This reminds me of how we have been talking about writing to meet the status quo of the perfect paper.

I am currently watching an episode of Gilmore Girls where one of the main characters bright up the question of how commonly used catch phrases can be used a plagiarism. Sometimes I live in fear of committing plagiarism. Sometimes a thought comes into my mind and I get nervous I read/heard it somewhere then I will get flagged for plagiarism. At times I worry more about the sources being peer reviewed or is it in MLA/APA format, more than the actual paper. It is hard to know what is/isn't plagiarism.

Return sentence is a great way of writing and I will make sure to use that in my next essay. Also, other template are very useful and give me a better understanding to what the writer try to teach us.

I like to use a statistic at the beginning of my essay because I think it grab people attention and make them curious about the rest of the essay.

A writers should know their audience and work to make them engage and not lost during the speech. Also, it is better to give each information on the right time to make the audience comfortable about what we are saying.

It is important to show why are you bringing other words and how it really helps you introducing your points.

Please note that I corrected the typos here. Alvin

eLife Assessment

This important paper demonstrates that different PKA subtypes exhibit distinct subcellular localization at rest in CA1 neurons. The authors provide compelling evidence that when all tested PKA subtypes are activated by norepinephrine, catalytic subunits translocate to dendritic spines but regulatory subunits remain unmoved. Furthermore, PKA-dependent regulation of synaptic plasticity and transmission can be supported only by wildtype, dissociable PKA, but not by inseparable PKA.

Reviewer #1 (Public review):

Summary:

This is a short self-contained study with a straightforward and interesting message. The paper focuses on settling whether PKA activation requires dissociation of the catalytic and regulatory subunits. This debate has been ongoing for ~ 30 years, with renewed interest in the question following a publication in Science, 2017 (Smith et al.). Here, Xiong et al demonstrate that fusing the R and C subunits together (in the same way as Smith et al) prevents the proper function of PKA in neurons. This provides further support for the dissociative activation model - it is imperative that researchers have clarity on this topic since it is so fundamental to building accurate models of localised cAMP signalling in all cell types. Furthermore, their experiments highlight that C subunit dissociation into spines is essential for structural LTP, which is an interesting finding in itself. They also show that preventing C subunit dissociation reduces basal AMPA receptor currents to the same extent as knocking down the C subunit. Overall, the paper will interest both cAMP researchers and scientists interested in fundamental mechanisms of synaptic regulation.

Strengths:

The experiments are technically challenging and well executed. Good use of control conditions e.g untransfected controls in Figure 4.

Weaknesses:

The novelty is lessened given the same team has shown dissociation of the C subunit into dendritic spines from RIIbeta subunits localised to dendritic shafts before (Tillo et al., 2017). Nevertheless, the experiments with RII-C fusion proteins are novel and an important addition.

Reviewer #2 (Public review):

Summary:

PKA is a major signaling protein which has been long studied and is vital for synaptic plasticity. Here, the authors examine the mechanism of PKA activity and specifically focus on addressing the question of PKA dissociation as a major mode of its activation in dendritic spines. This would potentially allow to determine the precise mechanisms of PKA activation and address how it maintains spatial and temporal signaling specificity.

Strengths:

The results convincingly show that PKA activity is governed by the subcellular localization in dendrites and spines and is mediated via subunit dissociation. The authors make use of organotypic hippocampal slice cultures, where they use pharmacology, glutamate uncaging, and electrophysiological recordings.

Overall, the experiments and data presented are well executed. The experiments all show that at least in the case of synaptic activity, distribution of PKA-C to dendritic spines is necessary and sufficient for PKA mediated functional and structural plasticity.<br /> The authors were able to persuasively support their claim that PKA subunit dissociation is necessary for its function and localization in dendritic spines. This conclusion is important to better understand the mechanisms of PKA activity and its role in synaptic plasticity.

Weaknesses:

While the experiments are indeed convincing and well executed, the data presented is similar to previously published work from the Zhong lab (Tillo et al., 2017, Zhong et al 2009). This reduces the novelty of the findings in terms of re-distribution of PKA subunits, which was already established, at least to some degree.

Reviewer #3 (Public review):

Summary:

Xiong et al. investigated the debated mechanism of PKA activation using hippocampal CA1 neurons under pharmacological and synaptic stimulations. Examining all major PKA-R isoforms in these neurons, they found that a portion of PKA-C dissociates from PKA-R and translocate into dendritic spines following norepinephrine bath application. Additionally, their use of a non-dissociable form of PKA demonstrates its essential role in structural long-term potentiation (LTP) induced by two-photon glutamate uncaging, as well as in maintaining normal synaptic transmission, as verified by electrophysiology. This study presents a valuable finding on the activation-dependent re-distribution of PKA catalytic subunits in CA1 neurons, a process vital for synaptic functionality. The robust evidence provided by the authors makes this work particularly relevant for biologists seeking to understand PKA activation mechanisms, its downstream effects, and synaptic plasticity.

Strengths:

The study is methodologically robust, particularly in the application of two-photon imaging and electrophysiology. The experiments are well-designed with effective controls and a comprehensive analysis. The credibility of the data is further enhanced by the research team's previous works in related experiments. The study provides sufficient evidence to support the classical model of PKA activation via dissociation in neurons.

Weaknesses:

No specific weaknesses are noted in the current study; future research could provide additional insights by exploring PKA dissociation under varied physiological conditions, particularly in vivo, to further validate and expand upon these findings.

Author response:

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

New Experiments

(1) Activation-dependent dynamics of PKA with the RIα regulatory subunit, adding to the answer to Reviewers 1 and 2. To determine the dynamics of all PKA isoforms, we have added experiments that used PKA-RIα as the regulatory subunit. We found differential translocation between PKA-C (co-expressed with PKA-RIα) and PKA-RIα (Figure 1–figure supplement 3), similar to the results when PKA-RIIα or PKA-RIβ was used.

(2) PKA-C dynamics elicited by a low concentration of norepinephrine, addressing Reviewer 3’s comment. We have found that PKA-C (co-expressed with RIIα) exhibited similar translocation into dendritic spines in the presence of a 5x lowered concentration (2 μM) of norepinephrine, suggesting that the translocation occurs over a wide range of stimulus strengths (Figure 1-figure supplement 2).

Reviewer #1 (Public Review):

Summary:

This is a short self-contained study with a straightforward and interesting message. The paper focuses on settling whether PKA activation requires dissociation of the catalytic and regulatory subunits. This debate has been ongoing for ~ 30 years, with renewed interest in the question following a publication in Science, 2017 (Smith et al.). Here, Xiong et al demonstrate that fusing the R and C subunits together (in the same way as Smith et al) prevents the proper function of PKA in neurons. This provides further support for the dissociative activation model - it is imperative that researchers have clarity on this topic since it is so fundamental to building accurate models of localised cAMP signalling in all cell types. Furthermore, their experiments highlight that C subunit dissociation into spines is essential for structural LTP, which is an interesting finding in itself. They also show that preventing C subunit dissociation reduces basal AMPA receptor currents to the same extent as knocking down the C subunit. Overall, the paper will interest both cAMP researchers and scientists interested in fundamental mechanisms of synaptic regulation.

Strengths:

The experiments are technically challenging and well executed. Good use of control conditions e.g untransfected controls in Figure 4.

We thank the reviewer for their accurate summarization of the position of the study in the field and for the positive evaluation of our study.

Weaknesses:

The novelty is lessened given the same team has shown dissociation of the C subunit into dendritic spines from RIIbeta subunits localised to dendritic shafts before (Tillo et al., 2017). Nevertheless, the experiments with RII-C fusion proteins are novel and an important addition.

We thank the reviewer for noticing our earlier work. The first part of the current work is indeed an extension of previous work, as we have articulated in the manuscript. However, this extension is important because recent studies suggested that the majority of PKA-RIIβ are axonal localized. The primary PKA subtypes in the soma and dendrite are likely PKA-RIβ or PKA-RIIα. Although it is conceivable that the results from PKA-RIIβ can be extended to the other subunits, given the current debate in the field regarding PKA dissociation (or not), it remains important to conclusively demonstrate that these other regulatory subunit types also support PKA dissociation within intact cells in response to a physiological stimulant. To complete the survey for all PKA-R isoforms, we have now added data for PKA-RIα (New Experiment #1), as they are also expressed in the brain (e.g., https://www.ncbi.nlm.nih.gov/gene/5573). Additionally, as the reviewer points out, our second part is a novel addition to the literature.

Reviewer #2 (Public Review):

Summary:

PKA is a major signaling protein that has been long studied and is vital for synaptic plasticity. Here, the authors examine the mechanism of PKA activity and specifically focus on addressing the question of PKA dissociation as a major mode of its activation in dendritic spines. This would potentially allow us to determine the precise mechanisms of PKA activation and address how it maintains spatial and temporal signaling specificity.

Strengths:

The results convincingly show that PKA activity is governed by the subcellular localization in dendrites and spines and is mediated via subunit dissociation. The authors make use of organotypic hippocampal slice cultures, where they use pharmacology, glutamate uncaging, and electrophysiological recordings.

Overall, the experiments and data presented are well executed. The experiments all show that at least in the case of synaptic activity, the distribution of PKA-C to dendritic spines is necessary and sufficient for PKA-mediated functional and structural plasticity.

The authors were able to persuasively support their claim that PKA subunit dissociation is necessary for its function and localization in dendritic spines. This conclusion is important to better understand the mechanisms of PKA activity and its role in synaptic plasticity.

We thank the reviewer for their positive evaluation of our study.

Weaknesses:

While the experiments are indeed convincing and well executed, the data presented is similar to previously published work from the Zhong lab (Tillo et al., 2017, Zhong et al 2009). This reduces the novelty of the findings in terms of re-distribution of PKA subunits, which was already established. A few alternative approaches for addressing this question: targeting localization of endogenous PKA, addressing its synaptic distribution, or even impairing within intact neuronal circuits, would highly strengthen their findings. This would allow us to further substantiate the synaptic localization and re-distribution mechanism of PKA as a critical regulator of synaptic structure, function, and plasticity.

We thank the reviewer for noticing our earlier work. The first part of the current work is indeed an extension of previous work, as we have articulated in the manuscript. However, this extension is important because recent studies suggested that the majority of PKA-RIIβ are axonal localized. The primary PKA subtypes in the soma and dendrite are likely PKA-RIβ or PKA-RIIα. Although it is conceivable that the results from PKA-RIIβ can be extended to the other subunits, given the current debate in the field regarding PKA dissociation (or not), it remains important to conclusively demonstrate that these other regulatory subunit types also support PKA dissociation within intact cells in response to a physiological stimulant. To complete the survey for all PKA-R isoforms, we have now added data for PKA-RIα (New Experiment #1), as they are also expressed in the brain (e.g., https://www.ncbi.nlm.nih.gov/gene/5573). Additionally, as Reviewer 1 points out, our second part is a novel addition to the literature.

We also thank the reviewer for suggesting the experiments to examine PKA’s synaptic localization and dynamics as a key mechanism underlying synaptic structure and function. We agree that this is a very interesting topic. At the same time, we feel that this mechanistic direction is open ended at this time and beyond what we try to conclude within this manuscript: prevention of PKA dissociation in neurons affects synaptic function. Therefore, we will save the suggested direction for future studies. We hope the reviewer understand.

Reviewer #3 (Public Review):

Summary:

Xiong et al. investigated the debated mechanism of PKA activation using hippocampal CA1 neurons under pharmacological and synaptic stimulations. Examining the two PKA major isoforms in these neurons, they found that a portion of PKA-C dissociates from PKA-R and translocates into dendritic spines following norepinephrine bath application. Additionally, their use of a non-dissociable form of PKC demonstrates its essential role in structural long-term potentiation (LTP) induced by two-photon glutamate uncaging, as well as in maintaining normal synaptic transmission, as verified by electrophysiology. This study presents a valuable finding on the activation-dependent re-distribution of PKA catalytic subunits in CA1 neurons, a process vital for synaptic functionality. The robust evidence provided by the authors makes this work particularly relevant for biologists seeking to understand PKA activation and its downstream effects essential for synaptic plasticity.

Strengths:

The study is methodologically robust, particularly in the application of two-photon imaging and electrophysiology. The experiments are well-designed with effective controls and a comprehensive analysis. The credibility of the data is further enhanced by the research team's previous works in related experiments. The conclusions of this paper are mostly well supported by data. The research fills a significant gap in our understanding of PKA activation mechanisms in synaptic functioning, presenting valuable insights backed by empirical evidence.

We thank the reviewer for their positive evaluation of our study.

Weaknesses:

The physiological relevance of the findings regarding PKA dissociation is somewhat weakened by the use of norepinephrine (10 µM) in bath applications, which might not accurately reflect physiological conditions. Furthermore, the study does not address the impact of glutamate uncaging, a well-characterized physiologically relevant stimulation, on the redistribution of PKA catalytic subunits, leaving some questions unanswered.

We agreed with the Reviewer that testing under physiological conditions is critical especially given the current debate in the literature. That is why we tested PKA dynamics induced by the physiological stimulant, norepinephrine. It has been suggested that, near the release site, local norepinephrine concentrations can be as high as tens of micromolar (Courtney and Ford, 2014). Based on this study, we have chosen a mid-range concentration (10 μM). At the same time, in light of the Reviewer’s suggestion, we have now also tested PKA-RIIα dissociation at a 5x lower concentration of norepinephrine (2 μM; New Experiment #2). The activation and translocation of PKA-C is also readily detectible under this condition to a degree comparable to when 10 μM norepinephrine was used.

Regarding the suggested glutamate uncaging experiment, it is extremely challenging because of finite signal-to-noise ratios in our experiments. From our past studies, we know that activated PKA-C can diffuse three dimensionally, with a fraction as membrane-associated proteins and the other as cytosolic proteins. Although we have evidence that its membrane affinity allows it to become enriched in dendritic spines, it is not known (and is unlikely) that activated PKA-C is selectively targeted to a particular spine. Glutamate uncaging of a single spine presumably would locally activate a small number of PKA-C. It will be very difficult to trace the 3D diffusion of these small number of molecules in the presence of surrounding resting-state PKA-C molecules. Finally, we hope the reviewer agrees that, regardless of the result of the glutamate uncaging experiment, the above new experiment (New Experiment #2) already indicate that certain physiologically relevant stimuli can drive PKA-C dissociation from PKA-R and translocation to spines, supporting our conclusion.

Reviewer #2 (Recommendations For The Authors):

It was a pleasure reading your paper, and the results are well-executed and well-presented.

My main and only recommendations are two ways to further expand the scope of the findings.

First, I believe addressing the endogenous localization of PKA-C subunit before and after PKA activation would be highly important to validate these claims. Overexpression of tagged proteins often shows vastly different subcellular distribution than their endogenous counterparts. Recent technological advances with CRISPR/Cas9 gene editing (Suzuki et al Nature 2016 and Gao et al Neuron 2019 for example) which the Zhong lab recently contributed to (Zhong et al 2021 eLife) allow us to tag endogenous proteins and image them in fixed or live neurons. Any experiments targeting endogenous PKA subunits that support dissociation and synaptic localization following activation would be very informative and greatly increase the novelty and impact of their findings.

We agreed that addressing the endogenous PKA dynamics is important. However, despite recent progress, endogenous labeling using CRISPR-based methods remains challenging and requires extensive optimization. This is especially true for signaling proteins whose endogenous abundance is often low. We have tried to label PKA catalytic subunits and regulatory subunits using both the homologous recombination-based method SLENDR and our own non-homologous end joining-based method CRISPIE. We did not succeed, in part because it is very difficult to see any signal under wide-field fluorescence conditions, which makes it difficult to screen different constructs for optimizing parameters. It is also possible that, at the endogenous abundance, the label is just not bright enough to be seen. Nevertheless, for both PKA type Iβ and type IIα that we studied in this manuscript, we have correlated the measured parameters (specifically, Spine Enrichment Index or SEI) with the overexpression level (Figure 1-figure supplement 1). We found that they are not strongly correlated with the expression level under our conditions. By extrapolating to non-overexpression conditions, our conclusion remains valid.

To overcome the inability to label endogenous PKA subunits using CRISPR-based methods, we have also attempted a conditional knock-in method call ENABLED that we previously developed to label PKA-Cα. In preliminary results, we found that endogenously label PKA were very dim. However, in a subset of cells that are bright enough to be quantified, the PKA catalytic subunit indeed translocated to dendritic spines upon stimulation (see Additional Fig. 1 in the next page), corroborating our results using overexpression. These results, however, are not ready to be published because characterization of the mouse line takes time and, at this moment, the signal-to-noise ratio remains low. We hope that the reviewer can understand.

Author response image 1.

Endogeneous PKA-Cα translocate to dendritic spines upon activation.

Second, experiments which would advance and validate these findings in vivo would be highly valuable. This could be achieved in a number of ways - one would be overexpression of tagged PKA versions and examining sub-cellular distribution before and after physiological activation in vivo. Another possibility is in vivo perturbation - one would speculate that disruption or tethering of PKA subunits to the dendrite would lead to cell-specific functional and structural impairments. This could be achieved in a similar manner to the in vitro experiments, with a PKA KO and replacement strategy of the tethered C-R plasmid, followed by structural or functional examination of neurons.

I would like to state that these experiments are not essential in my opinion, but any improvements in one of these directions would greatly improve and extend the impact and findings of this paper.

We thank the reviewer for the suggestion and the understanding. The suggested in vivo experiments are fascinating. However, in vivo imaging of dendritic spine morphology is already in itself challenging. The difficulty greatly increases when trying to detect partial, likely transient translocation of a signaling protein. It is also very difficult to knock down endogenous PKA while simultaneously expressing the R-C construct in a large number of cells to achieve detectable circuit or behavioral effect (and hope that compensation does not happen over weeks). We hope the reviewer agrees that these experiments would be their own project and go beyond the time and scope of the current study.

Reviewer #3 (Recommendations For The Authors):

Please elaborate on the methods used to visualize PKA-RIIα and PKA-RIβ subunits.

As suggested, we have now included additional details for visualizing PKA-Rs in the text. Specifically, we write (pg. 5): “…, as visualized using expressed PKA-R-mEGFP in separate experiments (Figs. 1A-1C).”.

Author response:

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

Reviewer #1 (Public Review): 

Summary: 

The authors examined the salt-dependent phase separation of the low-complexity domain of hnRN-PA1 (A1-LCD). Using all-atom molecular dynamics simulations, they identified four distinct classes of salt dependence in the phase separation of intrinsically disordered proteins (IDPs), which can be predicted based on their amino acid composition. However, the simulations and analysis, in their current form, are inadequate and incomplete. 

Strengths: 

The authors attempt to unravel the mechanistic insights into the interplay between salt and protein phase separation, which is important given the complex behavior of salt effects on this process. Their effort to correlate the influence of salt on the low-complexity domain of hnRNPA1 (A1-LCD) with a range of other proteins known to undergo salt-dependent phase separation is an interesting and valuable topic. 

Weaknesses: 

(1) The simulations performed are not sufficiently long (Figure 2A) to accurately comment on phase separation behavior. The simulations do not appear to have converged well, indicating that the system has not reached a steady state, rendering the analysis of the trajectories unreliable.

We have extended the simulations for an additional 500 ns, to 1500 ns. The last 500 ns show reasonably good convergence (see Figure 2A).

(2) The majority of the data presented shows no significant alteration with changes in salt concentration. However, the authors have based conclusions and made significant comments regarding salt activities. The absence of error bars in the data representation raises questions about its reliability. Additionally, the manuscript lacks sufficient scientific details of the calculations.  

We have now included error bars. With the error bars, the salt dependences of all the calculated properties (exception for Rg) show a clear trend. Additionally, we have expanded the descriptions of our calculations (p. 15-16).

(3) In Figures 2B and 2C, the changes in the radius of gyration and the number of contacts do not display significant variations with changes in salt concentration. The change in the radius of gyration with salt concentration is less than 1 Å, and the number of contacts does not change by at least 1. The authors' conclusions based on these minor changes seem unfounded. 

The variation of ~ 1 Å for the calculated Rg is similar to the counterpart for the experimental Rg. As for the number of contacts, note that this property is presented on a per-residue basis, so a value of 1 means that each residue picks up one additional contact, or each protein chain gains a total of 131 contacts, when the salt concentration is increased from 50 to 1000 mM.

Reviewer #2 (Public Review): 

This is an interesting computational study addressing how salt affects the assembly of biomolecular condensates. The simulation data are valuable as they provide a degree of atomistic details regarding how small salt ions modulate interactions among intrinsically disordered proteins with charged residues, namely via Debye-like screening that weakens the effective electrostatic interactions among the polymers, or through bridging interactions that allow interactions between like charges from different polymer chains to become effectively attractive (as illustrated, e.g., by the radial distribution functions in Supplementary Information). However, this manuscript has several shortcomings: 

(i) Connotations of the manuscript notwithstanding, many of the authors' concepts about salt effects on biomolecular condensates have been put forth by theoretical models, at least back in 2020 and even earlier. Those earlier works afford extensive information such as considerations of salt concentrations inside and outside the condensate (tie-lines). But the authors do not appear to be aware of this body of prior works and therefore missed the opportunity to build on these previous advances and put the present work with its complementary advantages in structural details in the proper context.

(ii) There are significant experimental findings regarding salt effects on condensate formation [which have been modeled more recently] that predate the A1-LCD system (ref.19) addressed by the present manuscript. This information should be included, e.g., in Table 1, for sound scholarship and completeness. 

(iii) The strengths and limitations of the authors' approach vis-à-vis other theoretical approaches should be discussed with some degree of thoroughness (e.g., how the smallness of the authors' simulation system may affect the nature of the "phase transition" and the information that can be gathered regarding salt concentration inside vs. outside the "condensate" etc.). Accordingly, this manuscript should be revised to address the following. In particular, the discussion in the manuscript should be significantly expanded by including references mentioned below as well as other references pertinent to the issues raised. 

(1) The ability to use atomistic models to address the questions at hand is a strength of the present work. However, presumably because of the computational cost of such models, the "phase-separated" "condensates" in this manuscript are extremely small (only 8 chains). An inspection of Fig.1 indicates that while the high-salt configuration (snapshot, bottom right) is more compact and droplet-like than the low-salt configuration (top right), it is not clear that the 50 mM NaCl configuration can reasonably correspond to a dilute or homogeneous phase (without phase separation) or just a condensate with a lower protein concentration because the chains are still highly associated. One may argue that they become two droplets touching each other (the chains are not fully dispersed throughout the simulation box, unlike in typical coarse-grained simulations of biomolecular phase separation). While it may not be unfair to argue from this observation that the condensed phase is less stable at low salt, this raises critical questions about the adequacy of the approach as a stand-alone source of theoretical information. Accordingly, an informative discussion of the limitation of the authors' approach and comparisons with results from complementary approaches such as analytical theories and coarsegrained molecular dynamics will be instructive-even imperative, especially since such results exist in the literature (please see below). 

We now discuss the limitations of our all-atom simulations and also other approaches (p. 13; see below).

(2) The aforementioned limitation is reflected by the authors' choice of using Dmax as a sort of phase separation order parameter. However, no evidence was shown to indicate that Dmax exhibits a twostate-like distribution expected of phase separation. It is also not clear whether a Dmax value corresponding to the linear dimension of the simulation box was ever encountered in the authors' simulated trajectories such that the chains can be reliably considered to be essentially fully dispersed as would be expected for the dilute phase. Moreover, as the authors have noted in the second paragraph of the Results, the variation of Dmax with simulation time does not show a monotonic rank order with salt concentration. The authors' explanation is equivalent to stipulating that the simulation system has not fully equilibrated, inevitably casting doubt on at least some of the conclusions drawn from the simulation data. 

First off, with the extended simulations, the Dmax values converge to a tiered order rank, with successively decreasing values from low salt (50 mM) to intermediate salt (150 and 300 mM) to high salt (500 and 1000 mM). Secondly, as we now state (p. 13), our low-salt simulations mimic a homogenous solution whereas our high-salt simulations mimic the dense phase of a phase-separated system. The intermediate-salt simulations also mimic the dense phase but at a somewhat lower concentration (hence the intermediate Dmax value).

(3) With these limitations, is it realistic to estimate possible differences in salt concentration between the dilute and condensed phases in the present work? These features, including tie-lines, were shown to be amenable to analytical theory and coarse-grained molecular dynamics simulation (please see below).  

The differences in salt effects that we report do not represent those between two phases. Rather, as explained in the preceding reply, they represent differences between a homogenous solution at low salt and the dense phase at higher salt. We also acknowledge salt effects calculated by analytical theory and coarse-grained simulations (p. 13).

(4) In the comparison in Fig.2B between experimental and simulated radius of gyration as a function of [NaCl], there is an outlier among the simulated radii of gyration at [NaCl] ~ 250 mM. An explanation should be offered.  

After extending the simulations and analyzing the last 500 ns, the Rg data no longer show an outlier though still have some fluctuations from one salt concentration to another.

(5) The phenomenon of no phase separation at zero and low salt and phase separation at higher salt has been observed for the IDP Caprin1 and several of its mutants [Wong et al., J Am Chem Soc 142, 24712489 (2020) [https://pubs.acs.org/doi/full/10.1021/jacs.9b12208], see especially Fig.9 of this reference]. This work should be included in the discussion and added to Table 1. 

We now have added Caprin1 to Table 1 (new ref 26) and discuss this paper (p. 13).

(6) The authors stated in the Introduction that "A unifying understanding of how salt affects the phase separation of IDPs is still lacking". While it is definitely true that much remains to be learned about salt effects on IDP phase separation, the advances that have already been made regarding salt effects on IDP phase separation is more abundant than that conveyed by this narrative. For instance, an analytical theory termed rG-RPA was put forth in 2020 to provide a uniform (unified) treatment of salt, pH, and sequence-charge-pattern effects on polyampholytes and polyelectrolytes (corresponding to the authors' low net charge and high net charge cases). This theory offers a means to predict salt-IDP tie-lines and a comprehensive account of salt effect on polyelectrolytes resulting in a lack of phase separation at extremely low salt and subsequent salt-enhanced phase separation (similar to the case the authors studied here) and in some cases re-entrant phase separation or dissolution [Lin et al., J Chem Phys 152. 045102 (2020) [https://doi.org/10.1063/1.5139661]]. This work is highly relevant and it already provided a conceptual framework for the authors' atomistic results and subsequent discussion. As such, it should definitely be a part of the authors' discussion. 

We now cite this paper (new ref 34) in Introduction (p. 4). We also discuss its results for Caprin1 (new ref 18; p. 13).

(7) Bridging interactions by small ions resulting in effective attractive interactions among polyelectrolytes leading to their phase separation have been demonstrated computationally by Orkoulas et al., Phys Rev Lett 90, 048303 (2003) [https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.90.048303]. This result should also be included in the discussion. 

We now cite this paper (new ref 41; p. 11).

(8) More recently, the salt-dependent phase separations of Caprin1, its RtoK variants and phosphorylated variant (see item #5 above) were modeled (and rationalized) quite comprehensively using rG-RPA, field-theoretic simulation, and coarse-grained molecular dynamics [Lin et al., arXiv:2401.04873 [https://arxiv.org/abs/2401.04873]], providing additional data supporting a conceptual perspective put forth in Lin et al. J Chem Phys 2020 (e.g., salt-IDP tie-lines, bridging interactions, reentrance behaviors etc.) as well as in the authors' current manuscript. It will be very helpful to the readers of eLife to include this preprint in the authors' discussion, perhaps as per the authors' discretion along the manner in which other preprints are referenced and discussed in the current version of the manuscript. 

We now cite this paper (new ref 18) and discuss it along with new ref 26 in Discussion (p. 13).

Reviewer #3 (Public Review): 

Summary: 

This study investigates the salt-dependent phase separation of A1-LCD, an intrinsically disordered region of hnRNPA1 implicated in neurodegenerative diseases. The authors employ all-atom molecular dynamics (MD) simulations to elucidate the molecular mechanisms by which salt influences A1-LCD phase separation. Contrary to typical intrinsically disordered protein (IDP) behavior, A1-LCD phase separation is enhanced by NaCl concentrations above 100 mM. The authors identify two direct effects of salt: neutralization of the protein's net charge and bridging between protein chains, both promoting condensation. They also uncover an indirect effect, where high salt concentrations strengthen pi-type interactions by reducing water availability. These findings provide a detailed molecular picture of the complex interplay between electrostatic interactions, ion binding, and hydration in IDP phase separation. 

Strengths: 

Novel Insight: The study challenges the prevailing view that salt generally suppresses IDP phase separation, highlighting A1-LCD's unique behavior. 

Rigorous Methodology: The authors utilize all-atom MD simulations, a powerful computational tool, to investigate the molecular details of salt-protein interactions. 

Comprehensive Analysis: The study systematically explores a wide range of salt concentrations, revealing a nuanced picture of salt effects on phase separation. 

Clear Presentation: The manuscript is well-written and logically structured, making the findings accessible to a broad audience. 

Weaknesses: 

Limited Scope: The study focuses solely on the truncated A1-LCD, omitting simulations of the full-length protein. This limitation reduces the study's comparative value, as the authors note that the full-length protein exhibits typical salt-dependent behavior. A comparative analysis would strengthen the manuscript's conclusions and broaden its impact.

Perhaps we did not impress on the reviewer how expensive the all-atom MD simulations on A1-LCD were: the systems each contained half a million atoms and the simulations took many months to complete. That said, we agree with the reviewer that, ideally, a comparative study on a protein showing the typical screening class of salt dependence would have made our work more complete. However, we are confident of the conclusions for several reasons. First, the three salt effects – charge neutralization, bridging, and strengthening of pi-types of interactions – revealed by the all-atom simulations are physically sound and well-supported by other studies. Second, these effects led us to develop a unified picture for the salt dependence of homotypic phase separation, in the form of a predictor for the classes of salt dependence based on amino-acid composition. This predictor works well for nearly 30 proteins. Third, recent studies using analytical theory and coarse-grained simulations (new ref 18) also strongly support our conclusions.

Reviewer #1 (Recommendations For The Authors): 

(1) In Figure 1, the color scheme should be updated and the figure remade, as the current set of color choices makes it very difficult to distinguish the magenta spheres.  

We have increased the sizes of ions in Figure 1 to make them distinguishable.

(2) Within the framework of atomistic simulations, the influence of salt concentration alteration on protein conformational plasticity is worth investigating. This could be correlated (with proper details) with the effect of salt-concentration-modulated protein aggregation behavior. 

We now use RMSF to measure conformational plasticity, which shows a clear salt-dependent trend with a 27% reduction in fluctuations from 50 mM to 1000 mM NaCl (new Fig. S1).

(3) The authors should mention the protein concentrations employed in the simulations and whether these are consistent with experimentally used concentrations.  

We have mentioned the initial concentration (3.5 mM). We now further state that this concentration is maintained in the low-salt simulations, indicating absence of phase separation, but is increased to 23 mM in the high-salt simulations, indicating phase separation. The latter value is consistent with the measured concentrations in the dense phase (last two paragraphs of p. 5).

(4) It would be useful to test the salt effect for at least two extreme salt concentrations at various protein concentrations, consistent with experimental protein concentration ranges.  

In simulation studies of short peptides (ref 37), we have shown that the initial concentration does not affect the final concentration in the dense phase, as expected for phase-separation systems. We expect that the same will be true for the A1-LCD system at intermediate and high salt where phase separation occurs. Though this expectation could be tested by simulations at a different initial protein concentration, such simulations would be expensive but unlikely to yield new physical insight.

(5) Importantly, the simulations do not appear to have converged well enough (Figure 2A). The authors should extend the simulation trajectories to ensure the system has reached a steady state.  

We extended the simulations for an additional 500 ns, which now appear to show convergence. In Figure 2A we now see Dmax values converge to a tiered order rank, with successively decreasing values from low salt (50 mM) to intermediate salt (150 and 300 mM) to high salt (500 and 1000 mM). 

(6) The authors mention "phase separation" in the title, but with only a 1 μs simulation trajectory, it is not possible to simulate a phenomenon like phase separation accurately. Since atomistic simulations cannot realistically capture phase separation on this timescale, a coarse-grained approach is more suitable. To properly explore salt effects in the context of phase separation, long timescale simulation trajectories should be considered. Otherwise, the data remain unreliable. 

Our all-atom simulations revealed rich salt effects that might have been missed in coarse-grained simulations. It is true that coarse-grained models allow the simulations of the phase separation process, but as we have recently demonstrated (refs 36 and 37), all-atom simulations on the μs timescale are also able to capture the spontaneous phase separation of peptides and small IDPs. A1-LCD is much larger than those systems, so we had to use a relatively small chain number (8 chains here vs 64 used in ref 37 and 16 used in ref 37). S2ll, we observe the condensation into a dense phase at high salt. We discuss the pros and cons of all-atom vs. coarse-grained simulations in p. 13.

(7) In Figure 5E, the plot does not show that g(r) has reached 1. If it does, the authors should show the full curve. The same issue remains with supplementary figures 1, 2, 3, etc.  

We now show the approach to 1 in the insets of Figs. S2, S3, S4, and 5E.

(8) None of the data is represented with error bars. The authors should include error bars in their data representations. 

We have now included error bars in all graphs that report average values.

(9) The authors state that "the net charge of the system reduces to only +8 at 1000 mM NaCl (Figure 3C)" but do not explain how this was calculated. 

We now add this explanation in methods (p. 16).

(10). The authors mention "similar to the role played by ATP molecules in driving phase separation of positively charged IDPs." However, ATP can inhibit aggregation, and its induction of phase separation is concentration-dependent. Given ATP's large aromatic moiety, its comparison to ions is not straightforward and is more complex. This comparison can be at best avoided. 

In this context we are comparing the bridging capability of ATP molecules in driving phase separation of positively charged IDPs in ref 36 to the bridging capability of the ions here. In ref 36 the authors show ATP bridging interactions between protein chains similar to what we show here with ions.

(11) Many calculations are vaguely represented. The process for calculating the number of bridging ions, for example, is not well documented. The authors should provide sufficient details to allow for the reproducibility of the data. 

We have now expanded the methods section to include more detailed information on calculations done.

Reviewer #3 (Recommendations For The Authors): 

Include error bars or standard deviations for all results averaged over four replicates, particularly for the number of ions and contacts per residue. This would provide a clearer picture of the data's reliability and variability. 

We have now included error bars in all graphs that report averaged values.

Strengthen the support for the conclusion that "each Arg sidechain often coordinates two Cl- ions, multiple backbone carbonyls often coordinate a single Na+ ion." While Fig. 3A clearly demonstrates ArgCl- coordination, the Na+ coordination claim for a 131-residue protein requires further clarification. Consider including the integration profile of radial distribution functions for Na+ ions to bolster this assertion. 

We now report the number of Na+ ions that coordinate with multiple backbone carbonyls (p. 7) as well as the number of Na+ ions that bridge between A1-LCD chains via coordination with multiple backbone carbonyls (p. 9). Please note that Figure 4A right panel displays an example of Na+ coordinating with multiple backbone carbonyls.

Address the following typographical errors in the main text: o Page 11, line 25: "distinct classes of sat dependence" should be "distinct classes of salt dependence" o Page 14, line 9: "for Cl- and 3.0 and 5.4 A" should be "for Cl- and 3.0 and 5.4 √Ö" o Page 14, line 18: "As a control, PRDFs for water were also calculated" should be "As a control, RDFs for water were also calculated" (assuming PRDF was meant to be RDF) 

We have now corrected these typos.

Consider expanding the study to include simulations of the full-length protein to provide a more comprehensive comparison between the truncated A1-LCD and the complete protein's behavior in various salt concentrations. 

As we explained above, even with eight chains of A1-LCD, which has 131 residues, the systems already contain half a million atoms each and the all-atom simulations took many months to complete. Full-length A1 has 314 residues so a multi-chain system would be too large to be feasible for all-atom simulations.

eLife Assessment

In this potentially important study, the authors conducted atomistic simulations to probe the salt-dependent phase separation of the low-complexity domain of hnRN-PA1 (A1-LCD). The authors have identified both direct and indirect mechanisms of salt modulation, provided explanations for four distinct classes of salt dependence, and proposed a model for predicting protein properties from amino acid composition. There is a range of opinions regarding the strength of evidence, with some considering the evidence as incomplete due to the limitations in the length and statistical errors of the computationally intense atomistic MD simulations.

Reviewer #1 (Public review):

Summary:

The authors examined the salt-dependent phase separation of the low-complexity domain of hnRN-PA1 (A1-LCD). Using all-atom molecular dynamics simulations, they identified four distinct classes of salt dependence in the phase separation of intrinsically disordered proteins (IDPs), which can be predicted based on their amino acid composition. However, the simulations and analysis, in their current form, are inadequate and incomplete.

Strengths:

The authors attempt to unravel the mechanistic insights into the interplay between salt and protein phase separation, which is important given the complex behavior of salt effects on this process. Their effort to correlate the influence of salt on the low-complexity domain of hnRNPA1 (A1-LCD) with a range of other proteins known to undergo salt-dependent phase separation is an interesting and valuable topic.

Weaknesses:

Based on the reviewer's assessment of the manuscript, the following points were raised:

(1) The simulation duration is too short to draw comprehensive conclusions about phase separation.<br /> (2) There are concerns regarding the convergence of the simulations, particularly as highlighted in Figure 2A.<br /> (3) The simulation begins with a protein concentration of 3.5 mM ("we built an 8-copy model for the dense phase (with an initial concentration of 3.5 mM)"), which is high for phase separation studies. The reviewer questions the use of the term "dense phase" and suggests that the authors conduct a clearer analysis depicting the coexistence of both the dilute and dense phases to represent a steady state. Without this, the realism of the described phenomena is doubtful. Commenting on phase separation under conditions that don't align with typical phase separation parameters is not acceptable.<br /> (4) The inference that "Each Arg sidechain often coordinates two Cl- ions simultaneously, but each Lys sidechain coordinates only one Cl- ion" is questioned. According to Supplementary Figure 2A, Lys seems to coordinate with Cl- ions more frequently than Arg.<br /> (5) The authors are requested to update the figure captions for Supplementary Figures 2 and 3, specifying which system the analyses were performed on.<br /> (6) It is difficult to observe a clear trend due to irregularities in the data. Although the authors have included a red dotted line in the figures, the trend is not monotonic. The reviewer expresses concerns about significant conclusions drawn from these figures (e.g., Figure 2C, Figure 5A, Supplementary Figure 1).<br /> (7) Given the error in the radius of gyration (Rg) calculations, the reviewer questions the validity of drawing conclusions from this data.<br /> (8) The pair correlation function values in Figure 5E and supplementary figure 4 show only minor differences, and the reviewer questions whether these differences are significant.<br /> (9) Previous reports suggest that, upon self-assembly, protein chains extend within the condensate, leading to a decrease in intramolecular contacts. However, the authors show an increase in intramolecular contacts with increasing salt concentration (Figure 2C), which contradicts prior studies. The reviewer advises the authors to carefully review this and provide justification.<br /> (10) A systematic comparison of estimated parameters with varying salt concentrations is required. Additionally, the authors should provide potential differences in salt concentrations between the dilute and condensed phases.<br /> (11) The reviewer finds that the majority of the data presented shows no significant alteration with changes in salt concentration, yet the authors have made strong conclusions regarding salt activity.

The manuscript lacks sufficient scientific details of the calculations.

Reviewer #2 (Public review):

This is an interesting computational study addressing how salt affects the assembly of biomolecular condensates. The simulation data are valuable as they provide a degree of atomistic details regarding how small salt ions modulate interactions among intrinsically disordered proteins with charged residues, namely via Debye-like screening that weakens the effective electrostatic interactions among the polymers, or through bridging interactions that allow interactions between like charges from different polymer chains to become effectively attractive (as illustrated, e.g., by the radial distribution functions in Supplementary Information). However, this manuscript has several shortcomings: (i) Connotations of the manuscript notwithstanding, many of the authors' concepts about salt effects on biomolecular condensates have been put forth by theoretical models, at least back in 2020 and even earlier. Those earlier works afford extensive information such as considerations of salt concentrations inside and outside the condensate (tie-lines). But the authors do not appear to be aware of this body of prior works and therefore missed the opportunity to build on these previous advances and put the present work with its complementary advantages in structural details in the proper context. (ii) There are significant experimental findings regarding salt effects on condensate formation [which have been modeled more recently] that predate the A1-LCD system (ref.19) addressed by the present manuscript. This information should be included, e.g., in Table 1, for sound scholarship and completeness. (iii) The strengths and limitations of the authors' approach vis-à-vis other theoretical approaches should be discussed with some degree of thoroughness (e.g., how the smallness of the authors' simulation system may affect the nature of the "phase transition" and the information that can be gathered regarding salt concentration inside vs. outside the "condensate" etc.).

Comments on revised version:

The authors have adequately addressed my previous concerns and suggestions. The manuscript is now significantly improved. The new results and analyses provided by the authors represent a substantial advance in our understanding of the role of electrostatics in the assembly of biomolecular condensates.

Reviewer #3 (Public review):

Summary:

This study investigates the salt-dependent phase separation of A1-LCD, an intrinsically disordered region of hnRNPA1 implicated in neurodegenerative diseases. The authors employ all-atom molecular dynamics (MD) simulations to elucidate the molecular mechanisms by which salt influences A1-LCD phase separation. Contrary to typical intrinsically disordered protein (IDP) behavior, A1-LCD phase separation is enhanced by NaCl concentrations above 100 mM. The authors identify two direct effects of salt: neutralization of the protein's net charge and bridging between protein chains, both promoting condensation. They also uncover an indirect effect, where high salt concentrations strengthen pi-type interactions by reducing water availability. These findings provide a detailed molecular picture of the complex interplay between electrostatic interactions, ion binding, and hydration in IDP phase separation.

Strengths:

• Novel Insight: The study challenges the prevailing view that salt generally suppresses IDP phase separation, highlighting A1-LCD's unique behavior.<br /> • Rigorous Methodology: The authors utilize all-atom MD simulations, a powerful computational tool, to investigate the molecular details of salt-protein interactions.<br /> • Comprehensive Analysis: The study systematically explores a wide range of salt concentrations, revealing a nuanced picture of salt effects on phase separation.<br /> • Clear Presentation: The manuscript is well-written and logically structured, making the findings accessible to a broad audience.

Weaknesses:

• Limited Scope: The study focuses solely on the truncated A1-LCD, omitting simulations of the full-length protein. This limitation reduces the study's comparative value, as the authors note that the full-length protein exhibits typical salt-dependent behavior. However, given the much larger size of the full-length protein, it is acceptable to omit it given the current computing resources available.

Overall, this manuscript represents a significant contribution to the field of IDP phase separation. The authors' findings provide valuable insights into the molecular mechanisms by which salt modulates this process, with potential implications for understanding and treating neurodegenerative diseases.

This is a good point how the struggle for power often comes with inhumane treatment.

This line, which seemingly emphasizes how water can kill/take apart human beings, draws a contrast to Corinthians, which states "All were baptized into Moses in the cloud and in the sea," which appears to show how water is used to "baptize" someone into a religion. I think the difference between the water usages in these respective works stems from Eliot looking at some of the more literal actions of water while Corinthians looks at more figurative, religious uses of it.

Eliot references the "Isle of Dogs". Matthew 7:6 states "Give not that which is holy unto the dogs, neither cast ye your pearls before swine, lest they trample them under their feet, and turn again and rend you." I find this interesting because I essentially understand to say "be careful who you associate with because not all people are good," which draws a contrast to this stanza which generally seems to lack intention. For example, it says "The barges drift" and references "Drifting logs," which implies a lack of control over the circumstances. This is all very interesting because in Matthew, "the dogs" seemingly refer to people you find yourself associating with if you become too careless with your actions, and going "Past the Isle of Dogs" feels similarly unintentional.

Interestingly, throughout this entire long stanza, the night seems to become darker as the actions become darker. First, we're just in the "violet hour", then time passes throughout the stanza, and it ends with "And gropes his way, finding the stairs unlit" (Eliot, 248), after Tiresias has raped a woman. The way light and darkness is used here draws a contrast to how it's used in Fragment 149 of a Sappho poem, where she refers to "Bringing everything that shining Dawn scattered, you bring the sheep, you bring the goat, you bring the child back to its mother" (Sappho). Here, darkness and nighttime are seen as things that bring people/animals together in a pleasurable way by reuniting them, whereas in this stanza Tiresias and a woman are brought together at night, but he rapes her, thereby correlating darkness and nighttime with darker actions in "The Waste Land".

This is a clear reference to Edmund Spenser's poem "Prothalamion". I think it might represent Eliot trying to get closer to that aesthetic of the 1500s, when the world was generally more untouched. In the next lines he says "The river bears no empty bottles, sandwich papers, / Silk handkerchiefs, cardboard boxes, cigarette ends / Or other testimony of summer nights" (Eliot, 176-178), which I think touches on the theme of industrialization. Therefore, Eliot may be referencing Spenser to feel closer to that pre-industrial world.

Here Eliot references the passage from Dracula when Dracula climbs down the side of the wall: “I saw the whole man slowly emerge from the window and begin to crawl down the castle wall over that dreadful abyss, face down with his cloak spreading out around him like great wings” (Stoker, 2), and subsequently Byron’s Dark Tower: “Into that ominous tract which, all agree, // Hides the Dark Tower” (Byron, 14-15). To break this down, the “bats” in “The Waste Land” represent Dracula, a symbol of terror and psychological torment. Through Dracula’s perspective, Lord Byron’s Dark Tower has been inverted. The word “ominous” recalls Eliot’s fascination with Tarot cards and brings to mind the “Tower” tarot card, which, read upright, signifies impending doom and destruction. However, inverted, that unfavorable omen changes its meaning, commonly associated with the denial of the aforementioned doom and destruction. Because of his upside down perspective, Dracula has essentially controlled the inversion of this card. Potentially, this would translate as a voluntary dismissal or rejection of chaos and destruction by the human psyche, specifically, the part of the human psyche that drives fear and terror.

Additionally, a second read of these two lines reveals that the orientation of Dracula in the scene may not actually be as simple as it seems. Eliot uses a rather redundant “downward down,” which is aligned with “upside down” in the next line. Perhaps the double “down” simply serves to emphasize. But, alternatively, it might negate itself, thus the orientation of the bats is actually right-side-up, making the orientation of the towers upside down from a right-side-up perspective, truly hanging from the “air.” Likely, Eliot meant to disorient the reader by confusing the orientation of perspective. In the context of our tarot card, this means the prophecy flips in every permutation of upside down and right-side-up in these lines–an ever changing future. Furthermore, the idea of a turbulent prophecy is nested within the context of the meaning of the card itself–chaos. Thus, Eliot has managed to completely muddle the perspective of the reader, as well as any definition in the image of the future.

What do we mean by preferred? What do we knwo about the the colelctive shadow that was not harvested?

A very limited intention - just to maximise apporoval What abotu to access the quantum potential?

We like the term Undividual rather than Individual Individual means undivided whole but we have come to understand it as separate.

Why only opinions and critiques? What about potentials? What about shadows? What about Qualia?

This is the same process as Quaker Clerks of Meetings have been doing for nearly 400 years

This shows the importance of language Yet, the language can come FROM the group rather than be PUT TO the group

What if consensus at the group meeting does not last after the meeting is over?

In Dialogue, DISCUSS comes from Percuss or Concuss - beating an idea to death. In Dialogue, the idea is held open for us all to witness and explore beenath its symptom, its explicate, by delving into its implicate as an undivided wholeness

Yes. And the collective must also be able to reach disagreement and still stay in Dialogic relations

metaphor

jfc

what the fuck?? THIS IS LITERALLY PART OF WHY WE GO TO GRADUATE SCHOOL

for - separation - reference - The three great separations

separation - reference - The three great separations - https://hyp.is/go?url=https%3A%2F%2Finthesetimes.com%2Farticle%2Findustrial-agricultural-revolution-planet-earth-david-korten&group=world

for - questions - collaboration literacy - Donna Nelham - to - book - The Birth and Death of Meaning - Ernest Becker -

questions - collaboration - Donna Nelham - These three questions are all related - To get to the root of collaboration, it is helpful to examine the roots of human psychology to understand the fundamental relationship between - the individual and - the group - In his work "The Birth ad Death of Meaning, Ernest Becker argues, citing other peers, that - the self concept needs to emerge for effective group collaboration to develop and - the self concept requires others in order to construct it - Hence, other is already implicated in the construction of our own self - In Deep Humanity terminology, we call this intertwingledness of the self and other the "individual / collective gestalt"

to - book - The Birth and Death of Meaning - Ernest Becker - https://hyp.is/40fZHv9CEe6bTovrYzF92A/www.themortalatheist.com/blog/the-birth-and-death-of-meaning-ernest-becker

for - adder - for deep collaboration - article - Co-creative Collaboration - Donna Nelham

adder - for deep collaboration - article - Co-creative Collaboration - Donna Nelham - symmathesy - mutual learning - Nora Bateson - https://hyp.is/_V3NAk4UEe6Z6btu_1LIkA/norabateson.wordpress.com/2015/11/03/symmathesy-a-word-in-progress/

for - portmanteau - collaboration washing - Donna Nelham

portmanteau - collaboration washing - Donna Nelham - like greenwashing - nice!

I appreciate how they discussed being open to getting an answer wrong and working with those students, with patient to help them gain a better understanding of the topic.

Allowing access to certain resources that enhance a student's learning is the prime example of a well-structured classroom

By embracing "storientation," educators can learn about students' interests, families, and experiences outside of school. This approach counters the tendency to rely on a single narrative, fostering a deeper understanding t

The main idea is that "lean-in assessment" is crucial for understanding each student's unique learning journey. By engaging with students and observing their approaches to tasks, strengths, and challenges, educators can gather valuable insights that standardized tests cannot provide.

The key point is that flexibility in teaching routines is essential for effective instruction. While structured mini-lessons can be useful, they may not meet the diverse needs of all learners.

The central message is that creating a safe space for failure in the classroom is essential for learning. By framing failure as valuable data rather than a source of shame, students can openly acknowledge their struggles.

The main idea is that culture should be viewed as a valuable resource in education. Ignoring students' identities diminishes their experiences and potential for learning. Recognizing and engaging with students' cultural backgrounds allows them to better understand and connect with challenging content. Encouraging students to share their backgrounds fosters a supportive environment that values diversity and enhances learning for everyone.

The key message is that achieving success for every child requires recognizing and addressing the inequalities faced by specific groups, including English language learners, students with special needs, and those impacted by trauma or poverty

Relaying to students that their point in their educational journey does not define them as an individual and instilling a joy for understanding and learning that differs among students is where the true importance lies

Although the implementation of mini lessons can be taught with the hope it will reach all students, understanding that not all students learn in the same way nor are they all at the same point in their educational journey, it is important to offer additional support when noticed to be prompted

Ensuring the success of every student individually is of greatest value is crucial to achieving an equitable classroom that values the learning point of all students

Yes its important to know about all of the students identities read books about different cultures to show everyone and boarder theyre horizons

Its important to teach them to learn from theyre mistakes so they won't be ashamed of the mistakes everyone makes because no one is perfect

Sometimes a student needs a break because theyre over simulated and its nothing to be uncomfortable about and you should explain we all have our moments for a little minting breather and come back in ready to effectively finish the lesson

The more you know about how a student works the more you can develop different lesson plans to build off those skills and expand off that

Its important to let know that theyre capable of being able to accomplish anything they wanna do give the the confidence to do what they wanna do and they'll succeed

eLife Assessment

This manuscript presents a valuable new quantitative crosslinking mass spectrometry approach using novel isobaric crosslinkers. The data are solid and the method has potential for a broad application in structural biology if more isobaric crosslinking channels are available and the quantitative information of the approach is exploited in more depth.

Reviewer #1 (Public review):

Summary:

Crosslinking mass spectrometry has become an important tool in structural biology, providing information about protein complex architecture, binding sites and interfaces, and conformational changes. One key challenge of this approach represents the quantitation of crosslinking data to interrogate differential binding states and distributions of conformational states.

Here, Luo and Ranish present a novel class of isobaric crosslinkers ("Qlinkers"), conduct proof-of-concept benchmarking experiments on known protein complexes, and show example applications on selected target proteins. The data are solid and this could well be an exciting, convincing new approach in the field if the quantitation strategy is made more comprehensive and the quantitative power of isobaric labeling is fully leveraged as outlined below. It's a promising proof-of-concept, and potentially of broad interest for structural biologists.

Strengths:

The authors demonstrate the synthesis, application, and quantitation of their "Q2linkers", enabling relative quantitation of two conditions against each other. In benchmarking experiments, the Q2linkers provide accurate quantitation in mixing experiments. Then the authors show applications of Q2linkers on MBP, Calmodulin, selected transcription factors, and polymerase II, investigating protein binding, complex assembly, and conformational dynamics of the respective target proteins. For known interactions, their findings are in line with previous studies, and they show some interesting data for TFIIA/TBP/TFIIB complex formation and conformational changes in pol II upon Rbp4/7 binding.

Weaknesses:

This is an elegant approach but the power of isobaric mass tags is not fully leveraged in the current manuscript.

First, "only" Q2linkers are used. This means only two conditions can be compared. Theoretically, higher-plexed Qlinkers should be accessible and would also be needed to make this a competitive method against other crosslinking quantitation strategies. As it is, two conditions can still be compared relatively easily using LFQ - or stable-isotope-labeling based approaches. A "Q5linker" would be a really useful crosslinker, which would open up comprehensive quantitative XLMS studies.

Second, the true power of isobaric labeling, accurate quantitation across multiple samples in a single run, is not fully exploited here. The authors only show differential trends for their interaction partners or different conformational states and do not make full quantitative use of their data or conduct statistical analyses. This should be investigated in more detail, e.g. examine Qlinker quantitation of MBP incubated with different concentrations of maltose or Calmodulin incubated with different concentrations of CBPs. Does Qlinker quantitation match ratios predicted using known binding constants or conformational state populations? Is it possible to extract ratios of protein populations in different conformations, assembly, or ligand-bound states?

With these two points addressed this approach could be an important and convincing tool for structural biologists.

Comments on latest version:

I raised only two points which they have not addressed: Higher multiplexing of Qlinkers (1) and experiments to assess the statistical power of their quantitation strategy (2).

I can see that point (1) requires substantial experimental efforts and synthesis of novel Qlinkers would be months of work. This is an editorial decision if the limited quantitative power of the "2-plex" approach they have right now is sufficient to support publication in eLife. While I like the approach, I feel it falls short of its potential in its current form.

For point (2), the authors did not do any supporting experiments. They claim "higher plex Qlinkers" would need to be available, but I suggested experiments that can be done even with Q2linkers: Using one of the two channels as a reference channel (similar the Super-SILAC strategy published in 2010 by Geiger et al; using an isotope-labeled channel as a stable reference channel between different experiments and LC-MS runs), they could do time-courses or ligand-concentration-series with the other channel and then show that Qlinkers allow quantitative monitoring of the different populations (e.g. conformations or ligand-bound proteins).

As an additional point, I was a bit surprised to read that the quantitation evaluation in Figure 1 is based on a single experiment (reviewer response document page 6, line 2 in the authors' reply). I strongly suggest this to be repeated a few times so a proper statistical test on experimental reproducibiltiy of Qlinkers can be conducted.

In summary, the authors declined to do any experimental work to address my concerns.

Reviewer #2 (Public review):

The regulation of protein function heavily relies on the dynamic changes in the shape and structure of proteins and their complexes. These changes are widespread and crucial. However, examining such alterations presents significant challenges, particularly when dealing with large protein complexes in conditions that mimic the natural cellular environment. Therefore, much emphasis has been put on developing novel methods to study protein structure, interactions, and dynamics. Crosslinking mass spectrometry (CSMS) has established itself as such a prominent tool in recent years. However, doing this in a quantitative manner to compare structural changes between conditions has proven to be challenging due to several technical difficulties during sample preparation. Luo and Ranish introduce a novel set of isobaric labeling reagents, called Qlinkers, to allow for a more straightforward and reliable way to detect structural changes between conditions by quantitative CSMS (qCSMS).

The authors do an excellent job describing the design choices of the isobaric crosslinkers and how they have been optimized to allow for efficient intra- and inter-protein crosslinking to provide relevant structural information. Next, they do a series of experiments to provide compelling evidence that the Qlinker strategy is well suited to detect structural changes between conditions by qCSMS. First, they confirm the quantitative power of the novel-developed isobaric crosslinkers by a controlled mixing experiment. Then they show that they can indeed recover known structural changes in a set of purified proteins (complexes) - starting with single subunit proteins up to a very large 0.5 MDa multi-subunit protein complex - the polII complex.

The authors give a very measured and fair assessment of this novel isobaric crosslinker and its potential power to contribute to the study of protein structure changes. They show that indeed their novel strategy picks up expected structural changes, changes in surface exposure of certain protein domains, changes within a single protein subunit but also changes in protein-protein interactions. However, they also point out that not all expected dynamic changes are captured and that there is still considerable room for improvement (many not limited to this crosslinker specifically but many crosslinkers used for CSMS).

Taken together the study presents a novel set of isobaric crosslinkers that indeed open up the opportunity to provide better qCSMS data, which will enable researchers to study dynamic changes in the shape and structure of proteins and their complexes.

Comments on latest version:

The authors have not really addressed most of the concerns. They have added minimal discussion points to the text. This is okay from my perspective as eLife's policy is to leave it up to the authors of how strongly to consider the reviewers' comments. I should add that I do fully agree with the other reviewer that the quantitative assessment from Figure 1 should have been done in triplicates at least and that this would actually be essential.

Author response:

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

Reviewer #1 (Public review):

Summary:

Crosslinking mass spectrometry has become an important tool in structural biology, providing information about protein complex architecture, binding sites and interfaces, and conformational changes. One key challenge of this approach represents the quantitation of crosslinking data to interrogate differential binding states and distributions of conformational states.

Here, Luo and Ranish present a novel class of isobaric crosslinkers ("Qlinkers"), conduct proof-of-concept benchmarking experiments on known protein complexes, and show example applications on selected target proteins. The data are solid and this could well be an exciting, convincing new approach in the field if the quantitation strategy is made more comprehensive and the quantitative power of isobaric labeling is fully leveraged as outlined below. It's a promising proof-of-concept, and potentially of broad interest for structural biologists.

Strengths:

The authors demonstrate the synthesis, application, and quantitation of their "Q2linkers", enabling relative quantitation of two conditions against each other. In benchmarking experiments, the Q2linkers provide accurate quantitation in mixing experiments. Then the authors show applications of Q2linkers on MBP, Calmodulin, selected transcription factors, and polymerase II, investigating protein binding, complex assembly, and conformational dynamics of the respective target proteins. For known interactions, their findings are in line with previous studies, and they show some interesting data for TFIIA/TBP/TFIIB complex formation and conformational changes in pol II upon Rbp4/7 binding.

Weaknesses:

This is an elegant approach but the power of isobaric mass tags is not fully leveraged in the current manuscript.

First, "only" Q2linkers are used. This means only two conditions can be compared. Theoretically, higher-plexed Qlinkers should be accessible and would also be needed to make this a competitive method against other crosslinking quantitation strategies. As it is, two conditions can still be compared relatively easily using LFQ - or stable-isotope-labeling based approaches. A "Q5linker" would be a really useful crosslinker, which would open up comprehensive quantitative XLMS studies.

We agree that a multiplexed Qlinker approach would be very useful. The multiplexed Qlinkers are more difficult and more expensive to synthesize. We are currently working on different schemes for synthesizing multiplexed Qlinkers.

Second, the true power of isobaric labeling, accurate quantitation across multiple samples in a single run, is not fully exploited here. The authors only show differential trends for their interaction partners or different conformational states and do not make full quantitative use of their data or conduct statistical analyses. This should be investigated in more detail, e.g. examine Qlinker quantitation of MBP incubated with different concentrations of maltose or Calmodulin incubated with different concentrations of CBPs. Does Qlinker quantitation match ratios predicted using known binding constants or conformational state populations? Is it possible to extract ratios of protein populations in different conformations, assembly, or ligand-bound states?

With these two points addressed this approach could be an important and convincing tool for structural biologists.

We agree that multiplexed Qlinkers would open the door to exciting avenues of investigation such as studying conformational state populations.  We plan to conduct the suggested experiments when multiplexed Qlinkers are available.

Reviewer #2 (Public review):

The regulation of protein function heavily relies on the dynamic changes in the shape and structure of proteins and their complexes. These changes are widespread and crucial. However, examining such alterations presents significant challenges, particularly when dealing with large protein complexes in conditions that mimic the natural cellular environment. Therefore, much emphasis has been put on developing novel methods to study protein structure, interactions, and dynamics. Crosslinking mass spectrometry (CSMS) has established itself as such a prominent tool in recent years. However, doing this in a quantitative manner to compare structural changes between conditions has proven to be challenging due to several technical difficulties during sample preparation. Luo and Ranish introduce a novel set of isobaric labeling reagents, called Qlinkers, to allow for a more straightforward and reliable way to detect structural changes between conditions by quantitative CSMS (qCSMS).

The authors do an excellent job describing the design choices of the isobaric crosslinkers and how they have been optimized to allow for efficient intra- and inter-protein crosslinking to provide relevant structural information. Next, they do a series of experiments to provide compelling evidence that the Qlinker strategy is well suited to detect structural changes between conditions by qCSMS. First, they confirm the quantitative power of the novel-developed isobaric crosslinkers by a controlled mixing experiment. Then they show that they can indeed recover known structural changes in a set of purified proteins (complexes) - starting with single subunit proteins up to a very large 0.5 MDa multi-subunit protein complex - the polII complex.

The authors give a very measured and fair assessment of this novel isobaric crosslinker and its potential power to contribute to the study of protein structure changes. They show that indeed their novel strategy picks up expected structural changes, changes in surface exposure of certain protein domains, changes within a single protein subunit but also changes in protein-protein interactions. However, they also point out that not all expected dynamic changes are captured and that there is still considerable room for improvement (many not limited to this crosslinker specifically but many crosslinkers used for CSMS).

Taken together the study presents a novel set of isobaric crosslinkers that indeed open up the opportunity to provide better qCSMS data, which will enable researchers to study dynamic changes in the shape and structure of proteins and their complexes. However, in its current form, the study some aspects of the study should be expanded upon in order for the research community to assess the true power of these isobaric crosslinkers. Specifically:

Although the authors do mention some of the current weaknesses of their isobaric crosslinkers and qCSMS in general, more detail would be extremely helpful. Throughout the article a few key numbers (or even discussions) that would allow one to better evaluate the sensitivity (and the applicability) of the method are missing. This includes:

(1) Throughout all the performed experiments it would be helpful to provide information on how many peptides are identified per experiment and how many have actually a crosslinker attached to it.

As the goal of the experiments is to maximize identification of crosslinked peptides which tend to have higher charge states, we targeted ions with charge states of 3+ or higher in our MS acquisition settings for CLMS, and ignored ions with 2+ charge states, which correspond to many of the normal (i.e., not crosslinked) peptides that are identified by MS. As a result, normal peptides are less likely to be identified by the MS procedure used in our CLMS experiments compared to MS settings typically used to identify normal peptides. Our settings may also fail to identify some mono-modified peptides. Like most other CLMS methods, the total number of identified crosslinked peptide spectra is usually less than 1% of the total acquired spectra and we normally expect the crosslinked species to be approximately 1% of the total peptides. 

We added information about the number of crosslinked and monolinked peptides identified in the pol I benchmarking experiments (line 173).  The number of crosslinks and monolinks identified in the pol II +/- a-amanitin experiment, the TBP/TFIIA/TFIIB experiment and the pol II experiment +/- Rpb4/7 are also provided.

(2) Of all the potential lysines that can be modified - how many are actually modified? Do the authors have an estimate for that? It would be interesting to evaluate in a denatured sample the modification efficiency of the isobaric crosslinker (as an upper limit as here all lysines should be accessible) and then also in a native sample. For example, in the MBP experiment, the authors report the change of one mono-linked peptide in samples containing maltose relative to the one not containing maltose. The authors then give a great description of why this fits to known structural changes. What is missing here is a bit of what changes were expected overall and which ones the authors would have expected to pick up with their method and why have they not been picked up. For example, were they picked up as modified by the crosslinker but not differential? I think this is important to discuss appropriately throughout the manuscript to help the reader evaluate/estimate the potential sensitivity of the method. There are passages where the authors do an excellent job doing that - for example when they mention the missed site that they expected to see in the initial the pol II experiments (lines 191 to 207). This kind of "power analysis" should be heavily discussed throughout the manuscript so that the reader is better informed of what sensitivity can be expected from applying this method.

Regarding the Pol II complex experiment described in Figures 4 and 5, out of the 277 lysine residues in the complex, 207 were identified as monolinked residues (74.7%), and 817 crosslinked pairs out of 38,226 potential pairs (2.1%) were observed. The ability of CLMS to detect proximity/reactivity changes may be impacted by several factors including 1) the (low) abundance of crosslinked peptides in complex mixtures, 2) the presence of crosslinkable residues in close proximity with appropriate orientation, and 3) the ability to generate crosslinked peptides by enzymatic digestion that are amenable to MS analysis (i.e., the peptides have appropriate m/z’s and charge states, the peptides ionize well, the peptides produce sufficient fragment ions during MS2 analysis to allow confident identification). Future efforts to enrich crosslinked peptides prior to MS analysis may improve sensitivity.

It is very difficult to estimate the modification efficiency of Qlinker (or many other crosslinkers) based on peptide identification results. One major reason for this is that trypsin is not able to cleave after a crosslinker-modified lysine residue.  As a result, the peptides generated after the modification reaction have different lengths, compositions, charge states, and ionization efficiencies compared to unmodified peptides. These differences make it very difficult to estimate the modification efficiencies based on the presence/absence of certain peptide ions, and/or the intensities of the modified and unmodified versions of a peptide. Also, 2+ ions which correspond to many normal (i.e., unmodified) peptides were excluded by our MS acquisition settings.

It is also very difficult to predict which structural changes are expected and which crosslinked peptides and/or modified peptides can be observed by MS.  This is especially true when the experiment involves proteins containing unstructured regions such as the experiments involving Pol II, and TBP, TFIIA and TFIIB. Since we are at the early stages of using qCLMS to study structural changes, we are not sure which changes we can expect to observe by qCLMS. Additional applications of Qlinker-CLMS are needed to better understand the types of structural changes that can be studied using the approach.

We hope that our discussions of some the limitations of CLMS for detecting conformational/reactivity changes provide the reader with an understanding of the sensitivity that can be expected with the approach.  At the end of the paragraph about the pol II a-amanitin experiment we say, “Unfortunately, no Q2linker-modified peptides were identified near the site where α-amanitin binds. This experiment also highlights one of the limitations of residue-specific, quantitative CLMS methods in general. Reactive residues must be available near the region of interest, and the modified peptides must be identifiable by mass spectrometry.” In the section about Rbp4/7-induced structural changes in pol II we describe the under-sampling issue. And in the last paragraph we reiterate these limitations and say, “This implies that this strategy, like all MS-based strategies, can only be used for interpretation of positively identified crosslinks or monolinks. Sensitivity and under sampling are common problems for MS analysis of complex samples.”

(3) It would be very helpful to provide information on how much better (or not) the Qlinker approach works relative to label-free qCLMS. One is missing the reference to a potential qCLMS gold standard (data set) or if such a dataset is not readily available, maybe one of the experiments could be performed by label-free qCLMS. For example, one of the differential biosensor experiments would have been well suited.

We agree with the reviewer that it will be very helpful to establish gold standard datasets for CLMS. As we further develop and promote this technology, we will try to establish a standardized qCLMS.

Reviewer #1 (Recommendations for the authors):

Only a very minor point:

I may have missed it but it's not really clear how many independent experiments were used for the benchmarking quantitation and mixing experiments for Figure 1. What is the reproducibility across experiments on average and on a per-peptide basis?

Otherwise, I think the approach would really benefit from at least "Q5linkers" or even "Q10linkers", if possible. And then conduct detailed quantitative studies, either using dilution series or maybe investigating the kinetics of complex formation.

We used a sample of BSA crosslinked peptides to optimize the MS settings, establish the MS acquisition strategies and test the quantification schemes.  The data in Figure 1 is based on one experiment, in which used ~150 ug of purified pol I complexes from a 6 L culture. We added this information to the Figure 1 legend. We also provide information about the reproducibility of peptide quantification by plotting the observed and expected ratios for each monolinked and crosslinked peptide identified in all of the runs in Figure S3.

We agree with the reviewer that the Qlinker approach would be even more attractive if multiplex Qlinker reagents were designed. The multiplexed Qlinkers are more difficult and more expensive to synthesize. We are currently working on different schemes for synthesizing multiplexed Qlinkers.

Reviewer #2 (Recommendations for the authors):

In addition to the public review I have the following recommendations/questions:

(1) The first part of the results section where the synthesis of the crosslinker is explained is excellent for mass spec specialists, but problematic for general readers - either more info should be provided (e.g. b1+ ions - most readers will have no idea why that is) - or potentially it could be simplified here and the details shifted to Materials and Methods for the expert reader. The same is true below for the length of spacer arms.

However - in general this level of detail is great - but can impact the ease of understanding for the more mass spec affine but not expert reader.

We have added the following sentence to assist the general reader: A b1+ ion is an ion with a charge state of +1 corresponding to the first N-terminal amino acid residue after breakage of the first peptide bond (lines 126-128).

(2) The Calmodulin experiment (lines 239 to 257) - it is a very nice result that they see the change in the crosslinked peptide between residues K78-K95, but the monolinks are not just detected as described in the text but actually go 2 fold up. This would have been actually a bit expected if the residues are now too far away to be still crosslinked that the monolinks increase. In this case, this counteraction of monolinks to crosslinked sites can also be potentially used as a "selection criteria" for interesting sites that change. Is that a possible interpretation or do the authors think that upregulation of the monolinks is a coincidence and should not be interpreted?

We agree with the reviewer that both monolinks and crosslinks can be used as potential indicators for some changes. However, it is much more difficult to interpret the abundance information from monolinks because, unlike crosslinks, there is little associated structural/proximity information with monolinks. Because it is difficult to understand the reason(s) for changes in monolink abundance, we concentrate on changes in crosslink abundances, which provide proximity/structural information about the crosslinked residues.

(3) Lines 267 to 274: a small thing but the structural information provided is quite dense I have to say. Maybe simplify or accompany with some supplemental figures?

We agree that the structural information is a bit dense especially for readers who are not familiar with the pol II system.  We added a reference to Figure 3c (line 177) to help the reader follow the structural information. 

As qCLMS is still a relatively new approach for studying conformational changes, the utility of the approach for studying different types of conformational changes is still unclear. Thus, one of the goals of the experiments is to demonstrate the types of conformational changes that can be detected by Q2linkers.  We hope that the detailed descriptions will help structural biologists understand the types of conformational changes that can be detected using Qlinkers.

(4) Line 280: explain maybe why the sample was fractionated by SCX (I guess to separate the different complexes?).

SCX was used to reduce the complexity of the peptide mixtures. As the samples are complex and crosslinked peptides are of low abundance compared to normal peptides, SCX can separate the peptides based on their positive charges.  Larger peptides and peptides with higher charge states, such as crosslinked peptides, tend to elute at higher salt concentration during SCX chromatography.  The use of SCX to fractionate complex peptide mixtures is described in the “General crosslinking protocol and workflow optimization” section of the Methods, and we added a sentence to explain why the sample was fractionated by SCX (lines 278-279).

(5) Lines 354 to 357: "This suggests that the inability to identity most of these crosslinked peptides in both experiments is mainly due to under-sampling during mass spectrometry analysis of the complex samples, rather than the absence of the crosslinked peptides in one of the experiments."

This is an extremely important point for the interpretation of missing values - have the authors tried to also collect the mass spec data with DIA which is better in recovery of the same peptide signals between different samples? I realize that these are isobaric samples so DIA measurements per se are not useful as the quantification is done on the reporter channels in the MS2, but it would at least give a better idea if the missing signals were simply not picked up for MS2 as claimed by the authors or the modified peptides are just not present. Another possibility is for the authors to at least try to use a "match between the run" function as can be done in Maxquant. One of the strengths of the method is that it is quantitative and two states are analyzed together, but as can be seen in this experiment, more than two states might want to be compared. In such cases, the under-sampling issue (if that is indeed the cause) makes interpretation of many sites hard (due to missing values) and it would be interesting if for example, an analysis approach with a "match between the runs" function could recover some of the missing values.

We agree that undersampling/missing values is an important issue that needs to be addressed more thoroughly. This also highlights the importance of qCLMS, as conclusions about structural changes based on the presence/absence of certain crosslinked species in database search results may be misleading if the absence of a species is due to under-sampling. We have not tried to collect the data with DIA since we would lose the quantitative information. It would be interesting to see if match between runs can recover some of the missing values. While this could provide evidence to support the under-sampling hypothesis, it would not recover the quantitative information.

We recommend performing label swap experiments and focusing downstream analysis on the crosslinks/monolinks that are identified on both experiments. Future development of multiplexed Qlinker reagents should help to alleviate under-sampling issues. See response to Reviewer #1.

(6) Lines 375 to 393 (the whole paragraph): extremely detailed and not easy to follow. Is that level of detail necessary to drive home that point or could it be visualized in enough detail to help follow the text?

We agree that the paragraph is quite detailed, but we feel that the level of detailed is necessary to describe the types of conformational changes that can be detected by the quantitative crosslinking data, and also illustrate the challenges of interpreting the structural basis for some crosslink abundance changes even when high resolution structural data exists.

To make it easier to follow, we added a sentence to the legend of Figure 5b. “In the holo-pol II structure (right), Switch 5 bending pulls Rpb1:D1442 away from K15, breaking the salt bridge that is formed in the core pol II structure (left). The increase in the abundances of the Rpb1:15-Rpb6:76 and Rpb1:15-Rpb6:72 crosslinks in holo-pol II is likely attributed to the salt bridge between K15 and D1442 in core pol II which impedes the NHS ester-based reaction between the epsilon amino group of K15 and the crosslinker.”

(7) Final paragraph in the results section - lines 397 and 398: "All of the intralinks involving Rpb4 are more abundant in holo-pol II as expected." If I understand that experiment correctly the intralinks with Rpb4 should not be present at all as Rpb4 has been deleted. Is that due to interference between the 126 and 127 channels in MS2? If so, then this also sets a bit of the upper limit of quantitative differences that can be seen. The authors should at least comment on that "limitation".

Yes, we shouldn’t detect any Rpb4 peptides in the sample derived from the Rpb4 knockout strain. The signal from Rpb4 peptides in the DRpb4 sample is likely due to co-eluting ions. To clarify, we changed the text to:

All of the intralinks involving Rpb4 are more abundant in the holo-pol II sample (even though we don’t expect any reporter ion signal from Rpb4 peptides derived from the ∆Rpb4 pol II sample, we still observed reporter ion signals from the channel corresponding to the DRpb4 sample, potentially due to the presence of low abundance, co-eluting ions)(lines 395-399).

(8) Materials and Methods - line 690: I am probably missing something but why were two different mass additions to lysine added to the search (I would have expected only one for the crosslinker)?

The 297 Da modification is for monolinked peptides with one end of the crosslinker hydrolyzed and 18 Da water molecule is added. The 279 Da modification is for crosslinks and sometimes for looplinks (crosslinks involving two lysine residues on the same tryptic peptide).

for - quote / critique - it is upon us, beyond our power to alter, and therefore to be accepted and made the best of. It is a waste of time to criticize the inevitable. - Andrew Carnegie - The Gospel of Wealth - alternatives - to - mainstream companies - cooperatives - Peer to Peer - Decentralized Autonomous Organization (DAO) - Fair Share Commons - B Corporations - Worker owned companies

quote / critique - it is upon us, beyond our power to alter, and therefore to be accepted and made the best of. It is a waste of time to criticize the inevitable. - Andrew Carnegie - The Gospel of Wealth - This is a defeatist attitude that does not look for a condition where both enormous inequality AND universal squalor can both eliminated - Today, there are a growing number of alternative ideas which can challenge this claim such as: - Cooperatives - example - Mondragon corporation with 70,000 employees - B Corporations - Fair Share Commons - Peer to Peer - Worker owned companies - Cosmolocal organizations - Decentralized Autonomous Organization (DAO)

for - quote / critique / question - Thus is the problem of Rich and Poor to be solved. The laws of accumulation will be left free; the laws of distribution free. Individualism will continue, but the millionaire will be but a trustee for the poor; intrusted for a season with a great part of the increased wealth of the community, but administering it for the community far better than it could or would have done for itself. - The Gospel of Wealth - Andrew Carnegie

quote / critique / question - Thus is the problem of Rich and Poor to be solved. The laws of accumulation will be left free; the laws of distribution free. Individualism will continue, but the millionaire will be but a trustee for the poor; intrusted for a season with a great part of the increased wealth of the community, but administering it for the community far better than it could or would have done for itself. - The Gospel of Wealth - Andrew Carnegie - The problem with this reasoning is that it is circular - By rewarding oneself an extreme and unfettered amount of wealth for one's entrepreneurship skills creates inequality in the first place - Competition that destroys other corporations ends up reducing jobs - At the end of life, the rich entrepreneur desires to give back to society the wealth that (s)he originally stole - If one had reasonable amounts of rewarding innovation instead of unreasonable amounts, the problem of inequality can be largely mitigated in the first place whilst still recognizing and rewarding individual effort and ingenuity

for - quote / critique - The price we pay for this salutary change is, no doubt, great - Andrew Carnegie

quote / critique - The price we pay for this salutary change is, no doubt, great - Andrew Carnegie - Carnegie goes on to write that the great freedoms offered by industrial mass production has an unavoidable price to be paid - Successful manufacturing and production cooperatives, B-Corporations, worker-owned companies, etc have disproved that it is an either-or situation. - Consider the case of the Spanish manufacturing giant, Mondragon, a federation of worker cooperatives employing 70,000 people located in Spain - where this price is NOT paid - Carnegie's essay reflects a perspective based on the time when he was alive - Were Carnegie alive today to witness the natural conclusion of his trend of progress in the Anthropocene, he would witness - extreme pollution levels of industrial mass production threatening to destabilize human civilization itself - astronomical wealth inequality - And these two are linked: - wealth inequality - a handful of elites have the same wealth as the bottom half of humanity - carbon inequality - that same handful pollutes as much as the bottom half of humanity

to - Mondragon cooperative - explore - https://hyp.is/GeIKao1rEe-9jA_97_KRBg/exploremondragon.com/en/ - Oxfam wealth and carbon inequality reports - https://jonudell.info/h/facet/?max=100&expanded=true&user=stopresetgo&exactTagSearch=true&any=oxfam

for - critique - destruction of Individualism - The Gospel of Wealth - Andrew Carnegie - individual / collective Gestalt - Deep Humanity

critique - destruction of Individualism - The Gospel of Wealth - Andrew Carnegie - From a Deep Humanity perspective, the individual and the collective are intertwingled - This is the individual / collective gestalt - Communism and Capitalism are both extreme poles - the truth lies somewhere in the middle - which acknowledges both are individual AND collective nature simultaneously - and works to balance them

for - critique - extreme wealth inequality cannot be avoided for the greater improvement of society - The Gospel of Wealth - Andrew Carnegie - stats - Mondragon corporation - comparison of pay difference between highest paid and lowest paid - adjacency - Gandhi quote - Andrew Carnegie beliefs in The Gospel of Wealth

critique - extreme wealth inequality cannot be avoided for the greater improvement of society - The Gospel of Wealth - Andrew Carnegie - It's a matter of degree - Wealth differences within US corporations of 344 to 1 are obscene and not necessary, as proven by - Wealth difference of 6 to 1 in Mondragon federation of cooperatives - To quote - Gandhi, there is enough to meet everyone's needs but not enough to meet everyone's greed - The great problem with such large wealth disparity is that those who know how to game the system can earn obscene amounts of money - and since the concept of luxury goods is made desirable and proportional to monetary wealth, it creates a positive feedback loop of insatiability - The combination of engaging in ever greater luxury lifestyle and power is intoxicating and addictive

to - stats - Mondragon corporation - comparison of pay difference between highest paid and lowest paid - https://hyp.is/QAxx-o14Ee-_HvN5y8aMiQ/www.csmonitor.com/Business/2024/0513/income-inequality-capitalism-mondragon-corporation

for - critique - extreme wealth a reward for rare management skills - Andrew Carnegie - The Gospel of Wealth - Mondragon counterexample - to - stats - Mondragon pay difference between highest and lowest paid - article - In this Spanish town, capitalism actually works for the workers - Christian Science Monitor - Erika Page - 2024, June 7

critique - extreme wealth a reward for rare management skills - Andrew Carnegie - The Gospel of Wealth - Mondragon counterexample - This is invalidated today by large successful cooperatives such as Mondragon

to - stats - Mondragon corporation - comparison of pay difference between highest paid and lowest paid - https://hyp.is/QAxx-o14Ee-_HvN5y8aMiQ/www.csmonitor.com/Business/2024/0513/income-inequality-capitalism-mondragon-corporation

for - quote / critique- Much better this great irregularity than universal squalor - Andrew Carnegie

quote / critique - Much better this great irregularity than universal squalor - Andrew Carnegie - Carnegie is writing from his perspective of the contrast between - life when he grew up, lived in an age of perceived universal squalor and - the world he helped shape through industrial mass production that produced high quality goods in such numbers that they became available to all - Yet, even before Carnegie, inequality had existed, for the world prior to Carnegie had its share of kings, queens, emperors and authoritarians - Even today, the best we might say of modern democracies is a decoupling of wealth and official governance - although even that is inaccurate as the thriving lobbying industry allows industrial magnates to decide upon rules of governance that are friendly towards their businesses - In contrast, from the commons perspective, and especially from the Cosmolocal movement of production, there is proposed a road that leads to - much less and much more tolerable levels of inequality and no universal squalor - a civilization existing within safe and just earth system boundaries

for - quote / critique - The Indians are today where civilized man then was

quote / critique - The Indians are today where civilized man then was - Andrew Carnegie - The Gospel of Wealth - Carnegie starts off his essay with this statement, that is meant to contrast how far industrial mass production has progressed society compared to the the rate of progress before it - It is an unfortunate choice of comparison as it is tainted with the mass genocide brought about by Carnegie's colonialist ancestors - Human civilization progressed in nonuniform spurts, with some parts of the world advancing greater than other parts at different times of human history

for - from - MSN article - How a poor boy from Scotland became the richest man on Earth - The life of Andrew Carnegie - Daniel Coughlin - essay - The Gospel of Wealth - Andrew Carnegie - philanthropy adjacency - Carnegie - The Gospel of Wealth - Anthropocene - critique

summary - It is interesting to read this article from the perspectives of a commons activist - The link to the MSN article that led me to Carnegie's essay is below and it provides a good summary of his life. - He came from a very challenging life of poverty, growing up in a family and in circumstances where they were constantly struggling to make ends meet - His is the story of the deep imprint of poverty providing him with motivation to escape it - Having risen to become the world's richest man, and then giving his fortune away due to the deep imprint of poverty experienced in childhood, - he formed an opinion on inequality and capitalist material production that was borne out of his experience as a successful entrepreneur and the contrast of quality of life between: - a pre-industralized society in which he was familiar from childhood experiences and - the profound material improvements accessible to all due to mass production that he helped to pioneer - In the essay, he sees the inequality found in society to be the price that needed to be paid for everyone to have access to a higher standard of living - This is where critical analysis from a modern post-Marxist, post-Capitalist perspective might provide an interesting critique, - especially from the anthropocene perspective, where the epitome of the system Carnegie praised has led to a state of environmental destruction so vast that Carnegie could never have foreseen it - A question: would Carnegie have written his essay differently were he alive to witness the environmental destruction of the Anthropocene?

from - MSN article - How a poor boy from Scotland became the richest man on Earth - The life of Andrew Carnegie - Daniel Coughlin - https://hyp.is/urXCfo1hEe-OdSMr4kqwyg/www.lovemoney.com/news/135656/the-astonishing-rags-to-riches-story-of-andrew-carnegie

first Norman King

A mouse the size of a New Your city rat jumped out at the cat, and the cat got scared for its life because the mouse was bigger than him

Working on that challenge and trying to fix something which can change that the page that no one is understanding.

This entails of a vacation that would be happening and veterans of the challenges and problems.

This explains how the oet veiws the cat as a extesion of his own soul, how they are alike yet simmilar all the same. They both have their challenges hey both overcome, taking resolve in ones company.

eLife Assessment

This useful study by Nandy and colleagues examined relationships between behavioral state, neural activity in cortical area V4, and trial-by-trial variability in the ability to detect weak visual stimuli. They present solid evidence indicating that certain changes in arousal and eye-position stability, along with patterns of synchrony in the activity of neurons in different layers of V4, can show modest correspondences to changes in the ability to correctly detect a stimulus. These findings are likely to be of interest to those who seek a deeper understanding of circuit mechanisms that underlie perception.

Reviewer #1 (Public review):

Summary:

In this study, Nandy and colleagues examine neural, physiological and behavioral correlates of perceptual variability in monkeys performing a visual change detection task. They used a laminar probe to record from area V4 while two macaque monkeys detected a small change in stimulus orientation that occurred at a random time in one of two locations, focusing their analysis on stimulus conditions where the animal was equally likely to detect (hit) or not-detect (miss) a briefly presented orientation change (target). They discovered two behavioral and physiological measures that are significantly different between hit and miss trials - pupil size tends to be slightly larger on hits vs. misses, and monkeys are more likely to miss the target on trials in which they made a microsaccade shortly before target onset. They also examined multiple measures of neural activity across the cortical layers and found some measures that are significantly different between hits and misses.

Strengths:

Overall the study is well executed and the analyses are appropriate (with some possible caveats discussed below).

Weaknesses:

I have two remaining concerns. First, with the exception of the pre-target microsaccades, the correlates of perceptual variability (differences between hits and misses) appear to be weak and disconnected. The GLM analysis of the predictive power of trial outcome based on the behavioral and neural measures is only discussed at the end of the paper. This analysis shows that some of the measures have no significant predictive power, while others cannot be examined using the GLM analysis because these measures cannot be estimated in single trials. Given these weak and disconnected effects, my overall sense is that the current results provide a limited advance to our understanding of the neural basis of perceptual variability.

In addition, because the authors combine data across stimulus contrasts, I am somewhat uneasy about the possible confounding effect of contrast. As expected, stimulus contrast affected the probability of hits vs. misses. Independently, contrast may have affected some of the physiological measurements. Therefore, showing that contrast is not the source of the covariations between the physiological/behavioral measurements and perception can be challenging, and I am not convinced that the authors have ruled this out as a possible confound. It is unclear why the authors had to vary contrast in the first place, and why the analyses had to be done by combining the data across contrasts or by ignoring contrast as a variable (e.g., in the GLM analysis).

Hi! Just showing you what an annotation looks like in context and also explaining what this is a bit more.

The FYW Committee is a committee comprised of full-timers at QC who teach in the first-year writing program and / or are experts in Writing Studies. We make decisions about stuff that happens in the FYW program. Formerly, we've also done things like review three-year contract materials.

Ah, I wish I could access their SIS and see the filter.

"Were" should be "was" as it is referring to the word "average," a singular quantity. "Were" would be used if the author was referring to multiple averages.

No values regarding sugar percent concentration are specified with the three repeated experiments. It is clear that the author repeated the experiment with different concentrations of sugar water when the reader refers to the graph. These values need to be included in the description.

It is unclear if the author is trying to make a general statement about calculations or if the author is trying to relay what actually happened during the experiment. The verb "is" must be changed to "was" to be in the past passive tense. And, the "liquid" needs to be specified. For ease of understanding, the previous sentence can be combined with this one: "Then, the mass of the liquid within the beaker was calculated by subtracting the initial mass from the final mass."

Abigail is doing what she can to provide for her family, she is currently very busy, this is probably why she hasn't attempted to make salt peter (white powder used to make gunpowder and preserve food)

In the second sentence of this paragraph Abigail mentions she is attending the sick, one of her neighbors and in this highlighted section she mentions how it has affected many other people and towns. Most likely just like Abigail was doing other women were also helping nurse the sick.

Thoughts: I find Abigail's actions important here because during a war it is vital to be in good health. Illnesses can bring death and also weaken, decreasing helping hands that could help them win this war.

Here Abigial is being resourceful. She has mention that her husband asked if she had made salt peter (white powder used to make gunpowder and preserve food)

But she has not attempted it yet, but she has information on who can provide that material to her husband and should he need it. She offers to make the purchase and send it to him.

Thoughts: Abigail is helping her husband, providing materials that would be vital to aide them in war and her husband is not taking her seriously about giving women equal rights.

Animal experimentation has been going on for hundreds of years and helped with pharmaceutical and illness research. Doing the same experiments on humans would not work because of the extent of the experiments and the types of tests preformed.

The comma is unnecessary. Also, using the preposition "by" when referring to subtraction creates confusion. The described values should be flipped: "The volume was calculated by subtracting the initial volume of the water in the graduated cylinder from the volume of the graduated cylinder after the metal rod had been added. To further clarify, numeric values should be used.

I don't have a problem with this kind of poisoning. When you stand up to a company like Kellog's that has money, expensive lawyers and cares only about their bottom line it needs to be done. The David and Goliath of it all begs for action to fighting against unfair work conditions for the ordinary worker.

for - stats - Mondragon corporation - pay difference comparison between highest paid and lowest paid - from - essay - The Gospel of Wealth - Andrew Carnegie - Carnegie organization

from - essay - The Gospel of Wealth - Andrew Carnegie - Carnegie organization - https://hyp.is/dIoiDo16Ee-0n2OpOK3lwg/www.carnegie.org/about/our-history/gospelofwealth/

stats - Mondragon corporation - comparison of pay difference between highest paid and lowest paid - Modragon - 6 to 1 - typical US - 344 to 1 - typical Spain - 77 to 1

This makes a lot of sense but is also incredible scary to know that someone is being watched and most likely being manipulated. The susceptible to scams and prone to addiction is probably the most frightening thing. I feel that is just evil to track people's vulnerabilities and possible use it against them.

Author response:

Review #1:

Also, they observed no difference in the binding free energy of phosphatidylserine with wild TREM2-Ig and mutant TREM2-Ig, which is a bit inconsistent with the previous report with experiment studies by Journal of Biological Chemistry 293, (2018), Alzheimer's and Dementia 17, 475-488 (2021), Cell 160, 1061-1071 (2015).

We directly note this contrast with experimental findings in the body of our work, particularly given the known limitations of free energy calculations in MD simulations, as outlined in the Limitations section. Our claim is that the loss of function in the R47H variant extends beyond decreased binding affinities and also impacts binding patterns. As stated in our manuscript: ‘Our observations for both sTREM2 and TREM2 indicate that R47H-induced dysfunction may result not only from diminished ligand binding but also an impaired ability to discriminate between different ligands in the brain, proposing a novel mechanism for loss-of-function.’

Perhaps the authors made significant efforts to run a number of simulations for multiple models, which is nearly 17 microseconds in total; none of the simulations has been repeated independently at least a couple of times, which makes me uncomfortable to consider this finding technically true. Most of the important conclusions that authors claimed, including the opposite results from previous research, have been made on the single run, which raises the question of whether this observation can be reproduced if the simulation has been repeated independently. Although the authors stated the sampling number and length of MD simulations in the current manuscript as a limitation of this study, it must be carefully considered before concluding rather than based on a single run.

The reviewer raises an interesting point regarding the repetition of individual simulations, a consideration we carefully evaluated during the design of this study. However, we believe our approach—running multiple independent models of the same system—offers a more rigorous methodology than simply repeating simulations of the same docked model. This strategy allows us to sample several distinct starting configurations, thereby minimizing biases introduced by docking algorithms and single-model reliance.

In our study, we demonstrate that within the 150 ns timescale of our protein/ligand (PL) simulations, the relatively small ligands are able to move from their initial docking positions to a specific binding site. While ideally, replicates of these independent models would further strengthen the findings, this was not computationally feasible given the unprecedented total duration of our simulations. Importantly, our conclusions are seldom based on the results of a single protein/PL simulation.

Moreover, the ergodic hypothesis suggests that over sufficiently long timescales, simulations will explore all accessible states. Additionally, we have performed several replicate simulations of our WT and R47H Ig-like domain models in solution, specifically to investigate CDR2 loop dynamics.

In this case, since the system involves only the protein and lacks the independent replicates seen in the protein/PL simulations, these runs were chosen to effectively capture the stochastic nature of CDR2 loop movement.

sTREM2 shows a neuroprotective effect in AD, even with the mutations with R47H, as evidenced by authors based on their simulation. sTREM2 is known to bind Aβ within the AD and reduce Aβ aggregation, whereas R47H mutant increases Aβ aggregation. I wonder why the authors did not consider Aβ as a ligand for their simulation studies. As a reader in this field, I would prefer to know the protective mechanism of sTREM2 in Aβ aggregation influenced by the stalk domain.

Our initial approach for this study used Aβ as a ligand rather than phospholipids. However, we noted the difficulties in simulating Aβ, particularly in choosing relevant Aβ structures and oligomeric states (n-mers). We believe that phospholipids represent an equally pertinent ligand for TREM2, given its critical role in lipid sensing and metabolism. Furthermore, there is growing recognition in the AD research community of the need to move beyond Aβ and focus on other understudied pathological mechanisms.

In a similar manner, why only one mutation is considered "R47H" for the study? There are more server mutations reported to disrupt tethering between these CDRs, such as T66M. Although this "T66M" is not associated with AD, I guess the stalk domain protective mechanism would not be biased among different diseases. Therefore, it would be interesting to see whether the findings are true for this T66M.

In most previous studies, the mechanism for CDR destabilization by mutant was explored, like the change of secondary structures and residue-wise interloop interaction pattern. While this is not considered in this manuscript, neither detailed residue-wise interaction that changed by mutant or important for 'ligand binding" or "stalk domain".

These are both excellent points that deserve extensive investigation. While R47H is the most common and prolific mutation in literature, an extensive catalog of other mutations is important to explore. We are currently preparing two separate publications that will delve into these gaps in more detail, as addressing them was beyond the scope of the present study.

The comparison between the wild and mutant and other different complex structures must be determined by particular statistical calculations to state the observed difference between different structures is significant. Since autocorrelation is one of the major concerns for MD simulation data for predicting statistical differences, authors can consider bootstrap calculations for predicting statistical significance.

We are currently working to address this comment to strengthen the validity of our results and statistical conclusions in the revised manuscript.  

Review #2:

The authors state that reported differences in ligand binding between the TREM2 and sTREM2 remain unexplained, and the authors cite two lines of evidence. The first line of evidence, which is true, is that there are differences between lipid binding assays and lipid signaling assays. However, signaling assays do not directly measure binding. Secondly, the authors cite Kober et al 2021 as evidence that sTREM2 and TREM2 showed different affinities for Abeta1-42 in a direct binding assay. Unfortunately, when Kober et al measured the binding of sTREM2 and Ig-TREM2 to Abeta they reported statistically identical affinities (Kd = 3.8 {plus minus} 2.9 µM vs 5.1 {plus minus} 3.7 µM) and concluded that the stalk did not contribute measurably to Abeta binding.

We appreciate the reviewer’s insight and acknowledge the need to clarify our interpretation of Kober et al. (2021). We will adjust and refocus how we reference this evidence from Kober et al. in our revised manuscript. 

In line with these findings, our energy calculations reveal that sTREM2 exhibits weaker—but still not statistically significant—binding affinities for phospholipids compared to TREM2. These results suggest that while overall binding affinity might be similar, differences in binding patterns or specific lipid interactions could still contribute to functional differences observed between TREM2 and sTREM2.

The authors appear to take simulations of the Ig domain (without any stalk) as a surrogate for the full-length, membrane-bound TREM2. They compare the Ig domain to a sTREM2 model that includes the stalk. While it is fully plausible that the stalk could interact with and stabilize the Ig domain, the authors need to demonstrate why the full-length TREM2 could not interact with its own stalk and why the isolated Ig domain is a suitable surrogate for this state.

We believe that this is a major limitation of all computational work of TREM2 to-date, and of experimental work which only presents the Ig-like domain. This is extensively discussed in the limitations section of our paper. Hence, we are currently working toward a manuscript that will be the first biologically relevant model of TREM2 in a membrane and will challenge the current paradigm of using the Ig-like domain as an experimental surrogate for TREM2.

eLife Assessment

This useful manuscript addresses some key molecular mechanisms on the neuroprotective roles of soluble TREM2 in neurodegenerative diseases. Thw study will advance our understanding of TREM2 mutations, particularly on the damaging effect of known TREM2 mutations, and also explain why soluble TREM2 can antagonize Aβ aggregation. However, the primary experimental method, MD simulations, suffers from limited sampling, rendering the results incomplete for definite conclusions.

Reviewer #1 (Public review):

In this manuscript, Saeb et al reported the mechanistic roles of the flexible stalk domain in sTREM2 function using molecular dynamics simulations. They have reported some interesting molecular bases explaining why sTREM2 shows protective effects during AD, such as partial extracellular stalk domain promoting binding preference and stabilities of sTREM2 with its ligand even in the presence of known AD-risk mutation, R47H. Furthermore, they found that the stalk domain itself acts as the site for ligand binding by providing an "expanded surface", known as 'Expanded Surface 2' together with the Ig-like domain. Also, they observed no difference in the binding free energy of phosphatidyl-serine with wild TREM2-Ig and mutant TREM2-Ig, which is a bit inconsistent with the previous report with experiment studies by Journal of Biological Chemistry 293, (2018), Alzheimer's and Dementia 17, 475-488 (2021), Cell 160, 1061-1071 (2015).

Perhaps the authors made significant efforts to run a number of simulations for multiple models, which is nearly 17 microseconds in total; none of the simulations has been repeated independently at least a couple of times, which makes me uncomfortable to consider this finding technically true. Most of the important conclusions that authors claimed, including the opposite results from previous research, have been made on the single run, which raises the question of whether this observation can be reproduced if the simulation has been repeated independently. Although the authors stated the sampling number and length of MD simulations in the current manuscript as a limitation of this study, it must be carefully considered before concluding rather than based on a single run.

sTREM2 shows a neuroprotective effect in AD, even with the mutations with R47H, as evidenced by authors based on their simulation. sTREM2 is known to bind Aβ within the AD and reduce Aβ aggregation, whereas R47H mutant increases Aβ aggregation. I wonder why the authors did not consider Aβ as a ligand for their simulation studies. As a reader in this field, I would prefer to know the protective mechanism of sTREM2 in Aβ aggregation influenced by the stalk domain.

In a similar manner, why only one mutation is considered "R47H" for the study? There are more server mutations reported to disrupt tethering between these CDRs, such as T66M. Although this "T66M" is not associated with AD, I guess the stalk domain protective mechanism would not be biased among different diseases. Therefore, it would be interesting to see whether the findings are true for this T66M.

In most previous studies, the mechanism for CDR destabilization by mutant was explored, like the change of secondary structures and residue-wise interloop interaction pattern. While this is not considered in this manuscript, neither detailed residue-wise interaction that changed by mutant or important for 'ligand binding" or "stalk domain".

The comparison between the wild and mutant and other different complex structures must be determined by particular statistical calculations to state the observed difference between different structures is significant. Since autocorrelation is one of the major concerns for MD simulation data for predicting statistical differences, authors can consider bootstrap calculations for predicting statistical significance.

Reviewer #2 (Public review):

Significance:

TREM2 is an immunomodulatory receptor expressed on myeloid cells and microglia in the brain. TREM2 consists of a single immunoglobular (Ig) domain that leads into a flexible stalk, transmembrane helix, and short cytoplasmic tail. Extracellular proteases can cleave TREM2 in its stalk and produce a soluble TREM2 (sTREM2). TREM2 is genetically linked to Alzheimer's disease (AD), with the strongest association coming from an R47H variant in the Ig domain. Despite intense interest, the full TREM2 ligand repertoire remains elusive, and it is unclear what function sTREM2 may play in the brain. The central goal of this paper is to assess the ligand-binding role of the flexible stalk that is generated during the shedding of TREM2. To do this, the authors simulate the behavior of constructs with and without stalk. However, it is not clear why the authors chose to use the isolated Ig domain as a surrogate for full-length TREM2. Additionally, experimental binding evidence that is misrepresented by the authors contradicts the proposed role of the stalk.

Summary and strengths:

The authors carry out MD simulations of WT and R47H TREM2 with and without the flexible stalk. Simulations are carried out for apo TREM2 and for TREM2 in complex with various lipids. They compare results using just the Ig domain to results including the flexible stalk that is retained following cleavage to generate sTREM2. The computational methods are well-described and should be reproducible. The long simulations are a strength, as exemplified in Figure 2A where a CDR2 transition happens at ~400-600 ns. The stalk has not been resolved in structural studies, but the simulations suggest the intriguing and readily testable hypothesis that the stalk interacts with the Ig domain and thereby contributes to the stability of the Ig domain and to ligand binding. I suspect biochemists interested in TREM2 will make testing this hypothesis a high priority.

Weaknesses:

Unfortunately, the work suffers from two fundamental flaws.

(1) The authors state that reported differences in ligand binding between the TREM2 and sTREM2 remain unexplained, and the authors cite two lines of evidence. The first line of evidence, which is true, is that there are differences between lipid binding assays and lipid signaling assays. However, signaling assays do not directly measure binding. Secondly, the authors cite Kober et al 2021 as evidence that sTREM2 and TREM2 showed different affinities for Abeta1-42 in a direct binding assay. Unfortunately, when Kober et al measured the binding of sTREM2 and Ig-TREM2 to Abeta they reported statistically identical affinities (Kd = 3.8 {plus minus} 2.9 µM vs 5.1 {plus minus} 3.7 µM) and concluded that the stalk did not contribute measurably to Abeta binding.

(2) The authors appear to take simulations of the Ig domain (without any stalk) as a surrogate for the full-length, membrane-bound TREM2. They compare the Ig domain to a sTREM2 model that includes the stalk. While it is fully plausible that the stalk could interact with and stabilize the Ig domain, the authors need to demonstrate why the full-length TREM2 could not interact with its own stalk and why the isolated Ig domain is a suitable surrogate for this state.

wichtig

eLife Assessment

The study provides a valuable showcase of a workflow to perform large-scale characterization of drug mechanisms of action using proteomics in which on-target and off-targets of 166 compounds using proteome solubility analysis in living cells and cell lysates were determined. The evidence supporting the claims of the authors is solid, however, the inclusion of more replicate experiments and more statistical rigor would have strengthened the study. This will be of broad interest to medicinal chemists, toxicologists, computational biologists and biochemists.

"I'm always trying to get back to the 20s a little bit." <br /> —John Dickerson, in Field Notes interview (2016) https://vimeo.com/169725470

Dickerson says he's got two screens on the computer in his office as well as an ipad and a phone. But he's also got a "notebook does only one thing". He's also got an old black lacquer Underwood (No. 4, 5, or 6?) on his office desk still.

Wonder if he uses it?

quote?

preconceived notion

look into?

sustainable agriculture backed up by financial incentives

economic incentive

soil is base for solving the problem

carbon sequestration

is this fast enough?

sustainable agriculture benefits for farmer, economy, and general public

harmful practices

rapidly declining

not specific but shows governmental policy needs to change

soil importance

potential source

getting worse

Mars CEO says he cares, but wheres the follow through

fertilizer problems

needs to be everyone

does he really care?

needs to happen asap to mitigate permanent damage and destruction

incentives and productivity

yes exactly that thank you

can help clean pollutted area

numbers

important for soil health and plant growth

QUOTE

holy grail of quotes

microbes role in climate change

why it sequesters carbon

Example of how this gets operationalized: There will be platforms (think Naviance on big data and personalized data steroids) that will help Learners discover right fit opportunities based in part on the credentials they already have. There will be savvy institutions connecting to others' credentials so as to increase the likelihood that Learners discover those institutions' program offerings. This will be akin to a sort of skill-based SEO approach as a recruitment/admissions strategy.

style varies on location

continued investment

literally my paper

more barriers

highlight

fertilizer

Probably the funniest portrayal of academia.

Insight: The energy efficiency of RISC processors makes them ideal for devices where power consumption is a critical factor, such as smartphones and other portable electronics.

Applications While RISC didn’t take off in desktop and server applications, it became dominant in embedded systems and mobile devices. RISC processors like ARM and MIPS are widely used in smartphones, tablets, gaming devices, and embedded systems.

Popular RISC Processors:

ARM: Dominates mobile and embedded markets (used in iPhones, Android devices). MIPS, PowerPC, SPARC: Found in various computing and embedded applications.

Advantages of RISC:

Speed: Simplified instructions mean faster execution per cycle. Cost: Fewer transistors reduce chip complexity and manufacturing costs. Energy Efficiency: Especially important in embedded systems and mobile devices.

Disadvantages of RISC:

Software Complexity: The need for more instructions places a heavier burden on software development. Blurring Lines: Modern CISC processors incorporate RISC-like features, reducing the distinction between the two architectures.

Insight: As the gap between RISC and CISC narrows, both architectures borrow elements from each other, creating hybrid designs in modern processors.

Performance RISC processors emphasize reducing the number of cycles per instruction (CPI), even at the cost of increasing the total number of instructions. This is in contrast to CISC, which focuses on reducing the number of instructions by using more complex ones.

Key Formula for Performance:

Time per program = Time per cycle × Cycles per instruction × Instructions per program

CISC vs. RISC:

CISC: Fewer instructions, but each instruction may take multiple cycles. RISC: More instructions but with fewer cycles per instruction, leading to faster performance in optimized scenarios.

Example: The multiplication process (MULT) in RISC involves multiple steps (LOAD, PROD, STORE), while CISC can perform the same task with a single command.

Insight: The programming model for RISC often increases the number of instructions required, but it optimizes the execution time for each instruction. This reduces the cycles per instruction (CPI), balancing overall performance.

Architecture and Programming The primary difference between RISC and CISC lies in how instructions are handled. RISC systems require that tasks be broken down into several smaller, simpler instructions, whereas CISC processors can perform complex tasks with fewer instructions.

RISC Characteristics:

Instructions executed in one clock cycle. Emphasizes pipelining to allow the processor to work on several instructions simultaneously. Large number of registers to reduce memory access time.

RISC Processors RISC (Reduced Instruction Set Computer) processors are designed to execute a smaller set of simple instructions. Historically, until the 1980s, CPUs were developed to handle complex instruction sets, known as CISC (Complex Instruction Set Computer) processors. RISC reversed this trend by simplifying instructions, which allows for faster execution and reduced hardware complexity.

Key Highlights:

Simplified Instructions: RISC processors handle fewer, simpler instructions than CISC, making execution faster. Lower Transistor Count: Fewer transistors in RISC chips make them cheaper and easier to design.

Insight: While simpler instructions often mean more lines of code for complex tasks, RISC systems are optimized for speed through streamlined execution.

I'm curious about how this relates to Eco's perspective on childhood. Are his examples just adults in children's clothes? And therefore, is the choice to portray children arbitrary or irrelevant? So I'm curious about how the themes of maturity and the themes of interpretation work together? Is interpretation itself a kind of maturity?

Can you use Noodletools and export your bibliography? It will do the MLA format for you and it looks sharp.

Okay, so what I'm getting is that cultural artifacts are sources for deep meaning and interpretation. I agree and I think Eco agrees. What I'm not getting past the second paragraph is how we're talking about maturity, adulthood, and the interaction between the worlds of adults and children.

*ciao

wwe

Ciao

For the most part though the missing type annotations won't change the behavior of the program. I guess unless you're using numeric literals with type annotations to change what the type of the number is. Othe wise it normally will just not type check.

Violation of the gradual guarantee. I'm coming around to this being fine but I think that it needs to be declared loudly in a languages design description and possibly alternative syntax for type declarations should be used so it's more obvious it's not just for clarity.

Trying a second annotation here

for - to - essay - The Gospel of Wealth - Andrew Carnegie

article details\ - title: How a poor boy from Scotland became the richest man on Earth - author: Daniel Coughlin - publication: https://www.msn.com/en-za/news/other/how-a-poor-boy-from-scotland-became-the-richest-man-on-earth/ss-AA1snaUl?ocid=widgetonlockscreen&cvid=7d9709f2a3784d09b14e49f448a1a4cc&ei=12#image=25 - date - 2024, Oct 18

Provide an example of such a campaign from each of the three countries. Cite your sources.

Explore ballot laws in another Western democracy and find either support for or against Nader's claim. Cite your source(s).

Under the US Constitution, what are the rules for becoming a Presidential candidate? Cite your source(s}

We conjure up the emotion in order to fulfill the goal

Interesting because I've heard the exact opposite statement

Choosing the next president by strictly majority vote would essentially make the whole process into a popularity contest. If this stayed in affect, a president with little to no real solutions regarding the improvement of the United States could be elected, setting back the nation by at least four years. However, this notion of selecting the five highest numbers and choosing the president based on their quality is how Hamilton ensures that corruption would not surface.

If less than half of the voting population is not in agreement on the election, it could be unsafe. Therefore, the House of Representatives will choose, in their opinion, who is the best fit. This could get out of hand as the HOR could be corrupt and may not represent the people accurately.

If all electors congregated in one place, there might be arguments and disagreements leading to the disruption of the task at hand.

Truy xuất: các phương pháp truy xuất dựa trên embedding của câu được sử dụng cùng với điểm tương đồng cosine làm thước đo đánh giá. K câu tương đồng gần nhất sẽ được sử dụng làm ngữ cảnh.

RA-IT: Một cách khác để thực hiện instruction-tuning trong việc chiết xuất có mục tiêu, được thể hiện khái quát ở hình 1. Trong cách tiếp cận này, mỗi mẫu sẽ được tăng cường với một đoạn ngữ cảnh được truy xuất. Đoạn ngữ cảnh này bao gồm k mẫu dữ liệu tương đồng về mặt ngữ cảnh được trích xuất từ bộ dữ liệu huấn luyện. Đoạn ngữ cảnh này được thêm vào đoạn hội thoại gốc. từ đó tạo ra mẫu instruction được tăng cường truy xuất. Bằng cách tinh chỉnh các mô hình ngôn ngữ (LMs) theo hướng này, LMs sẽ được trang bị khả năng tạo sinh câu trả lời NER cùng với RAG. Điều này có nghĩa là LMs có thể được cài đặt dễ dàng để thích ứng với nhiều kịch bản khác nhau bằng cách xác định xem có cần sử udngj RAG trong quá trình infer ko dựa trên các đặc tính cụ thể của kịch bản

IT đơn thuần: Mẫu instruction tuning ban đầu được sử dụng trong quá trình chiết xuất có mục tiêu được thể hiện ở bên dưới của hình 1, còn được gọi là mẫu IT đơn thuần. Trong mẫu này, mỗi câu đầu vào thô và các thực thể liên quan sẽ được hoán đổi thành một đoạn hội thoại có nhiều lượt.

Bước chuẩn bị: Chiết xuất có mục tiêu: Được làm dựa trên nghiên cứu UniNER, vốn đã thành công trong việc chiết xuất khả năng mạnh mẽ của chatGPT và truyền nó vào các mô hình nhỏ hơn mà không cần dữ liệu do con người gán nhãn. Qúa trình này bao gồm các bước: - Xây dựng dữ liệu: Các mẫu đầu vào thô được chọn từ nhiều domain đa dạng khác nhau và sử dụng chatGPT để gán nhãn. - Chiết xuất: Sau khi có được dữ liệu gán nhãn tự động, Instruction tuning được áp dụng để chiết xuất khả năng của chatGPT và truyền vào các mô hình nhỏ hơn.

Đóng góp chính của nhóm tác giả: - Tiến hành nghiên cứu RA-IT cho bài toán open NER. Các dữ liệu tăng cường truy xuất được chuẩn bị với các mẫu tương đồng về mặt ngữ nghĩa. Các thực nghiệm được tiến hành để đánh giá mức độ ảnh hưởng của các chiến lược truy xuất. - Xây dựng bộ dữ liệu IT cho bài toán open NER bằng tiếng Trung và tiến hành thực nghiệm đánh giá với cả tiếng Anh và tiềng Trung.

Các kết luận thu được: - RA-IT đạt được độ cải thiện bền vững với dữ liệu ở nhiều phạm vi khác nhau, từ đó thể hiện sự cần thiết của việc fine-tuning với ngữ cảnh được mở rộng. - Việc truy xuất các mẫu tương đồng về mặt ngữ cảnh làm cải thiện đáng kể chất lượng huấn luyện, tùy thuộc vào chiến lược chọn mẫu trích xuất. - Việc truy xuất các mẫu out-domain trong quá trình infer yêu cầu các chiến lược lọc mẫu để đạt được hiệu quả mong muốn. Ngược lại, việc cung cấp các mẫu in-domain sẽ làm gia tăng hiệu quả của quá trình infer.

Bằng hướng tiếp cận RA-IT, đối với mỗi mẫu huấn luyện, các mẫu tương đồng về mặt ngữ nghĩa sẽ được trích xuất từ bộ dữ liệu huấn luyện và được thêm vào mẫu dữ liệu huấn luyện gốc, tạo thành mẫu huấn luyện được tăng cường ngữ cảnh. Ngoài ra , một bộ dữ liệu huấn luyện bằng tiếng Trung cho bài toán openNER cũng được xây dựng và được dùng để đánh giá hiệu quả của mô hình trên cả tiếng Anh và tiếng Trung.

UniNER đã chắt lọc khả năng mạnh mẽ của ChatGPT trong bài toán open NER và truyền các mô hình bé hơn thông qua instruction tuning mà không cần dữ liệu do con người xây dựng. Nghiên cứu này được tiến hành theo hướng tương tự và RA-IT được điều tra theo hướng chắt lọc có mục tiêu (targeted distillation)

Ý tưởng chính: Sử dụng phương pháp instruction tuning có tăng cường truy hồi (RA-IT) cho bài toán IE, tập trung vào bài toán Open NER. Cụ thể, với mỗi mẫu huấn luyện, các mẫu khác có tính tương đồng về mặt ngữ nghĩa sẽ được truy xuất ra từ bộ dữ liệu và thêm các mẫu này vào đầu vào của mẫu huấn luyện ban đầu.

A covalent link (or covalent bond) occurs when two atoms share electrons, forming a stable connection between them. In DNA, covalent bonds link the deoxyribose sugar of one nucleotide to the phosphate group of the next,

When you are programming, you are writing a control flow diagrams embedded with state transition methods through code.

Acc to structured program theorem, You essentially need three control structures to write any computable program. 1. Sequence <code> <code> <code> ... 2. Selection if <condition> | <code_this> # if true else <code_that> # if false 3. Iteration <loop> | <code> # exists for do..while | if <condition> | escape # if true | <code> # exists for while repeat <loop>

Due to the reliable ubiquity of the first structure, any set of sequenced program statements could be deemed as a code block. Then, control flow structures command the order in which these various code blocks are executed.

There are various control flow methods. * Conditionals for selection (like if, switch...) * Loops for iteration (like for, while..) * Routines for abstraction (like function, class...)

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

PPARgamma is a nuclear receptor that binds to orthosteric ligands to coordinate transcriptional programs that are critical for adipocyte biogenesis and insulin sensitivity. Consequently, it is a critical therapeutic target for many diseases, but especially diabetes. The malleable nature and promiscuity of the PPARgamma orthosteric ligand binding pocket have confounded the development of improved therapeutic modulators. Covalent inhibitors have been developed but they show unanticipated mechanisms of action depending on which orthosteric ligands are present. In this work, Shang and Kojetin present a compelling and comprehensive structural, biochemical, and biophysical analysis that shows how covalent and noncovalent ligands can co-occupy the PPARgamma ligand binding pocket to elicit distinctive preferences of coactivator and corepressor proteins. Importantly, this work shows how the covalent inhibitors GW9662 and T0070907 may be unreliable tools as pan-PPARgamma inhibitors despite their widespread use.

Strengths:

- Highly detailed structure and functional analyses provide a comprehensive structure-based hypothesis for the relationship between PPARgamma ligand binding domain co-occupancy and allosteric mechanisms of action. - Multiple orthogonal approaches are used to provide high-resolution information on ligand binding poses and protein dynamics.

- The large number of x-ray crystal structures solved for this manuscript should be applauded along with their rigorous validation and interpretation.

Weaknesses

- Inclusion of statistical analysis is missing in several places in the text. - Functional analysis beyond coregulator binding is needed.

We added additional statistical analyses as recommended (Source Data 1, a Microsoft Excel spreadsheet).

Related to functional analysis, we cite and studies from our previous publication (Hughes et al. Nature Communications 2014 5:3571) where we demonstrated that the covalent inhibitor ligands (GW9662 and T0070907) do not block the activity of other ligands using a PPARγ transcriptional reporter assay and gene expression analysis in 3T3-L1 preadipocytes. Our study here expands on this finding and other published studies showing the structural mechanism for the lack of blocking activity by the covalent inhibitors.

Reviewer #2 (Public Review):

Summary:

The flexibility of the ligand binding domain (LBD) of NRs allows various modes of ligand binding leading to various cellular outcomes. In the case of PPARγ, it's known that two ligands can co-bind to the receptor. However, whether a covalent inhibitor functions by blocking the binding of a non-covalent ligand, or co-bind in a manner that weakens the binding of a non-covalent ligand remains unclear. In this study, the authors first used TR-FRET and NMR to demonstrate that covalent inhibitors (such as GW9662 and T0070907) weaken but do not prevent non-covalent synthetic ligands from binding, likely via an allosteric mechanism. The AF-2 helix can exchange between active and repressive conformations, and covalent inhibitors shift the conformation toward a transcriptionally repressive one to reduce the orthosteric binding of the non-covalent ligands. By co-crystal studies, the authors further reveal the structural details of various non-covalent ligand binding mechanisms in a ligand-specific manner (e.g., an alternate binding site, or a new orthosteric binding mode by alerting covalent ligand binding pose).

Strengths:

The biochemical and biophysical evidence presented is strong and convincing.

Weaknesses:

However, the co-crystal studies were performed by soaking non-covalent ligands to LBD pre-crystalized with a covalent inhibitor. Since the covalent inhibitors would shift the LBD toward transcriptionally repressive conformation which reduces orthosteric binding of non-covalent ligands, if the sequence was reversed (i.e., soaking a covalent inhibitor to LBD pre-crystalized with a non-covalent ligand), would a similar conclusion be drawn? Additional discussion will broaden the implications of the conclusion.

This is an interesting point, which we now expand upon in a new (third) paragraph of the discussion in our revised manuscript:

“In our previous study, we observed synthetic and natural/endogenous ligand co-binding via co-crystallography where preformed crystals of PPARγ LBD bound to unsaturated fatty acids (UFAs) were soaked with a synthetic ligand, which pushed the bound UFA to an alternate site within the orthosteric ligand-binding pocket 8. In the scenario of synthetic ligand cobinding with a covalent inhibitor, it is possible that soaking a covalent inhibitor into preformed crystals where the PPARγ LBD is already bound to a non-covalent ligand may prove to be difficult. The covalent inhibitor would need to flow through solvent channels within the crystal lattice, which may not be a problem. However, upon reaching the entrance surface to the orthosteric ligand-binding pocket, it may be difficult for the covalent inhibitor to gain access to the region of the orthosteric pocket required for covalent modification as the larger non-covalent ligand could block access. This potential order of addition problem may not be a problem for studies in solution or in cells, where the non-covalent ligand can more freely exchange in and out of the orthosteric pocket and over time the covalent reaction would reach full occupancy.”

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

- IC50 or EC50 values are not reported for the coregulator interaction assays, R2 for fit should also be reported where Ki and IC50s are disclosed.

We now report fitting statistics and IC50/EC50 values when possible in Figure 2B and Source Data 1 along with R2 values for the fit. We note that some data do not show complete or robust enough binding curves to faithfully fit to a dose response equation.

-  Reporter gene or qPCR should be performed for the combinations of covalent and noncovalent ligands to show how these molecules impact transcriptional activities rather than just coregulator binding profiles.

We previously performed PPARγ transcriptional reporter assay and gene expression analysis in 3T3-L1 preadipocytes to demonstrate that cotreatment of a covalent inhibitor (GW9662 or T0070907) with a non-covalent ligand does not block activity of the non-covalent ligand and showed cobinding-induced activation relative to DMSO control (Hughes et al., 2024 Nature Communications). We did not specifically mention this in our original manuscript, but we now call this out in the first paragraph of the results section.

- Inclusion of a structure figure to show the different helix 12 orientations should be included in the introduction. Likewise, how the overall structure of the LBD changes as a result of the cobinding in the discussion or a summary model would be helpful.

Our revised manuscript includes a structure figure called out in the introduction describing the active and repressive helix 12 PPARγ LBD conformations (new Figure 1). There are no major changes to the overall structure of the LBD compared to the active conformation that crystallized, so we did not include a summary model figure but we do refer readers to our previous paper (Shang and Kojetin, Structure 2021 29(9):940-950) in the penultimate paragraph of the discussion. We also added the following sentence to the crystallography results section related to the overall LBD changes:

“The structures show high structural similarity to the transcriptionally active LBD conformation with rmsd values ranging from 0.77–1.03Å (Supplementary Table S2)”

A typo in paragraph 3 of the discussion says "long-live" when it should probably say "long-lived."

We corrected this typo.

Reviewer #2 (Recommendations For The Authors):

It's interesting that ligand-specific binding mode of non-covalent ligands was observed. Would modifications of the chemical structure of a covalent inhibitor alter the allosteric binding behavior of non-covalent ligands in a predictive manner? If so, how can such SAR be used to guide the design of covalent inhibitors to more broadly and effectively inhibit agonists of various chemical structures? Discussion on this topic could be valuable.

This is an interesting point, which we now discuss in the penultimate and last paragraphs of the discussion:

“Another way to test this structural model could be through the use of covalent PPARγ inverse agonist analogs with graded activity 23, where one might posit that covalent inverse agonist analogs that shift the LBD conformational ensemble towards a fully repressive LBD conformation may better inhibit synthetic ligand cobinding.”

“It may be possible to use the crystal structures we obtained to guide structure-informed design of covalent inhibitors that would physically block cobinding of a synthetic ligand. This could be the potential mechanism of a newer generation covalent antagonist inhibitor we developed, SR16832, that more completely inhibit alternate site ligand binding of an analog of MRL20, rosiglitazone and the UFA docosahexaenoic acid (DHA)

21 and thus may be a better choice for the field to use as a covalent ligand inhibitor of PPARγ.”

eLife Assessment

This landmark study elucidates the intricate structural mechanisms by which both covalent and non-covalent synthetic ligands can co-occupy the binding pocket of the nuclear receptor transcription factor PPARγ. Through a compelling integration of structural, biochemical, and biophysical evidence, the authors challenge the reliability of two commonly used covalent inhibitors. These findings have far-reaching implications for the broader field of nuclear receptor research. This work will be of high interest to structural biologists and biochemists exploring ligand interactions within the nuclear receptor superfamily.

Reviewer #1 (Public review):

Summary:

PPARgamma is a nuclear receptor that binds to orthosteric ligands to coordinate transcriptional programs that are critical for adipocyte biogenesis and insulin sensitivity. Consequently, it is a critical therapeutic target for many diseases but especially diabetes. The malleable nature and promiscuity of the PPARgamma orthosteric ligand binding pocket has confounded the development of improved therapeutic modulators. Covalent inhibitors have been developed but they show unanticipated mechanisms of action depending on which orthosteric ligands are present. In this work, Shang and Kojetin present a compelling and comprehensive structural, biochemical, and biophysical analysis that shows how covalent and noncovalent ligands can co-occupy the PPARgamma ligand binding pocket to elicit distinctive preferences of coactivator and corepressor proteins. Importantly, this work shows how the covalent inhibitors GW9662 and T0070907 may be unreliable tools as pan-PPARgamma inhibitors despite their wide-spread use.

Strengths:

- Highly detailed structure and functional analyses provide a comprehensive structure-based hypothesis for the relationship between PPARgamma ligand binding domain co-occupancy and allosteric mechanisms of action.<br /> - Multiple orthogonal approaches are used to provide high resolution information on ligand binding poses and protein dynamics.<br /> - The large number of x-ray crystal structures solved for this manuscript should be applauded along with their rigorous validation and interpretation.

Reviewer #2 (Public review):

Summary:

The flexibility of the ligand binding domain (LBD) of NRs allows various modes of ligand binding leading to various cellular outcomes. In the case of PPARγ, it's known that two ligands can cobind to the receptor. However, whether a covalent inhibitor functions by blocking the binding of a non-covalent ligand, or cobind in a manner that weakens the binding of a non-covalent ligand remains unclear. In this study, the authors first used TR-FRET and NMR to demonstrate that covalent inhibitors (such as GW9662 and T0070907) weaken but do not prevent non-covalent synthetic ligands from binding, likely via an allosteric mechanism. The AF-2 helix can exchange between active and repressive conformations, and covalent inhibitors shift the conformation toward a transcriptionally repressive one to reduce orthosteric binding of the non-covalent ligands. By co-crystal studies, the authors further reveal the structural details of various non-covalent ligand binding mechanisms in a ligand specific manner (e.g., an alternate binding site, or a new orthosteric binding mode by alerting covalent ligand binding pose).

Strengths:

The biochemical and biophysical evidence as presented is strong and convincing.

Additional comments:

The co-crystal studies were performed by soaking a non-covalent ligand to LBD pre-crystalized with a covalent inhibitor. Since the covalent inhibitors would shift the LBD toward transcriptionally repressive conformation which reduces orthosteric binding of non-covalent ligands, one might ask if the sequence was reversed (i.e., soaking a covalent inhibitor to LBD pre-crystalized with a non-covalent ligand), would similar conclusion be drawn? The authors have reasonably speculated that it might be difficult to soak a covalent inhibitor into preformed crystals where the PPARγ LBD is already bound to a non-covalent ligand, because the larger non-covalent ligand could block the covalent inhibitor to gain access to the region of the orthosteric pocket required for covalent modification.

eLife Assessment

The manuscript presents an important model for the field of endosome maturation, providing perspective on the role of the deubiquitinating enzyme UPS-50/USP8 in the process. The evidence presented in the paper is clear, incorporating well-designed experiments that suggest the dual actions of UPS-50 and USP8 in the conversion of early endosomes into late endosomes. Overall, the work is convincing and centers on an intriguing subject.

Reviewer #1 (Public review):

Summary:

The manuscript focuses on the role of the deubiquitinating enzyme UPS-50/USP8 in endosome maturation. The authors aimed to clarify how this enzyme drives the conversion of early endosomes into late endosomes. Overall, they did achieve their aims in shedding light on the precise mechanisms by which UPS-50/USP8 regulates endosome maturation. The results support their conclusions that UPS-50 acts by disassociating RABX-5 from early endosomes to deactivate RAB-5 and by recruiting SAND-1/Mon1 to activate RAB-7. This work is commendable and will have a significant impact on the field. The methods and data presented here will be useful to the community in advancing our understanding of endosome maturation and identifying potential therapeutic targets for diseases related to endosomal dysfunction. It is worth noting that further investigation is required to fully understand the complexities of endosome maturation. However, the findings presented in this manuscript provide a solid foundation for future studies.

Strengths:

The major strengths of this work lie in the well-designed experiments used to examine the effects of UPS-50 loss. The authors employed confocal imaging to obtain a picture of the aftermath of USP-50 loss. Their findings indicated enlarged early endosomes and MVB-like structures in cells deficient in USP-50/USP8.

Weaknesses:

Specifically, there is a need for further investigation to accurately characterize the anomalous structures detected in the ups-50 mutant. Also, the correlation between the presence of these abnormal structures and ESCRT-0 is yet to be addressed, and the current working model needs to be revised to prevent any confusion between enlarged early endosomes and MVBs.

Reviewer #2 (Public review):

Summary:

In this study, the authors study how the deubiquitinase USP8 regulates endosome maturation in C. elegans and mammalian cells. The authors have isolated USP8 mutant alleles in C. elegans and used multiple in vivo reporter lines to demonstrate the impact of USP8 loss-of-function on endosome morphology and maturation. They show that in USP8 mutant cells, the early endosomes and MVB-like structures are enlarged while the late endosomes and lysosomal compartments are reduced. They elucidate that USP8 interacts with Rabx5, a guanine nucleotide exchange factor (GEF) for Rab5, and show that USP8 likely targets specific lysine residue of Rabx5 to dissociate it from early endosomes. They also find that localization of USP8 to early endosomes are disrupted in Rabx5 mutant cells. They observe that in both Rabx5 and USP8 mutant cells, the Rab7 GEF SAND-1 puncta which likely represents late endosomes are diminished, although that Rabex5 are accumulated in USP8 mutant cells. The authors provide evidence that USP8 regulates endosomal maturation in a similar fashion in mammalian cells. Based on their observations they propose that USP8 dissociates Rabex5 from early endosomes and enhances the recruitment of SAND-1 to promote endosome maturation.

Strengths:

The major highlights of this study include the direct visualization of endosome dynamics in a living multi-cellular organism, C. elegans. The high-quality images provide clear in vivo evidences to support the main conclusions. The authors have generated valuable resources to study mechanisms involved in endosome dynamics regulation in both the worm and mammalian cells, which would benefit many members in the cell biology community. The work identifies a fascinating link between USP8 and the Rab5 guanine nucleotide exchange factor Rabx5, which expands the targets and modes of action of USP8. The findings make a solid contribution toward the understanding of how endosomal trafficking is controlled.

Weaknesses:

- The authors utilized multiple fluorescent protein reporters, including those generated by themselves, to label endosomal vesicles. Although these are routine and powerful tools for studying endosomal trafficking, these results cannot tell that whether the endogenous proteins (Rab5, Rabex5, Rab7, etc.) are affected in the same fashion. Note that the authors have provided convincing evidence about the effects on Rab proteins in the revised manuscript.<br /> - The authors clearly demonstrated a link between USP8 and Rabx5, and they showed that cells deficient of both factors displayed similar defects in late endosomes/lysosomes. But the authors didn't confirm whether and/or to which extent that USP8 regulates endosome maturation through Rabx5. Additional genetic and molecular evidence might be required to better support their working model. Note that the authors have provided convincing evidence about the role of USP8-Rabx5 axis in the revised manuscript.

Reviewer #3 (Public review):

Summary:

The authors elucidated the role of USP8 in the endocytic pathway. Using C. elegans epithelial cells as a model, they observed that when USP8 function is lost, the cells have a decreased number and size in lysosomes. Since USP8 was already known to be a protein linked to ESCRT components, they looked into what role USP8 might play in connecting lysosomes and multivesicular bodies (MVB). They observed fewer ESCRT-associated vesicles but an increased number of abnormal enlarged vesicles (aberrant early endosomes) when USP8 function was lost. They showed that USP8 interacts with Rabx5 to dissociate it from early endosomes promoting the recruitment of the Rab7 GEF SAND-1/Mon1 and the maturation of the endosomes. The authors provided evidence that USP8 regulates endosomal maturation in a similar fashion in mammalian cells.

Strengths:

The use of two models, C. elegans and a mammalian cell line to describe a similar mechanism.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review): 

Summary: 

The manuscript focuses on the role of the deubiquitinating enzyme UPS-50/USP8 in endosome maturation. The authors aimed to clarify how this enzyme drives the conversion of early endosomes into late endosomes. Overall, they did achieve their aims in shedding light on the precise mechanisms by which UPS-50/USP8 regulates endosome maturation. The results support their conclusions that UPS-50 acts by disassociating RABX-5 from early endosomes to deactivate RAB-5 and by recruiting SAND-1/Mon1 to activate RAB-7. This work is commendable and will have a significant impact on the field. The methods and data presented here will be useful to the community in advancing our understanding of endosome maturation and identifying potential therapeutic targets for diseases related to endosomal dysfunction. It is worth noting that further investigation is required to fully understand the complexities of endosome maturation. However, the findings presented in this manuscript provide a solid foundation for future studies. 

We thank this reviewer for the instructive suggestions and encouragement.

Strengths: 

The major strengths of this work lie in the well-designed experiments used to examine the effects of UPS-50 loss. The authors employed confocal imaging to obtain a picture of the aftermath of the USP-50 loss. Their findings indicated enlarged early endosomes and MVB-like structures in cells deficient in USP-50/USP8. 

We thank this reviewer for the instructive suggestions and encouragement.

Weaknesses: 

Specifically, there is a need for further investigation to accurately characterize the anomalous structures detected in the usp-50 mutant. Also, the correlation between the presence of these abnormal structures and ESCRT-0 is yet to be addressed, and the current working model needs to be revised to prevent any confusion between enlarged early endosomes and MVBs. 

Excellent suggestions. USP8 has been identified as a protein associated with ESCRT components, which are crucial for endosomal membrane deformation and scission, leading to the formation of intraluminal vesicles (ILVs) within multivesicular bodies (MVBs). In usp-50 mutants, we observed a significant reduction in the punctate signals of HGRS-1::GFP and STAM-1 (Figure 1G and H; and Figure1-figure supplement 1B), indicating a disruption in ESCRT-0 complex localization (Author response image 1). Additionally, lysosomal structures are markedly reduced in these mutants. In contrast, we found that early endosomes, as marked by FYVE, RAB-5, RABEX5, and EEA1, are significantly enlarged in usp-50 mutants. Electron microscopy (EM) imaging further revealed an increase in large cellular vesicles containing various intraluminal structures. Given the reduction in lysosomal structures and the enlargement of early endosomes in usp-50 mutants, these enlarged vesicles are likely aberrant early endosomes rather than late endosomal or lysosomal structures. To address potential confusion, we have revised the manuscript according to the reviewer's comments and updated the model to accurately reflect these observations.

Reviewer #2 (Public Review): 

Summary: 

In this study, the authors study how the deubiquitinase USP8 regulates endosome maturation in C. elegans and mammalian cells. The authors have isolated USP8 mutant alleles in C. elegans and used multiple in vivo reporter lines to demonstrate the impact of USP8 loss-of-function on endosome morphology and maturation. They show that in USP8 mutant cells, the early endosomes and MVB-like structures are enlarged while the late endosomes and lysosomal compartments are reduced. They elucidate that USP8 interacts with Rabx5, a guanine nucleotide exchange factor (GEF) for Rab5, and show that USP8 likely targets specific lysine residue of Rabx5 to dissociate it from early endosomes. They also find that the localization of USP8 to early endosomes is disrupted in Rabx5 mutant cells. They observe that in both Rabx5 and USP8 mutant cells, the Rab7 GEF SAND-1 puncta which likely represents late endosomes are diminished, although Rabex5 is accumulated in USP8 mutant cells. The authors provide evidence that USP8 regulates endosomal maturation in a similar fashion in mammalian cells. Based on their observations they propose that USP8 dissociates Rabex5 from early endosomes and enhances the recruitment of SAND-1 to promote endosome maturation. 

We thank this reviewer for the instructive suggestions and encouragement.

Strengths: 

The major highlights of this study include the direct visualization of endosome dynamics in a living multi-cellular organism, C. elegans. The high-quality images provide clear in vivo evidence to support the main conclusions. The authors have generated valuable resources to study mechanisms involved in endosome dynamics regulation in both the worm and mammalian cells, which would benefit many members of the cell biology community. The work identifies a fascinating link between USP8 and the Rab5 guanine nucleotide exchange factor Rabx5, which expands the targets and modes of action of USP8. The findings make a solid contribution toward the understanding of how endosomal trafficking is controlled. 

We thank this reviewer for the instructive suggestions and encouragement.

Weaknesses: 

- The authors utilized multiple fluorescent protein reporters, including those generated by themselves, to label endosomal vesicles. Although these are routine and powerful tools for studying endosomal trafficking, these results cannot tell whether the endogenous proteins (Rab5, Rabex5, Rab7, etc.) are affected in the same fashion. 

Good suggestion. Indeed, to test whether the endogenous proteins (Rab5, Rabex5, Rab7, etc.) are affected in the same fashion as fluorescent protein reporters, we supplemented our approach with the utilization of endogenous markers. These markers, including Rab5, RAB-5, Rabex5, RABX-5, and EEA1 for early endosomes, as well as RAB-7, Mon1a, and Mon1b for late endosomes, were instrumental in our investigations (refer to Figure 3, Figure 6, Figure 5-figure supplement 1, Figure 5-figure supplement 2, and Figure 6-figure supplement 1). Our comprehensive analysis, employing various methodologies such as tissue-specific fused proteins, CRISPR/Cas9 knock-in, and antibody staining, consistently highlights the critical role of USP8 in early-to-late endosome conversion.

- The authors clearly demonstrated a link between USP8 and Rabx5, and they showed that cells deficient in both factors displayed similar defects in late endosomes/lysosomes. However, the authors didn't confirm whether and/or to which extent USP8 regulates endosome maturation through Rabx5. Additional genetic and molecular evidence might be required to better support their working model. 

Excellent point. To test whether USP-50 regulates endosome maturation through RABX-5, we performed additional genetic analyses. In rabx-5(null) mutant animals, the morphology of 2xFYVE-labeled early endosomes is comparable to that of wild-type controls (Figure 4H and I). Introducing the rabx-5(null) mutation into usp-50(xd413) backgrounds resulted in a significant suppression of the enlarged early endosome phenotype characteristic of usp-50(xd413) mutants (Figure 4H and I). These findings suggest that USP-50 may modulate the size of early endosomes through its interaction with RABX-5.

Reviewer #3 (Public Review): 

Summary: 

The authors were trying to elucidate the role of USP8 in the endocytic pathway. Using C. elegans epithelial cells as a model, they observed that when USP8 function is lost, the cells have a decreased number and size in lysosomes. Since USP8 was already known to be a protein linked to ESCRT components, they looked into what role USP8 might play in connecting lysosomes and multivesicular bodies (MVB). They observed fewer ESCRT-associated vesicles but an increased number of "abnormal" enlarged vesicles when USP8 function was lost. At this specific point, it's not clear what the objective of the authors was. What would have been their hypothesis addressing whether the reduced lysosomal structures in USP8 (-) animals were linked to MVB formation? Then they observed that the abnormally enlarged vesicles, marked by the PI3P biosensor YFP-2xFYVE, are bigger but in the same number in USP8 (-) compared to wild-type animals, suggesting homotypic fusion. They confirmed this result by knocking down USP8 in a human cell line, and they observed enlarged vesicles marked by YFP-2xFYVE as well. At this point, there is quite an important issue. The use of YFP-2xFYVE to detect early endosomes requires the transfection of the cells, which has already been demonstrated to produce differences in the distribution, number, and size of PI3P-positive vesicles (doi.org/10.1080/15548627.2017.1341465). The enlarged vesicles marked by YFP-2xFYVE would not necessarily be due to the loss of UPS8. In any case, it appears relatively clear that USP8 localizes to early endosomes, and the authors claim that this localization is mediated by Rabex-5 (or Rabx-5). They finally propose that USP8 dissociates Rabx-5 from early endosomes facilitating endosome maturation. 

Weaknesses: 

The weaknesses of this study are, on one side, that the results are almost exclusively dependent on the overexpression of fusion proteins. While useful in the field, this strategy does not represent the optimal way to dissect a cell biology issue. On the other side, the way the authors construct the rationale for each approximation is somehow difficult to follow. Finally, the use of two models, C. elegans and a mammalian cell line, which would strengthen the observations, contributes to the difficulty in reading the manuscript. 

The findings are useful but do not clearly support the idea that USP8 mediates Rab5-Rab7 exchange and endosome maturation, In contrast, they appear to be incomplete and open new questions regarding the complexity of this process and the precise role of USP8 within it. 

We thank this reviewer for the insightful comments. Fluorescence-fused proteins serve as potent tools for visualizing subcellular organelles both in vivo and in live settings. Specifically, in epidermal cells of worms, the tissue-specific expression of these fused proteins is indispensable for studying organelle dynamics within living organisms. This approach is necessitated by the inherent limitations of endogenously tagged proteins, whose fluorescence signals are often weak and unsuitable for live imaging or genetic screening purposes. Acknowledging concerns raised by the reviewer regarding potential alterations in organelle morphology due to overexpression of certain fused proteins, we supplemented our approach with the utilization of endogenous markers. These markers, including Rab5, RAB-5, Rabex5, RABX-5, and EEA1 for early endosomes, as well as RAB-7, Mon1a, and Mon1b for late endosomes, were instrumental in our investigations (refer to Figure 3, Figure 6, Figure 5-figure supplement 1, Figure 5-figure supplement 2, and Figure 6-figure supplement 1). Our comprehensive analysis, employing various methodologies such as tissue-specific fused proteins, CRISPR/Cas9 knock-in, and antibody staining, consistently highlights the critical role of USP8 in early-to-late endosome conversion. Specifically, we discovered that the recruitment of USP-50/USP8 to early endosomes is depending on Rabex5. However, instead of stabilizing Rabex5, the recruitment of USP-50/USP8 leads to its dissociation from endosomes, concomitantly facilitating the recruitment of the Rab7 GEF SAND-1/Mon1. In cells with loss-of-function mutations in usp-50/usp8, we observed enhanced RABX-5/Rabex5 signaling and mis-localization of SAND-1/Mon1 proteins from endosomes. Consequently, this disruption impairs endolysosomal trafficking, resulting in the accumulation of enlarged vesicles containing various intraluminal contents and rudimentary lysosomal structures.

Through an unbiased genetic screen, verified by cultured mammalian cell studies, we observed that loss-of-function mutations in usp-50/usp8 result in diminished lysosome/late endosomes. Electron microscopy (EM) analysis indicated that usp-50 mutation leads to abnormally enlarged vesicles containing various intraluminal structures in worm epidermal cells. USP8 is known to regulate the endocytic trafficking and stability of numerous transmembrane proteins. Given that lysosomes receive and degrade materials generated by endocytic pathways, we hypothesized that the abnormally enlarged vesicular structures observed in usp-50 or usp8 mutant cells correspond to the enlarged vesicles coated by early endosome markers. Indeed, in the absence of usp8/usp-50, the endosomal Rab5 signal is enhanced, while early endosomes are significantly enlarged. Given that Rab5 guanine nucleotide exchange factor (GEF), Rabex5, is essential for Rab5 activation, we further investigated its dynamics. Additional analyses conducted in both worm hypodermal cells and cultured mammalian cells revealed an increase of endosomal Rabex5 in response to usp8/usp-50 loss-of-function. Live imaging studies further demonstrated active recruitment of USP8 to newly formed Rab5-positive vesicles, aligning spatiotemporally with Rabex5 regulation. Through systematic exploration of putative USP-50 binding partners on early endosomes, we identified its interaction with Rabex5. Comprehensive genetics and biochemistry experiments demonstrated that USP8 acts through K323 site de-ubiquitination to dissociate Rabex5 from early endosomes and promotes the recruitment of the Rab7 GEF SAND-1/Mon1. In summary, our study began with an unbiased genetic screen and subsequent examination of established theories, leading to the formulation of our own hypothesis. Through multifaceted approaches, we unveiled a novel function of USP8 in early-to-late endosome conversion.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(1) Within Figures 1K-N, diverse anomalous structures were detected in the usp-50 mutant. Further scrutiny is needed to definitively characterize these structures, particularly as the images in Figures 1M and 1L exhibit notable similarities to lamellar bodies.

We thank the reviewer for the insightful question regarding the resemblance between the vesicles observed in our study and lamellar bodies (LBs). Lamellar bodies are specialized organelles involved in lipid storage and secretion1, prominently studied in keratinocytes of the skin and alveolar type II (ATII) epithelial cells in the lung2. These organelles contain not only lipids but also cell-type specific proteins and lytic enzymes. Due to their acidic pH and functional similarities, LBs are classified as lysosome-related organelles (LROs) or secretory lysosomes3,4. In usp-50 mutants, we observed a considerable number of abnormal vesicles, some of which contain threadlike membrane structures and exhibit morphological similarities to LBs (Figure 2O). However, further analysis with a comprehensive panel of lysosome-related markers demonstrated a significant reduction in lysosomal structures within these mutants. In contrast, vesicles marked by early endosome markers, such as FYVE, RAB-5, RABX-5, and EEA1, were notably enlarged. These results suggest that the enlarged vesicles observed in usp-50 mutants are more likely aberrant early endosomes rather than true lamellar bodies. We have revised the manuscript to reflect these findings and to clearly differentiate between these structures and lysosome-related organelles.

(2) The correlation between the presence of these abnormal structures and ESCRT-0 remains unaddressed, thus the assertion that UPS-50 regulates endolysosome trafficking in conjunction with ESCRT-0 lacks empirical support.

We thank the reviewer for the valuable suggestions. We apologize for any confusion and appreciate the opportunity to clarify our findings. The ESCRT machinery is essential for driving endosomal membrane deformation and scission, which leads to the formation of intraluminal vesicles (ILVs) within multivesicular bodies (MVBs). Recent research has shown that the absence of ESCRT components results in a reduction of ILVs in worm gut cells5. In wild type animals, the ESCRT-0 components HGRS-1 and STAM-1 display a distinct punctate distribution (Figure 1G and H). However, in usp-50 mutants, the punctate signals of HGRS-1::GFP and STAM-1::GFP are significantly reduced (Figure 1G and H; and Figure 1-figure supplement 1B), indicating a role for USP-50 in stabilizing the ESCRT-0 complex. Our TEM analysis revealed an accumulation of abnormally enlarged vesicles containing intraluminal structures in usp-50 mutants. When we examined a panel of early endosome and late endosome/lysosome markers, we found that early endosomes are significantly enlarged, while late endosomal/lysosomal structures are markedly reduced in these mutants. This suggests that the abnormal structures observed in usp-50 mutants are likely enlarged early endosomes rather than classical MVBs. To further investigate whether the reduction in ESCRT components contributes to the late endosome/lysosome defects, we analyzed stam-1 mutants. In these mutants, the size of RAB-7-coated vesicles was reduced (Author response image 1C), and the lysosomal marker LAAT-1 indicated a reduction in lysosomal structures (Author response image 1B). These results highlight the importance of the ESCRT complex in late endosome/lysosome formation. However, the morphology of early endosomes, as marked by 2xFYVE, remained similar to that of wild type in stam-1 mutants (Author response image 1A). Therefore, while reduced ESCRT-0 components may contribute to the late endosome/lysosome defects observed in usp-50 mutants, the enlargement of early endosomes in these mutants may involve additional mechanisms. We have revised the manuscript to incorporate these insights and to address the reviewer's comments more comprehensively.

Author response image 1.

(A) Confocal fluorescence images of hypodermis expressing YFP::2xFYVE to detect EEs in L4 stage animals in wild type and stam-1(ok406) mutants. Scale bar: 5 μm. (B) Confocal fluorescence images of hypodermal cell 7 (hyp7) expressing the LAAT-1::GFP marker to highlight lysosome structures in 3-day-old adult animals. Compared to wild type, LAAT-1::GFP signal is reduced in stam-1(ok406) animals. Scale bar, 5 μm. (C) The reduction of punctate endogenous GFP::RAB-7 signals in stam-1(ok406) animals. Scale bar: 10 μm.

(3) Endosomal dysfunction typically leads to significant alterations in the spatial arrangement of marker proteins across distinct endosomes. In the manuscript, the authors examined the distribution and morphology of early endosomes, multivesicular bodies (MVBs), late endosomes, and lysosomes in a usp-50 deficient background primarily through single-channel confocal imaging. By employing two color images showing RAB-5 and RAB-7, in conjunction with HGRS-1, a more comprehensive picture of the aftermath of USP-50 loss can be obtained.

Good suggestions. We have conducted a double-labeling analysis to examine the distribution of RAB-5 and RAB-7 in conjunction with HGRS-1. In wild type animals, HGRS-1 exhibits a punctate distribution that is partially co-localized with both RAB-5 and RAB-7. In contrast, in usp-50 mutants, the punctate signal of HGRS-1 is significantly reduced, along with its co-localization with RAB-5 and RAB-7 (Author response image 2). These results suggest that, in the absence of USP-50, the stabilization of ESCRT-0 components on endosomes is compromised.

Author response image 2.

ESCRT-0 is adjacent to both early endosomes and late endosomes. (A) Confocal fluorescence images of wild-type and usp-50(xd413) hypodermis at L4 stage co-expressing HGRS-1::GFP (hgrs-1 promoter) and endogenous wrmScarlet::RAB-5. (B) HGRS-1 and RAB-5 puncta were analyzed to produce Manders overlap coefficient M1 (HGRS-1/RAB-5) and M2 (RAB-5/HGRS-1) (N=10). (C) Confocal fluorescence images of wild-type and usp-50(xd413) hypodermis at L4 stage co-expressing HGRS-1::GFP (hgrs-1 promoter) and endogenous wrmScarlet::RAB-7. (D) HGRS-1 and RAB-7 puncta were analyzed to produce Manders overlap coefficient M1 (HGRS-1/RAB-7) and M2 (RAB-7/HGRS-1) (N=10). Scale bar: 10 μm for (A) and (C).

(4) The authors observed enlarged early endosomes in cells depleted of usp-50/usp8, along with enlarged MVB-like structures identified through TEM. The potential identity of these structures as the same organelle could be determined using CLEM.

We thank the reviewer for the valuable suggestion. Our TEM analysis identified a large number of abnormally enlarged vesicles with various intraluminal structures accumulated in usp-50 mutants. As the reviewer correctly noted, CLEM (correlative light and electron microscopy) would be an ideal approach to further characterize these structures. We have been attempting to implement CLEM in C. elegans for a few years. Given that CLEM relies on fluorescence markers, in this study we focused on two tagged proteins, RAB-5 and RABX-5, which show enlargement in their vesicles in usp-50 mutants. Unfortunately, we encountered significant challenges with this approach, as the GFP-tagged RAB-5 and RABX-5 signals did not survive the electron microscopy procedure. Attempts to align EM sections with residual GFP signaling yielded results that were not convincing. Consequently, we concentrated our analysis on a panel of molecular markers, including 2xFYVE, RAB-5, RABX-5, RAB-7, and LAAT-1. These markers consistently indicated that early endosomes are specifically enlarged in usp-50 mutants, while late endosomal/lysosomal structures are notably reduced. Thus, the abnormal structures identified in usp-50 mutants via TEM are likely to be enlarged early endosomes rather than the classical view of MVBs. We have revised the manuscript to reflect these findings and to clarify this point.

(5) The working model depicted in Figure 6 Y (right) requires revision, as it has the potential to mislead authors into mistaking enlarged early endosomes for multivesicular bodies (MVBs).

We thank the reviewer for the excellent suggestion. We have revised the model to clarify that it is the enlarged early endosomes, rather than MVBs, that are observed in usp-50 mutants.

Reviewer #2 (Recommendations For The Authors):

(1) Is there any change of Rabx5 protein level in USP8/USP50 mutant cells?

Good question. In the absence of usp-50/usp8, we indeed observed a noticeable increase in the signal of Rabex5 on endosomes. To determine whether usp-50/usp8 affects the protein level of Rabex5, we investigated the endogenous levels of RABX-5 using the RABX-5::GFP knock-in line. Compared to wild-type controls, we found an elevated protein level of RABX-5::GFP in the knock-in line (Author response image 3). This suggests that USP-50 may play a role in the destabilization of RABX-5/Rabex5 in vivo.

Author response image 3.

The endogenous RABX-5 protein level is increased in usp-50 mutants. (A) The RABX-5::GFP KI protein level is increased in usp-50(xd413). (B) Quantification of endogenous RABX-5::GFP protein level in wild type and usp-50(xd413) mutant animals.

(2) It is interesting that "The rabx-5(null) animals are healthy and fertile and do not display obvious morphological or behavioral defects.", which seems contrary to its role in regulating USP8 localization and endosome maturation.

It has been previously documented that rabx-5 functions redundantly with rme-6, another RAB-5 GEF in C. elegans, to regulate RAB-5 localization in oocytes6. RNA interference (RNAi) targeting rabx-5 in a rme-6 mutant background results in synthetic lethality, whereas neither rabx-5 nor rme-6 single mutants are essential for worm viability. RME-6 co-localizes with clathrin-coated pits, while Rabex-5 is localized to early endosomes. Rabex-5 forms a stable complex with Rabaptin-5 and is part of a large EEA1-positive complex on early endosomes, whereas RME-6 does not interact with Rabaptin-5 (RABN-5) or EEA-1. These findings suggest that while RME-6 and RABX-5 may function redundantly, they likely play distinct roles in regulating intracellular trafficking processes. In the absence of RABX-5, USP-50 appears to lose its endosomal localization, although the size of the early endosome remains comparable to that of wild type. This observation contrasts with the phenotype associated with USP-50 loss-of-function, in which the early endosome is notably enlarged. These results suggest that residual USP-50 present in the endosomes is sufficient to maintain its role in the endocytic pathway. Conversely, the complete absence of USP-50 likely disrupts the transition of early endosomes to late endosomes, indicating a crucial role of USP-50 in this conversion process. It is also noteworthy that, although loss-of-function of rabx-5 does not result in obvious changes to early endosomes, increasing the gene expression level of rabx-5/Rabex-5 alone is sufficient to cause enlargement of early endosomes (Author response image 4) . Indeed, we observed that loss-of-function mutations in u_sp-50/usp_8 lead to abnormally enlarged early endosomes, accompanied by an enhanced signal of endosomal RABX-5. When the rabx-5(null) mutation was introduced into usp-50 mutant animals, the enlarged early endosome phenotype seen in usp-50 mutants was significantly suppressed (Figure 4H and I). This implies that maintaining a lower level of Rab5 GEF may be crucial for endolysosomal trafficking.

(3) Does Rabx5 mutation has any impact on early endosomes?

To address the question, we utilized the CRISPR/Cas9 technique to create a molecular null for rabx-5 (Figure 4E). In the rabx-5(null) mutant animals, we found that the 2xFYVE-labeled early endosomes are indistinguishable from wild type (Figure 4H and 4I). Given that r_abx-5_ functions redundantly with rme-6, another RAB-5 GEF in C. elegans, it is likely that the regulation of early endosome size involves a cooperative interaction between RABX-5 and RME-6.

(4) The authors observed a reduction of ESCRT-0 components in USP8 mutant cells, could this contribute to the late endosome/lysosome defects?

Good suggestion. In wild-type animals, the two ESCRT-0 components, HGRS-1 and STAM-1, exhibit a distinct punctate distribution (Figure 1G and H). However, in usp-50 mutants, the punctate signals of HGRS-1::GFP and STAM-1::GFP are significantly diminished (Figure 1G and H; and Figure 1-figure supplement 1B), which aligns with the role of USP-50 in stabilizing the ESCRT-0 complex. To investigate whether the reduction in ESCRT components might contribute to defects in late endosome/lysosome formation, we examined stam-1 mutants. In stam-1 mutants, we observed a reduction in the size of RAB-7-coated vesicles (Author response image 1). Further, when we introduced the lysosomal marker LAAT-1::GFP into stam-1 mutants, we found a substantial decrease in lysosomal structures compared to wild-type animals (Author response image 1). This suggests that the ESCRT complex is essential for proper late endosome/lysosome formation. In contrast, the morphology of early endosomes, as indicated by the 2xFYVE marker, appeared normal in stam-1 mutants, similar to wild-type animals (Author response image 1). This implies that while a reduction in ESCRT-0 components may contribute to the late endosome/lysosome defects observed in usp-50 mutants, the early endosome enlargement phenotype in _usp-5_0 mutants may involve additional mechanisms.

(5) Rabx5 is accumulated in USP8 mutant cells, I am very curious about the phenotype of USP8-Rabx5 double mutants. Could over-expression of Rabx5 (wild type or mutant forms) cause any defects?

Excellent suggestions. To address the question, we employed the CRISPR/Cas9 technique to create a molecular null for rabx-5 (Figure 4E). In the rabx-5(null) mutant animals, we observed that the punctate USP-50::GFP signal became diffusely distributed (Figure 4F and G). This suggests that rabx-5 is necessary for the endosomal localization of USP-50. Interestingly, in rabx-5(null) mutant animals, the 2xFYVE-labeled early endosomes appeared similar to those in wild-type animals (Figure 4H and I). When rabx-5(null) was introduced into usp-50 mutant animals, the enlarged early endosome phenotype observed in usp-50 was significantly suppressed (Figure 4H and I). This finding indicates that usp-50 indeed functions through rabx-5 to regulate early endosome size. Additionally, we constructed strains overexpressing either wild-type or K323R mutant RABX-5. Our results showed that overexpression of wild-type RABX-5 led to early endosome enlargement (as indicated by YFP::2xFYVE labeling) (Author response image 4A, B and D). In contrast, overexpression of the K323R mutant RABX-5 did not result in noticeable early endosome enlargement (Author response image 4A, C and D). Together, these data are in consistent with our model that USP-50 may regulate RABX-5 by deubiquitinating the K323 site.

Author response image 4.

(A-C) Over-expression wild type RABX-5 causes enlarged EEs (labeled by YFP::2xFYVE) while RABX-5(K323R) mutant form does not. (D) Quantification of the volume of individual YFP::2xFYVE vesicles. Data are presented as mean ± SEM. ****P<0.0001. ns, not significant. One-way ANOVA with Tukey’s test.

(6) Rabx5 could be ubiquitinated at K88 and K323, and Rabx5-K323R showed different activity when compared with the wild-type protein in USP8 mutant cells. Could the authors provide evidence that USP8 could remove the ubiquitin modification from K323 in Rabx5 protein?

We appreciate the reviewer's insightful suggestions. To explore the potential of USP-50 in removing ubiquitin modifications from lysine 323 on the RABX-5 protein, we undertook a series of experiments. Initially, we sought to determine whether USP-50 influences the ubiquitination level of RABX-5 in vivo. However, due to the low expression levels of USP-50, we encountered challenges in obtaining adequate amounts of USP-50 protein from worm lysates. To overcome this, we expressed USP-50::4xFLAG in HEK293 cells for subsequent affinity purification. Concurrently, we utilized anti-GFP agarose beads to purify RABX-5::GFP from worms expressing the rabx-5::gfp construct. We then incubated RABX-5::GFP with USP-50::4xFLAG for varying durations and performed immunoblotting with an anti-ubiquitin antibody. As shown in Author response image 5A, our results revealed a decrease in the ubiquitination level of RABX-5 in the presence of USP-50, suggesting that USP-50 directly deubiquitinates RABX-5. Previous studies have indicated that only a minor fraction of recombinant RABX-5 undergoes ubiquitination in HeLa cells, which is believed to have functional significance7. Our findings are consistent with this observation, as only a small fraction of RABX-5 in worms is ubiquitinated. Rabex-5 is known to interact with both K63- and K48-linked poly-ubiquitin chains. To further elucidate whether USP-50 specifically targets K48 or K63-linked ubiquitination at the K323 site of RABX-5, we incubated various HA-tagged ubiquitin mutants with either wild-type or K323R mutant RABX-5 protein. Our results indicated that the K323R mutation reduces K63-linked ubiquitination of RABX-5 (Author response image 5). This experiment was repeated multiple times with consistent results. Additionally, while overexpression of wild-type RABX-5 led to an enlargement of early endosomes, as evidenced by YFP::2xFYVE labeling, overexpression of the K323R mutant did not produce a noticeable effect on endosome size (Author response image 4). Collectively, this finding indicates that RABX-5 is subject to ubiquitin modification in vivo and that USP-50 plays a significant role in regulating this modification at the K323 site.

Author response image 5.

(A) RABX-5::GFP protein was purified from worm lysates using anti-GFP antibody. FLAG-tagged USP-50 was purified from HEK293T cells using anti-FLAG antibody. Purified RABX-5::GFP was incubated with USP-50::4FLAG for indicated times (0, 15, 30, 60 mins), followed by immunoblotting using antibody against ubiquitin, FLAG or GFP. In the presence of USP-50::4xFLAG, the ubiquitination level of RABX-5::GFP is decreased. (B) Quantification of RABX-5::GFP ubiquitination level from three independent experiments. (C) HEK293T cells were transfected with HA-Ub or indicated mutants and 4xFLAG tagged RABX-5 or RABX-5 K323R mutant for 48h. The cells were subjected to pull down using the FLAG beads, followed by immunoblotting using antibody against HA or Flag.

(7) The authors described "the almost identical phenotype of usp-50/usp8 and sand-1/Mon1 mutants", found protein-protein interaction between USP8 and sand-1, and showed that sand1-GFP signal is diminished in USP8 mutant cells. These observations fit with the possibility that USP8 regulates the stability of sand-1 to promote endosomal maturation. Could this be tested and integrated into the current model?

are grateful for the insightful comments provided by the reviewer. Rab5, known to be activated by Rabex-5, plays a crucial role in the homotypic fusion of early endosomes. Rab5 effectors also include the Rab7 GEF SAND-1/Mon1–Ccz1 complex. Rab7 activation by SAND-1/Mon1-Ccz1 complex is essential for the biogenesis and positioning of late endosomes (LEs) and lysosomes, and for the fusion of endosomes and autophagosomes with lysosomes. The Mon1-Ccz1 complex is able to interact with Rabex5, causing dissociation of Rabex5 from the membrane, which probably terminates the positive feedback loop of Rab5 activation and then promotes the recruitment and activation of Rab7 on endosomes. In our study, we identified an interaction between USP-50 and the Rab5 GEF, RABX-5. In the absence of USP-50, we observed an increased endosomal localization of RABX-5 and the formation of abnormally enlarged early endosomes. This phenotype is reminiscent of that seen in sand-1 loss-of-function mutants, which also exhibit enlarged early endosomes and a concomitant reduction in late endosomes/lysosomes. Notably, USP-50 also interacts with SAND-1, suggesting a potential role in regulating its localization. We could propose several models to elucidate how USP-50 might influence SAND-1 localization, including:

(1) USP-50 may stabilize SAND-1 through direct de-ubiquitination.

(2) In the absence of USP-50, the sustained presence of RABX-5 could lead to continuous Rab5 activation, which might hinder or delay the recruitment of SAND-1.

(3) USP-50 could facilitate SAND-1 recruitment by promoting the dissociation of RABX-5.

We are actively investigating these models in our laboratory. Due to space constraints, a more detailed exploration of how USP-50 regulates SAND-1 stability will be presented in a separate publication.

References:

(1) Schmitz, G., and Müller, G. (1991). Structure and function of lamellar bodies, lipid-protein complexes involved in storage and secretion of cellular lipids. J Lipid Res 32, 1539-1570.

(2) Dietl, P., and Frick, M. (2021). Channels and Transporters of the Pulmonary Lamellar Body in Health and Disease. Cells-Basel 11. https://doi.org/10.3390/cells11010045.

(3) Raposo, G., Marks, M.S., and Cutler, D.F. (2007). Lysosome-related organelles: driving post-Golgi compartments into specialisation. Current opinion in cell biology 19, 394-401. https://doi.org/10.1016/j.ceb.2007.05.001.

(4) Weaver, T.E., Na, C.L., and Stahlman, M. (2002). Biogenesis of lamellar bodies, lysosome-related organelles involved in storage and secretion of pulmonary surfactant. Semin Cell Dev Biol 13, 263-270. https://doi.org/10.1016/s1084952102000551.

(5) Ott, D.P., Desai, S., Solinger, J.A., Kaech, A., and Spang, A. (2024). Coordination between ESCRT function and Rab conversion during endosome maturation. bioRxiv, 2024.2005.2014.594104. https://doi.org/10.1101/2024.05.14.594104.

(6) Sato, M., Sato, K., Fonarev, P., Huang, C.J., Liou, W., and Grant, B.D. (2005). Caenorhabditis elegans RME-6 is a novel regulator of RAB-5 at the clathrin-coated pit. Nature cell biology 7, 559-569. https://doi.org/10.1038/ncb1261.

(7) Mattera, R., Tsai, Y.C., Weissman, A.M., and Bonifacino, J.S. (2006). The Rab5 guanine nucleotide exchange factor Rabex-5 binds ubiquitin (Ub) and functions as a Ub ligase through an atypical Ub-interacting motif and a zinc finger domain. The Journal of biological chemistry 281, 6874-6883. https://doi.org/10.1074/jbc.M509939200.

bovenstaand figuur: consistency of social expectations = verwachten alle stakeholders hetzelfde?

eLife Assessment

This study demonstrates mRNA-specific regulation of translation by subunits of the eukaryotic initiation factor complex 3 (eIF3) using convincing methods, data, and analyses. The investigations have generated important information that will be of interest to biologists studying translation regulation. However, the physiological significance of the gene expression changes that were observed is not clear.

Reviewer #1 (Public review):

Summary:<br /> In this manuscript, Herrmannova et al explore changes in translation upon individual depletion of three subunits of the eIF3 complex (d, e and h) in mammalian cells. The authors provide a detailed analysis of regulated transcripts, followed by validation by RT-qPCR and/or Western blot of targets of interest, as well as GO and KKEG pathway analysis. The authors confirm prior observations that eIF3, despite being a general translation initiation factor, functions in mRNA-specific regulation, and that eIF3 is important for translation re-initiation. They show that global effects of eIF3e and eIF3d depletion on translation and cell growth are concordant. Their results support and extend previous reports suggesting that both factors control translation of 5'TOP mRNAs. Interestingly, they identify MAPK pathway components as a group of targets coordinately regulated by eIF3 d/e. The authors also discuss discrepancies with other reports analyzing eIF3e function.

Strengths:<br /> Altogether, a solid analysis of eIF3 d/e/h-mediated translation regulation of specific transcripts. The data will be useful for scientists working in the Translation field.

Weaknesses:<br /> The authors could have explored in more detail some of their novel observations, as well as their impact on cell behavior.

The manuscript has improved with the new corrections. I appreciate the authors' attention to the minor comments, which have been fully solved. The authors have not, however, provided additional experimental evidence that uORF-mediated translation of Raf-1 mRNA depends on an intact eIF3 complex, nor have they addressed the consequences of such regulation for cell physiology. While I understand that this is a subject of follow-up research, the authors could have at least included their explanations/ speculations regarding major comments 2-4, which in my opinion could have been useful for the reader.

Reviewer #2 (Public review):

Summary:<br /> mRNA translation regulation permits cells to rapidly adapt to diverse stimuli by fine tuning gene expression. Specifically, the 13-subunit eukaryotic initiation factor 3 (eIF3) complex is critical for translation initiation as it aids in 48S PIC assembly to allow for ribosome scanning. In addition, eIF3 has been shown to drive transcript-specific translation by binding mRNA 5' cap structures through the eIF3d subunit. Dysregulation of eIF3 has been implicated in oncogenesis, however the precise eIF3 subunit contributions are unclear. Here, Herrmannová et al. aim to investigate how eIF3 subcomplexes, generated by knock down (KD) of either eIF3e, eIF3d or eIF3h, affect the global translatome. Using Ribo-seq and RNA-seq, the authors identified a large number of genes that exhibit altered translation efficiency upon eIF3d/e KD, while translation defects upon eIF3h KD were mild. eIF3d/eKD share multiple dysregulated transcripts, perhaps due to both subcomplexes lacking eIF3d. Both eIF3d/e KD increase translation efficiency (TE) of transcripts encoding lysosomal, ER and ribosomal proteins, suggesting a role of eIF3 in ribosome biogenesis and protein quality control. Many transcripts encoding ribosomal proteins harbor a TOP motif, and eIF3d KD and eIF3e KD cells exhibit a striking induction of these TOP-modified transcripts. On the other hand, eIF3d KD and eIF3e KD leads to a reduction of MAPK/ERK pathway proteins. Despite this downregulation, eIF3d KD and eIF3e KD activates MAPK/ERK signaling as ERK1/2 and c-Jun phosphorylation was induced. Finally, in all three knockdowns, MDM2 and ATF4 protein levels are reduced. This is notable because MDM2 and ATF4 both contain short uORFs upstream of the start codon, and further supports a role of eIF3 in reinitiation. Altogether, Herrmannová et al. have gained key insights to precise eIF3-mediated translational control as it relates to key signaling pathways implicated in cancer.

Strengths:<br /> The authors have provided a comprehensive set of data to analyze RNA and ribosome footprinting upon perturbation of eIF3d, eIF3e, and eIF3h. As described above in the summary, these data present many interesting starting points to understand additional roles of the eIF3 complex and specific subunits in translational control.

Weaknesses:<br /> - The differences between eIF3e and eIF3d knockdown are difficult to reconcile, especially since eIF3e knockdown leads to reduction in eIF3d levels.<br /> - The paper would be strengthened by experiments directly testing what RNA determinants allow for transcript-specific translation regulation by the eIF3 complex. This would allow the paper to be less descriptive.<br /> - The paper would have more biological relevance if eIF3 subunits were perturbed to mimic naturally occurring situations where eIF3 is dysregulated. For example, eIF3e is aberrantly upregulated in certain cancers, and therefore an overexpression and profiling experiment would have been more relevant than a knockdown experiment.

The first review is unchanged as no additional experiments were provided to address the first review.

Reviewer #3 (Public review):

Summary:<br /> In this article, Hermannova et al catalog the changes in ribosome association with mRNAs when the multisubunit eukaryotic translation initiation factor 3 is disrupted by knocking down individual subunits. They find that RNAs relying on TOP motifs for translation, such as ribosomal protein RNAs, and RNAs encoding modification enzymes in the ER and components of the lysosome are upregulated. In contrast, proteins encoding components of MAP kinase cascades are downregulated when subunits of eIF3 are knocked down, but retain elevated levels of activity.

Strengths:<br /> The authors use ribosome profiling of well-characterized mutants lacking subunits of eIF3 and assess the changes in translation that take place. They supplement the ribosome association studies with western blotting to determine protein level changes of affected transcripts. They analyze what transcripts undergo translation changes, which is important for understanding more broadly how translation initiation factor levels affect cancer cell translatomes. Changes observed by both ribosome profiling and western blotting supports their claims that eIF3 functions in mRNA-specific control of translation.

Weaknesses:<br /> (1) The paper would be strengthened if there were a clear model tying the various effects together or linking individual subunit knockdown to cancerous phenotypes. It is noted that the authors plan to address such outcomes of eIF3 dysregulation in future work, which will be of interest.

(2) The paper could also be strengthened if some of the experiments were performed in at least one other cell type to determine whether changes observed are general or cell-type specific. The authors discuss this issue and provide a literature citation to support a more general mechanism.

. From this study, we concluded that over the course of a whole small-sided game, the forward-backward motion of the centroids is most strongly linearly related. Furthermore, goals show a specific pattern in the forward-backward motion of the centroid. Therefore, surface area and particularly centroid position may provide a sound basis for a collective variable that captures the dynamics of attacking and defending in soccer at team level. Future research should develop these ideas further

eLife Assessment

The study is considered important with solid evidence that demonstrates the impact of plasma membrane nano-domains and protein interactions in the plant defence response to viruses. It includes a molecular understanding of the role of a calcium dependent kinase (CPK3) and a remorin protein in the cell-to-cell spread of viruses and cytoskeletal dynamics demonstrating, conclusively, the role of CPK3 with multiple lines of evidence. The work opens avenues to investigate different viruses and other plasma membrane proteins to gain a fuller picture of the involvement of plasmodesmata and other nanodomains in virus spreading.

Reviewer #1 (Public review):

Summary:

How plants perceive their environment and signal during growth and development is of fundamental importance for plant biology. Over the last few decades, nano domain organisation of proteins localised within the plasma-membrane has emerged as a way of organising proteins involved in signal pathways. Here, the authors addressed how a non-surface localised signal (viral infection) was resisted by PM localised signalling proteins and the effect of nano domain organisation during this process. This is valuable work as it describes how an intracellular process affects signalling at the PM where most previous work has focused on the other way round, PM signalling effecting downstream responses in the plant. They identify CPK3 as a specific calcium dependent protein kinase which is important for inhibiting viral spread. The authors then go on to show that CPK3 diffusion in the membrane is reduced after viral infection and study the interaction between CPK3 and the remorins, which are a group of scaffold proteins important in nano domain organisation. The authors conclude that there is an interdependence between CPK3 and remorins to control their dynamics during viral infection in plants.

Strengths:

The dissection of which CPK was involved in the viral propagation was masterful and very conclusive. Identifying CPK3 through knockout time course monitoring of viral movement was very convincing. The inclusion of overexpression, constitutively active and point mutation non-functioning lines further added to that.

Weaknesses:

I would like to thank the researchers for including some additional work suggested in the previous round of peer review. However, I still have concerns over this work which are two fold.

(1) Firstly, the imaging described and shown is not sufficient to support the claims made. The PM localisation and its non-PM localised form look similar and with no PM stain or marker construct used to support this. In addition, the quality of lots of the confocal based imaging (including new figure on colocalisation) is simply not sufficient. The images are too noisy and no clear conclusions can be made. The point made previously, the system this data was collected on has an Airyscan detector capable of 120nm resolution and as such NDs can be resolved. The sptPALM data conclusions are nice and fit the narrative. The inclusion of sptPALM movies is useful for the reader and tracks numbers is highly beneficial. But they do not show a high signal to noise ratio compared to other work in the field (see work from Alex Martineire) and the mEOS prticles are only just observable over the detector noise in some videos. As such, I worry about the data quality on which the analysis is based on. In addition, in some of the videos the conversion laser seems too high as it is difficult to separate some of the single particles as they emerge which would again, hinder the analysis.

(2) Secondly, remorins are involved in a lot of nano domain controlled processes at the PM. The authors have not conclusively demonstrated that during viral infection the remorin effects seen are solely due to its interaction with CPK3. The sptPALM imaging of REM1.2 in a cpk3 knockout line goes part way to solve this and the inclusion of CPK3-CA also strengthens the authors claims. But to propose a kiss and go model bearing in mind the differences in diffusion between CPK3 and REM3 and differential changes to diffusion between the two proteins after PIAMV infection without two colour imaging of both proteins at the same time, the claims are much stronger than the evidence. Negative control experiments are required here utilising other PM localised proteins which have no role during viral infection (such as Lti6B).

Overall, I think this work has the potential to be a very strong manuscript but additional evidence supporting interaction claims would significantly strengthen the work and make it exceptional.

Reviewer #3 (Public review):

Summary:

This study examined the role that the activation and plasma membrane localisation of a calcium dependent protein kinase (CPK3) plays in plant defence against viruses.<br /> The authors clearly demonstrate that the ability to hamper the cell-to-cell spread of the virus P1AMV is not common to other CPKs which have roles in defence against different types of pathogens, but appears to be specific to CPK3 in Arabidopsis. Further, they show that lateral diffusion of CPK3 in the plasma membrane is reduced upon P1AMV infection, with CPK3 likely present in nano-domains. This stabilisation however, depends on one of its phosphorylation substrates a Remorin scaffold protein REM1-2. However, when REM1-2 lateral diffusion was tracked, it showed an increase in movement in response to P1AMV infection. These contrary responses to P1AMV infection were further demonstrated to be interdependent, which led the authors to propose a model in which activated CPK3 is stabilised in nano-domains in part by its interaction with REM1.2, which it binds and phosphorylates, allowing REM1-2 to diffuse more dynamically within the membrane.

The likely impact of this work is that it will lead to closer examination of the formation of nano-domains in the plasma membrane and dissection of their role in immunity to viruses, as well as further investigation into the specific mechanisms by which CPK3 and REM1-2 inhibit the cell-to-cell spread of viruses, including examination of their roles in cytoskeletal dynamics.

Strengths:

The paper provided compelling evidence about the roles of CPK3 and REM1-2 through a combination of logical reverse genetics experiments and advanced microscopy techniques, particularly in single particle tracking.

Weaknesses:

There is limited discussion or exploration of the role that CPK3 has in cytoskeletal organisation and whether this may play a role in the plant's defence against viral propagation. Further. although the authors show that there is no accumulation of CPK3/Rem1.2 at plasmodesmata, it would be interesting to investigate whether the demonstrated reduction of viral propagation is due to changes in PD permeability.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

How plants perceive their environment and signal during growth and development is of fundamental importance for plant biology. Over the last few decades, nano domain organisation of proteins localised within the plasma-membrane has emerged as a way of organising proteins involved in signal pathways. Here, the authors addressed how a non-surface localised signal (viral infection) was resisted by PM localised signalling proteins and the effect of nano domain organisation during this process. This is valuable work as it describes how an intracellular process affects signalling at the PM where most previous work has focused on the other way round, PM signalling effecting downstream responses in the plant. They identify CPK3 as a specific calcium dependent protein kinase which is important for inhibiting viral spread. The authors then go on to show that CPK3 diffusion in the membrane is reduced after viral infection and study the interaction between CPK3 and the remorins, which are a group of scaffold proteins important in nano domain organisation. The authors conclude that there is an interdependence between CPK3 and remorins to control their dynamics during viral infection in plants.

Strengths:

The dissection of which CPK was involved in the viral propagation was masterful and very conclusive. Identifying CPK3 through knockout time course monitoring of viral movement was very convincing. The inclusion of overexpression, constitutively active and point mutation non functioning lines further added to that.

Weaknesses:

My main concerns with the work are twofold.

(1) Firstly, the imaging described and shown is not sufficient to support the claims made. The PM localisation and its non-PM localised form look similar and with no PM stain or marker construct used to support this. The sptPALM data conclusions are nice and fit the narrative. However, no raw data or movie is shown, only representative tracks. Therefore, the data quality cannot be verified and in addition, the reporting of number of single particle events visualised per experiment is absent, only number of cells imaged is reported. Therefore, it is impossible for the reader to appreciate the number of single molecule behaviours obtained and hence the quality of the data.

(2) Secondly, remorins are involved in a lot of nanodomain controlled processes at the PM. The authors have not conclusively demonstrated that during viral infection the remorin effects seen are solely due to its interaction with CPK3. The sptPALM imaging of REM1.2 in a cpk3 knockout line goes part way to solve this but more evidence would strengthen it in my opinion. How do we not know that during viral infection the entire PM protein dynamics and organisation are altered? Or that CPK3 and REM are at very distant ends of a signalling cascade. Negative control experiments are required here utilising other PM localised proteins which have no role during viral infection. In addition, if the interaction is specific, the transiently expressed CPK3-CA construct (shown to from nano domains) should be expressed with REM1.2-mEOS to show the alterations in single particle behaviour occur due to specific activations of CPK3 and REM1.2 in the absence of PIAMV viral infection and it is not an artefact of whole PM changes in dynamics during viral infection.

In addition, displaying more information throughout the manuscript (such as raw particle tracking movies and numbers of tracks measured) on the already generated data would strengthen the manuscript further.

Overall, I think this work has the potential to be a very strong manuscript but additional reporting of methods and data are required and additional lines of evidence supporting interaction claims would significantly strengthen the work and make it exceptional.

Reviewer #2 (Public Review):

Summary:

The paper provides evidence that CPK3 plays a role in plant virus infection, and reports that viral infection is accompanied by changes in the dynamics of CPK3 and REM1.2, the phosphorylation substrate of CPK3, in the plasma membrane. In addition, the dynamics of the two proteins in the PM are shown to be interdependent.

Strengths:

The paper contains novel, important information.

Weaknesses:

The interpretation of some experimental data is not justified, and the proposed model is not fully based on the available data.

Reviewer #3 (Public Review):

Summary:

This study examined the role that the activation and plasma membrane localisation of a calcium dependent protein kinase (CPK3) plays in plant defence against viruses.<br /> The authors clearly demonstrate that the ability to hamper the cell-to-cell spread of the virus P1AMV is not common to other CPKs which have roles in defence against different types of pathogens, but appears to be specific to CPK3 in Arabidopsis. Further they show that lateral diffusion of CPK3 in the plasma membrane is reduced upon P1AMV infection, with CPK3 likely present in nano-domains. This stabilisation however, depends on one of its phosphorylation substrates a Remorin scaffold protein REM1-2. However, when REM1-2 lateral diffusion was tracked, it showed an increase in movement in response to P1AMV infection. These contrary responses to P1AMV infection were further demonstrated to be interdependent, which led the authors to propose a model in which activated CPK3 is stabilised in nano-domains in part by its interaction with REM1.2, which it binds and phosphorylates, allowing REM1-2 to diffuse more dynamically within the membrane.

The likely impact of this work is that it will lead to closer examination of the formation of nano-domains in the plasma membrane and dissection of their role in immunity to viruses, as well as further investigation into the specific mechanisms by which CPK3 and REM1-2 inhibit the cell-to-cell spread of viruses.

Strengths:

The paper provided compelling evidence about the roles of CPK3 and REM1-2 through a combination of logical reverse genetics experiments and advanced microscopy techniques, particularly in single particle tracking.

Weaknesses:

There is a lack of evidence for the downstream pathways, specifically whether the role that CPK3 has in cytoskeletal organisation may play a role in the plant's defence against viral propagation. Also, there is limited discussion about the localisation of the nano-domains and whether there is any overlap with plasmodesmata, which as plant viruses utilise PD to move from cell to cell seems an obvious avenue to investigate.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Viral spread work in CPK mutants with time courses is beautiful!

Regarding my public points on my issues with the imaging:

- Figure 2A shows 'PM' localisation of CPK3 and 'non-PM' imaging of CPK3-G2A. The images are near identical both showing cell outlines and cytoplasmic strands. Here a PM marker (such as Lti6B) tagged with a different fluorophore or PM stain should be used in conjunction with surface views (such as in Figure 2C) to show it really is at the PM and the G2A line is not.

Impaired membrane localization of CPK3-G2A is documented in Mehlmer et al., 2010 using microsomal fractionation. Although Figure 2A main purpose is to show correct expression of the constructs in the lines used for PlAMV propagation (Figure 2B), we replaced the images with wider view pictures to be more representative of the subcellular localization of CPK3 and CPK3-G2A.

- Regarding Figure 2C, this is extremely noisy and PM heterogeneity is barely observable over the noise from the system (looking at the edges of surface imaged). You mention low resolution was an issue. I notice from the methods you have taken confocal images on an Zeiss 880 with Airyscan. These images must be confocal but If imaged with Airyscan the PM heterogeneity would be much clearer (see work from John Runions lab).

Indeed, these are tangential views images obtained by Zeiss 880 with Airyscan. Based on tessellation analysis (Figure 2H-J), CPK3 is rather homogeneously distributed and forms ND of around 70nm of diameter. Objects of such size cannot be resolved using pixel reassignment methods such as Airyscan. Note also that AtREM in our study are less heterogeneously distributed than what was described in the literature for StREM1.3.

- Regarding all sptPALM data. At least an example real data image and video is required otherwise the data can’t be assessed. The work of Alex Martiniere (sptPALM) or Alex Jonson (TIRF) all show raw data so the reader can appreciate the quality of the data. In addition, number of events (particles tracked) has to be shown in the figure legend, not just number of cells otherwise was one track performed per cell? Or 10,000? Obviously where the N sits in this range gives the reader more or less confidence of the data.

We agree and we added example videos of sptPALM experiments in the supplementary data, we also indicated the number of tracked particles in the figure legends.

- On a slight technical aside, how do you know the cells being imaged for sptPALM with PIAMV are actually infected with the virus? In Fig 2C you use a GFP tagged version but in sptPALM you use none tagged. I think a sentence in methods on this would help clarify.

PlAMV-GFP was used for spt-PALM experiment and cell infection was assessed during PALM experiment. This is now precised in the corresponding figures and methods.

- I also have a concern over some of the representative images showing the same things between different figures. Your clustering data in 3F looks very convincing. However, in Figure 2H the mock and PIAMV-GFP look very similar. How is Figure 3F so different for the same experiment? Especially considering the scale bars are the same for both figures. Same for CPK3-mRFP1.2 in Fig 2C and 3A, the same thing is being imaged, at the same scale (scale bars same size) but the images are extremely different.

Figure 2 data were generated using CPK3 stably expressed in A. thaliana while Figure 3 data were obtained upon transient over-expression of CPK3 in N. benthamiana. We do not have a clear explanation for such a difference in CPK3 PM behavior, it could lie on a different PM composition or actin organization between those two species, this point is now addressed in the discussion.

- Line 193&194 - you state that the CA CPK3 is reminiscent of the CPK3 upon PIAMV expression. I don't agree, while CPK3CA is less mobile (2D), the MSD shows it is in-between CPK3 and CPK3 + PIAMV. Therefore, can’t the opposite also be true? That overall the behaviour of CPK3-CA is reminiscent of WT CPK. I think this needs rewording.

We agree and we reworded that part

- Line 651 - what numerical aperture are you using for the lens during confocal microscopy. This is fundamentally important information directly related to the reproducibility of the work. You report it for the sptPALM.

The numerical aperture is now indicated in the methods.

Regarding my bigger point about specific interactions between CPK3 and remorin during viral infection to strengthen your claim the following need doing. I am not suggesting you do all of these but at least two would significantly enhance the paper.

(1) Image a none related PM protein during viral infection using sptPALM and demonstrate that its behaviour is not altered (such as lti6b). This would show the affects on remorin behaviour are specific to CPK3 and not a whole scale PM alteration in dynamics due to viral infection.

(2) Two colour SPT imaging of CPK3 and REM1.2. You show in absence of proteins (knockouts effect on each other) but your only interaction data is from a kinase assay (where CPK1 and 2 also interact, even though they are not localised at the same place) and colocalisation data (see below). A two colour SPT imaging experiment showing interaction and clustering of CPK3 and REM1.2 with each other and the change in their behaviours when viral infected and simultaneously imaged would address all of my concerns.

- On another note, the co-localisation data (fig 5 sup 4) needs additional analysis. I would expect most PM proteins to show the results you show as the data is very noisy. In order to improve I would zoom in to fill the field of view and then determine correlation and also when one image is rotated 90 degrees (as described in Jarsch et al., plant cell) to enhance this work.

(3) In the absence of viral infection, but presence of CPK3-CA, is sptPALM REM1.2 behaviour in the PM altered, if so then the interaction is specific and changes in remorin dynamics are not due to whole scale PM changes during viral infection and the manuscript substantially strengthened.

(4) Building on from 3), if you have a CPK3 mutated with both CPK3-CA and G2A this would be constitutively active and non-PM localised and as such should not affect Remorin behaviour if your model is true, this would strengthen the case significantly but I appreciate is highly artificial and would need to be done transiently.

Regarding the first point, since the role of PM proteins involved in potexvirus infection is barely assessed, picking a non-related PM protein might be tricky. The data obtained with mEOS3.2-REM1.2 expressed in cpk3 null-mutant point towards a specific role of CPK3 in PlAMV-induced REM1.2 diffusion and not a general alteration of PM protein behavior.

Regarding the second point, we already reported the in vivo interaction between AtCPK3CA and AtREM1.2/AtREM1.3 by BiFC in N.benthamiana (Perraki et al 2018) and AtCPK3 was shown to co-IP with AtREM1.2 (Abel et al, 2021). While we agree on the relevance of doing dual color sptPALM with CPK3 and REM1.2, it is so far technically challenging and we would not be able to implement this in a timely manner. For the colocalization, although the whole cell is displayed in the figure, the analysis was performed on ROI to fill the field of analysis.

We agree with the relevance of adding the colocalization analysis of randomized images (mTagBFP2 channel rotated 90 degrees), this is now added to Figure 5 – supplement figure 5.

Finally, for the third and fourth points, spt-PALM analysis of REM1.2 in presence of CPK3-CA and CPK3-CA-G2A was performed (Figure 5 - figure supplement 4). The results suggest a specific role of CPK3-CA in REM1.2 diffusion.

Minor points:

Line 59 - from, I think you mean from.

Line 63 - Reference needed after latter.

Line 68 - Reference required after viral infection.

Line 85 - Propose not proposed.

Line 156 - Allowed us to not allows to.

Line 204 - add we previously 'demonstrated'

Line 622 and 623 - You say lines obtained from Thomas Ott. This is very odd phrasing considering he is an author. I appreciate citing the work producing the lines but maybe reword this

These points were corrected, thank you.

Reviewer #2 (Recommendations For The Authors):

The paper provides evidence that CPK3 plays a role in plant virus infection, and reports that viral infection is accompanied by changes in the dynamics of CPK3 and REM1.2, the phosphorylation substrate of CPK3, in the plasma membrane. In addition, the dynamics of the two proteins in the PM are shown to be interdependent. The paper contains novel, important information that can undoubtedly be published in eLife. However, I have some concerns that should be addressed before it can be accepted for publication.

Major concerns

When the authors say that CPK3 plays a role in viral propagation, it should be clarified what is meant by 'propagation', - replication of the viral genome, its cell-to-cell transport, or long-distance transport via the phloem. By default the readers will tend to assume the former meaning. In my opinion, the term 'propagation' is misleading and should be avoided.

We purposely chose the term “propagation” because it sums replication and cell-to-cell movement. Nevertheless, we previously showed that group 1 StREM1.3 doesn’t alter PVX replication (Raffaele et al., 2009 The Plant Cell). In this paper, as we do not investigate the role of AtREM1.2 or AtCPK3 in the replication of the viral PlAMV genome, we cannot state that these proteins are strictly involved in cell-to-cell movement of the virus.

The authors show that viral infection is associated with decreased diffusion of CPK3 and increased diffusion of REM1.2 in the PM. However, it remains unclear whether these changes are related to partial resistance to viral infection involving CPK3 and REM1.2, or whether they are simply a consequence of viral infection that may lead to altered PM properties and altered dynamics of PM-associated proteins. Therefore, the model presented in Fig. 6 appears to be entirely speculative, as it postulates that changes in CPK3 and REM1.2 dynamics are the cause of suppressed virus 'propagation'. In addition, the model implies that a decrease in CPK3 mobility leads to activation of its kinase activity. This view is not supported by experimental data (see my next comment). The model should be deleted (both as the figure and its description in the Discussion) or substantially reworked so that it finally relies on existing data.

For the first point, the results obtained from the additional experiments proposed by reviewer #1 supports the hypothesis of a direct impact of CPK3 on REM1.2 diffusion (Figure 5 - figure supplement 4).

We agree with the second point and reworked the model to remove the link between CPK3 activation and its increased diffusion.

The statement that 'changes in CPK3 dynamics upon PlAMV infection are linked to its activation' (line 194) is based on a flawed logic, and the conclusion in this section of Results ('changes in CPK3 dynamics upon PlAMV infection are linked to its activation') is incorrect, as it is not supported by experimental data. In fact, the authors show that CPK3 dynamics and clustering upon viral infection is somewhat reminiscent of the behavior of a CPK3 deletion mutant, which is a constitutively active protein kinase. However, this partial similarity cannot be taken as evidence that CPK3 dynamics upon PlAMV infection are related to its activation. Furthermore, the authors emphasize the similarity of the mutant and CPK3 in infected cells without taking into account a drastic difference in their localization (Fig. 3A, middle and right panels) showing that the reduced dynamics or the compared proteins may have different causes. I suggest the removal of the section 'CPK3 activation leads to its confinement in PM ND' from the paper, as the results included in this section are not directly related to other data presented.

The PM lateral organization of PM-bound CPKs in their native or constitutively active form as well as the role of lipid in such phenomenon was never shown before. We believe that this section contains relevant information for the community. We kept the section but reworded it to tamper the correlation made between CPK3 PM organization upon viral infection and its activation.

Line 270 - 'group 1 REMs might play a role in CPK3 domain stabilization upon viral infection'. This is an overstatement. The size of the CPK3-containing NDs may have no correlation with their stability.

We reworded the sentence.

Minor points

Line 204 - we previously that Line 234 and hereafter - "the D" sounds strange. Suggest using "the diffusion coefficient".

This was reworded.

Reviewer #3 (Recommendations For The Authors):

The authors have previously demonstrated that there was an increase in REM1.2 localisation to plasmodesmata under viral challenge. It would be useful to see if there was any co-localisation of REM1.2 and CPK3 with plasmodesmata in response to PlAMV and how this is affected in the mutants. This could be carried out relatively simply using aniline blue.

These experiments were added to the supplementary data of Figure 2 – figure supplement 2.  and Figure 4 – figure supplement 4. , no enrichment of CPK3 or REM1.2 at plasmodesmata could be observed upon PlAMV infection.

Fig 3 supplementary figure 2 would be better incorporated into the main body of Figure 3 as this underpins discussion on the involvement of lipids such as sterols in the formation of nanodomains.

We moved Figure 3 – Supplementary figure 2 to the main body of Figure 3.

Minor corrections:

Whilst the paper is generally well written there are a number of grammatical errors:

Line 1 & 2: Title doesn't quite read correctly, suggest a rewording for clarity.

L31: Insert "a"after only

L33: Replace "are playing" with "play"

L34: Begin sentence "Viruses are intracellular pathogens and as such the role..."59: replace "form" with "from"

L63: Insert "was demonstrated" after REM1.2)

L85: Replace "proposed" with "propose"

L86: replace "encouraging to explore" with "which will encourage further exploration of "

L129: replace "we'll focus on" with "we concentrated on"

L131: insert "an" before ATP

L138: change "among" to "amongst"

L156: change "allows to analyse" to "allows the analysis of"

L204: Insert "showed" after previously.

L232: "root seedlings" should this be the roots of seedlings?

L235: insert "to" after "as"

L280: insert "a" after "only"

L281: change " to play" with "as playing": change CA to superscript

L307: Insert "was" after "transcription"

L320: change "display" to "displaying"

L321: change "form" to forms"

L340: "hampering" should come before viral

L365: insert"us' after "allow"

Thank you, these were corrected

this is the basic building block of the model

problematic methods

apparent dissolution between the subject and the object

Ideal Gas is a model! It is incorrect based on the fact that gases never have 100% the assumptions it states but it proves to be very useful!

eLife Assessment

This valuable work describes results from a set of simulation and empirical studies of a set-up assessing exploratory behavior in a potentially rewarding environment that contains danger. The core idea is that an instrumental agent can be helped to be both effective and safe, thus avoiding excessive danger, during exploratory behavior, if its influence is flexibly gated by an independent Pavlovian fear learning system. The conclusion that safe, but effective exploration can be achieved based on a flexibly weighted combination of a Pavlovian and an instrumental agent is solid.

Reviewer #1 (Public review):

Summary:

This paper provides a computational model of a synthetic task in which an agent needs to find a trajectory to a rewarding goal in a 2D-grid world, in which certain grid blocks incur a punishment. In a completely unrelated setup without explicit rewards, they then provide a model that explains data from an approach-avoidance experiment in which an agent needs to decide whether to approach or withdraw from, a jellyfish, in order to avoid a pain stimulus, with no explicit rewards. Both models include components that are labelled as Pavlovian; hence the authors argue that their data show that the brain uses a Pavlovian fear system in complex navigational and approach-avoid decisions.

In the first setup, they simulate a model in which a component they label as Pavlovian learns about punishment in each grid block, whereas a Q-learner learns about the optimal path to the goal, using a scalar loss function for rewards and punishments. Pavlovian and Q-learning components are then weighed at each step to produce an action. Unsurprisingly, the authors find that including the Pavlovian component in the model reduces the cumulative punishment incurred, and this increases as the weight of the Pavlovian system increases. The paper does not explore to what extent increasing the punishment loss (while keeping reward loss constant) would lead to the same outcomes with a simpler model architecture, so any claim that the Pavlovian component is required for such a result is not justified by the modelling.

In the second setup, an agent learns about punishments alone. "Pavlovian biases" have previously been demonstrated in this task (i.e. an overavoidance when the correct decision is to approach). The authors explore several models (all of which are dissimilar to the ones used in the first setup) to account for the Pavlovian biases.

Strengths:

Overall, the modelling exercises are interesting and relevant and incrementally expand the space of existing models.

Weaknesses:

I find the conclusions misleading, as they are not supported by the data.

First, the similarity between the models used in the two setups appears to be more semantic than computational or biological. So it is unclear to me how the results can be integrated.

Secondly, the authors do not show "a computational advantage to maintaining a specific fear memory during exploratory decision-making" (as they claim in the abstract). Making such a claim would require showing an advantage in the first place. For the first setup, the simulation results will likely be replicated by a simple Q-learning model when scaling up the loss incurred for punishments, in which case the more complex model architecture would not confer an advantage. The second setup, in contrast, is so excessively artificial that even if a particular model conferred an advantage here, this is highly unlikely to translate into any real-world advantage for a biological agent. The experimental setup was developed to demonstrate the existence of Pavlovian biases, but it is not designed to conclusively investigate how they come about. In a nutshell, who in their right mind would touch a stinging jellyfish 88 times in a short period of time, as the subjects do on average in this task? Furthermore, in which real-life environment does withdrawal from a jellyfish lead to a sting, as in this task?

Crucially, simplistic models such as the present ones can easily solve specifically designed lab tasks with low dimensionality but they will fail in higher-dimensional settings. Biological behaviour in the face of threat is utterly complex and goes far beyond simplistic fight-flight-freeze distinctions (Evans et al., 2019). It would take a leap of faith to assume that human decision-making can be broken down into oversimplified sub-tasks of this sort (and if that were the case, this would require a meta-controller arbitrating the systems for all the sub-tasks, and this meta-controller would then struggle with the dimensionality j).

On the face of it, the VR task provides higher "ecological validity" than previous screen-based tasks. However, in fact, it is only the visual stimulation that differs from a standard screen-based task, whereas the action space is exactly the same. As such, the benefit of VR does not become apparent, and its full potential is foregone.

If the authors are convinced that their model can - then data from naturalistic approach-avoidance VR tasks is publicly available, e.g. (Sporrer et al., 2023), so this should be rather easy to prove or disprove. In summary, I am doubtful that the models have any relevance for real-life human decision-making.

Finally, the authors seem to make much broader claims that their models can solve safety-efficiency dilemmas. However, a combination of a Pavlovian bias and an instrumental learner (study 1) via a fixed linear weighting does not seem to be "safe" in any strict sense. This will lead to the agent making decisions leading to death when the promised reward is large enough (outside perhaps a very specific region of the parameter space). Would it not be more helpful to prune the decision tree according to a fixed threshold (Huys et al., 2012)? So, in a way, the model is useful for avoiding cumulatively excessive pain but not instantaneous destruction. As such, it is not clear what real-life situation is modelled here.

A final caveat regarding Study 1 is the use of a PH associability term as a surrogate for uncertainty. The authors argue that this term provides a good fit to fear-conditioned SCR but that is only true in comparison to simpler RW-type models. Literature using a broader model space suggests that a formal account of uncertainty could fit this conditioned response even better (Tzovara et al., 2018).

Reviewer #2 (Public review):

Summary:

The authors tested the efficiency of a model combining Pavlovian fear valuation and instrumental valuation. This model is amenable to many behavioral decision and learning setups - some of which have been or will be designed to test differences in patients with mental disorders (e.g., anxiety disorder, OCD, etc.).

Strengths:

(1) Simplicity of the model which can at the same time model rather complex environments.

(2) Introduction of a flexible omega parameter.

(3) Direct application to a rather advanced VR task.

(4) The paper is extremely well written. It was a joy to read.

Weaknesses:

Almost none! In very few cases, the explanations could be a bit better.

Reviewer #3 (Public review):

Summary:

This paper aims to address the problem of exploring potentially rewarding environments that contain the danger, based on the assumption that an independent Pavlovian fear learning system can help guide an agent during exploratory behaviour such that it avoids severe danger. This is important given that otherwise later gains seem to outweigh early threats, and agents may end up putting themselves in danger when it is advisable not to do so.

The authors develop a computational model of exploratory behaviour that accounts for both instrumental and Pavlovian influences, combining the two according to uncertainty in the rewards. The result is that Pavlovian avoidance has a greater influence when the agent is uncertain about rewards.

Strengths:

The study does a thorough job of testing this model using both simulations and data from human participants performing an avoidance task. Simulations demonstrate that the model can produce "safe" behaviour, where the agent may not necessarily achieve the highest possible reward but ensures that losses are limited. Interestingly, the model appears to describe human avoidance behaviour in a task that tests for Pavlovian avoidance influences better than a model that doesn't adapt the balance between Pavlovian and instrumental based on uncertainty. The methods are robust, and generally, there is little to criticise about the study.

Weaknesses:

The extent of the testing in human participants is fairly limited but goes far enough to demonstrate that the model can account for human behaviour in an exemplar task. There are, however, some elements of the model that are unrealistic (for example, the fact that pre-training is required to select actions with a Pavlovian bias would require the agent to explore the environment initially and encounter a vast amount of danger in order to learn how to avoid the danger later). The description of the models is also a little difficult to parse.

Author response:

Public Reviews: 

Reviewer #1 (Public review): 

Summary: 

This paper provides a computational model of a synthetic task in which an agent needs to find a trajectory to a rewarding goal in a 2D-grid world, in which certain grid blocks incur a punishment. In a completely unrelated setup without explicit rewards, they then provide a model that explains data from an approach-avoidance experiment in which an agent needs to decide whether to approach or withdraw from, a jellyfish, in order to avoid a pain stimulus, with no explicit rewards. Both models include components that are labelled as Pavlovian; hence the authors argue that their data show that the brain uses a Pavlovian fear system in complex navigational and approach-avoid decisions. 

We thank the reviewer for their thoughtful comments. To clarify, the grid-world setup was used as a didactic tool/testbed to understand the interaction between Pavlovian and instrumental systems (lines 80-81) [Dayan et al., 2006], specifically in the context of safe exploration and learning. It helps us delineate the Pavlovian contributions during learning, which is key to understanding the safety-efficiency dilemma we highlight. This approach generates a hypothesis about outcome uncertainty-based arbitration between these systems, which we then test in the approach-withdrawal VR experiment based on foundational studies studying Pavlovian biases [Guitart-Masip et al., 2012, Cavanagh et al., 2013].

Although the VR task does not explicitly involve rewards, it provides a specific test of our hypothesis regarding flexible Pavlovian fear bias, similar to how others have tested flexible Pavlovian reward bias without involving punishments (e.g., Dorfman & Gershman, 2019). Both the simulation and VR experiment models are derived from the same theoretical framework and maintain algebraic mapping, differing only in task-specific adaptations (e.g., differing in action sets and temporal difference learning for multi-step decisions in the grid world vs. Rescorla-Wagner rule for single-step decisions in the VR task). This is also true for Dayan et al. [2006] who bridge Pavlovian bias in a Go-No Go task (negative auto-maintenance pecking task) and a grid world task. Therefore, we respectfully disagree that the two setups are completely unrelated and that both models include components merely labelled as Pavlovian.

We will rephrase parts of the manuscript to prevent the main message of our manuscript from being misconveyed. Particularly in the Methods and Discussion, to clarify that our main focus is on Pavlovian fear bias in safe exploration and learning (as also summarised by reviewers #2 and #3), rather than on its role in complex navigational decisions. We also acknowledge the need for future work to capture more sophisticated safe behaviours, such as escapes and sophisticated planning which span different aspects of the threat-imminence continuum [Mobbs et al., 2020], and we will highlight these as avenues for future research.

In the first setup, they simulate a model in which a component they label as Pavlovian learns about punishment in each grid block, whereas a Q-learner learns about the optimal path to the goal, using a scalar loss function for rewards and punishments. Pavlovian and Q-learning components are then weighed at each step to produce an action. Unsurprisingly, the authors find that including the Pavlovian component in the model reduces the cumulative punishment incurred, and this increases as the weight of the Pavlovian system increases. The paper does not explore to what extent increasing the punishment loss (while keeping reward loss constant) would lead to the same outcomes with a simpler model architecture, so any claim that the Pavlovian component is required for such a result is not justified by the modelling. 

Thank you for this comment. We acknowledge that our paper does not compare the Pavlovian fear system to a purely instrumental system with varying punishment sensitivity. Instead, our model assumes the coexistence of these two systems and demonstrates the emergent safety-efficiency trade-off from their interaction. It is possible that similar behaviours could be modelled using an instrumental system alone. In light of the reviewer’s comment, we will soften our claims regarding the necessity of the Pavlovian system, despite its known existence.

We also encourage the reviewer to consider the Pavlovian system as a biologically plausible implementation of punishment sensitivity. Unlike punishment sensitivity (scaling of the punishments), which has not been robustly mapped to neural substrates in fMRI studies, the neural substrates for the Pavlovian fear system (e.g., the limbic loop) are well known (see Supplementary Fig. 16).

Additionally, we point out that varying reward sensitivities while keeping punishment sensitivity constant allows our PAL agent to differentiate from an instrumental agent that combines reward and punishment into a single feedback signal. As highlighted in lines 136-140 and the T-maze experiment (Fig. 3 A, B, C), the Pavlovian system maintains fear responses even under high reward conditions, guiding withdrawal behaviour when necessary (e.g., ω = 0.9 or 1), which is not possible with a purely instrumental model if the punishment sensitivities are fixed. This is a fundamental point.

We will revise our discussion and results sections to reflect these clarifications.

In the second setup, an agent learns about punishments alone. "Pavlovian biases" have previously been demonstrated in this task (i.e. an overavoidance when the correct decision is to approach). The authors explore several models (all of which are dissimilar to the ones used in the first setup) to account for the Pavlovian biases. 

Thank you, we respectfully disagree with the statement that our models used in the experimental setup are dissimilar to the ones used in the first setup. Due to differences in the nature of the task setup, the action set differs, but the model equations and the theory are the same and align closely, as described in our response above. The only additional difference is the use of a baseline bias in human experiments and the RLDDM model, where we also model reaction times with drift rates which is not a behaviour often simulated in grid world simulations. We will improve our Methods section to ensure that model similarity is highlighted.

Strengths: 

Overall, the modelling exercises are interesting and relevant and incrementally expand the space of existing models. 

We thank reviewer #1 for acknowledging the relevance of our models in advancing the field. We would like to further highlight that, to the best of our knowledge, this is the first time reaction times in Pavlovian-Instrumental arbitration tasks have been modelled using RLDDM, which adds a novel dimension to our approach.

Weaknesses: 

I find the conclusions misleading, as they are not supported by the data. 

First, the similarity between the models used in the two setups appears to be more semantic than computational or biological. So it is unclear to me how the results can be integrated. 

We acknowledge the dissimilarity between the task setups (grid-world vs. approach-withdrawal). However, we believe these setups are computationally similar and may be biologically related, as suggested by prior work like Dayan et al. [2006], which integrates Go-No Go and grid-world tasks. Just as that work bridged findings in the appetitive domain, we aim to integrate our findings in the aversive domain. We will provide a more integrated interpretation in the discussion section of the revised manuscript.

Dayan, P., Niv, Y., Seymour, B., and Daw, N. D. (2006). The misbehavior of value and the discipline of the will. Neural networks, 19(8):1153–1160.

Secondly, the authors do not show "a computational advantage to maintaining a specific fear memory during exploratory decision-making" (as they claim in the abstract). Making such a claim would require showing an advantage in the first place. For the first setup, the simulation results will likely be replicated by a simple Q-learning model when scaling up the loss incurred for punishments, in which case the more complex model architecture would not confer an advantage. The second setup, in contrast, is so excessively artificial that even if a particular model conferred an advantage here, this is highly unlikely to translate into any real-world advantage for a biological agent. The experimental setup was developed to demonstrate the existence of Pavlovian biases, but it is not designed to conclusively investigate how they come about. In a nutshell, who in their right mind would touch a stinging jellyfish 88 times in a short period of time, as the subjects do on average in this task? Furthermore, in which real-life environment does withdrawal from a jellyfish lead to a sting, as in this task? 

Thank you for your feedback. As mentioned above, we invite the reviewer to potentially think of Pavlovian fear systems as a way how the brain might implement punishment sensitivity. Secondly, it provides a separate punishment memory that cannot be overwritten with higher rewards (see also Elfwing and Seymour 2017, and Wang et al, 2021)

Elfwing, S., & Seymour, B. (2017, September). Parallel reward and punishment control in humans and robots: Safe reinforcement learning using the MaxPain algorithm. In 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 140-147). IEEE. 

Wang, J., Elfwing, S., & Uchibe, E. (2021). Modular deep reinforcement learning from reward and punishment for robot navigation. Neural Networks, 135, 115-126.

The simulation setups such as the following grid-worlds are common test-beds for algorithms in reinforcement learning [Sutton and Barto, 2018].

Any experimental setup faces the problem of having a constrained experiment designed to test and model a specific effect versus designing a lesser constrained exploratory experiment which is more difficult to model. Here we chose the former, building upon previous foundational experiments on Pavlovian bias in humans [Guitart-Masip et al., 2012, Cavanagh et al., 2013].  The condition where withdrawal from a jellyfish leads to a sting, though less realistic, was included for balancing the four cue-outcome conditions. Overall the task was designed to isolate the effect we wanted to test - Pavlovian fear bias in choices and reaction times, to the best of our ability. In a free operant task, it is very well likely that other components not included in our model could compete for control.

Crucially, simplistic models such as the present ones can easily solve specifically designed lab tasks with low dimensionality but they will fail in higher-dimensional settings. Biological behaviour in the face of threat is utterly complex and goes far beyond simplistic fight-flight-freeze distinctions (Evans et al., 2019). It would take a leap of faith to assume that human decision-making can be broken down into oversimplified sub-tasks of this sort (and if that were the case, this would require a meta-controller arbitrating the systems for all the sub-tasks, and this meta-controller would then struggle with the dimensionality j). 

We agree that safe behaviours, such as escapes, involve more sophisticated computations. We do not propose Pavlovian fear bias as the sole computation for safe behavior, but rather as one of many possible contributors. Knowing about the existence about the Pavlovian withdrawal bias, we simply study its possible contribution. We will include in our discussion that such behaviours likely occupy different parts of the threat-imminence continuum [Mobbs et al., 2020].

Dean Mobbs, Drew B Headley, Weilun Ding, and Peter Dayan. Space, time, and fear: survival computations along defensive circuits. Trends in cognitive sciences, 24(3):228–241, 2020.

On the face of it, the VR task provides higher "ecological validity" than previous screen-based tasks. However, in fact, it is only the visual stimulation that differs from a standard screen-based task, whereas the action space is exactly the same. As such, the benefit of VR does not become apparent, and its full potential is foregone. 

We thank the reviewer for their comment. We selected the action space to build on existing models [Guitart-Masip et al., 2012, Cavanagh et al., 2013] that capture Pavlovian biases and we also wanted to minimize participant movement for EEG data collection. Unfortunately, despite restricting movement to just the arm, the EEG data was still too noisy to lead to any substantial results. We will explore more free-operant paradigms in future works.

On the issue of the difference between VR and lab-based tasks, we note the reviewer's point. Note however that desktop monitor-based tasks lack the sensorimotor congruency between the action and the outcome. Second, it is also arguable, that the background context is important in fear conditioning, as it may help set the tone of the fear system to make aversive components easier to distinguish.

If the authors are convinced that their model can - then data from naturalistic approach-avoidance VR tasks is publicly available, e.g. (Sporrer et al., 2023), so this should be rather easy to prove or disprove. In summary, I am doubtful that the models have any relevance for real-life human decision-making. 

We thank the reviewers for their thoughtful inputs. We do not claim our model is the best fit for all naturalistic VR tasks, as they require multiple systems across the threat-imminence continuum [Mobbs et al., 2020] and are currently beyond the scope of the current work. However, we believe our findings on outcome-uncertainty-based arbitration of Pavlovian bias could inform future studies and may be relevant for testing differences in patients with mental disorders, as noted by reviewer #2. At a general level, it can be said that most well-controlled laboratory-based tasks need to bridge a sizeable gap to applicabilty in real-life naturalistic behaviour; although the principle of using carefully designed tasks to isolate individual factors is well established

Finally, the authors seem to make much broader claims that their models can solve safety-efficiency dilemmas. However, a combination of a Pavlovian bias and an instrumental learner (study 1) via a fixed linear weighting does not seem to be "safe" in any strict sense. This will lead to the agent making decisions leading to death when the promised reward is large enough (outside perhaps a very specific region of the parameter space). Would it not be more helpful to prune the decision tree according to a fixed threshold (Huys et al., 2012)? So, in a way, the model is useful for avoiding cumulatively excessive pain but not instantaneous destruction. As such, it is not clear what real-life situation is modelled here. 

We thank the reviewer for their comments and ideas. In our discussion lines 257-264, we discuss other works which identify similar safety-efficiency dilemmas, in different models. Here, we simply focus on the safety-efficiency trade-off arising from the interactions between Pavlovian and instrumental systems. It is important to note that the computational argument for the modular system with separate rewards and punishments explicitly protects (up to a point, of course) against large rewards leading to death because the Pavlovian fear response is not over-written by successful avoidance in recent experience. Note also that in animals, reward utility curves are typically convex. We will clarify this in the discussion section.

We completely agree that in certain scenarios, pruning decision trees could be more effective, especially with a model-based instrumental agent. Here we utilise a model-free instrumental agent, which leads to a simpler model - which is appreciated by some readers such as reviewer #2. Future work can incorporate model-based methods.

A final caveat regarding Study 1 is the use of a PH associability term as a surrogate for uncertainty. The authors argue that this term provides a good fit to fear-conditioned SCR but that is only true in comparison to simpler RW-type models. Literature using a broader model space suggests that a formal account of uncertainty could fit this conditioned response even better (Tzovara et al., 2018). 

We thank the reviewer for bringing this to our notice. We will discuss Tzovara et al., 2018 in our discussion in our revised manuscript.

Reviewer #2 (Public review): 

Summary: 

The authors tested the efficiency of a model combining Pavlovian fear valuation and instrumental valuation. This model is amenable to many behavioral decision and learning setups - some of which have been or will be designed to test differences in patients with mental disorders (e.g., anxiety disorder, OCD, etc.). 

Strengths: 

(1) Simplicity of the model which can at the same time model rather complex environments. 

(2) Introduction of a flexible omega parameter. 

(3) Direct application to a rather advanced VR task. 

(4) The paper is extremely well written. It was a joy to read. 

Weaknesses: 

Almost none! In very few cases, the explanations could be a bit better. 

We thank reviewer #2 for their positive feedback and thoughtful recommendations. We will ensure that, in our revision, we clarify the explanations in the few instances where they may not be sufficiently detailed, as noted.

Reviewer #3 (Public review): 

Summary: 

This paper aims to address the problem of exploring potentially rewarding environments that contain the danger, based on the assumption that an independent Pavlovian fear learning system can help guide an agent during exploratory behaviour such that it avoids severe danger. This is important given that otherwise later gains seem to outweigh early threats, and agents may end up putting themselves in danger when it is advisable not to do so. 

The authors develop a computational model of exploratory behaviour that accounts for both instrumental and Pavlovian influences, combining the two according to uncertainty in the rewards. The result is that Pavlovian avoidance has a greater influence when the agent is uncertain about rewards. 

Strengths: 

The study does a thorough job of testing this model using both simulations and data from human participants performing an avoidance task. Simulations demonstrate that the model can produce "safe" behaviour, where the agent may not necessarily achieve the highest possible reward but ensures that losses are limited. Interestingly, the model appears to describe human avoidance behaviour in a task that tests for Pavlovian avoidance influences better than a model that doesn't adapt the balance between Pavlovian and instrumental based on uncertainty. The methods are robust, and generally, there is little to criticise about the study. 

Weaknesses: 

The extent of the testing in human participants is fairly limited but goes far enough to demonstrate that the model can account for human behaviour in an exemplar task. There are, however, some elements of the model that are unrealistic (for example, the fact that pre-training is required to select actions with a Pavlovian bias would require the agent to explore the environment initially and encounter a vast amount of danger in order to learn how to avoid the danger later). The description of the models is also a little difficult to parse. 

We thank reviewer #3 for their thoughtful feedback and useful recommendations, which we will take into account while revising the manuscript.

We acknowledge the complexity of specifying Pavlovian bias in the grid world and appreciate the opportunity to elaborate on how this bias is modelled. In the human experiment, the withdrawal action is straightforwardly biased, as noted, while in the grid world, we assume a hardwired encoding of withdrawal actions for each state/grid. This innate encoding of withdrawal actions could be represented in the dPAG [Kim et. al., 2013]. We implement this bias using pre-training, which we assume would be a product of evolution. Alternatively, this could be interpreted as deriving from an appropriate value initialization where the gradient over initialized values determines the action bias. Such aversive value initialization, driving avoidance of novel and threatening stimuli, has been observed in the tail of the striatum in mice, which is hypothesized to function as a Pavlovian fear/threat learning system [Menegas et. al., 2018].

Additionally, we explored the possibility of learning the action bias on the fly by tracking additional punishment Q-values instead of pre-training, which produced similar cumulative pain and step plots. While this approach is redundant, and likely not how the brain operates, it demonstrates an alternative algorithm.

We thank the reviewer for pointing out these potentially unrealistic elements, and we will revise the manuscript to clarify and incorporate these explanations and improve the model descriptions.

Eun Joo Kim, Omer Horovitz, Blake A Pellman, Lancy Mimi Tan, Qiuling Li, Gal Richter-Levin, and Jeansok J Kim. Dorsal periaqueductal gray-amygdala pathway conveys both innate and learned fear responses in rats. Proceedings of the National Academy of Sciences, 110(36):14795–14800, 2013

William Menegas, Korleki Akiti, Ryunosuke Amo, Naoshige Uchida, and Mitsuko Watabe-Uchida. Dopamine neurons projecting to the posterior striatum reinforce avoidance of threatening stimuli. Nature neuroscience, 21(10): 1421–1430, 2018

eLife Assessment

The authors identify a novel relationship between exosome secretion and filopodia formation that has implications for cancer cell metastasis and neuronal synapse formation. Further, they identify the exosomal cargo, THSD7A, as a regulator of this process. The data presented is convincing, and represents an important advancement in our understanding of how these two biological processes are linked and play roles in regulating cell migration and cell-cell communication.

Reviewer #1 (Public review):

Summary:

The study significantly advances our understanding of how exosomes regulate filopodia formation. Filopodia play crucial roles in cell movement, polarization, directional sensing, and neuronal synapse formation. McAtee et al. demonstrated that exosomes, particularly those enriched with the protein THSD7A, play a pivotal role in promoting filopodia formation through Cdc42 in cancer cells and neurons. This discovery unveils a new extracellular mechanism through which cells can control their cytoskeletal dynamics and interaction with their surroundings. The study employs a combination of rescue experiments, live-cell imaging, cell culture, and proteomic analyses to thoroughly investigate the role of exosomes and THSD7A in filopodia formation in cancer cells and neurons. These findings offer valuable insights into fundamental biological processes of cell movement and communication and have potential implications for understanding cancer metastasis and neuronal development.

Weaknesses:

The conclusions of this study are in most cases supported by data, but some aspects of data analysis need to be better clarified and elaborated. Some conclusions need to be better stated and according to the data observed.

Reviewer #2 (Public review):

Summary:

The authors show that small EVs trigger the formation of filopodia in both cancer cells and neurons. They go on to show that two cargo proteins, endoglin, and THSD7A, are important for this process. This possibly occurs by activating the Rho-family GTPase CDC42.

Strengths:

The EV work is quite strong and convincing. The proteomics work is well executed and carefully analyzed. I was particularly impressed with the chick metastasis assay that added strong evidence of in vivo relevance.

Weaknesses:

The weakest part of the paper is the Cdc42 work at the end of the paper. It is incomplete and not terribly convincing. This part of the paper needs to be improved significantly

Reviewer #3 (Public review):

Summary:

The authors identify a novel relationship between exosome secretion and filopodia formation in cancer cells and neurons. They observe that multivesicular endosomes (MVE)-plasma membrane (PM) fusion is associated with filopodia formation in HT1080 cells and that MVEs are present in filopodia in primary neurons. Using overexpression and knockdown (KD) of Rab27/HRS in HT1080 cells, melanoma cells, and/or primary rat neurons, they found that decreasing exosome secretion reduces filopodia formation, while Rab27 overexpression leads to the opposite result. Furthermore, the decreased filopodia formation is rescued in the Rab27a/HRS KD melanoma cells by the addition of small extracellular vesicles (EVs) but not large EVs purified from control cells. The authors identify endoglin as a protein unique to small EVs secreted by cancer cells when compared to large EVs. KD of endoglin reduces filopodia formation and this is rescued by the addition of small EVs from control cells and not by small EVs from endoglin KD cells. Based on the role of filopodia in cancer metastasis, the authors then investigate the role of endoglin in cancer cell metastasis using a chick embryo model. They find that injection of endoglin KD HT1080 cells into chick embryos gives rise to less metastasis compared to control cells - a phenotype that is rescued by the co-injection of small EVs from control cells. Using quantitative mass spectrometry analysis, they find that thrombospondin type 1 domain containing 7a protein (THSD7A) is downregulated in small EVs from endoglin KD melanoma cells compared to those from control cells. They also report that THSD7A is more abundant in endoglin KD cell lysate compared to control HT1080 cells and less abundant in small EVs from endoglin KD cells compared to control cells, indicating a trafficking defect. Indeed, using immunofluorescence microscopy, the authors observe THSD7A-mScarlet accumulation in CD63-positive structures in endoglin KD HT1080 cells, compared to control cells. Finally, the authors determine that exosome-secreted THSD7A induces filopodia formation in a Cdc42-dependent mechanism.

Strengths:

(1) While exosomes are known to play a role in cell migration and autocrine signaling, the relationship between exosome secretion and the formation of filopodia is novel.

(2) The authors identify an exosomal cargo protein, THSD7A, which is essential for regulating this function.

(3) The data presented provide strong evidence of a role for endoglin in the trafficking of THSD7A in exosomes.

(4) The authors associate this process with functional significance in cancer cell metastasis and neurological synapse formation, both of which involve the formation of filopodia.

(5) The data are presented clearly, and their interpretation appropriately explains the context and significance of the findings.

Weaknesses:

(1) A better characterization of the nature of the small EV population is missing:

It is unclear why the authors chose to proceed to quantitative mass spectrometry with the bands in the Coomassie from size-separated EV samples, as there are other bands present in the small EV lane but not the large EV lane. This is important to clarify because it underlies how they were able to identify THSD7A as a unique regulator of exosome-mediated filopodia formation. Is there a reason why the total sample fractions were not compared? This would provide valuable information on the nature of the small and large EV populations.

(2) Data analysis and quantification should be performed with increased rigor:

a) Figure 1C - The optical and temporal resolution are insufficient to conclusively characterize the association between exosome secretion and filopodia. Specifically, the 10-second interval used in the image acquisitions is too close to the reported 20-second median time between exosome secretion and filopodia formation. Two-5 sec intervals should be used to validate this. It would also be important to correlate the percentage of filopodia events that co-occur with exosome secretion. Is this a phenomenon that occurs with most or only a small number of filopodia? Additionally, resolution with typical confocal microscopy is subpar for these analyses. TIRF microscopy would offer increased resolution to parse out secretion events. As the TIRF objective is listed in the Methods section, figure legends should mention which images were acquired using TIRF microscopy.

b) Figure 2 - It would be important to perform further analysis to concretely determine the relationship between exosome secretion and filopodia stability. Are secretion events correlated with the stability of filopodia? Is there a positive feedback loop that causes further filopodia stability and length with increased secretion? Furthermore, is there an association between the proximity of secretion with stability? Quantification of filopodia more objectively (# of filopodia/cell) would be helpful.

c) Figure 6 - Why use different gel conditions to detect THSD7A in small EVs from B16F1 cells vs HT1080 and neurons? Why are there two bands for THSD7A in panels C and E? It is difficult to appreciate the KD efficiency in E. The absence of a signal for THSD7A in the HT1080 shEng small EVs that show a signal for endoglin is surprising. The authors should provide rigorous quantification of the westerns from several independent experimental repeats.

(3) The study lacks data on the cellular distribution of endoglin and THSD7A:

a) Figure 6 - Is THSD7A expected to be present in the nucleus as shown in panel D (label D is missing in the Figure). It is not clear if this is observed in neurons. a Western of endogenous THSD7A on cell fractions would clarify this. The authors should further characterize the cellular distribution of THSD7A in both cell types. Similarly, the cellular distribution of endoglin in the cancer cells should be provided. This would help validate the proposed model in Figure 8.

b) Figure 7 - Although the western blot provides convincing evidence for the role of endoglin in THSD7A trafficking, the microscopy data lack resolution as well as key analyses. While differences between shSCR and shEng cells are clear visually, the insets appear to be zoomed digitally which decreases resolution and interferes with interpretation. It would be crucial to show the colocalization of endoglin and THSD7A within CD63-postive MVE structures. What are the structures in Figure 7E shSCR zoom1? It would be important to rule out that these are migrasomes using TSPAN4 staining. More information on how the analysis was conducted is needed (i.e. how extracellular areas were chosen and whether the images are representative of the larger population). A widefield image of shSCR and shEng cells and DAPI or HOECHST staining in the higher magnification images should be provided. Additionally, the authors should quantify the colocalization of external CD63 and mScarlet signals from many independently acquired images (as they did for the internal signals in panel F). Is there no external THSD7A signal in the shEng cells?

Author response:

Public Reviews: 

Reviewer #1 (Public review): 

Summary: 

The study significantly advances our understanding of how exosomes regulate filopodia formation. Filopodia play crucial roles in cell movement, polarization, directional sensing, and neuronal synapse formation. McAtee et al. demonstrated that exosomes, particularly those enriched with the protein THSD7A, play a pivotal role in promoting filopodia formation through Cdc42 in cancer cells and neurons. This discovery unveils a new extracellular mechanism through which cells can control their cytoskeletal dynamics and interaction with their surroundings. The study employs a combination of rescue experiments, live-cell imaging, cell culture, and proteomic analyses to thoroughly investigate the role of exosomes and THSD7A in filopodia formation in cancer cells and neurons. These findings offer valuable insights into fundamental biological processes of cell movement and communication and have potential implications for understanding cancer metastasis and neuronal development. 

Weaknesses: 

The conclusions of this study are in most cases supported by data, but some aspects of data analysis need to be better clarified and elaborated. Some conclusions need to be better stated and according to the data observed. 

We appreciate the reviewer's recognition of the impact of our study.  We will address the concerns about data analysis and statement of our conclusions in our full response to reviewers.

Reviewer #2 (Public review): 

Summary: 

The authors show that small EVs trigger the formation of filopodia in both cancer cells and neurons. They go on to show that two cargo proteins, endoglin, and THSD7A, are important for this process. This possibly occurs by activating the Rho-family GTPase CDC42. 

Strengths: 

The EV work is quite strong and convincing. The proteomics work is well executed and carefully analyzed. I was particularly impressed with the chick metastasis assay that added strong evidence of in vivo relevance. 

Weaknesses: 

The weakest part of the paper is the Cdc42 work at the end of the paper. It is incomplete and not terribly convincing. This part of the paper needs to be improved significantly.

We appreciate the reviewer's recognition of the impact of our study.  Indeed, more work needs to be done to clarify the role of Cdc42 in the induction of filopodia by exosome-associated THSD7A.  We anticipate that this will be a separate manuscript, delving in-depth into how exosome-associated THSD7A interacts with recipient cells to activate Cdc42 and carrying out a variety of assays for Cdc42 activation.

Reviewer #3 (Public review): 

Summary: 

The authors identify a novel relationship between exosome secretion and filopodia formation in cancer cells and neurons. They observe that multivesicular endosomes (MVE)-plasma membrane (PM) fusion is associated with filopodia formation in HT1080 cells and that MVEs are present in filopodia in primary neurons. Using overexpression and knockdown (KD) of Rab27/HRS in HT1080 cells, melanoma cells, and/or primary rat neurons, they found that decreasing exosome secretion reduces filopodia formation, while Rab27 overexpression leads to the opposite result. Furthermore, the decreased filopodia formation is rescued in the Rab27a/HRS KD melanoma cells by the addition of small extracellular vesicles (EVs) but not large EVs purified from control cells. The authors identify endoglin as a protein unique to small EVs secreted by cancer cells when compared to large EVs. KD of endoglin reduces filopodia formation and this is rescued by the addition of small EVs from control cells and not by small EVs from endoglin KD cells. Based on the role of filopodia in cancer metastasis, the authors then investigate the role of endoglin in cancer cell metastasis using a chick embryo model. They find that injection of endoglin KD HT1080 cells into chick embryos gives rise to less metastasis compared to control cells - a phenotype that is rescued by the co-injection of small EVs from control cells. Using quantitative mass spectrometry analysis, they find that thrombospondin type 1 domain containing 7a protein (THSD7A) is downregulated in small EVs from endoglin KD melanoma cells compared to those from control cells. They also report that THSD7A is more abundant in endoglin KD cell lysate compared to control HT1080 cells and less abundant in small EVs from endoglin KD cells compared to control cells, indicating a trafficking defect. Indeed, using immunofluorescence microscopy, the authors observe THSD7A-mScarlet accumulation in CD63-positive structures in endoglin KD HT1080 cells, compared to control cells. Finally, the authors determine that exosome-secreted THSD7A induces filopodia formation in a Cdc42-dependent mechanism. 

Strengths: 

(1) While exosomes are known to play a role in cell migration and autocrine signaling, the relationship between exosome secretion and the formation of filopodia is novel. 

(2) The authors identify an exosomal cargo protein, THSD7A, which is essential for regulating this function. 

(3) The data presented provide strong evidence of a role for endoglin in the trafficking of THSD7A in exosomes. 

(4) The authors associate this process with functional significance in cancer cell metastasis and neurological synapse formation, both of which involve the formation of filopodia. 

(5) The data are presented clearly, and their interpretation appropriately explains the context and significance of the findings. 

Weaknesses: 

(1) A better characterization of the nature of the small EV population is missing: 

It is unclear why the authors chose to proceed to quantitative mass spectrometry with the bands in the Coomassie from size-separated EV samples, as there are other bands present in the small EV lane but not the large EV lane. This is important to clarify because it underlies how they were able to identify THSD7A as a unique regulator of exosome-mediated filopodia formation. Is there a reason why the total sample fractions were not compared? This would provide valuable information on the nature of the small and large EV populations. 

We would like to clarify that there are two sets of proteomics data in the manuscript. The first was comparing bands from a Coomassie gel from two samples: small EVs and large EVs from B16F1 cells. In this proteomics experiment, we identified endoglin as present in small EVs, but not large EVs. For this experiment, we only sent 4 bands from the small EV lane, chosen based on their obvious banding pattern difference on the Coomassie gel.

In the second proteomics experiment, we used quantitative iTRAQ proteomics to compare small EVs purified from B16F1 control (shScr) and endoglin KD (shEng1 and shEng2) cell lines. In this experiment, we sent total protein extracted from small EV samples for analysis. So, these samples included the entire EV content, not just selected bands from a gel. In this experiment, we identified THSD7A as reduced in the shEng small EVs.

(2) Data analysis and quantification should be performed with increased rigor: 

a) Figure 1C - The optical and temporal resolution are insufficient to conclusively characterize the association between exosome secretion and filopodia. Specifically, the 10-second interval used in the image acquisitions is too close to the reported 20-second median time between exosome secretion and filopodia formation. Two-5 sec intervals should be used to validate this. It would also be important to correlate the percentage of filopodia events that co-occur with exosome secretion. Is this a phenomenon that occurs with most or only a small number of filopodia? Additionally, resolution with typical confocal microscopy is subpar for these analyses. TIRF microscopy would offer increased resolution to parse out secretion events. As the TIRF objective is listed in the Methods section, figure legends should mention which images were acquired using TIRF microscopy. 

We acknowledge that the frame rate naturally limits our estimates of the timing of filopodia formation after exosome secretion. We set out to show a relationship between exosome secretion and filopodia formation, based on their proximity in timing. While our data set shows a median time interval of 20 seconds, the true median could be between 10-30 seconds, based on our frame rate.  Regardless of the exact timing, our data show that exosome secretion is rapidly followed by filopodia formation events.

To address the question of the percentage of filopodia events that are preceded by exosome secretion, the reviewer is correct in stating that we might need TIRF microscopy to get an accurate calculation of this number.  Nonetheless, we will review our live imaging data for this experiment to determine if this calculation is possible. Again, we will be limited by the frame rate we used to capture the images, so we could possibly be missing secretion events taking place between the 10 second time intervals.  Regardless, for the secretion events that we visualized, we always observed subsequent filopodia formation.

No TIRF imaging was used in this manuscript.  A TIRF objective was used for selected neuron imaging (see methods); however, it was used for spinning disk confocal microscopy, not for TIRF imaging.  We will clarify this in the methods.

b) Figure 2 - It would be important to perform further analysis to concretely determine the relationship between exosome secretion and filopodia stability. Are secretion events correlated with the stability of filopodia? Is there a positive feedback loop that causes further filopodia stability and length with increased secretion? Furthermore, is there an association between the proximity of secretion with stability? Quantification of filopodia more objectively (# of filopodia/cell) would be helpful. 

Our data shows that manipulation of general exosome secretion, via Hrs knockdown, affects both de novo filopodia formation and filopodia stability (Fig 2g,h). Interestingly, knockdown of endoglin only affects de novo filopodia formation, while filopodia stability is unaffected (Fig 4g,h). These results suggest that filopodia stability is dependent upon exosome cargoes besides endoglin/THSD7A.  Such cargoes might include other extracellular matrix molecules, such as fibronectin. We previously showed that exosomes promote nascent cell adhesion and rapid cell migration, through exosome-bound fibronectin (Sung et al., Nature Communications, 6:7164, 2015). We also previously found that inhibition of exosome secretion affects the persistence of invadopodia, which are filopodia-dependent structures (Hoshino et al., Cell Reports, 5:1159-1168, 2013).  We agree that this is an interesting research direction, and perhaps future work could focus on exosomal factors that are responsible for filopodia persistence.

With regard to the way we plotted the filopodia data, we plotted the cancer cell data as filopodia per cell area so that it matched the neuron data, which was plotted as filopodia per 100 mm of dendrite distance. Since the neurons cannot be imaged as a whole cell, the quantification is based on the length of the dendrite in the image. We found that graphing the cancer cell data as filopodia per cell gave similar results as filopodia per cell area, as there were no significant differences in cell area between conditions and experiments. We plan to include a new supplementary figure showing the data in Figure 2 plotted as filopodia per cell to show that this quantification gives the same results.

c) Figure 6 - Why use different gel conditions to detect THSD7A in small EVs from B16F1 cells vs HT1080 and neurons? Why are there two bands for THSD7A in panels C and E? It is difficult to appreciate the KD efficiency in E. The absence of a signal for THSD7A in the HT1080 shEng small EVs that show a signal for endoglin is surprising. The authors should provide rigorous quantification of the westerns from several independent experimental repeats. 

Detection of THSD7A via Western blot was, unfortunately, not straightforward and simple. Due to the large size (~260 kDa) of THSD7A, its low level of expression in cancer cells, as well as the inconsistency of commercially available THSD7A antibodies, we had to troubleshoot multiple conditions.  We found that it was much easier to detect THSD7A in the human fibrosarcoma cell line HT1080 than in the mouse B16F1 cells, both in the cell lysates and in the small EVs. We were usually unable to detect THSD7A using these same conditions for the mouse melanoma B16F1 samples, but were successful using native gel conditions. We also detected THSD7A in rat primary neuron samples. All these samples were from different source organisms (human, mouse, rat) and from either cell lysates or extracellular vesicles, further complicating the analyses. Expression and maturation of THSD7A in these different cell types and compartments could involve different post-translational modifications, such as glycosylation, thus requiring different methods needed to detect THSD7A on Western blots and leading to different banding patterns. Based on our THSD7A trafficking data, we believe that in control cells, most of the THSD7A is getting trafficked and secreted via small EVs. As you can see in Figure 7A, the band for THSD7A in the shScr cell lysate is relatively light and also shows a double band similar to Figure 6E (both HT1080 samples).

With regard to the level of knockdown of THSD7A in the Western blot shown in Figure 6E, the normalized level is quantitated below the bands.  If you compare that quantitation to the filopodia phenotypes in the same panel, they are quite concordant.  Figures 7B and 7C show quantification of triplicate Western blots, highlighting the significant accumulation of THSD7A in shEng cell lysates, as well as significant small EV secretion of THSD7A in control and WT rescued conditions.

(3) The study lacks data on the cellular distribution of endoglin and THSD7A: 

a) Figure 6 - Is THSD7A expected to be present in the nucleus as shown in panel D (label D is missing in the Figure). It is not clear if this is observed in neurons. a Western of endogenous THSD7A on cell fractions would clarify this. The authors should further characterize the cellular distribution of THSD7A in both cell types. Similarly, the cellular distribution of endoglin in the cancer cells should be provided. This would help validate the proposed model in Figure 8. 

The image in figure 6D shows an HT1080 cell stained with phalloidin-Alexa Fluor 488 to visualize F-actin with or without expression of THSD7A-mScarlet.  In order to fully visualize the thin filopodia protrusions, the cellular plane of focus of the images for this panel was purposely taken at the bottom of the cell, where the cell is attached to the coverslip glass. Thus, we interpret the red signal across the cell body as THSD7A-mScarlet expression on the plasma membrane underneath the cell, not in the nucleus. The neuron images only include the dendrite portion of the neurons; therefore, there is no nucleus present in the neuronal images.

b) Figure 7 - Although the western blot provides convincing evidence for the role of endoglin in THSD7A trafficking, the microscopy data lack resolution as well as key analyses. While differences between shSCR and shEng cells are clear visually, the insets appear to be zoomed digitally which decreases resolution and interferes with interpretation. It would be crucial to show the colocalization of endoglin and THSD7A within CD63-postive MVE structures. What are the structures in Figure 7E shSCR zoom1? It would be important to rule out that these are migrasomes using TSPAN4 staining. More information on how the analysis was conducted is needed (i.e. how extracellular areas were chosen and whether the images are representative of the larger population). A widefield image of shSCR and shEng cells and DAPI or HOECHST staining in the higher magnification images should be provided. Additionally, the authors should quantify the colocalization of external CD63 and mScarlet signals from many independently acquired images (as they did for the internal signals in panel F). Is there no external THSD7A signal in the shEng cells? 

The images for Figure 7E were taken with high resolution on a confocal microscope.  Insets for Figure 7E were zoomed in so that readers could see the tiny structures.  Zoom 1 in Figure 7E shows areas of extracellular deposition. In these areas, we can see small punctate depositions that are positive for CD63 and/or THSD7A-mScarlet. Our interpretation of this staining is that the cells are secreting heterogeneous small EVs that are then attached to the glass coverslip. The images and zooms in Fig 7E were chosen to be representative and indeed reveal that there is more extracellular deposition of THSD7A-mScarlet outside the control shScr cells compared to the shEng cells, consistent with more export of THSD7A into small EVs from shScr cells when compared to those of shEng cells (Fig 7A,B). However, we did not quantify this difference, as these experiments were conducted with transient transfection of THSD7A-mScarlet and it is challenging to determine which cell the extracellular THSD7A-mScarlet came from, complicating any quantitative analysis on a per-cell basis.  Quantification of internal THSD7A localization is much more straightforward in this experimental regime.  Indeed, in Figure 7F we assessed internal colocalization of THSD7A-mScarlet and CD63, which we obtained by choosing only cells that were visually positive for THSD7A-mScarlet in each transient transfection and omitting all extracellular signals. Quantifying the extracellular colocalization of THSD7A and CD63 could certainly be a future direction for this project and would require establishing cells that stably express THSD7A-mScarlet.