https://www.derstandard.de/story/3000000226757/griechenland-kaempft-den-zweiten-tag-infolge-gegen-flaechenbrand-auf-kos

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Reviewer #1 (Public Review):

Summary:

The manuscript by Zhou et al offers new high-resolution Cryo-EM structures of two human biotin-dependent enzymes: propionyl-CoA carboxylase (PCC) and methycrotonyl-CoA carboxylase (MCC). While X-ray crystal structures and Cryo-EM structures have previously been reported for bacterial and trypanosomal versions of MCC and for bacterial versions of PCC, this marks one of the first high resolution Cryo-EM structures of the human version of these enzymes. Using the biotin cofactor as an affinity tag, this team purified a group of four different human biotin-dependent carboxylases from cultured human Expi 293F (kidney) cells (PCC, MCC, acetyl-CoA carboxylase (ACC), and pyruvate carboxylase). Following further enrichment by size-exclusion chromatography, they were able to vitrify the sample and pick enough particles of MCC and PCC to separately refine the structures of both enzymes to relatively high average resolutions (the Cryo-EM structure of ACC also appears to have been determined from these same micrographs, though this is the subject of a separate publication). To determine the impact of substrate binding on the structure of these enzymes and to gain insights into substrate selectivity, they also separately incubated with propionyl-CoA and acetyl-CoA and vitrified the samples under active turnover conditions, yielding a set of cryo-EM structures for both MCC and PCC in the presence and absence of substrates and substrate analogues.

Strengths:

The manuscript has several strengths. It is clearly written, the figures are clear and the sample preparation methods appear to be well described. This study demonstrates that Cryo-EM is an ideal structural method to investigate the structure of these heterogeneous samples of large biotin-dependent enzymes. As a consequence, many new Cryo-EM structures of biotin-dependent enzymes are emerging, thanks to the natural inclusion of a built-in biotin affinity tag. While the authors report no major differences between the human and bacterial forms of these enzymes, it remains an important finding that they demonstrate how/if the structure of the human enzymes are or are not distinct from the bacterial enzymes. The MCC structures also provide evidence for a transition for BCCP-biotin from an exo-binding site to an endo-binding site in response to acetyl-CoA binding. This contributes to a growing number of biotin-dependent carboxylase structures that reveal BCCP-biotin binding at locations both inside (endo-) and outside (exo-) of the active site.

Weaknesses:

There are some minor weaknesses. Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues. There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors state that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. This is not a particularly deep analysis and doesn't really require a cryo-EM structure to invoke. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. This suggests, perhaps, that these structures do not yet fully capture the proper conformational states. The authors also need to be careful with their over-interpretation of structure to invoke mechanisms of conformational change. A snapshot of the starting state (apo) and final state (ligand-bound) is insufficient to conclude *how* the enzyme transitioned between conformational states. I am constantly frustrated by structural reports in the biotin-dependent enzymes that invoke "induced conformational changes" with absolutely no experimental evidence to support such statements. Conformational changes that accompany ligand binding may occur through an induced conformational change or through conformational selection and structural snapshots of the starting point and the end point cannot offer any valid insight into which of these mechanisms is at play.

Some of these minor deficiencies aside, the overall aim of contributing new cryo-EM structures of the human MCC and PCC has been achieved. While I am not a cryo-EM expert, I see no flaws in the methodology or approach. While the contributions from these structures are somewhat incremental, it is nevertheless important to have these representative examples of the human enzymes and it is noteworthy to see a new example of the exo-binding site in a biotin-dependent enzyme.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this study, Jellinger et al. performed engram-specific sequencing and identified genes that were selectively regulated in positive/negative engram populations. In addition, they performed chronic activation of the negative engram population over 3 months and observed several effects on fear/anxiety behavior and cellular events such as upregulation of glial cells and decreased GABA levels.

Strengths:

They provide useful engram-specific GSEA data and the main concept of the study, linking negative valence/memory encoding to cellular level outcomes including upregulation of glial cells, is interesting and valuable.

Weaknesses:

A number of experimental shortcomings make the conclusion of the study largely unsupported. In addition, the observed differences in behavioral experiments are rather small, inconsistent, and the interpretation of the differences is not compelling.

Major points for improvement:

(1) Lack of essential control experiments

With the current set of experiments, it is not certain that the DREADD system they used was potent and stable throughout the 3 months of manipulations. Basic confirmatory experiments (e.g., slice physiology at 1m vs. 3m) to show that the DREADD effects on these vHP are stable would be an essential bottom line to make these manipulation experiments convincing.

In previous work from our lab performing long-term activation of Gq DREADD receptors in the vHPC, we quantify the presence of Gq receptor expression over 3-, 6- and 9-month timepoints and show that there is no decrease in receptor expression, as measured via fluorescence intensity (Suthard et al., 2023). In this study, we also address that even if our manipulation is only working for 1 month, rather than 3 months, we are observing the long-term effects of this shorter-term stimulation. This is still relevant, and only changes how we interpret these findings, as shorter-term stimulation or disruption of neuronal activity can still have detrimental effects on behavior.

Furthermore, although the authors use the mCherry vector as a control, they did not have a vehicle/saline control for the hM3Dq AAV. Thus, the long-term effects such as the increase in glial cells could simply be due to the toxicity of DREADD expression, rather than an induced activity of these cells.

For chemogenetic studies, our experimental rationale utilized a standard approach in the field, which includes one of two control options: 1) active receptor vs. control vector + ligand or 2) active receptor + ligand or saline control. We chose the first option, as this more properly controls for the potential off-target effects of the ligand itself, as shown in other previous work (Xia et al., 2017). This is particularly important for studies using CNO, as many off-target effects have been noted as a limitation (Manvich et al., 2018). We chose to use DCZ as it is closely related to CNO and newer ligands, but comes with added benefits of high specificity, low off-target effects, high potency and brain penetrance (Nagai et al., 2020), but any potential off-target effects of DCZ are yet to be completely investigated as this ligand is very new.

Evidence of DREADD toxicity has been shown at high titer levels of AAV2/7- CamKIIα-hM4D(Gi)-mCherry in the hippocampus at 5 weeks, as the reviewer pointed out in their above comment (Goossens et al., 2021). Our viral strategy is targeted to a much smaller number of cells using AAV9-DIO-Flex-hM3Dq-mCherry at a lower titer, unlike expression within a much larger population of CaMKII+ excitatory neurons in this study. Additionally, visual comparison of their viral load and expression with ours shows much more intense expression that spans a larger area of the hippocampus (Goossens et al, 2021; Figure 1D), whereas ours is isolated to a smaller region of vHPC (see Figure 1B).

Further, we attempted to quantify a decrease in neuronal health (Yousef et al., 2017) resulting from DREADD expression via NeuN counts within multiple hippocampal subregions for the 6- and 14-month groups across active Gq receptor and mCherry conditions and did not observe significant decreases in NeuN as a result (Supplemental Figure 1). However, immunohistochemistry of an individual marker may not be sufficient to capture the entire health profile of an individual neuron and future work should consider other markers of cell death or inflammation, which we have added to the Limitations & Future Work section of our Discussion.

(2) Figure 1 and the rest of the study are disconnected

The authors used the cFos-tTA system to label positive/negative engram populations, while the TRAP2 system was used for the chronic activation experiments. Although both genetic tools are based on the same IEG Fos, the sensitivity of the tools needs to be validated. In particular, the sensitivity of the TRAP2 system can be arbitrarily altered by the amount of tamoxifen (or 4OHT) and the administration protocols. The authors should at least compare and show the percentage of labeled cells in both methods and discuss that the two experiments target (at least slightly) different populations. In addition, the use of TRAP2 for vHP is relatively new; the authors should confirm that this method actually captures negative engram populations by checking for reactivation of these cells during recall by overlap analysis of Fos staining or by artificial activation.

We thank the reviewer for their comments and opportunity to discuss the marked differences between TRAP2 and DOX systems. In particular, we agree that while both systems rely on the the Fos promoter to drive an effector of interest, their efficacy and temporal resolution vary substantially depending on genetic cell-type, brain region, temporal parameters of Dox or 4-OHT delivery, subject-by-subject metabolic variability, and threshold to Fos induction given the promoter sequences inherent to each system. For example, recent studies have reported the following:

- The TRAP2 line labels a subset of endogenously activeCA1 pyramidal cells (e.g. 5-18%) while the DOX system labels 20-40% of CA1 pyramidal cells (DeNardo et al, 2019; Monasterio et al, BioRxiv 2024 ).

- The temporal windows for each range from hours in TRAP2 to 24-48 hours for DOX (DeNardo et al, 2019; Denny et al, 2014; Liu & Ramirez et al, 2012).

- The efficacy of “tagging” a population of cells with TRAP2 vs with DOX will constrain the number of possible cells that may overlap with cFos upon re-exposure to a given experience (e.g. see the observed overlaps in vCA1 - BLA circuits (Kim & Cho, 2020), compared to vCA1 in general (Ortega-de San Luis et al, 2023) and valence-specific vCA1 populations (Shpokayte et al, 2022).

- Tagging vCA1 cells with both the TRAP2 and DOX systems are nonetheless sufficient to drive corresponding behaviors (e.g. vCA1 terminal stimulation drives behavioral changes with the DOX and TRAP2 system (Shpokayte et al, 2022) and vCA1 stimulation of an updated fear-linked ensemble drives light-induced freezing in a neutral context utilizing the TRAP2 and DOX systems (Ortega-de San Luis et al, 2023)).

Finally, and promisingly, as more studies continue to link the in vivo physiological dynamics of these cell populations tagged using each system (e.g. compare Pettit et al, 2022 with Tanaka et al, 2018) and correlating their activity to behavioral phenotypes, our field is in the prime position to uncover deeper principles governing hippocampus-mediated engrams in the brain. Together, we believe a more comprehensive understanding of these systems is fully warranted, especially in the service of further cataloging cellular similarities and differences within such tagged populations.

(3)  Interpretation of the behavior data

In Figures 3a and b, the authors show that the experimental group showed higher anxiety based on time spent in the center/open area. However, there were no differences in distance traveled and center entries, which are often reduced in highly anxious mice. Thus, it is not clear what the exact effect of the manipulation is. The authors may want to visualize the trajectories of the mice's locomotion instead of just showing bar graphs.

Our findings show that our experimental group displays higher levels of anxiety-like behaviors as measured via time spent in center/open area, while there are no differences in distance traveled or center entries. For distance traveled, our interpretation is in line with complementary research (Jimenez et al, 2018; Kheirbek et al, 2013) that shows no changes in distance traveled/distance traveled in the center coupled with changes in anxiety levels as a result of manipulation within anxiety-related circuits. More broadly, any locomotion-related deficit could cause a change in distance traveled that is unrelated to anxiety-like behaviors alone. For example, a reduction in distance traveled could be coupled with a decrease in time spent in the center, but could also result only from motor or exploratory deficits. We hope that this explanation clarifies our interpretation of the open field and elevated plus maze findings in light of other literature.

In addition, the data shown in Figure 4b is somewhat surprising - the 14MO control showed more freezing than the 6MO control, which can be interpreted as "better memory in old". As this is highly counterintuitive, the authors may want to discuss this point. The authors stated that "Mice typically display increased freezing behavior as they age, so these effects during remote recall are expected" without any reference. This is nonsense, as just above in Figure 4a, older mice actually show less freezing than young mice. Overall, the behavioral effects are rather small and random. I would suggest that these data be interpreted more carefully.

In Figure 4B, we present our findings from remote recall and observe increased freezing levels in control mice with age, as mentioned by the reviewer, indicating increased memory. This is in line with previous work from Shoji & Miyakawa, 2019 which has been added as a reference for the quotation described above; we thank the reviewer for pointing this error out. As the reviewer has pointed out, above in Figure 4A, we measured freezing levels across all groups during contextual fear conditioning before the start of chronic stimulation, as this was the session we ‘tagged’ a negative memory in. Although it appears that there may be slightly lower levels of freezing in older (14-month old) mice, our findings do not determine statistical significance for difference between age group, only effects of time and subject which are expected as freezing increases within the session and animals display high levels of variability in freezing levels across many experiments (Figure 4A i-iii). We also find in previous work that control mice receiving 3-, 6- and 9-months of chronic DCZ stimulation in the vHPC with empty vector (mCherry) receptor show an increase in freezing with age (Suthard et al, 2023; Figure 2A ii).

(4) Lack of citation and discussion of relevant study

Khalaf et al. 2018 from Gräff lab showed that experimental activation of recall-induced populations leads to fear attenuation. Despite the differences in experimental details, the conceptual discrepancy should be discussed.

As mentioned by the reviewer, Khalaf et al. 2018 showed that experimental activation of recall-induced populations in the dentate gyrus leads to fear attenuation. Specifically, they pose that this fear attenuation occurs in these ensembles through updating or unlearning of the original memory trace via the engagement, rather than suppression, of an original traumatic experience. Despite the differences in experimental details with our current study and this work, we agree that the conceptual discrepancy should be discussed. First, one major difference is that we are reactivating an ensemble that was tagged during fear memory encoding, while Khalaf et al. are activating a remote recall-induced ensemble that was tagged one month after encoding. Although there is high overlap between the encoding and recall ensembles when mice are exposed to the conditioning context, these ensembles are not identical and may result in different behavioral phenotypes when chronically reactivated. Further, Khalaf et al rely on reactivation of the recall-induced ensemble during extinction to facilitate rapid fear attenuation. This differs from our current work, as their reactivation is occurring during the extinction process in the previously conditioned context, while we are reactivating chronically in the animal’s home cage over the course of a longer time period. It may be necessary that the memory is first reactivated, and thus, more liable to re-contextualization, in the original context compared to an unrelated homecage environment where there are presumably no related cues present. Importantly, this previous work tests the attenuation of fear shortly after an extinction process, while we are not traditionally extinguishing the context with aid of the memory reactivation. Finally, we are testing remote recall (3 months post-conditioning), while they are testing at a shorter time interval (28 days). In line with these ideas, future work may seek to tease out the mechanistic differences between recent and remote memory extinction both in terms of natural memory recall and chronically manipulated memory-bearing cells.

Reviewer #2 (Public Review):

Summary:

Jellinger, Suthard, et al. investigated the transcriptome of positive and negative valence engram cells in the ventral hippocampus, revealing anti- and pro-inflammatory signatures of these respective valences. The authors further reactivated the negative valence engram ensembles to assay the effects of chronic negative memory reactivation in young and old mice. This chronic re-activation resulted in differences in aspects of working memory, and fear memory, and caused morphological changes in glia. Such reactivation-associated changes are putatively linked to GABA changes and behavioral rumination.

Strengths:

Much of the content of this manuscript is of benefit to the community, such as the discovery of differential engram transcriptomes dependent on memory valence. The chronic activation of neurons, and the resultant effects on glial cells and behavior, also provide the community with important data. Laudable points of this manuscript include the comprehensiveness of behavioral experiments, as well as the cross-disciplinary approach.

Weaknesses:

There are several key claims made that are unsubstantiated by the data, particularly regarding the anthropomorphic framing of "rumination" on a mouse model and the role of GABA. The conclusions and inferences in these areas need to be carefully considered.

(1) There are many issues regarding the arguments for the behavioural data's human translation as "rumination." There is no definition of rumination provided in the manuscript, nor how rumination is similar/different to intrusive thoughts (which are psychologically distinct but used relatively interchangeably in the manuscript), nor how rumination could be modelled in the rodent. The authors mention that they are attempting to model rumination behaviours by chronically reactivating the negative engram ("To understand if our experimental model of negative rumination..."), but this occurs almost at the very end of the results section, and no concrete evidence from the literature is provided to attempt to link the behavioural results (decreased working memory, increased fear extinction times) to rumination-like behaviours. The arguments in the final paragraph of the Discussion section about human rumination appear to be unrelated to the data presented in the manuscript and contain some uncited statements. Finally, the rumination claims seem to be based largely upon a single data figure that needs to be further developed (Figure 6, see also point 2 below).

(2) The staining and analysis in Figure 6 are challenging to interpret, and require more evidence to substantiate the conclusions of these results. The histological images are zoomed out, and at this resolution, it appears that only the pyramidal cell layer is being stained. A GABA stain should also label the many sparsely spaced inhibitory interneurons existing across all hippocampal layers, yet this is not apparent here. Moreover, both example images in the treatment group appear to have lower overall fluorescence intensity in both DAPI and GABA. The analysis is also unclear: the authors mention "ROIs" used to measure normalized fluorescence intensity but do not specify what the ROI encapsulates. Presumably, the authors have segmented each DAPI-positive cell body and assessed fluorescence however, this is not explicated nor demonstrated, making the results difficult to interpret.

Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work.

(3) A smaller point, but more specific detail is needed for how genes were selected for GSEA analysis. As GSEA relies on genes to be specified a priori, to avoid a circular analysis, these genes need to be selected in a blind/unbiased manner to avoid biasing downstream results and conclusions. It's likely the authors have done this, but explicitly noting how genes were selected is an important context for this analysis.

As mentioned in our Methods section, gene sets were selected based on pre-existing biology and understanding of genes canonically involved in “neurodegeneration” such as those related to apoptotic pathways and neuroinflammation or “neuroprotection” such as brain-derived neurotrophic factor, to name a few. A limitation of this method is that we must avoid making strong claims about the actual function of these up- or down-regulated genes without performing proper knock-in or knock-out studies, but we hope that this provides an unbiased inventory for future experiments to perform causal manipulations.

Reviewer #3 (Public Review):

Summary:

The authors note that negative ruminations can lead to pathological brain states and mood/anxiety dysregulation. They test this idea by using mouse engram-tagging technology to label dentate gyrus ensembles activated during a negative experience (fear conditioning). They show that chronic chemogenetic activation of these ensembles leads to behavioral (increased anxiety, increased fear generalization, reduced fear extinction) and neural (increases in neuroinflammation, microglia, and astrocytes).

Strengths:

The question the authors ask here is an intriguing one, and the engram activation approach is a powerful way to address the question. Examination of a wide range of neural and behavioral dependent measures is also a strength.

Weaknesses:

The major weakness is that the authors have found a range of changes that are correlates of chronic negative engram reactivation. However, they do not manipulate these outcomes to test whether microglia, astrocytes, or neuroinflammation are causally linked to the dysregulated behaviors.

Recommendations For The Authors:

Reviewer #1 (Recommendations For The Authors):

- Figure 2c should include Month0, the BW before the start of the manipulation.

Regrettably, we do not have access to the Month 0 body weights at this time as this project changed hands over the course of the past year or so. This is an inherent limitation that we missed during analysis and we pose this as a limitation in the Results section after describing this finding. Therefore, it is possible that over the first month of stimulation (Month 0-1), there may have been a drop in body weight that rebounded by the first measurement at Month 1 that continued to increase normally through Months 2-3, as shown in our Figure 1. Thank you for this note.

- Figure 6a looks confusing - the background signal in the green channel is very different between control and experimental groups. Were representative images taken with different microscope settings?

The representative images were taken with the same microscope power settings, but were adjusted in brightness/contrast within FIJI for clarity in the Figure – we apologize that this was misleading in any way and thank the reviewer for their feedback. Further, based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work.

- Typo mChe;try

This typo was fixed

- "During this contextual... mice in the 6- and 14- month groups..." Isn't it 3- and 11- month respectively at the time of fear conditioning? Throughout the manuscript, this point was written very confusingly.

Yes, we thank the reviewer for pointing this out. It has been corrected to 3- and 11-month old mice at the timing of fear conditioning and clarified throughout the manuscript where applicable.

- "GABAergic eYFP fluorescence" Where does the eYFP come from? The methods state that GABA quantification is based on IHC staining.

Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this

E/I imbalance in future work. We discuss this E/I balance not being directly assessed in the Limitations & Future Directions section of our Discussion, noting the importance of detailed quantification of both excitatory and inhibitory markers within the hippocampus.

Reviewer #2 (Recommendations For The Authors):

(1) There is a full methods section ("Analysis of RNA-seq data") that mostly describes RNA-seq analysis that seemingly does not appear in the paper. This section should be reviewed.

We have included this portion of the methods that explain the previous workflow from Shpokayte et al., 2022 where this dataset was generated and this has been noted in the “Analysis of RNA-seq data” section of the methods.

(2) Figure 6: GABA staining should be more critically analyzed, as discussed above, and validated with another GABA antibody for rigor. From the representative images provided in Figure 6, it looks possibly as though the hM3Dq images were simply not fully in the focal plane when being imaged or were over-washed, as DAPI staining also appears to be lower in these images.

Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work. Specifically, it will be necessary to rigorously investigate both excitatory and inhibitory markers within this region to ensure these claims are substantiated. Thank you for this suggestion.

(3) The first claim that human GABAergic interneurons cause rumination is uncited. (Page 19, first sentence beginning with: "Evidence from human studies suggests...").

Based on the collective discussion from all reviewers on the completeness of our GABA quantification and its implications, we have decided to remove this figure and perform more substantive analysis of this E/I imbalance in future work. Apologies for the lack of citation in-text, the proper citation for this finding is Schmitz et al, 2017.

(4) Gene names throughout the manuscript and figure are written in the wrong format for mice (eg: Page 13, second line: SPP1, TTR, and C1QB1 instead of Spp1, Ttr, C1qb1).

This was corrected throughout the manuscript.

(5) Tense on Page 15 third sentence of the second paragraph: "...spatial working memory was assessed...".

This was corrected throughout the manuscript.

(6) Supplemental Figure 1 would benefit from normalization of the NeuN+ cell counts. The inclusion of an excitatory and inhibitory neuron marker in this figure might benefit the argument that there is a change in the excitation/inhibition of the hippocampus - as the numbers of excitatory neurons outweigh the numbers of inhibitory neurons that would be assayed here.

In an effort to normalize the NeuN+ cell counts, for each of our ROIs (6-8 single tiles for each brain region (DG, vCA1, vSub) x 3-5 coronal slices = ~18 single tiles per mouse x 3-4 mice) we captured a 300 x 300 micrometer, single-tile z-stack at 20x magnification. These ROIs were matched for dimensions and brain regions across all groups for each hippocampal subregion quantified. We initially proposed to normalize these NeuN counts over DAPI, but because DAPI includes all nuclei (microglia, oligodendrocytes, astrocytes and neurons), we weren’t sure this was the most optimal tool. We do agree that further quantification of excitatory and inhibitory cell markers would be vital to more concrete interpretation of our findings and we have added this to our Limitations & Future Work section of the Discussion.

Reviewer #3 (Recommendations For The Authors):

(1) The DOX tagging window lacks temporal precision. I suggest the authors note this as a limitation.

We thank the reviewer for noting this, and we have added this limitation to the Methods section with the context of the 24-48 hour DOX window being longer than other methods like TRAP.

(2) Is there a homeostatic response to chronic engram stimulation? That is, is DCZ as effective in increasing neuronal excitability on day 90 as it is on day 1. This could be addressed with electrophysiology, or with IEG induction. Alternatively, the authors could refer to previous literature-- for example, Xia et al (2017) eLife-- that examined whether there was any blunting of the effects of DREADD ligands after sustained delivery via drinking water. There, of course, may be other papers as well.

As noted by the reviewer, it is important to determine if DCZ maintains its effects on neuronal excitability throughout the 3 month administration period. To address this, previous work has shown that CNO administration in drinking water over one month consistently inhibited hM4Di+ neurons without altering baseline neuronal excitability as measured by firing rate and potassium currents (Xia et al, 2017). Although this is only for one month, it is administered via the same oral route as our DCZ protocol and suggests that at least for that amount of time we are likely producing consistent effects. In our reply above to Reviewer #1’s comment, we also note that even if DCZ is only having an effect for one month, rather than 3 months, we are still observing enduring changes that resulted from this short-term disturbance.

(3) Please double check there is no group effect on weight in 6-month-old mice in Figure 2C.

Two-way RM ANOVA showed no main effect of Group within the 6-month-old control and hM3Dq groups.

Group: F(1,17) = 1.361, p=0.2594.

(4) The shock intensity is much higher than is typical for fear conditioning studies in mice. Why was this the case?

Yes, we do agree that this shock intensity is on the higher side of typical paradigms in mice, however, our lab has utilized 0.75mA to 1.5mA intensity foot shocks for contextual fear conditioning in the past (Suthard & Senne et al, 2023; 2024; Dorst & Senne et al, 2023; Grella et al., 2022; Finkelstein et al., 2022) and we maintained this protocol for internal consistency. However, it would be interesting to systematically investigate how differing intensities of foot shock, subsequent tagging of this ensemble and reactivation would uniquely impact behavioral state acutely and chronically in mice.

(5) Remote freezing is very low. The authors should comment on this-- perhaps repeated testing has led to some extinction?

A reviewer above suggested a similar phenomenon may be occuring, specifically fear attenuation as a result of chronic stimulation. They referenced previous work from Khalaf et al. 2018, where they reactivated a recall-induced ensemble, while we reactivated an ensemble tagged during encoding. We expand upon this work in light of our findings within the Limitations & Future Work section of our Discussion. However, we do appreciate the lower levels of freezing observed in remote recall and sought out other literature to understand the typical range of remote freezing levels. One thing that we note is that our remote recall is occurring 3 months after conditioning, which is much longer than typical 14-28 day protocols. However, we find that freezing levels at remote timepoints from 21-45 days results in contextual freezing levels of between 20-50% approximately (Kol et al., 2020), as well as 40-75% approximately in a variety of 28 day remote recall experiments (Lee et al., 2023). This information, together with our current experimental protocol demonstrates a wide range of remote freezing levels that may depend heavily on the foot shock intensity, duration of days after conditioning, and animal variability.

(6) "mice display increased freezing with age": please add a reference.

Apologies, we missed the citation for that claim and it has been added in-text and in the references list (Shoji & Miyakawa, 2019).

(7) Related to the low freezing levels for remote memory, why is generalization minimal? Many studies have shown that there is a time-dependent emergence of generalized fear, yet here this is not seen. Is it linked to extinction (as above)? Or genetic background?

Previous work has shown that rats receiving multiple foot shocks during conditioning displayed a time-dependent generalization of context memory, while those receiving less shocks did not (Poulos et al., 2016), as the reviewer noted in their comment. In our current study, we observe low levels of generalization in all of our groups compared to freezing levels displayed in the conditioned context at the remote timepoint, in opposition to this time-dependent enhancement of generalization. It is possible that the genetic background of our C57BL/6J mice compared to the Long-Evans rat strain in this previous work accounts for some of this difference. In addition, it is possible that the longer duration of time (3 months) compared to their remote timepoint (28 days) resulted in time-dependent decrease in generalization that decreases with greater durations of time from original conditioning. As noted above, it is indeed plausible that the reactivation of a contextual fear ensemble over time is attenuating freezing levels for both the original and similar contexts (Khalaf et al, 2018). We discuss the differences in our study and this 2018 work more comprehensively above.

(8) Morphological phenotypes of astrocytes/microglia. Would be great to do some transcriptomic profiling of microglia/astrocytes to couple with the morphological characterization (but appreciate this is beyond the scope of current work).

We thank the reviewer this suggestion, we agree that would be an incredibly informative future experiment and have added this to our Limitations & Future Experiments section of the Discussion.

(9) The authors could consider including a limitations section in their discussion which discusses potential future directions for this work:

- causal experiments.

- E/I balance is not assessed directly (interestingly, in this regard, expanded engrams are linked to increased generalization [e.g., Ramsaran et al 2023]).

Thank you for this suggestion, we have added a Limitations & Future Directions section to our Discussion and have expanded upon these suggested points.

(10) For Figure 10, consider adding an experimental design/timeline.

We are making the assumption that the reviewer meant Figure 1 instead of Figure 10 here, but note that there is a description of the viral expression duration (D0-D10), followed by an off Dox period of 48 hours (D10-D12), with subsequent engram tagging of a negative (foot shock) or positive (male-to-female exposure) on D12. In our experiments (Shpokayte et al., 2022), Dox was administered for 24 hours (D12-D13), which was followed by sacrificing the animal for cell suspension and sequencing of the positive and negative engram populations. This figure also shows the viral strategy for the Tet-tag system (Figure 1A), as well as representative viral expression in vHPC (Figure 1B). We are happy to add additional experimental design/timeline information to this figure that would be helpful to the reviewer.

Reviewer #2 (Public Review):

Summary:

The paper sought to determine the number of myosin 10 molecules per cell and localized to filopodia, where they are known to be involved in formation, transport within, and dynamics of these important actin-based protrusions. The authors used a novel method to determine the number of molecules per cell. First, they expressed HALO tagged Myo10 in U20S cells and generated cell lysates of a certain number of cells and detected Myo10 after SDS-PAGE, with fluorescence and a stained free method. They used a purified HALO tagged standard protein to generate a standard curve which allowed for determining Myo10 concentration in cell lysates and thus an estimate of the number of Myo10 molecules per cell. They also examined the fluorescence intensity in fixed cell images to determine the average fluorescence intensity per Myo10 molecule, which allowed the number of Myo10 molecules per region of the cell to be determined. They found a relatively small fraction of Myo10 (6%) localizes to filopodia. There are hundreds of Myo10 in each filopodia, which suggests some filopodia have more Myo10 than actin binding sites. Thus, there may be crowding of Myo10 at the tips, which could impact transport, the morphology at the tips, and dynamics of the protrusions themselves. Overall, the study forms the basis for a novel technique to estimate the number of molecules per cell and their localization to actin-based structures. The implications are broad also for being able to understand the role of myosins in actin protrusions, which is important for cancer metastasis and wound healing.

Strengths:

The paper addresses an important fundamental biological question about how many molecular motors are localized to a specific cellular compartment and how that may relate to other aspects of the compartment such as the actin cytoskeleton and the membrane. The paper demonstrates a method of estimating the number of myosin molecules per cell using the fluorescently labeled HALO tag and SDS-PAGE analysis. There are several important conclusions from this work in that it estimates the number of Myo10 molecules localized to different regions of the filopodia and the minimum number required for filopodia formation. The authors also establish a correlation between number of Myo10 molecules filopodia localized and the number of filopodia in the cell. There is only a small % of Myo10 that tip localized relative to the total amount in the cell, suggesting Myo10 have to be activated to enter the filopodia compartment. The localization of Myo10 is log-normal, which suggests a clustering of Myo10 is a feature of this motor.

One of the main critiques of the manuscript was that the results were derived from experiments with overexpressed Myo10 and therefore are hard to extrapolate to physiological conditions. The authors counter this critique with the argument that their results provide insight into a system in which Myo10 is a limiting factor for controlling filopodia formation. They demonstrate that U20S cells do not express detectable levels of Myo10 (supplementary Figure 1E) and thus introducing Myo10 expression demonstrates how triggering Myo10 expression impacts filopodia. An example is given how melanoma cells often heavily upregulation Myo10.

In addition, the revised manuscript addresses the concerns about the method to quantitate the number of Myo10 molecules per cell and therefore puncta in the cell. The authors have now made a good faith effort to correct for incomplete labeling of the HALO tag (Figure 2A-C, supplementary Figure 2D-E). The authors also address the concerns about variability in transfection efficiency (Figure 1D-E).

A very interesting addition to the revised manuscript was the quantitation of the number of Myo10 molecules present during an initiation event when a newly formed filopodia just starts to elongate from the plasma membrane. They conclude that 100s of Myo10 molecules are present during an initiation event. They also examined other live cell imaging events in which growth occurs from a stable filopodia tip and correlated with elongation rates.

Weaknesses:

The authors acknowledge that a limitation of the study is that all of the experiments were performed with overexpressed Myo10. They address this limitation in the discussion but also provide important comparisons for how their work relates to physiological conditions, such as melanoma cells that only express large amounts of Myo10 when they are metastatic. Also, the speculation about how fascin can outcompete Myo10 should include a mechanism for how the physiological levels of fascin can complete with the overabundance of Myo10 (page 10, lines 401-408).

Author response:

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

eLife assessment

This valuable study reports on the packing of molecules in cellular compartments, such as actin-based protrusions. The study provides solid evidence for parameters that enable the building of a biophysical model of filopodia, which is required to gain a complete understanding of these important actin-based structures. Some areas of the manuscript require further clarification.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The manuscript proposes an alternative method by SDS-PAGE calibration of Halo-Myo10 signals to quantify myosin molecules at specific subcellular locations, in this specific case filopodia, in epifluorescence datasets compared to the more laborious and troublesome single molecule approaches. Based on these preliminary estimates, the authors developed further their analysis and discussed different scenarios regarding myosin 10 working models to explain intracellular diffusion and targeting to filopodia.

Strengths:

Overall, the paper is elegantly written and the data analysis is appropriately presented.

Weaknesses:

While the methodology is intriguing in its descriptive potential and could be the beginning of an interesting story, a good portion of the paper is dedicated to the discussion of hypothetical working mechanisms to explain myosin diffusion, localization, and decoration of filopodial actin that is not accompanied by the mandatory gain/loss of function studies required to sustain these claims.

To be fair, the detailed mechanisms that we raise related to diffusion, localization, and decoration are based on extensive work by others. Many prior papers use domain deletions of Myo10 and fall in the category of gain/loss-of-function studies. It is true that we have not repeated those extensive studies, but it seems appropriate to connect with and cite their work where appropriate.

Reviewer #2 (Public Review):

Summary:

The paper sought to determine the number of myosin 10 molecules per cell and localized to filopodia, where they are known to be involved in formation, transport within, and dynamics of these important actin-based protrusions. The authors used a novel method to determine the number of molecules per cell. First, they expressed HALO tagged Myo10 in U20S cells and generated cell lysates of a certain number of cells and detected Myo10 after SDS-PAGE, with fluorescence and a stained free method. They used a purified HALO tagged standard protein to generate a standard curve which allowed for determining Myo10 concentration in cell lysates and thus an estimate of the number of Myo10 molecules per cell. They also examined the fluorescence intensity in fixed cell images to determine the average fluorescence intensity per Myo10 molecule, which allowed the number of Myo10 molecules per region of the cell to be determined. They found a relatively small fraction of Myo10 (6%) localizes to filopodia. There are hundreds of Myo10 in each filopodia, which suggests some filopodia have more Myo10 than actin binding sites. Thus, there may be crowding of Myo10 at the tips, which could impact transport, the morphology at the tips, and dynamics of the protrusions themselves. Overall, the study forms the basis for a novel technique to estimate the number of molecules per cell and their localization to actin-based structures. The implications are broad also for being able to understand the role of myosins in actin protrusions, which is important for cancer metastasis and wound healing.

Strengths:

The paper addresses an important fundamental biological question about how many molecular motors are localized to a specific cellular compartment and how that may relate to other aspects of the compartment such as the actin cytoskeleton and the membrane. The paper demonstrates a method of estimating the number of myosin molecules per cell using the fluorescently labeled HALO tag and SDS-PAGE analysis. There are several important conclusions from this work in that it estimates the number of Myo10 molecules localized to different regions of the filopodia and the minimum number required for filopodia formation. The authors also establish a correlation between number of Myo10 molecules filopodia localized and the number of filopodia in the cell. There is only a small % of Myo10 that tip localized relative to the total amount in the cell, suggesting Myo10 have to be activated to enter the filopodia compartment. The localization of Myo10 is log-normal, which suggest a clustering of Myo10 is a feature of this motor.

Weaknesses:

One main critique of this work is that the Myo10 was overexpressed. Thus, the amount in the cell body compared to the filopodia is difficult to compare to physiological conditions. The amount in the filopodia was relatively small - 100s of molecules per filopodia so this result is still interesting regardless of the overexpression. However, the overexpression should be addressed in the limitations.

This is a reasonable perspective and we now note this caveat in the Limitations section so that readers will take note. Our goal here was to understand a system in which Myo10 is the limiting reagent for filopodia, rather than a native system that expresses high Myo10 on its own. Because U2OS cells do not express detectable levels of Myo10 (see below), the natural perturbation here is overexpressing Myo10 to stimulate filopodial growth.

The authors have not addressed the potential for variability in transfection efficiency. The authors could examine the average fluorescence intensity per cell and if similar this may address this concern.

Indeed, cells are heterogenous and will naturally express different levels of Myo10 not only due to transfection efficiency, but also due to their state (cell cycle stage, motile behavior, and more). In fact, we measure the transfection efficiency of each bioreplicate and account for it in our calibration procedure. We also measure the fluorescence intensity per cell, which lets us calculate the total Myo10s per cell and the cell-to-cell variability. These Myo10 distributions across cells are shown in Fig. 1D-E.

We note here an error that we made in applying this transfection efficiency correction in the first submission. When we obtain the total Myo10 molecules by SDS-PAGE, we should divide by the total number of transfected cells. However, due to an operator precedence error, the transfection efficiency appeared in the numerator rather than the denominator. We have now corrected this error, which has the effect of increasing the number of molecules in all of our measurements. The effect of this correction has strengthened one of the paper’s main conclusions, that Myo10 is frequently overloaded at filopodial tips.

The SDS PAGE method of estimating the number of molecules is quite interesting. I really like this idea. However, I feel there are a few more things to consider. The fraction of HALO tag standard and Myo10 labeled with the HALO tagged ligand is not determined directly. It is suggested that since excess HALO tagged ligand was added we can assume nearly 100% labeling. If the HALO tag standard protein is purified it should be feasible to determine the fraction of HALO tagged standard that is labeled by examining the absorbance of the protein at 280 and fluorophore at its appropriate wavelength.

This is a fair point raised by the reviewer, and we have now measured a labeling efficiency of 90% in Supplementary Figure 2A-C. We have adjusted all values according to this labeling efficiency.

The fraction of HALO tagged Myo10 labeled may be more challenging to determine, since it is in a cell lysate, but there may be some potential approaches (e.g. mass spec, HPLC).

As noted, this value is considerably more challenging. Instead, we determined conditions under which labeling in cells is saturated. We have now stained with a concentration range for both fixed and live cell samples. Saturation occurs with ~0.5 μM HaloTag ligand-TMR in fixed/permeabilized cells and in live cells (Supplementary Figure 2D-E). This comparison of live cells vs. permeabilized cells allows us to say that the intact plasma membrane is not limiting labeling under these conditions.

In Figure 1B, the stain free gel bands look relatively clean. The Myo10 is from cell lysates so it is surprising that there are not more bands. I am not surprised that the bands in the TMR fluorescence gel are clean, and I agree the fluorescence is the best way to quantitate.

Figure 1B shows the focused view at high MW, and there is not much above Myo10. The full gel lanes shown in Supp. Fig. 1C show the expected number of bands from a cell lysate.

In Figure 3C, the number of Myo10 molecules needed to initiate a filopodium was estimated. I wonder if the authors could have looked at live cell movies to determine that these events started with a puncta of Myo10 at the edge of the cell, and then went on to form a filopodia that elongated from the cell. How was the number of Myo10 molecules that were involved in the initiation determined? Please clarify the assumptions in making this conclusion.

We thank the reviewer (and the other reviewers) for this excellent suggestion. We have now carried out these live cell experiments. These experiments were quite challenging, because we needed to collect snapshots of ~50 cells to measure the mean fluorescence intensity of transfected cells and then acquire movies of several cells for analysis. The U2OS cells were also highly temperature-sensitive and would retract their filopodia without objective heating.

We have now analyzed filopodial initiation events and measured considerably more Myo10 at the first signs of accumulation– in the 100s of molecules. The dimmer spots that we measured in the first draft were likely unrelated to filopodial initiation, and we have corrected the discussion on this point.

We now also track further growth from a stable filopodial tip (the phased-elongation mechanism from Ikebe and coworkers) and find approximately 500 molecules bud off in those events. We also track filopodial elongation rates as a function of Myo10 numbers. We have added additional live cell imaging sections that include these results.

It is stated in the discussion that the amount of Myo10 in the filopodia exceeds the number of actin binding sites. However, since Myo10 contains membrane binding motifs and has been shown to interact with the membrane it should be pointed that the excess Myo10 at the tips may be interacting with the membrane and not actin, which may prevent traffic jams.

This is also an excellent point to consider, and we have expanded the relevant discussion along these lines. We agree that the Myo10 at the filopodial tip is likely membrane-bound. We now estimate the 2D membrane area occupied by Myo10, and find that it reaches nearly full packing in many cases (under a number of assumptions that we spell out more fully in the manuscript).

Reviewer #3 (Public Review):

Summary:

The unconventional myosin Myo10 (aka myosin X) is essential for filopodia formation in a number of mammalian cells. There is a good deal of interest in its role in filopodia formation and function. The manuscript describes a careful, quantitative analysis of Myo10 molecules in U2OS cells, a widely used model for studying filopodia, how many are present in the cytosol versus filopodia and the distribution of filopodia and molecules along the cell edge. Rigorous quantification of Myo10 protein amounts in a cell and cellular compartment are critical for ultimately deciphering the cellular mechanism of Myo10 action as well as understand the molecular composition of a Myo10-generated filopodium.

Consistent with what is seen in images of Myo10 localization in many papers, the vast majority of Myo10 is in the cell body with only a small percentage (appr 5%) present in filopodia puncta. Interestingly, Myo10 is not uniformly distributed along the cell edge, but rather it is unevenly localized along the cell edge with one region preferentially extending filopodia, presumably via localized activation of Myo10 motors. Calculation of total molecules present in puncta based on measurement of puncta size and measured Halo-Myo10 signal intensity shows that the concentration of motor present can vary from 3 - 225 uM. Based on an estimation of available actin binding sites, it is possible that Myo10 can be present in excess over these binding sites.

Strengths:

The work represents an important first step towards defining the molecular stoichiometry of filopodial tip proteins. The observed range of Myo10 molecules at the tip suggests that it can accommodate a fairly wide range of Myo10 motors. There is great value in studies such as this and the approach taken by the authors gives one good confidence that the numbers obtained are in the right range.

Weaknesses:

One caveat (see below) is that these numbers are obtained for overexpressing cells and the relevance to native levels of Myo10 in a cell is unclear.

A similar concern was raised by Reviewer 2; please see above.

An interesting aspect of the work is quantification of the fraction of Myo10 molecules in the cytosol versus in filopodia tips showing that the vast majority of motors are inactive in the cytosol, as is seen in images of cells. This has implications for thinking about how cells maintain this large population in the off-state and what is the mechanism of motor activation. One question raised by this work is the distinction between cytosolic Myo10 and the population found at the ‘cell edge’ and the filopodia tip. The cortical population of Myo10 is partially activated, so to speak, as it is targeted to the cortex/membrane and presumably ready to go. Providing quantification of this population of motors, that one might think of as being in a waiting room, could provide additional insight into a potential step-by-step pathway where recruitment or binding to the cortical region/plasma membrane is not by itself sufficient for activation.

As mentioned in our response to Reviewer 2, we have now carried out quantitation in live cells to capture Myo10 transitions from cell body into filopodial movement. We attempted to identify this membrane-bound population of motors in our new live cell experiments but were unable to make convincing measurements. Notably, we see no noticeable enrichment of Myo10 at the cortex relative to the cytosol. Although we believe there is a membrane-bound waiting room (akin to the 3D-2D-1D mechanism of Molloy and Peckham), we suspect that the 2D population is diffusing too rapidly to be detected under our imaging conditions.

Specific comments:

(1) It is not obvious whether the analysis of numbers of Myo10 molecules in a cell that is ectopically overexpressing Myo10 is relevant for wild type cells. It would appear to be a significant excess based on the total protein stained blot shown in Fig S1E where a prominent band the size of tagged Myo10 seen in the transfected sample is almost absent in the WT control lane.

Even “wildtype” cells vary considerably in their Myo10 expression levels. For example, melanoma cells often heavily upregulate Myo10, while these U2OS cells produce nearly none (Supplementary Figure 1E). Thus, there is no single, widely acceptable target for Myo10 expression in wildtype cells.

Please note that the new Supplementary Figure 1E is a Myo10 Western blot, not total protein staining as before.

Ideally, and ultimately an important approach, would be to work with a cell line expressing endogenously tagged Myo10 via genome engineering. This can be complicated in transformed cells that often have chromosomal duplications.

Indeed, we chose U2OS cells for this work because they do not express detectable levels of Myo10, and thus we can avoid all of these complications. Here we can examine how Myo10 levels control filopodial production through ectopic expression.

However, even though there is an excess of Myo10 it would appear that activation is still under some type of control as the cytosolic pool is quite large and its localization to the cell edge is not uniform. But it is difficult to gauge whether the number of molecules in the filopodium is the same as would be seen in untransfected cells. Myo10 can readily walk up a filopodium and if excess numbers of this motor are activated they would accumulate in the tip in large numbers, possibly creating a bulge as and indeed it does appear that some tips are unusually large. Then how would that relate to the normal condition?

As noted above, the normal condition depends on the cellular system. However, endogenous Myo10 also accumulates in bulges at filopodial tips, so this is not a phenotype unique to Myo10 overexpression. For example, the images from Figure 1 of the Berg and Cheney (2002) citation show bulges from endogenous Myo10 in endothelial cells.

(2) Measurements of the localization of Myo10 focuses in large part on ‘Myo10 punctae’. While it seems reasonable to presume that these are filopodia tips, the authors should provide readers with a clear definition of a puncta. Is it only filopodia tips, which seems to be the case? Does it include initiation sites at the cell membrane that often appear as punctae?

We define puncta as any clusters/spots of Myo10 signal detected by segmentation, not limited to any location within the surface-attached filopodia. We exclude puncta that appear in the cell interior (~5 of which appear in Fig. 1A). These are likely dorsal filopodia, but there are few of these compared to the surface attached filopodia of U2OS cells. In Figure 2, “puncta” includes all Myo10 clusters along the filopodia shaft, though a majority happen to be tip-localized (please see Supplementary Figure 4B). We have edited the main text for clarification.

Along those lines, the position of dim punctae along the length of a filopodium is measured (Fig 3D). The findings suggest that a given filopodium can have more than one puncta which seems at odds if a puncta is a filopodia tip. How frequently is a filopodium with two puncta seen? It would be helpful if the authors provided an example image showing the dim puncta that are not present at the tip.

We have now provided an example image of dim puncta along filopodia in Supplementary Figure 4C.

(3) The concentration of actin available to Myo10 is calculated based on the deduction from Nagy et al (2010) that only 4/13 of the actin monomers in a helical turn are accessible to the Myo10 motor (discussion on pg 9; Fig S4). Subsequent work (Ropars et al, 2016) has shown that the heads of the antiparallel Myo10 dimer are flattened, but the neck is rather flexible, meaning that the motor can a variable reach (36 - 52 nm). Wouldn’t this mean that more actin could be accessible to the Myo10 motor than is calculated here?

Although we see why the reviewer might believe otherwise, the 4/13 fraction of accessible actin holds. This fraction is obtained from consideration of the fascin-actin bundle structure alone, independent of the reach of any particular myosin motor. Every repeating layer of 13 actin subunits (or 36 nm) has 4 accessible myosin binding-sites. The remaining 9 sites are rejected because a single myosin motor domain will have a steric clash with a neighboring actin filament in the bundle. A myosin with an exceptionally long reach might reach the next 13 subunit layer, but that layer also has only 4 binding sites. Thus, we can calculate the number of binding sites per unit length along the filopodium. This number would hold for a dimeric myosin with any reach, including myosin-5 or myosin-2.

(4) Quantification of numbers of Myo10 molecules in filopodial puncta (Fig 3C) leads the authors to conclude that ‘only ten or fewer Myo10 molecules are necessary for filopodia initiation’ (pg 7, top). While this is a reasonable based on the assumption that the formation of a puncta ultimately results from an initiation event, little is known about initiation events and without direct observation of coalescence of Myo10 at the cell edge that leads to formation of a filopodium, this seems rather speculative.

As noted above, we have now performed the necessary live cell imaging of filopodial nucleation events and have updated our conclusions accordingly.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

I have made a series of comments that might help the authors improve their manuscript:

- A full calibration of the methodology would require testing a wider range of protein amounts, to exhaustively detect the dynamic range of the technique. The authors acknowledge in the discussion that “Furthermore, our estimates of molecules are predicated on the calibration curve of the Halo Standard Protein on the SDS-PAGE gels, which is likely the highest source of error on our molecule counts”. A good way of convincing a nasty reviewer is to provide a calibration with more than 3 reference points. At least this will help exclude from the analysis cells where Myo10 estimates are not in the linear regime of detection.

We completely agree with the reviewer’s suggestion to build a robust calibration curve. The SDS gel shown in Figure 1C originally contained 4 reference points, but the highest HaloTag standard protein point oversaturated the detector at the set exposure in the TMR channel and was omitted. We have now re-run the SDS gel to include a HaloTag standard protein curve comprising 5 points, alongside all three bioreplicates from the fixed cell experiments and all three bioreplicates from the live cell experiments (updated in Figure 1B-C). We had saved frozen lysates from the original fixed cell work, so we were able to reanalyze our data with the new set of standards. The Myo10 quantities are consistent, but with much tighter CIs from the standard curve.

- As already said this methodology is intriguing, however, a correlative validation with a conventional SMLM approach to address the bona-fide of the method would be ideal.

Unfortunately, single molecule approaches for validation are impractical for us. Due to the relatively high magnification of our TIRF microscope and the large spread area of the U2OS cells, single cells typically extend beyond the field of view. We acknowledge the benefits of SMLM quantitative techniques and other approaches cited in the introduction section. To avoid use of special tools/instruments, we offer our methodology, based off Pollard group’s quantitative Western blotting of GFP, as a simpler alternative accessible to anyone.

- TMR is a small ligand likely interacting also with Halo in its denatured state. However, to clear any doubts a parallel Native-PAGE investigation should be included, or if existing a specific reference should be provided.

Perhaps there is a misunderstanding here. One of the key advantages of the HaloTag labeling system is that the engineered dehalogenase is covalently modified by the ligand (the TMR-ligand is a suicide substrate). This means that the TMR remains bound even under denaturing conditions, which allows its detection in SDS-PAGE. Native gels are unnecessary here.

- Moreover, SDS-PAGE is run at alkaline pH, have the authors considered these points when designing the methodology? Fluorescence images were taken in PBS, which has a different pH. Could the authors, or the literature, exclude these aspects as potential pitfalls in the methodology? Also temperature is affecting fluorescence emission, but it is easier to control with certain tolerance in the room-temperature regime.

Our method does not compare fluorescence values that cross the experimental systems (SDS-PAGE vs. microscopy). Cellular proteins and HaloTag protein standards are compared in a single setting of SDS-PAGE to obtain the average number of Myo10s per transfected cell. Likewise, all measurements on intact (live or fixed) cells are conducted in that single setting to obtain average fluorescence per cell. Thus, there is no issue with the different buffers or temperatures affecting fluorescence emission.

- The authors should test their approach also with truncation variants of Myosin10 (for instance lacking the PH or motor domain). This is a classical approach that might prove the potential of the technique when altering the capacity of the protein to interact with a main binding partner. Also, treatments that induced filopodia formation might prove useful (i.e., hypotonic media induce filopodia formation in some fibroblast cell lines in our hands).

The reviewer raises interesting suggestions that we aim to address in future experiments, but truncation variants and environmental perturbations are beyond the focus of the current manuscript. Here, we report on the otherwise unperturbed state when we add exogenous full-length Myo10 to the U2OS cells. But indeed, experiments with Myo10 domain truncations, PI3K and PTEN inhibition, and cargo protein / activating cofactor knock-downs (among others) are on our drawing board.

- Most of the mechanisms hypothesized in the discussion are sound and plausible. However, the authors have chosen an experimental model where transient transfection of exogenous Myo10 in U2OS is performed. This approach poses two main and fundamental questions that are not resolved by the data provided:

A) how do different expression levels affect the Myo10 counting?

Our counting procedure does not assume uniform expression across a population of cells– quite the opposite, in fact. We directly measure Myo10 expression levels on a cell-by-cell basis with microscopy, once we know the number of molecules in our total pool (see the Methods for details). As an example of the final output, Figs. 1D and 1E show the total number of Myo10 molecules per cell for fixed and live cells, respectively.

B) how does endogenous and unlabeled Myo10 hamper the bonafide of counts? The authors claimed “U2OS cells express low levels of Myo10, so there is a small population of unlabeled endogenous Myo10 unaddressed by this paper”. As presented, the low levels of endogenous Myo10 sound an arbitrary parameter, and there are no data presented that can limit if not exclude this bias in the analysis. To produce data in a genetically modified cell line with Halo-tag on the endogenous protein will represent a much cleaner system. Alternatively, the authors should look for Myo10 KO cell lines where they can back-transfect their Halo-Tagged Myo10 construct in a more consistent framework, focusing on cells with low-to-mid levels of expression.

We agree, this is an important point to nail down (and is often neglected in the literature). We have now measured the endogenous Myo10 levels in U2OS cells by Western blotting and found that it is undetectable compared to our HaloTagged construct expression. Please see Supp. Fig 1E. Thus, for all intents and purposes, every Myo10 molecule in these experiments came from our expression plasmid. Accordingly, we have removed this caveat from the paper.

Minor points

- Figure 1B. To help the reader SDS-PAGE gels annotations should be clearer already from the figure.

We have updated the annotations for clarity.

- Methods should be organized in sessions. As it stands, it is hard for the reader to look for technical details.

We have expanded and added subsections to the Methods as requested.

- The good practice of indicating the gene and transcript entry numbers and the primer used to amplify and clone into the backbone vectors is getting lost in many papers. I would strongly encourage the authors to add this information to the methods.

We have included the gene entries to the methods and will include a full FASTA file of the coding sequence as supplementary information to avoid any ambiguity here.

The authors write “It is unclear how myosins navigate to the right place at the right time, but our results support an important interplay between Myo10 and the actin network.” It is a bit scholastic to say that Myo10 and actin have an important interplay, they are major binding partners. What is the new knowledge contained in this sentence?

Agreed– we have deleted the sentence in question.

Reviewer #2 (Recommendations For The Authors):

The authors should address all the weaknesses indicated in the public review.

There were a few other places that require clarification.

On page 4, the last paragraph. It is stated that the targeting of Myo10 was reported/proposed based on previous work (ref 31). The next few sentences are not referenced and thus likely refer to ref 31. The authors did not measure the parameters discussed in these sentences, so it is important to clarify that they are referring to previous work and not the current study.

Indeed, the next few sentences still refer to old reference 31, so we have now edited the paragraph for clarity.

On page 7, the reference to Figure 3A indicates that the trend of higher Myo10 correlating with more filopodia. However, the reference to Figure 3B indicates total intracellular Myo10 weakly correlates with more filopodia. However, the x-axis on Figure 3B is filopodia molecules not the intracellular Myo10. Please clarify.

We appreciate the reviewer for catching our mistake. Those plots are now in Fig. 2 and have been edited accordingly.

Reviewer #3 (Recommendations For The Authors):

The Discussion of results at the end of each section is rather brief and could be expanded on a bit more.

Before we were operating under the constraints of an eLife Short Report. We have now expanded the discussion for a full article.

The authors mention that actin filaments at the tips of filopodia could be frayed, citing Medalia et al, 2007 (ref 40). That paper describes an early cryoEM analysis of filopodia from the amoeba Dictyostelium. EM images of mammalian filopodia tips, e.g. Svitkina et al, 2003, JCB, do not show quite the same organization of actin as seen in the Dictyostelium filopodia tips. However, recent work from the Bershadsky lab, Li et al, 2023, presents a few cryoEM images of tips of left-bent filopodia that are tightly adhered to a substrate and there it looks like actin filaments become disorganized in tips, along with membrane bulging. The authors should consider expanding discussion of the filopodia tips to take into account what is known for mammalian filopodia.

We thank the reviewer for bringing these enlightening papers to our attention. We have now included these citations in the discussion.

Fig 1D - The x-axis is a bit odd, it goes from 0 then to 2.5e+06 with no indication of the bin size. Can this be re-labelled or the scale displayed a bit differently?

We have double-checked the axis breaks, which are large because the underlying values are large. We have also provided the bin size as requested for all histograms.

Fig 4A - What is the bin size for the histogram?

As above, we have now updated the figure legends (now in Fig. 3) to include the bin size.

Methods -

- Please provide an accession number for the Myo10 nucleotide sequence used for this work as there are at least two known isoforms.

Thank you for noting this. We are using the full-length, not the headless isoform. We have now updated the Methods accordingly.

- No mention is made of the SDS sample buffer used, was that also added to the sample?

We have now updated the Methods accordingly.

- How are samples boiled at 70 deg C? Do the authors actually mean ‘heated’?

Indeed. We have now corrected “boiled” to “heated.”

- Could the authors please briefly explain the connected component analysis used to identify filopodia?

We have now updated the Methods accordingly.

- The intensity of filopodia was determined by dividing tip intensity by the total bioreplicate sum of intensities then multiplying it by the total pool, if this reviewer understands correctly. It sounds like intensities are being averaged across a whole cell population instead of cell-by-cell. Is that correct? If so, can the authors please provide the underlying rationale for this? If not, then please better describe what was actually done.

We apologize for the confusion. Intensities are being averaged (summed) across a whole cell population, but importantly that step is only used to obtain a scale factor that converts the fluorescence signal at the microscope to the number of molecules. We then use that scale factor for all cells imaged in the bioreplicate, to both 1) find the total Myo10 in that cell, and 2) find the total amount of that Myo10 in any given location within that cell.

To further clarify, each bioreplicate has a known total number of Myo10 molecules associated with the number of cells loaded onto the SDS gel. From the SDS gel, we have an average number of Myo10 molecules per positively transfected cell. If 50 cell images are analyzed, then there is a Myo10 ‘total pool’ of (50 cells) * (average Myo10 molecules/cell). The fluorescence signal intensities in microscopy were summed for all cells within the bioreplicate (50 cells in this example). However, due to variation in expression, not every cell has the same signal intensity when imaged under the same conditions. It would be inaccurate to assume each cell contains the average Myo10 molecules/cell. Therefore, to get the number of molecules within a given Myo10 cell (or punctum), the summed cell (punctum) intensity was divided by the bioreplicate fluorescence signal intensity sum and multiplied by ‘total pool.’

- The authors quantify Myo10 protein amounts by western blotting using Halo tag fluorescence, a method that should provide good accuracy. The results depend on the transfection efficiency and it is rarely the case that it is 100%. The authors state that they use a ‘value correction for positively transfected cells’ (pg 11). It is likely that there was a range of expression levels in the cells, how was a cut-off for classifying a cell as non-expressing determined or set?

As described in the Methods, “microscopy was used to count the percentage of transfected cells from ~105-190 randomly surveyed cells per bioreplicate.” Cells were labeled and located with DAPI. If no TMR signal could be visually detected by microscopy, then the cell was deemed to be non-Myo10 expressing. We did not set a cutoff fluorescence value, as untransfected cells have no detectable signal. Please see Supplementary Figure 1F for examples.

- “In-house Python scripts” are used for image analysis. Will these be made publicly available?

Yes, we will package these up on GitHub.

Author response:

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

Reviewer #1 (Public Review):

Summary:

In this manuscript, Chowdhury and co-workers provide interesting data to support the role of G4-structures in promoting chromatin looping and long-range DNA interactions. The authors achieve this by artificially inserting a G4-containing sequence in an isolated region of the genome using CRISPR-Cas9 and comparing it to a control sequence that does not contain G4 structures. Based on the data provided, the authors can conclude that G4-insertion promotes long-range interactions (measured by Hi-C) and affects gene expression (measured by qPCR) as well as chromatin remodelling (measured by ChIP of specific histone markers).

Whilst the data presented is promising and partially supports the authors' conclusion, this reviewer feels that some key controls are missing to fully support the narrative. Specifically, validation of actual G4-formation in chromatin by ChIP-qPCR (at least) is essential to support the association between G4-formation and looping. Moreover, this study is limited to a genomic location and an individual G4-sequence used, so the findings reported cannot yet be considered to reflect a general mechanism/effect of G4-formation in chromatin looping.

Strengths:

This is the first attempt to connect genomics datasets of G4s and HiC with gene expression. The use of Cas9 to artificially insert a G4 is also very elegant.

Weaknesses:

Lack of controls, especially to validate G4-formation after insertion with Cas9. The work is limited to a single G4-sequence and a single G4-site, which limits the generalisation of the findings.

In the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).

To directly address the second point, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4 ChIP-qPCR binding was significant within the inserted region, and not in the negative control region (Figure S8), consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci.

We next checked the state of chromatin of the G4-array inserted at the 10M locus, or its negative control. Histone marks H3K4Me1, H3K27Ac, H3K27Me3, H3K9me3 and H3K4Me3 were tested at the G4-array, or the negative control locus. Relative increase in the enhancer histone marks was evident, relative to the control sequence. This was largely similar to the 79M locus, supporting an enhancer-like state. Interestingly, here we further noted presence of the H3K27me3 histone mark. The presence of the H3K27Me3 repressor histone mark, along with H3K4Me1/H3K27Ac enhancer histone marks, support a poised enhancer-like status of the inserted G4 region, as has been observed earlier in other studies. Together, although data from the two distinct G4 insertion sites support the enhancer-like state, there are contextual differences likely due to the sequence/chromatin of the sites adjacent to the inserted sequence.

Effect of the 10M G4-insertion on activation of surrounding genes (10 Mb window), and not the G4-mutant insert, was evident for most genes. Consistent with the enhancer-like state of the G4-array insert; in line with the 79M G4-array insert.

These results have been added as the final section in the revised version, data is shown in Figure 7.

Reviewer #2 (Public Review):

Summary:

Roy et al. investigated the role of non-canonical DNA structures called G-quadruplexes (G4s) in long-range chromatin interactions and gene regulation. Introducing a G4 array into chromatin significantly increased the number of long-range interactions, both within the same chromosome (cis) and between different chromosomes (trans). G4s functioned as enhancer elements, recruiting p300 and boosting gene expression even 5 megabases away. The study proposes a mechanism where G4s directly influence 3D chromatin organization, facilitating communication between regulatory elements and genes.

Strength:

The findings are valuable for understanding the role of G4-DNA in 3D genome organization and gene transcription.

Weaknesses:

The study would benefit from more robust and comprehensive data, which would add depth and clarity.

(1) Lack of G4 Structure Confirmation: The absence of direct evidence for G4 formation within cells undermines the study's foundation. Relying solely on in vitro data and successful gene insertion is insufficient.

Using the reported G4-specific antibody, BG4, we performed BG4 ChIP-qPCR at the 79M locus. In addition, a second G4-insertion site was created and BG4 ChIP-qPCR was used to validate intracellular G4 formation. Briefed below, more details in the response above.

In the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).

Further, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4-ChIP-qPCR was significant within the G4-array inserted region, and not in the negative control region (Figure S8), consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci. Added in revised text in the second and the final sections of results, data shown in Figures 7, S4 and S8.

(2) Alternative Explanations: The study does not sufficiently address alternative explanations for the observed results. The inserted sequences may not form G4s or other factors like G4-RNA hybrids may be involved.

As mentioned in response to the previous comment, we confirmed that the inserted sequence indeed forms G4s inside the cells. RNA-DNA hybrid G4s can form within R-loops with two or more tandem G-tracks (G-rich sequences) on the nascent RNA transcript as well as the non-template DNA strand (Fay et al., 2017, 28554731). A recent study has observed that R-loop-associated G4 formation can enhance chromatin looping by strengthening CTCF binding (Wulfridge et al., 2023, 37552993). As pointed out by the reviewer, the possibility of G4-RNA hybrids remains, we have mentioned this possibility for readers in the second last paragraph of the Discussion.

(3) Limited Data Depth and Clarity: ChIP-qPCR offers limited scope and considerable variation in some data makes conclusions difficult.

We noted variation with one of the primers in a few ChIP-qPCR experiments (in Figures 2 and 3D). The changes however were statistically significant across replicates, and consistent with the overall trend of the experiments (Figures 2, 3 and 4). Enhancer function, in addition to ChIP, was also confirmed using complementary assays like 3C and RNA expression.

(4) Statistical Significance and Interpretation: The study could be more careful in evaluating the statistical significance and magnitude of the effects to avoid overinterpreting the results.

We reconfirmed our statistical calculations from biological replicate experiments. We carefully looked at potential overinterpretations, and made appropriate changes in the manuscript (details of the changes given below in response to comment to authors).

Reviewer #3 (Public Review):

Summary:

This paper aims to demonstrate the role of G-quadruplex DNA structures in the establishment of chromosome loops. The authors introduced an array of G4s spanning 275 bp, naturally found within a very well-characterized promoter region of the hTERT promoter, in an ectopic region devoid of G-quadruplex and annotated gene. As a negative control, they used a mutant version of the same sequence in which G4 folding is impaired. Due to the complexity of the region, 3 G4s on the same strand and one on the opposite strand, 12 point mutations were made simultaneously (G to T and C to A). Analysis of the 3D genome organization shows that the WT array establishes more contact within the TAD and throughout the genome than the control array. Additionally, a slight enrichment of H3K4me1 and p300, both enhancer markers, was observed locally near the insertion site. The authors tested whether the expression of genes located either nearby or up to 5 Mb away was up-regulated based on this observation. They found that four genes were up-regulated from 1.5 to 3-fold. An increased interaction between the G4 array compared to the mutant was confirmed by the 3C assay. For in-depth analysis of the long-range changes, they also performed Hi-C experiments and showed a genome-wide increase in interactions of the WT array versus the mutated form.

Strengths:

The experiments were well-executed and the results indicate a statistical difference between the G4 array inserted cell line and the mutated modified cell line.

Weaknesses:

The control non-G4 sequence contains 12 point mutations, making it difficult to draw clear conclusions. These mutations not only alter the formation of G4, but also affect at least three Sp1 binding sites that have been shown to be essential for the function of the hTERT promoter, from which the sequence is derived. The strong intermingling of G4 and Sp1 binding sites makes it impossible to determine whether all the observations made are dependent on G4 or Sp1 binding. As a control, the authors used Locked Nucleic Acid probes to prevent the formation of G4. As for mutations, these probes also interfere with two Sp1 binding sites. Therefore, using this alternative method has the same drawback as point mutations. This major issue should be discussed in the paper. It is also possible that other unidentified transcription factor binding sites are affected in the presented point mutants.

Since the sequence we used to test the effects of G4 structure formation is highly G-rich, we had to introduce at least 12 mutations to be sure that a stable G4 structure would not form in the mutated control sequence. Sp1 has been reported to bind to G4 structures (Raiber et al., 2012). Therefore, Sp1 binding is likely to be associated with the G4-dependent enhancer functions observed here. We also appreciate that apart from Sp1, other unidentified transcription factor binding sites might be affected by the mutations we introduced. We have discussed these possibilities in the fourth paragraph of the Discussion section in the revised manuscript.

Reviewer #1 (Recommendations For The Authors):

Whilst the data presented is promising and partially supports the authors' conclusion, this reviewer feels that some key controls are missing to fully support the narrative used. Below are my main concerns:

(1) The main thing missing in the current manuscript is to validate the actual formation of G4 in chromatin context for the repeat inserted by CRISPR-Cas. Whilst I appreciate this will form promptly a G4 in vitro, to fully support the conclusions proposed the authors would need to demonstrate actual G4-formation in cells after insertion. This could be done by ChIP-qPCR using the G4-selective antibody BG4 for example. This is an essential piece of evidence to be added to link with confidence G4-formation to chromatin looping.

To address the concern regarding whether the inserted G4 sequence forms G4s in cells, as suggested, we used the G4-selective antibody BG4. PCR primers in the study were designed keeping multiple points in mind: Primers should not bind to any site of G/C alteration in the mutated control insert; either the forward/reverse primer is from the adjacent region for specificity; covers adjacent regions for studying any effects on chromatin; and, PCRs optimized keeping in mind the repeats within the inserted sequence. Given these, primer pairs R1-R4 were chosen for further work following optimizations (Figure 2, top panel). For BG4 ChIP-qPCR we used primer pairs R2, which covered >100 bases of the inserted G4-array, or the G4-mutated control. Significant BG4 binding was clear in the G4-array insert, and not in the G4-mutated insert, demonstrating formation of G4s by the inserted G4-array (Figure S4).

In response to comment #3 below, we inserted the G4-forming sequence (or its mutated control) at a second locus. This insertion was near the 10 millionth position of chromosome 12 (10M insertion locus in text). Here also, BG4 binding was significant within the G4-array inserted region, and not in the negative control region (Figure S8). Together these demonstrate G4 formation by the inserted sequence at two different loci.

(2) I found the LNA experiment very elegant. However, what would be the effect of LNA treatment on the control sequence that does not form G4s? This control is essential to disentangle the effect of LNA pairing to the sequence itself vs disrupting the G4-structure.

As per the reviewer’s suggestion, we performed a control experiment where we treated the G4-mutated insert (control) cells with the G4-disrupting LNA probes. The changes in the expression of the surrounding genes in this case were not significant, indicating that the effects observed in the G4-array insert cells were possibly due to disruption of the inserted G4 structures. This data is presented in Figure S5.

(3) The authors describe their work and present its conclusion as if this were a genome-wide study, whilst the work is focused on a specific genomic location, and the looping, along with the effect on histone acetylation and gene expression, is limited to this. The authors cannot conclude, therefore, that this is a generic effect and the discussion should be more focused on the specific G4s used and the genomic location investigated. Ideally, insertion of a different G4-forming sequence or of the same in a different genomic location is recommended to really claim a generic effect.

To address this we inserted the G4-array sequence, or the G4-mutated control sequence, at another relatively isolated locus – at the 10 millionth position of chromosome 12 – denoted as 10M. Using BG4 ChIP-qPCR intracellular G4 formation was confirmed. We observed that the enhancer-like features in terms of enhancer histone marks and increase in the expression of surrounding genes were largely reproduced at the 10M locus on G4 insertion (Figure 7). These results are added as the final section under Results.

Reviewer #2 (Recommendations For The Authors):

The study proposes a mechanism where G4s directly influence 3D chromatin organization, facilitating communication between regulatory elements and genes.

While the present manuscript presents an interesting hypothesis, it would benefit from enhanced novelty and more robust data. The study complements existing G4 research (e.g., PMID: 31177910). While the conclusions hold biological relevance, they largely reiterate established knowledge. Furthermore, the presented data appear preliminary and still lack depth and clarity.

Hou et al., 2019 (PMID: 31177910) showed presence of potential G4-forming sequences correlated with TAD boundaries, along with enrichment of architectural proteins and transcription factor binding sites. Also, other studies noted enrichment of potential G4-forming sequences at enhancers along with nucleosome depletion and higher transcription factor binding (Hou et al., 2021; Williams et al., 2020). These studies proposed the role of G4s in chromatin/TAD states based on analysis of potential G4-forming sequences using correlative bioinformatics analyses. Here we sought to directly test causality. Insertion of G4 sequence, and formation of intracellular G4s in an isolated, G4-depleted region resulted in altered characteristics of chromatin, and not in the negative control insertion that does not form G4s. These, in contrast to earlier studies, directly demonstrates the causal role of G4s as functional elements that impact local and distant chromatin.

Major concerns:

(1) Lack of G4 Structure Confirmation: Implement G4-specific antibodies or fluorescent probes to verify G4 structures inside the cells.

Detailed response given above. Briefly, in the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).

Further, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4 ChIP-qPCR binding was significant within the G4-array inserted region, and not in the negative control region (Figure S8), consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci. Added in revised text in the second and the final sections of results, data shown in Figures 7, S4 and S8.

(2) Alternative Explanations: Explore the possibility that the sequences may not form G4s or that other factors like G4-RNA hybrids are involved.

Response provided in the public reviews section.

(3) Limited Data Depth and Clarity: ChIP-qPCR offers limited scope. Consider employing G4 ChIP-seq for genome-wide analysis of G4 association with histone modifications. Address inconsistencies in data like H3K27me3 variation and incomplete H3K9me3 data sets.

A recent study performed G4 CUT&Tag (Lyu et al., 2022, 34792172) and observed G4 formation at both active promoters and active and poised enhancers. We have discussed this in the sixth paragraph of the Discussion. The H3K27Me3 occupancy at the 79M locus insertions did not have any significant G4-dependent changes, however, at the second insertion site at the 10M locus (introduced in the revised manuscript, Figure 7) there was significant G4-dependent increase in H3K27Me3 occupancy along with the H3K4Me1 and H3K27Ac enhancer histone marks, indicating formation of a poised enhancer-like element.

We completed the H3K9me3 data sets for both insertion sites.

(4) Statistical Significance and Interpretation: Re-evaluate the statistical significance of results and interpret them in the context of relevant biological knowledge. Avoid overstating the impact of minor changes.     

We revised several lines to avoid overstating results. Some of the changes are as below (changes underline/strikethrough)

- There was an a relatively modest increase in the recruitment of both p300 and a substantial increase in the recruitment of the more functionally active acetylated p300/CBP to the G4-array when compared against the mutated control.

- As expected, although modest, a decrease in the H3K4Me1 and H3K27Ac enhancer histone modifications was evident within the insert upon the LNAs treatment.

- Moreover, the enhancer marks were relatively reduced, although not markedly, when the inserted G4s were specifically disrupted.

(5) Unexplored Aspects: Investigate the relationship between G4 DNA and R-loops, and consider the role of CTCF and cohesin proteins in mediating long-range interactions. Integrate existing research to build a more comprehensive framework and draw more robust conclusions.

As mentioned in response to one of the earlier comments, a recent publication extensively studied the association between G4s, R-loops, and CTCF binding (Wulfridge et al., 2023). While, here we focused on the primary features of a potential enhancer, further work will be necessary to establish how G4s influence the coordinated action between cohesin and CTCF and consequent chromatin looping. We have described this for readers in the second last paragraph of the Discussion in the revised version.

Minor Concern:

(1) Enhancer Definition: The term "enhancer" requires specific criteria. Modify the section heading or provide evidence demonstrating the G4 sequence fulfills all conditions for being an enhancer, such as position independence and long-range effects.

Although we checked some of the primary features of a potential enhancer: Like expression of surrounding genes, enhancer histone marks, chromosomal looping interactions, and recruitment of transcriptional coactivators, further aspects may need to be validated. As suggested, in the revised manuscript the section heading has been modified to ‘Enhancer-like features emerged upon insertion of G4s.’

Reviewer #3 (Recommendations For The Authors):

In addition to the points in my public review, I would like to mention some less significant points.

The authors mention that "the array of G4-forming sequences used for insertion was previously reported to form stable G4s in human cells" (Lim et al., 2010; Monsen et al., 2020; Palumbo et al., 2009). However, upon reading the publications, I found that these observations were made in vitro. I may have missed something, but there are now several mappings of folded-G4 in human cells based on different approaches. It would be beneficial to investigate whether the hTERT promoter is a site of G-quadruplex formation in vivo. If confirmed, a similar analysis should be conducted on the 275 bp region inserted into the ectopic region to determine if it also has the ability to form a structured G4.

We performed BG4 ChIP to confirm in vivo G4 formation by the inserted G4-array as suggested (Figures S4, S8). Detail response given above. Briefly, in the revised version we validated G4 formation inside cells at the insertion site using the reported G4-selective antibody BG4. Significant BG4 binding (by ChIP-qPCR) was clear in the G4-array insert, and not in the G4-mutated insert, supporting formation of G4s by the inserted G4-array (included as Figure S4).

Further, we inserted the G4-sequence, or the mutated control, at a second relatively isolated locus (at the 10 millionth position on Chr12, denoted as 10M site in text). First, BG4 ChIP was done to confirm intracellular G4 formation by the inserted array. BG4-ChIP-qPCR was significant within the inserted region, and not in the negative control region (Figure S8). Consistent with the 79M locus. Together these demonstrate intracellular G4 formation by inserted sequences at two different loci. Added in revised text in the second and the final sections of results, data shown in Figures 7, S4 and S8.

The inserted sequence originates from a well-characterized promoter. The authors suggest that placing it in an ectopic position creates an enhancer-like region, based on the observation of increased levels of H3K27Ac and H3K4me1 on the WT array. To provide a control that it is not a promoter, it would be useful to also analyze a specific mark of promoter activity, such as H3K4me3.

As suggested by reviewer, we also analysed the H3K4Me3 promoter activation mark at both the 79M and 10M (introduced in the revised manuscript, Figure 7) insertion loci. We did not observe any significant G4-dependent changes in the recruitment of H3K4Me3 (Figures 2, 7).

In the discussion, the authors mention "it was proposed that inter-molecular G4 formation between distant stretches of Gs may lead to DNA looping". To investigate this further, it would be worthwhile to examine whether the promoter regions of activated genes (PAWR, PPP1R12A, NAV3, and SLC6A15) contain potentially forming G-quadruplexes (pG4). Additionally, sites that establish more contact with the G4 array described in Figure 6F could be analyzed for enrichment in pG4.

Thank you for pointing this out. We found promoters of the four genes (PAWR, PPP1R12A, NAV3, and SLC6A15) harbour potential G4-forming sequences (pG4s). Also as suggested, we analysed the contact regions in Fig 6F, along with the whole locus, for pG4s. Relative enrichment in pG4 was seen, particularly within the significantly enhanced interacting regions, which at times spreads beyond the interacting regions also. This is shown in the lower panel of Figure 6F in the revised version. We have described this in Discussion for readers.

Comment by onewheeljoe:

For example, we might simply ask that each participant refrain from using hashtags as a final thought because that is a form of sarcasm or punchline that can be misconstrued or shut down honest debate or agreeable disagreement.

We could ask respondents to reply to any comment that they read twice because of tone to use "ouch" as a tag or a textual response. The offending respondent could respond with "oops" in order to preserve good will in an exchange of ideas.

Finally, the first part of a flash mob might occur here, in the page notes, where norms could be quickly negotiated and agreed upon with a form of protocol.

Reviewer #1 (Public Review):

Summary:

Guo, Hue et al. focused on understanding the epigenetic activity and functional dependencies for two different fusions found in infantile rhabdomyosarcoma, VGLL2::NCOA2, and TEAD1::NCOA2. They use a variety of models and methods; specifically, ectopic expression of the fusions in human 293T cells to perform RNAseq (both fusions), CUT&RUN (VGLL2::NCOA2), and BioID mass spec (both fusions). These data identify that the VGLL2::NCOA2 fusion has peaks that are enriched for TEAD motifs. Further, CPB/p300 CUT&RUN support an enrichment of binding sites and three TEAD targets in VGLL2::NCOA2 and TEAD1::NCOA2 expressing cells. They also functionally evaluated genetic and chemical dependencies (TEAD inhibition), and found this was only effective for the VGLL2::NCOA2 fusion, and not for TEAD1::NCOA2. Using complementary biochemical approaches they suggest (with other supporting data) that the fusions regulate TEAD transcriptional outputs via a YAP/TAZ independent mechanism. Further, they expand into a C2C12 myoblast model and show that TEAD1::NCOA2 is transforming in colony formation assays and in mouse allografts. This is consistent with previously published strategies using VGLL2::NCOA2. Importantly, they show that a CBP/p300 (a binding partner found in their BioID mass spec) small molecule inhibitor suppresses tumor formation using this mouse allograft model, that the tumors are less proliferative, and have a reduction in transcriptional of three TEAD target genes. Generally, the data is interesting and suggests new biology for these fusion-oncogenes. However, the choice of 293T for the majority of the transcriptional, epigenetic, and proteomic studies makes the findings difficult to interpret in the context of the human disease, and the rationale for the choice of an epithelial-like kidney cell line is not discussed. Further, details are missing from the figures, figure legends, and methods that make the data difficult to interpret, and should be added to improve the reader's understanding. Overall, the breadth of methods used in this study, and the comparison of the two fusion-oncogene's biology is of interest to the fusion-oncogene, pediatric sarcoma, and epigenetic therapeutic targeting fields.

Strengths:

(1) Multiple experimental approaches were used to understand the biology of the fusion-oncogenes, including genomic, proteomic, chemical, and genetic inhibition. These approaches identify potential new mechanisms of convergent fusion-oncogene activity, around TEAD transcriptional targeting (that is YAP/TAZ independent) and reveal CBP/p300 as a functional dependency.

(2) Complementary models were used, including cell-based assays and mouse allograft models to show the dependency on CBP/P300.

(3) Co-IPs were clear and convincing and showed direct interaction of the fusion-oncogene with ectopic and endogenous TEAD1/pan-TEAD, but not YAP/TAZ.

(4) Potential to follow-up on additional targets/mechanisms of tumorigenesis. For example, in the BioID proteomics screen, a unique VGLL2::NCOA2 and TEAD::NCOA2 interactor is P53, which also is an enriched pathway in Figure 4C in the p300 CUT&RUN peaks in the VGLL2::NCOA2 and TEAD1::NCOA2 expressing cells - is this indicative of the toxicity of the fusion-oncogenes or do you think this informs potential mechanisms for transformation.

Weaknesses:

(1) The rationale for performing genomics, transcriptional, and proteomics work in 293T cells is not discussed. Further, there are no functional readouts mentioned in the 293T cells with expression of the fusion-oncogenes. Did these cells have any phenotypes associated with fusion-oncogene expression (proliferation differences, morphological changes, colony formation capacity)? Further, how similar are the gene expression signatures from RNA-seq to rhabdomyosarcoma? This would help the reader interpret how similar these cell models are to human disease.

(2) TEAD1::NCOA2 fusion-oncogene model was not credentialed past H&E, and expression of Desmin. Is the transcriptional signature in C2C12 or 293T similar to a rhabdomyosarcoma gene signature?

(3) For the fusion-oncogenes, did the HA, FLAG, or V5 tag impact fusion-oncogene activity? Was the tag on the 3' or 5' of the fusion? This was not discussed in the methods.

(4) Generally, the lack of details in the figures, figure legends, and methods make the data difficult to interpret. A few examples are below:

a. Individual data points are not shown for figure bar plots (how many technical or biological replicates are present and how many times was the experiment repeated?).<br /> b. What exons were included in the fusion-oncogenes from VGLL2 and NCOA2 or TEAD1 and NCOA2?<br /> c. For how long were the colony formation experiments performed? Two weeks?<br /> d. In Figure 2D, what concentration of CP1 was used and for how long?<br /> e. How was A485 resuspended for cell culture and mouse experiments, what is the percentage of DMSO?<br /> f. How many replicates were done for RNA-seq, CUT&RUN, and ATACseq experiments?

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required):

The majority of the conclusions are well supported by strong experimental evidence. The only area where that is not fully the case is the role of Pak1 as a downstream effector of FoxG1-FoxO6 and its effects on macropinocytosis. To further strengthen this claim, the authors should demonstrate that ablation of Pak1 can rescue the functional consequences of forced FoxO6 expression and whether overexpression of Pak1 rescues quiescence exit in FoxO6 knockout. Thank you to the reviewer for these helpful suggestions. To investigate the effects of Pak1 ablation, and therefore more directly the link between FOXG1 and FoxO6 and macropinocytosis, we tested the published Pak1 inhibitor IPA-3. Unfortunately, to distinguish the role of Pak1 in quiescence exit and macropinocytosis, we would need a dosage of IPA-3 that is efficacious but does not affect cell proliferation. It was not possible to optimise such a dosage (a dosage of 10uM is shown to be efficacious at inhibiting Pak1 (Verma et al, 2020; Wong et al, 2013) however even at 2.5uM we see significant cell death in our cells. Indeed, this is potentially due to pleiotropic roles for Pak1.

Also, it is not feasible to overexpress Pak1 in the FoxO6 KO cells with inducible FOXG1. To ensure we are investigating quiescence exit this would need to be in an inducible manner; however, re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels by excising the existing transgene.

As shown in Figure S3, we do not observe clear vacuole formation in F6 (FOXG1-inducible) cells upon Dox addition. As detailed in the discussion, we hypothesise that FoxO6-induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Indeed, active Pak1 has been found to modulate pinocytic cycling, enhancing both FITC-dextran uptake and efflux (Dharmawardhane et al, 2000). We therefore would not hypothesise that high Pak1 levels alone would be sufficient to drive quiescence exit.

Alternatively, the macropinocytosis observed may be a metabolic stress response because of the hyperactivation of signalling pathways upon FoxO6 overexpression. Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017).

We believe the observed macropinocytosis phenotype upon Foxo6 overexpression, and the changes in Pak1 expression upon Foxo6 loss or FOXG1 induction provide interesting insights into the function of this underexplored FoxO family member. However, currently we are unable to demonstrate a direct link between these processes and have therefore modified the text to reflect this (see lines 292-4, 330-3, 365-8).

• The manuscript stresses the role of NSC quiescence exit in GBM and demonstrates that FoxG1 KO reduces FoxO6 levels in a murine GBM cell line but a BMP4-mediated quiescence and dox-induced FoxG1 over-expression or an abolishment of cell cycle re-entry thereof by reduced FoxO6 levels in the case of FoxG1 KO is lacking. But this would significantly substantiate the relevance of the findings. *

Mouse GBM cells have elevated levels of FoxG1 and have been shown to be refractory to BMP4-mediated quiescence entry, maintaining colony formation following BMP treatment (Bulstrode et al, 2017). It is therefore challenging to specifically investigate cell cycle re-entry/ quiescence exit using these mouse GBM cells, or indeed any GBM cell line due to their inability to respond fully to BMP cues (Caren et al, 2015). It has also been shown by Bulstrode et al, 2017 that Foxg1 null mouse neural stem cells show an increased propensity to exit cycle in response to BMP treatment, and reduced colony formation on return to EGF/FGF-2 growth factors. FOXG1 null cell lines therefore show a reduced response to BMP cues, making it difficult to explore quiescence exit per se.To navigate this, instead we investigated Dox-induced FOXG1 overexpression in FoxO6 WT and KO mouse NS cells, which display similar quiescence characteristics upon BMP treatment (Figure 4).

• In the introduction and discussion, FoxO6 is mentioned for its oncogenic roles in various cancers but no reference to GBM specifically is cited. It feels like a missed opportunity to not show evidence of this in the IENS cell line that has reduced levels of FoxO6; is there an effect in their proliferative capacity? What are the expression levels of Pak1 following FoxG1 KO in IENS cells? *

Thank you for the helpful suggestion. It is indeed true the literature on FoxO6 in GBM is lacking, explaining the absence of citations on this. On investigation of expression of the proliferation marker Ki67 in these cells we found no significant difference in expression, now shown in Figure 1H. This is in fitting with previous findings of our lab (Bulstrode et al, 2017) which show that FOXG1 is dispensable for the maintenance of continued NSC or GSC proliferation in vitro. We investigated the expression levels of Pak1 following FOXG1 KO in IENS and found a decrease in both KO lines compared to parental cells (updated Figure 6F).

As explained in our discussion, these data suggest that Foxg1/FoxO6/Pak1 are not functionally important in sustaining GSC/NSC proliferation, as shown by the lack of proliferation defects upon Foxg1 or FoxO6 deletion (Bulstrode et al, 2017), but impact regulatory transitions, as cells prepare to exit quiescence into the proliferative radial-glia like state.

*Minor comments *

- Fig1A shows 4 and 2-fold respectively for the two mouse NSC lines, not 17 and 4-fold increase as written on manuscript, please adjust accordingly.

The qRT-PCR data are presented as log2(fold change) or - ddCt, where this value equals zero for the calibrator sample, as indicated in the figure legends and axes. The data are presented in this way to enable accurate visualisation of up- and down-regulation of gene expression. Data are stated as ‘fold increase’ in the text for ease of reading, which we have clarified in the text and figure legends (e.g. lines 154 and 176).

• • Fig2G manuscript reports a 235-fold upregulation, but graph looks more like a 7 or 8-fold as shown on Fig1A for the F6 NSC line. I would recommend checking the fold changes reported throughout the paper. *

See previous comment above. The qRT-PCR data are presented as log2(fold change) or - ddCt, where this value equals zero for the calibrator, as indicated in the figure legends and axes. The data are presented in this way to enable accurate visualisation of up- and down-regulation of gene expression. Data are stated as ‘fold increase’ in the text for ease of reading, which we have clarified in the text and figure legends (e.g. lines 154 and 176).

• The manuscript describes the increase of FOXG1 after BMP4-induced cell cycle exit as compared to non-BMP4 treated cells (p.8 first paragraph), but I am wondering if this expression is rather compared to dox negative and not vs BMP4 negative treatment. *

Data are presented relative to the non-BMP treated (EGF/FGF-2) control throughout the manuscript for consistency. This is to enable changes in expression between -Dox and +Dox to be visualised throughout the quiescence-exit time course relative to the initial starting population in EGF/FGF-2 growth media, prior to BMP treatment.

• 1. In Fig2G it is interesting that FoxO6 is upregulated in BMP4 treated throughout the experiment with highest values at day10 post treatment. At the same time, non-BMP4 treated cells keep decreasing their FoxO6 levels dramatically but there is no mention or reference to this effect.*

In Figure 2G, all cells have been treated with BMP4, prior to return to growth media (EGF/FGF) with or without Dox. It is true that in the +Dox condition with FOXG1 induction, FoxO6 levels continue to increase up to Day 10, perhaps reflective of the expansion of a highly proliferative radial glia-like population.

• 1. Fig2 would benefit from a western blot like Fig1D where FoxG1 and FoxO6-HA protein levels are also shown in dox-treated comparing BMP4-treated vs non-treated. *

Due to the lack of specific FoxO6 antibodies and the absence of a FoxO6-HA tag in this cell line, it is not possible to perform protein analysis of FoxO6 levels in this figure as for Figure 1D.

• The colonies in Fig3E should be quantified, as their ability to form neurospheres seems somewhat compromised upon FoxO6 KO. Fig3B and 3F could perhaps be consolidated into one panel in the interest of space and presentation. *

Good suggestion. We have now consolidated Fig 3B and 3F into one panel (now Figure 3F) as suggested by the reviewer. We performed additional replicates for Figure 3E to quantify the colony formation efficiency. This showed a small but insignificant decrease in colony forming ability in the KO cells (Figure 3E). Importantly the FoxO6 null cells do form colonies, and our results show that FoxO6 is not essential for proliferation or colony formation of NSCs in EGF/FGF-2 – this therefore does not account for the complete loss in colony formation we see the in the FoxO6 KO cells upon FOXG1 induction.

• Fig4A shows vs "parental" non-BMP on y axis but wouldn't this show fold change of dox+ parental vs parental. The authors should clarify this. *

All samples in Figure 4A are compared to parental cells in EGF/FGF-2, i.e. non-BMP treated, as the calibrator sample where log2(fold change) equals zero. We chose to set a single calibrator sample for all data (parental and FoxO6 KO cells included) to allow us to compare changes in FOXG1 transgene across the entire experiment.

• Perhaps the authors can add a non-BMP4 treated count of % FOXG1 positive cells to Fig4C for reference. *

As shown in Figure 4A, both parental and FoxO6 KO cells show similar, i.e. negligible, FOXG1 transgene expression without Dox, compared to the parental non-BMP4 treated control, therefore negligible FOXG1-V5 positive cells are seen by ICC. We have edited Figure 4A to include a non-BMP treated and BMP-treated control to show the negligible FOXG1-V5 expression by qPCR as controls.

• The sentence mentioning Fig5D for the first time (p.10 third paragraph) needs rephrasing for clarity and should also call out Fig5C for the mCherry expression live cell imaging data where appropriate. Fig5D does not appear to be live imaging as implied by the text. If vacuole formation is observed already as early as 10-11h after Dox induction, then it should be shown somewhere in Fig5. Vacuole formation is shown with a higher magnification image inset only in the 22h timepoint image. I think Fig5E should be more substantiated with some sort of quantification, e.g. % of vacuoles positive for EEA1 and/or LAMP1. *

We apologise for this. The first reference to Figure 5D one line 234 should refer to Figure 5C, this has now been corrected in the text. Vacuoles are visible in Figure 5C panel 10 h 30 min, however, to make this clearer we have also supplied an accompanying movie of the live imaging (Movie 1). The imaging in Fig 5E has not been quantified as this imaging was performed with the purpose of confirming the vacuole structures seen are not simply enlarged lysosomes, due to their similarity in appearance to those published elsewhere (Ramosaj et al, 2021; Leeman et al, 2018). Instead, we have provided Western blotting data in Figure S5E to support this conclusion that there is no clear increase in EEA1 or LAMP1 (early endosomal or lysosomal) expression upon FoxO6-HA induction.

*- Could the authors comment on the lack of proliferative advantage of the FoxO6 overexpression. FigS3 shows Edu staining, but there is no proliferation assay in either Fig5 or S3. What would be the effect of FoxO6 overexpression on BMP4-mediated quiescence with or without FoxG1 over-expression? *

Induction of FoxO6-HA overexpression does not provide a proliferative advantage to the cells. Looking at individual cells, those with high FoxO6-HA levels seem to associate with EdU negativity. In Figure S3 we provide quantitative EdU incorporation assay as a proliferation assay (quantification of the number of cells cycling, therefore incorporating EdU, within a 24h pulse period). Quantification of the EdU staining in Figure S3G is provided in Figure S3H. We have now clarified this in the text on page 11, lines 263-4.

Unfortunately, due to transgene overexpression using the PiggyBac transposon method, it is not feasible to overexpress FoxO6 and FOXG1 in the same cell line, as re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels and make results difficult to interpret. Given the association of vacuolated cells with EdU negativity, we predict that FoxO6 overexpression would not give an advantage for quiescence exit. Indeed, BMP-treated cells with FoxO6 overexpression show a decrease in EdU positivity, as shown in Figure S3H. As discussed in the text, we hypothesise that cells with FoxO6 overexpression are in a stalled state, potentially due to signalling hyperactivation. While this may not be physiological, it gives us clues as to the function and downstream targets of FoxO6, which remain uncharacterised.

*- Can the authors clarify if there is a proliferation change in F6 cells in Fig6F as in Fig2F? Fig6F shows Pak1 is already upregulated in quiescent NSCs, what are the expression levels of Pak1 in FoxO6 -/- ANS4 cells upon FoxG1-mediated quiescence exit as shown in Fig4? Is there a particular reason why the F6 cell line data is shown only up to day2 post Dox-induction rather than d4 or d10? For consistency with the rest of similar experimental data this timeline should be extended. Does Pak1 remain elevated, plateaus or keeps reducing further post day2? *

The data is (previous) Figure 6F is the same assay and cell line as presented in Figure 2, but at an early timepoint (Day 2) during the quiescence exit assay. We have provided in the panel qRT-PCR analysis of Ki67 to show that cells begin to show increased proliferation at this timepoint. Due to our hypothesis that Pak1 is required at an early transition point, we decided to analyse this expression at an earlier timepoint than Figure 2. We have also repeated this at D10 (data below), showing Pak1 levels continue to increase with time, along with FoxO6 and the proliferative marker Ki67. Due to technical issues with variable FOXG1 transgene levels we were unable to analyse Pak1 expression levels in FoxO6+/- ANS4 cells upon FOXG1-mediated quiescence exit.

*15 . Reviewer #1 (Significance (Required)): *

The study provides a conceptual advance for exit from stem cell quiescence. There is strong evidence provided for murine neural stem cells, but the link to GBM cancer stem cells is less developed (but perhaps this is the subject of a separate manuscript).

While FoxG1 is a known regulator of neurodevelopment and glioblastoma, the functions of FoxO6 have not been studied in the context of neural stem cells. In my view, this study should be of high interest to audiences in both neurodevelopment and cancer research. * Expertise: glioblastoma, cancer stem cells, neurodevelopment *

We have edited the text and title to clarify that neural stem cells are used here as a model for GSCs with high levels of FOXG1 (e.g. lines 36 and 69).

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Reviewer #2 (Evidence, reproducibility and clarity (Required)):

*Major comments: *

-The choice of NSCs as a main experimental model to understand the effects of FoxG1 and FoxO6 is not fully justified. The authors had previously shown that FoxG1 is expressed at very low levels in NSCs (Fig. 1A in Bulstrode et al. 2017). FoxO6 also seems to be barely expressed in NSCs (Fig. 1 of the current manuscript) and, in addition, its levels seem to go further down as cells exit quiescence (-Dox line in Fig. 2H). Therefore, these two genes do not seem to play an important role in the normal exit from quiescence of NSCs, with FoxO6 only affecting FoxG1 overexpression-induced exit from quiescence. * * *If the aim is to mimic a GBM-like state by FoxG1 overexpression, this should be made much clearer in the text, including title and abstract. In that case, the authors should also show a direct comparison of the levels of FoxG1 in GBM and upon Dox-induced overexpression in NSCs. *

We agree with this criticism and suggestion to fix this. It is indeed our aim to mimic a GBM-like state by inducing FOXG1 overexpression and we should have made that more explicit. All experiments are performed in the context of high FOXG1 level. Like Foxg1, FoxO6’s homeostatic roles may be subtle in adulthood, and mostly involved in neural plasticity (Yu et al, 2019). This is in keeping with our finding that basal FoxO6 levels are low in adult NSCs and not required for sustained proliferation but are important for cell state transitions. If the FoxO6 levels activated by elevated FOXG1 represent an acquired dependency of GBM, there may be a therapeutic window to target this pathway. However, given the poorly understood roles of FoxO6, further work is needed to determine its specific value as a therapeutic target. We have modified the title and the text to make this clearer. This is also stated in the first paragraph of the results section on page 7 (line 148).

We have provided below a Western Blot (Bulstrode, 2016) in which FOXG1 levels in F6 cells induced with Dox (1000 ng/ml the dosage used) with the GBM cell lines G7 and G144, and the normal NS cell line U5. This shows that the FOXG1 levels induced are significantly higher than found in normal neural stem cells (mouse or human). This model has been previously used and published in Bulstrode et al, 2017, upon which this manuscript expands.

*-While the authors state that they aim to study NSC quiescence, they use a protocol that is closer to modelling astrocytic differentiation. In fact, in their previous work, they use this very same protocol (removal of growth factors and addition of BMP) to study the role of FoxG1 and Sox2 on astrocyte de-differentiation (Bulstrode et al. 2017). While there is arguably no perfect in vitro model of NSC quiescence, the current standard in the field is treatment with both BMP and FGF for 48 to 72 hours (e.g.: Mira et al., 2010, Martynoga et al., 2013, Knobloch et al., 2017, Leeman et al., 2020). BMP alone is regarded as a pro-astrocytic differentiation cue, and 24 hours might not be enough for NSCs to fully commit to either differentiation or quiescence. Therefore, either the claims in the paper are changed to match the astrocytic differentiation model, or a standard quiescence protocol should be used throughout to confirm the findings also apply to the exit from quiescence of NSCs. *

We agree with the reviewer that there is indeed no perfect in vitro model of NSC quiescence and thank the reviewer for this useful discussion. Coincident with this project, this was an active area of research from our laboratory as explored by Marques-Torrejon et al, 2021 (Nature Comms). After 24 h BMP4 treatment, we found that adult mouse NS cells: exit cell cycle, are growth factor unresponsive, obtain an astrocytic morphology, upregulate astrocytic markers such as Gfap and Aqp4, and downregulate radial glia/NS cell markers such as Nestin and Olig2 (Figure 3).

We therefore initially viewed them as terminally differentiated. However, the exact state of these cells is difficult to define due to the lack of definitive markers and transcriptional differences that can distinguish terminally differentiated GFAP-expressing astrocytes from quiescent type B SVZ NS cells (which also express GFAP) (Bulstrode et al, 2017; Doetsch et al, 1999; Codega et al, 2014). Findings from our laboratory later suggested some NS cell markers are maintained following BMP4 treatment and these cells can be forced back into cycle with combined Wnt/EGF signalling, or FGF/BMP signalling (Marques-Torrejon et al 2021). This suggests in vitro NS cells may lie along a continuous spectrum of states from dormant quiescent, activated quiescent (primed for cell cycle re-entry) to actively proliferating, similar to that observed in vivo in the mouse SVZ (Dulken et al, 2017). Indeed, after 24 h BMP4 treatment, we observe a minimal level of colony formation in no Dox controls following 10 days of exposure to the growth factors EGF/FGF-2 (Figure 2D-F).

These non-cycling BMP4-induced astrocytic cells might therefore be better viewed as dormant quiescent NSCs, hence our reference as quiescent NSCs. The assay conditions used in this manuscript differ to those of Marques-Torrejon et al, in terms of density and length of BMP4 treatment; it is therefore likely that our BMP-treated cells are at different stages along the continuum between dormancy and primed quiescent states. Importantly, regardless of the exact cell type induced by 24 h BMP4 treatment, we have considered the changes induced by FOXG1 overexpression, in comparison to the effect of NS cell media alone.

*-The FoxO6-induced vacuole formation in NSCs is a very interesting finding. However, so far it was only observed upon FoxO6 overexpression. To claim vacuolization is required for quiescence exit, the authors should show whether this phenomenon is also observed upon normal exit from quiescence and FoxG1-induced reactivation of NSCs. From the author's own data, Pak1 (which induces vacuolization) is unlikely to reactivate NSCs, as its expression is highest in BMP-treated cells (Figure 6F). The authors should show whether some vacuolization is present at these stage in NSCs and if not, discuss the possible interplay between Pak1 and FoxO6 in vacuole formation and quiescence exit. *

As detailed in the discussion, we hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Indeed, active Pak1 has been found to modulate pinocytic cycling, enhancing both FITC-dextran uptake and efflux (Dharmawardhane et al, 2000). Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017).

We do not see clear evidence of vacuoles in FOXG1-induced reactivation of NSCs – this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation. While this may not be physical, it gives us clues as to the function and downstream targets of FoxO6, which remain uncharacterised (such as a link of FoxO6 and FOXG1 with Pak1-related pathways). Demonstrating a requirement for vacuolisation in quiescence exit is outwidth this manuscript and therefore we are careful not to claim this. We have modified the text to clarify this.

As the reviewer noted, it is interesting that Pak1 is highest in BMP-treated cells; it seems that BMP signalling itself is triggering elevated Pak1 levels, likely as cells undergo extensive cell shape changes during the transition from proliferation to quiescence. However, in EGF/FGF-2, Pak1 levels decrease, and our data suggests that FOXG1/FoxO6 are required to increase or maintain Pak1, potentially to again enable the cell shape/metabolic changes required on quiescence exit. We have added to the text to expand upon this observation on page 14 (lines 330-333). -Finally, the data on the regulation of Pak1 expression by FoxO6 is insufficient to draw any strong conclusions. Downregulation of Pak1 in FoxO6 cells is not enough evidence to claim a direct regulation. The authors should show whether Pak1 levels are increased after FoxO6 overexpression and whether FoxG1 is downregulated in FoxO6 KO NSCs (indirectly affecting Pak1 expression).

We have performed qRT-PCR analysis of Foxg1 expression in FoxO6 KO NSCs and see no consistent difference in expression, indicating this is not indirectly affecting Pak1 expression (see below, 1). We have also investigated Pak1 levels upon FoxO6 overexpression, over a time course following Dox addition (see below, 2). Interestingly, when FoxO6 is overexpressed, Pak1 is not clearly upregulated at any time-point. It may be that as Pak1 is already expressed in the -Dox controls, due to its roles in a variety of cellular functions, that the levels are saturated already. It is clear that Pak1 expression decreases upon FoxO6 loss in EGF/FGF (without coincident Foxg1 downregulation) and in F6 cells, higher FOXG1 correlates with higher Pak1 in EGF/FGF. Together with the induction of macropinocytosis upon FoxO6 overexpression, these data provide interesting insights into the potential pathways downstream of Foxo6 in controlling quiescence exit, directly or indirectly related to Pak1 signalling. We have modified the text to reflect this on page 14 (lines 330-333).

Minor comments: * Please state in the main text that NSCs are derived from the SVZ. *

This has been added to the text on page 7 (line 149) and is in the methods ‘Cell Culture’ section.

Reviewer #2 (Significance (Required)):

As I said before, I find this work tackles a very important question, how is the exit from quiescence controlled in NSCs. This manuscript will be of interest to researchers in the fields of adult stem cell biology and adult neurogenesis. While my expertise lies mostly on NSC biology, this work is of potential great interest for the cancer field, particularly for brain cancer research. Elucidating the mechanisms GBM cells use to exit quiescence is crucial in order to avoid the relapse of this aggressive form of brain cancer. To increase the relevance of the work to the cancer community, some of the key findings should be reproduced with GBM cells. It would be particularly important to show whether Pak1 induced vacuolization and macropinocytosis can be observed in GBM cells.

As detailed in the discussion, we hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes. Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017). We do not see clear evidence of vacuoles in FOXG1-indued reactivation of NSCs– this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation. We do not therefore think macropinocytosis per se would be observed in quiescence exit of GBM cells – indeed a normal form of macropinocytosis-induced cell death called methuosis has been observed in GBM cells with hyperactivated Ras signalling (Overmeyer et al, 2008). However, this phenotype still gives us clues as to the function of FoxO6 in quiescence exit in GSCs and the downstream signalling pathways it may regulate, such as Pak1-related signalling (discussed on lines 330-3 and 366-9).

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary: * The overall objective of the paper is to investigate the mechanisms by which co-option of the activity of developmental master lineage regulators by cancer cells allows them to gain fitness. To answer this question, they focus on FOXG1. This TF acts during the specification of the telecephalon. Its expression can be increased in Glioblastoma (GBM) and, more importantly for the paper, FOXG1 has previously been shown to promote exit from quiescence of glioblastoma stem cells (GSCs) and non-transformed neural stem cells (NSCs). In a previous screen, the authors identified FoxO6 as a potential direct target gene of FOXG1. In this paper, they showed that with the gain of expression for FOXG1 in NSCs and loss of FOXG1 in GSCs, FoxO6 is increased or decreased, respectively. Loss of FoxO6 in NSCs does not alter their cell cycle or cell shape and specification. Yet, loss of FoxO6 in NSCs blocks FOXG1-mediated exit from quiescence. To understand the mechanisms, they decided to overexpress FoxO6 in NSCs and demonstrated that the cells undergo macropinocytosis, a process by which cells can engulf large amount of nutriments from the external medium. It remains to be determined whether this macropinocytosis occurs in cells overexpressing FOXG1 and GSCs. The authors provide a first answer by showing that overexpression of FOXG1 induces not only FoxO6 but also the expression of PAK1, one of the key kinases that regulates the membrane engulfment of macropinocytosis in NSCs. In GSC lines, the decrease of FOXO6 decreases PAK1 levels. *

Major comments: * The paper describes interesting and convincing results (number of cell lines, repeated experiments seems sufficient) but it is difficult to reconcile them all in a single model, and this diminishes the impact of the study. Epistatic interactions between FoxG1, FoxO6, PAK1 and macropinocytosis are not always studied in the same cell models. Whether FOXG1-induced exit from quiescence of NSCs is dependent on a FOXG1-->FOXO6-->PAK1-->Macropinocytosis axis remains to be demonstrated. Also does such an axis operate in tumor cells remains to be fully assessed? In particular, if FoxO6 overexpression in NSCs can induce macropinocytosis, is this cellular process induced by FoxO6 downstream of FOXG1 activity during NSC quiescence exit? Is PAK1 a relay of FoxO6? Experiments looking at macropinocytosis and the involvement of PAK1 in the cell models of Figure 4 will definitely help to bridge the different results all together. *

We thank the reviewer for this useful insight and discussion for future work.

To directly investigate the effects of Pak1 ablation, and therefore more directly the link between FOXG1 and FoxO6 and macropinocytosis, we tested the published Pak1 inhibitor IPA-3. Unfortunately, to distinguish the role of Pak1 in quiescence exit and macropinocytosis, we would need a dosage of IPA-3 that is efficacious but does not affect cell proliferation. It was not possible to optimise such a dosage (a dosage of 10uM is shown to be efficacious at inhibiting Pak1 (Verma et al, 2020; Wong et al, 2013) however even at 2.5uM we see significant cell death in our cells. Indeed, this is potentially due to the variety of cellular functions Pak1 is involved in. Conversely, it is not feasible to overexpress Pak1 in the FoxO6 KO cells with inducible FOXG1. To ensure we are investigating quiescence exit this would need to be in an inducible manner; however, re-transfecting cells using the PiggyBac system would potentially alter FOXG1 transgene levels (through excision of the existing transgene) and therefore make results difficult to interpret.

We hypothesise that FoxO6- induced macropinocytosis could represent a stalled state, with other pathways downstream of FOXG1 necessary to be activated concomitantly to ensure cell cycle re-entry, e.g., through increased pinocytic flux that cannot be assessed within our experimental timeframes (as detailed in the text discussion). Alternatively, the macropinocytosis observed may be a metabolic stress response because of hyperactivation of signalling pathways upon FoxO6 overexpression Hyperactivation of Ras signalling, canonical Wnt and PI3K signalling have all been shown to play roles in inducing macropinocytosis (Overmeyer et al, 2008; Tejeda-Muñoz et al, 2019; Recouvreux & Commisso, 2017). We do not see clear evidence of vacuoles in FOXG1-induced reactivation of NSCs– this supports that the macropinocytosis seen upon FoxO6 overexpression is a stalled state or due to hyperactivation and therefore not a physiological process in quiescence exit. We do not therefore think macropinocytosis per se would be observed in quiescence exit of GBM cells – indeed a normal form of macropinocytosis-induced cell death called methuosis has been observed in GBM cells with hyperactivated Ras signalling (Overmeyer et al, 2008).

However, we believe the observed macropinocytosis phenotype upon Foxo6 overexpression, and the changes in Pak1 expression upon Foxo6 loss or FOXG1 induction provide interesting insights into the function of this underexplored FoxO family member, in GSCs and the downstream signalling pathways it may control, such as Pak1-related signalling. We have modified the text to reflect the limitations of our current data and discuss this (lines 330-3 and 366-9).

I only have a few very specific memes indexed in my box: https://boffosocko.com/tag/zettelkasten-memes/ and a few more at https://hypothes.is/users/chrisaldrich?q=zettelkasten+meme

Historically, Aby Warburg had a large image-based zettelkasten for his work on art which predated Richard Dawkins' conception of meme, but I think qualifies. See: https://boffosocko.com/tag/aby-warburg/ or his Bilderatlas Mnemosyne project: https://warburg.sas.ac.uk/archive/bilderatlas-mnemosyne

It's digital in nature, but Shawn Gilmore has a large collection of images of string walls, Anacapa charts, walls and floors littered with paperwork by obsessives, etc. for his cultural research. It also includes some popular memes. https://www.vaultofculture.com/nst

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replyy to u/a2jc4life at https://www.reddit.com/r/Zettelkasten/comments/1ddhn9n/memes/

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this manuscript, Eaton et al. examine the regulation of transcription directionality using a powerful genomic approach (more about the methodology below). Their data challenge the notion that the polyadenylation signal-reading Cleavage and Polyadenylation (CPA) complex is responsible for controlling promoter directionality by terminating antisense transcription. Namely, depletion of the required CPA factor RBBP6 has little effect on antisense transcription measured by POINT. They find instead that initiation is intrinsically preferential in the sense direction and additionally maintained by the activities of an alternative processing complex called Integrator, together with the kinase CDK9. In the presence of CDK9 activity, depletion of Integrator endoribonuclease INTS11 leads to globally increased transcription in the antisense direction, and minor effects in the sense direction. However, CDK9 inhibition reveals that sense transcription is also sensitive to INS11 depletion. The authors suggest that CDK9 activity is stronger in the sense direction, preventing INTS11-mediated premature termination of sense transcrpts.

Strengths:

The combination of acute depletion of the studied factors using degron approaches (important to limit possible secondary effects), together with novel and very sensitive nascent transcriptomics methods POINT and sPOINT is very powerful. The applied spike-in normalization means the analysis is more rigorous than most. Using this methodology allowed the authors to revisit the interesting question of how promoter/transcription directionality is determined.

The data quality appears very good and the fact that both global analysis as well as numerous gene-specific examples are shown makes it convincing.

The manuscript is well written and hence a pleasure to read.

We appreciate this positive assessment.

Weaknesses:

I am slightly worried about the reproducibility of the data - it is unclear to me from the manuscript if and which experiments were performed in replicate (lack of table with genomic experiments and GEO access, mentioned in more detail in below recommendations to authors), and the methods could be more detailed.

All sequencing data was deposited with GEO. Multiple biological replicates were performed for each sequencing experiment.  Bigwig files are presented as a table in the GEO submissions. This data has now been made public.

A separate discussion section would be useful, particularly since the data provided challenge some concepts in the field. How do the authors interpret U1 data from the Dreyfuss lab in light of their results? How about the known PAS-density directionality bias (more PAS present in antisense direction than in sense) - could the differential PAS density be still relevant to transcription directionality?

As suggested, we have expanded our discussion to relate our findings to existing data. We think the results from the Dreyfuss lab are very important and highlight the role of U1 snRNA in enforcing transcriptional elongation.  It does this in part by shielding PAS sequences.  Recent work from our lab also shows that U1 snRNA opposes the Restrictor complex and PNUTS, which otherwise suppress transcription (Estell et al., Mol Cell 2023).  Most recently, the Adelman lab has demonstrated that U1 snRNA generally enhances transcription elongation (Mimoso and Adelman., Mol Cell 2023).  Our work does not challenge and is not inconsistent with these studies.

The role of U1 in opposing PAS-dependent termination inspired the idea that antisense transcriptional termination may utilise PASs.  This was because such regions are rich in AAUAAA and comparatively poor in U1 binding sites. However, our RBBP6 depletion and POINT-seq data suggest that PAS-dependent termination is uncommon in the antisense direction. As such, other mechanisms suppress antisense transcription and influence promoter directionality. In our paper, we propose a major role for the Integrator complex.

We do not completely rule out antisense PAS activity and discuss the prior work that identified polyadenylated antisense transcripts. Nevertheless, this was detected by oligo-dT primed RT-PCR/Northern blotting, which cannot determine the fraction of non-polyadenylated RNA that could result from PAS-independent termination (e.g. by Integrator).  To do that requires an analysis of total nascent transcription as achieved by our POINT-seq.  Based on these experiments, Integrator depletion has a greater impact on antisense transcription than RBBP6 depletion. 

I find that the provided evidence for promoter directionality to be for the most part due to preferential initiation in the sense direction should be stressed more. This is in my eyes the strongest effect and is somehow brushed under the rug.

We agree that this is an important finding and incorporated it into the title and abstract.  As the reviewer recommends, we now highlight it further in the new discussion.

References 12-17 report an effect of Integrator on 5' of protein-coding genes, while data in Figure 2 appears contradictory. Then, experiments in Figure 4 show a global effect of INST11 depletion on promoter-proximal sense transcription. In my opinion, data from the 2.5h time-point of depletion should be shown alongside 1.5h in Figure 2 so that it is clear that the authors found an effect similar to the above references. I find the current presentation somehow misleading.

We are grateful for this suggestion and present new analyses demonstrating that our experiment in Figure 2 concurs with previous findings (Supplemental Figures 2A and B). Our original heatmap (Figure 2E) shows a very strong and general antisense effect of INTS11 loss. On the same scale, the effects in the sense direction are not as apparent, which is also the case using metaplots.  New supplemental figure 2A now shows sense transcription from this experiment in isolation and on a lower scale, demonstrating that a subset of genes shows promoter-proximal increases in transcription following INTS11 depletion.  This is smaller and less general than the antisense effect but consistent with previous findings.  Indeed, our new analysis in supplemental figure 2B shows that affected protein-coding genes are lowly expressed, in line with Hu et al., Mol Cell 2023. This explains why a sense effect is not as apparent by metaplot, for which highly expressed genes contribute the most signal.

As a result of our analyses, we are confident that the apparently larger effect at the 2.5hr timepoint (Figure 4) that we initially reported is due to experimental variability and not greater effects of extended INTS11 depletion. Overlaying the 1.5h and 2.5h datasets (Supplemental Figure 4B) revealed a similar number of affected protein-coding genes with a strong (83%) overlap between the affected genes.  To support this, we performed qPCR on four affected protein-coding transcripts which revealed no significant difference in the level of INTS11 effect after 2.5h vs 1.5h (Supplemental Figure 4C).

We now present data for merged replicates in Figures 2 and 4 which reveal very similar average profiles for -INTS11 vs +INTS11 at both timepoints. Overall, we believe that we have resolved this discrepancy by showing that it amounts to experimental variability and because the most acutely affected protein-coding genes are lowly expressed. As detailed above, we show this in multiple ways (and validate by qPCR) We have revised the text accordingly and removed our original speculation that differences reflected the timeframe of INTS11 loss.

Conclusion/assessment:

This important work substantially advances our understanding of the mechanisms governing the directionality of human promoters. The evidence supporting the claims of the authors is compelling, with among others the use of advanced nascent transcriptomics including spike-in normalization controls and acute protein depletion using degron approaches.

In my opinion, the authors' conclusions are in general well supported.

Not only the manuscript but also the data generated will be useful to the wide community of researchers studying transcriptional regulation. Also, the POINT-derived novel sPOINT method described here is very valuable and can positively impact work in the field.

We are grateful for the reviewers' positive assessment of our study.

Reviewer #2 (Public Review):

Summary:

Eaton and colleagues use targeted protein degradation coupled with nascent transcription mapping to highlight a role for the integrator component INST11 in terminating antisense transcription. They find that upon inhibition of CDK9, INST11 can terminate both antisense and sense transcription - leading to a model whereby INST11 can terminate antisense transcription and the activity of CDK9 protects sense transcription from INST11-mediated termination. They further develop a new method called sPOINT which selectively amplifies nascent 5' capped RNAs and find that transcription initiation is more efficient in the sense direction than in the antisense direction. This is an excellent paper that uses elegant experimental design and innovative technologies to uncover a novel regulatory step in the control of transcriptional directionality.

Strengths:

One of the major strengths of this work is that the authors endogenously tag two of their proteins of interest - RBBP6 and INST11. This tag allows them to rapidly degrade these proteins - increasing the likelihood that any effects they see are primary effects of protein depletion rather than secondary effects. Another strength of this work is that the authors immunoprecipitate RNAPII and sequence extracted full-length RNA (POINT-seq) allowing them to map nascent transcription. A technical advance from this work is the development of sPOINT which allows the selective amplification of 5' capped RNAs < 150 nucleotides, allowing the direction of transcription initiation to be resolved.

We appreciate this positive assessment.

Weaknesses:

While the authors provide strong evidence that INST11 and CDK9 play important roles in determining promoter directionality, their data suggests that when INST11 is degraded and CDK9 is inhibited there remains a bias in favour of sense transcription (Figures 4B and C). This suggests that there are other unknown factors that promote sense transcription over antisense transcription and future work could look to identify these.

We agree that other (so far, unknown) factors promote sense transcription over antisense, which was demonstrated by our short POINT.  We have provided an expanded discussion on this in the revision. In our opinion, demonstrating that sense transcription is driven by preferential initiation in that direction is a key finding and we agree that the identification of the underlying mechanism constitutes an interesting avenue for future study.

Reviewer #3 (Public Review):

Summary:

Using a protein degradation approach, Eaton et al show that INST11 can terminate the sense and anti-sense transcription but higher activity of CDK9 in the sense direction protects it from INS11-dependent termination. They developed sPOINT-seq that detects nascent 5'-capped RNA. The technique allowed them to reveal robust transcription initiation of sense-RNA as compared to anti-sense.

Strengths:

The strength of the paper is the acute degradation of proteins, eliminating the off-target effects. Further, the paper uses elegant approaches such as POINT and sPOINT-seq to measure nascent RNA and 5'-capped short RNA. Together, the combination of these three allowed the authors to make clean interpretations of data.

We appreciate this positive assessment.

Weaknesses:

While the manuscript is well written, the details on the panel are not sufficient. The methods could be elaborated to aid understanding. Additional discussion on how the authors' findings contradict the existing model of anti-sense transcription termination should be added.

We have added more detail to the figure panels, which we hope will help readers to navigate the paper more easily. Specifically, the assay employed for each experiment is indicated in each figure panel. As requested, we provide a new and separate discussion section in the revision.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Congratulations on this important piece of work!

Some specific suggestions.

MAJOR

-The data are not available (Accession "GSE243266" is currently private and is scheduled to be released on Sep 01, 2026.) This should be corrected and as a minimum, the raw sequencing files as well as the spike-in scaled bigwig files should be provided in GEO.

We have made the data public. Raw and bigwig files are provided as part of the GEO upload.

MINOR

- It would be useful for readers if you could include catalog numbers of the reagents used in the study.

We have included this information in our revision.

- A table in experimental procedures summarizing the genomic experiments performed in this study as well as published ones reanalyzed here would be helpful.

This is now provided as part of the resources table.

- It would be easier for reviewers to evaluate the manuscript if the figure legends were included together with the figures on one page. This is now allowed by most journals.

We have used this formatting in the revision.

- Providing some captions for the results sections would be helpful.

We have included subheadings as suggested.

Reviewer #2 (Recommendations For The Authors):

Generally, I would suggest writing the experiment-type above panels where it is not immediately obvious what they are so a reader can appreciate the figures without referencing the legend. E.g. write POINT-seq on Figure 1B just to make it obvious to someone looking at the figures what methodology they are looking at. Likewise, you could write RNAPII ChIP-seq for Supplementary Figures 3D and 3E.

We have carried out this recommendation.

Can a y-axis be indicated on POINT-seq genome browser tracks? This could make them easier to interpret.

Y-axis scales are provided as RPKM as stated in the figure legends.

The authors could address/speculate in the text why there is less POINT-seq signal for the antisense transcript in the treatment condition in Figure 1B? Or could consider including a different example locus where this is not the case for clarity.

Acute depletion of poly(A) factors (like RBBP6) results in a strong read-through beyond the poly(A) signal of protein-coding genes as Figure 1 shows.  However, it also causes a reduction in transcription levels, which can be seen in the figure and is correctly noted by the reviewer in this comment.  We see this with other poly(A) factor depletions (e.g. CPSF73 and CPSF30 – Eaton et al., 2020 and Estell et al., 2021) and other labs have observed this too (e.g for CPSF73-dTAG depletion (Cugusi et al., Mol Cell 2022)).  Plausible reasons include a limited pool of free RNAPII due to impaired transcriptional termination or limited nucleotide availability due to their incorporation within long read-through transcripts. For these reasons, we have retained the example in Figure 1B as a typical representation of the effect. Moreover, the heatmap in Figure 1D fairly represents the spectrum of effects following RBBP6 loss – highlighting the strong read-through beyond poly(A) signals and the marginal antisense effects.

"The established effect of INTS11 at snRNAs was detected in our POINT-seq data and demonstrates the efficacy of this approach (Figure 2B)." The authors could explain this point more clearly in the text and describe the data - e.g. As expected, depletion of INTS11 leads to increased POINT-seq signal at the 3' end of snRNAs, consistent with defects in transcriptional termination. This is highlighted by the RNU5A-1 and RNU5B-1 loci (Figure 2B).

We agree and have added more context to clarify this.

I would suggest adjusting the scale of the heatmap in Figure 2E - I think it would be easier to interpret if the value of 0 was white - with >0 a gradient of orange and <0 a gradient of blue (as is done in Figure 1C). I think making this change would make the point as written in the text clearer i.e. "heatmap analysis demonstrates the dominant impact of INTS11 on antisense versus sense transcription at most promoters (Figure 2E)." I'm assuming most of the sense transcription would be white (more clearly unchanging) when the scale is adjusted.

We agree and have done this. The reviewer is correct that most sense transcription is unchanged by INTS11 loss.  However, as we alluded to in the original submission, a subset of transcripts shows a promoter-proximal increase after INTS11 depletion. We have expanded the analyses of this effect (see responses to other comments) but stress that it is neither as general nor as large as the antisense effect.

The authors make the point that there is mildly increased transcription over the 5' end of some genes upon INST11 depletion and show a track (Supplementary Fig 2A). It is not immediately obvious from the presentation of the meta-analysis in Figure 2D how generalisable this statement is. Perhaps the size of the panel or thickness of the lines in Figure 2D could be adjusted so that the peak of the control (in blue) could be seen. Perhaps an arrow indicating the peak could be added? I'm assuming the peak at the TSS is slightly lower in the control compared to INST11 depletion based on the authors' statement.

We have provided multiple new analyses of this data to highlight where there are promoter-proximal effects of INTS11 loss in the sense direction.  Please see our response to the public review of reviewer 1 and new supplemental figures 2A, 2B, 4A and 4B which highlight the sense transcription increased in the absence of INTS11.

The authors label Figure 4 "Promoters lose their directionality when CDK9 is inhibited" - but in INST11 depleted cells treated with CDK9i they find that there still is a bias towards sense transcription. Suggested edit "Some promoter directionality is lost when CDK9 is inhibited" or similar.

We agree and have made this change.

The authors conclude that INTS11-mediated effects are the result of perturbation of the catalytic activities of Integrator, the authors should perform rescue experiments with the catalytically dead E203Q-INTS11 mutant.

This is a very good suggestion and something we had intended to pursue.  However, as we will describe below (and shown in Supplemental Figure 4G), there were confounding issues with this experiment.

The E203Q mutant of INTS11 is widely used in the literature to test for catalytic functions of INTS11.  However, we have found that this mutation impairs the ability of INTS11 to bind other Integrator modules in cells. Based on co-immunoprecipitation of flag-tagged WT and E203Q derivatives, INTS1 (backbone module), 10 (tail module), and 8 (phosphatase module) all show reduced binding to E203Q vs. WT. Because E203Q INTS11 is defective in forming Integrator complexes, rescue experiments might not fully distinguish the effects of INTS11 activity from those caused by defects in complex assembly. While this may at first seem unexpected, in the analogous 3’ end processing complex, catalytic mutants of CPSF73 (which is highly related to INTS11) negatively affect its interaction with other complex members (Kolev and Steitz, EMBO Reports 2005).

We hypothesise that INTS11 activity is most likely involved in attenuating promoter-proximal transcription, but we cannot formally rule out other explanations and discuss this in our revision. Regardless of how INTS11 attenuates transcription, our main conclusion is on its requirement to terminate antisense transcription whether this involves its cleavage activity or not.

The authors suggest that CDK9 modulates INTS11 activity/assembly and suggest this may be related to SPT5. Is there an effect of CDK9 inhibition on the snRNA's highlighted in Figure 2B?

We believe that snRNAs are different from protein-coding genes concerning CDK9 function. Shona Murphy’s lab previously showed that, unlike protein-coding genes, snRNA transcription is insensitive to CDK9 inhibition, and that snRNA processing is impaired by CDK9 inhibition (Medlin et al., EMBO 2003 and EMBO 2005).  We reproduce these findings by metaanalysis of 15 highly expressed and well-separated snRNAs and by qRT-PCR of unprocessed RNU1-1, RNU5A-1 and RNU7-1 snRNA following CDK9 inhibition. We observe snRNA read-through by POINT-seq following INTS11 loss whether CDK9 is inhibited or not (left panel, below). Note the higher TES proximal signal in CDK9i conditions, which likely reflects the accumulation of unprocessed snRNA as validated by qPCR for three example snRNAs (right panel, below).

Author response image 1.

For Figure 4, would similar results be observed using inhibitors targeting other transcriptional CDKs such as CDK7,12/13?

In response to this suggestion, we analysed four selected protein-coding transcripts (the same 4 that we used to validate the CDK9i results) by qRT-PCR in a background of CDK7 inhibition using the THZ2 compound (new Supplemental Figure 4E).  THZ2 suppresses transcription from these genes as expected.  Interestingly, expression is restored by co-depleting Integrator, recapitulating our findings with CDK9 inhibition.  As CDK7 is the CDK-activating kinase for CDK9, its inhibition will also inhibit CDK9 so THZ2 may simply hit this pathway upstream of where CDK9 inhibitors.  Second, CDK7 may independently shield transcription from INTS11.  We allude to both interesting possibilities.

What happens to the phosphorylation state of anti-sense engaged RNAPII when INTS11 is acutely depleted and/or CDK9 is inhibited? This could be measured by including Ser5 and Ser2 antibodies in the sPOINT-seq assay and complemented with Western Blot analysis.

We have performed the western blot for Ser5 and Ser2 phosphorylation as suggested.  Both signals are mildly enhanced by INTS11 loss, which is consistent with generally increased transcription.  Ser2p is strongly reduced by CDK9 inhibition, which is consistent with the loss of nascent transcription in this condition.  Interestingly, both modifications are partly recovered when INTS11 is depleted in conjunction with CDK9 inhibition. This is consistent with the effects that we see on POINT-seq and shows that the recovered transcription is associated with some phosphorylation of RNAPII CTD.  This presumably reflects the action(s) of kinases that can act redundantly with CDK9.

We have not performed POINT-seq with Ser5p and Ser2p antibodies under these various conditions.  Our rationale is that our existing data uses an antibody that captures all RNAPII (regardless of its phosphorylation status), which we feel most comprehensively assays transcription in either direction. Moreover, the lab of Fei Chen (Hu et al., Mol Cell 2023) recently published Ser5p and Ser2p ChIP-seq following INTS11 loss. By ChIP-seq, they observe a bigger increase in antisense RNAPII occupancy vs. sense providing independent and orthogonal support for our POINT-seq data.  Interestingly, this antisense increase is not paralleled by proportional increases in Ser5p or Ser2p signals.  This suggests that the unattenuated antisense transcription resulting from INTS11 loss does not have high Ser5p or Ser2p.  Since CDK7 and 9 are major Ser5 and 2 kinases, this supports our model that their activity is less prevalent for antisense transcription.  We now discuss these data in our revision.   

The HIV reporter RNA experiments should be performed with the CDK9 inhibitor added to the experimental conditions. Presumably CDK9 inhibition would result in no upregulation of the reporter upon addition of TAT and/or dTAG. Perhaps the amount of TAT should be reduced to still have a dynamic window in which changes can be detected. It is possible that reporter activation is simply at a maximum. Can anti-sense transcription be measured from the reporter?

We have performed the requested CDK9 inhibitor experiment to confirm that TAT-activated transcription from the HIV promoter is CDK9-dependent (new supplemental figure 4F).  Consistent with previous literature on HIV transcription, CDK9 inhibition attenuates TAT-activated transcription.  Importantly, and in line with our other experiments, depletion of INTS11 results in significant restoration of transcription from the HIV promoter when CDK9 is inhibited. Thus, TAT-activated transcription is CDK9-dependent and, as for endogenous genes, CDK9 prevents attenuation by INTS11.

While TAT-activated transcription is high, we do not think that the plasmid is saturated. When considering this question, we revisited previous experiments using this system to study RNA processing (Dye et al., Mol Cell 1999, Cell 2001, Mol Cell 2006). In these cases, mutations in splice sites or polyadenylation sites have a strong effect on RNA processing and transcription around HIV reporter plasmids. Effects on transcription and RNA processing are; therefore, apparent in the appropriate context. In contrast, we find that the complete elimination of INTS11 has no impact on RNA output from the HIV reporter. Our original experiment assessing the impact of INTS11 loss in +TAT conditions used total RNA.  One possibility is that this allows non-nascent RNA to accumulate which might confound our interpretation of INTS11 effects on ongoing transcription.  However, the new experiment described in the paragraph above was performed on chromatin-associated (nascent) RNA to rule this out.  This again shows no impact of INTS11 loss on HIV promoter-derived transcription in the presence of TAT.

To our knowledge, antisense transcription is not routinely assayed from plasmids. They generally employ very strong promoters (e.g. CMV, HIV) to drive sense transcription.  Crucially, their circular nature means that RNAPII going around the plasmid could interfere with antisense transcription coming the other way which does not happen in a linear genomic context. This is why we restricted our use of plasmids to looking at the effects of stimulated CDK9 recruitment (via TAT) on transcription rather than promoter directionality.   

The authors should clearly state how many replicates were performed for the genomics experiments. Ideally, a signal should be quantified and compared statistically rather than relying on average profiles only.

We have stated the replicate numbers for sequencing experiments in the relevant figure legends. All sequencing experiments were performed in at least two biological replicates, but often three. In addition, we validated their key conclusions by qPCR or with orthogonal sequencing approaches.

Reviewer #3 (Recommendations For The Authors):

The authors provide strong evidence in support of their claims.

ChIP-seq of pol2S5 and S2 upon INST11 and CDK9 inhibition will strengthen the observation that transcription in the sense direction is more efficient.

We view the analysis of total RNAPII as the most unbiased way of establishing how much RNAPII is going one way or the other. Importantly, ChIP-seq was very recently performed for Ser2p and Ser5p RNAPII derivatives in the lab of Fei Chen (Hu et al., Mol Cell 2023). Their data shows that loss of INTS11 increases the occupancy of total RNAPII in the antisense direction more than in the sense direction, which is consistent with our finding. Interestingly, the increased antisense RNAPII was not paralleled with an increase in Ser2p or Ser5p. This suggests that, following INTS11 loss, the unattenuated antisense transcription is not associated with full/normal Ser2p or Ser5p. These modifications are normally established by CDK7 and 9; therefore, this published ChIP-seq suggests that they are not fully active on antisense transcription when INTS11 is lost. This supports our overall model that CDK9 (and potentially CDK7 as suggested for a small number of genes in new Supplemental Figure 4E) is more active in the sense direction to prevent INTS11-dependent attenuation. We now discuss these data in our revision.

In Supplementary Figure 2, the eRNA expression increases upon INST11 degradation, I wonder if the effects of this will be appreciated on cognate promoters? Can the authors test some enhancer:promoter pairs?

We noticed that some genes (e.g. MYC) that are regulated by enhancers show reduced transcription in the absence of INTS11. Whilst this could suggest a correlation, the transcription of other genes (e.g. ACTB and GAPDH) is also reduced by INTS11 loss although they are not regulated by enhancers.  A detailed and extensive analysis would be required to establish any link between INTS11-regulated enhancer transcription and the transcription of genes from their cognate promoters.  We agree that this would be interesting, but it seems beyond the scope of our short report on promoter directionality.

Line 111, meta plot was done of 1316 genes. Details on this number should be provided. Overall, the details of methods and analysis need improvement. The layout of panels and labelling on graphs can be improved.

We have now explained the 1316 gene set.  In essence, these are the genes separated from an expressed neighbour by at least 10kb.  This distance was selected because depletion of RBBP6 induces extensive read-through transcription beyond the polyadenylation site of protein-coding genes.  To avoid including genes affected by transcriptional read-through from nearby transcription units we selected those with a 10kb gap between them. This was the only selection criteria so is unlikely to induce any unintended biases. Finally, we have added more information to the figure panels and their legends, which we hope will make our manuscript more accessible.

Reviewer #2 (Public Review):

Summary:

Eaton and colleagues use targeted protein degradation coupled with nascent transcription mapping to highlight a role for the integrator component INST11 in terminating antisense transcription. They find that upon inhibition of CDK9, INST11 can terminate both antisense and sense transcription - leading to a model whereby INST11 can terminate antisense transcription and the activity of CDK9 protects sense transcription from INST11-mediated termination. They further develop a new method called sPOINT which selectively amplifies nascent 5' capped RNAs and find that transcription initiation is more efficient in the sense direction than in the antisense direction. This is an excellent paper which uses elegant experimental design and innovative technologies to uncover a novel regulatory step in the control of transcriptional directionality.

Strengths:

One of the major strengths of this work is that the authors endogenously tag two of their proteins of interest - RBBP6 and INST11. This tag allows them to rapidly degrade these proteins - increasing the likelihood that any effects they see are primary effects of protein depletion rather than secondary effects. Another strength of this work is that the authors immunoprecipitate RNAPII and sequence extracted full length RNA (POINT-seq) allowing them to map nascent transcription. A technical advance from this work is the development of sPOINT which allows the selective amplification of 5' capped RNAs < 150 nucleotides, allowing the direction of transcription initiation to be resolved.

Weaknesses:

While the authors provide strong evidence that INST11 and CDK9 play important roles in determining promoter directionality, their data suggests that when INST11 is degraded and CDK9 is inhibited there remains a bias in favour of sense transcription (Figure 4B and C). This suggests that there are other unknown factors that promote sense transcription over antisense transcription and future work could look to identify these.

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Reply to the reviewers

We would like to thank all reviewers for their detailed and constructive feedback, which substantially helped improve the manuscript. We apologise for the time taken for the revisions, which was partially due to the first author (successfully) writing and defending her PhD thesis in the same time frame. We would like to point out already here that, based on reviewers' feedback, main figure 6 is completely redone and the conclusions of this figure have changed substantially. We no longer suggest RNA chaperoning activity (it was identified as being due to the high concentration of TEV protease, in a control suggested by the reviewers). Instead, our refined assay conditions with lower TEV protease concentration identified ribonuclease activity of membrane-bound full-length 2C, which is consistent with a publication from 2022 (PMID: 35947700).

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Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Evidence, reproducibility, and clarity

Summary:

In this study by Shankar and colleagues, the authors aim to understand the structure and function of the enterovirus 2C protein, a putative viral helicase with AAA+ ATPase activity. Using poliovirus (as a model enterovirus) 2C, the author's propose the protein contains two amphipathic helices (AH1 and AH2) at the N-terminus that are divided by a conserved glycine. Using purified MBP-tagged 2C and N-terminal 2C truncations, their data suggests AH1 is primarily responsible for clustering at membranes, whilst AH2 is the main mediator of 2C oligmerisation and membrane binding. Furthermore, 2C was suggested to be able to recruit RNA to membranes, with a preference for dsRNA, and the author's data implies that the helicase activity of 2C is ATP-independent. Instead, the ATP activity appears to be required for 2C hexamer formation or chaperone activity. The manuscript is generally well written /presented and the author's present very interesting data which raises several questions, some of which require additional experimentation to help support the author's conclusions. Specific comments are as follows.

We thanks the reviewer for the overall positive assessment, as well as the specific comments below.

Major Comments:

1. The authors use four main constructs throughout the paper: full-length 2C, 2C with deletion of AH1 (ΔAH1), 2C with both AH1 and AH2 deleted (ΔMBP) and 2C with an extended N-terminal deletion. From this, the author's draw conclusions on the function of both AH1 and AH2. One of the author's main conclusions is that AH2 is the main mediator of 2C membrane association (e.g., in line 169). However, is it possible to conclude the relative importance of AH1 vs AH2 without testing a construct containing the deletion of AH2 only (ΔAH2)? This should be generated and used alongside this data to fully define the relative importance of AH1 and AH2 in these assay and remove the possibility that the deletion of AH1 changes the structure and/or function of AH2, which could also result in the observed differences.

This was a very good suggestion. We expressed and purified the ΔAH2 protein requested by the reviewer and characterized its oligomeric state as well as its membrane binding. It turns out, as suspected, that the ΔAH2 protein behaves very similarly to the ΔMBD protein (i.e. it does not form higher order oligomers and does not bind membranes). The changes in the manuscript due to this addition are many but can primarily be found in main figures 2-3 and their associated supplementary figures.

Previous structural predictions of 2C do not appear to have two separate AHs at the N-terminus. Are the AH1 and AH2 structures predicted to be formed in the context of the entire 2C protein, 2BC precursors and polyprotein? Are there structural approaches that could provide experimental evidence for two separate AH at the N-terminus?

This is a good point. Previous predictions were not that detailed, partially since they were done in the pre-alphafold era. Unfortunately, we cannot think of a tractable experimental method that could verify the split nature of the amphipathic helix in the only context that would matter: the protein bound to a membrane. A long-term goal would be in situ structures of full-length 2C on membranes using cryo-electron tomography, but our current sample and data sets are not sufficient for this. We added a mention of the long-term need for experimental structures of full-length 2C on lines 315-318 in the discussion.

Why are the 2C dimers (lines 137-138) not apparent on the mass photometry data presented (figure 2)?

Different constructs were measured by mas photometry and SEC-MALS. Also, the required concentration is 100-1000x lower for mass photometry which will affect a dynamic equilibrium in case the same construct were measured by the two methods.

It appeared that binding of ΔMBD-2C was better when POPS is in the membrane (line 174). What is the explanation for this and was this finding significant?

Well spotted. It may mean that 2C has a second, lower affinity membrane-binding site which is charge-dependent somewhere outside the MBD. We now added a mention of this in the discussion, lines 321-323.

From the author's data on lipid drop clustering they conclude ΔAH1 is more effective for clustering, however, the ΔAH1 construct produces pentamers not hexamers (from Figure 2). Is formation of hexamers related to or required for membrane clustering?

ΔAH1 is LESS effective at clustering, not more. As for the mention of pentamers in the original submission: we now think this was an unfortunate choice of words. The mass photometry data for 2C(ΔAH1) could more parsimoniously be interpreted as a mix of hexamers and other (unknown to us) smaller oligomers such as trimers. We have removed all mentions of pentamers.

The replicon data presented in Figure 7 should include a replication-defective control (e.g., polymerase mutant), in order to compare how defective in replication ΔAH1 and ΔMBP deletions are compared to a fully-defective construct. Likewise, deletion of ΔAH1 in this construct is likely to affect processing of the viral polyprotein where several previous studies with picornaviruses have demonstrated that the residues in the P2'-P4' positions can change cleavage efficiency (e.g., PMID: 2542331), or the structure of 2C, leading to the reduction of replication.

Thanks for these good comments. We made the polymerase-dead (GDD-to-GAA) replicon and remeasured it side by side with the 2C replicons. It has a similar luciferase activity indicating that no replication takes place in the 2C deletion replicons. This is shown in the new figure 7. As for the possibility or processing defects, we mentioned this in the original discussion and have now cited the reference suggested by the reviewer in this context (line 324).

How does the author's model of ATPase-independent helicase activity and an APT-dependent required RNA chaperone activity fit with 2 step model for RNA binding and ATPase activity suggested by Yeager et al (PMID: 36399514)?

Acting upon comments from other reviewers, we completely redid the "helicase assay" in the revised manuscript. It turns out that the ATP-independent unwinding activity in the original submission was an artefact of the assay conditions (specifically, of the TEV protease at the higher concentration we used in the old assay). In our improved assay we neither see helicase activity nor ATP-independent RNA chaperoning activity.

Optional major comments that would increase the significance of the work:

All of the optional comments below are exceptionally interesting. But given the long time needed for the several major changes to this manuscript (e.g. the ΔAH2 protein characterization and reoptimisation of the helicase assay) we believe it is more sensible to address them in future studies, for which the 2C reconstitution system can be used.

The preference for dsRNA over ssRNA appears to be quite small (Figure 5d). In the context of a viral infection where ssRNA is likely to outnumber dsRNA at different times during infection is this preference physiologically relevant? In relation to this, what size stretch of dsRNA is required for preference, and could this correspond to cis-acting RNA structural elements, dsRNA as it escapes 3D polymerase or as part of the RF and RI forms (PMID: 9343205)? What is the proposed mechanism of how dsRNA outcompetes membrane tethering of 2C? OPTIONAL The author's study has been conducted in the absence of other viral non-structural proteins. What is the physiological importance of the observations, such as membrane interaction/clustering or RNA binding when presented in the context of the other replication machinery. OPTIONAL Do 2C monomers, dimers and hexamers have different functions in viral replication perhaps at different stages of replication and which of these forms are relevant during viral infection or can they all be detected during infection? Can any suggested separate functional arrangements be separated by genetic complementation experiments? OPTIONAL

Minor comments:

1. The author's appear to interchange between naming/nomenclature of the constructs which makes it confusing to follow (for example, ΔMBD is the same as 2C(41-329) likewise, 2C(Δ115) is sometimes called 2C(116-329)). It would be much easier to follow if the naming of constructs was consistent throughout (unless I am misunderstanding some subtlety in the difference between such constructs).

Thanks very much for spotting this. We have fixed it.

The author's suggest a pentamer arrangement for the ΔAH1 construct, however in the mass photometry data (figure 2D), a hexamer is indicated with the arrow. It would be helpful to change the label to indicate the size of the pentamer where this is being generated, not the hexamer.

As mentioned above, we think the "pentamer" designation of the original manuscript was unfortunate. It is more parsimonious to interpret this as a mix of states, hexamer and undefined snaller.

In most figures, data for full-length 2C, ΔAH1 and ΔMBP is shown. However data for ΔMBP is missing in Figure 4. Using ΔMBP may demonstrate even lower clustering, hinting that AH2 is also involved in this process.

Thanks for this comment. In our view, it can be derived from figure 3 (which shows lack of binding to PC/PE membranes) that the ΔMBD construct would not cluster membranes under the conditions of the assay (clustering requires concomitant binding to two membranes). We now describe our rationale for this on lines 220-222. However, we did include the ΔMBD protein in the new negative staining TEM supplementary figure where it and ΔAH2 show no signs of clustering (figure S10).

I think it would be better for normalise the data in the flotation experiments such that the percentage of 2C in the upper faction is presented as relative to the amount of lipid in the upper fraction (presented in Figure S4).

The change suggested by the reviewer would make it impossible to show the important no-liposome control (leftmost bar in Fig. 3C) in the same plot as the other measurements. We believe that would unnecessarily complicate the figure. Thus, we opted to keep the measurement that are normalised by lipid fluorescence in the supplementary figure. Instead, we now added another mention of this supplementary figure in the legend to main figure 3.

At several places (e.g., lines 232 and 272) the author's refer to "realistic systems". I think the term "physiologically relevant" might be more appropriate.

Agreed and changed throughout.

Line 237: I think "y" is a typo and should read "by".

Thanks. This text was reworked due to the major changes to figure 6.

Reviewer #1 (Significance (Required)):

Significance

I have limited expertise with structural biology but specialise my research on positive-sense RNA virus replication, structure and function. This research is of interest to a broad audience of researchers investigating many positive-sense RNA viruses, which extends beyond the viral family studied here. The work utilises novel techniques to begin to understand the specific roles of 2C in poliovirus replication. The author's data add important incremental new insight into recent studies on viral helicase proteins as referenced in the study, however, a key limitation is understanding the importance/relevance of their observations during a viral infection.

We thanks the reviewer for this positive and nuanced appraisal of our work.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The authors present an alternative assay system to investigate picornavirus 2C, a protein that is tricky to analyze biochemically in its full length form because of an amphipathic helix at the N-terminus. Poliovirus 2C is expressed with an N-terminal MBP tag, a 50kD protein that helps with solubility as is commonly used for 2C investigations. A difference here is that liposomes are included to mimic membranes for 2C attachment. The key findings are that 2C induces clustering of of liposomes, that double stranded RNA binding by 2C impacts this clustering effect and that a free N-terminus (after cleavage of MBP by TEV protease) is needed for RNA binding and an ATP independent (ie non helicase) RNA duplex separation activity.

Major:

In the floatation assays in figure 3 the authors use a system where MBP-2C is fluorophore-labeled with ATTO488 on exposed cysteines. Poliovirus and other enterovirus 2C has a very well characterized zinc finger domain that has cysteines coordinating a zinc ion. Mutation experiments previously showed that these cysteines are necessary for viral replication and 2C stability. Have the authors controlled for disruption of the zinc finger domain by the labelling of cysteines with ATT0488 and checked if the protein remains folded?

We completely agree with the reviewer and apologise for the omission in the original submission. We have now included a Zn content measurement, which shows unchanged levels between labelled and unlabelled 2C protein (Figure S7). Also, we now in the revised manuscript explicitly describe our original reasoning for labelling on native cysteines: the presence of two cysteines which are not necessary for viral replication and which are more solvent exposed-exposed (and thus more likely to be labelled) in the crystal structure of the soluble fragment of 2C (lines 176-181).

In the analysis of the amphipathic helix, did the authors include membranes in their structural predictions o just the free helix? How does inclusion of membranes impact the predictions? In the predictions in Figure D, only 2 of 4 show a kink and there doesn't seem to be a correlation between those that predict a kink or not and whether the hydrophobic side is aligned in Figure S1.

Unfortunately, predicting a protein structure with the interacting membrane is beyond what is currently doable with protein prediction methods (one would have to combine protein structure predictions with molecular dynamics simulations including a membrane). Based on general principles of protein structure, it is likely that there is some flexibility around G17. Thus there may not be a single "kink angle" for any given virus, but we believe that the presence of the kink (and offset hydrophobic surfaces) for a number of viruses lends credibility and robustness to the observation. We added some descriptions of this thinking on lines 126-127.

Based on previous structures of 2C from different viruses the N-terminal amphipathic helix containing region is predicted to localize on one face of the predicted hexametric structure tethering 2C to the membrane. How does the authors hypothesized model explain 2C dependent clustering? is there evidence that 2C hexamers can oligomerize further into dodecamers for example, maintaining separate faces to enable N-terminal interaction with different membranes? What is the distance between the liposomes in figure 4 at the points of density attributed to 2C? How does this compare to the size of 2C determined in previous structural studies? Is it consistent with one hexamer/2 hexamers sitting on top of one another?

These are very interesting questions but we believe it is prudent to limit our speculation at this point. Eventually, we hope that larger data sets of cryo-electron tomography, coupled to subtomogram averaging, may provide a more definitive answer. What we managed to do with our current cryo-electron tomography data set is to estimate the volume of individual protein densities, and from the volume calculate an estimated molecular mass of the individual complexes seen in the tomograms. This correlates very well with 2C hexamers (new figure 4D).

In the Discussion lines 278-285 the authors suggest that having MBP attached may reflect the polyprotein condition. Can they make a construct with MBP-2B2C to examine interaction with liposomes and assess 2C function?

This is a highly relevant question, but the biochemistry of 2BC is even more challenging than 2C, and we are unfortunately nowhere near being able to work with purified 2BC at the moment.

Discussion lines 293-296, the possibility of two different populations of 2C, binding RNA or membranes cannot be excluded, there is much more 2C around late in infection that present in early infection- the model in figure 8 doesn't acknowledge/capture this.

We have changed the model figure such that more 2C is seen later, and the clustering function is also seen late in infection. The original discussion text referred to (which is unchanged) talks about a "preferential role in RNA replication and particle assembly at later time points" specifically for this reason. We hope the new figure 8 is better at conveying this message.

Discussion lines 313-317, the authors don't reference a study where a mutant of foot-and-mouth disease virus 2C lacking the n-terminal amphipathic helix that could bind but not hydrolyze ATP, hexamerized in the presence of RNA that seems pertinent here (PMID: 20507978).

Thanks for the suggestion. However, after the extensive changes we made to the revised to figure 6 based on excellent reviewer comments (essentially: the RNA chaperoning activity turned out to be an artefact, the improved assay shows no sign of RNA unwinding but instead of 2C-mediated ribonuclease activity), these sentence of the original discussion lost most of their context and we opted to remove them.

Some evidence of MBP-2C cleavage by TEV in the different assays used should be presented as this is a major focus of discussion and currently no gels show TEV cleavage is happening.

Thanks for the suggestion - we agree. We now show these in the new supplementary figures S5 and S12.

Reviewer #2 (Significance (Required)):

The work presents an additional methodology to investigate a a protein that has previously been difficult to study. The authors acknowledge that there is still a lot of 2C biology that remains to be discovered.

Thanks, we agree.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

The manuscript provides insights into the role of the N-terminus in membrane binding and its importance in the various functions of 2C.

Major issues

Line 103-119. Is this novel? I thought people had done a lot of bioinformatic analysis of PV 2C (especially Wimmer) who also did mutational work to analyse the importance of various amino acids in the N-terminal helix. I feel like the paper in general, and this section in particular, underplays the large body of work that has been done on the amphipathic helix by various groups.

We apologise if our original manuscript didn't sufficiently acknowledge previous work in the field. In the first sentence of the mentioned paragraph (now lines 112-113) , we did however cite several papers that have previously addressed the amphipathic nature of the N-terminus of 2C. We have now added two more references along the same line, and changed the wording in a way that we hope better bring across that the amphipathic nature per se has been studies before. We would be happy to add more specific references if the reviewer has any suggestions. However, the rest of our analysis IS indeed novel for the following reasons: (i) we show that the amphipathic region is not a simple, single amphipathic helix, but instead has a conserved glycine (helix breaker/destabiliser residue) and two distinct amphipathic stretches before and after this region, (ii) we use alphafold2 (not available at the time of the earlier work) to provide the first reliable structural models of the membrane-binding domain. These models consistently, across several enterovirus 2C proteins, reveal that the hydrophobic surfaces of the first and second amphipathic regions, on either side of the conserved glycine 17, are offset from one another. This lends additional credibility to the distinct nature of these regions which have not previously been identified as such and which we also show in the biochemical assays to be functionally distinct. We have now also added a clarification to the Discussion that the N-terminus of 2C had previously been identified as its membrane-binding domain and we cite references for this. We hope that these changes will sufficiently acknowledge earlier work in the field while clearly pointing out the advance that our paper makes.

Line 132. Did you validate your column with known MW standards? The peak for full length and deltaAH1 look fairly standard for 2C, in that you have a mixture of species. Not sure you can say it is a hexamer when it is such a broad peak. C doesn't really help you too much since the counts at 400 (pentamer) and 480 (hexamer) are almost the same with quite large error bars. Like most people that have worked with 2C I think the best you can say is that you are making some kind of oligomerized 2C that includes hexamer, pentamer, etc. Why no dimer for MBP-2C and MBP-2C(delta AH1) when compared to the other constructs?

We did not calibrate the gel filtration column since the outcome would anyway be a more crude estimate of molecular mass than the mass photometry and SEC-MALS measurements. But we do agree with the reviewer on the broad mass photometry peaks. To address this experimentally, we compared the existing MBP-2C spectra to new recordings on apoferritin, a highly stable homomultimeric protein complex of a similar mass to aa MBP-2C hexamer. The apoferritin mass estimate is overlayed with the full-length MBP-2C in the new figure 2D and the corresponding supplementary figure S3. This indeed shows that the MBP-2C peak is broader, i.e. consistent with a mix of species which are predominantly but not only hexamers. We describe and discuss this on lines 145-149. As for the mention of pentamers in the original submission: we now think this was an unfortunate choice of words. The mass photometry data for 2C(ΔAH1) could more parsimoniously be interpreted as a mix of hexamers and other (unknown to us) smaller oligomers such as trimers. We have removed all mentions of pentamers.

Line 143. Does your data show that there are two amphipathic helices? Bioinformatics suggests it but your experiments just show the importance of the two areas in oligomerization, not that it is forming two helices.

We agree that the choice of words was not idea and have now changed it to "structure predictions indicate" (lines 162).

Figure S2. Your preps are still relatively dirty, which isn't ideal for biochemical assays. Especially lane 3, where you are looking at 50-60% purity. I don't want you to re-run experiments but I think you need to comment on the purity of the protein you are working with. Also I don't like that you removed the top and bottom of the SDS-PAGE. How much protein never entered the gel. Is there a big fat band at 20 kDa? You need to have the full gel here. Did you measure 260 nm of the preps as well to see if you had bound RNA to the 2C?

Thanks for the comment, we agree that our original submission lacked detail in the description of the protein purification. This is now addressed with the new figure S2 which shows size exclusion chromatograms of the fluorophore-labelled proteins (same chromatograms as in figure 2) and the corresponding uncropped gels imaged both in the stain-free channel (showing all proteins) and in the fluorescence channel. The A260/A280 ratio measured for all proteins shows that they are free of nucleic acids at the point of imaging. The protein preps are not 100% homogeneous but we do believe that they are more than 50-60% pure.

Lines 170. Wasn't this done in the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles"? I don't see it referenced. What is novel about the current work when compared to that paper? Any differences?

Thanks for pointing this out. The referenced study worked with a synthesized, isolated peptide corresponding to AH2 (i.e. not with full protein). An amphipathic peptide outside the context of its protein cannot be expected to recapitulate the properties of the entire protein, e.g. since it is not spatially constrained in how it interactis with membranes. As one example (relating to the title of that paper) we don't see full-length 2C protein tubulating membranes the way the isolated peptide does. As for the reviewer's question about novelty, the paper mentioned does not identify the split nature of the amphipathic region, does not consider the role of AH1, does not characterise the membrane-binding properties of full-length 2C with respect to liposome membrane composition and size, does not identify and characterise the membrane clustering properties of 2C, nor its interactions with nucleic acid when bound to a membrane. However, we do agree that we should have cited the paper in our manuscript. We now cite it in the discussion, lines 320-321.

I'm surprised by the lack of electron microscopy (negative stain mostly) of both the oligomerized 2C and the various liposomes. I know the Carlson group is a microscopy group so why the lack of validation using electron microscopy of the various DLS experiments? I know you did cryo-ET for one of the constructs but I think negative stain electron microscopy of other constructs would be useful.

Thanks for the suggestion. As suggested, we have now expanded the analysis with negative staining EM of several more constructs studied by DLS. It can be found in the new supplementary figure S10.

Figure 4C. What evidence is there that this is 2C apart from you added it to the liposomes? It also comes back to the relative impurity of your protein prep. Could this be E.coli contamination?

Thanks for this comment. We have now added a new supplementary figure (S5) showing SDS-PAGE gels of the reactions used for flotation and DLS assays - which are identical to the cryo-ET samples. In addition, we estimated the molecular mass of the individual, putative 2C desities in the cryo-electron tomograms by measuring their volume. This analysis, which can be found in the new figure 4D, shows that the estimated mass of individual protein densities is consistent with a hexamer of full-length 2C. In addition, we mention in the discussion the long-term need to determine high-resolution structures of membrane-bound 2C using cryo-ET and subtomogram averaging (lines 315-318).

Figure 8. Is this model supported by the data in this paper? Your cryo-ET says that 2C is there but that isn't supported by any other data. How is the dsRNA protected from the innate immune system in this model? is it just sat out in the cytosol? How is the nascent ssRNA packeged into the capsid? Is there competition between the dsRNA and capsid for 2C binding (which your model suggests)? I know it sounds like I am being overly critical of the model but in my opinion there are still too many unanswered questions in the field to come up with a half decent model.

Thanks for this comment. We are the first to agree that our understanding of the roles of 2C is far from complete! We should have been more clear that the model figure represents some of the roles of 2C identified to date, and does not claim to be complete. However we do feel that a model figure serves a purpose of putting our findings into a context, and also providing testable hypotheses for future research . As for the question, some of the roles of 2C shown in the model figure (in particular, particle assembly) are rather supported but earlier work of ourselves and others. We have now produced a new model figure and changed the figure legend to better reflect the incompleteness of the current understanding, and the origin of the different parts of the model figure. In addition, we extended the final paragraph of the discussion (which lists still-unknown aspects of 2C) with the reviewer's mention of dsRNA shielding from innate immunity (lines 374-375). The other aspects mentioned by the reviewer as not yet fully understood are already mentioned in that paragraph.

Minor issues

Lines 43-45: I feel like you underplay the success of the poliovirus vaccination program. Approximately 30 of WPV1 in 2022 and the full eradication of WPV2 and 3. Vaccine derived polio is still an issue but even that is relatively low compared to where the world was in the 1950s.

We agree that the previous wording was not ideal. We replaced it and added another recent reference - related to the type 2 vaccine switch (lines 47-49).

Line 66. I agree there are 11 individual proteins but I feel like this leaves out the fact that some of the uncleaved precursors appear to have some functions, for example 2BC.

Good point. We have now added a mention of 2BC and the fact that it has distinct functions to the introduction (lines 70-71). 2BC is also mentioned in the legend of the model figure (figure 8).

Line 56: LD needs to be defined.

Well spotted thanks. Since the abbreviation was not used anywhere else we opted to spell it out instead (line 59).

Line 75. I think you have misrepresented Xia et al here. They clearly say that in their study that they show helicase and chaperone activity. I never managed to repeat that work but you should still report what they claim. One major thing is that they used insect expressed protein, whereas most people (including myself and in the paper under review) use E.coli expressed protein. Do post translational modifications play an important role in function?

You are right that the reference to their paper for this statement was incorrect. We have now made this part of the introduction more explicit (lines 82-83) and we also in the new discussion mention the possibility of e.g. post-translational modifications affecting 2C helicase activity, under reference to Xia et al (lines 359-361)

Line 103. Need to make it clear here it is poliovirus 2C.

Thanks, we added it (line 112).

Line 135. I assume you mean kDa instead of uM?

It should actually be μM. It is the solution concentration at which the assay was performed. We added some words to clarify this (line 154).

Figure 3. What do you mean by "Only 2C"? Is that MBP-2C? Maybe I am reading the data wrong but adding TEV does nothing? How do you know TEV is removing the MBP? It looks like MBP-2C binds to the liposomes just the same as cleaved MBP-2C. I see in line 165 you acknowledge this. Could an alternative conclusion for line 168 be that MBP isn't being cleaved off but that AH2 is too small to be exposed in that construct? Did you do that construct without MBP being cleaved? I think you need to confirm that MBP is being cleaved off.

Thanks for spotting this mistake. It should indeed be MBP-2C (in the absence of liposomes). We corrected figure 3. Also, in response to this comment and similar ones, we have now added a new supplementary figure showing SDS-PAGE gels of the reaction loaded onto flotation assays and DLS (figure S5). It shows that MBP-2C is cleaved.

Line 184. Is there a reason you use the 2019 paper as a reference instead of the far earlier Bienz et al papers? I'd suggest they are the seminal papers on 2C membrane association. Once again how is this work different from the recent "An Amphipathic Alpha-Helix Domain from Poliovirus 2C Protein Tubulate Lipid Vesicles" paper?

See our response above of the paper mentioned here (which we have now cited). As for why we cite the 2019 paper here: our statement pertains specifically to the contact sites between lipid droplets and replication organelles, not to the membrane binding of 2C per se. We have now added a more general mention of membrane remodelling by non-structural proteins in the introduction, where we cite on of the Bienz papers (lines 75-77).

Figure 5D. So only 1-3% of RNA is found in the upper fraction? Is that significant enough to say that dsRNA was recruited significantly more than ssRNA? How confident are you in your quantification of the starting amounts of RNA?

We agree that the fraction is low, however, the fluorescence signal is very clearly above background. We are thus confident in the measurement. The low percentage at the end of the experiment likely has a simple physico-chemical explanation: in a dynamic equilibrium in a density gradient, whatever RNA dissociates during the run will migrate away from the 2C-vesicle fraction and not be able to rebind. We still tried to address this concern by a complementary experiment where we used fluorescence anisotropy to measure binding of RNA to 2C on vesicles. While the measurements showed the same tendency, they curves were not clean enough to be published, which we think is due to the complex system with 2C bound to vesicles and clusters of vesicles. Still, in view of the relatively low percentage of measured recruitment we opted to adjust the paper title and the title of figure 5 (including the subheading related to figure 5) to put less emphasis on the dsRNA recruitment.

Line 223. Any idea why the MBP needs to be cleaved off? Clearly the MDB is accessible or it would not bind to the liposomes.

Since we have no data directly supporting this we prefer not to speculate in the paper. But one guess would be that the NTD of 2C, as implicated by previous publications, has a dual role in membrane binding and RNA binding. It may be that it can bind membrane while conjugated to MBP, but needs MBP to be removed in order to simultaneously bind membrane and RNA.

Line 237: missing "b" in "by"

Thanks. This paragraph was rewritten in the light of the changes to figure 6.

Figure 6. I don't fully understand the results here. Earlier you showed that the delta MBD didn't really bind SUV. So presumably it isn't really membrane bound. Why does it have similar activity to full-length MBP in your helicase assay if membrane is important? Did you do SUV and TEV protease only control?

We are very grateful to this reviewer (and others) for pointing out the need for a TEV control. When performing the control, we found that the TEV protease, at the high concentrations initially used, surprisingly had an artefactual RNA chaperone-like effect on its own. We then proceeded to titrate down the TEV protease concentration to the point where it no longer interfered. At this TEV protease concentration, although 2C was substantially cleaved (see the new supplementary figure S12), we could no longer detect an RNA chaperone activity. Thus, the contents of the new figure 6, and its conclusions, have been substantially changed. We now focused our attention on the remaining effect that 2C has on RNA: single-strand ribonuclease activity. These experiments were all conducted in the presence of RNase inhibitors, and the presence of Mg2+-dependent ribonuclease activity parallels a recent publication that found this for truncated 2C from hepatitis A and several enteroviruses.

Line 257: "staring"?

Thanks, corrected. A staring glycine would indeed be something strange.

Line 336. Need to change the u to mu.

Thanks, corrected.

Any discussion on your observation in Figure 1D that EV71 and CVB3 don't appear to have AH1 and AH2 or do you think that the domains are conserved across the different viruses?

Thanks for bringing this up. Based on this and a comment from another reviewer, we have now clarified our thinking around this. Since the glycine will introduce some flexibility between AH1 and AH2, we cannot say from the single alphafold predictions that this is THE kink angle. The presence of the kink in the predictions of several MBDs lends more credibility to the robustness of the observation, but most importantly the hydrophobic surfaces in AH1 and AH2 are non-aligned for ALL sequences we looked at. This is now described on lines 126-128.

Table 1 (and possibly elsewhere): an apostrophe is not the prime symbol. 5' compared to 5′.

Thanks, we corrected this throughout.

Line 702 "and" should be "an".

Thanks, corrected.

I couldn't open one of the movies (140844_0_supp_2820374_a2g272.avi).

Sorry to hear this, we will check the movie again.

Reviewer #3 (Significance (Required)):

Overall I liked the paper and is worth publishing. One of the issues in the 2C field is the difficulty in making pure 2C and carrying out in vitro assays that correlate with what is observed in the natural infection. I think this paper suffers from similar struggles with a 2C preparation that doesn't appear that pure. I think it also suffers from not having 2C from a wild-type infection. I don't think that it is feasible to get that kind of 2C but by once again using a recombinant protein from E.coli we are left with another manuscript that provides conflicting evidence of the functions of 2C without a definitive answer. The experiments are well done, although are missing some controls and the manuscript is laid out in a logical manner and is relatively easy to follow.

We thanks the reviewer for these comments. We believe that we have now provided better information regarding the purification of the recombinant 2C protein, and we do think that the controls present in the original manuscript and the revised manuscript alleviate the concerns about lack of specificity. Of course, isolating 2C vesicles from wildtype infection would be another interesting way of approaching its function, but such an approach would come with its own set of challenges related e.g. to the presence of confounding host factors.

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

This is an interesting manuscript that reports the development of an in vitro membrane assay for probing the biochemical functions of the enterovirus 2C protein. The technique is interesting because it can be applied to 2C proteins from other members of the picornavirus family, an important group of mammalian pathogens. It has the capacity to probe different functions (e.g. membrane clustering, ATPase activity, RNA-binding and manipulation activities).

Overall, the manuscript is well written and gives a clear account of the work undertaken. It adds insight to previous studies of enteroviral (and picornaviral) 2C proteins, providing confirmation of some earlier work in a more physiological context and some new insights, particularly into the membrane and RNA binding aspects of 2C.

That said, there are a number of places where some amendment of the claims made is required to provide a more precise statement of the findings of this work. These are listed below.

We thank the reviewer for this positive feedback on our work, as well as for the specific comments below.

Line 21 (Abstract) - The authors claim to have shown that a conserved glycine divides the N-terminal membrane-binding domain into 2 helices. I would suggest instead what they have produced are computational predictions that this is the case - some way short of an experimental demonstration. Sequence analysis predicts helical secondary structure in the N-terminus and indeed Alphafold2 also predicts a helical structure, but these predictions require experimental verification. The authors should therefore rewrite sections that claim to have shown the presence of 2 helices. In doing so, they should perhaps also comment on the fact that Alphafold2 does not predict 2 helices in this region for all enteroviruses (see Fig 1D). Moreover, the sequence analysis in Fig. S1 shows the presence of two Lys residues in the segment 17-38; it would be interesting for the reader to have these indicated in the figures showing the Alphafold2 prediction - do they in any way interrupt the hydrophobic face of the predicted helix?

Thanks very much for this comment, which is in line with what other reviewers also wrote. We agree, and changed the abstract sentence. We have also rewritten the manuscripts in several places to address the limits of structure predictions and the eventual need for an experimental structure of full-length membrane-bound 2C (lines 126-128 and 315-318).

Line 82 (Introduction) - The authors write that the membrane binding domain (MBD) of poliovirus has been shown to mediate hexamerisation, citing Adams et al (2009) - reference 43. However, that is not what this paper shows. Rather it provides evidence of aggregation of an MBP-2C fusion protein into forms that ranged from tetramer to octamer, but no evidence that these aggregates assume functional forms (e.g. the presumed hexameric ring structure characteristic of the AAA+ ATPase family to which 2C belongs). As far as I am aware the first demonstration of hexameric ring formation by a picornaviral 2C protein was for the 2C of foot-and-mouth disease virus (see Sweeney et al, JBC, 2010). Although this is not an enterovirus, this finding was later confirmed for Echovirus 30 (ref 51). I should declare an interest here: the Sweeney paper is from my lab. I will leave it to the editor and the authors to determine how to write a more precise account of the early observations of hexamerisation in picornaviral and enteroviral 2C proteins.

Thanks very much for this insightful comment. As a response to this and other similar comments, we are much more cautious about our wording in the revised manuscript (see also response to comment below. In the part of the introduction discussed here (now lines 89-91) we now use the original wording of the Adams paper ("oligomerization"). In the context of that new text we didn't feel that Sweeney et al paper was a suitable reference, but we now cite it in the later mention of 2C's oligomeric/hexameric state in the first part of the Results (lines 137-138 ).

Line 132 - the authors used mass photometry to investigate oligomeric forms of their MBP-2C constructs and state that for the full length 2C protein "the high-mass peak closely corresponds to a hexamer". While it is true that the peak shown in Fig 2C aligns with the expected MW for an MBP-2C hexamer, the peak is very broad, indicative of the presence of other oligomeric states with lower and higher numbers of monomers. This should be commented on. Indeed, the finding seems to echo the early findings of Adams et al (ref 43) with poliovirus MBP-2C.

Thanks for this comment, which was also made by another reviewer. We cite here what we replied to that reviewer

...we do agree with the reviewer on the broad mass photometry peaks. To address this experimentally, we compared the existing MBP-2C spectra to new recordings on apoferritin, a highly stable homomultimeric protein complex of a similar mass to aa MBP-2C hexamer. The apoferritin mass estimate is overlayed with the full-length MBP-2C in the new figure 2D and the corresponding supplementary figure S3. This indeed shows that the MBP-2C peak is broader, i.e. consistent with a mix of species which are predominantly but not only hexamers. We describe and discuss this on lines 145-149.

Line 143 - for the reasons given above, this summary paragraph represents too strong a statement of what has been observed.

We agree, and changed the paragraph. It now only refers to "oligomerization" (lines 162-164).

Line 197 - I note that the authors did not test the membrane clustering capabilities of the 2C(41-329) construct. Although the 2C(deltaAH1) construct had already shown a significant loss of activity, the shorter construct could still have been a useful control. I don't think it is necessary for this experiment to be done, but if the authors have a rationale for not performing the experiment, perhaps they could include it in a revised manuscript.

Thanks for the suggestion. The rationale is that a protein that doesn't bind a membrane in the first place will also not cluster them (an action that requires binding TWO membranes). We now describe our reasoning on lines 220-222. Nevertheless, we did test these constructs in the new supplementary figure showing negative staining TEM (figure S10).

Line 223 - typo. I think you mean MBD.

Thanks! Corrected (now line 257).

Line 215 - the authors observed that the presence of ssDNA reduced membrane clustering and conclude that "nucleic acid binding partially outcompetes membrane tethering activity". Two things: (1) although I agree is it likely that this effect is due to binding of DNA to 2C, binding has not been demonstrated experimentally so the authors should be more careful in how they describe their result; (2) there is no data presented to show that RNA binding reduces membrane tethering so at best I think the conclusion has to be that the data are consistent with the notion that DNA binding reduces membrane tethering. It would of course be interesting to see the effects of RNA and I'm curious to know why the assay was not performed.

Thanks for the comment. The honest answer is that previous publications (primarily Yeager et al, NAR 2022) convinced us that the outcome should be near-identical with DNA, so we chose DNA oligos because they are cheaper and easier to work with. But we agree with the reviewer that RNA is of course more relevant. We now present a comparison at 5 μM of ssDNA and ssRNA, which in fact shows a slightly stronger effect on membrane clustering by RNA (figure 5C). In the light of this additional experiment, we feel that some of the text changes suggested by the reviewer may no longer be necessary.

Line 237 - typo: by, not y

Thanks. In the light of the extensive changes to figure 6 this text was removed.

Line 284 - the authors claim that 2C may only bind RNA after the N-terminus is liberated from 2B in infected cells, since cleavage of the MBP tag from their construct was needed for 2C to bind RNA in their in vitro assay. However, this does not automatically follow given the large structural differences between MBP and 2B and the fact that the authors have not tested the RNA binding capacity of a 2BC fusion protein. Their claim here is too strong and should be re-written.

We agree, and have added a discussion along the lines suggested by the reviewer (line 330-332).

Line 293 - The authors speculate that RNA binding might cause a shift between the membrane clustering activities and the role of the protein in RNA replication. However, since they have not shown that RNA binding reduces membrane clustering, this is too speculative.

In our revised manuscript we have studied the effect of RNA on membrane binding, thus we feel that this text is relevant in the context of the extended experiments.

Line 299-317 - within this discussion is the assumption that in their assay system enterovirus 2C adopts the ring-like hexameric structure typical of AAA+ ATPases. While I agree this may well be the case, it has not been demonstrated in this study so the authors should make clear they are making this assumption. The same applies to the legend of Fig 8.

This part of the discussion was extensively rewritten after our changes to figure 6. We now only refer to "hexamer" once in the corresponding part of the discussion, where we talk about structural models of hexamers produced by other groups who have crystallised fragments of 2C. There we believe we should refer to hexamers to accurately cite their work.

We are not sure what the reviewer is referring to when it comes to the legend for figure 8: the original legend had no reference to the oligomeric state of 2C. We have substantially changed figure 8 and its legend and the new figure and legend make no references to hexamers/oligomers.

Line 302 - the authors claim to have shown that 2C is 'selective' for dsRNA. I think at best they have shown a preference for binding dsRNA over ssRNA.

We changed the wording (line 349). We have also changed the title of the paper where we removed "double-stranded".

Line 313 - The sentence starting "A recent study..." needs a reference.

The revised discussion no longer contains this sentence.

Line 332 - the full sequence of the synthetic gene used in this study should be made available (e.g. as supplementary information or a deposited sequence with an accession number). This is a critical point before the paper can be published.

We will of course submit the sequences as supplementary data. Thanks for the reminder.

Line 362 - the authors should describe the likely points of attachment of fluorophores and comment on how this labelling might affect 2C function.

Thanks for the comment. In response to this and a similar comment from another reviewer, we discuss the likely conjugation site of the fluorophore (lines 175-181), and also (due to the proximity to the Zn finger) provide a new measurement showing that equal amounts of Zn can be detected in the labelled and unlabelled protein (figure S7).

Line 372 - Is a single protein standard (BSA) sufficient to calibrate the SEC-MALS system?

Yes, it is the recommended procedure (note that SEC-MALS is only dependent on scattering, not elution volumes etc).

Reviewer #4 (Significance (Required)):

As stated above this is an interesting study that presents findings from a novel assay. It will be of interest to picornavirologists and the wider community interested in the mechanisms of AAA+ ATPases.

We thanks the reviewer for this positive appraisal of our work.

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Referee #4

Evidence, reproducibility and clarity

This is an interesting manuscript that reports the development of an in vitro membrane assay for probing the biochemical functions of the enterovirus 2C protein. The technique is interesting because it can be applied to 2C proteins from other members of the picornavirus family, an important group of mammalian pathogens. It has the capacity to probe different functions (e.g. membrane clustering, ATPase activity, RNA-binding and manipulation activities).

Overall, the manuscript is well written and gives a clear account of the work undertaken. It adds insight to previous studies of enteroviral (and picornaviral) 2C proteins, providing confirmation of some earlier work in a more physiological context and some new insights, particularly into the membrane and RNA binding aspects of 2C.

That said, there are a number of places where some amendment of the claims made is required to provide a more precise statement of the findings of this work. These are listed below.

Line 21 (Abstract) - The authors claim to have shown that a conserved glycine divides the N-terminal membrane-binding domain into 2 helices. I would suggest instead what they have produced are computational predictions that this is the case - some way short of an experimental demonstration. Sequence analysis predicts helical secondary structure in the N-terminus and indeed Alphafold2 also predicts a helical structure, but these predictions require experimental verification. The authors should therefore rewrite sections that claim to have shown the presence of 2 helices. In doing so, they should perhaps also comment on the fact that Alphafold2 does not predict 2 helices in this region for all enteroviruses (see Fig 1D). Moreover, the sequence analysis in Fig. S1 shows the presence of two Lys residues in the segment 17-38; it would be interesting for the reader to have these indicated in the figures showing the Alphafold2 prediction - do they in any way interrupt the hydrophobic face of the predicted helix?

Line 82 (Introduction) - The authors write that the membrane binding domain (MBD) of poliovirus has been shown to mediate hexamerisation, citing Adams et al (2009) - reference 43. However, that is not what this paper shows. Rather it provides evidence of aggregation of an MBP-2C fusion protein into forms that ranged from tetramer to octamer, but no evidence that these aggregates assume functional forms (e.g. the presumed hexameric ring structure characteristic of the AAA+ ATPase family to which 2C belongs). As far as I am aware the first demonstration of hexameric ring formation by a picornaviral 2C protein was for the 2C of foot-and-mouth disease virus (see Sweeney et al, JBC, 2010). Although this is not an enterovirus, this finding was later confirmed for Echovirus 30 (ref 51). I should declare an interest here: the Sweeney paper is from my lab. I will leave it to the editor and the authors to determine how to write a more precise account of the early observations of hexamerisation in picornaviral and enteroviral 2C proteins. Line 132 - the authors used mass photometry to investigate oligomeric forms of their MBP-2C constructs and state that for the full length 2C protein "the high-mass peak closely corresponds to a hexamer". While it is true that the peak shown in Fig 2C aligns with the expected MW for an MBP-2C hexamer, the peak is very broad, indicative of the presence of other oligomeric states with lower and higher numbers of monomers. This should be commented on. Indeed, the finding seems to echo the early findings of Adams et al (ref 43) with poliovirus MBP-2C.

Line 143 - for the reasons given above, this summary paragraph represents too strong a statement of what has been observed.

Line 197 - I note that the authors did not test the membrane clustering capabilities of the 2C(41-329) construct. Although the 2C(deltaAH1) construct had already shown a significant loss of activity, the shorter construct could still have been a useful control. I don't think it is necessary for this experiment to be done, but if the authors have a rationale for not performing the experiment, perhaps they could include it in a revised manuscript.

Line 223 - typo. I think you mean MBD.

Line 215 - the authors observed that the presence of ssDNA reduced membrane clustering and conclude that "nucleic acid binding partially outcompetes membrane tethering activity". Two things: (1) although I agree is it likely that this effect is due to binding of DNA to 2C, binding has not been demonstrated experimentally so the authors should be more careful in how they describe their result; (2) there is no data presented to show that RNA binding reduces membrane tethering so at best I think the conclusion has to be that the data are consistent with the notion that DNA binding reduces membrane tethering. It would of course be interesting to see the effects of RNA and I'm curious to know why the assay was not performed.

Line 237 - typo: by, not y

Line 284 - the authors claim that 2C may only bind RNA after the N-terminus is liberated from 2B in infected cells, since cleavage of the MBP tag from their construct was needed for 2C to bind RNA in their in vitro assay. However, this does not automatically follow given the large structural differences between MBP and 2B and the fact that the authors have not tested the RNA binding capacity of a 2BC fusion protein. Their claim here is too strong and should be re-written.

Line 293 - The authors speculate that RNA binding might cause a shift between the membrane clustering activities and the role of the protein in RNA replication. However, since they have not shown that RNA binding reduces membrane clustering, this is too speculative.

Line 299-317 - within this discussion is the assumption that in their assay system enterovirus 2C adopts the ring-like hexameric structure typical of AAA+ ATPases. While I agree this may well be the case, it has not been demonstrated in this study so the authors should make clear they are making this assumption. The same applies to the legend of Fig 8.

Line 302 - the authors claim to have shown that 2C is 'selective' for dsRNA. I think at best they have shown a preference for binding dsRNA over ssRNA.

Line 313 - The sentence starting "A recent study..." needs a reference.

Line 332 - the full sequence of the synthetic gene used in this study should be made available (e.g. as supplementary information or a deposited sequence with an accession number). This is a critical point before the paper can be published.

Line 362 - the authors should describe the likely points of attachment of fluorophores and comment on how this labelling might affect 2C function.

Line 372 - Is a single protein standard (BSA) sufficient to calibrate the SEC-MALS system?

Significance

As stated above this is an interesting study that presents findings from a novel assay. It will be of interest to picornavirologists and the wider community interested in the mechanisms of AAA+ ATPases.

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Referee #2

Evidence, reproducibility and clarity

The authors present an alternative assay system to investigate picornavirus 2C, a protein that is tricky to analyze biochemically in its full length form because of an amphipathic helix at the N-terminus. Poliovirus 2C is expressed with an N-terminal MBP tag, a 50kD protein that helps with solubility as is commonly used for 2C investigations. A difference here is that liposomes are included to mimic membranes for 2C attachment. The key findings are that 2C induces clustering of of liposomes, that double stranded RNA binding by 2C impacts this clustering effect and that a free N-terminus (after cleavage of MBP by TEV protease) is needed for RNA binding and an ATP independent (ie non helicase) RNA duplex separation activity.

Major:

In the floatation assays in figure 3 the authors use a system where MBP-2C is fluorophore-labeled with ATTO488 on exposed cysteines. Poliovirus and other enterovirus 2C has a very well characterized zinc finger domain that has cysteines coordinating a zinc ion. Mutation experiments previously showed that these cysteines are necessary for viral replication and 2C stability. Have the authors controlled for disruption of the zinc finger domain by the labelling of cysteines with ATT0488 and checked if the protein remains folded?

In the analysis of the amphipathic helix, did the authors include membranes in their structural predictions o just the free helix? How does inclusion of membranes impact the predictions? In the predictions in Figure D, only 2 of 4 show a kink and there doesn't seem to be a correlation between those that predict a kink or not and whether the hydrophobic side is aligned in Figure S1.

Based on previous structures of 2C from different viruses the N-terminal amphipathic helix containing region is predicted to localize on one face of the predicted hexametric structure tethering 2C to the membrane. How does the authors hypothesized model explain 2C dependent clustering? is there evidence that 2C hexamers can oligomerize further into dodecamers for example, maintaining separate faces to enable N-terminal interaction with different membranes? What is the distance between the liposomes in figure 4 at the points of density attributed to 2C? How does this compare to the size of 2C determined in previous structural studies? Is it consistent with one hexamer/2 hexamers sitting on top of one another?

In the Discussion lines 278-285 the authors suggest that having MBP attached may reflect the polyprotein condition. Can they make a construct with MBP-2B2C to examine interaction with liposomes and assess 2C function?

Discussion lines 293-296, the possibility of two different populations of 2C, binding RNA or membranes cannot be excluded, there is much more 2C around late in infection that present in early infection- the model in figure 8 doesn't acknowledge/capture this.

Discussion lines 313-317, the authors don't reference a study where a mutant of foot-and-mouth disease virus 2C lacking the n-terminal amphipathic helix that could bind but not hydrolyze ATP, hexamerized in the presence of RNA that seems pertinent here (PMID: 20507978).

Some evidence of MBP-2C cleavage by TEV in the different assays used should be presented as this is a major focus of discussion and currently no gels show TEV cleavage is happening.

Significance

The work presents an additional methodology to investigate a a protein that has previously been difficult to study. The authors acknowledge that there is still a lot of 2C biology that remains to be discovered.

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Reply to the reviewers

1. General Statements [optional]

We thank all the reviewers for their constructive and critical comments. We provide a point-by-point response to the reviewers' comments, as detailed below. By responding to them, we believe that our revised manuscript will significantly improve so that it will be of interest for researchers in the field of cell biology, signaling pathways, physiology and nutrition.

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Summary: The manuscript by Yusuke Toyoda and co-workers describes that the phosphorylation of the a-arrestin Aly3 downstream of TORC2 and GAD8 (AKT) negatively regulates endocytosis of the hexose transporter Ght5 in S.pombe under glucose limiting growth conditions.

To arrive at these conclusions, the researchers define a set of redundant c-terminal phosphorylation sites in Aly3 that are downstream by GAD8. Phosphorylation of these sites reduces Ght5 ubiquitination and endocytosis. For ubiquitination, Aly3 interacts with the ubiquitin ligases Pub1/3.

We thank the reviewer for his/her time and reporting advantages and issues of this study.

Major points:

Figure 3B: it would be interesting to compare Aly3 migration pattern (and hence potential phosphorylation) under glucose replete or limiting growth conditions. Can the authors provide direct evidence that Aly3 phosphorylation changes in response to glucose availability? Also please explain the 'smear' in lanes aly3(4th Ala), aly3(4th Ala, A584S), aly3(4th Ala, A586T).

While it is an interesting possibility that the Aly3 migration pattern changes in response to glucose concentrations in medium, we think that this is unlikely and that examining this possibility is beyond the scope of this study. Because a phospho-proteomics study reported by Dr. Paul Nurse's lab showed Tor1-dependent phosphorylation of Aly3 at S584 under high glucose (2%) conditions (Mak et al, EMBO J, 2021), the Aly3 phosphorylation (migration) pattern is likely to be constant regardless of glucose conditions. Glucose conditions affect the mRNA and protein levels of Ght5, but supposedly not its endocytosis to vacuoles (Saitoh et al, Mol Biol Cell, 2015; Toyoda et al, J Cell Sci, 2021).

As for the smear in Aly3(4th A), Aly3(4th A;A584S), Aly3(4th A; A586T), we suspect that some posttranslational modification occurs on these mutant Aly3 proteins, but the identity of the modification is unclear. We did not mention the smear signals in the original manuscript, because the presence or absence of the smear did not necessarily correlate with cell proliferation in low glucose and thus vacuolar localization of Ght5, which is the main topic of this study. In the revised manuscript, we will mention this point more clearly.

Figure 4: Ght5 localization should be analyzed + / - thiamine and in media with different glucose levels. Also, a co-localization with a vacuolar marker (FM4-64) would be nice (but not necessary). Ideally, the authors should add WB analysis of Ght5 turnover to complement the imaging data. Also, would it be possible to measure directly the effects on glucose uptake (using eg: 2-NBDG).

In this revision, we plan to observe Ght5 localization under the conditions indicated by the reviewer (+/- thiamine and high/low glucose levels) to unambiguously show that the vacuolar localization of Ght5 occurs in a manner dependent solely on expression of the mutant Aly3 protein.

We thank the reviewer for the suggestion of co-staining with FM4-64. Indeed, because we previously reported that the cytoplasmic Ght5 signals were surrounded by FM4-64 signals in the TORC2-deficient tor1Δ mutant cells (Toyoda et al, J Cell Sci, 2021), the cytoplasmic Ght5-GFP signals in Figure 4 are very likely to co-localize with vacuoles. We will modify the text to clarify this point.

As suggested, we plan to add Western blot analysis of Ght5 turnover in Aly3-expressing cells, to complement the imaging data (Figure 4) in the revised manuscript. Persistent appearance of GFP in Western blot would be a good support for vacuolar transport of Ght5-GFP.

While regulation of glucose uptake is an important issue, measurement of Ght5-dependent glucose uptake using 2-NBDG was very difficult in our hands. Another reviewer (Reviewer #2) also mentioned the difficulty of this measurement in the Referees cross-commenting section.

Figure 5: Given the localization of Ght5 shown in Figure 4, I'm surprised that it is possible in to detect full length Ght5, and its ubiquitination in the phospho-mutants of Aly3. I expected that the majority of Ght5 would be constitutively degraded, and that one would need to prevent endocytosis and/or vacuolar degradation to detect full length Ght5 and ubiquitination. Please explain the discrepancy. Also it seems that the quantification in B was performed on a single experiment.

As the aim of Figure 5 is to compare the ubiquitinated species of Ght5 among the samples expressing different species of Aly3, the loading amount of each sample was adjusted so that the abundance of immunoprecipitated Ght5 is same across them. Therefore, as the reviewer points out, before the adjustment, abundance of the full-length Ght5 might be different in these samples. In the revised manuscript, we will add explanation on this point; why the anti-GFP blot of Figure 5A has the similar intensities in those samples.

In the revised manuscript, we will add two additional replicates of the same experiment as Figure 5 in Supplementary material to show reproducibility of the result.

Figure 6: Which PPxY motif of Aly3 is used for interaction with Pub1/3 and does their interaction depend on (de)phosphorylation?

In the revised manuscript, we will discuss that "both PY motifs of Aly3 might be required for full interaction with Pub1/3," by citing the following published knowledge:

(a) Mutation of both PPxY motif of budding yeast Rod1 and Rog3 (Aly3 homologs) diminished their interaction with the ubiquitin ligase Rsp5 (Andoh et al, FEBS Lett, 2002).

(b) Mutating either one of two PPxY motifs of budding yeast Cvs7/Art1 greatly decreased interaction with WW domain, and mutating both abolished the interaction (Lin et al, Cell, 2008).

Our preliminary results indicated that Pub3 interacted with Aly3, Aly3(4th A) and phospho-mimetic Aly3(4th D), and thus suggested that the Aly3-Pub1/3 interaction does not depend on the phosphorylation status of Aly3. Consistently, budding yeast Rod1 reportedly interacts with Rsp5 regardless of its phosphorylation status (e.g. Becuwe et al, J Cell Biol, 2012). While we have partially mentioned this point in the original manuscript (L499-503), we will discuss this point more clearly in the revised manuscript.

Reviewer #1 (Significance):

The results are well presented and clear cut (with few exceptions, please see major points). They provide further evidence that metabolic cues instruct the phosphorylation of a-arrestins. Phosphorylation then negatively regulates a-arrestin function in selective endocytosis and is essential to adjust nutrient uptake across the plasma membrane to the given biological context.

We thank the reviewer for finding significance of our study. We believe that adding new results of the requested experiments and responding to the raised comments will clarify the significance of our revised manuscript.

Reviewer #2 (Evidence, reproducibility and clarity):

**Summary / background. This paper focuses on the regulation of endocytosis of the hexose transporter, Ght5, in S. pombe by nutrient limitation through the arrestin-like protein Aly3. Ght5 is induced when glucose is limiting and is required for growth and proliferation in these conditions. ght5+ encodes the only high-affinity glc transporter from fission yeast. ght5+ is induced in low glucose conditions at the transcriptional level and is translocated to the plasma membrane to allow glc import. Ght5 is targeted to the vacuole in conditions of N limitation. Mutations in the TORC2 pathway lead to the same process, thus preventing growth on low glucose medium, as shown in the gad8ts mutant, mutated for the Gad8 kinase acting downstream of TORC2. Previously, the authors demonstrated that the vacuolar delivery of Ght5 in the gad8ts mutant is suppressed by mutation of the arrestin-like protein Aly3. Arrestin-like proteins are in charge of recognising and ubiquitinating plasma membrane proteins to direct their vacuolar targeting by the endocytosis pathway. This suggested that Aly3 is hyperactive in TORC2 mutants, and accordingly, Ght5 ubiquitination was increased in gad8ts.

**Overall statement This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments below.

We thank the reviewer for pointing both advantages and issues of our manuscript.

We admit that phosphorylation of Aly3 was not experimentally shown in our manuscript, although its phosphorylation has already been shown in phospho-proteomic studies by other groups. For this issue, we plan to add an experiment and modify the text, as explained below.

The other major issue raised by this reviewer is that detection of Ght5 ubiquitination by immunoprecipitation in a native condition cannot be conclusive. Although we noticed that many studies perform affinity purification after denaturing and precipitating proteins with TCA or acetone to detect ubiquitination of the affinity-purified protein (e.g. Lin et al, Cell, 2008), we disagree with this opinion of the reviewer #2. In a review article describing methods to study ubiquitination by immunoblotting (Emmerich and Cohen, Biochem Biophys Res Comm, 2015), affinity purification of the protein of interest in a native condition is mentioned as one major choice. Moreover, a denaturing condition was not applicable to detect ubiquitinated Ght5 because the Ght5 protein that is once denatured and precipitated with TCA cannot be re-solubilized for immune-purification and -blotting. As the reviewer points out, a pitfall of detection of ubiquitinated Ght5 in a native condition is the presence of co-immunoprecipitated proteins. In our previous study (Toyoda et al, J Cell Sci, 2021), we purified GFP-tagged Ght5 and showed that a 110 kDa band detected in an anti-Ub immunoblot was also recognized by an anti-GFP antibody, confirming that the detected 110 kDa band corresponded to an ubiquitinated species of Ght5, but not a co-immunoprecipitated protein. Similarly, in the revised manuscript, we will add a panel of high-contrast (over-exposed) anti-GFP immunoblot, in which the indicated 110 kDa band was clearly detected by an anti-GFP antibody, in Figure 5A.

We appreciate these issues raised by the reviewer #2. By responding to them, we believe that conclusions of our study will be more rigorous and undoubtful in the revised manuscript.

**Major statements and criticism.

*Fig 1. Based on the hypothesis that TORC2-mediated phosphorylation regulate Ght5 endocytosis, the authors first considered a possible phosphorylation of Ght5. They mutagenised 11 **possible** phosphorylation sites on the Ct of Ght5, but none affected the growth on low glucose in the absence of thiamine, suggesting that they don't contribute to the observed TORC2-mediated regulation. However, I disagree with the statement that "phosphorylation of Ght5 is dispensable for cell proliferation in low glucose", given that the authors do not show 1- that Ght5 is phosphorylated and 2-that this is abolished by these mutations. They should either provide data on this or tone down and say that these residues are not involved in the regulation, without implying phosphorylation which is not proven.

Although we did not experimentally test whether these 11 residues of Ght5 was phosphorylated in our hand, these residues have been shown to be phosphorylated in phospho-proteomics studies by other groups (Kettenbach et al, Mol Cell Proteomics, 2015; Swaffer et al, Cell Rep, 2018; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021). In the revised manuscript, we plan to be more precise by replacing this conclusion with the following statement: "11 Ser/Thr residues of Ght5, which are reportedly phosphorylated, are not essential for cell proliferation in low glucose."

In the presence of Thiamine (Supp fig 1), it seems that the ST/A mutant grows better in low glucose, and this is not explained nor commented. Since the transporter is not expressed, could the authors provide an explanation to this? If the promoter is leaky and some ght5-ST/A is expressed, it may be more stable and allow better growth than the WT, which would tend to indicate that impairing phosphorylation prevents endocytosis (which is classical for many transporters, see the body of work on CK1-mediated phosphorylation of transporters). Have the authors tried to decrease glc concentration lower than 0.14% in the absence of thiamine to see if this also true when the transporters is strongly expressed? (OPTIONAL)

Improved growth of Ght5(ST11A)-expressing cells in the presence of thiamine was mentioned in the legend of Supplementary Figure 1A. In the revised manuscript, we will mention this observation also in the main text for better description of the results.

Adding thiamine to medium does not completely shut off transcription from the nmt1 promoter but allows some transcription, as previously reported (Maundrell, J Biol Chem, 1990; Forsburg, Nuc Acid Res, 1993). In the revised manuscript, we will mention this "leakiness" of the nmt1 promoter and, by citing the suggested studies, will discuss a possibility that the ST11A mutations might prevent endocytosis of Ght5 and consequently promote cell proliferation in low glucose conditions.

We found that, in the absence of thiamine, cells expressing ght5+ and ght5(ST11A) proliferated to the comparable extent on medium containing 0.08% glucose. This result will be added to the revised manuscript.

*Fig 2. The authors then follow the hypothesis that TORC2 exerts its Ght5-dependent regulation through the phosphorylation of Aly3. They mutagenised 18 **possible** phosphorylation sites on Aly3. This led to a strong defect in growth in low-glc medium. Mutation of the possible Gad8 site (S460) did not recapitulate this phenotype, suggesting that it is not sufficient, however, mutations of 4 ST residues in a CT cluster (582-586) mimicked the full 18ST/A mutation, suggesting these are the important residues for Ght5 endocytosis.

We thank the reviewer for appreciating the results in Fig. 2. As we explain below, we plan to perform an additional experiment to show that the Aly3 C-terminus is phosphorylated. With this result, our model will gain another experimental support.

*Fig 3A. Further dissection did not allow to pinpoint this regulation to a specific residue, beyond the dispensability of the T586 residue. Fig 3B. The authors look at the effects of mutation of Aly3 on these sites at the protein level. They had to develop an antibody because HA-epitope tagging did not lead to a functional protein (Supp fig 2). Whereas I agree that the mutations causing a phenotype lead to a change in the migration pattern, I disagree with the statement that "This observation indicated that slower migrating bands were phosphorylated species of Aly3" (p.9 l.271). First, lack of phosphorylation usually causes a slower mobility on gel, which is not clear to spot here. Second, a smear appears on top of the mutated proteins (eg. 4th Ala) which is possibly caused by another modification. There are many precedents in the literature about arrestins being ubiquitinated when they are not phosphorylated (see the work on Bul1, Rod1, Csr2 in baker's yeast from various labs). My gut feeling is that lack of phosphorylation unleashes Aly3 ubiquitination leading to change in pattern. All in all, it is impossible to state about the phosphorylation of a protein without addressing its phosphorylation properly by phosphatase treatment + change in migration, or MS/MS. Thus, whereas the data looks promising, this hypothesis that Aly3 is phosphorylated at the indicated sites is not properly demonstrated.

We disagree with the reviewer's opinion that a lack of phosphorylation usually causes slower mobility on gel. There are many examples in which phosphorylation causes slower mobility on gel, including budding yeast Rod1 (Alvaro et al, Genetics, 2016), and mammalian TXNIP (Wu et al, Mol Cell, 2013). In the revised manuscript, we will cite these reports to support our interpretation that the slower migrating bands are likely phosphorylated species of Aly3 (L270-271).

Smear-like signals in Aly3(4th Ala), Aly3(4th A;A584S) and Aly3(4th A;A586T) might result from some modification, but identity of the modification is unknown. As the reviewer #2 mentioned, phosphorylation on Aly3 might negatively regulate another modification. The precedent studies revealed that budding yeast Rod1 and Rog3 arrestins tend to be ubiquitinated in snf1/AMPK-deficient cells (Becuwe et al, J Cell Biol, 2012; O'Donnell et al, Mol Cell Biol, 2015), and that Bul1 arrestin is dephosphorylated and ubiquitinated in budding yeast cells deficient in Npr1 kinase (Merhi and Andre, Mol Cell Biol, 2012). Also, budding yeast Csr2 arrestin is deubiquitinated and phosphorylated upon glucose replenishment, while non-phosphorylated Csr2 is ubiquitinated and activated by Rsp5 (Hovsepian et al, J Cell Biol, 2012). While the smear-like signals are interesting, we noticed that the smear-like signals did not necessarily correlate with cell proliferation defects in low glucose. We therefore think that clarifying the identity of the smear-like signals is beyond the scope of this study. We will discuss the smear-like signals only briefly in the revised manuscript, and would address this issue in our future work, hopefully.

While the 4 S/T residues at the C-terminus of Aly3 as well as the other 14 S/T residues have been already shown to be phosphorylated in the precedent studies (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021), we will confirm that the slower migrating Aly3 is indeed phosphorylated by phosphatase treatment in the revised manuscript. This planned experiment will further strengthen our study and support our conclusion and model.

*Fig 4. The authors now look at the functional consequences of these mutations on ALy3 on Ght5 localisation. The data clearly shows that mutation of the 4 identified S/T residues (Aly3-4th A) causes aberrant localisation of the transporter to the vacuole, likely to cause the observed growth defect on low glucose. There is a nice correlation between the vacuolar localisation and growth in low-glucose for the various aly3 mutants. (A final proof could be to express this in the context of an endocytic mutant, which should restore membrane localisation and suppress the aly3-4thA phenotype - OPTIONAL). However, I still disagree with the statement that "These results indicate that phosphorylation of Aly3 at the C-terminal 582nd, 584th, and/or 585th serine residues is required for cell-surface localization of Ght5." given that phosphorylation was not properly demonstrated.

While phosphorylation of the 582nd, 584th and/or 585th serine residues of Aly3 is not experimentally demonstrated in our hands, they have been shown to be phosphorylated in phospho-proteomics studies by other groups (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021). Among them, the 584th serine residue (S584) was reported to be phosphorylated in a TORC2-dependent manner (Mak et al, EMBO J, 2021), consistent with our model. To explicitly demonstrate that S584 is phosphorylated, we plan to make a strain expressing a mutant Aly3 protein in which all the possible phosphorylation sites except S584 are replaced with alanine, namely Aly3(ST17A;S584). Hopefully, we can properly show the phosphorylation of S584 by measuring the mobility of the Aly3(ST17A;S584) on gel with/without phosphatase treatment or gad8 mutation.

We thank the reviewer for suggestion of the experiment using an endocytic mutant. Previously we reported that vacuolar localization of Ght5 in gad8 mutant cells was suppressed by mutations in not only aly3 but also genes encoding ESCRT complexes (Toyoda et al, J Cell Sci, 2021). We therefore think that in cells expressing Aly3(ST18A) or Aly3(4th Ala), Ght5 is subject to endocytosis and ensuing selective transport to vacuoles via endosome-localized ESCRT complexes. We will discuss this point in the revised manuscript.

*Fig 5. Here, the authors question the role of Aly3 mutations on Ght5 ubiquitination. They immunoprecipitate Ght5 and address its ubiquitination status in various Aly3 mutants. The data is encouraging for a role in Aly3 phosphorylation (?) in the negative control of Ght5 ubiquitination. My main problem with this experiment is that it seems that Ght5 immunoprecipitations were made in non-denaturing conditions, which leads to the question of what is the anti-ubiquitin revealing here (Ght5 or a co-immunoprecipitated protein, for example Aly3 itself, or the Pub ligases, or an unknown protein). It seems that this protocol was previously used in their previous paper, but I stand by my conclusion that ubiquitination of a given protein can only be looked in denaturing conditions. The experiments should be repeated in buffers classical for the study of protein ubiquitination to be able to conclude unambiguously that we are looking at Ght5 ubiquitination itself, especially in the absence of a non-ubiquitinable form of Ght5 as a negative control. Could the authors comment on the fact that S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination?

As mentioned above, immunoprecipitation of Ght5 in denaturating conditions is not feasible. Ght5 can be affinity-purified only in a non-denaturing condition. In addition, affinity purification in a native condition is considered as a major choice to examine its ubiquitination according to a literature by Emmerich and Cohen (Emmerich and Cohen, Biochem Biophys Res Comm, 2015). A drawback of native condition is, as the reviewer points out, that the affinity-purified fraction might include non-bait (non-Ght5) proteins. The 110 kDa band indicated by an arrow in Fig. 5A was confirmed to be Ght5, not a non-bait protein, as a band at the identical position was detected in the immunoblot with anti-GFP antibody. Because this band in the anti-GFP immunoblot was too faint to be visible in Fig. 5A of the original manuscript, we will add an additional panel showing the contrast-enhanced anti-GFP immunoblot in which the 110 kDa band is clearly visible.

As for the result that "S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination," we are afraid that the reviewer #2 misunderstood the labels of the samples. We apologize for confusing notational system of the sample name. Full description of samples is as follows; In Aly3(4th A), all of S582, S584, S585 and T586 are replaced with A; In Aly3(4th A;A584S), S582, S585 and T586 are replaced with A, whereas S584 remains intact; In Aly3(4th A;A584D), S582, S585 and T586 are replaced with A, and S584 is replaced with phospho-mimetic D. Because cells expressing Aly3(4th A;A584S) and Aly3(4th A;A584D) exhibited similarly low levels of Ght5 ubiquitination, we speculated that phosphorylation at S584 of Aly3 negatively regulates ubiquitination of Ght5.

In the revised manuscript, we plan to add a table showing amino acid sequence of each species of Aly3 (just like Figure 3A) to avoid confusion.

*Fig 6. The authors want to document the model whereby Aly3 may interact with some of the Nedd4 ligases (Pub1/2/3) to mediate its Ght5-ubiquitination function. They actually use the Aly3-4thA mutant, it should have been better with the WT protein. But the results indicate a clear interaction with at least Pub1 and Pub3. By the way, are the Pub1/2/3 fusions functional? Nedd4 proteins are notoriously affected in their function by C-terminal tagging and are usually tagged at their N-terminus (See Dunn et al. J Cell Biol 2004).

We plan to test whether Pub1-myc is functional by comparing proliferation of the Pub1-myc-expressing strain and pub1Δ strain, as pub1Δ cells reportedly show proliferation defects at a high temperature (Tamai and Shimoda, J Cell Sci, 2002). As deletion of pub2 or pub3 reportedly exhibited no obvious defects (Tamai and Shimoda, J Cell Sci, 2002; Hayles et al, Open Biol, 2013), it is not easy to assess functionality of the myc-tagged genes.

Please note that C-terminally tagged Pub1/2/3 proteins have been widely used in studies with fission yeast. Both Pub1-HA and non-tagged Pub1 were reported to be ubiquitinated (Nefsky and Beach, EMBO J, 1996; Strachan et al, J Cell Sci, 2023). Pub1-GFP, which complemented the high temperature sensitivity of pub1Δ, localized to cell surface and cytoplasmic bodies (Tamai and Shimoda, J Cell Sci, 2002). Pub2-GFP, overexpression of which arrested cell growth just like overexpression of non-tagged Pub2, localized to cell surface, and consistently Pub2-HA was detected in membrane-enriched pellet fractions after ultracentrifugation (Tamai and Shimoda, J Cell Sci, 2002). They also reported ubiquitin conjugation of the HECT domain of Pub2 fused with myc epitope at its C-terminus. Pub3-GFP localized to cell surface (Matsuyama et al, Nat Biotech, 2006).

Regardless of functionality of the myc-tagged Pub1/2/3, we believe that results of this experiment (Figure 6) support our model, because the aim of this experiment, which is to identify the HECT-type and WW-domain containing ubiquitin ligase(s) that interact with Aly3, is irrelevant to functionality of the myc-tagged Pub proteins.

*Fig 7. The authors want to provide genetic interaction between the Pub ligases and the growth defects in low glc due to alterations in Ght5 trafficking. It is unclear how the gad8ts pub1∆ mutant was generated since it doesn't seem to grow on regular glc concentration (Supp fig 5), could the authors provide some information about this? It is also not clear whether it can be stated thatches mutant is "more sensitive" to glc depletion because of the low level of growth to begin with (even at 3%). Altogether, the data show that deletion of pub3+ is able to suppress the growth defect of the gad8ts mutant on low glc medium, suggesting it is the relevant ligase for Ght5 endocytosis. This is confirmed by microscopy observations of Ght5 localisation. However, I would again tone down the main conclusion, which I feel is far-reaching: "Combined with physical interaction data, these results strongly suggest that Aly3 recruits Pub3, but not Pub2, for ubiquitination of Ght5." Work on Rsp5 in baker's yeast has shown that Rsp5 function goes beyond cargo ubiquitination, including ubiquitination of arrestins (which is often required for their function as mentioned in the introduction) or other endocytic proteins (epsins, amphyphysin etc). I agree that the data are compatible with this model but there are other possible explanations. Anything that would block endocytosis would supposedly suppress the gad8ts phenotype.

gad8ts pub1Δ was produced at 26 {degree sign}C, a permissive temperature of the gad8ts mutant. While this is described in the Methods section of the original manuscript, we will mention this more clearly in the Results section of the revised manuscript.

We did not conclude low glucose sensitivity of gad8ts pub1Δ cells in the indicated part (L376-377). Rather, we compared proliferation of gad8ts single mutant and pub1Δ single mutant cells in low glucose, and we found that the pub1Δ single mutant exhibited the higher sensitivity. In the revised manuscript we will correct the text to clarify that we compared proliferation of two single mutants (but not gad8ts pub1Δ mutant).

We agree with the opinion that the recruited Pub3 may ubiquitinate proteins other than Ght5. In the revised manuscript, we will correct our conclusion of the Figure 7 experiment (L388-390), not to limit the possible ubiquitination target(s) to Ght5.

In a genetic screen, we found that mutations in aly3+ and genes encoding ESCRT complexes suppressed low-glucose sensitivity and vacuolar transport of Ght5 of gad8ts mutant cells (Toyoda et al, J Cell Sci, 2021). This finding appears consistent with the reviewer's opinion that blocking endocytosis would supposedly suppress the gad8ts phenotype. We will mention this point in the revised manuscript.

*Discussion Some analogy with the regulation of the Bul arrestins by TORC1/Npr1 and PP2A/Sit4 could be mentioned (Mehri et al. 2012), at the discretion of the authors. The possibility that phosphorylation may neutralise a basic patch on Aly3 Ct, possibly involved in electrostatic interactions with Ght5 is very interesting. Regarding the effect of the mutations on Aly3 localisation (p.15 l.498), did the authors tag Aly3 with GFP? There are examples where proteins tagged with HA are not functional whereas tagging with GFP does not alter their function (eg. Rod1, Laussel et al. 2022) - and here Supp Fig 2 only relates to HA-tagging. Proof of a change in Aly3 localisation upon mutation would definitely be a plus (OPTIONAL).

We thank the reviewer for the suggestion of a reference. In the revised manuscript, we will cite the indicated report in the corresponding part for an additional support of TORC1-mediated control of Aly3 (de)phosphorylation.

While examining localization of Aly3 by GFP-tagging is interesting, we do not believe that it is necessary in this study. We would like to produce Aly3-GFP and to examine its functionality and localization in our future study. We thank the reviewer's insightful suggestion.

**Minor comments.

*Introduction: - I believe the text corresponding to the work on TXNIP is incorrect (p.5 l.127). TXNIP is degraded after its phosphorylation, not "rectracted" from the surface.

In the revised manuscript, we will correct the text accordingly.

• For the sake of completion, the authors could add other references concerning the regulation of Rod1 in budding yeast such as Becuwe et al. 2012 J Cell Biol and O'Donnell et al. 2015 Mol Cell Biol, in addition to Llopis-Torregrosa et al. 2016.

In the revised manuscript, we will add the suggested references and correct the text in the corresponding part of the Introduction (L123-138).

• Other examples of the requirement for arrestin ubiquitination beyond Art1 (p.5 l.136-137) are listed in the ref cited: Kahlhofer et al. 2021.

We will cite the indicated review to navigate readers for more examples of arrestin ubiquitination (and transporter ubiquitination).

*Figures: In general, I think it would be clearer if the authors showed on the figures that the background strain in which the XXX gene is added (or its mutant forms) is a xxx∆ strain.

We will modify the figures to clearly show the genetic background of the strains used.

**Referees cross-commenting**

Cross review of Reviewer 1 - *I don't believe that the authors "define a set of redundant c-terminal phosphorylation sites in Aly3", because phosphorylation is not proven. *I thinks the points raised for Fig 3B are valid but the authors should focus on making their story conclusive before expanding to other data (except for the explanation of the smear, see my review). Also, I don't think 2NBDG actually works to measure Glc uptake. * same for Fig 6 - not sure the interaction site mapping between Aly3 and Pubs would bring much value since there are more urgent things to do to make the story solid.

As mentioned above, we will experimentally show phosphorylation of the Aly3 C-terminus in the revised manuscript. Such experiments would make our story more solid and conclusive. We truly appreciate the comments and suggestions.

We agree with the comments on difficulty of measuring glucose uptake using 2-NBDG. In fact, we tried and failed measuring Ght5-mediated glucose uptake using 2-NBDG.

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Cros review of Reviewer 3 - we have many overlaps, so briefly : *I agree that the bibliography is incomplete (mentioned in my review) *I agree that there is no demonstration of the phospho-status of Aly3, and it is a problem *I agree that the results can be better quantified, esp. in the light of the points raised by this referee concerning the variability of expression of ST18A Other specific comments : *I agree that the statement that dephosphorylation activates alpha-arresting should be toned down - this was observed in several instances but there are examples of arrestin-mediated endocytosis which does not require their prior dephosphorylation. *I fully agree that efforts could be made regarding the classification/nomenclature of arrestins in S. pombe, this had escaped my attention

As detailed in the individual point raised by the reviewers, we will add the suggested references and accordingly correct the text in the revised manuscript.

In addition to experimentally showing Aly3 phosphorylation, we will quantify the immunoblot result.

Our statement that dephosphorylation activates alpha-arrestins might be too generalized. We will mention reports in which arrestin-mediated endocytosis does not require prior dephosphorylation (e.g. O'Donnell et al, Mol Biol Cell, 2010; Gournas et al, Mol Biol Cell, 2017; Savocco et al, PLoS Biol, 2019), and modify the text precisely.

Reviewer #2 (Significance):

*strengths and limitations This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins in S. pombe. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand, including the discovery of Aly3 as the main arrestin for this regulation, and a signalling pathway (TORC2/Gad8) acting upstream. The main question is now to understand at the mechanistic level how TORC2 signaling impinges on the regulation of this arrestin.

Overall, the authors nicely demonstrate that C-terminal Ser/Thr residues are crucial for the function of Aly3 in Ght5 endocytosis. They propose a model whereby Aly3 phosphorylation by an unknownn kinase inhibits its function on Ght5 ubiquitination, which would favour its endocytosis. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments above.

*Advance

This study, if completed carefully, would provide among the first examples of mapping of phosphorylation sites on arrestins, which are usually phosphorylated at many sites and are thus difficult to study. Few studies went down to this level in this respect (see Ivshov et al. eLife 2020). There are no changes in paradigms or new conceptual insights, but this work is a nice example of the conservation of these regulatory mechanisms.

We appreciate that this study is highly evaluated by this reviewer. We understand the main problems raised by the reviewer, and as we detailed above, we plan to perform an experiment and make explanation to respond to the problems. With the raised issues answered, we believe that conclusions of the revised manuscript will be more rigorous.

Our study reveals mechanisms regulating vacuolar transport of the Ght5 hexose transporter via the TORC2 pathway in fission yeast. The serine residues at the Aly3 C-terminus (582nd, 584th and 585th serine residues), which are probably phosphorylated in a manner dependent on the TORC2 pathway, are required for sustained Ght5 localization to cell surface and cellular adaptation to low glucose. To our knowledge, there is no such study, and thus we think that this study is novel. By responding to the reviewers' comments and adding new data as explained above, the revised manuscript will be able to present novelty of our study more clearly. Comparison of our study in fission yeast to related studies in other model organisms may reveal the conservation and diversity of these regulatory mechanisms.

*Audience Should be of interest for people studying basic research in the field of cell biology, signalling pathways, transporter regulation by physiology. Reviewer background is on the regulation of transporter endocytosis by signalling pathways and arrestin-like proteins.

Reviewer #3 (Evidence, reproducibility and clarity): (Authors' response in blue)

In this manuscript, the authors work to address how phospho-regulation of a-arrestin Aly3 in S. pombe regulates the glucose transporter Ght5. The authors use a series of phospho-mutants in Aly3 and assess function of these mutants using growth assays and localization of Ght5. My main concerns with the manuscript are that 1) there is a lack of appreciation for the similar work that has been done in S. cerevisiae to define a-arrestin phospho-regulation, which is evidenced by the severe lack of referencing throughout the document, 2) the sites mutated on Aly3 are not demonstrated to change phospho-status of Aly3 and so all interpretations of these mutants need to be better contextualized and 3) almost none of the findings are quantified (imaging or immunoblots) making it difficult to assess the rigor of the outcomes. More detailed comments are provided below.

We thank the reviewer for thorough reading of the manuscript and the detailed comments. As explained below, we will respond to the points raised by the reviewer and accordingly modify the manuscript.

Minor Comments

Immunoblotting or immunostaining to define the levels and localization of phospho-mutants - In Figure 1, an immunoblot or immunostaining to define the abundance/localization of WT Ght5 vs its ST11A mutant would be appreciated. It is very difficult to know if ST11A is as functional as WT or not without an assessment of the levels and localization of the WT and mutant proteins to accompany the spot assays. Perhaps a version of Ght5 that is a phospho-mimetic would be more useful here as well since that version should not be dephosphorylated and then presumably would be internalized and not allow for growth on low glucose medium.

We plan to add fluorescence microscopy data of WT Ght5 and Ght5(ST11A) in the revised manuscript, to compare the localization and abundance of these two Ght5 species. In our preliminary observation, those of two Ght5 species seemed to be indistinguishable.

We'd like to emphasize that the primary aim of this study is to reveal mechanisms regulating Ght5 localization and consequently ensuring cell proliferation in low glucose. While analyzing a phospho-mimetic Ght5 mutant (e.g. Ght5(ST11D)) is interesting in terms of understanding of the nature of Ght5, we believe that such an analysis is out of the scope on this study. As Ght5(ST11A)-expressing cells proliferated comparably to Ght5(WT)-expressing cells and WT and ST11A Ght5 indistinguishably localize on the cell surface, phosphorylation of the ST residues of Ght5 is not likely to be the primary mechanism regulating Ght5 localization and function. We would like to assess a phospho-mimetic Ght5 mutant protein in our future studies.

For the Aly3 mutants where the abundance of Aly3 appears lower via immunoblotting (i.e., 4thA-A582S or S582A) how is the near perfect functional readout explained when the levels of the protein are much lower than WT? For the ST18A mutant, this is a particularly important point since the authors indicate on lines 194-197 that based on the functional data for ST18A, some of these ST residues are needed for phospho-regulation of Aly3. However, in Figure 3B the authors clearly show that there is very little ST18A protein in cells, and so these mutations have impacted Aly3 stability, which may or may not be linked to its phospho-status. The authors should be upfront about this finding on lines 194-197 and should not present this phospho-model as the only reason for why ST18A may not be functional. On lines 265-276 for the authors indicate that ST18A is expressed equivalently to WT Aly3, which is just not the case in Figure 3B. Perhaps quantification of replicate data would help clarify this issue. Further, if the authors wish to conclude that the upper MW bands in Figure 3B are due to phosphorylation, perhaps they should perform phosphatase treatments of their extracts to collapse these bands. However, most certainly the overall abundance of the single band for ST18A is reduced compared to the total bands of WT Aly3.

We disagree with the opinion that the levels of the mutant Aly3 are much lower than WT. For semi-quantitative measurement of the protein abundance, 2-fold dilution series of the WT Aly3 sample were loaded in the leftmost 3 lanes of Figure 3B. Although the levels of Aly3(4th A;A582S), Aly3(S582A) and Aly3(ST18A) were lower than that of WT Aly3, those are 50% or more of the WT, judging from the intensities of the serially-diluted WT samples. To clearly show that the expression of these Aly3 proteins is within comparable levels, we plan to add a column chart of the quantified expression levels and to mention abundances of the Aly3 proteins more quantitatively in the revised text. We do not think that replicate data (of Western blots as in Figure 3B) helps clarify this issue, because nmt1 promoter-driven gene transcription is induced with a small variation (Forsburg, Nuc Acid Res, 1993). We will cite this report and mention this point in the revised text.

We are afraid that this reviewer seems to consider that Aly3(ST18A) is not functional, but it is not a case and we do not intend to claim so. While deletion of aly3 did not interfere with cell proliferation in low glucose (see vector controls in Figures 2B, 2C and 3A, -Thiamine), expression of the ST18A mutant clearly hinders cell proliferation in low glucose, indicating that the ST18A performs dominant negative function to inhibit cell proliferation. That is, even though the expression level and/or stability of the ST18A is reduced, it is still sufficiently abundant to perform the dominant negative function. We propose the phospho-model not due to dysfunctionality of ST18A, but its dominant negative functionality. The 18 S/T residues of Aly3, which are shown to be phosphorylated in precedent phospho-proteomics studies, seem to be required to down-regulate Aly3's function to inhibit cell proliferation in low glucose. We apologize for this confusion, and we will modify the text and figures to clarify these points in the revised manuscripts.

To obtain an experimental support for our description that the slower migrating bands in Figure 3B are due to phosphorylation, we plan to perform a phosphatase treatment experiment as suggested.

Figure 2A - how do the phosphorylation sites identified in Aly3 compare to those identified in Rod1 from S. cerevisiae? See PMID 26920760 or SGD for more information. I am confused as to why the Aly3 protein has an arrowhead at the C-terminus. What does this denote?

We will mention reported phosphorylation sites of Aly3 and budding yeast Rod1/Art4 in the revised manuscript, by referring to the indicated report and database. It should be noted that similarity between amino acid sequences of Aly3 and S. cerevisiae Rod1 is not so high and limited in Arrestin-N and -C domains. The C-terminal half of Aly3, in which most of the potential phosphorylation sites are found, is not similar to Rod1. Thus, these sites are unlikely to be conserved between them.

An arrowhead indicates the direction of transcription (from N to C-terminus). We will describe it explicitly in the revised figure legend.

Figure 2 - The WT and Aly3-ST18A are expressed in S. pombe from a non-endogenous locus under the control of the Nmt1 promoter. However, are these mutants present in cells that contain WT copies of Aly3 at other genomic loci? If so, this would surely muddy the interpretations of these data as a- and b-arrestins are capable of multimerizing and the effect of multimerization on their activities can vary.

As mentioned in L188, an aly3 deletion mutant strain (aly3Δ) was used as a host, and thus all strains harboring an nmt1-driven aly3 gene lack the endogenous aly3 gene. We will add an illustration clearly showing that the host strain lacks the endogenous aly3+ gene and modify the legend of Figure 2.

Functional readouts for Aly3 using Ght5 localization - The reduced surface levels of Ght5 does correspond to the spot assay growth in low glucose for the various Aly3 mutants used. However, it would be useful if these assays incorporated an endocytosis inhibitor to help prevent the activities of these Aly3 plasmids to see if the transporter is retained at the PM. At the end of these mutational analyses, the authors conclude that phosphorylation of Aly3 at any of 3 sites is required for Ght5 trafficking to the vacuole in low glucose, however no experiment is done to demonstrate that these sites are phosphorylated residues. A phosphatase assay would be useful to help demonstrate that the modifications in 3B really are phosphorylation and a quantification of the phosphorylated bands in these WBs would also be useful to solidify the statement made on lines 306-309.

We thank the reviewer for suggestion of the experiment using an endocytosis inhibitor. Previously we reported that vacuolar localization of Ght5 in gad8ts mutant cells was suppressed by mutations in not only aly3 but also genes encoding ESCRT complexes (Toyoda et al, J Cell Sci, 2021). We therefore think that, in cells expressing Aly3(ST18A) or Aly3(4th Ala), Ght5 is subject to endocytosis and subsequent selective transport to vacuoles via ESCRT complexes. We will mention these previous findings in the revised manuscript.

As mentioned in responses to the comments above and other reviewer's, we will perform a phosphatase treatment experiment and its quantification in the revised manuscript. Here, we'd like to emphasize that these 3 sites have been shown to be phosphorylated in phospho-proteomic studies by other researchers (Kettenbach et al, Mol Cell Proteomics, 2015; Tay et al, Cell Rep, 2019; Halova et al, Open Biol, 2021; Mak et al, EMBO J, 2021), although we do not show it directly in this study.

Phosphorylation assessments - in general, it would be good to not only build the non-phosphorylatable versions of Aly3 but also the phospho-mimetic forms.

We produced a phospho-mimetic mutant Aly3 (i.e. Aly3(4th A;A584D)), and showed the result in Figure 5A; cells expressing Aly3(4th A;A584D) exhibited a low ubiquitination of Ght5, similarly to Aly3(WT)- and Aly3(4th A;A584S)-expressing cells. According to our experiences, replacing S/T with D/E does not necessarily mimic phosphorylation. Thus, we do not believe that systematic production of phospho-mimetic Aly3 mutants would help achieve the aim of this study.

Pub1, 2, and 3 - It would be helpful if the authors indicated what genes Pubs 1-3 correspond to in S. cerevisiae, where Rsp5 is the predominant Ub ligase interacting with a-arrestins. Is there no ortholog of Rsp5 in S. pombe?

Pub1, Pub2 and Pub3 are regarded as orthologs of budding yeast Rsp5, according to the fission yeast database PomBase. We will perform a homology search for these E3 proteins, and based on the result, we will add a description in the revised manuscript.

Pub-Aly3 interactions - could the authors please comment on the reason why so very little Aly3 is copurified with Pub1 or Pub2? Can any clear conclusion be drawn about pub2 given how very little Pub2 is present in the IPs? Based on my understanding of these data I do not think that this can be cleanly interpreted. What is is the identity of the ~50kDa MW band in Figure 6 in the upper MYC detection panel?

We do not have an accurate answer for the result that a small amount of Aly3 is copurified with Pub1 or Pub3. The Pub1/3-Aly3 interaction may be weak or transient. We will discuss this point in the revised manuscript.

Regarding whether Aly3 interacts with Pub2, we agree with the reviewer. As described in the Results (L360-362), we could not conclude anything about Aly3-Pub2 interaction by this immunoprecipitation experiment alone. On the other hand, the genetic interaction experiment (Figure 7A) suggests that pub2+ is not involved in defects caused by the gad8ts mutation (while pub3+ and aly3+ are). By this experiment, we think that Pub2 is not a partner of Aly3.

In the revised manuscript, we will describe that Pub2 is not a partner of Aly3 in a paragraph describing the Figure 7A experiment.

Because the 50 kDa band found in the IP fraction of all the samples appears even in "beads only" (Figure 6), those are supposedly derived from mouse IgG dissociated from the beads used for immunoprecipitation. We will mention this in the legend of Figure 6.

Phosphorylation and ubiquitination of a-arrestins - The paragraph from lines 123-138 is very superficial in addressing what is known about phosphorylation and ubiquitination of a-arrestins. The way this section is written, it feels misleading to the reader as it omits many of the details for regulation that would help place the current study in context. The discussion of Rod1 phosphorylation by AMPK for example, which is directly relevant to this study, is underdeveloped. I would recommend splitting this into two paragraphs and providing a more in depth, and accurate, view of the literature on this topic, with a focus on the regulation that is relevant for the ortholog of Aly3 in S. cerevisiae. For example, Rod1 phosphorylation by AMPK is greatly expanded upon in the following papers (PMID 22249293 and 25547292) and AMPK regulation of C-tail phosphorylation of a-arrestins is defined further in PMID 26920760. These references are each particularly important to compare with the current findings presented in this manuscript. Torc2 regulation ofa-arrestins is also reviewed in PMID 36149412 and references therein should be considered.

Because the primary aim of this study is to reveal mechanisms regulating Ght5 localization in fission yeast, but not to dissect modification and regulation of α-arrestins, we decided not to get into the details of phosphorylation and ubiquitination of α-arrestins. Furthermore, although budding yeast Rod1 and Rog3 are found to be downstream of the TORC2-Ypk1 signaling in the context of internalization of the Ste2 pheromone receptor, it is not clear whether TORC2-Ypk1 signaling also regulate α-arrestin-mediated internalization of hexose transporters in budding yeast. For these reasons, we focused on limited literatures essential for interpretation of the results and omitted many references describing the details of α-arrestin regulation. However, as this reviewer commented, we realize that our decision makes the discussion superficial and misleading to the reader. We sincerely apologize for this inconvenience.

In the revised manuscript, we will reorganize the paragraphs in the discussion and include the suggested references. Regarding budding yeast Rod1, we will cite the study reporting Ypk1-mediated phosphorylation on Rod1 in mating pheromone response via regulation of Ste2 endocytosis (Alvaro et al, Genetics, 2016). We will also mention other reports (Becuwe et al, J Cell Biol, 2012; O'Donnell et al, Mol Cell Biol, 2015) about AMPK-dependent phosphorylation of Rod1 in the corresponding part (e.g. L129-130). In addition, we will mention that Aly2, Rod1 and Rog3 α-arrestins were found downstream of the TORC2-Ypk1 signaling (Muir et al, eLife, 2014; Thorner, Biochem J, 2022).

As a further detailed example, there is far more work done on ubiquitination of a-arrestins in S. cerevisiae than the single citation provided by the authors on line 137. The way this section is written it feels misleading. Considerable effort has been spent on defining how mono- and poly-ubiquitination regulate a-arrestins and the authors should consider the data provided in the following citations and revise the two sentences they provide in this introduction to better reflect the breadth of our understanding rather than simply indicate that the 'mechanisms that regulate functions of a-arrestisn are not fully understood'. (PMIDs 23824189; 22249293; 17028178; 28298493)

Ubiquitination of α-arrestin itself is not the topic of this study, and physiological consequences of ubiquitination of Aly3 remain unknown. Because of these reasons, we did not describe the details of ubiquitination of α-arrestins in the original manuscript. However, we never intend to mislead the reader, and thus to avoid it, we will revise the indicated sentences and cite the suggested literatures (O'Donnell et al, J Biol Chem, 2013; Becuwe et al, J Cell Biol, 2012; Kee et al, J Biol Chem, 2006; Ho et al, Mol Biol Cell, 2017) in the revised manuscript.

Context of the findings and lack of citations - The referencing in this manuscript is very poor as many of the key papers that report analogous findings in the budding yeast Saccharomyces cerevisiae are not cited. This oversight in citing the appropriate literature must be remedied before this manuscript can be considered further for publication. Examples of these omissions occur at the following places:

We will modify the text and carefully cite more literatures describing analogous finding in budding yeast and other organisms in the revised manuscript. We appreciate the insightful suggestions by this reviewer. It should be noted, however, that it is not evident whether budding yeast Rod1 and Rog3 are orthologous to fission yeast Aly3. Although Rod1 and Aly3 share overlapping roles, amino acid sequence similarity of them is not high and limited only in domains which are generally conserved among α-arrestin-family proteins.

Line 90 - The Puca and Brou citations is one example of this but the first examples come from Daniela Rotin's work looking at Rsp5 interactions in budding yeast, which is where the association between HECT-domain Ub ligases and a-arrestins is also documented by Scott Emr and Hugh Pelham's labs. Here are some PMID numbers to improve the citations of this section (PMID 17551511; 18976803; 19912579) and each of these references long predates the Puca and Brou publication.

In the revised manuscript, we will improve the citations by including the suggested studies (Gupta et al, Mol Syst Biol, 2007; Lin et al, Cell, 2008; Nikko and Pelham, Traffic, 2009).

Lines 123-126 - Phosphorylation can also increase vacuole-dependent degradation of alpha-arrestins as demonstrated in PMID 35454122. The interaction with 14-3-3 proteins that is driven by phosphorylation of a-arrestins was first demonstrated by the Leon group in PMID 22249293). Lines 129-132 - Here again the Leon reference that helps demonstrate the 14-3-3 inhibition of Rod1 is lacking (PMID 22249293).

We will cite the suggested studies in description of these topics (Bowman et al, Biomolecules, 2022; Becuwe et al, J Cell Biol, 2012).

Lines 130-132 - Please include references for the statement that dephosphorylation activates a-arrestin activity. There are no citations on this statement and there are many to choose from and I would urge the authors to cite the primary literature on these points.

We will cite studies for the statement "Conversely, dephosphorylation is thought to activate α-arrestins and to promote selective endocytosis of transporter proteins" (L130-132).

These are just a few examples from the Introduction, but the Discussion is similarly wrought with issues in referencing and framing the experimental results within the context of the larger field, including what is known about Rod1/Rog3 regulation in S. cerevisiae. For example, the Llopis-Torregrosa et al reference and statement on lines 508-510 is incorrect. There are other phosphorylation sites defined in the C-terminus of Rod1, as described in Alvaro et al. PMID: 26920760.

We will carefully correct Discussion by citing the suggested references (e.g. Alvaro et al, Genetics, 2016) and framing the obtained results within the context of the larger field.

Of note, a combination of α-arrestin, upstream kinase(s) and distinct phosphorylation sites appears to determine the target transporter (Kahlhofer et al, Biol Cell, 2021; Thorner, Biochem J, 2022), and it has not been explicitly proved that TORC2-Ypk1 signaling also regulate α-arrestin-mediated internalization of hexose transporters in budding yeast. For these reasons, we stated "S. cerevisiae Rod1 and Rog3 are phosphorylated solely by Snf1p/AMPK" in the context of internalization of hexose transporters. We will also discuss this point in the revised manuscript.

Minor Comments Clarification needed - Lines 107-121 - The relationship between the S. pombe arrestins and those in other organisms is somewhat unclear. Frist, all the arrestins in humans and S. cerevisiae can be sorted into the alpha, beta and Vps26 classes. However, the authors indicate that the S. pombe genome has 11 arrestin-like proteins but only 4 of these are a-arrestins. What classes do the other 7 arrestins belong to? It would be appreciated if this point was clarified.

To our knowledge, fission yeast arrestins are not well classified yet. We will perform a phylogenetic tree analysis to classify them, and modify the description of the indicated part accordingly. We will also cite our previous report (Toyoda et al, J Cell Sci, 2021), in which the overall protein structure and domains of 11 fission yeast arrestin-like proteins were reported.

Next, for the 4 a-arrestins identified in S. pombe the authors indicate that Aly3 is the homolog of Rod1/Art4 and Rog3/Art7 from S. cerevisiae. What is the relationship of Rod1 in S. pombe to Rod1 in S. cerevisiae? Are these also homologs? You can see how the nomenclature is confusing and, given the functional overlap of S. cerevisiae Rod1/Rog3 proteins it is important to know if Aly3 is the only version of these a-arrestins or if there is an additional counterpart in S. pombe. This point becomes somewhat more confusing when on lines 134-136 the authors talk about Arn1/Any1 as an arrestin related protein in S. pombe yet this protein was not included on the list of a-arrestins in the preceding section. What class of arrestin is this protein?

According to PomBase, both Aly3 and Rod1 are assigned as the orthologue of budding yeast Rod1 and Rog3. However, as mentioned in responses above, it is unclear whether Aly3 is really orthologous to budding yeast Rod1/Rod3. In the revised manuscript, we will perform a homology search for these 4 proteins, and add information on how much these arrestins share homology.

Arn1/Any1 is regarded as a β-arrestin (Nakase et al, J Cell Sci, 2013). We will also mention this in the revised manuscript.

Alpha-arrestin homology - On lines 127-129 the authors indicate that TXNIP is the mammalian homolog of Aly3. To my knowledge, there are no evolutionary analyses that can draw these lines of homology between the a-arrestins in humans and those in yeasts. It would be appreciated if the authors could cite the work that leads to this conclusion or revise the sentence to more accurately reflect what is known on this topic. It certainly appears that, given their functional overlap in regulating glucose transporters, Txnip and Rod1/Rog3 in humans and S. cerevisiae are functionally connected. I urge the authors to use more caution when describing this protein family.

Among human α-arrestins, ARRDC2 (22%) but not TXNIP (20%) has the highest amino acid identity to Aly3 (Toyoda et al, J Cell Sci, 2021). However, as TXNIP has been reported to regulate endocytosis of hexose transporters, GLUT1 and 4 (Wu et al, Mol Cell, 2013; Waldhart et al, Cell Rep, 2017), we think that TXNIP and Aly3 share physiological roles. We will revise the sentence (L127-129) more accurately.

Text editing - The text could use editing as there are awkward and grammatically incorrect sentences in several places. Here are a few examples to help the authors:

Please note that the original manuscript is edited by a professional editor, who is a native English (American) speaker and has edited thousands of research papers, before initial submission. We will ask an editor to check the revised draft again before submission.

Lines 57-60 - the protein is not expressed over the entire cell surface, but is localized to the entire cell surface.

We will correct this wording.

Lines 80-83 - this sentence is very confusing

We will correct this part by changing the phrase "Unlike TORC1," into a clause.

Line 86 - Is there more than one gene encoding Aly3 in S. pombe?

No, there is only one gene encoding Aly3. We will correct this part so as to avoid being misunderstood.

Line 88, 109, - these sentences need to start with a capitol so either capitalize the A in arrestin or write out Alpha with a capitol A.

We will correct the sentence as suggested.

Lines 145-148 - unclear as written

We will clarify the meaning of the sentence by changing the voice.

Line 224 - why are these amino acids being referred to as hydroxylated? Perhaps hydroxyl-containing amino acids or 18 amino acids with hydroxyl side chains would be better choices?

We will correct the word as suggested.

Line 300 - very confusing sentence structure

We will correct this part by simplifying the structure of the sentence.

And elsewhere....

We will carefully check the revised text before submission.

Reviewer #3 (Significance):

The authors provide some information as to the residues needed in the Aly3 C-tail for Ght5 trafficking in S. Pombe. These results are not places in the context of similar phosphor-regulatory work done for a-arrestins in S. cerevisiae, and this is needed for appreciation of the significance of the study.

Overall, it appears that the model put forth is very similar to the one already proposed in S. cerevisiae where phosphorylation impedes a-arrestin-mediated trafficking of glucose transporters. It is interesting to see this similarity hold in S. Pombe, but it does not dramatically alter our appreciation of a-arrestin biology.

The significance of the findings are somewhat underscored by the fact that very little quantification of data are presented, making the rigor of the work difficult to assess.

We thank the reviewer for careful reading and evaluation of our study. As the reviewer states, the results are not placed in the context of similar phospho-regulatory works done for α-arrestins in S. cerevisiae. This may partly come from the fact that it remains unclear whether internalization of hexose transporters is regulated by TORC2-dependent phosphorylation in S. cerevisiae. We believe that our study is novel and significant for this reason. By performing the additional experiments/quantification and revising the text as suggested by the reviewers, the manuscript will be further strengthened, and we will be able to clearly conclude that TORC2-dependent phosphorylation of Aly3 regulates localization of the Ght5 hexose transporter and cellular responses to glucose shortage stress.

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Referee #2

Evidence, reproducibility and clarity

Summary/background.

This paper focuses on the regulation of endocytosis of the hexose transporter, Ght5, in S. pombe by nutrient limitation through the arrestin-like protein Aly3. Ght5 is induced when glucose is limiting and is required for growth and proliferation in these conditions. ght5+ encodes the only high-affinity glc transporter from fission yeast. ght5+ is induced in low glucose conditions at the transcriptional level and is translocated to the plasma membrane to allow glc import. Ght5 is targeted to the vacuole in conditions of N limitation. Mutations in the TORC2 pathway lead to the same process, thus preventing growth on low glucose medium, as shown in the gad8ts mutant, mutated for the Gad8 kinase acting downstream of TORC2. Previously, the authors demonstrated that the vacuolar delivery of Ght5 in the gad8ts mutant is suppressed by mutation of the arrestin-like protein Aly3. Arrestin-like proteins are in charge of recognising and ubiquitinating plasma membrane proteins to direct their vacuolar targeting by the endocytosis pathway. This suggested that Aly3 is hyperactive in TORC2 mutants, and accordingly, Ght5 ubiquitination was increased in gad8ts.

Overall statement

This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments below.

Major statements and criticism.

• Fig 1. Based on the hypothesis that TORC2-mediated phosphorylation regulate Ght5 endocytosis, the authors first considered a possible phosphorylation of Ght5. They mutagenised 11 possible phosphorylation sites on the Ct of Ght5, but none affected the growth on low glucose in the absence of thiamine, suggesting that they don't contribute to the observed TORC2-mediated regulation. However, I disagree with the statement that "phosphorylation of Ght5 is dispensable for cell proliferation in low glucose", given that the authors do not show 1- that Ght5 is phosphorylated and 2-that this is abolished by these mutations. They should either provide data on this or tone down and say that these residues are not involved in the regulation, without implying phosphorylation which is not proven. In the presence of Thiamine (Supp fig 1), it seems that the ST/A mutant grows better in low glucose, and this is not explained nor commented. Since the transporter is not expressed, could the authors provide an explanation to this? If the promoter is leaky and some ght5-ST/A is expressed, it may be more stable and allow better growth than the WT, which would tend to indicate that impairing phosphorylation prevents endocytosis (which is classical for many transporters, see the body of work on CK1-mediated phosphorylation of transporters). Have the authors tried to decrease glc concentration lower than 0.14% in the absence of thiamine to see if this also true when the transporters is strongly expressed? (OPTIONAL)
• Fig 2. The authors then follow the hypothesis that TORC2 exerts its Ght5-dependent regulation through the phosphorylation of Aly3. They mutagenised 18 possible phosphorylation sites on Aly3. This led to a strong defect in growth in low-glc medium. Mutation of the possible Gad8 site (S460) did not recapitulate this phenotype, suggesting that it is not sufficient, however, mutations of 4 ST residues in a CT cluster (582-586) mimicked the full 18ST/A mutation, suggesting these are the important residues for Ght5 endocytosis.
• Fig 3A. Further dissection did not allow to pinpoint this regulation to a specific residue, beyond the dispensability of the T586 residue. Fig 3B. The authors look at the effects of mutation of Aly3 on these sites at the protein level. They had to develop an antibody because HA-epitope tagging did not lead to a functional protein (Supp fig 2). Whereas I agree that the mutations causing a phenotype lead to a change in the migration pattern, I disagree with the statement that "This observation indicated that slower migrating bands were phosphorylated species of Aly3" (p.9 l.271). First, lack of phosphorylation usually causes a slower mobility on gel, which is not clear to spot here. Second, a smear appears on top of the mutated proteins (eg. 4th Ala) which is possibly caused by another modification. There are many precedents in the literature about arrestins being ubiquitinated when they are not phosphorylated (see the work on Bul1, Rod1, Csr2 in baker's yeast from various labs). My gut feeling is that lack of phosphorylation unleashes Aly3 ubiquitination leading to change in pattern. All in all, it is impossible to state about the phosphorylation of a protein without addressing its phosphorylation properly by phosphatase treatment + change in migration, or MS/MS. Thus, whereas the data looks promising, this hypothesis that Aly3 is phosphorylated at the indicated sites is not properly demonstrated.
• Fig 4. The authors now look at the functional consequences of these mutations on ALy3 on Ght5 localisation. The data clearly shows that mutation of the 4 identified S/T residues (Aly3-4th A) causes aberrant localisation of the transporter to the vacuole, likely to cause the observed growth defect on low glucose. There is a nice correlation between the vacuolar localisation and growth in low-glucose for the various aly3 mutants. (A final proof could be to express this in the context of an endocytic mutant, which should restore membrane localisation and suppress the aly3-4thA phenotype - OPTIONAL). However, I still disagree with the statement that "These results indicate that phosphorylation of Aly3 at the C-terminal 582nd, 584th, and/or 585th serine residues is required for cell-surface localization of Ght5." given that phosphorylation was not properly demonstrated.
• Fig 5. Here, the authors question the role of Aly3 mutations on Ght5 ubiquitination. They immunoprecipitate Ght5 and address its ubiquitination status in various Aly3 mutants. The data is encouraging for a role in Aly3 phosphorylation (?) in the negative control of Ght5 ubiquitination. My main problem with this experiment is that it seems that Ght5 immunoprecipitations were made in non-denaturing conditions, which leads to the question of what is the anti-ubiquitin revealing here (Ght5 or a co-immunoprecipitated protein, for example Aly3 itself, or the Pub ligases, or an unknown protein). It seems that this protocol was previously used in their previous paper, but I stand by my conclusion that ubiquitination of a given protein can only be looked in denaturing conditions. The experiments should be repeated in buffers classical for the study of protein ubiquitination to be able to conclude unambiguously that we are looking at Ght5 ubiquitination itself, especially in the absence of a non-ubiquitinable form of Ght5 as a negative control. Could the authors comment on the fact that S-A or S-D mutations display the same phenotype regarding the possible Ght5 ubiquitination?
• Fig 6. The authors want to document the model whereby Aly3 may interact with some of the Nedd4 ligases (Pub1/2/3) to mediate its Ght5-ubiquitination function. They actually use the Aly3-4thA mutant, it should have been better with the WT protein. But the results indicate a clear interaction with at least Pub1 and Pub3. By the way, are the Pub1/2/3 fusions functional? Nedd4 proteins are notoriously affected in their function by C-terminal tagging and are usually tagged at their N-terminus (See Dunn et al. J Cell Biol 2004).
• Fig 7. The authors want to provide genetic interaction between the Pub ligases and the growth defects in low glc due to alterations in Ght5 trafficking. It is unclear how the gad8ts pub1∆ mutant was generated since it doesn't seem to grow on regular glc concentration (Supp fig 5), could the authors provide some information about this? It is also not clear whether it can be stated thatches mutant is "more sensitive" to glc depletion because of the low level of growth to begin with (even at 3%). Altogether, the data show that deletion of pub3+ is able to suppress the growth defect of the gad8ts mutant on low glc medium, suggesting it is the relevant ligase for Ght5 endocytosis. This is confirmed by microscopy observations of Ght5 localisation. However, I would again tone down the main conclusion, which I feel is far-reaching: "Combined with physical interaction data, these results strongly suggest that Aly3 recruits Pub3, but not Pub2, for ubiquitination of Ght5." Work on Rsp5 in baker's yeast has shown that Rsp5 function goes beyond cargo ubiquitination, including ubiquitination of arrestins (which is often required for their function as mentioned in the introduction) or other endocytic proteins (epsins, amphyphysin etc). I agree that the data are compatible with this model but there are other possible explanations. Anything that would block endocytosis would supposedly suppress the gad8ts phenotype.

Discussion

Some analogy with the regulation of the Bul arrestins by TORC1/Npr1 and PP2A/Sit4 could be mentioned (Mehri et al. 2012), at the discretion of the authors. The possibility that phosphorylation may neutralise a basic patch on Aly3 Ct, possibly involved in electrostatic interactions with Ght5 is very interesting. Regarding the effect of the mutations on Aly3 localisation (p.15 l.498), did the authors tag Aly3 with GFP? There are examples where proteins tagged with HA are not functional whereas tagging with GFP does not alter their function (eg. Rod1, Laussel et al. 2022) - and here Supp Fig 2 only relates to HA-tagging. Proof of a change in Aly3 localisation upon mutation would definitely be a plus (OPTIONAL).

Minor comments.

Introduction:

• I believe the text corresponding to the work on TXNIP is incorrect (p.5 l.127). TXNIP is degraded after its phosphorylation, not "rectracted" from the surface.
• For the sake of completion, the authors could add other references concerning the regulation of Rod1 in budding yeast such as Becuwe et al. 2012 J Cell Biol and O'Donnell et al. 2015 Mol Cell Biol, in addition to Llopis-Torregrosa et al. 2016.
• Other examples of the requirement for arrestin ubiquitination beyond Art1 (p.5 l.136-137) are listed in the ref cited: Kahlhofer et al. 2021.

Figures: In general, I think it would be clearer if the authors showed on the figures that the background strain in which the XXX gene is added (or its mutant forms) is a xxx∆ strain.

Referees cross-commenting

Cross review of Reviewer 1

• I don't believe that the authors "define a set of redundant c-terminal phosphorylation sites in Aly3", because phosphorylation is not proven.
• I thinks the points raised for Fig 3B are valid but the authors should focus on making their story conclusive before expanding to other data (except for the explanation of the smear, see my review). Also, I don't think 2NBDG actually works to measure Glc uptake.
• same for Fig 6 - not sure the interaction site mapping between Aly3 and Pubs would bring much value since there are more urgent things to do to make the story solid.

Cros review of Reviewer 3 - we have many overlaps, so briefly :

• I agree that the bibliography is incomplete (mentioned in my review)
• I agree that there is no demonstration of the phospho-status of Aly3, and it is a problem
• I agree that the results can be better quantified, esp. in the light of the points raised by this referee concerning the variability of expression of ST18A

Other specific comments :

• I agree that the statement that dephosphorylation activates alpha-arresting should be toned down - this was observed in several instances but there are examples of arrestin-mediated endocytosis which does not require their prior dephosphorylation.
• I fully agree that efforts could be made regarding the classification/nomenclature of arrestins in S. pombe, this had escaped my attention

Significance

strengths and limitations

This study aims at deepening our understanding of the regulation of endocytosis by signalling pathways through arrestin-like proteins in S. pombe. Ght5 is a nice model to study a physiological regulation, and the authors have a great set of tools at hand, including the discovery of Aly3 as the main arrestin for this regulation, and a signalling pathway (TORC2/Gad8) acting upstream. The main question is now to understand at the mechanistic level how TORC2 signaling impinges on the regulation of this arrestin.

Overall, the authors nicely demonstrate that C-terminal Ser/Thr residues are crucial for the function of Aly3 in Ght5 endocytosis. They propose a model whereby Aly3 phosphorylation by an unknownn kinase inhibits its function on Ght5 ubiquitination, which would favour its endocytosis. However, I think the conclusions are not always rigorous and the conclusions are sometimes far-reaching. The main problem is that much of the conclusions concern a potential phosphorylation of Aly3 which is not experimentally addressed. An additional issue is the fact that they look at Ght5 ubiquitination by co-immunoprecipitation in native conditions (or at least, it seems to me) which cannot be conclusive. Overall, I think some experiments should be performed to address (at least) these 2 points before the manuscript can be published, see detailed comments above.

Advance

This study, if completed carefully, would provide among the first examples of mapping of phosphorylation sites on arrestins, which are usually phosphorylated at many sites and are thus difficult to study. Few studies went down to this level in this respect (see Ivshov et al. eLife 2020). There are no changes in paradigms or new conceptual insights, but this work is a nice example of the conservation of these regulatory mechanisms.

Audience

Should be of interest for people studying basic research in the field of cell biology, signalling pathways, transporter regulation by physiology. Reviewer background is on the regulation of transporter endocytosis by signalling pathways and arrestin-like proteins.

Author response:

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

Public Reviews:

Reviewer #2 (Public Review):

Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.

(1) The conclusions of the paper are mostly supported by the data and in the revised manuscript clarification is provided concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3 and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. The revised manuscript more clearly indicates for each individual experiment which form is used. However, a discussion on the potential effects of the modifications on CCL5 in the results and discussion sections is still missing.

Many thanks for the reviewer's suggestion. We fully agree it is important to clarify the potential issue of Cy3 labeling, and believe it is more suitable in the Materials and Methods section (line 312-314).

(2) In general, authors used high concentrations of CCL5 in their experiments. In their reply to the comments they indicate that at lower CCL5 concentrations no LLPS is detected. This is important information since it may indicate the need for chemokine oligomerization for LLPS. This info should be added to the manuscript and comparison with for instance the obligate monomer CCL7 and another chemokine such as CXCL4 that easily forms oligomers may clarify whether LLPS is controlled by oligomerization.

We are pleased by the help of the reviewers and accordingly inserted a brief discussion as suggested (line 240-246).

(3) Statistical analyses have been improved in the revised manuscript.

Thanks to the reviewer for his/her comment.

Worth considering Brooks's distinction of essential versus incidental complexity. It's especially worth considering the instances where the "incidental" part comes from being incidental to the fact that if it were easier, there it would make a lot of people unhappy for reasons that I call "the consultant effect".

Reviewer #1 (Public Review):

The study identifies the epigenetic reader SntB as a crucial transcriptional regulator of growth, development, and secondary metabolite synthesis in Aspergillus flavus, although the precise molecular mechanisms remain elusive. Using homologous recombination, researchers constructed sntB gene deletion (ΔsntB), complementary (Com-sntB), and HA tag-fused sntB (sntB-HA) strains. Results indicated that deletion of the sntB gene impaired mycelial growth, conidial production, sclerotia formation, aflatoxin synthesis, and host colonization compared to the wild type (WT). The defects in the ΔsntB strain were reversible in the Com-sntB strain.

Further experiments involving ChIP-seq and RNA-seq analyses of sntB-HA and WT, as well as ΔsntB and WT strains, highlighted SntB's significant role in the oxidative stress response. Analysis of the catalase-encoding catC gene, which was upregulated in the ΔsntB strain, and a secretory lipase gene, which was downregulated, underpinned the functional disruptions observed. Under oxidative stress induced by menadione sodium bisulfite (MSB), the deletion of sntB reduced catC expression significantly. Additionally, deleting the catC gene curtailed mycelial growth, conidial production, and sclerotia formation, but elevated reactive oxygen species (ROS) levels and aflatoxin production. The ΔcatC strain also showed reduced susceptibility to MSB and decreased aflatoxin production compared to the WT.

This study outlines a pathway by which SntB regulates fungal morphogenesis, mycotoxin synthesis, and virulence through a sequence of H3K36me3 modification to peroxisomes and lipid hydrolysis, impacting fungal virulence and mycotoxin biosynthesis.

The authors have achieved majority of their aims at the beginning of the study, finding target genes, which led to catC mediated regulation of development, growth and aflatoxin metabolism. Overall most parts of the study is solid and clear.

Reviewer #1 (Public Review):

Summary:

In this manuscript by Beardslee and Schmitz, the authors undertook a screen for potential degrons - short peptide sequences at the C-terminus that would target the toxin VapC for degradation. The authors randomly mutagenized 5 amino acids appended to the C-terminus of VapC and transformed this library into E. coli to look for surviving cells when the VapC gene was expressed. The authors found an enrichment for tags ending Ala-Ala, and found that this enrichment was dependent on the presence of the ClpXP protease, since this sequence was not similarly enriched in a mutant lacking this protease. Moreover, the authors identify the sequence FKLVA as the tag with the highest fold enrichment in the screen and confirm that GFP tagged with this sequence is degraded by ClpXP with similar kinetics to GFP tagged with the ssrA-derived tag.

Strengths:

This study has two major implications for understanding the nature of degrons in E. coli. First, peptides ending Ala-Ala, and especially degrons resembling the ssrA degron are likely the most degradation-promoting sequences in E. coli. Second, these findings suggest that ClpXP is the most central protease, at least for this particular protein with a randomized C-terminus under the particular conditions of this screen. It is also notable that the ribosome quality control protein RqcH tags truncated proteins with an alanine tag in a template-free manner when the large ribosomal subunit is obstructed. Although E. coli doesn't encode RqcH, the utility of alanine-tagging for protein degradation likely extends to other organisms.

Weaknesses:

The authors remark and show that mutations that inactivate the VapC protein are enriched potentially more than the proteolysis tags. This is a limitation of the study and the authors have done well to describe this as it will inform future screens. Perhaps using a protein with more intermediate toxicity in future screens would help to prioritize C-terminal mutations instead of toxin-inactivating mutations.

For clarity, the authors should explain why the NNK structure of the random codons was used. Why is it important that the codon end with a G or T?

Authors state on page 7 that by determining enrichment of individual tags they can rank the relative Km for proteolysis of the individual tags. This statement is not accurate since the tag could variously impact its association with any of the proteases in the cell. Since Km is specific to each particular protease, these can't be ranked in vivo when all proteases are present.

Reviewer #2 (Public Review):

Summary:

The authors studied the sequence determinants of C-terminal tags that govern protein degradation in bacteria. They introduce a new strategy to determine degron sequences: Detox (Degron Enrichment by toxin). This unbiased approach links degron efficiency to cell growth as degrons are C-terminally fused to the toxin VapC, which inhibits protein translation. Selecting for bacterial growth and thus toxin degradation enabled the identification of potent degron derived from a randomized library of pentapeptides. Remarkably, most degrons show sequence similarity to the SsrA-tag, which is fused to incomplete polypeptides at stalled ribosomes by the tmRNA-tagging system. These findings underline the extraordinary efficiency of the SsrA-tag and the ClpXP protease in removing incomplete polypeptides and demonstrate that most proteins are spared from degradation by harboring different C-termini. The introduced method will be highly useful to determine degron sequences in other positions and other bacterial species.

Strengths:

The work introduces an innovative and powerful strategy to identify degron sequences in bacteria. The study is well-controlled and results have been thoroughly analyzed. It will now become important to broaden the technology, making it also accessible for more complex degrons.

Weaknesses:

The approach is efficient in identifying strong degron sequences that are predominantly recognized by the ClpXP protease. The sequence specificity of other proteolytic systems, however, is not efficiently addressed, pointing to a potential limitation of this technology. The GS-rich linker sequence connecting the degron and the toxin might also impact proteolysis and thus outcome.

Author response:

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

Key Considerations:

There seem to be two inconsistencies related to some results depicted in Figures 1, 2, 3 and 5.

Firstly, Figure 1 shows the effect on C_Las infection (_C_Las+) compared to the control (_C_Las-), where results show an increase of TAG, Glycogen, lipid droplet size, oviposition period, and fecundity. In Figures 2, 3, and 5, the authors establish the involvement of the genes _DcAKH, DcAKHR, and miR34 in this process, by showing that by preventing the function of these three factors the effects of _C_Las+ are lost. However, while Figure 1 shows the increase of TAG and lipid droplet size in _C_Las+, Figures 2, 3, and 5 do not show a significant elevation in TAG when comparing _C_Las- and _C_Las+.

Secondly, in addition to the absence of statistical difference in TAG and lipid droplet size observed in Figure 1, Figures 2, 3, and 5 show an increase in TAG and lipid droplet size after ds_DcAKH_ (Figure 2), ds_DcAKHR_ (Figure 3) and agomiR34 (Figure 5) treatments. Considering that AKH, AKHR, and miR34 are important factors to _C_Las-induce increase in TAG and lipid droplet size, one might expect a reduction in TAG and lipid droplet size when _C_Las+ insects are silenced for these factors, contrary to the observed results.

Thanks for your excellent suggestion. Lipid droplets are cellular organelles responsible for storing lipids within cells, playing a crucial role in fat metabolism and energy homeostasis. The formation and breakdown of lipid droplets involve a complex interplay of genes and enzymes, including DGAT (for synthesis), ATGL and HSL (for breakdown). In C_Las-negative _D. citri, there is a delicate balance between creasing and breaking down of lipid droplets. The enlargement of lipid droplet size following C_Las infection may result from a significantly higher synthesis rate compared to breakdown, as more energy is required during early ovarian development. The hormone AKH, a key player in fat metabolism, primarily stimulates fat breakdown. Therefore, when _DcAKH and DcAKHR are silenced without affecting fat synthesis, there is no enhancement of fat breakdown; instead, there is an accumulation of lipid droplets, resulting in their enlargement. This suggests that _C_Las infection affects both the breakdown and synthesis of lipid droplets, while AKH and AKHR primarily impact the breakdown, leading to similar outcomes. However, the underlying physiological mechanisms warrant further in-depth exploration.

Reviewer #1 (Recommendations For The Authors):

(1) Line 25: change "In addition" to "Additionally".

Thanks for your wonderful suggestion. We have changed “In addition” to “Additionally” in our revised manuscript (Line 26).

(2) Lines 60-72: Have there been any previous reports on the interaction between host AKH hormones and microorganisms in insects or animals? If yes, please add more background.

Thanks for your wonderful suggestion. We have added the interactions between host AKH hormones and microorganisms in insects (Line 74-81).

(3) Lines 82-95: add the following reference about the miR-275 of Diaphorina citri in the background. Nian, X., Luo, Y., He, X., Wu, S., Li, J., Wang, D., Holford, P., Beattie, G. A. C., Cen, Y., Zhang, S., & He, Y. (2024). Infection with 'Candidatus Liberibacter asiaticus' improves the fecundity of Diaphorina citri aiding its proliferation: A win-win strategy. Molecular Ecology, 33, e17214.

Thanks for your wonderful suggestion. We have added the sentence “in D. citri-C_Las interaction, _C_Las hijacks the JH signaling pathway and host miR-275 that targets the _vitellogenin receptor (DcVgR) to improve D. citri fecundity, while simultaneously increasing the replication of C_Las itself, suggesting a mutualistic interaction in _D. citri ovaries with _C_Las” in our revised manuscript (Line 97-100).

(4) In the figures of Nile red staining, the digit of the scale bar should be added.

Thanks for your wonderful suggestion. We have added the digit of the scale bar for Nile red staining in the Figure 1C, 2E, 3E, 5C.

(5) In Figures 2G-H, 3G-H, 5E-F, the presentation of data should be consistent with Figure 1D-E.

Thanks for your wonderful suggestion. We have changed figure 1D-E in our revised manuscript.

(6) In the discussion part, more information should be added about miR-275 and DcVgR from the above reference.

Thanks for your wonderful suggestion. We have added the information “In D. citri-C_Las interaction, _C_Las operates host hormone signaling and miRNA to mediate the mutualistic interaction between _D. citri fecundity and its replication” in Line 350-353.

(7) For the primer specific, please add the melting curves for qPCR primers of DcAKH, DcAKHR, Dcβ-ACT, U6, and miR-34 in the supplementary material.

Thanks for your wonderful suggestion. We have added the melting curves for qPCR primers of DcAKH, DcAKHR, Dcβ-ACT, U6 and miR-34 in the supplementary material of Figure S6.

(8) Line 476: Dcβ-ACT was indicated as a gene and should be Italic.

Thanks for your wonderful suggestion. We have changed “DcβACT” to “Dcβ-ACT” in our revised manuscript (Line 491).

(9) Reference style should be consistent and correct. Like [5], [10], [37], [47].

Thanks for your wonderful suggestion. We have revised them in our revised manuscript.

Reviewer #2 (Recommendations For The Authors):

(1) In order to better engage readers, I suggest emphasizing the "enhanced fecundity" in the title. A suggestion for the revised title is: Adipokinetic hormone signaling mediates the enhanced fecundity of Diaphorina citri infected by 'Candidatus Liberibacter asiaticus'.

Thanks for your wonderful suggestion. We have changed the title to “Adipokinetic hormone signaling mediates the enhanced fecundity of Diaphorina citri infected by 'Candidatus Liberibacter asiaticus'” in our revised manuscript.

(2) For the abstract, in lines 14-15, please change the first sentence to "Diaphorina citri serves as the primary vector for 'Candidatus Liberibacter asiaticus' (C_Las), the bacterium associated with the severe Asian form of huanglongbing." In line 18, delete "present". In line 19, change "increased" to "increasing". In line 21, change "triacylglycerol accumulation" to "the accumulation of triacylglycerol". In line 33, change "in _D. citri ovaries with C_Las" to "between _C_Las and _D. citri ovaries".

Thanks for your wonderful suggestion. We have revised them following your suggestion in our revised manuscript, including changed “Diaphorina citri is the primary vector of the bacterium, ‘Candidatus Liberibacter asiaticus’ (C_Las) associated with the severe Asian form of huanglongbing” to “_Diaphorina citri serves as the primary vector for 'Candidatus Liberibacter asiaticus' (C_Las), the bacterium associated with the severe Asian form of huanglongbing” in Line 15-16; deleted "present" in Line 19; changed "increased" to "increasing" in Line 20; changed "triacylglycerol accumulation" to "the accumulation of triacylglycerol" in Line 22; changed "in _D. citri ovaries with C_Las" to "between _C_Las and _D. citri ovaries" in Line 34.

(3) In lines 57-59, change "How D. citri maintains a balance between lipid metabolism and increased fecundity after infection with C_Las is not known." to "However, the mechanism of how _D. citri maintains a balance between lipid metabolism and increased fecundity after infection with _C_Las remains unknown.".

Thanks for your wonderful suggestion. We have changed " How D. citri maintains a balance between lipid metabolism and increased fecundity after infection with C_Las is not known" to "However, the mechanism of how _D. citri maintains a balance between lipid metabolism and increased fecundity after infection with _C_Las remains unknown" in our revised manuscript (Line 58-60).

(4) In Figure 1, "n.s" should be changed to "n.s.", "n.s." should be added in 13 DAE of Figure 1A, and the specific numerical value of the scale bar should be indicated on Figures 1C, 2E, 3E, and 5C.

Thanks for your wonderful suggestion. We have revised them in our revised manuscript.

(5) In all the figure legends, the "**P < 0.01,***P < 0.001" should be changed to "**p < 0.01,***p < 0.001".

Thanks for your wonderful suggestion. We have revised them in our revised manuscript.

(6) In Figures 1D-E, the preoviposition period and oviposition period were presented using a box diagram, but in other figures (including Figure 2G-H, Figure 3G-H, Figure 5E-F) these were shown using a column chart. Please keep the method of presentation consistent.

Thanks for your wonderful suggestion. We have revised the figure 1D-E in our revised manuscript.

(7) For discussion, in line 333, change "Increasing numbers" to "An increasing number". In line 334, change "vertically transmitted" to "transmitted vertically".

Thanks for  your wonderful suggestion. We have changed "Increasing numbers" to "An increasing number" in Line 345; changed "vertically transmitted" to "transmitted vertically" in Line 346 in our revised manuscript.

(8) In lines 338-342, change "There are few studies on the mechanisms underlying vector-bacteria interactions. However, Singh and Linksvayer (2020) [38] found that Wolbachia-infected colonies of Monomorium pharaonis had increased colony-level growth, accelerated colony reproduction, and shortened colony life cycles compared to those that were uninfected." to "Although there is limited research on the mechanisms underlying vectorbacteria interactions, Singh and Linksvayer (2020) [38] found that Wolbachia_infected colonies of _Monomorium pharaonis exhibited increased colony-level growth, accelerated colony reproduction, and shortened colony life cycles compared to uninfected colonies.".

Thanks for your wonderful suggestion. We have revised it in our revised manuscript (Line 350-355) .

(9) In line 370, delete "present". In lines 386-387, change "More and more miRNAs have been reported to be involved in the metabolic processes of insects including reproduction." to "There is increasing evidence implicating miRNAs in the metabolic processes of insects, particularly in relation to reproduction.".

Thanks for your wonderful suggestion. We have revised them in our revised manuscript, including deleted "present" in Line 383 and changed "More and more miRNAs have been reported to be involved in the metabolic processes of insects including reproduction" to "There is increasing evidence implicating miRNAs in the metabolic processes of insects, particularly in relation to reproduction" in Line 399-400.

(10) In line 423, change "After infection with C_Las, _D. citri are more fecund than their uninfected counterparts." to "Upon infection with C_Las, _D. citri exhibits enhanced fecundity compared to uninfected individuals.". In lines 424-425 and 439-440, change "the more offspring of D. citri, the more C_Las in the field" to "the increased offspring of _D. citri contributes to a higher presence of _C_Las in the field.". In Line 429, change " information" to "insights".

Thanks for your wonderful suggestion. We have revised them in our revised manuscript, including changed "After infection with C_Las, _D. citri are more fecund than their uninfected counterparts" to "Upon infection with C_Las, _D. citri exhibits enhanced fecundity compared to uninfected individuals" in Line 436-437; changed "the more offspring of D. citri, the more C_Las in the field" to "the increased offspring of _D. citri contributes to a higher presence of _C_Las in the field" in Line 438-439; changed "information" to "insights" in Line 443.

(11) In lines 446-447, change "The _C_Las-infected lemon plants and psyllids were monitored to detect _C_Las infection monthly using the quantitative polymerase chain reaction (qPCR)" to "Monthly monitoring of the _C_Las infection in both the lemon plants and psyllids was conducted using quantitative polymerase chain reaction (qPCR)".

Thanks for your wonderful suggestion. We have revised it in our revised manuscript (Line 460-461).

(12) In lines 452-458, how did the authors identify homologous sequences of AKH and AKHR for phylogenetic tree analysis and alignment of the amino acid sequences? From NCBI or other databases? The methodological details should be added.

Thanks for your wonderful suggestion. We have added the methodological details in our revised manuscript (Line 469-470).

(13) In line 476, Dcβ-ACT should be italic.

Thanks for your wonderful suggestion. We have changed “DcβACT” to italic in our revised manuscript (Line 491).

(14) In line 538, the manufacturer should be provided for Nile Red.

Thanks for your wonderful suggestion. We have provided the manufacturer of Nile Red in our revised manuscript (Line 553).

(15) Does miR-34 have any other target genes? If yes, whether they have any function in the fecundity improvement of D. citri after infected by CLas.

Thanks for your insightful suggestion. In addition to DcAKHR, we predicted three other genes have binding sites in 3’UTR with miR-34, including Innexin, T-box transcription factor TBX1, and fatty acid synthase. Despite this, the mRNA expression levels of all three genes remained unchanged between _C_Las-negative and _C_Las-postive females. Therefore, we believe that these genes are not implicated in the fecundity improvement.

(16) The reference format should be unified. Please revise references 10, 28, 43, 47, and 53.

Thanks for your wonderful suggestion. We have revised them in the revised manuscript.

Reviewer #1 (Public Review):

Summary:

This manuscript by Shea and Villeda furnishes the field with a valuable scRNAseq data set detailing microglial aging in the mouse hippocampus. They provide clear evidence that changes in microglial attributes begin in mid-life, well before time points when mice are traditionally considered to be "aging." It also adds to a growing body of data in the field demonstrating that there is substantial heterogeneity in microglial responses to aging. Using in vitro experiments and transgenic manipulations in mice, the authors show that transforming growth factor beta (TGFb1)-based signaling can potently impact microglial state, consistent with previous findings in the field. They also demonstrate that manipulation of microglial TGFb1-based signaling can impact hippocampus-dependent behaviors.

Limitations of the study lie primarily in reaching too far with interpretations of the data. The authors argue that changes in microglial transcriptome during midlife represent a type of "checkpoint," after which microglial aging can progress along distinct trajectories depending on the status of TGFb1 signaling. They also posit that a specific intermediate "stress response" state in midlife is mechanistically linked to a translational burst that drives the subsequent progression of microglia to an "inflammatory state." Unequivocal data to support these causal links is lacking, however. similarly, key additional experiments would be needed to demonstrate that TGFb1 signaling and microglial progression through these identified intermediate states are causally linked to cognitive decline.

Guidance for readers along with study strengths and caveats:

The present manuscript provides valuable strengthening and expansion to a growing body of data showing prominent changes in the microglial state during aging. Microarray(1), bulkRNAseq(2-5), scRNAseq(6,7), snRNAseq(8,9), and spatial transcriptomic(10) approaches have been leveraged to map changes in microglial transcriptome during aging in rodents, non-human primates, and humans. A number of these studies include the hippocampus (1,8,9,11) and have highlighted variation across brain regions in microglial transcriptomic changes during aging (1,11). They have also revealed differences across sex (7) as well as increased cell-to-cell heterogeneity (6-10), consistent with the idea that individual microglia can follow distinct aging trajectories. Several of these studies revealed that changes in microglial attributes begin in middle age (1,7,11), supporting similar observations from studies that did not use omics (12-14). The present manuscript utilizes scRNAseq of hippocampal microglia at adulthood (6mo), middle age (12mo), late middle age (18mo) and aging (24mo) to show that aging-induced changes in microglia begin in middle age and that microglia exhibit ample phenotypic heterogeneity during the progression of aging.

To gain further insight into the dynamics of microglial aging in the hippocampus, the authors used a bioinformatics method known as "pseudotime" or "trajectory inference" to understand how cells may progress through different functional states, as defined by cellular transcriptome (15,16). These bioinformatics approaches can reveal key patterns in scRNAseq / snRNAseq datasets and, in the present study, the authors conclude that a "stress response" module characterized by expression of TGFb1 represents a key "checkpoint" in microglial aging in midlife, after which the cells can move along distinct transcriptional trajectories as aging progresses. This is an intriguing possibility. However, pseudotime analyses need to be validated via additional bioinformatics as well as follow-up experiments. Indeed, Heumos et al, in their Nature Genetics "Expert Guidelines" Review, emphasize that "inferred trajectories might not necessarily have biological meaning." They recommend that "when the expected topology is unknown, trajectories and downstream hypotheses should be confirmed by multiple trajectory inference methods using different underlying assumptions."(15) Numerous algorithms are available for trajectory inference (e.g. Monocle, PAGA, Sligshot, RaceID/StemID, among many others) and their performance and suitability depends on the individual dataset and nature of the trajectories that are to be inferred. It is recommended to use dynGuidelines(16) for the selection of optimal pseudotime analysis methods. In the present manuscript, the authors do not provide any justification for their use of Monocle 3 over other trajectory inference approaches, nor do they employ a secondary trajectory inference method to confirm observations made with Monocle 3. Finally, follow-up validation experiments that the authors carry out have their own limitations and caveats (see below). Hence, while the microglial aging trajectories identified by this study are intriguing, they remain hypothetical trajectories that need to be proven with additional follow-up experiments.

To follow up on the idea that TGFb1 signaling in microglia plays a key role in determining microglial aging trajectories, the authors use RNAscope to show that TGFb1 levels in microglia peak in middle age. They also treat primary LPS-activated microglia with TGFb1 and show that this restores expression of microglial homeostatic gene expression and dampens expression of stress response and, potentially, inflammatory genes. Finally, they utilize transgenic approaches to delete TGFb1 from microglia around 8-10mo of age and scRNAseq to show that homeostatic signatures are lost and inflammatory signatures are gained. Hence, findings in this study support the idea that TGFb1 can strongly regulate microglial phenotype. Loss of TGFb1 signaling to microglia in adulthood has already been shown to cause decreased microglial morphological complexity and upregulation of genes typically associated with microglial responses to CNS insults(17-19). TGFb1 signaling to microglia has also been implicated in microglial responses to disease and manipulations to increase this signaling can improve disease progression in some cases(19). In this light, the findings in the present study are largely confirmatory of previous findings in the literature. They also fall short of unequivocally demonstrating that TGFb1 signaling acts as a "checkpoint" for determining subsequent microglial aging trajectory. To show this clearly, one would need to perturb TGFb1 signaling around 12mo of age and carry out sequencing (bulkRNAseq or scRNAseq) of microglia at 18mo and 24mo. Such experiments could directly demonstrate whether the whole microglial population has been diverted to the TGFb1-low aging trajectory (that progresses through a translational burst state to an inflammation state as proposed). Future development of tools to tag TGFb1 high or low microglia could also enable fate tracing type experiments to directly show whether the TGFb1 state in middle age predicts cell state at later phases of aging.

The present study would also like to draw links between features of microglial aging in the hippocampus and a decline in hippocampal-dependent cognition during aging. To this end, they carry out behavioral testing in 8-10mo old mice that have undergone microglial-specific TGFb1 deletion and find deficits in novel object recognition and contextual fear conditioning. While this provides compelling evidence that TGFb1 signaling in microglia can impact hippocampus-dependent cognition in midlife, it does not demonstrate that this signaling accelerates or modulates cognitive decline (see below). Age-associated cognitive decline refers to cognitive deficits that emerge as a result of the normative brain aging process(20-21). For a cognitive deficit to be considered age-associated cognitive decline, it must be shown that the cognitive operation under study was intact at some point earlier in the adult lifespan. This requires longitudinal study designs that determine whether a manipulation impacts the relationship between brain status and cognition as animals age (22-24). Alternatively, cross-sectional studies with adequate sample sizes can be used to sample the variability in cognitive outcomes at different points of the adult lifespan(22-24) and show that this is altered by a particular manipulation. For this specific study, one would ideally demonstrate that hippocampal-based learning/memory was intact at some point in the lifespan of mice with microglial TGFb1 KO but that this manipulation accelerated or exacerbated the emergence of deficits in hippocampal-dependent learning/memory during aging. In the absence of these types of data, the authors should tone down their claims that they have identified a cellular and molecular mechanism that contributes to cognitive decline.

A final point of clarification for the reader pertains to the mining of previously generated data sets within this study. The language in the results section, methods, and figure legends causes confusion about which experiments were actually carried out in this study versus previous studies. Some of the language makes it sound as though parabiosis experiments and experiments using mouse models of Alzheimer's Disease were carried out in this study. However, parabiosis and AD mouse model experiments were executed in previous studies (25,26), and in the present study, RNAseq datasets were accessed for targeted data mining. It is fantastic to see further mining of datasets that already exist in the field. However, descriptions in the results and methods sections need to make it crystal clear that this is what was done.

References:

(1) Grabert, K. et al. Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. (2016). doi:10.1038/nn.4222<br /> (2) Hickman, S. E. et al. The microglial sensome revealed by direct RNA sequencing. Nat. Neurosci. (2013). doi:10.1038/nn.3554<br /> (3) Deczkowska, A. et al. Mef2C restrains microglial inflammatory response and is lost in brain ageing in an IFN-I-dependent manner. Nat. Commun. (2017). doi:10.1038/s41467-017-00769-0<br /> (4) O'Neil, S. M., Witcher, K. G., McKim, D. B. & Godbout, J. P. Forced turnover of aged microglia induces an intermediate phenotype but does not rebalance CNS environmental cues driving priming to immune challenge. Acta Neuropathol. Commun. (2018). doi:10.1186/s40478-018-0636-8<br /> (5) Olah, M. et al. A transcriptomic atlas of aged human microglia. Nat. Commun. (2018). doi:10.1038/s41467-018-02926-5<br /> (6) Hammond, T. R. et al. Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes. Immunity 50, 253-271 (2019).<br /> (7) Li, X. et al. Transcriptional and epigenetic decoding of the microglial aging process. Nat. aging 3, 1288-1311 (2023).<br /> (8) Zhang, H. et al. Single-nucleus transcriptomic landscape of primate hippocampal aging. Protein Cell 12, 695-716 (2021).<br /> (9) Su, Y. et al. A single-cell transcriptome atlas of glial diversity in the human hippocampus across the postnatal lifespan. Cell Stem Cell 29, 1594-1610.e8 (2022).<br /> (10) Allen, W. E., Blosser, T. R., Sullivan, Z. A., Dulac, C. & Zhuang, X. Molecular and spatial signatures of mouse brain aging at single-cell resolution. Cell 186, 194-208.e18 (2023).<br /> (11) Soreq, L. et al. Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging. Cell Rep. 18, 557-570 (2017).<br /> (12) Hefendehl, J. K. et al. Homeostatic and injury-induced microglia behavior in the aging brain. Aging Cell (2014). doi:10.1111/acel.12149<br /> (13) Nikodemova, M. et al. Microglial numbers attain adult levels after undergoing a rapid decrease in cell number in the third postnatal week. J. Neuroimmunol. 0, 280-288 (2015).<br /> (14) Moca, E. N. et al. Microglia Drive Pockets of Neuroinflammation in Middle Age. J. Neurosci. 42, 3896-3918 (2022).<br /> (15) Heumos, L. et al. Best practices for single-cell analysis across modalities. Nat. Rev. Genet. 24, 550-572 (2023).<br /> (16) Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods: towards more accurate and robust tools. (2018). doi:10.1101/276907<br /> (17) Zöller, T. et al. Silencing of TGFβ signalling in microglia results in impaired homeostasis. Nat. Commun. 9, (2018).<br /> (18) Bedolla, A. et al. Microglia-derived TGF-β1 ligand maintains microglia homeostasis via autocrine mechanism and is critical for normal cognitive function in adult mouse brain. bioRxiv Prepr. Serv. Biol. (2023). doi:10.1101/2023.07.05.547814<br /> (19) Spittau, B., Dokalis, N. & Prinz, M. The Role of TGFβ Signaling in Microglia Maturation and Activation. Trends Immunol. 41, 836-848 (2020).<br /> (20) L. Nyberg, M. Lövdén, K. Riklund, U. Lindenberger, L. Bäckman, Memory aging and brain maintenance. Trends Cogn. Sci. 16, 292-305 (2012).<br /> (21) L. Luo, F. I. M. Craik, Aging and memory: A cognitive approach. Can. J. Psychiatry 53, 346-353 (2008).<br /> (22) Y. Stern, M. Albert, C. Barnes, R. Cabeza, A. Pascual-Leone, P. Rapp.<br /> A framework for concepts of reserve and resilience in aging. Neurobiol. Aging, 124 (2022), pp. 100-103, 10.1016/j.neurobiolaging.2022.10.015<br /> (23) Y. Stern, C.A. Barnes, C. Grady, R.N. Jones, N. Raz. Brain reserve, cognitive reserve, compensation, and maintenance: operationalization, validity, and mechanisms of cognitive resilience. Neurobiol. Aging, 83 (2019), pp. 124-129, 10.1016/j.neurobiolaging.2019.03.022<br /> (24) R. Cabeza, M. Albert, S. Belleville, F.I.M. Craik, A. Duarte, C.L. Grady, U. Lindenberger, L. Nyberg, D.C. Park, P.A. Reuter-Lorenz, M.D. Rugg, J. Steffener, M.N. Rajah. Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing. Nat. Rev. Neurosci., 19 (11) (2018), Article 11, 10.1038/s41583-018-0068-2<br /> (25) Palovics, R. et al molecular hallmarks of heterochronic parabiosis at single-cell resolution. Nature 603, 309-314 (2022)<br /> (26) Sala Frigerio, C. et al. The major risk factors for Alzheimer's Disease: age, sex, and genes modulate the microglial response to Abeta plaques. Cell Rep, 27, 1293-1306 (2019)

Reviewer #1 (Public Review):

Summary:

In this manuscript, "PAbFold: Linear Antibody Epitope Prediction using AlphaFold2", the authors generate a python wrapper for the screening of antibody-peptide interactions using AlphaFold, and test the performance of AlphaFold on 3 antibody-peptide complexes. In line with previous observations regarding the ability of AlphaFold to predict antibody structures and antigen binding, the results are mixed. While the authors are able to use AlphaFold to identify and experimentally validate a previously characterized broad binding epitope with impressive precision, they are unable to consistently identify the proper binding registers for their control [Myc-tag, HA-tag] peptides. Further, it appears that the reproducibility and generality of these results are low, with new versions of AlphaFold negatively impacting the predictive power. However, if this reproducibility issue is solved, and the test set is greatly increased, this manuscript could contribute strongly towards our ability to predict antibody-antigen interactions.

Strengths:

Due to the high significance, but difficulty, of the prediction of antibody-antigen interactions, any attempts to break down these predictions into more tractable problems should be applauded. The authors' approach of focusing on linear epitopes (peptides) is clever, reducing some of the complexities inherent to antibody binding. Further, the ability of AlphaFold to narrow down a previously broadly identified experimental epitope is impressive. The subsequent experimental validation of this more precisely identified epitope makes for a nice data point in the assessment of AlphaFold's ability to predict antibody-antigen interactions.

Weaknesses:

Without a larger set of test antibody-peptide interactions, it is unclear whether or not AlphaFold can precisely identify the binding register of a given antibody to a given peptide antigen. Even within the small test set of 3 antibody-peptide complexes, performance is variable and depends upon the scFv scaffold used for unclear reasons. Lastly, the apparent poor reproducibility is concerning, and it is not clear why the results should rely so strongly on which multi-sequence alignment (MSA) version is used, when neither the antibody CDR loops nor the peptide are likely to strongly rely on these MSAs for contact prediction.

Major Point-by-Point Comments:

(1) The central concern for this manuscript is the apparent lack of reproducibility. The way the authors discuss the issue (lines 523-554) it sounds as though they are unable to reproduce their initial results (which are reported in the main text), even when previous versions of AlphaFold2 are used. If this is the case, it does not seem that AlphaFold can be a reliable tool for predicting antibody-peptide interactions.

(2) Aside from the fundamental issue of reproducibility, the number of validating tests is insufficient to assess the ability of AlphaFold to predict antibody-peptide interactions. Given the authors' use of AlphaFold to identify antibody binding to a linear epitope within a whole protein (in the mBG17:SARS-Cov-2 nucleocapsid protein interaction), they should expand their test set well beyond Myc- and HA-tags using antibody-antigen interactions from existing large structural databases.

(3) As discussed in lines 358-361, the authors are unsure if their primary control tests (antibody binding to Myc-tag and HA-tag) are included in the training data. Lines 324-330 suggest that even if the peptides are not included in the AlphaFold training data because they contain fewer than 10 amino acids, the antibody structures may very well be included, with an obvious "void" that would be best filled by a peptide. The authors must confirm that their tests are not included in the AlphaFold training data, or re-run the analysis with these templates removed.

(4) The ability of AlphaFold to refine the linear epitope of antibody mBG17 is quite impressive and robust to the reproducibility issues the authors have run into. However, Figure 4 seems to suggest that the target epitope adopts an alpha-helical structure. This may be why the score is so high and the prediction is so robust. It would be very useful to see along with the pLDDT by residue plots a structure prediction by residue plot. This would help to see if the high confidence pLDDT is coming more from confidence in the docking of the peptide or confidence in the structure of the peptide.

(5) Related to the above comment, pLDDT is insufficient as a metric for assessing antibody-antigen interactions. There is a chance (as is nicely shown in Figure S3C) that AlphaFold can be confident and wrong. Here we see two orange-yellow dots (fairly high confidence) that place the peptide COM far from the true binding region. While running the recommended larger validation above, the authors should also include a peptide RMSD or COM distance metric, to show that the peptide identity is confident, and the peptide placement is roughly correct. These predictions are not nearly as valuable if AlphaFold is getting the right answer for the wrong reasons (i.e. high pLDDT but peptide binding to a non-CDR loop region). Eventual users of the software will likely want to make point mutations or perturb the binding regions identified by the structural predictions (as the authors do in Figure 4).

Author response:

Reviewer #1 (Public Review):

This manuscript presents an exciting new method for separating insulin secretory granules using insulator-based dielectrophoresis (iDEP) of immunolabeled vesicles. The method has the advantage of being able to separate vesicles by subtle biophysical differences that do not need to be known by the experimenter, and hence could in principle be used to separate any type of organelle in an unbiased way. Any individual organelle ("particle") will have a characteristic ratio of electrokinetic to dielectrophoretic mobilities (EKMr) that will determine where it migrates in the presence of an electric field. Particles with different EKMr will migrate differently and thus can be separated. The present manuscript is primarily a methods paper to show the feasibility of the iDEP technique applied to insulin vesicles. Experiments are performed on cultured cells in low or high glucose, with the conclusion that there are several distinct subpopulations of insulin vesicles in both conditions, but that the distributions in the two conditions are different. As it is already known that glucose induces release of mature insulin vesicles and stimulates new vesicle biosynthesis and maturation, this finding is not necessarily new, but is intended as a proof of principle experiment to show that the technique works. This is a promising new technology based on solid theory that has the possibility to transform the study of insulin vesicle subpopulations, itself an emerging field. The technique development is a major strength of the paper. Also, cellular fractionation and iDEP experiments are performed well, and it is clear that the distribution of vesicle populations is different in the low and high glucose conditions. However, more work is needed to characterize the vesicle populations being separated, leaving open the possibility that the separated populations are not only insulin vesicles, but might consist of other compartments as well. It is also unclear whether the populations might represent immature and mature vesicles, distinct pools of mature vesicles such as the readily releasable pool and the reserve pool, or vesicles of different age. Without a better characterization of these populations, it is not possible to assess how well the iDEP technique is doing what is claimed.

Major comments:

1) There is no attempt to relate the separated populations of vesicles to known subpopulations of insulin vesicles such as immature and mature vesicles, or the more recently characterized Syt9 and Syt7 vesicle subpopulations that differ in protein and lipid composition (Kreutzberger et al. 2020). Given that it is unclear exactly what populations of vesicles will be immunolabeled (see point #2 below), it is also possible that some of the "subpopulations" are other compartments being separated in addition to insulin vesicles. It will be important to examine other markers on these separated populations or to perform EM to show that they look like insulin vesicles.

We thank the reviewer for this comment and have added the following to the discussion:

“The intensity peaks we observed at specific EKMr values likely correspond to some of the previously described insulin vesicle subpopulations34,54-57. Larger particles are expected to have a smaller EKMr value compared to smaller particles50. Subpopulations containing larger insulin vesicles, such as a mature pool34,54, synaptotagmin IX-positive vesicles57, or docked vesicles near the plasma membrane34 may have lower EKMr values than smaller immature vesicles. Additionally, phosphatidylcholine lipids increase the zeta potential of tristearoylglycerol crystals58. This effect may extend to insulin vesicle subpopulations containing more phosphatidylcholine, such as young insulin vesicles55 which could lead to higher EKMr values. Taken together, these two properties may be used to predict the EKMr values of known insulin vesicle subpopulations. For example, insulin vesicles with EKMr values of 1-2×109 V/m2 (Fig. 4C) may represent a synaptotagmin IX-positive subpopulation due to their larger radii and depletion under glucose stimulation. Additionally, young insulin vesicles may have EKMr values between 5 and 7.5×109 V/m2 (Fig. 4C) due to higher amounts of phosphatidylcholine present in this subpopulation55. In this EKMr range, we observed a higher intensity for glucose-treated cells which may suggest biosynthesis of new vesicles. Immature insulin vesicles are likely to have higher EKMr values due to their smaller size34, such as an EKMr value between 1.5-1.6×1010 V/m2 (Fig. 4C). Here we demonstrated the capabilities of DC-iDEP to separate insulin vesicle subpopulations in an unbiased manner. Future experiments using chemical probes to label subpopulations will be useful to accurately define the EKMr values associated with specific subpopulations.” pages 7-8, lines 176-191

Furthermore, we have conducted additional experiments using a modified INS-1 cell line with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61) in order to visualize a more complete population of insulin vesicles. By using this cell line, we have performed confocal microscopy, transmission electron microscopy, and cryo-electron microscopy experiments, demonstrating that the isolated vesicles resemble insulin vesicles and contain GFP-tagged C-peptide (Fig. 1-S3). While we acknowledge that further investigation using a more detailed labeling strategy of known insulin vesicle populations with DC-iDEP would be informative, we believe it is beyond the scope of our initial proof-of-concept experiments.

The following text was added to the results section to describe our additional microscopy analysis:

“To verify that the insulin vesicles were intact prior to DC-iDEP, we imaged a modified INS-1E cell line that contains a human insulin and green fluorescent protein-tagged C peptide (hPro-CpepSfGFP).49 This GFP tag allowed for quick visual verification of intact vesicles using fluorescence confocal microscopy. We observed distinct puncta rather than a diffuse GFP signal which indicated that the vesicles were intact and not ruptured. Further analysis of isolated vesicles was done using EM. We observed intact vesicles with the expected size and shape using both transmission electron microscopy (TEM) and cryo-electron microscopy (cryo-EM) (Fig. 1—figure supplement 3).” Page 5, lines 104 – 109.

2) An antibody to synaptotagmin V is used to immunolabel vesicles, but there has been confusion between synaptotagmins V and IX in the literature and it isn't clear what exactly is being recognized by this antibody (this reviewer actually thinks it is Syt 9). If it is indeed recognizing Syt 9, it might already be labeling a restricted population of insulin vesicles (Kreutzberger et al. 2020). The specificity of this antibody should be clarified. Furthermore, Figure 2 is not convincing at showing that this synaptotagmin antibody specifically labels insulin vesicles nor is there convincing colocalization of this synaptotagmin antibody with insulin vesicles. In the image shown, several cells show very weak or no staining of both insulin and the synaptotagmin. The highlighted cell appears to show insulin mainly in a perinuclear structure (probably the Golgi) rather than in mature vesicles (which should be punctate), and insulin is not particularly well-colocalized with the synaptotagmin. Other cells in the image appear to have even less colocalization of insulin and synaptotagmin, and there is no quantification of colocalization. It seems possible that this antibody is recognizing other compartments in the cell, which would change the interpretation of the populations measured in the iDEP experiments. It would also be good to perform synaptotagmin staining under glucose-stimulating conditions, in case this alters the localization.

We thank the reviewer for bringing this issue to our attention. The antibody originally used in Figure 2 recognizes the 386 aa isoform of synaptotagmin, which is called Syt 9 in the paper mentioned above (Kreutzberger et al. 2020). We have edited our manuscript to label this antibody as “Synaptotagmin IX” to match the existing literature. This antibody, therefore, likely labels only a subset of insulin vesicles. We believe that populations measured in the iDEP experiments consist solely of insulin vesicles, as supported by Western blot and dynamic light scattering results (Fig. 1—figure supplement 2B-C), as well as EM images (Fig. 1—figure supplement 3). Even with a subset of insulin vesicles, these results show the potential of this method, as iDEP analysis reveals heterogeneity within the population of Syt 9-positive insulin vesicles. We have replaced the original immunofluorescence images in Figure 2 with images that are more representative of INS-1E cells. We recognize that immuno-labeling did not yield perfect co-localization, which was expected. However, these experiments do provide valuable insights into the promise of using DC-iDEP for more in-depth separation analysis. Future work will use a modified INS-1 cell line or mouse model with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61) in order to visualize a less restricted set of insulin vesicles, avoiding the limitations associated with antibodies confined to a specific insulin vesicle subpopulation.

3) The EKMr values of the vesicle populations between the low and high glucose conditions don't seem to precisely match. It is unclear if this just a technical limitation in comparing between experiments or instead suggests that glucose stimulation does not just change the proportion of vesicles in the subpopulations (i.e. the relative fluorescent intensities measured), but rather the nature of the subpopulations (i.e. they have distinct biophysical characteristics). This again gets to the issue of what these vesicle subpopulations represent. If glucose stimulation is simply converting immature to mature vesicles, one might expect it to change the proportion of vesicles, but not the biophysical properties of each subpopulation.

We thank the reviewer for this question. We agree that glucose likely shifts the proportion of vesicles within a specific EKMr value rather than impacting the overall biophysical characteristics of all vesicles. We have performed new statistical analysis as suggested and rewritten this section to better explain the differences between conditions.

“Visual inspection of the collected data revealed generally similar patterns of vesicles collected at specific EKMr values (Fig. 4). However, at 1200 V we achieved adequate separation of vesicle populations to discern unique populations of vesicles from cells treated with glucose compared to no treatment. Using a two-way ANOVA, we found a statistically significant interaction between the effect of treatment on vesicles collected at each EKMr value for data collected only at 1200 V [F (8, 45) = 3.61, p= 0.003]. A Bonferroni post hoc test revealed a significant difference in the intensity or quantity of vesicles collected between treated and untreated samples at 1.10x109 V/m2 (p=0.0249), 5.35x109 V/m2 (p=0.0469), 7.45x109 V/m2 (p=0.0369). These differences reflect a shift in the populations of insulin vesicles upon glucose stimulation.” Page 7, lines 158-165

We have also now directly addressed the potential identities of the different populations in the discussion section. This was addressed in major comment #1 and on page 7 lines, 176-191 of the manuscript.

4) The title of the paper promises "isolation" of insulin vesicles, but the manuscript only presents separation and no isolation of the separated populations. Isolation of the separated populations is important to be able to better define what these populations are (see point #1 above). Isolation is also critical if this is to be a valuable technique in the future. Yet the paper is unclear on whether it is actually technically feasible to isolate the populations separated by iDEP. In line 367, it states "this method provides a mechanism for the isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis (imaging, proteomics, lipidomics, etc.)." However, in line 361 it says "developing the capability to port the collected individual boluses will enable downstream analyses such as mass spectrometry or electron microscopy," suggesting that true isolation of these populations is not yet feasible. This should be clarified.

We thank the reviewer for pointing this out. We have modified the text and title to put more focus on our ability to separate vesicles rather than isolate. We agree that the isolation and further biophysical characterization of these subpopulations will be critical to understanding them. However, this capability is still in development. We have made the following change to clarify that a way to isolate these subpopulations once iDEP-assisted separation has occurred is currently being developed.

Title: “Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles”

“this method serves as a stepping stone towards isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis…” page 9, line 230-232.

Reviewer #2 (Public Review):

This manuscript used DC-iDEP, a technology previously used on other organelle preparations to isolate insulin secretory granules from INS1 cells based on differences in dielectrophoretic and electrokinetic properties of synaptotagmin V positive insulin granules.

The major motivation presented for this work is to provide a methodology to allow for more sensitive isolation of subpopulations of granules allowing better understanding of the biochemical composition of these populations. This manuscript clearly demonstrates the ability of this technology to separate these subpopulations which will allow for future biochemical characterizations of insulin granules in future studies.

After proving these subpopulations can be observed, this method was then utilized to show there are shifts in these subpopulations when granules are isolated from glucose stimulated cells. Overall the method of isolation is novel and could provide a tool for further characterization of purified secretory granules.

The observation of glucose stimulation causing shifts in subpopulations is unsurprising. Glucose stimulation could cause a depletion of insulin and other secretory content from a subset of granules. It would be expected that this loss of content would cause a shift in electrochemical properties of the granules, but this is a nice confirmation that the isolation method has the sensitivity to delineate these changes.

Major comments:

1) It is unclear what Synaptotagmin isoform is being looked at. Synaptotagmin V and IX have been repetitively interchanged in the literature. See note in syt IX section of "Moghadam and Jackson 2013 Front. Endocrinology" or read "Fukuda and Sagi- Eisenberg Calcium Bind Proteins 2008".

The 386 aa. isoform that is abundant in PC12 cells has been robustly observed in INS1 cells in multiple studies and has been frequently referred to as syt IX. The sequence the antibody was raised against should be determined from the company where this was purchased and then this should be mapped to to which isoform of Synaptotagmin by sequence and clarified in the text.

We thank the reviewer for this comment. The supplier (Thermo Fisher Scientific) calls this antibody “Synaptotagmin V.” As it recognizes the 386 aa synaptotagmin isoform, we have changed references to this antibody to call it “Synaptotagmin IX” to match the existing literature.

2) Immunofluorescence of insulin and syt V is confusing. The example images do not appear to show robust punctate structures that are characteristic of secretory granules (in both the insulin and syt V stain).

We appreciate the reviewer bringing this point to our attention. We agree that the immunofluorescence images in Figure 2 are not representative of typical INS-1E cells and have replaced the original image for Figure 2 with new images that show punctate structures that are more characteristic of secretory granules. These images also have better colocalization of insulin and synaptotagmin V (now labeled synaptotagmin IX) than the original image, with Pearson’s R values of 0.66 and 0.64.

3) In the discussion it says, "Finally, this method provides a mechanism for the isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis (imaging, proteomics, lipidomics, etc.) that otherwise would not be possible given the low-abundance components of these subpopulations."

It would help to elaborate more on the yield and concentrations of isolated granules. This would give a better sense of what level of biochemical characterization could be performed on sub- populations of granules.

We thank the reviewer for this comment. This line has been changed to clarify the current capabilities of iDEP, as subpopulations cannot presently be removed from the channel.

“this method serves as a stepping stone towards isolation and concentration of fractions which show the largest difference between the two population patterns for further bioanalysis…” page 9 line 230-232.

Once it is possible to isolate subpopulations from the channel, we expect to obtain sufficient sample for further characterization. We anticipate that biophysical characterization such as imaging will be highly feasible, and small-scale proteomics could also be possible. However, currently we have not measured the concentration of isolated vesicles due to complications in the isolation steps. If the quantity of isolated subpopulations proves inadequate for proteomic analysis, we plan to scale up our cell culture to generate enough insulin vesicles for further biochemical characterization. However, these experiments are out of scope for our current work, so we removed details on this idea in the Introduction and Discussion.

Reviewer #3 (Public Review):

The manuscript from Barekatain et al. is investigating heterogeneity within the population of insulin vesicles from an insulinoma cell line (INS-1E) in response to glucose stimulation. Prevailing dogma in the beta-cell field suggests that there are distinct pools of mature insulin granules, such as ready-releasable and a reserve pool, which contribute to distinct phases of insulin release in response to glucose stimulation. Whether these pools (and others) are distinct in protein/lipid composition or other aspects is not known, but has been suggested. In this manuscript, the authors use density gradient sedimentation to enrich for insulin vesicles, noting the existence of a number of co-purifying contaminants (ER and mitochondrial markers). Following immunolabeling with synaptotagmin V and fluorescent-conjugated secondary antibodies, insulin vesicles were applied to a microfluidic device and separated by dielectrophoretic and electrokinetic forces following an applied voltage. The equilibrium between these opposing forces was used to physically separate insulin granules. Here some differences were observed in the insulin (Syt V positive) granule populations, when isolated from cells that were either non-stimulated or stimulated with glucose, which has been suggested previously by other studies as noted by the authors; however in the current manuscript, the inclusion of a number of control experiments may provide a better context for what the data reveal about these changes.

The major strength of the paper is in the use of the novel, highly sophisticated methodology to examine physical attributes of insulin granules and thus begin to provide some insight into the existence of distinct insulin granule populations within a beta-cell -these include insulin granules that are maturing, membrane- docked (i.e. readily releasable), in reserve, newly-synthesized, aged, etc. Whether physical differences exist between these various granule pools is not known. In this capacity, the technical abilities of the current manuscript may begin to offer some insight into whether these perceived distinctions are physical.

The major weakness of the manuscript is that the study falls short in terms of linking the biology to the sophisticated changes observed and primarily focuses on differences in response to glucose. Without knowing what the various populations of granules are, it is challenging to understand what the changes in response to glucose mean.

Specific concerns are as follows:

1) There is confusion on what the DC-iDEP separation between stimulated and stimulated cells reveals. Do these changes reflect maturation state of granules, nascent vs. old granules? Ready- releasable vs. reserve pool? The comments in the text seem to offer all possibilities.

We thank the reviewer for this comment. Additional experiments will be useful to concretely define the physical nature of these subpopulations. Our primary goal in this study is to assess the utility of DC-iDEP in reproducibly separating these subpopulations. Our current results reflect variations in the amounts of subpopulations described in the literature and/or in currently uncharacterized subpopulations. As addressed in Reviewer #1 question #1, we have added to the discussion to review these possibilities (Page 7-8, lines 176-191).

2) It is unclear what we can infer regarding the physical changes of granules between the stimulated states of the cells. Without an understanding of the magnitude of the effect, it is unclear how biologically significant these changes are. For example, what degree of lipid or protein remodeling would be necessary to give a similar change?

We thank the reviewer for this question. Separation by iDEP is sufficiently sensitive to distinguish particles with minimal differences between them. For example, we could successfully separate wild type GFP from a point mutation variant of GFP. We anticipate that this method is capable of distinguishing vesicles with greater physical differences between them resulting in more distinct EKMr values. However, significant future experiments are likely necessary to determine the extent of lipid and protein remodeling between each subpopulation to define the biological significance of each subpopulation.

3) The reliance on a single vesicle marker, Syt V, is concerning given that granule remodeling is the focus.

We appreciate the reviewer’s concern. The current manuscript focuses on synaptotagmin V (IX)-positive insulin vesicles. The results of these experiments demonstrate the capabilities of iDEP to reveal heterogeneity in a seemingly similar set of particles. In future experiments we plan to use the modified INS-1 cell line with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61). All insulin vesicles from this cell line contain GFP-tagged C-peptide, and therefore would allow for the detection of a more complete set of insulin vesicles. The results from the current manuscript provide the proof-of-concept validation that this method is promising for understanding vesicle remodeling in more detail in the future.

4) Additional confirmation that the isolated vesicles are in fact insulin granules would be helpful. As noted, granules were gradient enriched, but did carry contaminants. Note that the microscopy image provided does not provide any real validation for this marker.

Further confirmation that the immune-isolated vesicles are in fact insulin granules should be included. EM with immunogold labeling post-SytV enrichment would be a potential methodology to confirm.

We thank the reviewer for this comment. We have performed new immunofluorescence imaging to demonstrate the overlap of insulin and synaptotagmin (Fig 2). Additionally, we have performed microscopy experiments with a modified INS-1 cell line with a GFP-tagged C-peptide (hPro-CpepSfGFP, GRINCH cells RRID:CVCL_WH61) in order to provide evidence of these granules’ identity. Fluorescence microscopy revealed that the isolated granules contain GFP-tagged C-peptide (Fig. 1—figure supplement 3A), while transmission electron microscopy and cryo-electron microscopy confirmed that these vesicles have radii within the correct range to be considered insulin vesicles (Fig 1—figure supplement 3B-C). We added the following text in the results section to describe the new results included:

“To verify that the insulin vesicles were intact prior to DC-iDEP, we imaged a modified INS-1E cell line that contains a human insulin and green fluorescent protein-tagged C peptide (hPro-CpepSfGFP).49 This GFP tag allowed for quick visual verification of intact vesicles using fluorescence confocal microscopy. We observed distinct puncta rather than a diffuse GFP signal which indicated that the vesicles were intact and not ruptured. Further analysis of isolated vesicles was done using EM. We observed intact vesicles with the expected size and shape using both transmission electron microscopy (TEM) and cryo-electron microscopy (cryo-EM) (Fig. 1—figure supplement 3). Page 5, lines 104 – 109.

5) It would be useful to understand if the observed effects are specific to the INS-1E cell line or are a more universal effect of glucose on beta-cells.

We agree with the reviewer that it would be interesting to study these effects in primary beta cells. While we expect to see similar results in these cells, there may be differences in the population variations or EKMr values. However, working with beta cells is currently beyond the scope of this study, as our primary focus is on validating this approach.

Author response:

Reviewer #1 (Public Review):

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

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

We thank the reviewer for carefully reading our text and for the helpful recommendations. We have performed additional experiments and analysis to address the raised issues (detailed below). In addition, we have streamlined and shortened the text to improve its clarity and focus on the biological story.

Reviewer #2 (Public Review):

In this study, Wong and colleagues investigate mechanisms leading to input-specificity of LTP. They focus on the trafficking of AMPA receptors as the surface accumulation of AMPARs is one of the key features of potentiated synapses. They employ an elegant strategy to label endogenous GluA1 with a HaloTag using CRISPR-based technology and succeed to find targeting site which does not interfere with receptor's trafficking or function. This allowed them to visualize and track single receptors in endosomes as well as at the plasma membrane of primary rat hippocampal neurons. They develop and extend particle tracking and molecule counting algorithms to analyze active transport and diffusion of AMPARs and, as expected find that neuronal activation leads to increased surface expression of labelled AMPARs. Interestingly, they also observe a strong decrease in long-range motion of AMPAR-containing vesicles upon induction of chemical LTP. From this point, the manuscript focuses on explaining this observation. The authors switch from a global activation protocol to glutamate uncaging to induce LTP at individual synapses. Also, in these settings, they measure the reduction in mobile vesicle fraction within about 30 µm long dendritic segment containing the activated spine. In search of an explanation, they investigate activity-dependent actin polymerization as a possible confinement factor that could change the motility of organelles in dendrites. Their hypotheses is based on pre-existing literature demonstrating the role of F-actin in trapping and stalling dendritic endolysosomes as well similar role of F-actin in non-neuronal cells. Indeed, the authors convincingly show that pharmacological depolymerization or stabilization of F-actin bidirectionally impacts the trafficking behavior of AMPAR-containing vesicles in the dendritic shaft. To directly visualize effects of structural LTP at individual synapses on dendritic actin cytoskeleton, they employ a F-actin-binding probe Tractin. Here they find that cLTP results in the formation of dendritic F-actin fibers and bundles arranged in a network. The spatial extent of such a network correlates with an area where AMPAR vesicles exhibit decreased motility. Although this makes sense, I have some concerns about these experiments.

Tractin has been previously published as F-actin marker but like several other binding probes (i.e. lifeact), it affects F-actin structure and dynamics. The large number of F-actin bundles is not very typical for dendrites of hippocampal neurons and might be an artifact of Tractin overexpression. It is difficult to judge whether this is a case because there is no comparison with the endogenous situation where F-actin is labelled directly. The final series of experiments focus on the role of processive myosins in stalling and exocytosis of AMPAR vesicles. To address this point, the authors employ a mixture of three different myosin inhibitors and show that although myosins are not responsible for increased vesicle confinement they facilitate exocytosis of AMPARs. What I find somewhat missing are data and examples of AMPAR trafficking into dendritic spines. Also here, stronger experimental support could benefit the conclusions.

Overall, the authors achieved the aims of their study. They demonstrated that synapse-specific potentiation results in signaling which triggers actin polymerization in dendritic shaft beneath the activated input. This leads to trapping and accumulation of AMPAR-containing endosomes which then have higher probability to be delivered and secreted at activated dendritic spines. In addition to conceptual advance of this work, several state-of-the-art labeling and analysis techniques where developed in this project and they will likely be used by other groups.

We thank the reviewer for raising these important issues with regards to the use of tractin as a marker for actin polymerization. We have performed additional experiments (detailed below) using phalloidin and also dominant negative inhibitors of myosin Va, Vb, and VI in order to strengthen our conclusions. We find that inducing synaptic activity with cLTP increases phalloidin labeling and the appearance of F-actin fibers. Moreover, inhibition of myosin Va and Vb (but not VI) using their dominant negative c-terminal domains recapitulates the effects of pharmacological inhibition on both the motion states and directional bias of GluA1-HT vesicles in response to cLTP.

With regards to AMPAR trafficking into spines, we and others have found that GluA1-containing vesicles rarely enter dendritic spines (see response to Reviewer #2, comment 3). Furthermore, exocytic events occur largely at extrasynaptic sites, such as on the dendritic shaft (Figure 5-video 1-3; Lin et al., 2007; Makino et al., 2009; Patterson et al., 2010). Consequently, we believe vesicles are concentrated proximal to synaptic activity in the dendritic shaft rather than in the dendritic spine itself, creating a larger reservoir of intracellular AMPARs that can exocytose during synaptic activity. Others have demonstrated that surface bound AMPARs diffuse across the cell membrane into stimulated synapses where they are captured (Choquet and Opazo, 2022).

We also thank the reviewers for acknowledging the conceptual and technical advances in this work.

Reviewer #3 (Public Review):

Wong et al. developed a new versatile approach with a robust signal to track protein dynamics by inserting a tag into the endogenous loci and different properties of fluorescent dyes for conjugation. Using this approach, the authors monitor the trafficking of Fluorescent dye and Halo-tagged GluA1 with time-lapse imaging and found that neuronal stimulation induces GluA1 accumulation surrounding stimulated synapses on dendritic shafts and actin polymerization at synapses and dendrites. Furthermore, combining with pharmacological manipulations of actin polymerization or myosin activity, the authors found that actin polymerization facilitates exocytosis of GluA1 near activated synapses. The new approach may provide broad impacts upon appropriate control experiments, and the practical application of this approach to GluA1 trafficking upon neuronal activation is significant. However, there are several weaknesses, including confirmation of activity of the tagged receptors and receptor specificity mimicking endogenous LTP machinery. If the receptor tagged by the new robust approach reflects endogenous machinery, this approach will provide a big opportunity to the community as a versatile method to visualize a protein not visualized previously.

Although we use methods previously demonstrated to stimulate LTP, we do not ourselves demonstrate LTP using electrophysiological methods, and consequently we have changed the text to focus on synaptic plasticity (specifically structural plasticity). Furthermore, we confirm the activity of HaloTag knock-in receptors by expressing GluA1-HT and GluA1-HT-SEP in HEK293T cells and performing whole-cell patch clamp experiments. We find that GluA1-HT and GluA1-HT-SEP responds to glutamate in a similar manner to untagged GluA1.

We also thank the reviewer for acknowledging the novelty of our strategy.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Reply to reviewers

First, we would like to extend our gratitude to all reviewers for their supportive and enthusiastic feedback, which acknowledges our study as an interesting, well-executed, and well-documented contribution to the field. We are also pleased that the novelty and significance of our work have been recognized and appreciated.

As highlighted by reviewers 2, 3, and 4, our research represents a substantial advancement in understanding the mechanisms that coordinate the development of different cell types. Our findings have broader implications for developmental biology. We also thank the reviewers for their valuable insights, which have significantly improved the overall readability of our manuscript. We have carefully considered all minor corrections and text modifications they had suggested and made amendments accordingly.

The reviewers proposed several complementary experiments to enhance and clarify our points. We have conducted most of these experiments, with one exception (detailed below), and incorporated the corresponding results into this revised version of the manuscript.

Additionally, reviewers agreed that higher resolution images depicting the interactions between tendon and myoblast membranes would strengthen our manuscript. In response, we are pleased to present new high-resolution images of Ama::EGFP localization with respect to tendon and muscle cells, obtained using Zeiss Airyscan technology. We also provide new images using newly generated flies that allow simultaneous observation of both myoblast and tendon membranes.

We believe these modifications substantially enhance the quality and interest of our results, as already highlighted by the reviewers.

__Referees cross-commenting: __

All reviewers agreed* that "this is an interesting study that is well done and well documented. I agree with reviewer 1 that the study would further benefit from better imaging of the cellular extensions of tendons and myoblasts to see how both cell types interact." *

Reply: We agree with this point. To address it, we analyzed leg discs from Sr-Gal4>UAS-myrGFP line (labelling tendon membranes) crossed with a newly generated line R32D05::CD4TdTomato (myoblast specific expression of membrane tagged Tomato protein). Using confocal Zeiss Airy Scan technology, we generated high resolution images for which both tendon cell extensions and myoblast membranes are simultaneously visualized. These images are included in the new Figure 2 (O, P and O', P'). To be noticed: as we also provide new high resolution images of Ama::EGFP and Nrt localizations (Fig. 2 M, N and M', N'), we removed images of zoom in of 5h APF leg disc.

REVIEWER 1

Moucaud et al carried out single cell sequencing on myoblasts from the developing drosophila leg muscles, focusing on gene expressions overlapping with tendon and muscle cells. This study proposes that neuronal cell adhesion molecules Ama and Nrt interact in myoblast and tendon adhesion to support tendon and in proliferation of muscle progenitors. This study traces Ama and Nrt expression with various drosophila mutant strains and provides evidence to support its claims using single cell sequencing, immuno-fluoresence and in situ hybridisation. *The authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of their functions in muscle and muscle and tendon formation. *

• The authors report novel markers to study the interactions between muscle and tendon progenitors in the Drosophila leg provide convincing evidence of their functions in muscle and muscle and tendon formation. *

__ Reply:__ We are grateful to the Reviewer 1 for his/her supportive comments on the quality of our work.

Page 2 "cell types*..." might be worth including other cell types such as vascular/endothelial if listing all cell types in the limb, as the sentence is suggesting. *

__ Reply__: "blood vessels" have been added as components of the limb musculoskeletal system.

Reviewer's comment: The authors discuss the interactions between the myoblasts and tendon cells but do not show any cellular resolution of the interaction between the cells and the secreted adhesion proteins. It would enhance the manuscript if the authors could show high resolution images of these cellular interactions with the secreted protein in vivo.

__ Reply__: see reply to referees cross-commenting about newly generated high-resolution images shown in Fig. 2.

Lots of examples of definite article (the) missing throughout the text.

Reply: The text has been edited and missing articles added

Second line of Abstract does not flow: Ama encodes secreted proteins to "Ama encodes a secreted protein"

__ Reply__ the correction has been made accordingly

2nd para Intro- this para is essentially discussing vertebrate limb muscle/tendon precursors, although includes a non-vertebrate citation. It could be helpful to (briefly) compare/contrast the non-vertebrate vs vertebrate literature on this topic.

__ Reply__: Indeed, this paragraph is primarily focused on the development of the musculoskeletal system in vertebrates. The comparison (from a molecular standpoint) with the muscle system of the Drosophila leg appears in the following paragraph. For clarity, we have included a brief, more general description (end of second paragraph) about the muscle/tendon system in Drosophila to highlight certain divergences between vertebrate and invertebrate systems and to introduce the subsequent paragraph.

"in limb of chick embryo add "the limb"

__ Reply:__ the correction has been made accordingly

p6 because these two antibodies were raised in rabbit, as the Twist antibody, needs some additional explanatory text.

__ Reply__: We have modified the text to give a more accurate explanation: "Because these two antibodies were raised in rabbit, as was the Twist antibody, we could not use this latter to visualize the myoblasts"

P9 discussion creeping into results section-with some speculation on Ama forming homophilic adhesions which has not been experimentally tested.

__ Reply:__ Because we chose to submit this work as a short format paper, Results and Discussion sections are indeed combined. However, we agree that homophilic adhesion properties of Ama have been shown only in cell culture and not tested in physiological context. To clarify this point, we have modified the corresponding part of the text and only suggest that Ama could directly bind to membranes through its putative GPI modification as proposed by Seeger et al.

Ama depletion affects both viability and the proliferation rate of leg disc myoblasts (in a Nrt-independent way) Does it have similar role in tendon precursors? Could the authors provide any evidence of apoptosis given proposed role of Ama in glial cells?

__ Reply: __As asked by Reviewer 1, we have tested these two points and included the results in suppl figure 3 (A-C). As expected, the proliferation rate of tendon cells is not affected as we have previously showed that tendon cells are post-mitotic cells (Laurichesse et al. 2021). Moreover, we now show that Ama depletion does not lead to apoptosis of tendon cells. See Supp. Figure 3 (A-C), the main text has also been modified accordingly.

REVIEWER 2:

In this well-written, comprehensive, and interesting manuscript, the authors study the molecular circuitry that supports the coordinated activity of tendon cells and myoblasts during development. As the authors themselves point out in the introduction, the assembly of tissues within the musculoskeletal system provides a particularly attractive system in which to study how different cell types coordinate their behaviours to form higher-order structures. Using single-cell transcriptomics, the authors first identify the cell adhesion molecule Ama and transmembrane protein Nrt as enriched in Drosophila myoblasts and tendon cells. Their transcriptomic data suggest that Nrt is specifically expressed in the tendon cells while Ama is expressed in both. They support these data with a variety of in situ, antibody, and endogenous stainings. Using a series of genetic manipulations, they then convincingly show that Ama controls the total number of myoblasts during the larval stages: Ama knockdown is associated with both decreased proliferation and increased apoptosis of myoblasts. Ama's role in regulating myoblast number is shown to be independent of Nrt and likely under the control of the FGF/RTK pathway. Finally, the authors show that the loss of either Nrt or Ama activity is associated with a loss of adhesion between myoblasts and tendon cells and with the stunted growth of the long tendon. Thus, their data point to Ama playing dual roles in muscle development by regulating both myoblast number and cell adhesion.

* I very much enjoyed reading the paper, which I think makes an important contribution to our understanding of both the developing musculature and inter-cell-type coordination during development more broadly. I have only a handful of grammatical errors to point out.*

__Reply: __We appreciate these enthusiastic and supportive comments, and we would like to thank the Reviewer for highlighting the broader contribution of our work to the understanding of the mechanisms of coordination between different cell types.

*- Grammar: 'This prompted us to use Drosophila model to search' should read 'This prompted us to use the Drosophila model to search' - Grammar: '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama) as candidates...' should read '...identify Neurotactin (Nrt) and its binding partner, Amalgam (Ama), as candidates...' - Grammar: 'As tendon precursors in leg disc' should read 'As tendon precursors in the leg disc'. - Grammar : '...we performed a series of in situ hybridization...' should read '...we performed a series of in situ hybridizations...' - Grammar: 'Because these two antibodies were raised in rabbit, as the Twist antibody' should read 'Because these two antibodies were raised in rabbit, as was the Twist antibody' - Grammar: 'Statistical analysis reveals an increase myoblast total number when overexpressing an activated ERK' should read 'Statistical analysis reveals an increase in the total number of myoblasts when overexpressing an activated ERK' - Grammar: The following section header needs rephrasing: 'Ama, potential downstream effector of FGF pathway in the regulation of myoblast number'. Maybe 'Ama is a potential downstream effector of the FGF pathway in the regulation of myoblast number' or Ama: a potential downstream effector of the FGF pathway in the regulation of myoblast number. - Grammar: 'whereas its reduction (UAS-StyRNAi) lead to more myoblasts' should read 'whereas its reduction (UAS-StyRNAi) leads to more myoblasts' - For clarity 'The expression of the constitutively active form of ERK could rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020)' might read better as 'Previous work has shown that the expression of the constitutively active form of ERK can rescue the phenotype of Ama depletion in glial cells (Ariss et al. 2020). Therefore, we tried...' - Grammar: 'showed a significant higher number of myoblasts compared' should read 'showed a significantly higher number of myoblasts compared' - Grammar: 'Another, not exclusive, possibility' should read Another, non-mutually exclusive, possibility'. - Grammar: 'We measured the length of the tilt relatively to the length' should read '. We measured the length of the tilt relative to the length' *

Reply: All the modifications suggested above by Reviewer 2 are now included in the text.

REVIEWER 3:

*Myoblast and tendon precursors stem from different developmental origins. Hence, they need to find each other to build a functional muscle-skeleton. How they do so is an exciting biological problem, not only for this reviewer who is working on Drosophila muscle development, too. As we currently understand little about how myoblasts communicate with tendons during development, I find this manuscript a generally interesting contribution unravelling a new mechanism of cell-cell communication between these two cell types. It proposes a role for 2 interesting proteins that are little studied. Furthermore, Drosophila leg muscle-tendon development is complex and results in an intricate final architecture. Thus, a better understanding of its molecular mechanisms of development is exciting to this reviewer and to the muscle and tendon fields. *

Reply: We express our gratitude to Reviewer 3 for his/her keen interest in our work and for emphasizing its significance within the field of developmental biology.

*While some Ama mRNA expression in myoblasts was confirmed with in situ hybridisation, it was also shown that Ama mRNA is expressed in other sources including tendon precursors. As the interesting AmaGFP protein overlapping with the developing tendon cells is found at some distance from the myoblasts, the source for this Ama protein population is not entirely clear. To identify if it is secreted from myoblasts I suggest to stain for Ama-GFP in the muscle-specific Ama knock-down discs at 5h APF. This could use the late knock-down condition. *

__ Reply:__ In Suppl Fig.2 in a close-up view of the femur region, we show that at 5h APF Ama is transcribed in addition to myoblasts also in the developing tilt tendon. This tendon associated Ama expression is specific as it is detected after myoblast specific Ama knockdown. Thus, at 5h APF, the Ama-GFP signal detected at the interface of muscle and tendon precursors could in part correspond to Ama secreted by the tilt tendon cells. However, we also observed clear Ama-GFP signal at the interface of myoblasts and tendon precursors at 0h APF when Ama is not yet transcriptionally activated in tilt tendon precursors (not shown). Thus, we are confident that the myoblasts are the main source of secreted Ama protein that ensure close proximity of myoblast and tendon precursor cells. A view supported by the loss of myoblast-tendon cell proximity in myoblast-specific Ama knockdown. However, to clarify this point, we immunostained myoblast-specific Ama knock-down discs for the Ama protein in at 5h APF as suggested. As stated in the text, we were concerned that GFP tag could influence the life-time of the Ama protein, as GFP itself is pretty stable. This is why we used anti-Ama antibody kindly provided by Dr. Silman to determine whether myoblast-specific Ama knockdown (using R32D05-Gal4 driver) would completely abolish Ama protein at 5h APF. We indeed observed a strong reduction of Ama protein at this stage indicating that the contribution of Ama protein from tendon cells is minimal (but cannot be completely excluded), with myoblasts remaining the major source at this stage. This new result is now presented in Suppl Fig. 2M-P. This result is also in accordance with our new result showing that tendon-specific AmaKD has no effect on tendon growth (see reply to the comment below regarding tendon length). In light of this new result, we have modified the text accordingly in the corresponding paragraph (p5-6).

Generally, it might be useful to move the part of Figure 2 that shows the Ama-GFP Nrt co-staining to the later part in the text that addresses the interaction of both cell types and keep the autonomous Ama role in muscle for the start of paper only.

__ Reply: __We have indeed debated extensively about this possibility before submitting this work. While such a presentation would have some logical coherence, it also has the disadvantage of having to resume, at least partially, the expression of Ama, leading to certain redundancies. Additionally, we chose to begin with a comparison of the new myoblast transcriptomic data with pre-established tendon data to highlight the presence of ligand-receptor pairs. In this context, it seemed to us more pertinent to present the expression patterns of Ama and Nrt together in the initial figures.

To quantify the interaction of the myoblast cell membranes and the tendon cells better it would be useful to combine sr>CAAXmCherry with a myoblast membrane maker (possibly Him-CD8-GFP or use R15B03-Gal4 with R79D08-lexA). This could also improve the "mean distance" measurements. As currently presented, it is not so clear how the mean distance was measured. It could be helpful to indicate some examples in zoom-in vies on Figure 5. Does a distance of 4 µm in wild type mean that the myoblast is not touching the tendon precursors, or is only the myoblast nucleus that is Twi positive at this distance?

__ Reply: We are grateful to this reviewer for its relevant suggestion. Thus, as stated above (referees cross-commenting), we provide new high-resolution images with labelled membranes of both tendon cells and myoblasts (fig 2 O-P). As shown here, myoblast membranes are very closed to each other, and nuclei occupy an important part of myoblast volumes. So, we found more accurate to use the myoblast nucleus (stained with Twist antibody) to detect individual myoblasts using Imaris Spot function rather than myoblast membranes. We also believe that the distances between the center of myoblast nuclei and the tendon surface are representative of the distance between these two cell types as nucleus myoblast occupies most of the cell volume. We addressed this point in the new Suppl. Fig.5. __Regarding the distance of 4____ µm: As mentioned in the original text, the 4 µm distance represents the average distance between myoblasts and the tendon surface in wild type discs. We do not perceive this distance as indicative of a threshold distinguishing myoblasts that interact physically with tendons from those that do not. We rather use this mean distance to quantify the distribution of myoblasts around the tendon and their dispersion/mis-distribution in Ama and Nrt knockdown leg discs. To clarify this point, we have modified the corresponding paragraph: "This result indicates that AmaKD leads to myoblasts mis-distribution around the tilt, suggesting that the reduction of Ama level could affect myoblast-tendon adhesion".

For a better understanding of how the mean distance was measured, we added a new Supplementary Figure 5 (rather than a zoom-in in the main figure as suggested by this reviewer), with a corresponding description of how this distance was measured in addition to the explanations in the material and method section.

Is the tendon elongation phenotype seen after Ama RNAi in muscle and in Nrt mutants due to the fact that myoblasts are further away from tendons or is it an Ama/Nrt role that is autonomous to tendons? This could be tested by assaying tendon elongation after tendon-specific Ama knock-down as shown in Figure S2.

__ Reply: __As asked by this reviewer, we have performed this experiment using Sr-Gal4 driver to induce tendon-specific Ama knockdown and assessed tendon elongation using R79D08-lexA>lexAop-GFP marker. Overall statistical analysis is now included in Fig 5F and G graphs. This analysis shows that tendon-specific Ama knockdown does not affect tendon elongation. This is in concordance with the fact that Ama knockdown in myoblasts leads to tendon defects similar to that of Nrt loss of function in tendon clearly indicating that the observed phenotypes are due to Ama's role in myoblasts. This does not exclude an additional subsequent Ama function in growing tendon precursors in later development.

Minor : Is Figure 2Q a zoom-in from Figure 2P? If yes, it would be helpful to indicate the rough position of it in the lower magnification image.

Reply: Figure 2Q was not a zoom-in from Figure 2P in the previous version of the paper. As stated above Fig. 2 has now been modified.

Minor page 6 - w[1118] is with small "w".

Reply: modifications have been made accordingly in main and figure texts.

REVIEWER 4:

*The manuscript is well-organized, with clear descriptions of methods and results. The use of transcriptomic datasets and gene expression analyses provides insights into the molecular mechanisms underlying the interaction between muscle and tendon precursors. *

*The immunostaining and in situ hybridization experiments well illustrate the expression patterns of Ama and Nrt in muscle and tendon cells during leg disc development in Drosophila. *

*The functional analyses, including knockdown experiments, support the conclusion that Ama plays a crucial role in maintaining the pool of leg muscle precursor cells and coordinating tendon and muscle precursor growth. *

The manuscript significantly enhances our understanding of cell-cell interactions in the musculoskeletal system of Drosophila. The findings have broader implications for the field of developmental biology. In general, this manuscript provides valuable insights into the molecular processes governing leg muscle and tendon development.

Reply: We are indebted to Reviewer 4 for highlighting that our manuscript is well-organized and well-illustrated. We are also grateful to Reviewer 4 for highlighting the valuable insights of our work.

some aspects in the manuscript, for example how Ama regulates myoblast number and its interaction with the FGFR pathway, could be further explored or clarified.

__ Reply:__ Regarding Ama's contribution for maintaining the myoblast pool through its interaction with the FGF pathway, we demonstrate here that, contrary to what has been proposed for glial cells, Ama acts downstream of this pathway, although we emphasize that there is a synergistic effect with the MAPK pathway inhibitor, Sprouty. These findings thus reveal complex and variable regulatory mechanisms between Ama and the FGF pathway that would require specific investigation, the entirety of which appears challenging to integrate into this same publication.

the organization of the abstract could be improved to provide a clearer and more comprehensive overview of the study. The abstract currently lacks a structured presentation of essential components such as methods, results, and conclusions. It would greatly benefit from a more systematic arrangement.

__ Reply:__ We have made modifications to propose a more structured abstract.

I don't have time to proof this entire play, but hopefully someone else already has or will do so? I've been comparing it to the Dial publication, but probably better to look at Sara Crangle's edited version, reprinted in the Essays and Stories of Mina Loy. This is also the authoritative addition of Sacred Prostitute.

indranet

we have

FORK LYFT

https://philosophybreak.com/articles/if-a-tree-falls-in-the-forest-and-theres-no-one-around-to-hear-it-does-it-make-a-sound/#:~:text=So%2C%20the%20answer%20to%20this%20age-old%20question%20seems,lonesome%20falling%20tree%20does%20not%20make%20a%20sound.

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If a Tree Falls in the Forest, and There's No One Around to Hear It, Does It Make a Sound?

The age-old question of whether a falling tree makes a sound when there's no one around to hear it exploits the tension between perception and reality. This article explores possible answers and their consequences.

By Jack Maden  |  September 2022

3-MIN BREAK  

If a tree falls in the forest, and there's no one around to hear it, does it make a sound? Well, if by 'sound' we mean vibrating air, then yes, when the tree falls, it vibrates the air around it.

However, if by 'sound' we mean the conscious noise we hear when our sensory apparatus interacts with the vibrating air, then if no one is around to hear the tree when it falls, there'd be no sensory apparatus for the vibrating air to interact with, and thus no conscious noise would be heard.

So, the answer to this age-old question seems to be simple: it depends on how we define 'sound'. If we define it as 'vibrating air', the falling tree makes a sound. If we define it as a conscious experience, the lonesome falling tree does not make a sound.

There, problem solved.

The point of asking this question, however, is not so that it can be answered quickly and put aside.

Rather, its point is to draw out the rather strange tension between our two very different definitions of the word 'sound'.

On the one hand, we classify sound as a mechanistic process that exists without us, 'out there' in the world. On the other, we regard it as a private conscious experience, its existence entirely dependent on us.

And when you dwell on this latter definition, you realize it doesn't just extend to sounds. Everything we experience --- everything we see, hear, smell, touch, taste --- all of it depends on our sensory apparatus, on us. Without us, our experiences would not exist.

As the great 16th-century astronomer Galileo Galilei put it:

Tastes, odors, colors, and so on... reside only in consciousness. If the living creature were removed, all these qualities would be wiped away and annihilated.

Take away our senses, and the world of our experience would be replaced by a colorless, soundless, odorless, tasteless nothingness. Without us, what remains?

The reason our original question --- When a tree falls in the forest, and there's no one around to hear it, does it make a sound? --- is such a teaser, is because it hits on a deeper question. Namely:

If there was no conscious life, would the physical universe exist?

Our kneejerk reaction to this question might be, 'of course it would'. But let's think about it again: if there was nothing conscious, then nothing would be experienced. There would be nothing resembling anything we call 'existence'. No colors, no sounds, no smells, no tastes, no touch, no sense of time, no sense of space.

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For instance, in his 1710 work, A Treatise Concerning the Principles of Human Knowledge, the philosopher George Berkeley discusses the absurdity of a world existing independently of our conscious minds:

It is indeed an opinion strangely prevailing amongst people that houses, mountains, rivers, and in a word all sensible objects, have an existence natural or real, distinct from their being perceived by the understanding... for what are the forementioned objects but things we perceive by sense? And what do we perceive besides our own ideas or sensations? And is it not plainly repugnant that any one of these or any combination of them should exist unperceived?

On this view, it is absurd to say a lonesome falling tree makes a sound. For Berkeley, it is absurd to say the tree, without a conscious mind there perceiving it, even exists. (You can learn more about his mind-bending arguments for this position in our short explainer piece on Berkeley's subjective idealism, his theory that the world is in our minds).

But to conclude this brief reflection on the tension between perception and reality, consider a comment from the Nobel Prize-winning quantum physicist Max Planck in a 1931 interview (italics added):

I regard consciousness as fundamental. I regard matter as derivative from consciousness. We cannot get behind consciousness. Everything that we talk about, everything that we regard as existing, postulates consciousness.

What do you think? Can we get behind consciousness?

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About the Author

Jack MadenFounder\ Philosophy Break

Having received great value from studying philosophy for 15+ years (picking up a master's degree along the way), I founded Philosophy Break in 2018 as an online social enterprise dedicated to making the subject's wisdom accessible to all. Learn more about me and the project here.

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The Buddha's Four Noble Truths: the Cure for Suffering

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https://www.poetryfoundation.org/poems/44272/the-road-not-taken

The Road Not Taken

Launch Audio in a New Window

BY ROBERT FROST

Two roads diverged in a yellow wood,

And sorry I could not travel both

And be one traveler, long I stood

And looked down one as far as I could

To where it bent in the undergrowth;

Then took the other, as just as fair,

And having perhaps the better claim,

Because it was grassy and wanted wear;

Though as for that the passing there

Had worn them really about the same,

And both that morning equally lay

In leaves no step had trodden black.

Oh, I kept the first for another day!

Yet knowing how way leads on to way,

I doubted if I should ever come back.

I shall be telling this with a sigh

Somewhere ages and ages hence:

Two roads diverged in a wood, and I---

I took the one less traveled by,

And that has made all the difference.

n/a

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note the "honey of the ancients" description here with a tangential nod to the commonplace tradition

see: <br /> - https://hypothes.is/a/mCsl9voQEeuP3t8jNOyAvw<br /> - https://hypothes.is/users/chrisaldrich?q=tag%3A%22jonathan+swift%22+tag%3A%22commonplace+books%22

Author response:

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

Reviewer #1 (Recommendations For The Authors):

Major concerns:

(1) It is not clear about the biological significance of the inhibitory effects of human Abeta42 on gammasecretase activity. As the authors mentioned in the Discussion, it is plausible that Abeta42 may concentrate up to microM level in endosomes. However, subsets of FAD mutations in APP and presenilin 1 and 2 increase Abeta42/Abeta40 ratio and lead to Abeta42 deposition in brain. APP knock-in mice NLF and NLGF also develop Abeta42 deposition in age-dependent manner, although they produce more human Abeta42 than human Abeta40. 

If the production of Abeta42 is attenuated, which results in less Abeta42 deposition in brain. So, it is unlikely that human Abeta42 interferes gamma-secretase activity in physiological conditions. This reviewer has an impression that inhibition of gamma-secretase by human Abeta42 is an interesting artifact in high Abeta42 concentration. If the authors disagree with this reviewer's comment, this manuscript needs more discussion in this point of view. 

We thank the Reviewer for raising this key conceptual point, we acknowledge that it was insufficiently discussed in the original manuscript. In response to this point, we introduced the following paragraph in the discussion section of the revised manuscript:

“From a mechanistic standpoint, the competitive nature of the Aβ42-mediated inhibition implies

that it is partial, reversible, and regulated by the relative concentrations of the Aβ42 peptide (inhibitor) and the endogenous substrates (Figure 10C and 10D). The model that we put forward is that cellular uptake, as well as endosomal production of Aβ, result in increased intracellular concentration of Aβ42, facilitating γ-secretase inhibition and leading to the buildup of APP-CTFs (and γ-secretase substrates in general). As Aβ42 levels fall, the augmented concentration of substrates shifts the equilibrium towards their processing and subsequent Aβ production. As Aβ42 levels rise again, the equilibrium is shifted back towards inhibition. This cyclic inhibitory mechanism will translate into pulses of (partial) γsecretase inhibition, which will alter γ-secretase mediated-signaling (arising from increased CTF levels at the membrane or decreased release of soluble intracellular domains from substrates). These alterations may affect the dynamics of systems oscillating in the brain, such as NOTCH signaling, implicated in memory formation, and potentially others (related to e.g. cadherins, p75 or neuregulins). It is worth noting that oscillations in γ-secretase activity induced by treatment with a γ-secretase inhibitor semagacestat have been proposed to have contributed to the cognitive alterations observed in semagacestat treated patients in the failed Phase-3 IDENTITY clinical trial (7) and that semagacestat, like Aβ42, acts as a high affinity competitor of substrates (85).

The convergence of Aβ42 and tau at the synapse has been proposed to underlie synaptic dysfunction in AD (86-89), and recent assessment of APP-CTF levels in synaptosome-enriched fractions from healthy control, SAD and FAD brains (temporal cortices) has shown that APP fragments concentrate at higher levels in the synapse in AD-affected than in control individuals (90).  Our analysis adds that endogenous Aβ42 concentrates in synaptosomes derived from end-stage AD brains to reach ~10 nM, a concentration that in CM from human neurons inhibits γ-secretase in PC12 cells (Figure 7). Furthermore, the restricted localization of Aβ in endolysosomal vesicles, within synaptosomes, likely increases the local peptide concentration to the levels that inhibit γ-secretase-mediated processing of substrates in this compartment. In addition, we argue that the deposition of Aβ42 in plaques may be preceded a critical increase in the levels of Aβ present in endosomes and the cyclical inhibition of γsecretase activity that we propose. Under this view, reductions in γ-secretase activity may be a (transient) downstream consequence of increases in Aβ due to failed clearance, as represented by plaque deposition, contributing to AD pathogenesis.“

We have also added figures 10C and 10D, presented here for convenience.

Author response image 1.

(2) It is not clear whether the FRET-based assay in living cells really reflects gamma-secretase activity.

This reviewer thinks that the authors need at least biochemical data, such as levels of Abeta. 

We have established a novel, HiBiT tag based assay reporting on the global γ-secretase activity in cells, using as a proxy the total levels of secreted HiBiT-tagged Aβ peptides. The assay and findings are presented in the revised manuscript as follows:

In the result section, in the “Aβ42 treatment leads to the accumulation of APP C-terminal fragments in neuronal cell lines and human neuron” subsection:

“The increments in the APP-CTF/FL ratio suggested that Aβ42 (partially) inhibits the global γ-

secretase activity. To further investigate this, we measured the direct products of the γ-secretase mediated proteolysis of APP. Since the detection of the endogenous Aβ products via standard ELISA methods was precluded by the presence of exogenous human Aβ42 (treatment), we used an N-terminally tagged version of APPC99 and quantified the amount of total secreted Aβ, which is a proxy for the global γsecretase activity. Briefly, we overexpressed human APPC99 N-terminally tagged with a short 11 amino acid long HiBiT tag in human embryonic kidney (HEK) cells, treated these cultures with human Aβ42 or p3 17-42 peptides at 1 μM or DAPT (GSI) at 10 µM, and determined total HiBiT-Aβ levels in conditioned media (CM). DAPT was considered to result in full γ-secretase inhibition, and hence the values recorded in DAPT treated conditions were used for the background subtraction. We found a ~50% reduction in luminescence signal, directly linked to HiBiT-Aβ levels, in CM of cells treated with human Aβ42 and no effect of p3 peptide treatment, relative to the DMSO control (Figure 3D). The observed reduction in the total Aβ products is consistent with the partial inhibition of γ -secretase by Aβ42.”

In Methods:

“Analysis of γ-secretase substrate proteolysis in cultured cells using secreted HiBiT-Aβ or -Aβ-like peptide levels as a proxy for the global γ-secretase endopeptidase activity

HEK293 stably expressing APP-CTF (C99) or a NOTCH1-based substrate (similar in size as

APP- C99) both N-terminally tagged with the HiBiT tag were plated at the density of 10000 cells per 96-well, and 24h after plating treated with Aβ or p3 peptides diluted in OPTIMEM (Thermo Fisher Scientific) supplemented with 5% FBS (Gibco). Conditioned media was collected and subjected to analysis using Nano-Glo® HiBiT Extracellular Detection System (Promega). Briefly, 50 µl of the medium was mixed with 50 µl of the reaction mixture containing LgBiT Protein (1:100) and Nano-Glo HiBiT Extracellular Substrate (1:50) in Nano-Glo HiBiT Extracellular Buffer, and the reaction was incubated for 10 minutes at room temperature. Luminescence signal corresponding to the amount of the extracellular HiBiT-Aβ or -Aβ-like peptides was measured using victor plate reader with default luminescence measurement settings.”

As the direct substrate of γ -secretase was used in this analysis, the observed reduction (~50%) in the levels of N-terminally-tagged (HiBiT) Aβ peptides in the presence of 1 µM Aβ42, relative to control conditions, demonstrates a selective inhibition of γ-secretase by Aβ42 (not by the p3). These data complement the FRET-based findings presented in Figure 5.

(3) Processing of APP-CTF in living cells is not only the cleavage by gamma-secretase. This reviewer thinks that the authors need at least biochemical data, such as levels of Abeta in Figures 4, 5 and 7.

We tried to measure the levels of Aβ peptides secreted by cells into the culture medium directly by ELISA (using different protocols) or MS (using established methods, as reported in Koch et al, 2023), but exogenous Aβ42 (treatment) present at relatively high levels interfered with the readout and rendered the analysis inconclusive. 

However, we were successful in the determination of total secreted (HiBiT-tagged) Aβ peptides from the HiBiT tagged APP-C99 substrate, as indicated in the previous point. The quantification of the levels of these peptides showed that Aβ42 treatment resulted in ~50% reduction in the γ -secretase mediated processing of the tagged substrate.    

In addition, we would like to highlight that our analysis of the contribution of other APP-CTF degradation pathways, using cycloheximide-based assays in the constant presence of γ-secretase inhibitor, failed to reveal significant differences between Aβ42 treated cells and controls (Figure 6B & C). The lack of a significant impact of Aβ42 on the half-life of APP-CTFs under the conditions of γsecretase inhibition maintained by inhibitor treatment is consistent with the proposed Aβ42-mediated inhibitory mechanism.

(4) Similar to comment #3. Processing of Pancad-CTF and p75 in living cells may be not only the cleavage by gamma-secretase. This reviewer thinks that the authors need at least biochemical data, such as levels of ICDs in Figures 6C and E. 

To address this comment we have now performed additional experiments where we measured Nterminal Aβ-like peptides derived from NOTCH1-based substrate using the HiBiT-based assay. These experiments showed a reduction in the aforementioned peptides in the cells treated with Aβ42 relative to the vehicle control, and hence further confirmed the inhibitory action of Aβ42. These new data have been included as Figure 8D in the revised manuscript and described as follow:

Finally, we measured the direct N-terminal products generated by γ-secretase proteolysis from a HiBiT-tagged NOTCH1-based substrate, an estimate of the global γ-secretase activity. We quantified the Aβ-like peptides secreted by HEK 293 cells stably expressing this HiBiT-tagged substrate upon treatment with 1 µM Aβ1-42,  p3 17-42 peptide or  DAPT (GSI) (Figure 8D). DAPT treatment was considered to result in a complete γ-secretase inhibition, and hence the values recorded in the DAPT condition were used for background subtraction. A ~20% significant reduction in the amount of secreted

N-terminal HiBiT-tagged peptides derived from the NOTCH1-based substrates in cells treated with Aβ1-

42 supports the inhibitory action of Aβ1-42 on γ-secretase mediated proteolysis.

Minor concerns:

(1) Murine Abeta42 may be converted to murine Abeta38 easily, compared to human Abeta42. This may be a reason why murine Abeta42 exhibits no inhibitory effect on gamma-secretase activity. 

In order to address this question, we performed additional experiments where we assessed the processing of murine Aβ42 into Aβ38. Analogous to human Aβ42, the murine Aβ42 peptide was not processed to Aβ38 in the assay conditions. These new data have been integrated in the manuscript and added as a Supplementary figure 1B.

(2) It is curious to know the levels of C99 and C83 in cells in supplementary figure 3.  

The conditions used in these assays were analogous to the conditions used in the figure 3 (i.e. treatment with Aβ peptides at 1 µM concentrations). Such conditions were associated with profound and consistent APP-CTF accumulation in this model system.

Reviewer #2 (Recommendations For The Authors):

In the current study, the authors show that Aβs with low affinity for γ-secretase, but when present at relatively high concentrations, can compete with the longer, higher affinity APPC99 substrate for binding and processing. They also performed kinetic analyses and demonstrate that human Aβ1-42 inhibits γ-secretase-mediated processing of APP C99 and other substrates. Interestingly, neither murine Aβ1-42 nor human p3 (17-42 amino acids in Aβ) peptides exerted inhibition under similar conditions. The authors also show that human Aβ1-42-mediated inhibition of γ-secretase activity results in the accumulation of unprocessed, which leads to p75-dependent activation of caspase 3 in basal forebrain cholinergic neurons (BFCNs) and PC12 cells. 

These analyses demonstrate that, as seen for γ-secretase inhibitors, Aβ1-42 potentiates this marker of apoptosis. However, these are no any in vivo data to support the physiological significance of the current finding. The author should show in APP KO mice whether gamma-secretase enzymatic activity is elevated or not, and putting back Aβ42 peptide will abolish these in vivo effects. 

The findings presented in this manuscript form the basis for further in vitro and in vivo research to investigate the mechanisms of inhibition and its contribution to brain pathophysiology. Here, we used well-controlled model systems to investigate a novel mechanism of Aβ42 toxicity. Multiple mechanisms regulate the local concentration of Aβ42 in vivo, making the dissection of the biochemical mechanisms of the inhibition more complex. Nevertheless, beyond the scope of this report, we consider these very reasonable comments as a motivation for further research activities. 

The experimental concentrations for Aβ42 peptide in the assay are too high, which are far beyond the physiological concentrations or pathological levels. The artificial observations are not supported by any in vivo experimental evidence.

It is correct that in the majority of the experiments we used low μM concentrations of Aβ42. However, we would like to note that we have also performed experiments where conditioned medium collected from human APP.Swe expressing neurons was used as a source of Aβ. In these experiments total Aβ concentration was in low nM range (0.5-1 nM) (Figure 7). Treatment with this conditioned medium  led to the increase APP-CTF levels, supporting  that low nM concentrations of Aβ are sufficient for partial inhibition of  γ-secretase. 

In addition, we highlight that analyses of the brains of the AD affected individuals have shown that APPCTFs accumulate in both sporadic and genetic forms of the disease (Pera et al. 2013, Vaillant-Beuchot et al. 2021); and recently, Ferrer-Raventós et al. 2023 have revealed a correlation between APP-CTFs and Aβ levels at the synapse (Ferrer-Raventós et al. 2023). We therefore assessed the concentration of Aβ42 in synaptosomes derived from frontal cortices of post-mortem AD and age-matched non-demented (ND) control individuals. Our findings and conclusions are included in the revised version as follows: 

In the results section:

“We next investigated the levels of Aβ42 in synaptosomes derived from frontal cortices of post-mortem AD and age-matched non-demented (ND) control individuals (Figure 10B). Towards this, we prepared synaptosomes from frozen brain tissues using Percoll gradient procedure (62, 63). Intact synaptosomes were spun to obtain a pellet which was resuspended in minimum amount of PBS, allowing us to estimate the volume containing the resuspended synaptosome sample. This is likely an overestimate of the actual synaptosome volume. Finally, synaptosomes were lysed in RIPA buffer and Aβ peptide concentrations measured using ELISA (MSD). We observed that the concentration of Aβ42 in the synaptosomes from (end-stage) AD tissues was significantly higher (10.7 nM)  than those isolated from non-demented tissues (0.7 nM), p<0.0005***. These data provide evidence for accumulation at nM concentrations of endogenous Aβ42 in synaptosomes in end-stage AD brains. Given that we measured Aβ42 concentration in synaptosomes, we speculate that even higher concentrations of this peptide may be present in the endolysosome vesicle system, and therein inhibit the endogenous processing of APP-CTF at the synapse. Of note treatment of PC12 cells with conditioned medium containing even lower amounts of Aβ (low nanomolar range (0.5-1 nM)) resulted in the accumulation of APP-CTFs.” 

In the discussion: 

“The convergence of Aβ42 and tau at the synapse has been proposed to underlie synaptic dysfunction in AD (86-89), and recent assessment of APP-CTF levels in synaptosome-enriched fractions from healthy control, SAD and FAD brains (temporal cortices) has shown that APP fragments concentrate at higher levels in the synapse in AD-affected than in control individuals (90).  Our analysis adds that endogenous Aβ42 concentrates in synaptosomes derived from end-stage AD brains to reach ~10 nM, a concentration that in CM from human neurons inhibits γ-secretase in PC12 cells (Figure 7). Furthermore, the restricted localization of Aβ in endolysosomal vesicles, within synaptosomes, likely increases the local peptide concentration to the levels that inhibit γ-secretase-mediated processing of substrates in this compartment. In addition, we argue that the deposition of Aβ42 in plaques may be preceded by a critical increase in the levels of Aβ present in endosomes and the cyclical inhibition of γ-secretase activity that we propose. Under this view, reductions in γ-secretase activity may be a (transient) downstream consequence of increases in Aβ due to failed clearance, as represented by plaque deposition, contributing to AD pathogenesis. ”

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Author response:

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

eLife assessment

The authors present evidence suggesting that MDA5 can substitute as a sensor for triphosphate RNA in a species that naturally lacks RIG-I. The key findings are potentially important for our understanding of the evolution of innate immune responses, but the evidence is incomplete, as additional biochemical and functional experiments are needed to unambiguously assign MDA5 as a bona fide sensor of triphosphate RNA in this model. This also leaves the title as overstating its case.

We would like to thank the editorial team for these positive comments on our manuscript and the constructive suggestions to improve our manuscript. According to the suggestions and valuable comments of the referees, we have added substantial amounts of new data and analysis to substantiate our claims, and the manuscript, including the title, has been carefully revised to better reflect our conclusions. We are now happy to send you our revised manuscript, we hope the modified manuscript addresses your and the reviewers’ concerns satisfactorily and is suitable for publication in eLife now.

Reviewer #1 (Public Review):

This study offers valuable insights into host-virus interactions, emphasizing the adaptability of the immune system. Readers should recognize the significance of MDA5 in potentially replacing RIG-I and the adversarial strategy employed by 5'ppp-RNA SCRV in degrading MDA5 mediated by m6A modification in different species, further indicating that m6A is a conservational process in the antiviral immune response.

However, caution is warranted in extrapolating these findings universally, given the dynamic nature of host-virus dynamics. The study provides a snapshot into the complexity of these interactions, but further research is needed to validate and extend these insights, considering potential variations across viral species and environmental contexts.

We concur with the viewpoint that virus-host coevolution complicates the derivation of universal conclusions. To address this challenge, incorporated additional experiments and data based on the suggestions of the reviewers. These experiments were carried out across diverse models, including two distinct vertebrate species (M. miiuy and G. gallus), two different viruses (SCRV and VSV), and the synthesis of corresponding 5’ppp-RNA probes. We believe that these supplementary data bolster the evidence supporting the immune replacement role of MDA5 in the recognition of 5'ppp-RNA in RIG-I deficient species (Figure 1C-1E, Figure 2O and 2P, Figure 4). Moreover, we have duly incorporated references in both the introduction and discussion sections to further support our conclusion that MDA5 in T. belangeri, a mammal lacking RIG-I, possesses the ability to detect RNA viruses posed as RIG-I agonists (doi: 10.1073/pnas.1604939113). Lastly, meticulous revisions have been undertaken in the manuscript, including adjustments to the title, to ensure harmonization with our research outcomes.

Reviewer#2 (Public Review):

This manuscript by Geng et al. aims to demonstrate that MDA5 compensates for the loss of RIG-I in certain species, such as teleost fish miiuy croaker. The authors use siniperca cheats rhabdovirus (SCRV) and poly(I:C) to demonstrate that these RNA ligands induce an IFN response in an MDA5-dependent manner in M. miiuy derived cells. Furthermore, they show that MDA5 requires its RD domain to directly bind to SCRV RNA and to induce an IFN response. They use in vitro synthesized RNA with a 5'triphosphate (or lacking a 5'triphosphate as a control) to demonstrate that MDA5 can directly bind to 5'-triphosphorylated RNA. The second part of the paper is devoted to m6A modification of MDA5 transcripts by SCRV as an immune evasion strategy. The authors demonstrate that the modification of MDA5 with m6A is increased upon infection and that this causes increased decay of MDA5 and consequently a decreased IFN response.

The key message of this paper, i.e. MDA5 can sense 5'-triphosphorylated RNA and thereby compensate for the loss of RIG-I, is novel and interesting, yet there is insufficient evidence provided to prove this hypothesis. Most importantly, it is crucial to test the capacity of in vitro synthesized 5'-triphosphorylated RNA to induce an IFN response in MDA5-sufficient and -deficient cells. In addition, a number of important controls are missing, as detailed below.

To further support the notion that MDA5 is capable of detecting 5'ppp-RNA in species lacking RIG-I, we conducted additional experiments. Initially, we isolated the RNA from SCRV and VSV viruses. Subsequently, we synthesized 5'ppp-RNA probes that corresponded to the genome termini of SCRV and VSV in vitro. Then, these RNAs were treated with Calf intestinal phosphatase (CIAP) to generate dephosphorylated derivatives. Next, we separately tested the activation ability of various RNAs on IRF3 dimer and IFN response in MKC (M. miiuy kidney cell line) and DF-1 (G. gallus fibroblast cell line) cells, and determined that the immune activation ability of SCRV/VSV viruses depends on their triphosphate structure (Figure 1C-1E, Figure 4C and 4J). In addition, the knockdown of MDA5 inhibited the immune response mediated by SCRV RNA (Figure 2P and 2Q). Finally, we incorporated essential experimental controls (Figure 4B and 4I). We think that the inclusion of these supplementary experimental data significantly enhances the credibility and further substantiates our hypothesis.

The authors describe an interaction between MDA5 and STING which, if true, is very interesting. However, the functional implications of this interaction are not further investigated in the manuscript. Is STING required to relay signaling downstream of MDA5?

To better explore the role of STING in MDA5 signal transduction, we constructed a STING expression plasmid and synthesized specific siRNA targeting STING. Next, we found that co-expression of STING and MDA5 significantly enhance MDA5-mediated IFN-1 response during SCRV virus infection (Figure 2N). Conversely, silencing of STING expression restored the MDA5-mediated IFN-1 response (Figure 2O). These findings provide important evidence for the critical involvement of STING in the immune signaling cascade mediated by MDA5 in response to 5'ppp-RNA viruses.

The second part of the paper is quite distinct from the first part. The fact that MDA5 is an interferon-stimulated gene is not mentioned and complicates the analyses (i.e. is there truly more m6A modification of MDA5 on a per molecule basis, or is there simply more total MDA5 and therefore more total m6A modification of MDA5).

For the experimental data analysis in Figure 5E and 5F, we first compared the m6A-IP group to the input group, and then normalized the control group (IgG group of 5E and Mock group of 5F) to a value of “1”. Given the observed variability in MDA5 expression levels within the input group of Mock and SCRV virus-infected cells, our analysis represents the actual m6A content of each MDA5 molecule. To enhance clarity, we have updated the label on the Y-axis in Figure 5E and 5F.

Finally, it should be pointed out that several figures require additional labels, markings, or information in the figure itself or in the accompanying legend to increase the overall clarity of the manuscript. There are frequently details missing from figures that make them difficult to interpret and not self-explanatory. These details are sometimes not even found in the legend, only in the materials and methods section. The manuscript also requires extensive language editing by the editorial team or the authors.

We acknowledge the valuable feedback from the reviewer and have made significant improvements to our manuscript based on the recommendations provided in the "Recommendation for the authors" section. Furthermore, we have conducted a thorough review of the entire article, resulting in substantial enhancements to the format, clarity, and overall readability of our manuscript.

Reviewer#3 (Public Review):

Summary: In this manuscript, the authors investigated the interaction between the pattern recognition receptor MDA5 and 5'ppp-RNA in a teleost fish called Miiuy croaker. They claimed that MDA5 can replace RIG-I in sensing 5'ppp-RNA of Siniperca cheats rhabdovirus (SCRV) in the absence of RIG-I in Miiuy croaker. The recognition of MDA5 to 5'ppp-RNA was also observed in the chicken (Gallus gallus), a bird species that lacks RIG-I. Additionally, they reported that the function of MDA5 can be impaired through m6A-mediated methylation and degradation of MDA5 mRNA by the METTL3/14-YTHDF2/3 regulatory network in Miiuy croaker under SCRV infection. This impairment weakens the innate antiviral immunity of fish and promotes the immune evasion of SCRV.

Strengths:<br /> These findings provide insights into the adaptation and functional diversity of innate antiviral activity in vertebrates.

Weaknesses:<br /> However, there are some major and minor concerns that need to be further addressed. Addressing these concerns will help the authors improve the quality of their manuscript.One significant issue with the manuscript is that the authors claim to be investigating the role of MDA5 as a substitute for RIG-I in recognizing 5'ppp-RNA, but their study extends beyond this specific scenario. Based on my understanding, it appears that sections 2.2, 2.3, 2.5, 2.6, and 2.7 do not strictly adhere to this particular scenario. Instead, these sections tend to investigate the functional involvement of Miiuy croaker MDA5 in the innate immune response to viral infection. Furthermore, the majority of the data is focused on Miiuy croaker MDA5, with only a limited and insufficient study on chicken MDA5. Consequently, the authors cannot make broad claims that their research represents events in all RIG-I deficient species, considering the limited scope of the species studied.

We agree with the reviewer's perspective that functional analysis of MDA5 in M. miiuy may not adequately represent all species lacking RIG-I. To address this concern, we have incorporated additional experimental data utilizing different model systems, including two different vertebrate species (M. miiuy and G. gallus), two distinct viruses (SCRV and VSV), and the synthesis of two corresponding 5’ppp-RNA probes. While the functional characterization of G. gallus MDA5 remains relatively limited compared to M. miiuy, our current experimental findings provide support for two key observations. Firstly, the triphosphate structure of the VSV virus is pivotal in activating the innate immune response in G. gallus against the virus (Figure 1D and 4J). Secondly, G. gallus MDA5 can recognize 5’ppp-RNA (Figure 4I, 4K and 4L). Consequently, although we cannot definitively establish the immune surrogate function of MDA5 in all RIG-I-deficient species, our research data further substantiates this hypothesis. Moreover, we have adopted a more cautious attitude in summarizing our experimental conclusions, thereby enhancing the rigor of our manuscript language.

The current title of the article does not align well with its actual content. It is recommended that the focus of the research be redirected to the recognition function and molecular mechanism of MDA5 in the absence of RIG-I concerning 5'ppp-RNA. This can be achieved through bolstering experimental analysis in the fields of biochemistry and molecular biology, as well as enhancing theoretical research on the molecular evolution of MDA5. It is advisable to decrease or eliminate content related to m6A modification.

Following the reviewer's recommendations, we have revised the title to emphasize that our main research focus is a teleost fish devoid of RIG-I. Furthermore, we have conducted additional molecular experiments to further elucidate the 5'ppp-RNA recognition function of MDA5 in RIG-I-deficient species. In an attempt to analyze the potential molecular evolution of MDA5 resulting from RIG-I deficiency, we collected MDA5 coding sequences from diverse vertebrates. However, due to multiple independent loss events of RIG-I in fish, fish with or without RIG-I genes in the phylogenetic tree cannot be effectively clustered separately, making it extremely difficult to perform this aspect of analysis. Consequently, we have regrettably opted to forgo the molecular evolution analysis of MDA5.

Our article topic is to reveal an antagonistic phenomenon between fish receptor and RNA viruses. The MDA5 of RIG-I-lost fish has evolved the ability to recognize 5’ppp-RNA virus and mediate IFN response to resist SCRV infection. Conversely, the m6A methylation mechanism endows the SCRV virus with a means to weaken the immune capacity of MDA5. Therefore, we believe that the latter part is an important part of the arms race between the virus and its host, and should be retained.

Additionally, the main body of the writing contains several aspects that lack rigor and tend to exaggerate, necessitating significant improvement.

We appreciate the reviewer’s comment and have improved the manuscript addressing the points raised in the “Recommendation for the authors”. We have added corresponding experiments to strengthen the verification of the conclusions, and in addition, we are more cautious in summarizing the language of the conclusions.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(1) The evidential foundation within the Result 1 section appears somewhat tenuous.

Firstly, the author derives conclusions regarding the phenomenon of RIG-I loss in lower vertebrates by referencing external literature and conducting bioinformatics analyses. It is pertinent to inquire whether the author considered fortifying these findings through additional WB/PCR experiments, particularly for evaluating RIG-I expression levels across diverse vertebrates, encompassing both lower and higher orders.

Firstly, the species we analyzed are mostly model species with excellent genomic sequence information in the database. Secondly, the RIG-I protein sequences (at least some domain sequences) are relatively conserved in vertebrates. Therefore, the credibility of evaluating the existence of RIG-I in these species through homology comparison is high. Therefore, we do not intend to conduct additional PCR/WB experiments to confirm this.

Additionally, following the identification of RIG-I loss, the author postulates MDA5 as a substitute of RIG-I, grounding this speculation in the analysis of MDA5 and LGP2 protein structures. It is imperative to address whether the author could enhance the manuscript by supplying expression data for MDA5 and LGP2 across different vertebrates and elucidating further why MDA5 is posited as the compensatory mechanism for RIGI loss.

Like MDA5, LGP2 is also an interferon-stimulating gene, so they both likely exhibit high sensitivity to viral infections. Therefore, we think that comparing the expression data of these two genes is difficult to evaluate their function. In mammals, the regulatory mechanisms of LGP2 to RIG-I and MDA5 were complicated and ambiguous. To evaluate the potential function of LGP2 in M. miiuy, we further constructed LGP2 plasmid and synthesized siRNA targeting LGP2. Then, our results indicate that mmiLGP2 can enhance the antiviral immune response mediated by mmiMDA5 (Figure 1H and 1I), further indicating the regulatory role of mmiLGP2 in RLR signaling, rather than acting as a compensatory receptor for RIG-I.

Also, is it conceivable that other receptors contribute to this compensatory effect in lower vertebrates?

5’ triphosphate short blunt-end double-strand RNA is the ligand of RIG-I as contained in the panhandle of negative-strand viral genomes. We mainly focus on the immune recognition and compensatory effects of other receptors on RIG-I loss, and MDA5, as the protein with the most similar structure, first attracted our attention. In addition, IFIT proteins have been reported to recognize triphosphate single-stranded RNA (doi: 10.1038/nature11783). However, we used SCRV and VSV RNA as viral models, both of which have negative stranded genomes and meet the ligand standards of RIG-I, rather than IFIT. Therefore, we excluded the IFIT protein from our research scope.

(2) The article exclusively employs a singular type of 5'PPP-RNA virus and one specific lower vertebrate species, thereby potentially compromising the robustness of the assertion that this phenomenon is prevalent in lower vertebrates. To bolster this claim, could the author consider incorporating data from an alternative 5'PPP-RNA virus and a different lower vertebrate species?

To address this concern, we have incorporated additional experimental data utilizing different model systems, including two different vertebrate species (M. miiuy and G. gallus) and two distinct viruses (SCRV and VSV). While the functional characterization of G. gallus MDA5 remains relatively limited compared to M. miiuy, our current experimental findings provide support for two key observations. Firstly, the triphosphate structure of the VSV virus is pivotal in activating the innate immune response in G. gallus against the virus (Figure 1D and 4J). Secondly, G. gallus MDA5 can recognize 5’ppp-RNA (Figure 4I, 4K and 4L). Consequently, these experimental results further confirmed the conservatism of this immune compensation mechanism.

(3) A nuanced consideration of the statement in Result 5 is warranted. Examination of the results under SCRV infection conditions suggests dynamic fluctuations in MDA5 expression levels, challenging the veracity of the statement implying "increased expression", which contradicts the proposed working model of this article.

Because MDA5 acts as a receptor and plays a recognition immune role in the early stages of virus infection, the expression of MDA5 in the early stage of SCRV infection rapidly increases. In the later stage of infection, the expression of MDA5 may gradually decrease again due to the negative feedback mechanism in the host body to prevent excessive inflammation. However, compared to the uninfected group, the expression of MDA5 was significantly increased in the SCRV-infected group, so we believe that the term "increased expression" is not a problem. In addition, the m6A mechanism can weaken the function of MDA5, but it still cannot prevent the overall increase of MDA5 expression, which is not contradictory to the working model in this article.

Additionally, the alterations in m6A levels in miiuy croaker under SCRV infection conditions warrant clarification. Could the author employ m6A dot blotting to supplement the findings related to total m6A levels?

Our previous studies (doi: 10.4049/jimmunol.2200618) have suggested that the total m6A level is increased after SCRV infection in miiuy croaker. We cited this conclusion in the discussion of our manuscript.

(4) It would be beneficial if the editors could assist the author in enhancing the language of the manuscript.

We have carefully checked the full article and modified it with Grammarly tools, and we believe that the grammar, format, and readability of our articles have been greatly improved.

Reviewer #2 (Recommendations For The Authors):

Figure 1

(1) Figure 1B - some clarification needs to be added about this figure in the text. It is unclear what the main point is that the authors would like to convey.

What we want to emphasize is that some species with RIG-I, such as zebrafish, have also experienced RIG-I loss events, but have undergone whole genome replication events before the loss, thus preserving a copy of RIG-I. This indicates that loss events of RIG-I are very common in vertebrates and do not occur randomly. We have elaborated on this point in the results and discussion.

(2) Figure 1C - is not very informative other than showing Mm MDA5 and LGP2 side-by-side. It would be more useful to show a comparison of human RIG-I/MDA5 alongside Mm and Gg MDA5. Are there any conserved/shared key residues between hRIG-I/hMDA5 versus mmMDA5?

Homologous proteins are often known to adopt the same or similar structure and function. We have added human RIG-I domain information to this figure (Figure 1F). By comparing the domain information of human RIG-I with M. miiuy MDA5 and LGP2, M. miiuy MDA5 has a similar structure to human RIG-I, making it most likely to compensate for the missing RIG-I. While M. miiuy LGP2 lacks the CARD domain, which is crucial for signal transduction, so we will shift our focus to M. miiuy MDA5. In addition, we collected protein sequences of MDA5 and RIG-I from various vertebrates to identify key residues evolved in recognizing 5'ppp-RNA by M. miiuy MDA5. However, unfortunately, no potential residues were found during the comparison process.

Figure 2

(1) Figure 2B - It would be important to demonstrate MDA5-Flag expression by immunoblot and compare MDA5-Flag overexpression to endogenous MDA5 expression using the anti-MDA5 antibody from panel 2A. If IF is used, more cells need to be visible in the field.

After transfecting the MDA5 plasmid into MKC, endogenous MDA5 expression was detected using MDA5 antibodies. The results showed a significant increase in MDA5 protein levels, indicating that MDA5 antibodies can specifically recognize MDA5 protein. In addition, we retained the original immunofluorescence images to better demonstrate the subcellular localization of MDA5.

(2) Figure 2C - The 1:1 stoichiometry of MDA5:MAVS (in the absence of any stimulus) is quite surprising. How does the interaction between MDA5 and MAVS change upon stimulation with an RNA ligand (SCRV, poly(I:C))?

We do not believe that the actual stoichiometry between MDA5 and MAVS is what you described as 1:1. In fact, the proportion of proteins in the complex depends on many factors in the experimental results with Co-IP. Firstly, the MDA5 plasmid in this study has a 3 × Flag tag, while the MAVS only has a 1x Myc tag, which makes the antibody more sensitive for detecting MDA5-Flag. In addition, the Co-IP results are also affected by multiple factors such as the type of antibody and the number of recoveries, making it difficult to estimate the actual ratio of MDA5 to MAVS. Based on the above reasons and the fact that the detection of the interaction strength between MDA5 and MAVS after infection seems to be off-topic, we did not continue to explore this point.

(3) Figure 2D - The interaction between MDA5 and STING is a very interesting finding but is not elaborated on in the paper (even though the interaction between MDA5 and STING is mentioned in the abstract). The manuscript would be strengthened if the interaction between MDA5 and STING is further investigated. For example, does the IFN response that is reported in panels 2E to 2H require the presence of STING? Does mmMDA5 signal via STING in response to a DNA ligand?

We appreciate the referee's suggestion to study the mutual influence between MDA5 and STING. We found that co-expression of STING and MDA5 can enhance MDA5-mediated IFN-1 response during SCRV virus infection, while knocking down STING can restore MDA5-mediated IFN-1 (Figure 2N and 2O). This indicates that STING plays an important signaling role in the immune response of MDA5 to RNA viruses. We understand the importance of cGAS/STING pathways in identifying exogenous DNA, so exploring the MDA5 pathway for DNA ligand recognition is an interesting and meaningful perspective. But this seems to be detached from the theme of our article, so we didn't continue to explore this point.

(4) Figures 2F and 2H - the authors demonstrate that SCRV induces a type I IFN response in an MDA5-dependent manner. While SCRV is a single-stranded negative-sense RNA virus that contains 5'ppp-RNA, it cannot be excluded that MDA5 is activated here in response to a double-stranded RNA intermediate of viral origin or even a host-derived RNA whose expression or modification is altered during infection. To demonstrate in an unambiguous manner that MDA5 senses 5'ppp-RNA, it is crucial to use the in vitro synthesized 5'ppp-RNA (and its dephosphorylated derivative as a control) from Fig. 4 in these experiments.

We transfected 5 'ppp SCRV and 5' ppp VSV (and their dephosphorylated derivatives) synthesized in vitro into MKC cells and DF-1 cells, respectively. The results showed that 5’ppp-RNAs significantly promoted the formation of IRF3 dimers, while their dephosphorylated derivatives did not (Figure 4C and 4J). In addition, we extracted virus RNA from the SCRV and VSV viruses and dephosphorylated them with Calf intestinal phosphatase (CIAP). These RNAs were transfected into MKC and DF-1 cells and found that the immune response mediated by virus RNAs was much higher than the dephosphorylated form (Figure 1C-1E). The above results indicate that the immune response activated by SCRV and VSV is indeed dependent on their triphosphate structure. Finally, the IRF3 dimer and IFN induction activated by SCRV RNA can be inhibited by si-MDA5 (Figure 2P and 2Q), further demonstrating the involvement of MDA5 in the immune response mediated by 5’ppp-RNA ligands.

(5) In mice and humans, MDA5 is known to collaborate with LGP2 to jointly induce an IFN response. Does M.miiuy express LGP2? If so, it would be informative to include a siRNA targeting LGP2 in the experiments in panel F. In mammals, LGP2 potentiates the response via MDA5 while it may inhibit RIG-I activation.

M.miiuy express LGP2. We constructed an LGP2 plasmid and synthesized si-LGP2 to investigate the impact of LGP2 on MDA5-mediated immune processes (Figure 1G-1I). The results showed that LGP2 can enhance the IFN response mediated by MDA5 during SCRV virus infection, similar to that in mammals.

(6) Minor comment - Is the poly(I:C) used in this figure high or low molecular weight poly(I:C)? HMW poly(I:C) preferentially stimulates MDA5, while LMW poly(I:C) preferentially stimulates RIG-I.

We used poly(I:C)-HMW as a positive control for activating MDA5. We have modified the relevant information in Figure 2 and its legend.

Figure 3

(1) Figure 3F/G - The normalization in this Figure is difficult to interpret. It would be better to split Figure 3G into 4 separate graphs and include the mock-infected cells alongside the infected samples (as done in Figure 2).

To better demonstrate the function of the RD domain of MDA5 in M. miiuy, we have changed the experimental plan, as shown in figure 3F. We detected the induction of antiviral factors by overexpression of MDA5 and MDA5-△RD under poly (I:C)-HMW stimulation. This can indicate that the RD domain of MDA5 has a conserved function in the recognition of poly(I:C)-HMW in M. miiuy, and can serve as a positive control for the recognition of SCRV virus by the RD domain.

Figure 4

(1) Figure 4B - A number of important controls are missing. Was the immunoprecipitation of RNA successful? This could be shown by running a fraction of the immunoprecipitated material on an RNA gel and/or by showing that the input RNA was depleted after IP. In addition, a control IP (Streptavidin beads without biotinylated RNA) is missing to ensure that MDA5 does not stick non-specifically to the Streptavidin resin.

We appreciate the referee's suggestions. We rerun this experiment and added a non-biomarker RNA IP control group, and the results showed that MDA5 did not adsorb non-specific onto the beads (Figure 4B). In addition, based on the referee's suggestion, we tested the consumption of RNA before and after immunoprecipitation, and the results showed that biotin-labeled RNA, rather than non-biotin-labeled RNA, could be adsorbed by beads, indicating the success of RNA precipitation. However, we think that this is not necessary for the final presentation of the experimental results, so we did not show this in the figure.

(2) Figure 4B - It is unclear why there is such a large molecular weight difference between endogenous MDA5 and MDA5-Flag (110 kDa versus 130/140 kDa). Why is there less MDA5-Flag retrieved than endogenous MDA5?

After careful analysis, we believe that the significant difference in molecular weight between endogenous MDA5 and MDA5 Flag may be due to three reasons. Firstly, MDA5 flag has a 3× Flag tag. Secondly, as shown in the primer table, we constructed MDA5 between the NotI and XbaI cleavage sites in the pcDNA3.1 vector, which are located at the posterior position in the vector. This means that the Flag tag has a certain distance from the starting codon of MDA5, and these sequences on the vector can also be translated and increase the molecular weight of the exogenous MDA5 protein. Finally, in order to facilitate the amplification of the primers, the F-terminal primers of MDA5 contain a small portion of the 3'UTR sequence (excluding the stop codon). These above reasons may have led to significant differences in molecular weight. In addition, in order to supplement important experimental controls, we have conducted a new RNA pull-down experiment as shown in Figure 4B.

(3) Minor point: Figure 4B - please clarify in the figure whether RNA or protein is immunoprecipitated and via which tags.

We have conducted a new RNA pull-down experiment as shown in Fig 4B, and we have clearly labeled the relevant information in the figure.

(4) Figure 4E - the fraction of MDA5 that binds 5'ppp-RNA seems incredibly minor. And why is this experiment done using 5'OH-RNA as a competitor, rather than simply incubating MDA5 and 5'OH-RNA together and demonstrating that these do not form a complex?

The proportion of MDA5 combined with 5’ppp-RNA is influenced by many conditions, including the concentration and purity of the probe and purified protein. In addition, the dosage ratio between the RNA probe and MDA5 protein in the EMSA experiment can also have a significant impact on the results. Therefore, it is not possible to accurately determine the actual binding force between MDA5 and RNA. In the EMSA experimental program, both cold probes (5’ppp-RNA) and mutated cold probes (5’OH-RNA and 5’pppGG-RNA) are crucial for demonstrating the specific binding between MDA5 and 5’ppp-RNA, as they can exclude false positive errors caused by factors such as the presence of biotin in the purified MDA5 protein itself.

(5) Figure 4B/4C/4F - These experiments would be strengthened by including an MDA5 mutant that cannot bind to RNA. These mutants are well-described in mammals. If these residues are conserved, it is straightforward to generate this mutant.

As shown in Figure 3, the MDA5 of M. miiuy has an RD domain that can recognize the SCRV virus. We constructed MDA5-△RD mutant plasmids with 6x His-tags and purified them for EMSA experiments (Figure 4E). The experimental results further indicate that MDA5, rather than MDA5-△RD, can bind to 5’ppp-SCRV (Figure 4G). This further confirms the crucial role of the RD domain in recognizing the 5'ppp-RNA virus.

(6) Minor point: Figure 4E: please clarify in which lanes MDA5 has been added.

Thank you for the referee's suggestion. We have synthesized new 5'ppp-RNA probes (5’ppp-SCRV and their dephosphate derivatives) and rerun this experiment, and relevant information has been added in the Figure (Figure 4F).

Figure 5

(1) Figure 5C - As MDA5 is an interferon-stimulated gene (as shown in panel G/H/I)) the increased MDA5 expression could simply explain the increase in the amount of m6A-MDA5 that is immunoprecipitated after infection. Could this figure be improved by doing a fold change between input vs m6A-IP OR uninfected vs SCRV-infected conditions? This would reveal whether the modification of MDA5 with m6A is really increased after infection.

As shown in Figure 5F below, our data indicates that the proportion of m6A-modified MDA5 does indeed increase after SCRV infection, rather than solely due to the increased expression of MDA5 itself.

(2) Figure. 5E/F - The y-axis is unclear: relative MDA5 m6A levels. Relative to what? Input? Mock infected?

For experiments in Figure 5E/F, we first compared the m6A-IP group with the input group, and then normalized the control group (IgG group of 5E and Mock group of 5F) to “1”. We have replaced the Y-axis name with a clearer one (Figure 5E and 5F).

(3) General comment - It is not mentioned in the text that MDA5 is an interferon-stimulated gene. This would account for the increase in expression (qPCR) after viral infection or poly(I:C) transfection, hence there is no novelty in this finding. In addition, the authors suggest that MDA5 increases at the protein level (by immunoblot) but the increase on these blots is not convincing (figure 5H/5I).

We understand that the increase in expression of MDA5 as an interferon-stimulated gene after viral infection is a common phenomenon. We present this to further validate the m6A sequencing transcriptome data, and to demonstrate that although m6A modification interferes with MDA5 expression during viral infection, it cannot prevent the increase of mRNA level of MDA5. In addition, we rerun the experiment and the results showed that the expression of MDA5 protein can indeed be specifically activated by the SCRV virus and poly(I:C)-HMW.

Figure 6

(1) Figure 6E - What was the MOI of the virus used in this experiment? It is not mentioned in the figure legend.

MOI=5, we have added this point in the figure legend.

Figure 7

(1) Figure 7J - This graphic is somewhat misleading and should be altered to better reflect the conclusions that are drawn in the manuscript. The graphic suggests that MAVS and STING interact, but this is not demonstrated in the paper. In addition, the paper does not demonstrate whether MAVS or STING (or both) are needed downstream of MDA5 to relay signalling. Finally, please draw an arrow from type I IFNs to increased expression of MDA5 to illustrate that MDA5 is an ISG.

Thank you for the referee's suggestion. We have revised the images to more accurately match the conclusions of the manuscript (Figure 7J). Firstly, we have separated the STING protein from the MAVS protein. Secondly, arrows have been used to indicate that MDA5 is an IFN-stimulated gene. Finally, as we have added relevant experiments to demonstrate the importance of MITA protein in the signaling process of MDA5-activated IFN response. In addition, the function of MAVS binding to MDA5 protein and promoting its signal transduction is very conserved, and there is a good research background even in fish with RIG-I deficiency (10.1016/j.dci.2021.104235). Therefore, in Figure 7J, we still chose to bind MAVS to MDA5 protein and use it as a downstream signal transducer of MDA5.

Discussion<br /> (1) There is very little discussion about METTL and YTHDF proteins in the discussion despite the fact that the last 2 figures are entirely devoted to these proteins.

Based on the referee's suggestion, we have added relevant content about METTL and YTHDF proteins in the discussion. In addition, the basic mechanism and function of METTL and YTHDF proteins were briefly described in the introduction.

Reviewer #3 (Recommendations For The Authors):

Please refer to the specific suggestions and recommendations. They include proposals for experimental additions, improved methodologies, and suggestions to resolve writing-related concerns.

Major concerns

(1) I suggest changing the article title to "Functional Replacement of RIG-I with MDA5 in Fish Miiuy Croaker", or a similar title, to make it more focused and closely aligned with the content of the article.

Following the reviewer's recommendations, we have revised the title to emphasize our primary research subject is a teleost fish that lacks RIG-I. In addition, we have changed “5’ppp-RNA” to “5’ppp-RNA virus” to emphasize the interaction between the virus and the receptor. We believe that the revised title is more in line with the content of the article.

(2) Due to the inherent limitations in genome sequencing, assembly, and annotation for the Miiuy croaker, comprehensive annotation of immune-related genes remains incomplete. To address this critical gap, it is recommended that authors establish experimental protocols, such as Fluorescence In Situ Hybridization (FISH), to confirm the absence of RIG-I in the Miiuy croaker. They should simultaneously employ MDA5 probes as a positive control for validation purposes.

The miiuy croaker has good genomic information at the chromosomal level (doi: 10.1016/j.aaf.2021.06.001). In addition, studies have shown that RIG-I is absent in the orders of Perciformes (doi: 10.1016/j.fsirep.2021.100012), while miiuy croaker belongs to the order Perciformes, so it does indeed lose the RIG-I gene. Therefore, we do not intend to use FISH technology to prove this.

(3) Similarly, it is recommended that the authors first provide evidence of the presence of 5'ppp at the 5' terminus of the genome RNA of SCRV, as demonstrated in the study by Goubau et al. (doi: 10.1038/nature13590, Supplementary figure 1). This evidence is crucial before drawing conclusions about the compensatory role of MDA5 in recognizing 5'ppp RNA viruses, using SCRV as the viral model.

As suggested by the referee, we extracted SCRV RNA from SCRV virus particles and assessed the 5’-phosphate-dependence of stimulation by SCRV RNA. Calf intestinal phosphatase (CIAP) treatment substantially reduced the stimulatory activity of SCRV RNA in MKC cells of M. miiuy (Figure 1C and 1E). In addition, similar results were obtained by transfecting VSV-RNA isolated from VSV virus into DF-1 cells of G. gallus (Figure 1D). The above evidences confirm the presence of triphosphate molecular features between SCRV and VSV viruses, and indicating that birds and fish lacking RIG-I have other receptors that can recognize 5’ppp-RNA.

(4) The 62-nucleotide (nt) 5'ppp-RNA utilized in this study was obtained from Vesicular Stomatitis Virus (VSV). In order to provide direct evidence, it is necessary to include a 62-nt 5'ppp-RNA that is directly derived from SCRV itself.

We adopted this suggestion and synthesized a 67-nucleotide 5’ppp-SCRV RNA probe. We found that 5’ppp-SCRV activates dimerization of IRF3 and binds to MDA5 of M. miiuy in a 5’-triphosphate-dependent manner (Figure 4A-4F).

(5) Given that RNAs with uncapped diphosphate (PP) groups at the 5′ end also activate RIG-I, similar to RNAs with 5′-PPP moieties, and the 5′-terminal nucleotide must remain unmethylated at its 2′-O position to allow RNA recognition by RIG-I, it is necessary for the authors to conduct additional experiments to supplement and validate these two distinguishing features of RIG-I in RNA recognition. This will provide more reliable evidence for the replacement of RIG-I by MDA5 in RNA recognition.

Thank you for the reviewer's professional suggestions. We understand that exploring the combination of 5’pp-RNA and 2′-O-methylated RNA with MDA5 can further demonstrate the alternative function of MDA5. But we think that the use of 5’ppp-RNA and their dephosphorylation derivatives can fully demonstrate that the MDA5 of M. miiuy and G. gallus have evolved to recognize 5’triphosphate structure like human RIG-I. Therefore, we do not intend to conduct any additional experiments

(6) In section 2.3, the authors assert that Miiuy croaker recognizes SCRV through its RD domain. This claim is supported by their data showing that cells overexpressed with the MDA5 ΔRD mutant lost the ability to inhibit SCRV replication. As a result, the authors draw the conclusion that "these findings provide evidence that MDA5 may recognize 5'-triphosphate-dependent RNA (5'ppp-RNA) through its RD domain." However, to strengthen their argument, the authors should first demonstrate that during SCRV infection, MDA5-mediated antiviral immune response is indeed initiated by recognizing the 5'ppp part of the SCRV RNA, rather than the double-strand part (which can exist in ssRNA virus) of the viral RNA, as this is naturally a ligand for MDA5. Additionally, the authors should treat the isolated SCRV RNA with CIP to remove the phosphate group and examine the binding of MDA5 with SCRV RNA before and after treatment. They should also transfect CIP-treated or untreated SCRV RNA into MDA5 knockdown and wild-type MKC cells to investigate the induction of antiviral signaling and levels of viral replication. Finally, the authors should verify the binding ability of the mutants with isolated SCRV RNA, with or without CIP treatment, to determine which domain of MDA5 is responsible for SCRV 5'ppp-RNA recognition.

We understand the reviewer's concern that MDA5 may be identified by binding to dsRNA in the SCRV virus. Based on the reviewer's suggestion, we extracted SCRV RNA and obtained its dephosphorylated RNA using Calf intestinal phosphatase (CIAP). Next, we transfected them into MDA5-knockdown and wild-type MKC cells, and detected the dimerization of IRF3 and IFN reaction. The results indicate that SCRV RNA does indeed activate immunity in a triphosphate-dependent manner, and knockdown of MDA5 prevents immune activation of SCRV RNA (Figure 1C and 1E, Figure 2P and 2Q). Finally, we synthesized a 5'ppp-SCRV RNA probe and demonstrated that MDA5 binds to 5'ppp-SCRV through the RD domain (Figure 4E-4G). We believe that these results can better demonstrate that MDA5 recognizes 5’ppp-RNA through its RD domain and addresses the concerns of the reviewers.

(7) Similarly, merely presenting Co-IP data demonstrating the interaction between Miiuy croaker MDA5 and STING in overexpressed EPC cells does not justify the claim that "in vertebrates lacking RIG-I, MDA5 can utilize STING to facilitate signal transduction in the antiviral response". This is because interactions observed through overexpression may not accurately reflect the events occurring during viral infection or their actual antiviral functions. To provide more robust evidence, it is essential to conduct functional experiments after STING knockout (or at least knockdown). Furthermore, it is important to note that Miiuy Croaker alone cannot adequately represent all "vertebrates lacking RIG-I".

We found that co-expression of STING and MDA5 can enhance MDA5-mediated IFN-1 response during SCRV virus infection, while knocking down STING can restore MDA5-mediated IFN-1 response (Figure 2N and 2O). This indicates that STING plays an important signaling role in the immune response of MDA5 to RNA viruses. In addition, loss of RIG-I is a common phenomenon in vertebrates, and STING of birds such as chickens (doi: 10.4049/jimmunol.1500638) and mammalian tree shrews (doi: 10.1073/pnas.1604939113) can also bind to MDA5, indicating that STING can indeed play a crucial role in MDA5 signaling in species with RIG-I deficiency. We have added this section to our discussion and elaborated on our observations in more cautious language.

(8) In the manuscript, a series of experiments were conducted using an antibody (Beyotime Cat# AF7164) against endogenous MDA5. The corresponding immunogen for this MDA5 antibody is a recombinant fusion protein containing amino acids 1-205 of human IFIH1/MDA5 (NP_071451.2). However, the amino acid sequences of IFIH1/MDA5 differ substantially between humans and Miiuy croaker, which could introduce errors in the results. Therefore, it is essential to employ antibodies specifically designed for targeting Miiuy croaker's own MDA5 in the experiments.

As shown in Figure 2B, endogenous MDA5 antibodies can detect the MDA5 portion that is forcibly overexpressed by plasmids, suggesting that the MDA5 antibody can indeed specifically recognize the MDA5 protein of M. miiuy.

(9) It is recommended to investigate the phosphorylation of IRF3 in order to confirm the downstream signaling pathway during viral infection when MDA5 is knocked down or overexpressed.

Due to the lack of available phosphorylation antibodies for fish IRF3, we used IRF3 dimer experiments to detect downstream signaling (Figure 1C and 1D, Figure 2P, Figure 4C and 4J).

(10) The use of poly I:C as a mimic for dsRNA to investigate MDA5's recognition of 5'ppp-RNA in hosts lacking RIG-I, as well as the examination of the regulatory role of MDA5 m6A methylation upon activation by 5'ppp-RNA, may be inappropriate. Poly I:C does not possess 5'ppp, and while it has been identified as a ligand for MDA5 in various studies, MDA5 cannot serve as a substitute for RIG-I in recognizing poly (I:C). Therefore, the authors should utilize 5'ppp-dsRNA as the mimic and include the corresponding 5'ppp-dsRNA control without a 5'triphosphate as the negative control (both available from InvivoGen). This approach will specifically elucidate the mechanisms involved when MDA5 functions similarly to RIG-I in the recognition of 5'ppp-RNA.

In our study, we used poly(I:C)-HMW, a known dsRNA mimetic that can be preferentially recognized by MDA5 rather than RIG-I, as a positive control for activating MDA5. What we want to demonstrate is that, like poly(I:C)-HMW (positive control), SCRV can also promote MDA5-mediated IFN immunity, further indicating the important role of MDA5 in 5’ppp-RNA virus invasion. We have clearly labeled the type of poly(I:C) in the figures and legends to avoid misunderstandings for readers.

(11) In Figure 2, Figure 3, and Figure 6, the appearance of virus plaques is not readily apparent, and it is necessary to replace these images with clearer photographs. It appears that MKC or MPC cells are not appropriate for conducting plaque assays. To accurately assess viral proliferation, the authors should measure key indicators throughout the process, such as the production of positive-strand RNAs (+RNAs), replication intermediates (RF), and transcription of subgenomic RNAs. This approach is preferable to solely measuring the M and G protein genes from the virus genome as positive results can still be observed in contaminated cells.

As pointed out by the reviewer, we also think that the virus plaque images in Figure 2K and Figure 3D are not clear enough, so we have replaced them with new clear images (Figure 2J and Figure 3D). But we think that other images can clearly display the proliferation of the SCRV virus, so we did not replace them. In addition, the primers we currently use do measure +RNA, so the replication level of the SCRV virus can be accurately evaluated without being affected by virus contamination. Because the regions where the two pairs of primers are located belong to the SCRV-M and SCRV-G protein genes, we label them as SCRV-M and SCRV-G to distinguish between the two pairs of genes. To avoid reader misunderstanding, we have modified the Y-axis label in the figures (Figure 2I and 2K, Figure 3E, Figure 6E and 6O).

(12) There is a substantial disparity in the molecular size of M. miiuy MDA5 between endogenous and exogenously expressed proteins, as shown in Figure 2A and 2C-D. Please provide clarification.

Please refer to the response to Reviewer 2's question regarding Figure 4B above.

(13) The manuscript incorporates the evolutionary perspective, but lacks specific evolutionary analysis. Thus, it is essential to include relevant analysis to comprehend the evolutionary dynamics and positive selection on MDA5 and LGP2 in the absence of RIG-I in Miiuy croaker. This can be achieved through theoretical calculations using appropriate algorithms, such as the branch models and branch-site models based on the maximum-likelihood method implemented in the phylogenetic analysis by maximum likelihood (PAML) package.

In fact, we have analyzed the molecular evolution of MDA5 and LGP2. Unfortunately, even when analyzing only the MDA5/LGP2 CDS sequences in fish, we found that the topologies of gene trees of MDA5/LGP2 were largely consistent with the species tree. Thus, species with or without RIG-I in the gene trees cannot effectively separate clusters, making it extremely difficult to analyze the molecular evolution of MDA5/LGP2 caused by RIG-I deficiency. Consequently, we gave up this aspect of analysis.

(14) If the narrative regarding m6A methylation goes beyond the activation of MDA5 through recognition of 5'ppp-RNA and represents a regulatory mechanism for all MDA5 activation events, it is not relevant to the theme of "An arms race under RIG-I loss: 5'ppp-RNA and its alternative recognition receptor MDA5." Therefore, all investigations in this paper should focus solely on events when MDA5 recognizes 5'ppp-RNA. Any data associated with the broader regulatory mechanisms and m6A methylation of MDA5 should be excluded from this manuscript and instead be included in a separate study dedicated to exploring this specific topic.

Our theme aims to showcase RNA viruses, rather than an interaction between 5'ppp-RNA and host virus receptors, which our current topic cannot accurately express. Therefore, we made two main changes: firstly, we limited the study species to M. miiuy, although some studies on the functional substitution of MDA5 for RIG-I involved birds. Secondly, change “5’ppp-RNA” to “5’ppp-RNA virus”. We believe that the revised title is more in line with our current research contents.

(15) The running title appears to be hastily done.

We modified it to “MDA5 recognizes 5’ppp-RNA virus in species lacking RIG-I”.

(16) There are many descriptions that are not strongly related to the main theme of the article in the introduction section, making it lengthy and fragmented. Please focus on the research background of RIG-I and MDA5, including their structures, functions, and regulatory mechanisms, as well as the research progress on the compensatory effect of MDA5 in the absence of RIG-I and its evolutionary adaptation mechanism in other species.

Based on the suggestions of the reviewers, we have removed some of the less relevant content in the introduction and added research progress on the compensatory effect of MDA5 in the evolutionary adaptation mechanism of tree shrews in the absence of RIG-I.

(17) Lines 149-156 in the "Results" section include content that resembles an "Introduction" It is important to avoid duplicating information in the results section. Therefore, the authors are encouraged to revise this paragraph to ensure conciseness in the article.

We have streamlined this section to enhance the article's conciseness and clarity.

(18) In the "Results" section, at line 177, the authors assert, "As depicted in Figure 1F-1H," which should be corrected to Figure 2F-2H. Furthermore, the y-axis of the two figures on the right-hand side of Figure 2H represents the ISG15 genes. At line 182, "as demonstrated in Figure 1I-1L," should be revised as "as illustrated in Figure 2I-2L". The authors demonstrated a lack of attention to detail.

Thank you to the reviewer for pointing out our errors, and we have made the necessary corrections.

(19) In lines 197-198, the authors stated that "MDA5-ΔRD showed an inability to interact with SCRV." However, Figure 3D did not reveal any significant difference, thus it is advisable to repeat this experiment at least once.

We have replaced this virus spot image with a new one (Figure 3D).

(20) In lines 200-201 of the "2.3 RD domain is required for MDA5 to recognize SCRV" section, the authors report that the expression of antiviral genes was induced by the overexpression of both MDA5 and MDA5-ΔRD, even in the absence of infection (Figure 3F). Why does the expression of antiviral genes increase in the absence of viral RNA stimulation? Please provide a reasonable explanation.

In the absence of viral infection, overexpression of viral receptor proteins may still transmit erroneous signaling, affecting the body's immunity. We speculate that due to the preservation of the CARD domain by MDA5 and MDA5-ΔRD, they can still induce the expression of antiviral factors without ligands, although this induction effect is much smaller than that of viral infection. However, in order to better demonstrate the function of the RD domain of MDA5 in M. miiuy, we have changed the experimental plan, as shown in the figure 3F. We detected the induction of antiviral factors by overexpression of MDA5 and MDA5-△RD under poly (I:C)-HMW stimulation. This can indicate that the RD domain has a conserved function in the recognition of poly(I:C)-HMW in M. miiuy, and can serve as a positive control for the recognition of SCRV virus invasion by the RD domain of MDA5.

(21) Please provide the GeneBank accession number of M. miiuy MDA5.

The GeneBank accession number of M. miiuy MDA5 was added in the section 4.5 plasmids construction.

(22) The content of lines 228-233 in the "Results" section bears resemblance to that of the "Introduction." To ensure the avoidance of information duplication, it is recommended to remove this paragraph from the results section.

This section has been streamlined.

(23) The bands of mmiMDA5 in the 5'ppp-RNA and dsRNA lanes in Figure 4B are weak and almost unobservable. Please replace them with clear images.

We have rerun this experiment and replaced the images (Figure 4B).

(24) In Figure 5G and at line 253, there are only results presented for the SCRV infection group, while no results are shown for the control group. This raises the question of why the control group results are missing. It is necessary to provide a reasonable explanation or correction for this issue.

The "0 h" infection time point of the SCRV virus is the control group, and we have replaced it with a more intuitive image (Figure 5G).

(25) In Figure 7C, it would be necessary to include the western blot result of YTHDF protein expression in order to verify the efficiency of YTHDF siRNA.

In fact, we have attempted to detect the endogenous expression of YTHDF protein using available commercial antibodies. Unfortunately, only the YTHDF2 antibody can specifically recognize the endogenous protein expression of YTHDF2 in M. miiuy. In addition, the knockdown effect of si-YTHDF2 has been validated by YTHDF2 antibody (doi: 10.4049/jimmunol.2200618).

(26) In line 422 of the "4.3 Cell culture and treatment" section, the paragraph raises a question regarding the nature of Miiuy croaker kidney cells (MKCs) and spleen cells (MPCs) - whether they are cell lines or freshly isolated cells (or primary cultures) derived from kidney and spleen tissues. If these cells are indeed cell lines, it is requested to provide detailed information about the sources and properties of the cells (such as whether they are epithelial cells or other mixed cell types) and the generations of propagation. Alternatively, if the cells were freshly isolated or primary cultures obtained from fish, the method for cell isolation should be provided. The source and stability of cells are extremely important for ensuring the repeatability and reliability of experimental outcomes.

M. miiuy kidney cells (MKCs) and spleen cells (MPCs) are cell lines derived from the kidney and spleen tissues of M. miiuy, with passages ranging from 20 to 40 times. These details have been incorporated into section 4.3.

(27) There are many inaccurate descriptions in the text, which employ concepts that are too broad. These descriptions need to be narrowed down to specific species or objects. Here are a few examples, along with the necessary revisions. Other similar instances should also be revised accordingly. For instance, in line 119, "fish MDA5" should be changed to "Miiuy croaker MDA5." Similarly, in line 166, "fish MDA5-mediated signaling pathway" should be changed to "Miiuy croaker MDA5-mediated signaling pathway." In line 174, "fish MDA5" should be revised to "Miiuy croaker MDA5." Additionally, in line 185, "antiviral responses of teleost" should be changed to "antiviral responses of Miiuy croaker." In line 197, "interact with SCRV" should be revised to "interact with 5'ppp-RNA of SCRV." In line 337, "loss of RIG-I in the vertebrate" should be modified to "loss of RIG-I in Miiuy croaker and chicken." Similarly, in line 338, "MDA5 of fish" should be changed to "MDA5 of Miiuy croaker." Lastly, in line 348, "RIG-I deficient vertebrates" should be revised to "RIG-I deficient Miichthys miiuy and Gallus gallus."

Thank you for the reviewer's suggestions. We have made revisions to these inaccurate descriptions and reviewed the entire manuscript to address similar statements with broad concepts.

(28) Finally, it should be noted that a similar discovery has already been reported in tree shrews (Ling Xu, et al., Proc Natl Acad Sci., 2016, 113(39):10950-10955). This article shares similarities with that research report, therefore it is necessary to discuss in detail the relationship between the two in the discussion and compare and analyze the evolutionary patterns of MDA5 from it.

Based on the reviewer's suggestions, we have compared the similarities and differences between these two reports during the discussion and analyzed the evolutionary dynamics of MDA5 in these vertebrates lacking RIG-I.

Minor concerns:

Thank you to the reviewer for their meticulous examination to our manuscript, we have made revisions to the following suggestions.

(1) At line 120, the sentence "SCRV(one 5'ppp-RNA virus)" should have a space between "SCRV" and "(one 5'ppp-RNA virus)". Please make this correction.

Corrected.

(2) At lines 147-148, the sentence "However, the downstream gene of TOPORSa is missing a RIG-I" is not accurate and needs modification.

We have modified this sentence.

(3) At line 184, "findings indicate" should be corrected to "findings indicated".

Corrected.

(4) At line 189, "a 5'ppp-RNA virus" should be deleted and the text seems redundant.

Deleted.

(5) At line 198, "replication. (Figure 3C-3E)", please remove the punctuation between "replication" and "(Figure 3C-3E)".

Corrected.

(6) At line 416 in "Materials and methods" section, "4.2 Sample and challenge" should be corrected to "4.2 Fish and challenge".

Corrected.

(7) At line 419, the authors state that "The experimental procedure for SCRV infection was performed as described", please briefly describe the SCRV infection method and the infectious dose.

Based on the reviewer's suggestions, we have added relevant descriptions of SCRV infection in section 4.2.

(8) There are several formatting issues in the "Materials and Methods" section. For instance, in line 424, there is no space between the number and letter in "100 μg/ml" and "26 ℃" should be corrected to "26℃". Additionally, in line 430, "Cells" should be corrected to "cells".

Corrected.

(9) At line 446, "50 ng/ul" and "100 mU/ul" should be corrected to "50 ng/μl" and "100 mU/μl".

Corrected.

(10) At line 459, "primers 1)" should be corrected to "primers".

Corrected.

(11) At lines 461-464, the description "For protein purification, MDA5 plasmids with 6× His tag was constructed based on pcDNA3" seems to be no direct logical connection between protein purification and the plasmid construction. Please make the necessary corrections.

Corrected.

(12) At line 548, "cytoplasmic" should be corrected to "Cytoplasmic".

Corrected.

(13) At line 549, "5× 107" should be corrected to "5 × 107".

Corrected.

(14) At line 557, "MgCl2" should be corrected to "MgCl2".

Corrected.

(15) At line 558, "6 %" should be corrected to "6%".

Corrected.

(16) At line 565, "50μg" should be corrected to "50 μg".

Corrected.

(17) At line 571, "300{plus minus}50 bp." should be corrected to "300 {plus minus} 50 bp."

Corrected.

(18) At lines 592-593, the sentence "After several incubations, the m6A level was quantified colorimetrically at a wavelength of 450 nm" does not read smoothly, please improve it.

Revised.

(19) At line 786, "MDA5 recognize" should be corrected to "MDA5 recognized".

Corrected.

(20) At lines 788 and 798, "Pulldown" should be corrected to "Pull-down".

Corrected.

(21) At lines 790 and 796, "bluestaining" should be corrected to "blue staining".

Deleted.

(22) At line 825, "SCRV and infection" should be corrected to "SCRV infection".

Corrected.

(23) At lines 826-827, "SCRV (H) and poly(I:C) (I) infection" should be corrected to "SCRV infection (H) and poly(I:C) stimulation (I)".

Corrected.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The authors report a mass spectrometry (MS)-based interactomics technique, time-resolved interactome profiling (TRIP), which allows for tracking temporal changes in the interactome of protein of interest. To show that TRIP can successfully deconvolute interactomes over time, they pulsed thyroid cells with homopropargylglycine (Hpg), immunoprecipitated the Hpg incorporated thyroglobulin (Tg) and its interacting proteins at different time points, and subjected the samples to tandem mass tag (TMT)-based quantitative MS analysis. The MS results show that WT and variant Tg proteins indeed associate with different proteostasis network factors in a differential manner over the course of time. In addition, they utilized an siRNA-based luciferase fusion assay to evaluate whether silencing each proteostasis network component changes the levels of Tg in both lysate and media. From the combination of the TRIP and siRNA-based assays, they found many hits, including hits implicated in protein degradation, VCP and TEX264, which they validated with multiple experiments.

I am overall quite positive and think this is an important study. But there are some meaningful points to consider.

Our Response: We thank Reviewer #1 for their positive outlook on our manuscript and their constructive feedback. We have addressed the comments below.

Significant comments:

Reviewer #1, Comment #1: Oonly two replicates of the main data (the TRIP-MS experiments) for this paper is problematic. Especially since the manuscript is supposed to be demonstrating and validating the new technique. Consistent with this concern, the relative enrichment profiles for some of the results were surprising. For instance, interaction with CCDC47 was tapering off but then at 3 h it suddenly reaches the maximum level of engagement. Is this a real finding or the variability in the method? Impossible to tell with two replicates. Presenting heat maps based on biological duplicates is also very problematic. It masks the error, which is large as can be seen in some of the panels showing individual proteins. In my view, triplicates and a clear understanding of the error in the technique should be required.

Our Response: The TRIP datasets for WT Tg contains 5 biological replicates, while the A2234D and C1264R Tg contains 6 biological replicates. Two replicates are typically included in a TMTpro 16plex mass spectrometry run, and each analysis consists of 3 MS runs. We apologize that the number of replicates and layout of the MS runs was not clearly explained. Data for individual replicates is found in Dataset EV1, Dataset EV3, and a newly added Table EV3 delineates the sample layout across the TMT channels and MS runs. We clarified the text as follows:

"Subsequently, two sets of TRIP time course samples (0, 0.5, 1, 1.5, 2, and 3 hr) could be pooled using the 16plex TMTpro and analyzed by LC-MS/MS (Fig 2A). In total, 5 biological replicates were analyzed for WT and 6 biological replicates were analyzed for A2234D and C1264R, respectively (Table EV3)."

Reviewer #1, Comment #2: The same concern arises for the high-throughput siRNA screen, which was performed only in duplicate for WT and A2234D.

Our Response: While the initial screen was performed in duplicate for WT and A2234D, which is common for larger screens due to resource constraints, we would like to direct the reviewer to the fact that we followed up on observed hits using thyroid cell lines with many more replicates. Furthermore, most hits came from the C1264R Tg variant, which had three replicates in the initial screen. Hits were also extensively followed-up.

Reviewer #1, Comment #3: *There are issues with some of the immunoprecipitation experiments: In Figure 1C, a negative control for FLAG IP is missing. *

*-In Figure 2B, I am curious why the band (Hpg -, chase time 0 h) is so faint for the first WB (IB for FLAG) - is Hpg treatment indeed leading to much more Tg present at 0 h? If so, that is a concern. *

-Also, a negative control must be included (either plain cells or cells expressing fluorescent protein or a different epitope-tagged WT Tg).

-In this same figure, I am puzzled why the bands for 1.5-3 timepoints in Biotin PD elution, probed for Rhodamine, are very faint especially considering that in Figure 1D, the corresponding bands, which are 4 h after the pulse, look fine. It seems like the IP failed here?

Our Response: In Fig 2B, we have updated this figure with higher-quality images that are more representative of the results found when performing this experiment. Furthermore, to address the missing negative controls in Fig. 1C, we have added a separate figure (Fig EV2) where (-) FLAG-tagged Tg is included in this panel. We updated the text as follows:

"Furthermore, the C-terminal FLAG-tag and Hpg labeling are necessary for this two-stage enrichment strategy, and DSP crosslinking is necessary to capture these interactions after stringent wash steps (Fig 1D, Fig EV2)."

Regarding the Biotin PD rhodamine/TAMRA signal in Fig 2B: The blots in this figure panel represent the time-resolved Tg fractions from cell lysate, corresponding only to intracellular thyroglobulin. The decrease in band intensity for 1.5-3 hr time points is expected due to continued secretion and/or degradation dynamics taking place that decrease the intracellular population of labeled thyroglobulin that is able to be captured. For comparison, please note the C1264R panel (Fig 2C), where the rhodamine/TAMRA signal in the Biotin PD elutions is more stable compared to WT, indicating the cellular retention of C1264R while WT Tg is efficiently secreted and the signal is lost more rapidly. Fig 1D contains samples derived from a 4 hr Hpg pulse (without chase), explaining why the overall fluorescent Tg signal is more intense.

Suggestion to consider:

Reviewer #1, Comment #4: This manuscript, supported by the title and abstract, mainly focuses on the presentation of the development and application of TRIP, which is highly significant. The story becomes less coherent and harder to follow as significant amounts of text/figures are dedicated to siRNA-based high throughput screening and follow-up. In addition, although the discovery of TEX264 as one of the hits is very interesting and exciting, TEX264 apparently was not a hit in the TRIP experiment and is pretty distracting from the main point of the paper highlighted in the abstract and title, therefore. The siRNA-based assay and follow-up studies could be a separate scientific story of their own. Especially considering my concerns on the number of replicates for both the TRIP and siRNA-based assay, it could be beneficial to actually split the manuscript into two and conduct more replicates of the -omic work, which should corroborate the exciting discoveries the authors have made.

Our Response: We have edited the manuscript to hopefully provide a more cohesive presentation of all data, findings, and conclusions within the paper. Given the generally positive outlook on the manuscript from other reviewers and our responses to significant comments from Reviewer #1 we opted to keep the manuscript as a single piece and address all reviewer comments.

Minor comments:

Reviewer #1, Comment #5: Throughout the manuscript, the authors have not defined what FT is; presumably it means FLAG tag.

Our Response: Reviewer #1 is correct in FT corresponding to FLAG tag. We have now edited the manuscript text to clarify this as follows:

"Thyroglobulin was chosen as model secretory client protein, and we generated isogenic Fischer rat thyroid cells (FRT) cells that stably expressed FLAG-tagged Tg (Tg-FT), including WT or mutant variants (A2234D and C1264R)."

Reviewer #1, Comment #6: The authors might discuss their rationale for choosing 0-3 hrs for their TRIP studies. That includes any relevant information about the half-life of WT versus variant Tg, whether the Hpg pulse time is short enough to avoid missing key features of the temporal interactome, and discussion of what would happen if the TRIP were performed at prolonged time points (e.g. 6-10 h).

Our Response: Apologies that we omitted this important point, which is indeed related to the secretion and degradation half-life. We edited the manuscript text to discuss the rationale for 0-3 hr, length of the Hpg pulse and the impact on capturing interactions, and performing TRIP at prolonged time points as follows:

"Our previous study indicated that ~70% of WT Tg-FT was secreted after 4 hours, while approximately 50% of A2234D and 15% of C1264R was degraded after the same time period (Wright et al, 2021). Therefore, we reasoned that a 3-hr chase period would be a enought time to capture the majority of Tg interactions throughout processing, secretion, cellular retention, and degradation, while still being able to capture an appreciable amount of sample for analysis."

We explain the labeling timeline and limitations further in the discussion:

"To address this, we utilized a labeling time of 1 hr which allows us to generate a large enough labeled population of Tg-FT for TRIP analysis, but some early interactions are likely missed within the TRIP workflow. In the case of mutant Tg, performing the TRIP analysis for much longer chase periods (6-8 hrs) may provide insightful details to the iterative binding process of PN components that is thought to facilitate protein retention within the secretory pathway."

Reviewer #1, Comment #7: Lines 68-69: the two citations should probably come one sentence earlier (at least Coscia et al 2020 is a structure paper).

Our Response: We agree. We have edited the manuscript as follows to correct this:

"In earlier work, we mapped the interactome of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism (CH) (Wright et al, 2021). Tg is a heavily post-translationally modified, 330 kDa prohormone that is necessary to produce triiodothyronine (T3) and thyroxine (T4) thyroid specific hormones (Citterio et al, 2019; Coscia et al, 2020). Tg biogenesis relies extensively on distinct interactions with the PN to facilitate folding and eventual secretion."

Reviewer #1, Comment #8: Line 91: "(Figure 1A)" should follow the sentence "To develop the time-resolved..." to help readers better understand the system.

Our Response: __We agree. We have edited the manuscript to add the Fig 1A reference. Furthermore, we redesigned the schematic in Fig 1A to better explain the experimental system. (see also __Reviewer #2, comment 10)

"To develop the time-resolved interactome profiling method, we envisioned a two-stage enrichment strategy utilizing epitope-tagged immunoprecipitation coupled with pulsed biorthogonal unnatural amino acid labeling and functionalization (Fig 1A). Cells can be pulse labeled with homopropargylglycine (Hpg) to synchronize newly synthesized populations of protein. After pulsed labeling with Hpg, samples can then be collected across time points throughout a chase period (Fig 1A, Box 1) (Kiick et al, 2001; Beatty et al, 2006). The Hpg alkyne incorporated into the newly synthesized population of protein can be conjugated to biotin using copper-catalyzed alkyne-azide cycloaddition (CuAAC) (Fig 1A, Box 2). Subsequently, the first stage of the enrichment strategy can take place where the client protein of interest is globally captured and enriched using epitope-tagged immunoprecipitation, followed by elution (Fig 1A, Box 3)."

Reviewer #1, Comment #9: Line 101: Fisher should be Fischer

Our Response: Thank you. We have edited the manuscript text to correct this.

Reviewer #1, Comment #10: Line 131: Should be 1.5 hrs instead of 2 hrs.

Our Response: We edited this point (see below in comment #11)

Reviewer #1, Comment #11: Lines 135-136: I do not agree with the claim that HSPA5 profile looked similar for MS and WB. I do not see a peak for HSPA5 at 2 hrs in Figure 2D.

Our Response: We replaced the mass spectrometry quantification in Fig 2D, E with the scaled, relative enrichments. This provides a more meaningful comparison, as all interactions are scaled in the same way. Unfortunately, it is still difficult to directly compare the Western blot results in Fig. 2B-C to the mass spectrometry quantifications in Fig 2D-E because the WB intensities are not normalized to the Tg bait protein amounts, which is changing over time. At 2-3hrs time points, little WT Tg is pulled down as most of it is secreted. Therefore, the HSPA5 interactions are no longer detectable by Western blot. On the other hand, MS is much more sensitive to capture the interactions. We modified the text as follows:

"For C1264R, interactions with HSPA5 were highly abundant at the 0 hr time point and remained mostly steady throughout the first 1.5 hours (Fig 2C). A similar temporal profile was also observed for HSP90B1. Additionally, interactions with PDIA4 were detectable for C1264R and were found to gradually increase throughout the first 1.5 hr of the chase period, before rapidly declining (Fig 2C). We noticed similar temporal profiles for PDIA4 and HSPA5 to our western blot analysis, when measured via TMTpro LC-MS/MS as further outlined below (Fig 2D-E). In particular, the HSPA5 WT Tg interaction declined within the first hours, yet for C1264R Tg, the HSPA5 interactions remained mostly steady over the 3-hour chase period. (Fig 2E)."

Reviewer #1, Comment #12: Line 186: The cited paper Shurtleff et al 2018 is missing in the reference list.

Our Response: Thank you. We have corrected this in the citation management system and it is now available in the reference list.

Reviewer #1, Comment #13: Line 188: I disagree with the authors' claim here because, at least for CCDC47, interactions with C1264R seem to come back at the 3 hr time point.

Our Response: We have removed the discussion of EMC and PAT complex components from the text. The implications of these interactions for Tg biogenesis remain unclear and were therefore a distraction from the discussion of other core proteostasis network components pertinent to Tg processing. Nonetheless, the full dataset - including these interactions - remains available to readers in Appendix Fig S1 for further perusal.

Reviewer #1, Comment #14: Line 203: I am not sure if P4HA1 can be included in the examples for showing distinct patterns for mutants compared to the WT according to their data in Figure 3H.

Our Response: We agree. We have edited the text to remove the discussion of prolyl hydroxylation and isomerization family members and elected to discuss the new clustering analysis and the robustness of the TRIP method in more detail. The full TRIP data is nonetheless available to interested readers in Appendix Fig S1.

Reviewer #1, Comment #15: Line 216: The authors should add citations about the functions of STT3A and STT3B proteins.

Our Response: We've edited the manuscript text to include a reference to the primary literature for STT3A and STT3B functions, as follows:

"Previously, we showed that A2234D and C1264R differ in interactions with N glycosylation components, particularly the oligosaccharyltransferase (OST) complex. Efficient A2234D degradation required both STT3A and STT3B isoforms of the OST, which mediate co-translational or post-translational N-glycosylation, respectively (Kelleher et al, 2003; Cherepanova & Gilmore, 2016)."

Reviewer #1, Comment #16: Lines 248-251, "We found that interactions with these components...": this sentence should refer to Figure 3 - Figure Supplement 3 instead of Figure 3L and S4.

Our Response: Thank you. This section of the manuscript was significantly rewritten and the figure references updated.

Reviewer #1, Comment #17: Lines 258-260, "Another striking observation was that the temporal profile of EMC interactions for C1264R correlated with RTN3, PGRMC1, CTSB, and CTSD interactions.": Please provide more evidence to support the potential correlation between different interaction profiles. Or the authors should move this sentence to the discussion section as it sounds speculative. This highlights the issue of only having duplicates, as well.

Our Response: We agree that this point was highly speculative and we removed discussion of the EMC interactions.

To further investigate the correlation of interaction profiles across the dataset, we performed unbiased k-means clustering. This led to the identification of 7 and 6 unique clusters of interactors for WT and C1264R Tg-FT, respectively. These data are represented in Fig 3F and Fig EV5. Unique clusters highlight similar temporal interaction profiles for Tg-FT interactors, and provide a quantitative representation of correlative interactions that take place during Tg-FT processing.

"To assess temporal interaction changes in an unbiased fashion and identify protein groups exhibiting comparative behavior, we carried out k-means clustering of the temporal profiles for WT and C1264R. This analysis revealed a large divergence in the interaction profiles. For WT Tg, only one cluster exhibited steadily decreasing interactions (cluster 4), while others increased with time, or showed peaks at intermediate times (Fig 3F, Fig EV5A). On the other hand, C1264R largely exhibited clusters with decreasing interactions over time (Fig 3F, Fig EV5B). Cluster 2 for WT with biomodal interactions at early and late time points contains many Hsp70/90 chaperoning components. For C1264R Tg, many Hsp70/90 chaperoning components and disulfide/redox-processing components are instead part of cluster 2', which exhibited an initial rise in interactions strength before plateauing (Fig 3F, Fig EV5A,B). This divergent temporal engagement between WT Tg and the destabilized C1264R mutant is aligned with the patterns observed in the manual grouping (Fig 3B,C), highlighting that the unbiased temporal clustering can reveal broader patterns in the reorganization of the proteostasis dynamics."

One of the clusters of the C1264R Tg interactions contained autophagy interactors along with glycosylation components. We therefore postulate that this could point to a coordination of these processes. We discuss this new point in the updated manuscript:

"In the k-means clustered profiles, autophagy interactions largely group together in the same cluster, showing stronger interactions at earlier time points. In the same cluster are glycosylation components (UGGT1 and STT3B, MLEC), further supporting a possible coordination for C1264R Tg between lectin-dependent protein quality control and targeting to autophagy (Fig EV5B,C)."

Reviewer #1, Comment #18: Line 340: As written, should cite more than one paper

Our Response: Thank you. We reworded the manuscript to correct this, as follows:

"The discovery of several protein degradation components as hits for rescuing mutant Tg secretion may suggest that the blockage of degradation pathways can broadly rescue the secretion of A2234D and C1264R mutant Tg, a phenomenon similarly found for destabilized CFTR implicated in the protein folding disease cystic fibrosis (Vij et al, 2006; Pankow et al, 2015; McDonald et al, 2022)."

Reviewer #1, Comment #19: Line 371: Should be Figure 4 - figure supplement 2

Our Response: We edited the manuscript to correct this error.

Reviewer #1, Comment #20: Line 1231: "Zhang et al 2018" needs to be removed

Our Response: We have removed this citation.

Reviewer #1, Comment #21: Line 1286: FRTR should be FRT

Our Response: Thank you. We have corrected this within the text.

Reviewer #1, Comment #22: Figure 3E: Color used to highlight the three proteins (CCDC47, EMC1, EMC4) should match the color used in Figure 3 - Figure Supplement 3

Our Response: __We have edited Figure 3 to remove the section related to membrane protein biogenesis. This data is still available in __Appendix Fig S1 with consistent color coding.

Reviewer #1, Comment #23: Figure 4A: The bottom figure where lysate signal is inversely proportional to time is misleading because the authors are assessing steady-state level of proteins in this assay.

__Our Response: __We agree. We updated the schematic in __Fig 4A __to better explain the workflow and differentiate the steady-state protein level being measured within the lysate.

Reviewer #1, Comment #24: Figure 4 - Figure Supplement 1 caption: in (C), (F) should be (B). (K) should be (G) and I am not sure what the authors mean when they refer to (J) in caption of (G).

Our Response: We have corrected this lettering mistake to match the figure properly. Please note that this figure is now Fig EV6, and it includes some new and reorganized panels.

Reviewer #1, Comment #25: Figure 5 caption for (C and D): Need to specify the time that the samples were collected (8 hrs), as it seems different from A and B according to the main text.

Our Response: We have specified the collection time within the caption for these data in Fig 5C __and __5D.

Reviewer #1, Comment #26: Figure 5 - Figure Supplement 1: Data for HERPUD1 and P3H1 should be included.

Our Response: We have now included data to confirm the knockdown for HERPUD1 and LEPRE1 (P3H1) in Fig EV7F-G.

Reviewer #1, Comment #27: Figure 5 - Figure Supplement 2B: Please mention in the caption how degradation is defined.

Our Response: We have updated the Fig EV7H caption to include how "degradation" is defined within these experiments:

"% Degradation is defined as . Where is the fraction of Tg-FT detected in the lysate at a given timepoint n, and is the fraction of Tg-FT detected in the media at a given timepoint n."

Reviewer #1 (Significance (Required)):

Reviewer #1, Comment #28: This manuscript is highly significant because the authors (1) designed and validated a new methodology for time-resolved interactomics study, (2) presented the dynamic changes in Tg interactome for WT and variants, and (3) discovered how proteins implicated in degradation pathways (e.g. VCP, TEX264, RTN3) can change the secretion profile of WT and mutant Tg proteins. With TRIP, the authors demonstrated that they could obtain valuable data that were previously not captured from steady-state interactomics studies (Wright et al. 2021; Figure 3M and Figure 3 - Figure supplement 4D-4I). Furthermore, the authors treated cells with VCP inhibitors and performed both 35S pulse-chase analyses and TRIP. These experiments provide valuable information to the field by (1) presenting a new method to rescue Tg secretion defect, and (2) demonstrating a broader applicability of TRIP. If the major comments above can be addressed I believe this is a tremendous contribution to the field.

Our Response: We thank Reviewer #1 for their review comments and praise for the work presented within this manuscript.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Reviewer #2: In the manuscript 'Time-Resolved Interactome Profiling Deconvolutes Secretory Protein Quality Control Dynamics' Wright et al. developed an approach for time-resolved protein protein interaction mapping relying on pulsed unnatural amino acid incorporation, protein cross linking, sequential affinity purification, and quantitative mass spectrometry named time-resolved interactome profiling (TRIP). The authors applied the TRIP method to compare the interactions of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism. They further employed an RNA interference screening platform (1) to investigate if (1) interactors identified via TRIP are functionally relevant for Tg protein quality control and (2) to identify factors that can rescue mutant Tg secretion. The screen was initially performed in HEK293 cells, but selected hits with a phenotype in HEK cells were then followed up in Fisher rat thyroid cells. Further functional validation was performed by pharmacologic inhibition of VCP, a hit from the RNAi screen with an effect on Tg lysate abundance and Tg secretion. While the authors present a comprehensive study including identification of protein-protein interactions using proteomics followed up by an RNA interference screen for functional validation, major comments need to be addressed for both the proteomics as well as the functional genomics aspects of the study (see comments below).

Our response: Thank you to reviewer 2 for their constructive feedback. We addressed all comments in detail below.

Major comments:

Reviewer #2, Comment #1: The authors describe a new method for quantitative, temporal interaction mapping. The protocol involves two enrichment steps as well as several reactions including cross-linking of the samples as well as functionalization of the unnatural amino acids. Given all these steps, the authors should rigorously characterize the quantitative reproducibility of the experiment when performed in independent biological replicates. This is important because in the final quantitative MS experiment, the authors only use two biological replicates, which is too low especially for such an involved sample preparation procedure, which would expect to have a high variability between replicates. Given the low number of replicates and the unknown reproducibility of the quantification for this protocol, it is questionable at this point how reliable the quantification over the time course is.

__Our Response: __We apologize that the number of replicates and robustness of the analysis was not entirely clear in our manuscript. We thank the reviewer for the feedback, as this is important point to clarify. We included several additional analyses to further explain the robustness and quantitative reproducibility of our results:

• We clarified the number of replicates For quantitative MS experiments five biological replicates were analyzed for WT, while six biological replicates were analyzed for A2234D and C1264R Tg-FT, respectively not two as mistakenly presumed by Reviewer #2. These data are available in Dataset EV1 and Table EV3. There is only one place where two biological replicates are included, C1264R Tg-FT FRT cells treated with ML-240 treatment for TRIP analysis. We have further clarified the number of biological replicates within the manuscript text as follows (see also reviewer #1, comment 1):

"Subsequently, two sets of TRIP time course samples (0, 0.5, 1, 1.5, 2, and 3 hr) could be pooled using the 16plex TMTpro and analyzed by LC-MS/MS (Fig 2A). In total, 5 biological replicates were analyzed for WT and 6 biological replicates were analyzed for A2234D and C1264R, respectively (Table EV3)."

• We displayed the reproducibility of TRIP time profiles for several individual proteins in Fig EV3 __and in __Fig 3K (VCP). We included shading to indicate the standard error of the mean (SEM) for the individual protein time courses to provide further assessment of the quantitative reproducibility. We updated the text as follows: "To benchmark the TRIP methodology, we chose to monitor a set of well-validated Tg interactors and compare the time-resolved PN interactome changes to our previously published steady-state interactomics dataset (Wright et al, 2021). Previously, we found that CALR, CANX, ERP29 (PDIA9), ERP44, and P4HB interactions with mutants A2234D or C1264R Tg exhibited little to no change when compared to WT under steady state conditions (Fig EV4A). However, in our TRIP dataset we were able to uncover distinct temporal changes in engagement that were previously masked within the steady-state data. Our time-resolved data deconvolutes these aggregate measurements, revealing prolonged CALR, ERP29, and P4HB engagements for both A2234D and C1264R Tg mutants compared to WT (Fig EV4B-F). We found that these measurements for key interactors and PN pathways exhibited robust reproducibility, as exemplified by the standard error of the mean for the TRIP data (Fig EV4B-I, Appendix Figure S1B)."

• For full transparency, we also include the SEM of all TRIP profiles in the heatmap in Appendix Fig S1B.

• Furthermore, we included 25-75% quartile ranges for the pathway aggregated time courses (Fig 3B,C,J,K) and the k-means hierarchical clustering analysis (Fig 3F, Fig EV5). Especially these clustering data allow for the visualization and analysis of temporal protein interactions that are correlated with one another, while the accompanying quartile ranges provide further context for the reproducibility of these measurements and cluster profiles (see __Reviewer #1, Comment 17 __above for further explanation about the k-means clustering).

  Reviewer #2, Comment #2: Compared to the previous dataset published last year, the authors discover an overlap in interactors, but also a huge discrepancy, with 96 previously identified interactors not detected in the current study, but 198 additional interactors identified. How do the authors explain the big differences between these datasets?

__Our Response: __We can only speculate here but this difference in overlapping interactors may stem from several different factors, including but not limited to cell line, instrumentation, LC-MS/MS methodology, and sample processing workflows. Our previous dataset was published using transiently transfected HEK293 cell lines expressed FLAG-tagged constructs of Tg. The HEK293 cell line makes for a robust cell line used throughout several biological investigations, but it is not representative of the native cellular environment in which Tg is expressed. Moreover, transiently transfected cells can lead to high protein expression that may not always represent what is found within the native cellular environment and proteome. Here, we used Fischer rat thyroid (FRT) cells engineered to stably express FLAG-tagged constructs of Tg. This cell line model should more accurately represent the native cellular environment Tg is expressed as it is exclusively found within thyroid tissue. Our previous dataset was collected across two different instruments with similar LC-MS/MS methodology. Here, this dataset was collected on a single instrument after performing further method optimization from our methodology used to acquire the first dataset. In line with our LC-MS/MS methodology development, the sample processing workflows here are quite different. Our previous dataset utilized 6plex TMT labeling with globally immunoprecipitated samples from various Tg constructs. Global immunoprecipitation of Tg leads to much larger protein sample amounts than the TRIP methodology presented here, which we coupled with 16plex TMTpro labeling. This is also one of the reasons we chose to deploy a booster/carrier channel within our experimental labeling schemes.

Reviewer #2, Comment #3: For the temporal interaction analysis the authors describe differences in the temporal profiles of selected interactions comparing wt and mutant, however no statistical analysis is performed comparing wt and mutant interaction profiles across the time course. Furthermore the variability between the replicates for the temporal profiles is not shown and some of the temporal profiles appear to be noisy. A more rigorous statistical analysis should be performed including additional biological replicates to evaluate the changes over the time course, especially as the temporal interaction analysis is the novelty of this study.

Our Response: Please also see our response to Reviewer #2, comment 1 above. We previously presented an analysis of the variability of the TRIP measurements (SEM) (now in Appendix Fig S1B). We have since provided further statistical analysis found in the updated Fig 2B,C,J, which include 25-75% quartile ranges for respective proteostasis network pathways. We also included SEM for the time profiles of individual interactors in Fig EV4.

To assess the divergence in time profiles in an unbiased way, we added a k-means hierarchical clustering analysis (Fig 3F, Fig. EV5). These clustering data allow for the visualization and analysis of temporal protein interaction profiles that are similar to one another and how groups of interactors shift between different clusters for WT Tg and the C1264R mutant.

Reviewer #2, Comment #4: To functionally validate interactors derived from the TRIP analysis as well as to identify factors that can rescue mutant Tg secretion the authors developed an RNA interference screen. There are a number of aspects that need to be addressed/clarified for this part of the study.

Our Response: We have added some clarifying changes to the text and the figure panels associated with the siRNA screening and follow-up experiments on the trafficking and degradation factors that rescue Tg secretion. We have addressed other comments from Reviewers #3 and #4 related to these portions of the paper and hope that Reviewer #2 finds them satisfactory.

Reviewer #2, Comment #5: While the authors validate the stable cell lines expressing the nanoluciferase tagged Tg and the linearity of luminescence signal in lysate and media carefully, they do not validate their platform in combination with the RNAi knockdown strategy. The authors should select genes as positive controls that are expected to modulate Tg secretion and demonstrate that the knockout of these positive controls indeed results in changes in Tg secretion in their system.

Our Response: This is an excellent suggestion and certainly something we would have done given any prior knowledge on known control genes that would positively or negatively regulate Tg secretion. The purpose for developing the siRNA screening platform was to investigate and hopefully discover genes that are able to positively or negatively regulate Tg processing. We have done so to the best of our ability, identifying for example NAPA which positively regulates WT Tg secretion, as seen by the decrease in WT Tg secretion when treated with NAPA siRNA. Conversely, we found that VCP may negatively regulate C1264R Tg secretion, as discovered by the increase in secretion with VCP siRNA or ML-240 treatment. We included a standard "TOX" siRNA control, which we knew would likely negatively affect WT Tg secretion and this was indeed the case. As we stated within the manuscript:

"This is the first study to broadly investigate the functional implications of Tg in-teractors and other PQC network components on Tg processing."

Reviewer #2, Comment #6: For the screen the authors select 167 Tg interactors and PN (Proteostasis network) related factors. This statement is very vague and the authors should clarify which genes were knocked down and which criteria were applied to narrow down the list of interactors and to select PN factors. The authors should therefore provide a supplementary table including all genes included in the screen, their source (were this derived from the initial study by Wright et al, from the current study or compiled from prior knowledge about PN), as well as their results from the screen based on luminescence in media and lysate. It is unclear how many of the selected factors are actually coming from the TRIP analysis.

Our Response: The list of genes included within the siRNA screen, as well as the results were previously included, and are now included in Appendix Fig S2. We have further provided the information requested by Reviewer #2 within Dataset EV5 indicating whether a gene was included in the siRNA screen due to its identification within our previous proteomics dataset (Wright et al, 2021.), the proteomics dataset presented here, or based upon primary literature. We added a comment in the text:

"Moreover, we were interested in identifying factors whose modulation may act to rescue mutant Tg secretion. HEK293 cells were engineered to stably express nanoluciferase-tagged Tg constructs (Tg-NLuc) and screened against 167 Tg interactors and related PN components (see Dataset EV5 for the list of genes)."

Reviewer #2, Comment #7: Only a small number of the 167 selected genes shows an effect on Tg abundance/secretion. How do the authors explain this result? Would we not expect that Tg interactors, especially those from the TRIP method which interact with the newly synthesized are more enriched for functionally relevant genes.

Our Response: The proteostasis network contains genes and proteins of high redundancy in structure and function, and many single-gene knockdowns are likely insufficient to have a large impact on Tg abundance or secretion. In fact, these results are in line with what we would have expected when designing these experiments. Our goal here was to identify the key players that control Tg protein quality control.

We explain the proteostasis network redundancy in the manuscript:

"The functional implications of protein-protein interactions can be difficult to deduce, especially in the case of PQC mechanisms containing several layers of redundancy across stress response pathways, paralogs, and multiple unique proteins sharing similar functions (Wright & Plate, 2021; Bludau & Aebersold, 2020; Karagöz et al, 2019; Braakman & Hebert, 2013)."

Reviewer #2, Comment #8: The authors initially performed the screen in HEK293 cells and as a second step wanted to validate the hits from the HEK cells in more relevant Fisher rat thyroid cells. Indeed they could show that knockdown of NAPA increased WT TG in lysate and decreased WT Tg secretion. Furthermore, they further validated genes to modulate mutant Tg lysate and media abundance. The authors should perform a rescue experiment to demonstrate that the observed phenotype can be reversed through re-introduction of NAPA.

Our Response: We have now performed the requested NAPA complementation experiments and provided the data within Fig EV 7I. Overexpression of a human, siRNA-resistant NAPA construct partially reversed the increase in WT Tg lysate retention. These results further support the identification of NAPA as a pro-trafficking factor for WT Tg. We updated the manuscript text to include these data as follows:

"To understand if these results were directly attributable to NAPA function, we performed complementation experiments where FRT cells treated with NAPA siRNAs were co-transfected with a human NAPA plasmid. WT Tg lysate abundance decreased when NAPA expression was complemented, confirming that the observed retention phenotype could be attributed to NAPA silencing (Fig EV7I). These results established that NAPA acts as a pro-secretion factor for WT Tg."

Reviewer #2, Comment #9: One hit from this analysis was the ER-phagy receptor TEX264, while TEX264 was not identified in the TRIP data, is selectively increased the C1264R secretion, but not wt and the other Tg mutant. Following Co-IP data however revealed some interaction between the C1264R and to a lesser extent the A2234D mutant. How do the authors explain that TEX264 was missed in the TRIP dataset?

Our Response: The TRIP samples are of much lower protein abundance compared to globally purified samples used for the Co-IP analysis. While the interaction is seen with the globally purified Co-IP samples, this interaction is likely much more difficult to capture with the low abundance, time-resolved samples that are acquired through the TRIP workflow, especially if this interaction is transient or requires the coordination of other accessory proteins as has been detailed in the literature and discussed within the manuscript presented here:

"While A2234D and C1264R Tg were preferentially enriched with TEX264 compared to WT, it remains unclear what other accessory proteins may be necessary for the recognition of TEX264 clients (Chino et al, 2019; An et al, 2019). Furthermore, TEX264 function in both protein degradation and DNA damage repair further complicates siRNA-based investigations (Fielden et al., 2022). Further investigation is needed to fully elucidate 1) if Tg degradation takes place via ER-phagy and 2) by which mechanisms this targeting is mediated."

Minor comments:

Reviewer #2, Comment #10: The workflow needs to be described clearer. For example, it should be better explained why the authors selected a two-stage enrichment strategy, I assume that the first based on the Flag affinity tag is to purify the protein of interest and the second step based on the incorporation and functionalization of the unnatural amino acids to enrich for the newly synthesized fraction at specific time points after protein synthesis? These are critical steps for the method but the rationals are not well explained, neither in the text nor the figures captures all these steps of the method very clearly, which makes it really difficult for the reader to understand the individual steps of the method. Moreover, the structures in Figure 1 workflow are not clearly labeled, so that it is confusing which part represents which protein/molecule.

Our Response: Thank you for this feedback. We have updated Fig 1 to provide more detail to provide more clarity for the readers. Furthermore, we have edited the text to more clearly describe the workflow:

"To develop the time-resolved interactome profiling method, we envisioned a two-stage enrichment strategy utilizing epitope-tagged immunoprecipitation coupled with pulsed biorthogonal unnatural amino acid labeling and functionalization (Fig 1A). Cells can be pulse labeled with homopropargylglycine (Hpg) to synchronize newly synthesized populations of protein. After pulsed labeling with Hpg, samples can then be collected across time points throughout a chase period (Fig 1A, Box 1) (Kiick et al, 2001; Beatty et al, 2006). The Hpg alkyne incorporated into the newly synthesized population of protein can be conjugated to biotin using copper-catalyzed alkyne-azide cycloaddition (CuAAC) (Fig 1A, Box 2). Subsequently, the first stage of the enrichment strategy can take place where the client protein of interest is globally captured and enriched using epitope-tagged immunoprecipitation, followed by elution (Fig 1A, Box 3). The second enrichment step can then utilize a biotin-streptavidin pulldown to capture the Hpg pulse-labeled, and CuAAC conjugated population, enriching samples into time-resolved fractions (Fig 1A, Box 4) (Li et al, 2020; Thompson et al, 2019)."

Reviewer #2, Comment #11: Except for the general workflow shown in Figure 1, a more detailed workflow showing the experimental steps, such as the sample fractions with the following steps could be added so that the design of the method is clearer. Also the style of the workflows including Figure 1, Figure 2A, and Figure 3A are different. It would be helpful to make them the same style and make the Figure 2A as a zoom in or more detailed illustration on part of Figure 1.

Our Response: Thank you for this feedback. In addition to updating Fig 1, we also expanded Fig 2A to more clearly outline the experimental steps in the TRIP workflow. Assuming the term "style" used here is in reference to color pallets and figure schematics used, these have been updated to ensure they are agreeable aesthetically across manuscript figures.

Reviewer #2, Comment #12: A summary of proteomics results of time course labeling after all enrichment steps, including the total number of identified proteins at different conditions and control would be helpful for having an overview impression on the proteomics results

Our Response: __We have included an updated __Dataset EV1 that provides a summary of proteomics data included which runs given proteins were identified in, % of TMT channels quantified, % of Hpg Pulse channels quantified, and generally number of proteins quantified across runs for each construct.

Reviewer #2, Comment #13: In Figure 2B, the WB for PDIA4 in the Biotin PD elution is missing. Why was the PDIA4 interaction missing for the time course analysis, but the interaction was captured in the initial test for Wt Tg (Figure 1D). Additionally, in this panel the Rhodamine Probe Gel shows inconsistencies at the time points 1.5 - 3h. Does this mean that the labeling did not work well for these conditions? As we would expect a consistent Rhodamine Probe signal at every time point.

Our Response: Please also see our response to Reviewer #1, comments 3 & 11. Fig 1D features continuous Hpg labeling for 4 hours to ensure that most intracellular Tg is labeled for this proof-of-concept experiment for the two-stage enrichment strategy. Fig 2B features a shorter 60 minute pulse of Hpg labeling, prior to the full chase period and two-stage enrichment strategy. PDIA4 interactions were detectable throughout Fig 1D because those measurements captured a larger population of labeled Tg, whereas in Fig 2B Tg bait protein amounts were much smaller after the two-stage enrichment procedure to capture the time-synchronized population.

The Rhodamine/TAMRA Probe Gel in Fig 2B does not have inconsistencies in Tg abundance, but highlights the fact that pulse labeled WT Tg is being secreted or degraded in FRT cells. As you would expect as time continues during the chase period, intracellular WT Tg signal decreases as secretion and degradation take place. Constant Rhodamine/TAMRA probe signal would not be expected here. Consistent with this, the C1264R Tg signal remains more stable for the intial time course. This is expected as the C1264R Tg variant is retained intracellular undergoing increased interactions the proteostasis network. We have removed the PDIA4 panel for WT Tg because there was no signal above the detection limit. This is now explained as follows:

"For WT Tg, interactions with HSPA5 peaked within the first 30 minutes of the chase period and rapidly declined, in line with previous observations, but PDIA4 interactions were not detectable by western blot analysis (Fig 2B) (Menon et al, 2007; Kim & Arvan, 1995)."

Reviewer #2, Comment #14: In Figure 2, why was there no WB results for the A2234D? In Figure 2D and 2E, at which time point are the changes significant compared to WT?

Our Response: We did not perform the WB experiments with A2234D. We used WT and C1264R Tg in our proof of concept experiments via WB and decided to move forward with analyzing A2234D Tg by LC-MS/MS. Please see our response above to Reviewer #2, comment 3 for information on the statistical analysis.

Reviewer #2, Comment #15: All figure legends should indicate how many biological replicates were performed for each experiment represented in the figure.

Our Response: We have updated the figure captions to include this information where applicable.

Reviewer #2, Comment #16: The heatmaps shown in Figure 3, Figure 3 - Figure Supplement 3, and Figure 7 are in the current form incomprehensible. The heatmaps depict the relative enrichment vs the control sample, which was scaled between 1 and -1. The color coding with 5 different colors from 1 to -1 is very confusing and should be changed to just two colors, one for positive and one for negative relative enrichment. I would also suggest changing the visualization of the heatmap showing the wt and mutants side by side, instead of stacked on top of each other for each individual protein.

Our Response: Thank you for this feedback, and we apologize for the confusion. We adjusted our data analysis approach by removing previous negative enrichment values. As these served only as "background" within the dataset, they did not carry much meaning. The TRIP enrichment is now scaled from 0 to 1, where a value of 1 represents the time point at which the enrichment is greatest, while 0 represents the background intensity in the (-) Hpg control sample. The associated figures have been updated accordingly, and we feel they are now more comprehensible and aesthetically pleasing.

We opted to keep the Viridis color scheme in the heatmap to allow for more nuanced differentiation of the enrichment values.

Reviewer #2, Comment #17: The data analysis method for generating relative enrichment shown in the heatmap is not explained. This should be described in the method section for a better understanding of the data analysis.

Our Response: We have edited the methods section as follows to better explain the analysis:

"For time resolved analysis, data were processed in R with custom scripts. Briefly, TMT abundances across chase samples were normalized to Tg TMT abundance as described previously and compared to (-) Hpg samples for enrichment analysis (Wright et al, 2021). For relative enrichment analysis, the means of log2 interaction differences were scaled to values from 0 to 1, where a value of 1 represented the time point at which the enrichment reached the maximum, and 0 represented the background intensity in the (-) Hpg channel. Negative log2 enrichment values were set to 0 as the enrichment fell below the background."

Reviewer #2, Comment #18: There are no legends of flowcharts in Figure 2A and Figure 3A and it is difficult to understand which are the key components in the complex and what are the differences among different periods of labeling.

Our Response: We have now consolidated Fig 2A and Fig 3A into a single panel found in Fig 2A, which is significantly reorganized to better explain the TRIP workflow. The caption has additionally been updated to highlight key steps within the workflow with numbering to allow readers to follow and visualize the steps more easily. The figure caption now reads as follows:

"(A) Workflow for TRIP protocol utilizing western blot or mass spectrometric analysis of time-resolved interactomes. (1) Cells are pulse-labeled with Hpg (200μM final concentration) for 1 hr, chased in regular media for specified time points, and cross-linked with DSP (0.5mM) for 10 minutes to capture transient proteoastasis network interactions; (2) Lysates are functionalized with a TAMRA-Azide-PEG-Desthiobiotin probe using copper CuAAC Click reaction; (3) Lysates undergo the first stage of the enrichment strategy where the Tg-FT is globally captured and enriched using immunoprecipitation; (4) Eluted Tg-FT populations from the global immunoprecipitation undergo biotin-streptavidin pulldown to capture the pulse Hpg-labeled, and CuAAC conjugated population of Tg-FT, enriching samples into time-resolved fractions; (5) Time-resolved fraction may then undergo western blot analysis or (6) quantitative liquid chromatography - tandem mass spectrometry (LC-MS/MS) analysis with tandem mass tag (TMTpro) multiplexing or analysis. The (-) Hpg control channel is used to identify enriched interactors and a (-) Biotin pulldown channel to act as a booster (or carrier)."

Reviewer #2, Comment #19: Why did only one of the VCP inhibitors (ML-240) exhibit a phenotype in Tg abundance and secretion, but not the other VCP inhibitors?

Our Response: Please also see our response to Reviewer #3, comment 2 below. This could be due to a number of reasons, but we added a brief discussion on the mechanisms of action for the inhibitors that may at least partially explain the differences in phenotype seen with the VCP inhibitors. We updated the text as follows:

"ML-240 and CB-5083 are ATP-competitive inhibitors that preferentially target the D2 domain of VCP subunits, whereas NMS-873 is a non-ATP-competitive allosteric inhibitor which binds at the D1-D2 interface of VCP subunits (Chou et al, 2013, 2014; Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019). ML-240 and NMS-873 have been shown to decrease both proteasomal degradation and autophagy, in line with VCP playing a role in both processes (Chou et al, 2013, 2014; Her et al, 2016). Conversely, while CB-5083 is known to decrease proteasomal degradation it has been shown to increase autophagy. (Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019)."

Reviewer #2 (Significance (Required)):

Reviewer #2, Comment #20: __The authors __describe a novel and elegant method to map time resolved protein interactions of newly synthesized proteins, which allows monitoring of proteins regulating protein quality control.

Authors describe it as a general method, however, they only demonstrate the applicability to one protein and do not systematically evaluate the quantitative nature of their approach by determining quantitative reproducibility, which would be necessary to be able to claim that this is a method with broad applicability.

Given my expertise in quantitative proteomics, I can mainly comment on the technological aspects of the proteomics part of the manuscript, but do not feel qualified to evaluate the significance of this study in terms of novel biology. Nevertheless, it feels that there is a stronger emphasis on the biology in the current form of the manuscript which will raise interest of scientists with a focus on protein quality control and Tg biology.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Please place your comments about significance in section 2.

In this manuscript, the authors describe their efforts to develop a methodology for determining time-resolved protein-protein interactions using quantitative mass spectrometry. With TRIP (time-resolved interactome profiling), they combine a pulsed bio-orthogonal unnatural amino acid labelling (homopropargylglycine, Hpg), CuAAC conjugation and biotin-streptavidin pulldowns to enrich at different timepoints and time-resolve by combining TMT labelling and LC-MS/MS (Figure 1). This technique is then applied to the maturation of the secreted WT and mutant thyroglobulin (Tg-WT, Tg-C1264R, Tg-A2234D) expressed in HEK293 and rat thyroid cells (FRT) and linked to hyperthyroidism. There, they identify a collection of ER resident proteins involved in protein folding/processing (e.g. chaperones, redox, glycans, hydroxylation) as well as degradation (e.g. autophagy, ERAD/proteasomes) (Fig. 2). Here the authors effectively use pulse-labelled form of TRIPs to highlight the different interactions formed with Tg-WT vs. Tg-mutants during biogenesis and secretion (or retention). The analysis found ~200 new interactions compared to previous studies along with about 40% of those identified previously. Differences in interactions were observed for mutants, which shown extended interaction with chaperones and redox processing pathways. While many interactions appeared as might be expected, the identification of membrane protein processing elements (e.g. EMC, PAT) was puzzling and raised some questions about the specificity within the protocol. Mutants enriched for CANX CALR and UGGT, suggesting prolonged association with glyco-processing factors. Interaction of C1264R with the ER-phagy factors CCPG1 and RTN3 was greater than WT. The authors note that their interaction correlated with that of EMC1 & 4, but it is not clear why that might be.

With interactors in hand, the authors complemented the TRIP protocol with siRNA KD of identified factors, to investigate any changes to secreted vs intracellular Tg upon loss. KD of NAPA (a-SNAP) and LMAN1 increased WT lysate (intracellular) Tg but not mutants. NAPA also reduced Tg-WT secretion. In contrast, KD of NAPA increased A2234D secretion while LEPRE1 increased C1264R (but not A2234D or WT), suggesting mutants have differential processing paths and requirements. KD of VCP increased secretion of both mutants. Some ER-phagy receptors were found among interactors (e.g. RTN3 in Tg-C1264R only) but often their KD had no impact on secretion (CCPG1, SEC62, FAM134B). NAMA observations were recapitulated in thyroid derived cell line (FRT). KD of TEX264 and VCP increased Tg-C1264 secretion while RTN3 KD in FRTs decreased Tg-C1264 secretion. This was in contrast to data from HEK293s for reasons that are not clear. Co-IP with TEX264 enriched for all Tg forms but more so for C1264R and A2234D - motivating the authors to propose selective targeting of Tg to TEX264 and the consideration of ER-phagy as a "major" degradative pathway during Tg processing.

Given the observations with siRNAs to VCP, the authors next use a selection of VCP inhibitors to ask whether secretion can be rescued upon pharmacological impairment of the AAA ATPase. They observed that ML-240, but interestingly not the more conventionally used CB-5083 or NMS-873, increased secretion of Tg-C1264R but not lysate. Inhibitors increased lysate but decreased the secreted fraction for Tg-WT (Fig 7). Finally, the authors used TRIP again in ML-240 treated Tg-C1264R expressing cells to look for changes to interactome with treatment - observed decreases to glycan and chaperone interactions, CANX and UGGT1, decreased interaction with DNAJB11 and C10, like that of WT. There was no apparent change to the UPR, although activation was not directly measured.

Major comments:

Reviewer #3, Comment #1: __Are the key conclusions convincing? __The TRIP methodology appears to be quite robust and should be a powerful strategy for this field and others going forward. The drawback will be the length of pulse required will limit the number/type of proteins to be monitored to ones with longer t1/2's. There were interesting interactions found with Tg and the mutants linked to hyperthyroidism, but cut and dry differences did not appear as obvious, even though strong "trends" appear to be present. The path from identifying interactors in a time-resolved manner to then following them up with targeted KD does provides some clarity, which is important.

Our Response: We thank Reviewer #3 for their time in reviewing our manuscript and providing this positive feedback. We have enhanced our analysis of the TRIP data to more clearly highlight difference in time profiles between WT and mutant variants. Please see our response to Reviewer #2, comment 1 & 3. We also highlight the limitations of the time resolution in the discussion (see also Reviewer #2, comment 6):

"To address this, we utilized a labeling time of 1 hr which allows us to generate a large enough labeled population of Tg-FT for TRIP analysis, but some early interactions are likely missed within the TRIP workflow. In the case of mutant Tg, performing the TRIP analysis for much longer chase periods (6-8 hrs) may provide insightful details to the iterative binding process of PN components that is thought to facilitate protein retention within the secretory pathway."

We have addressed all further comments below.

__Reviewer #3, Comment #2: __Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? The data regarding VCP silencing and pharmacological impairment appear clear but leave some questions outstanding in this reviewer's opinion. The lack of effect with the 2 highly selective inhibitors suggests that the underlying mechanism for switching fate of intracellularly retained Tg-C1264R towards secreted forms is not at all clear. ML-240 is an early derivative of DBeQ and reportedly impairs both ERAD and autophagic pathways, similarly to DBeQ. The differences between the VCP inhibitors' mechanism of action were not discussed, but perhaps should be elaborated upon, particularly in the matter of how ERAD and ER-phagy pathways might be being differentially affected. At the risk of asking for too many additional experiments, this reviewer would just prefer to see this fleshed out in a bit more detail.

Our response: We agree with Reviewer #3 that the underlying mechanism for switching fate of the intracellular retained Tg-C1264R towards secreted forms remains unclear. We have added additional text to discuss further the details surrounding the inhibitors used and the general manner in which ERAD and ER-phagy pathways can be affected. This added text reads as follows:

"ML-240 and CB-5083 are ATP-competitive inhibitors that preferentially target the D2 domain of VCP subunits, whereas NMS-873 is a non-ATP-competitive allosteric inhibitor which binds at the D1-D2 interface of VCP subunits (Chou et al, 2013, 2014; Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019). ML-240 and NMS-873 have been shown to decrease both proteasomal degradation and autophagy, in line with VCP playing a role in both processes (Chou et al, 2013, 2014; Her et al, 2016). Conversely, while CB-5083 is known to decrease proteasomal degradation it has been shown to increase autophagy. (Anderson et al, 2015; le Moigne et al, 2017; Tang et al, 2019)."

"As we discovered that pharmacological VCP inhibition with ML-240 can rescue C1264R Tg secretion yet is detrimental for WT Tg processing, it is unclear whether VCP may exhibit distinct functions for WT and mutant Tg PQC. Finally, as ML-240 is shown to block both the proteasomal and autophagic functions of VCP it is unclear which of these pathways may be playing a role in the rescue of C1264R, or detrimental WT processing (Chou et al, 2013, 2014)."

__Reviewer #3, Comment #3: __Q1. The degree (if any) of Tg-C1264 aggregation during and/or detergent solubility do not appear to have been considered as a potential source of the increase in released secreted material (Figure 4, 5). Do Tg mutants partition into RIPA-insoluble fractions at all? That is to say.. is the total population of synthesized Tg being considered? A full accounting? Could the authors address this and if biochemical extraction data (via urea or high SDS) is available, include it to answer this concern.

Our response: The transient aggregation of Tg has been investigated in some detail previously (Kim et al, 1992, 1993). The transient aggregates have the ability to partition into RIPA-insoluble fractions. Of note, these aggregates are shown to be made up, at least in part, of mixed disulfide linkages requiring reducing agent to fully resolubilize. With that being said, these aggregates represent a minority of the overall Tg population. In our prior manuscript (Wright, et al. 2021), we quantified the RIPA-insoluble fraction found in the pellet (see Supplemental Info Fig. 5). As the majority of Tg remains soluble during processing it should be able to be captured via our TRIP methodology. That is to say, we are capturing most of the Tg that is available for analysis while understanding that some smaller population of Tg remains in RIPA-insoluble fractions.

__Reviewer #3, Comment #4: __Q2. Along the same lines, what does Tg-WT and mutant expression look like by microscopy? Is Tg-WT uniformly distributed while Tg-mutants appear in puncta... more aggregated - perhaps reflecting the increased engagement of chaperones and redox machinery? Changes in the pattern of Tg-C1264R mutant (e.g. w/ VCP KD or inhibition) would add additional support for the authors interpretation of improved secretion. If this data is at hand, including it might be worth consideration.

Our response: Thank you for this suggestion. The subcellular localization of Tg and any changes from proteostasis modulation is an ongoing area of follow up work in our lab. We have some preliminary results that the localization for WT and C1264R Tg indeed differs. However, given that this manuscript is already dense in information, we opted to reserve this data for a future manuscript where we plan to further elucidate the targeting mechanism of mutant Tg to VCP or TEX264. We direct the reviewer to work published by Zhang et al, 2022,(https://doi.org/10.1016/j.jbc.2022.102066) showing a staunch difference of WT vs mutant Tg in the localization from intracellular to a secreted population in rat tissue. While most all WT Tg is found in the follicular lumen (secreted), mutant Tg heavily co-localizes with the ER resident chaperone BiP. While this paper does not go into detail on the differences in subcellular localization, it further highlights the drastic changes in Tg processing and how these manifest in distinct differences in localization within tissue.

__Reviewer #3, Comment #5: __Q3. Does the level of Tg mutant expression in the FRT clones impact the profiles obtained by TRIP? (Figure 3). This is a question of gauging the relative saturation of QC machinery and how that might impact profiles from TRIP. Were clones expressing at different levels tested? Perhaps a brief discussion of this.

Our response: We do not foresee an impact from level of Tg expression on the profiles obtained by TRIP. We were able to identify distinct profiles because we processed the data and normalized it based on the relative Tg amount. For example, while WT and A2234D Tg are expressed at similar levels intracellularly, we were able to identify distinct differences in the interaction profiles across the two constructs. When developing FRT clones, we selected those that were expressed at similar levels and, therefore, did not have the capability to directly test differences, if any, in observed profiles that may be the result of different expression levels of the same Tg construct. Furthermore, Tg can make up 50% of all protein content within thyroid tissue (Di Jeso & Arvan, 2016). As such, thyroid cells are adept at maintaining the balance of QC machinery to process thyroid. Therefore, we do not anticipate that the amount of Tg expressed in TRIP experiments would have a significant impact on the profiles that we were able to observe.

__Reviewer #3, Comment #6: __Q4. For Figure 3, the hour-long labelling period seems a bit long, compared with 3 hr of chase. Perhaps this reviewer missed this but how long does Tg take to mature and/or mutants to misfold and degrade? Is there any possibility to shorten this so that the profiles of labelled Tg could be more synchronized? If not, perhaps this could just be discussed.

Our response: While the 1-hour labeling period may seem long, we had to balance the labeling time to 1) label a large enough population of Tg for it to remain detectible throughout the chase period, and 2) keep the chase period long enough to capture the large majority of Tg processing. In our hands we found that by 4 hours WT Tg was ~63% secreted, with ~25% retained intracellular (Fig EV7H). Conversely, we found that C1264R remains very stable over this period with most protein being retaining intracellularly and little degradation taking place (Fig EV9A). Hence, we opted for the overall ~4 hour total for sample processing (1 Hr pulse labeling + 3 hour chase period for time point collections). Literature suggest that WT Tg takes ~2 hours to be processed within the ER and reach the medial golgi. This is exemplified by the EndoH resistant population that appears at this ~2 hour time point (Menon et al. JBC. 2007). Please also see our response to Reviewer #1, comment 6. We updated the text as follows:

"We pulse labeled WT Tg FRT cells with Hpg for 1 hr, followed by a 3 hr chase in regular media capturing time points in 30-minute intervals and analyzing via western blot or TMTpro LC-MS/MS (Fig 2A). Our previous study indicated that ~70% of WT Tg-FT was secreted after 4 hours, while approximately 50% of A2234D and 15% of C1264R was degraded after the same time period (Wright et al, 2021). Therefore, we reasoned that a 3-hr chase period would be a enought time to capture the majority of Tg interactions throughout processing, secretion, cellular retention, and degradation, while still being able to capture an appreciable amount of sample for analysis."

We anticipate that this labeling period can be decreased with future iterations of this methodology. This will also be bolstered by the continued improvements that come about within quantitative proteomics in increased instrument sensitivity and improved sample preparation methods that have the ability to decrease sample loss.

We explain the labeling timeline and limitations further in the discussion:

"To address this, we utilized a labeling time of 1 hr which allows us to generate a large enough labeled population of Tg-FT for TRIP analysis, but some early interactions are likely missed within the TRIP workflow. In the case of mutant Tg, performing the TRIP analysis for much longer chase periods (6-8 hrs) may provide insightful details to the iterative binding process of PN components that is thought to facilitate protein retention within the secretory pathway."

__Reviewer #3, Comment #7: __Q5. It is curious that only ML-240 and not other well characterized inhibitors of VCP/p97, has an effect, as both are used far more often than ML-240. The authors do not really address this in detail but does it suggest that the ML-240 effect on VCP/p97 could be affecting different pathways, given the nature of this compound. Is this compound acting on Tg-C1264R maturation at the level of translation or post-translationally? If the latter, through what means?

Our Response: We thank Reviewer #3 for appreciating this surprising finding. We were similarly curious as to how, or why ML-240 was able to elicit this effect compared to other VCP inhibitors. We elaborated in the manuscript text on these compounds and on how the ERAD and ERphagy pathways, utilizing VCP, may be differentially regulated (See response to__ Reviewer #3, Comment 2__). While speculative, we believe that ML-240 acts on C1264R Tg maturation post-translationally. This is given by the fact that ML-240 does not seem to affect the translational velocity of C1264R Tg, as Fig EV9A shows similar levels of 35S-labeled C1264R in DMSO or ML-240 treated cells. It may be the case that acute treatment with ML-240 alters the folding vs degradation balance of the ER proteostasis network in such a way that some population of C1264R that is usually degraded is able to be secreted. Another Tg mutation G2320R was shown to be degraded via the proteasome in PLCCL3 thyrocytes, as MG-132 treatment slowed mutant Tg degradation (Menon et al. JBC. 2007), although G2320R degradation was not be exclusively proteasomal. The L2284P Tg mutation exemplified similar results to G2340R where MG-132 slowed degradation. Furthermore, L2284P Tg was not affected by autophagic/lysosomal inhibitors chloroquine and E64 (Tokunaga et al. JBC. 2000), suggesting ERAD more exclusively degrades L2284P. It is unclear which degradation pathway, ERAD or ER-phagy, may be the predominate pathway for C1264R Tg degradation. Furthermore, we do not exclude the possibility that both may be at play and affected by treatment with ML-240.

We utilized our HEK293 Tg-NLuc cells and screened other proteasomal and lysosomal inhibitors bafilomycin and bortezomib. Neither of these compounds were able to rescue A2234D or C1264R secretion, highlighting that the effect is specific to ML-240 treatment. This new data is now shown in __Fig EV10A,B __and described in the text:

"To understand whether this rescue in secretion was uniquely linked to VCP inhibition or could be more broadly attributed to blocking Tg degradation, we tested the proteasomal inhibitor bortezomib, and lysosomal inhibitor bafilomycin. Bafilomycin increased WT Tg lysate abundance, and bortezomib significantly increased A2234D lysate abundance, consistent with a role of these degradation processes in Tg PQC (Fig EV10A). When monitoring Tg-NLuc media abundance, neither bafilomycin nor bortezomib significantly altered WT, A2234D, or C1264R abundance (Fig. EV10B). confirming that general inhibition of proteasomal or lysosomal degradation does with rescue mutant Tg secretion."

__Reviewer #3, Comment #8: __Q6. Continuing from Q5.. At what point and where is VCP/p97 able to affect mutant Tg processing? In line 317, the authors seem to correlate increased VCP association with mutants to their increased secretion. It is not clear how this would result, as engagement with VCP would be in a compartment different to that which supports trafficking and secretion. Could the authors expand on how this might come about. This is also relevant to the ML-240 data in Figure 7. Moreover, VCP is associated with ERAD (as is HerpUD1) rather than ER-phagy and at least in the siRNA raw data, there are also effects from Derlin3 and FAF2 KDs.. both ERAD factors. Some clarity here would be appreciated.

Our Response: This line of discussion in the text was meant to suggest that, since VCP showed a higher enrichment for mutant Tg, particularly C1264R, it would make sense that inhibiting VCP would have a larger effect on mutant Tg processing as compared to WT Tg. As we saw with the siRNA screening data, suppression of VCP resulted in increased C1264R secretion, while not affecting WT Tg processing. This passage was not intended to suggest that increased VCP association with mutant Tg found within the TRIP dataset was the reason for rescued secretion. These are two different sets of experiments and environments in which these data are captured. We were simply looking for the opportunity to bridge the findings from the two sets of experiments to a single discussion point. Of note, we understand that VCP is associated with ERAD and acts to regulate autophagy. Given that core autophagy machinery is relevant for both bulk autophagy and ER-phagy, we did not want to rule out the fact that VCP inhibition via ML-240 could affect autophagic flux in these experiments (Chou et al. Chemmedchem. 2013; Khaminets et al. Nature. 2015; Hill et al. Nat. Chem. Bio. 2021.)

It is great that the reviewer also noted that DERL3 and FAF2 knockdown increased C1264R Tg secretion. Since these ERAD factors did not reach the defined threshold in the screen, we did not include further discussion, but this data remains available in Appendix Fig S3. We have updated the manuscript text to clarify the previous points we aimed to make. The text now reads as follows:

"VCP silencing exclusively affecting mutant Tg corroborates our TRIP dataset, and suggest a more prominent role for VCP in mutant Tg PQC compared to WT. VCP interactions were sparse for WT Tg while they remained more steady throughout the chase period for the mutants (Fig 3H,K)."

__Reviewer #3, Comment #9: __Q7. There does not appear to be a direct demonstration of Tg-C1264R turnover by ER-phagy (via TEX264). Given the inconsistency with it not being detected by TRIP, while another receptor RTN3 was, but has not impact on Tg-C1264R secretion, perhaps including that data would go some way to demonstrating a fate of ER-phagy (at least partly) for this mutant.

Our response: We performed follow-up experiments to test interactions with Tg and the wider panel of ER-phagy receptors. We transiently expressed FLAG-tagged CCPG1, RTN3L, and TEX264 in HEK293 cells stably expressing Tg-NLuc and performed FLAG IPs followed by western blot analysis. We found that WT and C1264R Tg were enriched, albeit modestly, in the RTN3L Co-IP compared to control samples expressing GFP. Additionally, we found that WT, A2234D, and C1264R Tg were all enriched with CCPG1 compared to control samples expressing GFP. CCPG1 was found to be a C1264R Tg interactor within our mass spectrometry datasets, along with RTN3. We have now integrated these data into the manuscript as Fig EV8, and updated the manuscript text as follows:

"Additionally, we monitored Tg enrichment with ER-phagy receptors CCPG1 and RTN3 via Western blot as both were found to be C1264R Tg interactors within our TRIP dataset. RTN3L is found to be the only RTN3 isoform involved in ER turnover via ER-phagy (Grumati et al, 2017). WT and C1264R Tg-NLuc were modestly enriched with RTN3L compared to control samples expressing GFP. Conversely, we found that all Tg variants exhibited modest interactions with CCPG1 compared to control samples expressing GFP, although less than with TEX264 (Fig EV8).

Together, these data suggest that TEX264, CCPG1, or RTN3L engage with Tg during processing, and CH-associated Tg mutants may be selectively targeted to TEX264. Furthermore, ER-phagy may be considered as a degradative pathway in Tg processing, as other studies have mainly focused on Tg degradation through ERAD (Tokunaga et al, 2000; Menon et al, 2007)."

Whether the TEX246 recruitment of mutant Tg leads to degradation remains to be tested. When we monitored C1264R Tg degradation by pulse-chase assay (Fig. EV9A), only a small fraction (

__Reviewer #3, Comment #10: __Q9. The authors provide data that the UPR was not induced by ML-240 at 3hrs (10µM) (Figure 7, supplemental 1). This is in stark contrast to the results of Chou et al (2013) which the authors reference, reporting that ML-240 induced ATF4 and CHOP by 2 hrs at concentrations lower than used here (albeit a different cell type). While not exclusively UPR, could the authors address the potential activation of the integrated stress response (eIF2a phosphorylation, ATF4 and CHOP) in the FRT cells due to ML-240 treatment? If present, is there some link that could this provide an explanation for increased Tg-C1264R secretion? [Basal PERK/UPR activation with mutants.]

Our Response: Thank you for bringing up this important point. As the reviewer acknowledges, the difference in UPR activation could stem from the different cell lines. Additionally, we measured activation via qPCR, whereas Chou et al. measured via immunoblot. We would like to point out that while we did not observe the upregulation of HSPA5 or ASNS (markers of ATF6 and PERK/ISR activation, respectively) in the presence of short ML-240 treatment (2-3 hr), we did observe the upregulation of DNAJB9 (a marker of IRE1/XBP1s activation).

To address Reviewer #3's point, we performed further experiments monitoring the potential activation of the ISR in FRT cells due to ML-240 treatment. We treated C1264R Tg-FT FRT cells with ML-240 (10μM) for 2 hours, and monitored eIF2a phosphorylation via immunoblot. Indeed, we observed that ML-240 induced eIF2a phosphorylation compared to cells treated with DMSO. Tunicamycin (1mg/mL) was used a positive control, and showed similar results to ML-240. We have integrated these results into the manuscript, available in Fig EV10C.

However, we would like to point out that all of these markers represent signs of early UPR inductions. Importantly, our results that HSPA5 transcript levels are not induced suggest that there is only very modest upregulation of ER chaperone levels occurring. Typically, the ER proteostasis network remodeling requires a longer time than the acute 2-4 hr treatment with ML-240. We have updated the manuscript text as follows:

"Finally, we monitored activation of the unfolded protein response (UPR) in the presence of ML-240 in FRT cells expressing C1264R Tg-FT. Phosphorylation of eIF2a, an activation marker for the PERK arm of the UPR, was induced within 2 hr of ML-240 treatment (Fig EV10C). We further investigated the induction of UPR targets via qRT-PC. HSPA5 and ASNS transcripts, markers of ATF6 and PERK UPR activation respectively, remained unchanged or slightly decreased after 3 hr treatment with ML-240 in C1264R Tg cells (Fig EV10D). Only DNAJB9 transcript expression showed a significant increase in both WT Tg and C2164R Tg FRT cells (Fig EV10D). Moreover, ML-240 did not significantly alter cell viability after 3 hr, as measured by propidium iodide staining (Fig EV10E). Overall, these results highlight that the short ML-240 treatment induces early UPR markers, but the selective rescue of C1264R Tg secretion via ML-240 treatment is unlikely the results of global remodeling of the ER PN due to UPR activation."

__Reviewer #3, Comment #11: __Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. Any of the suggested experiments above all use reagents reported in the manuscript and so would presumably incur minimal cost and hopefully time. This reviewer is sympathetic to time and financial constraints and so discussion of the issue could suffice.

Our response: We have addressed follow-up experiments whenever possible or provided further discussion details where applicable. We are appreciative of Reviewer #3's sympathy for the time and financial constraints that go into this work and addressing manuscript revisions. Unfortunately, the 1st and 2nd authors both left the lab immediately after the reviews were received. Hence, many of the experiments had to be addressed by other lab members joining the project, which took considerably longer than anticipated. We apologize for the long delay with our revisions.

__Reviewer #3, Comment #12: __Are the data and the methods presented in such a way that they can be reproduced? Yes. The methodology is explained in detail.

Our Response: Thank you.

__Reviewer #3, Comment #13: __Are the experiments adequately replicated and statistical analysis adequate? Yes. Relevant information is either in the figure legends or is provided in the source data.

Our Response: Thank you.

Minor comments:

__Reviewer #3, Comment #14: __Are prior studies referenced appropriately? The references are generally appropriate, with a few exceptions of more general references used

Our Response: Thank you.

__Reviewer #3, Comment #15: __Are the text and figures clear and accurate? The text is clearly written, and the figures are clear.

Our Response: Thank you.

__Reviewer #3, Comment #16: __Do you have suggestions that would help the authors improve the presentation of their data and conclusions? A summary figure comparing the changing profiles of WT and C1264R and the factors implicated for them could be helpful.

Our Response: We opted not to include a summary figure because the paper and figures area already dense in information.

__Reviewer #3, Comment #17: __Perhaps include common nomenclature for proteins as well (e.g. HSP5A - BiP, HSP90B1 - Grp94, etc..)

Our Response: We updated the manuscript throughout to reference common nomenclature or other protein names where applicable at their first mention.

__Reviewer #3, Comment #18: __Line 317 - our is misspelled

Our Response: Thank you. We have made this correction.

__Reviewer #3, Comment #19: __Figure 4 - Supplemental Figure 1 - Legend has text referring to panels J and K, but Figure only goes up to F.

Our Response: Thank you. This was an error in references to Figure panel lettering and we have since corrected this. Please note that this Figure is now Fig EV6.

Reviewer #3 (Significance (Required)):

__Reviewer #3, Comment #20: __

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

• Place the work in the context of the existing literature (provide references, where appropriate).

Protein-protein interactions are often used to illustrate complexes and functionality, but these provide only snapshots, rather than "movies". There are many datasets out there exploring P-P interactions, but most if not all lack any temporal resolution for the interactions they report. The TRIP method described approaches this from the dynamic perspective - identifying the transient interactions formed by folding nascent chains with proteins that aid in their maturation and trafficking, or degradation. This represents an important technical advance in our ability to dynamically monitor protein interactions. The use of Tg mutants is valuable and perhaps this will lead to new perspectives on how to rescue it or other pathophysiological mutants with loss of function phenotypes.

• State what audience might be interested in and influenced by the reported findings.

This work should appeal to a broad audience within cell biology, particularly as the TRIP technique is attempting to address a fundamental question - what interactions form during the biogenesis/lifetime of a protein. Moreover, the effort to try to understand the different interactions formed with pathologically relevant mutant proteins as a strategy to try to rescue functionality, is a valuable exercise of this approach.

• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

ER quality control

Our Response: We thank reviewer #3 for this positive endorsement.

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

Summary

In this manuscript, Wright et al. developed an approach (termed TRIP) that allowed to map the temporal changes in the interaction landscape of a newly synthesized protein of interest. Using their TRIP approach, the authors found that the extensive interactions of thyroglobulin (Tg) with the proteostasis network (PN) during its passage through the secretory pathway were profoundly altered in response to disease-causing mutations (e.g. C1264R). The authors cross-validated their findings with a focus RNAi screen monitoring the cellular and secreted abundance of Tg variants upon deletion of PN components. In subsequent experiments the authors focused on two hits, VCP and TEX264, for which they confirmed their inhibitory effect on the secretion of Tg C1264R. Importantly, the authors found that TEX264 increasingly interacts with the Tg mutant and that pharmacological inhibition of VCP yielded the same phenotype than depletion of VCP. Overall, Wright and colleagues__ established an elegant method to map protein interaction in a time-resolved manner and demonstrated its value by the analysis of disease-related Tg mutants__. Hence, this work has the potential to serve as a rich resource for Tg-related research and as a powerful new tool to examine protein interactions. However, several concerns remain.

Our response: Thank you to reviewer #4 for their valuable feedback and positive assessment. We addressed all comments in detail below.

Major points:

__Reviewer #4, Comment #1: __Overall, the TRIP workflow is quite difficult to understand at a first glance - even for a reader with a background in proteomics, biochemistry and cell biology. The authors may want to improve the description of the TRIP methodology and explain in more detail what the individual components and steps are good for. Along the same line, from the main text and the figure legend it was not clear that Tg was actually Flag-tagged. However, without this information it is difficult to follow the workflow. While Figure 1A is certainly helpful, the bulky graphics are deflecting the reader's attention. A more schematic version might be more informative.

Our Response: Thank you for this feedback, which was also mirrored by Reviewer #2 (comment 10). We have made significant updates to clarify Fig 1 to provide more detail and eliminate some of unnecessary bulky graphics. We also expanded the schematic for the TRIP workflow in Fig 2A and we aligned all symbols used. Furthermore, we have edited the text to describe the workflow more clearly:

"To develop the time-resolved interactome profiling method, we envisioned a two-stage enrichment strategy utilizing epitope-tagged immunoprecipitation coupled with pulsed biorthogonal unnatural amino acid labeling and functionalization (Fig 1A). Cells can be pulse labeled with homopropargylglycine (Hpg) to synchronize newly synthesized populations of protein. After pulsed labeling with Hpg, samples can then be collected across time points throughout a chase period (Fig 1A, Box 1) (Kiick et al, 2001; Beatty et al, 2006). The Hpg alkyne incorporated into the newly synthesized population of protein can be conjugated to biotin using copper-catalyzed alkyne-azide cycloaddition (CuAAC) (Fig 1A, Box 2). Subsequently, the first stage of the enrichment strategy can take place where the client protein of interest is globally captured and enriched using epitope-tagged immunoprecipitation, followed by elution (Fig 1A, Box 3). The second enrichment step can then utilize a biotin-streptavidin pulldown to capture the Hpg pulse-labeled, and CuAAC conjugated population, enriching samples into time-resolved fractions (Fig 1A, Box 4) (Li et al, 2020; Thompson et al, 2019)."

Additionally, we have improved text to very clearly state that for the TRIP experiments Tg is FLAG-tagged and this epitope tag is required for the two-stage enrichment strategy. As one small example:

"Thyroglobulin was chosen as the model secretory client protein. We generated isogenic Fischer rat thyroid cells (FRT) cells that stably expressed FLAG-tagged Tg (Tg-FT), including WT or mutant variants (A2234D and C1264R) (Fig EV1)"

"Furthermore, the C-terminal FLAG-tag and Hpg labeling are necessary for this two-stage enrichment strategy, and DSP crosslinking is necessary to capture these interactions after stringent wash steps (Fig 1D, Fig EV2)."

__Reviewer #4, Comment #2: __To what extend do the difference in protein abundance between Tg WT and Tg C1264R contribute to the increase binding of their interactors (e.g., HSP5 and PDIA4). The authors should perform a TRIP coupled immunoblot analysis where WT and Mutant are loaded side-by-side on the SDS-PAGE.

Our Response: As Reviewer #3 (comment 5) had a similar inquiry, we provide the same response as listed above:

We do not foresee an impact from level of Tg expression on the profiles obtained by TRIP. We were able to identify distinct profiles because we processed the data and normalized it based on the relative Tg amount. For example, while WT and A2234D Tg are expressed at similar levels intracellularly, we ere able to identify distinct differences in the interaction profiles across the two constructs. When developing FRT clones, we selected those that were expressed at similar levels and, therefore, did not have the capability to directly test differences, if any, in observed profiles that may be the result of different expression levels of the same Tg construct. Furthermore, Tg can make up 50% of all protein content within thyroid tissue (Di Jeso & Arvan, 2016). As such, thyroid cells are adept at maintaining the balance of QC machinery to process thyroid. Therefore, we do not anticipate that the amount of Tg expressed in TRIP experiments would have a significant impact on the profiles that we were able to observe.

__Reviewer #4, Comment #3: __While the RNAi screen was done with pooled siRNA, it is not clear what was used for the RNAi validation experiments shown in Figure 5. This should be done by individual siRNA and not the same pooled reagents as used for the screen.

Our Response: Similarly, pooled siRNAs were initially utilized for the data shown in Figure 5. The RNAi screen utilized siRNAs optimized for human cells, where as those found for Figure 5 were for rat cells. For the revisions, we performed control experiments with individual siRNAs, which are now shown in Fig EV7J,K. While we did not find that any one single siRNA recapitulated the full phenotype, we did find that several single siRNAs for VCP and TEX264 at least partially restored the observed phenotype of increased C1264R Tg secretion. This result is expected given that we reasoned the siRNAs are likely providing an additive effect contributing to the observed phenotypes. We provided these single siRNA control experiments in Fig EV7J,K, and updated the manuscript text as follows:

"Several individual VCP and TEX264 siRNAs were able to partially recapitulate these increased secretion phenotype on C1264R Tg-FT, confirming that the effect is mediated by the respective gene silencing (Fig EV7J,K)."

Reviewer #4, Comment #4: __In Figure 5A it is not clear which band was used to quantify the effect of NAPA reduction. Also, this analysis lacks normalization to an unrelated protein or loading control. Moreover, the authors should also examine the effect of the siRNA targets shown in Figure 5C for Tg WT and not only the mutant.__

Our Response: The uppermost band in Fig 5A was used for quantification. We added a red asterisk similar to that found in Fig 5C to denote this lower back in the lysate panel(s) as a non-specific background band found within the Western blot. These data are the result of immunoprecipitations of both cell lysate and medium content, as such there is no applicable loading control that can be used within the western blots. For experiments, cell amounts were normalized by seeding and subsequently culturing the same amount of cells, as denoted within the Materials and Methods - FRT siRNA validation studies section of the manuscript. Furthermore, there are no loading controls that are easily utilized for analyzing cell culture medium. We have further clarified the Fig 5 caption to provide clearer experimental detail:

"(A and B) Western blot analysis (A) and quantification (B) of WT Tg-FT secretion from FRT cells transfected with select siRNAs hits from initial screening data set. Red asterisk denotes a non-specific background band within the western blot. Cells were transfected with 25nM siRNAs for 36 hrs, media exchanged and conditions for 4 hrs, Tg-FT was immunoprecipitated from lysate and media samples, and Tg-FT amounts were analyzed via immunoblotting. N = 6.

(C and D) Western blot analysis (C) and quantification (D) of C1264R Tg-FT secretion from FRT cells transfected with select siRNA hits from the initial screening data set. Red asterisk denotes a non-specific background band within the western blot. Cells were transfected with 25nM siRNAs for 36 hrs, media exchanged and conditions for 8 hrs, Tg-FT was immunoprecipitated from lysate and media samples, and Tg-FT amounts were analyzed via immunoblotting. All statistical testing performed using an unpaired student's t-test with Welch's correction. *pFinally, as the siRNA targets shown in Fig 5C were shown to be hits exclusively for C1264R Tg-FT we did not believe it was necessary to follow-up on these with WT Tg-FT. Similarly, we did not follow-up on hits that were exclusive to WT Tg-FT with C1264R and A2234D Tg-FT.

__Reviewer #4, Comment #5: __The authors should also test for the binding of RTN3 to Tg WT and mutant - in particular in comparison to TEX264. This would be important in the context that only RTN3 but not TEX264 was detected in the TRIP approach. Do the authors also detect VCP and LC3B in their pulldowns?

Our response: Please also see Reviewer #3, comment 9, who made a similar point.

We performed follow-up experiments to test interactions with Tg and the wider panel of ER-phagy receptors. We transiently expressed FLAG-tagged CCPG1, RTN3L, and TEX264 in HEK293 cells stably expressing Tg-NLuc and performed FLAG IPs followed by western blot analysis. We found that WT and C1264R Tg were enriched, albeit modestly, in the RTN3L Co-IP compared to control samples expressing GFP. Additionally, we found that WT, A2234D, and C1264R Tg were all enriched with CCPG1 compared to control samples expressing GFP. CCPG1 was found to be a C1264R Tg interactor within our mass spectrometry datasets, along with RTN3. We have now integrated these data into the manuscript as Fig EV8, and updated the manuscript text as follows:

"Additionally, we monitored Tg enrichment with ER-phagy receptors CCPG1 and RTN3 via Western blot as both were found to be C1264R Tg interactors within our TRIP dataset. RTN3L is found to be the only RTN3 isoform involved in ER turnover via ER-phagy (Grumati et al, 2017). WT and C1264R Tg-NLuc were modestly enriched with RTN3L compared to control samples expressing GFP. Conversely, we found that all Tg variants exhibited modest interactions with CCPG1 compared to control samples expressing GFP, although less than with TEX264 (Fig EV8).

Together, these data suggest that TEX264, CCPG1, or RTN3L engage with Tg during processing, and CH-associated Tg mutants may be selectively targeted to TEX264. Furthermore, ER-phagy may be considered as a degradative pathway in Tg processing, as other studies have mainly focused on Tg degradation through ERAD (Tokunaga et al, 2000; Menon et al, 2007)."

Regarding VCP, we can detect it routinely in our AP-MS experiment as presented previously (Wright et al. 2021), and here in Fig 3, Appendix Fig S1. However, we have not been able to detect interactions via western blot, which may be attributed to the increased sensitivity that LC-MS offers. We have not probed for LC3 interactions via western blot as we did not detect it by LC-MS either, but we identified several lysosomal and other autophagy-related components previously (Wright et al. 2021), and here shown in Appendix Fig S1 and Fig EV5C.

__Reviewer #4, Comment #6: __The effect of TEX264 depletion on Tg secretion should be confirmed by TEX263 KO experiments. Do the authors observe a similar increase in secreted Tg C1264R in BafA1- or SAR405-treated cells? Moreover, the authors should show that Tg C1264R is actually delivered to lysosomes using biochemical assays such as LysoIP or colocalization experiments.

Our response: To address this concern, we generated stable TEX264 knockout FRT cell lines by CRISPR, and probed several clones for their impact on Tg secretion. We found that TEX264 knockout did not recapitulate the increase in C1264R Tg secretion observed with transient siRNA knockout. While disappointing, these results are not necessarily surprising, considering that prolonged TEX264 knockout may lead the cell to adapt compensation mechanisms by modulating other proteostasis factors and/or autophagy machinery.

We performed experiments utilizing the autophagy inhibitor Bafilomycin A1, and have now included these results with the manuscript available in Fig EV10A,B. We found that BafA1 treatment led to the accumulation of WT Tg in the lysate but not for the C1264R Tg. We updated the manuscript text to accompany these data as follows:

"To understand whether this rescue in secretion was uniquely linked to VCP inhibition or could be more broadly attributed to blocking Tg degradation, we tested the proteasomal inhibitor bortezomib, and lysosomal inhibitor bafilomycin. Bafilomycin increased WT Tg lysate abundance, and bortezomib significantly increased A2234D lysate abundance, consistent with a role of these degradation processes in Tg PQC (Fig EV10A). When monitoring Tg-NLuc media abundance, neither bafilomycin nor bortezomib significantly altered WT, A2234D, or C1264R abundance (Fig. EV10B). confirming that general inhibition of proteasomal or lysosomal degradation does with rescue mutant Tg secretion."

These results raise the possibility that the mutant Tg interaction with TEX264 may not lead to active autophagic degradation of mutant Tg. This is also consistent with the slow degradation of C1264R Tg observed in the pulse-chase experiment in Fig EV9A. Whether the TEX246 recruitment of mutant Tg leads to degradation or assumes an alternative function, for example, intracellular sequestration, remains to be tested. Importantly, we have refrained from making claims in the manuscript that C1264R Tg is delivered to the lysosome but have presented data showing that it interacts with ER-phagy-related components and have further speculated on the possibility how autophagy could play a role in Tg processing.

Thank you for the LysoIP suggestion. Ongoing work in the lab is addressing this question and experiments suggested by the reviewer, but this is better reserved for a follow-up manuscript.

__Reviewer #4, Comment #7: __Figure 7A and 7C lack loading controls. The quantification shown in Figure 7B and 7D should be normalized to this control. Since VCP activity is often coupled to the of the proteasome, the authors should check whether blocking the proteasome yields a similar effect than ML-240.

Our Response: Like Fig 5A discussed above (Reviewer #4, comment 4), these data are the result of immunoprecipitations from cell lysate and medium. As a result, there is not applicable loading control that can be used within the western blots. For experiments, cell amounts were normalized by seeding and subsequently culturing the same amount of cells, as denoted within the Materials and Methods - FRT siRNA validation studies section of the manuscript and Material and Methods - VCP pharmacological inhibition studies.

Regarding the effect of proteasome inhibition, we tested whether bortezomib treatment can increase C1264R Tg secretion. We found that bortezomib led to a small but significant increase in A2234D Tg accumulation in the lysate, but did not increase secretion of Tg for WT or any of the mutant variants. This new data is shown in Fig EV10A,B. We updated the text as follow:

"To understand whether this rescue in secretion was uniquely linked to VCP inhibition or could be more broadly attributed to blocking Tg degradation, we tested the proteasomal inhibitor bortezomib, and lysosomal inhibitor bafilomycin. Bafilomycin increased WT Tg lysate abundance, and bortezomib significantly increased A2234D lysate abundance, consistent with a role of these degradation processes in Tg PQC (Fig EV10A). When monitoring Tg-NLuc media abundance, neither bafilomycin nor bortezomib significantly altered WT, A2234D, or C1264R abundance (Fig. EV10B). confirming that general inhibition of proteasomal or lysosomal degradation does with rescue mutant Tg secretion."

__Reviewer #4, Comment #8: __With regard to Figure 7 - Figure supplement 1: The authors should monitor the effect of ML-240 on Tg secretion such that WT and C1264R mutants are directly compared (side-by-side on the same immunoblot). Otherwise, it is difficult to claim that ML-240 rescues the secretion of the mutant.

Our response: The reviewer is referring to the S35 pulse-chase experiments now shown in Fig EV9. We would like to clarify that these images are not immunoblots but autoradiographs. Even though the samples for WT and C1264R Tg were loaded onto separate gels, the gels were imaged at the same time and are therefore directly comparable. Regardless, the more meaningful information that can be gleaned from these experiments are the absolute rates of protein secretion and degradation and how they change in response to ML-240 treatment. The scale in the quantifications (0 - 100%) is the same and corresponds to the total amount of WT or C1264R Tg that is labeled with 35S during the 30 min pulse. Importantly, we found that C1264R Tg-FT secretion is significantly increased in the presence of ML-240, changing from

__Reviewer #4, Comment #9: __How did ML-240 affect the ER-phagy components (in particular RTN3) in the TRIP analysis of Tg C1264R (Figure 7G-L)?

Our response: This is a great discussion point raised by reviewer #4. We have updated the manuscript text to discuss in more detail changes in interactions with degradation components, especially with proteasomal degradation machinery (Fig 7M,N). The manuscript text now reads as follows:

"The most striking interaction changes occurred with proteasomal degradation components, which remained steady until 1.5 hr, but then abruptly declined with ML-240 treatment at later time points (Fig 7M,N). This decline tracks with changes to the glycan processing machinery, highlighting that the coordination between N-glycosylation and diverting Tg away from ERAD may be a key to the rescue mechanism."

Minor points:

__Reviewer #4, Comment #10: __The candidate labeling in Figure 3 - Figure supplement 2 and 3 is too small und unreadable. The authors should provide a higher resolution of these figures or increase the font.

Our response: These figures are now in the Appendix and we have edited this figure to provide higher resolution.

Reviewer #4 (Significance (Required)):

Please see above

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Referee #2

Evidence, reproducibility and clarity

In the manuscript 'Time-Resolved Interactome Profiling Deconvolutes Secretory Protein Quality Control Dynamics' Wright et al. developed an approach for time-resolved protein protein interaction mapping relying on pulsed unnatural amino acid incorporation, protein cross linking, sequential affinity purification, and quantitative mass spectrometry named time-resolved interactome profiling (TRIP). The authors applied the TRIP method to compare the interactions of the secreted thyroid prohormone thyroglobulin (Tg) comparing the WT protein to secretion-defective mutations implicated in congenital hypothyroidism. They further employed an RNA interference screening platform (1) to investigate if (1) interactors identified via TRIP are functionally relevant for Tg protein quality control and (2) to identify factors that can rescue mutant Tg secretion. The screen was initially performed in HEK293 cells, but selected hits with a phenotype in HEK cells were then followed up in Fisher rat thyroid cells. Further functional validation was performed by pharmacologic inhibition of VCP, a hit from the RNAi screen with an effect on Tg lysate abundance and Tg secretion. While the authors present a comprehensive study including identification of protein-protein interactions using proteomics followed up by an RNA interference screen for functional validation, major comments need to be addressed for both the proteomics as well as the functional genomics aspects of the study (see comments below).

Major comments:

• The authors describe a new method for quantitative, temporal interaction mapping. The protocol involves two enrichment steps as well as several reactions including cross-linking of the samples as well as functionalization of the unnatural amino acids. Given all these steps, the authors should rigorously characterize the quantitative reproducibility of the experiment when performed in independent biological replicates. This is important because in the final quantitative MS experiment, the authors only use two biological replicates, which is too low especially for such an involved sample preparation procedure, which would expect to have a high variability between replicates. Given the low number of replicates and the unknown reproducibility of the quantification for this protocol, it is questionable at this point how reliable the quantification over the time course is.
• Compared to the previous dataset published last year, the authors discover an overlap in interactors, but also a huge discrepancy, with 96 previously identified interactors not detected in the current study, but 198 additional interactors identified. How do the authors explain the big differences between these datasets?
• For the temporal interaction analysis the authors describe differences in the temporal profiles of selected interactions comparing wt and mutant, however no statistical analysis is performed comparing wt and mutant interaction profiles across the time course. Furthermore the variability between the replicates for the temporal profiles is not shown and some of the temporal profiles appear to be noisy. A more rigorous statistical analysis should be performed including additional biological replicates to evaluate the changes over the time course, especially as the temporal interaction analysis is the novelty of this study.
• To functionally validate interactors derived from the TRIP analysis as well as to identify factors that can rescue mutant Tg secretion the authors developed an RNA interference screen. There are a number of aspects that need to be addressed/clarified for this part of the study.
• While the authors validate the stable cell lines expressing the nanoluciferase tagged Tg and the linearity of luminescence signal in lysate and media carefully, they do not validate their platform in combination with the RNAi knockdown strategy. The authors should select genes as positive controls that are expected to modulate Tg secretion and demonstrate that the knockout of these positive controls indeed results in changes in Tg secretion in their system.
• For the screen the authors select 167 Tg interactors and PN (Proteostasis network) related factors. This statement is very vague and the authors should clarify which genes were knocked down and which criteria were applied to narrow down the list of interactors and to select PN factors. The authors should therefore provide a supplementary table including all genes included in the screen, their source (were this derived from the initial study by Wright et al, from the current study or compiled from prior knowledge about PN), as well as their results from the screen based on luminescence in media and lysate. It is unclear how many of the selected factors are actually coming from the TRIP analysis.
• Only a small number of the 167 selected genes shows an effect on Tg abundance/secretion. How do the authors explain this result? Would we not expect that Tg interactors, especially those from the TRIP method which interact with the newly synthesized are more enriched for functionally relevant genes.
• The authors initially performed the screen in HEK293 cells and as a second step wanted to validate the hits from the HEK cells in more relevant Fisher rat thyroid cells. Indeed they could show that knockdown of NAPA increased WT TG in lysate and decreased WT Tg secretion. Furthermore, they further validated genes to modulate mutant Tg lysate and media abundance. The authors should perform a rescue experiment to demonstrate that the observed phenotype can be reversed through re-introduction of NAPA.
• One hit from this analysis was the ER-phagy receptor TEX264, while TEX264 was not identified in the TRIP data, is selectively increased the C1264R secretion, but not wt and the other Tg mutant. Following Co-IP data however revealed some interaction between the C1264R and to a lesser extent the A2234D mutant. How do the authors explain that TEX264 was missed in the TRIP dataset?

Minor comments:

• The workflow needs to be described clearer. For example, it should be better explained why the authors selected a two stage enrichment strategy, I assume that the first based on the Flag affinity tag is to purify the protein of interest and the second step based on the incorporation and functionalization of the unnatural amino acids to enrich for the newly synthesized fraction at specific time points after protein synthesis? These are critical steps for the method but the rationals are not well explained, neither in the text nor the figures captures all these steps of the method very clearly, which makes it really difficult for the reader to understand the individual steps of the method. Moreover, the structures in Figure 1 workflow are not clearly labeled, so that it is confusing which part represents which protein/molecule.
• Except for the general workflow shown in Figure 1, a more detailed workflow showing the experimental steps, such as the sample fractions with the following steps could be added so that the design of the method is clearer. Also the style of the workflows including Figure 1, Figure 2A, and Figure 3A are different. It would be helpful to make them the same style and make the Figure 2A as a zoom in or more detailed illustration on part of Figure 1.
• A summary of proteomics results of time course labeling after all enrichment steps, including the total number of identified proteins at different conditions and control would be helpful for having an overview impression on the proteomics results
• In Figure 2B, the WB for PDIA4 in the Biotin PD elution is missing. Why was the PDIA4 interaction missing for the time course analysis, but the interaction was captured in the initial test for Wt Tg (Figure 1D). Additionally, in this panel the Rhodamine Probe Gel shows inconsistencies at the time points 1.5 - 3h. Does this mean that the labeling did not work well for these conditions? As we would expect a consistent Rhodamine Probe signal at every time point.
• In Figure 2, why was there no WB results for the A2234D? In Figure 2D and 2E, at which time point are the changes significant compared to WT?
• All figure legends should indicate how many biological replicates were performed for each experiment represented in the figure.
• The heatmaps shown in Figure 3, Figure 3 - Figure Supplement 3, and Figure 7 are in the current form incomprehensible. The heatmaps depict the relative enrichment vs the control sample, which was scaled between 1 and -1. The color coding with 5 different colors from 1 to -1 is very confusing and should be changed to just two colors, one for positive and one for negative relative enrichment. I would also suggest changing the visualization of the heatmap showing the wt and mutants side by side, instead of stacked on top of each other for each individual protein.
• The data analysis method for generating relative enrichment shown in the heatmap is not explained. This should be described in the method section for a better understanding of the data analysis. There are no legends of flowcharts in Figure 2A and Figure 3A and it is difficult to understand which are the key components in the complex and what are the differences among different periods of labeling.
• Why did only one of the VCP inhibitors (ML-240) exhibit a phenotype in Tg abundance and secretion, but not the other VCP inhibitors?

Significance

The authors describe a novel and elegant method to map time resolved protein interactions of newly synthesized proteins, which allows monitoring of proteins regulating protein quality control. Authors describe it as a general method, however, they only demonstrate the applicability to one protein and do not systematically evaluate the quantitative nature of their approach by determining quantitative reproducibility, which would be necessary to be able to claim that this is a method with broad applicability.

Given my expertise in quantitative proteomics, I can mainly comment on the technological aspects of the proteomics part of the manuscript, but do not feel qualified to evaluate the significance of this study in terms of novel biology. Nevertheless, it feels that there is a stronger emphasis on the biology in the current form of the manuscript which will raise interest of scientists with a focus on protein quality control and Tg biology.

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Referee #1

Evidence, reproducibility and clarity

The authors report a mass spectrometry (MS)-based interactomics technique, time-resolved interactome profiling (TRIP), which allows for tracking temporal changes in the interactome of protein of interest. To show that TRIP can successfully deconvolute interactomes over time, they pulsed thyroid cells with homopropargylglycine (Hpg), immunoprecipitated the Hpg incorporated thyroglobulin (Tg) and its interacting proteins at different time points, and subjected the samples to tandem mass tag (TMT)-based quantitative MS analysis. The MS results show that WT and variant Tg proteins indeed associate with different proteostasis network factors in a differential manner over the course of time. In addition, they utilized an siRNA-based luciferase fusion assay to evaluate whether silencing each proteostasis network component changes the levels of Tg in both lysate and media. From the combination of the TRIP and siRNA-based assays, they found many hits, including hits implicated in protein degradation, VCP and TEX264, which they validated with multiple experiments.

I am overall quite positive and think this is an important study. But there are some meaningful points to consider.

Significant comments:

1. Only two replicates of the main data (the TRIP-MS experiments) for this paper is problematic. Especially since the manuscript is supposed to be demonstrating and validating the new technique. Consistent with this concern, the relative enrichment profiles for some of the results were surprising. For instance, interaction with CCDC47 was tapering off but then at 3 h it suddenly reaches the maximum level of engagement. Is this a real finding or the variability in the method? Impossible to tell with two replicates. Presenting heat maps based on biological duplicates is also very problematic. It masks the error, which is large as can be seen in some of the panels showing individual proteins. In my view, triplicates and a clear understanding of the error in the technique should be required.
2. The same concern arises for the high-throughput siRNA screen, which was performed only in duplicate for WT and A2234D.
3. There are issues with some of the immunoprecipitation experiments: In Figure 1C, a negative control for FLAG IP is missing. In Figure 2B, I am curious why the band (Hpg -, chase time 0 h) is so faint for the first WB (IB for FLAG) - is Hpg treatment indeed leading to much more Tg present at 0 h? If so, that is a concern. Also, a negative control must be included (either plain cells or cells expressing fluorescent protein or a different epitope-tagged WT Tg). In this same figure, I am puzzled why the bands for 1.5-3 timepoints in Biotin PD elution, probed for Rhodamine, are very faint especially considering that in Figure 1D, the corresponding bands, which are 4 h after the pulse, look fine. It seems like the IP failed here?

Suggestion to consider:

This manuscript, supported by the title and abstract, mainly focuses on the presentation of the development and application of TRIP, which is highly significant. The story becomes less coherent and harder to follow as significant amounts of text/figures are dedicated to siRNA-based high throughput screening and follow-up. In addition, although the discovery of TEX264 as one of the hits is very interesting and exciting, TEX264 apparently was not a hit in the TRIP experiment and is pretty distracting from the main point of the paper highlighted in the abstract and title, therefore. The siRNA-based assay and follow-up studies could be a separate scientific story of their own. Especially considering my concerns on the number of replicates for both the TRIP and siRNA-based assay, it could be beneficial to actually split the manuscript into two and conduct more replicates of the -omic work, which should corroborate the exciting discoveries the authors have made.

Minor comments:

Throughout the manuscript, the authors have not defined what FT is; presumably it means FLAG tag.

The authors might discuss their rationale for choosing 0-3 hrs for their TRIP studies. That includes any relevant information about the half-life of WT versus variant Tg, whether the Hpg pulse time is short enough to avoid missing key features of the temporal interactome, and discussion of what would happen if the TRIP were performed at prolonged time points (e.g. 6-10 h).

Lines 68-69: the two citations should probably come one sentence earlier (at least Coscia et al 2020 is a structure paper).

Line 91: "(Figure 1A)" should follow the sentence "To develop the time-resolved..." to help readers better understand the system.

Line 101: Fisher should be Fischer

Line 131: Should be 1.5 hrs instead of 2 hrs.

Lines 135-136: I do not agree with the claim that HSPA5 profile looked similar for MS and WB. I do not see a peak for HSPA5 at 2 hrs in Figure 2D.

Line 186: The cited paper Shurtleff et al 2018 is missing in the reference list.

Line 188: I disagree with the authors' claim here because, at least for CCDC47, interactions with C1264R seem to come back at the 3 hr time point.

Line 203: I am not sure if P4HA1 can be included in the examples for showing distinct patterns for mutants compared to the WT according to their data in Figure 3H.

Line 216: The authors should add citations about the functions of STT3A and STT3B proteins.

Lines 248-251, "We found that interactions with these components...": this sentence should refer to Figure 3 - Figure Supplement 3 instead of Figure 3L and S4.

Lines 258-260, "Another striking observation was that the temporal profile of EMC interactions for C1264R correlated with RTN3, PGRMC1, CTSB, and CTSD interactions.": Please provide more evidence to support the potential correlation between different interaction profiles. Or the authors should move this sentence to the discussion section as it sounds speculative. This highlights the issue of only having duplicates, as well.

Line 340: As written, should cite more than one paper

Line 371: Should be Figure 4 - figure supplement 2

Line 1231: "Zhang et al 2018" needs to be removed

Line 1286: FRTR should be FRT

Figure 3E: Color used to highlight the three proteins (CCDC47, EMC1, EMC4) should match the color used in Figure 3 - Figure Supplement 3

Figure 4A: The bottom figure where lysate signal is inversely proportional to time is misleading because the authors are assessing steady-state level of proteins in this assay.

Figure 4 - Figure Supplement 1 caption: in (C), (F) should be (B). (K) should be (G) and I am not sure what the authors mean when they refer to (J) in caption of (G).

Figure 5 caption for (C and D): Need to specify the time that the samples were collected (8 hrs), as it seems different from A and B according to the main text.

Figure 5 - Figure Supplement 1: Data for HERPUD1 and P3H1 should be included.

Figure 5 - Figure Supplement 2B: Please mention in the caption how degradation is defined.

Significance

This manuscript is highly significant because the authors (1) designed and validated a new methodology for time-resolved interactomics study, (2) presented the dynamic changes in Tg interactome for WT and variants, and (3) discovered how proteins implicated in degradation pathways (e.g. VCP, TEX264, RTN3) can change the secretion profile of WT and mutant Tg proteins. With TRIP, the authors demonstrated that they could obtain valuable data that were previously not captured from steady-state interactomics studies (Wright et al. 2021; Figure 3M and Figure 3 - Figure supplement 4D-4I). Furthermore, the authors treated cells with VCP inhibitors and performed both 35S pulse-chase analyses and TRIP. These experiments provide valuable information to the field by (1) presenting a new method to rescue Tg secretion defect, and (2) demonstrating a broader applicability of TRIP. If the major comments above can be addressed I believe this is a tremendous contribution to the field.

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Reply to the reviewers

Compared to our initial submission to Review Commons, we have addressed all the reviewers' comments. We have extensively re-written the manuscript to make it clearer to a larger audience. In particular, we have transferred Figure EV1 to Figure 1 with more complete panels and included a scheme (Figure EV3) on the steps of D2R internalization which we measure with live cell imaging. We have added a new paragraph to the start of the Discussion to summarize our main conclusions and reordered the discussion on the possible mechanisms of membrane PUFA enrichment on D2R endocytosis. All the changes in the text are in red for easier comparison with the previous version.

As suggested by reviewer 1, we have performed additional experiments to test the specificity of the effects of PUFA treatments on D2R endocytosis, reinforcing the results shown in Figure 4 using feeding assays. We show with live cell TIRF imaging and the ppH assay that TfR-SEP endocytosis is not affected (Figure EV5) and that SEP-β2AR endocytosis and βarr2-mCherry recruitment to the plasma membrane are not affected (Figure EV6).

Reviewer #1

Evidence, reproducibility and clarity

*The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3*

We thank the reviewer for his/her positive assessment of our work. We have checked the statistical tests used for all our measures. For Figure 2 and 3 (now 3 and 4) we test for only one factor (PUFA treatment or not) so we ran ordinary one-way ANOVA using Graphpad Prism.

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are: • The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized

The number of puncta, as well as their fluorescence, is reported by the analysis program (written in Matlab2021 and available upon request). We chose to show number of puncta because they reflect more directly the number of labelled endosomes (in Figures 3 and 4). As shown in the figure below, we found slight but significant differences between groups for FLAG-D2R (88.6 % and 87.6 % of average fluorescence in DHA and DPA treated cells compared to control cells), (panel A), and no differences for FLAG-β2AR (panel B). We find a significant decrease in puncta fluorescence for transferrin uptake in cells incubated with DHA (but not DPA) relative to control cells (panel C). However, because we did not detect differences in the number of puncta or in the frequency and amplitude of endocytic vesicle creation events (see below), we still conclude that enrichment with exogenous PUFAs does not affect clathrin mediated endocytosis.

In conclusion, the most robust measure of endocytosis for this assay is the number of detected puncta per cell rather than their fluorescence.

• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent. • The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis. We thank the reviewer for pointing this difference in the protocol. As a matter of fact, we have not used acid stripping in all the conditions used for the uptake assays (Figures 3 and 4). We apologize for the confusion and we have clarified this point in the Methods section. In early experiments we compared conditions with or without stripping but we concluded from these experiments that indeed, the stripping was not complete. Moreover, we noticed early on that many cells treated with DHA or DPA did not have any detectable cluster (13 cells out of 58 quantified cells treated with DHA after addition of QPL, 12/56 cells treated with DPA, 0/68 for cells treated with vehicle). Stripping the antibody would have made these cells undetectable, biasing the analysis. Therefore, to make our results more consistent we decided to use non-stripping conditions. To detect endosomes specifically, we used a segmentation tool developed earlier (see Rosendale et al.* 2019). This tool is based on wavelet transforms which recognizes dot-like structures. In addition, we excluded from the cell mask the labelled plasma membrane by a mask erosion.

We agree the design of experiments was not aimed at comparing the effect of PUFA treatment on low levels of constitutive D2R endocytosis. This would require more sensitive assays and be addressed in subsequent studies.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

We have now performed live imaging experiments in HEK293 cells expressing SEP-β2AR, GRK2 and βarr2-mCherry and stimulated with isoproterenol (Figure EV6). We show that the clustering of SEP-β2AR, of βarr2-mCherry, as well as endocytosis, are not affected by treatments with DHA or DPA. In this study, we focused on the early trafficking steps of D2R internalization. It will be interesting in a future study to address its consequences on G protein dependent and independent signaling. Moreover, and for good measure, we performed experiments to assess TfR-SEP endocytosis with the ppH assay. Again, we found no difference between cells treated or not with PUFAs (Figure EV5)

*References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. *

We have now cited Schmidt et al. 2020 doi 10.1111/bcpt.13274 in the discussion with the following sentences: "D2R also shows constitutive endocytosis (Schmidt et al, 2020) which may be modulated by PUFAs although we did not detect any significant difference in our measures (see Figure 3) which were aimed at detecting high levels of internalization induced by agonists. Further work will be required to specifically examine the effect of PUFAs on constitutive GPCR internalization."

Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include: • Chosing actual representative pictures of the quantitative data in Fig 2 and 3 (e.g. hard to see 25 endocytic events in Fig 2A constitutive endo, EtOH)

We apologize for the confusion. We employ a normalization procedure to account for cell size. In addition, all numbers have been normalized to the condition stimulated with agonist with no PUFA treatment). In fact, we detect in unstimulated cells very few puncta (on average 0.6, range 0-5) compared to 27.3 clusters (range 2-87) in cells stimulated with QPL.

• Showing actual p values for the statistical comparisons* For easier reading, we have kept the stars convention for the figures but added two tables with all statistical tests and the p values for both main figures and EV figures.

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

We have added titles to panels (in particular for Figure 2A,B which correspond to former Figure 1A,B) and we have given new titles to Y axes to make them clearer. We hope that the reading of our figures will now be easier.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

We have changed substantially Figure EV1 (now Figure 1) with new presentation of data: all 4 conditions (control, treated with DHA, DPA or BA) systematically presented in the same graph, and clearer titles for the parameter displayed on the Y axes. We hope that this figure is now easier to follow.

Significance

*The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.*

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Reviewer #2 (Evidence, reproducibility and clarity (Required)):

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The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper. There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.

The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.

I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.

We thank the reviewer for his/her comments. Indeed, our main message was that two types of PUFAs (DHA and DPA) specifically alter D2R endocytosis by reducing the recruitment of β-arrestin2 without changing D2R clustering at the plasma membrane. We are sorry that our writing was not clear enough. We also found out that in the last steps of the submission to Review Commons, the first paragraph of the Discussion was inadvertently erased. This made our main conclusions, summarized in this first paragraph, less clear. We have now put back this important paragraph. Moreover, we have extensively rewritten the manuscript thriving to make it as clear as possible to a large audience. We have reduced the use of acronyms to keep only the most used ones [e.g. PUFA (used 99 times), DHA (37 times), GPCR (34 times), D2R (126 times), GRK (17 times)] and made them consistent throughout the manuscript. Following the reviewer's suggestion, we have also added a scheme of the steps following D2R activation by agonist leading to its internalization (Figure EV3).

We understand that the reviewer implies by "in vivo data" results obtained in the brain of animals. As written in the Introduction and in the Discussion, the current work follows up on a recently published manuscripts by a subset of the authors, namely (i) Ducrocq et al. 2020 (doi 10.1016/j.cmet.2020.02.012) in which we show that deficits in motivation in animals deprived in ω3-PUFAs can be restored specifically by conditional expression of a fatty acid desaturase from c. elegans (FAT1) that allows restoring PUFA levels specifically in D2R-expressing striatal projection neurons (which mediate the so-called indirect pathway), and (ii) Jobin et al. 2023 (doi: 10.1038/s41380-022-01928-6) which combines in cellulo (HEK 293 cells) and in vivo data to show that PUFAs affects the ligand binding of the dopamine D2 receptor and its signaling in a lipid context that reflects patient lipid profiles regarding poly-unsaturation levels.

Reviewer #2 (Significance (Required)):

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In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.

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Reviewer #3 (Evidence, reproducibility and clarity (Required)):

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Summary:

The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.

Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.

We thank the reviewer for the positive appreciation of our work, qualified as a "thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity". We will address the specific points raised by the reviewer with our answers below.

Comments:

1. • A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.* Regarding the general comment of the reviewer, we agree that direct conclusion cannot be drawn on the etiology of psychiatric disorders by looking at the effect of membrane fatty acid levels on D2R in HEK 293 cells. Nevertheless, we mention in the Introduction the intriguing occurrence of low PUFA levels in psychiatric disorders as starting point to look at D2R as an important target for psychoactive drugs prescribed for these disorders. In the Discussion, we propose that manipulating fatty acid levels might potentiate the efficacy of D2R ligands used as treatments. We felt raising these aspects was not putting too much emphasis on psychiatric disorders. However, in accordance with the reviewer's comment, we toned down these descriptions in the revised manuscript.

The goal of increasing the levels of fatty acids at the membrane in HEK 293, the most widely used cellular system to study GPCR trafficking, was to try to emulate the levels of lipids in brain cells. Indeed, the levels of PUFAs in our culture conditions are much lower (~8 %, Figure 1B) than in brain extracts (~30 %). Therefore, the "control" condition in HEK 293 cells would correspond to PUFA deficiency while after our enrichment protocol these levels are closer to those found in brain cells. Our results could therefore be interpreted as endocytosis of D2R being augmented under membrane PUFA decrease. Importantly, increased receptor internalization often correlates with decreased signaling. Therefore, membrane PUFA enrichment in our conditions would rather potentiate D2R signaling.

• Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.*

The Reviewer is right that the conventional view is that excessive ω3 PUFA may not be harmful. However, this rather applies to dietary consumption, which might have limited effect to brain fatty acid contents since their accretion is highly regulated. Moreover, the majority of studies looking at ω3 supplementation have been performed in young adults and the effects on the developing brain - as it might be happening in pathological conditions in which D2R is involved - remain poorly understood. Furthermore, as mentioned above, blunted internalization of D2R under membrane PUFA enrichment is not an indication of "detrimental" to D2R function. Nor do we argue that membrane enrichment corresponds to excess PUFAs.

• I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.*

The Reviewer must refer to the fact that nutrients rich in SFAs are usually poor in PUFAs and vice-versa. Based on our lipidomic analysis, we now present in Figure 1B the effect of treatments (DHA, DPA, BA) on the levels of PUFAs (Figure 1B) and saturated fatty acids (Figure 1C). In cells treated with behenic acid (BA), PUFA levels are not significantly changed relative to control, untreated cells, while saturated fatty acid levels are increased. BA was used here to determine whether the effects observed with PUFAs was related to the enrichment in unsaturations or due to carbon chain length (C22). It is not the case because BA treatment, unlike DHA or DPA treatment, does not affect D2R endocytosis (Figure 2G,H).

• It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's. *

We agree that we could have made the rationale clearer. The goal in comparing ω3-DHA and ω6-DPA was to assess whether the position of the first unsaturation (n-3 vs n-6), with the same carbon chain length (C22) might differentially impact D2R endocytosis.

• In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?*

The reviewer is correct: the level of SFAs is increased by 5.2% (34.5 % of total FAs in control cells to 39.7 % in BA treated cells), more than the increase in BA alone (1.18% from 0.35 % to 1.53 %). A close look at our lipidomics data showed that many of the 10 saturated fatty acids quantified are enhanced. In particular, the two most abundant ones, palmitic acid (16:0) and stearic acid (18:0) are increased, from 21.37 % to 22.28 % and 8.47 % to 11.17%, respectively. The reasons for these apparent discrepancies may involve lipid metabolic pathways which convert the rare and long BA into more common and shorter SFAs to preserve lipid contents and thus membrane properties.

• In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)*

We wanted to convey the impression that the time to reach the peak βarr2-mCherry recruitment was shorter in PUFA-treated cells than in control cells. However, after analyzing the kinetics in individual cells, we did not find a statistically significant difference in the time to maximum fluorescence. Therefore, we removed this reference to the kinetics of recruitment.

We now write: " However, treatment with DHA or DPA significantly decreased peak βarr2-mCherry fluorescence (Figure 5F-G).."

• In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.*

The purpose of this panel is to show the kinetics of increase in the frequency of endocytic vesicle formation upon agonist addition, and the decrease in frequency when the agonist is removed. We have now added examples of cells treated with DHA and DPA of similar surface for direct comparison with control (EtOH) cells.

• For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.*

We have now transferred Figure EV1 as Figure 1. We have adapted the scheme of the DERET assay and its legend (now in Figure EV1A) to make it clearer. We did not put in Figure 2 because this figure is already very big. We have changed "Normalized R" to "Ratio 620/520) (% max)" to be clearer and more consistent with the scheme.

Reviewer #3 (Significance (Required)):

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General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.

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Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.

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Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.

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Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions

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Referee #1

Evidence, reproducibility and clarity

The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are:

• The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent.
• The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include:

• Chosing actual representative pictures of the qunatiative data in Fig 2 and 3 (e.g. har to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
• Showing actual p values for the statistical comparisions

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

Significance

The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Compared to our initial submission to Review Commons, we have addressed all the reviewers' comments. We have extensively re-written the manuscript to make it clearer to a larger audience. In particular, we have transferred Figure EV1 to Figure 1 with more complete panels and included a scheme (Figure EV3) on the steps of D2R internalization which we measure with live cell imaging. We have added a new paragraph to the start of the Discussion to summarize our main conclusions and reordered the discussion on the possible mechanisms of membrane PUFA enrichment on D2R endocytosis. All the changes in the text are in red for easier comparison with the previous version.

As suggested by reviewer 1, we have performed additional experiments to test the specificity of the effects of PUFA treatments on D2R endocytosis, reinforcing the results shown in Figure 4 using feeding assays. We show with live cell TIRF imaging and the ppH assay that TfR-SEP endocytosis is not affected (Figure EV5) and that SEP-β2AR endocytosis and βarr2-mCherry recruitment to the plasma membrane are not affected (Figure EV6).

Reviewer #1

Evidence, reproducibility and clarity

*The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3*

We thank the reviewer for his/her positive assessment of our work. We have checked the statistical tests used for all our measures. For Figure 2 and 3 (now 3 and 4) we test for only one factor (PUFA treatment or not) so we ran ordinary one-way ANOVA using Graphpad Prism.

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are: • The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized

The number of puncta, as well as their fluorescence, is reported by the analysis program (written in Matlab2021 and available upon request). We chose to show number of puncta because they reflect more directly the number of labelled endosomes (in Figures 3 and 4). As shown in the figure below, we found slight but significant differences between groups for FLAG-D2R (88.6 % and 87.6 % of average fluorescence in DHA and DPA treated cells compared to control cells), (panel A), and no differences for FLAG-β2AR (panel B). We find a significant decrease in puncta fluorescence for transferrin uptake in cells incubated with DHA (but not DPA) relative to control cells (panel C). However, because we did not detect differences in the number of puncta or in the frequency and amplitude of endocytic vesicle creation events (see below), we still conclude that enrichment with exogenous PUFAs does not affect clathrin mediated endocytosis.

In conclusion, the most robust measure of endocytosis for this assay is the number of detected puncta per cell rather than their fluorescence.

• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent. • The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis. We thank the reviewer for pointing this difference in the protocol. As a matter of fact, we have not used acid stripping in all the conditions used for the uptake assays (Figures 3 and 4). We apologize for the confusion and we have clarified this point in the Methods section. In early experiments we compared conditions with or without stripping but we concluded from these experiments that indeed, the stripping was not complete. Moreover, we noticed early on that many cells treated with DHA or DPA did not have any detectable cluster (13 cells out of 58 quantified cells treated with DHA after addition of QPL, 12/56 cells treated with DPA, 0/68 for cells treated with vehicle). Stripping the antibody would have made these cells undetectable, biasing the analysis. Therefore, to make our results more consistent we decided to use non-stripping conditions. To detect endosomes specifically, we used a segmentation tool developed earlier (see Rosendale et al.* 2019). This tool is based on wavelet transforms which recognizes dot-like structures. In addition, we excluded from the cell mask the labelled plasma membrane by a mask erosion.

We agree the design of experiments was not aimed at comparing the effect of PUFA treatment on low levels of constitutive D2R endocytosis. This would require more sensitive assays and be addressed in subsequent studies.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

We have now performed live imaging experiments in HEK293 cells expressing SEP-β2AR, GRK2 and βarr2-mCherry and stimulated with isoproterenol (Figure EV6). We show that the clustering of SEP-β2AR, of βarr2-mCherry, as well as endocytosis, are not affected by treatments with DHA or DPA. In this study, we focused on the early trafficking steps of D2R internalization. It will be interesting in a future study to address its consequences on G protein dependent and independent signaling. Moreover, and for good measure, we performed experiments to assess TfR-SEP endocytosis with the ppH assay. Again, we found no difference between cells treated or not with PUFAs (Figure EV5)

*References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. *

We have now cited Schmidt et al. 2020 doi 10.1111/bcpt.13274 in the discussion with the following sentences: "D2R also shows constitutive endocytosis (Schmidt et al, 2020) which may be modulated by PUFAs although we did not detect any significant difference in our measures (see Figure 3) which were aimed at detecting high levels of internalization induced by agonists. Further work will be required to specifically examine the effect of PUFAs on constitutive GPCR internalization."

Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include: • Chosing actual representative pictures of the quantitative data in Fig 2 and 3 (e.g. hard to see 25 endocytic events in Fig 2A constitutive endo, EtOH)

We apologize for the confusion. We employ a normalization procedure to account for cell size. In addition, all numbers have been normalized to the condition stimulated with agonist with no PUFA treatment). In fact, we detect in unstimulated cells very few puncta (on average 0.6, range 0-5) compared to 27.3 clusters (range 2-87) in cells stimulated with QPL.

• Showing actual p values for the statistical comparisons* For easier reading, we have kept the stars convention for the figures but added two tables with all statistical tests and the p values for both main figures and EV figures.

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

We have added titles to panels (in particular for Figure 2A,B which correspond to former Figure 1A,B) and we have given new titles to Y axes to make them clearer. We hope that the reading of our figures will now be easier.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

We have changed substantially Figure EV1 (now Figure 1) with new presentation of data: all 4 conditions (control, treated with DHA, DPA or BA) systematically presented in the same graph, and clearer titles for the parameter displayed on the Y axes. We hope that this figure is now easier to follow.

Significance

*The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.*

• *

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

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The only conclusion that I was able to understand from the study was that enrichment of cell membranes with polyunsaturated fatty acids specifically inhibited agonist-induced internalization of D2 receptors. However, I think that the experiments used to conclude that PUFAs do not alter D2R clustering but reduce the recruitment of β-arrestin2 and D2R endocytosis need some clarification (i.e. data depicted in Fig. 2-5). This lack of clarity might be due to the fact I am not familiar enough with the employed technologies or to the unclear writing style of the paper. There was an overuse of acronyms, initialisms and abbreviations, which are difficult to understand for researchers outside of the specific lipid field. I think that the manuscript should be written in a way to be legible also for researchers not working in the immediate filed.

The paper was not written in a manner that a general audience of cell biologists or those interested in GPCR biology could understand and judge. It is indeed interesting that polyunsaturated fatty acids specifically inhibit D2R internalization in HEK293 cells, and it could be significant. But, it is difficult to judge the significance of the observation without more in vivo data.

I would suggest the following. Remove all acronyms and abbreviations. Significantly, expand the Materials and Methods section, either in the manuscript or in the Supplemental section. I suggest clearly explaining each construct used, and the function of each module in the construct, with diagrams. In addition, provide a comprehensive step by step description of each experimental protocol, providing the reader with the rationale for each step in the protocol with explanatory diagrams. The authors should also more clearly explain the rationale and logic that was utilized to make the conclusions that they did from the depicted observations. Only then can a broader audience determine if the authors' conclusions are justified.

We thank the reviewer for his/her comments. Indeed, our main message was that two types of PUFAs (DHA and DPA) specifically alter D2R endocytosis by reducing the recruitment of β-arrestin2 without changing D2R clustering at the plasma membrane. We are sorry that our writing was not clear enough. We also found out that in the last steps of the submission to Review Commons, the first paragraph of the Discussion was inadvertently erased. This made our main conclusions, summarized in this first paragraph, less clear. We have now put back this important paragraph. Moreover, we have extensively rewritten the manuscript thriving to make it as clear as possible to a large audience. We have reduced the use of acronyms to keep only the most used ones [e.g. PUFA (used 99 times), DHA (37 times), GPCR (34 times), D2R (126 times), GRK (17 times)] and made them consistent throughout the manuscript. Following the reviewer's suggestion, we have also added a scheme of the steps following D2R activation by agonist leading to its internalization (Figure EV3).

We understand that the reviewer implies by "in vivo data" results obtained in the brain of animals. As written in the Introduction and in the Discussion, the current work follows up on a recently published manuscripts by a subset of the authors, namely (i) Ducrocq et al. 2020 (doi 10.1016/j.cmet.2020.02.012) in which we show that deficits in motivation in animals deprived in ω3-PUFAs can be restored specifically by conditional expression of a fatty acid desaturase from c. elegans (FAT1) that allows restoring PUFA levels specifically in D2R-expressing striatal projection neurons (which mediate the so-called indirect pathway), and (ii) Jobin et al. 2023 (doi: 10.1038/s41380-022-01928-6) which combines in cellulo (HEK 293 cells) and in vivo data to show that PUFAs affects the ligand binding of the dopamine D2 receptor and its signaling in a lipid context that reflects patient lipid profiles regarding poly-unsaturation levels.

Reviewer #2 (Significance (Required)):

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In summary, I will reiterate that the reported experiments need to be much better explained to make the study understandable to a broader audience and for that audience to determine whether the conclusions are justified.

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Reviewer #3 (Evidence, reproducibility and clarity (Required)):

• *

Summary:

The authors investigate the role of lipid polyunsaturation in endocytic uptake of the dopamine D2 receptor (D2R). To modulate the degree of unsaturation in live cell plasma membranes, the authors incubate cell lines with pure fatty acid that is metabolized and incorporated into the cellular membranes. To quantify the internalization of D2R in these live cells, the authors utilized quantitative fluorescence assays such as DERET and endosome analysis to determine the degree and rate of D2R internalization in the presence of two model agonists - dopamine and quinpirole. The authors conclude that when the PUFA content of the plasma membrane is increased (i.e., via ω3 or ω6 fatty acids), both the quantity and rate of D2R internalization decrease substantially. The authors confirmed that these phenomena are specific to D2R as caveolar endocytosis and clathrin-mediated endocytosis were unaffected when these same experimental techniques were utilized for β2 adrenergic receptor and transferrin. Additionally, the authors conclude that the clustering ability of D2R is unaffected by lipid unsaturation but that the ability of D2R clusters to interact with β-arrestin2 is inhibited in the presence of excess PUFA. Based on these findings, the authors propose several hypothetical mechanisms for lipid-D2R interactions on the plasma membrane, which will likely be the scope of future work.

Overall, this is a highly thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity. However, I do not agree with the authors' conclusions pertaining to how their results should be interpreted in the context of fatty acid-related disorders. Additionally, this manuscript could benefit from some reorganization which would present the work more clearly. Please see the comments below.

We thank the reviewer for the positive appreciation of our work, qualified as a "thorough and rigorous body of work that convincingly illustrates the connection between PUFA levels and D2R activity". We will address the specific points raised by the reviewer with our answers below.

Comments:

1. • A recurring motivation for this study that is brought up by the authors is that dietary deficiency of ω3 fatty acids is tied to D2R dysfunction. This would indicate that PUFA reduction in the plasma membrane results in D2R dysfunction. However, the experiments emphasized in this manuscript investigate the condition where PUFA content is INCREASED in the plasma membrane and D2R function is compromised. It seems inappropriate for the authors to cite dietary deficiency of ω3 as a motivation when they experimentally test a condition that is tied to ω3 surplus.* Regarding the general comment of the reviewer, we agree that direct conclusion cannot be drawn on the etiology of psychiatric disorders by looking at the effect of membrane fatty acid levels on D2R in HEK 293 cells. Nevertheless, we mention in the Introduction the intriguing occurrence of low PUFA levels in psychiatric disorders as starting point to look at D2R as an important target for psychoactive drugs prescribed for these disorders. In the Discussion, we propose that manipulating fatty acid levels might potentiate the efficacy of D2R ligands used as treatments. We felt raising these aspects was not putting too much emphasis on psychiatric disorders. However, in accordance with the reviewer's comment, we toned down these descriptions in the revised manuscript.

The goal of increasing the levels of fatty acids at the membrane in HEK 293, the most widely used cellular system to study GPCR trafficking, was to try to emulate the levels of lipids in brain cells. Indeed, the levels of PUFAs in our culture conditions are much lower (~8 %, Figure 1B) than in brain extracts (~30 %). Therefore, the "control" condition in HEK 293 cells would correspond to PUFA deficiency while after our enrichment protocol these levels are closer to those found in brain cells. Our results could therefore be interpreted as endocytosis of D2R being augmented under membrane PUFA decrease. Importantly, increased receptor internalization often correlates with decreased signaling. Therefore, membrane PUFA enrichment in our conditions would rather potentiate D2R signaling.

• Following up on the first comment, the authors' results seem to indicate that excess ω3's are detrimental to D2R function. This result would be at odds with the conventional view that ω3's are essential and that excessive ω3 may not be harmful. The authors should rationalize their findings in the context of what is known about excess dietary ω3.*

The Reviewer is right that the conventional view is that excessive ω3 PUFA may not be harmful. However, this rather applies to dietary consumption, which might have limited effect to brain fatty acid contents since their accretion is highly regulated. Moreover, the majority of studies looking at ω3 supplementation have been performed in young adults and the effects on the developing brain - as it might be happening in pathological conditions in which D2R is involved - remain poorly understood. Furthermore, as mentioned above, blunted internalization of D2R under membrane PUFA enrichment is not an indication of "detrimental" to D2R function. Nor do we argue that membrane enrichment corresponds to excess PUFAs.

• I would argue that the control experiments with saturated fatty acids (i.e., Behenic Acid in figure 1), represent a scenario mimicking ω3 deficiency as the enrichment of Behenic Acid causes an overall reduction in PUFAs (Figure EV1C - an increase in SFA must correspond to a decrease in PUFA). These Behenic acid results are the only experiments presented by the authors that mimic a scenario resembling ω3 deficiency and the results show that the D2R internalization is unaffected (Figure 1G-H). Therefore, I would further argue that if anything, the authors results suggest that ω3 deficiency is NOT correlated to D2R internalization. Again, the authors must rationalize these findings in the context of what is known about dietary intake of ω3's.*

The Reviewer must refer to the fact that nutrients rich in SFAs are usually poor in PUFAs and vice-versa. Based on our lipidomic analysis, we now present in Figure 1B the effect of treatments (DHA, DPA, BA) on the levels of PUFAs (Figure 1B) and saturated fatty acids (Figure 1C). In cells treated with behenic acid (BA), PUFA levels are not significantly changed relative to control, untreated cells, while saturated fatty acid levels are increased. BA was used here to determine whether the effects observed with PUFAs was related to the enrichment in unsaturations or due to carbon chain length (C22). It is not the case because BA treatment, unlike DHA or DPA treatment, does not affect D2R endocytosis (Figure 2G,H).

• It's not clear why the authors decided to include an ω6 fatty acid in this study. The authors built up a detailed rationale for investigating ω3's as they are dietarily essential and tied to disease when deficient. To my knowledge, ω6's are considered much less beneficial than ω3's in a dietary sense. The inclusion of an ω6 almost seems coerced as the ω6-related results don't provide any interesting additional insights. It would benefit the manuscript if the authors provided some additional discussion explaining why ω6's are being investigated in addition to ω3's. *

We agree that we could have made the rationale clearer. The goal in comparing ω3-DHA and ω6-DPA was to assess whether the position of the first unsaturation (n-3 vs n-6), with the same carbon chain length (C22) might differentially impact D2R endocytosis.

• In Figure EV1D, the AHA and DPA percentages each increase by ~6%. The corresponding Figure EV1B indicates that the overall PUFA% in the plasma membrane also increases by 6%. This makes sense as the total change in PUFA content is consistent with the amount of AHA or DPA being internalized to cells. However, this consistency was not observed with BA and SFAs. In Figure EV1E, the BA percentage increases only ~1% while the total SFA percentage in Figure EV1C increases by ~6%. How can something undergoing a 1% change (relative to total lipid content) result in a 6% overall change in SFA content?*

The reviewer is correct: the level of SFAs is increased by 5.2% (34.5 % of total FAs in control cells to 39.7 % in BA treated cells), more than the increase in BA alone (1.18% from 0.35 % to 1.53 %). A close look at our lipidomics data showed that many of the 10 saturated fatty acids quantified are enhanced. In particular, the two most abundant ones, palmitic acid (16:0) and stearic acid (18:0) are increased, from 21.37 % to 22.28 % and 8.47 % to 11.17%, respectively. The reasons for these apparent discrepancies may involve lipid metabolic pathways which convert the rare and long BA into more common and shorter SFAs to preserve lipid contents and thus membrane properties.

• In Figure 4, the discussion of kinetics does not make sense. How exactly are kinetics being monitored in this figure? (Recruitment kinetics are discussed in panels D and G)*

We wanted to convey the impression that the time to reach the peak βarr2-mCherry recruitment was shorter in PUFA-treated cells than in control cells. However, after analyzing the kinetics in individual cells, we did not find a statistically significant difference in the time to maximum fluorescence. Therefore, we removed this reference to the kinetics of recruitment.

We now write: " However, treatment with DHA or DPA significantly decreased peak βarr2-mCherry fluorescence (Figure 5F-G).."

• In Figure 5, What is the purpose of panel D? Would it be more helpful to include additional, overlaid "cumulative N" plots for scenarios in which PUFAs were enriched? This would work well in conjunction with panel F.*

The purpose of this panel is to show the kinetics of increase in the frequency of endocytic vesicle formation upon agonist addition, and the decrease in frequency when the agonist is removed. We have now added examples of cells treated with DHA and DPA of similar surface for direct comparison with control (EtOH) cells.

• For the readers who are new to this area or unfamiliar with the assays used, Figure 1 is not intuitive and initially difficult to interpret. It would greatly benefit the flow of the manuscript if Figures EV1A-C and EV2A were included in the main text and "Normalized R" was clearly defined in the main text, prior to discussion of Figure 1.*

We have now transferred Figure EV1 as Figure 1. We have adapted the scheme of the DERET assay and its legend (now in Figure EV1A) to make it clearer. We did not put in Figure 2 because this figure is already very big. We have changed "Normalized R" to "Ratio 620/520) (% max)" to be clearer and more consistent with the scheme.

Reviewer #3 (Significance (Required)):

• *

General assessment: The work, for the most part, is rigorous and scientifically sound. The authors utilize impressive, quantitative assays to expand our understanding of protein-lipid interactions. However, the authors need to improve their discussion of the actual physiological conditions that correspond to their experimental results.

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Advance: This work may fill a gap in our understanding of disorders related to the dopamine D2 receptor. However, some of the results may be at odds with what is currently known/understood about dietary ω3 fatty acids.

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Audience: This work will be of broad interest to researchers in the biophysics field, with particular emphasis on researchers who study protein and membrane biophysics. This work will also be of interest to researchers who study membrane molecular biology.

• *

Reviewer Expertise: quantitative fluorescence spectroscopy and microscopy; membrane biophysics; protein-lipid interactions

• *

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #1

Evidence, reproducibility and clarity

The manuscript, using different live and fixed cell trafficking assays, demonstrates that incorporation of poly-unsaturated, but not saturated, free fatty acids in the membrane phospholipids reduce agonist induced internalization of the D2 dopamine receptor but not the adrenergic beta2 receptors or the transferrin receptor. Pulsed pH (ppH) live microscopy further demonstrated that the reduced internalization by incorporation of free fatty acid was accompanied by a blunted recruitment of Beta-arrestin for the D2R.

I believe said claims put forward in the manuscript are overall well supported by the data and as such I do not believe that further experiments are necessarily needed to uphold these key claims. Also, the methodology is satisfactorily reported, and statistics are robust, although two-way Anova like used in Fig 1 seems appropriate for Fig 2 and 3

That said, I suggest that the fixed cell internalization experiments (Fig 2 and 3), which relate the effect on the D2R to B2AR and transferrin are revised. This is important since this is relevant to judge whether the effect is a general or a selective molecular mechanism since this is the one of the three assay which this comparison relies on. Alternatively, I suggest omitting this data and include the B2AR in the Live DERET assay and both B2AR and TfR in the ppH assay. Specifically, my concerns with the fixed cell internalization are:

• The analysis is based on counting the number of endosomes, which is not necessarily equivalent to the number of receptors internalized
• The analysis relies on fully effective stripping of the surface pool of receptors - i.e clustered surface receptors not stripped by the protocol will be assessed as internalized. It is often very difficult to obtain full efficiency of the Flag-tag stripping and this is somewhat expression dependent.
• The protocol for the constitutive and agonist induced internalization is different and yet shown on the same absolute graph. Although I take it the microscope gain setting are unaltered between the constitutive and agonist induced internalization I don't believe the quantification can be directly related. This is confusing at the very least. More critically however, the membrane signal from the non-stripped condition of constitutive internalization will likely fully shield internalized receptors in the Rab4 membrane proximal recycling pathway leading to under-estimation of the in the constitutive endocytosis. I believe this methodological limitation underlies the massive relative difference in the constitutive endocytosis between panel 2A,B and 2C,D. For comparison, by a quantitative dual color FACS endocytosis assay, we have previously demonstrated the ligand endocytosis a ~4 fold increased over constitutive (in concert with Fig 2A,B here) (Schmidt et al 20XX). Importantly, high relative variability by this methodology could well shield an actual effect of incorporation of FFAs on the constitutive endocytosis.

'Optional' Also, it would be informative to see the ppH Beta-arrestin experiments with the B2AR to assess, whether the putative discrepancy between D2R and B2AR is upstream or downstream of the blunted Beta-arrestin recruitment. To the same point, it would be very informative to assess how the incorporation of the free fatty acids affect receptor signalling, which would also help relate the effect of incorporation of the FFA's in the phospholipids to previous experiment using short term incubation with FFA's

References overall seem appropriate although Schmidt et al would be relevant for reference of the constitutive vs agonist induced endocytosis of D2R and B2AR. Overall, the figures are well composed and convey the messages fairly well. Specific point that would strengthen the rigor include:

• Chosing actual representative pictures of the qunatiative data in Fig 2 and 3 (e.g. har to see 25 endocytic events in Fig 2A constitutive endo, EtOH)
• Showing actual p values for the statistical comparisions

Moreover, for ease of reading the figures (without consulting the legend repeatedly) it would be very helpful to headline individual panel with what the experiments assesses. Figure 1a and 1b for example can't be distinguished at all before reading the figure legend. Also, y-axis could be more informative on what I measured rather than just giving the unit.

Finally, the figure presentation and description of S1 is very hard to follow. I cannot really make out what is assessed in the different panels.

Significance

The strength of the manuscript is the use and validation of incorporation of FFA's in the plasma membrane, which more closely mimics the physiological situation than brief application of FFAs as often done. Is addition, the blunted recruitment of beta-arrestin as assessed by the ppH protocol is quite intriguing mechanistically. The limitation are the relative narrow focus on the D2 receptor (and not multiple GPCRs) that does not really speak to as or assess the physiological, pathophysiological or therapeutic role of the observations (except from referring the relation between FFAs and disease). Also, despite the putative role of Beta-arrestin recruitment in the process, the actual causation in the process is not clear. This shortcoming is underscored by the putative effect on the constitutive internalization described above.

My specific expertise for assessing the paper is within general trafficking processes (including the trafficking methodology applied), trafficking of GPCRs and function of the dopamine system including the role of D2 receptors.

Sounds cool

This is cool as well as sick!

Reviewer #1 (Public Review):

Summary:

This paper reports the finding that less fat accumulates in C. elegans that are feeding on Comamonas aquatica DA1877 (DA) vs the standard lab diet of Escherichia coli OP50 (OP50). While these bacteria are likely to be different in many ways, the authors found that fat accumulation phenotype depends on the vitamin B12 content of the bacterial diet and the involvement of B12 in the methionine cycle, affecting SAMS-1 and phosphatidylcholine (PC) synthesis. They report that low PC levels activate SREBP-1 (SBP-1 in C. elegans) and that an important target of SBP-1 is the delta 9 desaturase FAT-7. Finally, they describe a role for ASM-3, an acid sphingomyelinase, in influencing PC synthesis and fat accumulation in the worm.

Strengths:

This is a comprehensive story about how a dietary change affects fat accumulation in C. elegans. Their experimental evidence is convincing. The most novel aspect of this paper is that the coelomecyte expression of asm-3 contributes to PC/TAG homeostasis in C. elegans, which most likely occurs through the production of phosphocholine by the enzymatic breakdown of sphingomyelin by ASM-3. The phosphocholine will provide precursors for phosphatidylcholine (PC) synthesis, contributing to the PC synthesis pathway.

Weaknesses:

In the way the story is presented, the authors tend to imply that they discovered the pathways of B12, PC, SBP-1, and FAT-7, ignoring some important studies describing the relationship between PC synthesis and TAG accumulation in both the mammalian lipid metabolism field (liver) as well as in C. elegans. Many previous studies with similar results are not cited appropriately. Thus, the pathways reported in the paper are not new, and in this sense, the work is mostly confirmatory.

Reviewer #3 (Public Review):

Summary:

The authors presented data that linked vitamin B12, S-adenosyl methionine (SAM), and phosphatidylcholine (PC) synthesis to lipid homeostasis in C. elegans. They confirmed mechanisms previously shown by other labs, including the regulation of FAT-7 expression by SBP-1, and the targeting of SEIP-1 by PC levels. The authors also attempted to link the synthesis of phospho-choline by the ASM-3 sphingomyelinase to PC synthesis and lipid homeostasis. However, the relative contribution of phospho-choline by ASM-3 versus the canonical Kennedy pathway was not elucidated. Therefore, the significance of the ASM-3-dependent mechanism to PC synthesis requires further investigation.

Strengths:

The authors used a wide range of biochemical and cell biological methods to measure fatty acid composition, neutral lipid levels, and lipid droplet dynamics in C. elegans. The quality of the data is generally high.

Weaknesses:

Data interpretation and the construction of the working model did not seem to take into account the two well-established pathways for PC synthesis. The Kennedy pathway generates PC from phospho-choline and DAG via a cytidine-based intermediate. The second PC synthesis pathway entails the methylation of PE by PEMT, with the donor methyl groups provided by the vitamin B12-dependent 1-carbon cycle. The authors' model seemed to overlook part of the Kennedy pathway that involves choline kinase (and not ASM-3) as the canonical enzyme that generates phospho-choline. The authors also did not explicitly consider DAG as a precursor of triacylglycerol (TAG), which was directly or indirectly measured as a readout of organismal fat content in the paper. Therefore, alternative models should be entertained. For example, the proposed genetic and dietary effects on lipid homeostasis could stem from the competition for a limiting pool of precursors that were shared by PC and TAG synthesis. PC itself may not have a deterministic role, as depicted by the authors' model. Finally, the claim that "coelomocytes regulate diets-induced lipid homeostasis through asm-3" was not well supported. In the absence of quantitative analysis of phospho-choline in mutants, it was unclear how much ASM-3 contributed to the overall phospho-choline, and ultimately PC level. The proposed inter-tissue regulation of PC synthesis also requires coelomocytes-specific knock-down/depletion of asm-3 for verification.

Reviewer #3 (Public Review):

Summary:

The work by Kalita et al. reports regulation of RecB expression by Hfq protein in E.coli cell. RecBCD is an essential complex for DNA repair and chromosome maintenance. The expression level needs to be regulated at low level under regular growth conditions but upregulated upon DNA damage. Through quantitative imaging, the authors demonstrate that recB mRNAs and proteins are expressed at low level under regular conditions. While the mRNA copy number demonstrates high noise level due to stochastic gene expression, the protein level is maintained at a lower noise level compared to expected value. Upon DNA damage, the authors claim that the recB mRNA concentration is decreased, however RecB protein level is compensated by higher translation efficiency. Through analyzing CLASH data on Hfq, they identified two Hfq binding sites on RecB polycistronic mRNA, one of which is localized at the ribosome binding site (RBS). Through measuring RecB mRNA and protein level in the ∆hfq cell, the authors conclude that binding of Hfq to the RBS region of recB mRNA suppresses translation of recB mRNA. This conclusion is further supported by the same measurement in the presence of Hfq sequestrator, the sRNA ChiX, and the deletion of the Hfq binding region on the mRNA.

Strengths:

(1) The manuscript is well-written and easy to understand.<br /> (2) While there are reported cases of Hfq regulating translation of bound mRNAs, its effect on reducing translation noise is relatively new.<br /> (3) The imaging and analysis are carefully performed with necessary controls.

Weaknesses:

The major weaknesses include a lack of mechanistic depth, and part of the conclusions are not fully supported by the data.

(1) Mechanistically, it is still unclear why upon DNA damage, translation level of recB mRNA increases, which makes the story less complete. The authors mention in the Discussion that a moderate (30%) decrease in Hfq protein was observed in previous study, which may explain the loss of translation repression on recB. However, given that this mRNA exists in very low copy number (a few per cell) and that Hfq copy number is on the order of a few hundred to a few thousand, it's unclear how 30% decrease in the protein level should resides a significant change in its regulation of recB mRNA.<br /> (2) Based on the experiment and the model, Hfq regulates translation of recB gene through binding to the RBS of the upstream ptrA gene through translation coupling. In this case, one would expect that the behavior of ptrA gene expression and its response to Hfq regulation would be quite similar to recB. Performing the same measurement on ptrA gene expression in the presence and absence of Hfq would strengthen the conclusion and model.<br /> (3) The authors agree that they cannot exclude the possibility of sRNA being involved in the translation regulation. However, this can be tested by performing the imaging experiments in the presence of Hfq proximal face mutations, which largely disrupt binding of sRNAs.<br /> (4) The data on construct with a long region of Hfq binding site on recB mRNA deleted is less convincing. There is no control to show that removing this sequence region itself has no effect on translation, and the effect is solely due to the lack of Hfq binding. A better experiment would be using a Hfq distal face mutant that is deficient in binding to the ARN motifs.<br /> (5) Ln 249-251: The authors claim that the stability of recB mRNA is not changed in ∆hfq simply based on the steady-state mRNA level. To claim so, the lifetime needs to be measured in the absence of Hfq.<br /> (6) What's the labeling efficiency of Halo-tag? If not 100% labeled, is it considered in the protein number quantification? Is the protein copy number quantification through imaging calibrated by an independent method? Does Halo tag affect the protein translation or degradation?<br /> (7) Upper panel of Fig S8a is redundant as in Fig 5B. Seems that Fig S8d is not described in the text.

Author response:

Reviewer #1 (Public Review):

Summary:

In this study the authors use an elegant set of single-molecule experiments to assess the transcriptional and post-transcriptional regulation of RecB. The question stems from a previous observation from the same lab, that RecB protein levels are low and not induced under DNA damage. The authors first show that recB transcript levels are low and have a short half-life. They further show that RecB levels are likely regulated via translational control. They provide evidence for low noise in RecB protein levels across cells and show that the translation of the mRNA increases under double-strand break conditions. Authors identify Hfq binding sites in the recbcd [recBCD] operon and show that Hfq regulates the levels of RecB protein without changing the mRNA levels. They suggest that RecB translation is directly controlled by Hfq binding to mRNA, as mutating one of the binding sites has a direct effect on RecB protein levels.

Strengths:

The implication of Hfq in regulation of RecB translation is important and suggests mechanisms of cellular response to DNA damage that are beyond the canonically studied mechanisms (such as transcriptional regulation by LexA). Data are clearly presented and the writing is direct and easy to follow. Overall, the study is well-designed and provides novel insights into the regulation of RecB, that is part of the complex required to process break ends.

Weaknesses:

Some key findings need additional support/ clarifications to strengthen the conclusions. These are suggested to the authors.

Reviewer #2 (Public Review):

Summary:

The authors carry out a careful and rigorous quantitative analysis of RecB transcript and protein levels at baseline and in response to DNA damage. Using single-molecule FISH and Halo-tagging in order to achieve sensitive measurements, they provide evidence that enhanced RecB protein levels in response to DNA damage are achieved through a post-transcriptional mechanism mediated by the La-like RNA binding protein, Hhq1 [Sm-like RNA binding protein, Hfq]. In terms of biological relevance, the authors suggest that this mechanism provides a way to control the optimum level of RecB expression as both deletion and over-expression are deleterious. In addition, the proposed mechanism provides a new framework for understanding how transcriptional noise can be suppressed at the protein level.

Strengths:

Strengths of the manuscript include the rigorous approaches and orthogonal evidence to support the core conclusions, for example, the evidence that altering either Hhq1 [Hfq] or its recognition sequence on the RNA similarly enhance the protein to RNA ratio of RecB. The writing is clear and the experiments are well-controlled. The modeling approaches provide essential context to interpret the data, particularly given the small numbers of molecules per cell. The interpretations are careful and well supported.

Weaknesses:

The authors make a compelling case for the biological need to exquisitely control RecB levels, which they suggest is achieved by the pathway they have uncovered and described in this work. However, this conclusion is largely inferred as the authors only investigate the effect on cell survival in response to (high levels of) DNA damage and in response to two perturbations - genetic knock-out or over-expression, both of which are likely more dramatic than the range of expression levels observed in unstimulated and DNA damage conditions.

In the discussion, we proposed that the post-transcriptional regulation of recB that we have uncovered could be involved in keeping RecB levels within an optimal range. We agree that testing the phenotypic impact of small changes in RecB levels would add additional strength to this suggestion. However, this is experimentally very challenging because of the low copy number of RecB molecules, which makes it difficult to slightly alter RecB levels in a controlled and homogeneous (across cells) manner. Developing the synthetic biology tools necessary for such an experiment is beyond the scope of this article. In the manuscript, we will clarify the limits of our interpretation of the role of the uncovered regulation.

Reviewer #3 (Public Review):

Summary:

The work by Kalita et al. reports regulation of RecB expression by Hfq protein in E.coli cell. RecBCD is an essential complex for DNA repair and chromosome maintenance. The expression level needs to be regulated at low level under regular growth conditions but upregulated upon DNA damage. Through quantitative imaging, the authors demonstrate that recB mRNAs and proteins are expressed at low level under regular conditions. While the mRNA copy number demonstrates high noise level due to stochastic gene expression, the protein level is maintained at a lower noise level compared to expected value. Upon DNA damage, the authors claim that the recB mRNA level is not significantly affected, but RecB protein level increases due to a higher translation efficiency. [Upon DNA damage, the authors claim that the recB mRNA concentration is decreased, however RecB protein level is compensated by higher translation efficiency]. Through analyzing CLASH data on Hfq, they identified two Hfq binding sites on RecB polycistronic mRNA, one of which is localized at the ribosome binding site (RBS). Through measuring RecB mRNA and protein level in the ∆hfq cell, the authors conclude that binding of Hfq to the RBS region of recB mRNA suppresses translation of recB mRNA. This conclusion is further supported by the same measurement in the presence of Hfq sequestrator, the sRNA ChiX, and the deletion of the Hfq binding region on the mRNA.

Strengths:

(1) The manuscript is well-written and easy to understand.

(2) While there are reported cases of Hfq regulating translation of bound mRNAs, its effect on reducing translation noise is relatively new.

(3) The imaging and analysis are carefully performed with necessary controls.

Weaknesses:

The major weaknesses include a lack of mechanistic depth, and part of the conclusions are not fully supported by the data.

(1) Mechanistically, it is still unclear why upon DNA damage, translation level of recB mRNA increases, which makes the story less complete. The authors mention in the Discussion that a moderate (30%) decrease in Hfq protein was observed in previous study, which may explain the loss of translation repression on recB. However, given that this mRNA exists in very low copy number (a few per cell) and that Hfq copy number is on the order of a few hundred to a few thousand, it's unclear how 30% decrease in the protein level should resides a significant change in its regulation of recB mRNA.

While Hfq is a highly abundant protein, it has many mRNA and sRNA targets, some of which are also present in large amounts (DOI: 10.1046/j.1365-2958.2003.03734.x). As recently shown, the competition among the targets over Hfq proteins results in unequal (across various targets) outcomes, where the targets with higher Hfq affinity have an advantage over the ones with less efficient binding (DOI: 10.1016/j.celrep.2020.02.016). In line with these findings, we reason that upon DNA damage, a moderate decrease in the Hfq protein abundance (30%) can lead to a similar competition among Hfq targets where high-affinity targets outcompete low- affinity ones as well as low-abundant ones (such as recB mRNAs). Therefore, we hypothesise that the regulation of low abundant targets of Hfq by moderate perturbations of Hfq protein level is a potential explanation for the change in RecB translation that we have observed. We will expand this part of the discussion to explain our reasoning in a more explicit and coherent way.

(2) Based on the experiment and the model, Hfq regulates translation of recB gene through binding to the RBS of the upstream ptrA gene through translation coupling. In this case, one would expect that the behavior of ptrA gene expression and its response to Hfq regulation would be quite similar to recB. Performing the same measurement on ptrA gene expression in the presence and absence of Hfq would strengthen the conclusion and model

Indeed, based on our model, we expect PtrA expression to be regulated by Hfq in a similar manner to RecB. However, the product encoded by the ptrA gene, Protease III, (i) has been poorly characterised; (ii) unlike RecB, is located in the periplasm (DOI: 10.1128/jb.149.3.1027-1033.1982); and (iii) is not involved in any DNA repair pathway. Therefore, analysing PtrA expression would take us away from the key questions of our study.

(3) The authors agree that they cannot exclude the possibility of sRNA being involved in the translation regulation. However, this can be tested by performing the imaging experiments in the presence of Hfq proximal face mutations, which largely disrupt binding of sRNAs.

(4) The data on construct with a long region of Hfq binding site on recB mRNA deleted is less convincing. There is no control to show that removing this sequence region itself has no effect on translation, and the effect is solely due to the lack of Hfq binding. A better experiment would be using a Hfq distal face mutant that is deficient in binding to the ARN motifs.

We thank the referee for these suggestions. We have performed the requested experiments, and the quantification of RecB abundance in the presence of Hfq proteins mutated in the proximal and distal face will be added to the revised version of the manuscript.

(5) Ln 249-251: The authors claim that the stability of recB mRNA is not changed in ∆hfq simply based on the steady-state mRNA level. To claim so, the lifetime needs to be measured in the absence of Hfq.

We agree that this statement is not fully supported by our data and will address this issue in the revised version.

(6) What's the labeling efficiency of Halo-tag? If not 100% labeled, is it considered in the protein number quantification? Is the protein copy number quantification through imaging calibrated by an independent method? Does Halo tag affect the protein translation or degradation?

Our previous study (DOI: 10.1038/s41598-019-44278-0) described a detailed characterisation of the HaloTag labelling technique for quantifying low-copy proteins in single E. coli cells.

In that study, we used RecB-HaloTag as an example of a low-copy number protein. We showed a complete quantitative agreement of RecB detection between two fully independent methods: HaloTag-based labelling with cell fixation and RecB-sfGFP combined with a microfluidic device that lowers protein diffusion in the bacterial cytoplasm. This second method has previously been validated for protein quantification (DOI: 10.1038/ncomms11641) and provides detection of 80-90% of the labelled protein. Additionally, in our protocol, immediate chemical fixation of cells after the labelling and quick washing steps ensure that new, unlabelled RecB proteins are not produced. We, therefore, conclude that our approach to RecB detection is highly reliable and sufficient for comparing RecB production in different conditions and mutants.

The RecB-HaloTag construct has been designed for minimal impact on RecB production and function. The HaloTag is translationally fused to RecB in a loop positioned after the serine present at position 47 where it is unlikely to interfere with (i) the formation of RecBCD complex (based on RecBCD structure, DOI: 10.1038/nature02988), (ii) the initiation of translation (as it is far away from the 5’UTR and the beginning of the open reading frame) and (iii) conventional C-terminal-associated mechanisms of protein degradation (DOI: 10.15252/msb.20199208). In our manuscript, we showed that the RecB-HaloTag degradation rate is similar to the dilution rate due to bacterial growth. This is in line with a recent study on unlabelled proteins, which shows that RecB’s lifetime is set by the cellular growth rate (https://doi.org/10.1101/2022.08.01.502339) and indicates that the HaloTag fusion is not affecting RecB stability.

Furthermore, we have demonstrated (DOI: 10.1038/s41598-019-44278-0) that (i) bacterial growth is not affected by replacing the native RecB with RecB-HaloTag, (ii) RecB-HaloTag is fully functional upon DNA damage, and (iii) no proteolytic processing of the RecB-HaloTag is detected by Western blot.

These results suggest that RecB expression and functionality are unlikely to be affected by the translational HaloTag insertion at Ser-47 in RecB. In the revised version of the manuscript, we will add information about the construct and discuss the reliability of the quantification.

(7) Upper panel of Fig S8a is redundant as in Fig 5B. Seems that Fig S8d is not described in the text.

Indeed, the data in the upper panel in Fig S8a was repeated (from Fig 5B) for visual purposes to facilitate comparison with the panel below. We will modify the figure legend to indicate this repetition clearly.

In Fig S8d, we confirmed the functionality of the Hfq protein expressed from the pQE-Hfq plasmid in our experimental conditions, which was not described in the text. We will include this clarification in the updated manuscript.

In Südwestfrankreich wurden Anfan Oktober mit über 35° die höchsten Oktobertemperaturen der Messgeschichte festgestellt. An einem Tag wurden in 350 Städten Temperaturrekorde gebrochen. Vorangegangen waren Rekordtemperaturen im September. https://www.liberation.fr/environnement/climat/355-degres-dans-le-tarn-le-record-de-chaleur-pour-un-mois-doctobre-deja-battu-20231002_NJ6VFMGT4VDB5NL3JOISU7SDCY/?redirected=1

Der italienische Konzern Eni beginnt mit der Öl- und Gasforderung vor der Elfenbeinküste. Bei der Behauptung, es handele sich um das erste emissionsfreie Förderprojekt, werden die Emissionen durch Verbrennung der Produkte nicht berücksichtigt. Geplant ist eine Steigerung der Produktion bis auf täglich 150.000 Barrel Öl und ca. 5,6 Millionen Kubikmeter Gas. Das Erdgas wird über eine Pipeline an die Elfenbeinküste geliefert.

Zu Eni: https://hypothes.is/search?q=tag%3A%22actor%3A%20Eni%22

https://www.repubblica.it/economia/finanza/2023/08/28/news/eni_avvia_la_produzione_in_costa_davorio_descalzi_pietra_miliare-412524518/

20 reiche Länder planen bis 2050 neue Öl- und Gas-Projekte, die zusammen weitere 173 Gigatonnen CO₂-Emissionen verursachen werden, wenn es nicht gelingt sie zu stoppen. Oil Change International hat einen Bericht über den Anteil der verschiedenen Staaten an den Expansionsplänen veröffentlicht. Mit einem Drittel entfällt der Hauptanteil auf die USA.

https://www.theguardian.com/environment/2023/sep/12/us-behind-more-than-a-third-of-global-oil-and-gas-expansion-plans-report-finds

Mehr zur fossilen Expansion: https://hypothes.is/search?q=tag%3A%22process%3A%20fossil%20development%22

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In their manuscript, Yu et al. describe the chemotactic gradient formation for CCL5 bound to - i.e. released from - glycosaminoglycans. The authors provide evidence for phase separation as the driving mechanism behind chemotactic gradient formation. A conclusion towards a general principle behind the finding cannot be drawn since the work focuses on one chemokine only, which is particularly prone to glycan-induced oligomerisation.

Strengths:

The principle of phase separation as a driving force behind and thus as an analytical tool for investigating protein interactions with strongly charged biomolecules was originally introduced for protein-nucleic acid interactions. Yu et al. have applied this in their work for the first time for chemokine-heparan sulfate interactions. This opens a novel way to investigate chemokine-glycosaminoglycan interactions in general.

Response: Thanks for the encouragement of the reviewer.

Weaknesses:

As mentioned above, one of the weaknesses of the current work is the exemplification of the phase separation principle by applying it only to CCL5-heparan sulfate interactions. CCL5 is known to form higher oligomers/aggregates in the presence of glycosaminoglycans, much more than other chemokines. It would therefore have been very interesting to see, if similar results in vitro, in situ, and in vivo could have been obtained by other chemokines of the same class (e.g. CCL2) or another class (like CXCL8).

Response: We share the reviewer’s opinion that to investigate more molecules/cytokines that interact with heparan sulfate in the system should be of interesting. We expect that researchers in the field will adapt the concept to continue the studies on additional molecules. Nevertheless, our earlier study has demonstrated that bFGF was enriched to its receptor and triggered signaling transduction through phase separation with heparan sulfate (PMID: 35236856; doi: 10.1038/s41467-022-28765-z), which supports the concept that phase separation with heparan sulfate on the cell surface may be a common mechanism for heparan sulfate binding proteins. The comment of the reviewer that phase separation is related to oligomerization is demonstrated in (Figure 1—figure supplement 2C and D), showing that the more easily aggregated mutant, A22K-CCL5, does not undergo phase separation.

In addition, the authors have used variously labelled CCL5 (like with the organic dye Cy3 or with EGFP) for various reasons (detection and immobilisation). In the view of this reviewer, it would have been necessary to show that all the labelled chemokines yield identical/similar molecular characteristics as the unlabelled wildtype chemokine (such as heparan sulfate binding and chemotaxis). It is well known that labelling proteins either by chemical tags or by fusion to GFPs can lead to manifestly different molecular and functional characteristics.

Response: We agree with the reviewer that labeling may lead to altered property of a protein, thus, we have compared chemotactic activity of CCL5 and CCL5-EGFP (Figure 2—figure supplement 1). To further verify this, we performed additional experiment to compare chemotactic activity between CCL5 and Cy3-CCL5 (see Author response image 1). For the convenience of readers, we have combined the original Figure 2—figure supplement 1 with the new data (Figure R1), which replaced original Figure 2—figure supplement 1.

Author response image 1.

Chemotactic function of CCL5-EGFP and CCL5-Cy3. Cy3-Labeled CCL5 has similar activity as CCL5, 50 nM CCL5 or CCL5-Cy3 were added to the lower chamber of the Transwell. THP-1 cells were added to upper chambers. Data are mean ± s.d. n=3. P values were determined by unpaired two-tailed t-tests. NS, Not Significant.

Reviewer #2 (Public Review):

Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.

(1) The conclusions of the paper are mostly supported by the data although some clarification is warranted concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3, and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. Since lysines are important for the GAG-binding properties of CCL5, knowledge of the number and location of the Cy-3 labels on CCL5 is important information for the interpretation of the experimental results with the fluorescently labeled CCL5. Was the His-tag attached to the N- or C-terminus of CCL5? Indicate this for each individual experiment and consider/discuss also potential effects of the modifications on CCL5 in the results and discussion sections.

Response: We agree with the reviewer that labeling may lead to altered property of a protein, thus, we have compared chemotactic activity of CCL5 and CCL5-EGFP (Figure 2—figure supplement 1). To further verify this, we performed additional experiment to compare chemotactic activity between CCL5 and Cy3-CCL5 (see Author response image 1). For the convenience of readers, we have combined the original Figure 2—figure supplement 1 with the new data (Author response image 1), which replaced original Figure 2—figure supplement 1.

The His-tag is attached to the C-terminus of CCL5, in consideration of the potential impact on the N-terminus.

(2) In general, the authors appear to use high concentrations of CCL5 in their experiments. The reason for this is not clear. Is it because of the effects of the labels on the activity of the protein? In most biological tests (e.g. chemotaxis assays), unmodified CCL5 is active already at low nM concentrations.

Response: We agree with the reviewer that the CCL5 concentrations used in our experiments were higher than reported chemotaxis assays and also higher than physiological levels in normal human plasma. In fact, we have performed experiments with lower concentration of CCL5, where the effect of LLPS was not seen though the chemotactic activity of the cytokine was detected. Thus, LLPS-associated chemotactic activity may represent a scenario of acute inflammatory condition when the inflammatory cytokines can increase significantly.

(3) For the statistical analyses of the results, the authors use t-tests. Was it confirmed that data follow a normal distribution prior to using the t-test? If not a non-parametric test should be used and it may affect the conclusions of some experiments.

Response: We thank the reviewer for pointing out this issue. As shown in Author response table 1, The Shapiro-Wilk normality test showed that only two control groups (CCL5 and 44AANA47-CCL5+CHO K1) in Figure 3 did not conform to the normal distribution. The error was caused by using microculture to count and calculate when there were very few cells in the microculture. For these two groups, we re-counted 100 μL culture medium to calculate the number of cells. The results were consistent with the positive distribution and significantly different from the experimental group (Author response image 3). The original data for the number of cells chemoattractant by 500 nM CCL5 was revised from 0, 247, 247 to 247, 123, 370 and 500 nM 44AANA47 +CHO-K1 was revised from 1111, 1111, 98 to 740, 494, 617. The revised data does not affect the conclusion.

Author response table 1.

Table R1 Shapiro-Wilk test results of statistical data in the manuscript

Author response image 3.

Quantification of THP-1collected from the lower chamber. Data are mean ± s.d. n=3. P values were determined by unpaired two-tailed t-tests.

Recommendations for the authors:

Reviewer #1:

See the weaknesses section of the Public Review. In addition, the authors should discuss the X-ray structure of CCL5 in complex with a heparin disaccharide in comparison with their docked structure of CCL5 and a heparin tetrasaccharide.

Response: Our study, in fact, is strongly influenced by the report (Shaw, Johnson et al., 2004) that heparin disaccharide interaction with CCL5, which is highlighted in the text (page5, line100-102).

Reviewer #2:

(1) Clearly indicate in the results section and figure legends (also for the supplementary figures) which form and concentration of CCL5 is used.

Response: The relevant missing information is indicated across the manuscript.

(2) Clearly indicate which GAG was used. Was it heparin or heparan sulfate and what was the length (e.g. average molecular mass if known) or source (company?)?

Response: Relevant information is added in the section “Materials and Methods.

(3) Line 181: What do you mean exactly with "tiny amounts"?

Response: “tiny amounts” means 400 transfected cells. This is described in the section of Materials and Methods. It is now also indicated in the text and legend to the figure.

(4) Lines 216-217: This is a very general statement without a link to the presented data. No combination of chemokines is used, in vivo testing is limited (and I agree very difficult). You may consider deleting this sentence (certainly as an opening sentence for the Discussion).

Response: We appreciate very much for the thoughtful suggestion of the reviewer. This sentence is deleted in the revised manuscript.

(5) Why was 5h used for the in vitro chemotaxis assay? This is extremely long for an assay with THP-1 cells.

Response: We apologize for the unclear description. The 5 hr includes 1 hr pre- incubation of CCL5 with the cells enable to form phase separation. After transferring the cells into the upper chamber, the actual chemotactic assay was 4 hr. This is clarified in the Materials and Methods section and the legend to each figure.

(6) Define "Sec" in Sec-CCL5-EGFP and "Dil" in the legend of Figure 4.

Response: The Sec-CCL5-EGFP should be “CCL5-EGFP’’, which has now been corrected. Dil is a cell membrane red fluorescent probe, which is now defined.

(7) Why are different cell concentrations used in the experiment described in Figure 5?

Response: The samples were from three volunteers who exhibited substantially different concentrations of cells in the blood. The experiment was designed using same amount of blood, so we did not normalize the number of the cell used for the experiment. Regardless of the difference in cell numbers, all three samples showed the same trend.

(8) Check the text for some typos: examples are on line 83 "ratio of CCL5"; line 142 "established cell lines"; line 196 "peripheral blood mononuclear cells"; line 224 "to mediate"; line 226 "bind"; line 247 "to form a gradient"; line 248 "of the glycocalyx"; line 343 and 346 "tetrasaccharide"; line 409-410 "wild-type"; line 543 "on the surface of CHO-K1 and CHO-677"; line 568 "white".

Response: Thanks for the careful reading. The typo errors are corrected and Manuscript was carefully read by colleagues.

Reviewer #2 (Public Review):

Although the study by Xiaolin Yu et al is largely limited to in vitro data, the results of this study convincingly improve our current understanding of leukocyte migration.

(1) The conclusions of the paper are mostly supported by the data and in the revised manuscript clarification is provided concerning the exact CCL5 forms (without or with a fluorescent label or His-tag) and amounts/concentrations that were used in the individual experiments. This is important since it is known that modification of CCL5 at the N-terminus affects the interactions of CCL5 with the GPCRs CCR1, CCR3 and CCR5 and random labeling using monosuccinimidyl esters (as done by the authors with Cy-3) is targeting lysines. The revised manuscript more clearly indicates for each individual experiment which form is used. However, a discussion on the potential effects of the modifications on CCL5 in the results and discussion sections is still missing.<br /> (2) In general, authors used high concentrations of CCL5 in their experiments. In their reply to the comments they indicate that at lower CCL5 concentrations no LLPS is detected. This is important information since it may indicate the need for chemokine oligomerization for LLPS. This info should be added to the manuscript and comparison with for instance the obligate monomer CCL7 and another chemokine such as CXCL4 that easily forms oligomers may clarify whether LLPS is controlled by oligomerization.<br /> (3) Statistical analyses have been improved in the revised manuscript.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

We would like to thank the three reviewers for their time and effort, the constructive criticism, and suggestions to improve the quality of the manuscript. Below, we address the points raised by providing further clarifications or revising the manuscript as indicated.

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

This study investigates mitochondrial and apicoplast division and distribution during the life cycle of Plasmodium falciparum. Utilizing the MitoRed reporter line for fluorescent mitochondrial marking and employing high-resolution 3D imaging techniques, including FIB-SEM, the research unveils the dynamics of these essential organelles across various stages of the parasite's development. The authors' work marks a significant step forward in understanding the cellular biology of Plasmodium falciparum, offering novel insights into the dynamics of mitochondrial and apicoplast division. By addressing the additional comments and incorporating recent findings and clarifications, the research not only underscores the complexity of these processes but also situates the study within the continuum of apicomplexan parasite research.

Major comments: • Suitability of Reporter Line for Oocyst Development: The conclusion regarding the limitations of the MitoRed line for oocyst development stages prompts a discussion on alternative approaches, such as mito trackers, to validate observations in these stages. In the current state, it is difficult to conclude whether the data presented are only true for this specific transgenic line.

We agree with the reviewer that the lack of MitoRed salivary gland sporozoites indeed hints to a developmental issue and therefore interpretation of mitochondrial morphology in oocyst stages should be done carefully. Although we would like to verify these observations with a wild-type line, there are several complications with using a MitoTracker staining. Firstly, a general staining procedure will also highlight the much larger and more abundant host mitochondria thus complicating both the actual imaging and interpretation of the data. Secondly, our own data presented in this manuscript demonstrated that MitoTracker stainings of blood-stage parasites should be considered with great care and it remains to be tested whether mosquito-stage parasite viability and mitochondrial morphology remain unaffected. Thirdly, mosquito experiments are time intensive and costly and we lack the time and funding to expand on this part of the work. We therefore decided to move the oocyst data to the supplement and added additional qualifiers for interpretation to the text.

Line 578: “Although these mitochondrial observations should be interpreted with care since oocysts did not form salivary gland populating sporozoites and might therefore not be representing healthy oocysts, in P. berghei liver-stage schizonts, a very similar mitochondrial organization was observed in sub-compartments created by large membrane invaginations.”

To conclude, we think it is important to be open about the limitations of the MitoRed line and discuss this in the paper to provide a balanced view for others that might want to use this line in the future. At the same time, we think that the observation of the mitochondrial organization centers and the great similarity with mitochondrial organization in liver- and blood-stage schizonts offers tentative support for a biologically relevant phenotype and gives new insights that we would like to share in this manuscript, provided that they are interpreted with care.

• Analysis of Mitochondrion and Apicoplast Association with CPs: Could the author elaborate on how their statistical power and image data support assertions of random association between organelles and CPs (line 438-439) and the dynamic nature of Mito-CP interactions (line 504)? In addition, could the authors comment/discuss their findings regarding the distance between Mito-Api compared to the one reported in Figure S2 of Sun et al. preprint: bioRxiv 2022.09.14.508031; doi: https://doi.org/10.1101/2022.09.14.508031

We would like to clarify the point that the reviewer raises. Although we indeed observed that the distances between the CP-mito are significantly smaller compared to CP-apicoplast in schizont 1 in Figure 7, we do not think that there is interaction between the mitochondrion and CPs. In schizont 3-6, the apicoplast shows close apposition with CPs over the complete length of the apicoplast/with all apicoplast fragments and the distances between CPs and apicoplast range from 0-150 nm, therefore we think there is CP-apicoplast interaction. The distance between CPs and mitochondrion is much larger in all schizonts with an average of 500-600 nm, except for schizont 6 where the CP-mito distances become smaller due to the alignment of the mitochondrion with the apicoplast. Still the CP-mito distance is significantly bigger in schizont 6 compared to CP-apicoplast. Therefore, we do not think there are mito-CP interactions in any of the schizont stages. To clarify this in the text, we added the following sentences:

Line 483: “Although the distances between the mitochondrion and CPs (average 616 nm, SD 235 nm) in this early schizont are significantly smaller than the apicoplast-CPs distances (average 1350 nm, SD 260 nm), there is no direct interaction between the mitochondrion and CPs since the smallest CP-mitochondrion distance measured is 332 nm. The significant difference can be explained by the fact that the apicoplast is located in the center of the parasite, while the mitochondrion is larger and stretched throughout the whole cell leading to coincidental closer proximity to the peripheral CPs.”

We have also added extra comparisons of CP-apicoplast and CP-mitochondrion distances to the text to support this (Line 483-503).

We thank the reviewer for their suggestion of comparison with the data from Sun et al. The EM tomography data in that paper are indeed of much higher resolution and hint at physical interaction between the membranes of the mitochondrion and apicoplast. We have added the following sentences to the discussion:

Line 612: “EM tomography data from Sun et al. show there are hints of connecting structures between the mitochondrion and apicoplast in areas where the distance between the organelles is very small and similar to the distance between the inner and outer membranes of the organelles themselves in merozoites, suggesting physical link between the organelles.”

• Incorporation of Recent Findings into Schematic Models: I recommend the authors modify their current model in Figure 8 to reflect on recent findings on CP outer domain contact with the parasite plasma membrane (PPM) post-mitosis as demonstrated by Liffner et al. PMID: 38108809.

We agree with the reviewer that the data from Liffner et al. suggest contact of the outer CP with the PPM, however, we think ExM data should be interpreted with some care. Contact sites are strictly defined as an area where membranes of two organelles are in close proximity to each other, while there is no membrane fusion, there are tethering forces (protein-lipid or protein-protein interaction), and fulfill a specific function (PMID:30894536). The ExM data do not have the resolution to define the CP-PPM appositions as contact sites. Although we indeed see closeness of the CPs and the PPM in our FIB-SEM data, we do not see evidence of a physical contact between the two. Therefore, for this proposed model, we would keep the focus on the division and segregation of the two endosymbiotic organelles.

Minor comments: • Reference to WHO Report: The manuscript cites malaria incidence and mortality data from an older WHO report. Given the availability of the 2022 WHO reports, authors should update the text and citation (line 36).

Changed accordingly.

• Clarification of Host: The term "its mitochondrion" (line 42) should be specified as "human mitochondrion" to clearly distinguish between the two different hosts.

We changed “The malaria parasite harbors a unique mitochondrion that differs greatly from its host mitochondrion” to “The malaria parasite harbors a unique mitochondrion that differs greatly from the human mitochondrion”.

• Terminology of Parasite Development Stages: The usage of "schizogony" to describe division processes in liver and mosquito stages could be misleading due to the distinct process of endopolygeny nuclear-like division observed during sporogony (line 56; PMID: 31805442). I would recommend the authors use a more general language, such as cell division.

Changed accordingly.

• Prior Research on CP and Apicoplast Association: The observation of centriolar plaques (CPs) associating with the apicoplast (line 91) has precedents in the study of other apicomplexan parasites, such as Sarcosystis (PMID: 16079283). Acknowledging and discussing these findings would contextualize the current study within the broader range of the most commonly studied apicomplexan parasites.

We thank the reviewer for this suggestion and added the following sentence and citation to the discussion:

Line 646: ”In other apicomplexan parasites, such as Toxoplasma gondii and Sarcocystis neurona, centrosomes have also been indicated to be involved in apicoplast organization and distribution during cell division.”

• Depth of Imaging Data: Could the authors indicate the width of their z-stack, for instance, in Figure 1? I would also suggest the authors use hours of post-infection (h.p.i) for clarity (lines 234-254) to aid comprehension by a broader audience as they do later in the manuscript.

As suggested we added the depth and interval ranges of the Z-stacks are added to the legends of Figures 1, 2, 3, and 5.

It is common practice to describe the oocyst stages by days instead of hours post infection (of the mosquito; also referred to as days after feeding) as the development takes ~2 weeks. Later in the manuscript, we refer to the development of asexual blood stages, a ~48h cycle, which is commonly referred to by hours post invasion (of the red blood cell). Sticking to common practices in the field, we have decided leave the time indications used unaltered.

• Visualization of Mitochondrial Structures: Suggestions to include or reference images of bulbous mitochondrial structures (line 445) directly in the main text or within key figures (e.g., Figure 6) would help the reader understand what and where are these bulbous structures.

Arrows are added to Figure 6 to indicate bulins.

• Organelle Communication and Division Mechanisms: The discussion of bulbous invagination structures (buildings) (line 469) and their role in organelle division is interesting; could it be also for organelle communication or storage? Can the authors expand the discussion about it?

We have indeed wondered and discussed possible functions of these bulins extensively. While roles in organelle communication or storage are other interesting theories that also crossed our minds, the timing of appearance, the precise location of the bulins at the entrance of developing merozoites at the stage where bulins are most abundant, and their morphological features together to us strongly suggest a link to (mitochondrial) fission, via membrane remodeling and/or the distribution of certain components, such as mitochondrial DNA, proteins, or protein complexes. We would like to keep the focus of the paper at mitochondrial and apicoplast fission and as such we discuss various observations within this context. Discussing all our observations within the wider context of Plasmodium biology would be lead to overly long and unfocused paper and hence we would like to leave these discussions for other manuscripts with a different focus.

Reviewer #1 (Significance (Required)):

The study is a significant contribution to the field of parasitology, particularly in understanding the cellular biology of Plasmodium falciparum. The development of the MitoRed reporter line is a notable advancement, allowing for the real-time visualization of mitochondrial dynamics. This tool could be invaluable for future studies exploring parasite biology's intricacies and identifying new antimalarial drug targets. Furthermore, while the study provides detailed insights into the division and distribution of mitochondria and apicoplasts, the molecular mechanisms underlying these processes remain to be fully elucidated. Specifically, the role of specific proteins in mediating these divisions and the potential interplay between mitochondrial and apicoplast dynamics during parasite development warrant further investigation.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

During its development and growth, the human malaria parasite P. falciparum needs to guarantee that cellular organelles, including the mitochondrion and the apicoplast, will be divided and segregated correctly into the daughter parasites. However, the details and mechanisms of these processes are not clear. Here, authors provide a description of mitochondrial replication and segregation in P. falciparum schizonts, gametocytes and oocysts. They generated a reporter cell line by attaching mScarlet red fluorescent protein to the mitochondrial heat shock protein 70-3 and used high-resolution 3D-imaging and focused ion beam scanning electron microscopy to study mitochondrion dynamics in the asexual, gametocytes and mosquito stages. The authors found that in schizonts, the mitochondrion forms a cartwheel structure at the end of early segmentation stage with full division occurring only at a late stage of schizogony. Apicoplast division happens after nuclear division but is complete before nuclear division is completed. Authors also found apicoplast but not mitochondrion is associated with centriolar plaque (analogue of centrosome in P. falciparum) during the schizogony. At the end, authors proposed their model of nuclei, mitochondrial and apicoplast division in the asexual stage schizogony. This well-written manuscript provides insights on mitochondrion and apicoplast fission in P. falciparum blood stage schizogony and mitochondrion dynamic in the blood, gametocytes and mosquito stages. Questions and suggestions are below:

Major comments The marker line forms mature oocysts but does not produce salivary gland sporozoites. This phenotype needs to be explained more clearly. Are sporozoites produced in the midgut, are they released into the hemocoel?

For clarity, we have expanded our explanation of this phenotype and indicated the limitations of the tool in lines 250-259:

“While several free sporozoites were observed in dissected midguts and salivary glands on day 16 (data not shown), we never observed an oocyst containing fully mature sporozoites with a divided mitochondrion or an infected salivary gland on day 16 and 21 after infection. This indicates that sporozoites are produced and released into the hemocoel, however, they have a health defect that prevents them from infecting the salivary glands. Possibly the mitochondrial marker or the integration in the SIL7 locus causes issues for sporozoite development. We conclude that the MitoRed line is a great tool for mitochondrial visualization in asexual blood stages, gametocytes stages, and mosquito stages up until late oocysts (Supplemental Information S1) but that for studies later in the life cycle other tools need to be developed and tested.”

Does introduction of an exogenous copy of HSP70 influence total HSP70 expression in the parasite, and can this cause the observed defect in sporozoite production? Did authors try to tag the endogenous HSP70 to see if it's a suitable reporter?

For clarity, as we describe in the paper (e.g. lines 113-117) we did not express an additional copy of HSP70-3 but merely fused its promoter region and mitochondrial targeting sequence without any further functional domains to mScarlet. This is a strategy that has been employed with great success to study mitochondrial biology in all life-cycle stages of P. berghei (PMID:29669282). While we cannot formally exclude that the use of a second copy of the HSP70-3 promoter could somehow influence the expression of the endogenous copy, it seems rather unlikely. A plethora of promoters of a wide variety of genes have been used for transgenic expression of e.g. drug cassettes and other fluorescent markers in a multitude of studies and to the best of our knowledge there are no reports of this ever interfering with endogenous expression levels. Although we think it would be interesting to know what exactly causes the defective sporozoite production, this information will not add to our understanding of mitochondrial dynamics in mosquito stages and hence beyond the scope of this study (see also our responses to the previous comment and the first comment of reviewer 1).

Did authors compare the growth of the reporter parasite line to wild-type in gametocytes and oocysts?

Typically, conversion rates of gametocyte inductions are highly variable even within the same experiment. MitoRed gametocytes have been induced in at least five independent experiments. Although we have not performed a direct quantification of gametocyte conversion or growth rates between MitoRed and NF54 WT parasites, stage V male and female MitoRed gametocytes developed normally demonstrating no morphological aberrations in each of these experiments within the expected 12-day time frame, similarly as WT parasites, assessed by light microscopy. As we found no indications for a developmental phenotype deviating from what is commonly observed for wild-type parasites as is shown in supplemental figure S3. We have added comparison of exflagellation events in MitoRed vs WT parasites to figure S4, showing no significant difference and indicating formation of healthy male gametes. Normal healthy of MitoRed gametocytes is further supported by the fact that these parasites infect mosquitos.

A direct comparison of the growth of MitoRed with WT in oocyst stages is challenging, since infections can show high variance. In addition, these experiments are very costly and time intensive. As we focused our work on blood-stage development and because there are limitations in the use of MitoRed when studying subsequent mosquito- and liver-stage development as discussed above and in the manuscript, we decided not to invest our limited resources for a direct comparison with WT, reserving such a comparison for future transgenic lines that present no obvious developmental defects.

In figure 1A and Methods, are all MitoTracker stains incubated at 100 nM for 30 minutes? Did authors try to optimize the conditions to improve quality Mitotracker staining can be improved?

Indeed, all MitoTracker stains were performed at 100 nM, except for the Rhodamin123 used for life imaging. In the past, we have performed several pilot experiments to optimize staining conditions of which 100nM for 30 min most consistently resulted in sufficiently bright yet specific signals. Notably, this is the MitoTracker concentration that is described most frequently in other papers. The use of a lower concentration might indeed improve the mitochondrial morphology in MitoTracker stained parasites, however, for the scope of this paper we wanted to compare our new mitochondrial marker with the most commonly used MitoTracker staining conditions. Combined with the fact that MitoTrackers are toxic at low concentrations, we preferred to step away from MitoTracker when looking at mitochondrial division, to ensure we are looking at biologically relevant mitochondria.

In figure 1B, can authors replace the figures for the first ring? The parasite does not seem healthy and the scale bar is shorter than the others. Can authors define DIC in the legend?

Change accordingly.

In figure 8, it looks like some apicoplasts are not associated with the CP, contrary to what is stated in the text, for eg the one at the 7 o'clock position in stage 3.

It is indeed difficult to find an angle of visualization that shows clearly that all CPs associate with the apicoplast, a common challenge when trying to visualize 3D data in a 2D space. However, in the 3D animated movies that are provided with the manuscript, the reader can observe this association more clearly, as the organelles rotate slowly so that all angles can be observed. We therefore think that these movies are indispensable to demonstrate and clarify things that are difficult to extract from still, non-rotating image.

The Discussion should mention the failure in generating sporozoites from this reporter line Can authors discuss the SIL7 locus as the site of integration, in the context of potential effect of its disruption on sporozoite production.

In the discussion, we briefly mention the limitation of the use of MitoRed. We have now also added a reference to the more extensive discussion of this phenotype in the supplemental information and included an additional sentence in the results section to indicate the limitations. As indicated in response to previous comments, we think it is important to discuss these limitations as well as present the observations we made during oocyst development but to compartmentalize these to an extended, supplementary section. This allows us to keep the focus on fission during blood-stage schizogony and not make the discussion overly lengthy.

Authors should explain criteria for identifying organelles in FIB-SEM images eg mitochondria, apicoplast etc.

We added to following sentence to clarify how we identified the mitochondrion and apicoplast in the FIB-SEM images (lines 387-389):

"The mitochondrion and apicoplast can be recognized by their tubular shape in addition to the double membrane of the mitochondrion and the thicker appearance of the four membranes of the apicoplast.”

FIB-SEM images show other prominent organelles in these images (dense granules? hemozoin crystals?). It would be helpful for reader orientation and greater appreciation of the work if these organelles were marked as well.

We agree with the reviewer it would be an interesting addition to visualize other organelles, such as e.g. dense granules, rhoptries, and IMC, to learn more about general organellar biology of the parasite. However, segmentation of these organelles requires the training of a new deep learning model and/or the manual segmentation of +400 image slices per parasite. This is unfortunately not feasible for us. However, the dataset is going to be available online and we encourage researchers to revisit and reuse the dataset for their own research questions.

Minor comments The format of blood, mosquito and liver stage is not consistent. Eg. in line 17, 22, 56 and 65. Some has a dash line while some doesn't.

We use hyphens (dashes are longer and used between clauses/sentences) as appropriate. That is, when we use “blood-stage” as a compound adjective as in “the blood-stage parasites are” but not when using “stages” as the noun as “the blood stages are”. We have double-checked the entire manuscript once more to ensure correct hyphenation throughout.

In line 36, numbers of cases and death by malaria are by estimation.

Changed accordingly

Can authors define Plasmodium falciparum as P. falciparum in line 37?

It is common practice to write the full name of a species at first mention in the main body of a manuscript (not including the abstract).

The sentence in line 57-59 is confusing. At the end of schizogony, the daughter merozoite/sporozoite has one mitochondrion but it's multiple in the parasite.

We adapted the sentence so it will be clearer to the reader that the parasite has a single mitochondrion that divides into multiple fragments during cell division:

“During P. falciparum cell division, the single parasite mitochondrion needs to be properly divided and distributed among the daughter cells.”

Can authors specify which mitochondrial dyes are toxic in line 76?

We have included the following sentence to clarify:

“However, eight of these dyes were tested in a drug screen all showing IC50 values below 1mM with three, Mito Red, DiOC6, and Rhodamine B being highly active against P. falciparum with IC50 values below 30 nM14,15.”

In line 115, can authors indicate the Gene ID for PfNF54? Can authors define the reported parasite line as MitoRed here instead of line 125?

Although we indeed used NF54 as the parental strain for the MitoRed line, we think the 3D7 gene ID is more useful in this context. The 3D7 genome is used as the reference genome by the entire field and it is much better annotated than the NF54 genome. Furthermore, the genomes are not all too different to start with, as 3D7 is a subclone of the NF54 line.

In line 134 and 540, use punctate instead of 'punctuated'?

Changed accordingly.

In line 161 to 163, can authors also cite ref 19?

Reference 19 (now 20) is cited in line 163 precluding the need for an additional citation in the next sentence.

In line 174, pH change can also trigger gametocytes activation.

Changed accordingly.

In Figure S4, please indicate the percentage of parasites having close apposition of mitochondrion to axonemes.

When we revisited our images to check what percentage of parasites have close appositions of the mitochondrion and the axonemes, we found that in all exflagellating parasites that were analyzed there is close apposition or overlap between the mitochondrial and the tubulin signal. We changed the text to reflect this:

Line 189: “We found close apposition of the dispersed mitochondria to the axonemal tubulin in all 19 exflagellating males that were analyzed (Figure S4B, S4C).”

Line 237 to 239, please clarify why authors think there is one fragment in mitochondrial.

We have added the following sentence to clarify:

Line 239: “Segmentation of the fluorescent signal based on manual thresholding indicated that the mitochondrion consisted of one continuous structure.”

In line 259, the ookinete stage is II to IV.

Stage indications have been corrected.

In line 281, please define RBC.

Changed accordingly.

In figure 5A, please provide a scale bar for the original and reconstructed image. Should the unit of fragment volume be um3 but not um?

We have added scale bars to the original fluorescent images and the unit has been changed to mm3. Unfortunately, it is not really appropriate to provide a 2D scale bar with a 3D image, since this will not take the depth of your image into account, unless an orthographic projection is used. Objects that are more to the front are visualized slightly bigger than things in the back and therefore a scale bar would not help for interpreting the size of the depicted objects.

Can author do a statistical analysis in Fig 5B and 5C to show the stage at which the majority of nuclei and mitochondria divide?

Changed accordingly.

In figure 5D, the labels on Y axis are not the same size.

The two different sizes were used intentionally to show clearly it is a logarithmic instead of a linear scale.

In figure 6, what's the green black color organelle in the first column (like the organelle showing up as 4 in the first one, at 1/2/6/8 o'clock)? Can authors provide annotations of organelles using arrows at least in the supplementary?

We have added annotations of the RBC, food vacuole, rhoptries, parasite membrane and parasitophorous vacuole membrane to the micrograph images in Figure 6 and the Table S3.

In line 717, the font of ul is not consistent with others like line 691.

Changed accordingly

In line 731, 37 {degree sign}C.

Changed accordingly

Reviewer #2 (Significance (Required)):

The mitochondria of human malaria parasite Plasmodium falciparum differs from the host's and is an intriguing drug target. During the asexual blood stage replication, parasite mitochondrial elongates to form a branched network and undergoes rapid fissions to be distributed properly imto daughter merozoites. However, the details of these processes are unknown. In this study, authors use confocal microscopy and FIB-SEM to describe the dynamics of mitochondrial division in the asexual schizont stage, gametocytes and oocysts.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary The authors developed a new reporter parasite line that can facilitates the study of mitochondria cell biology in sexual and asexual stages of Plasmodium falciparum. This strategy gets around the need for antibodies or MitoTracker, that could be toxic in some parasite stages. The authors further provided new insights into how mitochondria divide and interacts with both apicoplast and centriolar plaques (CPs) using informative and cutting-edge imaging. The study showed that mitochondria get segregated during cellular division in a cartwheel model and aligns with the apicoplast. Finally, they highlight a potential unique association between CPs and apicoplast in the later stages of schizogony that might contributes to apicoplast segregation.

Major comments: 1. The authors should provide a positive control in the form of another mitochondrial marker to validate that the signal provided by the fluorescent parasite is specific to mitochondria. They could try to tag a well-known mitochondria protein in the reported cell line and compare the signal using antibody stain.

Although we agree with the reviewer that a co-localization of the mitochondrial marker with a tagged mitochondrial protein would verify the mitochondrial localization of the marker, we do think that the co-localization with MitoTracker (Figure 1 and Figure S2) is a good validation method. MitoTracker is a widely used and accepted mitochondrial dye to stain mitochondria in Plasmodium species and other eukaryotes. We believe that the co-localization of our mitochondrial marker with several MitoTracker dyes is enough to prove mitochondrial localization.

There should be more rigour in the observations: the authors should provide quantification of how many parasites/fields were analysed and the percentage of observations described in Figure 2. Was this data consistent in different parasites/experiments? How many times were the experiment repeated?

To provide more rigor we have included a more detailed description of the number of experiments, the number of parasites imaged, and the percentage of parasites with the described observation:

Line 159: “For each stage, between 11-19 parasites were imaged over two independent experiments and described observations were consistent over all analyzed parasites.”

Line 181: “While this particular activation experiment was performed on a gametocyte culture that did not exflagellate for unclear reasons, it was repeated twice, and very similar results were found in exflagellating males (n=19) (Figure 2C).”

Line 189: “We found close apposition of the dispersed mitochondria to the axonemal tubulin in all 19 exflagellating males that were analyzed (Figure S4).”

More rigour is required also in the analysis of oocyst: what was the criteria to define 'large oocysts' (lines 241-242)? How many oocysts were analysed?

We have added estimated diameters of the oocyst to provide more defined criteria:

Line 238: “At day 7, small oocysts (~10 mm diameter) were observed with a branched mitochondrial network stretched out throughout the cell (Figure 3C).”

Line 241: “Day 10 oocysts were much larger (~35 mm diameter) and the mitochondrial mesh-like network appeared more organized, also localizing to areas directly below the oocyst wall (Figure 3D).”

Line 243: “Some large oocysts (~70 mm diameter) showed a highly organized mitochondrial network, where mitochondrial branches were organized in a radial fashion around a central organizational point (Figure 3E, S5A).”

Line 247: “Some smaller oocysts (~35 mm diameter) at day 13 showed structures that looked like beginning MOCs (Figure S5B).”

Finally figure 5 also lacks rigour: How were the fragments quantified? How many times were the experiment repeated? Is there any statistical difference in different parasite stages? To clarify how mitochondrial fragments were quantified, we added the following sentences to the materials and methods section:

Line 765: “3D visualization and quantifications were done in Arivis 4D Vision software. For mitochondrial measurements, threshold-based segmentation was used. For nuclei, blob-finder function was used for segmentation. Number of segmented objects and volume of objects was determined by Arivis software.”

The experiment was repeated twice, and the second independent experiment, which shows the same mitochondrial division stages, is added to the supplement (Figure S7). We added the following sentence to the text for clarification (Line 310):

“These mitochondrial division stages were confirmed in a second, independent 3D imaging experiment (Figure S7).”

Statistical analysis between different parasite stages was performed and added to Figure 5.

Minor comments: 1. Error bars in Fig S1. should be in a different colour from the line graph (eg. black or white).

Changing the color of the error bars made the figure less clear to interpret, due to their small size. We therefore decided to leave the image unaltered.

Scale bar in Fig 2D is missing.

As indicated in response to reviewer 2, unfortunately, it is not really appropriate to provide a 2D scale bar with a 3D image, since this will not take the depth of your image into account. That is, things that are more to the front are visualized slightly bigger than things in the back and therefore a scale bar would not help for interpreting the size of the depicted objects.

In Fig 4. a square dotted line should be placed to represent the GAP45 crop area.

Changed accordingly.

In Table S3 the authors should provide a colour legend and highlight mitochondria in the micrographs.

Color legend and annotations of RBC, food vacuole, rhoptries, parasite membrane and parasitophorous vacuole membrane have been added to the table.

Lines 282-286. The authors should try to hypothesize why MitoRed does not work for live imaging during schizogony

Despite several attempts to improve imaging conditions to prevent this, including, reduced laser power, increase time interval, better temperature control, and gassing of the imaging chamber with low oxygen mixed gas, parasites remained unhealthy. In the discussion, we hypothesize that the mitochondrial marker might cause parasites to be unhealthy due to phototoxicity.

In Fig. 6B parasite is misspelled

Changed accordingly.

Reviewer #3 (Significance (Required)):

Significance

The current paper provides a significant advance in the study of mitochondria cell biology in P. falciparum. The authors used a new strategy for mitochondria visualization that works well in most of parasite stages, enabling them to described in detail mitochondria and apicoplast division that can be used as guideline for future work. The limitation of this study, is a lack of mechanisms that might explain the reported observations, which leaves the discussion somewhat speculative.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

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Referee #3

Evidence, reproducibility and clarity

Summary

The authors developed a new reporter parasite line that can facilitates the study of mitochondria cell biology in sexual and asexual stages of Plasmodium falciparum. This strategy gets around the need for antibodies or MitoTracker, that could be toxic in some parasite stages. The authors further provided new insights into how mitochondria divide and interacts with both apicoplast and centriolar plaques (CPs) using informative and cutting-edge imaging. The study showed that mitochondria get segregated during cellular division in a cartwheel model and aligns with the apicoplast. Finally, they highlight a potential unique association between CPs and apicoplast in the later stages of schizogony that might contributes to apicoplast segregation.

Major comments:

1. The authors should provide a positive control in the form of another mitochondrial marker to validate that the signal provided by the fluorescent parasite is specific to mitochondria. They could try to tag a well-known mitochondria protein in the reported cell line and compare the signal using antibody stain.
2. There should be more rigour in the observations: the authors should provide quantification of how many parasites/fields were analysed and the percentage of observations described in Figure 2. Was this data consistent in different parasites/experiments? How many times were the experiment repeated?
3. More rigour is required also in the analysis of oocyst: what was the criteria to define 'large oocysts' (lines 241-242)? How many oocysts were analysed?
4. Finally figure 5 also lacks rigour: How were the fragments quantified? How many times were the experiment repeated? Is there any statistical difference in different parasite stages?

Minor comments:

1. Error bars in Fig S1. should be in a different colour from the line graph (eg. black or white).
2. Scale bar in Fig 2D is missing.
3. In Fig 4. a square dotted line should be placed to represent the GAP45 crop area.
4. In Table S3 the authors should provide a colour legend and highlight mitochondria in the micrographs.
5. Lines 282-286. The authors should try to hypothesize why MitoRed does not work for live imaging during schizogony
6. In Fig. 6B parasite is misspelled

Significance

The current paper provides a significant advance in the study of mitochondria cell biology in P. falciparum. The authors used a new strategy for mitochondria visualization that works well in most of parasite stages, enabling them to described in detail mitochondria and apicoplast division that can be used as guideline for future work.

The limitation of this study, is a lack of mechanisms that might explain the reported observations, which leaves the discussion somewhat speculative.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

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Referee #2

Evidence, reproducibility and clarity

During its development and growth, the human malaria parasite P. falciparum needs to guarantee that cellular organelles, including the mitochondrion and the apicoplast, will be divided and segregated correctly into the daughter parasites. However, the details and mechanisms of these processes are not clear. Here, authors provide a description of mitochondrial replication and segregation in P. falciparum schizonts, gametocytes and oocysts. They generated a reporter cell line by attaching mScarlet red fluorescent protein to the mitochondrial heat shock protein 70-3 and used high-resolution 3D-imaging and focused ion beam scanning electron microscopy to study mitochondrion dynamics in the asexual, gametocytes and mosquito stages. The authors found that in schizonts, the mitochondrion forms a cartwheel structure at the end of early segmentation stage with full division occurring only at a late stage of schizogony. Apicoplast division happens after nuclear division but is complete before nuclear division is completed. Authors also found apicoplast but not mitochondrion is associated with centriolar plaque (analogue of centrosome in P. falciparum) during the schizogony. At the end, authors proposed their model of nuclei, mitochondrial and apicoplast division in the asexual stage schizogony. This well-written manuscript provides insights on mitochondrion and apicoplast fission in P. falciparum blood stage schizogony and mitochondrion dynamic in the blood, gametocytes and mosquito stages. Questions and suggestions are below:

Major comments

The marker line forms mature oocysts but does not produce salivary gland sporozoites. This phenotype needs to be explained more clearly. Are sporozoites produced in the midgut, are they released into the hemocoel?

Does introduction of an exogenous copy of HSP70 influence total HSP70 expression in the parasite, and can this cause the observed defect in sporozoite production? Did authors try to tag the endogenous HSP70 to see if it's a suitable reporter?

Did authors compare the growth of the reporter parasite line to wild-type in gametocytes and oocysts? In figure 1A and Methods, are all MitoTracker stains incubated at 100 nM for 30 minutes? Did authors try to optimize the conditions to improve quality Mitotracker staining can be improved? In figure 1B, can authors replace the figures for the first ring? The parasite does not seem healthy and the scale bar is shorter than the others. Can authors define DIC in the legend? In figure 8, it looks like some apicoplasts are not associated with the CP, contrary to what is stated in the text, for eg the one at the 7 o'clock position in stage 3. The Discussion should mention the failure in generating sporozoites from this reporter line Can authors discuss the SIL7 locus as the site of integration, in the context of potential effect of its disruption on sporozoite production. Authors should explain criteria for identifying organelles in FIB-SEM images eg mitochondria, apicoplast etc. FIB-SEM images show other prominent organelles in these images (dense granules? hemozoin crystals?). It would be helpful for reader orientation and greater appreciation of the work if these organelles were marked as well.

Minor comments

The format of blood, mosquito and liver stage is not consistent. Eg. in line 17, 22, 56 and 65. Some has a dash line while some doesn't. In line 36, numbers of cases and death by malaria are by estimation. Can authors define Plasmodium falciparum as P. falciparum in line 37? The sentence in line 57-59 is confusing. At the end of schizogony, the daughter merozoite/sporozoite has one mitochondrion but it's multiple in the parasite. Can authors specify which mitochondrial dyes are toxic in line 76? In line 115, can authors indicate the Gene ID for PfNF54? Can authors define the reported parasite line as MitoRed here instead of line 125? In line 134 and 540, use punctate instead of 'punctuated'? In line 161 to 163, can authors also cite ref 19? In line 174, pH change can also trigger gametocytes activation. In Figure S4, please indicate the percentage of parasites having close apposition of mitochondrion to axonemes. Line 237 to 239, please clarify why authors think there is one fragment in mitochondrial. In line 259, the ookinete stage is II to IV. In line 281, please define RBC. In figure 5A, please provide a scale bar for the original and reconstructed image. Should the unit of fragment volume be um3 but not um? Can author do a statistical analysis in Fig 5B and 5C to show the stage at which the majority of nuclei and mitochondria divide? In figure 5D, the labels on Y axis are not the same size. In figure 6, what's the green black color organelle in the first column (like the organelle showing up as 4 in the first one, at 1/2/6/8 o'clock)? Can authors provide annotations of organelles using arrows at least in the supplementary? In line 717, the font of ul is not consistent with others like line 691. In line 731, 37 {degree sign}C.

Significance

The mitochondria of human malaria parasite Plasmodium falciparum differs from the host's and is an intriguing drug target. During the asexual blood stage replication, parasite mitochondrial elongates to form a branched network and undergoes rapid fissions to be distributed properly imto daughter merozoites. However, the details of these processes are unknown. In this study, authors use confocal microscopy and FIB-SEM to describe the dynamics of mitochondrial division in the asexual schizont stage, gametocytes and oocysts.

Reviewer #3 (Public Review):

Summary:

This manuscript describes some biochemical experiments on the crucial virulence factor EsxA (ESAT-6) of Mycobacterium tuberculosis. EsxA is secreted via the ESX-1 secretion system. Although this system is recognized to be crucial for virulence the actual mechanisms employed by the ESX-1 substrates are still mostly unknown. The EsxA substrate is attracting most attention as the central player in virulence, especially phagosomal membrane disruption. EsxA is secreted as a dimer together with EsxB. The authors show that EsxA is also able to form homodimers and even tetramers, albeit at very low pH (below 5). Furthermore addition of a nanobody that specifically binds EsxA is blocking intracellular survival, also if the nanobody is produced in the cytosol of the infected macrophages.

Strengths:

Decent biochemical characterization of EsxA and identification of a new and interesting tool to study the function of EsxA (nanobody). Well written.

Weaknesses:

The findings are not critically evaluated using extra experiments or controls.<br /> For instance, tetrameric EsxA in itself is interesting and could reveal how EsxA works. But one would say that this is a starting point to make small point mutations that specifically affect tetramer formation and then evaluate what the effect is on phagosomal membrane lysis. Also one would like to see experiments to indicate whether these structures can be produced under in vitro conditions, especially because it seems that this mainly happens when the pH is lower than 5, which is not normally happening in phagosomes that are loaded with M. tuberculosis.<br /> Also the fact that the addition of the nanobody, either directly to the bacteria or produced in the cytosol of macrophages is interesting, but again the starting point for further experimentation. As a control one would like to se the effect on an Esx-1 secretion mutant. Furthermore, does cytososlic production or direct addition of the nanobody affect phagosomal escape? What happens if an EsxA mutant is produced that does not bind the nanobody?<br /> Finally, it is a bit strange that the authors use a non-native version of esxA that has not only an additional His-tag but also an additional 12 amino acids, which makes the protein in total almost 20% bigger. Of course these additions do not have to alter the characteristics, but they might. On the other hand they easily discard the natural acetylation of EsxA by mycobacteria itself (proven for M. marinum) as not relevant for the function because it might not happen in (the close homologue) M. tuberculosis.

reply to u/rocklover7 at https://www.reddit.com/r/typewriters/comments/1cnljgm/where_do_i_start/

The best thing you could do is to take a moment at the library or bookshop and pick up a copy of Polt, Richard. The Typewriter Revolution: A Typist’s Companion for the 21st Century. 1st ed. Woodstock, VT: Countryman Press, 2015.

He looks at typewriters from a writers' writer perspective which I'm sure you'll appreciate. He's got experience with a wide variety of machines as well as a large collection himself. He goes over all of the common/popular (and solid machines) in a variety of sizes and formats to help you figure out which one you might like to start out with. He also covers some of the common problems and repairs that regularly pop up. The book is really a "best of" list of typewriter material from the past 15+ years of this reddit forum and material from the "typosphere" of which he's been not only an active member, but literal ring-leader. The vast majority of the questions which appear on a weekly basis here are discussed and addressed in his book, along with some emphasis on writerly concerns and practice which most beginners here wouldn't be asking. Even reading 3 or 4 of the 8 chapters which are rife with images will give you a solid crash course for exactly the sorts of typewriter (and writing) advice you're searching for.

Definitely DO NOT pick up a new machine off of Amazon. They're even worse than some of the late 70s/early 80s machines. Instead, for beginners (and for the value) I'd recommend looking at Remingtons (Quiet-Riter), Royals (Quiet De Luxe), or Smith-Coronas (Clipper, Silent, Super) from roughly 1948-1958 which is generally the peak of U.S. typewriter manufacturing as well as for features. These were all built like tanks and are usually still in very good condition, even when they're in bad condition. I've provided links to some of these models in the typewriter database, so you have an idea visually of what to look out for.

If desperate, and you live in an area where machines are priced starting over $50 or you're more price sensitive (making eBay, Facebook Marketplace or Craigslist less appealing), you can find some of these every day listed at shopgoodwill.com starting at $10. Even with heaving bidding on auctions, these usually don't go over $35 (except for some of the Smith-Coronas). I've even seen them (sadly) not move at all for $10. This would give you an incredibly solid and inexpensive machine to tinker on, and will most likely work for you out of the box (as long as it's got a ribbon.) You'll end up with a solid machine to start off on while you search for your dream machine. It'll also give you some experience cleaning up and maintaining one. Of the seven machines I've gotten this way and paid an average of about $30-35 each (all in with shipping, tax, etc.) All but one were all immediately usable and only needed moderate cleaning that one could do at home with a cloth, dish soap, a toothbrush and maybe some canned air. Two of the seven were in near mint condition and didn't need any work at all. Tag/garage sales are also inexpensive options that usually allow you test out a machine, but it requires some shoe leather and lots of patience. If you've got a favorite author you love and trust, you might try searching out their machines: https://site.xavier.edu/polt/typewriters/typers.html

If there are any type-ins in your local area, try to go so you can not only meet others, but it might give you a chance to see and try out the machines of others to see what might suit you best.

Happiness and best wishes on your search!

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Reply to the reviewers

Reply to reviewer comments

• *

We extend our gratitude to the reviewers for their time and valuable feedback on our manuscript. We especially appreciate the insightful suggestions that have significantly contributed to refining our work and elucidating our findings. With the revisions made to the text and the inclusion of new experimental data, we believe our manuscript now effectively addresses all reviewer comments. We eagerly await your evaluation of our revised submission.

Small ARF-like GTPases play fundamental roles in dynamic signaling processes linked with vesicular trafficking in eukaryotes. Despite of their evolutionary conservation, there is little known about the ARF-like GTPase functions in plants. Our manuscript reports the biochemical and cell biological characterization of the small ARF-like GTPase TTN5 from the model plant Arabidopsis thaliana*. Fundamental investigations like ours are mostly lacking for ARF and ARL GTPases in Arabidopsis. *

We employed fluorescence-based enzymatic assays suited to uncover different types of the very rapid GTPase activities for TTN5. The experimental findings are now illustrated in a more comprehensive modified Figure 2 and in the form of a summary of the GTPase activities for TTN5 and its mutant variants in the NEW Figure 7A in the Discussion part. Taken together, we found that TTN5 is a non-classical GTPase based on its enzymatic kinetics. The reviewers appreciated these findings and highlighted them as being „impressive in vitro biochemical characterization" and "major conceptual advance". Since such experiments are "uncommon" for being conducted with plant GTPases, reviewers regarded this analysis as "useful addition to the plant community in general". The significance of these findings is given by the circumstance that „the ARF-like proteins are poorly addressed in Arabidopsis while they could reveal completely different function than the canonical known ARF proteins". Reviewers saw here clearly a "strength" of the manuscript.

With regard to the cell biological investigation and initial assessment of cell physiological roles of TTN5, we now provide requested additional evidence. First of all, we provide NEW data on the localization of TTN5 by immunolocalization using a complementing HA3-TTN5 construct, supporting our initial suggestions that TTN5 may be associated with vesicles and processes of the endomembrane system. The previous preprint version had left the reviewers „less convinced" of cell biological data due to the lack of complementation of our YFP-TTN5 construct, lack of Western blot data and the low resolution of microscopic images. We fully agree that these points were of concern and needed to be addressed. We have therefore intensively worked on these „weaknesses" and present now a more detailed whole-mount immunostaining series with the complementing HA3-TTN5 transgenic line (NEW Figure 4, NEW Figure 3P), Western blot data (NEW Supplementary Figures S7C and D), and we will provide all original images upon publication of our manuscript at BioImage Archives which will provide the high quality for re-analysis. BioImage Archives is an online storage for biological image data associated with a peer-reviewed publication. This way, readers will be able to inspect each image in detail. The immunolocalization data are of particular importance as they indicate that HA3-TTN5 can be associated with punctate vesicle structures and BFA bodies as seen with YFP studies of YFP-TTN5 seedlings. We have re-phrased very carefully and emphasized those localization patterns which are backed up by immunostaining and YFP fluorescence detection of YFP-TTN5 signals. To improve the comprehension, the findings are summarized in a schematic overview in NEW Figure 7B of the Discussion. We have also addressed all other comments related to the cell biological experiments to "provide the substantial improvement" that had been requested. We emphasize that we found two cell physiological phenotypes for the TTN5T30N mutant. YFP-TTN5T30N confers phenotypes, which are differing mobility of the fluorescent vesicles in the epidermis of hypocotyls (see Video material and NEW Supplementary Video Material S1M-O), and a root growth phenotype of transgenic HA3-TTN5T30N seedlings (NEW Figure 3O). We explain the cell physiological phenotypes in relation to enzymatic GTPase data. These findings convince us of the validity of the YFP-TTN5 analysis indicative of TTN5 localization.

*We are deeply thankful to the reviewers for judging our manuscript as "generally well written", "important" and "of interest to a wide range of plant scientists" and "for scientists working in the trafficking field" as it "holds significance" and will form the basis for future functional studies of TTN5. *

We prepared very carefully our revised manuscript in which we address all reviewer comments one by one. Please find our revision and our detailed rebuttal to all reviewer comments below. Changes in the revised version are highlighted by yellow and green color. In the "revised version with highlighted changes".

With these adjustments, we hope that our peer-reviewed study will receive a positive response.

We are looking forward to your evaluation of our revised manuscript and thank you in advance,

Sincerely

Petra Bauer and Inga Mohr on behalf of all authors

*

• *

__Reviewer #1 (Evidence, reproducibility and clarity (Required)): __

The manuscript from Mohr and collaborators reports the characterization of an ARF-like GTPase of Arabidopsis. Small GTPases of the ARF family play crucial role in intracellular trafficking and plant physiology. The ARF-like proteins are poorly addressed in Arabidopsis while they could reveal completely different function than the canonical known ARF proteins. Thus, the aim of the study is important and could be of interest to a wide range of plant scientists. I am impressed by the biochemical characterization of the TTN5 protein and its mutated versions, this is clearly a very nice point of the paper and allows for proper interpretations of the other results. However, I was much less convinced on the cell biology part of this manuscript and aside from the subcellular localization of the TTN5 I think the paper would benefit from a more functional angle. Below are my comments to improve the manuscript:

1- In the different pictures and movies, TTN5 is quite clearly appearing as a typical ER-like pattern. The pattern of localization further extends to dotty-like structures and structures labeled only at the periphery of the structure, with a depletion of fluorescence inside the structure. These observations raise several points. First, the ER pattern is never mentioned in the manuscript while I think it can be clearly observed. Given that the YFP-TTN5 construct is not functional (the mutant phenotype is not rescued) the ER-localization could be due to the retention at the ER due to quality control. The HA-TTN5 construct is functional but to me its localization shows a quite different pattern from the YFP version, I do not see the ER for example or the periphery-labeled structures. In this case, it will be a crucial point to perform co-localization experiments between HA-TTN5 and organelles markers to confirm that the functional TTN5 construct is labeling the Golgi and MVBs, as does the non-functional one. I am also quite sure that a co-localization between YFP-TTN5 and HA-TTN5 will not completely match... The ER is contacting so many organelles that the localization of YFP-TTN5 might not reflects the real location of the protein.

__Our response: __

At first, we like to state that specific detection of intracellular localization of plant proteins in plant cells is generally technically very difficult, when the protein abundance is not overly high. In this revised version, we extended immunostaining analysis to different membrane compartments, including now immunostaining of complementing HA3-TTN5 in the absence and presence of BFA, along with immunodetection of ARF1 and FM4-64 labeling in roots (NEW Figure 3P, NEW Figure 4A, B). In the revised version, we focus the analysis and conclusions on the fluorescence patterns that overlap between YFP-TTN5 detection and HA3-TTN5 immunodetection. With this, we can be most confident about subcellular TTN5 localization. Please find this NEW text in the Result section (starting Line 323):

„For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."

We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):

„Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

*And we discuss in the Discussion section (starting Line 552): *

„We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."

2- What are the structures with TTN5 fluorescence depleted at the center that appear in control conditions? They look different from the Golgi labeled by Man1 but similar to MVBs upon wortmannin treatment, except that in control conditions MVBs never appear like this. Are they related to any kind of vacuolar structures that would be involved in quality control-induced degradation of non-functional proteins?

Our response:

The reviewer certainly refers to fluorescence images from N. benthamiana leaf epidermal cells where different circularly shaped structures are visible. In these respective structures, the fluorescent circles are depleted from fluorescence in the center, e.g. in Figure 5C, YFP- fluorescent signals in TTN5T30N transformed leaf discs. We suspect that these structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al., 2020 for ANNI-GFP (reference in manuscript). The reviewer certainly does not refer to swollen MVBs that are seen following wortmannin treatment, as in Figure 5N-P, which look similar in their shape but are larger in size. Please note that we always included the control conditions, namely the images recorded before the wortmannin treatment, so that we were able to investigate the changes induced by wortmannin. Hence, we can clearly say that the structures with depleted fluorescence in the center as in Figure 5C are not wortmannin-induced swollen MVBs.To make these points clear to the reader, we added an explanation into the text (Line 385-388):

„We also observed YFP fluorescence signals in the form of circularly shaped ring structures with a fluorescence-depleted center. These structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al. (2020) for ANNI-GFP."

3- The fluorescence at nucleus could be due to a proportion of YFP-TTN5 that is degraded and released free-GFP, a western-blot of the membrane fraction vs the cytosolic fraction could help solving this issue.

Our response:

In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):

„We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

4- It is not so easy to conclude from the co-localization experiments. The confocal pictures are not always of high quality, some of them appear blurry. The Golgi localization looks convincing, but the BFA experiments are not that clear. The MVB localization is pretty convincing but the images are blurry. An issue is the quantification of the co-localizations. Several methods were employed but they do not provide consistent results. As for the object-based co-localization method, the authors employ in the text co-localization result either base on the % of YFP-labeled structures or the % of mCherry/mRFP-labeled structures, but the results are not going always in the same direction. For example, the proportion of YFP-TTN5 that co-localize with MVBs is not so different between WT and mutated version but the proportion of MVBs that co-localize with TTN5 is largely increased in the Q70L mutant. Thus it is quite difficult to interpret homogenously and in an unbiased way these results. Moreover, the results coming from the centroid-based method were presented in a table rather than a graph, I think here the authors wanted to hide the huge standard deviation of these results, what is the statistical meaning of these results?

Our response:

First of all, we like to point out that, as explained above, the BFA experiments are now more clear. We performed additional BFA treatment coupled with immunostaining using HA3-TTN5-expressing Arabidopsis seedlings and coupled with fluorescence analysis using YFP-TTN5-expressing Arabidopsis plants. In both experiments, we observed the typical BFA bodies very clearly (NEW Figure 4B, C).

Second, we like to insist that we performed colocalization very carefully and quantified the data in three different manners. We like to state that there is no general standardized procedure that best suits the idea of a colocalization pattern. Results of colocalization are represented in stem diagrams and table format, including statistical analysis. Colocalization was carried out with the ImageJ plugin JACoP for Pearson's and Overlap coefficients and based on the centroid method. The plotted Pearson's and Overlap coefficients are presented in bar diagrams in Supplementary Figure S8A and C, including statistics. The obtained values by the centroid method are represented in table format in Supplementary Figure S8B and D, which *can be considered a standard method (see Ivanov et al., 2014). *

Colocalization of two different fluorescence signals was performed for the two channels in a specific chosen region of interest (indicating in % the overlapping signal versus the sum of signal for each channel). The differences between the YFP/mRFP and mRFP/YFP ratios indicate that a higher percentage of ARA7-RFP signal is colocalizing with YFP-TTN5Q70L signal than with the TTN5WT or the TTN5T30N mutant form signals, while the YFP signals have a similar overlap with ARA7-positive structures. This is not a contradiction. Presumably this answers well the questions on colocalization.

Please note that upon acceptance for publication, we will upload all original colocalization data to BioImage Archive. Hence, the high-quality data can be reanalyzed by readers.

5- The use of FM4-64 to address the vacuolar trafficking is a hazardous, FM4-64 allows the tracking of endocytosis but does not say anything on vacuolar degradation targeting and even less on the potential function of TTN5 in endosomal vacuolar targeting. Similarly, TTN5, even if localized at the Golgi, is not necessarily function in Golgi-trafficking. __Our response: __

*Perhaps our previous description was misleading. Thank you for pointing this out. We reformulated the text and modified the schematic representation of FM4-64 in NEW Figure 6A: *

"(A), Schematic representation of progressive stages of FM4-64 localization and internalization in a cell. FM4-64 is a lipophilic substance. After infiltration, it first localizes in the plasma membrane, at later stages it localizes to intracellular vesicles and membrane compartments. This localization pattern reflects the endocytosis process (Bolte et al. 2004)."

6- The manuscript lacks in its present shape of functional evidences for a role of TTN5 in any trafficking steps. I understand that the KO mutant is lethal but what are the phenotypes of the Q70L and T30N mutant plants? What is the seedling phenotype, how are the Golgi and MVBs looking like in these mutants? Do the Q70L or T30N mutants perturbed the trafficking of any cargos?

__Our response: __

*We agree fully that functional evidences are interesting to assign roles for TTN5 in trafficking steps. A phenotype associated with TTN5T30N and TTN5Q70L is clearly meaningful. *

First of all, we like to emphasize that it is incorrect that the manuscript lacks functional evidences for a role of TTN5 and the two mutants. In fact, the manuscript even highlights several functional activities that are meaningful in a cellular context. These include different types of kinetic GTPase enzyme activities, subcellular localization in planta and association with different endomembrane compartments and subcellular processes such as endocytosis. We surely agree that future research can focus even more on cell physiological aspects and the physiological functions in plants to examine the proposed roles of TTN5 in intracellular trafficking steps. For such studies, our findings are the fundamental basis.

Concerning the aspect of colocalization of the mutants with the markers we show in Figure 5C, D and G, H that YFP-TTN5T30N- and YFP-TTN5Q70L-related signals colocalize with the Golgi marker GmMan1-mCherry. Figure 5K, L and O, P show that YFP-TTN5T30N and YFP-TTN5Q70L-related signals can colocalize with the MVB marker, and this may affect relevant vesicle trafficking processes and plasma membrane protein regulation involved in root cell elongation.

*At present, we have not yet investigated perturbed cargo trafficking. These aspects are certainly interesting but require extensive work and testing of appropriate physiological conditions and appropriate cargo targets. We discuss future perspectives in the Discussion. We agree that such functional information is of great importance, but needs to be clarified in future studies. *

__Reviewer #1 (Significance (Required)): __

In conclusion, I think this manuscript is a good biochemical description of an ARF-like protein but it would need to be strengthen on the cell biology and functional sides. Nonetheless, provided these limitations fixed, this manuscript would advance our knowledge of small GTPases in plants. The major conceptual advance of that study is to provide a non-canonical behavior of the active/inactive cycle dynamics for a small-GTPase. Of course this dynamic probably has an impact on TTN5 function and involvement in trafficking, although this remains to be fully demonstrated. Provided a substantial amount of additional experiments to support the claims of that study, this study could be of general interest for scientist working in the trafficking field.

__Our response: __

We thank reviewer 1 for the very fruitful comments. We hope that with the additional experiments, NEW Figures and NEW Supplementary Figures as well as our changes in the text, all comments by the reviewer have been addressed.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

The manuscript by Mohr and colleagues characterizes the Arabidopsis predicted small GTPase TITAN5 in both biochemical and cell biology contexts using in vitro and in planta techniques. In the first half of the manuscript, the authors use in vitro nucleotide exchange assays to characterise the GTPase activity and nucleotide binding properties of TITAN5 and two mutant variants of it. The in vitro data they produce indicates that TITAN5 does indeed have general GTPase and nucleotide binding capability that would be expected for a protein predicted to be a small GTPase. Interestingly, the authors show that TITAN5 favors a GTP-bound form, which is different to many other characterized GTPases that favor GDP-binding. The authors follow their biochemical characterisation of TITAN with in planta experiments characterizing TITAN5 and its mutant variants association with the plant endomembrane system, both by stable expression in Arabidopsis and transient expression in N.benthamiana.

The strength of this manuscript is in its in vitro biochemical characterisation of TITAN5 and variants. I am not an expert on in vitro GTPase characterisation and so cannot comment specifically on the assays they have used, but generally speaking this appears to have been well done, and the authors are to be commended for it. In vitro characterisation of plant small GTPases is uncommon, and much of our knowledge is inferred for work on animal or yeast GTPases, so this will be a useful addition to the plant community in general, especially as TITAN5 is an essential gene. The in planta data that follows is sadly not as compelling as the biochemical data, and suffers from several weaknesses. I would encourage the authors to consider trying to improve the quality of the in planta data in general. If improved and then combined with the biochemical aspects of the paper, this has the potential to make a nice addition to plant small GTPase and endomembrane literature.

The manuscript is generally well written and includes the relevant literature.

Major issues:

1. The authors make use of a p35s: YFP-TTN5 construct (and its mutant variants) both stably in Arabidopsis and transiently in N.benthamiana. I know from personal experience that expressing small GTPases from non-endogenous promoters and in transient expression systems can give very different results to when working from endogenous promoters/using immunolocalization in stable expression systems. Strong over-expression could for example explain why the authors see high 'cytosolic' levels of YFP-TTN5. It is therefore questionable how much of the in planta localisation data presented using p35S and expression in tobacco is of true relevance to the biological function of TITAN5. The authors do present some immunolocalization data of HA3-TTN5 in Arabidopsis, but this is fairly limited and it is very difficult in its current form to use this to identify whether the data from YFP-TTN5 in Arabidopsis and tobacco can be corroborated. I would encourage the authors to consider expanding the immunolocalization data they present to validate their findings in tobacco. __Our response: __

We are aware that endogenous promoters may be preferred over 35S promoter. However, the two types of lines we generated with endogenous promoter did both not show fluorescent signals so that we could unfortunately not use them (not shown). Besides 35S promoter-mediated expression we were also investigating inducible expression vectors for fluorescence imaging in N. benthamiana (not shown). Both inducible and constitutive expression showed very similar expression patterns so that we chose characterizing in detail the 35S::YFP-TTN5 fluorescence in both N. bethamiana*and Arabidopsis. *

We have expanded immunolocalization using the HA3-TTN5 line and compare it now along with YFP fluorescence signal in YFP-TTN5 seedlings (NEW Figure 3P; NEW Figure 4).

„For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."

• *

Many of the confocal images presented are of poor quality, particularly those from N.benthamiana.

Our response:

All confocal images are of high quality in their original format. To make them accessible, we will upload all raw data to BioImage Archive upon acceptance of the manuscript.

The authors in some places see YFP-TTN5 in cell nuclei. This could be a result of YFP-cleavage rather than genuine nuclear localisation of YFP-TTN5, but the authors do not present western blots to check for this.

__Our response: __

As described in our response to reviewer 1, comment 3, Fluorescence signals were detected within the nuclei of root cells of YFP-TTN5 plants, while immunostaining signals of HA3-TTN5 were not detected in the nucleus. In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):

• *

„We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

That YFP-TTN5 fails to rescue the ttn5 mutant indicates that YFP-tagged TTN5 may not be functional. If the authors cannot corroborate the YFP-TTN5 localisation pattern with that of HA3-TTN5 via immunolocalization, then the fact that YFP-TTN5 may not be functional calls into question the biological relevance of YFP-TTN5's localisation pattern.

__Our response: __

This refers to your comment 1, please check this comment for a detailed response. Please also see our answer to reviewer 1, comment 1.

At first, we like to state that specific detection of intracellular localization of plant proteins in plant cells is generally technically very difficult, when the protein abundance is not overly high. In this revised version, we extended immunostaining analysis to different membrane compartments, including now immunostaining of complementing HA3-TTN5 in the absence and presence of BFA, along with immunodetection of ARF1 and FM4-64 labeling in roots (NEW Figure 3P, NEW Figure 4A, B). In the revised version, we focus the analysis and conclusions on the fluorescence patterns that overlap between YFP-TTN5 detection and HA3-TTN5 immunodetection. With this, we can be most confident about subcellular TTN5 localization. Please find this NEW text in the Result section (starting Line 323):

„For a more detailed investigation of HA3-TTN5 subcellular localization, we then performed co-immunofluorescence staining with an Alexa 488-labeled antibody recognizing the Golgi and TGN marker ARF1, while detecting HA3-TTN5 with an Alexa 555-labeled antibody (Robinson et al. 2011, Singh et al. 2018) (Figure 4A). ARF1-Alexa 488 staining was clearly visible in punctate structures representing presumably Golgi stacks (Figure 4A, Alexa 488), as previously reported (Singh et al. 2018). Similar structures were obtained for HA3-TTN5-Alexa 555 staining (Figure 4A, Alexa 555). But surprisingly, colocalization analysis demonstrated that the HA3-TTN5-labeled structures were mostly not colocalizing and thus distinct from the ARF1-labeled ones (Figure 4A). Yet the HA3-TTN5- and ARF1-labeled structures were in close proximity to each other (Figure 4A). We hypothesized that the HA3-TTN5 structures can be connected to intracellular trafficking steps. To test this, we performed brefeldin A (BFA) treatment, a commonly used tool in cell biology for preventing dynamic membrane trafficking events and vesicle transport involving the Golgi. BFA is a fungal macrocyclic lactone that leads to a loss of cis-cisternae and accumulation of Golgi stacks, known as BFA-induced compartments, up to the fusion of the Golgi with the ER (Ritzenthaler et al. 2002, Wang et al. 2016). For a better identification of BFA bodies, we additionally used the dye FM4-64, which can emit fluorescence in a lipophilic membrane environment. FM4-64 marks the plasma membrane in the first minutes following application to the cell, then may be endocytosed and in the presence of BFA become accumulated in BFA bodies (Bolte et al. 2004). We observed BFA bodies positive for both, HA3-TTN5-Alexa 488 and FM4-64 signals (Figure 4B). Similar patterns were observed for YFP-TTN5-derived signals in YFP-TTN5-expressing roots (Figure 4C). Hence, HA3-TTN5 and YFP-TTN5 can be present in similar subcellular membrane compartments."

We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):

„Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

*And we discuss in the Discussion section (starting Line 552): *

„We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."

• *

Without a cell wall label/dye, the plasmolysis data presented in Figure 5 is hard to visualize.

__Our response: __

Figure 6E-G (previously Fig. 5) show the results of plasmolysis experiments with YFP-TTN5 and the two mutant variant constructs. It is clearly possible to observe plasmolysis when focusing on the Hechtian strands. Hechtian strands are formed due to the retraction of the protoplast as a result of the osmotic pressure by the added mannitol solution. Hechtian strands consist of PM which remained in contact with the cell wall, visible as thin filamental structures. We stained the PM and the Hechtian strands by the PM dye FM4-64. This is similary done in Yoneda et al., 2020. We could detect in the YFP-TTN5-transformed cells, colocalization with the YFP channels and the PM dye in filamental structures between two neighbouring FM4-64-labelled PMs. Although an additional labeling of the cell wall may further indicate plasmolysis, it is not needed here.

Please consider that we will upload all original image data to BioImage Archive so that a detailed re-investigation of the images can be done.

• *

__Minor issues: __

In some of the presented N.benthamiana images, it looks like YFP-TTN5 may be partially ER-localised. However, co-localisation with an ER marker is not presented.

Our response:

*Referring to our response to comments 1 and 3 of reviewer 2 and to comment 1 of reviewer 1: *

We did not find evidence that HA3-TTN5 can localize at the ER using whole-mount immunostaining (NEW Figure 3P; NEW Figure 4A, B). Hence, we are careful with describing that fluorescence at the ER, as seen in the YFP-TTN5 line (Figure 3M, N) reflects TTN5 localization. We therefore do not focus the text on the ER pattern in the Result section (starting Line 295):

„Additionally, YFP signals were also detected in a net-like pattern typical for ER localization (Figure 3M, N). (...) We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

*And we discuss in the Discussion section (starting Line 552): *

„We based the TTN5 localization data on tagging approaches with two different detection methods to enhance reliability of specific protein detection. Even though YFP-TTN5 did not complement the embryo-lethality of a ttn5 loss of function mutant, we made several observations that suggest YFP-TTN5 signals to be meaningful at various membrane sites. We do not know why YFP-TTN5 does not complement. There could be differences in TTN5 levels and interactions in some cell types, which were hindering specifically YFP-TTN5 but not HA3-TTN5. (...) Though constitutively driven, the YFP-TTN5 expression may be delayed or insufficient at the early embryonic stages resulting in the lack of embryo-lethal complementation. On the other hand, the very fast nucleotide exchange activity may be hindered by the presence of a large YFP-tag in comparison with the small HA3-tag which is able to rescue the embryo-lethality. The lack of complementation represents a challenge for the localization of small GTPases with rapid nucleotide exchange in plants. Despite of these limitations, we made relevant observations in our data that made us believe that YFP signals in YFP-TTN5-expressing cells at membrane sites can be meaningful."

• *

There is some inconsistency within the N.benthamiana images. For example, compare Figure 4C of YFP-TTN5T30N to Figure 4O of YFP-TTN5T30N. Figure 4O is presented as being significant because wortmannin-induced swollen ARA7 compartments are labelled by YFP-TTN5T30N. However, structures very similar to these can already been seen in Figure 4C, which is apparently an unrelated experiment. This, to my mind, is likely a result of the very different expression levels between different cells that can be produced by transient expression in N.benthamiana.

__Our response: __

Former Figure 4 is now Figure 5. As detailed in our response to comment 2 of reviewer 1:

The reviewer certainly refers to fluorescence images from N. benthamiana leaf epidermal cells where different circularly shaped structures are visible. In these respective structures, the fluorescent circles are depleted from fluorescence in the center, e.g. in Figure 5C, YFP- fluorescent signals in TTN5T30N transformed leaf discs. We suspect that these structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al., 2020 for ANNI-GFP (reference in manuscript). The reviewer certainly does not refer to swollen MVBs that are seen following wortmannin treatment, as in Figure 5N-P, which look similar in their shape but are larger in size. Please note that we always included the control conditions, namely the images recorded before the wortmannin treatment, so that we were able to investigate the changes induced by wortmannin. Hence, we can clearly say that the structures with depleted fluorescence in the center as in Figure 5C are not wortmannin-induced swollen MVBs.To make these points clear to the reader, we added an explanation into the text (Line 385-388):

„We also observed YFP fluorescence signals in the form of circularly shaped ring structures with a fluorescence-depleted center. These structures can be of vacuolar origin as described for similar fluorescent rings in Tichá et al. (2020) for ANNI-GFP."

**Referees cross-commenting**

It sems that all of the reviewers have converged on the conclusion that the in planta characterisation of TTN5 is insufficient to be of substantial interest to the field, highlighting the fact that major improvements are required to strengthen this part of the manuscript and increase its relevance.

__Reviewer #2 (Significance (Required)): __

General assessment: the strengths of this work are in its in vitro characterisation of TITAN5, however, the in planta characterisation lacks depth.

Significance: the in vitro characterisation of TITAN5 is commendable as such work is lacking for plant GTPases. However, the significance of the work would be boosted substantially by better in planta characterisation, which is where most the most broad interest will lie.

My expertise: my expertise is in in planta characterisation of small GTPases and their interactors.

__Our response: __

We thank the reviewer for the kind evaluation of our manuscript. We are confident that the changes in the text and NEW Figures and NEW Supplementary Figures will be convincing to consider our work.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

Summary: Cellular traffic is an important and well-studied biological process in animal and plant systems. While components involved in transport are known the mechanism by which these components control activity or destination remains to be studied. A critical step in regulating traffic is proper budding and tethering of vesicles. A critical component in determining this step is a family proteins with GTPase activity, which act as switches facilitating vesicle interaction between proteins, or cytoskeleton. The current manuscript by Mohr and colleagues have characterized a small GTPase TITAN5 (TTN5) and identified two residues Gln70 and Thr30 in the protein which they propose to have functional roles. The authors catalogue the localization, GTP hydrolytic activity, and discuss putative functions of TTN5 and the mutants.

__Major comments: __

The core of the manuscript, which is descriptive characterization of TTN5, lies in reliably demonstrating putative roles. While the GTP hydrolysis rates are well-quantified (though the claims need to be toned down), the microscopy data especially the association of TTN5 with different endomembrane compartments is not convincing due to the quality (low resolution) of the figures submitted. The manuscript text is difficult to navigate due to repetition and inconsistency in the order that the mutants are referred. I am requesting additional experiments which should be feasible considering the authors have all the materials required to perform the experiments and obtain high-quality images which support their claims.

In general the figure quality needs to be improved for all microscopy images. I would suggest that the authors highlight 1-2 individual cells to make their point and use the current images as supplementary to establish a broader spread. __Our response: __

*We have worked substantially on the text and figures to make the content well comprehensive. The mutants are referred to in a consistent manner in the text and figures. We have addressed requested experiments. *

As we pointed out in the cover letter and our responses to reviewers 1 and 2, we will upload all raw image data to BioImage Archive upon acceptance of the manuscript so that they can be re-examined without any reduction of resolution. Furthermore, we have conducted new experiments on immunolocalization of HA3-TTN5 (NEW Figure 3P, NEW Figure 4A, B). The text has been improved in several places (see highlighted changes in the manuscript and as detailed in the responses to reviewer 1. We think, this addresses well the reviewers' concerns.

Fig. S1 lacks clarity. __Our response: __

Supplementary Figure S1 shows TTN5 gene expression in different organs and growing stages as revealed by transcriptomic data, made available through the AtGenExpress eFB tool of the Bio-Analytic Resource for Plant Biology (BAR). The figure visualizes that TTN5 is ubiquitously expressed in different plant organs and tissues, e.g. the epidermis layers that we investigated here, and throughout development including embryo development. In accordance with the embryo-lethal phenotype, this highlights well that TTN5* is needed throughout for plant growth and it emphasizes that our investigation of TTN5 localization in epidermis cells is valid. *

We have added a better description to the figure legend. We now also mention the respective publications from which the transcriptome data-sets are derived. The modified figure legend is:

"Supplementary Figure S1. Visualization of TTN5 gene expression levels during plant development based on transcriptome data. Expression levels in (A), different types of aerial organs at different developmental stages; from left to right and bottom to top are represented different seed and plant growth stages, flower development stages, different leaves, vegetative to inflorescence shoot apex, embryo and silique development stages; (B), seedling root tissues based on single cell analysis represented in form of a uniform manifold approximation and projection plot; (C), successive stages of embryo development. As shown in (A) to (C), TTN5 is ubiquitously expressed in these different plant organs and tissues. In particular, it should be noted that TTN5 transcripts were detectable in the epidermis cell layer of roots that we used for localization of tagged TTN5 protein in this study. In accordance with the embryo-lethal phenotype, the ubiquitous expression of TTN5 highlights its importance for plant growth. Original data were derived from (Nakabayashi et al. 2005, Schmid et al. 2005) (A); (Ryu et al. 2019) (B); (Waese et al. 2017) (C). Gene expression levels are indicated by local maximum color code, ranging from the minimum (no expression) in yellow to the maximum (highest expression) in red."

For the supplementary videos, it is difficult to determine if punctate structures are moving or is it cytoplasmic streaming? Could this be done with a co-localized marker? Considering that such markers have been used later in Fig. 4? __Our response: __

We had detected movement of YFP fluorescent structures in all analyzed YFP-TTN5 plant parts except the root tip. Movement of fluorescence signals in YFP-TTN5T30N seedlings was slowed in hypocotyl epidermis cells. To answer the reviewer comment, we added three NEW supplemental videos (NEW Supplementary Video Material S1M-O) generated with all the three YFP-TTN5 constructs imaged over time in N. benthamiana leaf epidermal cells upon colocalization with the cis-Golgi marker GmMan1-mCherry as requested by the reviewer. In these NEW videos, some of *the YFP fluorescent spots seem to move together with the Golgi stacks. GmMan1 is described with a stop-and-go directed movement mediated by the actino-myosin system (Nebenführ 1999) and similarly it might be the case for YFP-TTN5 signals based on the colocalization. *

• *

It would be good if the speed of movement is quantified, if the authors want to retain the current claims in results and the discussion. __Our response: __

*We describe a difference in the movement of YFP fluorescent signal for the YFP-TTN5T30N variant in the hypocotyl compared to YFP-TTN5 and YFP-TTN5Q70L. In hypocotyl cells, we could observe a slowed down or arrested movement specifically of YFP-TTN5T30N fluorescent structures, and we describe this in the Results section (Line 278-291). *

"Interestingly, the mobility of these punctate structures differed within the cells when the mutant YFP-TTN5T30N was observed in hypocotyl epidermis cells, but not in the leaf epidermis cells (Supplementary Video Material S1E, compare with S1B) nor was it the case for the YFP-TTN5Q70L mutant (Supplementary Video Material S1F, compare with S1E)."

*The slowed movement in the YFP-TTN5T30N mutant is well visible even without quantification. We checked that the manuscript text does not contain overstatements in this regard. *

• *

Fig.2 I am not sure what the unit / scale is in Fig. 2D/E if each parameter (Kon, Koff, and Kd) are individually plotted? Could the authors please clarify/simplify this panel?

__Our response: __

We presented kinetics for nucleotide association (kon) and dissociation (koff) and the dissociation constant (Kd) in a bar diagram for each nucleotide, mdGDP (Figure 2D) and mGppNHp (Figure 2E). We modified and relabeled the bar diagram representation. It should be now very clear which are the parameters and units. Please see also the other modified figures (NEW modified Figure 2A-H). We also modified the legend of Figure 2D and E:

"(D-E), Kinetics of association and dissociation of fluorescent nucleotides mdGDP (D) or mGppNHp (E) with TTN5 proteins (WT, TTN5T30N, TTN5Q70L) are illustrated as bar charts. The association of mdGDP (0.1 µM) or mGppNHp (0.1 µM) with increasing concentration of TTN5WT, TTN5T30N and TTN5Q70L was measured using a stopped-flow device (see A, B; data see Supplementary Figure S3A-F, S4A-E). Association rate constants (kon in µM-1s-1) were determined from the plot of increasing observed rate constants (kobs in s-1) against the corresponding concentrations of the TTN5 proteins. Intrinsic dissociation rates (koff in s-1) were determined by rapidly mixing 0.1 µM mdGDP-bound or mGppNHp-bound TTN5 proteins with the excess amount of unlabeled GDP (see A, C, data see Supplementary Figure S3G-I, S4F-H). The nucleotide affinity (dissociation constant or Kd in µM) of the corresponding TTN5 proteins was calculated by dividing koff by kon. When mixing mGppNHp with nucleotide-free TTN5T30N, no binding was observed (n.b.o.) under these experimental conditions."

• *

Are panels D and E representing values for mdGDP and GppNHP? This is not very clear from the figure legend.

__Our response: __

Yes, Figure 2D and E represent the kon, koff and Kd values for mdGDP (Figure 2D) and mGppNHP (Figure 2E). As detailed in our previous response to comment 2a, we modified figure and figure legend to make the representation more clear.

• *

Fig. 3 Same comments as in para above - improve resolution fo images, concentrate on a few selected cells, if required use an inset figure to zoom-in to specific compartments. Our response:

As detailed in our responses to reviewers 1 and 2, we will upload all original image data to BioImage Archive upon acceptance of the manuscript, so that a detailed investigation of all our images is possible without any reduction of resolution.

Please provide the non-fluorescent channel images to understand cell topography __Our response: __

*We presented our microscopic images with the respective fluorescent channel and for colocalization with an additional merge. We did not present brightfield images as the cell topography was already well visible by fluorescent signal close to the PM. Therefore, brightfield images would not provide any benefit. Since we will upload all original data to BioImage Archive for a detailed investigation of all our images, the data can be obtained if needed. *

Is the nuclear localization seen in transient expression (panel L-N) an artefact? If so, this needs to be mentioned in the text. Our response:

As explained in our responses to reviewers 1 and 2, fluorescence signals were detected within the nuclei of root cells of YFP-TTN5 plants, while immunostaining signals of HA3-TTN5 were not detected in the nucleus.

In an α-GFP Western blot using YFP-TTN5 Arabidopsis seedlings, we detected besides the expected and strong 48 kDa YFP-TTN5 band, three additional weak bands ranging between 26 to 35 kDa (NEW Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins expressed from aberrant transcripts. α-HA Western blot controls performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size (Supplementary Figure S7D). We must therefore be cautious about nuclear TTN5 localization and we rephrased the text carefully (starting Line 300):

„We also found multiple YFP bands in α-GFP Western blot analysis using YFP-TTN5 Arabidopsis seedlings. Besides the expected and strong 48 kDa YFP-TTN5 band, we observed three weak bands ranging between 26 to 35 kDa (Supplementary Figure S7C). We cannot explain the presence of these small protein bands. They might correspond to free YFP, to proteolytic products or potentially to proteins produced from aberrant transcripts with perhaps alternative translation start or stop sites. On the other side, a triple hemagglutinin-tagged HA3-TTN5 driven by the 35S promoter did complement the embryo-lethal phenotype of ttn5-1 (Supplementary Figure S7D, E). α-HA Western blot control performed with plant material from HA3-TTN5 seedlings showed a single band at the correct size, but no band that was 13 to 18 kDa smaller (Supplementary Figure S7D). (...) We did not observe any staining in nuclei or ER when performing HA3-TTN5 immunostaining (Figure 3P; Figure 4A, B), as was the case for fluorescence signals in YFP-TTN5-expressing cells. Presumably, this can indicate that either the nuclear and ER signals seen with YFP-TTN5 correspond to the smaller proteins detected, as described above, or that immunostaining was not suited to detect them. Hence, we focused interpretation on patterns of localization overlapping between the fluorescence staining with YFP-labeled TTN5 and with HA3-TTN5 immunostaining, such as the particular signal patterns in the specific punctate membrane structures."

Fig. 4 - In addition to the points made for Fig. 3 The authors should consider reducing gain/exposure to improve image clarity. Especially for the punctate structures, which are difficult to observe in TTN5, likely because of the cytoplasmic localization as well.

__Our response: __

Thank you for this comment. We record image z-stacks and represent in single z-planes. Reducing the gain to decrease the cytoplasmic signal does not increase the clarity of the punctate structures as the signal strength will become weak.. As mentioned above, we will upload all original image data to BioImage Archive for a detailed investigation of all our images without any reduction of resolution.

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Reducing Agrobacterial load could be considered. OD of 0.4 is a bit much, 0.1 or even 0.05 could be tried. If available try expression in N. tabaccum, which is more amenable to microscopy. However, this is OPTIONAL, benthamiana should suffice. __Our response: __

Thank you for the suggestion. We are routinely using N. benthamiana leaf infiltration. When setting up this method at first, we did not observe different localization results by using different ODs of bacterial cultures. Hence, an OD600 of 0.4 is routinely used in our institute. This value is comparable with the literature although some literature reports even higher OD values for infiltration (Norkunas et al., 2018; Drapal et al., 2021; Zhang et al., 2020, Davis et al., 2020; Stephenson et al., 2018).

A standard norm now is to establish the level of colocalization is by quantifying a pearson's or Mander's correlation. Which I believe has been done in the text, I didn't find a plot representing the same? Could the data (which the authors already have) be plotted alongwith "n" as a table or graph? __Our response: __

*Please check our response to reviewer 1, comment 4. *

We like to insist that we performed colocalization very carefully and quantified the data in three different manners. We like to state that there is no general standardized procedure that best suits the idea of a colocalization pattern. Results of colocalization are represented in stem diagrams and table format, including statistical analysis. Colocalization was carried out with the ImageJ plugin JACoP for Pearson's and Overlap coefficients and based on the centroid method. The plotted Pearson's and Overlap coefficients are presented in bar diagrams in Supplementary Figure S8A and C, including statistics. The obtained values by the centroid method are represented in table format in Supplementary Figure S8B and D, which *can be considered a standard method (see Ivanov et al., 2014). *

Colocalization of two different fluorescence signals was performed for the two channels in a specific chosen region of interest (indicating in % the overlapping signal versus the sum of signal for each channel). The differences between the YFP/mRFP and mRFP/YFP ratios indicate that a higher percentage of ARA7-RFP signal is colocalizing with YFP-TTN5Q70L signal than with the TTN5WT or the TTN5T30N mutant form signals, while the YFP signals have a similar overlap with ARA7-positive structures. This is not a contradiction. Presumably this answers well the questions on colocalization.

Please note that upon acceptance for publication, we will upload all original colocalization data to BioImage Archive. Hence, the high-quality data can be reanalyzed by readers.

The cartoons for the action of chemicals are useful, but need a bit more clarity. Our response:

The schematic explanations of pharmacological treatments and expected outcomes are useful to readers. For a better understanding, we added additional explaining sentences to the figure legends (Figure 5E, M; Figure 6A). We also modified Figure 6A and the corresponding legend.

"(E), Schematic representation of GmMan1 localization at the ER upon brefeldin A (BFA) treatment. BFA blocks ARF-GEF proteins which leads to a loss of Golgi cis-cisternae and the formation of BFA-induced compartments due to an accumulation of Golgi stacks up to a redistribution of the Golgi to the ER by fusion of the Golgi with the ER (Renna and Brandizzi 2020)."

"(M), Schematic representation of ARA7 localization in swollen MVBs upon wortmannin treatment. Wortmannin inhibits phosphatidylinositol-3-kinase (PI3K) function leading to the fusion of TGN/EE to swollen MVBs (Renna and Brandizzi 2020)."

"(A), Schematic representation of progressive stages of FM4-64 localization and internalization in a cell. FM4-64 is a lipophilic substance. After infiltration, it first localizes in the plasma membrane, at later stages it localizes to intracellular vesicles and membrane compartments. This localization pattern reflects the endocytosis process (Bolte et al. 2004)."

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Fig. 5 does the Q70L mutant show reduced endocytosis ?

__Our response: __

We have not investigated this question. As detailed in our response to reviewer 1, *we like to emphasize that we agree fully that functional evidences are interesting to assign role for TTN5 in trafficking steps. A phenotype associated with TTN5T30N and TTN5Q70L would be clearly meaningful. *

Concerning the aspect of colocalization of the mutants with the markers we show in Figure 5C, D and G, H that YFP-TTN5T30N- and YFP-TTN5Q70L-related signals colocalize with the Golgi marker GmMan1-mCherry. Figure 5K, L and O, P show that YFP-TTN5T30N and YFP-TTN5Q70L-related signals can colocalize with the MVB marker, and this may affect relevant vesicle trafficking processes and plasma membrane protein regulation involved in root cell elongation.

*At present, we have not yet investigated perturbed cargo trafficking. These aspects are certainly interesting but require extensive work and testing of appropriate physiological conditions and appropriate cargo targets. We discuss future perspectives in the Discussion. We agree that such functional information is of great importance, but needs to be clarified in future studies. *

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The main text needs to be organized in a way that a reader can separate what is the hypothesis/assumption from actual results and conclusions (see lines #143-149).

Our response:

*Thank you for this comment. We reformulated text throughout the manuscript. *

The text is repeated in multiple places, while I understand that this is not plagiarism, the repetitiveness makes it difficult to read and understand the text. I highlight a couple of examples here, but please check the whole text thoroughly and edit/delete as necessary. a. Lines #124-125 with Lines #149-151 Lines #140-143

__Our response: __

*We checked the text and removed unnecessary repetitions. *

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• Could the authors elaborate on whether there are plan homologs of TTN5? Also, have other ARF/ARLs been compared to TTN5 beyond HsARF1? *

Our response:

Phylogenetic trees of the ARF family in Arabidopsis in comparison to human ARF family were already published by Vernoud et al. (2003). In this phylogenetic tree ARF, ARL and SAR proteins of Arabidopsis are compared with the members in humans and S. cervisiae. It is difficult to deduce whether the proteins are homologs or orthologs. In this setting, an ortholog of TTN5 may be HsARL2 followed by HsARL3. In Figure 1A we represented some human GTPases as closely related in sequence to TTN5, these are HsARL2, HsARF1 and AtARF1 since they are the best studied ARF GTPases. HRAS is a well-known member of the RAS superfamily which we used for kinetic comparison in Figure 2. We additionally compared published kinetics of RAC1, HsARF3, *CDC42, RHOA, ARF6, RAD, GEM, and RAS GTPases. *

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On a related note, a major problem I have with these kinetic values is the assumption of significance or not. For eg. Line#180 the values represent and 2 and 6-fold increase, if these numbers do not matter can a significance threshold be applied so as to understand how much fold-change is appreciable?

Our response:

The kinetics of TTN5 and its two mutant variants can be compared with those of other studied GTPases. To provide a basis for the statements about differences in GTPase activities, we modified the text and added respective references in the text for comparisons of fold changes.

The new text is now as follows Line 175-231):

„ We next measured the dissociation (koff) of mdGDP and mGppNHp from the TTN5 proteins in the presence of excess amounts of GDP and GppNHp, respectively (Figure 2C) and found interesting differences (Figure 2D, E; Supplementary Figures S3G-I, S4F-H). First, TTN5WT showed a koff value (0.012 s-1 for mGDP) (Figure 2D; Supplementary Figure S3G), which was 100-fold faster than those obtained for classical small GTPases, including RAC1 (Haeusler et al. 2006)and HRAS (Gremer et al. 2011), but very similar to the koff value of HsARF3 (Fasano et al. 2022). Second, the koffvalues for mGDP and mGppNHp, respectively, were in a similar range between TTN5WT (0.012 s-1 mGDP and 0.001 s-1mGppNHp) and TTN5Q70L (0.025 s-1 mGDP and 0.006 s-1 mGppNHp), respectively, but the koff values differed 10-fold between the two nucleotides mGDP and mGppNHp in TTN5WT (koff = 0.012 s-1 versus koff = 0.001 s-1; Figure 2D, E; Supplementary Figure S3G, I, S4F, H). Thus, mGDP dissociated from proteins 10-fold faster than mGppNHp. Third, the mGDP dissociation from TTN5T30N (koff = 0.149 s-1) was 12.5-fold faster than that of TTN5WT and 37-fold faster than the mGppNHp dissociation of TTN5T30N (koff = 0.004 s-1) (Figure 2D, E; Supplementary Figure S3H, S4G). Mutants of CDC42, RAC1, RHOA, ARF6, RAD, GEM and RAS GTPases, equivalent to TTN5T30N, display decreased nucleotide binding affinity and therefore tend to remain in a nucleotide-free state in a complex with their cognate GEFs (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). Since TTN5T30N exhibits fast guanine nucleotide dissociation, these results suggest that TTN5T30N may also act in either a dominant-negative or fast-cycling manner as reported for other GTPase mutants (Fiegen et al. 2004, Wang et al. 2005, Fidyk et al. 2006, Klein et al. 2006, Soh and Low 2008, Sugawara et al. 2019, Aspenström 2020).

The dissociation constant (Kd) is calculated from the ratio koff/kon, which inversely indicates the affinity of the interaction between proteins and nucleotides (the higher Kd, the lower affinity). Interestingly, TTN5WT binds mGppNHp (Kd = 0.029 µM) 10-fold tighter than mGDP (Kd = 0.267 µM), a difference, which was not observed for TTN5Q70L (Kd for mGppNHp = 0.026 µM, Kd for mGDP = 0.061 µM) (Figure 2D, E). The lower affinity of TTN5WT for mdGDP compared to mGppNHp brings us one step closer to the hypothesis that classifies TTN5 as a non-classical GTPase with a tendency to accumulate in the active (GTP-bound) state (Jaiswal et al. 2013). The Kd value for the mGDP interaction with TTN5T30N was 11.5-fold higher (3.091 µM) than for TTN5WT, suggesting that this mutant exhibited faster nucleotide exchange and lower affinity for nucleotides than TTN5WT. Similar as other GTPases with a T30N exchange, TTN5T30Nmay behave in a dominant-negative manner in signal transduction (Vanoni et al. 1999).

To get hints on the functionalities of TTN5 during the complete GTPase cycle, it was crucial to determine its ability to hydrolyze GTP. Accordingly, the catalytic rate of the intrinsic GTP hydrolysis reaction, defined as kcat, was determined by incubating 100 µM GTP-bound TTN5 proteins at 25{degree sign}C and analyzing the samples at various time points using a reversed-phase HPLC column (Figure 2F; Supplementary Figure S5). The determined kcat values were quite remarkable in two respects (Figure 2G). First, all three TTN5 proteins, TTN5WT, TTN5T30N and TTN5Q70L, showed quite similar kcatvalues (0.0015 s-1, 0.0012 s-1, 0.0007 s-1; Figure 2G; Supplementary Figure S5). The GTP hydrolysis activity of TTN5Q70L was quite high (0.0007 s-1). This was unexpected because, as with most other GTPases, the glutamine mutations at the corresponding position drastic impair hydrolysis, resulting in a constitutively active GTPase in cells (Hodge et al. 2020, Matsumoto et al. 2021). Second, the kcat value of TTN5WT (0.0015 s-1) although quite low as compared to other GTPases (Jian et al. 2012, Esposito et al. 2019), was 8-fold lower than the determined koff value for mGDP dissociation (0.012 s-1) (Figure 2E). This means that a fast intrinsic GDP/GTP exchange versus a slow GTP hydrolysis can have drastic effects on TTN5 activity in resting cells, since TTN5 can accumulate in its GTP-bound form, unlike the classical GTPase (Jaiswal et al. 2013). To investigate this scenario, we pulled down GST-TTN5 protein from bacterial lysates in the presence of an excess amount of GppNHp in the buffer using glutathione beads and measured the nucleotide-bound form of GST-TTN5 using HPLC. As shown in Figure 2H, isolated GST-TTN5 increasingly bonds GppNHp, indicating that the bound nucleotide is rapidly exchanged for free nucleotide (in this case GppNHp). This is not the case for classical GTPases, which remain in their inactive GDP-bound forms under the same experimental conditions (Walsh et al. 2019, Hodge et al. 2020)."

Another issue with the kinetic measurements is the significance levels. Line #198-201. The three proteins are claimed to have similar values and in the nnext line, the Q70L mutant is claimed to be high.

Our response:

Please see our response and changes in the text according in our response to the previous comment 9. We have provided extra explanations and references to clarify why the kinetic behavior of TTN5 is unusual in several respects (Line 215-220).

„First, all three TTN5 proteins, TTN5WT, TTN5T30N and TTN5Q70L, showed quite similar kcat values (0.0015 s-1, 0.0012 s-1, 0.0007 s-1; Figure 2G; Supplementary Figure S5). The GTP hydrolysis activity of TTN5Q70L was quite high (0.0007 s-1). This was unexpected because, as with most other GTPases, the glutamine mutations at the corresponding position drastic impair hydrolysis, resulting in a constitutively active GTPase in cells (Hodge et al. 2020, Matsumoto et al. 2021)."

Provide data for conclusion in line#214-215

Our response:

We agree that a reference should be added after this sentence to make this sentence clearer (Line 228-231).

"As shown in Figure 2H, isolated GST-TTN5 increasingly bonds GppNHp, indicating that the bound nucleotide is rapidly exchanged for free nucleotide (in this case GppNHp). This is not the case for classical GTPases, which remain in their inactive GDP-bound forms under the same experimental conditions (Walsh et al. 2019, Hodge et al. 2020)."

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How were the mutants studied here identified? random mutation or was it directed based on qualified assumptions?

__Our response: __

We used the T30N and the Q70L point mutations as such types of mutants had been reported to confer specific phenotypes in these well-conserved amino acid positions in multiple other small GTPases (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). In particular, these positions affect the interaction between small GTPases and their respective guanine nucleotide exchange factor (GEF; T30N) or on GTP hydrolysis (Q70L). We introduced the mutants and described their potential effect on the GTPase cycle in the introduction and cited exemplary literature. Please see also our response to comment 6 and the proposed text changes (Line 142-151).

Could more simplification be provided for deifitinition of Kon/Koff values. And can these values be compared between mutants directly?

__Our response: __

*We introduce kon and koff in the modified Figure 2D, E, and they are described in the figure legends. Moreover, we present the data for calculations in Supplementary Figures S3, 4, where again we define the values in the respective figure legends. *

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Data provided are not convincing to claim that both the mutant forms have lower association with the Golgi.

__Our response: __

*Our conclusion is that both YFP-TTN5 and YFP-TTN5Q70L fluorescence signals tend to colocalize more with the Golgi-marker signals compared to YFP-TTN5T30N signals as deduced from the centroid-based colocalization method (Line 404-405). *

"Hence, the GTPase-active TTN5 forms are likely more present at cis-Golgi stacks compared to TTN5T30N."

The Pearson coefficients of all three YFP-TTN5 constructs were nearly identical, but we could identify differences in overlapping centers between the YFP and mCherry channel. 48 % of the GmMan1-mCherry fluorescent cis-Golgi stacks were overlapping with signal of YFP-TTN5Q70L, while for YFP-TTN5T30N an overlap of only 31 % was detected. This means that less cis*-Golgi stacks colocalized with signals in the YFP-TTN5T30N mutant than in YFP-TTN5Q70L, which is the statement in our manuscript. *

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IN general the Authors should strongly consider the claims made in the manuscript. For eg. "This study lays the foundation for studying the functional relationships of this small GTPase" (line 125) is unqualified as this is true for every protein ever studied and published. Considering that TTN was not isolated/identified in this study for the first time this claim doesn't stand.

__Our response: __

*We reformulated the sentence (Line 123-124). *

"This study paves the way towards future investigation of the cellular and physiological contexts in which this small GTPase is functional."

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Line #185 - "characterestics of a dominant-negative...." What is this based on? From the text it is not clear what are the paremeters. Considering that no complementation phenotypes have been presented, this is a far-fetched claim Our response:

Small GTPases in general are a well studied protein family and the here used mutations T30N and Q70L are conserved amino acids and commonly used for the characterization of the Ras superfamily members. We added explaining sentences with references to the text. The characteristics referred to in the above paragraph is based on the kinetic study.

We modified the text as follows (Line 186-197 ):

„Third, the mGDP dissociation from TTN5T30N (koff = 0.149 s-1) was 12.5-fold faster than that of TTN5WT and 37-fold faster than the mGppNHp dissociation of TTN5T30N (koff = 0.004 s-1) (Figure 2D, E; Supplementary Figure S3H, S4G). Mutants of CDC42, RAC1, RHOA, ARF6, RAD, GEM and RAS GTPases, equivalent to TTN5T30N, display decreased nucleotide binding affinity and therefore tend to remain in a nucleotide-free state in a complex with their cognate GEFs (Erickson et al. 1997, Ghosh et al. 1999, Radhakrishna et al. 1999, Jung and Rösner 2002, Kuemmerle and Zhou 2002, Wittmann et al. 2003, Nassar et al. 2010, Huang et al. 2013, Chang and Colecraft 2015, Fisher et al. 2020, Shirazi et al. 2020). Since TTN5T30N exhibits fast guanine nucleotide dissociation, these results suggest that TTN5T30N may also act in either a dominant-negative or fast-cycling manner as reported for other GTPase mutants (Fiegen et al. 2004, Wang et al. 2005, Fidyk et al. 2006, Klein et al. 2006, Soh and Low 2008, Sugawara et al. 2019, Aspenström 2020)."

The claims in Line #224-227 are exaggerated. Please tone down or delete __Our response: __

*We rephrased the sentence (Line 240-243). *

"Therefore, we propose that TTN5 exhibits the typical functions of a small GTPase based on in vitro biochemical activity studies, including guanine nucleotide association and dissociation, but emphasizes its divergence among the ARF GTPases by its kinetics."

Line#488-489 - This conclusion is not really supported. At best Authors can claim that TTN5 is associated with trafficking components, but the functional relevance of this association is not determined. Our response:

*We toned down our statement (Line 604-608). *

„The colocalization of FM4-64-labeled endocytosed vesicles with fluorescence in YFP-TTN5-expressing cells may indicate that TTN5 is involved in endocytosis and the possible degradation pathway into the vacuole. Our data on colocalization with the different markers support the hypothesis that TTN5 may have functions in vesicle trafficking."

__Minor comments: __

Line #95 - " This rolein vesicle....." - please clarify which role? Our response:

We rephrased the sentence (Line 96-99).

„These roles of ARF1 and SAR1 in COPI and II vesicle formation within the endomembrane system are well conserved in eukaryotes which raises the question of whether other plant ARF members are also involved in functioning of the endomembrane system."

Line #168 - "we did not observed" please change to "not able to measure/quantify" __Our response: __

*We changed the text accordingly (Line 169-171). *

„A remarkable observation was that we were not able to monitor the kinetics of mGppNHp association with TTN5T30N but observed its dissociation (koff = 0.026 s-1; Figure 2E)."

Line#179 - ARF# is human for Arabidopsis?

Our response:

*The study of Fasano et al., 2022 is based on human ARF3 and we added the information to the text (Line 180-181) *

"(...) very similar to the koff value of HsARF3 (Fasano et al. 2022)."

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Line #181 - compared to what is the 10-fold difference?

__Our response: __

The 10-fold difference is between the nucleotides mGDP and mGppNHp, for both TTN5WT and TTN5Q70L. We added the information on specific nucleotides to this sentence for a better understanding (Line 181-185).

„Second, the koff values for mGDP and mGppNHp, respectively, were in a similar range between TTN5WT (0.012 s-1mGDP and 0.001 s-1 mGppNHp) and TTN5Q70L (0.025 s-1 mGDP and 0.006 s-1 mGppNHp), respectively, but the koffvalues differed 10-fold between the two nucleotides mGDP and mGppNHp in TTN5WT (koff = 0.012 s-1 versus koff = 0.001 s-1; Figure 2D, E; Supplementary Figure S3G, I, S4F, H)."

Lines #314-323 - are diffciult to understand, consider reframing. Same goes for the conclusion following these lines.

__Our response: __

We added an explanation to these sentences for a better understanding (Line 392-405).

„We performed an additional object-based analysis to compare overlapping YFP fluorescence signals in YFP-TTN5-expressing leaves with GmMan1-mCherry signals (YFP/mCherry ratio) and vice versa (mCherry/YFP ratio). We detected 24 % overlapping YFP- fluorescence signals for TTN5 with Golgi stacks, while in YFP-TTN5T30N and YFP-TTN5Q70L-expressing leaves, signals only shared 16 and 15 % overlap with GmMan1-mCherry-positive Golgi stacks (Supplementary Figure S8B). Some YFP-signals did not colocalize with the GmMan1 marker. This effect appeared more prominent in leaves expressing YFP-TTN5T30N and less for YFP-TTN5Q70L, compared to YFP-TTN5 (Figure 5B-D). Indeed, we identified 48 % GmMan1-mCherry signal overlapping with YFP-positive structures in YFP-TTN5Q70L leaves, whereas 43 and only 31 % were present with YFP fluorescence signals in YFP-TTN5 and YFP-TTN5T30N-expressing leaves, respectively (Supplementary Figure S8B), indicating a smaller amount of GmMan1-positive Golgi stacks colocalizing with YFP signals for YFP-TTN5T30N. Hence, the GTPase-active TTN5 forms are likely more present at cis-Golgi stacks compared to TTN5T30N."

Authors might consider a longer BFA treatment (3-4h) to see more clearer ER-Golgi fusion (BFA bodies)

__Our response: __

We perforned addtional BFA treatments for HA3-TTN5-expressing Arabidopsis seedlings followed by whole-mount immunostaining and for YFP-TTN5-expressing Arabidopsis lines. In both experiments we could obtain the typical BFA bodies. We included the NEW data in NEW Figure 4B, C

**Referees cross-commenting**

I agree with both my co-reviewers that the manuscript needs substantial improvement in its cell biology based experiments and conclusions thereof. I think the concensus of all reviewers points to weakness in the in-planta experiments which needs to be addressed to understand and characterize TTN5, which is the main goal of the manuscript.

Reviewer #3 (Significance (Required)):

Significance: The manuscript has general significance in understanding the role of small GTPases which are understudied. Although the manuscript does not advance the field of either intracellular trafficking or organization it holds significance in attempting to characterize proteins involved, which is a prerequisite for further functional studies.

__Our response: __

Thank you for your detailed analysis of our manuscript and positive assessment. Our study is an advance in the plant vesicle trafficking field.