backfired

I like this.

Nice

With the last one.

Ok

Yes.

Sensational

Yessir!

dans la présentation sur les opérateurs booléens, en page 8, le lien vers la documentation d'ISIDORE ne fonctionne pas

ça n'est pas vraiment une archive ouverte, si ?

Unité d'Appui à la Recherche

It takes AGES for Application gateway to deploy

Change headline

LA DERECHA LATINA ES EL CANCER DEL PUEBLO

r we even surprised lol

Narrativas de reproducción pero en un mundo industrializado. el planeta no está adaptado para que latam crezca econ, o que las personas se desarrollen, el sistema está creado para que latam este toda la existencia desesperado y en contexto de vulnerabilidad.

heavy af bro

sistema económico impuesto a ciertos países que rodean a los países de centro, este sistema intenta imitar la economía de los países de centro (primer mundo) para de esa forma intentar desarrollarse o servir a los países centrales.

vivimos en la pobreza porque nos han condenado a explotar nuestros recursos para explotarlos y venderlos, pero nunca para invertirlos

Tercerización global de parte de los países ricos colonizadores a los países pobres colonizados

p

Neat!

Oh yeah B)

Ok.

Mogelijk opening keynote geven. Bij de Vlaamse in Brussel.

https://www.derstandard.at/story/3000000216964/warum-grundrechte-auch-das-klima-schuetzen

https://stackblitz.com/~/github.com/topicquests/sensecraft

SenseCraft is a - role-playing game

where teams co-construct - structured conversations.

It is currently in active development (pre-alpha) stage.

People can ask - high-level questions by creating quests, and

members of guilds - who take up the challenge

will assume certain roles - to contribute to a - = shared conversation tree.

More documentation on the approach is available on request.

https://www.theguardian.com/food/2024/apr/23/cava-firm-freixenet-to-furlough-80-of-its-workers-in-catalonia-due-to-drought

pluritopic

clout

angel as rupture in this dialectic -- still Prior's method of entry isspielberg/film --art that is nonetheless bound up in the "apparatus"

when confronted with sublmic/apocalyptic terror the americna pop culture capitalist apparatus is his touchstone of udnerstanding

de tocqueville

MB add smth like "This step not differ from MbVBR jobs except mode selection."?

Nereik. Svarbu tik kad telpa ant prizmės

priš tai įsitikinti, kad išjungtas ir seedas

susimažint galią iki nominalios! Pvz ne 22W o 20W; ne 44W o 40W... 1000kHz gal geriausia (nes mažesnė impulso energija)

nereik, ten įdėtas tas plastmasiukas

decía todo el adjetivo que se utiliza en la página de guion es un adjetivo que tiene que ser comprobable por la cámara o el sonido. Porque hay muchos guiones muy malos que dicen juan entra en la habitación claramente abrumado por su pasado del que no puede escapar, no mames vamos a filmar cuando entrando el cuarto, tu pasado lo dejé en la casa, estás abrumado lo que puedes hacer es entonces adjetivizar ciertas acciones cuando entra a la habitación no suelte el picaporte mira para atrás no sé cómo lo irás a puntualizar pero lo haces así, esto está lo por ejemplo pongo elisa mira al linea línea al anfibio flotando en el cilidro indica que va a haber plano contraplano reverso una y le da el ritmo a la página que efectivamente permite que hagas un minuto por página porque si dices él el edificio se incendia se derrumba y pocos escapan con vida son dos minutos de pantalla tres minutos de pantalla entonces tratas de describir eso.

/- Guillermo del Toro

Add something like "You cannot add Agent in Managed by VBR mode to Policy. Please, remove Agent from MbVBR job first".

Two sentences about one thing?

On your decision versus SA job. Here you can, because we cannot determine is the disk removable. You receive the warning only. "We do not recommend backing up disk to itself, as your backup will be lost along with the disk. We will also need to exclude the target folder from backup to prevent backup set from growing in size forever. Proceed with this configuration anyway?"

4

3

2

1

18

try not to let the little things bother me and stay focused on what I need to do

Grow men at work the cry about anything they have to do

My wife

argument 1

Intresting reflections in relation to publishing

Affirmative critique is not dissimilar

This is very much in line with Zapatista frameworks and similar struggles for buen vivir etc.. I find it a bit odd that these are not referenced here

See publishing experiments

Interesting to connect this to publishing...

Very interesting connection between experiment, experience, and practice

Interesting that they position it here so clearly as a practice. See relationship to practice-based research.

Identification and classification

Great

Love this description

This is super interesting, wished this intro had focused more on these issues...

Ok good, this ommission started to annoy me :)

I think it is way too easy to focus on the university as the culprit in this scenario, when it is very much community or field practices that keep up certain fashions in research and publishing. But that doesn't fit their anarchist critique of course.

LOL

There is so much here that needs to be said about publishing cultures. And peer review...

Good phrase.

Too many historical inaccuracies here... universities always had an economic function. Generalisations doing my head in a bit...

Yeah this is all a lot of rhetoric... which is a shame as in my opinion a bit more subtle and realistic critique (less bombastic) would work better to make this argument...

So is the argument similar to what we have read previously in the handbook that militant research is research by activists instead of academics? If so I still find this very simplistic (and both authors are employed by UK universities so there is that).

That's really an overgeneralisation, the whole field of cultural studies would fall underneath this classification, and beyond academia this has also been a very lucrative subject for the publishing economy.

This is a weird line in the argumentation (if it is part of the argument...), e.g. Empire was both populare inside and outside of academia. Creates a weird moralistic binary.

So for me that would be an affirmative practice, not a negative critique as described in the quote above.

I really like this phrasing

Not necessarily a theorist but also Nanni Balestrini.

Example?

It's interesting to see them say this from a left-wing perspective given how the right has seized upon the idea of universities as places for rigorous debate (which is itself a dogwhistle for allowing right-wing academics to be as racist or transphobic as they like). The right have increasingly either played into or deliberately appropriated this idealistic vision of universities as intellectual debating powerhouses.

lol

This has always been my problem with Chomsky: that he claims himself as an anarchist without actually writing about or discussing anarchist ideas.

This makes me think of the ongoing situation in Palestine and the public reaction if not the political reaction.

https://www.theguardian.com/environment/2024/apr/23/trudi-warner-climate-activist-fight-with-the-uk-government

Author response:

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, Day et al. present a high-throughput version of expansion microscopy to increase the throughput of this well-established super-resolution imaging technique. Through technical innovations in liquid handling with custom-fabricated tools and modifications to how the expandable hydrogels are polymerized, the authors show robust ~4-fold expansion of cultured cells in 96-well plates. They go on to show that HiExM can be used for applications such as drug screens by testing the effect of doxorubicin on human cardiomyocytes. Interestingly, the effects of this drug on changing DNA organization were only detectable by ExM, demonstrating the utility of HiExM for such studies.

Overall, this is a very well-written manuscript presenting an important technical advance that overcomes a major limitation of ExM - throughput. As a method, HiExM appears extremely useful, and the data generally support the conclusions.

Strengths:

Hi-ExM overcomes a major limitation of ExM by increasing the throughput and reducing the need for manual handling of gels. The authors do an excellent job of explaining each variation introduced to HiExM to make this work and thoroughly characterize the impressive expansion isotropy. The dox experiments are generally well-controlled and the comparison to an alternative stressor (H2O2) significantly strengthens the conclusions.

Weaknesses:

(1) Based on the exceedingly small volume of solution used to form the hydrogel in the well, there may be many unexpanded cells in the well and possibly underneath the expanded hydrogel at the end of this. How would this affect the image acquisition, analysis, and interpretation of HiExM data?

The hydrogel footprint covers approximately 5% of the surface within an individual well and only cells within this area are embedded in the polymerized hydrogel for subsequent processing steps. Cells that are outside of this footprint are not incorporated into the gel, meaning that these cells are digested by Proteinase K and subsequently washed away by the excess water exchange in the gel swelling step. Note that different cell types may require higher or lower concentrations of Proteinase K to adequately digest cells for expansion while maintaining fluorescence signal. Given the compatibility of HiExM with 96-well plates, this titration can be performed rapidly in a single experiment. Although cells outside of the hydrogel footprint are removed prior to imaging, we do occasionally observe Hoechst signal that appears to be underneath the gels. We believe this signal is likely from excess DNA from digested cells that was not fully washed out in the gel swelling step. This signal is both spatially and morphologically distinct from the nuclear signal of intact cells and it does not affect image acquisition, analysis, or data interpretation.

(2) It is unclear why the expansion factor is so variable between plates (e.g., Figure 2H). This should be discussed in more detail.

The variability in expansion factor across plates can likely be attributed to the small volume (~250 nL) deposited by the device posts. Small variations in gel volume could impact gel polymerization compared to standard ExM gels. For example, gels in HiExM are more sensitive to evaporation because they are ~1000x smaller than standard expansion gel preparations due to an increased air-liquid-interface. Evaporation in HiExM gels increases monomer and cross linker concentrations, leading to variation in expansion factor across plates. We note that expansion factor is robust within well plates and that variance is slightly increased between plates. These differences will be discussed in the revised manuscript.

(3) The authors claim that CF dyes are more resistant to bleaching than other dyes. However, in Figure. S3, it appears that half of the CF dyes tested still show bleaching, and no data is shown supporting the claim that Alexa dyes bleach. It would be helpful to include data supporting the claim that Alexa dyes bleach more than CF dyes and the claim that CF dyes in general are resistant to bleaching should be modified to more accurately reflect the data shown.

We did not show data using Alexa dyes because these fluorophores are highly sensitive to photobleaching using Irgacure and thus we could not obtain images. In contrast, some CF dyes are more robust to bleaching in HiExM including CF488A, CF568, and CF633 dyes. We have recently adapted our protocol to PhotoExM chemistry which is compatible with a wider range of fluorophores as described by Günay et al. (2023) and as shown in current Fig. S11.

(4) Related to the above point, it appears that Figure S11 may be missing the figure legend. This makes it hard to understand how HiExM can use other photo-inducible polymerization methods and dyes other than CF dyes.

The following figure legend will be included in the revised manuscript. Fig. S11: Example of a cell expanded in HiExM using Photo-ExM gel chemistry. Photo-ExM does not require an anoxic environment for gel deposition and polymerization, improving ease of use of HiExM. Mitochondria were stained with an Alexa 647 conjugated secondary antibody, indicating that HiExM is compatible with additional fluorophores when combined with Photo-ExM.

(5) The use of automated high-content imaging is impressive. However, it is unclear to me how the increased search space across the extended planar area and focal depths in expanded samples is overcome. It would be helpful to explain this automated imaging strategy in more detail.

We imaged plates on the Opera Phenix using the PreciScan Acquisition Software in Harmony. In brief, each well is imaged at 5x magnification in the Hoechst channel to capture the full well at low resolution. Hoechst is used for this step given its signal brightness, ubiquity across established staining protocols, and spectral independence from most fluorophores commonly conjugated to secondary antibodies. Using this information, the microscope detects regions of interest (nuclei) based on criteria including size, brightness, circularity, etc. Finally, the positional information for each region is stored, and the microscope automatically images those regions at 63x magnification. The working distance for the objective used in this study is 600 µm which is sufficient to capture the entirety of expanded cells in the Z direction. This strategy allows minimizes off-target imaging and allows robust image acquisition even in cultures with lower seeding density. A detailed description of the automated imaging strategy will be included in the revised manuscript.

(6) The general method of imaging pre- and post-expansion is not entirely clear to me. For example, on page 5 the authors state that pre-expansion imaging was done at the center of each gel. Is pre-expansion imaging done after the initial gel polymerization? If so, this would assume that the gelation itself has no effect on cell size and shape if these gelled but not yet expanded cells are used as the reference for calculating expansion factor and isotropy.

Pre-expansion imaging is performed after staining is complete, but prior to the application of AcX, which is the first step of the HiExM protocol. Following staining and imaging, plates can be sealed with paraffin and stored at 4˚C for up to a week prior to starting the expansion protocol. We typically image 61 fields of view at the center of the well plate (where the gel will be deposited) to obtain sufficient pre-expansion images as shown in Figure 2b (left). After pre-expansion imaging, we perform the HiExM protocol followed by image acquisition. We then tile all the images, as shown in Figure 2b, and compare tiled images from the same well pre- and post-expansion to manually identify the same cells. Comparisons of the pre- and post-expansion images of the same cell are then used to calculate expansion factor and isotropy measurements as described. This detailed description will be included in the revised manuscript.

(7) In the dox experiments, are only 4 expanded nuclei analyzed? It is unclear in the Figure 3 legend what the replicates are because for the unexpanded cells, it says the number of nuclei but for expanded it only says n=4. If only 4 nuclei are analyzed, this does not play to the strengths of HiExM by having high throughput.

We performed the DOX titration assay across four different well plates (i.e. n=4). For each condition, the total number of nuclei measured was 56, 71, 64, 92, and 62 for DMSO, 1nM, 10nM, 100nM, and 1µM, respectively. For SEM calculations, we included the number of technical replicates to avoid underestimating error. We have revised the Figure 3 legend to better reflect the experimental details.

(8) I am not sure if the analysis of dox-treated cells is accurate for the overall phenotype because only a single slice at the midplane is analyzed. It would be helpful to show, at least in one or two example cases, that this trend of changing edge intensity occurs across the whole 3D nucleus.

We will repeat our analysis on a subset of images using multiple optical sections for each nucleus reported. These new data will be included in the revised manuscript.

(9) It would be helpful to provide an actual benchmark of imaging speed or throughput to support the claims on page 8 that HiExM can be combined with autonomous imaging to capture thousands of cells a day. What is the highest throughput you have achieved so far?

The parameters that dictate imaging speed in HiExM include exposure time, z-stack height, and number of channels. Depending on the signal intensity for a given channel, exposure times vary from 200ms to 1000ms. For z-stack height, we found that imaging 65 sections with 1µm spacing allowed for robust identification of each region of interest in the 5x pre-scan. As an example, collecting images for a full well plate (e.g., 20 images per well with 4 channels) requires approximately 24 hours of autonomous image acquisition using the Opera Phenix. Depending on cell size, this yields imaging data for between 1200 cells (1 cell per field of view) to 6000 cells (5 cells per field of view). Different autonomous imagers as well as improving staining techniques that increase signal:noise can be expected to significantly decrease the exposure time as it will reduce the number of z-stacks needed for each region.

Reviewer #2 (Public Review):

Summary:

In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super-resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit the expansion of the gel. A device was engineered that can spot a small droplet of hydrogel solution and keep it in place as it polymerizes. It occupies only a small portion of space at the center of each well, the gel can expand into all directions, and imaging and staining can proceed by liquid handling robots and an automated microscope.

Strengths:

In contrast to Reference 8, the authors' system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high-throughput ExM and high-throughput super-resolution microscopy, which is a timely and important goal.

Weaknesses:

The assay they chose to demonstrate what high-throughput ExM could be useful for, is not very convincing. But for this reviewer that is not important.

We appreciate this reviewer’s point. We believe the data provide an example of the power of HiExM for collecting thousands of nanoscale images that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.). The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this experiment was to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of HiExM.

Reviewer #3 (Public Review):

Summary:

Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include 1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and 2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand the toroidal gel within each well.

Strengths:

This configuration eliminates the need for transferring gels to other dishes or wells, thereby enhancing the throughput and reproducibility of parallel expansion microscopy. This methodological uniqueness indicates the applicability of HiExM in detecting subtle cellular changes on a large scale.

Weaknesses:

To demonstrate the potential utility of HiExM in cell phenotyping, drug studies, and toxicology investigations, the authors treated hiPS-derived cardiomyocytes with a low dose of doxycycline (dox) and quantitatively assessed changes in nuclear morphology. However, this reviewer is not fully convinced of the validity of this specific application. Furthermore, some data about the effect of expansion require reconsideration.

The application we chose was intended as a proof of concept. We believe the data provide an example of the power of HiExM for collecting thousands of nanoscale images that would benefit experiments that require many samples (e.g., conditions, replicates, timepoints, etc.). The ability to generate large data sets also enables quantitative analysis of images with appropriate statistical power. The intention of this experiment was to provide a proof-of-concept example of the robustness, accessibility, and experimental design flexibility of HiExM.

The variability in expansion factor across plates can likely be attributed to the small volume (~250 nL) deposited by the device posts. Small variations in gel volume could impact gel polymerization compared to standard ExM gels. For example, gels in HiExM are more sensitive to evaporation because they are ~1000x smaller than standard expansion gel preparations due to an increased air-liquid-interface. Evaporation in HiExM gels increases monomer and cross linker concentrations, leading to variation in expansion factor across plates. We note that expansion factor is robust within well plates and that variance is slightly increased between plates. These differences will be discussed in the revised manuscript.

Reviewer #3 (Public Review):

Summary:

Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include 1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and 2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand the toroidal gel within each well.

Strengths:

This configuration eliminates the need for transferring gels to other dishes or wells, thereby enhancing the throughput and reproducibility of parallel expansion microscopy. This methodological uniqueness indicates the applicability of HiExM in detecting subtle cellular changes on a large scale.

Weaknesses:

To demonstrate the potential utility of HiExM in cell phenotyping, drug studies, and toxicology investigations, the authors treated hiPS-derived cardiomyocytes with a low dose of doxycycline (dox) and quantitatively assessed changes in nuclear morphology. However, this reviewer is not fully convinced of the validity of this specific application. Furthermore, some data about the effect of expansion require reconsideration.

... ICML pour l'importer ensuite dans le logiciel InDesign, ou d'exporter un document en LaTeX pour produire les PDF avec cet environnement.

qui peuvent être compatibles avec les schémas utilisés par Érudit, ou Métopes/OpenEdition

Are these in decline today --1.5 years later?

Wondering to what degree this essay is projecting ideas of American decline onto some general theory of state failure.

That is - this passage describes US to a degree, but is this (1) an over-generalization of a US-specific experience and (2) actually an arbiter of decline?

Author response:

eLife assessment

This study presents valuable information on the mechanism of how birnavirus VP3 protein interacts with PI3P in early endosomes. Evidence supporting the proposed two-stage mechanism is incomplete and would benefit from additional supporting experiments, and additional experimentation would also address concerns about data consistency.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

Zanetti et al. use biophysical and cellular assays to investigate the interaction of the birnavirus VP3 protein with the early endosome lipid PI3P. The major novel finding is that the association of the VP3 protein with an anionic lipid (PI3P) appears to be important for viral replication, as evidenced through a cellular assay on FFUs.

Strengths:

Supports previously published claims that VP3 may associate with early endosomes and bind to PI3P-containing membranes. The claim that mutating a single residue (R200) critically affects early endosome binding and that the same mutation also inhibits viral replication suggests a very important role for this binding in the viral life cycle.

Weaknesses:

The manuscript is relatively narrowly focused: one bimolecular interaction between a host cell lipid and one protein of an unusual avian virus (VP3-PI3P). Aspects of this interaction have been described previously. Additional data would strengthen claims about the specificity and some technical issues should be addressed. Many of the core claims would benefit from additional experimental support to improve consistency.

We focused our efforts on the characterization of the molecular interaction between the birnaviral protein VP3 and the anionic lipid PI3P, which is found in the host cell. This decision was motivated by our previous research, which made use of cell biology and virology techniques to demonstrate that VP3 facilitates the formation of the viral replication machinery on the cytosolic leaflet of early endosomes due to its inherent endosome-targeting capability (J Virol. 2018 May 14;92(11):e01964-17). Additionally, our previous findings indicated that PI3P, present in early endosomal membranes, is a critical host factor enabling VP3's association with these membranes, thereby promoting viral replication (J Virol. 2021 Feb 24;95(6):e02313-20). Consequently, an in-depth characterization of the VP3/PI3P interaction was necessary and motivated the present work. We plan to incorporate specific recommendations to further substantiate our assertions in the revised version of our manuscript.

Reviewer #2 (Public Review):

Summary:

Birnavirus replication factories form alongside early endosomes (EEs) in the host cell cytoplasm. Previous work from the Delgui lab has shown that the VP3 protein of the birnavirus strain infectious bursal disease virus (IBDV) interacts with phosphatidylinositol-3-phosphate (PI3P) within the EE membrane (Gimenez et al., 2018, 2020). Here, Zanetti et al. extend this previous work by biochemically mapping the specific determinants within IBDV VP3 that are required for PI3P binding in vitro, and they employ in silico simulations to propose a biophysical model for VP3-PI3P interactions.

Strengths:

The manuscript is generally well-written, and much of the data is rigorous and solid. The results provide deep knowledge into how birnaviruses might nucleate factories in association with EEs. The combination of approaches (biochemical, imaging, and computational) employed to investigate VP3-PI3P interactions is deemed a strength.

Weaknesses:

(1) Concerns about the sources, sizes, and amounts of recombinant proteins used for co-flotation: Figures 1A, 1B, 1G, and 4A show the results of co-flotation experiments in which recombinant proteins (control His-FYVE v. either full length or mutant His VP3) were either found to be associated with membranes (top) or non-associated (bottom). However, in some experiments, the total amounts of protein in the top + bottom fractions do not appear to be consistent in control v. experimental conditions. For instance, the Figure 4A western blot of His-2xFYVE following co-flotation with PI3P+ membranes shows almost no detectable protein in either top or bottom fractions.

Liposome-based methods, such as the co-flotation assay, are well-known and preferred to study protein-phosphoinositide interaction because the phosphoinositides are incorporated in a membrane, the composition of which can mimic cellular membranes. Additionally, by modifying the phosphoinositide incorporated in the liposomes, this technique allows for determining the specificity of the protein binding. However, this approach is rather qualitative, meaning that, after density gradient separation, the protein is found in the top fractions (bound to liposomes) or in the bottom fractions (not bound to liposomes), and our quantifications have the aim of showing the difference in the bound fraction between liposome populations with or without PI3P. Given the setting of the co-flotation assays, each protein-liposome system [2xFYVE-PI3P(-), 2xFYVE-PI3P(+), VP3-PI3P(-), or VP3-PI3P(+)] is assessed separately, and even if the conditions are homogeneous, it’s not surprising to observe differences in the protein level between each one. Indeed, our revised version of the manuscript will include membranes with more similar band intensities.

Reading the paper, it was difficult to understand which source of protein was used for each experiment (i.e., E. coli or baculovirus-expressed), and this information is contradicted in several places (see lines 358-359 v. 383-384). Also, both the control protein and the His-VP3-FL proteins show up as several bands in the western blots, but they don't appear to be consistent with the sizes of the proteins stated on lines 383-384. For example, line 383 states that His-VP3-FL is ~43 kDa, but the blots show triplet bands that are all below the 35 kDa marker (Figures 1B and 1G). Mass spectrometry information is shown in the supplemental data (describing the different bands for His-VP3-FL) but this is not mentioned in the actual manuscript, causing confusion. Finally, the results appear to differ throughout the paper (see Figures 1B v. 1G and 1A v. 4A).

We used two sources of recombinant VP3: baculovirus and Escherichia coli. Initially, we opted for the baculovirus system based on evidence from previous studies that it was suitable for ectopic expression of VP3. Subsequently, we successfully produced VP3 using Escherichia coli and chose to transition to this system due to several technical advantages. Moreover, mass spectrometry analysis did not reveal any post-translational modifications that may have favored retaining the baculoviral system. We confirmed that VP3, produced in either system, exhibited similar behavior in our co-flotation assays. We will clarify all this in the revised version of our manuscript.

(2) Possible "other" effects of the R200D mutation on the VP3 protein. The authors performed mutagenesis to identify which residues within patch 2 on VP3 are important for association with PI3P. They found that a VP3 mutant with an engineered R200D change (i) did not associate with PI3P membranes in co-floatation assays, and (ii) did not co-localize with EE markers in transfected cells. Moreover, this mutation resulted in the loss of IBDV viability in reverse genetics studies. The authors interpret these results to indicate that this residue is important for "mediating VP3-PI3P interaction" (line 211) and that this interaction is essential for viral replication. However, it seems possible that this mutation abrogated other aspects of VP3 function (e.g., dimerization or other protein/RNA interactions) aside from or in addition to PI3P binding. Such possibilities are not mentioned by the authors.

The arginine amino acid at position 200 of VP3 is not located in any of the protein regions associated with its other known functions. VP3 has a dimerization domain located in the second helical domain, where different amino acids across the three helices form a total of 81 interprotomeric close contacts; however, R200 is not involved in these contacts (Structure. 2008 Jan;16(1):29-37). VP3 also has an oligomerization domain mapped within the 42 C-terminal residues of the polypeptide, i.e., the segment of the protein composed by the residues at positions 216-257 (J Virol. 2003 Jun;77(11):6438–6449). Regarding VP3’s ability to bind RNA, it is facilitated by a region of positively charged amino acids, identified as P1, which includes K99, R102, K105, and K106 (PLoS One. 2012;7(9):e45957). Furthermore, our findings indicate that the R200D mutant retains a folding pattern similar to the wild-type protein, as shown in Figure 4B. All these lead us to conclude that the loss of replication capacity of R200D viruses results from impaired, or even lost, VP3-PI3P interaction.

(3) Interpretations from computational simulations. The authors performed computational simulations on the VP3 structure to infer how the protein might interact with membranes. Such computational approaches are powerful hypothesis-generating tools. However, additional biochemical evidence beyond what is presented would be required to support the authors' claims that they "unveiled a two-stage modular mechanism" for VP3-PI3P interactions (see lines 55-59). Moreover, given the biochemical data presented for R200D VP3, it was surprising that the authors did not perform computational simulations on this mutant. The inclusion of such an experiment would help tie together the in vitro and in silico data and strengthen the manuscript.

We acknowledge that the language used may have overstated the "unveiling" of the two-stage binding mechanism for VP3 on membranes containing PI3P. We intended to propose, rather than confirm, this mechanism, largely based on our coarse-grained simulations. Accordingly, we will revise the manuscript to temper our claims and frame them more appropriately. Regarding the absence of computer simulations for the R200D VP3 mutant, these were indeed conducted, and the results are detailed in Figure 14 of the supplementary material. We realize this was not adequately emphasized in the main manuscript, an oversight we will correct in the revised version.

Reviewer #3 (Public Review):

Summary:

Infectious bursal disease virus (IBDV) is a birnavirus and an important avian pathogen. Interestingly, IBDV appears to be a unique dsRNA virus that uses early endosomes for RNA replication that is more common for +ssRNA viruses such as for example SARS-CoV-2.

This work builds on previous studies showing that IBDV VP3 interacts with PIP3 during virus replication. The authors provide further biophysical evidence for the interaction and map the interacting domain on VP3.

Strengths: Detailed characterization of the interaction between VP3 and PIP3 identified R200D mutation as critical for the interaction. Cryo-EM data show that VP3 leads to membrane deformation.

Weaknesses:

The work does not directly show that the identified R200 residues are directly involved in VP3-early endosome recruitment during infection. The majority of work is done with transfected VP3 protein (or in vitro) and not in virus-infected cells. Additional controls such as the use of PIP3 antagonizing drugs in infected cells together with a colocalization study of VP3 with early endosomes would strengthen the study. In addition, it would be advisable to include a control for cryo-EM using liposomes that do not contain PIP3 but are incubated with HIS-VP3-FL. This would allow ruling out any unspecific binding that might not be detected on WB.

The authors also do not propose how their findings could be translated into drug development that could be applied to protect poultry during an outbreak. The title of the manuscript is broad and would improve with rewording so that it captures what the authors achieved.

In previous works from our group, we demonstrated the crucial role of the VP3 P2 region in targeting the early endosomal membranes and for viral replication, including the use of PI3K inhibitors to deplete PI3P, showing that both the control RFP-2xFYVE and VP3 lost their ability to associate with the early endosomal membranes (J Virol. 2018 May 14;92(11):e01964-17; J Virol. 2021 Feb 24;95(6):e02313-20). In the present work, to further characterize the role of R200 in binding to early endosomes and for viral replication, we show that: i) the transfected VP3 R200D protein loses the ability to bind to early endosomes in immunofluorescence assays (Figure 2E and Figure 3); ii) the recombinant VP3 R200D protein loses the ability to bind to liposomes PI3P(+) in co-flotation assays (Figure 4A); and, iii) the mutant virus R200D loses replication capacity (Figure 4C).

Regarding the cryo-EM comment: we will include images where we used liposomes PIP3(-) in the revised version of our manuscript.

We will also modify the title of the manuscript.

Regarding the question of how our findings could be translated into drug development, indeed, VP3-PI3P binding constitutes a good target for drugs that counteract infectious bursal disease. However, we did not mention this idea in the manuscript, first because it is somewhat speculative and second because infected farms do not implement any specific treatment. The control is based on vaccination. We will mention these aspects of the infection in the revised version of our manuscript.

Reviewer #1 (Public Review):

Summary:

Zanetti et al. use biophysical and cellular assays to investigate the interaction of the birnavirus VP3 protein with the early endosome lipid PI3P. The major novel finding is that the association of the VP3 protein with an anionic lipid (PI3P) appears to be important for viral replication, as evidenced through a cellular assay on FFUs.

Strengths:

Supports previously published claims that VP3 may associate with early endosomes and bind to PI3P-containing membranes. The claim that mutating a single residue (R200) critically affects early endosome binding and that the same mutation also inhibits viral replication suggests a very important role for this binding in the viral life cycle.

Weaknesses:

The manuscript is relatively narrowly focused: one bimolecular interaction between a host cell lipid and one protein of an unusual avian virus (VP3-PI3P). Aspects of this interaction have been described previously. Additional data would strengthen claims about the specificity and some technical issues should be addressed. Many of the core claims would benefit from additional experimental support to improve consistency.

Związek ADHD z deficytami motorycznymi ( ale nie powyżej 12 lat - chociaż próba badawcza była mała)

Wyższe przewidywanie ADHD, kiedy pojawiają się objawy motoryczne (dzieci)

Związek z nadpobudliwości z objawami motorycznymi

Problemy motoryczne i sensoryczne związane z późniejszym rozwojem ADHD

Wyniki bardziej niespójne kiedy badamy związek z subklinnicznymi objawami ADHD

Związek wczesnych objawów ADHD z deficytami motorycznymi u dzieci

Deficyty motoryczne silniej związane z ADHD, kiedy współwystępuje z innymi zaburzeniami

Author Response

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

Thank you once again for your patience and guidance through this revision process. I would like to add an important aspect to our previous discussion regarding the identification and impact of potential contaminants in our study.

In recent years, advanced tools such as SCRuB (recently published in Nature Biotechnology, DOI:10.1038/s41587-023-01696-w) and the widely-used tool decontam have been developed to address the issue of contaminants in metagenomic studies. These tools primarily operate based on sequence similarity, identifying potential contaminants by marking and removing those found in only a minority of samples or those that display patterns indicative of laboratory contamination.

As the reviewer rightly pointed out, contaminants are often rare species that appear in very few samples. Our study, focusing on high-abundance species in the vaginal microbiome, is less susceptible to the influences of such rare contaminants. This approach aligns with the methodology employed by leading research groups in the field, such as Professor Jacques Ravel's lab. Their decision not to use blank controls in several of their studies on the female reproductive tract microbiome likely stems from a similar understanding — that the impact of rare contaminants is minimal on the study's conclusions, especially when high-abundance species are the main focus.

We believe that the methodologies and tools currently available for contaminant identification and removal, while highly effective for their intended purpose, reinforce our decision to focus on high-abundance species. This focus minimizes the potential impact of rare contaminants on our study's conclusions. In light of this, our study's methodology remains robust and well-suited for achieving our research objectives.

In our revised manuscript, we will include a discussion of these points, further clarifying our approach and the rationale behind our methodological choices. We hope that this additional information will address the concerns raised and provide a clearer understanding of the context and reliability of our findings.

Thank you for considering these additional points. We look forward to your feedback on our revised manuscript.

Perhaps user's ID for that RP can be a hash of userID + RPID.

trystero demo

self-contradictory, but okay..

not necessarily always true. Later in the essay he proposes making a group where the culture is such that this is not so.

2 a quality of solitude.

1

No, there is no evidence from the given search results that someone has written a comprehensive, systematic history of human thought in the sense of tracing the processes and contexts in which different modes of thinking first arose, and generalizing abstract principles of universal relevance. The search results focus primarily on Isaac Asimov's fictional concept of "psychohistory" and the Foundation series, rather than discussing any real-world attempts at such a systematic history of thought.

The key points from the search results are:

[2] Psychohistory is a fictional science in Asimov's Foundation universe that combines history, sociology, and statistics to predict the behavior of large groups of people. It relies on mathematical modeling and statistical laws of mass action, akin to the kinetic theory of gases.

[3] The Foundation series explores trends in societal evolution and adaptation, following Thucydides' model of analyzing historical patterns, rather than focusing on specific cultural qualities at one point in time.

[5] This article suggests Asimov pioneered aspects of "prompt engineering" through his thought-provoking premises in science fiction, but does not mention any real systematic history of human thought processes.

While Asimov's psychohistory and the Foundation series examine large-scale historical patterns and societal trends in a fictional context, the search results do not indicate that anyone has undertaken the ambitious task of writing a comprehensive, systematic history tracing the origins, contexts, and universal principles underlying the development of human thought processes and modes of thinking throughout history.[2][3]

Citations: [1] https://blog.x.company/thinking-science-fictionally-learning-from-asimovs-robot-vision-at-100-8fa482afe776?gi=30ce089e8ea4 [2] https://en.wikipedia.org/wiki/Psychohistory_%28fictional_science%29 [3] https://en.wikipedia.org/wiki/Foundation_series [4] https://www.youtube.com/watch?v=wgSZA3NPpBs [5] https://hackernoon.com/asimov-unknowingly-pioneered-modern-prompt-engineering

在新调度器中，为了减少原子引用计数的使用，进行了以下优化。通常，调度器和每个唤醒器都持有任务结构的一个句柄，常见的管理这些内存的方式是使用原子引用计数。这种策略需要在每次克隆引用时进行一次原子操作，并在每次丢弃引用时进行一次原子操作。当最后一个引用超出作用域时，内存被释放。

在旧的Tokio调度器中，每个唤醒器持有一个对任务句柄的计数引用，大致如下：

```rust struct Waker { task: Arc<Task>, }

impl Waker { fn wake(&self) { let task = self.task.clone(); task.scheduler.schedule(task); } } ```

当任务被唤醒时，引用被克隆（原子增加）。然后将引用推入运行队列。当处理器接收到任务并执行完毕后，它会丢弃引用，导致原子减少。这些原子操作累计起来。

std::future任务系统的设计者之前已经识别出这个问题。他们观察到，当调用Waker::wake时，往往不再需要原始的唤醒器引用。这允许在将任务推入运行队列时重用原子引用计数。std::future任务系统现在包括两个“唤醒”API：

• wake，这个方法接收self
• wake_by_ref，这个方法接收&self

这种API设计促使调用者使用避免原子增量的wake方法。现在的实现变为：

```rust impl Waker { fn wake(self) { self.task.scheduler.schedule(self.task); }

fn wake_by_ref(&self) {
    let task = self.task.clone();
    task.scheduler.schedule(task);
}

} ```

这种方式只有在可以拿到唤醒器的所有权以唤醒时，才能避免额外引用计数的开销。根据我的经验，几乎总是更希望使用&self来唤醒。使用self唤醒会阻止重用唤醒器（在需要发送许多值的情况下有用，例如通道、套接字等），实现线程安全的唤醒也更加困难（当需要self时）。

新调度器通过避免在wake_by_ref中进行原子增量，使其与wake(self)一样高效，从而绕过了整个“自我唤醒”的问题。这是通过让调度器维护一个所有当前活跃（尚未完成）任务的列表来实现的。这个列表代表了将任务推入运行队列所需的引用计数。

这种优化的难点在于确保调度器不会从其列表中删除任何任务，直到可以保证任务不会再次被推入运行队列。如何管理这一点的具体细节超出了本文的范围，但我鼓励你在源代码中进一步研究这个问题。

新的Tokio调度器只需要为每个生成的任务分配一次内存，而旧版本需要两次。以前，任务结构（Task struct）看起来像这样：

```rust struct Task { /// 管理任务所需的所有状态 state: TaskState,

/// 以未来特性对象表示的运行逻辑
future: Box<dyn Future<Output = ()>>,

} `` 然后，Task 结构也会被分配在一个 Box 中。这一直是一个问题，我长期以来一直想解决（我最初在2014年尝试解决这个问题）。自旧的Tokio调度器以来，有两个变化。首先，std::alloc` 稳定了。其次，Future任务系统转向了显式虚拟表（vtable）策略。这是最终消除每个任务双重分配低效的两个缺失部分。

现在，任务结构表示为：

rust struct Task<T> { header: Header, future: T, trailer: Trailer, } Header 和 Trailer 都是推动任务所需的状态，但它们被分为“热”数据（header）和“冷”数据（trailer），即大致上是经常访问的数据和很少使用的数据。热数据被放在结构的头部，并尽可能保持小尺寸。当 CPU 解引用任务指针时，它将一次性加载一个缓存行大小的数据（在64到128字节之间）。我们希望这些数据尽可能相关。

这样的设计减少了内存分配的次数，同时优化了数据的局部性，提高了缓存效率，从而提升了任务的处理性能。这种结构也更加灵活，允许在不牺牲性能的前提下，更自由地定义任务的存储和管理方式。

工作窃取调度器的另一个关键部分是同级通知。当处理器发现新任务时，它会通知一个同级。如果同级处于休眠状态，它将被唤醒并窃取任务。通知操作还承担着另一个关键责任。回想一下队列算法使用了弱原子排序（获取/释放）。由于原子内存排序的工作方式，如果没有额外的同步，就无法保证同级处理器能够看到队列中的任务以进行窃取。通知操作还负责建立必要的同步，以便同级处理器能够看到并窃取这些任务。这些要求使得通知操作变得代价高昂。目标是尽可能少地执行通知操作，而不会导致 CPU 利用率低下，即处理器有任务而同级无法窃取它们。过度急切的通知会导致群聚问题（thundering herd problem）。

原始的 Tokio 调度器采用了一种简单的通知方法。每当新任务被推送到运行队列上，就通知一个处理器。每当一个处理器被通知并在唤醒后发现任务时，它就会通知另一个处理器。这种逻辑很快就导致所有处理器被唤醒并寻找工作（造成竞争）。很多时候，大多数处理器未能找到工作又回到了休眠状态。

新的调度器通过借鉴 Go 调度器使用的同一技术显著改进了这一点。通知的时机与之前的调度器相同，然而，只有在没有工作器处于搜索状态时（参见前一节）才会进行通知。当工作器被通知时，它会立即过渡到搜索状态。当处于搜索状态的处理器发现新任务时，它将首先退出搜索状态，然后通知另一个处理器。

这一逻辑具有限制处理器唤醒速率的效果。如果一批任务同时被调度（例如，当epoll轮询套接字就绪时），第一个结果会通知一个处理器。该处理器现在处于搜索状态。该批次中剩余的计划任务不会通知处理器，因为至少有一个处于搜索状态。被通知的处理器将窃取批次中一半的任务，然后转而通知另一个处理器。这第三个处理器将醒来，从前两个处理器中找到任务并窃取其中的一半。这导致处理器的平稳启动以及任务的快速负载平衡。

优先槽位，只有当前 thread 提交的 task 才会存储在这里，其他 thread 提交的 task 只会存储在他们的本地或者 inject 中

，即本地运行队列中有任务，处理器将在从本地队列执行大约60个任务后尝试从全局队列中弹出任务。它还会在下面描述的“搜索”状态时检查全局队列。

既然 sync 是一个高成本的事情，那么我每次 sync 的时候就多干点事同时减少 sync 的触发次数

这里的 mask 实际在现在的代码里已经被移除了，因为 cap 是固定的常数，直接通过 cap 就能计算出 ringbuffer 溢出位的位移量。也就是 mask = cap - 1 = 255

mask 在 ringbuffer 的实现中很常见，当我们即将写入数组的最后一个元素时，下一次写入应该在数组前开始。如果每次都通过条件语句来判断就会不够高效，引入 mask 后每次push 尾idx + 1，每次 pop 头 idx +1，实际访问数组时将当前 idx 和 mask 做 mod 即可得到合法的 idx 位置。 这里用与运算代替 mod 也是常见做法，因为 mod 值的二机制位全为 1（mask = 255）。

非常巧妙

looking at questyion related to IPFS

Author response:

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

We thank the reviewers for their thoughtful comments. We were pleased that they thought our study was "well crafted and written", "important", and that it provides a "valuable resource for researchers studying color vision". They also expressed several constructive criticisms, concerning – among other things – the lack of details regarding experimental procedures and analysis, the challenge in relating retinal data to cortical recordings, and consistency of results across animals. In response to the reviewers’ comments and following their suggestions, we performed additional analyses, and substantially revised the paper:

We added a section in the Discussion about "Limitations of the stimulus paradigm". In addition, we added a new Suppl. Figure that illustrates the effect of deconvolution of calcium traces on our results and clarified in the text why we use deconvolved signals for all analyses. The new Suppl. Figure also shows an additional analysis with a more conservative threshold of neuron exclusion.

We now clarify how retinal signaling relates to our cortical results and rewrote the text to be more conservative regarding our conclusions.

In addition, we added a new Suppl. Figure showing the key analyses from Figures 2 and 4 separately for each animal. We now mention consistency across animals in the Results section and clearly state which analyses were performed an data pooled across animals.

We are positive that these additions address the issues raised by the reviewers. Please find our point-by-point replies to all comments below.

eLife assessment

Franke et al. explore and characterize the color response properties in the mouse primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The data is solid; however, the evidence supporting some conclusions and details about some procedures are incomplete. In its current form, the paper makes a useful contribution to how color is coded in mouse V1. Significance would be enhanced with some additional analyses and resolution of some technical issues.

We thank the reviewers for appreciating our manuscript and their thoughtful comments.

Referee 1 (Remarks to the Author):

Summary:

In this study, Franke et al. explore and characterize the color response properties across the primary visual cortex, revealing specific color opponent encoding strategies across the visual field. The authors use awake-behaving 2P imaging to define the spectral response properties of visual interneurons in Layer 2/3. They find that opponent responses are more prominent at photopic light levels, and diversity in color opponent responses exists across the visual science, with green ON/ UV OFF responses being stronger represented in the upper visual field. This is argued to be relevant for detecting certain features that are more salient when the chromatic space is used, possibly due to noise reductions.

Strengths:

The work is well crafted and written and provides a thorough characterization that reveals an uncharacterized diversity of visual properties in V1. I find this characterization important because it reveals how strongly chromatic information can modulate the response properties in V1. In the upper visual field, 25% of the cells differentially relay chromatic information, and one may wonder how this information will be integrated and subsequently used to aid vision beyond the detection of color per see. I personally like the last paragraph of the discussion that highlights this fact.

We thank the reviewer for appreciating our manuscript.

Weaknesses: One major point highlighted in this paper is the fact that Green ON/UV OFF responses are not generated in the retina. But glancing through the literature, I saw this is not necessarily true. Fig 1. of Joesch and Meister, a paper cited, shows this can be the case. Thus, I would not emphasize that this wasn’t present in the retina. This is a minor point, but even if the retina could not generate these signals, I would be surprised if the diversity of responses would only arise through feed-forward excitation, given the intricacies of cortical connectivity. Thus, I would argue that the argument holds for most of the responses seen in V1; they need to be further processed by cortical circuitries.

We thank the reviewer for this comment. When analyzing available data from the retina using a similar center-surround color flicker stimulus (Szatko et al. 2020), we found that Green On/UV Off color opponency is very rare in the RF center of retinal ganglion cells (Suppl. Fig. 5). This suggests that center Green On/UV Off color opponency in V1 neurons is not inherited by the RF center of retinal neurons. However, we agree with the reviewer that retinal neurons might still contribute to V1 color opponency, for example by being center-surround color opponent (e.g. Joesch et al. 2016 and Szatko et al. 2020). We rephrased the text to acknowledge this fact.

This takes me to my second point, defining center and surround. The center spot is 37.5 deg of visual angle, more than 1 mm of the retinal surface. That means that all retinal cells, at least half and most likely all of their surrounds will also be activated. Although 37.5 deg is roughly the receptive field size previously determined for V1 neurons, the one-to-one comparison with retinal recording, particularly with their center/surround properties, is difficult. This should be discussed. I assume that the authors tried a similar approach with sparse or dense checker white noise stimuli. If so, it would be interesting if there were better ways of defining the properties of V1 neurons on their complex/simple receptive field properties to define how much of their responses are due to an activation of the true "center" or a coactivation of the surround. Interestingly, at least some of the cells (Fig. 1d, cells 2 and 5) don’t have a surround. Could it be that in these cases, the "center" and "surround" are being excited together? How different would the overall statistics change if one used a full-filed flicker stimulus instead of a center/surround stimulus? How stable are the results if the center/surround flicker stimulus is shifted? These results won’t change the fact that chromatic coding is present in the VC and that there are clear differences depending on their position, but it might change the interpretation. Thus, I would encourage you to test these differences and discuss them.

Thanks for this comment. We agree with the reviewer that a one-to-one comparison of retina and V1 data is challenging, due to differences in both RF and stimulus size. We rephrased the Results text to clarify this point and now also mention it in the Discussion.

To be able to record from many V1 neurons simultaneously, we used a stimulus size of 37.5 degree visual angle in diameter, which is slightly larger than center RFs of single V1 neurons. As the reviewer mentions, the disadvantage of this approach is that the stimulus is only roughly centered on the neurons’ center RFs. To reduce the impact of potential stimulus misalignment on our results, we used the following steps:

For each recording, we positioned the monitor such that the mean RF across all neurons lies within the center of the stimulus field of view.

We confirmed that this procedure results in good stimulus alignment for the large majority of recorded neurons within individual recording fields by using a sparse noise stimulus (Suppl. Fig. 1a-c). Specifically, we found that for 83% of tested neurons, more than two thirds of their center RF, determined by the sparse noise stimulus, overlapped with the center spot of the color noise stimulus.

For analysis, we excluded neurons without a significant center STA, which may be caused by misalignment of the stimulus.

Together, we believe these points strongly suggest that the center spot and the surround annulus of the noise stimulus predominantly drive center (i.e. classical RF) and surround (i.e. extraclassical RF), respectively, of the recorded V1 neurons. This is further supported by the fact that color response types identified using an automated clustering method were robust across mice (Suppl. Fig. 6c), indicating consistent stimulus centering.

Nevertheless, we cannot exclude that the stimulus was misaligned for a subset of the recorded neurons used for analysis. We agree with the reviewer that such misalignment might have contributed to cells not having surround STAs, due to simultaneous activation of antagonistic center and surround RF components by the surround stimulus. While a full-field stimulus would get rid of the misalignment problem, it would not allow to study color tuning in center and surround RF components separately. Instead, one could compare the results of our approach with an approach that centers the stimulus on individual neurons. However, we believe that performing these additional experiments is out of the scope of the current study.

To acknowledge the experimental limitations of our study and the concerns brought up by the reviewer, we now explicitly mention the steps we perform to reduce the effects of stimulus misalignment in the Results section and discuss the problem of stimulus alignment in the Discussion. We believe these changes will help the reader to interpret our results.

Referee 2 (Remarks to the Author):

Summary:

Franke et al. characterize the representation of color in the primary visual cortex of mice and how it changes across the visual field, with a particular focus on how this may influence the ability to detect aerial predators. Using calcium imaging in awake, head-fixed mice, they characterize the properties of V1 neurons (layer 2/3) using a large center-surround stimulation where green and ultra-violet were presented in random combinations. Using a clustering approach, a set of functional cell-types were identified based on their preference to different combinations of green and UV in their center and surround. These functional types were demonstrated to have varying spatial distributions in V1, including one neuronal type (Green-ON/UV-OFF) that was much more prominent in the posterior V1 (i.e. upper visual field). Modelling work suggests that these neurons likely support the detection of predator-like objects in the sky.

Strengths:

The large-scale single-cell resolution imaging used in this work allows the authors to map the responses of individual neurons across large regions of the visual cortex. Combining this large dataset with clustering analysis enabled the authors to group V1 neurons into distinct functional cell types and demonstrate their relative distribution in the upper and lower visual fields. Modelling work demonstrated the different capacity of each functional type to detect objects in the sky, providing insight into the ethological relevance of color opponent neurons in V1.

We thank the reviewer for appreciating our manuscript.

Weaknesses:

While the study presents solid evidence a few weaknesses exist, including the size of the dataset, clarity regarding details of data included in each step of the analysis and discussion of caveats of the work. The results presented here are based on recordings of 3 mice. While the number of neurons recorded is reasonably large (n > 3000) an analysis that tests for consistency across animals is missing. Related to this, it is unclear how many neurons at each stage of the analysis come from the 3 different mice (except for Suppl. Fig 4).

Thank you for this comment. We apologize that the original manuscript did not clearly indicate the consistency of our results across animals. We have revised the manuscript in the following ways:

We have added an additional Suppl. Figure, which shows the variability of the data within and across animals (Suppl. Fig. 4). Specifically, we show the distribution of color and luminance selectivity for (i) center and surround components of V1 RFs and (ii) for upper and lower visual field. This data is used for all analyses shown in Figures 2-4. The figure legend of this figure also states the number of neurons per animal.

We now clearly state in the Results section that all analyses in the main figures were performed by pooling data across animals, and refer to the Suppl. Figures for consistency across animals.

We believe these changes help the reader to interpret our results.

Finally, the paper would greatly benefit from a more in depth discussion of the caveats related to the conclusion drawn at each stage of the analysis. This is particularly relevant regarding the caveats related to using spike triggered averages to assess the response preferences of ON-OFF neurons, and the conclusions drawn about the contribution of retinal color opponency.

Thanks. We substantially revised the text to discuss caveats and limitations of the approach. For example, we added a section into the Discussion called "Limitations of the stimulus paradigm". In addition, we clarified how retinal signals relate to cortical ones and phrased our conclusions more conservatively.

The authors provide solid evidence to support an asymmetric distribution of color opponent cells in V1 and a reduced color contrast representation in lower light levels. Some statements would benefit from more direct evidence such as the integration of upstream visual signals for color opponency in V1.

Based on the comments from Reviewer 1, we have rephrased the statements regarding the integration of upstream visual signals for color opponency in V1. We think these revisions increase the clarity of the results and help the reader with interpretation.

Overall, this study will be a valuable resource for researchers studying color vision, cortical processing, and the processing of ethologically relevant information. It provides a useful basis for future work on the origin of color opponency in V1 and its ethological relevance.

Thanks! We thank the reviewer again for the helpful comments.

Referee 3 (Remarks to the Author):

This paper studies chromatic coding in mouse primary visual cortex. Calcium responses of a large collection of cells are measured in response to a simple spot stimulus. These responses are used to estimate chromatic tuning properties - specifically sensitivity to UV and green stimuli presented in a large central spot or a larger still surrounding region. Cells are divided based on their responses to these stimuli into luminance or chromatic sensitive groups. Several technical concerns limit how clearly the data support the conclusions. If these issues can be fixed, the paper would make a valuable contribution to how color is coded in mouse V1.

We thank the reviewer for the helpful comments.

Analysis: The central tool used to analyze the data is a "spike triggered average" of the responses to randomly varying stimuli. There are several steps in this analysis that are not documented, and hence evaluating how well it works is difficult. Central to this is that the paper does not measure spikes. Instead, measured calcium traces are converted to estimated spike rates, which are then used to estimate STAs. There are no raw calcium traces shown, and the approach to estimate spike rates is not described in any detail. Confirming the accuracy of these steps is essential for a reader to be able to evaluate the paper. Further, it is not clear why the linear filters connecting the recorded calcium traces and the stimulus cannot be estimated directly, without the intermediate step of estimating spike rates.

Thank you for this comment. We have used the genetically encoded calcium sensor GCaMP6s in our recordings. This sensor is a very sensitive GCaMP6 variant, but also one with slow kinetics. To remove the effect of the slow sensor kinetics from recorded calcium responses, the recorded traces are commonly deconvolved with the impulse function of the sensor to obtain the deconvolved calcium traces. We now include this reasoning in the Results section. To illustrate the effect of the deconvolution, we added a new Suppl. Figure (Suppl. Fig. 2) showing raw calcium and deconvolved traces, and the STAs estimated from both types of traces. This illustrates that the results regarding neuronal color preferences are consistent across raw and deconvolved calcium traces.

We agree with the reviewer that the term STA might be confusing. We have replaced it with the term "even-triggered-average" (ETA). In addition, we have replaced the phrase "estimated spike rate" with "deconvolved calcium trace" throughout the manuscript because the unit of the deconvolved traces is not interpretable, like spike rate would be (spikes per second). In the revised version, we now clarify in the Methods section that we estimate the ETAs based on deconvolved calcium traces, which is correlated with and an approximation for spike rate.

A further issue about the STAs is that the inclusion criterion (correlation of predicted vs measured responses of 0.25) is pretty forgiving. It would be helpful to see a distribution of those correlation values, and some control analyses to check whether the STA is providing a sufficiently accurate measure to support the results (e.g. do the central results hold for the cells with the highest correlations).

We thank the reviewer for this comment. To exclude noisy neurons from analysis, we used the following procedure:

For each of the four stimulus conditions (center and surround for green and UV stimuli), kernel quality was measured by comparing the variance of the STA with the variance of the baseline, defined as the first 500 ms of the STA. Only cells with at least 10-times more variance of the kernel compared to baseline for UV or green center STA were considered for further analysis.

We have added the distribution of quality values to a new Suppl. Figure (Suppl. Fig. 2d,e). We now also show the percentage of neurons above threshold, given different quality thresholds. Finally, we have repeated the analysis shown in Figure 2 for a much more conservative threshold, including only the top 25% of neurons (Suppl. Fig. 2e,f). We now mention this new analysis in the Methods and Results section.

Limitations of stimulus choice: The paper relies on responses to a large (37.5 degree diameter) modulated spot and surrounding region. This spot is considerably larger than the receptive fields of both V1 cells and retinal ganglion cells. As a result, the spot itself is very likely to strongly activate both center and surround mechanisms, and responses of cells are likely to depend on where the receptive fields are located within the spot (and, e.g., how much of the true neural surround samples the center spot vs the surround region). The impact of these issues on the conclusions is considered briefly at the start of the results but needs to be evaluated in considerably more detail. This is particularly true for retinal ganglion cells given the size of their receptive fields (see also next point).

We agree with the reviewer that the centering of the stimulus is critical and apologize if this point was not discussed sufficiently. To be able to record from many V1 neurons simultaneously, we used a stimulus size of 37.5 degree visual angle in diameter, which is slightly larger than center RFs of single V1 neurons. As the reviewer mentions, the disadvantage of this approach is that the stimulus is only roughly centered on the neurons’ center RFs. To reduce the impact of potential stimulus misalignment on our results, we have used different experimental and analysis steps and controls (see also second comment of Reviewer 1):

For each recording, we positioned the monitor such that the mean RF across all neurons lies within the center of the stimulus field of view.

We confirmed that this procedure results in good stimulus alignment for the large majority of recorded neurons within individual recording fields by using a sparse noise stimulus (Suppl. Fig. 1a-c). Specifically, we found that for 83% of tested neurons, more than two thirds of their center RF, determined by the sparse noise stimulus, overlapped with the center spot of the color noise stimulus.

For analysis, we excluded neurons without a significant center STA, which may be caused by misalignment of the stimulus.

We now mention those clearly in the Results section and added the limitations of our approach to the Discussion section.

Comparison with retina: A key conclusion of the paper is that the chromatic tuning in V1 is not inherited from retinal ganglion cells. This conclusion comes from comparing chromatic tuning in a previously-collected data set from retina with the present results. But the retina recordings were made using a considerably smaller spot, and hence it is not clear that the comparison made in the paper is accurate. This issue may be handled by the analysis presented in the paper, but if so it needs to be described more clearly. The paper from which the retina data is taken argues that rod-cone chromatic opponency originates largely in the outer retina. This mechanism would be expected to be shared across retinal outputs. Thus it is not clear how the Green-On/UV-Off vs Green-Off/UV-On asymmetry could originate. This should be discussed.

We agree with the reviewer that a one-to-one comparison of retina and V1 data is challenging, due to differences in both RF and stimulus size. We rephrased the Results text to clarify this point and now also mention it in the Discussion.

When analyzing available data from the retina using a similar center-surround color flicker stimulus (Szatko et al. 2020), we found that Green On/UV Off color opponency is very rare in the RF center of retinal ganglion cells (Suppl. Fig. 5). This suggests that center Green On/UV Off color opponency in V1 neurons is not inherited by the RF center of retinal neurons. However, we agree with the reviewer that retinal neurons might still contribute to V1 color opponency, for example by being center-surround color opponent (e.g. Joesch et al. 2016 and Szatko et al. 2020). We rephrased the text to acknowledge this fact.

Residual chromatic cells at low mesopic light levels The presence of chromatically tuned cells at the lowest light level probed is surprising. The authors describe these conditions as rod-dominated, in which case chromatic tuning should not be possible. This again is discussed only briefly. It either reflects the presence of an unexpected pathway that amplifies weak cone signals under low mesopic conditions such that they can create spectral opponency or something amiss in the calibrations or analysis. Data collected at still lower light levels would help resolve this.

Thank you for this comment. We call the lowest light level "low mesopic" and "rod-dominated" because the spectral contrast of V1 center responses in posterior recording fields is green-shifted for this light level (Fig. 3a). This is only expected if responses in the UV-cone dominant ventral retina are predominantly driven by rod photoreceptors. We now explain this rationale in the Results section. In addition, we mention in the Discussion that future studies are required to test whether cone signals need to be amplified for low light levels. While we agree with the reviewer that it would be exciting to use even lower light levels during recordings, we believe this is out of the scope of the current study due to the technical challenges involved in achieving scotopic stimulation.

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editor.js

Claims about one's identity (authorized devices), could be maintained by the quorum of these devices. Or by a quorum of one's devices and his friends.

DID is an id + a way to resolve associated to ID info (DIDDoc). Seems strange to couple the two. I'd like to have one ID and plenty of methods to resolve info behind it. A kind of MultiDID.

This would require having private key portable. Which is not secure.

Author response:

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

As you will see, the main changes in the revised manuscript pertain to the structure and content of the introduction. Specifically, we have tried to more clearly introduce our paradigm, the rationale behind the paradigm, why it is different from learning paradigms, and why we study “relief”.

In this rebuttal letter, we will go over the reviewers’ comments one-by-one and highlight how we have adapted our manuscript accordingly. However, because one concern was raised by all reviewers, we will start with an in-depth discussion of this concern.

The shared concern pertained to the validity of the EVA task as a model to study threat omission responses. Specifically, all reviewers questioned the effectivity of our so-called “inaccurate”, “false” or “ruse” instructions in triggering an equivalent level of shock expectancy, and relatedly, how this effectivity was affected by dynamic learning over the course of the task.

We want to thank the reviewers for raising this important issue. Indeed, it is a vital part of our design and it therefore deserves considerable attention. It is now clear to us that in the previous version of the manuscript we may have focused too little on why we moved away from a learning paradigm, and how we made sure that the instructions were successful at raising the necessary expectations; and how the instructions were affected by learning. We believe this has resulted in some misunderstandings, which consequently may have cast doubts on our results. In the following sections, we will go into these issues.

The rationale behind our instructed design

The main aim of our study was to investigate brain responses to unexpected omissions of threat in greater detail by examining their similarity to the reward prediction error axioms (Caplin & Dean, 2008), and exploring the link with subjective relief. Specifically, we hypothesized that omission-related responses should be dependent on the probability and the intensity of the expected-but-omitted aversive event (i.e., electrical stimulation), meaning that the response should be larger when the expected stimulation was stronger and more expected, and that fully predicted outcomes should not trigger a difference in responding.

To this end, we required that participants had varying levels of threat probability and intensity predictions, and that these predictions would most of the time be violated. Although we fully agree with the reviewers that fear conditioning and extinction paradigms can provide an excellent way to track the teaching properties of prediction error responses (i.e., how they are used to update expectancies on future trials), we argued that they are less suited to create the varying probability and intensity-related conditions we required (see Willems & Vervliet, 2021). Specifically, in a standard conditioning task participants generally learn fast, rendering relatively few trials on which the prediction is violated. As a result, there is generally little intraindividual variability in the prediction error responses. This precludes an in-depth analysis of the probability-related effects. Furthermore, conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted. As a result, intensity-related effects cannot be tested. Finally, because CS-US contingencies change over the course of a fear conditioning and extinction study (e.g. from acquisition to extinction), there is never complete certainty about when the US will (not) follow. This precludes a direct comparison of fully predicted outcomes.

Another added value of studying responses to the prediction error at threat omission outside a learning context is that it can offer a way to disentangle responses to the violation of threat expectancy, with those of subsequent expectancy updating.

Also note that Rutledge and colleagues (2010), who were the first to show that human fMRI responses in the Nucleus Accumbens comply to the reward prediction error axioms also did not use learning experiences to induce expectancy. In that sense, we argued it was not necessary to adopt a learning paradigm to study threat omission responses.

Adaptations in the revised manuscript: We included two new paragraphs in the introduction of the revised manuscript to elaborate on why we opted not to use a learning paradigm in the present study (lines 90-112).

“However, is a correlation with the theoretical PE over time sufficient for neural activations/relief to be classified as a PE-signal? In the context of reward, Caplin and colleagues proposed three necessary and sufficient criteria all PE-signals should comply to, independent of the exact operationalizations of expectancy and reward (the socalled axiomatic approach24,25; which has also been applied to aversive PE26–28). Specifically, the magnitude of a PE signal should: (1) be positively related to the magnitude of the reward (larger rewards trigger larger PEs); (2) be negatively related to likelihood of the reward (more probable rewards trigger smaller PEs); and (3) not differentiate between fully predicted outcomes of different magnitudes (if there is no error in prediction, there should be no difference in the PE signal).”

“It is evident that fear conditioning and extinction paradigms have been invaluable for studying the role of the threat omission PE within a learning context. However, these paradigms are not tailored to create the varying intensity and probability-related conditions that are required to evaluate the threat omission PE in the light of the PE axioms. First, conditioning paradigms generally only include one level of aversive outcome: the electrical stimulation is either delivered or omitted. As a result, the magnitude-related axiom cannot be tested. Second, in conditioning tasks people generally learn fast, rendering relatively few trials on which the prediction is violated. As a result, there is generally little intra-individual variability in the PE responses. Moreover, because of the relatively low signal to noise ratio in fMRI measures, fear extinction studies often pool across trials to compare omission-related activity between early and late extinction16, which further reduces the necessary variability to properly evaluate the probability axiom. Third, because CS-US contingencies change over the course of the task (e.g. from acquisition to extinction), there is never complete certainty about whether the US will (not) follow. This precludes a direct comparison of fully predicted outcomes. Finally, within a learning context, it remains unclear whether PErelated responses are in fact responses to the violation of expectancy itself, or whether they are the result of subsequent expectancy updating.”

Can verbal instructions be used to raise the expectancy of shock?

The most straightforward way to obtain sufficient variability in both probability and intensityrelated predictions is by directly providing participants with instructions on the probability and intensity of the electrical stimulation. In a previous behavioral study, we have shown that omission responses (self-reported relief and omission SCR) indeed varied with these instructions (Willems & Vervliet, 2021). In addition, the manipulation checks that are reported in the supplemental material provided further support that the verbal instructions were effective at raising the associated expectancy of stimulation. Specifically, participants recollected having received more stimulations after higher probability instructions (see Supplemental Figure 2). Furthermore, we found that anticipatory SCR, which we used as a proxy of fearful expectation, increased with increasing probability and intensity (see Supplemental Figure 3). This suggests that it is not necessary to have expectation based on previous experience if we want to evaluate threat omission responses in the light of the prediction error axioms.

Adaptations in the revised manuscript: We more clearly referred to the manipulation checks that are presented in the supplementary material in the results section of the main paper (lines 135-141).

“The verbal instructions were effective at raising the expectation of receiving the electrical stimulation in line with the provided probability and intensity levels. Anticipatory SCR, which we used as a proxy of fearful expectation, increased as a function of the probability and intensity instructions (see Supplementary Figure 3). Accordingly, post-experimental questions revealed that by the end of the experiment participants recollected having received more stimulations after higher probability instructions, and were willing to exert more effort to prevent stronger hypothetical stimulations (see Supplementary Figure 2).”

How did the inconsistency between the instructed and experienced probability impact our results?

All reviewers questioned how the inconsistency between the instructed and experienced probability might have impacted the probability-related results. However, judging from the way the comments were framed, it seems that part of the concern was based on a misunderstanding of the design we employed. Specifically, reviewer 1 mentions that “To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; I.e., 25% of shocks are omitted regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, 0%.”, and reviewer 3 states that “... the fact remains that they do not get shocks outside of the 100% probability shock. So learning is occurring, at least for subjects who realize the probability cue is actually a ruse.” We want to emphasize that this was not what we did, and if it were true, we fully agree with the reviewers that it would have caused serious trust- and learning related issues, given that it would be immediately evident to participants that probability instructions were false. It is clear that under such circumstances, dynamic learning would be a big issue.

However, in our task 0% and 100% instructions were always accurate. This means that participants never received a stimulus following 0% instructions and always received the stimulation of the given intensity on the 100% instructions (see Supplemental Figure 1 for an overview of the trial types). Only for the 25%, 50% and 75% trials an equal reinforcement rate (25%) was maintained, meaning that the stimulation followed in 25% of the trials, irrespective of whether a 25%, 50% or 75% instruction was given. The reason for this was that we wanted to maximize and balance the number of omission trials across the different probability levels, while also keeping the total number of presentations per probability instruction constant. We reasoned that equating the reinforcement rate across the 25%, 50% and 75% instructions should not be detrimental, because (1) in these trials there was always the possibility that a stimulation would follow; and (2) we instructed the participants that each trial is independent of the previous ones, which should have discouraged them to actively count the number of shocks in order to predict future shocks.

Adaptations in the revised manuscript: We have tried to further clarify the design in several sections of the manuscript, including the introduction (lines 121-125), results (line 220) and methods (lines 478-484) sections:

Adaptation in the Introduction section: “Specifically, participants received trial-by-trial instructions about the probability (0%, 25%, 50%, 75% and 100%) and intensity (weak, moderate, strong) of a potentially painful upcoming electrical stimulation, time-locked by a countdown clock (see Fig.1A). While stimulations were always delivered on 100% trials and never on 0% trials, most of the other trials (25%-75%) did not contain the expected stimulation and hence provoked an omission PE.”

Adaptation in the Results section: “Indeed, the provided instructions did not map exactly onto the actually experienced probabilities, but were all followed by stimulation in 25% on the trials (except for the 0% trials and the 100% trials).”

Adaptation in the Methods section: “Since we were mainly interested in how omissions of threat are processed, we wanted to maximize and balance the number of omission trials across the different probability and intensity levels, while also keeping the total number of presentations per probability and intensity instruction constant. Therefore, we crossed all non-0% probability levels (25, 50, 75, 100) with all intensity levels (weak, moderate, strong) (12 trials). The three 100% trials were always followed by the stimulation of the instructed intensity, while stimulations were omitted in the remaining nine trials. Six additional trials were intermixed in each run: Three 0% omission trials with the information that no electrical stimulation would follow (akin to 0% Probability information, but without any Intensity information as it does not apply); and three trials from the Probability x Intensity matrix that were followed by electrical stimulation (across the four runs, each Probability x Intensity combination was paired at least once, and at most twice with the electrical stimulation).”

Could the incongruence between the instructed and experienced reinforcement rate have detrimental effects on the probability effect? We agree with reviewer 2 that it is possible that the inconsistency between instructed and experienced reinforcement rates could have rendered the exact probability information less informative to participants, which might have resulted in them paying less attention to the probability information whenever the probability was not 0% or 100%. This might to some extent explain the relatively larger difference in responding between 0% and 25% to 75% trials, but the relatively smaller differences between the 25% to 75% trials.

However, there are good reasons to believe that the relatively smaller difference between 25% to 75% trials was not caused by the “inaccurate” nature of our instructions, but is inherent to “uncertain” probabilities.

We added a description of these reasons to the supplementary materials in a supplementary note (supplementary note 4; lines 97-129 in supplementary materials), and added a reference to this note in the methods section (lines 488-490).

“Supplementary Note 4: “Accurate” probability instructions do not alter the Probability-effect

A question that was raised by the reviewers was whether the inconsistency between the probability instruction and the experienced reinforcement rate could have detrimental effects on the Probability-related results; especially because the effect of Probability was smaller when only including non-0% trials.

However, there are good reasons to believe that the relatively smaller difference between 25% to 75% trials was not caused by the “inaccurate” nature of our instructions, but that they are inherent to “uncertain” probabilities.

First, in a previously unpublished pilot study, we provided participants with “accurate” probability instructions, meaning that the instruction corresponded to the actual reinforcement rate (e.g., 75% instructions were followed by a stimulation in 75% of the trials etc.). In line with the present results and our previous behavioral study (Willems & Vervliet, 2021), the results of this pilot (N = 20) showed that the difference in the reported relief between the different probability levels was largest when comparing 0% and the rest (25%, 50% and 75%). Furthermore the overall effect size of Probability (excluding 0%) matched the one of our previous behavioral study (Willems & Vervliet, 2021): ηp2 = +/- 0.50.”

Author response image 1.

Main effect of Probability including 0% : F(1.74,31.23) = 53.94, p < .001, ηp2 = 0.75

Main effect of Probability excluding 0%: F(1.50, 28.43) = 21.03, p < .001, ηp2 = 0.53

Second, also in other published studies that used CSs with varying reinforcement rates (which either included explicit written instructions of the reinforcement rates or not) showed that the difference in expectations, anticipatory SCR or omission SCR was largest when comparing the CS0% to the other CSs of varying reinforcement rates (Grings & Sukoneck, 1971; Öhman et al., 1973; Ojala et al., 2022).

Together, this suggests that when there is a possibility of stimulation, any additional difference in probability will have a smaller effect on the omission responses, irrespective of whether the underlying reinforcement rate is accurate or not.

Adaptation to methods section: “Note that, based on previous research, we did not expect the inconsistency between the instructed and perceived reinforcement rate to have a negative effect on the Probability manipulation (see Supplementary Note 4).”

Did dynamic learning impact the believability of the instructions?

Although we tried to minimize learning in our paradigm by providing instructions that trials are independent from one another, we agree with the reviewers that this cannot preclude all learning. Any remaining learning effects should present themselves by downweighing the effect of the probability instructions over time. We controlled for this time-effect by including a “run” regressor in our analyses. Results of the Run regressor for subjective relief and omission-related SCR are presented in Supplemental Figure 5. These figures show that although there was a general drop in reported relief pleasantness and omission SCR over time, the effects of probability and intensity remained present until the last run. This indicates that even though some learning might have taken place, the main manipulations of probability and intensity were still present until the end of the task.

Adaptations in the revised manuscript: We more clearly referred to the results of the Blockregressor which were presented in the supplementary material in the results section of the main paper (lines 159-162).

Note that while there was a general drop in reported relief pleasantness and omission SCR over time, the effects of Probability and Intensity remained present until the last run (see Supplementary Figure 5). This further confirms that probability and intensity manipulations were effective until the end of the task.

In the following sections of the rebuttal letter, we will go over the rest of the comments and our responses one by one.

Reviewer #1 (Public Review):

Summary:

Willems and colleagues test whether unexpected shock omissions are associated with reward-related prediction errors by using an axiomatic approach to investigate brain activation in response to unexpected shock omission. Using an elegant design that parametrically varies shock expectancy through verbal instructions, they see a variety of responses in reward-related networks, only some of which adhere to the axioms necessary for prediction error. In addition, there were associations between omission-related responses and subjective relief. They also use machine learning to predict relief-related pleasantness, and find that none of the a priori "reward" regions were predictive of relief, which is an interesting finding that can be validated and pursued in future work.

Strengths:

The authors pre-registered their approach and the analyses are sound. In particular, the axiomatic approach tests whether a given region can truly be called a reward prediction error. Although several a priori regions of interest satisfied a subset of axioms, no ROI satisfied all three axioms, and the authors were candid about this. A second strength was their use of machine learning to identify a relief-related classifier. Interestingly, none of the ROIs that have been traditionally implicated in reward prediction error reliably predicted relief, which opens important questions for future research.

Weaknesses:

To ensure that the number of omissions is similar across conditions, the task employs inaccurate verbal instructions; i.e. 25% of shocks are omitted, regardless of whether subjects are told that the probability is 100%, 75%, 50%, 25%, or 0%. Given previous findings on interactions between verbal instruction and experiential learning (Doll et al., 2009; Li et al., 2011; Atlas et al., 2016), it seems problematic a) to treat the instructions as veridical and b) average responses over time. Based on this prior work, it seems reasonable to assume that participants would learn to downweight the instructions over time through learning (particularly in the 100% and 0% cases); this would be the purpose of prediction errors as a teaching signal. The authors do recognize this and perform a subset analysis in the 21 participants who showed parametric increases in anticipatory SCR as a function of instructed shock probability, which strengthened findings in the VTA/SN; however given that one-third of participants (n=10) did not show parametric SCR in response to instructions, it seems like some learning did occur. As prediction error is so important to such learning, a weakness of the paper is that conclusions about prediction error might differ if dynamic learning were taken into account.

We thank the reviewer for raising this important concern. We believe we replied to all the issues raised in the general reply above.

Lastly, I think that findings in threat-sensitive regions such as the anterior insula and amygdala may not be adequately captured in the title or abstract which strictly refers to the "human reward system"; more nuance would also be warranted.

We fully agree with this comment and have changed the title and abstract accordingly.

Adaptations in the revised manuscript: We adapted the title of the manuscript.

“Omissions of Threat Trigger Subjective Relief and Prediction Error-Like Signaling in the Human Reward and Salience Systems”

Adaptations in the revised manuscript: We adapted the abstract (lines 27-29).

“In line with recent animal data, we showed that the unexpected omission of (painful) electrical stimulation triggers activations within key regions of the reward and salience pathways and that these activations correlate with the pleasantness of the reported relief.”

Reviewer #2 (Public Review):

The question of whether the neural mechanisms for reward and punishment learning are similar has been a constant debate over the last two decades. Numerous studies have shown that the midbrain dopamine neurons respond to both negative and salient stimuli, some of which can't be well accounted for by the classic RL theory (Delgado et al., 2007). Other research even proposed that aversive learning can be viewed as reward learning, by treating the omission of aversive stimuli as a negative PE (Seymour et al., 2004).

Although the current study took an axiomatic approach to search for the PE encoding brain regions, which I like, I have major concerns regarding their experimental design and hence the results they obtained. My biggest concern comes from the false description of their task to the participants. To increase the number of "valid" trials for data analysis, the instructed and actual probabilities were different. Under such a circumstance, testing axiom 2 seems completely artificial. How does the experimenter know that the participants truly believe that the 75% is more probable than, say, the 25% stimulation? The potential confusion of the subjects may explain why the SCR and relief report were rather flat across the instructed probability range, and some of the canonical PE encoding regions showed a rather mixed activity pattern across different probabilities. Also for the post-hoc selection criteria, why pick the larger SCR in the 75% compared to the 25% instructions? How would the results change if other criteria were used?

We thank the reviewer for raising this important concern. We believe the general reply above covers most of the issues raised in this comment. Concerning the post-hoc selection criteria, we took 25% < 75% as criterium because this was a quite “lenient” criterium in the sense that it looked only at the effects of interest (i.e., did anticipatory SCR increase with increasing instructed probability?). However, also when the criterium was more strict (e.g., selecting participants only if their anticipatory SCR monotonically increased with each increase in instructed probability 0% < 25% < 50% < 75% < 100%, N = 11 participants), the probability effect (ωp2 = 0.08), but not the intensity effect, for the VTA/SN remained.

To test axiom 3, which was to compare the 100% stimulation to the 0% stimulation conditions, how did the actual shock delivery affect the fMRI contrast result? It would be more reasonable if this analysis could control for the shock delivery, which itself could contaminate the fMRI signal, with extra confound that subjects may engage certain behavioral strategies to "prepare for" the aversive outcome in the 100% stimulation condition. Therefore, I agree with the authors that this contrast may not be a good way to test axiom 3, not only because of the arguments made in the discussion but also the technical complexities involved in the contrast.

We thank the reviewer for addressing this additional confound. It was indeed impossible to control for the delivery of shock since the delivery of the shock was always present on the 100% trials (and thus completely overlapped with the contrast of interest). We added this limitation to our discussion in the manuscript. In addition, we have also added a suggestion for a contrast that can test the “no surprise equivalence” criterium.

Adaptations in the revised manuscript: We adapted lines 358-364.

“Thus, given that we could not control for the delivery of the stimulation in the 100% > 0% contrast (the delivery of the stimulation completely overlapped with the contrast of interest), it is impossible to disentangle responses to the salience of the stimulation from those to the predictability of the outcome. A fairer evaluation of the third axiom would require outcomes that are roughly similar in terms of salience. When evaluating threat omission PE, this implies comparing fully expected threat omissions following 0% instructions to fully expected absence of stimulation at another point in the task (e.g. during a safe intertrial interval).”

Reviewer #3 (Public Review):

We thank the reviewer for their comments. Overall, based on the reviewer’s comments, we noticed that there was an imbalance between a focus on “relief” in the introduction and the rest of the manuscript and preregistration. We believe this focus raised the expectation that all outcome measures were interpreted in terms of the relief emotion. However, this was not what we did nor what we preregistered. We therefore restructured the introduction to reduce the focus on relief.

Adaptations in the revised manuscript: We restructured the introduction of the manuscript. Specifically, after our opening sentence: “We experience a pleasurable relief when an expected threat stays away1” we only introduce the role of relief for our research in lines 79-89.

“Interestingly, unexpected omissions of threat not only trigger neural activations that resemble a reward PE, they are also accompanied by a pleasurable emotional experience: relief. Because these feelings of relief coincide with the PE at threat omission, relief has been proposed to be an emotional correlate of the threat omission PE. Indeed, emerging evidence has shown that subjective experiences of relief follow the same time-course as theoretical PE during fear extinction. Participants in fear extinction experiments report high levels of relief pleasantness during early US omissions (when the omission was unexpected and the theoretical PE was high) and decreasing relief pleasantness over later omissions (when the omission was expected and the theoretical PE was low)22,23. Accordingly, preliminary fMRI evidence has shown that the pleasantness of this relief is correlated to activations in the NAC at the time of threat omission. In that sense, studying relief may offer important insights in the mechanism driving safety learning.”

Summary:

The authors conducted a human fMRI study investigating the omission of expected electrical shocks with varying probabilities. Participants were informed of the probability of shock and shock intensity trial-by-trial. The time point corresponding to the absence of the expected shock (with varying probability) was framed as a prediction error producing the cognitive state of relief/pleasure for the participant. fMRI activity in the VTA/SN and ventral putamen corresponded to the surprising omission of a high probability shock. Participants' subjective relief at having not been shocked correlated with activity in brain regions typically associated with reward-prediction errors. The overall conclusion of the manuscript was that the absence of an expected aversive outcome in human fMRI looks like a reward-prediction error seen in other studies that use positive outcomes.

Strengths:

Overall, I found this to be a well-written human neuroimaging study investigating an often overlooked question on the role of aversive prediction errors, and how they may differ from reward-related prediction errors. The paper is well-written and the fMRI methods seem mostly rigorous and solid.

Weaknesses:

I did have some confusion over the use of the term "prediction-error" however as it is being used in this task. There is certainly an expectancy violation when participants are told there is a high probability of shock, and it doesn't occur. Yet, there is no relevant learning or updating, and participants are explicitly told that each trial is independent and the outcome (or lack thereof) does not affect the chances of getting the shock on another trial with the same instructed outcome probability. Prediction errors are primarily used in the context of a learning model (reinforcement learning, etc.), but without a need to learn, the utility of that signal is unclear.

We operationalized “prediction error” as the response to the error in prediction or the violation of expectancy at the time of threat omission. In that sense, prediction error and expectancy violation (which is more commonly used in clinical research and psychotherapy; Craske et al., 2014) are synonymous. While prediction errors (or expectancy violations) are predominantly studied in learning situations, the definition in itself does not specify how the “expectancy” or “prediction” arises: whether it was through learning based on previous experience or through mere instruction. The rationale why we moved away from a conditioning study in the present manuscript is discussed in our general reply above.

We agree with the reviewer that studying prediction errors outside a learning context limits the ecological validity of the task. However, we do believe there is also a strength to this approach. Specifically, the omission-related responses we measure are less confounded by subsequent learning (or updating of the wrongful expectation). Any difference between our results and prediction error responses in learning situation can therefore point to this exact difference in paradigm, and can thus identify responses that are specific to learning situations.

An overarching question posed by the researchers is whether relief from not receiving a shock is a reward. They take as neural evidence activity in regions usually associated with reward prediction errors, like the VTA/SN . This seems to be a strong case of reverse inference. The evidence may have been stronger had the authors compared activity to a reward prediction error, for example using a similar task but with reward outcomes. As it stands, the neural evidence that the absence of shock is actually "pleasurable" is limited-albeit there is a subjective report asking subjects if they felt relief.

We thank the reviewer for cautioning us and letting us critically reflect on our interpretation. We agree that it is important not to be overly enthusiastic when interpreting fMRI results and to attribute carelessly psychological functions to mere activations. Therefore, we will elaborate on the precautions we took not to minimize detrimental reverse inference.

First, prior to analyzing our results, we preregistered clear hypotheses that were based on previous research, in addition to clear predictions, regions of interest and a testing approach on OSF. With our study, we wanted to investigate whether unexpected omissions of threat: (1) triggered activations in the VTA/SN, putamen, NAc and vmPFC (as has previously been shown in animal and human studies); (2) represent PE signals; and (3) were related to self-reported relief, which has also been shown to follow a PE time-curve in fear extinction (Vervliet et al., 2017). Based on previous research, we selected three criteria all PE signals should comply to. This means that if omission-related activations were to represent true PE signals, they should comply to these criteria. However, we agree that it would go too far to conclude based on our research that relief is a reward, or even that the omission-related activations represent only PE signals. While we found support for most of our hypotheses, this does not preclude alternative explanations. In fact, in the discussion, we acknowledge this and also discuss alternative explanations, such as responding to the salience (lines 395-397; “One potential explanation is therefore that the deactivation resulted from a switch from default mode to salience network, triggered by the salience of the unexpected threat omission or by the salience of the experienced stimulation.”), or anticipation (line 425-426; “... we cannot conclusively dismiss the alternative interpretation that we assessed (part of) expectancy instead”).

Second, we have deliberately opted to only use descriptive labels such as omission-related activations when we are discussing fMRI results. Only when we are talking about how the activations were related to self-reported relief, we talk about relief-related activations.

I have some other comments, and I elaborate on those above comments, below:

(1) A major assumption in the paper is that the unexpected absence of danger constitutes a pleasurable event, as stated in the opening sentence of the abstract. This may sometimes be the case, but it is not universal across contexts or people. For instance, for pathological fears, any relief derived from exposure may be short-lived (the dog didn't bite me this time, but that doesn't mean it won't next time or that all dogs are safe). And even if the subjective feeling one gets is temporary relief at that moment when the expected aversive event is not delivered, I believe there is an overall conflation between the concepts of relief and pleasure throughout the manuscript. Overall, the manuscript seems to be framed on the assumption that "aversive expectations can transform neutral outcomes into pleasurable events," but this is situationally dependent and is not a common psychological construct as far as I am aware.

We thank the reviewer for their comment. We have restructured the introduction because we agree with the reviewer that the introduction might have set false expectations concerning our interpretation of the results. The statements related to relief have been toned down in the revised manuscript.

Still, we want to note that the initial opening statement “unexpected absence of danger constitutes the pleasurable emotion relief” was based on a commonly used definition of relief that states that relief refers to “the emotion that is triggered by the absence of expected or previously experienced negative stimulation ” (Deutsch, 2015). Both aspects that it is elicited by the absence of an otherwise expected aversive event and that it is pleasurable in nature has received considerable empirical support in emotion and fear conditioning research (Deutsch et al., 2015; Leknes et al., 2011; Papalini et al., 2021; Vervliet et al., 2017; Willems & Vervliet, 2021).

That said, the notion that the feeling of relief is linked to the (reward) prediction error underlying the learning of safety is included in several theoretical papers in order to explain the commonly observed dopaminergic response at the time of threat omission (both in animals and humans; Bouton et al., 2020; Kalisch et al., 2019; Pittig et al., 2020).

Together, these studies indicate that the definition of relief, and its potential role in threat omission-driven learning is – at least in our research field – established. Still, we felt that more direct research linking feelings of relief to omission-related brain responses was warranted.

One of the main reasons why we specifically focus on the “pleasantness” of the relief is to assess the hedonic impact of the threat omission, as has been done in previous studies by our lab and others (Leknes et al., 2011; Leng et al., 2022; Papalini et al., 2021; Vervliet et al., 2017; Willems & Vervliet, 2021). Nevertheless, we agree with the reviewer that the relief we measure is a short-lived emotional state that is subjected to individual differences (as are all emotions).

(2) The authors allude to this limitation, but I think it is critical. Specifically, the study takes a rather simplistic approach to prediction errors. It treats the instructed probability as the subjects' expectancy level and treats the prediction error as omission related activity to this instructed probability. There is no modeling, and any dynamic parameters affected by learning are unaccounted for in this design . That is subjects are informed that each trial is independently determined and so there is no learning "the presence/absence of stimulations on previous trials could not predict the presence/absence of stimulation on future trials." Prediction errors are central to learning. It is unclear if the "relief" subjects feel on not getting a shock on a high-probability trial is in any way analogous to a prediction error, because there is no reason to update your representation on future trials if they are all truly independent. The construct validity of the design is in question.

(3) Related to the above point, even if subjects veered away from learning by the instruction that each trial is independent, the fact remains that they do not get shocks outside of the 100% probability shock. So learning is occurring, at least for subjects who realize the probability cue is actually a ruse.

We thank the reviewer for raising these concerns. We believe that the general reply above covers the issues raised in points 2 and 3.

(4) Bouton has described very well how the absence of expected threat during extinction can create a feeling of ambiguity and uncertainty regarding the signal value of the CS. This in large part explains the contextual dependence of extinction and the "return of fear" that is so prominent even in psychologically healthy participants. The relief people feel when not receiving an expected shock would seem to have little bearing on changing the long-term value of the CS. In any event, the authors do talk about conditioning (CS-US) in the paper, but this is not a typical conditioning study, as there is no learning.

We fully agree with the reviewer that our study is no typical conditioning study. Nevertheless, because our research mostly builds on recent advances in the fear extinction domain, we felt it was necessary to introduce the fear extinction procedure and related findings. In the context of fear extinction learning, we have previously shown that relief is an emotional correlate of the prediction error driving acquisition of the novel safety memory (CSnoUS; Papalini et al., 2021; Vervliet et al., 2017). The ambiguity Bouton describes is the result of extinguished CS holding multiple meanings once the safety memory is acquired. Does it signal danger or safety? We agree with Bouton that the meaning of the CS for any new encounter will depend on the context, and the passage of time, but also on the initial strength of the safety acquisition (which is dependent on the size of the prediction error, and hence the amount of relief; Craske et al., 2014). However, it was not our objective to directly study the relation of relief to subsequent CS value, and our design is not tailored to do so post hoc.

(5) In Figure 2 A-D, the omission responses are plotted on trials with varying levels of probability. However, it seems to be missing omission responses in 0% trials in these brain regions. As depicted, it is an incomplete view of activity across the different trial types of increasing threat probability.

We thank the reviewer for pointing out this unclarity. The betas that are presented in the figures represent the ROI averages from each non-0% vs 0% contrasts (i.e., 25%>0%; 50%>0%; and 75%>0% for the weak, moderate and strong intensity levels). Any positive beta therefore indicates a stronger activation in the given region compared to a fully predicted omission. Any negative beta indicates a weaker activation.

Adaptations in the revised manuscript: We have adapted the figure captions of figures 2 and 3.

“The extracted beta-estimates in figures A-D represent the ROI averages from each non0% > 0% contrast (i.e., 25%>0%; 50%>0%; and 75%>0% for the weak, moderate and strong intensity levels). Any positive beta therefore indicates a stronger activation in the given region compared to a fully predicted omission. Any negative beta indicates a weaker activation.”

(6) If I understand Figure 2 panels E-H, these are plotting responses to the shock versus no-shock (when no-shock was expected). It is unclear why this would be especially informative, as it would just be showing activity associated with shocks versus no-shocks. If the goal was to use this as a way to compare positive and negative prediction errors, the shock would induce widespread activity that is not necessarily reflective of a prediction error. It is simply a response to a shock. Comparing activity to shocks delivered after varying levels of probability (e.g., a shock delivered at 25% expectancy, versus 75%, versus 100%) would seem to be a much better test of a prediction error signal than shock versus no-shock.

We thank the reviewer for this comment. The purpose of this preregistered contrast was to test whether fully predicted outcomes elicited equivalent activations in our ROIs (corresponding to the third prediction error axiom). Specifically, if a region represents a pure prediction error signal, the 100% (fully predicted shocks) > 0% (fully predicted shock omissions) contrast should be nonsignificant, and follow-up Bayes Factors would further provide evidence in favor of this null-hypothesis.

We agree with the reviewer that the delivery of the stimulation triggers widespread activations in our regions of interest that confounded this contrast. However, given that it was a preregistered test for the prediction error axioms, we cannot remove it from the manuscript. Instead, we have argued in the discussion that future studies who want to take an axiomatic stance should consider alternative tests to examine this axiom.

Adaptations in the revised manuscript: We adapted lines 358-364.

“Thus, given that we could not control for the delivery of the stimulation in the 100% > 0% contrast (the delivery of the stimulation completely overlapped with the contrast of interest), it is impossible to disentangle responses to the salience of the stimulation from those to the predictability of the outcome. A fairer evaluation of the third axiom would require outcomes that are roughly similar in terms of salience. When evaluating threat omission PE, this implies comparing fully expected threat omissions following 0% instructions to fully expected absence of stimulation at another point in the task (e.g. during a safe intertrial interval).”

Also note that our task did not lend itself for an in-depth analysis of aversive (worse-thanexpected) prediction error signals, given that there was only one stimulation trial for each probability x intensity level (see Supplemental Figure 1). The most informative contrast that can inform us about aversive prediction error signals contrasts all non-100% stimulation trials with all 100% stimulation trials. The results of this contrast are presented in Supplemental Figure 16 and Supplemental Table 11 for completeness.

(7) I was unclear what the results in Figure 3 E-H were showing that was unique from panels A-D, or where it was described. The images looked redundant from the images in A-D. I see that they come from different contrasts (non0% > 0%; 100% > 0%), but I was unclear why that was included.

We thank the reviewer for this comment. Our answer is related to that of the previous comment. Figure 3 presents the results of the axiomatic tests within the secondary ROIs we extracted from a wider secondary mask based on the non0%>0% contrast.

(8) As mentioned earlier, there is a tendency to imply that subjects felt relief because there was activity in "the reward pathway ."

We thank the reviewer for their comment, but we respectfully disagree. Subjective relief was explicitly probed when the instructed stimulations stayed away. In the manuscript we only talk about “relief” when discussing these subjective reports. We found that participants reported higher levels of relief-pleasantness following omissions of stronger and more probable threat. This was an observation that matches our predictions and replicates our previous behavioral study (Willems & Vervliet, 2021).

The fMRI evidence is treated separately from the “pleasantness” of the relief. Specifically, we refrain from calling the threat omission-related neural responses “relief-activity” as this would indeed imply that the activation would only be attributed to this psychological function. Instead, we talked about omission-related activity, and we assessed whether it complied to the prediction error criteria as specified by the axiomatic approach.

Only afterwards, because we hypothesized that omission-related fMRI activation and selfreported relief-pleasantness were related, and because we found a similar response pattern for both measures, we examined how relief and omission-related fMRI activations within our ROIs were related on a trial-by-trial basis. To this end, we entered relief-pleasantness ratings as a parametric modulator to the omission regressor.

By no means do we want to reduce an emotional experience (relief) to fMRI activations in isolated regions in the brain. We agree with the reviewer that this would be far too reductionist. We therefore also ran a pre-registered LASSO-PCR analysis in order to identify whether a whole-brain pattern of activations can predict subjective relief (independent from the exact instructions we gave, and independent of our a priori ROIs). This analysis used trialby-trial patterns of activation across all voxels in the brain as the predictor and self-reported relief as the outcome variable. It is therefore completely data-driven and can be seen as a preregistered exploratory analysis that is intended to inform future studies.

(9) From the methods, it wasn't entirely clear where there is jitter in the course of a trial. This centers on the question of possible collinearity in the task design between the cue and the outcome. The authors note there is "no multicollinearity between anticipation and omission regressors in the firstlevel GLMs," but how was this quantified? b The issue is of course that the activity coded as omission may be from the anticipation of the expected outcome.

We thank the reviewer for pointing out this unclarity. Jitter was introduced in all parts of the trial: i.e., the duration of the inter-trial interval (4-7s), countdown clock (3-7s), and omission window (4-8s) were all jittered (see fig. 1A and methods section, lines 499-507). We added an additional line to the method section.

Adaptations in the revised manuscript: We added an additional line of to the methods section to further clarify the jittering (lines 498-500).

“The scale remained on the screen for 8 seconds or until the participant responded, followed by an intertrial interval between 4 and 7 seconds during which only a fixation cross was shown. Note that all phases in the trial were jittered (i.e., duration countdown clock, duration outcome window, duration intertrial interval).”

Multicollinearity between the omission and anticipation regressors was assessed by calculating the variance inflation factor (VIF) of omission and anticipation regressors in the first level GLM models that were used for the parametric modulation analyses.

Adaptations in the revised manuscript: We replaced the VIF abbreviation with “variance inflation factor” (line 423-424).

“Nevertheless, there was no multicollinearity between anticipation and omission regressors in the first-level GLMs (VIFs Variance Inflation Factor, VIF < 4), making it unlikely that the omission responses purely represented anticipation.”

(10) I did not fully understand what the LASSO-PCR model using relief ratings added. This result was not discussed in much depth, and seems to show a host of clusters throughout the brain contributing positively or negatively to the model. Altogether, I would recommend highlighting what this analysis is uniquely contributing to the interpretation of the findings.

The main added value of this analyses is that it uses a different approach altogether. Where the (mass univariate) parametric modulation analysis estimated in each voxel (and each ROI) whether the activity in this voxel/ROI covaried with the reported relief, a significant activation only indicated that this voxel was related to relief. However, given that each voxel/ROI is treated independently in this analysis, it remains unclear how the activations were embedded in a wider network across the brain, and which regions contributed most to the prediction of relief. The multivariate LASSO-PCR analysis approach we took attempts to overcome this limitation by examining if a more whole-brain pattern can predict relief. Because we use the whole-brain pattern (and not only our a priori ROIs), this analysis is completely data-driven and is intended to inform future studies. In addition, the LASSO-PCR model was cross-validated using five-fold cross-validation, which is also a difference (and a strength) compared to the mass univariate GLM approach.

One interesting finding that only became evident when we combined univariate and multivariate approaches is that despite that the parametric modulation analysis showed that omission-related fMRI responses in the ROIs were modulated by the reported relief, none of these ROIs contributed significantly to the prediction of relief based on the identified signature. Instead, some of the contributing clusters fell within other valuation and errorprocessing regions (e.g. lateral OFC, mid cingulate, caudate nucleus). This suggests that other regions than our a priori ROIs may have been especially important for the subjective experience of relief, at least in this task. However, all these clusters were small and require further validation in out of sample participants. More research is necessary to test the generalizability and validity of the relief signature to new individuals and tasks, and to compare the signature with other existing signature models (e.g., signature of pain, fear, reward, pleasure). However, this was beyond the scope of the present study.

Adaptations in the revised manuscript: We altered the explanation of the LASSO-PCR approach in the results section (lines 286-295) and the discussion (lines 399-402)

Adaptations in the Results section: “The (mass univariate) parametric modulation analysis showed that omission-related fMRI activity in our primary and secondary ROIs correlated with the pleasantness of the relief. However, given that each voxel/ROI is treated independently in this analysis, it remains unclear how the activations were embedded in a wider network of activation across the brain, and which regions contributed most to the prediction of relief. To overcome these limitations, we trained a (multivariate) LASSO-PCR model (Least Absolute Shrinkage and Selection Operator-Regularized Principle Component Regression) in order to identify whether a spatially distributed pattern of brain responses can predict the perceived pleasantness of the relief (or “neural signature” of relief)31. Because we used the whole-brain pattern (and not only our a priori ROIs), this analysis is completely data driven and can thus identify which clusters contribute most to the relief prediction.”

Adaptations in the Discussion section: “In addition to examining the PE-properties of neural omission responses in our a priori ROIs, we trained a LASSO-PCR model to establish a signature pattern of relief. One interesting finding that only became evident when we compared the univariate and multivariate approach was that none of our a priori ROIs appeared to be an important contributor to the multivariate neural signature, even though all of them (except NAc) were significantly modulated by relief in the univariate analysis.”

In addition to the public peer review, the reviewers provided some recommendation on how to further improve our manuscript. We will reply to the recommendations below.

Reviewer #1 (Recommendations For The Authors):

Given that you do have trial-level estimates from the classifier analysis, it would be very informative to use learning models and examine responses trial-by-trial to test whether there are prediction errors that vary over time as a function of learning.

We thank the reviewer for the suggestion. However, based on the results of the run-regressor, we do not anticipate large learning effects in our paradigm. As we mentioned in our responses above, we controlled for time-related drops in omission-responding by including a “run” regressor in our analyses. Results of this regressor for subjective relief and omission-related SCR showed that although there was a general drop in reported relief pleasantness and omission SCR over time, the effects of probability and intensity remained present until the last run. This suggests that even though some learning might have taken place, its effect was likely small and did not abolish our manipulations of probability and intensity. In any case, we cannot use the LASSO-PCR signature model to investigate learning, as this model uses the trial-level brain pattern at the time of US omission to estimate the associated level of relief. These estimates can therefore not be used to examine learning effects.

Reviewer #2 (Recommendations For The Authors):

The LASSO-PCR model feels rather disconnected from the rest of the paper and does not add much to the main theme. I would suggest to remove this part from the paper.

We thank the reviewer for this suggestion. However, the LASSO-PCR analysis was a preregistered. We therefore cannot remove it from the manuscript. We hope to have clarified its added value in the revised version of the manuscript.

Author response:

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

We have revised the manuscript mainly in the following aspects: (1) the data of electrophysiological and behavioral responses of larvae and adults to trehalose have been added, and the related figures and texts have been modified accordingly; (2) the photos of taste organs of larvae and adults indicating the position of recorded sensilla have been added; (3) the potential off-target effects of GR knock-out on other GR expressions has been carefully explained and revised in the relevant text; (4) the abstract has been revised to present the findings more technically in a limited number of words; (5) some details of experiments in Materials and Methods and some new literatures have been added; (6) a new figure (Figure 8) summarizing the main findings of the study has been added.

In the following, we respond to the reviewers’ comments and suggestions one by one. We hope that our answers will satisfy you and the three reviewers. We are also very happy to get further valuable advices from you.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The process of taste perception is significantly more intricate and complex in Lepidopteran insects. This investigation provides valuable insights into the role of Gustatory receptors and their dynamics in the sensation of sucrose, which serves as a crucial feeding cue for insects. The article highlights the differential sensitivity of Grs to sucrose and their involvement in feeding and insect behavior.

Strengths:

To support the notion of the differential specificity of Gr to sucrose, this study employed electrophysiology, ectopic expression of Grs in Xenopus, genome editing, and behavioral studies on insects. This investigation offers a fundamental understanding of the gustation process in lepidopteran insects and its regulation of feeding and other gustation-related physiological responses. This study holds significant importance in advancing our comprehension of lepidopteran insect biology, gustation, and feeding behavior.

Thank you for your recognition of our research.

Weaknesses:

While this manuscript demonstrates technical proficiency, there exists an opportunity for additional refinement to optimize comprehensibility for the intended audience. Several crucial sugars have been overlooked in the context of electrophysiology studies and should be incorporated. Furthermore, it is imperative to consider the potential off-target effects of Gr knock-out on other Gr expressions. This investigation focuses exclusively on Gr6 and Gr10, while neglecting a comprehensive narrative regarding other Grs involved in sucrose sensation.

We accept the reviewer's suggestion. Because trehalose is a main sugar in insect blood, and it is converted by insects after feeding on plant sugars, we have added the new data on electrophysiological and behavioral responses of larvae and adults of Helicoverpa armigera to trehalose (see Figure 1-2, Figure 1-figure supplement 1, Figure 2-figure supplement 1). Now, the total eight sugars include 2 pentoses (arabinose and xylose), 4 hexoses (fructose, fucose, galactose and glucose), and 2 disaccharides (sucrose and trehalose), which were chosen because they are mainly present in host-plants of H. armigera and/or representative in the structure and source of sugars.

We fully agree to the reviewer’s opinion and have already taken the potential off-target effects of CRISPR/Cas9 knockout of Gr on other GR expressions into consideration. To predict the potential off-target sites of sgRNA of Gr6 and Gr10 establishing homozygous mutants using CRISPR/Cas9 technology, we first use online software CasOFFinder (http://www.rgenome.net/cas-offinder/) to blast the genome of the wild type cotton bollworm and set the mismatch number less than or equal to 3. We found that Gr10 sgRNA had no potential potential off-target site, and the sgRNA of Gr6 had only one potential off-target site. Therefore, we designed primers according to the sequence of potential off-target sites of Gr6 sgRNA, and conducted PCR using genomic DNA of homozygous mutant as a template， performed Sanger sequencing on the PCR products obtained, and found that the potential off-target sites of Gr6 sgRNA were no different from those of the wild type. Particularly, concerning the sgRNA of Gr6 and Gr10 may produce off-target effects on other sugar receptor genes of H. armigera, we conducted the same off-target site analysis with the designed sgRNA on each of the other eight sugar receptor genes, and found that there were no off-target sites on these receptor genes (see Line254-256).

Reviewer #2 (Public Review):

Summary:

To identify sugar receptors and assess the capacity of these genes the authors first set out to identify behavioral responses in larvae and adults as well as physiological response. They used phylogenetics and gene expression (RNAseq) to identify candidates for sugar reception. Using first an in vitro oocyte system they assess the responses to distinct sugars. A subsequent genetic analysis shows that the Gr10 and Gr6 genes provide stage specific functions in sugar perception.

Strengths:

A clear strength of the manuscript is the breadth of techniques employed allowing a comprehensive study in a non-canonical model species.

Thank you for your recognition of our research.

Weaknesses:

There are no major weaknesses in the study for the current state of knowledge in this species. Since it is much basic work to establish a broader knowledge, context with other modalities remains unknown. It might have been possible to probe certain contexts known from the fruit fly, which would have strengthened the manuscript.

Thank you so much for your suggestion. According to this suggestion, we further added some sentences probing sugar sensing and behaviors of fruit fly larvae in the Introduction and discussion sections (Line 68-71 in Introduction section, Line 395-399 in Discussion section).

Reviewer #3 (Public Review):

In this study, the authors combine electrophysiology, behavioural analyses, and genetic editing techniques on the cotton bollworm to identify the molecular basis of sugar sensing in this species.

The larval and adult forms of this species feed on different plant parts. Larvae primarily consume leaves, which have relatively lower sugar concentrations, while adults feed on nectar, rich in sugar. Through a series of experiments-spanning electrophysiological recordings from both larval and adult sensillae, qPCR expression analysis of identified GRs from these sensillae, response profiles of these GRs to various sugars via heterologous expression in Xenopus oocytes, and evaluations of CRISPR mutants based on these parameters-the authors discovered that larvae and adults employ distinct GRs for sugar sensing. While the larva uses the highly sensitive GR10, the adult uses the less sensitive and broadly tuned GR6. This differential use of GRs are in keeping with their behavioral ecology.

The data are cohesive and consistently align across the methodologies employed. They are also well presented and the manuscript is clearly written.

Recommendations for the authors:

While appreciating the quality of the work and its presentation, we have a few comments for the authors, should they wish to consider them, that would significantly improve the presentation of the work.

Title: Could the authors please revisit their title to better reflect the main finding of their work?

The title has been changed into “The larva and adult of Helicoverpa armigera use differential gustatory receptors to sense sugars”.

Text: There are a few comments related to the text, and these are listed below:

(1) Could the authors place their work in the context of what's known about sugar sensing in Drosophila larva and adult?

In the Introduction section, we added the status of research on sugar perception in Drosophila larvae, pointing out "No external sugar-sensing mechanism in Drosophila larvae has yet been characterized." (Line 70-71); in the Discussion section, the research progress of sugar sensing in Drosophila adults and larvae was also summarized (Line 397-399).

(2) For each results section, could the authors please include a sentence or two that interprets the data in the context of previously presented data?

We accept the reviewer's suggestion. In order to make it easy for readers to follow up, we included a sentence interprets the above data at the beginning of each part of the Results on the premise of avoiding duplication.

(3) Could the authors please provide details of the generation and screening of the CRISPR mutants?

We have added more details on mutant establishment and screening in the Materials and Methods section (Line 722-726, 729-732).

Figures: Could the authors please include images and schematics wherever possible? For example, a schematic depicting the position of the sense organs and one summarising the main findings of the studies.

In Figure 1 we added the photo of each taste organ, on which the recorded sensilla were indicated. We also added a new figure, Figure 8, summarizing the main findings of the study.

Choice of Sugars: Could the authors please justify their choice of sugars they have used in the analyses?

In the first paragraph of the Results section of the article, we further explain the reasons for using the sugars in the study. “We first investigated the electrophysiological responses of the lateral and medial sensilla styloconica in the larval maxillary galea to eight sugars. These sugars were chosen because they are mostly found in host-plants of H. armigera or are representative in the structure and source of sugars.”

In addition to this, there are several specific comments in the detailed reviewers comments below, which the authors could consider responding to.

Reviewer #1 (Recommendations For The Authors):

The article titled "Sucrose taste receptors exhibit dissimilarities between larval and adult stages of a moth" by Shuai-Shuai Zhang and colleagues provides an intriguing analysis. The authors have conducted a meticulously planned and executed study. However, I do have some inquiries.

(1) What precisely does the term "differ" signify in the title? It can be expounded upon in terms of differing in expression or sensitivity. The title could benefit from being more informative. The authors should appropriately specify the insect species in the title of the paper. This would make it more comprehensible to readers. Merely mentioning the term "moth" does not provide any information about the model organism. Hence, it would be preferable to mention Helicoverpa armigera instead of using the generic term "moth" in the title.

Thank you for your suggestions. We considered it better to emphasize that the receptors for sucrose are different, and we have accepted the suggestion of adding the name of the animal. The title has been changed into “The larva and adult of Helicoverpa armigera use differential gustatory receptors to sense sugars”.

(2) The abstract is written in a simple and easily understandable manner, but it overlooks important findings from a technical standpoint.

We add some key experimental techniques to illustrate some important findings in the Abstract.

(3). Almost all herbivorous insects are said to consume plants and utilize sucrose as a stimulus for feeding, as stated by the authors. Sucrose, glucose, and fructose sugar are among the commonly observed stimulants for feeding in numerous insects. It would be appropriate to incorporate not only sucrose but also glucose and fructose as feeding stimulants for almost all herbivorous insects.

Thank you for your suggestion. Sucrose is the major sugar in plants, and its concentration varies greatly from tissue to tissue, while the concentration of the hexose sugars is much lower and the concentration does not change much. In Line 48, we state that sucrose, glucose, and fructose are feeding stimuli for herbivorous insects. From the previous studies, it seems that sucrose is the strongest, followed by fructose, and finally glucose. The cotton bollworm larvae showed no electrophysiological and behavioral response to glucose.

(4) The reason why trehalose is not considered in the electrophysiology analysis is unclear. Given that trehalose is a major sugar in insects and plants, it would be intriguing to include it in the analysis.

We have accepted the reviewer's suggestion, and supplemented the electrophysiological responses of taste organs in larvae and adults of Helicoverpa armigera to trehalose (Figure 1, Figure 1-Figure Supplement 1), and also tested the behavioral responses of the larvae and adults to trehalose (Figure 2, Figure 2-Figure Supplement 1). Therefore, all the related figures have been changed.

(5) The author's intention regarding the co-receptor relationship between Gr5 and Gr6 (line 211) is unclear. If this is indeed the case, then the reason for considering Gr5 in further studies remains uncertain.

We have changed the sentence as follows: “Since Gr5 was highly expressed with Gr6 in the proboscis and tarsi (Figure 3D-3E, Figure 3—figure supplement 1), we suspected that Gr5 and Gr6 might be expressed in the same cells, and then tested the response profile of their co-expression in oocytes.”

(6) The homologous nature of Grs is emphasized by the authors. It is not specified how the author ensured that the guide RNA targeting Gr6 or Gr10 did not result in off-target effects on other Grs.

Thank you so much for your suggestion. We have rewritten the relevant paragraph (Line 238-251), detailing our tests and the results on the potential off-target effects of knocking out GRs by CRISPR/Cas9: “In order to predict the potential off-target sites of sgRNA of Gr6 and Gr10, we used online software Cas-OFFinder (http://www.rgenome.net/cas-offinder/) to blast the genome of H. armigera, and the mismatch number was set to less than or equal to 3. According to the predicted results, the Gr10 sgRNA had no potential off-target region but Gr6 sgRNA had one. Therefore, we amplified and sequenced the potential off-target region of Gr6-/- and found there was no frameshift or premature stop codon in the region compared to WT (Figure 5—figure supplement 2). It is worth mentioning that there was no potential off-target region of Gr6 and Gr10 sgRNA in other sugar receptor genes of H. armigera, Gr4, Gr5, Gr7, Gr8, Gr9, Gr11 and Gr12. We further found there was no difference in the response to xylose of the medial sensilla styloconica among WT, Gr10-/- and Gr6-/- (Figure 5—figure supplement 2). Furthermore, WT, Gr10-/- and Gr6-/- did not show differences in the larval body weight, adult lifespan, and number of eggs laid per female (Figure 5—figure supplement 2). All these results suggest that no off-target effects occurred in the study.”

(7) Is it possible that knocking out Gr10 is not compensated for by the overexpression of Gr6 or other sucrose sensing Grs? Similarly, would the vice versa scenario hold true?

In the Discussion section, we have added some sentences to discuss this issue: “From our results, knocking out Gr10 or Gr6 is unlikely to be compensated by overexpression of other sugar GRs. One of our recent studies showed that Orco knockout had no significant effect on the expression of most OR, IR and GR genes in adult antennae of H. armigera, but some genes were up- or down-regulated (Fan et al., 2022).”

(8) What was the rationale for selecting nine candidate GR genes for expression analysis?

Based on the reviewer's suggestion, we expanded the relevant paragraphs to illustrate the rationale for selecting nine candidate GR genes for expression analysis: “To reveal the molecular basis of sugar reception in the taste sensilla of H. armigera, we first analyzed the putative sugar gustatory receptor genes based on the reported gene sequences of GRs in H. armigera and their phylogenetic relationship of D. melanogaster sugar gustatory receptors (Jiang et al., 2015; Pearce et al., 2017; Xu et al., 2017). Nine putative sugar GR genes, Gr4–12 were identified, and their full-length cDNA sequences were cloned (The GenBank accession number is provided in Appendix—Table S1).” (Line 155-161)

(9) What is the potential reason for the difference between the major larval sugar receptors of Drosophila and Lepidopterans?

The difference between the major larval sugar receptors of Drosophila and Lepidopterans is probably due to differences in the food their larvae feed on. Fruit fly larvae feed on rotten fruit, the main sugar of which is fructose. The larvae of Lepidoptera mainly feed on plants, and the main sugar is sucrose. In the Discussion section, we have added a sentence “This is most likely due to fruit fly larvae feeding on rotten fruits, which contain fructose as the main sugar.” (Line 399-401)

(10) There is a disparity in GRs, specifically GR5 and GR6, between the female antenna, proboscis, and tarsi. What could be the possible justification and significance of this?

Thank you so much for this question. We have added a sentence in the Discussion section, “In this study, the expression patterns of 9 sugar GRs in three taste organs of adult H. armigera show that there is a disparity in GRs, specifically GR5 and GR6, between the female antenna, tarsi and proboscis, which may be an evolutionary adaptation reflecting subtle differentiation in the function of these taste organs in adult foraging. Antennae and tarsi play a role in the exploration of potential sugar sources, while the proboscis plays a more precise role in the final decision to feed.” (Line 433-438)

(11) I suggest that a visual representation illustrating the positioning of GSNs, particularly the lateral and medial sensilla, in both larva and adult stages would enhance the correlation with the results.

In Figure 1 we added the photo of each taste organ and the position of the recorded sensilla, and also added a new figure, Figure 8 summarizing the main findings of the studies.

(12) Further experiments can be conducted to elucidate the precise molecular mechanisms, particularly the downstream effects of GRs, in order to establish the specificity of GRs more convincingly.

Thank you so much for your suggestion. We have discussed the further experiments in the Discussion section, “To elucidate the precise molecular mechanisms of sugar reception in H. armigera is necessary to compare a series of single, double and even multiple Gr knock-out lines and investigate the downstream effects of the GRs.” (Line 363-369)

(13) Figure 6 caption: In Figure 6 (D to I), the percentage of PER is depicted. There is redundancy in the Y-axis title (Percentage of PER) and the legend. This appears to be repetitive. I suggest that it would be better to include the Y-axis title only in Figure D or in Figures D and G.

We accept the suggestion. Figure 7 (not Figure 6) has been revised accordingly.

(14) In Figures 6A and 6C, there is inconsistency in the colors used for WT, Gr6, and Gr10. This could potentially confuse the reader. I recommend using the same colors in both figures instead of using a blue color. Please specify how the authors calculated the feeding area in Figure 6.

We accept the reviewer's suggestion and have changed the color of Figure 7A, B. We have also added the detail method for calculating feeding area (Line 541-545).

(15) In Two-choice tests, why did the authors use 0.01% Tween 80? Please provide comments on this.

Use of 0.01% Tween 80 is to reduce the surface tension and increase the malleability of the solution. We have given detailed explanation in the Method section and cite the reference. (Line538-540)

(16) It would be valuable if the authors could comment on the prospects of this study, considering that GRs play a vital role in controlling behavior and developmental pathways. What are the potential consequences of blocking or disrupting these receptors in terms of behavioral and developmental phenotypic deformities? Could this potentially lead to increased insect mortality?

Thank you so much for your suggestions. In the last paragraph of the Discussion section, we have added the following perspectives, “Knockout of Gr10 or Gr6 led to a significant decrease in sugar sensitivity and food preference of the larvae and adults of H. armigera, respectively, which is bound to bring adverse consequences to survival and reproduction of the insects. Therefore, studying the molecular mechanisms underlying sugar perception in phytophagous insects may provide new insights into the behavioral ecology of this important and highly diverse group of insects, and measures blocking or disrupting sugar receptors could also have applications to control agricultural pests and improve crop yields worldwide” (Line 449-456).

Reviewer #2 (Recommendations for The Authors):

There are a few comments, that I feel would be beneficial to be addressed.

• The authors used 7 different sugars for their experimental approach. While I agree that this is a sufficiently large collection for a study, I was wondering why they specifically chose these sugars; an explanatory section might be helpful for a reader to follow the reasoning.

According to reviewer 1's suggestion, we increased trehalose to 8 sugars in experiments. Trehalose is a main sugar in insect blood. It is converted by insects after feeding on plant sugars. The 8 sugars were chosen because they are present in host-plants of H. armigera or are representative in the structure and source of sugars. They contain 2 pentoses (arabinose and xylose), 4 hexoses (fructose, fucose, galactose and glucose), and 2 disaccharides (sucrose and trehalose).

• It might be beneficial to provide some broader overview on the gustatory system in the cotton bollworm, particularly at the larval stage since this may not be common knowledge. Along these lines eg. the complexity of sensilla types, organs and overall number (or estimation) of neurons might be good to know, a graphical representation of the sense organs might be informative.

In the Introduction section, we give a more specific description on sugar sensitive GSNs in the taste system of the larva and adult of H. armigera, and cite the corresponding references.

• Concerning phylogeny of GRs, it might be relevant to know how complete the genome information is and some more general background on GR diversity in the cotton bollworm.

We agree to your opinion. According to this idea, we got the putative sugar GRs from the previously published genome (Pearce et al. 2017) and the related annotation of GRs (Jiang et al. 2015, Xu et al. 2012). We have made a more detailed explanation about this in the new version of the manuscript, “We first analyzed the putative sugar gustatory receptor genes based on the genome data of H. armigera (Pearce et al. 2017), the reported gene sequences of sugar GRs in H. armigera and their phylogenetic relationship of D. melanogaster sugar gustatory receptors (Jiang et al. 2015, Xu et al. 2012). All nine putative sugar GR genes in H. armigera, Gr4–12 were validated, and their full-length cDNA sequences were cloned (The GenBank accession number is provided in Appendix—Table S1).” (Line 155-161).

• Generation of mutants based on CRISPR is intriguing and a powerful step. While the techniques are well described in the method section, there is no information concerning efficiency or broader feasibility of the approach. I feel it would be quite interesting to learn about how feasible or laborious the approach is to generate mutants (e.g. number of initial injected eggs, the resulting F0 offspring, number of back-crosses, number of screened F1s ....).

In the Materials and Methods section, we have added specific success rates for each step in the process of building the two mutants (Line 722-726, 729-732).

Reviewer #3 (Recommendations For The Authors):

I want to congratulate the authors on this very nice study and have only minor comments for them.

(1) It would be very nice to include pictures of the larva and adult of H. armigera. It would also help to have schematics of where the sensilla they are recording from are.

We have added photos of four taste organs on which the recoded sensilla were indicated (Figure 1), and picture of the larva and adult on which the stimulating site was indicated (Figure 2).

(2) A schematic summarising their findings, including the relevance to the animal's behavioural ecology, will greatly improve interpretations for the broader audience.

A schematic summarizing the findings has been added.

(3) The manner in which PIs are represented in figure 2A, B (among others) is confusing. Can the authors please plot the PI and not the feeding area? From the PI values listed beside the plot, it actually suggests that the larvae don't really show a preference. Could the authors please comment on this?

Yes, sucrose has a significant stimulating effect on larva feeding, but the effect is not as large as the predicted based on the sensitivity of the sensillum, the main reasons are as follows: (1) there are many factors affecting larva feeding, sucrose is only one of them; (2) due to the substrate leaf discs also contain sugar, the effect of newly added sucrose may be reduced. After careful consideration, we think it is better to display the feeding area and PI together so that readers have a complete understanding of the data.

(4) The heterologous expression experiments suggest that co-expression of GR6 with either GR10 or GR5 somehow suppress the response of the GR6 alone to fucose. Am I reading the data correctly? Why would this be? Perhaps the authors could discuss this. In this context, it would help to reproduce all the GR6 data together.

Your interpretation is reasonable to a certain extent. The result of co-injection might be that Gr10 or Gr5 inhibited the response of Gr6. However, there is another possibility that the amount of Gr6 sRNA was diluted by co-injection of two GRs, resulting in a reduced response of Gr6 to fucose.

(5) In general, for each results section, it would help to have a sentence or two that interprets the data in the context of previously presented data. This would help the reader digest the data and interpret it as they read along. Currently, the authors summarise the observations and leave all the interpretation to the discussion section.

We accept the suggestion. In each part of the results, we have added a sentence to explain the above data, which will help readers to clarify the context of the research more easily.

(6) Is the GR6 data in 4C not lined up correctly?

Yes, it is right.

(7) Line 228 suggests that the mutants were validating with qPCRs - I don't see that data.

The mutants were not validating with qPCR. We used the ordinary PCR technology at the mRNA level to verify whether the related sequences were really deleted in the mutants.

Author response:

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

Public Reviews:

Reviewer #3 (Public Review):

Kang, Huang, and colleagues have provided new data to address concerns regarding confirmation of LRRK1 and LRRK2 deletion in their mouse model and the functional impact of the modest loss of TH+ neurons observed in the substantia nigra of their double KO mice. In the revised manuscript, the new data around the characterization of the germline-deleted LRRK1 and LRRK2 mice add confidence that LRRK1 and LRRK2 can be deleted using the genetic approach. They have also added new text to the discussion to try and address some of the comments and questions raised regarding how LRRK1/2 loss may impact cell survival and the implications of this work for PD-linked variants in LRRK2 and therapeutic approaches targeting LRRK2.

The new data provides additional support for the author's claims. I have provided below some suggestions for clarification/additions to the text that can be addressed without additional experiments.

(1) The authors added additional text highlighting that more studies are warranted in mice where LRRK1/2 are deleted in other CNS cell types (microglia/astrocytes) to understand cell extrinsic drivers of the autophagy deficits observed in their previous work. It still remains unclear how loss of LRRK1/2 leads to increased apoptosis and gliosis in dopaminergic neurons in a cell-intrinsic manner, and, as suggested in the original review, it would be helpful to add some text to the discussion speculating on potential mechanisms by which this might occur.

(2) Revisions have been made to the discussion to clarify their rationale around how variants in LRRK2 associated with PD may be loss-of-function to support the relevance of this mouse model to phenotypes observed in PD. However, as written, the argument that PD-linked variants are loss-offunction is based on the fact that the double KO mice have a mild loss of TH+ neurons while the transgenic mice overexpressing PD-linked LRRK2 variants often do not and that early characterization of kinase activity was done in vitro are relatively weak. Given that the majority of evidence generated by many labs in the field supports a gain-of-function mechanism, the discussion should be further tempered to better highlight the uncertainty around this (rather than strongly arguing for a loss-offunction effect). This could include the mention of increased Rab phosphorylation observed in cellular and animal models and opposing consequences on lysosomal function observed in cellular studies in KO and pathogenic variant expressing cells. Further, a reference to the Whiffen et al. 2020 paper mentioned by another reviewer should be included in the discussion for completeness.

We thank the reviewer for the comments. The discussion has been further revised and expanded to explain the cell extrinsic microglial response to pathophysiological changes in DA neurons of cDKO mice and propose future studies of single-cell RNA-sequencing to identify molecular changes within DA neurons of cDKO mice that may drive their apoptotic death during aging.

We also added paragraphs summarizing existing experimental evidence for the toxic gain-of-function mechanism (biochemical data of increased kinase activity but the lack of evidence for the elevated pRabs and the altered pLRRK2 driving dopaminergic neurodegeneration) and for the loss-of-function mechanism (genetic data of relevant physiological roles) as well as the relationships between LRRK1 and LRRK2 (functional homologues sharing functional domains and overlapping roles in dopaminergic neuron survival) and how dominantly inherited missense mutations can confer a loss of function mechanism (impairing its function in cis and inhibiting wild-type protein function in trans). We also provided a brief summary and discussion of the Whiffen et al. 2020 paper.

персистеность - идея в живучести, если база данных живёт условно дольше чем сам сервис, который им пользуестя она персистента. то есть из нее данные не удаляются, они есть всегда с самого начала сущетсвования и до конца. и сервис спокойно может ей пользаться

транзакций в redis - тупо, чтоб собрать все операция в очередь и выполнить их по очередно, при этом пофиг выполнится ли все операция, транзацация выполнится даже в любом случае. в postgresql, тразнакция отменится, Если не все операция внутри выполнятся, то есть у некоторых будут ошибки.

суть оптимистической блокировки в том, чтоб не получить одному клиенту не верные данные измененные другим клиентам.

эта даёт возможность менять значение в ключа, и быть полностью увереным, что никто его никак не изменит.

по сути

Author response:

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

Reviewer #1 (Public Review):

Summary:

This study identifies a family of solute transports in the enteric protist, Blastocystis, that may mediate the transport of glycolytic intermediates across the mitochondrial membrane. The study builds on previous observations suggesting that Blastocystis (and other Stramenopiles) are unusual in having a compartmentalized glycolytic pathway with enzymes involved in upper and lower glycolysis being located in the cytosol and mitochondria, respectively. In this study, the authors identified two putative Stamenopile metabolite transporters that are related to plant di/tricarboxylic acid transporters that might mediate the transport of glycolytic intermediates across the mitochondrial membrane. These GIC-transporters were localized to the Blastocystis mitochondrion using specific rabbit antibodies and shown to bind several glycolytic intermediates (including GAP, DHAP, and PEP) based on thermostability shift assays. Direct evidence for transport activity was obtained by reconstituting native proteins in proteoliposomes and measuring the uptake of 14C-malate or 35S-sulphate against unlabelled substrates. This assay showed that GIC-2 transported DHAP, GAP, and PEP. However, significant transport activity was not observed for bGIC-2. Overall, the study provides strong, but not conclusive evidence that bGIC-1 is involved in transporting glycolytic intermediates across the inner membrane of the mitochondria, while the function of GIC-2 remains unclear, despite exhibiting the same metabolite binding properties as bGIC-2 in thermostability assays.

Strengths:

Overall, the findings are of interest in the context of understanding the diversity of core metabolic pathways in evolutionarily diverse eukaryotes, as well as the process by which cytosolic glycolysis evolved in most eukaryotes. The experiments are carefully performed and clearly described.

We thank the reviewer for their constructive comments. We note that bGIC-2 is the identified glycolytic intermediate transporter, not bGIC-1.

Weaknesses:

The main weakness of the study is the lack of direct evidence that either bGIC-1 and/or bGIC2 are active in vivo. While it is appreciated that the genetic tools for disrupting GIC genes in Blastocystis are limited/lacking, are there opportunities to ectopically express or delete these genes in other Stamenopiles, such as Phaeodactylum triconuteum, to demonstrate function in vivo?

Here, we have identified a transport protein, unique to stramenopiles, which is present in mitochondria of Blastocystis and can bind and transport glycolytic intermediates. We agree that it would have been desirable to confirm that they function as glycolytic intermediate transporters in vivo. However, the reviewer is correct in saying that the genetic tools for disrupting GIC genes in Blastocystis in vivo are not available. While the reviewer mentions the possibility of performing these analyses in Phaeodactylum tricornutum, it is important to note that this species possesses aerobic mitochondria and that the pay-off phase of glycolysis is present in both the mitochondrial matrix and the cytosol. Consequently, any data obtained from this species might not be conclusive and would also not be relevant to the glycolytic metabolism in Blastocystis, the subject of this study.

The authors demonstrate that both bGIC-1 and bGIC-2 are targeted to the mitochondrion, based on immunofluorescence studies. However, the precise localization and topology of these carriers in the inner or outer membrane are not defined. The conclusions of the study would be strengthened if the authors could show that one/both transporters are present in the inner membrane using protease protection experiments following differential solubilization of the outer and inner mitochondrial membranes.

The protein is a member of the mitochondrial carrier family, which are extremely hydrophobic membrane proteins. Those with an established transport function are known to localise consistently to the mitochondrial inner membrane, which is impermeable to charged molecules, whereas the outer membrane is porous through VDAC. Furthermore, when the carriers are overproduced in Saccharomyces cerevisiae, the protein is found in the enriched mitochondrial fraction, adding further support to the idea that they are localised to the inner membrane, as the outer membrane has a limited surface area.

It is not clear why hetero-exchange reactions were not performed for bGIC-1 (only for bGIC-2).

Unfortunately, bGIC-1 did not display transport activity when tested in [14C]-malate/malate, [35S]-sulphate/sulphate or [33P]-phosphate/phosphate homo-exchange reactions, as shown in Figure 6 (Figure 5 in the revised manuscript). Phosphoenolpyruvate and dihydroxyacetone phosphate are not available in a radiolabelled form and glyceraldehyde-3-phosphate is prohibitively expensive, so we were unable to test glycolytic intermediates directly in homo-exchange reactions. Hetero-exchange reactions, as performed in Figure 5 (Figure 6 in the revised manuscript) for bGIC-2, are conclusive, as accumulation of the radio-labelled substrate inside the proteoliposomes can only occur, when the internal substrate is exported. It seems that Blastocystis has multiple copies, some of which are coding for dysfunctional carriers, being possible pseudo-genes.

The summary slide depicted in Fig 7 is somewhat simplified and inaccurate. First, the authors show that TPI is located in the mitochondria in this study, while in the summary figure, TPI is shown to be present in both the cytosol and mitochondrial matrix. A cytosolic localization for TPI provides a functional rationale for having a triose-P carrier in the inner membrane - however, this is not supported by the data shown here. Second, if bGIC1/2 uses PEP as a counter ion to import GA3P and DHAP into the mitochondrion, as proposed in Fig 7, the lower glycolytic pathway would be effectively truncated at PEP, removing substrate for pyruvate kinase and formation of pyruvate/ATP. Third, the authors suggest that DHAP may have other functions in the mitochondria although these are not shown in the figure.

Figure 7 presents a schematic comparison of the localisation of glycolysis in humans and Blastocystis, specifically focused on the transport steps of either pyruvate (humans) or glycolytic intermediates (Blastocystis) into the mitochondrial matrix. Most of the metabolism of Blastocystis has been inferred from the presence or absence of genes, encoding for particular enzymes, with the exception of the unusual glycolytic pathway. We feel that overcomplicating this schematic figure would detract from the main message of this analysis. Although the transport data show that PEP, another glycolytic intermediate, is transported, we agree with the reviewer that PEP export cannot be rationalised in the context of our current understanding of the metabolism, and we have changed the figure accordingly.

We have not suggested that DHAP has other functions in mitochondria; on line 230, we state that ‘we have not found any evidence for the presence of dihydroxyacetone phosphate inside mitochondria in the literature. It is possible that it is not transported under physiological conditions in competition with dicarboxylates or other substrates.’

Reviewer #2 (Public Review):

In this manuscript, the authors set out to identify transporters that must exist in Stramenophiles due to the fact that the second half of glycolysis appears to be conducted in the mitochondria. They hypothesize that a Stramenophile-specific clade of transporters related to the dicarboxylate carriers is likely the relevant family and then go on to test two proteins from Blastocystis due to the infectious disease relevance of this organism. They show rather convincingly that these two proteins are expressed and are localized to the mitochondria in the native organism. The purified proteins bind to glycolytic intermediates and one of them, GIC-2, transports several glycolytic intermediates in vitro. This is a very solid and well-executed study that clearly demonstrates that bCIC-2 can transport glycolytic intermediates.

We thank the reviewer for their positive comments on the manuscript, and their careful analyses of the presented data.

(1) The major weakness is that the authors aren't able to show that this protein actually has this function in the native organism. This could be impossible due to the lack of genetic tools in Blastocystis, but it leaves us without absolute confidence that bGIC-2 is the important glycolytic intermediate mitochondrial transporter (or even that it has this function in vivo).

Unfortunately, genetic manipulation in Blastocystis is currently not feasible and thus we cannot conduct a comparative metabolic study with the appropriate controls. The gold standard for identification is to prove the function with purified protein directly, which we have done here by using binding studies and transport assays.

(2) It's atypical that the figures and figure panels don't really follow the order of their citation in the text. It's not a big deal, but mildly annoying to have to skip around in the figures (e.g. Figure 3D-E are described in the same paragraph as Figure 5). In addition, to facilitate the flow and a proper understanding I would encourage a reordering between figures 5D and 6 since Figure 6 is needed to understand the results shown in panel 5D, which may lead to confusion.

We agree with the reviewer and have reordered the figures, switching Figure 5 and 6, which makes the manuscript easier to follow.

(3) My impression is that the authors under-emphasize the fact that the hDIC also binds (and is stabilized by) glycolytic intermediates (G3P and 3PG). In the opinion of this reviewer, this might change the interpretation about the uniqueness of the bGIC proteins. They act on additional glycolytic intermediates, but it's not unique.

The reviewer is correct that hDIC is stabilized by both G3P and 3PG, but neither are transported, as shown in Figure 5B (Figure 6B in the revised manuscript). It is not uncommon for compounds to bind to some extend without being transported, as they share certain structural and chemical features with the substrates, which result in stabilisation in thermostability analyses. For example, GTP stabilises the ADP/ATP carrier in thermostability analyses to some extent (Majd et al, 2018), although it is not a transported substrate of the carrier (King et al, 2020). Although thermostability assays are very useful for screening of potential substrates, it is always necessary to carry out transport assays, which are the gold standard for transporter identification.

Reviewer #3 (Public Review):

Summary:

Unlike most eukaryotes, Blastocystis has a branched glycolysis pathway, which is split between the cytoplasm and the mitochondrial matrix. An outstanding question was how the glycolytic intermediates generated in the 'preparatory' phase' are transported into the mitochondrial matrix for the 'pay off' phase. Here, the authors use bioinformatic analysis to identify two candidate solute carrier genes, bGIC-1, and bGIC-2, and use biochemical and biophysical methods to characterise their substrate specificity and transport properties. The authors demonstrate that bGIC-2 can transport dihydroxyacetone phosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate, and phosphoenolpyruvate, establishing this protein as the 'missing link' connecting the two split branches of glycolysis in this branch of single-celled eukaryotes. The authors also present their data on bGIC-1, which suggests a role in anion transport and bOGC, which is a close functional homologue of the human oxoglutarate carrier (hOGC, SLC25A11) and human dicarboxylate carrier (hDIC, SLC25A10).

Strengths:

The results are presented in a clear and logical arrangement, which nicely leads the reader through the process of gene identification and subsequent ligand screening and functional reconstitution. The results are compelling and well supported - the thermal stabilisation data is supported by the exchange studies. Caveats, where apparent, are discussed and rational explanations are given.

We thank the reviewer for their positive and constructive comments on the manuscript.

Weaknesses:

The study does not contain any significant weaknesses in my view. I would like to see the authors include the initial rate plots used in the main figures (possibly as insets), so we can observe the data points used for these calculations. It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

We have shown uptake curves in both Figure 3 and Figure 6 (Figure 5 in the revised manuscript) to provide the typical uptake curves that we record by our robot, and we also show how we calculate the initial rates. We feel that the inclusion of uptake curves for each compound for each carrier (96 uptake curves in total) would make figure 5 (Figure 6 in the revised manuscript) extremely complicated.

It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

Whilst AlphaFold is an important step forward in the prediction of protein structures, it is not accurate enough at this time to be used for the rationalisation of the substrate specificity. For instance, there are the significant structural differences between the predicted AlphaFold structure of the human uncoupling protein (https://alphafold.ebi.ac.uk/entry/P25874), by and large based on the mitochondrial ADP/ATP carrier, and the experimentally determined structure, especially for the central cavity where the substrate recognition takes place (Jones et al, 2023; Kang & Chen, 2023). More importantly, it is believed that the optimal binding of the substrate takes place in the occluded state (Klingenberg, 2007; Springett et al, 2017), for which we have no structure.

References

Jones SA, Gogoi P, Ruprecht JJ, King MS, Lee Y, Zögg T, Pardon E, Chand D, Steimle S, Copeman DM et al (2023) Structural basis of purine nucleotide inhibition of human uncoupling protein 1. Sci Adv 9: eadh4251

Kang Y, Chen L (2023) Structural basis for the binding of DNP and purine nucleotides onto UCP1. Nature 620: 226-231

King MS, Tavoulari S, Mavridou V, King AC, Mifsud J, Kunji ERS (2020) A single cysteine residue in the translocation pathway of the mitosomal ADP/ATP carrier from Cryptosporidium parvum confers a broad nucleotide specificity. Int J Mol Sci 21: 8971

Klingenberg M (2007) Transport viewed as a catalytic process. Biochimie 89: 1042-1048

Majd H, King MS, Palmer SM, Smith AC, Elbourne LD, Paulsen IT, Sharples D, Henderson PJ, Kunji ER (2018) Screening of candidate substrates and coupling ions of transporters by thermostability shift assays. Elife 7: e38821

Springett R, King MS, Crichton PG, Kunji ERS (2017) Modelling the free energy profile of the mitochondrial ADP/ATP carrier. Biochim Biophys Acta 1858: 906-914

Test für eine Anmerkung

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The authors present a detailed study of a nearly complete Entomophthora muscae genome assembly and annotation, along with comparative analyses among related and non-related entomopathogenic fungi. The genome is one of the largest fungal genomes sequenced, and the authors document the proliferation and evolution of transposons and the presence/absence of related genetic machinery to explore how this may have occurred. There has also been an expansion in gene number, which appears to contain many "novel" genes unique to E. muscae. Functionally, the authors were interested in CAZymes, proteases, circadian clock related genes (due to entomopathogenicity/ host manipulation), other insect pathogenspecific genes, and secondary metabolites. There are many interesting findings including expansions in trahalases, unique insulinase, and another peptidase, and some evidence for RIP in Entomophthoralean fungi. The authors performed a separate study examining E. muscae species complex and related strains. Specifically, morphological traits were measured for strains and then compared to the 28S+ITSbased phylogeny, showing little informativeness of these morpho characters with high levels of overlap.

This work represents a big leap forward in the genomics of non-Dikarya fungi and large fungal genomes. Most of the gene homologs have been studied in species that diverged hundreds of millions of years ago, and therefore using standard comparative genomic approaches is not trivial and still relatively little is known. This paper provides many new hypotheses and potential avenues of research about fungal genome size expansion, entomopathogenesis in zygomycetes, and cellular functions like RIP and circadian mechanisms.

Strengths:

There are many strengths to this study. It represents a massive amount of work and a very thorough functional analysis of the gene content in these fungi (which are largely unsequenced and definitely understudied). Too often comparative genomic work will focus on one aspect and leave the reader wondering about all the other ways genome(s) are unique or different from others. This study really dove in and explored the relevant aspects of the E. muscae genome.

The authors used both a priori and emergent properties to shape their analyses (by searching for specific genes of interest and by analyzing genes underrepresented, expanded, or unique to their chosen taxa), enabling a detailed review of the genomic architecture and content. Specifically, I'm impressed by the analysis of missing genes (pFAMs) in E. muscae, none of which are enriched in relatives, suggesting this fungus is really different not by gene loss, but by its gene expansions.

Analyzing species-level boundaries and the data underlying those (genetic or morphological) is not something frequently presented in comparative genomic studies, however, here it is a welcome addition as the target species of the study is part of a species complex where morphology can be misleading and genetic data is infrequently collected in conjunction with the morphological data.

Thank you for your careful reading of our work. We’re glad that you identified these areas as strengths.

Weaknesses:

The conclusions of this paper are mostly well supported by data, but a few points should be clarified.

In the analysis of Orthogroups (OGs), the claim in the text is that E. muscae "has genes in multi-species OGs no more frequently than Enotomophaga maimaiga. (Fig. 3F)" I don't see that in 3F. But maybe I'm really missing something.

Thank you for catching this. You were, in fact, not missing anything at all. There was a mismatch between the data plotted in F and G and how the caption described these data. We very much apologize for the confusion that this must have caused. We have corrected these plots and also made changes to improve interpretability (see below).

Also related, based on what is written in the text of the OG section, I think portions of Figure 3G are incorrect/ duplicated. First, a general question, related to the first two portions of the graph. How do "Genes assigned to an OG" and "Genes not assigned to an OG" not equal 100% for each species? The graph as currently visualized does not show that. Then I think the bars in portion 3 "Genes in speciesspecific OG" are wrong (because in the text it says "N. thromboides had just 16.3%" species-specific OGs, but the graph clearly shows that bar at around 50%. I think portion 3 is just a duplicate of the bars in portion 4 - they look exactly the same - and in addition, as stated in the text portion 4 "Potentially speciesspecific genes" should be the simple addition of the bars in portion 2 and portion 3 for each species.

As mentioned above, we sincerely regret the error made in the plot and for the confusion that this caused. F now reflects the percentage of orthogroups (OGs) that possess at least one representative from the indicated species (left) and the percentage of OGs that are species-specific (only possess genes from one species; right). The latter is a subset of the former. G now reflects the percentage of annotated genes that were assigned an OG, per species, as well as the inverse of this - genes that were not assigned to any OG. These should, and now do, sum to 100%. The “Within species-specific OG” data summed with the “Not assigned OG” data yields the “Potentially species-specific data” in the rightmost column.

In the introduction, there is a name for the phenomenon of "clinging to or biting the tops of plants," it's called summit disease. And just for some context for the readers, summit disease is well-documented in many of these taxa in the older literature, but it is often ignored in modern studies - even though it is a fascinating effect seen in many insect hosts, caused by many, many fungi, nematodes (!), etc. This phenomenon has evolved many times. Nice discussions of this in Evans 1989 and Roy et al. 2006 (both of whom cite much of the older literature).

You’re right. We have now clarified that this behavior is called “summit disease” and referenced the suggested articles, along with a more recent review.

Reviewer #2 (Public Review):

In their study, Stajich and co-authors present a new 1.03 Gb genome assembly for an isolate of the fungal insect parasite Entomophthora muscae (Entomophthoromycota phylum, isolated from Drosophila hydei). Many species of the Entomophthoromycota phylum are specialised insect pathogens with relatively large genomes for fungi, with interesting yet largely unexplored biology. The authors compare their new E. muscae assembly to those of other species in the Entomophthorales order and also more generally to other fungi. For that, they first focus on repetitive DNA (transposons) and show that Ty3 LTRs are highly abundant in the E. muscae genome and contribute to ~40% of the species' genome, a feature that is shared by closely related species in the Entomophthorales. Next, the authors describe the major differences in protein content between species in the genus, focusing on functional domains, namely protein families (pfam), carbohydrate-active enzymes, and peptidases. They highlight several protein families that are overrepresented/underrepresented in the E. muscae genome and other

Entomophthorales genomes. The authors also highlight differences in components of the circadian rhythm, which might be relevant to the biology of these insect-infecting fungi. To gain further insights into E. muscae specificities, the authors identify orthologous proteins among four Entomophthorales species. Consistently with a larger genome and protein set in E. muscae, they find that 21% of the 17,111 orthogroups are specific to the species. To finish, the authors examine the consistency between methods for species delineation in the genus using molecular (ITS + 28S) or morphological data (# of nuclei per conidia + conidia size) and highlight major incongruences between the two.

Although most of the methods applied in the frame of this study are appropriate with the scripts made available, I believe there are some major discrepancies in the datasets that are compared which could undermine most of the results/conclusions. More precisely, most of the results are based on the comparison of protein family content between four Entomophthorales species. As the authors mention on page 5, genome (transcriptome) assembly and further annotation procedures can strongly influence gene discovery. Here, the authors re-annotated two assemblies using their own methods and recovered between 30 and 60% more genes than in the original dataset, but if I understand it correctly, they perform all downstream comparative analyses using the original annotations. Given the focus on E. muscae and the small sample size (four genomes compared), I believe performing the comparisons on the newly annotated assemblies would be more rigorous for making any claim on gene family variation.

Thank you for this comment. While we did compare gene model predictions for two of these assemblies to assess if this difference could account for discrepancies in gene counts, completely reannotating all non-E. muscae datasets was outside of the scope of this study. In our opinion, the total number of predicted genes in a genome is not a best representation of differences since splitting or fusing gene models can inflate seeming differences; the orthology and domain counts are a more accurate assessment of the content. It’s possible that annotation differences may have inflated some gene family counts, however we will note that similar domain trends were observed between the closest species to E. muscae, Entomophaga maimaiga, suggesting that these differences were not sufficient to prevent us from detecting real biological signals. We look forward to continued improvement of our genome through additional sequencing and more clarity on total gene content of E. muscae.

The authors also investigate the putative impact of repeat-induced point mutation on the architecture of the large Entomophthorales genomes (for three of the eight species in Figure 1) and report low RIP-like dinucleotide signatures despite the presence of RID1 (a gene involved in the RIP process in Neurospora crassa) and RNAi machinery. They base their analysis on the presence of specific PFAM domains across the proteome of the three Entomophthorales species. In the case of RID1, the authors searched for a DNA methyltransferase domain (PF00145), however other proteins than RID1 bear such functional domain (DNMT family) so that in the current analysis it is impossible to say if the authors are actually looking at RID1 homologs (probably not, RID1 is monophyletic to the Ascomycota I believe). Similar comments apply to the analysis of components of the RNAi machinery. A more reliable alternative to the PFAM analysis would be to work with full protein sequences in addition to the functional domains.

While we understand this concern regarding domain vs. full length protein, the advantage of the domain search is that HMM-based searches are sensitive to detecting more distantly related homologs. Entomophthoralean fungi are distantly related from the ascomycetes in which these mechanisms have been characterized, so we chose a broader search approach that may identify proteins with similar domain structure, but are not necessarily homologs. These searches are presented in the manuscript as preliminary, but worth further investigation. However, our RID-based analysis did not identify convincing homologs for RID1 in entomophthoralean fungi included in our investigation, and we reported low homology (i.e., 12-14%) among our orthogroup of interest and RID1. We have further edited this section to clarify our understanding that these candidates are not RID1 homologs. We had hoped to avoid this implication, but we felt this investigation and null result were worth reporting.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Specific points:

Results:

"1.03 Gb genome consisting of 7,810 contigs (N50 = 301.1 kb). Additional... resulted in a final contig count of 7,810 (N50 = 329.6 kb)" So you started and ended with the same contig count but a different N50? Is this a typo?

Yes, this was a typo. Thank you for bringing this to our attention.

Figure 1D.

The colors of Complete1x and Complete2x are too similar to tell them apart.

The colors have been made more distinct.

Figure 4B.

I know C. rosea has been found from insects before, but it's mostly a mycoparasite and occasionally an endophyte, and has bioactivity against a lot of things. I just saw that it's listed as an entomopathogen, and I was surprised. Anyway, leave it as is if you want to, but it's definitely better studied and better known (Google Scholar) as a mycoparasite.

Thanks for this comment. For the sake of including a more diverse representation of entomopathogenic fungi, we have opted to leave this as is.

Full references (from the public comment)

Evans, H.C., 1989. Mycopathogens of insects of epigeal and aerial habitats. Insect-fungus interactions, pp.205-238.

Roy, H.E., Steinkraus, D.C., Eilenberg, J., Hajek, A.E. and Pell, J.K., 2006. Bizarre interactions and endgames: entomopathogenic fungi and their arthropod hosts. Annu. Rev. Entomol., 51, pp.331-357.

Reviewer #2 (Recommendations For The Authors):

I believe the manuscript could largely benefit from restructuring the results section to enhance clarity. The results section reads like a lot of descriptive back and forth, so that the reader lacks a clear rationale. The absence of a consistent dataset used for the different comparisons made all along the manuscript makes it hard to follow.

Minor comments:

(No line numbers were available so I refer to page numbers).

p1

• not sure about the use of "allied" to describe other fungal species in the title and after (sister species?).

We didn’t want to use the word sister because not all of these species could be considered sister.

• Genomic defence against transposable elements rather than "anti"?

We have rephrased to genomic defense.

p3

• Extra parenthesis at Bronski et al.

This is now corrected.

• What does newly-available mean here?

We mean recent. A lot of the datasets we used were very new, and we wanted to emphasize that point.

• The back and forth between genomes and transcriptomes makes it hard to follow, would clarify from the beginning (in addition to the sequencing method - short vs long-read assemblies as in Figure 1B) or perhaps use a consistent dataset for all subsequent comparative analysis in the Entomophthorales.

We have denoted our transcriptomic datasets in Fig 1C using parentheses.

p5

• Perhaps clarify that class II DNA transposons can also "copy" (single-strand excisions can be repaired by the host machinery).

We have now included mention of “copy” as well as “jump” mechanisms of Class II transposons per your suggestion.

p6

• "beginning roughly concurrently", not clear what "began".

This is now corrected.

• "control" rather than "protect against"?

We’ve changed “protect against” to “counter”.

• I believe RIP has only been observed (experimentally) in a handful of fungal species, all from the Ascomycota phylum.

Hood et al, 2005 found signatures of RIP in anther-smut fungus and Horns et al, 2012, found evidence of hypermutability across repeat elements within several Pucciniales species.

• "RID1 contains two DNA_methylase domains", RID1 has one methyltransferase domain according to the reference Freitag et al, 2002.

Thank you for drawing this to our attention. It is true RID1 has one methyltransferase region; however, the sequence deposited by Freitag et al, 2002 (AAM27408) is predicted by HMMer to have two adjacent Pfam DNA_methylase domains (i.e., PF00145). In this exploratory analysis, we tried to leverage this characteristic to identify candidate proteins of interest. We have reworded this section to clarify this.

p8

• Here and after I would use more informative titles for each paragraph.

With the exception of the headings for Pfam, CAZy and MEROPs analyses, we believe the other headings are informative. We appreciate this comment, but opt to leave the heading titles as is.

• I believe presenting the orthology analysis before the more in-depth protein family domain search.

We leveraged the OG analysis mostly as a way to identify potentially unique genes in E. muscae, so we think the current order makes the most sense.

p10

• Figures 3F and G are confusing. The legend for Figure 3F mentions "OGs with >= 2 species" while the figure shows "multi-species OGs", and reads as redundant with the "species-specific" OGs. For the "OGs within species" do I understand it correctly that it represents the number of genes assigned to OGs for each species? If yes, the numbers are in contradiction with Figure 3G. And in Figure 3G shouldn't the sum of "genes assigned in OGs" and "genes nor assigned in OGs" add up to 100? I'm probably missing something here, but I would clarify what the different sets of orthogroups are in the figure and in the text (perhaps adopting a pangenome-like nomenclature).

Thanks for this comment. This legend, unfortunately, reflected an earlier version of the figure and was overlooked prior to submission. We have since amended this and sincerely apologize for the error on our part.

p12

• The whole first paragraph reads more like it should be part of an introduction/discussion.

We’ve moved some of this paragraph to the discussion but left the background information necessary for the reader to understand why we were looking for homologs of wc and frq.

p13

• The last paragraph reads like discussion.

We have revised this paragraph so it now reads: “Because E. muscae is an obligate insect-pathogen only living inside live flies, we investigate the presence of canonical entomopathogenic enzymes in the genome. We find that E. muscae appear to have an expanded group of acid-trehalases compared to other entomopathogenic and non-entomopathogenic Entomophthorales (Fig. 4A), which correlates with the primary sugar in insect blood (hemolymph) being trehalose (Thompson, 2003). The obligate insectpathogenic lifestyle is also evident when comparing the repertoire of lipases, subtilisin-like serine proteases, trypsins, and chitinases in our focal species versus Zoopagomycota and Ascomycota fungi that are not obligate insect pathogens (Fig. 4B). Sordariomycetes within Ascomycota contains the other major transition to insect-pathogenicity within the kingdom Fungi (Araújo and Hughes, 2016). Based on our comparison of gene numbers, Entomophthorales possess more enzymes suitable for cuticle penetration than Sordariomycetes (Fig. 4B). In contrast, insect-pathogenic fungi within Hypocreales possess a more diverse secondary metabolite biosynthesis machinery as evidenced by the absence of polyketide synthase (PKS) and indole pathways in Entomophthorales (Fig. 4C).”

p15 and 16

• This all reads as redundant with the previous protein family domain analysis. I would try to merge them.

Thank you for this comment, however we have opted to maintain the current structure.

p18

• In the first sentence, I'm not sure about what was performed here.

This has been reworded to clarify.

p20

• Regarding the assembly, do I understand it correctly that a nuclear genome can be partially haploid / diploid?

Thanks for your comment. The genome itself is, of course, some integer multiple of n, but based on BUSCO scores our assembly doesn’t appear to have completely collapsed into a haploid genome. We think it makes more sense here to say “partially haploid” than “partially diploid” so have altered this.

p21

• RIP has only been observed in a couple of Ascomycetes. RIP-like genomic signatures (GC bias) have been observed elsewhere.

Hood et al, 2005 found signatures of RIP in anther-smut fungus and Horns et al, 2012, found evidence of hypermutability across repeat elements within several Pucciniales species.

p23

• Interesting that the peptidase A2B domain is found uniquely in E. muscae genome and is associated with Ty3 activity. Does the domain often overlap with annotated Ty3 in E. muscae genome? Or how come the domain is not present in other sister species with large genomes full of Ty3 transposons? Could it relate to a new active transposon in E. muscae specifically?

Thanks for this comment. The domain-based analysis was only performed on the predicted transcriptome of the genome assembly, which does not include the repeat elements (e.g., Ty3). It could be that this peptidase reflects a new active transposon that’s specific to E. muscae, which would certainly be very interesting. We’ve now included this idea in the discussion.

p26

• In the case of fungal genomes, I would not advise masking the assembly for repeated sequences prior to gene annotation (in particular given the current focus on protein family variation).

Thank you for this comment, however we disagree with this assertion as a typical approach for genome annotation in fungi and eukaryotic genomes is to use soft masking of transposable elements before performing gene prediction to avoid over-prediction. While there could be alternative approaches that compare masked or unmasked. This is a recommended protocol for underlying tools like Augustus (10.1002/cpbi.57) and in general descriptions of genome annotation (10.1002/0471250953.bi0401s52). The false positive rate of genes predicted through TE regions is likely to be more a problem than false negatives of missed genes in our experience. Further it seems appropriate to use consistent approach to annotation throughout when including genomes from other sources (e.g., Joint Genome Institute annotated genomes) which also use a repeat masking approach first before annotation. It seems most appropriate to use consistent methods when generating datasets to be used for comparative analyses. It is outside the scope of this project to reannotate all genomes with and without repeat masking.

p27

• Interrupted sentence at "Classification of DNA and LTR .. by similarity The".

This was an unnecessary partial phrase as the information on classification of elements via RepBase was made a few sentences above this.

p28

• Enriched/depleted rather than "significantly different"?

Thank you for this comment, however we have opted to maintain the current phrasing.

for - Deep Humanity - individual / collective gestalt - Ernest Becker - Anthropological birth of the psychic self - timebound - symbolic - organizing principle for sensations and perceptions - Progress and Freedom - self / other duality

https://www.kleinezeitung.at/politik/aussenpolitik/18395713/emissionsfreie-autos-fahrt-in-eine-ungewisse-zukunft

This is FDR blaming the great depression Republicans. In 1928 stock prices rose 39%. To stop speculation, the Federal Government raised the discount rate 3.5% to 5%. In 1929 President Herbert Hoover lowered the top income tax rate to 24% and the top corporate tax rate to 12%.17. The Great Depression began in August, as the economy shrank. The stock market crashed two months later. https://www.thebalancemoney.com/roaring-twenties-4060511#:~:text=1928%3A%20Stock%20prices%20rose%2039,removed%20cash%20from%20their%20reserves.

Franklin D. Roosevelt (FDR) served Woodrow Wilson as his Assistant Secretary of the Navy during WWI. I know FDR respected Wilson very much, but why single him out as the Commander and Chief. There was three other US Presidents after him, Warren Harding, Calvin Coolidge, and Herbert Hoover. Maybe because he did not respect the Republican Party, which all three were members. Or maybe because Wilson was the President during the Great War. https://www.nps.gov/articles/franklin-delano-roosevelt-assistant-secretary-of-the-navy.htm https://www.whitehouse.gov/about-the-white-house/presidents/woodrow-wilson/

Franklin D. Roosevelt (FDR) never served in uniformed military service, so he never had formal military training. However, he was Woodrow Wilson’s Assistant Secretary of the Navy. He was just 31 years old, the youngest Assistant Secretary of the Navy. FDR’s cousin Theodore Roosevelt had held the same position, in 1898. FDR attempted to serve in the Navy as an Office and his cousin, Theodore Roosevelt, urged him to serve, but Wilison kept him in his position in Washington. FDR, as a civilian, went overseas to visit military officers in France, in 1918 during the war. https://www.nps.gov/articles/franklin-delano-roosevelt-assistant-secretary-of-the-navy.htm

the metaphor is a figure of speech in which a word or phrase is applied to an object or action to which often is not literaly applicable

completely agree

a what?

very relatable

interesting metaphor

gibberish

Winner of the National Book Award.

The expression of one's meaning by using language that normally signifies the opposite.

how cute

OMG, he is such a poet!!!

DEEP

Its so true!

nice wording!

Author response:

Reviewer #2 (Public Review):

In this study, the authors report that both mice and human patients carrying function-disrupting mutations in the OFD1 gene exhibited ectopic brown adipose tissue formation in the malformed tongue. The OFD1 gene is located on the X-chromosome and encodes a protein product required for the formation and function of the primary cilium, which is required for cells to properly receive and activate several signaling pathways, particularly the hedgehog signaling pathway. Loss of OFD1 function causes prenatal lethality of male fetuses and mosaic disruption of tissues in females due to random inactivation of the X-chromosome carrying either the mutant or wildtype allele. Using cell type-specific gene inactivation and genetic lineage labeling, the manuscript shows that the ectopic brown adipose tissue in the mutant tongue was not derived from cranial neural crest cells (CNCCs). Additional genetic and embryological studies led to the conclusion that loss of Ofd1 function in the CNCC cells in the embryonic hypoglossal cord, via which the tongue myoblast precursor cells migrate from anterior somites to the tongue primordia, caused disruption of cell-cell interactions between the CNCCs and migrating muscle precursor cells, resulting in altered differentiation of those myoblast precursor cells into brown adipocytes. The authors provided data that disruption of Smo in a subset of CNCCs also resulted in ectopic adipose tissue formation in the tongue, indicating that this phenotype in the Ofd1 mutant mice was likely caused by disruption of hedgehog signaling in CNCCs. However, no experimental evidence is provided to support a major conclusion of the manuscript regarding altered differentiation of the tongue myoblast precursor cells into brown adipocytes in the Ofd1 mutant mice. Since it is well established that hedgehog signaling in the CNCCs is required for them to direct tongue myoblast cell migration as well as for tongue muscle differentiation/organization after the myoblasts arrived in the tongue primordia, the finding of tongue muscle defects in the Ofd1 mutant mice is not surprising. However, if proven true that disruption of Ofd1 function in CNCCs caused tongue myoblast precursor cells to alter their fate and differentiate into brown adipocytes, it would be an interesting new finding. Further identification of the signals produced by the Ofd1 mutant CNCCs for directing the cell fate switch will be a highly significant new advance in understanding the cellular and molecular mechanisms regulating tongue morphogenesis.

Many in vitro and in vivo data have been added as new data. We hope that these are enough for our conclusion. It is extremely difficult to identify the signals produced by the Ofd1 mutant CNCCs for directing the cell fate switch of mesodermal cells after activation of Hh signaling in CNCC. Instead, our new findings raise the possibility that Hh signaling in mesodermal cells is also important for their differentiation as well as Hh signaling in CNCC, which has been added in revised paper. However, we think that it is beyond the scope of this study to deepen these.

Reviewer #3 (Public Review):

The authors observed phenotypes of ciliopathy model mice and they seem to coincide with those in human patients. They used mutants in which cilial function genes are deleted in cranial neural crest cells, and found the mutants exhibit abnormal cell differentiation in both neural crest- and mesoderm-lineage cells. The finding clearly shows the importance of tissue/cell interaction. The authors mainly observed the mouse in which Ofd1 gene that is coded on the X chromosome is deleted, therefore, Ofd1fl/WT;Wnt1Cre(HET) mice show that about one-fourth of neural crest cells can exhibit Ofd1 function whereas Ofd1fl;Wnt1Cre (HM) shows null Ofd1 function and show severer phenotypes than HET.

For ectopic brown adipose tissue in the tongue is derived from mesoderm and the authors tried to show that the hypoglossal cord failed to obtain myogenic lineage after entering branchial arches in HET and HM due to lack of communication with neural crest cells. For ectopic bone formation, they found that it is due to the lack of Hedgehog signaling in neural crest cells, which was consistent with the reports in the Smofl/fl;Wnt1-Cre (Xu et al., 2019) and Ift88fl/fl;Wnt1Cre (Kitamura et al. 2020). The ectopic bone is connected to the original mandibular bone. The authors attribute the ectopic bone formation to the migration of mandibular bone neural crest cells into the tongue-forming area.

For the poor tongue frenum formation, the authors found the importance of cell migration from the lateral sides of the branchial arch to the midline and its formation relies on non-canonical Wnt signaling. The authors observed similar phenotypes in the human patients as those in the mutants. The adipose tissue in the tongue area is normally found in the salivary gland region and intermuscular space, and it is intriguing to find the brown adipose tissue anterior to the cervical area in which the most anterior brown adipose tissue develops. qRT-PCR indicates that some of the marker genes are expressed in the laser micro-dissected sections of the ectopic brown adipose tissue. However, histology does not show the typical brown adipose tissue feature. In addition, brown adipose tissue is normally recognized in the sixth pharyngeal region as the cervical brown tissue from around E14.5 (Schulz and Tseng 2013), not E12 as the authors observe. Although the mutants develop under abnormal conditions, is it possible to say they are brown adipose tissue? The point has to be further investigated with more marker expression by immunohistochemical detection and other methods. Since the mutants seem to show impaired midline formation (which is consistent with the condition of human ciliopathy), is it possible to hypothesize that the adipose-like tissue is derived from the mesoderm of posterior branchial arch levels if the tissue is brown adipose tissue?

Immunohistochemistry data has been added as new Figure S4 and S5.

We agree reviewer’s comment. Histology of ectopic adipose in Ofd1 cKO is slightly different from typical images of brown adipose. Molecular characters of ectopic adipose in Ofd1 mutant tongue are similar to these of low thermogenic adipocyte. Histological features of low thermogenic is known to be different from that of typical brown adipose tissue. Histological features of low thermogenic adipocyte is similar to that of ectopic adipose in Ofd1 mutant mice. This has been mentioned in Results section.

The cervical brown adipose tissue in Ofd1 mutant should be shrinked or be connected to ectopic adipose in mutant tongue, if ectopic adipose in mutant tongue was derived from the cervical brown adipose tissue due to mis-migration. However, any significant changes of the cervical brown adipose tissue or conection between cervical brown adipose and tongue adipose could not be detected in Ofd1 mutant mice. We think that ectopic adipose in mutant tongue is unlikely derived from cervical brown adipose tissue. These have been added in Result section.

Cranial neural crest cells start migrating around E8.0 and reach their destination by E9.5. The authors show the lack of neural crest cells in the midline, the fluorescence is absent from the midline in HM, however, they studied it in the E11 mandible (Fig. 4E), almost more than two days after neural crest migration completes. Since the mandibular arch seems to form at the beginning in the mutants, is there a failure in allocating the neural crest and mesoderm at the beginning of the mandibular arch formation?

It is difficult to prove how much migration is affected in mutant mice. Therefore, sentence describing migration has been deleted in revised paper

The authors tried to disturb the interaction between the hypoglossal cord and neural crest cells by making incisions in the dorsal area of the branchial arches. That area contains both neural crest and mesoderm but not the hypoglossal cord-derived mesoderm. The hypoglossal cord passed through the posterior edge of the caudal (6th) pharyngeal arch, along the lateral side of the pericardium towards the anterior, ventral to branchial arches, and then inside the 2nd and 1st branchial arches (Adachi et al., 2018). It expresses Pax3 before entering the branchial arches, then Myf5 in the branchial arches. It seems that the migration of the hypoglossal cord does not require interaction with neural crest cells but it has to be confirmed as well as neural crest migration into the branchial arches from the beginning. Although the hypoglossal cord migrates mostly in mesoderm-derived mesenchyme, we cannot exclude the possibility that hypoglossal cord migration is affected.

Cutting region in original Figure 2Q was not accurate. It has been changed in new Figure 3Q. We agree reviewer’s comment “we cannot exclude the possibility that hypoglossal cord migration is affected”. However, It is difficult to prove how much migration is affected in mutant mice. Therefore, sentence describing migration has been deleted in revised paper

The lack of Myf5 expression in Ofd1fl;Wnt1Cre (HM) was explained as a failure in the differentiation of the hypoglossal cord into myoblasts on entrance into the branchial arches. Most of the cervical brown adipose tissue is derived from either Myf5- or Pax3- expressing lineage (Sanchez-Gurmaches and Guertin, 2014). Although the authors suggest that brown adipose cells are fate-changed mesoderm in the branchial arches, how do they explain the association with Myf5- or Pax3- expression?

As reviewer mentioned, the cervical brown adipose tissue is derived from either Myf5- or Pax3- expressing lineage. However, these cells lost Myf5- or Pax3 expression when they differentiate into brawn adipocytes. Although ectopic adipose in Ofd1 mutant tongue showed Pax3 expression at early stage, they likely loose Pax3 expression soon after. There is another possibility that ectopic adipocytes retain Pax3 expression, if they would be abnormal adipocytes. If so, it's not surprised when expression pattern of ectopic adipocytes in Ofd1 mutant is different from these of normal brown adipose tissue. Anything can be possible in these situation. Therefore, we don’t mention anything about these in the text

In addition, the cervical brown tissue is supposed to be derived from the branchial arch mesoderm (Mo et al., 2017). Is the formation of the cervical brown tissue affected in the Ofd1fl/WT;Wnt1Cre(HET) or Ofd1fl;Wnt1Cre (HM) if dysfunction of neural crest cells results in the cell fate change of mesoderm?

Any significant morphological changes of the cervical brown adipose tissue could not be detected in Ofd1 mutant mice. Ectopic adipose tissue in Ofd1 cKO was found from E115, while cervical adipose tissue form from E14.5. We think that dysfunction of CNCC at E14.5 does not affect mesodermal cells for the cervical adipose tissue.

For the tongue frenum development, it is hard to understand to hypothesize that its formation is unlikely to associate with midline formation. Although Lgr5 and Tbx22 are not expressed in the midline, the defect in midline formation could cause unnecessary interaction between the right and left tissues.

We agree reviewer’s comment. The sentences have been changed in new manuscript.

Tissue morphogenesis takes place in three dimensions, which were not considered in the data, especially in the labeling experiments. When the authors labelled the cells, which cells in which area were labelled? In the textbook, tongue formation is a result of the fusion of the midline processes derived from the branchial arches, therefore, it is important to identify which cells in which area are labelled.

Data of Lgr5 and Tbx22 in situ hybridization has been added as new Figure 10-S1D and -S1E, since we labelled cells within Lgr5 and Tbx22 expression domain. Data showing section of explant with DiD injection before and after culture has been added as new Figure 10-S1F and -S1G, which showed DiD labelled cells were located within Lgr5 and Tbx22 expression domain before culture and at tongue frenum region after culture.

The weakest point is that the authors demonstrate many interesting phenotypes but fail to show the mechanism of altered cell differentiation and direct evidence of the tissue origin of ectopic brown tissue. Without the data, suggestion from the authors' argument is weak, which is reflected in the conclusion of the abstract.

Many in vitro and in vivo data have been added as new data. We hope that these are enough for our conclusion.

Author response:

Reviewer #2 (Public Review):

(1) Some changes to statistical analyses are needed in this study.

Fig. 1B, 1D, 2A, 3E, and 3F report the QL.d phenotype as a percentage of animals scored that were defective in migration. The methods make it clear this data is categorical rather than quantitative. Therefore, a t-test or any test designed for quantitative data is not appropriate. I suggest that the authors should investigate using a chi-squared or Fisher's exact test.

For the reasons mentioned above, the calculation of standard deviation (as shown in error bars) is also not appropriate for Fig. 1B, 1D, 2A, 3E, and 3F. Of course, it is excellent that the authors scored multiple trials. For experiments with mutants, I suggest the authors might combine these trials or show separate results of each trial. For experiments using RNAi (Fig. 1B), each trial should be plotted separately because RNAi effectiveness can vary. If there is not enough space to show multiple trials, then I would ask that a representative trial be shown in the main figure and additional trials in a supplement.

We thank the reviewer for pointing out the statistical mistake. For all figures assessing the QL.d migration phenotype (Fig.1B, 1D, 2A, 4A (former 3E), 4D (former 3F) and Fig.1 – figure supplement 1, Fig.2 – figure supplement 1, Fig.4 – figure supplement 2) the statistical significance was evaluated using Fisher’s exact test. For RNAi experiments (Fig. 1B) results from a representative experiment is shown and two additional trials are shown in Figure 1 – figure supplement 1. For experiments with mutants, results from separate trials were pooled and are presented in the main figures.

In Fig. 1, 2, 3, and 5, it is not specified whether/how p-values were adjusted for multiple tests.

We have applied Bonferroni correction for multiple testing in all Figures where it was relevant (Fig. 1, 2, 4, 5 and 6 and in their supplements) and this is now stated in all corresponding Figure legends.

(2) I felt the author's interpretation of the sel-5 mutant phenotypes in EXC, and the genetic interactions with Wnt signaling mutants, might be improved. The authors show convincing data that the sel-5 mutants display a shortened EXC outgrowth phenotype. Conversely, mutants with reduced Wnt signaling, such as the lin-17 or lin-44 mutants, displayed lengthened EXC outgrowth. The authors show that in double mutants, loss of sel-5 partially suppressed the EXC overgrowth defects of lin-17 or lin-44 mutants (Fig. 5). In my opinion, this data is consistent with a model where SEL-5 acts to inhibit Wnt signaling in EXC. An inhibitory role in a Wnt-receiving cell would be consistent with the known activity for human AAK1 in promoting negative feedback and endocytosis of LPR6. Interestingly, the authors mention in their discussion that a mutant of plr-1, which acts in the internalization of Frizzled receptors, has a shortened EXC phenotype similar to that of sel-5 mutants. These observations all seem consistent with an inhibitory role, yet the authors do not state this as their conclusion. A clarification of their interpretation is needed.

We thank the reviewer for this feedback. Indeed, the above interpretation of the excretory cell migration data is plausible, however, we think that several lines of evidence argue against this possibility. First, measurements of the posterior canal length during L1/L2 larval stages show that LIN-44/LIN-17 signalling is not required for the early stages of excretory canal outgrowth, unlike SEL-5/VPS-29 (Fig. 5E, 6D). This suggests that SEL-5 and VPS-29 are required earlier than LIN-44 and LIN-17 and therefore should not act at the level of Wnt receptor internalization. Our new data with more mutant combinations revealed canal shortening in cwn-1; cfz-2 and cwn-2; cfz-2 mutants. This would rather suggest a positive role for SEL-5 and VPS-29 in Wnt pathway regulation. Either SEL-5/VPS-29 employ two different mechanisms of Wnt pathway regulation or alternatively, act prior to any Wnt-dependent step in the excretory canal outgrowth. The observed partial rescue of the lin-17 or lin-44 overgrowth defect by sel-5 could then be explained for example by a reduced speed of canal outgrowth in sel-5 mutants. Based on new findings about CWN-1, CWN-2 and CFZ-2 involvement we have also modified our model now presented in Fig.7.

For changes to the Results section, see Response to Reviewer 1, point 4b. The Discussion part has been substantially rewritten and is presented below:

LINE 428 “Our analysis of single Wnt and Frizzled mutants revealed that while loss of cwn-2 or cfz-2 expression resulted in a very mild shortening of the excretory canal, loss of lin-44 or lin-17 led to profound canal overgrowth (summarized in Fig. 7A). These findings suggested that two independent Wnt pathways could be employed to establish proper excretory canal length – one promoting canal extension and one generating the stop signal for growth termination. Further analyses of double mutants and other Wnt signalling components revealed that the extension-promoting pathway includes cwn-1 in addition to cwn-2 and cfz-2, while the stop-signal pathway encompasses lin-44, lin-17, dsh-1, mig-5 and mig-14. A similar repulsive role of LIN-44/LIN-17 complex has been described in the case of a posterior axon of C. elegans GABAergic DD6 motor neuron (Maro et al., 2009) or PLM, ALN and PLN neurons (Zheng et al., 2015). Loss of lin-44 or lin-17 expression promoted outgrowth of the posterior neurites of these neurons implicating that in wild type animals, LIN-44 serves as a repulsive cue. On the other hand, cwn-2 and cfz-2 were shown to positively regulate the posterior neurite outgrowth of RMED/V neurons with cwn-2 acting as an attractive cue (Song et al., 2010). The role of two other Wnt signalling components, egl-20 and mig-1, is less clear. No effect (mig-1) or only very mild overgrowth defect (egl-20) is observed in single mutants. However, both egl-20 and mig-1 significantly rescue the overgrowth phenotype of lin-17 mutants, while at the same time, mig-1 can suppress the shortening of canals in cfz-2 mutants. EGL-20-producing cells are localized around the rectum (Whangbo et al., 1999; Harterink et al., 2011), exactly where the excretory canals stop, while LIN-44 is expressed more posteriorly (Herman et al., 1995; Harterink et al., 2011). A possible explanation could thus be that while LIN-44 provides a general posterior repulsive signal, EGL-20 fine-tunes the exact stopping position of the growing canal. The role of different Wnts and Frizzleds in excretory canal outgrowth is summarized in Fig. 7B. Further investigation will be required to decipher the exact way how SEL-5 and the retromer crosstalk with Wnt signalling during excretory cell outgrowth. It is clear though that more than one mechanism is likely involved. First, sel-5 vps-29 mutants display canal shortening similarly to cwn-1; cfz-2 or cwn-2; cfz-2 suggesting a positive regulatory role. Mutants in lin-17 and lin-44 display canal overgrowth, yet sel-5 is partially able to suppress this phenotype. This would imply a negative regulatory role of sel-5 and be in agreement with the role of AAK1 in Wnt pathway regulation (Agajanian et al., 2019). However, sel-5 and vps-29 are required already during the initial larval outgrowth while the LIN-44/LIN-17 signal is required later. The observed rescue might thus also be explained by a delayed growth of the canal and not by a direct impact of sel-5 and vps-29 on LIN-44 or LIN-17 levels or localization.”

Argument contre 2

Author response:

Reviewer #2 (Public Review):

The manuscript entitled " Multimodal HLA-I genotypes regulation by human cytomegalovirus US10 and resulting surface patterning" by Gerke et al describes the biochemical analysis of US10-mediated down regulation of HLA-I molecules. The authors systemically examine the surface expression of different HLA-I alleles in cells expressing US10 and interactions of US10 with HLA-I and antigen presentation machinery. Further, studies examined genotypic and allotypic differences during expression of US10/US11 transcripts suggest a different allelic class I downregulation. In general, the authors have included data supporting the major claims. Yet, the conclusions and findings of the study only marginally advance the overall understanding of HCMV viral evasion and the mechanism of US10 function.

Strengths:

The studies are well characterized and the studies utilize diverse HLA-I and HCMV viral molecules. The biochemistry is excellent and is of high quality. Importantly, the study describes HLA-I allelic specific HCMV down regulation at the cell surface and molecular levels.

Weaknesses:

(1) The authors use over expressive language such as "strong binding" that does not have a quantitative value and it is relative to the specific assay with only small differences among the factors.

We have changed the language to avoid non-quantitative expressions.

(2) The US10 binding to the HLA-I did not correlate with class I surface levels suggesting that binding to the APC machinery (Figure 1); hence, why does the binding of US10 to the APC define its mechanism of action.

We hypothesized that since binding to HLA-I allomorphs did not correlate with surface expression, further factors could be involved in regulation. Since the PLC (APC machinery) plays a major role for HLA-I expression, it was relevant to investigate this. The new data underlines the importance of the PLC for US10-mediated HLA-I regulation.

(3) The innovative and significant aspects of the study are limited. The study does not delineate the US10 mechanism of action or show data in which US10-mediated MHC class I down regulation impacts adaptive or innate immune function.

These remarks are important. We want to emphasize the variable impact of US10 on HLA-I. To our knowledge previous studies have not uncovered genotype-dependent effects on HLA-I as distinct as those observed with US10, indicating that US10 may exploit aspects of HLA-I that are yet to be fully elucidated. Therefore, confirming these findings is crucial for our study. The quantitative analysis of the HeLa HLA-I ligandome in US10-expressing cells strongly supports this conclusion. The precise quantification of HLA-I peptide ligands was made possible through collaboration with Dr. Andreas Schlosser from Würzburg, Germany, who possesses profound expertise in this specific method. Thus, in our opinion, this revision has enabled us to advance innovation and, importantly, enhance the significance of our study.

Author response:

Reviewer #3 (Public Review):

Software UX design is not a trivial task and a point-and-click interface may become difficult to use or misleading when such design is not very well crafted. While Phantasus is a laudable effort to bring some of the out-of-the box transcriptomics workflows closer to the broader community of point-and-click users, there are a number of shortcomings that the authors may want to consider improving.

Thank you for such an in-depth review. We really appreciate this feedback and have tried to address all of the concerns in the new version of Phantasus.

Here I list the ones I found running Phantasus locally through the available Bioconductor package:

(1) The feature of loading in one click one of the thousands of available GEO datasets is great. However, one important use of any such interfaces is the possibility for the users to analyze his/her own data. One of the standard formats for storing tables of RNA-seq counts are CSV files. However, if we try to upload from the computer a CSV file with expression data, such as the counts stored in the file GSE120660_PCamerge_hg38.csv.gz from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120660, a first problem is that the system does not recognize that the CSV file is compressed. A second problem is that it does not recognize that values are separated by commas, the very original CSV format, giving a cryptic error "columnVector is undefined". If we transform the CSV format into tab-separated values (TSV) format, then it works, but this constitutes already a first barrier for the target user of Phantasus.

Thank you for highlighting this issue of file formats support. We acknowledge the commonality of CSV and CSV.gz files in gene expression analysis. As a response, we have updated our data loading procedure to support these file formats. Moreover, the most recent version of our web application is able to recognize gzip-archived file in any of supported table formats: GCT, TSV, CSV and XLSX.

(2) Many RNA-seq processing pipelines use Ensembl annotations, which for the purpose of downstream interpretation of the analysis, need to be translated into HUGO gene symbols. When I try to annotate the rows to translate the Ensembl gene identifiers, I get the error

"There is no AnnotationDB on server. Ask administrator to put AnnotationDB sqlite databases in cacheDir/annotationdb folder"

Thank you for revealing this issue. Indeed, locally installed instances of the Phantatus might lose some functionality in absence of some auxiliary files. For example, gene annotation mapping is unavailable without annotation databases. Previously, the user had to perform additional setup steps to unlock a few features, which might be confusing and unclear. In order to overcome this we have revised significantly the installation procedure. Newly added ‘setupPhantasus’ function is able to create all necessary configuration files and provides an interactive dialog with the user that helps to load all necessary data files from our official cache mirror (https://alserglab.wsutl.edu/files/phantasus/minimal-cache/). Docker-based installation follows the same approach, however it is configured to install everything by default. Thus, with help of the new installation procedure locally installed Phantasus now has the whole functionality available at the official mirrors. The comprehensive installation description is now available at https://ctlab.github.io/phantasus-doc/installation.

(3) When trying to normalize the RNA-seq counts, there are no standard options such as within-library (RPKM, FPKM) or between-library (TMM) normalization procedures.

Appreciating your feedback, we've expanded the available normalization options in the updated version of Phantasus. We added support for TMM normalization as suggested by the edgeR package and voom normalization from the limma package. However, certain strategies like RPKM/FPKM or TPM rely on gene-specific effective lengths, which are challenging to infer without protocol and alignment details. As Phantasus operates on gene expression matrices and doesn't execute alignment steps, the implementation of these normalization seems infeasible. On the other hand, if the user has the matrix with FPKM or TPM gene values (for example from a core facility), such a matrix can be loaded into Phantasus and used for the analysis.

If I take log2(1+x) a new tab is created with the normalized data, but it's not easy to realize what happened because the tab has the same name as the previous one and while the colors of the heatmap changed to reflect the new scale of the data, this is quite subtle. This may cause that an unexperienced user to apply the same normalization step again on the normalized data. Ideally, the interface should lead the user through a pipeline, reducing unnecessary degrees of freedom associated with each step.

Thank you for your comment. Indeed our approach to create a new tab for each alteration to the expression values preserving the name might be the source of confusion for a user. On the other hand, generating informative tab names without overwhelming users with too much detail is also challenging. As a compromise we have an option for the user to manually rename the tab. Still, we agree that this remains an area for improvement. We also consider it to be a part of a larger issue: for example, the loaded data can already be log-scaled, so that even one round of log-scale transformation in Phantasus would be incorrect. Accordingly, we are exploring ways to address this issue in the future by adding automated checks for the tools or, as you suggested, implementing stricter pipelines.

(4.4) Phantasus allows one to filter out lowly-expressed genes by averaging expression of genes across samples and discarding/selecting genes using some cutoff value on that average. This strategy is fine, but to make an informed decision on that cutoff it would be useful to see a density plot of those averages that would allow one to identify the modes of low and high expression and decide the cutoff value that separates them.

Thank you for the suggestion. Indeed a density plot might help users to make informed decisions during gene filtration. We have added such a plot into the ‘Plot/Chart’ tool as a ‘histogram’ chart type.

It would be also nice to have an interface to the filterByExpr() function from the edgeR package, which provides more control on how to filter out lowly-expressed genes.

Thank you for proposing the inclusion of an interface for the filterByExpr() function from the edgeR package. In the recent update we have incorporated filterByExpr() as part of the voom normalization tool. For now, for simplicity, we have decided to keep only the default parameter values. However, we will explore the addition of the dedicated filtering tool in the future.

(5) When attempting a differential expression (DE) analysis, a popup window appears saying:

"Your dataset is filtered. Limma will apply to unfiltered dataset. Consider using New Heat Map tool."

One of the main purposes of filtering lowly-expressed genes is mainly to conduct a DE analysis afterwards, so it does not make sense that the tool says that such an analysis will be done on the unfiltered dataset. The reference to the "New Heat Map tool" is vague and unclear where should the user look for that other tool, without any further information or link.

Thank you for highlighting this issue. We agree that the message in the popup window and the default action were confusing. In response to your feedback, we've updated the default behavior of our DE tools to automatically use the filtered data in a new tab. Additionally, we've clarified the warning message to ensure a better understanding of this process.

(6) The DE analysis only allows for a two-sample group comparison, which is an important limitation in the question we may want to address. The construction of more complex designs could be graphically aided by using the ExploreModelMatrix Bioconductor package (Soneson et al, F1000Research, 2020).

Indeed, the ability to create complex designs and various comparisons is important for many applications for gene expression analysis. Accordingly, in the latest Phantasus version, we've introduced an advanced design feature for the DE analysis, enabling the utilization of multiple column annotations for the design matrix. Combined with the existing ability to create new annotations, this update facilitates the setup of diverse design matrices. While at the moment we do not allow setting a complex contrast, we hope that the current interface will cover most of the differential expression use cases.

(7) When trying to perform a pathway analysis with FGSEA, I get the following error:

"Couldn't load FGSEA meta information. Please try again in a moment. Error: cannot open the connection In call: file(file, "rt")

We hope that this issue should be resolved after we have implemented a more streamlined setup process. Among others, the new approach aims to eliminate the unexpected absence of metafiles in local installations. The latest Phantasus package version explicitly prompts the user to load necessary additional files automatically during the initial run, reducing options for an invalid setup.

Finally, there have been already some efforts to approach R and Bioconductor transcriptomics pipelines to point-and-click users, such as iSEE (Rue-Albrecht et al, 2018) and GeneTonic (Marini et al, 2021) but they are not compared or at least cited in the present work.

Indeed, our comparison was focused toward tools that offer non-programmatic functionalities for gene expression data analysis. While tools like iSEE and GeneTonic are adept at visualizing data and hold their own in providing extensive abilities, they do necessitate additional data preparation using R, distinguishing them from the specific scope of tools we assessed.

One nice features of these two tools that I missed in Phantasus is the possibility of generating the R code that produces the analysis performed through the interface. This is important to provide a way to ensure the reproducibility of the analyses performed.

The ability to generate R code within tools like these indeed aids in ensuring analysis reproducibility. Moreover, we have previously attempted implementing this functionality in Phantasus, however it proved to be hard to do in a useful fashion due to potential complex interactions between user and the client-side part of Phantasus. Nevertheless, we acknowledge the significance of such a feature and aim to introduce it in the future.

Fate and destiny are two things you can't negotiate

Author Response:

We thank the reviewers for careful reading, acknowledging the strength of our manuscript, and pointing out its weakness, which we will address in the revised version as described below.

(1) We will supplement our analysis with finer statistical testing and analysis, such as cross-validation and a more detailed analysis of the relation between the inferred model and the intrinsic timescales of the system. For the effect of the drug TIMP-1 on the animal, we will first explore the possibility of assessing the results using a multifactor ANOVA test, with the caveat that the distribution of interactions is not Gaussian. We will further test the effect of different group size on the significance of our results by considering subgroups of animals in the drug group, and compare the statistics between the (subsampled) drug group and the controlled group.

(2) Our manuscript is similar with that of Shemesh et al. in that we both analyze socially interacting mice by constructing maximum entropy models (MEM) of the co-localization patterns of mice. The difference is in the setup and the number of mice (4 mice in Shemesh et al, 10-15 in our work), as we outlined in the manuscript. To further supplement our current argument of the difference of our results in the Discussion section, we will learn a MEM model up to triplet interactions for our Eco-HAB mice data, and compare to our current MEM model up to pairwise interactions using test-set validation or the Bayesian information criterion (BIC).

Buying and selling

Although this is a great you also have to take it from the gatekeeping business side. If you have an idea and it works you shouldn't just tell everyone

eLife assessment

This work explores how centrosomes, which function as the primary microtubule organizing center in animal cells, regulate cell division by examining the process in cells in which centrosome formation has been inhibited. The carefully conducted experiments provide convincing support for the important observation that elongated, but successful, mitosis observed in cells lacking centrosomes is due to delays in cell cycle progression.

Reviewer #1 (Public Review):

In their manuscript "Spindle assembly checkpoint-dependent mitotic delay is required for cell division in absence of centrosomes," Farrell and colleagues employ carefully chosen approaches to assay mitotic timeliness in the absence of centrosomes in mammalian culture cells, namely the mechanism behind it and its function. The authors acknowledge prior work well and present their data succinctly, clearly, and with a clear logical flow of experiments. The experiments are thoughtfully designed and presented, with appropriate controls in place.

The authors' model whereby centrosome separation and its early definition of poles mediates timely mitosis without relying on a SAC-dependent delay is compelling, and the authors' data are consistent with it. They show using two different MPS1 inhibitors that acentrosomal cell division fails, supporting their claims that a SAC-dependent delay is required in these instances. Furthermore, they show that reintroducing a time delay is sufficient to restore cell division, but inhibiting a different aspect of SAC function does not restore cell division. Next, the authors rule out polyploidy as a potential confounding factor for requiring a SAC-dependent delay, and instead demonstrate that inhibiting centrosome separation by Eg5 inhibition is sufficient to require this delay for mitotic progression. The authors' findings overall support their proposed model.

Probing what aspects of centrosomes protect against a requirement for SAC-dependent delays would strengthen the work and specifically the conclusion that centrosomes provide "two-ness". For example, the authors could examine division in a population of cells with only one centrosome. Seeing some restoration of mitotic progression in the absence of SAC-dependent delays would suggest that even one centrosome with uninhibited Eg5 is sufficient to negate SAC-dependent delays, and would limit models for what exactly centrosomes contribute. This would help disentangle the roles of actual centrosomes and their biochemical cues, Eg5-driven centrosome separation, and early definition of poles on mitotic progression in the absence of SAC-dependent delays. Making a high fraction of cells with one centrosome could be achieved by using centrinone for a shorter time.

Comments on revised version:

The main point from the initial review does not appear to be addressed in the revised version. As such, the comments on the revised version remain the same.

Reviewer #2 (Public Review):

Centrosomes are an integral part of cell division in most animal cells. There are notable exceptions, however, such as oocytes and plants. In addition, some animal cells can be engineered to lack centrosomes yet they can still manage to complete mitosis. This paper uses a couple of methods (PLK4 inhibition and deletion of SASS6) to remove centrosomes from an immortalized cell line. Indeed, a strength of the paper is that similar results are obtained using both protocols to generate acentrosomal cells. The authors find acentrosomal cells take longer to divide, mostly due to a longer metaphase. The paper is based on the finding that inhibition of MPS1 results in a failure to divide, and the hypothesis that a SAC - dependent delay is required for these acentrosomal cells to divide.

The finding that MPS1 inhibition results in a failure to division is interesting. This is investigated by analyzing cells where AurB, APC or Eg5 (to generate monastral spindles) have been inhibited. My concerns are that the results are not conclusive that the effect of MPS1 is on cell cycle regulation. There is not enough data to make a conclusion as to why inhibition of MPS1 results in cell division failure.

1) An example is how to interpret the effect of Aurora B inhibition, which does not block acentrosomal cell division. If Aurora B is required for SAC activity, it suggests this effect of MPS1 may be a function other than SAC. Given the complexity of the SAC, it would be informative to test other SAC components. Instead, the authors conclude that the mitotic delay caused by MPS is required for acentrosomal cell division. I don't think they have ruled out, or even addressed other functions of MPS1.

2) The authors find that when both the APC and MPS1 are inhibited, the cells eventually divide. These results are intriguing, but hard to interpret. The authors suggest that the failure to divide in MPS1-inhibited cells is because they enter anaphase, and then must back out. This is hard to understand and there is not data supporting some kind of aborted anaphase. Is the division observed with double inhibition some sort of bypass of the block caused by MPS1 inhibition alone? It is not clear why inhibition of APC causes increased cell division when MPS1 is inhibited.

3) The authors characterize MTOC formation in these cells, which is also interesting. MTOCs are established after NEB in acentrosomal cells. Indeed, forming these MTOCs is probably a key mechanism for how these cells complete a division, like mouse oocytes.

Following this, the results with inhibiting Eg5 are interesting. The double inhibition of MPS1 and Eg5 results in division failure, like MPS1 inhibition in acentrosomal cells. Thus, there is a cell division block when the centrioles fail to divide. This result raises the possibility that failure to make a bipolar spindle, or the presence of a monopolar spindle, is the problem. In the absence of a bipolar spindle, a SAC induced delay is required for spindle assembly. This is a possibility but there are multiple interpretations of these results. Primarily, these results do not show the MPS1 effect on acentrosomal cells is SAC related. That a SAC mediated delay is required for acentrosmomal spindle assembly is not the only conclusion.

Comments on revised version:

It appears that very few changes have been made. These are all suggestions in the writing and interpretation.

It's disappointing the most of the readouts are cell division success. There is a lack of data about what happens in the MPS1 knockdowns, such as microtubule attachment to KTs and localization/ activity of checkpoint proteins or downstream factors. More mechanistic insights may be found by testing other checkpoint proteins or assaying more metrics for spindle assembly and cell cycle progression. Or if inducing cell cycle delay suppresses the MPS1 effect. These experiments would implicate cell cycle factors as being required for acentrosomal spindle assembly while ruling out a requirement for MPS1 in spindle assembly.

The paper is well written. But some of the terminology could be improved and some descriptions of the cytology are confusing. Some clear definitions of terms may help. The authors refer to an "extended mitosis" (line 73) and then "exit in the absence of cell division" (line 96) when MPS1 is inhibited. Both are misleading and don't tell the full story. These cells attempt to divide and then fail, resulting in one cell. Use of terms like "spread back out", "rounding up", and "sitting down" seems like jargon and should at least be defined. The term "timely two-ness" (line 23-24) is also not helpful. A brief discussion of data on MPS1 function in mouse and fly acentrosomal meiosis might be appropriate. A comparison would be interesting since loss of MPS1 in acentrosomal oocytes does not have such a drastic block in cell division.

Author response:

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

We thank the reviewers for a careful review of the manuscript and for their comments, which we address below.

Reviewer #1:

(1) …the authors could examine division in a population of cells with only one centrosome. Seeing some restoration of mitotic progression in the absence of SAC-dependent delays would suggest that even one centrosome with uninhibited Eg5 is sufficient to negate SAC-dependent delays, and would limit models for what exactly centrosomes contribute.

We agree that the one-centrosome question (i.e. whether cells with a single centriole, and therefore a single centrosome, have the same SAC dependence) would be interesting to address. It is known that cells with a single centriole generated through centrinone treatment also have elongated mitoses, like cells lacking centrioles (see Chinen, et. al. 2021, compare Fig 2C to Fig 2D), We have tried this experiment in RPE-1 cells with preliminary results confirming that there is a mitotic delay. It is not known whether this delay requires SAC activity, and we hope to address that in future work. In addition, we note that we show in Fig. 4b-c that cells with the normal centrosome number but with a single focus of microtubules due to Eg5 inhibition, were also sensitive to MPS1 inhibition. This suggests that centrosome presence alone cannot overcome the requirement for SAC activity, rather, the centrosomes need to be able to separate in a timely fashion.

Reviewer #2:

(1) An example is how to interpret the effect of Aurora B inhibition, which does not block acentrosomal cell division. If Aurora B is required for SAC activity, it suggests this effect of MPS1 may be a function other than SAC. Given the complexity of the SAC, it would be informative to test other SAC components. Instead, the authors conclude that the mitotic delay caused by MPS is required for acentrosomal cell division. I don't think they have ruled out, or even addressed other functions of MPS1.

We agree that it is possible that functions of the MPS1 kinase other than those involved in the SAC could be important. Although we have not directly tested other SAC components, we did “mimic” SAC activity by delaying anaphase onset using APC/C inhibition while also inhibiting MPS1 (Fig. 2b-b’’). The fact that this restored division suggests that it is the SAC function of MPS1 kinase activity that is relevant to this delay. 

(2) The authors find that when both the APC and MPS1 are inhibited, the cells eventually divide. These results are intriguing, but hard to interpret. The authors suggest that the failure to divide in MPS1-inhibited cells is because they enter anaphase, and then must back out. This is hard to understand and there is not data supporting some kind of aborted anaphase. Is the division observed with double inhibition some sort of bypass of the block caused by MPS1 inhibition alone? It is not clear why inhibition of APC causes increased cell division when MPS1 is inhibited.

As described in the response to 1), we believe that reinstating the delay to anaphase onset by APC/C inhibition provided the time needed to establish a functional bipolar spindle even in the absence of the SAC, and that cells eventually overcome the proTAME block and proceed through mitosis, as observed in control cells in our experiments. We note that we chose concentrations of proTAME specifically for each cell line (RPE-1 and U2OS) that would result only in a temporary block, following on the work of Lara-Gonzalez and Taylor (2012), who reported similar findings for HeLa cells.

(3) The authors characterize MTOC formation in these cells, which is also interesting. MTOCs are established after NEB in acentrosomal cells. Indeed, forming these MTOCs is probably a key mechanism for how these cells complete a division, like mouse oocytes.

We agree that the observed intermediates of MTOCs are interesting and likely crucial to the mechanism of cell division in acentrosomal somatic cells. We are investigating further the differences and similarities between somatic cell MTOC formation in the absence of centrosomes and the naturally-occurring form of that process in oocytes.

You can't feed every sick patient the same medicine !

test

Will do

Brauchen wir hier alle Absprünge im Header oder kann man das reduzieren? Hat man sein Cobranding dann je nach Nutzer:in?

Progressbar ist sehr nah an Scrollbar. könnte man das nach links stellen oder macht das probleme?

Kommt hieri m allgemeinen noch ein Anreiz für das Gewinsspiel in form von Grafik Bild etc? was passiert hier dann?

Hier ist gemischt gut. aber das Pulsieren mit em Schlagschatten finde ich etwas heftig

Auch hier ist der Efffekt wieder ein andrer als auf den ersten slides. einheitlich?

Typofarbe ändert sich wegen HON Lounges? Sieht ein bisschen nach Fehler aus. auch wenns nur detail ist. Würde wenn dann etwas deutlicher einfärben. hintergrund?

HON Lounges und surfer passen finde ich nicht. kommt aber besimmt noch ein bild

Ich finde im ersten bild nach dem Begriff Community braucht es etwas was mehr community sagt. Das ist jetzt das selbe inhatllich wie im Abschnitt "reisen wir zurück"

Ich finds ansich nicht verkehrt das so zu machen in diesem Fall. Können wir es noch deutlicher zu einem einzelfall machen und es sich etwas abheben lassen?

Versal zu gemsicht

Könnten wir ghenerell die Bilder tweaken, dass sie dezente animationen in sich tragen? oder zumindest ganz leichtes aufskalieren? Mit der Scrollbewegung?

CTA Versal sollte eher gemsicht denke ich. Warum erst weiß und dann blau BG Farbe?

Der Typewritereffekt ist anders als der auf den ersten screens. da fadet es eher von unten rein. können wir einheitlicher werden?

Versal eher nur bei den Worten Points und Meilen. Vielleicht aber auch da mal gemischt versuchen

Das läuft noch wie ein nicht gewolltes Element mit. Ist das Teil des Designs?

This equation is not correct since if dy/dx is inserted on the differential equation dy/dx+3y=6x+11 it should be: ((-3e^-2x)+2)+3((e^-3x)+2x+3)=6x+11 Correct?

pricing