Further, setting non-overlapping thresholds for pathogenic and benign variants seems to improve the balance in the prediction of some of the tools (with certain tradeoffs) in the context of the gene and the variant class. This is consistent with the findings of Wilcox et. al., while at the same time the authors have focused on globin variants and compared many more programs. Thus, while not a novel approach, the scale is expansive, and might guide future studies with the improved ACMG/AMP framework.

However, there are certain caveats from my perspective and these need to be explained or improved.

• The authors' approach relies heavily on the revised consensus annotations which, from my understanding, is essentially being considered as a "truth dataset", whereas variants are classified in silico according to existing annotations in the databases. The binary classification metrics compare the in silico predictions to the authors' annotations and these showed low specificity but higher sensitivity and accuracy indicating that many benign variants were misclassified as pathogenic. The authors have not clearly mentioned whether the "observed_pathogenecity" information in the input dataset in supplementary file 2 is from the Ithagenes database or the authors' reannotations. Hence, if a significant number of pathogenic variants were reannotated as benign by the expert panel, that will likely result in the tools misclassifying them as pathogenic since the tools rely on database annotations.

• The results and measure of success focus on different benchmarks for the two major analyses the authors performed. While they generated a lot of data, they have not attempted to explore and present all facets of the data for each analysis. For instance, to assess the predictive power of the 31 tools initially, the authors focus on benchmark metrics for binary classification such as Accuracy, Sensitivity, Specificity and MCC. However, in the later improved approach, the focus is on LRs but the effect of separate thresholds for pathogenic and benign classification on accuracy, sensitivity, and specificity and MCC are not explored in the results instead just mentioning PPV for certain variant types, tools, and genes.

• There is a general trade-off to altering thresholds to increase specificity which leads to reduced accuracy and sensitivity. Thus, in this case, the improved approach suggested by the authors increases specificity but there is a simultaneous reduction in accuracy and sensitivity thus leading to the potentially higher misclassification of pathogenic variants as benign. One has to consider then, whether this is ideal in the case of globins where an in silico misclassification of pathogenicity can be easily verified by subsequent diagnostic testing to confirm whether the variant actually affects hemoglobin. Overclassification of pathogenicity in the case of globins is thus not necessarily a major problem since they will not directly lead to patients receiving treatment before additional confirmatory tests. However, misclassification of pathogenic variants as benign will pose greater harm to individuals at risk of disease.

• This is a largely descriptive study of the performance of various programs, but the authors did not attempt to explain why according to them the various tools performed a certain way in their analysis. Thus, their rationale for proposing the improved approach of separate thresholds for pathogenic and benign variants was unclear. Attempting to understand whether there is a correlation between the type of data the tool uses, and its performance could explain the tools' prediction power and how to improve it. For instance, some of the tools are metapredictors that take as input scores from various other tools also tested in this study. Thus, there will be some redundancy in the final classification.

• Expanding on the previous point, the reason for discordance in HBA genes but concordance in HBB was unclear. It might be a result of the bigger HBB dataset compared to HBA although the authors did not explore or mention whether the size of the dataset correlates with concordance. They also did not test for concordance or discordance after the separate thresholds were applied so it is not clear whether their proposed approach improves concordance for the HBA variant predictions of the top tools.

Reviewer #1 (Public Review):

Mating influences many behaviours such as enhanced oviposition, suppressed mating, and a change in dietary preference. In this study, Boehm et al explore the circuit basis of the mated female's enhanced preference for polyamines.

A previous study from this group had identified a mechanism by which mating reduced sensitivity of the olfactory sensory neurons resulting in a preference for higher concentrations of polyamines after mating. However, the preference for polyamines outlasts this mechanism by many days. So, in this study, the authors explore central brain circuits that might encode this persistent behavioural switch. Briefly, they identify neurons within the mushroom body - intrinsic neurons, output neurons and dopaminergic neurons (DAN) - that are involved in this behaviour. They also identify output neurons of the lateral horn that are involved in it.

The behaviour itself consists of two phases: 1) the mating experience, and 2) the subsequent expression of the polyamine preference. The authors use behavioural assays and neurogenetics to demonstrate that:

1. The ability to detect odours via the OR67d neurons at the time of mating is necessary to bring about the behavioural switch.

2. Activity of the intrinsic neurons of the mushroom body is necessary at both times - during the mating and the expression - to bring about the behavioural switch.

3. They identify one set of dopaminergic neurons - B1 DANs - that are sufficient but not necessary ***at the time of mating*** to induce the switch in virgin females.

4. They identify a second set of dopaminergic neurons - B2 DANs - that are necessary to ***at the time of expression*** to demonstrate the increased polyamine preference ******in mated females.

5. They identify a set of mushroom body output neurons (MBONs) downstream of the B1-DANs and show that output from the B1 region is necessary and sufficient at the time of mating for the expression of polyamine preference.

6. They identify MBONs downstream of the B2 DANs and find that they play no role at the time of mating, but that they are necessary and sufficient at the time of expression to suppress the polyamine preference.

7. They identify a set of output neurons of the lateral horn and find that they are necessary at the time of expression of polyamine preference.

The authors also use functional imaging to show that there are no brain-wide changes upon mating in the encoding of one of the polyamines. They explore how cVA (an odour they believe is relevant at the time of mating) is represented in the neurons they have identified. They find that the B1 DANs show enhanced representation of cVA post mating, however, their MBONs do not alter their response to cVA post mating. The B2-MBONs respond to both putrescine and cVA and show no alteration in their response post mating.

In summary, the authors have identified a mechanism similar to associative learning that operates across the mushroom body and lateral horn, to 'learn' the experience of mating and express it as an enhanced preference to a nutritionally rich food source.

Reviewer #1 (Public Review):

In this study, Zheng and Zhao identified the unannotated open reading frames (ORFs) in Drosophila, termed utORF, mainly based on proteomics datasets. The authors extended their analyses to the birth and the evolutionary heterogeneity of utORF. These analyses uncovered several types of utORFs that bear different feature, including transcription, age, distribution, and evolutionary conservation.

The origin of de novo protein-coding genes is interesting. The authors' attempts to uncover utORFs from proteomics datasets are much appreciated, but crucial cross-validation is missing. Given a high potential of false positives in MS datasets, it is difficult to evaluate the evolutionary aspects of the identified ORFs. Some experimental validation is needed to confirm the translational potential of utORFs with or without start codons.

Reviewer #1 (Public Review):

In this manuscript, Goering et al. investigate subcellular RNA localization across different cell types focusing on epithelial cells (mouse C2bbe1 and human HCA-7 enterocyte monolayers, canine MDCK epithelial cells) as well as neuronal cultures (mouse CAD cells). They use their recently established Halo-seq method to investigate transcriptome-wide RNA localization biases in C2bbe1 enterocyte monolayers and find that 5'TOP-motif containing mRNAs, which encode ribosomal proteins (RPs), are enriched on the basal side of these cells. These results are supported by smFISH against endogenous RP-encoding mRNAs (RPL7 and RPS28) as well as Firefly luciferase reporter transcripts with and without mutated 5'TOP sequences. Furthermore, they find that 5'TOP-motifs are not only driving localization to the basal side of epithelial cells but also to neuronal processes. To investigate the molecular mechanism behind the observed RNA localization biases, they reduce expression of several Larp proteins and find that RNA localization is consistently Larp1-dependent. Additionally, the localization depends on the placement of the TOP sequence in the 5'UTR and not the 3'UTR. To confirm that similar RNA localization biases can be conserved across cell types for other classes of transcripts, they perform similar experiments with a GA-rich element containing Net1 3'UTR transcript, which has previously been shown to exhibit a strong localization bias in several cell types. In order to determine if motor proteins contribute to these RNA distributions, they use motor protein inhibitors to confirm that the localization of individual members of both classes of transcripts, 5'TOP and GA-rich, is kinesin-dependent and that RNA localization to specific subcellular regions is likely to coincide with RNA localization to microtubule plus ends that concentrate in the basal side of epithelial cells as well as in neuronal processes.

In summary, Goering et al. present an interesting study that contributes to our understanding of RNA localization. While RNA localization has predominantly been studied in a single cell type or experimental system, this work looks for commonalities to explain general principles. I believe that this is an important advance, but there are several points that should be addressed.

Comments:

1. The Mili lab has previously characterized the localization of ribosomal proteins and NET1 to protrusions (Wang et al, 2017, Moissoglu et al 2019, Crisafis et al., 2020) and the role of kinesins in this localization (Pichon et al, 2021). These papers should be cited and their work discussed. I do not believe this reduces the novelty of this study and supports the generality of the RNA localization patterns to additional cellular locations in other cell types.

2. The 5'TOP motif begins with an invariant C nucleotide and mutation of this first nucleotide next to the cap has been shown to reduce translation regulation during mTOR inhibition (Avni et al, 1994 and Biberman et al 1997) and also Lapr1 binding (Lahr et al, 2017). Consequently, it is not clear to me if RPS28 initiates transcription with an A as indicated in Figure 3B. There also seems to be some differences in published CAGE datasets, but this point needs to be clarified. Additionally, it is not clear to me how the 5'TOP Firefly luciferase reporters were generated and if the transcription start site and exact 5'-ends of these constructs were determined. This is again essential to determine if it is a pyrimidine sequence in the 5'UTR that is important for localization or the 5'TOP motif and if Larp1 is directly regulating the localization by binding to the 5'TOP motif or if the effect they observe is indirect (e.g. is Larp1 also basally localized?). It should also be noted that Larp1 has been suggested to bind pyrimidine-rich sequences in the 5'UTR that are not next to the cap, but the details of this interaction are less clear (Al-Ashtal et al, 2021)

3. In figure 1A, they indicate that mRNA stability can contribute to RNA localization, but this point is never discussed. This may be important to their work since Larp1 has also been found to impact mRNA half-lives (Aoki et al, 2013 and Mattijssen et al 2020, Al-Ashtal et al 2021). Is it possible the effect they see when Larp1 is depleted comes from decreased stability?

4. Also Moor et al, 2017 saw that feeding cycles changed the localization of 5'TOP mRNAs. Similarly, does mTOR inhibition or activation or simply active translation alter the localization patterns they observe? Further evidence for dynamic regulation of RNA localization would strengthen this paper

5. For smFISH quantification, is every mRNA treated as an independent measurement so that the statistics are calculated on hundreds of mRNAs? Large sample sizes can give significant p-values but have very small differences as observe for Firefly vs. OSBPL3 localization. Since determining the biological interpretation of effect size is not always clear, I would suggest plotting RNA position per cell or only treat biological replicates as independent measurements to determine statistical significance. This should also be done for other smFISH comparisons

6. F: How was the segmentation of soma vs. neurites performed? It would be good to have a larger image as a supplemental figure so that it is clear the proximal or distal neurites segments are being compared