Not every day that one sees a tangential reference to Denis Diderot's Encyclopédie, ou dictionnaire raisonné des sciences, des arts et des métiers (English: Encyclopedia, or a Systematic Dictionary of the Sciences, Arts, and Crafts).

This is a pressing question which our governments pay far too little attention to.

left us unprepared.” Although Heidegger found it necessary, in his attempt to rethink metaphysics, to go back to the insights of the pre-Socratic philosophers, Jonas does not believe that any earlier thinkers hold the key to the ethical challenge posed by technocratic modernity, because no previous society possessed powers that could extend its reach so far in both space and time. A wholly new ethics is required, and is required simply because of the scope of our technologies.

Hans Jonas, a student of Martin Heidegger, argues in The Imperative of Responsibility, that modern technology requires a new ethical framework because no previous societies possessed the technical powers to extend their reach so far in time and space as ours currently do.

Indeed, Maha! We hope participants in the Summer Open Pedagogy Adventure series might ponder, and explore here in annotation space.

How /what does annotation activity open up? Is that experience going to be the same for all? Yes we can create safer spaces in private group Hypothes.is annotation, but it is more cumbersome and we trade off perhaps the possible serendipity of connection with peers offering different perspectives.

And Why? Reply here and tag your annotation opsa

I think that it is interesting to read that not just having internet causes a divide, but it is also the digital literacy skills that go with it. I feel like digital literacy is a missed component especially when I think of the digital divide.

This is very true that it is easy to spout averages and numbers while lumping another human being in as a statistic. I agree that the numbers do represent individuals so the data should be approached that way too. If we start talking about the people being directly affected by it instead of just going by numbers and data points more people would probably relate to it and learn more about it. This link https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410028703 shows both the percentage and the actual number of people affected. This way we can see that the percentage does not seem all that big but the actual number of people affected is thousands.

I like the way that this was worded. I always thought of data as just numbers that you plug in and learn things from but that was all it was to me. The fact that it can be as complex or as simple as you want or as long or as short as you want means that each piece of data is unique to the person who created it. This has reminded me of the class and all of our final projects. We may be using some of the same software or tools to make our projects or we may even have a similar topic to someone else but each one is still going to turn out different. We will use the software and tools in our own way to represent the point we are making. This is something I have found throughout the whole course which is that even though each piece of digital humanities seems like there would only be one way to do it like data sets, there are actually so many interpretations and ways you can go with it.

And this what we are asking participants in the Summer Open Pedagogy Adventure series to explore and question. Is this framing of students as content creation, which is valuable, the full range of what is open pedagogy? Engage with us here and elsewhere we we look at annotation as a form of open pedagogy, of going being the creation and adoption of OERs but building activities around them.

What do you think of Annotations being freely reused as licensed CC0?

What do our adventurers think? Annotate and tag opsa

..

..

Or, even worse, to frame the ending of apartheid as a result of the armed struggle of MK. To the extent that armed struggle did contribute, it was that of Cubans, Angolans & Namibians.

Mamdani has interesting ideas about the possibility of redefining the concept of "nation" away from imagined community, towards shared struggle.

Isn't the causality the reverse of this?

SRWP & NUMSA both entangled themselves with RET politics during the run-up to the election, by supporting the coal-trucking mafia's assault on Eskom.

Right until his expulsion, Malema vowed to remain loyal to the ANC unto death.

Not only vague discontent, but specific historical grievances.

Tolsi's piece omits two important parts of the picture: from 1946, the Natal Indian Congress (whose leadership included some of Gandhi's children & grandchildren) had incurred the wrath of local racist elites with its "Passive Resistance" campaign; secondly, the 1980s targeting by ethnically mobilised Zulus of the "Indian" community at and around Gandhi's ashram in Phoenix, where his house (converted to a museum) and the school named after his wife were among the buildings razed.

Are there no other govts responding with austerity?

Both the RET faction and the EFF are alliances containing some genuine leftists who are prepared to tolerate authoritarian & hypocritical "leadership" on the dubious basis of "my enemy's enemy is my friend."

Two areas of the country - not even two whole provinces.

It also isn't a place any more than "postal space" is a place

I do sort of like getting to repeat, network, recontextualize

This is also what's overwhelming about it. Instagram presents me with the restriction of The Square. The web can be anything

Clarity is only one possible goal!

Trecho importante pro tcc.

Yeah, this part right here is gold. Authenticity means something completely different to them, they're using a completely different mental model to interpret what that means.

Yeah, I've never been able to understand the desire to get blue-checked on any platform. I see people tweet sometimes, complaining that their request to be blue-checked on Twitter was denied, or celebrating when they do get the check. It all feels so weird. You're celebrating that some people at Twitter deemed you worthy enough to have a verified profile on their platform? Why is that worth celebrating? "Congrats on your elevated status amongst us Twitter folk"

Thank Donald for that

This is interesting, because while these platforms are exposing people to a lot that they may otherwise not have seen, and teaching them things, there's also so much misinformation on the platform, and the people making content on it are evidently missing out on learning to chase the influencer bag

"I saw it on tik tok" is the new "I read it on the internet"

lol wut?

Funny enough, this made me think of how I've been seeing more and more people in devrel engaging with people via tik tok and other social media platforms. There are already communities for devrel where people share ideas and content they've created for their companies, which is in some way a virtual collab house of sorts (there's even a collab channel in a Slack group I'm in). Perhaps this is already kinda happening in that industry

wow. And every time I've eaten at Raising Cane's I've had to pay them!

The effect that social media is having on people's psyches is wild. I wonder how this plays out over the next decade or so, as these people enter the workforce and perhaps start families of their own. How different will the societies they create be from today's?

They've essentially figured out how to industrialize the process of making a celebrity

This description makes me feel very robotic as if she is emotionless, not totally autonomous and takes a lot of time to process information. But at the same time she ignores people, which makes me feel she is just really confused and lost.

Who's her here? Is it referring to Mrs. Raddick's daughter? Why is it in "--"?

This description makes this part sounds like a fairytale

She is so young, yet always waiting around for her mother. I guess this is why her character is so ambiguous, because though she is young, she does not live doing what she wants to do. Her mother, who she waits for, is named, but since her daughter's life is filled of waiting for her mother, she remains unnamed.

Who is the narrator of this story? There are a couple characters introduced, and a lot of dialogue, but the narrator, who refers to themselves as I, has not been introduced by name.

I guess we know who the young girl is, to give context to the title. I wonder how young she is, and why she's at the Casino. It says that she is there for her flight, but what flight would be at the Casino?

Sounds like PyPA does not like poetry as much for political/business reasons

Reason why Anaconda got so popular

Potential future of pyproject.toml

Finding the right balance while learning. For example, start with guided and eventually move to unguided learning:

Soudns like shotgun debugging is not the worst method to learn programming

Cultivating a growth mindset while learning programming

To truly learn something, it is good to have the concrete GOAL, otherwise you might not push yourself as hard

https://twitter.com/ankostis/status/1419562733616386052?s=19

Indeed, heading problems correlate to autism disorders particularly of that kind: nose understanding speech in noisy environments.

Inclusive teaching with technology means checking that things work properly on mobile devices. Annotating a document or website on a smart phone is easy!

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Broken link, 7/26/2021

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one word "shortcuts" for consistency

one word "shortcuts" for consistency

where's the link at?

semicolon

Suggest starting a new sentence here to avoid a run-on sentence.

duplicate "our"

I might suggest dropping the ',and' in favor of starting a new sentence.

Move the period outside the parenthesis

Split into two sentences - a period instead of a comma.

I might suggest moving toward "a" more accurate understanding

remove "in"

two accuracies do not equal a positive.

I would remove the commas

"among" is more accurate.

Remove this extraneous 'a'

Collaborative work: logic process within critical thinking.

The role of the human over the algorithms

The use of technology for military objectives is one of the advantages I could observe because the risk of people in the war field is dangerous. What about the easy way to manipulate information once someone can hack one of those systems?

This part might help researches with the data collection, even the analysis in terms of time.

The advantages shown in the article are fascinating because it brings new challenges and skills that education should focus on. However, it is scary because AI is growing triple more than education. That means that we as teachers should prepare children to an uncertain world with unknown jobs.

It is very impressive the capacity of the human beings to develop this time of intelligence. Although, How is it possible to find the limits of a human invention when we are incapable of knowing our own limits? In my opinion, AI is a motive to design better human beings that can over-reach our abilities, but How can we stop it?

According to Mydske (2020) Artificial intelligence has been developed to simulate, and precede human movements and thinkings. He believes it is a great opportunity for sustainability. Whereas, my opinion is to be cautious due to this type of intelligence that somehow it might go beyond what it is made of since the beginning.

I could imagine that this was the beginning of the famous game called Jeopardy. You can create you own in here https://jeopardylabs.com/

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A nice Unix oneliner really feels like instructions your grandmother might have written down about how to know when to flip the pancake, which in turn feels like how you know to stop eating blackberries at Michaelmas when the devil blights them. Patterns as charms.

Armstrong wrote about this topic, using the term "affecting presence". See https://4banks.net/Mes-Rel/temi/affecting.htm

On the definition of religion, see https://4banks.net/Mes-Rel/temi/definition%20of%20religion.htm

On the active nature of God, see https://4banks.net/Mes-Rel/temi/transitivity.htm

https://4banks.net/Mes-Rel/temi/innumerabilita%60.htm

consultant role mapping

All the Python import statements come down to the __import__() function

I really love how Buster laid out, hey, let's figure out exactly what questions we want to dig into here, and then the guy responds with just a shotgun blast of "not all police shootings". You can reject Benson's ideas of how to grid-out analysis, sure, but fuzzing around them with a bunch of "why is it bad to assume this person is a biker" is... bad.

Big woof at the idea that if a prejudice is based on accurate data, it ceases to be prejudice (and shouldn't be examined/criticized/worked against). If I observe that bad teeth are correlated with many things that are correlated with interesting ideas and arguments, I may come up with the heuristic of paying less attention to the person in front of me if they have bad teeth. This might be entirely substantiated by empirical evidence, and it would still be prejudice (prejudice, pre-judging), and it would still have the power to create shitty secondary effects in society (see: American orthodontia enforcing class lines).

This is overall a good piece, although it does contain some errors, but this claim is probably the weirdest and wrongest.

And that is what we are doing here in the OE Global Open Pedagogy Summer Adventure (2021) in particular, the interactivity strand.

We can use these tools to augment this text but also reply to others, like a greeting space. So if you are here during our live workshop, or maybe later, reply with a greeting to let us know who you are, how you see (or maybe want to ask about) web annotation as an act of open pedagogy.

And explore the many annotations already present here...

And if you remember, add a tag of opsa to your annotations during this activity -- watch what happens.

Let's go adventuring with web annotation

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operational readiness or remedial action?

warning, NOT administrative fine, due to remedial action/diligence post-factum

remedial action

risk assessment - personal data & political ideology - combination of data/sources

finding of not adequate security measures

1769

christian Kernt, 68

1758

Anna Maria Kernt, 61

1747

Gottfried Günther, Anna Maria Kernt

對中國來說甚麼是重要的? 軍事能力

中國政府認為consumer internet沒有真正創造價值

中國沒有對半導體與AI產業下手，而是對面像消費者的網路巨頭下手

中美監管不太一樣，美國是為了促進競爭，中國是為了殺死整個產業

Author Response:

We thank the editors and the reviewers for their careful reading and rigorous evaluation of our manuscript. We thank them for their positive comments and constructive feedback, which led us to add further lines of evidence in support of our central hypothesis that intrinsic neuronal resonance could stabilize heterogeneous grid-cell networks through targeted suppression of low-frequency perturbations. In the revised manuscript, we have added a physiologically rooted mechanistic model for intrinsic neuronal resonance, introduced through a slow negative feedback loop. We show that stabilization of patterned neural activity in a heterogeneous continuous attractor network (CAN) model could be achieved with this resonating neuronal model. These new results establish the generality of the stabilizing role of neuronal resonance in a manner independent of how resonance was introduced. More importantly, by specifically manipulating the feedback time constant in the neural dynamics, we establish the critical role of the slow kinetics of the negative feedback loop in stabilizing network function. These results provide additional direct lines of evidence for our hypothesis on the stabilizing role of resonance in the CAN model employed here. Intuitively, we envisage intrinsic neuronal resonance as a specific cellular-scale instance of a negative feedback loop. The negative feedback loop is a well-established network motif that acts as a stabilizing agent and suppresses the impact of internal and external perturbations in engineering applications and biological networks.

Reviewer #1 (Public Review):

The authors succeed in conveying a clear and concise description of how intrinsic heterogeneity affects continuous attractor models. The main claim, namely that resonant neurons could stabilize grid-cell patterns in medial entorhinal cortex, is striking.

We thank the reviewer for their time and effort in evaluating our manuscript, and for their rigorous evaluation and positive comments on our study.

I am intrigued by the use of a nonlinear filter composed of the product of s with its temporal derivative raised to an exponent. Why this particular choice? Or, to be more specific, would a linear bandpass filter not have served the same purpose?

Please note that the exponent was merely a mechanism to effectively tune the resonance frequency of the resonating neuron. In the revised manuscript, we have introduced a new physiologically rooted means to introduce intrinsic neuronal resonance, thereby confirming that network stabilization achieved was independent of the formulation employed to achieve resonance.

The magnitude spectra are subtracted and then normalized by a sum. I have slight misgivings about the normalization, but I am more worried that, as no specific formula is given, some MATLAB function has been used. What bothers me a bit is that, depending on how the spectrogram/periodogram is computed (in particular, averaged over windows), one would naturally expect lower frequency components to be more variable. But this excess variability at low frequencies is a major point in the paper.

We have now provided the specific formula employed for normalization as equation (16) of the revised manuscript. We have also noted that this was performed to account for potential differences in the maximum value of the homogeneous vs. heterogeneous spectra. The details are provided in the Methods subsection “Quantitative analysis of grid cell temporal activity in the spectral domain” of the revised manuscript. Please note that what is computed is the spectra of the entire activity pattern, and not a periodogram or a scalogram. There was no tiling of the time-frequency plane involved, thus eliminating potential roles of variables there on the computation here.

In addition to using variances of normalized differences to quantify spectral distributions, we have also independently employed octave-based analyses (which doesn’t involve normalized differences) to strengthen our claims about the impact of heterogeneities and resonance on different bands of frequency. These octave-based analyses also confirm our conclusions on the impact of heterogeneities and neuronal resonance on low-frequency components.

Finally, we would like to emphasize that spectral computations are the same for different networks, with networks designed in such a way that there was only one component that was different. For instance, in introducing heterogeneities, all other parameters of the network (the specific trajectory, the seed values, the neural and network parameters, the connectivity, etc.) remained exactly the same with the only difference introduced being confined to the heterogeneities. Computation of the spectral properties followed identical procedures with activity from individual neurons in the two networks, and comparison was with reference to identically placed neurons in the two networks. Together, based on the several routes to quantifying spectral signatures, based on the experimental design involved, and based on the absence of any signal-specific tiling of the time-frequency plane, we argue that the impact of heterogeneities or the resonators on low-frequency components is not an artifact of the analysis procedures.

We thank the reviewer for raising this issue, as it helped us to elaborate on the analysis procedures employed in our study.

Which brings me to the main thesis of the manuscript: given the observation of how heterogeneities increase the variability in the low temporal frequency components, the way resonant neurons stabilize grid patterns is by suppressing these same low frequency components.

I am not entirely convinced that the observed correlation implies causality. The low temporal frequeny spectra are an indirect reflection of the regularity or irregularity of the pattern formation on the network, induced by the fact that there is velocity coupling to the input and hence dynamics on the network. Heterogeneities will distort the pattern on the network, that is true, but it isn't clear how introducing a bandpass property in temporal frequency space affects spatial stability causally.

Put it this way: imagine all neurons were true oscillators, only capable of oscillating at 8 Hz. If they were to synchronize within a bump, one will have the field blinking on and off. Nothing wrong with that, and it might be that such oscillatory pattern formation on the network might be more stable than non-oscillatory pattern formation (perhaps one could even demonstrate this mathematically, for equivalent parameter settings), but this kind of causality is not what is shown in the manuscript.

The central hypothesis of our study was that intrinsic neuronal resonance could stabilize heterogeneous grid-cell networksthrough targeted suppression of low-frequency perturbations.

In the revised manuscript, we present the following lines of evidence in support of this hypothesis (mentioned now in the first paragraph of the discussion section of the revised manuscript):

1. Neural-circuit heterogeneities destabilized grid-patterned activity generation in a 2D CAN model (Figures 2–3).

2. Neural-circuit heterogeneities predominantly introduced perturbations in the lowfrequency components of neural activity (Figure 4).

3. Targeted suppression of low-frequency components through phenomenological (Figure 5C) or through mechanistic (new Figure 9D) resonators resulted in stabilization of the heterogeneous CAN models (Figure 8 and new Figure 11). We note that the stabilization was achieved irrespective of the means employed to suppress low-frequency components: an activity-independent suppression of low-frequencies (Figure 5) or an activity-dependent slow negative feedback loop (new Figure 9).

4. Changing the feedback time constant τm in mechanistic resonators, without changes to neural gain or the feedback strength allowed us to control the specific range of frequencies that would be suppressed. Our analyses showed that a slow negative feedback loop, which results in targeted suppression of low-frequency components, was essential in stabilizing grid-patterned activity (new Figure 12). As the slow negative feedback loop and the resultant suppression of low frequencies mediates intrinsic resonance, these analyses provide important lines of evidence for the role of targeted suppression of low frequencies in stabilizing grid patterned activity.

5. We demonstrate that the incorporation of phenomenological (Figure 13A–C) or mechanistic (new Figure panels 13D–F) resonators specifically suppressed lower frequencies of activity in the 2D CAN model.

6. Finally, the incorporation of resonance through a negative feedback loop allowed us to link our analyses to the well-established role of network motifs involving negative feedback loops in inducing stability and suppressing external/internal noise in engineering and biological systems. We envisage intrinsic neuronal resonance as a cellular-scale activitydependent negative feedback mechanism, a specific instance of a well-established network motif that effectuates stability and suppresses perturbations across different networks (Savageau, 1974; Becskei and Serrano, 2000; Thattai and van Oudenaarden, 2001; Austin et al., 2006; Dublanche et al., 2006; Raj and van Oudenaarden, 2008; Lestas et al., 2010; Cheong et al., 2011; Voliotis et al., 2014). A detailed discussion on this important link to the stabilizing role of this network motif, with appropriate references to the literature is included in the new discussion subsection “Slow negative feedback: Stability, noise suppression, and robustness”.

We thank the reviewer for their detailed comments. These comments helped us to introducing a more physiologically rooted mechanistic form of resonance, where we were able to assess the impact of slow kinetics of negative feedback on network stability, thereby providing more direct lines of evidence for our hypothesis. This also allowed us to link resonance to the wellestablished stability motif: the negative feedback loop. We also note that our analyses don’t employ resonance as a route to introducing oscillations in the network, but as a means for targeted suppression of low-frequency perturbations through a negative feedback loop. Given the strong quantitative links of negative feedback loops to introducing stability and suppressing the impact of perturbations in engineering applications and biological networks, we envisage intrinsic neuronal resonance as a stability-inducing cellular-scale activity-dependent negative feedback mechanism.

Reviewer #2 (Public Review):

[...] The pars construens demonstrates that similar networks, but comprised of units with different dynamical behavior, essentially amputated of their slowest components, do not suffer from the heterogeneities - they still produce grids. This part proceeds through 3 main steps: a) defining "resonator" units as model neurons with amputated low frequencies (Fig. 5); b) showing that inserted into the same homogeneous CAN network, "resonator" units produce the same grids as "integrator" units (Figs. 6,7); c) demonstrating that however the network with "resonator" units is resistant to heterogeneities (Fig. 8). Figs. 9 and 10 help understand what has produced the desired grid stabilization effect. This second part is on the whole also well structured, and its step c) is particularly convincing.

We thank the reviewer for their time and effort in evaluating our manuscript, and for their rigorous evaluation and positive comments on our study.

Step b) intends to show that nothing important changes, in grid pattern terms, if one replaces the standard firing rate units with the ad hoc defined units without low frequency behavior. The exact outcome of the manipulation is somewhat complex, as shown in Figs. 6 and 7, but it could be conceivably summed up by stating that grids remain stable, when low frequencies are removed. What is missing, however, is an exploration of whether the newly defined units, the "resonators", could produce grid patterns on their own, without the CAN arising from the interactions between units, just as a single-unit effect. I bet they could, because that is what happens in the adaptation model for the emergence of the grid pattern, which we have studied extensively over the years. Maybe with some changes here and there, but I believe the CAN can be disposed of entirely, except to produce a common alignment between units, as we have shown.

Step a), finally, is the part of the study that I find certainly not wrong, but somewhat misleading. Not wrong, because what units to use in a model, and what to call them, is a legitimate arbitrary choice of the modelers. Somewhat misleading, because the term "resonator" evokes a more specific dynamical behavior that than obtained by inserting Eqs. (8)-(9) into Eq. (6), which amounts to a brute force amputation of the low frequencies, without any real resonance to speak of. Unsurprisingly, Fig. 5, which is very clear and useful, does not show any resonance, but just a smooth, broad band-pass behavior, which is, I stress legitimately, put there by hand. A very similar broad band-pass would result from incorporating into individual units a model of firing rate adaptation, which is why I believe the "resonator" units in this study would generate grid patterns, in principle, without any CAN.

We thank the reviewer for these constructive comments and questions, as they were extremely helpful in (i) formulating a new model for rate-based resonating neurons that is more physiologically rooted; (ii) demonstrating the stabilizing role of resonance irrespective of model choices that implemented resonance; and (iii) mechanistically exploring the impact of targeted suppression of low frequency components in neural activity. We answer these comments of the reviewer in two parts, the first addressing other models for grid-patterned activity generation and the second addressing the reviewer’s comment on “brute force amputation of the low frequencies” in the resonator neuron presented in the previous version of our manuscript.

I. Other models for grid-patterned activity generation.

In the adaptation model (Kropff and Treves, 2008; Urdapilleta et al., 2017; Stella et al., 2020), adaptation in conjunction with place-cell inputs, Hebbian synaptic plasticity, and intrinsic plasticity (in gain and threshold) to implement competition are together sufficient for the emergence of the grid-patterned neural activity. However, the CAN model that we chose as the substrate for assessing the impact of neural circuit heterogeneities on functional stability is not equipped with the additional components (place-cell inputs, synaptic/intrinsic plasticity). Therefore, we note that decoupling the single unit (resonator or integrator) from the network does not yield grid-patterned activity.

However, we do agree that a resonator neuron endowed with additional components from the adaptation model would be sufficient to elicit grid-patterned neural activity. This is especially clear with the newly introduced mechanistic model for resonance through a slow feedback loop (Figure 9). Specifically, resonating conductances such as HCN and M-type potassium channels can effectuate spike-frequency adaptation. One of the prominent channels that is implicated in introducing adaptation, the calcium-activated potassium channels implement a slow activitydependent negative feedback loop through the slow calcium kinetics. Neural activity drives calcium influx, and the slow kinetics of the calcium along with the channel-activation kinetics drive a potassium current that completes a negative feedback loop that inhibits neural activity. Consistently, one of the earliest-reported forms of electrical resonance in cochlear hair cells was shown to be mediated by calcium-activated potassium channels (Crawford and Fettiplace, 1978, 1981; Fettiplace and Fuchs, 1999). Thus, adaptation realized as a slow negative-feedback loop, in conjunction with place-cell inputs and intrinsic/synaptic plasticity would elicit gridpatterned neural activity as demonstrated earlier (Kropff and Treves, 2008; Urdapilleta et al., 2017; Stella et al., 2020).

There are several models for the emergence of grid-patterned activity, and resonance plays distinct roles (compared to the role proposed through our analyses) in some of these models (Giocomo et al., 2007; Kropff and Treves, 2008; Burak and Fiete, 2009; Burgess and O'Keefe, 2011; Giocomo et al., 2011b; Giocomo et al., 2011a; Navratilova et al., 2012; Pastoll et al., 2012; Couey et al., 2013; Domnisoru et al., 2013; Schmidt-Hieber and Hausser, 2013; Yoon et al., 2013; Schmidt-Hieber et al., 2017; Urdapilleta et al., 2017; Stella et al., 2020; Tukker et al., 2021). However, a common caveat that spans many of these models is that they assume homogeneous networks that do not account for the ubiquitous heterogeneities that span neural circuits. Our goal in this study was to take a step towards rectifying this caveat, towards understanding the impact of neural circuit heterogeneities on network stability. We chose the 2D CAN model for grid-patterned activity generation as the substrate for addressing this important yet under-explored question on the role of biological heterogeneities on network function. As we have mentioned in the discussion section, this choice implies that our conclusions are limited to the 2D CAN model for grid patterned generation; these conclusions cannot be extrapolated to other networks or other models for grid-patterned activity generation without detailed analyses of the impact of neural circuit heterogeneities in those models. As our focus here was on the stabilizing role of resonance in heterogeneous neural networks, with 2D CAN model as the substrate, we have not implemented the other models for grid-patterned generation. The impact of biological heterogeneities and resonance on each of these models should be independently addressed with systematic analyses similar to our analyses for the 2D CAN model. As different models for grid-patterned activity generation are endowed with disparate dynamics, and have different roles for resonance, it is conceivable that the impact of biological heterogeneities and intrinsic neuronal resonance have differential impact on these different models. We have mentioned this as a clear limitation of our analyses in the discussion section, also presenting future directions for associated analyses(subsection: “Future directions and considerations in model interpretation”).

II. Brute force amputation of the low frequencies in the resonator model.

We completely agree with the reviewer on the observation that the resonator model employed in the previous version of our manuscript was rather artificial, with the realization involving brute force amputation of the lower frequencies. To address this concern, in the revised manuscript, we constructed a new mechanistic model for single-neuron resonance that matches the dynamical behavior of physiological resonators. Specifically, we noted that physiological resonance is elicited by a slow activity-dependent negative feedback (Hutcheon and Yarom, 2000). To incorporate resonance into our rate-based model neurons, we mimicked this by introducing a slow negative feedback loop into our single-neuron dynamics (the motivations are elaborated in the new results subsection “Mechanistic model of neuronal intrinsic resonance: Incorporating a slow activity-dependent negative feedback loop”). The singleneuron dynamics of mechanistic resonators were defined as follows:

Here, S governed neuronal activity, τ defined the feedback state variable, g represented the integration time constant, Ie was the external current, and g represented feedback strength. The slow kinetics of the negative feedback was controlled by the feedback time constant (τm). In order to manifest resonance, τm > τ (Hutcheon and Yarom, 2000). The steady-state feedback kernel (m∞) of the negative feedback is sigmoidally dependent on the output of the neuron (S), defined by two parameters: half-maximal activity (S1/2) and slope (k). The single-neuron dynamics are elaborated in detail in the methods section (new subsection: Mechanistic model for introducing intrinsic resonance in rate-based neurons).

We first demonstrate that the introduction of a slow-negative feedback loop introduce resonance into single-neuron dynamics (new Figure 9D–E). We performed systematic sensitivity analyses associated with the parameters of the feedback loop and characterized the dependencies of intrinsic neuronal resonance on model parameters (new Figure 9F–I). We demonstrate that the incorporation of resonance through a negative feedback loop was able to generate grid-patterned activity in the 2D CAN model employed here, with clear dependencies on model parameters (new Figure 10; new Figure 10-Supplements1–2). Next, we incorporated heterogeneities into the network and demonstrated that the introduction of resonance through a negative feedback loop stabilized grid-patterned generation in the heterogeneous 2D CAN model (new Figure 11).

The mechanistic route to introducing resonance allowed us to probe the basis for the stabilization of grid-patterned activity more thoroughly. Specifically, with physiological resonators, resonance manifests only when the feedback loop is slow (new Figure 9I; Hutcheon and Yarom, 2000). This allowed us an additional mechanistic handle to directly probe the role of resonance in stabilizing the grid patterned activity. We assessed the emergence of grid-patterned activity in heterogeneous CAN models constructed with networks constructors with neurons with different τm values (new Figure 12). Strikingly, we found that when τm value was small (resulting in fast feedback loops), there was no stabilization of gridpatterned activity in the CAN model, especially with the highest degree of heterogeneities (new Figure 12). With progressive increase in τm, the patterns stabilized with grid score increasing with τm=25 ms (new Figure 12) and beyond (new Figure 11B; τm=75 ms). Finally, our spectral analyses comparing frequency components of homogeneous vs. heterogeneous resonator networks (new Figure panels 13D–F) showed the suppression of low-frequency perturbations in heterogeneous CAN networks.

We gratefully thank the reviewer for raising the issue with the phenomenological resonator model. This allowed us to design the new resonator model and provide several new lines of evidence in support of our central hypothesis. The incorporation of resonance through a negative feedback loop also allowed us to link our analyses to the well-established role of network motifs involving negative feedback loops in inducing stability and suppressing external/internal noise in engineering and biological systems. We envisage intrinsic neuronal resonance as a cellular-scale activity-dependent negative feedback mechanism, a specific instance of a well-established network motif that effectuates stability and suppresses perturbations across different networks (Savageau, 1974; Becskei and Serrano, 2000; Thattai and van Oudenaarden, 2001; Austin et al., 2006; Dublanche et al., 2006; Raj and van Oudenaarden, 2008; Lestas et al., 2010; Cheong et al., 2011; Voliotis et al., 2014). A detailed discussion on this important link to the stabilizing role of this network motif, with appropriate references to the literature is included in the new discussion subsection “Slow negative feedback: Stability, noise suppression, and robustness”.

Evaluation Summary:

This is a careful and systematic simulation study that convincingly illustrates a role for intrinsic resonance properties in suppressing the effects of cellular and network heterogeneities in a continuous attractor network model of grid cell firing patterns. The study shows that overly simplified models of neurons can lead to fragility in important network level behaviour and that intrinsic neuronal properties strongly influence relevant network level dynamics. This an important result that likely applies to a broad range of network models. Further investigation into the mechanism, possibly using a simplified model, would substantiate the simulation results and fully exploit the power of models in providing intuition and illustrating the generality of the observations.

(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

Reviewer #1 (Public Review):

The authors succeed in conveying a clear and concise description of how intrinsic heterogeneity affects continuous attractor models. The main claim, namely that resonant neurons could stabilize grid-cell patterns in medial entorhinal cortex, is striking.

I am intrigued by the use of a nonlinear filter composed of the product of s with its temporal derivative raised to an exponent. Why this particular choice? Or, to be more specific, would a linear bandpass filter not have served the same purpose?

The magnitude spectra are subtracted and then normalized by a sum. I have slight misgivings about the normalization, but I am more worried that , as no specific formula is given, some MATLAB function has been used. What bothers me a bit is that, depending on how the spectrogram/periodogram is computed (in particular, averaged over windows), one would naturally expect lower frequency components to be more variable. But this excess variability at low frequencies is a major point in the paper.

Which brings me to the main thesis of the manuscript: given the observation of how heterogeneities increase the variability in the low temporal frequency components, the way resonant neurons stabilize grid patterns is by suppressing these same low frequency components.

I am not entirely convinced that the observed correlation implies causality. The low temporal frequeny spectra are an indirect reflection of the regularity or irregularity of the pattern formation on the network, induced by the fact that there is velocity coupling to the input and hence dynamics on the network. Heterogeneities will distort the pattern on the network, that is true, but it isn't clear how introducing a bandpass property in temporal frequency space affects spatial stability causally.

Put it this way: imagine all neurons were true oscillators, only capable of oscillating at 8 Hz. If they were to synchronize within a bump, one will have the field blinking on and off. Nothing wrong with that, and it might be that such oscillatory pattern formation on the network might be more stable than non-oscillatory pattern formation (perhaps one could even demonstrate this mathematically, for equivalent parameter settings), but this kind of causality is not what is shown in the manuscript.

Reviewer #2 (Public Review):

The manuscript takes a remarkably systematic and unbiased approach to the question of whether the models, that explain in terms of recurrent connectivity the grid firing patterns observed in the entorhinal cortex of rodents and other species, would really work given heterogeneity in the values of several parameters, that in the standard models are assumed to take a fixed value. Since the real degree of heterogeneity is difficult to measure, but even more because it is difficult to relate measured quantities to the parameters in simple models which perforce include many artificial components, the authors proceed by setting 5 levels of heterogeneity in 3 parameters, and by simulating the network with each parameter made heterogeneous alone, or all 3 in combination. In short, grids are destabilized (Figure 2), but with interesting differential effects on different aspects of the activity patterns (Fig. 3). This pars destruens is clear, strong and entirely convincing. It is concluded by showing that heterogeneities act on the slow components of the dynamics (Fig. 4).

The pars construens demonstrates that similar networks, but comprised of units with different dynamical behavior, essentially amputated of their slowest components, do not suffer from the heterogeneities - they still produce grids. This part proceeds through 3 main steps: a) defining "resonator" units as model neurons with amputated low frequencies (Fig. 5); b) showing that inserted into the same homogeneous CAN network, "resonator" units produce the same grids as "integrator" units (Figs. 6,7); c) demonstrating that however the network with "resonator" units is resistant to heterogeneities (Fig. 8). Figs. 9 and 10 help understand what has produced the desired grid stabilization effect. This second part is on the whole also well structured, and its step c) is particularly convincing.

Step b) intends to show that nothing important changes, in grid pattern terms, if one replaces the standard firing rate units with the ad hoc defined units without low frequency behavior. The exact outcome of the manipulation is somewhat complex, as shown in Figs. 6 and 7, but it could be conceivably summed up by stating that grids remain stable, when low frequencies are removed. What is missing, however, is an exploration of whether the newly defined units, the "resonators", could produce grid patterns on their own, without the CAN arising from the interactions between units, just as a single-unit effect. I bet they could, because that is what happens in the adaptation model for the emergence of the grid pattern, which we have studied extensively over the years. Maybe with some changes here and there, but I believe the CAN can be disposed of entirely, except to produce a common alignment between units, as we have shown.

Step a), finally, is the part of the study that I find certainly not wrong, but somewhat misleading. Not wrong, because what units to use in a model, and what to call them, is a legitimate arbitrary choice of the modelers. Somewhat misleading, because the term "resonator" evokes a more specific dynamical behavior that than obtained by inserting Eqs. (8)-(9) into Eq. (6), which amounts to a brute force amputation of the low frequencies, without any real resonance to speak of. Unsurprisingly, Fig. 5, which is very clear and useful, does not show any resonance, but just a smooth, broad band-pass behavior, which is, I stress legitimately, put there by hand. A very similar broad band-pass would result from incorporating into individual units a model of firing rate adaptation, which is why I believe the "resonator" units in this study would generate grid patterns, in principle, without any CAN.

Testing page notes

I also think there are interesting insights within the west to be had here. Sometimes I have to explain to colleagues here in Seattle what it's like over the mountains in central Washington, and that actually central Washington isn't eastern Washington, and it'd all be a lot easier if I could just point to this and say "there's the mega-Seattle-area, Yakima, the Tri-Cities, Spokane, and a bit of Portland spillover in denial about it. The rural areas around each of these places are different just like the populated areas are different."

why do you have to call me out like that

就如同netflix一直提到的 與其他的娛樂競爭 而不是只有串流平台

獨特IP是netflix進軍遊戲最弱的點

ô

pour uniformiser avec les autres éléments de l'énumération, j'enlèverais le s.

Ce serait intéressant de lancer ce terme dans le paragraphe de description.

les

virgule manquante

J'aurais fait l'accord avec la longueur qui est limitée. Mais ça marche aussi avec posts. D'ailleurs, on traduirait plus par «publication» ou «entrée»?

This is an interesting point and I do think such behavioral consequences of policy should be considered.

So we can go out of lockdown?

Responding to trends proactively does not equate to hysteria. We should expect that cases will continue to rise as the weather gets coolers and if vaccination rates remain at current levels.

Again, nothing is a strong word and can undermine trust for the small percentage of people who still develop complications of COVID despite being vaccinated. We need to be more comfortable speaking in terms of relative risk rather than black and white.

Unvaccinated children may be at low risk for hazard to their own health, but what about spreading to others like unvaccinated relatives?

Strong word.

This is a false dichotomy. In safety/quality, we talk about a layered approach to reduce risk. As long as we have significant portions of the population unvaccinated. Masks can play a part.

You won'y build on it eh, and bring an another walled garden.

Several of the comments I read on this page suggest going into more detail on some topics. I was able to integrate a couple of these suggestions, but my concerns about the length of the chapter kept me from acting on all of them. The clearest message I got from the instructors I talked with before starting this project was that the chapters needed to be short in order for them to actually be read. I've tried to honor that request. All your comments are appreciated and I'll take them into account as I continue to develop more info lit OER material.

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Reply to the reviewers

First of all, we would like to thank the editor and all reviewers for the effort to evaluate our paper in this difficult era of COVID-19.

Reviewer #1

(Significance): Overall, this manuscript is very clear and easy to follow. The manuscript could be improved by making the following changes:

We thank the reviewer for the favorable comment and will revise the manuscript according to the suggestions.

Reviewer #2

(Evidence, reproducibility and clarity): The use of genetics is particularly impressive but the lack of major discoveries dampens the enthusiasm. Additional efforts to mechanistically define wave initiation and wave propagation would significantly improve the impact of the manuscript. Moreover, some of the conclusions are not fully supported by the data and require further experimentation and/or analysis.

We admit that marked redundancy of function among the EGFR ligands and their essential roles in cell growth prevent us from obtaining very clear results. Considering the importance of EGFR ligands in biology, we believe, our observation will give invaluable suggestions to whom wishes to clarify the roles played by EGFR-family protein in other biological contexts.

(Significance): While it is known that ADAM17 is critical to process EGFR ligands, the specific or redundant roles of different ligands remains an open question. The authors find that all ADAM17 ligands contribute to ERK signaling waves but may have specific contributions to other phenotypes. This work would be of interest to the signaling dynamics, epithelial and developmental biology communities.

We thank the reviewer for the favorable comment.

Reviewer #3

(Evidence, reproducibility and clarity): Overall, this study is carried out with a high degree of rigor and technical excellence, with clear reporting of experimental details and replication. The writing and figures are very clear, and there are no obvious technical problems. However, there are some areas in which the strength and clarity of the conclusions could be strengthened by relatively simple experiments.

We thank the reviewer for the favorable comment. We have already performed some of the experiments suggested by the reviewer. As the reviewer might have anticipated, co-culture with the wild type MDCK cells helps mutant cells to survive. We believe we could propose a clearer model in the revised paper.

(Significance): This study definitively establishes the role of 4 EGFR ligands in the generation of ERK activity waves in MDCK cells. While other studies, including some from the senior author's lab, have strongly indicated that EGFR autocrine signaling is important for these waves, this study goes further in comparing the roles of these ligands using knockouts to unambiguously establish the autocrine factors involved. Others who use this common experimental system (MDCK) to study epithelial dynamics will find this study of great interest. A wider audience of those who work on EGFR-mediated signaling will also find the data quite fascinating as an example of the complex relationship between ERK activation and its downstream effects. The technical excellence of the paper will make it a must-read for those in these fields. However, there are some factors that limit the scope of the significance. MDCK cells are an important experimental model system but differ in substantial ways from other epithelial cells, particularly in the expression of EGFR ligands. Because different ligands such as amphiregulin dominate in other systems (as noted by the authors, and PMID 27405981), the ability to extrapolate from these findings to other cell types is somewhat limited. Also, the paper avoids addressing the major question of how ERK waves relate to collective migration rate. From the data presented it is clear that this relationship is complex; for example, bath application of the ligands restores a high migration rate but not ERK waves. Given this lack of a clear relationship it is an understandable decision to leave this question for future work; however this does limit the conclusions that can be drawn from the study.

We completely agree with the reviewer’s view. It is uncertain to what extent the observation with MDCK cells can be generalized to other cell types. We also admit that the conclusion is not very simple because EGFR signaling is required for various cellular functions including cell survival and migration. Even though the gene editing becomes so easy, it is still labor consuming work to knock out many genes in a single cell line with extensive characterization. We believe the data shown in our work will provide a basis for the understanding of EGFR ligands.

Reviewer #1

For Fig 1F, 3 individual experiments should be conducted to confirm results.

We will follow the reviewer’s suggestion and repeat the experiment.

For Fig 1G, could the authors please show the original western blot data in full rather than just the densitometry graphs?

We did not show just for the sake of brevity. We are happy to will include the images as a supplementary data.

The authors should explain the origin/phenotype of MDCK cells for those who are not familiar with the cell line.

We will modify the text according to the reviewer’s suggestion.

The authors should give a future outlook/direction for future experimentation to further confirm redundancy in EGF ligands in the propagation of ERK activation waves.

We will discuss on the redundancy in other cell types based on available NGS data.

Some mention of the use of biosensors in the abstract and introduction is recommended as this is a major part of the experimental work.

We will refer to the biosensors in the abstract and introduction.

Reviewer #2

There are conflicts with some of the conclusions made about ligands. dEGFR cells have basal ERK activity as high as WT which argues against EGF being responsible for basal ERK activity. Further, basal ERK activity was not rescued by restoration of EGF in the 4KO-EGF cells. The authors should address this discrepancy.

We agree that some new questions have arisen from our observations. The discrepancy of the phenotypes between dEGFR cells and dEGF cells is an example. We are currently establishing dEGF cell lines, in which different genomic sequences of the EGF gene were targeted. We have already started to develop these cell lines and will obtain them within a month. The result will provide some clues to answer the questions. However, even if we could not solve the question, we believe, it is worth reporting observations that could not be easily understood, because such questions are often leading to another discovery.

Besides the ones genetically disrupted in this work, other EGFR ligands seem to play functional roles given that dEGFR cells less migration and fewer ERK waves than 4KO cells. The authors could test if other ligands are upregulated in 4KO cells to compensate. On a similar note determining whether ADAM17 deficient cells are more similar to 4KO cells or dEGFR cells could provide some insight.

According to the reviewer’s suggestion, we will conduct qPCR of growth factors in mutant cell lines to see the expression levels of seven EGFR ligands might have changed significantly. At the same time, as the reviewer suggested, we will establish ADAM17 knockout cell lines and compare the phenotype with those of cell lines deficient from EGFR ligand genes.

• The authors propose that Nrg1 is responsible for ERK waves in QKO, 4KO, dEGFR, and 4KO-EGF cells but are limited in testing this due to Nrg1 being essential in 4KO cells. First, Nrg1 should have been deleted in TKO cells to confirm that it is only essential in the absence of the four EGFR ligands. Additionally, Nrg1 could be knocked out in 4KO-EGF cells to demonstrate the claim that EGF-induced ADAM17 cleavage of Nrg1 is responsible for ERK waves.*

We do not think the deletion of Nrg1 in the TKO cells will abolish the ERK activation waves because EREG in TKO cells could transmit the waves. To overcome the problem of cell growth, we will try to obtain 5KO cells by Cre-induced deletion of NRG1 in 5KO-loxP-NRG1 cells, wherein EGF is supplied exogenously. We already had preliminary data suggesting that co-culture with wild type MDCK cells helps 5KO cells grow.

The authors state that ERK activation waves are important for collective migration and seek to understand the roles of each EGFR ligand, but despite measuring migration and properties of ERK activity, there is very little analysis or commentary on the relationship between the two. The ability of HB-EGF to restore migration without ERK waves suggests that waves are not required per se. It is interesting to note that with restoration of ligands, migration is higher than WT but ERK activity is lower.

We refrained from spending much space about the essential role of ERK activation waves in collective cell migration, because several papers have already described this issue.

Probably, we should have spent more space to emphasize that the collective cell migration is comprised of at least two different phenomena. The migration of leader cells and the follower cells. The ERK activation waves are essential for the follower cells but not the leader cells. In 4KO cells, both the leader cell and follower cell migrations are impaired. We showed that GFs expression restore the leader cell migration, but not the follower cells. We will revise the text to include this issue.

It is suggested that the total amount of EGFR ligands may be the primary determinant of migration, but deletion of TGFα alone causes a significant decrease in migration comparable to the DKO cells. TGFα has the lowest expression of the four ligands studied but is the only ligand to have a significant impact on migration in the single knockout context, which disagrees with that conclusion.

Each EGFR ligand has different affinity to EGFR, which makes it difficult to link the mRNA levels directly to the effect of each EGFR ligand. We will modify the discussion to include this argument.

Other:

Fig. S3B needs clarification that the WT (black) and 4KO (green) did not receive a stimulus.

We will follow the reviewer’s advice.

Reviewer #3:

The experiments in Fig. 5 are undertaken with the purpose of assessing whether NRG acts as an additional ligand that mediates the residual ERK waves in 4KO/QKO cells. However, this question is never addressed in the NRG/4KO cells. While it might be challenging due to the proliferative defect, it seems important to attempt this experiment in some way; measuring the ERK waves for these cells would establish whether all of the critical autocrine factors have been identified. Can the proliferation be rescued by application of high amounts of growth factors?

This question is similar to a question raised by reviewer #2.

To overcome the problem of cell growth, we will try to obtain 5KO cells by Cre-induced deletion of NRG1 in 5KO-loxP-NRG1 cells, wherein EGF is supplied exogenously.

The bath exposure to EGFR ligands shown in Fig. S3A is an important experiment, but it is surprising that ERK signaling is not maintained under these conditions. Is this due to depletion of the added ligands, perhaps locally? Or is the intermittent nature of paracrine signaling needed to maintain ERK activity? These possibilities could be distinguished by checking whether the added EGF or the other ligands are depleted after several hours, or by restimulating with a new bolus of ligand after several hours.

We thank the reviewer for this invaluable suggestion. We will conduct the experiments suggested by the reviewer.

The connection between ERK activity and migration is somewhat confusing. It would be helpful to show the dose sensitivity of migration to a MEK or ERK inhibitor. Are other pathways downstream of EGFR such as PI3K involved in the autocrine-mediated migration? This could also be established with the appropriate inhibitors.

We should have spent more space to emphasize that the collective cell migration is comprised of at least two different phenomena. The migration of leader cells and the follower cells. The ERK activation waves are essential for the follower cells but not the leader cells. In 4KO cells, both the leader cell and follower cell migrations are impaired. We showed that GFs expression restore the leader cell migration, but not the follower cells. We will emphasize this issue in the revised manuscript.

Reviewer #1:

Line 47 in Abstract should read "Aiming for" not "Aiming at".

We have corrected the mistake as suggested.

Some in the field call fluorescence lifetime microscopy "FLIM", you could adopt the same wording in your manuscript to attract more readers.

We have included FLIM according to the reviewer’s suggestion.

Reviewer #1 :

Figure 1D, the images should be presented using the same scale for both the EKAREV and EKARrEV constructs so that they can be directly compared.

Because the basal FRET/CFP ratio is significantly different between EKAREV-NLS and EKARrEV-NLS, the changes during mitosis become unclear if we applied the same scale. This figure is prepared to show the reactivity to Cdk1 during mitosis; therefore, we believe the current scale is better for presentation.

The names QKO and 4KO are a bit confusing. Could the authors please change the naming of the knockout cells so that readers understand that QKO and 4KO are two separate cell types? Perhaps instead of 4KO use FKO for "full knockout" or something similar. The 5KO line might also need to be named something else if you change to FKO.

We have discussed this issue with the co-authors, but could not reach a better idea. Instead of changing the names, we will include a detailed explanation for each cell line.

Reviewer #2:

The interpretation of the RA-SOS coculture experiments is confusing. Based on the author's reasoning, I would expect ADAM17 shedding in the RA-SOS cells to trigger signaling at the interface of both WT and 4KO cells but the 4KO should be unable to propagate the wave farther away from the interface. This does not seem to be the case. Do RA-SOS ADAM17KO cells still trigger waves of ERK signaling in the WT cells? Do ADAM17KO cells behave as the 4KO cells in this coculture system?

Probably, the reviewer misunderstood the method. The GF-less 4KO cells were co-cultured with wild type cells harboring the RA-SOS system. We will describe more in detail to avoid misunderstanding.

Finally, the growth curve in Fig. 5B indicates that 5KO-loxP-NRG1-CreERT2 cells are viable for about two days after Cre induction. The authors could perform a confinement release assay of these cells 1-1.5 days after Cre induction to look for further reduction of ERK waves and migration to demonstrate the role of Nrg1.

This experiment may not be necessary. It is clear that NRG1 is required for the survival of 4KO cells. The reason why cells are still alive 1 to 2 days after 4-OHT application is simply because NRG1 protein is remaining. The interpretation of the results would be difficult during the phase of NRG1 reduction.

In Fig. 1G, the normalization of all WT pERK samples to 1 artificially lowers the variance to zero when performing the T-test.

For the comparison of immunoblotting data derived from independent experiments, the signals must be normalized to the control. We believe the use of pERK/ERK of the wild type cells as the control is reasonable for this experiment.

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Referee #3

Evidence, reproducibility and clarity

This manuscript seeks to clarify the mechanisms that underlie traveling "waves" of ERK activity that occur in monolayers of migrating epithelial cells. A combination of live cell imaging with ERK activity biosensors and CRISPR-mediated knockouts for autocrine regulators are used to dissect the factors that make these waves possible. The authors utilize the MDCK cell line, which shows very prominent wave behavior, and they perform an impressive number of knockouts to eliminate the most abundant autocrine EGFR ligands. They also introduce a novel ERK FRET reporter, which is less sensitive to off-target phosphorylation by Cdk1. Analysis of ERK biosensor data from the knockouts shows that knockout of all four main EGFR ligands is needed to substantially reduce the amplitude of ERK waves, although it does not completely eliminate it. Re-expression of any of the four ligands, with the exception of HBEGF, restores strong ERK waves. Application of the same ligands in solution restores migration but not the ERK waves.

Overall, this study is carried out with a high degree of rigor and technical excellence, with clear reporting of experimental details and replication. The writing and figures are very clear, and there are no obvious technical problems. However, there are some areas in which the strength and clarity of the conclusions could be strengthened by relatively simple experiments.

Major:

1. The experiments in Fig. 5 are undertaken with the purpose of assessing whether NRG acts as an additional ligand that mediates the residual ERK waves in 4KO/QKO cells. However, this question is never addressed in the NRG/4KO cells. While it might be challenging due to the proliferative defect, it seems important to attempt this experiment in some way; measuring the ERK waves for these cells would establish whether all of the critical autocrine factors have been identified. Can the proliferation be rescued by application of high amounts of growth factors?
2. The bath exposure to EGFR ligands shown in Fig. S3A is an important experiment, but it is surprising that ERK signaling is not maintained under these conditions. Is this due to depletion of the added ligands, perhaps locally? Or is the intermittent nature of paracrine signaling needed to maintain ERK activity? These possibilities could be distinguished by checking whether the added EGF or the other ligands are depleted after several hours, or by restimulating with a new bolus of ligand after several hours.

Minor (I think this is an important point overall, but it is outside of the scope of the paper as defined by the authors, which is focused on the ERK waves rather than how the waves relate to migration):

1. The connection between ERK activity and migration is somewhat confusing. It would be helpful to show the dose sensitivity of migration to a MEK or ERK inhibitor. Are other pathways downstream of EGFR such as PI3K involved in the autocrine-mediated migration? This could also be established with the appropriate inhibitors.

Significance

This study definitively establishes the role of 4 EGFR ligands in the generation of ERK activity waves in MDCK cells. While other studies, including some from the senior author's lab, have strongly indicated that EGFR autocrine signaling is important for these waves, this study goes further in comparing the roles of these ligands using knockouts to unambiguously establish the autocrine factors involved. Others who use this common experimental system (MDCK) to study epithelial dynamics will find this study of great interest. A wider audience of those who work on EGFR-mediated signaling will also find the data quite fascinating as an example of the complex relationship between ERK activation and its downstream effects. The technical excellence of the paper will make it a must-read for those in these fields. However, there are some factors that limit the scope of the significance. MDCK cells are an important experimental model system but differ in substantial ways from other epithelial cells, particularly in the expression of EGFR ligands. Because different ligands such as amphiregulin dominate in other systems (as noted by the authors, and PMID 27405981), the ability to extrapolate from these findings to other cell types is somewhat limited. Also, the paper avoids addressing the major question of how ERK waves relate to collective migration rate. From the data presented it is clear that this relationship is complex; for example, bath application of the ligands restores a high migration rate but not ERK waves. Given this lack of a clear relationship it is an understandable decision to leave this question for future work; however this does limit the conclusions that can be drawn from the study.

Areas of expertise: growth factor signal transduction, biosensors, quantitative modeling

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Referee #2

Evidence, reproducibility and clarity

Lin et al. address the mechanisms underlying ERK signaling waves in epithelial cells. While it is known that ADAM17 is critical to process EGFR ligands, the specific or redundant roles of different ligands remains an open question. First the authors generate a modified ERK FRET sensor with reduced cross-reactivity to CDK1 in MDCK cells and systematically knockout EGF, HBEGF, TGF⍺ and EREG (the highest expressed ligands in MDCK cells). The authors use live cell imaging of ERK activity upon release from confinement and find that all ligands contribute to ERK signaling waves. While differences in basal signaling and other dynamic features are found in individual knockouts, only the quadruple KO cells show a significant decrease in ERK waves. To determine if the 4KO cells are defective in wave propagation (as opposed to wave initiation), the authors coculture 4KO cells with an inducible cell line and conclude that 4KO cells are unable to propagate waves. Individual EGFR ligands are then restored in 4KO cells, and EGF, TGFα, and EREG, but not HBEGF, can rescue ERK activity waves. Finally, the authors attempt to eliminate all ERK activation waves by deletion of Nrg1 but find that it is essential in 4KO cells. The paper is well-written and technically sound. The use of genetics is particularly impressive but the lack of major discoveries dampens the enthusiasm. Additional efforts to mechanistically define wave initiation and wave propagation would significantly improve the impact of the manuscript. Moreover, some of the conclusions are not fully supported by the data and require further experimentation and/or analysis.

1. There are conflicts with some of the conclusions made about ligands. dEGFR cells have basal ERK activity as high as WT which argues against EGF being responsible for basal ERK activity. Further, basal ERK activity was not rescued by restoration of EGF in the 4KO-EGF cells. The authors should address this discrepancy.
2. Besides the ones genetically disrupted in this work, other EGFR ligands seem to play functional roles given that dEGFR cells less migration and fewer ERK waves than 4KO cells. The authors could test if other ligands are upregulated in 4KO cells to compensate. On a similar note determining whether ADAM17 deficient cells are more similar to 4KO cells or dEGFR cells could provide some insight.
3. The interpretation of the RA-SOS coculture experiments is confusing. Based on the author's reasoning, I would expect ADAM17 shedding in the RA-SOS cells to trigger signaling at the interface of both WT and 4KO cells but the 4KO should be unable to propagate the wave farther away from the interface. This does not seem to be the case. Do RA-SOS ADAM17KO cells still trigger waves of ERK signaling in the WT cells? Do ADAM17KO cells behave as the 4KO cells in this coculture system?
4. The authors propose that Nrg1 is responsible for ERK waves in QKO, 4KO, dEGFR, and 4KO-EGF cells but are limited in testing this due to Nrg1 being essential in 4KO cells. First, Nrg1 should have been deleted in TKO cells to confirm that it is only essential in the absence of the four EGFR ligands. Additionally, Nrg1 could be knocked out in 4KO-EGF cells to demonstrate the claim that EGF-induced ADAM17 cleavage of Nrg1 is responsible for ERK waves. Finally, the growth curve in Fig. 5B indicates that 5KO-loxP-NRG1-CreERT2 cells are viable for about two days after Cre induction. The authors could perform a confinement release assay of these cells 1-1.5 days after Cre induction to look for further reduction of ERK waves and migration to demonstrate the role of Nrg1.
5. The authors state that ERK activation waves are important for collective migration and seek to understand the roles of each EGFR ligand, but despite measuring migration and properties of ERK activity, there is very little analysis or commentary on the relationship between the two. The ability of HB-EGF to restore migration without ERK waves suggests that waves are not required per se. It is interesting to note that with restoration of ligands, migration is higher than WT but ERK activity is lower.
6. It is suggested that the total amount of EGFR ligands may be the primary determinant of migration, but deletion of TGFα alone causes a significant decrease in migration comparable to the DKO cells. TGFα has the lowest expression of the four ligands studied but is the only ligand to have a significant impact on migration in the single knockout context, which disagrees with that conclusion. Other:
7. In Fig. 1G, the normalization of all WT pERK samples to 1 artificially lowers the variance to zero when performing the T-test.
8. Fig. S3B needs clarification that the WT (black) and 4KO (green) did not receive a stimulus.

Significance

While it is known that ADAM17 is critical to process EGFR ligands, the specific or redundant roles of different ligands remains an open question. The authors find that all ADAM17 ligands contribute to ERK signaling waves but may have specific contributions to other phenotypes. This work would be of interest to the signaling dynamics, epithelial and developmental biology communities.

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Referee #1

Evidence, reproducibility and clarity

see below for comments.

Significance

Overall, this manuscript is very clear and easy to follow. The manuscript could be improved by making the following changes:

• Line 47 in Abstract should read "Aiming for" not "Aiming at".
• Some mention of the use of biosensors in the abstract and introduction is recommended as this is a major part of the experimental work.
• The names QKO and 4KO are a bit confusing. Could the authors please change the naming of the knockout cells so that readers understand that QKO and 4KO are two separate cell types? Perhaps instead of 4KO use FKO for "full knockout" or something similar. The 5KO line might also need to be named something else if you change to FKO.
• Figure 1D, the images should be presented using the same scale for both the EKAREV and EKARrEV constructs so that they can be directly compared.
• Some in the field call fluorescence lifetime microscopy "FLIM", you could adopt the same wording in your manuscript to attract more readers.
• For Fig 1F, 3 individual experiments should be conducted to confirm results.
• For Fig 1G, could the authors please show the original western blot data in full rather than just the densitometry graphs?
• The authors should explain the origin/phenotype of MDCK cells for those who are not familiar with the cell line.
• The authors should give a future outlook/direction for future experimentation to further confirm redundancy in EGF ligands in the propagation of ERK activation waves.

What do you think about this?

"Symmathesy (Noun): An entity composed by contextual mutual learning through interaction. This process of interaction and mutual learning takes place in living entities at larger or smaller scales of symmathesy.

Symmathesy (Verb): to interact within multiple variables to produce a mutual learning context." (https://norabateson.wordpress.com/2015/11/03/symmathesy-a-word-in-progress/)

Is this change related to the general pressure on the welfare state caused by the 2008 financial crash and the 2020 pandemic?

x

It's fascinating how thinking about structure and history motivates questions that unlock deeply meaningful information and conversations.

Author Response:

Reviewer #1 (Public Review):

I think that it is important for the authors to consider that for most (if not all) SARS-CoV-2 variants, increased transmissibility of the virus has not been directly demonstrated. While it is clear that numerous variants have emerged and will continue to emerge, the rapid upsurge of cases with a variant may be related to many factors (e.g. host susceptibility due to immunity or genetic factors, virus seeding events, predominant replication in particular age cohorts, ...) that cannot simply be captured as "transmissibility of the virus". Even for B.1.1.7 and D614G mutants, the direct evidence of increased transmissibility in humans is extremely limited if available at all. Most studies erroneously simply take the increasing occurrence of particular lineages or mutations in sequence databases as a measure of increased "transmissibility", which should be avoided, also in the present manuscript. Increased transmissibility can only be derived from field studies where transmission is measured directly.

We thank the reviewer for pointing out that this is a controversial area. We have adjusted the text throughout to accommodate the fact that the published evidence of increased transmissibility/infectivity is not definitive.

On several occasions in the manuscript (e.g. page 3, page 4 L58-59, page 9 in submitted version), the authors seem to suggest that changes that lead to increased "transmission" or binding affinity and changes that lead to immune escape are mutually exclusive. But the opposite might be true. Viruses may escape from antibody-mediated immunity by amino acid substitutions in linear or structural antibody-binding epitopes. However, viruses may also escape from antibody-mediated immunity through altered protein density on virion surfaces (e.g. less Spike) and/or altered affinity, making it harder for antibody to inhibit virus attachment. As an example, increased affinity may facilitate virus replication with less dense Spike protein, allowing more effective antibody escape. Lower affinity but more dense coverage of Spike may reduce accessibility of critical virus parts by antibodies. Several viruses are known to escape from antibody-mediated neutralization through changes in affinity/avidity.

We agree with this point and have modified the text to avoid implying that increased transmissibility and antibody escape are mutually exclusive.

In relation to the previous point, it is important that authors mention some limitations of the present work in the discussion. SARS-CoV-2 virion attachment to cells is not just a matter of spike protein binding and certainly not of a monomeric RBD. Escape from antibodies and effects on affinity are heavily influenced by the entire (trimeric) spike protein, including its N-terminal domains. Such components are not taken into account in the present experimental designs, and this should be discussed, as e.g. the NTD can be important in attachment and antibody-mediated neutralization.

We thank the reviewer for this suggestion. We have added an appropriate caveat to the Discussion.

The authors suggest that the pandemic virus as it spread across the globe initially did not have "optimized" affinity. However, in the first months of the pandemic, there was relatively limited variation in spike protein sequences. The major variants emerged only later and mostly in areas where population immunity was building up. Again, this begs the question whether natural selection is occurring as a consequence of receptor affinity or immune escape?

We thank the reviewer for making this point. However, we do not think it is that surprising that it took a few months for the first Spike variants to be detected, for the following reasons. Firstly, the number of infections would have been relatively low early in the pandemic and SARS-CoV-2 replicates with a comparatively low error rate for an RNA virus. Secondly, the introduction of strict non-pharmacological measures (social-distancing etc), which would have increased the selective pressure on the virus, was somewhat delayed. Thirdly, it would take some time for any variant that emerged by chance to expand sufficiently to be detected by sequencing. While there is evidence suggestive of broader immunity in populations were the Beta and Gamma variants emerged, which we cite, we are not aware of evidence of widespread immunity in populations where the D614G, S477N and Alpha variants first emerged.

Reviewer #2 (Public Review):

Barton and colleagues investigated the effect of common SARS-CoV-2 RBD mutations and two ACE2 mutations on the RBD/ACE2 interaction. They concluded that the N501Y, E484K and S477N increased receptor binding while the K417N/T had the opposite effect. Double and triple mutants were also included. The ACE2 mutations (that are rare in the human population) also increased binding to most RBD mutants. The study is well-performed and written clearly.

The primary conclusions of the manuscript were supported by the results. However, the interpretation was too speculative. In the abstract (lines 14-17), the authors suggest that the 501 and 477 mutations enhance transmission solely based on data on the RBD-ACE2 interaction. It is unknown whether increased affinity to ACE2 is beneficial for transmission. In addition, increased RBD affinity to ACE2 does not mean that the whole spike or virus particle also binds stronger to ACE2. Lastly, increasing ACE2 affinity does not necessarily increase binding to cells (for example S1A binding to sugars or spike abundance can also influence this).

We agree that it would be inappropriate to assume, based on our affinity/kinetic studies alone, that 501 and 477 enhance transmission. That is why the relevant sentence in the abstract starts with the phrase, “Taken together with other studies”. We summarises the evidence from these other studies in the Discussion. We acknowledge that we have not examined the effects of the mutations on binding of the whole Spike protein to ACE2 or viruses to cells, and have added a suitable caveats to the Discussion.

The overall impact on the field will be limited as there is substantial overlap with already published studies. The observation that the N501Y and E484K increase receptor binding while the K417N/T mutations decrease binding was already made prior by Laffeber et al (2021; J Mol Biol). Laffeber et al also investigated double and triple mutants and came to similar conclusions. Liu et al (2021) confirmed that the N501Y increases binding whereas the K417N/T have opposing effects (Liu et al., 2021 mAbs). The observation that the Y501N increases ACE2 affinity has been made by several groups (e.g. Liu et al 2021 Cell research; Starr et al 2020 Cell).

We thank the reviewer for highlighting these addition studies, two of which are very recent. We have now cited these studies.

Starr et all 2020 was a high throughput study in which the affinity measurements were semi-quantitative, and no kinetic analysis was performed. Liu et al (2021) and Laffeber et al (2021) were performed at 25 C and without rigorous controls for mass-transport and protein aggregation. Liu et al (2021) did not report kinetic measurements. Their results are broadly consistent with ours but their affinity and kinetic measurments are ~ 10 fold different. While we accept that some of the measurements of the effects of mutations have been made before, our measurements of affinity and especially kinetics are performed more rigorously than in previous studies and, for the first time, at a physiological temperature (37 C). Thus, the affinity and kinetic data that we have obtained for single and combinations variants are more definitive. As noted in our Discussion there is a wide variation in reported binding affinities and kinetics in previously published studies. We think the comprehensive data that we report here, the same robust method to measure binding properties of all these variants, adds significant value.

Reviewer #3 (Public Review):

[...] 1) The ACE2 receptor exists naturally as a dimeric form and the RBD is a component of the SARS-CoV-2 spike trimer. The assay format here was monomeric RBD binding against monomeric ACE2 throughout this study. While the measurements are indeed carefully executed and under more physiological conditions than many other reported studies, the authors should discuss potential avidity effects, the consequences of mutations on the accessibility of the RBD in VOC versus wildtype, and impact of other domains such as the NTD, in the context of their monomeric ACE2 measurements with isolated RBD here.

We thank the reviewer for raising this issue. We have added a section to the Discussion addressing these important points.

2) As shown in Figure S2, RBD WT, K417N, K417T, KN/EK, KT/EK, and S477N, the ~30kDa monomeric proteins were flanked by additional ~60kDa bands (which correspond to the smaller peaks to the left of the main peaks) some of which bleed through to the main fraction to different extents, whereas RBDs SA, UK1, UK2, BR, and E484K, do not seem to have as much or any of these extra species. Can the authors comment on whether these contaminants are RBD-dimers as observed before (Dai et al. 2020)? If yes, would such dimers affect the affinity and kinetics?

We thank the reviewer for pointing out these larger ~60 kDa bands in some RBD preps. We think that it is unlikely that these are RBD dimers as these are reducing gels. The strictly monophasic kinetics of all RBD preps, also argues against this being an RBD dimer. We have confirmed by densitometry that the larger band comprises less that 5% of the protein in all the preparations. This will have only a minor effect on estimated of RBD concentration. We have added this information to the Figure S2 legend.

Evaluation Summary:

This manuscript is of interest to virologists working on SARS-CoV-2, as well as biochemists and biophysicists who perform binding experiments with surface plasmon resonance (SPR), as it provides detailed affinity and kinetics analysis of the effect of mutations in variants of concern in the SARS-CoV-2 receptor binding domain with receptor ACE2 and two 'common' mutations in ACE2.

(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewer #1 (Public Review):

I think that it is important for the authors to consider that for most (if not all) SARS-CoV-2 variants, increased transmissibility of the virus has not been directly demonstrated. While it is clear that numerous variants have emerged and will continue to emerge, the rapid upsurge of cases with a variant may be related to many factors (e.g. host susceptibility due to immunity or genetic factors, virus seeding events, predominant replication in particular age cohorts, ...) that cannot simply be captured as "transmissibility of the virus". Even for B.1.1.7 and D614G mutants, the direct evidence of increased transmissibility in humans is extremely limited if available at all. Most studies erroneously simply take the increasing occurrence of particular lineages or mutations in sequence databases as a measure of increased "transmissibility", which should be avoided, also in the present manuscript. Increased transmissibility can only be derived from field studies where transmission is measured directly.

On several occasions in the manuscript (e.g. page 3, page 4 L58-59, page 9 in submitted version), the authors seem to suggest that changes that lead to increased "transmission" or binding affinity and changes that lead to immune escape are mutually exclusive. But the opposite might be true. Viruses may escape from antibody-mediated immunity by amino acid substitutions in linear or structural antibody-binding epitopes. However, viruses may also escape from antibody-mediated immunity through altered protein density on virion surfaces (e.g. less Spike) and/or altered affinity, making it harder for antibody to inhibit virus attachment. As an example, increased affinity may facilitate virus replication with less dense Spike protein, allowing more effective antibody escape. Lower affinity but more dense coverage of Spike may reduce accessibility of critical virus parts by antibodies. Several viruses are known to escape from antibody-mediated neutralization through changes in affinity/avidity.

In relation to the previous point, it is important that authors mention some limitations of the present work in the discussion. SARS-CoV-2 virion attachment to cells is not just a matter of spike protein binding and certainly not of a monomeric RBD. Escape from antibodies and effects on affinity are heavily influenced by the entire (trimeric) spike protein, including its N-terminal domains. Such components are not taken into account in the present experimental designs, and this should be discussed, as e.g. the NTD can be important in attachment and antibody-mediated neutralization.

The authors suggest that the pandemic virus as it spread across the globe initially did not have "optimized" affinity. However, in the first months of the pandemic, there was relatively limited variation in spike protein sequences. The major variants emerged only later and mostly in areas where population immunity was building up. Again, this begs the question whether natural selection is occurring as a consequence of receptor affinity or immune escape?

Reviewer #2 (Public Review):

Barton and colleagues investigated the effect of common SARS-CoV-2 RBD mutations and two ACE2 mutations on the RBD/ACE2 interaction. They concluded that the N501Y, E484K and S477N increased receptor binding while the K417N/T had the opposite effect. Double and triple mutants were also included. The ACE2 mutations (that are rare in the human population) also increased binding to most RBD mutants. The study is well-performed and written clearly.

The primary conclusions of the manuscript were supported by the results. However, the interpretation was too speculative. In the abstract (lines 14-17), the authors suggest that the 501 and 477 mutations enhance transmission solely based on data on the RBD-ACE2 interaction. It is unknown whether increased affinity to ACE2 is beneficial for transmission. In addition, increased RBD affinity to ACE2 does not mean that the whole spike or virus particle also binds stronger to ACE2. Lastly, increasing ACE2 affinity does not necessarily increase binding to cells (for example S1A binding to sugars or spike abundance can also influence this).

The overall impact on the field will be limited as there is substantial overlap with already published studies. The observation that the N501Y and E484K increase receptor binding while the K417N/T mutations decrease binding was already made prior by Laffeber et al (2021; J Mol Biol). Laffeber et al also investigated double and triple mutants and came to similar conclusions. Liu et al (2021) confirmed that the N501Y increases binding whereas the K417N/T have opposing effects (Liu et al., 2021 mAbs). The observation that the Y501N increases ACE2 affinity has been made by several groups (e.g. Liu et al 2021 Cell research; Starr et al 2020 Cell)

The S477N and ACE2 mutations on the ACE2-RBD interaction were not investigated prior. In addition, the authors indicate correctly that they performed the SPR experiments at 37 degrees Celsius, whereas others did SPR experiments at room temperature.

Reviewer #3 (Public Review):

Barton et al. performed detailed measurements and analysis of the binding of the SARS-CoV-2 receptor-binding domain (RBD) and mutations in currently circulating variants of concern (VOC) against the human receptor ACE2 using SPR. K417N/T that occurs in VOCs B.1.351 and P.1 was shown to decrease binding to ACE2, where N501Y (found in B.1.351, P.1, and B.1.1.7) increased binding. S477N and E484K exhibited more modest effects on binding to ACE2. The gain of binding by N501Y and E484K was found to make up for loss of binding caused by K417N/T in B.1.351 and P.1, respectively. Some of these effects have been noted in other publications. The authors also showed that two natural variants of human ACE2 (S19P and K26R), which are found in samples in the gnomAD database (0.4% and 0.03% respectively), also affected bind to SARS-CoV-2 RBDs. The authors then discussed possible causes of the variations of the relatively wide range of affinity values cited in the literature, including measurement at non-physiological temperature, mass-transport limitations and rebinding, and protein aggregation. These are all good points that should be taking into account in assessing absolute versus relative binding. The strengths of this paper are the comprehensive and careful analyses of wildtype and mutant SARS-CoV-2 RBD and ACE2 in one study. Points to be further considered include:

1) The ACE2 receptor exists naturally as a dimeric form and the RBD is a component of the SARS-CoV-2 spike trimer. The assay format here was monomeric RBD binding against monomeric ACE2 throughout this study. While the measurements are indeed carefully executed and under more physiological conditions than many other reported studies, the authors should discuss potential avidity effects, the consequences of mutations on the accessibility of the RBD in VOC versus wildtype, and impact of other domains such as the NTD, in the context of their monomeric ACE2 measurements with isolated RBD here.

2) As shown in Figure S2, RBD WT, K417N, K417T, KN/EK, KT/EK, and S477N, the ~30kDa monomeric proteins were flanked by additional ~60kDa bands (which correspond to the smaller peaks to the left of the main peaks) some of which bleed through to the main fraction to different extents, whereas RBDs SA, UK1, UK2, BR, and E484K, do not seem to have as much or any of these extra species. Can the authors comment on whether these contaminants are RBD-dimers as observed before (Dai et al. 2020)? If yes, would such dimers affect the affinity and kinetics?

Reference:

Dai, Lianpan, et al. (2020). A universal design of betacoronavirus vaccines against COVID-19, MERS, and SARS. Cell 182: 722-733.e11.

2017年，Schweder和Shelley决定在“The Newcomers”这个作品里，尝试在不接触地面的情况下，穿过纽约市中心的曼哈顿广场：他们邀请了另外两位搭档一起，一起搭建一个可移动的“营地”，然后进行这次为期10天的旅行。白天，艺术家们用营地材料搭建成可以前进的桥梁，到了晚上则重建房屋以供休息。他们在人流量密集的城市中缓慢前进，同时将自己的生活暴露在所有路人面前，同时与源源不断的访客聊天对话。

2014年，他们带来了“社会关系建筑”系列的另一件作品“In Orbit”，这次，两个人把居住空间搬到了一个仿佛仓鼠跑轮的巨型轮状结构里。轮状轨道内侧附有6个生活站点，包括床、桌椅和柜子等等，轮子外部也有对应的设置，其中一个人住在轮子的顶部，另一个人则住在轮子里面，想完成日常生活，两个人就必须保持密切的配合和协助，以此类推，持续10天。

“ReActor”的本体是一个微型长廊式建筑，长15米，依靠高5米的混凝土立柱保持稳定。当风吹过时，它会像风向标一样旋转，一旦居住者在里面走动，它就会开始倾斜。

这间酷似长方形盒子的“小屋”，建在纽约城里的Art Omi艺术中心里的一座小山上，在表演的过程中，两位艺术家会时不时跟经过的游客聊聊它是如何建造的，以及做这件作品的意义。他俩说，这些对话在他们之前的作品的讨论中也经常出现，但在那次，有一个问题发生了变化：大家的疑惑从“你们怎么可能住在那里？”变成了“我们什么时候也能搬进去？”

2009年，Schweder和Shelley又基于二人之前探索的共居模式创作了另一个表演“Stability”，这也是他们的系列创作“社会关系建筑”（social relationship architecture）的第一件作品。

顾名思义，“Stability”是一个可活动的结构，它可以像跷跷板一样移动。在无人居住时它是水平静止的，但当居住在其中的人们四处活动时，它的平衡也会被随之打破，很像我们生活中会看到的跷跷板。

看起来是一个超高难度的生活实验，但是Schweder和Shelley竟然一起在这里生活了一周。为了处于一个相对稳定环境中，他们必须协调彼此的动作，而这又会影响到他们自己在其中的日常生活

来自纽约的艺术家Alex Schweder和Ward Shelley，两位艺术家的第一个作品“Flatland”，是在纽约Sculpture Center 的一个长期表演，“旨在讨论人与建筑之间的主客体关系”。Schweder和Shelley与其他4位参与者，生活在一个狭窄到只有一人宽的空间里，其他人可以透过一层玻璃，直接看到几位实践者的生活状态。

两位艺术家为这次表演制定的规则是，如果中途因为任何原因离开了这间玻璃屋，就不能再回来，在此基础上，他们一起建立起一个为期 3 周的临时迷你社区，希望能用这个表演引发人们对自己生活的思考。

Schweder对建筑与行为表演之间的关系很感兴趣，在他看来，建筑是一种“基于时间的事物”，从我们使用建筑空间开始，它就会随着时间而改变。如果我们人为加快这种原本比较缓慢的变化速度，它或许就会成为可以被明确的一种行为表演。

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Reply to the reviewers

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

**Summary:**

Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Please place your comments about significance in section 2.

In this paper the authors used a targeted approach to identify rare mutations in a cohort of glioma patients. Using this approach they identified a recurrent mutation in the TOP2A gene encoding for Topoisomerase 2A, and suggest that this mutation creates a more effective protein, binding DNA strongly and maybe more enzymatically active. RNAseq analysis of TOP2A WT and TOP2A mut tumor samples suggest different transcription patterns and points to possible splicing defects. The most recurrent variant (E9448Q) is described in depth and some experimental information shows this variant might be a gain-of-function mutation.

**Major comments:**

• Are the key conclusions convincing? The validation of both the methodology and the presence of never described TOP2A variations in HGG is done quite successfully. Interesting evidence about relevance of the most frequent mutation is provided. However, besides having computational and biochemistry assays performed, lack of details about in vitro experiment statistics (no p-values are provided in figures 4 and 5, neither sample size, repetitions) weakens the conclusions claimed by the authors about the properties of the mutated topoisomerase. Ad. In the revised version we provided more details about in vitro experiments, including statistics when is applicable, sample size and a number of repetitions. In the fig. 4 we show the results of two repetitions (so we can’t calculate statistics) but I would like to stress that we tested independently two fragments of the protein and the results were similar, so our conclusion was justified. However, we do agree with the reviewer that a statistical analysis of those biochemical tests is required. We already started to produce a new batch of recombinant proteins and we will add repetitions to reinforce our claims. We will provide statistical analysis details once all experiments are performed. __

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? Claims about E948Q variant function should be revised. Data is not presented in a convincing way, plus there is ambiguous language used from the results ("We conclude that the E9448Q TOP2A protein is functional, and MIGHT have a higher activity than the WT protein") to the rest of the paper where they strongly support the claims about the TOP2A activity. Ad. We will provide more data on biochemical features of the TOP2A variant to confirm the impact of the E948Q substitution on enzyme activities, which would allow more strong conclusions. This will present our results in more convincing way. A language of the manuscript has been critically revised and modified (see a version with tracked changes).

• Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. In line with the presented data in the paper, additional experiments that show catalytic changes of the E9448Q variation must be added. It is shown that there are differences in the DNA binding capacity by EMSA compared to the WT form, however, the DNA supercoil relaxation activities is not that different, at least the way the results are presented. The authors suggest that TOP2A mutation is a driver mutation but no validation in vitro of this claim is shown. Can this mutation alone or in combination with e.g. tumor suppressors transform normal cells to cancer cells? Do cell lines expressing this mutation (compared to parental TOP2A wt expressing cells) display increased transcription? Increased invasion? Ad. In the revised version we moderated our conclusions and we do not state that the mutated TOP2A is an oncogenic driver. We suggest this mutation (and possibly other TOP2A mutations, as we analyzed the impact of other variants on the TOP2A protein function) contribute to gliomagenesis. This conclusion is based not only on the changes in biochemical properties, but also on the observation of the impact of the mutation of transcription and patient survival. We expanded the analysis of TOP2A mutations and expression levels on TCGA datasets and those new results support our conclusions about a pathogenic nature of TOP2A overexpression and mutations (the supplementary fig.4). We believe in such situation, there is no rationale to make a classical oncogenic driver experiment.

Due to a rarity of the TOP2A mutations it is impossible to find a patient derived cell line with such defect. We attempted to overexpress TOP2A in glioma cells but apparently there is some autoregulation preventing overexpression of this protein is cells with endogenous TOP2A expression. Therefore, we can’t verify if cell lines expressing this variant (compared to parental TOP2A wt expressing cells) have increased transcription. Moreover, such experiments are costly and require more time investment for substantial experiments

I would like to stress that modeling some events in cell cultures is difficult and we found in GBMs the link between the mutated TOP2A and increased transcription along with decrease of splicing factors expression.

We have attempted to make CRISPR/Cas9 mediated knock-in in glioma cells but without success. This is a difficult and time consuming procedure. Although in principle, we agree on the rationale for such experiment, we think that the current data are consistent and convincing. If reviewers find it necessary we may attempt to create glioma cell lines with TOP2A knock-out and overexpression of the mutated TOP2A gene and study it functionally, but it would require more time.

• Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. If the authors can complement the already presented in vitro experiments with additional ones supporting their hypothesis, this should be feasible. The authors can use patient derived glioma cells or glioma cell lines manipulated to express either the parental TOP2A wt enzyme or the identified mutated form. __Ad. Due to a rarity of the TOP2A mutations it is impossible to find a patient derived cell line with such defect. Our findings partly relied on frozen historical samples, so it is not possible to develop patient-derived cell lines. As mentioned above, we can create a TOP2A knock-out cell line and overexpress a wild type or mutated version but there is no certainty that TOP2A deficient cells would survive (this is an essential enzyme) and such manipulation would be feasible.__

• Are the data and the methods presented in such a way that they can be reproduced? Yes, the authors provide a quite detailed explanation of the methods implemented to reach each one of the results they are presenting.

• Are the experiments adequately replicated and statistical analysis adequate? No, there is no information about the statistical analysis or number of replicates in any of the in vitro experiments performed. This information should be added to the manuscript.

Ad. In the revised version the requested information was added where was possible and additional repetitions for biochemical experiments are currently in progress.

**Minor comments:**

• Specific experimental issues that are easily addressable.
• Are prior studies referenced appropriately? Yes, authors clearly address the state of the art regarding previous NGS methodologies and let us know the advantages and novelty of their approach.

• Are the text and figures clear and accurate? There are some discrepancies between the strength of the language used in different sections of the paper to refer the conclusions they can infer from the results they are showing. While they are all valid, authors should revise it. Ad. The text of the manuscript has been unified and revised.

• Do you have suggestions that would help the authors improve the presentation of their data and conclusions? First of all, describe the statistical analysis used in every figure, include number of biological and technical replicates. I would also suggest to change the title or the scope of the discussion, there is too much focus on the TOP2A in the introduction, neglecting all the technical NGS work that actually lead to several new variants being described. This may be confusing when it collides with a conclusion that is heavily focused on the first half describing potential implications of at least another 3 proteins where genetic alterations were described. Given the fact there is not much experimental work that shows TOP2A mutations relevance in HGG or strong enough evidence of the variant's function I would suggest to change a bit the scope of the title. Ad. The description of the results and discussion have been revised to include additional data/discussion on technicalities and other finding not related to TOP2A. We performed additional computational analyses of TOP2A expression/mutations in the TCGA datasets. We believe that the planned experiments on genetically modified cell lines would provide additional support for our claims. We think that in the revised version a balance between landscape/NGS content and TOP2A content is well balanced.

Reviewer #1 (Significance (Required)):

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. The authors describe a methodology that proved to be sensitive and specific enough in order to allow them to detect rare genetic alterations in patient glioma samples. This information could be valuable to describe new driver mutations or infer in genetic pathway alterations that could be potential therapeutic targets. As the authors state at the beginning of the paper, given the poor therapeutical approaches existing for HGG currently, information of this kind could still be highly useful and provide a better outcome to a specific cohort of patients.

On a personal note, I think there is too much speculation about how TOP2A mutations could be interesting from a biological point of view (authors referred to evidence about implications of this mutation in other forms of cancer) but since no experimental validation is provided in glioma cells, it is difficult to conclude that this enzyme gain-of-function mutation could have a relevant role in HGG and thus make these variants a potential therapeutic target. There are no experiments conducted in glioma cells that express TOP2A variants, it would be interesting to see if it has an effect in the migratory/invasive phenotype like described in other cancer types or like it is suggested by analysis of the genetic pathways activated in the HGG patients samples harboring TOP2A mutation. In addition, there is no evidence of the TOP2A mutations possible role as a driver mutation, which is an interesting aspect that could be further explored from both a computational and an experimental approach.

Ad. As mentioned above, there is no glioma cells that express TOP2A variants and we are not convinced that such experiment will be feasible taking into account an essential role of TOP2A. We will attempt to perform experiments with CRISP/Cas9 knock-in cell lines and functional validation, but until now we did not accomplish knock-in in glioma cells. We will try to knock-out the endogenous TOP2A using CRISPR and express a TOP2A WT or E948Q variant from plasmids encoding these proteins, but we can’t predict if TOP2A KO cell would survive. If we manage to produce such cells, then we will investigate proliferation, migration and invasion of cells expressing TOP2A WT or mutated variant.

We do agree with the reviewer that our previous conclusions were too strong, and in the revised version we moderated our claims. We do not say that the mutated TOP2A is an oncogenic driver. We suggest this mutation (and possibly other TOP2A mutations, as we analyzed the impact of other variants on the TOP2A protein structure) contribute to gliomagenesis.

__Data on the Fig. 1A suggests that TOP2A has a mutational hotspot in the position E948Q in our dataset. In the revised version of the manuscript we have extended RNA-seq analysis of our datasets and TCGA PanCancer datasets to search for TOP2A mutations/ overexpression. We found that another computational prediction using CADD algorithm strongly confirms that TOP2A E948Q is in the top 1% of most deleterious variants in the human genome (CADD score >20). This results was added to Supplementary Table 2.__

• Place the work in the context of the existing literature (provide references, where appropriate). The quality of the paper is high and in line with other studies in the literature that perform genome and transcriptome analysis of tumor samples. It is only the experimental validation that is lacking data supporting the "in silico" findings. Ad. We would like to point that we provided the results of experimental, biochemical validation (2 assays) showing that the variant TOP2A proteins have different properties. The associations of transcriptional dysregulation in variant TOP2A bearing gliomas was not a in silico prediction but the result of the analysis of real tumor samples.

As stated above, we are ready to perform further biological validation if the editors find it necessary.

• State what audience might be interested in and influenced by the reported findings. Computational biologists are the right audience to target this paper. If additional experimental work further validating their initial bioinformatic findings is added to the manuscript then probably a wider population could be targeted.

Ad. As stated above, we are working now on providing more replicates of biochemical assays and we are ready to perform further biological validation if the editors find it necessary. I would like to stress that genome editing by knock-in is not always possible/feasible, and these type of experiments is time and money consuming.

• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Brain tumors, immunotherapy, cancer stem cells, tumor microenvironment, tumor heterogeneity. I do not have sufficient expertise to evaluate the bioinformatic analysis and software/programs used to analyze the NGS data.

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

By exon targeted resequencing of 664 genes frequently mutated in cancer, authors identify novel mutations associated to Glioma in a cohort of 182 Polish and Canadian samples. Most of these novel mutations have been identified as potential rare germline mutations, somatic mosaicism or loss-of-heterozygosity variants. Among them, authors focus on mutations associated to the TOP2A gene, which encodes one of the two Type II topoisomerases paralogs present in humans. By a limited number of in vitro experiments, authors conclude that TOP2A recurrent variant E948Q, displays increased binding to DNA and topoisomerase activity. Therefore, authors suggest that the TOP2A E948Q variant is a gain-of-function mutation.

**Major comments:**

• Authors show an interesting plethora of new exon mutations associated with High Grade Glioma. Nevertheless, the characterization of TOP2A E948Q variant, which is the main focus of the study, although very interesting and potentially clinically relevant, remains incomplete. Association of the TOP2A E948Q glioma variant with a gain-of-function mutation would require to improve the statistical power of the presented experiments (increase number of replicates). With the existing experimental evidence, the increased DNA binding and activity of the TOP2A E948Q variant should be considered as preliminary, especially in the case of 431-1193 aa fragment. I would consider mandatory to increase experimental replicates and to analyse statistical significance in the case of DNA binding experiments and DNA relaxation assays with the TOP2A 431-1193 aa fragment. A more detailed biochemical characterization should be performed. A titration of different amounts of protein should be included in these experiments, and at least two batches of purified proteins should be analysed. Decatenation assays should also be performed to characterize the activity of the mutant protein in more detail. Recapitulation of DNA binding and activity results with other TOP2A variants obtained in this study will significantly reinforce authors claims too. This improved biochemical characterization should not take longer than two months.

Ad. We would like to stress that while two replicates are presented, we were testing two forms of TOP2A proteins and the results were similar, confirming our conclusions. But we agree that additional replicates would strengthen our claims. Therefore, we are in the process of producing another batch of recombinant proteins to increase a number of replicates and calculate statistics for the biochemical assays (binding and relaxation assay). We will perform titration of different amounts of the protein using two batches of purified proteins.

The occurrence of other TOP2A variants is low (identified in only a single patient sample), therefore we will perform experimental validation only for E948Q. However, we performed additional computational analysis for other TOP2A variants showing the influence of the substitution on DNA binding by docking the DNA fragment into TOP2A binding pocket (Supplementary table 4).

• To increase the significance of the results, I would encourage authors to include experiments showing the functional impact of this TOP2A mutation in cells. The connection with transcriptomic alterations is merely correlative, and would be greatly strengthened by functional experiments in cellular models. To draw definitive conclusions regarding the changes in transcription, I would encourage authors to complement the results with experiments that point to the physiological impact of TOP2A variants within the cell. Overexpression of WT and E948Q variants in a cell model and transcriptomic analysis would be desirable, but validation in these experimental models of some of the target genes identified as deregulated in patients could suffice. These experiments could be accomplished in no more than 3-4 months.

Ad. We agree that the connection of the TOP2A mutation with transcriptomic alterations is correlative, and would be greatly strengthened by functional experiments in cellular models. If we develop a TOP2A E948Q knock-in cell line or TOP2A KO cell line with E948Q over-expression, we are planning to evaluate transcriptomic changes on selected genes by qPCR or whole transcriptome by RNAseq. We estimate that developing a stable CRISPR/Cas9 cell line may take up to 6 months.

We provided additional results showing that the connection of the TOP2A mutation with transcriptomic alterations may be due to different expression of splicing factors (Supplementary Fig. 6).

• Some of the methods are not presented with sufficient detail. Regarding the DNA and RNA sequencing experiments, I consider necessary to specify the DNA fragmentation method, reference for the indexed adapters and ligation and amplification procedures (ligase reference, number of PCR cycles, etc). It would be helpful to clarify or reference which are the "special oligonucleotide probes" that are mentioned. Finally, a reference for the "special beads" and final amplification number of cycles is needed. The sequence of primers used for TOP2A cloning and mutagenesis should be included. The reference for the "site mutagenesis kit" used is missing. When studying the survival rate of glioma patients depending of TOP2A expression levels, it should be clarified what is considered HIGH or LOW expression (i.e: which percentiles are used).

Ad. We expanded the description of methodological aspects of DNA and RNA sequencing experiments. This description was revised and more details are provided in the revised version. Regarding cloning and mutagenesis, we added a table with primer sequences (Supplementary Table 5). We did not use any kit for cloning and mutagenesis. Standard methods and primers with modified nucleotides were used.

__We have included information about the partitioned groups in the survival analyses in the figure 2 caption. “D - Kaplan-Meier overall survival curve for patients with high (> TOP2A mRNA median expression x 1.25) or low (- There is a major concern about how the experiments are replicated and about the statistical analysis, which is inexistent in some cases. Indeed, Figures 4 and 5 do not present any statistical analysis, it is therefore hard to draw any conclusion. In Figure 4b, the results for the 890-996 aa fragment looks qualitatively clear, but this is not the case for the 431-1193 aa fragment. More replicates and statistical analysis are mandatory, together with a protein titration. The replicates should be performed with at least two independent batches of protein purifications. The individual values of each experiment should be included in the graph to provide a better understanding of experimental variability. All this also applies to Figure 5.

Ad. We will increase a number of replicates for the binding and relaxation assay. We will perform a titration of different amounts of protein in these experiments using two batches of purified proteins.

**Minor comments:**

• The effect on transcription of co-occurrence of TOP2A mutations with other mutations could also be analysed with the already available data. Also, a more detailed analysis of genome-wide transcription could also be used to at least partially address the proposed hypotheses of increased transcriptional rate or splicing aberrations.

Ad. We don’t have enough samples with the TOP2A mutation to analyze the effect on transcription of co-occurrence of TOP2A with other mutations.

We addressed the hypothesis of increased transcriptional rate or splicing aberrations by performed additional analyses of RNA-seq data to confirm splicing aberrations. Indeed we found splicing machinery genes down-regulated in the E948Q TOP2A glioma samples (Supplementary Fig.6).

• There is no reference for the following argument "As the identified germline variants were exceptionally rare in the general population ... it is likely that these variants are pathogenic". I also find low number of references to support the suggested high frequency of altered genes in gliomas compare to other cancer types. I miss specific works relating TOP2 activity with transcriptional regulation.

Ad. The appropriate references are provided to back-up these statements.

• At several points in the text there are quantitative and comparative statements that should be backed up by the actual numbers (e.g. "The results of the targeted sequencing indicate a high frequency of altered genes", "The most altered gene was TP53, followed by IDH1...", "Other genes that were found to be frequently altered included KDM6B...", "These partial results combined with a low frequency of this variant in the Polish population suggest a somatic mutation"). The same thing applies to the co-occurrence of mutations, in which the percentage of co-occurrence and significance is not indicated. This lack of detail in the description is also observed in the description of the transcriptomic alterations in which no detail is provided regarding how many of the 105 analyzed samples correspond to low or high gliomas.

Ad. We apologize that the frequencies of mutated genes were not specified. This information is included in the main text of the revised version. We now provide a gnomAD frequency for all variants of interest, confirming the low frequency in the population (AF__ __

Regarding the total number of samples in the transcriptomic analysis, we provided an updated supplementary table covering also samples that were used for transcriptomic analyses (Supplementary Table 1).

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• For TOP2A mutation analysis, sometimes is not clear when the analysis is done with the 9 mutated samples and when with the 4 recurrent TOP2A E948Q variants. For example, in figure 2b and 2c analysis are done with 9 samples while the figure 2e is based on the 4 E948Q variants. At least this is what I have deduced from the main text, it should be clarified in the figure legend).

Ad. This information has been included in the captions of Figure 2B, 2C and 2E and now we specify how many samples were used in each analysis.

• Fig1. In figure 1b it would be interesting to color-code patients by glioma grade. This would also apply to Figure S1a, S1c, 2a, S3 and S4. In figure 1D it would be very informative to distinguish mutations that passed the quality control or not with different colors.

Ad. Following reviewer’s suggestions, we have added this information, and oncoplot figures derived from the germline analysis have a distinct color for each glioma grade. In the figure 1D, all of the presented mutations have passed a quality control in terms of quality of sequencing. One additional criterion that was used for all genomic results (except some of the TOP2A variants) was a criterion of 20% variant penetration (20% of reads in the position had to come from the alternative allele). We corrected the description in the Supplementary Table to “passed 20% penetration criterion”. The rationale behind this criterion for TOP2A variants was a fact that for one of the E948Q samples it was ~13% and we didn’t want to lose this sample from the analysis due to rarity of the mutation.

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• Fig2. In figure 2b and 2c the statistical significance of differences between TOP2A and the rest of genotypes should be included. Looking at Figures 2d and 2e it looks surprising how similar is the overall survival of HIGH TOP2A mRNA expression (500 days, fig 2d) with the overall survival of the TOP2A WT samples (400 days, fig 2e). Here a I would include a graph that summarizes the TOP2A mRNA expression levels of each group in fig 2d and 2e.

Ad. We agree that median overall survival is similar comparing patients with high TOP2A mRNA expression to TOP2A WT patients in our cohort. It is worth noting, however, that both datasets were produced using different library protocols, and the methodology is different, so it can’t be expected the levels to be equal. We think that adding two more graphs, as suggested, would add another layer of information to this section of the analysis. We have included two boxplots depicting TOP2A mRNA RPKMs, and it is clear now that the medians of High TOP2 mRNA and TOP2A mutant (E948Q) are more closely related, despite the fact that we only have a few patients with the mutation.

• Fig3. It would be interesting to include the same simulation for the rest of TOP2A mutations as supplementary figure.

Ad. We agree that the other TOP2A SNPs could potentially affect DNA binding. We focused on the recurrent mutation and did not analyze those occurring in a single patient. In the revised version we included predictions whether these variants could affect TOP2A DNA binding. For WT TOP2A and variants, we calculated the Gibbs free energy (ΔG). This information can be found in Supplementary Table 4. We have extended description in the Results section: “The TOP2A E948Q substitution may affect protein-DNA interactions”

• Fig4 and Fig5. Include statistical analysis and dots representing individual replicates.

Ad. For Fig 4 we have two replicates for two protein fragments, so we can’t present statistics now. As mentioned above we are preparing a new batch of proteins and will make more repetitions of EMSA and relaxation assays. For Fig 5. we have 3 replicates but despite a trend there is no statistical significance. We intent to make more replicates and a separate protein preparation. After including additional repetitions we will present the results as dots representing individual replicates.

• Fig6. In Figure 6d I would increase the size differences in the dots representing the gene counts, as it is not easily perceived with current parameters.

Ad. The dot size in Fig 6d did not reflect the true meaning. To make it easier to understand, we changed a plot type to a barplot, which now represents the number of differentially expressed genes involved in each pathway.

• FigS2. In figure S2B, it would be informative to establish which dots are significatively above or below the diagonal.

Ad. The purpose of this figure was to show which oncogenic signaling pathways from TCGA cohorts were affected in our cohort. The pathway's size is a variable that is used to normalize the calculation (shown in abscissa axis in S2B). RTK-RAS and NOTCH pathways contain hundreds of genes, whereas other pathways, such as the NRF2 oncogenic pathway, contains only a few. On the other hand, we counted how many genes in each pathway in our cohort were mutated (shown in ordinate axis, S2B). We used logarithms in both axes for visualization purposes, but this has no effect on the enrichment of these pathways, which is shown in the color-coded legend.

• FigS3. How were the samples shown selected from the total?

Ad. In this plot we show only somatic variants that were found in at least two different patients. We apologize that this information was missing, and we have added it to the figure's caption.

• FigS4. I would include a line with the TOP2A mutation to have an idea of how these mutations are distributed between groups.

Ad. Based on the feedback of the reviewer, this figure has been modified and improved. A new row has been added to the figure, displaying TOP2A mutations alongside other highly frequent mutations in other genes.

Reviewer #2 (Significance (Required)):

In this work authors have identified new mutations associated to gliomas by targeted exome sequencing using an important cohort of 182 samples. Among these new mutations epigenetic enzymes and modifiers are found. These results potentially increase the repertoire of putative molecular targets for future cancer therapies. Authors focus in mutations associated to TOP2A gene, that provides stronger DNA binding and DNA relaxation capacity in vitro. Although further characterization is needed, tumours harbouring this kind of mutations could show higher level of sensitivity to TOP2 drugs, providing potentially interesting clinical implications. Although the link between TOP2A expression and cancer prognosis is well established, the relevance of specific mutations in still largely unexplored.

On one hand this work brings novelties in the field of Glioma providing a series of putative new players in the development of this type of cancer. Audience interested in basic or clinical aspects of these tumours would be a good target for this work. On the other hand, this putative gain-of-function mutation of TOP2A represent an interesting aspect for the DNA topology and topoisomerases field. Although, as stated above a more detailed biochemical and functional characterization would be required to draw the attention of this audience-

Scientifically, I have experience in the DNA topology and topoisomerases field, 3D genome organization and gene regulation. I have no experience in Gliomas or any other clinical aspect of cancer, so it is difficult for me to properly establish the potential impact of the newly discovered mutations. Technically I have no capacity to critically evaluate the aspects related to the targeted exome sequencing and the suitability of the analysis performed for mutation identification.

**Referee Cross-commenting**

I fully agree with the comments of the other reviewer, which are perfectly aligned with my own regarding the preliminary nature of the conclusions about the biochemical and functional characterization of the TOP2A mutations.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

By exon targeted resequencing of 664 genes frequently mutated in cancer, authors identify novel mutations associated to Glioma in a cohort of 182 Polish and Canadian samples. Most of these novel mutations have been identified as potential rare germline mutations, somatic mosaicism or loss-of-heterozygosity variants. Among them, authors focus on mutations associated to the TOP2A gene, which encodes one of the two Type II topoisomerases paralogs present in humans. By a limited number of in vitro experiments, authors conclude that TOP2A recurrent variant E948Q, displays increased binding to DNA and topoisomerase activity. Therefore, authors suggest that the TOP2A E948Q variant is a gain-of-function mutation.

Major comments:

• Authors show an interesting plethora of new exon mutations associated with High Grade Glioma. Nevertheless, the characterization of TOP2A E948Q variant, which is the main focus of the study, although very interesting and potentially clinically relevant, remains incomplete. Association of the TOP2A E948Q glioma variant with a gain-of-function mutation would require to improve the statistical power of the presented experiments (increase number of replicates). With the existing experimental evidence, the increased DNA binding and activity of the TOP2A E948Q variant should be considered as preliminary, especially in the case of 431-1193 aa fragment. I would consider mandatory to increase experimental replicates and to analyse statistical significance in the case of DNA binding experiments and DNA relaxation assays with the TOP2A 431-1193 aa fragment. A more detailed biochemical characterization should be performed. A titration of different amounts of protein should be included in these experiments, and at least two batches of purified proteins should be analysed. Decatenation assays should also be performed to characterize the activity of the mutant protein in more detail. Recapitulation of DNA binding and activity results with other TOP2A variants obtained in this study will significantly reinforce authors claims too. This improved biochemical characterization should not take longer than two months.
• To increase the significance of the results, I would encourage authors to include experiments showing the functional impact of this TOP2A mutation in cells. The connection with transcriptomic alterations is merely correlative, and would be greatly strengthened by functional experiments in cellular models. To draw definitive conclusions regarding the changes in transcription, I would encourage authors to complement the results with experiments that point to the physiological impact of TOP2A variants within the cell. Overexpression of WT and E948Q variants in a cell model and transcriptomic analysis would be desirable, but validation in these experimental models of some of the target genes identified as deregulated in patients could suffice. These experiments could be accomplished in no more than 3-4 months.
• Some of the methods are not presented with sufficient detail. Regarding the DNA and RNA sequencing experiments, I consider necessary to specify the DNA fragmentation method, reference for the indexed adapters and ligation and amplification procedures (ligase reference, number of PCR cycles, etc). It would be helpful to clarify or reference which are the "special oligonucleotide probes" that are mentioned. Finally, a reference for the "special beads" and final amplification number of cycles is needed. The sequence of primers used for TOP2A cloning and mutagenesis should be included. The reference for the "site mutagenesis kit" used is missing. When studying the survival rate of glioma patients depending of TOP2A expression levels, it should be clarified what is considered HIGH or LOW expression (i.e: which percentiles are used).
• There is a major concern about how the experiments are replicated and about the statistical analysis, which is inexistent in some cases. Indeed, Figures 4 and 5 do not present any statistical analysis, it is therefore hard to draw any conclusion. In Figure 4b, the results for the 890-996 aa fragment looks qualitatively clear, but this is not the case for the 431-1193 aa fragment. More replicates and statistical analysis are mandatory, together with a protein titration. The replicates should be performed with at least two independent batches of protein purifications. The individual values of each experiment should be included in the graph to provide a better understanding of experimental variability. All this also applies to Figure 5.

Minor comments:

• The effect on transcription of co-occurrence of TOP2A mutations with other mutations could also be analysed with the already available data. Also, a more detailed analysis of genome-wide transcription could also be used to at least partially address the proposed hypotheses of increased transcriptional rate or splicing aberrations.
• There is no reference for the following argument "As the identified germline variants were exceptionally rare in the general population ... it is likely that these variants are pathogenic". I also find low number of references to support the suggested high frequency of altered genes in gliomas compare to other cancer types. I miss specific works relating TOP2 activity with transcriptional regulation.
• At several points in the text there are quantitative and comparative statements that should be backed up by the actual numbers (e.g. "The results of the targeted sequencing indicate a high frequency of altered genes", "The most altered gene was TP53, followed by IDH1...", "Other genes that were found to be frequently altered included KDM6B...", "These partial results combined with a low frequency of this variant in the Polish population suggest a somatic mutation"). The same thing applies to the co-occurrence of mutations, in which the percentage of co-occurrence and significance is not indicated. This lack of detail in the description is also observed in the description of the transcriptomic alterations in which no detail is provided regarding how many of the 105 analyzed samples correspond to low or high gliomas.
• For TOP2A mutation analysis, sometimes is not clear when the analysis is done with the 9 mutated samples and when with the 4 recurrent TOP2A E948Q variants. For example, in figure 2b and 2c analysis are done with 9 samples while the figure 2e is based on the 4 E948Q variants. At least this is what I have deduced from the main text, it should be clarified in the figure legend).
• Fig1. In figure 1b it would be interesting to color-code patients by glioma grade. This would also apply to Figure S1a, S1c, 2a, S3 and S4. In figure 1D it would be very informative to distinguish mutations that passed the quality control or not with different colors.
• Fig2. In figure 2b and 2c the statistical significance of differences between TOP2A and the rest of genotypes should be included. Looking at Figures 2d and 2e it looks surprising how similar is the overall survival of HIGH TOP2A mRNA expression (500 days, fig 2d) with the overall survival of the TOP2A WT samples (400 days, fig 2e). Here a I would include a graph that summarizes the TOP2A mRNA expression levels of each group in fig 2d and 2e.
• Fig3. It would be interesting to include the same simulation for the rest of TOP2A mutations as supplementary figure.
• Fig4 and Fig5. Include statistical analysis and dots representing individual replicates.
• Fig6. In Figure 6d I would increase the size differences in the dots representing the gene counts, as it is not easily perceived with current parameters.
• FigS2. In figure S2B, it would be informative to establish which dots are significatively above or below the diagonal.
• FigS3. How were the samples shown selected from the total?
• FigS4. I would include a line with the TOP2A mutation to have an idea of how these mutations are distributed between groups.

Significance

In this work authors have identified new mutations associated to gliomas by targeted exome sequencing using an important cohort of 182 samples. Among these new mutations epigenetic enzymes and modifiers are found. These results potentially increase the repertoire of putative molecular targets for future cancer therapies. Authors focus in mutations associated to TOP2A gene, that provides stronger DNA binding and DNA relaxation capacity in vitro. Although further characterization is needed, tumours harbouring this kind of mutations could show higher level of sensitivity to TOP2 drugs, providing potentially interesting clinical implications. Although the link between TOP2A expression and cancer prognosis is well established, the relevance of specific mutations in still largely unexplored.

On one hand this work brings novelties in the field of Glioma providing a series of putative new players in the development of this type of cancer. Audience interested in basic or clinical aspects of these tumours would be a good target for this work. On the other hand, this putative gain-of-function mutation of TOP2A represent an interesting aspect for the DNA topology and topoisomerases field. Although, as stated above a more detailed biochemical and functional characterization would be required to draw the attention of this audience-

Scientifically, I have experience in the DNA topology and topoisomerases field, 3D genome organization and gene regulation. I have no experience in Gliomas or any other clinical aspect of cancer, so it is difficult for me to properly establish the potential impact of the newly discovered mutations. Technically I have no capacity to critically evaluate the aspects related to the targeted exome sequencing and the suitability of the analysis performed for mutation identification.

Referee Cross-commenting

I fully agree with the comments of the other reviewer, which are perfectly aligned with my own regarding the preliminary nature of the conclusions about the biochemical and functional characterization of the TOP2A mutations.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

Summary:

Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). Please place your comments about significance in section 2. In this paper the authors used a targeted approach to identify rare mutations in a cohort of glioma patients. Using this approach they identified a recurrent mutation in the TOP2A gene encoding for Topoisomerase 2A, and suggest that this mutation creates a more effective protein, binding DNA strongly and maybe more enzymatically active. RNAseq analysis of TOP2Awt and TOP2Amut tumor samples suggest different transcription patterns and points to possible splicing defects. The most recurrent variant (E9448Q) is described in depth and some experimental information shows this variant might be a gain-of-function mutation.

Major comments:

• Are the key conclusions convincing? The validation of both the methodology and the presence of never described TOP2A variations in HGG is done quite successfully. Interesting evidence about relevance of the most frequent mutation is provided. However, besides having computational and biochemistry assays performed, lack of details about in vitro experiment statistics (no p-values are provided in figures 4 and 5, neither sample size, repetitions) weakens the conclusions claimed by the authors about the properties of the mutated topoisomerase.

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? Claims about E948Q variant function should be revised. Data is not presented in a convincing way, plus there is ambiguous language used from the results ("We conclude that the E9448Q TOP2A protein is functional, and MIGHT have a higher activity than the WT protein") to the rest of the paper where they strongly support the claims about the TOP2A activity.

• Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. In line with the presented data in the paper, additional experiments that show catalytic changes of the E9448Q variation must be added. It is shown that there are differences in the DNA binding capacity by EMSA compared to the WT form, however, the DNA supercoil relaxation activities is not that different, at least the way the results are presented. The authors suggest that TOP2A mutation is a driver mutation but no validation in vitro of this claim is shown. Can this mutation alone or in combination with e.g. tumor suppressors transform normal cells to cancer cells? Do cell lines expressing this mutation (compared to parental TOP2A wt expressing cells) display increased transcription? Increased invasion?

• Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. If the authors can complement the already presented in vitro experiments with additional ones supporting their hypothesis, this should be feasible. The authors can use patient derived glioma cells or glioma cell lines manipulated to express either the parental TOP2A wt enzyme or the identified mutated form.

• Are the data and the methods presented in such a way that they can be reproduced? Yes, the authors provide a quite detailed explanation of the methods implemented to reach each one of the results they are presenting.

• Are the experiments adequately replicated and statistical analysis adequate? No, there is no information about the statistical analysis or number of replicates in any of the in vitro experiments performed. This information should be added to the manuscript.

Minor comments:

• Specific experimental issues that are easily addressable.

• Are prior studies referenced appropriately? Yes, authors clearly address the state of the art regarding previous NGS methodologies and let us know the advantages and novelty of their approach.

• Are the text and figures clear and accurate? There are some discrepancies between the strength of the language used in different sections of the paper to refer the conclusions they can infer from the results they are showing. While they are all valid, authors should revise it.

• Do you have suggestions that would help the authors improve the presentation of their data and conclusions? First of all, describe the statistical analysis used in every figure, include number of biological and technical replicates. I would also suggest to change the title or the scope of the discussion, there is too much focus on the TOP2A in the introduction, neglecting all the technical NGS work that actually lead to several new variants being described. This may be confusing when it collides with a conclusion that is heavily focused on the first half describing potential implications of at least another 3 proteins where genetic alterations were described. Given the fact there is not much experimental work that shows TOP2A mutations relevance in HGG or strong enough evidence of the variant's function I would suggest to change a bit the scope of the title.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. The authors describe a methodology that proved to be sensitive and specific enough in order to allow them to detect rare genetic alterations in patient glioma samples. This information could be valuable to describe new driver mutations or infer in genetic pathway alterations that could be potential therapeutic targets. As the authors state at the beginning of the paper, given the poor therapeutical approaches existing for HGG currently, information of this kind could still be highly useful and provide a better outcome to a specific cohort of patients.

On a personal note, I think there is too much speculation about how TOP2A mutations could be interesting from a biological point of view (authors referred to evidence about implications of this mutation in other forms of cancer) but since no experimental validation is provided in glioma cells, it is difficult to conclude that this enzyme gain-of-function mutation could have a relevant role in HGG and thus make these variants a potential therapeutic target. There are no experiments conducted in glioma cells that express TOP2A variants, it would be interesting to see if it has an effect in the migratory/invasive phenotype like described in other cancer types or like it is suggested by analysis of the genetic pathways activated in the HGG patients samples harboring TOP2A mutation. In addition, there is no evidence of the TOP2A mutations possible role as a driver mutation, which is an interesting aspect that could be further explored from both a computational and an experimental approach.

• Place the work in the context of the existing literature (provide references, where appropriate). The quality of the paper is high and in line with other studies in the literature that perform genome and transcriptome analysis of tumor samples. It is only the experimental validation that is lacking data supporting the "in silico" findings.

• State what audience might be interested in and influenced by the reported findings. Computational biologists are the right audience to target this paper. If additional experimental work further validating their initial bioinformatic findings is added to the manuscript then probably a wider population could be targeted.

• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Brain tumors, immunotherapy, cancer stem cells, tumor microenvironment, tumor heterogeneity. I do not have sufficient expertise to evaluate the bioinformatic analysis and software/programs used to analyze the NGS data.

Evaluation Summary:

The paper describes novel structures of a protein recently reported to function as a mechanosensitive ion channel. Surprisingly, the structures and functional data rather support the formerly suggested role of this protein in lipid metabolism. The paper is of relevance for ion channel field and for those interested in fatty acid metabolism.

(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewer #1 (Public Review):

Yao Rang and collaborators find that heterologous expression of TMEM120A from mouse and human in cells that lack Piezo1 does not result in poke- or stretch-activated currents in whole cells or excised patches, and further detect no mechano-sensitive currents when the purified human protein is reconstituted in giant unilamellar vesicles. Together with high-quality positive controls with Piezo1, Piezo2 and TMEM63a, the results presented here call into question a previous proposal (Beaulieau-Laroche et al., Cell 2020) that TMEM120A functions as the long sought-after mechano-activated channel responsible for detecting painful touch.

Although the evidence supporting a channel function for TMEM120A is not strong, it remains to be ruled out that the discrepancies between the two studies arise from the different methods that were used to deliver the mechanical stimuli, as mentioned by the authors in the Discussion, or from the C-terminal mCherry tag attached to human TMEM120A in this study that was not present in the construct used by Beaulieau-Laroche et al.

Upon determination of the structure of full-length human TMEM120A in nanodiscs using cryo-EM, the authors find that the protein forms a dimer with six transmembrane helices per subunit and a cytosolic N-terminal coiled coil domain. Surprisingly, the authors find a density attributable to coenzyme-A (CoASH) located within a highly conserved cytosolic cavity at the transmembrane domain. The authors provide evidence from mass-spectrometry and isothermal titration calorimetry (ITC) to demonstrate that CoASH binds TMEM120A, and solidify their conclusions by showing that mutation of a residue close to the CoASH density in TMEM120A disrupts binding measured by ITC. The authors show that a potential ion-conduction pathway in their TMEM120A structure would be occluded by CoASH on the cytosolic side and on the extracellular side by a series of not well-conserved residues. Finally, the authors solve a structure in detergents where no density for CoASH is observed, as expected from spectroscopic data showing that detergent-reconstitution results in loss of CoASH binding. In this structure, a conformational change is suggested to occur on the cytosolic cavity entrance where a loop becomes reoriented to occlude the cavity that is otherwise occupied by CoASH. Together, the data presented paints an intriguing alternative for the function of TMEM120A proteins with a role in metabolism or CoA transport.

Although the main conclusions are well supported by the evidence, it is challenging to appraise many of the interesting structural observations pointed out by the authors because the experimental data (i.e. the density) is in most cases not depicted. Some of these observations for which only the model rather than the experimental data is shown include the hinge-like motif at the dimer interface (Fig. 3C), the CoASH binding site (Fig. 4E and Fig. 4 Supplement 1C), the difference in the conformation of the IL5 loop between the apo and CoASH-bound structures (Fig. 5), the extracellular constriction of the possible ion-conduction pathway (Fig. 4 Supplement 1D and Fig. 5 Supplement 2), as well as the comment that the observed density in the structures cannot accommodate other CoA-derivatives, for which data is not shown. The relatively low resolution at which the data were obtained raises concerns regarding many of these detailed observations.

Reviewer #2 (Public Review):

In this manuscript, Rong et al., address the possibility that TMEM120A, also known as TACAN, might not be a mechanosensitive ion channel. They use extensive electrophysiological characterization to convincingly show that cells heterologously transfected with either human or mouse TMEM120A do not exhibit mechanosensitive currents above background in cell lines or when purified and reconstituted in giant unilamellar vesicles. They also solve the cryo-EM structure of TMEM120A and find that it does not resemble an ion channel (i.e., there is no obvious pore). Interestingly, there is a density consistent with coenzymeA in the structure, thus suggesting an alternative function for TMEM120A. Further evidence for this interaction is shown through biochemical analysis, as disrupting a residue proposed to form a π−π stacking interaction between TMEM120A and coenzymeA reduces the binding affinity as assayed by ITC.

Overall, the impact of this manuscript is extremely high, as it refutes a recent report that TMEM120A/TACAN is a high-threshold (pain) mechanosensitive ion channel, and further suggests an alternative function for this protein. The experiments are extremely carefully done, and the authors attempted to replicate the electrophysiological function of TMEM120A with high numbers and with appropriate positive and negative controls. The inclusion of structures (Coenzyme-A bound and apo) and corresponding biochemical analyses provide strong support for the direct binding of Coenzyme-A by TMEM120A.

Reviewer #3 (Public Review):

TMEM120A protein was recently reported to mediate mechanosensitive currents in response to painful stimuli. In the present manuscript, the authors aimed to elucidate TMEM120A mechanism of action by solving the structures and complementing them with functional characterization. In contrast to the recent report, the authors could not observe TMEM120A-mediated currents in response to mechanical stimuli neither in transfected cells nor in liposomes. Furthermore, the structure of human homolog HsTMEM120A revealed a co-purified endogenous ligand, which was shown to be coenzyme A (CoASH). The authors went on to solve the structure in the absence of CoASH, revealing a different conformation of HsTMEM120A. Together, structural and functional data point towards a conclusion that TMEM120A might not be a mechanosensitive channel, but might rather be important for fatty acid metabolism. The conclusions of the manuscript are supported by the presented data.

Strengths:

1. The authors conclusively show that TMEM120A does not mediate poking- or stretch-induced currents when compared to well-characterized mechanosensitive channels Piezo1 and TMEM63a.

2. The authors employed several approaches to confirm the identity of the co-purified ligand. Firstly, the presence of CoASH in the purified protein sample was confirmed by mass spectrometry. Secondly, the binding of CoASH to TMEM12A was confirmed by ITC. Thirdly, using the obtained structure the authors identified CoASH-interacting residues and show that mutating one of the key residues (Trp193) reduced TMEM120A affinity for its ligand.

3. The observation that CoASH dissociates from TMEM120A during size exclusion in detergent, but not in lipid environment allowed to solve a ligand-free TMEM120A structure, which revealed a different conformation at the entrance to CoASH-binding site and is possibly relevant for the mechanism of action.

Noteworthy, 3 other studies (Niu et al., 2021, Xue et al., 2021, Ke et al., 2021) independently arrived at the conclusion that TMEM120A is probably not a mechanosensitive channel, further supporting the results of the present study.

Weaknesses:

Despite the advances presented in this manuscript, physiological function of TMEM120A and its mechanism of action remain obscure, other than that it is probably not a mechanosensitive channel. However, the goal of the authors was to understand how TMEM120A might mediate mechanosensitive currents, while establishing its role in lipid metabolism is outside of the scope of this manuscript.

Regardless, this work provides an important insight into TMEM120 family and will serve as a basis for future investigations.

Evaluation Summary:

The paper is of interest for those studying tendon development. Starting from a transcriptomic analysis of Drosophila leg tendon cells it identifies a transcription factor, Dar1, required for normal tendon morphogenesis.

(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewer #1 (Public Review):

The well studied tendons in the fly embryo are formed by rather simple specialized epithelial cells that stay in the epithelium and attract the end of an attaching myotube. This study investigates the more complex 'long tendons' of the adult legs that form in the leg discs during pupal stages. The authors find that the long tendon precursors undergo an interesting collective migration process to re-shape into a higher order long tub-like structure. This elongation process had not been studied before.

By performing a transcriptomics analysis of sorted leg disc tendon precursors (0h APF), followed by systematic RNAi knock-down studies of all transcription factors enriched in the tendon precursors, the authors identify the Kr-like transcriptional regulator dar1 as key regulator of long-tendon development. RNAi specificity was confirmed by analyzing 2 different lines both resulting in locomotion defects and by confirming the tendon defect by the analysis of dar1 null alleles that rarely survive until pupal stages.

Dar1 protein is enriched in stripe positive tendon precursors of the leg discs (but not in the tendons of the wing disc). Dar1 knockdown animals show largely missing or too short internal tendons in the legs, hence strongly affecting the attachment of the adult leg muscles. This explains the observed locomotion defects of these flies.

Excellent imaging during early stages of pupal development shows that dar1 is required for the extension of the long leg tendon precursors into a long tube. Mechanistically, dar1 organizes actin-rich long filopodial extensions during tube elongation and hence equips these cells specifically with their collective migration ability to form a long tube.

Epistasis experiments show that dar1 acts downstream of the tendon master regulator stripe, making long tendons different from other tendons. Interestingly, the amount of stripe positive tendons cells is reduced upon dar1 knock-down, resulting in the hypothesis that dar1 is needed to recruit and specify the correct number of stripe positive tendons cells to form the larger long tendons in a non cell autonomous manner. Such a model makes sense, as likely the invagination and migration of tendon precursors into a long tube will recruit additional epithelial cells to turn on stripe and to follow the invagination as nicely illustrated in the model in figure 8.

I am not sure if the term 'master regulator' for dar1 for the long tendons is justified. Do the authors have access to a UAS-dar1 line to see if 'normal' tendons in the wing disc or the embryo can be changed to 'long tendons' when expressing dar1? If not, the term tendon identity gene might be more appropriate.

It would have been nice to include Dar1 antibody staining of dar1 know-down leg to confirm antibody specificity.

Together, this is an excellent study that genetically and molecularly characterizes a novel gene controlling an interesting morphogenesis process that was not well understood. As these complex long tendons are somewhat similar to mammalian tendons, these findings could also be relevant for mammalian tendon development and diversification.

Reviewer #2 (Public Review):

In their manuscript titled "Transcriptomic and genetic analyses identify the Krüppel-like factor dar1 as a master regulator of tube-shaped long tendon development," Quentin et al. identify Dar1 as a novel transcriptional regulator of tendon development. They present the first transcriptomic profiling of Stripe-expressing tendon progenitors in the leg disc, highlighting similarities to well-characterized tubulogenesis systems. After performing a candidate screen of 31 genes identified in this data, they focus on the transcription factor Dar1. Dar1 is selectively expressed in tendon cells of the leg and its knockdown results in both tendon and muscle defects. The long tendons are too short due to insufficient tube extension and decreased filipodial arborization. The number of tendon precursors is also greatly reduced upon knockdown of dar1. As dar1 expression is downstream of Stripe and there is little alteration of cell proliferation and death rates in the leg disc, the authors suggest Stripe positive cells are recruited during long tendon tubulogenesis and this recruitment is non-autonomously regulated by Dar1.

There are several new observations, approaches and datasets presented in this work that are of value to the muscle field and the broader Drosophila community. First, the FACS-based RNA-Seq approach and associated protocol for tendon cells in leg can be adapted for other imaginal discs, dissectible tissues and cell types. Second, this RNA-seq dataset expands on earlier observations suggesting long-tendon development proceeds via tube-formation and thus is a valid model to study the important process of tubulogenesis. Third, the candidate climbing and survival screen combined with the RNA-Seq data provide multiple candidate genes, and notably transcription factors, that may play a role in tendon specification or development and will be useful for future studies. Lastly, this work identifies and nicely characterizes the tendon phenotype after knockdown of Dar1, ultimately placing Dar1 downstream of Stripe in the regulatory hierarchy. Given the apparent conservation of Krüpel-like factors in tendon development, this finding is of general interest and may point to a conserved mechanism fueling long tendon elongation.

On a critical note, only select genes of interest and select GO terms are included from the RNA-Seq data, and a broader or more systematic analysis is not presented. While the title refers to Dar1 as a master regulator of tendon development, this is not addressed experimentally. The manuscript is largely descriptive, and while the characterization of Dar1 indeed raises interesting inferences notably about Stripe-positive cell recruitment, there are no experiments designed to test potential mechanisms of non-cell autonomous effects or even regulatory targets of Dar1 in tendon. The manuscript also does not address non-autonomous effects on muscle number, size and morphology in the ventral tibia, for example, and does not effectively place this result in the context of what is known about bi-directional muscle-tendon signaling. Lastly, the authors have previously characterized tendon-cell recruitment in the leg to be Notch dependent, and indeed they find enrichment of the Notch signaling pathway in their RNA-seq analysis, but the findings for Dar1 are not integrated in this context.

In conclusion, this manuscript identifies a new transcriptional regulator of tendon development and offers an insightful and informative description of the phenotype. It arrives at mechanistic inferences that provide a framework for future studies to identify the non-cell autonomous mechanism of tendon-cell recruitment, to elucidate the regulatory mechanisms of long-tendon extension and tube formation and to investigate the transcriptional hierarchy that defines long-tendon cell identity in Drosophila.

Reviewer #3 (Public Review):

In the introduction the authors frame some key background questions for the study concerning the specificity of muscle-tendon interactions, and the processes governing tendon development. To investigate they have set out to identify genes regulating the development of the long tendons in the Drosophila leg. These share similarities with autopod tendons in mouse and also their morphogenesis is similar to that of some tubule development.

To investigate, the authors have profiled the RNAs (total RNA transcriptomic analysis) that are enriched in the tendon progenitors in comparison to the limb disc as a whole. From the large number of enriched genes, the consequences of knocking 31 transcription factors whose expression was >1.5-fold higher in the tendon precursors, using a viability assay. Several gave phenotypes and their homologues had been reported to have expression in mouse limb tendons. Ultimately 1 gene was chosen for further analysis, Dar 1, and conventional analysis shows that it is involved in normal tendon development and its expression is dependent on the key tendon regulator stripe. The tendons from Dar1 knock-down animals don't extend as well, have reduced amounts of actin protrusions and have slightly fewer cells. The data demonstrating this provide good evidence that Dar1 plays a role in the development of the tendons and, interestingly is specific for the leg tendons. It's not required in the wing tendons.

The work is nicely done but it falls short of addressing the questions set. The initial RNA seq data are a good starting point and the analysis of dar1 expression and knock-down are sound. More could have been made of the primary data and the authors would need to include properly the "data not shown" about some of the other genes tested. The basic phenotypic analysis supports the conclusions that Dar1 as is an additional player in long tendon development, but its identification does not significantly add to the understanding of how tendons grow, navigate correctly and interact with the right muscle. What step is Dar1 regulating? There is a suggestion that it may regulate the cytoskeletal genes but there are no concrete data to support that. Could dar1 be involved in specifying leg versus wing tendons (the former being more tube like) given its expression in leg tendons only.

The results identifying a new gene involved in tendon morphogenesis will be of interest to those directly in the field.

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