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  1. Aug 2023
    1. Author Response

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

      We would first like to thank the reviewers and the editor for their insightful comments and suggestions. We are particularly glad to read that our so<ware package constitutes a set of “well-written analysis routines” which have “the potential to become very valuable and foundational tools for the analysis of neurophysiological data”. We have updated the manuscript to address their remarks where appropriate.

      Additionally, we would like to stress that this kind of tools is in continual development. As such, the manuscript offered a snapshot of the package at one point during this process, which in this case was several months ago at initial submission. Since then, several improvements were implemented. The manuscript has been further updated to reflect these more recent changes.

      From the Reviewing Editor:

      The reviewers identified a number of fundamental weaknesses in the paper.

      1) For a paper demonstrating a toolbox, it seems that some example analyses showing the value of the approach (and potentially the advantage in simplification, etc over previous or other approaches) are really important to demonstrate.

      As noted by the first reviewer, the online repository (i.e. GitHub page) conveys a better sense of the toolboxes’ contribution to the field than the present manuscript. This is a fair remark but at the same time, it is unclear how to illustrate this in a journal article without dedicating a great deal of page space to presenting raw code, while online tools offer an easier and clearer way to do this. As a work-around, our strategy was to illustrate some examples of data analysis in Figures 4&5 by comparing each illustrated processing step to the corresponding command line used by the Pynapple package. Each step requires a single line of code, meaning that one only needs to write three lines of code to decode a feature from population activity using a Bayesian decoder (Fig. 4a), compute a cross-correlograms of two neurons during specific stimulus presentation (Fig. 4b) or compute the average firing rate of two neurons around a specific time of the experimental task (Fig. 4c). We believe that these visual aides make it unnecessary to add code in the main text of this manuscript. However, to aid reader understanding, we now provide clear references to online Jupyter notebooks which show how each figure was generated in figure legends as well as in the “Code Availability” section.

      https://github.com/pynapple-org/pynapple-paper-2023

      Furthermore, we have opted-in for the “Executable Research Articles” feature at eLife, which will make it possible to include live scripts and figures in the manuscript once it is accepted for publication. We do not know at this stage what it entails exactly, but we hope that Figures 4&5 will become live with this feature. The readers will have the possibility to see and edit the code directly within the online version of the manuscript.

      2) The manuscript's claims about not having dependencies seem confusing.

      We agree that this claim was somewhat unfounded. There are virtually no Python packages that do not have dependencies. Our intention was to say that the package had no dependencies outside the most common ones, which are Numpy, Scipy, and Pandas. Too many packages in the field tend to have long list of dependencies making long-term back-compatibility quite challenging. By keeping depencies minimal, we hope to maximise the package’'s long term back-compatibility. We have rephrased this statement in the manuscript in the following sections:

      Figure 1, legend.

      “These methods depend only on a few, commonly used, external packages.”

      Section Foundational data processing: “they are for the most part built-in and only depend on a few widely-used external packages. This ensures that the package can be used in a near stand-alone fashion, without relying on packages that are at risk of not being maintained or of not being compatible in the near future.”

      3) Given its significant relevance, it seems important to cite the FMATool and describe connections between it (or analyses based on it) and the presented work.

      Indeed, although we had already cited other toolboxes (including a review covering the topic comprehensively), we should have included this one in the original manuscript. Unfortunately, to the best of our knowledge, this toolbox is not citable (there is no companion paper). We have added a reference to it in plain text.

      4) Some discussion of integration between Pynapple and the rest of a full experimental data pipeline should be discussed with regard to reproducibility.

      This is an interesting point, and the third paragraph of the discussion somewhat broached this issue. Pynapple was not originally designed to pre-process data. However, it can, in theory, load any type of data streams a<er the necessary pre-processing steps. Overall, modularity is a key aspect of the Pynapple framework, and this is also the case for the integration with data pre-processing pipelines, for example spike sorting in electrophysiology and detection of region of interest in calcium imaging. We do not think there should be an integrated solution to the problem but, instead, to make it possible that any piece of code can be used for data irrespective of their origin. This is why we focused on making data loading straightforward and easy to adapt to any particular situation. To expand on this point and make it clear that Pynapple is not meant to pre-process data but can, in theory, load any type of data streams a<er the necessary pre-processing steps, we have added the following sentences to the aforementioned paragraph:

      “Data in neuroscience vary widely in their structure, size, and need for pre-processing. Pynapple is built around the idea that raw data have already been pre-processed (for example, spike sorting and detection of ROIs).”

      5) Relatedly, a description of how data are stored a<er processing (i.e., how precisely are processed data stored in NWB format).

      We agree that this is a critical issue. NWB is not necessarily the best option as it is not possible to overwrite in a NWB file. This would require the creation of a new NWB file each time, which is computationally expensive and time consuming. It also further increases the odds of writing error. Theoretically, users who needs to store intermediate results in a flexible way could use any methods they prefer, writing their own data files and wrappers to reload these data into Pynapple objects. Indeed, it is not easy to properly store data in an object-specific manner. This is a long-standing issue and one we are currently working to resolve.

      To do so, we are developing I/O methods for each Pynapple core objects. We aim to provide an output format that is simple to read and backward compatible in future Pynapple releases. This feature will be available in the coming weeks. To note, while NWB may not be the central data format of Pynapple in future releases, it has become a central node in the neuroscience ecosystem of so<ware. Therefore, we aim to facilitate the interaction of users with reading and writing for this format by developing a set of simple standalone functions.

      Reviewer #1 (Public Review):

      A typical path from preprocessed data to findings in systems neuroscience o<en includes a set of analyses that o<en share common components. For example, an investigator might want to generate plots that relate one time series (e.g., a set of spike times) to another (measurements of a behavioral parameter such as pupil diameter or running speed). In most cases, each individual scientist writes their own code to carry out these analyses, and thus the same basic analysis is coded repeatedly. This is problematic for several reasons, including the waste of time, the potential for errors, and the greater difficulty inherent in sharing highly customized code.

      This paper presents Pynapple, a python package that aims to address those problems.

      Strengths:

      The authors have identified a key need in the community - well-written analysis routines that carry out a core set of functions and can import data from multiple formats. In addition, they recognized that there are some common elements of many analyses, particularly those involving timeseries, and their object- oriented architecture takes advantage of those commonalities to simplify the overall analysis process.

      The package is separated into a core set of applications and another with more advanced applications, with the goal of both providing a streamlined base for analyses and allowing for implementations/inclusion of more experimental approaches.

      Weaknesses:

      There are two main weaknesses of the paper in its present form.

      First, the claims relating to the value of the library in everyday use are not demonstrated clearly. There are no comparisons of, for example, the number of lines of code required to carry out a specific analysis with and without Pynapple or Pynacollada. Similarly, the paper does not give the reader a good sense of how analyses are carried out and how the object-oriented architecture provides a simplified user interaction experience. This contrasts with their GitHub page and associated notebooks which do a better job of showing the package in action.

      As noted in the response to the Reviewing Editor and response to the reviewer’s recommendation to the authors below, we have now included links to Jupyter notebooks that highlight how panels of Figures 4 and 5 were generated (https://github.com/pynapple-org/pynapple-paper-2023). However, we believe that including more code in the manuscript than what is currently shown (I.e. abbreviated call to methods on top of panels in Figs 4&5) would decrease the readability of the manuscript.

      Second, the paper makes several claims about the values of object-oriented programming and the overall design strategy that are not entirely accurate. For example, object-oriented programming does not inherently reduce coding errors, although it can be part of good so<ware engineering. Similarly, there is a claim that the design strategy "ensures stability" when it would be much more accurate to say that these strategies make it easier to maintain the stability of the code. And the authors state that the package has no dependencies, which is not true in the codebase. These and other claims are made without a clear definition of the properties that good scientific analysis so<ware should have (e.g., stability, extensibility, testing infrastructure, etc.).

      Following thFMAe reviewer’s comment, we have rephrased and clarified these claims. We provide detailed response to these remarks in the recommendations to authors below.

      There is also a minor issue - these packages address an important need for high-level analysis tools but do not provide associated tools for preprocessing (e.g., spike sorting) or for creating reproducible pipelines for these analyses. This is entirely reasonable, in that no one package can be expected to do everything, but a bit deeper account of the process that takes raw data and produces scientific results would be helpful. In addition, some discussion of how this package could be combined with other tools (e.g., DataJoint, Code Ocean) would help provide context for where Pynapple and Pynacollada could fit into a robust and reliable data analysis ecosystem.

      We agree the better explaining how Pynapple is integrated within data preprocessing pipelines is essential. We have clarified this aspect in the manuscript and provide more details below.

      Reviewer #1 (Recommendations For The Authors):

      Page 1

      • Title

      The authors should note that the application name- "Pynapple" could be confused with something from Apple. Users may search for "Pyapple" as many python applications contain "py" like "Numpy". "Pyapple" indeed is a Python Apple that works with Apple products. They could consider "NeuroFrame", "NeuroSeries" or "NeuroPandas" to help users realize this is not an apple product.

      We thank the referee for this interesting comment. However, we are not willing to make such change at this point. The community of users has been growing in the last year and it seems too late to change the name. To note, it is the first time such comment is made to us and it does not seem that users and collaborators are confused with any Apple products.

      • Abstract

      The authors mentioned that the Pynapple is "fully open source". It may be better to simply say it is "open source".

      We agree, corrected.

      Assuming the authors keep the name, it would be helpful if the full meaning of Pynapple - Python Neural Analysis Package was presented as early as possible.

      Corrected in the abstract.

      • Highlight

      An application being lightweight and standalone does not imply nor ensure backward compatibility. In general, it would be useful if the authors identified a set of desirable code characteristics, defined them clearly in the introduction, and then describe their so<ware in terms of those characteristics.

      Thank you for your comment. We agree that being lightweight and standalone does not necessarily imply backward compatibility. Our intention was to emphasize that Pynapple is designed to be as simple and flexible as possible, with a focus on providing a consistent interface for users across different versions. However, we understand that this may not be enough to ensure long-term stability, which is why we are committed to regular updates and maintenance to ensure that the code remains functional as the underlying code base (Python versions, etc.) changes.

      Regarding your suggestion to identify a set of desirable code characteristics, we believe this is an excellent idea. In the introduction, we briefly touch upon some of the core principles that guided our development of Pynapple: a lightweight, stable, and simple package. However, we acknowledge that providing a more detailed discussion of these characteristics and how they relate to the design of our so<ware would be useful for readers. We have added this paragraph in the discussion:

      “Pynapple was developed to be lightweight, stable, and simple. As simplicity does not necessarily imply backward compatibility (i.e. long-term stability of the code), Pynapple main objects and their properties will remain the same for the foreseeable future, even if the code in the backend may eventually change (e.g. not relying on Pandas in future version). The small number of external dependencies also decrease the need to adapt the code to new versions of external packages. This approach favors long-term backward compatibility.”

      Page 2

      • The authors wrote -

      "Despite this rapid progress, data analysis o<en relies on custom-made, lab-specific code, which is susceptible to error and can be difficult to compare across research groups."

      It would be helpful to add that custom-made, lab-specific code can lead to a violation of FAIR principles (https://en.wikipedia.org/wiki/FAIR_datadata). More generally, any package can have errors, so it would be helpful to explain any testing regiments or other approach the authors have taken to ensure that their code is error-free.

      We understand the importance of the FAIR principles for data sharing. However, Pynapple was not designed to handle data through their pre-processing. The only aspect that is somehow covered by the FAIR principles is the interoperability, but again, it is a requirement for the data to interoperate with different storage and analysis pipelines, not of the analysis framework itself. Unlike custom-made code, Pynapple will make interoperability easier, as, in theory, once the required data loaders are available, any analysis could be run on any dataset. We have added the following sentence to the discussion:

      “Data in neuroscience vary widely in their structure, size, and need for pre-processing. Pynapple is built around the idea that raw data has already been pre-processed (for example, spike sorting and ROI detection). According to the FAIR principles, pre-processed data should interoperate across different analysis pipelines. Pynapple makes this interoperability possible as, once the data are loaded in the Pynapple framework, the same code can be used to analyze different datasets”

      • The authors wrote -

      "While several toolboxes are available to perform neuronal data analysis ti–11,2ti (see ref. 29 for review), most of these programs focus on producing high-level analysis from specified types of data and do not offer the versatility required for rapidly-changing analytical methods and experimental methods."

      Here it would be helpful if the authors could give a more specific example or explain why this is problematic enough to be a concern. Users may not see a problem with high-level analysis or using specific data types.

      Again, we apologize for not fully elaborating upon our goals here. Our intention was to point out that toolboxes o<en focus on one particular case of high-level analysis. In many cases, such packages lack low level analysis features or the flexibility to derive new analysis pipelines quickly and effortlessly. Users can decide to use low-level packages such as Pandas, but in that case, the learning curve can be steep for users with low, if any, computational background. The simplicity of Pynapple, and the set of examples and notebooks, make it possible for individuals who start coding to be quickly able to analyze their data.

      As we do not want to be too specific at this point of the manuscript (second paragraph of the intro) and as we have clarified many of the aspects of the toolbox in the new revised version, we have only added the following sentence to the paragraph:

      “Users can decide to use low-level data manipulation packages such as Pandas, but in that case, the learning curve can be steep for users with low, if any, computational background.”

      • The authors wrote -

      "To meet these needs, a general toolbox for data analysis must be designed with a few principles in mind"

      Toolboxes based on many different principles can solve problems. It is likely more accurate to say that the authors designed their toolbox with a particular set of principles in mind. A clear description of those principles (as mentioned in the comment above) would help the reader understand why the specific choices made are beneficial.

      We agree that these are not “universal” principles and clearly more the principles we had in mind when we designed the package. We have clarified these principles and made clear that these are personal point of views.

      We have rephrased the following paragraph:

      “To meet these needs, we designed Pynapple, a general toolbox for data analysis in systems Neuroscience with a few principles in mind.“

      • The authors wrote -

      "The first property of such a toolbox is that it should be object-oriented, organizing so<ware around data."

      What facts make this true? For example, React is a web development library. A common approach to using this library is to use Hooks (essentially a collection of functions). This is becoming more popular than the previous approach of using Components (a collection of classes). This is an example of how Object-oriented programming is not always the best solution. In some cases, for example, object- oriented coding can cause problems (e.g. it can be hard to find the place where a given function is defined and to figure out which version is being used given complex inheritance structures.)

      In general, key selling points of object-oriented programming are extension, inheritance, and encapsulation. If the authors want to retain this text (which would be entirely reasonable), it would be helpful if they explained clearly how an object-oriented approach enables these functions and why they are critical for this application in particular.

      The referee makes a particularly important point. We are aware of the limits of OOP, especially when these objects become over-complex, and that the inheritance become unclear.

      We have clarified our goal here. We believe that in our case, OOP is powerful and, overall, is less error- prone that a collection of functions. The reasons are the following:

      An object-oriented approach facilitates better interactions between objects. By encapsulating data and behavior within objects, object-oriented programming promotes clear and well-defined interfaces between objects. This results in more structured and manageable code, as objects communicate with each other through these well-defined interfaces. Such improved interactions lead to increased code reliability.

      Inheritance, a key concept in object-oriented programming, allows for the inheritance of properties. One important example of how inheritance is crucial in the Pynapple framework is the time support of Pynapple objects. It determines the valid epoch on which the object is defined. This property needs to be carried over during different manipulations of the object. Without OOP, this property could easily be forgotten, resulting in erroneous conclusions for many types of analysis. The simplest case is the average rate of a TS object: the rate must be computed on the time support ( a property of TS objects), not the beginning to the end of the recording (or of a specific epoch, independent of the TS). Finally, it is easier to access and manipulate the meta information of a Pynapple object than without using objects.

      • The authors wrote -

      "drastically diminishing the odds of a coding error"

      This seems a bit strong here. Perhaps "reducing the odds" would be more accurate.

      We agree. Now changed.

      Page 3

      • The authors wrote -

      ". Another property of an efficient toolbox is that as much data as possible should be captured by only a small number of objects This ensures that the same code can be used for various datasets and eliminates the need of adapting the structure"

      It may be better to write something like - "Objects have a collection of preset variables/values that are well suited for general use and are very flexible." Capturing "as much data as possible" may be confusing, because it's not the amount that this helps with but rather the variety.

      We thank the referee for this remark. We have rephrased this sentence as follows:

      “Another property of an efficient toolbox is that a small number of objects could virtually represents all possible data streams in neuroscience, instead of objects made for specific physiological processes (e.g. spike trains).”

      • The authors wrote -

      "The properties listed above ensure the long-term stability of a toolbox, a crucial aspect for maintaining the code repository. Toolboxes built around these principles will be maximally flexible and will have the most general application"

      There are two issues with this statement. First, ensuring long-term stability is only possible with a long- term commitment of time and resources to ensure that that code remains functional as the underlying code base (python versions, etc.) changes. If that is something you are commisng to, it would be great to make that clear. If not, these statements need to be less firm.

      Second, it is not clear how these properties were arrived at in the first place. There are things like the FAIR Principles which could provide an organizing framework, ideally when combined with good so<ware engineering practices, and if some more systematic discussion of these properties and their justification could be added, it would help the field think about this issue more clearly.

      The referee makes a valid point that ensuring long-term stability requires a long-term commitment of time and resources to maintain the code as the underlying technology evolves. While we cannot make guarantees about the future of Pynapple, we believe that one of the best ways to ensure long-term stability is by fostering a strong community of users and contributors who can provide ongoing support and development. By promoting open-source collaboration and encouraging community involvement, we hope to create a sustainable ecosystem around Pynapple that can adapt to changes in technology and scientific practices over time. Ultimately, the longevity of any scientific tool depends on its adoption and use by the research community, and we hope that Pynapple can provide value to neuroscience researchers and continue to evolve and improve as the field progresses.

      It is noteworthy that the first author, and main developer of the package, has now been hired as a data scientist at the Center for Computational Neuroscience, Flatiron Institute, to explicitly continue the development of the tool and build a community of users and contributors.

      • The authors wrote -

      "each with a limited number of methods..."

      This may give the impression that the functionality is limited, so rephrasing may be helpful.

      Indeed! We have now rephrased this sentence:

      “The core of Pynapple is five versatile timeseries objects, whose methods make it possible to intuitively manipulate and analyze the data.”

      • The authors wrote that object-oriented coding

      "limits the chances of coding error"

      This is not always the case, but if it is the case here, it would be helpful if the authors explain exactly how it helps to use object-oriented approaches for this package.

      We agree with the referee that it is not always the case. As we explained above, we believe it is less error-prone that a collection of functions. Quite o<en, it also makes it easier to debug. We have changed this sentence with the following one:

      “Because objects are designed to be self-contained and interact with each other through well-defined methods, users are less likely to make errors when using them. This is because objects can enforce their own internal consistency, reducing the chances of data inconsistencies or unexpected behavior. Overall, OOP is a powerful tool for managing complexity and reducing errors in scientific programming.”

      • Fig 1

      In object-oriented programming, a class is a blueprint for the classes that inherit it. Instantiating that<br /> class creates an object. An object contains any or all of these - data, methods, and events. The figure could be improved if it maintained these organizational principles as figure properties.

      We agree with the referee’s remark regarding the logic of objects instantiation but how this could be incorporated in Fig. 1 without making it too complex is unclear. Here, objects are instantiated from the first to the second column. We have not provided details about the parent objects, as we believe these details are not important for reader comprehension. In its present form, the objects are inherited from Pandas objects, but it is possible that a future version is based on something else. For the users, this will be transparent as the toolbox is designed in such a way that only the methods that are specific to Pynapple are needed to do most computation, while only expert programmers may be interested in using Pandas functionalities.

      • The authors wrote that Pynapple does -

      "not depend on any external package"

      As mentioned above, this is not true. It depends on Numpy and likely other packages, and this should be explained. It is perfectly reasonable to say that it depends on only a few other packages.

      As said above, we have now clarified this claim.

      Page 5.

      • The authors wrote -

      "represent arrays of Ts and Tsd"

      For a knowledgeable reader's reference, it would be helpful to refer to these either as Numpy arrays (at least at first when they are defined) or as lists if they are native python objects.

      Indeed, using the word “arrays” here could be confusing because of Numpy arrays. We have changed this term with “groups”.

      • The authors wrote -

      "Pynapple is built with objects from the Pandas library ... Pynapple objects inherit the computational stability and flexibility"

      Here a definition of stability would be useful. Is it the case that by stability you mean "does not change o<en"? Or is some other meaning of stability implied?

      Yes, this is exactly what we meant when referring to the stability of Pandas. We have added the following precision:

      “As such, Pynapple objects inherit the long-term consistency of the code and the computational flexibility computational stability and flexibility from this widely used package.”

      Page 6

      • Fig 2

      In Fig 2 A and B, the illustrations are good. It would also be very helpful to use toy code examples to illustrate how Pynapple will be used to carry out on a sample analysis-problem so that potential users can see what would need to be done.

      We appreciate the kind works. Regarding the toy code, this is what we tried to do in Fig. 4. Instead of including the code directly in the paper, which does not seem a modern way of doing this, we now refer to the online notebooks that reproduce all panels of Figure 4.

      • The authors wrote -

      "While these objects and methods are relatively few"

      In object-oriented programming, objects contain methods. If a method is not in an object, it is not technically a method but a function. It would be helpful if the authors made sure their terminology is accurate, perhaps by saying something like "While there are relatively few objects, and while each object has relatively few methods ... "

      We agree with the referee, we have changed the sentence accordingly.

      • The authors wrote -

      "if not implemented correctly, they can be both computationally intensive and highly susceptible to user error"

      Here the authors are using "correctly" to refer to two things - "accuracy" - gesng the right answer, and "efficiency" - gesng to that answer with relatively less computation. It would be clearer if they split out those two concepts in the phrasing.

      Indeed, we used the term to cover both aspects of the problem, leading to the two possible issues cited in the second part of the sentence. We have changed the sentence following the referee’s advice:

      “While there are relatively few objects, and while each object has relatively few methods, they are the foundation of almost any analysis in systems neuroscience. However, if not implemented efficiently, they can be computationally intensive and if not implemented accurately, they are highly susceptible to user error.”

      • In the next sentence the authors wrote -

      "Pynapple addresses this concern."

      This statement would benefit from just additional text explaining how the concern is addressed.

      We thank the referee for the suggestion. We have changed the sentence to this one: “The implementation of core features in Pynapple addresses the concerns of efficiency and accuracy”

      Page 9

      • The authors wrote -

      This is implemented via a set of specialized object subclasses of the BaseLoader class. To avoid code redundancy, these I/O classes inherit the properties of the BaseLoader class. "

      From a programming perspective, the point of a base class is to avoid redundancy, so it might be better to just mention that this avoids the need to redefine I/O operations in each class.

      We have rephrased the sentence as follows:

      “This is implemented via a set of specialized object subclasses of the BaseLoader class, avoiding the need to redefine I/O operations in each subclass"

      • The authors wrote -

      "classes are unique and independent from each other, ensuring stability"

      How do classes being unique and independent ensure stability? Perhaps here again the misunderstanding is due to the lack of a definition of stability.

      We thank the referee for the remark. We first changed “stability” for “long-term backward compatibility”. We further added the following sentence to clarify this claim. “For instance, if the spike sorting tool Phy changes its output in the future, this would not affect the “Neurosuite” IO class as they are independent of each other. This allows each tool to be updated or modified independently, without requiring changes to the other tool or the overall data format.”

      • The authors wrote -

      "Using preexisting code to load data in a specific manner instead of rewriting already existing functions avoids preprocessing errors"

      Here it might be helpful to use the lingo of Object-oriented programming. (e.g. inheritance and polymorphism). Defining these terms for a neuroscience audience would be useful as well.

      We do not think it is necessary to use too much technical term in this manuscript. However, this sentence was indeed confusing. We have now simplified it:

      “[…], users can develop their own custom I/O using available template classes. Pynapple already includes several of such templates and we expect this collection to grow in the future.”

      Page 10

      • The authors wrote -

      "These analyses are powerful because they are able to describe the relationships between time series objects while requiring the fewest number of parameters to be set by the user."

      It is not clear that this makes for a powerful analysis as opposed to an easy-to-use analysis.

      We have changed “powerful” with “easy to use".

      Page 12

      "they are built-in and thus do not have any external dependencies"

      If the authors want to retain this, it would be helpful to explain (perhaps in the introduction) why having fewer external dependencies is useful. And is it true that these functions use only base python classes?

      We have rephrased this sentence as follows:

      “they are for the most part built-in and only depend on a few common external packages, ensuring that they can be used stand-alone without relying on packages that are at risk of not being maintained or of not being compatible in the near future.”

      Other comments:

      • It would be helpful, as mentioned in the public review, to frame this work in the broader context of what is needed to go from data to scientific results so that people understand what this package does and does not provide.

      We have added the following sentence to the discussion to make sure readers understand:

      “The path from data collection to reliable results involves a number of critical steps: exploratory data analysis, development of an analysis pipeline that can involve custom-made developed processing steps, and ideally the use of that pipeline and others to replicate the results. Pynapple provides a platform for these steps.”

      • It would also be helpful to describe the Pynapple so<ware ecosystem as something that readers could contribute to. Note here that GNU may not be a good license. Technically, GNU requires any changes users make to Pynapple for their internal needs to be offered back to the Pynapple team. Some labs may find that burdensome or unacceptable. A workaround would be to have GNU and MIT licenses.

      The main restriction of the GPL license is that if the code is changed by others and released, a similar license should be used, so that it cannot become proprietary. We therefore stick to this choice of license.

      We would be more than happy to receive contributions from the community. To note, several users outside the lab have already contributed. We have added the following sentence in the introduction:

      “As all users are also invited to contribute to the Pynapple ecosystem, this framework also provides a foundation upon which novel analyses can be shared and collectively built by the neuroscience community.”

      • This so<ware shares some similarities with the nelpy package, and some mention of that package would be appropriate.

      While we acknowledge the reviewer's observation that Nelpy is a similar package to Pynapple, there are several important differences between the two.

      First, Nelpy includes predefined objects such as SpikeTrain, BinnedSpikeTrain, and AnalogSignal, whereas Pynapple would use only Ts and Tsd for those. This design choice was made to provide greater flexibility and allow users to define their own data structures as needed.

      Second, Nelpy is primarily focused on electrophysiology data, whereas Pynapple is designed to handle a wider range of data types, including calcium imaging and behavioral data. This reflects our belief that the NWB format should be able to accommodate diverse experimental paradigms and modalities.

      Finally, while Nelpy offers visualization and high-level analysis tools tailored to electrophysiology, Pynapple takes a more general-purpose approach. We believe that users should be free to choose their own visualization and analysis tools based on their specific needs and preferences.

      The package has now been cited.

      Reviewer #2 (Public Review):

      Pynapple and Pynacollada have the potential to become very valuable and foundational tools for the analysis of neurophysiological data. NWB still has a steep learning curve and Pynapple offers a user- friendly toolset that can also serve as a wrapper for NWB.

      The scope of the manuscript is not clear to me, and the authors could help clarify if Pynacollada and other toolsets in the making become a future aspect of this paper (and Pynapple), or are the authors planning on building these as separate publications.

      The author writes that Pynapple can be used without the I/O layer, but the author should clarify how or if Pynapple may work outside NWB.

      Absolutely. Pynapple can be used for generic data analysis, with no requirement of specific inputs nor NWB data. For example, the lab is currently using it for a computational project in which the data are loaded from simple files (and not from full I/O functions as provided in the toolbox) for further analysis and figure generation.

      This was already noted in the manuscript, last paragraph of the section “Importing data from common and custom pipelines”

      “Third, users can still use Pynapple without using the I/O layer of Pynapple.”.

      We have added the following sentence in the discussion

      “To note, Pynapple can be used without the I/O layer and independent of NWB for generic, on-the-fly analysis of data.”

      This brings us to an important fundamental question. What are the advantages of the current approach, where data is imported into the Ts objects, compared to doing the data import into NWB files directly, and then making Pynapple secondary objects loaded from the NWB file? Does NWB natively have the ability to store the 5 object types or are they initialized on every load call?

      NWB and Pynapple are complimentary but not interdependent. NWB is meant to ensure long-term storage of data and as such contains a as much information as possible to describe the experiment. Pynapple does not use NWB to directly store the objects, however it can read from NWB to organize the data in Pynapple objects. Since the original version of this manuscript was submitted, new methods address this. Specifically, in the current beta version, each object now has a “save” method. Obviously, we are developing functions to load these objects as well. This does not depend on NWB but on npz, a Numpy specific file format. However, we believe it is a bit too premature to include these recent developments in the manuscript and prefer not to discuss this for now.

      Many of these functions and objects have a long history in MATLAB - which documents their usefulness, and I believe it would be fisng to put further stress on this aspect - what aspects already existed in MATLAB and what is completely novel. A widely used MATLAB toolset, the FMA toolbox (the Freely moving animal toolbox) has not been cited, which I believe is a mistake.

      We agree that the FMA toolbox should have been cited. This ha now been corrected.

      Pynapple was first developed in Matlab (it was then called TSToolbox). The first advantage is of course that Python is more accessible than Matlab. It has also been adopted by a large community of developers in data analysis and signal processing, which has become without a doubt much larger than the Matlab community, making it possible to find solutions online for virtually any problem one can have. Furthermore, in our experience, trainees are now unwilling to get training in Matlab.

      Yet, Python has drawbacks, which we are fully aware of. Matlab can be very computationally efficient, and old code can usually run without any change, even many years later.

      A limitation in using NWB files is its standardization with limited built-in options for derived data and additional metadata. How are derived data stored in the NWB files?

      NWB has predetermined a certain number of data containers, which are most common in systems neuroscience. It is theoretically possible to store any kind of data and associated metadata in NWB but this is difficult for a non-expert user. In addition, NWB does not allow data replacement, making is necessary to rewrite a whole new NWB file each time derived data are changed and stored. Therefore, we are currently addressing this issue as described above. Derived data and metadata will soon be easy to store and read.

      How is Pynapple handling an existing NWB dataset, where spikes, behavioral traces, and other data types have already been imported?

      This is an interesting point. In theory, Pynapple should be able to open a NWB file automatically, without providing much information. In fact, it is challenging to open a NWB file without knowing what to look for exactly and how the data were preprocessed. This would require adapting a I/O function for a specific NWB file. Unfortunately, we do not believe there is a universal solution to this problem. There are solutions being developed by others, for example NWB Widgets (NWB Widgets). We will keep an eye on this and see whether this could be adapted to create a universal NWB loader for Pynapple.

      Reviewer #2 (Recommendations For The Authors):

      Other tools and solutions are being developed by the NWB community. How will you make sure that these tools can take advantage of Pynapple and vice versa?

      We recognize the importance of collaboration within the NWB community and are committed to making sure that our tools can integrate seamlessly with other tools and solutions developed by the community.

      Regarding Pynapple specifically, we are designing it to be modular and flexible, with clear APIs and documentation, so that other tools can easily interface with it. One important thing is that we want to make sure Pynapple is not too dependent of another package or file format such as NWB. Ideally, Pynapple should be designed so that it is independent of the underlying data storage pipeline.

      Most of the tools that have been developed in the NWB community so far were designed for data visualisation and data conversion, something that Pynapple does not currently address. Multiple packages for behavioral analysis and exploration of electro/optophysiological datasets are compatible with the NWB format but do not provide additional solutions per se. They are complementary to Pynapple.

    1. Reviewer #1 (Public Review):

      This is a technically sound paper focused on a useful resource around the DRGP phenotypes which the authors have curated, pooled, and provided a user-friendly website. This is aimed to be a crowd-sourced resource for this in the future.

      The authors should make sure they coordinate as well as possible with the NC datasets and community and broader fly community. It looks reasonable to me but I am not from that community.

      I have only one major concern which in a more traditional review setting I would be flagging to the editor to insist the authors did on resubmission. I also have some scene setting and coordination suggestions and some minor textual / analysis considerations.

      The major concern is that the authors do not comment on the distribution of the phenotypes; it is assumed it is a continuous metric and well-behaved - broad gaussian. This is likely to be more true of means and medians per line than individual measurements, but not guaranteed, and there could easily be categorical data in the future. The application of ANOVA tests (of the "covariates") is for example fragile for this.

      The simplest recommendation is in the interface to ensure there is an inverse normalisation (rank and then project on a gaussian) function, and also to comment on this for the existing phenotypes in the analysis (presumably the authors are happy). An alternative is to offer a kruskal test (almost the same thing) on covariates, but note PLINK will also work most robustly on a normalised dataset.

      Minor points:<br /> On the introduction, I think the authors would find the extensive set of human GWAS/PheWAS resources useful; widespread examples include the GWAS Catalog, Open Targets PheWAS, MR-base, and the FinnGen portal. The GWAS Catalog also has summary statistics submission guidelines, and I think where possible meta-data harmonisation should be similar (not a big thing). Of course, DRGP has a very different structure (line and individuals) and of course, raw data can be freely shown, so this is not a one-to-one mapping.

      For some authors coming from a human genetics background, they will be interpreting correlations of phenotypes more in the genetic variant space (eg LD score regression), rather than a more straightforward correlation between DRGP lines of different individuals. I would encourage explaining this difference somewhere.

      This leads to an interesting point that the inbred nature of the DRGP allows for both traditional genetic approaches and leveraging the inbred replication; there is something about looking at phenotype correlations through both these lenses, but this is for another paper I suspect that this harmonised pool of data can help.

      I was surprised the authors did not crunch the number of transcript/gene expression phenotypes and have them in. Is this because this was better done in other datasets? Or too big and annoying on normalisation? I'd explain the rationale to leave these out.

      I think 25% FDR is dangerously close to "random chance of being wrong". I'd just redo this section at a higher FDR, even if it makes the results less 'exciting'. This is not the point of the paper anyway.

      I didn't buy the extreme line piece as being informative. Something has to be on the top and bottom of the ranks; the phenotypes are an opportunity for collection and probably have known (as you show) and cryptic correlations. I think you don't need this section at all for the paper and worry it gives an idea of "super normals" or "true wild types" which ... I just don't think is helpful.

      I'd say "well-established inversion genotypes and symbiot levels" rather than generic covariates. Covariates could mean anything. You have specific "covariates" which might actually be the causal thing.

      I wouldn't use the adjective tedious about curation. It's a bit of a value judgement and probably places the role of curation in the wrong way. Time-consuming due to lack of standards and best practice?

    1. to counter thepressures bearing down on you.

      Social media causes people a lot of stress and a lot of trying to fit in, although it shouldn't be like that and it's just meant to be a fun carefree activity.

    1. Author Response

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

      We would like to thank you for your thorough review of the manuscript. We have taken all comments into account in the revised version of the manuscript. Please find below our detailed responses to your comments.

      eLife assessment

      This study reports useful information on the limits of the organotypic culture of neonatal mouse testes, which has been regarded as an experimental strategy that can be extended to humans in the clinical setting for the conservation and subsequent re-use of testicular tissue. The evidence that the culture of testicular fragments of 6.5-day-old mouse testes does not allow optimal differentiation of steroidogenic cells is compelling and would be useful to the scientific community in the field for further optimizations.

      Thank you for this assessment. We have carefully considered all comments and made the requested revisions to improve the manuscript.

      Reviewer #1 (Public Review):

      In this manuscript, the authors aimed to compare, from testis tissues at different ages from mice in vivo and after culture, multiple aspects of Leydig cells. These aspects included mRNA levels, proliferation, apoptosis, steroid levels, protein levels, etc. A lot of work was put into this manuscript in terms of experiments, systems, and approaches. However, as written the manuscript is incredibly difficult to follow. The Introduction and Results sections contain rather loosely organized lists of information that were altogether confusing. At the end of reading these sections, it was unclear what advance was provided by this work. The technical aspects of this work may be of interest to labs working on the specific topics of in vitro spermatogenesis for fertility preservation but fail to appeal to a broader readership. This may be best exemplified by the statements at the end of both the Abstract and Discussion which state that more work needs to be done to improve this system.

      As suggested, we have reworked the manuscript to make it clearer, more meaningful and more precise. We believe that this work may be of interest to a broader readership. Indeed, the development of a model of in vitro spermatogenesis could be of interest for labs working on the specific period of puberty initiation, on germ and somatic cell maturation and on steroidogenesis under physiological and pathological conditions, and could also be useful for testing the toxicity of cancer therapies, drugs, chemicals and environmental agents (e.g. endocrine disruptors) on the developing testis.

      There is a crucial unmet need to optimize the culture conditions for in vitro spermatogenesis. It is important to identify the deregulated molecular mechanisms leading to a decreased in vitro spermatogenic yield. Such results will be of great help to improve organotypic culture conditions. In the present study, we not only uncovered for the first time a failure in adult Leydig cell development, but also an alteration in the expression of several steroidogenic and steroid-metabolizing genes, which could explain the accumulation of progesterone and estradiol and the deficiency of androstenedione in cultured tissues. This hyperestrogenic and hypoandrogenic environment could explain, at least in part, the low efficiency of in vitro spermatogenesis. Furthermore, we show that the addition of hCG (LH homolog) is not sufficient to facilitate Leydig cell differentiation, restore steroidogenesis and improve sperm yield. These data provide valuable information for improving culture conditions. More fundamentally, this culture system could be a useful tool for identifying factors that are essential for the differentiation and functionality of adult Leydig cells during puberty initiation.

      Recommendations For The Authors:

      This reviewer appreciates that a lot of work was put into this manuscript in terms of experiments, systems, and approaches. However, the manuscript needs significant revision, and in this reviewer's opinion is not appropriate for a broader readership journal. The results seem rather incremental, and the topic is too specialized in its current format.

      The manuscript was significantly revised taking into account the reviewer’s comments. In addition, as mentioned above, the development of a model of in vitro spermatogenesis could have wider applications and be of interest to a broader audience.

      Comments for improvement, roughly in order of appearance:

      1) Abstract - would recommend condensing to hit the main points of the manuscript.

      The abstract has been condensed as suggested.

      2) Introduction, overall - this is a rather loosely organized list of information that is not synthesized or communicated in a meaningful way. It contains overstatements and lumps together findings from both mice and primates and thus several statements for the actions of these steroid hormones are inaccurate. The authors rely much too heavily upon reviews and need to replace those with a more scholarly approach of carefully reading and citing primary literature.

      The Introduction has been reorganized to make it clearer, more synthetic, more meaningful and more accurate. Only findings from rodents are presented. We carefully read the literature and replaced most of reviews by primary literature.

      3) Results - this section was extremely difficult to read and comprehend, as it's essentially a laundry list of measurements of mRNAs, steroids, cholesterols, and proteins that go up or down or don't change at multiple ages, both in vitro and in vivo. The section would be improved greatly by an organization with rationale and concluding statements to prepare the reader for the factoid-style data that are presented.

      As suggested, the Results section has been improved by an organization with rationale and concluding statements to make it easier to read and comprehend.

      4) 47 - is this approach going to both "preserve and restore"? Sounds more like it will allow for the production of offspring, but the other goals are not going to happen from the approach listed in the latter part of that sentence - so not really "fertility restoration" but more of an insurance program that sperm can be produced for ART

      Freezing of prepubertal testicular tissue, which contains spermatogonia, is a fertility preservation option proposed to prepubertal boys with cancer prior to highly gonadotoxic treatments. Several fertility restoration strategies, which aim to allow the production of spermatozoa from cryopreserved spermatogonia, are being developed, including in vitro spermatogenesis. This sentence has been rewritten.

      5) 62 - specify whether this "decreased expression" is mRNA or protein, and is this because of a loss of Sertoli cells?

      “Decreased expression” was replaced by “decreased mRNA levels”. The results we obtained in the cited study (Rondanino et al., 2017) suggest that the decrease in Rhox5 mRNA levels is not the consequence of a change in the proportion of Sertoli cells but reflects an alteration in Rhox5 gene expression. In Figure 6U of the present study, we show indeed that there is no loss of Sertoli cells in organotypic cultures.

      6) 66 - what is "the first wave of mouse in vitro spermatogenesis"? Are these cultures from the first wave of mouse in vivo spermatogenesis, or is there a second wave of in vitro spermatogenesis? Please specify

      In the mouse, the first entry into meiosis occurs around 8-10 dpp and the first spermatozoa are produced at around 35 dpp: this is the first wave of spermatogenesis which takes place at the onset of puberty. By culturing 6 dpp-old testes for 30 days, our aim is to reproduce in vitro all the stages of this first wave of spermatogenesis, i.e. entry into meiosis, completion of meiosis and spermiogenesis.

      In the cited study (Pence et al., 2019), the authors cultured 5 dpp testes for 35 to 49 days and observed a decline in intratesticular testosterone levels in the cultured tissues, i.e. after the end of the first spermatogenic wave, compared to in vivo controls. Our sentence has been rewritten to make it clearer.

      7) 78 - is there a difference in T production by Fetal vs Adult LCs? It is this reviewer's understanding that the levels of T around birth in mice (and then a few months after birth in humans) are quite high, similar to adults. So, what are the authors suggesting here by providing the list of expressed genes in these two LC populations?

      As mentioned in the Introduction section, 17β-HSD3 – the enzyme responsible for the conversion of androstenedione to T – is not expressed in fetal Leydig cells but is expressed in adult Leydig cells. Therefore, unlike adult Leydig cells, fetal Leydig cells are not capable of synthesizing T.

      In the present study, we investigated steroidogenesis but also wondered which types of Leydig cells could be detected under in vitro conditions. It is therefore important to explain to the reader which steroidogenic proteins are expressed by the different Leydig cell populations.

      As described in O’Shaughnessy et al., 2002, levels of intratesticular T decline after birth, being very low between 10 and 20 dpp. Then, T levels increase. At 25 dpp, T levels are close to those observed at 1 dpp. T levels increase more than 16-fold between 25 and 30 dpp and then double between 30 dpp and adulthood. Therefore, intratesticular T levels around birth in mice are not as high as in adults, but are about 36-fold lower after birth than in adulthood. It has been shown that in the fetal testis, the conversion of androstenedione produced by fetal Leydig cells is achieved by the adjacent fetal Sertoli cells that express 17β-HSD3 (O’Shaughnessy et al., 2000; Shima et al., 2013). During postnatal development however, Sertoli cells lose the expression of 17β-HSD3 (O’Shaughnessy et al., 2000).

      8) 79 -99 - can the authors revise this long list of information to provide a summary of what they are trying to communicate to the reader? What is the intention of this information?

      This paragraph has been modified to make it clearer and more synthetic. As different Leydig cell markers are presented in the Results section, it is important to introduce the reader to the different types of Leydig cells, the proteins expressed by these cells and the factors involved in their proliferation and differentiation.

      9) 101-2 - replace "involved in" with a more meaningful word - and it is this reviewer's understanding that T has not been shown convincingly to have much of a role in spermatogonial development, at least in mice - that statement is likely true in primates, but not mice; provide primary literature citations to be more precise, rather than a broad review that covers multiple species

      “involved in” was replaced by “is essential for many aspects of spermatogenesis, including”. Moreover, we removed “spermatogonial proliferation and differentiation” and provide primary literature citations to be more precise.

      10) 105-7 - similar concern for E as for T, above - KO mouse models for ERalpha and beta did not show defects in spermatogenesis as described - not sure what evidence the authors are specifically referring to here - cite primary literature rather than a review on Vitamin D + estrogen

      We agree that the question of whether estrogens play a direct role in spermatogenesis was unanswered by the ER null mice. However, estrogens have been shown to be important for the long-term maintenance of spermatogenesis in the ArKO mouse (Robertson et al., 1999) and for the progression of normal germ cell development in the ENERKI mouse (Sinkevicius et al., 2009). This sentence has been reworded and primary literature is cited to be more precise.

      11) 113-4 - there is no convincing evidence this reviewer is aware of that the AR is expressed in male germ cells, and therefore T actions on germ cells are indirect, through Sertoli cells and perhaps PTMs; if there is some, this sentence needs a citation showing that

      We agree that there is no evidence that AR is expressed in male germ cells and that T acts indirectly on germ cells. This sentence has been rewritten.

      12) 114-6 - this is untrue - nowhere in that paper was testosterone or androgen even mentioned!

      This reference has been removed. We apologize for this mistake.

      13) 116-7 - again, E actions through the ERs are thought to be indirect in the testis, not acting on germ cells; if this is incorrect, please add supportive citations and explain; replace "involved" with a more meaningful word; Rhox5 has a very minor role in spermatogenesis

      In contrast to androgen receptors, which are localized in somatic cells, estrogen receptors have been found in most testicular cells, including germ cells. The studies reporting the expression of estrogen receptors in germ cells are cited in the Introduction section. The word “involved” was replaced by “promotes”.

      Rhox5 (also known as Pem) has not a very minor role in spermatogenesis. On the contrary, its expression is crucial for normal spermatogenesis and sperm maturation, as loss of Rhox5 in male mice leads to reduced fertility, increased germ cell apoptosis, decreased sperm count and decreased sperm motility (MacLean et al., 2005).

      14) 117 - Ref 29 does not support the statement about Rhox5's role in spermatogenesis

      The reference (MacLean et al., 2005), supporting the statement about Rhox5’s role in spermatogenesis, was added in the manuscript.

      15) 120 - Does FAAH have a protective role in that it is anti-apoptotic? Or just required for some other Sertoli cell function? Should re-word to be more specific.

      FAAH (fatty acid amide hydrolase), whose expression is stimulated by estrogens, has been shown to have a crucial role in promoting survival of Sertoli cells by degrading anandamide (N-arachidonoylethanolamine), an endocannabinoid which has a pro-apoptotic activity (Rossi et al., 2007).

      The sentence has been reworded to be more specific.

      16) 127 - should complete the Introduction with a sentence summarizing what was done and found, for reader clarity

      The Introduction has been completed for reader clarity.

      17) 136 - misspelled the procedure

      Orchidectomy was replaced by orchiectomy.

      18) Mice - why use half-day nomenclature for postpartum mice? This is not standard in the literature.

      Half-day nomenclature was used due to the uncertainty of the time of birth, which mostly takes place during the night. Since this is not standard in the literature, half-day nomenclature was removed in the entire manuscript.

      19) 172-3 - the half-life of RA is very short (<1 hr), and it is light-sensitive. This addition every 8 days means that retinoids are present for a very minimal window of time - are the authors sure retinoids have no requirement elsewhere during spermatogenesis? And in the literature, the measured pulse of RA in the mouse lasts >40 hours (stages VII-IX)...

      RA is mandatory for proper spermatogenesis and is needed many times during spermatogenesis (for review, see Schleif et al., 2022): RA is involved in spermatogonial differentiation, pre-meiotic activation and meiotic completion, establishment of the blood-testis barrier and spermiation. In our study, we did not add RA in the culture medium but retinol, the precursor of RA. Indeed, our previous studies have shown beneficial effects of retinol on in vitro spermatogenesis, including an increased production of spermatids with less nuclear alterations and DNA damage (Arkoun et al., 2015; Dumont et al., 2016).

      The reason we added retinol (and not RA, which has a very short half-life) in this study and in our previous studies is that it can be oxidized into RA but also be stored in Sertoli cells in the form of retinyl esters for later use. As retinol is photosensitive, handling and storage were performed in tubes covered with aluminum foil, which protects from direct light exposure.

      20) 362 - Start the Results section with a broader statement(s) that prepares the readers rather than jumping into specific experiments; it would be helpful for readers to have concluding sentences included as well for readers to navigate the Results section.

      As suggested, the Results section has been improved by an organization with rationale and concluding sentences to facilitate reading.

      21) 364 - KI67 is a marker of.

      Ki67 is widely used as a cell proliferation marker.

      22) 367 - replace "involved".

      “involved” was replaced by “necessary for”.

      23) What intensity thresholds were used to define a cell as positive or negative for a given marker? And there seemed to be no mention of controls - especially no primary antibody controls. This is a significant oversight if these were not done in parallel with every single immunostaining experiment.

      We did not apply intensity thresholds. Cells presenting detectable labeling were defined as positive, while unlabeled cells were defined as negative.

      Negative controls, performed by omitting the primary antibodies, were of course done in parallel to each immunostaining and are presented in Figure 1A, Figure 2J and Figure 5C. The mention of negative controls has been added in the Materials and methods section.

      24) 388 - INSL3 - is this referring to mRNA or protein? Protein nomenclature is used...

      INSL3 is here referring to the protein, whose concentrations were measured by radioimmunoassay.

      25) 402 - typo.

      “expect” was replaced by “except”.

      26) 409 - do mRNA levels really "determine the testicular steroidogenic potential"??

      This sentence has been reworded: “determine the testicular steroidogenic potential” was replaced by “highlight a potential deregulation of their expression”.

      27) 410 - western should not be capitalized.

      Western Blot was replaced by western blot in the entire manuscript.

      28) 405-28 - this reviewer is underwhelmed by qRT-PCR results for a handful of markers - what is the purpose? The results do not prove anything about the function of the system.

      As the differentiation of Leydig cells is not fully completed in organotypic cultures, we wanted to know which actors of the steroidogenic pathway show deregulated expression in vitro in comparison to physiological conditions, and thus which steps of the steroid hormone biosynthesis pathway may be impaired. We found that the expression of several genes encoding steroidogenic enzymes was decreased in vitro, notably that of Cyp17a1, necessary for the conversion of progesterone to androstenedione. Transcript levels of Hsd17b2, encoding an enzyme that converts estradiol to estrone and testosterone to androstenedione, were also decreased at D30.

      Our data therefore show that the expression of several steroidogenic genes and steroid metabolizing genes is deregulated in organotypic cultures but we agree that these results do not prove anything about the function of the system.

      We then found an accumulation of estradiol and progesterone, a decrease in androstenedione and unchanged testosterone levels in cultured tissues. The elevation in progesterone and the reduction in androstenedione in in vitro matured tissues could arise from the reduced expression of Cyp17a1. In addition, reduced Hsd17b2 transcript levels may explain why estradiol levels remain elevated in cultures while testosterone levels are similar to controls and androstenedione levels are low.

      29) How do the authors interpret data gleaned from tissues containing a variably-sized necrotic core?

      In the present study, the central necrotic area was consistent between all samples and variables: it represents on average 16-27% of the explants.

      As in our previous publications and recent RNA-seq analyses (Rondanino et al., 2017; Oblette et al., 2019; Dumont et al., 2023), the central necrotic area was removed so that transcript and protein levels in the healthy part of the samples (i.e. where in vitro spermatogenesis occurs) could be measured and compared with in vivo controls. In order to be able to compare the healthy part of the in vitro matured tissues with in vivo controls, transcript levels were normalized to housekeeping genes (Gapdh and Actb) or to the Leydig cell-specific gene Hsd3b1 while protein levels were normalized to ACTB or to 3β-HSD.

      30) 520 - after reading to this point, this reviewer was left confused and wondering why any of this is important to the reader unless that reader specifically works on this topic. The way the data were presented makes it nearly impossible for the reader to keep any of the data in their mind as they read. It's a seemingly endless list of ups and downs of many things under many conditions. What is the point of all of this? How will it advance our understanding of spermatogenesis? Or improve in vitro culture? Or help prepubertal cancer patients? Presumably, that will be explained in the Discussion, but at this point, this reviewer honestly has no idea what this all means. Why is this important??

      We have modified the Results section by including rationale and concluding statements to make it easier to read and follow for all readers, not necessarily for those working on this topic.

      As mentioned above, the identification of the molecular mechanisms that are deregulated in vitro will give us important insights for the optimization of the culture system. The development of an optimized model of in vitro spermatogenesis could lead to several applications, including improving our knowledge of the regulation of spermatogenesis during pubertal development.

      In this study, our main findings are that the differentiation of the adult Leydig cell lineage, steroid biosynthesis, metabolism and signaling are altered in organotypic cultures, leading to a hyperestrogenic and hypoandrogenic environment. In addition, we show that the presence of an LH homolog, known to be critical to adult Leydig cell differentiation and to stimulate steroidogenesis, does not rescue the expression of adult Leydig cell markers and of several steroidogenic genes, steroid metabolizing genes and steroid target genes. Other factors required for Leydig cell maturation and functionality will have to be tested in the future on cultured testicular tissues. Improvements to this in vitro maturation procedure in animal models may be useful for future cultures of human testicular biopsies, although we are aware that more work needs to be done before prepubertal cancer patients can benefit from this in vitro maturation approach.

      31) 619-20 - this sort of summarizes this reviewer's overall opinion of the manuscript. Not much seems to have been learned here that would justify publication in a broad readership journal like eLife. More work needs to be done to provide that sort of meaningful advance. The current work, with considerable re-writing to improve accuracy and clarity, is much better suited to a specialty journal where others who are working on this specific topic will appreciate its value.

      We have carefully considered the reviewer’s comments and modified the manuscript to improve accuracy and clarity. We understand the reviewer’s point of view, but we believe that this work may be of interest not only to labs working on fertility preservation and restoration, but also to those working on puberty initiation, germ and somatic cell maturation, steroidogenesis under physiological and pathological conditions, and on the effect of cancer therapies, drugs, chemicals and environmental agents (e.g. endocrine disruptors) on the developing testis.

      As mentioned above, we not only uncovered for the first time a failure in adult Leydig cell development, but also an alteration in the expression of several steroidogenic and steroid-metabolizing genes, which could explain the accumulation of progesterone and estradiol and the deficiency of androstenedione in cultured tissues. This hyperestrogenic and hypoandrogenic environment could explain, at least in part, the low efficiency of in vitro spermatogenesis. Furthermore, we show that the addition of hCG (LH homolog) is not sufficient to facilitate Leydig cell differentiation, restore steroidogenesis and improve sperm yield. These data provide valuable information for improving culture conditions. More fundamentally, this culture system could be a useful tool for identifying factors that are essential for the differentiation and functionality of adult Leydig cells during puberty initiation.

      32) Why are the figures repeated at the end of the manuscript?

      During the submission process, our bioRxiv preprint (which contains the figures) was merged with the same but higher quality figures.

      Reviewer #2 (Public Review):

      Preserving and restoring the fertility of prepubertal patients undergoing gonadotoxic treatments involves freezing testicular fragments and waking them up in a culture in the context of medically assisted procreation. This implies that spermatogenesis must be fully reproduced ex vivo. The parameters of this type of culture must be validated using non-human models. In this article, the authors make an extensive study of the quality of the organotypic culture of neonatal mouse testes, paying particular attention to the differentiation and endocrine function of Leydig cells. They show that fetal Leydig cells present at the start of culture fail to complete the differentiation process into adult Leydig cells, which has an impact on the nature of the steroids produced and even on the signaling of these hormones.

      The authors make an extensive study of the different populations of Leydig cells which are supposed to succeed each other during the first month of life of the mouse to end up with a population of adult and fully functional cells. The authors combine quantitative in situ studies with more global analyzes (RT-QtPCR Western blot, hormonal assays), which range from gene to hormone. This study is well written and illustrated, the description of the methods is honest, the analyses systematic, and are accompanied by multiple relevant control conditions.

      Since the aim of the study was to study Leydig cell differentiation in neonatal mouse testis cultures, the study is well conceived, the results answer the initial question and are not over-interpreted.

      My main concern is to understand why the authors have undertaken so much work when they mention RNA extractions and western blot, that the necrotic central part had to be carefully removed. There is no information on how this parameter was considered for immunohistochemistry and steroid measurements. The authors describe the initial material as a quarter testis, but they don't mention the resulting size of the fragment. A brief review of the literature shows that if often the culture medium is crucial for the quality of the culture (and in particular the supplementations as discussed by the authors here), the size of the fragments is also a determining factor, especially for long cultures. The main limitation of the study is therefore that the authors cannot exclude that central necrosis can have harmful effects on the survival and/or the growth and/or the differentiation of the testis in culture. In this sense, the general interpretation that the authors make of their work is correct, the culture conditions are not optimized.

      When using the organotypic culture system at a gas-liquid interphase, the central part of the testicular tissue becomes necrotic. As previously reported (Komeya et al., 2016), the central region receives insufficient nutrients and oxygen. In vitro spermatogenesis therefore only occurs in the seminiferous tubules present in the peripheral region. As in our previous publications and recent RNA-seq analyses (Rondanino et al., 2017; Oblette et al., 2019; Dumont et al., 2023), the central necrotic area was removed so that transcript and protein levels in the healthy part of the samples (i.e. where in vitro spermatogenesis occurs) could be measured and compared with in vivo controls. For histological and immunohistochemical analyses, only seminiferous tubules located at the periphery of the cultured fragments (outside of the necrotic region) were analyzed. Steroid measurements were performed on the entire fragments.

      The initial material was indeed a quarter testis, which represents approximately 0.75 mm3. No growth of the fragments was observed during the organotypic culture period (Figure 8-figure supplement 1). We agree with the reviewer that the composition of the culture medium is not the only parameter to be considered for the quality of the culture and that the size of the fragments is also a determining factor. We previously determined that 0.75 mm3 was the most appropriate size for mouse in vitro spermatogenesis (Dumont et al., 2016). We do not exclude at all that central necrosis can have harmful effects on the survival and/or the growth and/or the differentiation of the testis in culture. Optimization of the culture medium and culture design (so that the tissue center receives sufficient nutrients and oxygen) will be necessary to increase the yield of in vitro spermatogenesis.

      Organotypic culture is currently trying to cross the doors of academic research laboratories to become a clinical tool, but it requires many adjustments and many quality controls. This study shows a perfect example of the pitfall often associated with this approach. The road is still long, but every piece of information is useful.

      Reviewer #3 (Public Review):

      Moutard, Laura, et al. investigated the gene expression and functional aspects of Leydig cells in a cryopreservation/long-term culture system. The authors found that critical genetic markers for Leydig cells were diminished when compared to the in-vivo testis. The testis also showed less androgen production and androgen responsiveness. Although they did not produce normal testosterone concentrations in basal media conditions, the cultured testis still remained highly responsive to gonadotrophin exposure, exhibiting a large increase in androgen production. Even after the hCG-dependent increase in testosterone, genetic markers of Leydig cells remained low, which means there is still a missing factor in the culture media that facilitates proper Leydig cell differentiation. Optimizing this testis culture protocol to help maintain proper Leydig cell differentiation could be useful for future human testis biopsy cultures, which will help preserve fertility and child cancer patients.

      Methods: In line 226, there is mention that the central necrotic area was carefully removed before RNA extraction. This is particularly problematic for the inference of these results, especially for the RT-qPCR data. Was the central necrotic area consistent between all samples and variables (16 and 30FT)? How big was the area? This makes the in-vivo testis not a proper control for all comparisons. Leydig cells are not evenly distributed throughout the testis. A lot of Leydig cells can be found toward the center of the gonad, so the results might be driven by the loss of this region of the testis.

      When using the organotypic culture system at a gas-liquid interphase, the central part of the testicular tissue becomes necrotic. As previously reported (Komeya et al., 2016), the central region receives insufficient nutrients and oxygen. In vitro spermatogenesis therefore only occurs in the seminiferous tubules present in the peripheral region. As in our previous publications and recent RNA-seq analyses (Rondanino et al., 2017; Oblette et al., 2019; Dumont et al., 2023), the central necrotic area was removed so that transcript levels in the healthy part of the samples (i.e. where in vitro spermatogenesis occurs) could be measured and compared with in vivo controls. In order to be able to compare the healthy part of the in vitro matured tissues with in vivo controls, transcript levels of the selected genes were normalized to housekeeping genes (Gapdh and Actb) or to the Leydig cell-specific gene Hsd3b1.

      The central necrotic area was consistent between all samples and variables: it represents on average 16-27% of the explants.

      Moreover, we would like to point out that the gonads were cut into four fragments before in vitro cultures. It is therefore the central part of the cultured explants that was removed and not the central part of the gonads. The central part of the gonads was thus included in our analyses.

      What did the morphology of the testis look like after culturing for 16 and 30 days? These images will help confirm that the culturing method is like the Nature paper Sato et al. 2011 and also give a sense of how big the necrotic region was and how it varied with culturing time.

      Images showing mouse testicular tissues cultured for 16 and 30 days are presented in Figure 8-figure supplement 1. The cultured tissues resemble those shown by Sato et al., 2011. As mentioned above, the central necrotic area represents on average 16-27% of the explants. No significant difference in the area of the necrotic region was found between the two culture time points.

      There are multiple comparisons being made. Bonferroni corrections on p-value should be done.

      Bonferroni corrections are used when multiple comparisons are conducted. As mentioned in the Materials and methods section, multiple comparisons were not made in this study. Indeed, the non-parametric Mann-Whitney test was used to compare two conditions: in vitro vs in vivo (D16 FT vs 22 dpp, D16 CSF vs 22 dpp, D30 FT vs 36 dpp, D30 CSF vs 36 dpp, D30 FT + hCG vs 36 dpp, D30 CSF + hCG vs 36 dpp), cultures of fresh vs frozen tissues (6 dpp vs 6 dpp CSF, D16 FT vs D16 CSF, D30 FT vs D30 CSF, D30 FT + hCG vs D30 CSF + hCG) and cultures with vs without hCG (D30 FT + hCG vs D30 FT, D30 CSF + hCG vs D30 CSF). These comparisons were added in the Materials and methods section.

      Results: In the discussion, it is mentioned that IGF1 may be a missing factor in the media that could help Leydig cell differentiation. Have the authors tried this experiment? Improving this existing culturing method will be highly valuable.

      The decreased Igf1 mRNA levels found in the present study are in line with the RNA-seq data of Yao et al., 2017. As mentioned in the Discussion section, the addition of IGF1 in the culture medium led to a modest increase in the percentages of round and elongated spermatids in cultured mouse testicular fragments (Yao et al., 2017). However, the effect of IGF1 supplementation on Leydig cell differentiation was not investigated. The supplementation of organotypic culture medium with IGF1 is currently being tested in our research team.

      Add p-values and SEM for qPCR data. This was done for hormones, should be the same way for other results.

      p-values and SEM are shown for both qPCR and hormone data.

      Regarding all RT-qPCR data-There is a switch between 3bHSD and Actb/Gapdh as housekeeping genes. There does not seem to be as some have 3bHSD and others do not. Why do Igf1 and Dhh not use 3bHSD for housekeeping? If this is the method to be used, then 3bHSD should be used as housekeeping for the protein data, instead of ACTB. Also, based on Figure 1B and Figure 2A (Hsd3b1) there does not seem to be a strong correlation between Leydig cell # and the gene expression of Hsd3b1. If Hsd3b1 is to be used as a housekeeper and a proxy for Leydig cell number a correlation between these two measurements is necessary. If there is no correlation a housekeeping gene that is stable among all samples should be used. Sorting Leydig cells and then conducting qPCR would be optimal for these experiments.

      Hsd3b1 was used as a housekeeping gene only to normalize the mRNA levels of Leydig cell-specific genes. Therefore, Igf1 and Dhh transcript levels were not normalized with Hsd3b1 since Igf1 is expressed by several cell types in the testis (Leydig cells, Sertoli cells, peritubular myoid cells) and Dhh is expressed by Sertoli cells.

      Regarding western blots, the expression of AR, CYP19 and FAAH could not be normalized with 3-HSD since AR is expressed by Leydig cells, Sertoli cells and peritubular myoid cells, CYP19 is expressed by Leydig cells and germ cells and FAAH is expressed by Sertoli cells. For CYP17A1 however, 3B-HSD was used as housekeeping instead of ACTB (Figure 2G).

      No correlation was found between the number of Leydig cells per cm2 of testicular tissue shown in Figure 1 and Hsd3b1 mRNA levels presented in Figure 2. However, this result was expected since on the one hand the number of Leydig cells per cm2 was determined in the peripheral region of one tissue section whereas on the other hand Hsd3b1 transcript levels were measured in the entire peripheral region of the cultured fragments. The correction factor used for the analysis of genes expressed in Leydig cells present in the healthy part of the cultured tissues was therefore the Leydig cell selective marker Hsd3b1, as previously described (Cacciola et al., 2013).

      Figure 2A (CYP17a1): It is surprising that the CYP17a1 gene and protein expression is very different between D30FT and 36.5dpp, however, the immunostaining looks identical between all groups. Why is this? A lower magnification image of the testis might make it easier to see the differences in Cyp17a1 expression. Leydig cells commonly have autofluorescence and need a background quencher (TrueBlack) to visualize the true signal in Leydig cells. This might reveal the true differences in Cyp17a1.

      RT-qPCR and western blot analyses show that both Cyp17a1 mRNA levels and CYP17A1 protein levels are decreased in organotypic cultures at D30. However, we agree that such a decrease is not visible in immunostaining. No autofluorescence of Leydig cells could be observed in the negative controls (Figure 2J).

      Figure 3D: there are large differences in estradiol concentration in the testis. Could it be that the testis is becoming more female-like? Leydig and Sertoli cells with more granulosa and theca cell features? Were any female markers investigated?

      We show in the present study that the expression levels of the Sertoli cell-specific gene Dhh are not reduced in organotypic cultures. We also previously found that the expression levels of the Sertoli cell-specific gene Amh were not reduced in in vitro matured testicular tissues (Rondanino et al., 2017). Moreover, we have recently shown that Sox9, encoding a testis-specific transcription factor, is expressed in organotypic cultures (Dumont et al., 2023). Our recent transcriptomic analysis also revealed that the transcript levels of the pro-male sexual differentiation marker Sry and of the Sertoli cell-specific gene Dmrt1 remained unchanged in organotypic cultures compared to in vivo controls (Dumont et al., 2023). In addition, no increase in the mRNA levels of the female sex-determining genes Foxl2 and Rspo1 was found in vitro (Dumont et al., 2023). However, we cannot rule out that in vitro cultured testes are becoming more female-like as the expression of Hsd17b3, encoding an androgenic enzyme, is reduced (this study) while the expression of the feminizing gene Wnt4 is upregulated (Dumont et al., 2023).

      Figure 3D and Figure 5A: It is hard to imagine that intratesticular estradiol is maintained for 16-30 days without sufficient CYP19 activity or substrate (testosterone). 6.5 dpp was the last day with abundant CYP19 expression, so is most of the estrogen synthesized on this first day and it sticks around? Are there differences in estradiol metabolizing enzymes? Is there an alternative mechanism for E production?

      In the present study, abundant CYP19 expression was indeed found at 6 dpp. However, the expression of this enzyme was not measured between 6 dpp and D16. Therefore, we cannot be sure that 6 dpp is the last day with abundant CYP19 expression. We assume that the estradiol synthesized before D16 may then accumulate within the cultured tissues. In our study, we quantified the transcript levels of Sult1e1, encoding an estradiol metabolizing enzyme. SULT1E1 is thought to play a physiological role in protecting Leydig cells from estrogen-induced biochemical lesions (Tong et al., 2004). A reduction in Sult1e1 mRNA levels was found at D30 in comparison to in vivo controls, but this may occur earlier during organotypic culture. In addition, decreased transcript levels of Hsd17b2, which encodes an estrogen metabolizing enzyme that converts estradiol to estrone, were found at D30 in this study. We suggest in the Discussion section that elevated estradiol levels in cultured tissues could be a consequence of low Sult1e1 and Hsd17b2 expression. Our recent transcriptomic analyses show that the levels of Cyp1a1, Cyp1b1 and Comt, encoding other estrogen metabolizing enzymes, are unchanged in organotypic cultures (Dumont et al., 2023). To our knowledge, there is no alternative mechanism for estradiol production.

      Recommendations For The Authors:

      1) The acronyms, PLC, SLC, ILC, ALC, and FLC, become hard to follow. It is recommended to spell out the names.

      PLC was replaced by progenitor Leydig cells, SLC by stem Leydig cells, ILC by immature Leydig cells, ALC by adult Leydig cells and FLC by fetal Leydig cells in the entire manuscript.

      2) All Figures: Use letters for each bar graph. Difficult to make a connection from text to figure.

      A letter was added to each bar graph.

      3) Supplemental figure 1: Change "Changement du milieu" to English.

      These words were replaced by “Medium change”.

      4) Catalog numbers for antibodies are necessary.

      The catalog numbers of the antibodies used in this study are presented in Supplementary Table 1.

    1. have had to relearn this lesson many times before it began to stick

      I think it's really important to note that aside from just one semester of reflective journaling in UNIV 101, this is still a relatively new practice to many students; there's likely to be a learning curve and adjustment period as we begin completing assignments in this course.

    1. SubmissionofALLassignmentsisexpectedtobeontimeandintheprescribedformatandmanner.Generally,lateassignmentsbeyondoneweekarenotaccepted.Lateassignmentswithinoneweekaftertheduedatewillbereducedby10%ofthepossiblepointsforthisdelay.Exceptionsmaybearrangedbycommunicatingyourextenuatingcircumstancetoyourinstructorpriortotheduedate.Electronicsubmissionofassignmentsnotinthespecifiedformat(softwareavailableoncampus)orfailed/accessdeniedlinkswouldalsobeconsideredlate.Theseassignments5

      this is a good thing to know about the late police becausre this is going to show students like me to just get the work done when we need to and then when we need to turn things in late we now hoe much it will be delyed by and with the turning assignment this is going because we have to make sure it's in the right format that it is needed to be in.

    2. SubmissionofALLassignmentsisexpectedtobeontimeandintheprescribedformatandmanner.Generally,lateassignmentsbeyondoneweekarenotaccepted.Lateassignmentswithinoneweekaftertheduedatewillbereducedby10%ofthepossiblepointsforthisdelay.Exceptionsmaybearrangedbycommunicatingyourextenuatingcircumstancetoyourinstructorpriortotheduedate.Electronicsubmissionofassignmentsnotinthespecifiedformat(softwareavailableoncampus)orfailed/accessdeniedlinkswouldalsobeconsideredlate.Theseassignments5

      this is a good thing to know about the late police becausre this is going to show students like me to just get the work done when we need to and then when we need to turn things in late we now hoe much it will be delyed by and with the turning assignment this is going because we have to make sure it's in the right format that it is needed to be in.

    3. SubmissionofALLassignmentsisexpectedtobeontimeandintheprescribedformatandmanner.Generally,lateassignmentsbeyondoneweekarenotaccepted.Lateassignmentswithinoneweekaftertheduedatewillbereducedby10%ofthepossiblepointsforthisdelay.Exceptionsmaybearrangedbycommunicatingyourextenuatingcircumstancetoyourinstructorpriortotheduedate.Electronicsubmissionofassignmentsnotinthespecifiedformat(softwareavailableoncampus)orfailed/accessdeniedlinkswouldalsobeconsideredlate.Theseassignments5

      this is a good thing to know about the late police becausre this is going to show students like me to just get the work done when we need to and then when we need to turn things in late we now hoe much it will be delyed by and with the turning assignment this is going because we have to make sure it's in the right format that it is needed to be in.

    1. Over the course of the last 3 or 4 months I've been travelling ... around the Gulf and Atlantic Gulfstream shelf areas. I've been "discussing with myself" the need for an astrobiology and marine oceanography course "to search for exactly this kind of life ..."It's part of my ongoing reading and research into what I'm calling "The SCORPIO Disclosure" and will probably wind up turning into a book. Here what's found is a series of life forms that could help us genetically engineer a bio-computer that could thrive deep in space, in the place between stars. I think it's vital to the survival of a multistar/multihomed computing infrastructure, which is "frankly, obvious or not" what I think the "stuff of Heaven" literally is. I didn't get to "Anaconda" or actually seeing a "spinning Gravitron like ring space station yet; but that's also high on the list of things we'd need to "thrive in a world that raises it's thrown high above the ISS/Mir .." Which again, is "something that would outlive" the planet Earth, another thing high on my list of requirements for a near-immortal-afterlife. I'm hoping people "see" that I'm very much not wrong about that, nobody wants to be stuck in one place ... especially one that has a series of movies literally about it being struck by an incoming asteroid, a story about a literal ongoing collision with Andromeda ... and "religious secret lore" that connects the Hindu "red sun, Betelgeuse" to Beth-El and ... "Ash Wednesday" ...That same strange dot, once a year, around Pesach, "dimming as it's said to have done ... recently, in 2019.https://schmidtocean.org/scientists-discover-new...I'd like to see this as a sort of "Exodus to places bigger and better" than just Mars; which is also something I think I was not only named after, but have written a series of "info articles" about; Over time, "learning" how these specific stepping stones appear to be part of a real map and plan to space colonization; with technology "really being researched and disclosed" related to things like Graphene based supercomputers, tunnels under the surface of Mars and ...- http://fromthemachine.org/the_story_of_exodus.html- https://adamlamda.github.io/2017-07-22-roe-v-wade.html- lamc.la/MARSHALL.htmlI stopped writing about tunnels on Mars about the same time I decided I wouldn't want to wakeup there, which also hails from places like Vonnegut's Kilgore Trout, and what is probably realish connections to the inspiration of stories and movies like "Total Recall" which depict much of what I'm talking about.At this point the series of dreams and desires have evolved into what I called "Boca offshore Haulover" and tie to that specific place, where I physically was when I sent a series of FOIA requests to the military locations which publicized the "astral launch" of Nuclear missiles during a Cold War era "joint effort" with the USSR.Fishbowl, Wish You Were Here; and "back in the USSR" all very much related to here and now; this 2019 connection to COVID, Ragnarok and Korangard which has "opened my eyes significantly" adding in Taylor Momsen's early answer ... "like diamonds in the sky that is what we are told" ... she sang a decade or so before Graphene and this story evolved to the point of "being able to physically colonize the Corona's of Proxima Centauri; et, al ...Again, something that could create, perpetuate and foster a civilization "evolved past life and death"; what I like to think Heaven is. Of course, the truth is we are near the SOS of "the sound of silence" and "just another brick in the wall" as I write to you, suggesting "call a report" has evolved into "call the Wallstreet Journal" See what they say?

      Over the course of the last 3 or 4 months I've been travelling ... around the Gulf and Atlantic Gulfstream shelf areas. I've been "discussing with myself" the need for an astrobiology and marine oceanography course "to search for exactly this kind of life ..."

      It's part of my ongoing reading and research into what I'm calling "The SCORPIO Disclosure" and will probably wind up turning into a book. Here what's found is a series of life forms that could help us genetically engineer a bio-computer that could thrive deep in space, in the place between stars.

      I think it's vital to the survival of a multistar/multihomed computing infrastructure, which is "frankly, obvious or not" what I think the "stuff of Heaven" literally is.

      I didn't get to "Anaconda" or actually seeing a "spinning Gravitron like ring space station yet; but that's also high on the list of things we'd need to "thrive in a world that raises it's thrown high above the ISS/Mir .."

      Which again, is "something that would outlive" the planet Earth, another thing high on my list of requirements for a near-immortal-afterlife. I'm hoping people "see" that I'm very much not wrong about that, nobody wants to be stuck in one place ... especially one that has a series of movies literally about it being struck by an incoming asteroid, a story about a literal ongoing collision with Andromeda ... and "religious secret lore" that connects the Hindu "red sun, Betelgeuse" to Beth-El and ... "Ash Wednesday" ...

      That same strange dot, once a year, around Pesach, "dimming as it's said to have done ... recently, in 2019.

      https://schmidtocean.org/scientists-discover-new...

      I'd like to see this as a sort of "Exodus to places bigger and better" than just Mars; which is also something I think I was not only named after, but have written a series of "info articles" about;

      Over time, "learning" how these specific stepping stones appear to be part of a real map and plan to space colonization; with technology "really being researched and disclosed" related to things like Graphene based supercomputers, tunnels under the surface of Mars and ...

      I stopped writing about tunnels on Mars about the same time I decided I wouldn't want to wakeup there, which also hails from places like Vonnegut's Kilgore Trout, and what is probably realish connections to the inspiration of stories and movies like "Total Recall" which depict much of what I'm talking about.

      At this point the series of dreams and desires have evolved into what I called "Boca offshore Haulover" and tie to that specific place, where I physically was when I sent a series of FOIA requests to the military locations which publicized the "astral launch" of Nuclear missiles during a Cold War era "joint effort" with the USSR.

      Fishbowl, Wish You Were Here; and "back in the USSR" all very much related to here and now; this 2019 connection to COVID, Ragnarok and Korangard which has "opened my eyes significantly" adding in Taylor Momsen's early answer ... "like diamonds in the sky that is what we are told" ... she sang a decade or so before Graphene and this story evolved to the point of "being able to physically colonize the Corona's of Proxima Centauri; et, al ...

      Again, something that could create, perpetuate and foster a civilization "evolved past life and death"; what I like to think Heaven is.

      Of course, the truth is we are near the SOS of "the sound of silence" and "just another brick in the wall" as I write to you, suggesting "call a report" has evolved into "call the Wallstreet Journal"

      See what they say?

    1. https://www.instagram.com/p/Cu74F5lt3lr/I have "requests for comments" in several places. I'm honestly not sure it's possible to have a coherent conversation about the SEPTEMBER SOS; that was decades earlier just a "Simon and Garfunkel" song ... Today though, it's the whole of Rosh Hashanah, Yom Kippur, the months of June and July; octagons, Septuagint's and all of religion and history .. sort of "saying i bet you can't start public written conversation"nanny nanny boo boo

      can you?

      can you honestly even fathom what a "conversation" about what is going on would look like?

      where did you wake up? when?

      how long have we been looking for "here's your something" or ... Septuagint 9:11 really matters.

    1. civilly, as

      civilly in an online environment just as one would do in a face-to-face setting, but recognizing that it's easier to slide into incivility without the constrains afforded by face-to-face encounters.

    1. The largest

      Ah. I think conceptually (and physically) separating them earlier has its advantages, including if/when stability in the face of sea level rise is discussed. (Even then it's just framing, of course.)

      I've never heard the Peninsular Ice Sheet referred to as an "ice sheet." Given that it's so small, it's probably more akin to an icefield than ice sheet (or even ice cap). Then again, I'm not familiar with it, and so am fine with being overruled.

    1. Author Response

      eLife assessment

      This useful paper examines changes (or lack thereof) in birds' fear response to humans as a result of COVID-19 lockdowns. The evidence supporting the primary conclusion is currently inadequate, because the model used does not properly account for many potentially confounding factors that could influence the study's outcomes. If the analytic approach were improved, the findings would be of interest to urban ecologists, behavioral biologists and ecologists, and researchers interested in understanding the effects of COVID-19 lockdowns on animals.

      Many thanks for these supportive words. We did our best to improve our manuscript according to the reviewers and editor comments. Importantly, we regret being unclear in the Methods, as our models already controlled for most of the confounds (see below) discussed by the reviewers.

      For example, given that a single observer collected the data at most sites, site as a random intercept in the models controls also for the observer effects (which is one of the reasons why site is in the model). We added details to Methods (L352-356, see also “Statistical analyses” in the main text).

      The first reviewer asked us to use “some measure of urbanity (e.g. Human Footprint Index) that varies across the cities included here”. Our main results are now based on country-specific models and hence, the use of a single value predictor for each city is not appropriate. Please, see also below.

      The second reviewer is concerned about multicollinearity in our models because of the 0.95 correlation between Period and Stringency Index. However, these are key predictor variables of interest that have never been used within the same model as predictors. We now clearly explain this in the Methods (L458-538, 548-550) and within legend of Figure S2.

      The third reviewer suggested that our models would benefit from controlling for day in the species-specific breeding cycle. Although we don’t have precise city-specific information on the timing of breeding stages in the sampled populations of birds, we partly control for these effects by including a random intercept of day within each year and species. This random factor explained most of the variance (see Table S1-S2) – something that could have been expected. In other words, we do control for what the third reviewer asked for. Similarly, we account for habitat features that may influence escape distance by including site in the models. Site usually refers to a specific park (we assume that within-park heterogeneity is lower than between park variation) and hence partly addresses the reviewer’s concern. Again, we highlight this within the Methods (L466-476).

      Reviewer #1 (Public Review):

      This paper uses a series of flight initiation "challenges" conducted both prior to and during COVID-19-related restrictions on human movement to estimate the degree to which avian escape responses to humans changed during the "anthropause". This technique is suitable for understanding avian behavioral responses with a high degree of repeatability. The study collects an impressive dataset over multiple years across five cities on two continents. Overall the study finds no effect of lockdown on avian escape distance (the distance at which the "target" individual flees the approaching observer). The study considers the variable of interest as both binary (during lockdown or prior to lockdown) and continuous, using the Oxford Stringency Index (with neither apparently affecting escape distance). Overall this paper presents interesting results which may suggest that behavioral responses to humans are rather inflexible over "short" (~2 year) timespans. The anthropause represents a unique opportunity to disentangle the mechanistic drivers of myriad hypothesized impacts humans have on the behavior, distribution, and abundance of animals. Indeed, this finding would provide important context to the larger body of literature aimed at these ends.

      Thank you very much for your positive feedback.

      However, the paper could do more to carefully fit this finding into the broader literature and, in so doing, be a bit more careful about the conclusions they are able to draw given the study design and the measures used. Taking some of these points (in no particular order):

      Thank you. We did our best in addressing your comments (see below and updated Methods, Results and Discussion sections).

      1) Oxford Stringency Index is a useful measure of governmental responses to the pandemic and it's true that in some scenarios (including the (Geng et al. 2021) study cited by this paper) it can correlate with human mobility. However, it is far from a direct measure of human mobility (even in the Geng study, to my reading, the index only explained a minority of the variation). Moreover, particular sub-components of the index are wholly unrelated to human mobility (e.g. would changes to a country's public information campaign lead to concomitant changes in urban human mobility?). Finally, compliance with government restrictions can vary geographically and over time (i.e. we might expect lower compliance in 2021 than in 2020) and the index is calculated at the scale of entire countries and may not be very reflective of local conditions. Overall this paper could do more to address the potential shortcomings of the Oxford Stringency Index as a measure of human mobility including attempting to validate the effect on human mobility using other datasets (e.g. the google dataset and/or those discussed in (Noi et al. 2022). This is of critical importance since the fundamental logic of the experimental design relies on the assumption that stringency ~ mobility.

      Thank you for this comment. First, Oxford Stringency Index seemed to us as the best available index for our purposes, i.e to estimate people's mobility during the shutdown because restrictions surely influenced the possibility that people would be outside, and because the index is a country-specific estimate. However, in addition, we now checked all indices mentioned in Noi et al. 2022 and found useful only the Google Mobility Reports, which we now use, because (a) it is publicly available, (b) it is available also for territories outside US, and (c) provides data for each city included in our dataset as well as for urban parks where most of our data were collected. Note that some platforms are no longer providing their mobility data (e.g. Apple).

      However, Google Mobility provides day-to-day variation in human mobility, whereas we are interested in overall increase/decrease in human mobility. Nevertheless, we correlated the Google mobility index with the Stringency index and found that human mobility generally decreases with the strength of the anti-pandemic measures adopted in sampled countries (albeit the effect for some countries, e.g. Poland, is small; Fig. 5).

      Moreover, we also added analysis using # of humans collected directly in the field during escape trials (e.g. Fig. 6 and S6) and found that the link between # of humans and Stringency index or Google Mobility was weak and noise, 95%CIs widely crossing zero (Fig. 6).

      Importantly, if we use Google Mobility and # of humans, respectively, as predictors of escape distance, the results are qualitatively very similar to results based on Oxford Stringency Index (Fig. S6), or Period, with tiny effect sizes for both (95%CIs for Google Mobility -0.3 – 0.06, Table S5, for # of humans -0.12 – 0.02, Table S6) supporting our previous conclusions.

      Note that Google Mobility and the number of humans have their limitations (see our comment to the editor and the Methods section in the main manuscript, e.g. L418-433). The lack of Google Mobility data for years before the COVID-19 pandemic does not allow us to fully explore whether overall human activity decreased during COVID-19 or not (our test for period prior and during COVID-19). If the year 2022 reflects a return to “normal” (which is to be disputed due to COVID-19-driven rise in home office use) the 2020 and 2021 had on average lower levels of human activity (Fig. 4). Whether such a difference is biologically meaningful to birds is unclear given the immense day-to-day change in human mobility and presence (Fig 4). Moreover, the number of humans capture within- and between-day variation rather than long-term changes in human presence.

      We added details on the new analysis into the method and results sections (e.g. Fig. 4-6; L142-165, 418-438, 495-535) and Supplementary Information (Figs. S5-S9 and associated Tables) and discuss the problematic accordingly. Moreover, to enhance clarity about country specific effect (or their lack), we also add country specific estimates to the Results (Fig. 1 and Fig. S6 and respective Tables). Finally, our statistical design and random structure of the model allowed us to control for spatial and temporal variation in compliance with government restrictions.

      2) The interpretation of the primary finding (that behavioral responses to humans are inflexible) could use a bit more contextualization within the literature. Specifically, the study offers three potential explanations for the observed invariance in escape response: 1) these behaviors are consistent within individuals and this study provides evidence that there was no population turnover as a result of lockdowns; 2) escape response is linked to other urban adaptations such that to be an urban-dwelling species dictates escape response; and/or 3) these populations already exhibit maximum habituation and the reduction in human mobility would only have increased that habituation but that trait is already at a boundary condition. Some comments on each of these respectively:

      Thank for these comments. We incorporated them in the main text (L293-329). Your point 1) corresponds to our point (i): “Most urban bird species in our sample may be relatively inflexible in their escape responses because the species may be already adapted to human presence” (L293-306); your point 2) to our point (ii): “Urban environment might filter for bold individuals (Carrete and Tella, 2013, 2010; Sprau and Dingemanse, 2017). Thus, the lack of consistent change in escape behaviour of urban birds during the COVID-19 shutdowns may indicate an absence (or low influx) of generally shy, less tolerant individuals and species from rural or less disturbed areas into the cities…” (L307-314); your point 3) to our point (iii): “Urban birds might have been already habituated to or tolerant of variation in human presence, irrespective of the potential changes in human activity patterns” (L315-329). To distinguish between (ii) and (iii) or the two from (i), individually-marked birds and comprehensive genetic analyses are needed, which we now note in the Discussion (L330-348). Importantly, we also discuss that the lack of response might be due to relatively small changes in human activity (L253-292), which we unfortunately could not fully quantify.

      a) Even had these populations turned over as a result of a massive rural-to-urban dispersal event, it's not clear that the escape distance in those individuals would be different because this paper does not establish that these hypothetical rural birds have a different behavioral response which would be constant following dispersal. Thus the evidence gathered here is insufficient to tell us about possible relocations of the focal species.

      Thank you for this point. We address this point in the Introduction and Discussion (L92-101, 307-314). Rural bird populations/individuals are on average less tolerant of humans than urban birds (e.g. Díaz et al. 2013, PloS One 8:e64634; Tryjanowski et al. 2020, J Tropic Ecol 36:1-5; Mikula et al. 2023, Nat Commun 14:2146) and at the same time, bird individuals seem consistent in their escape responses (Carrete & Tella 2010, Biol Lett 23:167–170; Carrete & Tella 2013, Sci Rep 3:1–7).

      Additionally, the paper cites several papers that found no changes in abundance or movements of animals in response to lockdowns but ignore others that do. For example: (Wilmers et al. 2021), (Warrington et al. 2022) (though this may have been published after this was submitted...), and (Schrimpf et al. 2021).

      We added the papers (L89-91). Thank you!

      There is a missed opportunity to consider the drivers of some of these results - the findings in this paper are interesting in light of studies that did observe changes in space use or abundance - i.e. changes in space use could arise precisely because responses to humans are non-plastic but the distribution and activities of humans changed.

      Thank you. Indeed, we now address this in the Discussion (L303-306): “However, some studies reported changes in the space use by wildlife (Schrimpf et al., 2021; Warrington et al., 2022; Wilmers et al., 2021). and these could arise, as our results indicate, from fixed and non-plastic animal responses to humans who changed their activities”.

      To wit, the primary finding here would imply that the reaction norm to human presence is apparently fixed over such timescales - however, and critically, the putative reduction in human activity/mobility combined with fixed responses at the individual level might then imply changes in avian abundance/movement/etc.

      Unfortunately, we have not measured changes in avian abundance or movements. But, please, note that the change in human mobility in sampled cities might be not as dramatic as initially thought and we consider this scenario to be most plausible in explaining no significant differences in avian escape responses before and during the COVID-19 shutdowns (see Fig. 4). Nevertheless, we add your point into the Discussion: If our findings imply that in birds the reaction norm to human presence is fixed over the studied temporal scale, the putative changes in human presence might then imply changes in avian abundance or movement (L293 and text below it).

      b) If this were the case, wouldn't this be then measurable as a function of some measure of urbanity (e.g. Human Footprint Index) that varies across the cities included here? Site accounted for ~15% of the total variation in escape distance but was treated as a random effect - perhaps controlling for the nature of the urban environment using some e.g. remotely sensed variable would provide additional context here.

      Urbanity mirrors the long-term level of human presence in cities whereas we were interested mainly in the rather short-term effects of potential changes of human presence on bird behaviour. Thus, we are not sure how adding such variable will help elucidating the current results. Please, also note that we added the country-specific analysis. Site indeed accounted for considerable amount the total variance in escape distance and that is why it was included as random intercept, which controls for non-independents of data points from each city. This could partly help us to control for difference in habitat type (e.g. urbanization level) within cities.

      c) Because it's not clear the extent to which the populations tested had turned over between years, the paper could do with a bit more caution in interpreting these results as behavioral. This study spans several years so any response (or non-response) is not necessarily a measure of behavioral change because the sample at each time point could (likely does) represent different individuals. In fact, there may be an opportunity here to leverage the one site where pre-pandemic measures were taken several years prior to the pandemic. How much variance in the change in escape distance is observed when the gap between time points far exceeds the lifetime of the focal taxa versus measures taken close in time?

      We believe the initial Fig S4, now Figure 2, addresses this point. The between years temporal variation in FIDs exceeds the variation due to lockdowns. This is true both for measures taken in consecutive years, as well as for measures taken far apart.

      d) Finally, I think there are a few other potential explanations not sufficiently accounted for here:

      i) These behaviors might indeed be plastic, but not over the timescales observed here.

      We agree and have added this point (L301-303). Thank you.

      ii) Time of year - this study took place during the breeding season. The focal behavior here varies with the time of year, for example, escape distance for many of these species could be tied up in nest defense behaviors, tradeoffs between self-preservation and e.g. nest provisioning, etc.

      Please, note that we controlled for the date in our analyses. Date was used as a proxy for the progress in the breeding season (L463-464 and Fig. 1 caption). Note that we collected data only from foraging or resting individuals, and data were neither collected near the nest sites nor from individuals showing warning behaviours, which we now note (L400-401).

      iii) Escape behaviors from humans are adaptively evolved, strongly heritable, and not context dependent - thus we would only expect these behaviors to change on evolutionary timescales.

      We discussed this at L307-308 and 381-383. Escape behaviors from humans are highly consistent for individuals, populations, and species (Carrete & Tella 2010, Biol Lett 23:167–170; Díaz et al. 2013, PloS One 8:e64634; Mikula et al. 2023, Nat Commun 14:2146). Whether such behavior is consistent across contexts is less clear (e.g. Diamant et al. 2023, Proc Royal Soc B, in press; but see, e.g. Radkovic et al. 2019, J Ecotourism 18:100-106; Gnanapragasam et al. 2021, Am Nat 198:653-659). Escape distance is often not measured simultaneously, for example, with human presence. In other words, whereas general level of human presence may have no effect on escape distance, the day-to-day or hour-to-hour variations might. We need studies on fine temporal scales (day-to-day or hour-to-hour) using marked individual to elucidate this phenomenon.

      iv) See point one above - it's possible that the lockdown didn't modify human activity sufficiently to trigger a behavioral response or that the reaction norm to human behavior is non-linear (e.g. a threshold effect).

      We agree, now use also Google Mobility Reports and # of humans data to elucidated this phenomenon and have added such interpretations to L253-292 and, e.g. Fig. 4.

      LITERATURE CITED Geng DC, Innes J, Wu W, Wang G. 2021. Impacts of COVID-19 pandemic on urban park visitation: a global analysis. J For Res 32:553-567. doi:10.1007/s11676-020-01249-w

      Noi E, Rudolph A, Dodge S. 2022. Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework. Int J Geogr Inf Sci.

      Schrimpf MB, Des Brisay PG, Johnston A, Smith AC, Sánchez-Jasso J, Robinson BG, Warrington MH, Mahony NA, Horn AG, Strimas-Mackey M, Fahrig L, Koper N. 2021. Reduced human activity during COVID-19 alters avian land use across North America. Sci Adv 7:eabf5073. doi:10.1126/sciadv.abf5073

      Warrington MH, Schrimpf MB, Des Brisay P, Taylor ME, Koper N. 2022. Avian behaviour changes in response to human activity during the COVID-19 lockdown in the United Kingdom. Proc Biol Sci 289:20212740. doi:10.1098/rspb.2021.2740

      Wilmers CC, Nisi AC, Ranc N. 2021. COVID-19 suppression of human mobility releases mountain lions from a landscape of fear. Curr Biol 31:3952-3955.e3. doi:10.1016/j.cub.2021.06.050

      Reviewer #2 (Public Review):

      Mikula et al. have a large experience studying the escape distances of birds as a proxy of behavioral adaptation to urban environments. They profited from the exceptional conditions of social distance and reduced mobility during the covid-19 pandemic to continue sampling urban populations of birds under exceptional circumstances of low human disturbance. Their aim was to compare these new data with data from previous "normal" years and check whether bird behavior shifted or not as a consequence of people's lockdown. Therefore, this study would add to the growing body of literature assessing the effect of the covid-19 shutdown on animals. In this sense, this is not a novel study. However, the authors provide an interesting conclusion: birds have not changed their behavior during the pandemic shutdown. This lack of effects disagrees with most of the previously published studies on the topic. I think that the authors cannot claim that urban birds were unaffected by the covid-19 shutdown. I think that the authors should claim that they did not find evidence of covid-19-shutdown effects. This point of view is based on some concerns about data collection and analyses, as well as on evolutionary and ecological rationale used by the authors both in their hypotheses and results interpretation. I will explain my criticisms point by point:

      We are grateful for your positive appraisal of our manuscript, as well as for your helpful critical comments. We toned down the discussion to claim, as suggested by you, that we did not find evidence for effects of covid-19-shutdowns on escape behaviour of birds in urban settings (see Results and Discussion sections). In general, we attempted to provide a more nuanced discussion and reporting of our findings. We also changed the manuscript title to “Urban birds' tolerance towards humans was largely unaffected by the COVID-19 shutdowns” and added validation using Google Mobility Reports (Fig. 5 & S6, Table S3a and S5) and the actual number of humans (Fig. 6 and S6; Table S3b-e and S6). Note however that there is only a single robust study on the topic of shutdown and animal escape distances (Diamant et al. 2023, Proc Royal Soc B, in press), i.e. the topic is largely unexplored (e.g. L99-101), whereas we discuss our finding in light of shutdown influences on other behaviours (L293-329).

      1) The authors used ambivalent, sometimes contradictory, reasoning in their predictions and results interpretation. Some examples:

      We tried to clarify our reasoning and increased consistency in our claims in the Introduction. Please, note that we simplified the Introduction and now provide one main expectation: FIDs of urban birds should increase with decreased human presence. This pattern is robustly empirically documented, regardless of the mechanism involved (e.g. Díaz et al. 2013, PloS One 8:e64634; Tryjanowski et al. 2020, J Tropic Ecol 36:1-5; Mikula et al. 2023, Nat Commun 14:2146). Please, see our revised Discussion for a more comprehensive discussion of mechanisms which could explain the patterns described in our study.

      1.1) The authors claimed that urban birds perceive humans as harmless (L224), but birds actually escape from us, when we approach them... Furthermore, they escape usually 5 to 20 m away. This is more distance that would be necessary just to be not trampled.

      We agree and have deleted mentions that humans are perceived as harmless.

      1.2) If we are harmless, why birds should spend time monitoring us as a potential threat (L102)? Indeed, I disagree with the second prediction of the authors. I could argue that reduced human activity should increase animal vigilance because real bird predators (e.g. raptors) may increase their occurrence or activity in empty cities. If birds should increase their vigilance because the invisible shield of human fear of their predators is no longer available, then I would expect longer escape distances.

      Thank you for this comment. We deleted this prediction and largely rewrote Introduction based on your comments and comments from the other reviewers.

      1.3) To justify the same escape behavior shown by birds in pre- and pandemic conditions from an adaptive point of view, the authors argued a lack of plasticity and a strong genetic determination of such behavior. This contravenes the plasticity proposed in the previous point or the expected effect of the stringency index (L112).

      We now attempted to write this more clearly while incorporating your suggestions. In the Discussion, we now propose various hypothesis that can, but need not be mutually exclusive. Please, note that we simplified the Introduction and now provide one main hypothesis: FIDs of urban birds should increase with decreased human presence.

      In my opinion, some degree of plasticity in the escape behavior would be really favorable for individuals from an adaptive perspective, as they may face quite different fear landscapes during their lives. Looking at the figures, one can see notable differences in the escape distance of the same species between sites in the same city. As I can hardly imagine great genetic differences between birds sampled in a park or a cemetery in Rovaniemi, for instance, I would expect a major role of plasticity to explain the observed variability. Furthermore, if escape behavior would not be plastic, I would not expect date or hour effects. By including them in their models, the authors are accepting implicitly some degree of plasticity.

      We regret being unclear. We do accept some degree of plasticity. Yet, our study design prohibits the assessment of the degree of individual plasticity because sampled birds were not individually marked and approached repeatedly. We tried to soften the statements in our Discussion to not fully dismiss a possibility that urban birds have some degree of plasticity in their antipredator behaviour (L293-329). Note however, that while our data collection was not designed to test how hour-to-hour changes in human numbers influence escape distance, the effect of the number of humans (i.e. hour-to-hour variation in human numbers) in our sample was tiny.

      The date and hour effect simply control for the particularities of the given day and hour (e.g. warm vs cold times or the time until sunset). In other words, the within species differences (even from the same park) may have little to do with individual plasticity, but instead may reflect between individual differences. We now add this issue to Methods (L471-476): “This approach enabled us to control for spatial and temporal heterogeneity and specificity in escape behaviour of birds (e.g. species-specific responses, changes in escape distances with the progress in the breeding season, spatial and temporal variation in compliance with government restrictions or particularities of the given day and hour)....”

      2) Looking at the figures I do not see the immense stochasticity (L156, Fig. S3, S5) claimed by the authors. Instead, I can see that some species showed an obvious behavioral change during the shutdown. For instance, Motacilla alba, Larus ridibundus, or Passer domesticus clearly reduced their escape distances, while others like the Dendrocopos major, Passer montanus, or Turdus merula tended to increase it.

      At L138-141 and 327-329 we discussed the within and between genera and cross-country variation and stochasticity in response to the shutdowns (Fig. 2). The reference to species-specific plots was perhaps a little bit misleading. We think that the essential figure, that we now reference at this point, is Figure 2 that shows the temporal trends and/or stochasticity that seem to have little in common with lockdowns. Please, also look at Figure 3 and S3-S4. These show that in all selected genera/species, the trends did not significantly deviate from central regression line which indicates no change in FID before and during the COVID-19 shutdowns.

      On the other hand, birds in Poland tended to have larger escape distances during the shutdown for most species, while in Rovaniemi there was an apparent reduction of escape distances in most cases. The multispecies and multisite approach is a strength of this study, but it is an Achilles' heel at the same time. The huge heterogeneity in bird responses among species and sites counterbalanced and as a result, there was an apparent lack of shutdown effects overall. Furthermore, as most data comes from a few (European) species (i.e. Columba, Passer, Parus, Pica, Turdus, Motacilla) I would say that the overall results are heavily influenced (or biased) by them. The authors realize that results are often area- or species-specific (L203), therefore, does a whole approach make sense?

      We are grateful for this valuable comment. We believe the general approach makes sense as there is a general expectation about how birds should respond to changes in human presence. That is why we control for non-independence of data points in our sample. Thus, although lots of data come from a few European species, this is corrected for by the model. Note that given the sheer number of sampled species, some site- or species-specific trends may have occurred by chance. Importantly, we believe that Figure 2, with species-site specific temporal trends, reveals that the between year stochasticity in escape distances seems greater that any effects of lockdowns. Nevertheless, we have further dealt with this issue in the revised manuscript by running country-specific models which again clearly showed no significant effect of Period on escape behaviour of birds (including, no effects in Poland and Finland).

      3) The previous point is worsened by the heterogeneity of cities and periods sampled. For instance:

      3.1) I can hardly imagine any common feature between a small city in northern Finland (Rovaniemi) and a megacity in Australia (Melbourne). Thus, I would not be surprised to find different results between them.

      3.2) Prague baseline data was for 2014 and 2018, while for the rest of the study sites were for 2018 and 2019. If study sites used a different starting point, you cannot compare differences at the final point.

      We are slightly confused by these comments.

      3.1) The cities are expected to be different but (i) the difference may be smaller than imagined (e.g. park structures, managed grass cover, few shrubs and deciduous-dominated tree species) and (ii) we expect the effects of lockdowns to be similar across cities. Whether we have no people in Rovaniemi parks (which despite Rovaniemi’s small size are usually extremely well-visited) or no people in Melbourne parks should not make a difference in principle. Note however, that to avoid overconfident conclusions, we allow for different reaction norms within cities. Please, also note that we are now providing country-specific results which should identify whether shutdowns lead to different reaction in sampled countries. We found no strong effect of shutdowns in any of sampled countries/cities.

      3.2) Because of the possible between site differences at the starting point, we use study site as random intercept and control for the between site reaction norms by including the random slope of the period. In other words, such possible differences do not influence outcomes of our models. Regardless, our a priori expectation is that the human activity levels in a given park was similar prior to covid and hence in 2014, 2018, and 2019. Again, we are now providing country-specific results which identify whether shutdowns led to different reactions in sampled countries, which they mostly did not

      3.3) Due to the obvious seasonal differences between the northern and southern hemispheres, data collection in Australia began five months later than in the rest of the sites (Aug vs Mar 2020). There, urban birds faced already too many months of reduced human disturbances, while European birds were sampled just at the beginning of the lockdown.

      We agree that each city or even park within the city has its specific environmental conditions (here including the time point of lockdown). That is why we control for city and park location in the random structure of the model (see Method section). We now add results per country that shows no clear differences (e.g. Fig. 1).

      However, the aim of our study was to test for general, global effects of lockdowns, which are minimal. Note that we now specifically test for country-specific effects in separate models on each country (e.g. Fig. 1, Fig S6) but all country-specific effects are small and still centre around zero.

      3.4) Some cities were sampled by a single observer, while others by many of them. Even if all of them are skilled birders, they represent different observers from a statistical point of view and consequently, observer identity was an extra source of noise in your data that you did not account for.

      We agree. In Finland and Hungary, data were collected by two closely cooperating observers. In Poland, all data were collected by a single observer. In the Czech Republic and Australia, a single observer (P.M. and M.W., respectively) sampled 46 sites out of 56 and 32 sites out of 37, respectively. Each site was sampled by the same observer both before and during the shutdowns. We now clearly state it in the Methods (L352-356). In other words, our models already largely control for the possible observer confound by having site as a random intercept. Moreover, previous study showed that FID estimates do not vary significantly between trained observers (Guay et al. 2013, Wildlife Research, 40, 289-293).

      4) Although I liked the stringency index as a variable, I am not sure if it captured effectively the actual human activity every day. Even if restrictive measures were similar between countries, their actual accomplishment greatly depended on people's commitment and authorities' control and sanctions. I would suggest using a more realistic measure of human activity, such as google mobility reports.

      Thank you for this comment. We now validate the use of the stringency index with the Google Mobility Reports, showing that human mobility generally (albeit in some countries relatively weakly) decreases with the strength of governmental antipandemic measures. Please, note that our main research question is related to the general change in human outdoor activity and not to week-to-week, day-to-day or hour-to-hour changes captured by stringency index, Google Mobility or the number of humans during an escape trial data. Nevertheless, using Google Mobility and the number of humans as predictors led to the similar results as for stringency index and Period (Fig. 1 and S6). Please, see extended discussion on this topic in our manuscript (L270-292).

      5) The authors used escape trials from birds on the ground and perched birds. I think that they are not comparable, as birds on the ground probably perceive a greater risk than those placed some meters above the ground, i.e. I would expect shorter escape distances for perched birds. As this can be strongly dependent on the species preferences or sampling site (i.e, more or less available perches), I wonder how this mixture of observations from birds on the ground and perched birds could be affecting the results.

      We now added information that most birds were sampled when on the ground (79%). Importantly, previous studies have found that perch height has a minimum effect on FIDs (e.g. Bjørvik et al. 2015. J Ornithol 156:239–246; Kalb et al. 2019, Ethology 125:430-438; Ncube & Tarakini 2022, Afr J Ecol 60:533– 543; Sreekar et al. 2015,. Tropic Conserv Sci 8:505-512). We added this information to the Method section (L394-395).

      6) The authors did not sample the same location in the same breeding season to avoid repeated sampling of the same individuals (L331). This precaution may help, but it does not guarantee a lack of pseudoreplication. Birds are highly mobile organisms and the same individuals may be found in different places in the same city. This pseudoreplication seems particularly plausible for Rovaniemi, where sampling points must be necessarily close due to the modest size of this city.

      We appreciate your concern. We cannot fully exclude the possibility of sampling some individuals twice. However, we sampled during the breeding season within which most birds are territorial, active in the areas around the nests and hence an individual switching parks is unlikely. Also, most sampled birds in our study are passerines which have small territories (typically few hundred square meters). Some larger birds may have larger territories and move larger distance to forage (e.g. kestrels which often forage outside cities) but these birds represent a minority of our records and we have not sampled outside the cities.

      7) An intriguing result was that the authors collected data for 135 species during the shutdown, while they collected data only for 68 species before the pandemic. Such a two-fold increase in bird richness would not be expected with a 36% increase in sampling effort during 2020-21. I wonder if this could be reflecting an actual increase in bird richness in urban areas as a positive result of the shutdown and reduced human presence.

      There were 141 unique day-years during before COVID and 161 during COVID. So, the sampling effort as calculated by days does not explain the difference in species numbers. Whether the actual effort, which was 381 vs 463 h of sampling, explains the difference is unclear, which we now note in the Methods (L476-483). If not, your proposition is possible, but we would like to avoid any speculations on this topic in the manuscript as it is difficult to infer species diversity from FID sampling.

      8) The authors dismissed the multicollinearity problem of explanatory variables unjustifiably (L383). However, looking at fig. S1, I can see strong correlations between some of them. For instance, period and stringency index were virtually identical (r=0.95), while temperature and date were also strongly correlated.

      We are confused by this comment and think this reflects a misunderstanding. Period and stringency index are explanatory variables of interest that were never included in the same model and hence their correlation does not contribute to the within a model multicollinearity. To avoid further confusion, we note this within (Fig. S2) legend. However, we must be cautious when interpreting the results from the models on period, Google Mobility, # of humans and stringency index, as the four measure are similar.

      We discuss multicollinearity of explanatory variables within the manuscript (L458-538, 548-550) and noted that, with the exception of temperature and day within the breeding season (r = 0.48), the correlations among explanatory variables were minimal. We thus used only temperature as an explanatory variable (i.e. fixed factor; also because temperature reflects both season and variation in temperature across a season) whereas the day was included as a random intercept to control for pseudoreplication within day. Collinearity between all other predictors was low (|r| <0.36).

      9) The random structure of the models is a key element of the statistical analyses but those random factors are poorly explained and justified. I needed to look up the supplementary tables to fully understand the complex architecture of the random part of the models. To the best of my knowledge, random variables aim to account for undesirable correlations in the covariance matrix, which is expected in hierarchical designs, such as the present one. However, the theoretical violation of data independence may happen or not. As the random structure is usually of little interest, you should keep it as simple as necessary, otherwise random factors may be catching part of data variability that you would like to explain by fixed variables. I think that this is what is happening (at least, in part) here, as the authors included a too-complex random structure. For instance, if you include the year as a random factor, I think that you are leaving little room for the period effect. The authors simplified the random structure of the models (L387), but they did not explain how. Nevertheless, this model selection was not important at all, as the authors showed the results for several models. I assume, consequently, that the authors are considering all these models equally valid. This approach seems quite contradictory.

      The random structure of the model controls for possible pseudoreplication in the data, that is for the cases where we have multiple data points that may not be independent and hence technically represent one. Apart from that, random structure tells us about where the variance in the data lies. This is often of interest and your previous questions about city, site or species specificities can be answered with the random part of the model. To follow up on your example, year is included in the model because data from a single year are not independent (for example because of delayed breeding season in one year vs. in another).

      We regret being unclear about the model specification and have attempted to clarify the methods (L466-476). We first specified a model with an ideal random structure that necessarily was complex (perhaps too complex). We then showed that using models with simpler random structures did not influence the outcomes. We now use a simpler model within the main text, but do keep the alternative models to show that the results are not dependent on the random structure of the model (Fig. S1 and Table S2).

      Reviewer #3 (Public Review):

      This study examined the changes in fear response, as measured by the flight initiation distances (FID), of birds living in urban areas. The authors examined the FIDs of birds during the pandemic (COVID-19 lockdown restrictions) compared to FIDs measured before the pandemic (mostly in 2018 & 2019). The main study justification was that human presence changed drastically during the pandemic lockdowns and the change in human presence might have influenced the fear response of birds as a result of changing the "landscape of fear". Human presence was quantified using a 'stringency' index (government-mandated restrictions). Urban areas were selected from within five different cities, which included four European cities (Czech Republic - Prague, Finland - Rovaniemi, Hungary - Budapest, Poland - Poznan), and one city in the global south (Australia - Melbourne). Using 6369 flight initiation distances across 147 different bird species, the authors found that FIDs were not significantly different before the pandemic versus during the pandemic, nor was the variation in FID explained by the level of 'stringency'.

      Major strengths: There are several strengths to this study that allows for understanding the variety of factors that influence a bird's response to fear (measured as flight initiation distances). This study also demonstrates that FIDs are highly variable between species and regions.

      Specifically,

      1) One of the major strengths of this paper is the focus on birds living in urban areas, a habitat type that is hypothesized to have changed drastically in the 'landscape of fear' experienced by animals during the pandemic lockdown restrictions (due to the presumed decrease in human presence and densities). Maintaining the focus on urban birds allowed for a deeper examination of the effect of human behaviour changes on bird behaviour in urban habitats, which are at the interface of human-wildlife interactions.

      2) This study accounted for several variables that are predicted to influence flight initiation distances in birds including species, genus, region (country), variability between years, pandemic year (pre- versus during), the strictness of government-mandated lockdown measures, and ecological factors such as the human observer starting distance, flock size, species-specific body size, ambient air temperature (also a proxy of the timing during the breeding season), time of day, date of data collection (timing within the regional [Europe or Australia] breeding season), and categorization of urban site type (e.g. park, cemetery, city centre).

      3) This study examined FIDs in two years previous to the pandemic (mostly 2018 and 2019, one site was 2014) which would account for some of the within- and between-year FID variation exhibited prior to the pandemic.

      4) This study uses strong statistical approaches (mixed effect models) which allows for repeat sampling, and a post hoc analysis testing for a phylogenetic signal.

      Thank you for your supportive and positive comments.

      Major weaknesses: The authors used government 'stringency' as a proxy for human presence and densities, however, this may not have been an accurate measure of actual human presence at the study sites and during measurements of FIDs. Furthermore, although the authors accounted for many factors that are predicted to influence fear response and FIDs in birds, there are several other factors that may have contributed to the high level of variation and patterns in FIDS observed during this study, thus resulting in the authors' conclusion that FIDs did not vary between pre- and during pandemic years.

      Thank you for your suggestions. We agree. To capture the general human presence in parks, we now incorporated an analysis using Google Mobility Reports (Fig S6b) that directly measures human mobility in each of sampled cities and specifically in urban parks where most our data were collected, and also address your further concerns that you detail below. Albeit not the main interest of our study, we now also incorporated an analysis using actual # of humans during an escape trial (Fig. S6c).

      Moreover, we think that including further possible confounds should not influence our conclusions. In other words, including further confounds will decrease the variance that can be explained by shutdowns and thus such shutdown effects (if any) would be tiny and hence likely not biologically meaningful.

      Specifically,

      1) The authors used "government stringency" as a measure of change in human activity, which makes the assumption that the higher the level of 'stringency', the fewer humans in urban areas where birds are living. However, the association between "stringency" and actual human presence at the study sites was not measured, nor was 'stringency' compared to other measures of human presence such as human mobility.

      Thank you for this essential comment. Initially, we viewed Oxford Stringency Index as the best available index for our purposes. However, we now further acknowledge its limitations (L) and validate the Oxford Stringency Index with the Google Mobility Reports data, showing that both indices are generally negatively (albeit sometimes weakly) correlated across sampled cities (i.e. human mobility decreases with the increasing stringency index). Although other human presence indices were used in the past, e.g. Cuebiq, Descartes Labs and Maryland Uni index, Apple (see Noi et al. 2022, Int J Geograph Info Sci, 36, 585-616), we used only the Google Mobility index because (a) it is publicly available, (b) is available also for territories outside US, and (c) provides data for urban parks within each city included in our dataset. Note however that Google Mobility data are inappropriate to answer our primary question, i.e. whether changes in human presence outdoors due to the COVID-19 shutdowns had any effect on avian tolerance towards humans. First, Google Mobility was available only for 2020-22, i.e. the baseline pre-COVID-19 data for 2018-2019 were unavailable. Thus, there was no way to check whether the human activity levels really changed during the COVID-19 years. Second, Google Mobility data are calculated as a change from 2020 January–February baseline for each day of the week for each city and its location (here we used parks). In other words, the data are not comparable between days and cities, albeit we attempted to correct for this within the random structure of the mixed model. Also, the data may be influenced by extreme events within the 2020 Jan–Feb baseline period (see here). Third, the Google Mobility varies greatly between days and across season (see Fig 4 & S5 or the first figure in these responses), likely more than the possible change due to shutdowns. Nevertheless, we found that results based on Google Mobility are qualitatively very similar to results based on stringency index. Moreover, we showed that the relationships between # of humans and both Google Mobility or Stringency index (Figure 6) are weak and noise with 95%CIs widely overlapping zero (Table S3b-e). Also, similarly to other predictors of human presence, # of humans only poorly predicted changes in avian escape distances. We added details on the new analysis into the Methods and Results and Supplement (L134-165 and associated figures and tables, L415-535).

      2) There was considerable variation in FID measurements, which can be seen in the figures, indicating that most of the variation in FID was not accounted for in the authors' models.

      We are confused by this statement. The fact that the FIDs varied does not translate directly to that our models did not account for the variation. Nevertheless, we do control for most of the discussed confounds (see further answers below). Importantly, it is unclear how including further possible confounds should influence our conclusions, unless the lockdowns effects are tiny, in which case those might not be biologically meaningful.

      Factors that may have contributed to variation in FIDs that were not accounted for in this study are as follows:

      a. The authors accounted for the date of data collection using the 'day' since the start of the general region's breeding season (Europe: Day 1 = 1 April; Australia: Day 1 = 15 August). Using 'day' since the breeding season started probably was an attempt to quantify the effect of the breeding stage (e.g. territory establishment, nest young, fledgling) on FIDs. However, breeding stages vary both within- and between species, as well as between sub-regions (e.g. Finland vs. Hungary). As different species respond to predation or human presence differently depending on the stage during their breeding cycle, more specificity in the breeding cycle stage may allow for explaining the observed variation and patterns in FID.

      We agree. Although we don’t have a precise city-specific information on the timing of breeding stages in sampled populations of birds, we partly control for these effects by including a random intercept of day within each year and species. This random factor explained relatively high portion of the variance in our data (see Table S1 and S2) - perhaps something you expected.

      b. Variation in species-specific FIDs may also vary with habitat features within urban sites, such as the proximity of trees and other protective structures (e.g. perches and cover), the openness of the area, and the level of stressors present (e.g. noise pollution, distance to roads). Perhaps accounting for this habitat heterogeneity would account for the FID variation measured in this study.

      We agree. We don’t have such fine-scale data, but we included site identity (typically within a particular park or cemetery) which should account for the habitat heterogeneity among localities. Depending on the model, site explained relatively little variance (1-6%), indicating low heterogeneity between localities in these undescribed characteristics. Also note that park structure may be quite similar both within and between cities, i.e. managed green grass areas, with only a few shrubs and deciduous trees. Therefore, the possible minor habitat heterogeneity should not have any great impacts on our results.

      c. The authors accounted for species and genus within their models, however, FIDs may vary with other species-specific (or even specific populations of a species) characteristics such as whether the species/population is neophobic versus neophilic, precocial versus altricial, and the level of behavioural plasticity exhibited. These variables were not accounted for in the analysis.

      We agree that FIDs can be correlated with many possible factors. Here, we were interested in general patterns, while controlling for FID differences between species, as well as for possible species-specific reaction norms to lockdowns. Whether neophobic vs neophilic population or precocial versus altricial species react differently to lockdowns might be of interest, but it is beyond the scope of this study. However, that population and population specific reaction norms explain little variation (Table S2a, 0-6% of variation) so such a confound should not substantially influence our conclusion much. We do not have fine-scale data on the level of neophobia, but the effects of lockdowns seem similar for precocial (see Anas, Larus, Cygnus) and altricial (the remaining, mostly passerine) species in our dataset (see Fig. 3 and S3-S4). Please, note that we sampled mainly adults (L386). Moreover, the effects for clades, which may differ in their cognitive skills, are also similar (e.g. Corvids vs. Anas or Cygnus; Fig. 3).

      d. Three different methods of measuring the distances between flight and the observer location were used, and FIDs were only measured once per bird, such that there were no measures of repeatability for a test subject. Thus, variation surrounding the measurement of FIDs would have contributed to the variation in FIDs seen during this study.

      While all observers were trained, the three methods may add some noise to the FID estimates. However, the FID estimates from a single method may still slightly differ between observers (so do well standardized morphology measurements; Wang, et al. 2019, PLoS Biology, 17, e3000156). Importantly, FID estimates are highly replicable among skilled observers (Guay et al. 2013, Wildlife Research 40:289-293), and we previously validated this approach and showed that distance measured by counting steps did not differ from distance measured by a rangefinder (Mikula 2014, Ardea 102:53-60), which we now explicitly state (L391-394). Importantly, we control for observer bias by specifying locality as a random intercept (see further details in our response to the Editor). Moreover, each site was sampled by the same observer both before and during the shutdowns.

      3) The sample design of this study may have influenced the FID variability associated with specific species, and specific populations of species. A different number of species were sampled across the time periods of interest; 68 species were sampled before the pandemic versus 135 species after the pandemic. However, the authors do not appear to have directly compared the FIDs for the same species before the pandemic compared to during the pandemic (e.g. the FIDs of Eurasian blackbirds before the pandemic versus during the pandemic). Furthermore, within the same country-city, it is unclear whether the species observed before the pandemic were observed at the same location (e.g. same habitat type such as the same park) during the pandemic. As a species' FID response may be influenced by population characteristics and features specific to each site (e.g. habitat openness), these factors may have influenced the variability in FID measurements in this study.

      We regret being unclear in our methods. Our full model uses all data, but alternative models (see e.g. Fig. S1) used data with ≥5 as well as ≥10 observations before and during lockdowns for a given species. Importantly, Figure 2 and 3 depict data for species sampled at specific sites. We now clarify this within the Methods (L460-483) and the Results (L125-133 and associated figures) and in the figure legends (Fig. S1).

      4) The models in this study accounted for many factors predicted to affect FIDs (see the section on major strengths), however, the number of fixed and random factors are large in number compared to the total sample size (N =6369), such that models may have been over-extended.

      The number of predictors and random effects is well within the limits for the given sample size (Korner-Nievergelt et al. 2015. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan). Importantly, simpler models give similar results as the more complex ones (Fig. S1) and the visual (model free) representations of our raw and aggregated data confirm our model results. This, we suggest, makes our findings robust and convincing.

      Overarching main conclusion

      Overall, this study examines factors influencing FIDs in a variety of bird species and concludes that FIDs did not differ during the pandemic lockdowns compared to before the pandemic (2019 and earlier). Furthermore, FIDs were not influenced by the strictness of government-mandated restrictions. Although the authors accounted for many factors influencing the measurement of FIDs in birds, the authors did not achieve their aim of disentangling the effects of pandemic-specific ecological effects from ecological effects unrelated to the pandemic (such as habitat heterogeneity).

      We find this statement confusing. We accounted for most relevant confounding factors and found little evidence for the strong effect of pandemic. Moreover, we now added country-specific analyses that confirm the lack of evidence, highlight the Figure 3 that shows no clear shutdown effect and also explore how levels of human presence changed over and within the years. Adding more possible confounds (albeit note that not many are left to add) might only further reduce the variation that could be explained by pandemic and hence such hypothetical effects of pandemic will be if anything small and thus likely not biologically meaningful.

      Their findings indicate that FIDs are highly variable both within- and between- species, but do not strongly support the conclusion that FIDs did not change in urban species during the pandemic lockdown. Therefore, this study is of limited impact on our understanding of how a drastic change in human behaviour may impact bird behaviour in urban habitats.

      It is unclear why you think our study lacks support for the conclusion that FIDs changed little during pandemic, if all results show no such effects. However, we toned down our Discussion and highlighted also potential issues linked to our approach (e.g. that sampled individuals were not marked and hence we cannot distinguish between various mechanisms that might explain the described pattern (L293-329) or that human presence may not have changed (L253-269). For further details see our previous response.

      Overall, the study demonstrates the challenges in using FIDs as a general fear response in birds, even during a pandemic lockdown when fewer humans are presumably present, and this study illustrates the large degree of variation in FIDs in response to a human observer.

      We appreciate and agree that our study demonstrates the challenges in quantifying human activity to understand bird escape distance and we added a paragraph on this topic to the discussion (L270-292).

      Nevertheless, we hope that our above responses clarify and address most of the issues you had with our manuscript. We tried to show that (a) most of your proposed controls are indeed included in our study design, models, and visualisations, and that (b) multiple evidence (from models and visualisation of raw and aggregated data) support the no overall effect conclusion. We further emphasize the temporal and between- and within-species variability in FIDs in the Results and now specifically indicate that lockdowns did not influenced FIDs above such variability (Fig. 2-3, Fig. S3). In other words, the natural (e.g. temporal) variation in FIDs seems far greater that potential effects of lockdowns (Fig. 2). We believe that even if lockdowns would have tiny effects that could have been detected with more. stringent experimental design (e.g. individually tagged birds) or even more complex models, such effects would be far from being biologically meaningful.

    1. Author Response

      Reviewer #2 (Public Review):

      This work attempts to connect the diet of a mother to the physiology and feeding behaviors of multiple generations of her offspring. Using genetic and molecular biology approaches in the fruit fly model, the authors argue that this Lamarckian inheritance is mediated by germline-inherited chromatin and is regulated by the general activity of a histone methylase. However, many of the measured effects are small and variable, the statistical tests to prove their significance are missing or poorly described, and some experiments are inadequately described and lack important controls.

      1) The authors claim that the diet of a mother can influence the physiology of her progeny for several generations. However, the observed effects of maternal diet on later generations were small and variable for most assays (see Fig1C, S1.1A, B, D). Additionally, the effect size between F0 HSD to ND was often larger than the effect size between the progeny of F0 parents and ND. To put it another way, if the authors were to compare the F1, F2, etc. to the F0 HSD flies, they would conclude that the majority of the response to diet is not maternally transmitted, and is directly controlled by the diet of the individual being measured.

      We agree with the reviewer that the effect size of acute HSD exposure (in HSD-F0 flies) was stronger than that of transgenerational inheritance (in HSD-F1/2/3/4 flies). Similar observations were also made in other studies, see Klosin et al., Science, 2017, Bozler et al., eLife, 2019. We would argue this difference in effect size was as expected and with clear biological relevance.

      For all living organisms, acute environmental changes (diet change included) have direct and profound influences on their survival and reproduction, and therefore need robust and immediate responses. In comparison, ancestral environmental changes may only provide some vague and indirect indications of the current living environment of the offspring. Such information may be beneficial for the survival and reproduction of the offspring, but the effect size is expected to be much smaller, or at least smaller than that of acute environmental changes.

      Studies on Dutch Famine offers a good example. Human individuals who were prenatally exposed to famine were found to be associated with greater risk in metabolic diseases (Ravelli et al., NEJM, 1976). But nevertheless, direct high-fat diet exposure was still the much stronger risk factor for obesity and metabolic disorders (Bray et al., Am J Clin Nutr, 1998, Jéquier et al., Int J Obes Relat Metab Disord, 2002).

      We have added additional discussions in the manuscript for clarification.

      Furthermore, since our current study aimed to investigate the mechanism of behavioral transgenerational inheritance, we focused on the comparison between HSD-F1 flies (and their progeny) vs. ND-fed flies. As the ancestors of HSD-F1/2/3/4 flies were exposed to HSD, whereas HSD-F1/2/3/4 flies themselves were never exposed to HSD, any difference we observed between the two groups could be solely attributed to transgenerational inheritance of ancestral HSD exposure. With that saying, to better distinguish the effects of acute HSD exposure vs. transgenerational inheritance upon ancestral HSD exposure, we re-analysed and presented the comparisons among ND, HSD-F0, and HSD-F1 data in the manuscript (Figure 1. B-E, Figure 1-figure supplement 1. A-E, Figure 1-figure supplement 2. A-D, Figure 3. D-E, Figure 3-figure supplement 1. B-D, Figure 3-figure supplement 2 and 3. A-B).

      2) The authors chose to study PER, which had the largest average effect sizes between conditions. However, PER was highly variable in the averaged data, with some individuals showing large effects and others having no effects. A better characterization of transgenerational PER may increase the robustness of this assay and confidence in its results. For example, the authors could measure PER in lineages derived from individual flies to determine when transgenerational effects on PER decline or disappear. This form of data collection could help to explain the high variation in the averaged data presented in the paper.

      We acknowledged that PER in general was quite a variable behavioural trait (probably as to most if not all behavioural measures). It was not surprising since animal behaviours, as complex traits, could be influenced by numerous intrinsic and extrinsic factors, such as genetic background, developmental environment, diet, population density, environmental conditions, etc. Numerous PER studies have exhibited similar variability (Masek et al., PNAS, 2010, Marella et al., Neuron, 2012, Charlu et al., Nature Communication, 2013, Wang et al., Cell Metabolism, 2016, Wang et al., Cell Reports, 2020).

      Nevertheless, in our current study we were able to identify statistically significant behavioural difference between ND-fed flies and HSD-F1/2/3 flies, demonstrating that ancestral HSD exposure imposed transgenerational inheritance on sweet sensitivity. To further increase the robustness of the study as suggested by the reviewer, we have conducted additional repetitions of many PER experiments and further confirmed the phenotype with less variability and more statistical power (Figure 1. G-I, Figure 3. D-E, Figure 3-figure supplement 1. B-D, Figure 3-figure supplement 2 and 3. A-B). The reviewer also suggested the use of isogenic flies, which might help to minimize the variations of genetic background. However, we think that demonstrating the behavioural difference in genetically diverse fly populations is a more credible way to show that such transgenerational inheritance is a reliable and generalizable phenomenon.

      3) What do the error bars represent on any figure? There are many examples where the data is highly variable and lies completely outside of the error bars. What is the statistical test for significance that is carried out in each figure? The brief comment about statistics in the methods section is inadequate. The authors should also supply the raw data used to generate the figures so that readers can perform their own statistical tests.

      Data in the manuscript were represented as means ± SEM (standard error of the mean) in all of our figures, which is a standard practice in the field (Masek et al., PNAS, 2010, Charlu et al., Nature Comm, 2013, Wang et al., Cell Metabolism, 2016). We have provided detailed explanations of the statistical tests in the manuscript. We have also prepared raw data files as suggested by the reviewer.

      The model that global H3K27me3 is regulated by ancestral diet is unconvincing without further experimental validation and explanation. Points 4-10 address specific issues.

      4) The authors performed ChIP on cycle 11 embryos. This stage is extremely short (11 min) and contains roughly 10 times less chromatin than embryos only 30 minutes older. These features make it very difficult to collect large numbers of precisely staged embryos without significant contamination. It is also debatable whether early cell cycles (including and preceding cycle 11) are slow enough to deposit and propagate histone marks in the presence of new histone incorporation. See the opposing arguments in Zenk et al 2017 and Li et al 2014. The authors could perform ChIP on older embryos to avoid this controversy.

      We thank the reviewer for the clarification. Our embryo collection protocol involved allowing flies to lay eggs freely in a cage for 30 minutes followed by 50 minutes of incubation on a juice plate, and then completing the embryo sorting within 30 minutes. Therefore, to describe it in a more stringent way, our embryos should be in the stage between cycle 10-12. We have corrected this information in the manuscript (Figure 2. A).

      Since all the embryos were sorted using the same morphological criteria within the same time frame, their developmental stages should be comparable (i.e. all from cycle 10-12). In several references we consulted, a broader range (cycle 9-13) was used for ChIP-seq sequencing analysis (for example, see Zenk et al., Science, 2017).

      Surely any maternally inherited information will also be present in cycle 14 or 15 embryos if it is to influence the development or physiology of the brain. The observed differences in global H3K27me3 levels in F1 vs ND flies could be explained by slightly different aged embryo collections or technical variations in the ChIP protocol. The authors could strengthen their conclusion by performing more ChIP replicates. Alternatively, the authors could use orthogonal approaches like antibody staining or western blots to measure global H3K27me3 levels in precisely staged embryos.

      We chose to use cycle 10-12 embryos because we aimed to identify epigenetic modulations directly transmitted through the maternal germline. Embryos in cycle 14-15 might reveal more profound changes, but since embryos in that stage had entered the zygotic phase and started the remodeling of histone modifications, we think it might mask the maternally transmitted changes we sought to identify.

      In addition, we conducted two biological replicates for each group for the ChIP-seq analysis, which was a standard in the field (Zenk et al., Nature, 2021, Ing-Simmon et al., Nature Genetics, 2021). In the current study we further verified the genes identified in the ChIP-seq analysis in RNA-seq and qPCR analysis.

      We further verified the ChIP-seq results by using western blot, which showed a ~2 folds increase in H3K27me3 modification in HSD-F1 early embryos vs. ND-fed embryos, in line with the ChIP-seq data (Figure 2-figure supplement 1. B). We have also provided immunofluorescence results for embryos at cycle 13 and cycle 14, which clearly showed a significant increase in H3K27me3 modifications in HSD-F1 embryos (Figure 2-figure supplement 1. C).

      5) The authors measure PRC2 subunit mRNA levels in adult fly heads to attempt to explain the observed differences in inherited H3K27me3 levels in fly embryos. The authors should examine PRC2 components in germ cells and early embryos to understand how germ cells and early embryos generate H3K27me3 patterns.

      We have now shown that Pcl and E(z) mRNA expression in HSD-F0 flies were not significantly changed vs. ND-fed flies (Figure 2-figure supplement 2. D-G). Meanwhile, H3K27me3 demethylase UTX and H3K27ac acetyltransferase Cbp showed significant decrease (Figure 2-figure supplement 2. H). Therefore, HSD exposure imposed complex epigenetic modifications in HSD-F0 flies, which then led to transmission of epigenetic marks to their progeny. Given the main scope of this study was to understand which epigenetic program mediated the behavioral transgenerational inheritance upon ancestral HSD exposure (but not that mediated acute HSD exposure), we focused our effect on H3K27me3 which was significantly changed between HSD-F1 flies vs. ND-fed flies.

      6) The RNAi experiment targeting PRC2 components in embryos is uninterpretable without appropriate controls and an explanation of the genotypes used in the experimental paradigm. Are the authors crossing nosNGT mothers to UAS-RNAi fathers and assaying the progeny? What is the genotype of the F1 flies and how does it compare to the genotype of the ND flies? The authors should also note that the Gal4 drivers they use are not necessarily restricted to the ovary, and could directly affect other tissues controlling PER like neurons and muscle. Additionally, the authors should supply the appropriate controls to verify that their experimental paradigm has the intended effect. PRC2 proteins are presumably loaded into embryos and would be immune to zygotic-expressed RNAi. The authors could validate when PRC2 RNAi is effective by staining embryos for H3K27me3.

      We have now added schematic diagrams and detailed explanations in our revised manuscript to better explain the RNAi experiments (Figure 3-figure supplement 1. A). As shown in the diagram, we compared each RNAi treatment group to appropriate genetic controls. We have also noted in the manuscript that the GAL4 drivers we used were not restricted to the ovary.

      We have now verified the effect of PRC2 knockdown to reduce H3K27me3 in female germline by both western blot and immunofluorescence staining (Figure 3. B-C).

      7) Although the authors do not note this, nosNGT>RNAi affects the PER of ND flies (compare Gal4>RNAi to just RNAi or just Gal4 in ND columns in Fig3A-D). This could be due to RNAi expression in neurons or muscles or some other indirect effect. Regardless of the mechanism, this result makes it difficult to interpret how RNAi treatments affect the transgenerational inheritance of PER if there is an equivalently strong nontransgenerational effect.

      Although nosNGT>RNAi appeared to slightly affect PER response of ND-fed flies, there was no statistically significant difference (Figure 3-figure supplement 1. B and D, Figure 3-figure supplement 2. A-B). Rather, the effect of E(z) knockdown was evident in HSD-F1 flies (Figure 3-figure supplement 1. B), further confirming the involvement of H3K27me3 in transgenerational inheritance of PER reduction.

      8) The matalpha gal4 experiment is inadequately explained in the text or methods. Are the authors expressing RNAi in the ovaries of the F0 flies that are fed an HSD? Does the ovary influence their PER somehow? Similar to point 8, there appears to be a nontransgenerational component to the RNAi phenotype that clouds the interpretation of the transgenerational effect (compare F0 in S3.1A-C).

      We have now added a schematic diagram and detailed explanations in our revised manuscript to better explain the RNAi experiments (Figure 3. A). As shown in the diagram, we compared each RNAi treatment group to appropriate genetic controls.

      Similar to point 7, although Mat-tub-GAL4>RNAi might seem to affect PER responses of ND-fed flies, there was no statistically significant difference (Figure 3. D-E). Rather, the effect of E(z) knockdown was evident in HSD-F1 flies (Figure 3. D), further confirming the involvement of H3K27me3 in transgenerational inheritance of PER reduction.

      9) For the EED inhibitor experiments (both PER and calcium imaging), it is unclear whether the authors fed the mothers or their adult progeny the EED inhibitor. If adult progeny were fed, what tissues were affected? The authors should stain various tissues with an H3K27me3 antibody to verify the effectiveness of their inhibitor. Finally, the effect of the EED inhibitor on calcium imaging was not convincing because the variation was so large.

      We have added a new schematic diagram and provided more detailed explanations in the manuscript for pharmacological interventions (Figure 4. A-D). To verify the effect of the drug treatment, we showed that compared to the control group fed with DMSO, flies fed with the inhibitor showed a significant decrease in H3K27me3 levels, demonstrating the effectiveness of the inhibitor (Figure 4-figure supplement 1. A).

      We acknowledged the unsatisfactory quality of our calcium imaging experiments in our initial submission. We have now improved our experimental procedures to reach better data quality, while the conclusions remained consistent (Figure 4. E).

      10) In all of the PRC2 RNAi and inhibitor experiments, are there any other phenotypes that would suggest that the treatments are working? There are many published PRC2 loss-offunction phenotypes (molecular and developmental) in different tissues. The authors could assure the reader that their treatments are working as expected by doing these controls.

      As discussed above, we have now used western blot and immunofluorescence staining to validate the efficiency of PRC2 RNAi in female germline (Figure 3. B-C).

      11) The authors propose that a transgenerationally inherited state of the caudal gene is responsible for the transgenerationally inherited PER. However, the experiments investigating the methylation state and expression level of caudal are unconvincing. Cad mRNA abundance varied immensely in the ND RNAseq samples. When the authors compared cad levels across generations, the effect size was small. A single outlier in the ND sample in both the RNAseq and the RTPCR experiments appears to drive up its mean and effect size. The H3K27me3 ChIP on cad is very similar in the F1 and ND samples and the acetylation peak on its promoter appears unchanged. The authors could vastly improve the caudal experiments in this paper by simply using cad antibodies to stain the relevant tissues that contribute to PER. For example, the authors could stain GR5a neurons for cad expression in different generations that inherit (or don't inherit) maternal PER to more accurately determine if cad levels are indeed transgenerationally regulated. The authors could also perform more ChIP experiments at a less variable stage to convincingly correlate epigenetic marks on cad with its expression level.

      As discussed above, we conducted two biological replicates for each condition of the ChIP-seq analysis, which was a standard in the field (Zenk et al., Nature, 2021, IngSimmon et al., Nature Genetics, 2021). We have also performed western blot and immunofluorescence for H3K27me3 in ND vs. HSD-F1 embryos to further validate our ChIP-seq data (Figure 2-figure supplement 1. B-C).

      As for Cad gene, H3K27m3 signals showed a statistically significant difference between ND-fed and HSD-F1 flies (Figure 5. D). We have also conducted additional qPCR experiments to verify the gene expression changes of the Cad gene (Figure 5. F, right), which was in line with the ChIP-seq data and further supported its validity.

      It was worth noting that during the developmental time window of our ChIP-seq analysis, the acetylation signals in the promoter region of cad were very low (Figure 5. D), making it impossible to make a comparison.

      Reviewer #3 (Public Review):

      Jie Yang et al. investigated the transgenerational behavioral modification of a high-sugar diet (HSD) in Drosophila and revealed the underlying molecular and neural mechanisms. It has been reported that HSD exposure decreases sweet sensitivity in gustatory sensory neurons, resulting in reduced sugar response (Proboscis extension reflex, PER) in flies. The current study reports that this effect can be transmitted across generations through the maternal germline. Furthermore, the authors show that H3K27me3 modification is enhanced in the first-generation progenies of HSD-treated flies (F1), and genetical or pharmacological disruption of PCL-PRC2 complex blocks the behavioral change and restores the sweet sensitivity in the Gr5a+ sweet sensory neurons. The authors further analyze the differentially expressed genes in the F1 flies. Among H3K27me3 hypermethylated regions, they focus on homeobox genes and find a transcription factor Caudal (Cad), which shows decreased expression in the F1 flies. Knocking down Cad in Gr5a+ neurons results in decreased PER response to sucrose.

      Transgenerational changes in physiology and metabolism have been broadly studied, while inherited changes at the behavioral level are much less investigated. This work provides convincing evidence for transgenerational modification of feeding behavior and digs out the underlying molecular and neural mechanisms. However, there still are several concerns that need to be clarified.

      1) The epigenetic regulator PCR2 has been found to play an essential role in the 7d-HSDinduced modification of the PER response. In this study, it's important to clarify for the transgenerational change, whether epigenetic modification is required in the flies exposed to HSD (F0), the progenies (F1), or both. It would be very helpful for better interpretation if the procedures of HSD treatment in RNAi experiments and the drug treatments were stated in more detail. In addition, the F0 flies should be examined as the control.

      In this current study our main scope was to understand the transgenerational influence of HSD exposure on the progeny. To this aim, we chose to study the physiological and behavioral differences between ND-fed flies vs. HSD-F1 flies (and their progeny on ND). HSD-F1 flies (and their progeny) were not exposed to HSD in their whole life cycle and therefore the physiological and behavioral changes we observed vs. ND-fed flies could be solely attributed to epigenetic modifications transmitted via germline cells from HSD-F0 flies. Therefore ND-fed flies were used as the main control.

      As for HSD-F0 flies, the acute effects of HSD exposure could be more complex. Epigenetic factor was likely involved, as evident in Figure 3-figure supplement 1. C, Figure 3-figure supplement 3. A-B and Figure 4. C. In addition, HSD exposure might also directly affect gene expression and multiple signaling pathways in HSD-F0 flies (see Chen et al., Science China Life Sciences, 2020). Therefore, we did not aim to investigate how HSD exposure affected HSD-F0 flies in this current study. We have added additional discussions in the manuscript for clarification.

      With that saying, we still added more HSD-F0 flies as controls when needed (Figure 2-figure supplement 2. D-G, Figure 3-figure supplement 1. C, Figure 4. C, Figure 5. F, left).

      We have also modified the schematic diagrams and added more detailed explanations in the manuscript, in order to provide a clearer illustration of the experimental procedures (Figure 3. A, Figure 3-figure supplement 1. A, Figure 4. A, B and D). Specifically, we employed two different RNAi approaches. Firstly, we used genetic methods to obtain homozygous Mat-tub-gal4>UAS-gene X RNAi fly lines on chromosomes Ⅱ and Ⅲ for germline-specific knockdown (Figure 3, Figure 3-figure supplement 3). Secondly, we used heterozygous nosNGT-gal4>UAS-gene X RNAi flies for embryo-specific knockdown (Figure 3-figure supplement 1 and 2). Our drug experiments involved both treating the flies and measuring their PER (Figure 4. A-C) and treating the parental flies and measuring the PER of their progeny (Figure 4. D).

      2) The information on the drug treatment period is also missing for imaging experiments (Fig.4C). Moreover, the response curve is very different from those recorded in the same neurons in previous studies. What’s the reason? Please also provide a representative image showing which part of the Gr5a neurons is recorded.

      The experimental procedures of drug treatments were shown in Figure 4. A now. We fed adult flies with specific compounds for five days after eclosion, then measuring the calcium signals of Gr5a+ neurons when flies were fed with sucrose.

      As suggested by the reviewer, we have now conducted calcium imaging experiments more carefully and thoroughly. We have now added the new data into the revised manuscript and the conclusions remained consistent (Figure 4. E). We recorded the calcium signal in the axons of Gr5a+ neurons in the SEZ.

      3) It's unclear whether the decreased Cad expression upon HSD treatment specifically occurred in Gr5a+ neurons or a lot of cells. If the change in gene expression is significant in the qPCR test, it should occur in a large number of cells, most likely including different types of gustatory sensory neurons. If lower cad expression led to lower neural response and thereby lower behavioral response, how to specifically decrease the PER response to sucrose but not to other tastes? -whether HSD-induced desensitization is specific to sucrose in the offspring?

      We agree that Cad expression might decrease in a lot of cells including Gr5a+ neurons in the proboscis. In order to investigate whether taste perception other than sweet sensing was also affected, we conducted PER experiments with fatty acids, which was another type of appetitive taste cues like sugars. Perception of fatty acids is mediated by ionotropic receptors such as ir25a, ir76b, and ir56b (Ahn, et al., eLife, 2017, Brown., et al, eLife, 2021).

      Our results indicate that PER of fatty acid in HSD-F0 and HSD-F1 was not significantly reduced compared to the ND-fed controls (Figure 1-figure supplement 2. E-F). This suggests that the impact of Cad on gustatory sensory neurons might be specific to sweet sensitivity of Gr5a+ neurons.

      4) In Fig.2D, data are sorted for genomic regions showing an up-regulated modification of H3K27me. It's unclear whether similar sorting was performed in panel C. This needs to be clarified.

      The analysis shown in Figure 2C and 2D were linked. As for 2C, we identified genomic loci with enriched H3K27me3, H3K9me3, and H3K27ac peaks, and found that H3K27me3 peaks showed the most robust changes between ND-fed and HSD-F1 flies. Therefore we concentrated on these loci where H3K27me3 modifications were significantly changed between the two groups, and further analyzed their difference. As shown in Figure 2D, within these loci, H3K27ac modifications, which was functionally antagonizing to H3K27me3, were significantly reduced; whereas H3K9me3 signals within these loci remained unchanged. Such results confirmed that ancestral HSD exposure induced robust H3K27me3 modifications in certain genomic loci.

    1. AbstractBackground The domesticated turkey (Meleagris gallopavo) is a species of significant agricultural importance and is the second largest contributor, behind broiler chickens, to world poultry meat production. The previous genome is of draft quality and partly based on the chicken (Gallus gallus) genome. A high-quality reference genome of Meleagris gallopavo is essential for turkey genomics and genetics research and the breeding industry.Results By adopting the trio-binning approach, we were able to assemble a high-quality chromosome-level F1 assembly and two parental haplotype assemblies, leveraging long-read technologies and genomewide chromatin interaction data (Hi-C). These assemblies cover 35 chromosomes in a single scaffold and show improved genome completeness and continuity. The three assemblies are of higher quality than the previous draft quality assembly and comparable to the current chicken assemblies (GRCg6a and GRCg7). Comparative analyses reveal a large inversion of around 19 Mbp on the Z chromosome not found in other Galliformes. Structural variation between the parent haplotypes were identified in genes involved in growth providing new target genes for breeding.Conclusions Collectively, we present a new high quality chromosome level turkey genome, which will significantly contribute to turkey and avian genomics research and benefit the turkey breeding industry.Competing Interest Statement

      **Reviewer 2. Luohao Xu **

      This manuscript by Barros et al. presents a high-quality dipoid turkey genome assembly which shows significant improvement relative to the previous one. This new assembly is timely and will likely be used as the reference turkey genome, but the authors should acknowledge that the W chromosome is absent (because the F1 individual was a male?). This manuscript fits more with "Data Note" than "Research" as I see most results are descriptive and confirmatory. While the chromosomal assembly is relatively complete, I am concerned whether it still contains assembly errors (because of not being polished by long reads?) which led to fewer genes annotated. This assembly metric needs to be taken into accounts if this assembly were to be used as a reference. The authors need to provide the QV value (see the VGP standard), and evaluate indel errors in coding regions. Some of the results are very brief without showing details or a figure, so difficult for assessment, for instance those SVs affecting genes. Page 4, "two most important avian agricultural species", I think duck should be the second most important poultry species? Page 5, I believe the "F1 assembly" refers to the primary assembly or collapsed assembly - please define it more clearly. Page 6, it's unclear how the 36 chromosome models are defined, particularly for small microchromosomes (29-35). According to the karyotype of turkey (2n=80), a few chromosomal models are missing. Page 6, "This captures the chromosome arms in a single contig" does it apply to all chromosomes? This is unlikely, and data is not shown. Page 6, any idea why the coverage of two parents differs (110X vs. 137X)? Page 6, "anchored the assemblies to the F1 assembly using RagTag". This suggests and chromosomal assembly of the two haplotypes was not independent, and replied on the F1 assembly. This can potentially lead to missing structural variations between two haplotypes (inversions, translocations). Page 7, please show more data to support the correct assembly of the chrZ inversion, including Hi-C heatmap, and long-read alignment spanning the inversion breakpoints. Note the Z chromosome inversion has been reported in Zhang et al. 2011 (BMC genomics), which is not cited until in the Discussion. Page 8, it's possible some genes were not annotated because of the presence of indels in coding regions. The genome assembly QV value can be calculated to measure the error frequency (Rhie et al, 2021 Nature). Page 8, please provide a statistical result for gene density comparison. Page 8, at the bottom, please cite the sources of these bird genomes. Page 9, "Gene family contractions and expansions". These analyses were a bit crude. " Orthologous groups" is not equivalent to "gene family". Page 10, the phrase "F1 and parent assemblies" is confusing. Both haploid assemblies are derived from the diploid F1. Consider changing to "paternal and maternal genomes". Also, as I commented above, both parental chromosomal assemblies are based on the same reference (Mgal_WU_HG_1.0), so the contigs were ordered and placed in the same way. This process could mask the potential non-co-linear segments. For a more appreciated way to independently assemble two chromosome-level assemblies, see the marmoset diploid genome paper (Yang et al., 2021 Nature). Page 10, please use a figure to show the SV over the BLB2 gene. Page 11, again, please visualize the result on the MAN2B2, GEMIN8, RIMKLB and RALYL cases. Page 11, "Loss of function variation", I am wondering whether variations mentioned in this part are fixed in the corresponding populations? Page 11, "Knockouts of this gene lead.." reference is needed. Page 12, "Avian genomes are known to…" references are missing. Page 12, "Distinct genomic landscapes of turkey micro and macrochromosomes", some patterns have been described in the literature, for instance, 10.1111/nyas.13295. Please also perform some statistical analyses to support the claims, not just a figure. Page 13, "Conserved synteny within the Galliformes clade", please cite 10.1159/000078570 and 10.1007/s00412-018-0685-6 Page 13, "it is evident that especially the Z chromosome" also observed in 10.1038/s41559-019-0850-1 Page 13, "inversion of around 19 Mbp on the turkey Z" also reported in 10.1186/1471-2164-12-447 Page 14, "tail of the chicken Z chromosome lacks synteny" also reported in 10.1038/nature09172. This means figure S11 does not provide a novel finding. Page 14, "Combining long reads and genome-wide chromatin interaction data (Hi-C) enables the capture of chromosome arms in a single contig", again, is that correct, chromosome arms in a single contig? Page 18, it's known wtdgb2 assembly tends to contain errors, but it looks the authors did not use long reads for polishing, but only used short reads? Page 20, "The corrected reads from TrioCanu were mapped to the Triocanu assembly with Minimap2 v2.17-r941 (Minimap2, RRID:SCR_018550) [45], options -x map-pb", what was is used for? Page 20, "Duplicated sequences were removed." How was this done?

      Re-review The manuscript has been improved. After reading the revised manuscript, I have a few more concerns.

      Chromosome models. I suggest the chromosome naming should follow chicken's, e.g., chr6 can be chr2a, and the microchromosomes should be named according to chicken homology. I then noticed chr32 and chr35 do not have chicken homology which is very concerning. It is either due to novel. chromosomes (very unlikely), or the sequences could be an unlinked contigs. In either scenario, the chromosome models must be clarified. The authors should provide strong evidence to support the chromosome model assembly for chr32 and chr35, e.g. FISH images, Hi-C zoom-in view (Fig. S1 shows the whole genomes where the microchromosome models are not visible), synteny with chicken (note there is a new chicken assembly ASM2420605v1) or zebra finch chromosomes; otherwise, chi32 and chr35 can not be identified as a chromosome. Centromere and telomere. To support complete chromosome assembly, I suggest the authors provide information about the assembly of telomere and centromere sequences, e.g. the presence/absence of TTAGGG at chromosomal ends. Most galliformes microchromosome centromeres are known to contain a 41-bp satellite (10.1139/gen-2022-0012). The authors should investigate whether such centromere satellites are present in the assembly. Data availability. It appears the Hi-C data is not available in NCBI. The raw reads must be provided. In the abstract, there is not such term as "complete scaffold", please remove "complete". Again, I do not see the support for two chromosome models: chr32 and chr35. The chrZ inversion is highlighted in the abstract, but this is not a novel finding - the writing is thus misleading. Instead, the new genome assembly only CONFIRMS this inversion. The subtitle "Lineage specific expansion and contraction of protein-coding gene families" is unrelated to the following text. "a 1.47 Mbp inversion on chromosome 1" I am wondering if this is the centromere? According to chicken chr1 centromere position, it looks like so. In the Table 5, the Parent2 has a much large size of gained copy. Please show more details, e.g. chromosomal distribution "BLB2", is this gene associated with parent2-specific trait? Similarly, what about TRIM36, GRIA2 and MAN2B2, and LRRC41? "The inversion was supported by a normal alignment at the approximate breakpoints (Supplementary File 1: Table S7 - Figure S16) and by the HiC contact map". The writing here is unclear. Hi-c data does not show signal for inversion, instead, it only supports that the assembly is correct. Bellott et al 2020 should be Bellott et al 2017. "Centromeres, however, are too long to traverse reliably in most cases". I do not see any analyses on centromeres. PRJEB42643 does not contain Hi-C data

      Re-re-review A new chicken genome has been published during the revision: https://www.pnas.org/doi/10.1073/pnas.2216641120, I suggest the authors revise some parts of the manuscript: e.g. L66, L78, L83-85 L103, please make it clear only the F1 was sequenced with long-read. L117-142, those results are very interesting, but perhaps the language can be more concise. L231-236, this paragraph is not important, please either move them to supplementary material or remove them. In general, this manuscript can be much more streamlined. L310-315, this part has also been reported by Huang et al. 2023 PNAS, so this is not a novel finding. Please either streamline or remove it. L327, ref 36 is not a "recent" finding.

    1. Reviewer #3 (Public Review):

      This paper considers a challenging motor control task - the critical stability task (CST) - that can be performed equally well by humans and macaque monkeys. This task is of considerable interest since it is rich enough to potentially yield important novel insights into the neural basis of behavior in more complex tasks that point-to-point reaching. Yet it is also simple enough to allow parallel investigation in humans and monkeys, and is also easily amenable to computational modeling. The paper makes a compelling argument for the importance of this type of parallel investigation and the suitability of the CST for doing so.

      Behavior in monkeys and in human subjects suggests that behavior seems to cluster into different regimes that seem to either oscillate about the center of the screen, or drift more slowly in one direction. The authors show that these two behavioral regimes can be reliably reproduced by instructing human participants to either maintain the cursor in the center of the screen (position control objective), or keep the cursor still anywhere in the screen (velocity control objective) - as opposed to the usual 'instruction' to just not let the cursor leave the screen. A computational model based on optimal feedback control can similarly reproduce the two control regimes when the costs are varied

      Overall, this is a creative study that successfully leverages experiments in humans and computational modeling to gain insight into the nature of individual differences in behavior across monkeys (and people). The approach does work and successfully solves the core problem the authors set out to address. I do think that more comprehensive approaches might be possible that might involve, e.g. using a richer set of behavioral features to classify behavior, fitting a parametric class of control objectives rather than assuming a binary classification, and exploring the reliability of the inference process in more detail.

      In addition, the authors do fully establish that varying control objectives is the only way to obtain the different behavioral phenotypes observed. It may, for instance, be possible that some other underlying differences (e.g. the sensitivity to effort costs or the extent of signal-dependent noise) might also lead to a similar range of behaviors as varying the position versus velocity costs.

      Specific Comments:<br /> The simulations convincingly show that varying the control objective via the cost function can reproduce the different observed behavioral regimes. However, in principle, the differences in behavior among the monkeys and among the humans in Experiment 1 might not necessarily be due to difference in other aspects of the model. For instance, for a fixed cost function, differences in motor execution noise might perhaps lead the model to favor a position-like strategy or a velocity-like strategy. Or differences in the relative effort cost might alter the behavioral phenotype. Given that the narrative is about inferring control objectives, it seems important to rule out more systematically that some other factor might not potentially dictate each individual's style of performing the task. One approach to rule this out might be to try to formally fit the parameters of the model (or at least a subset of them) under a fixed cost function (e.g. velocity-based), and check whether the model might still recover the different regimes of behavior when parameters *other than the cost function* are varied.

      The approach to the classification problem is somewhat ad hoc and based on fairly simplistic, hand-picked features (RMS position and RMS velocity). I do wonder whether a more comprehensive set of behavioral features might enable a clearer separation between strategies, or might even reveal that the uninstructed subjects were doing something qualitatively different still from the instructed groups. Different control objectives ought to predict meaningfully different control policies - that is, different ways of updating hand position based on current state of the cursor and hand - e.g. the hand/cursor gain, which does clearly differ across instructed strategies. Would it be possible to distinguish control strategies more accurately based on this level of analysis, rather than based on gross task metrics? Might this point to possible experimental interventions (e.g. target jumps) that might validate the inferred objective?

      It seems that the classification problem cannot be solved perfectly, at least on a single-trial level. Although it works out that the classification can recover which participants were given which instructions, it's not clear how robust this classification is. It should be straightforward to estimate the reliability of the strategy classification by simulating participants and deriving a "confusion matrix", i.e. calculating how often e.g. data generated under a velocity-control objective gets mis-classified as following a position-control objective. It's not clear how this kind of metric relates to the decision confidence outputted by the classifier.

      The problem of inferring the control objective is framed as a dichotomy between position control and velocity control. In reality, however, it may be a continuum of possible objectives, based on the relative cost for position and velocity. How would the problem differ if the cost function is framed as estimating a parameter, rather than as a classification problem?

    1. 09:25It is impossible to talk about the single story without talking about power. There is a word, an Igbo word, that I think about whenever I think about the power structures of the world, and it is "nkali." It's a noun that loosely translates to "to be greater than another." Like our economic and political worlds, stories too are defined by the principle of nkali: How they are told, who tells them, when they're told, how many stories are told, are really dependent on power.

      The way stories become told and who accepts them stems from who has the power, she covers this later with Government oppression in Africa, but an idea can become just as easily accepted if it is forced or spoofed to the public by the elite and powerful, or simply because it is popular.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This paper by Schommartz and colleagues investigates the neural basis of memory reinstatement as a function of both how recently the memory was formed (recent, remote) and its development (children, young adults). The core question is whether memory consolidation processes as well as the specificity of memory reinstatement differ with development. A number of brain regions showed a greater activation difference for recent vs. remote memories at the long versus shorter delay specifically in adults (cerebellum, parahippocampal gyrus, LOC). A different set showed decreases in the same comparison, but only in children (precuneus, RSC). The authors also used neural pattern similarity analysis to characterize reinstatement, though I have substantive concerns about how this analysis was performed and as such will not summarize the results. Broadly, the behavioural and univariate findings are consistent with the idea that memory consolidation differs between children and adults in important ways, and takes a step towards characterizing how.

      Strengths:<br /> The topic and goals of this paper are very interesting. As the authors note, there is little work on memory consolidation over development, and as such this will be an important data point in helping us begin to understand these important differences. The sample size is great, particularly given this is an onerous, multi-day experiment; the authors are to be commended for that. The task design is also generally well controlled, for example as the authors include new recently learned pairs during each session.

      Weaknesses:<br /> As noted above, the pattern similarity analysis for both item and category-level reinstatement was performed in a way that is not interpretable given concerns about temporal autocorrelation within the scanning run. Below, I focus my review on this analytic issue, though I also outline additional concerns.

      1. The pattern similarity analyses were not done correctly, rendering the results uninterpretable (assuming my understanding of the authors' approach is correct).

      a. First, the scene-specific reinstatement index: The authors have correlated a neural pattern during a fixation cross (delay period) with a neural pattern associated with viewing a scene as their measure of reinstatement. The main issue with this is that these events always occurred back-to-back in time. As such, the two patterns will be similar due simply to the temporal autocorrelation in the BOLD signal. Because of the issues with temporal autocorrelation within the scanning run, it is always recommended to perform such correlations only across different runs. In this case, the authors always correlated patterns extracted from the same run, which moreover have temporal lags that are perfectly confounded with their comparison of interest (i.e., from Fig 4A, the "scene-specific" comparisons will always be back-to-back, having a very short temporal lag; "set-based" comparisons will be dispersed across the run, and therefore have a much higher lag). The authors' within-run correlation approach also yields correlation values that are extremely high - much higher than would be expected if this analysis was done appropriately. The way to fix this would be to restrict the analysis to only cross-run comparisons, but I don't believe this is possible unfortunately given the authors' design; I believe the target (presumably reinstated) scene only appears once during scanning, so there is no separate neural pattern during the presentation of this picture that they can use. For these reasons, any evidence for "significant scene-specific reinstatement" and the like is completely uninterpretable and would need to be removed from the paper.

      b. From a theoretical standpoint, I believe the way this analysis was performed considering the fixation and the immediately following scene also means that the differences between recent and remote could have to do with either the reactivation (processes happening during the fixation, presumably) or differences in the processing of the stimulus itself (happening during the scene presentation). For example, people might be more engaged with the more novel scenes (recent) and therefore process those scenes more; such a difference would be interpreted in this analysis as having to do with reinstatement, but in fact could be just related to the differential scene processing/recognition, etc. It would be important when comparing scene-specific neural patterns as templates for reinstatement across conditions that, at the time of scene presentation itself, the two conditions are equal (e.g., no difference in familiarity and so on); otherwise, we do not know which trial period (and therefore which underlying process) is driving the differences.

      c. For the category-based neural reinstatement: (1) This suffers from the same issue of correlations being performed within the run. Again, to correct this the authors would need to restrict comparisons to only across runs (i.e., patterns from run 1 correlated with patterns for run 2 and so on). With this restriction, it may or may not be possible to perform this analysis, depending upon how the same-category scenes are distributed across runs. However, there are other issues with this analysis, as well. (2) This analysis uses a different approach of comparing fixations to one another, rather than fixations to scenes. The authors do not motivate the reason for this switch. Please provide reasoning as to why fixation-fixation is more appropriate than fixation-scene similarity for category-level reinstatement, particularly given the opposite was used for item-level reinstatement. Even if the analyses were done properly, it would remain hard to compare them given this difference in approach. (3) I believe the fixation cross with itself is included in the "within category" score. Is this not a single neural pattern correlated with itself, which will yield maximal similarity (pearson r=1) or minimal dissimilarity (1-pearson r=0)? Including these comparisons in the averages for the within-category score will inflate the difference between the "within-category" and "between-category" comparisons. These (e.g., forest1-forest1) should not be included in the within-category comparisons considered; rather, they should be excluded, so the fixations are always different but sometimes the comparisons are two retrievals of the same scene type (forest1-forest2), and other times different scene types (forest1-field1). (4) It is troubling that the results from the category reinstatement metric do not seem to conceptually align with past work; for example, a lot of work has shown category-level reinstatement in adults. Here the authors do not show any category-level reinstatement in adults (yet they do in children), which generally seems extremely unexpected given past work and I would guess has to do with the operationalization of the metric.

      2. I did not see any compelling statistical evidence for the claim of less robust consolidation in children. Specifically in terms of the behavioural results of retention of the remote items at 1 vs 14 days, shown in Figure 2B, the authors conclude that memory consolidation is less robust in children (line 246). Yet they do not report statistical evidence for this point, as there was no interaction of this effect with the age group. Children had worse memory than adults overall (in terms of a main effect - i.e. across recent and remote items). If it were consolidation-specific, one would expect that the age differences are bigger for the remote items, and perhaps even most exaggerated for the 14-day-old memories. Yet this does not appear to be the case based on the data the authors report. Therefore, the behavioural differences in retention do not seem to be consolidation specific, and therefore might have more to do with differences in encoding fidelity or retrieval processes more generally across the groups. This should be taken into account when interpreting the findings.

      3. Please clarify which analyses were restricted to correct retrievals only. The univariate analyses states that correct and incorrect trials were modelled separately, but does not say which were considered in the main contrast (I assume correct only?). The item specific reinstatement analysis states that only correct trials were considered, but the category-level reinstatement analysis does not say. Please include this detail.

      4. To what extent could performance differences be impacting the differences observed across age groups? I think (see prior comment) that the analyses were probably limited to correct trials, which is helpful, but still yields pretty big differences across groups in terms of the amount of data going into each analysis. In general, children showed more attenuated neural effects (e.g., recent/remote or session effects); could this be explained by their weaker memory? Specifically, if only correct trials are considered that means that fewer trials would be going into the analysis for kids, especially for the 14-day remote memories, and perhaps pushing the remove > recent difference for this condition towards 0. The authors might be able to address this analytically; for example, does the remote > recent difference in the univariate data at day 14 correlate with day 14 memory?

      5. Some of the univariate results reporting is a bit strange, as they are relying upon differences between retrieval of 1- vs. 14-day memories in terms of the recent vs. report difference, and yet don't report whether the regions are differently active for recent and remote retrieval. For example in Figure 3A, neither anterior nor posterior hippocampus seem to be differentially active for recent vs. remote memories for either age group (i.e., all data is around 0). This difference from zero or lack thereof seems important to the message - is that correct? If so, can the authors incorporate descriptions of these findings?

      6. Please provide more details about the choices available for locations in the 3AFC task. (1) Were they different each time, or always the same? If they are always the same, could this be a motor or stimulus/response learning task? (2) Do the options in the 3AFC always come from the same area - in which case the participant is given a clue as to the gist of the location/memory? Or are they sometimes randomly scattered across the image (in which case gist memory, like at a delay, would be sufficient for picking the right option)? Please clarify these points and discuss the logic/impact of these choices on the interpretation of the results.

      7. Often p values are provided but test statistics, effect sizes, etc. are not - please include this information. It is at times hard to tell whether the authors are reporting main effects, interactions, pairwise comparisons, etc.

      8. There are not enough methodological details in the main paper to make sense of the results. For example, it is not clear from reading the text that there are new object-location pairs learned each day.

      9. The retrieval task does not seem to require retrieval of the scene itself, and as such it would be helpful for the authors to both explain their reasoning for this task to measure reinstatement. Strictly speaking, participants could just remember the location of the object on the screen. Was it verified that children and adults were recalling the actual scene rather than just the location (e.g. via self-report)? It's possible that there may be developmental differences in the tendency to reinstate the scene depending on e.g., their strategy.

      10. In general I found the Introduction a bit difficult to follow. Below are a few specific questions I had.

      a. At points findings are presented but the broader picture or take-home point is not expressed directly. For example, lines 112-127, these findings can all be conceptualized within many theories of consolidation, and yet those overarching frameworks are not directly discussed (e.g., that memory traces go from being more reliant on the hippocampus to more on the neocortex). Making these connections directly would likely be helpful for many readers.

      b. Lines 143-153 - The comparison of the Tompary & Davachi (2017) paper with the Oedekoven et al. (2017) reads like the two analyses are directly comparable, but the authors were looking at different things. The Tompary paper is looking at organization (not reinstatement); while the Oedekoven et al. paper is measuring reinstatement (not organization). The authors should clarify how to reconcile these findings.

      c. Line 195-6: I was confused by the prediction of "stable involvement of HC over time" given the work reviewed in the Introduction that HC contribution to memory tends to decrease with consolidation. Please clarify or rephrase.

      d. Lines 200-202: I was a bit confused about this prediction. Firstly, please clarify whether immediate reinstatement has been characterized in this way for kids versus adults. Secondly, don't adults retain gist more over long delays (with specific information getting lost), at least behaviourally? This prediction seems to go against that; please clarify.

    1. “GPU hardware was specifically designed for gaming, and right now it’s just Nvidia trying to brainwash all of us trying to say that only a GPU can do AI,” said Liu.

      To je lahko samo "PR talk". Lahko da nVidia samo reče temu GPU ker temelji na enaki platformi?

    1. "I know I used to be a puppet frog, and now I'm a robot frog, but I think I'm still a real frog. I think I always was."

      I think it's interesting how Kermit knows about his past. I didn't expect him to know that he used to be just a puppet. I'm also surprised that he can be a robot and a real frog at the same time.

    1. professor John on Beatty will always say 00:14:07 I am because we are since we are therefore I am so my being is not just my being alone and being the richest in the world and 00:14:19 owning everybody my property has no meaning my wealth has no meaning if it's not of service to the community so if you come to my Village and many other villages in the African continent and someone says is a wealthy person but 00:14:33 is not bringing his wealth to Advanced education Advanced roads and infrastructure train people support agriculture people don't care he's not respected but once you bring your wealth and no matter how poor you are that you 00:14:47 are contributing to the society you are considered great so these are the values we think we can start discussing in the International Community
      • for: individual / collective entanglement, ubuntu M2W, human interbeing, quote, quote - John Mbiti, quote - human interbeing
      • paraphrase
        • professor John Mbiti will always say "I am because we are since we are therefore I am:
      • so my being is not just my being alone and being the richest in the world and owning everybody
        • my property has no meaning my wealth has no meaning
          • if it's not of service to the community
        • so if you come to my Village and many other villages in the African continent and someone says is a wealthy person but is not bringing his wealth to
          • Advanced education
          • Advanced roads and infrastructure
          • train people
          • support agriculture
        • people don't care he's not respected
        • but once you bring your wealth and no matter how poor you are that you are contributing to the society
        • you are considered great so these are the values we think we can start discussing in the International Community
    2. what I'm advocating here isn't radical redistribution it's merely more 00:13:08 redistribution in a and structurally dependable manner that is fair that is inclusive and that allows for the poor and improvised Nations to be granted excess not just a vital strategic resources that are very much needed in 00:13:21 maintaining the quality of life at own citizens but also more importantly the ropes to climb the ladder
      • for: W2W, TPF, stats, inequality, wealth redistribution, wealth tax, quote, quote - wealth tax, quote - inequality, stats, stats - inequality, stats - wealth tax
      • quote
      • stats
        • An annual wealth tax of just 5% on multi-millionaires and billionaires
        • could raise US $1.7 trillion a year
        • enough to lift 2 billion people out of poverty
      • author Institute for Policy (2023)
      • comment
        • that breaks down to approximately $US 1,000 per person for 2 billion people from the 1% elites
        • this is pretty reasonable
        • W2W can begin with this simple VOLUNTARY ASK
        • if the multi-millionaires and billionaires do just this consistently, then it is so little from their coffers and they could avoid a wealth tax by simply stepping up voluntarily
        • Could W2W motivate them to?
    1. manage the learning environment to minimize distractions and maximize learning

      I think this is a really important point, because it's really easy to view the role of teacher as someone who is just standing in the front of the classroom and teaching students, but it's honestly way more complex than that. If we reshape our thinking to realize that our main role is to make our classroom into a place where students CAN learn, I think our methods will be way more effective. I've had teachers who are so intelligent and friendly, but they are unable to control their classrooms, and so their students are constantly distracted and they never learn

    1. aybe that's the most 00:06:49 important thing um where uh would just citizen science or participatory science dialogue with really uh inclusive participation play a role in the r d 00:07:05 programs of the future in what you're kind of thinking about yeah so so um i i i framed this this r d program that is it's conceptual at the 00:07:18 time it's not funded yet you know i'm hoping that we can secure funds but i frame it as a partnership between this global science community and local communities 00:07:29 so it's very so dialogue with the public and within the science community and among interested stakeholders is extremely important
      • for: earth system boundaries, cosmolocal, local movement, transition town, circular cities, TPF
      • comment
        • integrating science with local communities
        • this statement is key, to bring extra capacity to communities that are handicapped and don't have scientific, technological and engineering capacity -paraphrase
      • This project is a collaboration between the global scientific community and local communities to improve societal systems. It's not a one-size-fits-all process, but many different experiments.
      • TPF and SRG strategy is well aligned with Science-driven societal transformation ethos:
    1. There is simply no reason to use an AI language model to generate recipes like this. It's easy enough to get a bunch of recipes in a machine-readable format and then just match the ones that share ingredients with the ones customers select. This is, I am sure, the approach taken by existing recipe sites that offer this feature.

      This is just a clear example of someone using AI in an application which did not need it. AI is the new blockchain.

    1. I do want to point out one more really significant implication here which is how it affects our experience of time
      • for: the lack project, sense of lack, the reality project, sense of self, sense of self and lack, poverty mentality, sense of time, living in the future, living in the present, human DOing, human BEing
      • key insight
        • we construct different types of experiences of time, depending on the degree of sense of lack we experience
        • it means the difference between
          • living in the present
          • living in the future
      • paraphrase
        • it's the nature of lack projects insofar as we become preoccupied with them
        • that they tend to be future oriented naturally
        • I mean the whole idea of a lack project or a reality project is right here right now is not good enough
          • because I feel this sense of inadequacy this sense of lack
          • but in the future when I have what I think I need
            • when I'm rich enough or
            • when I'm famous enough or
            • my body is perfect enough or whatever
          • when I have all this then everything will be okay
          • and what of course that does is that future orientation traps Us in linear time in a way that tends to devalue the way we experience the world and ourselves in the world right here and now
          • it treats the now as a means to some better ends
          • Now isn't good enough
            • but when I have what I think I need everything is going to be just great
        • So many of the spiritual Traditions taught
        • especially the mystics and the Zen Masters
        • they end up talking about what is sometimes called
          • the Eternal now
          • or the Eternal present - a different way of experiencing the now
        • As long as the present is a means to some better end
          • this future when I'm gonna be okay
        • then the present is experienced as
          • a series of Nows that fall away
          • as we reach for that future
        • but if we're not actually needing to get somewhere that's better in the future
        • it's possible to experience the here and now
          • as lacking nothing and myself in the here and now
          • as lacking nothing
      • it's possible to experience the present as something that doesn't arise and doesn't fall away
    2. t the irony of course is that if this desire if this craving for money if this lack project and we could also call it reality project because another 00:13:08 way to talk about all this is to say that we don't feel real enough and we're looking for that which somehow will make us feel more real more complete more whole right 00:13:20 because whatever the lack project may be it is looking for out something outside that's going to secure this sense of self-insight the tragedy of the whole process of 00:13:32 course is that it doesn't matter how much money you earn it's never going to be enough because what we're dealing with is just a symptom and not the core problem
      • for: the lack project, the reality project, sense of lack, sense of self, poverty mentality, polylcrisis, polycrisis - root
      • paraphrase
        • the irony is that
          • if this desire
          • if this craving for money
          • if this lack project and
          • we could also call it reality project
            • because another way to talk about all this is to say that we don't feel real enough and we're looking for that which somehow will make us feel more real more complete more whole
        • because whatever the lack project may be it is looking for out something outside
          • that's going to secure this sense of self-inside
        • the tragedy of the whole process is that it doesn't matter how much money you earn
          • it's never going to be enough
          • because what we're dealing with is just a symptom and not the core problem
      • key insight
        • the lack project is at the root of our polycrisis
    1. Author Response

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

      We would like to thank the Reviewers for their careful reading and the many thoughtful suggestions to improve our manuscript, as well as both the Editors and Reviewers for the generally positive evaluations and encouraging statements.

      Editorial assessment:

      This important work presents an interesting perspective for the generation and interpretation of phase precession in the hippocampal formation. Through numerical simula- tions and comparison to experiments, the study provides solid evidence for the role of the DG-CA3 loop in generating theta-time scale correlations and sequences, which would be reinforced through the clarification of the concepts introduced in the study, in particular the notion of intrinsic and extrinsic sequences. This study will be of interest for the hippocampus and neural coding fields.

      We appreciate that our work has been considered important. In our revision we made a considerable effort to improve on the presentation of our results and the justification of our model assumptions. Particularly we aimed to clarify the meaning of intrinsic and extrinsic sequences by ad- ditional figure panels as well as fleshing out their definition via spike-timing correlations being independent or dependent on the direction of the running trajectory, respectively. To address all the requests, we added 3 new Fig- ures, multiple new Figure panels and simulated a new model variant.

      Reviewer #1 in their public review assessed ”The manuscript has the potential to contribute to the way we interpret hippocampal temporal coding for navigation and memory.”

      They criticized

      • The findings generally relate to network models of phase precession (re- viewed in e.g., Maurer and McNaughton, 2007, Jaramillo and Kempter, 2017). An important drawback of these models with respect to explaining specific experimentally observed features of phase precession, is that they cannot straightforwardly explain phase precession upon first exposure onto a novel track. This is because, specific connectivity in network models may re- quire experience-dependent plasticity, which would not be possible upon first exposure. This is essential, given that the manuscript addresses the possible origin of phase precession in terms of network models and at minimum, this weakness should be discussed.

      We agree with Reviewer # 1 (and also with Reviewer # 2, who brought up a similar point) that models based on recurrence struggle to ex- plain how the recurrent connectivity matrix should come about. While we feel that a full model of how the 2-d topology in the recurrent weights can be learned goes far beyond the scope of this paper (and to our knowledge has not been solved so far in any existing model), we added a new model variant (new Figure 6 and Supplementary Figure 1), which explains the ba- sic phenomenology of extrinsic and intrinsic sequences without the need of recurrent connections, only using feed-forward synaptic facilitation. Thus, assuming recurrent connection is not necessary for our main findings. How- ever, we would like to point out that this does not exclude the possibility that recurrent connections, if set up in an appropriate way, also contribute to phase precession and theta sequences.

      • An important and perhaps essential component of the manuscript, is the distinction between extrinsic and intrinsic models. However, the main con- cepts on which this hinges, namely extrinsic and intrinsic sequences (and the related extrinsicity and intrinsicity) could be better explained and illustrated. Along these lines, the result suggested by the title, namely, hippocampal theta correlations, may be important yet incidental in light of the new concepts (e.g., extrinsicity, intrinsicity) and computational models (e.g., DG-CA3 recurrent loop) that are put forward.

      We have added substantial new explanatory material to the figures, captions and text to more didactically introduce the concepts of in- trinsicity and extrinsicity. We have also completely rewritten the abstract and added a subtitle: ”extrinsic and intrinsic sequences”

      • The study seems to put forward novel computational ideas related to neural coding. However, assessing novelty is challenging as this manuscript builds on previous work from the authors, including published (Leibold, 2020, Yiu et al., 2022) and unpublished (Ahmadi et al., 2022. bioRxiv) work. For example, the interpretation of intrinsic sequences in terms of landmarks had been introduced in Leibold, 2020.

      We agree with the reviewer that this paper touches on many related ideas from previous papers (not only of our lab) and is supposed to tie loose ends. Thus, the novel contribution is a biologically plausible mechanistic model of how intrinsic sequences and 2-d place maps interact on the level of interconnected spiking neurons. Such a level of explanation has not yet been available in previous work. We have considerably extended the Discussion section in our revision detailing the bigger picture underlying this theory. Also our addition of the non-recurrent model variant (see above) adds considerable novelty, since it provides an account of phase precession and preplay in novel environments.

      • The significance of the readout tempotron neuron could be expanded on. In particular, there is room for interpretation of the output signal of that neuron (e.g., what is the significance of other neurons downstream? Why is the rationale for this output to being theta-modulated?)

      We have added an additional Figure 8 to better illustrate the inner workings of the tempotron. We also extended the discussion to better explain the potential use of the tempotron output (see above). In short, we consider the tempotron to signal a unique behaviorally important context that is independent of remapping induced by changes of sensory cues, which is a new prediction of the model. Since the context signal is resulting from DG loops it requires a stable code to also exits in the DG. Evidence for such long-term stability in DG has been found in Hainmu¨ller & Bartos (2018).

      Reviewer #2 in their public review find ”this research topic to be both important and interesting” and appreciates ”the clarity of the paper.”, com- mending our ”efforts to integrate previous theories into their model and con- duct a systematic comparison”.

      We are very happy about these positive remarks and sincerely would like to thank the reviewer!

      Reviewer #1 made the following specific recommendations for changes:

      The abstract is somewhat difficult to parse. I have identified some words and/or sections that could be improved.

      • ’ ....inherently 1 dimensional’. This statement seems to be related to an a priori interpretation of the authors. On the other hand, if offline sequences are trivially 1 dimensional because they are sequences (i.e., they constitute a vector), then online sequences would be 1-dimensional as well. What is the key difference between offline and online? Is it the omnidirectional place fields in two dimensions? Perhaps more importantly, how relevant is this fact with respect to the main results of the manuscript, which concern ex- trinsic and intrinsic sequences?

      We indeed meant that the sequences are trivially 1-dimensional. The main challenge that we would like to address in this paper is how a 2-d topology of place cells (and direction dependent theta sequences) and a 1-d sequence topology of intrinsic theta correlations and during (p)replay can be reconciled. We hope this has become clearer in the rewritten abstract.

      • The language in lines 36-38 is overly technical. I suggest modifying the language, the language was less technical and more understandable in the body of the manuscript, which should be also reflected in the Abstract.

      We would would like to apologize for making the abstract too technical. Also in response to Reviewer #2, we decided to rewrite the ab- stract entirely.

      The authors use a mixture of conductance based models and Izhikevich neurons, presumably for the spiking generating mechanism. The conductance component can be readily interpreted in terms of the underlying biophysics. The Izhikhevich neuron model, however, is phenomenological. I suggest you address i) the rationale for using Izhikevich model, 2) its biophysical inter- pretation, 3) and its combination with conductance-based currents.

      The reviewer is correct that spike generation is modelled using Izhikevich’s model whereas synaptic integration is included in a conductance- based manner. As suggested by the reviewer, we have added further expla- nation in the Methods part, explaining that the Izhikevich approach allows to adjust burst firing properties with only few parameters by efficiently em- ulating the bifurcation structure of spike generation in the full biophysical model (1&2) and otherwise has no effect on the integration of conductance- based synaptic currents in a subthreshold regime (3).

      Line 126: when you say preferred angle, do you mean preferred (heading) direction? If so, please maintain consistency throughout.

      We thank the reviewer for pointing out the inconsistency. We have added the word ”heading” throughout the manuscript whenever ap- propriate. To further improve the consistency, we have clarified the meanings of ”best” (or ”worst”) direction and reserved the use of it solely for cases when trajectory direction is compared with the preferred heading direction, namely, ”best” (”worst”) direction when trajectory is along (opposite) the preferred heading direction.

      Line 174: When discussing cross-correlation, sometimes you mean a cross-correlation function between two place fields and sometimes to the his- togram of all such correlations? Please clarify.

      We used histograms to empirically estimate the underlying cross-correlation function. For clarity, we have specified that it is a cross- correlation histogram in the revised manuscript whenever we refer to the empirical estimate.

      Figure 3:

      Understanding the difference between extrinsic and intrinsic sequences is fundamental for the manuscript. I suggest that in the section that refers to Figure 3 (or Figure 3 itself), you kindly provide an example depicting how extrinsic and intrinsic sequences can

      1) coexist yet be distinctly identified

      2) depend on trajectory

      3) depend on DG input

      By coexistence, we meant the heterogeneous population of ex- trinsic and intrinsic cell pairs and, hence, the extrinsic and intrinsic theta correlations, as shown in Figure 3J. To improve the clarity, we added the following sentence in the section that refers to Figure 3: ”In our simula- tion, extrinsically and intrinsically driven cell pairs are both present in the population (Figure 3J), indicating a coexistence of extrinsic and intrinsic sequences.”. To illustrate how extrinsic and intrinsic sequences depend on both tra- jectory and DG recurrence, we have also added annotations in Figure 3F to mark the extrinsic and intrinsic part of the sequence.

      Moreover, the caption of Figure 3 refers to the directionality of the theta sequences. How does this again relate to the extrinsic/intrinsic distinction?

      We hope the highlighting in panel F of Figure 3 has resolved this problem.

      Figure 5:

      • This is a crucial figure that should illustrate the differences between extrinsic and intrinsic sequences, as the figure caption suggests. Surprisingly, it is not at all clear where (i.e., in which panel) and how (i.e., methodologi- cally) should one distinguish one type of sequence from another. I suggest that at least one such panel is dedicated to illustrating the difference and/or detection of these sequences in time and/or from phase precession plots. Moreover, there is significant visual crowding that makes the interpretation challenging (e.g., insert a space between G and E)

      We would like to apologize that in the previous version of the manuscript, we seemed to have evoked the impression that the difference between intrinsic and extrinsic sequences should be mainly illustrated in Figure 5. We hope that our revisions of Figures 1 and 3 have made it sufficiently clear to this point. The main purpose of Figure 5 was (and is) to illustrate how intrinsic sequences can lead to out-of-field firing. We have modified the figure caption (and text) accordingly. To address the visual crowding problem in Figure 5, we have inserted a space between panels and also removed repeated labels.

      Tempotron neuron and Figure 6:

      From the reviewer’s questions on Figure 6, we feel that our presentation caused considerable confusion about the motivation and inter- pretation of the tempotron simulations. We therefore rewrote parts of the associated text and Figure caption. We hope that the revised presentation clarifies the issues. We therefore only briefly respond to the reviewer’s points here, because we think they largely resulted from misunderstandings.

      • Intuitively, and as the manuscript results suggest, late phases are asso- ciated to extrinsic mechanisms while early phases are associated to intrinsic. Why not construct a simpler classifier readout based on this fact? How does it compare to a tempotron?

      Opposite to the reviewer’s comment, extrinsic mechanisms are visible at early phases (late in the field), intrinsic mechanisms at late phases (early in the field). In fact, what the tempotron does is learning to identify the intrinsic (late phase) part and to disregard the extrinsic (early phase) part.

      • What is the significance of theta-modulated output of the tempotron (readout) neuron?

      The theta modulation of the tempotron output is a trivial re- sult of the theta-modulation of the input, i.e., the detection of the intrinsic sequence pattern is done once every cycle.

      Suggestion for Figure 6 related to Tempotron readout: Focus on ’with DG loop condition’, as the challenge and most important point here is to identify extrinsic and intrinsic sequences. The No-loop condition could be left as a supplementary figure or side panel.

      The no-loop condition is the essential control showing that the tempotron only responds to the previously learned intrinsic pattern and can- not identify spatial location based on the extrinsic pattern.

      Further work/predictions.

      Lines 196-198. ”Since intrinsic sequences can also propagate outside the trajectory (Figure 5) and activate place cells non-locally, our model predicts direction-dependent expansion of place fields.” If remote activation is ’suffi- ciently’ remote, wouldn’t this predict two separate place fields instead of an expansion?

      The reviewer is completely correct. Out of field spiking can be also affecting remote locations, if the intrinsic sequences link to remote place fields. This would lead to double fields, however, the intrinsic part would only be active at late theta phases. For simplicity, we have not added such a case in our paper, but we would like to thank the reviewer for this comment, since it leads to a nice prediction of the model, which can be experimentally tested and therefore was included to the discussion.

      Lines 556-558. ”In our model, firing rate is determined by both low-phase spiking from sensory input and high-phase spike arrivals of DG-CA3 loops, both producing opposing effects on the phase distribution.” Is it possible to make a differential prediction based on lesions here, e.g., along the lines of reduced range phase precession, for either high phases or for low phases?

      We thank the reviewer for this great suggestion. Lesion of DG in the model does indeed reduce the phase range and mean spike phase. This further corroborates the effect of DG-loop on theta compression and high-phase spiking. We have included a new panel D in Figure 4 and a corresponding mention in the result section.

      Line 570. ”We speculate that the functional roles of intrinsic sequences may not be limited to spatial memories.”. Is there any relationship to re- play and/or sleep-dependent memory consolidation? Some speculation in the Discussion section would be welcome and appropriate.

      We have added some further speculative ideas to the last section of the Discussion. We propose that replay and preplay reflects the intrinsic sequences that express the current expectation of the animal. We have not yet thought well enough about their relation to memory consolidation to phrase this in the manuscript, but would suggest that they could serve to signal multimodal context information to the neocortex where it can evoke retrieval of unimodal memory traces.

      The description of the results, as stated in the public review, can be im- proved. A key component is the definition and identification of extrinsic and intrinsic sequences.

      Some comments:

      • I think that the words ’extrinsic’ and ’intrinsic’ are problematic as both types of sequences/models rely on external (spatial) input, hence both are in some sense ’extrinsic’. On the other hand, both are network mechanisms, thus in some sense ’intrinsic’, where the asymmetry is either programmed directly onto the weights or due to synaptic depression. To add to the con- fusion, ’intrinsic’ mechanisms very often refer to cellular mechanisms in neurophysiology. I kindly ask you to, ideally, reconsider the terminology, or at the very least, be very thorough and precise when describing the mech- anisms. For example, sometimes extrinsic (intrinsic) ’models’ are referred to, sometimes ’sequences’, sometimes ’factors’, sometimes ’pairs’, etc.

      We understand and appreciate the reviewers argument, but would like to stick to the terminology, since it was already used in our prior publication. We have made considerable effort to improve the explanation and illustration of extrinsic vs. intrinsic pairs in the main text, Figure 1 and 3 to highlight our definition that is based on pair correlations: Extrin- sic pairs flip the correlation lag with reversal of running direction, intrinsic pairs don’t. This is simply a functional definition and should not be con- fused with potential microscopic mechanisms. One of those (DG-loops) is suggested in our paper.

      • As discussed in the public review, network mechanisms may require experience-dependent plasticity and hence cannot easily explain phase pre- cession on the first pass. Please discuss why and/or how your model fits with this observation.

      We agree that the two models under consideration both require the recurrent network be set up appropriately and there is no theory so far that would explain how. The reason we chose these two models is because they are well known in the community and relatively similar. We reasoned that comparison between an intrinsic model and an extrinsic model would make most sense if the two are a similar as possible. Nevertheless, we ex- tended the manuscript by a new set of simulations in which we do not use re- current CA3 connections and obtain phase precession solely be feed-forward synaptic facilitation (new Figure 6 and supplementary Figure S1). The new simulations show that the basic phenomenology can also be obtained with- out using recurrent CA3 connections, however, as expected when removing one mechanisms of phase precession, the range of phase range is somewhat reduced as compared to the full model.

      Along a similar vein, phase precession in Figure 1E only has a range of pi/2, which is about half of the typical range of phase precession for single runs. This should be characterized as a weakness of the intrinsic model.

      The precession range in spiking models is highly sensitive to a large number of parameters such that it is hard to make such definite claims (see also above response). In the original Tsodyks et al. 1996 paper the phase range went up to 270 degrees with a slightly different implementation to ours in terms of current vs. conductance-based synapses, an exponen- tial instead of a Gaussian recurrent weight function, and 1-d (original) vs 2-d (ours). We chose conductance-based synapses, and a Gaussian weight profile for better comparison with the Romani and Tsodyks (2015) model. In the original non-spiking implementation by Romani and Tsodyks (2015), the phase range was hardly 70 degrees. Our model implementation of the Romani and Tsodyks (2015) model fits the experimentally reported phase ranges of about 70 to 180 degrees in CA3 (Harris et al., 2001).

      Lines 282-284: ”...since phase precession properties change in relation to running directions, nor are they solely intrinsic since reversal of correlation is still observed in most of the sequences (Huxter et al., 2008; Yiu et al., 2022).”. To which extent is this a consequence of the phase precession model (extrinsic vs intrinsic) or the fact that place fields are sometimes directional?

      The reversal of sequences with reversed running direction is how we define extrinsic correlation. We hope our changes in relation to Figure 1 has clarified this point.

      Figure 2: Is it i) directional input or ii) short-term facilitation that gives rise to lower phase? (or perhaps both?) Please clarify.

      It’s both. This is now clarified in the revised version of the Re- sults sections related to Figure 2: higher depolarization always yields earlier phases in spiking models, however, pair correlations are not affected by ei- ther of the two mechanisms.

      Line 320. ”...onset of phase precession”. Do you mean in CA3/CA1/DG?

      Thank you for pointing this out. We have clarified that this statement refers to CA3.

      Line 323. ”....at a different location”. Please add rationale why it has to be at a different location and a reference to the appropriate equation.

      The sequence rationale as well as the equation number have been added.

      Line 384. ” ... predicting that loss of DG inputs is compensated for by the increase of release probability in the spared afferent synapses from the MEC.”. It wasn’t clear whether this was a ’homeostasis prediction’, or and implementation in the model. Please clarify.

      Since the model explained the experimental observations by implementing an increased probability of release, the model predicts that in animals with DG lesion the probability of release should be enhanced. We have modified the wording to avoid confusion.

      Line 428 ”...and near future locations) is obvious, the potential role of the lesser expressed intrinsic sequence contributions is not straightforward.”. Similar to my comments above regarding terminology, please clarify what are both contributions and why are intrinsic sequences ’lesser expressed’.

      We have rewritten this passage to avoid unclear wording.

      Line 474. ”...we showed that the trajectory-independent sequences”. Do you mean ’intrinsic sequences’?

      We thank the reviewer for careful reading! We have changed the wording ”intrinsic sequences” in the revision.

      Line 482. ”...field pairs being extrinsic”. Please clarify, as the usage of extrinsic now refers to field pairs.

      Thank you for pointing this out. We went through the whole manuscript and clarified the terms.

      Line 245 (heading). Consider rewriting as ’Dependence of theta se- quences on heading directions’. Extrinsic and Intrinsic models have not yet been introduced.

      Since the main purpose of the first Results section is to explain the difference between extrinsic and intrinsic sequences we kept these terms in the heading but modified it to ”Dependence of theta sequences on head- ing directions: Extrinsic and intrinsic sequences”. Additionally, we have put more emphasis on introducing the terms ”extrinsic” and ”intrinsic” in this section.

      Figure 1.

      • I suggest using the same font - C and D, and F and G are too close to each other, consider adding space. For example, the exponent, 10-2 makes reading cumbersome. Line 300. Phase tail means offset phase? Phase tail may be too informal. Line 325: DG loop. Do you mean CA3-DG projection?

      We thank the reviewer for the suggestions. In the revised manuscript, we have ensured that the same font is used in all of the fig- ures. To improve the readability of Figure 1, we have added space between panels as suggested, removed repeated axis label and downsized the text ”10-2”. Furthermore, we have rewritten the referenced line without using the word ”tail”, and also, clarified the meaning of DG loop as the short form of CA3-DG projection.

      Figure 4 caption: ”DG lesion reduces temporal correlations...”. It is more precise to say that the lesion reduces the slope of the fitted lag vs dis- tance. And how is this related to sequence compression?

      In the paragraph referring to Figure 4, we have elaborated on the meaning of theta compression and its relation with the the lag-distance plot. However, we argue that ”reduces the slope of the fitted curve” is not comprehensive enough to express our summarized conclusion in a caption title. We have modified the wording to be ”DG lesion reduces theta compression”.

      In addition, we have changed the slope unit to be radians per cm rather than radians per maximum pair distance, in conformity to unit standards.

      General comment about terminology with regards to tuning and connec- tivity: it is not formally correct to compare connectivity with trajectories (e.g., lines 388-395, caption of Figure 5A, etc). Perhaps compare tuning to particular directions/preference or receptive field?

      We have corrected the wording such that the direction of DG- loop projection is compared to the direction of trajectory.

      Line 470. ’...fixed recursive loop.” Sentence is not clear, do you mean recurrent loops?

      The reviewer is correct. We corrected the wording

      Reviewer #2 had the following recommendations.

      M1. The abstract focuses on the differences between online and offline hippocampal replays. However, the replay topic is not touched upon in the rest of the manuscript. I found this very confusing when I first read the pa- per. I suggest the authors reconsider the best way to approach the opening or at least discuss if and how their model would incorporate replay phenomena.

      Also in response to reviewer #1 we have rewritten the abstract focusing on the problem of how to generate 2-d topology from 1-d sequences. In addition, also in response to Reviewer#1 we added a paragraph in the discussion detailing a hypothesis on how er think replay and intrinsic se- quences work together.

      m2. On lines 89-91, the authors provide the selection of neuronal pa- rameters for excitatory pyramidal cells and inhibitory cells in the Izhikevich model. While the choice of model is reasonable, it would be helpful to clarify the source of these neuronal parameters, especially for readers who are not familiar with the model.

      Again, also in response to reviewer # 1, we have added more motivation for the Izhikevich model.

      M3. On lines 94-98, the model considers a 2D sheet of CA3 neurons. One of the most significant assumptions is that each 2x2 tile of place cells is considered a unit with four directional angles. What is the basis for this assumption? Is there any experimental result supporting this, or is it a completely artificial design for the model? This is important since the or- ganization of CA3 cells also affects the network architecture discussed later and impacts the realism of the model.

      This comment is related to Reviewer #1’s concern on experience- dependent plasticity: How is this connectivity pattern established? We fully agree that this is an open problem for the Tsodyks et al.-type networks. The main reason for choosing them (as argued in our response to reviewer #1) is to have two published models, representing one type of sequence each, that are similar enough for comparison. In addition, we added new simulations (new Figure 6 and Supplementary Figure S1), showing that the basic phe- nomenology can also be obtained in a model without recurrent connections (see also response to Reviewer # 1)

      m4. Similarly, on lines 111 and 140, the model uses 500 ms for the timescales of short facilitation and short-term synaptic depression. The choices of these two timescales are vital for producing directionality in extrin- sic and intrinsic sequences, yet their experimental sources are not clarified.

      In the Methods section of the revised manuscript, we have in- cluded the sources of previous experimental data and modelling work to support our choice of the time constants.

      M5. On line 126, the authors assume that the synaptic strengths be- tween CA3 cells, Wij, are given by the distances between neurons and the similarity between their directional preferences. While this assumption seems reasonable in the sensory cortex, I am unsure if this is also the case in the hippocampus, and the authors should clarify the basis for this assumption.

      The distance dependence simply reflects the original Romani and Tsodyks 2015 model (see response to M3) and we share the concern of the reviewers. The increased connectivity for neurons with the same di- rectional preference was necessary to recover the direction dependent phase precession properties (Figure 2) in the realm of the Romani and Tsodyks 2015 model. Please also see our new Figure 6 showing simulations without the recurrent matrix.

      More importantly, the existing connections within CA3 and DG cells completely determine the ”intrinsic” sequences. But wouldn’t this be fragile when place cells undergo global remapping, which can take place within only a few seconds? The author should comment on this in the discussion.

      We would like to thank the reviewer for bringing up this inter- esting point. In our thinking, the DG-CA3 connectivity is fixed (multiple 1-d trajectories, not necessarily requiring 2-d topology), i.e., the same in- trinsic sequence should show up in multiple environments (and should not remap), although it may just not be active in some environments). This is a prediction of our model and we have added it to the Discussion.

      M6. I found the setup of DG place cells unreasonable. DG place cells are found to be granule cells rather than pyramidal cells. Moreover, the model does not consider recurrent connections between DG cells (These setups are closer to CA1 place cells).

      We agree with the reviewer, DG granule cells should rather be modelled as high-input resistance EIF neurons. However, the feedback loop via the dentate is not a direct one. It involves hilar mossy cells plus multiple hierarchies of feedback inhibition (this is probably what the reviewer means with recurrent connections between DG neurons, because granule cells are not recurrently connected in the non-pathological state). To our knowledge a biologically realistic model of the hilar-DG network does not exist and it would be far beyond the scope of this paper to develop one. We therefore see our DG feedback model rather as phenomenological. The discussion paragraph on the anatomy of the dentate gyrus touches on these points.

      Therefore, a significant concern is: Why should it be the DG feedback projection to CA3 responsible for the ”intrinsic” sequences instead of pro- jections from other brain areas?

      The reviewer is generally correct, any brain structure which im- plements fixed sequences via a loop would do. The reason why we suggest the DG to be the best candidate is purely empirical referring to papers with dentate lesions: Sasaki et al. 2018 and Ahmadi et a. 2022. We have added a similar argument to the discussion.

      m7. On line 166, the authors claim that there are no connections between inhibitory cells at all. While I understand that this is for simplification of the model, the lack of recurrent inhibition between interneurons may have limited the model’s ability to produce gamma-band dynamics (referring to PING and ING mechanisms), which are robust rhythms produced in CA3. I am very curious if the model can incorporate theta-gamma coupling by in- troducing connections between CA3 inhibitory cells.

      We have omitted the gamma oscillation for simplicity, because we do not have a hypothesis for a functional role in the context of dis- tinguishing extrinsic from intrinsic sequences (Occam’s razor) and, as the reviewer correctly anticipates, they unavoidably show up when inhibitory in- terneurons connect to each other (e.g. Thurley et al. 2013). Of course, one could envision situations in which gamma for intrinsic sequences my have different frequency than for extrinsic ones, by differentially manipulating the CA3 and DG basket cell networks, but, as long as there is no experimental data, it would be pure speculation and thus we have not included it in the model.

      m8. The authors should clarify the source of parameters in Table 1, especially the synaptic strengths. These values are vital for extrinsic and intrinsic theta sequences.

      The weight values have been chosen to allow for large theta phase precession range, coexistence of extrinsic and intrinsic sequences, and stability of the network activity. A similar statement has been added to the manuscript.

      M9. I have another concern regarding the measurements of ”extrinsic- ity” and ”intrinsicity” defined on lines 185-196. Are they the best measures? To distinguish the cause of spike correlations, the ”extrinsicity” and ”intrin- sicity” of a pair of spikes should not be high at the same time. However, this is clearly not the case in the model, according to Figs 3 and 5. Moreover, in the data analysis carried out later, spike pairs are considered extrinsic or intrinsic merely by comparing the two measurements. I suggest the authors consider counterfactual methods in causal inference. For example, would a spike pair (cell1, cell2) still exist if we change the sensorimotor inputs or the DG-CA3 projections? If this is difficult to implement, the authors should at least discuss how different choices of measurements would impact the con- clusions of the paper.

      The problem the reviewer has identified arises from the funda- mental symmetry of theta phase quantification: if spikes of a pair of place fields have a phase difference of 180◦ one cannot say which cell leads and which cell follows, hence, the phase difference is both intrinsic (because the peak doesn’t flip) and extrinsic (because the peak flips and ends up at the same phase). The fact that in some cases extrinsicity as well as intrinsicity are high simply means that the field pair has a correlation peak lag close to 180◦. Since in the experimental data set in (Yiu et al. 2022) only field pairs were available, we have not been able to use a different quantification then and decided to apply the same quantification in our model for comparison. Moreover, Figure 5F nicely shows that the measures are able to retrieve the ground-truth intrinsic DG-loop structure when considered on the population level.

      In our model, though, we can go beyond 2-nd order statistics and derive sequence similarity measures including multiple cells, e.g., Chenani et al. 2019. However, since, we already know the ground truth by construction, we decided to not use these methods. We added a paragraph in the discus- sion elaborating on beyond 2nd order sequence quantification.

      m10. The authors begin discussing ”intrinsic sequences” from line 316. However, it is not defined before that (and in the rest of the paper as well), causing confusion when reading the paper. The exact definitions of extrinsic and intrinsic sequences should come earlier.

      We hope that our changes to the beginning of the results section (Figure 1), also asked for by Reviewer # 1 could clarify the confusion.

      m11. On lines 345-347, the authors claim that ”the intrinsic sequences are played out backward as determined by the direction of fixed recurrence (Figure 3F),” which is vague. If such sequences are present in that panel, it should be more explicitly indicated graphically.

      Also in response to Reviewer #1, we have graphically high- lighted the two types of sequences.

      M12. On lines 309, 356, 484, 495, 515, and possibly other instances, the authors repeatedly claim that the model simulations are in ”quantitative agreement” with their previous experimental paper. However, no experimen- tal data or comparison with the simulations are presented in this paper. The authors should at least create one figure to demonstrate the degree of consistency between them, instead of merely asking the reader to refer back to their previous paper.

      We agree with the reviewer that the experimental data of our previous paper should be presented in the manuscript. However, creating more panels or figures is likely to clutter the already crowded visuals and ob- scure our main message. We therefore decided to give numerical comparisons the previous findings in the main text whenever appropriate, specifically, in the sections referring to Figures 2, 3 and in the Discussion.

    1. Author response

      Reviewer #1 (Public Review):

      The potential role of the CaMKII holoenzyme in synaptic information processing, storage, and spread has fascinated neuroscientists ever since it has been described that self-phosphorylation of CaMKII at T286 (pT286) can maintain the kinase in an activated state beyond the initial Ca2+ stimulus that induced kinase activation and pT286. The current study by Lučić et al utilizes biochemical and biophysical methods to re-examine two pT286 mechanisms and finds:

      (1) that a previously proposed activation-induced subunit exchange within the holoenzyme can not provide pT286 maintenance or propagation; and

      (2) that pT286 can occur not only within a holoenzyme but also between two holoenzymes, at least at sufficiently high concentrations.

      For the observation regarding the subunit exchange, the authors go above and beyond to demonstrate that a previously proposed activation-induced subunit exchange does not actually occur in their hands and that the previous appearance of such a subunit exchange may instead be due to activation-induced interactions between the kinase domains of separate holoenzymes. This provides important clarification, as the imagination about the possible functions of this subunit exchange has been running wild in the literature.

      By contrast, pT286 between holoenzymes at sufficiently high concentrations was largely predicted by the previously reported concentration-dependence of pT286 between monomeric truncated CaMKII (although these previous experiments did not rule out that such pT286 could have been excluded for intact full-length holoenzymes). Notably, the reaction rate reported here for pT286 between two holoenzymes is more than two orders of magnitude slower compared to the previously described rate of the pT286 reaction within a holoenzyme.

      The only point on which we disagree (and we think it’s unarguable) is that the current consensus is that inter-holoenzyme phosphorylation simply doesn’t happen (whether or not monomers can phosphorylate each other). The reviewer is of course right that this view seems now less and less likely. We now performed new experiments to investigate this critical point further (see below).

      The probable reason for the discrepancy in reported half-time of phosphorylation measured in earlier reports and in our paper is the fact that earlier reports (for example Bradshaw et al., 2002) measured autophosphorylation rate of wild-type CaMKII holoenzymes, at catalytically-competent enzyme concentrations of 0.1-5 µM. We are reporting the phosphorylation rate of 4 µM kinase-dead CaMKII, which is only a substrate, by 10 nM catalytically competent enzyme (CaMKII wild-type). There is up to 500 times less catalytically competent enzyme in our reactions, which is probably the reason why the reaction itself is several orders of magnitude slower.

      In summary, this study contains two somewhat disparate parts: (1) one technical tour-de-force to provide evidence that argues against activation-induced subunit exchange, which was a tremendous effort that provides influential novel information, and (2) another set of experiments showing the somewhat predictable potential for pT286 between holoenzymes, but without indication for the functional relevance of this rather slow reaction. Unfortunately, in the current/initial title of the manuscript, the authors chose to emphasize the weaker part of their findings.

      We agree with the reviewer that the title should be modified to emphasize both findings of our study. We also hope that our new experiments do bolster our findings with regard to pT286 between holoenzymes, as the reviewer puts it.

      The seemingly slow inter-holoenzyme phosphorylation is only slow under conditions in which one of the proteins is kinase-dead. In situation in which all CaMKII holoenzymes are wild-type and therefore capable of performing phosphorylation (both intra- and inter-holoenzyme) the reaction rates for pT286 are expected to be orders of magnitudes faster, than those reported here for the phosphorylation of T286 on kinase-dead protein.

      Reviewer #2 (Public Review):

      This well-written manuscript provides a technical tour-de-force to provide a novel mechanism for sustaining CaMKII autophosphorylation through an interholoenzyme reaction mechanism the authors term inter-holoenzyme phosphorylation (IHP). The authors use molecular engineering to create designer molecules that permit detailed testing of the proposed interholoenzyme reaction mechanism. By catalytically inactivating one population of enzymes, they show using standard assays that the inactive enzyme can be phosphorylated by active holoenzymes. They go on to show that in cells, the inactive enzyme is phosphorylated only in the presence of co-expressed active CaMKII and that this does not appear to be due to active and inactive subunits mixing within the same holoenzyme. The authors suggest reasons for why previous experiments failed to expose IHP and in some experiments provide evidence that reproduces and then extends earlier studies. Some noted differences from earlier experiments are the reaction temperature, the time course of the reactions, and that significantly higher concentrations of the inactive (substrate) kinase in the present study amplify the IHP. These are plausible reasons for earlier studies not finding significant evidence for IHP and the presented data is well-controlled and of high quality.

      The authors then take on the idea of subunit exchange employing multiple strategies. Using genetic expansion, they engineer an unnatural amino acid into the hub domain of the kinase (residue 384). In the presence of the photoactivatable crosslinker BZF and UV illumination, a ladder of subunits was generated indicating intraholoenzyme crosslinks were established. Using this cross-linked enzyme, presumably incapable of subunit exchange, the authors show significant phosphorylation of the kinase-dead mutant. This further supports that IHP is the cause of phosphorylation and not subunit exchange. Extending these experiments, they could not find evidence when CaMKIIF394BZF was mixed with the kinase-dead mutant and exposed to UV light, that there was evidence of the kinasedead subunits exchanged into CaMKIIF394 (active) enzymes.

      Just a note, instead of residue 384, this should read 394.

      With an entirely different approach, the authors use isotopic labeling of different pools of wt CaMKII (N14 or N15) followed by bifunctional cross-linking and mass spec to assess potential intra- and interholoenzyme contacts. Several interesting findings came of these studies detailed in Figure 4, mapped in detail in Figure 5, and extensively documented in supplementary tables. Critically, numerous crosslinks were found between different domains of the enzyme (catalytic, regulatory, hub) that are themselves a nice database of proximity measurements, but critical to the hypothesis, no heterotypic cross-links were found in the hub domains at any activated state or time point of incubation. This data supports two findings, that catalytic domains come into close proximity between holoenzymes when activated, supporting the potential for IHP, but that no subunit exchange occurs.

      The authors then pursue the approach used originally to provide evidence of subunit mixing, single molecule-based fluorescence imaging. Using pools of CaMKII labeled with spectrally separable dyes, the authors reproduce the earlier findings (Stratton et al, 2016) showing that under activating conditions, but not basal conditions, colocalized spots were detected. Numerous controls were done that confirm the need for full activation (Ca2+/CaM + Mg2+/ATP) to visualize co-localized CaMKII holoenzymes. Extending these studies, the authors mix holoenzymes, fully activate them, and after sufficient time for subunit exchange (if it occurs), the reactions were quenched, and then samples were analyzed. The result was that no evidence of dual-colored holoenzymes was present; if subunits had mixed between holoenzymes, dual-colored spots should have been evident after quenching the reactions. This was not the case. Further, experiments repeated with pools of differentially labeled kinase dead enzymes produced no colocalization, as predicted, if activation of the catalytic domains is necessary to establish IHP.

      Finally, the authors employ mass photometry to investigate the potential for interholoenzyme interactions. At basal conditions, only a mass peak consistent with CaMKII dodecamers was evident. Upon activation, a small fraction of dimeric complexes was evident (with Ca2+/CaM bound) but the majority of the peak was a dodecamer with 12 associated CaM molecules, and importantly, a significant fraction of a mass population was found consistent with a pair of holoenzymes with associated CaM. As an aside, the holoenzyme population appeared to be modestly destabilized as evidence of a minor fraction of dimers appeared as the authors diluted the enzyme, but the pools of holoenzyme and pairs of holoenzymes (with CaM) remained the dominant species when activated under all three enzyme concentrations assessed. Supporting the importance of activation for interactions between holoenzymes, the catalytically dead kinase even under activating conditions, shows no evidence of dimers of holoenzymes.

      Each of the approaches is well-controlled, the data is of uniformly high quality, and the authors' interpretations are generally well-supported.

      We are very grateful for these supportive comments.

      Reviewer #3 (Public Review):

      CaMKII is a multimeric kinase of great biologic interest due to its crucial roles in long-term memory, cardiac pacemaking, and fertilization. CaMKII subunits organize into holoenzymes comprised of 1214 subunits, adopting a donut-like, double-ringed structure. In this manuscript, Lucic et al challenge two models in the CaMKII field, which are somewhat related. The first is a longstanding topic in the field about whether the autophosphorylation of a crucial residue, Thr286, can be phosphorylated between intact holoenzymes (inter-holoenzyme phosphorylation). The second is a more recent biochemical finding, which tested the long-running theory that CaMKII exchanges subunits between holoenzymes to create mixed oligomers. These two models are connected by the idea that subunit exchange could facilitate phosphorylation between subunits of different holoenzymes by allowing subunits to integrate into a different holoenzyme and driving transphosphorylation within the CaMKII ring. Here, the authors attempt to show that one intact holoenzyme phosphorylates another intact holoenzyme at Thr286. The authors also provide evidence suggesting that subunit exchange is not occurring under their conditions, and therefore not driving this phosphorylation event. The authors propose a model where instead of exchanging subunits, two holoenzymes interact via their kinase domains to enable transphosphorylation at Thr286 without integrating into the holoenzyme structure. In order for the authors to successfully convince readers of all three facets of this new model, they need to provide evidence that 1) transphosphorylation at Thr286 happens when subunit exchange is blocked, 2) subunit exchange does not occur under their conditions, and 3) there are interactions between kinases of different holoenzymes that lead to productive autophosphorylation at Thr286.

      Strengths:

      The authors have designed and performed a battery of cleverly designed and orthogonal experiments to test these models. Using mutagenesis, they mixed a kinase-dead mutant with an active kinase to ask whether transphosphorylation occurs. They observe phosphorylation of the kinase-dead variant in this experiment, which indicates that the active kinase must have phosphorylated it. A few key questions arise here: 1) whether this phosphorylation occurred within a single CaMKII holoenzyme ring (which is the canonical mechanism for Thr286 phosphorylation), 2) whether the phosphorylation occurred between two separate holoenzyme rings, and 3) why was this not observed in previous literature? To address questions 1 and 2, the authors implemented an innovative strategy introducing a geneticallyencoded photocrosslinker in the oligomerization domain, which when crosslinked using UV light, should lock the holoenzyme in place. The rate of phosphorylation was the same when comparing uncrosslinked and crosslinked CaMKII variants, indicating that phosphorylation is occurring between holoenzymes, rather than through a subunit exchange mechanism that would require some type of disassembly and reassembly (presumably blocked by crosslinking). The 3rd question remains as to why this has not been previously observed, as it has not been for lack of effort. The authors mention low temperature and low concentration as culprits, however, Bradshaw et al, JBC v. 277, 2002 carry out a series of careful experiments that indicated that autophosphorylation at T286 is not concentration-dependent (meaning that the majority of phosphorylation occurs via intra-holoenzyme), and this is done over a concentration and temperature range. It is possible that due to the mutants used in the current manuscript, it allows for the different behavior of the kinase-dead domains, which will have an empty nucleotide-binding pocket. Further studies will need to elucidate these details, and importantly, understand what physiological conditions facilitate this mechanism.

      We thank the reviewer for their assessment of our work.

      The paper cited by the reviewer (Bradshaw et al, JBC v. 277, 2002) is indeed a carefully designed biochemical investigation of CaMKII activity. As the reviewer pointed out, one of the conclusions of the paper is that the autophosphorylation of CaMKII is not concentration dependent, implying that it has to occur exclusively intra-holoenzyme. However, there are some limitations which colour the interpretation of this classic paper. Bradshaw and colleagues used only CaMKII wild-type protein, so the autophosphorylation which is taking place in their reactions is possible both within holoenzymes and between holoenzymes, but this is impossible to distinguish. The authors of the cited paper then used “Autonomous activity assay” (not any measurement of pT286 on CaMKII itself) in which they first stopped the initial autophosphorylation reaction at T286 by adding a quench solution which contained a mixture of EDTA and EGTA, and then measured phosphorylation of the peptide-substrate of CaMKII (autocamtide-2), in the absence of Calmodulin binding (autonomous activity). They also diluted the autophosphorylation reaction to 10 nM CaMKII before adding it to the “Autonomous activity assay”.

      As a side point, each reaction was quenched and diluted to the same final CaMKII concentration of 10 nM. They measured the activity of this dilution with phosphorylation of a peptide-substrate (autocamptide-2), in the absence of CaM binding. The authors contend that autonomous activity reported in this way reflects the amount of pT286, which is not impossible, but it is not a direct measure of pT286.

      All this adds up to allowing the autophosphorylation of wild-type CaMKII at various concentrations ranging from 0.1 to 4.6 µM in the presence of 10 µM Ca/CaM and 500 µM Mg/ATP. This is a very fast reaction, concentrations of enzyme (CaMKII wild-type), activator (Ca/CaM) and ATP/Mg are all high at the beginning of the autophosphorylation reaction and would expect to allow for maximal autophosphorylation in very short times (seconds). Most importantly, this experiment does not exclude a inter-holoenzyme reaction slower than the intra-holoenzyme one. It certainly could not detect it.

      In any case, to relate these concepts to our experiments and current understanding of CaMKII, we performed a new set of experiments modelled on the Bradshaw paper. Critically, we used CaMKII wild-type as the enzyme, and CaMKII kinase-dead, as the substrate. Intraholoenzyme phosphorylation cannot occur in this reaction, which was designed to detect a concentration-dependent phosphorylation reaction. We used a fixed concentration of the substrate kinase (4 µM), and 4 different concentrations of CaMKIIWT ranging from 0.5 -100 nM. In our assay, the level of phosphorylation on substrate CaMKII(CaMKIIKD) was dependent on concentration of enzyme CaMKII (CaMKIIWT) (Figure 1-figure supplement 3), adding more evidence to the hypothesis that CaMKII autophosphorylation can occur inter-holoenzyme.

      The possibility that empty nucleotide binding pocket is influencing the phosphorylation status of T286 in the regulatory domain of kinase-dead CaMKII is highly unlikely. One could maybe envision that empty nucleotide binding pocket might expose the regulatory domain in kinase-dead CaMKII for phosphorylation, which would be prevented in CaMKIIWT, but in all available structures of CaMKII (Chao et al, 2011; Myers et al., 2017, Buonarati et al., 2021), the regulatory domain is docked to the kinase domain of CaMKII, although the nucleotide binding pocket is empty (either by mutation of residue K42 and/or simply by not adding the ATP/Mg to reduce chemical dispersity of the sample). The only time the regulatory domain was not docked on the kinase domain is when CaMKII was in complex with Calmodulin (Rellos et al., 2010). Finally, in our crosslinking mass spectrometry experiments, we used both heavy and light forms of CaMKII wild-type, and there we can clearly see interactions between kinase/regulatory domains of two different species of CaMKIIWT, which are dependent on activation.

      The most convincing data that subunit exchange does not occur is from the crosslinking mass spectrometry experiment. The authors created mixtures of 'light' and 'heavy' CaMKII holoenzymes, either activated or not and then used a Lys-Lys crosslinker (DSS) to trap the enzyme in its final state. The results of this experiment indicate that subunit exchange is not occurring under their conditions. A caveat here is that there are not many lysines at hub-hub interfaces, which is the crux of this experiment. If there is no subunit exchange under their conditions, how does transphosphorylation occur between holoenzymes? The authors show very nice mass photometry data indicating that there are populations of 24-mers, which corresponds to a double-holoenzyme. Paired with the data from their crosslinking mass spectrometry which shows crosslinks between kinase domains of different holoenzymes, this indicates that perhaps kinases between holoenzymes do interact, and they do so in a competent manner to allow transphosphorylation to occur.

      It is true that there are “only” 6 Lysines in the hub domain of CaMKII. However, it is clear from our crosslinking mass spectrometry data that we can detect hub:hub peptides coming from the same holoenzymes (homocrosslinks, either 14N: 14N or 15N: 15N species), but never between holoenzymes (14N with 15N). The fact that peptides can be detected in the homocrosslinks speaks to the validity of using Lysine crosslinkers in this experiment.

      Weaknesses:

      The authors should be commended for performing three orthogonal experiments to test whether CaMKII holoenzymes exchange subunits to form heterooligomers. However, there are technical issues that dampen the strength of the results shown here. For simplicity, let's consider that CaMKII holoenzymes are comprised of two stacked hexameric rings. It has been proposed that the stable unit of CaMKII assembly and perhaps also disassembly and subunit exchange is a vertical dimer unit (comprised of one subunit from each hexameric ring). In the UV crosslinking data shown in this paper, the authors have a significant number of monomers, some crosslinked dimers (of which there are two populations), and fewer higher-order oligomers. To effectively block subunit exchange, robust crosslinking into hexamers is necessary, which the authors have not done. Incomplete crosslinking results in smaller species that can still exchange (and/or dissociate), confounding the results of this experiment. In addition, Figure 3 shows a trapping experiment, where if the exchange was occurring, there would be an oligomeric band in Lane 8, which is visible and highlighted with a blue arrow by the authors. This result is explained by nonspecific UV effects, however by eye it is not clear if there is an equivalent band in lane 10. The overall issue here is inefficient crosslinking.

      We agree with the reviewer that the robustness of the UV-induced crosslinking is not extremely high. However we do observe higher order oligomers on the gel (Figure 2 and Figure 3B, pT286 blot), which states that at least a portion of the holoenzymes is crosslinked. On the other hand, the UVinduced crosslinking is not slowing down the trans-phosphorylation reaction, which would be expected if the subunit exchange would be the prevailing mechanism for spread of kinase activity between holoenzymes.

      In figure 3, lanes 8 and 10 show a small portion of dimers (less than 5% by densitometry), and at the absolute limit of detection. This dimer band is most likely due to unspecific UV-induced disulfide bridging (we already lessened it by adding 50 mM TCEP prior to UV treatment (Figure 3-figure supplement 1B and C). Previous reviewers of this manuscript criticized the small dimer band in lane 8, and we wanted to address this transparently in the submission to eLife.

      Unfortunately, if we absolutely crank up the contrast to see this band in lane 10, we start to see other features in the noise as well. We have now edited the image in Figure 3B to highlight these minor bands more clearly, but this is also not ideal.

      With regard to the trapping experiment, the overall problem is not inefficient crosslinking, because we see that P-T286 signal is quite nicely represented in higher order bands from F394BzF protein, but kinase dead protein (Avi-tagged signal in Figure 3) is almost entirely absent. Any crosslinking of Avitagged protein (possibly corresponding to subunit exchange) is a minor process at the limit of detection on WB.

      Unfortunately we did not yet find any better crosslinking sites than the two we report (we have tried about 10). But the results we did obtain encouraged us to employ other techniques to probe subunit exchange (for example, the MS X-linking).

      The authors also employ a single-molecule TIRF experiment to further interrogate subunit exchange. Upon inspection of the TIRF images, it is not clear that the authors are achieving single molecule resolution (there are evident overlapping and distorted particles). The analysis employed here is Pearson's correlation coefficient, which is not sufficient for single molecule analysis and would not account for particle overlap, particles that are too bright, and/or particles that are too dim. For example, an alternative explanation for the authors' results is that activation results in aggregation (high correlation), and subsequent EGTA treatment leads to dissociation at these low concentrations (low correlation). However, further experimentation and analysis are necessary.

      In the manuscript we present raw images, not processed. As we wrote in the material and methods, we thresholded the images for further processing. All colocalization methods have drawbacks, but we found that our thresholding combined with the Pearson coefficient was highly reproducible. We did also look at Manders coefficients, but these are less straightforward to understand, whilst still giving in our hands the same answer. We agree, there are more experiments that can be done, with particular predictions based on our new mechanism. And we are doing them and will report them when they are ready.

      At the risk of repeating ourselves, the reversible loss of overlap of the two labelled populations is the key result and cannot be explained by spurious dim or bright particles, or by a few overlapping profiles.

      Taken together, the authors have provided important food for thought regarding inter-holoenzyme phosphorylation and subunit exchange. However, given the shortcomings discussed here, it remains unclear exactly what mechanisms are at play within and between CaMKII holoenzymes once activated.

      We thank the reviewer for their critical assessment of our manuscript. We will continue to investigate the relevant points and refine the overall picture of CaMKII, to better clarify the mechanisms.

    1. We continue to talk about grades long after they’ve ceased to matter because they mark us indelibly. We continue to talk about grades long after they’ve ceased to matter because they mark us indelibly. And it’s just as important to recognize that indelible mark as it is to recognize that if grades can cease to matter at some point in our lives, it might stand to reason they never really mattered in the first place.

      I think its an interesting matter to bring up with if grades ceased to exist because they have been ingrained into all of us for so long as a society that itd be almost impossible to not matter at any point. Its a reflection of where we were in society and where we had a winner's mentality.

    1. First, average automation risks decrease as education level goes up, largely because jobs requiring bachelor’s degrees involve a greater number of transferable skills that are less easy to automate.

      Hard disagree with the conclusion. Computers in general, and ChatGPT in particular, has been historically VERY good at replacing white collar and bureaucratic labour. It's particularly terrible at replacing manual labour, skilled trades and human-to-human emotional interaction. The axiom that low-education jobs are getting automated is an axiom we've been asked to accept for decades but it's just not happening.

    2. contemporary CTE focuses on equipping high school and community college students with technical skills that are closely tethered to specific workforce applications

      This is evolving constantly. What CTE means today is completely different than what it will mean next year. Just imagine how much more quickly it will evolve with AI influencing it's next steps.

    1. It is yet unclear whether use of content is covered under ‘fair use’ and will require additional licensing. For now, it seems that AI use is yet just another benefit to companies looking to license content from scholarly publishers. In turn, publishers may be able to increase their service offerings and add additional value to the companies, organizations, and governments that license their content. “As a matter of US copyright law, courts are more likely to rule in favor of copyright owners when licenses are available”, says Roy Kaufman, Managing Director, Business Development at Copyright Clearance Center.

      And how will this impact on copyright use law in countries like Australia where special libraries rely heavily on USA-centric publishers for academic best evidence? It's such a fraught conundrum and I expect there will be cases of "copyright breach" as a result of say Australian health libraries using content that to all intents and purposes is approved under US fair use but will be contested under fair dealing law, here. But... if this stuff is black boxed - how on earth can we even verify the copyright requirements behind LLM generated out puts?

    1. I just wanted to see what a long bass string sounded like.

      It's amazing how such a project can start from such a simple question.

      At 14 starting to build a piano and then following through with it is such an amazing feat. Then for it to work and for concert pianists to want to play on it. That is truly incredible.

    1. Reviewer #2 (Public Review):

      While the question of 'are AlphaFold-predicted structures useful for drug design' has largely seen comparisons of AF versus experimental protein structures, this paper takes a less explored (but perhaps more practically important) angle of 'are AlphaFold-predicted structures any better than the previous generation of homology modeling tools' to the protein-ligand (rigid) docking problem. The conclusions of this work will be of largest interest to the audience less familiar with the precision required for successful rigid docking, while the expert crowd might find them obvious, yet a good summary of results previously shown in the literature. Further work, understanding the structural objectives/metrics that should be placed on future AlphaFold-like models for better pose prediction performance, would greatly expand the practicality of the observations made here.

      The main conclusion of the paper, that structural accuracy (expressed as RMSD) of the protein model is not a good predictor of the accuracy the model will show in rigid docking protein-ligand pose prediction, is a good reminder of the well-appreciated need for high-quality side chain placements in docking. The expected phenomenon of AlphaFold predicting 'more apo-like structures' is often discussed in the field, and readers should be cautious about drawing conclusions from the rigid (rather than flexible, as in some previous works) docking done here.

      The authors have very clearly communicated that the use of AlphaFold-generated structures in traditional docking might not be a good idea, and motivated that the time of a molecular designer might be better spent preparing a high-quality homology model. The visual presentation of the conclusions is very clear but might leave the reader wanting a more in-depth discussion of which structural elements of the AF models lead to bad docking outcomes. For example, Fig. 3 presents an example of a very accurate AlphaFold prediction leading to the ligand being docked completely outside of the binding pocket. Close inspection of the Figure suggests a clash of the ligand with the slightly displaced tryptophan residue in the AF model that might be to blame, as can be confirmed by comparison of the model and PDB structure by the reader themselves but has not been discussed by the authors. Only a few examples of the systems used are shown even visually, leaving the reader unable to study more interesting cases in depth without re-doing the work themselves.

      The authors acknowledged that several recent studies exist in this space. They point out two advancements made in their work, worthy of further review. Similarly, it's important to evaluate the novelty of this work's claims vs previously available results, and the diversity of information made available to the reader.

      "First, we use structural models generated without any use of known structures of the target protein. For machine learning methods, this requires ensuring that no structure of the target protein was used to train the method." This is done by limiting the scope of the work to GPCRs whose structures became available only after the training date of AlphaFold (April 30, 2018), as well as not using templates available after that date during prediction. The use of a time limit seems less preferable than the approach taken in Ref. 1 of discarding templates above a sequence identity cutoff. On the other hand, the 'ablation test' performed in Ref. 2 showed no loss in accuracy when no templates were used at all. Authors should discuss in more detail whether these modeling choices could change anything in their conclusions and why they made their choices compared to those in previous work.

      "Second, we perform a systematic comparison that takes into account the variation between experimentally determined structures of the same protein when bound to different ligands." Cross-docking is indeed a more appropriate comparison than self-docking (as done in previous works), and the observation that the accuracy of AF models is similar to that between different holo structures of the same protein is interesting. Previous literature on cross-docking should however be discussed, and the well-known conclusions from it that small variations in side-chain positions, in otherwise highly similar structures, can lead to large changes in docked poses. It is important to realize that AlphaFold models are 'just another structure' - if previous literature is sufficient to show the sensitivity of rigid docking, doing it again on AF structures does not add to our understanding. Further, Ref. 3 might have already addressed the question of correlation between binding site RMSD and docking pose prediction accuracy - see e.g. Supplementary Figure 3 there (also Figure S15 in Ref. 2).

      Further, the authors should discuss the commonly brought up problem of AlphaFold generating 'more apo-like structures' - are the models used here actually 'holo-like' because of the low RMSDs? (what RMSD differences are to be expected between apo and holo structures of these systems?) How are the volumes of the pockets affected? The position on this problem taken by previous works is worth mentioning - "much higher rmsd values are found when using the AF2 models (...), which reflect the difficulties in performing docking into apo-like structures" in Ref. 1 and "computational model structures were predicted without consideration of binding ligands and resulted in apo structures" in Ref. 2.

      Because of this 'apo problem', Ref. 2 assumed that rigid docking (as done here) would not succeed and used flexible docking where "two sidechains at the binding site were set to be flexible". In fact, the reader of this new paper will be left to wonder if it is not simply presenting a subset of the results already seen in Ref. 2, where "the success ratios dropped significantly for them because misoriented sidechains prevented a ligand from docking (Figure S14)". While this conclusion is not made as clear in Ref. 2 as it is here, a comparison of Figures 4 and S14 there will lead the reader to the same conclusion, and more -- that flexible docking meaningfully improves the performance of AF models, and more so than homology models.

      Finally, certain data analyses present in previous works but not here should be necessary to make this work more informative to the readers:<br /> a) Consideration of multiple top poses, e.g., in Ref. 2, Figures 4 and S14 mentioned before, comparison of success rates in top 1 and top 3 docked poses add much context.<br /> b) Notes on the structural features preventing successful docking, see e.g., in Ref. 1, Table 2 or in Ref. 4, Tables 2 and 4.

      This work has the potential to become an important piece of the puzzle, if deeper insights into the reasons for AF model failures are drawn by the authors. These could include a discussion of the problematic structural elements (clashes of side chain with ligands, missing interactions/waters, etc.), potential solutions with some preliminary data (flexible docking, softening interactions, etc.), or proposals for metrics better than RMSD to score the soundness of pockets generated by AF for docking.

      References:<br /> 1. Díaz-Rovira, A. M., Martín, H., Beuming, T., Díaz, L., Guallar, V., & Ray, S. S. (2023). Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures. Journal of Chemical Information and Modeling, 63(6), 1668-1674. https://doi.org/10.1021/acs.jcim.2c01270<br /> 2. Heo, L., & Feig, M. (2022). Multi-state modeling of G-protein coupled receptors at experimental accuracy. Proteins: Structure, Function, and Bioinformatics, 90(11), 1873-1885. https://doi.org/10.1002/prot.26382<br /> 3. Beuming, T., & Sherman, W. (2012). Current assessment of docking into GPCR crystal structures and homology models: Successes, challenges, and guidelines. Journal of Chemical Information and Modeling, 52(12), 3263-3277. https://doi.org/10.1021/ci300411b<br /> 4. Scardino, V., Di Filippo, J. I., & Cavasotto, C. (2022). How good are AlphaFold models for docking-based virtual screening? [Preprint]. Chemistry. https://doi.org/10.26434/chemrxiv-2022-sgj8c

    1. Not only do mapmakers get to choose what data to use (for example, the mapmaker of “American Migrations to 1880” claims he just took a “rough stab” at gathering data), but they can also change how the viewer interprets the data from how they present the information. For instance, by titling the “Invasion of America” map as an invasion instead of something such as “US Land Expansion,” the viewers of the map view the US’s actions in a negative light, whereas expansion would have seemed positive.

      I agree. when it comes to curation you are as responsible for what you leave out as for what you put in. Implicit in the questions we ask are the assumptions we hold. Humanists can subtly frame conversations through the language they use to describe the world. It's important to acknowledge that there is no such thing as a "rough stab" as it is the curator who decides when their piece is complete.

    1. Reviewer #3 (Public Review):

      This work contributes to the literature characterizing early and late waves of transcription and associated chromatin remodeling following neuronal depolarization, here in cultured embryonic striatum. While they find IEG transcription 1h after depolarization, they find chromatin remodeling is slower (opening at the 4h time point). This may be due to chromatin at IEG regulatory regions already being open (in embryonic striatum), although previous work has found remodeling occurring at the 1h time point (in adult dentate gyrus). The authors next show that the chromatin remodeling that occurs at the late (4h) stage is largely in putative regulatory regions of the genome (rather than gene bodies), and is dependent on translation, which validates and extends the prior literature. The authors then transition from genome-wide basic neuroscience to focus on a specific gene of interest, prodynorphin (Pdyn), and a putative enhancer they identify from their chromatin analysis. They target CRISPR-activating and -inhibiting complexes to the putative enhancer and demonstrate that accessibility of this locus is necessary and sufficient for Pdyn transcription. They then show that at least one PDYN enhancer is conserved from rodents to humans, and is only activity-regulated in human GABAergic but not glutamatergic neurons. Finally, the authors generate snATAC-seq and show Pdyn gene and enhancer activity are also cell-type-specific in the rat striatum. The Pdyn work in particular is thorough and novel.

      Strengths:<br /> This work integrates multiple cutting-edge methods (multiple forms of genome-wide sequencing, combining new and published data across species, applying new forms of bioinformatic analysis, and targeted epigenome editing) to repeatedly and convincingly demonstrate these waves of chromatin remodeling and transcription. The figures and visual representations of data in particular set a new standard for the field. Although several findings within this paper are not novel, this paper ties previous findings all together in one place and goes on to show potential relevance for neuropsychiatric disorders beyond basic cellular neuroscience. The conclusions are mostly supported by the data.

      Results and conclusions that would benefit from clarification/extension.<br /> 1. Throughout the paper, the authors emphasize a "temporal decoupling" of transcriptional and chromatin response to depolarization, based on a lack of significant chromatin changes at 1h, despite IEG transcription. However, previous publications show significant chromatin remodeling at 1h (e.g. Su et al., NN 2017 in adult dentate gyrus) or 2h (Kim et al., Nature 2010; Malik et al., NN 2014 in cultured embryonic cortical neurons). The discussion briefly mentions this contrast, but it remains difficult to conclude decisively whether there is temporal decoupling when such decoupling is not found consistently. If one is to make broad conclusions about basic neural chromatin response to depolarization, it would be ideal to know under which conditions there is temporal decoupling, or if this is a region-specific phenomenon.

      2. The UMAP analysis is a novel way to probe transcription factor enrichment, but it's unclear what this is actually showing. The authors sought to ask whether "DARs could be separated based on transcription factor motifs in these regions." However, the motifs present in any genomic stretch are fixed based on genomic sequence, so it seems like this analysis might be asking whether certain motifs are more likely to be physically clustered together in the genome, in activity-regulated regions (rather than certain transcription factors acting in concert, as is implied in discussion). While still potentially interesting, this analysis does not seem to give much additional insight into activity-dependent chromatin remodeling beyond the motif enrichment analysis already performed. Nevertheless, to draw stronger conclusions, it would be necessary to compare clustering to a random set of genomic regions of the same length/size to interpret the clustering here. It would also be useful to know whether the ISL1 motif is also enriched in ubiquitously accessible genomic regions in the striatum (and not just DARs).

      3. The authors identify late-response gene enhancers by 3 criteria. However, only Pdyn was highlighted thereafter. How many putative DARs met these three criteria in striatum? Only Pdyn?

    1. It was after he heard a BBC interview with Marvin Minsky, a founding father of artificial intelligence, who had famously pronounced that the human brain is “just a computer made of meat.” Minsky‘s claims compelled Penrose to write The Emperor‘s New Mind, arguing that human thinking will never be emulated by a machine. The book had the feel of an extended thought experiment on the non-algorithmic nature of consciousness and why it can only be understood in relation to Gödel‘s theorem and quantum physics.↳Minsky, who died last year, represents a striking contrast to Penrose‘s quest to uncover the roots of consciousness. “I can understand exactly how a computer works, although I’m very fuzzy on how the transistors work,” Minsky told me during an interview years ago. Minsky called consciousness a “suitcase word” that lacks the rigor of a scientific concept. “We have to replace it by ‘reflection’ and ‘decisions’ and about a dozen other things,” he said. “So instead of talking about the mystery of consciousness, let‘s talk about the 20 or 30 really important mental processes that are involved. And when you’re all done, somebody says, ‘Well, what about consciousness?’ and you say, ‘Oh, that’s what people wasted their time on in the 20th century.‘ ”↳But the study of consciousness has not gone the way Minsky had hoped. It‘s now a cottage industry in neuroscience labs and a staple of big-think conferences around the world. Hameroff is one of the driving forces behind this current enthusiasm. For years he and Chalmers have run the biennial “Toward a Science of Consciousness” conference that features dozens of speakers, ranging from hardcore scientists to New Age guru Deepak Chopra and lucid dream expert Stephen LaBerge. Hameroff‘s connection to Penrose also goes back decades. He first contacted Penrose after reading The Emperor‘s New Mind, suggesting he might have the missing biological component that would complement Penrose‘s ideas about the physics of consciousness.

      人工智能之父马文·明斯基(Marvin Minsky)曾经提出过一个著名的说法,人类大脑只不过是「一台用肉做的计算机」。

      明斯基这一论断迫使彭罗斯很快写出了《皇帝新脑》,并在书中指出人类的思维永远不可能被机器模仿。这本书给人的感觉就好像跟着作者进行了一次关于意识非算法性质的脑内实验,以及为什么我们只能通过理解哥德尔定理和量子物理学来理解人类的意识。

      已故于 2016 年的明斯基代表着另外一种截然不同观点,与彭罗斯对意识根源的探索形成了鲜明对比。在很多年前的一次采访中,明斯基曾经告诉笔者,「虽然我完全搞不懂晶体管的工作原理,但我能准确地理解计算机的工作原理。」

      明斯基曾经将意识称为一种「皮包词语」,正因为它缺乏科学概念所必需的严谨性。「我们必须要用反思(Reflection)或者决定(Decisions)这样的词来替换意识一词,」明斯基说,「这样一来,与其讨论意识的神秘面纱,我们不如讨论一下意识过程中涉及到的 20 到 30 个重要的心理历程。当你真的完成了所有这些工作后,如果还有人问道,『那什么是意识呢?』你就可以回答说,『那玩意不过是 20 世纪时人类浪费时间的一种方式。』」

      中文译文来自微信公众号「利维坦(liweitan2014)」2020 年的推送「意识无法被计算吗?

    2. Penrose‘s theory promises a deeper level of explanation. He starts with the premise that consciousness is not computational, and it’s beyond anything that neuroscience, biology, or physics can now explain. “We need a major revolution in our understanding of the physical world in order to accommodate consciousness,“ Penrose told me in a recent interview. ”The most likely place, if we‘re not going to go outside physics altogether, is in this big unknown—namely, making sense of quantum mechanics.“↳ Nautilus Members enjoy an ad-free experience. Log in or Join now. He draws on the basic properties of quantum computing, in which bits (qubits) of information can be in multiple states—for instance, in the “on” or “off” position—at the same time. These quantum states exist simultaneously—the “superposition”—before coalescing into a single, almost instantaneous, calculation. Quantum coherence occurs when a huge number of things—say, a whole system of electrons—act together in one quantum state.↳It was Hameroff‘s idea that quantum coherence happens in microtubules, protein structures inside the brain’s neurons. And what are microtubules, you ask? They are tubular structures inside eukaryotic cells (part of the cytoskeleton) that play a role in determining the cell‘s shape, as well as its movements, which includes cell division—separation of chromosomes during mitosis. Hameroff suggests that microtubules are the quantum device that Penrose had been looking for in his theory. In neurons, microtubules help control the strength of synaptic connections, and their tube-like shape might protect them from the surrounding noise of the larger neuron. The microtubules‘ symmetry and lattice structure are of particular interest to Penrose. He believes “this reeks of something quantum mechanical.” ↳Still, you‘d need more than just a continuous flood of random moments of quantum coherence to have any impact on consciousness. The process would need to be structured, or orchestrated, in some way so we can make conscious choices. In the Penrose-Hameroff theory of Orchestrated Objective Reduction, known as Orch-OR, these moments of conscious awareness are orchestrated by the microtubules in our brains, which—they believe—have the capacity to store and process information and memory.↳“Objective Reduction” refers to Penrose‘s ideas about quantum gravity—how superposition applies to different spacetime geometries—which he regards as a still-undiscovered theory in physics. All of this is an impossibly ambitious theory that draws on Penrose’s thinking about the deep structure of the universe, from quantum mechanics to relativity. As Smolin has said, “All Roger‘s thoughts are connected … twistor theory, his philosophical thinking, his ideas about quantum mechanics, his ideas about the brain and the mind.”

      对于意识的本质问题,彭罗斯的理论提出了一种更深层的解读。他的理论基于一个前提假设,即意识无法被计算,而且它绝非神经科学、生物学和物理学现阶段能够解释的问题。

      在 2017 年的一次采访中,彭罗斯告诉笔者,「为了理解并认知意识,我们首先要经历一次对于物理世界的巨大认知变革。至于那个可以研究意识本质的领域,如果我们不打算完全脱离物理学范畴的话,那么该领域最有可能一直存在于那个巨大的谜题中,换句话说,我们首先要解开量子物理的谜题。」

      彭罗斯将量子计算的基本特性吸收到他的理论中,即每一比特的信息,即量子位(Qubit)可以同时表现为多种状态,比如同时既是「激活」的,又是「未激活」的。在一次几乎是瞬间完成的计算之前,这些量子态(Quantum States)并未聚合(Coalescing),而是同时存在的,即叠加态(Ssuperposition)。而量子相干性(Quantum Coherence)只有在大量事件在量子态下同时发生的时候才会出现——比如某系统中的大量电子相互作用。

      对此,哈默洛夫认为量子相干性发生于微管(Microtubule)中,这是一种大脑神经元内部的蛋白质结构。也许读者会好奇所谓微管到底是什么东西:它们是存在于真核细胞中的管状结构,可以把它看成是细胞骨架(Cytoskeleton)的一部分,它们可以在细胞活动时发挥决定性作用,这些细胞活动也包括细胞分裂在内,比如在有丝分裂时决定染色体的分离。

      哈默洛夫认为,这些微管就是彭罗斯一直在为自己理论寻找的一种「量子装置」。在神经元中,微管可以帮助控制突触的连接强度,而它们管状的结构可以帮助它们免受周围更大的神经元带来的噪音影响。这些微管的对称、晶格结构恰恰是彭罗斯最感兴趣的。他相信这样的特征「散发着某种量子物理的气味」。

      不过,想要对意识产生任何影响,你需要的不仅仅是随机且持续发生的量子相干性事件。这个过程首先要经过某种方式重组,或者重新经过精心的编排,人类正是因为这一重组过程才能做出有意识的选择。在彭罗斯与哈默洛夫提出的协同客观崩现(Orchestrated Objective Reduction,简称「Orch-OR」)理论中,他们认为人类大脑中的微管会精密编排、操纵这些有意识的瞬间,而正是这样的瞬间给了人脑处理信息并存储记忆的能力。

      所谓「客观崩现」的概念则要涉及到彭罗斯对量子引力——即叠加态如何应用于不同的多个时空几何结构——方面的观点,他也把该理论视为目前物理学尚未发现的理论。然而所有这一切都是一个不可能被验证的、野心勃勃的假说,这个假说不过是借鉴了彭罗斯在量子力学领域和相对论领域对宇宙深层结构的思考。正如斯莫林说过的另一句话:「罗杰的所有观点都是相互勾连的扭量理论(Twistor Theory),无论是他的哲学思想、那些关于量子力学的观点,还是关于人类大脑与心灵的观点。」

      中文译文来自微信公众号「利维坦(liweitan2014)」2020 年的推送「意识无法被计算吗?

    1. Metrics shape behavior, so by adding and valuing just two metrics, you've helped shape a change in your team and organization. This is why it's so important to be sure to pull from multiple dimensions of the framework: it will lead to much better outcomes at both the team and system levels.

      Probably the best statement here - but, the assumption that metrics lead to better outcomes may be false.

    1. Our goal is not to argue about proper nouns

      And yet you are arguing (instead of just fixing your mistake). Why?

      You even went out of your way to change the post: it used to say "Codecov is now Open Source"[1]. In the time since, you have changed it so "Code is Now Open Source"[2].

      This is notable for two reasons: it means that it's not outside the bounds of reasonableness to ask why the post hasn't changed since you've been confronted about the discontent, but it also raises questions about why you made that particular change in the first place. By a reasonable guess, I'd bet it has something to do with the fact that writing it as "Open Source" (rather than merely "open source") does real damage to any argument that the latter is generic and doesn't have any particular significance, thus allowing you to repudiate the OSI and the OSD. Which, of course, means that you guys are total fuckin' slimeballs, since you are now actively taking steps to cover your tracks.

      1. https://archive.is/aSH9K

      2. https://archive.is/pyd5b

    1. Why is the index card half full?

      reply to u/ManuelRodriguez331 at https://www.reddit.com/r/Zettelkasten/comments/15ehcy5/why_is_the_index_card_half_full/

      There has been debate about the length of notes on slips since the invention of slips and it shows no signs of coming to broad consensus other than everyone will have their personal opinion.

      If you feel that A6 is is too big then go down a step in size to A7. One of the benefits of the DIN A standard is that you can take the next larger card size and fold it exactly in half to have the next size smaller. This makes it easier to scale up the size of your cards if you prefer most of them to be smaller to save space, just take care not to allow larger folded cards to "taco" smaller cards in a way they're likely to get lost. If you really needed more space, you could easily use an A1 or A2 and fold it down to fit inside of your collection! (Sadly 4x6 and 3x5 cards don't have this affordance.)

      Fortunately there are a variety of available sizes, so you can choose what works best for yourself. Historically some chose large 5x8", 6x9", or even larger "slips". Some have also used different sizes for different functions. For example some use 3x5 for bibliographic cards and 4x6 for day-to-day ideas. I've seen stacked wooden card catalog furniture that had space for 3x5, 4x6, and 8.5x11 in separate drawers within the same cabinet. Some manufacturers even made their furniture modular to make this sort of mixed use even easier.

      One of the broadly used pieces of advice that does go back centuries is to use "cards of the same size" (within a particular use case). This consensus is arrived at to help users from losing smaller cards between larger/taller cards. Cards of varying sizes, even small ones, are also much more difficult to sort through. Slight of hand magicians will be aware of the fact that shaving small fractions of length off of playing cards is an easy way of not only marking them, but of executing a variety of clever shuffling illusions as well as finding some of them very quickly by feel behind the back. Analog zettelkasten users will only discover that smaller, shorter cards are nearly guaranteed to become lost among the taller cards. It's for this reason that I would never recommend one to mix 4x6, A6, or even the very closely cut Exacompta Bristol cards, which are neither 4x6 nor A6!

      I once took digital notes and printed them on paper and then cut them up to fit the size of the individual notes to save on space and paper. I can report that doing this was a painfully miserable experience and positively would NOT recommend doing this for smaller projects much less lifelong ones. Perhaps this could be the sort of chaos someone out there might actually manage to thrive within, but I suspect it would be a very rare individual.

      As for digital spacing, you may win out a bit here for "saving" paper space, but you're also still spending on storage costs in electronic formatting which historically doesn't have the longevity of physical formats. Digital also doesn't offer the ease of use of laying cards out on a desktop and very quickly reordering them for subsequent uses.

      There are always tradeoffs, one just need be aware of them to guide choices for either how they want to work or how they might work best.

      Personally, I use 4x6" cards because I often write longer paragraphs on them. Through experimentation I found that I would end up using two or more 3x5 cards more often than I would have had mostly blank 4x6 cards and used that to help drive my choice. I also find myself revisiting old cards and adding to them (short follow ups, links to other cards, or other metadata) and 3x5 wouldn't allow that as easily.

      As ever, YMMV...

      See also: [[note lengths]] and/or [[note size]].

    1. Does anyone has it’s Zettelkasten in Google Docs, Microsoft Word or Plain Tex (without a hood app like obsidian or The Archive)? .t3_15fjb97._2FCtq-QzlfuN-SwVMUZMM3 { --postTitle-VisitedLinkColor: #9b9b9b; --postTitleLink-VisitedLinkColor: #9b9b9b; --postBodyLink-VisitedLinkColor: #989898; }

      reply to u/Efficient_Earth_8773 at https://www.reddit.com/r/Zettelkasten/comments/15fjb97/does_anyone_has_its_zettelkasten_in_google_docs/

      Experimenting can be interesting. I've tried using spreadsheet software like Google Sheets or Excel which can be simple and useful methods that don't lose significant functionality. I did separate sheets for zettels, sources, and the index. Each zettel had it's own row with with a number, title, contents, and a link to a source as well as the index.

      Google Docs might be reasonably doable, but the linking portion may be one of the more difficult affordances to accomplish easily or in a very user-centric fashion. It is doable though: https://support.google.com/docs/answer/45893?hl=en&co=GENIE.Platform%3DDesktop, and one might even mix Google Docs with Google Sheets? I could see Sheets being useful for creating an index and or sources while Docs could be used for individual notes as well. It's all about affordances and ease of use. Text is a major portion of having and maintaining a zettelkasten, so by this logic anything that will allow that could potentially be used as a zettelkasten. However, it helps to think about how one will use it in practice on a day-to-day basis. How hard will it be to create links? Search it? How hard will it be when you've got thousands of "slips"? How much time will these things take as it scales up in size?

      A paper-based example: One of the reasons that many pen and paper users only write on one side of their index cards is that it saves the time of needing to take cards out and check if they do or don't have writing on the back or remembering where something is when it was written on the back of a card. It's a lot easier to tip through your collection if they're written only on the front. If you use an alternate application/software what will all these daily functions look like compounded over time? Does the software make things simpler and easier or will it make them be more difficult or take more time? And is that difficulty and time useful or not to your particular practice? Historian and author David McCullough prefers a manual typewriter over computers with keyboards specifically because it forces him to slow down and take his time. Another affordance to consider is how much or little work one may need to put into using it from a linking (or not) perspective. Using paper forces one to create a minimum of at least one link (made by the simple fact of filing it next to another) while other methods like Obsidian allow you to too easily take notes and place them into an infinitely growing pile of orphaned notes. Is it then more work to create discrete links later when you've lost the context and threads of potential arguments you might make? Will your specific method help you to regularly review through old notes? How hard will it be to mix things up for creativity's sake? How easy/difficult will it be to use your notes for writing/creating new material, if you intend to use it for that?

      Think about how and why you'd want to use it and which affordances you really want/need. Then the only way to tell is to try it out for a bit and see how one likes/doesn't like a particular method and whether or not it helps to motivate you in your work. If you don't like the look of an application and it makes you not want to use it regularly, that obviously is a deal breaker. One might also think about how difficult/easy import/export might be if they intend to hop from one application to another. Finally, switching applications every few months can be self-defeating, so beware of this potential downfall as you make what will eventually need to be your ultimate choice. Beware of shiny object syndrome or software that ceases updating in just a few years without easy export.

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      We thank the three reviewers for carefully reading our manuscript and for all considerations, ideas, suggestions, and comments. These were all very helpful for us to strengthen the scientific statements of our manuscript. Please, note that all changes are marked in red in the manuscript and supplement. Below you will find, point by point, our responses to all questions and comments.

      Reviewer #1 (Evidence, reproducibility and clarity):

      Overall, this is an exciting work. There are, however, several open questions that the authors could address to facilitate understanding of their work. These points are:

      1.) On page 5, lines 113ff, the authors mention the membrane bulges that they analyse in figure 1. They show these deformations by light (confocal) and electron microscopy. However, the bulges seen by confocal microscopy seem to be bigger that those seen by electron microscopy. The authors could quantify the sizes of the bulges for clarification.

      We quantified the size of the membrane bulges. At the confocal we measured in average 750nm as mean value of identified bulges (n=12) with 650nm as minimal and 890nm as maximal sizes. At the TEM we measure ~243nm as mean value (n=61), with a range between 62nm as minimum and 442 as maximum value. These measurements are shown as Figure 1E.

      Please note that measurements of TEM images do not always capture the three-dimensionality of bulges and may show only parts of them. In addition, ultrastructure is more sensitive and can easily detect small membrane changes that we cannot observe with confocal and airsycan microscopy. In contrast, even with our high-quality objective (63x Zeiss Plan Neofluar, Glycerin, 1.3 NA), standard confocal analysis is limited at ~200nm on the XY axis (airyscan ~110nm) and ~450nm on Z-axis. Therefore, TEM analysis detects smaller bulges than confocal analysis, and consequently, this method detected a large range of bulge lengths between 63nm and 441nm. In contrast, the airyscan method detected a range of bulge length between 0.65 and 0.83 µm. However, confocal and TEM analyses provide evidence of membrane bulges in pio mutant embryos. Please note that we extended our studies and now show membrane bulges in two different pio mutant alleles (17C and 5M) with airsycan microscopy.

      2.) The subject of the manuscript is rather complicated; presentation of data from Figure 1C and D on lines 113ff and 169ff is confusing.

      We apologize and thank the reviewer for careful reading. We revised both paragraphs (lines 108 – 123 and lines 166 - 174) and are confident that the descriptions are now much more understandable. All changes are marked in red.

      3.) The quality of the sub-images of Figure 2E differs. Especially, the phenotype of the wurst, pio transheterozygous embryo is not well visible.

      We apologize for it. We repeated the experiment with wurst;pio transheterozygotes, and generated wurst;pio double mutant embryos to improve the quality. The gas filling assay is shown in Fig. 3. With brightfield microscopy in overview images (10x air objective) and close-ups of the dorsal trunks (25x Glycerin objectives). Both show the gas-filling defects of dorsal trunk tubes. In a subsequent confocal analysis of chitin stainings in late-stage 17 embryos, we found that tracheal tube lumens are collapsed in the transheterozygotes and double mutant embryos.

      4.) Lines 246ff: the protein size are given for the mCherry:chimeric proteins; an estimate of the native Pio portions should be given.

      The endogenous Pio protein has a calculated mass of about 50.82 kDa. We state it now in the according legend of Fig. 6.

      5.) In Figure 6A, the appearance of chitin in the wildtype tube is different compared to the Np mutant situation, more filamentous. Can the authors comment on that?

      The author is correct. The chitin cable formation in Np mutant embryos is normal but lacks the condensation process, and, therefore, fiber structure of the chitin matrix differs from control embryos in late stage 16 and stage 17 embryos (see Drees et al., PLOS Genetics, 2019).

      6.) In the discussion section, I would appreciate if the timing of events was discussed or even shown in a model. The central question is: how are the functions of Pio and Np coordinated in time? As I understand, Np should not cleave Pio before morphogenesis is completed. Is there any example in the literature for how such an interaction could be controlled? The overexpression of Np shows that either the ratio between Np and Pio is important, or the btl promoter expresses Np at the "wrong" time point.

      We thank the reviewer for this interesting comment.

      Of course, we did not measure forces, but it has been published that axial forces appear at the apical cell membrane during stage 16 tube expansion. Our data show that Np cleaves Pio ZP domain and subsequent release increase during stage 16. The cleaved and released Pio enriches in the lumen during stage 16, from where cleaved Pio is internalized during stage 17 with the help of Wurst-mediated endocytosis. This is supported by several in vivo studies, video microscopy, antibody stainings and biochemical data, such as the interaction of Pio and Dumpy as well as the identification of different Pio products with and without Np cleavage. Moreover, we found membrane bulges that increase in size during stage 16 and identified a subsequent tear-off of the chitin matrix in Np mutant embryos. Thus, we propose that Np is required to cleave Pio-Dumpy linkages at the membrane-matrix when tubes elongate and postulated forces appear at the cell membrane during tube elongation in stage 16 embryos.

      We stated this in the discussion as follows:

      “The membrane defects observed in both Pio and Np mutants indicate errors in the coupling of the membrane matrix due to the involvement of Pio (Figs. 1,7). ..., the large membrane bulges in Np mutants affect the membrane and the apical matrix (Fig. 7). Since apical Pio is not cleaved in Np mutants (Fig. 7D), the matrix is not uncoupled from the membrane as in pio mutant embryos but is likely more intensely coupled, which leads to tearing of the matrix axially along the membrane bulges (Figs. 7, 9), when the tube expands in length.”

      How could Np be regulated at the membrane? Np is a zymogen that very likely undergoes ectodomain shedding for activation, similar to what has been described for matriptases. Additionally, human matriptase requires transient interaction of the stem region with its cognate inhibitor HAI-2, which Drosophila lacks (see Drees et al., PLOS Gen, 2019). Thus, the regulation of Np activation is not known.

      Further, we observed that Dumpy is not degraded in Np mutant embryos during stage 17. Nevertheless, in a previous publication, we showed that btl-G4 driven Np expression rescues Np mutant phenotypes in a time-specific manner. We used the btl-G4 driver line for these rescue experiments to express Np in tracheal cells. This restored tracheal Dumpy degradation in Np mutant embryos. Thus, btlG-G4 driven Np overexpression is able to rescue Np mutant tracheal phenotypes in a time-specific manner, although Gal4 is expressed from early tracheal development onwards. Further, btl-Gal4 driven Np expression mimics the endogenous Np, which is expressed from stage 11 onwards in all tracheal cells throughout embryogenesis (see Drees et al., PLOS Gen, 2019).

      Based on these experiments, we conclude that the btl-G4-driven Np overexpression can cleave Pio ZP domain in stage 16 embryos at the correct time.

      However, the ratio of Np expression and Pio is essential in the way that btl-Gal4 driven Gal4 Np overexpression may cause cleavage of a higher number of Pio proteins and the release of critical Pio-Dumpy linkages at the cell membrane and matrix. Thus, increased Pio shedding into the lumen reduces Pio linkages at the membrane, resulting in a pio mutant like tracheal overexpansion in btl-Gal4 driven Gal4 Np overexpression.

      Finally, we were able to prove the reviewer’s question in a new experiment. We used btl-Gal4 driven UAS-Np embryos for Pio antibody staining. This revealed Pio enrichment at the tracheal chitin cable in stage 14 and 15 embryos. In contrast, stage 16 embryos showed numerous Pio puncta appearing across the entire tube lumen, indicating that Np mediates Pio shedding specifically in stage 16 embryos and not before. This Np-controlled Pio releases modifies tube length control.

      Therefore, we stated this in the manuscript as follows:

      Results:

      “Our data assumes that Np overexpression may enhance Pio shedding in stage 16 embryos, affecting the Pio-mediated ZP matrix function. Upon breathless (btl)-Gal4-mediated expression of UAS-Np in tracheal cells, we observed a high amount of Pio puncta across the entire tracheal tube lumen, specifically in stage 16 embryos but not in earlier stages (Fig. S13). Consistently tracheal Np overexpression led to tube overexpansion in stage 16 embryos resembling the pio mutant phenotype (Fig. 8A,B). Thus, Np-mediated Pio shedding controls Pio function.”

      Discussion:

      “The btl-Gal4-driven Np expression mimics the endogenous Np from stage 11 onwards in all tracheal cells throughout embryogenesis (Drees et al., 2019), suggesting that Np is not expressed at a wrong time point. However, the ratio between Np and Pio is essential. We assume that Np overexpression increases Pio shedding, resulting in a pio loss-of-function phenotype. Thus, the tube length overexpansion upon Np overexpression indicates that Pio cleavage is required for tube length control.

      Our observation that the membrane deformations are maintained in Np mutant embryos supports our postulated Np function to redistribute and deregulate membrane-matrix associations in stage 16 embryos when tracheal tube length expands. In contrast, Np overexpression potentially uncouples the Pio-Dpy ZP matrix membrane linkages resulting very likely in unbalanced forces causing sinusoidal tubes.”

      7.) Also for the discussion: We have two situations where Pio amounts/density are enhanced at the apical plasma membrane. The wurst experiments on lines 136ff show that Pio amount and density depends on endocytosis; is the wurst phenotype (Figure 2), at least partially, due to over-presentation of Pio? Likewise, in Figure 2C, there is more Pio in Cht2 overexpressing tracheae (but there is overall more Pio in these tracheae) - is actually endocytosis reduced in chitin-less luminal matrices? First: does the Pio signal at the apical plasma membrane correspond to membrane-Pio or free-Pio? Second, as in the case of wurst: would more Pio on the membrane (density) affect tracheal dimensions in Cht2 over expressing tracheae? Or are the consequences of Pio accumulation in the apical plasma membrane different in Cht2 and wurst backgrounds? Maybe cleavage of Pio and its endocytosis are dependent on its interaction with the chitin matrix. These questions connect to the question immediately above: how are the functions of the different players coordinated in space and time? We need a discussion on this issue.

      We thank the reviewer for this very important idea to discuss the functions of the different players in a coordinated space and time and apologize that we haven’t done before.

      As this is an important point, we tried to figure out all questions raised by the reviewer and discussed it in several new paragraphs in the discussion:

      "Indeed, the anti-Pio antibody, which can detect all different Pio variants, showed a punctuate Pio pattern overlapping with the apical cell membrane marker Uif at the dorsal trunk cells of stage 16 embryos. Additionally, Pio antibody also revealed early tracheal expression from embryonic stage 11 onwards, and due to Pio function in narrow dorsal and ventral branches, strong luminal Pio staining is detectable from early stage 14 until stage 17, when airway protein clearance removes luminal contents.

      We generated mCherry::Pio as a tool for in vivo Pio expression and localization pattern analysis during tube lumen length expansion. The mCherry::Pio resembled the Pio antibody expression pattern from early tracheal development onwards. However, luminal mCherry::Pio enrichment occurs specifically during stage 16, when tubes expand. The stage 16 embryos showed mCherry::Pio puncta accumulating apically in dorsal trunk cells. Moreover, mCherry::Pio puncta partially overlapped with Dpy::YFP and chitin at the taenidial folds, forming at apical cell membranes. Supported by several observations, such as antibody staining, Video monitoring, FRAP experiments, and Western Blot studies (Figs. 4,5), these findings indicate that Pio may play a significant role at the apical cell membrane and matrix in dorsal trunk cells of stage 16 embryos.

      Furthermore, we show that Np-mediates Pio ZP domain cleavage for luminal release of the short Pio variant during ongoing tube length expansion. The luminal cleaved mCherry::Pio is enriched at the end of stage 16 and finally internalized by the subsequent airway clearance process during stage 17 after tube length expansion. Such rapid luminal Pio internalization is consistent with a sharp pulse of endocytosis rapidly internalizing the luminal contents during stage 17 (Tsarouhas et al., 2007). Wurst is required to mediate the internalization of proteins in the airways (Behr et al., 2007; Stümpges and Behr, 2011). In consistence, during stage 17, luminal Pio antibody staining fades in control embryos but not in Wurst deficient embryos.

      Nevertheless, Pio and its endocytosis depend on its interaction with the chitin matrix and the Np-mediated cleavage. In stage 16 wurst and mega mutant embryos, we detect Pio antibody staining at the chitin cable, suggesting that Pio is cleaved and released into the dorsal trunk tube lumen. Also, the Cht2 overexpression did not prevent the luminal release of Pio. However, reduced wurst, mega function, and Cht2 overexpression caused an enrichment of punctuate Pio staining at the apical cell membrane and matrix (Figs. 1,2). Although the three proteins are involved in different subcellular requirements, they all contribute to the determination of tube size by affecting either the apical cell membrane or the formation of a well-structured apical extracellular chitin matrix, indicating that changes at the apical cell membrane and matrix in stage 16 embryos affect the Pio pattern at the membrane. It also shows that local Pio linkages at the cell membrane and matrix are still cleaved by the Np function for luminal Pio release, which explains why those mutant embryos do not show pio mutant-like membrane deformations and Np-mutant-like bulges. This is in line with our observations that tracheal Pio overexpression cannot cause tube size defects as the Np function is sufficient to organize local Pio linkages at the membrane and matrix. Therefore, it is unlikely that tracheal tube length defects in wurst and mega mutants as well as in Cht2 misexpression embryos are caused the apical Pio density enrichment.

      Nevertheless, oversized tube length due to the misregulation of the apical cell membrane and adjacent chitin matrix may cause changes to local Pio set linkages and the need for Np-mediated cleavage. Strikingly, we observe a lack of Pio release in Np mutants. This shows that Pio density at the membrane versus lumen depends predominantly on Np function. The molecular mechanisms that coordinate the Np-mediated Pio cleavage are unknown and will be necessary for understanding how tubes resist forces that impact cell membranes and matrices. On the other hand, Pio is required for the extracellular secretion of its interaction partner Dpy. At the same time, Dpy is needed for Pio localization at the cell membrane and its distribution into the tube lumen. Consistently, in vivo, mCherry::Pio and Dpy::eYFP localization patterns overlap at the apical cell surface and within the tube lumen. These observations support our model that Pio and Dpy interact at the cell surface where Np-mediates Pio cleavage to support luminal Pio release by the large and stretchable matrix protein Dpy (Fig. 9).

      Taenidial organization prevents the collapse of the tracheal tube. Therefore, cortical (apical) actin organizes into parallel-running bundles that proceed to the onset of cuticle secretion and correspond precisely to the cuticle's taenidial folds (Matusek et al., 2006; Öztürk-Çolak et al., 2016). Mutant larvae of the F-actin nucleator formin DAAM show mosaic taenidial fold patterns, indicating a failure of alignment with each other and along the tracheal tubes (Matusek et al., 2006). In contrast, pio mutant dorsal tracheal trunks contained increased ring spacing (Fig. 3A). Fusion cells are narrow doughnut-shaped cells where actin accumulates into a spotted pattern. Formins, such as Diaphanous, are essential in organizing the actin cytoskeleton. However, we do not observe dorsal trunk tube fusion defects as found in the presence of the activated diaphanous.

      On the other hand, ectopic expression of DAAM in fusion cells induces changes in apical actin organization but does not cause any phenotypic effects (Matusek et al., 2006). DAAM is associated with the tyrosine kinase Src42A (Nelson et al., 2012), which orients membrane growth in the axial tube dimension (Förster and Luschnig, 2012). The Src42 overexpression elongates tracheal tubes due to flattened axially elongated dorsal trunk cells and AJ remodeling. Although flattened cells and tube overexpansion are similar in pio mutant embryos, we did not observe a mislocalization of AJ components, as found upon constitutive Src42 activation (Förster and Luschnig, 2012). Instead, we detected an unusual stretched appearance of AJs at the fusion cells of pio mutant dorsal trunks, which to our knowledge, has not been observed before and may play a role in regulating axial taenidial fold spacing and tube elongation.

      Self-organizing physical principles govern the regular spacing pattern of the tracheal taenidial folds (Hannezo et al., 2015). The actomyosin cortex and increased actin activity before and turnover at stage 16 drive the regular pattern formation. However, the cell cortex and actomyosin are in frictional contact with a rigid apical ECM. The Src42A mutant embryos contain shortened tube length but increased taenidial fold period pattern due to decreased friction. In contrast, the chitinase synthase mutant kkv1 has tube dilation defects and no regular but an aberrant pearling pattern caused by zero fiction (Hannezo et al., 2015).

      In contrast, pio mutant embryos do not contain tube dilation defects or shortened tubes but increased tube length (Figs. 1; 8; S1). Furthermore, our cbp and antibody stainings reveal the presence of a luminal chitin cable and a solid aECM structure in pio mutant stage 16 embryos (Figs. 8, S1; S6). In addition, apical actin enrichment in tracheal cells of pio mutant embryos appeared wt-like. Nonetheless, pio mutant embryos show an increased taenidial fold period compared with wt, indicating a decreased friction. Thus, we propose that the lack of Pio reduces friction. Reasons might be subtle defects of actomyosin constriction or chitin matrix, which we have not detected in the pio mutant tracheal cells. Further reasons for lower friction might be the loss of Pio set local linkages between apical cortex and aECM in stage 16 embryos, which are modified by Np, as proposed in our model (Fig. 9).

      Heterozygous and homozygous pio mutant embryos generally do not show tubal collapse. However, the loss of Pio and accompanying lack of Dpy secretion in stage 17 pio mutant embryos led to the loss of a Pio/Dpy matrix, impacting the late embryonic maturation and differentiation of a normal chitin matrix at the apical cell surface. TEM images reveal reduced dense chitin matrix material at taenidial folds and misarranged taenidial fold pattern (Figs. 1; S2), suggesting impaired taenidial function prevents tube lumen from collapsing after tube protein clearance. Wurst knockdown and mutant embryos do not show general tube collapse, but luminal chitin fiber organization is disturbed in stage 17 embryos (Behr et al., 2007). Therefore, transheterozygous wurst;pio mutant embryos may combine both defects and suffer from maturation deficits of the chitin/ZP matrix at the apical cell surface and within the tube lumen, which finally causes a high number of embryos with incomplete gas filling due to tube collapse. These maturation deficits are even more dramatic in the wurst;pio double mutants, which show no gas filling.”

      8.) The sentence on line 242ff should be rephrased: "dynamic" and "elastic" are not opposites.

      We thank the reviewer for careful reading. We revised the sentence as follow:

      “Our FRAP data suggest that Pio is the dynamic part of the tracheal ZP-matrix, while the static Dpy modulates mechanical tension within the matrix”

      9.) A central question to me is the amounts and the density of factors in different genetic backgrounds as mentioned above. Is there any mechanism adjusting the amounts or the density of the players according to the size of the apical plasma membrane or the tracheal lumen? Pio seemingly responds to these changes.

      We would like to know the molecular mechanisms that control the density of players at the apical membrane. This question is important and could be the starting point for novel scientific investigations. Mechanisms of protein trafficking, such as exocytosis, recycling and endocytosis regulate delivery and internalization of proteins at the apical cell membrane. Furthermore, protein junctions at the lateral membrane may recognize and therefore may respond to low and high mechanical stresses between cells that appear during tube length expansion. However, we did not observe any hint for misregulation of Pio expression levels in the different mutants which affect endocytosis, SJs and luminal ECM. But we observed a shift of Pio levels between apical cell membrane/matrix and lumen in wurst, mega mutants and Cht2 overexpression. This shift is analyzed with diverse ZEN tools and quantified (Fig. 2D-F; Fig. S4B). As discussed in the new paragraph, this shift is very likely caused by changes at the apical cell membrane and chitin matrix which impact Pio shedding. Moreover, we observe the lack of Pio release in Np mutants. This shows that Pio density at the membrane versus lumen depends predominantly on Np-mediated cleavage. As discussed above, how Np is activated at the apical cell membrane to cleave Pio is not known.

      10.) The connection of Pio and taenidia is mentioned in the results section (page 7) but not discussed.

      We appreciate the careful reading and comments of the reviewer very much. We included the connection of Pio and taenidial in the discussion section as follows:

      “Taenidial organization prevents the collapse of the tracheal tube. Therefore, cortical (apical) actin organizes into parallel-running bundles that proceed to the onset of cuticle secretion and correspond precisely to the cuticle's taenidial folds (Matusek et al., 2006; Öztürk-Çolak et al., 2016). Mutant larvae of the F-actin nucleator formin DAAM show mosaic taenidial fold patterns, indicating a failure of alignment with each other and along the tracheal tubes (Matusek et al., 2006). In contrast, pio mutant dorsal tracheal trunks contained increased ring spacing (Fig. 3A). Fusion cells are narrow doughnut-shaped cells where actin accumulates into a spotted pattern. Formins, such as Diaphanous, are essential in organizing the actin cytoskeleton. However, we do not observe dorsal trunk tube fusion defects as found in the presence of the activated diaphanous.

      On the other hand, ectopic expression of DAAM in fusion cells induces changes in apical actin organization but does not cause any phenotypic effects (Matusek et al., 2006). DAAM is associated with the tyrosine kinase Src42A (Nelson et al., 2012), which orients membrane growth in the axial tube dimension (Förster and Luschnig, 2012). The Src42 overexpression elongates tracheal tubes due to flattened axially elongated dorsal trunk cells and AJ remodeling. Although flattened cells and tube overexpansion are similar in pio mutant embryos, we did not observe a mislocalization of AJ components, as found upon constitutive Src42 activation (Förster and Luschnig, 2012). Instead, we detected an unusual stretched appearance of AJs at the fusion cells of pio mutant dorsal trunks, which to our knowledge, has not been observed before and may play a role in regulating axial taenidial fold spacing and tube elongation.

      Self-organizing physical principles govern the regular spacing pattern of the tracheal taenidial folds (Hannezo et al., 2015). The actomyosin cortex and increased actin activity before and turnover at stage 16 drive the regular pattern formation. However, the cell cortex and actomyosin are in frictional contact with a rigid apical ECM. The Src42A mutant embryos contain shortened tube length but increased taenidial fold period pattern due to decreased friction. In contrast, the chitinase synthase mutant kkv1 has tube dilation defects and no regular but an aberrant pearling pattern caused by zero fiction (Hannezo et al., 2015).

      In contrast, pio mutant embryos do not contain tube dilation defects or shortened tubes but increased tube length (Figs. 1; 8; S1). Furthermore, our cbp and antibody stainings reveal the presence of a luminal chitin cable and a solid aECM structure in pio mutant stage 16 embryos (Figs. 8, S1; S6). In addition, apical actin enrichment in tracheal cells of pio mutant embryos appeared wt-like. Nonetheless, pio mutant embryos show an increased taenidial fold period compared with wt, indicating a decreased friction. Thus, we propose that the lack of Pio reduces friction. Reasons might be subtle defects of actomyosin constriction or chitin matrix, which we have not detected in the pio mutant tracheal cells. Further reasons for lower friction might also be the loss of Pio set local linkages between apical cortex and aECM in stage 16 embryos, which are modified by Np, as proposed in our model (Fig. 9).

      Heterozygous and homozygous pio mutant embryos generally do not show tubal collapse. However, the loss of Pio and accompanying lack of Dpy secretion in stage 17 pio mutant embryos led to the loss of a Pio/Dpy matrix, impacting the late embryonic maturation and differentiation of a normal chitin matrix at the apical cell surface. TEM images reveal reduced dense chitin matrix material at taenidial folds and misarranged taenidial fold pattern (Figs. 1; S2), suggesting impaired taenidial function prevents tube lumen from collapsing after tube protein clearance. Wurst knockdown and mutant embryos do not show general tube collapse, but luminal chitin fiber organization is disturbed in stage 17 embryos (Behr et al., 2007). Therefore, transheterozygous wurst;pio mutant embryos may combine both defects and suffer from maturation deficits of the chitin/ZP matrix at the apical cell surface and within the tube lumen, which finally causes a high number of embryos with incomplete gas filling due to tube collapse. These maturation deficits are even more dramatic in the wurst;pio double mutants, which show no gas filling.”

      11.) Dp remains cytoplasmic in pio mutant background - is the pio mutant phenotype due to defects by lack of Pio AND Dp function? What is the tracheal phenotype of dp mutants?

      It has been discussed that dumpyolvr and pio mutants show similar phenotypes in early tracheal development (Jazwinska, 2003) and it has been discussed that dumpyolvr mutant embryos compromise tube size in combination with shrub mutants. The additional quantifications of the dumpyolvr mutant showed significantly increased tube length (Dong 2014). We used dumpyolvr mutant [In(2L)dpyolvr], an X-ray induced mutation of the dumpy gene locus (Wilkin 2000). dumpyolvr mutant resemble pio null mutant tracheal phenotypes including detached dorsal and ventral branches and oversized tracheal dorsal trunk with curly appearance in late embryos. We included chitin and Uif staining’s of stage 16 dumpy mutant embryos (Fig. S10).

      This data suggest that Pio mutant phenotype is due to a lack of Pio and Dumpy, which would support our model, of Pio and Dumpy protein interaction in the extracellular space of the tube lumen.

      In wt embryos Pio is predominantly in the luminal chitin cable, in contrast in dumpy mutant embryos most Pio is predominantly not at the luminal chitin cable. Less luminal Pio staining in dumpy mutant embryos but Pio accumulation apically shows that Dumpy is required for luminal Pio release in stage 16 embryos. This supports our model that Pio and Dumpy interaction may link membrane and matrix and that this link reacts on mechanical stress during tube expansion by Np-mediated cleavage of Pio and its accompanied luminal release due to linked Dumpy.

      12.) Lines 374ff: the reduced dorsal trunk in Np mutants is not significant; the respective statement should be formulated carefully. If we believe the statistics (no significance), this would mean that attachment of the apical plasma membrane to the luminal chitin via Pio is needed to restrict axial extension; release of Pio is needed for differentiation (taenidia formation, luminal clearance) beyond morphogenesis.

      We agree with the reviewer that the reduction of the dorsal trunks in Np mutant is statistically not significant. However, the mean value is clearly below that of WT. Therefore, we revised our statement as follow: “In Np mutant embryos, tracheal dorsal trunk length shows the tends to be reduced compared to wt embryos.” Further, the btlG4-driven UAS-Np overexpression of Np suggests strong Pio release from the apical membrane and therefore resembles the pio mutant tube length overexpansion (Fig. 8A,B; Fig S13). Thus, our current observations indicate that Np-mediated Pio release at the cell membrane enables precise tube length elongation.

      We thank the referee for discussing that Pio is needed for taenidial fold formation which would fit to our findings in pio null mutant embryos. Pio mutant embryos show the appearance of taenidial folds in stage 16 embryos (airyscan) and stage 17 embryos (TEM images). However, TEM images also show chitin matrix reduction in pio mutant stage 17 embryos. Further, co-stainings of Pio with Crb and Uif, as well as co-stainings of mCherry::Pio with Dpy-GFP and cbp confirms that the Pio localize at the apical cell membrane where taenidial folds form in late stage 16 embryos. Thus, our observations suggest that Pio and Dumpy are required at the apical membrane and matrix to stabilize taenidial folds and tube lumen during 17. This also includes the Np-mediated Pio release at the apical cell membrane. As requested by the referee we summarized Pio function during late tracheal development in our simplified model (see Fig. 9).

      However, it is of note that Np-mediated Pio release increases at late stage 16 (Fig. 5A, 6D; Fig. S13) but is strongly reduced in stage 17 embryos. In contrast, thin taenidial fold are formed at late stage 16 and becomes thicker and form at fusion points during stage 17 and reach their most mature form when the intraluminal chitin cable is cleared (Öztürk-Colak et al., elife, 2016). Thus, the pattern of Pio release and taenidial fold differentiation do not fully match. Moreover, in preliminary experiments we observe Pio antibody staining in stage 17 embryos at the apical cell membrane of dorsal trunks (data not shown). Furthermore, lumen clearance of Obst-A, Knk, Sepr and Verm are not affected in pio mutant embryos, but unknown luminal ECM contents remained (Fig. 1D). Therefore, we will follow this very interesting idea in future experiments.

      Nonetheless, we state in the results that Pio shedding is essential:

      “Our data assumes that Np overexpression may enhance Pio shedding in stage 16 embryos, affecting the Pio-mediated ZP matrix function. Upon breathless (btl)-Gal4-mediated expression of UAS-Np in tracheal cells, we observed a high amount of Pio puncta across the entire tracheal tube lumen, specifically in stage 16 embryos but not in earlier stages (Fig. S13). Consistently tracheal Np overexpression led to tube overexpansion in stage 16 embryos resembling the pio mutant phenotype (Fig. 8A,B). Thus, Np-mediated Pio shedding controls Pio function.”

      13.) Why don't we see the apical Pio signal in Figure 4B?<br />

      The red arrowhead points to apical mCherry::Pio punctuate staining in the Fig. 5B (before 4B) in the close up of the “bleached area” before bleaching and 56min post bleaching. However, in vivo bleaching experiments do not allow additional antibody stainings to detect precisely the apical cell membrane. Further, the Dpy::eYFP marks the tube lumen and the apical cell surface. The latter showed adjacent mCherry::Pio punctuate staining. However, due to bleaching Dpy signal was not detectable in the area.

      14.) The Strep signals in the merges in Figure 7C are not well visible.

      We are not sure which Strep signal the reviewer is referring to in Fig. 7C, which is now Fig. 8C. The top panel shows the Strep signal (right panel) overlapping with GFP in cells that do not express Np or human matriptase. Thus, the TGFB3 ZP domain is not cleaved, and the intracellular GFP and also the extracellular Strep signals are maintained and overlap.

      In contrast, when Np or human matriptase is added, the TGFB3 ZP domain is cleaved and only the intercellular GFP signal is retained, whereas the extracellular Strep signal is released from the cell surface. This explains why the Strep signal is barely detectable in the middle and lower panels of Fig. 8C.

      Reviewer #1 (Significance):

      This work brings together several factors (Pio, Dp, Np, Wst etc) already known to be needed for tracheal morphogenesis and differentiation in the embryo of D. melanogaster. Having worked myself with some of these factors, however, I recognize that the interaction between these factors is novel and very exciting. The experiments strongly indicate a new mechanism of cell-ECM connection that seems to be conserved to some extent (as they provide preliminary data on an example from humans). By integrating the functions of different factors, the work provides ample opportunity for future projects to elucidate this mechanism in detail. Therefore, I expect that it will have a significant impact not only on the field of developmental cell biology but also, due to the conserved proteins involved (ZP proteins, Matriptase), on the field of cell biology of human diseases.

      Reviewer #2 (Evidence, reproducibility and clarity):

      _The figures are clear, and the questions well addressed. However, I find that some of the claims are not completely backed by the data presented and have some suggestions that will hopefully make some points clearer.

      Major comments

      1.) In the abstract and at the end of the introduction the authors claim that they show that Pio, Dpy and Np support the balancing of mechanical stresses during tracheal tube elongation. However, this is not shown in this manuscript, where tension or mechanical stress were not measured and it is therefore speculative._

      As requested by the reviewer, we deleted “support balancing of” at the final sentence of the Introduction. Please, note that we did not use the term balancing of mechanical stresses at the abstract.

      However, we revised the abstract.

      It has been shown previously that forces and mechanical tension rise when apical membrane expands and elastic extracellular matrix, which is anchored to the membrane balances theses forces (Dong et al., 2014). Furthermore, its has been shown that the gigantic and elastic Dumpy protein modulates mechanical tension (Wilkin et al., 2000). Thus, these previous publications state that mechanical tension rise at the apical cell membrane and matrix when tubes expand during stage 16 and that Dpy is part of that molecular process, which we included in the abstract as essential background information.

      “The apical membrane is anchored to the apical extracellular matrix (aECM) and causes expansion forces that elongate the tracheal tubes. The aECM provides a mechanical tension that balances the resulting expansion forces, with Dumpy being an elastic molecule that modulates the mechanical stress on the matrix during tracheal tube expansion.”

      Nonetheless, our results show that Np-mediated Pio cleavage increases during stage 16 as response to tube length expansion which is accompanied by forces as postulated by others (see above). We further observe that the membrane bulges and chitin matrix tear off, when Pio cleavage does not occur in Np mutant embryos. Our data further show that Pio and Dumpy interact and that Pio release is prevented in Dpy mutant embryos. Altogether this suggests that the Np-mediated Pio cleavage responds to tube expansion and requires Dpy for luminal Pio release.

      We therefore claim in the final sentence of the introduction that “…ZP domain proteins Pio and, Dumpy, as well as the protease Np respond to mechanical stresses when tracheal tubes elongate”. The according changes are marked in red.

      2.) The authors state that all pio CRISPR/Cas9 generated mutants display identical tracheal phenotypes, however these data are not shown. Tracheal phenotypes, in particular DT phenotypes, of all mutants generated should be shown in supplementary materials.

      As requested by the reviewer, we included the data in the supplement. The pio5M and pio11R alleles showed embryonic lethality and a 100% gas filling defect resembling the pio17C allele. Additionally, we extended the tracheal analysis with the pio5M allele and identified tube size defects, irregular pattern of taenidial folds and apical membrane deformation, altogether resembling the pio17C allele. These new data are shown in the supplement Fig. S1.

      We clarify this in the results section as follows:

      “The tracheal phenotypes of pio5m are shown in the supplement (Fig. S1B-F). In all other Figures, we show images of the pio17c allele. “

      3.) At stage 16, pio null mutants display DT overelongation phenotypes (Fig. 1). The authors should quantify this phenotype.

      As requested by the reviewer, we quantified the DT overelongation phenotypes for pio5M (Fig. S1). The quantification of pio17C was shown already in Fig. 6B, now Fig 8B.

      4.) The authors analyse Pio distribution under tubular stress, using mega mutants and Chitinase overexpression. Pio localization changes in these genetic backgrounds and this is shown in Figure 2 only in a qualitative manner. The authors should measure Pio localization at the lumen and at the membrane and provide quantitative data.

      As requested by the referee, we measured Pio localization recognized by the anti-Pio antibody at the lumen and at the membrane to provide quantitative data. These are shown in Fig. 2E.

      All images were taken with a Zeiss Airyscan. For statistical analysis we used the the profile tool of the Zeiss ZEN 2.3 black software. This tool allows the measurement and comparison of fluorescence pixel intensities of individual channels. We determined the fluorescent intensities profile across the tube to identify values at apical membrane and tube lumen at minimum 10 different position of DTs (metameres 5 to 6) of two distinct embryos for each genetic background. The maximum values of membranes versus tube lumen were set into ratio and compared between control, mega mutant and Cht2 overexpression. The control embryos showed a ration below 0.4, the Cht2 overexpression a ratio of 1.2 and mega mutants a ratio of about ~0.9. These quantitative data confirm the statement that Pio localization increases at and near the apical cell membrane with respect to the lumen in mega mutants and in Cht2 overexpression embryos.

      5.) Surprisingly and interestingly, wurst;pio transheterozygotes display very strong tracheal defects. The authors say they observe gas filling defects; however it is not clear from figure 2E if this indeed the case. From the panel in the figure, it looks like these embryos suffer from strong tracheal morphogenetic defects. It would be necessary to have a better analysis of these embryos. What is the penetrance of this phenotype. If this is 100% penetrant, one would expect it to be lethal. Therefore, double mutant balanced stocks are not viable? Having analyzed the phenotypes and confirmed which morphogenetic defects the transheterozygote embryos present, how does this genetic interaction fit with the model presented?

      We are thankful to the reviewer for this interesting point of view suggesting that the wurst;pio embryos display tracheal morphogenetic defects. First, our data show that only 11.6% of the wurst;pio transheterozygous embryos completed gas filling and survived until adulthood. In contrast, 88.4% of transheterozygous wurst;pio mutant embryos did not complete gas filling which is now presented in Fig. 3B. The corresponding quantifications is presented in Fig. 3D. Importantly, the 88.4% wurst;pio transheterozygous embryos which show gas filling defects do not hatch as larvae and die.

      As requested, we performed a better morphogenetic analysis, which is presented in Fig. 3C. Analysis of the gas filling defects with light microscopy were repeated with a better objective (Zeiss Apochromat 25x Gly; 0.8 NA). Indeed, this analysis revealed a strongly compromised tube lumen morphology with irregular tube lumen pattern as if tubes twist and bend. This tube lumen deformation was further confirmed with the confocal analysis of chitin staining (cbp). The tube lumen of stage 17 transheterozygous wurst;pio mutant embryos showed irregular lumen pattern with unusual twists and even partially collapsed tubes.

      Furthermore, as asked by the referee, we generated the wurst,pio double mutation. All wurst,pio double mutant embryos lacked gas filling. In a more in-depth analysis of the tube lumen with a high-performance objective we could not identify any normal tube lumen in stage 17 embryos. Instead the double mutant embryos revealed completely collapsed tracheal tubes. This was confirmed by the chitin staining and confocal analysis. All new data are presented in the supplement.

      As shown in our manuscript and in previous publications, neither pio nor wurst mutant embryos affect cell polarity or gross organization of the actin and tubulin cytoskeleton. However, we found that wurst mutant embryos showed irregular apical membrane expansion at tube lumen (Behr et al., 2007; legend Fig. 4), irregular chitin fiber organization and to some extend collapsed tube lumen. In pio mutant embryos we found deformed apical membrane of DTs, irregular pattern of taenidial folds and to some extend collapsed tube lumen. Thus, the apical membrane is their common target of both proteins in late embryonic development, suggesting that pio functions provide stability and wurst functions the internalization of proteins at the apical membrane.

      We discussed it as follows:

      “Nevertheless, Pio and its endocytosis depend on its interaction with the chitin matrix and the Np-mediated cleavage. In stage 16 wurst and mega mutant embryos, we detect Pio antibody staining at the chitin cable, suggesting that Pio is cleaved and released into the dorsal trunk tube lumen. Also, the Cht2 overexpression did not prevent the luminal release of Pio. However, reduced wurst, mega function, and Cht2 overexpression caused an enrichment of punctuate Pio staining at the apical cell membrane and matrix (Figs. 1,2). Although the three proteins are involved in different subcellular requirements, they all contribute to the determination of tube size by affecting either the apical cell membrane or the formation of a well-structured apical extracellular chitin matrix, indicating that changes at the apical cell membrane and matrix in stage 16 embryos affect the Pio pattern at the membrane. It also shows that local Pio linkages at the cell membrane and matrix are still cleaved by the Np function for luminal Pio release, which explains why those mutant embryos do not show pio mutant-like membrane deformations and Np-mutant-like bulges. This is in line with our observations that tracheal Pio overexpression cannot cause tube size defects as the Np function is sufficient to organize local Pio linkages at the membrane and matrix. Therefore, it is unlikely that tracheal tube length defects in wurst and mega mutants as well as in Cht2 misexpression embryos are caused by the apical Pio density enrichment.”

      “Heterozygous and homozygous pio mutant embryos generally do not show tubal collapse. However, the loss of Pio and accompanying lack of Dpy secretion in stage 17 pio mutant embryos led to the loss of a Pio/Dpy matrix, impacting the late embryonic maturation and differentiation of a normal chitin matrix at the apical cell surface. TEM images reveal reduced dense chitin matrix material at taenidial folds and misarranged taenidial fold pattern (Figs. 1; S2), suggesting impaired taenidial function prevents tube lumen from collapsing after tube protein clearance. Wurst knockdown and mutant embryos do not show general tube collapse, but luminal chitin fiber organization is disturbed in stage 17 embryos (Behr et al., 2007). Therefore, transheterozygous wurst;pio mutant embryos may combine both defects and suffer from maturation deficits of the chitin/ZP matrix at the apical cell surface and within the tube lumen, which finally causes a high number of embryos with incomplete gas filling due to tube collapse. These maturation deficits are even more dramatic in the wurst;pio double mutants, which show no gas filling.”

      6.) mCherry::Pio Dpy::eYFP time lapse analysis and FRAP experiments is very interesting. However, it is not clear to which degree bleaching occurs in the tracheal lumen. The authors claim that recovery is very fast and can be seen from minute 2, however, frame-by-frame analysis of Movie S2 does not show a clear different between luminal Pio from minute 0 to minute 2. Rough comparison with the luminal area surrounding the bleached area, does not show a clear difference in luminal Pio before and after photobleaching. To claim fast recovery of luminal Pio after photobleaching, the authors should quantify luminal Pio, before and after bleaching.

      We agree with the reviewer and deleted “fast”. The Video2 shows intracellular mCherry::Pio recovery within 2min after photobleaching. The Video 2 shows extracellular (luminal) recovery within 6min after photobleaching, when first large mCherry::Pio puncta appear at the apical surface of the bleached area. Nonetheless, mCherry::Pio puncta appear in the lumen indicating recovery, whereas Dpy::eYFP did not.

      We state this in the Results section as follows:

      “In stage 16 embryos mCherry::Pio puncta reappeared in tracheal cells within 2 minutes of bleaching and in the tubular lumen within 6 minutes.”

      In addition, in figure 4D, the normalized mCherry::Pio fluorescence in the graph what does it refer to? Intracellular Pio?

      Figure 4D, now 5D, shows Western Blot signals. We guess that you refer to Fig 4B which is Fig. 5B.

      We are sorry for confusion and named it now Fig. 5B’.

      We stated in the Material section:

      “The bleaching was performed with 405nm full laser power (50mW) at the ROI for 20 seconds. A Z-stack covering the whole depth of the tracheal tubes in the ROI were taken at each imaging step. “Fluorescence intensity in the bleached ROIs was measured after correction for embryonic movements using Fiji.”

      Thus, to clarify this point, we added to the legends:

      “Fluorescence intensities refer to the bleached ROIs as indicated with the frame in corresponding Movie S2 and was measured after correction for embryonic movements.”

      7.) When mCherry::Pio Dpy::eYFP time lapse analysis and FRAP experiments was done in an Np mutant background, the authors describe lack of Pio recovery within the lumen (Movie S3). However, when comparing control and Np mutant background embryos, Pio is not properly released into the lumen of Np mutants (as stated by the authors and seen by comparing movies S1 and S4). Furthermore, on minute 0 of the FRAP experiment in Np embryos, there is no detectable Pio in the DT lumen. Therefore, recovery was not expected in Np mutants and should not be claimed as a conclusion for this experiment.

      We thank the reviewer for careful reading and apologize our wrong description. We changed it accordingly as follows:

      “In contrast to the control, extracellular mCherry::Pio is not released into the tube lumen within 56 min after bleaching in Np mutant embryos (Fig. 6C, Video S3).”

      8.) Brodu et al (Dev Cell 2010) have shown that Pio is important for cytoskeletal modulation during tracheal maturation. Pio is important for non-centrosomal microtubule (MT) arrays anchored at the tracheal cell apical membranes. In addition, MT disruption in tracheal cells leads to lumen formation defects (Brodu et al, Dev Cell 2010). In the absence of Pio, the tracheal cytoskeleton is altered, and this could explain some of the results observed. Ideally, the work should be complemented with a basic cytoskeletal analysis, but if this is not possible, the authors should discuss some of the phenotypes in light of this Pio function.

      Dear reviewer, this is a great idea. Therefore, we analyzed F-actin with Phalloidin and beta tubulin (E7 antibody, DSHB) in the dorsal trunk cells of stage 16 control and pio mutant embryos. However, tracheal cells are tiny and only gross irregularities can be realized. So, confocal Z-stack analysis of the stainings did not show gross differences between control and pio mutant embryos. We observe the expected apical subcortical accumulation for the actin and tubulin cytoskeleton in dorsal trunk cells of pio stage 16 mutant embryos which also has been shown for wt embryos elsewhere. These new data are presented in the supplement Fig. S7.

      Minor comments<br /> The model should not be in supplementary materials and should be moved to the main manuscript.

      We thank the reviewer for this suggestion and moved the model to the main part – now Fig.9. As requested by the reviewer 1, we extended the model, showing the timing events of Pio function.

      Throughout the manuscript embryonic stages are described using different nomenclature (stage X, stX and st X). Either way is correct, but the same nomenclature should be used throughout.

      We apologize for the different nomenclature and use "stage X" in the manuscript and "stX" in the figures for space reasons. Legend 1 clarifies the abbreviation.

      In Fig. S1 B and C the authors should specify which pio allele is being analysed (as in Fig. 7). The same should be done in the text.

      That's a fairly good point. To be clear from the beginning, we now state the following in the first paragraph of the results:

      “The tracheal phenotypes of pio5m are shown in the supplement (Fig. S1B-F). In the all other Figures, we show phenotypes of the pio17c allele.”

      Line 131, it is not correct to say that WGA visualizes cell membranes. WGA marks/stains cell membranes.

      Thanks for finding this mistake, it’s now corrected.

      Line 165 "leads to excessive tube dilation and length expansion due to strongly reduced luminal chitin" is not correct. Chitin reduction leads to excessive tube dilation but not to length expansion, as reported in the papers cited at the end of the sentence.

      Thanks very much for careful reading, we deleted “and length expansion” from the sentence.

      Line 220-221, what do authors refer to as "stage 16 wt-like control embryos"?

      Thanks for finding these mistakes. We corrected as follows:

      “In stage 16 embryos mCherry::Pio puncta….”

      Line 221, "some minutes" should be replaced by a specific number of minutes. According to Movie S2 reappearance of tracheal cell Pio happens from minute 16.

      We agree with the reviewer to state the time when mCerry::Pio puncta reappear. We observe first large puncta within two minutes after bleaching in tracheal cells at the ROI (Video S2, lower cell row at the movie). We further observe the reappearance of first large puncta at the ROI within 6 minutes in the tracheal tube lumen.

      We corrected it as follows: “In stage 16 embryos mCherry::Pio puncta reappeared in tracheal cells within 2 minutes of bleaching and in the tubular lumen within 6 minutes.”

      Line 291 "time laps" should be lapse.

      Thanks for finding the typo, it is corrected now.

      Line 302, "Pio was not shedded into the lumen but remained at the cell" should be "Pio was not shed into the lumen but remained in the cell".

      Thanks for finding the typo, it is corrected now.

      _Referees cross-commenting

      I agree. Taken together, all the comments will improve the quality of the work and of a future manuscript. Also, everything seems quite doable and will not present any problems._

      Reviewer #2 (Significance):

      _The findings shown in this manuscript shed light on the regulation of tubulogenesis by ZP proteins and how their interaction with the ECM can be regulated by proteolysis. It was known that Pio is involved in tracheal development, is secreted into the lumen, regulating tube elongation (Jaźwińska et al., Nat.Cell Biol., 2003) and anchoring MTs to the apical membrane during tubulogenesis (Brodu et al, Dev. Cell 2010). This work provides additional molecular insights into Pio dynamics and regulation during tube maturation.<br /> This work will be of interest to a broad cell and developmental biology community as they provide a mechanistic advance in ZP proteins involved in morphogenesis. It is of specific interest to the specialized field of tubulogenesis and tracheal morphogenesis.

      Field of expertise:<br /> Drosophila, morphogenesis, tracheal tubulogenesis, cytoskeleton_

      Reviewer #3 (Evidence, reproducibility and clarity):

      _Summary<br /> In this manuscript, Drees and colleagues analysed, during the formation and growth of tubular systems, how cells combine forces at the cell membranes while maintaining tubular network integrity. A fundamental question is to understand how cells manage to integrate the axial forces to stabilise the cell membrane and the apical extracellular matrix (aECM).<br /> To address this question, the authors study the formation of the tracheal system in Drosophila embryos, a well-established and detailed model system to investigate formation of tubular networks. In particular, they focused on the formation of the larger tube of the tracheal network, the dorsal trunk. The formation of this tube depends in part of axial extension along the antero-posterior axis.<br /> They concentrated their work on the function of Piopio (Pio), a Zona-Pellucida (ZP)-domain protein. They showed that Pio together with the protease Notopleural (Np) contribute the sense and support mechanical stresses when tracheal tubes elongate, thus ensuring normal membrane -aECM morphology.

      Major Comments

      In a previous work, Drees et al. (PLOS Genetics 2019), showed the matriptase-prostasin proteolytic cascade (MPPC), is conserved and essential for both Drosophila ECM morphogenesis and physiology.<br /> The functionally conserved components of the MPPC mediate cleavage of zona pellucida-domain (ZP-domain) proteins, which play crucial roles in organizing apical structures of the ECM in both vertebrates and invertebrates. They showed that ZP-proteins are molecular targets of the conserved MPPC and that cleavage within the ZP-domains is a conserved mechanism of ECM development and differentiation.<br /> Here, Drees et al. investigate further how the coupling between membrane and matrix takes place to ensure proper tube growth.<br /> Pio distribution and phenotypes<br /> They first focused on the tracheal phenotypes observed in a pio null mutant context. So far, the only pio mutant characterised was a point mutation in the ZP domain. Using CRISPR/Cas9, they generated new alleles of pio which are lack of function alleles. In the context, Drees and colleagues observed over-elongated dorsal trunk tubes, with bulges appearing at stage 16 between the apical domain of tracheal cells and adjacent extra-luminal matrix.<br /> Additionally, pio mutant embryos showed impaired tube lumen clearance of the some of the aECM components, which prevent gas-filling of the airways.<br /> To detect Pio distribution, the authors used either anti-Pio antibody directed toward a short stretch with the Pio ZP domain or generated a CRISPR/Cas9 piomCherry::pio line.

      _

      1.) The Pio antibody shows a strong luminal staining as already published. But the authors reported an apical membrane signal in tracheal cells. I find this apical membrane signal really difficult to observe in panel Fig. 2B. The overlap between the Pio dots and the apical membrane labelled with Uif showed in Fig 2C can be due to the 3D projection. It is only when endocytosis is unpaired (Suppl Fig. 2), that data are more convincing.

      We thank the reviewer for this important point, we are sorry for the unconvincing presentation and for having the chance to improve it.

      We show the 3D image of Pio puncta as voxels overlapping with Uif at the apical cell membrane. The amount of Pio voxels overlapping with the Uif marked apical cell membrane increased in mega mutant and due to tracheal Cht2 overexpression. This result was indicated by a representative region (frame) and white arrows and is shown now in Fig. 2C.

      We further used orthogonal projections across the tracheal tube of the airyscan Z-stacks. Random usage confirmed that puncta of Pio antibody staining overlap with Uif at the tube lumen. We observed overlap in controls, but increasing overlap in mega mutant and Cht2 overexpressing embryos. This result is shown now in Fig. 2E.

      However, to overcome any misinterpretations of projections, we used single images of the original airyscan Z-stacks for co-localization analysis with the Zeiss ZEN software (black, 2.3, sp1). We used two available and independent standard methods to compare fluorescence pixel intensities of different channels namely the ZEN co-localization and the ZEN profile tool. Both are described in the Materials section.

      a.) With the co-localization tool we compared directly fluorescence pixel intensities of Pio and Uif. Highest overlap of the intensities, shown in the ZEN tool as third quadrant, were set to white for better visualization in the images. These new images are included as Fig. 2D and show recurrent overlap of Pio and Uif antibody stainings (punctuate pattern) along the apical cell membrane at the dorsal trunk of stage 16 control embryos. This overlap pattern increased in mega mutant and Cht2 overexpression embryos.

      b.) A second approach for comparing fluorescence intensities is the ZEN “profile” tool. Drawing a line across the tube allowed us to compare peak fluorescence pixel intensities of the different channels at distinct regions, such as the apical cell membrane and the tube lumen including the cbp marked chitin cable. This tool detected overlap of peak fluorescence intensities of UIF and Pio antibody staining’s, confirming that Pio is located together with UIF at the apical membrane of dorsal trunk tracheal cells. These new intensity profiles and the corresponding images are presented in the supplement as Fig. S4B-D. Quantifications of this method comparing the ration of Pio peak intensities between the apical cell membrane and the tube lumen are presented as Fig. 2F (as requested by Reviewer 2).

      2.) When the author used their CRISPR/Cas9 piomCherry::pio line to characterise Pio distribution (Fig.4), Pio is localised at the apical plasma membrane before stage 16. Only at stage 16, Pio is detected within the lumen. This timing of Pio release in the lumen is critical for the model proposed by Drees at al. This is an important point to assess the difference between the use of the antibody (which mostly label the lumen) while piomCherry::pio line is mostly at the membrane.

      We agree with the reviewer that the Pio antibody shows a different pattern within the tube lumen of earlier stages. The Pio antibody shows intense extracellular staining from early stage 12 onwards, presumably due to its early function at dorsal and ventral branches, as shown by Anna Jazwinska (Jazwinska et al., 2003). The intense luminal Pio antibody staining, predominantly at the chitin cable, persist until its disappearance due to airway protein clearance during stage 17. Unfortunately, this strong luminal Pio staining made it impossible to examine the Pio distribution pattern in more detail during stage 16. Nevertheless, Np overexpression experiments indicate that luminal Pio release occurs specifically in stage 16 embryos (Fig. S13), which was tested with the Pio antibody, see results, second last paragraph:

      “Our data assumes that Np overexpression may enhance Pio shedding in stage 16 embryos, affecting the Pio-mediated ZP matrix function. Upon breathless (btl)-Gal4-mediated expression of UAS-Np in tracheal cells, we observed a high amount of Pio puncta across the entire tracheal tube lumen, specifically in stage 16 embryos but not in earlier stages (Fig. S13).”

      We further agree with the reviewer that mCherry::Pio was used to characterize in vivo Pio distribution within the dorsal trunk cells and tube lumen during stage 16. The Fig. 5A shows apical mCherry::Pio distribution pattern in early and late stage 16 embryos. Importantly, the appearance of luminal mCherry::Pio increased during stage 16 and mainly enriched at late stage 16. See Figure 5A, red arrowheads point to apical Pio and red arrows to luminal Pio staining.

      Furthermore, as discussed above and shown by different ZEN tools, such as co-localization and fluorescence intensity profile tools, Pio antibody stainings revealed a punctuate pattern at the apical cell membrane of dorsal trunk cells in stage 16 embryos, which is reflected also by the appearance of apical mCherry::Pio puncta at the membrane surface. Additionally, we observed mCherry::Pio puncta also within the tube lumen (see the new Figures S4B & S8). Thus, subcellular Pio distribution at the apical cell membrane and lumen were observed for both, Pio antibody staining and mCherry::pio pattern.

      Nonetheless, there is different luminal appearance between the Pio antibody staining and mCherry::Pio. Pio antibody detects a short stretch at the ZP domain and thus detects all possible Pio variants, uncleaved and cleaved. Due to early tracheal Pio function, Pio enriches within the tube lumen in an intense core-like structure, which is recognized by the Pio antibody and is comparable with the Dpy::eYFP pattern. Also mCherry::Pio labels all Pio variants, uncleaved and cleaved. The spatial temporal mCherry::Pio expression pattern (Fig. S5) is comparable with the Pio antibody pattern and the staining at the membrane in stage 16 embryos. However, mCherry::Pio did not enrich in the lumen in a core-like structure, nonetheless, shows overlap with luminal Dpy::eYFP.

      Jaswinska showed that Pio antibody staining is intracellular in the trachea of stage 11 pio2R-16 point mutation embryos (Jaswinska et al., 2003; Fig 2d). To understand more about the specificity of the antibody, we performed stainings in the null mutant embryos. In contrast, to the high number of intracellular Pio puncta in pio2R-16 point mutation embryos, Pio stainings were much more reduced in pio5m and pio17c mutants, but a low number of Pio puncta were still detectable in the embryos (Fig. S1G,H). It is of note that also dpy mutants showed strongly reduced Pio antibody staining (Fig. S10E). Thus, discussing underlying causes of enriched (Pio antibody) versus non-enriched (mCherry::Pio) luminal staining are speculative. However, observations by Jaswinska et al. (2003) and our new observations, investigating the Pio antibody stainings in pio null mutants, dpy mutants, eYFP::Dpy embryos and NP overexpression may hint to the possibility of cross-reactivity of the Pio antibody to other ZP domains which may intensify the appearance of luminal Pio antibody staining in control embryos.

      Anyway, we clarify the difference in luminal Pio pattern in the discussion as follows:

      “Indeed, the anti-Pio antibody, which detects all different Pio variants, showed a punctuate Pio pattern overlapping with the apical cell membrane markers Crb and Uif at the dorsal trunk cells of stage 16 embryos (Fig. 2; Fig. S3,S4). Additionally, Pio antibody also revealed early tracheal expression from embryonic stage 11 onwards, and due to Pio function in narrow dorsal and ventral branches, strong luminal Pio antibody staining is detectable from early stage 14 until stage 17, when airway protein clearance removes luminal contents. In the pio5m and pio17c mutants Pio stainings were strongly reduced although some puncta were still detectable in the trachea (Fig. S1G,H). Similarly, Pio antibody staining is intracellular in the trachea of stage 11 pio2R-16 point mutation embryos (Jaźwińska et al., 2003). Interestingly, also dpy mutants showed strongly reduced and intracellular Pio antibody staining (Fig. S10E).

      We generated mCherry::Pio as a tool for in vivo Pio expression and localization pattern analysis during tube lumen length expansion. The mCherry::Pio resembled the Pio antibody expression pattern from early tracheal development onwards. However, luminal mCherry::Pio enrichment occurs specifically during stage 16, when tubes expand. The stage 16 embryos showed mCherry::Pio puncta accumulating apically in dorsal trunk cells. Moreover, mCherry::Pio puncta partially overlapped with Dpy::YFP and chitin at the taenidial folds, forming at apical cell membranes. Supported by several observations, such as antibody staining, Video monitoring, FRAP experiments, and Western Blot studies (Figs. 4,5), these findings indicate that Pio may play a significant role at the apical cell membrane and matrix in dorsal trunk cells of stage 16 embryos.”

      3.) Another important point is to explain the discrepancy between the pio mutant alleles. The allele containing a point mutation in the ZP domain shows no over-elongated tubes (Dong et al 2014, Jazwinska et al. 2003) while the lack of function alleles does.

      The reviewer is correct that the pio2R-16 mutation shows only a disintegration phenotype whereas our pio null mutations show in addition tube length defects. However, Dong et al. showed significantly increased dorsal trunk length in shrub; pio2R-16 double mutant embryos when compared with shrub mutant embryos (Supplemental Fig. S4A). Also, the shrub;dpyolvR double mutant embryos revealed increased tube length expansion when compared with shrub mutant embryos. Moreover, their quantifications show that the also dpyolvR mutant embryos revealed significantly increased tube expansion when compared with wt. Altogether these previous findings suggests that Pio and Dpy are involved in controlling tube length control during stage 16.

      Furthermore, we generated three independent pio null mutation alleles, which lost all the essential Pio protein domains, and caused all embryonic lethality, gas-filling defects, branch disintegration phenotype and tube length defects (quantifications are shown in Figs. 9 and S1). In addition, pio null mutations prevent Dpy::eYFP secretion. Thus, we are confident that the observed tube length defects as well as the air-filling defects are due to the loss of Pio, and in particular since these defects could be rescued by Pio Expression in the pio null mutation background, as shown in Fig. 3B.

      So, what could make the difference?

      The described pio2R-16 mutation allele contains a X-ray induced single point mutation that led to an amino acid replacement (V159D) in the ZP domain. It is not clear how the amino acid exchange affects the protein and the ZP domain. It may hamper pio function and maybe this amino acid replacement is problematic for the early tracheal function but not during stage 16. As stated by Jazwinska et al. 2003 (Fig. 2 legend), Pio antibody staining is intracellular in the mutants and extracellular in the trachea of wt at stage 13.

      They further speculate that the mutant Pio protein may retain in the secretory pathway, but this is not confirmed with co-markers. As luminal Pio function is required to provide a barrier for autocellular AJ formation, this fails in pio2R-16 mutation. In contrast, it is still possible that Pio interacts and supports Dpy secretion in pio2R-16 mutation and additionally it is thinkable that intracellular Pio may reach to some extend the apical cell membrane in pio2R-16 mutation stage 16 and thus can support tube size control. But these assumptions are speculations.

      Nevertheless, to clarify this point we explain the discrepancy between the pio2R-16 mutation and pio null mutations alleles as follows:

      “Using CRISPR/Cas9, we generated three pio lack of function alleles (Fig. S1A), all exhibiting embryonic lethality and identical tracheal mutant phenotypes. The tracheal phenotypes of pio5m are shown in the supplement (Fig. S1B-F). In all other Figures, we show images of the pio17c allele. The pio17c and pio5m null mutant embryos revealed the dorsal and ventral branch disintegration phenotype known from a previously described pio2R-16 mutation allele which contains a X-ray induced single point mutation that led to an amino acid replacement (V159D) in the ZP domain (Jaźwińska et al., 2003). Additionally, the late stage 16 pio17c and pio5m null mutant embryos showed over-elongated tracheal dorsal trunk tubes (see below).”

      4.) A minor point, the author should provide hypothesis to explain why only the clearance of CBP, Obstructor-A and Knickkopf are affected in a pio mutant background and not Serpentine and Vermiform.

      We thank the reviewer for careful reading and the comment on this point. We would be happy to see such a scenario which could give us a hind of Pio interaction partners at the chitinous matrix. However, we stated that luminal material, such as Obst-A and Knk are removed from the lumen (see Fig. S5A). We further describe that in pio mutant embryos, luminal Serp and Verm staining appeared reduced but showed wt-like distribution (see Fig. S6) in stage 16 embryos. We do not show Serp and Verm in stage 17 embryos, but they are removed from the tube lumen (not shown). These data are received from immune-staining’s and confocal analysis.

      Nevertheless, we also state that pio mutant embryos revealed lumen clearance defects in TEM analysis, of undefined material in the tube lumen (see Fig. 1D and Fig. S2B).

      To clarify this point we state in the results as follows:

      “Fourth, ultrastructure TEM images revealed aECM remnants in the airway lumen of pio mutant stage 17 embryos, while control embryos cleared their airways (Fig. S2B). Consistently, the in vivo analysis of airways in stage 17 pio mutant embryos revealed lack of tracheal air-filling (Fig 3B). The pan-tracheal expression of Pio in pio mutant embryos rescued the lack of gas filling (Fig 3B). Thus, TEM images suggest that pio mutant embryos showed impaired tube lumen clearance of aECM, which prevented subsequent airway gas-filling. “

      And

      “Also, the pio mutant embryos showed tracheal lumen clearance defects of chitin fibers in ultrastructure (TEM) analysis (Figs. 1D, S2B). In contrast, confocal analysis revealed that well-known chitin matrix proteins, such as Obstructor-A (Obst-A) and Knickkopf (Knk), are removed from the lumen of pio mutants (Fig. S5A). These results suggest that the Pio function did not affect airway clearance of Obst-A and Knk and therefore did not play a central role in airway clearance like Wurst. Nevertheless, airway clearance defects observed in TEM images in pio null mutant embryos and, in addition, defective tube lumen morphology in wurst;pio transheterozygous mutant embryos explain the occurrence of airway gas filling defects.”

      5.) Pio and Dumpy. Dumpy (Dpy) is another ZP domain protein secreted by the tracheal cells and detected in the lumen. To follow Dpy distribution, Drees and colleagues used a Dpy::eYFP protein trap line, the same used in Dong et al. However, in this latter paper, Dong et al. stated, using a Crb staining, that Dpy is not at the apical cell surface but only in the lumen. However, Drees and colleagues reported (line 227 and Fig. 4C) that Dpy appears both at the apical cell surface and in the lumen of the tracheal system. But they did not show a co-localisation with an apical marker. Furthermore, in their previous work, (Drees et al. 2019) they called the apical staining a "peripheral shell" layer. In addition, in S2R+ cell culture, it is only when Pio and Dpy co-express that Dpy is detected at the cell membrane. The in vivo localisation of Dpy is an important point that needs to be clarified as it is of importance for the final model proposed Supp Fig. 9.<br /> Drees at al. also performed FRAP experiments on Dpy::eYFP protein trap embryos. As excepted as already shown by Dong et al.

      The referee is correct, we state “In stage 16 embryos Dpy::eYFP (Lye et al., 2014) appears at the tracheal apical cell surface and predominantly within the lumen (Fig. 4C).” The corresponding Fig. 4C reveals Dumpy::eYFP staining overlapping with chitin at two subcellular regions: Dpy is enriched as a core-like structure within the lumen overlapping with the chitin cable of the control embryos. Additionally, Dpy::eYFP overlaps with the chitin part that might be part of the apical cell surface. But this observation is hard to see in images in Fig. 4C and we apologize it. We therefore repeated the Dpy::eYFP localization analysis and analyzed in more detail with the ZEN profile tools, which shows peak fluorescence pixel intensities of different channels and provides the possibility to prove, if they overlap in XY axis.

      We asked first, if cbp (chitin) appears at the apical surface of dorsal trunk cells, when Pio becomes cleaved and released. In mid stage 16 embryos cbp staining appeared in the luminal chitin cable and additionally in a distinctive pattern, which fits to the pattern of taenidial folds that start to form. We therefore used the apical cell membrane marker Crumbs to co-stain cbp. Airycsan microscopy fluorescence intensity profile analysis and corresponding close ups images confirmed the overlap of Crb and cbp stainings at this distinctive pattern indicating this shows the chitin matrix at the apical cell surface (Fig. S8A). But there was no overlap of cbp and Crb at the chitin cable structure. Thus, knowing the localization of the apical cell surface chitin matrix, we performed co-stainings of cbp with mCherry::Pio (RFP antibody). This revealed, as expected, overlap of cbp and RFP antibody staining at the apical cell surface chitin matrix (distinct pattern) and with the luminal chitin-cable (Fig. S8B,C). Finally we repeated the stainings and analysis with cbp, mCherry::Pio (RFP antibody) and Dpy::eYFP (GFP antibody). First, these results revealed overlap of Dpy::eYFP and cbp at the apical cell surface and in the tube lumen (Fig. S8D) and second, overlap of punctuate staining of Dpy::eYFP, cbp and mCherry::Pio at the apical cell surface chitin matrix and also at the luminal chitin cable (Fig. S8E).

      Very obvious from images and Z-projection in Fig. 4C is the lack of extracellular Dpy::eYFP staining in pio mutant embryos. Dpy::eYFP enriched intracellularly, and thus, the pio mutant caused Dpy::eYFP mis-expression fits well to our results from S2R+ cell culture. As the reviewer notes, it is only when Pio and Dpy co-express that Dpy is detected at the cell membrane.

      Altogether, Fig. 4C, cell culture experiments and our new stainings support our model, that Pio and Dumpy interact and are co-secreted at the apical cell membrane/surface, where Np mediates Pio cleavage. As requested by reviewer 2, we moved the model to Fig. 9. As requested by reviewer 1, we extended the model for timing events.

      A minor point, the Dpy::eYFP protein trap line used in this study is not listed in the Materials and Methods section of the supplementary data.

      Thanks, we included it into the List of sources (Supplement). This YFP-trap line (called CPTI lines) was published by Claire M. Lye et al., Development, 141, 2014. We cite it in our manuscript.

      6.) The serine protease NP and Pio release. Drees and colleagues have pervious shown, preforming in vitro studies, that protease Notopleural (Np) cleaves the Pio ZP domain (Drees at al. 2019). Here the authors went a step further in demonstrating that it is also true in vivo at stage 17. In addition, they showed that, in Np mutant embryos, mCherry::Pio is mostly detected within tracheal cells and the luminal staining is strongly reduced. In this mutant context, the authors conducted FRAP experiment on the mCherry::Pio signal even very weak in the lumen. They showed hardly no recovery after photobleaching.<br /> In Drosophila S2 cells, Drees and colleagues showed that co-expression of the catalytically inactive NpS990A with mCherry::Pio in showed as a prominent signal the 90kDa mCherry::Pio variant in the cell lysate (Fig. 5B), and live imaging revealed mCherry::Pio localisation at the cell surface (Fig. S6B). However, in this inactive form context, a strong signal is also detected at 60kDA corresponding to a cleaved form of the Pio ZP domain (Fig. 5B), and Pio localisation at the cell surface appears weaker than in controls. They authors did not consider that another protease could be at play.<br /> On the other hand, in their previous work, Drees et al. identified a mutant form of Pio (PioR196A) which is resistant to NP cleavage in vitro. It will be a step forward to establish by CRISPR/cas9, as the authors seems to be successful with this technique, a mutant line carrying this point mutation. It will be important to determine whether the observed phenotype resembles that of a mutant Np phenotype.<br /> In their previous work (PLOS Genetics 2019), in Np mutant embryos, Drees et al. did not report "budge-like" deformations from stage 16 onwards leading to the detachment of the tracheal cell from their adjacent aECM. Either the alleles or the allelic combination is different between the two studies which could explain this difference, or it is a new phenotype that has not been previously described. In the latter case, it becomes important to quantify the proportion of segments showing these bubbles. Is this a rare phenotype to observe?

      We thank the reviewer for the very interesting comments and the careful reading of our manuscripts and the very useful suggestions. We agree, the we cannot exclude the possibility that another protease is involved in the cleavage of Pio. Therefore, we included this important point in the discussion section as follows:

      “Unknown proteases may likely be involved in Pio processing since cleaved mCherry::Pio is also detectable in inactive NpS990A cells.”

      We think the generation of the pioR196A mutant to address Pio localization and tracheal phenotypes is a great idea, which we would like to address in future experiments. Unfortunately, the production of this fly line with such a specific point mutation at this position will take several months, not included the subsequent evaluation and phenotypic analysis of this fly line and mutants. Therefore, we apologize that we cannot pursue this question experimentally. Nevertheless, mentioning the possibility and the requirement of such an experiment is important and we discuss it as follows:

      “Previously we identified a mutation at the Pio ZP domain (R196A) resistant to NP cleavage in cell culture experiments (Drees et al., 2019). Establishing a corresponding mutant fly line would be essential in determining whether the observed phenotype resembles the phenotype of the Np mutant embryos.”

      However, knowing that we are not able to provide a new mutant fly line to evaluate the formation of the dorsal tube when an NP non-cleavable form of Pio is expressed, we sought to use an alternative approach by overexpressing Np in the trachea with btl-Gal4. This shows a clear pairing of Np overexpression and Pio release specifically at stage 16 dorsal trunk and associated tube overexpansion.

      Finally, the reviewer is correct, we did not mention the appearance of bulges in Np mutant tracheal dorsal trunk cells in our previous publication. We used that same Np alleles in 2019 and a closer look at the publication of 2019 likewise shows the appearance of bulges in Np mutant embryos, e.g. Fig. 1B (red-dextran, left part of the tracheal lumen shows bulges) and even the Dpy::YFP matrix tear off at the site of bulges (Fig. 4F’’, above the arrowhead). But we did not know at the time the link with Pio and Dumpy

      However, we agree, it is important to know more about the appearance of the phenotype by means of quantifications. The quantifications of bulges per dorsal trunk (n=16) is shown in Fig. 7B.

      7.) Minor point: I don't understand what the authors are trying to show in supplementary Figure 8. Tracheal cells detach and are found in the lumen?

      We are sorry for the unclear description in the legend. We corrected it as follows in the legend of Fig. S12:

      “This indicates disintegration of apical cell membrane at bulges and subsequent leaking of cellular content into the lumen.”

      8.) Np function conserved matriptase.<br /> In this work, Drees and colleagues showed that Np controls in vivo the cleavage of the Pio ZP domain.<br /> Dumpy and Piopio are not conserved in vertebrates but they both contain a ZP domain which is conserved. The authors tested if other ZP proteins can be cleaved by Np or the human homolog Matriptase. The authors tested in cell culture the ability of the type III Transforming growth factor-β receptor which contains a ZP domain to be cleaved either by Np or Matriptase.<br /> This could be a general mechanism that needs to be extended to other ZP domain proteins and that could be at play to structure the matrix and give it its physical properties.<br /> However, as it is all speculative, I find the discussion section related to these data, for too long and that does not help to understand better the work done in the formation of the tracheal tubes of the drosophila embryo.

      We show that Np mediates cleavage of the Pio ZP domain in vitro and in vivo in Drosophila embryos. We further showed that also the human matriptase was able to cleave the Pio ZP domain. To understand if this is a more general mechanism, we extended our studies with the human TβIII and its ZP domain. These data show that both Drosophila and human matriptases are able to cleave ZP domains of different proteins from different species. These data suggest that Matriptase-mediated ZP domain cleavage is not a Drosophila specific mechanism. We cannot follow the argumentation of the referee to state it all speculative. Nevertheless, we agree that it will need follow up studies to show that the mechanism is more general than two different species and ZP domain proteins. Anyway, as requested by the referee, we deleted the following sentences of the paragraph, since they are speculative in the context of our manuscript and do not directly describe a potential matriptase and ZP domain function:

      “Matriptase degrades receptors and ECM in pulmonary fibrinogenesis in squamous cell carcinoma (Bardou et al., 2016; Martin and List, 2019). TβRIII is a membrane-bound proteoglycan that generates a soluble form upon shedding (López-Casillas et al., 1991), a potent neutralizing agent of TGF-β. Expression of the soluble TβRIII inhibits tumor growth due to the inhibition of angiogenesis (Bandyopadhyay et al., 2002). Idiopathic pulmonary fibrosis (IPF) is associated with a progressive loss of lung function due to fibroblast accumulation and relentless ECM deposition (King et al., 2011; Loomis-King et al., 2013). “

      However, the comparisons of the tubular organ and the phenotypic expressions of the bulging membrane and the aortic aneurysm appear to us as an important element of the article. In both cases, cell membrane loses its integrity and can break in tubular networks. Thus, with our findings on the modification of extracellular ZP proteins, we offer a potential new molecular approach even for clinical investigation.

      9.) Minor points: Pio and cytoskeleton organisation.<br /> Line 78-79, the authors wrongly quoted a work from Brodu et al (2010). Pio does not anchor the microtubule severing enzyme Spastin. Instead, Spastin releases the microtubule-organising centre from its centrosomal location, then Pio contributes to its apical membrane anchoring. It can therefore be assumed that the organisation of the microtubule network is affected in a pio null mutant. In addition, ZP proteins have been shown to link the aECM to the actin cytoskeleton. Therefore, it would be interesting to look at the organisation of the actin and microtubule cytoskeletons in a pio mutant context in which enlarged apical cell surface area are observed.

      We are very thankful for finding this mistake in the introduction. We corrected it as follows:

      “Further, Pio is involved in relocating microtubule organizing center components γ-TuRC (γ-tubulin and Grips; gamma-tubulin ring proteins). This requires Spastin-mediated release from the centrosome and Pio-mediated γ-TuRC anchoring in the apical membrane.”

      Studying cytoskeleton in pio mutant embryos is a helpful idea. Therefore, we analyzed F-actin with Phalloidin and beta tubulin (E7 antibody, DSHB) in the dorsal trunk cells of stage 16 control and pio mutant embryos. However, tracheal cells are tiny and only gross changes can be realized. The confocal Z-stack analysis of the stainings did not show gross differences between control and pio mutant embryos. We observe the expected apical subcortical accumulation for the actin and tubulin cytoskeleton in dorsal trunk cells of pio stage 16 mutant embryos which also has been shown for wt embryos elsewhere. These new data are presented in the supplement Fig. S7.

      _Referees cross-commenting

      I have just read the comments of the other two reviewers, who like me are specialists in the formation of the tracheal system in the drosophila embryo.<br /> I find the comments very fair and balanced. They are in the same spirit as my comments and are very complementary. I hope that all our comments will be constructive for the authors and will improve the quality of their work._

      Reviewer #3 (Significance):

      _Overall, the methodology is sound, the quality of the data is good and the paper is very well written. Authors combine in vivo, in vitro studies as well a cell culture approach. Using CRISPR/Cas9, they generated a large number of new tools allowing in vivo studies.<br /> Drees and colleagues generated new alleles of pio which are lack of function alleles. They described a new phenotype for pio mutant embryos, namely over-elongated tubes. But they authors do not comment on why these new alleles reveal a new phenotype. Furthermore, using their piomCherry::pio line, the authors state that Pio is localised to the plasma membrane. This location is very difficult to assess. Both new results require clarification.<br /> The authors had already demonstrated that Np cleaves the ZP domain of Pio in vitro. Here they demonstrate this in vivo. It appears important to evaluate the formation of the dorsal tube when an NP non-cleavable form of Pio is expressed.<br /> Finally, the model proposing a coupling between the extracellular matrix and the membrane of tracheal cells is very interesting. The demonstration that cleavage of Pio by Np could participate in this coupling is very interesting for those interested in the integration of mechanical stress and cellular deformation. However, such a model has already been discussed in Dong et al (2014). In this article, Dong et al. proposed that a "coupling of the apical membrane and Dpy matrix core is essential for tube length regulation".

      The audience for this article should be specialised and oriented towards basic research. It may be of interest to people working on tubular systems or working on ZP proteins.

      My field of expertise is cell biology and developmental biology in drosophila and formation of tubular networks._

  2. Jul 2023
    1. need to be breaking out of the template

      template no longer works - organization by entity - CRUD centric thinking // to bad It's the connections that matter

      'Tain't what you deal with that matter but why and how you do what you need to do to accomplish what intent flow process goal!

      the way you connect the meaings of the connections and their emnergent composition Wholeness of intent and its implicate ordr if you just let it self-actualize thorugh articulation

    2. need to trace tightly related code from entry point to controller level to 00:18:21 data access layer to service level to entity the tightly related code put it together keep it as close together in your code as you possibly can that means you're going to lose out on 00:18:33 some of that that rigor that people try to do through project references people try to force this kind of loose coupling rule by setting all those kind of rules of you know this project can only access 00:18:45 that project and can only have these Tack and all that that's great um it's extra overhead it's extra friction on you it's just better if

      xxx

    3. vertical slice architecture

      what folks can now call vertical slice architecture just the idea that I am going to organize first by cohesive features within the system a bit of functionality and I'm trying to show this here I'm showing separate databases it doesn't necessarily mean you're automatically having a giant modular monolith that's targeting six eight totally different databases just that if a segment of the database whether it's a schema a set of collections if at least between features could be a little bit Loosely coupled from each other that even if you're a monolith if you could do upgrades this at a time one feature at a time that's practical you can convince product owners of hey we can do this upgrade in our case it's it's not necessarily an upgrade it's cheap right we kind of like to replace SQL server with postgres and some of our big systems just purely cost savings it would be nice if we could do that if we could tackle it more bit wise a Sprint by Sprint we could deliver in a Sprint we could deliver switching part of the app from SQL Server to postgres but there's no way in hell within one Sprint we could ever do the whole whole horizontal layer that's something to think about other weakness layered architecture they talk about well you can reason about one layer at a time you never reason about one layer at a time you reason about one use case at a time the full vertical stack hopefully you can concentrate on only the business logic or only the data access logic but likely when you have customer problems when you have integration tests failing you need to trace tightly related code from entry point to controller level to data access layer to service level to entity the tightly related code put it together keep it as close together in your code as you possibly can that means you're going to lose out on some of that that rigor that people try to do through project references people try to force this kind of loose coupling rule by setting all those kind of rules of you know this project can only access that project and can only have these Tack and all that that's great um it's extra overhead it's extra friction on you it's just better if developers can be disciplined instead okay I want to keep harping on keep harping on a little layered architecture just a little bit

    1. the entire biosphere is made out of 00:41:23 um female desire for no reason no reason to it right night not with an objective of reproducing but just with an objective of wow that's really sexy I like it 00:41:35 and that's a very very good reason isn't it to to save the planet
      • for: climate communication, mass mobilization, collective action, climate messaging, beauty, evolution
      • claim
        • the natural world is sexy, beautiful, and it would be a waste to have it all destroyed
        • the entire biosphere is made out of female desire for no reason to it
          • not with an objective of reproducing
            • but just with an objective of wow that's really sexy I like it
          • and that's a very very good reason isn't it to to save the planet
        • these beautiful qualities that have no Rhyme or Reason to them but are actually to do with creativity and Imagination
          • are not some kind of special thing that human beings impose from some kind of abstract Heaven onto Earth
          • they are actually heaven on Earth
          • they're part of Heaven and they are coming out of our embodied biological being right and this is an amazing thing
            • pity and
            • compassion and
            • generosity
          • and all these things are are traits in primates
            • sharing things and
            • being kind right
          • and so I reckon you know the kind of religious feeling that we need to inculcate
          • it is actually about this feeling inside
            • this kind of surging feeling of
              • inspiration and
              • love and
              • passion
            • and everything is exactly coming to us from our Evolution and
            • it's coming for no reason at all
            • it's just coming from random genetic mutation and the fact that having these feelings doesn't kill you
          • so this is a very good reason I think to save Earth
          • the essence of us is
            • our future and
            • our physical biological being
          • and it's always just a little bit off to the side like tomorrow is just a little bit off to the side of today
            • but I'm going to get there at some point right and
            • I think that's the attitude
    2. The Divine image
      • for: William Blake, poem, evolution, beauty, climate communication, motivation
        • William Blake Poem
          • The Divine Image
            • To Mercy, pity, peace and love all pray in their distress and in these virtues of delight return their thankfulness
            • when push comes to shove as they say in English
            • when you're up against the wall when you're in an extreme situation
              • someone's going to hit you and what do you do? Mercy Mercy you just say it or
              • you see someone else, they're about to hit someone and you say for pity's sake don't do that or
              • you find somebody very, very attractive and you feel this love right?
            • that's why he says
              • love the human form Divine
              • mercy has a human heart
              • pity a human face
              • love the human form Divine
            • these things are actually almost spontaneous intuitive things that happen and what does it mean?
              • they come from the biosphere
              • they come from your body
              • they come from evolution
            • it's very, very clear for example that art and language ritual comes from at least as far back as primates
    3. one of the reasons 00:34:46 why we don't do it is that we think there needs to also be a sudden huge change inside but actually there doesn't need to be a sudden age change inside at all
      • for: climate communications, crisis communications,
        • one of the reasons why we don't do it is that
          • we think there needs to also be a sudden huge change inside
          • but actually there doesn't need to be a sudden age change inside at all
          • that thing is funnily enough getting in the way
        • An awful lot of people who write about ecological things in the newspaper are preventing you from being ecological
        • I know that sounds a bit rude to my to my colleagues you know who write editorials for newspapers
          • but it I'm afraid it's true because you know
          • you look at page one of the newspaper and basically it says
            • you're stupid right ?
            • it gives you a whole bunch of facts that you didn't know
              • in the form mostly of quite raw data
              • it just sort of dumps the data on you which we don't do about
            • anything else we don't do it about?
              • we don't do it about racism
              • we don't do it about economics
            • we don't just dump data on on page one but we do do it regarding global warming and I think that's a bit of a problem
          • then you go on to the middle of the newspaper and you get to the editorial section
          • and the editorial section is saying
            • you're evil
            • you're a bad person
            • you're not being ecological enough
          • stupid and evil is not a good place from which to launch a successful politics or ethics or any kind of creativity
          • what is creativity fundamentally?
          • it's inviting the future
          • creativity means you're allowing the future to be different from the past doesn't it?
            • because you're creating something (new)
            • that's what creating means
            • and in order to do it successfully you actually have to be incredibly gentle
    1. n Data Feminism, Catherine D’Ignazio and Lauren Klein explore how power and oppression intersect with digital representation. While they focus mostly on data science, many of their arguments extend beyond the world of big data. Ideas like privilege hazard, the matrix of domination, asymmetrical data extraction, counterdata, data justice (as opposed to data ethics), and more are relevant to just about any work in the digital humanities. Pick a key idea from either chapter 1 or chapter 2 of Data Feminism and apply it to the digital project you’re looking at. Maybe the DH project illustrates the kind of failing that D’Ignazio and Klein critique. Maybe the DH project is an antidote to some of the problems they critique. Maybe it’s both at the same time! In any case, take some time to provide context to the idea from Data Feminism and walk us through your argument.

      The project illustrates an antidote to the failing of asymmetrical data extraction by actively seeking counterdata from indigenous communities and incorporating their perspectives into the research. By centering marginalized voices, the project challenges the matrix of domination that often marginalizes indigenous languages.

      Question: How can this project navigate the privilege hazard in data collection and ensure that data justice is truly achieved, empowering indigenous communities and fostering meaningful collaborations?

    1. Well, I'll say there's a danger in that question.  It's a good question and it's a question we should   be asking, but there's a danger, and that  is that we're going to come up with a model   for ecological community and then we're going  to make it happen. And that right away violates   everything that Nora just pointed out. That's  absolutely critically important.
      • for: ecological civilization
      • Rex
        • danger is we will build a model
        • question to Rex:
          • what then is the alternative?
          • admit we are animals
          • if we overshoot, we have to contract
    2. If you think of a plague of locusts or   a plague of mice or frogs or whatever, every  species, when it is situated in an environment   00:39:06 which for whatever set of juxtapositional  reasons is favorable to the expansion of   that species, it will explode and expand. And humans are no different. With fossil fuel,   we acquired the ability to exploit the planet  and provide all the other resources needed to   grow the human enterprise to realize  for the first time in human history,   our full exponential growth potential.
      • for:nonexceptional human
      • If you think of a plague of locusts or a plague of mice or frogs or whatever,
        • every species, when it is situated in an environment<br /> which for whatever set of juxtapositional reasons is favorable to the expansion of that species,
          • it will explode and expand.
        • And humans are no different.
        • With fossil fuel, we acquired the ability to exploit the planet and provide all the other resources needed to grow the human enterprise
          • to realize for the first time in human history, our full exponential growth potential.
          • up until about the industrial revolution, we were held in check by negative feedback.
          • The positive feedback tendencies of the species shared by all other species was held back by resource shortages, disease, war, and all of that stuff.
          • Well, fossil fuel temporarily relieved us of that, and we exploded just as a plague of locusts explodes during a favorable environment.
          • But then what that explosion does is deplete the resources and it crashes.
          • So I think we're on a one-off population boom/bust cycle, which is completely natural.
          • It just, it's never happened to humans before on a global scale
          • it has many times before on a local scale. But this time it's a global thing.
          • It's natural, it's going to happen, get used to it.
          • And Rex is right. Don't panic. Start taking care of what you can in your immediate environments.
    3. I think this is also part of  our sense of who we are as humans, as ourselves,   and the idea of the self, the individual, and  even the humans as this individual species,   these divisions are arbitrary.
      • for: emptiness, human interbeing, human interbecoming
      • example
        • BEing journey
          • I think this is also part of our sense of who we are as humans, as ourselves,
          • and the idea of the self, the individual, and even the humans as this individual species,
          • these divisions are arbitrary.
          • I don't stop at my skin.
          • I'm breathing air.
          • I'm drinking the water.
          • I'm eating food.
          • I'm eating an apple.
          • When I eat an apple, when do the molecules of the apple become me? -When I'm chewing it in my mouth?
            • when it's in my stomach?
            • when my system has broken down the nutrients?
            • when is that point that nitrogen molecule becomes me versus the apple?
          • I would propose that apple is me when it's growing on the tree.
          • I think of the blossoms of the tree and the bees.
            • The blossoms of the tree,
            • the tree can't reproduce without the bees.
            • So is the bee part of the tree?
            • The bee is part of the reproductive system of the tree.
            • So the bee is part of the tree,
            • the tree is part of the bee.
            • The bee needs the tree.
            • The tree needs the bee.
          • This is just one simple relationship,
            • but it's not simple at all because
              • the bee needs a lot of other things,
              • and the tree needs a lot of other things.
              • And the mycelium and the soil.
          • We talk about a tree and the soil and the atmosphere and the bee as if they're all separate things.
          • And that's convenient because our language has nouns that mean certain things.
          • So we want to talk about trees.
          • It's nice to have a word for tree,
            • but we get it in our head that the tree is separate from the soil,
            • which is separate from the atmosphere,
            • which is separate from the bee.
          • And I'm saying no, those divisions are indeed somewhat arbitrary,
          • but we use them for convenience.
          • But the soil's not the soil without the relationship with the tree
            • and the tree's not the tree without the relationship with the soil and the atmosphere.
            • And the atmosphere is not the atmosphere without the relationshi to the tree, to the bee, to me and the soil.
          • So to me that's the essence of ecology.
          • And that we have to expand this sense of self,
            • individual self as well as
            • the species of humans.
        • And this isolated self, I think is a socially reinforced construct, - but we get sucked into it.
          • And we talk about relationships in ecology and we talk about the value of all living things,
          • but in our actions we come back to the individual self.
    1. cements the notion that Linked Data is something that we are only intended to use to make our information more available to some search engine crawler rather than make use of for ourselves: “

      I find this argument unfair. I joined Semantic Web research in 2004 and the only widespread use of RDF seemed RSS and annotating pages for parental control. We were all looking very hard for use cases where we could use the linked data, that would stick. Schema.org lead to a major use case and the creation of trillions of triples in millions of sites. But schema.org doesn't take away from other opportunities to use data. It's just I still think that the potential here is widely underused.

    1. we're following a path that would take us to 2.7 degrees Celsius even if all the nationally determined contributions are implemented 00:07:39 by the end of this century let me just make one point very clear 2.7 degrees Celsius is without any doubt a disaster it's a point we haven't seen for the 00:07:52 past five million years there's no evidence that we can support Humanity as we know it on a 2.7 degrees Celsius planet so we really need to transition and 1.5 00:08:04 is the scientific limit that we now need to hold on to
      • for: BAU
    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Please find our point-to-point response to the reviewer’s comments below, where we marked all changes implemented in the manuscript in italics.

      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      With the emergence and spread of resistance to Artemisinin (ART), a key component of current frontline malaria combination therapies, there is a growing effort to understand the mechanisms that lead to ART resistance. Previous work has shown that ART resistant parasites harbour mutations in the Kelch13 protein, which in turn leads to reduced endocytosis of host haemoglobin. The digestion of haemoglobin is thought to be critical for the activation of the artemisinin endoperoxide bridge, leading to the production of free radicals and parasite death. However, the mechanisms by which the parasites endocytose host cell haemoglobin remain poorly understood.

      Previous work by the authors identified several proteins in the proximity of K13 using proximity-based labelling (BioID) (Birnbaum et al. 2020). The authors then went on to characterise several of these proteins, showing that when proteins including EPS15, AP2mu, UBP1 and KIC7 are disrupted, this leads to ART resistance and defects in endocytosis leading to the hypothesis that these two processes are inextricably linked.

      In this manuscript, Schmidt et al. set themselves the task of characterising more K13 component candidates identified in their previous work (Birnbaum et al. 2020) that were not previously validated or characterised. They chose 10 candidates and investigated their localisations, and colocalisation with K13, and their involvement in endocytosis and in vitro ART resistance, 2 processes mediated by K13 and some members of the K13 compartments

      The authors show that of their 10 candidates, only 4 can be co-localised with K13. Then, using a combination of targeted gene disruption (TGD) as well as knock sideways (KS), they characterised these 4 proteins found in the K13 compartment. They show that MyoF and KIC12 are involved in endocytosis and are important for parasite growth, however their disruption does not lead to a change in ART sensitivity. The authors also confirm the findings of their previous publication (Birnbaum et al. 2020), using a slightly different TGD

      (note from the authors: we apologise if this has not properly transpired from the manuscript but the difference between the TGDs is substantial and relevant: one has less than 3% of the protein left and hence can be considered to fully inactivate MCA2 and has a growth defect whereas the other contains about two thirds of the protein (1344 amino acids/~66% are left), has no growth defect, although it lacks the MCA2 domain (hence that domain can not be critical for the growth defect)),

      that MCA2 is involved in ART resistance, however they did not check whether its disruption impacts haemoglobin uptake. They also show that KIC11 is not involved in mediating haemoglobin uptake or ART resistance. To finish, the authors used AlphaFold to identify new domains in the proteins of the K13 compartment. This led them to the conclusion that vesicle trafficking domains are enriched in proteins of the K13 compartment involved in endocytosis and in vitro ART resistance.

      The majority of the experiments conducted by the authors are performed to a good standard in biological and technical replicates, with the correct controls. Their findings provide confirmation that their 4 candidate genes seem to be important for parasite growth, and show that some of their candidates are involved in endocytosis. While the KD and KS approaches employed by the authors to study their candidate genes each have their own advantages and can be excellent tools for studying a large sets or genes, this manuscript highlights the many limitations of these approaches. For example, the large tag used for the KS approach can mislocalise proteins or disrupt their function (as is the case for MyoF), resulting in spurious results, or indeed the inability to generate the tagged line (as is the case for MCA2). The KS approach also makes the results of a protein with a dual localisation, like KIC12, extremely difficult to interpret.

      We thank the reviewer for this thorough and insightful review.

      The limitations mentioned above were addressed in the response to the main points and a general detailed response in regards to the systems used for this research are added at the end of this rebuttal. Briefly summarised here: while we agree that there are limitations of the system used, we are convinced that

      • the advantages of using a large tag in most cases outweighs the drawbacks as it permits to track the inactivation of the target, if need be on the individual cell level

      • while not optimal for MyoF, the partial inactivation actually helps in its functional study as detailed in major point 23&28 or reviewer#3 major point 11: it shows a consistent correlation of the phenotype with different causes and degrees of inactivation (this is now better illustrated in Figure 1L1M). Further, regarding the concern of the large tag: the effect of the tag based on localisation was overestimated in the review by what seems to have been a mix up comparing numbers from MyoF with a number from MCA2 (there is a difference, but it is only small) (see reviewer#1 major point #23).

      • KS is the optimal method for most of the assays in this work (e.g. bloated food vacuole assays and RSAs); these assays would be impossible or difficult to use with other inactivation systems currently used in P. falciparum research (see details in the response to the specific points and after the rebuttal)

      In regards to the difficulty to interpret KIC12 data: this is only true for measuring absolute essentiality, everything else we believe we actually have the optimal method. If not KS, which method targets a specific pool of a protein with a dual localisastion? Again, our assays targeting the K13 pool and revealing the specific function would have been difficult or impossible with any other system.

      Ultimately the question is whether any other system would have resulted in a different conclusion on the function of the proteins studied. At present we are confident this would not be the case and other systems probably would not have delivered the specific functional data shown in this work. Clearly, more in depth work will provide more nuanced and detailed insights into the proteins analysed in this work and this likely will also include the use of other systems for specific aspects they are most suitable for. However, this (e.g. different complementations in a diCre cKO) is complex and therefore beyond what fits into this work which had the goal to assess which proteins are true positives for the K13 compartment and to place them into functional groups in regards to endocytosis.

      Moreover, the manuscript is disjointed at times, with the authors choosing to conduct certain experiments for only a subset of genes, but not for others. For example, considering that the aim of this paper was to identify more proteins involved in ART resistance and endocytosis, it is confusing why the authors do not perform the endocytosis assays for all their selected proteins, and why they do not do this for the proteins they identify in their domain search. There is significant room for improvement for this manuscript, and a generally interesting question.

      The reviewer remarks that not every experiment was done for every target. Based on the rebuttal we tried to amend this but also note that there was some sentiment by the reviewers to better stick to the point and not make the manuscript more disjointed. We attempted to balance that as much as possible and hope we were able to honour both aspects (amendments were done as detailed in the point by point response below).

      In regards to endocytosis and choice of targets: We did do endocytosis assays for all proteins that showed a growth phenotype upon inactivation in this work. We therefore assume the reviewer here refers to major point #40 asking for endocytosis assays with KIC4 and KIC5 (which were not studied in this manuscript) as well as MCA2 (point 17). We fully agree with the reviewer that this would fill a gap in the work on K13 compartment proteins but such assays are difficult with TGDs (there are issues with non-comparable samples and compensatory effects) and proteins that are not essential (and hence likely have a smaller impact on endocytosis when truncated). We nevertheless now carried them out, but due to the limitations to do this with these lines would be hesitant to draw definite conclusions (see major point 17 and 40 for details and outcomes).

      But in it's current format, other than confirming that MCA2 is involved in ART resistance (which was already known from the Birnbaum paper), the authors do not further expand our understanding of the link between ART resistance and endocytosis in this manuscript.

      We would like to point out that the importance of the K13 compartment and endocytosis goes beyond ART resistance (see e.g. also newly published papers on the K13 compartment in Toxoplasma, (Wan et al., 2023; Koreny et al., 2023)). Endocytosis is an essential and prominent process in blood stages. However, in contrast to processes such as invasion, our understanding about endocytosis is only rudimentary. Hence, this manuscript provides important insights on an emerging topic that in our opinion deserves more attention:

      • it identifies novel proteins at the K13 compartment and provides 2 new proteins in endocytosis (MyoF and KIC12); getting an as complete as possible list of proteins involved in the process will be critical to study and understand it

      • it leads to the realisation that not all growth-relevant proteins detected at the K13 compartment are needed for endocytosis

      • it provides domains and stage specificity of function for several K13 compartment proteins, overall bolstering the model of endocytosis in ART resistance and providing a framework critical to direct future studies on endocytosis and their detailed mechanistic function at the cytostome

      • the identified vesicle trafficking domains (for instance now also found in UBP1) are expected to strengthen the support for the role of endocytosis of the K13 compartment; this and also the above points are important as (based on the current literature) there still seems to be prominent sentiment in the field that (in part due to the involvement of UBP1 and K13) the cause of ART resistance is due to various unclearly defined stress response pathways

      • with MyoF it also shows the first protein in connection with the K13 compartment that acts downstream of the generation of hemoglobin-filled containers in the parasite and provides the first protein that explains the suspected involvement of actin in endocytosis (so far this was only based on CytD studies)

      Overall we therefore believe this manuscript contains critical information and a framework for future studies on endocytosis and the K13 compartment. We hope the relevance of endocytosis as one of the most prominent and essential processes in the parasites and the connection to various aspects linked with many commercial drugs (in addition to the role of endocytosis in ART resistance), is adequately explained in the introduction. We also would like to mention that the main focus of the work is reflected in the title of the manuscript which does not mention ART susceptibility.

      Major Comments

      1) line 31: please change defined to characterised - defined suggests that novel proteins were identified in this study, which is not the case.

      We apologise, but we do not fully understand this comment. We did identify novel proteins not before known to be at the K13 compartment (MCA2 (admittedly this one was likely but had not previously been verified), MyoF, KIC11 and KIC12). In our view "further defining the composition of the K13 compartment" therefore is an accurate statement. Additionally, the identification of previously not-discovered domains, the stage-specificity and function of these proteins helped to further define the K13 compartment.

      If the reviewer is referring to the fact that the proteins analysed in this study were taken from a previously generated list of hits, we would like to stress that the presence in such a list (obtained from a BioID, but also if from an IP etc) can not be equalled for them to be true positives, they are merely candidates that still need to be experimentally validated. This is what we did in this work to find out which further proteins from the list can be classified as K13 compartment proteins (for hits with lower FDRs this is even more relevant as illustrated by the fact that 6 of the here analysed hits were not at the K13 compartment). In an attempt to address this comment in the manuscript, we changed the wording of this sentence to (line 31): "Here we further defined the composition of the K13 compartment by analysing more hits from a previous BioID, showing that MyoF and MCA2 as well as Kelch13 interaction candidate (KIC) 11 and 12 are found at this site."

      2) line 37: please change 'second' to "another". As explained further below, the authors identified 3 classes of proteins (confer ART resistance + involved in HCCU, involved in HCCU only, or involved in neither).

      We realized that the groups description wasn’t clear in the abstract. Please see response to major comment #41 for a detailed answer to this (endocytosis is an overarching criterion, ART resistance is a subgroup and applies only to those proteins with a function in endocytosis in ring stages). To clarify this (see also major point #8) we added an explanation on the influence of stage-specificity of endocytosis on ART susceptibility to the introduction (line 76): In contrast to K13 which is only needed for endocytosis in ring stages (the stage relevant for in vitro ART resistance), some of these proteins (AP2µ and UBP1) are also needed for endocytosis in later stage parasites (Birnbaum et al., 2020). At least in the case of UBP1, this is associated with a higher fitness cost but lower resistance compared to K13 mutations (Behrens et al., 2021; Behrens et al., 2023). Hence, the stage-specificity of endocytosis functions is relevant for in vitro ART resistance: proteins influencing endocytosis in trophozoites are expected to have a high fitness cost whereas proteins not needed for endocytosis in rings would not be expected to influence resistance.” The abstract was changed in response to this and other comments and hope it is now clearer in regards to the groups.

      3) Line 40: You define KIC11 as essential but according to your data some parasites are still alive and replicating 2 cycles after induction of the knock sideways. Please consider changing "essential" to "important for asexual parasite growth".

      We fully agree with the reviewer, we reworded the sentence as suggested.

      4) Line 40: please change 'second group' to 'this group'

      We reworded this part of the abstract and it know reads: (line 38): “While this strengthened the link of the K13 compartment to endocytosis, many proteins of this group showed unusual domain combinations and large parasite-specific regions, indicating a high level of taxon-specific adaptation of this process.”

      5) line 41: state here that despite it being essential, it is unknown what it is involved in.

      With the newly added data we show that this protein either has a function in invasion or very early ring development although we did not see any evidence for the latter. We therefore changed the sentence to (line 43): “We here identified the first protein of this group that is important for asexual blood stage development and showed that it likely is involved in invasion*..” *

      6) Line 50: the authors should state here that there is actually a reversal in this trend over the last few years.

      Done as suggested.

      7) Line 54: please separate out the references for each of the two statements made in this line (a: that ART resistance is widespread in SEA, and b: that ART resistance is now in Africa) Reference 14 also seems to reference ART resistance in Amazonia - which is not covered by the statement made by the authors (in which case the authors should state ART is now present in Africa and South America). The authors should also reference PMID: 34279219 for their statement that ART resistance is now found in Africa (albeit a different mutation to the one found in SEA).

      Done as suggested.

      8) Line 65: it is also worth mentioning here that there are other mutations in proteins other than K13, such as AP2mu and UBP1 (PMID: 24994911;24270944) that can lead to ART resistance.

      As suggested by the reviewer, we included a sentence about non-K13 mutations linked with reduced ART susceptibility in the introduction (line 74): Beside K13 mutations in other genes, such as Coronin (Demas et al., 2018) UBP1 (Borrmann et al., 2013; Henrici et al., 2020b; Birnbaum et al., 2020; Simwela et al., 2020) or AP2µ (Henriques et al., 2014; Henrici et al., 2020b)* have also been linked with reduced ART susceptibility." *

      We here also added data on fitness cost that is related to this and is also relevant for the issue of proteins with a stage-specific function in endocytosis, making a transition for this statement which might help clarifying the grouping of K13 compartment proteins (see also major point #2).

      9) Line 80, 86: ref 43 is misused. Reference 43 refers to Maurer's clefts trafficking which takes place in the erythrocyte cytosol and is not involved in haemoglobin uptake as far as I know. Please replace ref 43 with one showing the role of actin in haemoglobin uptake.

      We thank the reviewer for pointing this out, Ref 43 was removed from the manuscript.

      10) Line 98: the authors state here that they 'identified' further candidates from the K13 proxiome. This suggests that they identified new proteins in this paper, when in fact the list was already generated in ref 26. All they did was characterise proteins from that list that were not previously characterised. The authors should therefore remove identified from this statement.

      We agree with the reviewer that we did not identify further candidates, we identified new K13 compartment proteins from the list of potential K13 compartment proteins. We therefore changed “identified further candidates” into “identified further K13 compartment proteins” (line 116). Please see also response to major comment #1.

      11) Line 107-108: it is not clear from this sentence why these proteins were left out of the initial analysis in Ref 26. A sentence here explaining this would be valuable for the reader.

      This is a good point. One reason why we did not analyse more in our previous publication was that we had to stop somewhere and adding more would have been very difficult to fit into what was already a packed paper. However, as shown in this work, the list does contain further interesting candidates (e.g. K13 compartment proteins that are involved in endocytosis).

      We altered the relevant part of the introduction to highlight that we previously analysed the top hits, clarifying that the 'remaining' hits analysed in this work were further down in the list. This now reads: (line 113)“We reasoned that due to the high number of proteins that turned out to belong to the K13 compartment when validating the top hits of the K13 BioID (Birnbaum et al., 2020), the remaining hits of these experiments might contain further proteins belonging to the K13 compartment.” We hope this clarifies that we simply moved further down in the candidate list.

      12) Line 117-123: The authors say that PF3D7_0204300, PF3D7_1117900 and PF3D7_1016200 were not studied because they were not in the top 10 hits. However, the current organisation of Supplementary Table 1 shows all 3 proteins among the top 10 hits (MyoF, KIC12, UIS14 and 0907200 being after them). I think the authors should reorganise their table. It is also unclear according to what the proteins in the table are ranked. Could the authors indicate the metric used for the ranking?

      We thank the reviewer for alerting us to this. The issue here is that the 3 non-analysed proteins belong to a 'lower stringency' group comprising hits significant with FDRThe information about ranking is now also included as “Table legend” in the revised manuscript and the Table heading has been changed to: List of putative K13 compartment proteins, proteins selected for further characterization in this manuscript are highlighted.”

      13) Line 129-141: Can the authors be clearer with their explanations of the identification of mutation Y1344Stop? One dataset (ref 61) shows that 52% of African parasites have a mutation in MCA2 in position 1344 leading to a STOP codon. But another dataset (ref 62) shows that the next base is also mutated, reverting the stop codon. That should have been seen in the first dataset as well. Could the authors please clarify.

      This mutation was first spotted in the MalariaGEN database (https://www.malariagen.net) (MalariaGEN et al., 2021), which allows online accessing of the data by using the “variant catalogue” tool, which is in a table format of frequency rather than in a sequence context. Hence, only after further research later on it became evident to us, that this mutation does not occur alone when looking at individual MCA2 sequences from patient samples in (Wichers et al., 2021b). We hope this is accurately reflected in our results section.

      14) Line 147: the authors say that MCA2 is expressed throughout the intraerythrocytic cycle as shown by live cell imaging. In Birnbaum et al 2020 fig 4I, the authors show that MCA2 is mainly expressed between 4 and 16hpi. But in Figure 1B of this manuscript there is a clear multiplication of MCA2 signal between trophozoite and schizont. How do the authors explain this discrepancy? Could expression of the truncated MCA2 be different than the full length? This cannot be assessed as expression and localisation of the full-length HA tag MCA2 is not shown in Schizonts.

      The key difference lies in transcription vs protein expression (usually protein levels peak after mRNA levels peak and - depending on turnover - protein levels can stay high even after mRNA levels have declined). Figure 4 of the Birnbaum et al paper presents transcriptomic data, but with a peak in trophozoites (The axis label in Fig. 4l of that publication is a bit confusing, as hour 0 is at the top, 48 h at the bottom; it is clearer in Fig. S13 of that paper) which would fit very well with the multiplication of the signal between trophozoites and schizonts mentioned by the reviewer. So, overall, the temporal peaks of transcripts and protein of that protein fit well.

      For the signal in rings: Likely the protein has a turnover rate that is sufficiently low for some protein to be taken into the new cycle after re-invasion. Also different transcriptomic datasets e.g. (Otto et al., 2010; Wichers et al., 2019; Subudhi et al., 2020) available on plasmoDB show some mRNA present across the complete asexual development cycle, with each dataset showing maximum peak at a slightly different stage.

      Even when located in foci and hence aiding detection of small amounts of protein (as is the case for MCA2-Y1344-GFP), the MCA2 signal in rings is not strong. For MCA2-TGD, the GFP signal is dispersed and therefore likely below our detection limit, while the same amount of protein concentrated at the K13 compartment is visible as foci in the MCA2-Y1344 cell line. Please note that MCA2-TGD has only 2.8% of the protein left whereas MCA2-Y1344 has 66.5% left and based on our manuscript is almost fully functional, hence fitting the different locations between the two versions.

      Overall we believe this shows that there are actually no significant discrepancies of the expression of the different MCA2 versions.

      15) Line 158: would it not have been more useful for the authors to have episomally expressed MCA2-3xHA in their MCA2Y1344STOP-GFPENDO line to make sure that the truncated protein is indeed going to the correct compartment? The experiments done by the authors suggests that the MCA2Y1344STOP goes to the right location but does not really confirm it.

      We appreciate the reviewers caution here. However, considering that MCA2Y1344STOP-GFPendo co-locates with mCherryK13 and endogenously HA-tagged full length MCA2 does the same to a similar extent, there is in our opinion little doubt that MCA2 is found at the K13 compartment and that this is similar with both constructs. If there are minor differences, these might as well occur if MCA2 is episomally (as suggested in the comment) instead of endogenously expressed. Given the limited insight, we therefore decided against the episomal overexpression (which due to its size of > 6000bp may also be somewhat less straight forward than it may sound).

      16) Line 191: it is stated that MCA2 confers resistance independently of the MCA domain, however in both the MCA2-TGD and MCA2Y1344STOP-GFPENDO parasites, the MCA domain is deleted, and for both parasites, there is resistance (albeit to a lower level in the MCA2Y1344STOP-GFPENDO line). Therefore, how can the authors state that the ART resistance is independent of the MCA domain? This statement should be that resistance is dependent on the loss of the MCA domain.

      We agree that this can’t be categorically excluded. However, a ~5 fold difference in ART sensitivity was observed between the parasites with MCA2 truncated at amino acid 57 compared to those with MCA at amino acid 1344 even though both do not contain the MCA2 domain. Hence, at least this difference is not dependent on the MCA2 domain. The larger construct missing the MCA domain shows only a very moderate reduction in RSA survival, again suggesting the MCA domain is not the main factor. We amended our statement in an attempt to more accurately reflect the data (line 487): This considerable reduction in ART susceptibility in the parasites with the truncation at MCA2 position 57 compared to the parasites still expressing 1344 amino acids of MCA2, despite both versions of the protein lacking the MCA domain, indicates that the influence on ART resistance is not, or only partially due to the MCA domain.” We would be hesitant to state the reviewer's conclusion that “resistance is dependent on the loss of the MCA domain”, as the larger construct missing the MCA2 domain has a milder RSA effect compared to MCA2-TGD, which suggests the reduction in ART susceptibility is independent of the MCA domain. These considerations also agree with the fact that the parasites with the longer MCA2 version (in contrast to the MCA2-TGD) do not have any detectable growth defect which indicates that the protein can fulfil its function without the MCA2 domain.

      17) Line 192: Why did the authors not check if MCA2 is involved in endocytosis? They state later on in the manuscript that they did not do endocytosis assays with TGD lines, however if the authors include the correct controls, this could be easily done. It would also be really interesting to see whether endocytosis gets progressively worse going from WT to MCA2Y1344STOP to MAC2TGD. This experiment (as well as doing endocytosis assays for KIC4 and KIC5 TGD lines) would drastically increase the impact of this study. These experiments would not take more than 3 weeks to perform, and would not require the generation of new lines.

      So far were very hesitant to do bloated FV assays with TGDs (even though TGDs were available for the genes encoding MCA2 and KIC4 and KIC5). The reason for this was:

      1. the fact that these proteins could be disrupted indicated either redundancy or only a partial effect on endocytosis which might lead to only small effects that likely are difficult to pick up in an assay scoring for the rather absolute phenotype of bloated vs non-bloated. Using the refined assay measuring FV size could partly amend this but we note that also FV without hemoglobin have a certain size, reducing the relative effect if there are smaller differences.
      2. a TGD line does not permit tightly controlled inactivation of the target which makes comparing the outcome of bloated food vacuole assays difficult if there are smaller growth and stage differences to the 3D7 control.
      3. in contrast to conditional inactivation parasites, the TGD lines had ample times to adapt to loss of the target protein (compensatory mechanisms are well known for endocytosis, for instance in clathrin mediated endocytosis loss of individual components can be compensated (Chen and Schmid, 2020)). We nevertheless see the reviewer's point that this should at least be attempted and now conducted these assays (see also major point 40). For MCA2 (as requested in this point), the data is shown in Figure S5C-E. This assay showed that in MCA2-TGD, MCA2Y1344STOP-GFPendo (similar to the 3D7 control) >95% of parasites developed bloated food vacuoles. Additionally, we also measured the parasite and food vacuole size of individual cells in an attempt to solve some of the problems with TGDs with such assays. In order to specifically solve problem 2 mentioned above, we analysed the food vacuoles of similarly sized parasites, however, they were non-distinguishable between the three lines. Of note, in agreement with the reduced parasite proliferation rate (Birnbaum et al., 2020) a general effect on parasite and food vacuole size was observed for MCA2-TGD parasites, indicating reduced development speed in these parasites. Hence, it is possible that a potential endocytosis reduction was accompanied by a slowed growth, and the comparison of similarly sized parasites may have obscured the effect. It is therefore not sure if there indeed is no endocytosis phenotype, although we can exclude a strong effect in trophozoites.

      Based on the RSA results at least rings can be expected to have a reduced endocytosis in the MCA2-TGD. Apart from options 1-3 mentioned above, it is therefore possible there is an effect restricted to rings, although in that case the reduced growth in trophozoites would be due to other functions of MCA2. Overall, we can conclude that the MCA2-TGD parasites do not have a strongly reduced endocytosis, but given the fact that the parasites are viable, this is not surprising. Whether the MCA2-TGD has no effect at all on endocytosis we would be very hesitant to postulate based on these results.

      18) The authors should consider re-organising the MCA2 section, first showing that the 3xHA tagged line colocalises with K13, then performing the new truncation.

      We attempted to re-organise as suggested but because we now included additional fluorescence microscopy images of schizont and merozoites (in response to reviewer 2 major comment 3) the main figure would become even larger. To prevent this, we kept the 3xHA data in the supplement.

      19) Line 197: Once again ref 43 is not correct to illustrate that actin/myosin is involved in endocytosis

      We thank the reviewer for pointing this out – we removed Ref 43.

      20) Line 202: the authors state that MyoF localises near the food vacuole from ring stage/trophs onwards. However, how can this statement be made in schizonts based on these images (Fig. 2A), where it doesn't look like MyoF is anywhere near the FV? This statement can only be made for schizonts if co-localised with a FV marker (which is done in Fig. 2B), however, based on the number of MyoF foci, it appears that this was not done for schizonts. Please either remove the statement that MyoF is near the food vacuole from trophs onwards (because it is only seen near the FV up until trophs) or show the data in Fig. 2B of schizonts to substantiate these claims.

      This is a valid point. We originally did not focus on schizonts because most markers end up in some focal area in the forming merozoite but other proteins (such as e.g. K13) also have one or more additional foci at the FV, making interpretation unclear, particularly if the schizont is still organizing to become fully segmented. This is why we generally focused the K13 co-localisations on the trophozoite stage to obtain the clearest information on endocytosis. However, given the fact that this manuscript gives the first localization of MyoF in P. falciparum parasites, we now provide a comprehensive time course (Figure 1C, S1A) including schizonts, which show quite a complex pattern: while the MyoF-GFP localization in trophozoites appeared as multiple foci close to K13 and also the FV, the MyoF-GFP pattern changes in late schizonts (fully segmented) and merozoites, appearing as elongated foci no longer close to K13 or the FV. Of note, this pattern has been previously reported for MyoE in P. berghei (Wall et al., 2019).

      We therefore revised the statement about MyoF localization in schizont to better reflect the observed localization: (line 175): In late schizonts and merozoite the MyoF-GFP signal was not associated with K13, but showed elongated GFP foci (Figure 1C, S2A) reminiscent of the MyoE signal previously reported in P. berghei schizonts (Wall et al., 2019).”

      21) Line 204-206: what does this statement bring to the paper? Is it to show that it is the real localisation of MyoF because 2 tag cell line show the same localisation? I don't think this is needed, especially as later in the manuscript an HA-tag MyoF line is used and show similar localisation.

      We see the reviewers point, but prefer to keep this data included in the supplement, particularly because potential differences in the location of tagged MyoF were a major concern.

      Related to the tag issue: in order to get a better understanding of the effect of C-terminally tagging with different sized tags we now performed a more detailed analysis of the MyoF-3xHA cell line (Figure S2F-G), showing that this cell line shows a growth rate similar to the 3D7 wild type parasites, and has less vesicles than the 2x-FKBP-GFP-2xFKBP cell line, but still slightly, but significantly more than 3D7 parasites. Overall, this indicates that the smaller 3xHA tag has less effect on the parasite, than the larger 2x-FKBP-GFP-2xFKBP tag (see also new Figure 1L, showing a correlation of level of inactivation and the endocytosis phenotype for MyoF).

      22) Line 212: The overlap of K13 with MyoF in Figure 2C 3rd panel (1st trophozoite panel) is not obvious, especially as the MyoF signal seems inexistant. I would advise the authors to replace with a better image. Also, why are there no images of schizonts shown in Figure 2C?

      As suggested we exchanged the trophozoite image of panel Figure 2 C (now Figure 1C) and expanded this panel with images covering the complete asexual development cycle including schizonts in response to this and the previous points. As indicated above (point 20), schizont stages are complex to interpret. While late schizonts likely are not very relevant for endocytosis this is the first description of the location of the protein in this parasite and we therefore now provide a more thorough representation of the MyoF location across asexual stages in Figure1C and S2A.

      23) Line 217: the spatial association of MyoF with K13 is very different when it is tagged with GFP and when it is tagged with 3xHA. The way the authors word it here, it seems that there is agreement with the two datasets, when this is not in fact the case (59% overlap for MyoF-GFP and only 16% overlap with MyoF-3xHA). These data suggest that the GFP and the multiple FKBP tags are doing something to the protein and therefore maybe the ensuing results using this line should not be trusted or be taken with a pinch of salt.

      We agree with the reviewer that the location of this MyoF-GFP in the cell might differ due to the partial inactivation but in contrast to this comment, the data does not indicate any large differences. It seems the reviewer mixed something up (the 59% mentioned might come from the MCA2 figure?). The data with the two lines with differently tagged MyoF co-localised with K13 are actually quite comparable: GFP-tagged vs HA-tagged MyoF overlapping with K13 was 8% vs 16% full overlap, 12% vs 19% partially overlapping foci, 36% vs 63% foci that were touching but not overlapping (compare what now is Figure 1D and Figure S2C). Only in the 'no overlap' there is a much smaller proportion in the HA-tagged line. However, given that these are IFAs which on the one hand are more sensitive to see small protein pools but on the other hand also have pitfalls due to fixing of the cells (e.g. tiny increase in focus size due to fixing could increase the number of touching foci that in live cells might be close but did not touch), some variation can be expected to the live cells. We agree though that the partly reduced functionality of MyoF might be the reason for the consistent tendency of a lower overlap even though the difference is much less than indicated in the comment. We added "with a tendency for higher overlap with K13 which might be due to the partial inactivation of the GFP-tagged MyoF" to the sentence "IFA confirmed the focal localisation of MyoF and its spatial association with mCherry-K13 foci"

      While we expect the fact that the difference between these parasites is only small somewhat reduces the "pinch of salt" with the MyoF line, we do agree that the partial functional inactivation of the GFP-tagged MyoF line may have some impact. However, we do not think that this means the results with the MyoF-GFP line are untrustworthy. On the contrary, it provides insights into its function that in some ways is equivalent to a knock down or TGD. Overall all the MyoF lines show: few vesicles occur in the MyoF-HA-line, more in the MyoF-GFP line and even more after knock sideways of MyoF-GFP. Importantly the severity of this phenotype correlates with the growth rates in these lines. Hence, together with the bloated food vacuole assays, this provides consistent data indicating that MyoF has a role in the transport of HCC to the FV and its level of activity correlates with the number of vesicles and growth. To better highlight this, it is now summarised in Figure 1M.

      24) Line 219: the authors state here that they could not detect MyoF-GFP in rings, when in Figure 2C they show MyoF-GFP in rings, and also show that they could detect MyoF in Sup Fig. 3B with the 3xHA tagged line. Is this a labelling mistake in Figure 2C? If the authors could indeed not see MoyF-GFP in rings, this statement should have been made when Figure 2A was presented, and not so late in the manuscript, which causes confusion.

      We thank the reviewer for pointing this out. We now provide a detailed time course (see also previous points) which shows that there is no detectable MyoF-GFP signal during ring stage development until the stage where the parasites starts the transition to trophozoites (i.e. MyoF-GFP signal could only be observed in parasites already containing hemozoin). In addition to the extended time course in Figure 1C (previously 2C) we included a panel of example ring stage images below to further highlight this. We also changed the labelling of the parasite with MyoF-GFP signal the reviewer mentions in Figure 1C to “late ring stage” (it already contains hemozoin) to clarify this.

      The description of Figure 1A is now changed to: (line 153) *“The tagged MyoF was detectable as foci close to the food vacuole from the stage parasites turned from late rings to young trophozoite stage onwards, while in schizonts multiple MyoF foci were visible (Figure 1A, S2A).” *

      Please see our answer to major comment #45 where we provide an explanation for the difference between MyoF-3xHA and MyoF-GFP signal in ring stage parasites.

      [Figure MyoF]

      25) Line 237: Showing a DNA marker (DAPI, Hoecht) for Figure 2E, and subsequent figures using mislocalisation to the nucleus, would help the reader assess efficiency of the mislocalisation.

      Please see response to major comment #64 for a detailed answer on why we did not include DNA staining in the imaging used to assess mislocalization upon knock-sideways.

      26) Line 254-256: authors should show the results of the bloating assay for parental 3D7 parasites (+ and - rapalog) to see whether the MyoF line - rapalog has increased baseline bloating. This applies to all subsequent FV bloating assays.

      We did do several controls for bloated assays (including +/- rapalog of an irrelevant knock sideways line as well as using a chemical insult for which the control was 3D7 without treatment) in previous work (Birnbaum et al., 2020), which indicated that there is no effect of rapalog to reduce bloating. Although these controls are more stringent, we nevertheless did a 3D7 +/- rapalog control and added this to the manuscript (Figure S2I). As it is not possible to do this side by side with the assays that are already in the manuscript and the +/- rapalog 3D7 cells consistently showed no or very low numbers of cells without bloating (and stringent controls in the past equally did not show an effect), we believe adding this control once suffices.

      27) Line 254-257: The authors say that because fewer parasites show a bloated food vacuole upon inactivation of MyoF it means that less hemoglobin reached the food vacuole. I understand the authors statement, however, shouldn't they look at the size of the food vacuole, instead of the number of parasites with bloated FV, to make such a statement? This has been done for KIC12 so why not doing it for MyoF?

      This was now done and is provided as Figure 1J-K, S2J. The results confirm the assessment scoring bloated vs non-boated food vacuoles.

      28) Line 259-261: these results would be difficult to interpret namely because the authors have dying parasites, which is exacerbated with the protein being knocked sideways. The authors should mention the pitfalls their knock sideways and tagging design here. Line 260-261: RSA is an assay relying on measuring parasite growth 1 cycle after a challenge with ART for 6 hours.

      Fortunately, this concern is unfounded, as the survival (measured by parasitemia after one cycle) of the same sample + and - DHA is assessed, isolating the DHA effect independent of potential growth defects which are cancelled out. Hence, if there were parasites dying in the MyoF line (please note that they might not actually die, but simply grow more slowly), this factor applies for both the + and - ART condition. As we are testing for a decreased susceptibility to ART which would manifest as an increased survival in RSA surfacing above 1%, antagonistic effects of reduced MyoF function and ART treatment would not result in detectable differences as without effect, the RSA survival is always close to zero.

      The same applies for the knock sideways where we assess the survival of +rapalog between +ART and -ART. If the reduced MyoF activity of the knock sideways leads to a decreased survival, this applies to both +ART and -ART. Please also note that rapalog was lifted after the DHA pulse (see e.g. Figure S2K).

      That effects on growth are cancelled out is nicely illustrated for proteins where there is a stronger and more rapid effect on growth upon their conditional inactivation. For instance when KIC7 is knocked aside, there is a considerable increased of RSA survival, even though continued inactivation of KIC7 would have a severe growth defect (Birnbaum et al., 2020). Vice versa, a growth defect alone does not result in reduced RSA susceptibility as evident from knock sideways of an unrelated protein or using a chemical insult (Figure 4H in (Birnbaum et al., 2020) or simply slowing the ring stage by e.g. reducing EXP1 levels (Mesén-Ramírez et al., 2019). Hence, a growth reduction is not expected to alter the RSA outcome. And even if it did, it would only lead to an underestimation of the readout if growth is too severely affected (which would be obvious in the + rapalog without DHA sample, which was not the case).

      In that respect it is valuable to have the rapid kinetics of knock sideways which permit inactivation of a protein before severe growth defects occur (although the only partial responsiveness of MyoF clearly is not the most optimal). In contrast, the absolute loss of a gene (as is the case if diCre is used) prevents (or at least makes it extremely difficult as the timing would need to exactly hit sufficient protein reduction without killing the parasite until the end of the RSA) using this system in these experiments (again see (Mesén-Ramírez et al., 2021) where in a EXP1 diCre based knock out RSA was only possible because we complemented with a lowly, episomally expressed EXP1 copy to have parasites with only a partial phenotype to do this assay).

      29) Line 261-263: the authors sate that MyoF has a function in endocytosis but at a different step compared to K13 compartment proteins. I am not sure what they mean here. Can this be clarified?

      The different steps in endocytosis are explained in the introduction and we now tried to further clarify this (line 98). So far VPS45 (Jonscher et al., 2019), Rbsn5 (Sabitzki et al., 2023), Rab5b (Sabitzki et al., 2023), the phosphoinositide-binding protein PX1 (Mukherjee et al., 2022), the host enzyme peroxiredoxin 6 (Wagner et al., 2022) and K13 and some of its compartment proteins (Eps15, AP2µ, KIC7, UBP1) (Birnbaum et al., 2020) have been reported to act at different steps in the endocytic uptake pathway of hemoglobin. While inactivation of VPS45, Rbsn5, Rab5b, PX1 or actin resulted in an accumulation of hemoglobin filled vesicles (Lazarus et al., 2008; Jonscher et al., 2019; Mukherjee et al., 2022; Sabitzki et al., 2023), indicative of a block during endosomal transport (late steps in endocytosis), no such vesicles were observed upon inactivation of K13 and its compartment proteins (Birnbaum et al., 2020), suggesting a role of these proteins during initiation of endocytosis (early steps in endocytosis).

      VPS45 has not apparent spatial connection to the K13 compartment but the fact that MyoF does - and its inactivation also results in vesicle accumulation - indicates that it is downstream of vesicle initiation, providing the first connection from the initiation phase to the transport phase. More evidence for these different steps of endocytosis has been published in a recent preprint from our lab, where we simultaneously inactivated a protein of both “endocytosis steps” (Sabitzki et al., 2023).

      To clarify this in the results as requested, we changed the statement to: (line 256) Overall, our results indicate a close association of MyoF foci with the K13 compartment and a role of MyoF in endocytosis albeit not in rings and at a step in the endocytosis pathway when hemoglobin-filled vesicles had already formed and hence is subsequent to the function of the other so far known K13 compartment proteins.”

      30) Do the authors mean that it is involved in endocytosis but not in ART resistance? If so, this is a very difficult statement to make since the parasites are dying. Is there any evidence of point mutations in MyoF in the field?

      We split this point to address all issues raised here. Please see response to point 29 which clarifies that this was meant in a different way and our response to point 28 which explains why the dying parasite issue is not expected to affect the RSA (please also note that we do not have evidence of actually dying parasites in the MyoF-2xFKBP-GFP-2xFKBP line, most likely the growth is slowed).

      The mutation issue is interesting. In fact evidence exists that MyoF mutations may be associated with resistance (Cerqueira et al., 2017) (please note that there it is still called MyoC) but in a recent preprint from our lab we did not find any evidence for a significantly changed RSA survival in 12 tested mutations in the corresponding gene (Behrens et al., 2023).

      To clarify this we added the following statement to the discussion (line 709): "Of note, mutations in myoF have previously been found to be associated with reduced ART susceptibility (Cerqueira et al., 2017), but 12 mutations tested in the laboratory strain 3D7 did not result in increased RSA survival (Behrens et al., 2023)*. *

      31) Line 298: the authors state that there is no growth defect in the first cycle when rapalog is added to the KIC11 line, however based on Figure 3D, there is evidently a 25% reduction in growth compared to - rapalog at day 1 post treatment, and a 60% reduction by day 2, which is still within the 1st growth cycle. The authors should either revise their statement or provide an explanation for these findings. The authors should also explain why their Giemsa data in Fig. 3E is not in accordance with their FACS data.

      We think there is a misunderstanding here, as our figure legend was not detailed enough and we apologise if this had been misleading. The growth effect is restricted to invasion or possibly the first hours of ring stage development (see point 4&5, reviewer 2), which in asynchronous cultures more rapidly takes effect as the culture also contains schizonts that immediately generate cells that re-invade but can't due to inactivation of KIC11 (due to the rapid action of the knock sideways, KIC11 is already inactivated). In contrast, in highly synchronous cultures, this effect can only be evident once the parasites reached the schizont stage (starting with rings this takes close to 2 days). We now clarify that Figure 2E (previously Figure 3D) shows growth data obtained with an asynchronous parasite culture, while in Figure 2F the growth assay is performed with tightly synchronized (4h window) parasites as stated in the Figure legend.

      We now explicitly state in each Figure legend and for each growth experiment throughout the manuscript whether we used asynchronous or synchronized parasites for growth assays.

      Related to this, the incorrect y-axis label of what is now Figure 2E mentioned in major comment #58 is now corrected.

      32) Line 301: KIC11 could also be important very early for establishment of the ring stage for example for establishment of the PV. Also, was mislocalisation assessed in rapalog-treated parasites at 72 hours or in cycle 3?

      This is a valid point and this has now been addressed. We performed an invasion/egress assay revealing similar schizont rupture rates, but significantly reduced numbers of newly formed ring stage parasites (Figure 2H, S3G), indicating an effect of KIC11 inactivation either on invasion or possibly the first hours of ring stage development. A very similar point was raised by Reviewer 2, please see reviewer 2; major comment #4. This is now also reflected in line 302, which now reads: ”… indicating an invasion defect or an effect on parasite viability in merozoites or early rings but no effect on other parasite stages (Figure 2F-H, Figure S3F-G).”

      We further included an assessment of mislocalization 80 hours after the induction of knock-sideways by addition of rapalog in Figure S3E which showed mislocalization of KIC11 to the nucleus.

      33) Line 311: the authors should change the sentence from 'not related to endocytosis' to 'not related to endocytosis or ART resistance'.

      Done as suggested.

      34) Line 323-325: Authors say that a nuclear GFP signal can be observed in early schizonts for KIC12. According to the pictures provided in Figure 4A and Figure S5A it is not very obvious. Also faint cytoplasmic GFP signal could only be background as we can see that exposure is higher for schizont pictures

      We changed the sentence (line 339) to: “…nuclear signal and a faint uniform cytoplasmic GFP signal was detected in late trophozoites and early schizonts and these signals were absent in later schizonts and merozoites (Figure 3A, Figure S4A,B).” in order to emphasize that the nuclear signal disappears early during schizont development.

      35) Line 326-328: The authors say that kic12 transcriptional profile indicate mRNA levels peak (no s at peak) in merozoites. Should they show live cell imaging of merozoites then? Because from the Figure 4A schizont pictures where schizonts are almost fully segmented no signal can be observed.

      The observation that mRNA levels of early ring stage expressed proteins tend to increase already in mature schizonts and merozoites is well established (e.g. (Bozdech et al., 2003)). A very good example for this are exported proteins of which most show a transcription peak in schizonts but the proteins are only detected in rings see e.g. (Marti et al., 2004). Hence, our observation for KIC12 is quite typical.

      We originally did not include merozoites, as in the last row of Figure 3B fully developed merozoites within a schizont with already ruptured PVM are shown and no GFP signal can be detected in these parasites. We now provide images of free merozoites in Figure S4A-B showing again no detectable GFP signal.

      We thank the reviewer for pointing out the typo, "peak" has been corrected.

      36) Line 347: The authors state that using the Lyn mislocaliser the nuclear pool of KIC12 is inactivated by mislocalisation to the PPM. This tends to suggest that only the nuclear pool of KIC12 is mislocalised. How is it possible that only the nuclear pool is mislocalised?

      The Lyn mislocaliser is at the PPM which is continuous with the cytostomal neck where the K13 compartment likely is found. The effect of the Lyn mislocalizer on the KIC12 protein pool localizing at the K13 compartment is therefore somewhat unclear. For this reason we already had the following statement in the original submission (line 400): “Foci were still detected in the parasite periphery and it is unclear whether these remained with the K13 compartment or were also in some way affected by the Lyn-mislocaliser.” We would like to stress here that the same does not apply to the nuclear mislocaliser, which is only a trafficking signal delivering KIC12 to the nucleus and hence likely does not affect the nuclear pool of KIC12, only the K13 compartment pool (the main interest of this manuscript).

      We realised that the statement towards the end of this paragraph was unnecessarily ambiguous in regards to the K13 compartment pool of KIC12 which might have caused some confusion about the function of this pool of KIC12 and therefore modified it to (line 374): "Due to the possible influence on the K13 compartment located foci of KIC12 with the Lyn mislocaliser, a clear interpretation in regard to the functional importance of the nuclear pool of KIC12 other than that it confirms the importance of this protein for asexual blood stages is not possible. In contrast, the results with the nuclear mislocaliser indicate that the K13 located pool of KIC12 is important for efficient parasite growth.". It is also important to note that this limitation does not apply to the NLS knock sideways in regard to the K13 compartment and that the endocytosis function of this pool of KIC12 seems solid which with this statement is enforced.

      37) Line 368-369: Effect was also only partial for MyoF. Why didn't you measure the same metrics for MyoF?

      This was now done and is provided as Figure 1J-K, S2J, confirming our previous interpretation, see also point #27 which raises the same point.

      38) Line 379: you don't know if all proteins acting later in endocytosis will have an increased number of vesicles as a phenotype

      This is based on our current definition as stated in the introduction. It assumes a directional vesicular transport of hemoglobin to the food vacuole where inhibition of early stages will prevent transport before HCC-filled autonomous vesicular containers have formed and entered the cell. In contrast later inhibition stops such containers from further transport, leading to their accumulation. Such an accumulation is visible after VPS45-inactivation and other proteins (Jonscher et al., 2019; Mukherjee et al., 2022; Sabitzki et al., 2023) or treatment with cytochalasin D (Lazarus et al., 2008). While it is possible that there may be smaller intermediates formed at the K13 compartment that later on unite or fuse with the compartment evident after VPS45 inactivation and these might be missed due to small size (i.e. inhibition of a step between K13 compartment and an early endosome or equivalent), this would still be upstream of the VPS45 induced containers and hence would be earlier. We therefore believe that based on the framework given in the introduction (see also (Spielmann et al., 2020)) to assume that a phenotype manifesting as reduced food vacuole bloating without formation of detectable vesicles likely signifies inhibition of the process early whereas reduced bloating but with vesicles signifies inhibition later in the process.

      39) Line 413-414: The authors state that no growth defect was observed upon KS of 1365800. Is growth alone enough to say that there is no impact on endocytosis?

      This is an interesting point. The endocytosis proteins we studied so far indicate that efficient impairment of endocytosis manifests as a severe growth defect. Hence, lack of a growth defect can be assumed to be an indicator for absence of an important role for endocytosis (or any other growth relevant process). Clearly there is a gradual response, such as seen in the different MyoF versions resulting in proportional growth and vesicle appearance phenotypes. Hence, a protein with a minor role might have slipped our attention but then it probably is also not a very important protein in endocytosis.

      To further strengthen our assessment of PF3D7_1365800 importance for asexual blood stage development, we now also generated a cell line expressing the PPM Mislocalizer, enabling knock sideways to the PPM. This was done because this protein consistently has a focus at the nucleus that may be within the nucleus. Again this revealed no growth defect upon inactivation (Figure S7D).

      40) Line 432: in this section, the authors state that KIC4 and KIC5 seem to have domains that may suggest these proteins are involved in endocytosis, based on the alpha fold data that is publicly available. Considering the authors have TGD-SLI versions of these lines (Birnbaum et al. 2020) and have already confirmed in this previous publication that they confer resistance to ART; it would make sense to look at endocytosis for these genes. This would be a relatively simple and straightforward experiment, taking no longer than two to three weeks, and would require no additional reagents or line generation. Doing these experiments would add a lot more weight to this final section. The authors later state that KIC4 and 5 are TGD lines, so not the best for endocytosis assays. It is unclear why this would be difficult to do if an adequate control is contained in the experiment (such as parental 3D7). It explains why they did not perform the MCA2 endocytosis assays further up, but in my opinion, an attempt at doing these assays is important and would significantly increase the impact of this paper. Identical as major comment #17.

      As stated in the manuscript and above, we were originally hesitant to do these assays due to the fact that we can't induce inactivation which is less ideal than comparing the identical parasite population split into plus and minus and is further complicated by the likely smaller effect as the TGDs still permitted growth. However, we see the point of the reviewer and now performed these assays using 3D7 as controls and taking extra care to account for stage differences between the TGD lines and 3D7. However, there was no significant difference in the bloated food vacuole assays with these cell lines. Due to the reasons mentioned in major point 17, we are not sure this indeed means these proteins have no role in endocytosis. One possible reason why we were able to obtain these TGDs may have been because the effect on endocytosis is less than in the essential proteins (or is ring stage specific) and in a TGD an endocytosis defect may therefore not be detectable with our assays (see details and further possible explanations in response to point 17).

      In an attempt to address the TGD issue, we generated knock sideways cell lines for KIC4 and KIC5. Unfortunately, the mislocalization of KIC5 to the nucleus was inefficient (see figure below). As this did not result in a growth defect (in contrast to the clear KIC5-TGD growth defect (Birnbaum et al., 2020)), this line is not suitable to study a potential role of this protein in endocytosis. Therefore, we performed the bloated food vacuole assay only with KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites. However, this revealed no effect on HHC uptake, which is in line with the normal growth of KIC4-TGD parasites (Birnbaum et al., 2020) and suggests that this protein could only have a minor or redundant role in endocytosis (it is the line that shows the smallest effect in RSA). As the KIC4 and KIC5 knock sideway lines did not permit any conclusions, we did not include them into the revised manuscript but they can be found here:

      [Figure KIC4 knock sideways & KIC5 knocksideways]

      Figure legend: (A) Live-cell microscopy of knock sideways (+ rapalog) and control (without rapalog) KIC4-2xFKBP-GFP-2xFKBPendo+ 1xNLS mislocaliser parasites 4 and 20 hours after the induction of knock-sideways by addition of rapalog. Scale bar, 5 µm. Relative growth of asynchronous KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser plus rapalog compared with control parasites over five days. Three independent experiments were performed. Growth of knock sideways (+ rapalog) compared to control (without rapalog) KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser (blue) or KIC5-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser (red) parasites over five days. Mean relative parasitemia ± SD is shown. (B) Live-cell microscopy of knock sideways (+ rapalog) and control (without rapalog) KIC5-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites 4 and 20 hours after the induction of knock-sideways by addition of rapalog. Scale bar, 5 µm. Growth of asynchronous KIC5-2xFKBP-GFP-2xFKBPendo+ 1xNLSmislocaliser plus rapalog compared with control parasites over five days. Four independent experiments were performed. __(C) __Bloated food vacuole assay with KIC4-2xFKBP-GFP-2xFKBPendo+1xNLSmislocaliser parasites 8 hours after inactivation of KIC4 (+rapalog). Cells were categorized as with ‘bloated FV’ or ‘non-bloated FV’ and percentage of cells with bloated FV is displayed; n = 3 independent experiments with each n=19-30 (mean 21.4) parasites analysed per condition. Representative DIC are displayed. Area of the FV, area of the parasite and area of FV divided by area of the corresponding parasites were determined. Mean of each independent experiment indicated by coloured symbols, individual datapoints by grey dots. Data presented according to SuperPlot guidelines (Lord et al., 2020); Error bars represent mean ± SD. P-value determined by paired t-test. Area of FV of individual cells plotted versus the area of the corresponding parasite. Line represents linear regression with error indicated by dashed line.

      41) Line 490-493: the authors state that the K13 compartment proteins fall in two groups, some that are involved in ART resistance AND endocytosis, and some that have different functions. However, in this manuscript the authors have demonstrated 3 flavours that K13 compartment proteins can come in: • Some that confer ART resistance and are involved in HCCU (MCA2) • Some that are involved in HCCU but not ART resistance (MyoF & KIC12) • Some that are involved in neither (KIC11) The authors should therefore revise this statement.

      We agree that this was not well phrased. To account for the fact that not all endocytosis proteins confer increased RSA survival to the parasites when inactivated we changed this statement (line 604): "This analysis suggests that proteins detected at the K13 compartment can be classified into at least two groups of which one comprises proteins involved in endocytosis or in vitro ART resistance whereas the other group might have different functions yet to be discovered.

      Generally, we believe that endocytosis is the overarching criterion and we therefore would like to keep the definitions of the main groups (endocytosis or not). As indicated by the title, the focus of the manuscript is on the K13 compartment for which so far endocytosis is the only experimentally associated function. That this group contains proteins that do not confer reduced ART susceptibility when conditionally inactivated (KIC12 and MyoF) is explained by their stage-specificity, making this a subgroup of the overarching endocytosis group.

      We realise that with the endocytosis data on the KIC4, KIC5 and MCA2 TGD there is now also a subgroup we were unable to demonstrate an endocytosis effect in trophozoites although they show changes in RSA survival. However, as indicated above, we would be hesitant to fully exclude some role of these proteins in endocytosis in rings. Particularly as a comparably small reduction in endocytosis protein activity or abundance is sufficient to increase RSA survival (Behrens et al., 2023). A principal classification of "endocytosis or ART resistance" or "neither endocytosis nor ART resistance" still accounts for this and therefore seems to us to be the most useful, particularly also in light of our domain identification that then can be linked with one or the other group.

      42) Line 508: the authors state that they expanded the repertoire of K13 compartments, when in fact they functionally analysed them - they did not do another BioID to identify more candidates.

      We respectfully disagree with the reviewer in this point, we did expand the repertoire of known K13 compartment proteins. Only independently experimentally validated proteins from proximity biotinylation experiments can be considered part of the K13 compartment (or any other cellular site or complex). Without validation of the location, the identified proteins can only be considered candidates. This is highlighted in this manuscript by the finding that several proteins of the list did not localize at the K13 compartment.

      43) Line 570-572: has anyone ever tested whether CytoD or JAS treatment in rings, is sufficient to mediate ART resistance? Something similar to what was done in PMID 21709259 with protease inhibitors. If not this would be a pretty interesting experiment for the authors to do that could shed more light on the MyoF data. It would take maybe 2 weeks to do and not require the generation of any new lines. This would clarify whether other Myosins other than MyoF are involved in endocytosis, as is suggested by previous publications (PMID: 17944961).

      We now included this experiment. In agreement with a lacking need of MyoF in rings and no effect on RSA survival, there was no increased survival of the parasites in RSA (neither on 3D7 nor on K13 C580Y parasites) after cytD treatment (new part in Figure 1M). We thank the reviewer for pointing out that this experiment might also inform on whether other myosins influence endocytosis in ring stages. We added (line 250): Similarly, also incubation with the actin destabilising agent Cytochalasin D (Casella et al., 1981), had no effect on RSA survival in 3D7 or K13C580Y (Birnbaum et al., 2020) parasites, indicating an actin/myosin independent endocytosis pathway in ring stage parasites (Figure 1M) and speaking against other myosins taking over the MyoF endocytosis function in rings.”

      44) Line 608: inhibitors targeting the metacaspase domain of MCA2 may inadvertently inactivate other essential parts of the protein. They authors should acknowledge this possibility in the text.

      The inhibitors used in the cited studies (Kumari et al., 2018) are validated metacaspase inhibitors, such as Z-FA-FMK (Lopez-Hernandez et al., 2003). Activity against the other parts of PfMCA2 - which apart from the MCA domain shows no homology to other proteins - is therefore unlikely.

      45) Line 624-625: the authors state that MyoF is 'lowly expressed in rings' - indeed this is the case in their MyoF-2xFKBP-GFP-2xFKBP line which the authors established has defects due to the tag, but it appears from their MyoF-3xHA tagged line that it is expressed in rings. The authors should therefore revise their statement, and be careful of making claims based on their defective line and using fluorescence imaging as their only metric. If they do want to make the statement that it is not there in rings, they should also do a western blot, which is much more sensitive since it amplifies the signal compared to an image of one parasite.

      This comment is related to major point #24. We also would like to stress that while the MyoF-GFP line already shows a phenotype, the impression of defectiveness based on its location is due to a mix up (see major point #23).

      We now provide a comprehensive time course of the MyoF-GFP signal (Figure 1C, S2A) showing that there is no detectable MyoF-GFP signal until the transition from ring to trophozoite stage. As this is all under the endogenous promoter, we do not think the partial functional inactivation of the tagging is the reason for the absence of the signal. If anything, we would have expected adding a stably folded structure such as GFP to increase the stability of the protein. The main reason for the discrepancy of MyoF signal in rings between the GFP-tagged line (of note there is also no detectable MyoF-GFP signal in MyoF-2xFKBP-GFP ring stage parasites (Figure S2B)) and the HA-tagged line likely is that IFA is much more sensitive than live GFP detection (similar to the high sensitivity the reviewer mentions in regards to WB). This discrepancy therefore is likely due to the fact that the lowly expressed MyoF only become apparent with the HA-tagged line due to the IFA. We therefore believe that MyoF is 'lowly expressed in rings' is an appropriate description of our results obtained with three different cell lines (MyoF-2xFKBP-GFP-2xFKBP, MyoF-2xFKBP-GFP and MyoF-3xHA). We hope this is sufficiently well reflected in the manuscript where we write ‘a low level of expression of MyoF in ring stage parasites.’ not that it is ‘not there in rings’ (line 174).

      46) Line 635: arguably this is the 3rd variety and not the 2nd (the authors already mentioned 2 types - ones that are involved in HCCU AND ART and those involved in HCCU only). See comment for line 490-493 above.

      See response for major comment #41, we now consistently used "or" instead of "and". See line 490-493 how this was resolved for what previously was line 635.

      47) Line 785: Bloated food vacuole assay/E64 hemoglobin uptake assay method specify that a concentration of 33mM E64protease inhibitor was used. However, in reference 44, cited in the manuscript, a concentration of 33µM E64 was used. Please confirmed if this is just a typo or if 1000x E64 concentration was used which renders the experiment invalid.

      We thank the reviewer for pointing this out, we corrected this typo and will look out for symbol font conversion errors for the resubmission.

      48) Line 788: it is unclear from this section what is considered a bloated food vacuole - is there an area above which the FV is considered bloated? Do the authors do these measurements manually or use an addon in FIJI/ImageJ? What is the cutoff for if a FV is bloated? Please clarify. Additionally, for the representative images + rapalog for Figures 2H and 4H, it would be useful to see where the authors delineate the FV (add a white circle showing what is actually measured).

      The bloated FV assay is well established (Jonscher et al., 2019; Birnbaum et al., 2020; Sabitzki et al., 2023). Although the bloating of the FV is a human judgment call, it is actually quite obvious: bloating appears as an easily spotted bulging of the FV in DIC. As also minor bloating is scored as 'bloated', it is a very conservative assay. Using an-add on to measure this is not straight forward. It is unclear how this bulging effect of the FV in DIC could be spotted by a software and due to the obviousness to human operators, potentially lengthy and complicated efforts to design appropriate machine learning options were not undertaken. The situation faced by the scorer of the assay is evident from Figure S4F-G which contains close to 50 "on rapalog" cells and close to 50 control cells, giving representative cells from all replicas of bloated FV assays with KIC12. Please note that these images shows the most complicated situation as far as bloated assays go, because the phenotype is not 100% (see Figure 3F) compared to e.g. KIC7 inactivation which leads to lack of bloating in almost all cells (see (Birnbaum et al., 2020) Figure 3E) but nevertheless the difference is still obvious. We are aware that in such situations (less than absolute inhibition) this assay scoring of "yes" or "no" is a surrogate for the actual level of inhibition and may be more subjective. This is why in this case we also did the FV size measurements (which are less dependent on human judgment) to further support this and give a better quantifiable measure. Of note, the bloated food vacuole judgments are done "blinded", i.e. the examiner does not know which sample they are looking at.

      In response to this reviewer's point we now also added the FV size refinement of the assay for MyoF inactivation which is one of the cases where inhibition of bloating is not in 100% of the cells (see major comment #27). Please also note here the advantage of the rapidly acting knock sideways technique for these assays which shows the sum of effect 8 h after initiating inactivation and for which we carefully control size of the cells which shows that there is no significant growth reduction over the assay time, excluding secondary effects due to a generally reduced viability. Compared to slower acting systems suggested to have been used instead (see introductory part and significance of this review), the rapid speed of knock sideways reduces the risk of potential pleiotropic or compensatory effects due to the time needed for proteins to be depleted if the gene or mRNA is targeted instead.

      The suggestion to include a ‘white circle’ (raised also as minor comment#27) is useful as an aid to see the food vacuole. However, in contrast to the Figures in (Birnbaum et al., 2020) (where we did add such a circle), we here included the DHE staining images in the figure, labelling the parasite cytosol which readily shows the FV (the FV corresponds to the region where there is no DHE staining). As this shows the position of the FV we would prefer to not obscure the DIC images with additional features to permit the reader to see the difference between bloated or non-bloated food vacuoles and keeping the image as natural as possible.

      49) Line 863-864: this sentence seems to be out of place.

      We thank the reviewer for pointing this out, the details of nucleus staining were moved to the correct part.

      50) Line 875: the authors state that there is a light blue wedge, when the circle consists of grey and black wedges. Please revise this.

      This has been corrected.

      51) Line 1059-1061: it is unclear whether the individual growth curves are different clones or whether they are just the same experiment repeated? If it is the latter, then why are they not combined, as is traditionally done?

      These are the individual replicates of the growth curves shown in Figure 1G of the same cell lines done on a different occasion. We always try to show as much of the primary data as possible and believe that showing individual data points from the different experiments is better than only the combined values which obscure the actual course of each experiment.

      52) Line 919-924: the authors mention a blue and red line, but there is only a black line in figure 3D. Moreover, the experiment of using the LYN mislocaliser was only done for KIC12 according to the manuscript. Additionally, the y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis there are several days. In the text it says there is no growth defect until the second cycle, but from this graph it appears the growth defect is evident as early as 1 day post rapalog treatment. Can the authors please clarify and correct the issues pointed out.

      We thank the reviewer for pointing this out, this was due to a copy & paste error in the figure legend that was now amended. We also fixed the incorrect axis label. For the last part (growth defect) please see detailed answer to Major comment#31 raising the same concern for KIC11 (in synchronous parasites the defect only takes effect once the cells reached the relevant stage whereas in asynchronous cultures there are always cells in the relevant stage that due to the rapid effect of the knock sideways already have a growth phenotype).

      53) Figure 1 panel B & C: the label of the figure where the signal from MCA2Y1344STOP-GFP is shown with the DAPI signal overlayed is deceptive since it suggests that this is the signal of full length MCA2. Please change the label of this panel from MAC2/DAPI to MCA2Y1344STOP/DAPI. The same is true for Panel C for the image labeled MCA2/K13 - please change this to MCA2Y1344STOP/K13.

      Done as requested.

      54) Figure 2B: what stages are these parasites? Please state this in the figure. Based on the MyoF pattern, it looks like rings in the upper panel and trophs in the bottom pannel. Why were schizonts not shown?

      Both are trophozoites (early trophozoite in top panel and late trophozoite in bottom panel). This is now labelled in what now is figure 1B. As stated above, schizont stages are less relevant for the topic of this manuscript and in order to prevent the manuscript from getting more disjointed and keeping it more focussed on the main topic, we decided to not include a schizont in the manuscript. Nevertheless, we included an example image below.

      [Figure MyoF_p40px schizont]

      55) Figure 2D&F: it is not very meaningful when growth assays are shown as a final bar after 4 days of growth. It is much more useful and informative to see a growth curve instead (as is shown in the supplementary), since it shows if the defect is apparent in the first growth cycle or later. With the way the data is currently shown, this is not apparent. I would advise the authors to switch the graph in 2F out of a combined graph of all the biological replicates growth curves for S3D - showing error bars.

      While we in principle fully agree with the reviewer in showing the course of the full experiment (which is available in Figure S2E), the key here is to show the overall difference. Hence, we would like to keep this comparison of the overall effect on growth in what now is Figure 1E and G. It is part of the argument to the doubts this reviewer raises to the function of MyoF (mainly in the overall assessment and the significance statement) to show that the phenotype is actually very consistent (partial inactivation through tagging or further inactivation using knock sideways increases endocytosis phenotypes, correlating with parasite viability).

      Please also note, that the growth curves upon knock sideways shown in Figure 1G, S2E are performed with asynchronous parasite cultures, which doesn’t allow us to draw direct conclusions about growth cycle effects.

      Nevertheless, we now also included the suggested combined data representation in Figure S2E.

      56) Figure 3: why were the calculation of FV area, parasite area and FV/parasite area only done for KIC12 and not done for MyoF? It would be interesting to see if any of these values are different for MyoF - whether the parasites are smaller in area and therefore FV smaller. Please present them Figure 2. Images should be already available and would not require further experiments to be done, only the analysis.

      This now has been done (confirming our results) and is included as Figure 1J-K, S2J. This point was also raised as major comment #37, please also see detailed answer there.

      57) Figure 3B: why is there no spatial association assessment for KIC11 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins.

      This is now included in Figure 2C.

      58) Figure 3D: The y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis the experiment takes place over several days. Is this a typo in the y axis? Additionally, the authors state in line 287-290 that the growth defect upon addition of rapalog is only seen in the second cycle, but from this graph it appears the growth defect is already evident 1 day post rapalog addition. The figure legend also does not make sense for this figure since it mentions a blue and a red line, when there is only a black line present. The legend also mentions the LYN mislocaliser which was used for KIC12 not KIC 11 (see above).

      We apologise for the inadequate legend and colour issues, this was amended. This point was also raised in major comment #31 and #52, please find detailed answer there.

      59) Figure 3E: the colour for Control and Rapalog 4 hpi are very similar and very hard to discern. Please choose an alternative colour or add a pattern to one of the samples. The y axis is also missing a label. Is this supposed to be parasitemia (%)?

      We thank the reviewer for pointing this out, the missing label is now included and the colour has been adapted to make them better distinguishable.

      60) Figure 4A: the ring shown in this figure does not appear to be a ring (it is far too large and appears to have multiple nuclei?). Do the authors have any other representative images to show instead?

      This is in fact a ring, but we realize that we accidentally included an incorrect size bar in the ring image of Figure 4A (now Figure 3A) (size bar for 63x objective instead of the correct one for the 100x objective), we apologise for this oversight. We don’t think this parasite has multiple nuclei, instead the Hoechst signal shows the often elongated nucleus seen in rings that can appear as two foci in Giemsa stained smears which leads to the typical diagnostic feature of P. falciparum rings in diagnostics. In order to exclude any doubts about the nuclear localization of KIC12 in rings, we here attached a panel with more examples of KIC12-2xFKBP-GFP-2xFKBP ring stage parasites.

      [Figure KIC12]

      61) Figure 4B: why is there no spatial association assessment for KIC12 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins. This should be done for the different life cycle stages considering the changing localisation of KIC12.

      This is now provided in Figure S4A. As suggested by the reviewer, we independently quantified the association for ring stage, early trophozoite and late trophozoites stage. As there is no KI12 signal in schizonts, we did not include a quantification for this stage.

      62) Figures 4C&E: it is extremely important to show the DNA stain in both these samples considering that a portion of KIC12 is in the nucleus! Please add the DAPI signal for these figures (as for all other figures!).

      Please see major comment #64 for a detailed answer why we did not include DNA staining in the imaging used to assess mislocalization upon knock-sideways.

      63) Figure 4E: this figure should be presented before 4D (considering the line being presented in 4E is used in an experiment in 4D). The authors should switch the order of these two.

      We see the point the reviewer is raising here, Figure 4D (now Figure 3D) also contains the data with the Lyn mislocaliser while we first talk about the NLS mislocaliser. This permits a better comparison between the two mislocaliser lines. However, first explaining the Lyn-mislocaliser and then going back to the NLS would make it rather complicated for the reader to follow the storyline and therefore we would like to keep the order as it is. We realise that this means the reader has to go back one figure part for seeing the Lyn growth data, but believe this is worth the benefit that the data is there compared to the NLS result.

      64) It is unclear why in many of the fluorescence images the authors do not show the DAPI signal - particularly when colocalising with K13 and when doing the knock sideways experiments. Please add these images to the figures - I would assume they have already been taken, so would simply involved adding the images to the panel.

      We did not include DNA staining (DAPI or Hoechst) for any of the images used to assess the efficacy of mislocalization, as we would prefer to keep the parasites as representative of a viable parasites in culture as possible. Hence they were imaged without DNA stain (these stains are toxic). We would like to point out that a DNA stain is not necessary, as the mislocaliser already marks the nucleus (in the case of the NLS mislocaliser), actually even somewhat more accurately, as it fills the entire nuclear space rather than only the DNA which is marked by DAPI or Hoechst.

      For LYN this admittedly is not the case, there the mislocaliser marks the plasma membrane. However, we think the proper control for efficient mislocalisation is the comparison between the GFP-tagged protein of interest and the mCherry mislocaliser to show mislocalisation, as previously done in our lab (e.g. (Birnbaum et al., 2017; Jonscher et al., 2019; Birnbaum et al., 2020)).

      Due to their toxicity, we also avoided nuclear staining in some other parts of the manuscript when we were of the opinion that a nucleus signal was not necessary.

      65) Throughout the manuscript, there is no western blot confirming the correct size of their modified proteins. This should be provided.

      We did perform Western blot analysis for both MCA2 cell lines. MCA2 is the only gene-product for which we generated a disruption for this work, and together with the severe truncation from previous work, we provided a Western blot-based confirmation of the correct size.

      The MCA2 disruptions are at least partially dispensable for in vitro parasite growth, hence if degradation occurred, this might not have been noticed. In that case we considered it relevant to show that the truncations were of the expected size. The other proteins in the main figures are essential for growth. Hence, if the tagging approach would lead to unexpected changes in protein integrity (which we assume is what was intended by this concern to be assessed with a Western blot), the parasites expressing the tagged MyoF, KIC11 and KIC12 would - due to their importance for asexual blood stage development - not have been obtained. Hence, we can assume the integrity of the tagged protein is very unlikely to have been affected in a functionally relevant way.

      66) None of the figures are appropriate for individuals with colour blindness, limiting their accessibility to the paper. Please change the colour schemes for all fluorescent images using magenta/green or an alternative colour combination appropriate for colourblind individuals.

      We thank the reviewer for this comment. This has now been amended, individual channels of fluorescence microscopy images are now shown in greyscale, while the overlay was changed to green/magenta.

      Minor Comments

      1) line 29: remove 'are'.

      Done.

      2) Line 29: the text says "HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins are among the few proteins so far functionally linked to this process." The sentence should be: 'HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins among the few proteins so far functionally linked to this process."

      Done.

      3) line 44: remove 'the'

      Done.

      4) Line 48: consider mentioning here that malaria is caused by the parasite Plasmodium - otherwise the first mention of parasite in line 52 is confusing for the non-specialist reader.

      Done.

      5) Line 49: estimated malaria-related death and case numbers are from the 2021 WHO World malaria report. You cite the 2020 WHO World malaria report.

      We now cite the newest WHO report.

      6) Line 53: please insert the word 'have' between now and also.

      Done.

      7) Line 54: please change 'was linked' to is linked

      Done

      8) Line 72: I would specify that free heme is toxic to the parasite. Especially as you mention that hemozoin is nontoxic.

      Sentence would be "where digestion results in the generation of free heme, toxic to the parasite, which is further converted into nontoxic hemozoin"

      Done.

      9) Line 90: authors should either say "in previous works" or "in a previous work"

      The text has been altered to say: “ in a previous work”.

      10) Line 91: "We designated these proteins as K13 interaction candidates (KICs)"

      Done.

      11) Line 95: please change 'rate' to number

      Done.

      12) Line 109: Please include a coma before (ii).

      Done.

      13) Line 112: as shown by Rudlaff et al in the paper you are citing, PPP8 is actually associated with the basal complex. You can say that "(ii) were either linked or had been shown to localise to the inner membrane complex (IMC) or the basal complex (PF3D7...).

      Done.

      14) Line 114: Protein PF3D7_1141300 is called APR1 in the manuscript but ARP1 in Supplementary Table 1. Please correct.

      Done.

      15) Line 131: please define SNP - this is the first use of the acronym.

      Done.

      16) Line 133-134: South-East Asia instead of "South Asia"

      Done.

      17) Line 135: please explain what TGD is - it is referred to over and over again in the manuscript without ever being explained.

      We apologise for this oversight. We now explain what is meant with TGD at the suggested point of the manuscript.

      18) Line 145: change 'Western blot' to western blot - only Southern blot is capitalised since it is named after an individual, while the other techniques are not.

      To the best of our knowledge this issue has not been resolved, some Journals capitalize the “W” (e.g. Science), while others don’t (e.g. Nature). We would prefer to continue to capitalize the “W”, as this is consistent with the original publication from (Burnette, 1981), but if there are strong objections, we would be happy to change this____.

      19) Line 152: add "the" between 'and spatial'

      Done.

      20) Line 158: please define SLI as selected linked integration, since it is the first use of the acronym.

      Done.

      21) Line 178: introduce a coma after protein. Sentence should be "Proliferation assays with the MCAY1344STOP-GFPendo parasites which express a larger portion of this protein, yet still lacking the MCA domain (Figure 1), indicated no growth ...

      Done.

      22) Line 195: the authors could mention that MyoF was previously called MyoC in the Birnbaum 2020 paper. I wanted to check back in the Birnbaum 2020 paper and could not find MyoF

      Good point, this was done.

      23) Line 200: "Expression and localisation of the fusion protein was analysed by fluorescent microscopy". Why expression was not analysed also by western Blot same as for MCA2?

      Please see major comment #64 for a detailed answer.

      24) Line 204: I could not find any mention of MyoF (Pf3D7_1329100) in reference 65. Please remove reference 65 if not correct. Also reference 66 looks at Plasmodium chabaudii transcriptomes so I would specify that "This expression pattern is in agreement with the transcriptional profile of its Plasmodium chabaudii orthologue"

      Reference 65 (Wichers et al., 2019) provides an RNAseq transcriptome dataset for asexual blood stage development of 3D7 (originating from the same source as the 3D7 used in this study). While Ref 66 (Subudhi et al., 2020) indeed contain transcriptomic data from P. chabaudi, the authors also provide a nice 2h window RNAseq transcriptome dataset for asexual blood stage development of Plasmodium falciparum. Both datasets are therefore suitable as reference for the statement about myoF transcription pattern. Both datasets are also easily accessible and show the pattern in a graph in PlasmoDB.

      25) Line 208: Please indicate a reference for P40 being a marker of the food vacuole

      Done.

      26) Line 220-224: The authors should consider changing to " Taken together these results show that MyoF is in foci that are mainly close to K13 and, at times, overlapping, indicating that MyoF is found in a regular close spatial association with the K13 compartment."

      The suggested wording introduces "mainly" for "frequently" and likely was in part motivated by the discrepancy in location between cell lines that we hope we now could clarify to be only minor (see major point #23). We therefore think the original wording appropriately summarises the findings (line 178): “*Taken together these results show that MyoF is in foci that are frequently close or overlapping with K13, indicating that MyoF is found in a regular close spatial association with the K13 compartment and at times overlaps with that compartment.” *

      27) Line 255: In Figure 2H, and subsequent figures showing bloated FV assay, I would delineate the food vacuole with dashed line as in Birnbaum et al. 2020 to help the reader understanding where the food vacuole is.

      In contrast to the Figures in Birnbaum et al. 2020, we here included the DHE staining (parasite cytosol) in images of bloated FV assays which visualizes the FV. We therefore decided to avoid any further marking, to keep the image as unprocessed as possible (see also major point 48).

      28) Line 265-266: Here the title says that KIC11 is a K13 compartment associated protein, but the title of Figure 3 says KIC11 is a K13 compartment protein. I noticed that you make the difference between K13 compartment protein et K13 compartment associated protein for MyoF for example which is not clearly associated with the K13 compartment. Which one is it for KIC11?

      The interpretation of the reviewer is correct, we indeed graded this subconsciously based on level of overlap. Based on the newly added quantification shown in Figure 2C, we describe KIC11 now as K13 compartment protein.

      29) Line 309-310: indicate a reference for your statement "which is in contrast to previously characterised essential K13 compartment proteins".

      Done, we now included Birnbaum et al. 2020 as reference for this.

      30) Line 377: Figure 4I, please correct 1st panel Y axis legend

      Done.

      31) Line 404: replace "dispensability" with dispensable

      Done.

      32) Line 416: can the authors provide any speculation as to why they observed these proteins as hits in the BioID experiments?

      As some of these proteins were less well or less consistently enriched, they could be background of the experiment. Alternatively, some could be proteins that only transiently interact with the K13 compartment.

      33) Line 451: Where the "97% of proteins containing these domains also contain an Adaptin_N domain and function in vesicle adaptor complexes as subunit a" come from. Do you have a reference?

      The statement now includes references and reads (with small changes to original submission): "More than 97% of proteins containing these domains also contain an Adaptin_N (IPR002553) domain (Blum et al., 2021) and in this combination typically function in vesicle adaptor complexes as subunit α (Hirst and Robinson, 1998; Traub et al., 1999) (Figure 5D) but no such domain was detectable in KIC5."

      34) Line 465-467: the same could be said for KIC4 as it also has a VHS domain.

      The critical issue is the combination of domains and their position within the protein. While KIC4 also contains a VHS domain, the VHS domain in KIC4 is N-terminal, not in a central position and it is also not the first structural domain to be identified in KIC4. The similarity to adaptin domains was already described ((Birnbaum et al., 2020) and annotated in PlasmoDB) and these domains are also involved in vesicle formation and trafficking. These aspects of the statement can therefore not be extended to KIC4. With regards to VHS domains being involved in vesicle trafficking, this is already stated in line 538: «KIC4 contained an N-terminal VHS domain (IPR002014), followed by a GAT domain (IPR004152) and an Ig-like clathrin adaptor α/β/γ adaptin appendage domain (IPR008152) (Figure 5A-C, Figure S8). This is an arrangement typical for GGAs (Golgi-localised gamma ear-containing Arf-binding proteins) which are vesicle adaptors first found to function at the trans-Golgi (Dell’Angelica et al., 2000; Hirst et al., 2000)

      35) Line 477-479: Can be rephrased to "However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 could be demonstrated, suggesting a limited role for PF3D7_1365800 in endocytosis. Or something like that. Makes it clearer.

      We rephrased this sentence and it now reads (line 592): However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 was observed, suggesting PF3D7_1365800 is not needed for endocytosis“.

      36) Line 535: Have AP-2a or AP-2b been shown to be at the K13 compartment?

      AP2m is at the K13 compartment (Birnbaum et al., 2020). Adaptor complexes are heterotetramers and their subunits do not typically function on their own and this is conserved across evolutionarily distant organisms. In agreement that this is also the case in P. falciparum, Henrici et al. (Henrici et al., 2020a) showed that both, AP-2a and AP-2b, were present in an AP2µ Co-IP, indicating that the AP2 complex consist of the ‘classical’ subunits in P. falciparum. Therefore, the presence of all subunits at the K13 compartment is very likely, although this has only been experimentally confirmed for AP2µ. Of note, for Toxoplasma gondii the presence of AP-2a and AP-2b at the micropore has been experimentally confirmed (Wan et al., 2023; Koreny et al., 2023) and interaction suggested by presence in the same IP as DRPC (Heredero-Bermejo et al., 2019).

      37) Line 569: reference 43 is wrong

      We thanks the reviewer for pointing this out – we removed Ref 43.

      38) Line 746: typo "ot" instead of or.

      Changed.

      39) Line 801: method for Domain Identification using AlphaFold specify that RMSDs of under 5Å over more than 60 amino acids are listed in the results. However, there is a typo in Figure 5B for KIC5 where it says "RMSD 4.0 Å over 8 aa". Please correct.

      Done. In addition, we have now applied a more stringent cut-off of 4Å over more than 60 amino acids to ensure a higher reliability of our hits. This decision was based on results from our preprint (Behrens and Spielmann, 2023). Because of this the phosphatase domain in KIC12 is no longer included in this manuscript and accordingly the following sentence has been deleted. In KIC12 we identified a potential purple acid phosphatase (PAP) domain. However, with the high RMSD of 4.9 Å, the domain might also be a divergent similar fold, such as a C2 domain, which targets proteins to membranes.”

      40) Line 856: In Figure 1E, please use the same Y axis legend as in Figure 2D "relative growth at day 4 [%] compared with 3D7"

      Done.

      41) Figure S1: Some PCR gels check for integration are presented as 5', 3' and ori whereas other gels are presented as ori, 5' and 3'. This is confusing.

      We agree that ideally the order of sample loading should be consistent and we apologise for this. The explanation for this is that these gels were run by different people at different times before we were able to better standardize the loading scheme. However, in the interest of not unnecessarily using resources for something that has a similar meaning, we would prefer not to repeat these PCRs and re-run them only for consistency reasons (as the conclusion is not affected by the different loading schemes).

      42) Figure S1: Why was the expression of only MCA2 was verified by Western blot? What about the other proteins?

      See response to major comment 56.

      43) Line 493: Considering KIC11 was not involved in HCCU or ART resistance it might be worth mentioning in this section that it is of note that there are no domains detected that would be involved in endocytosis.

      We agree that this is the case, however it is also the case for all other proteins that either are not involved in endocytosis and/or lowered susceptibility to ART. We therefore now added a summary statement addressing this in line 602: In contrast, the K13 compartment proteins where no role in ART resistance (based on RSA) or endocytosis was detected, KIC1, KIC2, KIC6, KIC8, KIC9 and KIC11, do not contain such domains (Figure 5E).” We did not add this at the suggested part of the manuscript as at that point the domain search results are not yet introduced and doing this each time for all the individual proteins would disconnect the flow of the manuscript.

      44) Line 503-506: is it wise to generate more drugs that target a pathway that is already highly susceptible to mutations? The authors should add a statement explaining how this might be avoided.

      The only protein for which mutations do not have a large fitness cost is K13 (see also our preprint on fitness cost of ubp1 mutation (Behrens et al., 2023) and even with K13 the level of resistance seems to be limited by amino acid deprivation when endocytosis is reduced (Mesén-Ramírez et al., 2021). We therefore do not think that this pathway is particularly prone for mutations. Further, the number of commercial drugs targeting the "endproduct" of endocytosis (hemoglobin digestion and detoxification of heme) highlight it as the most prominent vulnerability for drug-based intervention if we go by number of commercially available drugs acting on things associated with a single process.

      45) Throughout, scale bars are stated in the figure legends at the end of the legend. This is a slightly confusing format. The authors should consider stating the scale bar for each sub-legend where a fluorescence image is taken.

      Done.

      ** Referees cross-commenting**

      After reading reviewer 2 and 3's comments, I think there are significant overlaps in the key points raised in terms of questions about fusion proteins and their potential partial mis-localisation, better descripton of results and target selection. Overall I think we agree that the work has potential, but in its current form does not represent a major advance. It would be immensely helpful if the manuscript would be carefully edited for a better flow and linear description of results.

      We now rearranged the manuscript for better flow but would like to highlight that the many requests for smaller experimental issues (and "better description of results") worked somewhat in the opposite way of a more linear description. We hope the rearranged version acceptably balances these two issues. The issues raised in regards to target selection and potential partial mis-localisation are addressed in our responses mainly to this reviewer. Please also see comments on systems used at the end of the rebuttal.

      Reviewer #1 (Significance (Required)):

      The authors set out to test whether other proteins that are in the vicinity of K13 are involved in mediating ART resistance and endocytosis. This is an interesting question. However, other than MCA2 which was already known to be involved in mediating ART resistance (and was not tested for its involvement in endocytosis), none of their candidate proteins seem to be involved in mediating both these functions. The authors show that the other proteins tested appear important for parasite growth, with KIC12 and MyoF involved in mediating endocytosis. While these findings are novel, the KS approach used by the authors casts some doubt over the findings, and would mean that these findings would have to be re-tested with a more reliable approach, such as the GlmS system or generating a conditional knockout using the DiCre system. Despite not advancing our understanding of ART resistance, or identifying further players involved in this process, this manuscripts provides two candidates that are involved in mediating endocytosis and a further candidate that appears to be important for parasite growth. Further work on these proteins will be required to understand their exact roles. As stated above, there is currently limited interest for these results (limited to researchers working on endocytosis in apicomplexan parasites and possibly the wider endocytosis field from an evolutionary perspective), however with further work, this could increase the impact and interest of this work substantially.

      The authors do not describe any novel methods/approaches within this work.

      In the significance statement the reviewer indicates that other systems would have been more reliable for the work here. This is addressed in our response above and in a detailed considerations on the properties of conditional inactivation systems at the end of the rebuttal. The systems used in this work were not only chosen because they permit rapid targeting of many different proteins, but because they have merits that are beneficial for our assays. In fact many of the functional assays in this manuscript are difficult or impossible to carry with the suggested conditional inactivation systems (please note that we have extensive experience with the systems considered preferable:

      • DiCre (Birnbaum et al., 2017; Mesén-Ramírez et al., 2019; Mesén-Ramírez et al., 2021; Wichers et al., 2022; Kimmel et al., 2023)

      • glmS (Wichers et al., 2021c; Wichers et al., 2021a; Wichers et al., 2022; Wichers-Misterek et al., 2023)).

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      In a previous publication the Spielmann lab identified the molecular mechanism of ART resistance in P. falciparum by connecting reduced levels of the protein K13 to decreased endocytosis (uptake of hemoglobin from the RBC cytosol), which results in reduced ART susceptibility. Using quantitative BioID the authors further identified proteins belonging to a K13 compartment, highlighting an unusual endocytosis mechanism.

      In the present manuscript the authors follow up on this work and closely examine ten more proteins of the K13/Eps15-related "proxiome". They successfully link MCA2 to ART resistance in vitro, while the proteins MyoF and KIC12 are involved in endocytosis but do not confer in vitro ART resistance when impaired. They further characterize one candidate (KIC11) that partially colocalizes with K13 in trophozoites but to a lesser degree in schizonts. Growth assays suggest an important function for KIC11 in late stages of the intraerythrocytic developmental cycle. Five analyzed proteins however do not colocalize with the K13 compartment, while a sixth was refractory to endogenous tagging.

      Using AlphaFold predictions of the KIC protein structures the author identify domains in most constituents of the K13 compartment, highlighting vesicle trafficking-related features that were not identified on primary sequence level before.

      The combination of functional data together with structure predictions leads them to propose a refinement of the K13 compartment as being divided into proteins participating in endocytosis and proteins that have an unknown function.

      We thank the reviewer for the assessment of the manuscript and the constructive comments.

      Major comments:

      1) -Table 1 is missing

      We apologise for this mistake; Table 1 is now included.

      2) -Lines 117-123: Given the total list of uncharacterized candidates encompasses 13 proteins, can the author gives the reason why only the top 10 and not all 13 were characterized in this study?

      A similar point has been raised by Reviewer 1 in major comment #12, please see our response there for an explanation why we chose which targets.

      3) -Line 174: 20% of observed MCA2 foci show no overlap with K13 and 21% only partially overlap, can the author confirm that the observed MCA2 foci in schizonts are the ones that co-localize with K13. (Addition of a schizont stage image in Fig 1C would be sufficient).

      We now extended Figure 4C with images of MCA2-Y1344STOP-GFP+mCherryK13 parasites covering the schizont and merozoite stage, showing that the majority of the MCA2 foci in schizonts are also mCherry-K13 positive.

      4) -The localization and observed phenotype of KIC11 is interesting but unfortunately the authors do not explore it further. Does KIC11 localize with markers of e.g. the secretory organelles (micronemes or rhoptries) in schizonts and could therefore be involved in RBC invasion?

      While we intended to focus mainly on the endocytosis aspect of these proteins, we see the reviewer's point and now generated new cell lines enabling assessment of spatial association of KIC11 with markers for rhoptry (ARO), micronemes (AMA1), and inner membrane complex (IMC1c). This revealed that the KIC11-GFP signal in schizonts does not overlap with apical organelle markers and the signal does not resemble a typical apical localization. In addition, we assessed all three organelle markers after inactivating KIC11 by knock sideways which showed that KIC11 inactivation has no apparent effect on the appearance of these markers, suggesting no major alterations in schizont morphology in respect to apical markers. These results are now presented as Figure S3A and in line 304 of the results.

      5) Can the author distinguish if KIC11 is involved in RBC invasion or in establishment of the ring-stage parasite?

      In order to look into this, we performed egress/invasion assays, quantifying schizont and ring stage parasites in tightly synchronized parasites at two different time points (pre-egress: 38-42 hpi & post-egress: 46-50 hpi). This revealed a significant decrease in newly formed ring stage parasite per ruptured schizont in parasites with inactivated KIC11, while the egress efficacy remained unaffected. This indicated an invasion or very early ring stage development defect (new Figure 2H, Figure S3G). To further determine at which point exactly the phenotype occurs (ie during invasion or early after invasion) would require extensive experimentation that goes beyond the scope of this study (e.g. invasion assays using video microscopy with a representative number of parasites or sophisticated flow based quantification assays). We hope by excluding egress and gross changes of apical organelles as well as no indication for similar number of early rings (indicating it is invasion or a very early ring-establishment phenotype) will sufficiently narrow down the phenotype for labs interested in invasion to more definitely answer this question.

      Minor comments:

      1) Table S1: Please add the criterion for the order of proteins (abundance in "proxiome"?) in the table as a separate column. I would also suggest adding a new column that highlights the 10 proteins investigated in this study as I found the color-coding slightly confusing.

      Done as suggested: we now include the “average log2 Ratio normalized Kelch13” values from the four DiQ-BioID experiments performed with K13 in (Birnbaum et al., 2020), as well as the suggested column to highlight the investigated proteins. Please also see reviewer 1 major point # 12 for additional information on the selection criteria and how this was added to the manuscript.

      2) -154-155: There is a discrepancy between the text and Fig1C regarding the % of partial overlapping and non-overlapping foci.

      We thank the reviewer for pointing this out, this was corrected.

      3) -The y-axis label is missing in Fig 3E

      Done.

      4) -Fig 4I left graph, the superscript 2 is missing in μm2

      We thank the reviewer for pointing this out, this is now changed.

      5) -Did the author colocalize KIC11 in schizonts with other proteins found in the K13 compartment group of proteins not involved in endocytosis/ART resistance? This may help to further subgroup these proteins.

      This is an interesting point but would actually be technically challenging to do. For this we would need to generate a KIC11endo parasite line for each of these KICs and then do co-localisation in schizonts. However, the outcome of this likely would not be very clear. The reason for this is as follows. There are foci of KIC11 that do overlap with K13 in schizonts. One can expect that these foci show KIC11 at the K13 compartment and that the other KICs would overlap with KIC11 in these K13 foci in schizonts. Hence, we would also need to see K13 to find the non-K13 compartment KIC11 foci and see if these contained the KIC of interest. This is technically challenging because it would mean we would need a third fluorescent protein which is not that trivial to do. Due to the difficulty to do this and the large amount of work involved and the already considerable amount of data in this manuscript, we believe this will be better suited for a different study.

      6) -As a general comment: to make the beautiful IFAs more accessible to a broader readership, I would encourage the authors to switch the color-coding to green/magenta/blue or an equivalent color system or add grayscale images.

      This was done as suggested, all fluorescence images are now provided as greyscale images and the overlays are shown in magenta/green.

      Reviewer #2 (Significance (Required)):

      Characterizing the molecular components involved in Plasmodium endocytosis will not only reveal interesting biology in these highly adapted parasites, but will more importantly lead to a better understanding and potentially open new avenues for intervention of ART resistance. The here presented manuscript is a carefully executed follow-up on previous work done in Dr. Spielmann's lab focusing on the K13 compartment. The authors use established assays to characterize novel components and reveal three new players in endocytosis with one mediating ART resistance in vitro. The proposition that parts of the K13 compartment have a function other than endocytosis is interesting, but will have to await more data from future studies. Taken together this manuscript adds significantly to our understanding of endocytosis in P. falciparum.

      This work is of interest for cell and molecular biologists working on Apicomplexa, but especially for the Plasmodium community.

      We thank the reviewer for this positive assessment.

      I am a cell and molecular biologist working on Toxoplasma gondii

      Reviewer #3 (Evidence, reproducibility and clarity (Required)):

      Summary: The authors characterized 4 proteins from P. falciparum via cellular (co-)localization, endocytosis, parasite growth, and artemisinin resistance assays. These proteins have been identified as candidates for Kelch13 compartment and a possible role in endocytosis in their previously work with quantitative BioID for potential proximity to K13 and Eps15 (Birnbaum et al. 2020). In the current work, additional 6 proteins were not confirmed as being associated to the K13 compartment. This experimental work was complemented by an in-silico analysis of protein domains based on AlphaFold algorithm. For this protein structure evaluation all proteins were chosen, which were experimentally confirmed to be linked to the K13 compartment in the current publication and previous work. With the work 3 novel proteins linked to artemisinin resistance or endocytosis could be functionally described (KIC12, MCA2, and MyoF) and a number of hypotheses were generated.

      We thank the reviewer for the assessment of the manuscript and the constructive comments.

      Major comments:

      The quality of the presented work is solid, the experimental design is adequate, and methods are presented clearly. The publication contains a lot of results both presented in text and in the figures and it is not always straight forward for the reader to follow the descriptions due to many details presented and a lack of context for some of these experiments.

      We thank the reviewer for this overall positive assessment.

      We now reordered the results section in an attempt to increase the flow of the manuscript. We also made changes to improve the context for the results. Given the further (very valid) requests for data on schizonts and invasion, there was an increased danger for a less linear manuscript that we hope to have acceptably managed with the re-arrange.

      Specific suggestions for consideration by the authors to improve the manuscript. Abstract: 1) R 31: Mention how the 4 proteins were identified as candidates, you need to refer to previous work to clarify this

      To clarify this the sentence was changed to (line 31): "Here we further defined the composition of the K13 compartment by analysing more hits from a previous BioID, showing that MyoF and MCA2 as well as Kelch13 interaction candidate (KIC) 11 and 12 are found at this site."

      2) R38: "Second group of proteins" is confusing - different from the 4 mentioned above? Significance to endocytosis unclear. Please unify terminology in the manuscript, see also comment below on proxiome.

      We changed the wording to clarify the group issue in the abstract as follows line 34: "Functional analyses, tests for ART susceptibility as well as comparisons of structural similarities using AlphaFold2 predictions of these and previously identified proteins showed that canonical vesicle trafficking and endocytosis domains were frequent in proteins involved in resistance or endocytosis (or both), comprising one group of K13 compartment proteins, While this strengthened the link of the K13 compartment to endocytosis, many proteins of this group showed unusual domain combinations and large parasite-specific regions, indicating a high level of taxon-specific adaptation of this process. Another group of K13 compartment proteins did not influence endocytosis or ART susceptibility and lacked detectable vesicle trafficking domains. We here identified the first protein of this group that is important for asexual blood stage development and showed that it likely is involved in invasion.”

      3) Abstract can only be understood after reading the full publication

      We attempted to amend this by expanding the abstract, particularly the changes highlighted in the previous two points.

      Results: 4) Table 1 is missing from the submitted materials

      We apologise for this mistake. Table 1 is now included.

      5) Consider to shorten and stratify the result section to focus on the significant data

      We rearranged the results in an attempt to streamline this section and are now starting with MyoF in the revised manuscript. However, as highlighted by the requests from reviewer 1, many details need to be available to support our conclusions. For instance the fact that GFP-tagging partially inactivated MyoF asked for further data to support our conclusion (HA-tagged version, showing that the location of the GFP-tagged version was consistent with the HA-tagged version, showing to what extent the different constructs affected growth and correlated with number of vesicles and bloating, see new figure 1M) or that KIC12 has two locations. Overall, we are therefore hesitant to remove data or description from the result part.

      6) Unclear how the localization and functionalization assays might be impaired by the fusion proteins Significance of ART resistance assay is not clear, in presence of strong growth effects due to inactivation or truncation of genes/proteins

      As indicated also in the example given in the previous point (this reviewer #5), the use of different cell lines (GFP-tagged live cells and small epitope tag in IFA) for targets with an indication for an effect of the tagging confirm that the location we assigned is reasonable. In the case of MyoF, the HA-tagged line, the partial inactivation due to GFP and the further inactivation in the GFP-tagged line by knock sideways show plausible increase of phenotypes (vesicle accumulation and bloated FV assays). Thereby the GFP-tagged line can be seen as a partial inactivation line that further supports our conclusions and overall this paints a consistent picture of the function of this protein in endocytosis (see new Figure 1M better illustrating this). Please note that the difference in location shown by this line compared to the HA-tagged proteins is only small (see also reviewer 1 major point 23ff). See also general discussion on tags at the end of this rebuttal.

      Significance of ART resistance assay: The ‘ART resistance assay’ is done comparing +/- ART (DHA) in identical parasites (originating from the same culture and the same condition). Hence, any growth effects are cancelled out and effects in reducing ART susceptibility would - if at all - be underestimated (see more detailed response to point 28, reviewer 1 and controls in Birnbaum et al., 2020 where we tested an unrelated essential protein, unrelated chemical insult and rapalog on 3D7 and did not detect any effect on RSA survival).

      MCA 7) Stratify results, order by significance of findings, it appears to be described in chronological order, improve readability/flow, eg ART resistance if mentioned in r138, but only reported in r183ff

      We attempted to stratify, but then the reason for generating the partial MCA2 disruption parasite line becomes very arbitrary and would leave the reader wondering why we at all truncated the protein at two thirds of the protein. Hence, we do not see a way around this chronological reporting. However, this part is now not at the start of the experimental results section anymore, possibly making it overall a bit more palatable.

      MyoF 8) R195 to 197 - consider moving to discussion as it is distracting here

      This was shortened and additional information (asked for by reviewer 1, major point 22) to clarify that MyoF was previously called MyoC, was added (line 147): “The presence of MyosinF (MyoF; PF3D7_1329100 previously also MyoC), in the K13 proxiome could indicate an involvement of actin/myosin in endocytosis in malaria parasites. "

      9) Term proxiome is introduced above, but not used in result section - suggest to unify language, eg r195 uses "K13 compartment DiQ-BioIDs" instead, which is not very convenient for the reader

      We carefully reviewed this and made this more consistent.

      10) What is the enrichment factor? Please provide for this and the following proteins, eg in Table 1

      The enrichment factor is log2 enrichment over control and this is now provided in table S1 (see also detailed answer for Reviewer 1 major point 12).

      11) R225 to 243 - overall significance of the growth experiments with mislocaliser is not clear, consider removing from manuscript or explain relevance more clearly

      See also point 28, reviewer 1: This experiment is actually quite important. It shows that if we conditionally inactivate the GFP-tagged MyoF, the growth is further reduced, as stated in line 208. It might have been confusing that the mislocalisation is only partial, but this is equivalent to a partial knock down and hence is useful. This becomes even more relevant with the specific assays following in the next paragraph: while the tagging of MyoF already resulted in vesicles, conditional inactivation with KS generated even more vesicles, showing that the same phenotype was rapidly increased when MyoF was further inactivated by a different means and this also correlated with growth. Hence, this is actually a very consistent phenotype that despite some shortcomings of the tools available to analyse this protein (due to the partial inactivation by the GFP tag) in our eyes looks very convincing. We now added a graph showing the correlation of growth and phenotypes to illustrate this (Figure 1L).

      We also tried to make this clearer by changing line 200 to: Hence, conditional inactivation of MyoF further reduced growth despite the fact that the tag on MyoF already led to a substantial growth defect, indicating an important role for MyoF during asexual blood stage development.” And line 208 to:“ This was even more pronounced upon conditional inactivation of MyoF by KS (Figure 1H), suggesting this is due to a reduced function of MyoF.”

      12) KIC11/KIC12 Enrichment factor?

      The enrichment (’average log2 Ratio normalized Kelch13 from Birnbaum et al. 2020’) is 1.65 for KIC11 and 1.32 for KIC12, which is now also explicitly shown in column D of Table S1.

      ** Referees cross-commenting**

      I would like to applaud reviewer #1 for a great, very thorough review and lots of detailed suggestions. I agree with the conclusions mentioned in the significance evaluation from reviewer #1 and #2: the work presented does not contain novel methods and the scope is rather narrow with the current results. (I am working on clinical studies with novel antimalarial agents)

      Reviewer #3 (Significance (Required)):

      On the one hand side, the authors have wrapped up some of the remaining protein candidates of the K13 compartment and could verify 4 of 10 proteins. The work is of interest for the scientific community working on endocytosis and malaria drug resistance mechanisms. Overall, the conclusions and findings from the previous work, Birnbaum et al. 2020, could be confirmed and extended mainly using the methods previously described. On the other hand, the authors made use of progress in protein structure predictions and identified domains linking the K13 compartment proteins to putative functions. The overlaid protein folds of the newly identified domains in figure 5 look convincing, but I can't comment on the technical details or cut-off used for this in-silico analysis.

      Extended general remarks on the systems used for this work:

      Mainly reviewer 1 suggest (in the general comments and the significance statement) that other systems would have been better suited to use for this work, namely glmS and diCre and also has concerns about the large tag which is seconded by a comment of reviewer 3. In light of this we here provide some extended considerations on the properties for conditional systems and tagging in regards to the goals of this work.

      We would like to point out that we do have experience with the systems considered better-suited by the reviewer (one of the first authors has extensively used glmS (Wichers et al., 2021c; Wichers et al., 2021a; Wichers et al., 2022; Wichers-Misterek et al., 2023) and our lab was one of the first to adopt the diCre system in P. falciparum parasites and we regularly us it (Birnbaum et al., 2017; Mesén-Ramírez et al., 2019; Kimmel et al., 2023)). Clearly, these methods have a lot of strengths but there are a number of issues to be considered for the assays we use in this work (see the next section on conditional inactivation systems). In a nutshell, we believe diCre would give a more reliable readout of the absolute level of "essentiality" (i.e. importance for growth) but is unsuitable or at least difficult to use for the assays that reveal the function of our interest in this work. GlmS basically combines the drawbacks of diCre and knock sideways and hence for most targets is not expected to give a better readout of level of "essentiality" but is similarly difficult to use for our specific assays. The fact that both of these systems are possible to use without adding a tag to the target may be an advantage but without tag one loses some very important features that can be critical to understand the outcome with a given system (see considerations on the tag further below).

      Conditional inactivation systems:

      1. __ speed of inactivation:__ glms acts on mRNA and diCre on the gene level, which makes them slower than techniques acting directly on the protein such as DD or KS. With diCre, mRNA and protein is still left, even if the gene is very rapidly excised. For instance for Kelch13 it takes 3-4 days after excising the gene until protein levels have waned enough that this manifests in a reduced growth (Birnbaum et al., 2017). While in some instances diCre permits same cycle analyses if the protein has a very rapid turn-over (e.g. Rab5a, (Birnbaum et al., 2017)), control in a few hours is still difficult. For vesicle accumulation and bloated food vacuole assays, which are done over comparably short time frames and with specific stages, it is rather challenging to hit the correct time of induction to have all the cells at the correct stage with suitably (and uniformly, ie all cells) sufficiently reduced target protein levels during the assay time. Slow acting systems are also more prone to secondary effects. The more immediate the inactivation, the closer it is to the core of the affected function. With vesicle trafficking processes this is particularly relevant as all vesicle trafficking in a cell is interconnected and there are always recycling pathways that maintain the membrane and protein homeostasis of individual compartments. Particularly for endocytosis there seem to be compensatory capacities at least in other organisms (see e.g. (Chen and Schmid, 2020)). One reason why knock sideways was developed is that it permitted to avoid compensatory changes when vesicle adaptors are inactivated (Robinson et al., 2010).

      The comparably short time frame for malaria parasites to go through different stages during blood stage development also is an issue relevant for inactivation speed. The advantage of speed and the danger of obscured phenotypes is highlighted by our work on VPS45 which showed that in trophozoites this protein is involved in the transport of hemoglobin to the FV whereas in late stages it also has a role in secretory processes. Both of these functions we were able to specifically assess in the same growth cycle using KS to rapidly inactivate the protein (Bisio et al., 2020) but with a slower system would have been more complicated to dissect.

      Speed of effect with glmS: unless the KS does not work well, glmS is slower acting than KS (it does not target the already synthesised protein which can remain in the cell) and also often suffers from only partial inactivation, hence the benefit of using it here is unclear. The option to have an untagged protein is a plus, however it also is a minus, as assessing efficiency (particularly in live cells e.g. for bloated assays etc a fluorescent tag is the only direct option to assess inactivation of target) is critical to ensure the phenotype manifests at the stage of interest.

      lethality/absolute phenotypic effects are detrimental to some assays to study the functions we are interested in for this work: no RSA can be conducted, if the gene is lost and the parasites die. Again, with diCre, one could attempt to hit the point when the parasites have lost sufficient amounts of the target protein when they are placed under ART but then the parasites need to continue growing for ~3 days, which is not possible if the cKO is lethal except for very slowly turning over proteins. However, in that latter case, the parasites likely still had full functionality of the target protein at the beginning of the RSA, when the drug pulse happens and there would be no effect. Knock sideways solves these problems by permitting knock sideways inactivation only under ART (or with a few hours pre-incubation depending on the inactivation speed) to not yet affect growth in a severe manner but inhibiting the process the protein is involved in. It may be possible to use glmS for RSAs, but the slow speed would complicate it (it would not permit control of target protein levels in a matter of a few hours to inactivate the target protein and then re-install it).

      None-absolute inactivation is also a strength for some functional assays. While we really like using diCre, in the case of EXP1 it made it necessary to complement the exp1 cKO parasites with low levels of EXP1 to be able to do functional assays without killing the parasites (Mesén-Ramírez et al., 2019; Mesén-Ramírez et al., 2021). While the lethality issue does not apply to glmS (like knock sideways, it also can be tuned), it is unclear what would be gained over knock sideways. Knockdown levels with glmS vary from gene to gene and cannot be predicted, it is in most cases considerably slower than KS, it requires glucosamine which becomes toxic at higher concentrations and might introduce off target effects and tracking protein levels during the assay would equally need GFP tagging.

      Integration of properties of conditional systems

      Given the above discussed properties, several factors have to be considered to be able to use a system for a given assay. Stage-specific transcription is one example. For diCre a protein not expressed in e.g. rings permits to remove the gene and the protein is never made in that parasite development cycle. We exploited this for instance for two proteins only expressed from the trophozoite stage onwards (Kimmel et al., 2023). However, if lethal (absolute effect problem), this also means one can also only see the phenotype on onset of expression of the target (e.g. if in mitosis, the first nuclear division in case the protein is absolutely essential for the process). This is just one example of such issues. Expression timing, turnover of the protein and homogeneity of stage-specific loss of protein will all influence how clearly the phenotype can be determined. All this will decide the exact time of loss/inactivation of the target protein to levels generating a phenotype and ideally therefore can be monitored during an assay (see considerations on tagging).

      For these reasons vesicle accumulation or bloated food vacuole assays are difficult with slow systems as ideally the target should rapidly be inactivated at the trophozoite stage and the result monitored before the cells have moved to the schizont stage. For this a well responding knock sideways is ideal as the protein can be rapidly taken away (sometimes within seconds) to visualise the immediate, direct effect in the cell.

      As shown for KIC11, there is also no disadvantage of using KS for proteins with other assays or proteins that result in different phenotypes. It permits stage-specific same cycle inactivation without having to worry about the turnover of mRNA and protein (Fig. 2F,G). Thus, besides the advantages of knock sideways for endocytosis related assays and RSAs, we also see no disadvantage of using knock sideways for the functional study of KIC11 which has a role other than endocytosis. KS also permits to specifically target the K13 pool of KIC12, something impossible or very difficult to do with other systems. Hence, we are of the opinion that the system for inactivation was adequate for most of the proteins analysed in this manuscript.

      Large tag: we agree that GFP-tagging can be a disadvantage but in our opinion its benefits often outweigh the drawbacks because it permits easy and immediate (on individual cell level, if need be) monitoring of the presence/location of the target protein (e.g. after KS, but given the discrepancy of the timing between gene excision and protein loss, it might be even more important for techniques such as diCre). No fixing/permeabilisation (prone to artifacts, prevents immediate view of cells) to detect a target with specific antibodies or via a small tag is needed with GFP. Similarly, the use of Western blots to do this is time consuming and impractical if monitoring of left-over protein in the course of an assay such as a bloated food vacuole assay is needed.

      In many cases, adding GFP has no negative effect. In addition, if the bulky folded structure of GFP is tolerated, it usually also tolerates the 2 to 4 12kDa FKBP domains in our standard tag. We also typically add a linker. This approach has worked for a large number of different proteins, including many essential ones for which we would not otherwise have obtained the integration cell lines (Birnbaum et al., 2017; Jonscher et al., 2019; Hoeijmakers et al., 2019; Birnbaum et al., 2020; Kimmel et al., 2023; Sabitzki et al., 2023). Hence, whenever a cell line is obtained with it, this tag in most cases is not a disadvantage. Admittedly an exception in this is MyoF and to some extent maybe MCA2 (we would like to stress that in the case of MCA2 the reason for not being able to obtain the full length tagged cell line is unclear: the protein can be severely truncated to less than 3% of its amino acid sequence and a GFP-tag is tolerated on the version with 2/3s of the protein left, which gives no good reason why the full length was not obtained; a potential reason could be a dominant negative effect). However, we obtained the full length with a small tag detected by IFA for both, MyoF and MCA2 and the location of these agreed well with the GFP tagged versions, indicating that the GFP-tagged versions are useful to show the location of these proteins in live cells.

      There are also tricks to attempt monitoring the effect of e.g. diCre without tagging the target. For instance, if a fluorescent protein is connected to excision without actually being fused to the target (ie excision of the gene leads to its expression of e.g. GFP), which would avoid adding a tag to the target itself. However, the problem with this is that expression of GFP does only show excision, but mRNA producing the target protein and left over target protein may still be there in the cell. All in all, the GFP-tag on the target, while with some drawbacks, is still our preferred method to control to monitor the target protein in the cell (in principle permitting quantification of ablation efficiency on the individual cell level).

      Conclusion on these considerations for this manuscript

      Based on these considerations we do not see the immediate benefit of changing the system for the conclusions drawn from this study and are unsure if they are indeed better suited for this work as suggested. While a more exact readout of "essentiality" might be possible with the diCre system we are of the opinion this is less important than learning the function of a protein which - as outlined above - we believe to be considerably more difficult with diCre and even more so with glmS considering our target functions. The same applies to target specific cellular pools of a protein as done here for KIC12. Clearly MyoF is one example where the employed systems shows limitations, but with the new Figure part showing consistency in phenotype with degree of inactivation (importantly with two different forms of inactivation) and the clarification that the location of the GFP-tagged and HA-tagged versions are actually quite similar in location, we do not think employing an extra system is warranted for the conclusions of this work. Admittedly, the apparent lack of need in ring stags might give an opening to attack MyoF using diCre (by excision before its major expression peak), but depending on lethality this might preclude extended analyses (possibly vesicle assays, for sure not RSAs).

      In the end the question is, if our approach provides the function of target analysed in this work and based on the data in our manuscript and the arguments in the rebuttal, we are reasonably confident that this is the case. It is not very likely the other mentioned techniques would result in a different conclusion on the function of the here studied proteins. In fact, we expect other commonly used techniques to be less suitable for the key assays in this work.

      References used in our responses to the reviewers’ comments:

      Behrens, H.M., Schmidt, S., Peigney, D., Sabitzki, R., Henshall, I., May, J., et al. (2023) Impact of different mutations on Kelch13 protein levels, ART resistance and fitness cost in Plasmodium falciparum parasites. bioRxiv 2022.05.13.491767.

      Behrens, H.M., Schmidt, S., and Spielmann, T. (2021) The newly discovered role of endocytosis in artemisinin resistance. Med Res Rev med.21848.

      Behrens, H.M., and Spielmann, T. (2023) Identification of domains in Plasmodium falciparum proteins of unknown function using DALI search on Alphafold predictions. bioRxiv 2023.06.05.543710.

      Birnbaum, J., Flemming, S., Reichard, N., Soares, A.B., Mesén-Ramírez, P., Jonscher, E., et al. (2017) A genetic system to study Plasmodium falciparum protein function. Nat Methods 14: 450–456.

      Birnbaum, J., Scharf, S., Schmidt, S., Jonscher, E., Hoeijmakers, W.A.M., Flemming, S., et al. (2020) A Kelch13-defined endocytosis pathway mediates artemisinin resistance in malaria parasites. Science (80- ) 367: 51–59.

      Bisio, H., Chaabene, R. Ben, Sabitzki, R., Maco, B., Baptiste Marq, J., Gilberger, T.W., et al. (2020) The zip code of vesicle trafficking in apicomplexa: Sec1/munc18 and snare proteins. MBio 11: 1–21.

      Blum, M., Chang, H.Y., Chuguransky, S., Grego, T., Kandasaamy, S., Mitchell, A., et al. (2021) The InterPro protein families and domains database: 20 years on. Nucleic Acids Res 49: D344–D354.

      Borrmann, S., Straimer, J., Mwai, L., Abdi, A., Rippert, A., Okombo, J., et al. (2013) Genome-wide screen identifies new candidate genes associated with artemisinin susceptibility in Plasmodium falciparum in Kenya. Sci Rep 3.

      Bozdech, Z., Llinás, M., Pulliam, B.L., Wong, E.D., Zhu, J., and DeRisi, J.L. (2003) The transcriptome of the intraerythrocytic developmental cycle of Plasmodium falciparum. PLoS Biol 1: e5.

      Burnette, W.N. (1981) “Western Blotting”: Electrophoretic transfer of proteins from sodium dodecyl sulfate-polyacrylamide gels to unmodified nitrocellulose and radiographic detection with antibody and radioiodinated protein A. Anal Biochem 112: 195–203.

      Casella, J.F., Flanagan, M.D., and Lin, S. (1981) Cytochalasin D inhibits actin polymerization and induces depolymerization of actin filaments formed during platelet shape change. Nature 293: 302–305.

      Cerqueira, G.C., Cheeseman, I.H., Schaffner, S.F., Nair, S., McDew-White, M., Phyo, A.P., et al. (2017) Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance. Genome Biol 18: 78.

      Chen, Z., and Schmid, S.L. (2020) Evolving models for assembling and shaping clathrin-coated pits. J Cell Biol 219.

      Dell’Angelica, E.C., Puertollano, R., Mullins, C., Aguilar, R.C., Vargas, J.D., Hartnell, L.M., and Bonifacino, J.S. (2000) GGAs: A family of ADP ribosylation factor-binding proteins related to adaptors and associated with the Golgi complex. J Cell Biol 149: 81–93.

      Demas, A.R., Sharma, A.I., Wong, W., Early, A.M., Redmond, S., Bopp, S., et al. (2018) Mutations in Plasmodium falciparum actin-binding protein coronin confer reduced artemisinin susceptibility. Proc Natl Acad Sci 201812317.

      Henrici, R.C., Edwards, R.L., Zoltner, M., Schalkwyk, D.A. van, Hart, M.N., Mohring, F., et al. (2020a) The plasmodium falciparum artemisinin susceptibility-associated ap-2 adaptin μ subunit is clathrin independent and essential for schizont maturation. MBio 11.

      Henrici, R.C., Schalkwyk, D.A. van, and Sutherland, C.J. (2020b) Modification of pfap2μ and pfubp1 Markedly Reduces Ring-Stage Susceptibility of Plasmodium falciparum to Artemisinin in Vitro. Antimicrob Agents Chemother 64.

      Henriques, G., Hallett, R.L., Beshir, K.B., Gadalla, N.B., Johnson, R.E., Burrow, R., et al. (2014) Directional selection at the pfmdr1, pfcrt, pfubp1, and pfap2mu loci of Plasmodium falciparum in Kenyan children treated with ACT. J Infect Dis 210: 2001–2008.

      Heredero-Bermejo, I., Varberg, J.M., Charvat, R., Jacobs, K., Garbuz, T., Sullivan, W.J., and Arrizabalaga, G. (2019) TgDrpC, an atypical dynamin-related protein in Toxoplasma gondii, is associated with vesicular transport factors and parasite division. Mol Microbiol 111: 46–64.

      Hirst, J., Lui, W.W.Y., Bright, N.A., Totty, N., Seaman, M.N.J., and Robinson, M.S. (2000) A family of proteins with γ-adaptin and VHS domains that facilitate trafficking between the trans-golgi network and the vacuole/lysosome. J Cell Biol 149: 67–79.

      Hirst, J., and Robinson, M.S. (1998) Clathrin and adaptors. Biochim Biophys Acta - Mol Cell Res 1404: 173–193.

      Hoeijmakers, W.A.M., Miao, J., Schmidt, S., Toenhake, C.G., Shrestha, S., Venhuizen, J., et al. (2019) Epigenetic reader complexes of the human malaria parasite, Plasmodium falciparum. Nucleic Acids Res 47: 11574–11588.

      Jonscher, E., Flemming, S., Schmitt, M., Sabitzki, R., Reichard, N., Birnbaum, J., et al. (2019) PfVPS45 Is Required for Host Cell Cytosol Uptake by Malaria Blood Stage Parasites. Cell Host Microbe 25: 166-173.e5.

      Kimmel, J., Schmitt, M., Sinner, A., Jansen, P.W.T.C., Mainye, S., Ramón-Zamorano, G., et al. (2023) Gene-by-gene screen of the unknown proteins encoded on Plasmodium falciparum chromosome 3. Cell Syst 14: 9-23.e7.

      Koreny, L., Mercado-Saavedra, B.N., Klinger, C.M., Barylyuk, K., Butterworth, S., Hirst, J., et al. (2023) Stable endocytic structures navigate the complex pellicle of apicomplexan parasites. Nat Commun 14: 2167.

      Kumari, V., Singh, A.P., Singh, J., Sharma, R., Akhter, M., Mishra, P.K., et al. (2018) Biochemical characterization of unusual cysteine protease of P. falciparum, metacaspase-2 (MCA-2). Mol Biochem Parasitol 220: 28–41.

      Lazarus, M.D., Schneider, T.G., and Taraschi, T.F. (2008) A new model for hemoglobin ingestion and transport by the human malaria parasite Plasmodium falciparum. J Cell Sci 121: 1937–1949.

      Lopez-Hernandez, F.J., Ortiz, M.A., Bayon, Y., and Piedrafita, F.J. (2003) Z-FA-fmk inhibits effector caspases but not initiator caspases 8 and 10, and demonstrates that novel anticancer retinoid-related molecules induce apoptosis via the intrinsic pathway. Mol Cancer Ther 2: 255–263.

      Lord, S.J., Velle, K.B., Mullins, R.D., and Fritz-Laylin, L.K. (2020) SuperPlots: Communicating reproducibility and variability in cell biology. J Cell Biol 219.

      MalariaGEN, Ahouidi, A., Ali, M., Almagro-Garcia, J., Amambua-Ngwa, A., Amaratunga, C., et al. (2021) An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples. Wellcome open Res 6: 42.

      Marti, M., Good, R.T., Rug, M., Knuepfer, E., and Cowman, A.F. (2004) Targeting malaria virulence and remodeling proteins to the host erythrocyte. Science 306: 1930–3.

      Mesén-Ramírez, P., Bergmann, B., Elhabiri, M., Zhu, L., Thien, H. von, Castro-Peña, C., et al. (2021) The parasitophorous vacuole nutrient pore is critical for drug access in malaria parasites and modulates the fitness cost of artemisinin resistance. Cell Host Microbe 0: 283.

      Mesén-Ramírez, P., Bergmann, B., Tran, T.T., Garten, M., Stäcker, J., Naranjo-Prado, I., et al. (2019) EXP1 is critical for nutrient uptake across the parasitophorous vacuole membrane of malaria parasites. PLoS Biol 17: e3000473.

      Mukherjee, A., Crochetière, M.-È., Sergerie, A., Amiar, S., Thompson, L.A., Ebrahimzadeh, Z., et al. (2022) A Phosphoinositide-Binding Protein Acts in the Trafficking Pathway of Hemoglobin in the Malaria Parasite Plasmodium falciparum. MBio 13.

      Otto, T.D., Wilinski, D., Assefa, S., Keane, T.M., Sarry, L.R., Böhme, U., et al. (2010) New insights into the blood-stage transcriptome of Plasmodium falciparum using RNA-Seq. Mol Microbiol 76: 12–24.

      Robinson, M.S., Sahlender, D.A., and Foster, S.D. (2010) Rapid Inactivation of Proteins by Rapamycin-Induced Rerouting to Mitochondria. Dev Cell 18: 324–331.

      Sabitzki, R., Schmitt, M., Flemming, S., Jonscher, E., Hoehn, K., Froehlke, U., and Spielmann, T. (2023) Identification of a Rabenosyn-5 like protein and Rab5b in host cell cytosol uptake reveals conservation of endosomal transport in malaria parasites. bioRxiv 2023.04.05.535711.

      Simwela, N. V., Hughes, K.R., Roberts, A.B., Rennie, M.T., Barrett, M.P., and Waters, A.P. (2020) Experimentally engineered mutations in a ubiquitin hydrolase, UBP-1, modulate in vivo susceptibility to artemisinin and chloroquine in plasmodium berghei. Antimicrob Agents Chemother 64.

      Spielmann, T., Gras, S., Sabitzki, R., and Meissner, M. (2020) Endocytosis in Plasmodium and Toxoplasma Parasites. Trends Parasitol 36: 520–532.

      Subudhi, A.K., O’Donnell, A.J., Ramaprasad, A., Abkallo, H.M., Kaushik, A., Ansari, H.R., et al. (2020) Malaria parasites regulate intra-erythrocytic development duration via serpentine receptor 10 to coordinate with host rhythms. Nat Commun 11.

      Traub, L.M., Downs, M.A., Westrich, J.L., and Fremont, D.H. (1999) Crystal structure of the α appendage of AP-2 reveals a recruitment platform for clathrin-coat assembly. Proc Natl Acad Sci U S A 96: 8907–8912.

      Wagner, M.P., Formaglio, P., Gorgette, O., Dziekan, J.M., Huon, C., Berneburg, I., et al. (2022) Human peroxiredoxin 6 is essential for malaria parasites and provides a host-based drug target. Cell Rep 39: 110923.

      Wall, R.J., Zeeshan, M., Katris, N.J., Limenitakis, R., Rea, E., Stock, J., et al. (2019) Systematic analysis of Plasmodium myosins reveals differential expression, localisation, and function in invasive and proliferative parasite stages. Cell Microbiol 21.

      Wan, W., Dong, H., Lai, D.-H., Yang, J., He, K., Tang, X., et al. (2023) The Toxoplasma micropore mediates endocytosis for selective nutrient salvage from host cell compartments. Nat Commun 14: 977.

      Wichers-Misterek, J.S., Binder, A.M., Mesén-Ramírez, P., Dorner, L.P., Safavi, S., Fuchs, G., et al. (2023) A Microtubule-Associated Protein Is Essential for Malaria Parasite Transmission. MBio .

      Wichers, J.S., Gelder, C. van, Fuchs, G., Ruge, J.M., Pietsch, E., Ferreira, J.L., et al. (2021a) Characterization of Apicomplexan Amino Acid Transporters (ApiATs) in the Malaria Parasite Plasmodium falciparum. mSphere 6.

      Wichers, J.S., Mesén-Ramírez, P., Fuchs, G., Yu-Strzelczyk, J., Stäcker, J., Thien, H. von, et al. (2022) PMRT1, a Plasmodium -Specific Parasite Plasma Membrane Transporter, Is Essential for Asexual and Sexual Blood Stage Development. MBio 13.

      Wichers, J.S., Scholz, J.A.M., Strauss, J., Witt, S., Lill, A., Ehnold, L.-I., et al. (2019) Dissecting the Gene Expression, Localization, Membrane Topology, and Function of the Plasmodium falciparum STEVOR Protein Family. MBio 10: e01500-19.

      Wichers, J.S., Tonkin-Hill, G., Thye, T., Krumkamp, R., Kreuels, B., Strauss, J., et al. (2021b) Common virulence gene expression in adult first-time infected malaria patients and severe cases. Elife 10.

      Wichers, J.S., Wunderlich, J., Heincke, D., Pazicky, S., Strauss, J., Schmitt, M., et al. (2021c) Identification of novel inner membrane complex and apical annuli proteins of the malaria parasite Plasmodium falciparum. Cell Microbiol 23: e13341.

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      Referee #1

      Evidence, reproducibility and clarity

      With the emergence and spread of resistance to Artemisinin (ART), a key component of current frontline malaria combination therapies, there is a growing effort to understand the mechanisms that lead to ART resistance. Previous work has shown that ART resistant parasites harbour mutations in the Kelch13 protein, which in turn leads to reduced endocytosis of host haemoglobin. The digestion of haemoglobin is thought to be critical for the activation of the artemisinin endoperoxide bridge, leading to the production of free radicals and parasite death. However, the mechanisms by which the parasites endocytose host cell haemoglobin remain poorly understood.

      Previous work by the authors identified several proteins in the proximity of K13 using proximity-based labelling (BioID) (Birnbaum et al. 2020). The authors then went on to characterise several of these proteins, showing that when proteins including EPS15, AP2mu, UBP1 and KIC7 are disrupted, this leads to ART resistance and defects in endocytosis leading to the hypothesis that these two processes are inextricably linked.

      In this manuscript, Schmidt et al. set themselves the task of characterising more K13 component candidates identified in their previous work (Birnbaum et al. 2020) that were not previously validated or characterised. They chose 10 candidates and investigated their localisations, and colocalisation with K13, and their involvement in endocytosis and in vitro ART resistance, 2 processes mediated by K13 and some members of the K13 compartments

      The authors show that of their 10 candidates, only 4 can be co-localised with K13. Then, using a combination of targeted gene disruption (TGD) as well as knock sideways (KS), they characterised these 4 proteins found in the K13 compartment. They show that MyoF and KIC12 are involved in endocytosis and are important for parasite growth, however their disruption does not lead to a change in ART sensitivity. The authors also confirm the findings of their previous publication (Birnbaum et al. 2020), using a slightly different TGD, that MCA2 is involved in ART resistance, however they did not check whether its disruption impacts haemoglobin uptake. They also show that KIC11 is not involved in mediating haemoglobin uptake or ART resistance. To finish, the authors used AlphaFold to identify new domains in the proteins of the K13 compartment. This led them to the conclusion that vesicle trafficking domains are enriched in proteins of the K13 compartment involved in endocytosis and in vitro ART resistance.

      The majority of the experiments conducted by the authors are performed to a good standard in biological and technical replicates, with the correct controls. Their findings provide confirmation that their 4 candidate genes seem to be important for parasite growth, and show that some of their candidates are involved in endocytosis. While the KD and KS approaches employed by the authors to study their candidate genes each have their own advantages and can be excellent tools for studying a large sets or genes, this manuscript highlights the many limitations of these approaches. For example, the large tag used for the KS approach can mislocalise proteins or disrupt their function (as is the case for MyoF), resulting in spurious results, or indeed the inability to generate the tagged line (as is the case for MCA2). The KS approach also makes the results of a protein with a dual localisation, like KIC12, extremely difficult to interpret.

      Moreover, the manuscript is disjointed at times, with the authors choosing to conduct certain experiments for only a subset of genes, but not for others. For example, considering that the aim of this paper was to identify more proteins involved in ART resistance and endocytosis, it is confusing why the authors do not perform the endocytosis assays for all their selected proteins, and why they do not do this for the proteins they identify in their domain search. There is significant room for improvement for this manuscript, and a generally interesting question. But in it's current format, other than confirming that MCA2 is involved in ART resistance (which was already known from the Birnbaum paper), the authors do not further expand our understanding of the link between ART resistance and endocytosis in this manuscript.

      Major Comments

      line 31: please change defined to characterised - defined suggests that novel proteins were identified in this study, which is not the case.

      line 37: please change 'second' to "another". As explained further below, the authors identified 3 classes of proteins (confer ART resistance + involved in HCCU, involved in HCCU only, or involved in neither).

      Line 40: You define KIC11 as essential but according to your data some parasites are still alive and replicating 2 cycles after induction of the knock sideways. Please consider changing "essential" to "important for asexual parasite growth"

      Line 40: please change 'second group' to 'this group'

      line 41: state here that despite it being essential, it is unknown what it is involved in.

      Line 50: the authors should state here that there is actually a reversal in this trend over the last few years.

      Line 54: please separate out the references for each of the two statements made in this line (a: that ART resistance is widespread in SEA, and b: that ART resistance is now in Africa) Reference 14 also seems to reference ART resistance in Amazonia - which is not covered by the statement made by the authors (in which case the authors should state ART is now present in Africa and South America). The authors should also reference PMID: 34279219 for their statement that ART resistance is now found in Africa (albeit a different mutation to the one found in SEA).

      Line 65: it is also worth mentioning here that there are other mutations in proteins other than K13, such as AP2mu and UBP1 (PMID: 24994911;24270944) that can lead to ART resistance.

      Line 80, 86: ref 43 is misused. Reference 43 refers to Maurer's clefts trafficking which takes place in the erythrocyte cytosol and is not involved in haemoglobin uptake as far as I know. Please replace ref 43 with one showing the role of actin in haemoglobin uptake.

      Line 98: the authors state here that they 'identified' further candidates from the K13 proxiome. This suggests that they identified new proteins in this paper, when in fact the list was already generated in ref 26. All they did was characterise proteins from that list that were not previously characterised. The authors should therefore remove identified from this statement.

      Line 107-108: it is not clear from this sentence why these proteins were left out of the initial analysis in Ref 26. A sentence here explaining this would be valuable for the reader.

      Line 117-123: The authors say that PF3D7_0204300, PF3D7_1117900 and PF3D7_1016200 were not studied because they were not in the top 10 hits. However, the current organisation of Supplementary Table 1 shows all 3 proteins among the top 10 hits (MyoF, KIC12, UIS14 and 0907200 being after them). I think the authors should reorganise their table. It is also unclear according to what the proteins in the table are ranked. Could the authors indicate the metric used for the ranking?

      Line 129-141: Can the authors be clearer with their explanations of the identification of mutation Y1344Stop? One dataset (ref 61) shows that 52% of African parasites have a mutation in MCA2 in position 1344 leading to a STOP codon. But another dataset (ref 62) shows that the next base is also mutated, reverting the stop codon. That should have been seen in the first dataset as well. Could the authors please clarify.

      Line 147: the authors say that MCA2 is expressed throughout the intraerythrocytic cycle as shown by live cell imaging. In Birnbaum et al 2020 fig 4I, the authors show that MCA2 is mainly expressed between 4 and 16hpi. But in Figure 1B of this manuscript there is a clear multiplication of MCA2 signal between trophozoite and schizont. How do the authors explain this discrepancy? Could expression of the truncated MCA2 be different than the full length? This cannot be assessed as expression and localisation of the full-length HA tag MCA2 is not shown in Schizonts. MCA2 expression seems also different for the MCA2TGD-GFP with no expression in rings.

      Line 158: would it not have been more useful for the authors to have episomally expressed MCA2-3xHA in their MCA2Y1344STOP-GFPENDO line to make sure that the truncated protein is indeed going to the correct compartment? The experiments done by the authors suggests that the MCA2Y1344STOP goes to the right location but does not really confirm it.

      Line 191: it is stated that MCA2 confers resistance independently of the MCA domain, however in both the MCA2-TGD and MCA2Y1344STOP-GFPENDO parasites, the MCA domain is deleted, and for both parasites, there is resistance (albeit to a lower level in the MCA2Y1344STOP-GFPENDO line). Therefore, how can the authors state that the ART resistance is independent of the MCA domain? This statement should be that resistance is dependent on the loss of the MCA domain.

      Line 192: Why did the authors not check if MCA2 is involved in endocytosis? They state later on in the manuscript that they did not do endocytosis assays with TGD lines, however if the authors include the correct controls, this could be easily done. It would also be really interesting to see whether endocytosis gets progressively worse going from WT to MCA2Y1344STOP to MAC2TGD. This experiment (as well as doing endocytosis assays for KIC4 and KIC5 TGD lines) would drastically increase the impact of this study. These experiments would not take more than 3 weeks to perform, and would not require the generation of new lines.

      The authors should consider re-organising the MCA2 section, first showing that the 3xHA tagged line colocalises with K13, then performing the new truncation.

      Line 197: Once again ref 43 is not correct to illustrate that actin/myosin is involved in endocytosis

      Line 202: the authors state that MyoF localises near the food vacuole from ring stage/trophs onwards. However, how can this statement be made in schizonts based on these images (Fig. 2A), where it doesn't look like MyoF is anywhere near the FV? This statement can only be made for schizonts if co-localised with a FV marker (which is done in Fig. 2B), however, based on the number of MyoF foci, it appears that this was not done for schizonts. Please either remove the statement that MyoF is near the food vacuole from trophs onwards (because it is only seen near the FV up until trophs) or show the data in Fig. 2B of schizonts to substantiate these claims.

      Line 204-206: what does this statement bring to the paper? Is it to show that it is the real localisation of MyoF because 2 tag cell line show the same localisation? I don't think this is needed, especially as later in the manuscript an HA-tag MyoF line is used and show similar localisation.

      Line 212: The overlap of K13 with MyoF in Fig 2C 3rd panel (1st trophozoite panel) is not obvious, especially as the MyoF signal seems inexistant. I would advise the authors to replace with a better image. Also, why are there no images of schizonts shown in Figure 2C?

      Line 217: the spatial association of MyoF with K13 is very different when it is tagged with GFP and when it is tagged with 3xHA. The way the authors word it here, it seems that there is agreement with the two datasets, when this is not in fact the case (59% overlap for MyoF-GFP and only 16% overlap with MyoF-3xHA). These data suggest that the GFP and the multiple FKBP tags are doing something to the protein and therefore maybe the ensuing results using this line should not be trusted or be taken with a pinch of salt.

      Line 219: the authors state here that they could not detect MyoF-GFP in rings, when in Figure 2C they show MyoF-GFP in rings, and also show that they could detect MyoF in Sup Fig. 3B with the 3xHA tagged line. Is this a labelling mistake in Figure 2C? If the authors could indeed not see MoyF-GFP in rings, this statement should have been made when Figure 2A was presented, and not so late in the manuscript, which causes confusion. Line 237: Showing a DNA marker (DAPI, Hoescht) for Figure 2E, and subsequent figures using mislocalisation to the nucleus, would help the reader assess efficiency of the mislocalisation.

      Line 254-256: authors should show the results of the bloating assay for parental 3D7 parasites (+ and - rapalog) to see whether the MyoF line - rapalog has increased baseline bloating. This applies to all subsequent FV bloating assays.

      Line 254-257: The authors say that because fewer parasites show a bloated food vacuole upon inactivation of MyoF it means that less hemoglobin reached the food vacuole. I understand the authors statement, however, shouldn't they look at the size of the food vacuole, instead of the number of parasites with bloated FV, to make such a statement? This has been done for KIC12 so why not doing it for MyoF?

      Line 259-261: these results would be difficult to interpret namely because the authors have dying parasites, which is exacerbated with the protein being knocked sideways. The authors should mention the pitfalls their knock sideways and tagging design here.<br /> Line 260-261: RSA is an assay relying on measuring parasite growth 1 cycle after a challenge with ART for 6 hours.

      Line 261-263: the authors sate that MyoF has a function in endocytosis but at a different step compared to K13 compartment proteins. I am not sure what they mean here. Can this be clarified? Do the authors mean that it is involved in endocytosis but not in ART resistance? If so, this is a very difficult statement to make since the parasites are dying. Is there any evidence of point mutations in MyoF in the field?

      Line 298: the authors state that there is no growth defect in the first cycle when rapalog is added to the KIC11 line, however based on Figure 3D, there is evidently a 25% reduction in growth compared to - rapalog at day 1 post treatment, and a 60% reduction by day 2, which is still within the 1st growth cycle. The authors should either revise their statement or provide an explanation for these findings. The authors should also explain why their Giemsa data in Fig. 3E is not in accordance with their FACS data.

      Line 301: KIC11 could also be important very early for establishment of the ring stage for example for establishment of the PV. Also, was mislocalisation assessed in rapalog-treated parasites at 72 hours or in cycle 3?

      Line 311: the authors should change the sentence from 'not related to endocytosis' to 'not related to endocytosis or ART resistance'.

      Line 323-325: Authors say that a nuclear GFP signal can be observed in early schizonts for KIC12. According to the pictures provided in Figure 4A and Figure S5A it is not very obvious. Also faint cytoplasmic GFP signal could only be background as we can see that exposure is higher for schizont pictures

      Line 326-328: The authors say that kic12 transcriptional profile indicate mRNA levels peak (no s at peak) in merozoites. Should they show live cell imaging of merozoites then? Because from the Figure 4A schizont pictures where schizonts are almost fully segmented no signal can be observed. Line 347: The authors state that using the Lyn mislocaliser the nuclear pool of KIC12 is inactivated by mislocalisation to the PPM. This tends to suggest that only the nuclear pool of KIC12 is mislocalised. How is it possible that only the nuclear pool is mislocalised? Line 368-369: Effect was also only partial for MyoF. Why didn't you measure the same metrics for MyoF? Line 379: you don't know if all proteins acting later in endocytosis will have an increased number of vesicles as a phenotype

      Line 413-414: The authors state that no growth defect was observed upon KS of 1365800. Is growth alone enough to say that there is no impact on endocytosis?

      Line 432: in this section, the authors state that KIC4 and KIC5 seem to have domains that may suggest these proteins are involved in endocytosis, based on the alpha fold data that is publicly available. Considering the authors have TGD-SLI versions of these lines (Birnbaum et al. 2020) and have already confirmed in this previous publication that they confer resistance to ART; it would make sense to look at endocytosis for these genes. This would be a relatively simple and straightforward experiment, taking no longer than two to three weeks, and would require no additional reagents or line generation. Doing these experiments would add a lot more weight to this final section. The authors later state that KIC4 and 5 are TGD lines, so not the best for endocytosis assays. It is unclear why this would be difficult to do if an adequate control is contained in the experiment (such as parental 3D7). It explains why they did not perform the MCA2 endocytosis assays further up, but in my opinion, an attempt at doing these assays is important and would significantly increase the impact of this paper.

      Line 490-493: the authors state that the K13 compartment proteins fall in two groups, some that are involved in ART resistance AND endocytosis, and some that have different functions. However, in this manuscript the authors have demonstrated 3 flavours that K13 compartment proteins can come in: • Some that confer ART resistance and are involved in HCCU (MCA2) • Some that are involved in HCCU but not ART resistance (MyoF & KIC12) • Some that are involved in neither (KIC11) The authors should therefore revise this statement.

      Line 508: the authors state that they expanded the repertoire of K13 compartments, when in fact they functionally analysed them - they did not do another BioID to identify more candidates.

      Line 570-572: has anyone ever tested whether CytoD or JAS treatment in rings, is sufficient to mediate ART resistance? Something similar to what was done in PMID 21709259 with protease inhibitors. If not this would be a pretty interesting experiment for the authors to do that could shed more light on the MyoF data. It would take maybe 2 weeks to do and not require the generation of any new lines. This would clarify whether other Myosins other than MyoF are involved in endocytosis, as is suggested by previous publications (PMID: 17944961).

      Line 608: inhibitors targeting the metacaspase domain of MCA2 may inadvertently inactivate other essential parts of the protein. They authors should acknowledge this possibility in the text.

      Line 624-625: the authors state that MyoF is 'lowly expressed in rings' - indeed this is the case in their MyoF-2xFKBP-GFP-2xFKBP line which the authors established has defects due to the tag, but it appears from their MyoF-3xHA tagged line that it is expressed in rings. The authors should therefore revise their statement, and be careful of making claims based on their defective line and using fluorescence imaging as their only metric. If they do want to make the statement that it is not there in rings, they should also do a western blot, which is much more sensitive since it amplifies the signal compared to an image of one parasite.

      Line 635: arguably this is the 3rd variety and not the 2nd (the authors already mentioned 2 types - ones that are involved in HCCU AND ART and those involved in HCCU only). See comment for line 490-493 above.

      Line 785: Bloated food vacuole assay/E64 hemoglobin uptake assay method specify that a concentration of 33mM E64protease inhibitor was used. However, in reference 44, cited in the manuscript, a concentration of 33µM E64 was used. Please confirmed if this is just a typo or if 1000x E64 concentration was used which renders the experiment invalid.

      Line 788: it is unclear from this section what is considered a bloated food vacuole - is there an area above which the FV is considered bloated? Do the authors do these measurements manually or use an addon in FIJI/ImageJ? What is the cutoff for if a FV is bloated? Please clarify. Additionally, for the representative images + rapalog for Figures 2H and 4H, it would be useful to see where the authors delineate the FV (add a white circle showing what is actually measured).

      Line 863-864: this sentence seems to be out of place.

      Line 875: the authors state that there is a light blue wedge, when the circle consists of grey and black wedges. Please revise this.

      Line 1059-1061: it is unclear whether the individual growth curves are different clones or whether they are just the same experiment repeated? If it is the latter, then why are they not combined, as is traditionally done?

      Line 919-924: the authors mention a blue and red line, but there is only a black line in figure 3D. Moreover, the experiment of using the LYN mislocaliser was only done for KIC12 according to the manuscript. Additionally, the y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis there are several days. In the text it says there is no growth defect until the second cycle, but from this graph it appears the growth defect is evident as early as 1 day post rapalog treatment. Can the authors please clarify and correct the issues pointed out.

      Figure 1 panel B & C: the label of the figure where the signal from MCA2Y1344STOP-GFP is shown with the DAPI signal overlayed is deceptive since it suggests that this is the signal of full length MCA2. Please change the label of this panel from MAC2/DAPI to MCA2Y1344STOP/DAPI. The same is true for Panel C for the image labeled MCA2/K13 - please change this to MCA2Y1344STOP/K13.

      Figure 2B: what stages are these parasites? Please state this in the figure. Based on the MyoF pattern, it looks like rings in the upper panel and trophs in the bottom pannel. Why were schizonts not shown?

      Figure 2D&F: it is not very meaningful when growth assays are shown as a final bar after 4 days of growth. It is much more useful and informative to see a growth curve instead (as is shown in the supplementary), since it shows if the defect is apparent in the first growth cycle or later. With the way the data is currently shown, this is not apparent. I would advise the authors to switch the graph in 2F out of a combined graph of all the biological replicates growth curves for S3D - showing error bars.

      Figure 3: why were the calculation of FV area, parasite area and FV/parasite area only done for KIC12 and not done for MyoF? It would be interesting to see if any of these values are different for MyoF - whether the parasites are smaller in area and therefore FV smaller. Please present them Figure 2. Images should be already available and would not require further experiments to be done, only the analysis.

      Figure 3B: why is there no spatial association assessment for KIC11 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins.

      Figure 3D: The y axis of the figure states relative growth day 4[%] compared to rapalog, but then on the x axis the experiment takes place over several days. Is this a typo in the y axis? Additionally, the authors state in line 287-290 that the growth defect upon addition of rapalog is only seen in the second cycle, but from this graph it appears the growth defect is already evident 1 day post rapalog addition. The figure legend also does not make sense for this figure since it mentions a blue and a red line, when there is only a black line present. The legend also mentions the LYN mislocaliser which was used for KIC12 not KIC 11 (see above).

      Figure 3E: the colour for Control and Rapalog 4 hpi are very similar and very hard to discern. Please choose an alternative colour or add a pattern to one of the samples. The y axis is also missing a label. Is this supposed to be parasitemia (%)?

      Figure 4A: the ring shown in this figure does not appear to be a ring (it is far too large and appears to have multiple nuclei?). Do the authors have any other representative images to show instead?

      Figure 4B: why is there no spatial association assessment for KIC12 and K13 as was done for the MCA2 and MyoF? The authors should show a pie chart showing the degree of association here as was done for the other proteins. This should be done for the different life cycle stages considering the changing localisation of KIC12.

      Figures 4C&E: it is extremely important to show the DNA stain in both these samples considering that a portion of KIC12 is in the nucleus! Please add the DAPI signal for these figures (as for all other figures!).

      Figure 4E: this figure should be presented before 4D (considering the line being presented in 4E is used in an experiment in 4D). The authors should switch the order of these two.

      It is unclear why in many of the fluorescence images the authors do not show the DAPI signal - particularly when colocalising with K13 and when doing the knock sideways experiments. Please add these images to the figures - I would assume they have already been taken, so would simply involved adding the images to the panel.

      Throughout the manuscript, there is no western blot confirming the correct size of their modified proteins. This should be provided.

      None of the figures are appropriate for individuals with colour blindness, limiting their accessibility to the paper. Please change the colour schemes for all fluorescent images using magenta/green or an alternative colour combination appropriate for colourblind individuals.

      Minor Comments

      line 29: remove 'are'.

      Line 29: the text says "HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins are among the few proteins so far functionally linked to this process." The sentence should be: 'HCCU is critical for parasite survival but is poorly understood, with the K13 compartment proteins among the few proteins so far functionally linked to this process."

      line 44: remove 'the'

      Line 48: consider mentioning here that malaria is caused by the parasite Plasmodium - otherwise the first mention of parasite in line 52 is confusing for the non-specialist reader.

      Line 49: estimated malaria-related death and case numbers are from the 2021 WHO World malaria report. You cite the 2020 WHO World malaria report.

      Line 53: please insert the word 'have' between now and also.

      Line 54: please change 'was linked' to is linked

      Line 72: I would specify that free heme is toxic to the parasite. Especially as you mention that hemozoin is nontoxic. Sentence would be "where digestion results in the generation of free heme, toxic to the parasite, which is further converted into nontoxic hemozoin"

      Line 90: authors should either say "in previous works" or "in a previous work"

      Line 91: "We designated these proteins as K13 interaction candidates (KICs)"

      Line 95: please change 'rate' to number

      Line 109: Please include a coma before (ii).

      Line 112: as shown by Rudlaff et al in the paper you are citing, PPP8 is actually associated with the basal complex. You can say that "(ii) were either linked or had been shown to localise to the inner membrane complex (IMC) or the basal complex (PF3D7...).

      Line 114: Protein PF3D7_1141300 is called APR1 in the manuscript but ARP1 in Supplementary Table 1. Please correct.

      Line 131: please define SNP - this is the first use of the acronym.

      Line 133-134: South-East Asia instead of "South Asia"

      Line 135: please explain what TGD is - it is referred to over and over again in the manuscript without ever being explained.

      Line 145: change 'Western blot' to western blot - only Southern blot is capitalised since it is named after an individual, while the other techniques are not.

      Line 152: add "the" between 'and spatial'

      Line 158: please define SLI as selected linked integration, since it is the first use of the acronym.

      Line 178: introduce a coma after protein. Sentence should be "Proliferation assays with the MCAY1344STOP-GFPendo parasites which express a larger portion of this protein, yet still lacking the MCA domain (Figure 1), indicated no growth ...

      Line 195: the authors could mention that MyoF was previously called MyoC in the Birnbaum 2020 paper. I wanted to check back in the Birnbaum 2020 paper and could not find MyoF

      Line 200: "Expression and localisation of the fusion protein was analysed by fluorescent microscopy". Why expression was not analysed also by western Blot same as for MCA2?

      Line 204: I could not find any mention of MyoF (Pf3D7_1329100) in reference 65. Please remove reference 65 if not correct. Also reference 66 looks at Plasmodium chabaudii transcriptomes so I would specify that "This expression pattern is in agreement with the transcriptional profile of its Plasmodium chabaudii orthologue"

      Line 208: Please indicate a reference for P40 being a marker of the food vacuole

      Line 220-224: The authors should consider changing to " Taken together these results show that MyoF is in foci that are mainly close to K13 and, at times, overlapping, indicating that MyoF is found in a regular close spatial association with the K13 compartment."

      Line 255: In Figure 2H, and subsequent figures showing bloated FV assay, I would delineate the food vacuole with dashed line as in Birnbaum et al. 2020 to help the reader understanding where the food vacuole is.

      Line 265-266: Here the title says that KIC11 is a K13 compartment associated protein, but the title of Figure 3 says KIC11 is a K13 compartment protein. I noticed that you make the difference between K13 compartment protein et K13 compartment associated protein for MyoF for example which is not clearly associated with the K13 compartment. Which one is it for KIC11?

      Line 309-310: indicate a reference for your statement "which is in contrast to previously characterised essential K13 compartment proteins".

      Line 377: Figure 4I, please correct 1st panel Y axis legend

      Line 404: replace "dispensability" with dispensable

      Line 416: can the authors provide any speculation as to why they observed these proteins as hits in the BioID experiments?

      Line 451: Where the "97% of proteins containing these domains also contain an Adaptin_N domain and function in vesicle adaptor complexes as subunit " come from. Do you have a reference?

      Line 465-467: the same could be said for KIC4 as it also has a VHS domain.

      Line 477-479: Can be rephrased to "However, we found this protein as being likely dispensable for intra-erythrocytic parasite development and no colocalisation with K13 could be demonstrated, suggesting a limited role for PF3D7_1365800 in endocytosis. Or something like that. Makes it clearer.

      Line 535: Have AP-2 or AP-2 been shown to be at the K13 compartment?

      Line 569: reference 43 is wrong

      Line 746: typo "ot" instead of or.

      Line 801: method for Domain Identification using AlphaFold specify that RMSDs of under 5Å over more than 60 amino acids are listed in the results. However, there is a typo in Figure 5B for KIC5 where it says "RMSD 4.0 Å over 8 aa". Please correct.

      Line 856: In Figure 1E, please use the same Y axis legend as in Figure 2D "relative growth at day 4 [%] compared with 3D7"

      Figure S1: Some PCR gels check for integration are presented as 5', 3' and ori whereas other gels are presented as ori, 5' and 3'. This is confusing. Figure S1: Why was the expression of only MCA2 was verified by Western blot? What about the other proteins?

      Line 493: Considering KIC11 was not involved in HCCU or ART resistance it might be worth mentioning in this section that it is of note that there are no domains detected that would be involved in endocytosis.

      Line 503-506: is it wise to generate more drugs that target a pathway that is already highly susceptible to mutations? The authors should add a statement explaining how this might be avoided.

      Throughout, scale bars are stated in the figure legends at the end of the legend. This is a slightly confusing format. The authors should consider stating the scale bar for each sub-legend where a fluorescence image is taken.

      Referees cross-commenting

      After reading reviewer 2 and 3's comments, I think there are significant overlaps in the key points raised in terms of questions about fusion proteins and their potential partial mis-localisation, better descripton of results and target selection. Overall I think we agree that the work has potential, but in its current form does not represent a major advance. It would be immensely helpful if the manuscript would be carefully edited for a better flow and linear description of results.

      Significance

      The authors set out to test whether other proteins that are in the vicinity of K13 are involved in mediating ART resistance and endocytosis. This is an interesting question. However, other than MCA2 which was already known to be involved in mediating ART resistance (and was not tested for its involvement in endocytosis), none of their candidate proteins seem to be involved in mediating both these functions. The authors show that the other proteins tested appear important for parasite growth, with KIC12 and MyoF involved in mediating endocytosis. While these findings are novel, the KS approach used by the authors casts some doubt over the findings, and would mean that these findings would have to be re-tested with a more reliable approach, such as the GlmS system or generating a conditional knockout using the DiCre system. Despite not advancing our understanding of ART resistance, or identifying further players involved in this process, this manuscripts provides two candidates that are involved in mediating endocytosis and a further candidate that appears to be important for parasite growth. Further work on these proteins will be required to understand their exact roles. As stated above, there is currently limited interest for these results (limited to researchers working on endocytosis in apicomplexan parasites and possibly the wider endocytosis field from an evolutionary perspective), however with further work, this could increase the impact and interest of this work substantially.

      The authors do not describe any novel methods/approaches within this work.

    1. it's a shame because I really like C# and the .NET standard library

      You can, by the way, target the design of the .NET APIs in your non-C# program and then just fill your own re-implementation that works just well enough to service your application's needs. This strategy is way too undervalued.

    1. a reusable component costs 3 to 5 times as much as a good module. The extra money pays for: ·         Generality: A reusable module must meet the needs of a fairly wide range of ‘foreign’ clients, not just of people working on the same project. Figuring out what those needs are is hard, and designing an implementation that can meet them efficiently enough is often hard as well. ·         Simplicity: Foreign clients must be able to understand the interface to a module fairly easily, or it’s no use to them. If it only needs to work in a single system, a complicated interface is all right, because the client has much more context. ·         Customization: To make the module general enough, it probably must be customizable, either with some well-chosen parameters or with some kind of programmability, which often takes the form of a special-purpose programming language. ·         Testing: Foreign clients have higher expectations for the quality of a module, and they use it in more different ways. The generality and customization must be tested as well. ·         Documentation: Foreign clients need more documentation, since they can’t come over to your office. ·         Stability: Foreign clients are not tied to the release cycle of a system. For them, a module’s behaviour must remain unchanged (or upward compatible) for years, probably for the lifetime of their system.   Regardless of whether a reusable component is a good investment, it’s nearly impossible to fund this kind of development.

      a reusable component costs 3 to 5 times as much as a good module. The extra money pays for: Generality[...] Simplicity[...] Customization[...] Testing[...] Documentation[...] Stability[...] ¶ Regardless of whether a reusable component is a good investment, it’s nearly impossible to fund this kind of development.

    1. Author Response

      Reviewer #1 (Public Review):

      This paper has significant strengths in taking a rich, quantitative, neurally-grounded approach to the development of human walking. It provides a rich empirical dataset of EMG and kinematic data at this challenging age, as well as sophisticated analyses of these data in terms of motor primitives, which are a concept that has recently been usefully applied to understanding human walking and its development.

      STRENGTHS

      It builds on emerging literature in this field and adds data at the key age of infancy-toddlerhood.

      It takes a longitudinal approach, sampling children at the ages of newborn, 3 months, and newly walking. This is still reasonably rare in developmental research and allows for a powerful, robust interpretation of data: the authors should be commended for taking this approach.

      WEAKNESSES

      Some aspects of the work could have been more clearly introduced. This includes neural aspects: the location of the CNS control centres at the spinal level, and which higher centres control them (e.g. brainstem); the justification for understanding primitives as modular (no cross-talk or feedback). It also includes developmental aspects: introducing the stepping reflex, and behavioural aspects of infant motor variability (e.g. Adolph, Hoch & Cole, TICS, 2018).

      The patterns relate to walking in a stereotypical manner, yet children's walking is full of skips, jumps, and climbs - both in relation to external obstacles and on even ground. Indeed, it is a challenge to get children to 'walk normally' in a lab. Thus, variability is in fact greater than is discussed here and this should be acknowledged.

      Thanks for the remarks. We reviewed the introduction and clarified these points. Mainly, we realized that we were not clear enough about the type of variability that we focused on, and added a paragraph at the top of the introduction to clearly define the different types of variability that exist during development and to specify that we only focus on the ability to produce a given coordination mode (like for example alternated leg movements) with various muscle activities (line 34-44). We also added some specification about the neural structures that are known to be involved in modularity in animals (line 53-58).

      The analyses are based on a limited sample of the data. (1) I am not clear on what basis the coders selected cycles, and why 5 cycles were selected. (2) It is not clear why certain movement parameters (cycle duration and flexion/extension proportions) and not others (e.g. step length, double support time) were selected. In particular, it is not clear why the authors focus on temporal, rather than spatial, variability. (3) Some data are based on stepping, and some on kicking. Because it's not clear that these are really equivalent, and because there are small samples of each (n<10), it's not clear that there is enough data to allow us to come to strong conclusions. The sample size should be justified - on the basis of power analyses and/or previous work in this area (e.g. Dominici, Science, n=40). From the results, where p values often hover around p=0.06, the paper seems underpowered to detect a decrease in variability with age for stepping kinematics and primitives.

      We initially limited to 5 the number of cycles to analyze in each individual and age in order to make the indexes of variability comparable across individuals and ages. However, as detailed in the general response above, in the new version of the manuscript we preprocessed (i.e. filtered and normalized) a different amount of data in each individual and age (i.e. between 5 and 22 cycles depending on what was available) and we reproduced every analysis of the paper for 5 randomly chosen combinations of 5 cycles when strictly more than 5 cycles were available (i.e. we used a bootstrapping approach, limiting the number of combinations to 5 because of the processing time of the algorithm). Therefore, every result presented in the paper correspond to an average value computed across these 5 random combinations (except when the number of available cycles was strictly equal to 5), which allowed to include a different number of steps in the analysis while keeping the indexes comparable across individuals and ages. This raised the number of cycles included in the analysis from 200 to 586.

      We do not present data on step length and double support time because we wanted to apply our analyses on the two behaviors (i.e. stepping and kicking) and there are no step length or support phase in kicking. Moreover, we do not have access to these data. In fact, the available space on the skin on newborns was limited after having disposed EMG sensors, and we could not dispose enough 3D markers to analyze step length. Furthermore, we had to record toddler’s walking in a room that was not equipped with motion capture, therefore we did not have access to any marker’s position at walking onset. As such, we report kinematic parameters that were available for each behavior, which are stride duration, variability of stride duration and percentage of extension phase. This was clarified in the manuscript line 581-583.

      As detailed in our general response, we had chosen a very conservative approach which reduced the amount of data that were presented in the original manuscript, however we systematically reviewed our data and we now present our analyses on 18 infants, of which 11 stepped at birth, 15 stepped at 3 months old, 15 kicked at birth, 15 kicked at 3 months old, and 15 were recorded at walking onset. Each infant was followed longitudinally and we only present data if they are available on at least two time points. The results were reinforced with this new number of included individuals, and the p values are stronger (see table S1 were all the p-values are reported, line 979).

      There are some points of interpretation that could have been clearer, for example highlighting how one might distinguish between variability as incidental (motor noise) or purposeful (for exploration); and how studying the time around walking onset can contribute to the broader literature on this topic.

      The main result of this study is that the structure of EMG variability evolves during the first year of life, but the origin of this variability (incidental or purposeful) remains unknown. Be it purposeful or incidental, variability might arise at any level of the nervous system (Dhawale et al., 2017), and here we propose that it arises at the level of primitives’ activation during early development. As this is coherent with the fact that different pharmacological or electrical stimuli applied to the spinal cord of neonatal rodents can generate variability (Kiehn and Kjærulff, 1996; Klein et al., 2010), we can hypothesize that such variability could be purposely generated at a supra-spinal level during early development. However, even if it is generated at this level, variability could result from an instability of the command rather than from purposeful explorations. Interestingly, the distinction itself might be challenging, because both types of variability (incidental or purposeful) might contribute to exploration: theoretically, variability might be useful for exploration and learning even if it has not been purposely generated by the individual (Dhawale et al., 2017). As such we used animal literature to make hypothesis about the origin of this variability but we are not aware or any protocol that could have helped to discriminate among the two. This was specified line 388-389: “As similar neurophysiological investigations cannot be conducted in human infants, discriminating among purposeful and incidental variability remains challenging,”.

      The time around walking onset was chosen to match previous literature on the topic (mainly, Dominici et al., (2011), but it also matches the period that is more and more recommended as a period when to intervene in early therapy. This was discussed line 469-471: “Overall, when compared with adult values (Figure 3, Figure 5, Table S3), our results suggest an immaturity of the modular system before and around walking onset, which confirms that infancy should be an ideal period of plasticity to benefit from in therapy (Ulrich et al., 2010; Morgan et al., 2021).”.<br /> As the age of walking onset is highly variable across infants (Martorell et al., 2006), we also chose to focus on walking onset rather than age to standardize recruitment along experience rather than age, as EMG variability is known to rapidly evolve with experience after a few months of walking experience (Chang et al., 2006). In the new version of the manuscript, we highlighted this variability by allocating legends according to the age of walking onset (Figure 2, Figure 3 and Figure 5, see Figure 3E detailing this legend).

      Reviewer #3 (Public Review):

      Hinnekens et al. examined the development of humans' leg movements as they learn to step, kick, and independently walk during infancy. An established theory argues that motor movements can be composed of a finite set of building blocks ("motor primitives"), just like any word can be composed of a finite set of letters. In their paper, Hinnekens et al. follow up this theory by longitudinally recording muscle activations of infants using EMG (at three time points: a few days after birth, at 3 months, and shortly after they learned to walk independently). The authors examined two modules that underlie the infants' stepping and two modules that underlie toddler walking, all based on previous literature. The authors also examined different modules that underlie infants' upright stepping and supine kicking. The authors used supervised machine learning (an advanced version of factor analysis) to identify the modules and to track their change at the different developmental time points. The authors found that trial-to-trial variability in the structure of primitives reduces from newborns to toddlers, even though the number of primitives increased. The authors relate these findings to motor exploration by arguing that newborns generate high variability with a low number of primitives.

      The paper has one clear strength - its longitudinal recordings. Unlike most papers in this area of research, the authors follow the same individuals from birth until they learn to walk and the comparison between the use of primitives is done on the same infants. This is certainly novel.

      That said, the contribution of the paper to the literature is unclear and it suffers from some critical weaknesses that challenge the current conclusions in the paper, based on the existing data.

      1) Although the data is based on longitudinal recordings, and this is certainly desirable, the paper is based only on 10 infants. Moreover, only seven infants contributed supine data at the first time points and only six infants contributed upright data at the different time points. The paper would benefit from a more reliable dataset that includes more infants and time points to compare. To conclude the authors' conclusions, much richer data is required.

      As detailed in our general response, we had chosen a very conservative approach which reduced the amount of data that were presented in the original manuscript, however we systematically reviewed our data and we now present our analyses on 18 infants, of which 11 stepped at birth, 15 stepped at 3 months old, 15 kicked at birth, 15 kicked at 3 months old, and 15 were recorded at walking onset. Each infant was followed longitudinally and we only present data if they are available on at least two time points. The results were confirmed by those analyses that yielded stronger p-values (see table S1, line 979).

      2) Relatedly, although the strength of longitudinal data is compared between individuals and has significant insights into individual differences in development, this was not clearly (sometimes not at all) discussed in the paper. The work would benefit from more focus on individual differences and a clear explanation of its contribution to the field from that aspect. The key arguments in the paper focus on the ratio between the number of primitives and the variability in each time point, but none of this from the lens of individual differences. This is challenging to do because there are not many individuals who contribute to the dataset but otherwise, it is not clear what the paper contributes to previous work and more critically.

      Thanks for the suggestion. To follow this remark, we modified each figure of the paper so the 18 individuals would each have their own color and could be followed across figures. Also, as the age of walking onset was different across infants, we allocated colors to each infant based on when they started to walk (Figure 2, Figure 3, Figure 5). Moreover, increasing our cohort highlighted some interindividual differences in the development of kicking only between birth and three months old (Figure 3, Figure 5, Table S1). This was discussed in a new paragraph of the discussion (line 469-487).

      3) The motivation for the paper is unclear. Why did the authors do what they did? Why is this important to do it the way they did? In the current manuscript, it is not clear why they used this design to get those conclusions.

      The main rational of the paper was to explore a paradox of the literature on early locomotor development: on one hand, newborn infants produce a highly variable muscular activity (Teulier et al., 2012), but on the other hand authors report that they produce rhythmic movement with a small number of invariant modules (Dominici et al., 2011; Sylos-labini et al., 2020). As the latest studies were based on averaged or single-step data, our main goal was to assess both EMG variability and features of modularity in the same cohort, in an attempt to refute or explain this paradox. We reviewed and clarified the introduction on this matter by clarifying the place of our study among the broader literature on variability in development (line 34-44) and by deepening explanations about the abovementioned paradox in relation to previous studies on infants’ modularity (line 72-96).

      4) The data selection process is also not clear. At each time point and from each infant, the authors examined 5 cycles from the same leg. The definition of a cycle was hip-flexion onset to another hipflexion onset on one side of hip extension. It is not clear what variability (measured by % of the cycle in flexion and extension) means in this case because infants hold their legs in one position for a long time. What are those 5 cycles? Why five? A lot of information is missing there about the arbitrary selection of analytic parameters. In addition, the authors argue they performed the same analyses with different parameters and that they got similar results. However, those results are not given in detail and it is hard to compare them with the authors' report.

      We entirely reviewed our data and less selection were applied in the current manuscript. Here is the complete data selection process:

      Among the 18 infants that we followed from birth on, 15 were followed until walking onset (among the other three, one had moved and the other two could not be seen around walking onset because of the covid pandemic). Around birth and three months old, in each infant we tried to elicit stepping (by holding the infant in an upright position with his feet above a surface) and kicking (by placing the infant in a supine position). Therefore, we systematically analyzed each video from every infant and every age to spot and count every alternated leg movement within the two behaviors. After this step, we checked the quality of EMG data for the 10 muscles that were recorded. As our analysis has to be based on the same number of muscles for each individual, if the quality of the signal was too low for even one muscle during a leg cycle, the cycle had to be removed from the analysis. After this check, if less than 5 alternated leg cycles were available, the whole trial was removed from the analysis. The rational is that the hypotheses that we tested were mainly about intra-individual variability and therefore analyses had to be based on a minimal number of cycles. In newborns this was particularly challenging because we were limited in recording time (1 to 2 minutes), moreover we did not always have qualitative EMG data because we always reduced the amount of adhesive surface on the skin for ethical reasons. Therefore for several babies we could not observe enough cycles to include them in the analysis, however in the current version of the manuscript we present data on 11 babies for newborn stepping, 15 babies for 3 mo stepping, 15 babies for newborn kicking, 15 babies for 3 mo kicking, and 15 babies for toddlers walking. The trials that were not included are grey in Table 1 of this document. For every other trial, the exact number of remaining cycles are reported in the same table.

      In the previous version of the manuscript, as we wanted the indexes to be comparable across individuals and ages, we had systematically analyzed 5 cycles that were randomly chosen among the available one. However this created data loss. As detailed in the general response above, to be less selective and to include every available cycle, we now rely on a new approach: if more than 5 cycles were available, we computed every variable of the study 5 times (for 5 random combinations of 5 cycles that were randomly chosen among every available cycle). The variables were averaged afterwards. Thanks to this new approach, 586 cycles are now included in the analysis, which confirmed the robustness of our findings.

      Infants can indeed hold their legs in one position for a long time but all of our results were obtained after having normalized each phase of flexion or extension by a given number of time points (see Figure 6, Temporal normalization). Our results were also verified with a different temporal normalization, directly normalizing the cycle instead of the phases. We choose not to report more results in the main text for the overall readability of the paper but here are the same table of p-value as in the appendix of the paper with a normalization based on cycles instead of phases.

      5) The recording times are not common across individuals. One newborn was recorded after 1 day and the other after 21 days. Not sure this is comparable, especially if the main contribution of the paper is the longitudinal data. Moreover, the second recording was conducted between 74 days to 122 days. This range is too broad. Same for the third time point - one walk onset is not reported, some infants were recorded at <380 days and some >500 days. This difference challenges the reliability of the data.

      Given the high inter-individual variability that relates to the age of walking onset (Martorell et al., 2006) it is often a challenge in developmental sciences to choose between standardizing recruitment according to the age or according to the experience. In the present study, we choose to recruit toddlers of similar experience (i.e. around walking onset) rather than on similar age because motor variability is known to depend a lot on experience, in particular regarding EMG data during the first months of walking (Chang et al., 2006). However, we agree with the reviewer that the age of walking onset is an important source of inter-individual variability and therefore we modified each figure of the paper so the 18 individuals would each have their own color which was ordered and allocated according to the age of walking onset (see Figure 3E detailing this legend).

      Regarding the other recording points, and the experience after walking onset, the recording time can indeed vary across individual despite our efforts during data collection to prevent this phenomenon. Main reasons were benign diseases of infants or work constraints for parents that induced postponements of the appointments. However, we report the precise age of each infant for each recording as well as individual data underlying each global figure (see source data of Figure 2, Figure 3 and Figure 5). Based on these data we checked that the individual that were recorded later than the others (for example, subject 1 and subject 14 who were recorded at 21 days for the 1st time point) did not demonstrate aberrant values.

      6) Conceptually, I'm not sure I understand why the authors selected leg alternation (and not other types of movements) as their modules. I was not convinced that leg alternations reflect their real-life locomotor experience (e.g., short bouts in all directions), and therefore the variability measured in this work does not reflect the variability of infants' natural locomotor behaviour.

      We fully agree that leg alternation do not reflect the whole variability that underlies real-life locomotor experience of these infants, however we did not intend to focus here on all the variability that exists during development but more specifically on the variability that allows to produce a given type of behavior with different inputs. This variability is interesting to study because infants tend to use steadier and steadier patterns of coordination to produce a given movement (Teulier et al., 2012), suggesting that they explore among different possible muscular associations before choosing some. As we wanted to study this phenomenon, it appeared methodologically pertinent to fix other sources of variability (i.e. to study different behaviors separately and to study only one coordination mode), as is commonly done in other EMG-based studies of the field (Dominici et al., 2011; Sylos-labini et al., 2020; Teulier et al., 2012). This choice allowed to remain comparable between infants and toddlers. Indeed, while infants produce numerous coordinative patterns while stepping or kicking, such as parallel cycles or singles cycles for example, toddlers only produce alternated flexion and extension cycle of the lower-limb when walking. Therefore, by selecting alternating cycles of flexion and extension only in infants, we ensure that the differences of variability that we observe between ages is not due to the ability of producing various movement, but really due to the ability of producing a given movement with various muscle outputs. Accordingly, and following our results, it allows to conclude that the structure of variability evolve between birth and independent walking to command a given movement. To explain this notion that relates to the redundancy of motor control, we added a new paragraph at the top of the introduction to better explain the place of our studies among broader literature on infant variability (line 34-44). We also clearly wrote in the discussion that our conclusions did not apply to every developmental source of variability (line 393-395): “As we observed such structure within alternated leg movements, other studies are needed to explore the extent of these results to other early behaviors or coordination modes”.

      7) There is not enough rationale for why the specific measurements (IEV, VAF, IRV, etc.) were used and why those are the appropriate ones for the address the questions in the paper. What is the justification for using those measurements?

      As our main goal is to characterize how EMG variability can be generated in a modular system, we defined those metrics as directly representative of the different features that we wanted to study: variability of the EMG output, dimensionality of the underlying modular organization, variability of module activations and selectivity of the command (be it through module activations or within module themselves). While VAF is commonly used in muscle synergies studies, this study is the first to explore how cycle-to-cycle variability could be generated in a modular system, and therefore these indexes were defined for its proper needs. As such to clarify their role to a broad audience we included a new table at the beginning of the Results section (see Table 1 of the ms, line 176).

      8) Some of the conclusions, especially those that relate to motor exploration, are not based on sufficient data. Motor exploration was not explicitly measured in this study, and how motor exploration is reflected by the current data and analyses is not clear.

      We fully agree with the reviewer: while we observed that the structure of EMG variability evolves during the first year of life, the origin of this variability (incidental or purposeful) remains unknown. This was specified line 388-389 “As similar neurophysiological investigations cannot be conducted in human infants, discriminating among purposeful and incidental variability remains challenging,”.

    1. Author Response

      Reviewer #1 (Public Review):

      Summary

      While DNA sequence divergence, differential expression, and differential methylation analysis have been conducted between humans and the great apes to study changes that "make us human", the role of lncRNAs and their impact on the human genome and biology has not been fully explored. In this study, the authors computationally predict HSlncRNAs as well as their DNA Binding sites using a method they have developed previously and then examine these predicted regions with different types of enrichment analyses. Broadly, the analysis is straightforward and after identifying these regions/HSlncRNAs the authors examined their effects using different external datasets.

      Strengths/weaknesses

      By and large, the analysis performed is dependent on their ability to identify HSlncRNAs and their DBS. I think that they have done a good job of showing the performance metrics of their methods in previous publications. Thereafter, they perform a series of enrichment-type analyses that have been used in the field for quite a while now to look at tissue-specific enrichment, or region-specific enrichment, or functional enrichment, and I think these have been carried out well. The authors achieved the aims of their work. I think one of the biggest contributions that this paper brings to the field is their annotation of these HSlncRNAs. Thus a major revisionary effort could be spent on applying their method to the latest genomes that have been released so that the community could get a clean annotation of newly identified HSlncRNAs (see comment 2).

      Comments

      1) Though some of their results about certain HSlncRNAs having DBSs in all genes is rather surprising/suspicious, I think that broadly their process to identify and validate DBSs is robust, they have multiple lines of checks to identify such regions, including functional validation. These predictions are bound to have some level of false positive/negative rate and it might be nice to restate those here and on what experiment/validation data these were conducted. However, the rest of their analysis comprises different types of enrichment analysis which shouldn't be affected by outlier HSlncRNAs if indeed their FPR/FNR are low.

      2) There are now several new genomes available as part of the Zoonomia consortium and 240 Primate consortium papers released. These papers have re-examined some annotations such as Human Accelerated Regions (HARs) and found with a larger dataset as well as better reference genomes, that a large fraction of HARs were actually incorrectly annotated - that is that they were also seen in other lineages outside of just the great apes. If these papers have not already examined HSlncRNAs, the authors should try and re-run the computational predictions with this updated set and then identify HSlncRNAs there. This might help to clarify their signal and remove lncRNAs that might be present in other primates but are somehow missing in the great apes. This might also help to mitigate some results that they see in section 3 of their paper in comparing DBS distances between archaics and humans.

      3) The differences between the archaic hominins in their DBS distances to modern humans are a bit concerning. At some level, we expect these to be roughly similar when examining African modern humans and perhaps the Denisovan being larger when examining Europeans and Asians, but they seem to have distances that aren't expected given the demography. In addition, from their text for section 3, they begin by stating that they are computing two types of distances but then I lost track of which distance they were discussing in paragraph 3 of section 3. Explicitly stating which of the two distances in the text would be helpful for the reader.

      (1) According to Figure 1A (according actually to Meyer et al., 2012, Prufer et al., 2017, and Prüfer et al., 2013), the phylogenetic distance from modern humans to Denisovan is shorter than the distance to Altai Neanderthal. However, also according to these studies, the branch of Denisovan is more remote to modern humans than Altai Neanderthal. Thus, it is not unreasonable to find that 2514 and 1256 DBSs have distances > 0.034 in genes in Denisovans and Altai Neanderthals, respectively. Probably, both the phylogenetic distances and DBS distances depend considerably on the sampled genomes of Altai and Denisovan who lived on the earth for quite long. When new samples are obtained, these distances may be somewhat changed.

      (2) Regarding “they are computing two types of distances but then I lost track of which distance they were discussing in paragraph 3 of section 3”, the second type of distances were discussed in section 3, and the distances computed in the first way were not further analyzed because “This defect may be caused by that the human ancestor was built using six primates without archaic humans”.

      4) Isn't the correct control to examine whether eQTLs are more enriched in HSlncRNA DBSs a set of transcription factor binding sites? I don't think using just promoter regions is a reasonable control here. This does not take away from the broader point however that eQTLs are found in DBSs and I think they can perform this alternate test.

      Indeed, the TFs-TFBSs and lncRNAs-DBSs relationships are comparable, and which one contains more QTLs is an interesting question. In this sense, it is reasonable to use TFBSs as the control. However, for three reasons, we did not perform the comparison and use TFBSs as the control. First, most TFBSs are predicted by varied methods, making us concern the reliability of comparing two sets of predictions. Second, most QTLs in DBSs are mQTLs but most QTLs in TFBSs are eQTLs. Third, probably a greater portion of TFBSs than DBSs are not in promoters, and the time consumption of LongTarget made us unable to predict DBSs truly genome-wide. Nevertheless, this is an interesting question deserving further exploring.

      5) In the discussion, they highlight the evolution of sugar intake, which I'm not sure is appropriate. This comes not from GO enrichment but rather from a few genes that are found at the tail of their distribution. While these signals may be real, the evolution of traits is often highly polygenic and they don't see this signal in their functional enrichment. I suggest removing that line. Moreover, HSlncRNAs are ones that are unique across a much longer time frame than the transition to agriculture which is when sugar intake rose greatly. Thus, it's unlikely to see enrichment for something that arose in the past 6000-7000 years would in the annotation that is designed to detect human-chimp or human-neanderthal level divergence.

      Multiple sugar metabolism-related pathways, including “glucose homeostasis” and “glucose metabolic process”, are found to be enriched only in Altai Neanderthal but not in chimpanzees (Figure 2). Indeed, HS lncRNAs are across a much longer time frame than the transition to agriculture. However, given that apes and monkeys know picking the ripe, sugar-rich fruits at the right time and place, we conjecture that archaic humans as hunter-gatherer could effectively explore natural sugars.

      Reviewer #2 (Public Review):

      Lin et al attempt to examine the role of lncRNAs in human evolution in this manuscript. They apply a suite of population genetics and functional genomics analyses that leverage existing data sets and public tools, some of which were previously built by the authors, who clearly have experience with lncRNA binding prediction. However, I worry that there is a lack of suitable methods and/or relevant controls at many points and that the interpretation is too quick to infer selection. While I don't doubt that lnc RNAs contribute to the evolution of modern humans, and certainly agree that this is a question worth asking, I think this paper would benefit from a more rigorous approach to tackling it.

      At this point, my suggestions are mostly focused on tightening and strengthening the methods; it is hard for me to predict the consequence of these changes on the results or their interpretation, but as a general rule I also encourage the authors to not over-interpret their conclusions in terms of what phenotype was selected for when as they do at certain points (eg glucose metabolism).

      I note some specific points that I think would benefit from more rigorous approaches, and suggest possible ways forward for these.

      1) Much of this work is focused on comparing DNA binding domains in human-unique long-noncoding RNAs and DNA binding sites across the promoters of genes in the human genome, and I think the authors can afford to be a bit more methodical/selective in their processing and filtering steps here. The article begins by searching for orthologues of human lncRNAs to arrive at a set of 66 human-specific lncRNAs, which are then characterised further through the rest of the manuscript. Line 99 describes a binding affinity metric used to separate strong DBS from weak DBS; the methods (line 432) describe this as being the product of the DBS or lncRNA length times the average Identity of the underlying TTSs. This multiplication, in fact, undoes the standardising value of averaging and introduces a clear relationship between the length of a region being tested and its overall score, which in turn is likely to bias all downstream inference, since a long lncRNA with poor average affinity can end up with a higher score than a short one with higher average affinity, and it's not quite clear to me what the biological interpretation of that should be. Why was this metric defined in this way?

      Length is an important metric of DBS, but it has a defect – a triplex of 100 bp may have 50% or 70% of nucleotides bound; in the two situations, the binding affinity of DBD and DBS is very different.

      2) There is also a strong assumption that identified sites will always be bound (line 100), which I disagree is well-supported by additional evidence (lines 109-125). The authors show that predicted NEAT1 and MALAT1 DBS overlap experimentally validated sites for NEAT1, MALAT1, and MEG3, but this is not done systematically, or genome-wide, so it's hard to know if the examples shown are representative, or a best-case scenario.

      More details are described in the citation Wen et al. 2022. We will put the sites into Supplementary Tables in the revised version.

      It's also not quite clear how overlapping promoters or TSS are treated - are these collapsed into a single instance when calculating genome-wide significance? If, eg, a gene has five isoforms, and these differ in the 3' UTR but their promoter region contains a DBS, is this counted five times, or one? Since the interaction between the lncRNA and the DBS happens at the DNA level, it seems like not correcting for this uneven distribution of transcripts is likely to skew results, especially when testing against genome-wide distributions, eg in the results presented in sections 5 and 6. I do not think that comparing genes and transcripts putatively bound by the 40 HS lncRNAs to a random draw of 10,000 lncRNA/gene pairs drawn from the remaining ~13500 lncRNAs that are not HS is a fair comparison. Rather, it would be better to do many draws of 40 non-HS lncRNAs and determine an empirical null distribution that way, if possible actively controlling for the overall number of transcripts (also see the following point).

      (1) If, say, three transcripts of a gene share the same promoter region (i.e., they have the same TSS) but differ only in 3’UTR, the promoter region was used to predict DBSs just for once. Otherwise, if the three transcripts have different TSS, the three promoter regions were used to predict DBSs.

      (2) A gene may have many DBSs if it has many transcripts, or few ones if it has just a few transcripts. We did not correct for this uneven distribution of transcripts, because our GTEx analysis was on the transcript level; it is well recognized that transcripts of the same gene can be expressed in different tissues.

      (3) We randomly sampled a pair of non-HS lncRNA and a transcript for 10000 times (i.e., 10000 pairs). It is a point that multiple draws of 40 non-HS lncRNAs should be made to make the statistics more robust.

      3) Thresholds for statistical testing are not consistent, or always well justified. For instance, in line 142 GO testing is performed on the top 2000 genes (according to different rankings), but there's no description of the background regions used as controls anywhere, or of why 2000 genes were chosen as a good number to test? Why not 1000, or 500? Are the results overall robust to these (and other) thresholds? Then line 190 the threshold for downstream testing is now the top 20% of genes, etc. I am not opposed to different thresholds in principle, but they should be justified.

      The over-representation analysis using g:Profiler was performed taking the whole genome as the background. Analyzing more DBSs (especially weak DBSs) would generate more results, but the results could be less reliable. Thus, there is a trade-off between analyzing fewer DBSs with relatively high reliability and analyzing more DBSs with relatively low reliability. Inevitably, the handling of this trade-off is somewhat subjective, and to carefully compare the two classes of DBSs per can be an independent question. Although weak DBSs were not systematically analyzed, the results from the strong DBSs undoubtedly suggest that HS lncRNAs have contributed greatly to human evolution.

      Likewise, comparing Tajima's D values near promoters to genome-wide values is unfair, because promoters are known to be under strong evolutionary constraints relative to background regions; as such it is not surprising that the results of this comparison are significant. A fairer comparison would attempt to better match controls (eg to promoters without HS lncRNA DBS, which I realise may be nearly impossible), or generate empirical p-values via permutation or simulation.

      We examined Tajima’s D in DBSs (Supplementary Figure 9) and in HS lncRNA genes (Supplementary Figure 18). In both cases, we compared the Tajima’s D values with the genome-wide background.

      4) There are huge differences in the comparisons between the Vindija and Altai Neanderthal genomes that to me suggest some sort of technical bias or the such is at play here. e.g. line 190 reports 1256 genes to have a high distance between the Altai Neanderthal and modern humans, but only 134 Vindija genes reach the same cutoff of 0.034. The temporal separation between the two specimens does not seem sufficient to explain this difference, nor the difference between the Altai Denisovan and Neanderthal results (2514 genes for Denisovan), which makes me wonder if it is a technical artefact relating to the quality of the genome builds? It would be worth checking.

      We used the same workflow (and the same cutoff 0.034) to analyze Vindija and Altai Neanderthal and Denisovan. If a smaller cutoff was used, one would see more Vindija genes. The question again is that there is a trade-off. Analyzing epigenome and epigenetic regulation in archaic genomes is an interesting direction, and much more studies are needed before more reasonably setting related parameters and cutoffs.

      5) Inferring evolution: There are some points of the manuscript where the authors are quick to infer positive selection. I would caution that GTEx contains a lot of different brain tissues, thus finding a brain eQTL is a lot easier than finding a liver eQTL, just because there are more opportunities for it. Likewise, claims in the text and in Tables 1 and 2 about the evolutionary pressures underlying specific genes should be more carefully stated. The same is true when the authors observe high Fst between groups (line 515), which is only one possible cause of high Fst - population differentiation and drift are just as capable of giving rise to it, especially at small sample sizes.

    2. Reviewer #1 (Public Review):

      Summary<br /> While DNA sequence divergence, differential expression, and differential methylation analysis have been conducted between humans and the great apes to study changes that "make us human", the role of lncRNAs and their impact on the human genome and biology has not been fully explored. In this study, the authors computationally predict HSlncRNAs as well as their DNA Binding sites using a method they have developed previously and then examine these predicted regions with different types of enrichment analyses. Broadly, the analysis is straightforward and after identifying these regions/HSlncRNAs the authors examined their effects using different external datasets.

      Strengths/weaknesses<br /> By and large, the analysis performed is dependent on their ability to identify HSlncRNAs and their DBS. I think that they have done a good job of showing the performance metrics of their methods in previous publications. Thereafter, they perform a series of enrichment-type analyses that have been used in the field for quite a while now to look at tissue-specific enrichment, or region-specific enrichment, or functional enrichment, and I think these have been carried out well. The authors achieved the aims of their work. I think one of the biggest contributions that this paper brings to the field is their annotation of these HSlncRNAs. Thus a major revisionary effort could be spent on applying their method to the latest genomes that have been released so that the community could get a clean annotation of newly identified HSlncRNAs (see comment 2).

      Comments<br /> 1) Though some of their results about certain HSlncRNAs having DBSs in all genes is rather surprising/suspicious, I think that broadly their process to identify and validate DBSs is robust, they have multiple lines of checks to identify such regions, including functional validation. These predictions are bound to have some level of false positive/negative rate and it might be nice to restate those here and on what experiment/validation data these were conducted. However, the rest of their analysis comprises different types of enrichment analysis which shouldn't be affected by outlier HSlncRNAs if indeed their FPR/FNR are low.

      2) There are now several new genomes available as part of the Zoonomia consortium and 240 Primate consortium papers released. These papers have re-examined some annotations such as Human Accelerated Regions (HARs) and found with a larger dataset as well as better reference genomes, that a large fraction of HARs were actually incorrectly annotated - that is that they were also seen in other lineages outside of just the great apes. If these papers have not already examined HSlncRNAs, the authors should try and re-run the computational predictions with this updated set and then identify HSlncRNAs there. This might help to clarify their signal and remove lncRNAs that might be present in other primates but are somehow missing in the great apes. This might also help to mitigate some results that they see in section 3 of their paper in comparing DBS distances between archaics and humans.

      3) The differences between the archaic hominins in their DBS distances to modern humans are a bit concerning. At some level, we expect these to be roughly similar when examining African modern humans and perhaps the Denisovan being larger when examining Europeans and Asians, but they seem to have distances that aren't expected given the demography. In addition, from their text for section 3, they begin by stating that they are computing two types of distances but then I lost track of which distance they were discussing in paragraph 3 of section 3. Explicitly stating which of the two distances in the text would be helpful for the reader.

      4) Isn't the correct control to examine whether eQTLs are more enriched in HSlncRNA DBSs a set of transcription factor binding sites? I don't think using just promoter regions is a reasonable control here. This does not take away from the broader point however that eQTLs are found in DBSs and I think they can perform this alternate test.

      5) In the discussion, they highlight the evolution of sugar intake, which I'm not sure is appropriate. This comes not from GO enrichment but rather from a few genes that are found at the tail of their distribution. While these signals may be real, the evolution of traits is often highly polygenic and they don't see this signal in their functional enrichment. I suggest removing that line. Moreover, HSlncRNAs are ones that are unique across a much longer time frame than the transition to agriculture which is when sugar intake rose greatly. Thus, it's unlikely to see enrichment for something that arose in the past 6000-7000 years would in the annotation that is designed to detect human-chimp or human-neanderthal level divergence.

    3. Reviewer #2 (Public Review):

      Lin et al attempt to examine the role of lncRNAs in human evolution in this manuscript. They apply a suite of population genetics and functional genomics analyses that leverage existing data sets and public tools, some of which were previously built by the authors, who clearly have experience with lncRNA binding prediction. However, I worry that there is a lack of suitable methods and/or relevant controls at many points and that the interpretation is too quick to infer selection. While I don't doubt that lnc RNAs contribute to the evolution of modern humans, and certainly agree that this is a question worth asking, I think this paper would benefit from a more rigorous approach to tackling it.

      At this point, my suggestions are mostly focused on tightening and strengthening the methods; it is hard for me to predict the consequence of these changes on the results or their interpretation, but as a general rule I also encourage the authors to not over-interpret their conclusions in terms of what phenotype was selected for when as they do at certain points (eg glucose metabolism).

      I note some specific points that I think would benefit from more rigorous approaches, and suggest possible ways forward for these.

      1. Much of this work is focused on comparing DNA binding domains in human-unique long-noncoding RNAs and DNA binding sites across the promoters of genes in the human genome, and I think the authors can afford to be a bit more methodical/selective in their processing and filtering steps here. The article begins by searching for orthologues of human lncRNAs to arrive at a set of 66 human-specific lncRNAs, which are then characterised further through the rest of the manuscript. Line 99 describes a binding affinity metric used to separate strong DBS from weak DBS; the methods (line 432) describe this as being the product of the DBS or lncRNA length times the average Identity of the underlying TTSs. This multiplication, in fact, undoes the standardising value of averaging and introduces a clear relationship between the length of a region being tested and its overall score, which in turn is likely to bias all downstream inference, since a long lncRNA with poor average affinity can end up with a higher score than a short one with higher average affinity, and it's not quite clear to me what the biological interpretation of that should be. Why was this metric defined in this way?

      2. There is also a strong assumption that identified sites will always be bound (line 100), which I disagree is well-supported by additional evidence (lines 109-125). The authors show that predicted NEAT1 and MALAT1 DBS overlap experimentally validated sites for NEAT1, MALAT1, and MEG3, but this is not done systematically, or genome-wide, so it's hard to know if the examples shown are representative, or a best-case scenario.

      It's also not quite clear how overlapping promoters or TSS are treated - are these collapsed into a single instance when calculating genome-wide significance? If, eg, a gene has five isoforms, and these differ in the 3' UTR but their promoter region contains a DBS, is this counted five times, or one? Since the interaction between the lncRNA and the DBS happens at the DNA level, it seems like not correcting for this uneven distribution of transcripts is likely to skew results, especially when testing against genome-wide distributions, eg in the results presented in sections 5 and 6. I do not think that comparing genes and transcripts putatively bound by the 40 HS lncRNAs to a random draw of 10,000 lncRNA/gene pairs drawn from the remaining ~13500 lncRNAs that are not HS is a fair comparison. Rather, it would be better to do many draws of 40 non-HS lncRNAs and determine an empirical null distribution that way, if possible actively controlling for the overall number of transcripts (also see the following point).

      3. Thresholds for statistical testing are not consistent, or always well justified. For instance, in line 142 GO testing is performed on the top 2000 genes (according to different rankings), but there's no description of the background regions used as controls anywhere, or of why 2000 genes were chosen as a good number to test? Why not 1000, or 500? Are the results overall robust to these (and other) thresholds? Then line 190 the threshold for downstream testing is now the top 20% of genes, etc. I am not opposed to different thresholds in principle, but they should be justified.

      Likewise, comparing Tajima's D values near promoters to genome-wide values is unfair, because promoters are known to be under strong evolutionary constraints relative to background regions; as such it is not surprising that the results of this comparison are significant. A fairer comparison would attempt to better match controls (eg to promoters without HS lncRNA DBS, which I realise may be nearly impossible), or generate empirical p-values via permutation or simulation.

      4. There are huge differences in the comparisons between the Vindija and Altai Neanderthal genomes that to me suggest some sort of technical bias or the such is at play here. e.g. line 190 reports 1256 genes to have a high distance between the Altai Neanderthal and modern humans, but only 134 Vindija genes reach the same cutoff of 0.034. The temporal separation between the two specimens does not seem sufficient to explain this difference, nor the difference between the Altai Denisovan and Neanderthal results (2514 genes for Denisovan), which makes me wonder if it is a technical artefact relating to the quality of the genome builds? It would be worth checking.

      5. Inferring evolution: There are some points of the manuscript where the authors are quick to infer positive selection. I would caution that GTEx contains a lot of different brain tissues, thus finding a brain eQTL is a lot easier than finding a liver eQTL, just because there are more opportunities for it. Likewise, claims in the text and in Tables 1 and 2 about the evolutionary pressures underlying specific genes should be more carefully stated. The same is true when the authors observe high Fst between groups (line 515), which is only one possible cause of high Fst - population differentiation and drift are just as capable of giving rise to it, especially at small sample sizes.

    1. Reviewer #3 (Public Review):

      Light energy drives photosynthesis. However, excessive light can damage (i.e., photo-damage) and thus inactivate the photosynthetic process. A major target site of photo-damage is photosystem II (PSII). In particular, one component of PSII, the reaction center protein, D1, is very suspectable to photo-damage, however, this protein is maintained efficiently by an elaborate multi-step PSII-D1 turnover/repair cycle. Two proteases, FtsH and Deg, are known to contribute to this process, respectively, by efficient degradation of photo-damaged D1 protein processively and endoproteolytically. In this manuscript, Kato et al., propose an additional step (an early step) in the D1 degradation/repair pathway. They propose that "Tryptophan oxidation" at the N-terminus of D1 may be one of the key oxidations in the PSII repair, leading to processive degradation of D1 by FtsH. Both, their data and arguments are very compelling.

      The D1 protein repair/degradation pathway in its simplest form can be defined essentially by five steps: (1) migration of damaged PSII core complex to the stroma thylakoid, (2) partial PSII disassembly of the PSII core monomer, (3) access of protease degrading damaged D1, (4) concomitant D1 synthesis, and (5) reassembly of PSII into grana thylakoid. An enormous amount of work has already been done to define and characterize these various steps. Kato et al., in this manuscript, are proposing a very early yet novel critical step in D1 protein turnover in which Tryptophan(Trp) oxidation in PSII core proteins influences D1 degradation mediated by FtsH.

      Using a variety of approaches, such as mass-spectrometry (Table 1), site-directed mutagenesis (Figures 2-4), D1 degradation assays (Figures 3, and 4), and simulation modeling (Figure 5), Kato et al., provide both strong evidence and reasonable arguments that an N-terminal Trp oxidation may be likely to be a 'key' oxidative post-translational modification (OPTM) that is involved in triggering D1 degradation and thus activating the PSII repair pathway. Consequently, from their accumulated data, the authors propose a scenario in which the unraveling of the N-terminal of the D1 protein facilitated by Trp oxidation plays a critical 'recognition' role in alerting the plant that the D1 protein is photo-damaged and thus to kick start the processive degradation pathway initiated possibly by FtsH. Coincidently, Forsman and Eaton-Rye (Biochemistry 2021, 60, 1, 53-63), while working with the thermophilic cyanobacterium, Thermosynechococcus vulcanus, showed that when the N-terminal DE-loop of the D1 protein is photo-damaged a disruption of the interaction between the PsbT subunit and D1 occurs which may serve as a signal for PSII to undergo repair following photodamage. While the activation of the processive degradation pathways in Chlamydomonas versus Thermosynechococcus vulcanus have significant mechanistic differences, it's interesting to note and speculate that the stability of the N-terminal of their respective D1 proteins seems to play a critical role in 'signaling' the PSII repair system to be activated and initiate repair. But it's complicated. For instance, significant Trp oxidation also occurs on the lumen side of other PSII subunits which may also play a significant role in activating the repair processes as well. Indeed, Kato et al.,( Photosynthesis Research volume 126, pages 409-416 (2015)) proposed a two-step model whereby the primary event is disruption of a Mn-cluster in PSII on the lumen side. A secondary event is damage to D1 caused by energy that is absorbed by chlorophyll. But models adapt, change, and get updated. And the data provided by Kato et al., in this manuscript, gives us a unique glimpse/snapshot into the importance of the stability of the N-terminal during photo-damage and its role in D1-turnover. For instance, the author's use site-directed mutagenesis of Trp residues undergoing OPTM in the D1 protein coupled with their D1 degradation assays (Figure 3 and 4), provides evidence that Trp oxidation (in particular the oxidation of Trp14) in coordination with FtsH results in the degradation of D1 protein. Indeed, their D1 degradation assays coupled with the use of a ftsh mutant provide further significant support that Trp14 oxidation and FtsH activity are strongly linked. But for FstH to degrade D1 protein it needs to gain access to photo-damaged D1. FtsH access to D1 is achieved by having CP43 partially dissociate from the PSII complex. Hence, the authors also addressed the possibility that Trp oxidation may also play a role in CP43 disassembly from the PSII complex thereby giving FtsH access to D1. Using a site-directed mutagenesis approach, they showed that Trp oxidation in CP43 appeared to have little impact on the PSII repair (Supplemental Figure S6). This result shows that D1-Trp14 oxidation appears to be playing a role in D1 turnover that occurs after CP43 disassembly from the PSII complex. Alternatively, the authors cannot exclude the possibility that D1-Trp14 oxidation in some way facilitates CP43 dissociation. Further investigation is needed on this point. However, D1-Trp14 oxidation is causing an internal disruption of the D1 protein possibly at the N-terminus of the protein. Consequently, the role of Trp14 oxidation in disrupting the stability of the N-terminal domain of the D1 protein was analyzed computationally. Using a molecular dynamics approach (Figure 5), the authors attempted to create a mechanistic model to explain why when D1 protein Trp14 undergoes oxidation the N-terminal domain of D1protein becomes unraveled. Specifically, the authors propose that the interaction between D1 protein Trp14 with PsbI Ser25 becomes disrupted upon oxidation of Trp14. Consequently, the authors concluded from their molecular dynamics simulation analysis that " the increased fluctuation of the first α-helix of D1 would give a chance to recognize the photo-damaged D1 by FtsH protease". Hence, the author's experimental and computational approaches employed here develop a compelling early-stage repair model that integrates 1) Trp14 oxidation, 2) FtsH activation and 3) D1- turnover being initiated at its N-terminal domain. However, a word of caution should be emphasized here. This model is just a snapshot of the very early stages of the D1 protein turnover process. The data presented here gives us just a small glimpse into the unique relationship between Trp oxidation of the D1 protein which may trigger significant N-terminal structural changes of the D1 protein that both signals and provides an opportunity for FstH to begin protease digestion of the D1 protein. However, the authors go to great lengths in their discussion section to not overstate solely the role of Trp14 oxidation in the complicated process of D1 turnover. The authors certainly recognize that there are a lot of moving parts involved in D1 turnover. And while Trp14 oxidation is the major focus of this paper, the authors show in Supplemental Fig S4 the structural positions of various additional oxidized Trp residues in the Thermosynecoccocus vulcans PSII core proteins. Indeed, this figure shows that the majority of oxidized Trps are located on the luminal side of PSII complex clustered around the oxygen-evolving complex. So, while oxidized Trp14 may be involved in the early stages of D1 turnover certainly oxidized Trps on the lumen side are also more than likely playing a role in D1 turnover as well. To untangle this complex process will require additional research.

      Nevertheless, identifying and characterizing the role of oxidative modification of tryptophan (Trp) residues, in particular, Trp14, in the PSII core provides another critical step in an already intricate multi-step process of D1 protein turnover during photo-damage.

    1. If you look at your home, did you hire an interior designer to put everything in the right place in your house? Some people do but most people don't.

      Important to note that what's also left out of this picture of software design being left up to designers is the staggering amount of software with positively bad UI and UX that people have forced on them all day in the form of e.g. awful enterprise software. The notion that the masses somehow need designers' (proper designers) involvement in software is just flatly contradicted by reality.

      And on that note there's also the matter of choice—if you were to hire a designer who did something you didn't like, you'd get rid of them. Among all the software that people interact with every day, whether it's terrible enterprise junk or an iOS app designed with a self-anointed designer, there isn't one in which the user actually hired anyone to do the UI. The publisher/whomever just makes the thing and says, essentially, "here you go; take it or leave". That's what's really on offer in the world made too favorable to designers and not malleable enough to users.

    1. Just be prepared to face a wall of references that don’tmean a whole lot to you.

      I'm already kind of use to this and it's comforting to know that the writer has sources for the things they're saying. Sometimes I will go through the references and read the source material that the author is pulling from, because it's interesting to see how they drew information out of the source.

    2. Abstracts, thus, are generallydense, and it’s not uncommon to read through an abstract and nothave a clue about what you just read. This is a good place to re-read,highlight, underline, look up what you don’t know. You still may nothave a firm grasp on everything in the abstract, but treat the key termsin the abstract like parts of a map when you see them in the main text,leading you to treasure: understanding the main argument

      I understand the difficulty of dealing with complex abstract concepts. Even after reading them, I sometimes find myself confused by their content. However, I've learned that taking the time to re-read, underline important parts, and look for up unfamiliar terms may be really beneficial. It's like going on a treasure hunt, with key phrases acting as guideposts to help me understand the main idea better. This method not only good for better understanding, but it also makes the experience of reading academic texts easier and more meaningful.

    1. Residents crossing between islands during a rising tide on Majuro, Marshall Islands, in 2015. Majuro is home to former residents of Bikini Atoll who were relocated in the 1940s.Credit...Josh Haner/The New York TimesBy Pete McKenzieMay 3, 2023The golden sand of Bikini Atoll is laced with plutonium. The freshwater is poisoned with strontium. The coconut crabs contain hazardous levels of cesium.In the 1940s and ’50s, the U.S. government used this coral reef, in the Pacific nation of the Marshall Islands, for testing nuclear weapons. Radioactive residue has left Bikini uninhabitable to this day, forcing those whose families once lived on the atoll into exile on a handful of other Marshallese islands and in the United States.Recognizing the damage its testing caused, the U.S. government established two trust funds in the 1980s to help pay for Bikinians’ health care, build housing and cover living costs. In 2017, after a campaign by Bikini leaders for greater autonomy, the Trump administration announced that the government would lift withdrawal limits and stop auditing the main fund, then worth $59 million.Six years later, only about $100,000 remains, and the Bikini community is in crisis.Anderson Jibas, the mayor of the council that oversees the displaced Bikini community, made a series of questionable purchases on Bikini’s behalf, including of a large plot of land in Hawaii and a fleet of new vehicles. He has defended some of the purchases as investments against climate change, as necessary to support isolated Bikinians and as attempts at revenue-generating projects.AdvertisementSKIP ADVERTISEMENTMr. Jibas has also acknowledged using trust fund money for personal expenses and has been accused by a top Marshall Islands official of receiving kickbacks from an investment manager — a charge Mr. Jibas denies.ImageA U.S nuclear bomb test at Bikini Atoll in 1946.Credit...Universal Images Group, via Getty ImagesWith the fund virtually depleted, the council’s roughly 350 employees are no longer being paid. Monthly payments of about $150 each to the community’s 6,800 members — a vital lifeline that helped cover food and rent among a population with high rates of poverty — have ceased.The emergency highlights the lasting consequences of decades of U.S. nuclear testing in the Pacific, including lingering questions about the American commitment to address that legacy, an undertaking made more difficult by pervasive fraud and mismanagement in the region.“It’s a disaster,” said Tommy Jibok, a former member of the Bikini council who challenged Mr. Jibas in an election in 2019. “They told us we would be sitting and sleeping on money. Look what is happening now. We’re sleeping on nothing.”AdvertisementSKIP ADVERTISEMENTIn 1946, the United States relocated the 167 inhabitants of Bikini to clear the way for nuclear tests that it said would “end all world wars.” It then left them virtually alone on a small, desolate island, where many nearly starved. In 1948, the islanders were moved again.Over 12 years, the United States tested 23 nuclear bombs in Bikini. In 1968, President Lyndon B. Johnson announced that the Bikinians would return home. But after scientists found that radiation levels remained dangerously high, the United States in 1978 evacuated the almost 150 people who had chosen to go back. The Marshall Islands gained independence from the United States the next year.In 1982, the American government established a $25 million resettlement fund to clean up Bikini and support its people. In 1987, it created a second fund to provide annual payments directly to Bikinians. A year later, it contributed an additional $90 million to the resettlement fund. American officials administered the money and could veto withdrawals.Bikini representatives argued that the resettlement fund contained too little money to remedy the atoll’s radioactivity. They used the funds instead to support the exiled Bikinians.Editors’ PicksWhy You Can’t Stop Reading About Sofia Vergara’s SplitWould You Drink Wastewater? What if It Was Beer?Does My Fiancé Love Me, or Does He Just Want U.S. Citizenship?AdvertisementSKIP ADVERTISEMENTImageMike Pompeo, then the secretary of state, visiting in the Marshall Islands in 2019. With him is Hilda Heine, the Marshallese president from 2016 to 2020.Credit...Jonathan Ernst/Agence France-Presse — Getty ImagesBut the Bikini leaders were frustrated by American officials’ refusal to release more than a few million dollars each year. The struggle culminated in 2016 with the election of Mr. Jibas, who promised to take control of the resettlement fund. (The other fund is overseen by independent trustees.)AdvertisementSKIP ADVERTISEMENTDuring a 2017 congressional hearing, Mr. Jibas explained that Bikinians “​​know far better than the intermediaries or distant agencies of the United States what is needed to make the lives of the displaced population more bearable.”Douglas Domenech, at the time an assistant interior secretary, announced that the Interior Department would relinquish control of the resettlement fund to “restore trust and ensure that sovereignty means something.”Mr. Jibok, the former Bikini council member, had a different interpretation: that U.S. officials wanted to “wash their hands clean” of responsibility for Bikinians.Whatever the motivation, the result was a rapid increase in council spending under Mr. Jibas, from $7.6 million in 2016 to $25.7 million in 2018, according to audits from the time. Bank statements provided by Gordon Benjamin, a lawyer for the council, show that the fund, worth $59 million in 2017, was down to just $100,041 in March of this year.AdvertisementSKIP ADVERTISEMENTMany of the council’s purchases were popular, including of a small aircraft and two cargo ships to help supply isolated Bikinians, as well as construction equipment to build protections against rising seas that threaten low-lying Pacific islands because of climate change.But there were also more dubious purchases: $4.8 million for 283 acres of land in Hawaii; $1.3 million for an apartment complex in the Marshall Islands’ capital, Majuro; and multiple new vehicles for the personal use of Bikini council members, according to Mr. Benjamin. Mr. Jibas also introduced an annual $100,000 “representation package” to fund his regular trips to the United States.ImageIsles that form part of Majuro, the Marshall Islands’ capital. One of the purchases made with the resettlement fund was an apartment complex in Majuro.Credit...Josh Haner/The New York TimesMr. Jibas has said he wants to develop housing in Hawaii for rent or sale, but no development has taken place yet. The Majuro apartment complex was purchased as an investment property, but it appears to be losing money so far.Lani Kramer, a Bikinian who previously worked as the council’s city manager and is now challenging Mr. Jibas for the mayoralty, said Mr. Jibas and council members had used public funds for personal spending. “They were bringing receipts for diapers, chewing gum,” Ms. Kramer said. “It was obviously not for the people, it was for their own grocery shopping.”AdvertisementSKIP ADVERTISEMENTThe Marshall Islands’ banking commissioner has also accused Mr. Jibas of accepting $50,000 from a local bank manager who is being prosecuted on suspicion of unlawfully investing Bikini funds and laundering money. The Marshallese auditor general did not respond to requests for comment about the allegations.Starting in 2018, Mr. Jibas refused to disclose council finances to the Marshall Islands’ auditor general, prompting the police to seize council documents in 2021. Late last month, a spokesman for the Interior Department said it had written to bank officials seeking information about the fund and to Mr. Jibas requesting the council’s recent budgets.That request came after Jack Niedenthal, an American expatriate who served as the Marshallese health secretary, wrote to the Interior Department warning about the depleted trust fund and asking the department to intervene. He was subsequently fired for breaching diplomatic protocol by circumventing the Marshallese foreign ministry and the American Embassy.Mr. Jibas acknowledged in an interview that he occasionally used his representation package to buy food and other items for his family, which he said council staff members were aware of and had approved, but he denied taking money from the bank manager.ImageCollecting laundry on Ejit, an isle in Majuro. The money from the resettlement fund is nearly gone, and the Bikini community is in crisis.Credit...Josh Haner/The New York TimesAdvertisementSKIP ADVERTISEMENTMr. Jibas said in the interview that he was trying to access the independently controlled second fund, which now holds $28 million, to sustain council spending.According to Mr. Benjamin, starting in October 2021 the trustees of that fund permitted the council to withdraw roughly $13 million to fund its spending, but reversed their stance earlier this year and halted all payments out of the fund, including the regular living payments to Bikinians, to avoid further depletion. In the interview, Mr. Jibas said he also hoped to tap into new American funding to replenish the main fund.Earlier this year, the Biden administration promised to provide the Marshall Islands $700 million in one-time aid and to continue underwriting much of the government’s budget. Under a treaty, the United States controls the country’s defense policy, which the American government considers crucial to countering China in the region. The aid has not yet been approved, meaning Bikinians’ future remains uncertain.In a statement on behalf of Mr. Jibas, Mr. Benjamin said that the mayor’s critics were not pushing the United States hard enough for more funding.Mr. Jibok, who as a council member opposed Mr. Jibas’s efforts to gain control of the fund, said that the United States had done little to facilitate self-sufficiency in the Bikini community, leaving few financial safeguards in place.“I didn’t think we were ready,” Mr. Jibok said, “because I knew that we didn’t have anything in place to control” mismanagement or fraud.A version of this article appears in print on May 4, 2023, Section A, Page 4 of the New York edition with the headline: Bikini Atoll Leaders Blew Through Millions From U.S.. Order Reprints | Today’s Paper | Subscribe
    1. Reviewer #3 (Public Review):

      Here, the authors trained catElMo, a new context-aware embedding model for TCRβ CDR3 amino acid sequences for TCR-epitope specificity and clustering tasks. This method benchmarked existing work in protein and TCR language models and investigated the role that model architecture plays in the prediction performance. The major strength of this paper is comprehensively evaluating common model architectures used, which is useful for practitioners in the field. However, some key details were missing to assess whether the benchmarking study is a fair comparison between different architectures. Major comments are as follows:

      - It is not clear why epitope sequences were also embedded using catELMo for the binding prediction task. Because catELMO is trained on TCRβ CDR3 sequences, it's not clear what benefit would come from this embedding. Were the other embedding models under comparison also applied to both the TCR and epitope sequences? It may be a fairer comparison if a single method is used to encode epitope sequence for all models under comparison, so that the performance reflects the quality of the TCR embedding only.<br /> - The tSNE visualization in Figure 3 is helpful. It makes sense that the last hidden layer features separate well by binding labels for the better performing models. However, it would be useful to know if positive and negative TCRs for each epitope group also separate well in the original TCR embedding space. In other words, how much separation between these groups is due to the neural network vs just the embedding?<br /> - To generate negative samples, the author randomly paired TCRs from healthy subjects to different epitopes. This could produce issues with false negatives if the epitopes used are common. Is there an estimate for how frequently there might be false negatives for those commonly occurring epitopes that most populations might also have been exposed to? Could there be a potential batch effect for the negative sampled TCR that confounds with the performance evaluation?<br /> - Most of the models being compared were trained on general proteins rather than TCR sequences. This makes their comparison to catELMO questionable since it's not clear if the improvement is due to the training data or architecture. The authors partially addressed this with BERT-based models in section 2.4. This concern would be more fully addressed if the authors also trained the Doc2vec model (Yang et al, Figure 2) on TCR sequences as baseline models instead of using the original models trained on general protein sequences. This would make clear the strength of context-aware embeddings if the performance is worse than catElmo and BERT.

    1. “I’d just slowly ease the world into this transition,” Cotra said. “I’m very scared because I think it’s not going to happen like that.” Why not? Because of the objections to slowing down AI progress. Let’s break down the three main ones, starting with the idea that rapid progress on AI is inevitable because of the strong financial drive for first-mover dominance in a research area that’s overwhelmingly private.

      I strongly agree with Cotra saying to slowly easing the world into the transition of AI, instead of just jumping into it. There is really no way to slow down the progress of AI. Especially with saying that rapid progress on AI is inevitable.

    2. “I’d just slowly ease the world into this transition,” Cotra said. “I’m very scared because I think it’s not going to happen like that.”

      In addition, it's important to consider the impact of AI on the workforce. While AI has the potential to automate many jobs and increase efficiency, it could also lead to job displacement and inequality. We need to work together to ensure that the benefits of AI are shared fairly across all members of society. This could include things like investing in education and training programs to help people develop the skills they need to succeed in a world of AI, or creating policies that ensure a basic income for those who are unable to find work.

    1. My thoughts are provisional and could be subtitled “what I’ve learned so far.”

      MacKinnon has tasked herself with squaring a circle, and squaring this particular circle is hard! Lesser intellects don’t even try, relying instead on a mix of piety and random insult (“just be kind”, “genocidal terfs!”). MacKinnon, though, a second waver of some stature, is attempting to do things properly.

      You have to admire her for it. It’s a bit like watching an avant-garde author commit to producing a 1,000-page novel without ever using the word “the” or the letter “e”. “Produce a radical feminist analysis of sex and gender that dismisses the proposition that women constitute a sex class!”. In both cases, the end product might not be very good, but god, you’ve got to appreciate the ambition. If the latter example weren’t contributing, in a non-avant-garde way, to the erosion of rights for non-avant-garde people, we could declare it a hoot then forget all about it.

      Against “squint a bit” feminism: Catharine Mackinnon can’t avoid the obvious by Victoria Smith

    1. “it is possible for educators to remix instruction in ways that use technology to bridge achievement gaps and to develop a sense of social responsibility in students while empowering them.”

      Beginning to use media and technology in the classroom isn't just a school skill-- it's a life skill. Using tech in the classroom allows students to begin to hone skills that will help them in their actual lives and become fluent in this kind of etiquette in a low-stakes environment.

    1. processes evolve

      Besides the fact that this article describes indeed an interesting practice of hiring process improvement, I also see it as a great example of how to formalize the feeling of needed changes for any process, functionality, or even Objective from the OKRs list.

      That's how I see the steps:

      1. formulate the problem. It should not be the final, well-stated problem, just write down your concern with some background info;

      2. create a Request-for-comments doc to collect suggestions from various stakeholders about how to solve your concern;

      3. hold some sessions to review the comments. At this moment, it's highly possible that your understanding of the problem will expand, and suggested ideas will transform into new ones. It's time to define your strategy for problem resolution;

      4. for each group of ideas, define metrics to measure the progress. Select the north star metric and its value;

      5. experiment!

      (1) Select stakeholders that are the most interested in the change and do not afraid of being early adapters; (2) hold impact mapping sessions and bet on some improvements to try them in the first place. Define the fundamental part of your changes; (3) validate the progress by the metrics regularly; (4) create a pipeline to visualize your progress;

      1. analyze the results of the experiment. Adjust the changes made before if needed.

      2. In case of positive results, spare the time for less significant changes and continue to track the progress.

    1. This topic was largely inspired by a recent event from a previous Hamilton student, Basil Brown’s negative experiences with accessibility at both a social and infrastructural level.

      It's impressive to see that you drew from current student experiences to inform your project topic. I'm also glad you included the link to the article you referenced because it helped to inform me of just how difficult the conditions are on Hamilton's campus—it is shocking how inaccessible the buildings and roads are. I'm interested to see how you will document the many shortcomings of accessibility from both campuses.

    1. Reviewer #1 (Public Review):

      In their manuscript titled "A human mitofusion 2 mutation causes mitophagic cardiomyopathy", Franco et al suggest that a rare mutation in MFN2 (R400Q) is over-represented in patients with cardiomyopathy, causes loss of conformational malleability, leading to mitochondrial fusion defects, impaired Parkin recruitment to mitochondria, and suppressed MFN2-Parkin mediated mitophagy. This work is an extension of previous work from the same group that found the MFN2 R400Q mutation is loss of function in a Drosophila model. Unlike MFN2 R94Q and T105M that cause Charcot-Marie-Tooth disease type 2 A, the MFN2 R400Q mutant has normal GTPase activity and mitochondrial electrochemical integrity, motility, and respiration. MFN2 R400Q knock-in mice exhibit cardiac-specific phenotypes.

      Strengths include detailed characterization of the MFN2 R400Q variant in variety of models, including cell models and novel knock-in mouse model.<br /> However, there are some weaknesses. The central claim that the R400Q mutation causes cardiomyopathy in humans and the claim that the pathogenetic mechanism is decreased mitophagy require additional support.

      First, the claim of an association between the R400Q variant (identified in three individuals) and cardiomyopathy has some limitations based on the data presented. The initial association is suggested by comparing the frequency of the mutation in three small cohorts to that in a large database gnomAD, which aggregates whole exome and whole genome data from many other studies including those from specific disease populations. Having a matched control population is critical in these association studies. For instance, according to gnomAD the MFN2 Q400P variant, while not observed in those of European ancestry, has a 10-fold higher frequency in the African/African American and South Asian populations (0.0004004 and 0.0003266, respectively). If the authors data in table one is compared to the gnomAD African/African American population the p-value drops to 0.029262, which would not likely survive correction for multiple comparison (e.g., Bonferroni). (The source and characteristics of the subjects used by the authors in Table 1 is not clear from the methods.)

      Relatedly, evaluation in a knock-in mouse model is offered as a way of bolstering the claim for an association with cardiomyopathy. Some caution should be offered here. Certain mutations have caused a cardiomyopathy in mice when knocked in have not been observed in humans with the same mutation. A recent example is the p.S59L variant in the mitochondrial protein CHCHD10, which causes cardiomyopathy in mice but not in humans (PMID: 30874923). While phenocopy is suggestive there are differences in humans and mice, which makes the correlation imperfect.

      Additionally, the argument that the Mfn2 R400Q variant causes a dominant cardiomyopathy in humans would be better supported by observing of a cardiomyopathy in the heterozygous Mfn2 R400Q mice and not just in the homozygous Mfn2 R400Q mice. Relatedly, it is not clear what the studies in the KI mouse prove over what was already known. Mfn2 function is known to be essential during the neonatal period and the authors have previously shown that the Mfn2 R400Q disrupts the ability of Mfn2 to mediate mitochondrial fusion, which is its core function. The results in the KI mouse seem consistent with those two observations, but it's not clear how they allow further conclusions to be drawn.

      Additionally, the authors conclude that the effect of R400Q on the transcriptome and metabolome in a subset of animals cannot be explained by its effect on OXPHOS (based on the findings in Figure 4H). However, an alternative explanation is that the R400Q is a loss of function variant but does not act in a dominant negative fashion. According to this view, mice homozygous for R400Q (and have no wildtype copies of Mfn2) lack Mfn2 function and consequently have an OXPHOS defect giving rise to the observed transcriptomic and metabolomic changes. But in the rat heart cell line with endogenous rat Mfn2, exogenous of the MFN2 R400Q has no effect as it is loss of function and is not dominant negative. Additionally, as the authors have shown MFN2 R400Q loses its ability to promote mitochondrial fusion, and this is the central function of MFN2, it is not clear why this can't be the explanation for the mouse phenotype rather than the mitophagy mechanism the authors propose.

      Finally, it is asserted that the MFN2 R400Q variant disrupts Parkin activation, by interfering with MFN2 acting a receptor for Parkin. The support for this in cell culture however is limited. Additionally, there is no assessment of mitophagy in the hearts of the KI mouse model.

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons

      Manuscript number: RC-2023-01919

      Corresponding author(s): Fumio, Matsuzaki and Quan, Wu.

      [The “revision plan” should delineate the revisions that authors intend to carry out in response to the points raised by the referees. It also provides the authors with the opportunity to explain their view of the paper and of the referee reports.

      The document is important for the editors of affiliate journals when they make a first decision on the transferred manuscript. It will also be useful to readers of the reprint and help them to obtain a balanced view of the paper.

      If you wish to submit a full revision, please use our "Full Revision" template. It is important to use the appropriate template to clearly inform the editors of your intentions.]

      General Statements [optional]

      This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

      We thank two reviewers very much for their comments. Their comments greatly contribute to our revision plan. Reviewer 1 fairly evaluated our data and provided us constructive and supportive comments. We incorporated responses to Reviewer 1’s comments to our revision plan, in which we made some novel analyses and discussions according to Reviewer1’s comments. Reviewer 2 also provided us very helpful comments, which are based on his/her careful reading of our manuscript, especially from the viewpoints of a ferret specialist. These comments help us to improve our manuscript very much, whereas some of the reviewer 2’s requests appear beyond the scope of our paper and against the policy of Review Comments; the standard policy of the review for Review Commons is “do not add new pipeline of experiments” such as adding additional replicates for scRNAseq. We have made revision plans (section 2) according to the order of comments given by reviewer 1 and then next by reviewer 2, considering all the statements of the two reviewers on balance; there are 6 comments from reviewer 1, and 25 comments from reviewer 2. In the section 2, we selected revision plans that we have reflected to the preliminary revision of our manuscript.

      Finally, we would like to note our fundamental interest; we are studying the cortical development of ferrets as a model of brain development to understand what mechanisms are conserved or species-specific during brain size expansion in the mammalian evolution, which, of course, includes humans. It would be great if the ferret model can be a tool used to study tRG cell biology, contributing to understanding the human cortical development.

      For this purpose, it’s been critical to create series of single cell transcriptomes along cortical development. A comparison between humans and ferrets, focused in this paper, is the first attempt, because human data of single cell transcriptomes have been extraordinary enriched. These attempts of comparisons between ferrets and humans will provide valuable information about which mechanism is shared and which is not shared for the cortical development in the gyrencephalic mammals. To represent the usefulness of our approach, we chose finding of tRG in ferrets as a symbolic example, and analyzed its origin and fates.

      Description of the planned revisions

      Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      Summary: Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).

      In this manuscript, the authors conduct a series of single-cell transcriptomic analyses and imaging assays in the developing ferret cortex suggesting that (1) ferrets harbor a radial glia (RG) subtype similar to the truncated radial glia (tRG) described previously in humans that may have the potential to (2) produce ependymal and astrogenic lineages which (3) can also be found in the developing human cortex. These findings appear to be an important step in the validation and development of the ferret model towards a tool that can be used to study tRG cell biology, a feat currently difficult due to the inaccessibility of a genetically tractable source of tRG for molecular and cell biology experiments.

      Major comments:

      - Are the key conclusions convincing?

      I found the key conclusions described above and in the authors' abstract convincing. I found the identification of a distinct, tRG-like cell type from the authors' single-cell transcriptomic analysis of the ferret cortex compelling, particularly because (1) the expression of the previously utilized tRG marker gene CRYAB is specific to the tRG-like cluster and (2) the tRG-like cluster marker genes (including CRYAB) are relatively unique to the tRG-like cluster. I found this strengthened by their morphological analyses showing the tRG-characteristic apical endfoot and short basal process in these CRYAB+ cells in the ferret cortex. I found the combination of imaging and bioinformatic analyses showing the increase in FOXJ1 co-expression in CRYAB+ cells to compellingly suggest that CRYAB+ cells can produce FOXJ1+ ependymal cells, and similarly with the authors' analyses to suggest that tRG-like cells can also contribute to SPARCL1+ astrocyte cells. I found that the cluster score analyses compelling suggest that the tRG-like cells in the ferret dataset correlate with the tRG cells annotated in a separate, human developing cortical dataset. I also appreciated the comparison of astroglial, ependymal, and uncommited ferret tRG sub populations from the pseudo time analysis with the clusters generated from the integrated ferret-human dataset in Fig. 7.

      - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

      - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      1-1. The weakest claim in the paper is lines 202: "...tRG cells are formed by apical asymmetric division(s) from unique apical IPC". From my understanding, the main evidence that the tRG parent cells shown in Fig. 3 are not tRGs are the data from Fig. 2E-G showing the low amounts of CRYAB+ cells co-expressing KI67, TBR2, or OLIG2 in P5 and P10. Especially given that these timepoints are after those used in Fig. 3, I believe further evidence is needed to confirm the cell type identity of tRG parent cells in Fig. 3. Such experiments (isolating IPCs from ferret cortex and growing in vitro to determine progeny cells) may be outside of the scope of this paper, in which case I believe the text can be strengthened with either (1) presenting the data from the cited Tsunekawa et al, in preparation that would suggest this claim or (2) rephrasing these claims to omit the mention of IPCs.

      We thank the reviewer for the suggestion to revise the definition of tRG parent cells in lines 194-204. This issue is also pointed out by the reviewer 2.

      Revision plan:

      1. We revise the term “IPC” as “mitotic sibling of vRG” and stated that these cells might be tRG (CRYAB+) or non-tRG (CRYAB-) intermediate progenitors. By the term of “intermediate progenitors”, we did not intend to refer to TBR2+ neurogenic IPCs, but rather to an intermediate state of progenitors, in a general sense, with a similar morphology as tRG. To avoid any confusions on this terminology, we revised our manuscript by replacing “IPC” with “a sibling of vRG”.
      2. We delete all statements relevant to Tsunekawa et al. data from the manuscript. We regret that we are not able to include Tsunekawa et al. data because we are planning to submit this data as a separate manuscript, which describes that in ferrets, vRG frequently (30% of apical division) generate non-Tbr2-positive mitotic sibling cells bearing a short basal process during the entire neurogenesis. This study includes a large volume of data with human ones and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not appropriate to combine these data with those described in this manuscript.
      3. As also pointed by reviewer 2, we cannot exclude the possibility that the mitotic sibling cells of vRG with a short basal process (IPC in the previous version of the manuscript) are also CRYAB positive tRG. To clarify the identity and variety of vRG sibling cells at tRG-generating stage, we are examining the sibling pairs of vRG by immunostaining for a mitotic marker Ki67 and CRYAB during P0-P5 after incorporating EGFP by electroporation to label vRG lineages. We will increase the sample size for a quantification and statistical analyses of this newly provided data to incorporate in our fully revised manuscript.

      1-2. I also believe the claim in Line 365-366 is overstated: "We found that ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." While I believe the transcriptomic comparisons suggest the presence of uncommitted tRG in both the ferret and human datasets, I would appreciate further analyses to confirm the prevalence of astroglial and ependymal tRG in the humans and/or functional analyses before claiming that human tRG cells make ependymal and astrogenic cells. I appreciate the authors' note that "GW25 is...the latest stages experimentally available" (line 376-377), but their comparative approaches could be applied to existing datasets of the human cortex (Herring et al., 2022, PMID: 36318921) that span later developmental ages. Identifying the presence of astroglial and ependymal tRGs in this and/or similar datasets would provide more convincing evidence of the tRGs' developmental potential. If this computational analysis is outside the scope of the paper, I believe paring the certainty of these claims (especially lines 379 - 383) and recognizing the need for further functional analyses would negate the need for deeper mechanistic validation.

      We agree with the Reviewer 1 that identifying the presence of astroglial and ependymal tRGs in datasets spanning later developmental stages would provide convincing evidence for the potential of human tRG.

      Revision plan:

      1. We compared our ferret dataset to the human postnatal dataset recommended by the Reviewer 1 (Herring et al., 2022). As a conclusion of our analyses shown below, we found that Herring et al., (2022) dataset was not favorable for a comparative analysis with our ferret dataset regarding the fates of human tRG, because Herring’s human dataset was derived from the prefrontal cortex; This human dataset does not include neither tRG cell population nor ependymal clusters. We have also elaborated our discussion after analyzing Herring et al. dataset in the discussion.
      2. We, therefore, pare down our claim in lines 365-366, by removing “(and presumably human)” to state that “Our pseudotime trajectory analyses and immunohistochemistry analyses strongly suggested that…”.
      3. We also tone down the statements as for the discussion of the relationship between human and ferrets regarding the tRG progeny fates (originally lines from 372 to the end) also elaborated our discussion after analyzing Herring et al. dataset in the same paragraph.

      We will describe the details of our analysis of Herring et al. (2022) below.

      https://www.dropbox.com/scl/fi/a0m72orxfsub66dh3hdbg/reviewer1_2ABC.pdf?rlkey=uzrd8ngclp87p5c8v24mqd1j7&dl=0

      As mentioned above, Herring’s human dataset was derived from the prefrontal cortex, and that it did not include a specific subtype defined as tRG nor other HES1-expressing progenitor clusters such as RG in the original cluster annotation. We, therefore, re-clustered the raw dataset from GW22 (the earliest stage available) up to 10-months after birth by using Seurat pipeline with default parameters (B), and found a CRYAB-expressing population in the original “Astrocyte_GFAP” subtype among astrocyte clusters (A), which distribute in the most of collected stages, from late development through the adulthood. We then examined this dataset to find out whether tRG or its progenies are present.

      After reclustering, CRYAB-expressing cells (with more than 1 raw count) represented 0.15% of the dataset and were grouped as a part of cluster 44, which was mostly derived from postnatal stages (among which 4-months was the most enriched one; C). Several astrocyte markers, such as SPARCL1, HOPX, CLU, and GJA1, as well as CRYAB, were enriched in the cluster 44 as revealed by FindMarkers (Methods). FOXJ1 expression was nearly absent overall in this dataset, indicating the absence of the ependymal cell population, a tRG-descendant cell types in ferrets (C).

      To evaluate the similarity between cluster 44 and tRG or astroglial tRG, we next integrated Herring dataset with our ferret subset (about 15,000 cells) and the human GW25 subset from Bhaduri et al. (2021) of approx. 3,000 cells, both of which contained only progenitor cells. As we have done in Figure 7 of our original manuscript; we have removed cells other than progenitors, astrocytes and oligodendrocytes, such as neurons, microglia, endothelial cells. This resulted in about 20,000 cells in Herring dataset.

      https://www.dropbox.com/scl/fi/nz3iulya5199i95ecr1un/reviewer1_2D.pdf?rlkey=kp7lwxtkn562un1uf9l1axn2p&dl=0

      This integration (D) reveals that Herring’s cluster 44 is closely located to Bhaduri’s human and our ferret tRG clusters on UMAP, but does not overlap with these tRG clusters. This result further suggested that tRG population might be lacking or very rare in this neuron- and glia-dominated dataset, which might be due to the sampling method that targeted the enrichment of neuronal layers (Herring et al., 2022). It is also possible that this fragmented information on astrocyte and ependymal lineages could be due to the regional and/or temporal difference of samples between two human datasets.

      1-3. I believe the most significant advance for this paper is the potential to use ferret tRG cells to model those of the human brain. However to support this claim (see Lines 83-84), I believe a comparison of the ferret tRG cells with existing cortical organoid datasets (Bhaduri et al., 2020, PMID: 31996853) would be helpful. If cortical organoids currently lack the presence of tRG cell types, that would strengthen the importance of the ferret model and the findings of this paper - otherwise, I feel that the use of the ferret model needs to be justified in light of the greater accesibility and genetic tractability of the cortical organoid system.

      We absolutely agree that human organoids are good models to study human brain development.

      Revision plan:

      According to the suggestion of reviewer 1, we analyzed two cortical organoid datasets (Bhaduri et al., 2020; Herring et al., 2022) to examine whether different tRG populations are present in organoids. Our analyses led us to conclude that tRG-like populations seem to be lacking in available organoid datasets; organoids can have CRYAB-expressing astrocyte-like cells in single-cell transcriptome datasets, but the presence of tRG-like cells seem to be unstable and dependent of lines and protocols how organoids are generated. A further assessment on tRGs’ cellular features is required on organoids by immunostaining experiments. In the light of this analysis, we elaborated our discussion by describing observations shown below. Below is our analysis of organoid data.

      Bhaduri dataset contained organoids generated from 4 different lines, which showed a variability in terms of cell distribution on UMAP while overall temporal and differentiation axes were recapitulated (A). While keeping the original cluster annotations except for YH10 line, we performed reclustering. CRYAB was expressed in clusters 26 and 30 enriched in YH10 line, and cluster 29 enriched in 13234 line (B).

      https://www.dropbox.com/scl/fi/8mj6u94t3hkzw6q61o7od/reviewer1_3AB.pdf?rlkey=10xiks25nzn9r90guw9l0onqh&dl=0

      To confirm the identity of these clusters, we integrated organoid dataset with the dataset of primary tissues from the same paper (Bhaduri et al., 2020; C).

      https://www.dropbox.com/scl/fi/qnqv2e87t74uom2pg836d/reviewer1_3CD.pdf?rlkey=mv370b3dlogwvgh6ig8bdathp&dl=0

      As a result of the integration, tRG cells from the primary tissue were not overlapped with organoid-derived CRYAB-expressing cells, although a part of CRYAB-expressing organoid cells were localized in the integrated cluster 16 where primary tRG resided (D). Other cell types that were included in the integrated cluster 16 were “lateRG”, “vRG”, “oRG” from primary tissue dataset, and “glycolyticRG” from organoid dataset. We found that CRYAB-expressing organoid clusters 26 and 30 overlapped with “oRG/astrocyte” clusters of primary tissues.

      Furthermore, we have analyzed another organoid dataset in stages including 5-months, 9-months and 12-months (Herring et al., 2022; E), but found no clusters that specifically expressed CRYAB (F).

      https://www.dropbox.com/scl/fi/b4kiqoqyhhzk4vm5hi1bb/reviewer1_3EF.pdf?rlkey=dd00hju5n4b90wpz2zexi9gxa&dl=0

      1-4. I found the total number of tRG-like cells in the ferret dataset quite small (162), but I understand the difficulty with isolating and sequencing rare cell types from primary tissue sources. I believe most of the transcriptomic analyses were conducted with this low n in consideration, but this caveat is even more reason to pare down the wording for the weaker claims mentioned above.

      We thank the Reviewer for appreciating the difficulties associated with isolating and sequencing rare cell types. We were able to identify a total of 409 tRG cells (in tRG-like cluster) after merging all timepoints of sequencing, (Figure 1C, S3C) as stated in line 162 of the original manuscript. However, to perform pseudotime analyses, we subset our dataset using 6,000 cells in total (excluding neuron and non-progenitor clusters; Methods), which included 162 tRG cells. Pseudotime analysis transcriptomically distinguished tRG into 3 subgroups (Figure 4E). Remaining 247 tRG cells also appear to distribute similarly into these subgroups rather than forming a distinct subregion within tRG cluster (right panel in figure below). Furthermore, we conducted extensive immunohistochemical analyses of tRG-like cells, and we found that both the morphology and gene/protein expression were consistent with the notion that “tRG-like” cluster in our ferret dataset represents tRG defined in humans (Nowakowski et al., 2016).

      Revision plan:

      As for human dataset, we agree that the population of committed tRG was minor. Thus, we pared down our statements regarding the fates of tRG as mentioned in other comments, both in the Results and Discussion.

      https://www.dropbox.com/scl/fi/aqsg5xlbxyoybzwq0xezp/reviewer1_4.pdf?rlkey=oxhmtko08nhvzkmsqxcjf9qua&dl=0

      - Are prior studies referenced appropriately?

      1-5. I found it interesting that tRGs persist and even expand in number in postnatal timepoints (Fig. 2C). I'd be interested to know if this is in line with what is known in human developing cortex. If so, it would strengthen the conclusion that ferret tRGs can model that of humans - and if not, this would either be an important finding regarding tRG function or an important caveat in the use of ferret tRGs to model the cell type in humans.

      We thank the Reviewer for bringing up this issue. This is an important issue because we wanted in this study to use the ferret as a good model for the complex brain development in gyrencephalic animals, in general, to know what characteristics are shared or not, across gyrencephalic species (such as the presence of the OSVZ vs. the temporal scale).

      Revision plan:

      Our study demonstrated the presence of tRG cells up to P10 by immunohistochemistry and scRNA-seq. P5~P10 is the stage where neurogenesis became dominated by gliogenesis in the dorsal cortex in ferrets, although its timing is delayed in the visual cortex. On the other hand, Nowakowski et al. (2016) originally identified and defined CRYAB-expressing tRG, based on morphology and gene expression on human primary tissues during mid-neurogenic stages, while cortical neurogenesis is mostly declined in human postnatal stages. We have failed to find literatures or textbooks describing the presence of CRYAB-expressing tRG, while an ependymal layer was detected in the postnatal human cortices (Honig et al., 1996; preprint Nascimento et al., 2022). At the moment, the lack of information thus makes it difficult to compare the relationship of birth timing with the period of tRG persistence between ferrets and humans. In the revised manuscript, the “Discussion” will include this argument as well as the following difference between humans and ferrets in the RG scaffold.

      Besides birth timing, Nowakowski et al. also reported that radial glia scaffold spanning from the VZ to the pial surface undergoes a transformation during neurogenic stages; tRG becomes the major RG population in the VZ, disconnecting VZ and OSVZ. In contrast, we did not find a discontinuous scaffold stage over the course of ferret neurogenesis. Instead, we still detected CRYAB-negative vRG with an apical attachment and a basal process extending beyond the OSVZ during stages where the peak of tRG expansion is achieved (such as P5 in Figure 2A, S3A). This appears to be a prominent difference between human and ferret corticogenesis.

      - Are the text and figures clear and accurate? Yes

      - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      1-6. For Fig. 2A, I would find it helpful to compare the morphology of GFP+/CRYAB+ cells vs GFP+/CRYAB- cells, with the hypothesis that GFP+/CRYAB- cells will have elongated basal processes. I believe this could be done by finding GFP+/CRYAB- cells in the raw images obtained to generate Fig. 2A (or similar), and showing those cells in an adjacent panel. This side-by-side comparison could provide more support that the CRYAB+ cells from the single-cell analyses are indeed specifically linked to tRG-like morphology.

      Revision plan:

      We prepared the images for GFP+/CRYAB- vRG cells in an adjacent panel in Figure 2A as recommended by the reviewer (below). To better distinguish the morphology of an isolated vRG cell from other labelled cells, we sparsely labeled RG cells with EGFP at P3 by electroporation (Methods), and fixed the samples two days later (right panel). We highlighted the morphology (cell body and basal fiber) of a CRYAB- GFP+ vRG and that of a neighboring CRYAB+ GFP- tRG on the same panel to clarify that vRG did not express CRYAB.

      https://www.dropbox.com/scl/fi/3wrmqdswt69t8pkdy30h7/reviewer1_6.pdf?rlkey=90ixbadan3mxx10m85jnpwphn&dl=0

      Reviewer #1 (Significance (Required)):

      This paper primarily presents a technical advance in the field, showing that tRG cells that can model those found in the developing human cortex are found in the developing ferret cortex.

      - Place the work in the context of the existing literature (provide references, where appropriate).

      - State what audience might be interested in and influenced by the reported findings.

      Several studies in the human and macaque brain have identified the presence of tRGs (deAzevedo et al., 2003; Nowakowski et al., 2016), but understanding the molecular functions and development of these cells - and many human-specific cell types in the brain - is difficult due to the lack of tractable models of human neurodevelopment. Ferrets, given their layered cortices, may be a potential model system for these cell types, but further analyses to determine their transcriptomic similarity to the developing human cortex and their ability to recapitulate human cell types are required in order to evaluate their use as a model system. By generating a useful resource in the ferret single-cell transcriptomic atlas, this study provides evidence that - at least for the tRG subtypes - ferrets may be useful in dissecting the generation and functional importance of tRG cells. With the caveat that a direct comparison with the use of cortical organoids to study tRG is lacking in this paper (see above), I believe this work can provide useful insight into the field's current search for model systems to functionally interrogate human-specific aspects of cortical development.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      2-1. In this report, Bilgic and colleagues study the diversity of progenitor cell types in the developing ferret cerebral cortex, a valuable in vivo model to understand cortex expansion and folding, as in primates including human. Using a single-cell transcriptomics approach, they describe a diversity of progenitor cell types and their interrelation by transcriptomic trajectories, which are conserved but biased as development progresses. Most interestingly, they identify in ferret a type of cell only identified in human before, tRG, which they then characterize throughoutly by transcriptomics. They also identify these cells in histological sections, and via time-lapse videomicroscopy they characterize their cell type of origin. They also provide indirect evidence that tRG may be the source of ependymal cells in the ventricle of the mature cerebral cortex, as well as astroglial progenitor cells. Finally, they extend their analyses to identify oRG in ferret based on previous human single cell data, concluding that they have in ferret a quite different transcriptomic profile than in human.

      We would like to thank the reviewer for carefully reading our manuscript and providing us with valuable feedback. However, we would like to clarify that there might have been a misunderstanding regarding our conclusion about the identification of oRG-like cells in ferrets.

      Our study did not conclude that we have identified oRG cells in ferrets with “a quite different transcriptomic profile than in human”. Instead, our findings indicate that unlike oRG cells in human, ferret oRG-like cells did not exhibit specificity for human oRG markers (such as HOPX and CLU) that would enable us to distinguish them from other late RG cells in ferrets. Despite this, oRG score derived from human oRG marker expression showed higher values in predicted ferret oRG-like cells compared to other ferret RG cells, reflecting a similarity of the transcriptome profile between human oRG and ferret oRG-like cells (Figure 7H-I). We will carefully describe our methodology to reach this conclusion in response to reviewer 2’s comment regarding how we determined ferret oRG in a later comment.

      Major issues:

      2-2. The authors must provide evidence that the cortical area they are examining will give rise to Somatosensory cortex. Their sampling area appears more like Cingulate cortex, while somatosensory may be a bit more lateral. The cingulate cortex is a very unique region, with some unique characteristics including lamination and connectivity. It would be important to provide some justification as to why they chose this particular part of the cerebral cortex, and keep this into consideration when discussing the general value of their findings.

      The reviewer 2 seems to misunderstand that we took cortical strips shown in Figure S1A as samples for scRNA seq. If our description in the main text is confusing, that would be our fault.

      In Figure S1A of the original manuscript, we showed the cropped images of the medial part to emphasize the distinguishment of different germinal layers (VZ/iSVZ/oSVZ) and their temporal changes in ferret cortices.

      Revision Plan. To avoid such a misleading, we inserted the dotty lines in the revised Figure S1A to demarcate the tissue parts for scRNAseq, which correspond to almost all lateral cortices, mainly including the somatosensory area 1 and 2 with surrounding areas. We accordingly added the following sentence in the legend, “The approximate boundaries of dorsal cortex area used for scRNA sequencing are highlighted with dotty line segments in the dorsal cortex hemisphere above each strip.”.

      We also show actual sampling for single-cell transcriptomics below. As our sampling was not restricted to the somatosensory cortex, we have revised “somatosensory cortex” as “dorsal cortex” in Lines 131 and 1191 of our manuscript.

      https://www.dropbox.com/scl/fi/9gg508iood73zl02836g6/reviewer2_2.pdf?rlkey=lufevala88ihvc1p6mts463as&dl=0

      2-3. It seems that the single cell datasets were collected from only 1 replica at each developmental stage. Current best practice sets the inclusion of several biological replicates. Whereas this represents multiplying the workload (and costs) and re-doing many of the analyses, it is currently highly valued. On the other hand, the authors already have their analysis pipelines defined, and so the time involved should be much shorter than before.

      We disagree with the reviewer 2’s comment. We would like to clarify that we collected brain tissues in two different ways for the same set of developmental stages; one brain tissue by removing cortical plate (T); another independent brain tissue at the same developmental stage by sorting GFP-labelled lineage from neural progenitors that were electroporated at embryonic stages (AG, Methods). Both manipulations of samples aimed to increase progenitor cell populations in scRNAseq. Therefore, we have two sets of samples of the same temporal series, each prepared in a totally different way. All cell types were present in both methods of collection shown as Supplementary Figure 2E’ (below left) that separates samples by different preparations at each stage (by modifying Supplementary Figure 2E; below right). We believe that the biological replica (n=2) in this manuscript would be sufficiently reliable, judged by its reproducibility.

      https://www.dropbox.com/scl/fi/levyqy9ngvpyio1yl9oif/reviewer2_3.pdf?rlkey=r4aw0hu9cdn68f1pvhp734vxx&dl=0

      Here, we also cite several examples of papers important in the field of single-cell or bulk transcriptomics of brain tissue, where only a single replicate or pair (replica) was taken for experiments on mice, humans and ferrets:

      mice: Ogrodnik et al., 2021 PMID: 33470505, Hochgerner et al., 2018 PMID: 29335606, Joglekar et al., 2021 PMID: 33469025;

      human: Herring et al., 2022 PMID: 36318921, Polioudakis et al., 2019 PMID: 31303374, Mayer et al., 2019 PMID: 30770253, Fietz et al., 2012 PMID: 22753484;

      macaque: Schmitz et al., 2022 PMID: 35322231;

      ferret: Johnson et al., 2018 PMID: 29643508.

      2-4. Single cell QC methods are incomplete as described in Methods. It is key to consider the relative abundance of mitochondrial RNAs when assessing the integrity and validity of cells, and thus a key criterion to select the cells for clustering analysis. The criteria for the selected choice of clustering resolution is also missing.

      The reviewer pointed out an important criterion, the abundance of mitochondria.

      Revision Plan:

      We have now added the mitochondrial QC metrics in the new Figure S2A, and revised the legends as follows: “Violin plots showing the number of genes, mRNAs and the percentage of mitochondrial genes per cell in each sample and time point”. We have computed the percentage of mitochondrial genes for each cell type and found that the majority of cells in each cell type had a value less than 5% while the content value in some cells distributed along the range between 0% and 10%, up to a maximum of 28% (Figure S2A). Despite this, we have decided to include all cells that had less than 30% of mitochondrial genes in our analysis based on the percentage of reads mapped on mitochondrial genome for the following reasons:

      1. The percentage of mitochondrial indicates respiratory activity, rather than apoptosis and the percentage of mitochondrial quite depends on the tissue type and species. For example, in human case, such percentage range from 5%~30% (Mercer et al., 2011 Cell; The human mitochondrial transcriptome).
      2. Unfortunately, unlike human and mouse brains, there is no reference to show the percentage of mitochondrial in ferret brains. Therefore, the suitable way is to keep all of these cells.
      3. These cells showing high percentage of mitochondrial genes are not clustered as an apoptosis cluster in UMAP, instead, these cells are observed in most of clusters (below). Therefore, we believed that these cells are not apoptotic cells and include these cells in further analysis.

      https://www.dropbox.com/scl/fi/4kp3fczxzo6x4fx8hqt8m/reviewer2_4_1.pdf?rlkey=ypojzbuwgelt51qlf56g883s9&dl=0 4. After all, we have obtained similar clustering overall after filtering cells with a higher percentage for mitochondrial genes; we set the threshold to 10%. This filtering resulted in 28,686 cells in our dataset. We then performed our workflow from the normalization step with the same settings that we applied to our original ferret dataset (Methods). Below, we show the results comparing newly generated clusters in this filtered subset on UMAP (left), and the original clusters shown in Figure 1B (right). 26 clusters were obtained in both conditions, and both major cell types and subtypes were conserved after filtering.

      https://www.dropbox.com/scl/fi/0mlk69z7hckpiw03ivfjb/reviewer2_4_2.pdf?rlkey=hfvjrifrytmnywc4vchjvf0ms&dl=0

      Clustering resolution: Our choice of the resolution was based on avoiding over- or under-clustering of ferret cells. After trying several resolution values, including 0.6, 0.8, 1.0 and 1.2, we have decided to use the resolution of 0.8 as the separation of cell types was the most reasonable among other resolutions that we have tried, in a similar way to actual known cell types. For example, the resolution of 0.6 did not distinguish “tRG” cells from “late_RG1” cells, as well as “early_RG” subtypes which were distinctly enriched with different cell cycle markers (Figure S2D). On the other hand, the resolution of 1.2 resulted in an over-clustering of IPC, OPC, DL neurons and microglia.

      2-5. When first describing tRGs (line 171), orthogonal views of the image z-stacks must be shown to demonstrate the full morphology of these cells. The basal process might have been cut during tissue sectioning. The same applies to images in Fig. 2C, 2D, S3A.

      Revision plan:

      We focused on Figure 2A and S3A (2D is a histogram) to show the full morphology of CRYAB+ tRG, because Figure 2A is the initial presentation of tRG in this paper, and Fig. 2A and Fig.S3A images are taken on a 200-micrometer thick section, originally aiming to indicate that CRYAB-positive fiber is short, spanning nearly along the VZ and the SVZ. We made 3D-reconstructions of those images, which are rather better than orthogonal projections, in order to show that CRYAB+ fibers are shorter than those of vRG (terminating at positions around the upper boundary of the SVZ) and that the short basal processes are not due to the cut of long radial fibers during tissue sectioning.

      We will show these 3D-reconstruction below. Please download movie files from the following URLs to look at them clearly.

      Figure 2A

      https://www.dropbox.com/s/qocve596c5xhtlc/%E2%98%85fig2A-Ver02.mp4?dl=0

      Figure S3A

      https://www.dropbox.com/s/v8gqwfi1r8ff5n5/%E2%98%85figS3A-P0%20movie-ver2.mp4?dl=0

      2-6. In Figure 3, the authors perform time-lapse imaging to visualize and characterize the cells and lineage that give rise to tRGs. While very nice and a technical challenge that must be properly acknowledged, they unfortunately only obtained a total of three examples, which is clearly insufficient to reach any meaningful conclusion on this respect. These conclusions, while fascinating, are based only on 3 cell divisions. If this is to be taken as a strong argument for the conclusions of the study, the authors must obtain. If the authors want to make a solid statement out of this experimental approach, they must obtain a sufficient amount of additional data, which will depend on the variability of the results they find.

      We thank the reviewer for appreciating our time-lapse imaging data as very nice and a technical challenge. The number of time-lapse imaging that could follow the cell fates was from “4” samples instead of 3. It is indeed very infrequent and difficult to obtain a complete set of consecutive divisions from vRG, followed by histochemical examinations (fixation, cryo-sectioning and immunostaining of slices). This is because some of EGFP-labeled cells are frequently indistinguishable from each other by overlapping within a clone or with cells in other clones. Therefore, we decided to take a different way to clarify the pathways from vRG and its variety to generate tRG at the tRG-generating stage.

      Revision plan:

      Increasing the number of time-lapse image series will be extremely inefficient because of the reasons described above, perhaps taking a long time such as 3-5 months according to our breeding schedule of ferrets. Therefore, we take an alternative way to clarify the division patterns from vRG to generate tRG, especially focusing on the identity and variety of vRG sibling cells at the tRG-generating stage; we are examining the sibling pair of vRG and/or precursor of tRG to see what kind of cell the vRGs actually generate at their mitosis. For this purpose, we electroporate ferret cortices with the EGFP-expressing plasmid approximately one cell cycle prior to fixation (E38 or P0). We then stain ferret cortices for a mitotic marker Ki67 and tRG marker CRYAB and other markers during the tRG-generating state (P0-P5), assuming the cell cycle length of vRG and IPC as approximately 33h~45h based on our own consecutive EdU labeling experiments and time-lapse imaging.

      2-7. Still regarding the time-lapse results presented in Figure 3, it is unclear why after first division the authors identify the blue cell as IPC, when it has the exact features of tRG: apical process anchored in VZ surface + short basal process. This is applicable to all three examples shown. For example, the authors describe: "the mother IPC of tRG also possessed both an apical endfoot and a short basal fiber (Fig. 3D)". Why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC? The interpretation of IPCs being the mother cells to tRGs must be changed, to those being vRGs. Or else, more convincing data must be provided.

      In fact, their analyses in Fig 4A contradict their interpretation on tRG mother cells, showing that the transcriptomic trajectory leading to tRGs does not inlcude Eomes+ cells, accumulated in the neurogenic state 2. At the end of this section, the authors indicate: "our data suggest that tRG cells are formed by apical asymmetric division(s) from unique apical IPC with a short basal fiber (Tsunekawa et al, in preparation).". Being as important as this point is, if there is solid supporting data the authors must include it in this study.

      We appreciate the reviewer 2’s question about “why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC?”

      Revision plan.

      1. We are confident that this blue-labeled cells in Figure 3A and D are not vRG but mitotic sibling cell (of vRG) with a short basal fiber (that we named IPC in the initial manuscript). We now made the morphological features of these cells clearly visible by constructing 3D-views of the images with different snapshot images (we show below and in the preliminary revision as a supplementary movie). In addition, it divides once as time-lapse imaging revealed, hence this cell is still mitotic, instead of a postmitotic cell. Therefore, we used the term that is generally used for this type of cells, namely, intermediate progenitor cells (IPC), by which we did not intend to refer to TBR2+ neurogenic IPC. We plan to include these revised images into our fully revised manuscript.
      2. We agree the reviewer 2 on the point that this blue-labeled cell may express CRYAB (the next comment of reviewer 2 essentially claims the same point), as we also wrote this possibility in line 204-207 of the original manuscript. It could not be technically possible at the moment to examine CRYAB expression in a cell emerging only in the course of time-lapse imaging. If we could label vRG with a transgenic or knock-in fluorescence marker, which mimics CRYAB gene expression, we could have figured out whether blue cells (the mitotic vRG sibling cells) express the CRYAB gene. Indeed, we tried to knock the EGFP gene in the CRYAB gene many times over a year, but have so far failed. Given that tRG is defined as the cell type expressing CRYAB with a short basal fiber at late-neurogenic stage, irrespective of its mitotic activity, this blue labeled vRG sibling cell in Fig. 3A (and/or Fig. 3D) might express CRYAB, hence can be a “mitotic tRG” (although its possibility seems to be low as shown in Fig. 2E). To avoid any possible misleading, we have changed the term of these cells to a “mitotic vRG sibling cell (or mitotic tRG parental cell) with a short basal process”, and add a comment that “this cell might be mitotic tRG with CRYAB expression”.
      3. As for the TBR2 expression, we do not know these cells that appeared in the course of time-lapse imaging express TBR2 or not. As shown in Fig. 2F, 10% (P10) to 30 % (P5) of CRYAB+ cells express TBR2. On the other hand, “intermediate progenitors” do not necessarily express TBR2 in general. Therefore, we disagree on the reviewer 2’s comment “their analyses in Fig 4A contradict their interpretation on tRG’s parent cells”, but “our analyses in Fig 4A is compatible with our interpretation on tRG’s parent cells in time-lapse imaging”, and that is “a mitotic vRG sibling (or mitotic tRG parental cell) with a short basal fiber divides to produce CRYAB+ tRG at the end of timelapse imaging”. However, to avoid any overstatements or misunderstanding on this issue, we have revised related text as described above.
      4. We are not able to include the data taken by Tsunekawa et al.. This is because we are going to submit a separate paper, which includes a large volume of data with human ones in collaboration with another group and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not practical to combine these data with those described in this manuscript. Therefore, we remove all descriptions related with Tsunekawa et al.

      Below we show snapshot images and 3D-reconstructions for Figure 3A and 3D. Please download movie files from the following URLs to view at them at the highest resolution.

      @Figure 3A:

      1)A time lapse movie (20 min interval) showing images around time 40:00 at which vRG underwent the second division.

      https://www.dropbox.com/s/znx3bboxefhj0jt/%E2%98%85Fig_3A%20movies%20around%2040%20h.mp4?dl=0

      2)Snapshot images for time 40:00

      https://www.dropbox.com/s/6y25mk4jhwqy6v7/%E2%98%85E38-fig3A-sRG-2.png?dl=0

      3) 3D-reconstruction images at the same time point (40:00)

      https://www.dropbox.com/s/so8hesjzy63yxmb/%E2%98%853D-reconstruction%20%2840.00%202nd%20div%29.mp4?dl=0

      4) The entire time-lapse movies of time 0:00-84:00; The mitotic sibling cell of the vRG is indicated by a white arrow.

      https://www.dropbox.com/s/ywua95f8fmohsmc/%E2%98%85Fig3A-arrow-time.mp4?dl=0

      @Figure 3D:

      A revised time-lapse snapshots of Figure 3D.

      https://www.dropbox.com/s/xyet4virt3j9u3t/%E2%98%8520211220%EF%BC%8DP0%EF%BC%8Dtimelaps-xt04corrected.psd?dl=0

      The assignment of the cell has corrected to the right one for the same mitotic cell because cell body position at the first two time points were misassigned in the original manuscript (at the following time points, there is no change).

      Snapshot image at time point of 06:20; https://www.dropbox.com/s/hn3v6ao1qkhnfjh/%E2%98%85Fig3D%20sRG%20at%200620.png?dl=0

      Rotating movie of 3D-reconstruction at time point of 06:40:

      https://www.dropbox.com/s/6taqjr0u21x5tn0/%E2%98%853Drotated%20movie%20of%20time%20point%2006.40.mp4?dl=0

      2-8. Alternative interpretation of time-lapse images (lines 196-197): maybe a tRG can generate one tRG CRYAB+, and one IPC CRYAB-.

      We agree with reviewer 2 that there is an alternative interpretation of cell identity appearing in time-lapse imaging of Fig. 3. In line 196-197, we wrote that “These mother IPC underwent an asymmetric division to generate a non-CRYAB expressing cell and a CRYAB__+ tRG”. As pointed by reviewer 2 here and in the previous comment, we cannot exclude the possibility that this vRG sibling cell may be a mitotic tRG (see our response to the previous reviewer 2 comment). If so, what we observed in Fig. 3A and D could be interpreted as a mitotic tRG, and generate one CRYAB+ tRG and one CRYAB- climbing cell. However, as we haven’t confirmed or stated whether this parent cell was a mitotic tRG, we also did not examine the identity of this sister cell of CRYAB+ tRG. It can be an IPC or nascent neuron or even an astroglial progenitor cell. From our data, we cannot say anything about the identity of the CRYAB-negative sister cell other than that this cell is CRYAB-negative, migrating upward. That is why we did not mention about the identity of this CRYAB-negative sister cell of tRG other than that the sister cell of tRG is CRYAB-negative.

      Revision plan. We changed the term of IPC to “a mitotic vRG sibling cell” and describe the possibility that “This mitotic vRG sibling cell (or mitotic tRG parental cell) can be a mitotic tRG if this cell express CRYAB, and its apical division generates one tRG and one CRYAB-negative climbing cell with an unknown identity, replacing the description of line 196-197.

      2-9. Arrows in Fig 5E are shifted between the top and bottom panels. There is no obvious evidence of mitosis visible. This should be unequivocally labeled with anti-PH3 antibodies.

      We thank reviewer 2 for pointing our careless mistake.

      Revision plan. We have corrected the shifted position of arrows in Figure 5E. We have removed “mitosis” in the title of Figure 5E since the initial manuscript did not include descriptions on mitosis in the text.

      2-10. Line 277: “Transcriptomic trajectories were homologous across the two species”. What does this refer to? What are these trajectories? Pseudotime? Is this statistically tested?

      The meaning of the term “Transcriptomic trajectories” was not clear.

      Revision plan. We revised our description in this part as “Temporal patterns and variety of neural progenitors during the cortical development were similar to each other between humans and ferrets at the single cell transcriptome level”.

      2-11. When comparing tRG cells between ferret and human, the authors indicate a remarkable similarity between the two species as represented by CRYAB, EGR1, and CYR61 expression. As shown in Fig 6E, EGR1 and CYR61 are not expressed selectively in human tRG as they clearly are in ferret tRG. Hence, this argument is not valid.

      In lines 291-292, we mention that “tRG cells also showed a remarkable similarity between the two species (Fig. 6C, 6D), as represented by CRYAB, EGR1, and CYR61 expression (Fig. 6E)”. Here, what we wanted to claim is that the same combination of gene expression (CRYAB, EGR1, and CYR61) is characteristically at relatively high levels in both ferrets and human tRG. As the reviewer 2 claimed, CRYAB and CYR61 genes are highly selective for ferret tRG among mid-late RG types, while the expression of EGR1 and CYR1 are just relatively enriched in tRG than in other cell types in human RG (except for highly selective CRYAB). Irrespective of the difference in their relative enrichment in tRG between humans and ferrets, one can still state that the combination of these marker expression at higher levels is shared in these two species”. We were not able to find which part in the manuscript was the reviewer referring to for the claimed argument (“EGR1 and CYR61 are expressed selectively in human tRG”).

      Revision plan. To clarify our statement, we changed this sentence into “tRG cells also showed a remarkable similarity between the two species (Fig. 6C, 6D), as represented by a high level of expression for the combination of CRYAB, EGR1, and CYR61 (Fig. 6E)”

      2-12. In the last part, the authors try to identify oRG-like cells in ferret by comparison with their transcriptomes identified in human. For this, they decide to call ferret oRG-like cells those that are near human oRGs in the integrated UMAP, as identified in a previous human study. What was the criterion for this? How much near is "near"? The fact that the selected cells have higher oRG scores is expected and obvious, as these cells were selected precisely based on their proximity in the UMAP. Even more importantly, the identification of oRGs in the human study is not unambiguous. Therefore, the correlate in ferret cells is also non-conclusive as to the identity of such cells.

      We apologize for a confusion caused by insufficient explanations for our methodology. We want to clarify that we did not find " ferret oRG-like cells as those near human oRGs in the integrated UMAP." Rather, we try to identify oRG-like cells in ferrets based on the hypothesis that, when comparing ferret and human datasets, oRG-like cells in ferrets would exhibit a higher degree of similarity to human oRG cells than to other cell types. This hypothesis was supported by our observations of other clusters such as tRG, later RG, and IPC (Figure 6 C and D).

      To identify oRG-like cells in ferrets, we utilized the mutual nearest neighbor (MNN) method to determine the similarity between cells from different species (Stuart et al., 2019 PMID: 31178118). For example, when attempting to identify the human cell that was most similar to a given ferret cell (F), we calculated the distance between cell F and all the cells in the human dataset in the high dimensional expression space. This allowed us to identify a human cell (H) that exhibited the smallest distance to cell F. Subsequently, we computed the distance between cell H and all the cells in the ferret dataset. If cell F had the smallest distance to cell H in the human dataset, we considered cells H and F as a pair of mutual nearest neighbors.

      Using this method, we can find all pair of mutual nearest neighbors in two datasets. We then find these pairs that one is human oRG and define the other is oRG-like in ferret. However, upon further investigation of the characteristics of these cells, we would not find any specific markers (such as HOPX and CLU in human oRG) that would enable us to distinguish them from other later RG cells in ferrets.

      Accordingly, only when our strategy to find mutual nearest neighbors is suitable, the selected cells can get higher oRG score, otherwise, the selected set of ferret cells will not show a high oRG score. Therefore, we disagree with the notion that “The fact that the selected cells have higher oRG scores is expected and obvious”.

      We hope this explanation provides a clearer understanding of our methodology and the rationale behind our approach to identifying potential oRG cells in ferrets.

      2-13. Discussion is surprisingly short, given the emphasis that the authors place on the importance of their findings. I would suggest extending it for a better coverage of those findings that have the greatest relevance and interest to a wider readership.

      Thank reviewer 2 for his/her precious advice.

      Revision plan.

      We added several issues discussed in the responses to the reviewers to Discussion. Please look at our responses to comment 2-14 and 2-15 as well as the preliminary manuscript.

      2-14. In Discussion, the authors state that "ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." Again, this conclusion is purely based on transcriptomic trajectories, which must not be confused with cell lineage. This sentence must be rephrased and toned down accordingly.

      We appreciate Reviewer’s comment regarding the difference between transcriptomic trajectories and cell lineage. We agree that transcriptomic trajectories do not necessarily reflect cell lineage. However, relationships along transcriptomic trajectories provides useful information about the differentiation potential of cells. Furthermore, in this study, we examined the temporal and spatial relationships between CRYAB+ tRG and FoxJ1+ ependymal cells that were predicted as tRG descendant cells by transcriptomic trajectories. We could confirm an increasing overlap of FoxJ1+cells with tRG cells along the course of post-natal development in Figure 5. We thus accessed the relationship of the two cell types by not only in silico but also in vivo analyses.

      Revision plan. We disagree with the reviewer 2 as for ferrets, because we accessed the relationship of tRG and their progeny cells by not only in silico but also in vivo analyses.

      On the other hand, as for progenies of human tRG, they were predicted certainly depending on the molecular relationship by comparison with ferrets without histochemical evidence, as pointed by reviewer 2, and the populations of these committed tRG are small. Therefore, we removed “(and presumably also human)” and we tone down about the progeny relationship of tRG as a prediction. We also acknowledge that further studies are needed to confirm the lineage relationships among cell types, as we discussed in the Discussion part.

      2-15. In Discussion: “our cross-species analysis highlights the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter”. As mentioned above, this is only based on transcriptomic trajectories, it is not demonstrated in this study. In vivo analyses of cell fate are needed to support this conclusion, and a more extensive videomicroscopy analysis is needed to confirm the cell lineage progression suggested by transcriptomes.

      The statement “the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter” is certainly a speculation based on our results, but not experimentally indicated yet by such as gene knockout, as the reviewer pointed out. Although we repeatedly tried to knock out the CRYAB gene in ferrets for a year, we have so far failed.

      Revision plan. Taking the comments from reviewer 1 and 2 into account, we largely revised “Discussion” with a more moderate expression, by incorporating comparative analyses with other human datasets, and we also emphasize the importance of in vivo studies as the next step. We just paste the last paragraph of the preliminary revised Discussion. Please see the “Discussion” in the preliminary revision of our manuscript.

      “In ferrets, genetic manipulations can be achieved through in utero or postnatal electroporation, as well as via virus-mediated transfer of DNA (Borrell, 2010; Kawasaki et al, 2012; Matsui et al, 2013; Tsunekawa et al, 2016). Thus, it is theoretically possible to disrupt the CRYAB gene in vivo in ferrets to investigate its role in tRG and their progeny, including ependymal cells, and to track the tRG lineage. If the CRYAB gene is essential to form ependymal layers, we will be able to explore how the ventricle contributes to cortical folding and expansion. Despite extensive efforts over a year, we have thus far been unsuccessful in knocking in and/or knocking out the CRYAB gene. Nevertheless, we anticipate that technical advances will surpass our expectations, both in ferret and human organoids. Taken together, these functional studies in ferrets as well as in human organoids hold promising insights into the understanding of the tRG lineage and its contribution to cortical development in the near future”.

      Minor issues:

      2-16. In line 59, the authors state: "cerebral carcinogenesis independently evolved to gain an additional germinal layer (outer SVZ (OSVZ);". Assuming that they mean "cerebral neurogenesis", what is the evidence for this independent evolution? Original publications demonstrating this must be cited.

      Revision plan. We removed the mentioned statement from our manuscript and revised lines 58-59 as follows: “In many mammalian phylogenic states, cerebral cortex evolved to gain an additional germinal layer (Smart et al. 2002; Zecevic et al. 2005; Kriegstein et al. 2006; Reillo et al. 2011)”.

      2-17. Lines 60-61, the third key publication reporting the existence of bRG must be cited together with Hansen 2010 and Fietz 2010: Reillo et al., 2011, Cerebral Cortex.

      We appreciate Reviewer 2’s remark.

      Revision plan. We now added these citations in lines 60-61 and in the Reference list as Reillo I, De Juan Romero C, García-Cabezas MÁ & Borrell V (2011). A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. Cereb Cortex 21: 1674–1694.

      2-18. When introducing ferret as an interesting or important animal model, suitable original studies should be cited.

      Revision plan:

      For ferrets, there is a long history as experimental animals for electrophysiology similarly with cats and monkeys, but this is not a review of ferret biology. We thus added 6 additional references regarding ferret brain morphology and development listed below.

      Jackson, C.A., J.D. Peduzzi, and T.L. Hickey (1989) Visual cortex development in the ferret. I. Genesis and migration of visual cortical neurons. J. Neurosci.9:1242–1253. PMID: 2703875.

      Chapman B & Stryker MP (1992) Origin of orientation tuning in the visual cortex. Curr Opin Neurobiol 2: 498–501.

      Chenn A., and McConnell S.K. (1995) Cleavage orientation and the asymmetric inheritance of Notch1 immunoreactivity in mammalian neurogenesis. Chenn A, et al. Cell PMID: 7664342.

      Noctor SC, Scholnicoff NJ, and Juliano SL. (1997) Histogenesis of ferret somatosensory cortex. J Comp Neurol. 387(2):179-93.PMID: 9336222.

      Reid CB, Tavazoie SF, Walsh CA. (1997) Clonal dispersion and evidence for asymmetric cell division in ferret cortex. Development. 1997 124(12):2441-2450. doi: 10.1242/dev.124.12.2441.PMID: 9199370

      2-19. In Figure 2F-H, layer borders should be labeled. The density of CRYAB+ cells in VZ (?) at P5 seems much greater in Fig 2E,F than in Fig. 2B. Clarifying this discrepancy is important to validate the quantification of Fig 2D.

      Revision plan.

      Layer borders: We now labeled the approximate position of the boundary of the VZ in Figure 2E-G. We have revised the legends as follows; “The border of the VZ is shown with a white line”. For counting, we have determined borders by the distribution of DAPI, and radial glia-specific markers in our hands and determined the approximative distance of the VZ border from the ventricular surface in the antero-posterior axis where we performed the imaging in Figure 2E-G. The distance was approximately determined as 80 µm at P5 and 40 µm at P10.

      Discrepancy in the intensity of CRYAB: We apologize for the unclear statement on how the images were acquired in the legends of Figure 2E-G. We now revised as follows; “Representative images taken with a 100X-objective lens are shown with MAX projection.”. In Figure 2E-G, images were taken as optical sections of 1.5 µm interval for 12 µm-thick sections. Those images were processed as MAX-projection onto the Z plane. On the other hand, In Figure 2B, we have used 20X-objective lens, instead of 100X-objective lens and did not perform any image projection procedure such as a MAX-projection and only 1 z-plane is shown. Therefore, the visual difference in the CRYAB intensity between Figure 2B and Figure 2E-G derives from whether max projection of several consecutive images was done.

      2-20. Co-expression of CRYAB and FOXJ1. In Fig 5B this must be demonstrated with merged channels.

      Revision plan.

      We added the images with merged channels as requested and revised corresponding legends as follows: “Images with merged channels in A are shown with the same color codes, antibodies and scale bars as A.”.

      2-21. Line 247: "near which nuclear line aggregates are observed more frequently (Fig. 2B)". It is very much unclear what the authors refer to. Please, define nuclear line aggregates.

      Revision plan.

      We will revise the cited sentence and will change the referred figure as follows: “These cells often aligned on a line parallel to the ventricular surface (Fig. 5A)”. We show these nuclear rows by arrows.

      2-22. There are a number of typos along the main text and figures, which must be fully checked and corrected. For example, line 59 "cerebral carcinogenesis"; also in Figure S4, Figure 5E. Labeling of graphs in Fig 5C is wrong. The plots present the fraction of CRYAB+ cells that express FOXJ1 (FOXJ1+/CRYAB+ cells), not the reverse.

      Revision plan.

      We thank the Reviewer for their remarks on typos. We corrected the typos indicated by Reviewer 2. We agree with the Reviewer and also modified the title of Figure 5B as suggested by the Reviewer.

      Reviewer #2 (Significance (Required)):

      This manuscript is of interest for being the first ferret single-cell study, and for identifying and characterizing to a great extent a unique population of cortical progenitor cells that so far had only been observed in human. The study is presented as a resource for studies of ferret cortex development, which as such is clearly of interest to a very limited audience. A more appealing perspective might be if this study in ferret is of interest or of use to the more general community studying cortex development, or even maybe cortex evolution.

      We disagree the reviewer’s view that this study is clearly of interest to a very limited audience. This study first enabled a precise comparative analysis in which we could compare rich human single cell transcriptomes and the ferret dataset of single cell transcriptomes, which were based on greatly improved genomic information (especially, gene models). This study is also first to show global temporal patterns of cortical progenitors of a carnivore species, a famous gyrencephalic mammalian model, and have been shown to be similar to a primate species at the single cell transcriptomic level. Indeed, upon uploading this manuscript in BioRxiv, many non-ferret specialists as well as specialists have inquired datasets and requested some collaborations with us. So we believe that this paper has already attract a general interest of brain scientists.

      Advance: it is, so far, the first study of single cell profiling of the ferret cerebral cortex, a well established and highly valued model of gyrencephalic mammals, and a suitable best-alternative to work in primates. In addition to the technical advance, providing a new resource for work in ferret, it shows for the first time the existence of truncated Radial Glia (tRG) in a non-human cortex, and even more importantly in this model, strengthening even more its value.

      This study as is presented will be of most interest to a specialized audience, those directly working with ferret. Nevertheless, it will also be of conceptual interest to the community of cortex development and evolution for the concepts that one can extract on cell type conservation.

      Description of the revisions that have already been incorporated in the transferred manuscript

      Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

      1-1. The weakest claim in the paper is lines 202: "...tRG cells are formed by apical asymmetric division(s) from unique apical IPC". From my understanding, the main evidence that the tRG parent cells shown in Fig. 3 are not tRGs are the data from Fig. 2E-G showing the low amounts of CRYAB+ cells co-expressing KI67, TBR2, or OLIG2 in P5 and P10. Especially given that these timepoints are after those used in Fig. 3, I believe further evidence is needed to confirm the cell type identity of tRG parent cells in Fig. 3. Such experiments (isolating IPCs from ferret cortex and growing in vitro to determine progeny cells) may be outside of the scope of this paper, in which case I believe the text can be strengthened with either (1) presenting the data from the cited Tsunekawa et al, in preparation that would suggest this claim or (2) rephrasing these claims to omit the mention of IPCs.

      1. We revise the term “IPC” as “mitotic sibling of vRG” and stated that these cells might be tRG (CRYAB+) or non-tRG (CRYAB-) intermediate progenitors. By the term of “intermediate progenitors”, we did not intend to refer to TBR2+ neurogenic IPCs, but rather to an intermediate state of progenitors, in a general sense, with a similar morphology as tRG. To avoid any confusions on this terminology, we revised our manuscript by replacing “IPC” with “a sibling of vRG”.
      2. We delete all statements relevant to Tsunekawa et al. data from the manuscript. We regret that we are not able to include Tsunekawa et al. data because we are planning to submit this data as a separate manuscript, which describes that in ferrets, vRG frequently (30% of apical division) generate non-Tbr2-positive mitotic sibling cells bearing a short basal process during the entire neurogenesis. This study includes a large volume of data with human ones and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not appropriate to combine these data with those described in this manuscript.

      1-2. I also believe the claim in Line 365-366 is overstated: "We found that ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." While I believe the transcriptomic comparisons suggest the presence of uncommitted tRG in both the ferret and human datasets, I would appreciate further analyses to confirm the prevalence of astroglial and ependymal tRG in the humans and/or functional analyses before claiming that human tRG cells make ependymal and astrogenic cells. I appreciate the authors' note that "GW25 is...the latest stages experimentally available" (line 376-377), but their comparative approaches could be applied to existing datasets of the human cortex (Herring et al., 2022, PMID: 36318921) that span later developmental ages. Identifying the presence of astroglial and ependymal tRGs in this and/or similar datasets would provide more convincing evidence of the tRGs' developmental potential. If this computational analysis is outside the scope of the paper, I believe paring the certainty of these claims (especially lines 379 - 383) and recognizing the need for further functional analyses would negate the need for deeper mechanistic validation.

      1. We compared our ferret dataset to the human postnatal dataset recommended by the Reviewer 1 (Herring et al., 2022). As a conclusion of our analyses shown below, we found that Herring et al., (2022) dataset was not favorable for a comparative analysis with our ferret dataset regarding the fates of human tRG, because Herring’s human dataset was derived from the prefrontal cortex; This human dataset does not include neither tRG cell population nor ependymal clusters. We have also elaborated our discussion after analyzing Herring et al. dataset in the discussion.
      2. We, therefore, pare down our claim in lines 365-366, by removing “(and presumably human)” to state that “Our pseudotime trajectory analyses and immunohistochemistry analyses strongly suggested that…”.
      3. We also tone down the statements as for the discussion of the relationship between human and ferrets regarding the tRG progeny fates (originally lines from 372 to the end) and also elaborated our discussion after analyzing Herring et al. dataset in the same paragraph.

      We will describe the details of our analysis of Herring et al. (2022) below.

      https://www.dropbox.com/scl/fi/a0m72orxfsub66dh3hdbg/reviewer1_2ABC.pdf?rlkey=uzrd8ngclp87p5c8v24mqd1j7&dl=0

      As mentioned above, Herring’s human dataset was derived from the prefrontal cortex, and that it did not include a specific subtype defined as tRG nor other HES1-expressing progenitor clusters such as RG in the original cluster annotation. We, therefore, re-clustered the raw dataset from GW22 (the earliest stage available) up to 10-months after birth by using Seurat pipeline with default parameters (B), and found a CRYAB-expressing population in the original “Astrocyte_GFAP” subtype among astrocyte clusters (A), which distribute in the most of collected stages, from late development through the adulthood. We then examined this dataset to find out whether tRG or its progenies are present.

      After reclustering, CRYAB-expressing cells (with more than 1 raw count) represented 0.15% of the dataset and were grouped as a part of cluster 44, which was mostly derived from postnatal stages (among which 4-months was the most enriched one; C). Several astrocyte markers, such as SPARCL1, HOPX, CLU, and GJA1, as well as CRYAB, were enriched in the cluster 44 as revealed by FindMarkers (Methods). FOXJ1 expression was nearly absent overall in this dataset, indicating the absence of the ependymal cell population, a tRG-descendant cell types in ferrets (C).

      To evaluate the similarity between cluster 44 and tRG or astroglial tRG, we next integrated Herring dataset with our ferret subset (about 15,000 cells) and the human GW25 subset from Bhaduri et al. (2021) of approx. 3,000 cells, both of which contained only progenitor cells. As we have done in Figure 7 of our original manuscript; we have removed cells other than progenitors, astrocytes and oligodendrocytes, such as neurons, microglia, endothelial cells. This resulted in about 20,000 cells in Herring dataset.

      https://www.dropbox.com/scl/fi/nz3iulya5199i95ecr1un/reviewer1_2D.pdf?rlkey=kp7lwxtkn562un1uf9l1axn2p&dl=0

      This integration (D) reveals that Herring’s cluster 44 is closely located to Bhaduri’s human and our ferret tRG clusters on UMAP, but does not overlap with these tRG clusters. This result further suggested that tRG population might be lacking or very rare in this neuron- and glia-dominated dataset, which might be due to the sampling method that targeted the enrichment of neuronal layers (Herring et al., 2022). It is also possible that this fragmented information on astrocyte and ependymal lineages could be due to the regional and/or temporal difference of samples between two human datasets.

      1-3. I believe the most significant advance for this paper is the potential to use ferret tRG cells to model those of the human brain. However to support this claim (see Lines 83-84), I believe a comparison of the ferret tRG cells with existing cortical organoid datasets (Bhaduri et al., 2020, PMID: 31996853) would be helpful. If cortical organoids currently lack the presence of tRG cell types, that would strengthen the importance of the ferret model and the findings of this paper - otherwise, I feel that the use of the ferret model needs to be justified in light of the greater accesibility and genetic tractability of the cortical organoid system.

      According to the suggestion of reviewer 1, we analyzed two cortical organoid datasets (Bhaduri et al., 2020; Herring et al., 2022) to examine whether different tRG populations are present in organoids. Our analyses led us to conclude that tRG-like populations seem to be lacking in available organoid datasets; organoids can have CRYAB-expressing astrocyte-like cells in single-cell transcriptome datasets, but the presence of tRG-like cells seem to be unstable and dependent of lines and protocols how organoids are generated. A further assessment on tRGs’ cellular features is required on organoids by immunostaining experiments. In the light of this analysis, we elaborated our discussion by describing observations shown below. Below is our analysis of organoid data.

      https://www.dropbox.com/scl/fi/8mj6u94t3hkzw6q61o7od/reviewer1_3AB.pdf?rlkey=10xiks25nzn9r90guw9l0onqh&dl=0

      Bhaduri dataset contained organoids generated from 4 different lines, which showed a variability in terms of cell distribution on UMAP while overall temporal and differentiation axes were recapitulated (A). While keeping the original cluster annotations except for YH10 line, we performed reclustering. CRYAB was expressed in clusters 26 and 30 enriched in YH10 line, and cluster 29 enriched in 13234 line (B).

      To confirm the identity of these clusters, we integrated organoid dataset with the dataset of primary tissues from the same paper (Bhaduri et al., 2020; C). https://www.dropbox.com/scl/fi/qnqv2e87t74uom2pg836d/reviewer1_3CD.pdf?rlkey=mv370b3dlogwvgh6ig8bdathpdl=0

      As a result of the integration, tRG cells from the primary tissue were not overlapped with organoid-derived CRYAB-expressing cells, although a part of CRYAB-expressing organoid cells were localized in the integrated cluster 16 where primary tRG resided (D). Other cell types that were included in the integrated cluster 16 were “lateRG”, “vRG”, “oRG” from primary tissue dataset, and “glycolyticRG” from organoid dataset. We found that CRYAB-expressing organoid clusters 26 and 30 overlapped with “oRG/astrocyte” clusters of primary tissues.

      1-4. I found the total number of tRG-like cells in the ferret dataset quite small (162), but I understand the difficulty with isolating and sequencing rare cell types from primary tissue sources. I believe most of the transcriptomic analyses were conducted with this low n in consideration, but this caveat is even more reason to pare down the wording for the weaker claims mentioned above.

      As for human dataset, we agree that committed tRG was minor. Thus, we pared down our statements regarding the fates of tRG as mentioned in other comments, both in the Results and Discussion.

      https://www.dropbox.com/scl/fi/aqsg5xlbxyoybzwq0xezp/reviewer1_4.pdf?rlkey=oxhmtko08nhvzkmsqxcjf9qua&dl=0

      1-5. I found it interesting that tRGs persist and even expand in number in postnatal timepoints (Fig. 2C). I'd be interested to know if this is in line with what is known in human developing cortex. If so, it would strengthen the conclusion that ferret tRGs can model that of humans - and if not, this would either be an important finding regarding tRG function or an important caveat in the use of ferret tRGs to model the cell type in humans.

      Our study demonstrated the presence of tRG cells up to P10 by immunohistochemistry and scRNA-seq. P5~P10 is the stage where neurogenesis became dominated by gliogenesis in the dorsal cortex in ferrets, although its timing is delayed in the visual cortex. On the other hand, Nowakowski et al. (2016) originally identified and defined CRYAB-expressing tRG, based on morphology and gene expression on human primary tissues during mid-neurogenic stages, while cortical neurogenesis is mostly declined in human postnatal stages. We have failed to find literatures or textbooks describing the presence of CRYAB-expressing tRG, while an ependymal layer was detected in the postnatal human cortices (Honig et al., 1996; preprint Nascimento et al., 2022). At the moment, the lack of information thus makes it difficult to compare the relationship of birth timing with the period of tRG persistence between ferrets and humans. In the revised manuscript, the “Discussion” will include this argument as well as the following difference between humans and ferrets in the RG scaffold.

      Besides birth timing, Nowakowski et al. also reported that radial glia scaffold spanning from the VZ to the pial surface undergoes a transformation during neurogenic stages; tRG becomes the major RG population in the VZ, disconnecting VZ and OSVZ. In contrast, we did not find a discontinuous scaffold stage over the course of ferret neurogenesis. Instead, we still detected CRYAB-negative vRG with an apical attachment and a basal process extending beyond the OSVZ during stages where the peak of tRG expansion is achieved (such as P5 in Figure 2A, S3A). This appears to be a prominent difference between human and ferret corticogenesis.

      1-6. For Fig. 2A, I would find it helpful to compare the morphology of GFP+/CRYAB+ cells vs GFP+/CRYAB- cells, with the hypothesis that GFP+/CRYAB- cells will have elongated basal processes. I believe this could be done by finding GFP+/CRYAB- cells in the raw images obtained to generate Fig. 2A (or similar), and showing those cells in an adjacent panel. This side-by-side comparison could provide more support that the CRYAB+ cells from the single-cell analyses are indeed specifically linked to tRG-like morphology.

      We prepared the images for GFP+/CRYAB- vRG cells in an adjacent panel in Figure 2A as recommended by the reviewer (below). To better distinguish the morphology of an isolated vRG cell from other labelled cells, we sparsely labeled RG cells with EGFP at P3 by electroporation (Methods), and fixed the samples two days later (right panel). We highlighted the morphology (cell body and basal fiber) of a CRYAB- GFP+ vRG and that of a neighboring CRYAB+ GFP- tRG on the same panel to clarify that vRG did not express CRYAB.

      https://www.dropbox.com/scl/fi/3wrmqdswt69t8pkdy30h7/reviewer1_6.pdf?rlkey=90ixbadan3mxx10m85jnpwphn&dl=0

      2-2. The authors must provide evidence that the cortical area they are examining will give rise to Somatosensory cortex. Their sampling area appears more like Cingulate cortex, while somatosensory may be a bit more lateral. The cingulate cortex is a very unique region, with some unique characteristics including lamination and connectivity. It would be important to provide some justification as to why they chose this particular part of the cerebral cortex, and keep this into consideration when discussing the general value of their findings.

      To avoid such a misleading, we inserted the dotty lines in the revised Figure S1A to demarcate the tissue parts for scRNAseq, which correspond to almost all lateral cortices, mainly including the somatosensory area 1 and 2 with surrounding areas. We accordingly added the following sentence in the legend, “The approximate boundaries of dorsal cortex area used for scRNA sequencing are highlighted with dotty line segments in the dorsal cortex hemisphere above each strip.”.

      We also show actual sampling for single-cell transcriptomics below. As our sampling was not restricted to the somatosensory cortex, we have revised “somatosensory cortex” as “dorsal cortex” in Lines 131 and 1191 of our manuscript.

      https://www.dropbox.com/scl/fi/9gg508iood73zl02836g6/reviewer2_2.pdf?rlkey=lufevala88ihvc1p6mts463as&dl=0

      2-4. Single cell QC methods are incomplete as described in Methods. It is key to consider the relative abundance of mitochondrial RNAs when assessing the integrity and validity of cells, and thus a key criterion to select the cells for clustering analysis. The criteria for the selected choice of clustering resolution is also missing.

      We have now added the mitochondrial QC metrics in the new Figure S2A, and revised the legends as follows: “Violin plots showing the number of genes, mRNAs and the percentage of mitochondrial genes per cell in each sample and time point”. We have computed the percentage of mitochondrial genes for each cell type and found that the majority of cells in each cell type had a value less than 5% while the content value in some cells distributed along the range between 0% and 10%, up to a maximum of 28% (Figure S2A). Despite this, we have decided to include all cells that had less than 30% of mitochondrial genes in our analysis based on the percentage of reads mapped on mitochondrial genome for the following reasons:

      1. The percentage of mitochondrial indicates respiratory activity, rather than apoptosis and the percentage of mitochondrial quite depends on the tissue type and species. For example, in human case, such percentage range from 5%~30% (Mercer et al., 2011 Cell; The human mitochondrial transcriptome).
      2. Unfortunately, unlike human and mouse brains, there is no reference to show the percentage of mitochondrial in ferret brains. Therefore, the suitable way is to keep all of these cells.
      3. These cells showing high percentage of mitochondrial genes are not clustered as an apoptosis cluster in UMAP, instead, these cells are observed in most of clusters (below). Therefore, we believed that these cells are not apoptotic cells and include these cells in further analysis. https://www.dropbox.com/scl/fi/4kp3fczxzo6x4fx8hqt8m/reviewer2_4_1.pdf?rlkey=ypojzbuwgelt51qlf56g883s9&dl=0
      4. After all, we have obtained similar clustering overall after filtering cells with a higher percentage for mitochondrial genes; we set the threshold to 10%. This filtering resulted in 28,686 cells in our dataset. We then performed our workflow from the normalization step with the same settings that we applied to our original ferret dataset (Methods). Below, we show the results comparing newly generated clusters in this filtered subset on UMAP (left), and the original clusters shown in Figure 1B (right). 26 clusters were obtained in both conditions, and both major cell types and subtypes were conserved after filtering.

      https://www.dropbox.com/scl/fi/0mlk69z7hckpiw03ivfjb/reviewer2_4_2.pdf?rlkey=hfvjrifrytmnywc4vchjvf0ms&dl=0

      Clustering resolution: Our choice of the resolution was based on avoiding over- or under-clustering of ferret cells. After trying several resolution values, including 0.6, 0.8, 1.0 and 1.2, we have decided to use the resolution of 0.8 as the separation of cell types was the most reasonable among other resolutions that we have tried, in a similar way to actual known cell types. For example, the resolution of 0.6 did not distinguish “tRG” cells from “late_RG1” cells, as well as “early_RG” subtypes which were distinctly enriched with different cell cycle markers (Figure S2D). On the other hand, the resolution of 1.2 resulted in an over-clustering of IPC, OPC, DL neurons and microglia.

      2-5. When first describing tRGs (line 171), orthogonal views of the image z-stacks must be shown to demonstrate the full morphology of these cells. The basal process might have been cut during tissue sectioning. The same applies to images in Fig. 2C, 2D, S3A.

      We focused on Figure 2A and S3A (2D is a histogram) to show the full morphology of CRYAB+ tRG, because Figure 2A is the initial presentation of tRG in this paper, and Fig. 2A and Fig.S3A images are taken on a 200-micrometer thick section, originally aiming to indicate that CRYAB-positive fiber is short, spanning nearly along the VZ and the SVZ. We made 3D-reconstructions of those images, which are rather better than orthogonal projections, in order to show that CRYAB+ fibers are shorter than those of vRG (terminating at positions around the upper boundary of the SVZ) and that the short basal processes are not due to the cut of long radial fibers during tissue sectioning (we show in below and in the final version as a supplementary figure and movies).

      We show these 3D-reconstruction in below. Please download movie files from the following URLs to look at them clearly.

      Figure 2A

      https://www.dropbox.com/s/qocve596c5xhtlc/%E2%98%85fig2A-Ver02.mp4?dl=0

      Figure S3A

      https://www.dropbox.com/s/v8gqwfi1r8ff5n5/%E2%98%85figS3A-P0%20movie-ver2.mp4?dl=0

      2-7. Still regarding the time-lapse results presented in Figure 3, it is unclear why after first division the authors identify the blue cell as IPC, when it has the exact features of tRG: apical process anchored in VZ surface + short basal process. This is applicable to all three examples shown. For example, the authors describe: "the mother IPC of tRG also possessed both an apical endfoot and a short basal fiber (Fig. 3D)". Why is this identified as IPC, when it looks exactly like vRG, NOT as an IPC? The interpretation of IPCs being the mother cells to tRGs must be changed, to those being vRGs. Or else, more convincing data must be provided.

      In fact, their analyses in Fig 4A contradict their interpretation on tRG mother cells, showing that the transcriptomic trajectory leading to tRGs does not inlcude Eomes+ cells, accumulated in the neurogenic state 2. At the end of this section, the authors indicate: "our data suggest that tRG cells are formed by apical asymmetric division(s) from unique apical IPC with a short basal fiber (Tsunekawa et al, in preparation).". Being as important as this point is, if there is solid supporting data the authors must include it in this study.

      1. We are confident that this blue-labeled cells in Figure 3A and D are not vRG but mitotic sibling cell (of vRG) with a short basal fiber (that we named IPC in the initial manuscript). We now made the morphological features of these cells clearly visible by constructing 3D-views of the images with different snapshot images (we show below and in the final revision as a supplementary figure and movies). In addition, it divides once as time-lapse imaging revealed, hence this cell is still mitotic, instead of a postmitotic cell. Therefore, we used the term that is generally used for this type of cells, namely, intermediate progenitor cells (IPC), by which we did not intend to refer to TBR2+ neurogenic IPC. We plan to include these revised images into our fully revised manuscript.
      2. We agree the reviewer 2 on the point that this blue-labeled cell may express CRYAB (the next comment of reviewer 2 essentially claim the same point), as we also wrote this possibility in line 204-207 of the original manuscript. It could not be technically possible at the moment to examine CRYAB expression in a cell emerging only in the course of time-lapse imaging. If we could label vRG with a transgenic or knock-in fluorescence marker, which mimics CRYAB gene expression, we could have figured out whether blue cells the mitotic vRG sibling cells (or mitotic tRG parental cell) express the CRYAB gene. Indeed, we tried to knock the EGFP gene in the CRYAB gene many times over a year, but have so far failed. Given that tRG is defined as the cell type expressing CRYAB with a short basal fiber at late-neurogenic stage, irrespective of its mitotic activity, this blue labeled vRG sibling cell in Fig. 3A (and/or Fig. 3D) might express CRYAB, hence can be a “mitotic tRG” (although its possibility seems to be low as shown in Fig. 2E). To avoid any possible misleading, we have changed the term of these cells to a “mitotic vRG sibling cell (or mitotic tRG parental cell) with a short basal process”, and add a comment that “this cell might be mitotic tRG with CRYAB expression”.
      3. As for the TBR2 expression, we do not know these cells that appeared in the course of time-lapse imaging express TBR2 or not. As shown in Fig. 2F, 10% (P10) to 30 % (P5) of CRYAB+ cells express TBR2. On the other hand, “intermediate progenitors” do not necessarily express TBR2 in general. Therefore, we disagree on the reviewer 2’s comment “their analyses in Fig 4A contradict their interpretation on tRG’s parent cells”, but “our analyses in Fig 4A is compatible with our interpretation on tRG’s parent cells in time-lapse imaging”, and that is “a mitotic vRG sibling (or mitotic tRG parental cell) with a short basal fiber divides to produce CRYAB+ tRG at the end of timelapse imaging”. However, to avoid any overstatements or misunderstanding on this issue, we have revised related text as described above.
      4. We are not able to include the data taken by Tsunekawa et al.. This is because we are going to submit a separate paper, which includes a large volume of data with human ones in collaboration with another group and largely concerns stages that are earlier than that of tRG formation. It is, therefore, not practical to combine these data with those described in this manuscript. Therefore, we remove all descriptions related with Tsunekawa et al.

      Below we show snapshot images and 3D-reconstructions for Figure 3A and 3D. Please download movie files from the following URLs to look at them clearly.

      @Figure 3A:

      1)A time lapse movie (20 min interval) showing images around time 40:00 at which vRG underwent the second division. https://www.dropbox.com/s/znx3bboxefhj0jt/%E2%98%85Fig_3A%20movies%20around%2040%20h.mp4?dl=0

      2)Snapshot images for time 40:00

      https://www.dropbox.com/s/6y25mk4jhwqy6v7/%E2%98%85E38-fig3A-sRG-2.png?dl=0

      3) 3D-reconstruction images at the same time point (40:00)

      https://www.dropbox.com/s/so8hesjzy63yxmb/%E2%98%853D-reconstruction%20%2840.00%202nd%20div%29.mp4?dl=0

      4) The entire time-lapse movies of time 0:00-84:00; The mitotic sibling cell of the vRG is indicated by a white arrow.

      https://www.dropbox.com/s/ywua95f8fmohsmc/%E2%98%85Fig3A-arrow-time.mp4?dl=0

      @Figure 3D:

      A revised time-lapse snapshots of Figure 3D.

      https://www.dropbox.com/s/xyet4virt3j9u3t/%E2%98%8520211220%EF%BC%8DP0%EF%BC%8Dtimelaps-xt04corrected.psd?dl=0

      The assignment of the cell has corrected to the right one for the same mitotic cell because cell body position at the first two time points were misassigned in the original manuscript (at the following time points, there is no change).

      Snapshot image at time point of 06:20; https://www.dropbox.com/s/hn3v6ao1qkhnfjh/%E2%98%85Fig3D%20sRG%20at%200620.png?dl=0

      Rotating movie of 3D-reconstruction at time point of 06:40:

      https://www.dropbox.com/s/6taqjr0u21x5tn0/%E2%98%853Drotated%20movie%20of%20time%20point%2006.40.mp4?dl=0

      2-8. Alternative interpretation of time-lapse images (lines 196-197): maybe a tRG can generate one tRG CRYAB+, and one IPC CRYAB-.

      We changed the term of IPC to “a mitotic vRG (or mitotic tRG parental cell) sibling cell” and describe the possibility that “This mitotic vRG sibling cell (or mitotic tRG parental cell) can be a mitotic tRG if this cell express CRYAB, and its apical division generates one tRG and one CRYAB-negative climbing cell with an unknown identity, replacing the description of line 196-197.

      2-9. Arrows in Fig 5E are shifted between the top and bottom panels. There is no obvious evidence of mitosis visible. This should be unequivocally labeled with anti-PH3 antibodies.

      We have corrected the shifted position of arrows in Figure 5E. We have removed “mitosis” in the title of Figure 5E since the initial manuscript did not include descriptions on mitosis in the text.

      2-10. Line 277: “Transcriptomic trajectories were homologous across the two species”. What does this refer to? What are these trajectories? Pseudotime? Is this statistically tested?

      We revised our description in this part as “Temporal patterns and variety of neural progenitors during the cortical development were similar to each other between humans and ferrets at the single cell transcriptome level”.

      2-11. When comparing tRG cells between ferret and human, the authors indicate a remarkable similarity between the two species as represented by CRYAB, EGR1, and CYR61 expression. As shown in Fig 6E, EGR1 and CYR61 are not expressed selectively in human tRG as they clearly are in ferret tRG. Hence, this argument is not valid.

      To clarify our statement, we changed this sentence into “tRG cells also showed a remarkable similarity between the two species (Fig. 6C, 6D), as represented by a high level of expression for the combination of CRYAB, EGR1, and CYR61 (Fig. 6E)”

      2-13. Discussion is surprisingly short, given the emphasis that the authors place on the importance of their findings. I would suggest extending it for a better coverage of those findings that have the greatest relevance and interest to a wider readership.

      We added several issues discussed in the responses to the reviewers to Discussion. Please look at our responses to comment 2-14 and 2-15 as well as the preliminary manuscript.

      2-15. In Discussion: “our cross-species analysis highlights the notable role of tRG as progenitors contributing to the formation of the ependyma and white matter”. As mentioned above, this is only based on transcriptomic trajectories, it is not demonstrated in this study. In vivo analyses of cell fate are needed to support this conclusion, and a more extensive videomicroscopy analysis is needed to confirm the cell lineage progression suggested by transcriptomes.

      Taking the comments from reviewer 1 and 2 into account, we largely revised “Discussion” with a more moderate expression, by incorporating comparative analyses with other human datasets, and we also emphasize the importance of in vivo studies as the next step. We just paste the last paragraph of the preliminary revised Discussion. Please see the “Discussion” in the preliminary revision of our manuscript.

      “In ferrets, genetic manipulations can be achieved through in utero or postnatal electroporation, as well as via virus-mediated transfer of DNA (Borrell, 2010; Kawasaki et al, 2012; Matsui et al, 2013; Tsunekawa et al, 2016). Thus, it is theoretically possible to disrupt the CRYAB gene in vivo in ferrets to investigate its role in tRG and their progeny, including ependymal cells, and to track the tRG lineage. If the CRYAB gene is essential to form ependymal layers, we will be able to explore how the ventricle contributes to cortical folding and expansion. Despite extensive efforts over a year, we have thus far been unsuccessful in knocking in and/or knocking out the CRYAB gene. Nevertheless, we anticipate that technical advances will surpass our expectations, both in ferret and human organoids. Taken together, these functional studies in ferrets as well as in human organoids hold promising insights into the understanding of the tRG lineage and its contribution to cortical development in the near future”.

      2-16. In line 59, the authors state: "cerebral carcinogenesis independently evolved to gain an additional germinal layer (outer SVZ (OSVZ);". Assuming that they mean "cerebral neurogenesis", what is the evidence for this independent evolution? Original publications demonstrating this must be cited.

      We removed the mentioned statement from our manuscript and revised lines 58-59 as follows: “In many mammalian phylogenic states, cerebral cortex evolved to gain an additional germinal layer (Smartet al. 2002; Zecevic et al. 2005; Kriegstein et al. 2006; Reillo et al. 2011)”.

      2-17. Lines 60-61, the third key publication reporting the existence of bRG must be cited together with Hansen 2010 and Fietz 2010: Reillo et al., 2011, Cerebral Cortex.

      We now added these citations in lines 60-61 and in the Reference list as Reillo I, De Juan Romero C, García-Cabezas MÁ & Borrell V (2011). A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. Cereb Cortex 21: 1674–1694.

      2-18. When introducing ferret as an interesting or important animal model, suitable original studies should be cited.

      For ferrets, there is a long history as experimental animals for electrophysiology similarly with cats and monkeys, but this is not a review of ferret biology. We thus added 6 additional references regarding ferret brain morphology and development listed below.

      Jackson, C.A., J.D. Peduzzi, and T.L. Hickey (1989) Visual cortex development in the ferret. I. Genesis and migration of visual cortical neurons. J. Neurosci.9:1242–1253. PMID: 2703875.

      Chapman B & Stryker MP (1992) Origin of orientation tuning in the visual cortex. Curr Opin Neurobiol 2: 498–501.

      Chenn A., and McConnell S.K. (1995) Cleavage orientation and the asymmetric inheritance of Notch1 immunoreactivity in mammalian neurogenesis. Chenn A, et al. Cell PMID: 7664342.

      Noctor SC, Scholnicoff NJ, and Juliano SL. (1997) Histogenesis of ferret somatosensory cortex. J Comp Neurol. 387(2):179-93.PMID: 9336222.

      Reid CB, Tavazoie SF, Walsh CA. (1997) Clonal dispersion and evidence for asymmetric cell division in ferret cortex. Development. 1997 124(12):2441-2450. doi: 10.1242/dev.124.12.2441.PMID: 9199370

      2-19. In Figure 2F-H, layer borders should be labeled. The density of CRYAB+ cells in VZ (?) at P5 seems much greater in Fig 2E,F than in Fig. 2B. Clarifying this discrepancy is important to validate the quantification of Fig 2D.

      Layer borders: We now labeled the approximate position of the boundary of the VZ in Figure 2E-G. We have revised the legends as follows; “The border of the VZ is shown with a white line”. For counting, we have determined borders by the distribution of DAPI, and radial glia-specific markers in our hands and determined the approximative distance of the VZ border from the ventricular surface in the antero-posterior axis where we performed the imaging in Figure 2E-G. The distance was approximately determined as 80 µm at P5 and 40 µm at P10.

      2-20. Co-expression of CRYAB and FOXJ1. In Fig 5B this must be demonstrated with merged channels.

      We added the images with merged channels as requested and revised corresponding legends as follows: “Images with merged channels in A are shown with the same color codes, antibodies and scale bars as A.”.

      2-21. Line 247: "near which nuclear line aggregates are observed more frequently (Fig. 2B)". It is very much unclear what the authors refer to. Please, define nuclear line aggregates.

      We revise the cited sentence and will change the referred figure as follows: “These cells often aligned on a line parallel to the ventricular surface (Fig. 5A)”. We show these nuclear rows by arrows.

      2-22. There are a number of typos along the main text and figures, which must be fully checked and corrected. For example, line 59 "cerebral carcinogenesis"; also in Figure S4, Figure 5E. Labeling of graphs in Fig 5C is wrong. The plots present the fraction of CRYAB+ cells that express FOXJ1 (FOXJ1+/CRYAB+ cells), not the reverse.

      We thank the Reviewer for their remarks on typos. We corrected the typos indicated by Reviewer 2. We agree with the Reviewer and also modified the title of Figure 5B as suggested by the Reviewer.

      Description of analyses that authors prefer not to carry out

      Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

      2-1. In this report, Bilgic and colleagues study the diversity of progenitor cell types in the developing ferret cerebral cortex, a valuable in vivo model to understand cortex expansion and folding, as in primates including human. Using a single-cell transcriptomics approach, they describe a diversity of progenitor cell types and their interrelation by transcriptomic trajectories, which are conserved but biased as development progresses. Most interestingly, they identify in ferret a type of cell only identified in human before, tRG, which they then characterize throughoutly by transcriptomics. They also identify these cells in histological sections, and via time-lapse videomicroscopy they characterize their cell type of origin. They also provide indirect evidence that tRG may be the source of ependymal cells in the ventricle of the mature cerebral cortex, as well as astroglial progenitor cells. Finally, they extend their analyses to identify oRG in ferret based on previous human single cell data, concluding that they have in ferret a quite different transcriptomic profile than in human.

      We would like to thank the reviewer for carefully reading our manuscript and providing us with valuable feedback. However, we would like to clarify that there might have been a misunderstanding regarding our conclusion about the identification of oRG-like cells in ferrets.

      Our study did not conclude that we have identified oRG cells in ferrets with “a quite different transcriptomic profile than in human”. Instead, our findings indicate that unlike oRG cells in human, ferret oRG-like cells did not exhibit specificity for human oRG markers (such as HOPX and CLU) that would enable us to distinguish them from other late RG cells in ferrets. Despite this, oRG score derived from human oRG marker expression showed higher values in predicted ferret oRG-like cells compared to other ferret RG cells, reflecting a similarity of the transcriptome profile between human oRG and ferret oRG-like cells (Figure 7H-I). We will carefully describe our methodology to reach this conclusion in response to reviewer 2’s comment regarding how we determined ferret oRG in a later comment.

      2-3. It seems that the single cell datasets were collected from only 1 replica at each developmental stage. Current best practice sets the inclusion of several biological replicates. Whereas this represents multiplying the workload (and costs) and re-doing many of the analyses, it is currently highly valued. On the other hand, the authors already have their analysis pipelines defined, and so the time involved should be much shorter than before.

      We disagree with the reviewer 2’s comment. We would like to clarify that we collected brain tissues in two different ways for the same set of developmental stages; one brain tissue by removing cortical plate (T); another independent brain tissue at the same developmental stage by sorting GFP-labelled lineage from neural progenitors that were electroporated at embryonic stages (AG, Methods). Both manipulations of samples aimed to increase progenitor cell populations in scRNAseq. Therefore, we have two sets of samples of the same temporal series, each prepared in a totally different way. All cell types were present in both methods of collection shown as Supplementary Figure 2E’ (section 2) that separates samples by different preparations at each stage (by modifying Supplementary Figure 2E; section 2). We believe that the biological replica (n=2) in this manuscript would be sufficiently reliable, judged by its reproducibility.

      https://www.dropbox.com/scl/fi/levyqy9ngvpyio1yl9oif/reviewer2_3.pdf?rlkey=r4aw0hu9cdn68f1pvhp734vxx&dl=0

      Here, we also cite several examples of papers important in the field of single-cell or bulk transcriptomics of brain tissue, where only a single replicate or pair (replica) was taken for experiments on mice, humans and ferrets:

      mice: Ogrodnik et al., 2021 PMID: 33470505, Hochgerner et al., 2018 PMID: 29335606, Joglekar et al., 2021 PMID: 33469025;

      human: Herring et al., 2022 PMID: 36318921, Polioudakis et al., 2019 PMID: 31303374, Mayer et al., 2019 PMID: 30770253, Fietz et al., 2012 PMID: 22753484;

      macaque: Schmitz et al., 2022 PMID: 35322231;

      ferret: Johnson et al., 2018 PMID: 29643508.

      2-14. In Discussion, the authors state that "ferret (and presumably also human) tRG cells differentiate into ependymal cells and astrogenic cells." Again, this conclusion is purely based on transcriptomic trajectories, which must not be confused with cell lineage. This sentence must be rephrased and toned down accordingly.

      We disagree with the reviewer 2 as for ferrets, because we accessed the relationship of tRG and their progeny cells by not only in silico but also in vivo analyses.

      On the other hand, as for progenies of human tRG, they were predicted certainly depending on the molecular relationship by comparison with ferrets without histochemical evidence, as pointed by reviewer 2, and the populations of these committed tRG are small. Therefore, we removed “(and presumably also human)” and we tone down about the progeny relationship of tRG as a prediction. We also acknowledge that further studies are needed to confirm the lineage relationships among cell types, as we discussed in the Discussion part.

      Reviewer #2 (Significance (Required)):

      This manuscript is of interest for being the first ferret single-cell study, and for identifying and characterizing to a great extent a unique population of cortical progenitor cells that so far had only been observed in human. The study is presented as a resource for studies of ferret cortex development, which as such is clearly of interest to a very limited audience. A more appealing perspective might be if this study in ferret is of interest or of use to the more general community studying cortex development, or even maybe cortex evolution.

      We disagree the reviewer’s view that this study is clearly of interest to a very limited audience. This study first enabled a precise comparative analysis in which we could compare rich human single cell transcriptomes and the ferret dataset of single cell transcriptomes, which were based on greatly improved genomic information (especially, gene models). This study is also first to show global temporal patterns of cortical progenitors of a carnivore species, a famous gyrencephalic mammalian model, and have been shown to be similar to a primate species at the single cell transcriptomic level. Indeed, upon uploading this manuscript in BioRxiv, many non-ferret specialists as well as specialists have inquired datasets and requested some collaborations with us. So we believe that this paper has already attract a general interest of brain scientists.

    1. Are you really telling me that Shakespeare and Aeschylus weren’t writing about kings? All good art is political! There is none that isn’t. And the ones that try hard not to be political are political by saying, “We love the status quo.” We’ve just dirtied the word “politics,” made it sound like it’s unpatriotic or something. ... My point is that it has to be both: beautiful and political at the same time. I’m not interested in art that is not in the world.

      Toni Morrison, 2008

    1. "The final test of the value of what is called science is its applicability" are words quoted from the recent address of the President of the American Association for the Advancement of Science. With Huxley and President Woodward, I believe that there is no valid distinction between a pure science and an applied science. The practical needs of the astronomer to eliminate the personal equation from his observations led to the invention of the chronograph and the chronoscope. Without these two instruments, modern psychology and physiology could not possibly have achieved the results of the last fifty years. If Helmholtz had not made the chronograph an instrument of precision in physiology and psychology; if Fechner had not lifted a weight to determine the threshold of sensory discrimination, the field of scientific work represented to-day by clinical psychology could never have been developed. The pure and the applied sciences advance in a single front. What retards the progress of one, retards the progress of the other; what fosters one, fosters the other. But in the final analysis the progress of psychology, as of every other science, will be determined by the value and amount of its contributions to the advancement of the human race.

      Here Witmer talks about how psychology can be used as a tool to help further humanity, much like tools that helped develop modern psychology. It's not just for science and knowledge that we use psychology, but to benefit the world.

    1. Our data show that teachers sometimes fail entirely to recognize exceptional superiority in a pupil, and that the degree of such superiority is rarely estimated with anything like the accuracy which is possible to the psychologist after a one-hour examination. B. F., for example, was a little over 7½ years old when tested. He was in the third grade, and was therefore thought by his teacher to be accelerated in school. This boy's intelligence, however, was found to be above the 12-year level. There is no doubt that his mental ability would have enabled him, with a few months of individual instruction, to carry fifth or even sixth-grade work as easily as third, and without injury to body or mind. Nevertheless, the teacher and both the parents of this child had found nothing remarkable about him. In reality he belongs to a grade of genius not found oftener than once in several thousand cases.

      it's interesting to notate that above average intelligence in children is seen as something less remarkable than the feebleminded. If you have above average intelligence you are not always challenged or moved up grades. Rarely were these children tested to see just how advanced these children were to provide them with with more challenging work.

    1. Reviewer #2 (Public Review):

      Hoang, Tsutsumi et al provide a comprehensive functional mapping of cerebellar climbing fiber responses in Lobule Crus II. The study derives from analysis of a dataset originally published in Tsutsumi et al eLife 2019, using two photon Ca2+ imaging throughout the learning of a Go/No-go reward-driven licking behavior. Each recording session yielded data from a ~two-hundred micron patch of tissue, with neurons spatially localized relative the "zebrin" banding pattern of the cerebellar cortex as reported by an aldolaceC-tdTomato transgenic line. In the present work, complex spike times were extracted at higher temporal resolution using subframe raster line-scan timing information, and then decomposed at the trial-averaged population level using tensor component analysis.

      The central conclusion is that the entirety of crus II climbing fiber responses decomposes into just a few patterns that capture key features of the behavior. Some of these patterns strengthen with learning, i.e., feature climbing fiber spiking that increases in frequency, while others decay with learning, i.e., feature climbing fiber responses that are prominent only in novice animals. These different climbing fiber activity components are in some cases associated with either positive or negative aldolace-C compartments of crus II. Finally, synchronization is concentrated among cells contributing to the same tensor components, and synchrony levels increase or decrease for different components over learning.

      The analysis therefore suggests that distinct principles of climbing fiber function can be present simultaneously in distinct cerebellar modules (and, according to the TCA cell weightings, potentially simultaneously in individual climbing fibers). This conclusion is contrary to the implied dichotomy in the literature that climbing fibers either function as "error signals" or as "timing signals" in a particular behavioral context or cerebellar region. The authors speculate that resolution of this dichotomy could result from the biophysics of the inferior olive, in which flexibly coupled oscillators might self-organize into a low dimensional decomposition of task dynamics. Relatedly, the authors speculate that changes in synchronization that contrast between different components could serve to either regulate instructive signal dimensionality or climbing fiber timing functions, depending on each component's functional contribution. From a theoretical standpoint, this is a helpful new direction. The framework is more agnostic to the details of the activity profiles of any specific group of climbing fibers, but more attuned to the systems-level distribution of activity profiles and how these might collectively serve a behavior.

      A valuable feature of the study is the simultaneous analysis of many imaging fields spanning 17 subjects and the entire dorsal surface of crus II. This bypasses some of the recurring interpretational issues with climbing fiber recordings that stem from their spatial organization across the cerebellar surface with often abrupt transitions at compartmental boundaries. By decomposing responses across many compartments simultaneously (at the trial-averaged level), the authors provide a quantitative estimate of the diversity of response patterns and their distribution across space and cells. It's worth noting that this approach is also a double-edged sword, as the trial-averaged decomposition does not depend on single-trial correlations between neurons, thus strictly speaking leaving it an open question whether apparently similar climbing fiber patterns present in distant imaging fields exhibit correlated variability either across trials or across learning.

      The data convincingly show that several dominant tensor components explain a large amount of climbing fiber variance across crus II. The authors speculate that this reflects an olivary decomposition of task dynamics. Due to the nature of the analysis - TCA applied over an entire dataset - there is not a clear test of this hypothesis in the present manuscript.

      The authors also present the interesting and compelling result that different CF response patterns undergo opposite learned changes in synchronization. They speculate that different trajectories of synchronization, specifically, increases for TC1 (hit) and decreases for TC2 (false alarm), could reflect different functional uses of TC1 and TC2, although it is difficult to assess the likelihood of this being true based on the data and analyses presented.

    1. loss of directional movement

      This is a very minor wording thing, but the movement in 2E actually does look quite directional (it's not distributed around the circle), just not the direction that you would expect.

    1. Author Response

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

      We will make some minor changes to address the issues in the revised manuscript during preparation of the Version of Record.

      1) Acknowledge the previous discovery that COUPTFII expression is confined to the ventral hippocampus in early human fetal forebrain (doi: 10.1093/cercor/bhx185).

      We agree. We will incorporate the previous discovery that COUPTFII expression is confined to the ventral hippocampus in early human fetal forebrain (doi: 10.1093/cercor/bhx185) in the discussion section of "COUP-TFII governs the distinct characteristics of the ventral hippocampus".

      2) Give some consideration to this observation from my original review "Abnormalities in the trisynaptic circuit. No studies of actual synapses, either physiological or morphological, were carried out. I wonder to what extent these immunohistochemical studies just further reflect the abnormalities in hippocampal morphology presented earlier in the manuscript without specifically telling us about synaptic circuits? Although the immunohistochemical preparations are beautiful, they are inadequate on their own in telling us much about what sort of synaptic circuitry exists in the transgenic animals".

      Our data in Figure 4 show clearly that at the neural circuit level, compared with the corresponding control, the trisynaptic circuit is abnormal in all three models; therefore, in the discussion section of "COUP-TF genes are imperative for the formation of the trisynaptic circuit", we will add the following sentence, "We would like to investigate what sort of synaptic circuitry is compromised either physiologically or morphologically in the trisynaptic circuit of individual animal model in detail in the future studies.

      In addition, we will correct a reference related to the COUP-TFII gene and congenital heart defects.

      The reference of "High, F. A., Bhayani, P., Wilson, J. M., Bult, C. J., Donahoe, P. K., & Longoni, M. (2016). De novo frameshift mutation in COUP-TFII (NR2F2) in human congenital diaphragmatic hernia. Am J Med Genet A, 170(9), 2457-2461. doi:10.1002/ajmg.a.37830" was replaced with "Al Turki, S., Manickaraj, A. K., Mercer, C. L., Gerety, S. S., Hitz, M. P., Lindsay, S., . . . Hurles, M. E. (2014). Rare variants in NR2F2 cause congenital heart defects in humans. Am J Hum Genet, 94(4), 574-585. doi:10.1016/j.ajhg.2014.03.007".

      —————

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

      Reviewer #1(Recommendations For The Authors):

      1) Better presentation of the western blot results

      We agree with the reviewer. Based on the suggestion, new information about the western blot results has been added in the revised Figure 1Ap. We added a dash to each western blot image to indicate the target band of COUP-TFI (46 KDa), COUP-TFII (45 KDa), and GAPDH (37 KDa), respectively. There were two bands in the blot of COUP-TFII, with the upper band corresponding to mouse IgG at 50 KDa, and the bottom band corresponding to COUP-TFII protein at 45 KDa. Therefore, only the lower bands of COUP-TFII are used for the quantitative analysis. The expression of COUP-TFII in the ventral hippocampus is clearly higher than that in the dorsal hippocampus.

      2) Full presentation of the Immunohistochemistry and qPCR results for at E11.5 and E14.5 in double knockdown mice.

      Thanks for the suggestion. Based on the suggestion, we added immunofluorescent data in the double knockout mice at E11.5 in the Figure 5Ba-h. Meanwhile, given that it takes time to prepare animal samples at E14.5 for RT-qPCR assays, we performed immunofluorescent assays at both E13.5 and E14.5 to make sure that the changes of Lhx5 and Lhx2 expression in the hippocampal regions between the control and mutant mice were consistent. As shown in the new Figure 5B, consistent with the downregulated expression of Lhx5 transcripts in the double mutant, the expression of the Lhx5 protein was reduced in the CH in the double mutants at E11.5; moreover, the numbers of Lhx5-positive Cajal-Retzius cells decreased in the double mutant embryos at E11.5, E13.5 and E14.5 (Figure 5Ba-d, a’-d’, a’’-d’’, i-l, i’-l’, q-t, q’-t’). Consistent with RT-qPCR data, the expression of Lhx2 was comparable between the control and double-mutant mice at E11.5 (Figure 5Be-h, e’-h’). Interestingly, the expression of the Lhx2 protein was increased in the hippocampal primordium in the COUP-TF double-mutant mice at E13.5 and E14.5 (Figure 5Bm-p, m’-p’, u-x, u’-x’). Please find the altered descriptions in the Page 15, lines 347-351, 353-358 and Page 21, lines 500-503 in the revised manuscript.

      3) Minor corrections. Lines 159-162, prospected not quite the right word. I would suggest "an ectopic CA-like region was observed medially in the temporal hippocampus in the COUP1TFII mutant, where the prospective posterior part of the medial amygdaloid nucleus was situated, (MeP), indicated by the star (Figure 1Ba-f). The presence of the ectopic CA-like region in the ventral but not dorsal hippocampus of the mutant was further confirmed by the presence of the prospective MeP and amygdalohippocampal area (AHi) in sagittal sections, as indicated by the star. See also line 251. Line437/438 I would suggest "... most important breakthroughs in understanding the role of the hippocampus in memory."

      Thanks for the suggestion. We made the changes based on the suggestion. Please find the amendments in Page 8, lines 178-181; Page 12, lines 270, 276; Page 14, line 318; Page 19, lines 451; Page 20, lines 461-462 in the revised manuscript.

      Reviewer #2 (Recommendations For The Authors):

      1) It is also important to point out that the immunofluorescence data in Figure 5B is contrary to what is known for Lhx5 (it's not expressed in the neocortical and hippocampal vz) and Lhx2 (it's not expressed in the choroid plexus). Authors should explain how their conclusions could align more clearly, and consider the possibility that their results are due to a possible artifact of image setting issues or worse, antibody specificity issues.

      Very good point. Based on the comments and suggestions, we first tested another Lhx5 antibody, R&D, Cat # AF6290, in the immunofluorescence assays. Indeed, there was something wrong with the previous Lhx5 antibody, Millipore, Cat # AB5762. With the new Lhx5 antibody, consistent with the reported in situ data, the expression of Lhx5 was detected specifically in the CH at E11.5, and in the Cajal-Retzius cells in the marginal zone of the telencephalon. The same Lhx2 antibody, Santa Cruz, Cat # sc-19344, which has been used successfully in one of our previous studies (Tang et al., Development, 2012) (PMID: 22492355), was used in the present study. We believe that the observations at the MP and DP of the samples are really associated with the expression of Lhx2 protein. We performed new immunofluorescence assays with the new Lhx5 antibody and confirmed with the Lhx2 antibody. As shown in new Figure 5B, consistent with the downregulated expression of Lhx5 transcripts in the double mutant, the expression of the Lhx5 protein was reduced in the CH in the double mutants at E11.5; moreover, the numbers of Lhx5-positive Cajal-Retzius cells decreased in the double mutant embryos at E11.5, E13.5 and E14.5 (Figure 5Ba-d, a’-d’, a’’-d’’, i-l, i’-l’, q-t, q’-t’). Consistent with RT-qPCR data, the expression of Lhx2 was comparable between the control and double-mutant mice at E11.5 (Figure 5Be-h, e’-h’). Interestingly, the expression of the Lhx2 protein was increased in the hippocampal primordium in the COUP-TF double-mutant mice at E13.5 and E14.5 (Figure 5Bm-p, m’-p’, u-x, u’-x’). Please find the changed descriptions in Page 15, lines 347-351, 353-358 and Page 21, lines 500-503 in the revised manuscript.

      The reference:

      Tang, K., Rubenstein, J. L., Tsai, S. Y., & Tsai, M. J. (2012). COUP-TFII controls amygdala patterning by regulating neuropilin expression. Development, 139(9), 1630-1639. doi:10.1242/dev.075564

      2) The expression domain of RxCre remains poorly explained, and the early expression of COUPTFI and II (E10.5-E12.5) could be considered major weaknesses of the paper.

      Thanks for the suggestion. The generation of RXCre was reported by Swindell et al., Genesis, 2006 (PMID: 16850473). Given that the activation of the LacZ expression serves as an indicator for the deletion of the COUP-TFII gene (Tang et al., Development, 2012) (PMID: 22492355), we performed the immunofluorescent data with antibodies against COUP-TFII and LacZ on the sagittal sections of RXCre/+; COUP-TFIIF/+ heterozygous mutant and RXCre/+; COUP-TFIIF/F homozygous mice at E11.5. As shown in the new Figure 1—figure supplement 1Da-f, COUP-TFII was readily detected at the hippocampal primordium of the heterozygous mutant embryo at E11.5 (Figure 1—figure supplement 1Da, c, g); in contrast, the expression of COUP-TFII significantly decreased in the homozygous mutant (Figure 1—figure supplement 1Dd, f, j). In addition, compared with the heterozygous mutant embryo, the LacZ signals increased distinctly in the hippocampal primordium of the homozygous mutant embryo at E11.5 (Figure 1—figure supplement 1Db-c, e-f, h, k), suggesting that RXCre recombinase can efficiently excise the COUP-TFII gene in the hippocampal primordium as early as E11.5. Please find the corresponding changes in Page 7, lines 149-159 and Page 8, lines 160-164 in the revised manuscript.

      Meanwhile, we also added the early expression of COUP-TFI and -TFII at E10.5 and E11.5 in new Figure 1—figure supplement 1Aa-d. At embryonic days 10.5 (E10.5), COUP-TFI was detected in the dorsal pallium (DP) laterally and COUP-TFII was expressed in the MP and CH medially (Figure 1—figure supplement 1Aa, b). At E11.5, the expression of COUP-TFII remained in the hippocampal primordium, including MP and CH (Figure 1—figure supplement 1Ac, d). Please find the corresponding changes in Page 6, lines 129-132 and Page 9, lines 202-203 in the revised manuscript.

      The references:

      Swindell, E. C., Bailey, T. J., Loosli, F., Liu, C., Amaya-Manzanares, F., Mahon, K. A., . . . Jamrich, M. (2006). Rx-Cre, a tool for inactivation of gene expression in the developing retina. Genesis, 44(8), 361-363. doi:10.1002/dvg.20225

      Tang, K., Rubenstein, J. L., Tsai, S. Y., & Tsai, M. J. (2012). COUP-TFII controls amygdala patterning by regulating neuropilin expression. Development, 139(9), 1630-1639. doi:10.1242/dev.075564

      Reviewer #3 (Recommendations For The Authors):

      1) Regarding the RxCre line, I was also confused about its spatiotemporal expression, as this line is not a commonly used Cre line and no detailed description is provided in the manuscript. Searching this line shows a previous paper by the authors (PMID: 22492355) in which they tested the RxCre recombinase activity. At E12.5, RxCre induced high LacZ expression in the ventral telencephalon but much less in the dorsal telencephalon. But they did not check later stage. Therefore, it's hard to explain the defective dorsal hippocampus in RxCre, CFI CKO. They should check later stage.

      The generation of RXCre was reported by Swindell et al., Genesis, 2006 (PMID: 16850473), which reveals high Cre recombinase activity of RXCre in the eye and ventral telencephalon. Given that the activation of the LacZ expression serves as an indicator for the deletion of COUP-TFII gene, Tang et al., Development, 2012 (PMID: 22492355), we performed the immunofluorescent data with antibodies against COUP-TFII and LacZ on the sagittal sections of RXCre/+; COUP-TFIIF/+ heterozygous mutant and RXCre/+; COUP-TFIIF/F homozygous mice at E11.5. As shown in new Figure 1—figure supplement 1D, compared with the heterozygous mutant embryo, the expression of COUP-TFII was significantly decreased in the homozygous mutant; in addition, the LacZ signals evidently increased in the hippocampal primordium of the homozygous mutant embryo at E11.5, suggesting that RXCre recombinase can efficiently excise the target gene in the hippocampal primordium as early as E11.5. The expression of COUP-TFI is barely detectable in the early developing hippocampal primordium including MP at E10.5, E11.5 and E12.5. The expression of COUP-TFI is high in the MP of the control (Figure 1Cj, l); in contrast, the COUP-TFI expression is barely detectable in the MP of the homozygous double mutant at E14.5, indicating that RXCre can efficiently delete the COUP-TFI gene in the hippocampal primordium at E14.5. The loss of the COUP-TFI gene in the MP as early as E14.5 by RXCre initiates the defective dorsal hippocampus in RXCre/+; COUP-TFIF/F knockout mice.

      2) Authors should check and review extensively for improvements to the use of English.

      We carefully checked and made changes throughout the manuscript accordingly. For example, “imperative” was used 6 times in the previous manuscript, lines 20, 255, 486, 499, 522, 553; “imperative” was used only once in Page 22, line 522 in the revised manuscript.

      3) Please correct the manuscript; 1-month-old mice are not adult mice.

      Thanks for the suggestion. Based on the suggestion, we have corrected related words and sentences in the manuscript. Please find the amendments in the revised manuscript (Page 7, line 146; Page 9, lines 203-204; Page 10, line 213; Page 13, lines 299-300; Page 17, line 406; Page 20, line 476).

      4) Additional ref should be added at line 93 on page 5.

      Based on the suggestion, we added some new references (Bertacchi et al., EMBO J, 2020) (PMID: 32572460); (Del Pino et al., Cereb Cortex, 2020) (PMID: 32484994); (J. Feng et al., Sci Adv, 2021) (PMID: 34215582) at line 96 on page 5.

      The references:

      Bertacchi, M., Romano, A. L., Loubat, A., Tran Mau-Them, F., Willems, M., Faivre, L., . . . Studer, M. (2020). NR2F1 regulates regional progenitor dynamics in the mouse neocortex and cortical gyrification in BBSOAS patients. Embo j, 39(13), e104163. doi:10.15252/embj.2019104163

      Del Pino, I., Tocco, C., Magrinelli, E., Marcantoni, A., Ferraguto, C., Tomagra, G., . . . Studer, M. (2020). COUP-TFI/Nr2f1 Orchestrates Intrinsic Neuronal Activity during Development of the Somatosensory Cortex. Cereb Cortex, 30(11), 5667-5685. doi:10.1093/cercor/bhaa137

      Feng, J., Hsu, W. H., Patterson, D., Tseng, C. S., Hsing, H. W., Zhuang, Z. H., . . . Chou, S. J. (2021). COUP-TFI specifies the medial entorhinal cortex identity and induces differential cell adhesion to determine the integrity of its boundary with neocortex. Sci Adv, 7(27). doi:10.1126/sciadv.abf6808

      5) I am confused why the authors analyzed 1-month-old mice in some instances but 3-month-old mice in others.

      The RXCre/+; COUP-TFIF/F; COUP-TFIIF/F double mutant mice barely survived beyond postnatal 3 weeks. To make our findings consistent and comparable, we mainly prepared figures with observations on about 1-month-old mice in the RXCre related single or/and double gene mutant mouse models. In the study of the Emx1Cre related COUP-TFI mouse model, due to behavioral tests such as the Morris water maze test, experiments were performed with the adult experimental animal about postnatal 3 months. In order to be consistent with the stage of the mice for the behavioral tests, we only displayed morphological data with observations on the control and Emx1Cre/+; COUP-TFIF/F mutant mice at about postnatal 3-month.

    1. Robert Hutchins, former dean of Yale Law School (1927–1929), president (1929–1945) and chancellor (1945–1951) of the University of Chicago, closes his preface to his grand project with Mortimer J. Adler by giving pride of place to Adler's Syntopicon. It touches on the unreasonable value of building and maintaining a zettelkasten:

      But I would do less than justice to Mr. Adler's achievement if I left the matter there. The Syntopicon is, in addition to all this, and in addition to being a monument to the industry, devotion, and intelligence of Mr. Adler and his staff, a step forward in the thought of the West. It indicates where we are: where the agreements and disagreements lie; where the problems are; where the work has to be done. It thus helps to keep us from wasting our time through misunderstanding and points to the issues that must be attacked. When the history of the intellectual life of this century is written, the Syntopicon will be regarded as one of the landmarks in it. —Robert M. Hutchins, p xxvi The Great Conversation: The Substance of a Liberal Education. 1952.

      Adler's Syntopicon has been briefly discussed in the forum.zettelkasten.de space before. However it isn't just an index compiled into two books which were volumes 2 and 3 of The Great Books of the Western World, it's physically a topically indexed card index or a grand zettelkasten surveying Western culture. Its value to readers and users is immeasurable and it stands as a fascinating example of what a well-constructed card index might allow one to do even when they don't have their own yet. For those who have only seen the Syntopicon in book form, you might better appreciate pictures of it in slipbox form prior to being published as two books covering 2,428 pages:

      Two page spread of Life Magazine article with the title "The 102 Great Ideas" featuring a photo of 26 people behind 102 card index boxes with categorized topical labels from "Angel" to "Will".

      Mortimer J. Adler holding a pipe in his left hand and mouth posing in front of dozens of boxes of index cards with topic headwords including "law", "love", "life", "sin", "art", "democracy", "citizen", "fate", etc.

      Adler spoke of practicing syntopical reading, but anyone who compiles their own card index (in either analog or digital form) will realize the ultimate value in creating their own syntopical writing or what Robert Hutchins calls participating in "The Great Conversation" across twenty-five centuries of documented human communication. Adler's version may not have had the internal structure of Luhmann's zettelkasten, but it definitely served similar sorts of purposes for those who worked on it and published from it.

      References

      syndication link: https://forum.zettelkasten.de/discussion/2623/mortimer-j-adlers-syntopicon-a-topically-arranged-collaborative-slipbox/

    1. But I would do less than justice to Mr. Adler's achieve-ment if I left the matter there. The Syntopicon is, in additionto all this, and in addition to being a monument to the indus-try, devotion, and intelligence of Mr. Adler and his staff, astep forward in the thought of the West. It indicates wherewe are: where the agreements and disagreements lie; wherethe problems are; where the work has to be done. It thushelps to keep us from wasting our time through misunder-standing and points to the issues that must be attacked.When the history of the intellectual life of this century iswritten, the Syntopicon will be regarded as one of the land-marks in it.

      p xxvi

      Hutchins closes his preface to his grand project with Mortimer J. Adler by giving pride of place to Adler's Syntopicon.

      Adler's Syntopicon isn't just an index compiled into two books which were volumes 2 and 3 of The Great Books of the Western World, it's physically a topically indexed card index of data (a grand zettelkasten surveying Western culture if you will). It's value to readers and users is immeasurable and it stands as a fascinating example of what a well-constructed card index might allow one to do even when they don't have their own yet.

      Adler spoke of practicing syntopical reading, but anyone who compiles their own card index (in either analog or digital form) will realize the ultimate value in creating their own syntopical writing or what Robert Hutchins calls participating in "The Great Conversation" across twenty-five centuries of documented human communication.

      See also: https://hypothes.is/a/WF4THtUNEe2dZTdlQCbmXw


      The way Hutchins presents the idea of "Adler's achievement" here seems to indicate that Hutchins didn't have a direct hand in compiling or working on it directly.

    1. Now, I don’t know if it was Mr. G’s master plan or just a happy little accident, but much of my shop class group also studied physics and chemistry. Mr. G used the concepts we learned about everyday life

      Sometimes, it's important to realize that life isn't always going to be predictable, and that random chance is going to be a factor as well. While it is still best to make an effort to connect with others either way, sometimes you just don't always get the kinds of people that you want to work with.

    1. Collectieve digitale ruime

      Some overall comments. I think this collection of ideas is great. We have discussed a lot of these in the past few encounters but as an article, at the moment, it lacks cohesion. It comes across as aimless, too broad, it's quite ambitious but the result doesn't match the ambition.

      I'd advise you to stick what you yourself just mentioned in the Signal group: "confused on how to tell the story... how to get across that a. collective digital ownership is a thing and b. that it matters."

      I think if you can do that 1-2 punch in the first page, the rest of the space you can leave as spaces for illustration.

      I think you do not need to explain the technology or go into the metaphor of the layers, the deeper you go into that cake of the layers the more trouble and confusion you get yourself into (like I could run an autonomous collective space at the hosting layer, but I could never write an OS from scratch... is my collective autonomous?)

      To run a collective not all those layers need to be collective owned or collective produced. Talking about those layers adds confusion.

      I do see why you do it though, it is tempting to try to cover that, but it's patronising and unproductive in this context I think.

    1. Reviewer #1 (Public Review):

      This is my first review of the article entitled "The canonical stopping network: Revisiting the role of the subcortex in response inhibition" by Isherwood and colleagues. This study is one in a series of excellent papers by the Forstmann group focusing on the ability of fMRI to reliably detect activity in small subcortical nuclei - in this case, specifically those purportedly involved in the hyper- and indirect inhibitory basal ganglia pathways. I have been very fond of this work for a long time, beginning with the demonstration of De Hollander, Forstmann et al. (HBM 2017) of the fact that 3T fMRI imaging (as well as many 7T imaging sequences) do not afford sufficient signal to noise ratio to reliably image these small subcortical nuclei. This work has done a lot to reshape my view of seminal past studies of subcortical activity during inhibitory control, including some that have several thousand citations.

      In the current study, the authors compiled five datasets that aimed to investigate neural activity associated with stopping an already initiated action, as operationalized in the classic stop-signal paradigm. Three of these datasets are taken from their own 7T investigations, and two are datasets from the Poldrack group, which used 3T fMRI.

      The authors make six chief points:<br /> 1. There does not seem to be a measurable BOLD response in the purportedly critical subcortical areas in contrasts of successful stopping (SS) vs. going (GO), neither across datasets nor within each individual dataset. This includes the STN but also any other areas of the indirect and hyperdirect pathways.<br /> 2. The failed-stop (FS) vs. GO contrast is the only contrast showing substantial differences in those nodes.<br /> 3. The positive findings of STN (and other subcortical) activation during the SS vs. GO contrast could be due to the usage of inappropriate smoothing kernels.<br /> 4. The study demonstrates the utility of aggregating publicly available fMRI data from similar cognitive tasks.<br /> 5. From the abstract: "The findings challenge previous functional magnetic resonance (fMRI) of the stop-signal task"<br /> 6. and further: "suggest the need to ascribe a separate function to these networks."

      I strongly and emphatically agree with points 1-5. However, I vehemently disagree with point 6, which appears to be the main thrust of the current paper, based on the discussion, abstract, and - not least - the title.

      To me, this paper essentially shows that fMRI is ill-suited to study the subcortex in the specific context of the stop-signal task. That is not just because of the issues of subcortical small-volume SNR (the main topic of this and related works by this outstanding group), but also because of its limited temporal resolution (which is unacknowledged, but especially impactful in the context of the stop-signal task). I'll expand on what I mean in the following.

      First, the authors are underrepresenting the non-fMRI evidence in favor of the involvement of the subthalamic nucleus (STN) and the basal ganglia more generally in stopping actions.<br /> - There are many more intracranial local field potential recording studies that show increased STN LFP (or even single-unit) activity in the SS vs. FS and SS vs. GO contrast than listed, which come from at least seven different labs. Here's a (likely non-exhaustive) list of studies that come to mind:<br /> o Ray et al., NeuroImage 2012<br /> o Alegre et al., Experimental Brain Research 2013<br /> o Benis et al., NeuroImage 2014<br /> o Wessel et al., Movement Disorders 2016<br /> o Benis et al., Cortex 2016<br /> o Fischer et al., eLife 2017<br /> o Ghahremani et al., Brain and Language 2018<br /> o Chen et al., Neuron 2020<br /> o Mosher et al., Neuron 2021<br /> o Diesburg et al., eLife 2021<br /> - Similarly, there is much more evidence than cited that causally influencing STN via deep-brain stimulation also influences action-stopping. Again, the following list is probably incomplete:<br /> o Van den Wildenberg et al., JoCN 2006<br /> o Ray et al., Neuropsychologia 2009<br /> o Hershey et al., Brain 2010<br /> o Swann et al., JNeuro 2011<br /> o Mirabella et al., Cerebral Cortex 2012<br /> o Obeso et al., Exp. Brain Res. 2013<br /> o Georgiev et al., Exp Br Res 2016<br /> o Lofredi et al., Brain 2021<br /> o van den Wildenberg et al, Behav Brain Res 2021<br /> o Wessel et al., Current Biology 2022<br /> - Moreover, evidence from non-human animals similarly suggests critical STN involvement in action stopping, e.g.:<br /> o Eagle et al., Cerebral Cortex 2008<br /> o Schmidt et al., Nature Neuroscience 2013<br /> o Fife et al., eLife 2017<br /> o Anderson et al., Brain Res 2020

      Together, studies like these provide either causal evidence for STN involvement via direct electrical stimulation of the nucleus or provide direct recordings of its local field potential activity during stopping. This is not to mention the extensive evidence for the involvement of the STN - and the indirect and hyperdirect pathways in general - in motor inhibition more broadly, perhaps best illustrated by their damage leading to (hemi)ballism.

      Hence, I cannot agree with the idea that the current set of findings "suggest the need to ascribe a separate function to these networks", as suggested in the abstract and further explicated in the discussion of the current paper. For this to be the case, we would need to disregard more than a decade's worth of direct recording studies of the STN in favor of a remote measurement of the BOLD response using (provably) sub ideal imaging parameters. There are myriads of explanations of why fMRI may not be able to reveal a potential ground-truth difference in STN activity between the SS and FS/GO conditions, beginning with the simple proposition that it may not afford sufficient SNR, or that perhaps subcortical BOLD is not tightly related to the type of neurophysiological activity that distinguishes these conditions (in the purported case of the stop-signal task, specifically the beta band). But essentially, this paper shows that a specific lens into subcortical activity is likely broken, but then also suggests dismissing existing evidence from superior lenses in favor of the findings from the 'broken' lens. That doesn't make much sense to me.

      Second, there is actually another substantial reason why fMRI may indeed be unsuitable to study STN activity, specifically in the stop-signal paradigm: its limited time resolution. The sequence of subcortical processes on each specific trial type in the stop-signal task is purportedly as follows: at baseline, the basal ganglia exert inhibition on the motor system. During motor initiation, this inhibition is lifted via direct pathway innervation. This is when the three trial types start diverging. When actions then have to be rapidly cancelled (SS and FS), cortical regions signal to STN via the hyperdirect pathway that inhibition has to be rapidly reinstated (see Chen, Starr et al., Neuron 2020 for direct evidence for such a monosynaptic hyperdirect pathway, the speed of which directly predicts SSRT). Hence, inhibition is reinstated (too late in the case of FS trials, but early enough in SS trials, see recordings from the BG in Schmidt, Berke et al., Nature Neuroscience 2013; and Diesburg, Wessel et al., eLife 2021).<br /> Hence, according to this prevailing model, all three trial types involve a sequence of STN activation (initial inhibition), STN deactivation (disinhibition during GO), and STN reactivation (reinstantiation of inhibition during the response via the hyperdirect pathway on SS/FS trials, reinstantiation of inhibition via the indirect pathway after the response on GO trials). What distinguishes the trial types during this period is chiefly the relative timing of the inhibitory process (earliest on SS trials, slightly later on FS trials, latest on GO trials). However, these temporal differences play out on a level of hundreds of milliseconds, and in all three cases, processing concludes well under a second overall. To fMRI, given its limited time resolution, these activations are bound to look quite similar.

      Lastly, further building on this logic, it's not surprising that FS trials yield increased activity compared to SS and GO trials. That's because FS trials are errors, which are known to activate the STN (Cavanagh et al., JoCN 2014; Siegert et al. Cortex 2014) and afford additional inhibition of the motor system after their occurrence (Guan et al., JNeuro 2022). Again, fMRI will likely conflate this activity with the abovementioned sequence, resulting in a summation of activity and the highest level of BOLD for FS trials.

      In sum, I believe this study has a lot of merit in demonstrating that fMRI is ill-suited to study the subcortex during the SST, but I cannot agree that it warrants any reappreciation of the subcortex's role in stopping, which are not chiefly based on fMRI evidence.

      A few other points:<br /> - As I said before, this team's previous work has done a lot to convince me that 3T fMRI is unsuitable to study the STN. As such, it would have been nice to see a combination of the subsamples of the study that DID use imaging protocols and field strengths suitable to actually study this node. This is especially true since the second 3T sample (and arguably, the Isherwood_7T sample) does not afford a lot of trials per subject, to begin with.<br /> - What was the GLM analysis time-locked to on SS and FS trials? The stop-signal or the GO-signal?<br /> - Why was SSRT calculated using the outdated mean method?<br /> - The authors chose 3.1 as a z-score to "ensure conservatism", but since they are essentially trying to prove the null hypothesis that there is no increased STN activity on SS trials, I would suggest erring on the side of a more lenient threshold to avoid type-2 error.<br /> - The authors state that "The results presented here add to a growing literature exposing inconsistencies in our understanding of the networks underlying successful response inhibition". It would be helpful if the authors cited these studies and what those inconsistencies are.

    1. Set up the Standard Ebooks toolset

      The "Standard Ebooks toolset" should just be... an ebook. That your browser can execute. (Because it's a ubiquitous runtime target that requires no setup...)

    1. Bollinger bands are just a simple visualization/analysis technique that creates two bands, one "roof" and one "floor" of some "support" for a given time series. The reasoning is that, if the time series is "below" the "floor", it's a historic low, and if it's "above" the "roof", it's a historic high. In terms of stock prices and other financial instruments, when the price crosses a band, it's said to be too cheap or too expensive.

      How to display Bollinger bands with Pandas.

    1. there's one glaring problem here 00:05:11 with creating this animal-free meat it's not actually animal-free that special fbs serum i just mentioned that stands for fetal bovine serum which is collected from the dying fetuses of 00:05:25 slaughtered cows
      • potential progress trap
        • FBS
          • Fetal Bovine Serum
      • This is used for the growth of all kinds of stem cells, not just those from cows

        • We do not know the full implications of mixing FBS from cows with all other species
      • Question

        • What are the views of the regulatory agencies that have passed Lab grown meat on this subject?
    1. Reviewer #4 (Public Review):

      Berger et al. 2023a argues that Homo naledi intentionally buried their dead within the Rising Star cave system by digging pits and covering the bodies with infilled sediment. The authors identified two burials: Dinaledi Feature 1 from the Dinaledi Chamber, and the Hill Antechamber Feature from the Hill Antechamber. The evolutionary and behavioral implications for such behavior are highly significant and would be the first instance of a relatively small-brained hominin engaging is complex behavior that is often found in association with Homo sapiens and Homo neanderthalensis. Thus, the scientific rigor to validate these findings should be of the highest quality, and thus, provide clear documentation of intentional burial. In an attempt to meet these standards, the authors stated a series of tests that would support their hypothesis of intentional burials in the Rising Star Cave system:

      "The key observations are (1) the difference in sediment composition within the feature compared to surrounding sediment; (2) the disruption of stratigraphy; (3) the anatomical coherence of the skeletal remains; (4) the matrix-supported position of some skeletal elements; and (5) the compatibility of non-articulated material with decomposition and subsequent collapse." (page 5)

      To find support for the first (1) test, the authors collected sediment samples from various locations within the Rising Star Cave system, including sediment from within and outside Dinaledi Feature 1. However:

      • The authors did not select sediment samples from within the Hill Antechamber Feature, so this test was only used to assess Dinaledi Feature 1.

      • The sediment samples were analyzed using x-ray diffraction (XRD) and x-ray fluorescence (XRF) to test the mineralogy and chemistry of the samples from within and outside the feature. The XRF results were presented as weighted percentages (not intensities) with no control source reported. The weighted percentages were analyzed using a principal components analysis (PCA) while the particle-size distribution was analyzed using GRADISTAT statistics package and the Folk and Ward Method to summarize "mean grain size, sorting, skewness and kurtosis in addition to the percentages of clay, silt and sand in each sample." (page 28).

      • The PCA results were reported solely as a biplot without showing the PC scores projected into the loading space, which is unusual and does not present the data accurately. Instead, the authors present the scores of a single component (PC2, figure 3) because the authors interpreted this component as "distinctly delineates fossil-bearing sediments from sterile sediments based on the positive loadings of P and S" (Page 6). However, the supplementary table that reports XRF bulk chemistry results as a weighted percentage of minerals within each sample (SI Table 1) shows mostly an absence of data for both Na and S. Since Na is at the lower end of detection limits for the method, and S seems to just be absent from the list, the intentions of the authors for showing the inclusion of these elements in their PCA results is unclear. Given that this is the author's primary method for demonstrating a burial, this issue is particularly concerning and requires additional attention.

      • Regardless of the missing data, this reviewer attempted to replicate the XRF PCA results using the data provided in SI Table 1 and was unsuccessful. The samples that were collected from within the feature (SB) cluster with samples collected from sterile sediments and other locations around the cave system. Thus, these results are not replicable as currently reported.

      • Visual comparisons of sediment grain size, shape, and composition were qualitatively summarized. Grain size was plotted as a line graph and is buried as supplemental Figure S13 showing sample by color and area, but these results do not distinguish samples from WITHIN the burial compared to OUTSIDE the burial as the authors state in the methods as a primary goal.

      To test the second (2) aim, the "stratigraphy" was primarily described in text.

      • For Dinaledi Feature 1, the authors state that the layer around Feature 1 "is continuous in the profile immediately to the east of the feature; it is disrupted in the sediment profile at the southern extent of the feature (fig. 3b)." Upon examination of figure 3b, the image shows an incredibly small depiction of the south (?) profile view with an extremely large black box overlaying a large portion of the photograph containing a small 5 cm scale. Visually, there is no difference in the profile that would suggest a disruption in the form of a pit. The LORM (orange-red mud layer) does seem to become fragmentary, but no micromorphological analysis was conducted on this section to provide an evaluation of stratigraphic composition. Also, by only excavating a portion of the feature, the authors were unable to adequately demonstrate the full extent of this feature.

      • The authors attempt to describe "a bowl-shaped concave layer of clasts and sediment-free voids make up the bottom of the feature" (page 13) and refer to figures and supplementary information that do not depict any stratigraphic profile. Moreover, the authors state that "the leg, foot, and adjacent [skeletal?] material cut across stratigraphy" indicating that the skeleton is orientated on a flat plane against the surrounding stratigraphy that is "30{degree sign} slope of floor and underlying strata" (page 51, fig. 10c captions). There is no mention of infilled sediment from a pit and how this relates to the skeleton or the slope of the floor. It is therefore extremely unclear what the authors are meaning to describe without any visual or micromorphological supplementation to demonstrate a "bowl-shaped concave layer".

      The third (3) test was to evaluate the anatomical coherence of the skeletal remains using macro- and micro-CT (computed tomography) of the Hill Antechamber Feature that was removed during excavation. To visually assess the anatomy of the Dinaledi Feature 1 burial, the authors describe the spatial relationship of skeletal elements as they were being excavated but halted partway through the excavation.

      • The authors do not provide any documentation (piece-plotting, 3D rendering of stages of excavation, etc.) of the elements that were removed from the Dinaledi Feature. Figure 4 and SI Fig. S22 show the spatial relationship between identifiable skeletal elements that remain in the Feature. However, in Fig. 4, it is unclear why the authors chose to plot 2023-2014 excavated material along with material reported here, and it's even more difficult to understand the anatomical positioning of the elements given their color and point size choices. Although, the authors do provide a 3D rendering of the unexcavated remains showing some skeletal cohesion, apart from the mandible and teeth being re-located near the pelvis (Fig. 9). That said, it is very difficult to visually confirm the elements from this model or understand the original placement of the skeleton.

      • 3D renderings of the Hill Antechamber feature skeletal material is clearly shown in SI Fig. S26. Contrary to what the authors state in text, there is a rather wide dispersal and rearrangement of elements for a "burial" that is theoretically protected from scavengers and other agents that would aid in dispersing bone from the surface. The authors do not offer any alternatives to explain disturbance, such as human activity, which clearly took place.

      • Moreover, there does not appear to be any intentional arrangement of limbs that may suggest symbolic orientation of the dead (another line of evidence often used to support intentional burial but omitted by the authors). Thus, skeletal cohesion is not enough evidence to support the hypothesis of an intentional burial.

      The fourth (4) test was attempted by evaluating whether some elements were vertically aligned from 3D reconstructed models of Hill Antechamber Feature and a photogrammetric model of the Dinaledi Feature 1. The authors state that "the spatial arrangement of the skeletal remains is consistent with primary burial of the fleshed body" (page 8 in reference to Dinaledi Feature 1) without providing any evidence, qualitative or quantitative, that this is the case for either burial.

      Since this reviewer was unable to understand the fifth (5) test as it was written by the authors, I am unable to comment on the evidence to support this test and will default to the other reviewers for evaluation of this claim.

      In addition to a lack of evidence to support the claims of intentional burial, this paper was also written extremely poorly. For example, the authors often overused 'persuasive communication devices' (see eLife article, https://elifesciences.org/articles/88654) to mislead readers:

      "During this excavation, we recognized that the developing evidence was suggestive of a burial, due to the spatial configuration of the feature and the evidence that the excavated material seemed to come from a single body." (page 5)

      As an opening statement to introduce Dinaledi Feature 1, the authors state the interpretation and working hypothesis as fact before the authors present any evidence. This is known as "HARKing" and "gives the impression that a hypothesis was formulated before data were collected" (Corneille et al. 2023). This type of writing is pervasive throughout the manuscript and requires extensive editing. I recommend that the authors review the article provided by eLife (https://elifesciences.org/articles/88654) and carefully review the manuscript. Moreover, as this text demonstrates, the authors’ word choice is indicative of storytelling for a popular news article instead of a scientific paper. I highly suggest that the authors review the manuscript carefully and present the data prior to giving conclusions in a clear and concise manner.

      Moreover, the writing structure is inconsistent. Information that should be included in results is included in the methods, text in the results should be in discussions, and so forth. This inconsistency is pervasive throughout the entire manuscript, making it incredibly difficult to adequately understand what the authors had done and how the results were interpreted.

      Finally, the "artifact" that was described and visualized using CT models is just that - a digitally colored model. The object in question has not been analyzed. Until this object is removed from the dirt and physically analyzed, this information needs to be removed from the manuscript as there is nothing to report before the object is physically examined.

      Overall, there is not enough evidence to support the claim that Homo naledi intentionally buried their dead inside the Rising Star Cave system. Unfortunately, the manuscript in its current condition is deemed incomplete and inadequate, and should not be viewed as finalized scholarship.

    1. Rails' default approach to log everything is great during development, it's terrible when running it in production. It pretty much renders Rails logs useless to me.

      Really? I find it even more annoying in development, where I do most of my log viewing. In production, since I can't as easily just reproduce the request that just happened, I need more detail, not less, so that I have enough clues about how to reproduce and what went wrong.

    1. A chatbot might have a lot to say about Chaucer, but it's only what others have written. It's a good start, one that might prompt you to consider new ideas, but ultimately it's up to you to process that information, form your own thoughts, and communicate in your own words.

      Even though Chat GPT can write essays, it does not create thoughts and ideas. It just collects data from a wide range of resources. Therefore, the outcomes are basically someone else’s ideas. Also, people Should keep their imaginations active because no matter how large the Chat GPT’s databases are, it will end if there are no new feeds over the years. In other words, the outcomes will be repeated information that lacks creativity.

    1. we're beginning to demonstrate is that actually contrary to our perceptions Consciousness does not become annihilated just because a person has just died and in fact Consciousness 00:04:49 appears to continue at least in the first period the early period of death the first minutes or hours after death
      • claim with evidence

        • Consciousness does not become annihilated just because a person has just died
        • Consciousness appears to continue at least in the first period the early period of death the first minutes or hours after death
        • Explanation
          • death is a biological process
          • when you stop blood flow to brain cells they undergo certain changes and will eventually become damaged
          • however the first thing that happens is that you stop oxygen delivery to the areas inside the core of the brain that modulate your sense of being awake and alert
          • the reticulate activating system various other parts and so it's very similar to the effect of giving a general anesthetics to somebody
          • if you give a high enough dose of general anesthetic to a patient or person then you basically shut down those areas of the brain
          • the person's consciousness looks like it's lost
          • it flips out of sight but we wouldn't say that person's Consciousness has become annihilated forever
          • we just realize it's gone temporarily and so when people first die what's happening is that oxygen is stopping to those parts of the brain and it's essentially taking Consciousness out of you and making it disappear but it doesn't necessarily disappear Forever
      • comment

        • could this be the reason in Tibetan Buddhism, there is the Thukdam meditation practice as well as dream yoga practice?
    1. You can tell people just like I have you to focus their attention, choose a target. Imagine there's a spotlight shining just on it. Don't pay much attention to what's in your periphery almost as if you have like blinders on, right? So don't pay attention to those distractors. People can do that. We have them talk to us about like, well, what is it that you're focused on? What's catching your attention right now? Those are easy instructions to understand and it's easy to make your eyes do it. What's important though is that that's not what their eyes do naturally. When they're walking or when they're running, people do take a sort of wider perspective. They broaden their scope of attention relative to what these instructions are having them do. And when we taught people that narrowed style of attention, what we found is that they moved 23% faster in this course that we had set up. From the start line to the finish line, it was always exactly the same distance. And we were using our stop watches to see how fast did they move. They moved 23% faster and they said it hurt 17% less. Right? So exactly the same actual experience, but subjectively it was easier and they performed better. They increase the efficiency of this particular exercise.

      (24:58) In order to perform significantly better, you need to FOCUS your attention on a single thing only. Multitasking won't work, and thinking about different things at once also doesn't work. Set up your environment to foster this insane level of focus.

    2. Those distances literally look farther to people that for whom it might be harder to make it to that finish line, to navigate that space. We also found that that's the case with motivation, that when people are more motivated to exercise or to make it to that finish line, that motivation can in a sense compensate for that effect of their body on their perception of distance. So that even highly motivated people, people who are highly motivated, even if they have a higher waist to hip ratio might see the distance in a way that suggests it's just as short as people who have a lower waist to hip ratio. So motivation can change our visual experience and align people to experience a world that looks more like a person who'd have an easier time navigating it. So those were two initial findings, sets of findings, that suggested our visual experiences are not just reflective of the world that's out there. But instead it has to do with what is our body capable of doing and what is our brain capable of supplementing, our own motivational states and physical states of our body are working together to shift what it is that we're seeing in the world out there.

      (21:47) There is a clear relation between the body and the brain and they influence each other, at least in terms of perception with regards to motivation.

    1. Miracles transcend the body.

      Let us perform a thought experiment: imagine your reactions if you hear that wildfires have destroyed your house. Compare it to another made up news that now your enemy has burned your house. And let's imagine also how we'd react on hearing that our kids were playing, gone too far and burned our house.

      Most likely if it were our kids our first intent would be to help them first and calm them down, neglecting all that happened to the house. While wildfires could have set us on the victim's mode to start complaining on some gods, the government and generally on bad luck. And if it were our enemy, oh boy, we could have gone to a crusade in courts... to say the last.

      There is a phrase in English, that comes from most unlikely area for spiritual seekers, and it goes: "It's nothing personal, just business". What if we could unplug events from personalities and take events as winds, as an unfoldment of our hidden conciseness in dreams. What if we looked at others as merely actors, who are playing sad or vicious roles not because it's what they really are.

      The focus on a body is judgment's first initial step. Remove the pieces off the board, look past all bodies and ask to realize the truth; for it isn't personal, just karma.

      As the ‪‎ego‬ would limit your perception of your brothers to the body, so would the ‪Holy Spirit‬ release your vision and let you see the Great Rays shining from them, so unlimited that they reach to ‪‎God‬. T-15.9.1

      The purpose of the world you see is to obscure your function of forgiveness, and provide you with a justification for forgetting it. W-64.1.2

      ...forgiveness looks past bodies. This is its holiness; this is how it heals. The world of bodies is the world of sin, for only if there were a body is sin possible ... Only the body makes the world seem real. C-4.5

    2. There is no order of difficulty in miracles. One is not "harder" or "bigger" than another.

      ACIM begins by stating some of it's concepts that are most difficult to grasp and so they will remain unknown to you for quite awhile. Don't push it, don't try to squeeze the meaning from it but allow it to surprise you and to reveal itself for you instead.

      The guiding rope for you to navigate this section is understanding: miracles are not some magic tricks. Behind the word a "miracle" hides mental process of shifting your perception and the tool to make it happen is forgiveness, although the way this book is looking at "for giving" is not what you may think of it right now.

      In swapping "miracles" -- "forgiveness" confusion goes away. An act of genuine forgiveness is meant to be applied to every thing that blows your peace, from major accidents to seeming little things like unwashed dishes or just cold outside.

      When you maintain that there must be an order of difficulty in miracles, all you mean is that there are some things you would withhold from truth. T-17.1.3

      And yet mistakes, regardless of their form, can be corrected. Sin is but error in a special form the ego venerates. It would preserve all errors and make them sins. T-22-3.4

      It is not easier to forgive one sin than to forgive all of them. The illusion of orders of difficulty is an obstacle the teacher of God must learn to pass by and leave behind. M-14.3

      The miracle forgives; the ego damns. Neither need be defined except by this. C-2.10

      Forgiveness is the key to happiness. W-121

    3. Principles of Miracles

      Please do not take these notes as my attempt at teaching you the Course, look at it rather as (hopefully!) the Holy Spirit's answers to my own struggles with the book.

      The focus here is on the piece entitled "Principles of Miracles" because I still remember how confusing and overall unreadable it felt, despite the fact that it's the very intro to the Text. I later realized that all these short yet powerful one-liners are reminiscent to the quotes of Jesus compiled together in the Bible under the so called Sermon on the Mount. And so although the Principles are minimal in form, they all reflect the foundations of The Holy Spirit's thinking framework presented in this Course and that allowed historic Jesus to reach Enlightenment and see no threat nor value in this world.

      This is what now I understand, but back in the beginning of my study I just kept asking Holy Spirit to unfold the meaning of these lines because I had been thinking: if I can't understand and put together in my mind the very first few pages of the book, how can I dare to read it on? Hoping that the answers I received could be of help to more than only me, these notes are offered.

      If you are interested in hearing more about my personal experiences with this, please consider visiting this channel on youtube.


      The goal of any journey has to be determined right at the beginning or else you wander idly as a leaf in winds. Consider carefully now: why did you take this book? You've read a lot of other books, you have been listening to many gurus, you even might belong to a religion of some sort, and yet you're here and reading this. Inquire: why?

      There is a splinter in your mind that fuels your strangeness, it does not allow you to just settle down and "live a normal life". But what's the goal of this desire? What is it that this splinter wants? The only reason that could motivate you to pick up this giant brick of paper and at least imagine taking in its yearly course is very simple: you are deeply disappointed and unsatisfied. All of those books and gurus didn't work for you, as well as many other things that you have tried in "normal life", but something deep in you continues striving forward refusing to give up, it looks for something so majestic that nothing is compared to that. Before you say this strive is meaningless and never could be reached, let me invite a simple question: what if the splinter's goal is happiness? Is this too much to ask?

      This course is a unique and self-sustained instruction for guiding you to happiness and it requires not from you to have a background in any other system of a thought. In fact, you'll do yourself a major favor if you would drop all that you've grasped before - those books and gurus failed you, hold on to it no more. Don't try to fit this course in well known patterns, accept the fact you need a teacher and open up your mind abroad. There is no stamp and sign on paper, no court supported guarantee this course is genuine, but if you follow it you'll get experience and only this can ever make you sure.

      If happiness is your desire but you do not abide in joy, then it is logical to figure: you must be doing something wrong. Depression, fear, anxiety are rather more familiar to you and so it follows that your habits and your entire thinking framework is dedicated heavily to those. There is a saying that to get a thing you never had, you gotta do what never tried. Another quote asserts: in goodness you are asked to bite the poison and after that the honey flows, while ignorance is giving you the honey barrel, but when you bite it - poison flows. To sum it up, you must be ready for a challenge, because ACIM is going to disturb, you will resist against what it is asking you and yet what if behind of your resistance is the key that's gonna make at last all of the difference in the world?

      Your past learning must have taught you the wrong things, simply because it has not made you happy. On this basis alone its value should be questioned. T-8.1.4

      You who are steadfastly devoted to misery must first recognize that you are miserable and not happy. The Holy Spirit cannot teach without this contrast, for you believe that misery is happiness. T-14.2.1

      Resign now as your own teacher. T-12.5.8

      Remember nothing that you taught yourself, for you were badly taught. T-28.1.7

      you are studying a unified thought system in which nothing is lacking that is needed, and nothing is included that is contradictory or irrelevant. W-42.7

      To learn this course requires willingness to question every value that you hold.T-24-in.2

      If you are willing to renounce the role of guardian of your thought system and open it to me, I will correct it very gently and lead you back to God. T-4.1.4

      God's Will for you is perfect happiness ... You are indeed essential to God's plan. Without your joy, His joy is incomplete. Without your smile, the world cannot be saved. W-100.2,3

    1. CPB vs Reading Notes .t3_14li1ri._2FCtq-QzlfuN-SwVMUZMM3 { --postTitle-VisitedLinkColor: #9b9b9b; --postTitleLink-VisitedLinkColor: #9b9b9b; --postBodyLink-VisitedLinkColor: #989898; } Does anyone separate their reading notes from their common place Notebook? I’ve always used a notebook to combine my Bullet Journal, reading notes, and Common Place. It’s been a mesh of words and I’ve been ok w that, but I just got the Remarkable 2 and I’m trying to figure out how to set it up. Any ideas?

      reply to u/Nil205 at https://www.reddit.com/r/commonplacebook/comments/14li1ri/cpb_vs_reading_notes/

      I have a similar and differently formed, but still simple system compared to most here. Rather than a traditional commonplace book, I keep all my notes on index cards. I keep all my reading notes for a particular book on a series of index cards that I staple together with a citation card for the book and then file them by author and title.

      When I'm done, I'll excerpt the most important parts each individual note (highlight/annotation) and expand on them on its own index card which I file away and index. In your case you might equivalently have a reading notebook where you might keep a section of notes as you read a book and then excerpt the most important or salient parts into your main commonplace. Some may prefer, especially if they own the book in question, to annotate (put their reading notes into) the book directly and then excerpt either as they go or at the end when they're done and can frame their ideas with a broader knowledge of the area in question. Sometimes at later dates you may realize you read something useful which you don't find in your commonplace book, but you can find the gist of it in your reading notes which you can reference, refresh your memory, and then excerpt into your commonplace.

      For more on my sort of card index or zettelkasten (German: slip box) practice you might take a look at one or more of the following which explain the broad generalities:

      If it's useful/inspiring as an example, Ross Ashby had a lifelong series of notebooks, much like a commonplace, and a separate card index where he cross-indexed all of his ideas to make them more easily searchable, findable, and cross referenceable. You can see digitized versions of the journals and index online which you can explore at http://www.rossashby.info/journal/index.html.

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Reviewer #1* (Evidence, reproducibility and clarity (Required)): *

      * Srinivasan et al. present a comprehensive study on systematizing the structure-dynamics-function relation of lipid transfer proteins (LTPs), combining extensive molecular simulations and complementary experiments. Indeed, the current state-of-the-art in the field is quite chaotic and fractional, and such systematic studies are necessary to advance our general and conceptual understanding of the mechanisms of action of LTPs. The selected techniques and research strategies are all suitable, their description is sufficient and enables reproducibility; the obtained results are carefully presented and discussed; the conclusions are adequately supported by the data.

      Given my primarily computational background, I evaluated mainly the simulation part of the manuscript. Considering experiments, I do not see any significant flows or deficiencies that could diminish the value of the data and following conclusions given in the manuscript. I would even suggest improving the abstract by more explicitly saying that this work includes experimental measurements because it currently reads like purely computational work was performed. *

      We thank Reviewer #1 for the positive evaluation of our work. The abstract has now been updated to include that our work allows us to interpret existing data but also to design and perform new experimental measurements.

      * Major comments: *

      1) Although I like the central message of the paper and have no objections, I am curious whether the conclusion "a more "dynamic" or/and "mobile" part of the protein interacts with the membrane or any other (macro)(bio)molecule" makes sense globally and is not limited to LTPs. For example, it is a reasonable assumption that a more flexible part of the protein, i.e., capable of adopting necessary binding configurations, would be a more likely interacting spot. Locking in a less flexible and more specific configuration upon binding with a target molecule is also anticipated and quite typical, e.g., when ligands interact with target proteins, thereby blocking their function. The authors themselves recognize this paradigm as referring to the enzymes' dynamics. It would be great if authors could comment more on dynamics-function relation, referring to the existing literature, where such observations were/were not observed for different protein families. Performing simulations on proteins that do not exhibit such a feature and do not belong to LTPs, but, e.g., structurally similar to some of the studied LTPs, would be an excellent addition too, highlighting this signature characteristic of LTPs.

      We have now added a discussion comparing the mechanism we observe with those described for other proteins such as membrane transporters and receptors. Since those proteins are very different and have been already thoroughly characterized (including with molecular simulations) we don’t think that additional simulations are required. Also, concerning protein binding dynamics, we refer to the excellent review of Wade and coworkers: "Acc. Chem. Res. 2016, 49, 5, 809–815"

      "____Notably, the conformational plasticity we observe for LTPs is reminiscent of other, previously described, functional protein mechanisms, including enzyme dynamics during catalysis (____DOI: 10.1126/science.1066176____), the alternating-access model of membrane transporters (____https://doi.org/10.1038/nsmb.3179____) or GPCR dynamics (____https://doi.org/10.1021/acs.chemrev.6b00177____). In all these cases, protein dynamics is strongly coupled to ligand binding (____https://doi.org/10.1021/acs.accounts.5b00516____) and protein function, be it for signaling, transport or enzymatic activity. Unlike for these fields, however, the contribution of structural and spectroscopic studies to uncover LTP dynamics remains quite limited, and our simulations provide an important contribution to fill this gap. We hope that our results will motivate researchers to increase efforts to experimentally quantify LTPs conformational plasticity, e.g. by structural determination of LTPs in different states (or bound to different lipids) or by single-molecule spectroscopy studies."

      *Minor comments: *

      *

      1) Fig 1d. What is so special in Lysine compared to Arginine? Is there any disbalance in their presence in studied proteins? Any correlations between the binding affinity of certain amino acids and their overall presence on the protein surface? *

      Indeed, there is disbalance in the presence of lysine and arginine residues in our proteins. The relation between the number of these residues in our dataset is Lys:Arg = 1.6:1. On top of that, and as described in (Tubiana T et al PLoS Comput Biol. 2022 ;18(12):e1010346) lysine is preferred over arginine in peripheral membrane proteins, likely because it induces fewer perturbations in the lipid bilayer. Our data also agree with Tubiana et al, concerning the correlation between abundance of specific residues on the protein surface and membrane binding.

      * 2) Fig S1. GM2A and TTPA seem to be irreversibly adsorbed to the membrane on the microsecond timescale in most replicas. Is anything special in these proteins? Did this affect the sampling of a claimed membrane-binding interface?*

      Our interpretation of the different adsorption profile of GM2A and TTPA is that these two proteins appear to have higher membrane affinity in our computational assay in comparison with the other proteins in our dataset. However, this has no effect on the membrane-binding interface as the proteins are still able to undergo significant tumbling before binding to the lipid bilayer, as demonstrated by the angle between the two main protein axes and the bilayer normal before membrane binding (Fig. S8 in Supplementary Information).

      * 3) A related follow-up question. Multiple replicas were performed to identify the membrane-binding interface. However, if I understand well, the initial orientation of the protein with respect to the membrane was always the same. I found it a pity since performing multiple replicas starting from different initial geometries (e.g., rotating the protein in a somewhat systematic way) would likely result in a more efficient exploration of the conformation space. Can the authors comment on whether this predefined initial configuration could negatively affect the results? Performing a few additional simulations for the most problematic proteins I mentioned earlier (GM2A and TTPA) could be a nice opportunity to apply this strategy. *

      In our protocol, all proteins start from the same initial orientation but undergo significant tumbling in solution before interacting with the lipid bilayer, including for the two most extreme cases, GM2A and TTPA (Fig. R1). Hence, we think that there is no bias for what pertains to the final membrane interacting region. We have added the Fig. R1 in Supplementary Information (Fig. S8) and added the following text in the Methods Section:

      "____Despite starting from a single orientation, all proteins undergo extensive tumbling before binding to the bilayer, as illustrated by the angle between the two principal protein axes and the membrane normal for the two proteins that display the highest binding propensity, GM2A and TTPA (Fig. S8)."

      * 4) How was the volume of the cavity affected by mutations in STARD11 and Mdm12? Do these data somehow correlate with the experimentally observed reduced efficiency of the lipid transfer? *

      Our data on the volume of the cavity in STARD11 and Mdm12 are inconclusive. However, we caution from such a simplistic interpretation, since it completely neglects the lipid-bound conformation that normally has a much larger cavity than the apo form (Fig. 3).

      *5) I would appreciate it if the authors considered playing with the templates of the main Figures at later stages because in the current version, and when printed on A4 paper, the readability of certain graphs and pictures is uncomfortable and sometimes even impossible. Obviously, the final schematics would depend on the journal and its formatting. *

      We will modify the templates of the main Figures to improve readability according to journal formatting.

      * **Referees cross-commenting** *

      * I would like to acknowledge the thoughtful and detailed reviews provided by other reviewers. I do like their reports, and I believe that by addressing the reviewers' comments and incorporating their revisions, the article will significantly improve in terms of scientific rigor and contribution to the field. *

      *Reviewer #1 (Significance (Required)):

      This manuscript is a solid scientific work addressing gaps in our knowledge about Lipid Transfer Proteins by employing state-of-the-art methods. It advances the field on conceptual and fundamental levels. This study is of interest to both computational biophysicists and physical chemists (to whom I belong myself) as well as experimentalists, who seek a rational explanation of the experimental observations. *

      We thank the reviewer again for the positive evaluation of the significance of our work.

      Reviewer #2* (Evidence, reproducibility and clarity (Required)): *

      * Summary:

      In a combined computational and experimental study, the authors provide insights into general features of lipid transfer proteins (LTPs), which play key roles in lipid trafficking: Through molecular dynamics simulations of a diverse set of 12 shuttle-like LTPs, they demonstrate that LTPs consistently exist in an equilibrium between two or more conformations, whose populations are modulated by a bound lipid, and that residues significantly involved in these collective conformational changes typically interact with a membrane. Their simulations indicate that conformational plasticity is a general feature of LTPs, leading them to suggest that the ability to change conformations is essential for LTP function. They test the generality of this hypothesis through in cellulo assays of two LTPs (STARD11 and Mdm12) that were not originally simulated. While experiments of STARD11 support their hypothesis, those presented for Mdm12 provide ambiguous results. *

      *

      Major comments: *

      * Throughout the manuscript, it's stated that common 'dynamical features' correlate with LTP function. The accuracy of this statement is unclear since 'dynamical features' are never precisely defined and, while equilibrium conformational ensembles are characterized, dynamics (ie kinetics or time-dependent observables) are not. Please clarify.*

      We plan to improve the scholarly presentation of our article to clarify this issue. In short, two distinct properties modulate protein function: 1. Conformational plasticity, i.e. the (thermodynamic) ability of the protein to adopt different conformations (and with different populations depending on the bound substrate). 2. Conformational “dynamics”, i.e. the propensity to exchange between these different thermodynamic states. This ability depends on the free energy barriers between different states and it is intrinsically a kinetic (rather than thermodynamic) property.

      *More importantly, further evidence is needed to determine a correlation with *function*. LTPs are suggested to have faster transfer rates (a measure of function) if the apo form adopts a substantial population of holo-like conformations, akin to enzyme preorganization. This is further tested by rationally mutating STARD11 and Mdm12. However, the support for this conclusion and if these mutations alter the LTPs conformational ensembles as desired is unclear: *

      In our opinion, the interpretation suggested by Reviewer #2 that there is a “correlation” between transfer rates and the overlap of apo-like and holo-like conformations, though fascinating, cannot be derived from the available data at this stage, and we did not mean to imply as such. Rather, lipid transport is a complex phenomenon that involves several steps (membrane binding/unbinding, lipid uptake/release,…). Our simulations indicate that protein conformational plasticity, including potentially the overlap between apo-like and holo-like conformations, also influences lipid transfer rates. We will clarify this aspect in the text.

      * Is there a quantitative correlation between the overlap of apo and holo conformational distributions (as could be quantified by KL divergence or Wasserstein distance, for example) and difference in transfer rates as suggested by Fig S6?*

      We plan to compute quantitative correlation between apo and holo conformational distribution for Fig.S6 and for mutant simulations (see answer below) but, as discussed above, we are skeptical that we will observe a clear correlation.

      * The conclusion and the generality of the findings would be greatly strengthened if a correlation can be shown for other LTPs through additional simulations of mutants whose transfer rates have been previously characterized experimentally in the literature. (For example: Ryan 2007 PMID 17344474, Grabon 2017 PMID 28718450, Iaea 2015 PMID 26168008, among many others)*

      We are currently running simulations of several mutants to address this point and provide additional data/context.

      * While differences in the apo conformational ensembles of the WT and mutants are observed in Fig S7b and d, if these mutations reduce overlap with holo-like conformations is not determined. Simulations of the WT holo forms are needed to properly test this hypothesis. *

      We are currently performing these simulations.

      • For Mdm12, mutations are specifically made to "lock the protein in the apo-like state;" however, the mutant adopts conformations distinct from the apo form as show in Fig S7d. How do the authors interpret the results of the cellular assays considering this and could it help explain why the mutant has similar kinetics to WT? What may explain the puzzling results of similar transfer kinetics but differing mitochondrial morphology? *

      As discussed above, interpretation of lipid transport rates based exclusively on apo and holo conformational population is premature, as this is a complex mechanism that depends on many variables. For what concerns the experimental results, we think three explanations are possible: 1. Mitochondrial morphology could be more sensitive to small variations in lipid composition than our METALIC assay. 2. Our assay only quantifies transport of unsaturated PC and PE species, and we can’t quantify variations in transport of other lipid species that are likely to also be transported by ERMES, such as PS and PA. 3. According to a recent structural model (Wozny et al, Nature 618, 88–192, 2023), Mdm12 might be part of a tunnel-like LTP complex in which it doesn't establish direct interactions with nearby organellar membranes. As such, its mechanism might be different from the one described here for other shuttle-like lipid transport domains. We will discuss these possibilities in the main text.

      • Confounding factors potentially complicate the interpretation of the in cellulo experiments. Simpler in vitro experiments may be better suited to determine if altering LTP's biophysical properties, namely rationally altering the population of apo- vs holo-like configurations, quantitatively affects transport rates as suggested.*

      We agree with Reviewer #2 that this information could be useful. However, this is beyond our technical abilities, and it would require lengthy and expensive experiments that are unlikely to be completed within a reasonable time framework for a revision (3 months). We have rather opted to better discuss our model in the context of published in vitro lipid transport experiments.

      • The abstract, intro, and title highlight that the manuscript's findings are indicative of and correlated with *function* but on p. 12 it's foreseen "that future studies will focus on the functional consequence of such observation." Please reconcile these conflicting statements and ensure connections to function are accurately described. The current title is rather bold. *

      We will rewrite and clarify the extent of our hypotheses and validations.

      * All mentions of "correlation" throughout the manuscript need to be quantitatively evaluated or properly qualified. In addition to that mentioned above regarding Fig S6, what is the correlation coefficient between residues' contribution to PC1 and membrane interaction frequency (Fig 2)? *

      To address this point, we will quantify the correlation between residues' contribution to PC1 and membrane interaction frequency. However, we expect a low correlation between residues' contribution to PC1 and membrane interaction frequency for at least two main reasons. __ First, not all residues contributing to PC1 interact with membranes, but only a subset, as discussed above. Second, our methodology to compute membrane binding, based on the geometric distance between residues and bilayer, is intrinsically quite noisy (since residues in proximity of bona fide membrane binding regions will also appear as involved in membrane binding), thus making quantification of correlations somewhat inaccurate. Rather, we will try to explain in the text that our observations are not of "correlation" but rather of dependence/association, and we will use quantitative measures to quantify these properties (such as rank correlation coefficients or multivariate analyses).__

      * Residue's contributions to collective conformational changes are found to be indicative of membrane binding. Yet, membrane interacting residues are identified from CG simulations that cannot capture such collective conformational changes due to the use of an elastic network. Given that the CG simulations agree with previous experimental findings, this suggests that collective conformational changes are not important for membrane binding. *

      We disagree with this interpretation by Reviewer #2 of our data: we do not claim that residue's contributions to collective conformational changes is indicative of membrane binding. Rather, membrane binding happens at protein regions displaying high contribution to collective conformational changes. This distinction is subtle but important: protein motion does not determine membrane binding regions. Rather, it appears that, for LTPs, membrane binding regions are also characterized by collective motions (suggesting function). We will clarify this in the main text.

      *Are similar conclusions drawn from residues' RMSFs? In other words, are local conformational fluctuations just as indicative of membrane binding? *

      We will compute protein residues’ RMSFs and compare it with the membrane binding data. However, given that RMSF is representative of thermal fluctuations, we again expect a bad correlation between RMSF and membrane binding. On the other hand, we indeed observe that most membrane binding regions are protein loops, but this is not unexpected (e.g. Tubiana et al, PLoS Comput Biol. 2022 Dec; 18(12): e1010346.). However, such observation does not provide any information on lipid transport, but only on the mechanism of membrane binding. Rather, the observation of a relationship between membrane binding and global motion is more interesting, since the latter is often indicative of protein function.

      *The stated correlation may in fact be spurious and instead arise because residues at the entrance to LTP's hydrophobic cavities need to be positioned at the membrane surface for productive lipid uptake and these same residues must undergo significant conformational changes to allow lipid entry. *

      This is exactly what we think it is happening and what our data suggest. However, one must remember that our simulations allow us to predict the membrane binding interface, that is often difficult to determine experimentally (and often via indirect evidence). Hence our data provide novel evidence in this direction.

      *Is proximity to cavity entrance more or less correlated with membrane binding than 'dynamics'? *

      If we consider that, as discussed before, dynamics does not correlate with membrane binding (there are many dynamical regions that are not at the membrane interface), it is safe to assume that proximity to cavity entrance would correlate more with membrane binding. However, we have to consider that often we do not know where the cavity entrance in LTPs is located simply based on structure alone, and hence our approach provides important clues into this process.

      p.12 speculatively suggests "the high degree of protein dynamics we observed in membrane proximal regions could potentially facilitate the energetically unfavorable reaction that involves the extraction of a lipid from a membrane." Yet, the logic behind this idea does not make sense since a free energy barrier, an equilibrium thermodynamic quantity, cannot be lowered by changes in dynamics. Please explain.*

      Our current understanding of the mechanism of lipid extraction is quite poor. However, both using chemical intuition and following a recent MD study on one LTP (Rogers et al, 2023, Plos Comp Biol), it is safe to assume that the hydrophobic environment around the lipid is important for its stabilization in the lipid bilayer. Hence, reducing the number of hydrophobic contacts between the lipid and its environment could facilitate transport. A highly dynamic protein, by cycling between different conformations, could “stir” the bilayer, and hence decrease the number of contacts between the lipid and its environment favoring transport. We will clarify this point in the text.

      *Examining how the LTPs impact membrane properties would offer insight into the functional relevance of such residues for lipid extraction. *

      Indeed, our point above is connected to this one. We are performing simulations to compute hydrophobic contacts in bilayer as proposed in (Rogers et al, 2023, Plos Comp Biol).

      The authors highlight that a bound lipid alters LTPs' conformational ensembles akin to "conformational selection" or "induced fit." How sensitive are these findings to the bound lipid species? Do LTPs with multiple known substrates exhibit an increasing diversity of holo conformations and are different conformations stabilized by different substrates? Would similar observations (Fig 3) be made with a lipid that is not known to be transferred by a given LTP? An interesting future direction would be to examine if lipid substrate specificity could be assessed by comparing conformational ensembles to that of a known substrate and/or by overlap with the apo ensemble.

      We deem that the role of lipid specificity on LTP conformational plasticity is beyond the scope of the current work. While this topic is certainly worth future investigations, we must point out that (i) not all proteins bind/transport multiple lipids (at least according to current knowledge) and (ii) only few LTPs have been structurally characterized bound to different lipids (Osh4, Osh6, …). This limitation prevents a wide generalization, and we prefer not to speculate on this topic. So far, we have tested our approach for Osh4 bound to cholesterol or PI(4)P and found that indeed the protein exhibits different holo conformations (in agreement with the experimental data) when bound to different substrates. We have added a short comment on this topic in the Discussion section.

      "____We foresee that future studies will focus on the functional consequence of such observation, and most notably to the characterization of the extent to which such conformational changes affect multiple steps of protein function, including membrane binding or lipid extraction and release, and whether these are further modulated when different lipids are being transported."

      For LTPs to transfer lipids between membranes, transitions between apo and holo forms ought to occur when LTPs are membrane bound. How does membrane binding influence the conformational ensembles observed in solution? Does it promote conformational changes between apo- and holo-like structures, as suggested to regulate lipid uptake and release by previous studies of Osh/ORP, Ups/PRELI, and START family members? (For example: Miliara 2019 PMID 30850607, Watanabe 2015 PMID 26235513, Grabon 2017 PMID 28718450, Iaea 2015 PMID 26168008, Kudo 2008 PMID 18184806, Dong 2019 PMID 30783101) While answering these questions would require further computational effort, doing so will allow more accurate assessment of the role of conformational changes in LTP function.

      We can’t unfortunately currently quantify how membrane binding influences the conformational ensembles observed in solution, as the slowdown in diffusion at the water-membrane interface makes this task computationally challenging (and certainly not feasible within the time framework of a review). We have so far tested two different proteins and have not succeeded in converging their conformational distribution when membrane-bound despite long MD simulations that lasted several months (even though the non-converged data indicate sampling of both “open” and “closed” conformations). Interestingly, our observations are in qualitative agreement with a recent study on CPTP (Rogers et al, PLOS Comp Biol, 2023), where membrane-bound CPTP is able to sample different conformations (“open” and “closed”) but not to transition between the two states in 300 ns-long MD simulations.

      * The authors motivate the study with the *assumption* that a common molecular mechanism of LTP function exists. Yet LTPs have evolved diverse sequences, structures, and substrate preferences; thus there seems to be no a priori requirement (or even necessarily a benefit) for a single molecular mechanism. What evidence then supports this premise? While previous studies are limited to individual LTPs, when viewed altogether retrospectively, they suggest features that could be shared among LTPs. Synthesizing previous studies and more thoroughly referencing them (only 5 are cited in the intro on p. 3) would strengthen both the premise and findings of the manuscript. *

      Indeed, despite having different structures, substrates and the ability to target distinct organelles, previous evidence on LTPs seem to suggest a potential role for protein conformational plasticity for function, e.g. for Osh/ORP (Jun Im et al, Nature 2005; Canagarajah et al, JMB 2008; Moser von Filseck et al, Nat Comm, 2015; Lipp et al, Nat Comm. 2019,...), StART (Arakane et al, PNAS, 1996; Feng et al, Biochemistry, 2000; Grabon et al, JBC, 2017; Khelashvili et al, eLife, 2019;...) and PITP domains (Tremblay et al, Archives of Biochemistry and Biophysics, 2005; Ryan et al, MBOC, 2007; …). Our simulations provide additional evidence in this direction and allow for generalizing these observations, allowing to draw parallelisms with “enzyme-like” or transporter-like” features that could be exploited for further design of testable hypotheses. We will rewrite our text to better contextualize/acknowledge previous findings and to clarify these points.

      *The LTPs investigated are known to target distinct membranes. Should they then be expected to share structural or sequence-based features predictive of membrane binding interfaces, as motivates the analysis in Fig 1d, 1e, and S3? Or is it beneficial for LTPs to recognize membranes in different ways? *

      Since membrane binding is membrane/organelle-specific, it is possible that residue’s diversity in membrane binding interfaces could indeed be beneficial for this diversity. We will add this comment as a potential explanation of our finding of a lack of conserved sequence-based features for membrane binding interfaces.

      *

      Minor comments:*

      * 2 "making lipid transfer across the cytoplasm a potentially energetically favorable process": Is it meant that it is less energetically costly than transfer without a LTP? Why it would be energetically favorable is unclear (and would indicate that the LTP sequesters lipids away from membranes instead of transferring them between membranes). *

      Yes, this is what we meant. We will rewrite this appropriately.

      * 3 "The excellent agreement between the membrane interface determined from the simulations and the experimentally-proposed one available for... Osh6" is missing a citation. *

      We have now added the relevant citation.

      * The plots in Fig 1d and S3 are difficult to interpret. Bar plots, for example, would allow easier comparison and evaluation. Currently, it seems that most proteins individually exhibit some of the same trends observed among the whole set, counter to the conclusion on p 5. *

      We will improve the presentation of our Figures.

      * Negatively charged residues engage in a number of membrane interactions (Fig 1d and S3). What is a potential explanation for this unconventional observation? *

      One possible interpretation is that negatively charged residues could interact with positively charged moieties (ethanolamine, choline) of PC and PE lipids.

      * How much variance is captured by PC1, and how many PCs are needed to capture most of the variance in the conformations? *

      PC1 explains 38 % of the total variance, by average, whereas PC2 accounts for 17 % of it. Therefore, PC1 and PC2 capture most of the variance in almost all cases.

      We have also added this to the text:

      "____We specifically focused on PC1 as it explains most of the variance in the dynamics (38% on average for all the proteins in our dataset, see Supplementary Table 2).____ "

      We have computed this variance and we have added this analysis in Supplementary Information.

      * Plots in Fig 3, especially panels c and d are difficult to see. Please make the panels larger (perhaps a 3 x 4 layout instead of 2 x 6 would work better). *

      We will improve the presentation of our Figures.

      * 8 "these conformational changes are localized in protein regions that interact with the lipid bilayer" is contradicted by the results in Fig 2b showing that all residues with large contributions to PC1 do not interact with the membrane and discussed on p 5. *

      As discussed above, we don’t observe “correlation” between membrane binding and conformational plasticity, but we rather observe that membrane binding regions display high conformational plasticity (the opposite is not true). We will further clarify in the text.

      *

      8 "in the absence of bound lipids, it is able to sample multiple conformations" is not supported by the orange distributions in Fig 3d that appear unimodal. Is it instead meant that the apo form exhibits larger variance in cavity volume? *

      Yes, this is what we meant. We’ll clarify.

      *

      Please clarify if the elastic network was constructed to maintain the holo or apo structures of each protein and if a bound lipid was used in the CG simulations. *

      For membrane binding CG simulations, we used the apo structure and no bound lipid was used in the simulations. However, analogous simulations in the holo form (not shown) have essentially identical membrane binding interfaces.

      *

      Was *CHARMM* TIP3P used? *

      Yes.

      * Please clarify how membrane interacting residues were defined and how interaction frequency was calculated from the longest duration of interaction. *

      We will add this explanation in the Methods. The method is identical to (Srinivasan et al, Faraday Discussion, 2021).

      * Refs 16 and 45 refer to the same paper. *

      Thanks, it is now corrected!

      * Reviewer #2 (Significance (Required)): *

      * General assessment: *

      * The work aims to tackle a grand question regarding membrane homeostasis mechanisms-what are universal principles underlying LTP function-and offers initial insights; however, further evidence is needed to support the conclusions as written, and some key results require further investigation and explanation. *

      *Advance and audience: *

      *

      By concurrently investigating the largest number of lipid transfer proteins to-date, the authors provide data invaluable for uncovering general mechanisms of non-vesicular lipid transport and advancing our understanding of membrane homeostasis mechanisms. By illuminating the wide-spread importance of conformational plasticity among lipid transfer proteins, the work presents a conceptual advance in our understanding of lipid transfer mechanisms and unifies previous studies. Because the manuscript emphasizes common biophysical principles and draws connections to enzyme biophysics, it ought to be of interest not only to membrane biologists but biochemists and molecular biologists more broadly.*

      We thank Reviewer #2 for the very positive evaluation of the significance of our work and for the in-depth analysis provided that will certainly help improve the quality of our work.

      Reviewer #3* (Evidence, reproducibility and clarity (Required)): *

      *The article "Conformational dynamics of lipid transfer domains provide a general framework to decode their functional mechanism." by Sriraksha Srinivasan, Andrea DiLuca, Arun Peter, Charlotte Gehin, Museer Lone, Thorsten Hornemann, Giovanni D'Angelo and Stefano Vanni study the interaction of Lipid transport Domains with membranes. This is done mainly by molecular modelling but also with selected experimental validations. *

      * Major comments: *

      * - The key conclusions are generally well supported by the analysis. - The authors could however analyze in more details some aspects in which specific cases appear. For example, p3 "multiple binding and unbinding events, as shown by the minimum distance curves" does not give an entire description of the variability seen in Fig S1, e.g. LCN1 versus GM2A.*

      We now discuss in more detail the variability seen in Fig. S1 and attribute it to different membrane binding affinities of the proteins in our dataset. We also discuss how this variability could reflect the diversity of organellar membranes to which these proteins bind in vivo.

      "____Notably, the proteins in our dataset display distinct binding affinities, with some proteins showing very transient binding while others remain membrane-bound for most of the simulation trajectory (Fig. S1). This behavior could be, in part, attributed to the wide diversity of organellar membranes to which the LTDs in our dataset bind to in vivo, and to the comparative simplicity of our in silico model DOPC lipid bilayers."

      • Later the "excellent agreement" for the data in Fig S2 is not quantified which does not allow the reader to know whether it better than would have been with other methods (SASA, OPM, DREAM). *

      We have explicitly quantified this agreement by providing a direct comparison between the experimental results and our in silico assay, and we further compared it against two alternative methods: OPM and DREAMM. In detail, we have identified 12 experimentally-characterized spots suggested to be involved in membrane binding in our protein dataset (see shaded blue regions in Fig. S2). Of those 12, our method identifies all of them (100%), while DREAMM identifies 7 of them (58 %) and OPM 4 out of 8 (50 %), since of the 12 proteins we tested, only 7 are available in the OPM database. Overall, even if our approach is much noisier than the others, and thus suggesting multiple binding regions that are not currently supported by experimental observations, using physics-based methodologies appears to remain a preferable strategy to characterize the binding of peripheral proteins to lipid bilayers. Given the limited size of our dataset, we prefer not to make a direct comparison between our assay and OPM/DREAMM in the main text as this won't be representative of the various methodologies.

      *p5 commenting on Fig2b the case of Osh6 that appears to disagree should probably be mentioned. *

      We now discuss this case, and attribute to this disagreement to insufficient sampling for the peculiar case of Osh6:

      "____One interesting exception in our database appears to be Osh6, where the experimentally determined membrane-binding region at the N-terminus (https://doi.org/10.1038/s41467-019-11780-y) is only marginally binding to the lipid bilayer in silico and it also appears to have limited contribution to PC1. However, our simulations are unable to sample the large conformational changes that the N-terminal lid of Osh6 has been proposed to undergo from its lipid-bound to its apo state, indicating that insufficient sampling could be the reason for this apparent discrepancy."

      *

      -The data and the methods are generally well presented allowing to be reproduced.

      • The experiments adequately replicated with adequate statistical analysis. *

      * Minor comments: *

      * - When presenting the dataset the authors could probably detail a bit more the protocol undertaken to chose the cases. In particular it is unclear whether the chosen proteins have any membrane selectivity, which in principle could be affected by the choice of lipid used here.*

      We have now added in Table 1 a column with a list of potential organelles the different LTPs have been shown to localize to (source: UniProt). As model membrane bilayer, we opted to use a pure DOPC bilayer, for both simplicity and to compare membrane binding in a uniform setting. We foresee that future studies investigating the membrane specificity of the various proteins will shed further light into the molecular mechanism of LTPs. Finally, we also indicate that our choice of proteins was mainly driven by the availability of lipid-bound structures in the protein data bank. We have added the following sentences in the main text:

      "____Specifically, we selected all LTPs for which a crystallographic structure in complex with a lipid was available at the start of our project, plus two additional proteins (GM2A and LCN1) to increase the structural diversity of our dataset (Fig. 1a)"

      and

      "____Notably, the proteins in our dataset display distinct binding affinities, with some proteins showing very transient binding while other remain membrane-bound for most of the simulation trajectory (Fig. S1). This behavior could be, in part, attributed to the wide diversity of organellar membranes to which the LTDs in our dataset bind to in vivo, and to the comparative simplicity of our in silico model DOPC lipid bilayers."

      *- The authors could probably give some indication of how much of the variance is explained by PC1 and comment briefly on the choice to ignore other PCs. *

      PC1 explains 38 % of the total variance, on average. This means that PC1 has a large contribution to the variance, especially in comparison to the other PCs. For instance, PC2 only accounts for 17 % of the total variance. This is the reason we limited our discussion to PC1. We have added a table in supplementary Information quantifying the variance explained by PC1 and PC 2 and added the following sentence in the main text:

      "____We specifically focused on PC1 as it explains most of the variance in the dynamics (38% on average for all the proteins in our dataset)____. "

      * - When analyzing the residues involved in the interaction with the membrane the results could probably be compared with that of the systematic analysis performed recently: Tubiana, T., Sillitoe, I., Orengo, C., & Reuter, N. (2022). Dissecting peripheral protein-membrane interfaces. PLOS Computational Biology, 18(12), e1010346. *

      We have added in the text a reference to the work by Tubiana et al and we have further stressed that our results agree with previous observations (including theirs). This includes the preference for Lys over Arg and the importance of protruding hydrophobes:

      "____Concomitant analysis of all LTDs (Fig. 1d) indicates that the membrane binding interface of LTDs is enriched in the positively charged amino acid Lysine, as this amino acid is less membrane-disruptive than Arginine22, and aromatic/hydrophobic ones (Phe, Leu, Val, Ile). This confirms previous observations, as (i) binding of negatively charged lipids via positively charged residues and (ii) hydrophobic insertions are two of the main mechanisms involved in membrane binding by peripheral proteins22-27."

      * - In the discussion on allostery/conformational selection might not be centered so much on enzymes. *

      We thank the reviewer for this important observation. We have now included in the Discussion the following paragraph that provides additional references and discussion of membrane transporters and receptors.

      "____Notably, the conformational plasticity we observe for LTPs is reminiscent of other, previously described, functional protein mechanisms, including enzyme dynamics during catalysis (____DOI: 10.1126/science.1066176____), the alternating-access model of membrane transporters (____https://doi.org/10.1038/nsmb.3179____) or GPCR dynamics (____https://doi.org/10.1021/acs.chemrev.6b00177____). In all these cases, protein dynamics is strongly coupled to ligand binding and protein function, be it for signaling, transport or enzymatic activity. Unlike for these fields, however, the contribution of structural and spectroscopic studies to uncover LTP dynamics remains quite limited, and our simulations provide an important contribution to fill this gap. We hope that our results will motivate researchers to increase efforts to experimentally quantify LTPs conformational plasticity, e.g. by structural determination of LTPs in different states (or bound to different lipids) or by single-molecule spectroscopy studies."

      * Reviewer #3 (Significance (Required)): *

      *

      The article shows convincing results on the debated issue of the mechanism of lipid transport by lipid transfer proteins. *

      First the study employs molecular modelling to allow a rather large test on 12 cases. The molecular dynamics experiments allow the authors to draw clear hypotheses on role of protein dynamics on the interaction with membranes and the effect on bound lipids on the modification of this dynamics.

      *Then the authors use this knowledge to design experiments that largely confirm those hypotheses. The results should therefore be interesting for a large audience of biochemists and cell biologists interested in lipid transport in the cell. *

      We thank Reviewer #3 for its very positive evaluation and contextualization of our work.

    2. Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Referee #2

      Evidence, reproducibility and clarity

      Summary:

      In a combined computational and experimental study, the authors provide insights into general features of lipid transfer proteins (LTPs), which play key roles in lipid trafficking: Through molecular dynamics simulations of a diverse set of 12 shuttle-like LTPs, they demonstrate that LTPs consistently exist in an equilibrium between two or more conformations, whose populations are modulated by a bound lipid, and that residues significantly involved in these collective conformational changes typically interact with a membrane. Their simulations indicate that conformational plasticity is a general feature of LTPs, leading them to suggest that the ability to change conformations is essential for LTP function. They test the generality of this hypothesis through in cellulo assays of two LTPs (STARD11 and Mdm12) that were not originally simulated. While experiments of STARD11 support their hypothesis, those presented for Mdm12 provide ambiguous results.

      Major comments:

      Throughout the manuscript, it's stated that common 'dynamical features' correlate with LTP function. The accuracy of this statement is unclear since 'dynamical features' are never precisely defined and, while equilibrium conformational ensembles are characterized, dynamics (ie kinetics or time-dependent observables) are not. Please clarify.

      More importantly, further evidence is needed to determine a correlation with function. LTPs are suggested to have faster transfer rates (a measure of function) if the apo form adopts a substantial population of holo-like conformations, akin to enzyme preorganization. This is further tested by rationally mutating STARD11 and Mdm12. However, the support for this conclusion and if these mutations alter the LTPs conformational ensembles as desired is unclear:

      • Is there a quantitative correlation between the overlap of apo and holo conformational distributions (as could be quantified by KL divergence or Wasserstein distance, for example) and difference in transfer rates as suggested by Fig S6?
      • The conclusion and the generality of the findings would be greatly strengthened if a correlation can be shown for other LTPs through additional simulations of mutants whose transfer rates have been previously characterized experimentally in the literature. (For example: Ryan 2007 PMID 17344474, Grabon 2017 PMID 28718450, Iaea 2015 PMID 26168008, among many others)
      • While differences in the apo conformational ensembles of the WT and mutants are observed in Fig S7b and d, if these mutations reduce overlap with holo-like conformations is not determined. Simulations of the WT holo forms are needed to properly test this hypothesis.
      • For Mdm12, mutations are specifically made to "lock the protein in the apo-like state;" however, the mutant adopts conformations distinct from the apo form as show in Fig S7d. How do the authors interpret the results of the cellular assays considering this and could it help explain why the mutant has similar kinetics to WT? What may explain the puzzling results of similar transfer kinetics but differing mitochondrial morphology?
      • Confounding factors potentially complicate the interpretation of the in cellulo experiments. Simpler in vitro experiments may be better suited to determine if altering LTP's biophysical properties, namely rationally altering the population of apo- vs holo-like configurations, quantitatively affects transport rates as suggested.
      • The abstract, intro, and title highlight that the manuscript's findings are indicative of and correlated with function but on p. 12 it's foreseen "that future studies will focus on the functional consequence of such observation." Please reconcile these conflicting statements and ensure connections to function are accurately described. The current title is rather bold.

      All mentions of "correlation" throughout the manuscript need to be quantitatively evaluated or properly qualified. In addition to that mentioned above regarding Fig S6, what is the correlation coefficient between residues' contribution to PC1 and membrane interaction frequency (Fig 2)?

      Residue's contributions to collective conformational changes are found to be indicative of membrane binding. Yet, membrane interacting residues are identified from CG simulations that cannot capture such collective conformational changes due to the use of an elastic network. Given that the CG simulations agree with previous experimental findings, this suggests that collective conformational changes are not important for membrane binding. Are similar conclusions drawn from residues' RMSFs? In other words, are local conformational fluctuations just as indicative of membrane binding? The stated correlation may in fact be spurious and instead arise because residues at the entrance to LTP's hydrophobic cavities need to be positioned at the membrane surface for productive lipid uptake and these same residues must undergo significant conformational changes to allow lipid entry. Is proximity to cavity entrance more or less correlated with membrane binding than 'dynamics'?

      p. 12 speculatively suggests "the high degree of protein dynamics we observed in membrane proximal regions could potentially facilitate the energetically unfavorable reaction that involves the extraction of a lipid from a membrane." Yet, the logic behind this idea does not make sense since a free energy barrier, an equilibrium thermodynamic quantity, cannot be lowered by changes in dynamics. Please explain. Examining how the LTPs impact membrane properties would offer insight into the functional relevance of such residues for lipid extraction.

      The authors highlight that a bound lipid alters LTPs' conformational ensembles akin to "conformational selection" or "induced fit." How sensitive are these findings to the bound lipid species? Do LTPs with multiple known substrates exhibit an increasing diversity of holo conformations and are different conformations stabilized by different substrates? Would similar observations (Fig 3) be made with a lipid that is not known to be transferred by a given LTP? An interesting future direction would be to examine if lipid substrate specificity could be assessed by comparing conformational ensembles to that of a known substrate and/or by overlap with the apo ensemble.

      For LTPs to transfer lipids between membranes, transitions between apo and holo forms ought to occur when LTPs are membrane bound. How does membrane binding influence the conformational ensembles observed in solution? Does it promote conformational changes between apo- and holo-like structures, as suggested to regulate lipid uptake and release by previous studies of Osh/ORP, Ups/PRELI, and START family members? (For example: Miliara 2019 PMID 30850607, Watanabe 2015 PMID 26235513, Grabon 2017 PMID 28718450, Iaea 2015 PMID 26168008, Kudo 2008 PMID 18184806, Dong 2019 PMID 30783101) While answering these questions would require further computational effort, doing so will allow more accurate assessment of the role of conformational changes in LTP function.

      The authors motivate the study with the assumption that a common molecular mechanism of LTP function exists. Yet LTPs have evolved diverse sequences, structures, and substrate preferences; thus there seems to be no a priori requirement (or even necessarily a benefit) for a single molecular mechanism. What evidence then supports this premise? While previous studies are limited to individual LTPs, when viewed altogether retrospectively, they suggest features that could be shared among LTPs. Synthesizing previous studies and more thoroughly referencing them (only 5 are cited in the intro on p. 3) would strengthen both the premise and findings of the manuscript.

      The LTPs investigated are known to target distinct membranes. Should they then be expected to share structural or sequence-based features predictive of membrane binding interfaces, as motivates the analysis in Fig 1d, 1e, and S3? Or is it beneficial for LTPs to recognize membranes in different ways?

      Minor comments:

      p. 2 "making lipid transfer across the cytoplasm a potentially energetically favorable process": Is it meant that it is less energetically costly than transfer without a LTP? Why it would be energetically favorable is unclear (and would indicate that the LTP sequesters lipids away from membranes instead of transferring them between membranes).

      p. 3 "The excellent agreement between the membrane interface determined from the simulations and the experimentally-proposed one available for... Osh6" is missing a citation.

      The plots in Fig 1d and S3 are difficult to interpret. Bar plots, for example, would allow easier comparison and evaluation. Currently, it seems that most proteins individually exhibit some of the same trends observed among the whole set, counter to the conclusion on p 5.

      Negatively charged residues engage in a number of membrane interactions (Fig 1d and S3). What is a potential explanation for this unconventional observation?

      How much variance is captured by PC1, and how many PCs are needed to capture most of the variance in the conformations?

      Plots in Fig 3, especially panels c and d are difficult to see. Please make the panels larger (perhaps a 3 x 4 layout instead of 2 x 6 would work better).

      p. 8 "these conformational changes are localized in protein regions that interact with the lipid bilayer" is contradicted by the results in Fig 2b showing that all residues with large contributions to PC1 do not interact with the membrane and discussed on p 5.

      p. 8 "in the absence of bound lipids, it is able to sample multiple conformations" is not supported by the orange distributions in Fig 3d that appear unimodal. Is it instead meant that the apo form exhibits larger variance in cavity volume?

      Please clarify if the elastic network was constructed to maintain the holo or apo structures of each protein and if a bound lipid was used in the CG simulations.

      Was CHARMM TIP3P used?

      Please clarify how membrane interacting residues were defined and how interaction frequency was calculated from the longest duration of interaction.

      Refs 16 and 45 refer to the same paper.

      Significance

      General assessment:

      The work aims to tackle a grand question regarding membrane homeostasis mechanisms-what are universal principles underlying LTP function-and offers initial insights; however, further evidence is needed to support the conclusions as written, and some key results require further investigation and explanation.

      Advance and audience:

      By concurrently investigating the largest number of lipid transfer proteins to-date, the authors provide data invaluable for uncovering general mechanisms of non-vesicular lipid transport and advancing our understanding of membrane homeostasis mechanisms. By illuminating the wide-spread importance of conformational plasticity among lipid transfer proteins, the work presents a conceptual advance in our understanding of lipid transfer mechanisms and unifies previous studies. Because the manuscript emphasizes common biophysical principles and draws connections to enzyme biophysics, it ought to be of interest not only to membrane biologists but biochemists and molecular biologists more broadly.

    1. Author Response

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

      Reviewer #1 (Public Review):

      Jamge et al. sought to identify the relationships between histone variants and histone modifications in Arabidopsis by systematic genomic profiling of 13 histone variants and 12 histone modifications to define a set of "chromatin states". They find that H2A variants are key factors defining the major chromatin types (euchromatin, facultative heterochromatin, and constitutive heterochromatin) and that loss of the DDM1 chromatin remodeler leads to loss of typical constitutive heterochromatin and replacement of this state with features common to genes in euchromatin and facultative heterochromatin. This study deepens our understanding of how histone variants shape the Arabidopsis epigenome and provides a wealth of data for other researchers to explore.

      Strengths:

      1) The manuscript provides convincing evidence supporting the claims that: A) Arabidopsis nucleosomes are homotypic for H2A variants and heterotypic for H3 variants, B) that H3 variants are not associated with specific H2A variants, and C) H2A variants are strongly associated with specific histone post-translational modifications (PTMs) while H3 variants show no such strong associations with specific PTMs. These are important findings that contrast with previous observations in animal systems and suggest differences in plant and animal chromatin dynamics.

      2) The authors also performed comprehensive epigenomic profiling of all H2A, H2B, and H3 variants and 12 histone PTMs to produce a Hidden Markov Model-based chromatin state map. These studies revealed that histone H2A variants are as important as histone PTMs in defining the various chromatin states, which is unexpected and of high significance.

      3) The authors show that in ddm1 mutants, normally heterochromatic transposable element (TE) genes lose H2A.W and gain H2A.Z, along with the facultative heterochromatin and euchromatin signatures associated with H2A.Z at silent and expressed genes, respectively.

      Weaknesses:

      1) Following up on the finding that H2A.Z replaces H2A.W at TE genes in ddm1 mutants, the authors provide in vitro evidence that DDM1 binds to H2A.Z-H2B dimers. These results are taken together to conclude that DDM1 normally removes H2A.Z-H2B dimers from nucleosomes at TE genes and replaces them with H2A.W-H2B dimers. However, the evidence for this model is circumstantial and such a model raises a variety of other questions that are not addressed by the authors.

      The Reviewer raises a series of interesting questions. We proposed that DDM1 exchanges H2A.Z to H2A.W because it is the simplest model and also because LSH - the mammalian ortholog of DDM1 exchanges H2A to macroH2A. However we do stress in the revised manuscript that this is a model and other possible models that could involve chaperones and additional remodelers are possible. Addressing why the loss of DDM1 results in a net exchange of H2A.W to H2A.Z is not the purpose of this study. Here we use the perturbation caused by ddm1 as a means to address the importance of the dynamics exchange of H2A variants in setting up the chromatin states. We do observe that perturbing this dynamic exchange causes an important perturbation of chromatin states. This further supports our main conclusion: H2A variants dynamics are one important factor that organizes chromatin states.

      For example: if DDM1 does remove H2A.Z from TE genes, how does H2A.Z normally come to occupy these sites, given that they are highly DNA methylated and that H2A.Z is known to anticorrelate with DNA methylation in plants and animals?

      The anticorrelation between H2A.Z and DNA methylation is observed at steady state. The exchange of H2A.Z to H2A.W that results from the action of DDM1 would indeed remove unwanted H2A.Z from regions occupied by DNA methylation as suggested by the Reviewer.

      Given that H2A.Z does not accumulate in TEs in h2a.w mutants, how would H2A.X and H2A instead become enriched at these sites if DDM1 cannot bind these forms of H2A?

      This is a valid question: We envisage that H2A.X and H2A are deposited by remodelers and chaperones other than DDM1 in the h2a.w mutant.

      Given that there are no apparent regions with common sequence between H2A.Z and H2A.W variants that are not also shared with other H2A classes, how would DDM1 selectively bind to H2A.W-H2B and H2A.Z-H2B dimers to the exclusion of H2A(.X)-H2B dimers?

      It was shown by the Muegge Lab both in vitro and in vivo that LSH - the mammalian ortholog of DDM1 binds to macroH2A and H2A, and these two H2A variants do not share similar specific region. Yet it remains to determine which region of H2A.Z and H2A.W binds to DDM1, which does not fit in the scope of this study.

      Reviewer #2 (Public Review):

      Jamge et al. set out to delineate the relationship between histone variants, histone modifications and chromatin states in Arabidopsis seedlings and leaves. A strength of the study is its use of multiple types of data: the authors present mass-spec, immunoblotting and ChIPseq from histone variants and histone modifications. They confirm the association between certain marks and variants, in particular for H2A, and nicely describe the loss of constitutive heterochromatin in the ddm1 mutant.

      The support for some of the conclusions is weak. The title of the discussion, "histone variants drive the overall organization of chromatin states" implies a causation which wasn't investigated, and overstates the finding that some broad chromatin states can be further subdivided when one considers histone variants (adding variables to the model).

      We have removed subtitles in the discussion and have taken care to avoid over simplified statements.

      Adding variables to a ChromHMM model naturally increases the complexity of the models that can be built, however it is difficult to objectively define which level of complexity is optimal. The differences between states may be subtle to the point that they may be considered redundant. The authors claim that the sub-states they define are biologically important, but provide little evidence to support this claim. It is not obvious whether the 26 states model is much more useful than a 9-states model. Removing variables naturally affects the definition of states that depend on these variables, but it is also hard to define the biological significance of that change. This sensitivity analysis is thus not very developed.

      We agree that adding more input tracks/ data will increase the complexity.

      But we would like to mention the differences of this study and the 9-state model,

      1) We have included the histone variants which have been previously missed in chromatin state definition.

      2) The previous 9-state model used data from different tissue types. In this study all the data generated and analyzed is from seedlings.

      3) Increasing the number of states allowed us to resolve heterochromatin states compared to 9-state model which was previously missed. (BioRXiv)

      4) The biological relevance of the 26 states model is analyzed and described in depth (States BioRxiv paper).

      In addition we have now updated the Figure 2F to include a more direct comparison of marks used in both models. And we have expanded the description in the methods section and our reasoning behind using 26 state model to be analyzed in depth.

      There are issues with the logical sequence of arguments in Fig1 and Fig3. Fig1A shows that nucleosomes often contain both H3.1 and H3.3. Therefore pulling-down H3.1-containing nucleosomes also pulls down H3.3 and whether specific H2A variants associated with H3.1 cannot be answered in this way (Fig1B).

      We thank the Reviewer for point this out. If 60% of nucleosomes are homotypic and if they would associate with a specific H2A variant this would be clearly visible on WB as a much stronger band. Also, the MS data presented in Figure1 figure supplement 1D clearly show that all H2A variants associate with both H3.1 and H3.3. We have included in the revised version more detailed explanation to clarify this point.

      The same issue likely carries to the investigation of the association with H3 modifications if Fig1C and 1D, since the H3.1-HA pull-down also pulls down endogenous H3.1 (so presumably the rest of the nucleosome, with H3.3, as well).

      We disagree on this point. The H3 band corresponding to the transgene copy is either H3.1 or H3.3, so all signals on upper band (T) in Figure 1C are associated with either H3.1 (H3.1 IP) or H3.3 (H3.3 IP), thus unambiguously showing that all modifications we analyzed are present on both H3.1 and H3.3. Furthermore, data shown in Figure 1D and E, where we analyzed modifications on K27 and K36 which are in the H3 region that can be distinguished between H3.1 and H3.3 by MS clearly demonstrate that these modifications are present on both H3.1 and H3.3. In order to make this clearer, we also extended the description of this part in the Results section to emphasize this.

      In Fig3, the conclusion that it is the loss of H2A.Z -> H2A.W exchange in the ddm1 mutant that causes loss of constitutive heterochromatin is rushed. The fact that the h2a.w mutant does not recapitulate the loss of constitutive heterochromatin seen in ddm1 argues against this interpretation.

      We agree that at first the minimal impact of the loss of H2A.W alone is surprising. However, we point to the preprint https://www.biorxiv.org/content/10.1101/2022.05.31.493688v1. There it is shown that the joint loss of H2A.W and H3K9 methylation (also observed in ddm1) affects silencing of a large range of transposons that also lose silencing in ddm1.

      It's also difficult to conclude about the importance of dynamic exchanges when the ddm1 mutation has been present for generations and the chromatin landscape has fully readapted. Further work is needed to support the authors' hypothesis.

      We apologize that the Reviewer could not find the information regarding the origin of ddm1 mutant material. We did not use a mutant where ddm1 mutations was kept for generations. We were in fact very careful on this point and used leaves from ddm1 first homozygous plants segregated from heterozygous ddm1 kept heterozygous.

      The study also relies on a large number of custom (polyclonal) antibodies with no public validation data. Lack of specificity, a common issue with antibodies, would muddle the interpretation of the data.

      We added information about validation of custom made antibodies into Methods: ”Specificities of custom made polyclonal antibodies against Arabidopsis H2A.Z.9, H2A.X, H2A.W.6, H2A.13, H2A.W.7, H2Bs, and linker histone H1 were validated in previous publications (Yelagandula et al., 2014; Lorkovic et al., 2017; Jiang et al., 2020; Osakabe et al., 2021).“ For H2A.2 and H2A.Z.11 antibodies we provide validation data as Figure 2 figure supplement 1.

      Overall, this study nicely illustrates that, in Arabidopsis, histone variants (and H2A variants in particular) display specificity in modifications and genomic locations, and correlate with some chromatin sub-states. This encourages future work in epigenomics to consider histone variants with as much attention as histone modifications.

      Reviewer #3 (Public Review):

      How chromatin state is defined is an important question in the epigenetics field. Here, Jamge et al. proposed that the dynamics of histone variant exchange control the organization of histone modifications into chromatin states. They found 1) there is a tight association between H2A variants and histone modifications; 2) H2A variants are major factors that differentiate euchromatin, facultative heterochromatin, and constitutive heterochromatin; 3) the mutation in DDM1, a remodeler of H2A variants, causes the mis-assembly of chromatin states in TE region. The topic of this paper is of general interest and results are novel.

      Overall, the paper is well-written and results are clearly presented. The biochemical analysis part is solid.

      Reviewer #4 (Public Review):

      This work aims at analyzing the impact of histone variants and histone modifications on chromatin states of the Arabidopsis genome. Authors claim that histone variants are as significant as histone modifications in determining chromatin states. They also study the effect of mutations in the DDM1 gene on the exchange of H2A.Z to H2A.W, which convert the silent state of transposons into a chromatin state normally found on protein coding genes.

      This is an interesting and well done study on the organization of the Arabidopsis genome in different chromatin states, adding to the previous reports on this issue.

      Reviewer #1 (Recommendations For The Authors):

      1) The rationale for switching from using 10-day old seedlings for chromatin profiling to using mature leaves in Figure 3 and beyond is not explained and introduces additional complexity into the analyses. The reasoning should be clearly explained in the text, and there are several additional suggestions or questions related to this that should be addressed:

      This was done for practical reasons. We had already obtained some profiles of marks in ddm1 mutants and extended the dataset using the same stage of development because this tied this study with our previous study. Using different stages of development provides an additional benefit. The same chromatin states are observed in 10 day old seedlings and leaves of older plants. Constitutive heterochromatin is occupied by the same chromatin states and logically euchromatin is positioned on different genes as expected by the distinct pattern of gene expression at the two stages of development.

      A) In the 16-state model (Figure 3A), euchromatin states were not well defined compared to the 26-state model. Why did the authors not profile these marks also, and could this explain why ddm1 mutants did not show a significant effect on euchromatin states in this model?

      We apologize for the lack of detailed explanation: In our previous study we used leaves of five weeks ld plants to show the impact of ddm1 on the profiles of H2A.W.6, H2A.X, H1, H3K9me2, H3K36me3 and H3K27me3 in leaves (Jamge, Osakabe et al., 2021). This study showed that DDM1 causes the deposition of H2A.W.6 to heterochromatin and we thus used leaves to extend this investigation to the two other marks of heterochromatin (constitutive or facultative) H3K9me1, H2A.W.7 and H2A.Z.9 and H2A.Z.11.

      B) The authors state that the tissue types do not impact the definition of chromatin states. However, there is a clear difference in the portion of the genome occupied by each chromatin state between leaf and seedling (states 1, 5, 8, 13, and 14; Figure S3A).

      We had missed a comment on supFig3B and have now provided more explanation: “Although the composition of the chromatin states did not vary significantly between seedlings and leaves, each state occupied a similar proportion of the genome in seedling or leaves to the exception of state 5 present primarily in leaves and state 13 only present in seedlings (Figure 3 figure supplement 3A, right column with green bars) and the euchromatin states occupied different genes (Figure 3 figure supplement 3B) as expected by the dissimilar transcriptomes of these two developmental stages.”

      2) The naming of supplemental figures throughout the text is confusing as the legends refer to them as "Figure SX" but they are called out in the text as "Figure X figure supplement XA-B". The eLifeconvention is "Figure X figure supplement XA-B".

      This was changed.

      3) In Figure 4, Panel D is mislabeled as C in the figure, and C is lacking a label.

      4) Please remove the word "the" from the title.

      This was done

      Reviewer #2 (Recommendations For The Authors):

      Fig1D legend should also mention K37.

      This was corrected.

      Fig2F legend should say "no H3 modifications" rather than "no histone modifications" This was corrected.

      Fig4 labels C/D do not correspond to the legend. D is missing and C should go to the ddm1 stacked barplot.

      This was corrected.

      H3 variants analysis: Taking the relative abundance of H3.1 and H3.3 (and transgenes) into account would be useful to interpret the results of the nucleosome composition results. If they are at equivalent amounts, the null hypothesis of independent association would give 50% heterotypic nucleosomes and 50% homotypic.

      This is a valid comment. In an ideal system the last statement would be correct, but this does not take into account chromatin dynamics associated with replication, transcription, etc. Also, total amounts of H3.1 and H3.3 in tissue we used for the experiment is not known. It could possibly be inferred from RNAseq data, but if this would reflect real amounts of the protein is highly questionable. In Arabidopsis there are 5 H3.1 genes and 3 H3.3 genes. Nevertheless, we recalculated data for H3.1 and H3.3 and this has been updated in the main text (~60% of H3.1 and ~42% of H3.3 immunoprecipitated nucleosomes contained both H3 variants). Thus, from the available data these numbers are the best we can get.

      p. 5 bottom paragraph. Repetition.

      This was corrected

      p12. The reference to LSH is dropped in without making clear how it is relevant. Expand on mechanism to suggest similar DDM1 mechanism?

      This section was expanded to provide more background in the interpretation of the results.

      p13. inversion between H2A.W and H2A.Z in "the loss of DDM1 prevents the replacement of H2A.W by H2A.Z".

      This was corrected

      p13. make it clear that the last sentence of the results is a working model, not a fully backed up conclusion.

      Alternative models are mentioned in this section and in the discussion in the revised version.

      p14 middle paragraph. Not clear what "in silico simulation" refers to. Simply chromatin-state classification with ChromHMM?

      This refers to the Jacard index calculation in Fig. 2F that models the impact of the loss of H2A variants (or other elements of chromatin) on the definition of chromatin states by ChromHMM. This is now clarified.

      p14 bottom paragraph: the H2A.Z tail repression of ubiquitin ligase but its being the favoured substrate for H2AK121Ub is apparently contradictory. Can this be explained?

      This refers to H2B Ubiquitination and is now clarified

      p15. Correlation between variants and modifications/chromatin states does not necessarily mean causation.

      We agree and have improved the revised version in this respect.

      p15 "forward feedback loop" is ambiguous (is it a feed-forward loop? A feedback loop?), just use "positive feedback loop".

      This was corrected.

      p23 top "$(Ingouff et al)" doesn't seem properly formatted.

      This reference did not belong there and has been removed.

      Data availability: GSE226469 is not public. The manuscript also mentions availability of source data for all the main figures, but I could not find it. It would be great to make the code publicly available too.

      All the data and code will be public upon posting the revised version of the manuscript.

      Reviewer #3 (Recommendations For The Authors):

      My major concern is authors only used DDM1 as an example to show that the exchange of the histone variant contributes to definition and distribution of chromatin state on transposons (i.e., constitutive heterochromatin regions associated with H2A.W). Readers may wonder whether similar mechanisms also work at the euchromatin region. This point should be clearly discussed and mentioned in the Results (for example, cite recent work on INO80).

      We discuss the impact of other remodelers in the Discussion in the revised version. We hope that the reviewer will understand that doing a study on the impact of other remodelers on chromatin states which would require dozens of new ChIP profiles and is clearly beyond the scope of revising a manuscript.

      Minor:

      1) Fig. 2A and 2B, what does color mean? I guess the color code is referred to chromatin states (Fig. 2F).

      We have clarified on Figure 2A the attribution of a specific color to each chromatin state. This same color is used also in other panels of Figures 2 and S2.

      2) Supplemental Figures: All the figure panels should be on the same page.

      We rearranged supplemental figures so that each figure fits on one page. In places where this was not possible, we created additional supplemental figures.

      3) "We observed that increasing state numbers from 26 to 27 gave rise to biologically redundant states.": Where are the data? Fig S2A? This figure is hard to understand.

      In the updated manuscript, we have described the legend and the methods for FigS2A in more detail.

      Reviewer #4 (Recommendations For The Authors):

      A general concern refers to the text that frequently falls into excessive oversimplifications and/or overstatements, with the danger of being misleading for the reader. This needs to be thoroughly revised.

      We added more careful statements and proposed alternative models when it was possible.

      Specific comments.

      1) Fig 1A. Authors found the ~40% of nucleosomes contained both H3.1 and H3.3. This is a significant finding that deserves a more detailed comment.

      We now provide a more detailed description of IP and MS data presented in Figure 1. This should also help to avoid oversimplifications and/or overstatements as criticized in a general comment.

      2) Fig 1C. "H3. And H3.3 bore the same sets and comparable levels of methylation and acetylation...". Too general statement, please specify. Is this also the case for H3K9me2? Others?

      We did describe this part into more detail to emphasize more precisely what Figure 1 shows. We also included data on K9me into Figure 1 figure supplement 1H.

      3) Fig 1D. Could you confirm the high level of H3K27me1 on H3.3?

      H3K27me1 data are shown both by WB (Figure 1C) and Mass spectrometry (Figure 1D and E). We also provide a possible explanation for high levels of this mark on H3.3 by taking into account the fact that H3K27me1 is also produced by demethylation of H3K27me3 by JMJ demethylases.

      4) All WB in Fig 1. They need to be quantified and normalized (plus statistical analysis) in order to provide strong support to the conclusions.

      The conclusion of all WB are supported by quantified Mass spectrometry data and many WB were even repeatedly shown in Figure 1F (for example IPs for H2A variants and a large set of H3 marks used for WBs) with the same results. Also, association of H3K4me3 and H3K36me3 with H2A variants was analyzed in both ways (Figure 1F); IPs of variants and WBs of variants and marks and IPs of marks and WBs of marks and variants. For most of the data we do not have more than two repeats, so statistical analysis may not be possible.

      Nevertheless, we are convinced that our major conclusions from data presented in Figure 1 and Supporting figure 1 (these are: that H3 variants form both homotypic and heterotypic nucleosomes, that H3 marks do not preferentially associate with H3 variants but some of them do so with H2A variants and that H3 modifications show very complex pattern of associations with each other) are fully valid as they were drawn from two orthogonal approaches and further supported by the chromatin states identified.

      5) Fig. 2A. Authors focus on "the most parsimonious model" based on 26 chromatin states. This needs to be justified in a more explicit manner. It is surprising that this number emerges for an analysis of 27 independent variants and marks. What are the differences in the conclusions when other number of states are used? See also below (reduced number of number derived from the "concatenated model").

      Why 26 states were chosen is now explained in great details in the method section. Since to the exception of H2A variants that are invariably homotypic, nucleosomes can be heterotypic for all other histone variants and histone modifications, the random combination of the 27 marks in one nucleosome representing one states is 4 H2A (without the subtypes) x 4H3 x 2H1 x 2(power16) (for each mark) which is well above the circa 26 states observed. This shows that our probabilistic model reduces the potential complexity of a theorical random association in a remarkable manner.

      6) As a summary, it would be very helpful to generated a table (or similar) where is proposed chromatin state is ascribed to functional genomic elements.

      This aspect of the work is presented in a preprint where the biological association with the chromatin is described in details. See Jamge et al 2002, https://www.biorxiv.org/content/10.1101/2022.06.02.494419v1

      7) Fig 2F (and S2B). A comprehensive comparison a various approaches should include others and estimate the Jaccard similarity index: (1) the same of marks and variants used in the Sequeira-Mendes et al paper, and (2) the subset of marks and variants added in this study. In this way, a direct evaluation of the contributions could be more properly made.

      We thank the reviewer for this suggestion and have now included a new column with the combination of marks and variants as used in Sequeira-Mendes et al., 2014 (see Figure 2F). These data clearly demonstrate that adding histone variants significantly contribute to the definition of chromatin states.

      8) Fig. 3. Explain in more detail the concatenated model used here. Does the reduction in the number of chromatin states mean that the other do not add new information?

      ChromHMM concatenated model allows to identify common definition of chromatin state in multiple tissue types. Here multiple cell types are concatenated leading to a shared definition of chromatin states, but specific to each cell type.

      In our paper we used the concatenated model to identify common chromatin states in two different genotypes (WT and ddm1). The data for WT and ddm1 was obtained from leaves. As we had a limited number of ChIP-seq profiles in the leaves dataset The complexity of the concatenated model was also reduced compared to the extensive 26 chromatin state model. We chose to analyze 16-states in the concatenated model because this was the minimal number of states that gave rise to a similar complexity of heterochromatic states.

      9) The ddm1 mutant. The text in page 14 is a bit confusing. It seems that H2A.Z is deposited on TEs and the exchanged by the H2A.W.

      We have provided additional alternative models that could explain our observations.

      10) Page 15: link between H2A.Z and H3K27me3. Gomez-Zambrano et al (2018, cited in the text, found that only a relatively small subset of (putative) targets are common to H2A.Z and H3K27me3. How do authors reconcile this with their statement supporting a link between both of them?

      We refer to Gomez-Zambranao et al to illustrate the link between H2A.Z and H2AK121ub so we do not understand this comment. The strong link between H2A.Z and H3K27me3 is shown without ambiguity by our work and also Carter et al., 2018.

    1. Step 4: Action It’s important to remember that the first three steps provide a foundation for the action stage. Quitting cold turkey just moments after watching a documentary about the dangers of smoking works for some – but it’s not guaranteed that everyone will successfully quit smoking that way. Precontemplation, contemplation, and preparation are extremely important steps. After all, you have to want and know that it’s time to change.

      .

  3. Jun 2023
    1. The author, Rediscovering Analog, reads a book at least twice, usually. He first reads it mainly for pleasure, just to enjoy it and to see what's in it. During the second time, if applicable, he goes through the book using intellectual (or learning) systems and methodologies to extract value from the book.

      The first pass, which the author terms Scouting, is thus namely for enjoyment, but keeping in mind what might be valuable or interesting that will be valuable in the future, basically an unguided open ear. He has a list of scouted books in each section of the Zettelkasten that might be relevant to the section. What he does is have a stack of physical cards there with just the name of the book and the author, without anything else. Then when author proceeds to extract value from the book, he takes the card out and puts it in the respective book. Afterwards throwing this particular card into the trash. It's a form of the Anti-Library.

      ( Personally, I would include an appropriate reading cost and a level on Adler's hierarchy of books. In addition, I would make sure that my process of orientation, in the Inquiry-Based Learning framework, has been completed before I put it as a book within the Anti-Library. )


      This may not be the most efficient for the purpose of acquiring value, but efficiency is not all there is. Enjoyment is a big part of intellectual work as well, as Antonin Sertillanges argues in his book The Intellectual Life: Its spirit, methods, conditions, as well as Mihaly Csikszentmihaliy in his book Flow.

  4. evergreen0-my.sharepoint.com evergreen0-my.sharepoint.com
    1. three different approaches to using digital con-tent curation tools in a first-year composition course that heteaches: clipping, tagging, and annotating (p. 178). Clippingrefers to the moment when you find something from theweb and save a portion of it as a clip rather than the wholepiece; tagging is adding a user-defined label or short phraseto something; and annotating is adding longer notes to atext.

      I already do this, I think it's freeing to not hold myself to a high standard each time something stands out, it can just be a passing note that something caught my eye or a small connection or coincidence.

    1. Fragmented runtimes While pretty much every single one of these problems could be fixed by either extending the specific runtime you’re using or by ECMA releasing a new standard, it’s just not that simple. Assuming you extend the runtime you’re using to allow for things like native/fast arrays and you define a module/namespace solution like node.js has done, now any code you write will only run on that specific runtime with your extensions which punches a big hole in the “same language everywhere”-argument that you hear every day on twitter (and it really is server-side JavaScript’s only claim to fame).

      In other words, the "problem" is the opposite of "fragmented runtimes"—it's that JS runtimes are so strictly committed to compatibility at the language level (to a degree not seen in any other widely deployed tech that I can think of). There are clear downsides (such as the sentiment expressed here), but there are also massive upsides. On net, the alignment is a huge win.

    1. With all the external push from various sectors, ultimately teachers are the ones that can cut through all of the cross-purposed mandates and transform their own process and practices to ensure the best educational experiences for their students.

      It's so easy to feel powerless in the fact of district and school mandates, and I find myself oscillating between feeling prepared to do what I believe the research tells me I should and thinking maybe I should just be going along with what I'm told even if I truly don't think it's what's best for my kids. This is an empowering reminder that I am a professional with a voice and I need to use it (and teach my TCs to use it too!)

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      We thank the referees for their interest, comments and advice on our manuscprit. The reply to the reviewers follows the revision plan proposed Review Commons.

      1. Description of the planned revisions

      R#1 major comments :

      R#1 raised three major points relative to quantitative data. For the two first, we have optimized our quantification methods, as explained in the next section, which clearly improved the results, but some data still have to be re-analyzed for figures 5,6,7.

      For the third one, here is the comment and our proposed additional experiments to answer it :

      c) Quantifications of lateral fraction Col IV in mosaic experiments do not support decreased lateral secretion in Rab8 OE (3G) or Dys- (S5C), which are central tenets of the study. “

      We have endeavoured to detect such differences in Dys mutants and Rab8 OE and do not see any possible improvement in the quantification method and therefore propose, instead, additional experiments.

      With respect to Rab8 OE, we suspect that this gain of function is not sufficiently effective under the specific conditions of the experimental setup described in Figure 3, as its effect appears to be more subtle than that of Rab10 OE in Figure 2. We therefore propose to repeat this experiment on a sensitised background in which Rab10 function is partially affected. Unpublished data indicate that this downregulation of Rab10 is not sufficient to induce significant differences in this experimental setup. However, based on the genetic interactions described in the other figures, an additive/synergistic effect between rab8 OE and Rab10 KD can be expected, which would allow to confirm the involvement of Rab8 in basal secretion.

      With regard to Dys mutant, we considered another possible explanation for this observation, namely that DAPC could affect the secretion of other BM proteins but not that of collagen IV. It should be noted that Perlecan and LamininA, which are also found in BM fibrils, are ligands for Dystroglycan, which is not the case for collagen IV. Unfortunately, there is no existing transgene with a UAS promoter and a tagged version of these proteins that would allow this hypothesis to be tested within a reasonable timeframe using the same method as that described in Fig.3. Therefore, we propose an alternative approach that would determine whether the secretion of endogenous laminin and/or perlecan is affected by Dystroglycan overexpression (i.e. secreted more laterally) and test whether this effect is Dys-dependent. It should be noted that this hypothesis would be fully consistent with all our data and in particular with that shown in Fig. 5.

      R#2 major comments

      From the data presented in Figure S1B, the authors state that the basement membrane mislocalization observed in Rab8/10KD has no major impact on polarity maintenance. They based this statement only on the localization of the apical marker aPKC. Although the aPKC data are convincing, it would be more compelling if the authors observe the distribution of other polarity proteins such as Dlg, E-Cadherin, and armadillo to better assess if the overall epithelial polarity is maintained in this condition.

      We will complete fig S1 and perform ECad and Dlg staining to provide a better description of apical-basal polarity in the different Rab knock-down conditions.

      R#3 comments

      Results Figure 4

      The authors suggest basal Rab10 expression domain near the Golgi exit point. Can the authors use a Trans-Golgi marker in order to confirm this statement other than the references stated?

      Such a staining will be included in the final version with for instance golgin245 staining.

      2. Description of the revisions that have already been incorporated in the transferred manuscript

      R#1 major comments :

      a) Rab8 KD does not significantly increase apical fraction of Collagen IV with respect to control (Fig. 1H). The image in 1C clearly shows that Col IV is present apically, something that has been shown by others and that never occurs in the wild type. Failure of the quantifying method to detect a difference can only mean the quantifying method is not adequate. A 10% average in the control when it's clear that no Col IV at all is found apically in the wild type suggests that the authors are quantifying background signal that they should not be acquiring, and, if acquired, they should be subtracting Rab8/Rab10 double knock down is said to show a synergistic effect, when an additive effect would be more consistent with alternative routes. Other problematic deductions drawn from apical fraction quantifications are found in Fig. 5J (Dys- enhancing Rab8 KD but not Rab10 KD) and Fig. 7D (Exo70- enhancing Rab10 KD but not Rab8 KD)

      We agree that this quantification was not optimal. We improved it by quantifying a narrower and more precise region for each domain. The new results are shown in Figure 1H. This improvement reduces the apical signal in the control from 10% to 6% and allows us to detect a significant increase between the control and Rab8 KD, thus resolving the problem raised. After verification, we did not subtract the background because there was no electronic background in our images (i.e. black is really black and equal to zero). Thus, the remaining signal is the true cytoplasmic GFP signal and it may not be appropriate to subtract it. Other data (fig 5J and 7D, now named fig 5L and 7H) were also re-analyzed with no major change.

      b) Similar to apical fraction, measurements of planar polarization (trailing/lateral ratio) show average ratios near 1 for Dg, Rab10 and Dys, which is striking given that the localization of these proteins is so clearly polarized. Ratios lower than 1, which are reported for many individual cells in these graphs, should mean reversed polarity. In light of this, I would not be too confident on the effects reported in 5O-Q. In fact, on two occasions, the authors obtain significant differences in these planar polarization measurements that they themselves disregard: Fig. 6J (Rab10 in Exo70-) and Fig. 7I (Dys in Rab8 KD).

      We agree that this quantification could be improved. Our initial quantification of the planar polarised proteins, Rab10 and Dys, found at the trailing edge, was confounded by their lateral spread. We have now reported with only the front half of the lateral side. By doing this in Figure 5, we increase the ratio in the control conditions, with almost no points below the value of 1, while the conditions in which polarity is visually affected are unchanged and still close to 1. We did not have time to re-analyze all the data (Figures 6 and 7), but will do so in the final revised version.

      R#1 minor comments :

      All the minor points raised by R#1 have been addressed by changes in the main text and/or the figures with the exception of the following :

      • Fig. S1B does not seem to make a significant point in the context of this study.

      Although we understand this comment, we followed suggestion of R#2 who asked in its major comments for more details with other cell polarity markers. These data are not yet included but will be generated for the fully revised version.

      • I suggest drawing a summary scheme to aid readers better assess interpretations alternative to the ones given in the text.

      While we will be happy to provide such a scheme in the final version, we prefer to wait for the results of the proposed complementary experiments to be as accurate as possible.

      R#2 major comments

      In the text for Figure 1G-H (page 4), the authors stated that the basal secretion was not restored in Rab8, 10, and 11 triple KD, in our opinion, it is unclear how the authors came to this strong conclusion from the presented data. It would be good if the authors explicitly explain how they come to this conclusion. Is it only based on the weak Coll-IV-GFP signal in the Rab8, 10, and 11 triple KD data compare to the control? If so, the authors should statistically quantify the difference with the control. In Figure 1H, no statistical analysis is provided between the control and triple KD conditions.

      We agree that it was not entirely appropriate to give such conclusions on the basis of the quantifications available. A new graph showing basal fluorescence intensity (new Figure 1H) (and not just the ratio of apical to apical plus basal as in Figure 1I) has been added to better support the text. A relevant statistical comparison has been added to Figure 1H (old Figure 1I). We apologize for this oversight.

      R#2 minor comments :

      We took in account all these comments and changed accordingly the text and the figures

      R#3 comments :

      Results figure 1

      The authors use RNAi lines to arrive at their conclusions, however, the extent of inhibition of gene expression achieved by the RNAi, has not been justified. Also observations from only one RNAi stock may not be completely conclusive:

      i) Efficiency of RNAi has not been tested or shown. No supporting data. Rab10-RNAi stock is 26289 BDSC which is in Valium10, which is a weak RNAi line and needs a Dicer.

      ii) Can same observations be made using classic alleles or generate somatic clones on follicular epithelial cells?<br />

      R#3 raised several questions regarding the efficiency of RNAi, the use of different lines and/or the use of classical mutants as an alternative method.

      For Rab10, we tested three different lines with similar results as shown now in Figure S1A-B. These data are also consistent with those obtained by overexpression of a dominant-negative form of Rab10 (Lerner et al, 2013). Unfortunately, Rab10 is located extremely close to the X chromosome centromere and is even more proximal than the FRT transgenes. It is therefore impossible to generate somatic mutant clones.

      Regarding Rab8, it is already published that Rab8 RNAi, expression of a dominant-negative form of Rab8 and Rab8 mutant cells obtained by somatic clones give similar defects (Devergne et al, 2017). The text has been modified to better illustrate the available data validating our approach.

      In addition, mutant clones would not allow analysis of genetic interactions in complex genetic contexts such as double and triple KDs. Similarly, the choice of the Rab10 line was motivated by the ease of obtaining the appropriate genetic combination according to their genomic location.

      iii) Intensity of Collagen IV in the basement membrane in Rab11 knock-down mutants seems to be significantly low as compared to the Rab8 and Rab10 knock downs in supplementary Fig 1B. Are the authors very sure that Rab11 has no functions in basement membrane basal organization?

      Good catch! Indeed, Rab11 RNAi significantly reduces basal secretion as now shown on fig 1H. Rab11 has pleiotropic functions in epithelial cells notably for their polarity (Choubey and Roy, 2017, Fletcher et al, 2012…) and, accordingly aPKC is partially disrupted in Rab11 RNAi conditions (Fig S1). Thus, the reason for such a decrease is unclear and could be an indirect consequence of an overall abnormal epithelial structure. Thus, we now report this observation but have not taken its interpretation too far.

      iv) Authors need to show where and how fluorescence intensities have been measured.

      Magenta rectangles with dashed lines on figure 1A illustrate the ROIs used for this analysis and more details have been added in the ‘experimental procedures’ section.

      Results Figures 2 and 3:

      Texts and figures have been modified as suggested.

      Results Figure 4 :

      The authors suggest a UAS-Rab10-RFP transgene show same results as endogenous Rab10-YFP as compared to spatial expression pattern. This is worrisome as expression of full length functional gene tagged with a fluorophore may be an overexpression. A control experiment would be helpful in suggesting/comparing with the Rab10 OE phenotype and that will be more convincing.

      We are not sure that we fully understand the reviewer's comment. However, we initially compared endogenous Rab10 and UAS-RAB10 at 25°C, a temperature at which the latter has no visible impact on BM structure (Cerqueira-Campos et al, 2020). Furthermore, even when higher expression was induced (by increasing the temperature and therefore Gal4 activity) and this had an impact on BM structure, this did not change the subcellular localization of Rab10, i.e. it was still planarly polarized, as shown in Fig 5S. The text has been modified to emphasize this point.

      Result Figure 5

      The authors may provide a Rab10 expression profile in DAPC null or KD mutants which would make their claims more comprehensive.

      Data showing Rab10 localization in Dys mutant cells were already shown on Figure S5A-B. Of notice, we also tried similar experiments using RAB10 knock-in line. However, for unexpected reason, having one copy of the chromosome with YFP insertion in Rab10 strongly enhanced DAPC mutant phenotypes in terms of F-actin orientation and follicle elongation ((as described in Cerqueira-Campos et al, 2020). We therefore considered these data as inappropriate.

      General comment

      In general some immunostainings should be carried out if not in all at least in some experiments with some cell domain specific markers, more specifically PCP markers such as Flamingo/Vangl and basolateral markers such as Lgl/Dlg. This makes the positions specific claims of the authors more valid in the eyes of the reader.

      We agree that this may help the reader but the pcp markers mentioned are not expressed in this tissue. However, the tissue planar orientation is now systematically indicated and consistent in all figures. We did not generally perform immunostaining for lateral markers but routinely included F-actin staining to detect cellular cortex. Our quantifications or cortical segmentations were based on the cell outline provided by this stain. On the basis of this staining, the outline of the cells was added on certain figures to facilitate understanding of the images.

      3. Description of analyses that authors prefer not to carry out

      R#3 comments :

      Result Figure 6 :

      Exo 70 is a versatile molecule and Rho kinases such as Cdc42 can direct Polarised exocytosis through interaction of Rab effectors with Exo 70. Have the authors considered this?

      We agree that it is an interesting prospect, but we consider it as beyond the scope of this article.

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript by Dennis et al. reports a study of the polarized secretion of basement membrane Collagen IV in the Drosophila (fruit fly) follicular epithelium. Using genetic manipulations and confocal imaging, the authors show that Rab-GTPases Rab8 and Rab10, both known to be required for proper basal secretion of Collagen IV (work by the labs of Sally Horne-Badovinac and Trudi Schupbach, respectively), mediate two alternative secretion routes: Rab8 mediates basal-most secretion of soluble Collagen IV that is incorporated homogenously into the basement membrane, whereas Rab10 mediates basal-lateral secretion of Collagen IV that produces insoluble fibers. The authors additionally study the relation between Rab10 and Dystroglycan/Dystrophin (Dystrophin-associated protein complex, DAPC), which they previously showed to be essential for fibril formation (Cerqueira-Campos et al., 2020). They show here that Dystrophin and Rab10 colocalize at the basal trailing side of follicle cells and that overexpressed Dystroglycan can recruit Rab10 to the plasma membrane; however, they also show that Dystrophin mutants fail to display an effect on Rab10 localization, leaving the significance of the proposed Rab10-DAPC interaction unresolved. Finally, the authors present convincing evidence that the exocyst complex opposes fibril formation, and suggestive but comparatively weaker results pointing that this opposition is due to two independent separate exocyst roles: an inhibitory interaction exocyst-Dystrophin (Dystrophin being required for fibril formation), and a positive role in the alternative Rab8 non-fibril route.

      Major comment:

      • There are several instances throughout the study in which the authors seem to have problems quantifying results. This affects some assertions central to the message of the paper that are not supported by the quantifications presented. It also casts doubts on accessory points deduced from quantitative differences (or lack of difference) that do not seem fully reliable. I would urge the authors to reevaluate their quantification methods.

      a) Rab8 KD does not significantly increase apical fraction of Collagen IV with respect to control (Fig. 1H). The image in 1C clearly shows that Col IV is present apically, something that has been shown by others and that never occurs in the wild type. Failure of the quantifying method to detect a difference can only mean the quantifying method is not adequate. A 10% average in the control when it's clear that no Col IV at all is found apically in the wild type suggests that the authors are quantifying background signal that they should not be acquiring, and, if acquired, they should be subtracting. Rab8/Rab10 double knock down is said to show a synergistic effect, when an additive effect would be more consistent with alternative routes. Other problematic deductions drawn from apical fraction quantifications are found in Fig. 5J (Dys- enhancing Rab8 KD but not Rab10 KD) and Fig. 7D (Exo70- enhancing Rab10 KD but not Rab8 KD).

      b) Similar to apical fraction, measurements of planar polarization (trailing/lateral ratio) show average ratios near 1 for Dg, Rab10 and Dys, which is striking given that the localization of these proteins is so clearly polarized. Ratios lower than 1, which are reported for many individual cells in these graphs, should mean reversed polarity. In light of this, I would not be too confident on the effects reported in 5O-Q. In fact, on two occasions, the authors obtain significant differences in these planar polarization measurements that they themselves disregard: Fig. 6J (Rab10 in Exo70-) and Fig. 7I (Dys in Rab8 KD).

      c) Quantifications of lateral fraction Col IV in mosaic experiments do not support decreased lateral secretion in Rab8 OE (3G) or Dys- (S5C), which are central tenets of the study.

      Minor comments:

      • It is stated that Rab10 and Dys associate with tubular endosomes, but no data here support identification as endosomes of these tubular structures, to my understanding.

      • The authors call sup-basal the cell region immediately apical to the most basal. Is there sufficient reason to not call this lateral? If a new term is needed, shouldn't it be supra-basal?

      • In Fig. S1A and B, Col IV is labeled as green but represented in cyan.

      • Fig. S1A should present a wild type control.

      • Fig. S1B does not seem to make a significant point in the context of this study.

      • Fig. 3C'-E' label suggests a gradient made from multiple images, but it looks like just two images and two colors.

      • Graphs in Fig. 3H-J, S5D and 7B are not legible.

      • It is not clear where Y2H results in Fig 6A come from.

      • I suggest drawing a summary scheme to aid readers better assess interpretations alternative to the ones given in the text.

      Significance

      This study reports important new information on the secretion of Collagen IV by polarized cells of the Drosophila follicular epithelium. It complements previous studies on the roles of Rab8, Rab10 and Dystroglycan/Dystrophin, additionally uncovering a role for the exocyst complex. Addressing some issues with quantitative imaging should increase confidence in its most critical conclusions.

    1. “The supreme reality of art,” he wrote, “is the isolated, self-contained work.”

      I think this is what makes art so special. It's just an expression of the artist, and the only thing that the viewer of the art can do is interpret it.

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      Reply to the reviewers

      Reviewer #1

      Major:

      - The statement (line 149'Together, our data suggest that systemic ecdysone levels are unlikely to be involved in modulating tumour-induced muscle detachment or to mediate the role of fatbody Insulin signalling in regulating muscle detachment.') is derived from an experiment with sterol free diet (in which 20HE is genetically addressed) and a pleiotropic experiment (PG>RasG12V). In neither paper nor the current manuscript, 20HE levels have been directly addressed.

      Therefore, this statement needs further experimental support and discussion. Ecdysone is a critical hormone during development and especially growth-related effects central to this study. The authors should consider doing pharmacology or augment their claims here with genetic manipulation experiments of 20HE related genes in larvae (Leopold, Rewitz, Rideout, Drummond-Barbosa, Schuldiner labs) and adult animals using genetics, pharmacology or direct assessment of 20HE levels (RIPA, Edgar and Reiff labs).

      The main point we were trying to convey is that we do not think global ecdysone levels plays a role in modulating fatbody insulin or tgfb signalling, which in turn affects muscle detachment. We are not claiming that edysone levels is not changing in control vs. tumour bearing animals. In fact, we predict that 20HE levels will be different in tumour bearing vs. control animals (as tumour bearing animals undergo developmental delay), but this is not the main point of our conclusions. We believe that our conclusions are supported by the experiment demonstrating global ecdysone alterations (via feeding sterol-free food) did not affect how fatbody Akt activation altered tgfb signalling and enhanced muscle integrity (Figure S1). Therefore, we don’t think measuring 20HE helps to support our conclusions. Pharmacological inhibition via feeding ecdysone inhibitors effectively demonstrate a similar point to feeding sterol-free food which we have already performed. We are happy to try direct manipulation of 20HE related genes (eip75B-RNAi) in the fatbody to see if this affects muscle detachment or pAkt and pMad levels in tumour bearing animals.

      - In Fig.7 the authors used a sog-LacZ stock to show transcriptional activation in fatbody cells. This stock is based on P-element insertion in the according regulatory regions and supposed to express lacZ with an nls. I can clearly see lacZ in nuclei in Fig. 7H, whereas this is very hard to see in nuclei in Fig7i in the tumour model. In addition, lacZ is known for its high stability and not the best option. As this finding is vital for central claims of this study, it should be complemented by either qPCR for sog on fat body cells or using another readout by converting one of the two Mimic lines (BL42189/44958) into GFP sensors for sog.

      We will add a counterstain to these images. We will also perform qPCR in the fatbody of control and cachectic animals to assess whether Sog transcription is altered. We agree converting one of the Mimic lines to a GFP sensor would be a good option, but this experiment would require getting new fly lines into Australia, which takes at least 2 months because of quarantine laws. We don’t believe this experiment would change the general conclusions of the paper, therefore would prefer not to do this experiment.

      - I have similar problems with Fig.7B-F, as phosphorylated Mad should be translocated to the nucleus. In 7F the authors measure pMad over Dapi, which is the right way but it is hard to see pMad in the nucleaus apart from Fig7B, wheras in D and E, where the authors measure higher levels, I cannot identify clear pMad in nuclei. These images either need to show the Dapi channel or more representative images should be chosen like in Fig.4 with arrows pointing to measured nuclei. Fig.7C something went wrong with the compression of this image.

      We will show more representative examples and fix Fig 7C.

      - The proper function of RNAi stocks targeting genes like sog, mad, etc. is vital for this study as these lines are used throughout the study. Functional evidence of specific knockdown efficiency should be provided or references given in which these stocks were shown to provide functional knockdown on transcript or protein level.

      We agree with the reviewer that this is an important point. We will demonstrate the knockdown of sog and mad (and other RNAis) used in the study by either referring to published data or demonstrate knockdown ourselves.

      - Fig.S7 discusses appearance of gbb/Bmp7 and Sog/CHRD in human patients. The analysis the authors performed shows a correlation between both factors, but is hampered by the fact that datasets for peripheral tissues of cachexia patients are unavailable. The authors may consider sorting these after tumor entities in which cachexia occurs frequently vs. low occurrence and then check for both genes.

      We will try this analysis.

      Fig.5 M-P pMAd is not indicated in the Panels only the legend.

      We will fix this error.

      - Please follow FlyBase nomenclature, e.g. dlg1 for discs large 1 and unify in the whole manuscript and figure for all genes.

      We will fix this error.

      - For endogenous fusion proteins like Viking-GFP (e.g. vkg::GFP) choose a format to clearly decipher them from transcriptional readout stocks like sog-lacZ.

      We will fix this error.

      - The quantifications in most figures are quite small with tiny lettering and XY axis are difficult to read in letter/A4 size.

      We will enlarge font size.

      Minor:

      1. Adjust in-figure caption alignments

      2. Line 104: add comma RasV12, dlgRNAi

      3. Line 114: replace little  not significant (n.s.)

      4. Line 334: 'sogRNAi overexpression' to my knowledge, RNAi are expressed, not overexpressed.

      5. Line 454: italicize r4>

      6. Fig S4E: remove frame

      7. Figures 6: It would be better to number and explain the pathway presented in the figure in text and fig legend.

      8. Just a personal preference. Lettering of images in images is commonly done horizontally, here it appears like a mix between vertical and horizontal.

      We will fix these minor errors.

      Reviewer #2

      Major comment

      Their genetic experiments clearly showed that the reduction of insulin signaling activity in the fatbody induces upregulation of TGF-β signaling and Collagen accumulation. Then, how does TGF-β signaling induce Collagen accumulation?

      From the experiments we have carried out, we do not have insights into how TGF-B signalling induce Collagen accumulation.

      They showed that Rab10 knockdown and SPARC overexpression reduced the accumulation of fatbody ECM. Are Rab10 and SPARC expression regulated by TGF-β signaling?

      We can address this point by assessing if Rab10 and SPARC expression is altered in cachectic fatbody.

      Minor comments

      Line 90: "Disc Large (Dlg) RNAi in the eye" must be "Discs Large (Dlg1) RNAi in the eye imaginal discs".

      we will fix this error.

      Figures 1D and 1L are from the same image. Also, Figures 1C and 1M are from the same image. Are both of them necessary to be shown in the different panels?

      The duplication of 1C and 1M, was an error, we thank the reviewer for picking this up. We will fix this error. We will use different images for 1D and 1L.

      Why are the staining patterns of anti-pAkt shown in Figures 1L and 1U so different? pAkt is not detected in the nuclei in Fig. 1L but its nuclear signal is clear in Fig. 1U.

      We will show more representative images of these staining.

      Figure 1: Images of counter staining for nuclei like DAPI should be also included for all these fatbody images.

      We will show counter staining for DAPI.

      Line 101: "Tumour specific ImpL2 inhibition was sufficient to reduce fatbody pAkt levels." Is this correct? ImpL2 inhibition in tumors should elevate the pAKT level in fatbody.

      This was a mistake, we will fix this error.

      Figure S1~S4: These figures and their legends do not correspond to each other. We thank the reviewer in picking up this error, there was an error in inserting the images into the text. S2 and S3 were swapped.

      We will fix this error.

      Line 189: The pAkt level in the muscle of tumour-bearing animals should be examined to confirm the activity of the insulin signaling is downregulated.

      We will include this data.

      Line 189: If the authors conclude that muscle insulin signaling predominantly regulates translation and atrophy, OPP assay for the muscle cells should be examined in the same experimental settings.

      We will carry out OPP assay upon Akt overexpression in the muscle.

      Line 247: The expression level of Rab10 and SPARC should be examined in the fatbody of tumour-bearing animals to see whether Rab10 is upregulated and SPARC is downregulated.

      Line 247: If Rab10 upregulation and SPARC downregulation are the causes of the accumulation of ECM proteins in the fatbody of tumour-bearing animals, how the overexpressed Collagen proteins can be secreted from the fatbody cells?

      We are not sure, but the overexpression of Collagen proteins is at an extremely high level, therefore, it is possible that some of it can be processed and secreted despite Rab10 upregulation and SPARC downregulation. We have carried out an experiment to overexpress Collagen proteins in the muscle, in this case, this manipulation did not rescue. This indicates that processing of Collagen in the fatbody is important, however, we do not know how the processing is regulated.

      Line 347: Sog is a secreted BMP antagonist. Thus, it can be expected that the Sog overexpression downregulates TGF-β signaling in fatbody and muscle tissues. If the rescued phenotypes with Sog overexpression can be explained by this logic, pMad level should be examined in these experiments.

      We have shown this data in Figure R-T. We will refer back to this data in Line 347.

      Reviewer #3

      Major comments:

      - Are the key conclusions convincing?

      Most of the conclusions are convincing. It is not clear however whether the ECM accumulation in the fat body of tumor animals is fibrotic and whether it is extracellular or in the cell cortex.

      - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      -The authors state in line 71 'This deposition of disorganized ECM leads to fibrotic ECM

      accumulation.' The authors haven't really provided evidence for the ECM being fibrotic. The authors could either rephrase this or provide additional experimental evidence of fibrosis in the fat body.

      We will tone down the claim that the ECM accumulation is fibrotic.

      - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

      -The authors state in line 147" Finally, in tumor-bearing animals fed a sterol-free diet, that underwent a prolonged 3rd instar stage due to reduced ecdysone levels (Parkin and Burnet, 1986), we activated insulin signalling in the fatbody via Akt overexpression (QRasV12, scribRNAi). We found that this manipulation caused a significant decrease in pMad levels in the fatbody and a rescue of muscle detachment (Figure S1 D-I), similar to animals fed a standard diet (Figure 1 O-Q, Figure 2 F-H)." Since it's not already known what the extent of muscle integrity defect there is in tumors with additional sterol free diet, it would be important to show a non-tumor control for comparison in FigS1F. This would also then make it clear to what extent the defect is rescued by Akt overexpression.

      We will include a non-tumour control for Fig S1F.

      -The authors state in line 158 'Upon the knockdown of Impl2, we found that tumor gbb was not significantly altered (Figure S3A).' Even though this shows an indication that Gbb levels are not reduced, the n number is too low to state that it is non-significant. The authors should increase the n number here.

      N=3 is generally enough to see a difference, we will include data done in parallel which shows Impl2 RNAi is sufficient to induce a reduction in Impl2 RNA levels. This will demonstrate that n=3 is sufficient to demonstrate a reduction in transcript levels if there is a reduction.

      -The authors state in line 171 'Conversely, knockdown of gbb alone or knockdown of gbb together with ImpL2 significantly rescued the Nidogen overaccumulation defects observed at the plasma membrane of fatbody from tumor-bearing animals, while ImpL2RNAi alone did not (Figure S2 Q-U).' This is a somewhat misleading representation, since again no non-tumor control was used, so the extent of the rescue by gbb knowdown is not obvious. In FigS2P Nidogen levels in the tumor seem ~100% higher than in control. But in FigS2U, in which no control was included, the tumor+gbb knowdown seems ~ 20% lower than tumor. So it is probably a more moderate rescue, but that's only possible to assess by including a non-tumor control in FigS2U. Also the images in FigS2Q-T don't seem representative since they appear to show a much bigger difference in fluorescence intensity than ~20%. Please show more representative images.

      We will include a non-tumour control for S2Q-T and show more representative pictures.

      -The authors state in line 174 'Finally, co-knockdown of gbb and ImpL2 in the tumor significantly rescued the reduction in OPP and Nidogen levels observed in the muscles of tumor-bearing animals (Figure S3 B-I).'

      Again, the single knockdowns and the non-tumor control are not shown in FigS3E and I and should be included for comparison and to see the contribution of each knockdown and to be able to judge the extent of the rescue.

      We will include the single knockdowns and a wildtype control

      -Regarding Fig3O: Is there a significant tumor muscle attachment defect here? In this graph the tumor only looks about 10% lower than the WT (rather than 40% in Fig2E). The other issue is the extremely low n number for WT. I would recommend increasing the n number for WT here and to indicate in the graph whether the tumor is significantly different to WT (or non-significant, in which case RabRNAi wouldn't actually 'rescue' the defect). In the present form, this graph is not very convincing.

      We will increase the n number for WT for this experiment. The reduction in muscle detachment is 10% rather than 40% here is because this experiment was done at day 6, which we will indicate in the figure legend. The 40% reduction in Fig2E is because these samples were processed at day7. Rab10RNAi experiment was carried out at day 6, because by day7, the Rab10RNAi rescue is so good, most of the tumour bearing animals have pupated, thus the experiment could only be carried out at day6.

      - Regarding Fig3W: A non-tumor control would be important to include to be able to judge the extent of muscle attachment defects and the extent of the rescue for UAS-Sparc. This will allow to assess the severity of muscle integrity defect in this particular experiment (since it appears to vary in different experiments e.g. muscle defect in tumor 40% in Fig2E and ~10% in Fig3O) and to assess the extent of rescue for the various genotypes.

      We will include a non-tumour control for 3W.

      -The authors show an accumulation of ECM in the fat body of tumors. It is not clear, whether this ECM accumulates intracellularly near the cell surface or extracellularly. The authors should assess this, maybe by doing electron microscopy.

      We do not have an EM facility that can accommodate this experiment, thus doing EM is not an option for us. However, we can address whether the accumulation of ECM is intracellular or extracellular by performing an experiment, where we try perform antibody staining against Viking-GFP without permeabilizing the cells. If Viking is detected without permeabilization, it would indicate the accumulations are extracellular. This approach has been previously used to address this question in Zang et al., elife, 2015.

      - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      -These suggested experiments should be quite straightforward since they are mostly just repeating previous experiments with the appropriate controls and n numbers. I would think that they can be done within a few months. The electron microscopy should not take more than a few weeks and not be costly.

      - Are the data and the methods presented in such a way that they can be reproduced?

      -The details on how old animals used in each experiment were, are not easy to find and not written very clearly. They should be included in the each figure legend rather than summarising those details in the methods.

      We will add the number of days in the figure legend.

      -Also, in line 788 in the methods, several stocks are indicated as coming from particular labs (e.g. UAS-FOXO (Kieran Harvey), UAS-GFP (Kieran Harvey), UAS-lacZRNAi (Kieran Harvey), UAS-RasV12 (Helena Richardson), UAS-cg25C;UAS-Vkg (Brian Stramer)).

      However, it is not clear whether these labs actually made these stocks and if so whether it has already been described in their papers how the lines were made. If the lines are unpublished, the detailed information should be given on how the lines were made. Or if the lines are published, the authors should provide the reference.

      We will fix these references.

      - Are the experiments adequately replicated and statistical analysis adequate?

      In general, the n number is rather low in several experiments, especially n of 3 for many controls. And as I mentioned before, rescues of tumor phenotypes are often shown without including a non-tumor control, making it hard to judge the extent of the rescue. Sometimes this information can be found in other figures, but the reader should not have to search for it. And also the severity of the phenotype can vary from experiment to experiment.

      We will include a non-tumour control when appropriate to address this.

      Minor comments:

      - Specific experimental issues that are easily addressable.

      - Are prior studies referenced appropriately?

      Yes, as far as I can tell.

      - Are the text and figures clear and accurate?

      -In the literature, people usually call it 'fat body' rather than 'fatbody'.

      We will fix this error.

      -The authors state in line 265 "Vkg accumulated in the membranes of fatbody where p60 was overexpressed using r4-GAL4 (Figure 5 A-C)."

      This must be a typo. I think it is shown in Fig5E-G. Unless it's labelled wrongly in the figure and B, C and D show p60 rather than TorDN.

      We will fix this error.

      -The authors state in line 188 'This manipulation significantly rescued muscle integrity (Figure S4 A-C) and muscle atrophy (Figure S4 D-F), without affecting muscle ECM levels (Figure S4 G-H).' According to the graph in FigS4H this does actually 'affect muscle ECM levels' significantly, as in that it reduced Nidogen levels further. The authors could rephrase this.

      We will reword this statement.

    2. Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate).

      This paper uses a Drosophila tumor model induced by the expression of RasV12+Scrib-IR or RasV12+Dlg-IR in the eye imaginal disc to understand how inter-organ communication affects cachexia in the fat body and muscle. The tumor has previously been shown to secrete the factors ImpL2 and Gbb which decreases insulin signalling and increases TGF-beta signalling in the fat body, respectively, and results in fat body and muscle defects. Here they dissect the role of insulin and TGF-beta signalling in the fat body in regulating muscle integrity further. They show that these two pathways converge via Sog in the fat body of tumor-bearing animals and result in aberrant ECM accumulation in the fat body which hinders ECM secretion. This then results in the muscle receiving less fat body-derived ECM which causes muscle attachment defects. Interestingly, these muscle defects can be ameliorated by activating insulin signalling or inhibiting TGF-beta signalling or even by increasing ECM secretion in the fat body. The authors also provide some evidence that the insulin and TGF-beta signalling pathways can converge in non-tumor settings.

      Major comments:

      • Are the key conclusions convincing?

      Most of the conclusions are convincing. It is not clear however whether the ECM accumulation in the fat body of tumor animals is fibrotic and whether it is extracellular or in the cell cortex.<br /> - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?<br /> - The authors state in line 71 'This deposition of disorganized ECM leads to fibrotic ECM<br /> accumulation.' The authors haven't really provided evidence for the ECM being fibrotic. The authors could either rephrase this or provide additional experimental evidence of fibrosis in the fat body.<br /> - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.<br /> - The authors state in line 147" Finally, in tumor-bearing animals fed a sterol-free diet, that underwent a prolonged 3rd instar stage due to reduced ecdysone levels (Parkin and Burnet, 1986), we activated insulin signalling in the fatbody via Akt overexpression (QRasV12, scribRNAi). We found that this manipulation caused a significant decrease in pMad levels in the fatbody and a rescue of muscle detachment (Figure S1 D-I), similar to animals fed a standard diet (Figure 1 O-Q, Figure 2 F-H)." Since it's not already known what the extent of muscle integrity defect there is in tumors with additional sterol free diet, it would be important to show a non-tumor control for comparison in FigS1F. This would also then make it clear to what extent the defect is rescued by Akt overexpression.<br /> - The authors state in line 158 'Upon the knockdown of Impl2, we found that tumor gbb was not significantly altered (Figure S3A).' Even though this shows an indication that Gbb levels are not reduced, the n number is too low to state that it is non-significant. The authors should increase the n number here.<br /> - The authors state in line 171 'Conversely, knockdown of gbb alone or knockdown of gbb together with ImpL2 significantly rescued the Nidogen overaccumulation defects observed at the plasma membrane of fatbody from tumor-bearing animals, while ImpL2RNAi alone did not (Figure S2 Q-U).' This is a somewhat misleading representation, since again no non-tumor control was used, so the extent of the rescue by gbb knowdown is not obvious. In FigS2P Nidogen levels in the tumor seem ~100% higher than in control. But in FigS2U, in which no control was included, the tumor+gbb knowdown seems ~ 20% lower than tumor. So it is probably a more moderate rescue, but that's only possible to assess by including a non-tumor control in FigS2U. Also the images in FigS2Q-T don't seem representative since they appear to show a much bigger difference in fluorescence intensity than ~20%. Please show more representative images.<br /> - The authors state in line 174 'Finally, co-knockdown of gbb and ImpL2 in the tumor significantly rescued the reduction in OPP and Nidogen levels observed in the muscles of tumor-bearing animals (Figure S3 B-I).'<br /> Again, the single knockdowns and the non-tumor control are not shown here in Fig3E and I and should be included for comparison and to see the contribution of each knockdown and to be able to judge the extent of the rescue.<br /> - Regarding Fig3O: Is there a significant tumor muscle attachment defect here? In this graph the tumor only looks about 10% lower than the WT (rather than 40% in Fig2E). The other issue is the extremely low n number for WT. I would recommend increasing the n number for WT here and to indicate in the graph whether the tumor is significantly different to WT (or non-significant, in which case RabRNAi wouldn't actually 'rescue' the defect). In the present form, this graph is not very convincing.<br /> - Regarding Fig3W: A non-tumor control would be important to include to be able to judge the extent of muscle attachment defects and the extent of the rescue for UAS-Sparc. This will allow to assess the severity of muscle integrity defect in this particular experiment (since it appears to vary in different experiments e.g. muscle defect in tumor 40% in Fig2E and ~10% in Fig3O) and to assess the extent of rescue for the various genotypes.<br /> - The authors show an accumulation of ECM in the fat body of tumors. It is not clear, whether this ECM accumulates intracellularly near the cell surface or extracellularly. The authors should assess this, maybe by doing electron microscopy.<br /> - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.<br /> - These suggested experiments should be quite straightforward since they are mostly just repeating previous experiments with the appropriate controls and n numbers. I would think that they can be done within a few months. The electron microscopy should not take more than a few weeks and not be costly.<br /> - Are the data and the methods presented in such a way that they can be reproduced?<br /> - The details on how old animals used in each experiment were, are not easy to find and not written very clearly. They should be included in the each figure legend rather than summarising those details in the methods.<br /> - Also, in line 788 in the methods, several stocks are indicated as coming from particular labs (e.g. UAS-FOXO (Kieran Harvey), UAS-GFP (Kieran Harvey), UAS-lacZRNAi (Kieran Harvey), UAS-RasV12 (Helena Richardson), UAS-cg25C;UAS-Vkg (Brian Stramer)).<br /> However, it is not clear whether these labs actually made these stocks and if so whether it has already been described in their papers how the lines were made. If the lines are unpublished, the detailed information should be given on how the lines were made. Or if the lines are published, the authors should provide the reference.<br /> - Are the experiments adequately replicated and statistical analysis adequate?<br /> In general, the n number is rather low in several experiments, especially n of 3 for many controls. And as I mentioned before, rescues of tumor phenotypes are often shown without including a non-tumor control, making it hard to judge the extent of the rescue. Sometimes this information can be found in other figures, but the reader should not have to search for it. And also the severity of the phenotype can vary from experiment to experiment.

      Minor comments:

      Specific experimental issues that are easily addressable.

      • Are prior studies referenced appropriately?

      Yes, as far as I can tell.<br /> - Are the text and figures clear and accurate?<br /> - In the literature, people usually call it 'fat body' rather than 'fatbody'.<br /> - The authors state in line 265 "Vkg accumulated in the membranes of fatbody where p60 was overexpressed using r4-GAL4 (Figure 5 A-C)."<br /> This must be a typo. I think it is shown in Fig5E-G. Unless it's labelled wrongly in the figure and B, C and D show p60 rather than TorDN.<br /> - The authors state in line 188 'This manipulation significantly rescued muscle integrity (Figure S4 A-C) and muscle atrophy (Figure S4 D-F), without affecting muscle ECM levels (Figure S4 G-H).' According to the graph in FigS4H this does actually 'affect muscle ECM levels' significantly, as in that it reduced Nidogen levels further. The authors could rephrase this.<br /> - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      Significance

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

      The field of inter-organ communication in cancer is a very interesting and trending research field. Several labs including this one have provided new insights into how the tumor, the fat body and the muscle communicate and affect each other and how this can cause cachexia. Previous work from the Chen lab already showed that the tumor secretes the factors ImpL2 and Gbb which decreases insulin signalling and increases TGF-beta signalling in the fat body, respectively and results in fat body and muscle defects. Here they dissect this role of insulin and TGF-beta signalling in the fat body in regulating muscle integrity during cachexia further. They show that these two pathways converge via Sog in the fat body of tumor-bearing animals and result in aberrant ECM accumulation in the fat body which hinders ECM secretion. As a result of this, the muscle receives less fat body-derived ECM and displays muscle attachment defects. Interestingly, the authors show that these muscle defects can be ameliorated by activating insulin signalling or inhibiting TGF-beta signalling or even by increasing ECM secretion in the fat body. This has potentially important implications for the clinic since it suggests that targeting ECM secretion or ECM remodeling in the fat tissue could be a promising treatment for cachexia.<br /> Moreover, the authors also provide some evidence that the insulin and TGF-beta signalling pathways can converge in tumor and non-tumor settings. This might also reveal new drug targets to treat cachexia.<br /> - Place the work in the context of the existing literature (provide references, where appropriate).

      The Chen lab showed previously that MMP1 secreted from the tumor induces ECM disruption in the fat body as well as muscle, ultimately causing fat body remodeling and muscle wasting (Lodge et al. 2021). They showed that this is via TGF-beta activation in the fat body. Another contributing factor is tumor-secreted Impl2 which decreases Insulin signalling in the fat body and tumor. However, it remained unknown, how ECM accumulation in the fat body might cause muscle wasting. In this paper, the authors look into this.<br /> - State what audience might be interested in and influenced by the reported findings.

      This paper would be of interest for scientists and clinicians interested in inter-organ communication in cancer, particularly in the context of cachexia.<br /> - Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

      My expertise lies in the field of Drosophila fat body and ECM, and to some extent tumors but less so signalling pathways.

    1. Author Response

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

      This important work reports the identification of a list of proteins that may participate in the clearance of paternal mitochondria during fertilization, which is known as essential for normal fertilization and embryonic and fetal development. While the main method used is state of the art and the supporting data are solid, the vigor of the biochemical assays and function validation is inadequate. This work will be of interest to developmental and reproductive biologists working on fertilization. Key revisions (for the authors) include 1) Use a mitochondria-enriched fraction instead of whole sperm for the assays, and add more control samples to monitor what got lost during sperm and oocyte treatments before the coincubation step. 2) Functional validation of the key proteins identified.

      We thank Editors of eLife, as well as Special Issue Guest-Editors and Reviewers for a favorable assessment and helpful recommendations for key revisions. Provisional revisions included in our revised article are detailed below. We agree with Editors’ comment about the use of mitochondrion enriched fractions and additional functional validation of key proteins. In fact, we are developing experimental protocols for oocyte extract coincubation with isolated sperm heads and tails, and eventually with purified mitochondrial sheaths, to separate the ooplasmic sperm nucleus remodeling factors from the mitophagic ones. Such experiments, as well as functional validations using porcine zygotes are contingent upon anticipated post-pandemic rebound in the availability of porcine oocytes, obtained from ovaries harvested on slaughterhouse floors, requiring currently unavailable workforce which has hampered our access to this necessary resource.

      Reviewer #1 (Peer Review):

      Could the authors make clear how much the presented pictures reflect the described localisation? There is no information on the number of spermatozoa and embryos observed nor the fraction of these embryos showing the presented pattern of localisation. This must be included.

      Two hundred spermatozoa were counted per replicate of the cell-free system co-incubation and 20 zygotes per replicate, with 3 replicates of immunolabelling for each phase/picture which were examined to establish the typical localization patterns that were observed. The displayed patterns were observed in 65 to 88% of examined spermatozoa/zygotes; varying dependent on protein, replicate, and phase of immunolabelling. In all cases, the signal displayed is the typical pattern that was displayed in most cells. This information has been added to the Materials and Methods section for clarification.

      It is not clear if the authors also examined the localization of other proteins and obtained a different pattern than anticipated from the proteomic approach or if they only tested these 6 proteins and got a 100% of correlation.

      These are the 6 proteins which were selected based on extensive literature review into known functions of all identified proteins, as well as extensive research into available and reliable antibodies to detect such proteins within our porcine systems. Even so, no particular localization patterns were anticipated; instead, we presented the patterns actually observed and even some patterns which defied our expectations (i.e., the localization of BAG5 in the sperm acrosome).

      The authors use "MS" in the text to indicate "mitochondrial Sheath" and "Mass spectrometry". this is confusing.

      The authors agree and the usage of MS as an acronym for either has been removed entirely to avoid confusion.

      In the introduction the author refers to Ankel-Simons and Cummins, 1996 as a reference for the number of sperm mitochondria in mammalian species, this is incorrect since the quoted paper is about the number of mtDNA molecules and mentioned an earlier publication.

      This has been revised and the appropriate citation has been used.

      Reviewer #2 (Peer Review):

      Major:

      1) It has been proved from the earlier studies from this group that the porcine cell-free system is useful to observe spermatozoa interacting with ooplasmic proteins in a single trial and could recapitulate fertilization sperm mitophagy events that take place in a zygote without affecting later cell-division process. However, the post-fertilization sperm mitophagy process is a complex time-associated event that many processes that occur sequentially and interactively, which means ooplasmic proteins might be involved in this process but may not directly interact with sperm or may associate with sperm-ooplasmic protein complex at different time points. It is certainly a great advance already in knowledge to identify "the candidate players" from the list of 185 proteins; however, with the time-resolution (4 and 24hr) in the current study and without functional validation experiments at this stage, it is still difficult to postulate the importance of these identified proteins. The functional validation experimental designs, in my opinion, is critically important for better interpretation of the data.

      The authors agree with this reviewer’s sentiments and do plan to conduct further functional analysis. This project was able to generate a list of candidate, sperm-mitophagy promoting proteins and we were further able to show that many of these proteins were detectable both via mass spectrometry and via immunocytochemistry in spermatozoa exposed to our cell-free system. Furthermore, similar localization patterns were found in spermatozoa that were detected within newly fertilized zygotes. These results boost our confidence in our cell-free system and show that our list of candidate proteins is truly a useful list for future localization and functional analyses. We are certainly aware that we have not captured every protein that may play a role in post-fertilization sperm mitophagy and that the proteins captured are just candidates until proven otherwise. Likewise, we have almost certainly captured multiple proteins that are currently candidates that will likely not be shown to play a role in postfertilization sperm mitophagy, while it is plausible that at least some of these candidate proteins do play a role in mitophagy and some of them likely participate (perhaps have yet to be described roles) in other fertilization events, in which we would be extremely interested in as well.

      2) As shown in Figure 1, whole sperm was used in the co-incubation and the later MS analysis; thus, proteins identified in the current study might be relevant in fertilization processes other than postfertilization sperm mitophagy, as proteins identified in the current study may be associated with other parts of the sperm (e.g. sticky sperm head, e.g. PSMG2 associated with sperm midpieces, tail at 4hr coincubation, but then only associate with sperm head at 24hr co-incubation) rather than sperm midpiece, despite the fact that authors applied immunohistochemistry to show the localization of this protein, but the evidence is indirect, so how authors functionally differentiate these 6 identified proteins from sperm mitophagy process with other processes and to confirm (or to associate) the relevance of these proteins with sperm mitophagy process?

      The authors agree that the 6 proteins which were further studied by using immunocytochemistry may be playing roles in other processes such as pronuclear formation. We discussed some potential roles including and beyond post-fertilization mitophagy, in the Supplemental Discussion. After reviewer comments, we moved the Supplemental Discussion back in the main Discussion section. Thus, this section now considers additional putative pathways in which the said 6 proteins cold participate, though we concede that thorough functional studies must still be performed.

      3) Class 3 proteins were present in both the gametes or only the primed control spermatozoa, but are decreased in the spermatozoa after co-incubation, which authors interpreted as sperm-borne mitophagy determinants and/or sperm-borne proteolytic substrates of the oocyte autophagic system, this data categorization may need to be revised as sperm-borne proteolytic substrates of the oocyte autophagic system only, not for sperm borne mitophagy determinants. The argument for this disagreement is due to the fact that if the protein is a sperm-borne mitophagy determinant, after coincubation, to execute the mitophagy process, this protein should still be associated with the sperm at least at the early stage (of 4hr) (constant under MS detection when comparing control with 4hr treated) rather than being released from the sperm. Or alternatively, they could result in class 3 proteins (but not all those 6 were in class 3). Nevertheless, if these proteins serve as substrates, they can be used (consumed) and show decreased under MS detection.

      This argument for redefining the Class 3 proteins more accurately is understood and we agree. The definition is revised in the paper.

      4) Of particular interest among the 6 proteins that were further investigated. Unlike other proteins, MVP was highly significant (p<0.001) after 4hr incubation, but the significance became less after 24hr (p=0.19). Interpretation of this dynamic change in the relevance of the mitophagy process would facilitate the readers to understand the relevance and the role of MVP.

      The differences in significance are likely influenced by the abundance of MVP detectable by mass spectrometry. As the time of cell-free system incubation increases, the variability between replicates also seemed to increase, likely due to the sustained proteolytic activity taking place in our system. This work was based on three replicates of mass spectrometry for each time point; additional replicates likely would have reduced the p-value for the 24hr cell-free data set, for MVP and potentially other proteins also. At both time points, MVP was only detectable in spermatozoa after they had been exposed to the cell-free system treatment which is the criteria that truly interested us more than the actual differences in content between the timepoints and is why it was added to our list of candidate proteins.

      5) In figure 3, the association of ooplasmic MVP to sperm midpiece is not convincing enough as sperm midpiece and tail often show some levels of non-specific signals under fluorescent microscopy. And the dynamic association of ooplasmic MVP to sperm midpiece in Fig. 3F-G is difficult to reach a conclusion solely based on data presented in the manuscript. Additional negative control of sperm MVP staining from the primed and treated sperm would be helpful. Additionally, a quantitative comparison (15 vs 25hr) of sperm-associated MVP signals from the fertilized embryo or a stack image from different angles would clarify the doubts raised here.

      For all images and all replicates, serum controls were also generated. These controls were then viewed under fluorescent microscope, and light intensities and exposures thresholds for each fluorescent light channel were set based on the background intensity that came from these nonimmune serum-treated control samples. We set our light intensity/acquisition time below a threshold where the non-specific signal began to appear. All the presented patterns are based on setting this peak intensity threshold and as such the signal we see should be the true signal. Furthermore, 200 spermatozoa were counted per treatment per replicate of the cell-free system co-incubation and 20 zygotes per replicate, with 3 replicates of immunolabelling for each protein and data point, which was used to represent the typical localization patterns that were observed. The displayed patterns were observed between in 65- 88% of examined spermatozoa/zygotes. Invariably, the signal displayed in the manuscript is the typical pattern that was seen in a majority of cells. This information has now been added to the Materials & Methods section for clarification.

      6) Same concerns for the other 5 proteins (PSMG2, PSMA3, FUNDC2, SAMM50, BAG5) as indicated above.

      See response to Question 5.

      7) The patterns of these 6 proteins under the immunofluorescent study are confusing as the pattern varies after co-incubation (treated), and mostly, the signal of these proteins observed from the fertilized embryos is not really associated with sperm midpieces. Therefore, the evidence of these proteins involving in post-fertilization sperm mitophagy is, at this moment, weak based on the data presented. But the relevance of these proteins in events post-fertilization or early embryo development is certainly (evidence did not strong enough to support "sperm mitophagy," in my opinion).

      The authors agree that some of these proteins seem to be playing roles beyond postfertilization sperm mitophagy and that there is a need for true functional studies before the authors can state with certainty that these proteins play a role in any of the discussed fertilization events. We state this in the discussion: “Considering the dynamic proteomic remodeling of both the oocyte and spermatozoa which takes place during early fertilization, these 185 proteins which have been identified likely play roles in processes beyond sperm mitophagy.” It should be noted that the authors went into greater detail about potential alternative protein functions based on the present data and literature review in the Supplemental Discussion. Based on this comment and other reviewer comments we have now included the Supplemental Discussion as part of the main Discussion section, and this will hopefully help clarify some of the authors’ thoughts about the 6 candidate proteins which were further analyzed during this study.

      Minor:

      1) To my understanding, statistical significance (relevance) is normally set at a p-value of either <0.1 or 0.05. The reason for loosening the p-value of 0.2 in the current study needs to be justified as this was not a common statistical criterium, and the interpretation of those candidates from this loosened criterium should also be careful.

      The loosening of statistical relevance in this study to 0.2, only applied to our Class 1 proteins. This is because for a protein to fall into the Class 1 proteins it was a protein that was only present in samples after they were exposed to the cell-free system. In the case of these Class 1 proteins, this happened for all 3 replicates at each stated timepoint. We found this pattern of detection to be important whether the p-value fell under 0.1 or 0.2. As such, we loosened our statistical threshold for our Class 1 proteins. Any proteins added to our candidate list will be subject to further investigation before definitive conclusions can be drawn, and as such we think that capturing more proteins was more important for the goals of this study than limiting the number of proteins captured, especially for those Class 1 proteins. An explanation of this has been added to the Materials & Methods section Mass Spectrometry Data Statistical Analysis.

      2) First cell cleavage of porcine embryo normally occurs within 48hr post-insemination or activation; therefore, the 4 and the 24hr time points used in the current study require justification included in the discussion or methods and material section.

      First cleavage of porcine embryos normally occurs around 24 - 28 hours post-insemination. Thus, for both the cell-free system and the embryo studies we were capturing an advanced 1 cell stage zygote/zygote like system with our 24 hour and 25-hour time points.

      3) In figure 2, colors used in different time points and in two different classes represent (sometimes) different protein categories, would be easier for the readers for quick comparisons if the same color could be used to represent the same protein category throughout the graph. (E.g, proteins for early zygote development are shown in red in "A", but blue in "B")

      This has been corrected and the color scheme for Figure 2 has been revised for easier comparisons.

      Reviewer #3 (Peer Review):

      I am not used to seeing a supplementary discussion in a manuscript. I also believe it should be incorporated into normal discussion.

      The Supplemental Discussion has been incorporated into the main Discussion now.

      It would be very helpful to make an additional figure in which the proposed interactome of identified factors with the sperm mitochondria before and after incubation are drawn schematically and also which factors are not IDed in both cases (when comparing to somatic mito- or autophagy). This eases to get through the discussion and will beautifully summarize and illustrate the importance and progress that the authors have made with this assay.

      We made a diagram that depicts the changes in protein localization patterns overtime within our cell-free system. This diagram has been added to the manuscript as Figure 9.

      Reviewer #1 (Public Review):

      In this manuscript, the authors used an unbiased method to identify proteins from porcine oocyte extracts associated with permeabilised boar spermatozoa in vitro. The identification of the proteins is done by mass spectrometry. A previous publication of this lab validated the cell-free extract purification methods as recapitulating early events after sperm entry in the oocyte. This novel method with mammalian gametes has the advantage that it can be done with many spermatozoa at the time and allows the identification of proteins associated with many permeabilised boar spermatozoa at the time. This allowed the authors to establish a list of proteins either enriched or depleted after incubation with the oocytes extract or even only associated with spermatozoa after incubation for 4h or 24h. The total number of proteins identified in their test is around 2 hundred and with very few present in the sample only when spermatozoa were incubated with the extracts. The list of proteins identified using this approach and these criteria provide a list of proteins likely associated with spermatozoa remnants after their entry and either removed or recruited for the transformation of spermatozoa-derived structures. Using WB and histochemistry labelling of spermatozoa and early embryos using specific antibodies the authors confirmed the association/dissociation of 6 proteins suspected to be involved in autophagy.

      While this unique approach provides a list of potential proteins involved in sperm mitochondria clearance it's (only) a starting point for many future studies and does not provide the demonstration that any of these proteins has indeed a role in the processes leading to sperm mitochondria clearance since the protein identified may also be involved in other processes going-on in the oocyte at this time of early development.

      We thank reviewer 1 for positive comments. We added a sentence in Discussion addressing the obvious shortcoming of present study, as further functional validations of candidate mitophagy factors are planned.

      Concerning the localisation of the 6 proteins further analysed, the authors must add how much the presented picture represents the observed patterns. They must include the details on the fraction of spermatozoa and embryos displaying the presented pattern.

      We now specify that the patterns depicted in manuscript are typical and representative of data from at least three replicates of immunolabeling in spermatozoa and zygotes. For each of these replicates, 200 spermatozoa were examined per replicate of the cell-free system co-incubation or 20 zygotes per replicate. The displayed patterns were observed between 65-88% in examined spermatozoa/zygotes. Invariably, the signal displayed in manuscript is the typical pattern that was seen in a majority of cells. This information has now been added to the Materials & Methods section for clarification.

      Reviewer #2 (Public Review):

      Mitochondria are essential cellular organelles that generate ATPs as the energy source for maintaining regular cellular functions. However, the degradation of sperm-borne mitochondria after fertilization is a conserved event known as mitophagy to ensure the exclusively maternal inheritance of the mitochondrial DNA genome. Defects on post-fertilization sperm mitophagy will lead to fatal consequences in patients. Therefore, understanding the cellular and molecular regulation of the postfertilization sperm mitophagy process is critically important. In this study, Zuidema et. al applied mass spectrometry in conjunction with a porcine cell-free system to identify potential autophagic cofactors involved in post-fertilization sperm mitophagy. They identified a list of 185 proteins that might be candidates for mitophagy determinants (or their co-factors). Despite the fact that 6 (out of 185) proteins were further studied, based on their known functions, using a porcine cell-free system in conjunction with immunocytochemistry and Western blotting, to characterize the localization and modification changes these proteins, no further functional validation experiments were performed. Nevertheless, the data presented in the current study is of great interest and could be important for future studies in this field.

      We thank reviewer 2 for positive comments. As we explain in our response to Editors and Reviewer 1, further validation studies will be resumed once the availability of slaughterhouse ovaries for such studies improves. Examples of such functional validation of pro-mitophagic proteins SQSTM1 and VCP are included in our previous studies (DOI: 10.1073/pnas.1605844113 and DOI: 10.3390/cells10092450) that led to the development of cell-free system reported here, and are cited in present study.

      Reviewer #3 (Public Review):

      In this manuscript, a cytosolic extract of porcine oocytes is prepared. To this end, the authors have aspirated follicles from ovaries obtained from by first maturing oocytes to meiose 2 metaphase stage (one polar body) from the slaughterhouse. Cumulus cells (hyaluronidase treatment) and the zona pellucida (pronase treatment) were removed and the resulting naked mature oocytes (1000 per portion) were extracted in a buffer containing divalent cation chelator, beta-mercaptoethanol, protease inhibitors, and a creatine kinase phosphocreatine cocktail for energy regeneration which was subsequently triple frozen/thawed in liquid nitrogen and crushed by 16 kG centrifugation. The supernatant (1.5 mL) was harvested and 10 microliters of it (used for interaction with 10,000 permeabilized boar sperm per 10 microliter extract (which thus represents the cytosol fraction of 6.67 oocytes). The sperm were in this assay treated with DTT and lysoPC to prime the sperm's mitochondrial sheath. After incubation and washing these preps were used for Western blot (see point 2) for Fluorescence microscopy and for proteomic identification of proteins.

      Points for consideration:

      1) The treatment of sperm cells with DTT and lysoPC will permeabilize sperm cells but will also cause the liberation of soluble proteins as well as proteins that may interact with sperm structures via oxidized cysteine groups (disulfide bridges between proteins that will be reduced by DTT).

      This is certainly a possibility, the lysoPC and DTT permeabilization steps were designed to mimic natural processing (plasma membrane removal and sperm protein disulfide bond reduction), which the spermatozoa would undergo during fertilization. However, we do realize that this is a chemically induced processing and thus is not a perfect recapitulation of fertilization processes. However, in this study and in previous studies with this system, we were able to show alignment between proteomic interactions taking place in the cell-free system and within the zygotes.

      2) Figure 3: Did the authors really make Western blots with the amount of sperm cells and oocyte extracts as the description in the figures is not clear? This point relates to point 1. The proteins should also be detected in the following preparations (1) for the oocyte extract only (done) (2) for unextracted nude oocytes to see what is lost by the extraction procedure in proteins that may be relevant (not done) (3) for the permeabilized (LPC and DTT treated and washed) sperm only (not done) (4) For sperm that were intact (done) (5) After the assay was 10,000 permeabilized sperm and the equivalent of 6.67 oocyte extracts were incubated and were washed 3 times (or higher amounts after this incubation; not done). Note that the amount of sperm from one assay (10,000) likely will give insufficient protein for proper Western blotting and or Coomassie staining. In the materials and methods, I cannot find how after incubation material was subjected to western blotting the permeabilized sperm. I only see how 50 oocyte extracts and 100 million sperm were processed separately for Western blot.

      The authors did make Western blots with the number of spermatozoa and oocytes stated in the materials and methods, a total protein equivalent of 10 to 20 million spermatozoa (equivalent to ~20-40 µg of total protein load) and 100 MII oocytes (equivalent to ~20 µg of total protein load). These numbers have been corrected in the Materials & Methods. Also, we did find in the Materials & Methods section that the Co-Incubation of Permeabilized Mammalian Spermatozoa with Porcine Oocyte Extracts section refers to using cell-free exposed spermatozoa for electrophoresis; however, for none of the presented Western blot work was this true. Rather, all of the presented Western blots as per their descriptions are utilizing ejaculated or capacitated sperm or oocytes. This line has been removed from the Materials & Methods to reduce confusion.

      Regarding preparation (2), we have previously assessed the difference between oocyte extract and intact oocytes in this manner internally and we are certainly losing proteins due to the oocyte extraction process. We make caveats in this vein throughout the article such as: “Furthermore, this cell-free system while useful does not perfectly capture all the events which take place during in vivo fertilization. The cell-free system is intended to mimic early fertilization events but is presumably not the exact same as in vitro fertilization.”

      3) Figures 4, 5, 6, 7, and 8 see point 2. I do miss beyond these conditions also condition 1 despite the fact that the imaged ooplasm does show positive staining.

      For all the presented Western blots, the tissue type is stated in the image description and the protocol which was used to prepare these samples is stated in the Materials & Methods.

      4) These points 1-3 are all required for understanding what is lost in the sperm and oocyte treatments prior to the incubation step as well as the putative origin of proteins that were shown to interact with the mitochondrial sheath of the oocyte extract incubated permeabilized sperm cells after triple washing. Is the origin from sperm only (Figs 5-8) or also from the oocyte? Is the sperm treatment prior to incubation losing factors of interest (denaturation by DTT or dissolving of interacting proteins preincubation Figs 3-8)?

      The authors understand that there are proteins and interactions lost on both sides of the cellfree system equation and we have added a sentence to the Discussion to caveat this limitation in the system.

      5) Mass spectrometry of the permeabilized sperm incubated with oocyte extracts and subsequent washing has been chosen to identify proteins involved in the autophagy (or cofactors thereof). The interaction of a number of such factors with the mitochondrial sheath of sperm has been shown in some cases from sperm and others for an oocyte origin. Therefore, it is surprising that the authors have not sub-fractionated the sperm after this incubation to work with a mitochondrial-enriched subfraction. I am very positive about the porcine cell-free assay approach and the results presented here. However, I feel that the shortcomings of the assay are not well discussed (see points 1-5) and some of these points could easily be experimentally implemented in a revised version of this manuscript while others should at least be discussed.

      We agree that the use of a mitochondrial-enriched subfraction for further analysis would be interesting and useful. We are actively developing experimental protocols for oocyte extract coincubation with isolated sperm heads and tails, and eventually with purified mitochondrial sheaths. However, such experiments are contingent upon our access to porcine oocytes, which has continued to be a struggle since the COVID-19 pandemic compromised our ability to attain oocytes in large, cheap, and reliable quantities. This was a continuous problem with preparing materials for this very paper and has continued to be an issue for our laboratory as well as many others at our university and across the country. We continue to maximize oocytes every time we can get access to them, but the unfortunate reality is that this access has become sparce and unreliable over the past three years.

    1. As Chris Aldridge says, for centuries the Zettelkasten approach was the standard and universal method for producing books and articles - until personal computers took over. Nearly every serious work ever published before the 1980s was drafted either with index cards or paper slips, or else with notebooks in a commonplace style. Every writer had their own take on these two options, but that’s what they all used. Then, in a single decade, word processing software took over. These days, most writers use something like Microsoft Word or Google Docs (just try persuading your publisher you’re not giving them a docx file). Scrivener became popular because it critiqued the ‘endless roll of paper’ model and reverted to an index card interface of sorts. But it remained a niche.Today, you either thrive on that word processor model or you don’t. I really don’t, which is why I’ve invested effort, as you have, in researching previous writing workflows, older than the all-conquering PC of the late 1980s and early 90s. At the same time, new writing tools are challenging the established Microsoft way, but in doing so are drawing attention to the fact that each app locks the user into a particular set of assumptions about the drafting and publishing process.The current academic scene is a brutal war to publish or perish. It’s not unusual for a researcher to write or co-write 30-40 peer-reviewed articles per year. General publishing is also frenetic. In the UK, 20 books are published every hour of the day. It all makes Luhmann’s ‘prolific’ output look lazy. Now though, AI is blowing the entire field apart. From now on, prolific writing is what computers do best. There’s no reason not to publish 20,000 books per hour. Soon enough, that will be the output per ‘author’. Where the pieces will eventually land is anyone’s guess. For example, the workflow of the near future might involve one part writing and nineteen parts marketing. Except that AI has got that sewn up too. Meanwhile, until the world ends, I’m just having fun doing my thing.

      Before the advent of the computer, the use of a zettelkasten or commonplace book to research was "common place".

      What happened with the transition? Perhaps the methodology was lost in the transition, people just dumping things into a word file?

    2. I just can't get into these sort of high-ritual triage approaches to note-taking. I can admire it from afar, which I do, but find this sort of "consider this ahead of time before you make a move" approaches to really drag down my process.But, I do appreciate them from a sort of "aesthetics of academia" perspective.

      Reply to Bob Doto at https://www.reddit.com/r/Zettelkasten/comments/14ikfsy/comment/jplo3j2/?utm_source=reddit&utm_medium=web2x&context=3 with respect to PZ Compass Points.

      I'll agree wholeheartedly that applying methods like this to each note one takes is a "make work" exercise. It's apt to encourage people into the completist trap of turning every note they take into some sort of pristine so-called permanent or evergreen note, and there are already too many of those practitioners, who often give up in a few weeks wondering "where did I go wrong?".

      It's useful to know that these methods and tools exist, particularly for younger students, but I would never recommend that one apply them on a daily or even weekly basis. Maybe if one was having trouble with a particular idea or thought and wanted to more exhaustively explore the adjacent space around it, but even here going out for a walk in nature and allowing diffuse thinking to do some of the work is likely to be just as (maybe more?) productive.

      It could be the sort of thing to write down in your collection of Oblique Strategies to pull out when you're hitting a wall?

    1. Produced one persona to accurately represent the people interviewed <img src="https://images.squarespace-cdn.com/content/v1/648ab2f8d6827b0a0cfd34e8/da90a6a0-d020-42db-b6c4-ddf55094c650/persona.jpg" alt="" loading="lazy" style=" object-fit: contain; object-position: calc(0.5 * 100%) calc(0.5 * 100%); "/>

      How does this relate to your HMW question? It's feeling a bit like you are just plopping the methods down without tying them together into a story. By distilling your research insights into a user persona you could begin ideating on that HMW question. Perhaps by switching the order in which you present the HMW question and the persona this could become clearer to the reader.

    1. Reviewer #1 (Public Review):

      Genetic, physiological, and environmental manipulations that increase roaming increase leaving rates. The connection between increased roaming and increased leaving is lost when tax4-expressing sensory neurons are inactivated. This study is conceptually important in its characterization of worm behaviors as time-series of discrete states, a promising framework for understanding behavioral decisions as algorithms that govern state transitions. This framework is well-established in other animals, thanks to Berman and others, but relatively new to worms.

      A key discovery is that lawn leaving behavior is probabilistically favored in states of behavioral arousal. I like the use of response-triggered averages (triggered on leaving events) that illustrate a "state-dependent receptive field" of the behavioral response. Response-triggered averages are common in sensory neuroscience, used, for example, to characterize the diverse "stimulus-dependent receptive fields" of different retinal ganglion cell types. It's nice to adapt the idea to illustrate the state-dependence of behavioral state transitions.

      The simplest metric of arousal state is crawling speed. When animals crawl faster, they are more likely to leave lawns. A more sophisticated metric of behavioral context is whether the animal is in a "roaming" or "dwelling" state, two-state HMM modeling from previous work (Flavell et al., 2013). Roaming animals are more likely to leave lawns than dwelling animals. Different autoregressive HMM tools can segment worm behavior into 4-states. Also with ARHMMs, the most aroused state is again the state that promotes lawn-leaving.

      (With the AR-HMM, I have a small quibble in its characterization as "orthogonal" to the 2-state HMM. Orthogonal has a precise mathematical meaning, but here orthogonal is taken loosely to only mean "very different". I'd prefer the authors just call them "very different" and not use mathematical terms so loosely.)

      HMM analysis seems to disentangle effects that were lumped by the simpler metric of overall speed. Crawling speed before lawn leaving events, when analyzed only within roaming periods, is only higher for ¡1 min before the event. I presume that the higher speed that is observed for several minutes before lawn leaving when all states are taken into account (e.g., Fig 1J, Fig 2A, and others) reflects the tendency to be in the faster roaming state than the slower dwelling state for several minutes before lawn leaving? If this is correct, it would be nice for the authors to be explicit about this interpretation, to help the reader understand what is going on.

      My principal worry is about the possible artifact if worms are more likely to be at lawn boundaries when moving quickly or in an arousal state (roaming in the 2-state HMM or in state 3 in the AR-HMM)? Lawn-leaving events only occur when the animal is at lawn boundaries. If animals are more likely to be at lawn boundaries when aroused, this should artificially increase the likelihood that these states precede lawn-leaving behaviors for a trivial environment-dependent reason instead of their interesting internal state-dependent reason. The authors might consider trying to disentangle the state-dependent statistics of lawn edge proximity when assessing by how much arousal states precede lawn-leaving events. I realize this is could be a formidable analytical challenge.

      One recourse is to align speed, HMM, and AR-HMM states to the other behavioral events that only happen at lawn boundaries. When they do this for head poke-reversals in Figure 2-supplement 3, they also observe an (albeit modest) increase in arousal states before head poke-reversals. It should be easy to also compare what happens with head poke-forward and head poke-pause to better understand potential artifacts in quantifying edge-associated events. In any case, this concern and their strategies to address it should be discussed for clarity and transparency.

      The authors use diverse environmental, genetic, and optogenetic perturbations to regulate the roaming state, thereby regulating the statistics of leaving in the expected manner. One surprise is that feeding inhibition evokes roaming and lawn-leaving in both pdfr-1 and tph-1 mutants, even though the tph-1-expressing NSM neurons have been shown to sense bacterial ingestion and food availability. I'm curious, is there anything in these new results that is inconsistent with previous claims by Rhoades et al., 2019, or did Rhoades et al. simply not do these tests?

      Another surprise is that evoking roaming does not evoke leaving in tax-4 mutants (which is something of an internal control that argues against the worry that roaming artificially increases the likelihood of leaving, see above). Without sensory neuron activity, worms are only more likely to roam for a minute before leaving rather than roaming for several minutes before leaving like wild-type (Figure 6C). ASJ seems to be the most important sensory neuron in this coupling between roaming and leaving (which is uncoupled when sensory neurons are inactivated).

      I'm a little puzzled why the wild-type animals shown in Figure 6C show elevated roaming for several minutes before leaving events, whereas the wild-type animals shown in Figures 4I,J,K show elevated roaming for only about a minute, not much different than tax-4 mutants. Am I missing something? What is different about these different wild-type animals?

    1. Reviewer #2 (Public Review):

      Schnell et al. performed two extensive behavioral experiments concerning the processing of objects in rats and humans. To this aim, they designed a set of objects parametrically varying along alignment and concavity and then they used activations from a pretrained deep convolutional neural network to select stimuli that would require one of two different discrimination strategies, i.e. relying on either low- or high-level processing exclusively. The results show that rodents rely more on low-level processing than humans.

      Strengths:

      1. The results are challenging and call for a different interpretation of previous evidence. Indeed, this work shows that common assumptions about task complexity and visual processing are probably biased by our personal intuitions and are not equivalent in rodents, which instead tend to rely more on low-level properties.<br /> 2. This is an innovative (and assumption-free) approach that will prove useful to many visual neuroscientists. Personally, I second the authors' excitement about the proposed approach, and its potential to overcome the limits of experimenters' creativity and intuitions. In general, the claims seem well supported and the effects sufficiently clear.<br /> 3. This work provides an insightful link between rodent and human literature on object processing. Given the increasing number of studies on visual perception involving rodents, these kinds of comparisons are becoming crucial.<br /> 4. The paper raises several novel questions that will prompt more research in this direction.

      Weaknesses:

      1. There are a few inconsistencies in the number of subjects reported. Sometimes 45 humans are mentioned and sometimes 50. Probably they are just typos, but it's unclear.<br /> 2. A few aspects mentioned in the introduction and results are only defined in the Methods thus making the manuscript a bit hard to follow (e.g. the alignment dimension), htus I had to jump often from the main text to the methods to get a sense of their meaning.<br /> 3. The choices related to the stimulus design and the network used to categorize them are not fully described and would benefit from some further clarification/justification. The choice of alignment and concavity as baseline properties of the stimuli is not properly discussed. Also, from the low-correlations I got the feeling that AlexNet is just not a good model of rat visual processing. Which indeed can be interpreted as further evidence of what the authors are trying to demonstrate, but it might also be an isolated case.<br /> 4. Many important aspects of the task are not fully described in the Methods (e.g. size of the stimuli, reaction times and basic statistics on the responses).

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      We thank the four reviewers for their generally positive feedback on the manuscript. Below, we provide a point-by-point response to each reviewer.

      We are performing new FCS and gradient measurements as suggested by the reviewers. We are confident we can have these completed within three months (accounting for the summer break).


      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      *This manuscript reports a very thorough and careful study of the mobility of Bicoid in the early embryo, explored with single-point fluorescence correlation spectroscopy. Although previous groups have looked into this question in the past, the work presented here is novel and interesting because of the different Bicoid mutants and constructs the authors have examined, in particular with the goal of understanding the role of the protein DNA-binding homeodomain. The authors convincingly show that there is a significant increase in Bicoid dynamics from the anterior to the posterior region of the embryo, and that the homeodomain plays an important role in regulating the protein's dynamics. Their experiments are very well designed and carefully analyzed. The authors also modelled gradient formation to see whether this change in dynamics might play a role in setting the shape of the gradient. I am not sure I fully agree with their conclusion that it does, as mentioned in my comment below. However, it is an interesting discussion to have, and I think this paper makes a significant advance in our understanding of Bicoid's behavior in the early embryo. *

      We thank the Reviewer for their positive comments and their suggestions for improving the manuscript. We will resolve the concerns raised by the reviewer with clarity in the revision. We will also add additional comment in the Discussion regarding the interpretation of our results.

      *Major comments: *

      • 1) Gradient profile quantification: Some of the conclusions made by the authors rely on the comparison between their model of gradient formation (as captured in the equations in lines 232 and 233) and the Bcd intensity profile measured in the embryos. Since the differences in gradient shape predicted by the different models are very small (see Fig. 3B, which is on a log scale and therefore emphasize small differences, and Fig. 3C), it is very important to understand how reliable the experimental concentration profiles are.*

      This is a fair comment. It is worth noting that the key differences between the 1- and 2-component models are only apparent at large distances (and hence low concentrations) from the source.

      We performed the quantification of the gradients in a manner similar to the Gregor lab, whereby the midsagittal plane is analysed. We used 488nm illumination (rather than 2-photon, as the Gregor lab does) so our measurements are likely noisier. However, we are not investigating the variability in the gradient here, but the mean extent. We currently correct background with a uniform subtraction, but we appreciate that is not the optimal method.

      In the revised manuscript, we will repeat the above experiments using a 2-photon microscope. Further, we will image lines expressing His::mcherry without eGFP under the same imaging conditions to more accurately estimate the background signal. While we expect this to improve the data quality, we do not envisage significant change to the observed profiles based on prior experience.

      At the moment, I do not find the evidence that [Bcd] concentration profile is more consistent with a 2-component diffusion model than a 1-component model very strong. A few comments related to this: * * 1a. Line 249, it is mentioned that: "observations ... incompatible with the SDD model". Which observations exactly are incompatible with the SDD model?

      The key points are in the preceding paragraph. We will improve the model presentation in the Results and also include further contextualisation in the Discussion.

      1b. In Fig. 3D, only the prediction of the 2-component model is shown. What would the simple 1-component diffusion model look like? Is it really incompatible with the data?

      We agree with this comment and will provide the 1-component fit to the gradient profiles. We expect it to fit well for the anterior half of the embryo but fail at larger distances (as has been previously shown).

      Regarding the FCS data, we also show one and two component fits. We will show the alternative fits – a 2 particle fit is clearly an improvement (see also related response to reviewer 2).

      1c. Line 243: "The increased fraction in the fast form ... consistent with experimental observation of Bcd in the most posterior" (Mir et al.)". I am not sure how this is significant, since the simple model also predicts there will be Bcd in the posterior - the only difference is how much is there (as shown in Fig. 3C), and it's a very small difference.

      The absolute differences are not large between the two models, but due to the observed clustering (Mir et al. 2018), even small differences can have very large effects. In the revision we will provide estimates of the actual concentration differences.

      We are performing new experiments with the Fritzsche lab at Oxford to estimate if there is clustering of Bcd. We will also repeat our FCS experiments to validate our key conclusion of AP differences in diffusion of Bcd. These should be completed by the end of the summer.

      1d. Since the difference between models is in the posterior region where Bcd concentration is very low, when comparing the models to the data the question of background subtraction is essential. How was the subtracted background (mentioned line 612) estimated?

      See above response to the first comment.

      1e. Along the same line, were the detectors on the Zeiss LSM analog or photon counting detectors, and how confident can we be that signal is exactly proportional to concentration?

      We used PMTs and did not directly do photon counting. But the intensity is still proportional to the concentration. It is possible to estimate the absolute concentration value, e.g., Zhang et al., 2021 (https://doi.org/10.1016/j.bpj.2021.06.035). However, our main conclusions – especially regarding the spatially varying Bcd dynamics – are not dependent on this.

      1f. Can the gradients created by the two Bcd mutants (FIg. 4B) be quantified as well, and are they any different from the original Bcd gradient?

      We agree this would be useful. We will provide the gradient quantifications of the bcd mutants in the revision.

      1e. What is the pink line in Figure 5C (I am assuming the green one is the same as in Fig. 3D)? It could be better to not use normalization here, or normalize everything respective to the eGFP::Bcd data to make comparison in relative concentrations in the posterior for different constructs more evident (also maybe different colors for the three different data sets would help clarity).

      This is a fair comment, and we will create graphs with new data for better visualisation.

      1f. Discussion, lines 402-403: Does the detailed shape of the Bcd in the posterior region matter at all, since the posterior is not a region where Bicoid is active, as far as we know? Could a varying Bcd dynamics have other consequences that would be more biologically relevant?

      Bcd is now known to act at 70% EL (Singh et al., Cell Reports 2022). So, the gradient is relevant for a large extent of the embryo length, though it is not known if there is any effect in the most posterior region.

      2) Model for gradient formation (lines 231-238): * * 2a. Whether the molecules of Bcd can change from their fast to slow form is never questioned. How do we know (or why might we suspect) they do exchange?

      This is a good point. Within the nucleus, and based on our mutant data, we suspect the fast/slow forms correspond to unbound/bound DNA states.

      In the cytoplasm, the dynamics are less clear. Bcd can bind to cytoskeletal elements (Cai et al., PLoS One 2017) as well as to Caudal mRNA. Therefore, it seems reasonable to have different effective dynamic modes – yet, how such switching occurs remains unclear.

      Ultimately, our model approximates multiple dynamic modes that are integrated to drive Bcd motion. Including switching between states is a reasonable assumption based on what is known about cytoskeletal and protein dynamics, but we do not have a specific mechanism.

      It is challenging to estimate a specific kon / koff rate, as the dynamic changes also depend on the diffusion – which itself is changing. For now, we believe our level of abstraction is appropriate given what is known about the system. It will be very interesting to explore the specific interactions underlying such behaviour in the future, but that is beyond this current manuscript.

      2b. The values used in the model for alpha, beta_0 and rho_0 should be mentioned. Maybe having a table with all the parameters in the method section, or even in the supplementary section, would help. The exact values of alpha and beta matter, because if they are large (fast exchange) a single exponential gradient is to be expected, if they are 0 (no exchange) a double exponential gradient is to be expected, with intermediate behavior in between. Which case are we in here?

      We agree and will add a more complete table in the revision.

      3) Discussion about anomalous diffusion (lines 386-388): The 2-component model used by the authors to interpret their FCS data seems very well justified here (excellent fits with very small residuals). I agree with the authors' conclusion that "the dynamics of Bcd within the nucleus are more complicated than a simple model of bound versus unbound Bcd", but I don't see how that can lead to a diagnostic of anomalous diffusion instead. Maybe it is just a matter of exactly explaining what is meant by anomalous diffusion here (since this term is often used to mean different things). A more likely scenario I think, is that there are more than just two Bcd components in the system.

      This is a good point, and we can’t easily differentiate two/multi- component fits from anomalous diffusion ones. This is a known problem. But we have recently shown in a collaboration with the Laurent Heliot lab (Furlan et al, Biophys J 2019), that anomalous diffusion is a good stable indicator of changes, even if it might not be the right model. We use anomalous diffusion as it stably predicts changes. We do not claim, however, that diffusion is anomalous. We will improve the discussion of these points in the revised manuscript.

      4) Line 440 and after: What is the evidence that the transition between the two forms might vary non-linearly with Bcd concentration? How would that help adapt to different embryo sizes? It would be good to be more explicit here instead of just referring to another paper.

      We will improve this discussion. The central point is that the action of Bicoid is unlikely to simply depend linearly on concentration as in that case the ratio of fast to slow forms would be constant across the embryo. Related to the above comment, it is important to emphasise that we are using a phenomenological model, not one based on a specific mechanism.

      5) Since an important aspect of this work is the study of different Bcd constructs in vivo, it is important that these constructs are very clearly described, so the section on the generation of the fly lines (Methods) should be expanded. In particular: * * 5a. It seems that the eGFP:: NLS control used here was different from that first described in Ref. 64 (and used for FCS experiments in Ref. 30 and 36)? If so, what NLS sequence was used here, and precisely what type of eGFP was used (in particular, was the A206K mutation that prevents dimerization present in the eGFP used)? If it is the same construct as in Ref. 64, it should be mentioned explicitly. * * 5b. Were the mutant N51A and R54A lines gifts as well, or have they been described before? If so, previous publications should be referenced. If not, how the plasmid was introduced in the embryo should be briefly explained.

      We agree and will expand on the fly lines in the revision.

      6) Concentration calibration measurements (Methods Fig. 2, line 568 and on). It is well known that background noise is going to interfere with the measurement of N when the signal becomes equivalent to the background noise (Koppel 197, Phys Rev A 10:1938-1945, and for a recent discussion of this effect for morphogens in fly embryos: Zhang et al., 2021, Biophysical Journal 120,4230-4241). It is almost certain that in the low signal regions of the embryo (e.g. posterior cytoplasm) this is affecting the reported concentration, and should be at least acknowledged.

      We agree with the reviewer. We will provide the SBR. We will also correct the N values based on the method followed in Zhang et al., 2021, Biophysical Journal 120,4230-4241.

      *7) Reference 3 is mis-characterized in two different ways in the manuscript: * * 7a. Line 50: The conclusion in Ref. 3 was not that the gradient was due to a diffusive process, on the contrary Gregor et al. argued that Bcd was too slow to form such a long-range gradient by diffusion. Studies that do present data consistent with a morphogen gradient formation mechanism driven by diffusion are reference 5, reference 30, Zhou et al., Curr. Biol. 2012;22(8):668-75 and Müller et al., Science 336 (2012) 721-724. *

      Gregor et al., do not argue against a diffusion process – indeed, they utilise a SDD model in their paper. However, they do extensively discuss how the predicted dynamics from the SDD model are not compatible with gradient formation as observed after n.c. 13. This problem was resolved to some degree by FCS measurements of Bcd (e.g., Dostatni lab, Development 2011) and the use of a Bcd tandem reporter which showed that production and degradation change during n.c. 14 (Durrieu et al., MSB 2018). We will improve the framing of these results in the revision.

      7b. The diffusion coefficient estimated from FRAP measurements and reported in Ref. 3 (D = 0.4 micron^2/s) is mentioned a couple of times in the manuscript (line 66, line 395, line 411). However, this number is simply incorrect. When fast components (such as the ones clearly detected here by FCS) are present, they diffuse out of the photobleached area during the photobleaching step. If that is not corrected for during the analysis (and it wasn't in Ref. 3), then the recovery time measured is just equal to the photobleaching time, and has nothing to do with either the fast or slow fraction of the studied molecule - it has no other meaning than to give a lower bound on the value of the actual effective diffusion coefficient of the molecule. This effect (called the halo effect) is well known in the FRAP community (see e.g. Weiss 2004, Traffic 5:662-671), it has been experimental demonstrated to occur for Bcd-eGFP in the conditions used in Ref. 3 (Reference 30), and the actual diffusion coefficient that should have been extracted from the data presented in Ref. 3 has been recalculated by another group to be instead D = 0.9 micron^2/s (Castle et al., 2011, Cell. Mol. Bioeng. 4:116-121). It would therefore be better to report the corrected value from Castle et al. to help the field converge towards an accurate description of Bcd mobility.

      We fully agree and will use the improved FRAP estimated value for Bcd.

      *Minor comments and suggestions: *

      • 8) Figure 1: From panel A, it seems that what is called "Anterior" and "Posterior" is about 150 micron away from the embryo mid-section, i.e. about 100 micron from either the anterior pole or the posterior pole (so not the tip of the embryo, but somewhere in the anterior half or posterior half). Maybe this should be made clear in the text. *

      We have made changes in Figure 1A to indicate the region within which the FCS measurements are carried out. We have added the relevant details in the legend of figure 1 lines 137-138.

      *9) Fig. 2A; It might be good to put this graph on a log scale, so that cytoplasmic values are seen more clearly. Also, what about reporting on nuclear to cytoplasmic ratios? *

      We will rework on this graph and make necessary changes.

      *10) Fig. 2: It could be interesting to plot D_effective as a function of the measured concentration of Bicoid in different locations, since the (interesting) suggestion is made several time that [Bcd] could the a determinant of the protein mobility. *

      Our work provides an indication that Bcd concentration is connected to the diffusion. We did this by measuring at two locations. To extend this to a rigorous model would require substantial new measurement along the whole length of the embryo. While interesting, this represents a very large investment of time and lies beyond the current manuscript.

      *11) Figure 3B&C: Is the curve for 2-component diffusion (without concentration dependence) for steady-state missing? *

      We will clarify in the revision.

      *12) Lines 78 and 471: What do the authors mean by "new reagents"? The word reagent evokes a chemical reaction, but there are none here. Do the authors mean new constructs? or new mutants? *

      We have changed lines 78 and 479 from “new reagents” to new Bcd mutant eGFP lines”.

      *13) Lines 57-59: Another good reference for FCS measurements performed to study the dynamics of a morphogen (in this case Dpp) is Zhou et al., Curr. Biol. 2012;22(8):668-75 *

      We added this reference in no.70.

      *14) Lines 109-111: A word must be missing. Precisely determined what? *

      Precisely measure within cytoplasm, and nuclear compartments and also during interphase stages. We have changed to “precisely measure in the cytoplasmic and nuclear regions during the interphase stages of nuclear cycles (n.c.)12-14.” in line no.111-112.

      *15) Line 278: The increase in the slow mode is expected. Maybe explicitly mention why. *

      In line 286, we have added “due to the loss of Bcd binding to the DNA”.

      *16) Line 282: "with the fast component increasing", maybe replace with "with the diffusion coefficient of the fast component increasing" or "with the fraction of the fast component increasing". *

      We have changed line 289 “with the diffusion component of fast component increasing towards the posterior”.

      *17) Line 517: Is there a reason why the dorsal surface is always placed in the coverslip? *

      We have added these details in line 528-529 in Methods.

      *18) Line 524 and on: FCS measurements: What was the duration of each individual FCS measurement? It is great that the exact number of measurements are reported in the supplementary! *

      Thank you for the complement. Typically, cytoplasmic measurements are 60secs and nuclear measurements are 20-40s. We have added this in line no.528-529. We also added a column to indicate the duration of each of the measurements in the supplementary tables.

      *19) An Airy unit of 120 um seems large in combination with an objective with a NA of 1.2, is there a reason for that? What was the radius of the resulting detection volume? *

      Olympus microscopes have a 3x magnification stage in their confocals. This leads to the change in the Airy unit. Otherwise, it would be 40 mm.

      *20) Thank you for detailing the reasons behind the choice of excitation power, an important and often omitted details. Where in the excitation path were the values of the laser power measured (before or after the objective?)? *

      Thank you for the complement. The laser power is measured before the objective. We removed the objective and measured the laser power in the objective path.

      *21) Line 585: "since the brightness of eGFP::Bcd..." do the authors mean the molecular brightness of a single eGFP::Bcd molecule, or the total fluorescence signal? *

      It is the total fluorescence signal. We have edited line no.592.

      *22) It would be good for reference to mention the approximate value of the molecular brightness recorded for these eGFP constructs at the laser power used. *

      We will measure and tabulate in the revised manuscript.

      *23) Reference 766: The year (and maybe other things) is missing. *

      We have corrected this reference.

      24) Figure 2 (Methods): The concentrations shown on the figure should be in nM not uM. * * Thanks for noticing – we have changed.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      MAJOR POINTS

      • 1) FCS measurements and fits *
      • a) Please state the duration of each individual FCS measurement. *

      In the cytoplasm, the measurements were carried out for 60 secs and in nuclei it is between 20-40s. We could not measure for 60s in the nuclei as the nuclear position fluctuates from its initial position. We will add another column to indicate the duration of FCS measurements in the supplementary tables.

      b) The authors acknowledge potential issues with fluorophore photophysics and use different lag time ranges for the calibration dye Atto-488 (0.001 ms in Method Fig. 2) and eGFP (0.1 ms in the main figures). Given the strong influence of different parameters on data interpretation and conclusions, Method Fig. 2 should be repeated with purified eGFP. This is particularly relevant for the noisy FCS measurements in posterior regions.

      Performing the experiment with purified eGFP will be a volume calibration. We routinely performed this before each imaging session, and that should be fluorophore independent. As noted by Reviewer 1, it is also important to be clear about background correction. We will provide brightness data for eGFP and background values in the revised manuscript. We can then use this to estimate the corrected concentrations.

      We use 0.1 ms to start, as at that point any contribution from the photo-physics should have decayed (0.1 ms is about 3-5 times the day rate of the photophysical process, Sun et al., Analytical Chem 2015).

      c) Please explain why no data is shown for "AN" around 0.1 ms lag time in Fig. 1B in contrast to all other figures.

      We will add the data for AN from 0.01 in the revised figures.

      d) Please state what the estimated diffusion coefficients with one-component model fits are. Please also explain why the fits in Fig. S1E do not reach a value of 1 and why they plateau higher than the experimental data at long lag times. Please constrain the fits to G=1 at 0.1 ms tau and G=0 at 1 s tau to make a fair comparison.

      The experimental ACF curves reach 0 at long lag times as would be expected. The one-component fits, however, don’t describe the data well and as a result they do not reach 1 and 0 at short and long lag times, respectively. The fitting is done using a mean-squared estimation of the best approximation of the particular model function to the data. Fixing the parameters can be done, but it will further reduce fit accuracy and deviations will be larger. We will perform this analysis and tabulate the one component fits in supplementary 1 with necessary corrections.

      e) Please assess the validity of all multi-component fits by comparing the relative quality of the models to the number of estimated parameters using the Akaike information criterion or similar approaches.

      We will provide the values denoting the quality of the fits in the revision. We will provide the 3D 1 particle fit, the 3D 1 particle fit with triplet, the 3D 2 particle fit and the 3D 2 particle fit with triple and will provide appropriate measures of fit quality.

      f) Please also present the Bcd-GFP fits with 0.001 ms that are mentioned in line 590, and present the results for the data that did not give comparable tau_D1 and tau_D2 values mentioned in line 593.

      We will provide all the curves from 0.001ms in the supplementary. We did not provide these details as we have followed the methods from Abu Arish et al., 2010. As our cytoplasmic and nuclear TauD values match with Abu Arish et al., 2010 and Porcher et al., 2010, we thought the excess data would be redundant.

      3) Bicoid gradient and modeling * a) Little et al. 2011 observed that the Bcd gradient decreases around n.c. 13. Can the authors of the present work observe a similar concentration decrease using FCS? This is important to i) validate the FCS concentration measurements, and ii) to resolve the controversy regarding "previous claims based on imaging the Bcd profile within nuclei, which predicted decrease in Bcd diffusion in later stages".*

      This is a good point regarding conclusions from the previous literature. The Little et al. paper inferred that diffusion had to decrease from fitting to the gradient profiles. However, subsequent analysis from our lab (Durrieu et al., MSB 2018 [which uses a different method involving a tandem reporter for Bicoid] and this manuscript) strongly suggest that Bicoid remains dynamic, at least through n.c. 13 and early n.c. 14. One way to test this is to use SPIM-FCS, where longer time courses can be taken (though with slower time resolution in the FCS). We have performed preliminary experiments with SPIM-FCS and we will revisit this data to see if we can find evidence for changes in the diffusion.

      We will also extend the Discussion to make the results clearer in terms of previous models and literature.

      b) Please explain why the experimental Bcd-GFP gradient data does not reach a value of 1 (e.g. in Fig. 3D) despite normalization. Please also explain why the fits become flatter in Fig. 5B compared to the steep fit in Fig. 3D.

      Both lines were measured under identical conditions. Therefore, we normalised to the maximum value of both experiments. We will redo, normalising to each individual experiment. Regarding Fig. 5C, the Bcd::eGFP curve is identical to Fig. 3D. The flatter curve is the line with eGFP tagged to a NLS alone.

      c) For modeling, please take into account observations that the Bcd source is graded with a wide distribution (30-40% EL, see Spirov et al. 2009, Little et al. 2011, Cai et al. 2017 etc.). The extent of the source used in the present work (x_s=20 um, line 620) is at least five times too small.

      Care must be taken in defining the source extent. The most careful measurements are reported in Little et al., PLoS Biology 2011 who performed single molecule FISH. They conclude “We demonstrate that all but a few mRNA particles are confined to the anterior 20% of the egg”. Further, the peak in the particle density is around 20-30um from the anterior (Figure 3, Little et al., PLoS Biology 2011), with the vast majority of counts being with 10% of the anterior pole. Further, Durrieu et al. MSB 2018, showed using a Bcd tandem reporter that there was unlikely to be an extended gradient of bcd mRNA (maximum extent of around 50um). Here, we used a simple source domain, which was arguable a little narrow, but not significantly so. We will increase the value in the revision, but the claim that there is an extended bcd mRNA gradient (Spirov et al., Development 2009) has not been substantiated by later experiments.

      • d) Please discuss in the paper how well the simulations in Fig. 3B agree with the experimental data.*

      We will provide these details in the revision.

      • e) Please provide a precise estimate for the statement "Even with an effective diffusion coefficient of 7 μm2s-1, few molecules would be expected at the posterior given the estimated Bcd lifetime (30-50 minutes)" to turn this into a quantitative argument. How many molecules are expected to reach posterior in which model, and how does it compare to experimental observations?*

      This can be estimated based on the root-mean-square distance for diffusive processes. We will provide this in the revision.

      • f) The sentence "we find that a model of Bcd dynamics that explicitly incorporates fast and slow forms of Bcd (rather than a single "effective" dynamic mode) is consistent with a range of observations that are otherwise incompatible with the standard SDD model" needs to be toned down and corrected since a simple SDD appears to be sufficient to account for the observed gradients. If the authors disagree, please specifically point out in the paragraph around line 249 what observations exactly are incompatible with a standard SDD model.*

      This is similar to the point raised by Reviewer 1. While the standard SDD model can explain the overall gradient shape, it is not compatible with the observed time scales and Bcd puncta tracked in the posterior pole. We will improve the Discussion around this point to make the distinctions between the models clearer.

      • 5) Data presentation *
      • a) In line 27 and 122 it would be better to rephrase the wording "find/found" and give credit to previous papers that first made these observations. *

      We will edit in the revision.

      • b) For the statement "This suggests that the dynamics of the fast fraction were not captured by previous FRAP measurements", please explain why this should not be the case even though the fast fraction is shown to be larger than the slow fraction in the current work.*

      We will edit in the revision.

      • c) Similarly, the sentence "The dynamics of the slower mode correspond closely to measured Bcd dynamics from FRAP" likely needs to be corrected since it neglects the contribution of the faster mode, which is fluorescent as well and should also contribute to the dynamics from FRAP.*

      This is similar to the point raised by Reviewer 1 and we will edit in the revision.

      d) In the absence of further evidence (see above), the sentences "We establish that such spatially varying differences in the Bcd dynamics are sufficient to explain how Bcd can have a steep exponential gradient in the anterior half of the embryo and yet still have an observable fraction of Bcd near the posterior pole" and "These results explain how a long- ranged gradient can form while retaining a steep profile through much of its range" in the abstract need to be toned down.

      We are not sure here what needs to be toned down. Our results show that there are (at least) two dynamic forms of Bcd and, combined, they are capable of forming a long-ranged gradient while also ensuring the gradient remains steep in the anterior (because the diffusion coefficient itself varies across the embryo). We will go through these statements and make sure the meaning is clear.

      e) The authors state that "However, we show that eGFP::Bcd in its fastest form can move quickly (~18 μm2s-1), and the fraction of eGFP::Bcd in this form increases at lower concentrations", but this has not been directly shown. Please tone down this statement or directly test the prediction that Bcd has a higher fraction of the fast form in earlier nuclear cycles when Bcd concentration is smaller.

      This is a good suggestion, and we will test whether early nuclear cycles of the anterior domain show faster dynamics.

      *MINOR POINTS * * 1) Introduction * * a) Please explain explicitly what exactly the contention in Bcd, Nodal and Wingless dynamics is in the cited references. *

      We will add in the revision. b) In line 95, it would be better to state that this is a variation of the SDD model rather than "a new model". * We changed from “a new model” to “an improved version of SDD model” in the current version of the manuscript. 2) Methods * * a) The authors state that "The same software was also used to calculate the cross-correlation function", but I couldn't find any cross-correlation analyses. Please clarify. *

      It is line 538. There is no cross correlation. We changed this to the autocorrelation function.

      b) Please correct the "uM" typo to "nM" in the legend of Method Fig. 2A.

      We have changed this in the current version.

      • c) In the sentence "Further, since the brightness eGFP:Bcd in the anterior and posterior cytoplasm is lower compared to the nuclei", "brightness" probably needs to be changed to "concentration" since the molecular brightness is unlikely to change. *

      We edited the line no.591.

      • d) Please explain the background-correction method mentioned in line 612. Please also state at what temperature the experiments were performed.*

      We will add a better background correction in the revision. Currently, it is the non-embryo background as background noise. The measurements are carried out at 25oC.

      *3) Results * * a) Please provide labels for anterior, posterior, dorsal and ventral in Fig. 1A. * * b) Please explain the colors in Fig. 5C. * * c) Please explain the dashed lines in Fig. 3C. * We have edited Figure 1A and Figure 5C. We will edit Figure 3C in further revision.

      *OPTIONAL * * 1) If possible, it would be helpful to mention whether the transgenic animals have any abnormal phenotypes or whether they can rescue the bcd mutant. * We will update in the revision.

      *2) To validate the concentration measurements, it would be ideal if the authors could determine the Bcd concentration gradient using FCS along the anterior-posterior axis. This would also address whether there are further unexpected changes in diffusivity in medial regions and along the anterior-posterior axis that would have to be considered for modeling. * To measure the Bcd concentration using FCS along the whole axis would be a very challenging undertaking. To get the data for the two positions analysed already represents a significant amount of work. We have done SPIM-FCS measurements, and we will be repeating our FCS measurements in the Fritzsche lab at Oxford. Combined, we believe this provides sufficient corroboration of our results.

      *3) Local photoconversion experiments, e.g. in Bcd-Dendra2 embryos if available, would provide compelling support for the relevance of the measurements in the current work. * This is a nice idea, but this would represent a substantial project in its own right and lies beyond the current work.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)):

      *In my estimation the experimental work is rigorous and the results fully support the conclusions of the authors. I was surprised, however, that the HD-only form localizes via very different and simpler dynamics than does full-length Bcd, but nevertheless forms at least a qualitatively similar gradient. That leads to the question as to whether the existence of the fast and slow forms and their different ratios in different parts of the embryo actually are physiologically relevant. I don't see a straightforward way to test this experimentally, because the mutations that effect Bcd gradient formation also affect essential functions of the protein that if abrogated produce severe downstream effects on embryonic development and lethality. However I would like to see this point at least addressed in the discussion. The data and the methods are presented in such a manner that they can be reproduced, and the number of replicates and statistical analysis is overall robust. * We thank the Reviewer for the positive and constructive review. They, like both previous reviewers, raise the issue of the model and how it fits with the data. As outlined above, we will improve this part of the data presentation and also the Discussion to make sure the main results are clear.

      We agree that the underlying importance of the different dynamic forms of Bicoid – and why they change across the embryo – remains unknown. We believe that our careful characterisation of such behaviour is important nonetheless, as it reveals that: (1) morphogen dynamics are more complicated than typically modelled, and this may be just as relevant for ligands moving through extracellular space; and (2) dynamics can vary in space/time, providing an additional possible mechanism of control for regulating morphogen gradient profiles.

      Of course, we would like to explore potential physiological relevance. Further exploration of the homeodomain and its role in regulating dynamics is a potential route, but that belongs in future work.

      *Minor comments: *

      • The presentation of the graphical data measuring Bcd levels along the a-p axis (Fig 1C, 1D, 4C-F and others) needs to be improved, because the grey lines that represent ACF curves are essentially invisible. This is partly because there is usually extensive overlap between the grey lines and other lines. This may be solved by using a more vivid colour than grey for the ACF curves, or perhaps the ACF lines could be made thicker but with some transparency so that overlapping data can be seen. In any event this aspect of the presentation needs to be improved. * We have made the ACF lines thicker to distinguish from the model fit.

      *In Figs 2D and 2I measurements of statistical significance between the proportion of protein in fast and slow modes need to be added. * We will add in the revision.

      *Relevant to line 174 and Fig 2, NLS should be defined when first used, the source of the NLS should be given (is it from Bcd?) and the rationale for looking at eGFP::NLS should be made explicit. *

      We have added details on how the eGFP::NLS is generated in the methods.

      *In Fig 3D the dashed lines need to be defined. I assume these are experimental error bars but this is not stated. *

      We now state this in the legends.

      *On lines 344-5, shouldn't this conclusion concern the HD rather than the NLS? * Yes, thanks for pointing it out it is related to only NLS not NLSHD. We removed this statement from line 351.

      *On line 432, CAP is not an acronym, the correct term is 5' 'cap' or 'cap structure'. Also Cho et al. PMID 15882623 should be added to the references here. * We changed the corresponding section and added the references.

      *On lines 446, 456, 469, and throughout: replace 'blastocyst' with 'blastoderm'. The former term is generally used for embryos that undergo full cellular divisions and cleavage in early embryogenesis, not for syncytial embryos such as Drosophila. * We have changed blastocyst to blastoderm throughout the manuscript.

      Reviewer #4 (Evidence, reproducibility and clarity (Required)):

      Major comments: The averaged autocorrelation curves were fitted to models of diffusion with one and two components. The one-component model was insufficient to reproduce the data and the two-component model seems to fit the data. Have the authors tested models with more than two components? Could it be possible to distinguish more Bcd populations?

      While it is possible to fit with further components, it rarely provides useful further insight. In particular, the error in measuring three tau_D’s is typically very large. In addition, the improvement in the fit will be marginal, and thus the extra components cannot be justified statistically. Of course, we cannot exclude a third (or more) possible dynamic modes, but within the resolution of our FCS measurements two components with triplets are in general the maximum that can be accommodated without overfitting. We will provide evidence for this claim in the supplement of the revised manuscript.

      In Figure 2E, the same concentration of eGFP::NLS is estimated to exist in the cytoplasm and nucleus. Since the NLS should target eGFP to the nucleus, what is the explanation for this observation? Is it possible that the method used to estimate the concentration of molecules is underestimating the concentration in the nucleus or the opposite in the cytoplasm?

      This is a good observation. There are two possible explanations. First, the regular division cycles “reset” the nuclear levels. Therefore, differences may not be so large. Second, FCS measurements of concentration can be noisy, as they depend on the very short time scales in the measurement. We will double check our measurements and clarify this in our revision.

      *In the simulation of the SDD model (Figure 3B), simulations at 10 min, 25 min and 120 min are shown. Assuming that 120 min corresponds to early nc14, are simulations at earlier timepoints corresponding to nc12 and nc13 indistinguishable from the profile at 120 min? This demonstration would further support the option to merge the data from all nuclear cycles. *

      This is a good point. Here, we were primarily focused on showing the time evolution of the model, rather than directly mapping onto experiment. We will clarify in the revision.

      *The results obtained with the BcdN51A mutant show an increase in diffusion speed, while retaining similar proportions of fast and slow populations. In the slow fraction, a new population is found. Assuming that the BcdN51A molecules cannot bind specifically to DNA due to the mutation, what would this newly found population correspond to? Could the authors explore the possibility of nonspecific binding to DNA? The article would also win by discussing more on this aspect or other options. *

      This is an interesting question. Dslow for anterior nuclei of N51A mutants increases (Dslow from ~0.2um2/s to ~1.5 um2/s), and the proportion is similar to the slow fraction of WT Bcd in the anterior nuclei (F=50%). The Dslow values of bcdWT suggest that 0.2um2/s is a result of DNA binding. For bcdN51A, Dslow of 1.5 um2/s is suggestive of nonspecific interaction of bcdN51A to the DNA. Such a nonspecific interaction is also noticed in the case of NLS::eGFP, where we see a significant amount (Dslow~ 1-1.5 um2/s , F=20%) of slow form in the anterior nuclei, likely due to non-specific interaction with the DNA.

      It is worth noting that the inactive homeodomain of transcription factor sex comb reduced (scr) also interacts non-specifically with DNA at high concentration (Vukojevic et al., PNAS 2010). Non-specific interaction of eGFP fluorophore is also noted to be higher in the nuclei of AT-1 cells that suggest “obstacle-free accessible space” is low in the nuclei (Wachsmuth et al., JMB 2000). Therefore, though we do not understand the specific mechanism, our results for N51 mutants are aligned with previous observations of intra-nuclei dynamics.

      The experimental rational behind the BcdMM reporter needs to be better explained as it is not clear. It was previously shown that the N51A mutation disturbs zygotic hb activation and Caudal gradient formation (see Figure 3 in Niessing et al., 2000). Since N51A already causes a strong phenotype by disturbing hb expression and Cad gradient formation, what is the reasoning being adding extra mutations to this background? Since the mutations in the PEST domain and YIRPYL motif are involved in cad translational repression, it would be more interesting to add them to the R54A mutation and further study the repression of cad? It would also shed light on the unexpected no difference or even decrease in diffusion in the cytoplasm of the R54A mutant which should increase if indeed the cad mRNA binding is being repressed.

      Our rationale was to remove more elements of Bcd to see if there was some degree of redundancy – at least in terms of the dynamics.

      The Bicoid homeodomain N51A mutation is physiologically known to cause de-repression of caudal and inhibit hunchback expression. Mechanistically, nuclear Bcd activates hb transcription. However, in the cytoplasm Bcd interacts with other proteins and forms a complex to de-repress caudal. Bcd binds to caudal mRNA through its HD at one end of the complex. However, in the other end, other proteins in the complex are bound to the 5’cap region caudal mRNA. Our rationale for generating the MM mutation was that the N51A mutation may not be sufficient for Bcd to be released from the protein complex. Therefore, additional mutations to N51A may release Bcd from interactions with either DNA or with other proteins through PEST domain and YIRPYL motif.

      *Have the authors confirmed that their BcdR54A indeed inhibits cad translation? *

      We have not tested the eGFP:bcdR54A to inhibit cad translation. We will add the data in the revision.

      *How many embryos of BcdMM were analysed? The authors should also provide a table with all the values in SI as they have done for all the other reporters. *

      We will add this data with the revision.

      *The claims with eGFP::NLSBcdHD need to be supported by data from multiple embryos. Even if multiple ACF curves are obtained from one embryo, analysing only one embryo is not sufficient. This would clarify the fact that this reporter seems to be able to reproduce the mobility of Bcd in the nucleus. *

      We agree and we are arranging to collect more data. This should be completed by the end of the summer.

      *According to the methods, all reporters were expressed in a bcd null background, made with the bcd1 allele. This allele is also known as bcd085 and according to Driever and Nusslein-Volhard, 1988 (PMID: 3383244), this allele only causes an intermediate phenotype. This indicates that a truncated version of the protein probably still exists on the embryo. Do the conclusions obtained here still hold if a truncated version of the Bcd protein exists in addition to their reporters? *

      We used the bcdE1 mutant, a null mutant of bcd. This was used by Gregor et al., Cell 2007 in their generation of the original Bcd::eGFP. We have also recently generated a more complete bcdKO mutation (Huang et al., eLife 2017). Our embryos do not have a clear phenotype that we can relate to the specific bcd- background used. Nonetheless, we agree it is an important point to be clear about the genetic background and we will clarify in the revised manuscript.

      Minor comments: * * In line 45: "Morphogens are signalling molecules", the authors should consider removing the word "signalling" since not all morphogens are, especially the one being studied, Bicoid. * * In lines 80-81 (and also throughout the text): "We measure the Bcd dynamics at multiple locations along the embryo AP-axis", should be more accurate and changed to anterior and posterior of the embryo. Using "multiple locations along the AP axis" is ambiguous and not exact for what was done.

      Yes, this is a fair comment. We have edited these sections in the current manuscript.

      *Throughout the article, the authors refer multiple times to "modes for/of Bcd transport". Since they or others have not proven that Bcd is being transported, which would involve at least another factor, the authors should replace transport by movement, diffusion or a similar word with which they are comfortable. *

      We have changed transport to movement wherever relevant in the text.

      *Suggestion: The authors claim that the Bcd gradient is exponential up to 60% of embryo length. Would this information allow a more precise calculation of the gradient decay length in the exponential region than the 80-100µm stated on line 202? *

      This is an interesting point, but our results suggest that the idea of the decay length is not so applicable in the posterior region. There, the Bcd dynamics are generally quicker, thereby increasing l. Of course, we cannot discount possible spatial variation in degradation. However, in previous work, our Bcd tandem reporter (which is sensitive to changes in degradation) did not reveal spatial variation in degradation.

      In lines 258-259, the sentence "Further, Bcd binds to caudal mRNA, repressing its expression in the cytoplasm" should be improved to clarify the role of Bcd in caudal mRNA translation repression and references should be added. This should also be corrected in the following paragraph.

      We will add the necessary corrections in the revision.

      *In line 262, "mutations" should be singular since it corresponds to only one amino acid mutation. *

      We have corrected this.

      *Figure 4J needs to be corrected as the fractions of the slow and fast populations do not correspond to what is shown in Table 3. For example, Fslow fraction of AC is ~45% in the figure while it is 36% in Table 3. The problem occurs in all fractions. *

      We are sorry there is a mislabelling in the corresponding figure. AN is in the place of AC. We have edited figure 4J and removed the mislabelling.

      *In the discussion, in lines 379-380, "Given the changing fractions of the fast and slow populations in space, the interactions between the populations are likely non-linear". What is the reasoning for non-linearity and not interchangeability? *

      If the interactions between the two populations were linear, then the fraction in each form would be constant across the embryo. Some degree of nonlinearity is required in order to have spatially varying relative populations.

      *In line 432 caudal should be italicized. *

      We have edited this.

      *In the discussion, the authors conclude that "In the nucleus, the two populations can be largely (though not completely) explained by Bcd binding to DNA". The discussion would win by explaining all the possible options. * We will add the necessary changes in the discussion. This is also related to above reviewer comments.

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      Referee #1

      Evidence, reproducibility and clarity

      This manuscript reports a very thorough and careful study of the mobility of Bicoid in the early embryo, explored with single-point fluorescence correlation spectroscopy. Although previous groups have looked into this question in the past, the work presented here is novel and interesting because of the different Bicoid mutants and constructs the authors have examined, in particular with the goal of understanding the role of the protein DNA-binding homeodomain. The authors convincingly show that there is a significant increase in Bicoid dynamics from the anterior to the posterior region of the embryo, and that the homeodomain plays an important role in regulating the protein's dynamics. Their experiments are very well designed and carefully analyzed. The authors also modelled gradient formation to see whether this change in dynamics might play a role in setting the shape of the gradient. I am not sure I fully agree with their conclusion that it does, as mentioned in my comment below. However, it is an interesting discussion to have, and I think this paper makes a significant advance in our understanding of Bicoid's behavior in the early embryo.

      Major comments:

      1. Gradient profile quantification: Some of the conclusions made by the authors rely on the comparison between their model of gradient formation (as captured in the equations in lines 232 and 233) and the Bcd intensity profile measured in the embryos. Since the differences in gradient shape predicted by the different models are very small (see Fig. 3B, which is on a log scale and therefore emphasize small differences, and Fig. 3C), it is very important to understand how reliable the experimental concentration profiles are. At the moment, I do not find the evidence that [Bcd] concentration profile is more consistent with a 2-component diffusion model than a 1-component model very strong. A few comments related to this:
        • 1a. Line 249, it is mentioned that: "observations ... incompatible with the SDD model". Which observations exactly are incompatible with the SDD model?
        • 1b. In Fig. 3D, only the prediction of the 2-component model is shown. What would the simple 1-component diffusion model look like? Is it really incompatible with the data?
        • 1c. Line 243: "The increased fraction in the fast form ... consistent with experimental observation of Bcd in the most posterior" (Mir et al.)". I am not sure how this is significant, since the simple model also predicts there will be Bcd in the posterior - the only difference is how much is there (as shown in Fig. 3C), and it's a very small difference.
        • 1d. Since the difference between models is in the posterior region where Bcd concentration is very low, when comparing the models to the data the question of background subtraction is essential. How was the subtracted background (mentioned line 612) estimated?
        • 1e. Along the same line, were the detectors on the Zeiss LSM analog or photon counting detectors, and how confident can we be that signal is exactly proportional to concentration?
        • 1f. Can the gradients created by the two Bcd mutants (FIg. 4B) be quantified as well, and are they any different from the original Bcd gradient?
        • 1e. What is the pink line in Figure 5C (I am assuming the green one is the same as in Fig. 3D)? It could be better to not use normalization here, or normalize everything respective to the eFP::Bcd data to make comparison in relative concentrations in the posterior for different constructs more evident (also maybe different colors for the three different data sets would help clarity).
        • 1f. Discussion, lines 402-403: Does the detailed shape of the Bcd in the posterior region matter at all, since the posterior is not a region where Bicoid is active, as far as we know? Could a varying Bcd dynamics have other consequences that would be more biologically relevant?
      2. Model for gradient formation (lines 231-238):
        • 2a. Whether the molecules of Bcd can change from their fast to slow form is never questioned. How do we know (or why might we suspect) they do exchange?
        • 2b. The values used in the model for alpha, beta_0 and rho_0 should be mentioned. Maybe having a table with all the parameters in the method section, or even in the supplementary section, would help. The exact values of alpha and beta matter, because if they are large (fast exchange) a single exponential gradient is to be expected, if they are 0 (no exchange) a double exponential gradient is to be expected, with intermediate behavior in between. Which case are we in here?
      3. Discussion about anomalous diffusion (lines 386-388): The 2-component model used by the authors to interpret their FCS data seems very well justified here (excellent fits with very small residuals). I agree with the authors' conclusion that "the dynamics of Bcd within the nucleus are more complicated than a simple model of bound versus unbound Bcd", but I don't see how that can lead to a diagnostic of anomalous diffusion instead. Maybe it is just a matter of exactly explaining what is meant by anomalous diffusion here (since this term is often used to mean different things). A more likely scenario I think, is that there are more than just two Bcd components in the system.
      4. Line 440 and after: What is the evidence that the transition between the two forms might vary non-linearly with Bcd concentration? How would that help adapt to different embryo sizes? It would be good to be more explicit here instead of just referring to another paper.
      5. Since an important aspect of this work is the study of different Bcd constructs in vivo, it is important that these constructs are very clearly described, so the section on the generation of the fly lines (Methods) should be expanded. In particular:
        • 5a. It seems that the eGFP:: NLS control used here was different from that first described in Ref. 64 (and used for FCS experiments in Ref. 30 and 36)? If so, what NLS sequence was used here, and precisely what type of eGFP was used (in particular, was the A206K mutation that prevents dimerization present in the eGFP used)? If it is the same construct as in Ref. 64, it should be mentioned explicitly.
        • 5b. Were the mutant N51A and R54A lines gifts as well, or have they been described before? If so, previous publications should be referenced. If not, how the plasmid was introduced in the embryo should be briefly explained.
      6. Concentration calibration measurements (Methods Fig. 2, line 568 and on). It is well known that background noise is going to interfere with the measurement of N when the signal becomes equivalent to the background noise (Koppel 197, Phys Rev A 10:1938-1945, and for a recent discussion of this effect for morphogens in fly embryos: Zhang et al., 2021, Biophysical Journal 120,4230-4241). It is almost certain that in the low signal regions of the embryo (e.g. posterior cytoplasm) this is affecting the reported concentration, and should be at least acknowledged.
      7. Reference 3 is mis-characterized in two different ways in the manuscript:
        • 7a. Line 50: The conclusion in Ref. 3 was not that the gradient was due to a diffusive process, on the contrary Gregor et al. argued that Bcd was too slow to form such a long-range gradient by diffusion. Studies that do present data consistent with a morphogen gradient formation mechanism driven by diffusion are reference 5, reference 30, Zhou et al., Curr. Biol. 2012;22(8):668-75 and Müller et al., Science 336 (2012) 721-724.
        • 7b. The diffusion coefficient estimated from FRAP measurements and reported in Ref. 3 (D = 0.4 micron^2/s) is mentioned a couple of times in the manuscript (line 66, line 395, line 411). However, this number is simply incorrect. When fast components (such as the ones clearly detected here by FCS) are present, they diffuse out of the photobleached area during the photobleaching step. If that is not corrected for during the analysis (and it wasn't in Ref. 3), then the recovery time measured is just equal to the photobleaching time, and has nothing to do with either the fast or slow fraction of the studied molecule - it has no other meaning than to give a lower bound on the value of the actual effective diffusion coefficient of the molecule. This effect (called the halo effect) is well known in the FRAP community (see e.g. Weiss 2004, Traffic 5:662-671), it has been experimental demonstrated to occur for Bcd-eGFP in the conditions used in Ref. 3 (Reference 30), and the actual diffusion coefficient that should have been extracted from the data presented in Ref. 3 has been recalculated by another group to be instead D = 0.9 micron^2/s (Castle et al., 2011, Cell. Mol. Bioeng. 4:116-121). It would therefore be better to report the corrected value from Castle et al. to help the field converge towards an accurate description of Bcd mobility.

      Minor comments and suggestions:

      1. Figure 1: From panel A, it seems that what is called "Anterior" and "Posterior" is about 150 micron away from the embryo mid-section, i.e. about 100 micron from either the anterior pole or the posterior pole (so not the tip of the embryo, but somewhere in the anterior half or posterior half). Maybe this should be made clear in the text.
      2. Fig. 2A; It might be good to put this graph on a log scale, so that cytoplasmic values are seen more clearly. Also, what about reporting on nuclear to cytoplasmic ratios?
      3. Fig. 2: It could be interesting to plot D_effective as a function of the measured concentration of Bicoid in different locations, since the (interesting) suggestion is made several time that [Bcd] could the a determinant of the protein mobility.
      4. Figure 3B&C: Is the curve for 2-component diffusion (without concentration dependence) for steady-state missing?
      5. Lines 78 and 471: What do the authors mean by "new reagents"? The word reagent evokes a chemical reaction, but there are none here. Do the authors mean new constructs? or new mutants?
      6. Lines 57-59: Another good reference for FCS measurements performed to study the dynamics of a morphogen (in this case Dpp) is Zhou et al., Curr. Biol. 2012;22(8):668-75
      7. Lines 109-111: A word must be missing. Precisely determined what?
      8. Line 278: The increase in the slow mode is expected. Maybe explicitly mention why.
      9. Line 282: "with the fast component increasing", maybe replace with "with the diffusion coefficient of the fast component increasing" or "with the fraction of the fast component increasing".
      10. Line 517: Is there a reason why the dorsal surface is always placed in the coverslip?
      11. Line 524 and on: FCS measurements: What was the duration of each individual FCS measurement? It is great that the exact number of measurements are reported in the supplementary!
      12. An Airy unit of 120 um seems large in combination with an objective with a NA of 1.2, is there a reason for that? What was the radius of the resulting detection volume?
      13. Thank you for detailing the reasons behind the choice of excitation power, an important and often omitted details. Where in the excitation path were the values of the laser power measured (before or after the objective?)?
      14. Line 585: "since the brightness of eGFP::Bcd..." do the authors mean the molecular brightness of a single eGFP::Bcd molecule, or the total fluorescence signal?
      15. It would be good for reference to mention the approximate value of the molecular brightness recorded for these eGFP constructs at the laser power used.
      16. Reference 766: The year (and maybe other things) is missing.
      17. Figure 2 (Methods): The concentrations shown on the figure should be in nM not uM.

      Significance

      Strengths:

      Very careful and systematic study of Bcd's dynamics in the early embryo Use of several mutant and truncated forms of Bcd to pinpoint the importance of the DNA binding domain in setting this dynamics Uncovers a previously unknown change in Bcd dynamics from the anterior to the posterior of the embryo Modelling of the Bcd concentration gradient shape taking into account the measured dynamics

      Limitations:

      The quantitative comparison between modelled and measured gradient could be improved. The discussion of the biological implications of the work is limited

      Advance:

      Uncovers a previously unknown change in Bcd dynamics from the anterior to the posterior of the embryo. This raises very interesting questions about molecular mechanisms involving Bicoid. Other studies (cited in this manuscript) reported on Bcd dynamics, but the present study represents a very welcome expansion of these earlier studies, by looking at spatial dependence and by examining several Bcd constructs.

      Audience:

      Somewhat specialized, as this work should firstly be of interest to scientists studying morphogen gradients. However, it is also a beautiful example dynamical studies in vivo, so it will also be of interest to experimental physicists studying protein motions in vivo (a rather large community).

    1. Tragedy is hard news, and the avoidance of it is so/I news. How do you ever win that game? I got more hard-to-place klds adopted in Florida than anybody ever thought could get done. You know, they didn't get two lines [in lhepress] ... , It's just tough. ... In child abuse and neglect, it's like you're playing a football game and when the evil opponents score, the scoreboard doesn't just light up-Ibey have a five-day discussion of It.

      This section reminds me of something I heard once on a television show. It involved national intelligence and the security of the country. How "our victories are silent but our mistakes are loud". Hardly anyone remembers Umar Farouk Abdulmutallab, the man who tried to detonate a plastics bomb on a Norwest Airlines flight on Christmas. Everyone remembers Ted Kaczynski aka "The Unabomber" I know hindsight is 20/20 but I wonder if Coler had ever even thought about the perception of having close acquittances next to him with HRS and how it would look?

    1. Author Response

      Reviewer #1 (Public Review):

      In this study, the authors study the effect of dynactin disruption on kinetochore fiber (k-fiber) length in spindles of dividing cultured mammalian cells. Dynactin disruption is known to interfere with dynein function and hence spindle pole formation. The main findings are that poles are not required for correct average k-fiber length and that severed k-fibers can regrow to their correct length both in the presence and absence of poles by modulating their dynamic properties at both k-fiber ends. In the presence of poles, regrowth is faster and the variation between k-fiber lengths is smaller. This is a very interesting study with high-quality quantitative imaging data that provides important new insight into potential mechanisms of spindle scaling, extending in an original manner previous work on this topic in cultured cells and in Xenopus egg extract. The Discussion is interesting to read as several possible mechanisms for k-fiber length control are discussed. The technical quality of the study is very high, the experiments are very original, and most conclusions are well supported by the data. Especially, the experiments observing the regrowth of k-fibers after severing and the study of the dynamic properties of these k-fibers provide very novel insight. Addressing the following concerns could potentially improve the manuscript:

      We thank the reviewer for their fair, rigorous, and conceptually engaging remarks.

      (1) The phenotype generated here by disrupting dynactin via overexpressing p50 appears to be different from that caused by knocking down NuMA or dynein - as previously reported by the Dumont lab (Hueschen et al., 2019). In this study here, unfocused spindles are observed whereas earlier turbulent spindles were observed. This raises the question of whether dynein activity that contributes to pole focusing is really completely inhibited here. These discrepancies in phenotypes seem to deserve an explanation. Is k-fiber length in cultured mammalian cells only maintained in the case of this specific type of inhibition?

      We thank the reviewer for the important point about the different phenotypes observed in different dynein inhibition conditions and we refer them to our response to Essential Revision #1. In summary, we believe that different dynein inhibition phenotypes are similar. Unfocused spindles appear turbulent on longer timescales and appear to reach a steady-state on shorter timescales. The amount of pole-unfocusing also seems to correspond to the severity of dynein inhibition (Figure 1—figure supplement 1). We have chosen to study inhibited spindles that were steady-state and unfocused. We have added this discussion in line 129 as well as better characterized our system of dynein inhibition by adding two new figures (Figure 1—figure supplement 1, Figure 1—figure supplement 3).

      Furthermore, we address the question of whether dynein might still be responsible for length regulation despite poles being unfocused in line 433 of the Discussion: “recent work has revealed that mammalian spindles can achieve similar architecture whether or not dynein (or its recruiter NuMA) is knocked out (Neahring et al., 2021). This suggests that the severe defects in spindle coordination (Figure 1, Figure 5) and maintenance (Figure 2) observed in p50-unfocused spindles are more likely due to the loss of spindle poles than due to the loss of dynein activity per se.”

      We have additionally overexpressed p50 in human RPE1 cells and observed qualitatively similarly unfocused yet generally bi-oriented spindles as in rat kangaroo PtK2 cells, showing that the formation of unfocused spindles in PtK2 is not an artifact unique to that cell line (see newly added Figure 1—figure supplement 3). However, these unfocused RPE1 spindles did not have clear, resolvable k-fibers as in PtK2, so length was not quantified. The only method we are aware of that robustly unfocuses poles in PtK2 spindles is p50 overexpression.

      (2) p50 addition and also p150-cc1 addition was often used in Xenopus egg extract in order to inhibit dynein function. Considerably larger concentrations of p50 than p150-cc1 needed to be used. Can the authors estimate the level of overexpression of p50 in the cells they study? It seems that could be possible given that a mCherry fusion protein can be overexpressed. Was it necessary to select cells with a particular level of mCherry-p50 overexpression to observe the reported phenotypes?

      We thank the reviewers for the suggestion to quantify p50 expression and have added Figure 1—figure supplement 1. Due to gradual red laser power loss over months, data from a single day were plotted for proper comparison, but trends were always consistent within any given day. As discussed above, we observed that higher levels of mean p50 intensity corresponded to unfocused spindles. We have clarified that we chose to study these highly overexpressing unfocused spindles in the text and methods, and we speculate that level of p50 overexpression correlates with amount of dynein inhibition and subsequent pole-unfocusing. This is also consistent with the higher concentrations of p50 needed to inhibit dynein in Xenopus.

      (3) Some comparison to previous experiments using p50 and p150-cc1 addition to Xenopus egg extract spindles could put this study better into the context of the available literature. It seems from previous publications that the p50 addition produced short, unfocused, barrel-shaped spindles, indicating that spindle length is maintained without poles, whereas the p150-cc1 addition produced elongating spindles (e.g. Gaetz & Kapoor, 2004).

      We appreciate the reviewer’s discussion of dynein inhibition in the Xenopus context.

      While Xenopus has been used to study spindle size regulation, it has not been as useful to study k-fiber length regulation, which we focus on. Xenopus spindles have a different architecture, with k-fibers that are not discrete and continuous like in mammalian spindles. Indeed, while p50 and p150-CC1 overexpression alter spindle length in Xenopus, they do not have the same effect in mammalian spindles. Additionally, p150-CC1 does not robustly unfocus poles in mammalian spindles as it does in Xenopus; instead, it leads to an inconsistent variety of spindle disorganization phenotypes with frequently focused poles in PtK2 (data not shown). We speculate this variety of spindle phenotypes arise from a different mechanism of dynein inhibition that does not fully target pole-focusing.

      However, we agree that referencing prior Xenopus work establishes important context and precedent. In line 95 of the Introduction, we state “…inhibiting dynein unfocuses poles but spindles still form albeit with altered lengths in Drosophila (Goshima et al., 2005) and Xenopus (Gaetz and Kapoor, 2004; Heald et al., 1996; Merdes et al., 1996), and without a clear effect on mammalian spindle length (Guild et al., 2017; Howell et al., 2001),” addressing the different effects of dynein inhibition in Xenopus compared to mammalian spindles. We have also added direct mentions of p50 in Xenopus in line 129 (see Essential Revision #1 response).

      Finally, we have added a figure showing overexpression of p50 in a human RPE1 cells to show reproducibility of pole unfocusing across other mammalian cell types (see newly added Figure 1—figure supplement 3).

      (4) In this context, it seems that some more explanation is required for the observations presented in Fig. 1D and 1E. It appears that spindle length and k-fiber length have been measured quite differently. Not much information is provided for how spindle length was defined and measured (please expand this part of the Methods). Could the two different methods of measurement be the reason for the mean k-fiber length remaining unaltered in dynactin-disrupted spindles, whereas the spindle length increases in these cells? If not, do non-k-fiber microtubules contribute to unfocused spindles being longer or are chromosomes not aligned in the metaphase plate causing the increase in spindle length by misalignment of k-fiber sister pairs?

      We thank the reviewers for pointing out the lack of clarity in Figures 1D and 1E. We have expanded and clarified the Methods section describing how spindle axes were measured and how k-fiber lengths were measured, as well as included examples and cartoons to illustrate them (see newly added Figure1—figure supplement 4).

      To clarify, we did not intend to directly measure spindle length, but we did approximate the size of each spindle’s “footprint” in Figure 1D as well as measure individual k-fiber length in Figure 1E. It is now clarified in the Methods line 898 as “Spindle minor and major axes lengths were determined by cropping, rotating, then thresholding spindle images with the Otsu filter using SciKit. Ellipses were fitted to thresholded spindles to approximate the length of their major and minor axes using SciKit’s region properties measurement (Figure1—figure supplement 4A). In control spindles, the major axis corresponded to spindle length along the pole-to-pole axis, and the minor axis corresponded to spindle width along the metaphase plate axis. However, unfocused spindles were disorganized along both axes to the extent where the minor axis did not always correspond to the metaphase plate axis. Thus, Figure 1D reports ”spindle minor axis length” and “spindle major axis length” rather than “spindle width” and “spindle length”. Furthermore, it is worth noting that in unfocused spindles, spindle length is decoupled from k-fiber length because of k-fiber disorganization along both axes. Thus, spindle length was not measured in unfocused spindles...”

      We additionally removed the potentially confusing terminology of “wider” and “longer” in the Results section to make clear that we are approximating spindle size, not spindle length and width, and we now state in line 168,“ k-fibers were more spread out in the cell, with spindles covering a larger area compared to control along both its major and minor axes (Figure 1D).”

      We believe our clarification and expansion of the Methods section, as well as inclusion of a new supplementary figure and cartoon address the reviewer’s points, and we thank them for pointing out the lack of clarity.

      (5) It seems that in the Discussion it is implied that k-fibers can respond to severing in both focused and unfocused spindles by modulating their dynamics at both ends of the k-fibers, but in the Results section the wording is more cautious because of the difference in 'flux' in severed and unsevered unfocused spindles is not significant (Fig. 4D, blue data). It appears indeed that there is also a difference in flux between severed and unsevered unfocused spindles, but the number of data points is too small. Depending on how difficult these experiments are, it could be worth increasing the size of the data set to come to a clear conclusion, given that the data shown in Figs. 3 and 4 are quite remarkable and form the core of the study.

      We appreciate the reviewer’s close reading and pertinent suggestions.

      As detailed in our response to Essential Revision #3, we did not increase the sample size for unfocused spindles since it would not be reasonably feasible to show significant differences in flux. However, we performed more ablations and photomarking in control spindles as detailed in our response to this reviewer’s point 6 below, a different but related point.

      (6) Can the authors exclude that the stopping of 'flux' at minus ends after severing is due to some sort of permanent damage induced by ablation? In other words, do severed spindles begin to flux again once they have regrown to their original length?

      We thank the reviewer for their important points.

      We have addressed this question in the newly added Figure 4—figure supplement 1 as described in our response to Essential Revision #3 to show that flux resumes after length recovery. In summary, we observed no adverse effects of ablation on k-fiber minus-ends. Severed k-fibers have restored lengths, and minus-end dynamics several minutes after ablation.

      (7) To this reader, the conceptualization of distinguishing between 'global' and 'local' effects/behavior was a little confusing, both in the title and also later in the text. The concept of 'local' regulation of k-fiber length appears to contradict the observation that k-fiber length can be regained after severing by changes in the dynamics at both ends (so at two very different locations) which is a rather remarkable finding. Maybe distinguishing between 'individual' and 'collective' k-fiber behavior could be clearer.

      We appreciate the reviewer’s consideration of terminology. We have addressed this by clearly defining our use of ‘local’ to refer to individual k-fibers as a unit where appropriate in the text (lines 271, 449). We chose these terms since they can help describe individual versus collective properties, while simultaneously emphasizing the aspects of global architecture and spatial organization in the spindle.

      (8) Can the authors exclude that some of the differences between unfocused and focused spindles could be due to altered dynein activity at kinetochores? Or due to the dynein-dependent accumulation of certain spindle proteins along microtubules towards the minus ends of k-fibers or other spindle microtubules, instead of being due to only the presence versus absence of poles? Could this be tested by ablating both poles? If this is too challenging, a discussion of these possibilities could be justified.

      We appreciate the reviewer’s consideration of kinetochore activity as well as other methods of removing poles. However, p50 overexpression is currently the only method to robustly unfocus spindles in PtK2 cells – ablating poles or removing pole-associated structures such as centrosomes does not abolish pole-focusing in this system (Khodjakov et al., 2000). Furthermore, we now discuss the possibility that altered dynein activity (such as activity at kinetochores) may give rise to the phenotypes we describe in our work in line 433: “…recent work has revealed that mammalian spindles can achieve similar architecture whether or not dynein (or its recruiter NuMA) is knocked out (Neahring et al., 2021). This suggests that the severe defects in spindle coordination (Figure 1, Figure 5) and maintenance (Figure 2) observed in p50-unfocused spindles are more likely due to the loss of spindle poles than due to the loss of dynein activity per se. Though we cannot exclude it, this also suggests that the findings we make in unfocused spindles are not due changes in activity of the dynein population at kinetochores.”

      Reviewer #2 (Public Review):

      The mitotic spindle of eukaryotic cells is a microtubule-based assembly responsible for chromosome segregation during cell division. For a given cell type, the steady-state size and shape of this structure are remarkably consistent. How this morphologic consistency is achieved, particularly when one considers the complex interplay between dynamic microtubules, spatial and temporal regulation of microtubule nucleation, and the activities of several microtubule-based motor proteins, remains a fundamental unanswered question in cell biology. In this work by Richter et al., the authors use biochemical and biophysical perturbations to explore the feedback between mitotic spindle shape and the dynamics of one of its main structural elements, kinetochore fibers (k-fibers) - bundles of microtubules that extend from kinetochores to spindle poles. Overexpression of the p50 dynactin subunit in mammalian tissue culture cells (Ptk2) was used to inhibit the microtubule motor cytoplasmic dynein resulting in misshapen spindles with unfocused poles. Measurements of k-fiber lengths in control and unfocused conditions showed that although mean k-fiber length was not statistically different, the variation of length was significantly higher in unfocused spindles, suggesting that k-fiber length is set locally, occurring in the absence of focused poles. With a clever combination of live-cell imaging with photoablation and/or photobleaching of fluorescently-labeled k-fibers, the authors went on to explore the mechanistic bases of this length regulation. K-fiber regrowth following ablation occurred in both conditions, albeit more slowly in unfocused spindles. Paired ablation and localized photobleaching on the same k-fiber revealed that microtubule dynamics, specifically those at the plus-end, can be tuned at the level of individual k-fiber. Lastly, the authors show that chromosome segregation is severely impaired when cells with unfocused spindles are forced to enter mitosis. The work's biggest strength is the application of an innovative experimental approach to address thoughtful and well-articulated hypotheses and predictions. Conclusions stemming from the experiments are generally well-supported, though the experiments addressing the "tuning" of k-fiber dynamics could be bolstered by additional data points and perhaps better presented. The manuscript would also benefit from the inclusion of some investigation of spatial differences in the observed effects as well as the molecular and biophysical basis of the observed feedback between k-fiber length and focused poles.

      We appreciate the reviewer providing pertinent, rigorous, and intellectually astute suggestions.

      Comments/Concerns/Questions:

      1) In the discussion, the authors acknowledge that the changes in spindle morphology resulting from p50 overexpression are likely also causing changes in the well-characterized RanGTP/SAF gradients that radiate from chromosome surfaces. Why did the authors did not include an analysis of k-fiber length as a function of positioning within the spindle? The inclusion of this data would not require more experimentation and could be added as a plot showing K-fiber length versus distance from the geometric center of the spindle (defined by the intersection of the major and minor axes perhaps?).

      We thank the reviewer for this pertinent suggestion and refer them to our response to Essential Revision #2. Briefly, we have added the recommended analyses to Figure 1—figure supplement 6 by correlating k-fiber length to position along the spindle’s longitudinal and latitudinal axes.

      2) The authors also acknowledge the established relationship between MT length and MT end dynamics, yet in their ablation studies, the average initial k-fiber length at ablation in control spindles was higher than that for k-fibers in unfocused spindles. It seems that this difference makes the interpretation of the data, particularly the conclusion that fiber growth rates differ due to the absence of focused poles, a bit tenuous. To address this, the authors should consider including plots of grow-back rates versus k-fiber length (again, this should not require additional experiments, just more analysis).

      We thank the reviewer for their critical thinking about experiments. We would like to clarify to the reviewer that initial k-fiber lengths within unfocused spindles preceding ablation were not actually longer on average compared to the average length of control k-fibers from Figure 1E (Figure 2—figure supplement 1). We apologize that this unexpected artifact was not clear in the text and have now reworded line 232 to be more straightforward: “Mean k-fiber lengths in unfocused spindles before ablation appeared to be shorter (Figure 2D); however, this was due to not capturing the full length of k-fibers in a single z-plane while imaging ablated k-fibers. Indeed, length analysis of full z-stacks from unfocused spindles before ablation yielded an indistinguishable mean k-fiber length compared to control k-fibers in Figure 1E (Figure 2—figure supplement 1). Thus, ablated k-fibers were compared to their unablated neighbors as internal controls.”

      We believe that this language clearly calls out the perceived inconsistency, and that our use of internal controls overcomes this confounding factor to make meaningful conclusions. We address the relationship of k-fiber length and growth rate in our response to Essential Revision #2. We are not including it in the manuscript based on our inability to make any meaningful conclusion to either support or exclude the possibility of length-dependent growth rates.

      3) As presented, the data shown in Figure 4 is confusing and does not seem very compelling. The relationship between the kymographs and time series is unclear as is the relationship between the dashed lines in the kymographs and the triangles and the plots in the 4B time series and 4C, respectively. Furthermore, it's not always clear what the triangles are pointing to (e.g. in the unfocused condition time series). The authors might want to consider reworking this figure and providing more measurements of flux following ablation in both the control and unfocused conditions. Lastly, the authors should clarify what negative displacement means.

      We apologize for the unclear figure annotations and thank reviewers for their suggestions. As discussed in our response to Essential Revision #3, we believe we have improved the clarity and presentation of figures and kymographs. More measurements of flux after ablation in unfocused spindles was not feasible as discussed; however, we have performed these measurements in control spindles and added Figure 4—figure supplement 1 to strengthen conclusions about turning flux off/on after ablation.

      We have additionally clarified axis titles by replacing “negative displacement” with the more intuitive descriptor “photomark position relative to minus-end” and clearly defining it in the figure legends in line 565 as follows: “Figure 3 […] (D) Minus-end dynamics, where photomark position over time describes how the mark approaches the k-fiber’s minus-end over time in control and unfocused k-fibers.”

      We thank reviewers for their suggestions to improve clarity and bolster our conclusions.

    2. Reviewer #2 (Public Review):

      The mitotic spindle of eukaryotic cells is a microtubule-based assembly responsible for chromosome segregation during cell division. For a given cell type, the steady-state size and shape of this structure are remarkably consistent. How this morphologic consistency is achieved, particularly when one considers the complex interplay between dynamic microtubules, spatial and temporal regulation of microtubule nucleation, and the activities of several microtubule-based motor proteins, remains a fundamental unanswered question in cell biology. In this work by Richter et al., the authors use biochemical and biophysical perturbations to explore the feedback between mitotic spindle shape and the dynamics of one of its main structural elements, kinetochore fibers (k-fibers) - bundles of microtubules that extend from kinetochores to spindle poles. Overexpression of the p50 dynactin subunit in mammalian tissue culture cells (Ptk2) was used to inhibit the microtubule motor cytoplasmic dynein resulting in misshapen spindles with unfocused poles. Measurements of k-fiber lengths in control and unfocused conditions showed that although mean k-fiber length was not statistically different, the variation of length was significantly higher in unfocused spindles, suggesting that k-fiber length is set locally, occurring in the absence of focused poles. With a clever combination of live-cell imaging with photoablation and/or photobleaching of fluorescently-labeled k-fibers, the authors went on to explore the mechanistic bases of this length regulation. K-fiber regrowth following ablation occurred in both conditions, albeit more slowly in unfocused spindles. Paired ablation and localized photobleaching on the same k-fiber revealed that microtubule dynamics, specifically those at the plus-end, can be tuned at the level of individual k-fiber. Lastly, the authors show that chromosome segregation is severely impaired when cells with unfocused spindles are forced to enter mitosis. The work's biggest strength is the application of an innovative experimental approach to address thoughtful and well-articulated hypotheses and predictions. Conclusions stemming from the experiments are generally well-supported, though the experiments addressing the "tuning" of k-fiber dynamics could be bolstered by additional data points and perhaps better presented. The manuscript would also benefit from the inclusion of some investigation of spatial differences in the observed effects as well as the molecular and biophysical basis of the observed feedback between k-fiber length and focused poles.

      Comments/Concerns/Questions:

      1) In the discussion, the authors acknowledge that the changes in spindle morphology resulting from p50 overexpression are likely also causing changes in the well-characterized RanGTP/SAF gradients that radiate from chromosome surfaces. Why did the authors did not include an analysis of k-fiber length as a function of positioning within the spindle? The inclusion of this data would not require more experimentation and could be added as a plot showing K-fiber length versus distance from the geometric center of the spindle (defined by the intersection of the major and minor axes perhaps?).<br /> 2) The authors also acknowledge the established relationship between MT length and MT end dynamics, yet in their ablation studies, the average initial k-fiber length at ablation in control spindles was higher than that for k-fibers in unfocused spindles. It seems that this difference makes the interpretation of the data, particularly the conclusion that fiber growth rates differ due to the absence of focused poles, a bit tenuous. To address this, the authors should consider including plots of grow-back rates versus k-fiber length (again, this should not require additional experiments, just more analysis).<br /> 3) As presented, the data shown in Figure 4 is confusing and does not seem very compelling. The relationship between the kymographs and time series is unclear as is the relationship between the dashed lines in the kymographs and the triangles and the plots in the 4B time series and 4C, respectively. Furthermore, it's not always clear what the triangles are pointing to (e.g. in the unfocused condition time series). The authors might want to consider reworking this figure and providing more measurements of flux following ablation in both the control and unfocused conditions. Lastly, the authors should clarify what negative displacement means.

    1. Author Response

      Reviewer #1 (Public Review):

      This paper studies color vision in anemonefish. The central conclusion of the paper is that anemonefish use signals from their UV cones to discriminate colors that would not otherwise be distinguishable; this differs from other fish in which UV cones extend the range of wavelengths of sensitivity but do not add a dimension to color vision. The work fits into a rich history of studies investigating how color vision fits into an animal's ecological niche. My primary concerns regard the microspectrophotometry data from single cones and some aspects of the presentation of the behavioral data.

      Microspectrophotometry

      The spectral properties of the cone types are a key issue for interpreting the results. These were measured using MSP, and fits are shown in Figure 2. The raw data shown in Fig. S1 appears more complicated than indicated in the main text. The templates miss the measurements across broad wavelength bands in each cone type. Particularly concerning is the high UV absorbance across cone types and the long-wavelength absorbance in the UV cone. It is not clear how this picture supports the relatively simple description of cone types and spectral sensitivities given in the main text and which forms the basis of the modeling.

      Microspectrophotometry is an inherently noise-prone measurement technique, particularly for very small photoreceptor outer segments such as that of single cones, which are also difficult to detect as intact, isolated (nonoverlapping) cells. As such, the absorbance curve fitting and derived lambda max (λmax) values should be treated as estimates. The accuracy of these estimates is adequate for this type of study, and visual modelling results have been shown to be robust against small errors (±10 nm λmax) in photoreceptor sensitivity for multiple species [see Lind, O. & Kelber, A. (2009). Vis Res. 49(15), 1939-1947; and Bitton, PP. et al. (2017). PLOS ONE, 12: e0169810]. We consider it highly unlikely that small shifts in cone λmax from measurement error would make a meaningful difference to the colour discrimination thresholds.

      It should be noted that the raw data shown in the original Supplementary Figure 1, included all scans overlain with an average absorbance curve for presentation purposes; however, the actual lambda max values for different cone types were measured and then averaged among individual scans fitted with photopigment absorbance curve templates. For clarity and transparency, we have now provided three multipaned plots (see Figure 1 – figure supplements 1-3) showing the individual pre- and post-bleach scans of absorbance spectra, fitted absorbance curve templates, and R2 values from the best visual pigment template fit.

      It is worth noting that most of the cone absorbance spectra found in our study closely resemble those in λmax and quality to those measured in another anemonefish species (Amphiprion akindynos) [see Supplementary Figure 1 in Stieb S. et al. (2019). Sci Rep. 9, 16459]. These cone λmax values can also be reconciled with previous estimates on opsin λmax based on amino acid sequences and cone opsin expression in the A. ocellaris retina characterised in Mitchell LJ et al. (2021). GBE, 13: evab184.

      Evidence that the unusual long-wavelength absorbance detected in a couple of the single cone (pre-bleach) measurements were not of visual pigment in origin comes from post-bleach scans, which showed their persistence (i.e., did not show a photobleaching response) and were likely instead contaminants (e.g., blood, RPE pigment). UV absorbance in some of the double cone measurements (above that expected of the prebleached beta peak from chromophore spectral absorption) can be attributed to either noise from scans as is quite typical of MSP and/or partial (accidental) bleaching from stray light sources. Although utmost care was taken to minimise contamination and unintended bleaching sometimes it is unavoidable.

      We refer the Reviewer to multiple published studies for further examples of typical MSP measurements that share similar levels of noise to ours e.g., see Figure 1 in Knott B. et al. (2013). JEB, 216:4454-4461; Figure 3 in Schott, RK et al. (2015). PNAS, 113(2): 356-361; Figure 2 in Dalton BE et al. (2014). Proc R Soc B. 281; Figure 5 in Tosetto, JE et al. (2021). Brain Behav Evol. 96: 103-123.

      Presentation

      The results are not presented in a straightforward way - at least for this reviewer. What is missing for me is a clear link between the psychometric curves in Figure 3A and the discrimination thresholds indicated in Figure 3B and Figure 4. Figure 3A is only discussed in the text on line 289 - after Figure 4 has been introduced and discussed. It would have been very helpful for me if the psychometric curves were first introduced and described, then the relation to Figure 3B was clearly indicated (perhaps with a single psychometric curve as an example). Similarly for Figure 4 the relationship between specific psychometric curves and the threshold plotted would be quite helpful. Currently it takes a careful reading to understand why being below the dashed line in Figure 4 is important.

      We have made the following changes, including the introduction of the psychometric curves earlier in the results (lines 236-249) and moved the psychometric function comparison before the mention of Figure 4. Additionally, to make the association between the plotted colour loci and psychometric curves clearer, we have added a smaller psychometric curve plot adjacent to the colour space (in Figure 3B) using red as an example which has an averaged psychometric curve overlying the individual fish curves. The figure caption (lines 250-274) explains that the plotted colour loci and given thresholds are mean values calculated from the individual fish behavioural data.

      We have also added a brief reminder that the theoretical limit of colour discrimination is predicted by the RNL model as 1∆S, where in our task fish should be just able to distinguish targets from grey distractors (see lines 222-224). To clarify, the plotted values in Figure 4B are both the individual fish thresholds (points) and average threshold (black bar) per colour set. The individual threshold values are taken at a correct choice probability of 50% from fitted psychometric curves of fish behavioural performance (shown in Figure 3A).

      RNL model

      The data is fit and interpreted in the context of the receptor noise limited model. The paragraph in the discussion about complementary color pairs suggests that this model is incorrect (text around line 332). Consideration of how the results depend on the RNL model is important, especially given the interpretation here.

      The inability of the RNL model to account for the observed asymmetry between color discrimination thresholds implies that they cannot be solely attributed to photoreceptor noise. We can therefore infer from the asymmetry that thresholds are set by a higher-level process, whether that involves post-receptor processes within the inner retina or in the brain remains to be investigated. As explained in lines 396-397 one possibility is that activation of the UV receptor suppresses noise in the visual pathway or enhances the saliency of colors for anemonefish. The high sensitivity to violet-green, which was found in all six of the fish tested, is consistent with the heightened saliency of this color (lines 397-399).

      Figure 3B

      This is the key figure in the paper. But several issues make seeing the data in this figure difficult. First, the important part of the figure is buried near the origin and hard to see. Can you show a surface that connects the thresholds in the different chromatic directions, or otherwise highlight the regions of discriminable and not discriminable colors?

      See previous comment. In short, we have taken the advice of the Reviewer and added highlighted areas around the regions of discriminable colors in Figure 3B to help visually separate them from the non-discriminable regions of colors (from grey). Additionally, we have added an inset showing an enlarged image of the area surrounding the centre of colour space.

      Reviewer #2 (Public Review):

      Mitchell and colleagues examined the contribution of a UV-sensitive cone photoreceptor to chromatic detection in Amphiprion ocellaris, a type of anemonefish. First, they used biophysical measurements to characterize the response properties of the retinal receptors, which come in four spectrally-distinct subtypes: UV, M1, M2, and L. They then used these spectral sensitivities to construct a 4-dimensional (tetrahedral) color space in which stimuli with known spectral power distributions can be represented according to the responses they elicit in the four cone types. A novel five-LED display was used to test the fish's ability to detect "chromatic" modulations in this color space against a background of random-intensity, "achromatic" distractors that produce roughly equal relative responses in the four cone types. A subset of stimuli, defined by their high positive UV contrast, were more readily detected than other colors that contained less UV information. A well-established model was used to link calculated receptor responses to behavioral thresholds. This framework also enabled statistical comparisons between models with varying number of cone types contributing to discrimination performance, allowing inferences to be drawn about the dimensionality of color vision in anemonefish.

      The authors make a compelling case for how UV light in the anemonefish habitat is likely an important ecological source of information for guiding their behavior. The authors are to be commended for developing an elegant behavioral paradigm to assess visual performance and for incorporating a novel display device especially suited to addressing hypotheses about the role of UV light in color perception. While the data are suggestive of behavioral tetrachromacy in anemonefish, there are some aspects of the study that warrant additional consideration:

      1) One challenge faced by many biological imaging systems is longitudinal chromatic aberration (LCA) - that is, the focal power of the system depends on wavelength. In general, focal power increases with decreasing wavelength, such that shorter wavelengths tend to focus in front of longer wavelengths. In the human eye, at least, this focal power changes nonlinearly with wavelength, with the steepest changes occurring in the shorter part of the visible spectrum (Atchison & Smith, 2005). In the fish eye, where the visible spectrum extends to even shorter wavelengths, it seems plausible that a considerable amount of LCA may exist, which could in turn cause UV-enriched stimuli to be more salient (relative to the distractor pixels) due to differences in perceived focus rather than due solely to differences in their respective spectral compositions. Such a mechanism has been proposed by Stubbs & Stubbs (2016) as a means for supporting "color vision" in monochromatic cephalopods (but see Gagnon et al. 2016). It would be worth discussing what is known about the dispersive properties of the crystalline lens in A. ocellaris (or similar species), and whether optical factors could produce sufficient cues in the retinal image that might explain aspects of the behavioral data presented in the current study.

      This is an interesting point, and we appreciate the reviewer’s thoughtful comment regarding this topic especially as LCA increases exponentially in the UV. Although we certainly cannot disprove such a mechanism in the present study, we are highly sceptical that LCA could be used by reef fish and is involved in the heightened saliency of UV stimuli. Previous work has found that LCA is mostly corrected for in the teleost retina of both marine and freshwater species by graded, multifocal lenses that focus different wavelengths at the same depth as their maximally sensitive cone photoreceptors [e.g., for evidence in African cichlids see Kröger, R. H. H. et al. (1999). J Comp Physiol. A, 184, 361-369; Malkki, P. E. & Kröger, R. H. H. (2005). J Opt. A, 7, 691-700; and for various reef fishes see Karpestam, B. et al. (2007). J Exp Biol., 210, 16: 2923-2931]. In essence, LCA is corrected in the eyes of many teleosts by accurately tuning longitudinal spherical aberration through having a graded density lens. We draw particular attention to the latter reference which comparatively examined the optical properties of reef fish lenses, including diurnal, planktivorous damselfishes (from the same family as anemonefishes, Pomacentridae). They found that not only were the lenses of these species highly UV-transmissive (as we show in anemonefish), but all were multifocal and capable of focusing both visible (non-UV) and UV wavelengths. Considering the coastal cephalopod species examined thus far, all of them contain only one type of visual pigment which is packed in their long photoreceptor (150-450µm long outer segment) across an entire retina (Chung and Marshall 2016, Proceeding B). Theoretically, given these long photoreceptors, the LCA and the resulting differentials of focal length onto different patches of photoreceptors or different depth of the outer segment might provide cues for colour discrimination even though no behavioural evidence exists to prove this hypothesis yet. Unlike the cephalopod case, the four specific spectral cones arranged in a mosaic pattern along with their very short outer segments (5-10µm) in the anemonefish retina likely makes the LCA less effective in this retinal design.

      We have added a short paragraph (Lines 400-412) discussing the possibility of an optical mechanism contributing to heightened UV saliency with a particular focus on LCA and our thoughts on why we consider it an unlikely mechanism in anemonefish.

      2) The authors provide a quantitative description of anemonefish visual performance within the context of a well-developed receptor-based framework. However, it was less clear to me what inferences (if any) can be drawn from these data about the post-receptoral mechanisms that support tetrachromatic color vision in these organisms. Would specific cone-opponent processes account for instances where behavioral data diverged from predictions generated with the "receptor noise limited" model described in the text? The general reader may benefit from more discussion centered on what is known (or unknown) about the organization of cone-opponent processing in anemonefish and related species.

      In short, we do not know the specific opponent interactions of anemonefish cones. The RNL model assumes all possible opponent interactions in its calculations. From our results, very little can be said about the post-receptor mechanisms involved in their putative tetrachromatic vision. We would like to avoid overreaching beyond what our data can show. A future directions section has now been added to the discussion (lines 467-497), which briefly mentions the known UV opponency in larval zebrafish and that future investigation in anemonefish should attempt to disentangle the specific opponent (chromatic) and non-opponent (achromatic) circuits in the anemonefish retina.

      Reviewer #3 (Public Review):

      The comments below focus mainly on ways that the data and analysis as currently present do not to this reviewer compel the conclusions the authors wish to draw. It is possible that further analysis and/or clarification in the presentation would more persuasively bolster the authors' position. It also seems possible that a presentation with more limited conclusions but clarity on exactly what has been demonstrated and where additional future work is needed would make a strong contribution to the literature.

      • Fig 3A. It might be worth emphasizing a bit more explicitly that the x-axis (delta S) is the result of a model fit to the data being shown, since this then means that if RNL model fit the data perfectly, all of the thresholds would fall at deltaS = 1. They don't, so I would like to see some evaluation from the authors' experience with this model as to whether they think the deviations (looks like the delta S range is ~0.4 to ~1.6 in Figure 4B) represent important deviations of the data from the model, the non-significant ANOVA notwithstanding. For example, Figure 4B suggests that the sign of the fit deviations is driven by the sign of the UV contrast and that this is systematic, something that would not be picked up by the ANOVA. Quite a bit is made of the deviations below, but that the model doesn't fully account for the data should be brought out here I think. As the authors note elsewhere, deviations of the data from the RNL model indicate that factors other than receptor noise are at play, and reminding the reader of this here at the first point it becomes clear would be helpful.

      We have now stated more explicitly in the figure caption for Figure 3A, that the delta S values presented were calculated by fitting fish behavioral data to the RNL model. To test the overall effect that the sign of the UV contrast had on the discrimination threshold, we have now included ‘contrast’ (positive or negative) as another fixed effect in the linear mixed effects model. We have now included details of this test in the results which shows the systematic effect (lines 338-340). Additionally, as suggested we now briefly introduce in the results the idea that factors other than receptor noise are causing the observed deviations in data from the RNL model.

      • Line 217 ff, Figure 4, Supplemental Figure 4). If I'm understanding what the ANOVA is telling us, it is that the deviations of the data across color directions and fish (I think these are the two factors based on line 649) is that the predictions deviate significantly from the data, relative to the inter-fish variability), for the trichromatic models but not the tetrachromatic model. If that's not correct, please interpret this comment to mean that more explanation of the logic of the test would be helpful.

      The interpretation of the ANOVA by the Reviewer is mostly correct. We had the variables color set and Fish ID, with threshold delta S as the dependent variable. This showed that deviations from the predicted threshold were significant relative to the inter-fish variability for the trichromatic models. Missing details describing the ANOVA have now been added to the methods (lines 789-798).

      Assuming that the above is right about the nature of the test, then I don't think the fact that the tetrachromatic model has an additional parameter (noise level for the added receptor type) is being taken into account in the model comparison. That is, the trichromatic models are all subsets of the tetrachromatic model, and must necessarily fit the data worse. What we want to know is whether the tetrachromatic model is fitting better because its extra parameter is allowing it to account for measurement noise (overfitting), or whether it is really doing a better job accounting for systematic features of the data. This comparison requires some method of taking the different number of parameters into account, and I don't think the ANOVA is doing that work. If the models being compared were nested linear models, than an F-ratio test could be deployed, but even this doesn't seem like what is being done. And the RNL model is not linear in its parameters, so I don't think that would be the right model comparison test in any case.

      Typical model comparison approaches would include a likelihood ratio test, AIC/BIC sorts of comparisons, or a cross-validation approach.

      If the authors feel their current method does persuasively handle the model comparison, how it does so needs to be brought out more carefully in the manuscript, since one of the central conclusions of the work hinges at least in part on the appropriateness of such a statistical comparison.

      Our visual model comparisons were aimed at assessing whether a trichromatic or tetrachromatic model best fit the colour discrimination data. The trichromatic and tetrachromatic models assume two and three opponency pathways, respectively. If the fish were not tetrachromatic, and instead trichromatic, then we would expect that the RNL model should better fit the data with two opponency mechanisms (rather than three). Our reason for making this assessment, is because of the possibility that not all the cones could be contributing to colour vision and could be used exclusively for achromatic tasks (e.g., luminance vision or motion detection). However, according to our finding that the data best fit the tetrachromatic model (i.e., how the behavioural discrimination thresholds more closely fitted the theoretical prediction of 1∆S), it is likely that anemonefish used all four cones for colour vision.

      We have also now repeated our analysis using unweighed delta S values which are calculated using general n-dimensional models of colour vision (using the PAVO2 package). These models essentially follow the same initial steps followed by the RNL model (and many others) but omit the receptor noise correction stage. After comparing (using ANOVA, see lines 303-311) the predicted thresholds with the data in this non-RNL space, it was found that again the tetrachromatic model predictions did not deviate significantly from the data relative to individual fish performance; however, we also found that the trichromatic model without M2 cone input no longer differed from the predicted values. In this case, it seems that the extra noise parameter did contribute to the difference in fit. Whether this is a biologically meaningful comparison (as all photoreceptors contain noise) is an open question. We have added a short statement explicitly framing our interpretation of anemonefish having a 3-D colour space to being in accordance with the closeness of RNL model predictions (lines 370-371, 506-508).

      • Also on the general point on conclusions drawn from the model fits, it seems important to note that rejecting a trichromatic version of the RNL model is not the same as rejecting all trichromatic models. For example, a trichromatic model that postulates limiting noise added after a set of opponent transformations will make predictions that are not nested within those of RNL trichromatic models. This point seems particularly important given the systematic failures of even the tetrachromatic version of the RNL model.

      This is a good point. We have limited our conclusions to specifically address trichromatic models generated within the framework of the RNL model by adding in the conclusion section that fish psychophysical thresholds were best explained by the RNL model when all four cone types contributed to colour vision (see lines 370-371, 506-508). In this same sentence, we have also added in parentheses that “suggesting (but not proving) tetrachromacy” (line 508). We have also edited the abstract to state that our results were “…best described by a tetrachromatic model using all four cone types…”, rather than stating we have shown tetrachromacy (lines 36-37).

      • More generally, attempts to decide whether some human observers exhibit tetrachromacy have taught us how hard this is to do. Two issues, beyond the above, are the following. 1) If the properties of a trichromatic visual system vary across the retina, then by imaging stimuli on different parts of the visual field an observer can in principle make tetrachromatic discriminations even though visual system is locally trichromatic at each retinal location. 2) When trying to show that there is no direction in a tetrachromatic receptor space to which the observer is blind, a lot of color directions need to be sampled. Here, 9 directions are studied. Is that enough? How would we know? The following paper may be of interest in this regard: Horiguchi, Hiroshi, Jonathan Winawer, Robert F. Dougherty, and Brian A. Wandell. "Human trichromacy revisited." Proceedings of the National Academy of Sciences 110, no. 3 (2013): E260-E269. Although I'm not suggesting that the authors conduct additional experiments to try to address these points, I do think they need to be discussed. We agree with the reviewer, that colour discriminability achieved by tetrachromatic vision could in theory be achieved by the combined effect of localised, distinct forms of trichromacy. Evidence in other fishes suggests that such multiple forms of trichromacy across the retina likely exist in many species. However, the behavioural effects of this retinal setup remain to be studied likely due to its extremely difficult nature. We have added a new section titled “future directions” (Lines 474-489), in which we discuss the possibility that distinct forms of trichromacy in the anemonefish retina could in theory achieve colour discrimination on par with tetrachromatic vision. We also give suggestions on how this could be investigated.

      Although we tried to include as many colour directions as practically possible in our experiment, we have certainly not provided an exhaustive range that completely encompasses anemonefish colour space. Whether 9 colour directions are adequate to assess the dimensionality of their color vision is difficult to say. As addressed in the previous comment, we now acknowledge this limitation by refining our conclusion, saying that our results do not prove tetrachromacy.

      • Line 277 ff. After reading through the paper several times, I remain unsure about what the authors regard as their compelling evidence that the UV cone has a higher sensitivity or makes an omnibus higher contribution to sensitivity than other cones (as stated in various forms in the title, Lines 37-41, 56-57, 125, 313, 352 and perhaps elsewhere).

      At first, I thought they key point was that the receptor noise inferred via the RNL model as slightly lower (0.11) for the UV cone than for the double cones (0.14). And this is the argument made explicitly at line 326 of the discussion. But if this is the argument, what needs to be shown is that the data reject a tetrachromatic version of the RNL model where the noise value of all the cones is locked to be the same (or something similar), with the analysis taking into account the fewer parametric degrees of freedom where the noise parameters are so constrained. That is, a careful model comparison analysis would be needed. Such an analysis is not presented that I see, and I need more convincing that the difference between 0.11 and 0.14 is a real effect driven by the data. Also, I am not sanguine that the parameters of a model that in some systematic ways fails to fit the data should be taken as characterizing properties of the receptors themselves (as sometimes seems to be stated as the conclusion we should draw).

      We have performed various modelling scenarios where receptor noise was adjusted for each channel; however, the UV channel was consistently found to be more sensitive than the other channels. In (the original) Supplementary Figure 6 (now Figure 4 – figure supplements 1 and 2), we show predicted dS values calculated using receptor noise levels in the exact manner that the Reviewer suggests by ranging from 0.05 to 0.15, and most importantly, included scenarios where receptor noise was held equal across cone types and others where it was varied between single cones and double cones. None of the models adjusted the data so that sensitivity was equal across all four channels, which means that by an unknown mechanism, the UV channel is more sensitive, but this is unrelated to noise levels. Our best-fit receptor noise values of 0.11 (for single cones) and 0.14 (for double cones) are estimate values and should be treated as such till actual receptor noise measurements are made.

      Then, I thought maybe the argument is not that the noise levels differ, but rather that the failures of the model are in the direction of thresholds being under predicted for discriminations that involve UV cone signals. That's what seems to be being argued here at lines 277 ff, and then again at lines 328 ff of the discussion. But then the argument as I read it more detail in both places switches from being about the UV cones per se to being about postive versus negative UV contrast. That's fine, but it's distinct from an argument that favors omnibus enhanced UV sensitivity, since both the UV increments and decrements are conveyed by the UV cone; it's an argument for differential sensitivity for increments versus decrements in UV mediated discriminations. The authors get to this on lines 334 of the discussion, but if the point is an increment/decrement asymmetry the title and many of the terser earlier assertions should be reworked to be consistent with what is shown.

      To clarify our argument, we found that the colour discrimination thresholds were systematically lower than predicted by the RNL model for colours which elicited higher UV cone stimulation relative to other cone types. These colours we refer to as UV positive based on the sign direction of their contrast against grey distractors produced by higher UV/V LED channel (i.e., in a positive direction). Whereas colours with UV negative chromatic contrast had lower UV cone stimulation relative to the other cone types. Therefore, our interpretation of the importance of UV cone signals for colour discrimination are congruent with the results. In the discussion, we suggest a possibility that activation of the UV receptor suppresses noise downstream in the visual pathway or enhances the saliency of colours (see lines 397-398). This activation of the UV receptor would, of course, be at its highest for colours with positive UV chromatic contrast.

      Note that we have added to the discussion the possibility that colour preferences or a difference in attentiveness might have contributed to differences in discrimination thresholds (see discussion lines 412-413, 427-428, 433-435, 456-466, and 469-473). However, we consider it a less likely explanation due to a couple of reasons, including 1) a lack of difference in responsiveness across colour sets in their timing to peck the target, and 2) any non-learnt bias would have likely been overridden or at least weakened by training prior to the experiment where colours were rewarded equally (see lines 462-466).

      We have edited the results (lines 334-352) to make our point clearer and by changing the subtitle to be more explicit: “Lower discrimination thresholds induced by positive UV contrast”. The subsection begins by explaining the different types of UV chromatic contrast by elevation angle and, finally, how this division among colour sets was a major determinant of colour discrimination thresholds.

      Perhaps the argument with respect to model deviations and UV contrast independent of sign could be elaborated to show more systematically that the way the covariation with the contrasts of the other cone stimulations in the stimulus set goes, the data do favor deviations from the RNL in the direction of enhanced sensitivity to UV cone signals, but if this is the intent I think the authors need to think more about how to present the data in a manner that makes it more compelling than currently, and walk the reader carefully through the argument.

      We have added to the results the linear mixed-effects model output with ‘contrast’ (positive/negative) added as a fixed effect. This analysis shows that the sign direction of UV contrast was a strong predictor of threshold (see address to previous comments and lines 399-401, 790-799).

      • On this point, if the authors decide to stick with the enhanced UV sensitivity argument in the revision, a bit more care about what is meant by "the UV cone has a comparatively high sensitivity (line 313 and throughout)" needs more unpacking. If it is that these cones have lower inferred noise (in the context of a model that doesn't account for at least some aspects of the data), is this because of properties of the UV cones, or the way that post-receptoral processing handles the signals from these cones mimicking a cone effect in the model. And if it is thought that it is because of properties of the cones, some discussion of what those properties might be would be helpful. As I understand the RNL model, relative numbers of cones of each type are taken into account, so it isn't that. But could it be something as simple as higher photopigment density or larger entrance aperture (thus more quantum catches and higher SNR)?

      It is unknown what aspect of the cone morphology or physiology sets the activation or inactivation threshold. Electrophysiological data collected from the UV cones of other fish species e.g., in goldfish and zebrafish [see Hawryshyn & Beauchamp (1985). 25, Vis Res.; and Yoshimatsu et al. (2020). 107, Neuron.] show that they have exceptionally high sensitivity. What has not been shown is that having a UV cone can improve colour discrimination.

      Previous quantitative cone opsin gene expression analysis showed that the single cone opsins (SWS1 and SWS2B) are expressed at lower levels than all double cone opsin genes. This difference in expression combined with the smaller size of single cone outer segments than the double cones make it unlikely that a larger photoreceptor size, higher volume or packing density of visual pigment is responsible. Contrary to our findings, these aspects of the different cone types (if they had an effect) would instead predict that double cones have a higher SNR, and non-UV colours would be more discriminable. We have now added these details to the discussion (see lines 391-397).

      • Line 288 ff. The fact that the slopes of the psychometric functions differed across color directions is, I think, a failure of the RNL model to describe this aspect of the data, and tells us that a simple summary of what happens for thresholds at delta S = 1 does not generalize across color directions for other performance levels. Since one of the directions where the slope is shallower is the UV direction, this fact would seem to place serious limits on the claim that discrimination in the UV direction is enhanced relative to other directions, but it goes by here without comment along those lines. Some comment here, both about implications for fit of RNL model and about implications for generalizations about efficacy of UV receptor mediated discrimination and UV increment/decrement asymmetries, seems important.

      The variation in the psychometric functions is difficult to interpret and cannot be explained by the RNL model. What the RNL model predicts is delta S based on low level factors (namely receptor noise). In the discussion, we completely agree with the notion that the asymmetry in thresholds from predicted values, and the variation in psychometric slopes cannot be explained by the RNL model, e.g., this is heavily implied by “colour discrimination thresholds cannot be directly attributed to noise in the early stages of the visual pathway…” (lines 388-390). To clarify the inability of the RNL model to account for this aspect of the data, we have included a statement (see line 390).

      It is a good point that this could be an indication of heterogeneity in colour space. Heterogeneity in discrimination thresholds across animal colour space (both surrounding the threshold area and for more saturated regions) has been explored in detail using trichromatic triggerfish by Green N. F. et al. (2022). JEB, 7(225):jeb243533. We have added this idea to the discussion (see lines 490-498). For UV, it seems that two of the five fish (#34 and 20) had noticeably shallower curves than the others tested for UV (fish #19, 33, 36). Both also varied more in their ability to distinguish targets, as shown by their wider confidence intervals. One of these two fish (#34) was retested for UV at the end of the experiment, and in the secondary assessment had a steeper psychometric curve more in line with the other fish in the experiment (see Figure 3 – figure supplement 1 and added lines 247-250). Based on this discrepancy in performance between assessments, it is also possible that individual learning effects had a role in impacting the shape of the psychometric curve. Note, this had minimal effect on colour discrimination thresholds and any differences were in the direction of change observed across colour sets in the experiment (i.e., lower dS for UV positive directions).

      • Line 357 ff. Up until this point, all of the discussion of differences in threshold across stimulus sets has been in terms of sensitivity. Here the authors (correctly) raise the possibility that a difference in "preference" across stimulus sets could drive the difference in thresholds as measured. Although the discussion is interesting and germaine, it does to some extent further undercut the security of conclusions about differential sensitivity across color directions relative to the RNL model predictions, and that should be brought out for the reader here. The authors might also discuss about how a future experiment might differentiate between a preference explanation and a sensitivity explanation of threshold differences.

      We have now added a paragraph (see lines 469-473) discussing that future work should test for color preferences and suggest how this could be done using a similar foraging task. We also include our thoughts immediately prior on why it is unlikely that a colour preference was a major contribution towards the results. In short, we consider it unlikely as fish showed no evidence of reduced latency for pecking at targets across the colour sets and because the training regime prior to the experiment equally rewarded fish for all colours and would likely have overridden a strong preference (at least in this specific foraging context).

      • RNL model. The paper cites a lot of earlier work that used the RNL model, but I think many readers will not be familiar with it. A bit more descriptive prose would be helpful, and particularly noting that in the full dimensional receptor space, if the limiting noise at the photoreceptors is Gaussian, then the isothreshold contour will be a hyper-ellipsoid with its axes aligned with the receptor directions.

      There is now added explanation of the RNL model (see lines 141-151), particularly on its assumptions that it only receives chromatic input and that discrimination is limited by noise arising in the photoreceptors and not by any specific opponent mechanisms. We also added the mention of the expected hyper-ellipsoid shape of isothreshold contours if receptor noise is Gaussian. Note, while we appreciate the importance of the reader to understand the basic functionality of the model, we wanted to avoid overloading the introduction with details on the RNL model which is not the focus of the paper. The RNL model is well-established in the field of visual ecology and animal vision research for well over a decade and has been thoroughly dissected by previous methodological reviews. We refer to one of these more recent reviews by Olsson et al. (2018) Behav Ecol. 29(2):273-282, and direct the reader to the methods section for further details on the RNL model.

      • Use of cone isolating stimuli? For showing that all four cone classes contribute to what the authors call color discrimination, a more direct approach would seem to be to use stimuli that target stimulation of only one class of cone at a time. This might require a modified design in which the distractors and target were shown against a uniform background and approximately matched in their estimated effect on a putative achromatic mechanism. Did the authors consider this approach, and more generally could they discuss what they see as its advantages and disadvantages for future work.

      The Reviewer is correct in that a targeted approach of isolated cone stimulation would be the optimal approach to demonstrating tetrachromatic colour vision. However, the extreme spectral overlap in the absorption curves of anemonefish cones, particularly in the mid-wavelength region makes this problematic in using the current LED display. We added to the discussion ways that this could be studied in the future (see lines 474-489). This might be possible (but still challenging) using a monochromator, but such technology severely limits the diversity of stimuli which can be created and usually restricts experiments to a simple paired choice design (or grey card experiment). The traditional paired choice experiment requires animals to be trained to distinguish a specific colour, while the Ishihara-like task trains animals to distinguish targets using an odd-one-out approach. This latter approach is highly efficient, as it does not require retraining when testing a new colour (i.e., fish learnt the task not a specific colour). Here, we wanted to assess colour discrimination in multiple directions to compare performance, and the flexible LED display combined with a generalisable task was important.

      The above assumes that anemonefish do not use multiple trichromatic systems. In which case, the use of standard experimental stimuli (e.g., a monochromator, an LED display) would be unsuitable as they illuminate the whole retina. To definitively test the range of opponent interactions, it would be necessary to make electrophysiological measurements targeting the transmitting neurons using a retinal multielectrode array (MEA) approach or by in-vivo calcium imaging (lines 484-486).

      We understand that our results are not a direct test of the dimensionality of anemonefish colour vision and should not be interpreted as such, as we do not have direct evidence of tetrachromacy. To recognize this limitation of our data, we have drawn back some of our conclusive statements that claimed to have demonstrated tetrachromacy.

    1. | can learn to

      This is so important! I make sure that I never say a student's name before I hear them say it. It was a huge shift for me after my first few years of stumbling through roll call on the first few days. It's just not necssary AND skips a great moment of connection. Beyond that though it is JUST as crucial to learn to pronounce our fellow staff members' (and teacher candidates') names correctly. It also has become important to me to make sure that I (lovingly) correct other people when I hear them mispronounce someone ELSE's name. It gets exhausting to constantly tell someone they're saying your name wrong (and it can be scary when you're a student and they're a teacher).

    1. Reviewer #2 (Public Review):

      In this paper the authors present an existing information theoretic framework to assess the ability of single cells to encode external signals sensed through membrane receptors.

      The main point is to distinguish actual noise in the signaling pathway from cell-cell variability, which could be due to differences in their phenotypic state, and to formalize this difference using information theory.

      After correcting for this cellular variability, the authors find that cells may encode more information than one would estimate from ignoring it, which is expected. The authors show this using simple models of different complexities, and also by analyzing an imaging dataset of the IGF/FoxO pathway.

      The implications of the work are limited because the analysed data is not rich enough to draw clear conclusions. Specifically,<br /> - the authors do not distinguish what could be methodological noise inherent to microscopy techniques (segmentation etc), and actual intrinsic cell state. It's not clear that cell-cell variability in the analyzed dataset is not just a constant offset or normalization factor. Other authors (e.g. Gregor et al Cell 130, 153-164) have re-centered and re-normalized their data before further analysis, which is more or less equivalent to the idea of the conditional information in the sense that it aims to correct for this experimental noise.<br /> - in the experiment, each condition is shown only once and sequentially. This means that the reproducibility of the response upon repeated exposures in a single cell was not tested, casting doubt on the estimate of the response fidelity (estimated as the variance over time in a single response).<br /> - another dataset on the EGF/EGFR pathway is analyzed, but no conclusion can be drawn from it because single-cell information cannot be directly estimated from it. The authors instead use a maximum-entropy Ansatz, which cannot be validated for lack of data.

    1. Are protected members/fields really that bad? No. They are way, way worse. As soon as a member is more accessible than private, you are making guarantees to other classes about how that member will behave. Since a field is totally uncontrolled, putting it "out in the wild" opens your class and classes that inherit from or interact with your class to higher bug risk. There is no way to know when a field changes, no way to control who or what changes it. If now, or at some point in the future, any of your code ever depends on a field some certain value, you now have to add validity checks and fallback logic in case it's not the expected value - every place you use it. That's a huge amount of wasted effort when you could've just made it a damn property instead ;) The best way to share information with deriving classes is the read-only property: protected object MyProperty { get; } If you absolutely have to make it read/write, don't. If you really, really have to make it read-write, rethink your design. If you still need it to be read-write, apologize to your colleagues and don't do it again :) A lot of developers believe - and will tell you - that this is overly strict. And it's true that you can get by just fine without being this strict. But taking this approach will help you go from just getting by to remarkably robust software. You'll spend far less time fixing bugs.

      In other words, make the member variable itself private, but can be abstracted (and access provided) via public methods/properties

    1. Background Reproducibility of data analysis workflow is a key issue in the field of bioinformatics. Recent computing technologies, such as virtualization, have made it possible to reproduce workflow execution with ease. However, the reproducibility of results is not well discussed; that is, there is no standard way to verify whether the biological interpretation of reproduced results are the same. Therefore, it still remains a challenge to automatically evaluate the reproducibility of results.Results We propose a new metric, a reproducibility scale of workflow execution results, to evaluate the reproducibility of results. This metric is based on the idea of evaluating the reproducibility of results using biological feature values (e.g., number of reads, mapping rate, and variant frequency) representing their biological interpretation. We also implemented a prototype system that automatically evaluates the reproducibility of results using the proposed metric. To demonstrate our approach, we conducted an experiment using workflows used by researchers in real research projects and the use cases that are frequently encountered in the field of bioinformatics.Conclusions Our approach enables automatic evaluation of the reproducibility of results using a fine-grained scale. By introducing our approach, it is possible to evolve from a binary view of whether the results are superficially identical or not to a more graduated view. We believe that our approach will contribute to more informed discussion on reproducibility in bioinformatics.

      This work has been peer reviewed in GigaScience (see https://doi.org/10.1093/gigascience/giad031 ) , which carries out open, named peer-review. These reviews are published under a CC-BY 4.0 license and were as follows:

      **Reviewer Stian Soiland-Reyes ** Hi, I am Stian Soiland-Reyes https://orcid.org/0000-0001-9842-9718 and have pledged the Open Peer Review Oath https://doi.org/10.12688/f1000research.5686.2: *

      Principle 1: I will sign my name to my review Principle 2: I will review with integrity Principle 3: I will treat the review as a discourse with you; in particular, I will provide constructive criticism Principle 4: I will be an ambassador for the practice of open science. This review is licensed under a Creative Commons Attribution 4.0 International License

      . --- This article presents a method for comparing reproducibility of computational workflow runs captured as RO-Crates, by calculating a set of genomics metrics ("features") and adding these to the crate's metadata. Overall I find this a valuable contribution and worthy of publication with GigaScience, primarily as a way for users of workflow systems CWL, Nextflow, Cromwell or Snakemake to ensure reproducibility, but also for workflow engine developers who may want to build on this methodology to improve their provenance support. In general the method proposed is sound, however it does have some limitations and inherent assumptions that are not highlighted sufficiently in the current manuscript, particularly concerning the selection of features and the reproducibility of the metrics calculation itself. I have detailed this with some points below that I would like the authors to clarify in a minor revision.

      --- Note - the below questions from GigaScience Reviewer Guidelines mainly relate to data, but I also here interpret them for the software described.

      Q1: Is the rationale for collecting and analyzing the data well defined? The author's workflow executions https://doi.org/10.5281/zenodo.7098337 are based on three 3rdparty bioinformatics workflows. Although they are not particularly "large-scale", they are representative best-practice pipelines in this field (data sizes from 200 MB to 6 GB) and also fairly representative for scalable workflow systems (Nextflow, CWL and WDL) used by bioinformaticians.

      Q2: Is it clear how data was collected and curated? It is not explicit in the text why these particular workflows were selected, beyond being realistic pipelines used in research. I would suggest something like "these workflows have been selected as fairly representative and mature current best-practice for sequencing pipelines, implemented in different but typical workflow systems, and have similar set of genomics features that we can assess for provenance comparison." The workflows have each been cited, but I would appreciate some consistency so that each workflow is cited both by its closest journal article and as their original download sources (e.g. GitHub).

      Q3: Is it clear - and was a statement provided - on how data and analyses tools used in the study can be accessed? Yes, full availability statements have been provided both for data and software, archived on Zenodo for longevity.

      Q4: Are accession numbers given or links provided for data that, as a standard, should be submitted to a community approved public repository? Yes, the tools have been added to https://bio.tools/ -- I don't think it's necessary to further register the data outputs with accession numbers. RRIDs for tools can be considered at a later stage, perhaps only for Sapporo.

      Q5: Is the data and software available in the public domain under a Creative Commons license? Yes, the software and dataset is open source under Apache License, version 2.0. The dataset https://doi.org/10.5281/zenodo.7098337 embeds existing workflows and data, however this is OK as included resources such as the rnaseq Nextflow workflow have compatible licenses (MIT) or are also Apache-licensed. The manuscript has software citations for two of the workflows, but this is missing for the CWL workflow, which is only cited by manuscript (33) (also missing DOI). It is unclear if any of the workflows are registered in https://workflowhub.eu/ but that should primarily be done by their upstream authors. The RO-Crates in https://doi.org/10.5281/zenodo.7098337 don't include any licensing and attribution for the embedded workflows, and its metadata file is misleadingly declaring the crate license as CC0 public domain. While CC0 is appropriate for examples and metadata file itself, the embedded MIT/Apache workflows from third parties can't legally be relicensed in this way and should have their original licenses declared. See https://www.researchobject.org/ro-crate/1.1/contextualentities.html#licensing-access-control-and-copyright I understand these RO-Crates are generated automatically by Sapporo, which does not directly understand licensing, and for documenting the test runs with Sapporo, I think these should not be modified post-execution. Pending further license support by Sapporo, perhaps a manual outer RO-Crate that aggregate these (e.g. adding a direct top-level ro-crate-metadata.json to the Zenodo entry) can provide more correct metadata as well as workflow citations. The authors could add to Discussion some consideration on (lack of) propagation of such metadata for auto-generated crates as part of workflow run provenance. For instance, if a workflow run was initiated from a Workflow Crate https://w3id.org/workflowhub/workflow-ro-crate/ at WorkflowHub, its license, attributions and descriptions could be carried forward to the final Workflow Run Crate provenance together with the Sapporo-calculated features.

      Q6: Are the data sound and well controlled? Yes, the data is sound. The testing on Mac gives null-results, but the authors explain the workflows failed to execute there due to archicectural differences, which is flagged as a valid concern for reproducibility. It may be worth further investigating if this is due to misconfiguration on that particular test machine in which case these columns should be removed.

      Q7: Is the interpretation (Analysis and Discussion) well balanced and supported by the data? The authors' discussion have some implicit assumptions that should be made more clear, together with implications: The Tonkaz tool assumes the workflow execution has already extracted the features and added them to the RO-Crate This assumes the right features have been correctly extracted by each execution Feature extraction also depend on bioinformatics tools that are subject to change/updates Newer versions of Sapporo-service, and in particular any non-Sapporo executors also making Workflow run Crates, may have a different feature selection Being able to fairly compare two workflow runs therefore depends on careful control of the Sapporo executor versions so that they have consistent feature selection This means the reproducibility metrics proposed has a potential reproducibility challenge itself This is not to say that the approach is bad, as the feature extraction is using predictable measures such as counting sequences, rather than heuristics. This means Future Work should point out the need for guidelines on what kind of features should be selected, to ensure they are consistent and reproducible. The set of features also depend on the type of data and class of analysis. As a minimum, the RO-Crate should therefore include provenance of that feature extraction, noting the Sapporo version, and ideally the version of the tools used for that. The authors may want to consider if feature extraction should be a separate workflow (e.g. in CWL), that itself can be subject to the same reproducibility preservation measures, and therefore also can be performed post-execution as part of Tonkaz' comparison or as a curation activity when storing Workflow Run Crates.

      Q8: Are the methods appropriate, well described, and include sufficient details and supporting information to allow others to evaluate and replicate the work? Yes, it was very easy to replicate the Tonkaz analysis of the workflow run crate that is already provided, as it is provided also as a Docker container. The Docker container is provided as part of GitHub releases, and so is not at risk of Docker Hub's automatic deletion. I have not tried installing my own Sapporo service to re-execute the workflow, but detailed installation and run details are provided in the README of both Tonkaz https://github.com/sapporowes/tonkaz#readme and sapporo-service https://github.com/sapporowes/sapporo/blob/main/docs/GettingStarted.md

      Q9: What are the strengths and weaknesses of the methods? The method provided is strong compared to naive checksum-based comparison of workflow outputs, which has been pointed out as a challenge by previous work. The advantage of the feature extraction is that the statistics can be compared directly and any disreprancies can be displayed to the user at a digestible high-level. The disadvantage is that this depends wholy on the selection of features, which must be done carefully to cover the purpose of the particular workflow and its type of data. For instance, a workflow that generates diagrams of sequence alignments could not be sufficiently tested in the suggested approach, as analyzing the diagram for correctness would require tools that may not even exist. Perhaps feature extraction should be a part of the workflow itself, so it can self-determine what is important for its analysis? The current approach also is quite sensitive to output data filenames, so changes in filename would mean features are not compared, even where such files are equivalent. This should be made more explicit in the manuscript, for instance workflows should ensure they don't include timestamps or random identifiers in their filenames. Further work could have a deeper understanding of the workflow structure to compare outputs based on their corresponding FormalParameter in the RO-Crate.

      Q10: Have the authors followed best-practices in reporting standards? Yes, the details provided are at a sufficient detail level, and the authors have re-used the RO-Crate data packaging. The RO-Crates created by Sapporo-service adds several terms for the metrics, which are declared on the @context according to RO-Crate specs https://www.researchobject.org/rocrate/1.1/appendix/jsonld.html#extending-ro-crate However the terms point to GitHub "raw" pages, which are not particularly stable, and may change depending on sapporo versions and GitHub's repository behaviour. I recommend changing the ad-hoc terms to PIDs such as a namespace under https://w3id.org/ or https://purl.org/ so that these terms can be stable semantic artefacts, e.g. submitting them to https://github.com/ResearchObject/ro-terms to register https://w3id.org/ro/terms/sapporo#WorkflowAttachment that can be used instead of https://raw.githubusercontent.com/sapporo-wes/sapporo-service/main/sapporo/roterms.csv#WorkflowAttachment or alternatively https://w3id.org/sapporo#WorkflowAttachment could be set up to redirect to the ro-terms.csv on GitHub. (discussed with the authors at ELIXIR Biohackathon) In doing so you should separate into two namespaces, the general Sapporo terms like "sha512", and the particular genomics feature sets including "totalReads" (e.g. https://w3id.org/datafeatures/genomics#WorkflowAttachment) as the second are a) Not sapporo-specific b) domainspecific. RO-Crate is developing Workflow Run profiles https://www.researchobject.org/workflow-runcrate/profiles/, although these have not been released at time of my review they are now stable, so the authors may want to check https://www.researchobject.org/workflow-runcrate/profiles/workflow_run_crate to ensure "FormalParameter" are declared correctly in the generated RO-Crate as separate entities, linked from the "File" using "exampleOfWork".

      Q11: Can the writing, organization, tables and figures be improved? The language and readability of this article is generally very good. Light copy-editing may improve some of the sentences, e.g. reducing the use of "Thus" phrases.

      Q12: When revisions are requested. See suggestions from above for minor revisions: Make explicit why these 3 workflows where selected (see Q2) Make pipeline software citations consistent in manuscript (see Q2, Q5) Avoid declaring CC0 within generated RO-Crate -- move this to only apply to the ro-cratemetadata.json Add an outer RO-Crate metadata file to Zenodo deposit to carry the correct licenses and pipeline licenses for each of rnaseq_1st.zip, trimming.zip etc. Improve discussion to better reflect limitations of the features and its own reproducibility issues (see Q7, Q9) Consider improvements to the RO-Crate context (see Q10) - this may just be noted as Future Work in the manuscript rather than regenerating the crates In addition: p2: Add citation for claim on file checksums different depending on software versions etc., for instance https://doi.org/10.1145/3186266 p3. "We converted Sapporo's provenance into RO-Crate" -- re-cite (20) as this is the paragraph explaining what it is. p10. Citations 7, 8 are missing authors p10. Citation 15 is now published, replace with https://doi.org/10.1145/3486897 p0. Citations 28, 33 is missing DOI

      Q13: Are there any ethical or competing interests issues you would like to raise? No, the third-party pipelines selected for reproducibility testing are already published and are here represented fairly, and only used as executable methods (as intended by their original authors), which I would say do not need ethical approval.

    1. How does it relate to cultural patterns ofexhibiting and controlling anxiety, anger, joy, the erotic, the religious, creativity?

      I've always believed it's intended to have control on exactly that. Don't do this, don't do that. Restrictions bring about a need to break them sometimes just to satisfy curiosity. If you keep people in check whatever you've convinced them of they'll likely keep believing.

    Annotators

    1. You always find these people where you’re like, “Oh, I thought this was a Steve Jobs idea.” No, no. It’s an [Sony founder] Akio Morita idea, or an Edwin Land idea. Watch the presentations that Steve Jobs gives where he says, “We’re building at the intersection of technology and liberal arts.” Edwin Land said those exact words! You’re never going to find anybody who gets to the top of the profession without studying the people that came before them and learning from them and admiring them.

      "Everything is a remix" - almost every thought you've had has been thought of by someone else in one form or another. As such, there are very few truly original ideas. Most ideas deemed "original" are just recycled and combined versions of ideas that came before.

      This is basically what the show "Connections" with James Burke was all about.

    1. I dare say not, for you are reserved in your behaviour, and seldom impart your wisdom. But I have a benevolent habit of pouring out myself to everybody, and would even pay for a listener, and I am afraid that the Athenians may think me too talkative. Now if, as I was saying, they would only laugh at me, as you say that they laugh at you, the time might pass gaily enough in the court; but perhaps they may be in earnest, and then what the end will be you soothsayers only can predict.

      Socrates tells Euthyphro that he is reserved in that way he act not bring attention to himself in such a way the he do by talking to anyone who will listen. Socrates state that the people my even think that he talk to much laughing at him and to say it's just nonsense. Socrates state that as they laugh the time that pass as they wait will be cheerful and that they will get a favorable verdict by the court but they can't predict the future .

    1. A sells the option for 0.55, gets all the business and makes a guaranteed 0.05 profit.Along comes B who sells the option for just 0.53, now he takes away all the businessfrom A, who responds by dropping his price to 0.52, etc. So really, supply and demandshould act to make the option price converge to the 0.5

      If there's low liquidity in the market, it could potentially lead to arbitrage opportunities. Low liquidity means that there are fewer buyers and sellers in the market, which can lead to larger price discrepancies and potentially a divergence from the theoretical price.

      In the scenario you're referencing, where the theoretical price of the option is 0.5, competition between sellers in a liquid market would typically drive the price towards this level. However, if there's low liquidity, sellers might be able to sell the option for a higher price, say 0.55, without immediately being undercut by competitors. Meanwhile, an arbitrageur who knows the theoretical price could theoretically create a risk-free profit by taking the opposite position in a different market or using a different financial instrument.

      However, it's important to note that arbitrage opportunities are often difficult to exploit in practice, especially for individual investors. Transaction costs, bid-ask spreads, and other market frictions can eat into arbitrage profits. Plus, arbitrage opportunities tend to be fleeting, as other market participants are also on the lookout for them and will quickly act to close the price discrepancy.

      Moreover, low liquidity itself can be a risk: if you need to unwind your position and there aren't enough buyers or sellers, you might have to do so at a less favorable price. So while low liquidity can theoretically lead to arbitrage opportunities, exploiting these opportunities can be risky and challenging.

    1. It isn’t that more people are depressed today, it’s that we’re more aware of the people who are depressed, and the instance of depression in itself.

      Ive never considered this before. Maybe a lot of people have been depressed but because they didnt have the internet, we didnt realize how big of an issue it was. Or maybe since it wasnt so widely talked about people just didnt know what depression was.

    1. my editor who's from completely outside this world just Mark that and said you know I don't know what these words mean the Evangelical subculture 00:36:03 right I was like okay take it out and let me let me show don't tell and but the truth is like it's invisible to people on the outside what the Evangelical subculture is

      my editor who's from completely outside this world just Mark that and said you know I don't know what these words mean the Evangelical subculture right I was like okay take it out and let me let me show don't tell and but the truth is like it's invisible to people on the outside what the Evangelical subculture is

    1. my editor who's from completely outside this world just Mark that and said you know I don't know what these words mean the Evangelical subculture 00:36:03 right I was like okay take it out and let me let me show don't tell and but the truth is like it's invisible to people on the outside what the Evangelical subculture is
      • definition
        • Evangelical Subculture
      • This is a culture that Evangelical Christians are immersed in
        • which constitutes a kind of bubble of repetitive indoctrination of
          • aggressive, male, patriarchal value system that is antithetical to
          • the traditional teachings of Christianity that once focused on values of
            • collaboration
            • compassion
            • empathy
            • tolerance
      • It is widespread deeply aculturated meme that affects hundreds of millions of people worldwide
      • one of its distinguishing features is the carefully controlled and orchestrated propaganda
  5. inst-fs-iad-prod.inscloudgate.net inst-fs-iad-prod.inscloudgate.net
  6. learn-us-east-1-prod-fleet01-xythos.content.blackboardcdn.com learn-us-east-1-prod-fleet01-xythos.content.blackboardcdn.com
    1. The question of new business models for content creators on the Internet is a profoundand difficult topic in itself, but it must at least be pointed out that writing professionallyand well takes time and that most authors need to be paid to take that time. In this regard,blogging is not writing. For example, it's easy to be loved as a blogger. All you have todo is play to the crowd. Or you can flame the crowd to get attention. Nothing is wrongwith either of those activities. What I think of as real writing, however, writing meant tolast, is something else. It involves articulating a perspective that is not just reactive toyesterday's moves in a conversation.

      https://www.nature.com/articles/d41586-023-00107-z

      AI poses a threat to writers, and the linked Nature article mentions the same idea. Authors need time and money to create their work, and yet AI can create quality work in less time without money in things as complicated as research papers.

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      1. General Statements [optional]

      We would like to thank all reviewers for their constructive feedback and for raising specific points that have helped to improve our manuscript. We accept that the initial submission did not include some quantitative aspects of the observed effects. These are now included together with all the suggested experiments from the reviewers with the use of additional mutants and appropriate protein markers. We believe that the manuscript offers a conceptual advance and a molecular mechanism for the effects of caffeine on cell cycle progression of eukaryotic cells and is of interest to geneticists working on cell cycle, cancer and biogerontology.

      Reply to the reviewers

      Reviewer #1 (Evidence, reproducibility and clarity):

      Summary:

      In the manuscript “The AMPK-TORC1 signaling axis regulates caffeine-mediated DNA damage checkpoint override and cell cycle effects in fission yeast,” the authors studied the role of genes that are potentially involved in the caffeine-mediated override of a cell cycle arrest caused by activation of the DNA damage checkpoint. The methylxanthine substance caffeine has been known to override the DNA damage checkpoint arrest and enhance sensitivity to DNA damaging agents. While caffeine was reported to target the ATM ortholog Rad3, the authors previously reported that caffeine targets TORC1 (Rallis et al, Aging Cell, 2013). Inhibition of TORC1, like caffeine, was also reported to override DNA damage checkpoint signaling. Therefore, in the present study, the authors compared the effects of caffeine and torin1 (a potent inhibitor for TORC1 and TORC2) on cell cycle arrest caused by phleomycin, a DNA damaging agent, using various gene deletion S. pombe mutants.

      The authors concluded that they identified a novel role of Ssp1 (calcium/calmodulin-dependent protein kinase) and Ssp2 (catalytic subunit of AMP-activated kinase) in the cell cycle effects caused by caffeine, based on the following findings; (1) the caffeine-mediated DNA damage checkpoint override requires Ssp1 and Ssp2; (2) Ssp1 and Ssp2 are required for caffeine-induced hypersensitivity against phleomycin; (3) under normal growth conditions, caffeine leads to a sustained increase of the septation index in a Ssp2-dependent manner; (4) Caffeine activates Ssp2 and partially inhibits TORC1.

      Major comments:

      I do not think that many of the authors’ claims are supported by the results of the present study. The corresponding parts are detailed below.

      1. The conclusion of the first paragraph in the Results (top in page 6; Our findings indicate that caffeine and torin1 indirectly and directly inhibit TORC1 activity respectively.) is not supported by the data in Figure 1. The result that caffeine, but not torin1, requires Ssp1 and Ssp2 to override the phleomycin-induced cell cycle arrest does not necessarily indicate that caffeine indirectly inhibits TORC1 via Ssp1 and Ssp2. Rather, the authors should mention that this conclusion is based on the authors’ previous reports by citing them (e.g., Rallis et al, Sci Rep, 2017). To add to Figure 1, an additional experiment using a constitutively active AMPK mutant, a temperature-sensitive TORC1 mutant, and a srk1 deletion mutant will help the authors claim their original conclusion as one possibility.

      Torin1 inhibits TORC1 and 2 leading to G2 cell cycle arrest following accelerated mitosis. In contrast, caffeine has been reported to enhance the inhibitory effect of rapamycin on TORC1 signaling but does not inhibit growth. It has not been reported that TORC1 is a direct target of rapamycin. We previously demonstrated that caffeine induces Srk1 in a Sty1 dependent manner (Alao et al., 2014). Furthermore, Ssp1 plays a role in regulating Srk1/ Cdc25 activity. It is therefore possible, that Ssp1 influences the ability of caffeine to promote mitotic progression as part of the stress response while also affecting TORC1 activity via Ssp2. As ssp2∆ cells have higher intrinsic TORC1 activity, this could also attenuate the effect of caffeine on mitosis.

      We have modified the first paragraph of the results section to address the reviewer’s concerns.

      We have previously reported that Srk1 modulates the ability of caffeine to drive cells into mitosis (Alao et al., 2014).

      1. The conclusion of the second paragraph in the Results (lower-middle in page 6; Our results indicate that caffeine induces the activation of Ssp2.) is not based on the results of Figure 2. Figure 2 simply illustrates that both caffeine and torin1 cause hypersensitivity to phleomycin dependent on Ssp1 and Ssp2.

      We appreciate the reviewer’s contention and have modified the text.

      1. The conclusion of the fourth paragraph in the Results (middle in page 7) is not clearly supported by the result, due to an insufficient data analysis. As the cell length and the progress through mitosis are the key assay parameters in Figure 3, the average cell length should be shown next to each micrograph of Figure 3A and 3B. In Figure 3C, a mitotic index and the average cell length should be shown next to each micrograph. A statistical analysis is necessary for the authors to compare the measurements and to claim as the headline (Caffeine exacerbates the ssp1D phenotype under environmental stress conditions), as the effect of caffeine was not evident._

      We have conducted additional experiments to measure cell length and modified the figure to include this data. We believe our observation that caffeine alone induces increased cell length in ssp1 mutants, confirms a role for the Ssp1 protein in modulating the effects of caffeine. We previously showed that Caffeine activates Srk1 which in turn inhibits Cdc25 activity similar to other environmental stresses (Alao et al., 2014). Ssp1 negatively regulates Srk1 following exposure to stress. In contrast, caffeine advances mitosis in wt cells and thus does not result in increased cell length. We also demonstrate that caffeine greatly enhances cell length in ssp1 mutants exposed to heat stress in marked contrast to rapamycin and torin1. These findings indicate that Ssp1 mediates the effect of caffeine on mitosis.

      1. In the middle of page 8, the statement “Accordingly, the effect of caffeine and torin1 on DNA damage sensitivity was attenuated in gsk3D mutants (Figure 5C and 5D).” is not supported by the corresponding results. Rather, Figure 5C and 5D look almost the same.

      We agree with this and other reviewers that demonstrating enhanced sensitivity to caffeine is problematic. Nonetheless, our cell cycle data clearly indicate a differential role for Gsk3 in mediating the cell cycle effects of caffeine and torin1. In terms of DNA damage sensitivity, we have reproducibly observed a lower degree of DNA damage sensitivity in gsk3 mutants relative to wt cells. Hence, while caffeine is less effective at enhancing DNA damage sensitivity relative to torin1 in wt cells; we observed that caffeine and torin1 increase DNA damage sensitivity to a similar degree in gsk3 mutants.

      1. The description and the conclusion of the last paragraph in the Results (bottom in page 8 – page 9) are not supported by the results of Figure 6, due to an insufficient data analysis. The extent of phosphorylation must be quantified as a ratio of the phosphorylated species (e.g., pSsp2) to all species of the protein (e.g., Ssp2).

      We have carefully repeated our experiments under various conditions. Our results clearly indicate caffeine induced Ssp2 phosphorylation. These observations have not been reported previously.

      From Figure 6, the authors claim that caffeine (10 mM) partially inhibits TORC1 signaling. However, the authors previously showed that the same concentration of caffeine inhibited phosphorylation of ribosome S6 kinase as strongly as rapamycin, the potent TOR inhibitor (Rallis et al, Aging Cell, 2013). The authors are advised to assess phosphorylation of S6 kinase again in the present study and compare to the results of the present results in Figure 6, because addition of that data may allow the authors to discuss that caffeine affects TORC1 downstream pathways at different intensities.

      While rapamycin is a strong inhibitor of TORC1 in budding yeast, this is not the case in fission yeast. Our previous assessments of p-S6 levels and polysomal profiles as well as cell-cycle progression kinetics have shown this (Rallis et al, Aging Cell, 2013). In addition, gene expression analysis from our previous studies have shown that caffeine treatment results in a gene expression profile similar to that of cells in nitrogen starvation (TORC1 inhibition).

      We have now used an Sck1-HA strain to further enhance our study and address the reviewer’s concerns. Previous studies have shown that 100 ng/mL rapamycin does not affect Sck1 phosphorylation. We demonstrate that in contrast to rapamycin (100 ng/ mL) 10 mM caffeine affects Sck1-HA expression and or phosphorylation. This effect was also observed with 5 µM torin1 albeit to a greater degree.

      Also, immunoblotting of the same proteins looks somehow different from panel to panel (e.g., pSsp2 in panel A and D; Actin in panel A, C, and D). Therefore, the blotting result before clipping had better be shown as a supplementary material.

      We repeated the blots were necessary and used ponceau S as a loading control. The original blots can be made available to all.

      Minor comments:

      1. (Figure 1) The septation index of the phleomycin-treated cells (without any further additional drugs) should be shown, as a baseline.

      We have included data for untreated cultures and phleomycin-only treated cultures.

      1. (Figure 1D, Optional) As a ppk18D cek1D double deletion mutant is reported, the authors are advised to add and test that mutant in this experiment.

      We have added the related data for the _ppk18_Δ _cek1_Δ double mutant.

      1. (Figure 2) The authors need to clarify the number of cell bodies spotted (e.g., in the Figure legend).

      We have modified the figure legend accordingly.

      1. (Figure 3) The different number of cells in micrographs may give an (wrong) impression on the cell proliferation rate. Therefore, it is advisable to use the micrographs in which the similar number of cells are shown for conditions with the similar cell proliferation rates.

      We have included data to show the cell lengths under different conditions. We find that different conditions greatly affect proliferation rates. For instance, cells do not proliferate in the presence of torin1. We initially sought to investigate if caffeine induces a phenotype in ssp1 mutants by virtue of its interaction with the DNA damage response. The micrographs were included as representative examples and have been now complemented with cell length data.

      1. (Figure 4B) ssp2D, not spp2D.

      The figure legend has been edited.

      1. (Figure 4) The septation index of the none-treated cells should be shown as a baseline.

      We have included base line data for untreated wt cells in figure 1. We have no reason to suspect any of the mutants would provide different results over the time investigated.

      1. (Figure 6B, 6E) What do the black arrows indicate? Figure Legend does not seem to explain them.

      The legend has been modified to indicate what the arrows refer to.

      1. (Figure 6C) Indicate which part of the Maf1-PK blot corresponds to the phosphorylated species, because Maf1-PK is probed with an anti-V5 (not a phosphorylation-specific) antibody.

      These experiments have been carefully repeated under different conditions and the figure is now modified accordingly.

      1. (Figure 6D) gsk3Dssp1D, not gs3Dssp1D.

      We have deleted this figure and have now replaced it with data we believe is more appropriate.

      Reviewer #1 (Significance):

      As caffeine is implicated in protective effects against diseases including cancer and improved responses to clinical therapies, the topic of the present study is of interest and importance to the broad audience.

      In the present study, the most significant finding is that caffeine- and torin1-induced hypersensitivity to phleomycin is dependent on Ssp1 and Ssp2 (Figure 2). This result may be important in chemotherapy against cancers. On the other hand, caffeine is known to activate AMPK (e.g., Jensen Am J Physiol Endocrinol, 2007). Besides, as detailed in the Major comments, many of the major conclusions are not supported by the present results. Therefore, based on my field of expertise (cell cycle, cell proliferation, and TOR signaling), I conclude that the present study hardly extends the knowledge in the field of "the cell biology of caffeine."_

      We thank the reviewer for their helpful comments. We accept the constructive criticisms and have carried out extensive additional experiments to provide further roles for Ssp2 and TORC1, in mediating the cell cycle effects of caffeine. We stress that caffeine has previously been proposed its effects via inhibition of Rad3 activity. Our previous work showed that caffeine did not inhibit Rad3 mediated checkpoint signaling. As later studies suggested caffeine inhibited TORC1 activity, the major goal was to investigate if caffeine is an indirect inhibitor of TORC1 via Ssp2 which is activated by several stresses. It has never been demonstrated that caffeine signals via Ssp2. This study provides the first evidence that caffeine modulates cell cycle progression by at least partially signaling via Ssp2 and TORC1. After nearly 30 years, it is vital that its precise activity, in particular enhancing DNA damage sensitivity is properly characterized. Such work woold open the way for additional studies on how caffeine activates cell physiology. For instance, we show that caffeine at 10 mM is more effective at inhibiting Sck1 activity than Rapamycin at 100 ng/ ml. In contrast, rapamycin at this concentration is more effective at inhibiting Maf1 activity. Hence further studies on how exactly the combination of caffeine and rapamycin influences their effect on ageing and other TORC1 regulated processes.

      Reviewer #2 (Evidence, reproducibility and clarity):

      Summary: In this paper, Alao and Rallis analyze the role of AMPK and TORC1 pathways, and the respective crosstalk, in regulating cell cycle progression in the presence of DNA damage in S. pombe. The authors show, almost exclusively through chemo-genetic epistasis assays, that caffeine inhibits TORC1 indirectly activating AMPK, in contrast to the specific ATP-competitive TORC1 inhibitor torin1. Specifically, it is shown that in the absence of a functional AMPK pathway caffeine is unable to revert the TORC1-inhibition-dependent override of cell-cycle arrest caused by the DNA-damaging agent phleomycin, henceforth partially suppressing the growth inhibition caused by the co-treatment.

      Major comments: The overall story of the paper is convincing. However, the choice of an almost exclusively chemo-genetic approach, lack of controls in some experiments and some discrepancy in data presentation suggest that the manuscript undergoes revision before the authors claim that their conclusions are fully supported by the results. In detail:

      In Figure 1, graphs of septation indexes are presented separately for each strain. This presentation prevents the reader from clearly comparing the differences of septation caused by genetic background rather than the treatment, i.e. the septation happening by treatment with torin1. I feel it would be better to group the results by drug rather than by strain/mutant. If the results are presented this way because the experiments on different strains were run separately, I further suggest that they are re-run so to always include at least the wt in every run._

      We have included data for untreated and phleomycin only treated wt cells as a reference. Additionally, all experiments were repeated at least 2 times. We have used this assay for over 10 years and have found it to be reproducible and reliable. We are not able to include wt cells in every run as this would be beyond the manpower capacity and time constraints involved. It is also likely that torin1 activity is influenced by the ssp1/ 2 backgrounds due to increased basal TORC1 activity as previously reported. The main goal was to illustrate that caffeine differs from a direct inhibitor such as torin1.

      Furthermore, torin1 inhibits both TORC1 and TORC2 and thus cannot be directly compared to caffeine. We do prove however, in this and other figures that in contrast to torin1 and rapamycin that caffeine signals via targets upstream of TORC1. We can therefore deduce that it functions in a manner similar to other environmental and nutrient stresses, which require with the Ssp1 and Sty1 regulated pathways to advance mitosis and other processes such as autophagy induction.

      In Figure 2C-D, an inconsistency is observable between the phleo+caffeine sensitivity of ssp1Δ and ssp2Δ, the latter retaining a higher sensitivity. Provided that this is not only due to this specific replicate, how would the authors explain such a difference and fit it into their conclusion of a "cascade" signaling with Ssp1 acting upstream of Ssp2?

      We agree that analyzing the different interacting pathways involved, is complex. For instance, Ssp1 is required for suppressing Srk1 following Sty1 activation independently of its effects on Ssp2 and TORC1. Furthermore, basal TORC1 activity is higher in Ssp2 mutants as previously reported. It is likely that Ssp1 exerts a more definitive role as it is required to directly reactivate Cdc25 activity following exposure to stress. In contrast Ssp2 activation eventually results in increased Cdc25 activity via inhibition of PP2A (Figure 8). These experiments are, thus, intended to compliment those in figure1 but the DNA damaging effects of caffeine must also be taken into account.

      In Figure 2I, a huge discrepancy is observable compared to panel 2A in terms of phleo+caffeine (no ATP) sensitivity of wt cells. Here, cells seem to cope well with the phleomycin treatment even if co-treated with caffeine. This renders the main finding of the panel (the effect of phelo+caffeine+ATP) rather uninterpretable.

      We have noted that relevant assays, at least in fission yeast, are influenced by the culture vessels (e.g., plastic type/ glass) as well as the vessel volume (probably due to different aeration, oxygen availability that affects growth and metabolism parameters). We have corrected figure 1a. In terms of ATP, these experiments are highly reproducible even if the exact mechanism remains unclear.

      In Figure 3A, the simple observation of elongation is sometimes hard to assess, for example in the ATP-caused suppression of the effect of torin 1, as also acknowledge by the authors in the text. I feel it would be really necessary to quantify such results on an adequate number of cells.

      We have reproducibly observed this uncharacterized effect of ATP. We have analysed the cell length in additional experiments to show that ATP influences average cell length under these conditions. It is important to note that the effects of phleomycin are pleotropic. For instance, it likely induces cell cycle arrest at various cell cycle phases as well as in early and late G2. Additionally, it may influence other cellular processes such as DNA or compete with drug targets such as TORC1 which is influenced by ATP.

      In Figure 3B,C wt is missing to compare the results in the presence of the same treatments. I understand the focus on Ssp1, but the authors should show the same treatments on wt cells. Similarly, it would be better to show the drug treatments in panel C also at 30{degree sign}C. For the same reasons as in the previous point, quantifications would greatly enhance the credibility of the claims here.

      Previous work by other investigators have shown that wt cells proliferate normally under these conditions. We also show in figure 1 that cell proliferation is not affected under nor cycling conditions in these assays. We have added cell length data that convincingly prove that Ssp1 is required to mediate the mitotic effects of caffeine. It appears that caffeine induces a cell cycle delay that requires Ssp1 to suppress Srk1- mediated Cdc25 inhibition. Furthermore, recent studies have demonstrated that rapamycin (which targets TORC1 downstream of Ssp1) allows cell proliferation at higher temperatures in S. pombe.

      A major point is the almost complete absence of molecular data. Except for Figure 6, the data do not include a detection of the relative activation of the relevant pathways. Figure 6 could hardly fill this gap, since the samples therein analyzed are not the ones utilized in most of the other figures, but simple, single time-point treatment with a single drug. The authors usually refer in the text to previous knowledge about how a treatment influences a pathway. However, they should show it here in their experimental conditions.

      We have performed extensive additional experiments including those suggested by the reviewer. These experiments conclusively show caffeine induces Ssp2 phosphorylation in an Ssp1- dependent manner. We also demonstrate that caffeine attenuates TORC1 signaling. Together with the cell cycle data, our findings strongly suggest caffeine indirectly inhibits TORC1 signaling a manner analogous to other environmental stresses. We also note that the inhibitory effect of caffeine on TORC1 has been demonstrated in several studies. What have provided further evidence for this but have for the first time demonstrated, that caffeine affects Ssp2.

      Minor comments:<br /> • A different grouping of the experiments/panels would help the reader. For example, Fig. 2I would fit better together with Fig. 3A, to match the composition of the various chapters of the results.

      We have performed additional experiments as suggested by the other reviewers. We believe the data is now easier to understand.

      Torin 1 is sometimes referred to with a capital T or with a lowercase t, especially in the Figures. I suggest to uniform the nomenclature.

      We have edited the text.

      In the results, the authors state that "ATP may increase TORC1 activity or act as a competitive inhibitor towards both compounds.". It's a little bit odd to refer to ATP as a competitive inhibitor of drugs. I would rather be ATP, the physiological agonist, outcompeting two compounds which are working as ATP-competitive inhibitors.

      We have modified the text accordingly.

      Reviewer #2 (Significance):

      The interplay between TORC1 and AMPK is of great interest in the cell signaling field, basically in every model organism.

      The paper provides a conceptual advance in the field showing a genetic interaction between the two pathways using a model organism which has probably been overlooked so far, which is a pity because S. pombe is the best organism to study G2/M cell cycle/size regulation. The story would be of interest especially for an audience working in cell signaling in microorganisms, but not so much (at least at this stage) for the community working on aging, disease and chemo-/radio-sensitization, contrary to what the authors claim. Furthermore, for the above-mentioned reasons, I feel like the authors are a little bit overshooting when claiming (for example in the abstract and in the discussion), that their work provides a clear understanding of the mechanism.<br /> As requested by Review Commons, I specify that my expertise is on TORC1/AMPK/PKA pathways, on their crosstalk and their regulation by metabolic intermediates.

      We believe that the additional requested experiments have adequately improved the manuscript and support our presented mechanistic model.

      Caffeine is interest in cancer biology and the biogerontology field proven by recent reports on metabolic phenotyping, liver function testing, induction of autophagy and interplay with HIF-1, just to mention a few.

      Reviewer #3 (Evidence, reproducibility and clarity):

      Summary<br /> This manuscript examines the genetic requirements for checkpoint override by caffeine in the fission yeast model organism. The main outcome is to show that checkpoint override, which has previously been linked to the downregulation of TORC1, is dependent on on the AMPK pathway (Ssp1/Ssp2). Additional analysis of downstream factors and the cross-talking Sty1 pathway implicates Greatwall kinases and Igo1 (PP2A inhibitor - endosulfine analogue) although the pleiotropic nature of these pathways and the rather blunt endpoints of septation index and phleomycin sensitivity makes robust data interpretation difficult.

      Major comments<br /> For clarity the manuscript would benefit from some restructuring. In particular it would help the reader if the diagram presented in figure 7 was presented first as this would help orientate the reader with the pathways. The mammalian equivalents should be indicated.

      Figure 8 (previously figure 7) summarizes our findings schematically. We believe that it works well at the end as a conclusion to the work and the discussion. Wherever appropriate we have mentioned the mammalian equivalent (e.g., for Rad3).

      For scientific accuracy and clarity the manuscript requires significant attention. For example in the abstract where Rad3 is introduced it is not made clear that this is the fission yeast gene. It would be better to introduce ATR at this point? Anther example in the abstract: 'Deletion of ssp1 and ssp2 suppresses...' should read 'Deletion of ssp1 or ssp2 suppresses...' as the two genes are not deleted in the same strain. I would recommend that the authors carefully revise the manuscript paying close attention to each statement. Fore example on page 4: 'Downstream of TORC1, caffeine failed to accelerate ppk18D but not igo1D and partially overrode DNA damage checkpoint signalling'. It is unclear what the authors mean by accelerate. I assume they mean accelerate cell cycle progression, but there is no direct analysis of cell cycle kinetics in the results. Similarly on page 5: '... ppk18D mutant displayed slower cell cycle kinetics than wild type cells exposed to phleomycin and caffeine or torin1 (Figuer 1D)'. However, the figure shows no cell cycle kinetic analysis.

      We have modified the wording of the abstract according to the reviewer’s suggestions.

      We refer to accelerated progression into mitosis and have edited the text where appropriate. Depending on the type of DNA damage, S. pombe cells transiently or permanently arrest cell cycle progression. It is well known that caffeine overrides these cell cycle DNA damage checkpoints. We previously proved that this was not due to Rad3 inhibition. Additionally, TORC1 (which controls the timing of mitosis) inhibition overrides checkpoint signaling. Our aim was to investigate if caffeine mimics this effect at least partially, via activation of Ssp2. We have demonstrated this is the case, although the basal state of the various mutants can complicate the data analysis in terms of cell cycle progression. Following exposure to phleomycin, this septation index peaks at 60 minutes following exposure to caffeine. In ppk18 mutants this peak was delayed by 30 minutes. Thus, wt and ppk18 mutants proceed through mitosis and cytokinesis at different rates (as determined by measuring the septation index).

      The authors appear to make the assumption that 'Inhibition of DNA damage signalling by caffeine and torin1 enhanced phleomycin sensitivity...' (page 6) but then clearly go on to show that the mutants used are sensitive for other unknown reasons. To make this link it would be necessary to artificially impose a G2 delay and show how much and in which circumstances this reverses the effect on sensitivity of caffeine/torin1. The authors should thus be very clear that they cannot equate sensitivity to 'checkpoint over-ride' and adjust their wording and assumptions accordingly. Assumptions on epistasis need to use the same assay and not equate between assays. As an example F1C and F2D do not equate as phleo+caffeine would be expected to be sensitised above phleo+torin1. This is not commented on in the text. Also on page 7 '... ATP also suppressed the ability of torin1 to override DNA damage checkpoint signalling albeit to a lesser degree (Figure 2I).' However, this figure only shows sensitivity, not septation index.

      We accept that these results can be difficult to interpret. Firstly, caffeine appears to modulate cell cycle progression by various means. We previously demonstrated that it stabilizes Cdc25 independently of checkpoint signaling. However, it also activates Ssp2 which subsequently affects Cdc25 activity via PP2A. Its effect on mitosis can thus differ depending on the context. For instance, igo1 mutants already have high PP2A activity which would affect the subsequent effect of caffeine on Cdc25 activity. Ssp2 on the other hand appears to regulate cell fate according to the nutritional state. Its sensing of nutritional cues is not limited to ATP/ AMP levels as it also regulates the response to amino acid quality (e.g., glutamate versus torin1).

      We have carried out additional experiments on the effect of ATP. While it did affect progression into mitosis, the results were complicated and have not been shown. Instead, we have provided additional data to show that it affects cell length which is an indicator of G2 cell length. In other words, longer cells spend more time in G2 prior to septation.

      We also suspect that caffeine is itself a DNA damaging agent as previously reported in the early 1970s. More recent studies have also indicated a role for Rad3 and DNA repair proteins for tolerance to caffeine. In fact, TORC1 itself has been reported to be required for DNA damage repair. Thus, TORC1 inhibition could potentially enhance DNA damage sensitivity independently of mitotic progression as shown in some of our experiments.

      While we have clearly identified a role for Ssp2 in mediating the cell cycle effects of caffeine, we accept that these findings will require further studies (beyond the scope of this one); to give more insights on how these caffeine- mediated effects occur. What is clear is that caffeine overrides DNA damage checkpoint signaling by at least partially inhibiting TORC1 signaling.

      All the septation index graphs require an untreated (I.e no caffeine or torin1) control.

      We now show in figure 1a, that the septation index does not change over the time period studied, when cells were left untreated. These assays have been routinely used for many years now and are very reproducible. The graphs clearly show the differential effects caffeine and torin1 exert on cell cycle progression in wt and mutant strains exposed to phleomycin.

      Figure 3 is not quantitative and cannot support the conclusions drawn from it. If, for example, the authors wish to demonstrate ATP can suppress checkpoint override (Figure 3A) they should use the same septation assay used before. If this is not possible, then it should be explained why not and an alternative quantitative assay should be developed. It is unclear why the authors include Figure 3B,C at all.

      Ssp2, on the other hand, appears to regulate cell fate according to the nutritional state. Its sensing of nutritional cues is not limited to ATP/AMP levels as it also regulates the response to amino acid quality (e.g., glutamate versus torin1). Additionally, exposure to stress may induce a transient decline in ATP levels. We thus investigated how ATP might affect caffeine or torin1. We could not detect any major changes in the septation index (not shown). Cells exposed to ATP in the presence of caffeine and phleomycin were shorter. We cannot tell how exactly suppresses the effect of caffeine and torin1 on DNA damage sensitivity.

      It is unclear to this reviewer what the significance of the data with gsk3D cells is (Figure 5). The authors should introduce the protein, why there is an expectation that it would have a role in the pathway and explain its relevance. Similarly when discussing the resulting data.

      Gsk3 lies downstream of TORC2 which is inhibited by torin1 but not caffeine. Gsk3 regulates Pub1 stability which is the E3 ligase for Cdc25. We showed previously that caffeine stabilizes Cdc25, suggesting it might interfere with Pub1 activity. Additionally, we are investigating caffeine as an indirect inhibitor of TORC1 with torin1 that directly inhibits both complexes. Our data provide further evidence for a differential effect of caffeine and torin1 on TORC1 signaling. We have modified the text accordingly.

      Figure 5A shows a similar response of wild type cells to phleomycin regarding checkpoint override as was shown in Figure 1A. However Figure 5C is not recognisable as equivalent to Figure 2A, yet both report sensitivity to phleomycin od wild type cells under equivalent circumstances. This is a major concern as to reproducibility of these data. It is also not possible to conclude from either Figure 5C or 5D that caffeine or torin1 treatment is, or is not, sensitising cells to phleomycin treatment, yet this conclusion is made when discussing the data.

      We agree with this and other reviewers that demonstrating enhanced sensitivity to caffeine is problematic. Nonetheless, our cell cycle data clearly indicate a differential role for Gsk3 in mediating the cell cycle effects of caffeine and torin1. In terms of DNA damage sensitivity, we have reproducibly observed a lower degree of DNA damage sensitivity in gsk3 mutants relative to wt cells. Hence, while caffeine is less effective at enhancing DNA damage sensitivity relative to torin1 in wt cells; we observed that caffeine and torin1 increase DNA damage sensitivity to a similar degree in gsk3 mutants.

      Figure 6A shows that caffeine, but not torin1 results in Ssp2 phosphorylation. Is this experiment reproducible and does the total level of Ssp2 increase reproducibly? This should be doe ae and the results discussed. Ideally, the bands would be quantified against actin intensity and presented as a bar graph with standard deviation.

      We have repeated these experiments alone and in combination with phleomycin. This data convincingly show that caffeine but not torin1 induces Ssp2 phosphorylation. In fact, torin1 suppresses Ssp2 phosphorylation, likely due to inhibition of a feedback mechanism resulting from TORC1 inhibition. In contrast, caffeine likely activates Ssp1 via the stress response, which in turn phosphorylates Ssp2.

      Figure 6B, when introduced should explain the background as to why eIF2alpha phosphorylation is a readout of TORC1 activity. Importantly, the figure should be supported by an actin control and 3 repeats quantified. Figure 6C purports to establish that caffeine moderately attenuates Maf1 phosphorylation. To be able to state this, it would be essential to quantify the gel and report repeated results relative to actin and the total levels of Maf1. Similarly Figure6D and 6E require an actin control and would benefit from proper quantification.

      We have repeated the Maf1 experiments to clarify the data and show that caffeine suppresses Sck1 an additional TORC1 phosphorylation target.

      Minor comments<br /> p3 'cigarette smoke and other gases'?

      We have edited the statement.

      P4 torin1 was dissolved in DMSO (not were)

      We have edited the text.

      p5 phospho not phosphor Ssp2

      We have edited the text.

      p6 exlpain why ppk18 deletion results are surprising. Also this result could be discussed.

      It had been proposed previously, that Ppk18 is the Greatwall homologue in S. pombe and thus the major regulator of PP2A and mitosis downstream of TOCR1. Later studies suggested a redundant role for Cek1 in this pathway. While deletion of cek1 in a ppk18 background modulated the effect of torin1 on cell cycle progression, it did not interfere with the effects of caffeine. At present we cannot account for this observation. We cannot rule out that caffeine activates an additional kinase that regulates Igo1 activity.

      Together our data show that caffeine advances progression into mitosis in a manner that differs from direct inhibition of TORC1 by torin1.

      We have now added the relevant comments on this unexpected observation within the discussion.

      Explain why Cek1 is not tested

      We have now tested a ppk18 cek1 double mutant.

      p6 introduce what pap1 is when first mentioned

      We have introduced PP2APab1 as requested.

      Reviewer #3 (Significance):

      The data show that fission yeast Ssp1/2 has a role in inhibiting TORC1 in response to caffeine and this influences checkpoint override. This is an incremental, but potentially interesting, observation contributing to understanding mechanism(s) of caffeine action. The lack of quantification, the pleiotropic nature of the mutants used and the rather blunt endpoints assayed make it hard to establish to what extent the direct TORC1 inhibition by Ssp2 causes the checkpoint override, which limits is potential impact. The core observation may, however, be of interest to the wider caffeine field. The referee has the perspective of a yeast cell cycle geneticist.

      We thank the reviewer for identifying the significance of the study in understanding the mechanisms of caffeine effects on the cell cycle. We have added all the suggested experiments with additional mutants and protein markers as well quantitative approaches that have appropriately improved the manuscript. We believe that the mechanism provided is of more general interest and not limited to the caffeine field: manipulating the cell cycle and understanding the interplays between growth and stress are of general interest and importance.

      Reviewer #4 (Evidence, reproducibility and clarity):

      The authors provide a series of genetic studies identifying a role for Ssp1-Ssp2 signaling in TORC1-dependent responses to DNA damage. The main assays are cell division (i.e. septation index) and cell viability (i.e. serial dilution spot assays) following treatment with the DNA damaging agent phleomycin. The authors perform these assays in a number of genetic mutant backgrounds to determine which genes and pathways are required for the relevant cellular response. Supporting data also include microscopy images and western blots to test protein phosphorylation. In general, the results support a role for Ssp1-Ssp2 acting upstream of TORC1. However, in several cases the data do not support a straightforward relationship, and it is confusing to parse through a number of intermediate effects, which often vary between different assays. I have provided some specific comments below that might be addressed to strengthen the technical aspects of the manuscript.

      Major<br /> 1. The authors conclude "that caffeine and torin1 indirectly and directly inhibit TORC1 activity respectively" based on Figure 1. This conclusion seems quite strong given the indirect nature of assays in Figure 1, which test septation in the presence of DNA damage. The conclusion would require experiments that assay TORC1 activity itself.

      Both caffeine and torin1 have previously been reported to inhibit TORC1 which controls the timing of mitosis. We sought to investigate if caffeine mediates its effects via the stress response pathway. We have conducted additional experiments which clearly demonstrate that caffeine inhibits TORC1 at least partially via the activation of Ssp2. These observations make sense as we have previously shown that caffeine actives the stress response pathway to activate Srk1 which inhibits Cdc25. More recent studies my others indicate that Ssp1 is required to suppress Srk1 to allow progression into mitosis. This accounts for the failure of ssp1 mutants to advance mitosis under stress conditions. Additionally, Ssp1 activates Ssp2 which leads to the downstream inhibition of TORC1.

      1. Figure 2 needs some explanation to introduce the idea that cell growth reflects an intact DNA damage response that prevented division in the presence of phleomycin. I also felt that the conclusions were very strong given the data, and the authors should discuss each case more carefully. For example, deletion of ssp1 does not really suppress the ability of torin1 to enhance phleo sensitivity (Figure 2C).

      We would not expect the deletion of ssp1 to suppress the effect of torin1 under stress conditions. We have provided further evidence to show that Ssp1 is required to facilitate progression into mitosis at least in the presence of phleomycin or heat stress.

      1. Microscopy imaging in Figure 3 nicely complements some of the other assays. However, it seems important to know if the cells are actively growing in each of these cases. An example is torin and rapamycin shortening ssp1 mutants at 35 degrees: are these cells actively cycling?

      Our aim was to demonstrate that caffeine exacerbates the ssp1 phenotype. This would provide further evidence to show that caffeine exerts its effects at least in part by activating Ssp1. Cells do not cycle in the presence of torin1 as it inhibits both TORC complexes. We have provided additional evidence to show that caffeine does indeed interact with Ssp1. As the primary aim of the study was to determine is caffeine overrides DNA damage via Ssp1 we have not investigated if they are cycling. Their shortened size suggests that rapamycin and torin1 affect cell division in a different manner from caffeine.

      1. From Figure 6A, the authors conclude that caffeine induces phosphorylation of Ssp2. However, it appears that both Ssp2 protein levels and its phosphorylation levels are both increased, which seems an important distinction.

      We have repeated these experiments several times under different conditions. Some proteins become more stable when phosphorylated as has been previously demonstrated for Srk1 for instance.

      1. In Figure 6D, the authors should show separate gsk3 and ssp1 mutants. It seems likely that all phosphorylation of Ssp2 is due to Ssp1, but this should be shown.

      We have replaced the figure with a ssp1 single mutant.

      1. I am confused about Maf1 phosphorylation in Figure 6C. It is increased upon torin1 treatment, but it is discussed as an indicator or TORC1 activity. Does that mean that loss of its phosphorylation correlates with increased TORC1 activity? As written, I thought it was a TORC1 substrate, which led to confusion about its increased phosphorylation upon torin1 treatment.

      Maf1 is phosphorylated by TORC1. Inhibition of TORC1 would thus lead to a loss of phospho-Maf1 moieties and the accumulation of the unphosphorylated form. We have conducted additional experiments and under various conditions to show that caffeine weakly inhibits Maf1 phosphorylation. We note however, that different stresses result in differential outcomes following TORC1 inhibition. As such we have included new data to show that caffeine suppresses the TORC1 target Sck1. In S. pombe Sck1 and Sck2 regulate progression into mitosis.

      Minor<br /> 1. An untreated control should be shown for assays in Figure 1.

      We have included this data for figure 1a.

      1. An untreated control should be shown for assays in Figure 4.

      We have noted in the results for figure 1, that untreated cells and phleomycin only treated cells do not show any changes in septation index over the time course studied in these experiments.

      Reviewer #4 (Significance):

      The study has significance in connecting several conserved and central signaling pathways including TORC1, AMPK, and PP2A. Also, the study uses caffeine and torin1 that have effects in many different cell types. The connection between caffeine and torin1 effects on phleomycin-treated cells was previously established by these researchers. The significance of the current study is providing a genetic pathway for this connection. The significance is partly limited by some of the technical points raised in the previous section, such as some inconsistencies in the strength of results from different assays. Also, the role of these pathways in DNA damage response signaling is not new. While the main significance of this work might relate to a more specialized audience, it does add to a broader body of literature regarding these conserved pathways and processes.

      My expertise is yeast cell biology.

      While the roles of the pathways in DNA damage has been reported usinbg genetic and pharmacological combinations we dissect their relationships and provide mechanistic connections.

      We thank the reviewer for identifying the significance of this study. We believe we have now addressed the technical issues raised.

    1. Reviewer #1 (Public Review):

      Ritvo and colleagues present an impressive suite of simulations that can account for three findings of differentiation in the literature. This is important because differentiation-in which items that have some features in common, or share a common associate are less similar to one another than are unrelated items-is difficult to explain with classic supervised learning models, as these predict the opposite (i.e., an increase in similarity). A few of their key findings are that differentiation requires a high learning rate and low inhibitory oscillations, and is virtually always asymmetric in nature.

      This paper was very clear and thoughtful-an absolute joy to read. The model is simple and elegant, and powerful enough to re-create many aspects of existing differentiation findings. The interrogation of the model and presentation of the findings were both extremely thorough. The potential for this model to be used to drive future work is huge. I have only a few comments for the authors, all of which are relatively minor.

      1. I was struck by the fact that the "zone" of repulsion is quite narrow, compared with the zone of attraction. This was most notable in the modeling of Chanales et al. (i.e., just one of the six similarity levels yielded differentiation). Do the authors think this is a generalizable property of the model or phenomenon, or something idiosyncratic to do with the current investigation? It seems curious that differentiation findings (e.g., in hippocampus) are so robustly observed in the literature despite the mechanism seemingly requiring a very particular set of circumstances. I wonder if the authors could speculate on this point a bit-for example, might the differentiation zone be wider when competitor "pop up" is low (i.e., low inhibitory oscillations), which could help explain why it's often observed in hippocampus? This seems related a bit to the question about what makes something "moderately" active, or how could one ensure "moderate" activation if they were, say, designing an experiment looking at differentiation.

      2. With real fMRI data we know that the actual correlation value doesn't matter all that much, and anti-correlations can be induced by things like preprocessing decisions. I am wondering if the important criterion in the model is that the correlations (e.g., as shown in Figure 6) go down from pre to post, versus that they are negative in sign during the post learning period. I would think that here, similar to in neural data, a decrease in correlation would be sufficient to conclude differentiation, but would love the authors' thoughts on that.

      3. For the modeling of the Favila et al. study, the authors state that a high learning rate is required for differentiation of the same-face pairs. This made me wonder what happens in the low learning rate simulations. Does integration occur? This paradigm has a lot of overlap with acquired equivalence, and so I am thinking about whether these are the sorts of small differences (e.g., same-category scenes and perhaps a high learning rate) that bias the system to differentiate instead of integrate.

      4. For the simulations of the Schlichting et al. study, the A and B appear to have overlap in the hidden layer based on Figure 9, despite there being no similarity between the A and B items in the study (in contrast to Favila et al., in which they were similar kinds of scenes, and Chanales et al., in which they were similar colors). Why was this decision made? Do the effects depend on some overlap within the hidden layer? (This doesn't seem to be explained in the paper that I saw though, so maybe just it's a visualization error?)

      5. It seems as though there were no conditions under which the simulations produced differentiation in both the blocked and intermixed conditions, which Schlichting et al. observed in many regions (as the present authors note). Is there any way to reconcile this difference?

      6. A general question about differentiation/repulsion and how it affects the hidden layer representation in the model: Is it the case that the representation is actually "shifted" or repelled over so it is no longer overlapping? Or do the shared connections just get pruned, such that the item that has more "movement" in representational space is represented by fewer units on the hidden layer (i.e., is reduced in size)? I think, if I understand correctly, that whether it gets shifted vs. reduce would depend on the strength of connections along the hidden layer, which would in turn depend on whether it represents some meaningful continuous dimension (like color) or not. But, if the connections within the hidden layer are relatively weak and it is the case that representations become reduced in size, would there be any anticipated consequences of this (e.g., cognitively/behaviorally)?

    1. Champine recognized that her data could support Darden in her pursuit of a promotion and, furthermore, that these data could help communicate the systemic nature of the problem at hand. Champine visualized the data in the form of a bar chart, and presented the chart to the director of Darden’s division.9

      Something I often forget regarding the importance of data is that if data is not analyzed or compiled legibly, it can easily be lost. It's tangible, visual form is just as important as the data itself, because it allows equal access to the content.

    1. But we also need new generations of user-accountable institutions to realize the potential of new tech tools—which loops back to what I think Holgren was writing toward on Bluesky. I think it’s at the institutional and constitutional levels that healthier and more life-enhancing big-world tools and places for community and sociability will emerge—and are already emerging

      institutionalising as a way for socsoft to become sustainable, other than through for profit structures that have just one aim. Vgl [[2022 Public Spaces Conference]], I have doubts as institutions are slow by design which is what gives them their desirable stability. Vgl [[Invisible hand of networks 20180616115141]] vs markets.

      Also : generations are institutions too. It is needed to repeat these things to new gens, as they take what is currently there as given. Is currently true for things like open data too.

    2. Even most of the emergent gestures in our interfaces are tweaks on tech-first features—@ symbols push Twitter to implement threading, hyperlinks eventually get automated into retweets, quote-tweets go on TikTok and become duets. “Swipe left to discard a person” is one of a handful of new gestures, and it’s ten years old.

      Author discusses specific socially oriented interface functions (left/right swiping, @-mentions) that are few and old. There's also the personal notes on new connections in Xing and LinkedIn (later), imo. And the groupings/circles in various platforms. Wrt social, adding qualitative descriptions to a connection to be able to do pattern detection e.g. would be interesting, as is moving beyond just hub with spokes (me and my connections) and allowing me to add connections I see between people I'm connected to. All non-public though, making it unlikely for socmed. Vgl [[Personal CRM as a Not-LinkedIn – Interdependent Thoughts 20210214170304]]

    1. Just as our perception of others affects how we communicate, so does our perception of ourselves.

      As chapter one mentioned, I think that positive or negative self-talk also plays a big role in how we perceive ourselves. I think that if talk to ourselves with compassion and understanding when we have negative thoughts and feelings about ourselves, it would definitely help increase our self-esteem. This section talks about how if you only think good things about yourself, it can lead to an unrealistic sense of self. Like I said, I think that it's okay to have positive self-talk when things go wrong, or you make a mistake to maintain your self-esteem. This can allow you to self-reflect and make improvements without harming your self-perception.

    1. In 2010, Paul Dourish and Genevieve Bell wrote a book about tech innovation that described the way technologists fixate on the “proximate future” — a future that exists “just around the corner.” The authors, one a computer scientist, and the other a tech industry veteran, were examining emerging tech developments in “ubiquitous computing,” which promised that the sensors, mobile devices, and tiny computers embedded in our surroundings would lead to ease, efficiency, and general quality of life. Dourish and Bell argue that this future focus distracts us from the present while also absolving technologists of responsibility for the here and now.

      Proximate Future is a future that is 'nearly here' but never quite gets here. Ref posits this is a way to distract from issues around a tech now and thus lets technologists dodge responsibility and accountability for the now, as everyone debates the issues of a tech in the near future. It allows the technologists to set the narrative around the tech they develop. Ref: [[Divining a Digital Future by Paul Dourish Genevieve Bell]] 2010

      Vgl the suspicious call for reflection and pause wrt AI by OpenAI's people and other key players. It's a form of [[Ethics futurising dark pattern 20190529071000]]

      It may not be a fully intentional bait and switch all the time though: tech predictions, including G hypecycle put future key events a steady 10yrs into the future. And I've noticed when it comes to open data readiness and before that Knowledge management present vs desired [[Gap tussen eigen situatie en verwachting is constant 20071121211040]] It simply seems a measure of human capacity to project themselves into the future has a horizon of about 10yrs.

      Contrast with: adjacent possible which is how you make your path through [[Evolutionair vlak van mogelijkheden 20200826185412]]. Proximate Future skips actual adjacent possibles to hypothetical ones a bit further out.

    1. 2.22 Mains Power

      This section discusses main power and the way that it works in it's entirety.

      In the US, three wires run from the transformer, (through meter) and into your "mains" (main circuit breaker for your home). * These 3 wires are Phase A (black wire), Phase B (black wire), and neutral (white wire). * Phase A and B are both connected into the main's main breaker. Neutral is connected to a "neutral bus". Additionally, there is a ground bar in the main panel, this ground bar connects to a rod that can be found lodged in the ground called a "grounding rod"

      • It's important to note the terms "line-to-line" and "line-to-neutral". Connected Phase A and Phase B together results in a voltage that is 240V (typically requiring a double pole breaker, and specifically for ovens, dryers, etc.). On the other hand, Phase A or Phase B connected to Neutral would be 120V (lower power appliances like lighting and switches, etc.)

      • It's also important to note that it's not good practice to just connect all of your breakers on one side of the panel (either Phase A solely, or Phase B solely), as this would lead to an "imbalanced" load. Having your panel imbalanced can lead to voltage imbalances and power loss through the system

      • Another note: Both neutral bar and ground bar are connected to each other and lead to the ground rod in the ground of your home

    1. The internal cognitive process that allows participants to send, receive, and understand messages is the encoding and decoding process. Encoding is the process of turning thoughts into communication. As we will learn later, the level of conscious thought that goes into encoding messages varies. Decoding is the process of turning communication into thoughts.

      I actually just had a conversation with someone about this. She works with ESL (English as a Second Language) students, and was talking about some of the ins and outs of their learning process. One common issue is that many tutors tend to rush the decoding process for students. They'll ask a question, then continue to speak without allowing enough time for a response. It takes another minute to come up with an answer when its a language you're still learning. It's hard enough in your native language sometimes!

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Reply to the reviewers

      Dear Editor and reviewers,

      We would like to thank the three reviewers for their thorough review of our manuscript and their detailed comments and very helpful suggestions to improve the manuscript. Overall, we thought the reviews were very positive with the reviewers commenting that our discovery of a novel genetic code variant is a “cause for celebration” and that our study is “technically solid” and “rigorous”. All three reviewers agree that our manuscript would “stimulate new discussions in the field of genetic code evolution” and also be of broad interest to evolutionary cell biologists, protistologists and the translation/protein synthesis community at large. The reviewers highlight the particular novelty of the genetic code variant described here due to it being an exception to the wobble hypothesis which adds a new level of complexity to stop-codon reassignment. The reviewers share our frustration about the lack of proteomics data due to being unable to establish a stable culture but acknowledge that we address this limitation frankly in our discussion and agree that it is “frustrating but it's not a limitation”.

      We present an updated and improved version of the manuscript after taking on board the reviewers’ suggestions. Our point-by-point responses to their comments and our modifications are detailed below in bold.

      Point-by-point description of the revisions

      __Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

      Summary

      This study by J. McGowan and colleagues reports the discovery of a ciliate species that uses a variant genetic code where the codons UAA and UAG, which are stop codons in the canonical code, instead code for lysine and glutamate respectively. The primary data are genomic and transcriptomic sequence libraries from single cells. The genetic code was predicted by aligning coding sequences to references from other species and examining the most frequent amino acids in positions homologous to putative coding-UAA/UAGs. They also identified suppressor tRNAs for UAA and UAG, and tandem in-frame stop UGAs (but not UAA/UAG) in the 3'-UTR, which further support the recoding of UAA and UAG.

      A limitation of this study (and several other recent studies on variant genetic codes) is that the predictions are based on nucleic acid sequencing, without confirmation from proteomics. The authors acknowledge and briefly but frankly discuss the limitations in their manuscript (lines 258-261).

      Major comments

      Controls against contamination and sequence chimeras

      The ciliate species studied here was an environmental isolate, and sequence libraries were prepared by amplification from small pools of cells sorted by FACS. The genome assembly was produced by co-assembly of multiple amplified libraries. Given the potential for contamination and amplification artefacts (such as sequence chimeras) associated with these methods, I think it is important to demonstrate that the data truly originate from one species, so as to rule out the possibility that the co-assembly may be chimeric, i.e. representing two or more organisms with different genetic codes (one with UAA recoded and the other with UAG recoded, for instance). Even if the cell sorting was accurate, contamination could still enter down the line during library preparation so it would be important to show internal evidence from the sequence data too.

      We understand the reviewer's concerns about the possibility of contamination as it can be a major issue in environmental single cell sequencing experiments. We have addressed the individual points below in detail to demonstrate that we have generated a clean genome assembly of a single ciliate species but also summarise here:

      • The cells we sequenced originated from the same clonally isolated cell propagated in culture
      • We have manually curated the assembly
      • The assembly has a unimodal GC content peak with a low BUSCO duplication score
      • Most genes (95.9 %) contain both in-frame UAA and UAG codons
      • We recovered a single identical ciliate 18S rRNA gene across all 10 samples
      • De novo assemblies of the 10 individual gDNA libraries are virtually identical in terms of average nucleotide identity
      • We also predicted the genetic code for each of the genome and transcriptome samples individually
      • 85% of the final assembly is taxonomically classified as Ciliophora. The remainder is either unclassified (i.e. no hits) or has spurious/inconsistent hits

        Specifically:

      (a) From the description in Methods under "Sampling, Ciliate isolation, culturing, and cell-sorting", it is not clear whether all the cells that were ultimately sequenced originated from the same clone (i.e. the same well in the 96-well plate described in line 389). Could the authors confirm whether this was the case?

      Yes. All the sorted cells originated from the same ciliate clone. A single-cell was isolated and cleaned (without removing all the environmental bacteria). The ciliate single-cell divided and we established a mono-clonal ciliate culture that we used for the cell sorting and sequencing. This culture grew but only for a relatively short period. We could not establish a long term culture.

      (b) What % of genes have in-frame coding UAA, UAG, or both? How per gene on average? Counts are given for the conserved genes/domains identified by PhyloFisher or Codetta (lines 192-207), and overall frequencies per codon are addressed later in lines 263 onward, but how often do they occur together in the same genes?

      My reasoning behind this is that if genes with both in-frame coding UAA and UAGs are common then it is very unlikely to be the result of chimeric sequence artefacts from whole-genome amplification.

      We have updated the text to include this information. From the PhyloFisher analysis, we had reported that 58 genes contained in-frame UAA codons and 46 genes contained in-frame UAG codons. We have now added the text “Amongst the genes identified by PhyloFisher, 27 contained both an in-frame UAA codon and an in-frame UAG codon.”

      Additionally, from our annotated gene set, we had reported that 98.6% of genes contain at least one UAA codon and 96.4% of genes contain at least one UAG codon. We have now added text to report how many genes contain both codons “The reassigned codons are widely used across genes with 95.9% of genes containing both a UAA codon and a UAG codon”.

      The example gene (tubulin gamma chain protein) shown in Figure 1 contains both in-frame UAA codons and in-frame UAG codons, with the UAA codons aligning to lysine and the UAG codons to glutamic acid.

      (c) What is the sequence identity of conserved marker sequences between the individual amplified replicate libraries?

      I would naively expect that individual replicates may not have the full set of markers because of uneven amplification, but if the sequences originate from the same clone they should have overlapping coverage of the conserved markers, and these should be +/- identical between replicates (save for allele variants). If so this would support the claim that contaminant sequences were mostly removed during sequence QC and that the cells were clonal.

      We generated an individual assembly for each of the 10 gDNA libraries and calculated average nucleotide identity at the whole assembly level. On average, the 10 assemblies are 99.43% identical to each other, with the least similar pair being 99.37% identical to each other. This level of variation includes not only allelic variants but also sequencing/assembly errors as the individual libraries are relatively low coverage. In terms of assembly alignment coverage (i.e. the fraction of each assembly that is aligned to another assembly), the average value is 76.5% and the value for the lowest pair is 59.1%. We have now also made the individual 10 assemblies available in the Zenodo repository (10.5281/zenodo.7944379) and updated the methods section.

      Furthermore, as an additional quality control step, we predicted the genetic code for each of the 10 individual genome assemblies and obtained the same predictions that UAA encodes lysine and UAG encodes glutamic acid for all 10 individual assemblies. We also predicted the genetic code for each individual RNA-Seq sample based on individual transcriptome assemblies which yielded consistent predictions.

      (d) Line 392: "Non-axenic" presumably refers to environmental prokaryotes. This also appears to contradict the statement that the cells were "free of any other contaminant" (line 387). Could authors confirm whether they mean "non-axenic but monoeukaryotic"?

      In line 387, when we say "free of any other contaminant” we mean that we isolated a ciliate single-cell from the environmental sample, and the picked ciliate cell was washed 3 times until it was free of any other eukaryotes, but still containing environmental bacteria. In line 392, when we say non-axenic, we mean that the mono-clonal ciliate culture contained environmental bacteria and was monoeukaryotic.

      We have modified the text in the methods section to say “free from any other eukaryote” and “non-axenic but monoeukaryotic”.

      (e) Lines 448-451: More details should be given on the criteria used to identify and bin out contaminants. MetaBAT typically bins prokaryotic genomes quite well, but not eukaryotic ones. What did the bins look like and how were the eukaryotic ones chosen?

      We routinely use MetaBAT2 to assist with separating bacterial contigs from protist genomes. From our experience we find that it generally performs well but requires careful manual curation. We only use tetranucleotide frequencies when binning single-cell assemblies and not coverage variance as this is heavily skewed due to amplification bias from single-cell amplification. We integrated the binning results from MetaBAT2 with taxonomic classification from tools such as CAT, Blobtools and Tiara, and manually curated the assembly.

      We have modified both the results and methods section to clarify that the assembly was manually curated to remove contaminant contigs.

      For example, using CAT, which taxonomically classifies contigs based on blast/diamond hits to open reading frames:

      The final curated assembly is 69.7 Mb in length.

      59.5 Mb (85.4%) is classified as Ciliophora.

      9.7 Mb (13.9%) is unclassified.

      The remaining 0.5 Mb (0.7%) have inconsistent, low-identity hits to 22 different Eukaryotic and Bacterial phyla (due to lack of closely related species in public databases).

      Furthermore, we recovered only a single ciliate 18S rRNA gene and the final curated assembly has a unimodal GC content peak with a low BUSCO duplication score and high cDNA mapping rate.

      __Minor comments __

      Line 52: Not strictly true, some germline-limited segments contain mobile elements with coding sequences, e.g. TBE elements in Oxytricha (doi:10.1371/journal.pgen.1003659)

      Thank you for pointing this out. We have rephrased “excision of non-coding sequences” to “excision of micronucleus-limited sequences” to describe the process of macronuclear development more generally.

      Lines 229-231, Supplementary Table 1: Presenting the identity matrix as a distance tree may make it easier to see the pattern of similarity between the tRNAs

      We have added a phylogenetic network of tRNA genes as a supplementary figure to better visualise the relationships between tRNA genes.

      Lines 274-275: Suggest stating the criterion for classifying genes as "highly expressed" on the first mention of this in the Results, although it's explained later on in the Methods.

      We have clarified this in the results section by adding the text: ‘We defined a subset of genes as “highly expressed” based on the 10% of genes with the highest transcripts per million (TPM) values for comparison below.’

      Lines 298-299: What is the frequency of tandem UGA stops in the 3'-UTR in genes with coding-UAA/UAG vs. genes without, and is there a significant difference? The argument in this paragraph is that UAA+UAG reassignment increases selective pressure to minimize translational readthrough. Therefore I think that it would make sense to compare the frequency in genes with and without these codons.

      Following the reviewer’s suggestion, we have looked at tandem UGA stop codons in the 3’-UTR of genes that don’t use UAA and genes that don’t use UAG. We found similar enrichment for in-frame UGA codons at the beginning of the 3’-UTR in these small subsets of genes.

      To clarify, the hypothesis from the literature is that there may be stronger selective pressure to maintain tandem stop codons in ciliates with reassigned genetic codes, particularly those that use only UGA as a stop codon. Within a genome, we wouldn’t expect a difference if a gene contains UAA/UAG codons.

      Lines 353-354, Figure 5: Suggest marking the internal nodes where genetic code changes likely occurred. At the moment only the leaves of the tree are annotated with the genetic codes of the respective species. This would make it clearer how one counts the numbers of independent origins as reported in the text (e.g. "... a fourth independent origin of UGA being translated as tryptophan").

      We have decided not to label the internal nodes on the phylogeny. We think that deeper sampling will reveal that some of these genetic code changes occurred independently, so we don’t want the figure to be misleading. Also, for the species with the genetic code UAA=Q, UAG=Q and UGA=W, we can’t determine the order of events.

      Lines 371-372: Question out of curiosity (not necessary to address for the manuscript at hand): Do the authors think the recoding of UAA and UAG happened simultaneously in both codons or stepwise, or is there insufficient information to speculate?

      An initial guess would be that it happened as a stepwise process but without deeper sampling of this lineage it is not possible to determine the order of events.

      This highlights the need for deeper sampling and sequencing across undersampled lineages of ciliates and demonstrates the utility of single-cell OMICs approaches for species that are not yet amenable to culturing.

      Line 395: "10uL" should use the actual symbol for "micro" prefix. Also, the choice of spacing or no spacing between numerical figure and units should be made consistent in manuscript.

      Fixed

      Line 403: "Biotynilated" should be "Biotinylated"

      Fixed

      Line 414 and elsewhere: "2" in MgCl2 should be subscripted

      Fixed

      Lines 419-420: Clarify whether the "r" and "+" symbols are to be read as prefixes or suffixes, i.e. is the modified base the preceding or succeeding one.

      We have clarified in the text that these symbols are to be read as prefixes.

      Table 1: What is the difference between the two sets of BUSCO completeness scores reported? One is given under "Genome assembly" and the other under "Genome annotation", but the annotation is based on the same assembly, right? I'm assuming this has to do with different modes in which BUSCO can be run, but this should be explained in the Methods (lines 452-453, 496-497) and briefly explained in the Table caption.

      Yes this is because we ran BUSCO in two different modes. BUSCO is run in genome mode on the genome assembly and in protein mode on the genome annotation. In genome mode gene prediction is performed by Augustus guided by amino acid BUSCO group block-profiles while in protein mode the gene set described in our methods is the input to BUSCO classification. The superior BUSCO results for the protein mode reflect the superiority of our final annotation over that generated by BUSCO Augustus. We have added text to the methods section and to the table caption to clarify which mode was used.

      **Referee Cross-commenting** I generally agree with the other reviewers' comments. Specifically I like reviewer #3's suggestion #3 to have a more detailed summary of the codon frequencies, perhaps as a graphic, and to compare the tandem stop frequencies with other ciliate species, especially those with all three canonical stops.

      Reviewer #1 (Significance (Required)):

      Any new genetic code variant discovered is a cause for celebration! This is a basic biological fact with inherent significance and should be generally interesting to biologists because the rarity of variant codes stands in contrast to the diversity of most biological systems.

      This variant code would also stimulate new discussions in the field of genetic code evolution specifically because, as the authors point out, when both UAA and UAG are recoded they both usually encode same amino acid, but here they are recoded to different ones. This is an apparent exception to the "wobble" hypothesis for why these codons often evolve in concert, which was well explained with relevant citations in the Introduction.

      For context: My expertise is in genomics and environmental microbiology.

      END reviewer 1

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      This study reports the reassignment of the UAA and UAG stop codons to lysine and glutamic acid, respectively, in the ciliate Oligohymenophorea sp PL0344. The paper is nicely written, easy to read and the experimental approach, ideas and questions are easy to follow. The work is technically solid both at the NGS - in house library preparation, sequencing and data interpretation - as well as phylogeny levels. The conclusions are consistent with the comparative genomic and transcriptomic data obtained by the study.

      __Reviewer #2 (Significance (Required)): __

      The work extends current knowledge on codon reassignment in ciliates, confirming previous discoveries of existence of very high stop codon assignment flexibility in these organisms. The assignment of UAA and UAG to two different amino acids by two different tRNAs is very interesting and reinforces the idea that stop codon reassignment in ciliates is rather common. It also raises important questions about the parallel evolution of the release factor-1 (eRF1), Lysine and Glutamine tRNAs, as the reassignment requires loss of recognition of both UAA and UAG by eRF1 with parallel appearance of the new Lysine and Glutamic Acid suppressor tRNAs.

      The main issue of this work is the inability to cultivate the ciliate Oligohymenophorea sp PL0344 in the laboratory to prepare protein extracts for direct analysis of the amino acids inserted at UAA and UAG sites by Mass Spectrometry. The comparative genomic and transcriptomic data, as well as the identification of cognate tRNA anticodons for UAA and UAG, are likely correct, but provide indirect evidence for the assignment of UAA to Lysine and UAG to Glutamic Acid. This issue is relevant because one cannot exclude the possibility of insertion of other amino acids at UAA and UAG sites beyond Lysine and Glutamic acid, respectively; nor can one exclude the possibility that such amino acids are inserted at high level. The authors do acknowledge the limitations of the unavailability of protein extracts for direct MS analysis of the reassignment, but should consider, in particular in the discussion, the possibility of multiple amino acid insertions in a context where Lysine and Glutamine Acid are the major but not the only amino acid species being inserted at those sites.

      Based on my expertise of studying codon reassignments in fungi of the CTG clade, I believe this work is very interesting and appealing to the genetic code community, and is of relevance to the evolution and protein synthesis research communities at large.

      We thank the reviewer for their positive review. They raise an important point about the possibility of amino acids other than lysine and glutamic acid being inserted for UAA/UAG codons which we hadn’t considered. We have added text and relevant references to our discussion to highlight this possibility:

      “Additionally, while the genomic and transcriptomic data provide strong evidence that lysine and glutamic acid are the major translation products of UAA and UAG codons, respectively, we cannot rule out the possibility that other amino acids are (mis)incorporated at these sites which could be detected using mass-spectrometry [38, 39].”

      Krassowski T, Coughlan AY, Shen X-X, Zhou X, Kominek J, Opulente DA, et al. Evolutionary instability of CUG-Leu in the genetic code of budding yeasts. Nat Commun. 2018;9:1887. Mordret E, Dahan O, Asraf O, Rak R, Yehonadav A, Barnabas GD, et al. Systematic Detection of Amino Acid Substitutions in Proteomes Reveals Mechanistic Basis of Ribosome Errors and Selection for Translation Fidelity. Molecular Cell. 2019;75:427-441.e5.

      END reviewer 2

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      Summary: from genome and transcriptome sequencing of what appears to be a novel ciliate from the class Oligohymenophorea, McGowan et al provide convincing evidence of a protist in which the stop codons UAA and UAG have almost certainly been recoded to specify incorporation of different amino acids (UAA = K; UAG = E) during translation. Several ciliates from different classes use a non-standard genetic code (as do a narrow variety of other protists), but this is an unusual observation in that stop codons which differ only in the wobble position code for different amino acids in the ciliate identified here.

      I say 'almost certainly' the stop codons have been recoded in Oligohymenophorea sp. PL0344 because in the absence of being able to retain the ciliate in culture the authors have not been able to complete the proteomics which would unequivocally (a) show stop codons now code for amino acids and (b) confirm the identity of the amino acids now encoded (the authors discuss this issue on p12).

      Comments: overall this manuscript is straightforward to read and the analyses realistically taken as far as is realistic in the absence of a continuous culture method. My suggested revisions should be straightforward for the authors to address.

      1) The manuscript appears to report the identification and genome/transcriptome sequencing of a novel ciliate species - clarity should be provided by the authors. However, it disappointed me that this manuscript was crafted entirely from nucleotide sequencing. I would have welcomed seeing the morphology of the ciliate identified here and would have anticipated that there was sufficient material to perform microscopy at the light level (for DIC images) and by scanning or transmission electron microscopy.

      Yes, based on the 18S rRNA sequence and phylogenies of protein-coding genes, this is a novel species that hasn’t been described before. The most similar hits to the 18S rRNA gene are to other unnamed/environmental sequences. We haven’t attempted to name or describe this species as we weren’t able to establish a culture, so have referred to it as Oligohymenophorea sp. PL0344. We have clarified in the text that this is a novel, unnamed ciliate species.

      The genomic and transcriptomic data was generated from a single cell isolate propagated into micro-cultures of 10’s of cells. These were done in the strictest conditions in an attempt to minimise contamination. Consistent with this approach it was not possible to obtain useful SEM/TEM as it would be very hard to recover EM imaging from 10’s of cells (a process that would have drastically reduced our ability to do replete genome sampling). Similarly, our approach to culturing limited our ability to acquire useful DIC images. After discovering that this ciliate uses a novel genetic code, we attempted on a number of occasions to re-isolate the same species from the same and surrounding water bodies but failed.

      2) It is unfortunate that the ciliate could not be maintained in culture (or cryopreserved). Coordinates for the University Parks pond are provided, but I got the impression that this ciliate could be repeatedly isolated. Thus, in the absence of culture methods could the authors indicate the points in the year when the ciliate could be isolated (i.e. is there a season element to when PL0344 could be isolated) and how frequently when sampling was performed could PL0344 be seen? From the environmental sequence data that is publicly available is there any evidence for the presence of PL0344 anywhere else in the world? I'd be surprised if this was a UK-specific ciliate.

      The water sample from which this ciliate was isolated was collected in April 2021. After having sequenced its genome and identifying the genetic code change, we made several attempts to reisolate it from the same pond but were unsuccessful. Regarding the geographic distribution of this ciliate, in the text we mention that the most similar 18S rRNA sequence in GenBank is to an unnamed species recovered in a metabarcoding study in France with 99.81% identity. We assume that this is the same species. We also examined other publicly available environmental datasets such as the PR2/metaPR2 database. The most similar match in the metaPR2 database was to a sequence “OLIGO4_XX_sp”. In the metaPR2 database this sequence is unique to Lake Garda in Italy (sample name: “Lake_Garda-LTER-euphotic-water”). However, this hit was only 98% identical with a partial alignment so we did not discuss it in the text. We agree that it is very unlikely that this is a UK-specific ciliate but cannot determine its geographic range based on the publicly available environmental sequence data, other than the single hit to a sequence from France. We think it is important to stress that it was not the aim of our paper to describe the taxonomy and biogeographical range of this ciliate but rather to report the exciting shift in codon usage.

      3) I felt the statistics presented on pages 13-14 (lines 277-301) for codon usage were a little superficial. It would be helpful to see how frequently other E and K codons are used in PL0344 and ideally to see how similar codon usage differs in the more model ciliates Paramecium, Tetrahymena or Stentor. To complete an analysis and justify/confirm conclusions drawn, I would also like to see how frequently in-frame, downstream stop codons are seen in ciliates where stop codons have NOT been reassigned - although the data in Fig 5 indicates genome/transcriptome sequences are not necessarily complete for many ciliate species (where stop codons are not reassigned), there is certainly more varied data to look at than when Fleming and Cavalcanti published their PLoS One work (which is cited in the manuscript).

      We have shortened this section about UAA and UAG usage, with supplementary table 3 showing usage of all codons in all genes compared to our subset of highly expressed genes.

      We have also added a sentence stating how many genes contain both in-frame UAA and UAG codons based on the point from Reviewer 1: “The reassigned codons are widely used across genes with 95.9% of genes containing both a UAA codon and a UAG codon.“

      According to our knowledge, there are no new genome assemblies available for ciliates that use the canonical genetic code since the Fleming and Cavalcanti publication from 2019, certainly not any with annotated gene sets available for comparison. The species in Fig 5 which use the canonical genetic code are all from transcriptome data (other than Stentor) that have generally low completeness. We do not think comparison with low-quality transcriptome assemblies would make a fair comparison as they would be biased towards transcripts with higher expression. Furthermore, they likely include many fragmented transcripts which are not suitable for detailed comparisons of the stop codon/3-UTR region.

      4) Given the presence of just one stop codon in PL0344 have the authors looked genome-wide at nucleotide composition 5' and 3' to UGA. The nucleotide sequences 5' and 3' to a stop can influence whether read through is and thus potentially limits the frequency of or tendency for unwanted readthrough?

      We thank the reviewer for this suggestion which is something we did not investigate initially but have now added a short section in the manuscript to address. Many studies in model organisms have demonstrated that UGA is the least robust stop codon and the most prone to read through. As the reviewer alludes to, this is particularly interesting for ciliates with reassigned genetic codes that use only UGA as a stop codon. Experimental data from model organisms have shown that the sequence composition surrounding a stop codon can influence the frequency of read through, with the nucleotide immediately downstream of the stop codon (“+4 position”) being particularly important.

      We have now looked at the sequence composition around stop codons for Oligohymenophorea sp. PL0344 and our results show that cytosine tends to be avoided following the UGA stop codon. From the literature, presence of a cytosine following UGA (i.e., UGAC) leads to a substantial increase in translational read through. Furthermore, when examining the subset of highly expressed genes, there are significantly fewer cases of UGAC when compared to all genes. This trend has previously been reported in Paramecium and Tetrahymena based on EST data (Salim, Ring and Cavalcanti; 2008).

      We have added a short section to the text reporting this and a supplementary figure showing a sequence frequency logo around the stop codon for all genes and for the subset of highly expressed genes. We are very cautious, however, that there is a paucity of experimental studies investigating stop codon robustness in ciliates. While several publications hypothesise that read through may happen at higher rates in ciliates due to a combination of factors (e.g., ERF-1 mutations, presence of tandem stop codons, competition from suppressor/near-cognate tRNA genes, etc..) we are careful not to speculate without experimental evidence.

      __Reviewer #3 (Significance (Required)): __

      Strengths - I found this a straightforward manuscript to read - aside from the interesting and unexpected observation about genetic code use in PL0344, Fig 5 draws together a lot of earlier published information into an easily accessible form - I felt this a particularly useful part of the manuscript.

      I don't feel the absence of proteomics to back up the genome/transcriptome analysis is a notable limitation - it's perhaps frustrating but it's not a limitation. However, the work does perhaps inevitably feel a little bit observational - there's not really a lot of insight or new insight into why the genetic code can be revised in some microbial eukaryotes - in contrast, for instance, to a recently published study of the aptly named Blastocrithidia nonstop. McGowan et al's manuscript, however, will be of interest and should be formally published.

      Descriptions of organisms that have tweaked the standard genetic code are not new; coupled to the limited insight into why the genetic code can be rewritten so readily in ciliates, this limits the general appeal of the work. However, the study executed is rigorous and it should be of interest to a wide variety of protistologists, evolutionary cell biologists, and researchers in the translation field.

      END reviewer 3

    2. Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Referee #3

      Evidence, reproducibility and clarity

      Summary: from genome and transcriptome sequencing of what appears to be a novel ciliate from the class Oligohymenophorea, McGowan et al provide convincing evidence of a protist in which the stop codons UAA and UAG have almost certainly been recoded to specify incorporation of different amino acids (UAA = K; UAG = E) during translation. Several ciliates from different classes use a non-standard genetic code (as do a narrow variety of other protists), but this is an unusual observation in that stop codons which differ only in the wobble position code for different amino acids in the ciliate identified here.

      I say 'almost certainly' the stop codons have been recoded in Oligohymenophorea sp. PL0344 because in the absence of being able to retain the ciliate in culture the authors have not been able to complete the proteomics which would unequivocally (a) show stop codons now code for amino acids and (b) confirm the identity of the amino acids now encoded (the authors discuss this issue on p12).

      Comments: overall this manuscript is straightforward to read and the analyses realistically taken as far as is realistic in the absence of a continuous culture method. My suggested revisions should be straightforward for the authors to address.

      1. The manuscript appears to report the identification and genome/transcriptome sequencing of a novel ciliate species - clarity should be provided by the authors. However, it disappointed me that this manuscript was crafted entirely from nucleotide sequencing. I would have welcomed seeing the morphology of the ciliate identified here and would have anticipated that there was sufficient material to perform microscopy at the light level (for DIC images) and by scanning or transmission electron microscopy.
      2. It is unfortunate that the ciliate could not be maintained in culture (or cryopreserved). Coordinates for the University Parks pond are provided, but I got the impression that this ciliate could be repeatedly isolated. Thus, in the absence of culture methods could the authors indicate the points in the year when the ciliate could be isolated (i.e. is there a season element to when PL0344 could be isolated) and how frequently when sampling was performed could PL0344 be seen? From the environmental sequence data that is publicly available is there any evidence for the presence of PL0344 anywhere else in the world? I'd be surprised if this was a UK-specific ciliate.
      3. I felt the statistics presented on pages 13-14 (lines 277-301) for codon usage were a little superficial. It would be helpful to see how frequently other E and K codons are used in PL0344 and ideally to see how similar codon usage differs in the more model ciliates Paramecium, Tetrahymena or Stentor. To complete an analysis and justify/confirm conclusions drawn, I would also like to see how frequently in-frame, downstream stop codons are seen in ciliates where stop codons have NOT been reassigned - although the data in Fig 5 indicates genome/transcriptome sequences are not necessarily complete for many ciliate species (where stop codons are not reassigned), there is certainly more varied data to look at than when Fleming and Cavalcanti published their PLoS One work (which is cited in the manuscript).
      4. Given the presence of just one stop codon in PL0344 have the authors looked genome-wide at nucleotide composition 5' and 3' to UGA. The nucleotide sequences 5' and 3' to a stop can influence whether read through is and thus potentially limits the frequency of or tendency for unwanted readthrough?

      Significance

      Strengths - I found this a straightforward manuscript to read - aside from the interesting and unexpected observation about genetic code use in PL0344, Fig 5 draws together a lot of earlier published information into an easily accessible form - I felt this a particularly useful part of the manuscript.

      I don't feel the absence of proteomics to back up the genome/transcriptome analysis is a notable limitation - it's perhaps frustrating but it's not a limitation. However, the work does perhaps inevitably feel a little bit observational - there's not really a lot of insight or new insight into why the genetic code can be revised in some microbial eukaryotes - in contrast, for instance, to a recently published study of the aptly named Blastocrithidia nonstop. McGowan et al's manuscript, however, will be of interest and should be formally published.

      Descriptions of organisms that have tweaked the standard genetic code are not new; coupled to the limited insight into why the genetic code can be rewritten so readily in cliates, this limits the general appeal of the work. However, the study executed is rigorous and it should be of interest to a wide variety of protistologists, evolutionary cell biologists, and researchers in the translation field.

    1. Reviewer #2 (Public Review):

      In this valuable manuscript Li & Jin record from the substantial nigra and dorsal striatum to identify subpopulations of neurons with activity that reflects different dynamics during action selection, and then use optogenetics in transgenic mice to selectively inhibit or excite D1- and D2- expressing spiny projection neurons in the striatum, demonstrating a causal role for each in action selection in an opposing manner. They argue that their findings cannot be explained by current models and propose a new 'triple control' model instead, with one direct and two indirect pathways. These findings will be of broad interest to neuroscientists, but lacks some direct evidence for the proposal of the new model.

      Overall there are many strengths to this manuscript including the fact that the empirical data in this manuscript is thorough and the experiments are well-designed. The model is well thought through, but I do have some remaining questions and issues with it.

      Weaknesses:<br /> 1. The nature of 'action selection' as described in this manuscript is a bit ambiguous and implies a level of cognition or choice which I'm not sure is there. It's not integral to the understanding of the paper really, but I would have liked to know whether the actions are under goal-directed/habitual or even Pavlovian control. This is not really possible to differentiate with this task as there are a number of Pavlovian cues (e.g. lever retraction interval, house light offset) that could be used to guide behavior.<br /> 2. In a similar manner, the part of the striatum that is being targeted (e.g. Figures 4E,I, and N) is dorsal, but is central with regards to the mediolateral extent. We know that the function of different striatal compartments is highly heterogeneous with regards to action selection (e.g. PMID: 16045504, 16153716, 11312310) so it would have been nice to have some data showing how specific these findings are to this particular part of dorsal striatum.<br /> 3. I'm not sure how I feel about the diagrams in Figure 4S. In particular, the co-activation model is shown with D2-SPNs represented as a + sign (which is described as "having a facilitatory effect to selection" in the caption), but the co-activation model still suggests that D2-SPNs are largely inhibitory - just of competing actions rather than directly inhibiting actions. Moreover, I am not sure about these diagrams because they appear to show that D2-SPNs far outnumbers D1-SPNs and we know that this isn't the case. I realize the diagrams are not proportionate, but it still looks a bit misrepresented to me.<br /> 4. There are a number of grammatical and syntax errors that made the manuscript difficult to understand in places.<br /> 5. I wondered if the authors had read PMID: 32001651 and 33215609 which propose a quite different interpretation of direct/indirect pathway neurons in striatum in action selection. I wonder if the authors considered how their findings might fit within this framework.<br /> 6. There is no direct evidence of two indirect pathways, although perhaps this is beyond the scope of the current manuscript and is a prediction for future studies to test.

    1. These links to these threads are priceless. Two questions: How can I connect with these Reddit users? Never mind, I’m sure I can find the answer myself. Second question - how do you keep these thread references so handy? Is this hypothes.is ? Zotero? Raindrop.io? I have no idea how to capture this kind of info and keep it accessible.

      reply to u/coachdan007 at https://www.reddit.com/r/antinet/comments/13ygoz9/comment/jn80a7z/?utm_source=reddit&utm_medium=web2x&context=3

      Mostly these references were using Hypothesis, though I do have some material in Zotero. I don't use Raindrop. IIRC, I knew I'd seen the topics before and did a search for the tag bible and then narrowed it down my adding on zettelkasten and it popped up immediately. A large number of my replies here are just querying my digital ZK and spitting out pre-packaged answers or pointers to relevant material. I also occasionally do the same thing with my analog version, though with those I have to type them out. I follow roughly the same process for doing my own queries and writing. You get surprisingly good at it after a while, particularly when you know it's in there somewhere. Of course r/ has it's own internal search function too, so you could check out: - https://www.reddit.com/r/antinet/search/?q=bible&restrict_sr=1 - https://www.reddit.com/r/Zettelkasten/search/?q=bible&restrict_sr=1

      and have a slightly wider net to get the fishes and loaves you're seeking. With the proper notes at hand, perhaps you'll soon be able to turn water into wine? Interestingly, I think you're the first who's ever asked this question here (or other related fora). I hope people don't think I spend all my time writing all these custom answers when I'm just tipping out my zettelkasten. (Though I do always keep my original answers too in the eventuality that I ever want to turn all of these thoughts into an article or book.)

    2. Thank you, Chris. I have been watching Dan Alosso's antinet book club. So, it's nice to have a face to the name. I just subscribed to your newsletter this morning from an article you wrote.This is probably not the correct place, but I'd like to learn more about your use of Hypothes.is.I think someone else mentioned a branch for each book, as well. I'll read the threads you cited. I am sure there will be some good stuff in there.@Chrisaldrich - have you heard or come across the "Encyclopedia Puritannica Project"?https://www.publishepp.com/This is kind of what I have in mind for my antinet. The ability to cross-reference authors to various topics ot themes or doctrines while also linking them to the specific verses or passages they use to make a point. AND to look up a Bible verse and see what authors in my antinet cite these verses and where. AND, lastly, to look at a theme and see which Bible verses map to that theme and which author wrote on that theme.I think the antinet is a good tool for this. Certainly not in a comprehensive way but in a way that interconnects my own studies and readings. But I suspect that I'll have to do some hard thinking over how to accomplish this.

      reply to u/coachdan007 at https://www.reddit.com/r/antinet/comments/13ygoz9/comment/jn6fwzr/?utm_source=reddit&utm_medium=web2x&context=3

      Thanks u/coachdan007. I've heard of the EPP, but never delved heavily into it. There's still a lot of digging I want to do into Edwards' Miscellanies, but I just haven't had the time, sadly. Perhaps I'll find it over the summer? While you're searching around you might also find it interesting/useful to have an interleaved bible as well to give you bigger "margins" to write in as you go. This may make some of the direct thinking on the page a bit easier. Don't think too hard about some super custom method, just start practicing something that makes sense and evolve it as you go and as you need to.

      As for Hypothesis, following my account or reading past notes may be useful/helpful. For the day to day, I've documented pieces of it along with tips and tricks over time on my site at https://boffosocko.com/tag/hypothes.is/. Some of the older posts when I was first starting out are probably more interesting as more recent ones can be sort of meta.

    1. Now, the question is not 'why do we not listen to God', but rather why do we forget. The example of Lamen and Lemuel is perfect. They not only were visited by angels (1 Neph 3:29), but also were shocked by their younger brother from God (1 Nephi 17:55). SO, let me explain through analogy from a book called Competing for the future by Gary Hamel and C. K. Prahalad (1996). In business I am very familiar with cultures that are created, and then I have to show how to break the culture and teach them a new one so that the business can thrive. The analogy I utilize to help explain to the people this concept when I come into their business without sounding condescending is about five monkeys. The analogy states: A study took 5 monkeys. In the middle of a room where these monkeys were placed to live was a ladder. On top of that ladder was some bananas. The monkeys didn't notice the bananas at first. Finally, one monkey takes notice of the bananas and decides to climb the ladder to get them. As soon as the monkey starts for the bananas, the other four monkeys are sprayed with ice cold water until they figure out that the monkey climbing the ladder is the problem. So, they push the monkey down and the cold water stops. When the same monkey tries for the bananas again, the same events takes place, and all is safe when that monkey stops climbing the ladder. The scientist remove one of the monkeys that was constantly sprayed with cold water and replaced with a new monkey. This monkey starts for the bananas and immediately, the monkeys are sprayed and the monkeys keep this new monkey off the ladder. Another monkey is removed and replaced with a new monkey. This time before the new monkey can start up the ladder, all the monkeys attack this new monkey before water can even be sprayed. This happens until all the monkeys are replaced and this continues. In the writing from the researchers, he queried that if latter monkey's could be interviewed, they would probably state that they do this because 'that is what is just done around here'. You can see this with crabs in a bucket. If one crab tries to escape from a bucket then the other crabs pull it down. When we take into consideration the power of the mind, which according to the gospel of 'me' is the opposition within man, we see that we can have a very powerful event take place in our lives, but habit/ conditioned responses are more powerful. In the story with the monkey's, this happens a lot in our everyday lives. Not because we are bad people, but because we develop heuristic pathways throughout our lives. Heuristic meaning mental shortcuts (neurological pathways that have been created and strengthened to help us make quick decisions) to help us be faster in our decision making process. Example: Hand to flame means hot after we touch it. Make a faster decision to not touch flame because it hurts next time we see it. The same thing happened with the monkey's. They developed heuristic pathways to attack the monkey that climbed the ladder because they KNEW bad thing happen. So, when we do this over time those neuro pathways become stronger, and then we choose those pathways faster. Especially when it comes to protecting oneself. So, as Brother Joseph stated that there is opposition in all things, man is no different. Our mind is that opposition to God when we are asked to do things that have already been learned behavior patterns of hurt/ pain. To Lamen and Lemuel their plush lifestyle is now gone, and they are left with pain of the wilderness to remind them of what they had, and how much they wish to go back to that. It doesn't matter the messenger, the dopamine hit they desire is more powerful and already apart of their psychological influence. Doing what God wants is showing opposition to what they have already learned. 'How can our life in Jerusalem be so bad?', is what they were asking themselves.  So, when we pit our psychological development against what God is asking, it is foreign - it hurts. What we think we are and developed over time is now met with the opposition of truth from God makes it harder to let go of strong neuro pathways. Try to ask someone to stop smoking that has done it for 20 years of their life. You have to actually die daily and be reborn again mentally to walk by God's request. Like the monkey's, you have to change your paradigm/ your world view filters. What does that mean? Well, when you have God in your life only during Sunday - but then soaked in the world's influence the six other day's - who will you more likely become? Even as he is? Or more like the world? Thus, this is the reason we are reminded to remember Him always. At the end of the day, you will forget whom you serve."
      • I love that the quote you shared from Elder Maxwell brought up the concept of crab mentality, as it more prevalent in our fallen world than we realize. Crab mentality is destructive in that its concept of unity is founded by a collective desire to be fixed to the system, which is why when a crab breaks free from this fixation, the others pull it down. This can result to both good or bad, depending on the soundness of the system. [[crab mentality]]

      • Forgetfulness is a topic that has intrigued me for quote some time now so I apologize if this is going to be lengthy. In the plan of salvation, we understand that every person who followed Jesus Christ in the Council of Heaven passes through the Veil of Forgetfulness before coming to earth. Therefore, whenever we learn something new about the gospel of Jesus Christ, we are essentially relearning or remembering this information in contrast to learning it for the first time. [[the limits of our mortality]] [[learning is remembering]]

      • The gospel of Jesus Christ is effective and efficient in that it has a workaround this Veil of Forgetfulness through the power of reminders. The Lord has the power of priesthood (which His kingdom is built upon) and all the appendix to it (the prophets, revelations, etc.), and the role of the third member of the godhead, the Holy Ghost.

      • This forgetfulness is now an intrinsic attribute to our natural man which is in domination every time we step out of the companionship of the Holy Ghost. Our spiritual man is in domination when we remember fragments of truth from the gospel of Jesus Christ. [[the natural man forgets, the spiritual man remembers]]

      • Another crucial detail is that when it comes to our shortsightedness (brought upon by our mortality), remembrance is more of a spotlight, a limited space where only a few select of things can be seen while the rest disappears into darkness. With this, we can think of forgetfulness as a fixed attribute of our natural man, but we have the ability to choose what to forget and what to remember. [[remembering is a choice]]

      • When Jesus Christ came to earth, He chose to remember His Father's will instead of himself. He looked at the world around Him and saw that the world is full of pain and suffering. Following this perspective and mission, it enabled Him to be perfected (completed). This is reminiscent of our mission here on earth: to determine what we should continually remember and let the rest blur and disappear into darkness. This is so because we have no other choice but to utilize our limited memory and perspective for eternal matters. After all, all spiritual things (this includes us; hence our spiritual man) are meant to be eternal. [[all things are spiritual because they're meant to be eternal]] [[it's important to keep an eternal perspective to navigate mortality]]

    1. One of the things that several students mentioned to do first, be-fore you even start reading, is to consider the context surrounding boththe assignment and the text you’re reading.

      In high school, I would just read to gather information but never really correlated that information to the bigger picture. In college, I find that we are constantly asked to consider or determine the context from our readings. I think it's important to stop yourself while reading to really think about what you just read and truly understand what the information is saying.

    1. Lucky people bathe in the reverie of adventure. They surround themselves with people who motivate and inspire them. People who maximize serendipity balance the humility of not knowing where their next big break will come from with the arrogance of knowing that it will come from somewhere.

      Plan ahead. And be confident in your plans. But don't insist on things panning out exactly the way you planned. It won'r happen. Review your situation. When your plans turns to shit, just ask yourself: Are you going in the direction the plan aimed you to, even though it's not exactly HOW you wanted to get there? Yes? Good, make a new plan and repeat.

    1. The artist model and the platform model are not just incompatible, but actively corrosive to one another. They cannot co-exist. I’m not arguing that one is better than the other, I’m saying that no living person will be able to do both effectively at the same time. The artist-as-platform model isn’t an evolution of the recording artist concept as we currently understand it, but a completely different proposition that would change the sound and character of popular music just as much as recordings themselves did during the “great music shift” of the fifties and sixties if it ever becomes dominant. For Vocaloid Drake to thrive, Drake the “recording artist” would almost certainly need to be destroyed. This is what advocates of “AI” are pushing for when they call for established artists to “open-source” their names, voices, and likenesses. They don’t understand how any of this works, and they don’t want to. They’re just here to break things. It’s all they know how to do.

      On the one hand this feels correct, but on the other... I dunno, there's probably some 100gecs-like angle on this that doesn't map onto a Drake

  7. mmm.brightspace.com mmm.brightspace.com
    1. Music is universal, a significant feature of everyknown culture, and a major investment of resources, and yet itdoes not serve an obvious, uncontroversial function for those whocreate it or listen to it

      I know this is like, a main argument of every scientist who studies music but I just like, don't think it's true. I think that A: more people need to accept that pleasure is a function, as much a need for humanity to thrive as food is. Also music is a form of communication, so...

    1. They ultimately conclude that school choice (presumably in the form of vouchers) is the only viable way to implement the findings from the research.

      I find this to be a bit of a shocking statement, though I suppose I see how it's realistic. It's challenging for me to not view vouchers and school choice as methods that are essentially communicating that we're okay that some kids are going to fail. But I suppose the point of this article isn't equity as much as it's that having effective schools truly matter to student performance. It would just be great if we could include ALL learners in that.

    1. Slippery Slope A slippery slope7 attempts to discredit a proposition by arguing that its acceptance will undoubtedly lead to a sequence of events, one or more of which are undesirable. Though it may be the case that the sequence of events may happen, each transition occurring with some probability, this type of argument assumes that all transitions are inevitable, all the while providing no evidence in support of that. The fallacy plays on the fears of an audience and is related to a number of other fallacies, such as the appeal to fear, the false dilemma and the argument from consequences. For example, We shouldn't allow people uncontrolled access to the Internet. The next thing you know, they will be frequenting pornographic websites and, soon enough our entire moral fabric will disintegrate and we will be reduced to animals. As is glaringly clear, no evidence is given, other than unfounded conjecture, that Internet access implies the disintegration of a society's moral fabric, while also presupposing certain things about the conduct.

      I see this all the time in rhetoric about lawmaking. "If you let kids do X, then they'll start Y and Z!" Its infuriating and has no real logical basis. It's just basic fearmongering used to get people on board with a specific agenda.

    1. Author Response:

      The following is the authors' response to the current reviews.

      Reviewer #1 (Public Review):

      This revised manuscript by Walker et. al. addresses some of the editorial points and conceptual discussion, but in general, most of my suggestions (as the previous reviewer #1) for additional experimentation or addition were not addressed as discussed below. Therefore, my overall review has not changed.

      In our previous response, we included i) extra experimental data illustrating the reproducibility of our results and ii) added transcription start site data at the request of this reviewer. We included the information because we agreed with the reviewer that these were important points to address. For the points raised again below, we explained why the additional analysis was unlikely to add much in terms of insight or rigour. We have elaborated further below.   

      1) For example, in point 1, the suggested analysis was not performed because it is not trivial. My reason for making this suggestion is that the original manuscript was limited to Vibrio cholerae, and the impact of the manuscript would increase if the findings here were demonstrated to be more broadly applicable. I expect papers published in eLife to have such broad applicability. But no changes were made to the manuscript in this regard. The revised version is still limited to only Vibrio cholerae.

      Our paper is focused on the unexpected co-operative interactions between HapR and CRP. Such co-binding of two transcription factors to the same DNA site is unexpected. Consequently, it is this mode of DNA binding that is likely to be of broad interest. With this in mind, we did provide experimental, and bioinformatic, analyses for other regulatory regions and other vibrio species (Figures S3 and S6). This, in our view, is where the “broad applicability” for papers published in eLife comes from.

      The analysis the reviewer suggests is not related to the main message of our paper. Instead, the reviewer is asking how many HapR binding sites seen here by ChIP-seq are also seen in other vibrio species by ChIP-seq. This is only likely to be of interest to readers with an extremely specific interest in both vibrio species and HapR. The reviewer states above that we did not make the change “because it is not trivial”. This is an oversimplification of the rationale we presented in our response. The analysis is indeed not straightforward. However, much more importantly, the outcome is unlikely to be of interest to many readers, and has no bearing on the rigour of work. With this in mind, we do not think our position is unreasonable. We also stress that, should a reader with this very specific interest want to explore further, all of our data are freely available for them to do so.

      2) For point 2, the activity of FLAG-tag luxO could have been simply validated in a complementation assay. Yes, they demonstrated DNA binding, but that is not the only activity of LuxO.

      DNA binding by LuxO is the only activity of the protein with which we are concerned in our paper. Furthermore, LuxO is very much a side issue; we found binding to only the known targets and potentially, at very low levels, one additional target. No further LuxO experiments were done for this reason. Indeed, even if these data were removed completely, our conclusions would not change or be supported any less vigorously. We are happy to remove the LuxO data if the reviewer would prefer but this would seem like overkill.

      3) For point 7, the transcriptional fusions were not explored at different times or different media, which is also something that was hinted at by other reviewers. In regard to exploring expression at different time points, this seems particularly relevant for QS regulated genes.

      In their previous review, the reviewer did not request that such experiments were done. Similarly, no other reviewer requested these experiments. Instead, this reviewer i) commented that lacZ fusions were not as sensitive as luciferase fusions ii) asked if we had done any time point experiments. We agreed with the first point, whilst also noting that lacZ is not unusual to use as a reporter. For the second point, we responded that we had not done such experiments (which by the reviewer’s own logic would have been complicated using lacZ as a reporter). This seems like a perfectly reasonable way to respond.   

      We should stress that these comments all refer to Figure 2a, which was our initial screening of 23 promoter::lacZ fusions, supported by separate in vitro transcription assays. Only one of these fusions was followed up as the main story in the paper. Given that the other 22 fusions were not investigated further, and do not form part of the main story, there would seem little value in now going back to assay them at different time points.

      4) For point 13, the authors express that doing an additional CHIP-Seq is outside of the scope of this manuscript. Perhaps that is the case, but the point of the comment is to validate the in vitro binding results with an in vivo binding assay. A targeted CHIP-Seq approach specifically analyzing the promoters where cooperative binding was observed in vitro could have addressed this point.

      We did appreciate the original comment, and responded as such, but we do think additional ChIP-seq assays are outside the scope of this paper.

      Reviewer #2 (Public Review):

      This manuscript by Walker et al describes an elegant study that synergizes our knowledge of virulence gene regulation of Vibrio cholerae. The work brings a new element of regulation for CRP, notably that CRP and the high density regulator HapR co-occupy the same site on the DNA but modeling predicts they occupy different faces of the DNA. The DNA binding and structural modeling work is nicely conducted and data of co-occupation are convincing. The work seeks to integrate the findings into our current state of knowledge of HapR and CRP regulated genes at the transition from the environment and infection. The strength of the paper is the nice ChIP-seq analysis and the structural modeling and the integration of their work with other studies.

      We thank the reviewer for the positive comments.

      The weakness is that it is not clear how representative these data are of multiple hapR/CRP binding sites

      This comment does not consider all data in our paper. We did test our model experimentally at multiple HapR and CRP binding sites. These data are shown in Figure S6 and confirm the co-operative interaction between HapR and CRP at 4 of a further 5 shared binding sites tested. We also used bioinformatics to show the same juxtaposition of CRP and HapR sites in other vibrio species (Figure S3). Hence, the model seems representative of most sites shared by HapR and CRP.

      or how the work integrates as a whole with the entire transcriptome that would include genes discovered by others.

      At the request of the reviewers, our revision integrated our ChIP-seq data with dRNA-seq data. No other suggestions to ingrate transcriptome data were made by the reviewers. 

      Overall this is a solid work that provides an understanding of integrated gene regulation in response to multiple environmental cues.

      We thank the reviewer for the positive comment.

      —————

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

      Reviewer #1 (Public Review):

      This manuscript by Walker et. al. explores the interplay between the global regulators HapR (the QS master high cell density (HDC) regulator) and CRP. Using ChIP-Seq, the authors find that at several sites, the HapR and CRP binding sites overlap. A detailed exploration of the murPQ promoter finds that CRP binding promotes HapR binding, which leads to repression of murPQ. The authors have a comprehensive set of experiments that paints a nice story providing a mechanistic explanation for converging global regulation.

      We thank the reviewer for their positive evaluation.

      I did feel there are some weak points though, in particular the lack of integration of previously identified transcription start sites

      For completeness, we have now added the position and orientation or the nearest TSSs to each HapR or LuxO binding peak in Table 1 (based on Papenfort et al.).

      the lack of replication (at least replication presented in the manuscript) for many figures,

      We assume that the reviewer is referring to gel images rather than any other type of assay output (were error bars, derived from replicates, are shown). As is standard, we show representative gel images. All associated DNA binding and in vitro transcription experiments have been done multiple times. Indeed, comparison between figures reveals several instances of such replication (e.g. Figures 4b & 5d, Figures 4d & 5e). We have added details of repeats done to the methods section.

      some oddities in the growth curve

      We do not know why cells lacking hapR have a growth curve that appears biphasic. We can only assume that this is due to some regulatory effect of HapR, distinct from the murQP locus. Despite the unusual shape of the growth curve, the data are consistent with our conclusions.

      and not reexamining their HapR/CRP cooperative binding model in vivo using ChIP-Seq.

      We agree that these would be interesting experiments and, in the future, we may well do such work. Even without these data, our current model is well supported by the data presented (and the reviewer seems to agree with this above).

      Reviewer #2 (Public Review):

      This manuscript by Walker et al describes an elegant study that synergizes our knowledge of virulence gene regulation of Vibrio cholerae. The work brings a new element of regulation for CRP, notably that CRP and the high density regulator HapR co-occupy the same site on the DNA but modeling predicts they occupy different faces of the DNA. The DNA binding and structural modeling work is nicely conducted and data of co-occupation are convincing. The work could benefit from doing a better job in the manuscript preparation to integrate the findings into our current state of knowledge of HapR and CRP regulated genes and to elevate the impact of the work to address how bacteria are responding to the nutritional environment. Importantly, the focus of the work is heavily based on the impact of use of GlcNAc as a carbon source when bacteria bind to chitin in the environment, but absent the impact during infection when CRP and HapR have known roles. Further, the impact on biological events controlled by HapR integration with the utilization of carbon sources (including biofilm formation) is not explored.

      We thank the reviewer for their overall positive evaluation.

      The rigor and reproducibility of the work needs to be better conveyed.

      Reviewer 1 made a similar comment (see above) and we have modified the manuscript accordingly.

      Specific comments to address:

      1)  Abstract. A comment on the impact of this work should be included in the last sentence. Specifically, how the integration of CRP with QS for gene expression under specific environments impacts the lifestyle of Vc is needed. The discussion includes comments regarding the impact of CRP regulation as a sensor of carbon source and nutrition and these could be quickly summarized as part of the abstract.

      We have added an extra sentence. However, we have used cautious language as we do not show impacts on lifestyle (beyond MurNAc utilisation) directly. These can only be inferred.

      2)  Line 74. This paper examines the overlap of HapR with CRP, but ignores entirely AphA. HapR is repressed by Qrrs (downstream of LuxO-P) while AphA is activated by Qrrs. With LuxO activating AphA, it has a significant sized "regulon" of genes turned on at low density. It seems reasonable that there is a possibility of overlap also between CRP and AphA. While doing an AphA CHIP-seq is likely outside the scope of this work, some bioinformatic or simply a visual analysis of the promoters known AphA regulated genes would be interest to comment on with speculation in the discussion and/or supplement.

      In short, everything that the reviewer suggests here has already been done and was covered in our original submission (see text towards the end of the Discussion). Also, we would like to point the referee to our earlier publication (Haycocks et al. 2019. The quorum sensing transcription factor AphA directly regulates natural competence in Vibrio cholerae. PLoS Genet. 15:e1008362).

      3)  Line 100. Accordingly with the above statement, the focus here on HapR indicates that the focus is on gene expression via LuxO and HapR, at high density. Thus the sentence should read "we sought to map the binding of LuxO and HapR of V. cholerae genome at high density".

      Note that expression of LuxO and HapR is ectopic in these experiments (i.e. uncoupled from culture density).

      4)  Line 109. The identification of minor LuxO binding site in the intergenic region between VC1142 and VC1143 raises whether there may be a previously unrecognized sRNA here. As another panel in figure S1, can you provide a map of the intergenic region showing the start codons and putative -10 to -35 sites. Is there room here for an sRNA? Is there one known from the many sRNA predictions / identifications previously done? Some additional analysis would be helpful.

      We have added an extra panel to Figure S1 showing the position of TSSs relative to the location of LuxO binding. We have altered the main text to accommodate this addition..

      5)  Line 117. This sentence states that the CHIP seq analysis in this study includes previously identified HapR regulated genes, but does not reveal that many known HapR regulated genes are absent from Table 1 and thus were missed in this study. Of 24 HapR regulated investigated by Tsou et al, only 1 is found in Table 1 of this study. A few are commented in the discussion and Figure S7. It might be useful to add a Venn Diagram to Figure 1 (and list table in supplement) for results of Tsou et al, Waters et al, Lin et al, and Nielson et al and any others). A major question is whether the trend found here for genes identified by CHIP-seq in this study hold up across the entire HapR regulon. There should also be comments in the discussion on perhaps how different methods (including growth state and carbon sources of media) may have impacted the complexity of the regulon identified by the different authors and different methods.

      We have added a list of known sites to the supplementary material (new Table S1). We were unsure what was meant by the comment “A major question is whether the trend found here for genes identified by CHIP-seq in this study hold up across the entire HapR regulon”. We have added the extra comment to the discussion re growth conditions, also noting that most previous studies relied on in vitro, rather than in vivo, DNA binding assays.

      6)  The transcription data are generally well performed. In all figures, add comments to the figure legends that the experiments are representative gels from n=# (the number of replicate experiments for the gel based assays). Statements to the rigor of the work are currently missing.

      See responses above. We have added a comment on numbers of repeats to the methods section.

      7)  Line 357-360. The demonstration of lack of growth on MurNAc is a nice for the impact of the work. However, more detailed comments are needed for M9 plus glucose for the uninformed reader to be reminded that growth in glucose is also impaired due to lack of cAMP in glucose replete conditions and thus minimal CRP is active. But why is this now dependent of hapR? A reminder also that in LB oligopeptides from tryptone are the main carbon source and thus CRP would be active.

      We find this point a little confusing and, maybe, two issues (murQP regulation, and growth in general) are being conflated. In particular, we do not understand the comment “growth in glucose is also impaired due to lack of cAMP in glucose replete conditions and thus minimal CRP is active”.

      Growth in glucose should indeed result in lower cAMP levels*, and hence less active CRP, but this does not impair growth. This is simply the cell’s strategy for using its preferred carbon source. If the reviewer were instead referring to some aspect of P_murQP_ regulation then yes, we would expect promoter activity to be lower because less active CRP would be available in the presence of glucose. The reviewer also comments “why is this now dependent of hapR?”. We assume that they are referring to some aspect of growth in minimal media with glucose. If so, the only hapR effect is the change in growth rate as cells enter mid-late log-phase (i.e. the growth curve looks somewhat biphasic). A similar effect is seen in all conditions. We do not know why this happens and can only conclude this is due to some unknown regulatory activity of HapR. Overall, the key point from these experiments is that loss if luxO, which results in constitutive hapR expression, lengthens lag phase only for growth with MurNAc as the sole carbon source.

      *Although in V. fischeri (PMID: 26062003) cAMP levels increase in the presence of glucose.

      8)  A great final experiment to demonstrate the model would have been to show co-localization of the promoter by CRP and HapR from bacteria grown in LB media but not in LB+glucose or in M9+glycerol and M9+MurNAc but not M9+glucose. This would enhance the model by linking more directly to the carbon sources (currently only indirect via growth curves)

      This is unlikely to be as straightforward as suggested. The sensitivity of CRP binding to growth conditions is not uniform across different binding sites. For instance, the CRP dependence of the E. coli melAB promoter is only evident in minimal media (PMID: 11742992) whilst the role of CRP at the acs promoter is evident in tryptone broth (PMID: 14651625). Similarly, as noted above, in Vibrio fischeri glucose causes and increase in cAMP levels. (PMID: 26062003).

      9) Discussion. Comments and model focus heavily on GlcNAc-6P but HapR has a regulator role also during late infection (high density). How does CRP co-operativity impact during the in vivo conditions?

      We really can’t answer this question with any certainty; we have not done any infection experiments in this work.

      Does the Biphasic role of CRP play a role here (PMID: 20862321)?

      Again, we cannot answer this question with any confidence as experimentation would be required. However, the suggestion is certainly plausible.

      Reviewer #3 (Public Review):

      Bacteria sense and respond to multiple signals and cues to regulate gene expression. To define the complex network of signaling that ultimately controls transcription of many genes in cells requires an understanding of how multiple signaling systems can converge to effect gene expression and ensuing bacterial behaviors. The global transcription factor CRP has been studied for decades as a regulator of genes in response to glucose availability. It's direct and indirect effects on gene expression have been documented in E. coli and other bacteria including pathogens including Vibrio cholerae. Likewise, the master regulator of quorum sensing (QS), HapR), is a well-studied transcription factor that directly controls many genes in Vibrio cholerae and other Vibrios in response to autoinducer molecules that accumulate at high cell density. By contrast, low cell density gene expression is governed by another regulator AphA. It has not yet been described how HapR and CRP may together work to directly control transcription and what genes are under such direct dual control.

      We thank the reviewer for their assessment of our work.

      Using both in vivo methods with gene fusions to lacZ and in vitro transcription assays, the authors proceed to identify the smaller subset of genes whose transcription is directly repressed (7) and activated (2) by HapR. Prior work from this group identified the direct CRP binding sites in the V. cholerae genome as well as promoters with overlapping binding sites for AphA and CRP, thus it appears a logical extension of these prior studies is to explore here promoters for potential integration of HapR and CRP. Inclusion of this rationale was not included in the introduction of CRP protein to the in vitro experiments.

      We understand the reviewer’s comment. However, the rationale for adding CRP was not that we had previously seen interplay between AphA and CRP (although this is a relevant discussion point, which we did make). Rather, we had noticed that there was an almost perfect CRP site perfectly positioned to activate PmurQP. Hence, CRP was added.

      Seven genes are found to be repressed by HapR in vivo, the promoter regions of only six are repressed in vitro with purified HapR protein alone. The authors propose and then present evidence that the seventh promoter, which controls murPQ, requires CRP to be repressed by HapR both using in vivo and vitro methods. This is a critical insight that drives the rest of the manuscripts focus. The DNase protection assay conducted supports the emerging model that both CRP and HapR bind at the same region of the murPQ promoter, but interpret is difficult due to the poor quality of the blot.

      There are areas of apparent protection at positions +1 to +15 that are not discussed, and the areas highlighted are difficult to observe with the blot provided.

      We disagree on this point. The region between +1 and +15 is inherently resistant to attack by DNAseI and there are only ever very weak bands in this region (lane 1). Other than seeing small fluctuations in overall lane intensity (e.g. lanes 7-12 have a slightly lower signal throughout) the +1 to +15 banding pattern does not change. Conversely, there are dramatic changes in the banding pattern between around -30 and -60 (again, compare lane 1 to all other lanes). That CRP and HapR bind the same region is extremely clear. Also note that this is backed up by mutagenesis of the shared binding site (Figure 4c).

      The model proposed at the end of the manuscript proposes physiological changes in cells that occur at transitions from the low to high cell density. Experiments in the paper that could strengthen this argument are incomplete. For example, in Fig. 4e it is unclear at what cell density the experiment is conducted.

      Such details have been added to the figure legends and methods section.

      The results with the wild type strain are intermediate relative to the other strains tested.

      This is correct, and exactly what we would expect to see based on our model.

      Cell density should affect the result here since HapR is produced at high density but not low density. This experiment would provide important additional insights supporting their model, by measuring activity at both cell densities and also in a luxO mutant locked at the high cell density. Conducting this experiment in conditions lacking and containing glucose would also reveal whether high glucose conditions mimicking the crp results.

      We agree with this idea in principle but note that the output from our reporter gene, β- galactosidase, is stable within cells and tends to accumulate. This is likely to obscure the reduction in expression as cells transition from low to high cell density. Since we have demonstrated the regulatory effects of HapR and CRP both in vivo using gene knockouts, and in vitro with purified proteins, we think that our overall model is very well supported. Further experimental additions may provide an incremental advance but will not alter our overall story. Also note the unexpected increase in intracellular cAMP due to addition of glucose, in Vibrio fischeri (PMID: 26062003).

      Throughout the paper it was challenging to account for the number of genes selected, the rationale for their selection, and how they were prioritized. For example, the authors acknowledged toward the end of the Results section that in their prior work, CRP and HapR binding sites were identified (line 321-22).

      This is not quite what we say, and maybe the reviewer misunderstood, which is our fault. The prior work identified CRP sites whilst the current work identified HapR sites. We have made a slight alteration to the text to avoid confusion.

      It is unclear whether the loci indicated in Table 1 all from this prior study. It would be useful to denote in this table the seven genes characterized in Figure 2 and to provide the locus tag for murPQ.

      Again, we are unsure if we have confused the reviewer. The results in Table 1 are all HapR sites from the current work, not a prior study. However, some of these also correspond to CRP binding regions found in prior work.

      The reviewer mentions “the seven genes characterised in Figure 2” but 23 targets were characterised in Figure 2a and 9 in Figure 2b. The “VC” numbers used in Figure 2 are the same as used in Table 1 so it is easy to cross reference between the two. We have added a footnote to Table 1, also referred to in the Figure 2 legend, to allow cross referencing between gene names and locus tags (including for murQP and hapR).

      Of the 32 loci shown in Table 1, five were selected for further study using EMSA (line 322), but no rationale is given for studying these five and not others in the table.

      This is not quite correct, we did not select 5 from the 32 targets listed in Table 1. We selected 5 targets from Table 1 that were also targets for CRP in our prior paper. This was the rationale.

      Since prior work identified a consensus CRP binding motif, the authors identify the DNA sequence to which HapR binds overlaps with a sequence also predicted to bind CRP. Genome analysis identified a total of seven sites where the CRP and HapR binding sites were offset by one nucleotide as see with murPQ. Lines 327-8 describe EMSA results with several of these DNA sequences but provides no data to support this statement. Are these loci in Table 1?

      This comment is a little difficult to follow, and we may have misunderstood, but we think that the reviewer is asking where the EMSA data referred to on lines 327-328 resides. We can see that the text could be confusing in this regard. We had referred to the relevant figure (Figure S6) on line 324 but did not again include this information further down in the description of the result. We have changed the text accordingly.

      Using structural models, the authors predict that HapR repression requires protein-protein interactions with CRP. Electromobility shift assays (EMSA) with purified promoter DNA, CRP and HapR (Fig 5d) and in vitro transcription using purified RNAP with these factors (Figure 5e) support this hypothesis. However, the model proports that HapR "bound tightly" and that it also had a "lower affinity" when CRP protein was used that had mutations in a putative interaction interface. These claims can be bolstered if the authors calculate the dissociation constant (Kd) value of each protein to the DNA. This provides a quantitative assessment of the binding properties of the proteins.

      The reviewer is correct that we do not explicitly provide a Kd. However, in both Figures 5d and 5e, we do provide very similar quantification. In 5d, our quantification is the % of the CRP-DNA complex bound by HapR (using either wild type or E55A CRP). Since the % of DNA bound is shown, and the protein concentrations are provided in the figure legend, information regarding Kd is essentially already present. In 5e, we show the % of maximal promoter activity. This is a reasonable way of quantifying the result. Furthermore, Kd is not a metric we can measure directly in this experiment that is not a DNA binding assay.

      The concentrations of each protein are not indicated in panels of the in vitro analysis, but only the geometric shapes denoting increasing protein levels.

      The protein concentrations are all provided in the figure legend. It is usual to indicate relative concentrations in the body of the figure using geometric shapes.

      Panel 5e appears to indicate that an intermediate level of CRP was used in the presence of HapR, which presumably coincides with levels used in lane 4, but rationale is not provided.

      There was no particular rationale for this, it was simply a reasonable way to do the experiment.

      How well the levels of protein used in vitro compare to levels observed in vivo is not mentioned.

      The protein concentrations that we use (in the nM to low μM range) are very typical for this type of work and consistent with hundreds of prior studies of protein-DNA interactions. The general rule of thumb is that 1000 molecules of a protein per bacterial cell equates to a concentration of around 1 μM. However, molecular crowding is likely to increase the effective concentration. Additionally, in vitro, where the DNA concentration is higher.

      The authors are commended for seeking to connect the in vitro and vivo results obtained under lab conditions with conditions experienced by V. cholerae in niches it may occupy, such as aquatic systems. The authors briefly review the role of MurPQ in recycling of the cell wall of V. cholerae by degrading MurNAc into GlcNAc, although no references are provided (lines 146-50). Based on this physiology and results reported, the authors propose that murPQ gene expression by these two signal transduction pathways has relevance in the environment, where Vibrios, including V. cholerae, forms biofilms on exoskeleton composed of GlcNAc.

      We have added a citation to the section mentioned.

      The conclusions of that work are supported by the Results presented but additional details in the text regarding the characteristics of the proteins used (Kd, concentrations) would strengthen the conclusions drawn. This work provides a roadmap for the methods and analysis required to develop the regulatory networks that converge to control gene expression in microbes. The study has the potential to inform beyond the sub-filed of Vibrios, QS and CRP regulation.

      As noted above, quantification essentially equivalent to Kd is already shown (% of bound substrate is indicated in figures and all protein concentrations are given in the figure legends).

      Reviewer #1 (Recommendations For The Authors):

      1.  As similar experiments have been performed in other Vibrios, it would be interesting to do a more detailed analysis of the similarities and differences between the species. Perhaps a Venn diagram showing how many targets were found in all studies versus how many are species specific.

      We appreciate this suggestion but would prefer not to make this change. A cross-species analysis would be very time consuming and is not trivial. The presence and absence of each target gene, for all combinations of organisms, would first need to be determined. Then, the presence and absence of binding signals for HapR, or its equivalent, would need to be determined taking this into account. For most readers, we feel that this analysis is unlikely to add much to the overall story. Given the amount of effort involved, this seems a “non-essential” change to make.

      2.  Line 101-Are the FLAG tagged versions of LuxO and HapR completely functional? Can they complement a luxO or hapR deletion mutant?

      The activity of FLAG tagged HapR (LuxR in other Vibrio species) has been shown previously (e.g. PMIDs 33693882 and 23839217). Similarly, N-terminal HapR tags are routinely used for affinity purification of the protein without ill effect. We have not tested LuxO-3xFLAG for “full” activity, though this fusion is clearly active for DNA binding, the only activity that we have measured here, since all know targets are pulled down.

      3.  Line 106-As the authors state later that there are additional smaller peaks for HapR that could be other direct targets, I think a brief mention of the methodology used to determine the cutoff for the 5 and 32 peaks for LuxO and HapR, respectively, would be informative here.

      We have added a little more text to the methods section. The added text states “Note that our cut- off was selected to identify only completely unambiguous binding peaks. Hence, weak or less reproducible binding signals, even if representing known targets, were excluded (see Discussion for further details)”.

      4.  Line 118-Need a reference here to the prior HapR binding site.

      This has been added.

      5.  Figs. 1e-What do the numbers on the x-axis refer to? Why not just present these data as bases? The authors also refer to distance to the nearest start codon, but this is irrelevant for 4/5 of the luxO targets as they are sRNAs. They should really refer to the distance to the transcription start site. Likewise, for HapR, distance to the nearest start codon is not as informative as distance to the nearest transcription start site. A recent paper used transcriptomics to map all the transcription start sites of V. cholerae, and these results should be integrated into the author's study rather than just using the nearest start codon (PMID: 25646441).

      The numbers are kilo base pairs, this has been added to the axis label. We have also changed “start codon” to “gene start” (since “gene start” is also suitable for genes that encode untranslated RNAs).

      Re comparing binding peak positions to transcription start sites (TSSs) rather than gene starts, this analysis would be useful if TSSs could be detected for all genes. However, some genes are not expressed under the conditions tested by PMID: 25646441, so no TSS is found. Consequently, for HapR or LuxO bound at such locations, we would not be able to calculate a meaningful position relative to the TSS. We stress that the point of the analysis is to determine how peaks are positioned with respect to genes (i.e. that sites cluster near gene 5’ ends). Also note that nearest TSSs are now shown in the revised Table 1. In some cases, these are unlikely to be the TSS actually subject to regulation (e.g. because the regulated gene is switched off).

      6.  Fig. 1e-Is there directionality to the site? In other words, if a HapR binding site is located between two genes that are transcribed in opposite directions, is there a way to predict which gene is regulated? It looks like this might be the case with the list presented in Table 1, but how such determination is made and what the various symbol in Table 1 mean are not clear to me. This also has ramifications for Fig. 2a as the direction to construct the fusion is critical for the experiment.

      The site is a palindrome so lacks directionality. The best prediction re regulation is likely to be positioning with respect to the nearest TSS (which is now included in Table 1). However, this would remain just a prediction and, where TSSs are in odd locations with respect to binding sites (taking into account the caveats above) predictions would be unreliable.

      We are unsure which symbol the reviewer refers to in Table 1, a full explanation of any symbols used is provided in the table footnotes.

      With respect to Figure 2a, if sites were between divergent genes, and met our other criteria, we tested for regulation in both directions. For example, see the divergent genes VCA0662 (classified inactive) and VCA0663 (classified repressed).

      7.  Fig. 2a-It is a little disappointing that the authors use LacZ fusions to measure transcription as this is not the most sensitive reporter gene. Luciferase gene fusions would have been much more sensitive. Also, did the authors examine multiple time points. The methods only describe "mid-log phase" but some of the inactive promoters could be expressed at other time points. Also, it would be simple to repeat this experiment in different media, such as minimal with glucose or another non- CRP carbon source, to expand which promoters are expressed.

      The reviewer is correct regarding the sensitivity of β-galactosidase, which is very stable and so accumulates as cells grow. Even so, this reporter has been used very successfully, across thousands of studies, for decades. We did not examine multiple timepoints. We appreciate that the 23 promoter::lacZ fusions could be re-examined using varying growth conditions but this is unlikely to impact the overall conclusions, though it could generate some new leads for future work.

      8.  Fig. 2a legend-typos

      This has been corrected.

      9.  Line 138-I think you mean Fig. 2a here.

      This has been corrected.

      10.  Fig. 2b and many additional figures quantify band intensity but do not show any replication or error. Therefore, it is impossible to gauge reproducibility of these experiments.

      We have added a reproducibility statement (all experiments were done multiple times with similar results) as is standard throughout the literature. Also note that there is a lot of internal replication between figures. Figure 4d and Figure 5e lanes 1-9 show essentially the same experiment (albeit with slightly different protein concentrations) and very similar results. To the same effect, Figure 5e lanes 10-18 and lanes 19-27 show the same experiment for two different mutations of the same CRP residue. Again, the results are very similar. Also see the response to your comment 15 below.

      11.  Fig. 4a-lanes 2-4-the footprint does not change with additional CRP. In other words, it looks the same at the lowest concentration of CRP versus the highest concentration of CRP. The footprints for HapR look similar. This is somewhat troubling as in these types of experiments one would like to observe a dose dependent change in the footprint correlating with more DNA occupancy.

      For CRP we agree but are not concerned at all by this. The site is simply full occupied at the lowest protein concentration tested. Given that the footprint exactly coincides with a near consensus CRP site (which, when mutated, abolishes CRP binding in EMSAs, and regulation by CRP in vivo) all our results are perfectly consistent. Note that i) our only aim in this experiment was to determine the positions of CRP and HapR binding ii) our conclusions are independently backed up using gel shifts and by making promoter mutations. With respect to HapR, there are changes at the periphery of the main footprint.

      12.  Fig. 4e-Why does the transcriptional activation of murQP decrease with increasing concentrations of CRP? This is also seen in Fig. 5e.

      In our experience, this often does happen when doing in vitro transcription assays (with CRP and many other activators). The anecdotal explanation is that, at higher concentrations, the regulator can start to bind the DNA non-specifically and so interfere with transcription.

      13. The authors demonstrate in vitro that HapR requires binding of CRP to bind the murQP promoter. It would strengthen their model if they demonstrated this in vivo. To do this, the authors only need to repeat their ChIP-Seq experiment in a delta CRP mutant and the HapR signal at murQP would be lost. In fact, such an experiment would experimentally confirm which of the in vivo HapR binding sites are CRP dependent.

      We agree, appreciate the comment, and do plan to do such experiments in the future as a wider assessment of interactions between transcription factors. However, doing this does have substantial time and resource implications that we cannot devote to the project at present. We feel that our overall conclusions, regarding co-operative interactions between HapR and CRP at PmurQP, are well supported by the data already provided. This also seems the overall opinion of the reviewers.

      14.  Fig. 5b-I am confused by the Venn diagram. The text states that "In all cases, the CRP and HapR targets were offset by 1 bp", but the diagram only shows 7 overlapping sites. The authors need to better describe these data.

      We mean that, in all cases where sites overlap, sites are offset by 1 bp (i.e. we didn’t find any sites

      overlapping but offset by 2, 3 4 bp etc).

      15. Line 287-288 and Fig. 5d-The authors state that HapR binds with less affinity to the CRP E55A mutant protein bound to DNA. There does seem to be a difference in the amount of shifted bands at the equivalent concentrations of HapR, but the difference is subtle. In order to make such a conclusion, the authors should show replication of the data and calculate the variability in the results. The authors should also use these data to determine the actual binding affinities of HapR to WT and the E55A mutant CRP, along with error or confidence intervals.

      All of these experiments have been run multiple times and we are absolutely confident of the result. With respect to Figure 5d, this was done many times. We note that not all experiments were exact repeats. E.g. some of the first attempts had fewer HapR concentrations. Even so, the defect in HapR binding to the CRP E55A complex was always evident. The two gels to the left show the final two iterations of this experiment (these are exact repeats). The top image is that shown in Figure 5d. The lower image is an equivalent experiment run a day or so previously. Both clearly show a defect in HapR binding to the CRP E55A complex. We appreciate that our conclusion re these experiments is somewhat qualitative (i.e. that HapR binds the CRP E55A complex less readily) but this is not out of kilter with the vast majority of similar literature and our results are clearly reproducible.

      16.  Fig. 6a-It is odd that the locked low cell density mutants have such a growth defect in MurNAc, minimal glucose, and LB. To my knowledge, such a growth defect is not common with these strains. Perhaps this has to do with the specific growth conditions used here, but I can't find that information in the manuscript (it should be there). Furthermore, the growth rate of the luxO and hapR mutants appears to be similar up to the branch point (i.e. slope of the curve), but the lag phage of the luxO mutant is much longer. The authors need to address these issues in relationship to previous published literature and specify their growth conditions because the results are not consistent with their simple model described in Fig 6b.

      This comment is a little difficult to pick apart as it covers several different issues. We’ll try and

      answer these individually.

      a)     The unusual “biphasic growth curve with hapR and hapRluxO cells: We do not know why cells lacking hapR have a growth curve that appears biphasic. We can only assume that this is due to some regulatory effect of HapR, distinct from the murQP locus. Despite the unusual shape of the growth curve, the data are consistent with our conclusions.

      b)     The extended lag phase of the luxO mutant in minimal media + MurNAc: We appreciate this comment and had considered possible explanations prior to submission. In the end, we left out this speculation but are happy to include it as part of our response. The extended lag phase might be expected if CRP/HapR regulation is largely critical for controlling the basal transcription of murQP. The locus is likely also regulated by the upstream repressor MurR (VC0204) as in E. coli. So, if deprepression of MurR overwhelms the effect of HapR on murQP, we think you would expect that once the cells start growing on MurNAc, the growth rates are unchanged. But the extended lag is due to the fact that it took longer for those cells to achieve the critical threshold of intracellular MurNAc-6-P necessary to drive murR derepression. Obviously, we can not provide a definitive answer.

      c)     We have added further details regarding growth conditions to the methods section and the Figure 6a legend.

      17.  Fig. S6-The data to this point with murPQ suggested a model in which CRP binding then enabled HapR binding. But these EMSA suggest that both situations occur as in some cases, such as VCA0691, HapR binding promotes CRP binding. How does such a result fit with the structural model presented in Fig. 5?

      This is to be expected and is fully consistent with the model. Cooperativity is a two-way street, and each protein will stabilise binding of the other. Clearly, it will not always be the case that the shared DNA site will have a higher affinity for CRP than HapR (as at PmurQP). Depending on the shared site sequence, expected that sometimes HapR will bind “first” and then stabilise binding of CRP.

      18. Line 354-356-The HCD state of V. cholerae occurs in mid-exponential phase and several cell divisions occur before stationary phase and the cessation of growth, at least in normal laboratory conditions. Therefore, there is not support for the argument that QS is a mechanism to redirect cell wall components at HCD because cell wall synthesis is no longer needed.

      We did not intent to suggest cell wall synthesis is not needed at all, rather that there is a reduced need. We made a slight change to the discussion to reflect this.

      19. Line 357-360-Again, as stated in point 16, the statement that cells locked in the HCD are "defective for growth" is an oversimplification. The luxO mutants have a longer lag phage, but they actually outgrow the hapR mutants at higher cell densities and reach the maximum yield much faster.

      In fairness, we do go on to specify that the defect is an extended lag phase. Also see our response above.

      Reviewer #2 (Recommendations For The Authors):

      Comments to improve the text

      1)  Line 103-106, line 130, line 136, etc. Details of the methods and the text directing to presentations of figures should be in the methods and/or figure legends with (Figure x) in citation after the statement. The sentences in lines indicated can be deleted from the results. Although several lines are noted specifically here, this comment should be applied throughout the entire results section.

      We appreciate this comment but would prefer not to make this change (it seems mainly an issue of personal stylistic choice). It is sometimes helpful for the reader to include such information as it avoids them having to cross reference between different parts of the manuscript.

      2)  Line 115. Recommend a paragraph between content on LuxO and HapR (before "Of the 32 peaks for HapR binding")

      We agree and have made this change.

      3)  Line 138 and Figure 1a. I am not convinced this gel shows that VC1375 is activated by HapR. Is the arrow pointing to the wrong band? There does seem to be an induced band lower down.

      We understand this comment as it is a little difficult to see the induced band. This is because this is a compressed area of the gel and the transcript is near to an additional band.

      4)  Line 147. Add the VC0206-VC0207 next to murQP (and the gene name murQP into Table 1).

      We have added the gene name to the figure foot note. The text has been changed as requested.

      5) Methods. It is essential for this paper to have detailed methods on the bacterial growth conditions. Referring to prior paper, bacteria were grown in LB (add composition...is this high salt LB often used for vibrios or low salt LB often used for E. coli). Growth is to "mid log". Please provide the OD at collection. Is mid log really considered "high density". Provide a reference regarding HapR activity at mid log to support the method. Could the earlier collection of bacteria account for missing known HapR regulated genes? In preparing the requested ç, include growth conditions for other experiments in the legends.

      Note that we have included a new supplementary table, rather than a Venn diagram. We have also added further details of growth conditions as mentioned above. Also not that, for the ChIP-seq, HapR and LuxO were expressed ectopically and so uncoupled from the switch between low and high cell density.

      6)  Content of Table 1, HapR Chip-seq peaks, needs to be closely double checked to the collected data as there seems to be some errors. Specifically, VC0880 and VC0882 listed under Chromosome I are most likely VCA0880 (MakD) and VCA0882 (MakB), both known HapR induced genes on Chromosome II with VCA0880 previously validated by EMSA. This notable error suggests the table may have other errors and thus requires a very detailed check to assure its accuracy.

      We appreciate the attention to detail! We have double checked, thankfully this is not an error, the table is correct (even so, we have also checked all other entries in the table). As an aside, VCA0880 is one of the locations for which we see a weak HapR binding signal below our cut-off (included in the new Table S1). In cross checking between Table 1 and all other data in the paper we noticed that we had erroneously included assay data for VC0620 in Figure 2A. This was not one of our ChIP-seq targets but had been assayed at the same time several years ago. This datapoint, which wasn’t related to any other part of the manuscript, has been removed.

      If VCA0880 and VCA0882 are correctly placed on Chr. I, then add comment to text that the Mak toxin genomic island found on Chromosome II in N16961 is on Chr. I in E7946. (See recent references PMID: 30271941, 35435721, 36194176, 34799450).

      See above, this is not an error.

      7)  Alternatively for both comments 8 & 9, are these problems of present/missing genes or misannotations the result of the annotation of E7946 gene names not aligning with gene names of N16961? (if so, in Table 1, please give the gene name as in E7946 but include a separate column with the N16961 name for cross study comparison)

      See above and below, this is not an issue.

      8)  Line 126-127. Also regarding Table 1, please add a column with function gene annotation. For example, VC0916 needs to be identified as vpsU. If function is unknown, type unknown in the column. This will help validate the approach of selecting "HapR target promoters where adjacent coding sequence could be used to predict protein function."

      We added an extra column to Table 1 in response to a separate reviewer request (TSS locations). This leaves no space for any additional columns. Instead, to accommodate the reviewer’s request, we have added alternative gene names to the footnote.

      Not following up on VCA0880 (promoter for the mak operon) is a sad missed opportunity here as it is one of the most strongly upregulated genes by HapR (PMC2677876)

      As noted above, this was not an error and VCA0880 was not one of our 32 HapR targets. As such, we would not have followed this up.

      9)  Figure Legends. Add a unit to the bar graphs in Figure 1e (should be kb??) This has been corrected.

      10) The yellow color text labels in figures 3c, 4a, 4c are difficult to read. Can you use an alternative darker color for CRP.

      We have made this slightly darker (although to our eye it is easily reliable). We haven’t changed the colour too much, for consistency with colour coding elsewhere.

      11) Figure S3. Binding is misspelled. Add units to the x-axis

      This has been corrected.

      12) Figure S7. The text in this figure is too small to read. Figure could be enlarged to full page or text enlarged. Are these 4 the only other known regulated promoters? Could all the known alternative promoters linked to HapR be similarly probed?

      We have increased the font size and included a new Table S1 for all previously proposed HapR sites.

      13) Figure S8. Original images..are any of these the replicate gels (see public comment 6)

      We have added a statement regarding reproducibility, and also note the internal reproducibility between different figures in our reviewer response. The gels in Figure S8 are full uncropped versions of those shown in the main figures.

      Reviewer #3 (Recommendations For The Authors):

      None

      Whilst there were no specific recommendations from this reviewer, we have still responded to the public review and made changes if required.

    1. I have read that a Maincard's Keyword usually is not a word that is used in the thought that you wrote on the card.

      reply to u/drogers8 at https://www.reddit.com/r/antinet/comments/13wlfbs/how_to_select_a_keyword_for_your_main_card/

      I'm don't think I've ever seen that advice anywhere in my own reading. I've been doing this for ages and would suggest that it's actively bad advice. Use a keyword that seems useful, beneficial, and which you're likely to have the most interest in in the future. What do you suspect the future you will use to search for that card or a branch on that idea in the future? Use that.

      Also, don't overthink this stuff. Just practice. You're going to make some mistakes, but with a small number of cards you'll start to figure it out on your own before things get too large. Your practice today is not going to look like your practice in 6 months and it'll change again 6 months after that.

  8. May 2023
    1. Though I do feel like generative AI will mean that decoration, ornament and filigree becomes cheap again? And maybe we’ll move into an aesthetic in which our furniture, white goods, and accessories superficially resemble the busy-busy arts and crafts era - but actually it’s because, well, it costs almost nothing to do (it’s just software) and it makes the object look NEW.

      I think this misunderstands how cheap they are right now, pre-AI, and why they're forgone anyway

    1. The dynamic fluidity of thought is mummified, reduced to a dead static statement to be evaluated numerically.But your thoughts need not be this way. Your opinions don’t have to be announced at all times, for they change constantly. Oftentimes it’s common to not have an opinion at all, much less codify it into stone for others to judge you by. When life makes you laugh, it is important to first laugh before trying to envision the Tweet that would cause you to accurately imagine what you just experienced.

      something something oral vs. written, set up an auto deleter, these kids these days taking cameras on their vacations

    1. Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Dear Editor and reviewers,

      Thank you very much for the thorough assessment of our manuscript. We have carefully considered the comments and reflected most of them in the new version. We recognized the need to shorten and clarify the manuscript. Therefore, we have omitted particularly the less important passages concerning metabolism and the loss of genes encoding mitochondrial proteins, which cut the text by six pages in the current layout. We have also removed the text relating this model to eukaryogenesis. Finally, we have slightly changed the structure and linked the different sections to improve the flow of the story and to emphasize the key messages, which are the absence of mitochondria in a large proportion of oxymonads and the impact of this loss, loss of Golgi stacking and transformation to endobiotic lifestyle on selected gene inventories. We hope the manuscript is now clear and more concise and will be of interest to a broad readership interested in the evolution of eukaryotes, mitochondria and protists.

      1. Point-by-point description of the revisions

      Reviewer #1 (Evidence, reproducibility and clarity):

      This is a very interesting paper that investigates through detailed comparative genomics the tempo and mode of the evolution of microbial eukaryotes/protists members of the Metamonada with a focus on Preaxostyla, currently the only known lineage among eukaryotes to have species that have lost, by all accounts, the mitochondria organelle all together. Notably, it includes a free-living representative of the lineage allowing potential interesting comparison between lifestyles among the Preaxostyla. This is a generally nicely crafted manuscript that presents well supported conclusions based on good quality genome sequence assemblies and careful annotations. The manuscript presents in particular (i) additional evidence for the common role of LGT from various bacterial sources into eukaryotic lineages and (ii) more details on the transition from a free-living lifestyle to an endobiotic one and (iii) the related evolution of MROs and associated metabolism.

      Thank you very much for the positive assessment.

      I have some comments to improve a few details:

      In the introduction, lines 42-43, the last sentence should be more conservative by replacing "whole Oxymonadida" with "...all known/investigated Oxymonadida".

      The sentence has been changed to: "Our results provide insights into the metabolic and endomembrane evolution, but most strikingly the data confirm the complete loss of mitochondria and every protein that has ever participated in the mitochondrion function for all three oxymonad species (M. exilis, B. nauphoetae, and Streblomastix strix) extending the amitochondriate status to all investigated Oxymonadida."

      Similarly on line 62, the sentence could state "... contain 140 described...".

      The sentence has been changed to: "Oxymonadida contain approximately 140 described species of morphologically divergent and diverse flagellates exclusively inhabiting digestive tracts of metazoans, of which none has been shown to possess a mitochondrion by cytological investigations (Hampl 2017)."

      When discussing the estimated completeness of the genome are discussed (lines 117-120) and contrasted with the values for Trypanosoma brucei and other genomes, the author should explicitly state that these genomes are considered complete, which seems is what they imply, is that the case? If so, please provide more details to support this idea.

      We have elaborated on this part also in reaction to comments of other reviewers. The text now reads: "It should be noted that, despite their wide usage, BUSCO values are not expected to reach 100% in lineages distant from model eukaryotes simply due to the true absence (or high sequence divergence) of some of the assessed marker genes. For example, various Euglenozoa representatives with highly complete genome sequences, including Trypanosoma brucei, have BUSCO completeness estimates in the range of 71-88% (Butenko et al. 2020), and representatives of Metamonada fall within the range of 60-91% (Salas-Leiva et al. 2021). Specifically in the case of oxymonad M. exilis, the improvement of the genome assembly using long-read resequencing from 2092 scaffolds to 101 contigs led to only a marginal increase of BUSCO value from 75.3 to 77.5 (Treitli et al. 2021). "

      Also please see the detailed table prepared in response to reviewers 2 and 3 summarizing the presence/absence of genes from BUSCO set in the selected representatives of Metamonada and Trypanosoma brucei. The table is commented in the answer to Reviewer 3 comment (page 18)

      The supplementary file named "132671_0_supp_2540708_rmsn23" is listed as a Table SX? (note: I found it rather difficult to establish exactly what file corresponds to what document referred in the main text)

      We apologize for this mistake. We have checked and corrected references to tables, figures and supplementary material throughout the manuscript and hope it now does not contain any errors.

      Lines 243-245, where 46 LGTs are discussed, it is relevant that the authors investigate their functional annotations. Indeed, it is suggested that these could have adaptive values, hence investigating their functional annotation will allow the authors to comment on this possibility in more details and precision. When discussing LGTs it would also be very useful to cite relevant reviews on the topic - covering their origins, functional relevance when known, distribution among eukaryotes. This is done when discussing the evolution and characteristics of MROs but not when discussing LGTs, with several reviews cited and integrated in the discussion of the data and their interpretation.

      Available annotations of all putative LGT genes are provided in Supplementary_file_3 and also in the Supplementary_file_6 if the gene belongs to a manually annotated cellular system. Although we agree with the reviewer that the discussion of 46 species-specific LGTs might be interesting, for the sake of conciseness and brevity of the manuscript, we have decided not to expand the discussion further. However, note that we discuss selected cases of P. pyriformis-specific LGTs in the part “P. pyriformis possesses unexpected metabolic capacities” which follows right after the lines reviewer is referring to.

      The sentence, lines 263-265, where the distribution of some LGTs are discussed, needs to be made more precise. When using the work "close" the authors presumably refer to shared/similar habitat,s or else? Entamoeba is not a close relative to the other listed taxa.

      The “close relatives” mentioned in the text were meant as close relatives of all p-cresol-synthesizing taxa discussed in the paragraph, including Mastigamoeba, i.e. a specific relative of Entamoeba. We have modified the text such as to make the intended meaning easier to follow.

      Lines 346-348, that sentence needs to end with a citation (e.g. Carlton et al. 2007).

      The citation proposed by the reviewer has been added. The sentence was changed to: " The most gene-rich group of membrane transporters identified in Preaxostyla is the ATP-binding cassette (ABC) superfamily represented by MRP and pATPase families, just like in T. vaginalis (Carlton et al. 2007). "

      In the paragraph (line 580-585) discussing ATP transporters, note that Major et al. (2017) did not describes NTTs but distantly related members of MSF transporter, shared across a broader range of organisms then the NTTs. Did the authors check if the genome of interest encoded homologues of these transporters too?

      The citation has been removed; we admit that it was not the most appropriate one in the given

      context. Concerning the NTT-like transporters, encouraged by the reviewer we searched for them in the Preaxostyla genome and transcriptome assemblies and found no candidates. This is not explicitly stated in the revised manuscript. The paragraph now reads: “MROs export or import ATP and other metabolites typically using transporters from the mitochondrial carrier family (MCF) or sporadically by the bacterial-type (NTT-like) nucleotide transporters (Tsaousis et al. 2008). We did not identify any homolog of genes encoding proteins from these two families in any of the three oxymonads investigated. In contrast, MCF carriers, but not NTT-like nucleotide transporters, were recovered in the number of four for each P. pyriformis and T. marina (Supplementary file 6).

      Line 920-921, I don't understand how the number 30 relates to "guarantee" inferring the directionality of LGTs events. This will be very much dataset dependent, 100 sequences might still not allow to infer directionality of LGT events. The authors probably meant to "increase the possibility to infer directionality".

      We agree the original wording has not been particularly fortunate, so the sentence has changed to: "Files with 30 sequences or fewer were discarded, as the chance directionality of the transfer can be determined with any confidence is low when the gene family is represented by a small number of representatives."

      Reviewer #2 (Evidence, reproducibility and clarity):

      Using draft genome sequencing of the free-living Paratrimastix pyriformis and the sister lineage oxymonad Blattamonas nauphoetae, Novack et al. infer the metabolic potential of the two protists using comparative genomics. The authors conclude that the common oxymonad ancestor lost the mitochondrion/mitosome and discuss general strategies for adapting to commensal/symbiotic life-style employed by this taxon. Some elaborations on pathways go on for several paragraphs and feel unnecessarily stretched, which made those sections of the paper rather difficult to digest.

      Having seen reflections on the manuscript by three reviewers we carefully reconsidered its content and attempted to make it shorter and more compact by removing some of the less substantial material. Namely, we have dispensed completely with the original last section of Results and Discussion (“No evidence for subcellular retargeting of ancestral mitochondrial proteins in oxymonads”) and made various cuts throughout other sections. We hope that the revised version makes a substantially better job of delivering the key messages of our study to the readers compared to the original submission.

      This might be also be because the work, and all conclusions drawn, depend entirely on incomplete (ca. 70-80%) genome data and simple similarity searches, and e.g. no kind of biochemistry or imaging is presented to underpin the manuscripts discussion.

      This is a very crude and superficial assessment of our data. We have actually good reasons to believe that the genome assemblies are close to complete. Please see the discussion on this topic below and an answer to a particular comment from reviewer 3 (page 18).

      This is noteworthy in light of other protist genome reports published in the last few years that differ in this respect, including previous work by this group. And for sequencing-only data, this paper - https://doi.org/10.1016/j.dib.2023.108990 - might offer an example of where we are at in 2023.

      Frankly, we do not think it is fair or relevant to compare our study to the paper pointed to by the reviewer, as that paper reports on a metagenomic study that delivers a set of metagenomically assembled genomes (MAGs) of varying quality retrieved from environmental DNA samples without providing any in-depth analysis of the gene content. Our study is very different in its scope and aims, and we are not certain what lesson we should take from this reviewer’s point. We have good reasons to believe that the datasets are close to complete. Please see the discussion on this topic below and answer to comment of reviewer 3 (page 18).

      With respect to previous work of the group (Karnkowska et al. 2016 and 2019), this submission is very similar (analysis pattern, even some figures and more or less the conclusion), i.e. to say, the overall progress for the broader audience is rather incremental. Then there are also some incidents, where the data presented conflicts with the author‘s own interpretation.

      It was our intention to use the previous analytical experiences and approaches, which at the same time makes the new results comparable with those published before. Although the format is intentionally similar, this work is a substantial step forward because only with our present study the amitochondrial status of the large part of Oxymonadida group can be considered solidly established. This in turn allows us to estimate the timing of the loss of mitochondrion (more than 100 MYA) demonstrating that the absence of mitochondrion in this group is not an episodic transient state but a long-established status. We do not understand what exactly the reviewer had in mind when pointing to “incidents, where the data presented conflicts with the author‘s own interpretation” – we are not aware of such cases.

      The text (including spelling and grammar) needs some attention and the choice of words is sometimes awkward. The overuse of quotation marks ("classical", "simple", "fused", "hits", "candidate") is confusing (e.g. was the BLAST result a hit or a "hit").

      The whole text has been carefully checked and the language corrected whenever necessary by a one of the co-authors, who is a native English speaker. The use of quotation marks has been restricted as per the reviewer’s recommendation.

      In its current formn the manuscript is, unfortunately, very difficult to review. This reviewer had to make considerable efforts to go through this very large manuscript, mainly because of issues affecting to the presentation and the lack of clarity and conciseness of the text. It would be greatly appreciated if the authors would make more efforts upfront, before submission, to make their work more easily accessible both to readers and facilitate the task of the reviewers.

      We admit that the story we are trying to tell is a complex one, consisting of multiple pieces whose integration into a coherent whole is a challenging task. As stated above, the reports provided by the reviewers provided us with an important stimulus, leading us to substantially modify the manuscript to make it more concise, less ambiguous when it comes to particular claims, and easier to read. We hope this intention has been fulfilled to a larger degree.

      About a fifth of the two genome is missing according the authors prediction (table 1). Early on they explain the (estimated) incompleteness of the genomes to be a result from core genes being highly divergent. In light of this already suspected high divergence, using (the simplest NCBI) sequence similarity approach to call out the absence of proteins (for any given lineage) may need lineage-specific optimization. The use of more structural motif-guided approaches such as hidden Markov models could help, but it is not clear whether it was used throughout or only for the search for (missing) mitochondrial import and maturation machinery. The authors state that the low completeness numbers are common among protists, which, if true, raises several questions: how useful are then such tools/estimates to begin with and does this then not render some core conclusions problematic? The reader is just left with this speculation in the absence of any plausible explanation except for some references on other species for which, again, no context is provided. Do they have similar issues such as GC-content, same core genes missing, phylogenetic relevance?, etc.. No info is provided, the reader is expected to simply accept this as a fact and then also accept the fact that despite this flaw, all conclusions of the paper that rests on the presence/absence of genes are fine. This is all odd and further skews the interpretations and the comparative nature of the paper.

      The question of the completeness of the data sets was raised also by reviewer 3 and we would like to provide an explanation at this point. First, it should be stated that there is no ideal and objective way how to measure the completeness of the eukaryotic genomic assembly. In the manuscript, we have used the best established method, adopted by the community at large, which is based on the search for a set of „core eukaryotic genes“ using a standardized pipeline BUSCO or previously popular CEGMA. The pipeline uses its own tools to identify the homologues of genes/proteins which ensures standardization of the procedure. This answers the question of reviewer 2, why we have not used more sensitive tools for these searches. We did not use them, because we followed the procedure that is the gold standard for such assessments, for comparability with other genomes and to make this as clear to the reader as possible. Although the result of the pipeline is usually interpreted as the completeness of the assembly, this is a simplification. Strictly speaking, the result is a percentage of the genes from the set of 303 core eukaryotic genes (in our case) which were detected in the assembly by the pipeline. Even in complete assemblies, the value is usually below 100% because some of the genes are not present in the organism and some diverged beyond recognition. We do not see any other way how to deal with this drawback than to compare with related complete genome assemblies acting as standards. This we have done in Supplementary file 11, where we list the presence/absence of each gene for Preaxostyla species and three highly complete assemblies of Trypanosoma brucei, Giardia intestinalis and Trichomonas vaginalis. T. brucei and G. intestinalis are assembled into chromosomes. As you can see, in these three „standards“ 63, 148 and 77 genes from the core were not detected resulting in BUSCO completeness values of 79%, 51% and 75%, respectively. 18 of the non-detected genes function in mitochondria (shown in red), which are highly reduced in some of these species, so the absence of the respective genes is therefore expected. Simply not considering these genes would increase the “completeness measure” for oxymonads by 6%. The values for our standards are not higher than the values for Preaxostyla (69-82%). In summary, the BUSCO incompleteness measure is far from ideal, particularly in these obscure groups of eukaryotes. The values received for Preaxostyla give no reason for concern about their incompleteness. See also our answer to reviewer 3 (page 18).

      At the same time, we admit that the BUSCO values do not confirm the high completeness of our assemblies. So, why do we think they are highly complete? One reason is that we do not see suspicious gaps in any of the many pathways which we annotated but the main reason is the high contiguity of the assemblies. Thanks to Nanopore long read sequencing, the assembly of P. pyriformis and B. nauphoetae compose of 633 and 879 scaffolds, suggesting that there are “only” hundreds of gaps. Although this may still sound too much, it is a relatively good achievement for genomes of this size and the experience shows that a further decrease in the number of scaffolds would allow the detection of additional genes but not in huge numbers. As we have shown for M. exilis (Treitli et al. 2021, doi:10.1099/mgen.0.000745) the decrease from 2 092 scaffolds to 101 contigs, i.e., filling almost 2 000 gaps, allowed the prediction of additional 1 829 complete gene models, of which 1 714 were already present in the previous assembly but only partially and just 115 were completely new. None of these newly predicted genes was functionally related to the mitochondrion. Thus, we infer the chance that all mitochondrion-related genes are hidden in the gaps of assemblies is very low.

      We have provided these arguments in a condensed form in the text following the description of genome assemblies: “It should be noted that, despite their wide usage, BUSCO values are not expected to reach 100% in lineages distant from model eukaryotes simply due to the true absence (or high sequence divergence) of some of the assessed marker genes. For example, various Euglenozoa representatives with highly complete genome sequences, including Trypanosoma brucei, have BUSCO completeness estimates in the range of 71-88% (Butenko et al. 2020), and representatives of Metamonada fall within the range of 60-91% (Salas-Leiva et al. 2021). Specifically in the case of oxymonad M. exilis, the improvement of the genome assembly using long-read resequencing from 2092 scaffolds to 101 contigs led to only a marginal increase of BUSCO value from 75.3 to 77.5 (Treitli et al. 2021).

      As a side note, this will also influence the number of proteins absent in other lineages and as such has consequences on LGT calls versus de novo invention. For the cases with LGT as an explanation, it would help to briefly discuss the candidate donors and some details of the proteins in the eco-physiological context (e.g. lines 263-268 suggest that HPAD may have been acquired by EGT which was facilitated by a shared anaerobic habitat and also comment on adaptive values for acquiring this gene). Exchanging metabolic genes via LGT (Line 163) blurs the differences between roles and extent of LGT in prokaryote vs eukaryote, and therefore is exciting and could use support/arguments other than phylogenies. I guess the number of reported LGTs among protists (whatever the source) over the last decade has by now deflated the novelty of the issue in more general; a report of the numbers is expected but they alone won't get you far anymore in the absence of a good story (such as e.g. work on plant cell wall degrading enzymes in beetles).

      We agree with the reviewer that the cases of LGT involving Preaxostyla would deserve more discussion in the manuscript. On the other hand, we also agree that none of them provides such a “cool” story that would deserve a special chapter or even a separate paper. Therefore, we have decided, also with regard to keeping the text in a reasonable dimension, not to expand the discussion of LGTs with the exception of HgcAB, where some new information has been included and the phylogeny of the genes updated. Please note that we had discussed in the original manuscript the donor lineages and ecological/biochemical context in the cases of GCS-L2, HPAD, UbiE, and NAD+ synthesis and this material has been kept also in the revised version.

      It would help to clarify which parts of the mitochondrial ancestor were reduced during the process of reductive evolution at what time in their hypothesized trajectory. For instance, loosing enzymes of anaerobic metabolism conflicts with the argued case of an aerobic (as opposed to facultative anaerobic) mitochondrial ancestor followed by gains of anaerobic metabolism in the rest of the eukaryotes via LGT, and some papers the authors themselves cite (e.g. the series by Stairs et al.). There is no coherent picture on LGT and anaerobic metabolism, although a reader is right to expect one.

      These are very interesting questions, that would fill a separate article. In the manuscript, we focus on the Preaxostyla lineage only and there the trajectory seems relatively simple: replacement of the mitochondrial ISC by cytosolic SUF in the common ancestor of Preaxostyla, loss of methionine cycle and in in consequence mitochondrial GCS and the mitochondrion itself. We have modified the first conclusion paragraph in this sense and it now reads the following:

      The switch to the SUF pathway in these species has apparently not affected the number of Fe-S-containing proteins but led to a decrease in the usage of 2Fe-2S clusters. The loss of MRO impacted particularly the pathways of amino acid metabolism and might relate also to the loss of large hydrogenases in oxymonads.

      It is not clear to us how to understand the reviewer’s remark concerning the conflict between loss of enzymes of anaerobic metabolism and the (presumed) aerobic nature of the mitochondrial ancestor. Provided that we read the reviewer’s rationale correctly, is it really so implausible that the anaerobic metabolism gained laterally by a particular lineage was then secondarily lost in specific descendant lineages? As a clear example demonstrating the feasibility of such an evolutionary pattern consider the evolution of plastids. There is no doubt these organelles move across eukaryotes by secondary or higher-order endosymbiosis or kletoplastidy, establishing themselves in lineages where there was no plastid before. Secondary simplification of such plastids, e.g. by the loss of photosynthesis, in its extreme form culminating in the complete loss of the organelle, has been robustly documented from several lineages, such as Myzozoa (e.g., https://pubmed.ncbi.nlm.nih.gov/36610734/). Hence, we see absolutely no reason to rule out the possibility that the ancestral mitochondrion was obligately aerobic and enzymes of anaerobic metabolism spread secondarily by eukaryote-to-eukaryote LGT, with their secondary loss in particular lineages. We really do not see any conflict here and we do not agree with the interpretation provided by the reviewer. That said, we admit that the discussion on the earliest stages of mitochondrial evolution is not an essential ingredient of the story we try to tell in our manuscript, so to avoid any unnecessary misunderstanding we have removed the original last sentence of Conclusions (“Thorough searches revealed …”) from the revised manuscript.

      In light of their data the authors also discuss the importance of the mitochondrion with respect to the origin of eukaryotes:

      First, the mitochondrion brought thousands of genes into the marriage with an archaeon, surely hundreds of which provided the material to invent novel gene families through fusions and exon shuffling and some of which likely went back and forth over the >billion years of evolution with respect to localizations. The authors look at a minor subset of proteins (pretty much only those of protein import, Fig. 6) to conclude, in the abstract no less: „most strikingly the data confirm the complete loss of mitochondria and every protein that has ever participated in the mitochondrion function for all three oxymonad species." I do not question the lack of a mitochondrion here, but this abstract sentence is theatrical in nature, nothing that data on an extant species could ever proof in the absence of a time machine, and is evolutionary pretty much impossible. A puzzling sentence to read in an abstract and endosymbiont-associated evolution.

      We feel that the reviewer is putting too much emphasis on an aspect of our original manuscript that is rather peripheral to its major message. Indeed, the manuscript is not, and has never been thought to be, primarily about eukaryogenesis and the exact role the mitochondrion played in it. We are, therefore, somewhat reluctant to react in full to the very long and complex argument the reviewer has raised in his/her report, so we keep our reaction at the necessary minimum. Concerning the criticized sentence in the original version of the abstract, it alluded to a section of the manuscript (“No evidence for subcellular retargeting of ancestral mitochondrial proteins in oxymonads”) that we have removed from the revised version, and hence we have modified also the abstract accordingly by removing the sentence. We still think our original arguments were valid, but apparently, much more space and more detailed analyses are required to deliver a truly convincing case, for which there is no space in the manuscript.

      Second, using oxymonads as an example that a lineage can present eukaryotic complexity in the absence of mitochondria and conflating it with eukaryogenesis is a logical fallacy. This issue already affected the 2019 study by Hampl et al.. We have known that a eukaryote can survive without an ATP-synthesizing electron transport chain ever since Giardia and other similar examples and the loss of Fe-S biosynthesis and the last bit of mitosome (secondary loss) doesn't make a difference how to think about eukaryogenesis. It confuses the need and cost to invent XYZ with the need and cost of maintenance. How can the authors write "... and undergo pronounced morphological evolution", when they evidently observe the opposite and show so in their Fig. 1? The authors only present evidence for reductive evolution of cellular complexity with the loss of a stacked Golgi. What morphological complexity did oxymonads evolve that is absent in other protists? A cytosolic metabolic pathway doesn't count in this respect, because it is neither morphological, nor was it invented but likely gained through LGT according to the authors. This is quite confusing to say the least. A recent paper (https://doi.org/10.7554/eLife.81033) that refers to Hampl et al. 2019 has picked this up already, and I quote: "Such parasites or commensals have engaged an evolutionary path characterized by energetic dependency. Their complexity might diminish over evolutionary timescale, should they not go extinct with their hosts first." Here the authors raise a red flag with respect to using only parasites and commensals that rely on other eukaryotes with canonical mitochondria as examples. If we now look at Fig. 1 of this submission, Novak et al. underpin this point perfectly, as the origin of oxymonads is apparently connected to the strict dependency on another eukaryote (or am I wrong?), and they support the prediction with respect to complexity reducing after the loss of mitochondria - mitosome gone, Golgi almost gone. What's next? This is a good time to remember that extant oxymonads are only a single picture frame in the movie that is evolution, and their evolution might be a dead-end or result in a prokaryote-like state should they survive 100.000s to millions of years to come.

      It seems that in this point the reviewer is particularly concerned with the following sentence that is part of the Introduction and which relates to the existence of amitochondrial eukaryotes we are studying: “The existence of such an organism implies that mitochondria are not necessary for the thriving of complex eukaryotic organisms, which also has important bearings to our thinking about the origin of eukaryotes (Hampl et al. 2018). Even after re-reading the sentence we confess we stay with it and find it perfectly logical. Nevertheless, we decided to omit it from the text so as not to distract from the main topic of the study.

      Next, when mentioning “… pronounced morphological evolution” we mean the evolution of four oxymonad families (Streblomastigidae, Oxymonadidae, Pyrsonymphidae and Saccinobaculidae) comprising almost a hundred described species with often giant and morphologically elaborated cells that evolved from a simple Trimastix-like ancestor (Hampl 2017, Handbook of Protists, 0.1007/978-3-319-32669-6_8-1). This is a fact that can hardly be dismissed. Also, given the current oxymonad phylogenies (Treitli et al. 2018, doi.org/10.1016/j.protis.2018.06.005) and the reported absence of a mitochondrion in M. exilis, B. nauphoetae, and S. strix we can infer that the mitochondrion was lost in the common ancestor of the three species at latest. This organism must have lived more than 100 MYA, as at that time oxymonads were clearly diversified into the families (Poinar 2009, 10.1186/1756-3305-2-12). So, these organisms indeed have lived without mitochondria for at least 100 MY. We think that these facts and our inferences based on them are solid enough to keep in the conclusion the following statement: “This fact moves this unique loss to at least 100 MYA deep past, when oxymonads had been already diversified (Poinar 2009), and shows that a eukaryotic lineage without mitochondria can thrive for eons and undergo pronounced morphological evolution, as is apparent from the range of shapes and specialized cellular structures exhibited by extant oxymonads (Hampl 2017).” Furthermore, as documented in Karnkowska et al. 2019 (https://pubmed.ncbi.nlm.nih.gov/31387118/), apart the loss of the mitochondrion oxymonads are surprisingly “normal” and complex eukaryotes, in fact much less reduced than, e.g., Giardia, Microsporidia, or even S. cerevisiae (in terms of the number of genes, introns, etc.). We strongly disagree with the claim that “Golgi is almost gone” in oxymonads, and our manuscript shows exactly the opposite. Viewing oxymonads as a lineage heading towards a prokaryote-like simplicity is dogmatic and ignores the known biology of these organisms.

      Some more thoughts: Line 47-52: Hydrogenosome or mitosome is a biological and established label as (m)any other and I find the use of the word "artificial" in this context strange. While the authors are correct to note that there is a (evolutionary) continuum in the reduction - obviously it is step by step - they exaggerate by referring to the existing labels as "artificial". You make Fe-S clusters but produce no ATP? Well, then you're a mitosome. It's a nomenclature that was defined decades ago and has proven correct and works. If the authors think they have a better scheme and definition, then please present one. Using the authors logic, terms such as amyloplast or the TxSS nomenclature for bacterial secretions systems are just as artificial. As is, this comes across as grumble for no good reason.

      We agree that the original wording sounded like unwarranted grumbling and we have changed the sentence in the following way: "However, exploration of a broader diversity of MRO-containing lineages makes it clear that MROs of various organisms form a functional continuum (Stairs et al. 2015; Klinger et al. 2016; Leger et al. 2017; Brännström et al. 2022)."

      Line 158: A duplication-divergence may also explain this since sequence similarity-based searches will miss the ancestral homologues.

      We do not disagree about this, in fact, the gene the reviewer’s point is concerned with for sure is a result of duplication and divergence, as it belongs to a broader gene family (major facilitator superfamily, as stated in the manuscript) together with other distant homologs. Nevertheless, this is not in conflict with our conclusion that it “may represent an innovation arising in the common ancestor of Metamonada”.

      Lines 201-202: Presence of GCS-L in amitochondriate should be explained in light of this group once having a mitochondrion, which then makes ancestral derivation and differential loss (as invoked for Rsg1) also a likely explanation along with eukaryote-to-eukaryote LGT.

      Yes, this most likely holds for the standard paralogue GCS-L1 (in P. pyriformis PAPYR_5544), which has the expected distribution and phylogenetic relationships and is absent in oxymonads. The discussion is, however, mainly about the rare, divergent and until now overlooked paralogue GCS-L2 (in P. pyriformis PAPYR_1328), which we found only in three distantly related eukaryote groups, Preaxostyla, Breviatea, and Archamoebae, which strongly suggests inter-eukaryotic LGT.

      Lines 356-392: Describes plenty of genomic signal for Golgi bodies but simultaneously cites literature suggesting the absence of a morphologically an identifiable Golgi in oxymonads. An explicit prediction regarding what to observe in TEM for the mentioned species might be nice to stimulate further work.

      We thank the reviewer for their suggestion and are glad that they are enthusiastic about this aspect of the manuscript. Unfortunately, the morphology of unstacked Golgi ranges from single cisternae (yeast, Entamoeba), vesicles (Mastigamoeba), and a “tubular membranous structure” in Naegleria. Therefore, no strong prediction is possible of what the oxymonad Golgi might look like under light or TEM. However, the data that we have provided should lead to molecular cell biological analyses aimed at identifying the organelle, giving target proteins to tag or against which to create antibodies as Golgi markers. An additional sentence to this effect has been added to the manuscript, “They also set the stage for molecular cell biological investigations of Golgi morphological variation, once robust tools for tagging in this lineage are developed.”

      Lines 414: The preceding paragraphs in this result section describes only the distribution, without mentioning origins - a sweeping one-line summary that proclaims different origin needs some context and support. Furthermore, the distribution of glycolytic enzymes might indeed be patchy, but to suggest it represents an 'evolutionary mosaic composed of enzymes of different origins' without discussing the alternative of a singular origin and different evolutionary paths (including a stringer divergence in one vs. another species) discredits existing literature and the authors own claim with respect to why BUSCO might fail in protists.

      The part of the text about glycolysis the reviewer alluded to has been removed while shortening the manuscript.

      Line 486: How uncommon are ADI and OTC in lineages sister to metamonada?

      This is an interesting but difficult question. Firstly, we are uncertain what is the sister lineage to Metamonada. Discoba, maybe, but a recent unpublished rooting of the eukaryotic tree does not support it (https://pubmed.ncbi.nlm.nih.gov/37115919/). Generally, the individual genes of the pathway (ADI, OTC and CK) are quite common in eukaryotes, but the combination of all three is rare (Metamonada, the heterolobosean Harpagon, the green algae Coccomyxa and Chlorella, the amoebozoan Mastigamoeba, and the breviate Pygsuia), see figure 1 in Novak et al 2016, doi: 10.1186/s12862-016-0771-4.

      Line 504: It might help an outside reader to include a few lines on consequences and importance of having 2Fe-S vs 4Fe-S clusters and set an expectation (if any) in Oxymonads.

      We apologize for omitting this explanation. The 2Fe-2S proteins are more common in mitochondria where 2Fe-2S clusters are synthesized in the early pathway of FeS cluster assembly, while the cytosolic CIA pathways produce 4Fe-4S clusters (https://pubmed.ncbi.nlm.nih.gov/33007329/). The original expectation therefore is that species without mitochondria should not have 2Fe-2S cluster proteins. Obviously, the switch to the SUF pathway affects this expectation as we do not know, what type of cluster this pathway produces in oxymonads (https://www.biorxiv.org/content/10.1101/2023.03.30.534840v1). For the sake of brevity, we have included a short statement as the beginning of the sentence in question, which now reads as follows: “As 2Fe-2S clusters are more frequent in mitochondrial proteins, the higher number of 2Fe-2S proteins in P. pyriformis compared to the oxymonads may reflect the presence of the MRO in this organism.

      Any explanations on what unique selection pressures and gene acquisition mechanisms may be operating in P. pyriformis which might allow for the unique metabolic potential?

      Every species exhibits a unique combination of traits that results from changing selection pressures imposed on historical contingency (including neutral evolutionary processes such as genetic drift). We lack real understanding of these factors for a majority of taxa including the familiar ones, so we should not expect to have a good answer to the reviewer’s question. In fact, we do not know how unique is the particular combination of P. pyriformis traits discussed in our manuscript, as there has been no comprehensive comparative analysis that would include ecologically and evolutionarily comparable taxa. We note that Paratrimastix represents only a third free-living metamonad with a sequenced genome (together with Kipferlia and Carpediemonas), so more data and additional analyses are needed to be in a position when we may start hoping answers to questions like the one posed by the reviewer are in reach.

      ** Referees cross-commenting** To R3: Hampl et al. 2019, to which Novak et al. refer, is about eukaryogensis and that is exactly the context in which this is discussed again and what Raval et al. 2022 had decided to touch upon. If the authors do not bring this up in light of the ability to evolve (novel) eukaryote complexity, then what else? Maybe they can elaborate, especially with respect to energetics to which they explicitly refer to in 2019 (and here). And with respect to text-book eukaryotic traits (and the evolution of new morphological ones), I do not see any new ones evolving in any oxymonad, but reduction as Novak et al. themselves picture it in this submission. Is a change in the number of flagella pronounced morphological evolution? Maybe for some, but I believe this needs to be seen in light of the context of how they discuss it. I see a reduction of eukaryotic complexity and not a gain. They have an elaborate section on the loss of Golgi characteristics (and a figure), but I fail to read something along the same lines with respect to the gain of new morphological traits. Again, novel LGT-based biochemistry does not equal the invention of a new morphology such as a new compartment. Oxymonads depend on mitochondria-bearing eukaryotes for their survival or don't they? This is the main point, and if evidence show that I am wrong, then I will be the first to adapt my view to the data presented.

      While we do see the logic of the reviewer’s point, a good reply would have to be too elaborate and certainly beyond the scope of the current manuscript. As the reviewers’ reports led us to reconsider the structure of the manuscript and to make it more focused and concise, we decided to simplify the matter by removing the allusions to eukaryogenesis, realizing that it is perhaps more suitable for a different type of paper (opinion, review). The comment on the evolution of complex morphology has been answered previously (see above).

      I have concerns with the presentation of a narrative that in my opinion is too one-sided and that has been has been publicly questioned in the community (in press, at meetings, personally). For the benefit of science and of the young authors on this study, this reviewer feels strongly that these issues should be taken very seriously and discussed openly in a more balanced way. . We only truly move forward on such complex topics, if we allow an open and transparent discussion.

      We agree that opinions on specific details of eukaryogenesis are divided in the community and that the topic requires a nuanced discussion for which there is perhaps no place in the current manuscript. As stated in the reply to the previous point, we have removed the discussion of the implications of our current study to eukaryogenesis from the revised manuscript.

      Having said that, I am happy that R3 has picked up exactly the same major concerns as I did with respect to e.g. the phrasing on mito (gene) loss and the BUSCO controversy.

      We appreciate these comments and hopefully have resolved the concern in the previous answers.

      Reviewer #2 (Significance):

      Using draft genome sequencing of the free-living Paratrimastix pyriformis and the sister lineage oxymonad Blattamonas nauphoetae, Novack et al. infer the metabolic potential of the two protists using comparative genomics. The authors conclude that the common oxymonad ancestor lost the mitochondrion/mitosome and discuss general strategies for adapting to commensal/symbiotic life-style employed by this taxon. Some elaborations on pathways go on for several paragraphs and feel unnecessarily stretched, which made those sections of the paper rather difficult to digest. This might be also be because the work, and all conclusions drawn, depend entirely on incomplete (ca. 70-80%) genome data and simple similarity searches, and e.g. no kind of biochemistry or imaging is presented to underpin the manuscripts discussion.

      We have addressed the concern about the possible incompleteness of our genome data above, demonstrating it is not substantiated ad stems from an inadequate interpretation of quality measures we provide in the manuscript. We hope that the revised manuscript, which is streamlined and more concise compared to the initial submission, conveys the key messages in a substantially more persuasive way and will be appreciated by a broad community of readers.

      Reviewer #3 (Evidence, reproducibility and clarity):

      Summary: The genome sequences of two members of the protist group Preaxostyla are presented in this manuscript: Paratrimastix pyriformis and Blattamonas nauphoetae. The authors use a comparative genomics and phylogenetic approaches and compare the new genome datasets with three previously available genomes and transcriptomes from the group. The availability of genome-scale data from five Preaxostyla species is powerful to address interesting basic evolutionary questions. A substantial part of the manuscript is spent on testing the hypothesis of mitochondrial loss in the oxymonad lineage, which turns out to be supported. The datasets are also explored regarding the role of lateral gene transfer in the group, metabolic diversification and the evolution of Golgi.

      Major comments: I find the manuscript very interesting with many different fascinating results presented. However, the manuscript is very long. Two genome sequences are presented and it is not clear to me what the main question was when this project was initiated and why these two species was selected to answer this question. I do not see an obvious reason for sequencing the P. pyriformis genome if the mitochondrial loss was the main question (given that a transcriptome was already available). Why not spend the time and resources on a member of Preoxystyla, which lacked previous data? The authors should more clearly state why these organisms were chosen to answer the main question or questions of the study.

      We are sorry for having done a poor job when explaining the choice of the taxa for the comparison. The idea was to sample an outgroup of oxymonads (P. pyriformis) and a representative of other clades of oxymonads than M. exilis (B. nauphoetae and S. strix) for which it was feasible to obtain the data, or the data were already available. Obviously, more representatives of morphologically a probably also genetically diverse oxymonads should be investigated (e.g. Pyrsonympha, Oxymonas, Saccinobacullus) and we have such a plan but these organisms are difficult to work with. We considered it necessary to sequence the genome of P. pyriformis, and not rely on the transcriptome only, to avoid the issue of data set incompleteness (raised also by R2). Transcriptomes by nature provide an incomplete coverage of the full gene complement of the species, while our genome assemblies are close to complete, as we explain elsewhere.

      The evolution of MROs have received substantial attention from the protist research community since the 1990's. During this period the mitochondrial organelle have been considered essential for eukaryotes. Therefore, the result presented in the manuscript has a high significance. However, I am not convinced that it is appropriate to use the term "evolutionary transition" for the mitochondrial loss. The loss of MRO is the endpoint of a gradual change of the internal organisation of the cell that probably started when the ancestor of these organism adapted to an anaerobic lifestyle. The last step described in the manuscript probably had little impact on how these organisms interacted with their environment. The presence or absence of biosynthesis of p-cresol by some, but not all, Preaxystyla probably is much more significant from an ecological point of view. My point is that the authors need to consider how they use the term evolutionary transition and be explicit about that.

      We appreciate the comment concerning the use of the term “evolutionary transition”. Nevertheless, we believe there is no real consensus in the literature on what is and what is not an “evolutionary transition”, and the application of the term to specific cases is more or less arbitrary. For a lack of a standardized or better terminology, we have kept the term to refer to three evolutionary changes in the evolution of the Preaxostyla lineage that are particularly important from the cytological or ecological perspective, i.e. dispensing with the mitochondrion, reorganizing the Golgi apparatus by losing the stacked arrangement of the cisternae, and gaining the endobiotic life style.

      In the abstract the main finding is describes as "the data confirm the complete loss of mitochondria and every protein that has ever participated in the mitochondrion function for all three oxymonad species (M. exilis, B. nauphoetae, and Streblomastix strix) extending the amitochondriate status to the whole Oxymonadida.". I find this a really interesting observation, but I do find the wording a bit too bold for several reasons: • Not every protein that has participated in the mitochondrial function is known. • Mitochondrial proteins could be present in oxymonads, but divergent beyond the detection limit for existing methods. • Genes for one or several mitochondrial proteins could be present in one or more oxymonad genomes, but remain undetected due to the incomplete nature of the datasets.

      Although I do think that the authors' claim very well could be true, I don't think their data fully support it. Therefore, it needs to be rephrased.

      As a result of our decision to streamline the manuscript by removing the final part of Results and Discussion (“No evidence for subcellular retargeting of ancestral mitochondrial proteins in oxymonads”, the revised manuscript no longer support the statement “the data confirm the complete loss of … every protein that has ever participated in the mitochondrion function for all three oxymonad species” that is criticized by the reviewer, and hence the statement has been removed from the abstract. This addresses bullet point 1. As for bullet points 2 and 3, the proof of absence is in principle impossible to deliver, and we have been fighting with this already in the Karnkowska et al. 2016 paper. Although our certainty will never reach 100% (this is in fact impossible for a scientific, i.e., falsifiable, hypothesis), the mounting of evidence through studies gives the hypothesis on the amitochodriate status of oxymonads more and more credit. The genes for mitochondrial marker proteins have not been detected by the most sensitive methods available neither in the first genome assembly of M. exilis (Karnkowska et al. 2016), nor in the improved M. exilis genome assembly composed of only 101 contigs (Treitli et al. 2021), nor in either of the other two oxymonad species investigated here. On the other hand, they were readily detected in the data sets of P. pyriformis and T. marina. What is the probability that these genes always hide in the assembly gaps, or that they have all escaped recognition? Obviously, this probability is not zero, but we believe it is approaching so low values that it is reasonably safe to make the conclusion on the amitochondriate status of these species.

      The sentence was changed to: "Our results provide insights into the metabolic and endomembrane evolution, but most strikingly the data confirm the complete loss of mitochondria for all three oxymonad species investigated (M. exilis, B. nauphoetae, and Streblomastix strix), suggesting the amitochondriate status may be common to Oxymonadida."

      The third point maybe could be analysed further. BUSCO scores are reported, but also argued not being reliable for this group of organisms (which is true). Would it, for example, be useful to analyse how large fraction of the BUSCO proteins found in all non-Preoxystyla metamonada genomes that are present in the various Preoxystyla datasets?

      We provide a comprehensive answer to a similar comment of reviewer 2 above (page 6-8). We performed the requested analysis and provide the result in Supplementary file 11. In this table, we record presence/absence of each gene from the BUSCO set for our data sets and the highly complete “standard” datasets of Trypanosoma brucei, Giardia intestinalis and Trichomonas vaginalis. Of the 303 genes, 117 were present in all data sets and 17 in none (see column I). 20 were present only in Trypanosoma and not in metamonads. 6 were present in all Preaxostyla and absent in other metamonads (Trichomonas and Giardia), 44 were present in all Preaxostyla and Trichomonas and absent in Giardia, suggesting high divergence of this species. Only 23 (marked by *) were present in the three “standard” genomes and absent in one or more Preaxostyla species. Of those 8 and 8 were absent specifically in S. strix and P. pyriformis, respectively, but only 1 was absent specifically in M. exilis and no such case was observed in B. nauphoetae. We conclude that this non-random pattern argues for lineage-specific divergence rather than incomplete data sets, particularly in the case of M. exilis and B. nauphoetae.

      Line 160-161: 15 LGT events specific for the Preaxostyla+Fornicata clade is reported. This is an exciting finding because it supports a phylogenetic relationship between these two groups. But such an argument is only valid if the observed pattern is more common than the alternative hypotheses (Preaxostyla+Parabasalids and Fornicata+Parabasalids). How many LGT events support each of these groupings? How are these observation affected by the current taxon sampling with the highest number of datasets from Fornicata? How were putative metamonada-to-metamonada LGTs treated in this context?

      19 LGT are uniquely shared between Preaxostyla+Parabasalids, which is more than the number of shared LGTs between Preaxostyla and Fornicata. No common LGT was unique to Fornicata+Parabasalids. However, the latter is a direct consequence of our investigation method, which involved reconstruction phylogenies of genes present in Preaxostyla, and not across all metamonads. So, we do not have a way to investigate LGT gene families uniquely shared between Fornicata and parabasalids.

      When it comes to the effect of taxon sampling, we agree that it is possible that the number of genes of horizontal origin shared between parabasalids and Preaxostyla is underestimated because of the lower taxon sampling in parabasalids. However, it is still larger (19) than the number of LGTs shared uniquely between fornicate and Preaxostyla (15). In addition, while the taxon sampling is larger in fornicates, it also contains some representatives of closely related lineages (e.g., Chilomastix caulleryi and Chilomastix cuspidate) which, while they increase the number of fornicate representatives, does not increase the detection of shared genes between fornicates and Preaxostyla. Altogether, it's difficult to estimate how the current taxon sampling is biasing the detection of LGTs one way or another.

      Regarding metamonad-to-metamonad putative LGTs: we did not consider this possibility for the sake of not overestimating the number of gene transfers for two main reasons. First of all, our LGT detection relies on the incongruence between species tree and gene tree. The closer the lineages are in the species tree, the more difficult it is to interpret any incongruence in the gene tree as single protein phylogenies are notoriously poorly resolved because they rely on the little phylogenetic signal contained in few amino-acid positions. Because of this, small incongruences with the species tree could either reflect recent LGT events between metamonads, or simply blurry phylogenetic signal. Second, we can certainly use the argument that a limited taxonomic distribution among metamonads favors an LGT event between them. However, here again, the closer the lineages involved are, the more difficult it is to distinguish a scenario where one lineage was the recipient of an LGT from prokaryote before donating it to another metamonad, from a scenario involving a single ancestral LGT from prokaryotes to metamonads, followed by differential loss, leading to a patchy taxonomic distribution. Finally, we are working with both limited taxon sampling and incomplete genomic/transcriptomic data, which makes it more difficult to identify true absences. For all these reasons, we chose to be conservative and invoke the smallest number of LGT events.

      The authors have used a large-scale approach to make single-gene trees for inferences of LGT. In other parts of the manuscript inferences of evolutionary origins of single genes are made without support of phylogenetic trees. I find this inconsistent and argue that the hypothesis of the origin of a specific protein should be tested with the same rigor whether it is a putative LGT, gene duplication, gene loss or an ancestral member of LECA. Specific cases where I think a phylogenetic analysis is needed includes: • Line 222-223: It is concluded that Rsg1 is a component of LECA. • Line 307: HgcAB are argued to be acquired by LGT of a whole opeon. • Lines 350-355: It is unclear how the different numbers of transporters are interpreted (loss or expansion by duplication). This could be address with phylogenetics. • Lines 407-408: A tree should support the claim of LGT origin. (PFP) • Lines 414-415: The different origins of glycolytic enzymes should be supported by data or references. • Line 486: Trees or a reference (if available) should support the claim for LGT.

      As requested, trees were constructed for HgcA, HgcB, PFP and the transporters AAAP, CTL, ENT, pATPase, and SP. Citations were added for the glycolytic enzymes and the ADI pathway. No tree for Rsg1 is needed, as this is a eukaryote-specific protein lacking any close prokaryotic relatives. The inference on its presence in the LECA is based on the phylogenetically wide, however patchy, distribution across the eukaryote phylogeny. Testing possible eukaryote-eukaryote LGTs is hampered by a limited phylogenetic signal in the short and rapidly evolving Rsg1 sequences, resulting in very poorly resolved relationships among Rgs1 sequence in a tree we attempted to make (data not shown). For this reason, we opt for not presenting any phylogenetic analysis for Rsg1.

      Lines 530-531 and 773-774: "The switch to the SUF pathway in these species has apparently not affected the number of Fe-S-containing proteins but led to a decrease in the usage of 2Fe-2S clusters." I find it difficult to evaluate if the data support this because no exact numbers or identities are given for 2Fe-2S and 4Fe-4S proteins in the various genomes in Suppl. Fig. S4 or Supplementary file 4.

      The functional annotation of all detected FeS clusters containing proteins is provided in Supplementary Table S8 including the types of predicted clusters (columns G or F). Basically, the only putative 2Fe2S cluster containing proteins in species of oxymonad is xanthine dehydrogenase, while Paratrimastix and Trimastix contain also 2Fe2S cluster-containing ferredoxins and hydrogenases.

      The method used in the paper varies between the different parts of the paper. One example is single gene phylogenies, which are described three times in the method section [Lines 959-973, lines 1011-1034, lines 1093-1101], in addition to the automated approach within the LGT detection pipeline lines 923-926]. The approaches are slightly different with, for example, different procedures for trimming. This makes it difficult to know how the different presented analyses were done in detail. No rationale for using different approaches is given. At the least, it should be clear in the method section which approach was used for which analysis.

      The reviewer is correct, and we apologize for the inconsistency. The reason is only historical –the analyses were performed by different laboratories in different periods of time. We believe this fact does not make our results less robust, although it does not “look” nice and makes the description of the methods employed longer. We have double-checked the description and introduced slight changes as to make it maximally clear which method has been used for particular analyses presented in the Results and Discussion.

      Specific comments on single gene phylogenies:

      • Line 966-967: Why max 10 target sequences?

      The limit of 10 was applied in order to keep the datasets in manageable dimensions. The sentence has been changed to: " In order to detect potential LGT from prokaryotes while keeping the number of included sequences manageable, prokaryotic homologues were gathered by a BLASTp search with each eukaryotic sequence against the NCBI nr database with an e-value cutoff of 10-10 and max. 10 target sequences.

      • Lines 996-998: Is it a problem that these are rather old datasets?

      Although the publications are slightly older the set of queries is absolutely sufficient for the purpose.

      Minor comments: I appreciate that many data is included as supplementary material. However, the organisation of the data could be improved. The numbering of the files is not included in their names or within the files, as far as I could find. Descriptions of the files are often missing and information on the annotation such as colour coding is not always included. These aspects of the supplementary material needs to be strengthened in order to make it more useful. Specific comments: • Supplementary file 1, Table 1: accession numbers are missing. Kipferlia bialta appears to have a much smaller number of sequences than reported in the publication. The file consists of three tables and it would be very helpful if the reference in the main manuscript indicate the table number. • Supplementary file 4: The trees lack proper species names and a documented colour coding. There are multiple trees in the file, which make it difficult to find the correct tree. I would appreciate if the different trees were labelled A, B, C, etc., and if these were used in the main text.

      Supplementary file 1: Accession numbers were added.

      Supplementary file 4: Species names and alphabetical labelling were added. Colour coding was explained in the text at the first mention of the file: "(Supplementary file 4 H; Preaxostyla sequences in red)."

      o There is no HPAD-AE tree (as indicated on line 258), but a HPAD tree. Which part of the tree contain the described fusion protein?

      Thank you for spotting the mistake. There should have been “HPAD” instead of “HPAD-AE” indicated in the text. The sentence has been changed to:" The P. pyriformis HPAD sequence is closely related to its homolog in the free-living archamoebid M. balamuthi (Supplementary file 4 K), the only eukaryote reported so far to be able to produce p-cresol (Nývltová et al. 2017)."

      o Line 280-281: "UbiE homologs occur also in some additional metamonads, including the oxymonad B. nauphoetae and certain fornicates." These sequences should be clearly highlighted in the tree.

      We discovered these additional UbiE homologs only after the tree presented in the supplement had been constructed, so these sequences are missing from it. To ensure consistency we have decided to remove the remark on the presence of UbiE homologs metamonads other than P. pyriformis, so it is no longer part of the revised manuscript.

      o Lines 538-544: A three-gene system is mentioned, but only two AmmoMemoRadiSam trees are found.

      This part has been removed while streamlining the manuscript.

      • Supplementary file 6: I find it difficult to find the proteins discussed in the text, for example "the biosynthesis of p-cresol from tyrosine (line 254-255)".

      Abbreviations identifying the different enzymes have now been added to all mentions in the text, facilitating their localization in the supplementary file: "P. pyriformis encodes a complete pathway required for the biosynthesis of p-cresol from tyrosine (Supplementary file 6), only the second reported eukaryote with such capability. This pathway consists of three steps of the Ehrlich pathway (Hazelwood et al. 2008) converting tyrosine to 4-hydroxyphenyl-acetate (AAT, HPPD, ALDH) and the final step catalyzed by a fusion protein comprised of 4-hydroxyphenylacetate decarboxylase (HPAD) and its activating enzyme (HPAD-AE)."

      • Supplementary file 11: Which group of species are highlighted in red? How do I know from which species these sequences are (I can make educated guesses, but prefer full species names). I do not find any reference to this file in the main manuscript.

      We apologise for this inconvenience. The taxon labels in the treed in this supplementary file have been corrected to contain full species names.

      Line 227-228: "630 OGs seem to be oxymonad-specific or divergent, without close BLAST hits". It is unclear if BLAST searches includes only a representative of each 630 OGs, or every single protein in these OGs.

      The BLAST searches include every single protein in the investigated OGs. We clarified it in the text: “Of these, 630 OGs seem to be oxymonad novelties or divergent ancestral genes, without close BLAST hits (e-value -15) to any of these sequences.

      Line 243: I think it is five LGT mapped to internal nodes of Preoxystyla in Figure 1 (1+3+1).

      You are correct, we apologize for the mistake. The sentence has been changed to: "Also, 46 LGT events were mapped to the terminal branches and 5 to internal nodes of Preaxostyla, suggesting that the acquisition of genes is an ongoing phenomenon, and it might be adaptive to particular lifestyles of the species."

      Lines 325-331: The argument would be stronger with a figure showing the fusion and the alignment indicating the conserved amino acids mentioned in the text.

      We agree with the reviewer but for the sake of space, we finally decided not to include a new figure.

      Lines 425: "none of the species encoded" should be replaced by something like "none of the enzyme could be detected in any of the species" (the datasets are incomplete).

      The sentence has been changed to: "None of the alternative enzymes mediating the conversion of pyruvate to acetyl-CoA, pyruvate:NADP+ oxidoreductase (PNO) and pyruvate formate lyase (PFL), could be detected in any of the studied species."

      Line 455: "suggesting a cytosolic localization of these enzymes in Preaxostyla." The absence of a phylogenetic affiliation with the S. salmonicida homolog does not preclude a MRO localisation.

      The sentence was changed to: "Phylogenetic analysis of Preaxostyla ACSs (Supplementary file 4 B) shows four unrelated clades, none in close relationship to the S. salmonicida MRO homolog, consistent with our assumption that these enzymes are cytosolic in Preaxostyla."

      Lines 570-571: "Manual verification indicated that all the candidates recovered in oxymonad data sets are false positives" Using which criteria?

      The manual verification was based on the annotation of predicted proteins by BLAST and InterProScan. If the annotations did not correspond to the suggested function, they were considered false positives. For example, the protein BLNAU_15573 of Blattamonas nauphoetae was detected by Sam50 HMM profile and thus was considered a candidate for Sam50 proteins. Its functional annotation from BLAST was, however, unrelated to Sam50 (“putative phospholipase B”). Therefore, this candidate was concluded as a false positive hit of the HMM search resulting from the very high sensitivity of this method.

      We clarified this in the Results

      Reciprocal BLASTs indicated that all the candidates recovered in oxymonad data sets are very likely to be false positives based on the annotations of their top BLAST hits (mainly vaguely annotated kinases, peptidases and chaperones) (Fig. 6, Supplementary file 9).”.

      And Material and Methods

      Any hits received by the methods described above were considered candidates and were furter inspected as follows. All candidates were BLAST-searched against NCBI-nr and the best hits with the descriptions not including the terms 'low quality protein', 'hypothetical', 'unknown', etc. were kept. For each hit, the Gene Ontology categories were assigned using InterProScan-5.36-75.0. If the annotations received from BLAST or InterProScan corresponded to the originally suggested function, the candidates were considered as verified. Otherwise, they were considered as false positives.

      Lines 743-755: "Similar observations were made in other protists with highly reduced mitochondria, such as G. intestinalis or E. histolytica,..." References are needed.

      This part of the manuscript has been removed while streamlining the text.

      Line 849: How was the manually curation done for the gene models in the training set?

      The sentence has been changed to: "For de novo prediction of genes, Augustus was first re-trained using a set of gene models manually curated with regard to mapped transcriptomic sequences and homology with known protein-coding genes."

      Lines 853-856: It is a bit unclear which dataset was used for BUSCO and downstream analysis. Was it the Augustus-predicted proteins, or the EVM polished?

      The sentence has been changed to: "The genome completeness for each genome was estimated using BUSCO v3 with the Eukaryota odb9 dataset and the genome completeness was estimated on the sets of EVM-polished protein sequences as the input."

      Lines 858: What is it meant that KEGG and similarity searches was used in parallel (what if both gave a functional annotation?)?

      A sentence has been added for clarity: "KEGG annotations were given priority in cases of conflict."

      Lines 861-862 and 1007-1008: Which genes or sub-projects does this apply to? How many genes were detected in this procedure?

      The sentence has been changed to make this clear: "Targeted analyses of genes and gene families of specific interest were performed by manual searches of the predicted proteomes using BLASTp and HMMER (Eddy 2011), and complemented by tBLASTn searches of the genome and transcriptome assemblies to check for the presence of individual genes of interest that were potentially missed in the predicted protein sets (single digits of cases per set). Gene models were manually refined for genes of interest when necessary and possible."

      Lines 878-879: It is not clear to me why the sum of the two described numbers should be as high as possible and would appreciate an argument or a reference.

      When optimizing the inflation parameter of OrthoMCL, we reasoned that the optimal level of grouping/splitting for our purpose should result in the highest number of orthogroups containing all representatives of the groups of interest (i.e. Preaxostyla) but no other species – pan-Preaxostyla orthogroups. When going down with the values, you observe more and more groupings of pan-Preaxostyla OGs with others (indication of overgrouping) in the opposite direction you observe splitting of pan Preaxostyla OGs which indicates oversplitting. Because we were optimizing the inflation parameter for Preaxostyla and Oxymonadida at the same time, we maximized the sum of pan-Preaxostyla and pan-Oxymonadida groups.

      Lines 879-881: "Proteins belonging to the thus defined OGs were automatically annotated using BLASTp searches against the NCBI nr protein database (Supplementary file 1)." Why were these annotated in a different way (compare lines 857-859).

      This little inconsistency resulted from the fact that these parts of the analyses were performed by different researchers who did not cross-standardize the procedures. This inconsistency has no effect on the downstream analyses and conclusions as the annotations from Supplementary file 1 were not used in any further analyses.

      Lines 894-957: "Detection of lateral gene transfer candidates": • It is not clear which sequences were tested in the procedure. All Preaxostyla, or all metamonada? I think I am confused because in the result sections you only report numbers for Preaxostyla, but in the method section metamonada is mentioned repeatedly.

      Thank you for noticing. There was indeed some inconsistency in our writing.

      We did an all-against-all search using all metamonads. However, we filtered out all homologous families in which Preaxostyla were not present or that had no hit against GTDB. So in the end, the LGT search was restrained to protein families containing Preaxostyla homologues. We corrected the wording in our method section.

      • It would be easier to follow the procedure if numbers are provided for the different steps.

      We are not sure what numbers the reviewer refers to here.

      • Why was only small oxymonad proteins discarded (line 900)?

      This is indeed a mistake. We meant “Preaxostyla proteins”. This is because we only considered Preaxostyla sequences with significant hits against GTDB as a starting point, so we aimed to first remove those that might be too short to yield reliable phylogenies.

      • Line 911: How many sequences were collected?

      Up to 10,000 hits were retained. We have added that information to the text.

      • Lines 916-919: What is the difference between the protein superfamilies (line 916) and the OGs (line 919)? Are the OGs the same orthogroups that is described earlier in the method section? How are the redundancy of NCBI nr entries retrieved in different searches dealt with?

      We understand the confusion here. It primarily stemmed from two different ways to establish homologous families across the manuscript because of different researchers being responsible for different parts. Protein superfamilies that were used for reconstructing the single protein trees used for the LGT analyses were assembled based on the procedure describe line 916-919 (“Protein superfamilies were assembled by first running DIAMOND searches of all metamonad sequences against all (-e 1e-20 --id 25 --query-cover 50 --subject-cover 50). Reciprocal hits were gathered into a single FASTA file, as well as their NCBI nr homologues.”). However, this was a somewhat stricter procedure than the one used to establish the OGs that are discussed in the rest of the manuscript (because of the e-value and identity cut-off used), so we eventually enriched the datasets with the putatively missing metamonad sequences that were present in the OGs but not in the initial superfamily assembly. However, since these were often more divergent sequences, we did not use these as queries for our BLAST searches against prokaryotes.

      Line 987-989: "...was facilitated by Rsg1 being rather divergent from other Ras superfamily members" This statement is vague. What does it mean in practise?

      The sentence has been changed to: " The discrimination was facilitated by Rsg1 having low sequence similarity to other Ras superfamily members (such as Rab GTPases)."

      Lines 1037-1038: Why were these proteins re-annotated?

      They were not. We are sorry for this mistake, which has been fixed in the revised manuscript.

      Figures: The figures would be easier to follow if the colour coding for the five different species were consistent between the figures.

      This is a good point, the colour coding has been unified across all figures.

      Figure 1: It appears that the Venn diagram in C only shows the Preaxostyla-specific protein in B, not all OGs for which contain Preaxostyla proteins. This is not clear from legend or from the figure itself. The same comment applies to D.

      The interpretation of the figure by the reviewer is correct; we have modified the legend to make the meaning of the figure easier to understand.

      Figures 2 and 6: It would be clearer with panel labels A, B, etc, instead of "upper" and "lower" panel, as in the other figures.

      This is a fair point, we have added the alphabetical labels proposed by the reviewer to the figures.

      Figure 6: What is the colour code in the figure? The numbers within the boxes are not aligned.

      We have added an explanation of the color code to the legend and edited the figure to make it aesthetically more pleasing.

      Supplementary figures 1-3: What do green and magenta indicate in the figure?

      As with the previous figure, the color code is now explained in the revised legend.

      ** Referees cross-commenting** I agree with the other reviewers that the discussion of the functional and ecological implications of the LGTs could be developed.

      We understand the reviewers but as already explained in response to Reviewer 1, we have decided not to extend the already rather long manuscript further. We believe that the several exemplar LGT cases that we do discuss in detail provide a good impression of the significance of LGT in the evolution of Preaxostyla.

      In contrast to reviewer 2, I do not see that the authors discuss their result in the context of eukaryogenesis in this manuscript. Maybe the reference reviewer 2 mention could be cited in the introduction together with Hampl et al. 2018 to acknowledge that there are different views about the importance of secondarily amitochondrial eukaryotes on our thinking about the origin of eukaryotes. I disagree with reviewer 2's objection against the wording "... and undergo pronounced morphological evolution" because I think Fig. 4 in Hampl 2017 shows a large morphological diversity among oxymonads.

      We are glad to see that our perspective is not shared by other colleagues in the field. Nevertheless, having carefully considered the case we have decided to remove any mentions of eukaryogenesis from the revised manuscript, as we admit this topic is peripheral to the key message of our present study. On the other hand, we appreciate very much the note by the reviewer on the large morphological diversity among oxymonads – we have now added a similar remark to the revised manuscript (the last sentence of Conclusions).

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      Referee #2

      Evidence, reproducibility and clarity

      Using draft genome sequencing of the free-living Paratrimastix pyriformis and the sister lineage oxymonad Blattamonas nauphoetae, Novack et al. infer the metabolic potential of the two protists using comparative genomics. The authors conclude that the common oxymonad ancestor lost the mitochondrion/mitosome and discuss general strategies for adapting to commensal/symbiotic life-style employed by this taxon. Some elaborations on pathways go on for several paragraphs and feel unnecessarily stretched, which made those sections of the paper rather difficult to digest. This might be also be because the work, and all conclusions drawn, depend entirely on incomplete (ca. 70-80%) genome data and simple similarity searches, and e.g. no kind of biochemistry or imaging is presented to underpin the manuscripts discussion. This is noteworthy in light of other protist genome reports published in the last few years that differ in this respect, including previous work by this group. And for sequencing-only data, this paper - https://doi.org/10.1016/j.dib.2023.108990 - might offer an example of where we are at in 2023. With respect to previous work of the group (Karnkowska et al. 2016 and 2019), this submission is very similar (analysis pattern, even some figures and more or less the conclusion), i.e. to say, the overall progress for the broader audience is rather incremental. Then there are also some incidents, where the data presented conflicts with the authors own interpretation. The text (including spelling and grammar) needs some attention and the choice of words is sometimes awkward. The overuse of quotation marks ("classical", "simple", "fused", "hits", "candidate") is confusing (e.g. was the BLAST result a hit or a "hit").

      In its current form the manuscript is, unfortunately, very difficult to review. This reviewer had to make considerable efforts to go through this very large manuscript, mainly because of issues affecting to the presentation and the lack of clarity and conciseness of the text. It would be greatly appreciated if the authors would make more efforts upfront, before submission, to make their work more easily accessible both to readers and facilitate the task of the reviewers.

      About a fifth of the two genome is missing according the authors prediction (table 1). Early on they explain the (estimated) incompleteness of the genomes to be a result from core genes being highly divergent. In light of this already suspected high divergence, using (the simplest NCBI) sequence similarity approach to call out the absence of proteins (for any given lineage) may need lineage-specific optimization. The use of more structural motif-guided approaches such as hidden Markov models could help, but it is not clear whether it was used throughout or only for the search for (missing) mitochondrial import and maturation machinery. The authors state that the low completeness numbers are common among protists, which, if true, raises several questions: how useful are then such tools/estimates to begin with and does this then not render some core conclusions problematic? The reader is just left with this speculation in the absence of any plausible explanation except for some references on other species for which, again, no context is provided. Do they have similar issues such as GC-content, same core genes missing, phylogenetic relevance?, etc.. No info is provided, the reader is expected to simply accept this as a fact and then also accept the fact that despite this flaw, all conclusions of the paper that rests on the presence/absence of genes are fine. This is all odd and further skews the interpretations and the comparative nature of the paper.

      As a side note, this will also influence the number of proteins absent in other lineages and as such has consequences on LGT calls versus de novo invention. For the cases with LGT as an explanation, it would help to briefly discuss the candidate donors and some details of the proteins in the eco-physiological context (e.g. lines 263-268 suggest that HPAD may have been acquired by EGT which was facilitated by a shared anaerobic habitat and also comment on adaptive values for acquiring this gene). Exchanging metabolic genes via LGT (Line 163) blurs the differences between roles and extent of LGT in prokaryote vs eukaryote, and therefore is exciting and could use support/arguments other than phylogenies. I guess the number of reported LGTs among protists (whatever the source) over the last decade has by now deflated the novelty of the issue in more general; a report of the numbers is expected but they alone won't get you far anymore in the absence of a good story (such as e.g. work on plant cell wall degrading enzymes in beetles). It would help to clarify which parts of the mitochondrial ancestor were reduced during the process of reductive evolution at what time in their hypothesized trajectory. For instance, loosing enzymes of anaerobic metabolism conflicts with the argued case of an aerobic (as opposed to facultative anaerobic) mitochondrial ancestor followed by gains of anaerobic metabolism in the rest of the eukaryotes via LGT, and some papers the authors themselves cite (e.g. the series by Stairs et al.). There is no coherent picture on LGT and anaerobic metabolism, although a reader is right to expect one.

      In light of their data the authors also discuss the importance of the mitochondrion with respect to the origin of eukaryotes:

      First, the mitochondrion brought thousands of genes into the marriage with an archaeon, surely hundreds of which provided the material to invent novel gene families through fusions and exon shuffling and some of which likely went back and forth over the >billion years of evolution with respect to localizations. The authors look at a minor subset of proteins (pretty much only those of protein import, Fig. 6) to conclude, in the abstract no less: „most strikingly the data confirm the complete loss of mitochondria and every protein that has ever participated in the mitochondrion function for all three oxymonad species." I do not question the lack of a mitochondrion here, but this abstract sentence is theatrical in nature, nothing that data on an extant species could ever proof in the absence of a time machine, and is evolutionary pretty much impossible. A puzzling sentence to read in an abstract and endosymbiont-associated evolution.

      Second, using oxymonads as an example that a lineage can present eukaryotic complexity in the absence of mitochondria and conflating it with eukaryogenesis is a logical fallacy. This issue already affected the 2019 study by Hampl et al.. We have known that a eukaryote can survive without an ATP-synthesizing electron transport chain ever since Giardia and other similar examples and the loss of Fe-S biosynthesis and the last bit of mitosome (secondary loss) doesn't make a difference how to think about eukaryogenesis. It confuses the need and cost to invent XYZ with the need and cost of maintenance. How can the authors write "... and undergo pronounced morphological evolution", when they evidently observe the opposite and show so in their Fig. 1? The authors only present evidence for reductive evolution of cellular complexity with the loss of a stacked Golgi. What morphological complexity did oxymonads evolve that is absent in other protists? A cytosolic metabolic pathway doesn't count in this respect, because it is neither morphological, nor was it invented but likely gained through LGT according to the authors. This is quite confusing to say the least. A recent paper (https://doi.org/10.7554/eLife.81033) that refers to Hampl et al. 2019 has picked this up already, and I quote: "Such parasites or commensals have engaged an evolutionary path characterized by energetic dependency. Their complexity might diminish over evolutionary timescale, should they not go extinct with their hosts first." Here the authors raise a red flag with respect to using only parasites and commensals that rely on other eukaryotes with canonical mitochondria as examples. If we now look at Fig. 1 of this submission, Novak et al. underpin this point perfectly, as the origin of oxymonads is apparently connected to the strict dependency on another eukaryote (or am I wrong?), and they support the prediction with respect to complexity reducing after the loss of mitochondria - mitosome gone, Golgi almost gone. What's next? This is a good time to remember that extant oxymonads are only a single picture frame in the movie that is evolution, and their evolution might be a dead-end or result in a prokaryote-like state should they survive 100.000s to millions of years to come.

      Some more thoughts:

      Line 47-52: Hydrogenosome or mitosome is a biological and established label as (m)any other and I find the use of the word "artificial" in this context strange. While the authors are correct to note that there is a (evolutionary) continuum in the reduction - obviously it is step by step - they exaggerate by referring to the existing labels as "artificial". You make Fe-S clusters but produce no ATP? Well, then you're a mitosome. It's a nomenclature that was defined decades ago and has proven correct and works. If the authors think they have a better scheme and definition, then please present one. Using the authors logic, terms such as amyloplast or the TxSS nomenclature for bacterial secretions systems are just as artificial. As is, this comes across as grumble for no good reason.

      Line 158: A duplication-divergence may also explain this since sequence similarity-based searches will miss the ancestral homologues.

      Lines 201-202: Presence of GCS-L in amitochondriate should be explained in light of this group once having a mitochondrion, which then makes ancestral derivation and differential loss (as invoked for Rsg1) also a likely explanation along with eukaryote-to-eukaryote LGT.

      Lines 356-392: Describes plenty of genomic signal for Golgi bodies but simultaneously cites literature suggesting the absence of a morphologically an identifiable Golgi in oxymonads. An explicit prediction regarding what to observe in TEM for the mentioned species might be nice to stimulate further work.

      Lines 414: The preceding paragraphs in this result section describes only the distribution, without mentioning origins - a sweeping one-line summary that proclaims different origin needs some context and support. Furthermore, the distribution of glycolytic enzymes might indeed be patchy, but to suggest it represents an 'evolutionary mosaic composed of enzymes of different origins' without discussing the alternative of a singular origin and different evolutionary paths (including a stringer divergence in one vs. another species) discredits existing literature and the authors own claim with respect to why BUSCO might fail in protists.

      Line 486: How uncommon are ADI and OTC in lineages sister to metamonada?

      Line 504: It might help an outside reader to include a few lines on consequences and importance of having 2Fe-S vs 4Fe-S clusters and set an expectation (if any) in Oxymonads

      Any explanations on what unique selection pressures and gene acquisition mechanisms may be operating in P. pyriformis which might allow for the unique metabolic potential?

      ** Referees cross-commenting**

      To R3: Hampl et al. 2019, to which Novak et al. refer, is about eukaryogensis and that is exactly the context in which this is discussed again and what Raval et al. 2022 had decided to touch upon. If the authors do not bring this up in light of the ability to evolve (novel) eukaryote complexity, then what else? Maybe they can elaborate, especially with respect to energetics to which they explicitly refer to in 2019 (and here). And with respect to text-book eukaryotic traits (and the evolution of new morphological ones), I do not see any new ones evolving in any oxymonad, but reduction as Novak et al. themselves picture it in this submission. Is a change in the number of flagella pronounced morphological evolution? Maybe for some, but I believe this needs to be seen in light of the context of how they discuss it. I see a reduction of eukaryotic complexity and not a gain. They have an elaborate section on the loss of Golgi characteristics (and a figure), but I fail to read something along the same lines with respect to the gain of new morphological traits. Again, novel LGT-based biochemistry does not equal the invention of a new morphology such as a new compartment. Oxymonads depend on mitochondria-bearing eukaryotes for their survival or don't they? This is the main point, and if evidence show that I am wrong, then I will be the first to adapt my view to the data presented.

      I have concerns with the presentation of a narrative that in my opinion is too one-sided and that has been has been publicly questioned in the community (in press, at meetings, personally). For the benefit of science and of the young authors on this study, this reviewer feels strongly that these issues should be taken very seriously and discussed openly in a more balanced way. . We only truly move forward on such complex topics, if we allow an open and transparent discussion.

      Having said that, I am happy that R3 has picked up exactly the same major concerns as I did with respect to e.g. the phrasing on mito (gene) loss and the BUSCO controversy.

      Significance

      Using draft genome sequencing of the free-living Paratrimastix pyriformis and the sister lineage oxymonad Blattamonas nauphoetae, Novack et al. infer the metabolic potential of the two protists using comparative genomics. The authors conclude that the common oxymonad ancestor lost the mitochondrion/mitosome and discuss general strategies for adapting to commensal/symbiotic life-style employed by this taxon. Some elaborations on pathways go on for several paragraphs and feel unnecessarily stretched, which made those sections of the paper rather difficult to digest. This might be also be because the work, and all conclusions drawn, depend entirely on incomplete (ca. 70-80%) genome data and simple similarity searches, and e.g. no kind of biochemistry or imaging is presented to underpin the manuscripts discussion.

    1. If you haven’t read any of his novels, it’s safe to describe Palahniuk’s characters and stories as dirty. It’s dark humor and appropriately the descriptions of the smells are not heavenly. He doesn’t describe the nice smell of perfume, but instead “smell a hint of Chanel No. 5 perfume mixed with his BO.” It’s not enough to say a dirty bedroom smells, but that it has the same smell as “tennis shoes in September after he’s worn them all summer without socks .” Palahniuk doesn’t just settle at describing the scent of someone’s bad breath, but instead makes note that it “smelled like a burp after you’ve ate pork sausage for breakfast.”

      detailed descriptions of smells

    1. winnicott once said you know there's no such thing as a baby there's only a baby and someone
      • "gestation rewires your brain in fundamental ways um you it rewire it primes you for caretaking as a as a mother in a way which is far more visceral and far it's it's pre-rational it's it's immensely transformative experience and it's permanent you know once you've been rewired for mummy brain you'd never really go back um and that from the point of view of raising a child that matters um because when after a baby is born it's you know as winnicott once said you know there's no such thing as a baby there's only a baby and someone there's a a baby doesn't exist as an independent entity until it's some years some years into its life arguably quite a few years into its life um and what I would say about artificial wounds is that you may be you may think that what you're doing is creating a baby without the misery of gestation but what you're doing in practice is creating a baby without creating a mother because a pregnancy doesn't just create a baby it also creates a mother"

      • Comment

    2. I don't know that we can assume that some point A Thousand Years in the future is going to have the same moral political economic or social priorities 00:41:36 as we do
      • Good insight on the absurdity of Longtermism from Mary Harrington
        • " I don't know that we can assume that some point a Thousand Years in the future
        • is going to have the same moral political economic or social priorities
        • as we do
        • It's very very clear even the most rudimentary grasp of history or literature
        • ought to make it clear that
          • people a thousand years ago didn't have the same priorities as us now and
          • if you can you can frame that difference as progress in our favor
          • or as decline in their favor
          • but it's it's very clear that Consciousness you've evolved and culture evolves over time and
          • there are there are threads of continuity and that's something that you and I both have in common
          • tracing some of those lines but
          • it's very clear that what how people think about what's important changes tremendously over over even a century,
          • let alone over a thousand years
          • so I I question the hubris of any movement which claims
          • to have a have any kind of handle on on what might matter in 25 000 years time
          • I just don't see how you can do that
          • it's absurd."
    1. whether you wake or sleep, you will live with him

      It seems Dr. Piper is equating sleeping, here, with death, and implying that we needn't fear death because it's not real.

      I used to fear death, when I believed there was an afterlife and I was plagued with doubts about whether I would be playing the harp in the clouds, or suffering eternal torture. Once I realized there isn't anything after death, I was able to understand that dying is just like not being born yet. I've already experienced that.

      The only fear left, really, is the fear of a painful death. But, I have a fear of painful life, too, so I have to keep dealing with that one.

    1. language needs to evolve toward the visual and that's why I'm very keen for technically against prosthetic environments where every time 01:00:18 you say the word and a yellow three-dimensional triangle appears in the air every time you stay or an orange ball appears a computer is listening to what you're saying and giving a 01:00:31 geometric accompaniment to speech I think that there are forms of telepathy that we can evolve through the use of drugs and computer-assisted technologies that will allow us to see each other's 01:00:45 dreams in spite of your correct assessment that I'm Keen for the spoken word I spend all summer learning modeling and three-dimensional animation programs from my son 01:00:58 because I want to animate I want to model I see things on my trips that I have never been able to English but that if I were a fully competent modeler and animator I would just say 01:01:13 check it out and I'm going to do that and and I urge you to do that I mean it's a funny thing to be told you want to spiritually Advance the study 01:01:25 3D animation but these are the frontiers of communication we have an obligation to make our language more immediate it is the most Godlike thing we do if you're looking for the thumbprint of 01:01:39 almighty God on the biological organization of this planet it is human language it is a miracle I don't give a hood what the Dolphins and the honeybees are out there in the woods doing it 01:01:51 ain't like Milton it ain't even like Bob Dylan it ain't even as good as this I'm willing to say uh no human human communication is what

      visual

    1. @chrisaldrich I think the is an underated idea more broadly. I would love to see this done with other authors books that use an index card system, like Robert Greene. I think it would be a useful illustration to help people better understand the research and writing process. I've been wanting to and created a few experimental vaults where I do a similar thing except for a podcast (all of Sean Carroll's Mindscape transcripts are free) or a textbook (Introduction to Psychology). But I never followed through on the projects just because of how much work it takes to due it right. This also makes me wish for a social media type zettelkasten, where a community can keep a shared vault, creating a social cognition of sorts. I know this was kind of happening with the shared vaults Dan Alloso was experimenting with but his seemed more focused than random/chaotic. I'm also not sure if he continued it for later books.

      Reply to Nick at https://forum.zettelkasten.de/discussion/comment/17926/#Comment_17926

      Some pieces of social media come close to the sort of sense making and cognition you're talking about, but none does it in a pointed or necessarily collaborative way. The Hypothes.is social annotation tool comes about as close to it as I've seen or experienced beyond Wikipedia and variations which are usually a much slower boil process. As an example of Hypothes.is, here's a link to some public notes I've been taking on the "zettekasten output problem" which I made a call for examples for a while back. The comments on the call for examples post have some rich fodder some may appreciate. Some of the best examples there include videos by Victor Margolin, Ryan Holiday (Robert Greene's protoge), and Dustin Lance Black along with a few other useful examples that are primarily text-based and require some work to "see".

      For those interested, I've collected a handful of fascinating examples of published note collections, published zettelkasten, and some digitized examples (that go beyond just Luhmann) which one can view and read to look into others' practices, but it takes some serious and painstaking work. Note taking archaeology could be an intriguing field.

      Dan Allosso's Obsidian book club has kept up with additional books (they're just finishing Rayworth's Doughnut Economics and about to start Simon Winchester's new book Knowing What We Know, which just came out this month.) Their group Obsidian vault isn't as dense as it was when they started out, but it's still an intriguing shared space. For those interested in ZK and knowledge development, this upcoming Winchester book looks pretty promising. I'd invite everyone to join if they'd like to.

    1. Files which render themselves when published (e.g. templates or other scripts) will be rendered when accessed from a mounted WebDAV volume. This is because WebDAV clients issue a GET (it's an extension of HTTP, after all) to hand you your data. You can't simply mount a WebDAV share and start editing PHP files, for example. Until a data type is provided for source code-based documents, this will remain a problem.

      This is a node-/organization-level information architecture problem.

      If /foo.php is a script that generates a Web page, then separate identifiers need to be assigned for each resource (one for the document itself, and one for the script that generates it). It is a failure of the node not to distinguish between the two. A separate content type would not solve this problem—it would just appear to cover it up (as well as create new ones).

  9. www.3x5life.com www.3x5life.com
    1. BJ Fogg is one of the leading authorities on habit change.  In his best selling book Tiny Habits he says: “Celebration will one day be ranked alongside mindfulness and gratitude as daily practices that contribute most to our overall happiness and well-being. If you learn just one thing from my entire book, I hope it’s this: Celebrate your tiny successes. This one small shift in your life can have a massive impact even when you feel there is no way up or out of your situation. Celebration can be your lifeline.”

      https://www.3x5life.com/pages/faq

    1. I used to think that if we just gave people a voice and helped them connect, that would make the world better by itself. In many ways it has. But our society is still divided. Now I believe we have a responsibility to do even more. It’s not enough to simply connect the world, we must also work to bring the world closer together.

      I think platforms such as Facebook Meta is a power social media source that is used worldwide to make posts and shares however, recently I feel as there has been more misinformation and hate that is spread online.

    1. They assume that it's worth someone's time to keep up with updates every month or two. But situated software doesn't have those kinds of surpluses. It requires programs to just work once built, with little maintenance

      I think there's a category error here.

    2. incompetence

      This accounts for ~all programmers. It's not just a matter of people presenting themselves as having credentials that are just backed up by monkey-see-monkey-do IT cargo cultism. Programmers write bugs.

      It's not really clear what this section has to do with the overall talk. How is this (specifically the part about all programmers creating bugs) mitigated or addressed by the contents of this talk?

    1. The abductees taught me that peo-ple go through life trying on belief systems for size. Some of thesebelief systems speak to powerful emotional needs that have littleto do with science—the need to feel less alone in the world, the de-sire to have special powers or abilities, the longing to know thatthere is something out there, something more important thanyou that’s watching over you. Belief in alien abduction is not justbad science. It’s not just an explanation for misfortune and a wayto avoid taking responsibility for personal problems. For manypeople, belief in alien abduction gratifies spiritual hungers. It re-assures them about their place in the universe and their own sig-nificance.

      YESSIR

    Annotators

    1. I never thought about the specific differences between shame and guilt. I think it’s very important to learn how to separate the two and realizing that just because you did a bad thing doesn’t inherently make you a bad person. It also makes me realize that the phrase “shame on you” is kind of messed up

    1. Schadenfreude# Another way of considering public shaming is as schadenfreude, meaning the enjoyment obtained from the troubles of others. A 2009 satirical article from the parody news site The Onion satirizes public shaming as being for objectifying celebrities and being entertained by their misfortune: Media experts have been warning for months that American consumers will face starvation if Hollywood does not provide someone for them to put on a pedestal, worship, envy, download sex tapes of, and then topple and completely destroy. Nation Demands Fresh Celebrity Meat - The Onion

      I think it is often linked with unfavorable characteristics like jealousy and bitterness, Schadenfreude may also embody a feeling of fairness or balance when those deemed deserving face adversity. As with any emotion, Schadenfreude doesn't possess inherent moral qualities; it's just one element of the wide array of human emotional experiences. Its moral significance largely hinges upon the circumstances of its occurrence and the way it shapes actions and responses.

    2. In this situation, they outline the following constraints that must be considered when publicly shaming someone in this way: Proportionality: The negative consequences of shaming someone should not be worse than the positive consequences Necessity: There must not be another more effective method of achieving the goal Respect for Privacy: There must not be unnecessary violations of privacy Non-Abusiveness: The shaming must not use abusive tactics. Reintegration “Public shaming must aim at, and make possible, the reintegration of the norm violator back into the community, rather than permanently stigmatizing them.”

      I think it's interesting how these norms were developed. I think these norms will help make sure subjects or people are not just shamed but still follow morals. I think these norms will help the online community.

    1. since Ruby code can work for Crystal with just slight changes, I was able to use the best code writing practice in the world: Copy and Paste!

      This works and it's great to get up and running again. But note that you might be importing practices from Ruby that are subpar in Crystal. For example, turning the regex results into an array is unnecessary and inefficient. And it requires some extra steps in the code to handle this transformation.

    1. The term “cancel culture” can be used for public shaming and criticism, but is used in a variety of ways, and it doesn’t refer to just one thing. The offense that someone is being canceled for can range from sexual assault of minors (e.g., R. Kelly, Woody Allen, Kevin Spacey), to minor offenses or even misinterpretations.

      Cancel culture is very prevalent on online social media platforms such as Instagram or TikTok. While cancel culture can spread real information about a subject or person, I think it's also important to be aware of the content we view and make sure it's not false or misleading.

    1. Author Response

      Reviewer #1 (Public Review):

      This manuscript presents an inference technique for estimating causal dependence between pairs of neurons when the population is driven by optogenetic stimulation. The key issue is how to mitigate spurious correlations between unconnected neurons that can arise due to polysynaptic and other network-level effects during stimulation. The authors propose to leverage each neuron's refractory period (which begins at approximately random times, assuming Poisson-distributed spikes and conditional on network state) as an instrumental variable, allowing the authors to tease apart causal dependence by considering how the postsynaptic neuron fires when the presynaptic neuron must be muted (i.e., is in its refractory period). The idea is interesting and novel, and the authors show that their modified instrumental variable method outperforms similar approaches.

      We wish to thank the reviewer for this positive assessment.

      However, the scope of the technique is limited. The authors' results suggest that the proposed technique may not be practical because it requires considerable amounts of data (more than 10^6 trials for just 200 neurons, resulting in stimulation of more than 5000 times per neuron). Even with such data sizes, the method does not appear to converge to the true solution in simulations. The method is also not tested on any experimental data, making it difficult to judge how well the assumptions of the technique would be met in real use-cases. While the manuscript offers a unique solution to inferring causal dependence, its applicability for experimental data has not yet been convincingly demonstrated, and would, therefore primarily be of interest to those looking to build on these theoretical results for further method development.

      We thank the reviewer for this assessment and agree that the requirement for this many trials makes the estimators practically unsuitable for identifying causal interactions in large systems. However, in the revised manuscript, we can observe that the IV estimator can be beneficial after even a few thousand trials when introducing a newly improved error measurement (which we discovered thanks to these reviews). Moreover, we agree that this work will be of interest to the more theoretically oriented community for methodological improvements; we believe that the methods and causal inference framework will be interesting and useful for the wider neuroscience community. For example, considering the first (new) example in the introduction, even under two-photon single-neuron stimulation, the IV framework should be used to avoid bias amplification.

      Reviewer #2 (Public Review):

      Lepperød et al. consider the problem of inferring the causal effect of a single neuron's activity on its downstream population. While modern methods can perturb neuronal activity, the authors focus on the issue of confounding that arises when attempting to infer the causal influence of a single neuron while stimulating many neurons together. The authors adapt two basic methods from econometrics that were developed to address causal inference in purely observational data: instrumental variables and difference-in-differences, both of which help correct for unobserved correlations that confound causal inference. The authors propose an experimental procedure where neurons have spike times measured with millisecond precision and a subset of neurons are optogenetically activated. As an instrumental variable, the authors propose using the refractoriness of a stimulated neuron, resulting in absent or delayed spiking which can be used to infer its causal effect in otherwise matched conditions.

      Based on this, they develop a collection of estimators to measure the pairwise causal relationship of one neuron on another. By simulating a variety of small networks, the authors show that, provided enough data is present, the proposed causal methods provide estimates that better match underlying connectivity than methods based on ordinary least squares or naive cross-correlograms (CCHs). However, the methods proposed require extensive data and highly targeted stimulation to converge.

      Strengths:

      The value of the paper comes from its attempt to find neuroscience applications for methods from fields where causal analysis of observational data is required. Moreover, as the field develops improved methods of measuring anatomical neuronal connectivity using molecular, physiological, and structural approaches, the question of the causal influence of one neuron's spiking on another remains vital. The authors thoughtfully lay out the necessary conditions - and difficulties - required to establish this type of causal functional influence and suggest one potential approach. The collection of models tested highlighted both the strengths and difficulties of the suggested approaches.

      We wish to thank the reviewer for the positive feedback, we are delighted to share your view that obtaining methodology for estimating causal influence is vital.

      Weaknesses:

      1) I found the paper's introduction to its analysis techniques to be very confusingly written, particularly as it is designed to bridge fields. It is vital that the ideas are communicated more clearly. Some topics are explained multiple times, even after being used previously, other ideas and notations are introduced and immediately dropped (e.g. the "do operator", the ratio of covariances in the introduction to instrumental variables), and still others are introduced with no clear explanation (e.g. the weight term w, the "|Y->Y-Y*" notation, and the notation in the methods with "Y(Z=0)").

      We thank the reviewer to point out this lack of clarity and we extensively rewrote the paper to make it more accessible. The do operator is used in the methods to define Y(Z=0), but is now removed from the introduction to reduce the number of concepts introduced early in the text. The w term is now defined from the generative model. The difference in differences notation is written out fully to be clear and a sketch of the method intuition is added to Figure 1.

      1) Of particular importance, the introduction of the Z,X, and Y variables in the first full paragraph on page five, it could be made much more clear that this method is pairwise: Z and X reference the spiking of one specific stimulated neuron at two time points and Y references one specific downstream neuron. 2) In the third paragraph of the same page, the authors refer to the "refractoriness of X" and "spiking of X onto Y", but this language confuses the neurons with variables in a way that took considerable time to unpack. 3) This was not helped by Figure 1b, which suggested that Z_i, X_i, and Y_i applied to all neurons and merely reflected time points around stimulation. 4) Similarly, the introduction of the Y* variable in the difference of differences method, which the authors view as one of the main contributions, is given little clear explanation or intuition. I assume "shifted on window-size left" means measuring the presence of spiking at the same time step as X, but I see no clear definition of this. 5) The confusion about variables remains when, in Figure 1d, a "transmission probability" goes below 0 and above 1.

      1) Thank you for pointing out this lack of clarity, the suggested explanation of the variables XYZ is adopted.

      2) The language is clarified such that variables and neurons are separated.

      3) Figure is fixed such that variables refer to the neurons they represent.

      4) We have now improved the explanation of DiD with a figure for intuition.

      5) We have now redefined the “transmission probability” to effective connectivity to reduce confusion.

      I also found the network models studied after the first section and the relevant variables difficult to understand with the detail necessary to interpret the results. For example, the cartoon in Figure 2a does not seem to match the text description. I see no explanation for the external "excitatory confounder" and "inhibitory confounder" terms, nor what is done to control the (undefined) \sigma_max/\sigma_min term. I don't see anything in the methods about distinct inhibitory and excitatory neurons either. Further, the violin plots (e.g. Fig 2d) seem quite noisy (e.g. is Br, DiD really bimodal?), and it is not clear what distribution is being covered by them. If this is computational simulations, I would imagine more samples could be generated. The same vagueness issues hold for the networks in section 2.4 and 2.7.

      We have now clarified the implementation of the excitatory and inhibitory confounder and how we distinguish between excitatory and inhibitory neurons and defined the condition number. The violin plots were removed in Fig 2 since the large variance represented changes across external drive which produced largely incomparable statistics. To illustrate variance, we now show the standard deviation of the absolute error in line plots 2e and 2g.

      2) Broadly speaking, the causal estimates appear better in the sense of having smaller errors, but it's not clear to me if they are actually good or not. What does an error of 0.4 mean in terms of your ability to estimate the causal structure, and what exactly does the Error(w{greater than or equal to}0) notion refer to? It would be useful to see actual reconstructions of ground truth versus causally inferred connectivity to better understand the method's strengths and weaknesses.

      To improve clarity, we have added a paragraph in the text before figure 2 explaining a new error measure. Since the estimators give the transmission probability and not the inferred connection strength directly, we previously computed a regressed error as in Das & Fiete 2020. This error measure is equivalent to the sine of the angle between $W$ and $\hat{W}$. This error measure is not ideal and gives an indirect population measure with deviations scaled during the error regression. Upon further reflection, we realized that we could define the error directly using our definition of effective connectivity on the generative model to obtain a much cleaner and more interpretable measure. This further led us to remove one of the proposed methods (brew) as it did not perform well under this new error measure. All error measurements are updated in all figures. Error(w{greater than or equal to}0) means that we only look at positive weights; now clarified in the text

      3) I found the section on optogenetic modeling to be unsatisfying in its realism. The general result that 1 photon excitation hits a wide collection of neurons is undisputed, but the simulation does not account for a number of key factors - optogenetic receptor expression is distributed across the axons and dendrites of a cell, not only soma, scattering in tissue greatly affects transmission, etc. Moreover, experiments that attempt to do highly targeted activation have other methods for exactly this reason, such as multiphoton activation or electrophysiology. The message of decreasing performance as a function of stimulus size is important, but I struggle with the idea of the model being "realistic".

      We thank the reviewer for pointing out this unsatisfactory comparison with realistic scenarios. To mitigate we have changed the wording, but kept the simulation as is. As the reviewer pointed out optogenetic receptor expression is distributed, and here we have assumed an expression that only affects soma (experimentally plausible according to Grødem et al 2023 (10.1038/s41467-023-36324-3)), scattering in tissue is included according to the Kubelka-Munk model.

      4) The authors spend a great deal of analysis of stimulation, but little time on measurement. It seems like this approach demands a highly precise measure of spike time to know if a neuron is firing or not at a given millisecond due specifically being in a refractory state. A stimulated but refractory neuron will still likely spike as soon as it can after the momentary delay, and given the noise in the network this difference might not be easily detectable in the delay-to-spike of the downstream neuron, even assuming one spike in the presynaptic neuron is likely to cause a spike in the downstream. It would be useful to see this aspect considered with the same detail as the rest of the study.

      We thank the reviewer for pointing out this. We have now added a paragraph discussing this: “As outlined in \citep{ozturk2000ill}, ill-conditioning can affect statistical analysis in three ways and therefore similarly in inverse connectivity estimates from measured activity. First, measurement errors such as a temporal shift in spike time estimate e.g. due to low sampling frequency, inaccurate spike sorting, or general noisy measurement due to animal movement etc. In the presence of ill-conditioning the outputs will be sensitive (unstable) to small input changes. If errors are included in some variables, the inference procedures will require information about the distributional properties of these errors. Second, optimized inference can give misleading results in the presence of ill-conditioning, caused by bad design or sampling.

      There will always exist a natural variability in the observations which necessitates the assessment of ill-conditioning before performing statistical analysis. Third, rounding errors can lead to small changes in input under ill-conditioning. This numerical problem is often not considered in neuroscience but will become evermore relevant when large-scale recordings require large-scale inferences.”

    1. Mastodon (Fediverse

      I don't really see the fediverse taking off because it's only really pushed by a specific set of people. Normal everyday people don't care about how a social media website is hosted they just care that the website works.

    1. Why is demographic math so difficult? One recent meta-study suggests that when people are asked to make an estimation they are uncertain about, such as the size of a population, they tend to rescale their perceptions in a rational manner. When a person’s lived experience suggests an extreme value — such as a small proportion of people who are Jewish or a large proportion of people who are Christian — they often assume, reasonably, that their experiences are biased. In response, they adjust their prior estimate of a group’s size accordingly by shifting it closer to what they perceive to be the mean group size (that is, 50%). This can facilitate misestimation in surveys, such as ours, which don’t require people to make tradeoffs by constraining the sum of group proportions within a certain category to 100%. This reasoning process — referred to as uncertainty-based rescaling — leads people to systematically overestimate the size of small values and underestimate the size of large values. It also explains why estimates of populations closer to 0% (e.g., LGBT people, Muslims, and Native Americans) and populations closer to 100% (e.g., adults with a high school degree or who own a car) are less accurate than estimates of populations that are closer to 50%, such as the percentage of American adults who are married or have a child.

      Or. perhaps, it's just rampant civic ignorance. I think there's a significant portion of the population who just don't care to be informed about the demographics of their own countries.

    1. So now, it’s your turn to think about how you would want a retraction feature to work on a social media site like Twitter:

      My retract feature would be quite simple. If a user posts a retraction, there will be a red box under the tweet that contains the original tweet that has "RETRACTED" written at the top. This would bring the focus towards the apology rather than the original tweet. Tweeters can edit retractions just like normal tweets. People who replied or engaged with the tweet for a significant amount of time will get a notification about the retraction.

    1. Author Response:

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

      We sincerely thank all the editors and reviewers for taking the time to evaluate this study. Here is our point-by-point response to the reviewers’ comments and concerns.

      Reviewer #1 (Public Review):The study by Oikawa and colleagues demonstrates for the first time that a descending inhibitory pathway for nociception exists in non-mammalian organisms, such as Drosophila. This descending inhibitory pathway is mediated by a Drosophila neuropeptide called Drosulfakinin (DSK), which is homologous to mammalian cholecystokinin (CCK). The study creates and uses several Drosophila mutants to convincingly show that DSK negatively regulates nociception. They then use several sophisticated transgenic manipulations to demonstrate that a descending inhibitory pathway for nociception exists in Drosophila.

      […]

      Weaknesses:

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

      We thank the reviewer for the kind and very positive evaluation of our manuscript. We agree that this study has not elucidated the intracellular molecular pathway(s) downstream of CCKLR-17D1 that are involved in the regulation of the activity of Goro neurons, and we think that it would definitely be an interesting topic for future research.       

      Reviewer #1 (Recommendations For The Authors):

      The response latencies for the control yw larvae seem large, with many larvae appearing to be insensitive to the thermal stimulus. Is this just an effect of the yw genetic background? A brief discussion of this might be helpful.

      We thank the reviewer for pointing this out. We have also noticed that the yw control larvae tend to show longer response latencies than the other control strains, and in the revised manuscript, we have added the following sentence in the Result section (Lines 91–94):

      “We have noticed that the yw control strain, which was used by us to generate the dsk and receptor deletion mutants, showed relatively longer response latencies to the 42 °C probe compared to the other control strains used in this study. This may be attributed to the effect of the genetic background, although, presently, the cause for this difference is unknown.”

      Reviewer #2 (Public Review):_

      This is an exceptional study that provides conclusive evidence for the existence of a descending pathway from the brain that inhibits nociceptive behavioral outputs in larvae of Drosophila melanogaster. […] The study raises many interesting questions for future study such as what behavioral contexts might depend on this pathway. Using the CAMPARI approach, the authors do not find that the DSK neurons are activated in response to nociceptive input but instead suggest that these cells may be tonically active in gating nociception. Future studies may find contexts in which the output of the DSK neurons is inhibited to facilitate nociception, or contexts in which the cells are more active to inhibit nociception._

      Reviewer #2 (Recommendations For The Authors):I have no recommendations for the authors as this is a very complete and thoroughly executed study. The writing is crystal clear.

      We thank the reviewer for the kind and very positive evaluation of our manuscript. We are happy to know that our current manuscript was deemed to be clear and convincing by the reviewer.

      Reviewer #3 (Public Review):[…] Overall the authors use clean logic to establish a role for DSK and its receptor in regulating nociception. I have made a few suggestions that I believe would strengthen the manuscript as this is an important discovery.

      Major comments:

      1. It's not completely clear why the authors are staining animals with an FLRFa antibody. Can the authors stain WT and DSK KO animals with a DSK antibody? Also, can the authors show in supplemental what antigen the FLRFa antibody was raised against, and what part of that peptide sequence is retained in the DSK sequence? This overall seems like a weakness in the study that could be improved on in some way by using DSK-specific tools.

      We thank the reviewer for this query. We would like to clarify that we first tried the FLRFa antibody to visualize an RFamide-type neuropeptide other than DSK in Drosophila and found that the staining pattern is quite similar to that of anti-DSK, as shown by Nichols et al. [1]. According to the original paper describing the anti-FLRFa antisera [2] (already cited in the reviewed manuscript), the antigen used to raise it was the Phe-Met-Arg-Phe-NH2 peptide conjugated with succinylated thyroglobulin, and the study experimentally shows that the antibody well binds to peptides containing Met-Arg-Phe-NH2 or Leu-Arg-Phe-NH2 sequence and has 100% cross-reactivity to FLRFa. As DSK contains Met-Arg-Phe-NH2 sequence [3], the cross-reaction of this antibody to DSK is consistent with the description of the original study.    

      Although we were unable to use an antibody specific to DSK, our staining data with dsk deletion mutants and the expression pattern of DSK-2A-GAL4 corroborate each other (Figure 2 and Figure 2-figure supplement 1), which we believe provides compelling evidence for the specific expression of DSK in MP1 and Sv neurons, and for that DSK-2A-GAL4 is a reasonably effective tool to specifically manipulate DSK-expressing neurons.

      2. What is the phenotype of DSK-Gal4 x UAS-TET animals? They should be hyper-reactive. If it's lethal maybe try an inducible approach.

      We thank the reviewer for this question. Unfortunately, we have not attempted this experiment, although we agree that this would be a nice addition to further strengthen the study if TET worked well in the DSKergic neurons.

      3. Figure 9. This was not totally clear, but I think the authors were evaluating spontaneous (i.e. TRPA1-driven) rolling at 35C. The critical question is "does activating DSK-expressing neurons suppress acute heat nociception" and this hasn't really been addressed. The inclusion of PPK Gal4 + DSK Gal4 in the same animal kind of clouds the overall conclusions the reader can draw. The essential experiment is to express UAS-dTRPA1 in DSK-Gal4 or GORO-Gal4 cells, heat the animals to ~29C, and then test latency to a thermal heat probe (over a range of sub and noxious temperatures). Basically prove the model in Figure 10 showing ectopic activation or inhibition for each major step, then test heat probe responses.

      We thank the reviewer for suggesting ideas for alternative experiments to potentially strengthen our conclusion. Regarding experiments using heat probes, previous studies have demonstrated that (i) Blocking ppk1.9-GAL4-positive C4da neurons almost completely abolishes the larval nociceptive response to local heat stimulations [4]; (ii) Local heat stimuli above 39 °C readily activate C4da neurons and larval nociceptive rolling [5-9]; and (iii) Thermogenetically or optogenetically activating these neurons is sufficient to trigger Goro neurons and larval rolling [4, 10-12]. Thus, it has now been made clear that heat probes induce larval nociceptive rolling via excitation of the C4da pathway, and we believe that our experiments using thermogenetic activation of C4da neurons can be safely interpreted as an alternative to experiments using heat probes. Using heat probes demands a more complicated experimental set-up to be combined with CaMPARI imaging experiments, and this is another reason why we preferred to take the thermogenetic approach.

      We have also considered the experiment using Goro-GAL4 instead of ppk-GAL4. However, if dTRPA1 artificially activates Goro neurons far downstream of the neuronal mechanism by which MP1 activation suppresses Goro neuron activity, the effect of MP1 activation may be bypassed and masked. As we currently do not know the epistasis between dTRPA function and the effect of MP1 activation in modulating the activity of Goro neurons, we rather chose to activate C4da neurons by using ppk-GAL4, which likely resulted in more natural activation of Goro neurons than dTRPA1-triggered direct activations.

      4. It would also then be interesting to see how strong the descending inhibition circuit is in the context of UV burn. If this is a real descending circuit, it should presumably be able to override sensitization after injury.

      Indeed, this is an interesting avenue to explore in future studies to understand the type of situation in which the DSKergic descending system functions to control nociception.

      Reviewer #3 (Recommendations For The Authors):Overall this is a good story and the claims are generally supported with experimental evidence. The way to really improve this study would be to use more precise and definitive tools, like specific antibodies, specifically targeted genes, and better temporal control of the descending circuit to prove this is inducible sufficient to suppress acute thermal nociception and this occurs only via a descending pathway, etc. However this would be exponentially more work, and so the authors I guess need to weigh the cost-benefit of definitive proof vs. strong evidence for their claims. Overall I think this study will be the beginning of a new line of inquiry in the field that has the potential to guide our understanding also of mammalian descending pathways, and as such, this study is of value to the community.

      We appreciate the reviewer’s multiple interesting ideas for experiments that could have been performed to further reinforce our findings. We agree that some experiments that the reviewer suggested would potentially strengthen this work if supplemented. However, as aforementioned, in our humble opinion, we think that the experiments that the reviewer suggested are either outside the scope of this paper or have no significant benefits over the experiments that were already conducted, and hence are not essential to the present study.

      References

      1. Nichols, R. and I.A. Lim, Spatial and temporal immunocytochemical analysis of drosulfakinin (Dsk) gene products in the Drosophila melanogaster central nervous system. Cell Tissue Res, 1996. 283(1): p. 107-16.

      2. Marder, E., et al., Distribution and partial characterization of FMRFamide-like peptides in the stomatogastric nervous systems of the rock crab, Cancer borealis, and the spiny lobster, Panulirus interruptus. J Comp Neurol, 1987. 259(1): p. 150-63.

      3. Nassel, D.R. and M.J. Williams, Cholecystokinin-like peptide (DSK) in Drosophila, not only for satiety signaling. Front Endocrinol, 2014. 5.

      4. Hwang, R.Y., et al., Nociceptive neurons protect Drosophila larvae from parasitoid wasps. Curr Biol, 2007. 17(24): p. 2105-2116.

      5. Tracey, W.D., Jr., et al., painless, a Drosophila gene essential for nociception. Cell, 2003. 113(2): p. 261-73.

      6. Xiang, Y., et al., Light-avoidance-mediating photoreceptors tile the Drosophila larval body wall. Nature, 2010. 468(7326): p. 921-6.

      7. Burgos, A., et al., Nociceptive interneurons control modular motor pathways to promote escape behavior in Drosophila. eLife, 2018. 7.

      8. Honjo, K. and W.D. Tracey, Jr., BMP signaling downstream of the Highwire E3 ligase sensitizes nociceptors. PLoS Genet, 2018. 14(7): p. e1007464.

      9. Im, S.H., et al., Tachykinin acts upstream of autocrine Hedgehog signaling during nociceptive sensitization in Drosophila. eLife, 2015. 4: p. e10735.

      10. Ohyama, T., et al., A multilevel multimodal circuit enhances action selection in Drosophila. Nature, 2015. 520(7549): p. 633-9.

      11. Honjo, K., R.Y. Hwang, and W.D. Tracey, Jr., Optogenetic manipulation of neural circuits and behavior in Drosophila larvae. Nat Protoc, 2012. 7(8): p. 1470-8.

      12. Zhong, L., et al., Thermosensory and non-thermosensory isoforms of Drosophila melanogaster TRPA1 reveal heat sensor domains of a thermoTRP channel. Cell Rep, 2012. 1(1): p. 43-55.

    1. you got it working is only half the job

      once the code works that's when you have to clean it no<br /> one writes clean code first nobody does because it's just too hard to get code to work so once the code works it will be a mess human beings do not think in Nice straight lines they don't think in if statements and while loops they cannot foresee the entire algorithm so we piece the thing together we cobble it together with wire and scotch tape and then it suddenly work so we're not<br /> quite sure why and that's the moment when you say all right now I need to clean it how much time do you invest in cleaning it roughly the same amount of time it took you to write it and that's the problem nobody wants to put that effort in because they think they're done when it works you're not done when it works you're done when it's right and if you adopted that attitude well then the<br /> code would stay clean and you would never go through the slow down

    1. function sample(), see ?sample. We can use it to simulate the random outcome of a dice roll. Let’s roll the dice! sample(1:6, 1) #> [1] 4 The probability distribution of a discrete random variable is the list of all possible values of the variable and their probabilities which sum to 111.

      Maybe it's because it's been a few years since I took a statistics course (and it was an introductory course), but I can't seem to understand it.

      • "Let's roll the dice!" helps a lot to see that we're looking at dice roll.
      • ?sample doesn't really help much; I might be able to understand the ?sample documentation if I take the time but at this point I'll look for another resource
      • Is the sum of all probabilities being 1 related to the 1 in "(1:6" or the 1 in ", 1)"? Just found out the first 1 is not related to either 1 (i.e. the "sum of all probabilities being 1" is not related to what was typed) but it was something I thought otherwise.
    1. —it’s—it’s just a little fad of mine.”

      Hewitt's stuttering is a huge indicator to the audience that something is amiss. Other than this one instance, the detective has remained a cool, confident, and put-together individual meant to be admired similarly to Holmes. Therefore, this single instance is meant to be a clue to the reader regarding the outcome of the case. Why does Hewitt choose Mr. Lloyd's room, and what could he want with sugar and a walnut?

    1. says Grace Peutherer, 24, based in Dublin. “So men must know that their friends exhibit this kind of behaviour because they’re around them all the time. Sometimes I think that they try to disassociate themselves with it because they know that it’s wrong and they don’t like to believe that they can be mates with a person who would assault women.”

      It's suspected that men are aware of their friends' signs of being an abuser since they are around them often. It is also a possibility that said men dissociate from the behavior, pretend it doesn't exist, because they don't want to believe their friends are abusers. They know it's bad, they just don't want to believe that they could be friends with someone who is capable of it. They have this sort of a defense mechanism, to block it out, deny it, try to find reasons it could be false, because they don't want to face the truth. Or maybe it's because deep down, they know it's wrong, but value their friendship enough to put a victims' story aside, essentially choosing the assaulter with full knowledge of their actions, at the end of the day proving that they do not care about victims.

    1. Conversely, limited social mobility hurts not just these children but all of society. We are leaving a vast amount of untapped talent on the table by investing unequally in our children, and it’s at all of our expense.Researchers have also used big data to uncover many specific education reforms that could lead to huge improvements. For instance, the evidence is clear that teachers are critical; my co-authors and I found that, when better teachers arrive at a school, the students in their classrooms earn around $50,000 more over each of their lifetimes. This adds up to $1.25 million for a class of 25 in just a single year of teaching.

      Slippery Slope: By implying that a lack of social mobility harms not only children but the entire society, the first phrase commits the slippery slope fallacy. Even if a lack of social mobility can have detrimental effects on both people and communities, presuming that it directly hurts society as a whole without presenting any supporting data or logic is oversimplification.

      Appeal to Consequences: By stating that limited social mobility harms not only children but the entire society, the first statement also makes use of the appeal to consequences fallacy. It means that, without taking into account the underlying reasons or potential downsides of particular remedies, action must be taken to address limited social mobility based purely on the adverse effects it may have.

      Appeal to Authority: By mentioning the "researchers" who have exploited big data to identify education innovations that potentially result in considerable advances, the second paragraph commits the error of appealing to authority. It simply relies on the authority of the researchers to persuade the reader without supplying any detailed information about the researchers, their techniques, or the validity of their findings.

      Cherry-picking: In the second paragraph, a single school reform—the value of teachers—is presented with only a few examples to support it, without noting its potential drawbacks or taking into account a wider variety of variables that affect educational outcomes. It misses out on other crucial factors that contribute significantly to academic performance by concentrating only on the effect of better teachers on students' lifetime earnings.

    1. One Synthesis employee says: “It’s been like a bad trip. I can say that the dissolution of the business was one of the most unprofessionally-handled and emotionally manipulative things I’ve ever witnessed. It has caused a lot of pain for a lot of people, and was nearly textbook 101 of how NOT to do this kind of thing. I don’t sense any intentional maliciousness—just a serious level of incompetence. Turns out you have to build your business on something more solid than a bunch of psychedelic journeys together! Heart-centered businesses can really fuck things up.”

      Indeed, especially that last point.

    1. That's my daughter, she was born June the 21st this year. I hear she's grown like a weed, she'ssaid dad for the first time 3 days ago, so she didn't say it over the phone but my wife was tellingme about it. It's very hard . Me and my wife, we've known each other since we were a lotyounger. We've been married for going on for 4 years, so it's hard but you learn not to let it eatyou alive. The time is drawing shorter, it's closer to us going home, so that makes it a little biteasier. Just try to focus on what you're doing and keep them in the back of your thoughts and inyour heart and carry on with your mission

      Family Sacrifice

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