• Tema: 1.036
• Processo(s): RE 1.188.352
• Relator: Min. Luiz Fux
• Título: Competência legislativa para editar norma sobre a ordem de fases de processo licitatório, à luz do art. 22, inciso XXVII, da Constituição Federal.
• O Tribunal fixou a seguinte tese: “São constitucionais as leis dos Estados, Distrito Federal e Municípios que, no procedimento licitatório, antecipam a fase da apresentação das propostas à da habilitação dos licitantes, em razão da competência dos demais entes federativos de legislar sobre procedimento administrativo”.

锐评JavaScript 中的 new 关键字

有待思考。为什么会带来这个问题？

Consolidated peer review report (24 May 2024)

GENERAL ASSESSMENT

The preprint by Vats et al. (2023) introduces a methodology of applying slow feature analysis (SFA) to AlphaFold ensembles, with the goal of identifying collective variables for subsequent MD simulations.

The study aims to leverage AlphaFold's predictive capabilities to enhance understanding of protein dynamics and rare events, such as cryptic pocket opening, protein-ligand binding/unbinding, and allosteric modulation. By integrating AlphaFold predictions with molecular dynamics (MD) simulations and slow feature analysis (SFA), the objective is to develop a comprehensive framework for efficiently sampling and analyzing these critical molecular events in ways that might not be sampled by classical simulations or using traditional collective variables alone.

Key findings are that AlphaFold-generated structural ensembles provide useful initial conformations that capture essential conformational heterogeneity. The study demonstrates the utility of AlphaFold in seeding MD simulations to capture rare events, such as the flipping of key residues necessary for cryptic pocket opening in plasmepsin II. In the RIPK2 test case, conformational alterations in the activation loop and DFG moiety elucidate their roles in protein function and interactions relevant to inflammatory diseases. Integration of SFA with metadynamics allows for the efficient sampling of rare events within a shorter simulation time compared to traditional methods, thereby accelerating the exploration of protein dynamics. Generally, their approach works for sampling relevant conformational changes in both side chains and backbones for at least two test cases.

Strengths of this work include the well written description of the SFA method, and demonstration of success in two distinct cases. Integrating AlphaFold with computational methods like SFA and metadynamics is in principle a powerful approach to studying protein dynamics and functional mechanisms, with potential applications in drug discovery and disease understanding. This study showcases the synergy between AI-based protein structure prediction and computational biology, facilitating more comprehensive and efficient exploration of protein dynamics and interactions.

Weaknesses include a lack of clarity as to what input data are required to run the method, what criteria were used to measure success, and what specifically is learned by the application of SFA, as well as some missing figure captions and citations. A general concern about applicability is the use of vanilla AlphaFold predictions as starting points for molecular dynamics, for example given the tendency of the AlphaFold inference system to bias towards states with more contacts.

RECOMMENDATIONS

The manuscript in its current state is convincing in presenting the method, but could benefit from reorganization and streamlining to more directly expose the relevant results to the reader.

Essential revisions:

1. The manuscript is not clear in defining what data are required to run this method. The initial modeling is done with AlphaFold, which requires only an input sequence. However, the pipelines for the two main test cases are quite different, with two 40-ns simulations for each of the 80 AlphaFold models of plasmepsin-II, but ten 20-ns simulations for each of 32 AlphaFold models of RIPK2; no explanation is given for these different parameterizations. More importantly, for plasmepsin-II the metadynamics simulations were executed on PDB structures instead of AlphaFold models, implying that such structures are in fact necessary. It is not clear what the starting structure was used for metadynamics simulations of RIPK2. The authors should clearly state whether they believe experimental structures as metadynamics inputs are necessary for this method to work, as it is an important consideration for prospective users.
2. Confidence in AlphaFold-generated models should be analyzed, or at least discussed. The underlying assumption regarding the presence of conformational diversity in the generated ensemble is speculative at best. The proposed method could be tested in protein systems with known conformational states as references to validate sampling; methods like AFcluster1 or SPEACH_AF2 could enhance diversity.
3. There are relatively few details about what specifically is learned by the application of SFA. Although the details of the approach for the given systems are clearly described in Methods, there is little description of its applicability to other fields. In Results, figures S3A and S8 aim to explain the learned features for plasmepsin-II and RIPK2 respectively, but it is not clear what these features are, or what exactly is communicated. The x-axes are particularly confusing, as they seem to indicate a sequential index of features that do not correspond to amino acids (for example, the text refers to Phe165 in RIPK2, but the x-axes in S8 end around 150). Although machine-learning-derived features are often difficult to explain, it would help to clarify the x-axis titles, and add qualitative descriptions to the text and/or captions. There are also few examples for how metadynamics with SFA-picked CVs compares to traditional metadynamics with hand-picked CVs. Figures 8E/F, S12, and S13 compare how this method captures transitions of RIPK2 between the two states of interest, while unbiased simulations do not; but otherwise, the authors rely on prior publications to illustrate advantages of their approach in uncovering cryptic pockets.

Optional suggestions:

1. The tests being carried out to evaluate success should be clarified. In the case of plasmepsin-II, success was evaluated on the basis of chi-angle rotations of Trp41 and Tyr77; for RIPK2, the relevant residues were Phe165 and Trp170. However, these residues are only introduced (briefly) in Methods, then explained in somewhat more detail in Results. It would be helpful to add at least one or two sentences about these residues in the Introduction.
2. The number of samples is an important factor in determining the extent of conformational diversity in the ensemble generated by AlphaFold. Optimizing this for downstream metadynamics-SFA should expedite convergence, as it is highly dependent on initial states.
3. In the simulations field, it is common to use time-lagged component analysis (TICA) to describe slow modes of motion. Could the authors compare their method with this previously established approach?
4. Before training SFA, the authors performed parallel MD simulations starting from the AlphaFold-generated seeds. It would be nice to see what conformational space is covered during the initial unbiased MD simulations, to see what information is gained from these relative to the static starting positions of the AlphaFold models. Are these simulations connected in the space that is used to train SFA? If not, how could this affect the analysis?
5. The description of RIPK2 on p. 14, particularly its biological relevance, seems out of place in Results. Consider moving some of this content to Introduction and/or Discussion.

REVIEWING TEAM

Reviewed by:

Diego del Alamo, Investigator, GSK, Switzerland: protein design, deep learning

Nandan Haloi, Postdoctoral Fellow, KTH Royal Institute of Technology, Sweden: molecular dynamics simulations, enhanced sampling, Markov state modeling

Yogesh Kalakoti, Postdoctoral Fellow, Linköping University, Sweden: computational biology, large language models, structural bioinformatics

Curated by:

Rebecca J. Howard, Senior Researcher, Stockholm University, Sweden

(This consolidated report is a result of peer review conducted by Biophysics Colab on version 2 of this preprint. Comments concerning minor and presentational issues have been omitted for brevity.)

Can we use it in lab? Looks highly inflammable.

O Índice de Vegetação por Diferença Normalizada (NDVI, do inglês Normalized Difference Vegetation Index) é uma métrica amplamente utilizada na área de sensoriamento remoto para quantificar a vegetação em uma determinada área a partir de imagens de satélite ou aeronaves. Este índice é baseado na reflexão da luz em diferentes comprimentos de onda pelas plantas.

Reviewer #1 (Public Review):

Summary:

This is an experimentally soundly designed work and a very well-written manuscript. There is a very clear logic that drives the reader from one experiment to the next, the experimental design is clearly explained throughout and the relevance of the acquired data is well analyzed and supports the claims made by the authors. The authors made an evident effort to combine imaging, genetic, and molecular data to describe previously unknown early embryonic movement patterns and to identify regulatory mechanisms that control several aspects of it.

Strengths:

The authors develop a new method to analyze, quantitatively, the onset of movement during the latter embryonic stages of Drosophila development. This setup allows for a high throughput analysis of general movement dynamics based on the capture of variations of light intensity reflected by the embryo. This setup is capable of imaging several embryos simultaneously and provides a detailed measure of movement over time, which proves to be very useful for further discoveries in the manuscript. This setup already provides a thorough and quantifiable description of a process that is little known and identifies two different phases during late embryonic movements: a myogenic phase and a neurogenic phase, which they elegantly prove is dependent on neuronal activity by knocking down action potentials across the nervous system.

However, in this system, movement is detected as a whole, and no further description of the type of movement is provided beyond frequency and amplitude; it would be interesting to know from the authors if a more precise description of the movements that take place at this stage can be achieved with this method (e.g. motion patterns across the A-P body axis).

Importantly, this highly quantitative experimental setup is an excellent system for performing screenings of motion regulators during late embryonic development, and its use could be extended to search for different modulators of the process, beyond miRNAs (genetic mutants, drugs, etc.).

Using their newly established motion detection pipeline, the authors identify miR-2b-1 as required for proper larval and embryonic motion, and identify an overall reduction in the quantity of both myogenic and neurogenic movements, as well as an increased frequency in neurogenic movement "pulses".

Focusing on the neurogenic movement phenotype the authors use in situ probes and perform RT-PCR on FACS-sorted CNS cells to unambiguously detect miR-2b-1 expression in the embryonic nervous system. The neurogenic motion defects observed in miR-2b-1 mutant embryos and early larvae can be completely rescued by the expression of ectopic miR-2b-1 specifically in the nervous system, providing solid evidence of the requirement and sufficiency of miR-2b-1 expressed in the nervous system to regulate these phases of movement.

To explore the mechanism through which miR-2b-1 impacts embryonic movement, the authors use a state-of-the-art bioinformatic approach to identify potential targets of miR-2b-1, and find that the expression levels of an uncharacterized gene, CG3638, are indeed regulated by miR-2b-1. Furthermore, they prove that by knocking down the expression of CG3638 in a miR-2b-1 mutant background, the neurogenic embryonic movement defects are rescued, pointing that the repression of CG3638 by miR-2b-1 is necessary for correct motion patterns in wild-type embryos. Therefore, this paper provides the first functional characterization of CG3638, and names this gene Motor.

Finally, the authors aim to discriminate which elements of the embryonic motor system miR-2b-1/Motor are required. Using directed overexpression of miR-2b-1 and Motor knockdown in the motor neurons and the chordotonal (sensory) organs, they prove that the miR-2b-1/Motor regulatory axis is specifically required in the sensory organs to promote normal embryonic and larval movement.

Weaknesses:

The initial screening to identify miRNAs involved in motion behaviors is performed in early larval movement. The logic presented by the authors is clear - it is assumed that early larval movement cannot proceed normally in the absence of previous embryonic motion - and ultimately helped them identify a miRNA required for modulation of embryonic movement. However, it is possible that certain miRNAs play a role in the modulation of embryonic movement while being dispensable for early L1 behaviors. Such regulators might have been missed with the current screening setup.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript, "A microRNA that controls the emergence of embryonic movement" by Menzies, Chagas, and Alonso provides evidence that Drosophila miR-2b-1 is expressed in neurons and controls the expression of the predicted chloride channel CG3638, here named "Motor". Loss of the miRNA leads to movement phenotypes that can be rescued by downregulation of Motor; using specific drivers, the authors show that a larval movement phenotype (slower movement) can be rescued by knockdown of Motor in the chordotonal organs, suggesting that the increase in Motor found in the chordotonal organs is likely the root of the movement defects. Overall, I found the data presented in the manuscript of reasonable quality and are well enough supported by the presented data.

The genetic and phenotypic analysis seems to be correct. The nicest part of the manuscript is the connection between the loss of a miRNA and finding its likely target in generating a phenotype. The authors also develop some protocols for the analysis of the movement phenotypes which may be useful for others.

Author response:

The following is the authors’ response to the original reviews.

Recommendations for the Authors:

Reviewer 1:

(1) Figure legends are too sparing, and often fail to describe with enough detail and accuracy the experiments presented. Especially in a work like this one, which uses plenty of different approaches and techniques and has a concise main text, description in the figure legends can really help the reader to understand the technical aspects of the experimental design. In my opinion, this will also help highlight the effort the authors put into exploring different and often new technical approaches. 

We thank Reviewer 1 for highlighting this point and agree with them that the original figure legends lacked detailed information. In this revised version of our paper we edited all figure legends providing higher detail on experiments and information displayed (see Main text p12-16, Supplementary Information p2-5). We hope this change will improve the clarity and accuracy of the description of our experiments. 

Reviewer 2:

(1) Is there evidence that the early movement phenotype is actually linked to the larval movement phenotype? I noticed that the chordotonal driver experiment was only examined for larval movement. Is this driver not expressed earlier? Could the authors check the early phenotype using this driver? Are there early drivers that are expressed in chordotonal organ precursors (not panneuronal) and does the knockdown of CG3638 in these specific cells suppress the early phenotype?

(2) More broadly, I would like to understand the function of the early embryonic movements. My concern is that they may only be a sign that the nervous system is firing up. If the rescue of the late miRNA mutant phenotype with chordotonal organ expression is only through a late change in the expression of CG3638, then the larval phenotype is probably not due to a developmental change, but a change in the immediate functioning of the neurons. Would this suggest that the early pulsing is not required for anything, at least at our level of understanding? If the driver is actually expressed early and late, then perhaps the authors could test later drivers to delimit the early and late functions of the miRNA? 

The comments by Reviewer 2 in the points above are important and enquire about the biological role of early embryonic movements and whether these movements are linked to later larval activity or are somewhat irrelevant to the behaviour of the animal at later stages. 

To address this important question, we conducted a new experiment in which we reduced neural activity specifically in the embryo (i.e. from 10hs AEL until the end of embryogenesis) and tested whether this treatment had any impact on larval movement. If – as put by Rev2 – the ‘early pulsing is not required for anything’ and the larval phenotype emerges from an acute change in neuronal physiology, then our experiment should show no effects at the larval stage. The results shown in Figure S4 (see Supplementary Information, p5) show that this is not the case: artificial reduction of neural activity during embryogenesis leads to a statistically significant reduction in larval speed, similar to that caused by the loss of miR-2b-1. This shows that modifications of embryonic activity impact larval movement. 

Furthermore, earlier work on the biological role of embryonic activity identified an activity-dependent ‘critical period’ during late embryogenesis (Giachello and Baines, 2015; Ackerman et al., 2021): manipulations at or around this critical period result in both locomotor and seizure phenotypes in larvae. We cite these papers in the main text (p7).

In addition, two recent papers (Zeng et al., 2021; Carreira-Rosario et al., 2021) – which we cite in the main text (p5) – show that inhibition of muscle activity specifically during the embryonic period prevents the generation of normal neural activity patterns in both, embryo and larva. Similar results are observed when proprioceptive sensory inputs to the central nervous system are blocked, with larval locomotion also disrupted. 

Altogether, the data already in the literature plus our new addition to the paper, show that early embryonic movements play a key role in the development of the nervous system and larval locomotion.

(3) Given the role in the larval chordotonal organs, have the authors also checked the adult movements? 

The question of whether miR-2b-1 action in chordotonal organs affects behaviour at later stages of the Drosophila life cycle is interesting and was the reason why we assessed different genetic manipulations at the larval stage. However, we believe that assessing adult locomotor phenotypes is beyond the scope of this paper. 

(4) The authors state that mir-2b-1 is a mirtron. I do not believe this is correct. It is not present in an intron in Btk from what I can see. Also, in the reference that the authors use when stating that mir-2b is a mirtron, I believe mir-2b-1 is actually used as a non-mirtron control miRNA. As mirtrons are processed slightly differently from regular hairpins and often use only the 3' end of the hairpin for miRNA creation, this may not be a trivial distinction. 

We are grateful to Rev2 for highlighting this point: indeed, as they say, miR-2b-1 is located in the 3’UTR of host gene Btk, rather than in an intron. Accordingly, in this revision we remove the comment on miR-2b-1 being a mirtron (p6) and deleted the citation accordingly. 

(5) For miRNA detection, the authors use in situ hybridization and QPCR. Both methods show that the gene is expressed but not that the mature miRNA is made. If the authors wanted a truly independent test for the presence of the miRNA, a miRNA sensor might be a better choice and it would hint at which part of the hairpin makes the functional miRNA. This is probably not necessary but could be a nice addition. 

We thank Rev2 for drawing attention to this point and allowing this clarification. The qPCR protocol we used is based on the method developed by Balcells et al., 2011 (w/303 citations) (see Materials and Methods section in Supplementary Information, p14) which allows the specific amplification of mature miRNA transcripts, and not their precursors. This method for mature miRNA PCR is so robust that it has even been patented (WO2010085966A2). To ensure that the reader is clear about our methods, we state in the main text (p6) that we perform "RT-PCR for the mature miRNA transcript".  [NB: miRNA sensors provide a useful method to assess miRNA expression but can also act as competitive inhibitors of physiological miRNA functions, titrating away miRNA molecules from their real targets in tissue; therefore, results using this method are often difficult to interpret.]

(6) Curious about mir-2b-1 and any overlap with the related mir2b-2 and the mir2a genes. I am just wondering about the similarity in their sequences/targets and if they might have similar phenotypes or enhance the phenotypes being scored by the authors. 

This is an interesting point raised by REV2 and indeed miR-2b-1 does belong to the largest family of microRNAs in Drosophila, the miR-2 family, discussed in detail by Marco et al., 2012. However, we consider that performing tests of additional miRNA mutations, both individually and in combination with miR-2b-1, is beyond the scope of this paper.

(7) Related to this, the authors show that the reduction of a single miRNA target suppresses the miRNA loss of function phenotype. This indicates that this target is quite important for this miRNA. I wonder if the target site is conserved in the human gene that the authors highlight.

This is another interesting comment by Rev2. To pursue their idea, we have performed a blast for the miR-2b-1 target site in the human orthologs of CG3638 and did not find a match suggesting that the relationship between miR-2b-1 and CG3638 is not evolutionarily preserved between insects and mammals. 

Public Reviews:

Reviewer #1:

Weaknesses: 

The authors do not describe properly how the miRNA screening was performed and just claim that only miR-2b-1 mutants presented a defective motion phenotype in early L1. How many miRNAs were tested, and how candidates were selected is never explicitly mentioned in the text or the Methods section.

We identified miR-2b-1 as part of a genetic screen aimed at detecting miRNAs with impact on embryonic movement, but this full screen is not yet complete. Seeing the clear phenotype of miR2b-1 in the embryo prompted us to study this miRNA in detail, which is what we report in this paper. 

The initial screening to identify miRNAs involved in motion behaviors is performed in early larval movement. The logic presented by the authors is clear - it is assumed that early larval movement cannot proceed normally in the absence of previous embryonic motion - and ultimately helped them identify a miRNA required for modulation of embryonic movement. However, it is possible that certain miRNAs play a role in the modulation of embryonic movement while being dispensable for early L1 behaviors. Such regulators might have been missed with the current screening setup. Although similar changes to those described for the neurogenic phase of embryonic movement are described for the myogenic phase in miR-2b-1 mutants (reduction in motion amplitude), this phenotype goes unexplored. This is not a big issue, as the authors convincingly demonstrate later that miR-2b-1 is specifically required in the nervous system for proper embryonic and larval movement, and the effects of miR-2b-1 on myogenic movement might as well be the focus of future work. However, it will be interesting to discuss here the implications of a reduced myogenic movement phase, especially as miR-2b-1 is specifically involved in regulating the activity of the chordotonal system - which precisely detects early myogenic movements. 

We thank Rev1 for their interest in that loss of miR-2b-1 results in a decrease in movement during the myogenic phase, in addition to the neurogenic phase. Indeed, two recent papers (Zeng et al., 2021; Carreira-Rosario et al., 2021) – which we cite in the main text (p5) – show that inhibition of muscle activity during a period that overlaps with the myogenic phase prevents the formation of normal neural activity patterns and larval locomotion. They also observe the same when inhibiting proprioceptive sensory inputs to the central nervous system. This could suggest that the effects of miR-2b-1 on the myogenic phase might have ‘knock-on’ effects upon the later neurogenic phase and larval movement. However, we note that genetic restoration of miR-2b-1 expression specifically to neurons completely rescues the larval speed phenotype (Fig. 3G), suggesting that the dominant effect of miR-2b-1 upon movements is through its action within neurons. To recognise Rev1’s comment we have added a short sentence to the text (p7) suggesting that ‘the effects of miR-2b-1 observed at earlier stages (myogenic phase) are possibly offset by normal neural expression of miR-2b-1’.  

FACS-sorting of neuronal cells followed by RT-PCR convincingly detects the presence of miR-2b-1 in the embryonic CNS. However, control of non-neuronal cells would be required to explore whether miR-2b-1 is not only present but enriched in the nervous system compared to other tissues. This is also the case in the miR-2b-1 and Janus expression analysis in the chordotonal organs: a control sample from the motor neurons would help discriminate whether miR-2b-1/Janus regulatory axis is specifically enriched in chordotonal organs or whether both genes are expressed throughout the CNS but operate under a different regulation or requirements for the movement phenotypes.

The RNA in situ hybridisation data included in the paper (Fig. 3B) show that RNA probes for miR2b-1 precursors reveal very strong signal in neural tissue – with very low signal detected in other tissues – strongly indicating that expression of miR-2b-1 is highly enriched in the nervous system.

Reviewer #2:

Weaknesses: 

As I mentioned above, I felt the presentation was a bit overstated. The authors present their data in a way that focuses on movement, the emergence of movement, and how their miRNA of interest is at the center of this topic. I only point to the title and name that they wish to give the target of their miRNA to emphasize this point. "Janus" the GOD of movement and change. The results and discussion section starts with a paragraph saying, "Movement is the main output of the nervous system... how developing embryos manage to organise the necessary molecular, cellular, and physiological processes to initiate patterned movement is still unknown. Although it is clear that the genetic system plays a role, how genes control the formation, maturation and function of the cellular networks underlying the emergence of motor control remains poorly understood." While there is nothing inherently untrue about these statements, it is a question of levels of understanding. One can always argue that something in biology is still unknown at a certain level. However, one could also argue that much is known about the molecular nature of movement. Next, I am not sure how much this work impacts the area of study regarding the emergence of movement. The authors show that a reduction of a miRNA can affect something about certain neurons, that affects movement. The early movements, although slightly diminished, still emerge. Thus, their work only suggests that the function of some neurons, or perhaps the development of these neurons may impact the early movements. This is not new as it was known already from early work from the Bate lab.  Later larval movements were also shown to be modified in the miRNA mutants and were traced to "janus" overexpression in the chordotonal organs. As neurons are quite sensitive to the levels of Cl- and Janus is thought to be a Cl- channel, this could lead to a slight dysfunction of the chordotonal neurons. So, based on this, the work suggests that dysfunction of the chordotonal organs could impact larval movement. This was, of course, already known. The novelty of this work is in the genes being studied (important or not). We now know that miR 2b-1 and Janus are expressed in the early neurons and larval chordotonal neurons and their removal is consistent with a role for these genes in the functioning of these neurons. This is not to trivialize these findings, simply to state that these results are not significantly changing our overall understanding of movement and the emergence of movement. I would call it a stretch to say that this miRNA CONTROLS the emergence of movement, as in the title. 

As already mentioned in our provisional response, on this point we politely – but strongly – disagree with Rev2’s suggestion that the findings are inflated by our language. We also note that they criticise our use of the verb ‘control’, yet this is a standard textbook term in molecular biology to describe biological processes regulated by genetic factors: given that miR-2b-1 regulates movement patterns during embryogenesis, to say that miR-2b-1 ‘controls’ embryonic movement in the Drosophila embryo is reasonable and in line with the language used in the field. 

Finally, the name Janus should be changed as it is already being used. A quick scan of flybase shows that there is a Janus A and B in flies (phosphatases) and I am surprised the authors did not check this. I was initially worried about the Janus kinase (JAK) when I performed the search. While I understand that none are only called Janus, studies of the jan A and B genes refer to the locus as the janus region, which could lead to confusion. The completely different molecular functions of the genes relative to CG3638 add to the confusion. Thus, I ask that the authors change the name of CG3638 to something else.

Thank you for spotting this omission. In the revised MS we propose a new name – Movement Modulator (Motor) – for the gene previously described as Janus (CG3638) to avoid annotation issues at FlyBase due to other, unrelated genes that include this word as part of their names. All instances where Janus was used are now replaced by Motor (abstract; main text pages 9-10; Figure 4).

This should be a regular paragraph rather than a quote block.

Delete the sentence about the time limit.

Add new section

"Idle timeout

If you do not interact with the codespace, it will close automatically when it reaches the idle timeout limit. By default, this is 30 minutes, but you can set a personal timeout limit in your GitHub settings.

• O conceito de cultura tem várias acepções, sendo a mais utilizada como um conjunto de crenças, conhecimentos, manifestações artísticas, morais, hábitos, entre outros, que são adquiridos no espaço e no tempo. Por isso, não existe ser humano que não tenha cultura, pois ela é inerente a sua vida.

• A cultura popular é qualquer manifestação artística (dança, música, ritos, folclore, literatura, arte) que o povo produz e que o povo participe ativamente, sendo o interlocutor.

• A cultura popular surge de tradições e costumes regionais, vindo de baixo para cima. Ou seja, não é imposta por uma elite ou pelo Estado ou por meio de comunicação tradicionais. Por isso, se diferencia da Cultura de Massas, que utiliza manifestações culturais com distribuição massificada, como a televisão, o futebol, entre outros, que tem por muitas vezes objetos comerciais e econômicos.

• Os elementos que compõem a cultura popular são importantes fontes da história de um povoado, um Estado e enfim uma nação, e por isso devem ser preservados.

Author Response:

Reviewer #1 (Public Review):

Summary:

This manuscript reports the substrate-bound structure of SiaQM from F. nucleatum, which is the membrane component of a Neu5Ac-specific Tripartite ATP-dependent Periplasmic (TRAP) transporter. Until recently, there was no experimentally derived structural information regarding the membrane components of the TRAP transporter, limiting our understanding of the transport mechanism. Since 2022, there have been 3 different studies reporting the structures of the membrane components of Neu5Ac-specific TRAP transporters. While it was possible to narrow down the binding site location by comparing the structures to proteins of the same fold, a structure with substrate bound has been missing. In this work, the authors report the Na+-bound state and the Na+ plus Neu5Ac state of FnSiaQM, revealing information regarding substrate coordination. In previous studies, 2 Na+ ion sites were identified. Here, the authors also tentatively assign a 3rd Na+ site. The authors reconstitute the transporter to assess the effects of mutating the binding site residues they identified in their structures. Of the 2 positions tested, only one of them appears to be critical to substrate binding.

Strengths:

The main strength of this work is the capture of the substrate-bound state of SiaQM, which provides insight into an important part of the transport cycle.

Weaknesses:

The main weakness is the lack of experimental validation of the structural findings. The authors identified the Neu5Ac binding site, but only tested 2 residues for their involvement in substrate interactions, which was very limited. The authors tentatively identified a 3rd Na+ binding site, which if true would be an impactful finding, but this site was not tested for its contribution to Na+ dependent transport, and the authors themselves report that the structural evidence is not wholly convincing. This lack of experimental validation undermines the confidence of the findings. However, the reporting of these new data is important as it will facilitate follow-up studies by the authors or other researchers.

The main concern, also mentioned by other reviewers, is the lack of mutational data and functional studies on the identified binding sites. Two other structures of TRAP transporters have been determined, one from Haemophilus influenzae (Hi) and the other from Photobacterium profundum (Pp). We will refer to the references in this paper as [1], Peter et al. as [2], and Davies et al. as [3]. The table below lists all the mutations made in the Neu5Ac binding site, including direct polar interactions between Neu5Ac and the side chains, as well as the newly identified metal sites.

The structure of Fusobacterium nucleatum (Fn) that we have reported shows a significant sequence identity with the previously reported Hi structure. When we superimpose the Pp and Fn structures, we observe that nearly all the residues that bind to the Neu5Ac and the third metal site are conserved. This suggests that mutagenesis and functional studies from other research can be related to the structure presented in our work.

The table below shows that all three residues that directly interact with Neu5Ac have been tested by site-directed mutagenesis for their role in Neu5Ac transport. Both D521 and S300 are critical for transport, while S345 is not. We do not believe that a mutation of D521A in Fn, followed by transport studies, will provide any new information.

However, Peter et al. have mutated only one of the 5 residues near the newly identified metal binding site, which resulted in no transport. The rest of the residues have not been functionally tested. We propose to mutate these residues into Ala, express and purify the proteins, and then carry out transport assays on those that show expression. We will include this information in the revised manuscript.

Reviewer #2 (Public Review):

In this exciting new paper from the Ramaswamy group at Purdue, the authors provide a new structure of the membrane domains of a tripartite ATP-independent periplasmic (TRAP) transporter for the important sugar acid, N-acetylneuraminic acid or sialic acid (Neu5Ac). While there have been a number of other structures in the last couple of years (the first for any TRAP-T) this is the first to trap the structure with Neu5Ac bound to the membrane domains. This is an important breakthrough as in this system the ligand is delivered by a substrate-binding protein (SBP), in this case, called SiaP, where Neu5Ac binding is well studied but the 'hand over' to the membrane component is not clear. The structure of the membrane domains, SiaQM, revealed strong similarities to other SBP-independent Na+-dependent carriers that use an elevator mechanism and have defined Na+ and ligand binding sites. Here they solve the cryo-EM structure of the protein from the bacterial oral pathogen Fusobacterium nucleatum and identify a potential third (and theoretically predicted) Na+ binding site but also locate for the first time the Neu5Ac binding site. While this sits in a region of the protein that one might expect it to sit, based on comparison to other transporters like VcINDY, it provides the first molecular details of the binding site architecture and identifies a key role for Ser300 in the transport process, which their structure suggests coordinates the carboxylate group of Neu5Ac. The work also uses biochemical methods to confirm the transporter from F. nucleatum is active and similar to those used by selected other human and animal pathogens and now provides a framework for the design of inhibitors of these systems.

The strengths of the paper lie in the locating of Neu5Ac bound to SiaQM, providing important new information on how TRAP transporters function. The complementary biochemical analysis also confirms that this is not an atypical system and that the results are likely true for all sialic acid-specific TRAP systems.

The main weakness is the lack of follow-up on the identified binding site in terms of structure-function analysis. While Ser300 is shown to be important, only one other residue is mutated and a much more extensive analysis of the newly identified binding site would have been useful.

Please see the comments above.

Reviewer #3 (Public Review):

The manuscript by Goyal et al reports substrate-bound and substrate-free structures of a tripartite ATP-independent periplasmic (TRAP) transporter from a previously uncharacterized homolog, F. nucleatum. This is one of the most mechanistically fascinating transporter families, by means of its QM domain (the domain reported in his manuscript) operating as a monomeric 'elevator', and its P domain functioning as a substrate-binding 'operator' that is required to deliver the substrate to the QM domain; together, this is termed an 'elevator with an operator' mechanism. Remarkably, previous structures had not demonstrated the substrate Neu5Ac bound. In addition, they confirm the previously reported Na+ binding sites and report a new metal binding site in the transporter, which seems to be mechanistically relevant. Finally, they mutate the substrate binding site and use proteoliposomal uptake assays to show the mechanistic relevance of the proposed substrate binding residues.

The structures are of good quality, the functional data is robust, the text is well-written, and the authors are appropriately careful with their interpretations. Determination of a substrate-bound structure is an important achievement and fills an important gap in the 'elevator with an operator' mechanism. Nevertheless, I have concerns with the data presentation, which in its current state does not intuitively demonstrate the discussed findings. Furthermore, the structural analysis appears limited, and even slight improvements in data processing and resulting resolution would greatly improve the authors' claims. I have several suggestions to hopefully improve the clarity and quality of the manuscript.

We appreciate your feedback and will make the necessary modifications to the manuscript incorporating most of the suggestions. We will submit the revised version once the experiments are completed. We are also working on improving the quality of the figures and have made several attempts to enhance the resolution using CryoSPARC or RELION, but without success. We will continue to explore newer methods in an effort to achieve higher resolution and to model more lipids, particularly in the binding pocket.

Move step 3 (Check changes made using diff) and step 4 (Revert Changes (Optional step)) before step 2 (Update using svn).

After the step reverting any changes (old step 4), add a new step (before the Update using svn step).

" N. Check R with local changes

If you have any local changes remaining (which you can check with svn diff), build and check R with these changes.

cd $BUILDDIR make make check cd $TOP_SRCDIR

If the check fails with an error, you have broken something with your local changes. Fix this before proceeding to the next step. "

"1) Close R terminal

If you have an R terminal open, quit R or close the terminal.

2) Change to the source directory"

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vibration and rotation leave marks? what kinds?

what????

If you are suffering from bad eyesight, you might need to see a specialist for healthcare advice. You can also change your life habits to protect and maintain your eye health, such as eating healthy foods rich in nutrients good for the eyes. Additionally, you can practice using protective eyewear. Read this article to learn more eye care tips. https://listium.com/@chrisialling/108787/how-does-nutrition-impact-our-vision

Create two new steps after the configure step:

"5. Build R

Having configured R, we run make to build R. This take 5-10 minutes on the codespace.

make

1. Check R

Check that the build of R passes R's standard checks:

make check

This takes a couple of minutes in the codespace. The check will stop with a error message if any of the tests fail. If this happens, see SVN Help for how to revert to a version that passes check.

" Note we no longer do sudo make install

Instead of sudo make install, we need to add instructions to switch to the new R version before the Make Contributions step. E.g.

"N. Run the multi_r script to switch the version of R used for R terminals in VSCode.

multi_r

When prompted, type "C" to switch to a custom build, then the select the version by the name of the build directory, here "r-devel"

[screenshot] "

[This documentation will need updating when https://github.com/r-devel/r-dev-env/issues/104 is implemented]

https://developer.mozilla.org/fr/docs/Web/HTML

https://developer.mozilla.org/fr/docs/Web/CSS

Bite the Testo

test

-> "link to launch an R terminal."

-> "the Status Bar at the bottom of the VSCode window."

If using the code command to open an R script, then this sentence can be deleted.

You can't see this in the screenshot and people might not know where this is.

It may be better the instruct people to run

code R/example.R

from the terminal - this has the advantage of putting the script in a sensible place and opening it for editing straight away.

This information should go under point 1. Can you use a callout box rather than a quote?

->"From the main branch of the r-dev-env repo, click"

patterns of intelligibility are immanent to reality

meaning <=> being

inexhaustible intelligibility

https://docdrop.org/video/6pwBgL0BbJ0/#annotations:rkWKbEo1Ee6ciU_zRorLuw

https://via.hypothes.is/https://www.youtube.com/watch?v=6pwBgL0BbJ0

eLife assessment

This manuscript is useful to researchers with an interest in cervical cancers because it provides scRNA-seq data from a diverse cohort of 15 early-stage cervical cancer patients. While the dataset could be of use to the research community, the key claims of the paper around the immunosuppressive microenvironment associated with specific tumour cell clusters (and the properties/importance of those clusters) are incomplete. Additional experiments will be required to substantiate these claims.

Reviewer #1 (Public Review):

Summary:

The authors in this manuscript performed scRNA-seq on a cohort of 15 early-stage cervical cancer patients with a mixture of adeno- and squamous cell carcinoma, HPV status, and several samples that were upstaged at the time of surgery. From their analyses they identified differential cell populations in both immune and tumour subsets related to stage, HPV status, and whether a sample was adenocarcinoma or squamous cell. Putative microenvironmental signaling was explored as a potential explanation for their differential cell populations. Through these analyses the authors also identified SLC26A3 as a potential biomarker for later stage/lymph node metastasis which was verified by IHC and IF. The dataset is likely useful for the community, however, the strong claims made are not adequately supported by the data and would require additional functional validation.

Strengths:

The dataset could be useful for the community.<br /> SLC26A3 could potentially be a useful marker to predict lymph node metastasis with further study.

Weaknesses:

The link between the background in the introduction and the actual study and findings is often tenuous or not clearly explained. A re-working of the intro to better set up and link to the study questions would be beneficial.

For the sequencing, which kit was used on the Novaseq6000?

Additional details are needed for the analysis pipeline. How were batch effects identified/dealt with, what were the precise functions and settings for each step of the analysis, how was clustering performed and how were clusters validated etc. Currently, all that is given is software and sometimes function names which are entirely inadequate to be able to assess the validity of the analysis pipeline. This could alternatively be answered by providing annotated copies of the scripts used for analysis as a supplement.

For Cell type annotation, please provide the complete list of "selected gene markers" that were used for annotation.

No statistics are given for the claims on cell proportion differences throughout the paper (for cell types early, epithelial sub-clusters later, and immune cell subsets further on). This should be a multivariate analysis to account for ADC/SCC, HPV+/- and Early/Late stage.

The Y-axis label is missing from the proportion histograms in Figure 2D. In these same panels, the bars change widths on the right side. If these are exclusively in ADC, show it with a 0 bar for SCC, not doubling the width which visually makes them appear more important by taking up more area on the plot.

Throughout the manuscript, informatic predictions (differentiation potential, malignancy score, stemness, and trajectory) are presented as though they're concrete facts rather than the predictions they are. Strong conclusions are drawn on the basis of these predictions which do not have adequate data to support. These conclusions which touch on essentially all of the major claims made in the manuscript would need functional data to validate, or the claims need to be very substantially softened as they lack concrete support. Indeed, the fact that most of the genes examined that were characteristic of a given cluster did not show the expected expression patterns in IHC highlights the fact that such predictions require validation to be able to draw proper inferences.

The cluster Epi_10_CYSTM1 which is the basis for much of the paper is present in a single individual (with a single cell coming from another person), and heavily unconnected from the rest of the epithelial populations. If so much emphasis is placed on it, the existence of this cluster as a true subset of cells requires validation.

Claims based on survival analysis of TCGA for Epi_10_CYSTM1 are based on a non-significant p-value, though there is a slight trend in that direction.

The claim "The identification of Epi_10_CYSTM1 as the only cell cluster found in patients with stage IIICp raises the possibility that this cluster may be a potential marker to diagnose patients with lymph node metastasis." This is incorrect according to the sample distributions which clearly show cells from the patient who has EPI_10_CYSTM1 in multiple other clusters. This is then used as justification for SLC26A3 which appears to be associated with associated with late stage, however, in the images SLC26A3 appears to be broadly expressed in later tumours rather than restricted to a minor subset as it should be if it were actually related to the EPI_10_CYSTM1 cluster.

The authors claim that cytotoxic T cells express KRT17, and KRT19. This likely represents a mis-clustering of epithelial cells.

Multiple claims are made for specific activities based on GO term biological process analysis which while not contradictory to the data, certainly are by no means the only explanation for it, nor directly supported.

Reviewer #2 (Public Review):

Summary:

Peng et al. present a study using scRNA-seq to examine phenotypic properties of cervical cancer, contrasting features of both adenocarcinomas (ADC) and squamous cell carcinoma (SCC), and HPV-positive and negative tumours. They propose several key findings: unique malignant phenotypes in ADC with elevated stemness and aggressive features, interactions of these populations with immune cells to promote an immunosuppressive TME, and SLC26A3 as a biomarker for metastatic (>=Stage III ) tumours.

Strengths:

This study provides a valuable resource of scRNA-seq data from a well-curated collection of patient samples. The analysis provides a high-level view of the cellular composition of cervical cancers. The authors introduce some mechanistic explanations of immunosuppression and the involvement of regulatory T cells that are intriguing.

Weaknesses:

I believe that many of the proposed conclusions are over-interpretations or unwarranted generalizations of the single-cell analysis. These conclusions are often based on populations in the scRNA-seq data that are described as enriched or specific to a given group of samples (eg. ADC). This conclusion is based on the percentage of cells in that population belonging to the given group; for example, a cluster of cells that dominantly come from ADC. The data includes multiple samples for each group, but statistical approaches are never used to demonstrate the reproducibility of these claims.

This leads to problematic conclusions. For example, the "ADC-specific" Epi_10_CYSTM1 cluster, which is a central focus of the paper, only contains cells from one of the 11 ADC samples and represents only a small fraction of the malignant cells from that sample (Sample 7, Figure 2A). Yet, this population is used to derive SLC26A3 as a potential biomarker. SLC26A3 transcripts were only detected in this small population of cells (none of the other ADC samples), which makes me question the specificity of the IHC staining on the validation cohort.

This is compounded by technical aspects of the analysis that hinder interpretation. For example, it is clear that the clustering does not perfectly segregate cell types. In Figures 2B and D, it is evident that C4 and C5 contain mixtures of cell type (eg. half of C4 is EPCAM+/CD3-, the other half EPCAM-/CD3+). These contaminations are carried forward into subclustering and are not addressed. Rather, it is claimed that there is a T cell population that is CD3- and EPCAM+, which does not seem likely.

Author response:

Reviewer #1 (Public review):

(1) The link between the background in the introduction and the actual study and findings is often tenuous or not clearly explained. A re-working of the intro to better set up and link to the study questions would be beneficial.

Response: upon revision, we plan to rewrite the introduction of the manuscript.

(2) For the sequencing, which kit was used on the Novaseq6000?

Response: for sequencing, we used the Chromium Controller and Chromium Single Cell 3’Reagent Kits (v3 chemistry CG000183) on the Novaseq6000. We feel sorry for lacking this quite important part and will add the information in Methods.

(3) Additional details are needed for the analysis pipeline. How were batch effects identified/dealt with, what were the precise functions and settings for each step of the analysis, how was clustering performed and how were clusters validated etc. Currently, all that is given is software and sometimes function names which are entirely inadequate to be able to assess the validity of the analysis pipeline. This could alternatively be answered by providing annotated copies of the scripts used for analysis as a supplement.

Response: we apologize for the inadequacy of descriptions of data analysis process due to word count limit. We plan to provide more information, and if possible we also would like to provide scripts as supplementary data in the revised manuscript.

(4) For Cell type annotation, please provide the complete list of "selected gene markers" that were used for annotation.

Response: we will add the list of marker genes for cell type annotation in the revised manuscript.

(5) No statistics are given for the claims on cell proportion differences throughout the paper (for cell types early, epithelial sub-clusters later, and immune cell subsets further on). This should be a multivariate analysis to account for ADC/SCC, HPV+/- and Early/Late stage.

Response: considering this inadequacy, we plan to use statistic approaches for further analyses to compare the differences between each set of groups up revision.

(6) The Y-axis label is missing from the proportion histograms in Figure 2D. In these same panels, the bars change widths on the right side. If these are exclusively in ADC, show it with a 0 bar for SCC, not doubling the width which visually makes them appear more important by taking up more area on the plot.

Response: we feel sorry for impreciseness when presenting histograms such as Fig 2D and we will add labels in Y-axis. As for the width of bars, we just used the histograms generated originally from the data package. However, we did not intend to double the width on purpose to strengthen the visual importance. We sincerely feel sorry for this and will correct the similar mistakes alongside the whole manuscript.

(7) Throughout the manuscript, informatic predictions (differentiation potential, malignancy score, stemness, and trajectory) are presented as though they're concrete facts rather than the predictions they are. Strong conclusions are drawn on the basis of these predictions which do not have adequate data to support. These conclusions which touch on essentially all of the major claims made in the manuscript would need functional data to validate, or the claims need to be very substantially softened as they lack concrete support. Indeed, the fact that most of the genes examined that were characteristic of a given cluster did not show the expected expression patterns in IHC highlights the fact that such predictions require validation to be able to draw proper inferences.

Response: we agree that many conclusions, which were based on bio-informatic predictions, are written in an over-affirmative way. Upon revision, we will rewrite these conclusions more precisely.

(8) The cluster Epi_10_CYSTM1 which is the basis for much of the paper is present in a single individual (with a single cell coming from another person), and heavily unconnected from the rest of the epithelial populations. If so much emphasis is placed on it, the existence of this cluster as a true subset of cells requires validation.

Response: we are thankful for this suggestion. We think that each cluster of epithelial cells is specified from other clusters and identified by DEGs, but they are not heavily unconnected from others. Upon revision, we plan to add further validation for the existence of Epi_10_CYSTM1.

(9) Claims based on survival analysis of TCGA for Epi_10_CYSTM1 are based on a non-significant p-value, though there is a slight trend in that direction.

Response: from the data of TCGA survival analysis for Epi_10, we found a not-so-slight trend of difference between groups (with a small P value). As a result, we presented this data and hoped to add more strength to the clinical significance of this cluster. However, this indeed caused controversy because the P value is non-significant. We plan to rewrite the conclusion more precisely or delete this data in the revised manuscript.

(10) The claim "The identification of Epi_10_CYSTM1 as the only cell cluster found in patients with stage IIICp raises the possibility that this cluster may be a potential marker to diagnose patients with lymph node metastasis." This is incorrect according to the sample distributions which clearly show cells from the patient who has EPI_10_CYSTM1 in multiple other clusters. This is then used as justification for SLC26A3 which appears to be associated with associated with late stage, however, in the images SLC26A3 appears to be broadly expressed in later tumours rather than restricted to a minor subset as it should be if it were actually related to the EPI_10_CYSTM1 cluster.

Response: we feel thankful for this question. The conclusion “The identification of Epi_10_CYSTM1 as the only cell cluster found in patients with stage IIICp raises the possibility that this cluster may be a potential marker to diagnose patients with lymph node metastasis” has indeed been written too concrete according to the sample distribution. We will correct the description in the up-coming revised manuscript. As for SLC26A3, we also do not think it is “broadly” expressed, but it is specified in later tumors. When we presented the data of IHC, we only showed the strongly-positive area of each slide in order to emphasize the differences, however, this has caused misunderstandings. Thus, upon revision, we would like to show the other areas of one case or even the scan of one whole slide as supplementary data.

(11) The authors claim that cytotoxic T cells express KRT17, and KRT19. This likely represents a mis-clustering of epithelial cells.

Response: we apologize for the ignorance of further validation of cytotoxic T cells. From fig. 4B and 4C, the four different clusters of T cells were basically identified based on canonical T cell markers. And then we focused mainly on the validation and further analysis of Tregs, neglecting the other clusters. In fig. 4D we intended to only show the top DEGs in each T cell cluster and hoped to find some potential marker genes for next-step analysis. However, we did not notice that there might be contamination of epithelial cells within cytotoxic T cells when clustering. We will optimize the analysis of this part in our revision.

(12) Multiple claims are made for specific activities based on GO term biological process analysis which while not contradictory to the data, certainly are by no means the only explanation for it, nor directly supported.

Response: our initial purpose was to use GO analysis as supports for our conclusions. However we know these are only claims but not evidence, which is also the problem of our writing techniques as in question (7). Therefore, in our revised manuscript, we plan to rewrite the conclusion from the GO analysis in a more scientific way or delete these data.

Reviewer #2 (Public review):

(1) I believe that many of the proposed conclusions are over-interpretations or unwarranted generalizations of the single-cell analysis. These conclusions are often based on populations in the scRNA-seq data that are described as enriched or specific to a given group of samples (eg. ADC). This conclusion is based on the percentage of cells in that population belonging to the given group; for example, a cluster of cells that dominantly come from ADC. The data includes multiple samples for each group, but statistical approaches are never used to demonstrate the reproducibility of these claims.

Response: we understand that many of the conclusions are too sure but lack profound supporting evidence, thus we will optimize the writing in the revised manuscript. More importantly, to strengthen the validity of our data, we will try to use statistical approaches for further analysis.

(2) This leads to problematic conclusions. For example, the "ADC-specific" Epi_10_CYSTM1 cluster, which is a central focus of the paper, only contains cells from one of the 11 ADC samples and represents only a small fraction of the malignant cells from that sample (Sample 7, Figure 2A). Yet, this population is used to derive SLC26A3 as a potential biomarker. SLC26A3 transcripts were only detected in this small population of cells (none of the other ADC samples), which makes me question the specificity of the IHC staining on the validation cohort.

Response: we sincerely feel grateful for being questioned on the validity, appropriateness and the real potential of SLC26A3. We plan to add more explanation of the importance of SLC26A3 in the discussion part. We are also sorry for some over-sure conclusions about ADC-specific cell clusters, as well as the marker gene SLC26A3. However, we do not think these conclusions are problematic. In fact, due to the heterogeneity among different individuals, as well as even different sites within one individual when sampling, we think a “small faction” does not means it will not make sense. Also, these ADC-specific clusters (including Epi_10_CYSTM1) do have certain proportions when comparing with those “big fraction” groups (Fig. 2D). Furthermore, when considering the specificity of DEGs to ADC only, but not to SCC, we think it might be these ADC-specific cluster genes to have the central function to make a difference between ADC and SCC. And we further used validation experiment to support our hypothesis. Lastly and most importantly, SLC26A3 was coming from sample 7 whose clinical stage is FIGO IIIC (late stage) and pathological type is ADC. Among the 15 cases, there are only 4 cases whose clinical stages are late (within which 3 are ADC). At this point of view, we think 1 in 3 (33%) having expression of SLC26A3 (or existence of cluster Epi_10_CYSTM1) should be considered as a potential choice. Samples coming from early-staged and SCC patients do not have fractions of Epi_10_CYSTM1. This likewise indicates the specificity of this cell cluster to ADC. Therefore, in our revised manuscript, we plan to add more in-depth discussion about this question.

(3) This is compounded by technical aspects of the analysis that hinder interpretation. For example, it is clear that the clustering does not perfectly segregate cell types. In Figures 2B and D, it is evident that C4 and C5 contain mixtures of cell type (eg. half of C4 is EPCAM+/CD3-, the other half EPCAM-/CD3+). These contaminations are carried forward into subclustering and are not addressed. Rather, it is claimed that there is a T cell population that is CD3- and EPCAM+, which does not seem likely.

Response: do you mean Figure 1B and D? In the revised manuscript, we will list the canonical marker genes to cluster different types of cells to at least support that the clustering of cell types match most of the present published references. To further avoid the contamination of cells in each cluster, we will use quality controls and re-analyze these data upon revision.

eLife assessment

This important work illuminates the dynamics of BRAF in both its monomeric and dimeric forms, with or without inhibitors, combining traditional techniques and sophisticated computational analyses. The evidence presented is convincing and suggests a potential allosteric effect, though substantiating the exact mechanism will require further studies. The work has implications for understanding kinase signaling and the development of potential drug candidates. This study will be of interest to structural biologists, medicinal chemists, and pharmacologists.

Reviewer #1 (Public Review):

Summary:

This manuscript from Clayton and co-authors, entitled "Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors", aims at clarifying the molecular mechanism of BRAF dimer selectivity. Indeed, first generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microseconds MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped identify a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

Strengths:

The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidines protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors are able to stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

Weaknesses:

Regarding the analyses of the mixed state simulations, the DFG dihedral probability densities for the apo protomer (Fig. 5a right) are highly overlapping. It is not convincing that a slight shift can support the conclusion that the binding in one protomer is enough to shift the DFG motif outward allosterically. Moreover, the DFG dihedral time-series for the apo protomer (Supplementary Figure 9) clearly shows that the measured quantities are affected by significant fluctuations and poor consistency between the three replicates. The apo protomer of the mixed state simulations could be affected by the same problem that the authors pointed out in the case of the apo dimer simulations, where the amount of sampling is insufficient to model the DFG-out/-in transition properly. There is similar concern with the Lys483-Glu501 salt bridge measured for the apo protomers of the mixed simulations. As it can be observed from the probabilities bar plot (Fig. 5a middle), the standard deviation is too high to support a significant role for this interaction in the allosteric modulation of the apo protomer.

Reviewer #2 (Public Review):

Summary:

The authors employ molecular dynamics simulations to understand the selectivity of FDA approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signalling and the development of future BRAF inhibitor drugs.

Strengths:

The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (All-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

Weaknesses:

Despite the use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems, the authors could consider adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review):

Comment 1: This manuscript from Clayton and co-authors, entitled ”Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors”, aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first-generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microsecond MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped in identifying a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidine protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors can stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

Response: We thank the reviewer for the positive evaluation of our work.

Comment 2: One potential weakness in the manuscript is the lack of reported uncertainties related to the analyzed quantities. Providing this information would significantly enhance the clarity regarding the reliability of the analyses and the confidence in the claims presented.

Response and revision: We agree with the reviewer that reporting uncertainties will clarify and strengthen our arguments. Following this suggestion, we have added error bars to Figures 3 and 5 representing the standard deviation of the K-E salt bridge probability. This shows that the deviation across replicas of how often the salt bridge is present. Thus, it better supports our claim that this salt bridge is promoted by the presence of PHI1, as the deviation of the salt bridge is minimal for protomers containing PHI1. In addition to these error bars, we have also included a table to the Supplementary Information (Supplementary Table 2) containing the mean and standard deviation of the αC position, K-E distance, and DFG pseudo dihedral for each protomer in our dimer simulations.

Reviewer #2 (Public review):

Comment 1: The authors employ molecular dynamics simulations to understand the selectivity of FDA-approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signaling and the development of future BRAF inhibitor drugs.

The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (all-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

Response: We thank the reviewer for the positive evaluation of our work.

Comment 2: The use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems. However, the authors could consider the adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

Response: The current free energy methods are capable of giving accurate estimates of the relative binding free energies of similar ligands; however, accurate calculations of the absolute free energies of hydrogen bond and hydrophobic interactions are not feasible yet. Thus, we decided not to pursue the calculations.

Reviewer #1 (Suggestions to author)

Comment 1: The general recommendation is to give more details about the procedure for the analyses performed and, when possible, show the uncertainties relative to the analyzed quantities. This would clearly indicate the reliability of the analyses and the confidence of the claims. Moreover, it is not always clear how the analyses were performed.

Response and revision: As previously mentioned, we have added uncertainties to our bar graphs in Figures 3 and 5 as well as Supplemental Table 2. In regards to the clarity of our analysis, we added more detail on how the probability distributions were created, which we will discuss in our response to Comment 3.

Comment 2: It is not clear why the authors decided to titrate only the histidines without considering the other charged residues. In particular, the authors show in Supplementary Figure 2 a network of which Asp595 (protomer A) is a part and that, given the direct interaction, could affect the protonation state of His477 (protomer B).

Response: The reviewer is correct in that Asp595 directly interacts with His477 on the opposite protomer. This is exactly the reason why we did not consider titrating Asp595 – the interaction with His477 should further stabilize the charged state of Asp595 and downshift its pKa from the solution value of about 3.8. Thus, Asp595 will be charged at physiological pH and does not need to be titrated in the CpHMD simulations.

Comment 3: Regarding the probability density plots (Figures 3 and 5), clarify if you used all the data from all the replicas and all the protomers. If possible, show a comparison between each replica in the Supplementary Figures. A Supplementary Table with the probability values for the measured K-E salt bridge could be helpful since the bar plots are hard to compare. Also in this case please report the uncertainty or a comparison between the replicas.

Response and revision: To clarify how we created the probability density plots, the following line was added to the Methods section:

On page 15, third paragraph: All probability distributions were created by combining the last three µs of each replica for each system, with each distribution consisting of 50 bins. Unless specified, distributions contain quantities from both protomers in dimeric simulations.

As previously mentioned, we have included Supplemental Table 2 which contains the mean and standard deviation of the K-E distance across systems. For comparison between replicas, we found the time series of the K-E distance in the inhibitor-bound monomer and dimer systems in Supplemental Figure 7 to be sufficient.

Comment 4: It would be better to define the claim: ”it is clear that the timescale of the DFG-out to DFG-in transition is longer than our simulation timeframe of a few microseconds” (lines 208-209). To me it is not obvious why this should be ”clear”.

Response and revision: Our original statement was to convey that, as DFG-in is sampled very rarely, our simulations cannot accurately represent DFG transitions. We have revised the manuscript to the following:

On page 6, fourth paragraph: While this does suggest dimerization loosens the DFG motif, our simulations do not appropriately model the DFG-out/-in transition as the DFG-in state is only occasionally sampled.

Comment 5: In the case of the inhibited monomer simulations, the authors state: ”the PHI1Glu501 interaction can become completely disrupted, with the distance moving beyond 6 A to˚ as high as 12 A; correlated with the disruption of the PHI1-Glu501 interaction, the˚     αC position is shifted out to the range of 21 A-24˚ A” (lines 241-244). However, the plot of the PHI1-Glu501˚ interaction time-series (Supplementary Figure 7) shows that just in one replica of one protomer (Protomer A), the interaction is disrupted, and the αC position never exceeds 21 A (time-series˚ reported in Supplementary Figure 6). None of the fluctuations of the αC position appear to be correlated with the disruption of the ligand-Glu501 interaction. The time-series reported in Supplementary Figures 6 and 7 suggest that the two events are uncorrelated. Please explain this aspect or quantify the correlation to support your claim.

Response: We believe the source of this confusion is because we did not include a time series of αC for inhibited monomer simulations–Supplementary Figure 6 mentioned in the comment is of dimeric BRAF. Thus, We have added Supplementary Figure 8, a timeseries plot of the αC position for inhibited monomer and dimer protomers.

Comment 6: Regarding the analyses of the positive cooperativity, the DFG dihedral probability densities for the apo protomer (Figure 5a) are highly overlapping. Thus, it is hard to believe that these small differences support the claim that ”PHI1 binding in one protomer can allosterically shift the DFG motif outward, making it favorable for binding a second inhibitor” (lines 300-302). The authors should show that the differences in the DFG distributions (in particular, apo dimer vs PHI1 mixed) are statistically significant. Only in this case, the data could support the claim that PHI1 bound to one protomer modulates the DFG conformation in the second one. In my opinion, the overlap between the DFG dihedral probability (Figure 5a) is too high to support the claim that PHI1 is able to allosterically modulate this region in the second apo protomer. Please provide an appropriate statistical test that demonstrates that those distributions are significantly different.

Response and revision: We have adjusted this statement based on the new Supplementary Table 2 to read as the following:

On page 9, third paragraph: Although the shift is small (the differences between means is approximately one standard deviation, see Supplementary Table 2), it suggests that PHI1 binding in one protomer can allosterically shift the DFG motif outward, making it favorable for binding a second inhibitor. In contrast, the DFG dihedral of the apo protomer in the LY-bound mixed dimer appears to be slightly smaller than the apo dimer with difference between means of approximately one standard deviation (Supplementary Table 2), which is unfavorable for binding the second inhibitor (orange and grey, Figure 5a right).

Comment 7: Regarding the dimer holo simulations, I agree that in the LY-bound dimer simulations, the hydrogen bond between the ligand and the E501 is weaker, but I do not understand the sentence ”as seen from the local density maximum centered at∼3.4 A” at line 233, since the 2D˚ density plot (Figure 3h) shows that the highest peak is close to 5 A. Also, it would be useful to˚ clarify how these 2D density plots reported in Figure 3 were obtained.

Response and revision: While the highest peak in Figure 3h is close to 5 A, we were more˚ interested in the local peak close to 3.4 A. To avoid confusion we have modified the line to separate˚ both peaks:

On page 7, second paragraph: In the LY-bound dimer simulations, however, the LY–Glu501 h-bond is weaker and less stable than the counterpart of the PHI1-bound dimer, as seen from the local density maximum centered at ∼3.4 and the global maximum near ∼4.5 A (Figure 3g,h).˚

Comment 8: I have a comment on the strategy suggested to empirically classify the inhibitors by comparing the Glu501-Lys483 distance and the αC position in the two protomers of the crystal structures (in the Concluding Discussion section). The authors suggest that differences below 1 A could determine whether the flexibility of these regions is restricted or not (and whether the˚ inhibitor is equipotent or dimer-selective). However, differences below 1 A, in structures where˚ the average resolution is 2.5 A, might be highly unreliable. In fact, as the authors pointed out, LY˚ and Ponatinib would be classified (erroneously) as dimer-selective inhibitors according to these criteria.

Response and revision: We agree that this proposed method could be unreliable; we intend this strategy to be used as a “quick and dirty” method for analyzing future structures in order to assess selectivity for dimeric BRAF. To convey this, we added the following sentence:

On page 12, second paragraph: Given that the resolution of a resolved structure is often ∼23 A, this proposed assessment is not intended to replace more rigorous tests, i.e. utilizing MD˚ simulations.

Comment 9: A suggestion is to include representative snapshots of the MD simulation in the GitHub repository could allow the reader to better appreciate the results described in the present study.

Response and revision: In order to convey the difference between induced effects of PHI1 and LY, we have added a new folder named snapshots to the GitHub repository which contains the snapshots from the simulations of one LY or one PHI1 bound BRAF (visualized in Figure 5c) in the form of PDB files.

Reviewer #1 (Public Review):

Summary:

In the manuscript by Tie et.al., the authors couple the methodology which they have developed to measure LQ (localization quotient) of proteins within the Golgi apparatus along with RUSH based cargo release to quantify the speed of different cargos traveling through Golgi stacks in nocodazole induced Golgi ministacks to differentiate between cisternal progression vs stable compartment model of the Golgi apparatus. The debate between cisternal progression model and stable compartment model has been intense and going on for decades and important to understand the basic way of function/organization of the Golgi apparatus. As per the stable compartment model, cisterna are stable structures and cargo moves along the Golgi apparatus in vesicular carriers. While as per cisternal progression model, Golgi cisterna themselves mature acquiring new identity from the cis face to the trans face and act as transport carriers themselves. In this work, authors provide a missing part regarding intra-Golgi speed for transport of different cargoes as well as the speed of TGN exit and based on the differences in the transport velocities for different cargoes tested favor a stable compartment model. The argument which authors make is that if there is cisternal progression, all the cargoes should have a similar intra-Golgi transport speed which is essentially the rate at which the Golgi cisterna mature. Furthermore, using a combination of BFA and Nocodazole treatments authors show that the compartments remain stable in cells for at least 30-60 minutes after BFA treatment.

Strengths:

The method to accurately measure localization of a protein within the Golgi stack is rigorously tested in the previous publications from the same authors and in combination with pulse chase approaches has been used to quantify transport velocities of cargoes through the Golgi. This is a novel aspect in this paper and differences in intra-Golgi velocities for different cargoes tested makes a case for a stable compartment model.

Weaknesses:

Experiments are only tested in one cell line (HeLa cells) and predominantly derived from experimental paradigm using RUSH assays where a secretory cargo is released in a wave (not the most physiological condition) and therefore additional approaches would make a more compelling case for the model.

eLife assessment

This important study sheds new light on cargo movement within the Golgi apparatus, challenging the cisternal progression model by providing convincing evidence for a velocity decrease from cis to trans Golgi and variable speeds within cisternae, suggesting a more stable compartmental nature. While these findings propose refinements to the classic model, they prompt further exploration of recent models like rapid partitioning and rim progression, necessitating additional experimental approaches to account for cargo expression variations and HeLa cell-specific effects.

Reviewer #2 (Public Review):

Summary:

This manuscript describes the use of quantitative imaging approaches, which have been a key element of the labs work over the past years, to address one of the major unresolved discussions in trafficking: intra-Golgi transport. The approach used has been clearly described in the labs previous papers, and is thus clearly described. The authors clearly address the weaknesses in this manuscript and do not overstate the conclusions drawn from the data. The only weakness not addressed is the concept of blocking COPI transport with BFA, which is a strong inhibitor and causes general disruption of the system. This is an interesting element of the paper, which I think could be improved upon by using more specific COPI inhibitors instead, although I understand that this is not necessarily straightforward.

I commend the authors on their clear and precise presentation of this body of work, incorporating mathematical modelling with a fundamental question in cell biology. In all, I think that this is a very robust body of work, that provides a sound conclusion in support of the stable compartment model for the Golgi.

General points:

The manuscript contains a lot of background in its results sections, and the authors may wish to consider rebalancing the text: The section beginning at Line 175 is about 90% background and 10% data. Could some data currently in supplementary be included here to redress this balance, or this part combined with another?

Reviewer #3 (Public Review):

The manuscript by Tie et al. provides a quantitative assessment of intra-Golgi transport of diverse cargos. Quantitative approaches using fluorescence microscopy of RUSH synchronized cargos, namely GLIM and measurement of Golgi residence time, previously developed by the author's team (publications from 20216 to 2022), are being used here.

Most of the results have been already published by the same team in 2016, 2017, 2020 and 2021. In this manuscript, very few new data have been added. The authors have put together measurements of intra-Golgi transport kinetics and Golgi residence time of many cargos. The quantitative results are supported by a large number of Golgi mini-stacks/cells analyzed. They are discussed with regard to the intra-Golgi transport models being debated in the field, namely the cisternal maturation/progression model and the stable compartments model. However, over the past decades, the cisternal progression model has been mostly accepted thanks to many experimental data.

The authors show that different cargos have distinct intra-Golgi transport kinetics and that the Golgi residence time of glycosyltransferases is high. From this and the experiment using brefeldinA, the authors suggest that the rim progression model, adapted from the stable compartments model, fits with their experimental data.

Strengths:

The major strength of this manuscript is to put together many quantitative results that the authors previously obtained and to discuss them to give food for thought about the intra-Golgi transport mechanism.<br /> The analysis by fluorescence microscopy of intra-Golgi transport is tough and is a tour de force of the authors even if their approach show limitations, which are clearly stated. Their work is remarkable in regards to the numbers of Golgi markers and secretory cargos which have been analyzed.

Weaknesses:

As previously mentioned, most of the data provided here were already published and thus accessible for the community. Is there is a need to publish them again?<br /> The authors' discussion about the intra-Golgi transport model is rather simplistic. In the introduction, there is no mention of the most recent models, namely the rapid partitioning and the rim progression models. To my opinion, the tubular connections between cisternae and the diffusion/biochemical properties of cargos are not enough taken into account to interpret the results. Indeed, tubular connections and biochemical properties of the cargos may affect their transit through the Golgi and the kinetics with which they reach the TGN for Golgi exit.<br /> Nocodazole is being used to form Golgi mini-stacks, which are necessary to allow intra-Golgi measurement. The use of nocodazole might affect cellular homeostasis but this is clearly stated by the authors and is acceptable as we need to perturb the system to conduct this analysis. However, the manual selection of the Golgi mini-stack being analyzed raises a major concern. As far as I understood, the authors select the mini-stacks where the cargo and the Golgi reference markers are clearly detectable and separated, which might introduce a bias in the analysis.<br /> The terms 'Golgi residence time ' is being used but it corresponds to the residence time in the trans-cisterna only as the cargo has been accumulated in the trans-Golgi thanks to a 20{degree sign}C block. The kinetics of disappearance of the protein of interest is then monitored after 20{degree sign}C to 37{degree sign}C switch.<br /> Another concern also lies in the differences that would be introduced by different expression levels of the cargo on the kinetics of their intra-Golgi transport and of their packaging into post-Golgi carriers.

eLife assessment

This study presents valuable findings on the ligand- and ion-dependent structural dynamics of a transcriptional riboswitch. The single-molecule data presented are solid and prompts intriguing hypotheses and models, which will undoubtedly stimulate future structural analyses. These findings are of considerable interest to biochemists and biophysicists engaged in the study of RNA structure and riboswitch mechanisms.

Reviewer #1 (Public Review):

Summary:

This work presents an in-depth characterization of the factors that influence the structural dynamics of the Clostridium botulinum guanidine-IV riboswitch (riboG). Using a single-molecule FRET, the authors demonstrate that riboG undergoes ligand and Mg2+ dependent conformational changes consistent with dynamic formation of a kissing loop (KL) in the aptamer domain. Formation of the KL is attenuated by Mg2+ and Gua+ ligand at physiological concentrations as well as the length of the RNA. Interestingly, the KL is most stable in the context of just the aptamer domain compared to longer RNAs capable of forming the terminator stem. To attenuate transcription, binding of Gua+ and formation of the KL must occur rapidly after transcription of the aptamer domain but before transcription of the rest of the terminator stem.

Strengths:

(1) Single molecule FRET microscopy is well suited to unveil the conformational dynamics of KL formation and the authors provide a wealth of data to examine the effect of the ligand and ions on riboswitch dynamics. The addition of complementary transcriptional readthrough assays provides further support the author's proposed model of how the riboswitch dynamics contribute to function.<br /> (2) The single-molecule data strongly support that the effect of Gua+ ligand and Mg2+ influence the RNA structure differently for varying lengths of the RNA. The authors also demonstrate that this is specific for Mg2+ as Na+ and K+ ions have little effect.<br /> (3) The PLOR method utilized is clever and well adapted for both dual labeling of RNAs and examining RNA at various lengths to mimic co-transcriptional folding. Using PLOR, they demonstrate that a change in the structural dynamics and ligand binding can occur after extension of the RNA transcript by a single nucleotide. Such a tight window of regulation has intriguing implications for kinetically controlled riboswitches.<br /> (4) In the revised version, the authors utilized multiple destabilizing and compensatory mutations to strengthen their structural interpretation of the KL structure and dynamics and cementing their conclusions.

Reviewer #2 (Public Review):

Summary:

Gao et al., used single-molecule FRET and step-wise transcription methods to study the conformations of the recently reported guanidine-IV class of bacterial riboswitches that upregulate transcription in the presence of elevated guanidine. Using three riboswitch lengths, the authors analyzed the distributions and transitions between different conformers in response to different Mg2+ and guanidine concentrations. These data led to a three-state kinetic model for the structural switching of this novel class of riboswitches whose structures remain unavailable. Using the PLOR method that the authors previously invented, they further examined the conformations, ligand responses, and gene-regulatory outcomes at discrete transcript lengths along the path of vectorial transcription. These analyses uncover that the riboswitch exhibits differential sensitivity to ligand-induced conformational switching at different steps of transcription, and identify a short window where the regulatory outcome is most sensitive to ligand binding.

Strengths:

Dual internal labeling of long RNA transcripts remains technically very challenging, but essential for smFRET analyses of RNA conformations. The authors should be commended for achieving very highly quality and purity in their labelled RNA samples. The data are extensive, robust, thorough, and meticulously controlled. The interpretations are logical and conservative. The writing is reasonably clear and illustrations are of high quality. The findings are significant because the paradigm uncovered here for this relatively simple riboswitch class is likely also employed in numerous other kinetically regulated riboswitches. The ability to quantitatively assess RNA conformations and ligand responses at multiple discrete points along the path towards the full transcript provides a rare and powerful glimpse into co-transcriptional RNA folding, ligand-binding, and conformational switching.

Weaknesses:

The use of T7 RNA polymerase instead of a near cognate bacterial RNA polymerase in the termination/antitermination assays is a significant caveat. It is understandable as T7 RNA polymerase is much more robust than its bacterial counterparts, which probably will not survive the extensive washes required by the PLOR method. The major conclusions should still hold, as the RNA conformations are probed by smFRET at static, halted complexes instead of on the fly. However, potential effects of the cognate RNA polymerase cannot be discerned here, including transcriptional rates, pausing, and interactions between the nascent transcript and the RNA exit channel, if any. The authors should refrain from discussing potential effects from the DNA template or the T7 RNA polymerase, as these elements are not cognate with the riboswitch under study.

Reviewer #3 (Public Review):

Summary:

In this article, Gao et. al. uses single-molecule FRET (smFRET) and position-specific labelling of RNA (PLOR) to dissect the folding and behavioral ligand sensing of the Guanidine-IV riboswitch in the presence and absence of the ligand guanidine and the cation Mg2+. Results provided valuable information on the mechanistic aspects of the riboswitch, including the confirmation on the kissing loop present in the structure as essential for folding and riboswitch activity. Co-transcriptional investigations of the system provided key information on the ligand-sensing behavior and ligand-binding window of the riboswitch. A plausible folding model of the Guanidine-IV riboswitch was proposed as a final result. The evidence presented here sheds additional light into the mode of action of transcriptional riboswitches.

Strengths:

The investigations were very thorough, providing data that supports the conclusions. The use of smFRET and PLOR to investigate RNA folding has been shown to be a valuable tool to the understand of folding and behavior properties of these structured RNA molecules. The co-transcriptional analysis brought important information on how the riboswitch works, including the ligand-sensing and the binding window that promotes the structural switch. The fact that investigations were done with the aptamer domain, aptamer domain + terminator/anti-terminator region, and the full length riboswitch were essential to inform how each domain contributes to the final structural state if in the presence of the ligand and Mg2+.

Weaknesses:

The system has its own flaws when comparing to physiological conditions. The RNA polymerase used (the study uses T7 RNA polymerase) is different from the bacterial RNA polymerase, not only on complexity, but also in transcriptional speed, that can direct interfere with folding and ligand-sensing. Additionally, rNTPs concentrations were much lower than physiological concentrations during transcription, likely causing a change in the polymerase transcriptional speed. These important aspects and how they could interfere with results are important to be addressed to the broad audience. Another point of consideration to be aware is that the bulky fluorophores attached to the nucleotides can interfere with folding to some extent.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

This work presents an in-depth characterization of the factors that influence the structural dynamics of the Clostridium botulinum guanidine-IV riboswitch (riboG). Using a single-molecule FRET, the authors demonstrate that riboG undergoes ligand and Mg2+ dependent conformational changes consistent with the dynamic formation of a kissing loop (KL) in the aptamer domain. Formation of the KL is attenuated by Mg2+ and Gua+ ligand at physiological concentrations as well as the length of the RNA. Interestingly, the KL is most stable in the context of just the aptamer domain compared to longer RNAs capable of forming the terminator stem. To attenuate transcription, binding of Gua+ and formation of the KL must occur rapidly after transcription of the aptamer domain but before transcription of the rest of the terminator stem.

Strengths:

(1) Single-molecule FRET microscopy is well suited to unveil the conformational dynamics of KL formation and the authors provide a wealth of data to examine the effect of the ligand and ions on riboswitch dynamics. The addition of complementary transcriptional readthrough assays provides further support for the author's proposed model of how the riboswitch dynamics contribute to function.

(2) The single-molecule data strongly support that the effect of Gua+ ligand and Mg2+ influence the RNA structure differently for varying lengths of the RNA. The authors also demonstrate that this is specific for Mg2+ as Na+ and K+ ions have little effect.

(3) The PLOR method utilized is clever and well adapted for both dual labeling of RNAs and examining RNA at various lengths to mimic co-transcriptional folding. Using PLOR, they demonstrate that a change in the structural dynamics and ligand binding can occur after the extension of the RNA transcript by a single nucleotide. Such a tight window of regulation has intriguing implications for kinetically controlled riboswitches.

Weaknesses:

(1) The authors use only one mutant to confirm that their FRET signal indicates the formation of the KL. Importantly, this mutation does not involve the nucleotides that are part of the KL interaction. It would be more convincing if the authors used mutations in both strands of the KL and performed compensatory mutations that restore base pairing. Experiments like this would solidify the structural interpretation of the work, particularly in the context of the full-length riboG RNA or in the cotranscriptional mimic experiments, which appear to have more conformational heterogeneity.

We thank the reviewer for describing our work “in-depth characterization” of riboG. We agree with the reviewer and we have added two more mutants, G71C and U72C with the mutations located at the KL (Figure 2– figure supplement 8A, 8B, 9A, 9B, Figure 3– figure supplement 6A, 6B, 7A, 7B, and Figure 4– figure supplement 6A, 6B, 7A, 7B). Furthermore, we have performed compensatory mutations, C30G-G71C and A29G-U72C that restore base pairing in the KL (Figure 2– figure supplement 8C, 8D, 9C, 9D, Figure 3– figure supplement 6C, 6D, 7C, 7D, and Figure 4– figure supplement 6C, 6D, 7C, 7D). We added the experimental results in the revised manuscript accordingly as “The highly conserved nucleotides surrounding the KL are crucial for its formation (Lenkeit et al., 2020). To test our hypothesis that the state with EFRET ~ 0.8 corresponds to the conformation with the KL, we preformed smFRET analysis on several mutations at these crucial nucleotides (Figure 2– figure supplement 8–10). Consistent with our expectations, the peaks with EFRET ~ 0.8 was significantly diminished in the riboG-G71C mutant, which features a single nucleotide mutation at site 71 (with 97% nucleotide conservation) in the KL (Figure 2– figure supplement 8A and 8B). It is worth noting that the C30G and G71C mutant, which were initially expected to restore a base pair in the KL, did not successfully bring about the anticipated peak of EFRET ~ 0.8 (Figure 2– figure supplement 8C and 8D). On the other hand, the riboG-U72C mutant exhibited a lower proportion at the state with EFRET ~ 0.8 than riboG-apt. However, the A29G and U72C mutations restored a base pair in the KL, as well as the formation of the KL (Figure 2– figure supplement 9). Furthermore, our investigation revealed that the G77C mutant, involving a single nucleotide mutation at a highly conversed site, 77 (with 97% nucleotide conservation), also hindered the formation of the KL (Figure 2– figure supplement 10). This finding aligns with previous research (Lenkeit et al., 2020) and the predicted second structure of G77C mutation by Mfold (Zuker, 2003)”  ( page 7), “In contrast to riboG-term, both its G71C and C30G-G71C mutants displayed a reduced proportion of the state with EFRET ~ 0.8. Remarkably, the fractions of EFRET ~ 0.8 remained unaffected by the addition of 1.0 mM Gua+ in these mutants. Distinct from riboG-term, no structural transitions between states were observed in the two mutants (Figure 3– figure supplement 6). Regarding the U72C mutant of riboG-term, the mutation at the site 72 had a reduced impact on the KL conformation in the presence of 1.0 mM Gua+ and 2.0 mM Mg2+. However, the increased proportion of EFRET ~ 0.8 in the A29G-U72C mutant of riboG-term suggests that these mutations can restore the base-pairing between sites 29 and 72, as well as facilitate the formation of the KL (Figure 3– figure supplement 7)” ( page 8), and “Upon comparing the G71C and C30G-G71C mutants of the full-length riboG with their wild-type counterpart, it was observed that the wild-type adopted higher proportions of the state with EFRET ~ 0.8 (Figure 4– figure supplement 6). Regarding the U72C and A29G-U72C mutants of the full-length riboG, their behaviors with regards to the peak with EFRET ~ 0.8 were similar to that of their counterparts in riboG-term (Figure 4– figure supplement 7)” ( page 9).

(2) The existence of the pre-folded state (intermediate FRET ~0.5) is not well supported in their data and could be explained by an acquisition artifact. The dwell times are very short often only a single frame indicating that there could be a very fast transition (< 0.1s) from low to high FRET that averages to a FRET efficiency of 0.5. To firmly demonstrate that this intermediate FRET state is metastable and not an artifact, the authors need to perform measurements with a faster frame rate and demonstrate that the state is still present.

We thank the reviewer for the great comment. We added smFRET experiments at higher time resolution, 20 ms, as well as lower time resolution (Figure 2– figure supplement 3).  Based on our experimental results, the intermediate state (EFRET ~0.5) exists at the smFRET collected at 20 ms, 100 ms and 200 ms. 

(3) The PLOR method employs a non-biologically relevant polymerase (T7 RNAP) to mimic transcription elongation and folding near the elongation complex. T7 RNAP has a shorter exit channel than bacterial RNAPs and therefore, folding in the exit channel may be different between different RNAPs. Additionally, the nascent RNA may interact with bacterial RNAP differently. For these reasons, it is not clear how well the dynamics observed in the T7 ECs recapitulate riboswitch folding dynamics in bacterial ECs where they would occur in nature. 

We thank the reviewer for the comment. We agree with the reviewer that the bacterial and T7 RNAPs may behave differently due to their differences in transcriptional speed, dynamics, interactions, and so on. And we added a statement in the Discussion as “It is worth noting that the RNAP utilized in our study is T7 RNAP, which exhibits distinct characteristics compared to bacterial RNAP in terms of transcriptional speed, dynamics, and interactions. However, Xue et al. have reported similarities between T7 and E. coli RNAP in the folding of nascent RNA. Additionally, Lou and Woodson have provided valuable insights into the co-transcriptional folding of the glmS ribozyme using T7 RNAP (Xue et al., 2023; Lou & Woodson, 2024)” ( page 13–14).

Reviewer #2 (Public Review):

Summary:

Gao et al. used single-molecule FRET and step-wise transcription methods to study the conformations of the recently reported guanidine-IV class of bacterial riboswitches that upregulate transcription in the presence of elevated guanidine. Using three riboswitch lengths, the authors analyzed the distributions and transitions between different conformers in response to different Mg2+ and guanidine concentrations. These data led to a three-state kinetic model for the structural switching of this novel class of riboswitches whose structures remain unavailable. Using the PLOR method that the authors previously invented, they further examined the conformations, ligand responses, and gene-regulatory outcomes at discrete transcript lengths along the path of vectorial transcription. These analyses uncover that the riboswitch exhibits differential sensitivity to ligand-induced conformational switching at different steps of transcription, and identify a short window where the regulatory outcome is most sensitive to ligand binding.

Strengths:

Dual internal labeling of long RNA transcripts remains technically very challenging but essential for smFRET analyses of RNA conformations. The authors should be commended for achieving very high quality and purity in their labelled RNA samples. The data are extensive, robust, thorough, and meticulously controlled. The interpretations are logical and conservative. The writing is reasonably clear and the illustrations are of high quality. The findings are significant because the paradigm uncovered here for this relatively simple riboswitch class is likely also employed in numerous other kinetically regulated riboswitches. The ability to quantitatively assess RNA conformations and ligand responses at multiple discrete points along the path towards the full transcript provides a rare and powerful glimpse into cotranscriptional RNA folding, ligand-binding, and conformational switching.

Weaknesses:

The use of T7 RNA polymerase instead of a near-cognate bacterial RNA polymerase in the termination/antitermination assays is a significant caveat. It is understandable as T7 RNA polymerase is much more robust than its bacterial counterparts, which probably will not survive the extensive washes required by the PLOR method. The major conclusions should still hold, as the RNA conformations are probed by smFRET at static, halted complexes instead of on the fly. However, potential effects of the cognate RNA polymerase cannot be discerned here, including transcriptional rates, pausing, and interactions between the nascent transcript and the RNA exit channel, if any. The authors should refrain from discussing potential effects from the DNA template or the T7 RNA polymerase, as these elements are not cognate with the riboswitch under study.

We thank the reviewer for describing our work “The data are extensive, robust, thorough, and meticulously controlled. The interpretations are logical and conservative. The writing is reasonably clear and the illustrations are of high quality”. We agree with the reviewer that the bacterial and T7 RNAPs may behave differently due to their differences in transcriptional speed, dynamics, interactions, and so on. And we added a statement in the Discussion as “It is worth noting that the RNAP utilized in our study is T7 RNAP, which exhibits distinct characteristics compared to bacterial RNAP in terms of transcriptional speed, dynamics, and interactions. However, Xue et al. have reported similarities between T7 and E. coli RNAP in the folding of nascent RNA. Additionally, Lou and Woodson have provided valuable insights into the co-transcriptional folding of the glmS ribozyme using T7 RNAP (Xue et al., 2023; Lou & Woodson, 2024)” ( page 14).

Reviewer #3 (Public Review):

Summary:

In this article, Gao et. al. uses single-molecule FRET (smFRET) and position-specific labelling of RNA (PLOR) to dissect the folding and behavioral ligand sensing of the Guanidine-IV riboswitch in the presence and absence of the ligand guanidine and the cation Mg2+. The results provided valuable information on the mechanistic aspects of the riboswitch, including the confirmation of the kissing loop present in the structure as essential for folding and riboswitch activity. Co-transcriptional investigations of the system provided key information on the ligand-sensing behavior and ligandbinding window of the riboswitch. A plausible folding model of the Guanidine-IV riboswitch was proposed as a final result. The evidence presented here sheds additional light on the mode of action of transcriptional riboswitches.

Strengths:

The investigations were very thorough, providing data that supports the conclusions. The use of smFRET and PLOR to investigate RNA folding has been shown to be a valuable tool for the understanding of folding and behavior properties of these structured RNA molecules. The co-transcriptional analysis brought important information on how the riboswitch works, including the ligand-sensing and the binding window that promotes the structural switch. The fact that investigations were done with the aptamer domain, aptamer domain + terminator/anti-terminator region, and the full-length riboswitch were essential to inform how each domain contributes to the final structural state if in the presence of the ligand and Mg2+.

Weaknesses:

The system has its own flaws when compared to physiological conditions. The RNA polymerase used (the study uses T7 RNA polymerase) is different from the bacterial RNA polymerase, not only in complexity, but also in transcriptional speed, which can directly interfere with folding and ligand-sensing. Additionally, rNTPs concentrations were much lower than physiological concentrations during transcription, likely causing a change in the polymerase transcriptional speed. These important aspects and how they could interfere with results are important to be addressed to the broad audience. Another point of consideration to be aware of is that the bulky fluorophores attached to the nucleotides can interfere with folding to some extent.

We thank the reviewer for describing our work as “The investigations were very thorough, providing data that supports the conclusions”. We agree with the reviewer that the bacterial and T7 RNAPs may behave differently due to their differences in transcriptional speed, dynamics, interactions, and so on. And we added a statement in the Discussion as “It is worth noting that the RNAP utilized in our study is T7 RNAP, which exhibits distinct characteristics compared to bacterial RNAP in terms of transcriptional speed, dynamics, and interactions. However, Xue et al. have reported similarities between T7 and E. coli RNAP in the folding of nascent RNA. Additionally, Lou and Woodson have provided valuable insights into the cotranscriptional folding of the glmS ribozyme using T7 RNAP (Xue et al., 2023; Lou & Woodson, 2024)” ( page 14). And we also agree with the reviewer that the lower NTP may affect the transcriptional speed. Regarding the fluorophores, we purposely placed them away from the KL to avoid their influence on the formation of the KL.

Reviewer #1 (Recommendations For The Authors):

Related to weakness 1

- The authors cite a paper that investigated mutations in the KL duplex but do not include these mutations in their analysis. It is unclear why the authors chose the G77C mutation and not the other mutants previously tested. Can the authors explain their choice of mutation in detail in the text? I also did not see the proposed secondary structure for the G77C mutant shown in Figure 2 -supp 3A in the cited paper, is this a predicted structure? Please explain how this structure was determined. 

We thank the reviewer for the comment. The reason we chosen the G77C mutation is based on previous report that G77C can disturb the formation of the KL, as we stated in the manuscript as “Furthermore, our investigation revealed that the G77C mutant, involving a single nucleotide mutation at a highly conversed site, 77 (with 97% nucleotide conservation), also hindered the formation of the KL (Figure 2– figure supplement 10). This finding aligns with previous research (Lenkeit et al., 2020) and the predicted second structure of G77C mutation by Mfold (Zuker, 2003)” ( page 7). And the secondary structure for the G77C mutant was predicted by Mfold, which as cited in the manuscript and added in the reference list as “Zuker, M. (2003). Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Research, 31(13), 3406-3415”. 

- It is not clear to me that the structural interpretation of their FRET states is correct and that the FRET signal reports on the base pairing of the KL in only the high FRET state. The authors should perform experiments with additional mutations in the KL duplex to confirm that their construct reports on KL duplex formation alone and not other structural dynamics. 

We thank the reviewer for the comment. We have included additional mutations to establish a connection between the high-FRET state to the formation of the KL. The results have been added to the manuscript as “The highly conserved nucleotides surrounding the KL are crucial for its formation (Lenkeit et al., 2020). To test our hypothesis that the state with EFRET ~ 0.8 corresponds to the conformation with the KL, we preformed smFRET analysis on several mutations at these crucial nucleotides (Figure 2– figure supplement 8–10). Consistent with our expectations, the peaks with EFRET ~ 0.8 was significantly diminished in the riboG-G71C mutant, which features a single nucleotide mutation at site 71 (with 97% nucleotide conservation) in the KL (Figure 2– figure supplement 8A and 8B). It is worth noting that the C30G and G71C mutant, which were initially expected to restore a base pair in the KL, did not successfully bring about the anticipated peak of EFRET ~ 0.8 (Figure 2– figure supplement 8C and 8D). On the other hand, the riboG-U72C mutant exhibited a lower proportion at the state with EFRET ~ 0.8 than riboG-apt. However, the A29G and U72C mutations restored a base pair in the KL, as well as the formation of the KL (Figure 2– figure supplement 9). Furthermore, our investigation revealed that the G77C mutant, involving a single nucleotide mutation at a highly conversed site, 77 (with 97% nucleotide conservation), also hindered the formation of the KL (Figure 2– figure supplement 10). This finding aligns with previous research (Lenkeit et al., 2020) and the predicted second structure of G77C mutation by Mfold (Zuker, 2003)”  ( page 7), “In contrast to riboG-term, both its G71C and C30G-G71C mutants displayed a reduced proportion of the state with EFRET ~ 0.8. Remarkably, the fractions of EFRET ~ 0.8 remained unaffected by the addition of 1.0 mM Gua+ in these mutants. Distinct from riboG-term, no structural transitions between states were observed in the two mutants (Figure 3– figure supplement 6). Regarding the U72C mutant of riboG-term, the mutation at the site 72 had a reduced impact on the KL conformation in the presence of 1.0 mM Gua+ and 2.0 mM Mg2+. However, the increased proportion of EFRET ~ 0.8 in the A29G-U72C mutant of riboG-term suggests that these mutations can restore the base-pairing between sites 29 and 72, as well as facilitate the formation of the KL (Figure 3– figure supplement 7)” ( page 8), and “Upon comparing the G71C and C30G-G71C mutants of the full-length riboG with their wild-type counterpart, it was observed that the wild-type adopted higher proportions of the state with EFRET ~ 0.8 (Figure 4– figure supplement 6). Regarding the U72C and A29G-U72C mutants of the full-length riboG, their behaviors with regards to the peak with EFRET ~ 0.8 were similar to that of their counterparts in riboG-term (Figure 4– figure supplement 7)” ( page 9).  

- For the full-length riboG-136 (Cy3Cy5 riboG in Figure 4), the authors have clearly defined peaks at 0.6 and 0.4. However, the authors do not explain their structural interpretation of these states. Do the authors believe that the KL is forming in these states? It would be helpful to have data on mutations in the KL in the context of the full-length riboG to better understand the structural transitions of these intermediate states. 

Based on our mutation studies, we proposed that the peak with EFRET ~0.8 corresponds to the conformation with the KL, while the states with EFRET ~0.4 and 0.6 are the states without a stable KL. 

Related to weakness 2:

- For the riboG-apt and riboG-term RNAs, the proposed intermediate FRET state (EFRET = 0.5) is poorly fit by a Gaussian and the dwell times in the state are almost entirely single-frame dwells. It is likely that this state is the result of a camera blurring artifact, in which RNAs undergo a FRET transition between two frames giving an apparent FRET efficiency which is between that of the two transitioning states. This artifact arises when the average dwell times of the true states (Elow and Ehigh) are comparable to the frame duration (within a factor of ~5-10; see https://doi.org/10.1021/acs.jpcb.1c01036). To confirm the presence of the intermediate state, the authors should perform at least a few experiments with higher time resolution to support the existence of the 0.5 state with a lifetime of 0.1 s. Alternatively, the data should be refit to a two-state HMM and the authors could explain in the text that the density in the FRET histogram between the two states is likely due to transitions that are faster than the time resolution of the experiment. 

We thank the reviewer for the great comment. Taking the suggestion into consideration, we performed smFRET experiments with a higher time resolution of 20 ms. As a result, we still detected the intermediate state, supporting that it is not an artifact. The new data has been included in the revised manuscript (Figure 2-figure supplement 3).  

Related to weakness 3:

- The authors depict the polymerase footprint differently in some of the figures and it is unclear if this is part of their model. Is the cartoon RNAP supposed to indicate the RNA:DNA hybrid or the footprint of T7 RNAP on the RNA? For example, in Figure 8a there are 8 nts (left) and 9 nts (right) covered by RNAP, and only 6nts in Figure 6 - supp 2A. This is particularly misleading for the EC-87 and EC-88 in Figure 6 - supp 2, where it is likely that this stem is not formed at all and the KL strand is single-stranded. The authors should clarify and at least indicate in the figure legend if the RNAP cartoon is part of the model or only a representation. 

We thank the reviewer for bringing the issues to our attention. Due to space limitations, we chose to represent the polymerase footprint differently in Figure 8. However, we have included the statement “DNA templates from EC-87 to EC-105 are not displayed in the model” in the legend of Figure 8 to avoid the confusion.

Moreover, we have corrected the error of 6 nts Figure 6-supplement figure 2.  

- With a correct 9 bp RNA:DNA hybrid, the EC-88 construct would not be able to form the top part of the P2 stem and the second half of the KL RNA would be single-stranded. In this case, an interaction between the KL nucleotides would resemble a pseudoknot and not a kissing loop interaction. Can the authors explain if this could explain the heterogeneity they observe in the EC-88 construct compared to the riboGapt  RNA?

Thank the reviewer for the comment. We have added the statement in the revised manuscript as “The T7 RNA polymerase (RNAP) sequestered about 8 nt of the nascent RNA, preventing the EC-88 construct from forming the P2 stem (Durniak et al., 2008; Huang & Sousa, 2000; Lubkowska et al., 2011; Tahirov et al., 2002; Wang et al., 2022; Yin & Steitz, 2002). Consequently, a pseudoknot structure potentially formed instead of the expected KL. This distinction may account for the observed heterogeneity between EC-88 and riboG-apt” ( page 11).

Other comments:

(1) It appears that the FRET histograms in the PLOR experiments (Figure 6 and related figures) only show the fits presumably to highlight the overlays. However, this makes it impossible to determine the goodness of the fit. The authors should instead show the outline of the raw histogram with the fit, or at least show the raw histograms with fits in the supplement. 

We have replaced Figure 6- figure supplements 2-4 to enhance the clarity of the raw and fitted smFRET histograms.  

(2) The authors should consider including a concluding paragraph to put the results into a larger context. How does the kinetic window compare to other transcriptional riboswitches? Would the authors comment on how the transcription speed compares to the kinetics for the formation of the KL? 

We thank the reviewer for the comment. We have added the comparison of riboG to other transcription riboswitches to the manuscript as “Nevertheless, the ligand-sensitive windows of riboswitches during transcription vary. In a study conducted by Helmling et al. using NMR spectroscopy, they proposed a broad transcriptional window for deoxyguanosine-sensing riboswitches, whereby the ligand binding capability gradually diminishes over several nucleotide lengths (Helmling et al., 2017). However, more recent research by Binas et al. and Landgraf et al. on riboswitches sensing ZMP, c-di-GMP, and c-GAMP revealed a narrow window with a sharp transition in binding capability, even with transcript lengths differing by only one or three nucleotides (Binas et al., 2020; Landgraf et al., 2022). In line with the findings for the c-GAMP-sensing riboswitch, our study on the guanidine-IV riboswitch also demonstrated a sharp transition in binding capability with just a single nucleotide extension” ( page 14). 

We appreciate the reviewer’s comment in comparing the transcription speed to the kinetics of the KL formation. However, we must acknowledge that we have limited kinetic data in this study to confidently make such a comparison.

(3) Cy3Cy5 RiboG is a confusing name because it implies that the others are not also Cy3Cy5 labeled. The authors should consider changing the names and being consistent throughout. I suggest full-length riboG or riboG-136. 

We have changed “Cy3Cy5 riboG” to “Cy3Cy5-full-length riboG” (pages 15 and 16).

(4) The transcriptional readthrough experiment should be explained when first mentioned in line 109. 

We have added the citation (Chien et al., 2023) of the transcriptional readthrough experiment to the manuscript as “we noted that the transcriptional read-through of the guanidine-IV riboswitch during the single-round PLOR reaction was sensitive to Gua+, exhibiting an apparent EC50 value of 68.7  7.3 μM (Figure 1D) (Chien et al., 2023)” (page 5). 

(5) Kd values in text should have uncertainties, and the way these uncertainties are obtained should be explained.

We have added the uncertainties of Kd values in the revised manuscript ( page 6) and the legend of Figure 2-supplement 6 as “The percentages of the folded state (EFRET ~ 0.8) of Cy3Cy5-riboG-apt were plotted with the concentrations of Gua+ at 0.5 mM Mg2+, with an apparent Kd of 286.0  18.1 μM in three independent experiments”.

(6) The authors mention "strategies" on line 306, but it is unclear what they are referring to. Are the strategies referring to the constructs (EC-87, etc) or Steps 1-8 in the supplemental figure? Please clarify. 

We have clarified the confusion by adding “The detailed procedures of strategies 1-8 were shown in Figure 7–figure supplement 1” to the manuscript ( page 12).

(7) What are the fraction of dynamic traces versus static traces in the cases for the full-length riboG? This would help depict the structural heterogeneity in the population. 

We have added the fractions of dynamic single-molecule traces of the full-length riboG to Figure 4-supplements 1-5. 

(8) The labels in Figure 4 (A-E) don't match the caption (A-H). 

We have corrected the error. 

(9) The coloring of the RNA strands in Figure 4A should be explained in the figure legend. It could be interpreted as multiple strands annealed instead of a continuous strand. 

We have revised the legend of Figure 4A by adding “The full-length riboG contains the aptamer domain (black), terminator (red) and the extended sequence (blue). Cy3 and Cy5 are shown by green and red sparkles, respectively”.

(10) Reported quantities and uncertainties should have the same number of decimal places. In many places, the uncertainties likely have too many significant figures, for example, in Figure 5 and related figures. 

We have corrected the significant figures of the uncertainties. 

(11) In Figure 5, A and B should have the same vertical scale to facilitate comparison. 

We have adjusted Figure 5A to match the vertical scale of Figure 5B in the revised manuscript.

(12) In Figure 5C-D, the construct from which those trajectories come should be indicated in the legend. 

We have added the construct to the legend of Figures 5C and D.  

(13) In Figure 6J, the splines between data points are confusing and can be misleading. They suggest that the data has been fit to a model, but I am not sure if it represents a model. The data points should be colored instead and lines removed. 

We thank the reviewer for the comment. We have changed Figure 6J by coloring the data points and removing the lines to avoid confusion. 

(14) Line 330 mentions a P2 structure in Figure 8, but there is no such label in Figure. Please clarify. 

We thank the reviewer for the comment and have added P2 to Figure 8. 

Reviewer #2 (Recommendations For The Authors):

(1) Figure 1B. The authors don't seem to address the role of the blue stem-loop following Stems 1 and 2. Is this element needed at all for gene regulation? Does it impact the conformations or folding of the preceding Stems 1 and 2? It seems feasible to disrupt the stem and see whether there is an impact on riboswitch function. 

We thank the reviewer for the comment. The presence of the sequence which formed blue stem-loop indicates the formation of an anti-terminator conformation in riboG during transcription. Our smFRET data shows that the inclusion of the stem-loop sequence induces additional peaks in the full-length riboG compared to the riboGterm. This indicates that the stem-loop influences the folding of the kissing loop (KL) and potentially also affects the stems 1 and 2.  

(2) Figure 7 supplement 1, C &D. Maybe I am missing something, but it seems to me in reaction #8 (EC-105, last two lanes), the readthrough percentage is close to 50% based on the gel but plotted in D as 20%. Further, there is a strong effect of guanidine in reaction #8 but that is not reflected in the quantitation in panel D. 

We thank the reviewer for the comment. The observed discrepancy between reaction 8 in (C) and (D) is from the differential handling of the crude product at the last step (step 17) in gel loading for (C), contrasted with the combination of crude products from steps 16 and 17 to calculate the read-through percentage in (D). We have corrected the discrepancy by replacing Figure 7-Supplement figure 1C (now Figure 7C), and revised the legend to include the following clarification: “Taking into consideration that the 17 step-PLOR reaction exhibited a pause within the terminator region, resulting in a significant amount of terminated product at step 16, crude products from steps 16 and 17 were collected for (C) and (D) of the 17 step-PLOR reaction (Lanes 15 and 16 in C)”.

(3) Figure 7C is a control that shows the quality of the elongation complexes, which probably should be in the supplement. Instead, in Figure 7 supplement 1, panels C and D are actual experiments and could be moved into the main figure.  

We thank the reviewer for the comment. We made the adjustment.  

(4) Figure S7D. I would suggest not labelling the RNA polymerase halt/stoppage sites due to NTP deprivation as "pausing sites" because transcriptional pausing has previously been defined as natural sites where the RNA polymerase transiently halts itself, but not due to the lack of the next NTPs. In this case, the elongating complexes were artificially halted, which is technically not "pausing", as it will not restart/resume on its own without intervention. 

We have changed the “pausing” to “halting”.  

(5) Figure 7 is titled "In vitro transcriptional performance of riboG." But the data is actually not about the performance of the riboswitch, or how well it functions. I would suggest the authors revise the title. This is mostly about the observed sensitivity window of the riboswitch to ligand-mediated conformational switching. 

We have changed the title of Figure 7 to “Ligand-mediated conformational switching of riboG during transcription”.

(6) Figure 7A, the illustration gives the visual impression that there are multiple RNA polymerases on the same DNA template, which is not the case. 

We have revised Figure 7A by adding arrows between RNA polymerases to illustrate the movement of a single RNAP, rather than multiple RNAP on the same template.

(7) It could be informative to compare the guanidine-IV riboswitch with the first three classes (I, II, III), to see how their architectures or gene regulatory mechanisms are similar or different. 

We thank the reviewer for the comment. We have added the comparison of the guanidine-IV riboswitch to other three guanidine riboswitches to the manuscript as “The guanidine-IV riboswitch exhibits similarities to the guanidine-I riboswitch in gene regulatory mechanism, functioning as a transcriptional riboswitch. Structurally, it resembles the guanidine-II riboswitch through the formation of loop-loop interactions upon binding to guanidine (Battaglia & Ke, 2018; L. Huang et al., 2017; Lin Huang et al., 2017; Lenkeit et al., 2020; Nelson et al., 2017; Reiss & Strobel, 2017; Salvail et al., 2020)” ( page 12).  

Reviewer #3 (Recommendations For The Authors):

In addition to the public review items, I provide the following recommendations:

(1) As a second language speaker, I understand that writing a compelling and concise story may be hard, and we tend to write more than needed or more repetitively. That being said, I do think that the writing could be improved to make it more concise, clear, and avoid repetitions.

We thank the reviewer for the comment. We re-wrote the abstract and some sentences in the manuscript.

(2) In the abstract, instead of saying that "...This lack of understanding has impeded the application of this riboswitch", which makes the statement too strong, perhaps, stating something along the lines of "this understanding would assist the application of this riboswitch", would be a better fit. 

We have re-wrote the abstract, and revised the sentence.  

(3) Methods should state which RNA polymerase was used. PLOR uses T7 RNA pol, so I assume it was the same. 

We have added the statement “T7 RNAP was utilized in the PLOR and in vitro transcription reactions except noted” in the Methods ( page 15). 

(4) The impact statement says comprehensive structure-function, where perhaps comprehensive folding-function would be more appropriate. We are still missing a lot of structural information about this particular riboswitch. 

We agree with the reviewer, and changed “comprehensive structure-function” to “folding-function” in Impact statement ( page 2).

(5) Higher Mg2+ concentrations implicated in a lesser extent of the switch of RiboGapt, a sentence talking about it would be useful (how Mg2+ could have promiscuous interaction and interfere with folding). 

We have added the role of higher Mg2+ to the manuscript as “However, at a higher concentration of 50.0 mM Mg2+, the proportion of the pre-folded and unfolded conformations were more prevalent at 50.0 mM Mg2+ than at 20.0 mM Mg2+. This suggests that an excess of Mg2+ may promote the pre-folded and even unfolded conformations” ( page 6).

(6) In the investigations of RiboG-term and RiboG, seems like that monovalents from the buffer are sufficient to promote secondary structure. A statement commenting on this would benefit the paper and the audience. 

We agree with the reviewer and have accordingly revised the manuscript accordingly by adding “This indicates that monovalent ions in the buffer can facilitate the formation of stable guanidine-IV riboswitch” ( page 8).

(7) Figure 3. Figure goes to panel E and legend to panel H. G and H colors do not correspond to actual figure colors. 

We made the correction.  

(8) Figure 4. The same as Figure 3, the panels and figures are divergent.  

We made the correction.  

(9) During the discussion, stating that the DNA and RNA pol play a role in folding and ligand binding may be excessive. This could be an indirect effect of the transcriptional bubble hindering part of the nascent RNA from folding, which is something intrinsic to any transcription and not specific to this system. 

We agree with the reviewer and deleted the statement about the DNA and RNAP play a role in folding and ligand binding.

(10) PLOR is not properly cited. When introduced in the manuscript, please cite the original PLOR paper (Liu et. al. Nature 2015) and additional related papers. 

We cited the original PLOR paper (Liu et al, Nature 2015) and the related papers (Liu et al, Nature Protocols 2018). ( pages 4 and 15)

(11) The kinetics race of folding and binding could be a little more emphasized in discussion, particularly from the perspective of its physiological importance. 

We agree with the reviewer and deleted the kinetics race of folding and binding from the Discussion part.

Add note (maybe in a callout box to make it stand out):

"Local setup is not recommended on macOS or Windows as the Docker container will work via a Virtual Machine and building R will take far longer (e.g. a full build may take 1 hour vs 10 minutes!)."

Love and Will (1969) is a book by American existential psychologist Rollo May,

The book explores how the modern loss of older values, whose structures and stories provided society with explanations of the mysteries of life, forces contemporary humanity to choose between finding meaning within themselves or deciding that neither oneself, nor life, has meaning.

https://www.pdfdrive.com/may-rollo-love-and-will-norton-1969-e200354050.html

Eros: Erotic, Passionate Love We might as well get that one out of the way first. Eros is erotic or sexual or passionate love. It's often all about need and it's more about the person who's feeling sexually attractive than it is about the person who is the focus of that love or thing that is the focus of that love. It is addicting. It can cause great joy and great sorrow. It isn't always good for you. More hearts are broken on Valentine's Day due to the unfulfillment of erotic love.

Philia: Love of Friends and Equals It can be the love between lovers when they've been together for a long time and are not so hot and bothered anymore. It's also called brotherly love as in the city of Philadelphia. The city of brotherly love. Of course, it could be sisterly love and it is the accepting love of good friendship. This is the love that is good for your health. The touch of a loved one. The philia touch lowers blood pressure. People in loving relationships feel your love have few doctor visits, shorter hospital visits, have less pain, and have more positive emotions. All of these positive consequences of philia love, loving friendships make us more resilient when hard times come.

Storge: Love of Parents for Children This kind of love is what mothers know best but isn't talked about too much when we talk about love. It is the love of parents for children. It is described as the most natural of loves. Natural in that it's present without corrosion. It's emoted because we can't help ourselves and it pays the least attention as to whether the person is worthy of love.

It's often transient behaviors that wouldn't be tolerated in philia love. For example, women can continue to love their children despite truly awful behaviors. Behaviors they wouldn't tolerate in their girlfriends or their spouses. It seems to come unbidden in the care of a newborn and it grows to allow us to love our children despite their behaviors. Thank goodness for that. In many ways it's probably a genetically programmed and hard wired love compared to the affectionate love, philia, which is maybe not so hot wired.

Agape: Love of Mankind The love modeled on the love of the Christian God for men and the love of man for God. It's the love that is given whether or not it's returned. It's the love without any self benefit. In the Buddhist tradition it is the central foundation of loving kindness for all mankind. This kind of love is important in the process of forgiveness. Forgiveness is important to your health, because the inability to forgive is associated with anger and a number of health outcomes that are not very good. It is love that sets a very hard bar but it may be at the foundation for happiness and contentment.

Reference:

Healthcare.utah.edu. (2023, February 10). The Four Types of Love: Some Are Healthy, Some Are Not. Retrieved from https://healthcare.utah.edu/the-scope/health-library/all/2020/02/four-types-of-love-some-are-healthy-some-are-not

830 in VOLUMETRIC/Overall

Résumé de la vidéo [00:00:00][^1^][1] - [00:08:28][^2^][2] :

Cette vidéo présente une méthode pour résoudre tout problème, basée sur le livre "How to Solve It" de George Pólya. Elle explique l'importance de comprendre le problème, de trouver des liens entre les données et l'inconnu, d'élaborer un plan de solution, d'exécuter ce plan et d'examiner la solution obtenue.

Points forts : + [00:00:00][^3^][3] Introduction à la résolution de problèmes * Présentation du livre de George Pólya * Importance de comprendre le problème avant de le résoudre + [00:01:50][^4^][4] Établir des connexions * Trouver des liens entre les données et l'inconnu * Considérer des problèmes auxiliaires si nécessaire + [00:03:20][^5^][5] Exécution du plan * Différence entre planification et action * Importance de prendre des décisions et d'agir + [00:04:08][^6^][6] Examen de la solution * Vérifier la solution et l'argumentation * L'importance de l'examen dans les mathématiques et dans la vie réelle

Brief Biography of .Søren Kierkegaard (1813-185

https://plato.stanford.edu/entries/nietzsche/

Existentialism is a philosophical idea that existence precedes essence, which means that above the labels, roles, or stereotypes that one may be given, we are first and foremost independently acting conscious beings. Quoting Jean-Paul Sartre from “Existentialism is a Humanism”, his famous essay defending existentialism

Sartre J.-P. World Publishing Company; 1946. Existentialism is a Humanism. [Google Scholar] [

Brief Biography of .Søren Kierkegaard (1813-185

https://plato.stanford.edu/entries/kierkegaard/

https://youtu.be/3-VxIk0YHKk?si=gPVr9PB_J8n7WtGm

check general statistics, where it says 600

abcdef

move p, before emplacement

loci actually include squares, see MZA volumetry

https://web.archive.org/web/20240531083407/https://www.euronews.com/green/2024/02/06/this-disused-mine-in-finland-is-being-turned-into-a-gravity-battery-to-store-renewable-ene publ #2024/02/06 A deep mineshaft to be used in Finland for gravity-storage of green energy. The mine is 1400m deep and a 530m shaft would be used. 2MW means about 1 windmill's capacity in storage. I think the deepest Dutch mine was 1100m (Hendrik mijn, Heerlen), but don't know about shaft length, and if that still exists.

Por no haberse reaccionado, por lo menos en con asentir su cabeza, pues parece que él ya intuía que su veredicto iba a resultar así. Culpable.

El la fecha que van a decir cual es la sentencia de Trump ("dictar la sentencia")

A little bit before..a poco más de....X tiempo. A poco más de 7 años (un ejemplo)

Résumé de la vidéo [00:00:00][^1^][1] - [00:23:42][^2^][2]:

Cette vidéo présente une conférence de Stéphanie Mazza sur l'importance du sommeil pour les apprentissages. Elle explore les études sur le lien entre le sommeil et l'apprentissage, l'évolution des habitudes de sommeil, et comment le sommeil influence le développement cognitif et la consolidation de la mémoire.

Points forts: + [00:00:22][^3^][3] L'importance du sommeil pour l'apprentissage * Le sommeil est crucial pour organiser et consolider les connaissances * Les recommandations de durée de sommeil varient selon l'âge * L'impact du manque de sommeil sur la santé physique et mentale + [00:02:03][^4^][4] La diminution du temps de sommeil * Une tendance à la baisse du temps de sommeil au fil des ans * Les enfants et adolescents sont les plus touchés par cette réduction * Les conséquences sur les performances académiques et cognitives + [00:03:44][^5^][5] Le sommeil et le développement cognitif * Les trajectoires de sommeil affectent le comportement et l'apprentissage * Les corrélations entre la qualité du sommeil et les compétences linguistiques * L'importance du sommeil profond pour la maturation cérébrale + [00:10:52][^6^][6] La consolidation de la mémoire pendant le sommeil * Le sommeil joue un rôle actif dans la stabilisation des apprentissages * Les processus de réactivation nocturne renforcent la mémoire * La sieste peut également être bénéfique pour la consolidation Résumé de la vidéo [00:00:00][^1^][1] - [00:23:42][^2^][2]:

Cette vidéo présente une conférence de Stéphanie Mazza sur l'importance du sommeil pour les apprentissages. Elle explore les études sur le lien entre le sommeil et l'apprentissage, l'évolution des habitudes de sommeil, et comment le sommeil influence le développement cognitif et la consolidation de la mémoire.

Points forts: + [00:00:22][^3^][3] L'importance du sommeil pour l'apprentissage * Le sommeil est crucial pour organiser et consolider les connaissances * Les recommandations de durée de sommeil varient selon l'âge * L'impact du manque de sommeil sur la santé physique et mentale + [00:02:03][^4^][4] La diminution du temps de sommeil * Une tendance à la baisse du temps de sommeil au fil des ans * Les enfants et adolescents sont les plus touchés par cette réduction * Les conséquences sur les performances académiques et cognitives + [00:03:44][^5^][5] Le sommeil et le développement cognitif * Les trajectoires de sommeil affectent le comportement et l'apprentissage * Les corrélations entre la qualité du sommeil et les compétences linguistiques * L'importance du sommeil profond pour la maturation cérébrale + [00:10:52][^6^][6] La consolidation de la mémoire pendant le sommeil * Le sommeil joue un rôle actif dans la stabilisation des apprentissages * Les processus de réactivation nocturne renforcent la mémoire * La sieste peut également être bénéfique pour la consolidation

This is an example of the prisoners dilemma being promoted by the way digital learning technologies are constructed. Scholia and hypothesis might present the antithesis to this problem, as these platforms constantly remind the user that the way their learning is dependent on others. Since hypothesis is always present at the side of the screen the learner is also constantly being reminded that they are able to contribute to the public knowledge database.

These values and interests might be best described as those of the private sector and the profit motive. The teaching management platform Moodle seems to follow this trend as the interactivity of the platform is largely controlled by the teacher. This is one way that capitalism enforces bisected learning, and it is also an example of how bisected learning and capitalism are indirect contradiction to explorative learning and free knowledge.

Schraube defines two (plural!) learning dimensions: content and reason. Perhaps there it is only one dimension containing those two aspects.

It seems possible that the arguments made against digital technologies for learning could also be made for any other human technology. Perhaps the underlying argument is that learning exists in the relation itself between the subject at hand and the learner. in that case, " nobody learns technologically". The point that seems to be made is that a digital technology for world making and learning needs to promote the relations themselves between the learner and the text. It could be argued that this is a quality of semantic tools.

Expansive acts are future-oriented

This might also be understood in the sense that you can't learn anything from a text that you don't have any expectations for. If you don't have some idea about the conclusions that are going to be drawn, there are no concepts in your mind that I improved changed or created.

Problem with tools like ChatGPT is not an inherent individualization, but that its lack of transparency hampers the ability for critical reasoning, including social collaborative reflection. Tools that present statements (words put together) without reference to the origins of presumed reasoning for concluding the statement, invites only for taking the statements as-is, not for reflecting and therefore do not stimulate a constructive learning process. But that is a criticism of tools lacking transparency, not of digitalization in general.

Interesting distinction!<br /> Collaboration versus Cooperation, and the more specific collaborative learning versus cooperative learning.

Only when asking students to reflect on their own potentials of digitalization does it seem reasonable to conclude about that.

If instead (as suspected here) the students were asked about their *practices", then it seems unfair to extrapolate potentials.

Related: Are the learners even capable of identifying what is potential? That seems to depend on their skills on the involved practices.

Probably¹ the argument here is that words placed into sentences are merely building blocks for information - i.e. they can contain information but can also lack information, and ChatGPT by design lumps together pieces of information through non-rational means: It hallucinates.

¹ The source Bender, 2023 is behind a paywall, so only guessing here.

Not all technology promotes "hiding behind" - some promotes transparency and collaboration.

Understandable that "Elaine" conflates an issue of peer pressure with a quite different issue of surveillance. But problematic that it is quoted in a context of understanding problems of digitalization, without defusing the obvious hyperbole: The word "surveillance" is commonly associated with control imposed by superior parties external to the (immediate, intended) dialogue (notably governments and multinational corporations). It is notably not commonly associated with kinds of the control the immediate group imposes on you when you expose your uncertainties in a collaborative learning process. Maybe "Elaine" really feels as strongly an oppression as if NSA of Google was puppetmastering her, but more likely she is sloppily describing "peer pressure" - which however does not as strongly give off a smell of being an issue with digitalization. In the context the quote is used to boost digitalization as a villain, which is not helpful.

Fun word play, but also deceptive: The haystack of finding relevant source material for covering a problem space is not a digital one. Jokingly framing it as such, exactly in the context of identifying problems with digitalization in learning, is quite problematic.

True that those digital tools intensifying individualization of learning is a serious problem for (expansive) learning. False (or unknown, however. that digital learning in general inherently is seriously problematic in this way. Reason is that only individualizing tools have so far been examined, and therefore only potential for individualization can be concluded.

seems the reasons given are relates to fluency in using the tool, more than the tool being digital.

Examinations so far have been biased: Not generally on digital tools, but highlighting problems by picking extreme tools. Problems exist, but examining the problematic part of a filed and concluding that the field is problematic is tautologic.

Probably the same urge to do it privately first, before risking the exposure of the group, is the same for non-digital collaborative tools like a whiteboard or a blackboard.

Right: This is something specific to ChatGPT - not general for digitalization.

The students identify a problem in navigating vast amount of information, but even if they mention "internet" they do not frame that as a problem of digitalization: The framing is on the author.

It is difficult not to read the text as arguing, that digitalization in general inherently is biased towards individualizing the practice of learning. Yes, there is potential for that quality, but no, it is neither general for digital tools nor unique for digital tools.

So this digital tool (computers used for writing) is internalized (possibly as a result of schooling and/or peer pressure or other interactions in a previous part of life) compared to alternatives for the same task (pen and paper), so it is not a comparison between options in principle equal but one being digital and the other not, but instead options in principle equal but the other internalized and the other not.

Why scoping that challenge as being "in the digital space"? Do any of the students examined here (or anyone else) find it particularly confusing or in other ways hard to search "in the digital space" as opposed to outside of it?

Search engines can be confusing to use effectively, especially as a new scholarly student, but I strongly doubt that many will find it harder than effectively using index cards.

True, lack of focus is a "highly problematic phenomenon", and nowadays where most entertainment is digital, distractions are quite often digital. But it is not a problem of digitalization. If it were, then students would have generally been super focused back in the day before the rise of the internet.

This problem seems not tied to digitalization: Responses from a collection of books in a library is also "completely disconnected" from the world outside, due to books being static. ChatGPT being static is not rooted in it being digital but despite that: Generative artificial intelligence systems like ChatGPT can easily be designed to be connected, and ChatGPT specifically is deliberately crippled as a security mechanism - i.e. concerns by those producing the service over the lack of control over the conversations possible between the service and its consumer/learner. Arguably, books are inherently disconnected and ChatGPT is designed to mimick a similar disconnected model even though digitalization offers opportunity for letting go of that constraint.

Commonly, sure, but are digital technologies really categorically insignificant for tentacular learning?

Seems that certain set of digital technologies are supportive of tentacular thinking by design, and thus potentially significant if used as per their intended design.

The dimension of learning concerned with the how might not be the only dimension that digital technologies can grasp. Using semantic digital technologies for learning could for example radically change the way we see the learning process as we learn. For example using scholia might prompt the learner to ask more questions about the why as they have more material in front of them and have to make choices about which one to read based on the information about each of them. Hard to understand concepts would be opened up to the learner and the learner would get used to being able to open up these concepts. Using a tool like hypothesis might also prompt the reader to ask critical questions about the text that they are reading and these critiques could be written down for the other students to use and learn from.

some dimensions are decisive - but which?

This is the precisely the conclusion you would draw on learning if you were to analyse the process of learning dialectically. This conclusion also stands in direct opposition to the dominant narrative and method of approximating knowledge by splitting up the whole into smaller and smaller isolated pieces

the material dimension is the use of technologies: Instrumentation

as this applies to the learning action as well, an effective digital learning tool would have to tear down the conceptual walls, that divide the different texts that constitute a university lecture

These four components of a learning action can serve as a framework for analyzing the efficiency of tools for learning digitally like Scholia and Hypothes.is.

Categorizing learning itself as an action is an important step to understanding the difficulties associated with learning digitally. Perhaps the problem with digital tools for learning is that they make the learning process less dynamic, more formulaic and predetermined?

eLife assessment

This study presents a valuable finding on the relationship between brain activity related to sustained attention and substance use in adolescence/early adulthood with a large longitudinal dataset. The evidence supporting the claims of the authors is solid, although the inclusion of more details of methods, results, and data analyses would have strengthened the study. The work will be of interest to cognitive neuroscientists, psychologists, and clinicians working on substance use or addiction.

Reviewer #1 (Public Review):

This study explored the relationship between sustained attention and substance use from ages 14 to 23 in a large longitudinal dataset. They found behaviour and brain connectivity associated with poorer sustained attention at age 14 predicted subsequent increase in cannabis and cigarette smoking from ages 14-23. They concluded that the brain network of sustained attention is a robust biomarker for vulnerability to substance use. The big strength of the study is a substantial sample size and validation of the generalization to an external dataset. In addition, various methods/models were used to prove the relationship between sustained attention and substance use over time.

Reviewer #2 (Public Review):

Weng and colleagues investigated the relationship between sustained attention and substance use in a large cohort across three longitudinal visits (ages 14, 19, and 23). They employed a stop signal task to assess sustained attention and utilized the Timeline Followback self-report questionnaire to measure substance use. They assessed the linear relationship between sustained attention-associated functional connections and substance use at an earlier visit (age 14 or 19). Subsequently, they utilized this relationship along with the functional connection profile at a later age (age 19 or 23) to predict substance use at those respective ages. The authors found that connections in association with reduced sustained attention predicted subsequent increases in substance use, a conclusion validated in an external dataset. Altogether, the authors suggest that sustained attention could serve as a robust biomarker for predicting future substance use.

This study by Weng and colleagues focused on an important topic of substance use prediction in adolescence/early adulthood. While the study largely achieves its aims, several points merit further clarification:

(1) Regarding connectome-based predictive modeling, an assumption is that connections associated with sustained attention remain consistent across age groups. However, this assumption might be challenged by observed differences in the sustained attention network profile (i.e., connections and related connection strength) across age groups (Figures 2 G-I, Fig. 3 G_I). It's unclear how such differences might impact the prediction results.

(2) Another assumption of the connectome-based predictive modeling is that the relationship between sustained attention network and substance use is linear, and remains linear over development. Such linear evidence from either the literature or their data would be of help.

(3) Heterogeneity in results suggests individual variability that is not fully captured by group-level analyses. For instance, Figure 1A shows decreasing ICV (better-sustained attention) with age on the group level, while there are both increasing and decreasing patterns on the individual level via visual inspection. Figure 7 demonstrates another example in which the group with a high level of sustained attention has a lower risk of substance use at a later age compared to that in the group with a low level of sustained attention. However, there are individuals in the high sustained attention group who have substance use scores as high as those in the low sustained attention group. This is important to take into consideration and could be a potential future direction for research.

The above-mentioned points might partly explain the significant but low correlations between the observed and predicted ICV as shown in Figure 4. Addressing these limitations would help enhance the study's conclusions and guide future research efforts.

Reviewer #3 (Public Review):

Summary:

Weng and colleagues investigated the association between attention-related connectivity and substance use. They conducted a study with a sizable sample of over 1,000 participants, collecting longitudinal data at ages 14, 19, and 23. Their findings indicate that behaviors and brain connectivity linked to sustained attention at age 14 forecasted subsequent increases in cigarette and cannabis use from ages 14 to 23. However, early substance use did not predict future attention levels or attention-related connectivity strength.

Strengths:

The study's primary strength lies in its large sample size and longitudinal design spanning three time-points. A robust predictive analysis was employed, demonstrating that diminished sustained attention behavior and connectivity strength predict substance use, while early substance use does not forecast future attention-related behavior or connectivity strength.

Weaknesses:

It's questionable whether the prediction approach (i.e., CPM), even when combined with longitudinal data, can establish causality. I recommend removing the term 'consequence' in the abstract and replacing it with 'predict'. Additionally, the paper could benefit from enhanced rigor through additional analyses, such as testing various thresholds and conducting lagged effect analyses with covariate regression.

eLife assessment

This interesting study reports that muscle contains fibro-adipogenic progenitor cells (FAPs) that promote regeneration following injury of peripheral neurons. These novel results indicate that several known growth factors are involved in the process of regeneration. This is an important contribution, however the analysis is incomplete since additional experimental data is needed to support the main conclusions.

Reviewer #1 (Public Review):

In this manuscript, Yoo et al describe the role of a specialized cell type found in muscle, Fibro-adipogenic progenitors (FAPs), in promoting regeneration following sciatic nerve injury. Using single-cell transcriptomics, they characterize the expression profiles of FAPs at various times after nerve crush or denervation. Their results reveal that a population of these muscle-resident mesenchymal progenitors up-regulate the receptors for GDNF, which is secreted by Schwann cells following crush injury, suggesting that FAPs respond to this growth factor. They also find that FAPs increase expression of BDNF, which promotes nerve regeneration. The authors demonstrate FAP production of BDNF in vivo is upregulated in response to injection of GDNF and that conditional deletion of BDNF in FAPs results in delayed nerve regeneration after crush injury, primarily due to lagging remyelination. Finally, they also find reduced BDNF expression following crush injury in aged mice, suggesting a potential mechanism to explain the decrease in peripheral nerve regenerative capability in aged animals. These results are very interesting and novel and provide important insights into the mechanisms regulating peripheral nerve regeneration, which has important clinical implications for understanding and treating nerve injuries. However, there are a few concerns that the authors need to address.

Given that only a fraction of the FAPs express BDNF after injury, the authors need to demonstrate the specificity of the Prrx1-Cre for FAPs. This is particularly important because muscle stem cell also express GDNF receptors (Fig. 3C & D) and myogenic progenitors/satellite cells produce BDNF after nerve injury (Griesbeck et al., 1995 (PMID 8531223); Omura et al., 2005 (PMID 16221288)). Moreover, as the authors point out, there are multipotent mesenchymal precursor cells in the nerve that migrate into the surrounding tissue following nerve injury and contribute to regeneration (Carr et al, PMID 30503141). Therefore, there are multiple possible sources of BDNF, highlighting the need to clearly demonstrate that FAP-derived BDNF is essential.

Similarly, the authors should provide some evidence that BDNF protein is produced by FAPs. All of their data for BDNF expression is based on mRNA expression and that appears to only be increased in a small subset of FAPs. Perhaps an immunostaining could be done to demonstrate up-regulation of BDNF in FAPs after injury.

The suggestion that Schwann cell-derived GDNF is responsible for up-regulation of BDNF in the FAPs is indirect, based largely on the data showing that injection of GDNF into the muscle is sufficient to up-regulate BDNF (Fig. 4F & G). However, to more directly connect the 2 observations in a causal way, the authors should inject a Ret/GDNF antagonist, such as a Ret-Fc construct, then measure the BDNF levels.

In assessing the regeneration after nerve crush, the authors focus on remyelination, for example, assessing CMAP and g-ratios. However, they should also quantify axon regeneration, which can be done distal to the crush injury at earlier time points, before the 6 weeks scored in their study. Evaluating axon regeneration, which occurs prior to remyelination, would be especially useful because BDNF can act on both Schwann cells, to promote myelination, and axons, enhancing survival and growth. They could also evaluate the stability of the neuromuscular junctions, particularly if a denervation was done with the conditional knock outs, although that may be a bit beyond the scope of this study.

Reviewer #2 (Public Review):

Summary:

Yoo and colleagues studied the cellular mechanism allowing fibro-adipogenic progenitors (FAPs), muscle resident mesenchymal progenitors, to contribute to nerve regeneration upon regenerative injury. In addition to their expected role in the maintenance of muscle tissue, FAPs also contribute to the maturation and maintenance of neural tissue. After nerve injury, they prevent dying back loss of motor neurons. Consistently, muscle denervation activates FAPs, suggesting that FAPs can sense the injured distal peripheral nerve.

A transcriptomic database was established using flow cytometry protocols and single-cell RNA-seq. FAPs were isolated from sciatic nerve crush (SNC), considered a regenerative condition, and compared to a non-regenerative condition consisting of denervation-affected muscles (DEN) at different time points after injury: early (3 and 7 days post-injury, dpi) and late (14 and 28 dpi), when the regeneration process has started to resolve. Transcriptome changes of the nine different conditions were compared: non-injured, 3, 7, 14, and 28 days after injury. Bioinformatic analysis and other filters were applied, including UMAP plots, hierarchical clustering analysis using differentially expressed genes (DEGs), volcano plots, and RNA velocity analysis. In addition to most of the supplementary material, the first three and a half central figures consist of the analysis of the transcriptome changes comparing the different conditions. Overall, the data indicate similar DEGs after both types of injury at early stages. Still, just after SNC, the gene expression pattern reaches similar levels compared to non-injured, meaning the injured process is resolved. For example, the Interleukin6/Stat3 pathway is upregulated in both injury models but downregulated at 28 days just in SNC. When focusing on the comparison between 28 dpi between both types of injury, it indicates a role of FAPs in the resolution of inflammation in SNC and participation of FAPs in fibrosis and inflammation in DEN at 28 dpi. Genes related to wound healing were enriched in both.

With the question in mind of how FAPs are sensing injury, the authors identified a subset of FAPs relevant to regeneration in the SNC model. The unsupervised clustering of FAPs cells considering the nine different types of samples resulted in seven clusters of FAPs. Cluster one was exclusive to non-injury animals or regenerated samples. Clusters two and three were exclusive to the early injured or denervated nerve, suggesting that cluster one senses injury and clusters two and three are derived from it. Among the highest DEGs in cluster one were the GDNF receptors Ret and Gfra1. It is known that GDNF is released by Schwann cells after nerve injury in the literature. Also, gene expression analysis in clusters two and three predicts RTK involvement and GDNF signaling. Altogether, transcriptomic data suggest that GDNF is the mechanism by which FAPs sense nerve injury.

On the other hand, they found BDNF expression limited to cluster two of injured FAPs, suggesting that FAPs respond to GDNF by secreting BDNF. Although the specific role of secreted BDNF by FAPs in nerve regeneration is unknown, BDNF is known to have a regenerative influence on injured sciatic nerves by promoting both axonal growth and myelination. Consistent with their hypothesis, the analysis of gene expression in Schwann cells (sorted using the Plp1CreER Rosatd tomato mouse) and FAPs after injury indicates an initial increase in GDNF gene expression in early time points after injury in Schwann cells, followed by increased expression of BDNF in FAPs. Using conditional knock-out of BDNF in low limb FAPs (Prrx1Cre; Bdnffl/fl), they were able to demonstrate that nerve regeneration is impaired in Prrx1Cre; Bdnffl/fl, by delayed myelinization of axons.

Strengths:

I found the article well-written and cleverly maximized the interpretation and analysis of single-cell transcriptome data. Their findings illuminate how growth factors allow communication between cells responding to injury to promote regeneration. I find the data generated by the authors sufficient to support their model and claims,

Weaknesses:

Although, I find the data the authors generated enough for their claims. I do see them as relatively poor, and a complementary analysis of protein expression would strengthen the paper through immunostaining of the different genes mentioned for FAPs and Schwann cells. The model is entirely supported by measuring mRNA levels and negative regulation of gene expression in specific cells. Additionally, what happens to the structure of the neuromuscular junction after regeneration when GDNF or BDNF expression is reduced? The determination of decreasing levels of FAPs BDNF mRNA during aging is interesting; is the gain of BDNF expression in FAPs reverting the phenotype?

Reviewer #3 (Public Review):

Summary:

The manuscript by Kyusang Yoo et al. "Muscle-resident mesenchymal progenitors sense and repair peripheral nerve injury via the GDNF-BDNF axis" investigates the role and mechanisms of fibro-adipogenic progenitors (FAPs), that are muscle-resident mesenchymal progenitors, in the maturation and maintenance of the neuromuscular system. There is earlier evidence that absence of FAPs or its functional decline with age cause smaller regenerated myofibers. Role of FAPs on peripheral nerve regeneration is very poorly studied. This study has translational importance because traumatic injury to the peripheral nerve can cause lifelong paralysis of the injured limb.

This manuscript provides data indicating that GDNF-BDNF axis plays an important role in peripheral nerve regeneration and function.

Strengths:

Because the role of FAPs on peripheral nerve regeneration is very poorly studied this investigation is a major step towards understanding the mechanism on the role of FAPs. They use scRNA-seq, animal models, and cKO mice that is also important. This study has translational importance because traumatic injury to the peripheral nerve can cause lifelong paralysis of the injured limb.<br /> This is an interesting and original study focusing on the role of FAPs and indicating that GDNF-BDNF axis plays an important role in peripheral nerve regeneration and function.

Weaknesses:

In Fig. 1 and 2 authors provide data on scRNA seq and this is important information reporting the finding of RET and GFRa1 transcripts in the subpopulation of FAP cells. However, authors provide no data on the expression of RET and GFRa1 proteins in FAP cells.<br /> Another problem is the lack of information showing that GDNF secreted by Schwann cells can activate RET and its down-stream signaling in FAP cells.<br /> There is no direct experimental proof that GDNF activating GFRa1-RET signaling triggers BDNF upregulation In FAP cells.<br /> The data that GDNF signaling is inducing the synthesis and secretion of BDNF is also not conclusive.

Meredith Whittaker on the origin of AI wave and consquences. Need to read this. #toread Current AI as 1980s insights now feasible on top of the massive data of bigtech silos. And Clinton admin wrt privacy and advertising in 1990s as the fautllines that enabled #socmed platform silos.

eLife assessment

Cancer treatments are not just about the tumor - there is an ever-increasing need for treating pain, fatigue, and anhedonia resulting from the disease. Using an implantable oral tumor model in the mouse, the authors provide valuable information showing that nerve fibers are transmitting sensory signals to the brain that reduce pleasure and motivation. These findings are in part supported by anatomical and transcript changes in the tumor that suggest sensory innervation, neural tracing, and neural activity measurements; however, the study is incomplete in its current form.

Reviewer #1 (Public Review):

Summary:

Using a mouse model of head and neck cancer, Barr et al show that tumor-infiltrating nerves connect to brain regions via the ipsilateral trigeminal ganglion, and they demonstrate the effect this has on behavior. The authors show that there are neurites surrounding the tumors using a WGA assay and show that the brain regions that are involved in this tumor-containing circuit have elevated Fos and FosB expression and increased calcium response. Behaviorally, tumor-bearing mice have decreased nest building and wheel running and increased anhedonia. The behavior, Fos expression, and heightened calcium activity were all decreased in tumor-bearing mice following nociceptor neuron elimination.

Strengths:

This paper establishes that sensory neurons innervate head and neck cancers and that these tumors impact select brain areas. This paper also establishes that behavior is altered following these tumors and that drugs to treat pain restore some but not all of the behavior. The results from the experiments (predominantly gene and protein expression assays, cFos expression, and calcium imaging) support their behavioral findings both with and without drug treatment.

Weaknesses:

Study suggests that the effects of their tumor models of mouse behavioral are largely non-specific to the tumor as most behaviors are rescued by analgesic treatment. So, most of the changes were likely due to site-specific pain and not a unique signal from the tumor.

Reviewer #2 (Public Review):

Summary:

Cancer treatments are not just about the tumor - there is an ever-increasing need for treating pain, fatigue, and anhedonia resulting from the disease as patients are undergoing successful but prolonged bouts with cancer. Using an implantable oral tumor model in the mouse, Barr et al describe neural infiltration of tumors, and posit that these nerve fibers are transmitting pain and other sensory signals to the brain that reduce pleasure and motivation. These findings are in part supported by anatomical and transcriptional changes in the tumor that suggest sensory innervation, neural tracing, and neural activity measurements. Further, the authors conduct behavior assays in tumor-bearing animals and inhibit/ablate pain sensory neurons to suggest the involvement of local sensory innervation of tumors in mediating cancer-induced malaise.

Strengths:

• This is an important area of research that may have implications for improving the quality of life of cancer patients.

• The studies use a combination of approaches (tracing and anatomy, transcriptional, neural activity recordings, behavior assays, loss-of-function) to support their claims.

• Tracing experiments suggest that tumor-innervating afferents are connected to brain nuclei involved in oral pain sensing. Consistent with this, the authors observed increased neural activity in those brain areas of tumor-bearing animals. It should be noted that some of these brain nuclei have also been implicated in cancer-induced behavioral alterations in non-head and neck tumor models.

• Experiments are for the most part well-controlled, and approaches are validated.

• The paper is well-written and the layout was easy to follow.

Weaknesses:

• The main claim is that tumor-infiltrating nerves underlie cancer-induced behavioral alterations, but the experimental interventions are not specific enough to support this. For example, all TRPV1 neurons, including those innervating the skin and internal organs, are ablated to examine sensory innervation of the tumor. Within the context of cancer, behavioral changes may be due to systemic inflammation, which may alter TRPV1 afferents outside the local proximity of tumor cells. A direct test of the claims of this paper would be to selectively inhibit/ablate nerve fibers innervating the tumor or mouth region.

• Behavioral results from TRPV1 neuron ablation studies are in part confounded by differing tumor sizes in ablated versus control mice. Are the differences in behavior potentially explained by the ablated animals having significantly smaller tumors? The differences in tumor sizes are not negligible. One way to examine this possibility might be to correlate behavioral outcomes with tumor size.

Reviewer #3 (Public Review):

Summary:

The authors have tested for and demonstrated a physical (i.e., sensory nerves to the brain) connection between tumors and parts of the brain. This can explain why there is an increase in depressive disorders in HNSCC patients. While connections such as this have been suspected, this is a novel demonstration pointing to sensory neurons that is accompanied by a remarkable amount of complementary data.

Strengths:

There is substantial evidence provided for the hypotheses tested. The data are largely quite convincing.

Weaknesses:

The authors mention in their Discussion the need for additional experiments. Could they also include / comment on the potential impact on the anti-tumor immune system in their model?

Minor:

The authors mention the importance of inflammation contributing to pain in cancer but do not clearly highlight how this may play a role in their model. Can this be clarified?

The tumor model apparently requires isoflurane injection prior to tumor growth measurements. This is different from most other transplantable types of tumors used in the literature. Was this treatment also given to control (i.e., non-tumor) mice at the same time points? If not, can the authors comment on the impact of isoflurane (if any) in their model?

The authors emphasize in several places that this is a male mouse model. They mention this as a limitation in the Discussion. Was there an original reason why they only tested male mice?

eLife assessment

The authors show that short bouts of chemical ischemia lead to presynaptic changes in glutamate release and long-term potentiation, whereas longer bouts of chemical ischemia lead to synaptic failure and presumably cell death (which could be confirmed experimentally). This solid work relies on rigorous electrophysiology/imaging experiments and data analysis. It is valuable as it provides new mechanistic details on chemical ischemia, though its implications for ischemic stroke in vivo remain to be determined.

Reviewer #1 (Public Review):

Summary:

This work by Passlick and colleagues set out to reveal the mechanism by which short bouts of ischemia perturb glutamate signalling. This manuscript builds upon previous work in the field that reported a paradoxical increase in synaptic transmission following acute, transient ischemia termed ischemic or anoxic long-term potentiation. Despite these observations, how this occurs and the involvement of glutamate release and uptake mechanisms remains unanswered.

Here the authors employed two distinct chemical ischemia models, one lasting 2 minutes, the other 5 minutes. Recording evoked field excitatory postsynaptic potentials in acute brain slices, the authors revealed that shorter bouts of ischemia resulted in a transient decrease in postsynaptic responses followed by an overshoot and long-term potentiation. Longer bouts of chemical ischemia (5 minutes), however, resulted in synaptic failure that did not return to baseline levels over 50 minutes of recording (Figure 1).

Two-photon imaging of fluorescent glutamate sensor iGluSnFR expressed in astrocytes matched postsynaptic responses with shorter ischemia resulting in a transient dip before the increase in extracellular glutamate which was not the case with prolonged ischemia (Figure 2).

Mechanistically, the authors show that these increased glutamate levels and postsynaptic responses were not due to changes in glutamate clearance (Figure 3). Next using a competitive antagonist for AMPA postsynaptic AMPA receptors the authors show that synaptic glutamate release was enhanced by 2 minute chemical ischemia.

Taken together, these data reveal the underlying mechanism regarding ischemic long-term potentiation, highlighting presynaptic release as the primary culprit. Additionally, the authors show relative insensitivity of glutamate uptake mechanisms during ischemia, highlighting the resilience of astrocytes to this metabolic challenge.

Strengths:

This manuscript uses robust and modern techniques to address the mechanism by which ischemia influences synaptic transmission in the hippocampus.

The data are of high quality, with adequately powered sample sizes to address their hypotheses.

Weaknesses:

The question of the physiological relevance of short bouts of ischemia remains.

The precise mechanisms underlying the shift between ischemia-induced long-term potentiation and long-term failure of synaptic responses were not addressed. Could this be cell death?

Sex differences are not addressed or considered.

Reviewer #2 (Public Review):

Summary:

To investigate the impact of chemical ischemia induced by blocking mitochondrial function and glycolysis, the authors measured extracellular field potentials, performed whole-cell patch-clamp recordings, and measured glutamate release with optical techniques. They found that shorter two-minute-lasting blockade of energy production initially blocked synaptic transmission but subsequently caused a potentiation of synaptic transmission due to increased glutamate release. In contrast, longer five-minute-lasting blockage of energy production caused a sustained decrease of synaptic transmission. A correlation between the increase of intracellular potassium concentration and the response upon chemical ischemia indicates that the severity of the ischemia determines whether synapses potentiate or depress upon chemical ischemia. A subsequent mechanistic analysis revealed that the speed of uptake of glutamate is unchanged. An increase in the duration of the fiber volley reflecting the extracellular voltage of the action potentials of the axon bundle was interpreted as an action potential broadening, which could provide a mechanistic explanation. In summary, the data convincingly demonstrate that synaptic potentiation induced by chemical ischemia is caused by increased glutamate release.

Strengths:

The manuscript is well-written and the experiments are carefully designed. The results are exciting, novel, and important for the field. The main strength of the manuscript is the combination of electrophysiological recordings and optical glutamate imaging. The main conclusion of increased glutamate release was furthermore supported with an independent approach relying on a low-affinity competitive antagonist of glutamate receptors. The data are of exceptional quality. Several important controls were carefully performed, such as the stability of the recordings and the size of the extracellular space. The number of experiments is sufficient for the conclusions. The careful data analysis justifies the classification of two types of responses, namely synaptic potentiation and depression after chemical ischemia. Except for the duration of the presynaptic action potentials (see below weaknesses) the data are carefully discussed and the conclusions are justified.

Weaknesses:

The weaknesses are minor and only relate to the interpretation of some of the data regarding the presynaptic mechanisms causing the potentiation of release. The authors measured the fiber volley, which reflects the extracellular voltage of the compound action potential of the fiber bundle. The half-duration of the fiber volley was increased, which could be due to the action potential broadening of the individual axons but could also be due to differences in conduction velocity. We are therefore skeptical whether the conclusion of action broadening is justified.

Reviewer #3 (Public Review):

Summary:

This valuable study shows that shorter episodes (2 minutes duration) of energy depletion, as it occurs in ischemia, could lead to long-lasting dysregulation of synaptic transmission with presynaptic alterations of glutamate release at the CA3-CA1 synapses. A longer duration of chemical ischemia (5 minutes) permanently suppresses synaptic transmission. By using electrophysiological approaches, including field and patch clamp recordings, combined with imaging studies, the authors demonstrated that 2 minutes of chemical ischemia leads to a prolonged potentiation of synaptic activity with a long-lasting increase of glutamate release from presynaptic terminals. This was observed as an increase in iGluSnFR fluorescence, a sensor for glutamate expressed selectively on hippocampal astrocytes by viral injection. The increase in iGluSnFR fluorescence upon 2-minute chemical ischemia could not be ascribed to an altered glutamate uptake, which is unaffected by both 2-minute and 5-minute chemical ischemia. The presynaptic increase in glutamate release upon short episodes of chemical ischemia is confirmed by a reduced inhibitory effect of the competitive antagonist gamma-D-glutamylglycine on AMPA receptor-mediated postsynaptic responses. Fiber volley durations in field recording are prolonged in slices exposed to 2 min chemical ischemia. The authors interpret this data as an indication that the increase in glutamate release could be ascribed to a prolongation of the presynaptic action potential possibly due to inactivation of voltage-dependent K+ channels. However, more direct evidence is needed to support this hypothesis fully. This research highlights an important mechanism by which altered ionic homeostasis underlying metabolic failure can impact on neuronal activity. Moreover, it also showed a different vulnerability of mechanisms involved in glutamatergic transmission with a marked resilience of glutamate uptake to chemical ischemia.

Strengths:

(1) The authors use a variety of experimental techniques ranging from electrophysiology to imaging to study the contribution of several mechanisms underlying the effect of chemical ischemia on synaptic transmission.

(2) The experiments are appropriately designed and clearly described in the figures and in the text.

(3) The controls are appropriate.

Weaknesses:

- The data on fiber volley duration should be supported by more direct measurements to prove that chemical ischemia increases presynaptic Ca2+ influx due to a presynaptic broadening of action potentials. Given the influence that positioning of the stimulating and recording electrode can have on the fiber volley properties, I found this data insufficient to support the assumption of a relationship between increased iGluSnFR fluorescence, action potential broadening, and increased presynaptic Ca2+ levels.

- The results are obtained in an ex-vivo preparation, it would be interesting to assess if they could be replicated in vivo models of cerebral ischemia.

Impact:

This study provides a more comprehensive view of the long-term effects of energy depletion during short episodes of experimental ischemia leading to the notion that not only post-synaptic changes, as reported by others, but also presynaptic changes are responsible for long-lasting modification of synaptic transmission. Interestingly, the direction of synaptic changes is bidirectional and dependent on the duration of chemical ischemia, indicating that different mechanisms involved in synaptic transmission are differently affected by energy depletion.

https://vimeo.com/949906701

Résumé de la vidéo [00:00:03][^1^][1] - [00:24:34][^2^][2]:

Cette vidéo présente une session d'information sur Parcoursup 2024, destinée à aider les étudiants et leurs familles à aborder sereinement la phase d'admission. Elle couvre les étapes clés du processus, les réponses possibles aux propositions d'admission, et les ressources disponibles pour se préparer efficacement.

Points forts: + [00:00:03][^3^][3] Introduction à la session * Accueil des participants et rappel des webinaires précédents * Objectif d'accompagner les étudiants avant l'ouverture officielle de Parcoursup + [00:01:49][^4^][4] Présentation de l'invité * Introduction de M. Gérant Théard, chargé de mission Parcoursup * Discussion sur l'amélioration continue de la plateforme + [00:05:02][^5^][5] Préparation à la phase d'admission * Conseils pour accompagner les enfants dans les prochains jours * Annonce d'une communication imminente aux lycées de France + [00:09:14][^6^][6] Statistiques et examen des vœux * Nombre de candidats et de vœux confirmés * Processus d'examen des dossiers par les formations + [00:16:01][^7^][7] Calendrier de la phase d'admission * Dates importantes et objectifs de la procédure * Suspension de Parcoursup pendant les épreuves écrites du baccalauréat + [00:20:07][^8^][8] Types de réponses et site d'entraînement * Explication des réponses possibles : oui, oui-si, en attente * Présentation d'un site d'entraînement pour se familiariser avec la procédure Résumé de la vidéo [00:24:35][^1^][1] - [00:46:20][^2^][2]:

Cette partie de la vidéo aborde la phase d'admission de Parcoursup 2024, offrant des conseils pour naviguer sereinement dans le processus. Elle explique les réponses positives, le droit à l'information, et comment gérer les propositions d'admission et les listes d'attente.

Points forts: + [00:24:35][^3^][3] Réponses positives et accompagnement * Une proposition "oui si" indique une réponse positive avec un dispositif d'accompagnement * Importance de comprendre que cela peut indiquer un besoin de soutien supplémentaire pour réussir + [00:25:33][^4^][4] Droit à l'information et délais de réponse * Parcoursup ne prend pas de décisions mais offre un accompagnement * Les candidats ont le droit de demander des explications et de contester les décisions + [00:27:01][^5^][5] Gestion des propositions d'admission * Les alertes par SMS et e-mail informent les candidats des propositions reçues * Les délais pour répondre aux propositions sont clairement indiqués dans le dossier Parcoursup + [00:35:59][^6^][6] Choix entre plusieurs propositions et vœux en attente * Les candidats doivent choisir entre les propositions reçues et indiquer les vœux en attente qu'ils souhaitent conserver * Importance de la solidarité et de la libération des places pour d'autres candidats Résumé de la vidéo [00:46:21][^1^][1] - [01:08:33][^2^][2]:

Cette vidéo explique le processus d'admission de Parcoursup 2024, en mettant l'accent sur la phase d'admission et la gestion des vœux en attente. Elle aborde les délais de réponse, le classement des vœux, et les conseils pour les candidats sans proposition d'admission.

Points forts: + [00:46:21][^3^][3] Accélération du processus d'admission * Informer les candidats avec des vœux en attente * Période de trois jours pour classer les vœux + [00:49:03][^4^][4] Vœux en apprentissage * Augmentation des candidats intéressés par l'apprentissage * Importance de trouver un employeur pour valider l'admission + [00:52:27][^5^][5] Pause pendant les épreuves du baccalauréat * Alignement des délais de réponse sur le 23 juin * Suspension des délais pour les lycéens passant le bac + [01:05:02][^6^][6] Solutions pour les candidats sans proposition * Accompagnement individuel ou collectif dès le 31 mai * Phase complémentaire du 11 juin au 12 septembre Résumé de la vidéo [01:08:37][^1^][1] - [01:31:30][^2^][2]:

Cette vidéo aborde la phase d'admission de Parcoursup 2024, expliquant les délais de réponse, le fonctionnement des commissions d'accès à l'enseignement supérieur, et les dispositifs pour les candidats en situation de handicap.

Points forts: + [01:08:37][^3^][3] Délais de réponse pour les formations * Maximum de huit jours pour examiner les candidatures * Pause estivale du 12 juillet au 23 août + [01:09:45][^4^][4] Commissions d'accès à l'enseignement supérieur * Aident les candidats sans propositions d'admission * Proposent des formations adaptées aux projets des candidats + [01:11:17][^5^][5] Dispositifs pour les candidats en situation de handicap * Possibilité de réexaminer les dossiers dès le 30 mai * Communication des fiches de liaison aux établissements d'accueil + [01:14:00][^6^][6] Gestion des vœux et propositions d'admission * Pas besoin de reconfirmer les vœux préférés à chaque étape * Les propositions acceptées en phase principale sont garanties + [01:25:02][^7^][7] Fin de la phase principale et inscription administrative * Les listes d'attente n'évoluent plus après le 12 juillet * Importance de respecter les dates limites d'inscription Résumé de la vidéo [01:31:33][^1^][1] - [01:54:20][^2^][2] : Cette vidéo aborde la phase d'admission de Parcoursup 2024 et fournit des conseils pour la gérer sereinement. Elle explique le processus de formulation des vœux, la gestion des délais de réponse, et l'importance de valoriser les expériences acquises pendant une année sabbatique ou de césure.

Points forts : + [01:31:33][^3^][3] La phase complémentaire * Explication de la formulation des vœux et des délais de réponse accélérés * Distinction entre année sabbatique et césure * Conseils pour valoriser les expériences acquises + [01:34:37][^4^][4] La fiche Avenir * Disponibilité des appréciations de la fiche Avenir le 30 mai * Importance de connaître les appréciations avant la phase d'admission * Rassure sur l'absence de surprises dans les appréciations + [01:37:02][^5^][5] Les délais de réponse et les inscriptions * Clarification sur l'acceptation des propositions et la suppression des vœux en attente * Instructions pour les inscriptions après les résultats du baccalauréat * Gestion des propositions reçues pendant l'été + [01:41:01][^6^][6] La réorientation en cours d'année * Possibilités de réorientation sans attendre la prochaine session de Parcoursup * Existence de passerelles entre les établissements * Encouragement à solliciter le service d'orientation en cas de doute

maybe he began to reconsider his sexuality or he was too overwhelmed with guilt?

.

https://www.youtube.com/watch?v=rVe7awv0i4A

Résumé de la vidéo [00:01:03][^1^][1] - [00:27:57][^2^][2] : Cette vidéo est un guide en direct pour les élèves et les parents sur la façon de répondre aux propositions des formations sur Parcoursup, la plateforme d'admission post-bac en France. Elle couvre la phase finale du processus Parcoursup 2024, qui commence le 30 mai et se termine le 12 juillet, où les candidats reçoivent les réponses des formations auxquelles ils ont postulé.

Points forts : + [00:03:51][^3^][3] Introduction à la session en direct * Présentation par le proviseur adjoint et les représentants des parents * Objectif : expliquer la phase de réception des vœux sur Parcoursup + [00:04:35][^4^][4] Détails de la phase finale de Parcoursup * Période du 30 mai au 12 juillet pour recevoir les réponses * Suspension des délais de réponse pendant les épreuves écrites du baccalauréat + [00:06:01][^5^][5] Actions mises en place par le lycée * Organisation des "nuits de Parcoursup" pour aider les élèves à répondre aux vœux * Rôle des professeurs principaux et référents en orientation + [00:13:14][^6^][6] Simulation de réception et réponse aux vœux * Utilisation d'une plateforme d'entraînement pour se préparer à la phase d'admission * Explication des règles d'or pour répondre aux propositions et maintenir les vœux en attente Résumé de la vidéo [00:28:00][^1^][1] - [00:41:46][^2^][2]:

Cette vidéo fournit des conseils sur la façon de répondre aux propositions des formations sur Parcoursup en 2024. Elle souligne l'importance de ne pas se précipiter et de prendre le temps de réfléchir avant de répondre, en utilisant les ressources disponibles telles que les nuits de l'orientation et les consultations avec les professeurs.

Points forts: + [00:28:00][^3^][3] Planification de la réponse * Consacrer une journée à la réflexion * Utiliser les ressources comme les nuits de l'orientation * Prendre rendez-vous avec les professeurs pour des conseils + [00:30:04][^4^][4] Phase complémentaire * Débute le 11 juin pour ceux sans proposition * Possibilité de choisir de nouvelles formations avec des places disponibles * Importance de faire une candidature supplémentaire + [00:32:02][^5^][5] Recherche d'entreprise pour l'apprentissage * Nécessité d'un contrat pour valider un vœu en apprentissage * Utiliser les vacances pour trouver une entreprise * Contacter les CFA ou UFA pour des opportunités + [00:34:50][^6^][6] Événements et annonces du lycée * Organisation d'un bal de fin d'année * Présentation des talents des élèves lors d'une émission spéciale * Clarification sur les contrats d'apprentissage et les propositions d'admission

eLife assessment

This important work provides interesting datasets of myofiber differentiation. The evidence supporting the involvement of SRF2 in selected biological processes is convincing, however, additional evidence to pin-point the major action of SRF2 during muscle differentiation is appreciated. The work will be of broad interest to developmental biologists in general and molecular biologists in the field of gene regulation.

Reviewer #1 (Public Review):

Summary

The work by She et al. investigates the role of SRFS2 in the MyoD+ progenitor cells during development. Deletion of SRFS2 in MyoD+ progenitor cells resulted in a defect in the directional migration of these cells and resulted in the presence of myoD+ progenitor in both nonmuscle and muscle tissues. The authors showed a defect in gene program regulation ECM, cell migration, cytoskeletal organization, and skeletal muscle differentiation by scRNA-seq. The authors further showed that many of these processes are regulated by a downstream target of SRFS2, the serine-threonine kinase Aurka. Finally, the authors showed that SRFS2 acts as a splicing factor and could contribute to differentiation by controlling the splicing of muscle-specific transcripts. This study addresses an important question in skeletal muscle development by focusing on the pathways and factors that regulate the migration of myoD+ progenitors and the impact of this process in skeletal muscle differentiation. This work is interesting but requires experimental evidence to support the findings.

Strengths

The regulators of myod+progenitor migration during skeletal muscle development is not completely understood. This work demonstrates that SRFS2 and aura kinase are key players in the process. Combining knockout and reporter lines in mice, the authors perform a detailed analysis of skeletal muscle cells to demonstrate the specific defects in SRFS2 in skeletal muscle development.

Weaknesses

This work explores an interesting question on regulating myoD+ progenitors and the defects of this process in skeletal muscle differentiation by SRFS2 but spreads out in many directions rather than focusing on the key defects. A number of approaches are used, but they lack the robust mechanistic analysis of the defects that result in muscle differentiation. Specifically, the role of SRFS2 on splicing appears to be a misfit here and does not explain the primary defects in the migration of myoD+ progenitors. There are concerns about the scRNA-seq and many transcripts in muscle biology that are not expressed in muscle cells. Focusing on main defects and additional experimental evidence to clear the fusion vs. precocious differentiation vs. reduced differentiation will strengthen this work.

(1) The analysis of RNA-seq data (Figure 2) is limited, and it is unclear how it relates to the work presented in this MS. The Go enrichment analysis is combined for both up and down-regulated DEG, thus making it difficult to understand the impact differently in both directions. Stac2 is a predominant neuronal isoform (while Stac3 is the muscle), and the Symm gene is not found in the HGNC or other databases. Could the authors provide the approved name for this gene? The premise of this work is based on defects in ECM processes resulting in the mis-targeting of the muscle progenitors to the nonmuscle regions. Which ECM proteins are differentially expressed?

(2) Could authors quantify the muscle progenitors dispersed in nonmuscle regions before their differentiation? Which nonmuscle tissues MyoD+ progenitors are seen? Most of the tDT staining in the enlarged sections appears to be punctate without any nuclear staining seen in these cells (Figure 3 B, D E-F). Could authors provide high-resolution images? Also, in the diaphragm cross-sections in mutants, tdT labeling appears to be missing in some areas within the myofibers defined as cavities by the authors (marked by white arrows, Figure 3H). Could this polarized localization of tDT be contributing to specific defects?

(3) Is there a difference in the levels of tDT in the myoD" muscle progenitors that are mis-targeted vs the others that are present in the muscle tissues?

(4) scRNA is unsuitable for myotubes and myofibers due to their size exclusion from microfluidics. Could authors explain the basis for scRNA-seq vs SnRNA-seq in this work? How are SKM defined in scRNA-data in Figure 4? As the myofibers are small in KO, could the increased level of late differentiation markers be due to the enrichment of these small myotubes/myofibers in scRNA? A different approach, such as ISH/IF with the myogenic markers at E9.5-10.5, may be able to resolve if these markers are prematurely induced.

(5) TNC is a marker for tenocytes and is absent in skeletal muscle cells. The authors mentioned a downregulation of TNC in the KO SKM derived clusters. This suggests a contamination of the tenocytes in the control cells. In spite of the downregulation of multiple ECM genes showed by scRNA-seq data, the ECM staining by laminin in KO in Figure 3 appears to be similar to controls.

(6) The expression of many fusion genes, such as myomaker and myomerger, is reduced in KO, suggesting a primary fusion defect vs a primary differentiation defect. Many mature myofiber proteins exhibit an increased expression in disease states, suggesting them as a compensatory mechanism. Authors need to provide additional experimental evidence supporting precocious differentiation as the primary defect.

(7) The fusion defects in KO are also evident in siRNA knockdown for SRSF2 and Aurka in C2C12, which mostly exhibits mononucleated myocytes in knockdowns. Also, a fusion index needs to be provided.

(8) The last section of the role of SRSF2 on splicing appears to be a misfit in this study. Authors describe the Bin1 isoforms in centronuclear myopathy, but exon17 is not involved in myopathy. Is exon17 exclusion seen in other diseases/ splicing studies?

Reviewer #2 (Public Review):

Summary:

This study was aimed to study the role of SRSF2 in governing MyoD progenitors to specific muscle regions. The Results confirmed the role of SRSF2 in controlling myogenic differentiation through the regulation of targeted genes and alternative splicing during skeletal muscle development.

Strengths:

The study used different methods and techniques to achieve aims and support the conclusions such as RNA sequencing analysis, Gene Ontology analysis, immunostaining analysis.<br /> This study provides novel findings that SRSF2 controls the myogenic differentiation of MyoD+ progenitors, using transgenic mouse model and in vitro studies.

Weaknesses:

Although unbiased sequencing methods were used, their findings about SRSF2 served as a transcriptional regulator and functioned in alternative splicing events are not novel.<br /> The introductions and discussion is not clearly written. The authors did not raise clear scientific questions in the introduction part. The last paragraph is only copy-paste of the abstract. The discussion part is mainly the repeat of their results without clear discussion.

Reviewer #3 (Public Review):

Summary:

This study employs an optogenetics approach aimed at activating oncogene (KRASG12V) expression in a single somatic cell, with a focus on following the progression of activated cell to examine tumourigenesis probabilities under altered tissue environments. The research explores the role of stemness factors (VENTX/NANOG/OCT4) in facilitating oncogenic RAS (KRASG12V)-driven malignant transformations. Although the evidence provided are incomplete, the authors propose an important mechanism whereby reactivation of re-programming factors correlates with the increased likelihood of a mutant cell undergoing malignant transformation.

Strengths:

· Innovative Use of Optogenetics: The application of optogenetics for precise activation of KRAS in a single cell is valuable to the field of cancer biology, offering an opportunity to uncover insight into cellular responses to oncogenic mutations.<br /> · Important Observations: The findings concerning stemness factors' role in promoting oncogenic transformation are important, contributing data to the field of cancer biology.

Weaknesses:

Lack of Methodological Clarity: The manuscript lacks detailed descriptions of methodologies, making it difficult to fully evaluate the experimental design and reproducibility, rendering incomplete evidence to support the conclusion. Improving methodological transparency and data presentation will crucially strengthen the paper's contributions to understanding the complex processes of tumourigenesis.<br /> Sub-optimal Data Presentation and Quality:

The resolution of images throughout the manuscript are too low. Images presented in Figure 2 and Figure 4 are of very low resolution. It is very hard to distinguish individual cells and in which tissue they might reside.<br /> Lack of quantitative data and control condition data obtained from images of higher magnification limits the ability to robustly support the conclusions.

Here are some details:<br /> · Tissue specificity of the cells express KRASG12V oncogene: In this study, the ubiquitin promoter was used to drive oncogenic KRASG12V expression. Despite this, the authors claim to activate KRAS in a single brain cell based on their localized photo-activation strategy. However, upon reviewing the methods section, the description was provided that 'Localized uncaging was performed by illumination for 7 minutes on a Nikon Ti microscope equipped with a light source peaking at 405 nm, Figure 1. The size of the uncaging region was controlled by an iris that defines a circular illumination with a diameter of approximately 80 μm.' It is surprising that an epi-fluorescent microscope with an illumination diameter of around 80μm can induce activation in a single brain cell beneath skin tissue. Additionally, given that the half-life for mTFP maturation is around 60 minutes, it is likely that more cells from a variety of different lineages could be activated, but the fluorescence would not be visible until more than 1-hour post-illumination. Authors might want to provide more evidence to support their claim on the single cell KRAS activation.<br /> · Stability of cCYC: The manuscript does not provide information on the half-life and stability of cCYC. Understanding these properties is crucial for evaluating the system's reliability and the likelihood of leakiness, which could significantly influence the study's outcomes.<br /> · Metastatic Dissemination claim: Typically, metastatic cancer cells migrate to and proliferate within specific niches that are conducive to outgrowth, such as the caudal hematopoietic tissue (CHT) or liver. In figure 3 A, an image showing the presence of mTFP expressing cells in both the head and tail regions of the larva, with additional positive dots located at the fin fold. This is interpreted as "metastasis" by the authors. However, the absence of a supportive cellular compartment within the fin-fold tissue makes the presence of mTFP-positive metastatic cells there particularly puzzling. This distribution raises concerns about the spatial specificity of the optogenetic activation protocol.<br /> The unexpected locations of these signals suggest potential ectopic activation of the KRAS oncogene, which could be occurring alongside or instead of targeted activation. This issue is critical as it could affect the interpretation of whether the observed mTFP signal expansion over time is due to actual cell proliferation and infiltration, or merely a result of ectopic RAS transgene activation.<br /> · Image Resolution Concerns: The cells depicted in Figure 3C β, which appear to be near the surface of the yolk sac and not within the digestive system as suggested in the MS, underscore the necessity for higher-resolution imaging. Without clearer images, it is challenging to ascertain the exact locations and states of these cells, thus complicating the assessment of experimental results.<br /> · The cell transplantation experiment is lacking protocol details: The manuscript does not adequately describe the experimental protocols used for cell transplantation, particularly concerning the origin and selection of cells used for injection into individual larvae. This omission makes it difficult to evaluate the reliability and reproducibility of the results. Such as the source of transplanted cells:<br /> • If the cells are derived from hyperplastic growths in larvae where RAS and VX (presumably VENTX) were locally activated, the manuscript fails to mention any use of fluorescence-activated cell sorting (FACS) to enrich mTFP-positive cells. Such a method would be crucial for ensuring the specificity of the cells being studied and the validity of the results.<br /> • If the cells are obtained from whole larvae with induced RAS + VX expression, it is notable and somewhat surprising that the larvae survived up to six days post-induction (6dpi) before cells were harvested for transplantation. This survival rate and the subsequent ability to obtain single cell suspensions raise questions about the heterogeneity of the RAS + VX expressing cells that transplanted.<br /> · Unclear Experimental Conditions in Figure S3B: The images in Figure S3B lack crucial details about the experimental conditions. It is not specified whether the activation of KRAS was targeted to specific cells or involved whole-body exposure. This information is essential for interpreting the scope and implications of the results accurately.<br /> · Contrasting Data in Figure S3C compared to literature: The graph in Figure S3C indicates that KRAS or KRAS + DEX induction did not result in any form of hyperplastic growth. This observation starkly contrasts with previous literature where oncogenic KRAS expression in zebrafish led to significant hyper-proliferation and abnormal growth, as evidenced by studies such as those published in and Neoplasia (2018), DOI: 10.1016/j.neo.2018.10.002; Molecular Cancer (2015), DOI: 10.1186/s12943-015-0288-2; Disease Models & Mechanisms (2014) DOI: 10.1242/dmm.007831. The lack of expected hyperplasia raises questions about the experimental setup or the specific conditions under which KRAS was expressed. The authors should provide detailed descriptions of the conditions under which the experiments were conducted in Figure S3B and clarifying the reasons for the discrepancies observed in Figure S3C are crucial. The authors should discuss potential reasons for the deviation from previous reports.

Further comments:

Throughout the study, KRAS-activated cell expansion and metastasis are two key phenotypes discussed that Ventx is promoting. However, the authors did not perform any experiments to directly show that KRAS+ cells proliferate only in Ventx-activated conditions. The authors also did not show any morphological features or time-lapse videos demonstrating that KRAS+ cells are motile, even though zebrafish is an excellent model for in vivo live imaging. This seems to be a missed opportunity for providing convincing evidence to support the authors' conclusions.

There were minimal experimental details provided for the qPCR data presented in the supplementary figures S5 and S6, therefore, it is hard to evaluate result obtained.

eLife assessment

This study provides valuable initial characterization of a verterbrate embryonic system that demonstrates aspects of an optogenetically inducible hyperplasia model. Although the evidence provided is incomplete to conclude that the system is demonstrating tumor initiation from a single cell that is metastasizing that can be quantitatively assessed, the authors propose a mechanism whereby reactivation of re-programming factors correlates with the increased likelihood of a mutant cell undergoing malignant transformation. This work will be of interest to developmental and cancer biologists mainly for the novel genetic tools described.

Reviewer #1 (Public Review):

Scerbo et al. developed an approach based on the oncogene kRasG12V and a reprogramming factor to induce deterministic and reproducible malignant transformation in a single cell. The activation of kRasG12V alone is not sufficient in their hands to initiate carcinogenesis, but when combined with the transient activation of a reprogramming factor (such as Ventx, Nanog, or Oct4), it significantly increases the probability of malignant transformation. This combination of oncogene and reprogramming factor may alter the epigenetic and functional state of the cell, leading to the development of tumors within a short period of time. The use of these two factors allows for the controlled manipulation of a single cell to study the cellular and molecular events involved in the early stages of tumorigenesis. The authors then performed allotransplantations of allegedly single fluorescent TICs in recipient larvae and found a large number of fluorescent cells in distant locations, claiming that these cells have all originated from the single transplanted TIC and migrated away. The number of fluorescent cells showed in the recipient larve just after two days is not compatible with a normal cell cycle length and more likely represents the progeny of more than one transplanted cell. The ability to migrate from the injection site should be documented by time-lapse microscopy. Then, the authors conclude that "By allowing for specific and reproducible single cell malignant transformation in vivo, their optogenetic approach opens the way for a quantitative study of the initial stages of cancer at the single cell level". However, the evidence for these claims are weak and further characterization should be performed to:

(1) show that they are actually activating the oncogene in a single cell (the magnification is too low and it is difficult to distinguish a single nucleus, labelling of the cell membrane may help to demonstrate that they are effectively activating the oncogene in, or transplanting, a single cell)<br /> (2) the expression of the genes used as markers of tumorigenesis is performed in whole larvae, with only a few transformed cells in them. Changes should be confirmed in FACS sorted fluorescent cells<br /> (3) the histology of the so called "tumor masses" is not showing malignant transformation, but at the most just hyperplasia. In the brain, the sections are not perfectly symmetrical and the increase of cellularity on one side of the optic tectum is compatible with this asymmetry.<br /> (4) The number of fluorescent cells found dispersed in the larve transplanted with one single TIC after 48 hours will require a very fast cell cycle to generate over 50 cells. Do we have an idea of the cell cycle features of the transplanted TICs?

Reviewer #2 (Public Review):

Summary:

In the work by Scerbo et al, the authors aim to better understand the open question of what factors constrain cells that are genetically predisposed to form cancer (e.g. those with a potentially cancer-causing mutation like activated Ras) to only infrequently undergo this malignant transformation, with a focus on the influence of embryonic or pluripotency factors (e.g. VENTX/NANOG). Using genetically defined zebrafish models, the authors can inducibly express the KRASG12V oncogene using a combination of Cre/Lox transgenes further controlled by optogenetically inducible Cre-activated (CreER fusion that becomes active with light-induced uncaging of a tamoxifen-analogue in a targeted region of the zebrafish embryo). They further show that transient expression and activation of a pluripotency factor (e.g. Ventx fused to a GR receptor that is activated with addition of dexamethasone) must occur in the model in order for overgrowth of cells to occur. This paper describes a genetically tractable and modifiable system for studying the requirements for inducing cellular hyperplasia in a whole organism by combining overexpression of canonical genetic drivers of cancer (like Ras) with epigenetic modifiers (like specific transcription factors), which could be used to study an array of combinations and temporal relationships of these cancer drivers/modifiers.

Strengths:

The combination of Cre/lox inducible gene expression with potentially localized optogenetic induction (CreER and uncaging of tamoxifen analogues) of recombination as well as well inducible activation of a transcription factor expressed via mRNA injection (GR-fusion to the TF and dex induction) offers a flexible system for manipulating cell growth, identity, and transcriptional programs. With this system, the authors establish that Ras activation and at least transient Ventx overexpression are together required to induce a hyperproliferative phenotype in zebrafish tissues.

The ability to live image embryos over the course of days with inducible fluorophores indicating recombination events and transgene overexpression offers a tractable in vivo system for studying hyperplastic cells in the context of a whole organism.

The transplant experiments demonstrate the ability of the induced hyperplastic cells to grow upon transfer to new host.

Weaknesses:

There is minimal quantitation of key aspects of the system, most critically in the efficiency of activation of the Ras-TFP fusion (Fig 1) in, purportedly, a single cell. The authors note "On average the oncogene is then activated in a single cell, identified within ~1h by the blue fluorescence of its nuclear marker) but no additional quantitative information is provided. For a system that is aimed at "a statistically relevant single-cell<br /> tracking and characterization of the early stages of tumorigenesis", such information seems essential.

The authors indicate that a single cell is "initiated" (Fig 2) using the laser optogenetic technique, but without definitive genetic lineage tracing, it is not possible to conclude that cells expressing TFP distant from the target site near the ear are daughter cells of the claimed single "initiated" cell. A plausible alternative explanation is 1) that the optogenetic targeting is more diffuse (i.e. some of the light of the appropriate wavelength hits other cells nearby due to reflection/diffraction), so these adjacent cells are additional independent "initiated" cells or 2) that the uncaged tamoxifen analogue can diffuse to nearby cells and allow for CreER activation and recombination. In Fig 2B, the claim is made that "the activated cell has divided, giving rise to two cells" - unless continuously imaged or genetically traced, this is unproven. In addition, it appears that Figures S3 and S4 are showing that hyperplasica can arise in many different tissues (including intestine, pancreas, and liver, S4C) with broad Ras + Ventx activation (while unclear from the text, it appears these embryos were broadly activated and were not "single cell activated using the set-up in Fig 1E? This should be clarified in the manuscript). In Fig S7 where single cell activation and potential metastasis is discussed, similar gut tissues have TFP+ cells that are called metastatic, but this seems consistent with the possibility that multiple independent sites of initiation are occurring even when focal activation is attempted.

Although the hyperplastic cells are transplantable (Fig 4), the use of the term "cells of origin of cancer" or metastatic cells should be viewed with care in the experiments showing TFP+ cells (Fig 1, 2, 3) in embryos with targeted activation for the reasons noted above.

Résumé de la vidéo [00:00:02][^1^][1] - [00:13:58][^2^][2]:

Cette vidéo présente une interview avec Christine Ferron, qui discute des inégalités de santé en Île-de-France, des défis posés par la crise du COVID-19, et des stratégies d'intervention pour une éthique de la santé publique. Elle souligne l'importance de comprendre et d'agir sur les déterminants sociaux de la santé pour réduire les inégalités et améliorer l'accès aux soins.

Points forts: + [00:00:02][^3^][3] Inégalités de santé en Île-de-France * Priorité de l'agence régionale de santé * Disparités considérables, comme l'espérance de vie et l'incidence du diabète * Accès inégal aux soins et ségrégation urbaine + [00:03:00][^4^][4] Impact du COVID-19 sur les inégalités * Augmentation des écarts de mortalité entre les territoires * Prise de conscience accrue des inégalités sociales de santé * Importance des déterminants sociaux et des conditions de vie + [00:06:44][^5^][5] Actions contre les inégalités sociales de santé * Nécessité de mesurer et comprendre les inégalités * Approches de régulation et de coalition pour intervenir * Importance de travailler avec divers partenaires et acteurs + [00:09:22][^6^][6] Stratégies d'intervention en santé publique * Interventions concrètes sur les déterminants sociaux * Programmes de santé publique adaptés aux besoins des populations * Approche communautaire et contractualisation pour des actions partagées

eLife assessment

This study describes the application of machine learning and Markov state models to characterize the binding mechanism of alpha-Synuclein to the small molecule Fasudil. The results suggest that entropic expansion can explain such binding. However, the simulations and analyses in their present form are inadequate.

Reviewer #1 (Public Review):

Summary:

This is a well-conducted study about the mechanism of binding of a small molecule (fasudil) to a disordered protein (alpha-synuclein). Since this type of interaction has puzzled researchers for the last two decades, the results presented are welcome as they offer relevant insight into the physical principles underlying this interaction.

Strengths:

The results show convincingly that the mechanism of entropic expansion can explain the previously reported binding of fasudil to alpha-synuclein. In this context, the analysis of the changes in the entropy of the protein and of water is highly relevant. The combination use of machine learning for dimensional reduction and of Markov State Models could become a general procedure for the analysis of other systems where a compound binds a disordered protein.

Weaknesses:

It would be important to underscore the computational nature of the results, since the experimental evidence that fasudil binds alpha-synuclein is not entirely clear, at least to my knowledge.

Reviewer #2 (Public Review):

The manuscript by Menon et al describes a set of simulations of alpha-Synuclein (aSYN) and analyses of these and previous simulations in the presence of a small molecule.

While I agree with the authors that the questions addressed are interesting, I am not sure how much we learn from the present simulations and analyses. In parts, the manuscript reads more like an attempt to apply a whole range of tools rather than with a goal of answering any specific questions.

There's a lot going on in this paper, and I am not sure it is useful for the authors, readers or me to spell out all of my comments in detail. But here are at least some points that I found confusing/etc

Major concerns

p. 5 and elsewhere:<br /> I lack a serious discussion of convergence and the statistics of the differences between the two sets of simulations. On p. 5 it is described how the authors ran multiple simulations of the ligand-free system for a total of 62 µs; that is about 25 times less than for the ligand system. I acknowledge that running 1.5 ms is unfeasible, but at a bare minimum the authors should discuss and analyse the consequences for the relatively small amount of sampling. Here it is important to say that while 62 µs may sound like a lot it is probably not enough to sample the relevant properties of a 140-residue long disordered protein.

p. 7:<br /> The authors make it sound like a bad thing than some methods are deterministic. Why is that the case? What kind of uncertainty in the data do they mean? One can certainly have deterministic methods and still deal with uncertainty. Again, this seems like a somewhat ad hoc argument for the choice of the method used.

p. 8:<br /> The authors should make it clear (i) what the reconstruction loss and KL is calculated over and (ii) what the RMSD is calculated over.

p. 9/figure 1:<br /> The authors select a beta value that may be the minimum, but then is just below a big jump in the cross-validation error. Why does the error jump so much and isn't it slightly dangerous to pick a value close to such a large jump.

p. 10:<br /> Why was a 2-dimensional representation used in the VAE? What evidence do the authors have that the representation is meaningful? The authors state "The free energy landscape represents a large number of spatially close local minima representative of energetically competitive conformations inherent in αS" but they do not say what they mean by "spatially close". In the original space? If so, where is the evidence.

p. 10:<br /> It is not clear from the text whether the VAEs are the same for both aSYN and aSYN-Fasudil. I assume they are. Given that the Fasudil dataset is 25x larger, presumably the VAE is mostly driven by that system. Is the VAE an equally good representation of both systems?

p. 10/11:<br /> Do the authors have any evidence that the latent space representation preserves relevant kinetic properties? This is a key point because the entire analysis is built on this. The choice of using z1 and z2 to build the MSM seems somewhat ad hoc. What does the auto-correlation functions of Z1 and Z2 look like? Are the related to dynamics of some key structural properties like Rg or transient helical structure.

p. 11:<br /> What's the argument for not building an MSM with states shared for aSYN +- Fasudil?

p. 12:<br /> Fig. 3b/c show quite clearly that the implied timescales are not converged at the chosen lag time (incidentally, it would have been useful with showing the timescales in physical time). The CK test is stated to be validated with "reasonable accuracy", though it is unclear what that means.

p. 12:<br /> In Fig. 3d, what are the authors bootstrapping over? What are the errors if the authors analyse sampling noise (e.g. bootstrap over simulation blocks)?

p. 13:<br /> I appreciate that the authors build an MSM using only a subset of the fasudil simulations. Here, it would be important that this analysis includes the entire workflow so that the VAE is also rebuilt from scratch. Is that the case?

p. 18:<br /> I don't understand the goal of building the CVAE and DCVAE. Am I correct that the authors are building a complex ML model using only 3/6 input images? What is the goal of this analysis. As it stands, it reads a bit like simply wanting to apply some ML method to the data. Incidentally, the table in Fig. 6C is somewhat intransparent.

p. 22:<br /> "Our results indicate that the interaction of fasudil with αS residues governs the structural features of the protein."<br /> What results indicate this?

p. 23:<br /> The authors should add some (realistic) errors to the entropy values quoted. Fig. 8 have some error bars, though they seem unrealistically small. Also, is the water value quoted from the same force field and conditions as for the simulations?

p. 23:<br /> Has PDB2ENTROPY been validated for use with disordered proteins?

p. 23/24:<br /> It would be useful to compare (i) the free energies of the states (from their populations), (ii) the entropies (as calculated) and (iii) the enthalpies (as calculated e.g. as the average force field energy). Do they match up?

p. 31:<br /> It is unclear which previous simulation the new aSYN simulations were launched from. What is the size of the box used?

Reviewer #3 (Public Review):

Summary:

In this manuscript Menon, Adhikari, and Mondal analyze explicit solvent molecular dynamics (MD) computer simulations of the intrinsically disordered protein (IDP) alpha-synuclein in the presence and absence of a small molecule ligand, Fasudil, previously demonstrated to bind alpha-synuclein by NMR spectroscopy without inducing folding into more ordered structures. In order to provide insight into the binding mechanism of Fasudil the authors analyze an unbiased 1500us MD simulation of alpha-synuclein in the presence of Fasudil previously reported by Robustelli et.al. (Journal of the American Chemical Society, 144(6), pp.2501-2510). The authors compare this simulation to a very different set of apo simulations: 23 separate1-4us simulations of alpha-synuclein seeded from different apo conformations taken from another previously reported by Robustelli et. al. (PNAS, 115 (21), E4758-E4766), for a total of ~62us.

To analyze the conformational space of alpha-synuclein - the authors employ a variational auto-encoder (VAE) to reduce the dimensionality of Ca-Ca pairwise distances to 2 dimensions, and use the latent space projection of the VAE to build Markov state Models. The authors utilize k-means clustering to cluster the sampled states of alpha-synuclein in each condition into 180 microstates on the VAE latent space. They then coarse grain these 180 microstates into a 3-macrostate model for apo alpha-synuclein and a 6-macrostate model for alpha-synuclein in the presence of fasudil using the PCCA+ course graining method. Few details are provided to explain the hyperparameters used for PCCA+ coarse graining and the rationale for selecting the final number of macrostates.

The authors analyze the properties of each of the alpha-synuclein macrostates from their final MSMs - examining intramolecular contacts, secondary structure propensities, and in the case of alpha-synuclein:Fasudil holo simulations - the contact probabilities between Fasudil and alpha-synuclein residues.

The authors utilize an additional variational autoencoder (a denoising convolutional VAE) to compare denoised contact maps of each macrostate, and project onto an additional latent space. The authors conclude that their apo and holo simulations are sampling distinct regions of the conformational space of alpha-synuclein projected on the denoising convolutional VAE latent space.

Finally, the authors calculate water entropy and protein conformational entropy for each microstate. To facilitate water entropy calculations - the author's take a single structure from each macrostate - and ran a 20ps simulation at a finer timestep (4 femtoseconds) using a previously published method (DoSPT), which computes thermodynamic properties of water from MD simulations using autocorrelation functions of water velocities. The authors report that water entropy calculated from these individual 20ps simulations is very similar.

For each macrostate the authors compute protein conformational entropy using a previously published Maximum Information Spanning tree approach based on torsion angle distributions - and observe that the estimated protein conformational entropy is substantially more negative for the macrostates of the holo ensemble.

The authors calculate mean first passage times from their Markov state models and report a strong correlation between the protein conformational entropy of each state and the mean first passage time from each state to the highest populated state.

As the authors observe the conformational entropy estimated from macrostates of the holo alpha-synuclein:Fasudil is greater than those estimated from macrostates of the apo holo alpha-synuclein macrostates - they suggest that the driving force of Fasudil binding is an increase in the conformational entropy of alpha-synuclein. No consideration/quantification of the enthalpy of alpha-synuclein Fasudil binding is presented.

Strengths:

The author's utilize MD simulations run with an appropriate force field for IDPs (a99SB-disp and a99SB-disp water (Robustelli et. al, PNAS, 115 (21), E4758-E4766) - which has previously been used to perform MD simulations of alpha-synuclein that have been validated with extensive NMR data.

The contact probability between Fasudil and each alpha-synuclein residue observed in the previously performed 1500us MD simulation of alpha-synuclein in the presence of Fasudil (Robustelli et. al., Journal of the American Chemical Society, 144(6), pp.2501-2510) was previously found to be in good agreement with experimental NMR chemical shift perturbations upon Fasudil binding - suggesting that this simulation is a reasonable choice for understanding IDP:small molecule interactions.

Weaknesses:

Major Weakness 1: Simulations of apo alpha-synuclein and holo simulations of alpha-synuclein and fasudil are not comparable.

The most robust way to determine how presence of Fasudil affects the conformational ensemble of alpha-synuclein conclusions is to run apo and holo simulations of the same length from the same starting structures using the same simulation parameters.

The 23 1-4 us independent simulations of apo alpha-synuclein and the long unbiased 1500us alpha-synuclein in the presence of fasudil are not directly comparable. The starting structures of simulations used to build a Markov state model to describe apo alpha-synuclein were taken from a previously reported 73us MD simulation of alpha-synuclein run with the a99SB-disp force field and water model) with 100mM NaCl, (Robustelli et. al, PNAS, 115 (21), E4758-E4766). As the holo simulation of alpha-synuclein and Fasudil was run in 50mM NaCl, snapshots from the original apo alpha-synuclein simulation were resolvated with 50mM NaCl - and new simulations were run.

No justification is offered for how starting structures were selected. We have no sense of the conformational variability of the starting structures selected and no sense of how these conformations compare to the alpha-synuclein conformations sampled in the holo simulation in terms of standard structural descriptors such as tertiary contacts, secondary structure, radius of gyration (Rg), solvent exposed surface area etc. (we only see a comparison of projections on an uninterpretable non-linear latent-space and average contact maps). Additionally, 1-4 us is a relatively short timescale for a simulation of a 140 residue IDP- and one is unlikely to see substantial evolution for many structural properties of interest (ie. secondary structure, radius of gyration, tertiary contacts) in simulations this short. Without any information about the conformational space sample in the 23 apo simulations (aside from a projection on an uninterpretable latent space)- we have no way to determine if we observe transitions between distinct states in these short simulations, and therefore if it is possible the construct a meaningful MSM from these simulations.

If the structures used for apo simulations are on average more compact or contain more tertiary contacts - then it is unsurprising that in short independent simulations they sample a smaller region of conformational space. Similarly, if the starting structures have similar dimensions - but we only observe extremely local sampling around starting structures in apo simulations in the short simulation times - it would also not be surprising that we sample a smaller amount of conformational space. By only presenting comparisons of conformational states on an uninformative VAE latent space - it is not possible for a reader to ask simple questions about how the conformational ensembles compare.

It is noted that the authors attempt to address questions about sampling by building an MSM of single contiguous 60us portion of the holo simulation of alpha-synuclein and Fasudil - noting that:

"the MSM built using lesser data (and same amount of data as in water) also indicated the presence of six states of alphaS in presence of fasudil, as was observed in the MSM of the full trajectory. Together, this exercise invalidates the sampling argument and suggests that the increase in the number of metastable macrostates of alphaS in fasudil solution relative to that in water is a direct outcome of the interaction of alphaS with the small molecule."

However, the authors present no data to support this assertion - and readers have no sense of how the conformational space sampled in this portion of the trajectory compares to the conformational space sampled in the independent apo simulations or the full holo simulation. As the analyzed 60us portion of the holo trajectory may have no overlap with conformational space sampled in the independent apo simulations - it is unclear if this control provides any information. There is no quantification of the conformational entropy of the 6 states obtained from this portion of the holo trajectory or the full conformational space sampled. No information is presented to determine if we observe similar states in the shorter portion of the holo trajectory. Furthermore - as the authors provide almost no justification for the criteria used to select of the final number of macrostates for any of the MSMs reported in this work- and the number of macrostates is effectively a free parameter in the PCCA+ method, arriving at an MSM with 6 macrostates does not convey any information about the conformational entropy of alpha-synuclein in the presence or absence of ligands. Indeed - the implied timescale plot for 60us holo MSM (Figure S2) - shows that at least 10 processes are resolved in the 120 microstate model - and there is no information to provided explaining/justifying how a final 6-macrostate model was determined. The authors also do not project the conformations sampled in this sub- trajectory onto the latent space of the final VAE.

One certainly expects that an MSM built with 1/20th of the simulation data should have substantial differences from an MSM built from the full trajectory - so failing additional information and hyperparameter justification - one wonders if the emergence of a 6-state model could be the direct result of hardcoded VAE and MSM construction hyperparameter choices.

Required Controls For Supporting the Conclusions of the Study: The authors should initiate apo and holo simulations from the same starting structures - using the same simulation software and parameters. This could be done by adding a Fasudil ligand to the apo structures - or by removing the Fasudil ligand from a subset of holo structures. This would enable them to make apples-to-apples comparisons about the effect of Fasudil on alpha-synuclein conformational space.

Failing to add direct apples-to-apples comparisons, which would be required to truly support the studies conclusions, the authors should at least compare the conformational space sampled in the independent apo simulations and holo simulations using standard interpretable IDP order parameters (ie. Rg, end-to-end distance, secondary structure order parameters) and/or principal components from PCA or tICA obtained from the holo simulation. The authors should quantify the number of transitions observed between conformational states in their apo simulations. The authors could also perform more appropriate holo controls, without additional calculations, by taking batches of a similar number of short 1-4us segments of simulations used to compute the apo MSMs and examining how the parameters/macrostates of the holo MSMs vary with the input with random selections.

Major Weakness 2: There is little justification of how the hyperparameters MSMs were selected. It is unclear if the results of the study depend on arbitrary hyperparameter selections such as the final number of macrostates in each model.

It is unclear what criteria were used to determine the appropriate number of microstates and macrostates for each MSM. Most importantly - as all analyses of water entropy and conformational entropy are restricted to the final macrostates - the criteria used to select the final number of macrostates with the PCCA+ are extremely important to the results of the conclusions of the study. From examining the ITS plots in Figure 3 - it seems both MSMs show the same number of resolved processes (at least 11) - suggesting that a 10-state model could be apropraite for both systems. If one were to simply select a large number of macrostates for the 20x longer holo simulation - do these states converge to the same conformational entropy as the states seen in the short apo simulations? Is there some MSM quality metric used to determine what number of macrostates is more appropriate?

Required Controls For Supporting the Conclusions of the Study: The authors should specify the criteria used to determine the appropriate number of microstates and macrostates for their MSMs and present controls that demonstrate that the conformational entropies calculated for their final states are not simply a function of the ratio of the number macrostates chosen to represent very disparate amounts of conformational sampling.

Major Weakness 3: The use of variational autoencoders (VAEs) obscures insights into the underlying conformational ensembles of apo and holo alpha-synuclein rather than providing new ones.

No rationale is offered for the selection of the VAE architecture or hyperparameters used to reduce the dimensionality of alpha-synuclein conformational space.

It is not clear the VAEs employed in this study are providing any new insight into the conformational ensembles and binding mechanisms of Fasudil to alpha-synuclein, or if the underlying latent space of the VAEs are more informative or kinetically meaningful than standard linear dimensionality reduction techniques like PCA and tICA. The initial VAE is used to reduce the dimensionality of alpha-synuclein conformational ensembles to 2 degrees of freedom - but it is unclear if this projection is structurally or kinetically meaningful. It is not clear why the authors choice to use a 2-dimeinsional projection instead of a higher number of dimensions to build their MSMs. Can they produce a more kinetically and structurally meaningful model using a higher dimensional VAE latent space?

Additionally - it is not clear what insights are provided by the Denoising Convolutional Variational Autoencoder. The authors appear to be noising-and-denoising the contact maps of each macrostate, and then projecting the denoised values onto a new latent space - and commenting that they are different. Does this provide additional insight that looking at the contact maps in Figures 4&5 does not? Is this more informative than examining the distribution of the Radii of gyration or the secondary structure propensities of each ensemble? It is not clear what insight this analysis adds to the manuscript.

Suggested controls to improve the study: The authors should project interpretable IDP structural descriptors (ie. secondary structure, radius of gyration, secondary structure content, # of intramolecular contacts, # of intermolecular contacts between alpha-synuclein and Fasudil ) onto this latent space to illustrate if any of these properties are meaningful separated by the VAE projection. The authors should compare these projections, and MSMs built from these projections, to projections and MSMs built from projections using standard linear dimensionality projection techniques like PCA and tICA.

Major Weakness 4: The MSMs produced in this study have large discrepancies with MSMs previously produced on the same dataset by the same authors that are not discussed.

Previously - two of the authors of this manuscript (Menon and Mondal) authored a preprint titled "Small molecule modulates α-synuclein conformation and its oligomerization via Entropy Expansion" (https://www.biorxiv.org/content/10.1101/2022.10.20.513005v1.full) that analyzed the same 1500us holo simulation of alpha-synuclein binding Fasudil. In this study - they utilized the variational approach to Markov processes (VAMP) to build an MSM using a 1D order parameter as input (the radius of gyration), first discretizing the conformational space into 300 microstates before similarly building a 6 macrostate model. From examining the contact maps and secondary structure propensities of the holo MSMs from the current study and the previous study- some of the macrostates appear similar, however there appear to be orders of magnitude differences in the timescales of conformational transitions between the two models. The timescales of conformational transitions in the previous MSM are on the order of 10s of microseconds, while the timescales of transitions in this manuscript are 100s-1000s microseconds. In the previous manuscript, a 3 state MSM is built from an apo α-synuclein obtained from a continuous 73ms unbiased MD simulation of alpha-synuclein run at a different salt concentration (100mM) and an additional 33 ms of shorter simulations. The apo MSM from the previous study similarly reports very fast timescales of transitions between apo states (on the order ~1ms) - while the MSM reported in the current study (Figure 9) are on the order of 10s-100s of microseconds).

These discrepancies raise further concerns that the properties of the MSMs built on these systems are extremely sensitive to the chosen projection methods and MSM modeling choices and hyperparameters, and that neither model may be an accurate description of the true underlying dynamics

Suggestions to improve the study: The authors should discuss the discrepancies with the MSMs reported in their previous studies.

eLife assessment

This valuable study establishes a method for live-cell imaging, tracking, and quantification of Alu elements marking euchromatic regions of the nucleus. The method will help characterize the relationship between chromatin dynamics and transcriptional activity. While the findings are largely consistent with previous reports, characterization of the technique is incomplete and could benefit from additional controls.

Reviewer #1 (Public Review):

The manuscript from Chang et al. presents a new technique to track chromatin locus mobility in live cells, by specifically tracking Alu rich sequences using a CRISPR based technique. The experiments in Fig. 1-2 provide extensive validation of the reagent, and the experiments in Figs. 3-4 yield new insights into chromatin dynamics and its relationship to transcription. While the findings in this manuscript are interesting, some points need to be addressed to support the central claims.

One item of consideration is the use of bulk PIV methods to monitor chromatin mobility. While these whole genome methods certainly are useful for studying chromatin mobility at a diffraction limited (or higher scale) as well as tracking correlations at the micron scale, these methods obscure dynamics at the TAD/nucleosomal level (~200 nm). Since the studies use fluorescently labeled H2B to study chromatin dynamics, some consideration should be given to using Halo-tagged variants of H2B to get a single molecule view within specific chromatin contexts. A few recent studies (Saxton et al. 2023, Daugird et al. 2023) have used these methods to show how histone dynamics at the single molecule level depends on the chromatin context.

Secondly, there should be additional discussion of how the mean-squared network displacement relates to single locus and histone mobility at the sub-diffraction level. While it is reassuring to see that MSND and single particle tracking MSD exponents roughly agree at the sub-second time scale, how these relate at longer time scales is not clear. Figure S5A shows MSD for individual loci, but only timelags upto 1s are shown. It should be possible to track loci considerably longer than that. MSD exponents in the literature are quite varied beyond the second time-scale, and the authors have an excellent system to shed light on this question.

Finally, some additional discussion about why the transcriptional inhibition results shown here differ from other studies in the literature (e.g. Daugird et al. 2023) would better place these findings in context.

Reviewer #2 (Public Review):

Summary:

Chromatin organization and dynamics are critical for eukaryotic genome functions, but how are they related to each other? To address this question, Chang et al. developed a euchromatic labeling method using CRISPR/dCAS9 targeting Alu elements. These elements are highly enriched in the A compartment, which is closely associated with transcriptionally active and gene-rich regions. Labeling Alu elements allowed live-cell imaging of the gene-rich A compartment (euchromatin). Using the developed system, Chang et al. found while Alu-rich chromatin is depleted in regions with high chromatin density (putative heterochromatin), Alu density and chromatin density are not correlated in the euchromatin. Combining the live-cell imaging of Alu elements with bulk chromatin labeling (fluorescent histone H2B), the authors showed that transcriptionally active chromatin (A compartment) has an increased mobility. Transcription inhibitors flavopiridol and 𝛼-amanitin treatments increased the mobility of Alu-rich chromatin, and ActD had the opposite effect on chromatin mobility.

Strengths:

Alu labeling is a valuable euchromatin labeling method, and measuring its mobility would contribute to a comprehensive understanding of the relationship between chromatin dynamics and transcriptional activity.

Weaknesses:

Some of the findings are consistent with the previous reports and not new. There are some issues to be addressed. My specific comments are the following:

Line 58. "these methods generally lack information regarding the local chromatin environment (e.g., epigenetic state) and genomic context (e.g., A/B compartments and TADs)." This description is not accurate because Nozaki et al. (2023) performed euchromatin-specific nucleosome labeling/imaging (Hi-C contact domains with active histone marks, A-compartment). More recently, Semeigazin et al. (2024)(https://www.researchsquare.com/article/rs-3953132/v1) also did euchromatic-specific nucleosome labeling/imaging in living cells.

Line 154. "we defined the euchromatin regions in our images by excluding heterochromatin (top 5% pixel intensity) and nucleolar areas."<br /> I am not so sure that this definition is reasonable. How were the top 5% H2B intensity regions distributed? Did they include the nuclear periphery region, which is also heterochromatin-rich? Could the authors show the ΔPCC between whole H2B (including both euchromatin and heterochromatin) and dCas9-sgAlu?

Line 214. "our data suggests that Alu-rich (gene-rich) regions have increased chromatin mobility compared to Alu-poor (gene-poor) regions." A similar finding on nucleosome motion has already been published by Nozaki et al. 2023 and Semeigazin et al. 2024 (described above).

Line 282. A recent important paper on the relationship between histone acetylation, transcription initiation, and nucleosome mobility (PMID: 37792937) is missing and should be discussed.

Line 303. "Alu-rich chromatin may be more sensitive upon flavopiridol and 𝛼-amanitin treatments compared to Alu-poor chromatin (Figure 5)." Nagashima et al. (2019) also revealed that 𝛼-amanitin treatment did not increase the chromatin dynamics in heterochromatin-rich nuclear periphery regions.

Reviewer #3 (Public Review):

The manuscript by Chang, Quinodoz and Brangwynne describes the results of live cell imaging of fluorescently labeled Alu element genomic sites in combination with H2B-GFP marked chromatin in human cancer cells. The study includes dCas9 based genomic engineering for Suntag enhanced Alu element labeling. The motion of Alu elements and chromatin was analyzed in real time at 500 ms intervals over 1 min at high resolution. Advanced image analysis algorithms were developed.

The main objective of the study is to understand how motion of euchromatin or active chromatin relates to chromatin density. Alu elements, which are spread throughout the genome are used as a proxy for euchromatin or also A compartments. The study finds that Alu-rich chromatin is more mobile than Alu poor one and that actinomycin but not flavopyridol or alpha amanitin cause some decrease in the determined mobility. The authors emphasize the heterogeneity of motion, Alu clustering and chromatin density underscoring the complexity of the problem.

Although the topic is important and the imaging well performed, the study lacks depth and does not provide any truly new insights into our understanding of the link between genome activity and mobility nor diffusive behavior of the chromatin fiber in situ. Although the approach to record context dependent dynamics based on segmentation of pixels of varying intensity is elegant, the analysis of the trajectories requires further explanation and justification to be able to interpret the results. Important information on the biology of the engineered cell lines is lacking. Presented results are not discussed with respect to existing literature and knowledge.

Major concerns:<br /> - Are Alu elements a good proxy for A compartments? What consequences do massive dCas9 tags have on the genome and the engineered cells? How does the bulky dCas9-Suntag label impact mobility and transcription of Alu elements themselves? How many off target sites are potentially labeled?

(1) The authors should state the size of the dCas9-Suntag construct and perform FRAP analysis to compare the tag's behavior to the one of H2B-GFP<br /> (2) dCas9 locally unwinds DNA and is strongly bound to its target sequence impeding polymerase progression.<br /> (3) The authors need to check if DNA breaks are induced. An immunofluorescence using a gH2AX antibody is a minimum in all conditions tested. DNA breaks largely affect chromatin mobility which is a topic of major debate (see PMC5769766, PMID33061931).<br /> (4) The authors need to confirm that in dCas/sgAlu cells Alu elements are still transcribed similarly to wt cells (transcriptome or at least some qPCR).<br /> (5) Please compare H2B-GFP mobility of sgAlu tagged and untagged cells.<br /> (6) Figure 1D shows significant background in the Cut&run sgAlu line compared to H3K4me3 line. Are these off target sites? Was the H3K4me3 Cut&run performed in the engineered cell line? Did the authors test another guide RNA? Non-specific binding could also contribute to the observed heterogeneity in the measured dynamics.<br /> (7) Figure 3G shows that H2B MSND at tau=5s is high for high H2B density independently of Alu density questioning the value of using Alu sg tagging as a proxy for euchromatin.

- What are the physical principles of the measured motion? What is the rationale for the MSND analyses deployed in this study?<br /> (1) Please provide the equation used for MSND (seems to be different from the standard MSD one).<br /> (2) Figure 3: all MSD curves have a slope suggesting an alpha exponent significantly smaller than 0.5 reminiscent of subdiffusion (example panels A and E compare thick line to slope of the triangle bottom right). Please explain. Is it gaussian noise? Confinement? This was seen before for faster acquisition rates, but still requires explanation and interpretation.<br /> (3) What is the rationale for choosing the value at τ =5 s? Figure 3 panel E shows large variations in the MSND at all time points, curves do not start at the same lag time.<br /> (4) Figure S5 shows that for Alu elements, alpha is close to 0.5 at τ =<1 s but lower for larger tau, the relationship to intensity is inverse as well. Please explain.<br /> (5) It would be important to show the D values of your estimations. Plots for MSD curves in non log scale are important to be presented to show if there are different diffusion regimes (such as in Figure 4).<br /> (6) It is mentioned that the "Our measurements of total chromatin dynamics at lag time τ = 5 s are typically on the order of 10-2 μm2 (Figure 3 A, B), in agreement with past studies (Shaban et al., 2020; Zidovska et al., 2013)". This is inaccurate as both cited studies were performed at different time lags 0.2 sec. Change in time lag is supposed to show different diffusion behaviour. For consistency, the comparison should be done at the same time lag and the same number of analyzed video frames.<br /> (7) The study applies the MSND analysis for different time lags starting from 0.5 s to 11 s for videos of 60 s. Change in the number of data points affects the accuracy to calculate the diffusion coefficient. What is the impact of this uncertainty on the results and conclusions?

- Inhibition of polymerase 2 activity increases mobility as was shown before.<br /> (1) Figure 4: change in motion following alpha amanitin and Flavopiridol treatments recapitulate results from the Maeshima group (Nagashima 2019). Data shown for actinomycin treated cells appear extreme. A huge drop in H2B MSND (panel B and D). Please ensure that the cells are still alive after 4-6h exposure to ActD. ActD also affects cytoskeleton and replication, so different conclusion may be drawn if cells are still alive.<br /> (2) Treatment effects could also be enhanced should dCas9/ sgAlu induce massive DNA damage (see above). Check H2B-GFP motion in cells (both treated and not) not labeled with sgAlu.

- Positioning with respect to the literature:<br /> (1) The introduction, first paragraph is oversimplified, please review the literature citing work performed by many groups in the field using H2B-GFP, telomere or single site labeling in the past 10 years. Give details on the cell type used (mouse or human normal or cancer cells, amplified signals or single genes, same cell or cells at different stages of development, methodologies from whole genome to single particle tracking etc.).<br /> (2) The manuscript claims to introduce a novel mapping of the spatiotemporal dynamics of the A compartment in living cells. However, the authors did not discuss other previous approaches that were developed for the same purpose. The dynamic motion of active transcription chromatin domains/A compartment over the whole nucleus was investigated in different studies that used Mintbody labeling, please check PMCID: PMC7926250, PMCID: PMC8647360, PMID: 27534817, PMCID: PMC8491620<br /> (3) PIV applies a relatively large interrogation window size of micrometers to estimate the displacement vectors. Dynamic changes within the set window can include both A and B compartments, where the contribution of genomic processes to local chromatin motion, typically taking place at the nanometer scale, is missed. The Hi-D method ( PMCID: PMC7168861) introduced an Optical Flow approach to overcome this limitation of PIV (PMCID: PMC6061878 ). Could the authors test if Hi-D method to analyze the movies recorded in this study confirms their conclusions?

Heterogeneity of chromatin dynamics independent of chromatin density was shown by previous studies such as PMCID: PMC7775763 , and PMCID: PMC7168861 . Could the authors discuss their findings in the context of these studies?

Author response:

We thank the reviewers for their positive feedback and helpful suggestions for improving our manuscript.

We appreciate the reviewers highlighting areas where we can improve clarity, particularly in the analysis methodologies and details. We agree that additional control experiments and expansion on single-molecule tracking analysis will provide additional support for our interpretations. 

We acknowledge the reviewers' suggestion to describe our work's relationship to other studies. While some of our findings are similar to those in past studies, our work introduces a new approach for labeling euchromatin with direct sequence specificity on a genome-wide scale, enabling a deeper understanding of euchromatin organization and dynamics. We will provide more context on the novelty of our work and incorporate a more comprehensive discussion of our work’s relation to other studies in the manuscript.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors use the model organism Drosophila to explore the sex and age impacts of a TBI method. They find age and sex differences: older age is susceptible to mild TBI and females are also more susceptible. In particular, they pursue a finding that virgin vs mated females show different responses: virgins are protected but mated females succumb to TBI with climbing deficits. In fact, virgin females compared to mated females are largely protected. They discover that this is associated with exposure of the females to Sex Peptides in the reproductive neurons of the female reproductive tract. When they extend to RNAseq of brains, they show that there are very few genes in common between males, mated females, virgins and females mated with males lacking Sex Peptide. The few chronic genes associated with mated females seem associated with the immune system. These findings suggest that mated females have a compromised immune system, which might make them more vulnerable.

Strengths:

This is an interesting paper that allows a detailed comparison of sex and age in TBI which is largely only possible in such a simple model, where large numbers and many variations can be addressed. Overall the findings are interesting.

Weaknesses:

Although the findings beyond Sex Peptide are observational, the work sets the stage for more detailed studies to pursue the role of the genes they find by RNAseq and whether for example, boosting the innate immune system would protect the mated females, among other experiments.

eLife assessment

In the current study, the authors describe how sex and age affect the consequence of traumatic brain injury in Drosophila. They find that females are more sensitive than males, and mated females are sensitive whereas virgin females are not. This fundamental work substantially advances our understanding of how sex-dependent response to traumatic brain injury occurs, by identifying the Sex Peptide and the immune system as modulators of sex differences. The authors provide a compelling set of results, showing that female Sex Peptide signaling in Drosophila adversely affects late-life neurodegeneration after early-life exposure to repetitive mild head injury.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors use the Drosophila model system to study the impact of mild head trauma on sex-dependent brain deficits. They identify Sex Peptide as a modulator of greater negative outcome in female flies. Additionally, they observe that increased age at the time of injury results in worse outcomes, especially in females, and that this is due to chronic suppression of innate immune defense networks in mated females. The results demonstrate a novel signaling pathway that promotes age- and sex-dependent outcomes after head injury.

Strengths:

The authors have modified their previously reported TBI model in flies to mimic mild TBI, which is novel. Methods are explained in detail, allowing for reproducibility. Experiments are rigorous with appropriate statistics. A number of important controls are included. The work tells a complete mechanistic story and adds important data to increase our understanding of sex-dependent differences in recovery after TBI. The discussion is comprehensive and puts the work in the context of the field.

Weaknesses:

A very minor weakness is that exact n values should be included in the figure legends. There should also be confirmation of knockdown by RNAi in female flies either by immunohistochemistry or qRT-PCR if possible.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors used a Drosophila model to show that exposure to repetitive mild TBI causes neurodegenerative conditions that emerge late in life and disproportionately affect females. In addition to well-known age-dependent impact, the authors identified Sex Peptide (SP) signaling as a key factor in female susceptibility to post-injury brain deficits.

Strengths:

The authors have presented a compelling set of results showing that female Sex Peptide signaling adversely affects late-life neurodegeneration after early-life exposure to repetitive mild head injury in Drosophila. They have (1) compared the phenotypes of adult male and female flies sustaining TBI at different ages, and the phenotypes of virgin females and mated females, (2) compared the phenotypes of eliminating SP signaling in mating females and introducing SP-signaling into virgin females, (3) compared transcriptomic changes of different groups in response to TBI. The results are generally consistent and robust.

Weaknesses:

The authors have made their claims largely based on assaying climbing index and vacuole formation as the only indicators of late-life neurodegeneration after TBI. However, these phenotypes are not really specific to TBI-related neurodegeneration, and the significance and mechanisms of especially vacuole formation are not clear. The authors should perform additional analyses on TBI-related neurodegeneration in flies, which have been shown before (Genetics. 2015 Oct; 201(2): 377-402). Furthermore, it is also really surprising to see so few DEGs even in wild-type males and mated females, and to see that none of the DEGs overlapped among groups or are even related to the SP-signaling. This raises questions about the validity of the RNA-seq analysis. It is critical to independently verify their RNA-sequencing results and to add some more molecular evidence to support their conclusion. Finally, it is unknown what the implication of female fly mating and its associated Sex Peptide signaling would be to mammalians or humans, and what are the mechanisms underlying the sexual dimorphism.

Author response:

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors use the model organism Drosophila to explore the sex and age impacts of a TBI method. They find age and sex differences: older age is susceptible to mild TBI and females are also more susceptible. In particular, they pursue a finding that virgin vs mated females show different responses: virgins are protected but mated females succumb to TBI with climbing deficits. In fact, virgin females compared to mated females are largely protected. They discover that this is associated with exposure of the females to Sex Peptides in the reproductive neurons of the female reproductive tract. When they extend to RNAseq of brains, they show that there are very few genes in common between males, mated females, virgins and females mated with males lacking Sex Peptide. The few chronic genes associated with mated females seem associated with the immune system. These findings suggest that mated females have a compromised immune system, which might make them more vulnerable.

Strengths:

This is an interesting paper that allows a detailed comparison of sex and age in TBI which is largely only possible in such a simple model, where large numbers and many variations can be addressed. Overall the findings are interesting.

Weaknesses:

Although the findings beyond Sex Peptide are observational, the work sets the stage for more detailed studies to pursue the role of the genes they find by RNAseq and whether for example, boosting the innate immune system would protect the mated females, among other experiments.

We thank the reviewer for their time and effort in evaluating our manuscript. We agree that future studies are needed to further determine the role of the genes that we have identified through RNA sequencing in the late life emergence of neurodegenerative conditions after the exposure to mild head trauma. We would like to investigate whether elevating mated female immunity can mitigate the risk for age-dependent neurodegeneration after mild head trauma.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors use the Drosophila model system to study the impact of mild head trauma on sex-dependent brain deficits. They identify Sex Peptide as a modulator of greater negative outcome in female flies. Additionally, they observe that increased age at the time of injury results in worse outcomes, especially in females, and that this is due to chronic suppression of innate immune defense networks in mated females. The results demonstrate a novel signaling pathway that promotes age- and sex-dependent outcomes after head injury.

Strengths:

The authors have modified their previously reported TBI model in flies to mimic mild TBI, which is novel. Methods are explained in detail, allowing for reproducibility. Experiments are rigorous with appropriate statistics. A number of important controls are included. The work tells a complete mechanistic story and adds important data to increase our understanding of sex-dependent differences in recovery after TBI. The discussion is comprehensive and puts the work in the context of the field.

Weaknesses:

A very minor weakness is that exact n values should be included in the figure legends. There should also be confirmation of knockdown by RNAi in female flies either by immunohistochemistry or qRT-PCR if possible.

We thank the reviewer for the evaluation of our manuscript and for the suggestion to include the exact n values in the figure legends. We will include the n values in our revision.

Regarding RNAi knockdown of sex peptide receptors (SPRs), we agree that confirmation of the knockdown by IHC or qRT-PCR will further strengthen our findings.  It should be noted, however, that the RNAi line we used has been extensively validated by Yapici et al., 2007 and several subsequent publications. Importantly, the effectiveness of SPR knockdown is evident in female flies as they exhibit dramatically reduced egg laying and, importantly, lack the typical post-mating behaviors (such as rejection of male flies after initial mating) observed in the wild type mated female flies. In fact, female flies with RNAi-mediated SPR knockdown behave identically to females mated with SP-null male flies, confirming the effective disruption of the SP-SPR signaling pathway. We will revise the manuscript to make these points clear. 

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors used a Drosophila model to show that exposure to repetitive mild TBI causes neurodegenerative conditions that emerge late in life and disproportionately affect females. In addition to well-known age-dependent impact, the authors identified Sex Peptide (SP) signaling as a key factor in female susceptibility to post-injury brain deficits.

Strengths:

The authors have presented a compelling set of results showing that female Sex Peptide signaling adversely affects late-life neurodegeneration after early-life exposure to repetitive mild head injury in Drosophila. They have (1) compared the phenotypes of adult male and female flies sustaining TBI at different ages, and the phenotypes of virgin females and mated females, (2) compared the phenotypes of eliminating SP signaling in mating females and introducing SP-signaling into virgin females, (3) compared transcriptomic changes of different groups in response to TBI. The results are generally consistent and robust.

Weaknesses:

The authors have made their claims largely based on assaying climbing index and vacuole formation as the only indicators of late-life neurodegeneration after TBI. However, these phenotypes are not really specific to TBI-related neurodegeneration, and the significance and mechanisms of especially vacuole formation are not clear. The authors should perform additional analyses on TBI-related neurodegeneration in flies, which have been shown before (Genetics. 2015 Oct; 201(2): 377-402). Furthermore, it is also really surprising to see so few DEGs even in wild-type males and mated females, and to see that none of the DEGs overlapped among groups or are even related to the SP-signaling. This raises questions about the validity of the RNA-seq analysis. It is critical to independently verify their RNA-sequencing results and to add some more molecular evidence to support their conclusion. Finally, it is unknown what the implication of female fly mating and its associated Sex Peptide signaling would be to mammalians or humans, and what are the mechanisms underlying the sexual dimorphism.

We thank the reviewer for the thorough evaluation of our manuscript. The reviewer raised a very important question: whether the neurodegeneration observed in our model is specific to TBI. As the reviewer rightly pointed out, the neurodegenerative phenotypes are unlikely specific to TBI-related neurodegeneration. Throughout the manuscript, we have tried to convey the notion that the mild physical impacts to the head represent one form of environmental insults, which in combination with other risk factors such as aging can lead to the emergence of neurodegenerative conditions. It should be noted that the negative geotaxis assay and vacuolation quantification are two well-established approaches to assess sensorimotor deficits and frank brain degeneration in fly brains.

It is important to emphasize that the head-specific impacts delivered to the flies in our study are much milder than those used in previous studies. As we showed in our figure 1, this very mild form of head trauma (referred to as vmHT) did not cause any death, nor affected the lifespan of the injured flies. Our supplemental data also show very minimal structural neuronal damage and essentially no acute and chronic apoptosis induced by vmHT exposure. Consistently, we did not observe any exoskeletal or eye damage immediately following injuries, nor did we observe any retinal degeneration and pseudopupil loss at the chronic stage of these flies. We will incorporate these important points in the revision. 

We agree that future studies are needed to independently validate our RNA sequencing results. We believe that the small number of DEGs are likely due to two unique features of our study: (1) the very mild nature of our injury paradigm and (2) the chronic examination timepoint that was long after the head injury and SP exposure, which distinguish our study from previous fly TBI studies.  As pointed out in the manuscript, our study was aimed to understand how early life exposure to repetitive head traumatic insults could lead to the late-life onset of neurodegenerative conditions. We hope to further validate our results in our next phase of experiments using single-cell RNA sequencing and RT-qPCR.

As the reviewer pointed out, it would be very interesting to explore the possible roles of sex peptide-signaling in other animals and humans. As far as we know, there is no known mammalian ortholog to the insect sex peptide, so it would be difficult to study SP or an SP-like molecule in mammalian models. However, we believe that prolonged post-mating changes associated with reproduction in female fruit flies contribute to their elevated vulnerability to neurodegeneration.  In this regard, drastic changes within the biology of female mammals associated with reproduction can potentially lead to vulnerability to neurodegeneration. We agree that this demands further study, which may be done with future collaborators using rodent or large animal models.  We have discussed this point in the manuscript, but will revise it to further clarify the discussion.

eLife assessment

The authors show in vitro that TAK1 overexpression reduces tumor cell migration and invasion, while TAK1 knockdown promotes a mesenchymal phenotype and enhances migration and invasion. The work is a valuable addition to the field of tumor biology of esophageal squamous cell carcinoma. Although minor limitations exist, the overall evidence is solid. The data aligns with previous findings by the same researchers and others.

Reviewer #1 (Public Review):

Summary:

In previously published work, the authors found that Transforming Growth Factor β Activated Kinase 1 (TAK1) may regulate esophageal squamous cell carcinoma (ESCC) tumor cell proliferation via the RAS/MEK/ERK axis. They explore the mechanisms for TAK1 as a possible tumor suppressor, demonstrating phospholipase C epsilon 1 as an effector of tumor cell migration, invasion and metastatic potential.

Strengths:

The authors show in vitro that TAK1 overexpression reduces tumor cell migration and invasion while TAK1 knockdown promotes a mesenchymal phenotype (epithelial-mesenchymal transition) and enhances migration and invasion. To explore possible mechanisms of action, the authors focused on phospholipase C epsilon 1 (PLCE1) as a potential effector, having identified this protein in co-immunoprecipitation experiments. Further, they demonstrate that TAK1-mediated phosphorylation of PLCE1 is inhibitory. Each of the observations is supported by different experimental strategies, e.g. use of different approaches for knockdown (pharmacologic, RNA inhibition, CRISPR/Cas). Xenograft experiments showed that suppression/loss of TAK1 is associated with more frequent metastases and conversely that PLCE1 is associated positively with xenograft metastases. A considerable amount of experimental data is presented for review, including supplemental data, that show that TAK1 regulation may be important in ESCC development.

Weaknesses:

As noted by the authors, immunoprecipitation (IP) experiments identified a number (24) of proteins as potential targets for the TAK1 ser/thr kinase. Prior work (cited as Shi et al, 2021) focused on a different phosphorylation target for TAK1, Ras association domain family 9 (RASSF9), but a more comprehensive discussion of the co-IP experiments would help place this work in a better context.

Reviewer #2 (Public Review):

Summary:

In this study, Ju Q et al performed both in vitro and in vivo experiments to test the effect of TAK1 on cancer metastasis. They demonstrated that TAK1 is capable of directly phosphorylating PLCE1 and this modification represses its enzyme activity, leading to suppression of PIP2 hydrolysis and subsequently signal transduction in the PKC/GSK-3β/β-Catenin axis.

Strengths:

The quality of data is good, and the presentation is well organized in a logical way.

Weaknesses:

The study missed some key link in connecting the effect of TAK1 on cancer metastasis via phosphorylating PLCE1.

Reviewer #3 (Public Review):

Summary:

The research by Qianqian Ju et al. found that the knockdown of TAK1 promoted ESCC migration and invasion, whereas overexpression of TAK1 resulted in the opposite outcome. These in vitro findings could be recapitulated in a xenograft metastasis mouse model.

Mechanistically, TAK1 phosphorylates PLCE1 S1060 in the cells, decreasing PLCE1 enzyme activity and repressing PIP2 hydrolysis. As a result, reducing DAG and inositol IP3, thereby suppressing signal transduction of PKC/GSK 3β/β Catenin. Consequently, cancer metastasis-related genes were impeded by TAK1.

Overall, this study offers some intriguing observations. Providing a potential druggable target for developing agents for dealing with ESCC.

The strengths of this research are:

(1) The research always uses different experimental approaches to address one question. The experiments are largely convincing and appear to be well executed.<br /> (2) The phenotypes were observed from different angles: at the mouse model, cellular level, and molecular level.<br /> (3) The molecular mechanism was down to a single amino acid modification on PLCE1.

The weaknesses part of this research are:

(1) Most of the phenotypes are only observed in the ECA-109 cell line. Whether TAK1-PLCE1 S1060 is a common pathway in other ESCC cells or just specific to the ECA-109 cell line is unclear. Using more cell lines to see whether this is a common mechanism of ESCC metastasis would greatly amplify the impact of this finding.<br /> (2) Most of the experiments were done in protein overexpression conditions, with the protein level increasing hundreds of folds in the cell, producing an artificial environment that would sometimes generate false positive results.<br /> (3) Whether TAK1 can directly phosphorylate PLCE1 S1060 needs more tests, especially the in vitro biochemical evidence.

sure it does

coming back to re-read it after 5 years

eLife assessment

This manuscript describes an AI-automated microscopy-based approach to characterize both bacterial and host cell responses associated with Shigella infection of epithelial cells. The methodology is compelling and should be helpful for investigators studying a variety of intracellular pathogens. The authors have acquired valuable findings regarding host and bacterial responses in the context of infection, which should be followed up with further mechanistic-based studies.

Reviewer #1 (Public Review):

Summary:

In this study, López-Jiménez and colleagues demonstrated the utility of using high-content microscopy in dissecting host and bacterial determinants that play a role in the establishment of infection using Shigella flexneri as a model. The manuscript nicely identifies that infection with Shigella results in a block to DNA replication and protein synthesis. At the same time, the host responds, in part, via the entrapment of Shigella in septin cages.

Strengths:

The main strength of this manuscript is its technical aspects. They nicely demonstrate how an automated microscopy pipeline coupled with artificial intelligence can be used to gain new insights regarding elements of bacterial pathogenesis, using Shigella flexneri as a model system. Using this pipeline enabled the investigators to enhance the field's general understanding regarding the role of septin cages in responding to invading Shigella. This platform should be of interest to those who study a variety of intracellular microbial pathogens.

Another strength of the manuscript is the demonstration - using cell biology-based approaches- that infection with Shigella blocks DNA replication and protein synthesis. These observations nicely dovetail with the prior findings of other groups. Nevertheless, their clever click-chemistry-based approaches provide visual evidence of these phenomena and should interest many.

Weaknesses:

There are two main weaknesses of this work. First, the studies are limited to findings obtained using a single immortalized cell line. It is appreciated that HeLa cells serve as an excellent model for studying aspects of Shigella pathogenesis and host responses. However, it would be nice to see that similar observations are observed with an epithelial cell line of intestinal, preferably colonic origin, and eventually, with a non-immortalized cell line, although it is appreciated that the latter studies are beyond the scope of this work.

The other weakness is that the studies are minimally mechanistic. For example, the investigators have data to suggest that infection with Shigella leads to an arrest in DNA replication and protein synthesis; however, no follow-up studies have been conducted to determine how these host cell processes are disabled. Interestingly, Zhang and colleagues recently identified that the Shigella OspC effectors target eukaryotic translation initiation factor 3 to block host cell translation (PMID: 38368608). This paper should be discussed and cited in the discussion.

Reviewer #2 (Public Review):

Summary:

Septin caging has emerged as one of the innate immune responses of eukaryotic cells to infections by intracellular bacteria. This fascinating assembly of eukaryotic proteins into complex structures restricts bacteria motility within the cytoplasm of host cells, thereby facilitating recognition by cytosolic sensors and components of the autophagy machinery. Given the different types of septin caging that have been described thus far, a single-cell, unbiased approach to quantify and characterise septin recruitment at bacteria is important to fully grasp the role and function of caging. Thus, the authors have developed an automated image analysis pipeline allowing bacterial segmentation and classification of septin cages that will be very useful in the future, applied to study the role of host and bacterial factors, compare different bacterial strains, or even compare infections by clinical isolates.

Strengths:

The authors developed a solid pipeline that has been thoroughly validated. When tested on infected cells, automated analysis corroborated previous observations and allowed the unbiased quantification of the different types of septin cages as well as the correlation between caging and bacterial metabolic activity. This approach will prove an essential asset in the further characterisation of septin cages for future studies.

Weaknesses:

As the main aim of the manuscript is to describe the newly developed analysis pipeline, the results illustrated in the manuscript are essentially descriptive. The developed pipeline seems exceptionally efficient in recognising septin cages in infected cells but its application for a broader purpose or field of study remains limited.

Reviewer #3 (Public Review):

Summary:

The manuscript uses high-content imaging and advanced image-analysis tools to monitor the infection of epithelial cells by Shigella. They perform some analysis on the state of the cells (through measurements of DNA and protein synthesis), and then they focus on differential recruitment of Sept7 to the bacteria. They link this recruitment with the activity of the bacterial T3SS, which is a very interesting discovery. Overall, I found numerous exciting elements in this manuscript, and I have a couple of reservations. Please see below for more details on my reservations. Nevertheless, I think that these issues can be addressed by the authors, and doing so will help to make it a convincing and interesting piece for the community working on intracellular pathogens. The authors should also carefully re-edit their manuscript to avoid overselling their data (see below for issues I see there). I would consider taking out the first figure and starting with Figure 3 (Figure 2 could be re-organized in the later parts)- that could help to make the flow of the manuscript better.

Strengths:

The high-content analysis including the innovative analytical workflows are very promising and could be used by a large number of scientists working on intracellular bacteria.

The finding that Septins (through SEPT7) are differentially regulated through actively secreting bacteria is very exciting and can steer novel research directions.

Weaknesses:

The manuscript makes a connection between two research lines (1: Shigella infection and DNA/protein synthesis, 2: regulation of septins around invading Shigella) that are not fully developed - this makes it sometimes difficult to understand the take-home messages of the authors.

It is not clear whether the analysis that was done on projected images actually reflects the phenotypes of the original 3D data. This issue needs to be carefully addressed.

Author response:

Reviewer #1 (Public Review):

Summary:

In this study, López-Jiménez and colleagues demonstrated the utility of using high-content microscopy in dissecting host and bacterial determinants that play a role in the establishment of infection using Shigella flexneri as a model. The manuscript nicely identifies that infection with Shigella results in a block to DNA replication and protein synthesis. At the same time, the host responds, in part, via the entrapment of Shigella in septin cages.

Strengths:

The main strength of this manuscript is its technical aspects. They nicely demonstrate how an automated microscopy pipeline coupled with artificial intelligence can be used to gain new insights regarding elements of bacterial pathogenesis, using Shigella flexneri as a model system. Using this pipeline enabled the investigators to enhance the field's general understanding regarding the role of septin cages in responding to invading Shigella. This platform should be of interest to those who study a variety of intracellular microbial pathogens.

Another strength of the manuscript is the demonstration - using cell biology-based approaches- that infection with Shigella blocks DNA replication and protein synthesis. These observations nicely dovetail with the prior findings of other groups. Nevertheless, their clever click-chemistry-based approaches provide visual evidence of these phenomena and should interest many.

We thank the Reviewer for their enthusiasm on the technical aspects of this paper, regarding both the automated microscopy pipeline coupled with artificial intelligence and the click-chemistry based approaches to dissect DNA replication and protein synthesis by microscopy.

Weaknesses:

There are two main weaknesses of this work. First, the studies are limited to findings obtained using a single immortalized cell line. It is appreciated that HeLa cells serve as an excellent model for studying aspects of Shigella pathogenesis and host responses. However, it would be nice to see that similar observations are observed with an epithelial cell line of intestinal, preferably colonic origin, and eventually, with a non-immortalized cell line, although it is appreciated that the latter studies are beyond the scope of this work.

The immortalized cell line HeLa is widely regarded as a paradigm to study infection by Shigella and other intracellular pathogens. However, we agree that future studies beyond the scope of this work should include other cell lines (eg. epithelial cells of colonic origin, macrophages, primary cells). 

The other weakness is that the studies are minimally mechanistic. For example, the investigators have data to suggest that infection with Shigella leads to an arrest in DNA replication and protein synthesis; however, no follow-up studies have been conducted to determine how these host cell processes are disabled. Interestingly, Zhang and colleagues recently identified that the Shigella OspC effectors target eukaryotic translation initiation factor 3 to block host cell translation (PMID: 38368608). This paper should be discussed and cited in the discussion.

We appreciate the Reviewer’s concern about the lack of follow up work on observations of host DNA and protein synthesis arrest upon Shigella infection, which will be the focus of future studies. We acknowledge the recent work of Zhang et al. (Cell Reports, 2024) considering their similar results on protein translation arrest, and we fully agree that this reference should be more fully discussed in a revised version of the manuscript.

Reviewer #2 (Public Review):

Summary:

Septin caging has emerged as one of the innate immune responses of eukaryotic cells to infections by intracellular bacteria. This fascinating assembly of eukaryotic proteins into complex structures restricts bacteria motility within the cytoplasm of host cells, thereby facilitating recognition by cytosolic sensors and components of the autophagy machinery. Given the different types of septin caging that have been described thus far, a single-cell, unbiased approach to quantify and characterise septin recruitment at bacteria is important to fully grasp the role and function of caging. Thus, the authors have developed an automated image analysis pipeline allowing bacterial segmentation and classification of septin cages that will be very useful in the future, applied to study the role of host and bacterial factors, compare different bacterial strains, or even compare infections by clinical isolates.

Strengths:

The authors developed a solid pipeline that has been thoroughly validated. When tested on infected cells, automated analysis corroborated previous observations and allowed the unbiased quantification of the different types of septin cages as well as the correlation between caging and bacterial metabolic activity. This approach will prove an essential asset in the further characterisation of septin cages for future studies.

We thank the Reviewer for their positive comments, and for highlighting the strength of our imaging and analysis pipeline to analyse Shigella-septin interactions.

Weaknesses:

As the main aim of the manuscript is to describe the newly developed analysis pipeline, the results illustrated in the manuscript are essentially descriptive. The developed pipeline seems exceptionally efficient in recognising septin cages in infected cells but its application for a broader purpose or field of study remains limited.

The main objective of this manuscript is the development of imaging and analysis tools to study Shigella infection, and in particular, Shigella interactions with the septin cytoskeleton. In future work we will provide more mechanistic insight with novel experiments and broader applicability, using different cell lines (in agreement with Reviewer 1), mutants or clinical isolates of Shigella and different bacteria species (eg. Listeria, Salmonella, mycobacteria).

Reviewer #3 (Public Review):

Summary:

The manuscript uses high-content imaging and advanced image-analysis tools to monitor the infection of epithelial cells by Shigella. They perform some analysis on the state of the cells (through measurements of DNA and protein synthesis), and then they focus on differential recruitment of Sept7 to the bacteria. They link this recruitment with the activity of the bacterial T3SS, which is a very interesting discovery. Overall, I found numerous exciting elements in this manuscript, and I have a couple of reservations. Please see below for more details on my reservations. Nevertheless, I think that these issues can be addressed by the authors, and doing so will help to make it a convincing and interesting piece for the community working on intracellular pathogens. The authors should also carefully re-edit their manuscript to avoid overselling their data (see below for issues I see there). I would consider taking out the first figure and starting with Figure 3 (Figure 2 could be re-organized in the later parts)- that could help to make the flow of the manuscript better.

Strengths:

The high-content analysis including the innovative analytical workflows are very promising and could be used by a large number of scientists working on intracellular bacteria. The finding that Septins (through SEPT7) are differentially regulated through actively secreting bacteria is very exciting and can steer novel research directions.

We thank the Reviewer for their constructive feedback and the excitement for our results, including our findings on T3SS activity and Shigella-septin interactions_._ In accordance with the Reviewer’s comments, we agree to carefully re-edit our manuscript to avoid overselling our data in a future version of the manuscript. We will also consider to rearrange figures depending on new results.

Weaknesses:

The manuscript makes a connection between two research lines (1: Shigella infection and DNA/protein synthesis, 2: regulation of septins around invading Shigella) that are not fully developed - this makes it sometimes difficult to understand the take-home messages of the authors.

We agree that the manuscript is mostly technical and therefore some of our experimental observations would benefit from follow up mechanistic studies in the future. We highlight our vision for broader applicability in response to weaknesses raised by Reviewer 2.

It is not clear whether the analysis that was done on projected images actually reflects the phenotypes of the original 3D data. This issue needs to be carefully addressed.

We agree with the Reviewer that characterizing 3D data using 2D projected images has limitations.

We observe an increase in cell and nuclear surface that does not strictly imply a change in volume. This is why we measure Hoechst intensity in the nucleus using SUM-projection (as it can be used as a proxy of DNA content of the cell). However, we agree that future use of other markers (such as fluorescent labelled histones) would make our conclusions more robust.

Regarding the different orientation of intracellular bacteria, we agree that investigation of septin recruitment is more challenging when bacteria are placed perpendicular to the acquisition plane. In a first step, we trained a Convolutional Neural Network (CNN) using 2D data, as it is easier/faster to train and requires fewer annotated images. In doing so, we already managed to correctly identify 80% of Shigella interacting with septins, which enabled us to observe higher T3SS activity in this population. In future studies, we will maximize the 3D potential of our data and retrain a CNN that will allow more precise identification of Shigella-septin interactions and in depth characterization of volumetric parameters.

eLife assessment

This valuable work characterized a new set of small molecules targeting the interaction between ELF3-MED23, with one of the reported compounds representing a promising novel therapeutic strategy, The evidence supporting the conclusions is solid, although including characterization with breast and lung cancer cell models would strengthen the study. This article will be of interest to medical and cell biologists working on cancer and, particularly, on HER2-overexpression cancers.

Reviewer #1 (Public Review):

Summary:

Soo-Yeon Hwang et al. synthesized and characterized a new set of small molecules targeting the interaction between ELF3-MED23, the transcription factor, and a coactivator for HER2 transcription, respectively. The authors used a combination of biochemical analysis, cell-based assays, and an in vivo xenograft model to prove that the lead compound 10 inhibits the HER2 transcription and protein expression levels, subsequently inducing anticancer activity in the gastric cancer cell line, the xenograft model, particularly in the trastuzumab-resistant cell line. The experiential data is solid and supports the model for the anticancer potency of the compound for the HER2+ gastric cancer model. Although the compound showed promising data for its potential antitumor activity for HER2+ cancers, it is a little bit narrow to the HER2+ cancer field since the most relevant HER2+ cancer model is HER2+ breast cancer and the Herceptin-resistance, indeed the author also discussed this point in the manuscript. Therefore, additional data with the breast cancer HER2+ cell model will help to impact the work in the field.

Strengths:

The current manuscript proposed a potential alternative strategy targeting HER2 overexpression cancers by attenuating HER2 transcription levels. The study provides solid evidence that the lead compound 10 can interrupt the binding of ELF3 to MED23, leading to the inhibition of HER2 transcription. Remarkably, the following cell-based assays and xenograft model revealed the promising antitumor activity of the compound in the gastric cancer model.

Weaknesses:

While the novel compound showed a promising potency to the HER2-positive gastric cancer cells and xenograft model, it would be great to also to be evaluated with the HER2-positive breast cancer cell models. The author did not compare the current compounds with other therapeutic strategies targeting HER2 expression at the genetic level. It is unclear whether the EGFR inhibitors gefitinib and canertinib but not HER2-specific inhibitors (i.e. tucatinib) were used as a control in the manuscript.

Reviewer #2 (Public Review):

Summary:

The findings highlight the importance of targeting the ELF3-MED23 protein-protein interaction (PPI) as a potential therapeutic strategy for HER2-overexpressing cancers, notably gastric cancers, as an alternative to trastuzumab. The evidence, including the strong potency of compound 10 in inhibiting ELF3-MED23 PPI, its capacity to lower HER2 levels, induce apoptosis, and impede proliferation both in laboratory settings and animal models, indicates that compound 10 holds promise as a novel therapeutic option, even for cases resistant to trastuzumab treatment.

Strengths:

The experiments conducted are robust and diverse enough to address the hypothesis posed.

Weaknesses:

The rationale behind the proposed structural modifications for the three groups of compounds is not clear.

Reviewer #3 (Public Review):

Summary:

The authors synthesized a compound which can inhibit ELF3 and MED23 interaction which leads to inhibition of HER2 expression in gastric cancer.

Strengths:

Enough evidence shows the potency of compound 10 in inhibiting ELF3 and MED23 interaction.

Weaknesses:

Compound 10 potency as PPI inhibitor has been shown in only one cell line NCI-N87.

eLife assessment

This manuscript describes a method for genetic manipulation of Leishmania species which should be sufficiently efficient to enable genome-wide genetic screens. The authors improved numerous aspects of their previously described method, which is based on sequence-specific genome editing to introduce premature stop codons using a CAS9-cytidine deaminase variant. The work is thoroughly described, with convincing data, and will be very important for Leishmania researchers, as well as perhaps suggesting the use of similar approaches in other organisms in which genetic manipulation is challenging.

Reviewer #1 (Public Review):

While CRISPR/Cas technology has greatly facilitated the ability to perform precise genome edits in Leishmania spp., the lack of a non-homologous DNA end-joining (NHEJ) pathway in Leishmania has prevented researchers from performing large-scale Cas-based perturbation screens. With the introduction of base editing technology to the Leishmania field, the Beneke lab has begun to address this challenge (Engstler and Beneke, 2023).

In this study, the authors build on their previously published protocols and develop a strategy that:

(1) allows for very high editing efficiency. The cell editing frequency of 1 edit per 70 cells reported in this study represents a 400-fold improvement over the previously published protocol,<br /> (2) reduces the negative effects of high sgRNA levels on parasite growth by using a weaker T7 promoter to drive sgRNA transcription.

The combination of these two improvements should open the door to exciting large-scale screens and thus be of great interest to researchers working with Leishmania and beyond.

Reviewer #2 (Public Review):

Summary:

Previously, the authors published a Leishmania cytosine base editor (CBE) genetic tool that enables the generation of functionally null mutants. This works by utilising a CAS9-cytidine deaminase variant that is targeted to a genetic locus by a small guide RNA (sgRNA) and causes cytosine to thymine conversion. This has the potential to generate a premature stop codon and therefore a loss of function mutant.

CBE has advantages over existing CAS-based knockout tools because it allows the targeting of multicopy gene families and, potentially, the easier generation of pooled loss of function mutants in complex population experiments. Although successful, the first generation of this genetic tool had several limitations that may have prevented its wider adoption, especially in complex genome-wide screens. These include nonspecific toxicity of the sgRNAs, low transfection efficiencies, low editing efficiencies, a proportion of transfectants that express multiple different sgRNAs, and insufficient effectivity in some Leishmania species.

Here, the authors set out to systematically solve each of these limitations. By trialling different transfection conditions and different CAS12a cut sites to promote sgRNA expression cassette integration, they increase the transfection efficiency 400-fold and ensure that only a single sgRNA expression cassette integrates that edits with high efficiencies. By trialling different T7 promoters, they significantly reduce the non-specific toxicity of sgRNA expression whilst retaining high editing efficiencies in several Leishmania species (Leishmania major, L. mexicana and L. donovani). By improving the sgRNA design, the authors predict that null mutants will be more efficiently produced after editing.

This tool will find adoption for producing null mutants of single-copy genes, multicopy gene families, and potentially genome-wide mutational analyses.

Strengths:

This is an impressive and thorough study that significantly improves the previous iteration of the CBE. The approach is careful and systematic and reflects the authors' excellent experience developing CRISPR tools. The quality of data and analysis is high and data are clearly presented.

Weaknesses:

Figure 4 shows that editing of PF16 is 'reversed' between day 6 and day 16 in L. mexicana WTpTB107 cells. The authors reasonably conclude that in drug-selected cells there is a mixed population of edited and non-edited cells, possibly due to mis-integration of the sgRNA expression construct, and non-edited cells outcompete edited cells due to a growth defect in PF16 loss of function mutants. However, this suggests that the CBE tool will not work well for producing mutants with strong fitness phenotypes without incorporating a limiting dilution cloning step (at least in L. mexicana and quite possibly other Leishmania species). Furthermore, it suggests it will not be possible to incorporate genes associated with a growth defect into a pooled drop-out screen as described in the paper. This issue is not well explored in the paper and the authors have not validated their tool on a gene associated with a severe growth defect, or shown that their tool works in a mixed population setting.

Although welcome, the improvements to the crRNA CBE design tool are hypothetical and untested.

The Sanger and Oxford Nanopore Technology analyses on integration sites of the sgRNA expression cassette integration will not detect the mis-integration of the sgRNA expression construct into an entirely different locus.

Reviewer #3 (Public Review):

Genetic manipulation of Leishmania has some challenges, including some limitations in the DNA repair strategies that are present in the organism and the absence of RNA interference in many species. The senior author has contributed significantly to expanding the available routes towards Leishmania genetic manipulation by developing and adapting CRISPR-Cas9 tools to allow gene manipulation via DNA double-strand break repair and, more recently, base modification. This work seeks to improve on some limitations in the tools previously described for the latter approach of base modification leading to base change.

The work in the paper is meticulously described, with solid evidence for most of the improvements that are claimed: Figure1 clearly describes reduced impairment in the growth of parasites expressing sgRNAs via changes in promoters; Figures 2 and 3 compellingly document the usefulness of using AsCas12a for integration after transformation; and Figures 1 and 4 demonstrate the capacity of the combined modifications to efficiently edit a gene in three different Leishmania species. There is little doubt these new tools will be adopted by the Leishmania community, adding to the growing arsenal of approaches for genetic manipulation.

There are two weaknesses the authors may wish to address, one smaller and one larger.

(1) The main advance claimed here is in this section title: 'Integration of CBE sgRNA expression cassettes via AsCas12a ultra-introduced DSBs increase editing rates', with the evidence for this presented in Figure 4. It is hard work in the submission to discern what direct evidence there is for editing rates being improved relative to earlier, Cas9-based approaches. Did they directly compare the editing by the new and old approach? If not, can they more clearly explain how they are able to make this claim, either by adding text or a new figure? A side-by-side comparison would emphasise the advance of the new approach more clearly.

(2) The ultimate, stated goal of this work is (abstract) to 'enable a variety of loss-of-function screens', as the older approach had some limitations. This goal is not tested for the new tools that have been developed here; the experiment in Figure 5 merely shows that they can, not unexpectedly, make a gene mutant, which was already possible with available tools. Thus, to what extent is this paper describing a step forward? Why have the authors not run an experiment - even the same one that was described previously in Engstler and Beneke (2023) - to show that the new approach improves on previous tools in such a screen, either in scale or accuracy?

Author response:

We would like to thank all reviewers and editors for their thorough peer review and valuable suggestions. In these provisional responses, we summarize the main concerns raised by the reviewers and outline our planned revisions to address them in the manuscript.

Overall, we are pleased to note that the reviewers agree on the potential value of our updated toolbox for gene editing, highlighting its various applications. However, they also raised several valid concerns, which we have summarized and responded to as follows:

(1) Mutant phenotypes in transfected populations can be occasionally reversed or escaped. This suggests it will not be possible to detect growth-associated phenotypes in pooled screens. An experiment with a pooled loss-of-function screen to test this is missing.

Escapes or reversals of mutant phenotypes have been observed with other genetic tools used for loss-of-function screening, including lentiviral CRISPR approaches in mammalian systems and RNAi in Trypanosoma brucei. Cells can escape phenotypes through various mechanisms, such as promoter silencing or selection of non-deleterious mutations. Additionally, not every CRISPR guide is efficient in generating a mutant phenotype, and RNAi constructs can also vary in their effectiveness. Despite these challenges, genome-wide loss-of-function screens have been successfully carried out in mammalian cells and Trypanosoma parasites. Therefore, we believe that the observed escape of one mutant phenotype does not preclude the detection of growth-associated or other phenotypes in pooled screens. Moreover, we did not observe a reversal of the mutant phenotype in L. mexicana, L. donovani, and L. major parasites expressing tdTomato from an expression cassette integrated into the 18S rRNA SSU locus (Figure 4). However, the reviewers are rightfully requesting a pooled loss-of-function screen to validate this. Since submitting this manuscript, we have conducted multiple pooled loss-of-function screens, which have confirmed the ability of our here presented method to detect a range of mutant phenotypes in pooled screening formats. We will include these results in our revised manuscript.

(2) The possibility of mis-integration of the CBE sgRNA expression construct into an entirely different locus is not explored.

We plan to reanalyze our ONT sequencing data to verify if the CBE sgRNA expression construct was integrated into an unintended loci. If we detect any mis-integration events, we will evaluate their potential negative impacts and discuss these findings in the revised manuscript.

(3) The achieved increase in editing efficiency compared to the previous base editing method could be more clearly presented.

We have directly compared our improved method to our previous base editing method in Figures 1E and 4, demonstrating higher editing rates in a much shorter time. In the revised manuscript, we will present and describe the increase in editing rate more clearly.

(4) The improvements on CBE sgRNA guide design are hypothetical and untested.

We agree that the improvements to the CBE sgRNA design are currently hypothetical. We plan to systematically test our guide design principles in future studies. Since this will require testing hundreds of guides to draw robust conclusions, we believe that this aspect is beyond the scope of the current study. However, we will discuss our plans for future validation in the revised manuscript.

Overall, we appreciate the reviewers' insights and are committed to addressing their concerns thoroughly. We believe that the planned revisions and additional experiments will significantly strengthen our manuscript and provide a more comprehensive evaluation of our updated gene editing toolbox.

Reviewer #1 (Public Review):

Summary:

Moir, Merheb et al. present an intriguing investigation into the pathogenesis of Pol III variants associated with neurodegeneration. They established an inducible mouse model to overcome developmental lethality, administering 5 doses of tamoxifen to initiate the knock-in of the mutant allele. Subsequent behavioral assessments and histological analyses revealed potential neurological deficits. Robust analyses of the tRNA transcriptome, conducted via northern blotting and RNA sequencing, suggested a selective deleterious effect of the variant on the cerebrum, in contrast to the cerebellum and non-cerebral tissues. Through this work, the authors identified molecular changes caused by Pol III mutations, particularly in the tRNA transcriptome, and demonstrated its relative progression and selectivity in brain tissue. Overall, this study provides valuable insights into the neurological manifestations of certain genetic disorders and sheds light on transcripts/products that are constitutively expressed in various tissues.

Strengths:

The authors utilize an innovative mouse model to constitutively knock in the gene, enhancing the study's robustness. Behavioral data collection using a spectrometer reduces experimenter bias and effectively complements the neurological disorder manifestations. Transcriptome analyses are extensive and informative, covering various tissue types and identifying stress response elements and mitochondrial transcriptome patterns. Additionally, metabolic studies involving pancreatic activity and glucose consumption were conducted to eliminate potential glucose dysfunction, strengthening the histological analyses.

Weaknesses:

The study could have explored identifying the extent of changes in the tRNA transcriptome among different cell types in the cerebrum. Although the authors attempted to show the temporal progression of tRNA transcriptome changes between P42 and P75 mice, the causal link was not established. A subsequent rescue experiment in the future could address this gap.

Nonetheless, the claims and conclusions are supported by the presented data.

Reviewer #2 (Public Review):

Summary:

The study "Molecular basis of neurodegeneration in a mouse model of Polr3 related disease" by Moir et.al. showed that how RNA Pol III mutation affects production, maturation and transport of tRNAs. Furthermore, their study suggested that RNA pol III mutation leads to behavioural deficits that are commonly observed in neurodegeneration. Although, this study used a mouse model to establish theses aspects, the study seems to lack a clear direction and mechanism as to how the altered level of tRNA affects locomotor behaviour. They should have used conditional mouse to delete the gene in specific brain area to test their hypothesis. Otherwise, this study shows a more generalized developmental effect rather than specific function of altered tRNA level. This is very evident from their bulk RNA sequencing study. This study provides some discrete information rather than a coherent story.

Strengths:

The study created a mouse model to investigate role of RNA PolIII transcription. Furthermore, the study provided RNA seq analysis of the mutant mice and highlighted expression specific transcripts affected by the RNA PolIII mutation.

Weaknesses:

1) The abstract is not clearly written. It is hard to interpret what is the objective of the study and why they are important to investigate. For example: "The molecular basis of disease pathogenesis is unknown." Which disease? 4H leukodystrophy? All neurodegenerative disease?

2) How cerebral pathology and exocrine pancreatic atrophy are related? How altered tRNA level connects these two axes?

3) Authors mentioned that previously observed reduction mature tRNA level also recapitulated in their study. Why this study is novel then?

4) It is very intuitive that deficit in Pol III transcription would severely affect protein synthesis in all brain areas as well as other organs. Hence, growth defect observed in Polr3a mutant mice is not very specific rather a general phenomenon.

5) Authors observed specific myelination defect in cortex and hippocampus but not in cerebellum. This is an interesting observation. It is important to find the link between tRNA removal and myelin depletion in hippocampus or cortex? Why is myelination not affected in cerebellum?

6) How was the locomotor activity measured? The detailed description is missing. Also, locomotion is primarily cerebellum dependent. There is no change in term of growth rate and myelination in cerebellar neurons. I do not understand why locomotor activity was measured.

7) The correlation with behavioural changes and RNA seq data is missing. There a number of transcripts are affected and mostly very general factors for cellular metabolism. Most of them are RNA Pol II transcribed. How a Pol III mutation influences RNA Pol II driven transcription? I did not find differential expression of any specific transcripts associated with behavioural changes. What is the motivation for transcriptomics analysis? None of these transcripts are very specific for myelination. It is rather a general cellular metabolism effect that indirectly influences myelination.

8) What genes identified by transcriptomics analysis regulates maturation of tRNA? Authors should at least perform RNAi study to identify possible factor and analyze their importance in maturation of tRNA.

9) What factors are influencing tRNA transport to cytoplasm? It may be possible that Polr3a mutation affect cytoplasmic transport of tRNA. Authors should study this aspect using an imaging experiment.

10) Does alteration of cytoplasmic level of tRNA affects translation? Author should perform translation assay using bio-orthoganal amino acid (AHA) labelling.

eLife assessment

This important chronobiological study in mice suggests that light modulated activity of Cdk5 activity on the PKA-CaMK-CREB signaling pathway provides missing molecular mechanistic details to understand light- induced circadian clock phase delays during the early night, but not for phase advances in the morning. The authors provide overall convincing evidence bridging from behavioral to molecular/cellular experiments to neural activity imaging.

Reviewer #1 (Public Review):

In the manuscript "Cyclin-dependent kinase 5 (Cdk5) activity is modulated by light and gates rapid phase shifts of the circadian clock", Brenna et al study the role of Cdk5 on circadian rhythms and they conclude that the CDK5 gates the activity of light on phase shifts at ZT by showing that the behavioural shifts to light as a result of CDK5 silencing only affect light-induced phase shifts at ZT/CT 14 but not at other times.

Further, they delineate the mechanism behind this phenotype and demonstrate that 1) CDK5 activity is downregulated following a light pulse via a loss of interaction with p35 and demonstrate this via an activity assay. 2) knock-down of CDK5: increases CREB, CAMK-ii/iv phosphorylation, likely via increasing calcium levels along with alterations to the localisation of Cav3.1, 3) reduces: light-induced response in vivo at ZT14 in the SCN.

They suggest this mechanism involves light 'silencing' CDK5-pathway (possibly by disrupting P35 interaction and dysregulating this pathway) which under basal conditions phosphorylates DARP32 leading to PKA inhibition and by extension reduction in activation of the calcium-calmodulin kinase activity and leading to reduced CREB activity. The authors finally evaluate gene expression changes of previously described light-responsive-genes in at ZT14 and the SCN.

This is an interesting piece of work that explains how circadian responses to light could be gated and is generally well supported by a wealth of data. Whilst I found the overall involvement of CDK5 in gating light response interesting and convincing, I have some concerns about their interpretation of the data surrounding the mechanism, which I have detailed below. I also think this manuscript could be improved with a slightly different structure and concise discussion for the benefit of a broader scientific audience.

Reviewer #2 (Public Review):

Summary:

Definition of the role of CdK5 in circadian locator activity and light induced neural activity in the mouse SCN in-vivo revealing its mode of action through PKA-CaMK-CREB signaling pathway.

Strengths:

The experimental approaches are carried from in-vivo, to cellular and molecular level and provide first evidence for the specific involvement of CdK5 in light-induced phase advance of the free-running rhythm.

Weaknesses:

The behavioral analyses are limited to some selected parameters.<br /> Downstream effects on circadian oscillation of gene expression and physiological functions in other brain regions, and organs is missing.

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Not necessary. You mentioned the importance earlier. Remove this.

Notes format needs to be consistent. Some places Note is bold.

Bold high, medium, low TMB

No need to expand every single time. Once is enough. Bold

Tumor Mutation Burden (TMB) measures the total number of mutations found in a tumor's DNA. This value is typically expressed as the number of mutations per million bases (megabase) of DNA analyzed.

Bold all UI labels

Do not use this term.

the disease

rephrase

less frequent what

in or around. Rephrase

is

Within Gene Mutations, users can access details like.........

Bold. No quotations

Image captions are missing

What is the subheading for this

Do not add value to the facets. Only mention what they do,

All the facets need to in bold

Gene

why mention this?

bold

This filter enables the categorisation individuals based on their blood type.

Again, this entire thing can be one sentence by removing repetitive information

remove

in time or age

Colloquial. Please use the medical term for death.

This can be one sentence. Combine it and remove the first part where it says creation of diverse patient cohorts.

like how boise state parking will account for x many spots being taken up by trespassers when deciding how many permits to give out